diff --git a/.DS_Store b/.DS_Store index 08358fa..78e8599 100644 Binary files a/.DS_Store and b/.DS_Store differ diff --git a/.idea/.gitignore b/.idea/.gitignore new file mode 100644 index 0000000..73f69e0 --- /dev/null +++ b/.idea/.gitignore @@ -0,0 +1,8 @@ +# Default ignored files +/shelf/ +/workspace.xml +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml +# Editor-based HTTP Client requests +/httpRequests/ diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml new file mode 100644 index 0000000..105ce2d --- /dev/null +++ b/.idea/inspectionProfiles/profiles_settings.xml @@ -0,0 +1,6 @@ + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml new file mode 100644 index 0000000..161b172 --- /dev/null +++ b/.idea/misc.xml @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/.idea/modules.xml b/.idea/modules.xml new file mode 100644 index 0000000..f5ab841 --- /dev/null +++ b/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/numpy_study.iml b/.idea/numpy_study.iml new file mode 100644 index 0000000..0686e3a --- /dev/null +++ b/.idea/numpy_study.iml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/vcs.xml b/.idea/vcs.xml new file mode 100644 index 0000000..94a25f7 --- /dev/null +++ b/.idea/vcs.xml @@ -0,0 +1,6 @@ + + + + + + \ No newline at end of file diff --git a/.ipynb_checkpoints/Untitled-checkpoint.ipynb "b/.ipynb_checkpoints/12\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214-checkpoint.ipynb" similarity index 100% rename from .ipynb_checkpoints/Untitled-checkpoint.ipynb rename to ".ipynb_checkpoints/12\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214-checkpoint.ipynb" diff --git "a/01\354\236\245/01\354\236\245 \354\241\260\355\230\204\354\247\204.txt" "b/01\354\236\245/01\354\236\245 \354\241\260\355\230\204\354\247\204.txt" new file mode 100644 index 0000000..08d1d78 --- /dev/null +++ "b/01\354\236\245/01\354\236\245 \354\241\260\355\230\204\354\247\204.txt" @@ -0,0 +1,37 @@ +1) 리터럴 표기법(literal)의 잇점은? + +정수, 문자를 간단하게 표현할 수 있다. + +2) 리스트, 튜플의 차이점? + +새로운 요소를 추가/변경할 수 있는지 여부 +리스트(가변) <-> 튜플(불변) + +3) 유니버셜함수의 종류는? + +단항 유니버셜 함수 + +abs, fabs : 각 원소(정수, 실수, 복소수)의 절대값을 구한다. 복소수가 아닌 경우에는 빠른 연산을 위해 fabs를 사용한다. +sqrt : 각 원소의 제곱근을 계산한다. +square : 각 원소의 제곱근을 계산한다. +Exp : 각 원소에서 지수를 계산한다. +Log : 자연 로그 +sign : 각 원소의 부호를 계산한다. 1(양수), 0(영), -1(음수) +ceil : 각 원소의 소수자리를 올린다. 각 원소의 값보다 같거나 큰 정수 중 가장 작은 수를 반환한다. +floor : 각 원소의 소수자리를 내린다. 각 원소의 값보다 작거나 같은 정수 중 가장 작은 수를 반환한다. +rint : 각 원소의 소수자리를 반올림한다. dtype은 유지된다. +modf : 각 원소의 몫과 나머지를 각각의 배열로 반환한다. +isnan : 각각의 우너소가 숫자인지 아닌지를 나타내는 boolean 배열을 반환한다. +cos(h), sin(h), tan(h): 삼각함수(쌍곡삼각). +arccos, arccosh, arcsin ... : 역삼각 함수 + +이항 유니버셜 함수 + +add : 두 배열에서 같은 위치의 원소끼리 더 한다. +subtract : 첫 번째 배열의 원소에서 두 번째 배열의 원소를 뺀다. +multiply : 배열의 원소끼리 곱한다. +divide, floor_divide : 첫 번째 배열의 원소에서 두 번째 배열의 원소를 나눈다. floor_divide는 몫만 취한다. +power : 첫 번째 배열의 원소에 두 번째 배열의 원소만큼 제곱한다. +maximum, fmax : 두 원소 중 큰 값을 반환한다. fmax는 NaN을 무시한다. +minimum, fmin : 각 배열의 두 원소 중 작은 값을 반환한다. fmin은 NaN을 무시한다. +mod : 첫 번째 배열의 원소에 두 번째 배열의 원소를 나눈 나머지를 구한다. \ No newline at end of file diff --git "a/01\354\236\245/1\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" "b/01\354\236\245/1\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" new file mode 100644 index 0000000..db132b7 --- /dev/null +++ "b/01\354\236\245/1\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" @@ -0,0 +1,59 @@ +Q1. 리터럴 표기법 이점 +- 간결한 표기가 가능 +- 생성 시점에 객체에 기능 추가 가능 + +Q2. 리스트와 튜플의 차이점 +- 리스트 : 변경이 가능(가변적) / 튜플 : 변경이 불가능(불변적) +- 리스트는 새로운 요소를 추가하거나 수정 가능하고, 기존 요소를 삭제할 수 있지만 튜플은 이러한 작업 허용 하지 않음. + +Q3. 유니버셜 함수의 종류 +- 단일 유니버셜 함수 +▶ abs, fabs : 각원소의 절대값을 구함. 복소수가 아닌 경우에는 fabs로 빠르게 연산 가능 + +▶ sqrt : 제곱근을 계산 arr** 0.5와 동일 + +▶ square : 제곱을 계싼 arr** 2와 동일 + +▶ Exp : 각 원소에 지수 ex를 계산 + +▶ Log, log10, log2, logP : 각각 자연로그, 로그10, 로그2, 로그(1+x) + +▶ sign : 각 원소의 부호를 계산 + +▶ ceil : 각 원소의 소수자리를 올림 + +▶ floor : 각 원소의 소수자리를 버림 + +▶ rint : 각 원소의 소수자리 반올림, dtype 유지 + +▶ modf : 원소의 몫과 나머지를 각각 배열로 변환 + +▶ isnan : 각 원소가 숫자인지 아닌지 NaN 나타내는 불리언 배열 + +▶ isfinite, isinf : 배열의 각 원소가 유한한지 무한한지 나타내는 불리언 배열 + +▶ cos, cosh, sin, sinh, tan, tanh : 일반 삼각함수와 쌍곡삼각 함수 + +▶ logical_not : 각 원소의 논리 부정(not) 값 계산, -arr와 동일 + +- 이항 유니버셜 함수 + +▶ add : 두 배열에서 같은 위치의 원소끼리 덧셈 + +▶ subtract : 첫번째 배열 원소 - 두번째 배열 원소 + +▶ multiply : 배열의 원소끼리 곱셈 + +▶ divide : 첫번째 배열의 원소에서 두번째 배열의 원소를 나눗셈 + +▶ power : 첫번째 배열의 원소에 두번째 배열의 원소만큼 제곱 + +▶maximum, fmax : 두 원소중 큰 값을 반환, fmax는 NaN 무시 + +▶ minimum, fmin : 두 원소중 작은 값을 반환, fmin는 NaN 무시 + +▶ mod : 첫번째 배열의 원소에 두번째 배열의 원소를 나눈 나머지 + +▶ greater, greater_equal, less, less_equal, equal, not_equal : 두 원소간의 >, >=, <, <=, ==, != 비교 연산 결과를 불리언 배열로 반환 + +▶ logical_and, logical_or, logical_xor : 각각 두 원소간의 논리연산 &, |, ^ 결과를 반환 diff --git "a/01\354\236\245/1\354\236\245 \355\200\264\354\246\210 \353\260\261\354\247\204\354\243\274" "b/01\354\236\245/1\354\236\245 \355\200\264\354\246\210 \353\260\261\354\247\204\354\243\274" new file mode 100644 index 0000000..13052c4 --- /dev/null +++ "b/01\354\236\245/1\354\236\245 \355\200\264\354\246\210 \353\260\261\354\247\204\354\243\274" @@ -0,0 +1,36 @@ +1. 리터럴 표기법의 이점 +- 짧게 코드 작성이 가능 +- 다양한 타입의 값을 생성 할 수 있음 + +2. 리스트와 튜플의 차이점 +- 리스트 : 중간에 변경이 가능(가변), 딕셔너리의 key값으로 쓸 수 없음 +- 튜플 : 변경이 불가능(불변적), 딕셔너리의 key값으로 사용 가능 + +3. 유니버셜 함수의 종류 +<단일 배열에 사용하는 함수> +abs, fabs : 각 원소의 절대값을 구한다. 복소수가 아닌 경우에는 fabs로 빠르게 연산가능 +sqrt : 제곱근을 계산 arr ** 0.5와 동일 +square : 제곱을 계산 arr ** 2와 동일 +Exp : 각 원소에 지수 ex를 계산 +Log, log10, log2, logp : 각각 자연로그, 로그10, 로그2, 로그(1+x) +sign : 각 원소의 부호를 계산 +ceil : 각 원소의 소수자리 올림 +floor : 각 원소의 소수자리 버림 +rint : 각 원소의 소수자리 반올림. dtype 유지 +modf : 원소의 몫과 나머지를 각각 배열로 반환 +isnan : 각 원소가 숫자인지 아닌지 NaN 나타내는 불리언 배열 +isfinite, isinf : 배열의 각 원소가 유한한지 무한한지 나타내는 불리언 배열 +cos, cosh, sin, sinh, tan, tanh : 일반 삼각함수와 쌍곡삼각 함수 +logical_not : 각 원소의 논리 부정(not) 값 계산. -arr와 동일 + +<서로 다른 배열 간에 사용하는 함수> +add : 두 배열에서 같은 위치의 원소끼리 덧셈 +subtract : 첫번째 배열 원소 - 두번째 배열 원소 +multiply : 배열의 원소끼리 곱셈 +divide : 첫번째 배열의 원소에서 두번째 배열의 원소를 나눗셈 +power : 첫번째 배열의 원소에 두번째 배열의 원소만큼 제곱 +maximum, fmax : 두 원소 중 큰 값을 반환. fmax는 NaN 무시 +minimum, fmin : 두 원소 중 작은 값 반환. fmin는 NaN 무시 +mod : 첫번째 배열의 원소에 두번째 배열의 원소를 나눈 나머지 +greater, greater_equal, less, less_equal, equal, not_equal : 두 원소 간의 >, >=, <, <=, ==, != 비교연산 결과를 불리언 배열로 반환 +logical_and, logical_or, logical_xor : 각각 두 원소 간의 논리연산, &, |, ^ 결과를 반환 diff --git "a/01\354\236\245/Q1_\354\240\204\354\244\200\354\232\251.docx" "b/01\354\236\245/Q1_\354\240\204\354\244\200\354\232\251.docx" new file mode 100644 index 0000000..f33a8f7 Binary files /dev/null and "b/01\354\236\245/Q1_\354\240\204\354\244\200\354\232\251.docx" differ diff --git "a/01\354\236\245/chaper1 quiz \352\271\200\353\257\274\352\267\234" "b/01\354\236\245/chaper1 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..c0845e0 --- /dev/null +++ "b/01\354\236\245/chaper1 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,12 @@ +1. 리터럴 표기법 이점 +- 여러 개의 데이터를 묶을 수 있음 +- 간결한 표기가 가능 +- 객체에 기능을 추가할 수 있음 + +2. 리스트와 튜플의 차이점 +- 리스트는 가변적 / 튜플은 불변적 +- 리스트는 딕셔너리 키값 사용 불가 / 튜플은 딕셔너리 키값 사용 가능 + +3. 유니버셜함수의 종류 +- 단항함수(abs, fabs, sqrt, square, Exp, Log, log10, log2, logp, sign, ceil, floor, rint, modf, isnan, isfinite, isinf, cos, cosh, sin, sinh, tan, tanh, logical_not) +- 이항함수(add, subtract, multiply, divide, power, maximum, fmax, minimum, fmin, mod, greater, greater_equal, less, less_equal, equal, not_equal, logical_and, logical_or, logical_xor) diff --git "a/01\354\236\245/quiz-sangguen.md" "b/01\354\236\245/quiz-sangguen.md" new file mode 100644 index 0000000..d17a662 --- /dev/null +++ "b/01\354\236\245/quiz-sangguen.md" @@ -0,0 +1,33 @@ +Q. 리터럴 표기법(literal)의 잇점은? +A. 생성자를 사용하지 않아 객체를 직관적으로 짧게 만들기 쉽다. + +Q. 리스트, 튜플의 차이점? +A. 리스트 : mutable, 튜플 : immutable + +Q. 유니버셜 함수의 종류? +```python +import numpy as np + +a = dir(np) + +count = 0 +for i in a : + if i == "Tester": + continue + if type(np.__dict__[i]) == np.ufunc : + print(i, end=", ") + count += 1 + if count % 10 == 0 : + print() +``` +A. +abs, absolute, add, arccos, arccosh, arcsin, arcsinh, arctan, arctan2, arctanh, +bitwise_and, bitwise_not, bitwise_or, bitwise_xor, cbrt, ceil, conj, conjugate, copysign, cos, +cosh, deg2rad, degrees, divide, divmod, equal, exp, exp2, expm1, fabs, +float_power, floor, floor_divide, fmax, fmin, fmod, frexp, gcd, greater, greater_equal, +heaviside, hypot, invert, isfinite, isinf, isnan, isnat, lcm, ldexp, left_shift, +less, less_equal, log, log10, log1p, log2, logaddexp, logaddexp2, logical_and, logical_not, +logical_or, logical_xor, matmul, maximum, minimum, mod, modf, multiply, negative, nextafter, +not_equal, positive, power, rad2deg, radians, reciprocal, remainder, right_shift, rint, sign, +signbit, sin, sinh, spacing, sqrt, square, subtract, tan, tanh, true_divide, +trunc, \ No newline at end of file diff --git "a/02\354\236\245/2\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" "b/02\354\236\245/2\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" new file mode 100644 index 0000000..77b84a3 --- /dev/null +++ "b/02\354\236\245/2\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" @@ -0,0 +1,25 @@ +1. +import numpy as np #넘파이를 import + +a = np.logspace(1, 10, num=5, endpoint=True, base=5.0) +b = np.logspace(0, 10, num=5, endpoint = False, base = 1.0) +""" +0 = start 값 : 시작값 +10 = stop 값 : 값의 마지막 값인데, endpoint가 True 면 포함, False면 포함하지 않음 +num=5 : 배열의 개수, 기본값은 50 +endpoint = stop값의 포함 여부를 확인, True = 포함, False = 미포함 +base = 로그값의 간격을 의미 + +""" +print(a) # a값을 출력 +print(b) # b값을 출력 + +[5.00000000e+00 1.86918598e+02 6.98771243e+03 2.61226682e+05 9.76562500e+06] +[1. 1. 1. 1. 1.] + +2. +정방 행렬/정사각 행렬, 대각 행렬, 삼각 행렬, 스칼라 행렬, 단위 행렬, 영 행렬, 전치 행렬, +대칭 행렬, 반대칭 행렬, 직교 행렬, 계수 행렬, 첨가 행렬, 항등 행렬, 역 행렬 + +3. +선형연립방정식을 계수 행렬과 미지수 벡터와의 곱으로 표현한것 diff --git "a/02\354\236\245/2\354\236\245\355\200\264\354\246\210_\352\271\200\353\257\274\352\261\264" "b/02\354\236\245/2\354\236\245\355\200\264\354\246\210_\352\271\200\353\257\274\352\261\264" new file mode 100644 index 0000000..15879d6 --- /dev/null +++ "b/02\354\236\245/2\354\236\245\355\200\264\354\246\210_\352\271\200\353\257\274\352\261\264" @@ -0,0 +1,20 @@ +1. +numpy.linspace(start, end, num=개수, endpoint=True, retstep=False, dtype=자료형) + +import numpy as np + +a = np.logspace(0, 10, num=5, endpoint=True, base=10.0) +b = np.logspace(1, 10, num=5, endpoint=True, base=5.0) +c = np.logspace(0, 10, num=5, endpoint=False, base=1.0) + +print(a) //[1.00000000e+00 3.16227766e+02 1.00000000e+05 3.16227766e+07 1.00000000e+10] +print(b) //[5.00000000e+00 1.86918598e+02 6.98771243e+03 2.61226682e+05 9.76562500e+06] +print(c) //[1. 1. 1. 1. 1.] + +2. + 0행렬, 정사각행렬, 대각행렬, 삼각행렬(하,상), 단위행렬(항등행렬), 스칼라행렬, + 계수행렬, 첨가행렬, 전치행렬, 대칭행렬(반대칭행렬), 역행렬, 직교행렬, 복소수행렬, + 가역행렬, 특이행렬, 치환행렬, 블록행렬, 부울행렬 + +3. +선형연립방정식을 행렬로 나타낸 것 diff --git "a/02\354\236\245/Q2_\354\240\204\354\244\200\354\232\251.docx" "b/02\354\236\245/Q2_\354\240\204\354\244\200\354\232\251.docx" new file mode 100644 index 0000000..0653ff0 Binary files /dev/null and "b/02\354\236\245/Q2_\354\240\204\354\244\200\354\232\251.docx" differ diff --git "a/02\354\236\245/[\353\204\230\355\214\214\354\235\264]02\354\236\245.pptx" "b/02\354\236\245/[\353\204\230\355\214\214\354\235\264]02\354\236\245.pptx" new file mode 100644 index 0000000..b0aca89 Binary files /dev/null and "b/02\354\236\245/[\353\204\230\355\214\214\354\235\264]02\354\236\245.pptx" differ diff --git "a/02\354\236\245/chaper2 quiz \352\271\200\353\257\274\352\267\234" "b/02\354\236\245/chaper2 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..cc5dd51 --- /dev/null +++ "b/02\354\236\245/chaper2 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,24 @@ +1. numpy.logspace(start, stop, num, endpoint, base, dtype) +Start = 시작 값 +Stop = 종료 값 +Num = 배열 개수 +Endpoint = stop값 포함 여부 +Base = log 값의 베이스 값 설정 (기본 10) +Dtype = 배열의 데이터 타입 + +Import numpy as np +X = np.logspace(1,10, 10, base=2) +Print(x) +[ 2. 4. 8. 16. 32. 64. 128. 256. 512. 1024.] + + + +2. 0행렬, 정사각행렬, 대각행렬, 삼각행렬(하,상), 단위행렬(항등행렬), 스칼라행렬, + 계수행렬, 첨가행렬, 전치행렬, 대칭행렬(반대칭행렬), 역행렬, 직교행렬, 복소수행렬, + 가역행렬, 특이행렬, 치환행렬, 블록행렬, 부울행렬 + + + +3. 선형 연립 방정식을 계수 행렬과 미지수 벡터와의 곱으로 표현한 것 +(선형연립방정식을 행 위주의 정방행렬과 미지수 벡터와의 곱셈으로 나타낸 것) +A가 m*n행렬일 때, Ax=b의 형태 diff --git "a/02\354\236\245/quiz_\354\236\245\354\203\201\352\267\274.ipynb" "b/02\354\236\245/quiz_\354\236\245\354\203\201\352\267\274.ipynb" new file mode 100644 index 0000000..3626c0e --- /dev/null +++ "b/02\354\236\245/quiz_\354\236\245\354\203\201\352\267\274.ipynb" @@ -0,0 +1,81 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "collapsed": true, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "1. 넘파이 로그 베이스를 자연로그가 아닌 다른 수로 하고 싶을 경우, 표현식의 예를 들어라." + ] + }, + { + "cell_type": "code", + "source": [ + "import numpy as np\n", + "\n", + "# 로그 밑이 3인 지수 1에서 10까지의 10개 원소 출력하기, 닝겐이 알아보기 쉽게 정수형으로\n", + "x = np.logspace(1, 10, base = 3, num = 10, dtype=int)\n", + "print(x)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + }, + "execution_count": 9, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 3 9 27 81 243 729 2187 6561 19683 59049]\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "2. 행렬의 종류 14개 이상 적어라.\n", + "> 단위행렬, 영행렬, 정방행렬, 대각행렬, 삼각행렬, 항등행렬, 전치행렬, 직교행렬, 대칭행렬, 비대징행렬, 계수행렬, 첨가행렬, 스칼라행렬, 삼각행렬, 치환행\n", + ">[참고링크](http://www.ktword.co.kr/abbr_view.php?m_temp1=4646)\n", + "\n", + "3. 행렬 방정식이란?\n", + "> 연립방정식을 선형대수의 형태로 치환하여 해를 구하는 법??\n", + "> 답을 모르겠습니다.ㅜㅜ" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file diff --git "a/03\354\236\245/3\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" "b/03\354\236\245/3\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" new file mode 100644 index 0000000..fa58c36 --- /dev/null +++ "b/03\354\236\245/3\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" @@ -0,0 +1,13 @@ +1. +c -> c 배열을 보여줘라 +c[tuple([[1, 3, 4], [3, 4, 5]])] +-> 1행 인덱스에 3열의 포함되는 값 검색, 3행 인덱스 4열 인덱스에 포함되는 값 검색, 4행 인덱스 5열 인덱스 포함되는 값 검색 +c[1][3] -> c 배열에 1행 3열의 값을 검색 +c[3][4] -> c 배열에 3행 4열의 값을 검색 +c[4][5] -> c 배열에 4행 5열의 값을 검색 + +2. +단일 스칼라 대신 인덱스 배열을 반환, 복잡한 배열 값의 하위 집합에 매우 빠르게 접근하여 수정하는 기법 + +3. +파이썬에서는 리스트, 튜플, range, 문자열처럼 값이 연속적으로 이어진 자료형을 시퀀스 자료형이라고 함 diff --git "a/03\354\236\245/3\354\236\245\355\200\264\354\246\210-\354\236\245\354\203\201\352\267\274.md" "b/03\354\236\245/3\354\236\245\355\200\264\354\246\210-\354\236\245\354\203\201\352\267\274.md" new file mode 100644 index 0000000..4977cf8 --- /dev/null +++ "b/03\354\236\245/3\354\236\245\355\200\264\354\246\210-\354\236\245\354\203\201\352\267\274.md" @@ -0,0 +1,11 @@ +### 퀴즈1) 튜플 인덱싱 설명 +![Imgur](https://i.imgur.com/QoJgY9e.png?1) +두개의 배열을 순서쌍으로 만들어 검색하는것. 그림 자체가 설명입니다. + +### 퀴즈2) 팬시 인덱싱이란? +정수 배열을 만들어 행과 열의 원소를 추출하는 방법으로 논리갑으로 만든 배열을 색인연산에 전달하여 배열을 추출하는 논리식 검색입니다. 이 방법을 사용하면 다른 검색조건과 혼합하여 검색 할 수 있기 때문에 다양한 검색조건을 만들 수 있습니다. 기본 인덱싱과 달리 원본의 불러오는 방식이 아니라 사본을 만들어 인덱싱하는 특징이 있습니다. + +### 퀴즈3) 파이썬 시퀀스 자료형에 대해 설명하시오. +각각의 요소들이 연속적으로 이어진 자료형으로 데이터에 순서(번호)를 붙여서 나열한 것입니다. +시컨스형 자료에는 list, tuple, range, string 등이 있으며 순서(번호)가 있기 때문에 indexing, slicing, 연산, 반복 등이 가능합니다. + diff --git "a/03\354\236\245/[\353\204\230\355\214\214\354\235\264]03\354\236\245.pptx" "b/03\354\236\245/[\353\204\230\355\214\214\354\235\264]03\354\236\245.pptx" new file mode 100644 index 0000000..901ac65 Binary files /dev/null and "b/03\354\236\245/[\353\204\230\355\214\214\354\235\264]03\354\236\245.pptx" differ diff --git "a/03\354\236\245/chaper3 quiz \352\271\200\353\257\274\352\267\234" "b/03\354\236\245/chaper3 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..60f6d6a --- /dev/null +++ "b/03\354\236\245/chaper3 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,25 @@ +1. +넘파이 모듈에서 팬시 인덱싱을 사용할 때는 배열을 명확히 이해하기 위해 tuple로 묶어서 처리합니다. +Tuple로 묶어서 순서쌍을 만들어 팬시검색을 합니다. +tuple([[1,3,4], [3,4,5]])에서 첫 번째 괄호에서 index가 0인 1을 행으로, 두 번째 괄호에서 index가 0인 3을 열로 (1,3) 순서쌍을 이루어 13 원소를 찾는 것입니다. +첫 번째 괄호 index 1 = 3, 두 번째 괄호 index 1 = 4, 순서쌍은 (3,4), 원소는 34 +첫 번째 괄호 index 2 = 4, 두 번째 괄호 index 2 = 5, 순서쌍은 (4,5), 원소는 45 + + +2. +기존 배열의 형상을 유지하고 정수 배열을 만들어서 행과 열의 원소(검색된 원소)를 추출하는 것을 팬시 인덱싱이라고 합니다. +다른 검색조건과 혼합해서 검색할 수 있기 때문에 다양한 검색조건을 만들 수 있습니다. +대괄호 [, ]를 사용하여 행괄 열을 지정하여 검색하거나 tuple을 사용하여 묶어서 검색할 수 있습니다. + +3. +파이썬에서는 리스트, 튜플, range, 문자열처럼 값이 연속적으로 이어진 자료형을 시퀀스 자료형라고 부릅니다. + +- 시퀀스 자료형의 종류 +List, tuple, range, str, bytes, bytearray + +- 시퀀스 자료형의 특성 +인덱싱 = 인덱스를 통해 해당 값에 접근이 가능하고 인덱스는 0부터 시작합니다. +슬라이싱 = 특정 구간의 값을 얻을 수 있고 구간을 [x:y]라 하면 x이상, y미만으로 정의됩다. +연결 = 두 시퀀스를 '+' 연산자로 연결하여 새로운 시퀀스 자료를 생성 가능합니다. +반복 = 시퀀스 자료를 '*' 연산자로 여러번 반복하여 새로운 자료를 생성가능합니다. +크기 = len()을 사용하여 스퀀스 자료의 크기를 알 수 있습니다. diff --git "a/04\354\236\245/.ipynb_checkpoints/4\354\236\245 \355\200\264\354\246\210 - \354\236\245\354\203\201\352\267\274.md-checkpoint.ipynb" "b/04\354\236\245/.ipynb_checkpoints/4\354\236\245 \355\200\264\354\246\210 - \354\236\245\354\203\201\352\267\274.md-checkpoint.ipynb" new file mode 100644 index 0000000..7fec515 --- /dev/null +++ "b/04\354\236\245/.ipynb_checkpoints/4\354\236\245 \355\200\264\354\246\210 - \354\236\245\354\203\201\352\267\274.md-checkpoint.ipynb" @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git "a/04\354\236\245/4\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" "b/04\354\236\245/4\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" new file mode 100644 index 0000000..1b38210 --- /dev/null +++ "b/04\354\236\245/4\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" @@ -0,0 +1,6 @@ +1. +언더바라고 읽는, '_' 와 같은 표시를 언더스코어라고 하는데 이것이 +여러가지 상황에서 쓰이는데 이 상황에서 쓰이는 의미는 값을 무시하고 싶은 경우에 사용하는거 같습니다. + +2. +a변수 2행 2열의 배열을 문자열로 지정한 후 뒤에 연산된 결과 축을 문자열로 지정한다. diff --git "a/04\354\236\245/4\354\236\245 \355\200\264\354\246\210 - \354\236\245\354\203\201\352\267\274.md.ipynb" "b/04\354\236\245/4\354\236\245 \355\200\264\354\246\210 - \354\236\245\354\203\201\352\267\274.md.ipynb" new file mode 100644 index 0000000..e75867e --- /dev/null +++ "b/04\354\236\245/4\354\236\245 \355\200\264\354\246\210 - \354\236\245\354\203\201\352\267\274.md.ipynb" @@ -0,0 +1,37 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Q1) d.flat = [i for _, i in z]에서 '_'의 의미는? \n", + "해당 코드에서 언더스코어의 사용은 변수를 지정해야 하는데, 특별히 나중에 쓸일이 없는 변수를 할당해야 해서 사용됨. \n", + "일반적으로 변수는 코드에서 의미를 가지거나, 협업시 가독이 필요하게 명명해야 하나, 이경우에는 그냥 할당만 하는 목적이므로 언더스코어를 사용함. \n", + "\n", + "## Q2) np.einsum(\"ij→ji\", a) 이 명령어의 의미는? \n", + "a.T 와 같은의미임. 행과열을 열과행으로 바꿈. " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git "a/04\354\236\245/4\354\236\245.ipynb" "b/04\354\236\245/4\354\236\245.ipynb" new file mode 100644 index 0000000..c8dba5c --- /dev/null +++ "b/04\354\236\245/4\354\236\245.ipynb" @@ -0,0 +1,4004 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from IPython.display import Image" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.18.5'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.__version__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# chapter 4. 다차원 배열의 연산" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 산술 연산" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 벡터간의 덧셈" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 동일한 원소를 가진 1차원 배열간의 덧셈, 벡터간의 덧셈은 새로운 벡터를 만듭니다.\n", + "- 1차원 배열의 __원소별 덧셈 연산__합니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](numpy/04/04_1.png)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "d = np.array([3,4])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 4])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.array([5,6]) " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([5, 6])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 8, 10])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d + e" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 8, 10])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.add(d, e)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "f = np.array([1,2,3])" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "operands could not be broadcast together with shapes (3,) (2,) \n" + ] + } + ], + "source": [ + "try :\n", + " f + e\n", + "except Exception as ex :\n", + " print(ex)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 벡터간의 뺄셈" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 벡터간의 뺄셈도 덧셈과 동일하게 평행사변형을 만듭니다. 대신 반대 방향이라서 반대 방향의 평행사변형이 그려집니다.\n", + "- 1차원 배열의 __원소별 뺄셈처리__로 계산합니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](numpy/04/04_2.png)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "d = np.array([3,4])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 4])" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.array([5,6])" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([5, 6])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "f= d - e" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-2, -2])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-2, -2])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.subtract(d,e)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-2, -2])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d + (-e)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-2, -2])" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.add(d, np.negative(e))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 스칼라 값을 벡터에 곱하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 특정 벡터가 있을 때 이 벡터를 특정 상수만큼 크기를 확장할 수 있습니다. 이를 스칼라 배라고 합니다. __벡터에 상수를 곱한 결과__입니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](numpy/04/04_3.png)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "d = np.array([2,3])" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2, 3])" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "e = 3 * d" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([6, 9])" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.array([3,3]) * d" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([6, 9])" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.multiply(3, d)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([6, 9])" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.multiply(np.array([3,3]), d)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([6, 9])" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "e = 1/3 * d" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.66666667, 1. ])" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.divide(d,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.66666667, 1. ])" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.multiply(d, (1/3))" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.66666667, 1. ])" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 브로드캐스팅 이해하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 브로트캐스팅" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 차원이 다른 배열간의 계산을 할 때에는 먼저 __원소별 계산__을 위해 __동일한 shape를 구성__합니다. 이를 브로트캐스팅이라고 합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(10).reshape(2,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2, 3, 4],\n", + " [5, 6, 7, 8, 9]])" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.arange(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4])" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "z = np.broadcast(x,y)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "z" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape : (2, 5), dimension : 2\n" + ] + } + ], + "source": [ + "print(\"shape : {}, dimension : {}\".format(z.shape, z.ndim))" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.broadcast" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(z)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1차원 배열을 2차원 배열로 변환" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(0, 0)\n", + "(1, 1)\n", + "(2, 2)\n", + "(3, 3)\n", + "(4, 4)\n", + "(5, 0)\n", + "(6, 1)\n", + "(7, 2)\n", + "(8, 3)\n", + "(9, 4)\n" + ] + } + ], + "source": [ + "for i in z :\n", + " print(i)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "t = x + y" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 2, 4, 6, 8],\n", + " [ 5, 7, 9, 11, 13]])" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "t" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 브로드캐스팅 처리 규칙" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "x1 = np.ones(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 1.])" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "x2 = np.ones((2,3))" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 1., 1.],\n", + " [1., 1., 1.]])" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__마지막 원소 갯수 확인__" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((3,), (2, 3))" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1.shape, x2.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(2, 3)" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x2.shape[0], x2.shape[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1.shape[0] == x2.shape[1]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__차원 추가__" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [], + "source": [ + "x1 = x1[np.newaxis,]" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(1, 3)" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "x1 = x1[np.newaxis,]" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(1, 1, 3)" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1.shape ############ 새로운 차원은 앞에만 추가되는지?" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "##########차원 삭제는 어떻게 하는지?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__행을 하나 더 추가__" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[1., 1., 1.]]])" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "x1 = np.vstack((x1[0])) ################" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 1., 1.]])" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 행벡터와 열벡터 브로드캐스팅 확장" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 행벡터와 열벡터의 연산은 __동일한 shape를 구성한 후__에 __원소별로 계산__합니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](numpy/04/04_4.png)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(1,4)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3])" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [], + "source": [ + "x1 = x.reshape(1,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3]])" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [], + "source": [ + "x2 = x[np.newaxis,]" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3]])" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x2" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.arange(1,4)" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3])" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [], + "source": [ + "y1 = y.reshape(3,1)" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1],\n", + " [2],\n", + " [3]])" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y1" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [], + "source": [ + "y2 = y[:,np.newaxis]" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1],\n", + " [2],\n", + " [3]])" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y2" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[array([[1, 2, 3],\n", + " [1, 2, 3],\n", + " [1, 2, 3]]),\n", + " array([[1, 1, 1],\n", + " [2, 2, 2],\n", + " [3, 3, 3]])]" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.broadcast_arrays(x1,y1)" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2, 3, 4],\n", + " [3, 4, 5],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1 + y1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 행렬의 연산" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 벡터의 내적" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 벡터의 내적은 두 벡터의 크기와 내각의 곱, 또는 두 벡터의 원소별 곱셈 후에 더해서 구할 수 있습니다.\n", + "- 보통 벡터 내적은 __두 벡터가 수직인지 확인__할 때 많이 사용됩니다.

\n", + "공식 : $\n", + "a \\cdot b=|a| \\times|b| \\times \\cos (\\theta)\n", + "$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](numpy/04/04_5.png)" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([3,4])" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 4])" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array([5,6])" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([5, 6])" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "39" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a @ b" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "39" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(a,b)" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "39" + ] + }, + "execution_count": 85, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.inner(a,b)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 벡터의 외적(cross product)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 두 벡터의 외적은 두 벡터를 평면으로 인식한 후에 두 벡터가 만나는 점에 대하여 수직인 벡터를 구하는 것입니다.

\n", + "cross product :
\n", + "https://ko.wikipedia.org/wiki/%EB%B2%A1%ED%84%B0%EA%B3%B1
\n", + "outer product :
\n", + "https://ko.wikipedia.org/wiki/%EC%99%B8%EC%A0%81" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](numpy/04/04_6.png)" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,4])\n", + "b = np.array([3,6])" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(-6)" + ] + }, + "execution_count": 87, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cross(a,b)" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.array([1,4,3])\n", + "d = np.array([3,4,5])" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 8, 4, -8])" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cross(c,d)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 행렬 dot product" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- dot product는 A 행렬의 행과 B 행렬의 열 간의 원소를 곱해서 더한 값을 새로운 행렬의 A행렬의 0번 축의 위치와 B행렬의 1번 축의 위치에 해당하는 원소가 됩니다.

\n", + "$ a \\cdot b=\\sum_{n} a_{n} b_{n} $ <---------- 넘파이로 구현 시 : np.dot(a,b)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](numpy/04/dot_product_1.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](numpy/04/dot_product_2.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 행렬 dot product 계산" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 2개의 2행 2열의 배열을 만들고, dot 함수, dot 메소드, @ 연산자로 dot 연산을 실행합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([[3,4],[5,6]])" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 4],\n", + " [5, 6]])" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array([[5,6],[6,7]])" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[5, 6],\n", + " [6, 7]])" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[39, 46],\n", + " [61, 72]]),\n", + " array([[39, 46],\n", + " [61, 72]]),\n", + " array([[39, 46],\n", + " [61, 72]]))" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(a,b), a.dot(b), a@b " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 행렬 dot product 계산 : 행렬분해이용" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 두번째 행렬을 열벡터로 분해한 후에 dot product를 계산한 결과도 알아봅시다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$\n", + "A b_{1}=A\\left[\\begin{array}{c}\n", + "b_{11} \\\\\n", + "b_{21} \\\\\n", + "\\vdots \\\\\n", + "b_{n 1}\n", + "\\end{array}\\right]\n", + "$\n", + "        \n", + "$\n", + "A b_{2}=A\\left[\\begin{array}{c}\n", + "b_{12} \\\\\n", + "b_{22} \\\\\n", + "\\vdots \\\\\n", + "b_{n 2}\n", + "\\end{array}\\right]\n", + "$\n", + "        \n", + "$\n", + "A b_{n}=A\\left[\\begin{array}{c}\n", + "b_{1n} \\\\\n", + "b_{2n} \\\\\n", + "\\vdots \\\\\n", + "b_{n n}\n", + "\\end{array}\\right]\n", + "$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "dot product 연산" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([[1,2,3],[4,5,6],[7,8,9]])" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6],\n", + " [7, 8, 9]])" + ] + }, + "execution_count": 96, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array([[1,2,3],[4,5,6],[7,8,9]])" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6],\n", + " [7, 8, 9]])" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 30, 36, 42],\n", + " [ 66, 81, 96],\n", + " [102, 126, 150]])" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(a,b)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 행렬식, 역행렬 처리하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 행렬식" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 행렬식(determinant)은 정사각행렬일 때 이 원소들을 대응해서 값을 구하는 방식입니다. 정사각행렬이 아닌 경우에는 행렬식을 계산할 수 없습니다. 행렬식으로 계산하면 벡터와 행렬 간의 dot product를 통해 선형 변환한 결과의 부피를 구할 수 있습니다. 또한 행렬식을 사용해서 연립방정식의 해를 구할 때도 사용합니다.

\n", + "https://ko.wikipedia.org/wiki/%ED%96%89%EB%A0%AC%EC%8B%9D" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([[3,1],[2,2]])" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 1],\n", + " [2, 2]])" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "module 'numpy' has no attribute 'det'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdet\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/numpy/__init__.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(attr)\u001b[0m\n\u001b[1;32m 217\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mTester\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 218\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 219\u001b[0;31m raise AttributeError(\"module {!r} has no attribute \"\n\u001b[0m\u001b[1;32m 220\u001b[0m \"{!r}\".format(__name__, attr))\n\u001b[1;32m 221\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mAttributeError\u001b[0m: module 'numpy' has no attribute 'det'" + ] + } + ], + "source": [ + "np.det(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.000000000000001" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 104, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(4.0, np.linalg.det(a))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 행렬식" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 행렬이 차원이 커질 경우 행렬식을 구할 때는 소행렬식을 사용해서 행렬식을 구할 수 있습니다. 3행 3열의 배열을 소행렬식으로 계산하기 위해 첫 번째 행을 제외하고 나머지 두 개의 행을 2행 2열로 만들어서 소행렬식을 구하고 첫 번째 행의 값을 곱한 후에 부호를 조정하면 행렬식 계산과 같습니다" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$\n", + "\\operatorname{det}\\left[\\begin{array}{lll}\n", + "a_{11} & a_{12} & a_{13} \\\\\n", + "a_{21} & a_{22} & a_{23} \\\\\n", + "a_{31} & a_{32} & a_{33}\n", + "\\end{array}\\right]\n", + "$\n", + "$\n", + " =a_{11} \\text { det }\\left[\\begin{array}{ll}\n", + "a_{22} & a_{23} \\\\\n", + "a_{32} & a_{33}\n", + "\\end{array}\\right]-a_{12} \\text { det }\\left[\\begin{array}{ll}\n", + "a_{21} & a_{23} \\\\\n", + "a_{31} & a_{33}\n", + "\\end{array}\\right]+a_{13} \\text { det }\\left[\\begin{array}{ll}\n", + "a_{21} & a_{22} \\\\\n", + "a_{31} & a_{32}\n", + "\\end{array}\\right]\n", + "$" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array([[3,1,3],[2,2,3],[1,1,1]])" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 1, 3],\n", + " [2, 2, 3],\n", + " [1, 1, 1]])" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-3.0" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "3 * np.linalg.det(b[1:, 1:])" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-1.0" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(b[1:, ::2]) #########################" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 109, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(b[1:, :2])" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-2.0" + ] + }, + "execution_count": 110, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-2" + ] + }, + "execution_count": 111, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "-3 + 1 + 0" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 역행렬 (Inverse Matrix)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 역행렬을 구할 때 행렬식의 결과값으로 나누는 것은 매우 중요합니다. 행렬식이 0이 나오면 수학적인 계산이 불가능해서 역행렬을 계산하지 못합니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$\\begin{aligned} A^{-1}=& \\frac{1}{a d-b c}\\left[\\begin{array}{cc}d & -b \\\\ -c & a\\end{array}\\right]=\\left[\\begin{array}{ccc}\\frac{d}{a d-b c} & -\\frac{b}{a d-b c} \\\\ -\\frac{c}{a d-b c} & \\frac{a}{a d-b c}\\end{array}\\right] \\\\ &=\\frac{a d j A}{\\operatorname{det} A} \\end{aligned}$" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([[3,2],[6,4]])" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 2],\n", + " [6, 4]])" + ] + }, + "execution_count": 113, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 114, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array([[1,2,3],[4,5,6],[3,2,4]])" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6],\n", + " [3, 2, 4]])" + ] + }, + "execution_count": 116, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-9.000000000000002" + ] + }, + "execution_count": 117, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "metadata": {}, + "outputs": [], + "source": [ + "bi = np.linalg.inv(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.88888889, 0.22222222, 0.33333333],\n", + " [-0.22222222, 0.55555556, -0.66666667],\n", + " [ 0.77777778, -0.44444444, 0.33333333]])" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bi" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": {}, + "outputs": [], + "source": [ + "bb = np.dot(b, bi)" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.00000000e+00, 1.66533454e-16, -5.55111512e-17],\n", + " [ 0.00000000e+00, 1.00000000e+00, -1.11022302e-16],\n", + " [ 0.00000000e+00, -2.22044605e-16, 1.00000000e+00]])" + ] + }, + "execution_count": 121, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bb" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.eye(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 0., 0.],\n", + " [0., 1., 0.],\n", + " [0., 0., 1.]])" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 124, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(np.eye(3), bb)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 역행렬의 교환법칙" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 역행렬의 행렬곱 연산은 반대로 계산해도 동일한 단위행렬이 나옵니다. 단위행렬은 보통 대문자 I로 사용하지만 대문자 E로도 표기하는 경우도 있습니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$\n", + "A^{-1}=A^{-1} A=E\n", + "$" + ] + }, + { + "cell_type": "code", + "execution_count": 125, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([[1,2],[3,4]])" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2],\n", + " [3, 4]])" + ] + }, + "execution_count": 126, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [], + "source": [ + "ai = np.linalg.inv(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-2. , 1. ],\n", + " [ 1.5, -0.5]])" + ] + }, + "execution_count": 128, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ai" + ] + }, + { + "cell_type": "code", + "execution_count": 129, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.dot(a, ai)" + ] + }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1.00000000e+00, 1.11022302e-16],\n", + " [0.00000000e+00, 1.00000000e+00]])" + ] + }, + "execution_count": 130, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 131, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.eye(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 0.],\n", + " [0., 1.]])" + ] + }, + "execution_count": 132, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 133, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(b, x)" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.dot(ai, a)" + ] + }, + { + "cell_type": "code", + "execution_count": 135, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1.0000000e+00, 4.4408921e-16],\n", + " [0.0000000e+00, 1.0000000e+00]])" + ] + }, + "execution_count": 135, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 136, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(np.eye(2), y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 역행렬의 분배처리" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 두 행렬 A, B의 행렬곱을 하면 하나의 행렬이 만들어집니다. 이를 -1을 위 첨자로 사용해서 역행렬을 표시할 수 있습니다. 이 산식을 전개하면 두 행렬의 위치가 변경되고 각 행렬마다 위 첨자를 사용해서 역행렬을 표시합니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$\n", + "(A B)^{-1}=B^{-1} A^{-1}\n", + "$" + ] + }, + { + "cell_type": "code", + "execution_count": 137, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([[1,2],[3,4]])" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2],\n", + " [3, 4]])" + ] + }, + "execution_count": 138, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 139, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-2.0000000000000004" + ] + }, + "execution_count": 139, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array([[3,4],[1,2]])" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 4],\n", + " [1, 2]])" + ] + }, + "execution_count": 141, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 142, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2.0000000000000004" + ] + }, + "execution_count": 142, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 143, + "metadata": {}, + "outputs": [], + "source": [ + "ai = np.linalg.inv(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 144, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-2. , 1. ],\n", + " [ 1.5, -0.5]])" + ] + }, + "execution_count": 144, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ai" + ] + }, + { + "cell_type": "code", + "execution_count": 145, + "metadata": {}, + "outputs": [], + "source": [ + "bi = np.linalg.inv(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1. , -2. ],\n", + " [-0.5, 1.5]])" + ] + }, + "execution_count": 146, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bi" + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "metadata": {}, + "outputs": [], + "source": [ + "ab = np.linalg.inv(np.dot(a, b))" + ] + }, + { + "cell_type": "code", + "execution_count": 148, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-5. , 2. ],\n", + " [ 3.25, -1.25]])" + ] + }, + "execution_count": 148, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ab" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "metadata": {}, + "outputs": [], + "source": [ + "ba = np.dot(bi, ai)" + ] + }, + { + "cell_type": "code", + "execution_count": 150, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-5. , 2. ],\n", + " [ 3.25, -1.25]])" + ] + }, + "execution_count": 150, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ba" + ] + }, + { + "cell_type": "code", + "execution_count": 151, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 151, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(ab,ba)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### - 의사 역행렬" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 역행렬은 정사각행렬 중에 행렬식이 0이 아닌 경우에만 구할 수 있습니다. 특정 행렬이 역행렬이 없을 떄에 역행렬을 임의로 계산하는 것을 의사 역행렬이라고 합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 152, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.ones((3,3))" + ] + }, + { + "cell_type": "code", + "execution_count": 153, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 1., 1.],\n", + " [1., 1., 1.],\n", + " [1., 1., 1.]])" + ] + }, + "execution_count": 153, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 154, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 154, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.det(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0.11111111, 0.11111111, 0.11111111],\n", + " [0.11111111, 0.11111111, 0.11111111],\n", + " [0.11111111, 0.11111111, 0.11111111]])" + ] + }, + "execution_count": 155, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.pinv(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 156, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Singular matrix\n" + ] + } + ], + "source": [ + "try : np.linalg.inv(a)\n", + "except Exception as e: print(e)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## einsum 연산 확인하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 전치행렬" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 아인슈타인의 합은 선형대수학을 물리학에 응용하면서 좌표계에 관한 공식을 다룰 때 유용한 표기규칙으로 선형대수를 편리하게 계산할 수 있는 방법입니다.\n", + "- 전치행렬을 처리하려면 먼저 문자열에 두 행렬의 인덱스 정보를 반대로 만듭니다. " + ] + }, + { + "cell_type": "code", + "execution_count": 157, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([[1,2,3],[4,5,6]])" + ] + }, + { + "cell_type": "code", + "execution_count": 158, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 158, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 159, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 4],\n", + " [2, 5],\n", + " [3, 6]])" + ] + }, + "execution_count": 159, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.T" + ] + }, + { + "cell_type": "code", + "execution_count": 160, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 4],\n", + " [2, 5],\n", + " [3, 6]])" + ] + }, + "execution_count": 160, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.einsum(\"ij->ji\", a)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 하나의 벡터와 행렬 계산" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- Einsum으로 벡터의 원소를 합산할 경우는 하나의 인덱스를 표시하고 결과는 아무것도 표시하지 않습니다. \n", + "- 벡터는 하나, 행렬은 두 개의 인덱스를 문자로 표시해야합니다. " + ] + }, + { + "cell_type": "code", + "execution_count": 161, + "metadata": {}, + "outputs": [], + "source": [ + "aa = np.arange(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 162, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])" + ] + }, + "execution_count": 162, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "aa" + ] + }, + { + "cell_type": "code", + "execution_count": 163, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.einsum('i->', aa)" + ] + }, + { + "cell_type": "code", + "execution_count": 164, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "45" + ] + }, + "execution_count": 164, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 165, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.sum(aa)" + ] + }, + { + "cell_type": "code", + "execution_count": 166, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "45" + ] + }, + "execution_count": 166, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 167, + "metadata": {}, + "outputs": [], + "source": [ + "a__ = np.array([[1,1,1],[3,2,4],[7,5,8]])" + ] + }, + { + "cell_type": "code", + "execution_count": 168, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 1, 1],\n", + " [3, 2, 4],\n", + " [7, 5, 8]])" + ] + }, + "execution_count": 168, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a__" + ] + }, + { + "cell_type": "code", + "execution_count": 169, + "metadata": {}, + "outputs": [], + "source": [ + "__a = np.einsum(\"ij->\", a__)" + ] + }, + { + "cell_type": "code", + "execution_count": 170, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "32" + ] + }, + "execution_count": 170, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "__a" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "metadata": {}, + "outputs": [], + "source": [ + "__a = np.sum(a__)" + ] + }, + { + "cell_type": "code", + "execution_count": 172, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "32" + ] + }, + "execution_count": 172, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "__a" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__행렬 축에 따른 계산__" + ] + }, + { + "cell_type": "code", + "execution_count": 173, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.einsum(\"ij->i\", a__)" + ] + }, + { + "cell_type": "code", + "execution_count": 174, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 3, 9, 20])" + ] + }, + "execution_count": 174, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 175, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.sum(a__, axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 176, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 3, 9, 20])" + ] + }, + "execution_count": 176, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 177, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.einsum(\"ij->j\", a__)" + ] + }, + { + "cell_type": "code", + "execution_count": 178, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([11, 8, 13])" + ] + }, + "execution_count": 178, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 179, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.sum(a__, axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 180, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([11, 8, 13])" + ] + }, + "execution_count": 180, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 두 개의 배열 연산" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 두 개의 1차원 배열을 가지고 곱셈과 닷연산은 동일한 인덱스 문자를 사용합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.arange(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])" + ] + }, + "execution_count": 182, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 183, + "metadata": {}, + "outputs": [], + "source": [ + "d = np.arange(5, 15)" + ] + }, + { + "cell_type": "code", + "execution_count": 184, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])" + ] + }, + "execution_count": 184, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__두 벡터의 곱셈__" + ] + }, + { + "cell_type": "code", + "execution_count": 185, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.einsum('i,i->i', c, d)" + ] + }, + { + "cell_type": "code", + "execution_count": 186, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 6, 14, 24, 36, 50, 66, 84, 104, 126])" + ] + }, + "execution_count": 186, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 187, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.einsum('i,i->', c, d)" + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "510" + ] + }, + "execution_count": 188, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 189, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.dot(c,d)" + ] + }, + { + "cell_type": "code", + "execution_count": 190, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "510" + ] + }, + "execution_count": 190, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 행벡터와 열벡터의 닷연산" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 두 개의 벡터를 행벡터와 열벡터의 닷연산으로 계산이 가능합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 191, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])" + ] + }, + "execution_count": 191, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 192, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])" + ] + }, + "execution_count": 192, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": {}, + "outputs": [], + "source": [ + "c_ = c.reshape(10,1)" + ] + }, + { + "cell_type": "code", + "execution_count": 194, + "metadata": {}, + "outputs": [], + "source": [ + "d_ = d.reshape(1,10)" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0],\n", + " [1],\n", + " [2],\n", + " [3],\n", + " [4],\n", + " [5],\n", + " [6],\n", + " [7],\n", + " [8],\n", + " [9]])" + ] + }, + "execution_count": 195, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c_" + ] + }, + { + "cell_type": "code", + "execution_count": 196, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]])" + ] + }, + "execution_count": 196, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d_" + ] + }, + { + "cell_type": "code", + "execution_count": 197, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],\n", + " [ 10, 12, 14, 16, 18, 20, 22, 24, 26, 28],\n", + " [ 15, 18, 21, 24, 27, 30, 33, 36, 39, 42],\n", + " [ 20, 24, 28, 32, 36, 40, 44, 48, 52, 56],\n", + " [ 25, 30, 35, 40, 45, 50, 55, 60, 65, 70],\n", + " [ 30, 36, 42, 48, 54, 60, 66, 72, 78, 84],\n", + " [ 35, 42, 49, 56, 63, 70, 77, 84, 91, 98],\n", + " [ 40, 48, 56, 64, 72, 80, 88, 96, 104, 112],\n", + " [ 45, 54, 63, 72, 81, 90, 99, 108, 117, 126]])" + ] + }, + "execution_count": 197, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(c_,d_)" + ] + }, + { + "cell_type": "code", + "execution_count": 198, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],\n", + " [ 10, 12, 14, 16, 18, 20, 22, 24, 26, 28],\n", + " [ 15, 18, 21, 24, 27, 30, 33, 36, 39, 42],\n", + " [ 20, 24, 28, 32, 36, 40, 44, 48, 52, 56],\n", + " [ 25, 30, 35, 40, 45, 50, 55, 60, 65, 70],\n", + " [ 30, 36, 42, 48, 54, 60, 66, 72, 78, 84],\n", + " [ 35, 42, 49, 56, 63, 70, 77, 84, 91, 98],\n", + " [ 40, 48, 56, 64, 72, 80, 88, 96, 104, 112],\n", + " [ 45, 54, 63, 72, 81, 90, 99, 108, 117, 126]])" + ] + }, + "execution_count": 198, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.einsum('i,j->ij', c,d)" + ] + }, + { + "cell_type": "code", + "execution_count": 199, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],\n", + " [ 10, 12, 14, 16, 18, 20, 22, 24, 26, 28],\n", + " [ 15, 18, 21, 24, 27, 30, 33, 36, 39, 42],\n", + " [ 20, 24, 28, 32, 36, 40, 44, 48, 52, 56],\n", + " [ 25, 30, 35, 40, 45, 50, 55, 60, 65, 70],\n", + " [ 30, 36, 42, 48, 54, 60, 66, 72, 78, 84],\n", + " [ 35, 42, 49, 56, 63, 70, 77, 84, 91, 98],\n", + " [ 40, 48, 56, 64, 72, 80, 88, 96, 104, 112],\n", + " [ 45, 54, 63, 72, 81, 90, 99, 108, 117, 126]])" + ] + }, + "execution_count": 199, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.outer(c,d)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 행렬 einnum 연산" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 두 개의 2차원 배열을 인자로 받아서 행렬의 곱셈, 닷연산을 einsum 함수로 계산합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 200, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.arange(10).reshape(2,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 201, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2, 3, 4],\n", + " [5, 6, 7, 8, 9]])" + ] + }, + "execution_count": 201, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 202, + "metadata": {}, + "outputs": [], + "source": [ + "f = np.arange(5, 15).reshape(2,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 203, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 5, 6, 7, 8, 9],\n", + " [10, 11, 12, 13, 14]])" + ] + }, + "execution_count": 203, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__행렬의 곱셈__" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 6, 14, 24, 36],\n", + " [ 50, 66, 84, 104, 126]])" + ] + }, + "execution_count": 204, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.einsum('ij,ij->ij', e, f)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__행렬의 닷연산__" + ] + }, + { + "cell_type": "code", + "execution_count": 205, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2, 3, 4],\n", + " [5, 6, 7, 8, 9]])" + ] + }, + "execution_count": 205, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 206, + "metadata": {}, + "outputs": [], + "source": [ + "f_ = f.T" + ] + }, + { + "cell_type": "code", + "execution_count": 207, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 5, 10],\n", + " [ 6, 11],\n", + " [ 7, 12],\n", + " [ 8, 13],\n", + " [ 9, 14]])" + ] + }, + "execution_count": 207, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f_" + ] + }, + { + "cell_type": "code", + "execution_count": 208, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 80, 130],\n", + " [255, 430]])" + ] + }, + "execution_count": 208, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.einsum('ij,jk->ik', e,f.T)" + ] + }, + { + "cell_type": "code", + "execution_count": 209, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 80, 130],\n", + " [255, 430]])" + ] + }, + "execution_count": 209, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(e,f.T)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# chapter 4 끝" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/04\354\236\245/[\353\204\230\355\214\214\354\235\264]04\354\236\245.pptx" "b/04\354\236\245/[\353\204\230\355\214\214\354\235\264]04\354\236\245.pptx" new file mode 100644 index 0000000..09e6481 Binary files /dev/null and "b/04\354\236\245/[\353\204\230\355\214\214\354\235\264]04\354\236\245.pptx" differ diff --git "a/04\354\236\245/chapter 4 quiz \352\271\200\353\257\274\352\267\234" "b/04\354\236\245/chapter 4 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..1e4b817 --- /dev/null +++ "b/04\354\236\245/chapter 4 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,12 @@ +1. +변수 명의 일종으로 사용되는 경우로 이 사용법은 인터프리터에서 사용할 경우와 약간 관계가 있습니다. +'_' 는 일종의 'throw-away' (버려도 상관없는, 필요없는) 변수명으로 사용됩니다. +이는 코딩 컨벤션에 따라 어떤 변수명이 할당되었으나 사용되지 않는다는 것을 당신의 코드를 보는 사람에게 알려주는 역할을 합니다. +예를 들어 'for' 루프를 단순 반복시키는 경우 지역변수 i 대신에 '_' 를 사용하면 됩니다. + + +2. +a변수 2행 2열의 배열 축을 문자열로 지정하고 -> 뒤에 연산된 결과 축을 문자열로 지정. +전치행렬을 하는 것과 같음. +b= a^T +b_ij=a_ji diff --git "a/04\354\236\245/numpy/.DS_Store" "b/04\354\236\245/numpy/.DS_Store" new file mode 100644 index 0000000..c1507cd Binary files /dev/null and "b/04\354\236\245/numpy/.DS_Store" differ diff --git "a/04\354\236\245/numpy/04/04_1.png" "b/04\354\236\245/numpy/04/04_1.png" new file mode 100644 index 0000000..868b9f3 Binary files /dev/null and "b/04\354\236\245/numpy/04/04_1.png" differ diff --git "a/04\354\236\245/numpy/04/04_2.png" "b/04\354\236\245/numpy/04/04_2.png" new file mode 100644 index 0000000..85d2bcd Binary files /dev/null and "b/04\354\236\245/numpy/04/04_2.png" differ diff --git "a/04\354\236\245/numpy/04/04_3.png" "b/04\354\236\245/numpy/04/04_3.png" new file mode 100644 index 0000000..e14d935 Binary files /dev/null and "b/04\354\236\245/numpy/04/04_3.png" differ diff --git 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"b/04\354\236\245/numpy/04/inverse_matrix_2.png" new file mode 100644 index 0000000..4f82fe8 Binary files /dev/null and "b/04\354\236\245/numpy/04/inverse_matrix_2.png" differ diff --git "a/05\354\236\245/5\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" "b/05\354\236\245/5\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" new file mode 100644 index 0000000..d97f43c --- /dev/null +++ "b/05\354\236\245/5\354\236\245 Quiz \354\265\234\352\262\275\354\233\205" @@ -0,0 +1,14 @@ +3. +b = np.arange(4) +b.resize(4, 4) +b +array([[0, 1, 2, 3], + [0, 0, 0, 0], + [0, 0, 0, 0], + [0, 0, 0, 0]]) + +4. +왜 그러는지는 저도 찾아봤는데 잘 모르겠어서 같은 int형 타입인데 숫자에 따라서 어떤 차이가 있는지 찾아봤습니다. +int16, int32, int64의 차이점들은 크기라고합니다. 더 자세한 것들은 제가 찾아본 링크 남겨 드리겠습니다. +int 16: 2바이트, int 32 및 int : 4바이트, int64 : 8바이트 입니다. +https://c10106.tistory.com/5958 diff --git "a/05\354\236\245/5\354\236\245.ipynb" "b/05\354\236\245/5\354\236\245.ipynb" new file mode 100644 index 0000000..a9157a1 --- /dev/null +++ "b/05\354\236\245/5\354\236\245.ipynb" @@ -0,0 +1,4077 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.18.5'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.__version__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# chapter 5. 다차원 배열의 구조 변경하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 변경 및 결합 주요 함수" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 배열의 형상 변경" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 1차원 배열을 만들고 내부의 원소 개수가 동일한 형상을 가진 다른 차원의 배열로 변경할 수 있습니다.\n", + "- Reshape 메소드에 형상을 인자로 전달해서 배열의 형상을 변경합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(16)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "x1 = x.reshape(2,8)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 1, 2, 3, 4, 5, 6, 7],\n", + " [ 8, 9, 10, 11, 12, 13, 14, 15]])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__원소의 개수가 안 맞으면 에러 발생__" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cannot reshape array of size 16 into shape (4,5)\n" + ] + } + ], + "source": [ + "try:\n", + " x2 = x.reshape(4,5)\n", + "except Exception as e:\n", + " print (e)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__-1을 지정하면 나머지 형상이 자동으로 세팅됨__" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "y1 = x.reshape(4,-1)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 1, 2, 3],\n", + " [ 4, 5, 6, 7],\n", + " [ 8, 9, 10, 11],\n", + " [12, 13, 14, 15]])" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y1" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "y2 = x.reshape(8,-1)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0, 1],\n", + " [ 2, 3],\n", + " [ 4, 5],\n", + " [ 6, 7],\n", + " [ 8, 9],\n", + " [10, 11],\n", + " [12, 13],\n", + " [14, 15]])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 배열의 크기 변경" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 배열의 크기는 resize로 변경해봅니다. reshape와 차이점은 __더 큰 배열로 확장할 수 있다는 것__입니다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__동일 차원에서 크기만 확장__" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.arange(4)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.resize(a,8)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 0, 1, 2, 3])" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3])" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 0, 1, 2, 3, 0])" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.resize(a,9)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 0, 1, 2, 3, 0])" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.resize(a,9)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 0, 1, 2, 3])" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.append(a,a)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__shape를 다른 차원으로 확대 가능__" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.arange(4)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3])" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2, 3],\n", + " [0, 1, 2, 3],\n", + " [0, 1, 2, 3],\n", + " [0, 1, 2, 3]])" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.resize(b,(4,4)) \n", + "########### [0,1,2,3],[0,0,0,0],[0,0,0,0],[0,0,0,0] 나오게 하려면" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "cannot reshape array of size 4 into shape (4,4)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m<__array_function__ internals>\u001b[0m in \u001b[0;36mreshape\u001b[0;34m(*args, **kwargs)\u001b[0m\n", + "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/numpy/core/fromnumeric.py\u001b[0m in \u001b[0;36mreshape\u001b[0;34m(a, newshape, order)\u001b[0m\n\u001b[1;32m 299\u001b[0m [5, 6]])\n\u001b[1;32m 300\u001b[0m \"\"\"\n\u001b[0;32m--> 301\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_wrapfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'reshape'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnewshape\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 302\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 303\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/numpy/core/fromnumeric.py\u001b[0m in \u001b[0;36m_wrapfunc\u001b[0;34m(obj, method, *args, **kwds)\u001b[0m\n\u001b[1;32m 59\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 60\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 61\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mbound\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 62\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 63\u001b[0m \u001b[0;31m# A TypeError occurs if the object does have such a method in its\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: cannot reshape array of size 4 into shape (4,4)" + ] + } + ], + "source": [ + "np.reshape(b,(4,4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__새로운 배열을 만들 때 refcheck=False 지정__" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.arange(8)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5, 6, 7])" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [], + "source": [ + "c.resize(4, refcheck=False) # 구글링 결과 refcheck는 resize에만 해당" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3])" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(16)" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "'refcheck' is an invalid keyword argument for this function", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mrefcheck\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m: 'refcheck' is an invalid keyword argument for this function" + ] + } + ], + "source": [ + "x.reshape((2,8),refcheck=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1차원 배열을 2차원 배열로 변경(1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- Meshgrid 함수를 이용하면 두 개의 배열을 가지고 확장된 두 개의 다른 배열을 만듭니다." + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2])" + ] + }, + "execution_count": 96, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.arange(4)" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3])" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [], + "source": [ + "x_, y_ = np.meshgrid(x,y)\n", + "\n", + "# x, y에 포함된 좌표를 바탕으로 좌표를 반환.\n", + "# x_는 각 행이 x의 복사본인 행렬\n", + "# y_는 각 열이 y의 복사본인 행렬" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2],\n", + " [0, 1, 2],\n", + " [0, 1, 2],\n", + " [0, 1, 2]])" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x_" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0],\n", + " [1, 1, 1],\n", + " [2, 2, 2],\n", + " [3, 3, 3]])" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [], + "source": [ + "x__, y__ = np.meshgrid(y,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2, 3],\n", + " [0, 1, 2, 3],\n", + " [0, 1, 2, 3]])" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x__" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0, 0],\n", + " [1, 1, 1, 1],\n", + " [2, 2, 2, 2]])" + ] + }, + "execution_count": 104, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y__" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [], + "source": [ + "x_1, x_2 = np.meshgrid(x,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2],\n", + " [0, 1, 2],\n", + " [0, 1, 2]])" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x_1" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0],\n", + " [1, 1, 1],\n", + " [2, 2, 2]])" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x_2" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [], + "source": [ + "x_1 = x.reshape(1,-1)" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2]])" + ] + }, + "execution_count": 109, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x_1" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [], + "source": [ + "x_2 = np.concatenate([x_1,x_1])" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2],\n", + " [0, 1, 2]])" + ] + }, + "execution_count": 112, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x_2" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": {}, + "outputs": [], + "source": [ + "x_3 = np.concatenate([x_1,x_2],axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2],\n", + " [0, 1, 2],\n", + " [0, 1, 2]])" + ] + }, + "execution_count": 124, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x_3" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": {}, + "outputs": [], + "source": [ + "y_1 = y.reshape(-1,1)" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0],\n", + " [1],\n", + " [2],\n", + " [3]])" + ] + }, + "execution_count": 117, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_1" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0],\n", + " [1, 1],\n", + " [2, 2],\n", + " [3, 3]])" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.concatenate([y_1,y_1],axis=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1차원 배열을 2차원 배열로 변경 (2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- mgrid 함수에 인자로 슬라이스를 전달하면 두 개의 배열을 반환합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 125, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 20])" + ] + }, + "execution_count": 125, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.arange(10,30,10)" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4])" + ] + }, + "execution_count": 126, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.arange(1,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[array([[10, 10, 10, 10],\n", + " [20, 20, 20, 20]]),\n", + " array([[1, 2, 3, 4],\n", + " [1, 2, 3, 4]])]" + ] + }, + "execution_count": 127, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.broadcast_arrays(np.arange(10,30,10).reshape(2,1),np.arange(1,5).reshape(1,4)) ##########broadcast" + ] + }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[array([[1, 2, 3, 4],\n", + " [1, 2, 3, 4]]),\n", + " array([[10, 10, 10, 10],\n", + " [20, 20, 20, 20]])]" + ] + }, + "execution_count": 130, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.broadcast_arrays(np.arange(1,5).reshape(1,4),np.arange(10,30,10).reshape(2,1))" + ] + }, + { + "cell_type": "code", + "execution_count": 131, + "metadata": {}, + "outputs": [], + "source": [ + "a,b = np.mgrid[10:30:10, 1:5]" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[10, 10, 10, 10],\n", + " [20, 20, 20, 20]])" + ] + }, + "execution_count": 132, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3, 4],\n", + " [1, 2, 3, 4]])" + ] + }, + "execution_count": 133, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [], + "source": [ + "a,b,c = np.mgrid[10:30:10, 1:5, 2:7]" + ] + }, + { + "cell_type": "code", + "execution_count": 139, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[10, 10, 10, 10, 10],\n", + " [10, 10, 10, 10, 10],\n", + " [10, 10, 10, 10, 10],\n", + " [10, 10, 10, 10, 10]],\n", + "\n", + " [[20, 20, 20, 20, 20],\n", + " [20, 20, 20, 20, 20],\n", + " [20, 20, 20, 20, 20],\n", + " [20, 20, 20, 20, 20]]])" + ] + }, + "execution_count": 139, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[1, 1, 1, 1, 1],\n", + " [2, 2, 2, 2, 2],\n", + " [3, 3, 3, 3, 3],\n", + " [4, 4, 4, 4, 4]],\n", + "\n", + " [[1, 1, 1, 1, 1],\n", + " [2, 2, 2, 2, 2],\n", + " [3, 3, 3, 3, 3],\n", + " [4, 4, 4, 4, 4]]])" + ] + }, + "execution_count": 140, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[2, 3, 4, 5, 6],\n", + " [2, 3, 4, 5, 6],\n", + " [2, 3, 4, 5, 6],\n", + " [2, 3, 4, 5, 6]],\n", + "\n", + " [[2, 3, 4, 5, 6],\n", + " [2, 3, 4, 5, 6],\n", + " [2, 3, 4, 5, 6],\n", + " [2, 3, 4, 5, 6]]])" + ] + }, + "execution_count": 141, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1차원 배열을 2차원 배열로 변경 (3)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- ogird함수에 인자로 슬라이스 전달하면 2차원 두 개의 배열을 반환합니다. 첫번째는 열벡터이고 두번째는 행벡터입니다. 이 두개를 브로드캐스탱해서 동일한 형상의 배열을 만들 수 있습니다. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "c, d = np.ogrid[10:30:10,1:5]" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[10],\n", + " [20]])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3, 4]])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "e,f = np.broadcast_arrays(c,d)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[10, 10, 10, 10],\n", + " [20, 20, 20, 20]])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3, 4],\n", + " [1, 2, 3, 4]])" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 축이 1인 차원을 줄이기" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 다차원 배열에서 축의 차원이 1인 것을 없애서 차원을 축소할 필요가 있습니다. 이때 축소하는 함수 squeeze에 배열을 전달해서 사용합니다. " + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([[[0],[1],[2]]])\n", + "y = np.array([[0,1,2]])" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[[0],\n", + " [1],\n", + " [2]]]),\n", + " array([[0, 1, 2]]))" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x, y" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((1, 3, 1), (1, 3))" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x.shape, y.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "x1 = np.squeeze(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [], + "source": [ + "x2 = np.squeeze(x, axis = 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "cannot select an axis to squeeze out which has size not equal to one", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mx3\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m<__array_function__ internals>\u001b[0m in \u001b[0;36msqueeze\u001b[0;34m(*args, **kwargs)\u001b[0m\n", + "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/numpy/core/fromnumeric.py\u001b[0m in \u001b[0;36msqueeze\u001b[0;34m(a, axis)\u001b[0m\n\u001b[1;32m 1481\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1482\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1483\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1484\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1485\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: cannot select an axis to squeeze out which has size not equal to one" + ] + } + ], + "source": [ + "x3 = np.squeeze(x, axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "x4 = np.squeeze(x, axis = 2)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[[0],\n", + " [1],\n", + " [2]]]),\n", + " array([[0, 1, 2]]),\n", + " array([0, 1, 2]),\n", + " array([[0],\n", + " [1],\n", + " [2]]),\n", + " array([[0, 1, 2]]))" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x, y, x1, x2, x4" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((3,), (1, 3), (3,), (3, 1), (1, 3))" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x1.shape, y.shape, x1.shape, x2.shape, x4.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 내부 원소를 가지고 배열 확대하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 원소를 반복해서 증가하는 repeat 함수, 주어진 배열의 크기를 확대하는 tile 함수등을 알아봅시다." + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.linspace(1,5,5, dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5], dtype=int32)" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 2, 2, 3, 3, 4, 4, 5, 5], dtype=int32)" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.repeat(a,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 5], dtype=int32)" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.repeat(a,a)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.arange(4)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3])" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "e = np.arange(4).reshape(2,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1],\n", + " [2, 3]])" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 0, 1],\n", + " [2, 3, 2, 3]])" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.tile(e,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 0, 1, 0, 1],\n", + " [2, 3, 2, 3, 2, 3]])" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.tile(e,3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 배열을 결합하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 동일한 형상을 가진 두 개의 배열을 만들고 concatenate 함수로 수직과 수평으로 결합을 할 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.linspace(1,6,6, dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6], dtype=int32)" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.linspace(1,6,6, dtype=np.int32).reshape(2,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]], dtype=int32)" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.linspace(7,13,6, dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 7, 8, 9, 10, 11, 13], dtype=int32)" + ] + }, + "execution_count": 85, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.linspace(7,13,6, dtype = np.int32).reshape(2,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 7, 8, 9],\n", + " [10, 11, 13]], dtype=int32)" + ] + }, + "execution_count": 87, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__열의 크기가 동일할 때 수직 결합__" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 2, 3],\n", + " [ 4, 5, 6],\n", + " [ 7, 8, 9],\n", + " [10, 11, 13]], dtype=int32)" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.concatenate([a,b])" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 2, 3],\n", + " [ 4, 5, 6],\n", + " [ 7, 8, 9],\n", + " [10, 11, 13],\n", + " [ 1, 2, 3],\n", + " [ 4, 5, 6],\n", + " [ 7, 8, 9],\n", + " [10, 11, 13],\n", + " [ 7, 8, 9],\n", + " [10, 11, 13]], dtype=int32)" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.concatenate([a,b,a,b,b])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__행의 크기가 동일할 때 수평 결합__" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 2, 3, 7, 8, 9, 1, 2, 3, 7, 8, 9, 7, 8, 9],\n", + " [ 4, 5, 6, 10, 11, 13, 4, 5, 6, 10, 11, 13, 10, 11, 13]],\n", + " dtype=int32)" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.concatenate([a,b,a,b,b], axis = 1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__배열을 쌓기__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 두 개의 ~~일차원~~배열을 만들고 stack, vstack, hstack 함수로 배열을 수직과 수평으로 쌓을 수가 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([1,2,3])" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.array([4,5,6])" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.stack([x,y])" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.stack([x,y], axis = 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 4],\n", + " [2, 5],\n", + " [3, 6]])" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.stack([x,y], axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [], + "source": [ + "a = 0" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.vstack([x,y])" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6],\n", + " [1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 109, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.vstack([a,a])" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 4],\n", + " [2, 5],\n", + " [3, 6]])" + ] + }, + "execution_count": 110, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.stack([x,y], axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.hstack([x,y])" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6])" + ] + }, + "execution_count": 112, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([[1,2,3,4,5,6]]).reshape(2,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 122, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.array([[7,8,9,10,11,12]]).reshape(2,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.hstack([x,y])" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 2, 3, 7, 8, 9],\n", + " [ 4, 5, 6, 10, 11, 12]])" + ] + }, + "execution_count": 121, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]], dtype=int32)" + ] + }, + "execution_count": 105, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 배열을 분리하기 (np.split)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 선형대수에서 큰 배열을 작은 배열로 분리해서 계산을 합니다. 넘파이 모듈의 다차원 배열도 하나의 배열을 분리해서 처리할 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 151, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.linspace(1,8,8, dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 152, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6, 7, 8], dtype=int32)" + ] + }, + "execution_count": 152, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 153, + "metadata": {}, + "outputs": [], + "source": [ + "a = a.reshape(2,4)" + ] + }, + { + "cell_type": "code", + "execution_count": 154, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3, 4],\n", + " [5, 6, 7, 8]], dtype=int32)" + ] + }, + "execution_count": 154, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.linspace(9,16,8, dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 156, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 9, 10, 11, 12, 13, 14, 15, 16], dtype=int32)" + ] + }, + "execution_count": 156, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 157, + "metadata": {}, + "outputs": [], + "source": [ + "b = b.reshape(2,4)" + ] + }, + { + "cell_type": "code", + "execution_count": 158, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 9, 10, 11, 12],\n", + " [13, 14, 15, 16]], dtype=int32)" + ] + }, + "execution_count": 158, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 159, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.vstack([a,b])" + ] + }, + { + "cell_type": "code", + "execution_count": 160, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 2, 3, 4],\n", + " [ 5, 6, 7, 8],\n", + " [ 9, 10, 11, 12],\n", + " [13, 14, 15, 16]], dtype=int32)" + ] + }, + "execution_count": 160, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 179, + "metadata": {}, + "outputs": [], + "source": [ + "x,y = np.split(c, [2]) # ( , ) <---분리하고자 하는 위치 : 2번째 column 앞\n", + "# https://numpy.org/doc/stable/reference/generated/numpy.split.html" + ] + }, + { + "cell_type": "code", + "execution_count": 180, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3, 4],\n", + " [5, 6, 7, 8]], dtype=int32)" + ] + }, + "execution_count": 180, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 9, 10, 11, 12],\n", + " [13, 14, 15, 16]], dtype=int32)" + ] + }, + "execution_count": 181, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 배열 쌓기 객체" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 행과 열을 쌓을 때 r_, c_를 사용할 수도 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.arange(6).reshape(2,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 183, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 2],\n", + " [3, 4, 5]])" + ] + }, + "execution_count": 183, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 184, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.random.randn(2,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 185, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.08703845, -1.34217544, 0.33380794],\n", + " [ 0.47838035, 0.6434542 , 0.16241262]])" + ] + }, + "execution_count": 185, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 186, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0. , 1. , 2. ],\n", + " [ 3. , 4. , 5. ],\n", + " [-0.08703845, -1.34217544, 0.33380794],\n", + " [ 0.47838035, 0.6434542 , 0.16241262]])" + ] + }, + "execution_count": 186, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.r_[a,c]" + ] + }, + { + "cell_type": "code", + "execution_count": 187, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0. , 1. , 2. , -0.08703845, -1.34217544,\n", + " 0.33380794],\n", + " [ 3. , 4. , 5. , 0.47838035, 0.6434542 ,\n", + " 0.16241262]])" + ] + }, + "execution_count": 187, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.c_[a,c]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 내부 조작 함수" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 정렬 함수 : sort" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 다차원 배열도 내부의 원소를 기준으로 처리를 할 때는 순서대로 정렬을 해서 사용할 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 248, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.linspace(1,9,9, dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 249, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)" + ] + }, + "execution_count": 249, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 250, + "metadata": {}, + "outputs": [], + "source": [ + "np.random.shuffle(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 251, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([8, 6, 1, 9, 5, 2, 4, 3, 7], dtype=int32)" + ] + }, + "execution_count": 251, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 232, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.sort(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 233, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)" + ] + }, + "execution_count": 233, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 234, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([4, 2, 8, 3, 7, 1, 5, 9, 6], dtype=int32)" + ] + }, + "execution_count": 234, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 235, + "metadata": {}, + "outputs": [], + "source": [ + "a.sort()" + ] + }, + { + "cell_type": "code", + "execution_count": 236, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32)" + ] + }, + "execution_count": 236, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 252, + "metadata": {}, + "outputs": [], + "source": [ + "b1 = a.reshape(3,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 253, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[8, 6, 1],\n", + " [9, 5, 2],\n", + " [4, 3, 7]], dtype=int32)" + ] + }, + "execution_count": 253, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b1" + ] + }, + { + "cell_type": "code", + "execution_count": 256, + "metadata": {}, + "outputs": [], + "source": [ + "np.random.shuffle(b1)" + ] + }, + { + "cell_type": "code", + "execution_count": 257, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[4, 3, 7],\n", + " [9, 5, 2],\n", + " [8, 6, 1]], dtype=int32)" + ] + }, + "execution_count": 257, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b1" + ] + }, + { + "cell_type": "code", + "execution_count": 260, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 4, 7],\n", + " [2, 5, 9],\n", + " [1, 6, 8]], dtype=int32)" + ] + }, + "execution_count": 260, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sort(b1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 정렬함수 : argsort" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 값을 정렬하지 않고 인덱스 정렬은 arg 함수를 사용합니다. 기존 원본 배열의 인덱스를 가지고 배열한 정렬을 반환합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 261, + "metadata": {}, + "outputs": [], + "source": [ + "bb = np.linspace(1,6,6, dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 262, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6], dtype=int32)" + ] + }, + "execution_count": 262, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bb" + ] + }, + { + "cell_type": "code", + "execution_count": 271, + "metadata": {}, + "outputs": [], + "source": [ + "np.random.shuffle(bb)" + ] + }, + { + "cell_type": "code", + "execution_count": 272, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([5, 1, 6, 3, 2, 4], dtype=int32)" + ] + }, + "execution_count": 272, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bb" + ] + }, + { + "cell_type": "code", + "execution_count": 273, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.argsort(bb)" + ] + }, + { + "cell_type": "code", + "execution_count": 280, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 4, 3, 5, 0, 2])" + ] + }, + "execution_count": 280, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 281, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([5, 1, 6, 3, 2, 4], dtype=int32)" + ] + }, + "execution_count": 281, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bb" + ] + }, + { + "cell_type": "code", + "execution_count": 275, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 275, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c.dtype #question np.argsort 하고 data type이 바뀌는 이유?" + ] + }, + { + "cell_type": "code", + "execution_count": 279, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(1, 2, 3, 4, 5, 6)" + ] + }, + "execution_count": 279, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bb[c[0]], bb[c[1]], bb[c[2]], bb[c[3]], bb[c[4]], bb[c[5]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 배열 클래스 변경" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 넘파이 모듈은 다차원 배열인 nmdarray와 행렬을 처리하는 matrix 클래스가 있습니다. 이들은 서로 자료형을 교환할 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 282, + "metadata": {}, + "outputs": [], + "source": [ + "m = np.matrix([1,2,3,4])" + ] + }, + { + "cell_type": "code", + "execution_count": 283, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[1, 2, 3, 4]])" + ] + }, + "execution_count": 283, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m" + ] + }, + { + "cell_type": "code", + "execution_count": 284, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.matrix" + ] + }, + "execution_count": 284, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(m)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__자료형 변경하기__" + ] + }, + { + "cell_type": "code", + "execution_count": 285, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.asarray(m)" + ] + }, + { + "cell_type": "code", + "execution_count": 286, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3, 4]])" + ] + }, + "execution_count": 286, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 287, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ndarray" + ] + }, + "execution_count": 287, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 288, + "metadata": {}, + "outputs": [], + "source": [ + "m1 = np.asmatrix(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 289, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[1, 2, 3, 4]])" + ] + }, + "execution_count": 289, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m1" + ] + }, + { + "cell_type": "code", + "execution_count": 290, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.matrix" + ] + }, + "execution_count": 290, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(m1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 배열의 값 변경" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 다차원 배열을 ones 함수로 만들면 모든 원소의 값이 1 입니다.
모든 원소를 다른 값으로 변경하려면 fill 메소드를 사용해서 변경합니다.
또한 full 함수는 새로 만드는 배열의 모든 값을 동일하게 처리합니다." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 291, + "metadata": {}, + "outputs": [], + "source": [ + "o = np.ones(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 292, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])" + ] + }, + "execution_count": 292, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "o" + ] + }, + { + "cell_type": "code", + "execution_count": 294, + "metadata": {}, + "outputs": [], + "source": [ + "o.fill(321)" + ] + }, + { + "cell_type": "code", + "execution_count": 295, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([321., 321., 321., 321., 321., 321., 321., 321., 321., 321.])" + ] + }, + "execution_count": 295, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "o" + ] + }, + { + "cell_type": "code", + "execution_count": 298, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.full(o.shape, 99)" + ] + }, + { + "cell_type": "code", + "execution_count": 299, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([99, 99, 99, 99, 99, 99, 99, 99, 99, 99])" + ] + }, + "execution_count": 299, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 300, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.full(o.shape, 99.)" + ] + }, + { + "cell_type": "code", + "execution_count": 301, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([99., 99., 99., 99., 99., 99., 99., 99., 99., 99.])" + ] + }, + "execution_count": 301, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 위치변경 및 이동" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 배열의 좌우, 상하의 위치 및 각도에 따라 이동을 시킬 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 302, + "metadata": {}, + "outputs": [], + "source": [ + "array = np.arange(4).reshape((2,2))" + ] + }, + { + "cell_type": "code", + "execution_count": 303, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1],\n", + " [2, 3]])" + ] + }, + "execution_count": 303, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "array" + ] + }, + { + "cell_type": "code", + "execution_count": 304, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 0],\n", + " [3, 2]])" + ] + }, + "execution_count": 304, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.fliplr(array)" + ] + }, + { + "cell_type": "code", + "execution_count": 305, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2, 3],\n", + " [0, 1]])" + ] + }, + "execution_count": 305, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.flipud(array)" + ] + }, + { + "cell_type": "code", + "execution_count": 308, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 2],\n", + " [1, 0]])" + ] + }, + "execution_count": 308, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.fliplr(np.flipud(array))" + ] + }, + { + "cell_type": "code", + "execution_count": 309, + "metadata": {}, + "outputs": [], + "source": [ + "m = np.array([[1,2],[3,4]],int)" + ] + }, + { + "cell_type": "code", + "execution_count": 310, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2],\n", + " [3, 4]])" + ] + }, + "execution_count": 310, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m" + ] + }, + { + "cell_type": "code", + "execution_count": 315, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[2, 4],\n", + " [1, 3]]),\n", + " array([[4, 3],\n", + " [2, 1]]),\n", + " array([[3, 1],\n", + " [4, 2]]),\n", + " array([[1, 2],\n", + " [3, 4]]))" + ] + }, + "execution_count": 315, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.rot90(m), np.rot90(m,2), np.rot90(m,3), np.rot90(m,4)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 배열 내의 원소 점검하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 원소의 값에 대한 체크를 할 수 있습니다. 또한 무한대나 nan도 점검할 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 316, + "metadata": {}, + "outputs": [], + "source": [ + "m = np.random.randn(3,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 317, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.89233249, -0.17760658, 1.8349804 , -0.06946602, 0.95761699],\n", + " [-2.02211281, 0.52930752, 0.90502321, 0.17716964, 1.04976568],\n", + " [ 0.65836556, 0.78887321, -0.18504683, -0.76807261, 2.63346282]])" + ] + }, + "execution_count": 317, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m" + ] + }, + { + "cell_type": "code", + "execution_count": 318, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[ True, True, True, True, True],\n", + " [ True, True, True, True, True],\n", + " [ True, True, True, True, True]]),\n", + " array([[False, False, False, False, False],\n", + " [False, False, False, False, False],\n", + " [False, False, False, False, False]]),\n", + " array([[False, False, False, False, False],\n", + " [False, False, False, False, False],\n", + " [False, False, False, False, False]]))" + ] + }, + "execution_count": 318, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.isreal(m), np.isinf(m), np.isnan(m)" + ] + }, + { + "cell_type": "code", + "execution_count": 341, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":1: RuntimeWarning: invalid value encountered in log\n", + " np.isnan(1), np.isnan(np.log(-7))\n" + ] + }, + { + "data": { + "text/plain": [ + "(False, True)" + ] + }, + "execution_count": 341, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.isnan(1), np.isnan(np.log(-7))\n", + "# http://blog.daum.net/swrush/342" + ] + }, + { + "cell_type": "code", + "execution_count": 342, + "metadata": {}, + "outputs": [], + "source": [ + "y = [3.7, 6.2, 8.3, -7.6, 5.5]" + ] + }, + { + "cell_type": "code", + "execution_count": 343, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":1: RuntimeWarning: invalid value encountered in sqrt\n", + " result = np.sqrt(y)\n" + ] + } + ], + "source": [ + "result = np.sqrt(y)" + ] + }, + { + "cell_type": "code", + "execution_count": 344, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.92353841, 2.48997992, 2.88097206, nan, 2.34520788])" + ] + }, + "execution_count": 344, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 배열의 padding 처리" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### padding" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 기존 배열 밖에 다른 원소를 더 붙여서 배열을 확장하는 방식입니다." + ] + }, + { + "cell_type": "code", + "execution_count": 345, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(1,5).reshape(2,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 346, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2],\n", + " [3, 4]])" + ] + }, + "execution_count": 346, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 347, + "metadata": {}, + "outputs": [], + "source": [ + "z = np.zeros((3,3))" + ] + }, + { + "cell_type": "code", + "execution_count": 348, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0., 0., 0.],\n", + " [0., 0., 0.],\n", + " [0., 0., 0.]])" + ] + }, + "execution_count": 348, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "z" + ] + }, + { + "cell_type": "code", + "execution_count": 349, + "metadata": {}, + "outputs": [], + "source": [ + "z[:2, :2] = x" + ] + }, + { + "cell_type": "code", + "execution_count": 350, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 2., 0.],\n", + " [3., 4., 0.],\n", + " [0., 0., 0.]])" + ] + }, + "execution_count": 350, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "z" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### padding 함수 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- 함수 pad를 가지고 배열에 padding을 처리합니다. 상수값으로 padding을 할 때는 constant 문자열을 인자로 전달합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 355, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2],\n", + " [3, 4]])" + ] + }, + "execution_count": 355, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,0,\"constant\")" + ] + }, + { + "cell_type": "code", + "execution_count": 356, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0, 0],\n", + " [0, 1, 2, 0],\n", + " [0, 3, 4, 0],\n", + " [0, 0, 0, 0]])" + ] + }, + "execution_count": 356, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,1,\"constant\")" + ] + }, + { + "cell_type": "code", + "execution_count": 352, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 0],\n", + " [3, 4, 0],\n", + " [0, 0, 0]])" + ] + }, + "execution_count": 352, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(0,1),\"constant\")" + ] + }, + { + "cell_type": "code", + "execution_count": 353, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0],\n", + " [0, 1, 2],\n", + " [0, 3, 4]])" + ] + }, + "execution_count": 353, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(1,0),\"constant\")" + ] + }, + { + "cell_type": "code", + "execution_count": 354, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0, 0],\n", + " [0, 1, 2, 0],\n", + " [0, 3, 4, 0],\n", + " [0, 0, 0, 0]])" + ] + }, + "execution_count": 354, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(1,1),\"constant\")" + ] + }, + { + "cell_type": "code", + "execution_count": 357, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 2, 0, 0, 0],\n", + " [0, 0, 0, 3, 4, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0]])" + ] + }, + "execution_count": 357, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(3,3),\"constant\")" + ] + }, + { + "cell_type": "code", + "execution_count": 358, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(1,5).reshape(2,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 359, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2],\n", + " [3, 4]])" + ] + }, + "execution_count": 359, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 360, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 2],\n", + " [3, 4, 4],\n", + " [3, 4, 4]])" + ] + }, + "execution_count": 360, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(0,1),'edge')" + ] + }, + { + "cell_type": "code", + "execution_count": 361, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 1, 2],\n", + " [1, 1, 2],\n", + " [3, 3, 4]])" + ] + }, + "execution_count": 361, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(1,0),\"edge\")" + ] + }, + { + "cell_type": "code", + "execution_count": 362, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 1, 2, 2],\n", + " [1, 1, 2, 2],\n", + " [3, 3, 4, 4],\n", + " [3, 3, 4, 4]])" + ] + }, + "execution_count": 362, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(1,1),\"edge\")" + ] + }, + { + "cell_type": "code", + "execution_count": 363, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 1, 1, 1, 2, 2, 2, 2],\n", + " [1, 1, 1, 1, 2, 2, 2, 2],\n", + " [1, 1, 1, 1, 2, 2, 2, 2],\n", + " [1, 1, 1, 1, 2, 2, 2, 2],\n", + " [3, 3, 3, 3, 4, 4, 4, 4],\n", + " [3, 3, 3, 3, 4, 4, 4, 4],\n", + " [3, 3, 3, 3, 4, 4, 4, 4],\n", + " [3, 3, 3, 3, 4, 4, 4, 4]])" + ] + }, + "execution_count": 363, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(3,3),'edge')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### padding 함수 3" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- padding 되는 값을 최대값, 최소값, 평균, 중앙값 등으로 지정할 수 있습니다." + ] + }, + { + "cell_type": "code", + "execution_count": 364, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[4, 4, 4, 3, 4, 4, 4, 4],\n", + " [4, 4, 4, 3, 4, 4, 4, 4],\n", + " [4, 4, 4, 3, 4, 4, 4, 4],\n", + " [2, 2, 2, 1, 2, 2, 2, 2],\n", + " [4, 4, 4, 3, 4, 4, 4, 4],\n", + " [4, 4, 4, 3, 4, 4, 4, 4],\n", + " [4, 4, 4, 3, 4, 4, 4, 4],\n", + " [4, 4, 4, 3, 4, 4, 4, 4]])" + ] + }, + "execution_count": 364, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(3,3), \"maximum\")" + ] + }, + { + "cell_type": "code", + "execution_count": 365, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2, 2, 3, 2],\n", + " [2, 1, 2, 2],\n", + " [4, 3, 4, 4],\n", + " [2, 2, 3, 2]])" + ] + }, + "execution_count": 365, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(1,1), \"mean\")" + ] + }, + { + "cell_type": "code", + "execution_count": 366, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 1, 2, 2, 2, 2],\n", + " [4, 4, 4, 3, 4, 4, 4, 4],\n", + " [2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 2, 3, 2, 2, 2]])" + ] + }, + "execution_count": 366, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(3,3), \"mean\")" + ] + }, + { + "cell_type": "code", + "execution_count": 367, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 1, 2, 2, 2, 2],\n", + " [4, 4, 4, 3, 4, 4, 4, 4],\n", + " [2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 2, 3, 2, 2, 2],\n", + " [2, 2, 2, 2, 3, 2, 2, 2]])" + ] + }, + "execution_count": 367, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.pad(x,(3,3), \"median\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git "a/05\354\236\245/5\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" "b/05\354\236\245/5\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" new file mode 100644 index 0000000..ed395e6 --- /dev/null +++ "b/05\354\236\245/5\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" @@ -0,0 +1,25 @@ +Q3) 입력값 : b = np.arange(4) + 사용명령어 : np.resize(b,(4,4)) + +어떻게 하면 입력받은 b = np.arange(4)로부터 기대출력값을 출력? + +> ([[0,1,2,3], + [0,1,2,3], + [0,1,2,3], + [0,1,2,3]]) + +기대 출력값 : + +> ([[0,1,2,3], + [0,0,0,0], + [0,0,0,0], + [0,0,0,0]]) + + +A3) +b.resize(4, 4) + + +Q4) np.argsort 실행 후 data type이 바뀌는 이유? + +A4) 문제가 좀 이상합니다. np.argsort를 한다고 하더라도 원본 데이터의 타입이 변하지는 않습니다. 다만, argsort가 정렬된 행렬의 index값을 나타낼뿐입니다. diff --git "a/05\354\236\245/[\353\204\230\355\214\214\354\235\264]05\354\236\245.pptx" "b/05\354\236\245/[\353\204\230\355\214\214\354\235\264]05\354\236\245.pptx" new file mode 100644 index 0000000..6f0aadc Binary files /dev/null and "b/05\354\236\245/[\353\204\230\355\214\214\354\235\264]05\354\236\245.pptx" differ diff --git "a/05\354\236\245/chapter 5 quiz \352\271\200\353\257\274\352\267\234" "b/05\354\236\245/chapter 5 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..bc8e5b5 --- /dev/null +++ "b/05\354\236\245/chapter 5 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,12 @@ +3. +b = np.arange(4) +b.resize(4, 4) +b +array([[0, 1, 2, 3], + [0, 0, 0, 0], + [0, 0, 0, 0], + [0, 0, 0, 0]]) + +4. +내부 정렬을 하기 때문에 메모리 효율이 훨씬 높을 수 있기 때문인거 같습니다. +argsort를 사용하면 (원본, 정렬할 인덱스, 반환된 인덱스) 최소 3배의 메모리가 필요하여 변경된다고 생각합니다. diff --git "a/06\354\236\245/.ipynb_checkpoints/C6-7_summary-Copy1-checkpoint.ipynb" "b/06\354\236\245/.ipynb_checkpoints/C6-7_summary-Copy1-checkpoint.ipynb" new file mode 100644 index 0000000..915ec95 --- /dev/null +++ "b/06\354\236\245/.ipynb_checkpoints/C6-7_summary-Copy1-checkpoint.ipynb" @@ -0,0 +1,3098 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Chapter 6. 넘파이 모듈의 자료형 이해하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 01. dtype으로 자료 객체 생성하기" + ] + }, + { + "cell_type": "code", + "execution_count": 468, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.19.2'" + ] + }, + "execution_count": 468, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "np.__version__" + ] + }, + { + "cell_type": "code", + "execution_count": 469, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.dtype" + ] + }, + "execution_count": 469, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 470, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,2,3,4,5], dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 471, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int32')" + ] + }, + "execution_count": 471, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 472, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ndarray" + ] + }, + "execution_count": 472, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(a)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 474, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "int" + ] + }, + "execution_count": 474, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b = 10\n", + "type(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 504, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 504, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.array([10])\n", + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 505, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,2,3,4,5], dtype='i8')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ℹ️ [참고. numpy dtypes](https://numpy.org/doc/stable/reference/arrays.dtypes.html)" + ] + }, + { + "cell_type": "code", + "execution_count": 506, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 506, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 480, + "metadata": {}, + "outputs": [], + "source": [ + "py_number = 12345\n", + "#np_number = np.int64(12345)\n", + "np_number = np.array([12345], dtype='int64')" + ] + }, + { + "cell_type": "code", + "execution_count": 481, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "int64\n" + ] + } + ], + "source": [ + "print(type(py_number))\n", + "print(np_number.dtype)" + ] + }, + { + "cell_type": "code", + "execution_count": 482, + "metadata": { + "collapsed": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__bool__',\n", + " '__ceil__',\n", + " '__class__',\n", + " '__delattr__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floor__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getnewargs__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__index__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__le__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__round__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__trunc__',\n", + " '__xor__',\n", + " 'as_integer_ratio',\n", + " 'bit_length',\n", + " 'conjugate',\n", + " 'denominator',\n", + " 'from_bytes',\n", + " 'imag',\n", + " 'numerator',\n", + " 'real',\n", + " 'to_bytes']" + ] + }, + "execution_count": 482, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(py_number)" + ] + }, + { + "cell_type": "code", + "execution_count": 465, + "metadata": { + "collapsed": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['T',\n", + " '__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__array__',\n", + " '__array_finalize__',\n", + " '__array_function__',\n", + " '__array_interface__',\n", + " '__array_prepare__',\n", + " '__array_priority__',\n", + " '__array_struct__',\n", + " '__array_ufunc__',\n", + " '__array_wrap__',\n", + " '__bool__',\n", + " '__class__',\n", + " '__complex__',\n", + " '__contains__',\n", + " '__copy__',\n", + " '__deepcopy__',\n", + " '__delattr__',\n", + " '__delitem__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getitem__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__iadd__',\n", + " '__iand__',\n", + " '__ifloordiv__',\n", + " '__ilshift__',\n", + " '__imatmul__',\n", + " '__imod__',\n", + " '__imul__',\n", + " '__index__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__ior__',\n", + " '__ipow__',\n", + " '__irshift__',\n", + " '__isub__',\n", + " '__iter__',\n", + " '__itruediv__',\n", + " '__ixor__',\n", + " '__le__',\n", + " '__len__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__matmul__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmatmul__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__setitem__',\n", + " '__setstate__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__xor__',\n", + " 'all',\n", + " 'any',\n", + " 'argmax',\n", + " 'argmin',\n", + " 'argpartition',\n", + " 'argsort',\n", + " 'astype',\n", + " 'base',\n", + " 'byteswap',\n", + " 'choose',\n", + " 'clip',\n", + " 'compress',\n", + " 'conj',\n", + " 'conjugate',\n", + " 'copy',\n", + " 'ctypes',\n", + " 'cumprod',\n", + " 'cumsum',\n", + " 'data',\n", + " 'diagonal',\n", + " 'dot',\n", + " 'dtype',\n", + " 'dump',\n", + " 'dumps',\n", + " 'fill',\n", + " 'flags',\n", + " 'flat',\n", + " 'flatten',\n", + " 'getfield',\n", + " 'imag',\n", + " 'item',\n", + " 'itemset',\n", + " 'itemsize',\n", + " 'max',\n", + " 'mean',\n", + " 'min',\n", + " 'nbytes',\n", + " 'ndim',\n", + " 'newbyteorder',\n", + " 'nonzero',\n", + " 'partition',\n", + " 'prod',\n", + " 'ptp',\n", + " 'put',\n", + " 'ravel',\n", + " 'real',\n", + " 'repeat',\n", + " 'reshape',\n", + " 'resize',\n", + " 'round',\n", + " 'searchsorted',\n", + " 'setfield',\n", + " 'setflags',\n", + " 'shape',\n", + " 'size',\n", + " 'sort',\n", + " 'squeeze',\n", + " 'std',\n", + " 'strides',\n", + " 'sum',\n", + " 'swapaxes',\n", + " 'take',\n", + " 'tobytes',\n", + " 'tofile',\n", + " 'tolist',\n", + " 'tostring',\n", + " 'trace',\n", + " 'transpose',\n", + " 'var',\n", + " 'view']" + ] + }, + "execution_count": 465, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(np_number)" + ] + }, + { + "cell_type": "code", + "execution_count": 483, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 483, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 489, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.99999999999998\n" + ] + } + ], + "source": [ + "py_result = 0\n", + "\n", + "for i in range(0, 100):\n", + " py_result += 0.1\n", + "\n", + "print(py_result)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ℹ️ [참고. 파이썬 부동 소수점 오차 해결](https://winterj.me/floating-point-in-python/)" + ] + }, + { + "cell_type": "code", + "execution_count": 490, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "float" + ] + }, + "execution_count": 490, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(py_result)" + ] + }, + { + "cell_type": "code", + "execution_count": 491, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[10.]\n" + ] + } + ], + "source": [ + "np_result = np.array([0], dtype='float64')\n", + "\n", + "for i in range(0, 100):\n", + " np_result += 0.1\n", + "\n", + "print(np_result)" + ] + }, + { + "cell_type": "code", + "execution_count": 492, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('float64')" + ] + }, + "execution_count": 492, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np_result.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([1,2,3,4,5], dtype=np.float32)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 2., 3., 4., 5.], dtype=float32)" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 515, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array(['ab', 'cd'], dtype=np.str)" + ] + }, + { + "cell_type": "code", + "execution_count": 516, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['ab', 'cd'], dtype=', , , , , , ]\n" + ] + } + ], + "source": [ + "print(np.float64.mro())" + ] + }, + { + "cell_type": "code", + "execution_count": 500, + "metadata": {}, + "outputs": [], + "source": [ + "import pprint" + ] + }, + { + "cell_type": "code", + "execution_count": 501, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ]\n" + ] + } + ], + "source": [ + "pprint.pprint(np.float64.mro())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 02. 날짜 자료형" + ] + }, + { + "cell_type": "code", + "execution_count": 521, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "# 넘파이는 np.datetime64와 timedelta64 두가지 모듈을 제공합니다. \n", + "\n", + "np.datetime64\n", + "print(np.datetime64)" + ] + }, + { + "cell_type": "code", + "execution_count": 524, + "metadata": { + "collapsed": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['T',\n", + " '__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__array__',\n", + " '__array_interface__',\n", + " '__array_priority__',\n", + " '__array_struct__',\n", + " '__array_wrap__',\n", + " '__bool__',\n", + " '__class__',\n", + " '__copy__',\n", + " '__deepcopy__',\n", + " '__delattr__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getitem__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__le__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__setstate__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__xor__',\n", + " 'all',\n", + " 'any',\n", + " 'argmax',\n", + " 'argmin',\n", + " 'argsort',\n", + " 'astype',\n", + " 'base',\n", + " 'byteswap',\n", + " 'choose',\n", + " 'clip',\n", + " 'compress',\n", + " 'conj',\n", + " 'conjugate',\n", + " 'copy',\n", + " 'cumprod',\n", + " 'cumsum',\n", + " 'data',\n", + " 'diagonal',\n", + " 'dtype',\n", + " 'dump',\n", + " 'dumps',\n", + " 'fill',\n", + " 'flags',\n", + " 'flat',\n", + " 'flatten',\n", + " 'getfield',\n", + " 'imag',\n", + " 'item',\n", + " 'itemset',\n", + " 'itemsize',\n", + " 'max',\n", + " 'mean',\n", + " 'min',\n", + " 'nbytes',\n", + " 'ndim',\n", + " 'newbyteorder',\n", + " 'nonzero',\n", + " 'prod',\n", + " 'ptp',\n", + " 'put',\n", + " 'ravel',\n", + " 'real',\n", + " 'repeat',\n", + " 'reshape',\n", + " 'resize',\n", + " 'round',\n", + " 'searchsorted',\n", + " 'setfield',\n", + " 'setflags',\n", + " 'shape',\n", + " 'size',\n", + " 'sort',\n", + " 'squeeze',\n", + " 'std',\n", + " 'strides',\n", + " 'sum',\n", + " 'swapaxes',\n", + " 'take',\n", + " 'tobytes',\n", + " 'tofile',\n", + " 'tolist',\n", + " 'tostring',\n", + " 'trace',\n", + " 'transpose',\n", + " 'var',\n", + " 'view']" + ] + }, + "execution_count": 524, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(np.datetime64)" + ] + }, + { + "cell_type": "code", + "execution_count": 526, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(numpy.datetime64('2018'), dtype('#### Quiz 1\n", + ">바이트 문자열이란?" + ] + }, + { + "cell_type": "code", + "execution_count": 601, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([['0', '1', '2', '3', '4'],\n", + " ['5', '6', '7', '8', '9']], dtype='" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 264, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n" + ] + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + " \n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 263, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n", + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAesAAAD8CAYAAABXV4w2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAN70lEQVR4nO3dX4ild33H8c+3uwbqnxoxq9jdiNuyGvfCFB2jlNrGSms2vVgELxLF0CAsoUa8TChUL7ypFwURo8sSluCNe1GDxhINhaIppLGZhZhkDZHpSpNthGxULERo2OTbixnLdDK788zkzOxv97xecGCe8/xm5suPYd95zpw8U90dAGBcv3OxBwAALkysAWBwYg0AgxNrABicWAPA4MQaAAa3Yayr6nhVPVdVT5znfFXVV6pqqaoeq6r3zn5MAJhfU66s70lywwXOH0pyYOVxJMnXX/1YAMBvbRjr7n4wyS8vsORwkm/0soeTXFlVb5vVgAAw73bP4GvsTfLMquMzK8/9fO3CqjqS5avvvO51r3vfNddcM4NvDwCXhpMnTz7f3Xs2+3mziHWt89y69zDt7mNJjiXJwsJCLy4uzuDbA8Cloar+cyufN4t3g59JcvWq431Jnp3B1wUAMptY35fklpV3hX8wya+7+xUvgQMAW7Phy+BV9c0k1ye5qqrOJPlCktckSXcfTXJ/khuTLCX5TZJbt2tYAJhHG8a6u2/e4Hwn+czMJgIA/h93MAOAwYk1AAxOrAFgcGINAIMTawAYnFgDwODEGgAGJ9YAMDixBoDBiTUADE6sAWBwYg0AgxNrABicWAPA4MQaAAYn1gAwOLEGgMGJNQAMTqwBYHBiDQCDE2sAGJxYA8DgxBoABifWADA4sQaAwYk1AAxOrAFgcGINAIMTawAYnFgDwODEGgAGJ9YAMDixBoDBiTUADE6sAWBwk2JdVTdU1VNVtVRVd65z/o1V9d2q+nFVnaqqW2c/KgDMpw1jXVW7ktyV5FCSg0lurqqDa5Z9JslPuvvaJNcn+YequmLGswLAXJpyZX1dkqXuPt3dLyY5keTwmjWd5A1VVUlen+SXSc7NdFIAmFNTYr03yTOrjs+sPLfaV5O8O8mzSR5P8rnufnntF6qqI1W1WFWLZ8+e3eLIADBfpsS61nmu1xx/NMmjSX4/yR8l+WpV/d4rPqn7WHcvdPfCnj17NjkqAMynKbE+k+TqVcf7snwFvdqtSe7tZUtJfpbkmtmMCADzbUqsH0lyoKr2r7xp7KYk961Z83SSjyRJVb01ybuSnJ7loAAwr3ZvtKC7z1XV7UkeSLIryfHuPlVVt62cP5rki0nuqarHs/yy+R3d/fw2zg0Ac2PDWCdJd9+f5P41zx1d9fGzSf5ytqMBAIk7mAHA8MQaAAYn1gAwOLEGgMGJNQAMTqwBYHBiDQCDE2sAGJxYA8DgxBoABifWADA4sQaAwYk1AAxOrAFgcGINAIMTawAYnFgDwODEGgAGJ9YAMDixBoDBiTUADE6sAWBwYg0AgxNrABicWAPA4MQaAAYn1gAwOLEGgMGJNQAMTqwBYHBiDQCDE2sAGJxYA8DgxBoABjcp1lV1Q1U9VVVLVXXnedZcX1WPVtWpqvrhbMcEgPm1e6MFVbUryV1J/iLJmSSPVNV93f2TVWuuTPK1JDd099NV9ZZtmhcA5s6UK+vrkix19+nufjHJiSSH16z5RJJ7u/vpJOnu52Y7JgDMrymx3pvkmVXHZ1aeW+2dSd5UVT+oqpNVdct6X6iqjlTVYlUtnj17dmsTA8CcmRLrWue5XnO8O8n7kvxVko8m+buqeucrPqn7WHcvdPfCnj17Nj0sAMyjDX9nneUr6atXHe9L8uw6a57v7heSvFBVDya5NslPZzIlAMyxKVfWjyQ5UFX7q+qKJDcluW/Nmu8k+VBV7a6q1yb5QJInZzsqAMynDa+su/tcVd2e5IEku5Ic7+5TVXXbyvmj3f1kVX0/yWNJXk5yd3c/sZ2DA8C8qO61v37eGQsLC724uHhRvjcAXAxVdbK7Fzb7ee5gBgCDE2sAGJxYA8DgxBoABifWADA4sQaAwYk1AAxOrAFgcGINAIMTawAYnFgDwODEGgAGJ9YAMDixBoDBiTUADE6sAWBwYg0AgxNrABicWAPA4MQaAAYn1gAwOLEGgMGJNQAMTqwBYHBiDQCDE2sAGJxYA8DgxBoABifWADA4sQaAwYk1AAxOrAFgcGINAIMTawAYnFgDwOAmxbqqbqiqp6pqqaruvMC691fVS1X18dmNCADzbcNYV9WuJHclOZTkYJKbq+rgedZ9KckDsx4SAObZlCvr65Isdffp7n4xyYkkh9dZ99kk30ry3AznA4C5NyXWe5M8s+r4zMpz/6eq9ib5WJKjF/pCVXWkqharavHs2bObnRUA5tKUWNc6z/Wa4y8nuaO7X7rQF+ruY9290N0Le/bsmTgiAMy33RPWnEly9arjfUmeXbNmIcmJqkqSq5LcWFXnuvvbsxgSAObZlFg/kuRAVe1P8l9JbkryidULunv/bz+uqnuS/JNQA8BsbBjr7j5XVbdn+V3eu5Ic7+5TVXXbyvkL/p4aAHh1plxZp7vvT3L/mufWjXR3//WrHwsA+C13MAOAwYk1AAxOrAFgcGINAIMTawAYnFgDwODEGgAGJ9YAMDixBoDBiTUADE6sAWBwYg0AgxNrABicWAPA4MQaAAYn1gAwOLEGgMGJNQAMTqwBYHBiDQCDE2sAGJxYA8DgxBoABifWADA4sQaAwYk1AAxOrAFgcGINAIMTawAYnFgDwODEGgAGJ9YAMDixBoDBiTUADG5SrKvqhqp6qqqWqurOdc5/sqoeW3k8VFXXzn5UAJhPG8a6qnYluSvJoSQHk9xcVQfXLPtZkj/r7vck+WKSY7MeFADm1ZQr6+uSLHX36e5+McmJJIdXL+juh7r7VyuHDyfZN9sxAWB+TYn13iTPrDo+s/Lc+Xw6yffWO1FVR6pqsaoWz549O31KAJhjU2Jd6zzX6y6s+nCWY33Heue7+1h3L3T3wp49e6ZPCQBzbPeENWeSXL3qeF+SZ9cuqqr3JLk7yaHu/sVsxgMAplxZP5LkQFXtr6orktyU5L7VC6rq7UnuTfKp7v7p7McEgPm14ZV1d5+rqtuTPJBkV5Lj3X2qqm5bOX80yeeTvDnJ16oqSc5198L2jQ0A86O61/3187ZbWFjoxcXFi/K9AeBiqKqTW7mYdQczABicWAPA4MQaAAYn1gAwOLEGgMGJNQAMTqwBYHBiDQCDE2sAGJxYA8DgxBoABifWADA4sQaAwYk1AAxOrAFgcGINAIMTawAYnFgDwODEGgAGJ9YAMDixBoDBiTUADE6sAWBwYg0AgxNrABicWAPA4MQaAAYn1gAwOLEGgMGJNQAMTqwBYHBiDQCDE2sAGJxYA8DgxBoABjcp1lV1Q1U9VVVLVXXnOuerqr6ycv6xqnrv7EcFgPm0YayraleSu5IcSnIwyc1VdXDNskNJDqw8jiT5+oznBIC5NeXK+rokS919urtfTHIiyeE1aw4n+UYvezjJlVX1thnPCgBzafeENXuTPLPq+EySD0xYszfJz1cvqqojWb7yTpL/qaonNjUtm3VVkucv9hBzwD5vP3u8/ezxznjXVj5pSqxrned6C2vS3ceSHEuSqlrs7oUJ358tssc7wz5vP3u8/ezxzqiqxa183pSXwc8kuXrV8b4kz25hDQCwBVNi/UiSA1W1v6quSHJTkvvWrLkvyS0r7wr/YJJfd/fP134hAGDzNnwZvLvPVdXtSR5IsivJ8e4+VVW3rZw/muT+JDcmWUrymyS3Tvjex7Y8NVPZ451hn7efPd5+9nhnbGmfq/sVv1oGAAbiDmYAMDixBoDBbXus3ap0+03Y40+u7O1jVfVQVV17Mea8lG20x6vWvb+qXqqqj+/kfJeLKftcVddX1aNVdaqqfrjTM17qJvx78caq+m5V/Xhlj6e8B4lVqup4VT13vnuJbKl73b1tjyy/Ie0/kvxBkiuS/DjJwTVrbkzyvSz/v9ofTPKj7ZzpcntM3OM/TvKmlY8P2ePZ7/Gqdf+S5Tdcfvxiz32pPSb+LF+Z5CdJ3r5y/JaLPfel9Ji4x3+b5EsrH+9J8sskV1zs2S+lR5I/TfLeJE+c5/ymu7fdV9ZuVbr9Ntzj7n6ou3+1cvhwlv8/eKab8nOcJJ9N8q0kz+3kcJeRKfv8iST3dvfTSdLd9npzpuxxJ3lDVVWS12c51ud2dsxLW3c/mOV9O59Nd2+7Y32+25Budg3nt9n9+3SW/4uO6Tbc46ram+RjSY7u4FyXmyk/y+9M8qaq+kFVnayqW3ZsusvDlD3+apJ3Z/nGVo8n+Vx3v7wz482NTXdvyu1GX42Z3aqU85q8f1X14SzH+k+2daLLz5Q9/nKSO7r7peULErZgyj7vTvK+JB9J8rtJ/q2qHu7un273cJeJKXv80SSPJvnzJH+Y5J+r6l+7+7+3ebZ5sunubXes3ap0+03av6p6T5K7kxzq7l/s0GyXiyl7vJDkxEqor0pyY1Wd6+5v78iEl4ep/148390vJHmhqh5Mcm0SsZ5myh7fmuTve/mXq0tV9bMk1yT5950ZcS5sunvb/TK4W5Vuvw33uKrenuTeJJ9yBbIlG+5xd+/v7nd09zuS/GOSvxHqTZvy78V3knyoqnZX1Wuz/BcAn9zhOS9lU/b46Sy/cpGqemuW/0rU6R2d8vK36e5t65V1b9+tSlkxcY8/n+TNSb62cuV3rv11nckm7jGv0pR97u4nq+r7SR5L8nKSu7vbn9qdaOLP8heT3FNVj2f55do7utufztyEqvpmkuuTXFVVZ5J8Iclrkq13z+1GAWBw7mAGAIMTawAYnFgDwODEGgAGJ9YAMDixBoDBiTUADO5/ARnswWeEC5GsAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + "ax = plt.axes()\n", + "print(ax)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 356, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1. , 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2. ,\n", + " 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1,\n", + " 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. , 4.1, 4.2,\n", + " 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5. , 5.1, 5.2, 5.3,\n", + " 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 6. , 6.1, 6.2, 6.3, 6.4,\n", + " 6.5, 6.6, 6.7, 6.8, 6.9, 7. , 7.1, 7.2, 7.3, 7.4, 7.5,\n", + " 7.6, 7.7, 7.8, 7.9, 8. , 8.1, 8.2, 8.3, 8.4, 8.5, 8.6,\n", + " 8.7, 8.8, 8.9, 9. , 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7,\n", + " 9.8, 9.9, 10. , 10.1, 10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 10.8,\n", + " 10.9, 11. , 11.1, 11.2, 11.3, 11.4, 11.5, 11.6, 11.7, 11.8, 11.9])" + ] + }, + "execution_count": 356, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.arange(1, 12, 0.1)\n", + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 357, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.84147098, 0.89120736, 0.93203909, 0.96355819, 0.98544973,\n", + " 0.99749499, 0.9995736 , 0.99166481, 0.97384763, 0.94630009,\n", + " 0.90929743, 0.86320937, 0.8084964 , 0.74570521, 0.67546318,\n", + " 0.59847214, 0.51550137, 0.42737988, 0.33498815, 0.23924933,\n", + " 0.14112001, 0.04158066, -0.05837414, -0.15774569, -0.2555411 ,\n", + " -0.35078323, -0.44252044, -0.52983614, -0.61185789, -0.68776616,\n", + " -0.7568025 , -0.81827711, -0.87157577, -0.91616594, -0.95160207,\n", + " -0.97753012, -0.993691 , -0.99992326, -0.99616461, -0.98245261,\n", + " -0.95892427, -0.92581468, -0.88345466, -0.83226744, -0.77276449,\n", + " -0.70554033, -0.63126664, -0.55068554, -0.46460218, -0.37387666,\n", + " -0.2794155 , -0.1821625 , -0.0830894 , 0.0168139 , 0.1165492 ,\n", + " 0.21511999, 0.31154136, 0.40484992, 0.49411335, 0.57843976,\n", + " 0.6569866 , 0.72896904, 0.79366786, 0.85043662, 0.8987081 ,\n", + " 0.93799998, 0.96791967, 0.98816823, 0.99854335, 0.99894134,\n", + " 0.98935825, 0.96988981, 0.94073056, 0.90217183, 0.85459891,\n", + " 0.79848711, 0.7343971 , 0.66296923, 0.58491719, 0.50102086,\n", + " 0.41211849, 0.31909836, 0.22288991, 0.12445442, 0.02477543,\n", + " -0.07515112, -0.17432678, -0.27176063, -0.36647913, -0.45753589,\n", + " -0.54402111, -0.62507065, -0.69987469, -0.76768581, -0.82782647,\n", + " -0.87969576, -0.92277542, -0.95663502, -0.98093623, -0.99543625,\n", + " -0.99999021, -0.99455259, -0.97917773, -0.95401925, -0.91932853,\n", + " -0.87545217, -0.82282859, -0.76198358, -0.69352508, -0.61813711])" + ] + }, + "execution_count": 357, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y = np.sin(x)\n", + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 327, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n", + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 1\n", + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + "ax = plt.axes()\n", + "print(ax)\n", + "\n", + "ax.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 328, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288) AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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/vX+QkbEhzB3jXffGT3XrzBRCA3156D09K1fnTgu5hwr0s3HXBelsPlzD5gI9K1eu4628Yxw4dpKvXTgcHy9pqX46gwP9+NKsVF7ffZT8YyesjqPclBZyD7YkK5mokAD+qt/2lYswxvDQewdJjgji6glDrY7jEm6fPYwgfxt/e19nRlPnRgu5Bxvkb+OO84bxUX4Ve8r0Hpyy3scHq8gtqeOrF6bja9M/PwARwf7cPD2ZV3aU6hjs6pzoJ8nDLZ2eTLC/jcc+Omx1FKV46L2DxA0O5IYp3jGKW0995fw0fH18eOzjAqujKDekhdzDhQ3yY3FWMv/eWUZZbZPVcZQXyy2pZVNBDXecN4wAX5vVcVxKzOBArpscz5qcEo43tFodR7kZLeRe4PbZqRjgiU/0rFxZ558fHyYkwJdFWZ49w9m5uvP8NJrb7Dyz6YjVUZSb0ULuBRKHBHFVxlBWbimmvrnN6jjKC5XVNvFqbjmLpiUxONDP6jguaWRsKHNGRvPkxiO0tHdYHUe5ES3kXuIr56dxsqWd57cUWR1FeaEnPy3EGMPts1OtjuLSvnJ+GlUnW3hlR5nVUZQbcUohF5ErRGS/iBwUkfu6WX+hiNSJyA7H4yc93Vc5R0ZiGDPTInn840Ja2+1Wx1Fe5GRLO89tKeLKjKEkDgmyOo5Lmz08ktFxofzzo8M6vLLqsT4XchGxAQ8BVwJjgSUiMrabTT8yxkxyPP63l/sqJ1g+J42j9c28mqvf9tXAWbW1mBPN7Xzl/DSro7g8EeEr56ex/9gJPsyvsjqOchPOOCPPAg4aYwqMMa3A88D8AdhX9dKFI6MZHhPCE58U6rd9NSA67IbHPzlMZsoQJiWFWx3HLVwzMZ6Y0AAe+0i7oqmecUYhTwCKu7wucSw71UwR2Skir4vIuF7uq5xARFg2K5VdpXVsK6q1Oo7yAm/uOUrJ8Sbu1LPxHvP39WHZrFQ+yq9i/1EdtlWdnTMKeXeDJZ96urcNSDHGTAT+Arzci307NxRZLiLZIpJdWanzbJ+rGyYnEBroy78+LbQ6ivICT3xSSFLEIOaO9e7JUXpraVYyAb4+PLWx0Oooyg04o5CXAF07hiYC/3UT1hhTb4w56Xi+HvATkaie7NvldzxqjMk0xmRGR0c7IbZ3Cg7wZWFmEq/vKudYfbPVcZQH21tWz5bCGm6bkYrNyydH6a0hwf5cOzGetdtKqWvSLqPqzJxRyLcCI0RkmIj4A4uBdV03EJE4cUw6LCJZjuNW92Rf5Xy3zUyhwxie1YEnVD96elMhgX4+LMhMtDqKW1o2K5Wmtg7W5JRYHUW5uD4XcmNMO3APsAHIA1YZY/aIyAoRWeHY7CZgt4jsBP4MLDadut23r5nUmaVEBnPxqBie21KkA0+oflHX2MZL20u5blIC4UH+VsdxS+MTwpiaMoSnNxZit2vjVHV6TulHboxZb4wZaYxJN8b8yrHsEWPMI47nfzXGjDPGTDTGzDDGfHqmfVX/WzYrlaqTrbyWW251FOWBVucU09xm59aZKVZHcWvLZqVSWN3IB/naLkidno7s5qXOGx5FWnQw//pUu6Ip57LbDU9tPMK01CGMiw+zOo5bu2JcHNGhATyljVPVGWgh91I+PsKXZqWSW1LH9uJaq+MoD/LBgUqKahq5bWaq1VHcnr+vD0uzknn/QKXOVa5OSwu5F7thSiLB/jae3aTjryvneXJjITGhAVw+Ls7qKB7h5unJ2ER4WhunqtPQQu7FQgJ8uW5yAq/mllHbqHMgq74rrGrg/f2VLJ2ejL+v/nlxhpjBgVwxPo5V2cU0tWrjVPVF+knzcjdPT6Gl3a5dXJRTrNxShM1HWJKVbHUUj3LLjBRONLfrPAmqW1rIvdzY+MFMTg7nuc1F2uhN9UlLewerc0qYOyaW2MGBVsfxKNOHRZAeHcxzOg2x6oYWcsUt01MoqGpgY0G11VGUG3tj91FqGlpZOl3Pxp1NRLh5egrbi2rZU1ZndRzlYrSQK66aMJSwQX7a6E31yXObi0iOCOK84VFWR/FIN05JJMDXh+c26+dU/Tct5IpAPxs3TU1kw56jVJzQ8ddV7x2sOMHmwzUsyUrGR8dV7xdhQX5cPSGel7eXcrKl3eo4yoVoIVcALJ2eTLvdsDpbG72p3ntuczF+NtFx1fvZzTOSaWjtYN0ObfSm/kMLuQIgPTqEWemRPLe5iA4d11n1QnNbBy9uK+GycXFEhQRYHcejTU4KZ8zQwTy7+Yg2TlWf00KuPrd0ejKltU18pOM6q15Yv6ucuqY2btYuZ/1ORFg6PZk9ZfXklmijN9VJC7n63NyxsUQE+/P8lmKroyg38uzmItKigpmZHml1FK9w3aR4gvxt2uhNfU4LufpcgK+NG6ck8HbeMSpPtFgdR7mBA8dOkHPkOEuykhHRRm4DITTQj2smxPPv3DJt9KYALeTqFIumJdFuN7y4TRu9qbN7YWtnI7cbpiRYHcWrLMpKorG1g1d3aqM3pYVcnWJ4TCjTUofwwtZibUyjzqilvYO120q4bGwckdrIbUBNTgpnVGwoK7fqbTDlpEIuIleIyH4ROSgi93Wz/mYRyXU8PhWRiV3WFYrILhHZISLZzsij+mbxtGQOVzWwqaDG6ijKhb219xjHG9tYNC3J6iheR0RYNC2JncW15JXXWx1HWazPhVxEbMBDwJXAWGCJiIw9ZbPDwBxjzATgF8Cjp6y/yBgzyRiT2dc8qu/mZQwlNNCXF7ZqYxp1ei9sLSYhfJCO5GaR6ycn4G/z4QU9K/d6zjgjzwIOGmMKjDGtwPPA/K4bGGM+NcYcd7zcBOioES5skL+N6yYlsH73UZ3eVHWruKaRj/KrWJiZpCO5WWRIsD+Xj4/jpe2lNLfp9KbezBmFPAHo+pWwxLHsdO4AXu/y2gBvikiOiCw/3U4islxEskUku7JS+zn3t8VZSbS223lpe6nVUZQLWp1djAg6kpvFFk9Loq6pjQ17jlodRVnIGYW8u6/j3baSEpGL6CzkP+iyeLYxZgqdl+bvFpELutvXGPOoMSbTGJMZHR3d18zqLMbFhzEhMUwbvakv6LAbVmWXMGdkNPHhg6yO49VmpkWSFDFIx37wcs4o5CVA19YuicAX+kSIyATgMWC+Mebz+TKNMWWOnxXAS3ReqlcuYGFmEvuOnmBXqY4gpf7jwwOVHK1vZrE2crOcj4+weFoyGwuqKaxqsDqOsogzCvlWYISIDBMRf2AxsK7rBiKSDKwFbjXGHOiyPFhEQj97DlwG7HZCJuUE10yMJ8DXh1XZ+m1f/cfzW4uICvHn4tGxVkdRdE5v6iOwOkc/p96qz4XcGNMO3ANsAPKAVcaYPSKyQkRWODb7CRAJ/O2UbmaxwMcishPYArxmjHmjr5mUc4QN8mNexlBe2VGmjWkUAFUnW3gnr6KzxbSvDkPhCuLCApkzMpo1OSU64ZGXcson0Riz3hgz0hiTboz5lWPZI8aYRxzP7zTGDHF0Mfu8m5mjpftEx2PcZ/sq17EgM5ETze3amEYB8PL2UtrthoWZelndlSzMTOJYfQsf6oRHXkm/UqszmjGsszGNXl5Xxhhe2FrM5ORwRsSGWh1HdXHJmM4Jj1br59QraSFXZ+TjIyyYmsQnB6sprmm0Oo6y0M6SOvIrTurZuAvy9/XhukkJvLX3GDUNOvaDt9FCrs7qpqmJiMDqHJ1IxZutyi4m0M+HqycMtTqK6sbCaYm0dRhe1rEfvI4WcnVW8eGDOH9ENGuyi7UxjZdqau3g3zvKmDd+KKGBflbHUd0YHTeYCYlhrMrWsR+8jRZy1SMLMxMpq2vmk4NVVkdRFtiw5ygnWtpZoJfVXdoCx9gPu0t1IhVvooVc9cjcsbGEB/np5XUvtSq7mOSIIKYPi7A6ijqDa3XsB6+khVz1SICvjfkT49mw5yh1jW1Wx1EDqLimkU8PVbNgaqJOkOLiwgb5ccX4OF7ZoROpeBMt5KrHFmR2TqSyLvcLI/AqD7Y6pwQRuGGqTpDiDhZMTaK+uZ039x6zOooaIFrIVY+Nix/M6LhQ1uhlO69htxtezCnhvOFRJOgEKW5hVnokCeGDWKO3wbyGFnLVYyLCTVMT2VlSx4FjJ6yOowbApoJqSmubuEnPxt2Gj49w45QEPsqvpLyuyeo4agBoIVe9cv3kBHx9REeQ8hKrc0oIDfTl8nFxVkdRvXDj1ESMgbXbtE+5N9BCrnolMiSAi0fH8NL2Mto67FbHUf2ovrmN13eXc83EeAL9bFbHUb2QEhlM1rAI1uSUaJ9yL6CFXPXaTVMTqTrZwgf7dYIGT7Y+t5zmNjsL9LK6W1owNZHDVQ3kHDludRTVz7SQq167aHQMUSH+Ov+xh1udU8LwmBAmJYVbHUWdg3kZQwnyt7E6Wxu9eTot5KrX/GydEzS8k1dB9ckWq+OoflBQeZKcI8dZMDUREe077o6CA3yZlzGUV3PLaGxttzqO6kdayNU5WZCZRLvd8MoO7VPuidbklGDzEa6fnGB1FNUHC6Ym0tDawRu7j1odRfUjpxRyEblCRPaLyEERua+b9SIif3aszxWRKT3dV7mmUXGhZCSE6ZCtHqjDbli7rZQ5I6OJGRxodRzVB1nDIkiJDNLL6x6uz4VcRGzAQ8CVwFhgiYiMPWWzK4ERjsdy4OFe7Ktc1ILMRPLK69lTVmd1FOVEHx+s4mh9s/Yd9wAiwk1TEtlYUE1xTaPVcVQ/ccYZeRZw0BhTYIxpBZ4H5p+yzXzgKdNpExAuIkN7uK9yUddOjMff5qPf9j3M6uxiwoP8uGRMjNVRlBPcMDUREXhxm35OPZUzCnkC0LX5coljWU+26cm+AIjIchHJFpHsykrt9uQKwoP8mTs2lld2lNLarn3KPUFdYxtv7j3GdZMSCPDVvuOeICF8ELPSI3lxWwl2u/Yp90TOKOTdNWk99V/L6bbpyb6dC4151BiTaYzJjI6O7mVE1V9uykzkeGMb7+7TCRo8wbrcMlrb7XpZ3cMsmJpEcU0Tmw/XWB1F9QNnFPISIKnL60Tg1KbMp9umJ/sqF3b+8ChiQgN0ggYPsSanhNFxoYyLH2x1FOVEl4+LIzTAVz+nHsoZhXwrMEJEhomIP7AYWHfKNuuA2xyt12cAdcaY8h7uq1yYr82HG6Yk8t7+SipPaJ9yd5Z/7AQ7i2u5SfuOe5xB/jaunjiU9bvKOdmifco9TZ8LuTGmHbgH2ADkAauMMXtEZIWIrHBsth4oAA4C/wC+dqZ9+5pJDaybpibSYTe8vF0naHBna3JK8PURrtO+4x7ppqmJNLV1sH5XudVRlJP5OuOXGGPW01msuy57pMtzA9zd032VexkeE8Lk5HBW5xRz5/nD9GzODbV32Fm7vdQx/G6A1XFUP5iSPIS0qGDWZJewMDPp7Dsot6EjuymnuGlqIgeOnSS3RPuUu6MP8ztvjegEKZ5LRLhxaiJbCmsorGqwOo5yIi3kyimumRhPgK+PTqTiplZnlxAZ7M9Fo7XvuCe7cUoiPtqn3ONoIVdOMTjQjyvGx7FuRxnNbR1Wx1G9UNPQytt5x5g/KQE/m/5J8GRxYYGcPyKaF3NK6NA+5R5DP7XKaRZMTaK+uZ0392qfcnfyyo5S2joMC6fpZXVvsCAzkbK6Zj49VGV1FOUkWsiV08xKjyQhfBCrs/XyujtZnV1CRkIYo+O077g3uHRMLGGD/FilQyt7DC3kyml8fIQbpyTw8cEqymqbrI6jemB3aR17y+tZkKln494i0M/G/EnxbNhzlLrGNqvjKCfQQq6c6qapSRgDa7UxjVtYk1OCv82HayfGWx1FDaAFU5NobbezLlcH0vQEWsiVUyVHBjF9WARrckroHD5AuaqW9g5e3lHKZeNiCQ/ytzqOGkDjEwYzOi6UNXobzCNoIVdOtyAzicLqRrYWHrc6ijqDt/dWUNvYxgIdHMTriAgLMpPYWVLH/qMnrI6j+kgLuXK6eRlxBPvbWKXf9l3a6pxihoYFct7wKKujKAtcNykeXx/RxqkeQAu5crogf1+unhCvEzS4sKN1zXx4oJIbpyRi89Ehdb1RZEgAl4yJ4eUdpbR12K2Oo/pAC7nqFwunJdHY2sFr2pjGJb24rQS7Qecd93ILpiZRdbKVd/dVWB1F9YEWctUvpiSHkx4drH1VXZAxhjU5JWSlRpAaFWx1HGWhC0dFExMawKqtenndnWkhV/1CRFg0LYmcI8c5WKGNaVzJlsM1HK5qYNE0beTm7XxtPtw4NZH39ldwrL7Z6jjqHGkhV/3m+smJjsY0elbuSl7ILiY0wJd5GUOtjqJcwMLMJOymc0wB5Z60kKt+Ex0awMWjY3hxW4k2pnER9c1trN9VzjWT4hnkb7M6jnIBw6KCyRoWwersYh37wU31qZCLSISIvCUi+Y6fQ7rZJklE3hORPBHZIyLf7LLuZyJSKiI7HI95fcmjXM+iaZ2Nad7TxjQuoXN2OjuLtO+46mKRY+yHLYdrrI6izkFfz8jvA94xxowA3nG8PlU78B1jzBhgBnC3iIztsv6PxphJjsf6PuZRLmbOSEdjGu2r6hJWZRczOi6UCYlhVkdRLmRexlBCA3x5QT+nbqmvhXw+8KTj+ZPAdaduYIwpN8Zsczw/AeQBCX08rnIT/2lMU0mFNqaxVF55PbkldSzMTEJE+46r/xjkb+OaSZ1jP9Q360Qq7qavhTzWGFMOnQUbiDnTxiKSCkwGNndZfI+I5IrI491dmu+y73IRyRaR7MrKyj7GVgNpYWYSHXbDam1MY6kXthbjb/Ph+sn6PVp90aLMJJrb7Px7p4794G7OWshF5G0R2d3NY35vDiQiIcCLwLeMMfWOxQ8D6cAkoBz4/en2N8Y8aozJNMZkRkdH9+bQymLDooKZkRbBC1uLsdu1MY0Vuk6QMiRYJ0hRXzQhMYzRcaHap9wNnbWQG2MuNcaM7+bxCnBMRIYCOH5226JJRPzoLOLPGmPWdvndx4wxHcYYO/APIMsZ/1HK9SzJSqaoppGNBdVWR/FKb+45Rm1jm/YdV6f12dgPO0vq2FNWZ3Uc1Qt9vbS+DljmeL4MeOXUDaTzZtw/gTxjzB9OWde1I+v1wO4+5lEu6vJxcYQH+bFyS5HVUbzSyi1FJA4ZxOx0nSBFnd71kxMI8PXh+S16Vu5O+lrIHwDmikg+MNfxGhGJF5HPWqDPBm4FLu6mm9n/icguEckFLgLu7WMe5aIC/WxcPzmBDXuOUn2yxeo4XuVwVQOfHqpmSVYyPjpBijqD8CB/rsoYysvbS2ls1QmP3EWfCrkxptoYc4kxZoTjZ41jeZkxZp7j+cfGGDHGTDi1m5kx5lZjTIZj3bWfNZxTnmlJVjJtHYa120qtjuJVnt9ahM1HWKATpKgeWJyVzImWdl7N1T/H7kJHdlMDZmRsKFOSw1m5tUhHkBogre121mSXcOmYGGIGB1odR7mBaalDSI8O5nm9DeY2tJCrAbUkK5mCygYdQWqAvLn3KNUNrSzJSrY6inITIsKSrGS2FdWy72j92XdQltNCrgbUVRM6R5B6Xru4DIiVW4pICB/E+SO0y6bquRunJOJv00Zv7kILuRpQQf6+zJ8cz2u7yqltbLU6jkcrrGrgk4PVLJ6WhE0bualeGBLsz5UZcazdVkJTa4fVcdRZaCFXA25pVkrnvVsd6a1fPb+1uLORm06Qos7B4mnJ1De3s36XNnpzdVrI1YAbGz+YKcnhPLu5SEd66yedX5SKuXh0DHFh2shN9d6MtAjSooJ5ZvMRq6Oos9BCrixxy4yUz/s3K+fbsOcoVSdbWTpdG7mpcyMi3Dwjhe1Ftewu1ZHeXJkWcmWJeRlDGRLkxzOb9Nt+f3h64xGSI4KYo43cVB/cNCWRQD8fntWzcpemhVxZItDPxsLMJN7KO8bROp3e1Jn2Ha1nS2ENt8zQkdxU34QF+TF/YgIvby/T6U1dmBZyZZml05PpsBue36oDTzjTM5uO4O/rw4Kp2shN9d0tM1JoautgrTZOdVlayJVlUiKDuWBkNM9vKaa9w251HI9wormNl7aVcs2EeJ2uVDlFRmIYE5PCeXrTER2R0UVpIVeWumV6Mkfrm3k7r9sZcFUvvby9lIbWDm6bmWJ1FOVBbp2RwqHKBp2G2EVpIVeWunh0DEPDArXRmxMYY3hq4xEmOM6glHKWqycMJVwbp7osLeTKUr42H26ZkcLHB6vIP3bC6jhubfPhGvIrTnLLDD0bV871WePUDXu0caor0kKuLLd4WhL+vj7869NCq6O4tac3HSFskB/XTIi3OoryQDdPT8ZuDM9pVzSX06dCLiIRIvKWiOQ7fg45zXaFIrJLRHaISHZv91eeLTIkgPkT41m7rZS6Ru3ici7Kapt4Y/dRFk1LYpC/zeo4ygOlRAZzyegYnt1cRHObjr/uSvp6Rn4f8I4xZgTwjuP16VxkjJlkjMk8x/2VB/vS7FSa2jpYla2zLZ2LpzZ2tijWRm6qP90+exjVDa2s21lmdRTVRV8L+XzgScfzJ4HrBnh/5SHGxYeRNSyCJzcW0qHjr/dKY2s7K7cUccX4OBKHBFkdR3mwWemRjIoN5YlPCrUrmgvpayGPNcaUAzh+xpxmOwO8KSI5IrL8HPZHRJaLSLaIZFdWVvYxtnJFX56dSsnxJt7OO2Z1FLeydlspdU1tfHn2MKujKA8nItw+O5W88no2FdRYHUc5nLWQi8jbIrK7m8f8XhxntjFmCnAlcLeIXNDboMaYR40xmcaYzOhoHT/aE106JpaE8EH865NCq6O4Dbvd8MQnh5mQGMbUFG1iovrfdZMTGBLkxxOfHLY6inI4ayE3xlxqjBnfzeMV4JiIDAVw/Ox2VA9jTJnjZwXwEpDlWNWj/ZV38LX5cOvMFDYWVJNXXm91HLfwYX4lhyob+PLsYYjouOqq/wX62Vg6PZm38o5RVN1odRxF3y+trwOWOZ4vA145dQMRCRaR0M+eA5cBu3u6v/Iui6clEejnw+Mf67f9nnj8k0JiQgOYlzHU6ijKi9w6IxWbCE9uLLQ6iqLvhfwBYK6I5ANzHa8RkXgRWe/YJhb4WER2AluA14wxb5xpf+W9woP8WZiZxMs7SjlWrwNPnEn+sRN8eKCS22am4O+rQ0KogRMXFsi8jKGs2lrMCZ0VzXJ9+vQbY6qNMZcYY0Y4ftY4lpcZY+Y5nhcYYyY6HuOMMb862/7Ku915XhoddsPjeg/ujP758WH8fX1YkpVsdRTlhe48fxgnWjp7TChr6dd45XKSI4OYlzGU5zYV6bf90zhW38zabaUszEwkMiTA6jjKC01IDGdWeiT//PgwLe06QIyVtJArl3TXBen6bf8MHv/4MO12O8vPT7c6ivJiK+akc6y+hVe26wAxVtJCrlxSRmIYs9IjefzjQlrbda7yruqa2nh2cxFXTYgnOVIHgFHWOX9EFGOHDuaRDw9h14GcLKOFXLms5RekcbS+WYeDPMUzm45wsqWdFXPSrI6ivJyIcNecNAoqG3hLB3KyjBZy5bLmjIxmdFwoj354SIeDdGhu6+CJTw5zwchoxsWHWR1HKa7KGEpSxCAe+UA/p1bRQq5c1mff9g8cO8nbeTpWEMDqnBKqTrby1Tl6b1y5Bl+bD185P43tRbVsOawdjwBWbini0QG83aCFXLm0aybEkxwRxJ/fyff6b/vtHXb+8WEBk5LCmZEWYXUcpT63YGoSEcH+PPzBIaujWK6xtZ3fv7mfDw9U4eMzMKMtaiFXLs3X5sM9Fw1nV2kd7+337rPyf+eWUVTTyIo56Tocq3Ipg/xt3HHeMN7fX8mO4lqr41jq2U1FVJ1s5ZuXjhiwY2ohVy7v+ikJJEUM4sG3vfesvL3DzoNv5zM6LpTLxsZaHUepL1g2K5UhQX786e0DVkexTGNrO3//8BDnDY9iWurAXTXTQq5cnp/Nh7svHM7OkjreP+CdU9i+vKOMwupG7p07csAu1ynVGyEBvnzlgjTe31/JtqLjVsexhBVn46CFXLmJG6YkkhDunWflbR12/vxOPuPiB+vZuHJpy2amEhHsz5/ezrc6yoBrau2w5GwctJArN+Hv68PdFw1nR3EtH+ZXWR1nQK3dVkJRTSPfnjtS740rlxYc4MvyC9L48EAlOUe866z82c1HLDkbBy3kyo3cNLXzrPxPbx/wmrPy1nY7f37nIBMTw7h4dIzVcZQ6q9tmphAZ7O9V98qbWjt45ANrzsZBC7lyI/6+Ptxz8XC2F9Xy1l7vGEVqdU4xpbVN3Ktn48pNBPn7ctecND7KryK70Dv6lT+5sdCys3HQQq7czIKpiaRHB/ObN/bR3uHZY7A3t3Xw13cPMiU5nDkjo62Oo1SP3TIjhaiQAH7zxj6Pv3p2vKGVh947yEWjoi05Gwct5MrN+Np8+MEVozlU2cCq7BKr4/Srf358mPK6Zr53+Wg9G1duJcjfl2/PHcnWwuNs2OPZV8/+8u5BGlraue/KMZZl6FMhF5EIEXlLRPIdP4d0s80oEdnR5VEvIt9yrPuZiJR2WTevL3mUd5g7NpZpqUP449sHaGxttzpOv6g62cLD7x/i0jGxzEyPtDqOUr22MDORETEhPPB6nsfOYHikuoGnNxWyYGoSo+JCLcvR1zPy+4B3jDEjgHccr/+LMWa/MWaSMWYSMBVoBF7qsskfP1tvjFnfxzzKC4gI9105hsoTLTz20WGr4/SLP751gOa2Dn44b7TVUZQ6J742H340bwyF1Y08u/mI1XH6xf9t2I+vjw/fvmykpTn6WsjnA086nj8JXHeW7S8BDhljPPP/qhowU1OGcOX4OP7+wSEqT7RYHcepDhw7wcotRdwyI4X06BCr4yh1zi4cFc15w6N48J186prarI7jVNuLjvNabjlfOX8YsYMDLc3S10Iea4wpB3D8PFv/mMXAylOW3SMiuSLyeHeX5j8jIstFJFtEsisrvXN0L/Xfvnf5KFra7R7XzeX+9XkEB/jyjUusaQGrlLOICD+cN5q6pjb+9t5Bq+M4jTGGX6/fR1SIP8tdYCbCsxZyEXlbRHZ385jfmwOJiD9wLbC6y+KHgXRgElAO/P50+xtjHjXGZBpjMqOjtQWvgrToEG6dmcJzW4rY6SETNXyUX8n7+yv5xsUjiAj2tzqOUn02Lj6MG6ck8sQnhRRVN1odxyn+nVvOlsIavnXpSEICfK2Oc/ZCboy51BgzvpvHK8AxERkK4Ph5pumprgS2GWM+b8JojDlmjOkwxtiBfwBZffvPUd7m23NHEh0SwP+8vJuOAZr7t7+0tHfw83/vJTkiiNtmpVgdRymn+e5lo/D39eF/Xtnt9t3R6pra+MWre8lICGNJVrLVcYC+X1pfByxzPF8GvHKGbZdwymX1z74EOFwP7O5jHuVlQgP9+H9Xj2VXaR3PbHLvphePvF/AwYqT/Hz+OAJ8bVbHUcpp4sIC+e5lI/nwQCX/zi23Ok6f/P7N/VSfbOH+6zOwucgERn0t5A8Ac0UkH5jreI2IxIvI5y3QRSTIsX7tKfv/n4jsEpFc4CLg3j7mUV7o6glDOX9EFL/bsJ+K+mar45yTgxUneei9g1w7MZ6LRulQrMrz3DozlQmJYfzvv/dS1+ieDd92FNfy9KYj3DYzlYzEMKvjfK5PhdwYU22MucQYM8Lxs8axvMwYM6/Ldo3GmEhjTN0p+99qjMkwxkwwxlz7WcM5pXpDRPj5teNoabfzy9fyrI7Ta3a74UdrdzHI38b/u3qs1XGU6hc2H+H+6zOoaWjhgTf2WR2n19o77Pz4pV1EhwTwHYu7m51KR3ZTHiEtOoQVF6azbmcZH7rZnOWrsovZUljDj+eNITo0wOo4SvWb8QlhfHn2MFZuKXK7cdif2niEPWX1/PSacYQG+lkd579oIVce42sXppMeHcz31uzkeEOr1XF6pOJEM/evz2NGWgQLMhOtjqNUv7t37kgSwgfxw7W7aG7rsDpOjxyqPMlvN+znwlHRzMuIszrOF2ghVx4j0M/Gg4snU9PQyo9e2uXyrWPtdsP3VufS3G7n/uszdDx15RWCA3y5/4YM8itOcv96178V1tpu51vP7yDAz4cHbpjgkp9TLeTKo4xPCOPbc0fx+u6jrMlx7UlV/vFRAR8cqOQnV48lTUdwU15kzsho7jhvGE9tPMKbe45aHeeMfv/WfnaV1vGbGycQF2btCG6no4VceZzlF6QxfVgEP1u3hyPVDVbH6db2ouP8dsN+rhwfx83TXaMvqlID6ftXjGJc/GC+/2Iu5XVNVsfp1icHq/j7BwUsnZ7M5eNc75L6Z7SQK49j8xH+sGgSPj7CvS/soM3F5i2va2rj6yu3Ezs4kAdudM1LdUr1twBfG39ZMpnWdjv3vrDD5QZ0qmlo5durdpAeHcz/u8q1e5NoIVceKSF8EPdfn8G2olp+8soel7lfbkxnV7Pyumb+snQyYYNcq/WrUgMpLTqEn187jk0FNfz5nXyr43yurcPON5/fTk1DKw8unswgf9ceoMn6QWKV6ifXTIwnr7yev71/iPToYO48P83qSPzl3YO8tqucH1wxminJp50jSCmvcdPURDYWVPPgO/kMiwrmuskJluYxxvDTdXv4KL+K39yYwfgE1xn45XS0kCuP9t3LRlFQ2cCv1ueRGhnMpWNjLcuyamsxf3jrADdMSWDFHOu/VCjlCkSEX9+QQenxJr63ZicxgwOYlR5lWZ5/fFTAc5uL+OqF6Sya5h7tV/TSuvJoPj7CHxdNYnx8GN94fjt7y+otyfHe/gp++NIuzh8RxW/0vrhS/yXA18ajt2aSEhnMXU/ncODYCUtyvLG7nF+/vo+rMobyvctGWZLhXGghVx5vkL+Nx5ZlMjjQjy89sWXA/0jkltTytWe2MToulIdvmYqfTT92Sp0qLMiPf90+jUA/G7c/sZWjdQM7b8Kmgmq+9cIOJiWF8/uFE/FxkQlRekL/oiivEDs4kKfu6Jwld9HfN5JbUjsgx80urOG2x7cQGeLPE7dPc4m5i5VyVYlDgnh82TRqG1u58eFPOVR5ckCO+9beY9z2+BYShwTxj9syCfRz7cZtp9JCrrzGyNhQVq+YSXCAL0v/sZnNBdX9erz1u8pZ+thmhgT589ydM4gJdc3BJJRyJRmJYaxcPoPmtg5uevhTthcd79fjrc4uZsUzOYwZOpjVd80kKsT95jvQQq68SkpkMGtWzCIuLJDbHt/C+l39M+HeYx8VcPdz28hICOPFr84iOTKoX46jlCeakBjOi1+dRWigH0v+sYl39x1z+jGMMfz9g0N8b00us9Ijee7O6QwJ9nf6cQaCFnLldeLCAnlh+QxGDx3M157dxndW7aS+2TnzIx9vaOU7q3byy9fyuGJcHM/eOZ0IN/3joJSVUqOCefGrsxgeE8KdT2bzq9f20tTqnElWymqb+NITWz9v2PbYskyC3fi2l7jKQBm9kZmZabKzs62OodxcW4edv7yTz0PvHyI2NIDfLZjIrOHn1u3FGMPabaX8an0e9U1trJiTzr1zR2JzowYzSrmiky3t/Oq1PFZuKSI5IogHbsjo0+d0VXYxv3w1j3a74b4rR3PrjBS3aNgmIjnGmMxu1/WlkIvIAuBnwBggyxjTbXUVkSuABwEb8Jgx5gHH8gjgBSAVKAQWGmPOekNEC7lypu1Fx/nOqp0UVDUwZ2Q0X5qdypwR0T36cLd32PnkUDWPvH+IjQXVTEkO5/4bMhgdN3gAkivlPT49VMWP1u6isLqRayfGc8uMFKalDulRV86W9g427DnGU58Wkn3kOFnDIvjtTRNIiQwegOTO0Z+FfAxgB/4OfLe7Qi4iNuAAMBcoAbYCS4wxe0Xk/4AaY8wDInIfMMQY84OzHVcLuXK2ptYO/vFRAU9vOkLliRaGRQWzaFoS4+PDGBEbQkxoACJCh91QfbKF4uNNvLG7nJd3lFF5ooXwID++e9kolmYlu8W3e6XcUXNbBw++k89TnxbS0NpBWlQwCzKTmJkeSUL4IKJC/D//nJbVNnG4qoGNBdWs2lpMdUMrSRGDWH5BOje74ee03wp5lwO8z+kL+UzgZ8aYyx2vfwhgjPm1iOwHLjTGlIvIUOB9Y8xZe+FrIVf9pbXdzuu7y3nik0J2FNd+vnxwoC+BfjaqTrbw2dwOfjbhwlEx3DA5gYvHxBDg615dVpRyV42t7byWW86q7GK2Fv7nIm6Arw9RIQFUnmih1TFZko/AJWNiuXl6Mhf08EqbKzpTIR+Iu/sJQHGX1yXAdMfzWGNMOYCjmMec7peIyHJgOUBysnsMm6fcj7+vD/MnJTB/UgIVJ5o5eOwk+RUnya84QWu7ndjBgcSEBhAzOJCs1Ai3beWqlDsL8vdlQWYSCzKTKKpu5MCxE5TWNlFa20RFfTOxgwNJjQomNTKYkbEhRLphl7LeOGshF5G3ge4mYv2xMeaVHhyju68/vb4MYIx5FHgUOs/Ie7u/Ur0VExpITGjgOTesUUr1v+TIIK/v3nnWQm6MubSPxygBkrq8TgTKHM+PicjQLpfWK/p4LKWUUsqrDEQ/8q3ACBEZJiL+wGJgnWPdOmCZ4/kyoCdn+EoppZRy6FMhF5HrRaQEmAm8JiIbHMvjRWQ9gDGmHbgH2ADkAauMMXscv+IBYK6I5NPZqv2BvuRRSimlvI0OCKOUUkq5uDO1WtchWpVSSik3poVcKaWUcmNayJVSSik3poVcKaWUcmNu2dhNRCqBI1bn6GdRQJXVIdyEvlc9o+9Tz+l71TP6PvVcX9+rFGNMdHcr3LKQewMRyT5dC0X13/S96hl9n3pO36ue0fep5/rzvdJL60oppZQb00KulFJKuTEt5K7rUasDuBF9r3pG36ee0/eqZ/R96rl+e6/0HrlSSinlxvSMXCmllHJjWsiVUkopN6aF3MWISJKIvCcieSKyR0S+aXUmVyYiNhHZLiKvWp3FlYlIuIisEZF9jn9bM63O5IpE5F7H5263iKwUkUCrM7kKEXlcRCpEZHeXZREi8paI5Dt+DrEyo6s4zXv1W8fnL1dEXhKRcGcdTwu562kHvmOMGQPMAO4WkbEWZ3Jl36Rzelx1Zg8CbxhjRgMT0ffsC0QkAfgGkGmMGQ/YgMXWpnIp/wKuOGXZfcA7xpgRwDuO16r79+otYLwxZgJwAPihsw6mhdzFGGPKjTHbHM9P0PkHN8HaVK5JRBKBq4DHrM7iykRkMHAB8E8AY0yrMabW0lCuyxcYJCK+QBBQZnEel2GM+RCoOWXxfOBJx/MngesGMpOr6u69Msa8aYxpd7zcBCQ663hayF2YiKQCk4HNFkdxVX8Cvg/YLc7h6tKASuAJx22Ix0Qk2OpQrsYYUwr8DigCyoE6Y8yb1qZyebHGmHLoPAkBYizO4y6+DLzurF+mhdxFiUgI8CLwLWNMvdV5XI2IXA1UGGNyrM7iBnyBKcDDxpjJQAN6CfQLHPd35wPDgHggWERusTaV8jQi8mM6b6E+66zfqYXcBYmIH51F/FljzFqr87io2cC1IlIIPA9cLCLPWBvJZZUAJcaYz67srKGzsKv/dilw2BhTaYxpA9YCsyzO5OqOichQAMfPCovzuDQRWQZcDdxsnDiIixZyFyMiQue9zDxjzB+szuOqjDE/NMYkGmNS6WyQ9K4xRs+eumGMOQoUi8gox6JLgL0WRnJVRcAMEQlyfA4vQRsFns06YJnj+TLgFQuzuDQRuQL4AXCtMabRmb9bC7nrmQ3cSucZ5g7HY57VoZTb+zrwrIjkApOA+62N43ocVyzWANuAXXT+fdQhSB1EZCWwERglIiUicgfwADBXRPKBuY7XXu8079VfgVDgLcff9UecdjwdolUppZRyX3pGrpRSSrkxLeRKKaWUG9NCrpRSSrkxLeRKKaWUG9NCrpRSSrkxLeRKKaWUG9NCrpRSSrmx/w+guBrFNqi/sgAAAABJRU5ErkJggg==\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 2\n", + "fig, ax = plt.subplots(figsize=(8, 4))\n", + "print(fig, ax)\n", + "ax.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 329, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 3\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 330, + "metadata": {}, + "outputs": [], + "source": [ + "# 함수를 정의해 cos 함수의 값을 가지고 선그래프 그리기.\n", + "def plot_cos(x) :\n", + " y = np.cos(x)\n", + " plt.plot(x, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 331, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(8, 4))\n", + "ax1.plot(x, y)\n", + "ax2.plot(x, np.cos(x))\n", + "#ax2 = plot_cos(x)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 333, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10,4))\n", + "ax1 = fig.add_subplot(2, 1, 1)\n", + "ax1.plot(x, y)\n", + "ax2 = fig.add_subplot(2, 1, 2)\n", + "ax2.plot(x, np.cos(x))\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 334, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 컬러를 집어넣자\n", + "fig = plt.figure(figsize=(8, 4))\n", + "for i in np.arange(0.1, 1.2, 0.1):\n", + " x += i\n", + " plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 335, + "metadata": {}, + "outputs": [], + "source": [ + "# 선을 구별하자\n", + "linestyles = ['-', '--', '-.', ':', 'solid']\n", + "# 선에 음영처리 - pass" + ] + }, + { + "cell_type": "code", + "execution_count": 336, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "for i, j in enumerate(np.arange(0.1, 0.6, 0.1)):\n", + " x = x+j\n", + " plt.plot(x, y, ls=linestyles[i])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 340, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 마커 처리하기\n", + "x = np.arange(1, 8)\n", + "y = x\n", + "marker = ['+', 'o', '*', 's', '.']\n", + "\n", + "fig = plt.figure(figsize=(8, 4))\n", + "for i, j in enumerate(np.arange(0.3, 2.8, 0.5)):\n", + " x = x+j\n", + " plt.plot(x, y, marker=marker[i], markersize=8)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**[마커 모양 참조!](https://matplotlib.org/3.1.1/api/markers_api.html)**" + ] + }, + { + "cell_type": "code", + "execution_count": 349, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그래프 선과 색상을 문자열로 지정하기\n", + "t = np.arange(0., 5., 0.2)\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 352, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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LdWAyC+u2Aqh6BDBqSsVqyuvXS729uQBdtUo6/fSw7+KLcwuf9/WFbbvtlpuB6e67paeeCgGaHXKz9965z/7jH0Oobr998Z7B+SvmAEgtAhjY2BtvSEuXFtZQly+XfvrTEIgXXCD94Ae5nr9SWNHmtNPC/tGjw+o4Bx6YmzN4551zx9511+BDbnbZpVzfDEAVIYBRH9zDa9SoUBNdsCDXgSn7uvPOMB71qqvC6jb5mpqk7343TCZx6KGhM1N+J6b8ySIuuWTwsjDeFYAIYCQkWgeq7JCb5ctDCI4bF8aqXnPNwMki/vpXab/9wlzBn/lMOL+xMReg77wTtp18cugNnO3AtPGQmxNPpBkYwIgRwEhEWTtQNa6Tbro9hOfuu4eAPe+8XLBmh9zccYd0wglh269+lev9mx1y09gYjjvppDAncGurtM02Ay+4117hBQBlRACj8vr7pZdeKhxm092tFddPDzMpvfCCtO++oeewJP2vpFMl/ehHIYCzS891dhZOadiZme3t6KNDrbiUxsZcGANAJAQwyt98/KlPhSbiGTOk888PY1jzV7CRQhNvY2MI4OZm6ayzBj5jzXZkmjgxzClcCs9YAaQAAYxNNx9nh9ysXZsLzssvl/7xj1wtVk+UvsCf/1y4Ss3YsWGB9NbWXLjmD7kZOzb0MgaAGkYA17P+fmnlSknNpY9pbw9J3N8fnqUuWBC233hjCOVszfRvg1zn5ZcHbjvzzJGUHABSjwBOuZLNx839WnH/4sJewG+9FdZjlUIA3nhjqN1qkHX6Zs7M1VInTsxtX7QoDOnJXm+QZmwAwEAEcJpkF7Q1k555RurqUk/P6UUP7ekdVTi7khSerX7rW+H8/AXPvzDINa+5pvj2vPCV6mCuZgBIGAFcLd56K9RSd9op9PJ99FHpllsKV7zp7g7PXdvbpVtvzUz4UDyAJUm/+11hL+H8ITdnnZX7fbAABgCUBQFcbmvXFgbowQeHQHz4YbVOn6SeddtnDmyQFJp4W1qkFZctCWu0TpgQwnPqVOm443Ir5pxzjvTJT0p7DHLtT3xiSEWsugUMAKAOEMDDtWHDwJmWurvDRBDTpoUa7MyZ0uuvF553221hIgizvPAt1NMj6YwzwnPaUkNq2toKexaPAM3HAFB5BHAp69ZJ99wzMGBPPVU67TS1trp6Vu4kaaeC01p+/LZWvKlQc501q3Aca1tbWBVHCjXhwWRrugCAmjSiADazGZJ+IGkLSde4+2WJlGoQw540or9feu016b331Dq1vfhnjOrViguukK64ItRwjz8+7DDLLXC+dq0kqWdl8VvXsyqzbuuOO0o/+clmfLPhofkYANJp2AFsZltI+omkoyQtk/S4mc1z98VJFa6YQSeNuPfesBTcEUeEjWefLS1enOvI9N570sc/rp6eW4p/Rn+ztP/+4c0220iPPx5qrS0t0pbV2VhA8zEApNNIUmWapOfd/UVJMrObJZ0gqawBPKhjjglrsD7ySHj/5pth2bjDD881A++9t3TrIJ+R33EpO7cwAAAJG0kAT5D0St77ZZIO2PggM5stabYk7Zy/KHk5LFgQhvFk3XZbea83QjQfA0D9GkkAF+ueO2BKJXefI2mOJHV2dg4y5VICDjmkrB+fNJqPAaB+jdr0ISUtU2EX4B0ldY+sOOlRqpZK7RUAMBQjCeDHJU00s13MbCtJsyTNS6ZYpSURfEl8xooVYWbIjV/UagEAQzHsJmh3X29m50m6R2EY0rXu/nRiJSshiYAjJAEAsY1obI27z5c0P6GyAABQN0bSBA0AAIaJAAYAIAICGACACAhgAAAiMPfyzo1RcDGzPkkvJfiRO0hameDngXuaNO5n8rinyeJ+Ji//nv6LuzcVO6iiAZw0M+tydyZsThD3NFncz+RxT5PF/UzeUO8pTdAAAERAAAMAEEHaA3hO7ALUIO5psrifyeOeJov7mbwh3dNUPwMGACCt0l4DBgAglQhgAAAiSG0Am9kMM3vWzJ43s4tilyftzOxaM+s1s6dil6UWmNlOZvaAmS0xs6fN7Euxy5RmZvY+M3vMzP6WuZ/fiF2mWmFmW5jZ/5jZf8UuSy0ws6Vm9qSZPWFmXYMem8ZnwGa2haR/SDpK0jKFtYlPcffFUQuWYmZ2qKQ1kn7t7nvFLk/amVmbpDZ3X2RmYyUtlHQif0eHx8xMUoO7rzGz0ZIelvQld//vyEVLPTO7QFKnpHHuflzs8qSdmS2V1Onum5zcJK014GmSnnf3F919naSbJZ0QuUyp5u4PSXo9djlqhbsvd/dFmd9XS1oiaULcUqWXB2syb0dnXumrPVQZM9tR0kckXRO7LPUorQE8QdIree+XiX/cUKXMrEPSvpIejVyUVMs0lT4hqVfSfe7O/Ry5qyR9RVJ/5HLUEpd0r5ktNLPZgx2Y1gC2Itv43zCqjpltK+l2SV9291Wxy5Nm7r7B3adI2lHSNDPjUckImNlxknrdfWHsstSYg919qqRjJZ2bebxXVFoDeJmknfLe7yipO1JZgKIyzypvl3SDu/8+dnlqhbu/IekvkmbELUnqHSzp+Mwzy5slHWlmv41bpPRz9+7Mz15JcxUemRaV1gB+XNJEM9vFzLaSNEvSvMhlAv5fptPQLyUtcffvxy5P2plZk5m9P/P7NpI+LOmZqIVKOXf/D3ff0d07FP4N/bO7nx65WKlmZg2ZTpcyswZJR0sqObIklQHs7uslnSfpHoXOLbe4+9NxS5VuZnaTpEck7WFmy8zs7NhlSrmDJZ2hUKt4IvOaGbtQKdYm6QEz+7vCf8Dvc3eGzaDatEh62Mz+JukxSXe5+92lDk7lMCQAANIulTVgAADSjgAGACACAhgAgAgIYAAAIiCAAQCIgAAGACACAhgAgAj+D7xtiwe0nDMrAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--', t, t**2, 'bs')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 354, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. 그래프 제목 / 레이블 / 범례 처리" + ] + }, + { + "cell_type": "code", + "execution_count": 368, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그래프에 설명 달기, title, 축 label, 그래프 label, 범례 추가\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.title('Salery')\n", + "plt.xlabel('years')\n", + "plt.ylabel('K/USD')\n", + "plt.plot(t, t, 'r--', label='Kim')\n", + "plt.plot(t, t**2, 'bs', label='Park')\n", + "plt.plot(t, t**3, 'g^', label='Me')\n", + "\n", + "plt.legend()\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 370, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 좌표에 레이블 부여하기\n", + "x = [1, 2, 3, 4]\n", + "y = [20, 21, 20.5, 20.8]\n", + "plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 372, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='green')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 381, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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VvMdU9BXY6ZzT3BF/B4eyDvFw94e9jlMhnVnsYsehHTz96dNEvhbJq1+/GjQXSdt+cDt/XP5HYhJz1xO6uvnV/L7b79k4diOf/vJT7u54N7Wq1vI4pajoK7BHlz/Kih0rmHbzNDo06uB1nAotom4E68aso1t4N371wa/o8UYPNu3b5HWsAmWdzmLuurn0ntObS6ZcwrOfP0vy3mQg91IEz/Z6Vpd/CDAao6+gFm1axKC5g7jvyvt+sEaqeMs5x5w1cxi/dDw1Q2qybdw2qlau6nWsHxjyzyHM3zCfiLoRjOg4gns63qNr8gcAnYyVn1iftp7Jn01m5qCZuo5NANp7ZC+b9m2iR0QPsnOy+W7fd0Q2jCz3HIdPHGbuurnMSp7FvMHzCK8Tzr93/ZsjJ49wQ6sbqGQaFAgUOhkr+U7nnMY5R2TDSN66/S2VfIBqHNo4f3756wmvc8XrVzBx2USyTmeV+Ws75/jyv18yYuEImvy5Cfctvo/ME5nsztwNQNfmXel9SW+VfBDRB6YqmPsX349zjhkDZ+ij+EHizg53kpiayJ8+/xMLNi4gdmAs3Vt0L/XXyXE5VLJKpB1N47pZ11G9SnXuvPxORnUeRZdmXfT9EsT0I7kCmbV6FrGrY2lSu4n+0waRejXqMXPQTJbetZSs01lcO+tanvv8uVJ57uycbJZuXcqQfw6h/1v9AWgU2ogl0UtInZDK9IHTubr51fp+CXI6oq8gkvcmM2bJGHq16sWT1z/pdRy5ADdeeiPrxqxj4rKJdAvvBvzfUXhxpWSkMHP1TGYlzyIlI4WLa1zM3Vfcnf98N156Y2nHFw+p6CuAQ1mHGDxvMBfXuJi3bn+LypUq9gLfwSy0aihTbpqSf/t3//odB44f4OX//zL1a9Q/774ns08CULVyVeI3xPPUyqfoc2kfXurzEgPbDNQno32s0KI3s3BgDtAYyAFinHN/NbP6wDtABLADGOqcO1jA/juATCAbOH2us8JSdjakbyDjRAYLhy+kYa2GXseRUhRaNZQpq6bw4dYPebXfq2RlZzFp2SRSMlJoUacFk3tNplPjTsQmxTLn2zm82OdF7ul4D7/s9EtubXcrEXUjvP4nSDkodHqlmTUBmjjnksysNpAI3ALcAxxwzj1nZg8D9ZxzP7mAeV7RRznn9hU1lKZXlr6jJ4/qE4o+lbw3mRELR7B672oqW2WyXXb+fZWsEjkuhyqVqjCozSAmXDNBq135VIkuU+ycSwVS877ONLONQDNgEHB93sNmAysArVQRQFbuWElSahIPdn1QJe9jHRt35Ot7vybsxTAOZR36wX05Loe61euy6Veb9NtcBVasszhmFgF0AlYBjfJ+CJz5YXCu7yIH/MvMEs1s9Hmee7SZJZhZQnp6enFiSQFSM1MZNn8Yrye+zrFTx7yOI2WsSqUqZGRlFHhfRlaGSr6CK3LRm1koEA886Jw7XIzX6O6c6wzcBIw1s+sKepBzLsY5F+WciwoLCyvG08uPnc45zfD44WSezCR+aLyO5iuIFnVaFGu7VBxFKnozCyG35OOccwvyNn+fN35/Zhw/raB9nXN78v5OA94FupQ0tJzfxGUT+XTnp0y7eRqXN7zc6zhSTib3mkzNkJo/2FYzpKaW6ZPCi95yPykRC2x0zr181l2LgLvzvr4bWFjAvrXyTuBiZrWAG4F1JQ0t57Zl/xb+/NWfuf/K+7nrZ3d5HUfKUXSHaGIGxNCyTksMo2WdlsQMiCG6Q7TX0cRjRZl183PgM2AtudMrASaSO04/D2gBpABDnHMHzKwpMMM518/MLiH3KB5yT/y+5Zwr9PBCs25K5rOdn9GlWRfNixapQHT1ygrg+KnjJOxJ4NqW13odRUQ8oKtXVgBjl4yl5+yebD+43esoIhJgVPQ+EJsUy6zkWUy8diKt6rXyOo6IBBgVfZBLSk1i7JKx9LmkD4/3eNzrOCISgFT0QSzzRCaD5w0mrFYYcbfF6WJlIlIgXb0yiIVWDeXXXX5N1+ZdCaulD5mJSMFU9EHqyMkjhFYNZfw1472OIiIBTkM3QWjFjhVEvBLBql2rvI4iIkFARR9kUjNTGT5/OGG1wmgf1t7rOCISBDR0E0ROZZ9i2PxhZJ7MZNn/LKN2tdpeRxKRIKCiDyITl03ks5TPiLstjsiGkV7HEZEgoaGbIJHjckg/ls6YqDHc2eFOr+OISBDREX2QqGSVmDVoFjkup/AHi4icRUf0Ae7YqWMM+ecQNqRvwMz0oSgRKTYVfQBzzvHA+w8QvyGelIwUr+OISJBS0Qew6UnTmbNmDo/1eIy+l/X1Oo6IBCkVfYBK3JPIrz/4NTdeeiN/vO6PXscRkSCmog9QL3z5Ag1rNdTFykSkxDTrJkDNuWUOKRkpNKjZwOsoIhLkdEQfYOI3xHPw+EGqValG64tbex1HRHxARR9Alm9fztD5Q3lq5VNeRxERH1HRB4jdh3czfP5w2lzchqdveNrrOCLiIyr6AHDmYmXHTh0jfmg8oVVDvY4kIj6ik7EB4JlPn+GL/37B3Nvn0i6snddxRMRnVPQB4IGrHqBRaCOGXT7M6ygi4kMauvHQ3iN7yc7JpnFoY8ZcNcbrOCLiUyp6jxw9eZQ+b/YhekG011FExOdU9B44c7Gy9WnrGdlppNdxRMTnNEbvgZjEGN789k2evP5J+lzax+s4IuJzOqIvZwl7EvjNh7+h72V9efS6R72OIyIVgIq+nBlG1+Zd+cet/6CS6e0XkbKnoZty4pzDzLiy6ZWsvGel13FEpALRIWU5mfzZZMZ9MI7snGyvo4hIBaOiLwcfb/uYxz55jH3H92m4RkTKnVqnjO06vIs74u+gXVg7Ym6Owcy8jiQiFYyKvgydzD7J0H8OJet0FvFD46lVtZbXkUSkAtLJ2DKUvDeZNd+v4Y1Bb9C2QVuv44hIBaWiL0NdmnXhP7/5D41DG3sdRUQqMA3dlIFN+zYxa/UsAJW8iHhOR/Sl7MjJI9w27zbSjqYxqO0g6teo73UkEangVPSlyDnHfYvvY2P6Rv71i3+p5EUkIKjoS9HUhKm8tfYtnun5DL0v6e11HBERQGP0pWbX4V2MXzqe/q3788i1j3gdR0Qkn47oS0nzi5ozf8h8urfork+/ikhAUSOVUI7LYV3aOgAGtBmgcXkRCTgq+hJ65tNn6DStU37Zi4gEmkKHbswsHJgDNAZygBjn3F/NrD7wDhAB7ACGOucOFrB/X+CvQGVghnPuuVJL74G4tXFMWjaJlIwUwmqFkXY0jbt+dheRYZFeRxMRKVBRjuhPAxOcc+2ArsBYM2sPPAwsc861Bpbl3f4BM6sMvArcBLQH7sjbNyjFrY1j9Huj2ZmxE4cj7WgahtEzoqcuViYiAavQonfOpTrnkvK+zgQ2As2AQcDsvIfNBm4pYPcuwFbn3Dbn3Elgbt5+QWnSskkcO3XsB9scjqdWPuVRIhGRwhVrjN7MIoBOwCqgkXMuFXJ/GAANC9ilGfDfs27vyttW0HOPNrMEM0tIT08vTqxyk5KRUqztIiKBoMhFb2ahQDzwoHPucFF3K2CbK+iBzrkY51yUcy4qLCysqLHKVYs6LYq1XUQkEBSp6M0shNySj3POLcjb/L2ZNcm7vwmQVsCuu4Dws243B/ZceFxvTe41mZohNX+wrWZITSb3muxRIhGRwhVa9JZ7ljEW2Oice/msuxYBd+d9fTewsIDdvwFam1krM6sKDM/bLyhFd4gmZkAMLeu0xDBa1mlJzIAYojtEex1NROSczLkCR1L+7wFmPwc+A9aSO70SYCK54/TzgBZACjDEOXfAzJqSO42yX97+/YBXyJ1eOdM5V+jhb1RUlEtISLigf5CISEVkZonOuaiC7it0Hr1z7nMKHmsH6FXA4/cA/c66vQRYUrSoIiJS2vTJWBERn1PRi4j4nIpeRMTnVPQiIj6nohcR8TkVvYiIz6noRUR8TkUvIuJzKnoREZ9T0YuI+JyKXkTE51T0IiI+p6IXEfE5Fb2IiM+p6EVEfE5FLyLicyp6ERGfU9GLiPicil5ExOdU9CIiPqeiFxHxORW9iIjPqehFRHxORS8i4nMqehERn1PRi4j4nIpeRMTnVPQiIj6nohcR8TkVvYiIz6noRUR8TkUvIuJzKnoREZ9T0YuI+JyKXkTE51T0IiI+p6IXEfE5Fb2IiM+p6EVEfE5FLyLicyp6ERGfU9GLiPicil5ExOdU9CIiPqeiFxHxORW9iIjPqehFRHxORS8i4nMqehERnzPnnNcZfsLM0oGdXucoRANgn9chfETvZ+nS+1m6guH9bOmcCyvojoAs+mBgZgnOuSivc/iF3s/SpfezdAX7+6mhGxERn1PRi4j4nIr+wsV4HcBn9H6WLr2fpSuo30+N0YuI+JyO6EVEfE5FLyLicyr6YjKzmWaWZmbrvM7iB2YWbmafmNlGM1tvZuO8zhSszKy6mX1tZmvy3ssnvc7kB2ZW2cxWm9lir7NcKBV98b0B9PU6hI+cBiY459oBXYGxZtbe40zB6gRwg3PuCqAj0NfMunobyRfGARu9DlESKvpics59ChzwOodfOOdSnXNJeV9nkvsfqpm3qYKTy3Uk72ZI3h/NtigBM2sO9AdmeJ2lJFT0EjDMLALoBKzyOErQyhtmSAbSgI+cc3ovS+YV4A9Ajsc5SkRFLwHBzEKBeOBB59xhr/MEK+dctnOuI9Ac6GJml3scKWiZ2c1AmnMu0essJaWiF8+ZWQi5JR/nnFvgdR4/cM4dAlag80kl0R0YaGY7gLnADWb2D28jXRgVvXjKzAyIBTY65172Ok8wM7MwM6ub93UNoDfwnaehgphz7hHnXHPnXAQwHFjunLvL41gXREVfTGb2NvAV0MbMdpnZSK8zBbnuwC/IPVpKzvvTz+tQQaoJ8ImZfQt8Q+4YfdBOCZTSo0sgiIj4nI7oRUR8TkUvIuJzKnoREZ9T0YuI+JyKXkTE51T0IiI+p6IXEfG5/wWxLoqSKufPbQAAAABJRU5ErkJggg==\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='green')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.xticks(x)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.yticks(y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 376, + "metadata": {}, + "outputs": [], + "source": [ + "labels = ['High', 'Low', 1234567, 'asdjsdjflskj']" + ] + }, + { + "cell_type": "code", + "execution_count": 382, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='red')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.xticks(x, labels)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.yticks(y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 385, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot([1,2,3,4], [1,4,9,16], 'b')\n", + "\n", + "#plt.axis([1,5,1,17])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 387, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot([1,2,3,4], [1,4,9,16], 'b')\n", + "\n", + "plt.axis([1,5,1,18])\n", + "plt.show()\n", + "# 왜 필요한지 모르겠음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### * 함수를 위한 그래프 그리기" + ] + }, + { + "cell_type": "code", + "execution_count": 388, + "metadata": {}, + "outputs": [], + "source": [ + "# 그래프의 중심을 특정 위치로 이동하려면 좌표출에 해당하는 spines를 이동해야 합니다. \n", + "# 이동할 때마다 spines 처리하지 않기 위해 하나의 함수 spines를 정의해서 사용합니다.\n", + "# spines는 4개의 좌표축을 가지므로 오른쪽과 위를 표시하지 않도록 색깔을 주지 않습니다. \n", + "# 아래와 좌측에만 좌표 측을 중심으로 이동하고 레이블을 지정합니다.\n", + "\n", + "def spines() :\n", + " ax = plt.gca() # 현재의 축 구하기\n", + " ax.spines['right'].set_color('none')\n", + " ax.spines['top'].set_color('none')\n", + "\n", + " ax.spines['bottom'].set_position(('data', 0))\n", + " ax.spines['left'].set_position(('data', 0))\n", + " \n", + " ax.xaxis.set_ticks_position('bottom')\n", + " ax.yaxis.set_ticks_position('left')" + ] + }, + { + "cell_type": "code", + "execution_count": 391, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = np.arange(-10, 13)\n", + "y = -3*x + 3\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 393, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 항등함수\n", + "\n", + "y = x\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3. 활성화 함수 그래프로 그려보기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">#### Quiz 2\n", + ">활성화 함수를 선형 함수로 사용하지 않는 이유를 적어주세요.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 397, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "## 계단함수\n", + "\n", + "def step(x) :\n", + " return np.where(x>0, 1, 0)\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = step(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 399, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 시그모이드 함수 : 자연상수를 지수로 사용해 작은 값과 큰 값을 특정 범위 내의 값으로 처리. 0과 1사이로 변환\n", + "\n", + "def sigmoid(x) :\n", + " return 1/(1 + np.exp(-x))\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = sigmoid(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 400, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 하이퍼볼릭 탄젠트 함수 : 자연상수를 분모에는 더하고 분자에는 빼는 구조. -1과 1사이의 값을 0을 중심으로 대칭형태로 변환\n", + "\n", + "def htan(x) :\n", + " return (np.exp(x) - np.exp(-x)) / (np.exp(x) + np.exp(-x))\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = htan(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 403, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 렐루 함수 : 입력값이 0보다 크면 그 값을 그대로 반환하고, 0보다 작거나 같으면 0으로 출력. \n", + "# 기울기의 미분을 역으로 전파 될 때 기울기의 값이 사라지는 것을 방지하기 위해 많이 사용됨.\n", + "\n", + "def relu(x) :\n", + " return np.maximum(0, x)\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = relu(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">#### Quiz 3\n", + ">역전파(Backpropagation)란 무엇이고 왜 딥러닝에서 왜 중요한가?" + ] + }, + { + "cell_type": "code", + "execution_count": 409, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 소프트맥스 함수 : 0보다 크고 1보다 작은 n개 노드 출력. n개별 확률값을 출력하여 분류를 구하는 출력층에 주로 사용.\n", + "\n", + "def softmax(x) :\n", + " return np.exp(x) / np.sum(np.exp(x))\n", + "\n", + "x = np.arange(1, 5)\n", + "y = softmax(x)\n", + "\n", + "np.sum(y) # 1입니다.\n", + "\n", + "ratio = y\n", + "labels = y\n", + "\n", + "plt.pie(ratio, labels=labels, shadow=True, startangle=90)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 부록" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "t = np.arange(0, 5, 0.01)\n", + "\n", + "plt.figure(figsize=(10, 12))\n", + "\n", + "plt.subplot(411)\n", + "plt.plot(t, np.sqrt(t))\n", + "plt.grid()\n", + "\n", + "plt.subplot(413)\n", + "plt.plot(t, np.sin(t))\n", + "plt.grid()\n", + "\n", + "plt.subplot(423)\n", + "plt.plot(t, t**2)\n", + "plt.grid()\n", + "\n", + "plt.subplot(424)\n", + "plt.plot(t, t**3)\n", + "plt.grid()\n", + "\n", + "plt.subplot(414)\n", + "plt.plot(t, np.cos(t))\n", + "plt.grid()\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "![matplotlib graphic](https://mblogthumb-phinf.pstatic.net/MjAxOTA0MjNfNjkg/MDAxNTU1OTkxMzkxNDQ0.JN62ph8P1qug3h5dPIkLFGl1hGinWVq95Bi0zfhYVqAg.4CyrOHysh2bIzbKs0AA1jIDTVIrhY7i7uQ1BfaDh8qwg.PNG.heygun/anatomy.png?type=w800)\n", + "

" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git "a/06\354\236\245/.ipynb_checkpoints/C6-7_summary-checkpoint.ipynb" "b/06\354\236\245/.ipynb_checkpoints/C6-7_summary-checkpoint.ipynb" new file mode 100644 index 0000000..915ec95 --- /dev/null +++ "b/06\354\236\245/.ipynb_checkpoints/C6-7_summary-checkpoint.ipynb" @@ -0,0 +1,3098 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Chapter 6. 넘파이 모듈의 자료형 이해하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 01. dtype으로 자료 객체 생성하기" + ] + }, + { + "cell_type": "code", + "execution_count": 468, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.19.2'" + ] + }, + "execution_count": 468, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "np.__version__" + ] + }, + { + "cell_type": "code", + "execution_count": 469, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.dtype" + ] + }, + "execution_count": 469, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 470, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,2,3,4,5], dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 471, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int32')" + ] + }, + "execution_count": 471, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 472, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ndarray" + ] + }, + "execution_count": 472, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(a)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 474, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "int" + ] + }, + "execution_count": 474, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b = 10\n", + "type(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 504, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 504, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.array([10])\n", + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 505, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,2,3,4,5], dtype='i8')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ℹ️ [참고. numpy dtypes](https://numpy.org/doc/stable/reference/arrays.dtypes.html)" + ] + }, + { + "cell_type": "code", + "execution_count": 506, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 506, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 480, + "metadata": {}, + "outputs": [], + "source": [ + "py_number = 12345\n", + "#np_number = np.int64(12345)\n", + "np_number = np.array([12345], dtype='int64')" + ] + }, + { + "cell_type": "code", + "execution_count": 481, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "int64\n" + ] + } + ], + "source": [ + "print(type(py_number))\n", + "print(np_number.dtype)" + ] + }, + { + "cell_type": "code", + "execution_count": 482, + "metadata": { + "collapsed": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__bool__',\n", + " '__ceil__',\n", + " '__class__',\n", + " '__delattr__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floor__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getnewargs__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__index__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__le__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__round__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__trunc__',\n", + " '__xor__',\n", + " 'as_integer_ratio',\n", + " 'bit_length',\n", + " 'conjugate',\n", + " 'denominator',\n", + " 'from_bytes',\n", + " 'imag',\n", + " 'numerator',\n", + " 'real',\n", + " 'to_bytes']" + ] + }, + "execution_count": 482, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(py_number)" + ] + }, + { + "cell_type": "code", + "execution_count": 465, + "metadata": { + "collapsed": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['T',\n", + " '__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__array__',\n", + " '__array_finalize__',\n", + " '__array_function__',\n", + " '__array_interface__',\n", + " '__array_prepare__',\n", + " '__array_priority__',\n", + " '__array_struct__',\n", + " '__array_ufunc__',\n", + " '__array_wrap__',\n", + " '__bool__',\n", + " '__class__',\n", + " '__complex__',\n", + " '__contains__',\n", + " '__copy__',\n", + " '__deepcopy__',\n", + " '__delattr__',\n", + " '__delitem__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getitem__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__iadd__',\n", + " '__iand__',\n", + " '__ifloordiv__',\n", + " '__ilshift__',\n", + " '__imatmul__',\n", + " '__imod__',\n", + " '__imul__',\n", + " '__index__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__ior__',\n", + " '__ipow__',\n", + " '__irshift__',\n", + " '__isub__',\n", + " '__iter__',\n", + " '__itruediv__',\n", + " '__ixor__',\n", + " '__le__',\n", + " '__len__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__matmul__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmatmul__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__setitem__',\n", + " '__setstate__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__xor__',\n", + " 'all',\n", + " 'any',\n", + " 'argmax',\n", + " 'argmin',\n", + " 'argpartition',\n", + " 'argsort',\n", + " 'astype',\n", + " 'base',\n", + " 'byteswap',\n", + " 'choose',\n", + " 'clip',\n", + " 'compress',\n", + " 'conj',\n", + " 'conjugate',\n", + " 'copy',\n", + " 'ctypes',\n", + " 'cumprod',\n", + " 'cumsum',\n", + " 'data',\n", + " 'diagonal',\n", + " 'dot',\n", + " 'dtype',\n", + " 'dump',\n", + " 'dumps',\n", + " 'fill',\n", + " 'flags',\n", + " 'flat',\n", + " 'flatten',\n", + " 'getfield',\n", + " 'imag',\n", + " 'item',\n", + " 'itemset',\n", + " 'itemsize',\n", + " 'max',\n", + " 'mean',\n", + " 'min',\n", + " 'nbytes',\n", + " 'ndim',\n", + " 'newbyteorder',\n", + " 'nonzero',\n", + " 'partition',\n", + " 'prod',\n", + " 'ptp',\n", + " 'put',\n", + " 'ravel',\n", + " 'real',\n", + " 'repeat',\n", + " 'reshape',\n", + " 'resize',\n", + " 'round',\n", + " 'searchsorted',\n", + " 'setfield',\n", + " 'setflags',\n", + " 'shape',\n", + " 'size',\n", + " 'sort',\n", + " 'squeeze',\n", + " 'std',\n", + " 'strides',\n", + " 'sum',\n", + " 'swapaxes',\n", + " 'take',\n", + " 'tobytes',\n", + " 'tofile',\n", + " 'tolist',\n", + " 'tostring',\n", + " 'trace',\n", + " 'transpose',\n", + " 'var',\n", + " 'view']" + ] + }, + "execution_count": 465, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(np_number)" + ] + }, + { + "cell_type": "code", + "execution_count": 483, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 483, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 489, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.99999999999998\n" + ] + } + ], + "source": [ + "py_result = 0\n", + "\n", + "for i in range(0, 100):\n", + " py_result += 0.1\n", + "\n", + "print(py_result)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ℹ️ [참고. 파이썬 부동 소수점 오차 해결](https://winterj.me/floating-point-in-python/)" + ] + }, + { + "cell_type": "code", + "execution_count": 490, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "float" + ] + }, + "execution_count": 490, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(py_result)" + ] + }, + { + "cell_type": "code", + "execution_count": 491, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[10.]\n" + ] + } + ], + "source": [ + "np_result = np.array([0], dtype='float64')\n", + "\n", + "for i in range(0, 100):\n", + " np_result += 0.1\n", + "\n", + "print(np_result)" + ] + }, + { + "cell_type": "code", + "execution_count": 492, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('float64')" + ] + }, + "execution_count": 492, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np_result.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([1,2,3,4,5], dtype=np.float32)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 2., 3., 4., 5.], dtype=float32)" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 515, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array(['ab', 'cd'], dtype=np.str)" + ] + }, + { + "cell_type": "code", + "execution_count": 516, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['ab', 'cd'], dtype=', , , , , , ]\n" + ] + } + ], + "source": [ + "print(np.float64.mro())" + ] + }, + { + "cell_type": "code", + "execution_count": 500, + "metadata": {}, + "outputs": [], + "source": [ + "import pprint" + ] + }, + { + "cell_type": "code", + "execution_count": 501, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ]\n" + ] + } + ], + "source": [ + "pprint.pprint(np.float64.mro())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 02. 날짜 자료형" + ] + }, + { + "cell_type": "code", + "execution_count": 521, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "# 넘파이는 np.datetime64와 timedelta64 두가지 모듈을 제공합니다. \n", + "\n", + "np.datetime64\n", + "print(np.datetime64)" + ] + }, + { + "cell_type": "code", + "execution_count": 524, + "metadata": { + "collapsed": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['T',\n", + " '__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__array__',\n", + " '__array_interface__',\n", + " '__array_priority__',\n", + " '__array_struct__',\n", + " '__array_wrap__',\n", + " '__bool__',\n", + " '__class__',\n", + " '__copy__',\n", + " '__deepcopy__',\n", + " '__delattr__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getitem__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__le__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__setstate__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__xor__',\n", + " 'all',\n", + " 'any',\n", + " 'argmax',\n", + " 'argmin',\n", + " 'argsort',\n", + " 'astype',\n", + " 'base',\n", + " 'byteswap',\n", + " 'choose',\n", + " 'clip',\n", + " 'compress',\n", + " 'conj',\n", + " 'conjugate',\n", + " 'copy',\n", + " 'cumprod',\n", + " 'cumsum',\n", + " 'data',\n", + " 'diagonal',\n", + " 'dtype',\n", + " 'dump',\n", + " 'dumps',\n", + " 'fill',\n", + " 'flags',\n", + " 'flat',\n", + " 'flatten',\n", + " 'getfield',\n", + " 'imag',\n", + " 'item',\n", + " 'itemset',\n", + " 'itemsize',\n", + " 'max',\n", + " 'mean',\n", + " 'min',\n", + " 'nbytes',\n", + " 'ndim',\n", + " 'newbyteorder',\n", + " 'nonzero',\n", + " 'prod',\n", + " 'ptp',\n", + " 'put',\n", + " 'ravel',\n", + " 'real',\n", + " 'repeat',\n", + " 'reshape',\n", + " 'resize',\n", + " 'round',\n", + " 'searchsorted',\n", + " 'setfield',\n", + " 'setflags',\n", + " 'shape',\n", + " 'size',\n", + " 'sort',\n", + " 'squeeze',\n", + " 'std',\n", + " 'strides',\n", + " 'sum',\n", + " 'swapaxes',\n", + " 'take',\n", + " 'tobytes',\n", + " 'tofile',\n", + " 'tolist',\n", + " 'tostring',\n", + " 'trace',\n", + " 'transpose',\n", + " 'var',\n", + " 'view']" + ] + }, + "execution_count": 524, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(np.datetime64)" + ] + }, + { + "cell_type": "code", + "execution_count": 526, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(numpy.datetime64('2018'), dtype('#### Quiz 1\n", + ">바이트 문자열이란?" + ] + }, + { + "cell_type": "code", + "execution_count": 601, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([['0', '1', '2', '3', '4'],\n", + " ['5', '6', '7', '8', '9']], dtype='" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 264, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n" + ] + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + " \n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 263, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n", + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + "ax = plt.axes()\n", + "print(ax)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 356, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1. , 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2. ,\n", + " 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1,\n", + " 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. , 4.1, 4.2,\n", + " 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5. , 5.1, 5.2, 5.3,\n", + " 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 6. , 6.1, 6.2, 6.3, 6.4,\n", + " 6.5, 6.6, 6.7, 6.8, 6.9, 7. , 7.1, 7.2, 7.3, 7.4, 7.5,\n", + " 7.6, 7.7, 7.8, 7.9, 8. , 8.1, 8.2, 8.3, 8.4, 8.5, 8.6,\n", + " 8.7, 8.8, 8.9, 9. , 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7,\n", + " 9.8, 9.9, 10. , 10.1, 10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 10.8,\n", + " 10.9, 11. , 11.1, 11.2, 11.3, 11.4, 11.5, 11.6, 11.7, 11.8, 11.9])" + ] + }, + "execution_count": 356, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.arange(1, 12, 0.1)\n", + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 357, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.84147098, 0.89120736, 0.93203909, 0.96355819, 0.98544973,\n", + " 0.99749499, 0.9995736 , 0.99166481, 0.97384763, 0.94630009,\n", + " 0.90929743, 0.86320937, 0.8084964 , 0.74570521, 0.67546318,\n", + " 0.59847214, 0.51550137, 0.42737988, 0.33498815, 0.23924933,\n", + " 0.14112001, 0.04158066, -0.05837414, -0.15774569, -0.2555411 ,\n", + " -0.35078323, -0.44252044, -0.52983614, -0.61185789, -0.68776616,\n", + " -0.7568025 , -0.81827711, -0.87157577, -0.91616594, -0.95160207,\n", + " -0.97753012, -0.993691 , -0.99992326, -0.99616461, -0.98245261,\n", + " -0.95892427, -0.92581468, -0.88345466, -0.83226744, -0.77276449,\n", + " -0.70554033, -0.63126664, -0.55068554, -0.46460218, -0.37387666,\n", + " -0.2794155 , -0.1821625 , -0.0830894 , 0.0168139 , 0.1165492 ,\n", + " 0.21511999, 0.31154136, 0.40484992, 0.49411335, 0.57843976,\n", + " 0.6569866 , 0.72896904, 0.79366786, 0.85043662, 0.8987081 ,\n", + " 0.93799998, 0.96791967, 0.98816823, 0.99854335, 0.99894134,\n", + " 0.98935825, 0.96988981, 0.94073056, 0.90217183, 0.85459891,\n", + " 0.79848711, 0.7343971 , 0.66296923, 0.58491719, 0.50102086,\n", + " 0.41211849, 0.31909836, 0.22288991, 0.12445442, 0.02477543,\n", + " -0.07515112, -0.17432678, -0.27176063, -0.36647913, -0.45753589,\n", + " -0.54402111, -0.62507065, -0.69987469, -0.76768581, -0.82782647,\n", + " -0.87969576, -0.92277542, -0.95663502, -0.98093623, -0.99543625,\n", + " -0.99999021, -0.99455259, -0.97917773, -0.95401925, -0.91932853,\n", + " -0.87545217, -0.82282859, -0.76198358, -0.69352508, -0.61813711])" + ] + }, + "execution_count": 357, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y = np.sin(x)\n", + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 327, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n", + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 1\n", + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + "ax = plt.axes()\n", + "print(ax)\n", + "\n", + "ax.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 328, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288) AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 2\n", + "fig, ax = plt.subplots(figsize=(8, 4))\n", + "print(fig, ax)\n", + "ax.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 329, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 3\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 330, + "metadata": {}, + "outputs": [], + "source": [ + "# 함수를 정의해 cos 함수의 값을 가지고 선그래프 그리기.\n", + "def plot_cos(x) :\n", + " y = np.cos(x)\n", + " plt.plot(x, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 331, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(8, 4))\n", + "ax1.plot(x, y)\n", + "ax2.plot(x, np.cos(x))\n", + "#ax2 = plot_cos(x)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 333, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10,4))\n", + "ax1 = fig.add_subplot(2, 1, 1)\n", + "ax1.plot(x, y)\n", + "ax2 = fig.add_subplot(2, 1, 2)\n", + "ax2.plot(x, np.cos(x))\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 334, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 컬러를 집어넣자\n", + "fig = plt.figure(figsize=(8, 4))\n", + "for i in np.arange(0.1, 1.2, 0.1):\n", + " x += i\n", + " plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 335, + "metadata": {}, + "outputs": [], + "source": [ + "# 선을 구별하자\n", + "linestyles = ['-', '--', '-.', ':', 'solid']\n", + "# 선에 음영처리 - pass" + ] + }, + { + "cell_type": "code", + "execution_count": 336, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "for i, j in enumerate(np.arange(0.1, 0.6, 0.1)):\n", + " x = x+j\n", + " plt.plot(x, y, ls=linestyles[i])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 340, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 마커 처리하기\n", + "x = np.arange(1, 8)\n", + "y = x\n", + "marker = ['+', 'o', '*', 's', '.']\n", + "\n", + "fig = plt.figure(figsize=(8, 4))\n", + "for i, j in enumerate(np.arange(0.3, 2.8, 0.5)):\n", + " x = x+j\n", + " plt.plot(x, y, marker=marker[i], markersize=8)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**[마커 모양 참조!](https://matplotlib.org/3.1.1/api/markers_api.html)**" + ] + }, + { + "cell_type": "code", + "execution_count": 349, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그래프 선과 색상을 문자열로 지정하기\n", + "t = np.arange(0., 5., 0.2)\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 352, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--', t, t**2, 'bs')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 354, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. 그래프 제목 / 레이블 / 범례 처리" + ] + }, + { + "cell_type": "code", + "execution_count": 368, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그래프에 설명 달기, title, 축 label, 그래프 label, 범례 추가\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.title('Salery')\n", + "plt.xlabel('years')\n", + "plt.ylabel('K/USD')\n", + "plt.plot(t, t, 'r--', label='Kim')\n", + "plt.plot(t, t**2, 'bs', label='Park')\n", + "plt.plot(t, t**3, 'g^', label='Me')\n", + "\n", + "plt.legend()\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 370, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 좌표에 레이블 부여하기\n", + "x = [1, 2, 3, 4]\n", + "y = [20, 21, 20.5, 20.8]\n", + "plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 372, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='green')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 381, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='green')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.xticks(x)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.yticks(y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 376, + "metadata": {}, + "outputs": [], + "source": [ + "labels = ['High', 'Low', 1234567, 'asdjsdjflskj']" + ] + }, + { + "cell_type": "code", + "execution_count": 382, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='red')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.xticks(x, labels)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.yticks(y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 385, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot([1,2,3,4], [1,4,9,16], 'b')\n", + "\n", + "#plt.axis([1,5,1,17])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 387, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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l1t3nmNkTwDxgEzAfGBZVMJFtzZgRGoV9+SU8+mj4WkR2LK9dNO7+O3dv5e5HuvsF7r4hqmAiEBqF/fGPcNppUFIS2g+ouItkR7elJLFWrgyNwqZMgfPPh/vugyZN4k4lUjhU4CWRXn0VuneHzz6De+8Ne93VS0akdnTWTxLFHYYMgfbtw7bHl18OT15ScRepPRV4SYy1a+FnP4NrroHTT4e5c8NedxHJjQq8JMLbb0NpKYwfDwMGhINMzZrFnUqksGkNXmL30EPhYRx77QUzZ4blGRHJn2bwEpv16+HnP4eLL4a2bUOjMBV3keiowEssFi+G446DESPg1lth+nRo3jzuVCLpoiUaqXfjx8Mll4RdMs8+C126xJ1IJJ00g5d68/XXcMMNcM450KpVaBSm4i5SdzSDl3qxZEnYAvnyy9CnT2gYtvPOcacSSTcVeKlz06eHB2F/9RWMGRMKvYjUPS3RSJ3ZvBn69YNOncIN1PJyFXeR+qQZvNSJigro1QumTQsNw+65R43CROqbCrxE7uWXQ6OwlSth2LCw1129ZETqn5ZoJDLucOed8OMfwy67wCuvwGWXqbiLxEUzeInEmjXQu3fY496tGzzwQGg9ICLxyWsGb2Z7mdkTZvaumb1jZsdFFUwKxxtvhEZhTz0Vtj+OH6/iLpIE+c7g7wKmuPu5ZrYz0DiCTFJARo6Eq66CvfeG55+HE06IO5GIbJXzDN7M9gDaAyMA3H2ju6+OKJck3JdfhnYDl14aivr8+SruIkmTzxLNIUAF8ICZzTez+81su41wZlZmZuVmVl5RUZHHx0lSvP9+6P740EPw29+GZ6buu2/cqUSksnwKfEPgGOAed/8R8AXQt/JF7j7M3UvdvbSkpCSPj5MkGDs2rLcvWwaTJ4eDTA0axJ1KRKqST4FfAixx9zmZ758gFHxJoY0b4dprw/72I44ISzKdOsWdSkR2JOcC7+7/AP5uZodnXjoFWBRJKkmUTz8Ne9vvuisU+RdegAMPjDuViNQk3100fYDRmR00HwGX5B9JkmTKlNByYOPGsDxz7rlxJxKRbOVV4N39DaA0miiSJFsbhf3xj/Af/xGK+2GHxZ1KRGpDJ1llOytWhPa+M2aErZB//jM01gkHkYKjAi//5qWXQkvfVavC81J79447kYjkSs3GBAiNwgYNgpNOCrP1V19VcRcpdJrBC6tXh6WYCRPC81JHjIA994w7lYjkSwW+yM2fH3bGfPppaPV7zTVq7yuSFlqiKVLuMHw4HHdc2AL5wgthj7uKu0h6qMAXoS++gIsvhrKycIBp3jxo1y7uVCISNRX4IvPee/Cf/wkPPwy//z1MmgRqESSSTlqDLyJ//Wt4Puquu8LUqXDaaXEnEpG6pBl8EdiwAfr0gR494Kijwo1VFXeR9FOBT7m//Q3atw+nUa+/Pjx1qUWLuFOJSH3QEk2KTZ4cGoVt2gTjxsFPfxp3IhGpT5rBp9CmTXDrrdClS2jrO3euirtIMdIMPmX+8Y/QKGzWrPC81Lvvht12izuViMRBBT5FZs8OjcLWrIEHHgh73UWkeGmJJgW2bIEBA6BDB2jaFObMUXEXkQgKvJk1MLP5ZjYxikBSO//8J3TrBrfcEtbZy8vDAzpERKKYwV8DvBPBnyO1NHcuHHNMeKzekCHhINMee8SdSkSSIq8Cb2YtgDOA+6OJI9nYvBn+8pfQP2bzZnjxxXCQSY3CRGRb+c7gBwM3A1uqu8DMysys3MzKKyoq8vy44vbll6GwH3YYXHVVWHOfPz/0lhERqSznAm9mZwIr3H3ujq5z92HuXurupSXqapWTlSvDA7APPjgU9n33DQeXnn0WvvWtuNOJSFLls03yeOAsM+sC7ArsYWaPuHuvaKLJhx/CHXeELY/r18NPfgI33wzHH6/lGBGpWc4zeHf/lbu3cPeWQA9gpop7NF5/Hbp3D0sx998PPXvCokXw9NNwwgkq7iKSHR10Sgj30Dvm9ttDQ7A99wyz9auvhv32izudiBSiSAq8uz8PPB/Fn1VsNm6Exx4LhX3hwtDpcdAguOyycGhJRCRXmsHHZO1aGDYMBg+GpUvD4aRRo0LP9kaN4k4nImmgAl/Pli6Fu+6C++4LRb5DBxgxAjp21Nq6iERLBb6eLFwIAwfC6NHhcFL37nDjjdC6ddzJRCStVODrkHvo8Hj77WHPeuPG8ItfwHXXwXe+E3c6EUk7Ffg6sHkzPPlk6PD4+utQUgJ/+ANceaUOJolI/VGBj9D69fDgg2EXzIcfwve+B/fcAxddpIduiEj9U4GPwMqVMHRoeLD1ypWhN8yAAdC1KzRoEHc6ESlWKvB5+Oij0Epg5MhvWgncdJNOm4pIMqjA56C8PNw4feKJMEO/4AK44Qb4wQ/iTiYi8g0V+Cy5hwdrDBjwTSuBm24KrQT23z/udCIi21OBr8HGjTBmTJixL1gQWgkMHBhaCejpSSKSZCrw1ajcSuDII0MrgZ/9DHbeOe50IiI1U4GvZNmy0Erg3nu/aSVw//3QqZNunIpIYVGBz1i0KCy9PPJIOKh03nlhjV2tBESkUBV1gXcPD6weMCC0EthtN7j88tBK4JBD4k4nIpKfoizwmzfDhAmhsL/2GuyzT3jm6ZVXhq9FRNKgqAr81lYCd9wBixfDd7+rVgIikl45F3gzOxAYBXwb2AIMc/e7ogoWpc8//6aVQEUFtGkTDil166ZWAiKSXvnM4DcBN7j7PDNrCsw1s+nuviiibHn7+OMwWx8xIszezzwz3Dg98UTtiBGR9Mu5wLv7cmB55ut1ZvYOcAAQe4Gv3EqgV6/wcA21EhCRYhLJGryZtQR+BMyp4r0yoAzgoIMOiuLjquQOU6eGG6ezZoVTpjfeGFoJHHBAnX2siEhi7ZTvH2BmuwPjgGvdfW3l9919mLuXuntpSUlJvh+3nY0bwwnTo4+G00+H998P+9n//nf4059U3EWkeOU1gzezRoTiPtrdx0cTKTtr18Lw4aGVwJIloZXAQw9Bjx5qJSAiAvntojFgBPCOu98RXaQdW7YMhgwJrQTWrIGTTw49Yzp31o1TEZFt5TODPx64AHjbzN7IvPZrd5+Ud6oqVG4lcO65YUdMaWldfJqISOHLZxfNS0Cdzpnd4aWXwo3TiRPDYaSyMrj+erUSEBGpSSJPsm5tJXD77TBnjloJiIjkIlEFfv36cKN00KBvWgn85S+hlUDjxnGnExEpLIko8J9/Hgr53XeHVgLHHgtjx8LZZ6uVgIhIrmIt8FtbCYwcCV9+CWecEW6ctm+vHTEiIvmKpcDPnRvW18eODTP0888Pp06POCKONCIi6VSvBX7tWjjlFJg5U60ERETqWr0W+A8+gC++CLP3yy6DPfesz08XESku5u7192Fm64D36u0Dc7cPsDLuEFlQzugUQkZQzqgVSs7D3b1pbX+ovtfg33P3xJ89NbNy5YxOIeQshIygnFErpJy5/Fze3SRFRCSZVOBFRFKqvgv8sHr+vFwpZ7QKIWchZATljFqqc9brTVYREak/WqIREUkpFXgRkZSKvMCb2UgzW2FmC6p538xsiJktNrO3zOyYqDNkI4ucJ5nZGjN7I/PrtzFkPNDMZpnZO2a20MyuqeKa2Mczy5xJGM9dzew1M3szk7NfFdckYTyzyRn7eGZyNDCz+WY2sYr3Yh/LbbLsKGcixjKT5RMzezuTY7utkbUeU3eP9BfQHjgGWFDN+12AyYSHhbQF5kSdIaKcJwET48i2TYb9gGMyXzcF3gd+kLTxzDJnEsbTgN0zXzcC5gBtEzie2eSMfTwzOa4HHq0qSxLGMsuciRjLTJZPgH128H6txjTyGby7zwZW7eCSrsAoD14F9jKz/aLOUZMscsbO3Ze7+7zM1+uAd4DKnXtiH88sc8YuM0b/ynzbKPOr8i6DJIxnNjljZ2YtgDOA+6u5JPaxhKxyFpJajWkca/AHAH/f5vslJLAYZByX+WvyZDOLtdelmbUEfkSYzW0rUeO5g5yQgPHM/FX9DWAFMN3dEzmeWeSE+MdzMHAzsKWa9xMxltScE+Ify60cmGZmc82srIr3azWmcRT4qjq9J252AswDDnb3o4G7gQlxBTGz3YFxwLXuvrby21X8SCzjWUPORIynu2929x8CLYA2ZnZkpUsSMZ5Z5Ix1PM3sTGCFu8/d0WVVvFavY5llzkT8u5lxvLsfA5wOXGVm7Su9X6sxjaPALwEO3Ob7FsCyGHLskLuv3frXZHefBDQys3p/IqyZNSIUzdHuPr6KSxIxnjXlTMp4bpNnNfA80LnSW4kYz62qy5mA8TweOMvMPgHGAB3M7JFK1yRhLGvMmYCx3DbLsszvK4AngTaVLqnVmMZR4J8GLszcDW4LrHH35THk2CEz+7ZZeK6UmbUhjNXn9ZzBgBHAO+5+RzWXxT6e2eRMyHiWmNlema93A04F3q10WRLGs8accY+nu//K3Vu4e0ugBzDT3XtVuiz2scwmZ9xjuU2OJmbWdOvXQEeg8i6/Wo1p5N0kzewxwl3pfcxsCfA7wk0i3P1eYBLhTvBi4EvgkqgzRJTzXOAKM9sErAd6eOY2dj06HrgAeDuzHgvwa+CgbXImYTyzyZmE8dwPeMjMGhD+I37c3Sea2S+2yZmE8cwmZxLGczsJHMsqJXQsmwNPZv5f0xB41N2n5DOmalUgIpJSOskqIpJSKvAiIimlAi8iklIq8CIiKaUCLyKSUirwIiIppQIvIpJS/w/EW5LQveYP5AAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot([1,2,3,4], [1,4,9,16], 'b')\n", + "\n", + "plt.axis([1,5,1,18])\n", + "plt.show()\n", + "# 왜 필요한지 모르겠음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### * 함수를 위한 그래프 그리기" + ] + }, + { + "cell_type": "code", + "execution_count": 388, + "metadata": {}, + "outputs": [], + "source": [ + "# 그래프의 중심을 특정 위치로 이동하려면 좌표출에 해당하는 spines를 이동해야 합니다. \n", + "# 이동할 때마다 spines 처리하지 않기 위해 하나의 함수 spines를 정의해서 사용합니다.\n", + "# spines는 4개의 좌표축을 가지므로 오른쪽과 위를 표시하지 않도록 색깔을 주지 않습니다. \n", + "# 아래와 좌측에만 좌표 측을 중심으로 이동하고 레이블을 지정합니다.\n", + "\n", + "def spines() :\n", + " ax = plt.gca() # 현재의 축 구하기\n", + " ax.spines['right'].set_color('none')\n", + " ax.spines['top'].set_color('none')\n", + "\n", + " ax.spines['bottom'].set_position(('data', 0))\n", + " ax.spines['left'].set_position(('data', 0))\n", + " \n", + " ax.xaxis.set_ticks_position('bottom')\n", + " ax.yaxis.set_ticks_position('left')" + ] + }, + { + "cell_type": "code", + "execution_count": 391, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = np.arange(-10, 13)\n", + "y = -3*x + 3\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 393, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 항등함수\n", + "\n", + "y = x\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3. 활성화 함수 그래프로 그려보기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">#### Quiz 2\n", + ">활성화 함수를 선형 함수로 사용하지 않는 이유를 적어주세요.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 397, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "## 계단함수\n", + "\n", + "def step(x) :\n", + " return np.where(x>0, 1, 0)\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = step(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 399, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 시그모이드 함수 : 자연상수를 지수로 사용해 작은 값과 큰 값을 특정 범위 내의 값으로 처리. 0과 1사이로 변환\n", + "\n", + "def sigmoid(x) :\n", + " return 1/(1 + np.exp(-x))\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = sigmoid(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 400, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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SusLt5R2oBWDRtHCVKxFCQlcMATn7a0kcP5oJgXLZr1CfhK5waxUNrZTVnWNxohzlCucgoSvcWu7BOjw0sEAu+xVOQkJX2FR+fj4xMTHo9XoyMzMv2f7mm2+SkJBAQkICs2bN4sCBA9ZtERERTJ06lcTERGbOnGmTerZ9Xsf1E8cQMnK4TV5PiG9LLkAXNmM2m1m5ciUFBQXodDqSkpJIS0tjypQp1jYTJ06kuLiYgIAAtm3bxk9+8hP27Nlj3V5YWEhQUJBN6qloaKXilJEf32C/x/4IcbXkSFfYTGlpKXq9nsjISLy9vUlPTycnJ6dPm1mzZhEQEABAcnIy1dXVdqvn35/XodHA/PixdnsPIa7WoEe6JSUlmEwmR9ViM0ajkaKiIrXLcDi1+11cXIxWq7XW0NraSnl5+YA1/eMf/yAxMdG63WQyMWvWLAAWLVrEokWL+t0vNzeXvLw8AJqamgZ8/bd3txM92oOyT3dTds29ck5qf9ZqcKU+p6SkDLxxsOezq/CseJsoLCxUuwRVqN3vTZs2KRkZGdbl9evXK6tWreq37fvvv69MnjxZOXPmjHVdTU2NoiiK0tDQoCQkJCjFxcWXfc/o6Oh+11c0nFMm/DJPef2jyqvogetQ+7NWg4v1ecBcleEFYTM6nY6qqirrcnV1NeHhl56qdfDgQR544AFycnIIDAy0rr/QNiQkhCVLllBaWnrNtWz9vF6GFoRTktAVNpOUlERFRQWVlZV0dXWRnZ1NWlpanzYnT57kjjvuYMOGDURHR1vXt7W10draap3fvn078fHx11zL1s/rmDkhgNBRctaCcC5y9oKwGa1Wy9q1a0lNTcVsNrN8+XLi4uJYt24dACtWrOCpp57i7NmzPPzww9Z99u7dS0NDA0uWLAGgp6eHe+65h/nz519THV+eNnKkvpX/WTTl8o2FcDAJXWFTBoMBg8HQZ92KFSus86+88gqvvPLKJftFRkb2OWf329j2eR0At8fLBRHC+cjwgnA7+Yfrue47oxnrL0MLwvlI6Aq3Ut3UzqGac8yPky/QhHOS0BVu5b3DDQCkSugKJyWhK9zKe4frmTx2JBFBchtH4ZwkdIXbOGM08cmJRubJUa5wYhK6wm3sKGtAUZDxXOHUJHSF28g/XM/4MT7y8Enh1CR0hVs419nNx1+cZX7cWHn4pHBqErrCLRQeOUWX2SL3WhBOT0JXuIXtZQ0EjRjGdeMD1C5FiEFJ6AqXZ+oxU3TkFHOnhOLhIUMLwrlJ6AqX9/GXZ2nrMjMvLlTtUoS4LAld4fK2H27Az9uTWZMCL99YCJVJ6AqXV1DWQMrkEIZpPdUuRYjLkls7CpdmMoPJaGLeFBlaEK5BjnSFS2vvVvDy1PC9ySFqlyLEFZHQFTaVn59PTEwMer2ezMzMS7YrisIjjzyCXq8nISGBffv2XfG+/WnvUUiODGTUcC+b9UEIe5LQFTZjNptZuXIl27Zto6ysjI0bN1JW1vfh59u2baOiooKKigpefvllHnrooSve95u+OGWk24Lc4Ea4FAldYTOlpaXo9XoiIyPx9vYmPT2dnJycPm1ycnK4//770Wg0JCcn09zcTF1d3RXt+03by+oBmBsr47nCdWgURRlwY3JystLU1OTAcmyju7sbL6+h989Ntfvd2tpKW1sbY8f2HnmeO3eOzs5OQkK+Hm+tqalhzJgx+Pj4AFBVVUVwcDDd3d2X3feClpYWmpubUUaG0t1cT1RkhP0752TU/qzV4Ep9Pnbs2HuKovT/ZFVFUQabXFJ0dLTaJahC7X5v2rRJycjIsC6vX79eWbVqVZ82BoNB2bVrl3X5tttuU/bu3XtF+16svqVDmfDLPMXbP9iGPXAdan/WanCxPg+Yq3LKmLAZnU5HVVWVdbm6uprw8PAratPV1XXZfS9WUNb7WB5Nd4etyhfCIWRMV9hMUlISFRUVVFZW0tXVRXZ2NmlpaX3apKWlsX79ehRFYffu3fj7+xMWFnZF+15se1kDE4P8wNxt724JYVNueaS7cOFCtUtQhdr91mq1rF27ltTUVMxmM8uXLycuLo5169YBsGLFCgwGA1u3bkWv1+Pr68vf//73Qfftz7nObkq+PMPyGydSPnq0o7rnVNT+rNXgLn0e9Is0YNCNzqqoqIiUlBS1y3C4odLv3AO1/MfGz/jXQzdwz7wbOHr0qNolOdxQ+awv5mJ9HvB2dzK8IFxO771zvUmUe+cKFyShK1yKqcdM4ZFTzIkNxVPunStckNuH7vPPP49Go+HMmTNql2J369atY/LkySQkJLBkyRKam5vVLsnmdh9vxGjqYV5cKPn5+VRWVl7VZcOurKqqiu9973vExsaybNkyXnrpJbVLchiz2cyDDz7oFuO6bh26VVVVFBQU8J3vfEftUhxixowZHDp0iIMHDxIdHc0zzzyjdkk2t/1wPb7eniRHBLBy5Up0Ot0VXzbs6rRaLS+88ALl5eX85S9/4c9//rPb9/mCl156yW3+jt06dB977DGee+65IfN02KSkJLTa3hNSkpOTqa6uVrki27JYFLaXNZASE8yBzz5Fr9fj5eV1xZcNu7qwsDCmT58OgK+vL7GxsdTU1Khclf1VV1fz73//mwULFqhdik24behu2bKFcePGMW3aNLVLUcVrr73G7bffrnYZNvVZVROnW02kxo2lpqaG8ePHW7fpdLohEUAX1NfX89lnn/Hd735X7VLs7mc/+xnPPfccHh7uEVcufZ7unDlzqK+vv2R9eno6ubm5bN++XYWq7GugPv/+97/H39/fOq/Varn33nsdXZ5d5R+qt947972KS89mHCr/ojEajfz2t7/lxRdfZNSoUWqXY1d5eXmEhIQwY8YMdu3apXY5NuHSobtjx45+17/22mtUVlZaj3Krq6uZPn06paWl1huquKqB+gy95zFmZWWRl5fHzp073SqEFEXhvcMN3KgPYtRwryu65NgddXd3c+eddzJnzhzuuOMOtcuxu48++ogtW7awdetW602Q7rvvPt544w21S7tmLh26A4mMjOTUqVPW5YiICPbu3UtQUJCKVdlfaWkpr7/+OsXFxfj6+qpdjk2V17VysrGdh1ImAV9fcgxYLxt+66231CzR7hRFISMjg9jYWL7//e+rXY5DPPPMM9YvhF988UV27Njh0oELbjymOxS99NJLtLa2MnfuXBITE1mxYoXaJdnMe4fr0Whgzvl75164bLi6uprY2FjuuuuuAS8bdhcfffQRGzZs4P333+eBBx4gMTGRrVu3ql2WuEpyGbAbced+z3/xA0YN92LTihv6rI+JiZHLgIcIF+uzXAYsXNeJM20cqW9lXpw8IUK4Pgld4fTeO9x7tkaqPAtNuAEJXeH08g/XExc+ivFj3OvLQTE0SegKp1bb3MFnJ5sxTA1TuxQhbEJCVzi1rZ/XAXB7vAwtCPcgoStsorGxkblz5xIVFcXcuXPp7ynSF98lKy4urs9dsp588knGjRtHYmJin1Ohth2qZ/LYkUQGj3BYX4SwJwldYROZmZnMnj2biooKZs+e3e+tFi++S9bu3bsvuUvWY489xv79+9m/fz8Gg4G6lg4+/aqJBTK0INyIhK6wiZycHJYuXQrA0qVLeffddy9pc/FdskaOHHnZu2Rt+7z3rAVDgoSucB+DXhxRUlKimEwmB5ZjG0ajkREjht4/R9Xs98KFC8nLy7MuL1q0iNzc3AHb19fX8+ijj/Laa6/h5+fH66+/Tn5+Pn5+fkRHR/Pwww/zpzIt7d0K/3tT37MWcnNzre/V1NTEpk2b7NMpJzYUf8ddqc8pKSkDXhwhV6S5EXv3e7A7nC1durTPkyoCAgL6HdeF3j+eW2+9lV/96lfWm7Y0NDQQFBSERqPhN7/5DScamvg4eAE/mx3No3OiBqxJrkgbOlyszwOGrlve8EbYx2B3OAsNDaWuro6wsDDq6uoICQnpt92Fu2Tde++9fe6SFRr69dVmDz74IPNWPY0SBAsS5KwF4V5kTFfYRFpaGllZWQBkZWWxePHiS9pcfJesn//853221dXVWec3b97MMH0y0aEj0IeMtG/hQjiYhK6widWrV1NQUEBUVBQFBQWsXr0agNraWgwGA9D3LlnfPDXsiSeeYOrUqSQkJPDerlKMw0NZMNX9748rhh4ZXhA2ERgYyM6dOy9ZHx4ebg3Wm266iYG+Q9iwYYN1/uUPvuTprUdYnCihK9yPHOkKp5Ozv5Zp40cTEeSndilC2JyErnAqX5wycrj2HIunyVGucE8SusKpbDlQi4cGFsoFEcJNSegKp6EoClv21zBrUhAho4arXY4QdiGhK5zGweoWTpxtJ02GFoQbk9AVTiNnfy3enh6kym0chRuT0BVOocdsIfdgLSkxwfj7eKldjhB2I6ErnMIHFac53Wrizhk6tUsRwq4kdIVTeHtvNYF+3tw2uf97NgjhLiR0heoa27rYUd7A968bh5en/EoK9ya/4UJ1Oftr6DYr/HCmDC0I9yehK1T39t5qpo7zZ/LYUWqXIoTdSegKVR2ubaGs7hw/kC/QxBAhoStU9fbearw9PeSOYmLIkNAVqunsNpOzv4a5U0IZ7eutdjlCOISErrCJxsZG5s6dS1RUFHPnzh3w+WgRERFMnTqVxMREZi55kKb2btKvH3/F+wvh6iR0hU1kZmYye/ZsKioqmD17NpmZmQO2LSwsZP/+/UQbMogM8uPGSUFXtb8QrkxCV9hETk4OS5cuBWDp0qW8++67g7Y/VNPCvpPN3Js8AQ8PzVXvL4Srksf1CJtoaGggLKz3HrhhYWGcOnWq33YajYZ58+bRNmUx2vHT+cF03VXtL4SrGzR0S0pKMJlMjqrFZoxGI0VFRWqX4XD27vd//ud/0tjYeMn6jIwMenp6+rz3N5cvWLNmDT7+gTxW2Ib5ixJe/9txpk2bdsX7A+Tm5pKXlwdAU1OTfNZDhCv1OSUlZeCNiqIMNrmkwsJCtUtQhZr9jo6OVmpraxVFUZTa2lolOjp6wLav7jquTPhlnrLqN88qa9asuer9v/m+Q9FQ/B13sT4PmKsypitsIi0tjaysLACysrJYvHjxJW3a2tpoOXeON/Z8xbRxo/h0x7vEx8df8f5CuAMJXWETq1evpqCggKioKAoKCli9ejUAtbW1GAwGoHfc9oY7HuD46TaO5P6VBQsWMH/+/EH3F8LdyBdpwiYCAwPZuXPnJevDw8PZunUrAJGRkcT/8DGqG9sp3ra+zx3FBtpfCHcjR7rCYfadbKK0spGMmyPlFo5iyJLffOEwfy3+En8fL9KTxqtdihCqkdAVDvHlaSPbyxq4/4YJ+A2TUS0xdEnoCof42wfH8fb0YOmsCLVLEUJVErrC7upbOnlnXw0/nKkjaMQwtcsRQlUSusLu/vR+BQoKP71lktqlCKE6CV1hVyfPtvOPT6r4UdJ4xo/xVbscIVQnoSvs6sWdx/D00PAft0WpXYoQTkFCV9hNRUMrmz+rYemsCEJHDVe7HCGcgoSusJs/FBzDz1vLiltlLFeICyR0hV18drKJbYfqybhpImP85PlnQlwgoStszmxR+J8thwkZOYwHbp6odjlCOBUJXWFzm/ZWcbC6hf82xDJyuJfa5QjhVCR0hU01t3fxXP4Rro8Yw+LEcLXLEcLpSOgKm3p++1HOdfbwu8VxaDQatcsRwulI6AqbOVDVzJt7TvLj5AnEho1SuxwhnJKErrCJ2obT/OD5XJS2Zj74yy9pamq6pM3Ro0dJTEy0TqNGjeLFF18E4Mknn2TcuHHWbRdufC6Eu5F77AmbWPaHd+j20bEh43o++lcVmZmZPPvss33axMTEsH//fgDMZjPjxo1jyZIl1u2PPfYYv/jFLxxZthAOJ0e64lv7+MszHNPouDMhmJujglm6dCnvvvvuoPvs3LmTSZMmMWHCBMcUKYST0CiKMuDGkpISxWQyObAc2zAajYwYMULtMhxOjX539Cj8+sMOTtXX8soPJjFM2/vl2aJFi8jNzR1wv2effZbo6Gjrke7rr79Ofn4+fn5+REdH8/DDDzNy5Mh+983NzSUvLw+ApqYmNm3aZONeOb+h+DvuSn1OSUkZ8FvkQUMXGHSjsyoqKiIlJUXtMhzO3v2eM2cO9fX11mUFDZ0z7kMJi6Nl85OcPbrXui0gIKDfcV2Arq4uwsPDOXz4MKGhoUDvk4KDgoLQaDT85je/oa6ujtdee+2yNcXExHD06NFv2TPXMxR/x12szwOGrozpiiu2Y8eOPstr36/g+e3H+PWCWNZsbqWuro6wsDDq6uoICQkZ8HW2bdvG9OnTrYEL9Jl/8MEHWbhwoe07IIQTkDFdcU3eP9LACwXH+H5iOBk3TSQtLY2srCwAsrKyWLx48YD7bty4kbvvvrvPurq6Ouv85s2biY+Pt0/hQqhMQldctS9PG3k0ez+xY0fxzB0JaDQaVq9eTUFBAVFRURQUFLB69WoAamtrMRgM1n3b29spKCjgjjvu6POaTzzxBFOnTiUhIYHCwkL++Mc/OrRPQjiKDC+Iq1Lb3MH9r5bi7enBX388Ax9vTwACAwPZuXPnJe3Dw8P7nHPr6+vL2bNnL2m3YcMG+xUthBORI11xxc4YTdz36h7OdXSTtfx6efyOENdAjnTFFWnp6Ob+V0upbe5gQ8Z3iR/nr3ZJQrgkOdIVl3WqtZO7X95NxalW1t03g6SIMWqXJITLkiNdMajKM23c/9oezrR28bf7Z5ISM/CpYEKIy5PQFQPaX9VMxuufoAAbf5JM4vjRapckhMuT0BWXUBSFDbu/4n/zygkZNYz1y68nMtg1Lr8UwtlJ6Io+jKYeVv/rIHkH67htcgh/uGsao33lwZJC2IqErrAqPHqKX28+RP25TlbfPpmf3ByJh4c8/UEIW5LQFZwxmngqt4wtB2rRh4xg00+TmTFBzlAQwh4kdIcwo6mHV3dV8rddxzH1mPnZnCgeSpnEMK2n2qUJ4bYkdIeg1s5uskurWFf8JWfbupgfN5ZfpMagD5Evy4SwNwndIeSrs21kffwVm/ZWYTT1MGtSIE/MnyynggnhQBK6bu5cZzdbD9bxzr4aSk80ovXQsDAhjIybIpmqk0t5hXA0CV03VNXYzvtHTrGjvIHdx8/SbVaIDPbj8dQY7pyuY6z/cLVLFGLIktB1cWaLwvHTRvZXNZPzuYlf73mf6qYOACKD/Vh+40RunxrGNJ0/Go2c/iWE2iR0XYSiKJw2mjhxpp1jDa0ca2jlSH0rh2taaOsyA+DnBTdFB7L8xoncGhPMJLmKTAinI6HrBLrNFprbuznbZuJ0a+/UcM5EXUsHtc2d1DR38NXZNtrPhyvAiGFaokJHcOcMHVPH+TNt/Giqy/Zy2/dmqtKHt99+myeffJLy8nJKS0uZObP/OvLz83n00Ucxm8088MAD1idMNDY28qMf/YgTJ04QERHBpk2bCAgIcGQXhHAICd1vsFgUzIqC2XJ+UhR6zAo9FkvvT7NC9/n5brMFU4+Frh4LXeben53d5t6px0Jnl5n2LjMd3Wbau3owdvZgNPVOLR3dnOvsprm9m9bOnn5rGTVcS/hoH8JH+5AcOYYJY3yZEORHdOhIwv2HXzJcUFuu3vBBfHw877zzDj/96U8HbGM2m1m5ciUFBQXodDqSkpJIS0tjypQpZGZmMnv2bFavXk1mZiaZmZk8++yzDuyBEI5hl9AtPnaa/5dXZl0e6DHvygALF2YVRenT5sLLXFirKBetO99WUaDTZMLrox3ntylYlK+3WywKigIWpXd978/egLXY6YHz3loPfL09GTFMa53GjhpOdOhI/H28CPD1ZswIb8b4ehM8cph1GjHMdf6fGBsbe9k2paWl6PV6IiMjAUhPTycnJ4cpU6aQk5NDUVERAEuXLiUlJUVCV7ilQf+qS0pKMJlMV/2iXzSZCfDo7rPuSo7BLm5z8UGcpp9GmvMzmovaX5jv8bHg7WXuXdacv1P7+e0e539q0KDRaKzLHpre1/C4MJ1f5+nR28bzwuQBnhoNWg/QevSu8/LoXfby6J338gRvD/D21DDMs/c1vmYBus5PF+nsndob4St6p6tlNBqtwaWW5uZmPv30U4xG4yXbiouL0Wq11hpbW1spLy+nqKiImpoajh49ytGjR4HeB1oO1Jfc3Fzy8vIAaGpqUr3PanCGz9rRXKnPKSkpA29UFGWwySUVFhaqXYIq7N3v2bNnK3FxcZdM7777rrXNrbfeqnzyySf97r9p0yYlIyPDurx+/Xpl1apViqIoir+/f5+2o0ePvqKaoqOjr7IX7mEo/o67WJ8HzFXX+ferUN2OHTu+1f46nY6qqirrcnV1NeHh4QCEhoZSV1dHWFgYdXV1hITIEyqEe5JnpAmHSUpKoqKigsrKSrq6usjOziYtLQ2AtLQ0srKyAMjKymLx4sVqliqE3UjoCpvYvHkzOp2OkpISFixYQGpqKtA7NmswGADQarWsXbuW1NRUYmNjueuuu4iLiwNg9erVFBQUEBUVRUFBgfVUMiHcjQwvCJtYsmQJS5YsuWR9eHg4W7dutS4bDAZrCF8sMDCQnTt32rVGIZyBHOkKIYQDSegKIYQDSegKIYQDSegKIYQDaZQBLtEVwhVoNJp8RVHmq12HEFdKQlcIIRxIhheEEMKBJHSFEMKBJHSFEMKBJHSFEMKBJHSFEMKB/j9SrSf/TzMC/gAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 하이퍼볼릭 탄젠트 함수 : 자연상수를 분모에는 더하고 분자에는 빼는 구조. -1과 1사이의 값을 0을 중심으로 대칭형태로 변환\n", + "\n", + "def htan(x) :\n", + " return (np.exp(x) - np.exp(-x)) / (np.exp(x) + np.exp(-x))\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = htan(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 403, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 렐루 함수 : 입력값이 0보다 크면 그 값을 그대로 반환하고, 0보다 작거나 같으면 0으로 출력. \n", + "# 기울기의 미분을 역으로 전파 될 때 기울기의 값이 사라지는 것을 방지하기 위해 많이 사용됨.\n", + "\n", + "def relu(x) :\n", + " return np.maximum(0, x)\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = relu(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">#### Quiz 3\n", + ">역전파(Backpropagation)란 무엇이고 왜 딥러닝에서 왜 중요한가?" + ] + }, + { + "cell_type": "code", + "execution_count": 409, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 소프트맥스 함수 : 0보다 크고 1보다 작은 n개 노드 출력. n개별 확률값을 출력하여 분류를 구하는 출력층에 주로 사용.\n", + "\n", + "def softmax(x) :\n", + " return np.exp(x) / np.sum(np.exp(x))\n", + "\n", + "x = np.arange(1, 5)\n", + "y = softmax(x)\n", + "\n", + "np.sum(y) # 1입니다.\n", + "\n", + "ratio = y\n", + "labels = y\n", + "\n", + "plt.pie(ratio, labels=labels, shadow=True, startangle=90)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 부록" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "t = np.arange(0, 5, 0.01)\n", + "\n", + "plt.figure(figsize=(10, 12))\n", + "\n", + "plt.subplot(411)\n", + "plt.plot(t, np.sqrt(t))\n", + "plt.grid()\n", + "\n", + "plt.subplot(413)\n", + "plt.plot(t, np.sin(t))\n", + "plt.grid()\n", + "\n", + "plt.subplot(423)\n", + "plt.plot(t, t**2)\n", + "plt.grid()\n", + "\n", + "plt.subplot(424)\n", + "plt.plot(t, t**3)\n", + "plt.grid()\n", + "\n", + "plt.subplot(414)\n", + "plt.plot(t, np.cos(t))\n", + "plt.grid()\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "![matplotlib graphic](https://mblogthumb-phinf.pstatic.net/MjAxOTA0MjNfNjkg/MDAxNTU1OTkxMzkxNDQ0.JN62ph8P1qug3h5dPIkLFGl1hGinWVq95Bi0zfhYVqAg.4CyrOHysh2bIzbKs0AA1jIDTVIrhY7i7uQ1BfaDh8qwg.PNG.heygun/anatomy.png?type=w800)\n", + "

" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git "a/06\354\236\245/6\354\236\245_7\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" "b/06\354\236\245/6\354\236\245_7\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" new file mode 100644 index 0000000..ab1e437 --- /dev/null +++ "b/06\354\236\245/6\354\236\245_7\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" @@ -0,0 +1,19 @@ +Quiz 1. 바이트 문자열이란? +컴퓨터에 인식하게 메모리에 저장하기 위해 인코딩을 해야합니다. 즉, 바이트로 변환해야 하는 문자열입니다. +b'abcd'형태로 나온다면 ascii로 인코딩한것. + + +Quiz 2. 활성화 함수를 선형 함수로 사용하지 않는 이유는 무엇인가요? +선형함수를 사용할 시 층을 깊게 하는 의미가 줄어들기 때문 +선형함수인 h(x)=cx를 활성화함수로 사용한 3개의 레이어 층을 쌓으면 +y(x)=h(h(h(x))), y(x)=ax. a=c3 +즉, 은닉층이 없는 네트워크로 표현할 수 있습니다. 뉴럴네트워크에서 층을 쌓는 혜택을 얻고 싶다면 활성화함수로는 반드시 비선형 함수를 사용해야 합니다. + + +Quiz 3. 역전파(Backpropagation)란 무엇이고 왜 딥러닝에서 왜 중요한가요? +역전파 알고리즘은 input과 output 값을 알고 있는 상태에서 신경망을 학습 시키는 방법이다. +이 방법을 Supervised learning(지도학습)이라고 한다. 초기 가중치, weight 값은 랜덤으로 주어지고 +각각 노드들은 하나의 퍼셉트론으로, 노드를 지날때 마다 활성함수를 적용한다. + +딥러닝에서 역전파는 어떤 가중치(w)와 bias를 바꿀때 비용함수가 얼마나 빠르게 바뀌는지를 보여줌. +결국 경사하강법으로 에러를 0에 가까워지도록 하기 위한 자세한 식견을 보여줍니다. \ No newline at end of file diff --git "a/06\354\236\245/C6-7_summary-Copy1.ipynb" "b/06\354\236\245/C6-7_summary-Copy1.ipynb" new file mode 100644 index 0000000..915ec95 --- /dev/null +++ "b/06\354\236\245/C6-7_summary-Copy1.ipynb" @@ -0,0 +1,3098 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Chapter 6. 넘파이 모듈의 자료형 이해하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 01. dtype으로 자료 객체 생성하기" + ] + }, + { + "cell_type": "code", + "execution_count": 468, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.19.2'" + ] + }, + "execution_count": 468, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "np.__version__" + ] + }, + { + "cell_type": "code", + "execution_count": 469, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.dtype" + ] + }, + "execution_count": 469, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 470, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,2,3,4,5], dtype=np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 471, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int32')" + ] + }, + "execution_count": 471, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 472, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ndarray" + ] + }, + "execution_count": 472, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(a)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 474, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "int" + ] + }, + "execution_count": 474, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b = 10\n", + "type(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 504, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 504, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.array([10])\n", + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 505, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,2,3,4,5], dtype='i8')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ℹ️ [참고. numpy dtypes](https://numpy.org/doc/stable/reference/arrays.dtypes.html)" + ] + }, + { + "cell_type": "code", + "execution_count": 506, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 506, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 480, + "metadata": {}, + "outputs": [], + "source": [ + "py_number = 12345\n", + "#np_number = np.int64(12345)\n", + "np_number = np.array([12345], dtype='int64')" + ] + }, + { + "cell_type": "code", + "execution_count": 481, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "int64\n" + ] + } + ], + "source": [ + "print(type(py_number))\n", + "print(np_number.dtype)" + ] + }, + { + "cell_type": "code", + "execution_count": 482, + "metadata": { + "collapsed": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__bool__',\n", + " '__ceil__',\n", + " '__class__',\n", + " '__delattr__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floor__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getnewargs__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__index__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__le__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__round__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__trunc__',\n", + " '__xor__',\n", + " 'as_integer_ratio',\n", + " 'bit_length',\n", + " 'conjugate',\n", + " 'denominator',\n", + " 'from_bytes',\n", + " 'imag',\n", + " 'numerator',\n", + " 'real',\n", + " 'to_bytes']" + ] + }, + "execution_count": 482, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(py_number)" + ] + }, + { + "cell_type": "code", + "execution_count": 465, + "metadata": { + "collapsed": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['T',\n", + " '__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__array__',\n", + " '__array_finalize__',\n", + " '__array_function__',\n", + " '__array_interface__',\n", + " '__array_prepare__',\n", + " '__array_priority__',\n", + " '__array_struct__',\n", + " '__array_ufunc__',\n", + " '__array_wrap__',\n", + " '__bool__',\n", + " '__class__',\n", + " '__complex__',\n", + " '__contains__',\n", + " '__copy__',\n", + " '__deepcopy__',\n", + " '__delattr__',\n", + " '__delitem__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getitem__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__iadd__',\n", + " '__iand__',\n", + " '__ifloordiv__',\n", + " '__ilshift__',\n", + " '__imatmul__',\n", + " '__imod__',\n", + " '__imul__',\n", + " '__index__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__ior__',\n", + " '__ipow__',\n", + " '__irshift__',\n", + " '__isub__',\n", + " '__iter__',\n", + " '__itruediv__',\n", + " '__ixor__',\n", + " '__le__',\n", + " '__len__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__matmul__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmatmul__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__setitem__',\n", + " '__setstate__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__xor__',\n", + " 'all',\n", + " 'any',\n", + " 'argmax',\n", + " 'argmin',\n", + " 'argpartition',\n", + " 'argsort',\n", + " 'astype',\n", + " 'base',\n", + " 'byteswap',\n", + " 'choose',\n", + " 'clip',\n", + " 'compress',\n", + " 'conj',\n", + " 'conjugate',\n", + " 'copy',\n", + " 'ctypes',\n", + " 'cumprod',\n", + " 'cumsum',\n", + " 'data',\n", + " 'diagonal',\n", + " 'dot',\n", + " 'dtype',\n", + " 'dump',\n", + " 'dumps',\n", + " 'fill',\n", + " 'flags',\n", + " 'flat',\n", + " 'flatten',\n", + " 'getfield',\n", + " 'imag',\n", + " 'item',\n", + " 'itemset',\n", + " 'itemsize',\n", + " 'max',\n", + " 'mean',\n", + " 'min',\n", + " 'nbytes',\n", + " 'ndim',\n", + " 'newbyteorder',\n", + " 'nonzero',\n", + " 'partition',\n", + " 'prod',\n", + " 'ptp',\n", + " 'put',\n", + " 'ravel',\n", + " 'real',\n", + " 'repeat',\n", + " 'reshape',\n", + " 'resize',\n", + " 'round',\n", + " 'searchsorted',\n", + " 'setfield',\n", + " 'setflags',\n", + " 'shape',\n", + " 'size',\n", + " 'sort',\n", + " 'squeeze',\n", + " 'std',\n", + " 'strides',\n", + " 'sum',\n", + " 'swapaxes',\n", + " 'take',\n", + " 'tobytes',\n", + " 'tofile',\n", + " 'tolist',\n", + " 'tostring',\n", + " 'trace',\n", + " 'transpose',\n", + " 'var',\n", + " 'view']" + ] + }, + "execution_count": 465, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(np_number)" + ] + }, + { + "cell_type": "code", + "execution_count": 483, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 483, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 489, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.99999999999998\n" + ] + } + ], + "source": [ + "py_result = 0\n", + "\n", + "for i in range(0, 100):\n", + " py_result += 0.1\n", + "\n", + "print(py_result)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ℹ️ [참고. 파이썬 부동 소수점 오차 해결](https://winterj.me/floating-point-in-python/)" + ] + }, + { + "cell_type": "code", + "execution_count": 490, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "float" + ] + }, + "execution_count": 490, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(py_result)" + ] + }, + { + "cell_type": "code", + "execution_count": 491, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[10.]\n" + ] + } + ], + "source": [ + "np_result = np.array([0], dtype='float64')\n", + "\n", + "for i in range(0, 100):\n", + " np_result += 0.1\n", + "\n", + "print(np_result)" + ] + }, + { + "cell_type": "code", + "execution_count": 492, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('float64')" + ] + }, + "execution_count": 492, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np_result.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([1,2,3,4,5], dtype=np.float32)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 2., 3., 4., 5.], dtype=float32)" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 515, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array(['ab', 'cd'], dtype=np.str)" + ] + }, + { + "cell_type": "code", + "execution_count": 516, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['ab', 'cd'], dtype=', , , , , , ]\n" + ] + } + ], + "source": [ + "print(np.float64.mro())" + ] + }, + { + "cell_type": "code", + "execution_count": 500, + "metadata": {}, + "outputs": [], + "source": [ + "import pprint" + ] + }, + { + "cell_type": "code", + "execution_count": 501, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ]\n" + ] + } + ], + "source": [ + "pprint.pprint(np.float64.mro())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 02. 날짜 자료형" + ] + }, + { + "cell_type": "code", + "execution_count": 521, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "# 넘파이는 np.datetime64와 timedelta64 두가지 모듈을 제공합니다. \n", + "\n", + "np.datetime64\n", + "print(np.datetime64)" + ] + }, + { + "cell_type": "code", + "execution_count": 524, + "metadata": { + "collapsed": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['T',\n", + " '__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__array__',\n", + " '__array_interface__',\n", + " '__array_priority__',\n", + " '__array_struct__',\n", + " '__array_wrap__',\n", + " '__bool__',\n", + " '__class__',\n", + " '__copy__',\n", + " '__deepcopy__',\n", + " '__delattr__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getitem__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__le__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__setstate__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__xor__',\n", + " 'all',\n", + " 'any',\n", + " 'argmax',\n", + " 'argmin',\n", + " 'argsort',\n", + " 'astype',\n", + " 'base',\n", + " 'byteswap',\n", + " 'choose',\n", + " 'clip',\n", + " 'compress',\n", + " 'conj',\n", + " 'conjugate',\n", + " 'copy',\n", + " 'cumprod',\n", + " 'cumsum',\n", + " 'data',\n", + " 'diagonal',\n", + " 'dtype',\n", + " 'dump',\n", + " 'dumps',\n", + " 'fill',\n", + " 'flags',\n", + " 'flat',\n", + " 'flatten',\n", + " 'getfield',\n", + " 'imag',\n", + " 'item',\n", + " 'itemset',\n", + " 'itemsize',\n", + " 'max',\n", + " 'mean',\n", + " 'min',\n", + " 'nbytes',\n", + " 'ndim',\n", + " 'newbyteorder',\n", + " 'nonzero',\n", + " 'prod',\n", + " 'ptp',\n", + " 'put',\n", + " 'ravel',\n", + " 'real',\n", + " 'repeat',\n", + " 'reshape',\n", + " 'resize',\n", + " 'round',\n", + " 'searchsorted',\n", + " 'setfield',\n", + " 'setflags',\n", + " 'shape',\n", + " 'size',\n", + " 'sort',\n", + " 'squeeze',\n", + " 'std',\n", + " 'strides',\n", + " 'sum',\n", + " 'swapaxes',\n", + " 'take',\n", + " 'tobytes',\n", + " 'tofile',\n", + " 'tolist',\n", + " 'tostring',\n", + " 'trace',\n", + " 'transpose',\n", + " 'var',\n", + " 'view']" + ] + }, + "execution_count": 524, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(np.datetime64)" + ] + }, + { + "cell_type": "code", + "execution_count": 526, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(numpy.datetime64('2018'), dtype('#### Quiz 1\n", + ">바이트 문자열이란?" + ] + }, + { + "cell_type": "code", + "execution_count": 601, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([['0', '1', '2', '3', '4'],\n", + " ['5', '6', '7', '8', '9']], dtype='" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 264, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n" + ] + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + " \n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 263, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n", + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + "ax = plt.axes()\n", + "print(ax)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 356, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1. , 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2. ,\n", + " 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1,\n", + " 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. , 4.1, 4.2,\n", + " 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5. , 5.1, 5.2, 5.3,\n", + " 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 6. , 6.1, 6.2, 6.3, 6.4,\n", + " 6.5, 6.6, 6.7, 6.8, 6.9, 7. , 7.1, 7.2, 7.3, 7.4, 7.5,\n", + " 7.6, 7.7, 7.8, 7.9, 8. , 8.1, 8.2, 8.3, 8.4, 8.5, 8.6,\n", + " 8.7, 8.8, 8.9, 9. , 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7,\n", + " 9.8, 9.9, 10. , 10.1, 10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 10.8,\n", + " 10.9, 11. , 11.1, 11.2, 11.3, 11.4, 11.5, 11.6, 11.7, 11.8, 11.9])" + ] + }, + "execution_count": 356, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.arange(1, 12, 0.1)\n", + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 357, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.84147098, 0.89120736, 0.93203909, 0.96355819, 0.98544973,\n", + " 0.99749499, 0.9995736 , 0.99166481, 0.97384763, 0.94630009,\n", + " 0.90929743, 0.86320937, 0.8084964 , 0.74570521, 0.67546318,\n", + " 0.59847214, 0.51550137, 0.42737988, 0.33498815, 0.23924933,\n", + " 0.14112001, 0.04158066, -0.05837414, -0.15774569, -0.2555411 ,\n", + " -0.35078323, -0.44252044, -0.52983614, -0.61185789, -0.68776616,\n", + " -0.7568025 , -0.81827711, -0.87157577, -0.91616594, -0.95160207,\n", + " -0.97753012, -0.993691 , -0.99992326, -0.99616461, -0.98245261,\n", + " -0.95892427, -0.92581468, -0.88345466, -0.83226744, -0.77276449,\n", + " -0.70554033, -0.63126664, -0.55068554, -0.46460218, -0.37387666,\n", + " -0.2794155 , -0.1821625 , -0.0830894 , 0.0168139 , 0.1165492 ,\n", + " 0.21511999, 0.31154136, 0.40484992, 0.49411335, 0.57843976,\n", + " 0.6569866 , 0.72896904, 0.79366786, 0.85043662, 0.8987081 ,\n", + " 0.93799998, 0.96791967, 0.98816823, 0.99854335, 0.99894134,\n", + " 0.98935825, 0.96988981, 0.94073056, 0.90217183, 0.85459891,\n", + " 0.79848711, 0.7343971 , 0.66296923, 0.58491719, 0.50102086,\n", + " 0.41211849, 0.31909836, 0.22288991, 0.12445442, 0.02477543,\n", + " -0.07515112, -0.17432678, -0.27176063, -0.36647913, -0.45753589,\n", + " -0.54402111, -0.62507065, -0.69987469, -0.76768581, -0.82782647,\n", + " -0.87969576, -0.92277542, -0.95663502, -0.98093623, -0.99543625,\n", + " -0.99999021, -0.99455259, -0.97917773, -0.95401925, -0.91932853,\n", + " -0.87545217, -0.82282859, -0.76198358, -0.69352508, -0.61813711])" + ] + }, + "execution_count": 357, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y = np.sin(x)\n", + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 327, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n", + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 1\n", + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + "ax = plt.axes()\n", + "print(ax)\n", + "\n", + "ax.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 328, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288) AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 2\n", + "fig, ax = plt.subplots(figsize=(8, 4))\n", + "print(fig, ax)\n", + "ax.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 329, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 3\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 330, + "metadata": {}, + "outputs": [], + "source": [ + "# 함수를 정의해 cos 함수의 값을 가지고 선그래프 그리기.\n", + "def plot_cos(x) :\n", + " y = np.cos(x)\n", + " plt.plot(x, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 331, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(8, 4))\n", + "ax1.plot(x, y)\n", + "ax2.plot(x, np.cos(x))\n", + "#ax2 = plot_cos(x)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 333, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10,4))\n", + "ax1 = fig.add_subplot(2, 1, 1)\n", + "ax1.plot(x, y)\n", + "ax2 = fig.add_subplot(2, 1, 2)\n", + "ax2.plot(x, np.cos(x))\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 334, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 컬러를 집어넣자\n", + "fig = plt.figure(figsize=(8, 4))\n", + "for i in np.arange(0.1, 1.2, 0.1):\n", + " x += i\n", + " plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 335, + "metadata": {}, + "outputs": [], + "source": [ + "# 선을 구별하자\n", + "linestyles = ['-', '--', '-.', ':', 'solid']\n", + "# 선에 음영처리 - pass" + ] + }, + { + "cell_type": "code", + "execution_count": 336, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "for i, j in enumerate(np.arange(0.1, 0.6, 0.1)):\n", + " x = x+j\n", + " plt.plot(x, y, ls=linestyles[i])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 340, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 마커 처리하기\n", + "x = np.arange(1, 8)\n", + "y = x\n", + "marker = ['+', 'o', '*', 's', '.']\n", + "\n", + "fig = plt.figure(figsize=(8, 4))\n", + "for i, j in enumerate(np.arange(0.3, 2.8, 0.5)):\n", + " x = x+j\n", + " plt.plot(x, y, marker=marker[i], markersize=8)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**[마커 모양 참조!](https://matplotlib.org/3.1.1/api/markers_api.html)**" + ] + }, + { + "cell_type": "code", + "execution_count": 349, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그래프 선과 색상을 문자열로 지정하기\n", + "t = np.arange(0., 5., 0.2)\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 352, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--', t, t**2, 'bs')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 354, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. 그래프 제목 / 레이블 / 범례 처리" + ] + }, + { + "cell_type": "code", + "execution_count": 368, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그래프에 설명 달기, title, 축 label, 그래프 label, 범례 추가\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.title('Salery')\n", + "plt.xlabel('years')\n", + "plt.ylabel('K/USD')\n", + "plt.plot(t, t, 'r--', label='Kim')\n", + "plt.plot(t, t**2, 'bs', label='Park')\n", + "plt.plot(t, t**3, 'g^', label='Me')\n", + "\n", + "plt.legend()\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 370, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 좌표에 레이블 부여하기\n", + "x = [1, 2, 3, 4]\n", + "y = [20, 21, 20.5, 20.8]\n", + "plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 372, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='green')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 381, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='green')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.xticks(x)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.yticks(y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 376, + "metadata": {}, + "outputs": [], + "source": [ + "labels = ['High', 'Low', 1234567, 'asdjsdjflskj']" + ] + }, + { + "cell_type": "code", + "execution_count": 382, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='red')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.xticks(x, labels)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.yticks(y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 385, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot([1,2,3,4], [1,4,9,16], 'b')\n", + "\n", + "#plt.axis([1,5,1,17])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 387, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot([1,2,3,4], [1,4,9,16], 'b')\n", + "\n", + "plt.axis([1,5,1,18])\n", + "plt.show()\n", + "# 왜 필요한지 모르겠음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### * 함수를 위한 그래프 그리기" + ] + }, + { + "cell_type": "code", + "execution_count": 388, + "metadata": {}, + "outputs": [], + "source": [ + "# 그래프의 중심을 특정 위치로 이동하려면 좌표출에 해당하는 spines를 이동해야 합니다. \n", + "# 이동할 때마다 spines 처리하지 않기 위해 하나의 함수 spines를 정의해서 사용합니다.\n", + "# spines는 4개의 좌표축을 가지므로 오른쪽과 위를 표시하지 않도록 색깔을 주지 않습니다. \n", + "# 아래와 좌측에만 좌표 측을 중심으로 이동하고 레이블을 지정합니다.\n", + "\n", + "def spines() :\n", + " ax = plt.gca() # 현재의 축 구하기\n", + " ax.spines['right'].set_color('none')\n", + " ax.spines['top'].set_color('none')\n", + "\n", + " ax.spines['bottom'].set_position(('data', 0))\n", + " ax.spines['left'].set_position(('data', 0))\n", + " \n", + " ax.xaxis.set_ticks_position('bottom')\n", + " ax.yaxis.set_ticks_position('left')" + ] + }, + { + "cell_type": "code", + "execution_count": 391, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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2sxovEzCzScAkgISEhBCOI+KdnYdPMHV+Jivz9nF2QlWhWO+OKhST0PP8g1fn3CxgFkBKSorzeByRoPL5HG9+uY0ZS3NxwMPXJnH7uSoUk7oTypDfa2bx/qP4eKAwhGuJhJ3N+46Rlp7JV1sP8qM+7Xl87GC6t1WhmNStUIb8QmACMMP/dUEI1xIJGxWVPl7+ZAvPLt9Akwb1eOr6ZK4f2k2VBOKJYF1C+VeqPmRtb2YFwENUhfscM5sIbAduCMZaIuEse9cRUtMzyNp5lFEDO/PomIF0jFOhmHgnWFfX3HySXZcF4/lFwl1JeSXPf7iRl/5nM22aNeIPt57NlYPjvR5LxPsPXkUi3ZptB5k8N4NN+44z/uxuPHjNAFo3U6GYhAeFvEgtHS+t4KllecxetZUurZoy++7hXNS3g9djifwLhbxILXy8YR9T5mWy68gJ7jinB/eP6k+LxvrjJOFH70qR03C4uIzHFq9n7poCenVozpx7zmVYYluvxxI5KYW8yClamrmbBxdkc6i4jJ9ffAa/vEyFYhL+FPIiP6CwqISHFmSzNGsPSfEt+dNdwxjUtZXXY4mcEoW8yEk455i7poBpi3IoqfCpUEwikkJepAY7Dhbz6/mZfLJxPyk92jBjfDK9O7bweiyR06aQF6nG53O8sWorM5flYcCjowdy24ge1FOhmEQohbyIX35hEanpmazZdogL+3bg8bGD6NZGhWIS2RTyEvPKK33M+ngzzy3fSNNG9Xn6hjMZd3ZXFYpJVFDIS0zL2nmEyXMzyNl9lKsHx/PwdQPpENfY67FEgkYhLzGppLyS51ZsZNbHm2nbvBEv3TaUUYM6ez2WSNAp5CXmfL31IKlzM9i8/zg3pnRj6lVJtGrW0OuxREJCIS8x41hpBTP/nssbq7bRrU1T/jJxBBf0ae/1WCIhpZCXmLAyr5Cp87PYdeQEd52fyH//uB/NVSgmMUDvcolqh46XMW1xDvO+2Unvji2Ye+95DO3RxuuxROqMQl6iknOOJZl7eGhhFoeLy/nlpb2579LeNG6gQjGJLQp5iTqFR0t44N0s3s/Zy+CurXjj7hEkdWnp9VginlDIS9RwzvG31QVMW5xDWYWPKVf2Z+IFPWmgQjGJYQp5iQo7DhYzZV4mn+bvZ3jPtswYN5heHVQoJhLykDezUcBzQH3gFefcjFCvKbGj0ueY/flWnlqWR/16xmNjBnHL8AQVion4hTTkzaw+8AJwOVAAfG1mC51zOaFcV2LDxr1FpKZn8M32w1zcrwOPjx1Ml9ZNvR5LJKyE+kh+OJDvnNsMYGZvA6MBhbzUWnmlj5dWbuL5D/Np3rg+v/vJEEYP6aJCMZEahDrkuwI7qt0vAEZUf4CZTQImASQkJIR4HIl0GQWHmTw3g9w9RVyTXFUo1r6FCsVETibUIV/ToZX7lzvOzQJmAaSkpLgaHi9CSXklz36wgZc/2UyHuMa8fEcKlyd18noskbAX6pAvALpXu98N2BXiNSXKfLH5AGnpGWw9UMzNw7uTduUAWjVVoZjIqQh1yH8N9DGznsBO4CbglhCvKVGiqKScGUtzefPL7SS0bcZbPx3Beb1VKCZyOkIa8s65CjP7BbCMqksoX3POZYdyTYkOH+buZer8LPYeLeGnF/TkP3/cl2aN9GMdIqcr5H9qnHNLgCWhXkeiw8HjZTz6Xjbvrt1F304tePHW8zgrQYViIrWlQyMJC8453svYzcMLsykqKeffL+vDfZf0plEDVRKIBEIhL57bc6SqUGz5+r2c2a0VT14/gv6dVSgmEgwKefGMc463v97B44vXU+7z8cDVA7jr/J7UVyWBSNAo5MUT2w4cJy09k1WbD3BOr7bMGJdMYvvmXo8lEnUU8lKnKn2O1z/bwm/fz6NhvXo8MW4wNw3rrkoCkRBRyEudydtTxOT0DNbtOMzIAR15bMxgOrdq4vVYIlFNIS8hV1bh48WV+bzwUT5xTRryf28+i2uT43X0LlIHFPISUmt3HCZ1bgZ5e4sYM6QLv7l2IG2bN/J6LJGYoZCXkDhRVsnT7+fx2mdb6NSyCa/dmcKl/VUoJlLXFPISdJ9v2k9aeibbDxZz64gE0q7sT1wTFYqJeEEhL0FztKScJ5as569f7SCxXTPennQO5/Rq5/VYIjFNIS9BsTxnL1PfzWRfUSn3XNSLX43sS5OG9b0eSyTmKeQlIAeOlfLwezm8t24X/TvH8fIdKSR3a+31WCLip5CXWnHOsWDtLh55L5vjpZX81+V9ueeiM1QoJhJmFPJy2nYdPsED72bxYW4hZyW0Zub4ZPp0ivN6LBGpgUJeTpnP53jrq+3MWJpLpc/xm2uSmHBeogrFRMKYQl5OyZb9x0lLz+DLLQe5oHd7nhg3mO5tm3k9loj8AIW8fK+KSh+vfrqFZz7YQKMG9Zg5PpkbUrqpkkAkQijk5aRydh0lNT2DzJ1H+HFSJ6aNGUSnlioUE4kkCnn5jtKKSn7/YT5/WLmJ1s0a8sItZ3PV4M46eheJQAp5+Rdrth0iLT2DjYXHGHd2Vx68Ook2KhQTiVgBXdRsZjeYWbaZ+cws5Vv7pphZvpnlmdkVgY0poVZcVsEj72Vz/Uufc7y0gtfvGsYzNw5RwItEuECP5LOAccAfq280syTgJmAg0AVYbmZ9nXOVAa4nIfDpxv2kzcug4NAJ7ji3B5NH9adFY/0lTyQaBPQn2Tm3HqjpXO1o4G3nXCmwxczygeHAqkDWk+A6cqKc6YtzmLO6gJ7tmzPnnnMZ3rOt12OJSBCF6nCtK/BFtfsF/m3fYWaTgEkACQkJIRpHvm1Z9h4efDeLA8fL+LeLz+DfL+ujQjGRKPSDIW9my4HONeya6pxbcLJvq2Gbq+mBzrlZwCyAlJSUGh8jwbOvqJSHF2azOHM3A+Jb8uqEYQzu1srrsUQkRH4w5J1zI2vxvAVA92r3uwG7avE8EiTOOeb/YyePLsqhuLSS+6/ox6QLe9GwvgrFRKJZqE7XLATeMrNnqPrgtQ/wVYjWkh+w8/AJps7PZGXePob2aMOT45Pp3bGF12OJSB0IKOTNbCzwPNABWGxma51zVzjnss1sDpADVAD36cqauufzOd78chszlubigIevTeKOcxOpp0IxkZgR6NU184H5J9k3HZgeyPNL7W3ed4y09Ey+2nqQH/Vpz+NjVSgmEot0MXSUqaj0MeuTzfxu+UaaNKjHzOuTuWGoCsVEYpVCPopk7zpCanoGWTuPMmpgZx4dM5COcSoUE4llCvkoUFJeyfMfbuSl/9lMm2aN+MOtZ3Pl4HivxxKRMKCQj3Brth1k8twMNu07zvVDu/HA1QNo3Ux9MyJSRSEfoY6XVvDUsjxmr9pKl1ZNeePu4VzYt4PXY4lImFHIR6CPN+xjyrxMdh05wYRzE7n/in40V6GYiNRAyRBBDheX8dji9cxdU0CvDs352z3nkpKoQjEROTmFfIRYmrmbBxdkc6i4jF9c0ptfXNpbhWIi8oMU8mGusKiEhxZkszRrDwO7tGT23cMY2EWFYiJyahTyYco5x9w1BUxblENJhY/Jo/ox6Ue9aKBCMRE5DQr5MLTjYDG/np/JJxv3MyyxDTPGJ3NGBxWKicjpU8iHEZ/P8caqrcxclocB00YP5NYRPVQoJiK1ppAPE/mFRaSmZ7Jm2yEu6tuB6WMH0a2NCsVEJDAKeY+VV/qY9fFmnlu+kWaN6/PMjWcy9qyuKhQTkaBQyHsoa+cRJs/NIGf3Ua5OjufhawfSIa6x12OJSBRRyHugpLyS51ZsZNbHm2nbvBF/vH0oVwys6Z/RFREJjEK+jn215SBp6Rls3n+cn6R059dXDaBVs4ZejyUiUUohX0eOlVbw5NJc/vzFNrq1acpfJo7ggj7tvR5LRKKcQr4OfJRXyNR5mew+WsJd51cVijVrpJdeREJPSRNCh46XMW1RDvP+sZPeHVsw997zGNqjjddjiUgMUciHgHOOJZl7eGhhFoeLy/nlpb2579LeNG6gQjERqVsBhbyZPQVcC5QBm4C7nHOH/fumABOBSuCXzrllgY0aGfYeLeHBd7N4P2cvg7u24s8TRzAgvqXXY4lIjAr0SP4DYIpzrsLMngSmAKlmlgTcBAwEugDLzayvc64ywPXClnOOOat38Nji9ZRV+JhyZX8mXtBThWIi4qmAQt459361u18A1/tvjwbeds6VAlvMLB8YDqwKZL1wtf1AMVPmZ/BZ/gGG92zLk+OT6dm+uddjiYgE9Zz83cA7/ttdqQr9fyrwb/sOM5sETAJISEgI4jihV+lz/Onzrfx2WR716xmPjRnELcMTVCgmImHjB0PezJYDNf045lTn3AL/Y6YCFcCb//y2Gh7vanp+59wsYBZASkpKjY8JRxv2FjF5bgZrdxzm0v4deWzMILq0bur1WCIi/+IHQ945N/L79pvZBOAa4DLn3D9DugDoXu1h3YBdtR0ynJRV+Hjpfzbx/IcbadG4Ac/dNITrzuyiQjERCUuBXl0zCkgFLnLOFVfbtRB4y8yeoeqD1z7AV4GsFQ7W7ThManoGuXuKuPbMLjx8bRLtWqhQTETCV6Dn5H8PNAY+8B/JfuGcu9c5l21mc4Acqk7j3BfJV9acKKvk2eUbeOWTzXSIa8zLd6RweVInr8cSEflBgV5d0/t79k0Hpgfy/OFg1aYDTJmXwdYDxdw8vDtTrhpAyyYqFBORyKCfeD2JoyXlzFiay1tfbiehbTPe+ukIzuutQjERiSwK+Rp8mLuXX8/LorCohJ/9qCf/eXk/mjZSJYGIRB6FfDUHjpXy6KIcFqzdRb9Ocbx0+1CGdG/t9VgiIrWmkKeqkmDhul088l4ORSXl/MfIPvz84t40aqBKAhGJbDEf8ruPnOCB+VmsyC3kzO6tmTk+mX6d47weS0QkKGI25H0+x9tf7+CJJesp9/l44OoB3HV+T+qrkkBEokhMhvzW/cdJm5fBF5sPcm6vdswYP5ge7VQoJiLRJ6ZCvtLneO3TLTz9QR4N69VjxrjB/GRYd1USiEjUipmQz91zlNS5GawrOMLIAR15bMxgOrdq4vVYIiIhFfUhX1pRyQsfbeLFj/Jp1bQhz998Ftckx+voXURiQlSH/D+2HyI1PYMNe48x9qyuPHhNEm2bN/J6LBGROhOVIV9cVsHT72/gtc+20LllE167M4VL+6tQTERiT9SF/Of5+0mbl8n2g8Xcdk4CqaP6E6dCMRGJUVET8kdOlPPEkvW8/fUOEts14+1J53BOr3ZejyUi4qmoCPmMgsP87I3V7Csq5Z6LevGrkX1p0lCFYiIiURHyCW2b0bdTHC/fkUJyt9ZejyMiEjaiIuRbN2vEnyeO8HoMEZGwo5pFEZEoppAXEYliCnkRkSimkBcRiWIBhbyZTTOzDDNba2bvm1mXavummFm+meWZ2RWBjyoiIqcr0CP5p5xzyc65IcAi4DcAZpYE3AQMBEYBL5qZLlwXEaljAYW8c+5otbvNAee/PRp42zlX6pzbAuQDwwNZS0RETl/A18mb2XTgDuAIcIl/c1fgi2oPK/Bvq+n7JwGTABISEgIdR0REqjHn3Pc/wGw50LmGXVOdcwuqPW4K0MQ595CZvQCscs79xb/vVWCJcy79B9baB2w7zd9Dde2B/QF8fzTSa/Jdek2+S6/Jd0XSa9LDOdehph0/eCTvnBt5iou8BSwGHqLqyL17tX3dgF2nsFaNQ54qM1vtnEsJ5DmijV6T79Jr8l16Tb4rWl6TQK+u6VPt7nVArv/2QuAmM2tsZj2BPsBXgawlIiKnL9Bz8jPMrB/go+o0y70AzrlsM5sD5AAVwH3OucoA1xIRkdMUUMg758Z/z77pwPRAnr8WZtXxepFAr8l36TX5Lr0m3xUVr8kPfvAqIiKRS7UGIiJRTCEvIhLFIj7kzewGM8s2M5+ZpXxrX8z355jZw2a2098vtNbMrvJ6Jq+Y2Sj/eyHfzNK8nidcmNlWM8v0vz9Wez2PF8zsNTMrNLOsatvamtkHZrbR/7WNlzPWVsSHPJAFjAM+rr5R/Tn/4lnn3BD/ryVeD+MF/3/7F4ArgSTgZv97RKpc4n9/RPx14bX0J6pyoro0YIVzrg+wwn8/4kR8yDvn1jvn8mrYpf4cqW44kO+c2+ycKwPepuo9IoJz7mPg4Lc2jwZm+2/PBsbU5UzBEvEh/z26Ajuq3T9pf04M+IW/Evq1SP0rZxDo/XByDnjfzNb4u6SkSifn3G4A/9eOHs9TKxHxD3mfan/Ot7+thm1Reb3o970+wB+AaVT93qcBTwN31910YSNm3g+1cL5zbpeZdQQ+MLNc/5GtRIGICPnT6M+prlb9OZHoVF8fM3uZqt7/WBQz74fT5Zzb5f9aaGbzqTq1pZCHvWYW75zbbWbxQKHXA9VGNJ+uUX8O4H9z/tNYqj6ojkVfA33MrKeZNaLqQ/mFHs/kOTNrbmZx/7wN/JjYfY9820Jggv/2BOBkZw3CWkQcyX8fMxsLPA90ABab2Vrn3BXqz/lfM81sCFWnJrYC93g6jUeccxVm9gtgGVAfeM05l+3xWOGgEzDfzKAqD95yzv3d25Hqnpn9FbgYaG9mBVS16c4A5pjZRGA7cIN3E9aeag1ERKJYNJ+uERGJeQp5EZEoppAXEYliCnkRkSimkBcRiWIKeRGRKKaQFxGJYv8P6v7JZPsXyb0AAAAASUVORK5CYII=\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = np.arange(-10, 13)\n", + "y = -3*x + 3\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 393, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 항등함수\n", + "\n", + "y = x\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3. 활성화 함수 그래프로 그려보기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">#### Quiz 2\n", + ">활성화 함수를 선형 함수로 사용하지 않는 이유를 적어주세요.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 397, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "## 계단함수\n", + "\n", + "def step(x) :\n", + " return np.where(x>0, 1, 0)\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = step(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 399, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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212DuDWrEDvI162sTXaqLTi8UFBRAr9fLlcVs2tvbkZ+fr3QM2VnzuEtKSlBbW9ubr6ysDDU1NX3ynjx5EuXl5ViyZAkMBgPmzp0LSZL6lDUAZGdnIycnBwDQ1NR0SWPWGQWe+74L4T4Skpy0yM+vMdfQFGHNx9pSbGnMqamp/W67aOlOmDDB3FlkkZ+ff9FB2ytrHre7uzsKCgp68xUUFCAlJaVP3p07d2LkyJG49dZbAQBff/01PDw8zhtTamoqlixZAgCIi4u7pDH/OacUjboKfJE5AWMH2/7C5NZ8rC3FXsbM6QWSRUpKCjQaDSoqKmAwGLBmzRqkp6f32ef222/H9u3bYTQa0dnZicLCQsTHx1/x9z5Y3YJ//VCB31wdZReFS7aNVy+QLFxcXLB06VJMnjwZJpMJGRkZSExMxLJlywAAmZmZiI+Px5QpU5CcnAwnJyc8+OCDSEq6sptCGk09eObLYgz0ccdTU4abYyhEV4SlS7JJS0tDWlpan69lZmb2eb5gwQIsWLDAbN9zxY4TOFTTin/8ZjT8PV3N9rpEl4vTC2S3qps6sWTzEdw0PARTkkKVjkMEgKVLdkoIgRe+PgQAePH2RH7Ul6wGS5fs0qZDdfimrB6P3zIMqkB+1JesB0uX7E673ogXvj6E+DA/3H/NEKXjEPXB0iW7s2RzOeradFg0PYm3USerw59Isisl2hZ8tOMEfnN1FEZFBSodh+g8LF2yG6YegefWH0SQtxsWTOY1uWSdWLpkN1YVVeJAdQuen5rAa3LJarF0yS7Ut+nwWt7Z2++kjwxXOg5Rv1i6ZBde2VAGfXcPXr49idfkklVj6ZLN++FoA7L21yAzdShign2UjkN0USxdsmkCwPNflSB6gBfmpA5VOg7RT+KCN2TTWvQChoYOfJQxDh6uzkrHIfpJPNMlm3WysQMteoHbRoTh+thgpeMQXRKWLtkkIQT+mHV2QZvnpyb8xN5E1oOlSzYpt+QUth05jUAPCaH+HkrHIbpkLF2yOe16I17KLkVCmB/83Hh5GNkWli7ZnDe2HEFdmw6vTL+yW/kQKYGlSzaltKYVK3acwKxxXNCGbBNLl2xGT4/Ac18dRICnK57mgjZko1i6ZDPW7KrCvspmPHdbPPy9uKAN2SaWLtmEhnY9FueWYXxMEKaPilA6DtFlY+mSTVi0oQxd3Sb8+Y4RXNCGbBpLl6zejmMN+HKfFpnXD4U6hAvakG1j6ZJV0xtN+MNXJYgK8sLcG9RKxyG6YlzwhqzasvzjOH6aC9qQ/eCZLlmt46fb8e7Wo5g2MpwL2pDdYOmSVRJC4A9flcDd1QnPT41XOg6R2bB0ySqt36fFjmONeHrKcIT4ckEbsh8sXbI6ZzoM+POGMoyKCsDd46KUjkNkVixdsjqvbChDa1c3Xp0xAk5OvCaX7AtLl2STl5eHuLg4qNVqLF68+IL7/HC0Aev2VuPMD5+h5PvNMicksjyWLsnCZDJh7ty5yM3NRWlpKVavXo3S0tI+++i6TVi4/iBcdE0Y53NGoaRElsXSJVkUFRVBrVYjJiYGbm5umDlzJrKysvrs8853Gpxs7MSMSD1CgwcolJTIsli6JAutVovIyMje5yqVClqttvd5aU0rlm07Bu/6g3h1/mwFEhLJ46KfSCsoKIBer5cri9m0t7cjPz9f6Riys+Zxl5SUoLa2tjdfWVkZampqkJ+fD1OPwMs7dRD6DmSMCsD27dtx6tQpHDp0CAMHDjzvtbKzs5GTkwMAaGpqstoxW5I1H2tLsaUxp6am9r9RCHGxh03aunWr0hEUYc3j3rFjh5g0aVLv80WLFolFixYJIYR4b9tREf10joj+xQwRHR0toqOjhbe3twgODhbr16+/6OvGxsZaMrbVsuZjbSk2NuZ+e5VrL5AsUlJSoNFoUFFRgYiICKxZswarVq3CycYOvL7lCG6OD8E/X/2id9nG2bNnY+rUqbjjjjuUDU5kZixdkoWLiwuWLl2KyZMnw2QyISMjAwkJCUh98Uv0GN3w8h1JXCeXHAJLl2STlpaGtLS03uerCitxUueBV6YnIczfs8++K1askDkdkTx49QIpQtvchUUbyzBx6AB+1JccCkuXZCeEwDPritEjBP5yZzKnFcihsHRJdp/vrsZ2TQOeuXU4IoO8lI5DJCuWLsmqprkLL+eU4uohQbjn6mil4xDJjqVLshFC4Ol1xTAJgdfuSuYKYuSQWLokm08LK7Fd04CFafGIHuCtdBwiRbB0SRYnGzuwaGMZfjFsIH5zNa9WIMfF0iWLM/UILPi8GM5OEq9WIIfH0iWL++f24yg6cQZ/mpaI8ADPn/4NRHaMpUsWVaJtwZLN5UgbEYo7R0coHYdIcSxdspgugwnzP9uPIG83vHLHCE4rEIFrL5AFLc4tw9H6dnz8wDgEerspHYfIKvBMlyziu8N1+KjgJDKuGYJfDAtWOg6R1WDpktnVterw5OfFGB7qi6emxCkdh8iqsHTJrEw9AvPX7EeXwYSld4+Gh6uz0pGIrArndMms/pF/FAXHG/HanclQh/goHYfI6vBMl8xm14kzeOMbDaaNDMcvx6qUjkNklVi6ZBYN7Xo8umovVIGeeGU6b71D1B9OL9AV+3Eet6mzG+vnpMDPw1XpSERWi2e6dMXe+laD74824OXbE5EY7q90HCKrxtKlK5JfXo93vtPgztEq/GpspNJxiKweS5cu28nGDjy2eh/iBvniz7yFOtElYenSZenQG/Hwyj2QJAnv3zsWnm68HpfoUrB06WcTQuCpdcXQ1Ldh6d2jEDWAN5ckulQsXfrZ/p5/DBuKa/HUlOFcV4HoZ2Lp0s+SV1KLv24qR/rIcPzuuhil4xDZHJYuXbISbQse/+wARkUF4LW7eNsdosvB0qVLUteqw4Mf7UaQtxvev3csF7Ihukz8RBr9pDZdN2Yv34VWXTfWPTIRwb7uSkcislksXbqoblMP5ny6F0fq2vDhb8ciPsxP6UhENo3TC9QvIQSeXleM7ZoGvDpjBFLjQpSORGTzWLrUr79uKseXe7V4/OZYs3zENy8vD3FxcVCr1Vi8ePF52z/99FMkJycjOTkZEydOxIEDB674exJZG04v0AUt23YMf88/hruvjsJjN6mv+PVMJhPmzp2LLVu2QKVSISUlBenp6UhISOjdZ8iQIdi2bRsCAwORm5uLhx9+GIWFhVf8vYmsCc906TyfFp7E4tzDmDYyHC/fbp41FYqKiqBWqxETEwM3NzfMnDkTWVlZffaZOHEiAgMDAQDjx49HdXX1FX9fImvD0qU+svZr8YevSnDj8BC8/quRcHYyz7W4Wq0WkZH/maJQqVTQarX97v/hhx/i1ltvNcv3JrImkhCi340FBQVCr9fLGMc82tvb4ePjePfnutJx76w14r0DesQGOuGJsR5wczbfhx/y8/Oxa9cuLFiwAACwefNmHD58GI899th5++7btw9vvvkm3n77bfj7n78+b3Z2NnJycgAATU1NWLt2rdly2gpH/Bm3pTGnpqb2/5dHCHGxh03aunWr0hEUcSXj/nq/Vgx5Jkf8ctkO0a7rNl+oc3bs2CEmTZrU+3zRokVi0aJF5+134MABERMTI8rLyy/pdWNjY82W0ZY44s+4jY25317l9AIhp7gG8z/bj7HRQVg+OwXe7uZ/fzUlJQUajQYVFRUwGAxYs2YN0tPT++xTWVmJGTNm4OOPP0ZsbKzZMxBZA1694ODW7q7CM+uKzxbu/ZYpXABwcXHB0qVLMXnyZJhMJmRkZCAxMRHLli0DAGRmZuKll15CY2Mj5syZ0/t7du/ebZE8REph6Tqwf31fgZdySnFdbDDeu2eMxRciT0tLQ1paWp+vZWZm9v76gw8+wAcffGDRDERKY+k6ICEE3vpWgze/0eDWpFC8OfMquLtwARsiObB0HUy3qQfPf1WCNbuqcNcYFRbPGAEXZ07tE8mFpetAOvRGzPl0L7YdOY3f36jG/90SyzVxiWTG0nUQNc1deGjlbhw+1YZF00fg7qujlI5E5JBYug5gz8km/O7jPdB1m/DBfWNxw3CuFkakFJaunftiTzUWfnkQYQEeWP3Q1Rg2yFfpSEQOjaVrp3TdJryUU4pVhZWYOHQA3r17NAK93ZSOReTwWLp2qLKxE3NW7UGJthWPpA7FE7fE8goFIivB0rUz2QdqsHD9QUgAPrhvLG5OGKR0JCL6LyxdO9Gm68Y/i/X4oWYfRkUF4O2ZoxAZ5KV0LCL6HyxdO1BwrBFPrTuA6jNGzLtpGH5/o5rTCURWiqVrw9r1RizOLcMnOysRPcALC6/2wEO3cHUuImvG0rVR35TW4U9fH0JNSxceuHYInpwUh8Id25WORUQ/gaVrY6rOdOLF7FJ8U1aHYSE++CJzAsZEBykdi4guEUvXRnQajHhv23G89+9jkCDh2VuHI+PaIXDl3C2RTWHpWjlTj8CXe6vx103lqG/T47YRYVh4WzwiAjyVjkZEl4Gla6WEENh06BRe33IER+raMTIyAP+4ZzSnEohsHEvXyvT0CHx3uB5vfavBQW0LYoK9sfTuUUhLCoOTmW6HTkTKYelaCaOpBxsO1uIf+cdw+FQbVIGe+OtdyZg+KoLX3BLZEZauwlq6uvHZrkp8tOMktM1dGBbigzd+PRLTksNZtkR2iKWrkBJtC1YXVWL9Pi06DSaMjwnCn6Yl4Ob4QZxGILJjLF0ZtXR1Y0NxLT7bVYkD1S1wd3HCtJHhuP+awUgM91c6HhHJgKVrYXqjCf8+0oCv9muxpbQOBmMPhoX44E/TEjBjlAr+Xq5KRyQiGbF0LUDXbcIPRxuw4WAtthyqQ5veiEAvV8xKicSdY1QYEeHPG0ISOSiWrpnUt+qQf+Q0vimtw3ZNA7q6TfD1cMHkpFDclhyGa4YOhJsL3xgjcnQs3cvUaTBi14km7DjWgH8faUBZbSsAINTPA3eOicAtCaEYHxMEdxdnhZMSkTVh6V6i5k4D9pxswq4TTdh14gyKq5vRbRJwdZYwOioQT08ZjutjgxEf5supAyLqF0v3AjoNRpTVtuJgdQsOVLfgQFUzjjd0AABcnSUkhvvjgWtjMHHoAIwdHAgvN/4xEtGlcei2MPUIVJ3phKa+HeWnWnH4VBsOn2rD8dPt6BFn9wn2dcdVkQG4c4wKY6MDMTIyAB6unDIgostj96Xb0yNQ36ZH5ZlOnGzswInGDlQ0dOD46Q4cb+iAwdjTu29kkCfiBvlhanIYksL9kRjhh1A/D04XEJHZ2HTpCiHQ2mVEXZsOda061LbocKpFh91lenx4rBDapi5UN3f1KVYXJwlRQV4YPNAb18UGQx3sg6EhPogL9YWPu03/cRCRDbCqljH1CLR2daOlqxvNXd1o6jSgudOAxnYDznScfTS0G3C6XY+GNj1Ot+v7FOqP/NwkDBlkxPAwX9ycMAiRQV6IOvdQBXpy4W+F5OXlYd68eTCZTHjwwQfxzDPP9NkuhMC8efOwceNGeHl5YcWKFRg9erRCaYkswyKlW9+qQ3F1Czq7TejUG9FhMKFDb0SH3oj2Hx86I9p0RrTquvv8tz/OThICvdww0McNA33cETPQGwN93DDIzwMhfh4Y5OuO8ABPhPi5o+D77UhNvcYSQ6PLZDKZMHfuXGzZsgUqlQopKSlIT09HQkJC7z65ubnQaDTQaDQoLCzEI488gsLCQgVTE5mfRUp314kmzF2197yvu7k4wcfd5T8PDxeoAr3g5+kCPw9X+Hm6IsDTFf6ergjwckWAlxsCvVwR5O0GPw9XLgRjw4qKiqBWqxETEwMAmDlzJrKysvqUblZWFu677z5IkoTx48ejubkZtbW1CAsLUyo2kdlZpHQnDh2Arx+9Bl5uLvByc4aXmzO83V34z3oHptVqERkZ2ftcpVKddxZ7oX20Wi1Ll+yKJITod+P48eNFU1OTjHHMo7u7G66ujreQjDWPu62tDR0dHQgNDQUAtLa2QqfTISQkpHcfrVaLoKAgeHqevf9bVVUVgoOD4eHh0ee1Wlpa0NzcDAAwGo0YOnSoPIOwItZ8rC3FlsZ85MiRTUKIKRfadtHSBXDRjdYqLi4O5eXlSseQnTWPu6CgAC+88AI2bdoEAHj11VcBAM8++2zvPr/73e+QmpqKWbNmATg7nvz8/Iue6Xp4eECn01kwuXWy5mNtKTY25n7nQvnvfZJFSkoKNBoNKioqYDAYsGbNGqSnp/fZJz09HStXroQQAjt37oS/vz+nFsjuWNUlY2S/XFxcsHTpUkyePBkmkwkZGRlITEzEsmXLAACZmZlIS0vDxo0boVar4eXlheXLlyucmsj87LJ0p06dqnQERVj7uNPS0pCWltbna5mZmb2/liQJ77777s96zYCAAHNEsznWfqwtwV7GbJfTC9OmTVM6giIccdz+/o55myNHPNb2Mma7LF0iImtl96X7t7/9DZIkoaGhQekoFrds2TIMHz4cycnJmD59eu9lVfYqLy8PFRUVUKvVWLx4sdJxLK6qqgo33HAD4uPjMXv2bLz11ltKR5KNyWTCQw89ZBdTDD91yZhNkyQpEsAHAIYDGCOEsOvmlSRpEoDvhBBGSZL+AgBCiKcVjmURkiQ5AzgCoBrALQB2AZglhChVNJgFSZIUBiBMCLFXkiRfAHsA3GHPY/6RJEn/B2AsAD8hhE03r72f6b4B4CnY6PXGP5cQYrMQ4scFLHYCUCmZx8LGATgqhLheCGEAsAbA7QpnsighRK0QYu+5X7cBKAMQoWwqy5MkSQXgNpw9gbJ5dlu6kiSlA9AKIQ4onUUhGQBylQ5hQREAqv7reTUcoIB+JEnSYACjADjCikBv4uzJ0/lLCtogm75kTJKkbwCEXmDTcwAWApgkbyLLu9iYhRBZ5/Z5DoARwKdyZpPZhT7x4xD/opEkyQfAOgDzhRCtSuexJEmSpgKoF0LskSQpVeE4ZmHTpSuEuPlCX5ckaQSAIQAOnLvrgwrAXkmSxgkhTskY0ez6G/OPJEn6LYCpAG4S9jxhf/bMNvK/nqsA1CiURTaSJLnibOF+KoT4Uuk8MrgGQLokSWkAPAD4SZL0iRDiHoVzXTa7fiPtR5IknQAw1gHeSJsC4HUA1wshTiudx5IkSXLB2TfSbgKgxdk30u4WQhxSNJgFSWfPID4CcEYIMV/hOLI7d6b7JN9II2uyFIAvgC2SJO2XJGmZ0oEs5dwbho8C2ISzbyittefCPecaAPcCuPHc8d1/7gyQbIhDnOkSEVkLnukSEcmIpUtEJCOWLhGRjFi6REQyYukSEcmIpUtEJCOWLhGRjFi6REQy+n/mFdiq1DXuQwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 시그모이드 함수 : 자연상수를 지수로 사용해 작은 값과 큰 값을 특정 범위 내의 값으로 처리. 0과 1사이로 변환\n", + "\n", + "def sigmoid(x) :\n", + " return 1/(1 + np.exp(-x))\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = sigmoid(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 400, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 하이퍼볼릭 탄젠트 함수 : 자연상수를 분모에는 더하고 분자에는 빼는 구조. -1과 1사이의 값을 0을 중심으로 대칭형태로 변환\n", + "\n", + "def htan(x) :\n", + " return (np.exp(x) - np.exp(-x)) / (np.exp(x) + np.exp(-x))\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = htan(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 403, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 렐루 함수 : 입력값이 0보다 크면 그 값을 그대로 반환하고, 0보다 작거나 같으면 0으로 출력. \n", + "# 기울기의 미분을 역으로 전파 될 때 기울기의 값이 사라지는 것을 방지하기 위해 많이 사용됨.\n", + "\n", + "def relu(x) :\n", + " return np.maximum(0, x)\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = relu(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">#### Quiz 3\n", + ">역전파(Backpropagation)란 무엇이고 왜 딥러닝에서 왜 중요한가?" + ] + }, + { + "cell_type": "code", + "execution_count": 409, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 소프트맥스 함수 : 0보다 크고 1보다 작은 n개 노드 출력. n개별 확률값을 출력하여 분류를 구하는 출력층에 주로 사용.\n", + "\n", + "def softmax(x) :\n", + " return np.exp(x) / np.sum(np.exp(x))\n", + "\n", + "x = np.arange(1, 5)\n", + "y = softmax(x)\n", + "\n", + "np.sum(y) # 1입니다.\n", + "\n", + "ratio = y\n", + "labels = y\n", + "\n", + "plt.pie(ratio, labels=labels, shadow=True, startangle=90)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 부록" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "t = np.arange(0, 5, 0.01)\n", + "\n", + "plt.figure(figsize=(10, 12))\n", + "\n", + "plt.subplot(411)\n", + "plt.plot(t, np.sqrt(t))\n", + "plt.grid()\n", + "\n", + "plt.subplot(413)\n", + "plt.plot(t, np.sin(t))\n", + "plt.grid()\n", + "\n", + "plt.subplot(423)\n", + "plt.plot(t, t**2)\n", + "plt.grid()\n", + "\n", + "plt.subplot(424)\n", + "plt.plot(t, t**3)\n", + "plt.grid()\n", + "\n", + "plt.subplot(414)\n", + "plt.plot(t, np.cos(t))\n", + "plt.grid()\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "![matplotlib graphic](https://mblogthumb-phinf.pstatic.net/MjAxOTA0MjNfNjkg/MDAxNTU1OTkxMzkxNDQ0.JN62ph8P1qug3h5dPIkLFGl1hGinWVq95Bi0zfhYVqAg.4CyrOHysh2bIzbKs0AA1jIDTVIrhY7i7uQ1BfaDh8qwg.PNG.heygun/anatomy.png?type=w800)\n", + "

" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git "a/06\354\236\245/C6-7_summary.ipynb" "b/06\354\236\245/C6-7_summary.ipynb" new file mode 100644 index 0000000..a01f023 --- /dev/null +++ "b/06\354\236\245/C6-7_summary.ipynb" @@ -0,0 +1,3120 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Chapter 6. 넘파이 모듈의 자료형 이해하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 01. dtype으로 자료 객체 생성하기" + ] + }, + { + "cell_type": "code", + "execution_count": 208, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.19.2'" + ] + }, + "execution_count": 208, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "np.__version__" + ] + }, + { + "cell_type": "code", + "execution_count": 209, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "print(np.dtype)" + ] + }, + { + "cell_type": "code", + "execution_count": 210, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([1, 2, 3, 4, 5]), dtype('int64'))" + ] + }, + "execution_count": 210, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.int64([1,2,3,4,5])\n", + "a, a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 211, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([1, 2, 3, 4, 5]), dtype('int64'))" + ] + }, + "execution_count": 211, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.array([1,2,3,4,5], dtype=np.int64)\n", + "a, a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 212, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([1, 2, 3, 4, 5]), dtype('int64'))" + ] + }, + "execution_count": 212, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.array([1,2,3,4,5], dtype='i8')\n", + "a, a.dtype" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ℹ️ [참고. numpy dtypes](https://numpy.org/doc/stable/reference/arrays.dtypes.html)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "int" + ] + }, + "execution_count": 213, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b = 10\n", + "type(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 215, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 215, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.array([10], dtype=np.int64)\n", + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 216, + "metadata": {}, + "outputs": [], + "source": [ + "py_number = 12345\n", + "np_number = np.array([12345], dtype='int64')" + ] + }, + { + "cell_type": "code", + "execution_count": 217, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "int64\n" + ] + } + ], + "source": [ + "print(type(py_number))\n", + "print(np_number.dtype)" + ] + }, + { + "cell_type": "code", + "execution_count": 218, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__bool__',\n", + " '__ceil__',\n", + " '__class__',\n", + " '__delattr__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floor__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getnewargs__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__index__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__le__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__round__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__trunc__',\n", + " '__xor__',\n", + " 'as_integer_ratio',\n", + " 'bit_length',\n", + " 'conjugate',\n", + " 'denominator',\n", + " 'from_bytes',\n", + " 'imag',\n", + " 'numerator',\n", + " 'real',\n", + " 'to_bytes']" + ] + }, + "execution_count": 218, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(py_number)" + ] + }, + { + "cell_type": "code", + "execution_count": 219, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['T',\n", + " '__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__array__',\n", + " '__array_finalize__',\n", + " '__array_function__',\n", + " '__array_interface__',\n", + " '__array_prepare__',\n", + " '__array_priority__',\n", + " '__array_struct__',\n", + " '__array_ufunc__',\n", + " '__array_wrap__',\n", + " '__bool__',\n", + " '__class__',\n", + " '__complex__',\n", + " '__contains__',\n", + " '__copy__',\n", + " '__deepcopy__',\n", + " '__delattr__',\n", + " '__delitem__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getitem__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__iadd__',\n", + " '__iand__',\n", + " '__ifloordiv__',\n", + " '__ilshift__',\n", + " '__imatmul__',\n", + " '__imod__',\n", + " '__imul__',\n", + " '__index__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__ior__',\n", + " '__ipow__',\n", + " '__irshift__',\n", + " '__isub__',\n", + " '__iter__',\n", + " '__itruediv__',\n", + " '__ixor__',\n", + " '__le__',\n", + " '__len__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__matmul__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmatmul__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__setitem__',\n", + " '__setstate__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__xor__',\n", + " 'all',\n", + " 'any',\n", + " 'argmax',\n", + " 'argmin',\n", + " 'argpartition',\n", + " 'argsort',\n", + " 'astype',\n", + " 'base',\n", + " 'byteswap',\n", + " 'choose',\n", + " 'clip',\n", + " 'compress',\n", + " 'conj',\n", + " 'conjugate',\n", + " 'copy',\n", + " 'ctypes',\n", + " 'cumprod',\n", + " 'cumsum',\n", + " 'data',\n", + " 'diagonal',\n", + " 'dot',\n", + " 'dtype',\n", + " 'dump',\n", + " 'dumps',\n", + " 'fill',\n", + " 'flags',\n", + " 'flat',\n", + " 'flatten',\n", + " 'getfield',\n", + " 'imag',\n", + " 'item',\n", + " 'itemset',\n", + " 'itemsize',\n", + " 'max',\n", + " 'mean',\n", + " 'min',\n", + " 'nbytes',\n", + " 'ndim',\n", + " 'newbyteorder',\n", + " 'nonzero',\n", + " 'partition',\n", + " 'prod',\n", + " 'ptp',\n", + " 'put',\n", + " 'ravel',\n", + " 'real',\n", + " 'repeat',\n", + " 'reshape',\n", + " 'resize',\n", + " 'round',\n", + " 'searchsorted',\n", + " 'setfield',\n", + " 'setflags',\n", + " 'shape',\n", + " 'size',\n", + " 'sort',\n", + " 'squeeze',\n", + " 'std',\n", + " 'strides',\n", + " 'sum',\n", + " 'swapaxes',\n", + " 'take',\n", + " 'tobytes',\n", + " 'tofile',\n", + " 'tolist',\n", + " 'tostring',\n", + " 'trace',\n", + " 'transpose',\n", + " 'var',\n", + " 'view']" + ] + }, + "execution_count": 219, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(np_number)" + ] + }, + { + "cell_type": "code", + "execution_count": 220, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int64')" + ] + }, + "execution_count": 220, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 221, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.99999999999998\n" + ] + } + ], + "source": [ + "py_result = 0\n", + "\n", + "for i in range(0, 100):\n", + " py_result += 0.1\n", + "\n", + "print(py_result)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ℹ️ [참고. 파이썬 부동 소수점 오차 해결](https://winterj.me/floating-point-in-python/)" + ] + }, + { + "cell_type": "code", + "execution_count": 222, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "float" + ] + }, + "execution_count": 222, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(py_result)" + ] + }, + { + "cell_type": "code", + "execution_count": 223, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[10.]\n" + ] + } + ], + "source": [ + "np_result = np.array([0], dtype='float64')\n", + "\n", + "for i in range(0, 100):\n", + " np_result += 0.1\n", + "\n", + "print(np_result)" + ] + }, + { + "cell_type": "code", + "execution_count": 224, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('float64')" + ] + }, + "execution_count": 224, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np_result.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 225, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([1,2,3,4,5], dtype=np.float32)" + ] + }, + { + "cell_type": "code", + "execution_count": 226, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 2., 3., 4., 5.], dtype=float32)" + ] + }, + "execution_count": 226, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 227, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array(['ab', 'cd'], dtype=np.str)" + ] + }, + { + "cell_type": "code", + "execution_count": 228, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['ab', 'cd'], dtype=', , , , , , ]\n" + ] + } + ], + "source": [ + "print(np.float64.mro())" + ] + }, + { + "cell_type": "code", + "execution_count": 238, + "metadata": {}, + "outputs": [], + "source": [ + "import pprint" + ] + }, + { + "cell_type": "code", + "execution_count": 239, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ]\n" + ] + } + ], + "source": [ + "pprint.pprint(np.float64.mro())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 02. 날짜 자료형" + ] + }, + { + "cell_type": "code", + "execution_count": 240, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "# 넘파이는 np.datetime64와 timedelta64 두가지 모듈을 제공합니다. \n", + "\n", + "np.datetime64\n", + "print(np.datetime64)" + ] + }, + { + "cell_type": "code", + "execution_count": 241, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['T',\n", + " '__abs__',\n", + " '__add__',\n", + " '__and__',\n", + " '__array__',\n", + " '__array_interface__',\n", + " '__array_priority__',\n", + " '__array_struct__',\n", + " '__array_wrap__',\n", + " '__bool__',\n", + " '__class__',\n", + " '__copy__',\n", + " '__deepcopy__',\n", + " '__delattr__',\n", + " '__dir__',\n", + " '__divmod__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__float__',\n", + " '__floordiv__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getitem__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__init__',\n", + " '__init_subclass__',\n", + " '__int__',\n", + " '__invert__',\n", + " '__le__',\n", + " '__lshift__',\n", + " '__lt__',\n", + " '__mod__',\n", + " '__mul__',\n", + " '__ne__',\n", + " '__neg__',\n", + " '__new__',\n", + " '__or__',\n", + " '__pos__',\n", + " '__pow__',\n", + " '__radd__',\n", + " '__rand__',\n", + " '__rdivmod__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__rfloordiv__',\n", + " '__rlshift__',\n", + " '__rmod__',\n", + " '__rmul__',\n", + " '__ror__',\n", + " '__rpow__',\n", + " '__rrshift__',\n", + " '__rshift__',\n", + " '__rsub__',\n", + " '__rtruediv__',\n", + " '__rxor__',\n", + " '__setattr__',\n", + " '__setstate__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__sub__',\n", + " '__subclasshook__',\n", + " '__truediv__',\n", + " '__xor__',\n", + " 'all',\n", + " 'any',\n", + " 'argmax',\n", + " 'argmin',\n", + " 'argsort',\n", + " 'astype',\n", + " 'base',\n", + " 'byteswap',\n", + " 'choose',\n", + " 'clip',\n", + " 'compress',\n", + " 'conj',\n", + " 'conjugate',\n", + " 'copy',\n", + " 'cumprod',\n", + " 'cumsum',\n", + " 'data',\n", + " 'diagonal',\n", + " 'dtype',\n", + " 'dump',\n", + " 'dumps',\n", + " 'fill',\n", + " 'flags',\n", + " 'flat',\n", + " 'flatten',\n", + " 'getfield',\n", + " 'imag',\n", + " 'item',\n", + " 'itemset',\n", + " 'itemsize',\n", + " 'max',\n", + " 'mean',\n", + " 'min',\n", + " 'nbytes',\n", + " 'ndim',\n", + " 'newbyteorder',\n", + " 'nonzero',\n", + " 'prod',\n", + " 'ptp',\n", + " 'put',\n", + " 'ravel',\n", + " 'real',\n", + " 'repeat',\n", + " 'reshape',\n", + " 'resize',\n", + " 'round',\n", + " 'searchsorted',\n", + " 'setfield',\n", + " 'setflags',\n", + " 'shape',\n", + " 'size',\n", + " 'sort',\n", + " 'squeeze',\n", + " 'std',\n", + " 'strides',\n", + " 'sum',\n", + " 'swapaxes',\n", + " 'take',\n", + " 'tobytes',\n", + " 'tofile',\n", + " 'tolist',\n", + " 'tostring',\n", + " 'trace',\n", + " 'transpose',\n", + " 'var',\n", + " 'view']" + ] + }, + "execution_count": 241, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dir(np.datetime64)" + ] + }, + { + "cell_type": "code", + "execution_count": 242, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(numpy.datetime64('2020'), dtype('\n" + ] + } + ], + "source": [ + "np.timedelta64\n", + "print(np.timedelta64)" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": {}, + "outputs": [], + "source": [ + "delta = np.datetime64('2020-11-03') - np.datetime64('2020-01-01')" + ] + }, + { + "cell_type": "code", + "execution_count": 247, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(numpy.timedelta64(307,'D'), dtype('#### Quiz 1\n", + ">바이트 문자열이란?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 164, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([['0', '1', '2', '3', '4'],\n", + " ['5', '6', '7', '8', '9']], dtype='" + ] + }, + { + "cell_type": "code", + "execution_count": 326, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 327, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n" + ] + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + " \n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 329, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(936x576)\n", + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": "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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(13, 8))\n", + "print(fig)\n", + "ax = plt.axes()\n", + "print(ax)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 288, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([ 1. , 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2. ,\n", + " 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1,\n", + " 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. , 4.1, 4.2,\n", + " 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5. , 5.1, 5.2, 5.3,\n", + " 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 6. , 6.1, 6.2, 6.3, 6.4,\n", + " 6.5, 6.6, 6.7, 6.8, 6.9, 7. , 7.1, 7.2, 7.3, 7.4, 7.5,\n", + " 7.6, 7.7, 7.8, 7.9, 8. , 8.1, 8.2, 8.3, 8.4, 8.5, 8.6,\n", + " 8.7, 8.8, 8.9, 9. , 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7,\n", + " 9.8, 9.9, 10. , 10.1, 10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 10.8,\n", + " 10.9, 11. , 11.1, 11.2, 11.3, 11.4, 11.5, 11.6, 11.7, 11.8, 11.9]),\n", + " 110)" + ] + }, + "execution_count": 288, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.arange(1, 12, 0.1)\n", + "x, x.size" + ] + }, + { + "cell_type": "code", + "execution_count": 289, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.84147098, 0.89120736, 0.93203909, 0.96355819, 0.98544973,\n", + " 0.99749499, 0.9995736 , 0.99166481, 0.97384763, 0.94630009,\n", + " 0.90929743, 0.86320937, 0.8084964 , 0.74570521, 0.67546318,\n", + " 0.59847214, 0.51550137, 0.42737988, 0.33498815, 0.23924933,\n", + " 0.14112001, 0.04158066, -0.05837414, -0.15774569, -0.2555411 ,\n", + " -0.35078323, -0.44252044, -0.52983614, -0.61185789, -0.68776616,\n", + " -0.7568025 , -0.81827711, -0.87157577, -0.91616594, -0.95160207,\n", + " -0.97753012, -0.993691 , -0.99992326, -0.99616461, -0.98245261,\n", + " -0.95892427, -0.92581468, -0.88345466, -0.83226744, -0.77276449,\n", + " -0.70554033, -0.63126664, -0.55068554, -0.46460218, -0.37387666,\n", + " -0.2794155 , -0.1821625 , -0.0830894 , 0.0168139 , 0.1165492 ,\n", + " 0.21511999, 0.31154136, 0.40484992, 0.49411335, 0.57843976,\n", + " 0.6569866 , 0.72896904, 0.79366786, 0.85043662, 0.8987081 ,\n", + " 0.93799998, 0.96791967, 0.98816823, 0.99854335, 0.99894134,\n", + " 0.98935825, 0.96988981, 0.94073056, 0.90217183, 0.85459891,\n", + " 0.79848711, 0.7343971 , 0.66296923, 0.58491719, 0.50102086,\n", + " 0.41211849, 0.31909836, 0.22288991, 0.12445442, 0.02477543,\n", + " -0.07515112, -0.17432678, -0.27176063, -0.36647913, -0.45753589,\n", + " -0.54402111, -0.62507065, -0.69987469, -0.76768581, -0.82782647,\n", + " -0.87969576, -0.92277542, -0.95663502, -0.98093623, -0.99543625,\n", + " -0.99999021, -0.99455259, -0.97917773, -0.95401925, -0.91932853,\n", + " -0.87545217, -0.82282859, -0.76198358, -0.69352508, -0.61813711])" + ] + }, + "execution_count": 289, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y = np.sin(x)\n", + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 325, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288)\n", + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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iA4AKWsTPjrd2smpTOU9tKKeprYu5FyXx8DwXU8bGOx1NRAKYClqkn5xo6+TZLZU8sb6chpYOZmQlkD/PxYysBIzRPalF5O+poEX6WWtHF8+/d4CV68qoP9HO1LEjWOp2MfeiJBW1iPyVClrEIW2dXl7cfpDHikupOd7GZaOHsTTPxZfGJ6uoRUQFLeK0ji4fr7xfxYpiDwcbTnLxqDjy3Tl8eeIoQkJU1CKDlQpaJEB0en28/mENy4s8lB1pwTUylqV5Lm68LIWwUH9e3E9EApEKWiTAeH2Wt3YeYlmhh/21J8hIiGZxroubJ6cRrqIWGTRU0CIByuezvLOnloLCEnbXNJE2fAgP5WZzy9TRRIaFOh1PRPxMBS0S4Ky1FO+v51eFJXxwoJHkoZE8OCeb26elMyRCRS0SrFTQIgOEtZaNnqP8qrCEreUNJMZG8MDsLO6cPpaYyDCn44lIH1NBiwxA75UdZVmRh/UlRxgeHc6CmZncMzODoVHhTkcTkT6ighYZwD44cIxlhR7W7KsjLiqMe6/O4P6ZmYyIiXA6moj0kgpaJAjsqj7OskIPf959mJiIUO6cMZYHZmeRGBvpdDQRuUAqaJEg8kntCZYVenjj4xoiwkL49rSxLJyTxahhUU5HE5EvSAUtEoTK6ptZUVzKqx9UE2oMt145mkVzsxk9ItrpaCJynlTQIkHsYEMrK4pLeXnHQayFr09OY3Gui4zEGKejicg5qKBFBoFDx0+ycm0Zq7ceoNPrY/6kNJbkZeMaGed0NBE5AxW0yCBSd6KNJ9aX8+zmStq6vNwwMYWlbheXpAx1OpqIfIYKWmQQamjp4MkNZTy9qZLm9i6+ND6ZfLeLy0YPdzqaiHQ7U0H7/Yr8xpjrjTH7jTEeY8z3/L0+Efmb+JgI/vm6i9n4iJv/ec1FbC1v4GvLNnLPU1vZUdngdDwROQu/7kEbY0KBT4AvAVXANuB2a+2e071ee9Ai/nWirZNnt1TyxPpyGlo6mJGVQP48FzOyEjBG96QWcYJTe9DTAI+1tsxa2wG8AMz38zpF5AziosJZnOtiwyN5/K+vXEJpfTPf/s173PLYZor31xFIX3mJDHb+Lug04GCP51Xd0/7KGLPQGLPdGLO9vr7ez3FEBCA6IozvzM5i3b/k8aP5E6hpPMm9q7Yxf/lG/rKnVkUtEgD8XdCnGzP7u3/51trHrbVTrbVTk5KS/BxHRHqKCg/lrhkZFP9zHj/5+qU0tnbywDPb+fJ/refNjw/h86moRZzi74KuAsb0eD4aqPHzOkXkC4oIC+G2aekU/uNcfnHr5XR4fSx5/n2u/eU6Xv2gii6vz+mIIoOOvw8SC+PUQWLzgGpOHST2bWvt7tO9XgeJiQQGr8/yp12HWFboYd/hE4xNiGZJroubrkgjIszvJ3+IDCqOnQdtjLkB+CUQCjxlrf3xmV6rghYJLD6f5S97a1lW6GFn9XHShg9hUW42t0wZTVR4qNPxRIKCLlQiIhfMWkvxJ/UUrCnh/QONJA+NZOGcbL49LZ0hESpqkd5QQYtIr1lr2Vx6lF8VlrClrIHE2Ai+MzuLO6ePJTYyzOl4IgOSClpE+tS2igYKCj2s+6Se4dHh3D8zk3uuzmDYkHCno4kMKCpoEfGLDw82sqywhHf31hEXGcY9V2dw/6xM4mMinI4mMiCooEXEr3bXHGd5kYc/7TrMkPBQ7po+lu/MziIpLtLpaCIBTQUtIv2ipPYEy4s8vP5RDeGhIdw+LZ1Fc7MZNSzK6WgiAUkFLSL9qvxICyuKPLz6QTUhxvDNqaN5aG42Y+KjnY4mElBU0CLiiIMNrTy2tpSXtlfhs5abr0hjcZ6LzMQYp6OJBAQVtIg46tDxk6xcW8bqrQfo9Pr46uWpLM1zkZMc53Q0EUepoEUkINSfaOeJ9WU8u6WSk51erp8wiqVuFxNShzkdTcQRKmgRCSgNLR2s2ljObzdWcKK9i2suGclSdw6Txgx3OppIv1JBi0hAOn6yk6c3VfDUxnIaWzuZnZPIw/NyuDIj3uloIv1CBS0iAa25vYvntlTyxPoyjjR3MD0rnnx3DldnJ2DM6W4tLxIcVNAiMiCc7PCyeusBVq4rpbapncnpw8mfl0PuRUkqaglKKmgRGVDaOr28tKOKx4pLqW48yaVpw1jqdvGlS5IJCVFRS/BQQYvIgNTR5eOPH1SzvNhD5dFWLh4Vx1K3iy9PTCFURS1BQAUtIgNal9fHf39cw7JCD6X1LWQnxbAkz8XXLk8lLDTE6XgiF0wFLSJBweuz/HnXYQoKS9h3+ATp8dEszs3m65NHExGmopaBRwUtIkHF57O8u7eWgkIPO6uPkzZ8CIvmZnHL1DFEhYc6HU/kvKmgRSQoWWsp/qSegjUlvH+gkZFxkSyck8UdV41lSISKWgKfClpEgpq1ls2lR/lVYQlbyhpIiIlgwexM7p6RQWxkmNPxRM5IBS0ig8a2igYKCj2s+6SeYUPCuX9mJvfOzGDYkHCno4l8zpkKuldHVBhjbjHG7DbG+IwxUz8z7/vGGI8xZr8x5rrerEdE5Iu4MiOeZ+6fxh+XzOTKjBH857ufMOsnhfz87X00tHQ4HU/kvPRqD9oYcwngA1YC/2St3d49fTywGpgGpALvAhdZa71nW572oEXEH3bXHGd5kYc/7TrMkPBQ7pw+lu/MzmRkXJTT0UTOuAfdqy9mrLV7uxf+2VnzgReste1AuTHGw6my3tyb9YmIXIgJqcNYcccUSmpPsLzIwxPry3h6UwW3T0vnwblZpAwb4nREkc/x10mDacDBHs+ruqd9jjFmoTFmuzFme319vZ/iiIhATnIcv7ztCtb8Yy5fuzyV57ZUMvdnxfzrqzs52NDqdDyRv3POgjbGvGuM2XWan/lne9tppp12LN1a+7i1dqq1dmpSUtL55hYRuWCZiTH8/JbLKfqnXG6ZOpqXt1eR9/+K+eeXPqL8SIvT8USA8xjittZecwHLrQLG9Hg+Gqi5gOWIiPjNmPhofnzzpSx1u1i5tozVWw/wyvtVfPXyVJbmuchJjnM6ogxi/hrifh24zRgTaYzJBHKArX5al4hIr6QMG8IPvzaBDY+4eWB2Fn/ZU8u1v1zHQ8/tYHfNcafjySDV26O4bwYKgCSgEfjQWntd97xHgfuBLuC71to/nWt5OopbRAJBQ0sHT20o5+lNFZxo7+KaS0ay1J3DpDHDnY4mQUgXKhER+YKOn+zk6U0VPLWxnMbWTmbnJPLwvByuzIh3OpoEERW0iMgFam7v4rktlTyxvowjzR1Mz4rnYXcOM7ITTneaqcgXooIWEemlkx1ent96gJVrS6k70c7k9OHkz8sh96IkFbVcMBW0iEgfaev08tKOKh4rLqW68SSXpg1jqdvFly5JJiRERS1fjApaRKSPdXT5+OMH1Swv9lB5tJWLR8WxJM/FDZemEKqilvOkghYR8ZMur4///riGZYUeSutbyE6KYUmei69dnkpYqL/OZpVgoYIWEfEzr8/y512HKSgsYd/hE6THR7M4N5uvTx5NRJiKWk5PBS0i0k98PsuafXUUFJbwcdVxUodFsSg3m1unjiEqPNTpeBJgVNAiIv3MWsu6kiMUrClhe+UxRsZFsnBOFt++Kp3oiF7dTFCCiApaRMQh1lo2lx2lYI2HzWVHSYiJYMHsTO6aPpa4qHCn44nDVNAiIgFge0UDBYUe1n5Sz7Ah4dw3M4P7rs5kWLSKerBSQYuIBJCPDjayrMjDX/bUEhcZxt1Xj2XBrCziYyKcjib9TAUtIhKA9tQ0sbzIw1u7DhEVFsqd09N5YE4WI+OinI4m/UQFLSISwDx1J1heVMprH1YTHhrC7dPSWTgni9ThQ5yOJn6mghYRGQAqjrTw6+JSXnm/CmPgm1PGsDg3mzHx0U5HEz9RQYuIDCBVx1p5bG0pL26rwmstN1+RxuLcbLKSYp2OJn1MBS0iMgDVNrWxcm0Zz2+tpKPLx42XpbIkz8W4UXFOR5M+ooIWERnA6k+088SGMp7bXElLh5frJ4xiqdvFxLRhTkeTXlJBi4gEgWMtHazaWM6qTRWcaOti3sUjWep2cUX6CKejyQVSQYuIBJHjJzt5ZlMFT24sp7G1k9k5ieS7c5iWGe90NPmCVNAiIkGopb2L57ZU8pv1ZRxp7mBaZjwPu3OY6UrAGN2TeiBQQYuIBLG2Ti+rtx5g5doyDje1cUX6cPLdLvLGjVRRB7gzFXSvblBqjPm5MWafMeZjY8yrxpjhPeZ93xjjMcbsN8Zc15v1iIjI2UWFh3LfzEzW/ksuP755InVN7dz/2+18ddkG/rzrMD5f4OyMyfnp1R60MeZaoNBa22WM+SmAtfYRY8x4YDUwDUgF3gUustZ6z7Y87UGLiPSNTq+PVz+oZkWRh4qjrYxLjmOJ28VXLk0hNER71IHEL3vQ1tp3rLVd3U+3AKO7H88HXrDWtltrywEPp8paRET6QXhoCLdOHcO7/zCX/7ptEj5reXj1B3zpF2t5eUcVXV6f0xHlHHpV0J9xP/Cn7sdpwMEe86q6p32OMWahMWa7MWZ7fX19H8YREZGw0BDmT0rj7e/OYcUdk4kMD+WfXvqIvP8oZvXWA3R0qagD1TkL2hjzrjFm12l+5vd4zaNAF/C7TyedZlGnHUu31j5urZ1qrZ2alJR0IX8GERE5h5AQww2XpvDWw7N44u6pxEdH8P0/7GTuz4t4elMFbZ1n/QZSHBB2rhdYa68523xjzD3AjcA8+7cvtKuAMT1eNhqoudCQIiLSN4wxXDM+mXmXjGR9yREKCkv4weu7WVbkYeHsLO6Ynk50xDmrQfpBbw8Sux74BTDXWlvfY/oE4Hn+dpDYGiBHB4mJiAQWay1byhooKCxhU+lR4mMiWDArk7tnjCUuKtzpeIOCX86DNsZ4gEjgaPekLdbaRd3zHuXU99JdwHettX86/VL+RgUtIuKcHZUNFBR6KN5fz9CoMO6bmcn9MzMZFq2i9iddqERERM7Lx1WNLCv08M6eWmIjw7h7xlgWzMokITbS6WhBSQUtIiJfyN5DTSwr8vDWzkNEhYVyx1XpLJyTxcihUU5HCyoqaBERuSCeuhOsKCrltY9qCA0x3H7lGB6cm03q8CFORwsKKmgREemVyqMtrCgq5ZX3qzAGvjllNA/NdZGeEO10tAFNBS0iIn2i6lgrj60t5cVtVXit5aZJaSzOyyY7KdbpaAOSClpERPpUbVMbK9eW8fzWStq7fNx4WSpL81yMGxXndLQBRQUtIiJ+caS5nSfWl/Ps5gpaOrxcNyGZfHcOE9OGOR1tQFBBi4iIXx1r6WDVxnJWbargRFsX7otHstTtYnL6CKejBTQVtIiI9IvjJzt5dnMFT2wop7G1k1muRPLdLq7KSnA6WkBSQYuISL9qae/iuS2V/GZ9GUeaO5iWEU/+PBezXIkYo3tSf0oFLSIijmjr9LJ66wFWri3jcFMbk8YMJ9/twn3xSBU1KmgREXFYe5eXl3dUsaKolOrGk0xIHUq+28W140cREjJ4i1oFLSIiAaHT6+PVD6pZUeSh4mgr45LjWOJ28ZVLUwgdhEWtghYRkYDS5fXx5s5DLCv0UFLXTFZiDIvzXMyflEp4aIjT8fqNClpERAKSz2d5e/dhflXoYe+hJsbED+GhuS6+MSWNyLBQp+P5nQpaREQCmrWWNXvrKCgs4aOq46QMi2LR3Gy+deUYosKDt6hV0CIiMiBYa1lfcoSCwhK2VRwjKS6ShbOzuGN6OtERYU7H63MqaBERGXC2lB2loLCEjZ6jxMdEsGBWJnfPGEtcVLjT0fqMClpERAasHZXHWFZYQtH+eoZGhXHfzEzun5nJsOiBX9QqaBERGfB2Vh2noLCEd/bUEhsZxl0zxvKdWZkkxEY6He2CqaBFRCRo7D3UxPIiD2/uPERUWCh3XJXOwjlZjBwa5XS0L0wFLSIiQcdT18yKYg+vfVhDaIjhtivHsGhuNqnDhzgd7bz5paCNMT8C5gM+oA6411pb0z3v+8ACwAs8bK19+1zLU0GLiMiFqDzawq+LS3nl/SoAvjF5NItzXaQnRDuc7Nz8VdBDrbVN3Y8fBsZbaxcZY8YDq4FpQCrwLnCRtdZ7tuWpoEVEpDeqG0+ycm0pL2w7iNdnmT8plSV5LrKTYp2OdkZnKuheXUvt03LuFgN82vbzgReste3W2nLAw6myFhER8Zu04UP49/kTWf8vedx7dQZv7TzENb9Yy9Ln32ff4aZzLyCA9PqMb2PMj4G7geNAXvfkNGBLj5dVdU873fsXAgsB0tPTextHRESE5KFR/O8bx/NQbjZPbijnmU0VvPHxIa4dn8zD83KYmDbM6YjndM4hbmPMu8Co08x61Fr7Wo/XfR+Istb+wBizHNhsrX2ue96TwFvW2lfOti4NcYuIiD80tnawamMFqzaW09TWRd64JPLn5TA5fYTT0fx/FLcxZizwprV2YndZY639v93z3gZ+aK3dfLZlqKBFRMSfmto6eXZzJU+sL+NYayczXQnku3OYnpXgWCa/fAdtjMnp8fRrwL7ux68DtxljIo0xmUAOsLU36xIREemtoVHhLMlzseERN4/ecAn7Dzdz2+NbuPWxzaz7pJ5AOvW4t0dxvwKM49RpVpXAImttdfe8R4H7gS7gu9baP51redqDFhGR/tTW6eWFrQd4bG0Zh5vamDRmOPluF+6LR2KM6ZcMulCJiIjIGbR3eXllRzUrij1UHTvJ+JSh5LtdXDdhFCEh/i1qFbSIiMg5dHp9vPZhDSuKPJQdaeGi5FiW5Lm48bJUQv1U1CpoERGR8+T1Wd74uIblRR4+qW0mMzGGxbnZ3HRFGuGhvTp863NU0CIiIl+Qz2d5Z89hCgo97K5pYvSIITx255Q+PY/6TAXd6wuViIiIBKuQEMP1E1O4bsIoivbXsWpjBWP76freKmgREZFzMMbgvjgZ98XJ/bbOvh1IFxERkT6hghYREQlAKmgREZEApIIWEREJQCpoERGRAKSCFhERCUAqaBERkQCkghYREQlAAXWpT2NMPaduW9mXEoEjfbxMOTNt7/6l7d2/tL3732DY5mOttUmfnRhQBe0Pxpjtp7vGqfiHtnf/0vbuX9re/W8wb3MNcYuIiAQgFbSIiEgAGgwF/bjTAQYZbe/+pe3dv7S9+9+g3eZB/x20iIjIQDQY9qBFREQGHBW0iIhIAArKgjbG3GKM2W2M8Rljpn5m3veNMR5jzH5jzHVOZQxmxpgfGmOqjTEfdv/c4HSmYGSMub77c+wxxnzP6TzBzhhTYYzZ2f2Z3u50nmBjjHnKGFNnjNnVY1q8MeYvxpiS7t8jnMzY34KyoIFdwNeBdT0nGmPGA7cBE4DrgRXGmND+jzco/Ke1dlL3z1tOhwk23Z/b5cCXgfHA7d2fb/GvvO7P9KA8L9fPfsup/5d7+h6wxlqbA6zpfj5oBGVBW2v3Wmv3n2bWfOAFa227tbYc8ADT+jedSJ+YBnistWXW2g7gBU59vkUGJGvtOqDhM5PnA093P34auKk/MzktKAv6LNKAgz2eV3VPk7631Bjzcfew1aAaluon+iz3Pwu8Y4zZYYxZ6HSYQSLZWnsIoPv3SIfz9KswpwNcKGPMu8Co08x61Fr72pnedpppOs/sApxt+wO/Bn7EqW37I+A/gPv7L92goM9y/5tpra0xxowE/mKM2de91yfiFwO2oK2111zA26qAMT2ejwZq+ibR4HK+298Y8xvgDT/HGYz0We5n1tqa7t91xphXOfU1gwrav2qNMSnW2kPGmBSgzulA/WmwDXG/DtxmjIk0xmQCOcBWhzMFne5/SJ+6mVMH7Unf2gbkGGMyjTERnDr48XWHMwUtY0yMMSbu08fAtehz3R9eB+7pfnwPcKbR0aA0YPegz8YYczNQACQBbxpjPrTWXmet3W2MeRHYA3QBS6y1XiezBqmfGWMmcWrItQJ40NE0Qcha22WMWQq8DYQCT1lrdzscK5glA68aY+DU/5vPW2v/7Gyk4GKMWQ3kAonGmCrgB8BPgBeNMQuAA8AtziXsf7rUp4iISAAabEPcIiIiA4IKWkREJACpoEVERAKQClpERCQAqaBFREQCkApaREQkAKmgRUREAtD/B5HANLtM4AA5AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 1\n", + "fig = plt.figure(figsize=(8, 4))\n", + "print(fig)\n", + "ax = plt.axes()\n", + "print(ax)\n", + "\n", + "ax.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 298, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Figure(576x288) AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": 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74a/vHWJ0bAjzxnnXvfFT3TY7hdBAXx56V8/K1bnTQu6hAv1s3HVhOluO1LClQM/Klet4M+84B4838NWLRuLjJS3VT2dooB9fmJPKa3uOkX/8pNVxlJvSQu7BlmYlExUSwF/0175yEcYYHnr3EMkRQVwzabjVcVzCHeeNIMjfxl/f05nR1LnRQu7Bhvjb+NL5I/gwv4q9ZXoPTlnvo0NV5JbU8ZWL0vG16Z8fgIhgf26ZmczLO0t1DHZ1TvRI8nDLZiYT7G/jsQ+PWB1FKR569xBxQwO5cZp3jOLWW1++IA1fHx8e+6jA6ijKDWkh93BhQ/xYkpXMv3eVUVbbbHUc5cVyS2rZXFDDl84fQYCvzeo4LiVmaCDXT41nbU4JJxrbrI6j3IwWci9wx3mpGOCJj/WsXFnnHx8dISTAl8VZnj3D2bm684I0Wtrt/GvzUaujKDejhdwLJA4L4uqM4azaWkx9S7vVcZQXKqtt5pXcchbPSGJooJ/VcVzS6NhQ5o6O5slNR2nt6LQ6jnIjWsi9xJcvSKOhtYPnthZZHUV5oSc/KcQYwx3npVodxaV9+YI0qhpaeXlnmdVRlBtxSiEXkStF5ICIHBKR+3pYf5GI1InITsfjx73dVzlHRmIYs9MiefyjQto67FbHUV6kobWDZ7cWcVXGcBKHBVkdx6WdNzKSsXGh/OPDIzq8suq1fhdyEbEBDwFXAeOBpSIyvodNPzTGTHE8/reP+yonWDE3jWP1LbySq7/21eBZva2Yky0dfPmCNKujuDwR4csXpHHg+Ek+yK+yOo5yE844I88CDhljCowxbcBzwIJB2Ff10UWjoxkZE8ITHxfqr301KDrthsc/PkJmyjCmJIVbHcctXDs5npjQAB77ULuiqd5xRiFPAIq7vS9xLDvVbBHZJSKviciEPu6rnEBEWD4nld2ldWwvqrU6jvICb+w9RsmJZu7Us/Fe8/f1YfmcVD7Mr+LAMR22VZ2dMwp5T4Mln3q6tx1IMcZMBv4MvNSHfbs2FFkhItkikl1ZqfNsn6sbpyYQGujLPz8ptDqK8gJPfFxIUsQQ5o337slR+mpZVjIBvj48tanQ6ijKDTijkJcA3TuGJgL/dRPWGFNvjGlwvN4A+IlIVG/27fZvPGqMyTTGZEZHRzshtncKDvBlUWYSr+0u53h9i9VxlAfbV1bP1sIabp+Vis3LJ0fpq2HB/lw3OZ5120upa9Yuo+rMnFHItwGjRGSEiPgDS4D13TcQkThxTDosIlmOz63uzb7K+W6fnUKnMTyjA0+oAfT05kIC/XxYmJlodRS3tHxOKs3tnazNKbE6inJx/S7kxpgO4B5gI5AHrDbG7BWRlSKy0rHZzcAeEdkF/AlYYrr0uG9/M6kzS4kM5pIxMTy7tUgHnlADoq6pnRd3lHL9lATCg/ytjuOWJiaEMT1lGE9vKsRu18ap6vSc0o/cGLPBGDPaGJNujPmlY9kjxphHHK//YoyZYIyZbIyZZYz55Ez7qoG3fE4qVQ1tvJpbbnUU5YHW5BTT0m7nttkpVkdxa8vnpFJY3cT7+douSJ2ejuzmpc4fGUVadDD//ES7oinnstsNT206yozUYUyID7M6jlu7ckIc0aEBPKWNU9UZaCH3Uj4+whfmpJJbUseO4lqr4ygP8v7BSopqmrh9dqrVUdyev68Py7KSee9gpc5Vrk5LC7kXu3FaIsH+Np7ZrOOvK+d5clMhMaEBXDEhzuooHuGWmcnYRHhaG6eq09BC7sVCAny5fmoCr+SWUdukcyCr/iusauS9A5Usm5mMv6/+eXGGmKGBXDkxjtXZxTS3aeNU9Xl6pHm5W2am0Nph1y4uyilWbS3C5iMszUq2OopHuXVWCidbOnSeBNUjLeRebnz8UKYmh/PsliJt9Kb6pbWjkzU5JcwbF0vs0ECr43iUmSMiSI8O5lmdhlj1QAu54taZKRRUNbKpoNrqKMqNvb7nGDWNbSybqWfjziYi3DIzhR1Ftewtq7M6jnIxWsgVV08aTtgQP230pvrl2S1FJEcEcf7IKKujeKSbpiUS4OvDs1v0OFX/TQu5ItDPxs3TE9m49xgVJ3X8ddV3hypOsuVIDUuzkvHRcdUHRFiQH9dMiuelHaU0tHZYHUe5EC3kCoBlM5PpsBvWZGujN9V3z24pxs8mOq76ALtlVjKNbZ2s36mN3tR/aCFXAKRHhzAnPZJntxTRqeM6qz5oae/khe0lXD4hjqiQAKvjeLSpSeGMGz6UZ7Yc1cap6jNayNVnls1MprS2mQ91XGfVBxt2l1PX3M4t2uVswIkIy2Yms7esntwSbfSmumghV5+ZNz6WiGB/nttabHUU5Uae2VJEWlQws9MjrY7iFa6fEk+Qv00bvanPaCFXnwnwtXHTtATeyjtO5clWq+MoN3Dw+Elyjp5gaVYyItrIbTCEBvpx7aR4/p1bpo3eFKCFXJ1i8YwkOuyGF7Zrozd1ds9v62rkduO0BKujeJXFWUk0tXXyyi5t9Ka0kKtTjIwJZUbqMJ7fVqyNadQZtXZ0sm57CZePjyNSG7kNqqlJ4YyJDWXVNr0NppxUyEXkShE5ICKHROS+HtbfIiK5jscnIjK527pCEdktIjtFJNsZeVT/LJmRzJGqRjYX1FgdRbmwN/cd50RTO4tnJFkdxeuICItnJLGruJa88nqr4yiL9buQi4gNeAi4ChgPLBWR8adsdgSYa4yZBPwcePSU9RcbY6YYYzL7m0f13/yM4YQG+vL8Nm1Mo07v+W3FJIQP0ZHcLHLD1AT8bT48r2flXs8ZZ+RZwCFjTIExpg14DljQfQNjzCfGmBOOt5sBHTXChQ3xt3H9lAQ27Dmm05uqHhXXNPFhfhWLMpN0JDeLDAv254qJcby4o5SWdp3e1Js5o5AnAN1/EpY4lp3Ol4DXur03wBsikiMiK063k4isEJFsEcmurNR+zgNtSVYSbR12XtxRanUU5YLWZBcjgo7kZrElM5Koa25n495jVkdRFnJGIe/p53iPraRE5GK6Cvn3uy0+zxgzja5L83eLyIU97WuMedQYk2mMyYyOju5vZnUWE+LDmJQYpo3e1Od02g2rs0uYOzqa+PAhVsfxarPTIkmKGKJjP3g5ZxTyEqB7a5dE4HN9IkRkEvAYsMAY89l8mcaYMsdzBfAiXZfqlQtYlJnE/mMn2V2qI0ip//jgYCXH6ltYoo3cLOfjIyyZkcymgmoKqxqtjqMs4oxCvg0YJSIjRMQfWAKs776BiCQD64DbjDEHuy0PFpHQT18DlwN7nJBJOcG1k+MJ8PVhdbb+2lf/8dy2IqJC/LlkbKzVURRd05v6CKzJ0ePUW/W7kBtjOoB7gI1AHrDaGLNXRFaKyErHZj8GIoG/ntLNLBb4SER2AVuBV40xr/c3k3KOsCF+zM8Yzss7y7QxjQKgqqGVt/MqulpM++owFK4gLiyQuaOjWZtTohMeeSmnHInGmA3GmNHGmHRjzC8dyx4xxjzieH2nMWaYo4vZZ93MHC3dJzseEz7dV7mOhZmJnGzp0MY0CoCXdpTSYTcsytTL6q5kUWYSx+tb+UAnPPJK+pNandGsEV2NafTyujLG8Py2YqYmhzMqNtTqOKqbS8d1TXi0Ro9Tr6SFXJ2Rj4+wcHoSHx+qprimyeo4ykK7SurIr2jQs3EX5O/rw/VTEnhz33FqGnXsB2+jhVyd1c3TExGBNTk6kYo3W51dTKCfD9dMGm51FNWDRTMSae80vKRjP3gdLeTqrOLDh3DBqGjWZhdrYxov1dzWyb93ljF/4nBCA/2sjqN6MDZuKJMSw1idrWM/eBst5KpXFmUmUlbXwseHqqyOoiywce8xTrZ2sFAvq7u0hY6xH/aU6kQq3kQLueqVeeNjCQ/y08vrXmp1djHJEUHMHBFhdRR1Btfp2A9eSQu56pUAXxsLJsezce8x6prarY6jBlFxTROfHK5m4fREnSDFxYUN8ePKiXG8vFMnUvEmWshVry3M7JpIZX3u50bgVR5sTU4JInDjdJ0gxR0snJ5EfUsHb+w7bnUUNUi0kKtemxA/lLFxoazVy3Zew243vJBTwvkjo0jQCVLcwpz0SBLCh7BWb4N5DS3kqtdEhJunJ7KrpI6Dx09aHUcNgs0F1ZTWNnOzno27DR8f4aZpCXyYX0l5XbPVcdQg0EKu+uSGqQn4+oiOIOUl1uSUEBroyxUT4qyOovrgpumJGAPrtmufcm+ghVz1SWRIAJeMjeHFHWW0d9qtjqMGUH1LO6/tKefayfEE+tmsjqP6ICUymKwREazNKdE+5V5AC7nqs5unJ1LV0Mr7B3SCBk+2IbeclnY7C/WyultaOD2RI1WN5Bw9YXUUNcC0kKs+u3hsDFEh/jr/sYdbk1PCyJgQpiSFWx1FnYP5GcMJ8rexJlsbvXk6LeSqz/xsXRM0vJ1XQXVDq9Vx1AAoqGwg5+gJFk5PRET7jruj4ABf5mcM55XcMpraOqyOowaQFnJ1ThZmJtFhN7y8U/uUe6K1OSXYfIQbpiZYHUX1w8LpiTS2dfL6nmNWR1EDyCmFXESuFJEDInJIRO7rYb2IyJ8c63NFZFpv91WuaUxcKBkJYTpkqwfqtBvWbS9l7uhoYoYGWh1H9UPWiAhSIoP08rqH63chFxEb8BBwFTAeWCoi40/Z7CpglOOxAni4D/sqF7UwM5G88nr2ltVZHUU50UeHqjhW36J9xz2AiHDztEQ2FVRTXNNkdRw1QJxxRp4FHDLGFBhj2oDngAWnbLMAeMp02QyEi8jwXu6rXNR1k+Pxt/nor30Psya7mPAgPy4dF2N1FOUEN05PRARe2K7HqadyRiFPALo3Xy5xLOvNNr3ZFwARWSEi2SKSXVmp3Z5cQXiQP/PGx/LyzlLaOrRPuSeoa2rnjX3HuX5KAgG+2nfcEySED2FOeiQvbC/Bbtc+5Z7IGYW8pyatp/7XcrpterNv10JjHjXGZBpjMqOjo/sYUQ2UmzMTOdHUzjv7dYIGT7A+t4y2DrteVvcwC6cnUVzTzJYjNVZHUQPAGYW8BEjq9j4ROLUp8+m26c2+yoVdMDKKmNAAnaDBQ6zNKWFsXCgT4odaHUU50RUT4ggN8NXj1EM5o5BvA0aJyAgR8QeWAOtP2WY9cLuj9fosoM4YU97LfZUL87X5cOO0RN49UEnlSe1T7s7yj59kV3EtN2vfcY8zxN/GNZOHs2F3OQ2t2qfc0/S7kBtjOoB7gI1AHrDaGLNXRFaKyErHZhuAAuAQ8Hfgq2fat7+Z1OC6eXoinXbDSzt0ggZ3tjanBF8f4XrtO+6Rbp6eSHN7Jxt2l1sdRTmZrzP+EWPMBrqKdfdlj3R7bYC7e7uvci8jY0KYmhzOmpxi7rxghJ7NuaGOTjvrdpQ6ht8NsDqOGgDTkoeRFhXM2uwSFmUmnX0H5TZ0ZDflFDdPT+Tg8QZyS7RPuTv6IL/r1ohOkOK5RISbpieytbCGwqpGq+MoJ9JCrpzi2snxBPj66EQqbmpNdgmRwf5cPFb7jnuym6Yl4qN9yj2OFnLlFEMD/bhyYhzrd5bR0t5pdRzVBzWNbbyVd5wFUxLws+mfBE8WFxbIBaOieSGnhE7tU+4x9KhVTrNwehL1LR28sU/7lLuTl3eW0t5pWDRDL6t7g4WZiZTVtfDJ4Sqroygn0UKunGZOeiQJ4UNYk62X193JmuwSMhLCGBunfce9wWXjYgkb4sdqHVrZY2ghV07j4yPcNC2Bjw5VUVbbbHUc1Qt7SuvYV17Pwkw9G/cWgX42FkyJZ+PeY9Q1tVsdRzmBFnLlVDdPT8IYWKeNadzC2pwS/G0+XDc53uooahAtnJ5EW4ed9bk6kKYn0EKunCo5MoiZIyJYm1NC1/ABylW1dnTy0s5SLp8QS3iQv9Vx1CCamDCUsXGhrNXbYB5BC7lyuoWZSRRWN7Gt8ITVUdQZvLWvgtqmdhbq4CBeR0RYmJnErpI6Dhw7aXUc1U9ayJXTzc+II9jfxmr9te/S1uQUMzwskPNHRlkdRVng+inx+PqINk71AFrIldMF+ftyzaR4naDBhR2ra+GDg5XcNC0Rm48OqeuNIkMCuHRcDC/tLKW90251HNUPWsjVgFg0I4mmtk5e1cY0LumF7SXYDTrvuJdbOD2JqoY23tlfYXUU1Q9ayNWAmJYcTnp0sPZVdUHGGNbmlJCVGkFqVLDVcZSFLhoTTUxoAKu36eV1d6aFXA0IEWHxjCRyjp7gUIU2pnElW4/UcKSqkcUztJGbt/O1+XDT9ETePVDB8foWq+Ooc6SFXA2YG6YmOhrT6Fm5K3k+u5jQAF/mZwy3OopyAYsyk7CbrjEFlHvSQq4GTHRoAJeMjeGF7SXamMZF1Le0s2F3OddOiWeIv83qOMoFjIgKJmtEBGuyi3XsBzfVr0IuIhEi8qaI5Dueh/WwTZKIvCsieSKyV0S+0W3dT0WkVER2Oh7z+5NHuZ7FM7oa07yrjWlcQtfsdHYWa99x1c1ix9gPW4/UWB1FnYP+npHfB7xtjBkFvO14f6oO4NvGmHHALOBuERnfbf0fjDFTHI8N/cyjXMzc0Y7GNNpX1SWszi5mbFwokxLDrI6iXMj8jOGEBvjyvB6nbqm/hXwB8KTj9ZPA9aduYIwpN8Zsd7w+CeQBCf38XOUm/tOYppIKbUxjqbzyenJL6liUmYSI9h1X/zHE38a1U7rGfqhv0YlU3E1/C3msMaYcugo2EHOmjUUkFZgKbOm2+B4RyRWRx3u6NN9t3xUiki0i2ZWVlf2MrQbToswkOu2GNdqYxlLPbyvG3+bDDVP1d7T6vMWZSbS02/n3Lh37wd2ctZCLyFsisqeHx4K+fJCIhAAvAN80xtQ7Fj8MpANTgHLgd6fb3xjzqDEm0xiTGR0d3ZePVhYbERXMrLQInt9WjN2ujWms0H2ClGHBOkGK+rxJiWGMjQvVPuVu6KyF3BhzmTFmYg+Pl4HjIjIcwPHcY4smEfGjq4g/Y4xZ1+3fPm6M6TTG2IG/A1nO+B+lXM/SrGSKaprYVFBtdRSv9Mbe49Q2tWvfcXVan479sKukjr1ldVbHUX3Q30vr64HljtfLgZdP3UC6bsb9A8gzxvz+lHXdO7LeAOzpZx7loq6YEEd4kB+rthZZHcUrrdpaROKwIZyXrhOkqNO7YWoCAb4+PLdVz8rdSX8L+QPAPBHJB+Y53iMi8SLyaQv084DbgEt66Gb2fyKyW0RygYuBe/uZR7moQD8bN0xNYOPeY1Q3tFodx6scqWrkk8PVLM1KxkcnSFFnEB7kz9UZw3lpRylNbTrhkbvoVyE3xlQbYy41xoxyPNc4lpcZY+Y7Xn9kjBFjzKRTu5kZY24zxmQ41l33acM55ZmWZiXT3mlYt73U6ihe5bltRdh8hIU6QYrqhSVZyZxs7eCVXP1z7C50ZDc1aEbHhjItOZxV24p0BKlB0tZhZ212CZeNiyFmaKDVcZQbmJE6jPToYJ7T22BuQwu5GlRLs5IpqGzUEaQGyRv7jlHd2MbSrGSroyg3ISIszUpme1Et+4/Vn30HZTkt5GpQXT2pawSp57SLy6BYtbWIhPAhXDBKu2yq3rtpWiL+Nm305i60kKtBFeTvy4Kp8by6u5zapjar43i0wqpGPj5UzZIZSdi0kZvqg2HB/lyVEce67SU0t3VaHUedhRZyNeiWZaV03bvVkd4G1HPbirsauekEKeocLJmRTH1LBxt2a6M3V6eFXA268fFDmZYczjNbinSktwHS9UOpmEvGxhAXpo3cVN/NSosgLSqYf205anUUdRZayJUlbp2V8ln/ZuV8G/ceo6qhjWUztZGbOjciwi2zUthRVMueUh3pzZVpIVeWmJ8xnGFBfvxrs/7aHwhPbzpKckQQc7WRm+qHm6clEujnwzN6Vu7StJArSwT62ViUmcSbecc5VqfTmzrT/mP1bC2s4dZZOpKb6p+wID8WTE7gpR1lOr2pC9NCriyzbGYynXbDc9t04Aln+tfmo/j7+rBwujZyU/1366wUmts7WaeNU12WFnJlmZTIYC4cHc1zW4vp6LRbHccjnGxp58XtpVw7KV6nK1VOkZEYxuSkcJ7efFRHZHRRWsiVpW6dmcyx+hbeyutxBlzVRy/tKKWxrZPbZ6dYHUV5kNtmpXC4slGnIXZRWsiVpS4ZG8PwsEBt9OYExhie2nSUSY4zKKWc5ZpJwwnXxqkuSwu5spSvzYdbZ6Xw0aEq8o+ftDqOW9typIb8igZunaVn48q5Pm2cunGvNk51RVrIleWWzEjC39eHf35SaHUUt/b05qOEDfHj2knxVkdRHuiWmcnYjeFZ7YrmcvpVyEUkQkTeFJF8x/Ow02xXKCK7RWSniGT3dX/l2SJDAlgwOZ5120upa9IuLueirLaZ1/ccY/GMJIb426yOozxQSmQwl46N4ZktRbS06/jrrqS/Z+T3AW8bY0YBbzven87FxpgpxpjMc9xfebAvnJdKc3snq7N1tqVz8dSmrhbF2shNDaQ7zhtBdWMb63eVWR1FddPfQr4AeNLx+kng+kHeX3mICfFhZI2I4MlNhXTq+Ot90tTWwaqtRVw5MY7EYUFWx1EebE56JGNiQ3ni40LtiuZC+lvIY40x5QCO55jTbGeAN0QkR0RWnMP+iMgKEckWkezKysp+xlau6IvnpVJyopm38o5bHcWtrNteSl1zO188b4TVUZSHExHuOC+VvPJ6NhfUWB1HOZy1kIvIWyKyp4fHgj58znnGmGnAVcDdInJhX4MaYx41xmQaYzKjo3X8aE902bhYEsKH8M+PC62O4jbsdsMTHx9hUmIY01O0iYkaeNdPTWBYkB9PfHzE6ijK4ayF3BhzmTFmYg+Pl4HjIjIcwPHc46gexpgyx3MF8CKQ5VjVq/2Vd/C1+XDb7BQ2FVSTV15vdRy38EF+JYcrG/nieSMQ0XHV1cAL9LOxbGYyb+Ydp6i6yeo4iv5fWl8PLHe8Xg68fOoGIhIsIqGfvgYuB/b0dn/lXZbMSCLQz4fHP9Jf+73x+MeFxIQGMD9juNVRlBe5bVYqNhGe3FRodRRF/wv5A8A8EckH5jneIyLxIrLBsU0s8JGI7AK2Aq8aY14/0/7Ke4UH+bMoM4mXdpZyvF4HnjiT/OMn+eBgJbfPTsHfV4eEUIMnLiyQ+RnDWb2tmJM6K5rl+nX0G2OqjTGXGmNGOZ5rHMvLjDHzHa8LjDGTHY8Jxphfnm1/5d3uPD+NTrvhcb0Hd0b/+OgI/r4+LM1KtjqK8kJ3XjCCk61dPSaUtfRnvHI5yZFBzM8YzrObi/TX/mkcr29h3fZSFmUmEhkSYHUc5YUmJYYzJz2Sf3x0hNYOHSDGSlrIlUu668J0/bV/Bo9/dIQOu50VF6RbHUV5sZVz0zle38rLO3SAGCtpIVcuKSMxjDnpkTz+USFtHTpXeXd1ze08s6WIqyfFkxypA8Ao61wwKorxw4fyyAeHsetATpbRQq5c1ooL0zhW36LDQZ7iX5uP0tDawcq5aVZHUV5ORLhrbhoFlY28qQM5WUYLuXJZc0dHMzYulEc/OKzDQTq0tHfyxMdHuHB0NBPiw6yOoxRXZwwnKWIIj7yvx6lVtJArl/Xpr/2Dxxt4K0/HCgJYk1NCVUMbX5mr98aVa/C1+fDlC9LYUVTL1iPa8Qhg1dYiHh3E2w1ayJVLu3ZSPMkRQfzp7Xyv/7Xf0Wnn7x8UMCUpnFlpEVbHUeozC6cnERHsz8PvH7Y6iuWa2jr43RsH+OBgFT4+gzPaohZy5dJ8bT7cc/FIdpfW8e4B7z4r/3duGUU1Taycm67DsSqXMsTfxpfOH8F7ByrZWVxrdRxLPbO5iKqGNr5x2ahB+0wt5Mrl3TAtgaSIITz4lveelXd02nnwrXzGxoVy+fhYq+Mo9TnL56QyLMiPP7510Ooolmlq6+BvHxzm/JFRzEgdvKtmWsiVy/Oz+XD3RSPZVVLHewe9cwrbl3aWUVjdxL3zRg/a5Tql+iIkwJcvX5jGewcq2V50wuo4lrDibBy0kCs3ceO0RBLCvfOsvL3Tzp/ezmdC/FA9G1cubfnsVCKC/fnjW/lWRxl0zW2dlpyNgxZy5Sb8fX24++KR7Cyu5YP8KqvjDKp120soqmniW/NG671x5dKCA3xZcWEaHxysJOeod52VP7PlqCVn46CFXLmRm6d3nZX/8a2DXnNW3tZh509vH2JyYhiXjI2xOo5SZ3X77BQig/296l55c1snj7xvzdk4aCFXbsTf14d7LhnJjqJa3tznHaNIrckpprS2mXv1bFy5iSB/X+6am8aH+VVkF3pHv/InNxVadjYOWsiVm1k4PZH06GB+/fp+Ojo9ewz2lvZO/vLOIaYlhzN3dLTVcZTqtVtnpRAVEsCvX9/v8VfPTjS28dC7h7h4TLQlZ+OghVy5GV+bD9+/ciyHKxtZnV1idZwB9Y+PjlBe18J3rxirZ+PKrQT5+/KteaPZVniCjXs9++rZn985RGNrB/ddNc6yDP0q5CISISJviki+43lYD9uMEZGd3R71IvJNx7qfikhpt3Xz+5NHeYd542OZkTqMP7x1kKa2DqvjDIiqhlYefu8wl42LZXZ6pNVxlOqzRZmJjIoJ4YHX8jx2BsOj1Y08vbmQhdOTGBMXalmO/p6R3we8bYwZBbzteP9fjDEHjDFTjDFTgOlAE/Bit03+8Ol6Y8yGfuZRXkBEuO+qcVSebOWxD49YHWdA/OHNg7S0d/KD+WOtjqLUOfG1+fDD+eMorG7imS1HrY4zIP5v4wF8fXz41uWjLc3R30K+AHjS8fpJ4PqzbH8pcNgY45n/r6pBMz1lGFdNjONv7x+m8mSr1XGc6uDxk6zaWsSts1JIjw6xOo5S5+yiMdGcPzKKB9/Op6653eo4TrWj6ASv5pbz5QtGEDs00NIs/S3kscaYcgDH89n6xywBVp2y7B4RyRWRx3u6NP8pEVkhItkikl1Z6Z2je6n/9t0rxtDaYfe4bi73b8gjOMCXr19qTQtYpZxFRPjB/LHUNbfz13cPWR3HaYwx/GrDfqJC/FnhAjMRnrWQi8hbIrKnh8eCvnyQiPgD1wFrui1+GEgHpgDlwO9Ot78x5lFjTKYxJjM6WlvwKkiLDuG22Sk8u7WIXR4yUcOH+ZW8d6CSr18yiohgf6vjKNVvE+LDuGlaIk98XEhRdZPVcZzi37nlbC2s4ZuXjSYkwNfqOGcv5MaYy4wxE3t4vAwcF5HhAI7nM01PdRWw3RjzWRNGY8xxY0ynMcYO/B3I6t//HOVtvjVvNNEhAfzPS3voHKS5fwdKa0cnP/v3PpIjgrh9TorVcZRymu9cPgZ/Xx/+5+U9bt8dra65nZ+/so+MhDCWZiVbHQfo/6X19cByx+vlwMtn2HYpp1xW//RHgMMNwJ5+5lFeJjTQj/93zXh2l9bxr83u3fTikfcKOFTRwM8WTCDA12Z1HKWcJi4skO9cPpoPDlby79xyq+P0y+/eOEB1Qyv335CBzUUmMOpvIX8AmCci+cA8x3tEJF5EPmuBLiJBjvXrTtn//0Rkt4jkAhcD9/Yzj/JC10wazgWjovjtxgNU1LdYHeecHKpo4KF3D3Hd5HguHqNDsSrPc9vsVCYlhvG//95HXZN7NnzbWVzL05uPcvvsVDISw6yO85l+FXJjTLUx5lJjzCjHc41jeZkxZn637ZqMMZHGmLpT9r/NGJNhjJlkjLnu04ZzSvWFiPCz6ybQ2mHnF6/mWR2nz+x2ww/X7WaIv43/d814q+MoNSBsPsL9N2RQ09jKA6/vtzpOn3V02vnRi7uJDgng2xZ3NzuVjuymPEJadAgrL0pn/a4yPnCzOctXZxeztbCGH80fR3RogNVxlBowExPC+OJ5I1i1tcjtxmF/atNR9pbV85NrJxAa6Gd1nP+ihVx5jK9elE56dDDfXbuLE41tVsfplYqTLdy/IY9ZaREszEy0Oo5SA+7eeaNJCB/CD9btpqW90+o4vXK4soHfbDzARWOimZ8RZ3Wcz9FCrjxGoJ+NB5dMpaaxjR++uNvlW8fa7YbvrsmlpcPO/Tdk6HjqyisEB/hy/40Z5Fc0cP8G178V1tZh55vP7STAz4cHbpzkksepFnLlUSYmhPGteWN4bc8x1ua49qQqf/+wgPcPVvLja8aTpiO4KS8yd3Q0Xzp/BE9tOsobe49ZHeeMfvfmAXaX1vHrmyYRF2btCG6no4VceZwVF6Yxc0QEP12/l6PVjVbH6dGOohP8ZuMBrpoYxy0zXaMvqlKD6XtXjmFC/FC+90Iu5XXNVsfp0ceHqvjb+wUsm5nMFRNc75L6p7SQK49j8xF+v3gKPj7Cvc/vpN3F5i2va27na6t2EDs0kAducs1LdUoNtABfG39eOpW2Djv3Pr/T5QZ0qmls41urd5IeHcz/u9q1e5NoIVceKSF8CPffkMH2olp+/PJel7lfbkxXV7Pyuhb+vGwqYUNcq/WrUoMpLTqEn103gc0FNfzp7Xyr43ymvdPON57bQU1jGw8umcoQf9ceoMn6QWKVGiDXTo4nr7yev753mPToYO68IM3qSPz5nUO8uruc7185lmnJp50jSCmvcfP0RDYVVPPg2/mMiArm+qkJluYxxvCT9Xv5ML+KX9+UwcQE1xn45XS0kCuP9p3Lx1BQ2cgvN+SRGhnMZeNjLcuyelsxv3/zIDdOS2DlXOt/VCjlCkSEX92YQemJZr67dhcxQwOYkx5lWZ6/f1jAs1uK+MpF6Sye4R7tV/TSuvJoPj7CHxZPYWJ8GF9/bgf7yuotyfHugQp+8OJuLhgVxa/1vrhS/yXA18ajt2WSEhnMXU/ncPD4SUtyvL6nnF+9tp+rM4bz3cvHWJLhXGghVx5viL+Nx5ZnMjTQjy88sXXQ/0jkltTy1X9tZ2xcKA/fOh0/mx52Sp0qLMiPf94xg0A/G3c8sY1jdYM7b8Lmgmq++fxOpiSF87tFk/FxkQlRekP/oiivEDs0kKe+1DVL7uK/bSK3pHZQPje7sIbbH99KZIg/T9wxwyXmLlbKVSUOC+Lx5TOobWrjpoc/4XBlw6B87pv7jnP741tJHBbE32/PJNDPtRu3nUoLufIao2NDWbNyNsEBviz7+xa2FFQP6Odt2F3Osse2MCzIn2fvnEVMqGsOJqGUK8lIDGPVilm0tHdy88OfsKPoxIB+3prsYlb+K4dxw4ey5q7ZRIW433wHWsiVV0mJDGbtyjnEhQVy++Nb2bB7YCbce+zDAu5+djsZCWG88JU5JEcGDcjnKOWJJiWG88JX5hAa6MfSv2/mnf3Hnf4Zxhj+9v5hvrs2lznpkTx750yGBfs7/XMGgxZy5XXiwgJ5fsUsxg4fylef2c63V++ivsU58yOfaGzj26t38YtX87hyQhzP3DmTCDf946CUlVKjgnnhK3MYGRPCnU9m88tX99Hc5pxJVspqm/nCE9s+a9j22PJMgt34tpe4ykAZfZGZmWmys7OtjqHcXHunnT+/nc9D7x0mNjSA3y6czJyR59btxRjDuu2l/HJDHvXN7aycm86980Zjc6MGM0q5oobWDn75ah6rthaRHBHEAzdm9Os4XZ1dzC9eyaPDbrjvqrHcNivFLRq2iUiOMSazx3X9KeQishD4KTAOyDLG9FhdReRK4EHABjxmjHnAsTwCeB5IBQqBRcaYs94Q0UKunGlH0Qm+vXoXBVWNzB0dzRfOS2XuqOheHdwdnXY+PlzNI+8dZlNBNdOSw7n/xgzGxg0dhORKeY9PDlfxw3W7Kaxu4rrJ8dw6K4UZqcN61ZWztaOTjXuP89QnhWQfPUHWiAh+c/MkUiKDByG5cwxkIR8H2IG/Ad/pqZCLiA04CMwDSoBtwFJjzD4R+T+gxhjzgIjcBwwzxnz/bJ+rhVw5W3NbJ3//sICnNx+l8mQrI6KCWTwjiYnxYYyKDSEmNAARodNuqG5opfhEM6/vKeelnWVUnmwlPMiP71w+hmVZyW7x614pd9TS3smDb+fz1CeFNLZ1khYVzMLMJGanR5IQPoSoEP/PjtOy2maOVDWyqaCa1duKqW5sIyliCCsuTOcWNzxOB6yQd/uA9zh9IZ8N/NQYc4Xj/Q8AjDG/EpEDwEXGmHIRGQ68Z4w5ay98LeRqoLR12HltTzlPfFzIzuLaz5YPDfQl0M9GVUMrn87t4GcTLhoTw41TE7hkXAwBvu7VZUUpd9XU1sGrueWszi5mW+F/LuIG+PoQFRJA5clW2hyTJfkIXDoulltmJnNhL6+0uaIzFfLBuLufABR3e18CzHS8jjXGlAM4innM6f4REVkBrABITnaPYfOU+/H39WHBlAQWTEmg4mQLh443kF/RQH7FSdo67MQODSQmNICYoYFkpUa4bStXpdxZkL8vCzOTWJiZRFF1EwePn6S0tpnS2mYq6luIHRpIalQwqZHBjI4NIdINu5T1xVkLuYi8BfQ0EeuPjDEv9+Izevr50+fLAMaYR4FHoeuMvK/7K9VXMaGBxIQGnnPDGqXUwEuODPL67p1nLeTGmMv6+RklQFK394lAmeP1cREZ3u3SekU/P0sppZTyKoPRj3wbMEpERoiIP7AEWO9Ytx5Y7ni9HOjNGb5SSimlHPpVyEXkBhEpAWYDr4rIRsfyeBHZAGCM6QDuATYCecBqY8xexz/xADBPRPLpatX+QH/yKKWUUt5GB4RRSimlXNyZWq3rEK1KKaWUG9NCrpRSSrkxLeRKKaWUG9NCrpRSSrkxt2zsJiKVwFEgCqiyOI470O+p9/S76h39nnpHv6fe0+/qzFKMMdE9rXDLQv4pEck+XSs+9R/6PfWefle9o99T7+j31Hv6XZ07vbSulFJKuTEt5EoppZQbc/dC/qjVAdyEfk+9p99V7+j31Dv6PfWeflfnyK3vkSullFLezt3PyJVSSimvpoVcKaWUcmNuV8hFJElE3hWRPBHZKyLfsDqTKxMRm4jsEJFXrM7iykQkXETWish+x39bs63O5IpE5F7HcbdHRFaJSKDVmVyFiDwuIhUisqfbsggReVNE8h3Pw6zM6CpO8139xnH85YrIiyISbmFEt+J2hRzoAL5tjBkHzALuFpHxFmdyZd+ga/pYdWYPAq8bY8YCk9Hv7HNEJAH4OpBpjJkI2IAl1qZyKf8Erjxl2X3A28aYUcDbjveq5+/qTWCiMWYScBD4wWCHclduV8iNMeXGmO2O1yfp+oObYG0q1yQiicDVwGNWZ3FlIjIUuBD4B4Axps0YU2tpKNflCwwREV8gCCizOI/LMMZ8ANScsngB8KTj9ZPA9YOZyVX19F0ZY94wxnQ43m4GEgc9mJtyu0LenYikAlOBLRZHcVV/BL4H2C3O4erSgErgCcdtiMdEJNjqUK7GGFMK/BYoAsqBOmPMG9amcnmxxphy6DoJAWIszuMuvgi8ZnUId+G2hVxEQoAXgG8aY+qtzuNqROQaoMIYk2N1FjfgC0wDHjbGTAUa0Uugn+O4v7sAGAHEA8Eicqu1qZSnEZEf0XUL9Rmrs7gLtyzkIuJHVxF/xhizzuo8Luo84DoRKQSeAy4RkX9ZG8lllQAlxphPr+yspauwq/92GXDEGFNpjGkH1gFzLM7k6o6LyHAAx3OFxXlcmogsB64BbjE6yEmvuV0hFxGh615mnjHm91bncVXGmB8YYxKNMal0NUh6xxijZ089MMYcA4pFZIxj0aXAPgsjuaoiYJaIBDmOw0vRRoFnsx5Y7ni9HHjZwiwuTUSuBL4PXGeMabI6jztxu0JO15nmbXSdYe50POZbHUq5va8Bz4hILjAFuN/aOK7HccViLbAd2E3X3w8dVtNBRFYBm4AxIlIiIl8CHgDmiUg+MM/x3uud5rv6CxAKvOn4u/6IpSHdiA7RqpRSSrkxdzwjV0oppZSDFnKllFLKjWkhV0oppdyYFnKllFLKjWkhV0oppdyYFnKllFLKjWkhV0oppdzY/wdjRBrFE5MVDgAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 2\n", + "fig, ax = plt.subplots(figsize=(8, 4))\n", + "print(fig, ax)\n", + "ax.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 299, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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74a/vHWJ0bAjzxnnXvfFT3TY7hdBAXx56V8/K1bnTQu6hAv1s3HVhOluO1LClQM/Klet4M+84B4838NWLRuLjJS3VT2dooB9fmJPKa3uOkX/8pNVxlJvSQu7BlmYlExUSwF/0175yEcYYHnr3EMkRQVwzabjVcVzCHeeNIMjfxl/f05nR1LnRQu7Bhvjb+NL5I/gwv4q9ZXoPTlnvo0NV5JbU8ZWL0vG16Z8fgIhgf26ZmczLO0t1DHZ1TvRI8nDLZiYT7G/jsQ+PWB1FKR569xBxQwO5cZp3jOLWW1++IA1fHx8e+6jA6ijKDWkh93BhQ/xYkpXMv3eVUVbbbHUc5cVyS2rZXFDDl84fQYCvzeo4LiVmaCDXT41nbU4JJxrbrI6j3IwWci9wx3mpGOCJj/WsXFnnHx8dISTAl8VZnj3D2bm684I0Wtrt/GvzUaujKDejhdwLJA4L4uqM4azaWkx9S7vVcZQXKqtt5pXcchbPSGJooJ/VcVzS6NhQ5o6O5slNR2nt6LQ6jnIjWsi9xJcvSKOhtYPnthZZHUV5oSc/KcQYwx3npVodxaV9+YI0qhpaeXlnmdVRlBtxSiEXkStF5ICIHBKR+3pYf5GI1InITsfjx73dVzlHRmIYs9MiefyjQto67FbHUV6kobWDZ7cWcVXGcBKHBVkdx6WdNzKSsXGh/OPDIzq8suq1fhdyEbEBDwFXAeOBpSIyvodNPzTGTHE8/reP+yonWDE3jWP1LbySq7/21eBZva2Yky0dfPmCNKujuDwR4csXpHHg+Ek+yK+yOo5yE844I88CDhljCowxbcBzwIJB2Ff10UWjoxkZE8ITHxfqr301KDrthsc/PkJmyjCmJIVbHcctXDs5npjQAB77ULuiqd5xRiFPAIq7vS9xLDvVbBHZJSKviciEPu6rnEBEWD4nld2ldWwvqrU6jvICb+w9RsmJZu7Us/Fe8/f1YfmcVD7Mr+LAMR22VZ2dMwp5T4Mln3q6tx1IMcZMBv4MvNSHfbs2FFkhItkikl1ZqfNsn6sbpyYQGujLPz8ptDqK8gJPfFxIUsQQ5o337slR+mpZVjIBvj48tanQ6ijKDTijkJcA3TuGJgL/dRPWGFNvjGlwvN4A+IlIVG/27fZvPGqMyTTGZEZHRzshtncKDvBlUWYSr+0u53h9i9VxlAfbV1bP1sIabp+Vis3LJ0fpq2HB/lw3OZ5120upa9Yuo+rMnFHItwGjRGSEiPgDS4D13TcQkThxTDosIlmOz63uzb7K+W6fnUKnMTyjA0+oAfT05kIC/XxYmJlodRS3tHxOKs3tnazNKbE6inJx/S7kxpgO4B5gI5AHrDbG7BWRlSKy0rHZzcAeEdkF/AlYYrr0uG9/M6kzS4kM5pIxMTy7tUgHnlADoq6pnRd3lHL9lATCg/ytjuOWJiaEMT1lGE9vKsRu18ap6vSc0o/cGLPBGDPaGJNujPmlY9kjxphHHK//YoyZYIyZbIyZZYz55Ez7qoG3fE4qVQ1tvJpbbnUU5YHW5BTT0m7nttkpVkdxa8vnpFJY3cT7+douSJ2ejuzmpc4fGUVadDD//ES7oinnstsNT206yozUYUyID7M6jlu7ckIc0aEBPKWNU9UZaCH3Uj4+whfmpJJbUseO4lqr4ygP8v7BSopqmrh9dqrVUdyev68Py7KSee9gpc5Vrk5LC7kXu3FaIsH+Np7ZrOOvK+d5clMhMaEBXDEhzuooHuGWmcnYRHhaG6eq09BC7sVCAny5fmoCr+SWUdukcyCr/iusauS9A5Usm5mMv6/+eXGGmKGBXDkxjtXZxTS3aeNU9Xl6pHm5W2am0Nph1y4uyilWbS3C5iMszUq2OopHuXVWCidbOnSeBNUjLeRebnz8UKYmh/PsliJt9Kb6pbWjkzU5JcwbF0vs0ECr43iUmSMiSI8O5lmdhlj1QAu54taZKRRUNbKpoNrqKMqNvb7nGDWNbSybqWfjziYi3DIzhR1Ftewtq7M6jnIxWsgVV08aTtgQP230pvrl2S1FJEcEcf7IKKujeKSbpiUS4OvDs1v0OFX/TQu5ItDPxs3TE9m49xgVJ3X8ddV3hypOsuVIDUuzkvHRcdUHRFiQH9dMiuelHaU0tHZYHUe5EC3kCoBlM5PpsBvWZGujN9V3z24pxs8mOq76ALtlVjKNbZ2s36mN3tR/aCFXAKRHhzAnPZJntxTRqeM6qz5oae/khe0lXD4hjqiQAKvjeLSpSeGMGz6UZ7Yc1cap6jNayNVnls1MprS2mQ91XGfVBxt2l1PX3M4t2uVswIkIy2Yms7esntwSbfSmumghV5+ZNz6WiGB/nttabHUU5Uae2VJEWlQws9MjrY7iFa6fEk+Qv00bvanPaCFXnwnwtXHTtATeyjtO5clWq+MoN3Dw+Elyjp5gaVYyItrIbTCEBvpx7aR4/p1bpo3eFKCFXJ1i8YwkOuyGF7Zrozd1ds9v62rkduO0BKujeJXFWUk0tXXyyi5t9Ka0kKtTjIwJZUbqMJ7fVqyNadQZtXZ0sm57CZePjyNSG7kNqqlJ4YyJDWXVNr0NppxUyEXkShE5ICKHROS+HtbfIiK5jscnIjK527pCEdktIjtFJNsZeVT/LJmRzJGqRjYX1FgdRbmwN/cd50RTO4tnJFkdxeuICItnJLGruJa88nqr4yiL9buQi4gNeAi4ChgPLBWR8adsdgSYa4yZBPwcePSU9RcbY6YYYzL7m0f13/yM4YQG+vL8Nm1Mo07v+W3FJIQP0ZHcLHLD1AT8bT48r2flXs8ZZ+RZwCFjTIExpg14DljQfQNjzCfGmBOOt5sBHTXChQ3xt3H9lAQ27Dmm05uqHhXXNPFhfhWLMpN0JDeLDAv254qJcby4o5SWdp3e1Js5o5AnAN1/EpY4lp3Ol4DXur03wBsikiMiK063k4isEJFsEcmurNR+zgNtSVYSbR12XtxRanUU5YLWZBcjgo7kZrElM5Koa25n495jVkdRFnJGIe/p53iPraRE5GK6Cvn3uy0+zxgzja5L83eLyIU97WuMedQYk2mMyYyOju5vZnUWE+LDmJQYpo3e1Od02g2rs0uYOzqa+PAhVsfxarPTIkmKGKJjP3g5ZxTyEqB7a5dE4HN9IkRkEvAYsMAY89l8mcaYMsdzBfAiXZfqlQtYlJnE/mMn2V2qI0ip//jgYCXH6ltYoo3cLOfjIyyZkcymgmoKqxqtjqMs4oxCvg0YJSIjRMQfWAKs776BiCQD64DbjDEHuy0PFpHQT18DlwN7nJBJOcG1k+MJ8PVhdbb+2lf/8dy2IqJC/LlkbKzVURRd05v6CKzJ0ePUW/W7kBtjOoB7gI1AHrDaGLNXRFaKyErHZj8GIoG/ntLNLBb4SER2AVuBV40xr/c3k3KOsCF+zM8Yzss7y7QxjQKgqqGVt/MqulpM++owFK4gLiyQuaOjWZtTohMeeSmnHInGmA3GmNHGmHRjzC8dyx4xxjzieH2nMWaYo4vZZ93MHC3dJzseEz7dV7mOhZmJnGzp0MY0CoCXdpTSYTcsytTL6q5kUWYSx+tb+UAnPPJK+pNandGsEV2NafTyujLG8Py2YqYmhzMqNtTqOKqbS8d1TXi0Ro9Tr6SFXJ2Rj4+wcHoSHx+qprimyeo4ykK7SurIr2jQs3EX5O/rw/VTEnhz33FqGnXsB2+jhVyd1c3TExGBNTk6kYo3W51dTKCfD9dMGm51FNWDRTMSae80vKRjP3gdLeTqrOLDh3DBqGjWZhdrYxov1dzWyb93ljF/4nBCA/2sjqN6MDZuKJMSw1idrWM/eBst5KpXFmUmUlbXwseHqqyOoiywce8xTrZ2sFAvq7u0hY6xH/aU6kQq3kQLueqVeeNjCQ/y08vrXmp1djHJEUHMHBFhdRR1Btfp2A9eSQu56pUAXxsLJsezce8x6prarY6jBlFxTROfHK5m4fREnSDFxYUN8ePKiXG8vFMnUvEmWshVry3M7JpIZX3u50bgVR5sTU4JInDjdJ0gxR0snJ5EfUsHb+w7bnUUNUi0kKtemxA/lLFxoazVy3Zew243vJBTwvkjo0jQCVLcwpz0SBLCh7BWb4N5DS3kqtdEhJunJ7KrpI6Dx09aHUcNgs0F1ZTWNnOzno27DR8f4aZpCXyYX0l5XbPVcdQg0EKu+uSGqQn4+oiOIOUl1uSUEBroyxUT4qyOovrgpumJGAPrtmufcm+ghVz1SWRIAJeMjeHFHWW0d9qtjqMGUH1LO6/tKefayfEE+tmsjqP6ICUymKwREazNKdE+5V5AC7nqs5unJ1LV0Mr7B3SCBk+2IbeclnY7C/WyultaOD2RI1WN5Bw9YXUUNcC0kKs+u3hsDFEh/jr/sYdbk1PCyJgQpiSFWx1FnYP5GcMJ8rexJlsbvXk6LeSqz/xsXRM0vJ1XQXVDq9Vx1AAoqGwg5+gJFk5PRET7jruj4ABf5mcM55XcMpraOqyOowaQFnJ1ThZmJtFhN7y8U/uUe6K1OSXYfIQbpiZYHUX1w8LpiTS2dfL6nmNWR1EDyCmFXESuFJEDInJIRO7rYb2IyJ8c63NFZFpv91WuaUxcKBkJYTpkqwfqtBvWbS9l7uhoYoYGWh1H9UPWiAhSIoP08rqH63chFxEb8BBwFTAeWCoi40/Z7CpglOOxAni4D/sqF7UwM5G88nr2ltVZHUU50UeHqjhW36J9xz2AiHDztEQ2FVRTXNNkdRw1QJxxRp4FHDLGFBhj2oDngAWnbLMAeMp02QyEi8jwXu6rXNR1k+Pxt/nor30Psya7mPAgPy4dF2N1FOUEN05PRARe2K7HqadyRiFPALo3Xy5xLOvNNr3ZFwARWSEi2SKSXVmp3Z5cQXiQP/PGx/LyzlLaOrRPuSeoa2rnjX3HuX5KAgG+2nfcEySED2FOeiQvbC/Bbtc+5Z7IGYW8pyatp/7XcrpterNv10JjHjXGZBpjMqOjo/sYUQ2UmzMTOdHUzjv7dYIGT7A+t4y2DrteVvcwC6cnUVzTzJYjNVZHUQPAGYW8BEjq9j4ROLUp8+m26c2+yoVdMDKKmNAAnaDBQ6zNKWFsXCgT4odaHUU50RUT4ggN8NXj1EM5o5BvA0aJyAgR8QeWAOtP2WY9cLuj9fosoM4YU97LfZUL87X5cOO0RN49UEnlSe1T7s7yj59kV3EtN2vfcY8zxN/GNZOHs2F3OQ2t2qfc0/S7kBtjOoB7gI1AHrDaGLNXRFaKyErHZhuAAuAQ8Hfgq2fat7+Z1OC6eXoinXbDSzt0ggZ3tjanBF8f4XrtO+6Rbp6eSHN7Jxt2l1sdRTmZrzP+EWPMBrqKdfdlj3R7bYC7e7uvci8jY0KYmhzOmpxi7rxghJ7NuaGOTjvrdpQ6ht8NsDqOGgDTkoeRFhXM2uwSFmUmnX0H5TZ0ZDflFDdPT+Tg8QZyS7RPuTv6IL/r1ohOkOK5RISbpieytbCGwqpGq+MoJ9JCrpzi2snxBPj66EQqbmpNdgmRwf5cPFb7jnuym6Yl4qN9yj2OFnLlFEMD/bhyYhzrd5bR0t5pdRzVBzWNbbyVd5wFUxLws+mfBE8WFxbIBaOieSGnhE7tU+4x9KhVTrNwehL1LR28sU/7lLuTl3eW0t5pWDRDL6t7g4WZiZTVtfDJ4Sqroygn0UKunGZOeiQJ4UNYk62X193JmuwSMhLCGBunfce9wWXjYgkb4sdqHVrZY2ghV07j4yPcNC2Bjw5VUVbbbHUc1Qt7SuvYV17Pwkw9G/cWgX42FkyJZ+PeY9Q1tVsdRzmBFnLlVDdPT8IYWKeNadzC2pwS/G0+XDc53uooahAtnJ5EW4ed9bk6kKYn0EKunCo5MoiZIyJYm1NC1/ABylW1dnTy0s5SLp8QS3iQv9Vx1CCamDCUsXGhrNXbYB5BC7lyuoWZSRRWN7Gt8ITVUdQZvLWvgtqmdhbq4CBeR0RYmJnErpI6Dhw7aXUc1U9ayJXTzc+II9jfxmr9te/S1uQUMzwskPNHRlkdRVng+inx+PqINk71AFrIldMF+ftyzaR4naDBhR2ra+GDg5XcNC0Rm48OqeuNIkMCuHRcDC/tLKW90251HNUPWsjVgFg0I4mmtk5e1cY0LumF7SXYDTrvuJdbOD2JqoY23tlfYXUU1Q9ayNWAmJYcTnp0sPZVdUHGGNbmlJCVGkFqVLDVcZSFLhoTTUxoAKu36eV1d6aFXA0IEWHxjCRyjp7gUIU2pnElW4/UcKSqkcUztJGbt/O1+XDT9ETePVDB8foWq+Ooc6SFXA2YG6YmOhrT6Fm5K3k+u5jQAF/mZwy3OopyAYsyk7CbrjEFlHvSQq4GTHRoAJeMjeGF7SXamMZF1Le0s2F3OddOiWeIv83qOMoFjIgKJmtEBGuyi3XsBzfVr0IuIhEi8qaI5Dueh/WwTZKIvCsieSKyV0S+0W3dT0WkVER2Oh7z+5NHuZ7FM7oa07yrjWlcQtfsdHYWa99x1c1ix9gPW4/UWB1FnYP+npHfB7xtjBkFvO14f6oO4NvGmHHALOBuERnfbf0fjDFTHI8N/cyjXMzc0Y7GNNpX1SWszi5mbFwokxLDrI6iXMj8jOGEBvjyvB6nbqm/hXwB8KTj9ZPA9aduYIwpN8Zsd7w+CeQBCf38XOUm/tOYppIKbUxjqbzyenJL6liUmYSI9h1X/zHE38a1U7rGfqhv0YlU3E1/C3msMaYcugo2EHOmjUUkFZgKbOm2+B4RyRWRx3u6NN9t3xUiki0i2ZWVlf2MrQbToswkOu2GNdqYxlLPbyvG3+bDDVP1d7T6vMWZSbS02/n3Lh37wd2ctZCLyFsisqeHx4K+fJCIhAAvAN80xtQ7Fj8MpANTgHLgd6fb3xjzqDEm0xiTGR0d3ZePVhYbERXMrLQInt9WjN2ujWms0H2ClGHBOkGK+rxJiWGMjQvVPuVu6KyF3BhzmTFmYg+Pl4HjIjIcwPHcY4smEfGjq4g/Y4xZ1+3fPm6M6TTG2IG/A1nO+B+lXM/SrGSKaprYVFBtdRSv9Mbe49Q2tWvfcXVan479sKukjr1ldVbHUX3Q30vr64HljtfLgZdP3UC6bsb9A8gzxvz+lHXdO7LeAOzpZx7loq6YEEd4kB+rthZZHcUrrdpaROKwIZyXrhOkqNO7YWoCAb4+PLdVz8rdSX8L+QPAPBHJB+Y53iMi8SLyaQv084DbgEt66Gb2fyKyW0RygYuBe/uZR7moQD8bN0xNYOPeY1Q3tFodx6scqWrkk8PVLM1KxkcnSFFnEB7kz9UZw3lpRylNbTrhkbvoVyE3xlQbYy41xoxyPNc4lpcZY+Y7Xn9kjBFjzKRTu5kZY24zxmQ41l33acM55ZmWZiXT3mlYt73U6ihe5bltRdh8hIU6QYrqhSVZyZxs7eCVXP1z7C50ZDc1aEbHhjItOZxV24p0BKlB0tZhZ212CZeNiyFmaKDVcZQbmJE6jPToYJ7T22BuQwu5GlRLs5IpqGzUEaQGyRv7jlHd2MbSrGSroyg3ISIszUpme1Et+4/Vn30HZTkt5GpQXT2pawSp57SLy6BYtbWIhPAhXDBKu2yq3rtpWiL+Nm305i60kKtBFeTvy4Kp8by6u5zapjar43i0wqpGPj5UzZIZSdi0kZvqg2HB/lyVEce67SU0t3VaHUedhRZyNeiWZaV03bvVkd4G1HPbirsauekEKeocLJmRTH1LBxt2a6M3V6eFXA268fFDmZYczjNbinSktwHS9UOpmEvGxhAXpo3cVN/NSosgLSqYf205anUUdRZayJUlbp2V8ln/ZuV8G/ceo6qhjWUztZGbOjciwi2zUthRVMueUh3pzZVpIVeWmJ8xnGFBfvxrs/7aHwhPbzpKckQQc7WRm+qHm6clEujnwzN6Vu7StJArSwT62ViUmcSbecc5VqfTmzrT/mP1bC2s4dZZOpKb6p+wID8WTE7gpR1lOr2pC9NCriyzbGYynXbDc9t04Aln+tfmo/j7+rBwujZyU/1366wUmts7WaeNU12WFnJlmZTIYC4cHc1zW4vp6LRbHccjnGxp58XtpVw7KV6nK1VOkZEYxuSkcJ7efFRHZHRRWsiVpW6dmcyx+hbeyutxBlzVRy/tKKWxrZPbZ6dYHUV5kNtmpXC4slGnIXZRWsiVpS4ZG8PwsEBt9OYExhie2nSUSY4zKKWc5ZpJwwnXxqkuSwu5spSvzYdbZ6Xw0aEq8o+ftDqOW9typIb8igZunaVn48q5Pm2cunGvNk51RVrIleWWzEjC39eHf35SaHUUt/b05qOEDfHj2knxVkdRHuiWmcnYjeFZ7YrmcvpVyEUkQkTeFJF8x/Ow02xXKCK7RWSniGT3dX/l2SJDAlgwOZ5120upa9IuLueirLaZ1/ccY/GMJIb426yOozxQSmQwl46N4ZktRbS06/jrrqS/Z+T3AW8bY0YBbzven87FxpgpxpjMc9xfebAvnJdKc3snq7N1tqVz8dSmrhbF2shNDaQ7zhtBdWMb63eVWR1FddPfQr4AeNLx+kng+kHeX3mICfFhZI2I4MlNhXTq+Ot90tTWwaqtRVw5MY7EYUFWx1EebE56JGNiQ3ni40LtiuZC+lvIY40x5QCO55jTbGeAN0QkR0RWnMP+iMgKEckWkezKysp+xlau6IvnpVJyopm38o5bHcWtrNteSl1zO188b4TVUZSHExHuOC+VvPJ6NhfUWB1HOZy1kIvIWyKyp4fHgj58znnGmGnAVcDdInJhX4MaYx41xmQaYzKjo3X8aE902bhYEsKH8M+PC62O4jbsdsMTHx9hUmIY01O0iYkaeNdPTWBYkB9PfHzE6ijK4ayF3BhzmTFmYg+Pl4HjIjIcwPHc46gexpgyx3MF8CKQ5VjVq/2Vd/C1+XDb7BQ2FVSTV15vdRy38EF+JYcrG/nieSMQ0XHV1cAL9LOxbGYyb+Ydp6i6yeo4iv5fWl8PLHe8Xg68fOoGIhIsIqGfvgYuB/b0dn/lXZbMSCLQz4fHP9Jf+73x+MeFxIQGMD9juNVRlBe5bVYqNhGe3FRodRRF/wv5A8A8EckH5jneIyLxIrLBsU0s8JGI7AK2Aq8aY14/0/7Ke4UH+bMoM4mXdpZyvF4HnjiT/OMn+eBgJbfPTsHfV4eEUIMnLiyQ+RnDWb2tmJM6K5rl+nX0G2OqjTGXGmNGOZ5rHMvLjDHzHa8LjDGTHY8Jxphfnm1/5d3uPD+NTrvhcb0Hd0b/+OgI/r4+LM1KtjqK8kJ3XjCCk61dPSaUtfRnvHI5yZFBzM8YzrObi/TX/mkcr29h3fZSFmUmEhkSYHUc5YUmJYYzJz2Sf3x0hNYOHSDGSlrIlUu668J0/bV/Bo9/dIQOu50VF6RbHUV5sZVz0zle38rLO3SAGCtpIVcuKSMxjDnpkTz+USFtHTpXeXd1ze08s6WIqyfFkxypA8Ao61wwKorxw4fyyAeHsetATpbRQq5c1ooL0zhW36LDQZ7iX5uP0tDawcq5aVZHUV5ORLhrbhoFlY28qQM5WUYLuXJZc0dHMzYulEc/OKzDQTq0tHfyxMdHuHB0NBPiw6yOoxRXZwwnKWIIj7yvx6lVtJArl/Xpr/2Dxxt4K0/HCgJYk1NCVUMbX5mr98aVa/C1+fDlC9LYUVTL1iPa8Qhg1dYiHh3E2w1ayJVLu3ZSPMkRQfzp7Xyv/7Xf0Wnn7x8UMCUpnFlpEVbHUeozC6cnERHsz8PvH7Y6iuWa2jr43RsH+OBgFT4+gzPaohZy5dJ8bT7cc/FIdpfW8e4B7z4r/3duGUU1Taycm67DsSqXMsTfxpfOH8F7ByrZWVxrdRxLPbO5iKqGNr5x2ahB+0wt5Mrl3TAtgaSIITz4lveelXd02nnwrXzGxoVy+fhYq+Mo9TnL56QyLMiPP7510Ooolmlq6+BvHxzm/JFRzEgdvKtmWsiVy/Oz+XD3RSPZVVLHewe9cwrbl3aWUVjdxL3zRg/a5Tql+iIkwJcvX5jGewcq2V50wuo4lrDibBy0kCs3ceO0RBLCvfOsvL3Tzp/ezmdC/FA9G1cubfnsVCKC/fnjW/lWRxl0zW2dlpyNgxZy5Sb8fX24++KR7Cyu5YP8KqvjDKp120soqmniW/NG671x5dKCA3xZcWEaHxysJOeod52VP7PlqCVn46CFXLmRm6d3nZX/8a2DXnNW3tZh509vH2JyYhiXjI2xOo5SZ3X77BQig/296l55c1snj7xvzdk4aCFXbsTf14d7LhnJjqJa3tznHaNIrckpprS2mXv1bFy5iSB/X+6am8aH+VVkF3pHv/InNxVadjYOWsiVm1k4PZH06GB+/fp+Ojo9ewz2lvZO/vLOIaYlhzN3dLTVcZTqtVtnpRAVEsCvX9/v8VfPTjS28dC7h7h4TLQlZ+OghVy5GV+bD9+/ciyHKxtZnV1idZwB9Y+PjlBe18J3rxirZ+PKrQT5+/KteaPZVniCjXs9++rZn985RGNrB/ddNc6yDP0q5CISISJviki+43lYD9uMEZGd3R71IvJNx7qfikhpt3Xz+5NHeYd542OZkTqMP7x1kKa2DqvjDIiqhlYefu8wl42LZXZ6pNVxlOqzRZmJjIoJ4YHX8jx2BsOj1Y08vbmQhdOTGBMXalmO/p6R3we8bYwZBbzteP9fjDEHjDFTjDFTgOlAE/Bit03+8Ol6Y8yGfuZRXkBEuO+qcVSebOWxD49YHWdA/OHNg7S0d/KD+WOtjqLUOfG1+fDD+eMorG7imS1HrY4zIP5v4wF8fXz41uWjLc3R30K+AHjS8fpJ4PqzbH8pcNgY45n/r6pBMz1lGFdNjONv7x+m8mSr1XGc6uDxk6zaWsSts1JIjw6xOo5S5+yiMdGcPzKKB9/Op6653eo4TrWj6ASv5pbz5QtGEDs00NIs/S3kscaYcgDH89n6xywBVp2y7B4RyRWRx3u6NP8pEVkhItkikl1Z6Z2je6n/9t0rxtDaYfe4bi73b8gjOMCXr19qTQtYpZxFRPjB/LHUNbfz13cPWR3HaYwx/GrDfqJC/FnhAjMRnrWQi8hbIrKnh8eCvnyQiPgD1wFrui1+GEgHpgDlwO9Ot78x5lFjTKYxJjM6WlvwKkiLDuG22Sk8u7WIXR4yUcOH+ZW8d6CSr18yiohgf6vjKNVvE+LDuGlaIk98XEhRdZPVcZzi37nlbC2s4ZuXjSYkwNfqOGcv5MaYy4wxE3t4vAwcF5HhAI7nM01PdRWw3RjzWRNGY8xxY0ynMcYO/B3I6t//HOVtvjVvNNEhAfzPS3voHKS5fwdKa0cnP/v3PpIjgrh9TorVcZRymu9cPgZ/Xx/+5+U9bt8dra65nZ+/so+MhDCWZiVbHQfo/6X19cByx+vlwMtn2HYpp1xW//RHgMMNwJ5+5lFeJjTQj/93zXh2l9bxr83u3fTikfcKOFTRwM8WTCDA12Z1HKWcJi4skO9cPpoPDlby79xyq+P0y+/eOEB1Qyv335CBzUUmMOpvIX8AmCci+cA8x3tEJF5EPmuBLiJBjvXrTtn//0Rkt4jkAhcD9/Yzj/JC10wazgWjovjtxgNU1LdYHeecHKpo4KF3D3Hd5HguHqNDsSrPc9vsVCYlhvG//95HXZN7NnzbWVzL05uPcvvsVDISw6yO85l+FXJjTLUx5lJjzCjHc41jeZkxZn637ZqMMZHGmLpT9r/NGJNhjJlkjLnu04ZzSvWFiPCz6ybQ2mHnF6/mWR2nz+x2ww/X7WaIv43/d814q+MoNSBsPsL9N2RQ09jKA6/vtzpOn3V02vnRi7uJDgng2xZ3NzuVjuymPEJadAgrL0pn/a4yPnCzOctXZxeztbCGH80fR3RogNVxlBowExPC+OJ5I1i1tcjtxmF/atNR9pbV85NrJxAa6Gd1nP+ihVx5jK9elE56dDDfXbuLE41tVsfplYqTLdy/IY9ZaREszEy0Oo5SA+7eeaNJCB/CD9btpqW90+o4vXK4soHfbDzARWOimZ8RZ3Wcz9FCrjxGoJ+NB5dMpaaxjR++uNvlW8fa7YbvrsmlpcPO/Tdk6HjqyisEB/hy/40Z5Fc0cP8G178V1tZh55vP7STAz4cHbpzkksepFnLlUSYmhPGteWN4bc8x1ua49qQqf/+wgPcPVvLja8aTpiO4KS8yd3Q0Xzp/BE9tOsobe49ZHeeMfvfmAXaX1vHrmyYRF2btCG6no4VceZwVF6Yxc0QEP12/l6PVjVbH6dGOohP8ZuMBrpoYxy0zXaMvqlKD6XtXjmFC/FC+90Iu5XXNVsfp0ceHqvjb+wUsm5nMFRNc75L6p7SQK49j8xF+v3gKPj7Cvc/vpN3F5i2va27na6t2EDs0kAducs1LdUoNtABfG39eOpW2Djv3Pr/T5QZ0qmls41urd5IeHcz/u9q1e5NoIVceKSF8CPffkMH2olp+/PJel7lfbkxXV7Pyuhb+vGwqYUNcq/WrUoMpLTqEn103gc0FNfzp7Xyr43ymvdPON57bQU1jGw8umcoQf9ceoMn6QWKVGiDXTo4nr7yev753mPToYO68IM3qSPz5nUO8uruc7185lmnJp50jSCmvcfP0RDYVVPPg2/mMiArm+qkJluYxxvCT9Xv5ML+KX9+UwcQE1xn45XS0kCuP9p3Lx1BQ2cgvN+SRGhnMZeNjLcuyelsxv3/zIDdOS2DlXOt/VCjlCkSEX92YQemJZr67dhcxQwOYkx5lWZ6/f1jAs1uK+MpF6Sye4R7tV/TSuvJoPj7CHxZPYWJ8GF9/bgf7yuotyfHugQp+8OJuLhgVxa/1vrhS/yXA18ajt2WSEhnMXU/ncPD4SUtyvL6nnF+9tp+rM4bz3cvHWJLhXGghVx5viL+Nx5ZnMjTQjy88sXXQ/0jkltTy1X9tZ2xcKA/fOh0/mx52Sp0qLMiPf94xg0A/G3c8sY1jdYM7b8Lmgmq++fxOpiSF87tFk/FxkQlRekP/oiivEDs0kKe+1DVL7uK/bSK3pHZQPje7sIbbH99KZIg/T9wxwyXmLlbKVSUOC+Lx5TOobWrjpoc/4XBlw6B87pv7jnP741tJHBbE32/PJNDPtRu3nUoLufIao2NDWbNyNsEBviz7+xa2FFQP6Odt2F3Osse2MCzIn2fvnEVMqGsOJqGUK8lIDGPVilm0tHdy88OfsKPoxIB+3prsYlb+K4dxw4ey5q7ZRIW433wHWsiVV0mJDGbtyjnEhQVy++Nb2bB7YCbce+zDAu5+djsZCWG88JU5JEcGDcjnKOWJJiWG88JX5hAa6MfSv2/mnf3Hnf4Zxhj+9v5hvrs2lznpkTx750yGBfs7/XMGgxZy5XXiwgJ5fsUsxg4fylef2c63V++ivsU58yOfaGzj26t38YtX87hyQhzP3DmTCDf946CUlVKjgnnhK3MYGRPCnU9m88tX99Hc5pxJVspqm/nCE9s+a9j22PJMgt34tpe4ykAZfZGZmWmys7OtjqHcXHunnT+/nc9D7x0mNjSA3y6czJyR59btxRjDuu2l/HJDHvXN7aycm86980Zjc6MGM0q5oobWDn75ah6rthaRHBHEAzdm9Os4XZ1dzC9eyaPDbrjvqrHcNivFLRq2iUiOMSazx3X9KeQishD4KTAOyDLG9FhdReRK4EHABjxmjHnAsTwCeB5IBQqBRcaYs94Q0UKunGlH0Qm+vXoXBVWNzB0dzRfOS2XuqOheHdwdnXY+PlzNI+8dZlNBNdOSw7n/xgzGxg0dhORKeY9PDlfxw3W7Kaxu4rrJ8dw6K4UZqcN61ZWztaOTjXuP89QnhWQfPUHWiAh+c/MkUiKDByG5cwxkIR8H2IG/Ad/pqZCLiA04CMwDSoBtwFJjzD4R+T+gxhjzgIjcBwwzxnz/bJ+rhVw5W3NbJ3//sICnNx+l8mQrI6KCWTwjiYnxYYyKDSEmNAARodNuqG5opfhEM6/vKeelnWVUnmwlPMiP71w+hmVZyW7x614pd9TS3smDb+fz1CeFNLZ1khYVzMLMJGanR5IQPoSoEP/PjtOy2maOVDWyqaCa1duKqW5sIyliCCsuTOcWNzxOB6yQd/uA9zh9IZ8N/NQYc4Xj/Q8AjDG/EpEDwEXGmHIRGQ68Z4w5ay98LeRqoLR12HltTzlPfFzIzuLaz5YPDfQl0M9GVUMrn87t4GcTLhoTw41TE7hkXAwBvu7VZUUpd9XU1sGrueWszi5mW+F/LuIG+PoQFRJA5clW2hyTJfkIXDoulltmJnNhL6+0uaIzFfLBuLufABR3e18CzHS8jjXGlAM4innM6f4REVkBrABITnaPYfOU+/H39WHBlAQWTEmg4mQLh443kF/RQH7FSdo67MQODSQmNICYoYFkpUa4bStXpdxZkL8vCzOTWJiZRFF1EwePn6S0tpnS2mYq6luIHRpIalQwqZHBjI4NIdINu5T1xVkLuYi8BfQ0EeuPjDEv9+Izevr50+fLAMaYR4FHoeuMvK/7K9VXMaGBxIQGnnPDGqXUwEuODPL67p1nLeTGmMv6+RklQFK394lAmeP1cREZ3u3SekU/P0sppZTyKoPRj3wbMEpERoiIP7AEWO9Ytx5Y7ni9HOjNGb5SSimlHPpVyEXkBhEpAWYDr4rIRsfyeBHZAGCM6QDuATYCecBqY8xexz/xADBPRPLpatX+QH/yKKWUUt5GB4RRSimlXNyZWq3rEK1KKaWUG9NCrpRSSrkxLeRKKaWUG9NCrpRSSrkxt2zsJiKVwFEgCqiyOI470O+p9/S76h39nnpHv6fe0+/qzFKMMdE9rXDLQv4pEck+XSs+9R/6PfWefle9o99T7+j31Hv6XZ07vbSulFJKuTEt5EoppZQbc/dC/qjVAdyEfk+9p99V7+j31Dv6PfWeflfnyK3vkSullFLezt3PyJVSSimvpoVcKaWUcmNuV8hFJElE3hWRPBHZKyLfsDqTKxMRm4jsEJFXrM7iykQkXETWish+x39bs63O5IpE5F7HcbdHRFaJSKDVmVyFiDwuIhUisqfbsggReVNE8h3Pw6zM6CpO8139xnH85YrIiyISbmFEt+J2hRzoAL5tjBkHzALuFpHxFmdyZd+ga/pYdWYPAq8bY8YCk9Hv7HNEJAH4OpBpjJkI2IAl1qZyKf8Erjxl2X3A28aYUcDbjveq5+/qTWCiMWYScBD4wWCHclduV8iNMeXGmO2O1yfp+oObYG0q1yQiicDVwGNWZ3FlIjIUuBD4B4Axps0YU2tpKNflCwwREV8gCCizOI/LMMZ8ANScsngB8KTj9ZPA9YOZyVX19F0ZY94wxnQ43m4GEgc9mJtyu0LenYikAlOBLRZHcVV/BL4H2C3O4erSgErgCcdtiMdEJNjqUK7GGFMK/BYoAsqBOmPMG9amcnmxxphy6DoJAWIszuMuvgi8ZnUId+G2hVxEQoAXgG8aY+qtzuNqROQaoMIYk2N1FjfgC0wDHjbGTAUa0Uugn+O4v7sAGAHEA8Eicqu1qZSnEZEf0XUL9Rmrs7gLtyzkIuJHVxF/xhizzuo8Luo84DoRKQSeAy4RkX9ZG8lllQAlxphPr+yspauwq/92GXDEGFNpjGkH1gFzLM7k6o6LyHAAx3OFxXlcmogsB64BbjE6yEmvuV0hFxGh615mnjHm91bncVXGmB8YYxKNMal0NUh6xxijZ089MMYcA4pFZIxj0aXAPgsjuaoiYJaIBDmOw0vRRoFnsx5Y7ni9HHjZwiwuTUSuBL4PXGeMabI6jztxu0JO15nmbXSdYe50POZbHUq5va8Bz4hILjAFuN/aOK7HccViLbAd2E3X3w8dVtNBRFYBm4AxIlIiIl8CHgDmiUg+MM/x3uud5rv6CxAKvOn4u/6IpSHdiA7RqpRSSrkxdzwjV0oppZSDFnKllFLKjWkhV0oppdyYFnKllFLKjWkhV0oppdyYFnKllFLKjWkhV0oppdzY/wdjRBrFE5MVDgAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그리기 방법 3\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 300, + "metadata": {}, + "outputs": [], + "source": [ + "# 함수를 정의해 cos 함수의 값을 가지고 선그래프 그리기.\n", + "def plot_cos(x) :\n", + " y = np.cos(x)\n", + " plt.plot(x, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 301, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(8, 4))\n", + "ax1.plot(x, y)\n", + "ax2.plot(x, np.cos(x))\n", + "#ax2 = plot_cos(x)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 303, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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mqNoLpRRPjI8lKTKQe1buIi2n3OhIop21SRErpS5USh1QSmUqpe5vi9cU7cPZSfHqNfH0DPLmpve2c0QeEOGQdudUcM+qnST0COSpCbHySEM74+7izPypCQT5uHPD8hR5QISDO+0iVko5A28AFwExwDVKqZjTfV3Rfnw9XFk0IwknBdcvS6ayXkZSO5ITI6Q7e7vz1rQE3F1khLQ9CvJxZ9HMRKrrTcx5R0ZSO7K2OCMeCmRqrQ9prRuBFcC4Nnhd0Y4iOnsxb0oCR0tque39HZhlhKZDqG8yc8M7qVTWN/H29ESCfNyNjiROQ78ufrxydTy7cyu4b/UuWZPaQbVFEYcB2b/6OKflc/9FKTVHKZWilEopKipqg82K0zW8d2cevyKWHzKKeOpzGUlt77TW/P2jNHZll/PSVYNlhLSDGBMTyt8u6Me6tDxe/zbT6DiiHbRFEf/ezaffvG3TWi/QWidqrRODg4PbYLOiLVwzNIKZIyJZtPkwHyYfMzqOOA3zvs/ik53Hue+CvrJmsYO58ZxeTIgP44WvMvhyT57RcUQba4sizgF+vXJ8OHC8DV5XWMk/L+nPWdFB/PPjPfxyqMToOOIUbEjP57kNBxg3uBs3n9vb6DiijSmleGrCQOIjArjrw12yJrWDaYsiTgailVI9lVJuwNXAp23wusJKXJydeP3aIXTv5MWN76ZyrKTW6EjiJKQfr+CuD3cyqHsAz0yMkxHSDsrD1Zm3piUQcGJN6ioZSe0oTruItdYm4FZgA7APWKm1Tj/d1xXW5e/ZPJLaoptHUlfJSGq7UFhVzw3LUvDzcOXtabKGtKNrXpM6kfLaJuYsT6W+SUZSO4I2mUestf5ca91Ha91ba/1kW7ymsL6eQd7MnzKEw8U13P6BjKS2dfVNZuYsT6WstomFMxIJ8ZM1pDuCAd38eemqwezMLudvq9NkJLUDkJW1xH8ZERXEo5cP4LsDRfxbRlLbrBMjpHdml/PSVYOIDfM3OpKwogtju3DfBX35dNdxGUntAGStafEbU4f1ILOwmoWbD9Mr2Idrz4gwOpL4H69/m/mfEdIXxnY1Oo4wwM3n9iazsJoXvsqgV7APl8TJ94G9kjNi8bv+eUl/zu0bzEOf7GHzQVmT2pZ8tus4L3yVwfj4MBkh3YEppfj3hIEk9gjk7pU72XGszOhI4hRJEYvf5eLsxGvXxBMV7MNN76WSWVhldCQBpB4t455Vu0iKDOTpiQNlhHQHd2IkdYifOzcsTyWnTGY82CMpYvGHfD1cWTQzEXcXZ2YtTaGkusHoSB1admktc5an0NXfg7emJcoa0gKAzj7uLJmZRIPJzPVLU2TGgx2SIhZ/KjzQi7enJ1DQ8iABmS5hjIq6JmYtTabJbGHxzCQ6ebsZHUnYkKgQX+ZPSSCzqJpb39+ByWwxOpI4CVLE4i/FRwTy8lWD2ZFdzl0f7sQi05qsqtFk4cZ3UjlcXMOb0xLoHexjdCRhg86MDuKJlrXjH/pkj0xrsiNSxKJVLhrYlQcv7s8Xe/J5+sv9RsfpME5MU/r5UAnPTIxjRO8goyMJG3bN0AhuOa83H2zLZt73WUbHEa0k05dEq11/Zk+yS2tZsOkQ3QM9mTY80uhIDu/FrzJYuyOXu8f2YWJCuNFxhB249/y+5JTV8dyGA4QFeHJF/G8ehidsjBSxaDWlFA9fNoDc8joe+TSdED8PecpPO/pg2zFe+zaTq5O6c9uoKKPjCDuhlOLZSXEUVNZz3+pdhPi5y5UUGyeXpsVJcXZSvHpNPIO6B3DbBzvYdrjU6EgO6eu9Bfzz4z2c0yeYx6+IlWlK4qS4uzjz1rREIjt7M3d5KunH5WlNtkyKWJw0LzcXFs1IIjzQk9nLktmfX2l0JIeSfKSUW97fTmw3P96YMgRXZzlMxcnz93Rl2ayh+Hi4MGNxsjxVzYbJES5OSSdvN5bPGoqnmzMzFm+ThQTayL68SmYtTSYs0JPFM5PwcZe7R+LUdQvw5J3rh2KyWJi2+BeKqmQtAFskRSxOWXigF8tmDaW20cz0RdsolgU/Tkt2aS0zFm/D282F5bOG0tnH3ehIwgFEhfiyeGYShZUNzFyyTRb8sEFSxOK09Ovix+KZSRyvqGPaom1U1MpBfioKKuuZtugXGkwWll8/lPBAL6MjCQcyJCKQeVOHcCC/illLk6ltNBkdSfyKFLE4bUmRnXh7eiJZhdXMWLKN6gY5yE9GcXUDUxY2XzZccl0SfUJ9jY4kHNB5fUN4+erBpB4tY87yVFklz4ZIEYs2cVZ0MK9fG8/u3ApmL0uWg7yVymsbmbao+R77oplJDIkINDqScGCXxnXj2UmD2JxZzK3vb6dJlsK0CVLEos2cP6ALL04exC+HS2Vd6laoqm9ixuJtZBVWs2BaIsN6dTY6kugAJiWE8/i4AXy9r5A7V+yUdaltgBSxaFPjBofxzMQ4NmcWM3tZCnWNUsa/p6KuiWmLtpF+vJJ5U4Zwdp9goyOJDmTa8EgevLg/63fncceKnXJmbDCZGyHa3OTE7jgpxX2rd3H9smQWzUjC000e2XfCicvR+/MreWPKEMbEhBodSXRAN5zdC6XgifX7aDJbeO3aeHm0pkHkjFi0i0kJ4bxw5SC2Hiph1tJkamQAFwAl1Q1cvWArBwqqeGtagiwRKgw1+6xePHb5ADbuLeCmd7fL7aQWhZX1HMivstr2pIhFu5kwJJwXJw/ml8MlTFn4C2U1jUZHMlRBZT1XL9jKkZIaFk5PZFQ/ORMWxpsxIpInx8fy7f5CZi9L6fCzHg4X1zBh/hZufDfVavfPpYhFu7oiPow3pyawN6+SK9/6mePldUZHMkRmYTUT5m3heHkdS2YOlXvCwqZMOaMHz185iJ8PlXDt21s77OI8u3MqmDR/C7WNZl65ejAuVlpeVopYtLvzB3ThnVlDKaioZ9L8LWQWVhsdyapSj5Yx6c0tNJjMfDh3OMN7y+hoYXsmJYSzYFoCGQVVTJq/pcOtTf1TZjFXL/gZD1dnVt84nLjwAKttW4pYWMUZvTqzYu4wGs2aSW9u4eesEqMjWcXXewuYsnArAZ6urLlpJLFh/kZHEuIPje4fynuzh1Fe18SE+VvYk9sxntr08Y5crluSTHigF2tuHkGvYB+rbl+KWFjNgG7+rLlpBEE+7kxb9AsfbDtmdKR2o7XmrR+ymPNOCn1DfVl90wgiOsuylcL2JfQIZPWNw3F3cWLSm1tYl3bc6EjtxmLRPPPlfu78cCfxEQGsnDucUD8Pq+eQIhZWFdG5+R3nyKggHlizm8c+S3e4BQXqm8zc+eFO/v3Ffi6K7coHc4YRJA9wEHYkKsSXj28ZSWw3f259fwfPbziAxaKNjtWmqhtMzHknlfnfZ3HN0Ajeuf4M/L1cDcmitLb+zk1MTNQpKSlW366wHSazhac+38/inw4zMqozL101mBBf678TbWvHy+uY804K6ccruff8vtx8bm+UUkbHEuKUNJjMPPxxOh+mZDOmfygvXjUIPw9jyqotZRVVc/O728ksqubhS2OYPrxHux+nSqlUrXXi735NilgYaWVyNg99sgdfD1devmowZ0YHGR3plH25J5/716RhMmteuXowo/vL9CRh/7TWLNtyhMfX76OrvwevXB1PQg/7XBNda81H23N5+JM9uLs48do1Q6z2M0eKWNi0A/lV3PL+drKKqrn1vCjuGB1ttWkDbaG20cTj6/bxwbZjxIX788rV8fQM8jY6lhBtavuxMm7/YAd5FfXcNSaam86NwtnJfq72VDeYeOjjPazdkcuwXp14+ap4uvhb7yqcFLGwebWNJh79NJ2VKTkMDPPn6YkDGdDN9kcY78wu556VOzlUXMPcs3tz99g+uLnYz5sIIU5GZX0T/1izm3VpeZzRsxNPT4yzizedPx4s4h9rd5NbVsedY/pwy3nWfxMhRSzsxue783j4k3TKahuZc3Yv7hgdjYer7a1/W1HXxHMb9vPeL8cI9fXghcmDGBllv5fVhWgtrTWrUnN4fN1eGkwWbj0virnn9LLJdapLaxp5Yt1e1uzIpVeQN89MiiMpspMhWaSIhV0pr23kqc/3sTIlh8jOXtx/UT8uGNDFJgY9WSyaT3cd54n1+yitaWDGiEjuHtsHXwcYwCLEySisrOexdXtZn5ZHVIgP/7p8ACNs5M2oyWxhVWoOz365n6p6Ezed25tbzosy9E29FLGwSz9lFvPIp+lkFlYTHxHA/Rf24wyDntmrteabfYW8+FUGe/MqiQv356nxA2WBDtHhfbe/kIc+2UNOWR0jozpz7/l9iY8wZjCXxaL5Yk8+L2w8wKHiGhJ6BPLU+IH07eJrSJ5fkyIWdstktvDR9hxe+uog+ZX1nN0nmOtGRnJOdDBOVrjHY7Zovj9QyKvfZrIru5yITl7cMTqaK+LD7GqgihDtqb7JzHu/HGPed5mU1DQypn8Ic8/pTWKPQKtcyWo0WfgyPZ+3Nx1id24FfUJ9uPf8voyNCbWJK2kgRSwcQF2jmaVbjrD4p8MUVTXQM8ib6cN7MCE+vF0m4RdU1rMyOZsVydnkltcRFuDJbaOimJgQjqsdjegWwppqGkws3XKEt37IorLeRN9QX6YMi2B8fFi73L7Jq6jjg1+O8UFyNkVVDfTo7MXto2zzjXK7FbFS6krgUaA/MFRr3ap2lSIWp6rRZOGLPXks3XKEHcfKcXZSDOvVifNjujAmJpSwAM9Tel2tNQcLq/n+QCE/ZBSx9VApZovmzKggrhkawdiYUBkNLUQr1Taa+GzXcd7deozduRV4uDoxsncQ5/ULYVS/ELqdxnGaUVDN1/sK+GpvATuzy1EKzusbwrThPax2pexUtGcR9wcswFvAvVLEwpr25Fbw+e48NqTnk1VUA0BXfw8GdPMnNsyPvqG+dPJ2I9DbjQAvV1ydnKhpNFHbaKa6wcTRkhoOFlSTUVBN+vEK8irqAegb6svo/iFcldSdHp1tf2qGELYsLaecj1Jz+PZAIdmlzY9B7RnkTb8uvvTt4ku/Lr6E+nng6+GCj7srnm7O1DSYqKhrorKuifzKevblVbE3r5K9xyv/84jGQeH+jO4fyhWDw+xiHfd2vzStlPoeKWJhoMyWs9k9uRXsOV5JVlE1rfnWdnFS9Azypm8XX0ZGBXFOn+BTfrcuhPhjWmuyiqr5dn8h24+Wc6CgiiMlNa06Tl2dFdEhvvTv6kdCj0BG9w8x5OEMp+PPitjFiiHmAHMAIiIirLVZ0UFEhfgQFfL/jy6raTBxpKSGspomymobKattxGzReLu54OXujJebM90DvYgM8pZ7vkJYgVKKqBBfokL+fwRzXaOZzMJqimsaqK43Ud1goqbBhLe7C/6ervh7uhLk407PIG+HvjX0l0WslPoa6PI7X3pQa/1JazektV4ALIDmM+JWJxTiFHi7u9jFylxCdGSebs4MDJfj9C+LWGs9xhpBhBBCiI7Icc/1hRBCCDtwuqOmxwOvAcFAObBTa31BK/5eEXAUCAKKTzlAxyH7qfVkX7WO7KfWkf3UerKv/lwPrXXw733BkAU9/rNxpVL+aBSZ+H+yn1pP9lXryH5qHdlPrSf76tTJpWkhhBDCQFLEQgghhIGMLuIFBm/fXsh+aj3ZV60j+6l1ZD+1nuyrU2ToPWIhhBCiozP6jFgIIYTo0KSIhRBCCANZvYiVUt2VUt8ppfYppdKVUndYO4M9UUo5K6V2KKXWGZ3FlimlApRSq5VS+1u+t4YbnckWKaXuajnu9iilPlBK2dfK+e1IKbVYKVWolNrzq891Ukp9pZQ62PJroJEZbcUf7KvnWo6/NKXUWqVUgIER7YoRZ8Qm4B6tdX9gGHCLUirGgBz24g5gn9Eh7MArwJda637AIGSf/YZSKgy4HUjUWscCzsDVxqayKUuBC//nc/cD32ito4FvWj4Wv7+vvgJitdZxQAbwgLVD2SurF7HWOk9rvb3l91U0/8AMs3YOe6CUCgcuARYancWWKaX8gLOBRQBa60atdbmhoWyXC+CplHIBvIDjBuexGVrrTUDp/3x6HLCs5ffLgCusmclW/d6+0lpv1FqbWj7cCoRbPZidMvQesVIqEogHfjEyhw17GfgbYDE4h63rBRQBS1ou4y9USnkbHcrWaK1zgeeBY0AeUKG13mhsKpsXqrXOg+aTCCDE4Dz2YhbwhdEh7IVhRayU8gE+Au7UWlcalcNWKaUuBQq11qlGZ7EDLsAQYL7WOh6oQS4h/kbL/c1xQE+gG+CtlJpqbCrhaJRSD9J8C/I9o7PYC0OKWCnlSnMJv6e1XmNEBjswErhcKXUEWAGMUkq9a2wkm5UD5GitT1xZWU1zMYv/NgY4rLUu0lo3AWuAEQZnsnUFSqmuAC2/Fhqcx6YppWYAlwJTtCxS0WpGjJpWNN/L26e1ftHa27cXWusHtNbhWutImgfUfKu1lrOX36G1zgeylVJ9Wz41GthrYCRbdQwYppTyajkORyOD2v7Kp8CMlt/PAD4xMItNU0pdCPwduFxrXWt0HntixBnxSGAazWd4O1v+u9iAHMKx3Aa8p5RKAwYDTxkbx/a0XDFYDWwHdtN8/MuyhC2UUh8APwN9lVI5SqnrgaeBsUqpg8DYlo87vD/YV68DvsBXLT/X3zQ0pB2RJS6FEEIIA8nKWkIIIYSBpIiFEEIIA0kRCyGEEAZyMWKjQUFBOjIy0ohNCyGEEFaXmpparLUO/r2vtUkRK6UW0zx3rLBlDds/FRkZSUpKSltsWgghhLB5Sqmjf/S1tro0vZTfLgAuhBBCiL/QJmfEWutNLetGC2GTSmsaKa5uoK7RTF1T83/ebi508najk7cbAZ6uODkpo2MK0aFV1DaRU15LfZMFk9mCyaJxUopgX3dC/dzxcXeheS0ax2K1e8RKqTnAHICIiAhrbVZ0QEVVDfx4sIjkI2VkFVaTWVRNaU3jn/4dV2dF3y6+DAzzJzbMn8QenegT6uOQB70QtiC/op4tWcX8nFVCRmE1R0tqKK9t+tO/4+XmTGRnb+IjAoiPCGRIRAA9g7zt/jhtswU9Ws6I17XmHnFiYqKWe8SiLWUWVrNmew7fHyhib17zM0T8PV3pE+pDVIgPvYN96OLvgZebMx6uzri7OFPbaKK0ppGS6kbyK+tJP17B7pwKKuubn+QW0cmLC2O7cMGAUOK7B8oZsxCnKaOgitWpOXy9r4BDRTUABHi5MqCbH5GdvYns7E14oCeebs64Ojvh4qQwWzRF1Q0UVNaTX9FARkEVO7PLqW5oPk4jO3txSVxXLhnYjf5dfW22lJVSqVrrxN/9mhSxsFd1jWY+353HiuRjJB8pw9lJkdAjkHP6BHNOn2BiuvqddHlqrTlWWsuWrBK+3JPPlqximsyaiE5ezBgRyZWJ4fh5uLbT/5EQjqe6wcSa7TmsTs0hLacCFyfFyKggzooOYnjvzvTvcvLHqdmiySqqZtvhUjak57MlqwSzRdM72Jvpw5uPUy83QyYF/SEpYuFQahpMLP/5KAs2ZVFW20TPIG+uSurOxCHhBPu6t+m2Kuub+GZfAe9uPUbq0TK83Zy5MrE7c87uRbcAzzbdlhCOpKKuiWVbjrD4p8OU1zbRv6sfVyaEM25wNzr7tO1xWlLdwIb0AlalZrPjWDn+nq5MHRbBjBGRhPh6tOm2TlW7F3HLAuDnAkFAAfCI1nrRH/15KWJxKuoazby79Shv/pBFSU0j5/QJ5sZzejOsVyerXI5Kyyln6U9H+CztOE5KMXNkJDefE4W/l5whC3FCTYOJtzYdYsnmw1Q1mBjTP4RbzosiPiLQKttPPVrKgk2H2Li3AHcXJ+ac3Zu5Z/fC293YM2SrnBGfDClicbI2pufz2Gd7yS2v46zoIO4c04eEHtY5sP9XdmktL36Vwcc7c/HzcOW2UVHMGBGJq7MsVCc6Lq01n6Xl8dT6feRX1nNRbBduHRXFgG7+huQ5XFzDi19l8Nmu44T4unPv+X2ZmBCOs0FjPaSIhd3KLq3lsc/S+XpfIX1DfXls3ACG9epsdCwA0o9X8PQX+/nxYDExXf14dlIcsWHG/NARwkgZBVU8/Mketh4qJTbMj8cujzXsjfL/Sj1axhPr97LjWDmDugfw/KQ4okN9rZ5DiljYHa01y38+yr+/2IdCceeYaGad2dMmzzq/2J3HQ5+kU1bbyJyze3HH6Gg8XJ2NjiVEu7NYNAs3H+L5DRl4ujlz3wV9uWZohGFnnX9Ea82nu47z2Gd7qa43cefYaOac1QsXK/48kSIWdqW4uoH7Vu3iuwNFnNMnmKcmDCTMxgdGVdQ28cT6vaxKzSEqxIc3rh1C3y7Wf9cthLXkltdxz8qdbD1UyvkxoTw1YSBBbTwIq60VVzfw0Md7+GJPPoPC/XnpqsH0CvaxyraliIXd+P5AIfeu2kVlvYl/XNSPGSMibXZe4O/5IaOIe1buorqhiccuH8DkxO52lV+I1liflsf9a9KwWDSPXD6AKxPC7er7fF3acR76eA+NJgvPTIrj0rhu7b5NKWJh8ywWzSvfHOSVbw7SN9SXV6+Jt9szysKqeu5csZMtWSVcMbgbT44faPiITSHagsls4dkNB1iw6RDxEQG8clU8EZ29jI51So6X13Hr+9vZfqycmSMi+cfF/XFzab9L1VLEwqZVN5i4+8OdbNxbwMQh4Tw5Ptbu77GaLZo3vsvk5a8z6BPqy8IZiYQH2ucPLCGgeb322z7Yzk+ZJUwb1oOHLo1p1+KyhkaThWe+3M+izYcZ1D2ABdMSCPVrn3nHUsTCZh0pruGG5SkcKq7hn5f0Z6adXYr+Kz8eLOLm97bj7uLEW9MSSOjRyehIQpy0fXmVzF6WQlF1A09eEcuVid2NjtSmvtidxz2rduHv6cqiGUnEdPNr8238WRHb99sZYddSj5ZyxbyfKK5u4J3rh3LdyJ4OVcIAZ0UHs/bmkXi7u3DNgl9YuyPH6EhCnJSfMouZ/ObPmC2a1TcOd7gSBrhoYFdW3TgcrWHSm1v4Zl+BVbcvRSwMsTE9n2vf/oVALzc+ueVMRvQOMjpSu4kK8eHjm0cypEcAd324ize+y8SIK1FCnKyPUnOYsXgb3QI8WXvLCOLCA4yO1G4GdPPnk1tH0ivYmxuWp7B482GrHadSxMLq3vvlKDe+m0q/rn6svnG43Q72OBmB3m4sn3UG4+PDeG7DAR5ftw+LRcpY2CatNa9/e5B7Vu1iaM9OrLppOF39bXsKYVsI9fNg5dzhjOkfyob0fMxWOkZlKKewGq01r36TyUtfZzCqXwivXxtvc09IaU9uLk68cOUgArxcWfzTYcpqG3l2UpxNLlIiOi6tNU99vo+3fzzMFYO78eykQXY/KOtkeLm58ObUBGqbzFZb8KPj/BQUhtJa89yGA8z7PosJQ8J4dmKcVVe1sRVOToqHL42hs7cbz2/MoLKuiTemDLH7UeLCMVgsmoc/3cO7W48xfXgPHr1sQId8DreTk8LHilMOO95PQmF1WmueWL+Ped9ncc3QCJ6fNKhDlvAJSiluHRXNE1fE8s3+Qua+k0p9k9noWKKDM5kt3Lc6jXe3HmPuOb147PKOWcJG6Lg/DYVVWCyahz9JZ9Hmw8wcEclT42Pl4G4xdVgPnpk4kE0Hi7hheYqUsTCMyWzhrpW7+Gh7DneN6cP9F/ZzuBkMtkyKWLQbrTWPfJrOO1uPMvfsXjxyWYwc3P/jqqQInpkQx+bMYiljYQizRfO31Wl8tus491/UjzvGRMtxamVSxKJdnBjw8c7Wo8w5uxf3XyTvsP/I5KTuPDvx/8u4wSRlLKzDYtE8sCaNNTtyuff8Ptx4Tm+jI3VIUsSiXbz4VQZv/3iYGcN78ICU8F+6MrE7z0yM48eDxdz2/g5MZovRkYSD07p5YNbKlBxuHx3NraOijY7UYUkRizb3xneZvPZtJlcndeeRywZICbfS5MTuPHpZDBv3FnDf6jSZZyzazYkrVu9uPcZN5/bmrjFSwkaS6UuiTb2z9SjPbTjwn6cOycCskzNzZE9qGs08t+EA3u7OPD4uVt7IiDY3/4es/1yx+tsFfeV7zGBSxKLNrE/L4+FP9jC6XwjPXTkIZynhU3Lzub2pqjfx5g9Z+Hu6ct8F/YyOJBzI+78c49kvDzBucDe5YmUjpIhFm9h8sJg7P9xBYo9AXr92iKwWdRqUUvz9wr5U1DXxxndZBPu4M3NkT6NjCQfw+e48Hvx4N+f2Deb5KwfJFSsbIUUsTltaTjlz3kmhd7APC6cn4ekmq0SdLqUUj48bQHF1A4+t20uwrweXxHU1OpawY1uyirljxQ4SIgKZPyVB3izbEPmXEKflaEkN1y1JppO3G8tmDcXfy9XoSA7DxdmJ166JJ7FHIHd9uJMtWcVGRxJ2an9+JXOXp9IzyJtFM+TNsq2RIhanrLSmkZlLkjFrzbJZQwn18zA6ksPxcHVm4fQkIoO8mLs8lX15lUZHEnYmr6KO65Yk4+XuzJLr5M2yLZIiFqekvsnM7GXJ5JbXsXB6Ir2DfYyO5LD8vVxZNmso3u4uzFqaTH5FvdGRhJ2orG/iuiXJVNWbWDJzKGEBjv8oQ3skRSxOmtmiuXPFTnZkl/PyVYNJjOxkdCSH19Xfk8Uzk6isa2LW0mSqG0xGRxI2rtFk4aZ3U8ksrObNqQnEdPMzOpL4A1LE4qT9+/N9fJmez4MX9+figTKAyFpiuvkxb2oCBwqquOW97bL6lvhDWmseXLubnzJLeHpiHGdGBxkdSfwJKWJxUt7depSFLU9Smn1WL6PjdDjn9AnmiSti+SGjiIc/TUdrWX1L/Na877NYlZrD7aOimJQQbnQc8Rdk+pJotR8yinjk03RG9QvhoUtjjI7TYV0zNIJjpbXM/z6LXkHe8oZI/Jd1acd5bkPzgh13je1jdBzRClLEolUO5Fdx63vbiQ7x4dVr4mXVLIPdd35fjpbU8OTn+4js7M2YmFCjIwkbkHq0jLtX7iKxRyDPTIyTVbPshFyaFn+puLqBWUuT8XRzZvHMJHzc5f2b0ZycFC9cOZiBYf7cvmIH6ccrjI4kDJZTVsvcd1Lo6u/BgumJeLjKXGF7IUUs/lR9k5k5y1MoqWlg4YxEusn0B5vh6ebMwumJ+Hu6MntZCoWVMq2po6puMDF7WQoNJguLZiTRydvN6EjiJEgRiz+kteaBNbvZfqycFycPJi48wOhI4n+E+HmwaEYSFXVNzF6eQn2T2ehIwsrMFs0dH+zgYGE186YMISpE5vTbGyli8YfmfZ/F2h253DO2j0xTsmEx3fx45ep4dudWcO+qXTKSuoN5+ot9fLO/kEcvi+Gs6GCj44hTIEUsfteXe/L/M/Ly1lFRRscRf2FsTCh/u6Af69LyePWbTKPjCCtZmZzN2z8eZvrwHkwbHml0HHGKZNSN+I09uRXc9eFOBncPkJGXduTGc3pxsLCKl77OICrER57W5OC2HS7lwY93c1Z0EA/LdEK71iZnxEqpC5VSB5RSmUqp+9viNYUxCqvqmbM8hQAvVxZMT5CRl3ZEKcVT4wcyJCKAe1btZHeOjKR2VNmltdz4birdA714/ZohuMgjDe3aaf/rKaWcgTeAi4AY4BqllLw9s0P1TWbmvpNKWW0Tb09PJMRXnqZkbzxcnXlrWiKdvd25YbmMpHZEJ0ZIm8wWFs5IlKcpOYC2eBs1FMjUWh/SWjcCK4BxbfC6woq01vxjzW52HCvnxcmDiA3zNzqSOEXBvu68PT2RirombngnVUZSO5DmB67sILOomnlTEuglTz1zCG1RxGFA9q8+zmn53H9RSs1RSqUopVKKioraYLOiLb216RBrduRy99g+XCQjpO1eTDc/XrpqMLuyy/n7R2kyktpBPLfhAF/vK+SRy2LkQQ4OpC2K+PdG8vzmqNdaL9BaJ2qtE4ODZYi9LflqbwHPfLmfS+K6cpuMkHYYF8Z24d7z+/DJzuPM+z7L6DjiNK3ZnsObP2QxdVgE02WEtENpi1HTOUD3X30cDhxvg9cVVrA/v5I7V+xgYJg/z08aJCOkHcwt50WRUVDNcxsOEBXiwwUDuhgdSZyC1KNl3P/Rbob36swjlw0wOo5oY21xRpwMRCuleiql3ICrgU/b4HVFOyupbmD2shS83V1YMC0RTzcZIe1olFI8OymOQeH+3PXhTvYerzQ6kjhJueV1zWtIB3gwb8oQXGWEtMM57X9RrbUJuBXYAOwDVmqt00/3dUX7ajRZuOnd7RRVNfD29ES6+MsIaUfl4erM29MT8fNwZfayZIqqGoyOJFqppsHEDctSaGiysGhGIoGyhrRDapO3Vlrrz7XWfbTWvbXWT7bFa4r2o7XmwbW72XaklOevHMSg7gFGRxLtLMTPg4UzEimtbWTuO7ImtT2wWDR3fbiT/fmVvHZtPFEhvkZHEu1ErnF0QAs2HWJVag53jI7mskHdjI4jrCQ2zJ+XJg9m+7FyHlizW0ZS27jnNh5g494CHro0hnP7hhgdR7QjKeIOZmN6Pk9/uZ9L47py55hoo+MIK7toYFfuGduHtTtyeeM7WZPaVq1OzWH+91lMOSOCmSMijY4j2pmsNd2BpB+v4I4VO4kLD+D5K2WEdEd166gosoqqeX5jBj2DZE1qW5N8pJR/rNnNyKjOPHr5ADlOOwA5I+4gCirrmb2seQ3pt6fJGtIdmVKKpyfGkdAjkLtX7mRndrnRkUSLI8U1zFmeQnigJ/OuTZAR0h2E/Ct3ALWNJq5flkxFXRMLZyQS4icjpDs6D1dnFkxLIMTPndnLUsgtrzM6UodXUdvErKXJACyemSRrSHcgUsQOzmzR3LGief7o69fGM6CbrCEtmnX2cWfxjCQamszMWpJMZX2T0ZE6rEaThbnvppBTVsdb0xKJDPI2OpKwIiliB/fU5/v4am8Bj1w2gFH9Qo2OI2xMdKgv86cmkFVUzS3vbafJbDE6UoejteYfa3ez9VApz0wayNCenYyOJKxMitiBLf/5CIs2H+a6kZHMkJGX4g+cGR3EU+MH8uPBYh76eI9Ma7Ky177NZHXLdMLx8eFGxxEGkFHTDmpjej6PfprOmP4h/PMSeTy0+HOTk7qTXVbLa99m0r2TF7ecJw//sIZVKdm8+FUGE4aEyXTCDkyK2AGlHi3jtg92MDA8gFevicfZSaY/iL9299g+HCut5bkNB+gW4CFnZ+1sU0YRD6zZzZlRQTw9IU6mKXVgUsQO5lBRNbOXJdPV34NFMxLxcpN/YtE6Jx4QUVjZwH2r0ujs7c7ZfeSRpe0h/XgFN72bSlSID/OnDsHNRe4SdmTyr+9AiqoamLFkG05KsWzWUIJ83I2OJOyMu4szb01PIDrUlxvfTSUtp9zoSA4nu7SW65Yk4+fpytLrhuLrIdOUOjopYgdRWd/EjMXbKK5qZPHMJHp0lukP4tT4ebiy7LokAr3cuG5JMkeKa4yO5DCKqhqYuugXGkwWls0aKk89E4AUsUOoazQze2kKBwureHNagjxNSZy2ED8Pll8/FIvWTF+8jcLKeqMj2b0Tb5YLKxtYPDOJPqHyNCXRTIrYzjWZLdzy/naSj5by4uTBnCP39EQb6R3sw5LrhlJc3XwWV1bTaHQku1XfZOaGZSlkFFQxf+oQEnoEGh1J2BApYjtmsWj+tjqNb/cX8vi4WHmkoWhzg7sHsHBGIkdKapm5ZBvVDSajI9mdRpOFW9/fzrYjpbwweZA80lD8hhSxnbJYNA9+vIe1O3K59/w+TB3Ww+hIwkGN6B3EvGuHkH68kuuXJlPfZDY6kt0wmS3csWIHX+8r5F/jYhk3OMzoSMIGSRHbIa01j3yazgfbjnHzub1l8QXR7sbEhPLiVYPZdqSUue+kShm3gtmiuWfVLr7Yk88/L+nPNHmzLP6AFLGd0Vrzr3V7eWfrUeac3Yv7LugrCwEIq7h8UDeemRDHpoNFUsZ/wWLR3P9RGp/sPM7fLuzL7LN6GR1J2DApYjuitebfX+xnyU9HuG5kJA9c1E9KWFjV5KTuUsZ/wWzR3L8mjVUt60fffK5csRJ/TorYTlgszZejF2w6xPThPXj40hgpYWGIX5fxHCnj/9JktnDXhztZmZLD7aOjZf1o0SpSxHbAZLbwt4/SWP5z8+Xoxy4fICUsDHWijH88WMTMJduokmcZ/2d09Ke7mi9H3z22jxynolWkiG1co8nCHSt2sjo1h7vG9JHL0cJmTE7qzstXDSblSBnXvv0LJdUNRkcyTF2jmbnvpLAhvYCHL42Ry9HipEgR27DqBhM3LE9h/e48Hry4P3eMiZYSFjZl3OAwFkxPIKOgiivf/Jnc8jqjI1ldaU0j1y7cyvcZRTw1fiCzzuxpdCRhZ6SIbVRBZT2T3/yZzZnFPD1hIDecLaMuhW0a1S+Ud2efQVF1A5Pmb2Hv8UqjI1nNsZJaJrb8P8+fMoRrz4gwOpKwQ1LENuhAfhXj3/iJoyU1LJyRyNVD5eAWti0pshMfzhmORWuufHML3+wrMDpSu9udU8GE+T9RVtvIe7PP4MLYrkZHEnZKitjGfH+gkEnzt2DWmpU3Duc8WQ5P2ImYbn58csuZ9Az2ZvbyFBb+eAittdGx2sUnO3O58q0teLg6s/rGESRGdjI6krBjUsQ2wmLRvPrNQa5bmkx4Jy/W3jySAd38jY4lxEnp4u/ByrnDuSCmC0+s38cDa3Y71PQmk9nCk+v3cseKncSFBbD25pFEhfgYHUvYORejAwioqGvi7g938s3+QsbHh/HU+IF4ujkbHUuIU+Ll5sK8KUN44asDvPFdFmk5FcybMoTIIPt+RnZpTSO3fbCdnzJLmDG8B/+8NAZXZzmXEafP7r+Lsktr+WRnrt1eAttxrIzLX9/MDxlFPHb5AF6cPEhKWNg9JyfFfRf0Y9GMRI5X1HHpa5tZn5ZndKxT9uPBIi58eRPJh8t4dlIcj42LlRIWbcbuv5MW/3SYO1bs5Ob3tlNsR/MYm8wWXth4gInzt2Aya1bMGcaMEZEyPUk4lNH9Q1l/+1lEh/pwy/vbuf+jNCrtaPGP+iYz//psL9MWbcPP05U1N49gcmJ3o2MJB6OMOJNMTEzUKSkpbfJaJrOFhZsP8+LGDHw8XHjiilguHmjboxcPFlRx18qd7MmtZFJCOA9fFoOfh6vRsYRoN40mCy9+lcGCTVmE+Hrw1IRYRvULNTrWn9qZXc79H6WxP7+KGcN7cP9F/eVqlThlSqlUrXXi737N3ov4hIyCKu5dtYu0nAouHNCFBy/pT/dOXm26jdNVVd/Ea99msnjzYfw8XXlq/EAujO1idCwhrGZXdjn3rd5FRkE14+PDeODifoT4ehgd67+U1TTy7IYDrEg+RrCPO89MipPZC+K0dYgihuaz47c2HeL1bzMxWzSzzuzJLef1xtfgs02LRbNmRy5Pf7GfkpoGJid0574L+xLk425oLiGM0GAy88Z3Wcz7LhM3Fyfmnt2bG87uiZebsWNHTWYLq1JzePbL/VTWm5g5IpI7x0Qb/vNDOIYOU8Qn5FfU8+yG/azZnkuQjxs3ntObq4dG4ONu3QPdbNF8vjuPN77LZH9+FfERATx62QAGdQ+wag4hbNHh4hqe/XI/X+zJJ8TXnTvH9GHCkDA8XK17+bfJbGHtjlze+C6ToyW1JEUG8q9xsfTv6mfVHMKxdbgiPmFXdjn//mIfWw+V4ufhwtRhPZg5MrLdL4XVNZr5bNdx5v+QxeHiGnoHe3PbqGguH9QNJycZjCXEr6UeLeXJ9fvYfqycIB83pg7rwZQzehDs275XjCrqmvh013He3nSIY6W1xIb5ccfoPozpHyKDJkWba7ciVkpdCTwK9AeGaq1b1a7WKuITdhwrY8GmQ3yZno+Lk+KcPsFcNqgbY2NC2+xymMWi+eVwKWu25/DFnnyqG0wM6ObHredFccGALlLAQvwJrTVbskpYtPkw3+4vxM3ZiQtju3DxwK6c2ze4zc6SzRbNtsOlrEzJ5vPdeTSYLMSF+3PH6GhG9ZMCFu2nPYu4P2AB3gLutdUiPuFwcQ3vbT3KurQ88ivr8XR15uw+QSRFdiKhRyADuvnj5tK6GV1aa46V1rL1UAlbD5WyJauYgsoGvN2cuWhgVyYMCWN4r85yYAtxkrKKqln60xHWpR2nrLYJLzdnzusbwvDenRncPYC+XXxbPYfXYtFkl9WyJauEzQeL+SmrmPLaJnw9XBg3uBtXJUYQG+Ynx6lod+1+aVop9T12UMQnWCyabUdK+XTXcTZlFJFT1vzoNncXJ3oGedPV34OuAZ6E+nrg7AQW3fxOuq7JTHZpLdlltRwrqaWy3gRAZ283zujVifNjunD+gLY7yxaiIzOZLfxyuJTPd+excW8BRVXN6wS4uTjRr4svoX4eBPm4E+zjhpe7C40mCw0mMw1NFvIq6skqquZISQ31TRYAQv3cOTMqmHP6BnN+TKjV70WLjs0milgpNQeYAxAREZFw9OjR095uWymorCf1aBmpR8s4WlJDXkU9eRX1lNY0/tefc3NxIjzQk+6BXnTv5EnfLn4M79WJ3sE+8o5aiHaktSanrI5dOeXsyi5nX14VRVUNFFc3UFrbyIkfY04K3F2cCfVzp2eQN72Cfegd7MPQnoFynApDnVYRK6W+Bn5vsuuDWutPWv7M99jRGXFrNZmb30k7KYWTQg5iIWyQyWyhwWTB3cUJF1l2UtioPyviv7yGqrUe0/aR7IOsJSuE7XNxlgIW9k2+e4UQQggDnVYRK6XGK6VygOHAeqXUhraJJYQQQnQMhizooZQqAo4CQUCx1QPYH9lPrSf7qnVkP7WO7KfWk33153porYN/7wuGFPF/Nq5Uyh/dvBb/T/ZT68m+ah3ZT60j+6n1ZF+dOrlHLIQQQhhIilgIIYQwkNFFvMDg7dsL2U+tJ/uqdWQ/tY7sp9aTfXWKDL1HLIQQQnR0Rp8RCyGEEB2aFLEQQghhIKsXsVKqu1LqO6XUPqVUulLqDmtnsCdKKWel1A6l1Dqjs9gypVSAUmq1Ump/y/fWcKMz2SKl1F0tx90epdQHSikPozPZCqXUYqVUoVJqz68+10kp9ZVS6mDLr4FGZrQVf7Cvnms5/tKUUmuVUgEGRrQrRpwRm4B7tNb9gWHALUqpGANy2Is7gH1Gh7ADrwBfaq37AYOQffYbSqkw4HYgUWsdCzgDVxubyqYsBS78n8/dD3yjtY4Gvmn5WPz+vvoKiNVaxwEZwAPWDmWvrF7EWus8rfX2lt9X0fwDM8zaOeyBUiocuARYaHQWW6aU8gPOBhYBaK0btdblhoayXS6Ap1LKBfACjhucx2ZorTcBpf/z6XHAspbfLwOusGYmW/V7+0prvVFrbWr5cCsQbvVgdsrQe8RKqUggHvjFyBw27GXgb4DF4By2rhdQBCxpuYy/UCnlbXQoW6O1zgWeB44BeUCF1nqjsalsXqjWOg+aTyKAEIPz2ItZwBdGh7AXhhWxUsoH+Ai4U2tdaVQOW6WUuhQo1FqnGp3FDrgAQ4D5Wut4oAa5hPgbLfc3xwE9gW6At1JqqrGphKNRSj1I8y3I94zOYi8MKWKllCvNJfye1nqNERnswEjgcqXUEWAFMEop9a6xkWxWDpCjtT5xZWU1zcUs/tsY4LDWukhr3QSsAUYYnMnWFSilugK0/FpocB6bppSaAVwKTNGySEWrGTFqWtF8L2+f1vpFa2/fXmitH9Bah2utI2keUPOt1lrOXn6H1jofyFZK9W351Ghgr4GRbNUxYJhSyqvlOByNDGr7K58CM1p+PwP4xMAsNk0pdSHwd+ByrXWt0XnsiRFnxCOBaTSf4e1s+e9iA3IIx3Ib8J5SKg0YDDxlbBzb03LFYDWwHdhN8/EvyxK2UEp9APwM9FVK5SilrgeeBsYqpQ4CY1s+7vD+YF+9DvgCX7X8XH/T0JB2RJa4FEIIIQwkK2sJIYQQBpIiFkIIIQwkRSyEEEIYSIpYCCGEMJAUsRBCCGEgKWIhhBDCQFLEQgghhIH+Dwlb5yDv4sSMAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8,4))\n", + "ax1 = fig.add_subplot(2, 1, 1)\n", + "ax1.plot(x, y)\n", + "ax2 = fig.add_subplot(2, 1, 2)\n", + "ax2.plot(x, np.cos(x))\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 304, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 컬러를 집어넣자\n", + "fig = plt.figure(figsize=(8, 4))\n", + "for i in np.arange(0.1, 1.2, 0.1):\n", + " x += i\n", + " plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 305, + "metadata": {}, + "outputs": [], + "source": [ + "# 선을 구별하자\n", + "linestyles = ['-', '--', '-.', ':', 'solid']\n", + "# 선에 음영처리 - pass" + ] + }, + { + "cell_type": "code", + "execution_count": 306, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "for i, j in enumerate(np.arange(0.1, 0.6, 0.1)):\n", + " x = x+j\n", + " plt.plot(x, y, ls=linestyles[i])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 307, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 마커 처리하기\n", + "x = np.arange(1, 8)\n", + "y = x\n", + "marker = ['+', 'o', '*', 's', '.']\n", + "\n", + "fig = plt.figure(figsize=(8, 4))\n", + "for i, j in enumerate(np.arange(0.3, 2.8, 0.5)):\n", + " x = x+j\n", + " plt.plot(x, y, marker=marker[i], markersize=8)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**[마커 모양 참조!](https://matplotlib.org/3.1.1/api/markers_api.html)**" + ] + }, + { + "cell_type": "code", + "execution_count": 308, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그래프 선과 색상을 문자열로 지정하기\n", + "t = np.arange(0., 5., 0.2)\n", + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 309, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--', t, t**2, 'bs')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 310, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. 그래프 제목 / 레이블 / 범례 처리" + ] + }, + { + "cell_type": "code", + "execution_count": 324, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Image size of 86400x288 pixels is too large. It must be less than 2^16 in each direction.", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m 339\u001b[0m \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 340\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 341\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mprinter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 342\u001b[0m \u001b[0;31m# Finally look for special method names\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 343\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_real_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_method\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/IPython/core/pylabtools.py\u001b[0m in \u001b[0;36m\u001b[0;34m(fig)\u001b[0m\n\u001b[1;32m 246\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 247\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m'png'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mformats\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 248\u001b[0;31m \u001b[0mpng_formatter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfor_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFigure\u001b[0m\u001b[0;34m,\u001b[0m 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key)\n\u001b[1;32m 417\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mreuse_renderer\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 418\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 419\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lastKey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 420\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mcleared\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, width, height, dpi)\u001b[0m\n\u001b[1;32m 94\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwidth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 95\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 96\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_renderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_RendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwidth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m 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It must be less than 2^16 in each direction." + ] + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 그래프에 설명 달기, title, 축 label, 그래프 label, 범례 추가\n", + "fig = plt.figure(figsize=(1200, 4))\n", + "plt.title('Salery')\n", + "plt.xlabel('years')\n", + "plt.ylabel('K/USD')\n", + "plt.plot(t, t, 'r--', label='Kim')\n", + "plt.plot(t, t**2, 'bs', label='Park')\n", + "plt.plot(t, t**3, 'g^', label='Me')\n", + "\n", + "plt.legend()\n", + "plt.show()\n", + "plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 312, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 좌표에 레이블 부여하기\n", + "x = [1, 2, 3, 4]\n", + "y = [20, 21, 20.5, 20.8]\n", + "plt.plot(x, y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 313, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='green')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.xticks(x)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.yticks(y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 315, + "metadata": {}, + "outputs": [], + "source": [ + "labels = ['High', 'Low', 1234567, 'asdjsdjflskj']" + ] + }, + { + "cell_type": "code", + "execution_count": 194, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, linestyle='dashed', marker='o', color='red')\n", + "\n", + "plt.xlim(0.5, 4.5)\n", + "plt.xticks(x, labels)\n", + "plt.ylim(19.5, 21.5)\n", + "plt.yticks(y)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 316, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot([1,2,3,4], [1,4,9,16], 'b')\n", + "\n", + "plt.axis([1,5,1,18])\n", + "plt.show()\n", + "# 왜 필요한지 모르겠음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### * 함수를 위한 그래프 그리기" + ] + }, + { + "cell_type": "code", + "execution_count": 320, + "metadata": {}, + "outputs": [], + "source": [ + "# 그래프의 중심을 특정 위치로 이동하려면 좌표출에 해당하는 spines를 이동해야 합니다. \n", + "# 이동할 때마다 spines 처리하지 않기 위해 하나의 함수 spines를 정의해서 사용합니다.\n", + "# spines는 4개의 좌표축을 가지므로 오른쪽과 위를 표시하지 않도록 색깔을 주지 않습니다. \n", + "# 아래와 좌측에만 좌표 측을 중심으로 이동하고 레이블을 지정합니다.\n", + "\n", + "def spines() :\n", + " ax = plt.gca() # 현재의 축 구하기\n", + " ax.spines['right'].set_color('none')\n", + " ax.spines['top'].set_color('none')\n", + "\n", + " ax.spines['bottom'].set_position(('data', 0))\n", + " ax.spines['left'].set_position(('data', 0))\n", + " \n", + " ax.xaxis.set_ticks_position('bottom')\n", + " ax.yaxis.set_ticks_position('left')" + ] + }, + { + "cell_type": "code", + "execution_count": 322, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = np.arange(-10, 13)\n", + "y = 3*x + 3\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 323, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = np.arange(-10, 13)\n", + "y = -3*x + 3\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 200, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 항등함수\n", + "\n", + "y = x\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3. 활성화 함수 그래프로 그려보기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">#### Quiz 2\n", + ">활성화 함수를 선형 함수로 사용하지 않는 이유를 적어주세요.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 201, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "## 계단함수\n", + "\n", + "def step(x) :\n", + " return np.where(x>0, 1, 0)\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = step(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 202, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 시그모이드 함수 : 자연상수를 지수로 사용해 작은 값과 큰 값을 특정 범위 내의 값으로 처리. 0과 1사이로 변환\n", + "\n", + "def sigmoid(x) :\n", + " return 1/(1 + np.exp(-x))\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = sigmoid(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 203, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 하이퍼볼릭 탄젠트 함수 : 자연상수를 분모에는 더하고 분자에는 빼는 구조. -1과 1사이의 값을 0을 중심으로 대칭형태로 변환\n", + "\n", + "def htan(x) :\n", + " return (np.exp(x) - np.exp(-x)) / (np.exp(x) + np.exp(-x))\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = htan(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# 렐루 함수 : 입력값이 0보다 크면 그 값을 그대로 반환하고, 0보다 작거나 같으면 0으로 출력. \n", + "# 기울기의 미분을 역으로 전파 될 때 기울기의 값이 사라지는 것을 방지하기 위해 많이 사용됨.\n", + "\n", + "def relu(x) :\n", + " return np.maximum(0, x)\n", + "\n", + "x = np.arange(-5, 5, 0.1)\n", + "y = relu(x)\n", + "plt.plot(x, y)\n", + "plt.grid()\n", + "spines()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">#### Quiz 3\n", + ">역전파(Backpropagation)란 무엇이고 왜 딥러닝에서 왜 중요한가?" + ] + }, + { + "cell_type": "code", + "execution_count": 205, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 소프트맥스 함수 : 0보다 크고 1보다 작은 n개 노드 출력. n개별 확률값을 출력하여 분류를 구하는 출력층에 주로 사용.\n", + "\n", + "def softmax(x) :\n", + " return np.exp(x) / np.sum(np.exp(x))\n", + "\n", + "x = np.arange(1, 5)\n", + "y = softmax(x)\n", + "\n", + "np.sum(y) # 1입니다.\n", + "\n", + "ratio = y\n", + "labels = y\n", + "\n", + "plt.pie(ratio, labels=labels, shadow=True, startangle=90)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 부록" + ] + }, + { + "cell_type": "code", + "execution_count": 206, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "t = np.arange(0, 5, 0.01)\n", + "\n", + "plt.figure(figsize=(10, 12))\n", + "\n", + "plt.subplot(411)\n", + "plt.plot(t, np.sqrt(t))\n", + "plt.grid()\n", + "\n", + "plt.subplot(413)\n", + "plt.plot(t, np.sin(t))\n", + "plt.grid()\n", + "\n", + "plt.subplot(423)\n", + "plt.plot(t, t**2)\n", + "plt.grid()\n", + "\n", + "plt.subplot(424)\n", + "plt.plot(t, t**3)\n", + "plt.grid()\n", + "\n", + "plt.subplot(414)\n", + "plt.plot(t, np.cos(t))\n", + "plt.grid()\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "![matplotlib graphic](https://mblogthumb-phinf.pstatic.net/MjAxOTA0MjNfNjkg/MDAxNTU1OTkxMzkxNDQ0.JN62ph8P1qug3h5dPIkLFGl1hGinWVq95Bi0zfhYVqAg.4CyrOHysh2bIzbKs0AA1jIDTVIrhY7i7uQ1BfaDh8qwg.PNG.heygun/anatomy.png?type=w800)\n", + "

" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git "a/06\354\236\245/[\353\204\230\355\214\214\354\235\264]06\354\236\245.pptx" "b/06\354\236\245/[\353\204\230\355\214\214\354\235\264]06\354\236\245.pptx" new file mode 100644 index 0000000..7a8be1a Binary files /dev/null and "b/06\354\236\245/[\353\204\230\355\214\214\354\235\264]06\354\236\245.pptx" differ diff --git "a/06\354\236\245/numpy_chapter_6_1_1.ipynb" "b/06\354\236\245/numpy_chapter_6_1_1.ipynb" index 5f788dc..9adf549 100644 --- "a/06\354\236\245/numpy_chapter_6_1_1.ipynb" +++ "b/06\354\236\245/numpy_chapter_6_1_1.ipynb" @@ -36,6 +36,13 @@ "## 예제 6-1-1 dtype 클래스 알아보기" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, { "cell_type": "code", "execution_count": 3, @@ -460,9 +467,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git "a/07\354\236\245/[\353\204\230\355\214\214\354\235\264]07\354\236\245.pptx" "b/07\354\236\245/[\353\204\230\355\214\214\354\235\264]07\354\236\245.pptx" new file mode 100644 index 0000000..7ec4d24 Binary files /dev/null and "b/07\354\236\245/[\353\204\230\355\214\214\354\235\264]07\354\236\245.pptx" differ diff --git "a/07\354\236\245/chapter 6,7 quiz \352\271\200\353\257\274\352\267\234" "b/07\354\236\245/chapter 6,7 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..7379bc4 --- /dev/null +++ "b/07\354\236\245/chapter 6,7 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,15 @@ +1. 바이트 문자열은 b'abcd'와 같이 나타내며 내부적으로는 인간이 읽을 수 없는 인코딩된 일련의 바이트들 입니다. +문자들을 바이트들로 표현하기 위해 b'문자들'과 같이 접두어 b를 앞에 붙입니다. +이렇게 접두어 b를 붙여 바이트 리터럴을 만들때, 각 문자는 ASCII 코드를 갖는 문자로 처리됩니다. + +2.히든레이어를 여러 개 다층으로 구성하고 활성화함수로 모두 선형함수를 이용하는 경우 +단층으로 구성한 것과 정확하게 동일하게 구성할 수 있어 무의미합니다. +따라서 깊게 망을 구성하려면 1개 이상의 비선형함수를 이용하여야 합니다. + + +3. 역전파란 신경망 학습 처리에서 오차를 최소화하는 함수의 경사를 효율적으로 계산하기 위한 방법입니다. +오차를 역방향으로 전파하는 방법으로 기본적인 원리는 경사하강법과 다르지 않으며 출력 노드만 미분하고, +그 값을 앞의 노드들에 전달하여 재사용하므로 경사하강법에 비해 빠르게 신경망을 학습시킬 수 있습니다. + +역전파가 딥러닝에서 중요한 이유는 가중치와 편향이 변할 때 뉴럴 네트워크가 +전체적으로 어떻게 변하는지에 대한 통찰력을 길러줍니다. 즉, 최적화된 가중치와 편향 값을 구할 수 있습니다. diff --git "a/07\354\236\245/numpy_chapter_7_2_2.ipynb" "b/07\354\236\245/numpy_chapter_7_2_2.ipynb" index 5189dd1..8be8200 100644 --- "a/07\354\236\245/numpy_chapter_7_2_2.ipynb" +++ "b/07\354\236\245/numpy_chapter_7_2_2.ipynb" @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -11,16 +11,16 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'1.18.2'" + "'1.19.2'" ] }, - "execution_count": 2, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -31,7 +31,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -49,7 +49,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -64,6 +64,32 @@ " ax.yaxis.set_ticks_position('left')" ] }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = np.arange(-10, 13)\n", + "y = 3*x + 3\n", + "plt.plot(x, y)\n", + "spines()\n", + "plt.show()" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -559,7 +585,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.8.5" } }, "nbformat": 4, diff --git "a/08\354\236\245/8\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" "b/08\354\236\245/8\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" new file mode 100644 index 0000000..7c4f8d6 --- /dev/null +++ "b/08\354\236\245/8\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" @@ -0,0 +1,8 @@ +Q1) 육십분법(0 ~ 360)을 호도법으로 표현해 보자. +π/n + +Q2) np.log1p(x) 함수를 사용하는 이유는? +원본+1에 자연로그나, 원본에 log1p나 결과가 같음으로 편하게 사용하기 위해 + +Q3) Vanishing gradient problem 문제란? +역전파로 학습시키려고 할때 신경망 레이어가 늘어날수록 기울기가 사라지는 문제 \ No newline at end of file diff --git "a/08\354\236\245/[\353\204\230\355\214\214\354\235\264]08\354\236\245.pptx" "b/08\354\236\245/[\353\204\230\355\214\214\354\235\264]08\354\236\245.pptx" new file mode 100644 index 0000000..e8018e2 Binary files /dev/null and "b/08\354\236\245/[\353\204\230\355\214\214\354\235\264]08\354\236\245.pptx" differ diff --git "a/08\354\236\245/chapter 8 quiz \352\271\200\353\257\274\352\267\234" "b/08\354\236\245/chapter 8 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..46507dd --- /dev/null +++ "b/08\354\236\245/chapter 8 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,21 @@ +Q1) 육십분법(0 ~ 360)을 호도법으로 표현해 보자 + +육십분법 0도 30도 45도 60도 90도 180도 360도 + 호도법 0 π/6 π/4 π/3 π/2 π 2π + + + +Q2) np.log1p(x) 함수를 사용하는 이유는? + +자연로그를 씌우면 -inf 경고메시지가 뜨지만 원본에 1을 더한 값에 로그를 씌우면 결국 log1인 것이니 0부터 값이 잘 나오게 된다. +이렇게 매번 1을 더하기는 귀찮으니 Numpy에서는 log1p라는 함수로 이를 한번에 해줄 수 있다. +원본+1에 자연로그나, 원본에 log1p나 결과가 같다. + + + +Q3) Vanishing gradient problem 문제란? + +활성화 함수의 선택에 의존한다. 많은 활성화 함수(시그모이드 함수나 쌍곡탄젠트 함수)는 그들의 입력값을 아주 작은 범위에 비선형적으로 강제적 입력을 한다. +예를 들어 시그모이드 함수는 실수를 작은 범위 [0,1]에 넣는다. 결과적으로 매우 큰 수들이 매우 작은 범위에 들어가게 된다. +입력 공간의 영역들에서 입력의 큰 변화가 출력의 작은 변화밖에 만들지 못하는 결과를 보여준다. +따라서 기울기가 작게 되고 비선형 함수들로 쌓아 올리면 올릴수록 악화된다. diff --git "a/08\354\236\245/chapter_8.ipynb" "b/08\354\236\245/chapter_8.ipynb" new file mode 100644 index 0000000..f9aef86 --- /dev/null +++ "b/08\354\236\245/chapter_8.ipynb" @@ -0,0 +1,4700 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.18.5'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.__version__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-1-1-1 소수점 이하 처리" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([3.14, 4.32])" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3.14, 4.32])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3., 4.])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.fix(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3., 4.])" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.trunc(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.array([3.14, 4.52])" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([4., 5.])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.ceil(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3., 4.])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.floor(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3., 5.])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.round(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3., 5.])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.around(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3.1, 4.5])" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.round(b,1)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3.1, 4.5])" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.around(b,1)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.array([5.55,6.66])" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([10., 10.])" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.round(c,-1)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([10., 10.])" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.around(c,-1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-1-2-1 산술연산 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([2,4,5,8,9])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 4, 8, 10, 16, 18])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x + x" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 4, 8, 10, 16, 18])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.add(x, x)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1., 1.])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x / x" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1., 1.])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.true_divide(x,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 1, 1, 1], dtype=int32)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x // x" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 1, 1, 1], dtype=int32)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.floor_divide(x,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 2., 3., 5., 6.])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x // 1.5" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.mod(4,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.remainder(4,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(1, 1)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.divmod(4,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([0. , 0.5]), array([0., 3.]))" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + " np.modf([0, 3.5])" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "d = np.reciprocal(2.)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.5" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d * 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-1-3-1 부호 및 절대값 처리" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([2,4,-5,8,-9])" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 2, 4, -5, 8, -9])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 1, -1, 1, -1])" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sign(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-2, -4, 5, -8, 9])" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.negative(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 2, 4, -5, 8, -9])" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.positive(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2, 4, 5, 8, 9])" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.abs(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sign(np.inf)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-inf" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.negative(np.inf)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "nan" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.negative(np.nan)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-1-3-2 제곱, 제곱근 처리" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.arange(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 4, 9, 16, 25, 36, 49, 64, 81], dtype=int32)" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.square(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 4, 9, 16, 25, 36, 49, 64, 81], dtype=int32)" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(a,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 1, 8, 27, 64, 125, 216, 343, 512, 729], dtype=int32)" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(a,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 1., 2., 3., 4., 5., 6., 7., 8., 9.])" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sqrt(np.power(a,2))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-2-1-1 논리연산 이해하기" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(2.0,4)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2., 3.])" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "1 & 2 " + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.bitwise_and(1,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "True & False" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "True and False" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.logical_and(True,False)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()\n" + ] + } + ], + "source": [ + "try :\n", + " x and x\n", + "except Exception as e :\n", + " print(e)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.logical_and(x,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.logical_or(x,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()\n" + ] + } + ], + "source": [ + "try :\n", + " x or x\n", + "except Exception as e :\n", + " print(e)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "y = x < 5" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "z = x > 5" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False, False])" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "z" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "z | y" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()\n" + ] + } + ], + "source": [ + "try :\n", + " z and y\n", + "except Exception as e :\n", + " print(e)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "z ^ y" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.logical_xor(z,y)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()\n" + ] + } + ], + "source": [ + "try :\n", + " not z\n", + "except Exception as e :\n", + " print(e)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "~ z" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.logical_not(z)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()\n" + ] + } + ], + "source": [ + "try :\n", + " not z\n", + "except Exception as e :\n", + " print(e)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-2-2-1 비교연산 이해하기" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(2.0,4)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2., 3.])" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.array([3,5])" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 5])" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x < y" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.less(x,y)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False, False])" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x > y" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False, False])" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.greater(x,y)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False, False])" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.equal(x,y)" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.less_equal(x,y)" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False, False])" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.greater_equal(x,y)" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True])" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.not_equal(x,y)" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [], + "source": [ + "z = np.random.randint(10,size=(3,3))" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[5, 7, 0],\n", + " [0, 4, 1],\n", + " [8, 2, 9]])" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "z" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [], + "source": [ + "bb = z < 6" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ True, False, True],\n", + " [ True, True, True],\n", + " [ True, False, True]])" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bb" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "7" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sum(bb)" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "7" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.count_nonzero(bb)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-2-3-1 연속되는 수의 합을 계산하기" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.arange(1,11)" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "55" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sum(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 3, 6, 10, 15, 21, 28, 36, 45, 55], dtype=int32)" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cumsum(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.arange(1,11).reshape(2,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 2, 3, 4, 5],\n", + " [ 6, 7, 8, 9, 10]])" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 7, 9, 11, 13, 15])" + ] + }, + "execution_count": 85, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sum(b, axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([15, 40])" + ] + }, + "execution_count": 86, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sum(b, axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 2, 3, 4, 5],\n", + " [ 7, 9, 11, 13, 15]], dtype=int32)" + ] + }, + "execution_count": 87, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cumsum(b, axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 3, 6, 10, 15],\n", + " [ 6, 13, 21, 30, 40]], dtype=int32)" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cumsum(b, axis=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-2-3-2 연속되는 수의 곱을 계산하기" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3628800" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.prod(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 6, 14, 24, 36, 50])" + ] + }, + "execution_count": 90, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.prod(b, axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 120, 30240])" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.prod(b, axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 2, 6, 24, 120, 720, 5040,\n", + " 40320, 362880, 3628800], dtype=int32)" + ] + }, + "execution_count": 92, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cumprod(b)" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 2, 3, 4, 5],\n", + " [ 6, 14, 24, 36, 50]], dtype=int32)" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cumprod(b ,axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1, 2, 6, 24, 120],\n", + " [ 6, 42, 336, 3024, 30240]], dtype=int32)" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cumprod(b ,axis=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-2-3-3 결측값을 제외하고 합과 곱을 계산하기" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.arange(1,11).reshape(2,5).astype('float')" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [], + "source": [ + "c[0,2] = np.nan" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [], + "source": [ + "c[1,2] = np.nan" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1., 2., nan, 4., 5.],\n", + " [ 6., 7., nan, 9., 10.]])" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "nan" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sum(c)" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "44.0" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.nansum(c)" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1., 3., 3., 7., 12., 18., 25., 25., 34., 44.])" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.nancumsum(c)" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "nan" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.prod(c)" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "151200.0" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.nanprod(c)" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.000e+00, 2.000e+00, 2.000e+00, 8.000e+00, 4.000e+01, 2.400e+02,\n", + " 1.680e+03, 1.680e+03, 1.512e+04, 1.512e+05])" + ] + }, + "execution_count": 104, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.nancumprod(c)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-3-1-1 지수법칙 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.1353352832366127" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(-2)" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.1353352832366127" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "1/ np.exp(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.power(np.e,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "7.3890560989306495" + ] + }, + "execution_count": 110, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.power(np.e,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "20.085536923187664" + ] + }, + "execution_count": 112, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "148.41315910257657" + ] + }, + "execution_count": 113, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a*b" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "148.41315910257657" + ] + }, + "execution_count": 114, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(np.e,5) " + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "148.4131591025766" + ] + }, + "execution_count": 115, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "148.4131591025766" + ] + }, + "execution_count": 116, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(2+3)" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.36787944117144233" + ] + }, + "execution_count": 117, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a / b" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.36787944117144233" + ] + }, + "execution_count": 118, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(2-3)" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "403.428793492735" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(a,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "403.428793492735" + ] + }, + "execution_count": 120, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a ** 3" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "403.4287934927351" + ] + }, + "execution_count": 121, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(2*3)" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "160.68429538550131" + ] + }, + "execution_count": 122, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(np.e*2, 3)" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "160.68429538550134" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(3) * np.power(2,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.4816890703380645" + ] + }, + "execution_count": 124, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(3/2)" + ] + }, + { + "cell_type": "code", + "execution_count": 125, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.4816890703380645" + ] + }, + "execution_count": 125, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(np.e, (3/2))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-3-1-2 지수함수 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4])" + ] + }, + "execution_count": 127, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ufunc" + ] + }, + "execution_count": 128, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.exp)" + ] + }, + { + "cell_type": "code", + "execution_count": 129, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1. , 2.71828183, 7.3890561 , 20.08553692, 54.59815003])" + ] + }, + "execution_count": 129, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1. , 2.71828183, 7.3890561 , 20.08553692, 54.59815003])" + ] + }, + "execution_count": 130, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(np.e,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 131, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ufunc" + ] + }, + "execution_count": 131, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.exp2)" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1., 2., 4., 8., 16.])" + ] + }, + "execution_count": 132, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp2(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 2, 4, 8, 16], dtype=int32)" + ] + }, + "execution_count": 133, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(2,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ufunc" + ] + }, + "execution_count": 134, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.power)" + ] + }, + { + "cell_type": "code", + "execution_count": 135, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 10, 100, 1000, 10000], dtype=int32)" + ] + }, + "execution_count": 135, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(10,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "147.4131591025766" + ] + }, + "execution_count": 136, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.expm1(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 137, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "147.4131591025766" + ] + }, + "execution_count": 137, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(5) - 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-3-1-3 배열을 지수함수로 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.linspace(-2*np.pi, np.pi, 10)" + ] + }, + { + "cell_type": "code", + "execution_count": 139, + "metadata": {}, + "outputs": [], + "source": [ + "a = a[:, np.newaxis]" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-6.28318531],\n", + " [-5.23598776],\n", + " [-4.1887902 ],\n", + " [-3.14159265],\n", + " [-2.0943951 ],\n", + " [-1.04719755],\n", + " [ 0. ],\n", + " [ 1.04719755],\n", + " [ 2.0943951 ],\n", + " [ 3.14159265]])" + ] + }, + "execution_count": 140, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": {}, + "outputs": [], + "source": [ + "a = (a+1j) * a" + ] + }, + { + "cell_type": "code", + "execution_count": 142, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[39.4784176 -6.28318531j],\n", + " [27.41556778-5.23598776j],\n", + " [17.54596338-4.1887902j ],\n", + " [ 9.8696044 -3.14159265j],\n", + " [ 4.38649084-2.0943951j ],\n", + " [ 1.09662271-1.04719755j],\n", + " [ 0. +0.j ],\n", + " [ 1.09662271+1.04719755j],\n", + " [ 4.38649084+2.0943951j ],\n", + " [ 9.8696044 +3.14159265j]])" + ] + }, + "execution_count": 142, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 143, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.39720110e+17+3.42215572e+01j],\n", + " [ 4.03087945e+11+6.98168800e+11j],\n", + " [-2.08489928e+07+3.61115149e+07j],\n", + " [-1.93336891e+04-2.36769404e-12j],\n", + " [-4.01789676e+01-6.95920133e+01j],\n", + " [ 1.49701860e+00-2.59291228e+00j],\n", + " [ 1.00000000e+00+0.00000000e+00j],\n", + " [ 1.49701860e+00+2.59291228e+00j],\n", + " [-4.01789676e+01+6.95920133e+01j],\n", + " [-1.93336891e+04+2.36769404e-12j]])" + ] + }, + "execution_count": 143, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(a)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-3-2-1 로그함수 법칙 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 144, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(10000,1000000,100000)" + ] + }, + { + "cell_type": "code", + "execution_count": 145, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 10000, 110000, 210000, 310000, 410000, 510000, 610000, 710000,\n", + " 810000, 910000])" + ] + }, + "execution_count": 145, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ufunc" + ] + }, + "execution_count": 146, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.log)" + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 147, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 148, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 148, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(np.e)" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.605170185988092" + ] + }, + "execution_count": 149, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(100)" + ] + }, + { + "cell_type": "code", + "execution_count": 150, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.605170185988092" + ] + }, + "execution_count": 150, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(10) + np.log(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 151, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-0.916290731874155" + ] + }, + "execution_count": 151, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(2/5)" + ] + }, + { + "cell_type": "code", + "execution_count": 152, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-0.916290731874155" + ] + }, + "execution_count": 152, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(2) - np.log(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 153, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "9.210340371976184" + ] + }, + "execution_count": 153, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(np.power(100,2))" + ] + }, + { + "cell_type": "code", + "execution_count": 154, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "9.210340371976184" + ] + }, + "execution_count": 154, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "2 * np.log(100)" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.605170185988092" + ] + }, + "execution_count": 155, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(100)" + ] + }, + { + "cell_type": "code", + "execution_count": 156, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.605170185988092" + ] + }, + "execution_count": 156, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log10(100) / np.log10(np.e)" + ] + }, + { + "cell_type": "code", + "execution_count": 157, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.605170185988092" + ] + }, + "execution_count": 157, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(100)" + ] + }, + { + "cell_type": "code", + "execution_count": 158, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.21714724095162588" + ] + }, + "execution_count": 158, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "1/ np.log(100)" + ] + }, + { + "cell_type": "code", + "execution_count": 159, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9999999999999999" + ] + }, + "execution_count": 159, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(100) * (1/np.log(100))" + ] + }, + { + "cell_type": "code", + "execution_count": 160, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 160, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(np.log(100) * (1/np.log(100)),1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-3-2-2 로그함수 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 161, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 9.21034037, 11.60823564, 12.25486281, 12.64432758, 12.92391244,\n", + " 13.142166 , 13.32121424, 13.47302025, 13.60478953, 13.72119988])" + ] + }, + "execution_count": 161, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 162, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([10., 12., 13., 13., 13., 14., 14., 14., 14., 14.])" + ] + }, + "execution_count": 162, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.ceil(np.log(x))" + ] + }, + { + "cell_type": "code", + "execution_count": 163, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "9999.99998023818" + ] + }, + "execution_count": 163, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(9.21034037)" + ] + }, + { + "cell_type": "code", + "execution_count": 164, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 164, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(np.exp(9.21034037), 10000)" + ] + }, + { + "cell_type": "code", + "execution_count": 165, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([4. , 5.04139269, 5.32221929, 5.49136169, 5.61278386,\n", + " 5.70757018, 5.78532984, 5.85125835, 5.90848502, 5.95904139])" + ] + }, + "execution_count": 165, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log10(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 166, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([4., 6., 6., 6., 6., 6., 6., 6., 6., 6.])" + ] + }, + "execution_count": 166, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.ceil(np.log10(x))" + ] + }, + { + "cell_type": "code", + "execution_count": 167, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "10000" + ] + }, + "execution_count": 167, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(10,4)" + ] + }, + { + "cell_type": "code", + "execution_count": 168, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "5.041392685158225" + ] + }, + "execution_count": 168, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log10(110000)" + ] + }, + { + "cell_type": "code", + "execution_count": 169, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "110000.00000000009" + ] + }, + "execution_count": 169, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(10, 5.041392685158225)" + ] + }, + { + "cell_type": "code", + "execution_count": 170, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "5.0" + ] + }, + "execution_count": 170, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log2(32)" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "32" + ] + }, + "execution_count": 171, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.power(2,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 172, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3.044522437723423" + ] + }, + "execution_count": 172, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log1p(20)" + ] + }, + { + "cell_type": "code", + "execution_count": 173, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3.044522437723423" + ] + }, + "execution_count": 173, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(1+20)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-4-1-1 배열의 유일한 원소 확인하기" + ] + }, + { + "cell_type": "code", + "execution_count": 174, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([[1,2,3],[4,5,6],[3,4,5]])" + ] + }, + { + "cell_type": "code", + "execution_count": 175, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6],\n", + " [3, 4, 5]])" + ] + }, + "execution_count": 175, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 176, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "function" + ] + }, + "execution_count": 176, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.unique)" + ] + }, + { + "cell_type": "code", + "execution_count": 177, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6])" + ] + }, + "execution_count": 177, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.unique(x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-4-1-2 포함여부 확인하기" + ] + }, + { + "cell_type": "code", + "execution_count": 178, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 179, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4])" + ] + }, + "execution_count": 179, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 180, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "function" + ] + }, + "execution_count": 180, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.in1d)" + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False])" + ] + }, + "execution_count": 181, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.in1d(5,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True])" + ] + }, + "execution_count": 182, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.in1d(4,x)" + ] + }, + { + "cell_type": "code", + "execution_count": 183, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True, False])" + ] + }, + "execution_count": 183, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.in1d([3,4,5],x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-4-2-1 합집합과 교집합" + ] + }, + { + "cell_type": "code", + "execution_count": 184, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([[1,2,3],[4,5,6],[3,4,5]])" + ] + }, + { + "cell_type": "code", + "execution_count": 185, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6],\n", + " [3, 4, 5]])" + ] + }, + "execution_count": 185, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 186, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.array([[11,21,13],[4,15,6],[3,14,5]])" + ] + }, + { + "cell_type": "code", + "execution_count": 187, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[11, 21, 13],\n", + " [ 4, 15, 6],\n", + " [ 3, 14, 5]])" + ] + }, + "execution_count": 187, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "function" + ] + }, + "execution_count": 188, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.union1d)" + ] + }, + { + "cell_type": "code", + "execution_count": 189, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 4, 5, 6])" + ] + }, + "execution_count": 189, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.intersect1d(x,y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-4-2-2 차집합과 대칭차집합" + ] + }, + { + "cell_type": "code", + "execution_count": 190, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.unique(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 191, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6])" + ] + }, + "execution_count": 191, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 192, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.unique(y)" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 3, 4, 5, 6, 11, 13, 14, 15, 21])" + ] + }, + "execution_count": 193, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 194, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "function" + ] + }, + "execution_count": 194, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.setdiff1d)" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.setdiff1d(a,b)" + ] + }, + { + "cell_type": "code", + "execution_count": 196, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2])" + ] + }, + "execution_count": 196, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 197, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "function" + ] + }, + "execution_count": 197, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.setxor1d)" + ] + }, + { + "cell_type": "code", + "execution_count": 198, + "metadata": {}, + "outputs": [], + "source": [ + "d = np.setxor1d(a,b)" + ] + }, + { + "cell_type": "code", + "execution_count": 199, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 2, 11, 13, 14, 15, 21])" + ] + }, + "execution_count": 199, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 200, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 2, 11, 13, 14, 15, 21])" + ] + }, + "execution_count": 200, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.setxor1d(x,y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-5-1 삼각함수 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 201, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array((0., 30., 45., 60., 90.))" + ] + }, + { + "cell_type": "code", + "execution_count": 202, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0., 30., 45., 60., 90.])" + ] + }, + "execution_count": 202, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 203, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0. , 0.5 , 0.70710678, 0.8660254 , 1. ])" + ] + }, + "execution_count": 203, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sin(a* np.pi / 180.)" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0. , 0.5 , 0.70710678, 0.8660254 , 1. ])" + ] + }, + "execution_count": 204, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.sin(np.radians(a))" + ] + }, + { + "cell_type": "code", + "execution_count": 205, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.00000000e+00, 8.66025404e-01, 7.07106781e-01, 5.00000000e-01,\n", + " 6.12323400e-17])" + ] + }, + "execution_count": 205, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cos(a* np.pi / 180.)" + ] + }, + { + "cell_type": "code", + "execution_count": 206, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.00000000e+00, 8.66025404e-01, 7.07106781e-01, 5.00000000e-01,\n", + " 6.12323400e-17])" + ] + }, + "execution_count": 206, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.cos(np.radians(a))" + ] + }, + { + "cell_type": "code", + "execution_count": 207, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000000e+00, 5.77350269e-01, 1.00000000e+00, 1.73205081e+00,\n", + " 1.63312394e+16])" + ] + }, + "execution_count": 207, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.tan(a* np.pi / 180.)" + ] + }, + { + "cell_type": "code", + "execution_count": 208, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000000e+00, 5.77350269e-01, 1.00000000e+00, 1.73205081e+00,\n", + " 1.63312394e+16])" + ] + }, + "execution_count": 208, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.tan(np.radians(a))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-5-2-1 역삼각함수 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 209, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt \n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 210, + "metadata": {}, + "outputs": [], + "source": [ + "in_array = np.linspace(-np.pi/2, np.pi/2, 12) " + ] + }, + { + "cell_type": "code", + "execution_count": 211, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-1.57079633, -1.28519699, -0.99959766, -0.71399833, -0.428399 ,\n", + " -0.14279967, 0.14279967, 0.428399 , 0.71399833, 0.99959766,\n", + " 1.28519699, 1.57079633])" + ] + }, + "execution_count": 211, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "in_array" + ] + }, + { + "cell_type": "code", + "execution_count": 212, + "metadata": {}, + "outputs": [], + "source": [ + "out_tan1 = np.tan(in_array) " + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-1.63312394e+16, -3.40568724e+00, -1.55603037e+00, -8.66504933e-01,\n", + " -4.56684698e-01, -1.43778294e-01, 1.43778294e-01, 4.56684698e-01,\n", + " 8.66504933e-01, 1.55603037e+00, 3.40568724e+00, 1.63312394e+16])" + ] + }, + "execution_count": 213, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "out_tan1" + ] + }, + { + "cell_type": "code", + "execution_count": 214, + "metadata": {}, + "outputs": [], + "source": [ + "out_tan2 = np.arctan(out_tan1) " + ] + }, + { + "cell_type": "code", + "execution_count": 215, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-1.57079633, -1.28519699, -0.99959766, -0.71399833, -0.428399 ,\n", + " -0.14279967, 0.14279967, 0.428399 , 0.71399833, 0.99959766,\n", + " 1.28519699, 1.57079633])" + ] + }, + "execution_count": 215, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "out_tan2" + ] + }, + { + "cell_type": "code", + "execution_count": 216, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(in_array, out_tan1, color = 'blue', marker = \"*\") \n", + "plt.plot(in_array, out_tan2, color = 'red', marker = \"o\") \n", + "plt.title(\"blue : numpy.tan() \\nred : numpy.arctan()\") \n", + "plt.xlabel(\"X\") \n", + "plt.ylabel(\"Y\") \n", + "plt.show() " + ] + }, + { + "cell_type": "code", + "execution_count": 217, + "metadata": {}, + "outputs": [], + "source": [ + "out_array1 = np.sin(in_array) \n", + "out_array2 = np.arcsin(out_array1)" + ] + }, + { + "cell_type": "code", + "execution_count": 218, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 218, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(in_array, out_array2)" + ] + }, + { + "cell_type": "code", + "execution_count": 219, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(in_array, out_array1, color = 'blue', marker = \"*\") \n", + "plt.plot(in_array, out_array2, color = 'red', marker = \"o\") \n", + "plt.title(\"blue : numpy.sin() \\nred : numpy.arcsin()\") \n", + "plt.xlabel(\"X\") \n", + "plt.ylabel(\"Y\") \n", + "plt.show() " + ] + }, + { + "cell_type": "code", + "execution_count": 220, + "metadata": {}, + "outputs": [], + "source": [ + "in_array2 = np.linspace(0, np.pi, 12) " + ] + }, + { + "cell_type": "code", + "execution_count": 221, + "metadata": {}, + "outputs": [], + "source": [ + "out_cos1 = np.cos(in_array2) \n", + "out_arccos2 = np.arccos(out_cos1)" + ] + }, + { + "cell_type": "code", + "execution_count": 222, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 222, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(in_array2, out_arccos2 )" + ] + }, + { + "cell_type": "code", + "execution_count": 223, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(in_array2, out_cos1, color = 'blue', marker = \"*\") \n", + "plt.plot(in_array2, out_arccos2, color = 'red', marker = \"o\") \n", + "plt.title(\"blue : numpy.cos() \\nred : numpy.arcos()\") \n", + "plt.xlabel(\"X\") \n", + "plt.ylabel(\"Y\") \n", + "plt.show() " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 8-5-3-1 쌍곡선 삼각함수 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 224, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt \n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 225, + "metadata": {}, + "outputs": [], + "source": [ + "in_array = np.linspace(-2 * np.pi, 2*np.pi,100) " + ] + }, + { + "cell_type": "code", + "execution_count": 226, + "metadata": {}, + "outputs": [], + "source": [ + "out_tanh = np.tanh(in_array) " + ] + }, + { + "cell_type": "code", + "execution_count": 227, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(in_array, out_tanh, color = 'red', marker = \"o\") \n", + "plt.title(\" numpy.tanh\") \n", + "plt.xlabel(\"X\") \n", + "plt.ylabel(\"Y\") \n", + "plt.show() " + ] + }, + { + "cell_type": "code", + "execution_count": 228, + "metadata": {}, + "outputs": [], + "source": [ + "out_sinh = np.sinh(in_array) " + ] + }, + { + "cell_type": "code", + "execution_count": 229, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(in_array, out_sinh, color = 'red', marker = \"o\") \n", + "plt.title(\" numpy.sinh()\") \n", + "plt.xlabel(\"X\") \n", + "plt.ylabel(\"Y\") \n", + "plt.show() " + ] + }, + { + "cell_type": "code", + "execution_count": 230, + "metadata": {}, + "outputs": [], + "source": [ + "out_cosh = np.cosh(in_array) " + ] + }, + { + "cell_type": "code", + "execution_count": 231, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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"a/09\354\236\245/9\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" "b/09\354\236\245/9\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" new file mode 100644 index 0000000..6f87359 --- /dev/null +++ "b/09\354\236\245/9\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" @@ -0,0 +1,13 @@ +Q1) 균등 분포를 만드는 함수 중 randint와 uniform의 차이는?? +randint : 정수리턴, uniform : 부동소수리턴 + +Q2) 배열 원소의 개수가 짝수일 경우 중앙값 처리방식은?? +중앙값의 두개수의 평균값으로 처리 + +Q3) 상관 계수와 공분산이란?? +상관계수 : 상관분석에서 변수간의 연관성을 -1~1 사이의 값으로 표현하는것으로 말그대로 변수간의 상관성을 보여줌 +공분산 : 확률변수들이 어떻게 퍼져있는지 나타내는것 +Cov(X, Y) > 0 X가 증가 할 때 Y도 증가한다. +Cov(X, Y) < 0 X가 증가 할 때 Y는 감소한다. +Cov(X, Y) = 0 공분산이 0이라면 두 변수간에는 아무런 선형관계가 없으며 두 변수는 서로 독립적인 관계에 있음을 알 수 있다. +그러나 두 변수가 독립적이라면 공분산은 0이 되지만, 공분산이 0이라고 해서 항상 독립적이라고 할 수 없다. \ No newline at end of file diff --git "a/09\354\236\245/[\353\204\230\355\214\214\354\235\264]09\354\236\245.pptx" "b/09\354\236\245/[\353\204\230\355\214\214\354\235\264]09\354\236\245.pptx" new file mode 100644 index 0000000..869933c Binary files /dev/null and "b/09\354\236\245/[\353\204\230\355\214\214\354\235\264]09\354\236\245.pptx" differ diff --git "a/09\354\236\245/chapter 9 quiz \352\271\200\353\257\274\352\267\234" "b/09\354\236\245/chapter 9 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..00cf4b5 --- /dev/null +++ "b/09\354\236\245/chapter 9 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,21 @@ +Q1) 균등 분포를 만드는 함수 중 randint와 uniform의 차이는?? +randint(최소, 최대) : 입력 파라미터인 최소부터 최대까지 중 임의의 정수를 리턴합니다. + +uniform(최소, 최대) : 입력 파라미터인 최소부터 최대까지 중 임의의 부동소수점(float) 숫자를 리턴합니다. + + +Q2) 배열 원소의 개수가 짝수일 경우 중앙값 처리방식은?? +중간에 위치한 두 개의 숫자의 평균으로 중앙값을 계산해줍니다. + + +Q3) 상관 계수와 공분산이란?? +상관분석은 두 변수간에 어떤 선형적 또는 비선형적 관계를 갖고 있는지를 분석하는 방법입니다. +두 변수간의 관계의 강도를 상관관계라고 하며, 그 정도를 파악하는 것을 상관 계수라고 합니다. +상관계수는 두 변수간의 연관된 정도를 나타낼 뿐 인과관계를 설명하는 것은 아닙니다. +두 변수가 함께 변하는 정도를 -1 ~ 1 범위의 수로 나타낸 것입니다. + + +공분산은 두 변수가 함께 변화(방향성)하는 정도를 나타내는 지표입니다. +공분산이 +인 경우: 두 변수가 같은 방향으로 변화합니다.(하나가 증가하면 다른 하나도 증가) +공분산이 -인 경우: 두 변수가 반대 방향으로 변화합니다.(하나가 증가하면 다른 하나는 감소) +공분산 = 0이면 두 변수가 독립, 즉, 한 변수의 변화로 다른 변수의 변화를 예측하지 못합니다. diff --git "a/10\354\236\245/10\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" "b/10\354\236\245/10\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" new file mode 100644 index 0000000..32658b0 --- /dev/null +++ "b/10\354\236\245/10\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" @@ -0,0 +1,8 @@ +1. trapz 함수로 적분을 하면 결괏값이 차이가 난다. 그 이유는? +근사값을 구하기 때문. + +2. 합성곱 연산을 처리할 때 모드를 full로 처리하면 원소가 하나 추가된 8개가 된다, 이 이유는? +입력데이터의 모든 원소가 합성곱 연산에 같은 비율로 참여하도록 하기 위함. + +3. lstsq 함수란? +역행렬이 존재하면 a * X = b 가 되므로 최소자승해를 구할수 있다. 이때 사용하는 함수. \ No newline at end of file diff --git "a/10\354\236\245/[\353\204\230\355\214\214\354\235\264]10\354\236\245.pptx" "b/10\354\236\245/[\353\204\230\355\214\214\354\235\264]10\354\236\245.pptx" new file mode 100644 index 0000000..61478a5 Binary files /dev/null and "b/10\354\236\245/[\353\204\230\355\214\214\354\235\264]10\354\236\245.pptx" differ diff --git "a/10\354\236\245/chapter 10 quiz \352\271\200\353\257\274\352\267\234" "b/10\354\236\245/chapter 10 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..27b1b80 --- /dev/null +++ "b/10\354\236\245/chapter 10 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,11 @@ +1. trapz 함수로 적분을 하면 결괏값이 차이가 난다. 그 이유는? +trapz(x,y) =>x는 미리 정해진 간격을 y는 그 x값에 따른 y값을 적분한다를 의미 +근사해를 구하기 때문 ( quad는 소수점 이하 4자리까지 정확) + +2. 합성곱 연산을 처리할 때 모드를 full로 처리하면 원소가 하나 추가된 8개가 된다, 이 이유는? +원본 배열의 원소가 연산에 동일하게 참여하도록 하기 위해서 원본 배열에 양 끝에 가상의 원소를 추가한 방식. 이때 가상의 원소로는 0을 사용하기 때문. + +3. lstsq 함수란? +행렬 A와 b를 모두 인수로 받고 뒤에서 설명할 최소자승문제(least square problem)의 답. +잔차제곱합(residual sum of squares) resid, 랭크(rank) rank, 특잇값(singular value) s를 반환. +미지수와 방정식의 개수가 같고 행렬 A의 역행렬이 존재하면 최소자승문제의 답과 선형 연립방정식의 답이 같으므로 lstsq() 명령으로 선형 연립방정식을 풀 수도 있음. diff --git "a/10\354\236\245/numpy_chapter_10.ipynb" "b/10\354\236\245/numpy_chapter_10.ipynb" new file mode 100644 index 0000000..8745b6d --- /dev/null +++ "b/10\354\236\245/numpy_chapter_10.ipynb" @@ -0,0 +1,5800 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.18.1'" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.__version__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-1-1-1 방정식 알아보기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " ### x**2 − 2*x + 1" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "ef = np.array([1,-2,1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "위의 수식에 맞는 계수를 1차원 배열로 만듦" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "p = np.poly1d(ef)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([ 1, -2, 1])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 2\n", + "1 x - 2 x + 1\n" + ] + } + ], + "source": [ + "print(p)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.poly1d" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(p)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " 다항식은 ploy1d 클래스 생성자에 계수를 가진 1차원 배열을 넣어서 다항식 객체를 만들고\n", + " 이 다항식의 객체를 print 함수로 출력을 하면 수식을 구성해서 표시한다\n", + " 만들어진 객체의 클래스를 확인하기 위해 type 클래스로 확인하면 poly1d 클래스라는 것을 알 수 있다" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'x'" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p.variable" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p.order" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "다항식의 미지수인 변수를 variable 속성으로 확인한다\n", + "만들어진 다항식의 차수를 order 속성으로 확인한다" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, -2, 1])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p.coef" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, -2, 1])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p.coefficients" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, -2, 1])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p.coeffs" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "다항식의 계수는 coef, coefficients,coeffs 속성으로 확인한다" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1.])" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p.roots" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p(0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "방정식의 해는 roots 속성을 조회하면 구할 수 있고, 이 다항식 객체에 0을 인자로 전달해서 방정식의 해를 구할 수 있다" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "### p[0] * x**n + p[1] * x**(n-1) + ... + p[n-1]*x + p[n]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "다항식 객체를 만들지 않고도 계수를 만든 1차원 배열을 roots 함수에 인자로 전달해서 방정식의 해를 구할 수 있다" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1.])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.roots(ef)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 방정식의 값을 계산하기" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.polyval([1,-2,1], 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "16" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.polyval([1,-2,1], 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "다항식을 계수를 1차원 배열로 전달하고 미지수 x의 값을 지정해서 polyval 함수에 인자로 전달하면 다항식의 값을 계산한다" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-1-1-2 다항식 수식 알아보기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### (x+2) + (x-2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "두 개의 다항식을 정의한 후 덧셈 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([2, 0])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.poly1d([1,2]) + np.poly1d([1,-2])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "미지수 x의 계수가 2이고, 상수의 값은 0" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### (x+2)*(x-2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "두 개의 다항식을 정의한 후 곱셈 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([ 1, 0, -4])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.poly1d([1,2]) * np.poly1d([1,-2])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "차수가 2인 경우는 1, 차수가 1인 경우는 0이고 상수는 -4" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### (x**2 -4x +4) / x -2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "나눗셈 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(poly1d([ 1., -2.]), poly1d([0.]))" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.poly1d([1, -4, 4]) / np.poly1d([1, -2])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "두 다항식에 동일한 1차원 다항식을 약분되어 1차원이 남는 것을 확인할 수 있음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-1-1-3 다항식의 계수를 ploy 함수로 생성하기 " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 방정식의 계수 생성 " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "차원이 1인 다항식의 계수는 하나의 원소를 가지는 튜플을 poly 함수의 인자로 전달해서 1차원 배열로 생성한다\n", + "이 계수를 poly1d 함수에 전달해서 다항식 객체로 전달한 후에 차수와 해를 확인해보자" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.poly((1, ))" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1., -1.])" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "a_ = np.poly1d(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(1, array([1.]))" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a_.order, a_.roots" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "2차원일 때는 두 개의 원소를 가진 튜플에 전달해서 다항식에 들어갈 계수를 생성한다 \n", + "\n", + "이 계수의 1차원 배열을 poly1d 함수에 인자로 전달한 후에 다항식 객체를 만든 후에 roots 속성의 해를 구한다" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.poly((1,1 ))" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1., -2., 1.])" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1.])" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.poly1d(b).roots" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "튜플의 원소를 2로 지정해서 다항식을 구하고 해를 구한다" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.poly((2,2 ))" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1., -4., 4.])" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2., 2.])" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.poly1d(c).roots" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "3차원 다항식을 구하기 위해 poly 함수에 3개의 원소를 가지는 튜플을 전달한다 \n", + "\n", + "이를 poly1d 함수로 다항식을 객체로 변환한 후에 해를 구하면 복소수를 가진 해를 구한다" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "복소수란?\n", + "복소수의 특징을 알기 전에 허수의 정의를 설명해 드리자면\n", + "허수 입니다.\n", + "\n", + "여기서 영어 소문자 i는 단어 imaginary unit(상상의 수)의 첫글자 i에서 따온 것으로 수학자 오일러(1707~1783)가 처음 사용하였다고 합니다.\n", + "\n", + "\n", + "여기서, 복소수의 개념을 알려드리겠습니다.\n", + "\n", + "복소수란 a, b가 실수 일 때, a+bi의 꼴로 나타낸 수를 복소수라고 합니다. \n", + "\n", + "이때, a를 실수부분, b를 허수부분이라고 합니다." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "d = np.poly((1,1,1 ))" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1., -3., 3., -1.])" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.0000055 +0.00000000e+00j, 0.99999725+4.76060528e-06j,\n", + " 0.99999725-4.76060528e-06j])" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.poly1d(d).roots" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-1-1-4 다항식을 사용해서 그래프 그리기" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "t = np.arange(0, 10, 0.01)\n", + "y = 3*t + 5\n", + "y_noise = y + np.random.randn(len(y))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "그래프 그릴 모듈을 import 하고 입력값을 1차원 배열로 만든다\n", + " \n", + "1차원 함수를 정의해서 결괏값을 만든다\n", + "\n", + "이 결과값에 대한 노이즈를 정규분포의 값으로 만든다\n", + " \n", + "\n", + "노이즈로 만든 1차원 다항식을 만들기 위해 출력값을 넣어서 1차원 다항식의 계수를 만든다\n", + " \n", + "이를 poly1d함수에 넣어서 다항식을 만들어서 적정한 방정식을 찾는다" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "fp1 = np.polyfit(t, y_noise, 1)\n", + "f1 = np.poly1d(fp1)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2.97039316, 5.16812474])" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fp1" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([2.97039316, 5.16812474])" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "두 개의 그래프를 만들기 위해 subplots 함수로 행 1을 지정하고 열에 2를 지정한 후에 실행을 하면\n", + " \n", + "axes 변수에 Axes 객체가 2개가 만들어진다\n" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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v3r17O7WY+yImJsahNVyI1qauLg8AVfU8c7i744oRBi+EyANQ1Q12LYVuYUF+K58s5SJEO1VcvJ7KSstErrYASlXhtdeWs2HD1dTWhrJw4accOmQ/vL1NtUAJIdosrV5yNcq0tvYU+fnfaLlctUCp0P9liN0MtdGw81mo6wC+r5fnXasIoBoyNUB7JN8f0RTS0yewZYulWdz2M/bpp4/yxRcPWvdvvPFF+vbdZXdmq6g2Wg35/dTI90H4n+VnyrnO2bnzD+zefSVGYxXgHED1+id0+xaMQbB7KVRZV285iwKokJAQCgoK5JfPDVVVKSgoICQkpKWLIs5S1dU5GAzasPSff76WN998wXps4sR/M336rHpn+K8Cauuk/tJIPSWagm2Gcec6p6rqMAC1tSeors5xOBb/H0h8F1QFMuZBaRMt3djibfEJCQnk5uaSl5fnkF5dXd1mfxn9XfaQkBASEvyz+KEQ9W3apI1H2b17HEuX/hNV1Z6rkpPXM2fO7eh07Ts48MRd/QVttw5rbLmlnhL+5/4Vnk4XgtFYwubNjlNpdNgKA83PgAcfhPzx9c/03wNgiwdQgYGB1hW/7aWlpbXYfCJnqi2XXZz9VNXE6dMrHdJyc/vx5JOrqa3VljlISDjA009fTVBQjatLCDN39Re03XqgrZZbnI0sD2+OQU9Jyf+oqzvllDs8E4Y8BTojHP0jHJ/StKVr8Vd4Qoiml5v7V0pKNlFbm8eJE++SkXGL9VhJSSypqd9RWhoHQEzMaZYt+wPR0b7N7iuEEE3B8mq8rOxXcnNfxWiswGAoY/t2p2Ylgk/B0NkQUAmnJsPh6a6v2dhlj1xp8RYoIYT/VVcfpbb2tHU/M/Mhl/kMhgCefHI1x471ByAoqIolS66ie/fDzVJOIYSoT1VNFBR8jaVzeEbGrQBkZc3DaHRediqgDIbOguB8KD4H9s3CQ/OQBFBCCA82berlU76AAAOTJv2bvXvHAjB37p8YPHizl7OEEKLpnDjxNgcOOM9t6yp4UmoheR6EH4GKXrD7aVA9TvUkAZQQwk+uv/4VOnXKobCwKxMmfOkxb7du93L8eDMVTAjRLtXU5PqW0QRJz0LMDqiJ1eZ6MkS4zx4enkK3btPJzs7wSzklgBLiLJKfv5qwsEENPs9xpnFNv36vkJn5sF2KngEDXuf48bRGl08IIdyprMykstL3tRb7vA3xP4EhFHYtg5p427HAwM6A4tDZfPToneYt/wRQ0olciDbg0KFZnDjxvtd8u3dfzZYtAzzm2bv3XGpqvA9TT0hw3W9KCCEaoqhoLXv33ux1vrRffx3M7t1X+3TNbl9Az5Vg0sOehVDez/H44MEr0en8t2yLKxJACdEG5OQ8x/79d7g8ZjLV+XydjIzRzJjxEzNn/khxcZy/iieEEG7t2HExp0+vdLlmnaoarRNmqqpvdVnseui/Qts+8BgUjXbOExAQZTcRZ9OQAEqINqyy8iC//BLEqVPeF7g+fjyROXO+oaYmjD17zmPJkn828G4yoaYQwr9++SWULVscux14eiiM2guDnwbFBFl3wMlLXecLDk6gqessCaCEaMMqKrR3+nl5q6iudt/xsrS0A6mp31Fc3BmAqKgCHnroQbf5Bw58z78FFUK0Y5ZAxrlFSFXrqKo6YF7TzpzLVOnyKqG5kDwH9DVw/HI4cpvru8XH327uA9W0LVDSiVyINs0yJFdl06YeLnPU1gYzd+5X5ORoCwcHBlbz9NNX0aPHQZf5e/SYRdeu05qgrEKI9kkLoDz1gdq792brdlXVIafjgUXaXE9BJVBwLhx8FLczEgwa9IHX+/mDtEAJ0aZpNYi7isJkUli27H127ZpgTZsz5zZSUjY04l7yCk8IcSbctwgVFf3Xul1Y+J3DMV01pMyB0ONQ1h/2PgWq3pf7SQAlhHDL8gjmumJ6552lrF17k3X/nnseY9KkVZ6v6MelDoQQwtYC5T6AUhQ3L8SMMHgxRO2Dqi7adAXGUF/vK53IhRBulJb+z7zl/KS1evVf+PjjVOv+1Ve/xo03vthMJRNCiPoc66mqqizrtqIEWrd1ulBr9v6vQtwGqIuEXc9CbccG3E1e4Qkh6jMaq6iqyiYn5wXAuaL49deLeeWV16z748Z9zYMPPox941KHDpe4vHZsrLt5WOQVnhDiTFimKzBiNFaweXMf6xH7FiiTSetQ3mMldF8NpkDYvQQqe4Ki2OZ2Cg52XrKqU6cb7fYkgBJC1LNuXRjp6RPtUhwriv79tzNw4K8ADBiwlXnzbkKvNxIU1MWaZ9CgD52uO2mSSnT02CYpsxCifbM86B04cB/r1jmuuWLfAgXQeQ30fQtUBTKehJIULT0u7hpAW1YqJuYCh3PGjctlyJBP7FJkFJ4QwoWamqPWbaOxzOFYTEw+L700mb/97Tluu+1pQkO1YcH2LVWK4lMvTAB69HicTp1uOMMSCyHaNy2gOXXKeQ662lrbIpsx27U17gAO3Qd5ds+K1td7qDi3MDnWaZb6bsCAt10uRHymJIAS4ixQUrLOKS0kpIqHH64/15P9E5nvAVTfvs81rmBCCGFm6USu14e5nespPAuS54HOADnXQ+71jsf1+jBAm2yzftcF547o2vG4uKsJCup05h+gHnmFJ0QLKir6kbQ0xaEzZWPU1gbVe6XnmsFgewpzO+pFCCF8lJamcOhQqveMgLc+SUF5kDILAirg9EQ4dK9znuBgbb67urrTTtdzblU3uUn3DwmghGhBJ068C0BJyf+85LQpKPiPw76qwgsvvMOMGT+xatXDHs9V1RprJ3GdLtBjXiGE8EVOzrM+5jRRXZ1DXV2+0xF9BQxNhZA8KEmGfXNwGaFERo4AIDx8CPX7ONUPlCwtVBJACXEWa8jcS7t2/cFh/733FvHDD7ehqjpee205W7f+zuP5gwevZPToDHS64EaVVQghGkNVVdLTL3BKV+pgyFMQcRgqe8Cup8EU5OICQGjoAEaP3kPv3otcvMJz3QLVkO4KDSEBlBDN4NSpj6iuPuriSMOG2aalOQZa3357Jx9+OM+6f/nlbzFy5Bq35wcGxqPXhxAentSg+woh2q+ysnSnlm9o+DxLO3ZMpro6u95FYODz0HEb1HaAnc+CIdr9NUJCehEePtjcgu65E7nluKI0TagjnSCEaGImUx0ZGbcSHNyLceOy6x21VAANn/17y5ZLeOmlv1n3x4z5nkcfvQ9PjVm9es1xeywgIKbBZRBCnP22bRsOaNOc2FNVY4OuU1mZ4ZSW+C50+QGMIbDzGaju6vkajsGQ5xYoW4AnAZQQbZTWjGw/TNfCl19wV8sfZGYOZcGCVZhM2q9wv37beeqpG9HrbRVap05/JC9PmxMlKmosPXumEht7pct7jBt33G54sE3PnnMIDe3vtmxCiPZLVevO6PyuX0Ovf4Kqgz1PQflA93lHjNjsMI8d2OaOSkr6kOjo8536dZ5zzn85fvytJuuuIAGUEE3M81OaZZSI+2aj+gFUXl53Zs/+lqqqSAA6dz7KM89cTlhYuUO+uLgrrQHUsGHr0Omcf92Tk1djMBQTHOz6sa9PnyUeyi6EaM9U1dDocztuhAHLte0DM6DQxfy9/fq9Qmbmw8TFTSEqaoyL48sJDOxE585/dDkoJiZmIjEx3kcnN5YEUEI0MVsA5SpIcn6FZzLVUF2dQ1hYP3OKLQArL48iNfU78vMTAAgPL2HZssuIizvhsQzuRqHExblukRJCCG/cBVCVlfsJCenr8qENIHI/DFkEigmyb4MTl7u+flBQPOB+ypWgoE7077+84QX3E+lELkQT8xRA2V7h2Y5lZNzKli39MZlqzHks60fBokWfcPjwUAD0+joWLryWxMQ9XsvQkFF+QgjhC1cBVFXVIbZsSSI7e77Lc0KOQ8ps0FfDyd9D9h3er99a56yTAEqIJqcFUK6DGOcAKi9vFaB1PtdYXvPB5Ze/Q2BgNQCPPfZnRo78ye1dVVUlMXGJdA4XQjQJ1wFUJgBlZVudjgWUaHM9BRVB4SjYPxOP42eio7XXb926uZhRsxWQAEoIPyoo+I60NIXKygPWNM99oNwPsy0q+j+OHXvT4fyJEz/jpZcmc++9M7n00n94LU+vXnMYP77I9w8ghGjX0tIUDhx4wKe8rjqRGwzFgNZt4ODBhzAaKwDQ1UDKkxCWA+V9Yc8CUL3M5RsSksCkSSoxMRMa9BmaS+tsFxOijTp9+mMASks3ExY2ALB/SnMOklyNsLPYs+c6ADp3/qNDenLyRpKTN1r3u3a9mxMn3j6TYgshhNXx468xYMAKr/lctUBZlosqLPwP8B9t5JwRBi2B6D1Q3Rl2LgNjuL9L3fykBUoIP3I1sVxl5T7zlvtXeJZAqrj4F4eje/eey3ffuZ5GIDp6PABxcdc0rrBCCOGFyVTr9lj9AEpVjRw4MN0hLevwk/R7HTqtA0O4FjzVxjnWW2FhQ/xb6GYiAZQQTWzHjosAbx25tdd0Bw8+aE3JyhrCE0/8l/vv38ixY32dztDptFXJVdVIz56zCQyM91+hhRACyMqa6/ZY/QDK1Rp3CZ9CwudgCoTdT0Nlopau09maoAYOfJvo6Nb5ms4TrwGUoighiqJsURRlh6IoexRFWWhOT1QUZbOiKAcVRflEURQ3K9cI0R75OurN0gJlpKRkExUVOwHIz+9Kaup3VFREc+xYf556ahX1G7d0uhDruX36LCUx8WmX127vpA4TovGqq7PcHrMPoIzGavbtu8vheKe10O8NbXvfLCgeZjum14dZt6OjxzF8uGPre1vgSwtUDTBZVdVzgGHApYqijAWeBV5WVbU/UATc5eEaQrQrBw/e5yLVOagqKPga0IKg7dvHAVBZGcHs2d9y+nRPAEJDy0hNnea0RIttbiet9Uqvd55JXABShwnRYK6mWKmvrOw363Z+/pcUFn5r3Y/eAYOe0bYPTYfTFzme62rlg7bGawClaixTHAeav1RgMrDKnP4BIB0xhDAzGstcpNaviGxPb5aRdkajnoUL/01mprb2lE5nYMGC6+nXb4fz1cwBlOXcttqPoKlJHSaEb+z7cNpal9wHUPv32yZxsq/zwo5A8lzQ1cGxayDnJudzz4YASvFlNWVFq6m3Af2A14DngU2qqvYzH+8BfK+qarKLc6cD0wHi4+NHrly50qeClZeXExER4ePHaF3aatml3P6wBFhj3l5r/vdCu+OvA4MAKC/PJyLiBusRVYUXX/wb335r64T52GN3cfnl77q514Xme8wFLI93J4G/m8swG7jkDD6Law39fl944YXbVFUd5feCNEBj67DG1l/Q2n4ufSflbl6tq9xG4Hfm7f8CQcBiwDLf3Ay0OiXYXG7nlQyCCmDE/RByCvLPh90LAZcLIUxFe24BW11Zai7DtfXS/ash33NP9ZdP0xio2iPuMEVRYoAvsPwFqJfNzblvAW8BjBo1Sp00aZIvtyQtLQ1f87Y2bbXsUu4zt3fv25w+rW1bypSWZp/jPsaM2U9Y2ADS0p5xOPdf/0p1CJ5uvfVpD8ETdO7cldOnISlpIF26TLKmZ2R8y6lTkJQ0yCHdX1rT99tXja3DGlt/Qdv8PoGUu7m1pnKbTLX8Yu6KNH78eQQERDjUafASHTvuZ+jQb0hL+9TpfH2lNst4yCkoGQx75+ImeIIhQ65mzx4tgLL//PZlaKrvi7++5w0ahaeqajGQBowFYhTb/OoJgPNS80K0O45/g43Gaqcctkk251jT1qy5mXfesQVUF1/8IXfeOc/tXcaOzbHOMxUU1Mmnsgipw4TwxHFeOiOqasRkqnLIY+vndKdDumKAwQsh8iBUdofdS8AU4vo+I0b8SqdOUwAIDu5Z72jbmRzAl1F4ncxPbSiKEorWvpeB1rZ2vTnbVOCrpiqkEG3VunXO7/nr6vIc9vfuHcNzz71n3R82bC2PP36XU6dxeyEhCfTs+SQpKd/QsePv6x2Vde/sSR0mhK9sAZSqGjhw4D7y879wk7fctqnCgJcgdgvURsOuZ6HOwwpSkZEjARg+fCMjR25xOOZu4fPWyJdQryuwVlGUncCvwA+qqn4DzAJmKIqSCcSidbwQQnixf/+dFBause736Z2K9MkAACAASURBVLOLMWO+B6BXrz0sWnQtgYHOSyTUp9MFEBvrZhlzYU/qMCF8YN8CpapGtyscZGbOdNjv9Q/o+j0Yg2HXUqjq7vk+ljnxoqPHEhQU7/JYW+C1D5SqqjuB4S7SDwNjmqJQQrRFWVkLrEu5eLN7t63zZUhIFQsXXscHHyzgssveITJSW0sqKekDDh+eRW3tySYpb3shdZgQ3pWX72Tnzkut+9ooPNfdAHJzX7Jud/keEt8HVQd750HZYC29V6+nMBpLyM1d3oSlbllt52WjEK1Ybe1pjhxZ6JBmWUTTFZPJsW+UXm/izjvn06XLUQCioyfQpcvthIc7DWwVQgi/UlWV9PTJ1NaesKbV1OR4Pa/DFhj4grZ98CEoON92LDFxAZ07u5i/4CwiAZQQfrBpU6JTWnr6RS5ygtGo43//cx7+a0+nC7ZsOaR36XIH55zj69Be6UQuhPDu5Mn3MRgKHNJ++22sx3MiDsKQBaCY4Mif4PjVznlsYzQ0oaED6NlzjnPGNkoCKCH8wGSqdEorK9vslKaq8Ne/vsrcuat57bUXMZlcv+9XFEsA5Xg8KeldOnSY5KU0bacPgRCi5VVVHfCeyU7wSUhJhYAqOHURZLmZw19RAh32e/R4nD59ljS2mK2OBFBCnKHS0i3eM5n9+98z+eqr+wFYtWoGa9bc4jJfbOwVgGOHymHDfvbpHkFBXQEICPAwDEYIIdA6jh89uszn/AFlMDQVgguhaDjsewKnSCIgoCPgGEDpdCF07eo49YEnen2kz3lbik8TaQrRXhUX/0J4eDKBgR3d5vntt3N9ulZa2vW8+eYL1v0LL1zJ7373kUOeoKCujBq1g8DAOHOKrWaKihrn030SExcSHj6I2NirfMovhDg7VVcfoa6uiMjIYW7z5Od/6fP1dLXaEi3hR6CiN+xZBGq9JbjHjy9DUbR6y/4VXqdO11vTvUlJ+Z7w8ME+l6ulSAAlhBsmUy3p6ROJihrHiBEbzuhau3adx9KlH1r3U1LWkZo6DZ2u/sSblfUmxrS1QPk6P4pOF0yXLlPPqLxCiLZv06beAEya5L4/pKfBLg5MkPQMxOyEmjjY+SwYXKyGEhBgS6z/Cs9XsbGXes/UCsgrPCHcsIyUKy/feUbXycnpz9y5q6mr06bl7dFjP4sXX0NQUA2KEkBwcA9rXssEcxa2zuT4/PQmhBC+8rVe6fMWdE4DQxjsXAY1nbX0xET3fZr0+jA/lLD1khpZCDcsAZROF+Qlp3vFxXGkpn5PaWksADExp1m27A9ERxcC0L//a4wZk2HNn5z8ucP5nTpdixBCNB3vLdvdP4een4BJD7sXQUVf27FeveZYB7306fO8w3mBge6WmTo7SAAlhBuWNaAa2wxdXR3KnDlfc/y4VtsEB1eydOkVdOuWZc2jKAHo9eHW/YCAaIdrxMe77mQuhBD+4K0FKm4d9Fuhbe9/AopHOufp2FF75RYa2tchXVEUEhOfcT7hLCEBlBBuWFqg6gdQp059xPr1cZhMBo/nP//8O2RkjDVfw8TcuTczaNCvDnksnSx79pxNly5uxgILIYSfGAxl/PJLBAUF35tT3IcBUbth0NOgqHDi/kROXeI6X+/eTxEc3IuYmIlOx0JDtTnydDrndUHbOgmghHDDaNRaoHQ6xwAqM/MRDIYCDIZCj+dfc81rREVpk9Olpr7P+PGrnfJYAqg+fZaSlPSOy+uMGrWD/v3faHD5hRCivqqqTEymCg4fng24b4EKzYGUJ0FfC8evgKJ73Y82jowczrhx2S5HK8fFXUevXnPp2/d5F2e2bTIKTwg3bC1Qjn2g9PoI6uryMRrLgM5uz09J2cCKFeNYv34Kt9ySRV6ec576M/W6EhExlIiIoQ0quxBCuGLpMqDVX+Bq4t3AQhg6CwJLoWAsHHwEugS4GHLnA50ugMTExY0tbqsmLVBCuKGqNYA2fUBh4Q/k5X0B2CZ4MxjK3J5r0aPHQW6++Tny8j61pkVGjrJu1w/OhBDC3+rqCsnKegpVNWL5s280lgNQXZ3tkFdXBSlzIPQElA6EvfNB1YNOp42oi4gY0ZxFb9UkgBLCDVU1Wbd37ryEPXu0EXF6vfYkZjSWcOzY69Y8+/eP5NixPm6v16fPc3TqdD3Dh2+0pp3JCD8hhPDFwYMPcOTIIgoL/wNo9ZrRWEZZ2TYOHZphzacYYfBiiNoPVV1h11Iwmrsude/+IMHBPUlO/qoFPkHrJK/whHBLm3zOPpAC+xaoEg4e1JZlOXasD7NmfY+iqCxZchWDBzuvg9ez5+NOab5OjimEEI1lMJQCWl2mtUJpo4y3bbO1hqNC/1cgbiPURWlzPdXZdWkKDe3LuHFHmrPYrZ60QAnhhi1wqh9AaS1QBkMJACUlHUlN/Z6Skk4UF3dm4cJ/U1vra8uSBFBCiKamBU3aA5vJZY6e/4JuX4MxCHYtgaqejsft1+UUGgmghHDLuQWqqOgn8vO1yS737bud2tpg5s79itzcAQAEBlYzb95NBAXV+nQHaYESQjQ1S6sTwK+/Jjsdj/8/6PMOqApkPAmlzlmECxJAiXanqiqbQ4ced3o1Z89orKSw8L/mPds6UocPp1q3TSaFZ575gN27xwPaXE9PPnkryckb8ZUEUEKIhlBVlays+VRU7PWYr6goze6cOsA2ObC9mG0w8DltO/N+yL+gIaVp361SEkCJdicj41Zycl6grGyrQ3px8XpOnvwHoHW6zM190XzEPtCyVRhvvbWMtLQ/WvfvuedxJk78rEFl8WUaAyGEsDAYSjhyZDHp6Y6TVhqN2txORmM1RmMFO3ZcaD1mMmkt4vXrm/BDkPwU6IyQcwMcu863MkRHa1GW/Vqd7ZEEUKId0lqULJWKRXr6BPbtmwpAZeV+a7r9MF/LpHNffXUPn3zyhDV96tRt3HLLxwDEx9/qddbdoKDu5utJC5QQwneWOsNorHBIP3r0OY4eXcbx429gNFY6HCst3WDesv3JD86DoakQUAGnJ4H+JduI4nPOWeuxDEOG/NtclsYtc3W2kABKtDuWqQMszdquuKsYKisPsHHj5bz66gpr2nnnfcX8+T/QufON5hQ9I0Zs8liGIUM+BfoSHi4TZAohGsLSN9Ox/rK8nlPVWqfgyuLUqY8A0JdDyiwIzofiobBvNkRGj7Hmi44e77EE2iLBQxg8+OPGfoizggRQot2xTF6pqu47erubn+nw4U4sWvQJJpP2FDhw4K/Mnfsn9HqjtXVKUfReZw6Pjh4HvINef/atDyWEaDqWvpuq6n4tTpOp0mV6Xt4nKHWQPB8isqCiJ+xeDKYgsA8HdLoAwsPd9yTX6roVxMZe3piPcNaQAEq0O5bgqP4rPEeqy9Tu3Q9y6aXvAdClSxZLl15BaGiluVKzBVCAxwpICCEax3XdZK/+Kzz7U5Oegw7boaYj7HoWDFHaofpr4iUkPHqmBT3rSQ9W0e5YXs/Zt0DV1RVbtwsK/kNR0RqX5+r1Jh566EESEg4watQPdOx42nzEZJ0nxRJAjR69i7S09j1KRQjhb65HD+fkaIv1Ggxl7Nz5e5d5Et+B+DVgDIFdz0B1F/ujjgFU1653Ult7kqysJ/1R6LOStECJdsfyCs9ksvUhqK7Osm4fObLIy/lw3XV/pVevfdY0VTVx6pTWH8Aykk8IIfzN0/QrAFVVBzEYCp3Su62GXv8CVQd7FkL5AMfj9VugfLlXeycBlGh3dDrnFij7ZvHSUts8TqoKP/54EyaT55ak+Pg/UVt7DHDd/0BR2vdwXyGEv3gOavLy/u2UFrtBW6YFYP9MKBzjeLxXr/m4ntPJ++vC9kwCKNHuWOZCsUxZAO6ftN59dzFPP/0xixZ9Qk1NiMs8EycaCAsb6PGeY8bs83hcCCF8YV9XVVVlecipicyAwYtAMUH2VDh5mePxgQPfJTFxIa7DAe1eUVFjz6DEZy8JoEQ75Dj30tGjz/Pbb6Odcn377V38859zAfj55xv48sv7XV7NNpeT+1aq0NDejSqpEEI4srUKVVTspK6uwG1fy5BjkDIH9DVw4lItgKovOLgH4O4VnnavDh0u8UO5zz4SQIl2p35FcfToUqc8W7b8npdeetO6f+6533L99cud8o0evdtuT36dhBBNy7G1XHHbChVYDENnQVAxFI6GAzNxesaLjp5Ahw4XWa/l4m7aERfBlZAaX7RLjj/2Op3jq7nMzHNYsOBTTCbtVV///tt46qk/otcbqS8sbJB1W2YVF0I0PccAqn79BaCrhuQnIewYlPWDPQtAdTHmPjw82Tp62H7BYed7yWhiVySAEu1O/UCntvakdfv06QRmz/6WqqpIAOLjj/DMM1cQGup6Zl/HJzOpZIQQTat+f82TJ99zzGCEQUsgei9Ux8OuZWAMc30t+7nwXK3MYHmFJ3WbazIPlGh37AOo7OzF1u3y8ihSU78jP19bpy48vJhnnrmM2NiTTtdwfV0FVQatCCGalK2SOXnyXfLzv3Q41O816LQe6iJg5zKojXV/pc6dbYuhu16ZQV7heSLfFdEO2X7ss7PnA1BXF8iCBavIykoBICCglkWLriUxca/bq0ya5BgtRUSMBGDAgL/5u8BCCGFma4FyCJ6AHv+GhC/AFAi7n4bK3u6vMmTIF3TseLF1X6dz1Uwlr/A8kQBKtCuqqnL8+JtO6W+88QLbttkqk8cfv4sRI9yvSD5w4DtOaSkpX3POOT/Srdt0a1qXLncRFNTFKa8QQjRGcXGay/TOP0Ffc9WWkQol53i+Tmys43wG4eGDSEn5jgkTbN0VOnW6wZz3ykaX92wmAZQ4a1VWHmT//ulUVWVRWPgDAOXlO1DVGqe811zzOl27Hgbgjjvmcckl//R47a5d73JKCwzsQIcOkx3SkpLe4bzzTjT2Iwgh2ilVVTl48GHKyrZz8uSH1v5K+/f/2SlvdDokLdO2M++FvMlOWRz06bPM5YLpsbF/QK+3tURFRo5g0iSViIiUxn+Qs5jXAEpRlB6KoqxVFCVDUZQ9iqI8bE5foCjKMUVR0s1fl3m7lhBNJS1N4cABx3ma9u69iRMn3mbz5j7s3KnNY1JXl+fy/J4997NixTjuvjuV2257usnLK5qH1F+iLdi//y9OczkZDIUcO/Yq27aNYN++28nOXujy3LAsSJ4HujrIuymB3Bu830+Vzpp+4UsLlAGYqarqIGAscL+iKIPNx15WVXWY+eu7JiulED44fvx1r3kMhhK3xzp2PM2f/vQsirzuP5tI/SVavRMn3vKax360sEVQPgxNhcByyJsAxx8fbO2uFBo6wCm/RUBAVKPLKmy8jsJTVfUEcMK8XaYoSgbQvakLJkRTMBpLAcjKGkJ1dRiDBv3a4GvEx9/m72KJJiL1lzib2E9hoK/QgqeQ01AyBDKehJiAQOtxT/PSde063e0x4TulIU15iqL0Bn4BkoEZwDSgFNiK9pRX5OKc6cB0gPj4+JErV6706V7l5eVERET4XLbWpK2WvW2X29LJ0b7j93TgoN3+JUA/8vK+5P77N1FaGsvcuTczfvxqF1eNBMrc3HEucJGbYw0td1v9fvte7gsvvHCbqqqjmrBIPmnO+gvaz/9va9G2y+2q/ioBrqmX++/AXSgGSJkNHbdCZQJsXwF10QDnA/8z5x0K7HRzV/cDZBpW7rb3/YaGld1T/eVzAKUoSgTwM7BEVdXPFUWJB/LRJopYDHRVVfVOT9cYNWqUunXrVp/ul5aWxqRJk3zK29q01bK35XLDhYDj1AJbt46kvPw3h7yxsYuYMuVKDh0aBkBERBEff5xIRITjq73zzjvFhg3xLu83aNBHxMf/yS/lbqvf74aUW1GUFg+gmrv+gvbz/9tatOVyu6q/amvz2LChs0PeuLhryM/7koHPQdf/QG0M/LYCqs1tqrGxV1NQ8BVRUecTGBhLQYGrh0PnKVgaW+62+P2GhpXdU/3l0yg8RVECgc+Aj1RV/RxAVdVTqqoaVa1N8W1gjE+lEcLvfKsMDIYA7rprtDV40ukMzJ//R6fgCUBRnEeoiLZJ6i/RNpmcUvLzv6T3+1rwZAyBXc/YgicAVTVYtpC5m5qe1z5QirZQzt+BDFVVX7JL72ruXwAwBdjt6nwhmp5jRaOqJjZsiKeuLt8uDZYvf51ff73UmjZz5nRGj/7B5RUVxdOvhoxgaSuk/hJtUWbmTAoKvnFK7/ot9P4HqDrYOx/KkurnsKxnp1rXuBNNx5elXM4HbgN2KYqSbk6bA9ysKMowtL8m2cBfmqSEQnhV5bBnMlU5BE8AH300m2+/vdu6f9tti7jssnprSAGhof2oqsqUyufsIfWXaOVsi/iqqhb45Oa+5JSr42YYYE4+8DAUjHO+kqXlPCioG65asIR/+TIKbz2u2wJl2K9oMevWRWM0ljJsWBrgOEtu/VXFf/jhT/z970ut+xdf/A/uuOMpl9c955yfKC3dhF4f7vbeMTFn3oFcNA+pv0RrlJ29kOzsBfTuvRjYZHfEBDiPnovYD0MWgGKCI7fAiatcXzc8fAidOl1LXNw17Nt3h8s8/fr99UyLL8xkJnLRJlmmI0hPn+SQfuLEuxw69Lh1Pz19Is89Z2tpGj78Jx5//M9u53oKDk6gc2fHmegGDHibbt3uAyAp6R8EB8vSLEKIxsvOXmD+dx7wrTW9qiqLnTv/4JA35CQMnQ36ajh5MWQ5L4Jgpap1dOkylYCAaCzPDV263MmIEVqQpigBJCQ84M+P0q758gpPiDZj/35b7VJQ0IV5877AYNCatXv12sOiRdcSGFjn9nxXr+46dbqeLl1uIzS0L5073+j/QgshBJCZ+RCFhf+x7geUwtAnIKgIikbA/sfx2DfcZLKv27SMERHDiIo6lyFDviA0NLFpCt5OSQuUOGt17HiSW25Zat4+wbJll7kcceeNoujQ6YLp0WMGOl2wv4sphBAAlJXZpsnQ1ULyXAjLgfI+sHshqIEeTkZrgbLIz/8MgJqaXAA6dbqGiAgvKwyLBpEWKNGq1dSc4NSpD+nR43Fr61BNzTGfzlUUuOmmF4iPP0L37pl06XK0kaWQDuVCiMbJzX2F2NirrK0/BkP9CXoVLCN7rWt1miBpKcTsgpo42LUMjD7M+2gfQFnU1DS23hPeSAuUaNX27r2Zw4dnUVGhzahrMtWxcWNCg65x4YWfMmDAdrfHAwM7eTxfUeTXRAjRcHV1hWRmPsKOHRdb0zZv7u/1vL5vQOefwRAOO5+FGg9VVOfON1m3Q0Jsr+hiYiYBsnBwU5K/DKLVqaw8SFqaQl7eF9bO4pYJ4kymarfnqSp8//00amsb9ppt3Lgcxo49wogR7tbFkxYoIYTvfvklgm3bRlvXrjMYbKsE1dWdqpfbMcBJWAU9VoEpAHYvgoo+nu/VvfuDjB9fzNCh/6Vnzyds10l4FACTqaLxH0R4JAGUaHXKyrYAkJf3KZYfUctTlKrWuj3vk08e47nn3uOxx36gpKSjz/fT6YIJCelJVFT92fotvx4SQAkhfGcyVVBWttVuUIpvrUBxP0Pf17XtfU9A8Qjv5yhKIAEB0XTseInDAsKWqViMRgmgmooEUKLVsTU5K3YVkPYkZzLVuDxn7dob+Nvfngdg164JfPxxqoc7+PZjn5DwkFYKj7OSCyGEa5Y56SwtUZ5E7YLBS0BR4fCf4fTFXk8BtADKlbAwbZryuLgpvl1INJgEUKIVsgVQltafI0cWk5Oz3GUAtWvX+TzzzIfW/aFDf+HOO+e6vfqoUemMH+99NF7fvi8yYUIVOp2XoS9CCOGCJYAyGkvYufOKetMM2IQdhZS5oKuDY1fBUQ9rlcfEXMR5550iOLgn4P4BLzi4OxMmVNK9u8z71FQkgBItJjd3BYWF/3VxRAugtNYnLYAqKPiGQ4cedQqgjh4dwNy5X1FXp/V76tFjH4sXX0NQkPtXfXp9OAEBUV7Lpyg69PoQ3z6MEKJdKSv7jaws1ysaWNgW94XCwm+pqjrglCeoEFJmQWAp5J8HmQ/hpdeASlBQZ+vgFk8PeHp9qCxL1YTk3YRoMZmZDwIwaZJj/wBbc7fOaQScqtoCqKKiTsye/R2lpbEAdOhwimef/QNRUUV4Yt9PQAghGmPbtjGAkd69F7gNUuovK2UyOT7Y6asgZTaEnoTSJNg7F1Sv1ZOlvrTUjVKftRRpgRKtkBZAacGTY8VkaYGqrg5lzpyvOX68LwDBwZUsXXoFXbtm+3B9qXCEEGfK0r/J6DWPhf0gGMUIgxdC5AGo6ga7loIp1Pe72x4uZdHgliIBlGhVKisPkJdnmUH3BDU1OQ7H8/I+w2jUsWTJR+zbdy4AOp2RefNuIilpq9P1XJEWKCGE/9iCJFU1kZtrW6y3qirTIWd5+S5zRuj/MsRuhrooba6nug6OV+3W7X4393NsgfKlg7poGvIKT7QKFRV7CQjowJYtA61pRUXO/aNycp7jo4/msn69bWTJAw88zPnnf+3zvSwBlF4fTVBQ/BmUWgjR3qmqibq6YqqqMqmuPkxm5kPWYzt3XuqQ98CBuwHo9U/o9i0Yg7SWpyoXcwO76xxuGaXcrdtfOHRoptRhLUhaoESr8OuvQ9i4sZtPea+44i0GDtQmvbzhhheZMuU1r+cEBsZZty0B1PjxhYwZs68RpRVCCI2qGtm581J++200BkOp1/zx/4HEd0FVIGMulA5xna9+ABUbe5XljoA2UebEiUYCA+s1XYlmIwGUaHM6djzNyy9P4p57HuOeex53madv3xfp2/cl636XLtNQlCDznhZAKYpORqgIIc6QkbKyzeZtz6/TOmyFgS9o25kPQv4E93m7d3d8hdejxwzzlm2Usiwz1bLkuy/apNDQSv74xxfR6VzP8BsePpQePR6lT59l5hRbh3TpAyWE8Bf7PkieOpSHZ8KQp0BnhKN/hGMe57dUCA1NrDdCuWGzmoumJwGUaPWOHevDxo2XN+gcy5OZrXKzzWouT21CCH+xD5rcBVDBp2DobAiohFOT4fB0b1d1VUcp5ntIANVayF8S0eJqao67PVZSEktq6vfMnfsVX3xxn9drRUaONm85DvF1NSWCEEI0nlafmExVdmnOAVRAOQxNheB8KD4H9s3C7V/ekJBE7couuxZIC1RrIwGUaDLFxesoLPw/h7Ta2jxOnvynQ9rGjd1dnl9TE8KTT35Fbu4ATCY9b775AidP9nTI06HD7wDo3PkW4uKmoNNpM5JbKiD7STlTUr4mNvYqdLqwM/1oQoiznMFQQk7Oiw4tPqqqcurUx9TUnLSmHThwr91xxz5QSi0MmQfh2VDRC3YvBjXIdrxLl2nW7Q4dLqZ/f/NKwi7+NEdGjiImZjL9+3sfNCOah0xjIJpMevoFgONM49u3j6eq6gAdO17i8VyTSeGZZz5gz57zAVAUE3Pm3EqXLkcd8nXt+heKitbQq9ccwsMHs327pVemVgEFBEQDEBjYgQ4dLqJDh4v88dGEEGe5gwcf5NSpDwkPT7HWVyUl68nI+BMJCY9Y8xUV/WDdtl+6BRMkPQsd0qEmFnY/F4IhstrhHpbRwfHxtzNo0AfU1p4CXHcz0OtDGDbsR799PnHmJIASzcqyFpSrRYHtvfXWs/z8843W/Xvvncn11weQl+eYr3Pn69m797+Ehw8GbE+AlgqoW7d7Hf4VQghfGAzaguP2r+gMBm2ZqKqqQ2iv1FSHoOnw4Ses233ehvifwBAKu5ZB/JjZZGc7rp2n10cAP5CUNNmcYgmcbK/wUlK+ITi4l78+lvAjeYUnWoSqul6VHOCLL+7jk09s0xNMmfIq11+/3Lo/cODf6d79IcLCkswpdm3i2DqNg7bQZkLCQx4X3BRCCGf1uwHY0rR+SJZt56kLun0BPVeCSQ97FkJ5P9DpbOu0jBq1A4BOnW4EAqwPfLYRwrY/zbGxlxMRkXzmH0f4nbRAiRZRXZ3lMn3DhitYseJV6/7553/J/fc/italSXsVqNMF07//Ky7Pt/VXkGcDIUTj2V6j2Xfa1oKloqK1uOowDhC7Hvqv0LYPPAZF5nEtOp3tQS8iYqhd14ZTdmdbAimpv9oCCaCE32lBjOcJ5Xbs+J1T2r59o1i8eCUmk/YUlpS0mblz/4Reb7mWZQI5Tz+2jq/whBCiobTpCJxHvVle15lMFS7Pi9oLg58GxQRZ0+Ck3Uounuut+mTEcFsgAZTwK1U18fPPjhNVGo1V6PWelxmvrIzgySdXU10dDkDXrodZuvRKQkJs/Q9MJu21n21Gcdf310gFJIRouEOHniAn53ksrUEGQ5n1mKeJMkOPQfIc0NfAicvgyO2Ox30LoOQBsC2R/yXhV3V1+U5p69Z5nzYgLKyc++9/lMDAGqKiCli27A906ODYY1xVtY7nlqkKXElIeBiA0NC+DSm2EEIAmIMnsAQz+/ffQV7e54D7ACqwGIY+AUElUDAGDjyK0zOcLwGU1qkcevWa16iyi+YlLVDCr+rqCl2mm0y11NXluTxmMXnyJ8TFHUNRVHr2POB03GjUWqN0uhC31+jS5Ta6dLmtASUWQgjPCgv/j8jIkahqrdMxXTWkzIbQ41DWH/YuANXFX1ZbAOV+KSmdLqje8i2iNZMASviVwVDgMn3fvjs4ffpfXs8fOnS922MmkzaHiqcASggh/K2m5iibNvUmJKSP4wEjDF4MUfugOl6brsDotreCFjhJ/XX2kFd4wq8sQU59roKnb7+9i9LSDj5fOyZmIgDBwQmNK5wQQjRCefl2AKqrD9sSVej/KsRtgLpI2Pks1HZ0fw3LVCqdOnlcRVi0IRJAiTNSW5vPxo09KC/fCTgvZeDO11/fzQsvvMMDD2zg+PFEr/kTEmaSmLiEc889REhIT6/5hRDCFxkZt5OV5bnPUW3tSae0Hiuh+2owBcLuJVDpYa7LwMBOdOx4Geeem8XAWpQ5ZAAAIABJREFUgX8/0yKLVkICKHFGCgu/p6Yml6NHnwM8j1Kx2Lz5UpYv19Z8yslJ4h//mO/1nH79XkCnCyA0tI/XvEII4atTpz7kyJGnG3RO5zXQ9y1QFciYAyUpnvOPGrWdgIBIQkN7O8wHJdo2CaDEGbIMu7V0jPQcQB04MJwFCz7FZNK63/Xvv42HH36gKQsohBB+E7NdW+MO4NC9kDfJ8Xhk5Cincxo2B5RoKySAEmfE0uJkmbfE0yu8U6d6MHv2t1RXa0N14+OP8MwzVxAa6npSOiGEaE3CsyB5HugMkHsd5N7gnMcyX50j9yPvRNslAZQ4I7aASasgTpx4x2W+8vJoUlO/o7CwKwDh4cUsW/YHYmOd+xYMHvxJk5RVCCE8qapyvcQUQFAepMyCgArIuwAy3axP3qPHo05pthZ6cTbxGkApitJDUZS1iqJkKIqyR1GUh83pHRVF+UFRlIPmf30fTiXOIo4tUAUFq51y1NUFMn/+Z2RnawtiBgTUsnjxFHr3znDK26XLnXTufGMTlle0J1J/iYY4ePA+l+n6ChiaCiF5UJKs9Xty16gUG3sVQ4asckiTV3hnJ19aoAzATFVVBwFjgfsVRRkMpAI/qqraH/jRvC/OYhUVeygr+80hzdYC5fpHSVXh+effYfv2i6xpTzxxJ8OHp7nMn5QkI1SEX0n9JQAwGqs5ffpTj3ksa93ZU+pgyFMQcRgqe8Cup8HkZjGExMRnCAzsgKIEOl5DWqDOSl4DKFVVT6iq+pt5uwzIALoDVwMfmLN9AFzTVIUUrcOvvyazbdtIh7T6faDq+/rrv/DDD7ZFoe6660kuvvijpiukEHak/hIWmZkPsXfvjZSWbnGbxymAUmHgC9BxG9R20OZ6MkS7v4eiKOZ/JYBqDxRV9X3aeEVRegO/AMnAUVVVY+yOFamq6tQMrijKdGA6QHx8/MiVK1f6dK/y8nIiIiJ8Lltr0lbL7r7cKnAKuNm8v9bu2GfACrS/Pw8DFzqcWVUVzuLFH7Nx45VcfvnbzJw5HcXjOr+Wa0/GfhV0x3v6Wu7Wrb2U+8ILL9ymqqrz0KRm1pz1F7Sf/9/WwnO5C4DHgSzgNWCw3TFLnbUWeAjYZT3S+13o/SEYQyB9OZQNdHXtMKDSvP0k8DtgG/CYXZ41uHvnd3Z+v1u3hpTdU/3lcwClKEoE8DOwRFXVzxVFKfalArI3atQodevWrT7dLy0tjUmTJvmUt7Vpq2W3lNtkMnDy5Ht07XoniqInN/dVMjMftuabNEmlsvIghYXfAyqZmY/QvftD9O//CmlpztGR0ahn9eq/cOWVbxEQ4PiEN25cLocOPcbp0yvp0WMWffsuA2DDhu7U1h53uKe3crc17aXciqK0eADV3PUXtJ//39bCvtyFhWsICelBWNhA8zFbvTRy5DYiIoZz5MjTdOv2FzZsiAe0Oua338ZRWroJgK5fw8CXQNXBriVQONb5nvHxt9Gv3yv873/aFOQTJ5pQFIWSkg1s336+NZ8l3Vu525K2Wm5oWNk91V8+jcJTtPbIz4CPVFX93Jx8SlGUrubjXYHTPpVGtHrHjq3gwIHpHD/+JiUlGx2CJ4vt2yeQmfkwRmOF+ZxX3U5hoNcbmTLldWvwFBY2yHosKKgrliA+IuIca/rw4evp0eMJABTFTYcDIXwg9Vf7s3PnxWzZkgTg9FCnqnWUlm4iO3s++/ZNtaYXFaVZpyDouBEGLNfSDzzqOngC0OsjCAiIsu5bgqSoqHH06fO8U7o4u/gyCk8B/g5kqKr6kt2h1YDlp28q8JX/iydaQl1dvvnfIgoL/+Myj9FYAkBW1pPWtKyseeTldef776f5fC/HvlO2SiY0NJFu3bRxwnq929U5hfBI6i9Rn8lUZ+3rZF+/7dhxIeXl24jcD0MWgWKC7NvgxBWerqbi6s+ooij07PmYc3ZxVvFlbOX5wG3ALkVR0s1pc4BlwL8VRbkLOAq4mFJMtE2212XuOoe7qjQyMv5Kauo6Dh8+hyNHBjF9eio6nS+viF3nsTy16XQSQIlGk/pLOFDVOrfLqYQch5TZoK+Gk5dA9h3erqVK61I75jWAUlV1PfZNA44ucpMu2jQtoFEUncvXclVVWU6BlcEQwIIFn3L4sPYabtWqR/nd7/5Fv347XFzf8ccpMDAOAL0+3LEU5qdEnS6kUZ9CCKm/xP+3d9/hcRTnA8e/c9Kpd9mW3G3hbssdG2OKTQg1QEgINZQE4l9oAQIJboABVyAQEiBAQiD0UEOHELCxMS644N4td1sukmV1XZnfH3u9SHfSSbqT3s/z8Gh3dnbvlZBH787OzviqqdlNUpL/yr/xZcZcTwmlUDIKttxD8N8cF/fNn8mUEtE4RfST2b2EH3fSpAjU07RsWYFPfXj88WdZseJcV9k99/wmSPIEeXm/pKhoqmv/pJMeISVlALm53n3ldnsNIAmUECJytmzx71Yy1ULhNEjZCxUFsOFB0OYAJwcxaNC/SU8f1XBF0aZIAiWCOnbsI06cWNJgvVdfncZnn93o2r/++hmcd96/gtZPTj7Jaz8uLpVu3W73q5eY2AOAXr0eCDVkIYRwWbgwhFfVbTBwFmRugJqOsHYu2FLrP6Vfv2fZuvW3OHuggq2ekJt7EVbriTCjFrFCEigRgNEohJI8ffnlNfzznzNd++ee+xLXX/9gRKKIj0+vd/oCIYSoj93ewELlGvo8Ax0XgTUV1s2Duo4NX9dkMjIs32EHvgoL/Ze2Em2HJFACALu9FngNu/1Ugg3q9rVq1UQeeeSfrv0RI74KYaJMAM3JJ6/3WxZGCCEabwHl5Zmkp48I+Yxub0O398AeD+sfhsreoZ2Xl3cVtbV76NbNf4oX0X6ENA+UaPv27fsz8A/273+KUBKooqJB3H//e1itxtssvXuv46GHfobZbAnp81JTB5Off20TIhZCCE8PsnLlyJBrd5wPff5mbG++F46HnnehVBw9e05tsAdKtG2SQAkArNZyAGy2SvbufazeujZbHPff/z6VlcZEzrm5B5g79wLS0kJ71p+dfU7TghVCiCCKixteazNzLQycY2zvmASHzw79+gMHylqewiAJlADCmyk3Ls7GPffcRFpaKcnJ5cyZcyGdOu0LdFWSkrzf2DOZkjCb610xQwghGu3AgefrPZ6yG4ZMB5MF9l8Ce68MXrdjx8v8yvLyrm5qiKKNkDFQAoBwFpUGGDZsEU89dSpHj3alb98fAtZJSurFKafs8FlKQSadE0I0H5utPOixhGMw9F4wl8PR8bDtduptkgYPfjvg+p5CgPRAiSbo2XMzo0Z95VdeUDDPseX/6yVjBoQQkeZ5Axhs2oC4KmOW8aRiODEQNk4H4vzrJSb6T7IpRCCSQLVjxppQvjONB77b+uSTX3PwYK+Qrpube5FxJeXdOhUUzGX48EXhhimEEH60trsW/9Xa5ioP1AOlrDDoQUjfBlVdYd1ssAeZnzcv76qA5UOGfMSAAS83PXDRZkgC1Y4tXJjA5s2/9irTus6v3tdfX8Fjj73ArbcuZfPm0QGvFReXhtncybFnJGW+CVSPHveSmjqg6YELIdq9DRt+zsKFxlvAnu2WXwKlod/jkLsc6jKNuZ4sWf7X69lzOgDp6WMCfl529tny5rDwImOg2innHVtx8b8YOPAlnFMXWK1lXvXWrj2NuXONWcVLS/N46aUHmTv3Qq8648YdIDGxMxZLCTZbuesavgmUEEJEytGj/3Ft2+11HtvVXvV6vgydPwNbotHzVN3V+zqdOl3DoEGvorWmQ4efBZ1HKvjC6qK9kt+IdirYOIEDB/7m2t6zpz/Tp3+AxZIIQM+eG5k27Rq/c5yJktmcQ1JST4/HgvLrJYRofoF6zgHyP4PeL4E2wcb7oHxQ8GsopRqYhFPaM+FNfiPaKav1uNe+1havryUlnZg8+VPKy3MAyM4+xNy5F5Ce7n0egFLeHZkJCcZaCLm5F0Q8biGE8KS1HZutyq88ezn0d0xpt+12ODY+8PmhTuEiPVDClzzCa2c2bLiC8vLvycgY51VeWbnRtV1Tk8y0aR9y8KAxh1NSUiVz5vyE/PzdAa/p+6guMbErp5yyh8TELhGOXgjRnh069Aq7ds0gMbG7q8xur6WiYqVXvbRtMHgGKDvsuQoO/LS+q/onUKeddjzA1C4ynYHwJil1G1dS8gXffdeV8vLV2GzVHDnyFjU1RRw+/LpXPbu9BjBmGZ8583U2bx4LgMlk4777rqR//5V+13bzH+uUlNTdlVilpAykS5dbI/MNCSHaDbvdwpIlvThw4O/U1Oxl8+brqKnZSVnZNx51arDZKlz7iYegcDLEV0PxWbDzpvA/Nz4+E7PZGGnep8+fUcoc1mTDon2QHqg2bseOe6irO8DKlSPp0OHnQetpbUVrePrpx1m82H27dvvtt3PqqR/X+xm+j/B8jRmzsd7jQggRiMVylNra3WzdOiloHbu9Bq2tAMSXw9DJkFgCpcONNe4a7iaoPzHq1u0OWTRYBCQJVDtSWvplwPLlywdTVbWRRYsu5f33f+cqv+KKR/jpT/8W8BxP8radEKK1FBVN49ChF1F1xhItqbuhshdseBh0QihXkJ4l0TjyCK+NKi5+jaVLC3wmygy8XEtVldFDNH78h1x00bMATJjwbyZNmhzSZ0kCJYSIJKu1jG+/zeX48QUN1j106EWww8C5kLUWajvA2rlgTQvts+TRnGgs6YFqozZv/hVaW0hO7uMqq2+NKDAWCb7rrpsZMmQxEya8jckU2vp48naKECKSystXY7WWsGvX/SHVL3geOs0HawqsnQO1eeF8miRQonEkgWqzjKTGudRBqJSCc855tTkCEkKIkDhvyvyXmvLX9T3o8W+wx8GGB6GyT4OnCBER0nXQRjm7pZ3zOgVy/HgH3nzzHuz20O7Aune/NyKxCSFE/Zztl7XeWh0WQZ+njO0tf4DSwCtNATB27PZ6P0uIcEkCFYNqavZw6NAr9dZxTksQLIGqrU1i2rQPee65R5k16zXq6hoebWkyhTQiUwghgtJas3//01gspUHr1NUVO+oGT6Ay1sPAmaA0FP0ais+t/3OVSgx2pKGQhQhIEqgYtHr1GWzefF1Ij+c814hylylmz36FjRuNyTTnz7+C9evd0/QOHBj4EV5ycj/X9oABL4UZtRBCwIkTy9i27Ta2bPlN0DobN/4CCH4DmLwXCqdBXB0cuBB2/9LjWHKwZ3juMZ3Z2eeSmjoEgNzcC4PUF6J+MgYqBtXVHXBsNTw+INAaUc8++ygLF17m2r/llrsYOXK+az8lZXDAa+XlXcOhQy9w4sQy8vOvJy/v2ga72IUQwpOzd9xiOdpg3UDti7nUmOvJfAKOjYVtd+HViZSc3Jfq6kCP6+wMHfo5a9eeR69e95GZOR67vRaTKVjPlBD1kwQqhmlt89rfvv1urNYy+vf/u6vMtwfqvfdu4+2373bt//znf+ayy/7iVScuLjng5ymlGD58vse+CaXksZ4QojG83/I9cWIZGzZcxujR69w1fHqgTNVQOBWSD0B5P9j4AGifWVSCTeyrtZ2cnHOZMMH9uZI8iaaQBComOQdYGglUcfFrZGVNYN++xwHo189z8kt3kvXttxfz1FNPuvZPP/09br75bnyZTIETKCGEaCr3vEtGIlNevhqL5Sj79j1Bbe0+TpxY7KrruUSLssGghyFjM1R3NqYrsAVoqpQyB/nk0KZlESJUkkDFJHcCVV29i02bful6ng/4rXMHsGnTycyc+QZaG8PeBg5cytSpvyQuzv8xoO9dWa9eM0hPPzmS34AQot1yJ1A2Ww0rV44EICfHGItUVbXZ/xQNfZ+EDkvAkmFMlGnJCXJ1n4l9s7LOIiNjHElJvSP1DQgByCDymOS+g7OxbJnRKNTWHnAd37z5Bq/6Bw/2Ytq0j6itTQGgS5cdzJp1MUlJ1QGvHxeX6fXGSq9eD5Cbe0HkvgEhRDvmHrC0Zs1Z7lJH4rNjxz1+Z/R4Hbp8BHYzrJsJ1T3qubqKp0uXm137ubkXUVAwU2YcFxEnCVQM8xwDFWw5Fa1h5szXKS01pubNyDjG3Lnnk519JOh1TaZEzjyzJrLBCiGEB601J04sce0HW9Eg70so+AdoBRunwYnC+q+rlJl+/Z6ha1fnAsDy6E40D0mgYpJxJ+WcK8WzzK+mgj/84Uby8nZhNtcwc+YldO++rf6ry52aEKLZeI+Bciop+dyvZtZK6P+Isb39Fjh6ZghXdwwi9x1rJUSkyRiomGQ0DBs3Xu4qsVgOB63dq9cmnnnmFLZvH05h4eKg9YQQork5ExvfaQyc0xs4pe6AIQ+AyQp7fwH7LyMk2dk/dn6S46skUKJ5SA9UTDIahpqaPSGfkZNTzJgxXzRQayynnVbm2svNvRiTKakxAQohRBANJzaJR4y5nuIr4fCZsOO3oV15/Pij5OVdCUCHDpcCkJ19dlOCFSIoSaBiWKBJMgG++OJatmwZGdI1Tj21mH79nnXsJREfn+E6Vlj4AWecEXiguRBCNI13AuWcUy6uAgrvhcSjcLwQNk8l6F+q3r1neq1xZzbnurazsk5nwgRNWtqwiEcuBEgCFdX27n2cEyeWYbfXepW7Fwr2n6V36dLzeeSRF7nzzoUsWdLwEgUJCZ1ISxvu2BtSb10hhAhVWdli9u17Cpst8E2Ybw+61nUoCwy5H9KKoLIHrJ8J9nrm6lUqkeTkkxx78udMtKwGf+OUUv9USh1WSq33KJuhlNqvlPrB8Z+8494Mduy4m1WrTmHhwiRKS7/yOBJ4kPeWLSN58MG3sNvjqKlJ5ZVXpmO3NzwgPCNjLCefvBH4eWQCFyKKSBvWOlavPo3t229n0aIUFi/u5CrX2u746tODrmHAI5C9GmpzYN08sGZQL+fN5LhxB4H3Ixm+EA0KJWV/CTgvQPkTWuvhjv8+jWxYwtfmzb/m8OG3KSn5gkAJ1KFDPZg69WNqatIAyMvbxcyZP8VkCm0AZWrqwIDXFaINeAlpw1qVxXKE6upd7N49C8/VETz1/gfk/Q9sSbBuDtTkN3xd5wLniYn5QAPZlhAR1mACpbVeCJS0QCyiHrW1e9i48XLWrvX/O1BRkcnkyZ9SUtIZgLS0UubNO5+cnGKvep06XeW1P3bszuYLWIgoIW1YdFi2rDdFRdOprd3vd6zLh9DzddAm2DADKvq5j/XoMdm1nZR0kms7LW0kHTpc1JwhC1EvpXXDPRRKqV7Ax1rrIY79GcANwAlgBXC31ro0yLmTgEkAeXl5o958882QAquoqCAtLS2kutEmcrFPDFKeClQCYLGYuffez1m92pjR12yu5ZFHzmH48IXAtcAw4F6Mu7538X5MN9/zojH7M5e4W1a4cU+cOHGl1np0M4bUoMa2YY1tv6D9/P8NLlj7NRWY7drL/Q6G3AfKDpvvgUNeQzcnAf2Bu4HhQBrwrePYhYB71nL5ebesWI0bwou9vvarsQlUHnAU4zWKh4HOWutfN3Sd0aNH6xUrVoQU9IIFC5gwYUJIdaNNJGLX2s433wSeXTw+Pgur9Thaw5w5/+LLL69zHZs27WrOPvsNAMaNO0BiYme++caM1lZOPfUw333nHovguSp5pOJuDRJ3ywo3bqVUNCZQYbdh4bRf0H7+/wa/TuAhAf37/4MtW24CIH0TDL8L4mph13Ww61fuep07/x/9+z9Lael81qw5i6ysCZhMqZSUfOI4/hv6938+4nG3NIm75YUTe33tV6NeW9BaF2utbdoYDfh3YExjriOC81ymJZgXX3zQK3m68capruQpJWUgiYmdHdcyEiWlTOTknN8M0QoRW6QNaz3Ot4qT9kPhVCN5Onge7LrBu17fvk85ttw3el273uxRQ8ZsitbVqARKKdXZY/dSYH2wuqJxGkqg1q0bzyuv3O/av/DC57nmmjmu/aSkXgHOMjF0qIyVFULasNZjt9dgLjMmykw4DiWjYevd+OVDJpP/Qhm5uRd6zFsnROsKZRqDN4AlQH+l1D6l1I3AI0qpdUqptRgPuu9q5jjbofoSKMWQIYu56aYpAIwZ8xl33XULnkvYOV8VBvervs4Fh5OT+0Y8WiGilbRh0UVXnmDIVEjZB+V9jEHjut5Fxbwzq6Sk3gCkpg5qthiFCEWDa+Fpra8KUPxCM8QigKqqbZSUfEF+/nVB61itpSgF11wzl169NjBixHzi4nwTrkAJmJEvjxy5jLq6Q5ELWogoJm1Yy9Fas2fPbDp3nhS4gg1SJ80mcyPU5BnTFdhSw/uMnJxzGDFiCRkZY5sesBBNIIsJR5nVq0/DYjlMcnJBSPXHj/8IgHHj9rFt2+84evQ9IPAjQKWMBMpszsZszo5QxEIIYSgrW0xR0XQOHnzR/6CGPk9D7iILljRYOwfqOhiHBg16C7M5hzVrQlu3LjPzlAhGLUTjyNz3UcZmOwHAunXey7BUVGTwwgsPU1cXeF2DxMSuFBS4Xw32fITn5HyEJ4QQzcMY8F1Ts8PvSPe3oNv7YDfD+oehqrf7mMmURHb2j0hPl14lETskgWpGVmu53zp2DVHKv1PQao3nwQff5tVXp/PHP35BeXmW1/H8fOPt65SU/gwfvshRGugRnry1IoQIjd1uxWI5HtY5gdovgE5fw0mOsd+bJ0PZcO/jmZmnAzBq1NKw4xSitUgC1Yy+/TaDVavGBzxWWbmB8vIfXPs1NXtYvnwINluFVz2t4U9/eo4VK84BYM2aCaxa9SOvOgMGuIdzOB/TefZAZWU5J7ST/91CiNBs3nwdixcHftRvs1Vx5Ij32nObNl3Pzp1/9Kub+QMMmGts7/gtHDbm/CU93Zg5ok+fJzGbs/zOc0pIyAMgLW1UuN+CEM1KxkA1s4qKlQHLv/9+CGBMZllVtYWNG6+kqmqDX71XXpnO55+75/e74YYHOPPMd4N+nlIJjq9mV9ngwe9RU7Mr4GvBQggRyOHDxpxyWttdN2ZOu3Y9wN69jzFs2NdkZZ3Jrl0PUVz8st81UnYZs4ybLLDvUth7ufuY2Zzj2Kp/MufU1EGMGrWS1NTCpnw7QkSc/EVtZd9+m4vVGniZri++uJYXX3zYtX/eeS9y3XUPufZzcy/h+PGvvM5JTx9Jjx5T6NLFPeFcfHwaaWlDIhy5EKI90NqCUoleZVar8WhvzZqzgp6XcNSY68lcAUdOg+234jWKoGPHKygp+ZysLO9rDB78nt9LMOnpI5v2TQjRDCSBamXBkqdVqyby6KPuR3OjRn3J73//f15zPRUW/sfvPKVMXoPJhRCiKex2CyaTdwIVH58TpLYhrtJInpKKoWwQbJoO+LzDkpNzjt9yUgAdO17a1JCFaBEyKCYKFRUN5v7738NmMx7D9e27kxkzLsNstrRyZEKI9kbrugClwV9IUVYYPAPSdkBVNyj6yzDsif71TKbkiMUoRGuQBCrKHD3amcmTP6Wy0hhUmZdXzgcfVJGWdqKVIxNCtEd2e6AEKggN/f4EOSugLgt2PFVI4YTFAatKAiVinSRQzSSUxYAD+fOfn+Hw4R4AJCeX8/rrSxg4UMYvCSFah9b+Pd9KBe6B6vUSdP4cbImwbjYcy1xHXFwqmZln+tX1fSwoRKyRBCqCbLYqDh58AdDh3bV5uOuum+nbdxUmk5UZMy6jsLCi4ZOEECICjh79ACj2Kgv8CM9f/ifQ62XQJth4P5QPdB8LlCwFS8KEiBWSQEXQjh13s2XLTcDKgHdtocjNPcSTT57B7NkXMWbMfzGZkgLWS0zs1oRIhRDC3/r1PwVu9ioL5WYwZxn0f9zY3nYHHDvVt4YkS6LtkQQqgtwL9FYHbXS2br2FBQvqb0ySkysZO/ZzAEymlIB1Ro1a0eg4hRAiuFKvPc+bwcrKTSxYoCgt/Z+rLG2LMWhc2WH31XDg4oY/YciQDyIVrBCtRhKoCNJae2z7J1CVlZs4cOBvXmVff305S5eeH/SacXH+CVSXLre4ZucVQohICLR+Jrh7oOz2WtdM4+Xlxg1c0iEYOgXiaqD4bCi6KbTP6tAhhCxLiCgn80A1E88lWcrKlnD8+HyKiqZ51Vmz5nTmzn0Zmy2OO++8hYsu+rvfdZwzi3sL3NAJIURjaW0NWF5Xt5/du7/g6NEPKS9f7iqPPwFD/wgJpVA6Ajb/kaBP6mS8k2iLJIGKKGcPlKKuzj0Qc/VqvwEB7N49gOnTP8BiMQZXvvvunZx77sskJHgvPuy7hAIQ9gLFQgjRkGBvDhvjoryZ6mDIdEjZCxUFsP4h0OYAJzsEvhEUIrbJI7xmcR+1tfuCHi0p6cTkyZ9SUWEs1JmdfYi5cy/wS57A/fbK4MHv0bHjZQBYLIFnLxdCiMbyTKBKS78OXtEOA2ZD1jqo7QDr5oItLXDVuLgMAPr1e5Zu3e6KZLhCtDpJoJqoru4oO3dOcTQ+7jFQJ04sCVi/ujqFqVM/5tCh3gAkJVUyZ86F5OfvDlg/JaU/YCxv4GyAlIoLWFcIIcK1d+8TVFSsBdwJ1IYNPw9a/6RnodM3YE2FtfOgtmPwaw8d+hkAiYmd6dPn8UiFLERUkEd4YSovX0Va2gjXM/1t227jyJF/k5Ex3qteXd1hv3NtNhMzZ77Bli0nA2Ay2bj//ivo33+VYz8Vu70y6GdnZIyjoOBR8vOvjdS3I4RoR2pq9mAyJZOQYGQ9Wmt27Pg9EMf48e5hB87Fgn11ewe6vw32eFj/IFQWeB/PyprI8ePzXfuJid29jg8d+l88bzSFiGXSAxWG0tIFrFw5in37nnSVOQeLG2+luBsGi+Wo17law1NPPcl337nfPvnd725j3LhPXPsNDbRUStGjxz3yBp4QolGWLu3Jd991cu27B47bPKZhCazDN3DSM8b2lj/A8VH+dXx7x333c3J+TE7OOWHHLUQ0kh6oMNTU7ASgsnKNq8z23cGLAAAgAElEQVTZAO3e/aBXXd+epLff/j3/+c9trv0rr5zHJZc86/MJiq5db8dmq+DQoRcjGLkQQviz22tc299/H3zJqIx1MGgWKA07b4LiIDlQr14PUVm53pWMyXAD0ZZJD1STBX5zxWarcm3v2dOP5557xLU/ceKb/OY3U/zOMZtz6dv3LwwY8M/IhymEED5CeaM3eQ8UTgeTBQ5cBHuuDl43M3Mcp5560KNEEijRdkkC1UTBXv31nAeqR4+tTJ58PfHxdRQWLmLy5BswmbTfbOLDhtXz5osQQkSY1vUnUAklMPReMJ+Ao+OMZVqccz0NG/aVV91u3e72O196oERbJo/wwuKe58lVEjSBKvfa//GPXyM/fxc9emwiIaGW9PSxpKd7DyJITu4d0WiFEKI+9fVAxVVD4RRIPgQnBsDG+0B75EPZ2Wd51XdOs+JJEijRlkkPVKM0nEBZLEf8ygoLF5OZaczhlJExtnlCE0KIEAVLoJQNBj0I6VuhugusmwX2ZP96qanucVOBJv2VBEq0ZZJANVGg5Q9qa5N4+unHKS/PCnjOiBFLOOmkRwEYNWpVs8YnhBDBeA4id9HQ9wnIXQaWDFg7Fyw57sPJyf045ZS9AAwfvsDjxEBvEUsCJdouSaBCVFz8Olu2uFfK3L17Fps2XYfvIHKbzcSsWa/xzjt3cfvtizl0qIfftTIyxmAyGUsbpKePaNa4hRDCYjnGihXuIQOVlZtYurSA2tq9fnV7vgpdPgFbgtHzVN3d53jPaSQldQOMF1/S00c7jvjP7yQ9UKItkwQqRJs2XeOxpygqmk5x8SuuVcmdnn32MRYt+hkAu3cPYvny87yOT5igA3Z1CyFEczl8+C0qKty93Xv2zKampoj16y/xqpf3OfT+J2gFm6bDCZ+ZDQoLPyE//zqfqxtJktb+i5xLAiXaMvlLXo+amr3Y7XUh13/33dt55x33ek+XXfY4F1/8fHOEJoQQ9bJaT1BXZ0zoq5T3+0Kei507Za+A/o8Z29tvg6On+1/TZPIfCOW+IfQfDyo3i6Itk9/uIGy2KpYu7cHWrf8XUv1vv72Ep5/+s2v/9NPf5ZZbpjb687Ozz6V375mNPl8I0b4tWdKD775zLlTn/XjNN4FK3Q6DHwCTDfZcAft/FviacXEpfmXOXibPHqgBA14iJWVw44MXIgZIAhWEcyLM4uLXqKra6nWsrOwbr/2NG8fw8MNvoLXx4xw0aAnTpv2S3NwfNfrzhw37nJ49pzX6fCFE+2azlQFQVbXN70bQc9mWxGIYOgXiq+DwRNg5yV1v4MDXvc4zmfwTKOefEc83kvPzr2fMmPVN/A6EiG6SQAVl3LFpbWH58v5eR6qrt7u29+8vYNq0j6irM7q2u3TZzqxZF5OYWEOHDpcSF5fWciELIYSP5cv7+ZVZLMZi5/EVMHQyJB6F40Nh82RcfxVMpmSSknp5nVdfDxT4j4ESoi2TBCqIYPM7eSory2HKlE85ftxYnDMj4yjz5p1PVpYx7qBLl5sCDqwUQojWpupg8H2Qugsqe8L6mWBPcB8fOvQzfJOiUHughGgPJIEKItD8Tr5eeGEWe/cavVNmcw2zZl1Mt27bvepIoyKEiDp2GDAPsn+A2hxjridruvPgMADi43P82q9Ag8idkwInJOQ3Z8RCRB1JoIBt2+5gwQLlemMFjEd3Dfntb//AmDGfoZSdadN+yZAhSxxH/s3YsUWO7YZ7oMaNO+CamE4IIcJRWbmZBQsUBw48F/I5Bf+AvK/Bmgzr5kKtV+5zOyNGfEdaWqFfD3qgR3i9ez/EqFGrSEsrbOR3IERsajCBUkr9Uyl1WCm13qMsRyn1pVJqm+NrdvOGGXlaa7Q2xjnt3/8XAL7/fojH8YZ7oFJSKpg9+yIeeeRczjzzXY8jnUhO7gVAYqJ7Ik3f8QROiYmdXRPTCSEiqy22YZ7t1/Hj8wHYuvW3IZ3b5X3o8QZoE2yYARV9fWskkpk5DgCTKcnriFJmv+spFScTAot2KZQeqJeA83zKJgNfaa37Al859qPegQPPcfjw2wAsWpTKihXe/+gtlmJstmrs9tqQeqAA4uJsjB79v6DHPZc6GD16bfhBCyGa6iXaQBtWWbmBbdvuRGvNnj1z+eYbE1ZrhVdSo7Udq7U86DVyv4W+TxnbW+6B0jGBarknv/Rcs3P48EUoFWi5FiHapwYTKK31QqDEp/gS4F+O7X8BP41wXM1i69bfsnHj5QDY7dVUVq7xq7NoUQrLlvUNmEAtWXIhH398k195fdw9S4r4+PR66wohIq+ttGFr117A/v1PUlu7hwMHngXAYjnqNUnmzp2T+fbbjIBJVMZGGDQTlB2KboBD5wf7JHeSpJSic2djXoPU1EGR+laEaBOUsxu43kpK9QI+1loPcewf11pneRwv1VoH7AJXSk0CJgHk5eWNevPNN0MKrKKigrS0SE8BMNHxdb7H9mvANQHqPgu4u8S3bBnFnXd+Q01NKtdcM4sbb5xOsJuxioqPfGI/jnFXF90JVPP8zJufxN2ywo174sSJK7XWoxuu2Xwa24Y1tv2C5vj/eyVQDLwB3A0cAF4FHgKcc9VlA6XAW8DlrjOT98OIWyGhDA6eD1v+QOC1f4HKypdJTfVcAM8KHAWie5B4e/n3FC1iNW4IL/b62q/4QIWRpLV+HngeYPTo0XrChAkhnbdgwQJCrRuqBQuMrxMmTHBtJyXdT02ABclHjBjG6tXG9qFDPZky5WNqalIB+Oqrq7n88j+RkVHqd96wYf9jzZq4iMfeEprjZ94SJO6WFatxN0Zj2y+I/M9p6dJkampg7NixrF2bSnU1DBhgZ/Nm90S/8fFgtcK4ceNZ4ninxXwchv7RSJ5KToatvydo8mQypZKa2j0m///G6u+lxN3yIhV7Y9/CK1ZKdQZwfD3c5Egi7IcfJrJgQcPP6222Ctd2dvbZfuXl5VlMnvwppaXG3Vd6egnz5p0fMHkCSE72G5EphIg+Ud2GlZR8yYIFiooKz2EGzuba7pq80ndQt3vogfFkwVQDhVMg+QCU9zUGjet6bpuzss6ISPxCtAeNTaA+BK53bF8PfBCZcCLn+PEFXvt1dUcC1jObc1zbnnOcbN9+O3V1Cdx33/vs3j3IUbeWhx/+KT16bAn6ubL6uBAxIarbsKNH/wPA8eOLALDZqrFajZs2Y2oBZwLl3YTb7UYCVVOzC2ww6GHI2Aw1ebBuDtgCzYPppeEhHUIIQ4OP8JRSbwATgA5KqX3AA8Bc4C2l1I3AHuAXzRlkU+zePZuiovsJtFI4eL+me+zYR65tpVJ49NEXWLNmgqvs3ntvYNiwRfV+nu+q50KI1hXLbVhNzY4APenuHii7vdbriNbGvtVSSt+/QIfvwJIOa+dBXW6wT1G4l66SBEqIUDX4115rfVWQQ41fKbcFFRX5L8hbU+M5aWXgBuOll+bxv/+5H+n95jeT+dGP/AeQnnTSn9iz5xEsFufq5tIDJUQ0ieU2bN++P/uVaW2nstKYEsU3gXJKfPJNcj8Eu9lYoqWqZ/DPGD36B1asGOa8elNDFqLdaJczke/f/1fXdqA7ro8/volnnnEnTz/5yXNcddW8IFfTdOrkfttFeqCEEM3LPTu4s8fJU6f/QdrM1wDYNAXKhtZ/tcREz0l8JYESIlTtMoHyVFd3yGu/pKQTTz31pGt/7NhPuPPOW11TFpx88ibS071nnzvppMdd25JACSGak+fyKhUV3pPzZq021rgD2H4zHJnodZjRo9cwcuT3XmVmcw79+v29WWIVoi1r9wmU+9GbISfnMLNn/4S0tHL69l3FAw9cQVyce/xUauoAzGb3YAKtNSaTO2mSQeRCiObkucDvwYPPu7ZTi2DIfWCywr6fwb4Ao7ri47NJTR3iV56U5HzGJz1QQoRKuksCGDlyPs88cy7JybtITq70Ox64l8kYiCk9UEKI5uX/QkzCESi8F+Ir4cjpsP0WAs71pFQcJlNigGsalWUQuRCha6c9UA03Er16baBr13iGDfvaVTZihDEzXffuf/Crn5t7ESA9UEKI5uW70HlcJQydDElHoGwwbJqG612WgQNfc9Xr1OlqEhO7oJRCqQSvazjHQWVmntassQvRlsR0ArVt2x3s3j23SdewWMw88cTTFBd39yq32U4QH59FUlIvV1lm5ikAZGWdTrdudztKjWRs0KB/M3bsTr95WYQQIpDS0q9Zvfp07HZrw5U9eD7CUxYY/ACk7YSq7rBuFtg9OphSUwe7trt0udm1feqp3kMXUlMHMGbMFnr1ui/M70KI9ium/9rv3/8XioqmeJXt2PFHSksXhHS+1vCnPz3Phx/ewi23LGPr1hFex5UyYzIlBDzX2dPkbMzi4pJITu4d5ncghGivNm26lrKyb73GYR479ilFRTPqPc/VA6Wh/2OQsxLqsmHtXLBmetf1nKncZAq87ZSS0k960IUIQ0wnUL5KSv7L3r2PsmbNxAbqfQ7Ayy/fzxdf3OAo68z335/rVc9kSvBbKsHzGHgunSCEEOHwHkpQWbmZdesuZPfuB+s9a8MGY9qUXi9C/n/BlmTMMl7Txb+u56M67+1A46CEEOFoMwlUZeUG1q49t+GKQGXlej7//HpeesndUJ1//gtcfbX340ClgidQznKt6xoZsRBCgHMA9/ffD/QrC8RiKabzR9DrFdAm2HA/lPcPXNezB927N0pedhGiqWImgaqq2s6OHZODviVitZaFfK2VK3/EY4+55z0ZPfq//P73v3XN9eRkMiXU8wjPKHeuPSWEEMFordm5cwpVVVubfK2cJdDPMUH51juhZFzwup69ToEe2wkhGi9mEqj16y9m7955VFdvb9J1du4cwgMPvIvNZjQmBQVrmDHjMhITk/zq1tcD5WyMpAdKCNGQ2tq97Nkzl7Vrzw9wNPSpA9K3wOCHQNlh9y/h4EXuY2lpw/3qe94Aeq77KYRoupjpx61vrNHixflek1sGc+RIFyZP/pTKSmOkZYcO+5g790JSU8uBzABnqBAe4UkPlBCiIc7Fev3fuNuw4RcB2hn/pCrpABROgbgaOHQOFP3a+/hJJz3hN/7T87rx8Q23kUKI0MVMD1R9LJZiqqo21lunqiqNKVM+4cgRY7qClJQTzJlzIR077nfV6dLlVp+z7Cjf53oO8ghPCBEJJ04soaxsoVeZ51QFAPFlxlxPCaVQMgq23IPfMKmsrDP8ru3ZAxUXlxqxmIUQbSSBCsXbb/+eHTuMLm6TycqMGZfRp4/3OlK+s4jb7dWu7dzcn3gdS0joBIDZ3KE5whVCtCHhzvDt2bNtqoXCaZCyFyoKYMMM0AE6xgPNQaeUmczMMx3bwQemCyHCFzOP8JyOHfuQ5cvv4ZRT9oR13jXXzObIkW588slvuPvuSZx88pdex43ZeY0fR3b2uZSWfkF1dREA48eX+N29dehwKQMGvEynTlc04bsRQrQ3CxYoevSYVm8d19hKGwycBZkboKajMdeTLS30z1LKxLBhX2CzVfsdGzHiO+LjAw1dEEKEIup7oKzWCqzWctf+wYMvAlBe/n2wUwKKj7dy992TeOKJM7ngghcD1snJMaZB6NTpSgAslqMAmM3Zfm/jKaXIz7826Ft6Qgihtaaurtij98foidqzZxb1DR7X2goa+jwDHReBNRXWzYO6jg1/Zk6O90B1kykRsznLr15m5jhSUweF+q0IIXxEfQK1eHEO336b4dp3LoRpt4f/9ptSMHz4wqDHc3J+zOmnV9Ghw8WOz/BfSFgIIUK1b9/jfPddvuvtYa3tIZ2ntY1ub0O398AeD+sfhsoQFjo444xaCgs/akrIQogQRX0C5fuWm/Otkk2brqr3vB9+OJMXX5xBuIuLx8UlEx+f5fgsma1XCNF4JSX/BXDN/+T5Fl5d3aHgJ771Nn3+ZmxuvheOjwhe1ZOxeoIsxyJES4i5MVChTAa3e/cA7rvvfSoqsjl4sIA//OFGzObQ35ZTykS/fs+RkVHPDHVCCNEA5w2f3V7rKLEFr+yQuRYGzjG2D905mMNnbwj7c0eOXE5V1aawzxNChC7qe6B8+b4p56ukJI977/2MiopsAFauPJvjxzuFcmWvvS5dJpGWVtjYMIUQwmPCXSOBamjak5TdMGQ6mCyw/2Kw3PWrRn1uRsbJ5Odf16hzhRChaVMJVHV1KlOmfExxcS8AUlIsfnM9CSFES3H3QNU4SoL3QCUcg6H3grkcjp4K234HBJiaQAgRHWLuEV4wNlscDz/8Blu3jgaMuZ7+8Y/ldO68up6zTEBogzqFECJcvo/wfCfIdIqrMmYZTyqGEwNg432ADGUSIqrFzO1Nbe0BIPBbLFrDX//6JEuWuBeGuuOOWzn77CP1XnP8+MMeezLJnBAispwJVFnZYiDwUi7KCoMehPRtUN0F1s0Gu2vZuuDtUp8+f4l0uEKIMERlAlVRsQ6YTVXVNleZ3V4FwPHjX/vVf+utu/ngA/cyLFdfPYeLL36+wc+Jj892bQ8c+HITIhZCCLetW28DPnONgXIu1eK3dqaGfo9D7nKoy4S1j4DF3SzVO3t4Sko/13Z+/q+D1hNCNI+oTKCM13u/pK6uuMG68+f/gmeffcy1f9ZZb3DjjcYsv56Nz5gxW/3O9Vz6IDf3wiZELIQQbkeOvANsDLoYuVPPl6HzZ2BLhPWzobqr93GTKRmAbt3urPc6Awa80JRwhRCNEJVjoNzzmNQ/Pqm6OoW//vWvrv2hQ7/h3ntvwGRyT/40atQqKip+cDVEvgoKHiUra0JTQxZCCBejDdPUd4+a/xn0fgm0CTZOhxMBJgXPz/8VtbX76NHjXvbt+7Pf8eHDF1FR8UPE4hZChC4qEyhnoxNswKVTcnIVjz12NpMnf0pSUiUPP3wpCQneM5Snp48gPX0EtbWBJ63r0eOeyIQshBAORu+2LeikltnLod+fjO1tt8Gx0wJfx2Qy07v3Q8E+hays08jKCnKyEKJZRWUC5Wx0amp2Nli3oGA9zzwzFqs1gYyM0qD14uIC90AJIUSk2WxVwFqUGuB3LG0bDJ4BJhvsuRIOXNri4QkhIiAqx0A5xyZt2XJTSPU7dDhIfv7ueuvEx2dSWPhJk2MTQoiGWK0lwAEsFu+busRDUDgZ4quh+CzY+ZvQrzlmzGa6d/+ja7+h8VVCiOYVlQlUsAlQbDYTjz/+N7ZtG17v2QkJ+QHLc3MvIC4uHYDevWc1LUQhhGhAcfG/XNvx5TB0MiSWwPFhxhp3gVrg7OxzA14rJaU/OTnnuPazss6MdLhCiDBEZQKlgsy++8wzj/PRR7/ljjsWsmzZeUHP79jxcgBSUvxHZZpMSY46l0UgUiGEaJiqM5ZoSd0Nlb1g/UzQCcFqGy/BBJqaIC4uE4DU1KFB20khRMuIyn+BgQZevvPOHbz33h0AVFens3r1xKDnd+58I6efXkVKSl+/Y84ESqmgrZcQQkSOHQbOhay1UNsB1s4Fa1p9J2jOOKOG/v3/7nckLs440b04sRCitURlAuX7CG/hwkt55pnHXftnnvk2kyZNBqBfP/9GRqn4oIPGk5P7OupE6bcuhGhTCp6HTvPBmgLr5kBtnvtYnz5PBjhDYzIlBmyj4uONIQiJiZ2bKVohRKiiMovwbDg2bhzLrFmvobVRNnjwd0yZcp1rrqf8/GsDnB98EanBg99i4MBXSUrqEeGohRDCW9f3oMe/wR4HGx6Eij7exzMyxvqdE2i5F6fExK4MHPg6gwa9FelQhRBhiuppDPbvP4mpUz+irs7oTeradRuzZl1MYmKNR23/HFCp4N+W2ZxLXt41EY1XCCF8dVgEfZ4ytrfcA6WjA9Xyb78aejyXl3dV04MTQjRZk3qglFK7lFLrlFI/KKVWRCooMFFWlsvkyZ9SVtYRgMzMI8ybdz6Zmcfo3HmSRwzhJVBCCOHUXG1YxnoYOBOUhqJfQbHHOy99+vjPKO5JxjcJERsi8QhvotZ6uNY64P1VY9TWxjN9+n/Yt89YLDMhoZpZsy6ma9cddO9+D/37P+dR2/0tmM0dHVvBH+EJIYSPyLZhW7dSOA3i6uDAhbDbZ5RBt253kJ4+BvBebWHIkA8cZd6rKQgholNUdtW8/nom69c7B3vbmTr1lwwevJSEhK4UFDziVddzwWDnenf1jSEQQohmVV2N3QzHxsK2uwB3E8X48SWAZ8+5e73PlJT+Ron0QAkRE5TWuuFawU5WqggoxZi45Dmt9fMB6kwCJgHk5eWNevPNNxu8rtYHeeWVjbz44sPcfPPvufzyJxxHRgGPObad0xjM99g+B/gv8C6Q07hvKgIqKipIS6v3PeWoJHG3rPYS98SJE1dGsoc6khpqwxrTfgEkFk/EmgE2v5eB5zu+3gZsAP4C/M5R9j5wKXA2MC3s7yVS2svvZbSQuFteOLHX1341NYHqorU+oJTqBHwJ3K61Xhis/ujRo/WKFQ0PM6ip2cPSpT3ZuHEMAwcux9nJlJV1FsOHfwXAggVG4YQJ2rV9xhk1VFZuIj29/pnKm9uCBQuYMGFCq8bQGBJ3y2ovcSulojmBCrkNC7X9Anf75GvCBKO9Xb36dMrKvmX48AX88MME17GKijUkJ/dr1bU728vvZbSQuFteOLHX1341aQyU1vqA4+thjNunMU25npsR1qBBRvLUrdtdjnJ78FMAkymx1ZMnIUTsaL42rCFxjs/3btPS0obJwudCxIhGJ1BKqVSlVLpzG+P52fpIBOU7j1NKykDAe8ClL/cAciGEaFhztmGeEhK6+JWlp48AwGzuEOmPE0K0kKYMIs8D3ncM4o4HXtdafx6JoHynJsjN/QkA+fm/cpWdcsou193b0KFfBFz3Tggh6tFsbZinoUM/Z/36n3pNr1JQ8AgdO15GWlohY8fuoKZmT6Q/VgjRzBqdQGmtdwLDIhiLB3cC1anTNSQmdnaNHXBKSurp2vZcoVwIIULRvG2YW2rqYE45ZYdXmclkJjNzPADJyQUkJxc0dxhCiAiLyqVcPN/7lUkxhRCxTNbdFKJtivp/2SaTubVDEEIIIYTwEqUJlPtxncmU0opxCCGEEEL4i8oEKj4+27VtMiW1YiRCCBG+vLxrG64khIhpUZlAmUzxwPWObUmghBCxpaBgXmuHIIRoZlGZQBmM9aAkgRJCxBp5+UWIti+KEyhjRXJJoIQQsUYSKCHavihOoCyAJFBCiNijlLw9LERbF8UJlPRACSFik/RACdH2SQIlhBARJvPXCdH2RXECZaxzZzLJyuRCiFgTxU2rECIiorif+Ta6dBlEbu4FrR2IEEKExVig+HpGjry1tUMRQjSTKE6gOtCv3zOtHYQQQjTSDWRknNzaQQghmon0MwshhBBChEkSKCGEEEKIMEkCJYQQQggRJkmghBBCCCHCJAmUEEIIIUSYJIESQgghhAiTJFBCCCGEEGGSBEoIIYQQIkySQAkhhBBChEkSKCGEEEKIMEkCJYQQQggRJkmghBBCCCHCJAmUEEIIIUSYlNa65T5MqSPA7hCrdwCONmM4zSlWY5e4W1Z7ibun1rpjcwXTUsJsv6D9/P+NFhJ3y4rVuCG82IO2Xy2aQIVDKbVCaz26teNojFiNXeJuWRJ32xarPyeJu2VJ3C0vUrHLIzwhhBBCiDBJAiWEEEIIEaZoTqCeb+0AmiBWY5e4W5bE3bbF6s9J4m5ZEnfLi0jsUTsGSgghhBAiWkVzD5QQQgghRFSKygRKKXWeUmqLUmq7Umpya8cTCqVUd6XUfKXUJqXUBqXUHa0dUziUUnFKqdVKqY9bO5ZwKKWylFLvKKU2O37241o7plAope5y/J6sV0q9oZRKau2YAlFK/VMpdVgptd6jLEcp9aVSapvja3ZrxhhtYrH9gthuw6T9alnSfhmiLoFSSsUBTwPnA4OAq5RSg1o3qpBYgbu11gOBU4BbYyRupzuATa0dRCM8CXyutR4ADCMGvgelVFfgd8BorfUQIA64snWjCuol4DyfssnAV1rrvsBXjn1BTLdfENttmLRfLUTaL7eoS6CAMcB2rfVOrXUd8CZwSSvH1CCt9UGt9SrHdjnGP4SurRtVaJRS3YALgX+0dizhUEplAGcALwBoreu01sdbN6qQxQPJSql4IAU40MrxBKS1XgiU+BRfAvzLsf0v4KctGlR0i8n2C2K3DZP2q1VI+0V0JlBdgb0e+/uIgX/EnpRSvYARwLLWjSRkfwb+CNhbO5AwFQBHgBcd3ff/UEqltnZQDdFa7wceA/YAB4EyrfV/WzeqsORprQ+C8UcX6NTK8USTmG+/IObaMGm/WpC0X27RmECpAGUx86qgUioNeBe4U2t9orXjaYhS6ifAYa31ytaOpRHigZHA37TWI4BKYuBxkuOZ+yVAb6ALkKqU+mXrRiUiJKbbL4itNkzar5Yn7ZdbNCZQ+4DuHvvdiNLuQV9KKTNGw/Oa1vq91o4nROOBi5VSuzAeN5yllHq1dUMK2T5gn9baeZf8DkaDFO3OBoq01ke01hbgPeDUVo4pHMVKqc4Ajq+HWzmeaBKz7RfEZBsm7VfLk/bLIRoTqO+Bvkqp3kqpBIzBaR+2ckwNUkopjGfZm7TWj7d2PKHSWk/RWnfTWvfC+Fl/rbWOibsJrfUhYK9Sqr+j6EfAxlYMKVR7gFOUUimO35sfEQODRz18CFzv2L4e+KAVY4k2Mdl+QWy2YdJ+tQppvxziIxJOBGmtrUqp24AvMEb3/1NrvaGVwwrFeOBaYJ1S6gdH2VSt9aetGFN7cDvwmuOP1U7gV60cT4O01suUUu8AqzDefFpNlM7qq5R6A5gAdFBK7QMeAOYCbymlbsRoTH/RehFGlxhuv0DasNYg7Vczau72S2YiF0IIIYQIUzQ+whNCCCGEiGqSQAkhhBBChEkSKCGEEEKIMEkCJYQQQggRJkmghBBCCBejngMAAAAiSURBVCHCJAmUEEIIIUSYJIESQgghhAiTJFBCCCGEEGH6f6lZsut28l+TAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1,2, figsize=(10, 6))\n", + "axes[0].plot(t, y_noise, label='noise', color='y')\n", + "axes[0].plot(t, y, ls='dashed', lw=3, color='b', label='original')\n", + "axes[0].legend()\n", + "axes[0].grid()\n", + "axes[1].plot(t, y_noise, label='noise', color='y')\n", + "axes[1].plot(t, f1(t), lw=2, color='r', label='polyfit')\n", + "axes[1].legend()\n", + "axes[1].grid()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "첫 번째 그래프에는 노이즈 선 그래프를 그리고 노이즈가 없는 그래프를 데이터를 전달받아 그린다\n", + "\n", + "두 번째 그래프는 노이즈 데이터를 가지고 그래프를 그린 후에 poly1d 객체에 입력값을 넣어서 이 다항식의 모든 해를 구해서 그래프를 그린다\n", + " \n", + "\n", + "이 두 개의 그래프가 동일한 것을 알 수 있다" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-1-2-1 연립 방정식 풀기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " \n", + "### 3 * x0 + x1 = 9 \n", + "### x0 + 2 * x1 = 8" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "두 개의 방정식 중에 계수들을 하나의 행렬로 정의한다\n", + "\n", + "그리고 값을 별도의 배열로 정의한다\n", + "\n", + "두 개의 미지수를 구하려면 넘파이 내의 linalg 모듈에 있는 solve 함수를 실행해서 해를 구한다\n", + " \n", + " 이 해가 맞는지 행렬곱으로 행렬과 해를 곱한 후에 \n", + " \n", + " 값을 표시한 변수 b와 같은지 확인하면 동일한 결과인 것을 알 수 있다" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([[3,1], [1,2]])\n", + "b = np.array([9,8])" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.linalg.solve(a, b)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2., 3.])" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(np.dot(a, x), b)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "역행렬을 구해서 연립방정식을 풀어보기" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "A = np.array( [[1,0,0],[1,1,1],[6,7,0]])" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "b =np.array([0,24,0])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "방정식의 계수에 행렬에 역행렬을 구한다" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "A_1 = np.linalg.inv(A)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.00000000e+00, 0.00000000e+00, -3.70074342e-17],\n", + " [-8.57142857e-01, -0.00000000e+00, 1.42857143e-01],\n", + " [-1.42857143e-01, 1.00000000e+00, -1.42857143e-01]])" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A_1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "이 역행과 변수 b의 벡터를 행렬곱으로 계산하면 방정식의 해가 나온다\n", + "\n", + "동일한 값인지 allclose로 확인한다" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.dot(A_1, b) " + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0., 0., 24.])" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(np.dot(A_1, b), x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "계수를 가진 행렬과 행렬곱을 해도 동일한 결과가 나온다" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0., -0., 24.])" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.solve(A, b)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(np.dot(A_1, b), x)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-1-2-2 lstsq 함수로 연립 방정식 풀기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### lstsq 최소자승 해 풀기\n", + "\n", + "lstsq 명령은 행렬 𝐴\n", + " 와 𝑏 모두 인수로 받고 뒤에서 설명할 최소자승문제(least square problem)의 답 x, 잔차제곱합(residual sum of squares) resid, 랭크(rank) rank, 특잇값(singular value) s를 반환한다. 미지수와 방정식의 개수가 같고 행렬 𝐴의 역행렬이 존재하면 최소자승문제의 답과 선형 연립방정식의 답이 같으므로 lstsq 명령으로 선형 연립방정식을 풀 수도 있다. 최소자승문제, 랭크, 특잇값에 대해서는 뒤에서 자세히 설명할 것이다.\n", + "\n", + "\n", + "lstsq 명령을 사용하는 것이 inv 명령을 사용하는 것보다 수치오차가 적고 코드도 간단하므로 선형 연립방정식의 해를 구할 때도 lstsq 명령을 사용하는 것을 권장한다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Q3. lstsq 함수란?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "위에서 정의된 A 행렬과 b 벡터를 가지고 lstsq 함수로 연립방정식의 해를 구한다\n", + "\n", + "이 함수의 처리결과는 최소자승 문제의 답과 같은 결과이다\n", + "\n", + "이 함수는 세 가지 결과(잔차제곱합, 랭크, 특이값)를 추가해서 반환한다\n", + "\n", + "\n", + "해의 값을 행렬 A에 행렬곱으로 계산한 후에 변수 b에 저장한 값과 동일한 것을 확인한다" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.matrix_rank(A)" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "x, resid, rank, singulr = np.linalg.lstsq(A,b, rcond=-1)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-1.52752173e-15, 3.33066907e-16, 2.40000000e+01])" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(np.dot(A, x), b)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "잔차는 e = Ax - b 의 제곱은 선형대수의 크기를 구하는 norm 함수로 계산할 수 있다\n", + "\n", + "계산된 결과가 0인지 확인한다\n", + "\n", + "실제 잔차가 0이라서 아무런 배열을 만들지 않은 것을 알 수 있다" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### resid는 잔차벡터의 𝑒=𝐴𝑥−𝑏 의 제곱합, 즉 놈의 제곱이다" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "9.97593891563694e-15" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.linalg.norm(A @ x - b)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(np.linalg.norm(A @ x - b) , 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([], dtype=float64)" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "resid" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "특이값이 같은지 확인하려면 특이값 분해 결과를 통해 동일한 것을 알 수 있다" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 특이값분해(singular value decomposition;svd)\n" + ] + }, + { + "attachments": { + "image.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![image.png](attachment:image.png)\n", + "\n", + "\n", + "https://blog.naver.com/cjh226/220861349129\n", + "\n", + "https://darkpgmr.tistory.com/106" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [], + "source": [ + "u, s_, vh = np.linalg.svd(A, full_matrices=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([9.3509151 , 1. , 0.74858984])" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "s_" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([9.3509151 , 1. , 0.74858984])" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "singulr" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-1 -1 원소간의 차이를 구하기" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([1, 2, 4, 7, 10])" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 2, 4, 7, 10])" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1차원 배열을 만들고\n", + "\n", + "차분을 구하는 함수 diff호 계산하면 원소들 사이의 차분을 구해서 하나의 원소가 작은 4개의 원소 배열을 반환한다" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 3])" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.diff(x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "차분 함수 diff로 계산하는 방식을 확인하면 배열의 원소들 간의 차이를 구하는 것을 알 수 있다" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1\n", + "2\n", + "3\n", + "3\n" + ] + } + ], + "source": [ + "for i in range(len(x)-1) :\n", + " print(x[i+1] - x[i])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "이 차분함수에 매개변수 n=2를 지정하면 차분을 구한 배열을 가지고 다시 차분을 만든다" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 0])" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.diff(x, n=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.diff(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 0])" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.diff(c)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-1-2 차분으로 미분하기 " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "입력 데이터를 배열로 만들어서 차분을 구한다" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([1,2,3,4,5,6])" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [], + "source": [ + "dx = np.diff(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 1, 1, 1])" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dx" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "출력 데이터를 배열로 만들어서 차분을 구한다" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.array([2,4,6,8,10,12])" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [], + "source": [ + "dy = np.diff(y)" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2, 2, 2, 2, 2])" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dy" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "미분의 값을 보관하는 배열을 만들고\n", + "\n", + "이 배열의 형상은 6개의 0인 원소를 가진다" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [], + "source": [ + "dydx = np.zeros(y.shape,np.float)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "두 개의 차분을 나누고\n", + "\n", + "5개의 원소만 값을 구할 수 있어서 마지막 원소에는 값이 들어가지 않는다\n", + "\n", + "마지막 원소에도 차분의 값을 넣는다\n", + "\n", + "미분한 결과도 총 6개의 원소의 배열이 들어갔다" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [], + "source": [ + "dydx[:-1] = dy/dx" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2., 2., 2., 2., 2., 0.])" + ] + }, + "execution_count": 87, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dydx" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [], + "source": [ + "dydx[-1] = (y[-1] - y[-2])/(x[-1] - x[-2])" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2., 2., 2., 2., 2., 2.])" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dydx" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "gradient 함수로 출력 데이터의 미분을 구해보자\n", + "\n", + "위에서 차분을 사용해서 구한 미분 값과 동일하다" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2., 2., 2., 2., 2., 2.])" + ] + }, + "execution_count": 90, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.gradient(y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-1-3 차분으로 sin 함수 미분하기 " + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "그래프 그리는 matplotlib 모듈 import" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.linspace(0, 2*np.pi, 100)\n", + "y = np.sin(x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "입력데이터를 2파이까지의 값을 가지는 배열을 만든다\n", + "\n", + "출력 데이터는 sin 함수에 입력 데이터로 변환한 값을 가진 배열이다" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [], + "source": [ + "dy = np.zeros(y.shape,np.float)" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [], + "source": [ + "dy[: -1] = np.diff(y)/np.diff(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [], + "source": [ + "dy[-1] = (y[-1] - y[-2])/(x[-1] - x[-2])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "기존 sin 함수와 차분으로 미분한 결과를 그래프로 그리기" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 96, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x,y)\n", + "plt.plot(x,dy)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "결과 확인을 위해 sin 함수의 미분은 cos 함수의 그래프 그리기" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x,y)\n", + "plt.plot(x,np.cos(x))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "결과가 동일한 것을 확인\n", + "\n", + "차분을 사용해서 sin 함수의 미분도 가능한 것을 확인" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 중앙 차분 \n", + "\n", + "https://en.wikipedia.org/wiki/Finite_difference_coefficient" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-2-1 다항식 미분 알아보기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "3개의 원소를 가진 배열을 하나 만들고 이 배열을 ploy1d 클래스의 인자로 전달해서 다항식 객체를 하나 만든다\n", + "\n", + "이 객체를 print 함수로 출력하면 이차 함수가 만들어진 것을 확인할 수 있다" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,-2,1])" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [], + "source": [ + "p = np.poly1d(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 2\n", + "1 x - 2 x + 1\n" + ] + } + ], + "source": [ + "print(p)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "다항식 객체를 미분할 때는 polyder 함수를 사용\n", + "\n", + "배열의 원소 2와 -2" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [], + "source": [ + "d = np.polyder(p)" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([ 2, -2])" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "18" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d(10)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 추가 모듈 설치\n", + "\n", + " pip install autograd\n", + " \n", + " \n", + " https://github.com/HIPS/autograd" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "18.0\n" + ] + } + ], + "source": [ + "import autograd.numpy as np\n", + "from autograd import grad\n", + "\n", + "def fct(x):\n", + " y = x**2 - 2*x + 1\n", + " return y\n", + "\n", + "grad_fct = grad(fct)\n", + "print(grad_fct(10.))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "미분을 구하는 모듈 추가 설치 (pip install autograd)" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [], + "source": [ + "d_ = np.polyder(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \n", + "2 x - 2\n" + ] + } + ], + "source": [ + "print(np.poly1d(d_))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "미분은 직접 배열을 넣어서 처리할수도 있음" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([2])" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.polyder(d)" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([2])" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d.deriv()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "상수 2만 남는 것을 확인 할 수 있음\n", + "\n", + "다항식 객체에 deriv 메소드로 미분을 처리할 수도 있음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-2-2 중앙 차분으로 미분 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [], + "source": [ + "x= 10" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [], + "source": [ + "def f(x):\n", + " return x**2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "하나의 변수와 변수를 제곱하는 함수를 정의" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "수치 미분을 처리하는 함수를 정의하고, 매개 변수는 함수와 입력 데이터를 받는다 (변화량은 작은 값으로 지정)\n", + "\n", + "중앙차분은 첫 번째 함수에 인자로는 입력데이터와 변화량을 더하고 두 번째 함수에는 입력데이터에 변화를 뺀 후에 함수의 실행결과를 뺄셈으로 처리한다\n", + "\n", + "분모인 변화량은 2를 곱해서 전체의 변화율을 계산한다" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [], + "source": [ + "def numerical_differentiation(f, x): # 수치미분\n", + " delta_x = 1e-7 # 0.0000001\n", + " return (f(x+delta_x) - f(x-delta_x)) / (delta_x*2) # 중앙 차분 " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "중앙차분으로 미분을 하는 함수의 인자로 함수 f와 입력값 x를 전달해서 미분 값을 계산한다" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [], + "source": [ + "nd = numerical_differentiation(f, x)" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "19.99999987845058" + ] + }, + "execution_count": 113, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nd" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "위 함수로 다항식으로 표시하면 변수의 제곱을 표시하는 수식이 아래처럼 만들어진다\n", + "### y = x2(제곱)" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,0,0])" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": {}, + "outputs": [], + "source": [ + "p = np.poly1d(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([1, 0, 0])" + ] + }, + "execution_count": 116, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "다항식을 미분하면 2x가 만들어진다\n", + "\n", + "이 다항식에 10을 입력 값으로 넣으면 20이 나옴" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "metadata": {}, + "outputs": [], + "source": [ + "s = np.polyder(p)" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([2, 0])" + ] + }, + "execution_count": 118, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "s" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "20" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "s(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 120, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(nd, s(10))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "중앙차분 함수로 구한 미분 값과 다항식으로 구한 미분 값이 같은지 allclose 함수로 확인하면 같은 값이라는 것을 확인할 수 있음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-2-3 gradient 알아보기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 기울기 = (y의 변화) / (x의 변화)\n", + "\n", + "1차원일 경우에는 첫 번째와 마지막은 인접 값을 빼고 1로 나누고, 중간에는 2로 나눈다" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [], + "source": [ + "f = np.array([ 1, 2, 4, 10, 13, 20])" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[1, 1.5, 4.0, 4.5, 5.0, 7]" + ] + }, + "execution_count": 122, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "[(f[1]-f[0]), \n", + " ((f[1]-f[0])+(f[2] -f[1]))/2, \n", + " ((f[2]-f[1])+(f[3] -f[2]))/2 , \n", + " ((f[3]-f[2])+(f[4] -f[3]))/2, \n", + " ((f[4]-f[3])+(f[5] -f[4]))/2, \n", + " (f[5] -f[4])] " + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1. , 1.5, 4. , 4.5, 5. , 7. ])" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.gradient(f)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "두 번째 인자가 2로 지정되면 중앙 차분으로 2를 곱한 값으로 나눈다" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[0.5, 0.75, 2.0, 2.25, 2.5, 3.5]" + ] + }, + "execution_count": 124, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "[(f[1]-f[0])/2, \n", + " ((f[1]-f[0])+(f[2] -f[1]))/4, \n", + " ((f[2]-f[1])+(f[3] -f[2]))/4 , \n", + " ((f[3]-f[2])+(f[4] -f[3]))/4, \n", + " ((f[4]-f[3])+(f[5] -f[4]))/4, \n", + " (f[5] -f[4])/2] " + ] + }, + { + "cell_type": "code", + "execution_count": 125, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.5 , 0.75, 2. , 2.25, 2.5 , 3.5 ])" + ] + }, + "execution_count": 125, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.gradient(f, 2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "여러 개의 실수를 원소로 하는 배열을 만든다" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.linspace(0,10)" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0. , 0.20408163, 0.40816327, 0.6122449 , 0.81632653,\n", + " 1.02040816, 1.2244898 , 1.42857143, 1.63265306, 1.83673469,\n", + " 2.04081633, 2.24489796, 2.44897959, 2.65306122, 2.85714286,\n", + " 3.06122449, 3.26530612, 3.46938776, 3.67346939, 3.87755102,\n", + " 4.08163265, 4.28571429, 4.48979592, 4.69387755, 4.89795918,\n", + " 5.10204082, 5.30612245, 5.51020408, 5.71428571, 5.91836735,\n", + " 6.12244898, 6.32653061, 6.53061224, 6.73469388, 6.93877551,\n", + " 7.14285714, 7.34693878, 7.55102041, 7.75510204, 7.95918367,\n", + " 8.16326531, 8.36734694, 8.57142857, 8.7755102 , 8.97959184,\n", + " 9.18367347, 9.3877551 , 9.59183673, 9.79591837, 10. ])" + ] + }, + "execution_count": 127, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(50,)" + ] + }, + "execution_count": 128, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "결과 값은 x **2 + 1이므로 이 값을 계산한 배열을 만든다" + ] + }, + { + "cell_type": "code", + "execution_count": 129, + "metadata": {}, + "outputs": [], + "source": [ + "y = (x**2) +1" + ] + }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(50,)" + ] + }, + "execution_count": 130, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 131, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1. , 1.04164931, 1.16659725, 1.37484382,\n", + " 1.666389 , 2.04123282, 2.49937526, 3.04081633,\n", + " 3.66555602, 4.37359434, 5.16493128, 6.03956685,\n", + " 6.99750104, 8.03873386, 9.16326531, 10.37109538,\n", + " 11.66222407, 13.0366514 , 14.49437734, 16.03540192,\n", + " 17.65972511, 19.36734694, 21.15826739, 23.03248646,\n", + " 24.99000416, 27.03082049, 29.15493544, 31.36234902,\n", + " 33.65306122, 36.02707205, 38.48438151, 41.02498959,\n", + " 43.64889629, 46.35610162, 49.14660558, 52.02040816,\n", + " 54.97750937, 58.0179092 , 61.14160766, 64.34860475,\n", + " 67.63890046, 71.01249479, 74.46938776, 78.00957934,\n", + " 81.63306955, 85.33985839, 89.12994586, 93.00333195,\n", + " 96.96001666, 101. ])" + ] + }, + "execution_count": 131, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "기울기를 구하는 gradient 함수에 함수의 처리결과와 순간변화율을 전달해서 미분을 구하면 내부의 원소들이 기울기가 나온다" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": {}, + "outputs": [], + "source": [ + "dydx = np.gradient(y)" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.04164931, 0.08329863, 0.16659725, 0.24989588, 0.3331945 ,\n", + " 0.41649313, 0.49979175, 0.58309038, 0.666389 , 0.74968763,\n", + " 0.83298626, 0.91628488, 0.99958351, 1.08288213, 1.16618076,\n", + " 1.24947938, 1.33277801, 1.41607663, 1.49937526, 1.58267389,\n", + " 1.66597251, 1.74927114, 1.83256976, 1.91586839, 1.99916701,\n", + " 2.08246564, 2.16576426, 2.24906289, 2.33236152, 2.41566014,\n", + " 2.49895877, 2.58225739, 2.66555602, 2.74885464, 2.83215327,\n", + " 2.9154519 , 2.99875052, 3.08204915, 3.16534777, 3.2486464 ,\n", + " 3.33194502, 3.41524365, 3.49854227, 3.5818409 , 3.66513953,\n", + " 3.74843815, 3.83173678, 3.9150354 , 3.99833403, 4.03998334])" + ] + }, + "execution_count": 133, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dydx" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "중앙 차분으로 처리하면 결과도 나온다" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.02082466, 0.04164931, 0.08329863, 0.12494794, 0.16659725,\n", + " 0.20824656, 0.24989588, 0.29154519, 0.3331945 , 0.37484382,\n", + " 0.41649313, 0.45814244, 0.49979175, 0.54144107, 0.58309038,\n", + " 0.62473969, 0.666389 , 0.70803832, 0.74968763, 0.79133694,\n", + " 0.83298626, 0.87463557, 0.91628488, 0.95793419, 0.99958351,\n", + " 1.04123282, 1.08288213, 1.12453145, 1.16618076, 1.20783007,\n", + " 1.24947938, 1.2911287 , 1.33277801, 1.37442732, 1.41607663,\n", + " 1.45772595, 1.49937526, 1.54102457, 1.58267389, 1.6243232 ,\n", + " 1.66597251, 1.70762182, 1.74927114, 1.79092045, 1.83256976,\n", + " 1.87421908, 1.91586839, 1.9575177 , 1.99916701, 2.01999167])" + ] + }, + "execution_count": 134, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.gradient(y,2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 최소 변화량을 제공해서 미분 구하기" + ] + }, + { + "cell_type": "code", + "execution_count": 135, + "metadata": {}, + "outputs": [], + "source": [ + "dx = x[1]-x[0]\n", + "dydx = np.gradient(y, dx)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "x에 대한 변화량을 넣고 미분을 구할 수 있다" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.20408163, 0.40816327, 0.81632653, 1.2244898 , 1.63265306,\n", + " 2.04081633, 2.44897959, 2.85714286, 3.26530612, 3.67346939,\n", + " 4.08163265, 4.48979592, 4.89795918, 5.30612245, 5.71428571,\n", + " 6.12244898, 6.53061224, 6.93877551, 7.34693878, 7.75510204,\n", + " 8.16326531, 8.57142857, 8.97959184, 9.3877551 , 9.79591837,\n", + " 10.20408163, 10.6122449 , 11.02040816, 11.42857143, 11.83673469,\n", + " 12.24489796, 12.65306122, 13.06122449, 13.46938776, 13.87755102,\n", + " 14.28571429, 14.69387755, 15.10204082, 15.51020408, 15.91836735,\n", + " 16.32653061, 16.73469388, 17.14285714, 17.55102041, 17.95918367,\n", + " 18.36734694, 18.7755102 , 19.18367347, 19.59183673, 19.79591837])" + ] + }, + "execution_count": 136, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dydx" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 사이파이 모듈을 사용해서 미분 구하기" + ] + }, + { + "cell_type": "code", + "execution_count": 137, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy.interpolate import InterpolatedUnivariateSpline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " 두 변수를 인자로 전달해서 객체를 만든다\n", + "\n", + "이 객체를 미분을 derivative 메소드로 수핸하고 그 다음에 실제 미분할 변수를 지정한다" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [], + "source": [ + "# Get a function that evaluates the linear spline at any x\n", + "f = InterpolatedUnivariateSpline(x, y, k=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 139, + "metadata": {}, + "outputs": [], + "source": [ + "# Get a function that evaluates the derivative of the linear spline at any x\n", + "dfdx = f.derivative()\n", + "\n", + "# Evaluate the derivative dydx at each x location...\n", + "dydx = dfdx(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.20408163, 0.6122449 , 1.02040816, 1.42857143, 1.83673469,\n", + " 2.24489796, 2.65306122, 3.06122449, 3.46938776, 3.87755102,\n", + " 4.28571429, 4.69387755, 5.10204082, 5.51020408, 5.91836735,\n", + " 6.32653061, 6.73469388, 7.14285714, 7.55102041, 7.95918367,\n", + " 8.36734694, 8.7755102 , 9.18367347, 9.59183673, 10. ,\n", + " 10.40816327, 10.81632653, 11.2244898 , 11.63265306, 12.04081633,\n", + " 12.44897959, 12.85714286, 13.26530612, 13.67346939, 14.08163265,\n", + " 14.48979592, 14.89795918, 15.30612245, 15.71428571, 16.12244898,\n", + " 16.53061224, 16.93877551, 17.34693878, 17.75510204, 18.16326531,\n", + " 18.57142857, 18.97959184, 19.3877551 , 19.79591837, 19.79591837])" + ] + }, + "execution_count": 140, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dydx" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "gradient 함수의 결괏값과 차이가 있음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 차분으로 미분 구하기" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": {}, + "outputs": [], + "source": [ + "di_dx = np.diff(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 142, + "metadata": {}, + "outputs": [], + "source": [ + "di_dy = np.diff(y)" + ] + }, + { + "cell_type": "code", + "execution_count": 143, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.20408163, 0.6122449 , 1.02040816, 1.42857143, 1.83673469,\n", + " 2.24489796, 2.65306122, 3.06122449, 3.46938776, 3.87755102,\n", + " 4.28571429, 4.69387755, 5.10204082, 5.51020408, 5.91836735,\n", + " 6.32653061, 6.73469388, 7.14285714, 7.55102041, 7.95918367,\n", + " 8.36734694, 8.7755102 , 9.18367347, 9.59183673, 10. ,\n", + " 10.40816327, 10.81632653, 11.2244898 , 11.63265306, 12.04081633,\n", + " 12.44897959, 12.85714286, 13.26530612, 13.67346939, 14.08163265,\n", + " 14.48979592, 14.89795918, 15.30612245, 15.71428571, 16.12244898,\n", + " 16.53061224, 16.93877551, 17.34693878, 17.75510204, 18.16326531,\n", + " 18.57142857, 18.97959184, 19.3877551 , 19.79591837])" + ] + }, + "execution_count": 143, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "di_dy/di_dx" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "차분 diff 함수를 통해 미분을 해보면 사이파이 모듈의 미분한 결과와 거의 같은 것을 확인할 수 있음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-2-4 차원별로 gradient 처리하기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "2차원 배열의 경우, 축으로 정렬된 두 개의 배열이 반환된다\n", + "\n", + "결과의 첫 번째 배열은 행의 그래디언트를 나타내고 두 번째 배열은 열 방향의 그래디언트를 나타낸다" + ] + }, + { + "cell_type": "code", + "execution_count": 144, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([[4,5,6],[3,4,5]])" + ] + }, + { + "cell_type": "code", + "execution_count": 145, + "metadata": {}, + "outputs": [], + "source": [ + "adx = np.gradient(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-1., -1., -1.],\n", + " [-1., -1., -1.]])" + ] + }, + "execution_count": 146, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adx[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 1., 1.],\n", + " [1., 1., 1.]])" + ] + }, + "execution_count": 147, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adx[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 153, + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "module 'autograd.numpy' has no attribute 'mgrid'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmgrid\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m100\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m101\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m25.\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;36m100\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m101\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m25.\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;36m100\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m101\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m25.\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m: module 'autograd.numpy' has no attribute 'mgrid'" + ] + } + ], + "source": [ + "x,y,z = np.mgrid[-100:101:25., -100:101:25., -100:101:25.]" + ] + }, + { + "cell_type": "code", + "execution_count": 154, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'z' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mV\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m2\u001b[0m \u001b[1;33m-\u001b[0m \u001b[1;36m4\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mz\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mNameError\u001b[0m: name 'z' is not defined" + ] + } + ], + "source": [ + "V = 2*x**2 + 3*y**2 - 4*z " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Ex,Ey,Ez = np.gradient(V)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 155, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'Ex' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mEx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mNameError\u001b[0m: name 'Ex' is not defined" + ] + } + ], + "source": [ + "Ex.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Ey.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Ez.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-3-1 기본 적분 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 294, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([1,-2,1]) #다항식 만들기" + ] + }, + { + "cell_type": "code", + "execution_count": 295, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, -2, 1])" + ] + }, + "execution_count": 295, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 296, + "metadata": {}, + "outputs": [], + "source": [ + "p = np.poly1d(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 297, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "poly1d([ 1, -2, 1])" + ] + }, + "execution_count": 297, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 298, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 2\n", + "1 x - 2 x + 1\n" + ] + } + ], + "source": [ + "print(p)" + ] + }, + { + "cell_type": "code", + "execution_count": 299, + "metadata": {}, + "outputs": [], + "source": [ + "d = np.polyint(a) " + ] + }, + { + "cell_type": "code", + "execution_count": 300, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.33333333, -1. , 1. , 0. ])" + ] + }, + "execution_count": 300, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 301, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 3 2\n", + "0.3333 x - 1 x + 1 x\n" + ] + } + ], + "source": [ + "print(np.poly1d(d))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-3-2 trapz 방식으로 적분하기\n" + ] + }, + { + "cell_type": "code", + "execution_count": 303, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.arange(1,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 304, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4])" + ] + }, + "execution_count": 304, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 305, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "7.5" + ] + }, + "execution_count": 305, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.trapz(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 306, + "metadata": {}, + "outputs": [], + "source": [ + "c = a[len(a) -1] - a[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 307, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 307, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 308, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "7.5" + ] + }, + "execution_count": 308, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c * ((a[len(a) -1] + a[0] )/2)" + ] + }, + { + "cell_type": "code", + "execution_count": 309, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(1,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 310, + "metadata": {}, + "outputs": [], + "source": [ + "y = x " + ] + }, + { + "cell_type": "code", + "execution_count": 311, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "7.5" + ] + }, + "execution_count": 311, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.trapz(y,x=x)" + ] + }, + { + "cell_type": "code", + "execution_count": 312, + "metadata": {}, + "outputs": [], + "source": [ + "x2 = np.arange(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 313, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4])" + ] + }, + "execution_count": 313, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x2" + ] + }, + { + "cell_type": "code", + "execution_count": 314, + "metadata": {}, + "outputs": [], + "source": [ + "y2 = x2**2" + ] + }, + { + "cell_type": "code", + "execution_count": 315, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "22.0" + ] + }, + "execution_count": 315, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.trapz(y2,x=x2)" + ] + }, + { + "cell_type": "code", + "execution_count": 316, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([0, 0.5, 1, 1.5, 2])\n", + "y = x**3\n", + "\n", + "x2 = np.linspace(0, 2,100)\n", + "y2 = x2**3" + ] + }, + { + "cell_type": "code", + "execution_count": 317, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 318, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(x, y, label='5 points')\n", + "plt.plot(x2, y2, label='50 points')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 319, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.25" + ] + }, + "execution_count": 319, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.trapz(y, x)" + ] + }, + { + "cell_type": "code", + "execution_count": 320, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.000408121620243" + ] + }, + "execution_count": 320, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.trapz(y2, x2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Q1. trapz 함수로 적분을 하면 결괏값이 차이가 난다. 그 이유는?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-2-3-3 quad 방식으로 적분하기" + ] + }, + { + "cell_type": "code", + "execution_count": 321, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy.integrate import quad" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "하나의 함수를 람다로 지정 0~4까지의 적분을 계산한다 적분한 값과 오차를 반환한다" + ] + }, + { + "cell_type": "code", + "execution_count": 322, + "metadata": {}, + "outputs": [], + "source": [ + "x2 = lambda x: x**2" + ] + }, + { + "cell_type": "code", + "execution_count": 323, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(21.333333333333336, 2.368475785867001e-13)" + ] + }, + "execution_count": 323, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "quad(x2, 0, 4)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "다시 람다함수를 지정하고, 두 개의 매개변수를 전달해서 수식을 정의한다\n", + "\n", + "이 중에서 a에 대한 값을 quad 함수의 매개변수 args에 튜플로 전달해서 적분을 구한다" + ] + }, + { + "cell_type": "code", + "execution_count": 324, + "metadata": {}, + "outputs": [], + "source": [ + "f = lambda x,a : a*x" + ] + }, + { + "cell_type": "code", + "execution_count": 325, + "metadata": {}, + "outputs": [], + "source": [ + "y, err = quad(f, 0, 1, args=(1,))" + ] + }, + { + "cell_type": "code", + "execution_count": 326, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.5" + ] + }, + "execution_count": 326, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "복잡한 산식을 람다함수로 지정해서 quad로 처리해도 적분을 처리한다" + ] + }, + { + "cell_type": "code", + "execution_count": 327, + "metadata": {}, + "outputs": [], + "source": [ + "func = lambda x: np.cos(np.exp(x)) ** 2" + ] + }, + { + "cell_type": "code", + "execution_count": 328, + "metadata": {}, + "outputs": [], + "source": [ + "y, err = quad(func,1,3)" + ] + }, + { + "cell_type": "code", + "execution_count": 329, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0829625047031528" + ] + }, + "execution_count": 329, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "결괏값 확인을 위해 trapz 함수를 실행하여 결괏값을 확인한다" + ] + }, + { + "cell_type": "code", + "execution_count": 330, + "metadata": {}, + "outputs": [], + "source": [ + "x = [0, 0.5, 1, 1.5, 2]\n", + "y = [0, 0.1250, 1.0000, 3.3750, 8.0000]" + ] + }, + { + "cell_type": "code", + "execution_count": 331, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.25" + ] + }, + "execution_count": 331, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.trapz(y, x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 보간하는 객체를 만든다" + ] + }, + { + "cell_type": "code", + "execution_count": 332, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy.interpolate import interp1d" + ] + }, + { + "cell_type": "code", + "execution_count": 333, + "metadata": {}, + "outputs": [], + "source": [ + "f = interp1d(x, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 334, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(nan)" + ] + }, + "execution_count": 334, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f.fill_value" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "하나의 배열을 만들어 더 세밀한 보간법을 수행한다\n", + "\n", + "그런 후에 quad 함수로 적분을 하면 위의 trapz 함수로 적분한 결과가 유사한 것을 알 수 있다" + ] + }, + { + "cell_type": "code", + "execution_count": 335, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4.251561849229487\n" + ] + } + ], + "source": [ + "xfine = np.linspace(0., 2.)\n", + "yfine = f(xfine)\n", + "print(np.trapz(yfine, xfine))" + ] + }, + { + "cell_type": "code", + "execution_count": 336, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(50,)" + ] + }, + "execution_count": 336, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "yfine.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 337, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4.25\n" + ] + } + ], + "source": [ + "ans, err = quad(f, 0., 2.)\n", + "print(ans)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 합성곱 및 필터링 알아보기" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-3-1-1 convolve 함수 처리" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1차원 배열을 만들고, \n", + "\n", + "합성곱을 하는 필터는 2개의 원소를 가진 배열로 만든다" + ] + }, + { + "cell_type": "code", + "execution_count": 338, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.array([0, 1, 2, 3, 4, 5,6])" + ] + }, + { + "cell_type": "code", + "execution_count": 339, + "metadata": {}, + "outputs": [], + "source": [ + "v = np.array([0.2, 0.7])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "넘파이 모듈에서 제공하는 1차원 배열의 합성곱 함수 convolve에 첫 번째 인자는 입력 데이터, 두 번째 인자는 필터, 세 번째 인자인 mode는 합성곱 내부의 원소들이 연산하는 횟수를 지정한다\n", + "\n", + "mode에 smae을 지정하면 입력 데이터의 원소의 연산이 동일하지 않은데,\n", + "\n", + "이유는 입력 데이터와 동일한 형상을 가진 배열을 반환하기 때문" + ] + }, + { + "cell_type": "code", + "execution_count": 340, + "metadata": {}, + "outputs": [], + "source": [ + "same = np.convolve(a,v, mode='same')" + ] + }, + { + "cell_type": "code", + "execution_count": 341, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(7,)" + ] + }, + "execution_count": 341, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "same.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 342, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0. , 0.2, 1.1, 2. , 2.9, 3.8, 4.7])" + ] + }, + "execution_count": 342, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "same" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "합성곱을 처리하는 입력데이터에 첫 번째 언소 앞에 패딩으로 0을 추가\n", + "\n", + "기본적으로 합성곱을 처리할 때 먼저 필터의 배열을 반대로 만들어야 한다\n", + "\n", + "roll 함수로 원소의 위치를 변환한다" + ] + }, + { + "cell_type": "code", + "execution_count": 343, + "metadata": {}, + "outputs": [], + "source": [ + "a_ = np.array([0,0, 1, 2, 3, 4, 5,6])" + ] + }, + { + "cell_type": "code", + "execution_count": 344, + "metadata": {}, + "outputs": [], + "source": [ + "v_ = np.roll(v,1)" + ] + }, + { + "cell_type": "code", + "execution_count": 345, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.7, 0.2])" + ] + }, + "execution_count": 345, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "v_" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 동일한 원소의 개수를 가지려면 배열의 첫 번째 원소 앞에 0이 하나 더 추가되는데 이런 처리를 패딩이라고 한다" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "합성곱 연산을 처리하는 필터가 2개의 원소를 가진다\n", + "\n", + "이 필터와 내적을 계산하려면, 두 개의 원소씩 계산해야 하는데\n", + "\n", + "패딩된 원소 0과 첫 번째 원소 0을 하나의 배열로 만들어서 필터와 연산을 한다\n", + " \n", + " \n", + " \n", + "두 번째 연산은 첫 번째와 두 번째 원소를 쌍으로 필터와 벡터곱인 내적을 구한다\n", + "\n", + "합성곱은 필터의 원소 개수에 맞춰서 입력 데이터 원소를 필터의 원소와 동일하게 구성해서 내적을 구하는 것과 같다" + ] + }, + { + "cell_type": "code", + "execution_count": 346, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 346, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot([0,0], v_)" + ] + }, + { + "cell_type": "code", + "execution_count": 347, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.2" + ] + }, + "execution_count": 347, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot([0,1], v_)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "입력 데이터 전체를 가지고 내적을 구한 후에\n", + "\n", + "convolve 함수와 동일한 결과인지 allclose 함수로 확인한다" + ] + }, + { + "cell_type": "code", + "execution_count": 348, + "metadata": {}, + "outputs": [], + "source": [ + "ll = []" + ] + }, + { + "cell_type": "code", + "execution_count": 349, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(7) :\n", + " ll.append(np.dot(a_[i : i+2], v_).tolist())" + ] + }, + { + "cell_type": "code", + "execution_count": 350, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[0.0, 0.2, 1.1, 2.0, 2.8999999999999995, 3.8, 4.7]" + ] + }, + "execution_count": 350, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ll" + ] + }, + { + "cell_type": "code", + "execution_count": 351, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 351, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(same, ll)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Q2. 합성곱 연산을 처리할 때 모드를 full로 처리하면 원소가 하나 추가된 8개가 된다, 이 이유는?" + ] + }, + { + "cell_type": "code", + "execution_count": 352, + "metadata": {}, + "outputs": [], + "source": [ + "full = np.convolve(a,v, mode='full')" + ] + }, + { + "cell_type": "code", + "execution_count": 353, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(8,)" + ] + }, + "execution_count": 353, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "full.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 354, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0. , 0.2, 1.1, 2. , 2.9, 3.8, 4.7, 4.2])" + ] + }, + "execution_count": 354, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "full" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 355, + "metadata": {}, + "outputs": [], + "source": [ + "ll = []" + ] + }, + { + "cell_type": "code", + "execution_count": 356, + "metadata": {}, + "outputs": [], + "source": [ + "a__ = np.array([0,0, 1, 2, 3, 4, 5,6,0])" + ] + }, + { + "cell_type": "code", + "execution_count": 357, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(8) :\n", + " ll.append(np.dot(a__[i : i+2], v_).tolist())" + ] + }, + { + "cell_type": "code", + "execution_count": 358, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[0.0, 0.2, 1.1, 2.0, 2.8999999999999995, 3.8, 4.7, 4.199999999999999]" + ] + }, + "execution_count": 358, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ll" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "valid 모드를 사용하면 패딩이 발생하지 않아 계산된 결과가 입력 데이터보다 하나의 원소가 작음" + ] + }, + { + "cell_type": "code", + "execution_count": 359, + "metadata": {}, + "outputs": [], + "source": [ + "valid = np.convolve(a,v, mode='valid')" + ] + }, + { + "cell_type": "code", + "execution_count": 360, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(6,)" + ] + }, + "execution_count": 360, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "valid.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 361, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.2, 1.1, 2. , 2.9, 3.8, 4.7])" + ] + }, + "execution_count": 361, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "valid" + ] + }, + { + "cell_type": "code", + "execution_count": 362, + "metadata": {}, + "outputs": [], + "source": [ + "ll = []" + ] + }, + { + "cell_type": "code", + "execution_count": 363, + "metadata": {}, + "outputs": [], + "source": [ + "a___ = np.array([0, 1, 2, 3, 4, 5,6])" + ] + }, + { + "cell_type": "code", + "execution_count": 364, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(6) :\n", + " ll.append(np.dot(a___[i : i+2], v_).tolist())" + ] + }, + { + "cell_type": "code", + "execution_count": 365, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[0.2, 1.1, 2.0, 2.8999999999999995, 3.8, 4.7]" + ] + }, + "execution_count": 365, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ll" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "교차상관을 처리하는 correlate함수를 사용해서 합성곱 convolve 함수와 동일한 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 366, + "metadata": {}, + "outputs": [], + "source": [ + "w = np.array([1,3,3,0])" + ] + }, + { + "cell_type": "code", + "execution_count": 367, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([2,4,6,8,0,8,0])" + ] + }, + { + "cell_type": "code", + "execution_count": 368, + "metadata": {}, + "outputs": [], + "source": [ + "w_r = np.flip(w)" + ] + }, + { + "cell_type": "code", + "execution_count": 369, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 3, 3, 1])" + ] + }, + "execution_count": 369, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "w_r" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "이때 flip 함수로 필터의 원소를 반대 방향으로 변환함" + ] + }, + { + "cell_type": "code", + "execution_count": 370, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 24, 38, 42, 32, 24, 24])" + ] + }, + "execution_count": 370, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.correlate(x, w_r,mode='same')" + ] + }, + { + "cell_type": "code", + "execution_count": 371, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 24, 38, 42, 32, 24, 24])" + ] + }, + "execution_count": 371, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.convolve(x,w, mode='same')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "교차상관에 필터를 역방향으로 전달해서 계산한 결과와 합성곱으로 연산한 결과가 동일한 것을 알 수 있음" + ] + }, + { + "cell_type": "code", + "execution_count": 372, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 6, 18, 32, 46, 30, 32, 24])" + ] + }, + "execution_count": 372, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.correlate(x, w,mode='same')" + ] + }, + { + "cell_type": "code", + "execution_count": 373, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 6, 18, 32, 46, 30, 32, 24])" + ] + }, + "execution_count": 373, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.convolve(x,w_r, mode='same')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "딥러닝 합성곱에서는 필터를 역방향으로 만들지 않고 계산하기 때문에\n", + "\n", + "딥러닝에서는 필터의 배열을 임의로 초기화한 후에 최적화를 계산을 통해 필터의 값을 변형하기 때문에 역방향으로 변환한 후에 처리할 필요가 없다\n", + "\n", + "따라서 역방향으로 변환하지 않고 교차상관을 계산한 다음에 합성곱에서 필터를 역방향으로 변환한 후에 실행한다\n", + "\n", + "두 결과가 동일한 것을 알 수 있음" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-3-2-1 convolve 2차원 처리하기 \n" + ] + }, + { + "cell_type": "code", + "execution_count": 374, + "metadata": {}, + "outputs": [], + "source": [ + "A= [[5, 4, 5, 4],\n", + " [3 ,2, 3 , 2], \n", + " [5 , 4, 5, 4],\n", + " [3 ,2 ,3 , 2 ]]" + ] + }, + { + "cell_type": "code", + "execution_count": 375, + "metadata": {}, + "outputs": [], + "source": [ + "A = np.array(A)" + ] + }, + { + "cell_type": "code", + "execution_count": 376, + "metadata": {}, + "outputs": [], + "source": [ + "k = np.array([0.707, 0.707])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "합성곱을 처리할 때 필터가 입력 데이터를 계산할 때 이동하는 것을 스트라이드라고 한다\n", + "\n", + "기본적으로 이동은 1칸씩 좌에서 우로 이동함" + ] + }, + { + "cell_type": "code", + "execution_count": 377, + "metadata": {}, + "outputs": [], + "source": [ + "C = np.zeros((4,5))" + ] + }, + { + "cell_type": "code", + "execution_count": 378, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(4) :\n", + " C[i] = np.convolve(A[i],k, mode='full')" + ] + }, + { + "cell_type": "code", + "execution_count": 379, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3.535, 6.363, 6.363, 6.363, 2.828],\n", + " [2.121, 3.535, 3.535, 3.535, 1.414],\n", + " [3.535, 6.363, 6.363, 6.363, 2.828],\n", + " [2.121, 3.535, 3.535, 3.535, 1.414]])" + ] + }, + "execution_count": 379, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "C" + ] + }, + { + "cell_type": "code", + "execution_count": 380, + "metadata": {}, + "outputs": [], + "source": [ + "k_ = np.array([0.707, 0.707]).reshape(1,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 381, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((4, 4), (1, 2))" + ] + }, + "execution_count": 381, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.shape, k_.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "2차원 합성곱 연산의 함수는 scipy.sigmal 모듈에 있음\n", + "\n", + "계산된 결과가 앞에서 계산한 것과 같음" + ] + }, + { + "cell_type": "code", + "execution_count": 382, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy import signal" + ] + }, + { + "cell_type": "code", + "execution_count": 383, + "metadata": {}, + "outputs": [], + "source": [ + "grad = signal.convolve2d(A, k_, boundary='fill', mode='full')" + ] + }, + { + "cell_type": "code", + "execution_count": 384, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(4, 5)" + ] + }, + "execution_count": 384, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "grad.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 385, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3.535, 6.363, 6.363, 6.363, 2.828],\n", + " [2.121, 3.535, 3.535, 3.535, 1.414],\n", + " [3.535, 6.363, 6.363, 6.363, 2.828],\n", + " [2.121, 3.535, 3.535, 3.535, 1.414]])" + ] + }, + "execution_count": 385, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "grad" + ] + }, + { + "cell_type": "code", + "execution_count": 386, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([[1, 1, 1, 0, 0],\n", + " [0, 1, 1, 1, 0],\n", + " [0, 0, 1, 1, 1],\n", + " [0, 0, 1, 1, 0],\n", + " [0, 1, 1, 0, 0]],dtype='float')" + ] + }, + { + "cell_type": "code", + "execution_count": 387, + "metadata": {}, + "outputs": [], + "source": [ + "w_k = np.array([[1, 0, 1],\n", + " [0, 1, 0],\n", + " [1, 0, 1],],dtype='float')" + ] + }, + { + "cell_type": "code", + "execution_count": 388, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((5, 5), (3, 3))" + ] + }, + "execution_count": 388, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x.shape, w_k.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 389, + "metadata": {}, + "outputs": [], + "source": [ + "f = signal.convolve2d(x, w_k, 'valid')" + ] + }, + { + "cell_type": "code", + "execution_count": 390, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3, 3)" + ] + }, + "execution_count": 390, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 391, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[4., 3., 4.],\n", + " [2., 4., 3.],\n", + " [2., 3., 4.]])" + ] + }, + "execution_count": 391, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f" + ] + }, + { + "cell_type": "code", + "execution_count": 392, + "metadata": {}, + "outputs": [], + "source": [ + "fs = signal.convolve2d(x, w_k, 'same')" + ] + }, + { + "cell_type": "code", + "execution_count": 393, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(5, 5)" + ] + }, + "execution_count": 393, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fs.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 394, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2., 2., 3., 1., 1.],\n", + " [1., 4., 3., 4., 1.],\n", + " [1., 2., 4., 3., 3.],\n", + " [1., 2., 3., 4., 1.],\n", + " [0., 2., 2., 1., 1.]])" + ] + }, + "execution_count": 394, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fs" + ] + }, + { + "cell_type": "code", + "execution_count": 395, + "metadata": {}, + "outputs": [], + "source": [ + "fl = signal.convolve2d(x, w_k, 'full')" + ] + }, + { + "cell_type": "code", + "execution_count": 396, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(7, 7)" + ] + }, + "execution_count": 396, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fl.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 397, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 1., 2., 1., 1., 0., 0.],\n", + " [0., 2., 2., 3., 1., 1., 0.],\n", + " [1., 1., 4., 3., 4., 1., 1.],\n", + " [0., 1., 2., 4., 3., 3., 0.],\n", + " [0., 1., 2., 3., 4., 1., 1.],\n", + " [0., 0., 2., 2., 1., 1., 0.],\n", + " [0., 1., 1., 1., 1., 0., 0.]])" + ] + }, + "execution_count": 397, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fl" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-4-2-3 이미지 처리 알아보기 " + ] + }, + { + "cell_type": "code", + "execution_count": 398, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy import misc" + ] + }, + { + "cell_type": "code", + "execution_count": 399, + "metadata": {}, + "outputs": [], + "source": [ + "face = misc.face(gray=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 400, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(768, 1024)" + ] + }, + "execution_count": 400, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "face.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "이미지 확인 시에 imshow를 사용한다\n", + "\n", + "인자 cmap에 이 이미지를 회색조로 처리한다" + ] + }, + { + "cell_type": "code", + "execution_count": 401, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 402, + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": 403, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax_orig = plt.subplots(1, 1, figsize=(6, 15))\n", + "ax_orig.imshow(face, cmap='gray')\n", + "ax_orig.set_title('Original')\n", + "ax_orig.set_axis_off()\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "복소수를 원소로해 2차원 배열을 만들어 필터로 사용한다" + ] + }, + { + "cell_type": "code", + "execution_count": 404, + "metadata": {}, + "outputs": [], + "source": [ + "scharr = np.array([[ -3-3j, 0-10j, +3 -3j],\n", + " [-10+0j, 0+ 0j, +10 +0j],\n", + " [ -3+3j, 0+10j, +3 +3j]]) # Gx + j*Gy" + ] + }, + { + "cell_type": "code", + "execution_count": 405, + "metadata": {}, + "outputs": [], + "source": [ + "grad = signal.convolve2d(face, scharr, boundary='symm', mode='same')" + ] + }, + { + "cell_type": "code", + "execution_count": 406, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(768, 1024)" + ] + }, + "execution_count": 406, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "grad.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "복소수의 값의 크기는 절댓값 연산으로 크기를 구할 수 있는데, 그래서 abs 함수나 absolute 함수에 원소를 하나씩 넣어서 실행하면 복소수의 크기를 실수로 표시한다\n", + "\n", + "배열의 하나의 행을 인자로 전달하면 각각의 원소의 크기를 계산한다" + ] + }, + { + "cell_type": "code", + "execution_count": 407, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-271.+481.j, -523.+419.j, -299.+349.j, ..., -244. +16.j,\n", + " -318. -74.j, -140.-132.j])" + ] + }, + "execution_count": 407, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "grad[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 408, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "552.0887609796091" + ] + }, + "execution_count": 408, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.abs(grad[0,0])" + ] + }, + { + "cell_type": "code", + "execution_count": 409, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "552.0887609796091" + ] + }, + "execution_count": 409, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.absolute(grad[0,0])" + ] + }, + { + "cell_type": "code", + "execution_count": 410, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([552.08876098, 670.14177604, 459.56718769, ..., 244.52402745,\n", + " 326.49655435, 192.41621553])" + ] + }, + "execution_count": 410, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.absolute(grad[0])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "복소수의 값을 angle 함수에 전달하여 라디안 값을 표시한다\n", + "\n", + "이 값을 각으로 표시하려면 deg=True를 지정해야 함" + ] + }, + { + "cell_type": "code", + "execution_count": 411, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2.0838764628714874" + ] + }, + "execution_count": 411, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.angle(grad[0,0])" + ] + }, + { + "cell_type": "code", + "execution_count": 412, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "119.39732634918663" + ] + }, + "execution_count": 412, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.angle(grad[0,0], deg=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 413, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 2.08387646, 2.46615257, 2.27918658, ..., 3.07611263,\n", + " -2.91295726, -2.38559778])" + ] + }, + "execution_count": 413, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.angle(grad[0])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "복소수의 크기와 복소수를 라디안 값으로 변환해서 이미지를 변환시키기" + ] + }, + { + "cell_type": "code", + "execution_count": 414, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax_mag, ax_ang) = plt.subplots(1, 2, figsize=(6, 15))\n", + "ax_mag.imshow(np.absolute(grad), cmap='gray')\n", + "ax_mag.set_title('np.absolute ')\n", + "ax_mag.set_axis_off()\n", + "ax_ang.imshow(np.angle(grad), cmap='hsv') # hsv is cyclic, like angles\n", + "ax_ang.set_title('np.angle')\n", + "ax_ang.set_axis_off()\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-3-3-1 필터링 처리" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "필터링을 통해 같은 형상의 배열을 만들거나 풀링을 통해 더 작은 배열을 만들 수 있음" + ] + }, + { + "cell_type": "code", + "execution_count": 415, + "metadata": {}, + "outputs": [], + "source": [ + "B = [[3, 4, 5, 2, 3],\n", + " [3, 5, 1, 2, 7],\n", + " [2, 2, 5, 6, 7]]" + ] + }, + { + "cell_type": "code", + "execution_count": 416, + "metadata": {}, + "outputs": [], + "source": [ + "B = np.array(B)" + ] + }, + { + "cell_type": "code", + "execution_count": 417, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy.ndimage.filters import maximum_filter, minimum_filter" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "매개변수 size와 footprint에 동일한 형상을 넣으면 결과가 동일함.\n", + "\n", + "따라서 둘 중 하나만 작성할 수 있다" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "최댓값 기준으로 필터링" + ] + }, + { + "cell_type": "code", + "execution_count": 418, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 4, 5, 5, 3],\n", + " [3, 5, 5, 5, 7],\n", + " [3, 5, 5, 6, 7]])" + ] + }, + "execution_count": 418, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "maximum_filter(B, size=(2,2))" + ] + }, + { + "cell_type": "code", + "execution_count": 419, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[5, 5, 5, 7, 7],\n", + " [5, 5, 6, 7, 7],\n", + " [5, 5, 6, 7, 7]])" + ] + }, + "execution_count": 419, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "maximum_filter(B, footprint=np.ones((3,3)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "최솟값 기준으로 필터링" + ] + }, + { + "cell_type": "code", + "execution_count": 420, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 3, 4, 2, 2],\n", + " [3, 3, 1, 1, 2],\n", + " [2, 2, 1, 1, 2]])" + ] + }, + "execution_count": 420, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "minimum_filter(B, size=(2,2))" + ] + }, + { + "cell_type": "code", + "execution_count": 421, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 1, 1, 1, 2],\n", + " [2, 1, 1, 1, 2],\n", + " [2, 1, 1, 1, 2]])" + ] + }, + "execution_count": 421, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "minimum_filter(B, footprint=np.ones((3,3)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "이미지를 필터링 하기 위해 matplotlib를 import하고 \n", + "\n", + "경고 메시지를 제외시키기 위해 warnings import" + ] + }, + { + "cell_type": "code", + "execution_count": 422, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 423, + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": 424, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy import misc\n", + "face = misc.face(gray=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 425, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax_orig = plt.subplots(1, 1, figsize=(6, 15))\n", + "ax_orig.imshow(face, cmap='gray')\n", + "ax_orig.set_title('Original')\n", + "ax_orig.set_axis_off()\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 426, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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hsH5dhBA4HA4sFgvj4+MYjUadaFitVhwOh35eNpvFbrfjdrtxOByUlpbqZFJRFLLZLC0tLRw+fJh0Ok13dzcmkwmDwcC1117LpEmTeOKJJ0in01itVqLRKABms/l3SFsmk9HbrpEwp9OJoihMnz4dQP/dZDJhsVj0eux2OwaDAZNJPvcUFhayfft2nnnmmZOG8AjOVRazld13KHJD/4YSYCPv8ymSyJ3hLsWLlQAvA6uRZvAI6+DQY3AlWA8KvoI0Av+JfJHdpUhjcTNWfk2CFUl4xiLNWhfyJU5FwGeQnGYjj8EX1klLtHIyF9DJy7wFvAJ33C4bG0ayh7XnUstWuvDCp/2wEVnw+cCaQ8APWM8TbPiyAhsAdxT53spVyHddrmLClGi07hGkKQQrm3gZWJIBm9ENXM1qHsaCNJL/ykNAO/N5mP3NCtc0CH6KgyyPw81ruesewaOAj1d5hfM47zlgKbxaLsdkF/B1YH4UTN8DzoPGZXCEt2jjdKbipZwAV6NTS77CPcBUruFyNrIERt/C6hYk+Dyykw8CKbWF3dzKjRwF/gcjV5KhB3gNPxMkYQCdNNx8LtxzO7x4O9ZLBAmOweUN8Gwn65nMhu0KLL9cHfx7gVYkVZihjuFp8uI0d0DDS+r356jl3wK0sZ6b2cA6dVbMQ9I9C/DP6jWZizTjN2HgU2S5CjP/RYpHgFdYzIuEgSNcB3RjZgsZbDiIMM5yJLvQaEAYD6PMVFtnQZKHanXuzlDnXimSd1QDp2TAkAGRhqftE2TGovZCuxe2AWbgDXlJSQIbqEQSievhRTWjfhVgLEF5OcDeC2DRI2oBYXSWdNtdcEcXvFo7cVWS6pUZVtuK2tYp6v8FGThmlO0A7d5Zq/6VZKLlNWpJYeTbQWTv32cyc58DLlN+7xr2oS6tdDrN9OnTMRgMRKNRDh8+zPHjxwmFQlRXV2O1Wpk0aRJ2u51UKoXf7ycQCFBUVEQ0GqW9vZ2qqiouueQSGhsbmTdvHpMmTcJkMjFt2jTy8vKIx+O4XC4KCgqYMWMGVquVoaEhent75WAUFelPoJlMBrPZTGFhIcFgEKfTidvtxmw2E4vFSKfT1NfXs337dnbt2sU777xDIpHQn2zLyspobGxk586dDA0N4fP5GB0dxeVy8cYbb1BYWEg6ncZkMnH8+HGi0SgdHR0YjUaKioo49dRTWblyJaeffjput5va2lpisRjTpk1jwYIFumqQTCbp7+/HZDLpykV/fz9ut5tUKkVRURFLly6lqqqK66+/nrPOOovGxkbOO+88SktLWbp0KYFAgLlz57J9+3Y2bdpEV1cXFosFIQQWi4Xy8nKSySTTp0/H6XRit9tZsGCBrqwdPXoUk8mE3+/Xlai2tjZdvaqpqSEQCOD3+xkdHdUVDY0AaarTyMgIfX19pNNpZs+ejcVi4dVXX8Xn89HW1sa+ffuYMmUKqVQKq9WK0+mkv78fg8GAw+FgdHQUj8eDzWZjaGgIRVGor6+noKCA8fFxUqkU4+PjRKNRzGYzAwMDGAwGnTRoBC8WixEKhXSCEQ6HCQQCjI+Pk0wmdTVpZGSEwsJCUqkUHR0dFBYWkkgkdJKZTqexWCxEInKjVovFQiaTQQihqyhCCAwGA/F4XFeZMpkMJpMJIQSxWIxUKkUkEiGbzf6OahOLxYhGo8RiMV1hstlspNNpIpEI8XicdDrN7t27OXbsmK7oacRm9erV1NTUsHHjRjKZjK7ipNNpzGazTla0NmvIZDLk5+fjdrvJz8+nvr6eTCaDzWbTVSmLxYLdbtdVnmg0it/v5/jx47pK6XafXFuEPMhW3gkCt83hqw0CE2Ncw6fYApxKHW0AlJEgxYqYwpeQSzvkc9dsAQdPJ8FjPPC4wsvcQA0reZpKLmWh3P6bBLcCWyxwNTcwipV83HwR+SKoImAj9wHd8OPLYeWn4FAHI8CDnA5fvl0yhFLk43oTwJc4/jI8SAB++ba0cU2oL2j4KfCAfDfBY58C99vwsB256N+qFvKPcON9SAvUzvfp5Ao+BU89i5NNJLiQC4A1RniFUa7hYTbza5Yity9ezdeAJ9nPz5jfIFgEFBJhNVehXCD4DnVsAFZzHudTiTiu8EI5nM+F7AX+Oyi3jH/ZDgvuAgZlq+Bi1gPLCOBjOT8ENuPlBUBpvRk4n42sAwrBfbtKdsJIWvRZYA9mroDOGxhGUpIUq9hIHa8xG+73QmyhPGf6QiApyc4/A8yEr0KiTwEOwLOXQ6aODfyMacsFxJ5FEpV84EHMrGZCh+jGQyc0PKFehG1Iiz8XuAjYxQbcaGRnFvfjYZ86A7vVcnYhtxB7RVXlXiHFTKTuNcgUtUTZ13xSLGUuEfVFX1PVMl7BxBAwlyImTP0w0twnAYf6t0X2kilImthrlK1JqHvqV6s9nSafo7CoLV2KpBIXqb17Uv81CZhlI8+HZUZBKqqSHW3eWtQKZ8K9d8EdR+CFWlm+pgIOMPEujRnA2jG4aDfMaIXS/WD9Jcw9Imnto8BGlqst08ZRo2i7kPLnNuS+tN8ClvEKsOAy/iA+VOF57LHHlPLycvx+Px6Ph7GxMVwuFxaLhVQqxaFDhzCbzRw7doyLL75YNxIej4dkMsnAwABCCHw+HwBlZWX4/X78fj9Wq5V4PK4bi1NPPRW/34/T6aSlpUVf3J1OJ319fQCUl5cTjUaprq4mk8lQVFSkGyfNADidTqLRKHfffTerV6/GZrMxd+5cRkdHaW1t5dxzz6Wrq4sf/OAH/NM//RM2m41oNKq7DSKRCIqiEI/HmT59OkajkeHhYQ4cOKCrFtOnT2dsbIxDhw7R09NDQ0MDTqeTrq4u3eUwNjaGoii6O2769Om4XC5KSkro6Ojg0KFDnHvuuRiNRmbNmsXbb7/N8PAwiUQCi8XC1KlTcbvd9Pb20tbWxrx58xgeHsZsNpOfn09nZydms5k5c+boBmvx4sW662J8fJyCggIikQjhcFhX6JYuXcrAwAAtLS1YLBZKSkqw2WykUikaGhoAdGWqrq6OsbExTCYTZrOZwcFB3G43o6OjFBYWkkwmaW5uZs6cObS1tWG320kmk3R3dzNnzhwMBgO9vb3Y7XaKiooYHBzE6XRSVlZGKBQiGAxiNpsZHx8nkUiQyWQIBAK43W5dTYnFYgSDQcrKynTXUjQapbCwEEVRGB0dJZFI4HQ6MRgM2Gw2YrEYkUgEq9WKx+MhLy+PYDCoKyuaUqiRJI0IafeC0WjUSZbD4WBsbIxEIqG3SyNniYR86bvVasVoNOrjbDKZsNlsFBQU4HA4yM/Px+Vy6XN93759jIyMkEwm8fv9jI+PU1hYyEUXXcRpp53Go48+qhMpbT4YjUY8Hg+NjY1UVFSQl5enqz3aPaC5tmw2m07GtPZqfdPuXYvFQiwWo7W1VXfz2mw2TCYT995770mk8DylwF6sPMw8YDchiLnhh8ANVzGNp7gFzdlwCfpz6JwfgwXM75r4ezL8AiMpLgUGWMZ2wsi1fQWSZoxixUsCH+tg62NsWymHcAULgf8gnjkFt1ESoGEgwUKk/tMET/wM41cg8z66lTIszCfznQjirjrgJti0Drph8Q2C3Q8rrL9O8L1HQHy1Aw7VwewbkQ4BWMbNvDEGNpeR08iwgxB0urm1TnAna2UfM/dJi+k+l8zYVgw/APOtVtaSYCOzmcUhuoFx6higk9L/BBZB03xpsNYD790JiZthoRGO8C228T1mII3kTfvhYvU1nyuQhnkVa/gvNvEo0kViooWVJHiZOsrp5E79GqxCqhx3qwpIu9q3X2HiPdIvxuGSTuDv1Sv3b5A5F4ynU8vbdG1XJI+473LY9Cys6YNDlXJL1a8DeaPIfUtvAtop5yp8vKvWE0a6pECSrAGk6QU4n+/zOP/Kj5HmeirllODjPvW8CHCUxbzEbryYGCPNOTh5iSSQ0N0yu/DQSRAvsJTFvEghsBUrl5DgOdzMYpQBIEgdUk+cgomvk2YZkGQx2wFp+jXyMkNtxaDeWjg7Cs/Z4dMZMEdgn0v2UtObZiYhaZHnFSWlArTbLnuyC8m124Aga9QSk8zny/yHWs9FPuRYb5M/p9eA2X4PSuvNHJgmy5iLpJLdSIJ1xA7TM/AzI3wVSPAWbFoiy9DeujYV+Ef1dvT+FrlfI0j2OlVt/a3qDWNBUr0UEMZABxnCf7pLa/PmzUoqlWJsbIy+vj4URWHOnDkUFhbi9/t1l1YkEmFgYICamhqCwSDHjx8nGAxit9upr6+nuLgYq9WK2WzW3QYGgwEhBJlMRncX7d+/X3cJ2Ww2QqEQg4OD9PT0kMlkKC8v19UCr9dLLBYjk8no8S6aC8TtdjM4OEgkEmFkZIT6+nrdZRQKhaiqquLw4cN0dnZSX1+Pz+dj8eLF/PKXv6SsrIx4PA5ANBolm82yYMECvF4v7e3tBINB/H4/JSUltLa2kk6nGR8fp6ioCK/XSzabJT8/n2w2+3+55yZNmqTHluzatYuuri4qKipoaGjA4XCwe/duysrK9Cf19vZ2CgoKKC0tpa2tjbq6OoxGI319fbrBtVgseoyNpk55PB7i8bju6kulUtTW1mI2mykoKMDv9+Pz+SgvL6eyspKBgQFsNhtNTU3U1tYyefJkUqkUiUSClpYWDAaDHrcVi8UYGJCzUjPqiUSCkZERjEYjbrebSCRCJpOhuLgYp9NJNptlaGiInp4eKioqqKqqIpFIMDQ0hNvtxm63E4/Hee+99wiHw/q1VBSFkZERXaFIpVKMjIwA6LFj6XRaV020eBybzcb4+Djl5eX6OMTjcSoqKhgaGsLv92MymchkMoyOjuoKpsvlIplM6oRRU0T6+/ux2+3Y7Xa9PkAv226368RQI902mw2z2UxRUREOh0Nv8+HDh3W3ZTQa1VXLa665hpqaGl5//XXa26VHfunSpUyZMkUnc5lMRndNpVIphoeH2b9/Px0dHVRWVuL1enX3mxYfp7nxMpkMyWQSh8OBwWDA6/VSU1NDQUGBfl/6/X7efPNNfvGLX5xEhOeQIhfFZ4C9XEGAp3kL7l8CN6SxYpYLLmHgbiCf+bzEL5DE5F7kep5gHdK0LIWXzpTygvZY/FgBTkYpA1qOgJj1FvB3rGaUzSxkMft45zlIXwiv22FFEsotEOQt9AX75s/LskaQTGov/PAtQbvach8r4cu/hcf2AT/CKR5jXOljNVVs3q4wf7lgf0bhFaPgfO4B7uV5RvnM03DlFdJwBVnJOWzl1TFodsFM1rGHxxlEmo+9SHIyAFyNm/WMsgEv7xNgHo/h4csUAUejcL0d/n0z8D784FapO+1nIbPYxy+AhjE4yyUjh8ZZguZeu4ztPMeFdPMS64GnWQLM4H2eYB7LuYDt3AJ8To40e4EjaK/Q+6y8KocWwuy3uYLTeZpj8grFbpCH5BVgZZTEjYrm/YIbPgUUQeBn8mJ+fg4T7+9chZWvkWAl8oSZ6igsU3//iZwXsd9C3u1Iw3un+psa+dJ5JtQ9rs6YbVzDVjayUC0vjJOnGKcS+CzzuZ+wOtt8LAQG+Cp9HJBDSRwjxWQoAlowkmIe0phHmNBgBpnG27pbSFNPZiCFlqTaMs3xsxdYlYRui+QUNWrvZ0XBFIOsWRKhRa2QLYWsSZKSn6tT/BmgFTcwldXs43q1RYu6mAjIOSArFt9Yg3LnJlLr4ahF1gFQZIfxQ4qU/n4BzoWCI0D160gfWgRevUBenkdwo5FeOIAZubOJgQwz1SoBOrGykAT/BpyxSYE1JXQToPo/gWt/v0vrQwnPnj17lOHhYT2IMy8vT1/Ig8EgVquVRCJBfn4+mUyGTCaD0+mkvb2diooKIpEIxcXFZLNZmpqaiMfjVFdX63ETL7zwgm5UKisrqaqqYmBggN/85jecccYZeDweXVmKRCJ0dHTQ1tbGtddeS2FhIVu3bqW8vJxMJqMbBu1JNRAI0NTURGNjI93d3VRXV2MymcjPz9efqNva2igoKMDlcrFlyxY+/elP09bWxrFjx3SlSAhBWVkZPp8Pr9dLd3c3DoeDU045hXfffZf3339fVx7y8vJwu91MmTJFV7+8Xi/Dw8P4fD7OOOMMysvLOXr0KKlUCkBva+XfDEwAACAASURBVEFBASaTiUQigd/v59RTT0UIQWlpKS6Xi1QqRVdXF3l5eSSTSVpaWojFYnq/ysvLaWpqYnBwkLKyMk455RTdtdLW1sakSZMwGo3Mnj2bWCxGPB4nHA7rMT9jY2MMDAwwPDxMcXExDodDJyKtra0oiqLHyPT09BCPxxkcHMRut+suP7fbTWdnJ8PDw1itVqZNm6aTr4GBAZ20er1eBgYGdBdQXl4e6XSaoaEh3eXm9Xrp7+9n3rx5tLe36+6dzs5OwuGw7s4MBoOEQiEA3G43sVhMH8eGhgaCwSDRaBS3243FYqGrq0snRcFgkHQ6TTqdBqRSk8lkCIfDOiGPx+OYzWYikYge/KuNnRanAxCJRHRlR5uD2ue8vDyMRiOBQEBXlMJhedva7XY+97nP4fF42LFjB/PmzcNqteruSwBFUYhEIrz88ssMDw+TSqVwOBx6sL/JZCKdTjM2NqaTHJfLpRM47R7XArC1sWpubmZ0dJRsNsvixYtZsWIFBoOBVatWnTyE5wsohJHrZxGSs7wAP7xNsA14jhTfwKwurdBKLwQqwXs7dN7OtDrBcYykqEEasHbkM++dJJNfw3wEqIEej1y8xdlelI0BqIF/OVu24RHcfJ9RaoA1Y2CIwN5yOJVLWM+LbOAh4Odw/1vwcxDNYEhD5odwzucFr5ECvgmHHsI820TqUFo+Ov8IePdywML7PMXcHSCWHWQac2jlNrZxB8vHwO6CBJXqiMxFWfES39wGD7AWZfNTpC6QT/ZH7PLZuU0OEXOR5vUcZCjueU/LLxprpVFtCcKrHjmkWijpT5EP5rPHwOhaizRajyA1iLtx8gT5yHq+jqSYtwCXsla9QE+yk1HOYDlwPrO4mSN04GEyQa6TDfjeGvjWJhk83IMUa3q/q9YRlhcksBa8j8P0dXA1GL4lXzuY5QbYejusfJP5nMX5wAZuQ1KBIibCq9ux0kfiJQUuHIVON9QVqC0/D0a/C+4+dUwt6qiF1YvShKQU+UhVpAg5YlOQFt8iy8aNVCwe5RuM0oYkpivU1nwFeIB1ah1bgDKs7GOqWlMXlVxAHyNqqy1Ih1gSzT0mjztVbU1YLX+mem1ro2Dqg55pUDkGBjWKOFECbxrl8XvVK9iktv58pOhyUVCtQAvIScEPzoavbwQWgZi1Dh5+TBL42y7nG2xiQ1KekjVCh1G2twz5UHEnS1iskjgt/mhQLbobSFAnC9YDhfK5gLe5Uy2jugt5TwDiiuUovPnRFB4tOPn48eO6dC+EwOVykU6nOXz4sB5k2trayqxZs3RXhqY4CCEoKSmhvLycUCikP3F7vV4GBwcxmUwEg0HdUI6OjnLuuefy4osvcskllxAOhykpKSEUChGLxfD7/Zx11lkYDAb27NmDxWLB6/VSUlKC0+nU41yGhoZobm6muLiY+vp63UglEglcLhcALS0tFBcXk0wmOX78OA6HA6PRyNDQkG7MXnvtNaxWKw0NDRiNRkZGRmhoaKC+vp7nn38er9erx6Pk5eVRXl5Of38/7e3tuN1uqqqqaGlpIZ1OU1tbSzgcpra2lqNHj+oxLZo7wmq1AlBdXU0oFKKnp4fy8nKqqqro6urCbDZTVlZGc3MzZ511Fvv27aO2tlZ3KWnxOC6Xi8mTJ+uxMAaDAUVRdFKYyWTYu3cv06dP14mmFsMyODjI8PCw7iJLp9MkEgmampooLy+npKSEtrY2DAYD/f39gHQDzZkzh+HhYQYHB/F6veTl5bF48WJ6enoYGxsjFotRXFzM8PAwU6dOpbe3l7KyMvr6+vRMp7y8PBRFwW63c/ToUU455RQURdEzz95//32Ki4t1d1J3dzepVIpp06Zx6NAhnXhoWXzxeBxFUXQik81mKSyU0r/D4WBgYEBXQDSXlxaQDJIEuVwu/H4/qVSKaDRKIpEgHo+Tny8X0WQyqbvVtBghzQ2lBbhripkWZJxKpTAajVx99dXk5eXh9XqxWCyMjckXPx8/fpw33niDvLw8XZ3xeDwUFRXpY5RIJHR3ldFo1LPRDIaJ0LxsNqt/TiaTuqu4paWFeDyOEAIhBAMDAxiNRsxmM01NTScP4eFc5Yds5Su8hYkVpHkU+AZORhnnNp7kDsqQi+964C2VIJyBjGP4KTKm5xVkwPKjSIP+I2ADa4ClfJ+vUYZcnL9+BAZnSQPxDeC96+HnD0oytQEvdxHgO1SymD52swQDB/k6ER7gPqTxi+AUXukCuQ9YAZctFDyHH7Z6WbZSsIMOIB9u9sLXweMVBG9W4J4zUV7fzvKzpeELspbneYp7gXdehuzpYHhDZqltnwr8BCYtg+MPIMUT4N5yaVKagF9nwHohvPqKJDVFSJvyJPB8FM62w28zYH0M2r8qX/a3AmnAVjAR9Pok0nh9BpkF9BoLgfOQo7KLZYxSyIQr5igyl+kA8FpMgbwo0Aj8j2zBvnWSd7g75RXpuw8xHZTxTfKq9dmhchT5eq1bYHQduJ8CtmDif0izF7bPhuUlwFwWs5W9OKgmQhcdai+fQSe49/8MbtDe5bwUHj8T1p2LpIHfgDt+Kzu8/JB63lfUUQDYBoGDcnL9OIrUTbYh6cMP1DJuRYvImcY+lqpzaS/gw8ssAhxhCR7e1snOEbxAEgNpphDRs6mSSGVn0Ql/W5C8ZAUTcT9zAa/6jvmsCUwBJLOYKgnPMaOcBxqf0ajgMNI95VCzvswvQ/YsMLr8wPNQtQ56v0sbN1OrqjvP2eWIXqpWYUG6spYic63uBg5hJY1NbVlEHbtqJtyZFiYChfL5Lw7p7SkCZviY8G5tA+76CArPE088oXg8HkZGRjCZTLpbwGq18t577zE+Ps7AwICeYu7z+ZgxY4buvtDiWBYsWKATFi0rRHMbDA4O0tfXp8c61NfX61lFWipze3s7nZ2dVFRUYDQa9WyYRYsW4XA42LFjhx4IW1xcjMvlIpPJ4PP59Pic2tpaDAYDfr+fjo4OXC4XNTU1jI+P43A4aG1t1SX+7u5u6uvrOXz4MF6vl3Q6rWf5VFdXk0wmOXLkCDNnzqSpqYmRkREaGxvp6+tj5syZxONxSktLCYVC7Nixg2w2i8Viobe3l9LSUuLxuJ66Pjg4SEVFhd5mo9FIYWEhsVhMJybBYJBJkyYRiUQYHR3VFQC73U5hYSFFRUUcOnSI0dFRTjnlFOLxODabjb6+PsrKyrBarfT39+tlFBQUMDAwQH9/P1OmTNGDeDVVpby8nHfffZeqqiqam5spKysjLy8Pn89HOp3GbrdTUVFBT08Pg4ODelaY1+vFbrczODiIy+XS63Y4HBw5coQ5c+bo2XJaplNZWRmBQACTyUQgEKCmpkZ3+zU1NVFfX4/X60VRFAYGBvRU/HA4zMyZMzlw4ADFxcVEIhF6e3uJx+Mkk0ksFgvxeFyfK8lkkrGxMQoKCnC73boqEgqFKCgo0LP5gsGgnnloMBgoKirC7/cDUsXRAoi1a6UFP2sxRtr2DFrAukaiNEISjUYxmUwsX76chQsX4nK5sFqt+Hw+9uzZw+7du7FYLLrCdmKgsRZ/1NXVRWlpKR6PR8+w0uJ1tLR2LeA7nU7r2WRauzo6OvQsQ20bAI0UGwwG2tvbTxrC8yOE8iWWw9Y3JyzwFrh1reAm5GLbrX49Exlo+a1Zct38DNI4OF6G1Nlg/izwCIjyb/E+32NuEP7OIxfcf0aecyXQyj18lZuZgjRlcYwkgxnSchcDyuwy5udZEvw9DrLYqSVAF49JY74NPDdC8FzgFli/XLCBSmbRx5FOBeo6gSsp5218XAisgpvXsfgewe7tCiwPIA1vPufwBV5jJXApd/FlbtkPYv6vAbOaxn4Pyv6boQYSBfC2Ec5T3So+3kK583Tab5VRLTe1SjVgG9JwXq3+v16tbRXwHD9mPV9gKdLIbVPH9ifAApVUzAU2sxzpXHkFWMR8XmI/P0bW9Ajw9zD6LvPdgv0vKtJaW5CZ3zORLNR7P7BCBirPZ8LK/7t68RtKIOMHYwFQBFs7YOX9aotAEpP16gzQ6MH5ELgPvM1q2z4r27RpnezgNcCzvwXmQcAL3q/BjQ9JlvH5AHAF3Pxb6fV6HlhzObz0rJwIZWD4VT5ZmoHnMfBtslyOmSdJcTUwAyc38iUk2WlTR2hYnopDnY9bgC6Wo8WsmDmKgglBGhsZXkOGK2nqyAE5jWhiQrXLZ0IPK+2SY5vyyFExj0syA9ItpZGmJGrmXQwtWYyfXwuffUnBdKGN1JGEPKgMmsrlIZoemq+e8hxwng89R/2bs+AB6jDgJ4uJific8AnfgYE0RuIomHiMBIuY8P5W+9SORtRBsgDzPwLh2bx5s9Ld3c3kyZMxGo20tLTgdDp5++23cTqdWCwW3bAHAgFOO+00Dh8+TCKRQFEUQqEQZ599th7joSgKb7zxhp76u3r1aj2bq7OzE6PRSFVVFVarlVgsxvTp0ykrK2P37t2EQiGOHz+Ox+OhtLSUyspK4vE4U6dOJRgMUldXR1tbG8XFxTQ2NtLb26s/VWtP3yUlJRw+fJhsNsvg4CAzZ87EbDZjt9uJRCLs3buXoqIiFEXB7XZjs9loaWmhoqKCadOmkUgk8Pl8OBwOurq6mDJlCl1dXQQCAYqLi/F6vfT29v6OO6+1tVWPM9qzZ4+uQGnGOJlMks1micViTJ06lWQyqasThYWFBAIBSktLSSaTVFRUsHPnTt1ga+RTS43Xgni1QOzy8nKdFAF6oKtG3vr7+/V9XKZMmUIsFmNsbIxAIKAfbzAYaGlpoaCgQCcTWgZZQUEBY2NjdHR06KQhm81SUlKCxWKhurqa9vZ26urqSCaTeL1efD6f7t6xWq3YbDYsFguhUAi73a4barPZTHd3N4sWLdLjVbS4Lo1AxGIxKioqdPKWSqXo6+vDZDLpc8zpdFJYWMjw8LBOeLTtEDo6OohGozqx0DINrVarHqhttVoJBAI6oYhEInrdBoOBUCiEx+PRs7M+SDw0RUVTZC666CJqa2vJz8+ntLSUt956i61bt+rzAMDr9WI0GnV34fj4OENDQ3qsUmVlJaWlpXpd6XRaD1oGfidOTlN9AN21qAVoa/F3J+JkIzzFCCXIWiY2u7kbuJTFPMxnkHY0H2n2/mcHXLlsQjh/AC9KMMAujzQalyKfimMuaeC/6ANRvpJX2MoUtb4pu2FwsQwANY/DXg+cyls8yOnMA5aq6euXIslAG3A91yFF/K9gopR0Z1w+/D+URi7rFuZTwH4qobkXGqQbS5q+VuAZeOk65l8oqAY2cwkX8CK3AEtfh/qz5dFHDilcMFvozpvXkArWD4Hrge9iJc1ilJe388IFUpmZqdZ0x3eg8S44fCcwDx5dDf/8MqSXS/fbJhf8QyvsmibjbwD2A9OQRns3l7CaF5kH3PFZmPQM9GElTYU8ONAB3gDy2V+Oppl7SV2VhgMw7ZDq2vCqhZchuUgp8PlN0LdGCjor1Au1tkrW3PcWVD6Bky8wznVIKmFmGdtpA3wcBG5lNS+yGa96cqHa873w8EPyq+flQJR/GXxKJ/TVQWUzkIQXZ8sLeSqwfBSecMPnR6HZDQ1fBm6CQJ3sQD6YGmykaUdSAI1uaxsybcHJVu4EblRjVIaRhCWMdDXuBBJcAuRzDU+xC92RRxi5+8IgE/selam/VatDN1X9X9u0YMmYqvK8o3Y9qd4URbLPiQLwG1W316/kpF15K7x2h4Lhtnwyz0XInifjwiaraeUvqHO7CckTpyDvq8kZsPolubrCAs+hXVCNVsnPWtxOBptKdhJksPIzEpQhw35OTSJdyuETToWPTngOHz6sxGIxDh48yODgIIsWLeKhhx4iGo1is9k47bTT9NgTi8VCc3OznlEFcNlllxGJRHjppZf0AOOqqira29uZN28elZWVerDtyMgIHR0deDwelixZgslkore3l7GxMXbu3InH4yGVStHf3082m2XGjBlUVVUxY8YMfD4fyWSS8vJy/Ym2sLCQ9957j8mTJ9Pe3s7Y2BhnnnkmAwMDtLa24vf79Q0BNfeUEIL+/n4KCgro7e3Vg3zfffddJk+erLtHHA4HZrNZd2Voikk2m9VVipaWFgCGhoZobGwkEongcrkYHBwkHA4zPDzMKaecQktLi579prkvysrKaGhowGq1Mj4+DkBJSQldXV0sXLiQQCDAoUOH9Ninzs5O3G63HnsyZ84cfSPHSZMmYbPZ9HHW1Bzt87Fjx0in08RiMT2AVcsgikajlJSUkMlk2L17t76p3fHjx3G73cyePZtoNKobdofDQU9PD9FolNmzZ+vZUFrAs9vtRlEUuru79YygaDRKcXExIyMjlJaWMjg4qAcbHzt2jDlz5tDb26vHqkQiEX2fp7GxMd31GAqFSCaT9PT06EqKFhM0adIkmpub9f4BuptWI5cGg4GhoSFdVXM6nbrrSsvi0uLRhoaGdBeZpsSFQiEURdFduJoSabPZSCQSFBYWUltbq2fFxeNxduzYoWf0GQwG8vPzdfVO2wgxk8mQSCR08t7Q0EBRUdHvECQt3ujEe1lz0WnurWg0SiAQ0NWpSCSi7zeklaGpryeXS6tAuVWNjxgEXmM5qeh2XrbLtf0cIEEHxOrIpARvu6S7qga4Q91IT9sU7Xtd8KtaaTJvScIeC5zBQbRUZTP3kvRlpB2rAXF2HTvp5JtIcrEMmRf0D12QKgfzd+C278Od+JEhqymkhHELvLgOLrmdH3IHX+lUuKBOsBcI8jOOchVzMXIOGS5Figc+HlNdN5twcjnjGQWrUbAZOJ9jlDOdYSbiNzbqeTj/BCRRuvrAAivL4d+AeVzHOTzMHpDBpZuBpXCxR7qznrPDP5wP4hU3YUaxRuFf7fDvGLmbDHcD4zyGluR/AWZe5mdIw16Nk68xzhoktTwLSez+AUlIn4bHvbCuGS5v4PpNksfMRCYgr1JLeRLY40YSkhVqUQ7guoCqvlwFlMHD98F1jyPp3QCwiHPYxHnAv+JXS9W2udusXqkVantUyYIp8JRJ+imfBla+DZ1L5ORwq4oP98L37pPBSdfKi+2ZLQg+pcDatDy/TD2XRfCECT7/MBPOprlYcVADtLKcWrbzz2pft8lZwY+A/VRiIISDCLcgycVu6oAkP6SPuUi+/AIO5hIhX73mpci5OxM596cCn/FB1gEGLW5f2wtKk4CAA+UTHOhR4BHVNXvLbjk0kVpJnLTTd6n32gx1RHWiE5LDmXaD2V7JhNJmYSLdXCtF/mYgTRYT0xjl60yE4elkZ4QJVQe1CAtQ+xEIz1NPPaVoWR6a5O1yuTh48CD19fWkUikCgQD9/f1UV1frxiQvL083Zr/+9a91F9bs2bMZGBjA5/NRVlaG3W6npKREdxVpKeft7e10dXVhtVqZP38++/bt04mU3+9n+fLlxONx9uzZg91uZ8mSJWQyGaqrq/WN4bQnc80FdPToUc4880yKioro6+vDYrHQ1tampxLX19frcRn5+fnYbDaam5vJZDIcP36ccDjM2NgYFotFT3+uq6ujpKREVws0l1NBQYEeIKsFy2rqi9aPiooKiouLaW9vx+Px4Pf7KSsro6KigubmZsbHxyktLcXr9TJ79mz9d81d5PV66ejoAPidrDlNnXA6nXp2nGbUNDfOiTErWoyO5soZHh7G6XTqKdPhcJjGxka2b9+uKyzBYJCSkhLq6uro7e3V3YBLliyhtbWVWCxGZWWlHjNjNpuZOnWqHm8yNjZGYWEh7e3tGAwGTjnlFILBoL5rs9frpbW1ld7eXhobGxkZGdFdS+l0Wie2mrtRy0jq7e2lr6+P4uJimpqaKC4uZmhoSFdlDAaDrnLFYjFAqiGpVAqXy0UoFCIUClFbW6unpkejUcLhMBaLRXdbaaRKS6fX3FwnEg9tA0CQOzFrSpa2F09eXp6+O7Sm5mgqjZZlFY1G9YB4m82mbxz5QXKjKUha/VqdIAOVtc04tS0LtDihDxImzeV1chGebytP8j2u5gYMPMZ7RLgXKet/hQ7gHC6jk88il9l7kfZKizN4DVi0A360TJqlR5FmsAYo3Qg/vQauZgmZsbd52AXX8y1gBMXyOBcnpXKygjra6OQVZATH9lY4MA3mbkZanhow1jqYQYQj1CGjhNqBRazma2ymknL6uAm4nmdh+xpmLRdqsrLMqJJm7CL43rdVo/9lpKPtcyxjHwNIA/R8VCoyMZfsbxkLMXCMm4jQBjzHfXyfGzkVuAAposxQxyuCfGpfgTRqS4GZfJ7v8wRNSKO3meXMYjsPqF07FTfzGWX/wwpcdy4yDkdVN+64QVpxbWubtQFgMWzqkIX/FJ75tjSYRcitB28hyd1YuAmpHsxQx/RLn0I+9u9CMrQfqZ9/daOcCF+4D8+PBUEWAlNwsolTkQRYKitLmcZZtKo7VZu4hXRfHCrfVNt7PmytlBVWjgLfZ4IKJ+Gl6yRR+CrwSy1jS0tz/0+gG+6YLS9tXSdsrYOVcj8ezgvJMTioudG2AUtZxo26+a+RtdAN9GPERYYvIWmytlv1VCZcX/+CjIVapY6RJth8FbmNo7Z93zzA0cpEPrvGbJCTq0ndR0dTbizqZ2svDNZObCRYhiRTR9XTa5ggJ3VqoD7D0DQL5upJAMNMMJRqJOE3q/9r+elhLiPApWrTaoCzjjAR2qOdUqQerqpSeD4C4bn33nsVLfU2EAiwYMECstmsvpmetlAmEgmOHDmCz+ejrq5OjxXRFJvh4WFGRkaYN28eBw4c+J2N3KZPn66ny77zzjs4nU4ymQx1dXXs3LmTgoICkknJ9hobG6mqqsLn82G1WikvL9d3oY3H43R2duLxeCgoKMDpdGK1WmlpaWH69Ols2bIFRVG45JJL6Ozs1GNcNMNiMBiYPXu23ifNwO7cuZOamhr8fj/nnXceu3bt0gN3g8EgqVSKN998k3n/h7szjW6zutf9T5JleZYteZbn2XEc23HmOSQhnEACBRqalBIK5VwoFCgNEFqGpFCGwoFCKeWUlsN0SKFJyYESCEkIJE1CBsfEzmDHduQxli1PkiXbsizrftjv3jL33natc75dvJaXwdbwar+K9vM+/2eorCQQCJCens6hQ4dYunQp3d3dNDQ0qGwUma0zODjI5OQk2dnZfPnll5SXlyv7dSAQYHBwEI/Hg06nY3JykoyMDJKTk4mLi2NwcFCJpIuKijh79ixFRUVER0dz+PBhCgsLVfic3HBHRkYUSJmYmCAmJkYl/oaFhankYhneKFN9dTodvb29Ksvl1KlTapwTERFBYmKiYl1GR0dJS0sDQiOV8PBwurq6lM5Igk9pC5dp1NLGrdfrMZvN1NfX4/P5lB6qp6eHmTNn0t7erlK5rVarigGQIYc1NTU4HA6ioqKIjo5W4YNy3CTzhsbGxsjJyWF0dFSN9NxuNxEREXg8HuLi4hgeHlYCYJkOLt2JMmRRpkBPZVtMJpNi8yIiIpSOTQIRyWxJnZIEOvI28nHGx8cZGxtjcnKSpKQkUlJSFJMGKAAnox2kmUACWpnh43A4GB4eVize8PCwur36ENAYKQnmT58+/S0CPC8FTdzDLxFgRjh9noJdUVpa7A/I5h0+QXzmV45DeHgSsJZ2Xlfy1QeAhe/CXzeKjeJRBMSQOSV9tai42nnXi9t/l2gCx7z8ZK4AUfmfwx8vE1fsr2Jigh8CMVh5TqXmbgCuY704ePt7kLuV19jGbYEgfzfoSAUKKEdm0xp5k/H+ADqrmTRcIk+mvhrKfw73PwnP3kozr+NBcDn5iH35QZKYi5NjNACvEGx6icOFsIhbgD2MBbqIMHwGPMHfOYgFKBgH4x9Ad9dDzOUpVgO/5DE8bKOQ0AYn18UDHENs0lcjBLhhuDHgE6waB6DxFm3sUwpdd4MtD/iEWF0xFoQc5zBCk3L2SeB3cHOX2OsqERu+ZHz2aKfg87sJaYdTEIip2k4YpeiYIJEATiWSnU0o83cn4kzJdCXpzHsLoeiaOhYtQByFlPP+FQGFPfDOUrgxGaFyatYe84cCyK1vRLqMOFgsXsAr4mFMR8EXFPqsuzjKv2PAzwa28A57tJfi1V7jQu27HQH4UrSjm4aAETsJAUVJ2rQQEuHLr7UIATIOQrpg2UkxW2N/pDEKcRt/mcjuCQsIt1ULoUjAcULC6VS0vO9j4o+vVME9mJhgeujBMBJidyRNIyHUOBvZpYo21gIpZwkBMwglLsaEHmYiEsKi/geAZ/PmzcHY2FgiIyMpKiri4sWL7N27V214MlBOakYkI9HX14fdbldXznIEJUPl9uzZQyAQYPbs2cTFxbFv3z4iIiJUfcD58+dZtWoVn332GVdffTVjY2MqTTg8PJwPP/yQiIgIZs2axVdffaUSnIPBoNqgJUtjt9tZtGgRXq+X999/n/LycoLBoBKBVldXc+HCBVWNIFN/582bh9FoJBgMKjt8bm4uc+fOpbW1VYlz5cbz9ddfK4bjzJkzFBYWkp6ezu7du9XoaWBgALPZrK7iCwoKiIqKUpUNer2e7OxsUlNTsVqt9PT04PP5VN+Y7LAqKioiNjaW+Ph4hoaGOH36NJmZmcTFxdHU1MSMGTNUb9Po6CgDAwNqM/X7/SobJyVFZFHI/BoQG6nMPoqPj1djRDlikvqsiYkJtYYSAERGRhITE6MyeaxWKw6Hg+joaGUrl4nCPp+PxMREFRyYlZWl9DSXLl1SKdYul4u+vj6qqqoUuJE6n5ycHNxutwozbGtr4+LFi6SlpSn2pLGxUQE+aUXX6XSkpaURGRmJw+FQrInsBpOVDTKhOTMzU/0uJiZGgYy+vj419poKNCS7Ipk9OfaS7xXJtMlRo3yfTWXdpKNLVp1MZepkaKJcC/lzKsszOTlJQ0OD0up4PB68Xu83HgP4BvsXExPDtGnTePPNN79FgCcvCDHspJ5HER/2CH6FcwAAIABJREFU9/ZDi6bLOUGoy2cPQvdgARoD8Cet/6cAARR+hti6TiAu1EHkzei/EA8yUQ5NUdoV8Gb44gVY9jw8cR88XAt/q4KrNsBPtsNv2wAHzJwLpz4EXgDdARuwkGzepwDYzxcAfMQy1vIxd3ElP0IAlxpMTLAFsdGWIiDWR0jbbhj/BcDEq2Nw+zts5AeqH+tHCABxzB6kKldHOOKqf1kb6LKvoZBdXDgEKxfDfm7nHK9yQhwuD2SBzx7a6G5GbOv3IkDNb7V1OsYastlNG7cAA5jYJYL3Gt+D4ivFkdx/USxsKnDN60A4jN5IWGQEE++PkX2DeGWfFiNOxAPaondA7EswvBXKtoYs108j9r7zwE9tiNHTfdryvD0CnKaQBeRrt4nRXtMgIidrkmRCJQcHuB4nO8jFhJ05wCElrl3F9exiB+XaK/6hdp//QLBD/6GBqRhgNlZ2MQ04pEDmx9oRO+Cdu+HGRninWOCoBq3uwhUE8wxw1lGYpCNGOzLJclgQWOkwAp9s0s7+f/bDD61iqXZqt5XuqJ0I9+E57X6rgRs0tkZlSslWDq+2bg5tsQZQamd/trCW6wNC1NxCCH/IQpNUNM2PkKCRk4aoSlGiZLnOkqYZn/ItWLN1vKrs9WvRgJMXldujnP9M+RkOXitE8z+oloiMjGTBggVkZWXx2Wef4fP5mDdvHvPmzVPdUP39/cod09fXx5EjRwgLCyM1NRW/34/dbqeyspLMzEy1QUox8sWLFzl8+DApKSlKa+B2u5kzZw7BYJClS5fS2tqKy+ViaGiIt99+m4GBARYtWkRiYqIKwDtx4gRHjhxheHiYrq4uzp07p3q7oqKiuHDhgtKKyOqE9PR0FRpYWlpKRESEGh0EAgH27dunWKq8vDxWr16tGJDw8HA1apAbZmFhIadPn6akpIRp06aRkJCAzWZToz7Z35Wdna2qKBITE/H7/VRWVrJo0SJWrFhBRUWF0mykpKSQmprKvHnzFEMiM3kmJyc5d+4ckZGRrF69Gp/Ph9vtprKyUmkz7HY7x48fp7u7WzETg4ODym3ldDrVZi81JyBGZFL7I3U7EiRIBkjWEkh2SDIT/f39ZGZm4vf7uXDhAn6/X2XwSEbN6XSqoLzk5GSioqJwOp3o9XqlD5IBgB0dHSoB22w2ExcXh16vZ3BwELvdzsjIiNLPuFwulWo8MDBAIBBQY6fY2FgVGDg5OUlHRwctLS0K7Em90rx58wgLC1NBlVKrZbFYVEaQzMWRgEUGRcpRoXSFTe39kunGks0JDxdXM9IpNbWoVCY5V1RUKKYSUCWrsl4CUC4t2f8mAbVkFqUTTbJ2UzN5JAgzmUxMnz6diooK9R74tny9iZ3g5/VYgDNN4nc6q5n/hfgs1yYnbCf0oX0MuFHr8zmNuN4HOMQaTgNbAwJWvAXY4+DEOjg8Fz6MEmDIdBEee0F8Lq+8T1iseUtsNCyHF0ZAlz2f784Vz//HdcAfwD/SBRwgC9h3DK5gGdDCRmAuV/Iyb/MWYqM7gg8at/IR9RjZiZ6lgJf7eJ27eB8AGz64/UrgN7zLSvxAG3fzCH/iGGZuzhUi52PciAN4KxseZRdN3ELPYth3FoJtr9KircEDG+CLdvjAAKXHxHjkXeB5biGL9dQyn0X8nkzQwM6zQD7YP8DXFaSQ96H4HrB/TCx2MXG7/Qdi0Vy3AOcg0s7EL8agRXAqn34MNOyF3veFKDgGuAmG3wb2wNkkwWpsQmyfyxlnLbCzS1soScA8FQW00KStg2xfmg0sx0smXlZgB7zE8j5QwQngCuxYEFgA4Md4KWMXJwDBm7zCCuwY+RoBRX/EBIlAFlV0AQMqZdiEk2OYCeNaAGK5B27sEi/kxucgBn5HnhjmmMU5JMmuBMuynWsAsdffhgB5IDBJFvA3qwAyWxCg1kIom0fyWFIeHINw5dEudDW+WTCRhEArCdqD9mj/X6D9P0KMrw+IIEONq1KJz9qElswm0J+HjmzQpeXSxkptvRK0VZdPEq79jNYeoRTB7LyqDAU/6oaUJlS7BRAqEZMH4BBs1EorxLCEf/T1TwFPZmYm/f399PX1kZOTQ0NDA4ODg1y4cIGzZ8+qxFapaXG73RQVFTE4OKgyPlatWoVer2fHjh04nU5qa2vxeDxqDFNRUaFSiSUz097ejtFoJCUlhQsXLqgahPXr15OamkpRURG5ubnKfp2enk5lZSVDQ0PMmDEDg8GgNtmhoSHV3C27tmw2m+rWMhqNuN1uleUitTlpaWnU1taSmJjI4cOHOX/+PMPDw7S2tqocE5nRcu7cOdW8bTQaSUtLIyUlhdbWViwWiypxBLHRtLa24nA4yMwUunlZHtnS0qJCCMfHx/H7/WoEBlBVVaUawgOBAMXFxXR1danS0sTERJxOJ8FgUAHRiYkJWlpauHjxomJoZKWCXq+no6MDl8ulbNxyA5QCWpkWLNmbnJwc4uPjleXZ6/Wq0YzP5/uG0Fpa6mV9RCAQUONHqYXp7u5WScISVMlmc1kaKlO16+rqOHPmDEajEZfLxfj4uHKInTt3TiVT9/T0KAAu9TpGo1EJrCW7IkdRly5dQqfTkZ+frwTq0glos9koLy+nuLhYFW9OdWDFxMR8I0lZgiA5upIgS47TJGCSAFHm9YyNjalxm6wviYuL+wYgDQsLUyySTNHW6XTKTRYZGcnAwAANDQ0Aahwo+8ekTmcqCyTBtwz5/LZ1aZ0A0i8TGtI/F4oN4He4WEbIgRSOGI+cRthmZbrybcBf+gUwmkM5W9jNY27YaxCDigTE5+2/EJIQ3BCAtwrF3xb2i7SZJDewFh7ohp/9K0RFGdjIUVKR6hFx1bwpCoLHnHiA38yFT84CrGaYlZqL91oeQIy95pALxTWsZQ1+NmjsRArP08vLzOdFfLSehRXsxkoNhezTHmM7cBicQ8wGPuSkOvoDwLZPAXZyNaAru5F/yRbrkcU16Lav5HdyYbPEuq3mds7xOnCY6zlKFXewg8do4wiF3C9WMzcPHNC0OwiBFyHXyTA38rtcHWx7G35VgzUeuPxJuCdXaYVfSALWdCHg5QAsuR9u3yoO9zrgSCM8Dy/nwp3VUGmGvxJOCoI/KLtH+48YBHqiFPgl+1nCfpLYoL0HJMMnpjYS2sRgQWhiNyC2Z6vWIi/1MLLTyQH4WUho3PUAsdQzAGRrFRAgwx9jeBEfcEJLX65CcC8VcPIl7sTMG6wnjJuAdqrIY7t2DKvFrbAQAi8xiCSfTMT79GZCchwHIRao4pA4X48Sqrxq1r4nqkWh6JABuqMISWvktOlrvtH+6Y8VQZUgjfEh0DMroIETD/x5LmRprzl0tBLoSHpmXFtlqYf6M1t4Vf27+F6TdjxauKEaXclvxEM8UQWGuFz2s55Qk/r//fVPAY8EI1MzXRITE1m2bBmLFi1S1uOoqCgyMzP5zne+Q2Fhoco+KSgoID4+noMHDxIfH4/JZGJ8fJyoqCg6OjrUxis3pIGBARwOB7m5uej1etrb28nIyCArK0tR8h6Ph4mJCQoKCpg3bx5z585Vm9aJEyeYmJjgyiuvxOfzkZycTE5ODgsWLGBycpJ58+ZhMBgoKSlRyc61tbWEh4dTV1fH6OgonZ2dDAwMqI1W9nv5fD4KCwuJj4/nL3/5C0ajkdbWVo4cOUJXV5eqtDh58iRDQ0P4/X76+/uZM2cOVqtVBQbK9ZLjFavVSk5ODqWlpSxbtoy0tDQyMzNVerHX61UjjbCwMCwWi1pjl8tFSUkJFy5cUBUCOp2OhIQEkpOT1f9brVZiY2MZHh6mvr5eWbgbGxsJDw8nIiKCuro65d6RYycJRKXVXSYJm81mkpOTmZycVGnUvb295ObmEh8fT19fH6Ojo4pF8Pv9auOWjqeRkREuXbqEyWRS9zObzaSkpKiGccmsxMfHq9BKn8+H3W4nOTlZWb6lOF2Csp6eHtxuN3a7nd7eXlUJIYXDxcXFlJSUYDabmTVrFqmpqSQkJOB2u9W6lZeXY7FYSE5OJiUlBbvdrsIO3W63AnBSUyNt7HK0JcMAZd6SBIiAGmtJM4BMvvZ6vYpdm1pSKm8LKGGxtKRLd5XUK8mAy8HBQRUFITU78nmNRiNZWVnMnj2btLQ0EhISVJihfJ5vy9fLvwjSPRqkiRe5C/gRBjYhyIJHER+3KYjN/jpgNSt5ns0sQti1n9BGX8FP65kN7IoTV8wHEJtlD+Jzdw9i09lrEJvJW4jI/izg9Tj42WUi0O3f2mB8U4B3eYg9wFp7kGnczc3h8C42/FXio/+n/Ik/lwFdNuAPNHE38DOS3PAGKxFZNQCb2MI7wBnu4n5kgst9wLwy2M+NuDGQhYynWc5dvE7wSuH6eoFZBM++pF6D7oolvICLrz6HYOU7fNImRjnr2MUV7GM1sIG7+WEatGIA/o1p1LGOLnY4g9Ti11YXmvg9gi+7V+y6a7rA8BwkJ8HlbwuW5LGtcE81/UGXADrnEQuukJVUhogWsjCexpqrIztSBzwBN9rhkLb4zwvnVhECsP5W3t2hLcv71YQ21hje0s792inPYsTBMDbmskvpUgYIMSRZwCmk/m0nc+niLDbtNQsICBsYxqbuv59c2rABy5lLF3eyRDuoCvSMsI6DhAZVPwaWM8EK9EwwgJjebEfAIikcF4LkJNoRkOktZH3IfG4jl2PYaONX/BrB9ugWb+aPU97rWdoROxB1J6mIpnIAUmHCRqiiqlJbpEzxO8OYEL5LQfVqBJSs6AdTnVisn1TB94kmlJsszfFTHVnyBAlUms09PEON0iPNPkvoK5zQ7HIcBcq+qAJjtolHuEa8z/gRIU72//76pxqea6+9Nuh0Otm8ebPStrS2tnLx4kUWLFjA4OCgSu612Wy0t7fz+eefMzExwb/8y7/g9Xr58ssv1UYAwl4dHx9Pd3c3VVVV1NXVMTQ0RFFREXq9nnPnzjFnzhzpFuHChQssXbqUjo4OvF4v3d3dXHfddURERHD69GkWLVqE0Wjkiy++IDc3l6SkJEwmE11dXYpBkSnK8+fP5+DBg5SWlqpjam9vV84haQ+Pjo5WouWp7rOwsDA8Ho/K4DEYDLS1tTE4OEh0dDR9fX3Mnj0bl8vFwMAAY2NjtLS0MHPmTIqKirDb7SQlJXH+/Hny8vIUq5WamorZbFZaoLy8vG+wHtI6DSGxqmRSpE6np6dHJVhnZGQwNjZGXV0d9fX1Sq8RFhbGpUuX1LitrKyM2NhYPB4POTk56nXKwDyj0aiAaWNjI2azmdbWVvr6+vD7/Xz99dfo9XoSEhJITExUEQVdXV2MjY0p0DkwMEBpaSn19fVKmF1WVqYiAGTeT3x8PAA+n0+xfBERESxbtozOzk4uXLjA0NAQsbGx6jx7vV6cTqdiOmTcgNSuSEZFgidp/46MjCQyMpKhoSG1yUtGMSMjg+zsbBobG5Vd/8yZM9hsNlWrIdmh6Oho9X4eHh5WvVpyhBQREaFGVZJpkUnM8hhlFUZmZqbSnslKCpk5JO8HKHZGsj4+n0+547xerxIpA4pNkqApJiaGkpISYmJi1HFI5keu4eOPP/6t0fDQrwv6Y2FnOGxwBtmSpGNrAH5uEDqc2RiYToBmYDgQZKdBpzQeWkYhqxH79VSnzJsj4mpY9h0OInuz4YE20GVXA9HczEH+4134zcYQC3TTWTCUicDBZ3DyIDa+pouKWtBV/Z5s7qCNcvwj9RijNgPRhPG0KJZ8Lsjjm3U8Qjm46sA8i3XUKGfM4yNwW5QAb5mILqOzUVDZFQRbPfAoG9nFu6or61cE3L8gPk60u8tS9kdIogonnyAYqvo4YXUeQDz2DQGoM8hGaxtQCq/uFVZyngAWwuu3wy0T8FSYuFy/Hqqc8HUMPOyBx69BCEA+QXUscR/wwW6qdGuobQCK3+EFfsAe8YhYtLu8BgyzEngenOXixOyBtFuhuxqsNYL5aAYeb0CMZAxbgR6u51V2UA2083eceBEkRiWwEeinnDTqReiktiYy1VdmKFcAL7OGm9nNG9yNaFTfRT9LiOUgw/wKI4/i1wYzRj5iBQEOa4dSy3ognyt4ik+pJhQr6GAFuzmIAT+pLKZLpVy3I0D274BhFdzYrq1IKYvZxyHeYzE3cIjHtL/fhxghnedRutipPdblU+4tFTQJwANnoaVM1E7oJ0DvF7UpqVquFA4gBiYT4GgczJW3GxQPMmGDDVGwCxMTFCHATLj2bJIykv8S5Nc4G7mfCm0FrnGLcZhKBBA5hCFGJ1ykmc8FTSOWr529c8g+tCBJ/30Nz7p163jkkUcIBALU1NTQ3t5OIBDgu9/9Lunp6Sp8TgaoHTx4kOLiYi677DJ6e3uVfX369OmkpKQwMTFBb28vbrebmTNn0tnZqYIE5UgiOTlZMSsJCQnk5eVhsVi47LLLsNlsrFq1ipSUFCoqKli2bBmBQID29nZSUlKYNWsWRqMRq9VKZmYm7e3tOJ1OdYXrdDqJjo6mtrZWHXdZWRk9PT1kZmaqUZe0WXs8HqV3kWLolpYWwsPD2b9/P3V1dbhcLuUAknk7LS0t9PX1qZRcp9PJ8PAwAwMDdHZ2MjIygt/vp6mpifj4eCwWi+qwKi4uVoBm6nhJXtlPTakeGRlRzI/Ut0h7tGQNZIWG3++ns7MTEInBvb29dHV1EQgEFCsjLeeyl0kma0uWwO12c+nSJaZNm8bChQtVWq/sa5K6qfDwcKWb6e3tVSAyOjpaJTVLEDc6OorFYsFqtSoWZ3x8nIyMDGJiYhTI3bt3r+qhio2NJSYmhkuXLtHZ2alKVCXwls4zr9ertEBFRUWq701WbMhzHRERQWVlpbL29/f3U1dXp56vvb2dqKgolTWUmJiotFyyvkICKKlvkoyYBFNyneRr9/v9qk9LuhIl0JHONXnO5YhMful0OhXa6PP5aGhoUI6zwcFBBayk80vetrS0lPLyclXqKvVBsiNvqjD62/J13grh4bewgXK+ThJgJskAz7OZSjpZQoBakkgFHjfo+AixXd8MbGINyxEumHHER2mp9v1GFORjoJSQKHQQLdTt1wAHeUYbZzyhlXf+kGhOg9gwiILGXh5kPn+ni0rKeagKeO527gUgE2PUF9qr+Ctr8Ilr4s31fAasoF7oPLadVOzD0zxErQZ2YrTj1k+I58626djIDEzsYg9wHy6+B+zkF9wTB28ACw+JZ3uEG7kPJ8fGxeveF6cgDA8jgM9mA8xhJf/RBkrkcfteQmqOtXBLl8iaeagLw2pgtdhU/+ARt5qzC3R2eCEDsmsQ6KkAeGkNZ8KA4i4gk5+yhE+xKad5AiLI+FH2kc0MkbezE/irADvkixHQb+T5WAGkaQvPQlIB+DdicTJHE25NQ1UxYaJeOZu8COD0EfApSaQQKussYzdvEY2AvRtwYQI6tHGTBz8btHfFafy42USIDRFrdhuHgeupIY2D6HkPq9asPo+ApgEScEa6rbcjkrvRXoUY9wn25BC/x8hGDlFOSIE2G/CSTZfm2LdxLaHyhusQAEpWTnjLICMgqiYCEcLxJLVtgOr/qI8TgYVhLu33MeDLg7VR4v02QRyhDneZyCM5MolchIB5hQZ2FgLX1oL+NKG54TeeHLxV8P0ySOUa2ngbweqsRgY0iDP5f9xpypdh69at//CPx44d23ru3DmOHz/O/Pnzyc3NZf78+ej1evbs2UN+fj4mk4k//OEPin4fHh5WfUV5eXlER0dz6tQp3G63ahKXVQ5tbW1UVVVx+vRpgsEgiYmJpKWlfSOLRoKN0tJSkpKS6OjooLCwEJ1OR01NjXKzpKWl0d3djcPhULbn9PR0+vv7VVggoJ5/dHRUbbayo0qOPIaHh4mLi2PRokUMDQ3R0tKi9DCzZ8/G7XaTnp6Ox+OhurpaXcUnJSXR3NzMjBkz0Ol0qmQUUC3vmZmZZGVlkZCQQFFRkQJEVqtViVwbGhrUyEKO02SJqtRryA1+qiZHZgpJIe2ZM2cA1LhQZsCMjo7i8XiUiNlutyvQIR1UMktItnS7XC76+/sV4HC5XAo46fV6lUUjReHSji2DEIeGhpiYmMBisajRkRRg9/T0UFBQoMTYMl1aMikyCFDqhOTzyFweWSba2dnJ+Pg4Q0NDKkAQUJ1W0gUmx4HymGw2GzU1NSpuQQI+n8+nGJzJyUny8vJwOBz09PQo0CTdZ9Kt5ff7FWiQDesgWCuZTwUCdEowKy3n0qofFRVFTk6OcrtN7cmSgAigp6cHu92u3Gyys06ODSVrU1BQQGFhoRpd6fV6pR2aGjgob79s2bJt//BD4f+zr9ls2+oilhWcYCHwHe5m/Iav8F+5mg3G59kGvMYIawAXcKV2v2nAGZr4ADMf42Mf4kp4EHADPyeJv+BhcQAq9PBzQu6Xv1wJ9VRwPzs4A/x6BBxGaMXPKeBn22DbFd+Dm6/mo40/4iogwDYsfEzjggL20Ay4CTb9mm1Rh8H4GY0k8DV3ANfQzj4axzs5b9jBuWXjNJPDeeoYJcBr/IBK/s4dCGJ/WWuQfYl/xDk+zEyDuA5uQexbNuB7y+G3N8OTLGFb9ghljPAIddzJ3TzqO0bCKfh+BlQjtqorWI+DX3Md77KPZWyL3wgYgFOw7RlY9i7sehBKpgFrocoHmAkmRvD5U7B1PnxUAfObxHYXGIcvgFHAk4fYuy+J1m6+141AK7FsoZEAME877gBi27wdWEcd7rnbaN64EP6QT+w+seWtQWz5dw7DR/nAHYXAAY4jEqxjOcbdWrZMJAK0zgZaAScmbiVABeAEPmQN0MoV+NhMNVl0Mx84xCzSqMHHB1Tjx80QneQCXyH4oC6sfMUo4+ykGxNDmIFKjlFPLWm0cQnIBbrQs4IAp7QVdSHGc5MIPHcGExEEcJGunV03ArokAPt4lJ00EKSQXmJpo4xjFHIRO5ksRVzsxjLMOChjuBcBmQ5q69UBWPWgi4eAASLc8OcoKDdAeBeQBKezxbkzacnRvQlwMgp+phdr58DEJJXALdojmrXvce3M5Wpn73ds599JB9YD0z/UXric7g1oNx8VD/OTFXANudRzk3aPHO2xNA5sNBb00aCPYiv6/+dn2D8daf32t78Nyg9fGRb48ccf4/P5WLlyJZcuXeLw4cMkJCRgMplYunQpvb29Sr+wd+9e9eELUFBQwNjYGAkJCQwODpKamorP56O+vl5deRsMBpYuXcrY2Bjt7e0kJCQoB5HNZqOlpYVFixYxOjrKK6+8QnFxMYmJiapPyel0UlpaqioNZDWC1WolMjISk8lESkqKcjLJ1GOn06k0IPJqXWpnpPX3008/pbKykuzsbE6dOoVer6ehoYHi4mLq6uooKSnhyJEjrFy5koqKCmpqamhtbeX6669XbqLw8HDMZjO1tbUqaDE8PJzY2FjsdjtGoxG9Xq8AgcFgoL+/X3WFyaZsl8ulslamJkAPDAyoTfL8+fMqDLGhoUGJnQOBgMqwSUhIIDw8nOnTp6vxnWQcpuqChoeHOXz4MGNjYwpYDA8PY7fbiY6OVixQVFSU6tDKy8ujr69PBVZKa7isvfD7/bhcLlWrIUs1pTNMskWTk5O4XC5ycnKoqakhEAgQGRlJenq60iNJPY90jI2MjCiGSII36ZQaHx8nNzeX0dFRnE4nDoeDiooKXC4XTqeTvLw8JZRPSkoiEAhQUFBAXV0dJpMJk8mker2kJV++f2TA39jYGGazWbnnZBaT/CmP1WQyKRdcWFgYkZGRai36+/sV6zI1N8fv99PR0fENh5fsS5PlsQBZWVnYbDZiY2OVs0u2uP+f4EmO/QAefvjhbw3No2NWcDE1HOL3vMAd/BEx5e8BnuZGjGznLQIq4P8RHtLuuYidGvz5DSEb+l0IlmMR4vP4MILlz0IMJVIRm2YldwPjWHmVBxDXnimfgy4pSLBeh27j74E9fMQuxoHr+BWP8wumIbRFZ/ES7I9GZxW1E9fzC3YwBPwrAff7GOKOADGwu5yb1+jYDvhIIpS48mPtiA/D+x/A+i/RcyWX8JJyDB6aK477PzYB22HluLAyryaX4IN24p6BYeYT1B3lsyBchYHPCGAEvgt0PxXkvod0PE85cC9jgVuJMLxIGfdwFi22t3EVFN+vrVg7BMqJDROswglt/Z5GsCc7YyCYBIV2aEoCqxP6bwd+/xLwEVb2qeyZAkJaWq+23r8BDlENPAA3rIflkH2H0CpLcfomG9BpB76LngYS8KpzE4MArBaxHLRov79Zu28Ta9DzJRV4qeUx7mIbrxDNJD8AtnMFLg4APm4hZB+STIaQixv5iCICrNZ+ewI4xHyyOQqETNmDRBONl9WE9Da1JLEYJ4ewYaWLfnIRdn8XleJVcx/QRi7PYOdBVvIM+7QUZhE10MSfeIZbeRgD3ydAlrb2mdq/h5u0nz+aciwd2rFe3i9+cT5NHE9YACYMoSb1NwnFLIrKkBXakcvIy6kya4jlBzyMAOCX70AQNHLG1kFING0R46sMTEyoJCmpC9Ik511hIVJHo8KCkfz3c3g++eSTIKCu6g8cOIDL5eKqq66iubmZmJgYlf+xYMECRkdHOXPmDK2trXi9XlpbW1W3kgx2y87OVnkx7e3tik5PTRUUncViUcWUHo+HjIwMdDqdatROTU1l2rRpqn/LaDSSkJBAT08PQ0NDFBcXq+yT48ePc/XVV6vRhGQjiouLiY2NJS4ujoMHD5KVlUVzc7OySQ8NDSmGxOPxsGTJErq6unA6nQwMDLB48WKys7Pp6+vD5XLR3NyM3+9n1qxZDA8P09nZSUFBASUlJbz33ntYLBYKCgqIjIzkyy+/JD09nYKCAmpqaliwYAHDw8OqB0xmv1RXVyvGwWKx4PF4lBi5vb1diXAB4uPjFSsh7fIGg4H29nba2tpwOBxqc5dCZAkqLBYLxcXFhIWFkZODLBGlAAAgAElEQVSTQ0JCghInp6enfwOIdnZ24vF4OH78OJcuXaKrqwu3263cQpOTk1itVgoKCnA6nSxZskSVt0ZHRyu3mc1m49KlSyqReGxsjLy8PHw+H+fOnSMlJUV1YgEMDQ2pcZh0l2VmZiqbPkB3d7dyycn3tASEcXFxpKWl0d/fz+DgIBMTEyxcuFAFGU4NEiwsLMTtdqtm+LCwMHXsVqv1G+9pyZrJbjR5fDqdjqSkJCX2l5UfEtDJwEbgG84rOTLLzc2lp6cHs9msAKgcZY6Pj9PX14fD4aCyspKJiQk++eQTpQWSPXClpaUqeVuCJvk80m02ldXR6XQqP+jBBx/89gCe3QTvW6Pj39pAl70GE7v5FFiOGSMe9AQ098y9wG0E343nNxvhpzxGFduUbqQZsfks1245h1sIdr/OY2lKPkI7QjQKQM0RqF7KYg5yOfAIb7OFH5CPmHg1PRdk3WYd/3UWdGUrAS/bOcorwCGepYr7OekW9L5ucTU7qeFN7RgeQGxML88IQt1exCxoOXCaWF4nC6H/jUEEDnsQmtOXWSI0RZ+D7jJZRTGDc9QzjV9xPb9gE2Lz+i9NmOvvmuB3Np0WGPe/gEy2cz/fWwu6G4KU3SjGhB9yN+t4iU8w4Jeqp5ohqG4EwqExV6DDAai6H2rvBl6sx2gsJ3FCbGPHwsDvFz1+vJqk9VZNAA9h4jlWI0DIbLQkl374zArLx8H4NExsBmPUZ/D6KrgPdAF42hMiCzzA4zcCby9gLkc5h5APLWwSjNLBOLH5H0aM8PYDWbzIXO4hAfhUdZ6dJgRoREqT0F19hpACazkDPKq9Cz08ym7eBDq0AlXNXc/DGAgQQQJe+sllMXaOYsKgjTAHidb+dg0CCbRzPU4KgKe5mzJeUhBgJyG57odsZgXPaVqgGKCAFdRwnFAS8jHKCeMC1fi4V3uPS9ea5kBnj7bmUnacqa1VIAI+Chf36SCEU5qBYZIQUPaAdi85CEzVHnkPH/E6V7Vpy3ha+9MAShgtAxANhdFMshQBdWVbmGZYd9rE7aRNTFZMjEOw+n8AeK699trgHXfcweTkJHv27GFkZIRFixaRkpKCx+Ph4MGD3HTTTRiNRurq6lQ8/xdffEFOTg4AOTk51NXVKUt0cnIyhYWF6oNcWoUHBweV6DMzM5Pm5mbGxsZYsWIFnZ2d1NbWEhcXx7p169RVcVNTkxpVyEyV8vJylZjrcrnIyMhQ2hOpWYiNjSUrK0tF7gcCAc6dO6dcaIFAgJSUFJxOJxaLhebmZvU8iYmJ7Nixg02bhPWtpqZGjckOHz6scni++uorFixYQGFhIX/729/IyMhgeHiYqqoq6uvr8fv9qp4gNTVV6VdiYmJwOBzEx8dTVlZGb28vTU1NFBcXYzQaMZvNKjW3tbVVFYhKkbDZbMbv92MwGLDb7QwMDGC32+nv71eshMfjUc4hWesRFxeH1+tl06ZNqutp6hjJYrGoMeC+fftoaGigpaVF1R/I8ZTFYuHaa69VeT/z589XXWdms5nGxkZyc3OJi4vj7Nmz5Obmqgbx/v5+ent7sdls9Pb2KoeSz+dTuTNSNyQLUWW5pmS5ZGWDdLlJfY3FYlFgROpp3G43SUlJKr05LS2NYDDIyZMnSUxMpKSkhPb2dlWhIp9L6l1iYmLo7e1VLJIUqsfHx/P973+f8+fPU1NTw8DAABaLRYmrJWMqmUur1Up/f7/KpxodHVWsWVpaGhERETgcDhwOh8qFGhkZYf/+/d8AutHR0VRWVhIZKWq5p+p/JDiWtnnJnMnRKYTE0N8mwPNndMFUYDlHWMECbgI2BYJgeJKb+YWSTz7P3RzgJZbzHh5uoBkhaD5NgOlEM0kYG3GRhbgy3081Mu/3Cm0zthCCHk/zLOu4n3BgByfJZpYWBQiV+4KwchUk7+WuXh3NiKvjJlYSyz5N1LoEoUSRJQ6ye1xqFTLFM92qUSZr9hLsvpwv0mA5a1jMbqHlcNZxfZKOtcAmqpHql4+o4aoPQVceJBihg9dg3qPwVa1w2LzMSd5kFps4Ca5qghd16KouAt+FwEmCW3XoHl+JuEbfidh1ZiOSedYBa8G1Gcw1EKim0KCjiS9g1lJuroE3yoH/BMrvgRkvkl0vQEz3fOAczHEJUNcWdGIimQcJaWdStGcNC4g8GGObKC1d+CkQDb9eDA++GoQtUOYSAHGPtnI9wB+uBP62lWDTNnx5YGpA2K3LYCAcUnbA1dcLH9x24MH3g7A+Hgm19NQwOeqByB9o5+SXCIiUDwySTQ1taqAmHElzqaeZb3qU2glxQdOm/O6S1lY/DvRr4nEBph9DwApZu3BY1HZQzmLqOcRKRJjCHtZpKeH9bAaauYJdnNb+2g78pwa0JqnmBQ5y5zhkh4tXeCeC+clHAObZ2it0ALNrxTqdCxdYQxaESnH/aQQbtpHdvEs5BOrEHW1C7LOYeL4H3O4G/UOEEhJlo6kHKIWrq+BDcrV/TZmEkpOyIJAb0mpLJ5m02QFYIJj7/wY8/1S0fOedd6qeqJkzZ3LHHXeo0UtkZCTr16/H6/VSU1OD0+nk0KFDdHR0UFJSwsyZM6msrOTIkSM4nU5lqe7v76e5uZlDhw6pK+L29nYGBgbQ6/WqTykvLw+v18sbb7xBT08POTk5lJeXKwq/qamJoqIilQws82YuXLjA8ePHvyGadbvdTJ8+XRVY/uUvf6Grq0ul7losFuLi4lTzu7wyj4+Px+PxqCA82aQ+e/ZsnnjiCXECFy8mKSmJo0ePUllZqWoJrr32WnQ6HQ6Hg1WrVjEwMEBvby8HDhxQVQtyxNPb20tjYyMmkwmLxUJpaalqEI+NjaW4uFjpburr65UF22az4Xa71ehpaGiI2tpapRex2Wyq0b6goECNySRoMpvNio1JT09n6dKlqo9qcnJS6bHCw8NxuVzK5TVr1izi4+NVLYIcuZSUlKjuq+HhYVVAKsGQHONIC3h+fj5ZWVmKmZA2787OTmVhl04sOeoyGAwkJycrBkhu0lLkLRkXKfiWf+/r6yMYDBITE0NycjIGg4HU1FQ16hkYGKCpqYnY2FhKS0tJTU1VDetOp1OBHulKTElJUcBHlo/KTiy5LpcuXSImJkY10ZeUlFBZWamYxIqKCjIzMwkEAixZskRFMFxxxRUsXryYFStWkJ+frx5v5syZLFy4UFnuIyMjycjIIBgMUlhYqFKZpd5HurAk6ImJiVHHKcdhEvBIJk/mA31bviqA5dzIRhZwFbBpV5CNBh3wZ/4TA8/fH+R53iPY/xJbgID7BqI/FGnBfjYQAwRqvWTj4jDig30hsIUatrAPOKwuMqXD6Wle5E3u50PuZhpwnFmMIzaPAoCV78Nze6F3Ly/vCvIpf9Is0Qc4ixYZo/zZLwPnMfEO7OpEJvcE370cGBfUjQdwrUKXdgvPAFewm0PkAofgBOw4GGQTL7KFGhF6d/CkWJyP4M1cHbqng/ztUfjqLHRUiU1+C7PYxGdkMwvML6Gr+hXbySNYUENws06bmP0UE88h+rEEpILtGCK/hHs2g7kR7q+Gj6DpniDsXgp/gTc+AB6AOTPAaHwRnhebqwfgyJMwtIrjwVdpuwZ4NQkfL/JLruE65vMm8Bli/HTRAM3hIl9p7ghcfQXoFs/nQV6E20fgTmiIEOOuUgQ02Y72P11b8RaK7BkALKIuoRlxEjdoZ+CvAMshDRdi659DPl4YBz0f8AxdhPFjqrADT2PkayzAfewGwrFiBxK4ilAlRBtJnMXMT9HE29prT0CMg1YQUFZ4uI5azPRTjpVt4mBYCKzVwM4S4F4OYcbKPqq4AVjNh5TjxgBcxRXsYmo7xAnt5014gUFeARaHh1JxmrX38U8Z4ixJCrbNboM/VoHxTvHvQ/I172LDAuzgRZpGg3D5x7xLAzfr6sgOg8syEA3yrOAQ13Anf0L/Q9SkUyUMhsMrG0FXZeZD1iMATgUCDmozL3tuqGA+QfuWIUDy6uUfa5b/OeCJjY2lo6OD0tJS1ToeGRlJYWGhCtzbsWOH0nO43W4yMjKYPn064+PjvP766xQUFODz+aioqFBX5RMTE+Tl5WEymVSvlGRkpCU7PDxcxf9XVFSQn59PRUUFYWFh+P1+MjIyuHTpEvv37ycsLIz8/HzS0tLo6enBZDIpvYoUUktB56lTp7BarVy8eJHo6Gj279/P7t27sdlsWCwWwsLCSEtLIykpSXV2gbDTHzt2jMjISMrKyvjlL3/Jxx9/rDb2RYsWUVRURGdnJykpKUrsKkXEpaWlqmG7q6uL+vp6SkpKiI2NJT8/n4KCArKzs5mcnFTgRzbIR0dHk5KSwuTkpKrycLvdKnNHJkCXlJQQFRVFZ2enGntJR44cYUk2RI6+gsEg+fn5tLa28vnnn3Py5Ena2tqUu02G5QE4HA7FgGVkZJCQkEBcXJwS7waDQfr6+tSmGRkZSVdXF3V1dSpvxusV/gC3283JkydVJ5sEoxkZGSr8TgbvSc1JMBhULieDwcD06dMpLS1lYmJC6bNkz1lJSYkS5wKqTkSyimazmYiICBISEpSbKzIykuHhYQW6L168yODgIGFhYcTFxREVFYXL5SIqKkoFQ8qMJZ1Oh9frJSkpifz8fBobGzEajRQXF2O320lPT2doaAiv10tOTg7Tpk0jNjaWmTNncttttzFnzhxWrVrFjBkzSElJISoqCpPJRFJSEiUlJSxZsoSsrCySkpK47rrrmDlzJmFhYbhcLiorK9W/lalgR6/XqzHZ1BqKqUBHBjHKsZZcr2/L17TkIPA072Lmp98Jctc1Ot5lCLrqiCBA8F91vMkNTLfCEbeg6nXr3uNLTOzkHZIDoKvarPl7Qsz5CWS/dj4gNuFmpFJhNVnAFl5STp9ubudl1hDzahDeWQ+b95LN5XCNnTe5ldazMOYOcJc68oVk8ypGrJTxEj5y4Zpbof7nbKeEn2yEQqLhmtfZsl6H1axDz3t8yq+0VvK1wDn0a2JgyVLAwtOsxxPwwZInWdsV5CevwU0vAy9+yVqeRVdmYy5iGHMO4J5VtLEZXHdzme7nbGAz6c3w5xfgiTRYwZX4eBExvvqT+Nl4O4HRvfDiz+GpYmWgKXtJW7C5YPwu8Gc4/ieImwB+A5+vgrEw4ODPgfOw+3ZYDrF3APuEHgocdCC2wVQEW3MCAWIio0zaKz7KFu6hjGj4lZPA4m9ay4eTxPHoSiBOq5Q4Xyba6xGHxYm7YAO3868I/QtJC/glYOTX6nxj7mKSJ7knABM8Si23AD34uQ0P8Dy5GGnXnFsxqv7Jg0hchtsYB9pYwyEasAAfYkbHBCcQeixhPR8HlhPGBfpZieAQhQdcWNsF3DZp7GMzIBDdw/ipJI1liolBOwUWoIgAb1AOVGh5SgJH7EDAi48AoWBaTQqQskEkca8FVr4mbO3LWc+7JAGraeMzjMa74WbYuReCujh+zyQXcfNfwMCtcFx3Eu74AHgC3c6P8SVrTwZMzIP0K+BObAhgKfu0ZP1EOLhyv2FNJ1X72UMon0dSZv/g65+OtF5++eVgVFSU6myaMWMGHo8Hg8HAl19+qRrK29tFOqVMFB4ZGeHgwYNMny604C0tLVRUVHDgwAHy8/NVrYPP5+Pw4cNqA7HZbCQnJ6uU3VmzZnHu3Dkuv/xyVY9QWVnJ4OAgbrcbm81GX1+fouQ/+OAD0tPTiY2NVR/8M2bMYO/evSxYsIDU1FSVQizrIaT+or+/X9mzJYMyMTFBcXEx3d3dFBQUqBGaFD673W66u7tVyWNBQQE2m42uri51f2lFNpvNBINBGhoaVGeYy+XCaDQqga4M9ZOFqBaLRQmQpY5Hlk7qdDoGBwdVjorM7QkEAjgcDtxuN6mpqbjdbhobG3G5XPT29uJ0OhkfH1eVB9IZJ63gctSVlpaG1WpVglir1aqKNvv6+hgYGOC1116jqqqK3t5eent7ycjI4LLLLqO5uZnMzExqa2vx+/2q+8vlcuFwOJRra2BggPLycux2u2LSAJUWLa3nHo+H/Px8enp6CAsLo7q6mtraWnJzc0lMTOTUqVMkJCQwPDxMTEwMubm5TExM0NfXpwICvV4vk5OTBAIBpWuR7+3m5mb0er0adba3t6PX61UJqBz/nD9/nmAwqMpkk5OT1Uivs7MTvV6vKjMk6JOPJdmY/Px8NWKTAYsSmMgQSKlTkjlN8qfRaFSauSNHjtDT08PZs2eVZkuKuXU6nQq3lCMsg8HA5OQkcXFxykEntVcS+AQCAcbGxti6deu3ZqSlY1ZQfDxvwkoJ/XwBry8l7RYdyxGygU95DP/INm6LgjdYD3RQyFFKER+3bxHN5Xj5lIdYwVOUAi+Tq/01n3W8L+zmCGbgaeZTyFHOjoM1XIxfDr0ahOtgS5KOp/cFYWUNsBMan4TiemAnsWzDPQd+dhyeJ4mNODW7eR2LmcEhroGnPhD7wcrvwK4P4JpViF3jJgSX4WAF+/gecBu30MzrFLCZv/Mci9iMWIvPgOOgOqgtBD+/lYl58IcouLMxSFmxjrM8BLSA6z0w3w+/eFbc/Nk8xJAjnO3cwF1AP2uoYje1dMJzNgF0ykdgQRSXHYUvIyBsDHw3AsvhwVvFRGLHKrDuhf75wL+DdQb02xDimvJ6ynTlnD0JVO8GXmAu+7iWUHwgiP3txxiYqY2Barkblf9iv12Ipjxw2TvweTFYG6H/RuBtF2OBeJ7VnFoPnIXHyuCXvAjsxMhh0gmwEHiX9YSq3X+GVLqY6MLHZsp4TgsgrOBmdnMYaGIJUICJ13kZuI31FPI+TZgBC+uw8yE3AmtJ4wa6uR0BNe7Vzul24McUsoAm1gAx6PmYaM1UPkwugmr7DWH0oWMCP9cB9xLLAjU+6+ZuBOz7gus5ynngAgYeJcAj5AKwGDsLEVBpC9BDNJPMZyP76NBe7RtA9DHQzW0Al9b99SPYWCJ4GJEE/bl2VkqBHiYoopsoviakDwIRu/R58H5gD0bO4cdCyGovk4e0sS3TgARwCscr5xFPKEMlp2rEc+uBJwjy3n9/pBUfH092djZZWVksWLBAbc5vvfUWIIBNW1sbDQ0N9PT0KAHoV199pcYE4eHhLFu2jMHBQZYtW0Z2drZy2hQWFmIymcjKyqKsrIzBwUGam5sxmUzKqTJ9+nSGh4dpa2tTGo+///3vtLW1AbB//37Gx8dpampiyZIl6HQ6EhMTSU1NVZkoq1evpru7m2PHjuFyuXC73bS0tKiguoiICEZHR+nr68Nms5GamqrAx9GjR1UoYGJiohoVRUVFkZCQQFlZmbKM79mzh/fee0+5wC5evEhraysXLlzgzJkztLW1kZiYyNDQEPX19VRXV5OYmMjZsyJS8uuvvyYyMlK5qGQtgtywpQVarn1SUpLajB0OB21tbdjtdjo6OtTrKiwsZMaMGZSWllJUVER1dTVFRUUqaVh2QpWUlCg2RzIj0jWk0+mU4FfWaTgcDpVWnZWVpbqc5Oivra2NadOmYTabaWtrY2BgAI/HQ2RkJHa7nfj4eAoKCtDpdFRWVuJwOCgvLyc7O5vi4mKKioqU1kgGEkoxtdTRDA0NYbfbKSsrIyEhAbPZTFZWlsrp8fv99PX1qY1finJlAerQ0BCtra1ER0czOTmp8nFkorPUR8nqEfn+djgcCvyFh4erHrDJyUlVQOvxeFTVhnT7LVy4kPDwcLKzs0lLS1Oi4ri4OCVKlnocl8uFx+NRIYaStfN4PHg8HoqLi8nPz2f16tWq0kKCJylIlu8VOaqSIE6CZGmDl7Z6u91OXV3dP/tI+P/w68cQ/ySwk/7dQbhqKffdouN5xN79KbfwOwTYKQW28z43c1SJMN8imuV4+ZQjbOEpDhDNduB32FlMDfAA44hR1QDiSlrWRlSFw4fa75kGjyfpeKoJWDkLD7O4nqfgFfAwAxhnB9BzHJ4MwGs4KUWOtw5ziGfFIz2UrD1gAdnX6MC1FxMvAefZyDvEso92xPjsAK9TwGM8ynMs4jNofBZcq4AHoP5L4NewbTOwB91lj7E2Sgylgl06HMBY4ClgOV+bdcBr8Ksn4dndovWbE2znBjbQSz8NwHk8wEdkCBx1GmJ1UTAAn98CgS3gs8HGd4AWeOZZ2DEfcGhgJwV4AvpHgLNoVNlpzl5EONP5GmjhGCt5AgELZNIvwHcJcIzHqGUJadp6YL89lJaYKkAXMdrEYzkUEs/vDfDwMTHuokMyG9cBm0gkQAzwLmvYw/vAYgTDshAr+4DntUzpcc7SyUa6gHvJ+t/cvXl4lOXZ9/+ZzEyWySSTbbKSZRJCCCEbYV9FQCibWihuuBS1D1aLy4uKWrVa60pdqAutlSryYKG2WhEKCqWC7CQQUhJC9j0zSSaZTDLJTJZ5/7ju6wLf31N/x/vn630cHAQyc8+9zX1+7/P8LkAVGxEQQaxxD2Dkr9QRRADDhFHHF8wgjB1AO20cRwCqe6BlI3Qs1fbsTcXYgT5GSVewQCDfYwTQwzAxJDJCDruRbZAu1tPGE0AkhbzEAU5wL+I6v40RohBZc+Dkl4iunsQSo5j4loPsxEYyopMW+jrETEMcxAXw683gHA+/Bx7BQy69QD52rmUPCZyhgPsxcRhY+R6MtUIiQhJ/Bnhc9xpwD0OyzaPmU9KcULozm2HAdKVFFscVFnqfuJ7IqgTbMgrJ4xEtS+5/Wr4X8GRlZZGQkEBjYyOdnZ10d3dz9OhRJk2aRH19PSMjI7S1tRETE0NKSgo6nY5Dhw4xceJExo0bR2RkJDqdjkuXLhEXF4fL5aK+vl5FJ/h8PvLz8xkeHsZutyvJdkNDA2fOnFGFxuv10traqmIU5s2bR2RkpCJ6SsWWzMqSCeEnT57E4XAQHx9PdnY2VVVVigDr8/moq6tT3QCbzUZzczMnT55kzJgxNDU10dzcrCTIEtA5HA7+/e9/ExQURFNTE06nk8TERGbNmkVGhmh3Xrx4EYfDoTgt0p9FOhFPnjyZwsJCdu7cSVBQEIsWLcJkMjFjxgw1dgkPD6e7uxur1aqSz9vb21XaeVxcnCJLSzAWHh6Ox+NR3JuKigpFhDYYDMpkTxZHWfDq6urUeEcaMIaFhSl34NDQUAWApNRd8lkuXbpEbW2tGgnJAi4zycaPH6/GPHl5ecrnyGAw4HA4OHfuHF1dXfzoRz/C4XDgcrmUCWFsbKyyCWhvb1dqr/Pnz6tOiNFoJCYmhtDQUJVULjtuMuwTUIRzQBV8n89HQkICYWFhREdHKzVhamoqkZGReDweXC4XiYmJJCUlqW6gHJe2t7fjdDoZGBgAICEhgd7eXpWrJo/H8PAw11xzDUFBQcpeQDoph4SEqJGkDLPt6+ujvr6ewcFBqqurqaiooKurC7vdTkVFhcofk+PfzMxMYmNjv5OrdXUauvTaudp7R46N+/v7aWxspKSkRI3wflDLvnVwFF7hKe5aquPWL3X4EM/OwuCvnfsp4r/R8zgz+Bmozo4TGGUjh1hIGDN5md8wSixm4H7WaMV2O4eBQ1gZRM/nBLETG7MQT7zzsXGRjeAT/9ZlbuDXFGPmrJD8vi4cYz/iJa67U5TUYP067uU9VgB5I+C/9z4E/JpPHx0ae/eXgrJguQ8v64EDfNwrRhL3AKeYoZXa7TzXBSu5DrK2kmDRYSQBf4uOabRoCeQryOQ59vMaPwJevVZgjhl6gDv4X0gOC0AkrNkHdW9xCxb6iKWa8TBQSzuw4qAfbI+CD9weBAXpeQRe2Qk7PwYa4elH4dcnYGoZXHsCjF/Ckt2I9oIPsDwpzpLthKh/k59EDFTOEIgAKAcQVO4aROnfxHMw8A1tOGDre2B7Ed4qhimQsBnGDEJmMbj9j8LfRDTGm8Cz07TJSr42yqMUKOXvwEXWAbNYzAYW4EKoj5zasTCzHIhmC/CqZlwYz/Osg4HXoMwGvIyXNXzBGtIYwYaXUZZpoOU63CwFzkDlDETiWz8kfQ3WE6ClrQmF9gGgGwOX8YECWu/wuaZiEpdFI2BkGv2EAuUk8BJLeI44ceYoR4DzWdphvsUHmzR+2izEoZ4FhNHBC8Az1FEqLlOOPQJdXICBJKqLBTi20EsNMIiJYYLZTjSbEPnxU5PgDzfAnRuB9R3guBu3v4WGz8C9SHz+Et0GePACopPTrZ3JFK4YFmqJoRLsOK/6Wyamzr2PVMZzF/tYrO3nf1q+F/CMjo7yxRdfEB0dTUBAAGVlZYSEhHDo0CHFXTCbzWRlZSlib0ZGhsqjApg6dSoZGRmUlJRgNpvp6Oigs7NTJaLLsEyDwaBylHp7e4mOjsZut3P69GlCQ0OJj4+nqqqKlJQUzp49q6z9s7OzlaIoMDBQgYXS0lKCg4PZt28fe/fuZWhoiPvvv5/+/n56e3uJjIykoqJChSu63W5SUlLIzMykvb2d66+/Xrnr+nw+EhMTyc3NpbW1lUuXLvH+++9z6dIldVwsFgsDAwMqrFSOzqxWq+qwdHV1Ke8eyQspLxdfsfT0dLq7uzly5Ahut5uuri4sFotyQJY8pejoaFUcJUCUhVyOoiIjI/F6vVy8eFElx/t8vu+M8VpaWlQxHBoa4vjx4yrKQBJ9Q0JCqK+vVyRkWTTlz+np6UraLvlLZ86cobKyUvkryQJ86tQpYmJiGDNmDOnp6SQkJJCfn688h7Kzs/H7/RQUFDB27FhlChgXF6eCPKUp5fLly1XgJoDD4aChoYGUlBQF9Nra2gBh/ie7YzIxXnKrBgcHFXk6KiqKuro69T4pSY+IiKCjo4Pjx48r6XZaWhojIyPU19crTyKp4JLfCem5lJeXx+TJk2lsbMRisRASEqK8lgICApSztdPpxO/34/f76e7uJiAgAI/HQ2VlJRUVFezdu5eysjJ8Ph9Op5POzk7xBdYCYAcHBxXf6WoPqasNDWX3RxKbW1paqPMPRnIAACAASURBVKiooKqqSuW/yS7YD2V5YKmOu3J1PM6zKqwzA/EsLRx3zKykmCFeBx5iJ/A4RZgR99RMnoPPv8YHBPEU8CcasJDJbo1DcYzHAbiTEYIZJhgDrTQin+0X8xGbwSmdfI/xNE9gZBqnsIF+GRf5DdsRG1VFLbCYadxHPCK+wf4++FdsAc5gxgJZY4BjRAGb2Ip0m40IFyDgj8AcTvA6Z3mGOhKj4WEggI20YcP3hxHeXQInv4D2EB2ruZ3LY4GtGznSpo0e3oYygoCfcohcOtED77KJmSxgGYU2HXCOBQh4cD5Eh/tRPyyM5Rk2w7piCNkmFDjvQtDnkDAPpt4OD+8Q2ym8kATl+Y/DmufLHuA2oOxFoJRUZoJjnjgZHW9BRw9dPMG9iMIt3V3sCCk+IVuhzCqwwswn4b4i2DhMm38HDYugag2w+TX4spIhVtCARWVjfpkAg22wiWVEs4VfAAHs0tZeLWJFb8oCUugiCT5fyuOsFUT0lrdo2KrRQ3Z8IDpLX0ICdyOKuJMq1mjb+zZVvEYAm7WjtweyvkEc+XyoW4SB+YhxlXCGjmEEaESPyPM7xA1Anwa6m4C/YEeMuYaYwCh5wPN8iJDT7+cGDmivvJkrfkbnNWVWvraXMjr1XgT8KEeAvlXMYDZzgXjaTZBBF8m08Q3htCOu7aB1gazTDOG7LNqHrAJe281qYgljG/AM3DAZ/gJvzNDGkg+hfdvmI9o30rcnSvzcYRKjK2kKJG2i524myKJjCVtZgTjlMr3rPy3fC3h8Ph8LFy7k8uXL/PGPf1TmcdIjRqfTkZqayrRp0zCbzZSUlCi7fJPJxKJFi+ju7uarr75SvjWJiYmkpKQoKfnAwAA+n4+IiAiSkpIYGhrCarUqR1zJaZFhkUeOHFEJ3tJVtqqqitTUVPx+P5cvX6asrEzFUCQnJ3PhwgX27NlDbW0t8fHxdHR0UFtbS1ZWFl1dXVRVVeFwOKitrf2OMeLSpUuZOHEihYWF9PT00NbWxvz581XOk1ThpKSkcObMGcaNG0dycrJS8MTGxtLa2qqASWJiInV1dUq9NGHCBKKjo5WJ3IwZM7j22mtJTU1VRVSOPmTBApSsuL+/X6m/ZMhrf3+/8qGR45fQ0FBSU1MVCTsmJkZtZ3h4uMrBkt44krfS3d3NhAkT1OeZTCZGR0epra3FarUSERGhuB8BAQH09vbS3t5Oa2ur8tLp6elRvC1JxpbGhENDQxQUFCgDw4kTJxIaGkpLSwuRkZGMHTtWyawnTpxIQEAApaWleL1exXHS6XTKE+r8+fO43W5iY2MJCwujv79f+TtdzVeRRODk5GQVtClBnN/vJ00Lc3U4HIqEnZSUxOjoqIroGBoaIjg4mJiYGJUP5vF4FFk9ICAAm81GYGAgaWlpLFu2TMVZSIds6fws0+qdTieNjY00NzdTVlbGn//8Z06fPk1lZSXBwcGKxN7d3a1CXp1Op+JXSR6QBDnyb8n7kWCns7OTkpISSktLlTeTfM33cfr+X1y2EsSH/ItHeI6X7oU7Wa89IS/kGKGAT4w4XBuI5ibeBIIo5mVEXlHVgJ9nbtCxCvAyA/gF8JAwy79xFzCf58kF2hnFAKSwFy/HkOGa7fwMIB8eZgawnE28xBDz+TV1ELEXeIj9HhiXCeAkgHWYEcOTol6BAex74NfsoxwXFDcDmzhELqHA4Mh4EridFYjXVpHLUZbCQBHPH/TTxmvMr/MzymfAQ+h+ZuPnE+DdlaLMPAYYq4Pw79WhS1jICiy8+QDswgv8CbiHoaeGgZcJRBRBMWqL4hRvsYpLFLAWXnuUIJ2D50f80FIEmAWpKU6Ms34JPM4Vof07ZlhsEIyYTYht0Wk2POS6gAx8wK0cwdgEWL8BqwBCr7Oel1nHXxFFOgMRXgmHRWEUGarQBNE6A4xfC30wezeaycxHwC+5FRcViOL/CFCjkZc/BE6xDiP9CJg8lirWwa4XRfeG+ZrNzkOc2uEX66wADuby8O3AEy2wHNpYCzdtFHtcuYtD5DKNWOBeES+ihY0KlHed2H7bTQzzAoLD8oxqbgAMEaoV9D5gFk8RhOhp/E0DK9l8RBnwd6icx2IsFLIFSOFp5jJL28zD2uHp5ooqS7xbdMzeEXvIpzwrzszu48D9eHUW4qhimBBuI4ED2vqWZEHhNu3YrQV6TpCzS8fqtToauYk7EUaWAgEni47Nz8V1IFCgxtNRWfCaFN2lhRlL7nI3MHcHQUU6PuHR7yTex/HdEPX/afle0vL27dv95eXl9Pf3k5ubS01NjZJyR0ZGYrPZmDhxIs3NzTQ3N3+HCHnttdfS19fHzp07MZsFvUyGGMqsrfb2djo6OvB4PKSlpZGYmMjFixex2+1kZGTgcDiYPn26KqRxcXGUlZURFRVFSkoKMTExDA0NKeO18ePHU1lZqQiaiYmJhIeHc+HCBfx+P/Hx8eTn55OQkEB1dTWZmZmUlpYSGxtLcXGxUuJIv6Dw8HDOnDlDWVkZGRkZhIaGUlhYSGhoqBqhVVdXM2vWLBUJMXbsWGVOJ1VpUr0zZcoUgoODqa2tJT8/n6GhIUpLS8nPzycwMJCamhosFovqogQHBxMVFaUUVsHBwd8hqPb19SnF1eDgoPq31+ulpqYGu92uEtonT55MV1eXApmjo6P09PQolY7sRsmEe+k6LX2SZD7UwMAALS0tKg+srKxMxX3I3DEJsDIzM1Wsw7fffktERAQLFizA5XJhNptpaWkhPDyc6Oho5YQsFWAOh4PGxkZycnI4e/asch1ubm4mPz+f8vJyZScgj7dUNplMJkZGRhgYGFBgMiQkRBGjMzIyGDduHIODg7S2tirgOGfOHL755hvFV2tubqa2tpawsDBycnLYtWsXRqMRu92uxorDw8P09/fT0tKi0tGTkpIYGRlh+fLlykkbhGrN6XQSFBSkuFlS/i9HS0NDQ0rKLwGuNCyUo0i9Xq+cwxsaGmhoaFBJ7ld3cySvSHaUuru7FSAFlLOy3A75+qNHj/6ASMvD/gSM/B34EeIm3oTwm/lpIXzIXti2lKB1On4JPM0uqrkJJzD1QT8H3tJxXRXoMq1Mo4NTrEU8lT8GxWuh6EmglGj20cUTwP1EMwYQZOU4YCdfMYfrSAZ2sgE4hpHzDHEOAVFWsYDx/MMHgYEfkMPdvI6gFX+FcBB+h2KOAf9dJTxnZm/188B6HW+3+JmTpOMo63iHbWxCdE1eRTy5f8oa3mA3D52CP08TdaMPWFXmh9z7+Ctb+fEtoPukGbiVao4wlrncyhGiELhB8jueIohhDsDuebCmGMiHMoOokE7xT4q+huWLxI7/Uvz/A5OvjFvuRHBdf6nt+WMGkfflLUJUvz6uuAuGPMomNpMP3MJGiHgNejoQ/SGpmDIDFeRQTCCiTH5x0C/SRaU50kfaSf+9duoOI6RoIcXAHoy8QCkjbEJAD5lX+SNNxTVKD/AVqSwjBThKErACNr8HG7dCy3pxcUk7nmTtJJiBpA5YbhVtLP2jCEjxAuyrhaV3s5JtfMEGprGFU6zRDmQpgrV9BthENC66sCBKex+plNHABrFjLT2Q9A0CiM8H8hnpvRv9w36xI7+pw0imlutVwSYtjTwKWNsLLeGQRij5mut0u3YKnmYG0zjBKS5AbC7vd8BaRnERoAJzP+EKwPinfxh2GGBtJVd8mu3AtwieUTEBDGPFSz6wn1yovEDmeKjyb9XO50Nc6e4kC97O1ZH1Wfsw8GMW4lX6LSml13RcKm/0Dvz/96TlqqoqAgICuO6665QcODY2FpPJRG1tLUVFRfh8PioqKggPD8fv9xMXF8c111yD2+1m2zYB+aSlv+xYSEKtVGRJkqU0XOvt7SUmJkaRYquqqhQ3JDY2VpFky8vLcTgcpKenq46L0Wikuroar9erVFCSuyJNCMvLy1V3SHKGkpKSVEq4VGmdOXOGiIgIFi5cSGZmJi0tLRw8eBCXy6XSxhcsWMDIyAgnTpxQ6qjExETlGSMTzA0GAxcuXODf//43MTExNDU14fP5yMvLIzg4WKWYG41G+vv7VWGVROK2tjbKy8vxeDzKjbmzs5POzk7q6+uVsWB3dzcNDQ0K+FRWVipFlByjSUJ0aGioUu3IEY3D4VDdrMHBQYKDg+ns7KS3t1eFx0p+jzyPqampWCwWEhISmDVrFkajUSm/uru7FZG5vb2dc+fO8fe//53e3l76+vqIiYlR3B1ptud0Oqmvr1eE3dTUVCIiIhSolnElEqzJ6Ao5Cuzu7sZkMtHZ2cmSJUsoKChQSrdZs2bR2trK5cuXVb5aQ0MDiYmJ6PV6pkyZAghis0wWlyA1LS2NOXPmqHwvmbUlg1pNJhPjx4/H7XZz/fXXk5KSosaE8nsgR50GgwGj0UhHRwfDw8MEBQXhcrk4e/Ys58+f58SJExw7doySkhIuX75Mc3MzdrtdjTjlKDgnJ+c7aepSIg9XSN5er5eKigrOnz+vCNeSdC0feOQxHDt2LD+kJQgj8cBUPqBrxE8F8K0HphdKN1kjxnVigPD0gB9wsh2YWuzH95qOw4AucyEwi1NsRNx5tZTNIg9gJpV9dFGEGByJh5wJwCEusQII0y2iEdiJBZ57izcoZohexM39b0AgvwWMVWDkZ/yDK7604go9woMEMQswZgYxm/X8db2Ot5/ywwMCjKSyjYfQM0AQP++C+vvhU57A37ab7cDcaXDjCFx3i/jUZ3J1GHmfVQ/6MX4SxODIGKo5Qjzgv/8IO1nH7xaLEvoqIgF+L17gBVizBcqKxNN3BeJF7wKBoAtbdEW3fwwoKuNt/5Pcux5+vQjGvijgyvuIsj50B3h/hWgzZSNAytzNEHIjcF4VsVfYLBjgN1qhYy0yICSHHSygmHaETq0bYOE8MZOZhQA7q4Czw+KA3olo3/iAgSLt+Iu+QxOCJbQJAcYCGGaUDcBccC3Fqc7HfKrZChtdwGHYDlwohhseJacY+KxOHLSkSrEBGWgtlEYM/JxbqdPyNJ18wbPAY5ri7ABXiLrPAHcQwDBdZbIp4SOAWhrYC/TxBi5Imgz8jWmUaQc8A334swJRTgEI1JRb8UC+4j6tAgK+Eu9Ipp+buaKRKkWMRE9RhD4kl/MdYgw2TACPALdY4eFlcHo9fDsM/5wBbDFos6Q3uZU85jCZBJYxh5fI4Qj59GuKrVztU6ZA1g7NTFJ4Tl+56jNgxCSQVzxgLSMoS8evWcaTeJnAlQhSmb8OV8DXYf7zYvie3zFz5ky6uro4evQoJSUlWK1WYmJiKCwsZOlSwSLfs2cPEyZMUOTWiRMnMjQ0xCeffEJeXh6lpaUkJCTQ1NREXl4esbGxyhvm8OHDjI6OYrFYiIuLw2AwcOLECVasWKECFHt6esjNzVWeMLGxscrvxWw2c/nyZaxWqyrAZrNZPdHKUVB6ejplZWWcPn0ak8lEfn6+8uaRuUbZ2dl0dnbS1NTE8ePHVXejv7+furo6br31VhYvXoxOp1OxF3a7nfT0dCZOnEhubq4iy0ZGRlJUVERHRwdFRUW43W6GhoaoqalRiprR0VHsdrsCZOnp6YqXJH+fmJjI6OiocuSVKh7pPhwZGalAnTRLlA7MVyeL9/X10dPTg8ViUY7GJpMJg8GgoiFk2nprayupqanExcXR1NSkOgRy1Hfp0iXFt8nOzqa2tpauri61DXL/ZUfC4XBgMplUaGV8fDwTJ06kvr6etrY2UlNTFZclMDBQmfRJkrHkZUneTFtbG3a7XXW/mpqaVAF3uVwKSMsRTkREhOrSxMXF4fP5yMnJoampSXW1FixYoNyoLRaLCkkNDAykqakJo9GowlK9Xi/Tp0+nuLhYZVOZzWbVBcrKymLu3LkkJSVhNpuVDL6rqwuXy6VGwbW1tRgMBvr6+ggPD6evr08BELvdjs/nU2G2IyMjCqDLzo1U8LW2tjI4OKjAjvRDAujr66Ozs5O6ujrVxbnaWVlaN4SGhpKcnKz4Pz+kZQLiPnyau+nX381HwJ0m0W0QN/hXOcwIsymCkMncSjHP7/bDmsm8A7zMszzCc7yOUDOJiqz54d+3lqD3nqIVPfAYtFiJTtIxS3vlEsZzCzbw1+HmK+BdeHYbD3MWUZpfAH7LAtIp4AbeyPmcSYzwDKLTcE8bHEsAuJ5hHmE7L/EeXirYyptA+W90TKCWLnp4iAie3jHMXWt1/DQa/nQACnmJcQmilNzxOPzkFbjzE7iRIIaOeomcM8JDc3RMAoL1x6lmJmZstL9Tx61s44UDsJkghvkJutQ9nMZFDge5yMOiHpciOheNwNnd6MLWUNAHobsFeMi+Hcy35/KpP1sgiUfEoWuzwiv3AnfA6vHwqaDFiLq35kGMvEM4I0zQVu3U/jD3dqj+WKtwPqCci8zgIj7mUEwp8BIwq+0IuoVl8FKuADgAuw1iGw4DC2eC8zjY0qGjliFrOhXUcY6lmOmmkBO8D1jw0kU8hZzgnKUON1bMdAD3MJYMRFsnUtNavwquXVz0vwgcI2zbXtwfNMLARnGhJXUADzGMmRS2gW2bttPzgXJEot1YprGDUyzVrtw/Msoy8THNDwFNjDIFcfCzeRgrdJyFCjg19xhiJHYMMAviuC0DPl8PN9ypXZF/pZgghnmXPdzNze2iGTVLOyxTgQc88HCTH7JuolC3ixLagED2EM3K94DtYDwDQzdrX4Vq4LiYQ54mlilVIjX9a/13Pat8wEOUad84yGQbVdwszj01CLBjFnJ3yzDoO8DaBzzArewjniup8fLswxWw49P2/M+EMsoG/sT/vHxvh6e7u5svv/ySc+fOERAQQE5OjnLbDQsL4+jRo+Tm5uJyucjIyCAjIwO3282hQ4dUmvj06dMJCgpizJgxFBQUEBMTg9lsprKykr6+PjIzMykoKADg5MmTyvzsyJEjiofQ39+viL5ms1kpd3p7exkYGECv1zN58mQyMzMxm82sWrWKcePG0dDQoMibycnJ+P1+xo4di9/vZ//+/YSFheF0OlVwZFtbG1lZWTz55JPk5eWxcuVKJk6cyOLFi6mtrf1OsGVISAhZWVmKdwEwbtw45d4bGBhIbm6uyl1qbGxUYOTAgQMUFxer8Eaj0ajSyyVQ0+l0NDQ0KH5OV1cXHo9HjckCAgLo6ekhISHhO10qKZH+P9PQZXbZ0NCQcu6V0mmZNC87Ovv37+fcuXOKXOxwOHA6nbS0tBAcHKxGOuHh4cyaNYuoqChlOBkTE4Pf76e3t5fLly/T2dlJX18f/f39zJw5UymE2tvbSUhIUCZ4PT09HD58WCmVLBaLkvu73W4CAwMVoDabzUpSbzQaVT6V9LcJCAigs7OT4eFhWlpaGBkZIS8vj+TkZKW8kx0ZnU6H1+vF4XBgt9s5f/48zc3NavwaFRWlrrng4GDa2tqUU7LNZiMiIoKsrCwWL17M6tWrGTduHBkZGYpc3NzcTHl5uZLYy9GVzOiSBpd2u53W1lbGjBlDbm6uSosfHBxUI2G3262yskAYQZ4/f57R0VFFZJfjXIfDwfnz56mqqlK/k4o1CZqCg4NJSkoiOTmZiIgIJef/IS3lXCFktiNu+4FAowfOcYl3OMhsFpJDMaspZudzfm69CVZSzMPY+JbntJ5NKFfAzgFIfw3eW0QgMMRjULcGkpbRxUa+wIK30i8cbfNqYbkNOMwcPkeUl0dgZhKSYlwOfMvnAsQgKa7w0wT4gw8gCopf5BRrMCNiMKqB9BEgzwZ8xNPP+WFtMYcRN39d9RDn6KeKufwV0L2yhr+0wfIvRKdm+hyNV7taNBuMzNGejG/memAnDp7mLYZfGgT+BE/18F8I8GRkJdM+0/FArY5NuTrxgdvW4Hd7mIJorsiOwacbgZkGeEH433AYaEM0wl6AT5fBK5XaSVq7GcgnmBHuRPRw7tF+JfqOTli3T3PRiwfGEsAFoJF87cw8AbybAN+SR9gT2lTDB6ypFFEQCx8EDoLtQSBbq6D/YCc2sYaO4wQixpEiluFN5gPRpHMrHXyKDUiBvF8xhxPimli3VWyppZhUnoLle3H7t8DniyAB0T6iD1H6H+JlNojPplysi6nEA6sp5hRW7QqNA5pYwm5o9iDaSL+Dbe+Ja/Glj8XrDmurKjuLgJl/RrTdPgGegWzIZJm2vsUMswADP1fS/AXAX9CzHxuhgPE2P4XjYb9uF78E/osEdOujWel/EKYIRd3QYu0C/RkiSfYpK3CGGkTO1l692CwjAvSs0rasVPsOXiSJKo6L4/EPtN9oEMbi0Xg7b7CAdF5hn2iGad8LKVqXQ7N+7d1PY2MnTzDK1zDyIv9p+V7Ac+LECaxWK2FhYeTn59Pf34/b7eaaa65haGgIn89HTU0NBQUFatThcrlUUnRMTAw2m03Jb/v7+1UmkHxaTUxMpLOzk8bGRvR6PdOnT8fj8TB27Fjq6uowmUycPHlSjS+klb8EAh6Ph9LSUkW+nTNnDsXFxTQ0NCgHXfnkGx4eTm1tLR6Ph/z8fGpqapgwYQJ+v1/5ynR2djI4OMilS5e4dOkSQUFB5ObmEh8fT0lJCcXFxbjdbioqKkhLS2PGDBEWWFhYqLgoFRUVyp+otbWV0dFR5s6dy4wZM5g6dSrjx49n3LhxKuV7YGBAOSdLPonVaiU7Oxubzaa8XKxWKwMDA4SFhakCLz134uLiqK2txWw2q0gG2XFyu92Ul5djt9sxm81YrVYCAgIUDyssLIy0tDR8Ph+hoaGEhYVRU1PD119/rQwMpZRbr9dz6dIlpV4yGAxMmzYNQBlRFhUVKQ5NSEgIdrud8PBw1WFzOp0KbEg/odjYWIqKilT6uYw7kN4/jY2NSrEVFBSkiL/SZK+xsRGdTqeMMSVht6SkhIGBAeWhY7PZMJlMJCUl0dPTQ2trK16vV/Gm5DUgCbxXq5akWaSMKrHZbIrkPXXqVDWCk0o4OY60Wq0q5NRgMBAZGYnf71cKrEOHDlFdXU1SUhJ9fX2UlJQop2uPx6P8i8LCwhRXyGKxKM7U1Xydvr4+Ll26xMWLF5Wnz9DQ0Hc6O3LkmJKSQnx8PNHR0Uog8EPr8LyMuFGWI+7PnehpB4ym95jGeO4nFyilkiA+pQiOCen0F+wC7uBvwNP3+ZnGcySwGW56D7gZ/gLK+u7Ii1rh/ANK55K1jy6WwgUPRMIjvKSRpOfA7d9oW3cP8Bi3IJ5eGziLmzUc5ory9kAgwCzto/q4Az2FbKGNDQTrPybzgk68ewpEM5kGLrGTdcD1+I+G8ghHtKfgh5iUAGdWwnV3ir5C/QRY/jZ86ANf4Ag/R08mL/EQ8D6xfMKDPPOEDngCftPBuZv83FLnZ4hBTrGRt3Hw8t1+wbddVwwtJv6wTjRyvgJ+j4/9myHnBBAHXUXwyQnQRaDESdfuhcfXaTu8YyPwLvcjmTkC6NyCgJv+o/sY8iyDovtg31ooPstoXR9wiLd5jb8RSiNwPxaOoYVY3vAorGmBrVkw8DFC+ZTGAraIq0OfB1uytHPxPFjv41Sln1M4gPMc1mTZR4Gd5PIOdcCb5FzQcRQb0TyIyA1bBPyRBnJF16tjA9wwLC7AsyfgdhvaHAsDv0dQtQsQA7QDfMgMbcRqRsAD0cGqAYRN32PAn8XBYJXGYv4HrNkG1skik0xL35zDNu6iBYiHrEqquEH8rKn5homhAnghB7zUEsAIkM9PAOxwbqPYCuVz9BBw5C3emQz/vEG7dI+J3ebCNn79Gx3+U8vIAAK2iwneb09d8aZyai+NQwwQF9DCEmaK9UTBd+nGL5Bj0fEMLzELAWj6taNi1z5adnXKgTeAT7lBnDtuAfK/d6b1vYBn3LhxjB07lsLCQpWZdfPNN6PX66mvr8fv9zNv3jzsdjt1dXVK8SFv3LKbMjo6yvTp0wkPDycpKQmn00llZSVpaWlK1ZWenk5ycrLi9cgW/fHjx8nIyFCKGNmdkLlLMuNJ8oe2bdumwiqvNliTknedTsfAwABdXV3ExsbS1tam1h0ZGfkdz5f29nZ6enrYt2+fMhn0+XyUlJQQERHBvn37lErqs88+o6qqis7OTgVOnE4nRqORo0eP0tPTo46F9CYqKSmhsbGRuro69Ho9fr9f+eoMDg6q4hkYGEhYWBjV1dU4nU7sdjtNTU3U1dWpXKW2tja8Xq8Cor29vWr/r85Xkp2c9PR0MjMz8Xg8NDU14ff7lWIsLi6OiIgIdDodly9fpqmpiZiYGNVNS0tLUz5MJpOJwMBAGhsb8Xq9yrNJpnlLd+v09HRmzpxJZ2cntbW1uFwuIiIicLvdOJ1OSkpK8Hg81NbWKtK1wWDA6XTi8/nIzc1Fp9PR0dHB+PHj1bYDSk4tgfaYMWMYHBxUyeOyuHu9Xvr7++np6WH8+PEMDg6q8z84OMiYMWOw2+3KkPDixYvU1tYqo0xJGg8NDVXgKC8vT3HDuru7FWn/6owt2UWS3aqamhoaGhro7u6mtLRUBY+ePn2af//734AgKpvNZpXNNTw8rAjRg4ODapR5dVenpaWFM2fOYLfbFQn56jR0yWNKSEggKiqK6OhogoOD1WdIIPlDWp5BlJTHyeVhoIYRvvABHOMUGwmiDCod6PESRrFoTawVUuJPeI4tBPHAewIoti33ixt9sYmcIgE03GyEuVJaJFyLKetBlOjXocUEH+/gdfYyShFscYh78+9hNU8BjxCJ5BOVAnfyl4uiWFQgc4+iIGs3Rg7wX4xoip1G5nA7VbzGJrZAo+xINAKvs4l99M8RReEvR8F//0zOsZFfALwMLzUgtmMFJARCjQ98p0aoYi63YGVdL9z8qeiu+D/dDKwWqGwTMGBgCZuBTPjgJlIv6YBAKIWfbRMAsxqYRCD9CIjxz8/h2mK4xQF+99eaCQz8018JH2yF94ph7Q4gg80EkY8onDKYEmBoGhhNFqh87wpHaA2mOAAAIABJREFU6BcgyvKbzKKfQGAPLqYCq+lAjHmA9WUQ8qJ2jH/OIT5ACPgPid/veJIcrgGSIetB4Fbe4CDz+ZjDhCIe6U4iEhRFyV1JnTZieRUsm8lhq3i/frNYNa+KpiBR8PEw0bpFUJcrUucrjwNTCGI3OdwEXEMFoRhpJJVi2PEk0EcVC8UJ61gPOAkI0XomPwZuzwWSiaYYuJkw9pHJPo50wZ/a5DfgZ7zC59zK3Yjuz58Jo4U9aNiJKIYIhc2f0XC3X5pHaSaS8IkmF3xjnjj13An8Ftj1Nax7EWjnXwhDwm7ESvMb4Mw0cSWWatfweQTkugc4TKggLbc8CRYpm6vAQDZ38RJ3APIu9H/GYhm1a+uvwH5uwM0uBBhcDHW5sM/EVU6N/5/lewFPS0uLard7PB6WL19Oe3s7lZWVtLS0MGHCBFpbW+nu7iY6OprBwUEqKysJCQkhIiICn8/Hl19+yezZszGbzfT19VFdXU11dbVyUo6MjGRwcJDOzk6VGJ6YmIjb7cbr9WK328nJyVGuzICS/4JIY4+Njf3O/8txiJRK19bWkpCQgMvlIjk5Wd3wZchmZWWlkiaHhYUpMjMIOfOECROoqKhQPijp6enqif1f//oXFy9eVP4ukqBcUlKinHonT55MeHg4drud6upq5Ysj5dNjxoxBr9crcrFM/HY6nSqrS6/Xk56eTnR0NJ2dnZhMJtLT01VHJiQkhOjoaGWCJzOTkpOTiYqKIjU1la6uLtUJA1Qm2TXXXKPyymSHY9KkSeh0OsLDw1WXTI5KpNrJZrOpcV5qaqoCTiMjI+Tn56PT6ZTqbGhoSBHPrVYrycnJXL58mZ6eHhwOB8PDwypOoqenh+zsbEpKSigpKVE8FhBdJNnhkGDIZDIpMDpnzhyioqLUcZWqQgC73U5oaKjqLg0ODmKz2WhpaWH8+PGYzWbcbjft7e1Kpdbb26vUbHJ0Vltby+joKP39/djtdsVhSkpKUplnkocTFxeH2+1WgFB2vUwmE6mpqcybN4/c3Fxl8jk6OqqMKnU6HSEhIQwNDanPGhgYICIigtjYWOx28czT1NSkjAOvlpgD6u+IiAiSk5NVHIfFYsFkMin+keQWSWXYD2Vxs0YbhwRyHu05coefaexgAZvx8jH0ibKXArBuC7AHXDZuYQPDxPA2N3CKXSzZiwAJRdu4yFyUo89WK1jmAdXQ8p54HP18HlAKSR1kcjtCrWKGDTeKB/jcfQQCQRzkDLKof0QQy/hFjrhnV5GrgRsn8CpDDPIRaE/sL3MSPZDCy+zl1vU6hK6rAviIcsSDbjegm5OE7p2N+Bdv5uSHiCryV3F8vGOgzQcZ54B+yOQIkII+PInS1fATQklcjdj2s0+yaZeO1SE69rNOMyM8Q0OLH+7OhVJhNHdAU6Nf/AxWrRf7cgZRK1+JBbYsEnOOA8DuLChbD64ixJP+MV7DixlRIM8j3v8VEBqoJwgXZBULifmD2gvyZkBeM0d3+6niLCtYxzsI0rYo8ogtcD0p9oN3tS36rTh3GzwQL/ovOTwF/JXVHORVAI4xynjc3AB8qZFuP+Eiu5R4CDII4Fdav08bzzxxu9gD24v8mvGw1UCvATFDankLfQGwZY04TtwAfMUoG/hfjNBAv0Y4LgB2kslkcc5u38godwN94lf5ADV08SzTmIkbG1UuPwuj5dXfB0wlENHFe4ctpHKCCYimTal2bY3W9Yk55AqEHv0Rce18aoPHtAnuw7ng/pXaYdi3CIqfhOInOVTpp4u9LMbCL6KhPxUKPcI0cxUq9hMn4tIX0Ri/hSQRAwF/5gFu5zW8TOFKryeS72aE+hCDvZ3k0sCziI1eDAMzYJ9VAOBy0Npi/+PyvXe3iRMnMnHiRFpbW5WXSnh4OJ999hlpaWkqSuDUqVM4nU4sFgvp6emEhIRQW1vL119/zfLly2lublZjlcrKShITE9HpdIqU7HQ6yczMVOGQLpdL8VMkV8hutytuSHV1NWPGjFHtd9n1cTgcWK1WoqOjlZJIBpXGxcWptPOqqio1wvF4POh0OuLj4zGbzWq8ZDKZSElJITQ0lJqaGs6dO0dbWxuxsbEMDg7S3d2tiubMmTNJSUlh9+7dyoVY+rjU1NTQ39/P6dOnSU9Pp7OzU3FDZCzBpUuXqKysVLycxsZGmpqaMJlMdHd309PTg9vtxu12Kz5SR0eHkq7bbDYGBgZUZ0seJ4/Ho2TXLpeLJUuWEBUVRUtLC62trQwPD2MwGHC73SrYUxJYAwICmDlzJomJiWRnZytXY+klYzKZKCsrU8TYuLg4IiMjiY6OJigoiMzMTC5fvoxOp2PSpEmUlZXR3d3NN998ozhO9fX1jBs3jpSUFNLT00lKSuL8+fNUV1cTGRlJbGwsw8PDlJaWKoK3HOMNDAyQmJiowNDIyIjqZHR1dTFt2jSmTZtGamqqArWDg4OqsHd2dhIdHY3ZbCYqKgqfz0dTUxNFRUUUFhbS3d2t4h2sVitNTU24XC7lrCwl7TKNXo6VAgICcLlcREVFYbfbaW9vp76+np6eHnUepbP48ePH+fDDDzl69CinT59WZHMJxGUHKzQ0lJSUFGJjY0lLSyMiIkKByPr6empqahgcHFRgU6q2fD4fZrNZeS7JUebVQEfK3GU46w9vOcPBL8DnK+Z5IP5zP9+u03HyIhxy+WH3Wl4p0jHrn3CR44iyXAWWzSxhC2/QAmTDvjXsLwLWLQIqiOYIEAURFt5Yr8PAKXh00ZUQQzPAJ3C7VQMtX4p1j/8M5p4AktnJb/CSyzEQAKruG8wIHHAbocDPuQOAPZynGF2Y1JjEAz9iiC8Qj/rV7GQj8AU8ugF4kwJgBes5xUJgPu+zmeHPoOIu+GkqPPEInFktjA2NX0BFIcRcC5ffhrsoxudrYSzwJ/pFk4KHgAJeZoh7ARGHINa9IEkHH+xWFrf+dfCH9xBIJQp+vUaUtTuL4PFvuFK5nkcALzta9e0GonhBe2s2omAuRrgBfckIXtbAc0UwH74tQiqxr/whH9jDp7wmojt4GVxJQJ8gwxKH8JGOA87A+keBfxG2UMenz/mZD8A9lAJtI34M/IlCioEpLOAmwMz7tMDAGiYghpiQzyjpnMIC/Ld2roGZ64ACZgOsT2fo9ygL75GfiZd8qDLZkoEvxUB0uUn819a3eEBnpYq9kLQbPn5UixFpFDK3ChDV/WFODfiBxzBaDDiBrxLASCNBbKYJWBkoXt7AXKZwNeZ9hmk2nchKewB0AzC7UsDBnDp4ZQZw6QRc2AfP/kqcjGPA0pug6HYai3T4W3T4/7mMu3CxAgj9JxjKIOis6MZIYFgKPI8FN2/B7kXwVC45lPEOJ1Qwr/zqSK6OFtXK34CXSdIiOx5DQOpZUGZBmTH1cYUp/R+W7wU8kuOQnp7O/PnzGRwc5Pjx49x7771YrVaam5tpaGhQcQXBwcG4XC6ampqYPXs206dPR6/XKw5GVVUVs2fPZnh4WAVbXrx4kb6+PgwGA/39/Xg8HuUYLPkfMhfI4/HQ0tLCmDFj8Pl8tLS0qC5FRESEGvUEBwerDoxer2f//v14PB4mTZpEREQEDodD5RfV19crzxOn06lS1UNCQnA4HAQGBuJyubjuuuuU1FoaHNpsNgoLCxW/IiEhgfj4eNLS0rBarfT29nLq1Cn+/ve/KzXW9ddfT2dnpyK8ytTx+Ph4BgYGVPcjKSlJxWDIsEuXy6UcfU0mkyqOIyMjSuEl5elSdi4zoHp7e9m+fTv9/f1ERkYSGhqq1E29vb0YjUYV11FbW6v+SL+d/v5+ZVQYHBysyLBy/HbmzBlSU1MJCwsjNTUVs9nM8PAwRqORuro61YlbsGABfX19TJ48menTp3P69GnFr3I4HIwdO1aBUMkBy8rKore3VwGMsLAwqqqqKCgoYPz48SqoVRbvtLQ0LBYLfX19REZG0tbWpgB0eXk5AQEBingveVft7e0MDAxQUVGh8twMBlFg5GjK4/EQFBSkiOPSQNHj8ahIBjnqa29vp7S0lN7eXmJjY0lKSlLqNdkJLS8vZ2hoiIqKChwOBwMDAyoGRGaI6fV6YmNjlYJqeHgYj8fDwYMHOX78OE6nUxkmSkWf0WjEarUqoC8T7WU3UHZ0pG2CXOT+/pCWu6jjbyvh/UAoYAPc4OEFQJczA+6Cj9YIVdVPrwVogqcssM1CIY8SDzzMEGx9UczGzt7NKxyE515jBQDZ0HMj24FhFnCrNM7V/Pmn8flVyc0/Fv85H0T598GRJ1lJGd2Eijf9l7DwfwwhFYYXtJFJARWA392hJWiLLC9GliKQwx6oew2es4jOwEAtz7OUaLaykoNAtrC30+KIVohPZ0obTGmAH62GCayjixn85AH4kHUEBi4kpFds/i8B//7r8F+8iQcwshL4ln18xEEo+4BD9/kFafsWhCT7rUpS7wPehMwXgXjxmTnFiBVuHL6SdeoTm88bAHtYTRmfggp2lcqcw4g662/YDc/OE5XwMaQ1jcCpfwNcBhLoYCWPasa8b4hz0rFBkGFdRUAh8CYBLAKqCWMZbp5l9bM6MoA9PCccr98AG17OsYHzPMV5ADKEK3ZIHs/zG94FVnINtFzQtvRVqDtOITs0AFbOfG4Q18q6ZXB2n2hzxAMbJsOOWjjyAcLLqUyAkFAIihVJ8QcAeABBQn4fLxeAP8P6E/DBTSjCykfwEfdxPSOcYwYHgCHux0suQt8Fb5NEDkeo0P69EwvwtvD/eek1uB/8C+HbRfBPK1z0L4LjN4qTNHkp3PgrSLqJ99fpACf+th0ka6F0o5MFwT4b+OpaGM2GimkypEN0eP4bPfA8HNwA7bDgN8L7qg+BV9oReEVOpJq0S+MpgjjKQsQF9nNxBbuy4HOLuCiauEI4kkSf/7D8/zotT5o0idtuu43Kykp6e3tZsmQJ8fHxVFRU4HQ6iYyMJC8vD6fTqboGLpeLkydPqjyj0dFRvv32W+bOFV/WlJQU9eTu9/uZOXMmw8PDKq1bGvt5vd7vEJ8BpSoKCQnB7Xbj8XgwGAzKFyU4OFglmUtir+z0yA5PREQEZrOZ6Oho5Rg8MjKiXHWHhoY4ceIEoaGhVFRU0N7eTmNjIyaTiby8PCIiIli1apWSVp89e5aIiAhmzZpFeHj4dzxc1q5dy9KlS6msrOR3v/sd58+fJzw8nJGREaKjozGZTGRmZhIcHPwdGbHcFxDp4Q6HQxnXAcokUXYmwsPDSUtLIz4+Xu2P3+9X45PMzExmz55Nc3MzNTU1uFwiG0cCC6/XS1RUFCtWrCA0NFSNi/r6+tDpdLjdbqVi6urqUuqh+Ph4EhISSE5OxuVysX37dpKTk6mvr8dqtapxmuSh+P1+bDYbNTU1yuOpvb1ddWccDgdTpkwhKiqKyMhIpk6dqjgxcmSo1+tpa2tT3RLZKbTZbOq1RqOR7u5umpubycrKIjw8nMjISKUevHDhAtXV1YyMjKiwUAnEMzMzlcRddlJk2rrBYCAhIYE5c+ao0Zfcpvr6elpbW/n22285cOAAUVFRGAwGpZaSJOKTJ0+qXDSPx8PAwABer1eZSKalpWEwGBT4joqKUkTj7OxszGYzer1eyd5l5pk0ebxacRUVFaWuAb1er/bpar+eH/KyAljFLt7U+XmELcBPeR2AKfDZNu5kBrPZwA6CgDfFg/+6DvkK4HpVU75lGy8Atz6r40Pegs83Asc4hw1YzE4rKOvZkDIRddAEbawTP9AOPi0XaWsRzL0JO6BnELZ9DU5RHGoQmOkZWjRuT59GhX4VMXw7JrgN5XIPF/OJTQfPboM18zQPm1s4BHzBRsJ4ije1LWgCVvEeHwG6hCLoE2vw79zGak7wiQegmrs4yOZwuB8bY/kX9iWwPQd+94WYpsxmF3c+pxGW4wFbB1huBJJhSxYN/t1wFKqKQP8H2HkDXMyFsGXAVgNsAl0lYofnI1ollR/zKRs1qzqx2mREM0NKm3WpSfjPHYGsfbCmQ9S/XwILO0QT6hlo41kOIynli8WJtO4AS56mpGoB4A76WcLnuLkEm3/Fp+TycKWf5bcA/Aw2btbkzb9lEqF0fgpGPuEoa+HgBTj4JId4gi+wQdIOYBVU7gXb3VpiOyIIlOfFdvAysImEpTrmPKFjD8Ww1gVzy4BkfIAXC+waxrsM3C9ClX83Qsr0MktwwUAuaP2Qj9jNSopFl2P9N8xH4msjx0C73mfh07bgAC1cRo8R+C16RNDZj+D2XSKU9okxcL/2cY7bCdPAMhyGs7+Cz24EsrmXhfirDjJs0XbrrxBQA75AAfkygIFwcQ3fiYBrbwBDMhz1EWDDr4hEgFo5vhyLeH+g9jXaTBD7Wcowf0R4XN0jXlFmEUhIWkX7gCFtRZHaz/9h+V7AM3fuXHw+H5WVlQBce+21XL58mW+++Yb4+HhFgJTGgv39/YwZM4aSkhIKCgpITEzE4XDg8/lYvnw5gYGBqk0vRzRZWVmEhobS19dHW1sbvb29XLp0SYVUDg8PK8deQI2b5Hhi3rx5KgFayqqDg4Opr68nLCxMkVw7OzsZGhqiqqoKg8FAdXU1YWFhanQBEBUVhcPhwGKxMG7cOKUCKyoqIiQkhLy8PEJDQ1X2Um5uLmazmTFjxvDll1/S3t5OV1cXkyZNUgoaWaiXL19OSEgIxcXF6PV6NZLq6OhQXirjx4/HZrORm5urilJkZCQpKSlMnDiRqKgogoODSUhIUPus1+sVEfzixYv09PTQ19enOhITJ06koKBAmUT29PQod2KHw6GIu3KU5/V6+fGPf8zcuXPxer0qxDQ6OhqXy4XValVBr2PHjlWAobOzk4KCAm677TaOHDlCYGAg1dXVio/S2dlJf3+/SiOXYaUylkHGhURFRSmA0dPTQ0tLC3V1dQQFBSnFluxESN8ko9FIb+//5u5No6Mq073vX1UllaGSVKbKVJlHQgghBoKAIMggjWJDi3i0cWjUbrA90HrQdsShuxWV14G2jxxtOQ4cbGhQFEFlFJAhhBiSkIQMJJCkEpLKnFSGqiT7/XDv+4693qf7Xet8e9xroZBUqva+986+rv2//kMvPT09HDx4kDNnztDQ0KDQyerqatW8+fn5cfnyZRISEqitraWrq0vxceQ5HxsbY3BwUKn3rFYrmZmZytkYhNIpKCiIkZERNbI6efKkOkaPx4OXlxfHjx9XxopXrlyhtLRUkcybm5vVqFBK0CXSKRFByXuSvknyOpdhtpqmKcm+HClK2wS5VtKbSsaDyEZHojs/RnZ+ahye23EB86jRksXUZPJOJmFhOlsQ1fYXgBkbw0JmnArwGA+iJwdM2A87nybwvIFZHdDHn0RR2bUOlk0G7sKbBgyB68Td+nZgSTKwT3ye8ozRI0l1iUnYWljMLgqwE8MorF4PR+QTPdTwNpmIp90EtvIZ8Ac2w3YvplPGo+RB9o0IZ73PuItlvMoD+qjtYeAjpvAJ2jeb+RB4g2xmAUtZB3xKixsCKcKUZSEK+PndsMMNXicggRN8eEATvFtu5hHmMh24j7dZcJuuCmcPxucDoPQBeH4AimzwyueY/Lz4w3pYbFjJDRGQUATBQxC4F7wrxeH7rIW760GzMW6ssgfIeBkfNuvcknED59uBd8ijAXgEBzG5IIp+IVi3Mj3PANwtduztKuAJ+pyaHg77GvjVQ/0q/Vx/zFXeJZAePmQG3+zSYDQDNoywmDLIcMAb4Bk4DJToXk0xjLGOoBUwn1Ho+UQGowETYWudfn7/DTK2i70+8Ta8e1wccH02EADbs0mgjBY+4CR1/Bp4kmDEWb8LYc4yD7gDvuqBJ8CLe5Fap2/4Tide1xLNZD5F9Cdk3wL8O5eBb7gEeChghj4ODSDeLa4SeW1NAXHNrV8F/F10vPr16Z5jAFMRb7JdvPcBSfT+DPHCz2jgMISC1wHGrbijwHIVLMVib08hmFJ/BMYw8Q0ziOZF4D9E38Kpfxhdwbh781vAlyQxorzRI4FpAtWpso7r22WzIzc34+Sff7L9/460jEYjdrud/Px8GhoaCAgIUPlKSUlJKjDRZDLh7+9PTU0NCxcuVIWrtbWV/v5+pWJpa2vDaDRy7Ngx5ckin6bla3/stzN58mTFZ+ns7GTKlCnKeM/Pz0/lc8lCJYsEiFFET08PPT09Shk0ceJEVVyl6SCI+AdAmdVJ36GFCxdiNBqJjY0lMjJSRU+cOnWK8+fP093dzffff4/b7aa0tJTy8nIaGhr49ttvuXbtGuXl5XR2dnLt2jWWL19Oeno6f//732lsbMTj8ZCamkp8fDw2m02ZK8rCLCXF0gVZKrA6OjoUf0r66QQFBWG1WlVYpyQcX7lyhfj4eBXSOWnSJAYHB7nuuutUar3koUjCcFFREQMDAwp5AhS3ymq1Eh8frzyS5Ohv4sSJnDt3Dj8/P5UmP3fuXLy9vWlvb1eRCvK6KioqIjw8nKtXr6rjuHLlCk6nk7CwML7++mvFe+no6FDnq7a2lgsXLjA8PExFRYXiLk2aNEmNz6QdwaRJk2hsbCQxMZGxsTHcbjc9PT1qFDUyMqKcjCVZ+OTJk4pYrGkagYGBdHd3MzY2Rnt7O3a7XQWqjoyMKCPIS5cuERsbi5eXF9XV1UyZMoXm5mbCw8NJT09H0zTq6upoaWlRnCFJLPfx8SEgIEA1JDabjcTERBXPERISQnR0NCkpKQwNDbFz505l4yDdsuWYUvoFyTGovBZgnMgO/INMXY7EpCfST2or8ieBCD6lniMzNShdzxj+FPA8YubwFtp7m/UilARLypjOdn6HiY5gDS5tQaix8jCE/QlI5SsssHK9UHjRiYcCtJWIGrykCDjJdJ7hFGAqBngD6jcAe+DdMjxsoiNbKrDmcZXVYl+viafjTViBVOHFg4UCRDn6m3g5DcBiioBN+vv+AtZ+zrOY6KAJAUlVAnuYtFjgQj6U6flXkcBD3G2G3mLoxcU14Itv4JQZPlssGC4smUz1SXiMrfwnFmYBCaznCHZOAlrLLl7BBZhhpr+Ix94HoyvguZdF0ZuFaL2eQBS22SMCEHhY30Me0v9xM7BmBHiCYfJwI9ZBFs7XAG8usIMk3hnVaOE00AAnlgC3U1CkAbshe5cgQfMW2G5h6T0aHNgPPUmie3K+QDRbYHQNfXr+Gd8Cpnrg59wFaF/GYoh+G6/NAMd4TD9H4BmXRlsXwvMO4ehMDqyZyrghjk7R/gssZi78FR5LMogQ0VVbuMoHwEYSSKaFNTpyJyLAT5IETGMFe1lBMJi2MnJgSF+BfWJ0RiPgIh74hndZAYRxACN1uoLsVzzJGbSTZwhFNMneLXAAH97gbe5glELAgY+Yn/IIrBwB3iOXMqLNIm39dzWwiSRylxiIZi9wK7CR9ynjI8S55pR+yCVQGS0I8CMZMK1YoHJvkMcmVuvBvP9Ni1MjzPAurHPyGIeZpR/5jxudvfjQwgx9zWVyej6M2sbHVj9ubCz6H8nfMSM65H+y/cuGZ3R0FLvdjq+vLxUVFXz33Xc0NTUpvsq2bdtUDlNsbCxJSUmUlJQwefJkenp6OH78OImJidTV1REUFERnZyeJiYm0traSlpZGZmamIpsGBQWp9O2mpiYyMzOVA63JZKK3t1d5jUhFUlpamlK+dHd3YzAYyM7OxmazkZ6ervKGQkJCFLJhs9lUo1RWVobNZuPYsWNUVFRgMpmIi4ujv7+fvr4+Tp8+TUdHB5mZmdjtdhobG+nq6lImcTJfaubMmWRlZZGQkEBDQ4PiC1VXVzMwMKDIycXFxeTl5bF8+XLFt/nhhx+oqKigtLRUKXukQk2azMmxycDAgCKbymOT32tsbFTO0QEBAQQHB5OTk0NiYqI40Xp0gFQayRFeVVUVAwMDKsVeNlM/bkalj8zEiRPJyMhgwoQJTJgwQeU3paWl0dzcrBCfKVOm0NTURFRUlGp64+Pj/4EQbrPZcDgciqs0NiaS7/v7+zl9+jRXrlxRajkvLy+qqqoIDg5mcHBQNaxSQQao5kiaP8r1kqM5mX7u5+englwjIiJoampidHSU5uZmamtrlQePx+PB6XRis9kUWdnlcuFyuQgICFD5XjI6QxpFHjhwAKvVqsaMkiTe0NCgVFZ9fX2Eh4cTFhZGeHi4Us7FxMSQkpJCVFQUIyMjisMlmxAZzSET1mXArsViwc/PT42r5N+lXYO0ZpAqLMn3AZRnkRzdNTY2/n9vBP83b2a4ykpBAn4Y7mcLi3ECn/E+D6C1ODD8eg6v8gCLqQcy+R3gOTwC70Ea66FqJ3soggNPAxcY42WOsUUPE30YqvJE0e4E1ucBgrp6GQujewCnDZK2omIDtm/guTLoYCfwLNFsEzsaLwCPLHpg1xI2AmN4MRtRlx8EsDtpwaYjD29B0iEgno3vGvh3RqHeDkRxPw4a2MuDYg8JBW5gPwBp3MPfO4A7wLJD1AfTYgtz3xFl2/IGaPPKODhbqPRzcLGDJt4DcnEwHxiOEA3NfLby/mkDT5YaBLN4KXhvhHN2eC1APOGHIlrLo4dgx9PiwTwHePNpMP0W/Sm9EmEbOI+vdB1PLaKGPQx4aBEmjgkIVc72bDHvIgTydOUSn8JKyYreAZ/cAksGwJoMCyLgNWjhbTAtB+aJ8/1BGRxOgmf2UwgM3wIfsR7fjXAbDr7cIuJGAtnMLKC4R0NkU0SK81mWDZzAi2fF9bZ3AytwwM6nBV3rqS0EIIEsCUdkcpVVQAU7mEEYryBaKTF4ugzsxg6H18CS7XizD6jU6SmRGPlAR28+5T7E2OhFXDwL3MYZQY+aLRCWUKAkQf4y/I1ZCJzrdYbBlIyAS54ilwkU8xTxwMeMcn0arKCea0ALpXjzGvtwqPiNkZVw6k1onA4jC0QbVmeCD/0hKBc+w4I3Fxhvvk+BrZ4ObS3TiSBSX41GBHZ0BBM+B40gAAAgAElEQVRXsTHCdYguahai4ZkGWMYbnVbGG54AxPiqS1wGrB6A1ZPZY/vno/p/GR5aUlKiSedbmaUkM7OqqqqUaignJ4f4+HgaGxtVREJHR4e6gWZlZTEyMkJNTQ3e3t4UFxdjt9uVi21cXByAIsBevXqV5ORkRkdHqampISMjA6fTqUjDMTExtLS0qNRqj8fDxIkT2b17NzfddJOSo7tcLqqqqggPD6ezs5Ply5fj8Xj44osvmDNnDlarVTkBy9Rpj8dDS0uLGiuYzWZycnIoKxO22IGBgcTExChH3ptuuklJ3Ds7O4mIiMBkMhEfH4/T6aSjo4OWlhYSExPZtWsXU6ZM4YYbbsDj8VBbW8vly5eVh1Bubq5K+5ZrIvcD+AcTRVmwenp6uHjxIi0tLYqkGxoaSnl5uUpylxJtqQyT6eQ2m42AgADGxsZobm5W3i4mkwmbzabM/GQaeUBAADExMSp3ClAmeampqTQ3NxMXF0draytFRUUsWLCApqYmjEYjaWlpqjGQY7dp06YpVMbtdpORkcHAwID6XOn9c/ToUZWH1dvby4QJE/jss89IS0ujrq6OqKgo2tvbSU9Pp6KiArvdrqT8MsokODiY+vp6jh07xuTJkwkKCqK2tlbZINTV1REeHk57ezuLFi2iqKgIu91OdXU1XV1dJCUlqfiL7u5u4uLi6OzsZNasWUo5Jr1/ZPbX4OAg1dXVynvH5XLR3NysXI6tVqsaNwUFBSmvnNTUVIW4AUrVt2vXLvr7+7l27ZpCd2QOnSQhy2v2x8iOJEH7+vpiMBgUuiPRzd7eXhobG7lw4QIej4eCgoKfDLlnowHtD/uBJU5gPtqHZRjuXwf08xjbiEPccP8bSI3VCGwyMIgPI8yGXYcgAPYsEctx+2aNrA0GylnJbHZxFhMeamAwSYxNqpJEhf9kIRAKe3fCsjOI0iNKFIcXwikwbAZtBkw/aKAW6MAGu9rwWWkQSiR+p+9ZCE/yDJtYwkcc4D42QM/rrLAa2I0HDnuJwp9xSD/iY8BlAtklJw3cxwLgHRYzgUYEevIlG3ifzfQjaM+hwBE+YTH36GOR12DmB3id9mW4d5gHguBD5gj+TCEYxjRYM5XH9Byrfv2T+7gE2zLgMXikRzRM+xCxBZ2Ixq0QUc7MiMbn0VuAr0YQtr2NQAjRHOYhxKE9RDZwEmKt5DrESj6qjYDTS7xhDhizA/Tcq0IE3+N+3sTJo9iBagTZqBVRGZ+FrTME4XnOenzYosCB5pNgmP0B0MCbvMijrMHIJ2TiopxV3M12drCTNO6khp2wdSWsqRL7PloKphF9JUqI5nFasMNgE9P9DBSwBoF35UJ9N7OTDJxkDdFsxYkPNzLMEZZwPwf4FJGMPgsXJ1nNk2xjE0l408BbevzINESfbUagIycRyMqzJ8Ew+3lqeZFUFnA/h3kJyEKAapnAgx3w72GimZyIC0gkDScPA4+yANgNr1jhKSdGkrgVF42I1z9YDARAZZpY7WmIieRnjOeZvcS70LNGV8a1wuN2eL2eb0kmBNHauhFNbYuOaIomcqK+h3H6VZkKeItsrVrGSW5x+uVuBlY6CCOWLxjvgzL/SXjov2x4Pv30U02ODyZPnkxAQADnzp1TN+jm5mbmzp2LzWZTMQUg1CvSvycwMJC4uDjFqejr62NsbEyZ16WlpZGVlaUUSidPimA+aRJYWVlJRkaG8l6R7r4hISHU1NSovKPrrruO4uJiVRhdLhft7e04HA6sVisej4cpU6bQ2NhIVVUVS5YswWKx0NDQoAIpGxoaKC0tVXlgsbGxREdH09TUxLFjxwgMDKStrY20tDSioqLw9vamu7sbm81GTEyMcuWVsQenTp0iMDCQ4OBgAEJCQjCbzbjdbmWmZzQaFbdIGsFJkqlUHsmxEqDWTyrX5KhQjn4SEkQ7L1Vc0v1YIgXSddfj8ah4DjkKkWiZr6+vkv87HA7V6Mh1knEisbGxao2Hh4eJjIxUERi9vb2kpqYq52g/Pz86Ojq4/vrrKSkpYXBwkNmzZyvFl2wkbDYbP/zwA9HR0QwMDCjDxaSkJJKSkhSfrKqqSnFU/Pz8cDgc5OXlceLECcbGxoiNjVW8Fx8fH2V9IDlJ0oSwsbFRNWnV1dUkJyeTlJREa2sr/v7+uFwuqqurmTZtmlozmeNmtVoJCQmhuLhYNUvSciE4OJiuri58fX2pqqrCbDYrGb8cB0qkSuaYSRI9gI+PD+Hh4URGRuLt7c2FCxeU2WR/f78iZvv6+mI0GpWztOR+STNCuQZ+fn7K3FJGUcjw2bKysn/I2iouLv7JNDyvYdCWItB3SYjsR/QlTyBu2KEIQ7Pn2AmLVsLB7dCzCqwvAIX4cIDhRRocXA/MIow7mQfsphRxq8+HO5fADoQAqFQvgJtLxf162XJy2Usx+2HzEtjwMhQ9jff14PG8TALPcBU7vNgEz09GYDl3IYrzr5jPdo6g2xHv2gkrDwC/hslNomP4JBgoh1E7mIJ5nx4CEIOQPyOQnY+4hTtH4QWTGBYsOgpP3QSbWAC4uY0TBAA76CaXYIqpAx5Be+kA/BZeCxNeOEe2a7AqgttwcjPw272aWIJPtgH3wqiXID+l6DvQD39xoMYXrQirlwDE0riB91YiJhevn0E49s3T36AQqATnu2Jd7wPTGxAxJN5r+AW9cUwCUw2sHRIFf3gZ3LAXvtcG2IeF5fgwwmuIQpqPYM02kMthilmlXxV/5hoWougGhxXsM3mVM9wOZGLCw4dAA7fxDF/+KLkcTuLtbcXjeRm2PM0j6wy8U6Xhk2Fg2KEx327gCDt5kzv5I9BRpRGYYaAPK2n0UIMN0ZZmcje72EEd95NMCvAcc4BG9lHPUmyk4VSJ8KHADv7E3TxDCVDOAlZwmE36ml5G9AePksRi6vl6Nzy1QhCBTQxzFYgiST8r96Gd3IJhtj7m4y5EG5PCbczki9vhqz2it3y7F+qDxp2wpSP4Y/pRlLMBWATOhaLPbxBmlJnAo1o98Gvmc5hr+id1YNdPfor+DpH6v0OQgSIQCT3+49mq6Lvn9zSzeYX/Yhz0kQ1P5P8mLd1gMJCXl0dSUhKjo6McOXKE4eFhHA4HRqOR6dOnYzAY+Nvf/qbGFAaDQfnoSFltWVmZQg+MRiMJCQn4+PgoBYnJZKK6ulr9nM1mUxB8e3s7ISEh+Pr6EhYmHJWkLFgGhkr+S3R0tArD/HFkgZQV9/X1ERwcTHZ2NgMDAwwNDREWFkZUVBQWi0VJr8PDw4mPj1dIUnt7OzfddBMul4usrCzS09NJTEwkNzeX7OxsEhISVBhpZWUlu3fvVk2iHB99/fXXHDx4UKnEMjMzuXDhAleuXOHKlSvKx0bydoxGI1arVYWGysytoKAggoOD1dcDAwMBaG5uJjo6WpkdBgQEkJiYqJpFiQj4+/sDqEDLgIAAPB4P58+fZ3R0lJCQEEUinjp1KjfeeCM33HADUVFRpKSkMH36dEpLS2loaODs2bOEhoaqkE9pLmk2m0lLS+Obb74hJCSE8PBw0tLSyM7ORtM0xYmSEnPpKyPDNOPi4rDZbPj4+Kjx59DQkFKIhYWFKZNKiVJIW4HrrrsOX19f5syZo1R3ISEhpKSkkJ+fT1ZWlnI2jo6OJiQkhKtXryrEbMqUKZw9exZ/f39iY2NJTU0lPz+fH374ge+//15lV0npvHT67ujoIDk5mcDAQBX02dzcjMPhwGazUV9fD6BGWTJUVKrYgoKCcDgcqkmS3lDy9+fcuXPKNsFiseDj46PGVt7e3qoBHhsbUyaN8usmk4mhoSHlx9TZ2cmpU6c4ePAgpaWlSuklidM/pU0XbfMQC3gNwX95DIE83KenRHeimw7uXakzcjvBuhXIh137Gd6mwUHhKgtvkQrsZgHidn8XEEngLsDkxKcMxJ35JGzYpcvQT+l+IrWi08IMeQ5GfAGi9EHHezp7878Yz+y6DEyjHwhjG3CfPhuJA/4uuohPRsQ+3GOHRyCXHiFBZw21wA18x2xuYR+QYYJXbodFO+Djm3Ql+OFDvMkJDuCjR1I8ghvQJibjzbcYNiZhCrPwRA187YYnVxmAB+lCNDuBywzwyS59n/8TTA7RAOl8i187xMjsr/q56ESUMUkXvwDjUAV/RRxgBZTNgKnrWGx4l9wIREX7Fl4eEu3g8EIgBLTnxc+PDm7hHW2AYa0KPn+B77XH4YA/S7drjLw4BMyDsoUw1Sr+TrzuuTMLln9AIBaiqAN+RoXdgLb7DG8hsBoPQzC4Ch+e4cu9GvfTo+/9EcIIxmNBmBquO8B/YYKMEcYwgRuO8BTwRx4liQ7mQMad9GEHjnAFE/NxkksZWezSydpv8SFrhHcP+WRRz6cApOpNhoUSg8YO1nA/z7CDOVwDXuUwsrHP3CGuVOGfdDPfMIenVghu8XcM8w4QhY1o6hGYjwXDbBvzKWM2TuHcTQofMZMvToJhj52NwJ8LYNRXnN5T+lWYo69RKAL9+QObxXVgOySWOQo+8IVHtTPsIZnvOUwDUI6NDpIQjY5EdOIYT8ryoIycnP7iA3OAOSMw53FW+Bn4nlf4H/3VUUBGLyT1QpjQRf0ft3+J8Ozbt08bHh7GYrGwY8cOuru7ue6663C5XPzsZz9D0zQVVXD99dercEmZmZSWlkZBQQGpqal4eXlRWVmp/EWGh4fx9vZmypQpXLx4EZPJREJCAhUVFYSEhNDQ0EBycjIXL15k8uTJeHl5kZyczNGjRxWa0tnZSUdHB+np6QwPDyuuht1uV4qv7777jvz8fDo6OpSizOPxkJ6eDqDQFrPZzJkzZ4iIiCAyMhJfX1+VaC0dn3Nzc3E4HFRXVzN9+nRGRkYIDw/H4/EQEBBAaWmp4n709fUp918QLtDBwcFYrVYqKytV4xEdHU1SUhJDQ0OKX+Tv769QHEm29fX1ZXR0VDUFUt0jibPS18hsNiuZuXR09vPzUzJ1aTDndDpVwrokrLrdbsLCwggJCSEyMpL6+nrFFRoaGlJjzaysLM6dO0dbWxsDAwMsXboUb29vGhoaSEhIwGazUVVVha+vL8ePH+fmm2+mqKiI5ORkNQaNiIjghx9+IC8vT2WmlZeXk5aWhp+fH4ODg5SUlCguUV1dnbIvyMnJobi4mJMnT+Ln50dERAT19fXEx8fjdruZO3cuo6OjVFRUcOONN9LZ2YndbsdoNFJcXIyfnx/nzp1j2rRpBAcHc/LkSeXxI1Gd8PBwZWZptVoVKhIaGkpUVBSXLl1SOXO9vb20t7ertZ40aRLFxcUEBQUxODiI0+lUqi050vLx8VEGgP7+/qSkpBAWFobVamV4eFj9zjQ2NlJeXk5tbS1ut1vJz6VCT5oGytGWHGnJaAlfX1+VO9bd3U1jYyONjY0q78vtdisis7xGqqqqfjIIjwGHBj9njz56qWQcOL+9SIO8Q4hH0SeEY29pGazN5rZ3DXyJBx7wIvADA33sB8cSsCcjbq85wCwYXSUCItucgqvzc4Ss1zoCPAVlr0P2cuBDeMZK7stQrCUDBYib+/sYeYGxzf0CfJhzBrbOIGEtXNWqYDAD/GL1z7wXuA/qraIXOsZ4joMLQd7c8DiijfgC0WJcYzEv0oooSsfxwc4wR4BUlol9GNwpFsvvabSCVzg1XRCk/7xU/JDhowVM5zBnl4JnD5jNb/MI6/lPLNyLiw/ZCa+shKfWAvfyB8MMnrPCl0L8ymVE6Zqnn5NKRONTCXzuC6N3A4XgUwbD2hYgh/sNN/I/XuCZBwmHxL4v+tF5LQSOBYDmB1wF/A4AKULJEyDWJnohtGRAVpVYomGbvhM7nbDLpo8P7TyJg02c526m4gZ2s1pf1Gdh20LCVhvo4DxpTKWGtxHtWieUfc6T2QY2Pa4pZnaYn4GOWzX46gCwh+lsoxboxcQxRrlhVAPT47DrdVh5nFrmkooVL4Z4mmFe0sNDs3CQA+xgGTg/B9tysthLOfuhbAn7sg3cWgOmNAtj3MNtbFWZ4/v0S/A3CORnI4eJQ/SgZuC32IFyjNgZY62+spXAx0yniHnAJjbgzZt4iCIQh8j4RFgq3qpfjX9k3BjwK6CAZTD4OfiNwCte0ADefwWPpwiYTxg9CmEVpPEQxKOGlOrJIafEXKP0r4XqF/cdPMIBfse4vVUAEO8GwwgYR8Do0i+urP8FwiPTto8ePaqylYaGhoiLi8PPz08V7sjISBV86Xa7sdlsTJkyRSmNgoODqayspKmpSTnogghjHBgYUBwM6UJss9mUx4p0NpYGe/39/YyMjCj0QxI3AwMDGR4exmQyMTw8TFVVFR6PR3FqNE1T/JaQkBCuXbumxklNTU2q0ZB8D5m1ZbFYyMzMJC0tTSWEL126FD8/P4KCgigpKaG6uprz589jMpk4dOiQStu+dOmScgieOXMmNpuNwsJCgoOD8fPzIyYmBovFQnl5OUajEbfbzdGjRxW5tb+/H03TFOIllUQguEReXl5K5i/5IzL+Qaq1rFYrg4ODjI2N4evry/DwsHJk9vX1JT4+nvDwcCwWC2FhYTidTpXzlJKSgpeXF62trTQ0NDA6OkpUVBTffvstcXFxZGdnM2nSJPbt20dBQYEy+5OqJynhb2hoUEaM/v7+fP/993R2dpKamkpJSQljY2N0dXWp4l9TU0NbW5tKaS8qKiIqKkqpAwcHB9XoJjY2lpaWFsxms2rUuru7aWlpYdq0aVy5coWmpiZKSkoYGBggIiICo9GobAIkgiQNE4eGhggJCaGrq4tJkybR19eHy+WitraW06dPKyl6fHw87e3tVFZWUl9fz9DQEGazmezsbKXEstvtdHR0kJ2dTWpqKh0dHQrZiYmJITw8XJkKyrGh2WxWSGZFRQWHDh3i3LlzSkVoMBgUp0sGrEpER26yyfb29sbtdtPU1ERhYSHHjh2jpqaGwcFBPB4Pg4ODquFxu914PJ5/GJ/+JLZRO/B3nkTcB+chimUK6LKnj4GboWqGuHs+k03Cuwa+5E9AInzwNH08D8uXgH09udQDv4Bb3wVywHQIUx9w2Aa25eKNG4BdXuL7igP+PjwoM4JuFzLuF63At4yRLB+0gX3wLTT5AlyDBgjEgUB+zIC38LyJBOIgcLnYfZ536P4jcbD3EPBHvHkEtr3AN6yhmG6OsIwRfslVdpLq1AA309lFtJ8B/CLQCl7huukCgfnzbmApfPcRJHCYAv6EYd8MLGYT2tX1pABjrNV9guKEjwv7ADfPaRFwVTByJF8nSv/zFrDBVzywpwCTh9Bl0TC8DohYB6/cyCe+8MiIIDr/NzBXP/pXrfDq03B0NWg3QoITfu0PbF0iQkA7AdN6WLCWlksiib3cDsN2REr7NPAijsdWGhjmbeDvbGI13kxnB2vYXa+J88YUqBJ8qw6HRhhTuYyFfawHNvEYeyG7ik3Y4PU7wfYA+L1AB+8KxrrO40lBUJH/yijz0YNT8YaV24FGSoDZ9GBimJfxAcwk4KCcP4m1PfA52G4BnqUaEzyzBOJhKRswpK1ijF3MZyvvIRyadpDN7fpaXTSDkTO8WCOu8ijg4Xzhx2PEzsO48OZNolmEVrCexRSRghg5fspmPDzLChzsQFxav9EvtUb9t6YSeA4rz5FEAXbgIXEJvOIlTvC34PHcySNMZTE9xANOfHBhYdx9x63/ZjYwnqDljZ7MhWgus/gIC6O9B3jDLRoc6duTMADefeDlAONB/RIM4J9u/xLh2bRpkxYcHMwXX3yBx+MhKCiImTNnkpOTo8zPZOE0m810dXWxe/duli1bhsvloqmpifj4eBwOByUlJWRmZpKZmankxampqQQGBrJ3715MJhPp6emqoBQVFZGXl4fD4SAmJgYvLy9iYmLUOG14eJj6+nqioqLo6upiYGBARQXExMRw5coVenp6qKioYMaMGTQ0NDA4OMjUqVNV4nh1dTWzZs1ScL8MLZX5UJKHUlZWpgwUe3t7mTNnDkVFRcTFxamvRUVFER4eTldXF6dOnVKNXVhYGAaDgaqqKtrb25UvTGhoKNOmTVN8n+DgYMWLkUXRaDRiNpvVmAuEnFiOUUJDQ1USuDwfY2Nj6unf7XarRknmK8nxmHzCHxwcVJlNly9fVsovs9nM4OCgcoD29vamsbFRjcba29uJi4tT8ura2loiIiKIioqip6eH5uZmgoKClEllQUEBY2Nj3Hzzzezdu5f8/HzKysqUeqq7u5uIiAhFtg0NDaWuro7ExETKyspISEjA4XAwbdo0jh07pnLCent7VaiplNFL073u7m5VyPv6+pg4caIaX/n7+ytCfXt7O4ODg9jtdk6cOEFeXh4xMTEcP34cj8ejUMU5c+Zw4MABrrvuOhUU6nA4CAsLU5EqsnH++uuvWbBgASEhIVy6dImCggKVrG61Wunp6WF0dJTExEQlKZcNuZ+fH4WFhRQXFytenOT8yEDQH/9bOiZL7o4kd0u/H9kAyWvDy8tLNToSSezs7CQ4OBhvb28uXrz4k0F47sCgNSK4LMcQQIgb2LRNEw+Xj+gvnAZp26FmJ9y/0sCHDg3sI8D10HMeH6uBMUx4CIXkNjHJ+pMTttnADT5rDAzzJ+B3sMgfDm4FOmHwafGB1rWw6F3xeByA4LksBd69Uf/LQ9BjBWsVBGeQ2wPFTYC9h2iCadmrwbIDRHOLiHToOQRpQNtmfm/YQCFwVCuC0TwBToQCtq2IQhIK/JFj9CiuZ+o2DVZP1v8Vh2DXpFDBLlL1J+bn/EWDWIEgsn7KYdzAvS3wXbRYz5dYiWhJ/h0Bc1wmzLCE20HFBfwFUfRb9b2R6E4DomjtWIkokO/B728RPzMRkQwmUSEQKILMQ7tP369X8xi3j+5EeOnJtOw9+teX7CLasJIWTSSdC2RBpylvWSdq6/Pb9ZPiJt/QxLn9sGKJgYnAS1s0WHcjj3BCT04/yKss4vc8D3yMkTbGuIc0tlLDAm7jMPMQYZvfAPOowzOQjLf/agLZRt9hjY8WGHgE6OM0AiuJx4etDLOExRzgGw5C2UK0KgOFKyAfO1qNg1+midHURD4BzCzmTr45oMGSp8niFco5jxezGOFXQA7aS2v5+Ub4ogNcYTAb+OFmmPStuCoeZJz3spQlQCo+bGGYT9AK7uHgdLiZBfRzGEsxNOaKJlbStFpBjy+ZBc4XxImtAPohd4NBiaukotyDhTH89a/mMN74SJ25SN0y8jL/hYv73DBmAuOoaGzoFJezK0z4/qg8imsI1nQOuFaA5X/D4amtreXSpUtERkby7LPPsnr1aq6//noiIiIYHR1VfBmz2aySuu+66y7q6upUgKemaSojaObMmRgMBurq6lRaswxVlI6zAQEB1NbWYjAY6O3tVRwfaak/NDSE2+3G5XIRGhpKf3+/QiZkMZayX5n71N3djb+/vyo+Q0NDihPj7e1NU1MTQUFBFBUVMTQ0pOT4PT09tLa2csMNN6icqZSUFGpra5X/SUxMDGlpaRw9epSSkhJlwJeenk50dDQgxlm33HILDz30ELNnz2bt2rXceuuthISEqHR56ZQs862kGku68/5YdRMSEkJgYKAi0YaHh+Pt7a2clQMDA//BY2V4eJj29nZ6e3uVz480LpQGhVKC7XK5VANhMplU2OvFixdVwrmPjw+apjE4OEhQUBA9PT2kp6eTlpbGtWvXiI6OVmqwoqIidYyBgYG0trYyefJkFYOQnJxMeno6nZ2deHl5ERERoaTePj4+lJaWYjAYOH36NCEhIfT39xMbG0tYWBgmk0n9X/JqpFy7u7ub/fv3MzQ0pDKsLl26RFxcHC6Xi7i4OLKysoiKimJgYIAJEyZQWFhIVFQUp0+fZvPmzWqkGRMTw+TJk2ltbWXWrFmUlpaq/KqIiAi8vb1pa2tTa3vlyhXuvvtuhW5JhC8+Pp7g4GBlL2C327FYLMTExChCe3t7u0J0ZJMtM7ok4RzG0R3ZCEuPnfb2dgoLCzl58iQtLS3q93JkZESd7/7+ftWoms1mRWSWvLmf0vYSov5HIYW/+/kI8P4NsKBe3PFniW/W3AJ3rzTw4QEN7NtgkRfsOg/fwjBrcJePMh8n1CXrBIkn+egBYI2DYUV+NbPiEIhyPkt8yboZWCqqdxeiyt+OEGLxDtAP663CCRgz/F78NKcAh1XkNS4F6KcVC3s4LKpOPsBE8oGjmhOTXx6PmQziEdx2HLiL23gFUYXmMacXUnZDKqth9VRyKYP6UuBDtOeK0L7cRSvwqRmW+sMmPuFmXufR7RrRHOYu2riPPAxfa8zjNC+t1whkF/BzSP4AXsmAmUvoWCUak37Es/pdiN31RpQzt77kz+or9pdd8HsH/OUWgRykIqJW70I0qF0IVtQx/RweXQf31cGrmkO8QRQqDJXHQCVQZuqngWu0aA6hpuP/EYX5xQ3Aw+NTFDbC2jrgCc5pm2GJg9108xJr4CF4hBO8wwIuAFks0oNF47mbeoHQEcDtQCCH+RZ4lA38HrgfMJKNt38StWyjtwNqFxgIBfpYRgIzATDyiX4AvxPYxuhCqITGFZDPSrQvHZjSLOxgCb8E7ucecrmTbwY1PYfsY8r5E9FMZQwvXmUr2u61oK/1mDf8DPjhQ9HsFCAeAgKQLkAgg2eHeR0f7sEwfRU3Y+VNDhNAHl/liibpMUR/8SULdGRnijhrtjLhcLhmG/dvMLCUcSKxFAxE4sLIAONtltRquYGvyGIt/TzD6FUXD3aAdwf41IF3ufhQT4I4FkuNvlxS6S/zKeJEltc/2/5lw5OQkMCvfvUr/uM//kMprqSFfl9fnyK4OhwOpYzavn074eHhVFVVYbPZKC8vp6+vjxUrVtDf36+KSHx8vGpeNE3D19dXSZ0rKysJDg7G39+f2tpaxVuRpn9eXl4MDg4SGRmp+CdyFCGdfGXyto+PD3a7XfEyQBw5ui4AACAASURBVBBHu7u7iY+Pp6+vj9DQUNrb25k7d64Kv7x06RJZWVn4+/urMFCTycSRI0doaGhQad8SSZo2bRoWi4Vjx44phMblchEUFKTez+FwUFVVRWdnJ52dneq4JQLT3t6untSloZ0c3UjuhlRvSfSmvb1djfLCwsJUiry/v79Cl34sS+/u7qapqYna2lrlzCzJs2azGbvdrnxc/Pz8MBgMNDU10dPTQ0ZGBiEhISrmYHR0lLa2NkW2rq6uJjg4WDW0UunkdDoJDg5WIzgpBU9MTOTEiRP09/eTkJBASUkJHR0dZGRkKA5YXl6eGs1NmjSJa9euqWZNIntyRCjdkWXsRaIeEGuxWIiNjVVoTkJCAm63m5SUFJxOJyEhIZhMJgIDAzlz5oxCXmSu19SpU/Hz8yM9PV1dL5J/4/F4iIoS0oELFy5gMBhUjtjx48dpb2/n4sWLlJeXKx5QSEiISrGPjIzEy8uLoaEhLl68yO7duzlw4ABnz55VKfLSrVoStKW0XD5sDA4O0tDQwJkzZzh//jwOh0Pl0kkkT27S2+fHZG8Z5PuLX/yCtWvX/qtbwv91m0QL4iM0tuADdBIPeDwjUJWE91PAB1VwDRbvFzXSZ4kBcAu1VgqwciqL2crBLDhCHYKeCWz+gPt2ApvtoFgShey2gxdvAKmwAkRJmQv/Bje8gKhAlxGuvjOzoecFAY7QIDxhMqFjP6KIF8IwNh2JqmCMCbwForB85QQiETmU+xh9Fd6gCRa8wJvMZSPBOhF2D0+yl+AgoAK0b7ah1RRRPKiJSApe45d/AMNtefwFuNcsdlH78B6xo6sO0VKmARthy3nRiD0zAx6GvpkacBfUlUEcJJyBX28XCMw14LZsYSo3DVEWryH6sUJEAyMngKH6a67gZgUDvEEHOdSwjF5uRgjN/xvdiyhTX2rccPpxOFgmSCv9kLYF8YGyhr4lf2CPHrnxM/4QgWhyyrzEKHHZcXigDp+twOZ1Ig5i1A7brESzFfy28g47ATd9rKQW3eF4y2p2cJr3KQNSeB/4EtFkwyu8xAyuOjTGeIF91HMHYAizMRtYygzgFB8CEM8YdzKKD/AbgcKZ6jGuDOCXADzMV7fBs7jAsZ9inudDFlC8VwO/7RifCkC0jw9xFzD6jYtjwGsr4G8bdUZMkIU4wHD/d6rJmTAKtw0IqvhdrMSLZirooYLH9cyuOPbpgaBagRh37UH06R2sFOedN4BXwLkKTmTz5gcGKniA+8RviK71Ej2pMG6UCI98BHHhwwnuZxtDo2VcvAqWAn0HCxmHBHVAzrsDjF38Y8KoW3+tnknx1E380+1fpgWmpqYqnxWJPhQVFSlibHd3N5MmTcJms+F0Ojly5IgqxgaDQaWo5+TkYDKZuHz5Mr29vQQFBTE2NkZraystLS1ERkYqLo/ZbCY3N1dFAWiaplLUBwYGiIyMVLEDUgE1NDSk+DASxZBKJ+m+LHksktMj3XDb2tqIiIjAy8uL3t5enE4nERERNDc3093dTWhoKIcPH2by5MkEBgZiNpuVYV1KSgpnz54lJiaG6Ohozp49y7333quKeE9PD2NjYyxatAin00lFRQUpKSnKBFFmkclxk0RmZK6VfHoHlIlcZ2cnFotFPZnHxMSoAiaVcRL50TSNiIgIent7VcBodHQ0Q0ND6nVxcXFKlSULsiTuhoWF4e3tTXh4OFarlc7OTgoKCpg5cyYREREqRkEq3CR5W7ofT5kyRTldJyYmKm7KlClT0DSNG2+8kYaGBkpKSpgwYYIa/dx66600NDSQnZ1Nf38/ycnJnD17FrPZrEz55JgrMTERg8FASUkJkyZN4tKlS9TX1+Pl5cXEiRMpLS2lpqaGnJwcrFYrAwMDZGdnqwZUmmF+/vnn5Ofnk56eTklJiWoupft3e3s7fX19mEwmNWoNCwsjPT2dgYEBrl27RkREhEqOP3bsGHV1dUycOJGJEycqU0jplyPHwCCaEKmekmorSeqXaJ98na+vryIZ9/X1qUiWoaEhxQOTPjvydfI9ZfMjXaaNRiPz588nOTlZRUrImJWfyhbPB0Ah7iYDZtYBN1PAHGAjZNyFx/Mb4FaY9jTfvCGK8W5g6Str4KktkOcALCKx6oQGc+4kjF10xG0QTUjp41D1OnADikr5HmQwTHm9XXez9cDj/vCEAGq+34joKKiFUDtYp4J1kfiirkbi3ePw2I3iJr4sUx/TVAIPcpJaAQzxKdy5jo5VQP1q8e1FdjiYyqO7NFj5NFAI9Yf4tyQDm1jFxxu3Uwi8QxLHMLAY0J7bDNNgx22d7HCDwW1H+9LBW/dDA1vpZysTszegFW/lrXVb2YhAJzayl5dOZ8OEUkEgiYKrh+DbhfDeMmjYC0vLxKrEIyTjElDpZFyL9jMG8MIBBPAt0URhJpsRjIRi5BIhQD/57EMgQLyFaLo+kfkOeyA3m/weOJcHK9bCbm1ENDQfIz517ToM29eh9dXznCaI4Qo2evBGKBT7dQ5gPqJrmYY+SnxZfAbPAiUME8BLzIN1sUABD2HlL6zlt7xOP4/zRAf8PiydXOopPgWsLGQpn+B234PZ2UarPQD4Nx5jPfNIQh+yMkI/OHey2xZMAslcxcZJioDXWDwAf/GHc3YDTwFH1mvwdg84VzFmK+R+1rKJtfwSMCy2ob3kZOx3sCVILNdogQvXdPifL+eCGcZmQlUQ/NUfiqnjSZL5FAEW5QDCsbmIW4theDJcng4TOSgWvueFcQOejYzHmq/ZxUb9nE5k3CoHRH8PAuFpZwijbmtwO7CqF4znGXdLlqBPPKInkl+TknQzonM26zucAqcegxuog/ok6BEWQv+n7V8iPAUFBXh7e3P99ddjNBqVyqqurk4lfff393P58mUuXLhAamoqM2bMUO64VqtVScaLi4sVoVj6zciAUS8vLzWC8vPzIyoqSqE5qamptLW1qQIhXYsDAgKwWCxUVVWp95VP69IkUPJ5AIKDg5Wku7q6mra2NpUYLg0PDQaD8n+x2WxERkbS399PZGQkx48fJygoiJ///OdMmDCBuro6hoeHSUpKorKykq6uLubOncumTZu4cuUKFouFpUuXcscddyhzvPT0dFpaWjh37hxdXV0YjUalkpKjorGxMcWxkYiPpmnKSFGiGZKbMjIyQn9/P2NjY4SHhyuCtgyilByQ0dFRpf6KiIggNjYWo9GoojCqqqoU2iPl73IcNDIyQmur8PlMSEjgypUrKvxSqpRk8vpnn33GhQsXFJcmNDSUnp4eurq6qKqq4uTJk4yNjVFSUqK8h2JjY5kwYQK33347aWlpCsHo7u7GbDZTX1/P8uXLuXbtmspmi4uLY2RkhAsXLqiYk8uXLyvzw+joaNrb27FYLCrCore3l2nTprFv3z6ioqKIjIwkLS0Nf39/fvnLX6rg1ejoaObMmYPL5aK8vFyd29mzZ2M2m7l69aqSzZ89e1bZA0gUsKuri46ODnJycoiKiqKqqorTp0/T0NCAy+VShHd/f39lJRAWFkZnZyd9fX2KVCwbXqmsM5lMamzW2NhIZWUlly5dUjEX8lzLINYfIzlSyTU2NkZOTg5r1qzhkUceITMzU3G55Cjzp7Qd4wEgAPN2DXGXzGVo9ARGtgDxMPk0bH4aPtgGC3ZRTpLImzqFSNjmSeANfstBZs8xAI18COQmGfSx1kcQAEZWohxSUqCcJkga0BuVBwXI8Joo9HyKIB0TChZ0R9qHgABYUk/+VhBZDegEzDfwqQLRLi2FB7p1KF8MVpiGKN7xiDnF9lV6bsUNgsCc9Dg55bCP7dxHEu+QRC71HAOGWcLBP4il0X5bz/tm0B51MLJAvHs8p5nIMuAUhtzTTNH3opa9vESbOLZiwD7ATQvBsBya9cfo+DzITxp/ANd9ppmn/5GFsQV/viWNISK5mRZy+AYjLmQDOcRUAvQV+juQViWO1+S3Cja/DptfgN1w7nNxHF94AXd6CWjjDWDyjfAOaJ8D25OgZ4bYmXeL4FIVbHgaTuqxERumwqXHYWUwZCcL+KP+af7CYRhcCLSymG2wdRVhOAAz8+kR0Vo9G1hKNt5hPlBWJxwOVr4MvMSr3MN8MwTaDYyxHy+e0GMlcshlm36smRhtASTQw1Wy6cdJAxMA2O0P+3tFT3vkgIb2mEGEaL4G1L9NIxCHiSMsAJ7AsPFPmI5qTANq3HBquhgD/cdtCGFekODzXAPcbmEG+DBwF6v5IzA0WkQhkJgLvqbn+U/gbhYBH4N1Gyw4BPNFMGzgZsQ68T7zECPJTP1cxyHOv5txLvEvGaUY+KIc7v0SjF8xHpEuDXUkrScSZWqtuDolQCWMxYHh7ucx+GvcUKWBM0k8sdTyT7d/2fBMnTqVpqYmXC4XhYWFNDY28vXXX7Nw4UIsFguXL1/Gy8uLq1evKnPB2NhYgoKCaGlpoaOjQ8U/yGJbV1enEJLU1FR185YqsJ6eHoVgSAKny+VSjYlEbiTRMiQkBIPBQEhIiJLmStQmIiJCIQA2m03xc2JiYujt7WVgYIDo6Gg6Ozvp7e3F4XAQGBhIY2MjdrtdqaIMBgPp6emUl5djt9sZGBhg0aJFKubi1ltvxdfXl4sXLzJ9+nQVreFyuRgdHaW1tVU93SckJJCbm0tzczODg4NkZGQo35W2tjZ6e3sV0dRqFW2qjF6QEmM5rgsMDFQSb2nCJ/1hZABmf38//f39atTncrnUGtntdiZNmqS8eyRXqrGxEafTydDQkFLgSVdfyfswGAz09/djsViUK3BMTAyzZ88mOTkZgMuXL2M2m8nPz6e1tZWAgABl/Jeamqpk+ikpKdhsNi5fvszUqVMxGo309PTQ1tamIkcCAgKoqKhQiN6+fftoamrC4XDQ39+vFIDx8fFUVVWpdZowYQJ33HGHMs784YcfCA0NpaioiNLSUkVgb25uVs18ZmamSjefN28eEyZMoKGhgcOHD+Pv76/SyCWv69KlS7S3t9Pa2kpsbCwxMTHMmjWLkJAQnE4nCQkJZGZmKmKyyWSir69PxYjU1tayf/9+xbPy8/NTKjsQqqvBwUG6urqoq6ujrKxMZYbJEeiPM7AkeVn+nhiNRqZMmcKdd97J448/Tn5+vorPkOpHyRP6qW3z+A6tZjOsrmcxuwjDQZ0JpuECroli/UfEfwZXorXUE8gWyIT5NgPefAqv5PERizjJHOAw94MwEXwWcnGCPYIx8uDFGeDIgIwBDIF2QI+PXpshHmVrdSs1GROEGV4Cj3IsjAf2cG4hZFEPlxyi8dqSx/AyEN4vkeK9noTFOMafftc4RGHI2C6q4ut3iqypZYcAb57PEsUni3rYXscTwEucBnZwDjD8+nUI0DMxfwcT/aH5HTimc0w8A2fQimfyPrDjsEYqB8VO8JrYdcwc1Y6j7QfPD0AlZBXBR/XiPfchxP+1iNo4C4GJpXCVAGAebnzpQrSEAmMYI4R+8nFg5FXxSeTn6bXRDKNvIkaSXYyzmY9A+AiiK9ONl0w1+t/36DtxTd+h2DyYkEGY4WW4A65eAu45D1teh6pu5lMPX02G+fBbSsFvPRApgIb7EL46/y93bxoeVZluf/+qKqlKKqlU5oGEFEmAEEJCQgiKIIhCQ2vDwUbBARWx8Ug3DW03Du1AK44tHAfaqR0QlXagpZsjDYJMAjITQghTSCBjkXmopFJJash+Pzz7eRLPv48fzrfXui4uCKnatfezd9W99rrXvZZ+Kj+jW8efbvwv9UJOmT6NJIDsYyzmIA/pA2kfkEkffy+GRWwRIJhl3Maz9LMNJxa+p5RILKQSB2SwFXggAu7bqPHxzQb6oxCAbM06SGvmACZ8TMPCbip4BJxPsGyugUnvQfD3YtcMI+L4r9Hw/I1iCe5DnBuzuYBaBKbQzq1nOBBimsse5vMecJpnlSZcNBWnARPgdxC4CboK4PqTBr4f5I69WT/XchR+KCIr/mo9fLRDeAVxQT8Xsj3lHfQnGqFhli2rrfrG2gWDZUjRMFVrUPQMgAA6uoYHMdD6bx8/+g1XVFREVlaWSnt2uVzcf//92O12SktLGT58uNKIVFVVMXXqVOV8LFsa0sNF+uKMHz+eoKAgrFYrJ06cUCxGS0sLIDKRZG6W3W5X3jNhYWHqTlR60MhWUCAQIDIykt7eXkJDQ8nIyKCpqUnpfSQIkMZqHo+HCRMmEAgEFGsgAYTRaGTs2LHK10dmdt15551kZ2dz6NAhIiMjaWlpUdEXTqdTpZ5nZGRw5coVRowYoRyEFy5cqCaf5PFef/31DB8+nMbGRg4cOMCWLVtob2/H7XYrMavU94AYQ5dtPr/fj9/vV1ohyeq4XC68Xi+9vb309PSo9qJkWuTYfXBwsGK3XC6XGvP3+XxUVVUphgSExiMxMRFN0wgODmbkyJHKlyY+Pl4xDyEhIRw4cIDOzk6ioqIUaKuoqGDIkCGMGzcOgBtuuAGr1UpXVxf19fWKxXE6nSpVHVB+Tz09PRiNRq5evQoIwfaxY8dUUGdLSwsNDQ3YbDZGjBihYiNk3pT0/Tlz5gznz5+nra1NgXjZUvruu+84fvw4V65c4ZprrlFAasyYMVy5ckX5Nt11113k5+czfvx4NT2maRq5ubmkpaURHR1Nf38/9fX1HD58mEAgoEJn5Ri/3W7HarUqPdzZs2dVEGhPT4/SaAUFBSlA0t7ejtPp5PLlyzQ3NyvNl/TRkQGz8rMgrw2z2cwtt9zC/fffz4QJEwgNDVWMnQQ3UrAsmZ2fGuhZxg28PgIspLODHPIQN4jHSjXgc7gGCAcblRB6K4akiZgNGqxJ4SPAF/DDH5dyP2Gs4gDwHa1MZJnhZiZESgeRLOA++NMt3JYCbLKi2RHRBxUMmAY36oRPIpCzXbxxphPR7JFNgNEs2wXnSEMxOPsQX/xrrSJKAuDDjexgsdiWDyBB4A/2iQLR86UoErrNXwaQx0LO8RDGheHcuV5jGdfxGpE89R5o8x7hT38WWMrg+BOXfgP/sUxMys9hC8GHNQz50/k7Jpg+A5gE4z/kLkMdXNzFNQRznhtgylR4HvLLhNZDRiDMRvycx0D8gBvoZShRnMbMBqCEE2RzgiRqSaKUCEoQQz9LEKX2/SJB2jzsFGvq+wXwMSQ9ApZbgMehXitVoCb4P+GJXrA9IZabO8AyCvjwEajz8FyZ2N6sXfqF8emt4qRm7hLtLX4BV67DFJoDW94AvGxgDYS6WMQBVhEvdEVFVnhhIzBPHGBlJv3vurEQr2u8CoFfkgVANGOBknwBcQsBMIsx9Oap+HmdG7Dg8faJnQ48wWfk8FE9VCw0MA8YFSGuu0WsUNf679ktwhie1JiTbOAvn8F3DwJjBdiAsRjOd/MvIONrcVl9A/yeIt5kMfcxn/uzBQjSPtvCW2xiJg+Rx6dM4wV24IPSJ6A0DW61C/D4EXDyOl29Jo6llgEXbbN+3v5eDr/cgdi4REES3JxmgOGRKmf0i+Qf4vm//T0YRmkYkjUoahLbOIRie1Qw12UGTHr+zeNHx9K/+OILrampif7+fsrKyhg2bJjKEJIpzmVlZcrXZuTIkQQCAeUofNNNN1FbW8vFixdJTU1F0zTy8/Ox2Wy0trayY8cO+vv7ycvLo6OjgylTplBdXY3f76enp4eUlBTq6uqUqNLj8dDX18eZM2dISUmht7dXTUzl5+crTxXpgzNmzBjcbjfl5eWMGDFCMQ7S5C8QCBASEkJ9fb3S59jtdjWZ1traqozxANxut2JZ6uvr2bdvHyaTidzcXBV6Kr1YLl++THZ2tvJikQ7ENptNFbuysjJlOmixWIiKilIFZ/AosdTvyL/9fr+KFQCUF4vBYFBFXGqfZMtLil5dLhcWi4WwsDDluyJBUlhYmCqAwcHB9PT0qHwxufbSCykqKkpNa8lWo8lk4vTp0/j9frKystizZ48SP0dGRnLq1CnGjRtHR0cHHo+HixcvMmbMGHJzczl58qTSrRw/fpxp06aRlJSkfIOCgoI4cuQIkZGRdHd3M2TIEI4dO6a2P3fuXCU+l9NLkZGR1NXV0dTURE1NDbfffjuaplFdXU1wcLDK15Lj7cnJyWzdupX29na6u7uZMGECPp9PacRCQkLU9dnQ0EBISAjDhg0jLS0NQKWs+/1+2tvbFUiXjuMgWktyIjEhIYHe3l4uX77M8ePHFcvS1tambgJkkKzJZPrBVJYEOYMfUrOWm5tLYWEhFosFs9msNFpy+5L5kZ4+g20LTCYTy5Yt+8mMahl60K4JNXAH8DB2xFf/r4BVcM+L3LgR9morgH18TCm/R8+1IpxgavDl+uHMi+TzJG6gnO+gbCrZo+BcGliuyHH1JUAFIwy7KP8QnWWphPQ0EXJ0AkFteIFv/YiW1csIt5qxzOJddqzVYDbEjIJW7RFgGh8bbuZBoO8K3JYOX2keWGEVGhP7flg6VQCqlR64xwozwXIP9J3RFyDHD1uCBNOzcQYsfBfYCRv/SdJCA1fN0N8CzghIZT7am5ugBAzvL0Z7ej2G5z6EnsXwIPDpE8ASeCAN23ro0iOuWAWWddA3H27cJCwPv0UQTtLzaIK+O+cRdWkskEk/QfQSRA/txBBFNb0MJUSZF4nK2M4I3kLUNlkvoxkQw+rezCpbUuqEZBtlEkJuZQa6vkTQD/OA38Nm5wDr9JRYGT7Tjgin55x3CWYZPt7kLpby2VoNVs6A3btEkV65grdYx284Sb6hgGItUo+LqGMrKcyWI+fXbYPDpUA42aTr5FMY/YyigiL2IQDhg8DXzRrErSWYx3mbAEvWa7D4GbT6Z/HFQIg5jAS6eQ+4uRNMEdvYzC3M4ySQxe+FmROzEWD1Hwgs8dEO+GQW3IedfFycKobn8+Fp4jDioZ939bN1B1CIjWC8QB92fTW/1rO1PLDUKhZfRzXvzzcQrp+fmYPOczhwb6u+WYl+5DRVLQPAR5qKJzAgUNZn5g3Xixw4xfyVCsNeFRgqWSIJklLF9rT5/NvvsB8VLTc2NlJVVaWKq4x4kHf2UjgsAyalKR1AYWEhV65cobq6mtTUVEpLS8nLy1ORBmazmTFjxqgplI6ODuUnEwgE6OnpISgoCL/fT2ZmJq2trdhsth/c4V69ehW/3680MBI4SP2HZHekSWFLSwu5ubn09fVhsVhoaWnBYDAwZMgQxSy0tLQQExOjvFzKy8tVjtelS5cYPnw4R48epaOjg0mTJlFcXExFRQVut5ukpCS6urpoa2sjPz8fs9nM1atX+frrr7nhhhsAaGtr49SpUwwZMkQVSqldkhqNlpYWlb8lwYz05QFUPIPU8MipKqn1kOJUyfBIRsjj8WA0GgkEArS2tpKWlvaD8yHfTwIZOeUl2Z2QkJAfTEJJL5iwsDDl3JycnKxG0qdNm8bp06f5/vvvGTlyJJGRkRw6dEiNazscDmUsKY0HExISmDx5stoX2YI7cuSIaqPFxsaSmJhIeno63d3dNDQ0UFJSQm9vL6NGjcLv9+NwOKisrGTIkCE4HA6mTp2K0+lUURNJSUnU1tbS09OjDA41TSMjI0O1uXw+H9nZ2SqXTYJWt9vN1KlTCQsLo7a2Fk3TqK2tVcnlgUCA+Ph4lUDf3t5OfHy8EnRHRkaSlpamwE1ycjL33nsvPp+Ps2fPUlpaSkNDA21tbepa93q9yj1b6nPk7+T1OX78eEaMGKG0OoNH1iVwludMPuT2Bvs1/aQeoddxL+KL/xpc1LCUeu4FHoNC2LsT4Hd8zjpmA/ct0LB9aaCLQnx8BE/BLJ5kB4vZynpmBwSDca4JTKniu7mVgwiL5dWUZyKq8iFgZpr4Mk/eBcnT4OMgRmwDMVGbJe78VzYAWYKtuQxk7ieDqbSWroGcI2rqlrRmsogDGqEtDeyl4JoqgM/dwMp/wadCCtx3OU1UnxIgOkh4//AFLGwEVsFLTWhJBj4ADN65aOYtDD0H7hGb+I9l0isxC8Nzf4TAYjaHGmj4FH5LGP1Mgw/D6fqwAtgKRS/CbOjbBx9vEmXJVgC0wazKAXHy6wh4N5F+CvXGggsjYMVOCFHUA15COIM0W/EymkbMIn4C+MqOcpzr+i+oXgVPb4JVeHgTq9D5PCGO+9Ft4tw0AL+iniySmJwMSQtEbayeJnZs83qBfcpnwK/2wet+KDFM5FwO2EofojfoIfCViXq6MoVZONkx/VaYPhyoEG2eJwsoTgaYR7lOXbwFxHAdrXTAX8FCLuVABibCCNBPLvA7LrCAXz0N/3gOvmYNc+IMfM1DrCLAkjKNfYsNTCvT+I/MZ/l6qQbvbKKeraI1NvpTqLuOcCCG8bQynb8gbqymEWAaE7mNI3zFfDbMagNmo5WvAC/8IR9eJQ24g34O6dlxXqAd1gfRNVOD5HUMIIlV8MdCOLBQ4J9ViNG5BFiyQhOL/YKfl7mfVWzk2Vb9NLbpL/fqn4maQZ/NcP1nL+jKdAFYVoPB8an+iywGvHr0f9bqJ7aGH2p/5IxPKv/r40cZnt/+9rea2+1WpnbTp09XBUNS5yaTiU2bNqkC39nZSUdHByNHjqSmpkaJTltbW3nwwQeJi4tj586djBs3js7OTk6ePInFYiEnJ4fQ0FDsdjv19fVYrVY0TVMiVJkH5PF4qK6uVtqJmJgYent7ueaaa+jr6yMlJYW+vj7q6urIyspSni4hISGcP3+elJQUlRBeXl5OZGSkEuRKnYoMwpTRC83NzeTk5FBdXa1Gre12uwozjYmJUd4mkZGRnD9/ntGjR9Pf3698WK699lpAACqpYzl69CiaphEdHc3QoUNJTU1V5nU1NTWkpqaqIiS1GHa7HaPRqEIhpbZJTvbIfCxZJP1+v8pckq09qdlobm5W+iar1YrRaKS1tZXQ0FDFJsk4io6ODpU/JQtucHCwCnnt6urC5/MplkkCyCtXrihNyenTp3E4HPT395OaaP6EtAAAIABJREFUmkp1dTVRUVGq/Zieno7H4yE9PZ2GhgYqKiqIjo6msrISo9FIeXk5I0eOxGg0kpWVxUcffcSdd97Jli1bAJg+fTp9fX0MGzZMgVqz2UxTU5MS2MvW4OHDh5k8eTJ9fX0UFRWRn59PTU0NVVVVWCwWent7yczMVJ5P8fHxdHR0UFZWRm5uLu3t7cTExCgGaujQoSow1Gw209bWRkNDA5mZmcTExChgbrPZFHiULI00SCwuLqaqqor6+nqVzeb3++no6MDn8/1AuCzbV9nZ2eTl5SnTwO7ubqXfkSPnUogeHBysBM3yepIj6/39/fT19aFpGo8++uhPhuG5FoP2a+A+ZFvhVUHJP4+4S6wAfg1vrTTwD2CPSwN7Ctfj5OB2DW4uRVACJSxiCxt6NIIjdLv8ewrg0wVABkG8iv/dXiiBG9+FvVop5OYI2iADQSFkISiIF1YAp2H7frj5FgQHMRwC88FUBvGZ4gu8YxenDTPIm4suQgbqboUV/4RCSLoH6rVN0DNf15dshQNXRDwF0bApU6ANu4hrEEXjY+AQ2qsHGPZ7qGYl2azlHNPZym5+cRC+u14QGA9TwFt61MBoCjByEc3mRutaCoTzHGsJR+C090E4Fy9dDjPhtlvhqyfguRdFnbsP0aALQ2C0adTjJokg+glRMzzgxcFOzKrjIbUlwcBMvPwBMx8DXXPBsQWqk8HmFJxdNMI8+1wycCc41oo22jz9DD4sY7QOAWZY5hSr8ivq+QdJBCOGumYD930qztes8bBDyxXn6JF3YM09wFPMYhQ7Apoouq8A78SzjGbe3KhBA4x4BMr9gGk92TzAJUz4COd6XITpx7SBNWjVjzDGAWer4Q8OsWvHmA/MZhb38E01GBxvwIHlMMUDjITddbw23cDDFMDakwQeNLA9AmZjZzMuzgNP80eMrKOflcAn2KikiybgNf7MSwA8RhoOKrmPAVzy5lpND7xdz208IIwXmQhFh0U/8nngNTD1wa29Yn/rJ4rleW2NgeH6R2o2kHFO32gtYvytloHguhP6xVCrfywnwfQHYQ9vIFDMcAS6GaqvlhtcOWLjsh8qW2Jym15UT02b8u8Znh8FPAsWLNCkMPf222/HarXS1NREenq6mnIqLy/nm2++Ye7cuaq1IdtELS0tJCUlcf78eQAWLVrE/v37iY+PVyZq3d3dlJaWqvZXYWGhGq92u904nU4CgQAOh4OgoCDa29tpbGxUURQjRoygtbWVrKwszGazCgqtqakhLy9PjbDLKbOMjAwVPlpZWalM4+Lj46mqqiI7O1sxGJGRkTQ0NJCcnEx1dTUhISEqOFPmiblcLoxGIzk5OVy9epUDBw4oNmPSpEmKbYqKimLPnj1MnTqV9vZ2KisruXLlCn6/n7y8PGJjYzl58iRGo5Ho6Giys7MVUyHPkcFgwOfzqfaGHE2XHjRySkcaQUpxsmzv2Gw2BYCkPkRqR4KDg5WGSbJKcqw5LCxM+SxJX6Curi7l09Pd3a1sAyQLZTKZcLvdyqtHjjtbrVZlqOhwODh06BCjR49WeperV68yZswYTp06pY4hJCSEU6dOUVpaytSpUykpKeG6667DbrfT29vLvn37FGjs6+sjPDwcg8GAw+FQ030ysTwxMZGsrCyam5s5evSoMpMMDw+nq6uL6upqYmNjldFjeHg4ly5dUgLxpqYmoqOjaWpqoq6uTjFe7e3tJCQkqPWXAa92u11NrEkmFFCMj2wxFhcX09DQQHFxsbIzcLvd9PT0YLFYVDsRICQkhNGjR5ORkaGsBKRgXzI+cqR9cL4WoNgdOUQggXFcXJwSRy9fvvwnA3g+waB9APwXwql3dboGV26F0n9CzgJEOZyJm0jC2QbA+9zCJ8DBSg3SZJ7VOkawgpkGjTe1WxEgZRpsL4Cbd5HEz6hfq8HKJ1hmeJE3tUoYlQYXK4Fw2BgnqoMX+NCFgBSpCGboKGCGJ4PE79d44BdW+Dsctwppzt6JiC/2i+sgfTn5laIs1GubEA2E+xA8yljgDqEpqQXTnRD4M+SvgOJ/AnOLsDGezh1QO0usUXInGGPhWq94+1OTofZ7QRz9DUjdosEhqFkjWKEXseDf2MuchQaFGc1AtR4m2kUa9FwRUzzFsKBXYL6ZCKVSGF7M1OPGQQge+gnCTCu9JNCDkQrEUqXqq/Q2A1jxG8RxJ/JDwuCQOBssAaJoxU8oQbjYR9IP5CKjEdoVGVMp/Qn3IUTUj+v/VwHsKBA7HfwK+HzjWUURbwGt/AmBYM/BOjssnwq8CbtzuGsGfKa5WGaw86a2lMd5l5dZiOzb+DylDLeKKf7hzRp3xQk34oeRIHMlQpx+GVgl2qrb/eJysy8giP/Gv7sXpnvAaWVRsoHPgT5WImDfTow8QT/L9X0UHsq9gXWEmB5SK7WIdRTqzxgLbKCA1yjSj2olAo10E8Rf8Jf2Dpg7eoHlQuJBWRpkbkI0Ahv4mO0U6k8ZWw19KWD5EAFqMhhoXcmI9WjoexdCTNP1syh1bI2DzlAhKmvLmTZg2dyuXwhuBqLtpBfPUNAK/g8tLakr6enpIS0tjTNnzhAWFobb7cZkMrF7926GDBmijOiCg4OVKNflcim34mF6srj0CQGorq5myJAhKhdJjpYHAgElSpbBiFarlatXrzJq1CjlilxXV6eCFrOysrBYLIrRkMGc8o5aZi3J7YWHh6tR3qioKKqqqlSrQY4H22w23G438fHxqogCpKenk5eXx/79+9m+fTvDhw9nypQpHDlyhKSkJB544AEVW7B582YuXLjAvHnz6O7uJi8vj7a2No4cOYLD4WDcuHGEh4cTGhpKWVkZqampZGdnq4kr6YJsMpmU+DsoKEh56kjPFSlSdrlcysU3KChIJZHL0EnpMC1bVv8zhBJQRVIyNW1tbWofZOCl3+8nMTFR5TvJqATpKSR1PlLMHBQURGJionLPbm9vV2PzeXl5GI1GIiIilIuyBMoSWISHh7N//37FhsiQz5aWFkpLS9WYt5z+am9vV9N4dXV11NfXk5GRgaZpJCYmcunSJS5cuKCiQcLCwtiyZQs9PT04HA5lWLl3714qKiqUUWF2drZy8rZarfh8PjVmbrVaaWhoICcnB5fLpYTZUiwvQVhmZqbyTLp69Soul0sZFEr2LSoqiq6uLuLj45VIvbe3l/T0dDU6Lye9pEZHMjVBQUFKyC6Bj2S6wsPDfyD2lwadkhGSzNZP6fEJ4qu7cC9M+KUGHTOAryBnLTi/5PfJBl7VzeTQS+0SvgTaIO0I9EyE0DLgC8opoFxzArXw7kp46EXIKAD+wH3Ay58AK2cKFcUjaVjKoK85DeLWQupKWLgJnp0PeIX25p10pE0dm4JEBsN7wForpj0QcAuJwhJg72zgj83iuZNgbCUULwac8wXOWfMERj6kn7XC82cscAECc4BoKJ6I3p1w08UZPpmVy73FcDkfjNPB4I1Dm9fM85vBMFWDA7BoigEzELjRgPEhMK8x4aOe3kA8IQtTOIScVPoNsJnr5xo4yBooWknMeOHm24Bw5n1ZrCj7gGmY6cah36RbKQEqSMINPBcH5EH2LrgYAut7B177OkLnIjx9PLixKrtHGab9PTAa4fflQLTQtmDU5eAQRycziSBBZ5ga9etkNsfZyQTeoRMPEZwAZhZBSZE4hh18xGrehk3vwHwPRtbSz4OQ+iVs2i9q8iL4zA4xBjt/DQJK3+Hl8Hcw5IJ2GMjJ5WkrVBNHRn0zJC1gH1DXCf1B8JoVFrGWDTyLQAaz8UW+AR3PAN3g/BJ/8kaY/ggO1jI8GTbQpK/ATcDnjMBJORNx8BLVLERr3Uh3zDq2mUD4IYwGsthAExu4iZso1TtACTyPHB2P0lflTkJZS1fOE8BseMgNu2fAijRi1kFnEPi+mU/+9AUc88Jp84COqsQB2dJQOUt/62j9De6F+68XIGvAKtnMAHxN0P9ORY1wNccN+BvoYIlJ+qHLk9jAQBfsf3n86EhGQkICdrudlStX0tnZCaAYESk8dbvdzJkzh6tXr3L06FHi4+O5dOkSISEhGI1GNW4eFRWlzOOKioqIjY1VAlkJghwOhyqI0iROjmdLQa0slHa7ndTUVEJCQpSgVBZomVTu8XgIBAKEhobS3t6uim9fX5+ahrJarSqqoKGh4QfCUIfDQWxsrAIBshjExcWRn59Pfn4+DoeDuro6pk6disVi4fjx42zcuJHq6mrS09O5//77VbyFy+Viy5YtNDY20tDQgMfjoaurS00/jR8/Ho/Hg9PpVHEcwcHBanJNAhE5Ji5bgFLHI9tT8fHxxMbG4nK5qKurU6yODOd0u92qbSUn4uQ6+f1+NR0lQUx0dLRqmUmRsjQZlCAoNTVV2QnIqTq73Y7ZbMbhcBATE6PCQ6Wrs9lsVo7U0jhPjuJLUbm0CZDgtbGxkejoaN544w0uXrxIX1+fCg11Op3quMaMGYPX61X6Fo/HQ0REBGvWrOHbb7+lpaVFRUOcPHmSiooKQkJC1DVXVVXFhAkTCA8PJysrSwGZ2NhYPB4PxcXFBAIB1Q6UxyADdD0ej3IPlxNXkpWTXlMZGRkkJCRw++23M2fOHEaOHEl0dLTSRVksFpKSkkhMTKSgoEC5YPf09NDb2/uDz87/nLKS14kEMzKDraWlhba2Ntxut/q9XFubzfaTAzwJwDcbwHDjO9CxgmXshh478Dqnkw2sBhxs4j8Acadaq4OSLOB5oVXgJiCDfMNJxAz2HTgeMgCz9SmrBl4hDM5sh/VTeRtgzSbmga4xGA1TSqFnPrc9A7BZEEv8TmgneqzYFiBY/Eni6YGt4u0r0M3wakCMXe2DDbBhG/BhszBTeRl46UX6eQILSwl+HUGLZACp8PU9iLpx83jxepZxH3P5bb6oD7cfB624mcbN8FQxaLsMBPIMfPSVuKm3RsC/GsBrCKA9HI9lOWitTp4CRGH+HPgbB9dqULQS9kHrYhj+DkwugMcQjbQL+uFF0UoU9SThoQ1xLx+OuGmf3IzMTCW3F+57CJYsFkc+DdEhvAPYg5VoRN1rRMhaD+k/l+h/d2HlCEZ+iZdJfI2dfpqJIIEdwFbC+ZoM3iScr4DjzOQx9utgpxDBmT2FwKCbDTliL+cLQNmPE7jMiFsRqHr6RgwumOASLNTdfuB6eC4dtDWwL8fALEpJAB6nmT8mgfbVJkYDL0bABqs4/jtBiNLRL55osPAsbF8DyUuBzTzHWn4N7CEZOAG/SOM2KtFanbqkJZjq7RpUfoohxs4rCLA4AhezOMIslvI48SyilHv1dYMSZiJA4008iQAgbXS5NNj9org4i2aIC2IftHaAT8fqxSwk2yyiK1YhmKovEMfEJMALjVvh0Mcw7i0Ycr24YoI4i0As3eJzhxlxeyJRUgZK4CO1Pqni8yEBPbX6/6d5BNOzcj9bM/93gvpHW1p33XWXtmrVKvx+v4ojGDVqFJ2dnWzatEnpcBITEzl16hSLFy9WQKihoYHY2FiKi4u59dZbCQ0NZfPmzcTHx3P69GlmzJgBiJRvp9NJRkaGcjz2eDxKNFxcXExqaqrylpEp5/I1MhLAbDZz7tw5YmJi6O/vZ9iwYWoKa+/evSroMisri76+Pi5fvkxKSgo2m01NzXzzzTfceOONREdH097ervxpzp49q9iupqYmQHjjhIWF4fV6cblcnDp1ipiYGHbt2kVGRgZ+v5/k5GR8Ph/5+flKRNrV1UVYWBjDhg3D6XSq8e+ysrIf2PxLrYoEW9KAUD7Cw8MxGo10d3ertoZk1qS4VibJDy5+spUohciSSQsNDVVTW7I4S9ZAsmY+n0+59EpwID1jBu+fZOkkmJITX7I9KZPoJQPkcrlUKrw0MpSFurOzk927d3Ps2DHllwMokC2Py2QyMXToUMxmMxEREYwaNUr5N0k2UBoCOhwO5Q5+8OBBoqKiGDVqFM3NzbhcLkaNGkV4eDiHDx8GUG7MDQ0NXLlyhYiICCZPnozNZlPAtbW1lcLCQpxOpxqTj4qKUg7g3d3dSkMjjS47OzuxWCx4PB4uX75Ma2srra2tKkpCtgkB9brBU1by3Mk2MqD0OtLD53+yd/8zK0u+zuv10tzcjMVi4ZlnnvnJtLQuYNBG0022wcq5bcDNa4Gt4NqP5jHwpyRYjR14la08wGx8wB+heQ3EpQBPsZmlzFsgtA1BL4Tg53WuYSnHsAOfIb6cHwfcMH6bqMw74cZS2HsGyNkFL80Q3+13ADlO2JQsErPLFopqLsdprjhhezLc7OJGg53hiOK7RHtRGCSu1ANLG1FTKjeug71pwJUFONhE9a2iBUUijCgVqRVLdjEQKpoFt+UY+Eq1T55Hm7ddFI8EYDb848GBNtKUTnSNSAHPUcTTTATGwpPvwAsLuIZNHGM5EiReg5NjZRpkrifGsJhfI+rUHYjSljCo5dRIEucRmp4vSOJ54NxisZ+mN+GZXlEz8xCtsBOYOYFY4hoG/OnGcg6VHslWhHonHD9xAARxCgH2xupXxlhxksjTny9Hh2Sx/R3QSAkTiAaG0splYhhuRxBaL4yH9SfFOf0AaIN8XRO0GrgLse61CIZrjybafx/rW550DD64BpaQQxKl7BFXDzsR+huYiSl0KoHn9JOwxgnvJsNDL/IaT/Lwbg1Wge2wgaf0dV3NRGAoz7GJp4mDsiaOZxooAZYwkd7AESzb4MQcAa5m8icsPKtPGc4D9pFNM+e4GekqTdFDA+PfetvIshH6dN0Ohfpy5ZSxjFEkIFrH0ntnHgMWOiCArRyscmLBzxCUYSfDEYAnVd+o/nOPdSCBVLbEBst7AEIfYRZrAfjmGHDNvw8P/VHAc+rUKU2yI2VlZVgsFmpqaggKCuLAgQP8/Oc/p76+nra2NqZMmUJ8fDzfffcdGRkZxMbG0tnZic1mIzU1lTNnztDa2orBYGD37t2MHz+erKwsnE4ncXHiokxJSVHZWlIQW1JSosJK+/r66OzsJDY2VkVAyCIs4yJsNhsJCQkkJCRgNpvp7u7mv//7v8nMzCQ1NVUxPM3NzWoKx2g0Ul9fz/79+5k9ezahoaFK0Cu9XmRGVWNjI2FhYezfvx+DwUBCQgKlpaXU1dUxbdo00tPTlSGh9BCqq6tTrYjy8nLa29uxWCwK5J05c4aMjAx6e3tJTU3FZDIRGRlJV1eXmuCSolfZ5pJTW7Kt0t7eroIuZdvCYrEogCLDIjs6OhRAiY+PVz4uklWQuh3JIMhWiHy0tLSo5wJKAC0ZJhiY/JEiaqn7kT5Dg9uRkZGRauQ+OjpatekkWO3t7WX79u0q9PXChQtYrVbFvkkWKSYmhrNnz3LnnXeSmJhISEgI7e3tuFwuQkNDcblcygRQ6nS6u7spLy9XZpJVVVWMHj2ahIQEzpw5g9ls5sKFCxgMBiZMEIO1MqJBprsbjUaOHj2qDDalvxEId+/BcQ7x8fFKGC8DTyVQdLvdXLx4Eb/fz4kTJ+js7KSrq0tpcqRjsgQwg60AJPiR7SzZEh3M8EjQLMGuxWJRU36y3Xn48GEqKyuprKz8yQCeP2DQXrNpaPOBD+WY8Xu8xgO6pmQb13MLB7HzPS6mEMZHdHMfLxDDk/wG8b3+nEHj+zNAzouI0Mh7+Ixt8OzNovpO2Q/8FsafgXvBtgLc4aDNRdAPdyOo+MN+2B4kisgL62HdYlF9ahD1+Ipf+PfElfK+IUf9d7Rm4OtNGnwAk3fB9/MRlTURbosUtejplTBijYFyrvBnQxqPvYMoEBeAfx2BpRPhHReCpXoU7eBSfNfA783COqawHngFal8Tu5rHQmxsFHf59nTEsx4liGjs9JEKFPMt0M5rLOBh3oBNy0V6/D2CGdmJqE1PAXH0E0IjXmK4gFnJQrbq52rHRJHF9UsEDFmlv6McdZbedCX6v6OAqfQTwj+o5TaS8FCPlaEc1xc0HLEyskJuFgum3GJkrHoGA6M/UmiVhRST93MdXsIx46aZCK4HyrUiFAq4rgDOwyyXOCVj8dKImfcR2pzoOKDpRSp4knAg4RyUZAtQcEHfizbg75gYQoBqzpBtyFH4tH4XghKZhxDR/yyHa741EAXs4Aqwk2tYSoJ+lJ/xBrCVGnbzCvCXr+GLOQLvdiNAVz3bgAqoXA4nxGj5fxLGULpJBI4xF3gUAhPFEu3TX/gecD0sKxrIaJXho48tB96IJ4lmYbCpr6y0oZLNq0YGCJsukvVzksUAghk+6JVecFnFGzToBzAJMDnBlQz2qTg4gBe4ulpfsEPA5/+HtPRAIEB7ezttbW3U1taqAn3+/HllaOfxeHC5XMTHx7N9+3aVowWokfbGxkYVICmFttLuPzo6GpPJxKhRo9T7SqFnX18foaGhyofF7XYr92WZ5SVHpUNDQ+nr61NTVMHBwcrXJTMzk4iICFVcZD5UdHS0AiWRkZHK9ViOcA8ewZcxFu3t7ezdu5eCggLlDZSTk8OSJUvIzs6mvr6e8vJyzp49q0St0i364MGDREREkJeXR25uLmVlZYDIljKZTKSmphIREaGA3OAUdOnhI40eJVAxGAxERESQmpqqgiiNRqPSK0mvlcFhpiEhIUqLY7PZsNvtKvU7IiJCOTnL4FOv10tHR4eKr4iMjFQ6IpvNpibqfD6fshOQrRIZxtrX16daYYFAgLKyMmJjY5XGJjQ0FECZIyYkJChAJ8FBR0eHaj/KVllCQgLDhg1j9OjR5OfnK1G0XKe0tDTCwsKIiYlhzJgxnDhxgvj4eMxmM0eOHFHszsmTJ/H5fBw8eJCLFy/S09OjTBhHjhyp2lQ7duwgKiqKYcOGUV1drcTK0hm6ubmZK1euqH2WeV9paWkKnEoH7MGfM03TGDlyJImJiepcSOdrqeGRbJm8JmCA+fl/Ptg6ExQIBBQDKMN65Weqq6sLl8vFxx9/zEcffcS5c+dUi+yn8ni1UkObCDwFc1iKz+UnmAd5G9n6j+JngNfrYnKpRq+3m19hAgpp3aQJse0Bje/3AzmbEI2OCl1GeR7+5BIjSnwAzBTV+V9CPjraLYI09WomflcZJFimNoB7BVjSK5uhGeAfEOcBvCxJFgVlEnrb4TIk7YLvP0RUi8wieBC+ekM5+1PORFifxmPJwEPPgBdu3IbQItWCqBp3sJmlGK4XrYi/lEPhe2BI+pJ/vCa8GH8LjGAjDwOb7QZ2UsltPMvnhPEdfbTyBqVY2MzPgAb+BdzECnDDrHtETEEFguV4CtHmcGGkX5csS0FyIuK5TwHHj4jnN+qvvYSX1ZQzie+ZxGnGUv0DKDKTVkJoBC6TTCdBLGUo55DJoV5upJEkUL4+dzIQAHUaQWeZ9dU9jSjLYxEzRo2IXpUbI4cx4tdTyOXjC1bxABwoEF5ESwSuLaQVM+XE0c9qjnMamNAMb/EkXiChFQgXODTrnJCbS1Dr2+2nmsPkG3J4CejEy2rgzzPgtfVw2y0w2ZAD30ZyjDTagWtI5/cs5Vilhhn4jClks4Jg9rFZP5Jr58CdfMrTvEEhoiMEH3MXK5iTZiBpvoHHgaF0M02/XG9ji7gK9oEtCDGJNhqhMwPeTBb/vDNNrPbbwIR1QHwT9ZzhIAUMRU7kif0YzcCAFUAPFn7oNCjnygfPspsHptJHIybVvAAPgn0Br3GAqvvg6jx944383zU8LpeL8+fPExERQXZ2NhcvXiQQCJCYmMgvf/lLBSzuvvtuysrKSElJITg4mMTERKXHkF+2fX19DBkyRNH1drud8PBw4uLi0DRNtYp6enpUG0Y+T4KolJQU1V4JDQ1VfjmS9ZD6G8lUyOkjKdaVLISmaVy+fFnpiyRrIVPK3W43cXFxuFwuNa0kR87lKHx4eLjKx0pNTaWqqoqysjJOnz5NS0sLISEhREREYLfbKSsro6ioCJ/PR0lJCVarFYPBQEFBgZpeGjp0qLrrllESfX19imUCVPq1nMwClGhZtsxkgrickJL77/f7SUpKIiwsTKWvS88e2ZqTbUObzaZAi/SWkSBH7odkF6QgWopfpSBappTLGAoYYH6kvqujo4Ps7Gxyc3P/7aj7YJ8Zp9OpzPra2tpoamri4sWLlJSUqDH+yZMnK68beW1Kx2r5Jzg4mNraWgwGA2PGjGH69Om0tLQwf/58MjIyGD9+PFFRUYwZM4YZM2aQlJSEw+FQoHLYsGFs3bqVEydOcPr0aY4dO0ZCQoJysgYU8JJTVjLQNjIyUh2jPDcej0exlNKLKSMjQwnOY2JiFIMjGRpAMTcwwLLJluhgJ255XUjWqa2tjYsXL3Lp0iXeeustPvjgAzo6OtTvf4zx/f/lI+0IfFsEqbAdC9hT8LGEscANrQBv8zR2zOYpLMoxYDYv5hAB4DLMd3IffxLf6FPW8T4LYJ3QTWQBFh4BauBTEXwJL8lIJGYC5+zwXiaiboY+An8q05HLEkFrOIPgeVi0EYgGLQcU25BSwF1OeHqxuGlt5SHI0ktBIwT/C6CEWZvA9BhU2xFjRksPC/NCJ8BTMEln/eWoEm/zOS/p4tREyjkMJ8Dw4KfMYQFzO4X9/6/EYfALRLNuakB0cpYBk4YDjGUufcyjAzjEeWAPX2J5AHa8KGrPbMRyxNHPTLxE4aWZCNr1XZlKvz4LJKadP2CAiwkH/oWZfYxAcgj9RFFAP4V49f2Xs1cZGHkDAZf+geBNDmHmaRJ4GqFgWYUwedyKAD2JDFhYz2TAplCfWVdlugQx+eTHTwjzEDzEMtbylBeY8iLZQWAR3RRqiQHCCeGPQA0zgwYME9MDwHn4wiHO8ifZonnTDdTzJUwvg90T+QihgTHTykL6eZQdoK9NHgCzcVDJsSKNY6zk1aUapJXyFd9xmgM8CviYwMMsZ2aPxjEW6h+GC8xjCoXAHDaRhTinxUArE6kljA3Mp5yFfMV34iXTy+i6BQgDxxOQ/wgvrivZAAAgAElEQVQCE04T2CK4VsDJLH3VHc3AuhyCOc0hxAzi8wimr0I/kw1AO2H4CUHPcmdg/EraSjaIC512weaYnBC6C7gfQuPRvt6OducmfjePgWBRGSo6kLn9/zx+dEqrsrKSiIgIzpw5Q2ZmJiaTib/97W+EhYWRm5uLx+Nh+PDhtLW1UVxcTGhoKBMmTFDOwtKZWLrq3nDDDYwdO5YdO3ao4i7DEOPj47Hb7VgsFlUkpEhZtrDkaHBvb69iTyQrIr10pC+PzWZT49Tp6enU1dURHx+P1Wqlvb1dMUXyC765uVl50dhsNo4dO6YCUKXoNCEhgZtuugmj0ahypA4cOEBsbKwypMvLy+P48eOUlpYyffp0KisrKSwsVNNAkk0oLi4mKSmJ/Px8enp6OHToEGFhYcodWopvzWazavPInwePKMsCOHj6anB45GCGR4qOjUajynSSbY3u7m4lXgWh6QgKClL+OtLYUDoyy+1LPxhZgOU5G+zhI1tWcp/r6uo4duwYOTk5SoSckJCA3+9XE0hSr2W1Wjl06JASbxcVFSndSUFBgRKaS/CWmJhITEwMHo9HiXrl7+QEm5yUys3N5fTp08pAEFAiZLfbTVtbG1VVVVitViIiIigpKQFg5MiRpKSkMG3aNCUmt1qtDBkyBJ/PR2dnJzExMSQnJwMoAO7z+TCbzbhcLqV1kwaZgHKkttlsXH/99Vy9epWLFy/i8XgUcydBzmCwI9tXgwEPDISOSqF/UFAQe/bsob6+Xnz4dWbTZrMRERFBYmKiGl//qTyCmIafWDBNIpQ+5uHko3Pv8ko2GGLeAPbxPi6W4ONRIIP1mAEjK+mnDTgBi1cQxF+FW8xyD/Aew0mhj2REyfqYID7CH3gHtgqm5rcA1Yhv+YIFiHvdoXr8gx1TKwR2iv/ecFn8im+AsgLIdDHCqeud3boFz9p3YOURRjOR4s/BdxR4dzE7/gkP3grv3Yb40m8APofWGQB/hPlhfPbJM2AqhaE5wHnupAl2x8H0dUAitXeBkYf4DBEqGVYCk5Lg3g3w9iK4NBkM+zWWYeBVwFBRwBxu4O/n4PbsSL4imXq+ZCsLeFxbwLl0jQ1zYUMJvF8JhTo7YsZNAl14sfEJZhIwUsLALM5qBOOxnH6cGPXsSC+iwtbiIQIrnRjx6ZxAIwII/QwjbQjeZBoDg+Xi335C9WvhADCWXhII4V/6gtUwYORSo792J4J3akPAkV/jJ4QgenFjZe8a2MtiMszrWcSTbFj4BLdtFLlgAurtQ9o5D/NDuebiZeCkCcZfJ2CUxQMnrLAUi7g+i+ZDKthmiHf9G8eBMJwk8SCzmI3oaL0OwAWqX9J0bLBGUEtP5sALK4TGHqDsMGRuh9AFGNlGP20Es5O7CfAyOVgo5WsmInyxz8OCqfRLUPzlLcDbGLlI/wOZ5G8TU37VBZBRpC/Rh36qHw2CnCN85Zwo9iXTSRc14JyIj98wjXU0IFy2Za6WNFfupZd+EvU1NuvnUl4JkgM6pP+9FWijgd0k3MmAeBkENpIkUSH45sD7ZnH2/t3jRwHPkSNHmD59OiNHjsRsNrN69WoyMzPJzc1VheTo0aNkZmaSlZWlTNpaWlowmUyKdZHZRfX19TgcDuWxI9tbst0i7+ytViv19fWEhYXR2tqq0tWrqqoYM2YMBoMBu92uxqITEhKora3FarUydOhQIiIiaGpqor6+nqysLEJCQoiJiVFj893d3URFReFyudRYr5yeGaxjkeGp6enpamJJuksHBwdz5swZXC6XEq/a7XZ6enq49tprlTbI5/Nx7Ngx7HY7WVlZbNu2jatXrzJlyhQMBgNff/011113Hddeey3h4eFKayPH0GUxlwJlQLWdZItCPvx+v2KGpJC1u7ubkJAQBT6k/4pkFSRzIIGOHI2WzIwESXK/ZDtKZllJBsrr9aq1BAHA5DXS1dWlzBJdLhdpaWmcPXuWv/71r4wbN465c+cCKINLn8+H1+slISGBEydOMGTIEMrKyhSLJM0la2pqyMnJoaurS4EYyYLIfZHXkQTucqJPsi5VVVWq0KelpVFfX8+wYcNwu91kZGQwatQolVlVWFhIa2ur8nQ6cOAAY8aMISwsjIMHD6pcLZ/Px6FDh4iLi1OOypcuXSI7O1sB0IiICCIjI3E4HFitVhXvoWkadXV1dHZ2UlFRofyg3G43mqYp7yTJfsnJQ6mpklNWEiS73W5qamo4f/68Gt/PzMxUoubBQaPyRuOn9NhFH+/j5LOyL+nKdPPRe9speRAeIw6KljOnYAW/qof/TDrDaBayk43ksZjPWc/rPMlpoC+gYTC9xT7gccJ4OVLjeAcIhYkXSpfjz8kCN+RXirvdQuDhVxDf3QXR8FKmuK2vK4OUTAp64bgZyMyFxDO6ieA9YF8N1DCJqWzIAe6D8E2IuhuYyL2IO3ISgYeaoTJOFP+tQMcRWDtxQDXKs9gMVrreAZpzRKXlUeBxOP0htC3n8fkGNgOBDd28vUiUndeuh6+A4YvmAzsp/N6FtsEAs8EQqYEphWjAkG3nJlxsxskC7mU2b0D8cm5rhp2V0IKXLzCzEzN5QA0RJCLkKKkMxIB9zgC3MhTYqI+RdwNhmJmEAzNJmPFixIcANmYEM/CxDna6ESvfgBLc6omSQUzCz1z6uQ4jPkI4SQlzGKtSKgdnHuxjwBbYC7xML1GswMgdWJlJPTyfBCvH8gWiU7nh0wX8buOXDARffCxOHFF8BEwmjMeBv7VCXyQEBWCHVbxTDn0UM02A4pe+pBqI4jVEu20maXQymggeDRIu0Oe0Zig9yY1PwF4/YNoFfAEv/AVWvMHXl9+Afz0iWlDmm+HzmxnvEivyvL4qnIE+M5D5CPnEYwaOffmGvl47gbEY+af4AH24juKXl4vDSlvL3qKVLBoPH28MwuwGmMhwfdVb7clgFjd5NCVQC7yEuKYkHB2OtOEJ0IaTLuL0dZ6kn78aBnImPuA5KnnqMQaEQlI4pE9qfRsjQLKUwUmi5397/Cjguf3224mJiWHr1q0kJSURGxurirHZbObMmTM4HA5liT9r1iwOHz5MamoqRqOR9vZ2ZR4nnXKTkpL4xS9+QXd3N8nJycqHRzIpsn3k9XpVArvJZKKjo0M528qRbDmmOzgwMzExkd7eXqxWKzExMWqKSyaFm81mJRaVY8vx8fEqP0m2B+RrZPCpZA0iIiLo7++nqqqK9vZ2UlJSGDt2rEoYHzlypHruuXPncDqdjBs3DrPZTGtrK16vl8zMTDRNo7GxkfHjxzNy5EgaGxvp6OhQd/kSyERGRhIUFKSMBWWrR+ZjSaZscOaWFLZKXY3b7SYmJoaIiIgftEJka0oyNLL1JBkZqckxmUxqak2Gfg421JPbk2wQCAZCblsa9oWHhxMZGcnBgwfp7u4mMTGRcePG4fV61Yj7YMaqvr6e/v5+mpqaaGhoUPs0adIkDh06pFpjubm52Gw2BWpli0+KuU0mE42NjcTExOD1eqmpqWHo0KF0dXUpHyC5nxMmTKCtrY309HTMZjP19fW4XC4lzpdg0+Px8POf/xyAkpIS+vv7yc7OpqWlRfkOyVac0+lk1KhRuN1uLBaLshKQayvXPyIiAo/Hw8iRI3G73aSlpVFZWcnly5cV2JGsjXyNFBzLqA95HpxOp/IjMpvNP9B3SSAeExOD1WolPj5eeQn91FpahcC0Mo2aTAOpTKH/DtFhgj1QUMlsYHoS9GNlDhtZBWj16zEkFXANRSQC1efBl/MqQ1lBBnCXS2gWgngVf+mL4oeXZ8Dd4iu7BPjsQ2AnGLaD9sajA/UzIFyURwPHF64HZsLPYOw2qKcEeAXK3mFDHOIb/JB+n6vblHwCoro8DmyIgw/gTa2ZZYY4Thsm8v0V4DsErnHp482Xgc1gehge6J3Be9tmiMowfy0vlYsdvn+R2Ow31bDasZiZvAx8TjCbKbwP/O9AtBVgI3/GyWMkA9PYw+/YQxssmAFfFsFq+OoCfL8OXtG1OolAMp2cJoLRwKN4MdNFLTG4Ee0zaTHXKFaEcP0QNyOUN+9j1ptMMfxaWQ96ESjuhP6K04iifb/+/17g17xONlsRets0OtnGBOY0ATtvQ7tnLwMOQVkIusRNIw526vuSwDlmks1O4BOSIFHolb7xCsG3wfYlhUqS281A0lc0k5Mhn2CyAH8oBHeD8ROYvczOW7j4jBzY/SmcgB1PoEdsgGC1LjOKCZQvhKSN4jJjfByshu+0cKAJHpkBa8LhXau4UL4Bm2GNck8uAY7fAnOCgX/6Ec2yj4HRZLOOYr7lJn6mr+FWBOOTKiJESISem8WGMh+A6z6EsbChCWzxiFYXMGmbgCfRLt2O8QngwBPsmfIbJvA+t/EIoxmI+pBnDsBLMwE6sVNEK2lABn9mN4/uRQxsnWBgQn20WMOABY6YBP5J0K+PCkRLzT1o2//u8aOAp6+vj88//5yKigqlB0hOTlZBi0ePHuXuu++mpqaGn/3sZ3g8Hq5evUpUVBQjRozg7NmzSrjc09PDxYsXGTFiBD6fj5MnT5Kenk5LSwuhoaGEh4crfU5bW5vyiAkLC8PpdKo2isfjISYmhoqKCtVKkDS8NLfr6ekhJCSEpqYmVQR7enoYMmSI8lmRwMBmsynNR2lpKXa7HYfDQVZWlmqNDXaqTUhIoLOzUwmeATX5FB8fz9atW/n/uDvz+KbKtO9/0yXd0qRNSdt0L6UtZSuLbFZUGBQFQUcUlEHxcRlRfBR93cZxwWWccfRxYUQZXB4YGBdEZWBQcIFBQGSppUL3ltKNpk2TLknaNEvP+8ed+2553nn9//F8Pv0U0iQnZ8m5fue6fkttbS2LFy+muLiYkpISurq6lBotIyOD2NhYHA4HUVFRjBs3DqPRqAq+LGI6nU55ssiOmRxLyRHHSIAwslBJt2mZHi9He319fQwNDSlfHcn18Pv9ihMkgyYlSVmqq86fP8+xY8cUONu5cyd33XWXyvwaSfaWXQMZfDk4OKhASExMDIWFhVRVValxpPTukZ2skaMwm82mRnhRUVFceumlyuPHZDKRl5enxpMyfiQqKgq73a74Mv39/XR2diqukASJMiJF8pckMEtNTVUcqKioKHJycsjIyFCva25uxuVyUVtbS0pKCkVFRURGRvLll18ybtw4ysvLMZlMjBs3Tp1jNpuN7u5uldU2e/ZstZ0xMTEqciQiIkIZXw4ODpKamkpUVBS1tbUq123kOFHGpgwMDDAwMIDT6SQ6OhqLxcLo0aMVZysmJkaBULlvJSlaAjrJdfslLQZOoh3UUVUIERzjfaO4IN7GJDbTyp074PUbQLvLztB/wVEjnBBOERzjbT7kHm6eeAf0vscq0wO8DnxbCPRqjDfpqJ4BwYE2YDzj9/RI2xEqbq+BpYVou4Hvcoejw/cBnUdp1s0GDPD+y9AtxhV7+TvQwiVj4Wg0XOGFvXmhDXkNSIQyE0yxQ5nMUzwB7LQoBQ65AfhrBFMyoGxlyI/mHREFsNwLm26H+EXgMgErUzmSD/+RD3VsRWu6hY5s0F59H7rf56vnYQGt6LZUEs+VfAlcgpknCQ9tZYP42b6MDdshb/s0BT2kAe4yhhggjDaMLMCHnjqeZjwGklgaem4D4v7+hdA2vEEfjRi5BjGauC/0+xKxC3iX8dxOH2FKo7wgtDMSEXuyIbSjRY7EWvw4mcwYrRe4Df74OVjuYcrKjegaNK5aB5tZQj0wmz4ayWYmoityG+BkPMefAGwQ+Tew1sC3WJipt1PGH9jihhb05NHCcPR3A/9JEvigjHR+bGoDA3iSIG4pPE5vSJ32J9gHW16BBVQgynYx8E8+4zHWIng2WZqOY70is8oWAeCmMnT473plNqcQ3ZMNyQLkyAQqA+DcE9I76SLQs5LDn68EJ1RMf4MpE3V8y/eIHsl/cx+R3ItoENmA7hg4VugB/gLffx06GY/g0mYAJVh1Jt4xwBq3YE9VFEL2i9DkAw6Y4N6H2WH5G09zmszQWRPJsAchgI1B+ghnA43cu79RoBcpO18KHmtIeBX6GWQhcITX6CWFYfEWobPhZyg8Pw942tvbVTK3VMtIPorkSPT09DB9+nQGBwfZtWsXEydOJCoqitOnT5OTk0NKSopSU5nNZgKBAHq9njFjxqiRSHl5ufLUAWhubiY5OVmlWoeHh5OWlqYiJyR59dy5cxQXFysFiyQhDwwMqCDK6Ohoxc9xOByYzWaqq6tJTEyksLCQ3t5enE4nsbGxWK1WpSKSBoYej0d1I3JzcxWvRcYIyIDLmpoaFixYQEZGhnIa/vHHHwFBYp0xYwZHjx7FaDTicrmor69n+vTpaoSmaRp2u10ZzgHKHE52viSxVHZiRpr/DQ4OKj6O5Kr4fD4iIyNVYrrRaFQ8nJGSaElyloVTStpl7ITb7SYiIoLExETq6upITU0lJSWFPXv2KLAqwUBMTAwWi4WEhARVZGVAp9Vqpbe3l/Pnz9PT08OePXu4/PLLVS6Y5P3Icags4LITJQHvd999x5gxY9T2SLdqSXSXnZDu7m527NjB7NmzGT9+vCKmy22THSO5D6Kjo5UhptlsVtsdFxenTAX1ej15eXl4PB4yMzNV6KjX62XatGn88MMPtLa2KsPHgoICZX4ou1ADAwO0trYSFxdHd3e3kuHLbQaUvLyvr4+BgQGVzi7l6CMl6YAK9pWPSUK5PNby3LHb7fh8PlwuFy6Xi6ioKOXALL2WfknLFi5i6CYocoAuKYAbMYia0aah9eugCCrohHuTudwoGiNi+SPe4JVEdcLN1mLYB5XL4FtuF3ERX+RiXgjBgVeAI2ygV9yBAzsswPrCYXlVFsNqrA8Aitm/EuB6yIIZdxByes6D9RNZChzOhpIa2LtbdEAeG4OoZDfD9RuhTE5jroH4X8Pe6yBqJ3A6AqpEm58qaPpYvC74HHzwOLAFXNOAkwF4ZCWXzF0JCyehTb5FEJw3rOa2hzaymVbgt8wkgwXAkz7Q67fyKxbxLbN5nKPsxk4Fbnh8GWu0R+CBl+ENIX9/bSM8ZIAF7jBOIcCKBz2PMx692Az0oU0wI4jNf6IbH/H4MGBGTOYSEeO13aHdtwqYSxOgp4UZOJnBePqpIJYG4HocBJgATKCCWJxcQhXwvAl4wARvGPA+qiP6tMaTEzeif0bHlmcglWUIVFoFGIhiOZ8Bh36tkb1THCqm9eKfa6K9BeZg5zkghd8z7o0nCD7Qx/DgxgycEJ2GzgcAM35rGzZ9iJRtHU5CoHEhHIEV9COpyjCdAh6jzgJhnQaW4MEAHDMdxKa7TDkGzQXm0I+XWPSIY/4kYEAmd5pJIQk9Qki4NrTOB38tjsdSzU4Zy6B0ttjslRfzJqtJYSPPAclBeCIcjpED/F14SVUCN1+hYh3avxYrfrMK0VRb2EZTYzrkNsLOUBSE5R+8xmhFu3EDp4kigBHxJRFmOmtIYc08A8yTTOR9DLN+PuNxjuIA4g59IQBRFryVJJ7xFtLXx8gc7DzLv19+FvDEx8dz8cUX09vbS2pqKhkZGTQ3N2Oz2cjLy+POO+9U4YmfffYZOTk5REZGUl5eTkdHB7NmzaKrq4u+vj6KiooYPXo0paWlTJ8+XRXirKws2traVA7Q4OAgmZmZykMkNTWVM2fOMHHiRAWcHA6Har/LO1IZpyDHMZKoKkmlVqtVEUQliJI5WCkpKZw9e1YpySSHJy8vD5vNpuTf0pjN4/Gwf/9+ld/l9XrJy8tj165d5OTkkJqaisViUXEGaWlpHD16FL1eT1pamjIXzM/Pp7GxUQWCym5SIBBQAaCyCyCLs+wISBXOwMCAkqj/z7GElK9LR2aPx6O4HnI7zGazKpRDQ0OKZyO7MlJy/dVXXzE0NMQPP/zAkiVLGBoa4l//+hf9/f2KSxQREUF+fj7jx49X6jBpHtjT08NNN91Ed3c3X3/9NV1dXSpgVZKsAfU5fD4f9fX1quBLs0Ppp6NpGvn5+cp0cuRYrrOzE71ez549e6itrWX16tWK0CvVWhK8+Hw+kpKS1BjR7/crwCDPK8mVkcozadcg/x4eHq5UhhdddJG6Eeju7lYOzmlpaaqT1dPTo/LVTCYTwWCQ3t5eent7SUhIYHBwkPLycmw2m+p8FhYWUl1drcaYslsmwdtImbrcLnmuSFVYbGys8m8a2eWU+03TNMUT+6Usq27RmLtVR+Ze4CpYuxl0szUofIVAP4yLBYgjckoUPQyGOhPp3MCVfB4ON7kBFsOyi/gzwBfv8fhCHX/6VOPQwtnIsIQD7KQYMSyw2sH5AAx2Agsg/zLQazqcdo32+Xa4wyIKTGkEzG+khVyhvvkmFlJFpwPguQjADE9GAJXw2FF4aXYoWcgMhDdCVS7eCJi3E/a/DOghfjm4qhH68scR7ZEtCNSwBuLXwQAG/vDyICXAJSyDb0/DbjjORqa3w3RrBk7gKT7mryxH/3uN+Jd1XAOs5SiL+R4VkXE2EAI7v4btnxO/ER6cDdpRYdY3GYinnwDRPEcY+tDQYShUfsyEcZAw5hKPHhfdJNEM/BUHYKOb8dzJcQ4wg1PAOLLJ5DiZvEUmi4FEiqkKcXJ8RDCOciZjBqZHgP9eRGvgjVeAA+wJh9smCil2dR9cFQGfnN4O3dtDttaIhsdcGPW5MPZbDKTsB93KlcAB8hgO6qYbwlS4E6HfhhDl9iaeZz1OvSjb0g1IOZs5CaFTQo/GAU6agas6dZgR3J+CJDiuu4wk+okjluk0EcBCBGeIZgIlfIdAxNcwRCa95BPDUOjsFJ/IzLBv3/po4FkL7P5YrNoNrPwS+JCnSMdDGwvCxceLws4gN8JNPeJNTNuBRLBfIXDJhwi3b0uveLwB+DQXHr4ntHEtbEKAkjtDp2EZ0Qwnf+oRPahUxN1BfejfcrjpBlbxJ/T8iUjhLm6PhS6gD5F3RzPwOhF8K+JN/j/LzwIeOcbR6XTKFE3a9x88eJCsrCzGjh1LVVUVJpMJq9XK6dOn1QhGAou+vj6mTp2KTqfjzJkzFBYW4vV6FRHYYrGoO3KZJO1wOEhNTSUYDJKSkqL8ZhwOhwqZlPEJCQkJFBQUKLO2hIQE5aHT2tqqHJNlB8RoNKpRl/RrAZQ/TV9fHxaLhaGhIQwGgyIBy2IyMDDApEmT+O677/D7/TidTsaMGUNOTo4iV589e5aDBw+ybt06mpqaVDDjmTNnVLp7RUUFdrudxMREBgcHSU9PJy0tDbPZrIi+er1edWKkgZ+M5JCSbVnMRvq1AMqAUHYRYmJicDgcKthSbpvdblcgTwa0NjU1YbVacTgc1NTUEAgEqKysJBgMsnfvXtLS0tQIKRAIUFJSwrFjxygvL+fHH38kPDycUaNGkZycrEYrR48eVSTokT5I0jRPfgYJfD0ejzo+fX19KvIhJiaGWbNmqfGk9GwKBAK4XC4CgQAvvvgiACtWrFD8FunCDWA2m9V5Ltcr+V2S2yW9nGSGlwRvMqbj3Llz6vXJycmKX3XxxRdz/vx5/H4/RqMRq9WqQF9ERAQGg0EdTwnCTCYTnZ2deL1eSktLVafN4XAos0IZyVFVVaWA8b9zVQ4LC1M+SnL0Kc91+b4jVX2y8zWSvP6LWXyQtV6D+7fTzHKeuQ1gEfl8wapYcXmt2x6LP38QjoDhPpEaXokoEv/MB9hCEqU4/qjB70qFV28xQD3x2HHt3MOO6/7GBkQxGyyEpBoY3A20wNloCJKLzgA8IkJEw5sg2AIcyaU9F/IaEYXDB450uKRGDGeefh9cT8CMF8XIgsqQND18O6xfBrthVCC0rQ83wrZcXOkIOY9ZyIb95eJ9sUHUOlGzmjjCY7zLbjbi823HHw/Nt4kQDb0VHOTyEI1oi5fz+m4IPqUjnFz20YgbCOMKrsTD3rfPAr+CN24FXoVlR3E5Z3P8HphJEmsQ45V0AkTgJZpehogjDA9DxNGIkWaERL0FPSkkkUgTTrIpJ4lPQzwfMzM4gugM/R/gJmawihlksh9IoYUlnEB0hAziE+HSvoDtC2HZenjjXeZwWo0cFyMwZ5sRMh2IIl2M2LlqFgRdm6HhNkjZBQ1L4Hm2sYphLso+4Kl1iAOtyNQ+4FauBCr4M2MAsw+GwuFsuOAq+RFNo2+nBfhtbwQR/DX06ccRYCqDmp0vHVCeBL9LgjydFmoWxpIYktAL9+hmIhRdVwRu2jECEEeAm9ErMvgLiA7ZcWCbF26uBE7agRsQrDLZQ9PzJ/zsJpIFwCB7xM7JPYpw0DTDxpNiQ6ath/dCHZnluYICNb+GsPnTKMaDG8GdciO6T3HAJ68CS3vpyIZmvqOF4S6NDwHQ5PirhWGT5zeZhugIlYDFAJY4KL0MWgohsxDcVxCQURPX8W+XnwU8kuyakpKiHGQlf0QmNvf29pKSkkJGRgZHjhyhp6cHn89HVlaWUpRUVlZSUlJCbW2tilJITEykpqaG2bNnY7Va8Xq9dHV1qTt3GUsxfvx4RQZNSUlRRofSXE92PiIjI0lMTFR3/5LoKwmpMtJBFgQZiyBJ1YAaY0huQ1tbG2PGjOHs2bOq+El5eSAQYObMmURERLB161ZOnDhBUVGRKlpjx45l7dq1/PDDD+h0OmVid/78eW655RZ0Oh1Hjhxh4cKFaJqmwksjIyNpbW1VRFMJlEYayUmiqnQrlsVZr9fT3d2tSN+y6yE7FnLsFxYWRkdHh8qykuaCslsjQdV///d/s2DBAmJiYqiurlYKJUkKl59n3LhxXH755bS2tmK32xWokCDF6/Vis9kwGo1kZmaqc2gkCVh2s4aGhhgYGKCpqYm+vj7lpAwoR2W9Xk9+fr5KeAfUPgwEAthsNmw2G9nZ2YrPFRkZidPpxGKxXJA4Lzk8RqNR7S8QfjVRUVEX5IPJEFU5xszJycHlcqnXSdAlYzI8Hg/19U3g1csAACAASURBVPXExMRw/vx50tLSaGlpISwsjNzcXAKBAE6nE4PBgNfrRa/XK2m+z+cjOTkZo9FIW1sbTqdTOXsXFBQo8CjVcxLQjR07Vlk8eL1e7HY7nZ2dar8ODAyQmJiovh9yHGk0GrFYLAo8/WKWEsRs5K1lZBmWccNJHeCjDhM308sHLGTfMh20g+6+ag4wlk8RRfoEUiDrowTYdQ3A3aI/cf8kYDEePhbcnMU/cZ8BtPfEi4rvgP3vAt+vI/jpOrjmLNpCuOoV+DYC5gRgf0gQlN8oim/4BxAcDzwKhw/Aqp3gsgCZcPxt6LgH8ntDhon2ZeCB/Dao2wPPLYL9NbmiULeWwvJpsAr8xWLk5dIa4YFcBj8N8Ssap0Huf9AM/FYv7rxL2sGeDFGtgLNRSOx356I92AgG0O5sRJedy5d7G3my3kP5fWBmNJsAg/AQ5ildLvuAGQGYFyEaTGcZIkA03egxEU0bYVRixC82DQA9bsDIEaCFbF4P/a2Y4YLXEHruc4jC+TSwgHkijuJt8UC2HZpWE7JntrFlmY59iH02neG8SRCEVyeQWS9WolvRimbIYCiUnRnWAdggLwR28g7Bkx1QfoPCQxQhbfL2iYNJJpDJblbwmraew+xkDPChXqxbWupdXgFzx/8Ofi1LsAjYGGISrxILPENV0rCjtBMB0sSzdiDtA4d9axKRaWIpeOhgMlXoyQOKcQCwiiSqgDdXw81vN4p3HT0Nxh2Ef9pDe7UDGs9C7jYqsPAn7LzKCuBLwriCIe4Q61x9R+jIyKDRVWIe/CFw/wmGGEsJpexDjNNEj0Z8/pLF0JINmfshJROmh5DNrcWCryOOHIwHBrkU8e2ws5tSDJSyj/Uh2jXETRPNpdFBmBgOiyfKsfS/F1/8LOCJiIjA4XAoro102S0rK2P+/PmcO3dO+dV4vV4uu+wybDYbP/74I2azWRFfU1NTFShxOp3U1NRQWFiI3++nt7eXpCSRbmuziZZgUlISFouF9PR0laQ9NDSkoha6u7uVxLqnp4fMzEzVEZAyXSnLleOF9PR05VkSFxdHQ0MD0dHRtLa2YjAYVMdHplX39/crANXZ2anurmXOl+ToTJs2jTvuuIO9e/eqKI2LL76YyZMnU1paSnd3Nz09PQwMDPD999+TmZmJx+Nh9OjR3HDDDUrZJFVhwWBQEYFLS0tVPpQsam63W41RJEcHBJ8nLCxMRSZIVU8wGKSlpYWcnBx6enoUIJGjNa/XS0dHB2lpaSrrasuWLVitVhISEvjkk0+UV4tUA+Xl5VFfX6+k77/61a8AoQ5KTEykpKSE5uZmhoaGqK6uxuVyKVdlh8NBSkoKMTExxMfHK96OHN3JbsqJEyeoqalRSi0JemJiYigoKFBAS5o4Sh+kc+fO0dLSgtFoJD09nTFjxuDz+ZSXjtvtJjY2Vrlwy67Z4OCg4s/IbqLdbr9g5GMwGJT5Y3Z2trI4iI6OJiYmhpycHAKBAE1NTTgcDmVg2NnZSVRUFC0tLQwMDOByuejo6FDEaznOlXlmqampijjudrvVSK25uZnm5maCwSCTJk3C6/VSUVGhoiOGhoaorKykoaFBdXHy8vLIyMi4QIHn8/no6+tT0R+RkZHU1NRw5swZYmJiuPvuu3/usvC/a2lBVBoxyWXHlRp8tY4NIdt9bdUXXL0FtlhBqxvLW/niAhp3DHQz59PMNzzFXLL4o7gFfftWminlV5zm24GfuCnmfT74yU6UzsLgapQ4aP9nsGEPrOGf8NMY4nUr0QN70+GpNnjBgFJDGxAN/Ye90FAKO9YCN0P5zlABdwNZYjM+jgafFzGiuhecTwDT4bcGBGvUBzCNyM/AH8oRcBUCfAhznyB/PdRNBOtoaNcOcYIENrOM3Wynyw0kw2fZsCAbbpgCbhr522tw6w4E6FnVCK+C7qpniOdZXNdofPB3wHQZsIrntf8DF72NNQL2fy22L8YXxkvL9UwHJhPGlNBuWgsqgsCHgTwcpJCEgToM5FMZet5LubD/Oci+BVatY9hi52nYbACqvwAOwOoPaeJOIJVg3z34g/ByuOiUuRnOcJKdgxJCjZ3PgEdB25UBRaLrcy1wqxHW6qFlTsgpZg6kHIPiQ0A3eJaI95M+zopYQhZfAXCAE+KpFDPsiecE5o8HrnmR5/fAk3wQ2qADNLKCx66AeF6hsE+Q6B/DA7Phz0fhDYZwswIDexFApzv0kwXciY94OtCTSR168kPi/CQyGY5K27sRDmzM5S1ycV0B/BW4xQIloHskF20rkCsUa4tVz+wjhtgY2vmfEk8bXsIxEsRBqnj3aW6YVgncBfzAbiJpIQ43HqYD1+8SO/1v+XBrEwRmQVhAJMU7xg8rrKpCa9kL+PgOEFTwFYCL3wEtWNlGIsPO3EVboVa2soBhQ6ILl591WpZZQDLiQXp8jB07loaGBg4fPgyIfCmHw8EXX3xBdnY2V199tXK6lXfFLS0t+P1+LrroIuW2PHHiRJKTkzEYDDidTrq7u+nu7qajowOdTkdSUpK6Ax8cHKSzs1ONvKRMeWRitNFoxOPxqPypzs5OBRTkeE2GccqsL6vVqt5jcHBQBVl2d3fjcrkwGAwqHd5oNOJ0OlUUgyxwBw8eZMmSJcyfP59gMMjZs2fZtm0bkZGRTJgwgQULFnDjjTfy6KOPcvfddxMfH09lZSWnT59m165dip+iaRplZWX84Q9/4Pz58ypMVaqXpAGg7IZIUCPJrr29vXR3d6uiFh4ejsFgIC8vT/m/pKSkYLfb+eyzz+jq6qK/v1+Rdh0OBx988AETJ05UgK69vZ2zZ89SWSkGzdHR0bS1tSmwGgwGycjIUIXX6/ViNpu57777WLt2LdHR0YoYK1Vy58+fJzIykra2tguM8aRpnsvlUgBjJNCRHRfp9SSdtSVYksTcTZs24fF4VPJ8bGwsbW1ttLS0KENMOTbr6+vD4/EorpCMfujv71eO3nLsJjuHktw7atQosrKy1EhIdoOysrIoLi4mISEBr9erFGxmsxmLxaJI3yaTCU3TlDRckuwdDgf9/f3ExcUpp2er1UpeXp7iRv30008MDQ1RUFCgOnhyX0ji/eDgIBUVFXz77bccOHCAEydOqP2RlZVFQUEBs2bNorCwkKlTpzJ//nxl6viLWeRt/V2I6poIXLyONY9oYio1VzztZuCzfLi3CeLq4JmZ4OYbrP0A3bzJRHg7wAoeUAlNxNj5gK3Ap2yWbxJzMZjWwx9DJnH2k8ACvBEhf5AnRZGd7EagnANQViiYQMLiDlG7/iZcjpveAL4CPoUPJkLwIfjvCODhg2Cy43hDSISXyrZFqKL7ZdD0ZsiugRX8Hq7L4CaAn0QgLb83sZk/QNvHdD0HuvzriFoI178ZkqjrBDOiHEi7AXTHNHR9GrqkaiL4E3rg+X/q2G2SsUU3AOVoG3Rs0nQw/2Ioh/HLhwNAjwNO+tlCPxMRneBKROyEl0T+BtxNPvUIoOJDNJuev0V0dtgHbN0mzCBbo6G6F29wESt4BajgJZ7lMPfwjRHeDocnHcOq5lsRRbUFgX/Nof+jB12ZBpnwVT5Y++GYDx5cr6HLriZzk9i6FId4rswYjQhC3gcSS0v3pRPA9awFtPadmBm2M2xAKJSOhA4Tfxzu+MgO0YbQ432rYJsRfgfilQbY9LLwKPoMaOGq0LveCVyDl4toIIl96NkH7AtxeFpCp/w+RBSEdB1aEzrXxn8Nl2SIjx35n6GPogfapkHNMth5RegorAXeIYlnQ3sSZhHEwXygivG8EnregtDP1TRxP0M8rFLun1kiRnQAVdlCXt5ohGOx4hyTP5KmfDz0js0I4HsIOMAf2c02zu8V58MM/sVc3kB3W654wM+wZOvfLD8LeGSRMpvN2Gw2ReqcPHkyCxYs4NFHH2X+/Pmq0Hi9Xj755BOioqJUMKjM0oqIiKCsrEyRI8+dO0dDQwN9fX0q06mzs1ONHWpqakhMTKSqqopgMMioUaMUCVdyDaT7r+RCyNFCb28vQ0NDdHV1qfGKJJx6vV4sFouKU0hOTlYqJbPZrGIirFarAmK9vb2KUyMTyY1GI+PGjSM5OZni4mLa2tqIjo7mxhtvZNGiRUyYMEERUI1GI2lpaSQmJnL+/Hnq6+vxeDz4/X4mTJjAqVOnOHr0KPX19XR2drJo0SJqa2tVcrbkt8jOjdwmCeYkaJDcHUlIlQBCAqGOjg7lOC0J3RJU/P3vf6e8vJyCggIFbOXIy+/3YzablVOw5N4EAgGSkpJob2+ntbWVoaEhlUofFxfH0NAQK1as4IorrqCrqwuz2YzZbFZcpv7+fjwejwonlRJ5KcmXBoQgxo1yfDV16lRmzJihOnbSu0mOLqOjo0lNTVWg48svv6Svr4+mpiZlrie7f5LXJblCUlkmwYM0CZT8HEDZEUgzRelaLb8HUVFRKp7DaDSqfC+/34/VaqW4uJjc3FxiY2NJSUlRoD8sLEx1GmXSfXx8PA6HQ/GMYmJiVHeso6MDj8ejODqSpzM0NKTWK9VhMsR2z549vPrqq7z00kts2rSJ06dPk5iYSGZmJiUlJfznf8qr3i9kuQ+hsc0EXj4oOAZF8Pwr4NRp6G5rpQG4Zpcoim9lQ0s+PNMnJMkRIa8Rbf9p4AQLgAd5OPTmp4jkNnhktYihLIF6jgIvwBioOwsPJgP8ipmBEOD5syiJZRMZzl8wiLvUlNBDnAL+2S+K3f2PKMNfXSO89iJMCIBVdxm8YoH7hVdQFYhKcUAADL4U28mfoWnisDfJdIBtsSJu6B3guycgvQ3j0/AOO3lrH0y9T/A9/kODcVzKq8ynBGBhL+F7YQNjQ4Z58BSXci1xuPmOZr4D6tHNnMbioAbcBNdDxTJRyMyfw1UWuItYviUWO2EhErKYhDxAGPWh/TAmtE1ZDA+LXofQvEIMo95gEPiU6EqNVcBDJDAZwTKpD21rIEb0Jy4KCn6VzKD0h96zGETlnw7/nCJOk7AAOPWIjt6kQnS3aFyLOKyfTQmdS5UQtVXsw5eqQWyhE0ihgWyuBXTWXBUBBcN57C8GoQKRbfYUgPS8YSlfAe9M08Eq8cg1QBKTmPmVDgxwjxbNqkVif0EmXhLpYDxthImQWWAlQxwBviCMRITT8RrgW3zKTECaP96EAKKX1MB9AXjUDb9dhMiXfQG4rgZxdr4OTMbBe0A3rm80Dg1owFLiKQ0lrN/K8OBuKQIKdtMS2pVuBP/KENpbH4eL357QMQkJv1TIh1Se6YGiQ1C8FC5fCtcsFfu9aCloCy5HW/oA2oONzLKC7joN3Utb+f8tPzvSamtrU+MHvV6PzWbD5XJx7tw5JbedOXMmo0ePZv/+/Rw9elQlSefl5XH77bdTVVWlFCQSTIwZMwa73Y5er6e5uZnExER8Ph9Wq5Xu7m6qq6vp7u4mPz+fCRMmqJGZVONIEqvT6VReJf39/eqOWXJcmpubsVqtSkEkOUlNTU2KJDzSfBBQPBWZ6QWoQhsMBlVxkjJ7GYHg9Xr5+uuvMRgMXHXVVWRlZXHy5EncbjcFBQX4/X6++eYbZs2apYqjjHKQoEI67J4+fZrFixczODio7rgl2JDyaalmknwqqdySPJKRmUuy4EmwWF1dzYwZMygrK2Pr1q0sXryYOXPmKF5IU1PTBZwPybMZmY1mMpmIjIxUiq7e3l4VIVJdXc1HH33EwoULaW9vV2Gdvb29xMXFqdGdNAUcaTY4MDBAR0cHycnJCsBKL5nMzEwmTZqkwlYl/0juH5/PR1lZmQIPmzZtorCwEL1eT2lpKT09PZhMJu666y7liaPT6ZQlwki1GaAckCX/SZLApbJMjhQNBoNSFUrpvOTiJCYmKpsF6ZZts9lUd0gCz66uLtV1lN0ked7FxsbS0NBAQ0OD4pfJ81GCNXkuSNDr8XhwOBzq3Bzp0yQ/v9frZceOHXz55ZeEh4eTn5/Ptdde+3OXhP91y5JOHbvu0JgxCY6/fBk8fBrec/JU1mVMWQcuXTrx6RrzW4UaB4QcN9z4Mtpjj6A7cB35LMd/CUA3vwWyeYVXWU0Yv8bPk4x/WcemezUio+F1P0AqxDwBuVm8lrsaKOFwALAC90LJI6A/DRV/QoCbBXCkVBTpb0G04xtiQ1L1ffDly9AMb14kOkH/APJBVK7T0wBR3CsQHjGVUgq0BaJ6YXC2AFk30MYzQOR/iML4vB2eXgSaqxIX99PCep59E1Lvg+s3ASdg1TvfcfkmoAhGzUlg7gCsYSFuvuA2AMoZYhIGroSadYQVGhiimTnhOg4xDcz3Y90Oa76G8MXwtVeUT5mWVIUABKsQ22ZD7AcR/ykK3l0ISFAF8Gso23MFLLyRNfyEVjGJf068IxQmmo6TNr5EGODtBr7sFbt9U6worG6UDyOrxJGi2AZMOc2R0HrCQs4MWkAnSEifI5CRD5b0Q2AaRFQhKvFdQOGLiALfDFRxBKjYA/Amu1lEcegvHcBT5EL4Wnjgfk6tBxN9DLs7Z1FxFu68GQa3wZXtcKUeSkJdkZm36vgAePefOr4CHuM62Pa5APTThUfQbwJwhDAWIABNIhAdkq4DTKMPH0bFY5oe2ieRDLsgtwC8itj2hEJ4sBCecYqtaLsdqm4XuV/BQnhkNa6Xq5BGi+IofYZotwiIdwiwsZ5NDOeryfVLgFPEMEerCCjej/CeMqMyRNVvGI5R84Xe5BT88CDQrBOd1htkftiFi+7nnFXnzJmjZWRksHDhQhITE5Ufj81mY+zYscpfRI4TTp06xebNm1myZAnBYJDc3FySkpI4cuQIVqtVyWSrq6vJzMwkNjaW6upqioqKyMjI4PDhw8TFxXHmzBlyc3PJzc2lqKhIBVzKcUNMTAw9PT2cP3+elJQUrFYrbW1t5OTk0NXVpfgwdXV1qiMyfvx4lZju9/tVZIXH41EdJhk22t3dTXp6Om63G5/PR2NjI4BKQ09ISFBjjfr6etra2ujt7eX06dMYDAZF1v3Nb35DamoqHo+HyspKZsyYwYEDBxgaGsJut7N48WKlqOnq6uL777+nuLhYjUCKi4vx+XyqsHd2dioDRukNJKMUPB4PMTExdHd3qxwu2ZGTTszSz6ajo4PS0lJKSkrQ6XTs3LmTlJQURo8ezSeffILf7yc2NlYZF8rXSW8fqVQbGBggGAyycuVKKioqOHTokCIEj0w6l1EOMsjTZrOp0eTGjRuxWq3KBLCjowO3283Bgwf57jsxv/X5fMyZM4f4+HiSk5NJS0sjKytLdZGkzLq9vZ1XX32VtrY2WltbVTK8x+NRYERGXkhSuMFgYOHChYo/I20JRsrRJYiWrx/pjiwl9fKzS66Y7DQODg5is9loampSoFHyrOQ+HD16NF6vVwXXxsfHo9PpqKioUOBfxozITqdU3wGKW9XT04PL5QK4QMEnv+PyMfl/+d2Qo16z2YzBYKCsrEz3P68F/2uXD3QaC+D1JHjwDo2o92FQ6wfuBhYTHrOMJ7yiCX9JNbxWqOO+foiMfQbN8Sy6JAswHe3QF+jaNVh2EHid59nJU5wFbCRxMalAxXINPr4HWMzjLOJP/AsogfUR8BG8dFRIzP1d8HyCKMpN2ovwwBM8vx6emggfnoaHEIX4TAT4/RcD10Pvw1ySIK7lmYgOxdKDMO8y2F+IkKOfFmV3cy4wBi4J+cQdjYbgwGjADcs74Wa4KuTdwxjg5TbEHbyPD1lPJqJs3bkUBrdDNBo3hOv45BDo5vzEh0wiD5heAbrx0xAtEjev8QAnkCaBJxGwYjLsXAYvQHwpeEOEbUm1vQtRlLMQOO8A0J4r1GVzArDfgvAuaka0CZYC18CUiToWIJpUk4FvDomdMnWeGH1Ig96Udii3Dru6hHjIgCi+xUDxLjFuqQQ+8EFkO3iyIa5d7LKhFMEziSgV6/DMg7i9qLgD3W/38FvdQv7Ka0Akd3Mfm96DpNt1rAmtKxJ4ij8QydP4ccBFJraUwq3UQShONcBUIv4RJwDMX0IvNDOsHGsJ7QezOK08SWI7DyMgRtl3Glw6SfwRA3AnDBTCQ5C/URwXMyOJ1gJsSvegpStDH+UUvNQ2zKexAfs/B677OvQhFsA96WJOld4GA+kCXRaFdvD8ttAH7eYhFkldFSnHxHlKlhhtyQi56XWIL8NIVb9cZE7WyNYPDLeAnAwDn1TE+bwWSNL+7TXsZzs8sr0uW/8g2vXJycmcOXOGsLAwRo8eTUZGBtHR0cycOZOioiLKy8v56quv0Ov1uFwurrzySmVzL0dKI0HT8ePHSU9Pp6CgQIGL9PR0urq6qKurIzc3l/7+fqKiomhoaCA/P/+C52RlZWE2m/H5fJhMJtxut5I6S5KzXq+nr6+P2NhY5cXS1NSEyWTCaDReEB8hi1x4eDjNzc1q1CGdiWNjY6mtrVXSbIvFosCG5BCdPXuWzMxMlfE1evRotm/fTkJCAhaLhcsuu4zz588TGxtLS0sLZrOZJUuW0N/fT1hYGKmpqaoTIgGe0WikpaWFsWPHEhUVpbx4ZFyBNAyUfJ7ExETcbjeJiYJJ73a71XguLS2NEydOMGnSJK6++mr++te/4vP5uO6669izZw9dXV2YTCacTifjxo2jrq5OGT7qdDpyc3Ox2Ww4HA5aW1uZMmUKVVVV2Gw21WGSnkcyEV4Ch8TERDRNY+HChQq0Si6R7NQkJCQwd+5czp07x7lz53C5XIpbk5+fr54r19XR0cG9996r1qNpmjKVlGOxkXyoqKgopdz7y1/+QlRUlFJWZWdnc/HFFyswPTLxXaq4pIy7v79ffV/S0tLUukb6Q0kullQXyu6hpmkkJSWpkN5gMKjMH6VazmQyqQy3sLAwBgcHaWhooL+/X/G1AoHABeGtI/ldchnpdSTHyv8zpkICx1/S8tYKUSPXOuDB9yYRfK+W8Bgvwde2wurlBAcO8Pw9b1O1EVxj4QU0IrVb2MezgmyxRE8+X6C7WYPWKxBlsgMzMIXRlAU1xoWLwlm9C4L8F+AJdWf+DzSeBA+El4lrdE4A6kx2PsMi1ETLnxAFAGA6/Pm0uFcGmBKA4198L6qFqRcw8SGiSOkBtsD+kGS9NBpcK8G9TYSXaoh69B9A8B0QkC6Rq7bD3lDSNZ83EqXLZfDlFCJ5DT9v0gzDHjOpEB3+MdoHOnQrZnPjnKN8yiSur4NZ+XCsTiNyfAR+bMARHiQdWMAHD7wHbyyHjI+JaoPBgwLsAPifhP3P9LNBJ8zy4hBgR/olFyFyuA6vg/0liOJ/BDgB2aXQ9Cgw8SBlmCjDgM/XRuRmBFL6CH48B7psC9qDdjpeA6qgWA8tSWp6yD4EdpJjM5bAs4dAN8fEm/pekiwQIyPlzKFA1XYEyowMgYWrhGPyPz+FOSziGjR8rEHPXo4A8+6A/bc/zHMcIYqjzAVm8nsMwLesgFv3sLK0D4lkrmYee7UX0QyIsDQZFi5l1pIIJN37DkBcJlyeBZfXw5Op0HGpyEXL4jQLfGDVv4LjzxpMh7kbxcuKQ8e3ShxeUvDRjB4n0LxNNBy/Cq3qI6Dsbci/R+x/TlwhKEO570PW7WJcvDhdfL7Vi8SZOfFK2HgF3JXOnHDxeeSoSj8TbtoF/E0ck2IJ5CSTXIKbkfFmEsx0MywIM494XD7PH/pdws8uP8vhyczM5PLLLyctLY09e/bwwgsvcOzYMYaGhhg1ahQxMTEcPnxYecvIFO7s7GymTp1KSkqKGhPExcWRlJREdnY2xcXFzJo1C4vFwrRp0xgYGKC9vV0pRlJSUpTDrsyyknlakjwt09FlDMBIJ97w8HClxJEdAZnXJO+U5d89Ho+6yAeDQYxGo8qHkoRgOTbRNI3o6GhaWlpUZlJKSooayRUUFGCxWCgsLGTlypU0NDQoT6CBgQGuvPJKioqKiIiI4KeffsJkMpGQkKAcqI8dO4bZbMZoNBIZGYnFYiE8PJz6+npaWlrQ6XRkZ2dfUOAMBoOSV4/keQQCAex2O0ajUY2pmpqaKC8vp66ujubmZhobG9m/fz9Op5OHHnqIrq4uvv32W6699lq1j91uN2VlZcTHx19Q0J1Op1Lt7d+/n66uLmbPnq0UfRIYyNHd5Zdfrjou0h6gvLyctLQ0AKXok8Z+NptNedcYjUa8Xi/9/f1YrdYLfGM0TePgwYP813/9lyKXS9Dl8/mYMWMGU6ZMwWq1kpycrNYtDRmld5F0gJbHq7a2lq+//pqTJ0/S3NyslE3Nzc3Y7XZ1vkrCNQyPHcPDw7HZbCQkJGC321UOWnh4uOL7SBDY0tKCpmmKPC0l5DExMTidTrxeL6dPn6ayspLvv/+ekydP0traSk9PD4DqcEk5/Mgu1Mh0dRlHIf8tuW8j87WkzcAvabm3DlLmgi7pJ7S60/j3DxJ4WwerL4ZJHwNz4e0n2KFtJ/5FASYe1G1lAXu4dglACYuB+1p16OK/hvX386Due9as1yj7owY3wFGiKAGCrwH4IWhhBxZslELuK7AWghtE3dYDXGkR1+6322AuRL0CO8RkihREMTpsgePLgIXLRRvjDhOHtQBrEAW7BDHC4Dk4/qIggLIqdM0PFQo9AkCQBWx/G3pfFFyet6DsdgA9gxZgdAT+WwJAOY+xEB/wFNPQbZgNnEC/IpzXOMonu0QfyJMv6i/X3YOfBbD+CeBR5tDGHN6HN+4AitH1CrAz4zJwvQEurZ+odcDoWJ5GgLxxQDpDigi+CtGxiV+HGKmE0t+5Bpq0NuGpw0eAgTm08bQeTvwWTnwI/9KAG0HbZOfPr0GKNAFqFkRkN4KWIlML3Ige1AmAr+AdenkBiGiDsBZUByemDzgiVEV4xMhzH8ACMQI7xNshNZQw0DtDHfs/huO8AhTzAcP1WEimn4MTEEYHIoJiHmZNh/bg74eTMeSU61OxbgwIxJbJsJ6+PHSSj4NAunhIt59JogAAIABJREFURJaCXr+Q6UDkMxFw+1E2vQwPfgyTp0H8RIEjVwAvoOcAorv1NMPGhA8uEmA0/EGoWxZa/wLE+Qzwu35hsHP7eli9HNGGC7GvVpeyIlzHIXKZDvz9Tbh1KdwkY89kEKgELiMUiwrEpDKcPyH9GBnxXLgQJMEwKPqZe7afHWm9++67Wm5uLlu2bMFms9He3o7ZbGbSpElMmDABi8WCz+ejq6uLQCDA2LFjycjIAKC+vh6Xy8WBAweYOnUqMTExlJSU0NTURHJysnKmlRfr6OhoTp48id/v56effqKgoABN05g6dSput5vs7Gy8Xi/Z2dl0dHSgaRotLS0UFRXhdrtJTk6mr6+P3t5eLBYLwWCQf/3rX0oV5nQ6mTp1KhUVFWRmZiqZb1JSEl1dXWRkZKgOSVtbmxoznD9/XpkbDgwMKLM26VIsgdQPP/ygTN5cLhdZWVlYrVZOnDiBy+UiJydHKcssFotKYff5fHR0dBAXF8e4ceNUhyc2Npbu7m7MZrNySNbr9Zw7d04pemRhkyRjOa6RpnSyWxIdHU1HR4cCn1L+7/F4+PHHH0lOTqa+vp5bb70Vh8PB4cOHmTdvHu+8847aZklQ1uv1JCYmotfrlRpIGj6uWrWK2tpaTp48qQwYvV4vaWlpxMbG0tXVRXR0NImJibhcLubOncu8efOIiYlhzJgxSl1WX1/PyZMnCQsLu6C4JycnKw6PVH91dHSwevVq5VQsCe0ul4sNGzYQHR1NRUWFSh7v6emhqqqK1NRUZs2axf79+1XRl3woOaLS6XSK0Ot2u5kyZQq5ubmMGjVKyeDl9yciIgKPx6OIx4FAgIiICLq6uujp6VHdJq/XS05ODklJSZSXl6uA2/PnzxMWFkZnZ6f6v8PhwGKxMDg4SEtLCzU1NarTKrlP8nNKHpQ8P0eO+kbK/iXokd892b01m80KbNbX1/9yRlp6nabz+dGaIsENHeNFDS3eC89cBc89q4mqdekXwHTYZiH7FvHQ5h7AVMNhxnIJy9Dat3N1msZebTniVvcIkAr3rBYvcAO3XwTcygoeAERhdNyiwdZeSDZBHdyWAJvXIapfzD1YdW/Tvg4+XAe3hnruLwTE53xNexEeeUI819LLKZ2JyWfhsdGi3u3tR1SuN0E3Fp50w4vRAgAN9A5xGWGURkNwCaJYFIHuWdBiEJ2Et4B3IMoOg9r74gk8zUy+4RhfASfI5/c0IzxRIjhGgJn4fN+RrRe1RYQ+lnAD29hBD4Jh9HfADL3TBAH2ydDO6A79+8/AYbD1So9cVEL6m1eE9uWXwBZ46gF4PjSmo4gQoMrEyrPYiaKQQeYCf9GL/cDdCLbvc8BvIHASBmOF+q4qX9TcpxFRBDoCTCDIvcCdz8Gfn4YHfRB5jGGyz2QEwpwu0s7DB+HNWFjbBFdnw971Grc9EPIyYgc+lhClBYDfsI+duIGlTGQmp7kXgePaL9JwloqOyjztFbSKR4bD1mURLxenmC5X4/jnOqb1wftGuLMMpFvftSvgH+0i/60DwX3SE8JG++GreWJXH0eAy2MshPV72PCAwB27gRMGQdSe5B0O5JSE5heA44XiUJIJfPxA6CC44fcPhzo+NaEDegLRP8piCev5R4X4enyWBIuCEPU5w9tI6HyUnRqQMerDLUz5vGb+X3Aj/y3NmrsRoGhT6Lhd9e9HWj/b4UlNTWXr1q1K4i39avr6+ujr62PHjh10dXWp8VF5eTmnTp3C5XKRnJxMcnIya9asoaCggLS0NCorKzEajcoMTtM0YmJiVI6UVD/JZOmGhgZ0Oh319fX4/X6Vmi39UFpaWhSPQZKSJYlUSsKllFgCCbPZrFr5UsYu7fTDwsJUqKdc5NhExjjIGALp4TIwMICmaUycOBGDwUBqairz5s0jLCyMH374AZPJhMFgIDMzk8mTJ5OSksLAwIDK9NI0jerqar744gvsdjsmk4mUlBTlxyIl0ZIPkpGRoQCD2+2mtbUVQIEeGa3Q3Nys7AKqqqpobm6mtrZW8UDk6Cs5OZmWlhYiIyNZv349RUVFLFmyhO7ubtasWXNBJtdIx17ZKZOkYqPRyLvvvovf7ycrS/Rdx4wZw5w5c5g5cybp6emkpqaqLLKIiAhqa2tVxIL0TbLb7crPSPKy0tLS1HGVsvxAIEB7ezsfffSRsjOQ0nWZueZwOIiPjycxMRGr1apGYdJ2QHKAIiMjSUhIUE7LkqvW29tLV1cXnZ2d/8/Yx+PxXEAEl2RxSSqW/BmTyURGRgYZGRkqW87tdtPR0UFRUREJCQlEREQowr3P56O8vJyzZ8/S3d3N3r17OXjwIHV1dSpiZCTQkZEZ8tjLbtPI0ZvshsmOmFxGhpfKEdwvLTx0lg+0pkhuzAZ/PiQExWX5o6vgOa5D0+l451Id2BcCJ2DlRpq+hs0TITsBuKaQSxI0uOdjdEMae7WjkPExZFxBvm4dfLNaEGuWtYUu0EIfNAZRTB4F2NrLeBLEBf4F2LwILlmH6Nxgo30a4BavDAuAf62oZ+KqlAovrwtd6I+LbsS7osdRAmKs8CSQvpy1bpGmHusVRXk7YRwvhGCSeBvJyp3sRjnnZb8oHhtcCdTcDr2zoe1rjjVqLOFKtKbfU8dEBrkfrf07ArQAk4nTh7MWcDAbmM5htvHJMYgiAXgOeq8AroXs0IG4fTt8HLKEfgFxJ74GlgAzCgl59MDb0chkBnGgfPB8NbAZ+CPwxjZY/h4wg3a+J8BDNCP4Ka/7EHU3EVHx54gDEPEKxJVBR74ABU4ELrqMQXIIUk4cjwMnnoZHN0Pkfnh9DqJ2vwkfPQ8Uw7+SYGs4VIgEEP6WLT5m2P0G8oASDjOVG4gq1MMXscAJjgBLOUkEtSxAAK12nuGdUhG3MW8dRPL4sB57TOjHFtqGT0B7SMdbQLjxDyLehNA21sMurgO96Ap+isAlLaH1VM2DKx3wLLALAWSgG+6CNVovT2ltZAEGNwTnQNkTwhU8i+EYuMeA22rg+aOhB295Q5zz3zw8PIqiGQGPJEvoCP94DgGmH4Lr10DU/YhtlB2d/8lcto34m+wAyW5OVuhtGfE3ucgRWGboeSOJzf9m+VkOz6FDh9QFNTw8XMlhc3NzMRqNVFVVkZeXR0FBAcnJyXi9XgYGBmhubsZsNjNq1Ci6uroUX0FGJsii5ff7aWxspL29nZ6eHkaPHq34MA0NDeTk5NDb26skwrGxgml+/vx5MjIyaG1tpaKiQvmUyORtp9OpgEpKSgpVVVUkJibi9XpxuVyYTCbF3wgEAlRXVyvV2eDgoLqDlz484eHhdHd3K3M/v99PR0eHIt7KMZjT6SQvL4+enh5OnTrFhAkTVLClvGv3+/3Y7XZyc3NxOp10dXUxc+ZM5RzsdDqVGV5HRwcDAwPk5OSoLpXdbqegoIDo6Ghl4Ci7E/LzyQBSST6Oi4ujo6NDEWuljN3hcNDW1qY6MOPHj+ell17ioYceUiOY3/3udzz99NPodDpsNptyyh4cHLyACyO5TLW1tXR2dpKYmEhSUhI+nw+Hw0EwGFSdD9mdcDgcF0jnJYiRied+v5+amhqSkpJIT08nKSmJUaNGKX5LZWUltbW1eDweFRvh9XopKCjAZrOxYcOGCyT8koOlaRrjxo1TxV0qriRIkXwhGXsSHx9PTk4O9fX1aJqG1WpVJPrY2FjlGC3HWZJAnZSUhMlkUueO3W4nISEBt9uN0+nE6XQyNDSEyWRS2VfJyckMDg7icrmoqKhQHDopa4dhjtJIZdb/5OjIyAq57XJ8JUGdXGTHRwKhX9pI64dj8LeZAnhEOqDDKqYFSwEwgBnudMBdllJ4ZCG83Csumn+HptcZdjZ7XPiV6JlNFdBugrpCRIG9Cbj0cZ6/fxtPsQcYRyXDNnS0mXCmA2cfgFve4P9yd97hUdbp3v/MTDLpvZNOEgKGEGJAQBDURXApLq4srh4sB8vBXQ+uHrtrX3EV1ra2syorK6IgllVUEBVBMEsTSKSElEnvPZNJZpLJ8/7xe+7fDJ73Pdf1+qe5Li6SKc88bZ77+9z3t8R9CvtWwJzbYN+aq+DweuAmwtdH4Y4CPlHF5ugygFPw0To179l5CTclqO1aiCKq3roBXswASmJ59nnIvE0V4/BhVS8jKtTrB3YDp5ugPJVJwNG/AYXTqFt5GHaDrQvYBt56INXFTsKY36+KOvwFeA7LdANno4WwSuAQWK5exk4+YjalnATenQFutnABV/Lt8dUw9+9qRbfcBjwG3gD4ogP4E9zyPOyGg4YLbgjljib4sxPmDUN1OXjKoaUKChzguQsqTwP5WwngRqK2XGMCrb8QyNNmJro6FNVV8FcLCggmo4rfKeBhSPockuyQfrECBGqroJ5B7kaBxZevV2X79x4YmQFVpkPyuymKVzsdH+dIMMk2QokFIpmjQGg4sKgCvI08ZruSPKbxT+AcVqNgyXm8A9gJhYc34an0+kLSY1BIdyE+P5kM+PtV8PfkB9RrliLZoGTyEafiVM1faG5qvXl+nwLa4hRuuxf4mIcJ5E+MhKyFJ+/H9lgU21ZA3lYYyFHHdN4wbM42M26BOAd0mQG07Pf7PiwahUkBqpuSPwLshvJ1UHgVmUQz4SHVoMv5G74gL3+THSEbh5vHSUCugBUhQMtPrPm6GHyRW+nq95EI2G/3eSt5CsxR7v/l538dad17772G1WrlxIkTGkDMnj1bRyzU1dVx8cUXs2/fPgoLC0lLSyMoKAiv10tLSwvFxcUEBQVplY842coduiR8y2tqa2uJioqir6+PoKAgnZGUmZmJy+XSKhKHw0F8fDygZOTiqtvd3U1ycrK28f/666+ZPHkySUlJWmIv3QMx2xsdHcXhcFBYWKhN3wTESFipx+Ph+++/JzMzk5iYGH13L4VIeEcSChkREYHD4dC5Xx6Ph6SkJIKCgti4cSPnnXcewcHBJCUlabmzOFELZ0XAj+RJxcfHayfjqKgozpw5Q2pqqgaTMsLwV3E1NTXhdDo1ILLb7ezfv18DzqGhIU6dOqVVXDNmzCAoKIiDBw+yZs0aABobG4mPj2f9+vVERERoxZNhGMTExGhA1d/fr1PiJfLCP+EdYPz48TQ2NhISEkJHRwcJCQksXryYrKws7WAtmW1ut5uqqioNqlJSUoiNjaWgoABQnYht27bx4Ycf4nK5tBu3AOuuri59ngHagVuiQ5YuXUpUVBRffKE8UWX/uN1ufdzT0tKw2+10dHToYFc5fwV8JSYmaiWhHANR/Hk8Hrq7u0lJScFms9Hd3U1dXZ22VhBQ0t/fT1tbm+7KCMequ7ub/v5+zR0TwrWMovyz7vyJyAJi/IGNbKO/wkx+5H3S2dyzZ8/PZqQ1GYtxEfDXb8F9Pli9YLdnE4GDAdZhHL2LCcVw5naU4ua11fDlK6pKZB+BihJem6iUU8MBMBoMxnyw7QDv46ii9PA1KLva/dzBAp6hEThp/n4ncBL2fkrBXAsnKgxVWZ9wqbDQQ8B9dwHXcrGlkK/XwT13qZvjZKCyHUgYVUGj4hjwB7j5Lp/U+WghUDYPeJN7LNl8gbqbvxvleyJ360eNS2DJLrTt7nYHvJBNym3QkgD1HZDhQrWm3ge2XIOqTM8A78CGR2BVExtJ4zrTi6iA9ZxgHVYeYazCSUB+MKMVwz4JTuF62Hqnb85ii4YpvWqxjaPQEcA9iapjlQ7su1N99g4HXPoICkx6UOY6fwdKyoGniWATj6EmiULdyMWXr33tTSiEci3wD3jagLu3wT+W61gxXTc3okBwN8qz5lp8KqYefP5IklglYOciRJk+C1vId3jjYE4T7DNeAKbzFOcDCpgeIowx7gS2k2c5jAeouxN2rrOwYJtakHsxBO1RG7O/GGafwDf2ccJoPgR0oAHEoTwF3J7BR+fZiQJsUz1Qb1eH8RzU6SyTH6HRbMQX1emmBpZkq/2N2mf8zjwPklH243eYj+XfD9wODhN9ZzeZJ81xCniV36IA16QdMHY+WNehZGoj5oGSrozkZmSg4zw6VAwYHnwCNX9+MvioPmIz4P8jGGoB//eR1v8KeDZs2GCcOXOGHTt2cO6552K1WnW3wev1agLo6dOn8Xg8nHPOOSxatEiDAQEwcpGWi7I49Y6MjNDb20toaCgnT54kKSmJ8vJynS4dHx+v3ZldLhcJCQkMDw8THh7Ot99+S3Z2NoGBgRw+fJg5c+boYEYpyP/617/IyMjA4/EQHx+v77pjYmK0JNjpdBIdHY3X6yU5OZnGxkYGBwcpKCjQfCOr1UpZWRldXV1cfPHFmuws3QqLxUJKSoo29ZNuhXBKpPtQUVGh7/aLioo4deoUs2bNoqKiQnvpVFRUMH36dI4ePcqkSZN00UpMTKS2tlbbA0i0Rk9PD+3t7Xp0Mzg4SEVFBdnZ2aSmpjI0NERXVxcej0d3lQYGBigrK9PRE8KbEVJwWloaXV1d/Pa3v9WS58jISB5//HHdsRKjPxkBifJNRmCiiBPZc1eXynOR/Kve3l7sdjs333yz7oB5vV6dt9be3s7AwIAOkR0eHiY3N1fnTI2NjfHCCy9QXV1NbGwsgYGB1NXVkZeXR1ZWFt9//70OypR1lO7FpEmTSE5Opquri46ODgBtYCgKKTmHJT7D4/Gc5YszODjIzJkzycnJITIykqCgIE3QljgUGXVJJEh3d7e2OoiIiCA8PJyhoSEsFgvNzc26g9fV1XVWYr1/1piMteTfj4nI8l3zdxcXQC0dIa/Xq7s+ISEhAGd5N33wwQc/G8AziMXIA5pfhJm3quvrDlawj63MJQxvyyDHU1R34E0PhNltjNDP+5ZQ/gQcNfpgaxTFV6q7Rg+wba258HoUmrgKsD1CHo9SyUpeYxN3mK91U8InHGFphQH50+D8w/AV2GLBOxQNjl4FDuYvhiWfmgQj4BMo7oCjW4AVpudJHnAdpDyi6o5QYk6cRiGkx2BfNMzJBv4Mz14Jty+DoI9Ucd5hPAL0UGx5nqOLUVWwGtgHEX1Kzj11HaoKvgPWD8OxMsoox6EiH/LLgd1YuZ+/MsjvDsDcGfAtb2HqqwAPRuWjSsI/N9rcmJtQLZeboGmdko4dU6nyAC3LUGO5qZAZAHVvoMiwR9YokDcVNZf5AoXiPEDILtSCphPA5yzDzTnmp13mgvBQGJ6DQnpfqW1kBEiCp29V+03UcNKxeQ5F3p2KogCJZ4/wh4vw4Y/PsXEfXsKAe0igwNKOHTiaDdQ4UPDt34BwMtlAHY1YyWfsGie89Rm8sAjWTMNoOYKONLcD78PoSrg4FPa2oCp+svp/LMnM9zIBkGXGLHZSyjF8DZRJ5ik50avA/ZgNGm2Q5oV2m8/raD9wOwr0vMlKuOYthYx+7bewd8CyFYxCvwWHo9pc4UBCE+xNVTtqkQPRvz1EOUXAr1tgLExJ+gEC+tQ2jgWCdVA9B0oF5zdl1any8lNvPi7+TaC6OeH4bAbk+ZPm7vrrTwE8zz33nCFETslzkrvYsbEx+vr69J10Z2cnoaGhzJ49m7S0NA1oWlpaSEtLIyQkRDsvC9FVliWjJBlfCdFz0qRJWvkiUm3h/YhBXE9PDy6Xi9mzZ9Pe3k5PTw9xcXHExcVpwqvT6dRFPD4+nnHjxtHR0aHJuKBa+wkJCXR1ddHd3c348eP59ttvmTNnjh5xlJeXU1RURFxcHMeOHSMrKwu3201sbCwhISHU1NScZc0v0RUDAwPae2bHjh0UFRWRmppKUlISra2tNDQ0kJGRwfHjx/nVr35Fe3s7x48fp6ioCJfLRVZWFo2NjTqCQLhG4r2TmJiI0+kkKChIq296e3sZHR3FarVqb5ahoSHNeZLA1mPHjnHw4EGdBC7k1ZiYGMbGxli8eDHR0dE0NjYSExPDX/7yF80JEVAgXBY5tjKGkZFhaGioBn9CeO7r6yMqKkqTkIOCgrR3jngajY2N4XQ6mTdvHpmZmXR3d2O1WmloaKC7u5sPPviAjo4ObdhntVo1If3kyZM6osL/HI+OjqakpATpXEpumcSdSNq6bJ+cGz/+PSIigtzcXH28s7OzycrK0oRzMb4UcCfGmcLZaWho0N0vAaFnzpzRI1OJOxkYGNBARNbBX10l6+Q/zhL5vT/nx380LeBIujoyVpSO0ebNm382gMfCLoO9l/jSF20OVLP/VhSrtYqNPMq1XwMeaLgU0uvA8keDqzfB5vtRle51uHoXbH4FVQWPo4qUB1Uk7gPeA0IcFDOeH7Dxn3h5hi2ogYLJer1rjW/G0Hs+cKMyc0t1wPpsJbPZCfwJbq2AF9cC9+2BV+dhux283WBJBGMlaqSxFupWAFuOwIISVS0CgQ9f4DXLGm5ywbOhyjuO033AHVxveYM3o1C8mBywnA8ZTnUTf3U4GKvwGdlcBdTD1assNAB7u5Sn0R92gP1SG6MRoxgDoxhHA7EUp2LUNfGfmfAiq1Hl5ytgLiz4Dr7YAOWrKJgCJ3qBqK3Ar7mUQHZcY6iKdS1wB1zcAV+LOugKfN4sdmDlYnPFTgL7eYi93I3qVBT2gzcYDtoVBnxb8iOeUcsd61TF9rkUdRglx+w4qpNjx1c4w81P2W++Zqf5/DYSgCKT2D0L+CM8sEi94ACKO/QekHo5cAVWVjPGI7D3TsUe/gdQVg78Cm+/A2s1DBZD2Am1rt/MUHAppwXVOPmx+V46/NcF6vBcZC6uCt9YKx2fiaBwejG3J80Lp23qtbuBG7GRhVd1nFitDsCCWWoHTEeRnX4FHFZgl4/W+MjFS4HsV801aOUYDoo+NnfYr9UHjqWr/S3tmcE4H31HAKVMuOyc/Zzp/6i7OGJGKY/H+D1fja8T1A0M/xTA8+qrrxpyQRcliJj0CZ+mu7tbp1RLFIGoeYSYGxcXp9v8Il/fv38/ubm5OstqeHiYsrIyenp6uPLKKwElVXa5XLqtLynPMTExdHd3a28TwzDIysoiKCiIjz76iPnz5xMVFcX333/PhAkTaGpqIj4+np6eHiZOnKiVSgKCxNtGiLnV1dXk5OTwww8/aIPE+vr6szx/Tp48SWBgIJmZmbjdbk0klhiB4eFhXWD279/PjBkzNJAbGxsjNDRUjxjElyg3N1f7xggvZnBwkEmTJvHdd98xe/Zsenp6NL9E4jiCgoKIj4/H5XIRGBhIS0uLHgU5nU46Ozv1iCUqKkqP5MTrp6qqis7OTqqrqzX5efbs2VpNN3PmTB25MDY2xosvvvg/iqxweiSFW8jMcv5INyw6Opq4uDhaW1ux2WwUFRXpCAWHw0FOTg6tra3ExsZy5MgR3eU755xzsNlstLS0aHL65s2bz/KREYWSSM1FISYRIwEBAaSnp2Oz2bStgAAMr9ervYBEYeV2u7W7t/Ci5MftdpOQkEB4eDgpKSlERUXR3NxMU1MTM2fO1Kq6+vp6cnNziY2N1d1Ql8ul1VmS4VZbW6ul9PX19RogAhqkyD73B1/+z/8YBMn5JftfuD8yPv2xh4/cfGzbtu3nA3gewDjLs/73qAt5t/lPItEz0K32grkWTtAOHyWolr7c0T4ENLoUIfUkBN1p4SrgTbbAkhWw/RLgKq7mBtqArxINVVmeARZdjipDr0FfL9wMbCmHvYVqPZa9Cq+uVuuxSHU35kyDfYaZfP43lNrpz7D8SvhnAIz8APwbWCrAGDgCU0oUYGgAboTlU2DbpxC3GLpKUF2UZesJstxJLNCyFpgNl86DneGw2al41LnA3/JRxe4d9Zp7V1n486sGrN6EceIaviiAhXwBL1xCwRoL1wL3UIKEYKpyfCNqWNUNTCeFu2i5wVDYbymQ0AfTotQYZdA8Fv9tHo/8JkhLVe2WMGDLVlSJe12tkO4D7AeuJYXzucp8RtRe+4A/SpekGBo8kP4tVF8AOUfh3WJfbEUyqpMgURYLURhrIWqSI/QSBQxWAZDCBlpYoXZUU4Ja/2Xj4bMaWLTLfMd/otgs++GaFeqDFsIv5lv4imUYLR9xPAWKzG6INxgCTwA9cPxi9bieXeYoAFEaqSC7FPebzF0moC0c1eGxuVVXZTBFSev9x0WyzYBOHr8ahbefrIOsTKjjYcS5yEopY5SbJ8QHKEQzGwUrFyIC/+vpwGmeOtFe1V3y4KPjiDFyvfl3D76vptPvdxlZgW+sJbgPtPG1fn2P+bjdXHbtTwE8b775piEXTuHQiIldUFAQ5eXlHD9+XCdWBwcHa4mryIbj4uJobm4mIiJC36V/++23eDwe7UlSUFBAUlISY2NjOorg2LFjNDU10drayrhx44iIiCA2Npa0tDTi4+OJjY3F4XBw6tQpSkpKqK+vZ9KkSZw5c4axsTHOPfdc2tradMESoq6Ml6RABwYG0t7ernOvxo8fT2VlpTYolLyp3t5eTWxNTU2loaGBiIgI4uPjqa6upqCgQBOZhUtksVgYGhri5MmTJCQk8Nlnn/GLX/yCgYEBUlJS+OSTT1i2bJkGh3In/u2335KUlERDQwMzZ85kcHBQk7gjIyN11ENFRYX2OAoNDcXlclFTU0N2djYdHR2EhIRox+CwsDAaGhr+x+glJCSEcePGYRgG7777Lk1NTdqJeObMmZogHBkZyYwZM+jt7SUoKIjXX39dy6wNw9DKLOk2CZjdsWMHw8PDWq0WHx+vQaqEVQpHpra2lqCgIK1aGhkZIT09nYGBATo6OoiLi8PtdlNeXk5bWxs1NTUMDQ3pLmBgYKDu9Mjf4qA8PDx8loIqMjKSyy67jJCQEFpbWzly5AiVlZW4XC4tS5exkT/QcTqduosmHS0Zo86ZMwdQxN+kpCQNWmV0FRUVRVxcHBaLhTNnzmC326mqqtJ8HX9jSxkXAhqQABqY+Hd7ZH1kZOcPfOQ94Bt7+avJgLOAkNVq/XkBnssxaMMnc3ZCwURVOvcthhnbLRwgAZ9rjdwbx6Iqrck7EPHhAAAgAElEQVRVyL4FKIIbVsMbaaTQxHuoS/8zvAK0wpePqDvy5zcA92LFRQ6DXAX8iTDGuBK4Gzbk+2rGQiD1frhrrQIkmUDvXUA9t1q28OIyky8kM7J1LiIsoQxEQXGfMobDo1Y7aLFSW72zCa5aBhyH8xxwMMFMXTfK4YVCFei5AU6sU695bRPc9CG8drmCKpsvQdUyIbp4wPpEOGMPOBl5wEJg6CIgmRls4Frg9+crcztyUABlP3DfeqCaT3iVSUAB4OY7uGUWF78KX7+CQhYflgIfcBnr2eqFZTbYwRNqg/pWqDnTH81l3gycvh/VUXgbhuZByFYwo0ZnMJElKMglnYPZQLrEJFwHv3lNnRfvLVWH9h8XK5ATpnYFu/Fxa8GXqB5ufkodUcB1BPISI9wOHesUBlizHjVobAPqoXweFPbBbVHqtFq9B76cp7b5ImDRq1zALdIIYRKqaKfjCzXNc0FLqDq8IviefkBtvvsFeMPm8yFcyiw2Usq1J2A0W6n9rCMqS6wl1AfmUlzKZ0grpU4p7lCpDS58Br64QyU67MZ3D3CCLeanvIaCV62wYQ2s2gWc4npu44/mIusR32hfI0g4yZh7J9B8TTe+pPluzgYwHqAfP54hAVhQ16tz8er7lX4zsd1frDUI7P0pgOedd94xpGsj7ryRkZH09/dTU1PDrl27dIEQnoSMwKToREZGEhMTQ0xMDMnJydpMzuPx0NfXpy/Uc+fO1SDk+PHjNDY2MjIyQnh4OE1NTZSUlOigxsrKSn75y19y8uRJzd/o7e3V4wuPx0NWVpYenQhwCQ0NZXR0lNraWnJycoiOjtZuxzJKEZ6QKGI6OjpITU2loqKCCRMmaP8cGeMJuTkrK4uBgQE8Hg+VlZXMmjWLoaEhmpqaOHz4MNOmTdOjqoyMDC3dnzt3rpZRd3R0UFNTQ3t7O2lpaSQnJ5OQkMAnn3zCzJkzdSbV6OgoZ86c0eOSvr4+PcYQIDM8PIzb7SYjI4P09HQOHz5MaGgodXV1BAYG4na7NZckLi6OhIQEEhISOH36NB988AGgCvd5553H0NAQOTk59Pf3c+GFF9LW1kZ7eztbt27F7XZrMq/wRRITEzXJWryAZs2aRVhYGFarlfr6et1RMwyDzs5OrXCSLo10P+R/UeqNjY1x8OBBamtriYyMpKOjQxsvyuhTzsORkRGtuhOu0vnnn8/AwADDw8Okp6fzww8/6K6bmFkODw8TGhpKUFCQ7i5KF0u6KfK/7MNJkyZpXyoBSVFRUXR2dmrAlJqayuDgIH19fbo7JvL3trY27awt+VjyuYAmmgt4l/0VHBysOTmANn4Urg6gO5eA5jRJt05+RObu9Xp56623fj6AZyIGdlSRKYLA/4CXRxVn51rDou88/e/ghcdxDJ+MuRUYYBV0vAEJlyM9+gD+iQ03bu6Ej9aReblKOE9ZY6GFBGbQwQEKuZRydnAncDdsTYAVaym23M9R4xroeAsSXFhJZGzIqWTbT3TAtATV8ThlruQ/UBXhItQ0boa5wmUOGJ9NhAMGVsOtr6qi8mwCLO+Abash7lXoMkoJsszCvQvOu0RtW90KcxlXwDvXqPv0buBrY5TzLAH8HriuF4i6EqZtgcMvYITfBgfgeAEUVYLlbgPLl2Csg6tXq67Xks1guXqN2l5u5iE+47G7DCLWq7v/GwNg5C/AmkfI5FFigaM0mht4M3TsgQQHVgoZY6va/k2LVPWcL14wdqysYYx5pPAZfwR+zypa2UCcCx4MVbtqwYvmAX4Oqo9BLlHAdAz7l3zj8Y2D7KiC6UGxg06QjZV2LmKQfYCbRageiGnne1sqPH85NH2oEMnTKAD7a3yEmnAgv1TJ/Z2oKIaKVMhPZCcdWuQn4OIgPouZblTauyCAU5kS7FDIU5TzHKp5mA7M3qHO7+oU9b6pHgg8ikIW083zx0/u7R6vOD6WUeXZFPQhvLtcveRe8xT7mFTyaOJuRE4/HzXk85DHLVSSzeM4CEeNOImBsUmKkyNjtFZ8GVnC0ZHHB1EASUylY/GFhUr3yk0UPkZPkd+zHr/HBSoN6r8Nyv7/Ac8333xjSOBhXFycjjjo6+vj4MGD2mDOX67t3xr3l84GBgaSk6NoYsIVkDiG7OxskpKSiIuLo6+vj5CQEOrq6vjmm28oKCjQACQgIIAZM2Zw7NgxCgoKCAwM1KOwkpIS2tvb9Trk5+frrk5YWBhNTU26MyOdj4SEBJ1fFB4eTkREBCMjI9qBV/xpLBYLvb295OXlaZPFrKwsXWyjo6MJCQlhcHAQp9NJRUUFF1xwAVarlZ6eHn744QeGhoYoLi7W0n3DMMjJycFut1NXV8f27dtJTU0lPj6ejo4OvX3d3d1YLBbtKSRhk4cOHWLcuHH09/eTkJBAUFAQDoeDxMREurq6yM7OJiwsjObmZpxOJx0dHeTn52sVkmSb1dXVacO53t5eZs6cSWhoKC+99BLNzc16jDlz5kzGxsaIjo7m3HPPxWaz8d5773HmzJmzRi5xcXFMmDCBnp4eBgYGsNvt5OTkcO6552pjR1BAUjpiISEhxMbG0t/fT3Z2tubedHR0MDg4qKXbYvg4MjLC/v37tQdOa2urDo8V/owcN7fbrcepws0RhVx3dzetra14PB6cTqcGAzIGioqK0vJ4AQcyDrRYLISHh5Ofn69tDpxOpx4XRUdHExUVpc0eMzMz9Y3AwMAAzc3N2pwzPj5eqx7FXfzHPBw5L/3HV/6hpaKOlI6PvFeMFIWA7Q8MwQdS5Xs7OjrKyy+//PMBPGkYXAWs2wQLVhK0S5EoR0aOYLRM4+kU3x29P00CfAqdQdSFWC6rbkpQSOQf+PQ9b8M181i+STV53LsgZb6FIuBLghjlN+bSF8L4FVBTCutnqdFOMhRHWTiK6QXERcCfYUq2QgdOyFwMdWvMRaxzgCMbGmDOPNh3PwQ+rVLUj5ao1ZnjUEV081soAOUElsLyV03S9RIU18SOAk9maNJrW83iZqzlccv95KJS452DFu4JhWccBndkW3jmLkOlz385D26GqhoLvzH31w4epp5HybjFgFdcqLHHIZZbtjAdM7KgHQISghnlE55iAfcwi6sp5QpUAX8XeIZVsOkNWHmLeQRkPlhsrnQrbF0LK9YicaTX86g+jheZ/z4BfncA/msG/GUzfHA1XMHzwHUYGdG8XI92eq5GNZX+hY3deHkZ2EwCeXRQycNQ/ojanE+AxiboMC2OZcY0HfgNBB1RnRNmA/dtAiapoNfCXea6vs9DPKkNkx9DgdT95qJygO3m/jwHH5ddzk0xIvYAv640V7wIHxlGCDF2RXbeG6mWPxWwe8A2bIak7oQ/Xa3Oulx1imibpG3MNz/9fR6niQc5rD7cUQLZpdzK+az3QlANvJsHy11mZ0n2hbR6uvG1ourN9ZKua5G5IcqvkJEIpS5rMI+4xIf5+xUC9BHEKJP99ki4uQcV6DE4/P8PeD7//HND5OGS0N3V1aUvvO3t7bz++uu69S8AB85uw0uuj4CflJQUgoODdRr17Nmz9fJFgmuz2Vi/fj3z5s1jYGBA8ymmT59ObW2tlppPmDCBqqoqEhMTNXeksrKSuXPn6u5NYGAgXV1dWv4sY5i4OBVDK3ykwcFBPaqQkFRQAC0iIkJHTpSXlzN58mRd4KTLI9wmkcBLsWxqatIBoNXV1ZSUlOiivGnTJsrKypg6dSrV1dXMnz+f9PR02traGD9+PCMjIwQHBxMREaGdnwWESqCnYRjs3LmTiRMnMjY2pl2lKyoqsFgsZGRkYLfbdTxDb2+v3h+yflKQ29vbSU1NJTMzk56eHl566SXdccnPzycsLIzh4WEuvfRSDMPgiSee0M9HRkaSm5tLbm6uTqT3er1ceOGFREVFaafo3NxcQkND+frrr8nMzNQdMpHxu91u2tvbcblc2nYgIiKClpYWOjo6dKdwaGiIhoYGxsbGKCsrIzg4mLi4OK18ku6LdDREUi+j1K6uLnp6evB4PPrf6OioNuszDEODAUCTfO12u5aii0t2bGwsdrtd85F6e3v1+Mrlcml1WUZGBk6nkwMHDmCxWHA4HLS3tzM4OEh4ePhZ3xPp1Enkg38QqHByJMBVvmeidpNujRhv+kvaf0zC9o/p8Hq9OByOnw/geRSDh10UWEJ1aOLXu1AFqxtG/tvCgVDFOa7ye58UzW5g7Edtc7lRHmAVkEMEDzDwmaHIENVqQSl9KgTznRoLV/EFqvL9BrgbXpgHa3bBo5fAw+uh4k7Id8GRUCgxwxhDpsGUw2qcI5kBdpgTAPt2oWcUxZeoGvu3QhS511ReXfqIKhYn7scnXTHX7XYHPHsn3L4engsHYxlcvwneDlDdL4Cb7oeUtYrIfC/QYqyHBcpZ9/EVFh48YpA3DSrfAONTC9jhN+/AJi8E2xKgvB0K1X4/sRjYfgRuK4Hnze3+LarzgQe1pku5nmjeZBlQRAqP0jJkEBASTCFujvIF3HaJ2r6bwBoSzmwGlULMuxJse1AtllPADzxOGA/yKVUsZr+5u65DTZ9u88IqG2zmTq5mPW/fAx885RvHHAM+5gnzDKg2D8BCAgNXMTIJWAjL16tnjo6iEOEfUKKsPwDbIe5T6IpCOffdaG7my8ATpai5llgE7uYyjjAVWGA+Ip6LMebfrfiAuBh6Z5ivCVO7g6Q6vxfKi80GiHu8UmgJb8fugVY7pB+FPxWbqrQ6sGfaGOEmFOy51fz/bnNN3jXfnYOEdGzkI67dDF9cjZLWO2Hs12DtUZ89okStyrVaiMsiSz+Ob84lLSB/qZagOWkJeX70GjhbyjUd35fTDtz6E0Zar7/+uiG+O9Jar6qqwuFwaGWN3W5n48aNDAwM6CIhElq5qIoaShyLpaiEhYUxbtw4EhISOHz4MGlpaUyePFlzOI4cOUJ/fz/5+fl0d3drno04FXu9XiorK5kwYQJhYWFaKVReXk5xcbEOaYyIiNCjt9TUVO3cLMnVFotFjy4Azbvo7++npaWFlJQUQkND6e/vJykpSSemCwlbiij4IgYEpIgjdGdnJ1OmTNGEZZvNxqFDhzh58iTTp0/XvjTCOUlPT9cyd+Fb7N27l5ycHJ29JJ0BgG+++Ya8vDzq6+uxWq2cf/75HD16lJkzZ2pn7NjYWOrq6jh9+rTO8JI8sJGRES3Rl9iM9PR0AJ599ln9/G9/+1ucTidut5t58+Zht9t56KGHdGEOCwtjxowZ5OTkaH5RVlYW0dHRDA8Pa26RABJA2xPI6FN4WI2NjTqDTXgxbW1tOBwOJk2aRGBgIEePHqWyspLGxkb6+vq0k7YcT5vNpv11JJ2+traWoaEhfvjhBwYHB7Wpnz9vxn8sJuOjiRMnEhsby/DwMJWVlaSnp5Oenk5CQoJ2jxYyfUBAAGFhYYSHhxMaGqqjVJqbm3X0SVtbG6dPn9YqOulmDQ4OnmUuKGBEulP+Pjv+YEfGdjL+8wc58ruAIFmWdN3EDNIcOf58AM8DGBevVcWuG7h9FLClUUUTuQyqgmzczx08yftAHWaLREOecHxOLOrqm4kDJ9BFAgrIHIK+Ri6NsrCDVOBGmPgIKRWQbFj4I3DFJgNWlkN5IRQ2oeDVP4A/EsF4BjYZqgisU0omCq9BGc/8B3AFfLZIbVArXH8DvOlCu9PmTVRr8eYscxX/YK7uU6jbdtNDZXm5Gm/d+iq8eBoyJ0JjMHiHKuCafC7epAYWO4Ftj4Dtz1AyrKIHjAHFyeGuV2A2WK4BY6AU+DeM8xz8+0F4UzoghdHAe9B0idqN2VthyQqCtluUUd+rJuen5HJm8BEHPjNg0ZUcYytT9xowNw24CDa8xWWrLHzsNcDmgiGT0BK1hwguZCGwjbmoo/sc8N8wNAtCNsHQSgj5DLyLwJbIRjq42gX7zEUssAObYf5y+LIOuBWe/kTV5W4UW2UMGyMVo5DfxHJLKn80z6l/N3d9SxRwnqneex6FCR6D1y6Bmxajuhe/QynwHNlqFaVN8cZicHxqqpw+4Vk+07mXh/D5/WSg8KqKp1CffS1q9HgRaoKmCcoOfOQbkTAJAJIOCwqIdJuxIPtRHb1JwMdkE4fD7J7EoxDEdPOE2s313EaRedYKNz4HBYtSXBDwJQotChNZPt9/+iSBodPND33XfO10fO0cf/byIL58LP9lCfARgtAVnJ2xdf1PADxHjhwxZAQRGhrKzp07qa+v58SJE0yYMIELLrhAj7q+/fZbjh8/ru8W/a34pQ0vgMdqtdLX16dl1tHR0Xo0MzAwoDsVhmGwceNGrrzySkZHR3VUQEhIiDaSE07IuHHjNF+np6eHyMhIEhMTOXjwINOmTSMyMpLKykpycnIICwujrKxMd3lycnK0H4sEi4aFhdHV1aWLZnh4OHa7XWdndXZ2aik+oIM+ZeQUGRmpid4ej4cNGzawYMECrRJzOBw6zHPGjBnat8hqtTJ9+nT93rCwMB3SmpGRoRVqsbGxGvhIUe3q6tImj/Hx8VoO3dzcTHBwMNnZ2ezZs4fY2FidbdXc3Kw7XZL/BaqDIGGrycnJtLe3s2fPHsrKyvjNb35Dd3c36enpFBUVAXDvvfdSWFioR0gJCQlkZmaSlZWlw1yFeyK8HlGcDQ8P60Rw2V81NTXambmlpYXJkydTWVmpw2ITExOpq6vD6XRSX1/PsWPH9DkmWVpZWVkkJyeza9cubdwnXcS2trazLBHkXBLDRPlepKSkkJ2drX2VWlpa9OjL32U7NTVVn8dZWVl4vV59PkoafF1dHV1dXdTW1qprgckx6+zs1CaYct7LuSg/wrmRbQgKCtLgRjg6/l0gGX/K3/7mhP4y99DQ0LPcl392gOcjjKcuV9fGT4BDhoXOSlQzwAOWjXOZY9nDvkbIS7WgwqpXcraWRUCPiF9bsbLH9KiZjOSL38FenuEwqiRMQpgKRtd6LHHfIcnYSj/0DSor4SEuYy8XAbc/acB9a1H37DvVBmxYCasSgc/JtJRQ1wtEmcTlXlSBA26+HP7Wi5pHtAKPwa3j4cVsFIp5Ce7pU5gqA3gjWEVQDCwG21dqzJfsVHXjJLAnGLw3q82YcwvsM87H2FyK5eooiO5V8utksEaF4/16EMvFq3mcV3XEgZvD6s3XhMJbayHtfgIagxmlDa6JUp2rDLgjxMIzSwzYfgPvs4Er6AV+CUyHrc8TtMKCm0/RwZRPRsF9U4B/ohDEMS5gL+nAVoIYZSdsmqfAxi9Q7Ysc4BmIC7HQ+TEcugymdwEPwdiTEBQZxMiDbvg13FesGnWKrzIV1q8j4i7Fdy9CSaLD8GBngP3E8UtgIB+ww63l8GIqxDWpo79vLWo+txt4o5wUSyEtRgU48hWq+RNQth5YSBxTaDUJxcfzoMAFm0PVW/9eqR4zk9tkT5D0N3Olcs2D1oMP4ITha1ABxMLYNLB+gObnjxQon549NrXM/8SHN14ErmIZPpfAxwDII5HHgN9uw0xdRaEfmeyKXOrHgOfH2VexP/pbQEwsMp30i1nnbDAj2nSP38646Eef8//I0vpfAU9VVZUhip329nY+//xzWlpaqKiooLCwkOHhYVauXKkVWadOnWLfvn3a8Ex+pND5X9DF5E14BpIO3t7ezqRJk3A4HEyZMoWysjIyMjI0z6Szs5OpU6dSU1OjC5t0JSIjI2lvbycxMVFzfiQ/qri4WBObJ0yYoItXVFQUUVFROsE6NDRU+/YMDQ1pqbd4qNTV1ZGVlUVnZycVFRUUFxczODioRxZhYWG6C9Xf3695NlJQDMOgsbGRiIgIKisrtS/Lrl27yM3NJTIyUpOoZQwjTtMy1snMzOSrr75i79693HvvvTr5/eTJk3rUAqpjIJ5DkmNVVlbGmTNnAHSXKzk5Wedrtba2UlNTw0UXXaTjEhwOh1Zhbd26VW9HZGQkaWlpTJ06lZGREV566SUuu+wyEhMTGRsbIz4+XpsPitJNRmJC+u7o6MDtdtPf36/9baTrVFdXR19fHykpKaSnp9Pa2kp8fLzuFg4PD+vx5oYNG0hNTdXdHAEbbreb+vp6HWkiPCAB5WLuJ6MgOR7Tp0/XcSGHDx/WoMF/3BQaGqpjVsQDSEJb5Rh4vV5SU1P1GLitrU2fe06nk+bmZs0hknGrAGcBMLIc4CxfIZvNpj9LjBPlhkN4PhIeKtw2WbZ0GiUfTUAS8LMCPE9bMKajKAOHDAVojgHvC98gCzgBltkGQQ74m2GhGniMNeYShMYq1rD+SYa7CWQ3I8Si7nPVMKKYUo7yFgVcw4mtBq0rLPwKOLDBgFWjwD/AsQqyz+dZSiVii3DgxFYDVkyBI2VQshh4kQjG83vgz7cYajxSsgm2rlTF7D4HlGcrjNUNvNEEm1IhGQouQY2TZoOZZcCDR+DxVZC5QRXlHb1wXjQczIZ7HKZ3DWrEd2KFuZlFwJ2PoMBaEqr4qaCFC5jGv7Dh+dgL78PYX+H8SDjAaRjKh5AO4kiki0+hYhE8B3GvWJgOfL4NeAgsJ9W8I5BgfoGXHV8acAdElFkYYDV5lleo3ILa3jA00Vlcgs8BvuILOHKJuc/uRm0J8OoWtQ0moXjj8xaurYP9mTC7Dv7TzPp6mTC8RwcZKQC7zQDbKNwVAO+At6mfPUQyj35GCcbOPiCHl8nkZeDEWhR95DzzdNmPQpbpwJpbzP11DFvIJXiHSiFtFpY+5X1U9wjwcBPwEMYzG/i3O1T9LjK34MtKxcFxmJLyVlStn+NSZGOAoEbzMz3mPopBE4MaMiH9TXxSMGCwQMnUvcEQOKBO6f3FCvCkozo9vhANmSmZJ8KXq2H+I8DrXE0TfzCfKXBBwBF0qKkeVwkwwW9R0r0RpUA3PmduAT12v38yqhOJVzg+YJWOOr9/nKN12U8APGVlZYZcTN98800mT57M9u3bycjIwOVycejQIQICArjuuuuYPHmyDuN8++239R29dHlkJAbo3CBAK5tEBj44OEhOTo6+c+3p6SElJUWrXdLT03VHoru7m6+++oqLLrpIZ1W1tbWxZMkSnE4FMfv7+2lubiYoKIjh4WGKioq0WWBDQ4MeeSQlJfHFF19wwQUXUF5ezrRp0/B4PDQ3NwMwceJEenp6MAyDqKgoAgIC+P7778nJydEcJ4lVEKNCp9NJfHw8ycnJfPfdd6Snp3P69GlKSkpwu910dnayd+9exsbGGBgYYMmSJbr4S2ctIyNDc2xEKl1WVkZFRQUhISEsWbKEmJgY6urqzvIoamhoIDc3VwddhoSEaLK4AEyJ+vj888+x2Wy4XC491hA+yezZs8nJycHpdNLS0sKECRMYGRnh008/paamhgULFhATE6P5QC0tLWRnZ2ufIQEKAiiEtNvf3099fb32nhHPHKfTSXJyMi0tLZoPlZKSQkBAAOPGjQNUF6Kmpgar1UpKSgqVlZXs3r1bA1YZkUl+lQADfxM+p9N5FqAQbpl0qc6cOUNbW5smRktHR1SIycnJRERE6E5YfHy8jhcJDAzE5XJpC4D+/n7CwsKoq6sjJyeHnp4e2tradKfLfxQl3zfpkHZ2dupUdn8VooA1GVf5Z2n5j7P8/XsE/Mj4Ss5b8IWNGobxswI8+y0Yp4CbjFI8nvOpsqsu+hLUNTKpDoVhngbLeoNLJ8JSw0I38CAPo8oPqKuwf7Cq6Ls+wUepLAKm8hIv8DpwlCigiKvZy2ZWoq7MTnjhTljjQJE+nsSovBD3eAi2vQJcxT6i+RVCzHQCH3AvV/JnHjbX4zqgFSbmw+nFQDJMfANbHXiHNsGUlVB2OddbPuTNBFQwkh2K5/lGMcv71NrcPgpkQmaTogNfEQWX9sGOBGAbMNcBl2dz6Ueww1D+QE+VWLjnLkPd2RdeTgEfSbA556HYH5V8AR2XQMIl4N0Ftgq4Ml+1kFbcBhxixFXK0VAVf7HEYnDPOuDOJliQSt4XFl4EFtILH0XBsvvVdpILjkWQ/RlMWwSH53EZe9mOsu0dYzEpbMUO1PEEy3mAQ0Add8Jt69RG2tYy4noAIwACXwTLHakE0spIxygzEiwc4Dtesswi3DxiOfzN3LLdCDP4EMs5Dty0BtVd2IkqxKfUaZL3EVQaTeZ5sRu4Fu4KZfl6hTv+FA7GatTI6xSwaD3F3MUzKEAuTZvbvArQDGaeTdoNB8K68IGLD/DJCReiUOAxfGRmUB+coZYV4IUPTQPCp80zWyJIdvAF8DCY+1Qt8Dl+QRNhwMfM53q+xKMWp8VocltQBCQdRSv0NaiJxecpJJp1AUP+HSD8fvfv2oCv4yM/4rYY7rcS8NM6PD/88IMxODjIP//5T51YXVFRgdVq5auvvtJxD3Jxfeihh3Sh3LJli+78CEnS/y5ZSJWAJqeKw6/b7WbatGns27eP6dOnc+TIESIjI/X4STg00dHRtLa2Ul1dTXZ2NkFBQZw+fVqrhURJk5mZycjICKdPnyYgIIDo6GhNjG5qaiI3N1ePM6qrqzVvJiEhAbvdTnNzM8nJyYyOjtLZ2UlWVhbBwcEcO3aMpKQkPbYQWXN/fz/JyclatZWVlUV7ezuGYbBp0yYuvPBCMjIy+P7772lqaqKhoYFzzz2XuLg4Tp06RWpqqvb1yc3Npba2lkmTJtHS0nJWxAaglWVSyFpbWwkICNBcE1HPCXiQoEqXy4XX66W2tpaioiISEhIYHR0lLCyMvr4+9u7dq1O0BUyNHz+e2bNnaz6UJLXLWDI2NlZ7+8h5Jd0DATty/F0uF62trQwNDdHb24vb7SY6Olq/VrodOTk5VFVVkZubS0dHB+PGjdNZWXa7nZ6eHtxuN3v27MHpdOo4jdLSUiwWC11dXYSHh9Pc3KxjIoSwLMf4ggsuwGazUVdXR2lpKXB27lRmZibjx48HfCNPUQCOjo7qrCw55i6Xi5CQEEJDQzU/Z3h4mN7eXh3eKljMWcoAACAASURBVFwv2UcCxATAyI+oxyTrS7LRBgcHdQCpAFX/98m+9ic6y2hZvn/+gEcet1qtPyvS8gcWjCs+BWOGBXc0rLApuLBYeA9N8E2eup8Nuw5+tRE+iTC4asBCMqZSiOn4WJFytZV4ZzuqYj2H6jfYgRsp5kmO0s6tJPJin4FRZsFywTrgOrghgUvfsPBpP9gi1wBhXMqTnAc8xmEUJBPHw6UolsXfgQzuYDxVwMcdBiSMB/5IHDfQ9aVB3CXQZaxHVZSDwJuwJJuUT6HFuAG4ERJnwQm4OFHth+tGUaKn6fDSBvh9IT5OxPsosDT/Sh60bOHx1cAraxn2PqDA2S2r4ZW1xPEAnR+D5bIoAhjG5XFjt8+HF3bx1BoL9zxgwBPnw8Tv4PRW2LBCpadPXKGaMauOwA0lasx1CFhxg1qhF1arRtIBc7feCrxSDuTAC6Gw5hpuZRMv8jBwHLwfqiJfcgOBbGQyXm5E1f4LW8CSks2lONjBOqAIyi8hqFDMI78jyDKLpeYev5YWfLo8sdaWLA6llxrm11yOlR2XoIDLdBRieA4FBs2uim0OeP0Cu+ZshV2McRdWXjJJ47zVwQUkAj6z7CtQEG9Jl3nKmSzl0RJwh0LY31DIaCM+E5pT+Joz0pz0AxKDxcrOKMNcVfHJ+YqV5gp+ZW7jRmawlQPMN00Hb0C5S9+gHY/l2yCUG/kdc7UWorCg0Hpa8X2TZu9AEaUkK6Kes/k6QhD6MfCBszk8Eu3ur1CHnwZ4ysvLjZaWFu2Fsnv3bqxWK+3t7bS0tNDe3k5kZCTR0dEsXLhQj0bsdjsnTpygtLSUsLAwLUsXqbD8E7KotN47OzsBNHdF8qFCQkI4ePAgqampREVFERgYyPvvv68jJMTfJTY2FqfTyYkTJ5g8ebIGNsJTsdvttLS0EBgYSF5enr7LbmpqYt68eTQ2NuJ0Omlvb2fatGm0tbXpMYVwJJxOJxMmTCAwMJDOzk6qqqqYPHmyHtmJx01YWBh79uxh2rRpDA0NaTnz3r17mTJlChEREZSXl5OYmKh9YcaNG0d9fT2ZmZkkJCToZUve0alTp3A6ncTFxTF+/Hh27dpFQUEBFouF2NhYtm/fjsfjYdq0aXp/yHoJQVju/p1OJyEhIRp0+pOKPR4PBQUFugB++umnVFRUMHHiRHJzcxkZGWHGjBnExMTogEwxmZQsrcjISA0YxHVagPHIyAg9PT2awF5bW0tERIRWdfX09JCcnExnZye5ubn09fURGBhIRkYGIyMjuFwuQHFgKioqSE5OprW1lcOHD2sQJbYCQoaOiIigqalJc3QWLFigO1dbt27V3Q+v10tOTg45OTnYbDad+dXe3q6J9tJxEW5XYGAgfX19eL1eEhMTSU5OJiYmhoaGBqKioujv79fARz5fOjr+3wf/+AdQIES+M/7qLEB7VAFaPCDxFLW1tTp01v+YC/gRQrZ4bMmy5XNqa2t/NoBnsgXjxBogFo49bKHohHr8lwWKy1u0A3WL6gT+HSIPwkCFAflXEsdWHkN5u6irqhAmwjhbvO5BgZ3XUWVEqs/veYfFPIfPBO/P5YYqSkvh/RALT6Pq/G7gBYJYjZsXSeApOriHKPD2gu0SPuFLYoA5lLCPI8yhBKXruYJ7mQbAn/kONs2ChRCXYKGryYDUDbBhFayaAueXqXrWDbZcWDMMz/YCUePJtNRQV4iuZOeVqvV91ngBnlxD3P3QZSyGTZ+ye6WFi1gGj37I8ocVEbkINRL5lhFuJZAX+Q6WzCJouwX3lQZseURtNBnAS7zPo1xBKk6aCD9iEFRiYbbF4JRh4QCQQQmBHGNk06g6NqvXowXbD9yvCtx9a+Gz+xUQuBHF796+C3idX7CV/wZyyWYfDp5GjTEBAkOfN5c1m2LLSo62Q0SiOrLfMUYwz5vHuAfVwfsDvjhzaVeEc4jL+MR85MH7VcxHfTgYs/AZTQOPT4EHZ6l9e/URhYUk7PMQsG0FCgXceRs7eYGH8Am7bhajQLsK2LS24TNhzEUBLaGWgS8gzA4kw/7l6tdiF3SFqs99Fh9GqEZNO0GBE1DNqgGigN/xFE9yjzbmjAWSCOJLTbURSGj3+11WZQwbXoIZIwAIx0ovgQySbO6eBnNPdmLjP/Dy16NIfL1PcTXit00ijwQf2pJ8DczXSkjpxT8B8JSWlhr79+/XBnjiuVNaWordbtdp3d3d3TQ3N3Pq1CkCAwNZunSp5nG8/fbbhISEEBISol10/dvv/negkrIeHBysU8Hb2to455xztERcHu/p6cFms3HgwAFtcOf1esnOzmbKlCl4PB4aGho0YfTw4cNYrVZycnI4deoUMTExzJo1i4GBAdra2ggNDWXChAmcPHmStLQ0YmJidHEpLS1l/vz5jI2NERERoV2UnU4nNTU1FBYW4nK5tBeMxCtIEGpiYiI//PADM2fO5MyZM9oH6NSpUzQ2NnL06FESEhJYunQpIyMj2Gw2xo8fT3l5OVOnTmVoaIiKigpSU1MJDQ3FarVy5swZWlpaWLBggZbSv/feexQXF+NyuRg3bpwOZg0NDaW8vBy32629hDo7OwkJCSE9PZ2QkJCzpMugiqTkkE2ZMoWQkBDGxsY4cuQIzc3NzJ07l9bWVgoLC7XqShyHhR8jpOfR0VENUsLCVJu0p6eH5uZmbDabltyLA7YApLGxMRITEwkJCcHpdOpuojgnj46OamuAEydO4HQ6qaur04aEQsoWYG2xWLjjjjuwWq16nNjc3ExnZyf5+fmMGzdO+9hILpp0c4QMLz424oEzMDBAcnKyzv1yOp0kJSXpzp+sY11dnQYyAjJFZSUdHv/vogAf6fjI98a/CySjKZvNpuNGgLM4Oa2trTgcDqqqqrTDslgdyLkkx1t4QD8nwGOpwCB/FxAOX87CthQeGLLwO5T1fdArYLn1DS7lBuz4ZMHpwJYQA+9QGtfTxJvMQpUhU14yFODjG9gq8F2h78AHem4EcvmEK1lKNurK/U8oD1UmK/dNoYByPkcVngsPAD2w/1LFoekGzmDjabwkm0stAm7sguo4yPBAnh3qWMdO7lKjpCcNiu+zsBBVqk/QDthZTjTbHAZkVwA7ibCs4QpUsXMb18CUt1TxOA6XVsCOKNQt+pa7oHwdHIeHVlp4jPuAaq5mK5vLDZ4qtPAnoP/3asdZnmpkOWlsYxXc8gbWV8IZu82pitiHpejS6JgF2a/yErfwe1abj/+ah7iQx5gFJMFnH6pQyr5suABuLbPwIvPhs11YF4VzN4MkAbfzBnCR8i1qhbgOJQkv7rWQg4IqJ7gPlqzFuj2c9xjkCpbBbR9CEVhug2+dUMIYwTou9DgKFkjeeCzD3IYdJ1ZGaCOOd8xXbQyHK5xqC5JQIGbfG+bJ9HAfyy1RijcdAHeMKkBwHgp4LAUeXAZ86AL+iwD+zjzcMvwkB/hdHb5xzfVq9bI8Kq5r+u3mSfE+vnnSQmUKKRT5h9ARXBqyH0eNzG5CdWC2AwcoJI9ykvGJvD7mYWA/t/IlreY55SWIENz/w/pPuj4ezm7KeBADQVE9Sky6Hck8z6Mc/F7vIIi3cPPbzWgLCd1CEl5QDmePs8AnqPwpgOepp54yUlJSOHjwIGNjY2RlZZGbm0tiYiJut5uWlhYqKyupqakB1IV2ypQpxMfHa+XQ0NAQH3zwgfaoERdau92uR1ziLCtGfS0tLVqOnJyczJkzZ5g6dSoVFRWkpaURFhbG4OAgO3fuZHBwkPz8fH0xdzqdxMTE4HA4tGIqICBAK7Ekqyo6Opri4mLNS5EEbFFnpaen09XVxaRJk9i3bx+ZmZmaw3TdddcRHBxMY2MjHo+HtLQ0HZ8hBb2iooJx48bp3CQxzDMMg9LSUvLy8rBarXz22We0trYSGRlJUVEReXl5pKSk6CiFoaEh4uPj+f7777W/TXx8PImJiXr77HY71dXVREdH88QTT7Bu3TpcLhdVVVU6mqKuro6enh7S0tJ0GOzo6Kjm80RGRtLd3a3JxtJtEE+iiIgImpub9WhzaGhIRyCIKZ4U3+HhYd29EZ6MODsLqBocHNTBlUNDQwQGBmpjQPGfERNBAQbCeQEFFiIjIzVgFrWVnENOp5P+/n5iYmJ46623ePDBB4mMjKSqqoq33nqLrq4u8vLySE5O1t26/8Pde8a3VZ/9/29JluUhW16yrXhhh8RxdnASGgIBwggNECihodAwGsbNuqFwl1Joy4awyujNSBkplBRKftBSRkpYIUCSZi8SO7HjvWVblm1Zsmz5/B98z/U9Mvf/SXmIXy9ewbJ0ts71Odf1GW1tbXqMl5CQQHp6uu4ayjbLyFY6VcKNkeMkHRPhWyUnJ5ORkUFPT48+BvIj3KB4ro38xI+4ZASlv7Q227jujHRgRUYPaN8qGc9KZ6epqYldu3YRCAT0dzA+tsIcc/5gAM8F2Iwq1OTkIRSvAy6Fs0vhk3Xcw+VEUYW/AlXaXgd63jPgOrN4GmWcQT2fU4li/5yv3t2aYrXZvUEszsN/kcBfGWUCAnoe5BJ+z5coxsqfYc0MXr5eAZMsIPUdwK3AzvGokivAa5YZIjl8NbhuwWo25QP74fHFqmB9TSWqEvyaSVyOGziIi1FOQUGqiVD/KVeV2nhttcHrd8OVyi0BR7Gp2toF2XNVHXmzDij1wxovtjvMUNFZwKrdPM1cbqMO2MgmbtCCmmu5F3VQrjT34nHgn7hspQwba+G8VfBhIaprstD8+0JY/Suev8vGje8AV8GHg3A+dzGJ1dTEDJVNUf0I8ILi27Ad2M8yruZ9vjQPRpFyq6YPchMo8asxyvAMc+PqtqltWne32umVG1hsW8qlKIKw5DsNAqNmBnQsDRwDiuA+lgC5Eauw1xRgkW+z0BJp2xEwSrHaKCpKzFJNTcTi1cgYRyr9MeDCDTzGufx6O6rdUozq6IzA8Ci4EszLUEBQPqrTs19tx7FzFND5AFX/70EBjmkE9VBuEGjDQQ4xBq1NZyqwBweTUQ9lP0MBOMkmk8s9fnwlmz6GA4MExkjAgaJcyO+AqWpMwsmg2fkpMw+GzLUk87yWafg1hklEgbNLgf99DitQNX6cJfQ6AUPfZ6S1bt06Q7oWNpuNY8eOUVNTQ0VFBbm5uUyYMIHh4WE6OzvZtWsXBQUF5OfnEwwGKSkpIRKJsHXrVvx+P06nU5v3JSYm6q5A/E0e0PyK3t5e0tPTOe6447QvSW5urgYHdrudPXv2cODAAQAdryDjJ0milhHE3LlzmTJlCq+//rpW2UgopBgLZmRkMGXKFNra2ujq6mLevHkEg0HNUXE4HOTl5RGLxZgwYYJ+UhcFUl9f37ikePHyEQKqqIdkPFJcXMyOHTvw+/0kJSVRXl7OyMgIxcXFmoe0bds2TjzxRA4ePMiUKVNoamriwIEDXHjhhWRkZHD48GG6urp0kGpRUZEmeOfm5pKWlobT6dT8IJ/Px+DgoDbhkwIsxc8wDNra2sa570q3Jt7FWHxmpFsnxV2AJ6CzpgSUiIpN1g3o8U58zEG8F45wlQQACIgaGxsjHA6PU7P5/X4CgQAej0dzgNxuNwMDA5SVlbF9+3aam5upqKggMTGR5uZmmpubcbvdWnUlMvNgMKi7l9IRyc7OJhKJ0NPTM87TJj7CQYBFPF9NujciyY9XXMX/K///3dgH+Y4K8JHvjHjyCKCJV3d992EiPgdOticajXL06FGOHDky7vtXW1v7gwE8tvUYrLgEOx/xs7h2ehRzVHXwVZhxFu/yGS8DH7MIDm6GGevh7BXwyTrsXM9Iv+JbudJdjPJzLBeUTGhNsO76BX5UoX8eO7sZ41Tg12RzGj2ciY7+Dt4HvbCj1Ma8L1DVYx+WMKYTy7l3Ieom/wpq/vU6ptscqhJVwKhHqXaud6Dde2uikJi4ggdZz+95FssS+Jfw5AIuuwPerDbXdRmqiFTAtPVw6EXg+kdYbLubL1YCb3wK552livMS2LjSxu3AoScNbv6VGmvJeEf5GXXB/Wb46oGZMPcA7FoHhSthL3zjtXHyJQYcb+Z0cS7Qi9H4GVUlKjVDmhfLWw01rtoHtGyAz5bCmZ+imLoTsQzxzHHj+hQrRTK+bSfqpXysDIMAlolzLdhiSj2F+dLZ5nU0FdVhk9iRd80zmYn2c+R4LA1fAGhIgJFM8PmhK0mdH2cIRvKwRH955jYdb57ne+uxyC3H1LVi9vZK+IyG41GV/y34Sy1cYXbWWAhblqmzazouUNcP69PVZSNjJzkk+ebhDJvdmkSs7KokYkRwMEIW2fjpwYvPDAUdoAAXrYx9J+dqlCQSiDCKkpPZUR39MVLMd6k6k0DEjGLxYl3gghiFxSwoUnFinewgnRizzcM1iMKBdwL3v28eop1Y4MfN9wM87733nmGz2WhoaMDtdtPQ0MCBAwd0p2LGjBkUFxczceJEfRNvaGjQqqLq6mpisRj79u3D6XTqLCyPx6M5HtKql2IrT9YtLS34/X5ycnLIycnRZoPimpyQkEBXVxcHDhzg22+/1V0A6RpMnz5dy4oPHjyIzWbjuuuu45///Kder/Ap8vPz9dO6FFYxJHS73RQUFJCenq55GBdccIEGVI2Njfh8Pp01JkGq3377LXl5efj9fi3vrqurIyMjg5qaGp0lNTo6yrPPPsuJJ56ojQDnzJmjAzyPHTtGQUGBLmiNjY10dHSwePFi6uvrtfP1pEmTtJuyKNT8fj8+n4/t27dr/su+ffsoLS0lGo3icrk04MvNzSUlJYXq6moNYMQgEVQhlvGOKMjiVXhCTo8npEtwqUiiDcPQwFSUetKJCAQCmrQuPjPSeZK8LunEBAIB+vr6MAxDE4Ql1FM8ngYGBnRXKBQKkZubq8ebAmICgQCtra1kZ2eTmZmpf5cssO7ubp17JQG6xx13HIBOWxcVF1hKJ7BIwwI85O8yqorvasZHWsSrq+KPpSznu6osWV7890icluU7IQBH3i/LldwzsZHo7u5mz549fPPNNz8cwHMQ47EZNkIoH75G1G31XdSNfypwPgXAUfMTH6L6PUpSksDXjLw/DFug+TH12Z8CNZyJ6mJUILlOVi50ItQXQOm5qGJ1KSpg6V7UM3MH6q58E9PI4Ns3UUVPqEDHmxs5C0ZuBufJqDv9RngmCr9cgiIgCX/WfGQPXTwuLol7gJeisDFRYaSFwG2UMol6agjBlBSlQcfctP8FToFJrVCzANh6N8x8RCmbztwMU06F6nXgXwneDHMjNgKdxPq3Yf8QbJet4jBrmfqZoQi7x0PsMFBaD5eXKoX2MZh2po1DJxkKwC1dB2whmzX0nGTA1jXAb4j1BylMh05SKSKk/RRVEOtZ5oGqRS1kEJgNYY+lmMpEIYBNWC2MWViGNjvN42qqibJbrQRx4s5SvPinF+gRb6OH15gH/zzYfaoCVlnAItMk8TfmuuPlSyKtF96JJIaebm7r0t3mm+JDTeahyC1bUCD7GMvYxpvmlXpNo3n57VSgZzZKdv5Z+nhRk6SiD5pLkjUICbnbdBTH/D2Mi1GSsDPKGBlYfR05KsLYycfSnMfPl4RQIyBGjqqcDOlhCuBxM34gJlsiMaNZ+rU5HKTCPDI7gTdZRCT2Fa5fmYt58HsAnhtvvNEQJVQkEuHHP/4xTqeTXbt2UVlZidvtxuVyMTY2xpEjRygpKdFFeceOHVRVVTE6Oqrb6gIyioqKtEJEXGzj+QlSQDo6OjQR1Ol0Mjg4SFlZGU1NTXps0tvbS1dXl5aX+/1+KioqtNeObJ8Up127duluhCh2UlNTqampAdBFUfgRGRkZWh0jROqkpCSKioq0Mkk4MJINJcTa7OxsvT8Oh4P6+nrGxsZ0p0Mcg998803sdjuVlZUMDQ2xePFiGhoaNA9HyKlyjJqamigrK9PjoIGBAZqampg6dSpNTU00NDQwOjpKcXExU6dO1TEZJSUlDA4O6nFcXV0d8+fP16OcSCQyTl4fCoVobW3Vx2jChAnaAdntdjNv3rxxajjZPhlhScdNukgDAwNaHTY0NERCQgLZ2dkkJSXp99TU1GC328nMzMTn82mAJaTqeA8fkbi73W5CoRA7d+7Ubto9PT10dHRQXFys/Z0CgQD9/f20tLSQlJTEpEmTdPdQun09PT309fVpyTyg5eiizJL9FZD83S6ldHOkwxWvmHI4HBokxo+qBOzHE4jlX1mGABnh/MiPdONkuTIalG6SvPbd9cTzgyKRCD6fj8TERO67774fDOBJwmZIMOOjwHk18D+TVNl4GjOZe+3dsGobqgxcCYATHwFipD6AutfeiGoomL4fj0+DO7kQtSQR5n6Xo1CFcr/DfF8+qhr/P9BU5iayeY/uj1EzN1H6LIThJ8FVCmxXoZATn0I9vr8G/30O+oa/CaHgWtLiLcCfTZO9e1BFMIqquYPm2mv4CNHQTLM9QRTVARj2mh/45AisKVe7cykWl2LV3VzGarKA/20Hm+8NjDcvZ/gSSHJ8xG84l0efNHj5VzauPWJA+W6ymUtPoaEOw6sqgDQhZhB7GnzX22gxC/QS6jiFMlajxkybgPbfmhL48k+Bu7iY3bwTNiB5Ljezm+fuMNjxhI35rDCP79fqnOxOgMoNcefiXeA5EqhgAcN8TSUl7CbLZrCHHvOoSQ8kPl1L/f8g2VyAKrvveFDo+Rl1IX0chB+7TW+dXwE/g2lz0T41icDP6CFCJldj5xpzbcej+jmDwI6VwBtXA5tMUGqO9DgThRSbUeV9C5PYRiJwiBmog/MMy2ilE9iOl6vwa5PCfKw8quVYnGCxzBGQLL6FApJ6gUN4ScOvR1Z2YoyQGte5ETKzDMa+6xTojFtbKlbGRJ7593gAJcuC/2vaI5RomQHKj3IpFPPJN/ECx2Ow9T8HPHfeeafh9/s1N0Ce1vv6+sjJyeGMM87QN8mmpiZqamq0KiYlJUXLjKX4yc1XeAZS/OQ9UtxkLBAOh3UgqDgpi8S8u7ub/v5+TQqdNWsWQ0ND2mxPgj8lZFHCMt9++22cTicej4fk5GTt+RKLxZg8ebLmfggBVxybQ6EQbW1t9Pf309jYiNfrZebMmdrjRrKTJBV+bGyMjo4OTe6Od4QeHBwkGAzS1taGz+ejtbWVw4cPM3/+fHw+H0ePHuWUU06hu7tbJ5VLkRsaGtLOw4ODgxw7dozt27fjdrspLS3F6XRSW1tLIBAgLy+PoqIi7Ha7dgt2Op243W4OHz6sZdkyshHptoC80dFRzT0KBAKMjIzQ0NBAeXk5hYWFms8isn6xH5BCL7wSQI+xent7cTgcHDt2jJGREXJycrQSTzpAEs0hKruBgQGys7NJT0/H7XbT2tr6fwjOoVBIg6a2tjbKy8s1IX3v3r3k5OTooFI5jvG+SUJGFo8gcT5OSEhgYGBAb5OMI4U8Deju03c7NOIJpL9scaAe0KNV6QzJ5+W98eT+eFAlYEkeFOIJzvGfkc6RBMDK/8sy5HOiBJNQ0ccff/wHA3hszDQuNgmRp6Nuu7OAnzUq1cuGdDXNGVhvwIrNwH/j5DAjLESVh9OBfHjPazVyhKxcEASeN9ckYxWwCoAY8T9EAt0ml2Y/1jhsE9CEj694FIVlJNj6NRawkW1kAhcA7RQAEzH2fqUqUypsORHmxsDtUOquK4D5eLnYLHZCddhLKaoLokDWNHbzHFa0wM9QCqvPWQCcDWvvU5vuBsrXo+1szy6AT+6Gqx+BV+cC/+YtnPycVM4jxD9vgleeh2uDBqd4bHzNwygAOQjhcialQM1H5nIXbYOZC+DP0FRp4xTU4d0J9PARmziX014DrgNbtJpzmMLHbFUnIKMS+jbDJadCPtjWgjGwFgVqfg3cDK1vq51LNA918hBK7t/BifyWG4ErKUDJ/efzvM3DjXyDRRWuwur3KPrtKNPZTgrNwKWVKJwhSHMTvL9WnUOAbwrg92bHaB4Kht1NP3Z2sYnFWvOlGCvq504PLA7CJjcYA0G13lYvFKgIjs0xOMsBX5uqKRetxHAxyj3mkatgGqupIpW/muPbD8zzO9vs9B0Gft0IIz7YYmIS6bUIrNiIxc+RaWC8CUP84CleNa6AUAaWhErsnmE8CCJujfJ6FhaQyWe85msQC57Fs4fiHzLy4pZVhcGr/zngWbVqlREIBLSJmhSvgYEB/cSYn59PQUGBWr1pwCY3ZCEoyxPn0NAQra2ttLS00NurEJx0DxITE8nMzCQpKYnU1FRtgd/b26v9SjweD+FwmMLCQpxOJ9XV1SQnJ5OWlobP56Orq0u71trtdm1oGAwGaW5uJi0tjRkzZuD1esnMzNQuv6IoGxwc1HyScDhMcnIy9fX19PX1UVJSor16MjMztRw5FArpAllSUoLNZtMmc/Pnz8dut+suTVpamu4uHDt2jLGxMXw+H/X19boTNXv2bC31FyWYRFi0trZiGAZut5vi4mLq6uro7+/XAGLOnDk6DkNAp4xexKk6Go2Sm5tLUlISR44coaKigkAgoAu2pKbn5eXpApmWlkYoFKKvrw9Ac2MMw9CeRMnJyXg8Hj1GkeMv3CABJoFAgH379tHV1cXkyZMpKiqisbERj8ejpek2m0pKnz59uiYvi4fOwMAAKSkp9PX1aS8bp1Mx1oR0LmTumpoaDWT6+/ux21Xwa2dnpx53RiIR0tLSWLZsmf59bGyMvr4+PfaTbCwBhmKUKNEdQngXMNna2qrdt+X8xI+1vqu+iudSCWiMJxTHOyeLeWJ8WrqAqnjSt3SGvhs1Id/beKAEjEtQf+qpp34wgOe/sRmJWLzQ24cg4YjyI+nFzABqhRcmwU0UAC8BE+FguaUdLkY9Fq9cA9zDHPwswXp6noh67tyI6iHU4EW1hG5ClTMZRyQCRUziK2pYCmSRxjpewrqF34CLuxmmFsuKpArFUb0jBi864DY85ruzeJ16w7XnUwAAIABJREFU9jO+SLXiYpT/Rj1df8gpHKQIPfWgCRigEmucsAWrtfQoasfzOMwdTOVtuGEFvHgEbi1XRb7Sj+obdagsLOrYRBmn3aRWYltg8NgKG3d+ZihV0ZXAw4Uwt4VTdtn4mhnALLj1DWIP2rD/F9je8mB8EWRsLjjShXe0CoKvqk103KC2r/UAFGyD3QtwzYVhYzN8daqa17x6K9z/LNwbl05eZe74fvMgVrYCG3FyHSO8D/TCmpW8fgNcxhAJbFCfZQSrtEvc90T+jo/ldwMPHyGBWYzSq+IzrgQug0l+c+z1hDoXv79DLeF3gJseoJlBZjMSd75qUcDnXeAfSXBDRG3BTWcBn6wDlsARr3pzeSEX08r55mcvjapcrHdRcO4P6OB7OlH0+o3A46SafDKF0KaxjiXmMuKT2M9HQY+dWKPf2VheO9J3kb5XYtxrxB2xoDkOswAJ5pJTUYO1aNxroiETEBQ/SBTAI+BHgI/8xIOeTMRy2WDVfw54Vq5cafj9fubNm0dGRgZerxe3282+ffvo7OzE4/Fgt6sQwpycHLxer+7kCGdgYGCAjo4Odu7cSW9vr1YxCX8kIyODWCyG3++nq6sLt9tNVlYWXq+XsrIyOjs78fv9urBIp2natGm0t7dTXFysidNbt24d194HVUASExPH8UYKCgp0/lB/f7/mYYh/zsjICPn5+dTX12tvmPT0dM1TicViFBYW0tPTo71ZJJpB9j8ajdLX16cB3bRp07QaCZSPSmdnJ/n5+aSnp2vJf2pqqt5nIWlL9lVfX5929k1KSuLzzz9ndHSU9PR0cnJyOHDgAFOmTMHlcpGVlUVXVxdNTU0UFhZy3HHHYRiGjqEQwmtjYyPZ2dkMDAzomA6xEHC5XEiHLy0tTYPAeBL25MmTiUajekQpoEnys4RXEgqF2L9/Pxs2bNBdOLfbrVPiI5EIM2fOpKenh5aWFsrKyvB4POTl5WlQK+fT4XBoibgQqUUhJRlWXV1dGuSJZcCRI0eYPHkybrebpqYm3b0JBoO6w2iz2QgGg/j9fs3/kRGVnFuJLvF6vZozZrPZtPRfzldycjI9PT10d3frruV3R2DxHRnh4QgoAsZdxzabTQNjGRGL67mMx+I5U3LshcMjI67vdpGEiyXrf/rpp38wgOdvpkrrMOp2qRQ9PweyMLYf5G8nwqU8C0Jn3jBDESMkgygK7LqPfdzP1Cg49wJZ8Mkka5kvoGguS7BoIftRNfhj7gUCuPgj52MVoyXAm3zCzZzNB0AzqTQQougQfDht/GihAytX8RpUV+cN0yX3KpQh8uNYfoHzUPSRQdRw53Vz74Ssugl4EiFfb8JFPcMsMNcgujGx8N2JAkEmHfeO+9RbBlHVMWqu7NnN8N6piiGrc7HegDUrOeN6G5+zFC75CN6+HCdvMUIxkM8ctrHnfEj8wMELxLjmJXBe52KUH8ORf0D5HRi3PYnt6VXo0eHM69U2PAo4RpmDk70sRQHMb2DdI2ont6AaPqLmeR41Q/oNUH0DqtNWxBmcxOcxg+cT4EYaUVAhPqtcSdRt3mXYu9ysJsQrQA0e4CX44wq4ZTNq588H8rBzLmNcDhte5Plz1UQwmTFGsZPAGH7sbEIB2oU00kwJz5vnrxfF0W6UHNt8VJiX51ZO4Y9gXmPvcCGQxTLWaq77RqCHM/mAz9ho7uH5UTicqEJGnSE1OpQRl+lEwPHA/T3Qma1e7zCXFTWvCIEUVSjIYlGKLTgSnwAxyHiYEhnnyVPM+BEY5pZWxP0tHtQIrJJ/xfsqGvd36SYdDyRisOI/BzyXXXaZISqZ7Oxs7S3S3d2tC5yMfOTpXsYZ4mK8adMm3TZPT0/X5FThdwDa9RZU9yAQCOByuSgsLCQxMZGhoSHtVOzxeDAMg8rKStLS0mhubqahoUEneA8NDWmfFmnTS3GXjo/L5WL27Nm6sMRiMbZu3aq3KyMjg9TUVC1vNgyDiooKnd4diUTIzc0lGAxit6uYAlExifEeqI5XbW0tZWVlWgrv8/nIzs7WXB+n00k0GqW6ulqbxcViMcrKyhgZGdFjphNPPJHu7m6+/fZb3Tn64osvdFaT3W5n48aN5OTkMGXKFObNm0dLSwt///vfWbp0Kfn5+ezatQu3201GRgZlZWU6m0pUStJRE8A2NDREd3c3Xq96ukhOTqapqYmMjAyOHTvGggULSE1N1WRrUUwJeVwAqiS9b9iwAb/fT2pqKh6PRztAC6F99uzZADQ3N2uvoxNOOIHR0VGdoSUjUZHKDw8P605UOBzWBX54eFiPGsXcUjocPT09tLa2kpWVRUtLC21tbbqTmJqaSlJSEn6/XyvO4onCgAY+ktsF6FGmjMeam5ux2Wz4fD7dNRSVnnRkpGsT32kRQBf/OzBu9CTvERXWd/2t5LPx7ubxCrfv8oniO0l2u/0H1eH5KTajGVUbe9EJS2wilTHuRktcNlTCVeAMQPqounW2nwt8OJPHOKgZIMdjcYsTUTfy/yKmI5Q6UY0EodP+BahhKWls4Hfm37eYaz0MtLMLuIdsNnA+qgTIk/fCKDQlWlFDiZiK5h54JVv1jY7g4m2GuagRqkpU30UGBAJbpHezxlTkXInEQa7Ax3odEaA8hVMZoxKoIhs/QVz8imEepRQBCLAQ1p6lLIfmo4gqE4HyXG7GzyzgWs6EdZ/CIIxcYWN7CpyabBALX84ZrDPHZ4d5iyD7gUcpAB7AOP9quBYmLIP2uQbs+gnGbe/BM2DrM0jwJKmuCiFsaV6MPpSkaznMuVsBgY9Xmju9HCi4AbgIYmepEzgRqDwIfICP31IMbOdCWP0PeBoMfw8WaRhU2c9nJ8v4uWEjqvZej6KEstsEBEhlrH6Qm0ttPMdSXGxgmDputpXiBJ7iC2QuuolsZqOCSDtJpMM8B8Ln+dA8j3svNC+WXwKVa0jjBrKARu7iG1ZzBkpyfjNBMM+OxEwJLpUOknQ6O1HgZCLwCRavSyTr+cDqdhQSqoDHSyxnqah5FUj4ugCd+BGXACH5jgjzJhr3/m4NgIQL5Da3oNP8V7o8Mqpyxy1BMu3lc7JnFg/oewGeX/ziF8bo6CgzZ84kMTGRnp4ePaYQjoXIeIU0LE+Y7e3tfPLJJ9p1V36E0CrgQnxK4kFNOBwmGAySmJioib+dnZ2Ew2ESExNZsmQJNpuN9vZ2LQeXwhMKhRgbG6O/v18XFFFDRaNRsrOzmT59OoWFhdjtdrZu3cpJJ52EzWZj165dOp4gEonQ1dWlvYPi4xoSEhJoa2ujoqKC3t5eKisrx8mrRZUlKilgXAr84OAgfr+fUChEJBLRbs7COyosLNTb3d7eTiAQYMGCBUQiEZqbmzly5IhWC3V0dOg0c6/XS2trK9OnT9dp5v/+97+x2WxMmTJFJ9KnpKRQXFysC6YkeQuAEB+iYDBIOBzG4/HQ3d1Nbm6udlYeGhrC7XZrw7uKigoyMjJIS0vTJGDx+Pn222+5++67dfaU0+kkMzNTF24Bfna7XXeRBgYGmDFjBtOmTWPOnDnjCL0yHpVsMAFAMuqRa2BgYIA9e/YQjUa151A4HMbv97N3714SExP56U9/qtVkoMZC27Zt0yApFAoRCAQ0WTiekDw8PKzVZPGcotzcXNLT0xkbGyMSidDS0kJCQoIGeQI4hMA+NjZGKBQaN5KKJ7uD5br8XYAU/6/dbv8/oCje4Vw6PSJJB3SHSq5xh8PB6tWrfzCAx0mSMYNhMwH9l6in8ApU2Toe6j3wLjh+r3xoKlA39o9XwrQ3lHGdPEdOxdKLyDPoITzmsvK5irU0o270wtJRcaKqkD2AKiano4DJU5wJ7Occ/IwAp5nvvRR1215mjtuGy6DLAQX9ptPuMVQFOht+cQr8OR94CRKXOXiFmI44XQhU9sOt6ZaE+gRSqSDEIKr5ceMhtVLbVU9gPUFfqrY05gHHGlRf6e9qjwo9ShJ/75OoIYpJwN7wLCzdwMjQuThTlpLA54zyF/MoXAcUw5NPwHLILrVxOvAOHwFvYecfjFHPJHKZCPyrEWwlL6JabZ9zD07ut0Gi4WCE880t/zncUcdtT6oCvxFof8Q8xbcDL9YDH4D/FvCqyIYT8bOdXXBDJby4Fqt9spNv+CN3AU6bwefUoAqvgrGbuIyQYeO87fDQiRZgkKMlBV7GQjKKvBQFajcBHyUbrInAFaikdeggyiQ2kUi+Ojo6cFxsBTYB7cZm84r8Oar4ZwFVvMVBfvZ7dSn/+DLVYZyFgxOIcZ75+eVYgjUBQpLpKdsfMq/jIvN1yeCU/sos4JeiAhuEY5MsP/FZWLAw3/x93nb1S2eJ+h5UYRGim7CAtexngPHjsn4cjJCPxZ+Sb2QmVkeoFwv0xEvgRO2VisGp/zngOe200wy3261TsUWq7HK58Hg8ZGdna7VTvO9HU1MTX3zxheZ/SNckKysLt9vN6OgogUCA5uZmXUCysrKw2WwcPXpUk5HFVE9GZ5FIhJNPPpmsrCy2b9+uIxvAygKSEYSkscsTbUpKCqeeeqomwkoqudfr1fJ04bIITyZeKi+5SB988AENDQ2UlJQwPDzMyMgIx5nBmTabjf7+fioqKvD5fFrqLV2Gzs5OPd5oaWnhhBNOoK2tjXA4TFFREaFQiJ6eHu0snZuby2effcZPfvIT+vv7KSgo4Msvv2R4eFhHagQCAWbNmsUnn3zCwoUL9ejP5XLR1dWluxqzZs0iOztbnyfx4gH0mEqAQygU0uejqqqK5ORkDSgkU6ylpYX8/Hyi0SgDAwN4PB6mTp2qCc/SVQsEAnz66ae0tbVRXV2tC7wAZiEDJyUl6S7NyMgIwWAQwzCYPXs2Cxcu1N45QqYWYB1vWijnf2RkhN7eXjo6OohGo7S3t+ug1KSkJILBILt27cLlcmmCuXSHpk+fTnFxsR5JtrW1YRiGBj3x6jPhm0mXRUJf4w0Yk5KS8Hg8+jsVDAYZHBxkdHRU+1vJmHNoaEir7oaGhmhra9OdMxkXCr9HtkGAjYz8xPBQgJEYFMp4UUQB0WhU/yfHVXhcjzzyyA8G8PCAzai6ByYNweIU+JoXgSvAn6LHHs4XYM6oZYHzxQq4+G2bVi67UTfvRryoinot6vb9CyyiZRYwjxP5LVdg3a5F5yP+LDd+DX85Ba7kTNL4TAdsxzuRnB/32byvURV0ifrjsUkqLsFFPWM4GOFKOOlVlQR+r41fkMrY7kFV8VbdiqKtng7hV6EJasttTGw3VV97VUr2h+Z+fs4KzmC9JtE2Ug2XlONbD+2Gn3vI5QEOkMA8RpnAzdTzXMzgDIeNPOBN6nBRRiIwwApU2b+Sp5nCbTys9uyPMzAO2vjRy4rXcj5fAlWw4XrOWGrjc65nGmtwA9t5A0hkB5cwrx1sPmX8eJvtPt0l6wQOuyEhYvrbFANblZs04VsguRUXhQyzlRJOopEFwO/gvaVwoYpyWMKFJPAvPAzT80eD226FpziEqIsmGycSRdF0xJxQumJbzN/l/ErawX7z/UWoy+wdDtBkm2H2IRoZxcsoSYTN0dY+FKAW0FMFHKoDSv9o/gawBSeHeYUYV7yGbk7+VD1T6y6m21zOJmBdDFaZ3kxTUQClCivaQbx5xBUBFKQo1le0Ws5204vnRuBkLGXXB+a1I8djCXB/I6qVGs8tFjwiIrjj1eXRXKKWvxOLvC06LAGWbTgYYb659RVYsnaxUJQFpiJxpgYL/nPAc/rppxsVFRX6hiu8G8m48ng8+gkxEokQjUZpaWnh448/Jjs7Wz/Rp6WlkZ6erp80e3p6NGl0YGCAwcFBrYjKyMhgZGSELVu2aBWXcFJOPfVUHA4HO3bsoL+/XxNM40dTItUWToNhGOTl5ZGbm0tJSQlZWVn6vY2NjSQmJnLSSSdp0DMyMqIDNsVIT1r+sm1Hjx7ljTfeIDU1VRNVp0+fzsKFCxkYGCAtLU1zKA4cOEBdXZ3uYkQiEbxer85XEqBWX19Peno6ZWVlel1DQ0OajD1p0iQ8Hg8vv/wy2dnZ2itGRkK1tbXMnDmTzs5OhoeHSU9PZ+rUqWRnZ+t1NzU16bFjRkaGPnYyDhRuT2pqKocOHcLn89HZ2YnX62Xv3r161OfxeGhtbdVBpcXFxSQlJZGWlkZZWZkGPbFYjEceeYR58+bx/vvva/lz/I+AAgEQsk3izeN0Orn44otZtGgRYHU0RkZGGBwc1J0wsSCw2+309PQQCoUIh8M0NjYSiUR0HISo7UT5JbERkUhEA0DpDk2dOhWv10s0GqWnp4djx46N2+5IJDKO+yL8NBlXxhsMynbKtsvxEffoeHK2GGcKN0nUZsIrivfYASU1T0tLIzc3Vxt0xpsSAuPAbnyIqOxDfIfoh8Th2WmOtJZzC3AFxCpVdakC/ga+j7RvMvuB18rh+Wobg4hD7Sq0SonTsWSzr6N05KcDm0jDr/OHoJONrOXUGGxzWKlMmSg1VC2q+CzEYh6I44pwbR4AUr+G5lOg6Au1CZYU/jWgiUnM5Gtza/K5hTTbswyUou//zo1w3KglKpNy8I5Rj3FpGVwKw+eC61PoPEcJ6GuB4bUG/B2mfQSHjFym4Wd3DJ5wqAnW46ho0gEWAft50BynzDaPyizzPcrH5adAFk6eZ6R1FApu4C3WcDvwT3N78hmBcALnJNv4mAPA47zLOpbzK+DXcLmXO9epoiijpDGln2HOKOww1kL9Kigdhd8myHwJPqyHWCk4nkSd5ReAixTX6F0oecNGI16m4ScL+JpXgSUws4DwwTGSaMb2YgkPXm/jfjPq4C1zm0XZJIbJQml6HGv0+KV5NWQB5wDn2wzNsSqln4Oka0dtsMZCLwA1jwB3rYXwKkguVNulnXOivMsaLjL5ZA+VqN19igKW0cpsVE9OwEwVcDUuKk0yfBAXp5rREELmH0SdWxUzkYqT0DgdVb8pSVdgtgD1jenkRA6SiQXWq1B8tExCBHGxgGG+akQhI7DyseLbOvGeg3KxCq/5RpXuDvBjxE0cLOCzD2uwKJ0gNwZ3fz8fnry8PGw2m85/EsDj8Xi0066MGDo6Ovjwww/HGcfJv8KNEPCQmpqqyaSDg4MEAmryKB4s0WiUPXv26G7DkiVL6OzspK6uDr/fD6BHDgkJCSQlJelcokgkQkVFBQMDA/j9fux2O4WFhZo4Cioss7y8XBvVlZeXA6qQDQ8P66dvMbaT7pUQaPfs2cNHH33EFVdcgdvtxuv16q5DJBLhs88+0+62sVgMr9ern7AbGhrIycnR0ufDhw/rblZpaSn19fVkZmaSmpqq07+nTp1KdXU1DQ0NOiB0aGiI6dOnU1dXR35+PtOnT9c8jsTERMLhMP39/RiGQVaWulG7XC66u7tpbGxkwoQJtLe3c9xxx1FbW0thYSG9vb1kZWVRV1dHVlaW5ptEo1E97iorK6O9vZ3m5mbNsZo8eTJlZWX4fD7tSh2LxXjooYcIBAJa8SSjIxnpOBwOkpKSCIVCugshYanS4Zg6dSrnnnsukydP1oVeRpYyVhLOlnC4hP8k56W9vZ2qqipCoZB2V544cSJDQ0P09fURDoc10BDlXkpKih5VSUirgFgxeRwZGdHGiBKdkZKSopPjRd0VDof/j1+PXMMCTmTfOjo6SElJ0d2j+E5MJBKhra2NhoYGbYQp+WsCZkQlB+PNIR0OB6WlpeTk5FBeXo7L5aKzs1O7Z4MClH/6059+MIDnL9iMK3kW1eDPgw0JqnLuVGDnZ6gnVnFvfdewacuZHhagntHPN/+dDQc9qgKoDEz1p/LNiM9LAl8zRgJjnMU5vMf7UYgmQuqbcMFl6ml2KsqGENSiRC6/D+vevwQ1jgKwh2CLT3kDfk4l09iti2MjZwK/411OY/kRA98U6HCDsRJ4sRWmFEAxnPOpxX6YBbxWoBLkWah2y7Z4BdNsb3MFcGcB7Gix8Qyw3iyURQhJdhD1oReAWVzFZ/wVNUoDBQSExD2I4jD9Fcgegqkpqj8m4OCnKNHXnTwMfMhlbOPNOwx4Yjcn2yo5HtVBaTDBjX3UYnO0G7vVaGoTUF2GilTfBKtXKJQxCeh6BNbfDSsuB/JVJtiMXOCXKnR06TbgL6SxhndQk7BD6wy4HYb9avQ02chRieVY5F7p5lRgedfUYnUIj2E5MH+7F/4yR23zct5gxHYRCRxllMlcSYqGz6lYvsrNQONmYFEhcD5zWMNC85gJ7/oPh9SBeKjE4qUJcHpOHQmIO1vSNbwKeAePaSaYSxr1JJp/r4r7TD7S1fQAU7FzgEwTBKkumcB4UVVVAB1MYwMTsUj2AVIZYwpQSzZBXgIueh/FpxI0JRdOfJaETKqyvvM+WV2ROhBVixUQkq7UXjwoDk/dfw547r33XkNM9eTJXuTVIssGNBlzw4YNGgjFxwUIOdnpdGpeh4wmpEg1NDSM8/pJTk4mMTGR3t5eFi9ezNGjR2lqatIeNrL+5uZmHYJ47rnn0tfXR3V1NXl5eSQmJuLz+TRh+d///jdpaWnEYjGSk5O1xH3RokXa1DApKYn29nZ6e3v12EhiBkQSLABIZMr9/f2kp6cTDof505/+RCwWIxwOa+lwZmYmJSUlpKWlkZycrJPhhQ9jGAbHjh3DMAyKioqorq6mpKQEn8+nozxsNhvNzc2Ew2Hy8vI488wzyctTE1TpiAiXKRaL6agM+dm7dy9DQ0MUFBRoNVMkEsHlctHY2MiUKVPYvXs3xcXFWql25MgRnYK+bds2KioqNDcnEolohZ7NZqOzs5PU1FQmTpyojSU3b97M1q1bNadGCM1ybYgbs9Pp1FEQ8fyU9vZ2LrnkEg4cOMDy5cuZOHGiNkiUrK7+/n4NkAYGBohGoxqs1tbW6vWmp6djs9no6upi8+bN9PX1kZ6erhV6IsuWMaUANAEPIgEHqKiowOVyUVNTo0GOkKXjQY/47AhfCdCAWK4dWYeQoMXFWkZ0YqopIy2xQpBRaywWo6amht27d2uzTPmRDpAQk2V8Jp00eUAoLy8fl0v2j3/84wcDeGzcasBqlXulPNvgLfC1quKrEpgUwHna2IyP02hnFQogORkvkXVDuNx6bK7Cmkdd+CQKMlXhNJkSI2QxBz97fg+2B2dgp44iQlyDujnvRxXGO0z1TDgd3NzCVfxRe7eIV84S1AgoH9VFeQFVpIQj9DmLwL+ZklyV2J0/KPyPV8i2vUFPATh64PKI2nwZub1ZDo5GiF0FzILB622k3gmfPAZnH1JdJaVIWoQqcD9DjfSi5lF7gXM4yCbgTVTduhUXBximGTgXFx8xzGVAD16exs8vL4W73oJHeZi3+C2Xnmdw8UdWwW2KO+KgSuk3xlou5mrTcHA33G926vIh4cUkbIwy8t4oXLgW7l+F41GI/Qac9yYwosdTPwb+DMEZ4KmHI6VQXg+cYuZziezsJq6zLeUPwH7Dxv+Y25OK9oQEFJPo71hp47PMq6bZ/H0Q+MPx8EqtWvtyfoUj+Qk2R1SnSmTfgygQXAt8cZb5Py8BZ87Ex0HaeYObuVwFp3I8z7OGG79Qm/qXc1SfMQuLnwOqi9SJ1ZuUAdD/om2cmI9wrXLMT0VJw697mVHgT3EREiMsMbe0ydxL4RRJa2Yh6sqW2dUrZLNb83s6gc9ZGbelVXTQSt61WBxkoVUJwIkHQcS9Jt+7eF/C4+GFZeqcfMb3cFp+9NFHDeGDiK+LkIyFZGoYBr29vezfvx+/36/5HpKXlZqaqrk28WGVcqNPSUmho6ODuro6XfDiZeBTp06ls7OThoYGenp69JhLZM8ZGRlUV1ezePFiJk+eTCwWIxQKUVBQQCwWY926dbhcLi644AIA7QMkI6e0tDSi0ShTpkzRoyIhTre0tDBlyhQtdU5LS9OFQp7Me3p6CIfDPPDAA3psJ1lM0tHKy8tjdHRUh6kKv0e6UmIm2N/fT0ZGBkePHtVk5tzcXFwuFz/60Y+YMGGC7jJIdwhgcHBQK8TS09N1krjf76exsZGuri7NI0lOTmbWrFk6WFO6YDk5OQQCAXp7e0lLS8Pr9dLX14ff7yc/P5+dO3dit9spKSkhISGB/v5+Ojo6tPonXhE0ffp0KioqePzxxwkEAiQnJ+NwODQAC4fD2jlZuhRS0FtbWxkaGtJKqZ///OccPXqUmTNnctJJJ+kk+qGhIa3uisViOk6jt7eX3bt3MzIyQmWlan8KQbe7u1tnitXX12vDxGg0SkNDgwYLAhBEqi5AIp4PFovFmD59OqFQiN7eXg2ApZsioCYajWobARmrxSsZI5GI7noKfyz+2pRznJiYSDQapa2tTXN3pEsmnbFwOEx3dzd79+6lt7dXc5viA0KFqyPkcVmW7HdOTg47d+78AQGeeoNgqUIJm8DxMVRG1PjlRiyy6HIP0Pdp3CdN87SDM9Qbbgmi7q6Z8FWK1b+vQN3bb7kE2Ek29brBLk/+w3wEXMUk0xDwGizS6EYUkFnYCK+UwLW7DfWHGbcCv+Q3lLEQi8j6FCu5nXU8hRer9M5iEvdTwy7IrWSxHzYnQWwScOAn2PmUVNsgAyvguvWqTMlwNgt4zriESGw9rhWw/12YtRdemGOpvEBBm6ko8rUiHC8191IMGk/hFA5yEWqs80vg1zWwZZKpDm+HE3zqUPWcbXDZp2rsE0DhFgEAoF7fUQC/abGZvkbXm0cyH7gUPltK9lnQ8wYwD2xzwRjYgNO5lJGjQOkGWLtUHdy364HX4eB9xEpsONIfhifvVgr25D8CG82ir3IgNvEVL6O2+RqbwemGSoOXUZoaW87DzjbGyMBFKyOkMpEQNXg5Az+nmccK4KJE6Iyq43YMwGbwKMrluxl4cwZcd1CB1sPA8ErgjVO5mK84hhV6eyhmgOMRNvFbMoFZLwFvwaJN6hwdxMUMhumNu7akQSK/F2PF2wrr5XXzXM0Gzje7OTIj1FB5AAAgAElEQVRrSqCblQzjVqui3wwb7SSVMX6C5fIjfSohUWWaS88CnCpmI3k98AyT2KbcvPVoapbewjm8x55GFMKOt0AS8ZW094qwLs54IBTfDVr2PQDPc889Z6SlpWkCa7wLb0pKiiYG+/1+du3aRWJi4riRBFg3amn5CzlUpLQyYggGg3R2Kr67w+HA7XZrt+Ha2lptHCcFUkwNRREzd+5cbVon3JtvvvmG3t5eXC4XAwMDLF26lLy8PAYGBhgeHsbtduuU7KGhIRYsWEBeXp42knM4HHzyySecc845gBXeKF0oCR1tbm5mcHCQ999/X0cTiGJNgFFSUpIOp+zs7KSiokIbCDY1NZGUlERVVRV5eXl4vV7tfSSSa+F5yJhE4ibEcyUhIYHW1lYaGxvJyMjQ/KiKigpdgKVDILEIArDEJE/OZWFhIY2NjdqFemhoaBwfRLo8wWBQ/10clJOTk/F6vZx33nk88sgj2igwKytLH5OsrCzdOYtGozqKAxQoGRwc1KOis88+m66uLjIyMjjvvPPIysoiFAppUBQMBhkdHWV4eFj7ODmdThobGzl27JjmcU2cOJHKykoCgQCHDx/WBHEp+NJtjHc2llFtPHAQDpQAoOLiYnw+H8FgkOrqarxerwZI8enlIqcfGxvD4/FohaIQhgF9jsECgNKtk++SbIO4J9fV1WmwKd22SCRCOBwmGo1SW1vLkSNH9D4K4dlms2kgKKBOxtNNTU0/HMDzFQZbgA8ge5t68q1A3aqnogrAQ8BjRj2q7FwEBxOslOsQirAiN13JOoQ4x+V1+LicYvVp/VHFq5gBuPGxjdPN16U/MogCMbWoEdBUkUfLA/BEePkWG1Xmchd+rT5g+9hQaG0WUPAklnvz7bC+j3MusYz8d2yG7EU2elYbKkxsCdy5Xvxo1ba+ZoxinOzkoW/gd0vUBlZdrIr8ghjUOdT7PzC3uQr0uEnIq8dIxc4o5Si17OcIkfUT0mxnaS6LGOLVmuueCjy3CwUqf1UG/IzfsJrHSeV3hNgHvO831N8Hzd2co/aD5cCKq2HmqzALfOug3TgI/hng9QNNym5gaau5tTtx8STD9KktuLoSXl0LRMnmBm4y3xUFvuZM5ts+5atRG8861D73Au+b0QVqyCUMnHxcrGGYAuz0cX9cSO3CdtjvU/yoXwN3nm3w2KfwG7ML1+EGY4Z5XV0BzsoEJhCjES/n4CfAeAeabhxEs2JwLfzPY6LmSsVBhBhJ5BHCj9klJh2XmTr+/2fVJwTrhcADOPiQGLXmen6PF/UtkVmTaqXM4TMl/WcRlrNTFNWS6jCPyUR1ZsMFkHzEOvMHZ1gX3elA8n3m++Pzti5C9GT7WM+sB8wLRsAMWI0l4l6D8R6HF3/PtHQZw8R3bAB90w8EAlr6G88DcDgcOnZBbthDQ0OajyAKLumaHD58mH//+9+aUHvyySfT19dHfX29dhq22+14vV4GBgaoq6vTLfmzzjqLyZMnj8s+6ujooKqqiqamJk2WjkajLFu2bBwYEV5EKBRieHiYefPmMTQ0REpKCv39/bq7JNJ12UdAu/QmJCTw8MMPs2jRIux2O99++y1HjhwhLS1NE4YFjLlcLl0QPR4PJSUlzJ8/n6ysLD1+kQ6CjEriCajyVN/U1MTmzZv1iDEQCDBt2jTsdjv19fXMnj2bv/3tb/zkJz9hdHSUYDBIfn4+brebQCBAZmamJpqD6hKVlpZy9OhRAoEAJ5xwgs4y8/v9FBcXs2/fPoqLi0lISND5atLVE76JdCWmT5/Oli1b+Oqrr8jJydEFXGTx+fn5+P1+TZzt7+/X6ipx4R4aGtL5YkVFRSxfvpxQKKTzwMLhMElJSTQ2NhKLxfB4PLoLKBycffv2aR7O6OgoHR0dLFmyhGAwiNPppL6+XoeJSudFrg3pXIl/DYyPeIj/KS0tBdBO2uL5JOaH8QRmAS2yLJvNNs7wUcZ6Iu9PSUnR3xnhxMkYUzpEEsvR1NSkQ1+FdybWA93d3VRXV2v/KOmoilJSxncNDQ0/HMBzKwbvwrRWdZ+ch0U/FsXKKcCwsQ2CC6zevwQOSbT6C+a/U1FAQ8xLJN7orlw+MIvLYawIi0tZhYu1zDdf78fBj4nxHNZgQJ6g31xrWPMJgF1HgBM5gyBNqE3rPwTN06D4BkOHhzqeg9i7YF/qZowpTLLtwo2lsKkxjjCJKfTaDPoTYPqoKknxHrcPGqdi5H+lgJRZrTtPUSBHxiNFQHk/2KvgmRPh5iFoT1Fdgt9zr9qb1a9y292W4igPVc7k2f914AtjM0bjadxVopbfAfSEDezJbsZYC+ykhCdp5EtqOY3j7zDgiXrYUGqZCj0E83fDjgtBC3jcqAU+AJTeAHe8qE7CByi08V/ArlOBm+CrFerceu9A9EZOOrAT4zZzX2+iFOPKengUnvGp09yMRDtIsJmyDoReXKzmZPO3a8zL6LRG+LAEbkYd2g9sBlVAj8c8AVcC996HnScZ4xLUkOtRoMN8TaXIAyzjM6LAv2bDl/vgdFYBg7hYb0ZMpJNAf9y/ObhoZZgCEujGhqqPMZJIJUQYFx6G6Tfl7DvNjKxT8DMPa2jZyCKUyF6u2CLgFd2x3KJ5OiZ9Ofy21ZATHCOoTYx6mszvjXRqnhhCqR47sHpTkvy1hdtZxx8+RjWURBgpXyohvsX7GX6ftPR//OMfhsvl0sZ0MtKSJ/1oNIrf7+ef//yn9jKR9wvIGBgY0IVWnnIDgYAGRfGeJi0tLYyMjODz+RgdHWXHjh1awis+Jvn5+RQVFfHtt9+yZ88eHA4HN910E5mZmQwPDxMOh0lLS6O1tZW2tjaamppwuVy6ULe3tzNnzhz9tCwjO/HH8Xq9moMEquj+61//Yvny5SQmJhIMBscZw8ViMTIzMxkZGeHyyy+nqKiIFStWMDAwQE1NDZFIhKamJgKBAPPnz2fu3Ln4fD49EozPVhJAlJmZOS6RPCEhgQcffJDq6moSEhLIzMzUii6Rtw8NDZGVlUVvb69+ih8YGGDy5Mk0NzczYcIEhoeHSUlJ0R0nt9tNZ2enzj+TEeXBgwd1TpiAwdzcXPbt20dRUZGWaUs3Qjosg4OD2itp0aJFBINBnnnmGU4//XRqa2s1eVoCY0F1LdLT0zVpu6OjQ7sfAxQWFhIKhZgzZw4/+tGPNHjp7+/X4aZ+v5/MzEwSExM1X0gcoHNzc/H7/Rw+fFgDpJSUFCZOnKjBRFtbGy0tLbqLIwBAAK4AHgEq8W7SMlqS6z07O1srCOXz8nr86EoAUHxnSUBQRkaG5gCJAEDI53JdyDWTmpqqQbTwgwS81NYqoWf8qCwUCukxXnV1NXv27NHrlg5QfX39DwfwzMWYtFvVyXmgCagBwMcQ/yKFZUYrdsoZ42rzXRMV+NmPuoEuHYIjKYplOxGFmOZhtWiOodtGvkU2XSw+5lfAy0wjqB2Tu3EwwmzgIg7zW3rNxT0EvGwzGEuAkfPA9R4MG+uBQd7lat4F3uReYBOH+Yr/Ar6eayCJn74gdCegRjqvwHWPqFJRATz9BrByJrQe4KpCeM0LaX7VJJmIqjuJwO8MGwunguRQ/PQD+H+vwd+vgotewkI+E+Hvk2A5K+C8t1n8kTrWkqAkfisSEfmYsRtj+1x10M108rvOgUfNLsLFrOUdziSBrxmNRcBxH6qaNaG0cs+pPflsBpy5Du5fqRDry3DnOnjsbXNHBFG9ANSdC4UfWS55vwR+AdM+tHGIT7BkQKKT3gj8nds5yLuIBgn27FXHM/S8On9bzOMl/jb7zSHRGDMRdtSJ7OZ35q5OxXIuvjQKiVcbFt3lUqDgSZz8hnuI8TgwwF2cyGoqsFy5G3mbm7mENbjYyjDzvoDQYnBzF8tYzftcz82s4S2gBw+QaAKeCVhnpoMEugHV+RmvDSsGDmM3AdEYKdyDn4fMztEEYrSZSeo9XIgawlaZB7057jj+DYUwhQG0HNZ41YGch2X2sx+LAgQKrHyJakkKAWqrAKBZcS8+YB6Rd3mQ+/mdNJVCWF0f6fJ8n5HWv/71L0PIug6HA4/Ho588Zazz+eefc+jQIUpLS/XNNv5naGhIh0MWFxdrjx0hJot3Snd3tyaOJiUlUVtbi9/vZ2BgQHNDxNNkxowZJCUl8dprr+Hz+bj22mt1HpHIjbdt26ZlvwcPHqSgoIC8vDzC4TDhcJjKykpd+F0uly5w3d3dlJWVEQqFSE9P1/lfwtkAdOZWPElUxnirVq3C4/Fw8sknM3nyZP1ELiBEJMsyyoiXyQuZNBqN8vHHH7Nx40ZGRkbIzMzUrs+iLhobG2PixInalVoCVoWYHA6H6e3t1RyktLQ02tvb8fl8DA8P4/P5NLeqq6tL55N1dXWRnZ1Ne3u7jhNpaWnR3i2NjY0UFBQQCAS067aAHCEFd3R04Ha7Ofvss3nyySfJzc1l8uTJ7N+/X5/z/Px8WltbtTuzjH+EjxONRgmFQroDeO211+pCLrEW0i0UwrOM1eJJvaIojEajfPrpp0SjUebNm8fIyAgFBQV0dXVRXl5OJBKhvr5eWyTI90I6Jd/9nggwEnAUTxZOT0/XsnJAX2MCgjIzM8cFf8pPPOgQR/G0tDSd1i4jJ3GXBvR3U86xXGuSXyZjNIl4kQcT8aqSLlJ7eztfffUVgUDgB9XhOc6GcT5WPUwFTidqqlQSeIVEmg0bTwPDrEA9m4+gmCViqr8TyIfdS9VD/aXAhUEIetChV+cDjm2oO3sAeJpsVmsLNZH/Wh2C07mH9dzfA6PJ4Gw2FBelAFWc70GpjFgOXEcHX7HffHk7F3I77/EUt8CUZ2EQsltVkd6WBLGL4Zx1al3XoJIUho1WaC0gu1DtlZBvZbQkhnN/PdtmuR9eA2yCC26H97kXbr2P7D9a1Am3uW+9qHVfCyx/FRJWJTEYG8ZVB2TBmBPWpcMlMWWgWIWV/PA1KoexhFauAX7PLVjp8/eYZ+45tLtMcKVCh0/4KbF56QCGzwJWo+ZGL5mn64l6tfKzPWoR16C4Ib+GU0ptfE0fak8eN/8osK8I+B/OYTdLgNvYipF4EtwGIw+C8x14/DIFUp9BdW2aUETZheYxXIhFM5Eumm8IXkuBa9cbFvXJcQQrBavXXJpKD0/gAZNMLML3eTzG/WqiNwSXpsA7VAIVZlSHYg05ORwX4SBnSFyI41OvwLL9kxwqUOgBLKmU+CjPI40NmrLcCwzzZdxexmeuS9/uRhRwHYT3CiyzHXF3EPMfyatYaK7+XcjerbpgjmFFPud3mCaYqO0Nr1SrLBgFJhDr92N/Ju6A3/49AM8XX3xhxJuSiWmgFO1QKMQbb7yhb/wOh4O8/4+7Nw9vq7zWvn+yJluSLU+y5XjO5Aw1iQlhCkMDhNAcoDlNXiBl/KBwWtpC6UvD8AGlQFOgPRTyQuG0QAlNmZpyUkJSUiCBDE0hzZzYMRkc2/EoW5YseZJk6/3j2evZ22lLv+/8V/Z15UqsbO3hebb3up+17nXfxcW65Vq4A9IW7vF48Pv9DAwM0NLSogGOuJNLZ1FDQ4NuFxYCrpTM8vPzyc7O5vTTT2fv3r2cffbZFBYWkk6nNd/C4XCwefNmnZXq6+tj586d2lZBNEukNdftdpOdna2JpyLOJmapsmIXArGUCaymjLLKjkaj40oywuFxOBwEAgEdkDIyMsjOzqa/v593332XNWvWkJubi8/n095IMqZW8CXZrqqqKoLBIMXFxfT29uLxeBgcHCQWi1FXV0dzc7MW1pswYYLurJJshMPhoKioSJcRg8GgDp7AOLsMud/W1lZyc3NpamrSfmKNjY04HA4NoKQc2Nvbq3V9Xn/9dUpLS+nq6hrHZWpvbx9n+2Ht6pO5FE7QLbfcQnd3NwMDA5w4cUKTvaVUKcBJ+C3y3IlicjCo+lL27dtHeXm51mqaMGGCBpkCJiKRyDggIpvVhkF+BjTRXkjNYPpiCaAQ7o9kNaXNPD8/X2eB5DhiaSFdbALcAG0qK6U26zMo1zM2NqZlEISjZLPZdHYnmUxqjy/JGAnBPplMcvvtt39hAM+1NtKSlFGmCCpz66KZPqaQvwD40xmYuQ5lukDbIh4ttbEQFRLXcB0wHxpvVpH65kbUC/5FTOUVw1n9QMBof/bhpIXTjZbtScaer0oJoOmv1Ffb2A78wpYmARxagTp+HvCbt/S3NnMa5ZhcjHuNs92zJQ1LwR6Dq4dV6PrlOUAnXNZkVsdeux/48SB1NiXlv8egaFz2soIXA5jCb5tOopzgN/jVkMRRCKVTdbd1lMKUNjiSbuIJJrJ8ISrOzQO+BsmzYK8LTjP4Pzsx1/xWsPQ08BR+oIJfcYBbuYrXDeHDB/kz8DbZ/IzYlrS6SInXFUDW/XDaCr5zAJ79b2DxINzpUfhAerJ/8zDc8jC4wP0CjNQC+6PwEz/c1wQUw2oPXLcSMxXkBKqA6VzMFi4Flt+FSfyKQ+sUk76VwGxDD6La7x27jAE1TNOOlcCk18D29ePGhT3EUlazhnNws4MRqjHZuQsZb9QAksZIDu7AMaQApD3nZuNzeSL2Gd+/wvh3J2ZK5e/1dkt/N/ytO7nsI9T7uHGX9ZaZFLMK8V9bjmmjG1djO+RQu9jb1L67AmZJ6ybLKWROE8YppDESdagzG00PWBeGovZ9bagndq76dINDZXnm7OIhzuBH/5MurR07dqRBabdkZWVp/ooEhr6+Pn73u9+RTqcpKyvTbdHSvl5YWMixY8dob2/XIoUClqLRqBYaFHJolWFw+ec//5nCwkI6Ojq0gJzomBQWFuJ0Ojn77LMZHBxk2rRpmk/U1tamCaFbtmzRrchut5s//elPJJNJamtrCYVChMNhrrzySiZPnqytLqQ9ub+/X3dWOZ1O+vv76enp0WrIQv6VbIOsomVFfujQIWKxmAaJAPn5+YyMjNDS0sJTTz2lNYFOzYj5/X5NqJZOIbFGkOxXIBAgMzNTB3EJ2GK26fP5CIfDZGVlIbIC4mZ+4sQJJk+erPlTu3bt0maaU6dOxe/3E41GNQgdGhpiypQphEKhcaUYAQZCmK2srGRwcFCXB4eGhujt7SUcDnPkyBG2bdumM3syrgJK5HMhR5911lmaq9PX18ftt99OcXExR48epbW1lVgspsuO8h3pVAI0qJIWfYCjR48ydepUCgsLtfWItKAHg0H6+/s1KBEPLiljCTdMgI4AYQEpVjNO2WRfAXECOuT3ycrvicfjuN1uDYwFEEm5S5ST8/LyNBlZPNBEtNFKvB4eHtbEfUArMQuQF60pAfd2u52TJ08SiUTweDzcfPPfdxr+V9wespGejApIs4FyOkjhx0GIViqpiAD+W1CRch5qtV0PzIXQw2QHbIQMs85bEQNLoe4eQwWqx1Fky2OwpQYuEFdqJUpYSYjpqPJGHqri0kEtcDtL+RZr+CZ1tucB2PNXFBJYAiz+N1SzdwL4OvV8wPRPoOEspW/zk09g51lwZlma7DZTazYBfBqAr4dUSFiGgmWHRKDvLAWQxhwwI27yTeKo8HUMaE5/DI0X6kW78xIHg4OjOG7BLOHFUSf9GqZZkhdGzgV3NwyUqDzZbMAxisr4APjgjRJVffoTXsZw8HWihFGSik8CK3FjZ8RQk35EjdoHJ1W705uNMLEGe4cCea+lQ7AhAIsehjsf5raV8MvrjINNUVM55S04cgfwTBRW+tV1r0MF3OXGlPepk9e9D3vOMabvx98CwqTvecsUTwLTT8KKIdYxjkQ7sAq876AyUo8rF3myHqaOH7F7E3z3IjU/omj8hjH+cSCmNaAUWMnmZfYgOZtqlILR25hks3mYBGMroeVUk04BOlLK6rR8blUWkpuTDJDsI9ahPrRcMrehCWXMgrYVCrSL5oO11Vw4csLriaupndKk/tnhV4e1H4KiYeg2ug3tR2DisJnvkkJkK9B8FWYSsF79R7qW//+A59NPP00DOnBat3g8zoEDB2hqatJBWnRdhBPg8Xg0t+L999/XBNVkMkldXR0TJkygq6trnILzpk2bcLlceL1eioqK2LNnD/39SoFL+AqZmZlMnDgRm82mfZaSySSHDx/Wrc8NDQ26ZCUWCW1tbdrNGlQm4cYbb9QlACk9pFIp8vLyCIVC4yT7pZW+q6uLkpIS7Ha77i6S40n32HvvvceGDRt0mcLaRi6+X9YyhZRFrABIMi5W/6V0Oq2J4FOmTNGdTlJGycvL03wl4ZNIZko4MpLNKSwsZNu2beTk5JBKpcjPz6egoEBbR5SWlurSXWZmpuYACfm8v79fZ7AEoLndbm33MDY2xqFDh8jMzGTPnj1ajFFAghVIpFIpKisrtV/XZ599RmZmJpdddhkzZszQ4FeAWGZmJvF4nEgkMo5PJJkzuQ9RdxaLiHPOOUdfu2SuMjIy9NwKcM3MzNQSCFawAgpAyPcE/Ah4s6oZS5ZGsjAyJvIdAc4y55KhEnkD2UeyT5K9kt9ZITnLAkMySKLhI95kVg6PgHLJKklZVsbDZrMxf/78LwzgedtGWl7Rc41o5EA9KyvI4cH0CmC+4uz4P8ZULTHE+A+UwnbY+E2b5lVcNAhpB0xxQfOBtFnXCQL+1Ti5ydAsUfJt2WzhTFTuYADYqv23ZgB74dL3ueh92DQHZW++EVj8FiocLodGBwRhld9GCwpALBiFZ+zqKOdxnEpbNS0+mBtXgWBbDTzYqOLOEmMsvv0+8Drc9DKs8sEDcVPPB0y6qAt45acwepuNjHcx/RGMDIchp6s2IXVL2kY8IPehotNOOLYUqg0RxTGHEhBMemG9XRV0bkcBsnXGqLSi1H7u4a8oOcBbgbmwskZVuSKr4YzrqNtltIqnN8DKReIEIRZY6sZFe2ku2B9X1zB6vrGPqOvdikKifca+2zGRx4fgrHGQZAnpZW+ZDvGCA0QpWP7tg5Grwf28cfx64A2w7UiD/0JUNmSfMUhvMIUm6g3y90ZMrzWFkUQg8EIeZYMuUF2LlzHuxiSZSRfVDMvFdWKq+8hmBT5W0YEgpuaU5FEEKMnkCuvYd8p3pFNLJn+j8f+T1MPxI4+ZAE1YDrs4pbohg8bEr1OHWvqWqQougsy/x+SECUAUlWuBeQnU79ZeYNsKSN/39wGP4+99KJsEY/k7kUjolzUoUAFobk0wGNQaNvIiFULs6aefjt1u56OPPmLWrFlkZmZqnRJpW96/f79+Yft8Pvx+P6WlpbrEI6vd7OxsQqGQ1lmRcoIE7p6eHi2OaOVySOBub29neHhYt2Tn5+cTj8d1OcHn8+lOIAn0wk8pLy+noKBAZ4WE1CrXLavmSy+9lMrKSsLhML/+9a8BdLASvRYpMYkIowgbApozJS30AiKllDE4OMhnn30GgLWTTq43Ho9z5MgRbQHS3t6uibzhcFiXFqdNm8bJkyd1O7WUYIRHVVdXp0GdEIKljDRhwgSdrcnJyeGzzz7DbreTl5entXrq6urYt28fHo+Ha6+9lk2bNtHS0qJBhpRhQGkkdXR06MC7ZMkSDYqFjC06TlLukYAvWknxeFwbzQofRmwgxKPM7/frsqLVBsLaRi73IZ5ect/WkpVs8jti5f5IZklAiHwumR/52+qHZe0mFICcm5urQaUAKAE0kq0RkUspZYnH3djYmP4dkN8hyQZKZkzG0LoI+CJtAnbUC7ODOJW46KWVEh4MgG6y9ldAVFkOkF9qSubeDnyziYXcDLSQfuQDOAa2VT8FZqiDB0IQAH4WgLs3kqQCFXkrYMPHnLnIpjMvpjjcZMAJ0fdZ+r4RRoJon00WbwcuhzaHyiYcg4ZFKi7Hgb/albYNwKh3ImWkcQybruo3NSowswwzHPIQ8F+w8GV4pRYezYfn1issY/CUdU7grh+A/cU0HL6Q9LNb1O1IVUOyOXmYDpHzMIO+Fw2MBpbCpF60mmCGETvtNTDdo8L/AGYQk3b3nYACBFtwsYVD/BDu8MGrd6ub/gT2lEBBCHUhfShTsG8Y17LTOOd9b8G0qyABucPQezNqPLswKzj3gnMfJKej/C46MWWvX4TkpBTnf9OG7fVFpBduUAMlCQ2Rm7HgBPf9mDzoPrDV/wZ4y9ixD5XPOQZcwxFm4/SoTqTzWUs5Csz+5CQ8GogaXXAbtI5OGIyOKGuWxlquKjYvhDCmm5sI21gzPAJ6vMYsWMVuBDRh3KQAmjz+tuwl5Tgn7LpKHeqCQeBt+KFh7LmyVD1DgpsaHKZFez4KdG6HNS+hWwKzr1d0tgcwTVmFaSRU5hcxgfojxsguvB+4j7+7/VPAY5W+l89SqRThcJju7m6KioqIx+O6lCQdURKApNxTVFSkXbUHBgaor6+nvb2dgoICTj/9dE6ePEl3d7cmpkpHzYwZM2hsbNRmpUL+BXQ2xyrdL8FeSjtCfhWRQrEQiEajRKNRXnvtNW6//XYAbREAaBdw8euSTA2Ax+MhHo8Ti8XIz8/X5FkJSKIRI51A99xzDwcOHGDt2rVawVfuU7JeVt4JqMDT1tamsz+SORCyuJSShDcipQ3hPk2YMEGPSyqVoqamhrGxMcLhMIWFhXi9XlpaWiguLqa4uBiv10t7ezvFxcUaiInqdG5uLvF4XJctbTYbPp9vnAWE0+mkuLhYPwMiuBcKhXA4HFRXVzMyMsKiRYt0t5DNZuP48ePs2LFj3HwHAgGKioo0qJNgLMai0tUnZTEp+QjgrqqqIhaL0dfXRyQS0QDKKnIoPCMY788lgEb4V6LJJM++tVNLFgJW8rpk7ax6PtafpbPLejyZbyF/i5K3x+PR2aFYLKaNeuXccnx5PkU9u7u7W+suVVVV6ZKm7CsLl1NtOgBdgv2ibPL6DmDMD2NAmHpKoHuX4dRtRD7/12CnB9aBswuS84GvApOqYd5L8CoU7oLeO4Ao4G+E6h0wdI4KrnevRL1+r0C92SfBPBU7l+0jc4wAACAASURBVCOKxeegyhFGVF6lrrMe1II5H4UCcMGBBQqNGALHj/MS6U9u4dhZ6mXfVQK5o+D+DXT8FbLPgH6H8pdyAb0BIKRi/yTgvB2w7T9U8Pj5DrirBr5dC+8cUKtpKWcJVeaeRnjirY+xfaeNeynjJ8LhXmbsIG358zEFdiTjYyAo7yfGvhKXDZKqwweuKeq6gqgw3Yyfp3AB8/gea1nDdhLAEWqNg9yoIhphVdqaDL2/BG45RwHTvcb5/x/M8tMHV8E8OPNl+PSbcNELsKkG3I0wUgMFjdA7R831ee9Dw0Qzh3FNCJ4IA0tgK4eBzdg2fg+ASi7lKYzutc2YrWkiNlQBOesgRi1TuN5Qqh7ABAjirS661/PYaqTQXrM/ibuyjV6gfCssPN+kUrUCv2IXj7GLZq1abPWREm6N1JCOWf4NZhbHeMY0QEpYPhPZQqvSn1XyWICPfE+yPcCcQYh6FDeK60yxn9nGH5GXfh3T5RRM/HUUvTKIvQSPGtjrzFuUVqTQr+VOpGrWiRJzFErQP9o+t6S1e/futJSXrGTQwcFBPv30U9avX4/b7aakpISpU6fqluORkRECgcC4l6nP59PtyMlkks7OTtrb28nOziYYDPLee+9pI0ZZmVZUVDBhwgReeeUVCgsLteO6AIszzjhDBz1xIpdMiXSXpdNpIpEI3d3dNDY28sc//lGXpyT4PP/88/q8AkaGhoY0UViCe0dHB6WlpTpL09PTQ2lpqQZDooki1+BwOOju7iYcDuP1ehkeHubJJ5/UXURZWVlEo1ENIiUQS8ZIrAMAXcbJzMwkEolocrDYEUiWTbhW5eXlOJ1OhoaG9H6TJ08mEokAEAgE2Lt3L6WlpVqFuaGhgcrKSq11JDwk8T2rqakhFovhdrs5fvy45hNJ15AATFFRljJcf38/LS0tNDU16RKNZEzk2ZLykgTzvr4+/ex4vV5dZhodHSU3N1ebhUqgludYxn1kZISMjAza29vp6urSc9bV1cWECRM0p0Xa4mWcZZPrEyuGWCymOT6SoQOzi8tqwCkARxYMco3Wz+X4Qky37me9X/G5kjGSzJO0rQO6G1H2EWAjfwtPTtS9peNO7tOa1RobG+Occ/6+0/C/4rbZRlqtMXsZNtaHLuKsJIfWtM3gjYjC7AdwrscMXi2q+6k3ACRgStR8ze/IhNGhn6GcyOdAAkr8Njp0l9FGYB6M3g32JtYxkaXACD8Evg2jAbB/DJdeyHfeVzGgYwUqDi5qUye/+hwzV/9fQPUG0gv/7W/F1hqA5TDhu2m1jvepstHoxXDmelO3rRh47zqoW60sBhqAWwNwZkhRIBowEzjiBeUDfpk+ALtq4VVIp2wqSM1HoRWRSJbqRzkGKEEBNdBtXF11xqJexOQkkWDo26WugjUeFQtVW38tMznAZ4Zx5Qg/hQ+MDM8lKZjoMEuA84Aao+vp0vtV4NyDIgTNAvfVMPIx3HYh/NoBmSmIrVDDnP0CxALAbMh+H2K1MOWAwkxvoLDUAw5IJu/EFDjYh+kz/g10Ood9SL/1FNZqfs6zlBoDNlvdrO5EE7iXRIMGHdJbgY1cyctaUuEbvZjqiNPhqzNNkNrBYsaTja01JCHQCLJwYRaOii3fszKGxdrWWtqS7JB8R707GPWbz6XIPYsdu3wm4KfVmK+NwG2qEysjBUmhLIknqFTg5ht/G7bsdU1qASF3ZHV48RlffSr9PyxpAdr/KCsrSxNpT548STAYJBwO09vbS1NTky4TeTwevbKXwBCJRLQSbyqVoqysTPN8pKvJuoKWTdLuEiAyMjLIysrSL3wRGRSdkoGBASoqKsa1AUtAkdS/EGTT6TRer5d33nmHZcuWMTg4SDQa1UFfSmNSDhBjSSkXZGdn097eTllZmQ7ukmWSrEJJSQmNjY2aF/SjH/2IgYEBOjs7tcaKdBvJWMt9WVujJYgLsJAAJ5kAa3AVW4nMzEyqqqo4dOgQNpuNjo4OsrKytMu4yAzIdQiHSLIiGRkZ5Ofna36M8K+SyaR2aY9Go2RlZZGTkzNuDqUEKt1IkyZN0iWnoaEhTY4OBoNaTVtAiXSrFRcXE41GNbgTDzUBQsPDw+P4MJLxEr5MIpGgpaWFVCrF7Nmzsdvt2hIjFApRUFDAwYMHKS4uJhgM6hZ46/MvGkPyPFkFA2WfU8UI5Zm3dk/JZ6dyfawEaPlbMk3xeFzPrwBbp9NJKBQiEomQTqcpLS3Vv1d2u514PK6vRzKIQvIWk9TMzMxx6ulSXhbV7i/SJotugCEyyOMICSp5CGUTUEKUi4mylx30ci38eT6svUPLCoej4A7ByBw4Ug7jyDin3W02rTx/Lh1ch5l0N7pm9gL/Uc3mv8KooYBLNKCC1tELueh99Y2On4KW1aUTfnSOepNLVqS6CfCqt7yYIUlAmQ48BB1Xgf0dSPth1KBnfFoNFzWpr7yfCba1CtRMNr6+NARramH7ATVWkzHJy8jdXF0Lb6ZgwIHtyTTUT+RRmthpjO/jgLdZfXFkGnxsV6F9Uq85D2NOdTvbgAcfWowqViRQA/EqDtrJYoQBQ/slyY3AZpYDN7KVizmXD5mhIttOIOpQfqEyPg8B+TXw/GSFMJajMnCuGngSRu4ANioy89LVsCZgjOE6iPtgSghueB8ezlRj+gBqnCahCOJ1Kfj0W8+oy665E0FxJaymg1ncxE8A0y7Dh9J7eht1yZfRxntUMJOVtAAxFmFmUwRQCCVXsirTgee4AnVLjwENBTD9SgNvNqtK0OVrjK9NWsvbdaoBSh1fnnwpcVk5OFKTFEQS5G+BjnxXkIxkh+QZB20dkbDsJl4WVkVyqY6tM25TBAP3KNHM0VcVMdnRpAB7OstyydK+vhDYDPszYdnF4NwIhSkF1ostu53HP94+F/DIallejIDOZLS1tWllXbEH6OjooK+vD6/Xq+0h5OUejUbp6+vD4XBw2mmnafNGl8vFli1bNM9GUvsSYKRlWnyb5IUs3Tayj6zGhfAp1y2aLVJCktWypPNTqRTvvPMOixcv1mCst7dX21hIoJJsRm9vL1VVVToYZmVlaaBjzRLIz+l0mtraWm2fUVhYSF5eHqlUit27d+NwODQokCBoLV1Zu6IETAg52JopET6KzWbD7/fr65W2/mAwOI4fIqUgAVVDQ0OUlpbqFngJ1AJKRkZGCIVC2u5Cur+sonzRaJTc3FwSiYQeawFSw8PDzJ49m4MHD2rgIPo5XV1ddHZ2ai6Ty+Wivr6eiRMnkpubq4nkAloHBgbwer0622e32+nu7h5XlrFmLuVZGBsbw+v1UlNTQyqVIhKJMGvWLFpbWzl06NA44rZk06TEKaVLeY4A/ZxJJsVaarICIyvAkXIk/G1569Sy16kLjqGhIbxeL2VlZYyOjjIyMkJPT4/mQ0lzgc1m0552kk2UErO1RV7sOwKBgO4c+6JxeMBcN6vNxT5cxO4H8NHBZEIc5MeM8CJrOUIcFm+GxUpdMM3XGNnlUEjAfyHprVu45Hz4sDGtVqjHgN9CNjuIMQuTOFoOzId8mLlLfaK0URJmLNmpAEMXUPID6HgGI0ZVwCpwthqr3gRozeMEKqrGjVMMoN70wKo3bdycldYxdOZ6OLQYZjUpsHH1sDILHXkWOheow8wF/tAAd82B13eZ7dZh1Np9AOW/9fs3nbgugI7ONLx8nAdbgR8W4STMrxglWek17i/fuLAkzoJPmcDoOJprJ1DAWmAtYIpBiqj1dgboBO7hZW4DbqQW2MeH+Pk9/8aSmgjs84P/LVRd6ym4otbsW2aWuvhy4N9r1HQsBOeTRonSmDJ7DCbeqYDdZON+NwKjVyri7L3Gde1ZDGeuVSDmohdg03SgRkCAjw78wNPEUZU+EZLch3K7vy9HwYNlwId8anirzaGODRoHxLgKB38gxemYJSpF+j2LLWAcby1uUnzXeKJfZWllm9pzKUwZBMda+No++Np82Fm5AYD/jeg+zcKsK0oXl5SupG3dh+m2JRkd2X8y5iYtaoZyYNjyFRgPUoQX7TO+diNmd5byxVCXcgWMAqPTgZ3gXgmTQ/CZw/gdiKOydpNhtA6oV8T3RBSWGCXKyahc23T+8fZPMzySuYjH4+Tm5mp+DZiOzp2dnXz88cd85Stf0ZL9Pp+PSCRCRkYGkUiEvXv3MnPmTObMmaO7R3JycmhtbdVtuFJWKi4uHtcVJp1WArbk5S6BRDyI7HY7BQUFGkQAurThdrvp7OwcZw0hGYXMzEwaGxs5/fTTdQZrcHCQwsJCnamRrNCxY8coKyvTQnvS+SSBWbIkUvoTgbtEIkFTU5MWBgwGg8yfP5+XXnpJk4HFX0wAlARRATbxeFybsKZSKZ2hGRwcxO/3a1uOzs5OysvLdaDv7++nrKxM800A7dIuys4DAwOaq+LxePR9xGIxkskkXq9Xu8Kf2jEmpTgBvkIqttmUoaWUpcScUvhTiUSCTz75RAM7yWxI0A2FQmRkZNDW1kZ2djZVVVU6yxGPxzV3SAjrcu7e3l5NbBfJBJkTObbD4dC+adnZ2cTjcXp6ehgcHMTlcrF7926ysrIoKCigsLCQ0dFRCgoKdHZMSlHW7icrYJHN2p5uLVNalboFsMqxrHo+8rmAFLHzEIVvaU8fHR2lvb1d20oIGb6oqEjPg3CE8vLytBXIyMgIsVhMZ/GEL/VF2RQZtpcXKeDW/fDoaZWq4vLjlUCcDA6TopDlS9pY7gOWfcCfLlMBbw/nAE8zZc4OHsBYf8+AD1mvWseLoWAt9PpvIcZPUW/luagUxBXANVAdopMA24ExJgL7ICsE5UqBVhqKOqSqNh/4IEBBk1FKk0jKEmgsNf1C8zEzQNOBINwwA54chkNGfPICJWtVnNHr91nAJVezmTeZa/x4bwoeTcAyP/xKCZwbTBqVoPICc21pfpm28dBVNl5ZnVZR/PJuqt618dm3gfCAwcOOQmuTurFjGOQhDJKSui4dW4+qCxibruwqCMKsSjV6nxq3dYT50PZNKG1gCZOAFkjUGge4C2iF0k7YuEAFzsYaeH6HypC5UDhxD4w9peaL34TAFmDMoS5j5H6oXwm+uCpT3vSWGvIlGEybtWYS7fdAyZ3Q4fsp3Pw+iiXtYhVtWne4GCFcw64cuBSV5fnLI7DkoVEKAGjhIHaS+JhClBm8hQv4C58CkEMT+eygCTdfQ0GgJJDiaUwE8QBr2AjM4llaudjzMl/+ukkvXpgA5yuwJYFCDsUf8Kc6WMg5aO2acVkdq2bPqXo9+af8nIdmrg95/rZsJSkuAUIDmILMr1tOOwuToS6lTYPiNLICDhkAasrDlgTSLhOGuYDmxcoQ2GfM0ZOo51Z+TU7dPhfwWFeZ+fn5OjAdP36ceDyug2J/fz+Dg4P84Q9/YOLEiZx99tkkk0nq6+vp7OxkcHCQGTNmUFFRoTMnslLetWsXOTk5eDwefV4RW5OS2JQpU2hqaqK/v5/s7GydbZKWY1nBnmq0KKv4VCpFQUGBbjO2ehlJwHz55ZeZNWsWbrebeDyuy0zWVbbb7aayslK3lUswy8rKoqurS2d+RP9FyjzJZJJJkybxySefUFZWRnt7O6WlpTgcDm666SYOHjzIqlWrdLATEKYnyRgLybpIucva3i4GoJJdCYfD+h59Ph8HDx7ksssuY2xsjI6ODj0PkUiEyspKfa7+/n7d9SSZEis5GhQQycnJwW63a4K0iAxGIhHdEWfNDPb29uqsk2S6PB4Pu3fv1gRwIV9Lx5yUKKVF3FABZtasWeTk5JCTk6MBlQDcoaEhLUQppVIRb5SOKYfDQW9vLz6fD7vdrudJdIcSiQQVFRVaauHw4cMMDw8zZcoUACorK8e1nFu7tGScTlVrto6jAE8BSVbAZM3ynQqErNk8udeMjAw6OzuZOHEi1dXVjI2NafuTdDpNKBTSQo9er1frZ0nWU5So5Xetvb39814J/3JblkFWPgqwD+5mjJfJIIP7yWMAFzCXAZPtuF0FqUvL4fSZO9i9B8YmoVRck2B7tBbWLtLunL0rwMFvSfEfqDf4USAO0bvVP7d76C1VL+RsDhAjDOyFvgXYdqiX9nYwRZ33At8xSnEhOJ4Jo5OAUKmKZgPqvJqY4zT+bdAzDqXAmQnJhMJDyzCbkcqBkregI/9NXkQFBVnjX3YA3vs3eGy9qtooswE1LA0oAFBxfZrkf9mYd52NWxtVO/4JZxpb8nrS561W4zcfdbN9xpdklT8LMxga/x47AzL6IKMVnWaZ2wH5JWrh3wrMZCWHSicB25lilING5qYtN54Afg++BWriagbViC4/RxlYdQItSsvFvRpGFgbYUwo8AIlvAa9DehEsewumG8KNt1ZDZZOilkvRzQVsE5z1NjB3AdTCUlZyQzOMlIH7JTWY8+bB2yXj/S6ffkgNzXzgWUI0AFfg4giLMdknYaCVXuL0GmHdxwESCLf3VWPwlEBCAWuN/WbxIVfxIWFgJ5cRZbsLJt1mlL4+UXNw6RpIl++AnTsgDD98CB7hDkyxHB/jr9qa5ZGffZgsLyArBXEDRkiFzsv4rI+Q8VswE0ZHMbv9XChS2U5gqdrXvVp9PJgJRxarQ122Vh1mHaoMOT8Oc9eqq5+Mmq9fGH/+0fa5BXt5AYvDuXBYDh8+zODgoF4dChk1nU7T1tbGxo0b2bx5M4ODg3i9Xurq6pg9ezYFBQWaGCnE1pKSEgoKCqitrSUej2upfiGUSmkM0O3FhYWFWv1ZrCmknCVlLyuPQlbAwvk4tWwkuizicg6m0akYLUo5JBgM0tfXpwX0AM0rEp6TlDxEPE4yUIsXL6apqQmHw0FfX5/mZ5x22mncd999uN1uCgoKNHARYCb/FpCYSqXwer16HISsGg6HaWtr0/u1t7fT2dlJd3c36XSajz76iPb2dqZNm6bHVjJEdrtdz+Pg4KAWEczOziYajeoMgxDQhRQuLd6iXCyCf4ODg1o0UsonooVTXl5OMBhkzpw5LFq0iCuvvJILLriAoaEhmpubOXnypOZNybMnPllOp5MDBw5w4MABWlpaGB4e1uUtac8fGhqiv7+fRCJBZmamzsbZ7XZisRitra26TNbf369LqE6nk+zsbIqLi5k6dSqlpaXk5ORQWFg4rqy6fft2PvjgA7Zs2UIsFtMg0wpkrF111pZ0GXORS5C5k+9YNym9Wru5rJkf+buoqEiXjG02m87ESkNBRkYG8Xhc24bU1dUxY8YMncGLxWL09vbS29urPcy+WFuCM4H09YcIkcH3HHApA8xGBfY/HMJsWBF/n+2Gj9IxlX1ofQhsjy6G6H5TRqUVuK+IFFNRb/mFaP38o6i2rKD6uJlLjAO71D6T4Na4Zf08Dy1+V9KojpYHOIaNrwUOgP1qs8/eWqeTOASku20UptRnsRp1Ga/7zEX4QtS1H0q/r8UGg6gwWrkemg1/TpGXAbMLZtVqcHpOKjBUYwMfJD8Eyn6D7eG0NvXUTF1r0BM+7yw0OEt6FVDQ5FQfpPxQOWgKK6vb2kcluzhCrcKlNS9D2wJUusAw7xTTU76qzpn1MNxotK1XN0LQUFp2QV0b0KB2r2uCi94y5YXCwEwjQdUAPOGHbVcZzXSdqLb1YlQn2A8WsCaaxlZZi/skpubPk/C1PTDp2/BAsxrzLmNoulCls8v3QHIwRHrTWp5jNaYj7aUouvR8KjmgodAGg/81kxdwcyfPsdLI9XQaRxSl7+W8x308zgU8iUpEPnYWvHE+jF2q5mHnd9Qc/ehGSF+xkvQVPyC96VsUcL1x19LSbuUACTIRRINSUh5yqN0CKXM3cacAM4Ekkj1aI8HYWlAg/2LjNs5TIoSTUaBmtFIBnbq16spe96nPffHx+antwAUYZqcL+IfbPy1piT6I8A7GxsY4evSozjb09PQA6PKG8EfS6bReOZ5//vkUFhZqM0rh2ezdu1cryIp5pXRxZWRkaDVdIShL6SsnJ2ccd0ZalEUt2dopJcFFeCvyRwKRlTR6+PBhzj33XL1SFwKxBCMJuEJ4lZW9HKevr0+vpiUDJnyVdDpNbm4uZ599tnZSF6FAn89HWVkZ999/P88//7y2VRBSq5SKrPYBkq0QrRgJnOKHlUwmKS4u1i7wAqIA/vrXv1JdXU1xcTFNTU20tbVpcCWlISG/Dg0NkZ+fj8/n4+jRo1oKQMbI6XTS3t5OIBDQ8+dyuXTwBTNTKLYIwWBQqyh7vV5cLhfTp0+npKSE5uZmPvroIyKRCPF4nKqqKl2qk062nJwcEokEra2tjI0pTzGfz0d+fj6ZmZkMDAwQiUQ0ABNxv1AopM1ru7u7tdaT8NCs1ikOh4OysjJtyGoVPJwzZw579+4FYOfOnQwPDxOPxzWQsJp5WlvWTxUwlHKpPH9WqQKrTIEAdCuItwolglJvlvkCNKAVsnx/fz9VVVX09/fT39+vHeul1CVEcmum9YuwZZBimGJjjepiL5A8qKgEr2OUqSReSKNKMXRdBsWHgE64dim8xksQvRm+gopgnVCwA3qZjlJDLobLHTjefYQUL6ry1FxUDDoGcCMVfMAhUbNdp8LGixi4QBbRR82OE9H2UzZJk1jFWwo4VBifx1HBRYLIDcBXjUMZZS2D3qM1gIqBmT+AQ/kL2Iwi1nox23ubEypIfsM4tCzKJQSuspWyMP0RG/kyBYts9H6QVorG3wfbtDTJtTYclwL/icmVlQOIpqOxie3ErALwFSiSs6MNyIegB36HAghP87JR7CmnGZdSi65+ixI20MFrwC/g5hcwsw/71GBc8DG9b16oLq54PfatMHqFut/slWYzmVS+hPvxNXUJ3FWq5AkyDDG8WAXYK2D0OeN+lgPXAvP2Y8sDfrWL9KEz1GcimPQ0/OgG4FV48ufmvN5XZ+jxXQS3jMIs+7f4kzHer/BNIK4FIX1AimuBfcxF6c3EUX7tPraQDzzHFqT57QquAmZzhHs4wjpKeEEVWnOg+DJ1/jk3QNN3YFIHqn77e+hZBeRfDbPgsZvgQf6K2QslhGUfjHrAbuH6hVE6VLIVYxKO5RmQbnm5oVOeXdsoZLyntJL04xIHX6Op0VQMfMNYJDxaDa8F4aYdqo/AUK3iF0DB+/zD7Z+WtKRsJdkKKWG0tLQwNjameRYulwufz4fP59MdQZdffrkGJVaRN1ldi56KtFNXVVXR3d2tgVIoFMJmU07TAixEH0W6gKQTSzgwIs4npSW5/sOHDwOqvGQtG0iWxmaz8dJLLzF37txxrujCZ7GScKWzSoCdEKYBWltbNW9CskUSvAYGBpg4cSJNTU309PRQXV1NOBwmlUqRk5OD3+9n+fLl3H333eMCo2Qo5FjZ2dmabyNK1nLfkq3p7u7WDuSFhYXaBkJKdbt27dIZIunqCgQCNDU1kZGhHLubm5s1z0myb1IClPl0u93k5uaOA6qjo6Pk5+cTCoV0h5PT6aSvr48JEyZw4sQJrTEjGZhoNMrQ0BDTp09nxowZ9PX18dFHH2kByGPHjlFUVERGRoa2RhC+ivCBYrGY5k7FYjGCwaDu2AuFQjQ2NuqykjjSS/ZMsjTyfAmAyMnJITs7m1gspi1GAoEAgUBAd+4J2bmrq4vdu3eTTqeZOnUq06dP11IN8jzI+a2/XwIeTxX2tO4rz78A4VNbyaXslZGRoRcIIkHgcDjIz89H/Nw8Hg+tra0cPXqU/v5+qqurNWH51Pb8f/XNRS/bKWE6MMwk9c6t+RbrULhhrtrJ7LadBMfqjJXjq/DYE/CaEYC4FgV2DOfn3iWgwk4nrC6lbj10MkIHLSq1cgwIvAzX3AyN19FScz26bvULhWNcwEgpptPnQ6YAH8DhTHVNrPRww/uYb3+5btny0TZGvek7oewZmA69YZUx2oxKIs1CBYZDDymw8TVMnDcD6GuDNXdD589URcoqKyexi2kXsvDDNPeW2ii/xMa3X06r4P8YOK9Nk77BpjIgzxpfEuK19bo7wVcJN3TASJFqTT5WAJVZ4IiqLE+ZG07aVUf+vUCDQfRtrl4JbKeDc1BKjeIMuhP4rTGY24G74KoU8Dg0KJVnHoNt1erG8naoKVqGSkBUGN8SKaG72lQAHXkJmu9VAzj6B+B/GXNSh+oUexIjM+jCNvNN2Hs58FXSt36g7nWzOuDyW9Xzs32pmfzbCayzq/N1AVsT8IjrBXZiqvWorYF6djH9CIxMBOeA4ghJw7nods8A6gw/shiTgGvoYD7vsJlsXmChcZ+n5Sh8PKME4qsMn7lD5jA+sBkemHsGHIOun0OQxahJLjeycQ4TvLpQApmiYyjd7zLnUuKUn+tRpCSLvIJjWEkFiNWplFI7LYebi6omXg683gTfb4JXroNXXMZA/QL10FrFpU/Z/mlJS4KbvAybm5vx+/3U1dVp8qyUNiSAxmIxpk6dSjKZpLCwUIOXgYEBotEoLpeLnp4ezUeR7EwwGNQk2NzcXILBoG6Pltb0iRMn6lKW8C08Ho8mgsrKVjI9wi3p7u7WpR0rwVTuUzpaBBhY29AloAhAsurMWI8jwKa/v19r4FizHAKu5s6dS2FhIS0tLVrjRfhFyWSSBx98UAc+CcRy3SJCl0wmte6NZG7k+JKdEn6TWDJI5quvr0+LMArhWYQLhTg8PDxMX18fvb29DA4OEg6HddeXuLoLD8h6fdFoVHdTBQIBDZa7urq0BEF+fr42Us3Ly9OlwKysLK0snU6n+cpXvsKyZcu45JJLKCkp0WBVfK7EHLWwsFCXq0ZGRpg5cybz589n3rx5FBQU0NvbS2trK36/n4qKCs477zw8Hg/d3d309fXhdDqpqqrS2avu7m5isZgez8zMTPLy8ggGg0ybNk2LWEpnk2TApAOsqqqKtrY23n33XVatWsVvf/tbjh49qg1wT7VpsZbD5FkBxpXFpLRlBUCS5ZNjWFWe/X4/U6dO821mogAAIABJREFUJRgMkkwmCYVCdHR0EI1G6enp0YTs7Oxsuru7OXnyJJ2dnRQUFHzeK+FfcIsbDcQJomQwAHyHF9iOygNc85pl18nQWqcSPsX3qI8epBYVzW5XL1Vlt67evFe9D6Nz1JF2qtV5B5cAXfAGuFcAXANxcH5JYSUn64A+bjugjt8cYJw+fsFas5cmDoxmowLJG1jSLJjCucKDAF0WSr+yclytqsNYfUu2pgKwRU2tQBgXe2CVsqYQNaEGTLZMGPhVI1DaxOMk2QhcdrNNXeONKBXqT9IqDfF146RdmD4BcbRdU3mvMtbstivDTS0aFwdHCNwnVdanEynWmFkZOEYBO1BX+Sd1QJag+tOPqrsc8gPbYbQW5kO6FngOpd3TaXJln8BMyO0E7lqhxmifnO9p45TPGO1uLTBlNYpke686BXHgg1pUNN8HPI7tV29ie2I/b38fk0TVAvOehV/fAz85pJ4J6Z/aiZcrXQpzANyKn9n8mdm8CdTzBvDGFPhvO7ycow5Z2g+BftWefhbKOuzXQKQfMrjfeHCKgQeI8WfW8GM2YibetqPI2O8Cb8+EV38Ox54znp0uIA+KH4H0g2tJP3Iu6a1e8J+mLrA6CtWDau5Lo3rutGhz0HIiQcySLJKUo0F0ThYrvk6L8Xi0oIp7Qm2TbkbhM9WjgHDJamPSfoF65n68gplv8Q+3z83wALrtW0oejY2NnDhxgmnTpo0TgvN4PLjdbs3bqK2tpbS0VHeDCAgpKirC4XDQ2tqKw+HQ4AUUGfTw4cO6q8rq8F1eXs6hQ4eYOnUqYPoQSSDIzs7W4EkCI6BBy+7du7HZbEQiEd0NJUHb2jWzdetWFi1apMGNZABEIE9W2tnZ2brklUqlxmWXxPldZP/l/0EBmLy8PG3lEAqFcLvdhMNh7eSeTqd59NFHue+++8YFP6vzdWZmJv39/bq93KqhIv+WTJdcYywW0+Pr8XhIJpPj/M+kbCYgS0phwucZHR0lFAoRDAZxu9309PTo7jAxrLSK/g0NDVFQUEAikSAYDOp7zcrKoqenR3t9+f1+ndmTbF5LSwvJZJL+/n7y8/P56le/qoGcNdAPDQ1pAm4sFqOrq4tUKqVLeaFQaJxNSEVFBeXl5WRlZdHd3U1zczMNDQ163L/0pS/R3d2Nx+PRoM/n85Gbm0tFRYU+Z2lpKSdOnNAikIDu4hobG9P79vb2EolE2LZtG9u2bWNsbIyamhouuOACfQ4BelbNnlPtKKzAWojR1kwRjNfN6uzs1IrVwlOSTKWAXLFHER7b8PAwf/nLX8aR2P/1Nx8DqNJWHBffR9E9JgNbsMNRI6M1C7rOV1jigWeBMLzxK4Dfwspas8ukExU0twHMM6gON8NOpXKswvIvIK6C9Habh9gdavXqAx5ilAfJ01IkZ4ZUR5J4kc7FpOhMBrbNRsXP5cBLxi21ovirczGbagSxTAIeUxmTUYuWXOcQEFfBJB9I/xjCd6prmG0cwujaJhGCIz61nxgTCINDymz32Kp5Ir2Ld7akeeICGzcusrEsnoYlYPsZ2HamSU+3KeLKU5hkJbF+alU/V6geExrOh8kJ6PVAsfB3fdBaoK55I2bwu5c7eRw/vQSMgx5DZXk2I7YNGaxgLOsx4Hdgb4QHahSJGeA/FHfHhSJqX7ReHWUjCj411ysHr3nGz/sOQKwU+H+r4ccfw/wLYbU63W2N8Mv7jfu5IwS8DaMPq/PYpwNdLOFu+NUNmKQmgApoqoYtwAUbgHVcyQu8wyW8xwAq/7IQVWzbRzZRNqIa8TsoBa7gXl7gDINOsw6V2+rCSETmKDL+Xl5ghO1orhM3csjo0nqQ7zKTA3re9xnP3SQg/oSashkYBqibEfsv0jsPQL4NEvDd2+DZrMMwVGMiE0HGAnZgPG9HaECiu2jw/DNSip8Tjqv/3mcM63LjMKJJ3WBczmbU83nNAQXreq6F5O/v59BJ/uH2uYDH2nIrJSPh7/T19VFRUUF3d7c2okwkEhw/fpz58+dTWFioO3kkdS9gQLgVAgQkuyGtzfLCF5AxOjpKSUkJmzZtIjMzUwv/FRYWEg6HGR0d1eq0oF78brebSCRCIBDAZrPR3t6uA4eQl10ulwYHArrWr1/PV77yFd0tJKJ+Vg0Wr9erRfAkyEi5AaCrq4t4PK4VfK2r75GREXJycpg2bRpbt27F7XbT29tLSUmJDkoS9J955hnuuUctNa3t3sJDkUyBlUAtnUfDw8M6o+B0OikqKhpnrdDV1UVxcbEGNwUFBePKc6FQiAkTJmgxO3EQFwE74alI2VEIvwI4ZbzkXDJeIiAonWQi3lhcXMzIyAgDAwNMmDCBadOm0dbWRjAYpKOjg2AwSDQapaWlBafTyZQpU/QzI3IFra2tGqim02lOnDjB2Jjyc3M6nVpfx+PxUFBQQGlpKYFAgP3792tbju3btzN79mw+/vhjDdaENC3gPxAIMHXqVFpbW8nNzdV2GJJJy8rKwuv1Ul9fz0UXXURubq7WCZIW8IMHDxKNRonFYsyePZuysjINaAVIC29HQKuAdGvbu5VDJlINoIB1X18f4XBY6ypJCVZI5sIxys7O1iUwr9fLF2mLU0ICcBClEw/Nd5j85H2M8r8egt8dglS1Wuk+0IHBuYFlvKnAzmZMZWBROJPMkLzY50HVDjgybQEc/hOgXtY3As9uV+q9r1DNNpqAp0gY/78M+HQfuvSRj4orooPD91Bvdf/V8Azja0s7jeuRuoYF+IwO7YA7z9FeRek4dNSg23p5V5VqnvoPeDFlLrqFP2TvgDOr4dMmlQUQWJFAAYPJAFvmwAWN3EOSbTh54iob9/wkTfoZ4CGwudKkn7UpFLncuCGJ+Ya6odOQhKkogDG7ylbQaZYVi0bh8pPQWanmp9UY/gKi9FJq/LQdlW6RAdjHGKexmR3Ml84jfxvcWqouvh723A1n/gz4L9j0KmzaDgXr1XBdtlpd3nZgTSksbYM1S1COprcoB/kj1WryfnkNVE6D5o+B1QGYu199+UXgeSBarSxLDOJVCacxz3ictlZfBdUJ9fAwl3fYiZPNZDDKKLtJMZU6DmjTiGNAl2ZcXcPjPM7j9lU4+T6JI6M8NgV+MAoH9+thgHnw9MwDXMEBlPbRD0ANMW8Yj9A6oJkAKkMmkpPzgZ2U8BYdV/q56cooz6IA1/fWoGt//+cR+D+Tp0E+PHkZ3MPNUPs4VAR0KU9n9uT3RVJ51oYwYwvGzV4xUI/+742/ZxvP5lzjcG8Ab2bCe25YGoVjKdi7AdKbgW7+7va51hLHjx9Py+p+ZGSESCTCihUrtBbIWWedxdjYGC0tLfh8Po4dO8ZFF11Efn4+5eXl+P1+HXwAzeXo6enRgniJRILJkydrDsvGjRupqqoiGAxqH6OBgQESiQS/+93v+O53v6s7gUKhkOZciIihNSMSCoUYG1NO0MuXL9fEXskASRlBWn3lz3PPPaevMysrS5uMikCb0+mks7NTW05Yu2jsdrsuZeXm5urWZjDLWna7nUAgQHt7O/X19aRSKbq7u5kxY4YeewFaGRkZLF++fByJGszylVVwUFrZreatLpdLE4rF3kMAbH5+Pm63m7KyMnw+H+3t7bor7MSJE0ydOhW3260dxvv6+nRGT/YbGBigqKhIk7Al8yW8l8HBQXJzczXXS0qFZWVltLW1YbPZGBgYoLS0VJfTBIyJ/lMoFNKAUCw6MjIy+PDDDzVICIVCOqNmtVWQsqn8LJwaAT6Dg4OcPHkSj8fDwYMHNWE5MzNTP/eZmZnjxAIdDge1tbXs379fyyAImJaMiXQNSpeaGM1KR2BhYSFVVVUA2hLF4/Fo8vXBgwd1J6LL5dJcK6/Xq+fayvcRArPX6yUvL08DSSnxWktgkhGU0qEQtoXjde65535hrCXW2dT772f000YOFenreZTVzAfmPQIsgVdnqgCwBJg0GbgCpv4cjmxJq6X+XLTysnNAqbt2pJtgdbVKAcyJwjQ/BY3q/R1LN8EL1Vz0LRWGnwR6HJDcDTfV2nilKM3rIVV8OZ4JoyXoN/xdu8zuk33ALxUNi5/7bXzvCkyvJrFtkIyJmAzlo9jYW8G2JK14NK+D8w1ILoSvr1fhtQF4PlOtqp9OmaKAFk1EfrkYeBzumjaeLjSA6a39aHoFUAGj17HNbqMLWPJBWgGxi4HJkD7fpgLkf6LLWdpNVZCWITY8MMXw3+pDO5ons6HepbBKFyorJTqDLcAIi1EBWhgvXwWeZR3XcwUB4BvQuEKVpkRVcTMKjbYA3wPbGarzJ3YO3LXD4O4EwDYE6WrIPgCxOzCd1JcY43wElcVqMQZthjGQ+5sosVXTMcd4fhaiIrdM7J8HgQmkm6O8WGl6wt+OWfVrMe4qbBz6VQwFa2MOHmcR0EAG3Yx2DPC/S+A/DU7UcbsCh52YeKMVk2IzD3iQAPcS4jlgGDtVjBIGerkK0z9EBApmGDdfbHwuVp7fgyYPVH+M+RTNgA0BWHSnsc9yaPSYCo/fNyZQnmVJHxqLB9souOKm2f1CTM81MMnl8mvwnGXopxtX3v4/sZYQboW0tZ44cUJ3LcViMY4cOcKXv/xlfD4f27dvZ+nSpeO6eqQMIp1GQgIOhUJa1VhKUZIBks4mAVqiHQJQU1OjzUOthEwhmcomfl5CjBYir5QARPzN2g0j92Wz2di5cyfz5s0jMzOTRCKhVY6FIyTnkHZmyUgJKBEScXNzM+Xl5VoHBtAZCelA2rRpExUVFQSDQRobGznjjDO0bxOoQPrwww+zY8cO/vjHP/5dZ3XJMsnnMu4SzC6++GLWr1+vO7dkjPv7+wkGgyQSCSKRiC47pdNpbfY6depULT3g8Xi0AKHMm9/vJxKJEIlEqK6uJisriyNHjuiMmwgmFhUV6XNaNwnEkUhEc6Nqa2u1qGBmZibBYJCTJ09it9vp6upi7969mjPT09NDR0eH1luSzIhwgkQAU7Ib7e3teL1enT20Gr8KyBHCsrTgy7xLhk2AhtgzWDV0EomEno+Ojg5t2yCdhAMDA+Tn52uA3NTUpLNkbrdb885knqVryul04vf7SSaTNDc3a0Dl8Xg0t0r+X8pwlZWVtLa26q4uazZSnndrU0J3dzdlZWWf90r4l9u6EDkYH6uA81mtZQFFFPlG/HyHKJN8wFNgu+3HwK2w3XDRFhJkEDIahRPTAK5q9eKu8DOz0aQoxAx27k5UTJ0E+FJw5DF45c37KAipGHikGtxNMBoG5ipbCDAXvbLWZh98rxuzHgVmgBCraCGJivfQtZgXtBCSO4HpcNQAPF6U19ZoPWxuQncEyWFcwHfWwrP/vYGf37GIB1eq0ztRIU8sKTntfth/NWy+jvMuOclRylh6iY01Wwwez0Ngy0+Tvt2mUEQCU23XqmdnSDx7m5UQYdILbmOV7rwHzvo5DB+Cd2eqhNFkdVt8CrynUVMXjF4F9meBe7kCP98nxFOrV8B1G+CpRSaRKWi5hqch/QzEXkQLJI48DCUPq7nbNg9iYbhpJazyQfqnKPR1hfG32IsshJJvQcd1UGCrpuNmzKTTFcDij4EEGfw7NzDAKwSwVZ7DZexgjTGulYOKvzRQqYbkdWOIJPNnaEziApayge3GWLxbohJQuBQnSkjPwhX2Go/CPuNz1b23jJ/xX6TIBCqUyri2uUhwMW9Rbtxih1bQDgLryGAHY/w38F2oFtlFMcN6FRbFMaHZD6HG0CMIVMBvWlCwZDmmiJSwm8tJj57DyBR4PQQ3xk3NSsHzLZiUMFBA8S7jiM8GDCmCf7B9LuCR1bmsBPfv369Vf7Ozs3Ub8Zw5c3TpaMKECVoB2Koc63K5dMlKgqlkhgQgALp8JIRoQGdFZsyYobM08ke6dsDsWBHhPwmAx44dGyfuJlkgObYQbqVU8O6773LBBRcAphO71YNKyKrWLi9A36eAjWAwSFtbG6WlpVqVOhKJaK5LOBxmwYIFNDQ0aLG8v/zlL8yZM0eX40St+Utf+hJFRUW0t7dz4sQJmpub9TkleMrciP6MtFlL6z5AX18fGRkZuhQoujNCcJaW+pqaGnJycmhvb6e1tRWPx8PQ0BDhcJiKigotzlhYWEhvb68uIUpJSgQIhecj4yClnSNHjmjO0ujoKE1NTQwMDFBQUEB7e7sGdOFwmEgkQn9/v+binHbaacTjcRoaGmhpadEO9GLGKs+DlLoyMzP1/fv9fnJyckin0/T19RGLxbS4oRivSkbIyhUSUCvZNCsolefHOs7Z2dkUFRXpMufg4KDOvEkpS9zahZ8lmcfi4mKdiRkcHNSK5f39/boMJSR7gPr6es1tkgyQAPTc3FymTp1KcXGxPo888/L7IQAoNzeXeNxabP9ibHNJ0IpL0xDACNZheHEp7CXKbEopjrfxIH4Yul9ldFapbE73iEEeDqv17pEPAb6s9lmo9vOiXsbzgGcNnZLYYqhfq8pW3y5FRaG2FSxHveLPbFLAIT8KHS64fni827MP4zu/Bw5g+jVK97W4AggyGsDsfokDHkxvy2Vqv0+vg4WrjfMYWj5yGxKbJUC+AXDLInhpIq6Vx3k+E6YNw6Fqde2TgFUH4EYmwSXXw49+w+QfDpA+4uWSC2x86E0ro60XwbY1DasagSdJv/OyqeY3n/HWTQbacx9XnyULwOmDES6BnR9QPhMOoZI1l6I6do6xmiO0qC/Y4xC6mYLA9fTi56mmNFz378CtSuG6xqVufIZH1Wfmo7qulhmDEIdfHADnY9Dpg2visM2nSN6vrEeRlF9EJZOE5DOAsuqeYdiDPAm9C4x5u8fY1/6yMXEtjFHEKzwArOMoa5nUrC79WInBYUqAdw/46hRO6kIB5OmY3XvbMcs7FcDl70HqAtXp9nvjkvaiAI9FCUCDhC5DHTBFISaEilPCDjAeq3rgQ2qNB0hY8q1AkDEWGLMgHidCJpO8kvwsuSqDqMONqFUCKAQsTqFGHZklYN8MxyHNXF4x+tk34QMuxZ7l4PphNS6CV0XbcC7wYMg0YP972/8n81BZdba2tmoAEwgEyM/Pp76+npycHHw+H3l5eeTn549b+Uo2RTRxenp69CoU0MabokkiJQQYz02x2Wy6fV3+T1p9T23nFZKuZI327Nkz7n6sCrlOp1PvK6Coq6tLX3NWVhZnnHEG+/bt08FMAIsYOFpJo3JO6SLq7OykqqpKA0DpjhJAlpOTownLYtvw0UcfsWDBArq6unSnk3iNud1uJkyYwHnnnUcymaShoYHc3Fy2bt2qgaIASCl9iK3D6OioBlxOp1NnIOx2O+Xl5XocCwoKGBoa4p133mHSpElkZGTQ29ur28hPnjypuR7RaFRzlY4fP47P59NZIa/Xq8eqqqqKnp4e3fEmasUjIyO0tbWNs9WQbMvg4CAlJSVaQ6ilpYXc3Fz6+/s5fPgwPp+PKVOmaHuPWCxGUVGR5jl5vV7Ky8vJz8+ntLSUSCTC1q1biUaj2qTUKjdQUFCgS5SSrROyc0ZGhi67tbe3a5VjARZut5vi4uJxFhZCEJbymRh8iqiikPb7+/vHgae+vr6/UWYWrpm1k05KsFZhRSn3yXy3/1/u3j0ururc/38PMwwwDHcIEMIdjCRGiJhojEbjzxjv9ac90XqpNdY22pxWPdUerfVU2x578ai1am3V1Hu99lg1HqMeoyYxNZgrEkKAEG4BwnWYGWAuMN8/1n7WXkOt/fu4Xy9ewFz27L32mv181uf5PJ/nyBFd1SY9yCorKykoKNDnD2ig91XrpaXsQPrYSykfFMHPULfg/CagSmUjDm+Bu07rVRVZ0/vUsvpF1Z/HjdV5vAroUpijddHbMHmeCmQF4LhBxb5u4A8ugG2wdxXUQfvrlg/b91CR6LvqxnwLsCMPCgetWO+OL2RxYzW4FNFMtXVC4mEiNAzYIlEprxf2p+tl+P/XqIh4CSo+XQrtzylyK+l1FUCb5kN/iw22pMAmG7h8A/zmyaP8JHY6Cx0f0ZSnjOF2uxRrtRLguv/kricdbPqP5/j0sRiOdc8Sa70aRzP2Zz8BXDYfXngSx0XARV18nfe5FLi803r+AvXhCdK6KQxhNyTeCLASRt6ndjfsXawkvV6gcAK+7YFtfMwbrAF+DiNrGQ7HiLU4INWBo3wZigvaj647c66Gdb9T6ZjbsJta/i+EulAMGTDQosZ7eQBWnq/8X3CjUMijqBxUNrartHWoOtV4uTokHl8LK6Hw+w76WEQO1/FH4FiSKCoNUWLt6vJhiBbBbo+CCVtR82clGZTi44/A2d+DS+6B1Tl2v/bmcxRAlQYRm9R01VmjKuBznKQzzSjS90wgg3RNr6GPGqCWPt2kQoCKABKBGJXWXqVdahu2CrnYGiBpqFWALTluMCauzLg6lJtOPnYjLi8K1m2zPvtyYD/Tk3t5imyeotK6YN3gu0pdiz2Q9rLC2P9o+1LAI1VQImwVsanf76e+vh6A448/HrfbTXZ2ttZ2pKamaoGslMiKULinp4fMzEwikQhz5szRVVxygxewEggEdDohKSkJv99PYWEhoIS/4kMCaBNCWYWbJonhcJi+vj4NaiAeyEnQEtdlAXSjo6Okp6fj9/t59913ycnJIRgM6safUqFmujfLPuVYpqamKCgo4IUXXuDcc8/VjswzMzMMDw/rMugVK1awYcMGTjzxRLxeLwsWLNDl/yLYlZYXBQUFHDx4kFgsRlZWFvPmzaOkpIStW7fGBSxJW0nVlHjYiJBX0nW9vb1xjVwlKL/zzju6BF/EyD6fj7a2NrxeL4WFhdqkUEqfRZPV398flzIT8bGkXKQiTIC0pPOkbYh0bDfTR9KqY3R0lJ07d2otkrhhi4hd5qy4Cnd0dNDR0cHw8DCnnXYaxcXFvPrqq9q9W5p5CiARMCgi5fT0dMrLy+nt7SU/P599+/ZpQC5+UHKte3p6dJpIroF8j8z5KiBUAKTJIooQW9pzyPmJ9YDMX9PmQFg8Ad7BYFADIElHy/MTExM0NTXR0tKiq+vkOyMM7dKlS7/stvB/alNXOayM8HsaCWKVGo9A85nQGob20xQWgf9R+ZK9UPqeeu9Bl0qvMALOYSnjPluBIktHc1NAAYhu4GtReJUBFfT+bFdcJd0BoVVwqlURFEFR726gy6paEp2CWJWkDYJ/P3DoIwWYJB0jqmuhY6z7vnWq6qcK3uQyLgyuUdHPEIha2S2uAf5ogapmbKyk/XaAX9UDrwfYc7GDupcg8UpLjhKFDxZBbSP8agP86MnfcBe38um6x+DjdThWbCb2oAPHPEvPIybU3wGevIcc5vEqK3iVbC7f9jplP4PDr2I3QbLio1vqkK/I5sVb1MpeWA45xmust63kZW7mdph/B7CXvUWwcAJeYzuXcgZp3IoX1Qn9GjaQyfNEyzcp4fDeVWoQruqF5iKVjvs1vLBKHffWn0LDTxXYa12LGtPvwdLrYMc6a1Kt7YCWcnURf45t7LMXJT6/FPpYxBU0MgBcjpMo6bgZ1G2mXsuxGZ0lqHTNJmArPtqB1fyWnEd+QCeqC4MwPUM4iVCH7rCJG2ijDzc59LKbFSSwk2E82FqbbhI4xAyZJDDGDJmU0ouXt3FjNzQfwkkutj+XGzhiPaY+d7lxkmCr+033QXlMHIdM90yzzPBxqvHRyhpshXslsJcEPmKGY7FtvC1VdMYdcLtqd+F/qYTv0cWN/JQv2v4p4JE0kHjYTE1NkZOTw/T0NIcPH6akpIS5c+eSk5OjV63SoVkYkczMTEZHR3XFlQh/ha0RlkaYFzGWKy4u1itmMdEDdN8lYQTM9gFSMp6cnExvb68aUqtUWBic2Tb9krYw00E9PT3Mnz9fCzxlZR0OhwkEArp6KSMjQ4+XBBlJbR09ehSn08nxxx+v22x0dXXpkmDpDJ+dnc0pp5xCX18fZWVlRCIRRkZGCIVC5OTkMDY2RlFRkQ6slZWV9PT0MDo6itvtJjMzk7Vr1/Lf//3fDA0N6Qo0sBuvirNwQUEBY2NjhMNhbWA4MTFBX18fCxcu1KZ9aWlpdHd309XVRXFxsfa/cTgc9Pb2cvToUerr65mYmNBeOiIMljSSlLZL7yq5NhJ8Jd0l7IlcV9FHRaNRfD4fwWAQv9/PoUOH6O3t1Y1TxdU6Pz+fgYEBzWzl5uZy1llnEYvFaGhooK2tjebmZg4ePMh5553H/Pnz6ezs1OxGLBbD4/EwPj6uBdSSTly6dCmHDh0iJSWFffv2xXU7FysCYVnMakQ5D1MrY4IQU6NltvmQtOTg4KCeU6ILEubLTOHKnDe9kOQ50RyJwaJswqaJrQGg93n48OEvuyX8n9vcwAz5jAI5KP+QNZaM7F+Av7rhu0ATv4GHipB+C51rIfEZiFgFNkvvU0+1vgQwCu15KoDvV4t7UKFGfeu6VATOVimt61G36K2pNqDZ41XCzBKgcz6K1Te2Baj9PvUi8MOf2+5/chklRkhLc9P0zYoxFywAMlEHLq6DK6F1FYy8pwiVPwI5HVhtKO1dA5wB7LZ6LvzbxcCaW0m47Dc8vAzO2Q59KDuiS4DvOH7IPTGL8ioGPn4SajcQ63bgGIhBMTg2qGoxTimi8xNwTX9M0rPK1beT78Pmh7TDXGShqtoC67yo4fJOeLdUnaK0v8QD+cOQv1n1sLq5sJtSnqOTFWwDFlqv/Tr3skldSgIogBtpCnHywjP4lF/Ab95CHfg3bCGt0CPfAN6E0DI43ABJG9RDT10CO2rhnPPhnW7giXI1GB+qKcA1KMX6PcDFPuDPlNJIlXVtz2CadxlkCytw8SkphPBTRBq9bKEc2A30s55j+WYfLN8G33T/AJbAvxYqiFGCmhrpTDNMMYnsIUIXcCH4PoGM6xiueBIOrWKGG1BMlxcFIkqYsTqqzVjAoxM3SmisJlGfpevp07xfvzVOEes5aX9r5QP207eWAAAgAElEQVR1g452XAzhJESIcuO9ltO4TgILQhdR1UpadfrMLOEKM8Ppxv9B61zc1hU2E3f/uAHyP01piQPsgQMH9M23vLxce3jMmTNH97ASsCLBSoSa0qNqcnJS0/iRSISUlJS4wByLxSgsLNTaEkAHb2Eo5CZvGrIJWyGaC+nxJW6+IlCW90hQEAAGtuutpNX+9re/UV1drTU7EsSl7cPMzAwpKSka2MlnC3MRDodJTU3VlUDt7e3U19fr3lOFhYVaeC2lyWNjY5qVkTJySfUNDg6SnZ2tNUsiLn3yySfp6+ujsLAwjtGRlJmwUdJmQByxxXDP4/GwevVqPB4Pu3fv1gG4pKSE7u5u3XtK0joCJru7u2lsbGT+/Pls3ryZgoICzfQJyydjIgaREvy9Xm+cV5DZN0zSbDIu0WhUG+YNDAxonx1JzWVlZZGTk0N6erruf9be3q79gTweD/PmzaO5uZnq6mqam5u1+7PoYYRVNNkkv99PX18fLpeLvr4+3ThXwIycg8niSHpMmEozRSdskOh8REgszKOAbbN1iGxyrHJ8sliQ6yvzWr53kqY1bSVMFkfctk2gbwrfv0pbDTBBOm+iSJIRICGifF8uR4Ge3axTzT73ou6VJcDTELkNFbi8tpcaBYAvTz1eC0n32QBB1rKwXN1/H7eLUe4E/uV1hTu8QF3AsCYpgKSdNnkjDM9T9cC34Qre16JewH6jgJ6A8UZmPfcHbCe71ahzfB6656iwkzSodttaBCO98b2y3UBpC1xyBzxxO1zEfQT4DZsb1Xmd2qiwlJwjO1dB/WPAIngTHBfGiBU4iI04cHTGiP0HOH8C0+eA94YY3ASxgIM7q+DOSx9i7iNw5I/KSTipB5tq8gIMKD8h1Lrea53OCChQcQGcVQixe57jyrtUywVzmFYbQ1OH2k/DQuVdcy4/5kasMnRehDX/pV51aYbS7DyCIi+CSsDumIS9AVXZlRBVw5y2EfwbgfNa4NL5tqj5TiDlbWA9/x8d/AlluDiTCOenQpUTvs3H9KOqsFpQrZrW08EImYSBhzmLlYXvc/HZcGs63E8GSSijP4EEypNohAglaE1OxnXqTA/diqUWw4bc+dZv6fkg/gbd2M2wCrChpSDAGhS0T8QuDVyC3TBN2KViogSx7yaJ1r7d2AqhTdgiabCRZtA6XpFogy1qltfuwfaYFptx2WbVuhvblwIeCZIzMzMcOHBA31TFYbesrEx3rXY6nYyPj2tdQCAQ0EJmEaNKSwGphBFnZmEHhM6XdJg0hjT9YSQwmH2spMJFgkRSUhLd3d0abJk3fkADptmPC+hJSEhgx44drFmzRr9ePtPn85GRkYHDoVpeSC8xWaHL62UTlmZkZESzIRLYU1JS4oJZdXU1AwMDWnsjJf9VVVVajC2GhqOjo0xNTbF27VrdAfvHP/4xd999t67sEVGrVAkJSJs7dy4lJSXs2rWLiy66CI/Hw6OPPqp1WYmJiSQkJOg+XcFgUJe1S/m3lKHv27eP1NRU+vv7mTt3rq7sy8vL02Z2kgZMSUnRIEFSexMTE0xNTTE0NKSBcWdnJ+Pj46SnpzM8PKw1M+LWLXNt7ty5jI+Pa7AifbMSEhLYtWsXoVAIr9er2cKZGdVJXCr6UlNTtROzVPbJ3BwaGtLd3002Rq5xeno6ycnJuiGqgBwBNQLMTdsDEwDJvBXAb4rPTa2ZzElJVwogNTdJlaampuqeYwKEZLxlrIWtFKBvVi/K/1+lbREzNJLAU+UqZbAXoAv+PUfdKlVQ/KZ6chtqNb4Xu/LGqns9kKxExU/VIF5wUKtu9WKH/wQGURNUP+bterX12s3EG84KIVSCWvcmWq9ztEAMeL4Jdf83DUoECIiex0RLxgI5cZGLSMAw2tkGrBgkQB6brLe0WQfXvcE+Vll7d94BL/4n+DnAGzRQDXwvAA/Xq75bzlYIT6n9/OpE+FFsr3Lgzc+AbeC4LUbsEweRNQ4Sfxtj+jsW03M68Bdw3D4G69cTcz/HkWLoXg/FC2DmbzCYDvl9WDnI1dAFl2VC2Kk0UP+LatA58Iga0/dLgN3wfCv8W7Uq+78FW8MSQIGK06dV2fab1nneZg3pbcBydnIzT6gPTQF+eynUFMG6CfixB0rUNdldo8Zy+hvwQTFKQ3JeizLgK5+AddeSwEbyCep2Dj+ZsHqF7VUtDpLccHkN/KXaLqn2orIitdax7QVO4n36gcl0hb1yLLAzTAYhC5CovmJuXAwRJRuFtkSYVGD9n4rtpjQAun2uJfjWfUBk1hZjwngbdEjtvQCLBcYEFKZFuCdREsnz/6quJRegG9cxgK0+KoHJciUw1/1ZpCuraI76sYXW72KLpgX9/+Ptn5alCwsyNDTE9PS0bgIqbQGkrYPclKXkXMSl0qBQKrSEbZCVrhkkxDF5fHw8DmxJ53RhTmQlLFU5Up0lN24BTA6Hg5aWFu1MC/G9h0zgI68XbcTk5CRjY2M65SKmcz6fj5KSEu1QLABMgpnpiissV3Jysu6ZJX4+GRkZWsMhrNi8efNobW3VabLExEQWLlzIK6+8wte+9jVGRkZwOp1kZGRoMCNap4qKClJTU7nhhht4+umndZXT7A7ufr+fjIwM8vPzufzyy+ns7OSzzz4jLy+PaDRKf38/2dnZTExMkJ2drcWuQBxDNzU1pZ2CBfQ1NjZSV1eHw+HQjUEnJye1q7I4Vvv9fu2yHIlE9PUShkuapQ4ODsaJqEXvFQgEtADb6/XqEn/RrgSDQa3JCQaDcf5Mcp2FLRkeHiYnJ0ezY1K9JOydKU4200p+v5/c3Fy8Xm9cikn2b/ZRk02Ahsx/2af8CLgxWUfZp4jWhR0C4kCWHPvo6CiRSERXnQm4cjqdzJkzR6fHzMalgGbH5Fp/VbaodM85NIEbJXalQKUU2oFWzoOWZVZ5OYrpX41a2XcBN0LhRmXa95QsTkG7HJegQM6pqNDiBnZQAisG4Tuqp0M/dtFuMXDqfPUZhQ+p/x0dtnRFirCaUaDAeTPwC+yMgUm/yKJb/nYb/1uvDd8/jcMyNdQLcfp5Z1kep25Xn+VXdi50Ybe9Eh109X9aIeSC+fBWP63lyoX5WzvhqSJYNqXGoE12/djvYd11UPWkApHfAsezvyB2/4/ZeruDUx9STE/i7RApBh7KgOufxRF+mPVk8vDdMWLPO2hJt1o7FELlO8C8DGiG6GKbqKqiHh7JJ/bU21weRrWMsJiw21BhstWjeIValAB4ObDRqcLsAhTPIFLbBcCSJrgp+zkSC18hytfU1VsH8D240WN7MjUDh6Jwr0v9/SfUjErZhlKHjzDDMrJ5n6fIIJEAezzT/LEavOI1ZIHT86dVzzCx9hEj6m5rbokNQCmzNVZSpid9xfYT5QTsWsRaa2/SNlagrKS0tmG5T1mfkD9rcpk1g/K4AJrsWa+37hvTi8A5aLxmNu34J+txATiWEG46T+26aAJSfNgw1YvKE0ZgOsOWKDknrGMWINROfFrri7d/2ktL7P1N8za/3092drYWs4rWIjk5mby8PC10nT9/vvY2Ebdb8VoRx2Kp3pKUlwQ12UTkKhoEcfAVRkUA1BexK9PT0wwMDGhw80XnJ6kHc2Uuq/K9e/dqIa3ZwkJKgmXVLOyUqaOQ4CYVQ8KcSCNOGQPxjJHtlFNO0Wkxl8vF1NQU5557Li+99BIJCQlaEJyZmalTFBL8Ozs7deuN0tJS6urqtImeALJgMKgN/wCKioo48cQT9bUV7ZEY+InPkJgISgAXFklEvmKw+NlnnzE9Pc3w8DCjo6MMDg4yNjZGf38//f39DA4O0tXVRVdXFyMjI7qM/+DBg/T19WkmzOVy6eoyaRkibGBKSgqVlZWceuqpui9We3u71vqEw2GGhoa0T5LH49E+OqmpqRoMzJs3j9zcXF0an5SUREZGBpmZmVpYXFxcrN8v8yMlJYVTTjmFlJQUDU5lLknqSBYBMq9k/ng8nrgWGgkJCTqFJ/Md0KAG0PNd9icpLHOhIHNWXi8soaS25LssBoMyBjK2aWlpuprtq7Yp6ePX2AvUDKtSZxCPk2tso97/QolSTkJFm3bgNegrQt3/X0EBB8nhLFGhYgGQwgw1SCAKA/thia1q0JkZIFHyQNavWLnahynfDAOJm2D6Cuwuil7i2Rz5KNmC2NIIYXvuQlEHVmpOxbAw/EGFGjFxY7X6fwCbIIoYb7liI2rHK4G/wlPvwcJeddxZ6u1kAz+7AeBGuPg9O15edgeOWy5m+T1Q/X0HdEPkThQiGUWVh9+bwcP0wH9cjWPxZ9QsUJdknpCPKW8TvRiSJlRl1u9+BIvZCazG8a2LoQoihergI2lK11OL0meFreGrw2ZzxKdGhrAYSG2yBqANIsMhvs7LwKO4uJ+FzIOit+HiQXhyED55D3wutUM3UN+CQsmPkkQjafSSw/s0UQ/Uks4021DFX11A8CTYthCuPAmSPoHKN+Dyd1SFkVnxXmcd3yMoRsdPOQOk4qcckbnn0IvdeUrcemqwAVE2tk+xG7tTmEyQn6Ogn1k9tYB4dC2OjSPWvothUsUAJl3WxEsFZyPxfSVkNmWp5331isHRqSvL2V26r097jGNwW5/lVmAHFNjZA7ztUb3LPl4HjXfA9JPg2wiDG/myOq0vBTygVpki/h0ZGdFlyLm5udqJ1ufz6X5C0pF5YmICt9vN+Pg4SUlJdHV1kZ+fz9y5c3XAB7SzrdykpYWBrHKl8kfEt5JykBSPrNTlpm+KQoWhEEofbM8U82/zB9Cr4oaGBt3UFNAi7JGREa3/kDJg0ztIAsz09LRmCkSb5HK56Orq0oFKDBZFByVaELPyzOVycckll/Dpp5/icrk025aVlUVycjLZ2dm6DURSUhJ33XUXlZWVOkj29/eTlpZGNBpl+fLl3HjjjSQlJdHb20swGKS0tJRly5bpKjtp8mk2P5VxEcDgdrvJyckhMzNTMz4+n49AIMCHH37Inj17aG5uprOzk5aWFtrb2+ns7OTw4cP4fD7dnqK/v59gMKgND6VCLjc3V+tmBHwB2lvowIEDNDY2Mjk5ybnnnsvq1as5ePCg7tclXcFFnyOaoZycHCoqKigrKyMvL0+nwkwwI/2tFi9eTElJSRwbIuzf1q1bGRgYoLCwkJqaGkpLSyksLCQrK0uDaAE+Mk+l5F1sGUyNnBgDmkaW0hZEPltas8g8Ee8hmWNOp5P09HT9uSMjIxoYCfiW752wSrIft9utf3+VtlHUbb2a9xU2CECbWwWdVlbA4Br1grOisMgHIwqQJG0EnodTNwC/hNIO1P13m2I9WImSIACV9JFMM8ss6SfPzVcvvBANggZQIaMKeDEK1e/ZagrrsHRbh2yUqDaarASyf9eHykRFZkwS2VciNhPlBb7/mBIwZUQthJMNi94mC/WwAKmmdWpcxJE3HwUUsrDwWcciqIXCCuCsy3Q4C6LC5yY5n4p69Y7l2BKNW/+bE+6CgzejmnAy65xuA24tgpZn4e56IntUM/KNTqyYmIXLB667wXUv8G3VoiuJHwBVOM78kAfcEJ0PXW7Vg2u1dZlMjkHM/Lqtc3rGujajWA/uR4HaTfDKCxB72McYIW4C/p3zgXNRCG0vZLytgu+FAP0k0YiYIq0GhjmPNHYCexkmQ3/+a6i3VaFK0feeBo6L1sBrULMabtsNZ06o4dtjHY66vGaPhmJr5IsZZhF2vZa49TxqfZK0W30ae9K0WSdrOV6y3HpPEHumml4HAZRA2OxYOwopLdbvQeNxSYuJ8DkbJosUKPK51MtSouDzqAs7bf0edNnzejIDbcU96VI/IyhQJBSoZNvERfE1bBfslkX8o+1LU1oCNvbv36+refLz88nLy9OiTbHRT0tL0wyIrPal0sjr9TI0NKRLmfPy8ujt7dVpEUkryWpfKqFyc3N1gJCgagYQ0fyIFkdSVZLyCAQCdHV16fSYCEplM1fIYmhoanrS0tK0MDcjIwO/309iYiJdXV1a+yEut36/n8zMTP1eE4hJimVsbEz3jJLUhZxLYWEhbW1tJCQksHjxYj777DNyc3N1qlDMB9966y2uuOIK/Xler5eBgQGGhoaoqqqiubmZ4447jqKiIk444QR6e3u18ZyIu5955hn6+/uZN28exx57LLFYjOrqaoqLi9myZYtOMUn1EqCDq7AhkUiEU045hWOOOQafz8eDDz6oW4bI3InFYrrCSVIqxcXFRCIRcnJySEpKora2lp6eHhITEwkEAprh+Pzzz/U1y8vL09qTWCxGVVWVTmVt27aNxsZGli9fzoUXXsjBgwd1vza57sJ+hMNhTj31VM02btu2jTKrjcm8efO0X1NFRQWFhYUcOXKEo0ePkpubqzuxSzm7w+FgaGiIo0ePar2TaU0g88AES8IGxmIxrTUyNTXitCwViSazI+J4Uygtm4Aa0eMIGyvfT3GOltYWJusk5yIspimW/ipsXahGA99DrYFxq3vmXwD4JVLQAqPQkQd74aQobM0AAuoWnna1RZaXD8LTefwJOPW8DXCem2duvYp7LD7ETYDlpPPqXcBVYfDCBxmw3meHmk3YjiX5wO41tsOykDLNqEaksUUQKkbFowbjpES7I0yOadEvO5I4dT/8Ozfwy5PWwRaXWtxvKIe129iaB3WD2Av366HhMftYpYh4r3U8fA24SdnQ/YwGWmPzcDt6tJ3/L1FQYHEH7PZ9H9b0QkOROt43Ybc7huOBOcR+UoHjZ+/CQ6ssExk1KLGTHLAOHJsjnOOI0Rr7iL2cwSXPAKf9mr2FUPer84jd/Db8Gs4Iw+6nYQGPA2fzIw7woudY7sdmb2pRoX4JdlWTEicXsZBebZmzmgxim302EhF97RJIvV+dM8C97KT9lp08aF3Hd+qvQgm//tVqwqrSOc3AabxNJRDGxwtkMEoqewiykyT+Qog/AMv71KDFeJnQY+oznnUqHbYoUqThUBvTHMMgTWy0zmg9hdxKH7+3zup+VO934Ae/UYLpvF6UPN+LrTArwQZCgjglRbUEBVZklooXQje2gDmAradxYztHumFwPuRtR3ODg3nxH+NGAR8vwCgE8iDgsYG75BgHPFDssTNrAaDBpX5LoZccmgB/U882ny/cvhTwyM24vb2do0ePappfQIYwGrIylhW1OPBKJVYsFiMjI0OXKmdlZXH06FFdii7tI0STIyvPcDj8d9ofaU1g3uQFsMj75EdK5GU1K8cKdlAyBZuyH1BgSFJxkUhEp1MEAIhvj5nSEsAkKSnpDC+6CjEcTE9P59VXX+Xiiy/W3ijBYFAH1vT0dK0/EYGtBLGTTz6Z/fv3U1FRwcjIiE71OZ1OOjs7OXjwIJWVldTV1dHa2sq1116Lw+Fgz5497NixQ4+DMCySfhSGrbKykqamJlwuF9/4xjfYuXOnrlISBmBycpLbbrsNh8PB9u3buf/++7W+SHRM4mAsDtWgRNQ9PT1xQncBpjK/RA8lgV2CsTQtnZqaYnh4WIOfvLw8enp62LVrl36dpESF8RKmLCUlhffff19f74ULF+o0q4DmSCRCX18f+/bti7MZEHNAAd8ypyRlJgyf6GkEuEnaUphA+U7Id0sqyaRaTeaIABwzVWsabMrjMg6SlpVjlPdI5aC0qpC5L/uQ8Y3FYjp9/FXbht9TC8Jl4yqdtQnYTQZQZd9oW/KUiLZRBZitLwADNo4I/SewMw9nn4U9Pl4LQGcGRH15uGgngURgIad2wFbCKn5UQWCnrUgQ3TBYJIwXKqZsOai0xUqOQrQRYncCB7AdlQPYHallk3QXxHeozgdqlW7pl25UXuQbWABvBF6Ah9dbr12g9iHrdJG1fhN4YJHab2IzRDYLWDwIzKUpdjoBx0eMJcOvpxRR8zTws0z4SexNuGmdyiu5UYhj51FW/MxBrOlsHCUx9SEWoHNcdZT+r88htiURR2wNdLzEPd4Y97gA7qD2R68TW/42Aw+olBUNUPMG3HKRj/t5C1p+y+75h1jJaTxOL+2osF2LEpRLX6kQ5ZyGYpkeZh+x64/nd0/7lH+AiL6loZUEYMNMsPIp+J2VC2w46TkaeI4XUecuLbWE3xDIAEuYYZRsduImhBvFwVAId94FlVtUS4hNaOJQT00zrjeTirJ1buccOniHi1GiovutM7T8bX57B3YRvlIrXcS9vMFaEvk1gFXRJaI1gYjN2Aqnvdi50DDxSUBRRqGe981XH1UUxTYa9EKelY7yYjNB01bafDIvvpmo7L4bI9dKvKmmNAUTpkdIpwBWt90v374U8AD6JgyqMiUtLU2Xk6elpTEyMqJN5YSWHxsbo6ysTDsIS0d1MZ4TfxK/36+dls10lPj6ZGZmaiZDbsoixk1KStI9g2avmEV4KSJnswzdFBXLNrtKC9Bpjs8++4y6ujqt/5CeRf39/bq3lIhnwQ5wklKQ8xHtyeTkpE4f7N+/n/nz5xOJRGhtbdUakOTkZCoqKti7dy9ZWVn62ESwLEBR2DHRhkxMTHDWWWfR0dGhWRBhBdra2rTIWBybOzs7cTgcusnrnDlzyMzMpLy8nPb2doqLi9mxY4euJvN4PDidTq677jqSkpJYv3697qMlPbMknWeWYEvaSK7B+Pi4rsgS8beUaEvVlejDRDCfl5dHTk6ONkoMhUJMTk4yMTFBcXGxZiYkdSPXWh4TpiUWi+kqMukm3tbWprVZCQmqEemyZcs4ePAgR4+qhj7iWSQtO9xuN8FgUAvTZS4IgAgEArp1hMxvYZ0k3ZWenq4b48o1BfScBrsRrIydCN0FiInVgAAoM4Ul5yug2Uzril+QLFyEAfqqbWGAszYQAKaTYcQt1vPXq/LyUayWA6nwpofVASvgeKH0dG0Lw9Z8YDMcP2UBlV+jIpwXmnweai1otISFBICt1GnrkafKYX2HCj+bscS4xjGaWEUKbP3lKo3WeV4HfEZ8KbqslmcHAvlbGotmwYcL4dQJ4JNeuKzINjDMc8NZDwHfJ/EtiFSpYw2tgsB7tp1PG3BOowJr24Cu56wAfoGLnLcGGaaGLq/qch2whqVYDndyHRS1wE3z4RalSYoAW+6Nce0iB/0LHRS8GVM5pgvVARfwJJx2qdrDv1o7+72l71gNL55pZfhy4IIsdVD/9Q6Ez3mIh+c3oILw/VRxGd/+FBwnraOAx2gijyQGrcLsDrKAN1jEHo5XqC5gXRhznME2/+1GATNhHILqtUu2wJICWF1tF3evBkrC0O9WUKQfuIj3eYMi+sjjLgZ1/ZLMg7dOUwqgYuujVmObQQqBobRIQby8r/Xnp/E6W1hEEscq12xLM6Te+Rq6pwhh3mAdqnT9NtAmhTLzBqw9llh/N1snLHAL6/EsbI2PF135leGDDPP+YdhDOrsgxci9OnsV6BmxPs7pU/vxutRhOaOoSSwTPctOh4ke2+yZMVsXPcI/3L4U8ExPT9PV1aUrZ9xut9buiH5FtDriuRIOhykqKoprVihVI3KDTk1N1Td5YQEkSEpQj8Vi2ulYVqyyiha9gqmTMctsxTjP7JxtujmbFTtmWa5ZrSUsViymGqWKVmJkZES3lSguLtbuv2YDytnnPTIyogOVBK1FixbR2NhIRUWFTllJWkPYEunYnpOTo9mp/Px8EhMTOXToEDU1Nbqtg3gEhcNhNm3aRF1dnQYgwWCQ2tpaWltbtQdLcXExOTk5NDc3s3//fo477jgtTJ6amtLXWa6ZjOO1116Lx+Ph9ttv13qiQCCgz98s9zfbHgh7ICBGrsnAwECcl43os4aGhrQX08TEhE6LgqrmEoNFOX9JGwqYkGMW3yHZdyQSIS8vTwPVY489lsnJSfr6+jSwLiws5ODBgxw+fFgDONMjR6oXZc4kJibGARPZBGwLsyKgWCr+5PrInJCxlv3IvDcZK2FsxHdKfKMkxTvbR0fSjwKiZFEB6PSa6Qz9VfPh6QbSuI7lQGIntFUL4LlA3e9rAF6Dh9ZRvV3df995Evi5fe/0glq2W27GbizflZuAbOjvhVpWAnv1uhjyoaiFM3vn88FV8LhViSX2bdr4eDlkbbC7FYRREhzHIBxxAay3QYxZpWUa5vyjLayUF2EPnMY8tnitdP78CfCtg4wboAaOaYEmQ4h9eDNkRdXxCAh7eJFieL4Whde8sHQj7GAFECHmvwwcLzHkAjFe2QY4s2F6slLX7kcA5//C9L/BU+/u406OZ/2TDh6+NWahKRf88FJgPb/iOX70SoyLUhy8PA3Jzn04zvyQf2c7ldbleO0k+JNXfdjvPoDVZ27nQrrI4THeBCpPAlp+j3f+Y7gY15Kh3Syji+08QCO1nwK3Ex88BV0ITSP6X7PiWf4OqnlRaRlWFkunBi8Ut8ONXXCjLnjqtQN2EKiEv5TanaX+av1+xvr9TeuwmrFJjC5slY7YCkANIWpoogARsqTxPtlAJ80k0YsbLKGzKMW2WXvtQs36LGzqRBCeQC5pL2F2rr3T+r0f2/GyALsFBdZADFh/mxVdbnB6oUj0RNZkzhBdkslpZQMNkDECy6+yMRrWU/K/LACkvv8fbF8KeBISEujp6QHQKSvTwj4QCFBSUhL3eE9PD+Xl5XoFD3ZTTQESgKb9zd5ZApq8Xi/d3d0UFRVpzxvTCwds8GOCpdkusz6fj9TU1LgSYBPUSMrE1PUIWJEAIedUUVGh00GSshkfH9dC66mpKQ1wYrEY5eXl9Pf3a9Al5yaeMdKmoKGhgZNPPhmwm11KwK6oqGD37t1kZmZqfYfsq66uTrcgGBwc1GxHT08P+fn5dHd3k5uby+eff04oFKKiooLy8nK2bt2qRebV1dUUFBTQ1NTErl27dC800Q21tbXp85ozZw7f/e53GR8f56GHHiIajXL48GHdtkPGUyru5BqY7J1ZDi5pIGHtJKUpFVJlZWVaIC0shQivq6urNYDKzohO1BcAACAASURBVM7Wr5FrKVoySWeaqU1JbU1PT1NSUqKZmry8PF0x5XK5qK2tpba2llAopEXFTqdTC+qdTqfWmInlgIjSzbk9NDTE+Pg4w8PDHD16lIKCAhwOBz6fL87JXLyYJL1rMj6mcaHsW4C6ySgKQJfvg6TcZntNCZNoskHy3FfNh2c/6h5YAhBWgTLEeUCVurfmfQTU4vyRfc8kAM4t9i0+DFrnIlmlS4Gn+oF+BaBWkUoCBWTRRCULEffCbH6qXHqLYEmvUlHUWvt8dZE6jOuxi3Sl8DchqhqXhnnb1pPISlZWsGJe6yV+VWvpPSmxw8a3UVXb/BlYOwB7y2FFPtwMWa9b79kM3AiRLNg7qILqkAvCUTizUe06G+UQraD4NdYO++m7ChyvQzigDjcfxYbt/tgFK3bCu9lwYjnTC8GxHWLPLaLqql9QyI/t+OaVA1zNjyiGlFW0O2IsiznYz/HU3AzvPqDG/1FUsbJj4VmEq98n8SdwwR6IrOvlGx61lxogYb6XlcBmQnwbuJ53uYuzecC6hvwbNngxNVDiwyf4QJ88dnyvNf6XgbaosZmzIeFBdJ6y+RbFt/zc2tUvsTOTbuCCT9F5xLuLsX0Cd2AXTFn+Bz8/E+78Cdx7NgRPg1/zMo8DfdwO/Al6F+F/E/wD6rqGSiC0ZtD69C4SeZp0puOsnACmSSLKudZ/3dbJN+i2E9X0UgO8wXmoxKXU9NViwzYv8Z7dMjhSBVZnPS+PS/WXKTwT2bwYG6YCXWpsF/mgI0M7ouu3iZatzboG9Xzh9k9TWh0dHQQCAa0rkZWksD7C5Eiwka7M0ncKiNMsiDBZbtByY5cbuqQ3BgYG4sSXksIQLYK0agD0DVsEwsIgSKrJDAZSsSUpMLnpmyv2hIQEDZRmZmb49NNPtbhXPk/SSZKeS05OZmhoSDMJAwMDmk0RMGCKryXwj4+PMzExoRklKaXOzMwkJSVFl2pnZ2fjdDopKirC7XYzOjpKU1MThw8fZunSpUxPTzNnzhyt69m0aRMXXnghc+bMYXR0lEAggNvtprS0VGt0hoeHmTNnDueccw47duxg165dFBQUUFhYSHZ2Nq2trcyfP58jR47wgx/8gAMHDvDiiy8yOTlJd3c3vb29cYyZ6YIt42vqXURXlZycTHV1dZwnkwRlEby3tbVpLyTR85ipS7MNiWlTIABAxlcAgMvlYtGiRUxNTdHU1BTH/MkmYCA9PZ3MzEwSEhIYHR3VKV15XirZysrKSEtL098NcaEWNhCgrKxMLwhkjESYPzU1pRkaQJsfynuFSZqZUV3jp6am4pyZJXUnoMbU6ESjUV3RJY8LaEtMTNRVlfKdkOtggv+vwvardXAOkN8JzQuF3bFKh1YMAg0w+UM8UypAvmBJH1ZNqdcuBz5YhbpPB+0AVQw6UmwGfKSTZVIwG8phbVhlanyqI/rj2LUxVaBkF1326l1u/3eh3IhXvq5SIkgAlBdJlBLdqPlbWJ8gGkU1AHd/Ctf8ESX/INuKSdmwopcGitSLVlrvrYLwJByIKuBlhq0AEMqAz4PAzrVQv0md1bM/wJX4W8aSYTwKh4G5UZUW7IxtU2N+aTmkQuxFlCNg+A761tax5yUHdTtjSmjz+jq4+CFgVKWBYg/BrTHu+o2DV26C1VYbhh8S4m6SgFHc7o2c9Kvz+dsL4LoPXikBVsO5hfA/BOkH/jYMjpyreI2zeRO4GSg+lb+vdjM3s9LNzC151RyhHVgCzYsV27IcleKiGRKewc4sATV/VJzInSKzMXqb6WOQ/Tdbv7OsazJqPbcAgmfCna+iJusApL4Bd4fh7k2A914ovlftfzE2W9UNvGBcQAEG4sYo+KI4BAOv22CvZqfCNKkQOSnIHrc6z27eZj9vE+JZNckaT1efmRHFTtrKjOnGVqY1w/Qd4LwPe7bLAAufWoLiOMPWAFehOdFs0KWIYiUk42fmhc0U16ztSwHP1NSUvsm63W7NxAhIyc3N1WkE8YgRx2NZZQptL6kMCfpyoxYjNbP0VlbgJvhwOp1apyJBIj09XesO5GadmpqqPVOkf5NUSAFfuKo1WR/z2CRoigGe6F8ikYgW3UYiETIyMujt7SUvL0/32RoZGfk7QaikFOR8PR4PwWCQbdu2ceaZZ2pTOOmllZqaSlVVFZFIhAULFjAxMUFjY6MeW4/HQ319PaFQSFcV1dfX8+677zI9Pc3nn3/O3Llz2bdvHyUlJbpxqDgqt7e3k52djdfr5ZRTTqGuro5HH32UkZERiouLddC8/vrrGRgYYMOGDQQCAfx+v26UKdobOSYBNFJ1V1JSQk5OjjYsdDgcNDY20tvbq3UuZlpRgIEE4dmWATJGZum/zCF5jwnAnU4nhYWFzJkzh+bmZi2glvktfjVSOScl7FJ9Zc4ZAQ8inh8aGoqbO/pL5Yr/WpmAWpgXYTZNVkb2I07UycnJHHfccTrtmZOTQ2pqqv5uyD5TUlIYHx/H4/EQCoUIhUKMj4/r9iFmxRbEi5bl+yNzdHYF2P/57feNCnQ0w95SEQzLijQLJn+ofOKwSJIbgVvUbTqaDOEpFHB4BPCqW+9+VG9nCVKSCJC9VAGJ34XI2lN1j2iwK9k1IbNSfZbUyAhh0w5QomLaKzhpuGWaJRcSvwgWKkjsSuR4zHTMasPD9kHgz5kwMKZEpBlRaxweJ7Top3ZKRyqVGyHT0it1W7sbQOEoZwgi+dY+n12CijzdRH4HPAHTAXB2Qo9L7YP7vg8/vAOWr4H11hg/ihL8ZJ9H3cXLWF/v4OFrY+rcLlYK4TdYoT49rMbEUfoZSZxIiO/j5iF+S4gH2Ukrd/FpSwzHFW8Tu/98NcgB+J9aePE0dTqOP8WI/YuDbaUqpN69xTpfczwFzOQbj6far4tcBG+61ZiccT8KiDRATSXUyLhj7EsU76OoOC3AKWB8pvkeYYiklH/A+t8qoOo+DYrfID6gC7P3TeycqBvt9A3YICcLW9+1kji8MaO4CRIM39FIDjgrVSuWRD8sToElHXBnM5aB8tU20B5D0X4y4QXYha0xFCV81stQBc2FCsz/iDzgr7BzGdTvxAZCS62diVFCPqqyPwzlASivM3acCtMupf2ZdlmmhOLnE799KeDp6urS7RCkQmdqaoq8vDwd6ExDwuHhYSorK+OC3+DgoO6xJIDFBClyIxaaXZ7Lz8/Xq3YJRFLyLOyE1+vF5/Ph9Xp1kEtISNDsyJEjR7Q3SSAQ0KtjWRkLGDFZGLnhmw63oJiunJwcfczSdkDaEgiDI8JXSUHNDuRmxc68efPo6OhgZmaGsbExne4TBiwjI0M3UN2zZ48WkIs4Nj09XXfSlt5hCQkJnHDCCfztb3+jra2NwsJCnSbJzMzE5/Pp6+X3+2lsbKSmpkYzYTfffDPPP/88Bw4cICEhgUceeYSmpiaeeEI15JFg6vf7NVOWnJysHbe9Xq/+AVVddvjwYfx+P3PnziUajTI8PKxbaJjVcgKKJWUk18t0sZ7NQAjjImMrvwXoFhUVkZCQwOeff/537zFBuOxDwL38b7Z3kM1sDyHspKRHZW7JJnNLNpNRkvks88N8bTAYJBgM8tFHH7F169Y47Y2Ab/P7IV5WOTk5HHvssWRlZVFVVaUFzeZ4TkxMaJZUmFdJD37VGB74swI8NQrsKD8Uo8Qp5SN483SqgHcygKIoSS+7dJyrA7ZabQToVwW+Og4GIcmnUiM7gAvJAgIUE2Zx1M0OVBLhfhS8asC2gQuAEm/2F/E4qlVTMyo4jyUDf1ZxJIKXUXx2pwCwS6mkblzYB1Nn4lXmdlqDBMRu9uGYQaVG6gfAdzpk/EXhniXYmYgaiJ0H438BorZGV+Qpp0/BZh94nwP/s1IzXAnrXoYn1kAAZqyy+uE2uOJWeGHlf8KKq+GmZ1WZV7/VDX4zcOEnZDsduPYlE711Ci5bBC+9SSLbOIGP+XTJb6yqugZCrAUC3P2OOtTl58CD7OSp+VcD38Bxy0ZiH5yviIZn4PIV4Ij9nthGB3xNXcaVoMCWgDxJh2Sh0keiur4Q2+7YC4kvwCUSzEXeAnZhk/joCWgQZm42+yCASK7l7OcFtBiNYPmL0gTF2RGMGO+RjBLEpzxNUDVgHeeocUGtY0gQsCRVgEDisH0sM6mK7QPUPJEcrDAtcpyVCjzNWMgi5lJNYKNWplxqvgIoOfUtE4O4Gk9Rx9MK0SJwddjHFToe1jnhGVKZoQN1kbZhs0DWhHdafztFm7SWL9q+FPD09/frFIEAgISEBN3Oobq6Wt+ghTkQXYL4iJhMjVS1yEpcQIe5zczM6JSCCHlF/yM/AnhKS0vjxMiAXoELU+PxeEhOTiY3N5eBgQGtj5F02uzUlrACYK+Ax8bG2LlzJ6effnqco+3Y2BgTExNajAzoKjRJv8mYmdon0UqkpaVplujgwYMsXrxYv6a2thanUzVCbWlpYc+ePZSWlpKVlUUgENBMWkZGBqOjo7S2trJo0SKGh4fJysoiLS2N9vZ2BgcHyc3NpbW1lfr6etrb21m6dClPPvkkwWBQl6efcMIJ5OfnE4lEuOyyy3jxxRd58MEHGRwc5LbbbiMxMZHc3Fympqbo7e3VQEDSVtLQEuDo0aP09fXFgbxYLEZra2uc3sfU/QhgNMGB6ZNkpqhMRkS0M7P3J1VdPT09mkUywawpFjY/U85LXJRlvjidTrKysrReR6oVzWMCBQil3Nx0ABeRvmymEFz+N8/XZEXlR8bA/A6FQiGtLZNFwZEjR/S8jkajcSkvj8fD0qVLKSsrY+7cuZrZcTqdDA0N6S7tX53tQ4o/hQ9PEjGxeBrvB7KhcS1p2y1J5RvAThcrsaWXv09GLTafgcRgfD0LqYoFypqKr4h1M8xqCtlBLaG10L9BeQBlq93oWzb0w7YiXZm1BBUQptPUZ45uhASi6jO/A/ndxNuihLEDzxeIav9s/ZkKKvg1AGuwA3IXsCisEMBdqN9vAi9FodlFJBUCyotRdyuSBX0sRWl57LyCVfT9V7Wv2GagFpZuhxd+isUs3AMrIek61XncPYhu93RPVYzFKxzsdqMC7nN3ELlqlNXcx6dXvQ208nXm8OpgjMQ8F45zlhG7Zzu1wJ9qoL/0Od5hNWy4Csfadew48zGWuGFvDGLuGzRrctswigGSllIydsWo7Im4/WFdJGFLGqzXdKEuttB2ida5RYzxF5BhVhUJIO2y/rdSRTrjY3rJyHBKiyqzY4KAGZMtMkFNv/G/G4UqpKQeCJZC6m51/N2F9svcQKbl0OIMgWvQ2KcbEkZhoBTyZ0tuBJgZ7bIS2pWjcXQ+OKcgcRQSLQbJmx6fzOrzQPik+NMaWaiGUwrhVwKXEmTV9ByOOi3g3Qrd1eo7fSFrUAlDQZ6mcDp++1LAI664Zi8r+Z2RkaGZFZfLRVtbG3PnztVtBqT8WHxRRBthBjUpixUDQrC7REuFluh0ZJ/C0AiYkJJbARGBQACPx6ODm7zO4/Hg9Xq1b44JUMzgYAqMJdXi8/nYsmULq1at0sFvZmaGnJwczYCFw2HS0tLivHrA1kiYQVUYhLS0tDhH3qNHj3LGGWfozt+7du3Spo5lZWX09PRoPyOpGpKVf15eHuPj4zoduGzZMoaHh5mcnKSsrIzGxkby8/M5//zzefPNN7n66qt54IEH6OvrIz09HY/HQ0VFBQBz587l+eefJxqN8t3vflezPwLwAoGAZhRkjPx+v2Y+zHOHeH+jL0oBmf+b7IiZzhKmzBSay7WQMRBA7Ha7GRwc1HomYV5Moa8A29k+TAI6hH2R8U5IUJ3ipYpNUlJy/WRumj3MZJ8C/mXhsHPnzjgQJ9qazMxMioqKyM3Npaenh7S0NNLS0mhpadGtTMwFhAn6zE3mslkOL+c5NTXFtm3b+Pjjj3XVWjQapbCwkEWLFlFWVsZXa9vPuyepBb+6qYoQciVQAM+ga1tYMQE/8EhdCADTd6GDSm5UL37VotytVr0Sr+xnBqijEAaLFL1jVWG9hrodNwNb7wDYTOKAUlcmon3uWDwId26ESz+CHKv5ZBuQL91OhREQbYcEOTkQy15a4uGlYBfkfP8yeOwlWOFVAlDaYO1OHD+oJ1aACvjTlsFbAVh9KnU6S+Js4aAVQ99eBuc12wdQdB8EfsiZHfBBO+y4CngAcn4Kw7EAeCH0fTUIw/XgbILpnwNPwW7WkPYLB/6rYxZQ6OdxYCHn0/R6jNGLgbwJItTxK7YrtfctQA38zzfAUb0e1hbDzt+ztOT3EN5AzH2dumj/iw1CHsSOulJlbQpesf4fNd5jamvkYgtbM3sTECKVdbJJHJb9YFw7AVCSzjI9ZuTzZleJmdoj+V1CPPB6zfqMJYot+TNwzULF3hROQJNHfTcU42jtwgOVpfYu9hqHllUIy9djl+eLIE3AnRvavxMPavI/gcFzIGcCCsLgMG5XIQ+4w1Dgtk/L9NEUwmw/0O9Up7cfcFfbQ7OVl6njZV2g4A4D7nV80falgGdiYkIzGsJ+COUvpdIpKSmEQiFdmi5mfPn5+fh8Pr3CTElJiRN9yn7NICSb+NQMDAxQWloaV9HjdDqZmJjQTT1NQTAoEbAIg1NTUxkdHdWrXzlW87MkEJrCWUAHM7/fr4PH2NgYJSUlumza6/UyMjKinXnD4TA5OTlxxm9Sai4lw9L/SoCjjMOaNWsoKCjA5XLxySefaJGx+AoVFhYyMDCgO8+HQiHtWJ2WlobP58Pn8zFnzhyGhobIz88nJyeH9vZ2SktLNcjLzc0lFouxfft2rr32WrZs2cL+/fs1MC0oKGDBggXMzMzwu9/9jvz8fGZmZggGgwwNDWnNUigUIiEhQQMK81rMrnoz01EmSyeB2ATBpnhZgvVs/YsJWE3jRfkxG2yarJ1cAwEM5mskrWqmxUKhEEePHtWtVKSCUF4fDAZJTU2NK6eXc5RrLnNB9p2UlMQZZ5xBS0sLR44c0WOWkJDA5OQko6OjzJs3j+rqal1puGTJEgKBAHv27NGNdWWxMPv9opWSMZFmq6ZWx2wqKtdhYGBA95277rrrvuy28H9sc+uYogCPRCkrYmxWf/nXApMeqh9S7xpLBs8U+L+JihIBu7+RtrpxK+reHVX7iFKOiyAwoqSVjwL/MUEBHrwobxVLvgu/2A5ksziqbvARbG9budGzolE35ixAeeQkjaAiVAk2UzNqnZLlpUOW2okXy8PtU3s0YsMv49j8EqyTztnXAHcRW7QRvoPKrUkn0BqgRZ2b6Fvbsdt1BUABjvNeQ4ef4z+ClfDBeyjWqEsxBuMu4JRF8Mkg3JZH2jzwrwPXTpjOxup88BL+s0Zs8fS9z9J3+zYGOKrK/wG4FljJj2ijrtDHtj/D3ReqMZi+24cz/WtQ/1ckVD8RhmvCsN8NtU0oJDvbXsYEDwIczKo30/NIBOKmkFlA59+b5vy97kr2J49JNwcRSglwzTb2Z7An2j1R9hfERsvyegFPcn7N6idpJdRcpFqrVMyBhGn1tgUoUmsbtgtPA/GZqgAKO60Eul+Dyz+wrm+qcZ4D6lgq31D/R1fAbg9wjnp//tvWjlPRwM5ljUVipTr+VOuY80sgmGNr82utjxm1jleyee0orbsM2YtAsVtN4y/a/mlrCUlZmKBA0lZCuUtaBBRQEAGlNKlMSUnRq14zRSE3Z7npms9JhUxZWZle4csNXvolCZgQMawZwCSYpqWlaQ1QQkICXq9XC5gl8ElAFtaivr5eB4ixsTEN9Do7OzWgkR+/36+ZlEAgwJw5czSLJAFuds8vGdtIJMKVV16p3Xb37dvHvn37qKqq0iBOHJ4nJycpLi6mo6NDd6rv6urSjI6wRuPj46SlpeH3+znhhBP4+OOPmZqaIisri3fffZezzz6bb33rWwC88sorXHnllRw6dIiXX36Z+vp6MjMzmTNnDhs3bsTj8VBQUEBfX5/2s/H5fHpsBTiaLTskBWrqar4I9AhQkfeZGprZYmW5tgKUZTPfK/PDLN+WuWAej1klZQqjvwj0yGdJGX9aWpoGhsIcSkopIyNDPyYpJjkfOVeZsw6HcrSeN28eDQ0NmrUSfVdvb68e8+OPP16bMx533HEAtLW1MTg4yOjoaJzBoJy3MLKisSsuLtY6L/GQcjqduhjAZOa+iuaD/agYPkAq9q0yCI+VQ5e6UfatJs57ZzpHlZF/UOSD5gwcqp0g2dgFU6BAkWRE+vBQTCoQUCTMNmDaQwMK7LyGumErzjoAjWt1KisVe3EuaTN4QgedMJB0FBVxpH9QPvEpDdFftAELlD54CagoIJ5DpwHLgEYXLBpBqZJeU78kmnhRoOAtCJXDTDd0ReNjaioKBO12A9zJQscymnqAfSeqA7tgoxogr5Wi80PSdghN5oEb/C8BmxSIY791fDcC3AZrV8F171nAZwmwEVbcRwHQwl+JnjIFn5zNal4kMrGBD9+EM7IhoQs2veajizO4/rIYvNTN9TxNiVvRVJFqSAxY4yDOf9JsTcrPTUZHLvLs+m1hXoSGEPAjIEmsbcwqLJMJchuvT8UGXAPG89K8vIB4AGOCMlN34zV+y36k44Mc42ZY3gBP/Ay6nYCTOK1aWF1yjbuasQG+yJw2yymeCaNnwr3XEG+A6UZb67jehiXZED0Z8MCDX4dHvw77J9RzevykzF+2AmAUUoshdZsahu5vQe1u9PUJnQIHnOr42u2HgXgibPb2pc1D5SYqdLyktKR7tAQVcZo1b5p+v59Dhw7pfQmwgfiAIEFNqphM0DIyombQ5OSkDiygBMRSvm6WuYsbsqzyZfVtpo2k/YAJuMBujCn+NlIyLT5EsViMTz75ROuOJA0WDofp7+/XgUNW+pJiM9kEM42Tnp7OMcccozVR9913H9u3b9eMiexPdEzi8gvoVI2ZkpF2DZOTk7okPysri5ycHHw+n27xIIAmIUH1f2poaCAUCnHllVeyf/9+rrjiCiYnJ3U6JS8vj2OOOUY7aQvAlC7pJqszW/BqMj8CWgUACOtmmj6a4MAUNJul5aaWDP5eVCxAMhwOaz2NyejJtZY5bb5PXJMFYIoHkcfjwePxMDAwoO0IhNURU0PTn0cq1eR3ZmamnpPmnE9LS+OMM86gqqpKfwek6mxmZoapqSl27drFZ599xr59+/S4HHvssZx55plUVFSQlZWlP1MWIMJmyhhJFd5FF13ElVdeyTXXXMPVV1/NwoUL44whZRy+Slshg2xDLSxnqLAetWp+m5VwtmkZ6ia7Sd3sN4PyTgFV0dStNCsmw+O2XjMlbYFQcVu2BUDhe4CzkS7shbnojaEZnlAxvRg7O+BFGQ4q77SnKbEeK27CTktJ11GTKcB47ho44RH19CtNxiljfcj9WHbSkv8KKK2HYMFngHXRuPcJ4ZCIiqcD1vm+0whctoym2DzSihzAn4DV8NYNdulZiQKQoTxUP668QYUAN1sDWgKOaev/DauAm20Bxw0vMcPpwIOkAhmE4JPHoGMVZD5JoucszvgAHrWYr7PdinjgpVUojuJ6VrNWMQVu6D4JO/0iSDURG6wIoBBwMXuMZRwDxAOgfuJBlMn0yGvMVJj8baa9ZJ/S22wUBWz38PcC6y/q7xk23i86rwFsTx9LbHz1NJzdpA71LeuQpSD8Eutte63HGlAyq/3EA4q/oHDNvz6NIgm91o76sR0rrc3Vq1qB3DSsvKDO8UDu1yG4HvWlAjutKGPWZh13LcxcAsV/BJ4Ax0m/wHFaOe85FQBavgW+2QnfboIb+9Qp1vGPty9leGaLQ+VvYXxktSiNEx0OB8PDw6SmpjIzM6PbIJiMjqQv8vOV86KsqE0Gx+lUPZDEBE+0NeJfY7raSssG8QYSUCA9ubxeL2effbZmTKampojFYgwODjIxMcHo6Cjt7e14PB4WLFgQB6QaGxs1e5CYmMiBAwe0KV96ejpTU1Pa6VfKmyX1JucteiKTaQiHw+Tl5dHR0YHH4+HDDz/UTVcBDhw4QFlZmU6/yNiA8nXp6OggMzOT7OxsBgcHSUlJ0b4uqamp2hk6Eolw4oknsmvXLv3+gwcPcvLJJxONRqmvr2fPnj06mN9zzz1MTk7yhz/8QQdTKZ0WXZLD4dDgS8CFzA8gziPH1C/NLneWMTHN92YDptnl2iZTBOjPkfGXfcjrBFiLuNhkQoR5nJycjPt8M7UmFX8CbkOhEImJiQwMDOgeZMIoiX5M2nYIKBZmUdKAAuiE1QsEAtTU1FBWVsZHH32kz0m0ZbFYTHtLtbe3E4up5qkej4clS5bo5r5HjhyJG/fh4WGdity5cyeHDx8mKSmJpUuXUlSketlUVFQwf77qsud0OjV4/ypttZiWJ12oSGeZowXUfdb/PPAiOFrUTX/rMmA/9P3e2km+2knBILiYwUuCEjlnK9FyYsAEMirhlUWYGtz0vb9I96IMo0ifpjsAmqHLXuCLPvUWlPHfyCCcho9twH+9YR/DtSdB4CRY/XX49qdY0R07MBfDim+pYPUU6rzi0ilAYYaDvtGY9amWwCPvOeAqO3ARhloVHiL90O+z43Q/EPopVP8UzvkNluDpm/hp/n/cnXl4HNWZ7n+tbrWkVkutlqzNsmxk2XFsYwwEQzxOALMGwhZMQmCYwGWACyH7QJgsk5BMJgvJZGHJ5WabkJBACGSDEDzx4AB2jBFgbIONkWTZkmVJltTaurW0utX3j1PvqdONIfe5f92hnqdtqbur6tSpUn1vvd/7vR+m/Onz5v96bwIVlBs808Euw/KwAb+txG5MgGsABs+Hn2fgTq+DNuuBNWzmS1wIbOYmli++ka3ADOsJnLEE6OCGQ5sILYDDw/CZmk183eZPPsEGmjmTL3EXqLWUCbayMS5kYDRnhW0KXGA0gl/CrvWdsu6jVmIVaoDc9lSFeiDRFju976p3pzQ/1d5nbi813+49nAAAIABJREFUoea087/aZRWb798ehK8l4bp22LnUpITC2EuMDZjr9L+IUcGYJW087GqHudl7722XQfVl8OwVBcegsbhzVgO/8IZ8B/CNlTC8EspfwT//Lss2YETQVAPrIXf95yAMqXsg8Pac13k9BIu6OIXF/BdQPmz2c7TlTQGPm3aQP45YHt0gBwYGWLLE9M1QqbPaLUg7IZbFZTik93EFqO4TfUlJCfF4nFAoxPj4eJ7GRkFIKSgJTN10ypEjR2zge+ihh/KqsPS+xtrY2Mgxxxxjg1BZWRnbt2+nr6/PHr+YoKGhIRoaGmzLiIqKCtstXdoTlaarUiyTyVBTU2N1IWJmBJpaWlro6elhbGyMWCxm01divZSuUouFcDjM5OSkDYxuNVQ6nbbpFx2fgvrc3BwHDx60wtSFCxfS09NDIpFg5cqVzJ8/n8cee8xWds2fPz/Pd0jpLBnhuVVGrn2ACxpcTY8LgvSZy+SIEdKx6OWCJWmeBIJ13bnraV9aX/Ooc+JuX8BNlVWujYDYQ1cUDVjtVjKZpLGx0QJ0OW6rokpiZP2tRCIRSkpKLOiempqyIv9AIMAZZ5xBd3c37e3t9hqRiH52dtZ2UX/llVcIh8M0NzezZMkSTj75ZObm5tizZw8HDx5kcnIyDwTOzs7S399PLBbjr3/9KwDV1dWceeaZlJaW5p3Xt5poWffPBBBimox9bAf2QvtazI31PtMPKgFQDY1j0LcBX+uRUNxOApVGf9oMuRaY3e1mQxoJkyRMH2tYxJOPmjj1Q3xZzCv/9jiwE1ImPiqg4P185aC598cxWOI3F8GlG8y4/qMaH7NtJi/A9jwA52GCyTo8rxg39eIxQzuAhg7g6Vo4VY6D34XVV5njvQKz4WjE6i0mqiE5COcm4WAtrLzdS4d819uZDYdfAC6kgl4mlKNTiVcCcrWYZqKf914bzfhyy7zjiXoH/b00bA2Z6HvvLXDjvUxwCUv4HY/ia6oPfvyz8L3Hgc0UR1Jw+1/JNQb4GvD19PeBTxjxePJ2/quljf/J49x1Bqx2m06myE+vuMIVPweZz9yknO9LyY7zXbdSS5X7LmvkMkQuo+SmrfS51L8SPdfjp8yavd9leuyWovdjLrjV3mceOGvGH//qTtMI9fuLfI+ohd5q/YzxCquABEWM0oNahvrQPoFJFfeTYv4D0D0JoVsxQNJ1pk6bDddMwrDXHP0czJX3Q+CTK6+ie+X9NPfhszuaGzeX+iFgBZRfDbl0AMIQuG8X0Mp2ZolmQ3AAcm8AeN40paX+WW5H5lgsRlVVlQUw8+fPz6toUonr4cOHbQdot7WAApibUnADoV7hcNgyF+o1FQgE6O/vz3vCl9uzWBixK8PDw9aqv6WlxVbeiCnSuOrq6qxXi5pkvvjiiwwMmESogqV0GwcPHgR8UaueopVWS6VSVFdXW01IZWUltbW1VgCtp/CJiQkbCKurq60Y2J4YJ+CWlpZSXV1tGbMFCxYwMDCQl9ZywaTeU1PPxsZGqwVyWZS+vj6y2SyLFi3ixBNPtLqW4uJiurq6OHLkCL29vUxNTZFOp21z0ZqaGtsJXkZ3SscUVg+551QB3LUBgPzKLLd83xUBuy+d+zda3HV07pTakmmmC7CUpnNZJ7XzEIPlVpmJwRwfH+e1115jZMS4eYVCIaLRKMFg0Lb6kABfKUC5aCvFqrnRMR9//PEWwMj4Ux3UlfJTZVV/fz9btmxh3759hMNhTjzxRDZs2EBra6u1CtADh4DV8PAwyWSS8fFx/vSnP3HvvfdSXV1NPB63/b3eSovEjNVAgAwGLaRhU8QEhL8aZrJxn7mvPtEENHtBoXbSD8KYuF7kFaB3gLkpn5vfhmnEKZuJgq0NX4eJl3uBYi4CToc9+W4im/GrlhWHBylhA6uMCnM5fiDba8bJarPx1CMG7CSB3iz8/mZMEHQDp0ds1f8BU+GkPhqcbD7U95ZjGqt63d5ZDu/qgtC0IRQaB/1k2JW9eD3GjLqpiEngDiZ4B3xxgZ96K/YObgkmRdPsje1C/DJvgYBWYF/EfJbE68dgcl/qtPDcN73hN2AmJPtNMzkfe4GBNPBTyF2/m/fwj1B7J7T8HfB1niHGg8Dey7y5syVA5KVh7CLqTsi0EBThzLHe93ppvS495uYFNfWFiwt23LSlvp8A2wY+io8z1arKZYrWYx3C7b4Wwod34Jc/dQOPwIfvhrsxzI6uw2ZgEbuBNHOcxhxvZ44IO2ix6dswEGSaNNBHjJJIOcX3lPhoSGm+TvMK7YPacVg27gvflwCbuZ+tQKDxRh57N+YpQQK2Zu/n5fhPB582AJ8o5C48jtz6cpZS7Bs3vsHypoBHzSgVJGU4KFBx6NAhmzpRYKmoqLA0vNJTR2N4Kioq8gzc9GSsG38hk6TgtGvXLioqKmxgcau0JPItLS1lZGTEfhYKhaiqqiISiTA1NWXHe/LJJ9PY2GircLLZLJs2bbKVMErPzM0Z5+XKykp6e3vtE7p6OymIZjIZ20OssrKSxYsXE4lEGB4eZnBwME88rePTsaXTaUKhEGNjY+RyOTo7O20lzsTEBIODgwwNDeV1gnfTH5pLsWEK8NlslpoaA3fVl8x16o3H49bccNOmTdTW1lJbW0tfXx/PPvss8XicmZkZXn75ZdLptHXXLi8vt+aQCsDymlElnI5X59WtFCrU5xSmm1wPG6WM9L4LfAo9jgpFzu6i91wDSr3v6rlqamqIRqOUlpbmmRPqXDU2NtptptNpOjs7efnll21Vo6wUXLNMXcsyjZQuyAU9ABMTEyxYsIANGzZYo0tdAwLYutZSqZRNz27ZsoUtW7aQyWT4+7//ez772c9y7LHHWr1dJBKxwGduzpiEDg8P09zczKZNm7jrrrvYs2dPnij8rbBEMUG6GsgRwkTXc81jZRhgL/wsv9qbhdAWBbIRAyySRutj+G7Dz4f14xq/47VscqCBaeppAEoG/dgUx/w86yUOanr9ntICQyIbdmKegMuYAZr5y7vxBT9yuh0AWuGOe+BKMxQOXA8lHzOHSDN+OkFGcytg50XAWdu8VJS6g6UNsxMGar1a+2t7CX4ban4HW95rKtIUN1XcD95+/uEqIMEcf0buKd+h1+xDT+gSKp2LYYYSGNFIMX7lDt5xLpuEq54y612IGThrGAG20wK33GSIlW9gJiH4VbjgeeD7NPBXHrzS7PdPGyD35McBqOA4LmOMjZjO5L9ZiQEKKrsbwQTmHu9/MToK3OCzLYWZXzeFBD7Sdiuz4t6xCviI+XC1OPq92vk5TD7TUY1fSqVtNOC3skhjLobrvblUM81OzOl+FF+ko9TcXmi+EA78wL/ENMxFeC1YaPU2XM0Mp3KQFg4TpJQsUaCEMeaIkOFtBL6x1rAx6kGaALaYn4v2Gl+fJWk/IyiC7TnuJQoEVv4bO0+A1HvwwXAUWAIzJ0GmBZr7YPY70PMocDW89knIXRswJpNvsLwp4HHpfQkzJcBURYlAhQSfsVjMamnEqkgkq0UeJq62RWkKlzFQMJVIVE+99fX1Np2loKJ9CcykUilbtaJXJBKhurqapqYmjjvuOMLhsG1W+fTTT/Poo48yMjLC+Pg4DQ0NeY1L9fQuNgewgCUajVqBrEzeysrKGB0d5dVXX7XtOVx2ZXJykiNHjlgdicqelRbZs8dgaNfFV6+ZmRnmzZtn21i4wu1YLEZFRYXtI6Yy/UgkQl1dHd3d3SQSCfv0L01SW1ubLVlvaGjgbW97GzU1NfzoRz9icHCQVCrF7t27OXjwoGXKJBBXkHTTUwrgCuhiJnStaCkUc7uLjluAx10EjlRp5VaFFZbGu+sIIEovpUXXWHl5uW0rIoAglmVmZoZDhw5ZRlHHmU6nGR0dZdeuXRw5coR0Om2vq2w2y/j4uHXIVmm72p+oZ5u7Pf1dve997+Oyyy6zY1S6UoyVUqj6HeDZZ5/lwQcfpL29nXe+85186EMfYvXq1ZSVldkqMom/s9ksfX19jI+Ps379euLxuHXUfistccz9NkOp985Oc/O/DqAV7jP30n4wT8tbITfRC8Exg1DONTF6DcN2ewPeZmQs1+Otb7oa1LCPItIYZkcdAraVwsyvIMQ4/OQdVgD9GQzp0Qq8FDUgSH6xE8SABvYAbSdgUjwXeh9+Gf7+UyYU/f6T8B/HY4KLhK7y7QEDKIqBc8z3Q7b2ex0mAkah9nYPdPSYAV/eRPYRGP6eWT9bk18Nk/DGaffJakz0bACeM6X7/+F9WQyHqpE6vXVUzgw+67Pqz9AVwdT1YwL2nbXAarbTRAldXMO91GNSj/AbWPBZeOxWePzHQJIreAcn3gNz/wHcALkntvFJDKb7EPBbj2FggzdHElNBPgjR/0l8dW+afHbG1ehQ8L4WASu3omuW/OoqN+1VKJIu3K6r7xGzJNCz3Duu5fiu0XsxF+dWbx35DCQx13iHv71fP2l0Nr8maA99EYMU4VXecY63gWZmWcE0QTvsEONIxR04ZS3HfId8wJLEPhkU98E7xv2MJxh2qQPYzOc8M+tT+Uoj/GUl9NSYUvXgjEmL9TRCOgxN46aK6y/fwTRJc+e9YHlTwOMGETBltarWmZycpLGxMS9lIHO0Q4cO2dRIXV2dDUAKjrlczrZ6ABMUlQJwQY/0B5WVlbZ7uf6PRCIkEglyuZx9EldJM2CbUEpfIfDT0NBAS0sLtbW1RCIR2tra+O1vf0tvb69liubmTKuHTCZDXV2d7eIt8WtfX59lBZQCkC9PbW0t4XCY/v5+ent77dy4mhONUQFOKSu1rFAaSxoPgQRV3lRUVNgu3zpPanCp/ciLZmRkxAI+nYONGzfappurV68mGo1y+PBhkskk5eXl1NbWctJJJ3HiiSeyZMkSHnvsMUZGRpicnMzrvh0KhaitrbX7FMgQiyQti6urcYGvOw9H0/AIlAkM6/tuGlT7cheXMXIZpEKApNRmobg6mUzmeSmJ0ZyamqKvr8+K0wXipDkLhUJ0dnayZ88eC4RdlmhsbCzPyVnd4Gtqauw5VXoymUwyODhILBbjwx/+MIsWLbLeTbq2BfA1BoHLbDbLrl272Lp1Kz09PSxfvpyLL76YhQsX0tDQYNlLgenBwUGeffZZurq6OPPMM9/slvDfbgmDrXQy/3bAQ+cT2AfcDLwQobgT+mphuAWohsBTQLYJpmI2lfEhwNzIU1TjZSU8Ux09oSruz3o/i12XprRqGvjAx8kwH3aacV3d5Ot3q4FoEi4AuqN+EICoFYvOLIDUlfDRB+DiGvjFzfDrq/HLaMSWCFDoKd4DFW3vNuM5nxmD3MbWeiuup5ivmAf4m1qMgeCvHvLNT7x5yJT60hbF5+K9eMBvOZ5FIiG2kwaW1gZ8bYlSE834KaQw8Gnv/+MxoGLf2fB9TIBdjWEpfgZkVwG/N33MgCc/YDZ7QuB7sB0zmvP/DPefDfwX/cDHKzFVac/Bl/5gdr0Q+Inn+Nu5CJ/Z0QWjxWVr3IotV4w866yXdH7X5LhVXoVl7cXOHBRWhbnpMDFMLiBzt9mJOf9uefhmZOftAzQBpE7YewY+ABK1KDuCbljzbUhvz7IEGKOEHsopJkUFj2Nqu6T26WeW9UxwPhPEvLSxav/LOcglBP71FjK34Jd/7cGCnqIew/Ssxlwa+nu5z3v9K097fW1jPOAN+ZWIf2o6gG2VZgreNQlzfwc/+whvuPxNhkcpKTUulJ5geHjYVp5MT0/bFgui/QUOAPukLMfZYDBoxaKunb5SMwqcepIeHR1ldHSU9vZ2YrGYBSTBYNCyJ65rrYKTQJN6PS1atIiGhgYCgQC7du3iySeftD2d3NSInoCHhoaYmJiwbQRUeTM8PJwnKA0Gg1YHNDo6yvPPP29ZkMLUisCJgrBSdvF43Aat6elpiouLOXTokA38gUDAOk8L+FRWVtpjVODXXDc0NNgUiAwRy8rKePvb305RURH19fW2eemrr75qS91zuRzz5s2joqKCpqYmNmzYwAknnEBPTw+BgPFAkmi8r6/PNlR100zuUpi+crUwLgtTCE5cQbLLArnvu0DqaIyOWxKv69ldV+ORkFyLROi61nXelT4qLS21bssCO66BZiKRYPPmzezZs8eeP6V1XXaptLTUsj3qSeYacxYVFXH48GHGxsa49NJLufzyyy341XWvcUiorPnQ9Xno0CF27tzJ8PAwa9eu5YwzzuCYY46hrq6OkpKSvNTgkSNHaGtr4620KF6YxeP52yB3FlDWBd+F2VZMsPWqd4oy+KWxXvmy0aWahJM0w8VecyzpREUCdOCnfJZj4sn30U16M3AhbDW/f6TX3OAfwPc9SQG5zwqjRIF624Po+aCJUXf9wdPpCBWF/bGCN5g2TCQYMLvkZLMPEQv+07DJgczSbgLS3QAbYeoDftmwNCL4AE+EzbyMN+ius71PryfDKTyAR6Kt8yZEDosJKHkBn8a65AXfrbcBa+07x+2w7Cbz2YXexNLAM3zADKvNDOvlEOS2BejgTnPAV22Dr8Xo44vczY8JXlRuDvwlWHPQTNNm4LQstN6NQbOFQOONKqZcEJTk6GyCu77L/BSCHxlGHo0dKtyWUlUu6HG3J08el4HabObIVnTp+wmPO/PAjy3REiPY6a23EZ7+JbyKuV/NsJYJVnkbug8zkx/G8J/rgA3Mcry3QdF3JlFVHPkAge/UmlW24rNOCSh+Ber7zJ/gcvJdF/7iDWclYwwA12DSkd/H99+RLGpLBDZV+inmoy1vCngAyzZIRCufmZKSEhKJBFNTU6RSKRscVI7uBj8BCKWwFKTVSFSgyjX0E3MjwfLk5CS7du2y3dAFqlSGrrSTFlUxKZg0NjZaW/3nnnuOwcHBPC8g8LUiYleknZCRogKEjhew5doTExP09fUxNDREeXk5kUjEBh4tboCWgFapMpkkBoOmK3wmk6Gtrc0KX9W6YnJy0vYEi8ViDAwMMDU1ladJ0bzKaE7Mm0r6xY4pzbJjxw6eeuopDh8+TF9fn+0DVlRURF1dnQ2209PTjI+P09fXR0VFhW0VoookF6gIzBUCFpcFOtrLTe9oKUx7iVUUQNZ6heBSQMj9jt5XObm8k3Qt6TsCJgIxYielt3GBjI5dWjR958CBA2zdupVUKmVbR2j7YtgEpNX4tbS01Gq6lNYdHh6mp6eHWCzGbbfdxkknnWR9otwUcCqVsq0vdC507EeOHGHbtm0MDAywZs0azjrrLJqbm2lsbLTl9a6G7q2yeKbDHujZAJxu7sWf976QxNyvP4iJzlHIXobR+OhxU02prKWs+fd/ZoCyQV7CAKLNmLiz03ulMcRENeZGPqGMAB8k+Ip5v9Xb9V4MkbHEe49LNebVQJrfAK0/gHVfhnPuxkcckO/M63bMVhVPGNhonG/VYuNCgOCd3k6uAJZTwWI49Vum6zQroKwXlmX8fl0NBgymgUmP6RmXZ9AevK7zPt91kFUGKH7sBROdlmMQ4U7PcLDNmyiW++mXNc58j91iNtyNob1+AyYy321W238vO4EzPS36okl4gJvMup/pgstvBx5ljo8ReOCP9HzBnKSVk/AD4KtBTJzu8SZdaS2XjXGZFy0ueyOXPr1k9ud+txDQSK3rmjO5gCZR8L/GUe1sK+3sW9O+wjseN3UmgXMxPrsWNZe3vQBXYy6IavzcrHRNHQYUZv8lxbvZ5kzOGsxVO4DvflPtbKwV/2JUud65BD71RXZuxC+nT/k/l/eZb67B/C2scA4NjHHnTzG2P/9OkK9gXBd68FuZJfFbYRxt+b+6u0nXIA3CyMiIdZwdGxuzpdGulb30CbqRuhoWpY4SiYStXFLQd3U9rlhT6R7pdsQgiZUpKSlhYmICwGp6pMMoKipi27Zt7N27N++43kg7Ipt+jVfl8QJVMzMzJJNJW9Wk7uGuA6/Sczp2ARw3MLupFGmMJiYm7O9VVVUWmIiNmZqask/26k8mcbmCveZoaGjIpmPC4TDxeJxwOMz8+fMty+TqnXbv3s3w8LCtzKqrq2P//v20t7cD8La3vY3KykqGhobo6emx/jINDQ15Wiylztzz4zJALrvlMjduWqtQxOwycIXbEShx2YrC9JkLhlxQJSDjCr/ddVxvGxeQCZhWVFQAWGZO49HYJiYmePrpp9m5c6c1MRTbMzY2ZkXuAj+qGJNzucY7OzvLoUOHSKVSnHPOOdx4443270KM5uTkJKlUygJTga9MJkM0GqWpqYnx8XFeeeUVxsfHeec738maNWuorq626bKjMWX/nRdXbwLA7ojXLfx+yLaY+/SXMfdptR0YwdxV9QS8UduRHS/2N9jDg95+rsPcnNX5Ieq9B7A9BJx/J9APU2vJVviZpyUYKNYM/HKZJ2ReNugJoBcCK7hAO12B/wgsEax7sF6TRq+u2A/YcfhlJN+DDtoMg0IS+CcmaMKEjxRGTXwCMGDFotTD7HKT1iry2mnMxs0awWH8FApbMUEvTgewiJOkdTVsytX43jCPYPb5gUl/ahvw22qz0ByDsdqB+0MwVstm4ARuogF44ufwmxNMX6b1wDf4O7OBrwMLfuud2JdYyLU8eA2ExqD8IHxpB+w9ATO2T5LfAdZdXJbFfQ/yWZZ0wfcFOovJb0TmbqMwzeUurn9SIcOkNKXea8U3/Ys721A53axzfAmTzbXiZlEiO/E17OoYq7F1w9MbIPdEl7eCaKMEpoxuM35plRwny50BihLby/F8k8A9t5hz+giqbYcOqG83gHQ55lyegyC/+doGTuVTwB1k+RBwF0Fu8Ebg6rvfaHlTwCNa3aXdp6amGB4etmLOxYsXs3jxYstqyPBP7ImeavXkClhfGZkXqkFjdXW19Rpxe/0Eg0ESiYSttFJAd92bM5kMzc3NBAIBG0RcTxzId+XVjV1Axg2WbjVVIBCgqqqKaNRcqSqTHxszduUCDICtVgoGg3R0dFBeXv66NF3hIuAxOTlJdXW17VGl4KyURiAQYHx8nLm5OaqqqmzaSaJXd/uqVguFQjblIZF5eXk55eXlbNy4kWAwyMDAACeffDK5XI7JyUmef/55y+IcOnTInoc1a9Zw4okn2kaj09PTjI2N0dzcbHU9mg+xC4WpvML0kquzcauvClkgdx2BEBdU6Pi1HZ3nQt2Ye55doCnQoG3qmhC4KSxjV5WVrj2lDaU/c683AaH29nYefvhhent7reBe31P7ktLS0rwHC4EeN8V16NAh2w39C1/4AqeddpoFRHpgmJ6eJpVKkU6nLQDq6+sjkUjY9O7BgwfZvn07IyMjvOtd7+K8886z6d630qLCnxlOBZb7sZhqc5f84hjEboX346eBLiDP8fZKNcr0lCtR2gmjCqsVdAAfpI/bMDDhUcxNVyXmO1pgth5CfBr4MPzQlHZLY7oGn4j5yD54DoBHvNiYBlabym/X9U2BTD+7d3kF5yh+2+kVhjgpBz6f9oyWCWP4JVELEjCXw9hpZgNjTebtYn8ysyUw22xcpoMT5jjXTuvzndjeAkR5DCPR4VqvxF+ptyvwLaZ3LwP+4jdyWogfS0nDqofMjqUsb4NXGLV6XK66lw2sovxm87VPt8O/cjq0DBrTITAb3PRj7gN+1Gg6fzMCy3d4h70ZX1Pjzqk7r24zT02ZaygIPrBxdTOuN45eOne6QF2XYbx1q53tHC3Vpm0V9s5yt+XqfYQ7qj0sI7DWgJ8fEvMkfAK+6j4N3Ae5u3/CA9zvDOx4zB/WRnwXnwbvfbE7bVhfBG8wgSt/xV9+iH/JePRjaB8szpoxHo//N3Iy0MjT9BHjk5zPPwPvJ8s6zN9MM3BBH1x6kDdc/qaGR4ClsrLSBk2JdROJhH06npmZsc7I1dXVeeDCrdBRxZcEyKLdg8EgsVjMGhxWVVVZMJFOp2lra7MC0LKyMhuogLzSZwEtBWGBJwEnASC9tJ7LSIiB0mfl5eVWKC0zPjEqKi8GI1wWkyWA5AZ21wdGgVMslI5JDJHAQnd3N3Nzc1RWVtr5VWVOb2+vTaNIOOwa/2m+Ffzl8xMIBGhubqaoqIj29nbi8bj9/vT0NM8//zwTExP09/dTVVXFihUrePXVV5k3bx4XX3yxZSIA63kUjUZfl3ZyX26J/9E8dFw2p1Cv44Ie9313XffcuaDWZS3EKrngR4yMu3233N99X+vrPLlpOreFReF4XcfsLVu28Mc//pGhoSE7ZqV1U6mUvf7j8bhtjaJ0r0BaKpWis7OT8fFxTj31VG6++Wbr+C0xdSaTsazPzMwMExMTjI6OMjw8bAX54XCYoaEhtm/fzuHDh7n44ot5//vf/7pz8995kUTB3DqXmLTIj7uAZvjiIHAPLPimYRtWG7dlFmLM8TzQoDJxP+IM+ICmt5adQIYYMcY5F98WZT1m3eIe4MswRwg4F3bmy23EPqnvp4lfe/3Ytm+ZqSAvL1hBQqFCUa0hhcz3ZPTjFWXNAivD8ElWYf1zB1eZg+dqbGRMYv6P/cTX3ji6kWCfAXFFbieSeuD+73lHEAeSJPBseviuiXkL8btBaswPegfjiq7VL4wkNVxuvrsavyrp8Rh/4Hzaa719d+2CVrO5vUvh1iwU0wi1YzD4Z+A6OOt+nvhdzptd6DnDG1wHviePrxT3Fxc4CBS8kYeOm+KqdtYvLlhXZe0uwIJ8oOGyOe7+3PJ3ESlu6bx+7iC/sgwsHtkK5nwJf/gN5/KZrkJA12C+88HrIXf3/byb+70BXOBt7Ifehj5odmSlyEJlMoeqB15iPd8jcN+vfJDrAcGSXdAybtZegXlGOR2DTU9gjGI20keMX1LLbyjn2xgpdaAqR2DR93ij5U0BT2lpqdU2iGpXdZUaG87OzlJTU0M6nbYdvuWSXFJSQmlpqWUY1LahrKzMPiULbGidpqam1zWQ1OdKacmi3w2cSmMBtjLJNe9zWyO4wch+7KCFAAAgAElEQVRNkeh3aWuUsikuLrbeP6lUin379tl0gRgwzZXbvHJwcNCCJTfYS3vhCnhViXZMgdOtnt67urqYnJy0KbSBgQFKSkqora2loaEhr6JLgE1l6VoCgQALFiwgGAxa8CSg0tLSktdP6sCBA8zOztLX10cmk6GlpcXOwZVXXklpaSm1tbVks1kGBgYYHh7OA1uaZ3duXUZGjE7hd1ymSOsIsGl9V3vlbsOdT23HLenXNo+2LX1XQEdAQZVcbjqsuLjYasSkJdLPbppSi0CSvjs6OsoTTzxBW1tbHqOkNLHYHP0t6W/P1YQVFRXR2dlJV1cXpaWl3HjjjZx33nmvq0DLZDL2WNTsVulaVfytXLmSefPmsWnTprdkSsuwGRdAVwzKoZilWL7jHz4LV8DSezFOwNea9ZZKbxM2WChpt2Yilo1BTV1MNEER5jpazzBhjKhSD/tzIeDah7xeXksgbeKs2zKpEz8j9Kj37y8Imr3stXrd16dN9HNhBZEcor3gtfcis589GJlp7ondGPTwqHcgqlNOA3/xAt0PzHtlvSbSrPH3U5QBFsJsuVMEttnbpB1kymZIiviq0U1txQS2jfiAoBvYt9bXnwhY1ZuDvhlMQL4avz12B8BPCU4ArDMM3UajA1mShj8G4T/JAmdCbRfwM/jaVZCA62/K0QE0D0PmLMzJuA9f8IUzn1rctJY7727Gxv2eLpBq53OXEdJxHk207GpwCseTxtf+uHoegRSxM93ecXk6HPbgg5+o9zfhmhiaAsR84OSORVkq7c/rovv09ZDr+xq+gdG5+KLl9ZiTVo9JTrn0pDaaBPYQuOh5PvoRfNKoB4p2wkKngut4zCW4HHgnWRYxRhGTzLGY63kHG4GPlAV4Nx/njZY3BTzSxshfZnp62hriVVVVsX//flsNpL5a1dXVlJWV0dDQYG/euvm6ugnpcGS0p5RZVVWVTXkJbHV3dxONRi1r4qZwlC7Tks1mGRkZsaBD4k7ACo0hP6Dqf63j6keOO+44li5dSnl5ua0W09O2qnTELMViMVspJRZIVVguu+P6yygICcTNmzfPCox1nCMjIxa4yehRPa56e3tJJpPEYrG8Sp1IJEJlZSWvvfaaLfuXbqSmpoZ4PM7c3Bx1dXWk02nWrVtne43Nzc3R09PDvn377Ph0LmXAeMMNN9i5FNBxK59cxqZQP+MyNG5aq5BNAfLWKzx3+lzg2P28kAVyP3N1VC5AdMeh912GSpVUGvPU1FSeC7KrNXIBlmuaKDATDJrGtA8//DDt7e3270EifY0/Go3aNK70aO5xz87O0tHRwczMDCeddBK33nqrbX0yN2dcwN0y9snJSfsSo3r48GE6OjooKirihRdeOOq8/XdeRigHesxT5N0m/w9tcGcEfn4/rIP2D2CCw3Lgn81tW2XnYO7DGU5EkUtZCkjAoQxPUUkR+4HvSvtMh9krddOYjbIOemtho/V7JomJs+swAmdZ0pxJl2dQuBB2ep3e/wdGGFzYHtqrvAHy0xmKL/WeWTEG1hyP1o2aeUiDoSD2eMDtBojJlXo9dHlpLXXwXmh0PIHdUDFmVu/GsD4GiCxHfbVnKacb+DQpE4zlntyPQXYSFG3Gt90VCPgRWCFJi/dg0oqJnQPAplqy/d5BS3B7DRRPmPOXBh7lBeBMYA18ZtIqWq//xxz0Q+i93nnWxDuVTHlz6JoEHg0MuZ+774MPPDTvUtjqd9ejxl3c/acL3ld6M01+m4vCl/aXKtgG3vuq4lMKV+N2GarwG7yavdcdkLvwJzzCtzAg52R88XoCc1KX4EOX8FF28gXu5osEqnI+2K2G4mGoPwjHZX2uaA3mEjCpYL+3ShvlPHCUw3SXNwU8VVVVVFZW2pvn7OwsVVVV1NfXMz4+TlNTk7XRLysrY3x83KZrKisrzVx51L+0FSohV7mvAMHg4CBTU1PWel+VSZlMxlrn53I5W94unUMgELBVRRrj0NBQXmAtLi4mGo3aDtiQD5rABzwqMa6qquKiiy6ipaXFuhwLsEiQLFfjYDCYZ8kvXY56XrnAyNWEuIFUoEkO1DqeUCjEoUOHrNuvxqztKjC7oE/bLS0t5aSTTiIcDpNIJCybMT4+TiwWY2hoyFYiLViwgEQiwezsrD2W/v5+Xn75ZWsNIAM+pdg+/vGPs3LlSttjrdBJGchLF7kgVf/rpUVjLNTaFIIpdz+F6Ss3Lebqg9zz7Gp8NBaxI2JdBIClq1GlntJXLpMjPVlhlZMAqJtW1fnWNmQWuHfvXqtN03lVlaRSpwLwLlAsKiqir6+Prq4u5ubmuOqqq7j00kut14+ArPRcAq9lZWUMDAxw5MgRy8K+1aq0tgJzvBfYYASSTQu86o8/wcf+EajmG+/Df1q+Avi8Vyl1H7Aaq9fZTgRFY2lwze11K8cDAxwPXMeHeYL/zXMsxACBvrPB6he8qn/FIhEA0kt/HoMDZI6rVM8ci/07+VZ8oaeEq+7Tfj3KI0ErhDcGbf/JejydczMUMQrs9cRIhl6Z4xYW0WvWHVtmRtgyaEwYo/42c7Wm1UQaw2AtBBZPYwLo1FcxsKqVOSLWeoVrHzIBciu+lkcGfF4lmRUzWZfoc2kGQkRN9diAc2xtQGwSNjXBOTD3LAbQ3GGYHpM0gX+ly5vVlGnR4TkUB27LEdi8ypB9un27LA/kszhaXHLCfa9wHaW3NPHuOdL39HthyqwQ4LifuakyjSGJ3/4iRb6pIfho4UJgPUagLtQNfsWWsk2ulkhitEKgE3b2czxcej3kbvs7TuG92NwXnd6X1+ELhuREKOOghd7AGuCsmwgs+guBU9bavxWAklHTjmIN5nL1HgVYApzJbip4gWJSDFNrnLjfYHnTu5tAi9I6XV1dVFRU2I7RixYtIpVK2e7cmUyGeDxuU1ai8KX9cYMOmCAzMDBgn3xVViu34dHRUdsZvaKigrq6OtuNWlUyc3NzeQLQ2dlZDh8+bIWoAgPqf+T2fXJTBG7lUGVlJevXryccDtPTY/663JJ3LXp6doO9KqPUY0zbL3RadrUkClo6Lm1LP0uXIa1OJBLJY2NU2u6KXAUse3p6GBkZsb2UxNIIGLpakeuuu85WgSWTSebmTBPW3bt3A5BIJCyQFLtx7rnncu2119pzWthCpBDQFC5H0+7ofS1iM44matb/R9uP3hfwlTmgUrTqbyUwoc+VRlIVlsw2ZW6ZTCYt2JC5ouszVZjG0/G4x+iOTYznU089xe9//3symYwVo+u6Ecujseva17allevs7CSVSrFw4UKuueYa5s+fb1Ot0tJJg/TSSy/ZxqFiYd9qi3lovRr2xWAnnEAv5xKDW0NAPdx0viESqrGCWLrNvf+aXmzAiKI4a6JRPWmnbHzAxp45G+UeoQ2jFeE/93nvXQF7YemgeX8dZj8p/DZBYeC5WsVCL6ex2jsYNxBtLjhIV9gaBcph5nH46H1wMdm89kLVmO2UK4cR/DNMRVDBuu2a0I0RLascTCkngSwgHTWAx2KuMIbM4iU7GFmuLOJy86UN+KBhOb4V9mZ8FGgf/h/kZ3jsWjZkFNAK5I8A7DT9Sr8LwTNypuLOS9GsSPutO67kc2ZgDRgbYZklvm8Xgf6fmy+JBSks8zla2sn9zP3Z/V09rIq9OXPZt0JQ4547Nz2ZLvg9Sn5vKYGU5Rg0sA5znbQ631uDobzUbqQbKgRqxWSpJ5eQvBgkNy0Xxwc67nwUfPbsv0B2/L0YPY+aR7Th+/W0ejswxoX5ub0LMSfngwROy/FgI8w2QmeNSZ8Kl63w1rwO8+dxMuZcF+fV8r9+eVPAU11dbdmYqakpRkZGqKmpIZvNsnjxYnvDF63venm4N1ExIzLQ05NtKBTK6/qtYAtYsDQxMWEN2VS+Lo8ZPaHncjl7E0+n0/T29trArmARi8XsU7XbPbxQK3Lsscdy/PHHMzU1xY4dOyzQmZqashoi6XDEKAl0aewzMzMWAKZSKevJo4BcVlZmA52+L4CSyWRoaGjIYw9U9TU7O2v1SUCeg7LaRSgIzszMUFtbS1dXl00Fagzz58+3FWXqgVVUVERNTQ1XX321TZfJv6erq4sXX3zRVunJHymXyzE+Ps5pp53GXXfdZZmeSCSSF9ALdTpaXDBYqO1xAag7Dy5jpPk8Gqhw9xkIBCwDo7kTQJLvkgTxbhsSVcEJSIplE/DR/BSm3dy0k6svckGc9uOa/8mN+Re/+AXPP/+8nUu9r8o7ad9ctsmdi6GhIesGfv7553PeeedZgBcMBqmpqWF0dJSJiQlbyaUHARUCvFWWdj5gfugE/m3Q0+62wzcfBxZy5b1eFa8YhiSw1dx6P4j5XXHJ/G+iUBEZ8/tPIkA9z2FuwF+lErP2h6ycwih61kFvDJKGxfkEvoeI2k8k8HTJd5vYUcQRoA3CEOI1c5cv93Yksa2bvtC9vhqO/QKUvAp3/dSMeAt+u6ow0HmKfE7CWBdE76m8WhM2AMSeMj8PRvLMB4sHDNAJJw2z0+2Ju63GBG0vwTC1dFFisEDtmJ/x0sTKgE/VUhKvtgKPf49zgH62mWNbjwFiEtmymkXboKTXbC9wwy6z2x9Bd9hsUgXUV/ITKLvV9On6NZb04fKrCKzK+TqWQn2M/i9kZATawE8HHQ3EgB/3w974XWCUdtYvjNWF2qE1+EBIXXHVEX09PlAxPoDm9UHv92YM7hjw/CTVbkLzCb4FgUTWKef9Ecx1J8BZjd+tXYCpGIhD0YOQu3sTj3K6t1O3CZzymFH8Bmsd3o6Kvc9WQ8u3uILPEA7fQhjYHzRDWpw1W/k8r690PJYsjQzyRsvf1PAUFRVZrc2yZcsoKyujp6eH+vp6y8gocAgMSMwrJkLusbox6/vFxcX2CXNuzlj6T01NWVPAcDhMX1+fTWFVVVVZ0aXAmNJVCt4qyZZ5n3sMYhLcIC92qbW1lXe9612UlpYyMTHBtm3bbJNIgTTwg7NAisCPUlBKO0xMTBCPx4lEIrZfliqp1HxUQVCMjpiw+fPnWwCkIDkyMmLBlVJmbh8lsQGFaZaVK1fy2GOPUV5ebn189u/fbwGiQGgqlbJpG/XUSqfTVr/T19fHiy++SCAQsKBLwXpkZIRYLMYdd9xhdUwKwG6vLR3j0cCPm5Zy01hwdLdmgW0XBOn8CoDoOgSfoRP7peCu69IFJa4njtKuYnZcYK6xqPRc14hbNq8KLBeQqPJKL1dTpG3s2rWLX//613R2djI7O0ssFsvTGenvR+DZFfC73kJDQ0M0NTVx44030tzcTF1dHalUiuHhYaampqx+LJfL2ZTlW2tZA3RDP9RQx52UwLdqgefgczcC8NzZmOC6AXNvbvNjCmm/R6OJgebfEFPmp50Ae2nD14D2cDIbWUkYaG/B+2S5GcNXTQZFHj0XYtI95zPHGrz48oHPOnHT5NSWMWMCmhv8pL1wAuvsD+Gj18DLz2D0Pg1m/PKsk261tQ/P2yeNTxeZuu9BSoB/hrPGsG0ka8dgVcYE1+WmLD1b4TcUrU56ahsLdqThMB7VATLeEPth2QtGyyrA4Jr1qYM33mR+xbxVlcWkr4KDZpM3A8+YE3CwyROGtwLcQeCes+ARaH3SbGa9mUUagHfzLeA3xlDx8xgiqsfsP/CxnM9quKxKIaNRyOS4i1sGXowPEl3i4Y0ICDfVVajRUipJLJHR+pq56ia/14fYsYXAOsis8n5vw7pbX699uk1K1YOtH+uI/TqpTRwf7AjkyCEwjd+E1ZvDC3ZA7uFbuYy/wy8JE60kqCJjKTe/GcUwQg0YD6UUW4HmV+DVoD819fjk1rne7xrO0ZY3BTyRSIR4PE5RURFDQ0P2xr5q1Sr7HbWSmJqaslUf4FezSIejIKBgqNSHRMAAR44csU/boVCIiYkJjhw5QiAQyEtR6WeVpqtUfm5ujrGxMUv/gwlwSlu4zIH0L6FQiJNOOolYLEYwaLqNb9u2zTJW0nMAVlAq1grIa3TqgqFEImGbig4MDFBWVnbUcmcFLwGzo6VF3MocaXdcUbO+Ozs7a/ejtKP0UG5ps3scQ0NDtoN8NBolnU5z5pln0tvba5/+db56enrYsWMHmUzGMkrRaJRQKMT4+DjRaJQ777wzT8/ippQKK5e0FKY6Ne+uvkbrFAqcXXAlsF1YhSfgqHSWGCCdD1e0rP277VBcJk8gQ+MV8NA1qnEWHp/YQQEgjU0vASgBTf2/ZcsWHn74YQ4fPmy1PLqGxfjE43E7BlWLpVIp4vE4ra2tDA8Pk8vluPTSSzn77LMZHR21KTrApqXVm+uttXjOaktgnCAZ9sIttwMpTviqF59ld68WCElsGoZq73/k5yZXt37TfmkjQNjqcH4aM8+qJ+PZ/XzefA4bYCEMx0ys8OqjeAkT13d7t+KtQAlfYyEwx3HAu6DZ3OB71DlaQa0fH2BUw2cegGvCcNcrmBrdBHS+x4/VinkNmINbaN/tNNubuhboIMO7qeB33lpXYCKr53CozgGiTYC+JrOtTuCEQbwd/t6bwShFTFJE1iMxPMMj6XdclkRBPYmJXM3AaiOlygQBzjIH/2FMkF91rzkB/2UMEQ0I2cxFbOKYbuAL0Hw1tL5iSIuod/bewz8APzKH9gNvDj2DycB0TqfXZ6sEMI4GfCDfUDCMAXDLnd/FxLhAtTB7rIqsQn2PAEcxPgskfAB+R3et1++ssxxmFsPBCH7PLA9v2MNI4utwinm9+aKutTgGn8hmR87U5c52OvEnOemNs8cc+6/vhtzNCyjifZi/SU269zBAA34CUgryNOYp5GHgYq7nMwSeybEEuK7dJzblJrACg6PVDeVoy5sCHhn4Kf0SjUbp7++3gRGwN1M5JqsaScHXZR/cVEQgELDl3GCAidpVDA0NkUqlGBkZsTd2dROXDkfVXwI9eqI+cOCATVO4AUrBS8GvuLiYpUuXsnbtWqqqqojH43R0dFjhp3yHNGYFKrXS0Jwo1QBGSFxXV0d/f7/VNaldgdsuIxaL5WlAFKgBy5KJGXMDvzxzJDRWis6tKhLAnJ2dpb6+3grLpb/p7++37Sb6+voYGBggm83a87dr1y5CoRC33XabnYepqSkr0D548CD79u2z1WOa42AwaNOTDz74IM3NzXbcR2N0/m8WV6PizhX4pphHK21XeswFuBLMz8zMWEBZyCBpn5pzpRjdRp21tbV5OhiXzXF1WQJaGqc79mw2a4HyzMxMHmOkvw+X8clkMvzhD3/gvvvuY3R0FMA2mQWsd4/ApdaRtcCKFSusAeG8efO44YYbqKurex3gkoP4W2vZC7vfAafeT5ZSeLoFGIBvfZM4HpiRmFNtBhb6cYQGeLXULx/3I9Ms5UDJPr1nYkFwxlj4fAcPi7iNfdpg6ZjfekI9Odd5W1zj/X8bim2mAaOC2X3alctCjMDO++Cj34GvPQO/uN4cHuXAClPopFi40zvU5nasTslurGwMyiYxkfHLHgZJwE9inglhGLpC/iA9vcZcCAJj+dZA7MTTSPk0yBxBBijnI+w2R9rUlW+kKEDgAiDMeenjLM/WbhtQD7W7IQwV3GSOaNmYAS83A9lDLAEOE/SDf9SMa72z6RO4CcqeMuf99/jdX5dDYG3ObC+BP8Y3YnTebJF3EeSDEhc8hQvec4GO5qPcmR/P9dgyPTJucqu90kArZGJwJAitz2BOq6wK9sJZ497vzRigo7mSc3exd+zNHN25udN57fG2r3J5EJr2x+VpmLK3pcjdXY75K5G6PozPwxU7K4J5ongOfvdnIAU3LiD6kxz/Yyms2Z5/6OCnuN5o+ZsMTyaTYXBw0HYpr642l4zK1OU83N/fb9NFetpVSkt6EcBqcVww4VbMSFegbuBus1G3OkvbUJ8iMDqbI0eO5OlyBAg0rlzOmAKedtppVFVVUVpaSiKR4JlnnqG7u9umRurr6/PWU9AaHh7OE3cqrRQOh4nFYiSTSdsnSXNYXm5g8OjoKJOTk9ZZVyyYxuW666p7ugtqBPQSiYRtMOp6+ygto/9HRkYYHR1l3rx5HDx40M5RcXGxBa5jY2OMjY1ZQfSCBQt48cUXicViXHTRRTYgqkElGJDb1dVFPB63TWPFPog5uueee1i6dGleVZILQFyhua4Bt0qosCxd72k9nX/IFzhrW4Bly9xUptaRQFwARd9zxyoNmZv2aWkxFQACGO61q5eO0U0bCsTKfkBpVZWMC2AVpr7cdNjY2Bg/+9nPeOihhxgfH7etRdTCRalc98Fgz549jIyMcMwxx1BZWcn+/fsZGRnh6quv5qMf/ah9CCgUeL91ljWe2vhTzHELnNoFwNJbzad9qzAB5VGgyXQHL9nte7CRhOwNfjPtubyIoGfSuM1C1E1D+1pz4/3kWjw6xaMfvm/VCVbjGcfc0hswT6hfwWkbxWqgExr8oiyr/4gD58JXnjM3+7tuw9S1K60xYob4CH5QeA5Pl+Q9WK8dBz/S7TFtN1gCPOgBgzYTh2IZeCHkV0ddh2UZsiWmWkvxeQRMMO7GDmaOCDlCxEk5MqA2v7m6/H3Eqii4z+JV6qwj6c0GYyEzYwmv0kig8EPAqaYTaz9wDFkCHX+EDaYjuir5N3jznAZO4XQIdvnkgswOwxB4Jsdj/c6YxHS4Lxk/pgu+o3SQmA6XzRHzkXa2XcjmuFVZ0sfoM4EapZNmC9Z1/HuyJdD8DPCf+ExgAtgLRT/DgDr1QKl2trscH1ypDlyGkTIzlO5nL2ZyBdhanf0ofxr2jiPuf5a7rYvc3Sdh/vCUbA1D9mz8nhY669WmwewL3zM/X3sSP+WbBBbnaP6DaQK7xvvm6c94lhJvsPxNDU8ul2NgYMAyC9XV1aTTaUpKSmzPrKKiImpra/OqRdwbP5Cnl4B8LYWCjgzfZmdnGR4eBrApEwWl2dlZ28BU6Qvtc2Zm5nVVVXJwBgM+FixYwEknnWTHtmXLFl588cU88XQgEKCystIGQKU4VLnkilEFisD0HBsbG7PNR8GU9guQaftKA7qsgsYqQeyiRYtswBNwUx+s+vr6PAGtGAOl1RScZ2ZmWLBgAUuWLOHAgQM22KbTadtXbG5uzrIGU1NTHHfccaTTadrb21m0aBFLliyx6R2xW7lcju7ubp599llCoZBtNaLy7dHRUUZGRvjc5z7HhRdeaAPy0crQ30jTUwiG3RSU5l6g52hVYNJtuakkVzsmMKQKLbfBra6nVCpFMpnMK/9vaGjIszYoBHIuQCmsNNN7YnukudIYBe4FlkKhEPX19Sxbtoyzzz6b9773vZx55pmccMIJHDhwgGeffdZWjAmES9RcXl5u56uzs5NnnnmGaDTK2WefTVdXF3v27KG9vZ0zzzyTCy64gPe9731ccsklXHLJJW92S/hvuIS99EIYsrdjhC1fpyPqPRWeiwkaawCaYQRmlvkZI6VdpCtN2+gwSw+SaMxaDW4z0LjNY44+7a3EhfB0zAY+MS3ge73JfP+V9xrQYGQsXrRoMOm4u2kygXk58C/wT9+Az/8U1m3A5Mbk8qdgebXZRzkwTBPVmLYLPGe+V9QDfrR/0BvfGvzn5TugZcyADLVyD+OnLrxUTVHGh01xYNGf8cx++pFaN+CJvI0G9lRztMsmrQO0DdRumkvCWT7td5qIvQB8HzqhhF5s+XPToPly0+M2/jbyXgLvWUtrn+8IA37KoxtYyWKzr/8cg3Mh0IXVuVx4To5AR60PMpW+KWR8CvU+cXwgUk0+kEl685jA18/gbC/p/K6XUklublKIWeIk1WsLVIxAya8w8iwZCwp8XICvH5ayXmBH43XHIKZqgHzPnx7n5yXktznXWOWoKcQucfUnzLZzzzzENbwdI+F/CYJP4RecS0HuaX7ecbs3eb8ANkLt5QQuupbS4F9pIEUDowTefRVf4I2X19daO4v0DvKGGRgYsC0JEomENbpTAHdFwOl0mrKyMht8xcq4DIRbpaT3U6kUJSUlvPbaa4ApjY/H45bFmJqaIhqN2oAmAa+CzfDwMPF43KbSBDwCgQBvf/vbbeCdmJjgpZdeyks1aFxFRaadhJp2Cozt37/fdi+Xzmhubs6W0kciEYaHh4nFYkxPTzM0NMTChQuZmJiwjJfLxqiqTAF/enqasrIyYrEYkUiEHTt25LEO0lIdOnTIao7c1Ja0RGIu5GEUiUQsCFUwLi4utvocAaZsNktrayuBQIDe3l6WLl3K0qVLGR0dZWhoyALORCJBTU0Nhw8fBmDFihUMDw+zYMECa44YCJj+YJdddhkNDQ38/Oc/p6ioyKZMCnU7un5cMbI+czU6YrYU4AU+C5kh9xrTdsXwiGUU0HFBmMz5dF5dUKoqwW3bttn3Cvej+ZfOCvKr6QScdM2qZDwajVJfX09jY6MF266AW+J+pWNLSkqoqKhgeHjY9nXTfuXQLO2c+ntt2rTJatPGx8ctS6W5fSuWpUMaWh4HWk1O6Now3BljTdJjbeox99ZL9gF7IbHW+tgBBp2sM7FhPTBFEaVe9Etj8NKT+A+5KWAoBB0Z4JJBYzQ4uAw6IPiM2WS52aSVbOpBuRvgP0yGwDe7bYbgQ8xysvnGavjKNSYO/fvV+MyCcnAKVvXw/kXmxxEgxJDBPw94g2zGBKyV/di28GEwHMhOdrCKU3iB7WyF/vPhqm9B1y1mg8sxQcwLrnMhSGd8SdG5wMF+MFHtu96R9jNFCf9OhkZeoA+A6yC9DJZ9FRo+a0+X1fCojQQP8ijw768AK88ze6g3abKjOQRu54ucwpc8UmMPgcYYHYzZlk1rvJF9AXiFtZQEA8zsy8EnINcAxd+F2bR3QhYfIdALuVUBn8IqLMkuXCQuERko2xmBxQ7nPTcf4/rr5JcG+n04hY6j+JXd6uTR4Hz+En7pn7bndSaf7YdidVaXxkhpMjDXhcCdxuW2reggX9ektF8cq9XX998AACAASURBVPCfuwsur4SHWYvEQUXsIsg0WUqZowpuaMBciDqwx7yf34/fcd2lxHTAbZhur5iDmPKEc1Gg+ud8m5/z77HXnRXgbwCeSCTC1NQUFRUVhEIh6urqLEshej6bzZJKpWzKQB46AjduJVOh2FSBoJCpEN0/NzdHeXk5tbW1hMPhvLEAdv96Mk+lUpSVlVFWVmaNCktLS23aq7KykpmZGTo7O+nr67PgRjd7pQMqKyvtk7KqXaanpxkcHMxLn9XW1pJMJm3jTwUjCYbD4TDHHHOMLeUWy1VSUsLk5GQeUNOiMYs9EzOgtNnzzz9PfX29DZz79+/nbW97Wx5zFovFqKmp4ciRIzQ1NVnWK5lM2jSltEWFpdMqZx8dHWXbtm2ccMIJnH322Tz22GOW2VCD13g8TiKR4MCBAyxevJju7m7q6upQR3m1YDj99NNpamrijjvusGyZAIBeAiOu7kdBX/9rfvQdtwrLXcdNh+kacvtZuSknl10SU+dWXGk7YEDiggULuOCCC/jxj39s9W0CpKruqq2tteaV9fX1VFRU2IcHlYYLJE1OThIMBq1BoIBeMGicmFXVFw6Hqa6utq0i1GrCrX5UGsytBBSjJWAvsFRokqh133rLEuA84GoTy2mGB03cGW7BL63ln4ErYDWc8RNze+0Gv8QXPzbFvdxBP4oR3fStBbZ5BS718IT7lLwTGDANNj2PNhbiN2N3SQBqbwcUA0UdrAb2UEyS918Dv36CfLM87UtxvxuYNWGhH2jHNJz62vZB87TulJeboOLlYKIYgNbUCkRJsxtYDv8EPPYJ/2F7Bb4fy07jjxKcAaYdLLAXDKz4PgA5QgTIMMsKDm/fTeAUrzQrDJfxOR5Of9YP6q3e+h147FyUb1PLp1cO8kMGuZ51cMtuz4nany1bK951O9tbvk+IcUJMk+GjPMq3rHZ4q3cInwc+zovMsAqWLYDfHYIPG0BQcT9MlkLW1LMT2J0jd1bAF+Uq0Jfjl26rVD2K31dE58f14PF0Yq9j5ARuXBG3wBP4fkVJ8pmZemd9vQbwq91wxrgQirdjhN97C9ZvwAdpsgoY8balirNm4EL4z0Um/foMp2LEUwIuaW+GoxjWppxFbLJ4KQr0cblzoKL0VKqXwlw3mkwpvEWHuSpuz6dBX3Xlh/8vgKeoqIgDBw6wZMkSpqenLdiQs7BKmQcGBqivr7dPjBIUS6zrlvyCX00TDAZto1G9L1q/vLycZDJpq4sUJMbGxqy5oaqs9FQ9MmJkhWJe3OqeQCBAOp1mx44djI6Ovs4zRb4mgUCARYsWWU2Fgt3g4KDdpqvBkLBVKSqBMQUlCZkTiYQNTvF43AIlzZk0UQJZMzMz1NTUMDg4aE3jstms9YVRMG9pabHAUk/2ah0QCASsQV0kEqGrq4tjjz3WHoNAjxvcAebPn08qlSKTybBr1y5OOeUULr30Uu677z4bQEdHRwkEAsTjcQ4ePEgoFKKlpYVEIkFjY6PteSZR7rHHHss3vvENPvWpT9l0G2D9b3QOxcppLuUKrBSQmEMFdumcdJ5jsZhtnKnSfoESzbEYDzl7g8/gqErJTaWBATs1NTUUFRXxxBNPMH/+fBYuXMi8efPstaXUlMCPUowTExMAtst8a2sru3fvtvuSXk1MUzwet4yg0nEyItTYVLGnB4qxsTF7XbpMj4Cd5kvsqIC8uxReB2+JZV+MomWTzPEJiD0OrKHCs3RhPU61UTVwKfQYaYMqc8F8RzGpA2j2IpFkJ2BqspPbYDzkbfP33rpKGzxnbuVbMXFjHQazXO9tV8LlGr5EGJghhrmhq9t0lPmM8eufYpCM9BqFTICCZDMctNvo4D14bofFznqWnfCEIi2T8EIEmhLAh1jOt9jBXvjfLfCtkJ9OKxuEaK1Jl8jB9xk/fO0FQ1PdGoFvmmiUodIzhYO/nAI/5GmuJwoN5jS01QY4WJ3zdTTVmIf8buDpD5gsGJdzzSRcH2kFdtLIIH02CEplBbQ85e1TE7KZT/Jj/pV/tA1dt5op4mPM8G36gSVwyQJ44RB8GiYe9bZ1BUZmcjEETs+R+1XAjEmkg1JBq8l3jxzAD8IiKXQ9gJOucxYXuLqLlO3y0VE7CF0acn0WNhCzo/PsGlN2QODd/4vc399kcMVeDKhZD3dcCbdRiwssQgyRYZ53cJpjV0jUg1GKLcdXz6z33v8w0MpBvg3ZVZCECU8uRhRYtts7E0oI64DUCKwYLzfqLbrCWiH7DrMdV+Ced00ffXlTwCPAkcvlGBsbs3oU6USmpqYoLy9ncHDQ3vhdwahSVAI3CtKukLiqqspqgsAErf3791udRWlpqU2p6Tt6ytW+IpEIo6OjtoQdDOiRu7K8VeQ1Ar57r8biMgrHHHOMHWc6nWZycpIjR47kzY3E1Vr0lK0URVVVFYANqpFIxKbrXn31VdsjyS17B2zKBrAlxWLHBGzUGkKNW3t6epg3b56dF7cEW9urrq7mtddeY+3atZYJ0/y5vbCSySR1dXX09vbauers7GTJkiVcdNFF/PnPf7YeRipvVl+14uJiFi9eTF9fHwsWLCAQCNi2I2NjY9TV1fHd736XW265xVYZKeWpc1ReXk5FRYU9P266T98V8CxsVlpeXm6F2C67KBG8Ar97znV9SAPl+vzoZ6WapFM75phjrJGlbBD096Jr1GWrxIJOTExQU1PDvn37CAQCVjittJUAx9jYWJ4mq6jItAkZGRmxwNctnQ8GgzQ0NNhzKYZN4Efj0P9y6C4s8/9/rab7/3pZdr+hz3c3waoHYPctTIdgVtqH1RjVcMtO2BeCev9WHgfzS2wfbSxjParUKidDE1FUsp6EqyH9EMzKrr/pq9DrpWk2Q83vzDPsOfi8jUh5MLf9Dkx8NUW5urm7dc29Psvimr8VPvjuxQQzj5payiB/Gibf5iTs/W77ESSAv0D4fAxI0uPyV6AJaDjf/BrGzMy1Y3BtEm5tgr2QXQp9CVOx9do01PTCcCv4Xa2giCyQ4DJghzZWNsnNtPASXX6PL5EF0oZsBU6NsxW4dBBY1AYcTx9fLDh4bWCrNwGPIGOfIj7Gv5Dih5Tb7EsPJkxfwyA/FVJ8x3Fw/y74JQbolGO0WF8B+iEwniNXGvBNEPGmrg0fAMkIUCyY2BbX82YAm0kEfHCyHIOCf4ivkUngIzT3UHV57HG2KfZOIjSvd5hlMtOwlJvo6TaJI3EnCeBlglQwyASrkHA4Y9GUysej3sE9hu+avNo5eCEr9RDZClxnxOExbwDv0IGFMQnG9c7ELIcxcz8l9mfnYLy/yrGmfHG7mw601/QbL28KeBKJBPPnz7dP47rJDg4OWoAgvYtLy+tJWakg1zNHT9wKWgpAbllue3s7y5YtyxPLqsxcT9PhcJjp6Wlr8hcIBHj55Zfzqk4UUMLhsC2rLjQ/dKuc5E3imvEBdHd3W4DlBkrwdRzqgaRUTSwWY2pqiq6uLltNI98a8JtmKri6bMTMzIx1iRZo0TgFmE455RT7ZP/ss8/ynve8x25LYE9BL5fL2aCczWZtZZX2HwqFbIm/zrm7jb6+PhobG2lsbOTUU0/lySeftOevt7eXXC5HTU0Nr732GiUlJTQ1NXH48GHq6uos41JSUsLo6CilpaX84Ac/4J577uHAgQNWfyLvGWlodI50LsR2zJs3z5aIiyVz05eu87DAuuvb5Jayq/pM13I4HLbgRqBL6SqxjFu2bLHzHo1GLfMi9sRdBCDEpAnIFhUZvyql2Ny0lNJRrp4sFAoxMDDA3JzfRkWGk/rb1LUoEKt0sRhQCbilr8tms9aqwE0bvvVAz/eB5bBqN1BtWHYtXgGISXWttxR/Ob4m0yzdDF+yjOTvJIlYygBhR8oRhfMnmSXisC5pE2890x2XkBFTpPUTmNv+j4Cv45WfqzQna9JRBOMGvqzAty8RO7XH25CyAsvhrKXaRjdfBhO8FRAVKBPeOK2TyRbgfBSsHgGuZBu/pB6u6oUpL9iMhSAdg7CXN5CnTj/kgsaUMNmFV5r8IUzNWQNzJChilGFOJc3T2Mfxsf00xAIQfByazjHb78ev+AFgxDzMPwp8RIqpd2EQnB7z1S8iAdmPQbAHCafnaANO5Xr28x4WS89NJ2LXevkl7zDrX/U++NZvYR0Er4fItJfeqjHzH+jPkftUwBAThW7LCsId/uHZkx7FgJkHMEBkjXfu/k975x4cZ3We8d9Ke7Gk1a51tWzJsoVlFFyMAds4ricQUy6dEGba0JLQutBxQidN09ImJtNO26Qh0IZLYMqQQJqYcEsgBArTFlLTEAcY6oJjYlmJjcdgWxKyVhfruivJq730j/M955zdNKR/e/ad8VjSfpfznfPt9z7f+z7v8y6aNSMbrG/c216hxWB+6fSOK7kaBUTqMAEREZSvhqeeNd8ADUHk8s/hYimm2q0NqAvShOViQyK2NwQDUPhNg17E1bwH5YEsBjMrwDuAu+u7caEvXazO0wtJgXxpkKtq67dMquobr9jUGuAq/DTc94ny/FrA09raytzcHA0NDYTDptu2yswTiYR1ZnJQAjZ6cEq2XqXZvmlfhd/BvIXqXHJCcjh6oPtOS4TcXC5noyF+Lypw4MIng8oZirsgfsWmTZvs228kEuHUqVOkUqmSUnc/1aHjqfu0ohZLlizh5MmTrF69GsByWoCSFINf7ZXP50mn07blhoChT0Sen5/nnHPOAbBg5dxzz7UgRkBMKTWlgPz04vT0tNXiUXRJTk+RKB8MVVVVcfToUXp6emhvb2fjxo0cPXqU2dlZqqurSaVSVu/o0KFD5PN5Ojs7GRsbs3ovuVyOxsZGWwH1mc98hm9961uWOK4UoubCr4ATCBAAUX+r5uZmSz5WRFBroqiIgIbmT0rc/v0qoCF+k1KbAgu5XI54PE5rayuTk5MlKTdF9UTS1vYC4/l83kYxVUquOfCJyboHfdCqtRQA0jz6wMQXyPTL7BUxKhQKNDc32+avyWTS6ge1tLTYqJIitmefDQC/wPIKBmBRPYeun4a+JKx/GFhmn8ES+10DHNOD9GqIPi+HMcwEq+zLtXnKHmGCjUR6YXEBYNL4X4M5LDYpb8oNxoVMAv1BgZyJGgWJL8vHvZAor7o3eKVIxLmQ0N0aGPksvMwOO65P/Bivb0W5qX4aIGOOm78MqjOcYStt7AO6DTG05iike9y5v4FLoQVAKjQExSic6cKM/cCVsPEpoMHoIAEwGPinZ4HtkIyQBr7INdw2X3T8mL24wAIr2Qt8uBOcq74ZrMa14GlQClQ9hyOmiIiVBW7nP3mJDFfxCVxhmNFuOcD3VI616xq45QXyn4XZJ6F+CNLTEN5r7p/QV4tseTvE/6zDlOlrKn2T8xV+2I8BbOCAyyPYdiYCqwzgbhDtGweuhcImmDctLq10wutmxFbfScOQ4vBrbMTl4QwnrJ9lmLtuZXAU1di/iwMyCknFMXe6WNGNOBVDX1XRBzMy/eyXpUmwxwdWQo0adQTytVC9EubDJsL2sVdcldle4LPB5WzHBZ8oO2yZvS/gUdg+nU6zYsWKkge13nBPnz5NKGTUhf0O6SIyy7G2tLTYh7Jf1aJt5TAnJiaor6+3Tl76IlAqCqdqIL0di98jbR1VRInYvLCwYFsFCLCEw2GrEF1dXc25555rlYoFNtTmwo9oyXH6/JdMJkMikbCVV2D0apYvX048Hrf7q2EnUALc/H9ycA0NDTQ3N1uxQD96IZAnrs/Q0BA9PT3U19fbUmWlV6LRKE1NTZYIPjs7a8nF4nEIwKkSS+KSPqn42LFjbNmyhc2bN7OwsMA777xj+TACNzU1NRw9epSqqioLepQKmpqask1Ma2pq2LlzJy+88AIvvfSSBT1Kw8gUsdC41eZC6S9xy3y9G62TomYC6AKZAoZKFwlcCOjMzMyU8G5qamq48cYbmZ6e5vHHH2dmZqaEdF9dbRrZrl69mlWrVpFMJmlsbLTrG4/HbfpROk4ixU9MTFBTU2Mjoj6R2q/60r0PTnFaLwA+cPYjNNp/fHzcfuckQXDmzBl7HxaLRZYuXWqjTmeXSYYsBVzrSmPjAG9C45WYp+fV5lnc6wIL+yEAG+b5M4hxDwUabAsjQ8m4Oth6I6tzcKz6H4EbrR+OjTnqjNyKClukKTcC8NwcR+zZGiHfbrzaEeD685gA/vU34GPgXnoFqsBW/7SxEaUX/poh1z5BuEZIa53/S6Cy1zIHJ2qhqwH4OyYImkDW3ACsMceRbPGnMEVYuDEUFUrQC/rtwEbzhypy5FgCNPIuJ/gcf8q9HAcytlG6NVW0E0zWia18vQu+vBlc88kJHONWjF4xonox6/opb5Yjwd/38xovMcBVRgjbu4QPsY/XCASU/vmT8Mnd0A8LS4ze0GIDlofzxjlFQsdbKd4w5tJTfqrLj/AEgtY21SQei9jr5+GUEYXTUt4xzjP7VO2FumXACGwIuFpXqcpKJeMbMFhSmaM1B8wNtn/MTEf6gIsIRYP11LpFMQhK5+yE3JcgUrueoJcHLtwkMKR5fwcT2dngHSxY1XyP6XZv/z4ZHKs8L+sVTlTnTMPYLCYaJiK1SgGvDubvcDC3vd71/4qG6e8LeJYtW2ZTHSKM+uXeiUTCkohFvPVJxjJVWElV2XdiIsDW19eTy+X4+c9/Tnd3N4VCwfJh5Lh8jpDAhjRIFFXx+1L5XdVVoaLPFEVRhVhHRweJRKLEIU5OTnLq1KkSro9fplxeAi3isEDR0qVLLTCS84tGo8zNzVnnKjChqqf5+Xmmp6ctKbW1tZWxsTELRAQWdL0SCzx58qQFpwJr0k0SF0ZpLOkfqaxZFTyKAgmUDQ0N2blTKfehQ4fYtm0bmzZtsmq+SqucPn3aAqkjR44QiUTYtGkTb7/9Nk1NTcTjcZtaFI/ommuusWXr/pxqjRVlUuoJsMAIsGkacGR4KUOrGkkcJvF5BNoV/amvr7cASfdJIpGwALG5uZkVK1bwyCOP2FSSH+GLRqNMTU3x05/+lP3799sIouZTqcienh42b95Mc3OzvX+TyaTVeAKnHyUxwiVLlliA5JezCwT5AMmPEAnsKDWqiI8P3iUrociiNK/OLtuAeRBvgKNBeqiRQHen0zwo26PAtZCGyJEyrbgo5rc95igNQBWLNrAxATDdA8l/ZwIjOgidMLbR+gBfrNcGbHA0FenUweet6K0V/3kd+/LbiHHhHzNFVO7hT3CAS4w2j/NkWefQy0uqNQgmcFAjYjaaqIWuQWBDgGO+AfldrlmpUmLKjyjlMkgpp0IpPQzJuECYCGmqOMBNJDnMNPcGKO3PuJ4UT0PNE8DV0NbixpkGeuF0190U6m4FbmItH+CYDa2M4JR2FC9Ls5Y+jvEsjhou9vDrwBfo525u51ZuCz6ZxHCsouzjZaXGdv8udDzH4uIcfKC2NF3SCHSMEnrvHorX3eooKeVl5orU+HOnzwKsbbsr1OFIxyPecfZigIm6ZPpBlDZY/ANIRaE1byrmwmsw97YaqR2EUPFLFLd/2QCrCQxAaguWJx6sVzr4XQGzgxD+Iyju74P4Upc+Og8KP4DfTMAbvIcjXCltlcUhkTVQ3QnzXUBY5YgBF63FpeB8nSFlvEyQspS7ppL+THB4paY3eLfCr7Bfq8MzPDxsybVyKHLe5SW+qkyJxWIlb8HaZmFhgUQiYYGDnLdAge/89ZD2y2f9h7se7HImo6Oj9s0XsOkl8R6KxSJ1dXUlpbe+6OHatWtLiMG5XI733nuvhOCqMl9to+39Xlp++wql62ZnZ+3fFVWS+TyT0dFRywNSdKWpqalkTfJ50+399OnT9PT0UCgUmJmZ4dSpU6xdu5bGxkYmJydtlZTWL5FI0N7ebsesFJsfFRC4BCOimM1mbVWP70QPHz7MBRdcwEUXXUShUGB4eJj5+Xny+TypVIrOzk7C4TAHDx6kpqaG1tZWZmZmrMTA+Pi4dbgNDQ2sX7+eHTt28Mwzz9jqMh9QCIj4gDMUMtpIIofr3vM5OQI6AkwyVa6JkF5fX2/vNUXndB/Pzc3xwQ9+kPHxcQ4cOGDnz68Q9Dld+m5o/fT73NwcBw8epK+v75dSrZs2bWLLli0kk0lisZgFg4pMCUD5zXEBG7FUZAhcab2+jz7XzOetgdG4WlhYsE1Rxac6u+yvMHmENvMGuAzz0NwPfKQRLp0DojCdhAz8Ya60+MU0cZ6EQT8InyZLk2UvkAKST5FllyHhMOE6caddKTo4/+0XlDQgIPU4APPEgDrXFX0zwHb7Hm1TPge9g8SBL8C9dGlUbOFp6h5AtfSunBpcZsFaFNuCvbEdOa0U8Huc4JnqPuhc784lU/AkiitrE654F+Ncp/8BktdQoJUIJzhDC9DNY+zDUWa/yus8bRZmegck+yC63mVLtgFDuzjQfiuQ5gFUE6TqISVyhAa62Qz8kFfp5jpcWO9IMKjfh799jv477uKLjNk4UAZB5CfoZxewF947Bz55HF6DplY43YLL7kSBD+wi9NouiveEnLMWR6e8cj5a9vPKsu2U6soGA1oM/vZRb6q0ho0Evdwgch2kVwHVsFyfKXASFEEV133Z/P4YDnkPBGPVmioatZJSdO43qFpjxlx1N/zPOwAdbszXwcV/DD9jCtdZNODw1DyKCyeloaUNTlzvqvJGvPkR6Cu/XuFWWRqzpFr2OlzE8/+w9wU8fvWUSqHlgER+lPaIHKT4PHrY+9wE32n5IfnZ2VnC4TDj4+PW4fuVXXIa4LRWBDB0nlQqZSNB8XjclnzLOcixx+NxCgUnKhcKhejp6Sl58wVTKSNhPXBRKUW4NH6Z3pQVKQFXPSb+ktI5/v4Ce0qpQKkqtRwvGP0bOcu6ujoLlGKxGMuXL7dpRkVjdN3pdJpVq1axdu1acrkcU1NTNDU12UqubDZrxyhAcebMGXp7e9m6dauNgOjvs7OzTE1N0dHRwfT0NPl8ntHRUav9kkqlaGxsJJFI8NZbb7FlyxZWrlzJ0NBQSfVRKBRiYmKCRCLBJZdcQjwe59FHH7VpSH+OyzV2VMGnn7UGujfU6V6l8X6k0K8AW1hYYGZmxoIgnUOyCm1tbXR0dPDYY48BpZE9RUx8Plg58df/3Y/O6N4Nh8McOnSIw4cP2/ujUChw6aWXcvHFF1uyuUCWIj/xeNymq3T9/suFz1vSiwk4XpsimOVRtbPO8i1Q/QlsnF4tBG4EgwA+D2wwD8vN7mW3DYN1QvNQZBlMON3XAg32+Z4GI+Hz3EpTtHvpw0CjAVQHITLp5GWEN/RPLApRPbeR4SmgQFDbPojXxGsNe4EMdXz3ukBURar8AJ1wRRPYsl0GeE2Rl3IOqjIRvRAhzWJJ06fXIX6ZmRMGeBK4DXiGNNTkoDHs0GAjpkvqm5TyTVR6ncW1mr8+UETmBFXMUWAgoBS9i/FWZucw3ySXXAPcUMrJyAJ74PZ2gL1c9WPgcjCrIia2CLVmx+/xEt/9+6u46Cu38DN+gvOEE8B1cMct8Kej9D94C9/mfm7DYcztwF7uCUDPs7B7E3zyp5w+hJF18q0T+A0IjU5R/MVSAyh8tWHffCkBbSP1ZT8EuA6XuvEzQNLT6YYzrRB7CtsLq3MVhKUsMRisyxGzBtXv1JGPZhze8Mm9AhZ+FRnez+VRQT8LqqItb/u3tgOLS82yHgG+CaEtO2F+d6lOZPs+6HoIuoJ6eW6AA+tdakpRrnLGvx8J2kbpMbOU6UyV2vu2lshms0QiEasqLGcvoKMqD8A+vGXlZcU+wJHD1+eKWpw4ccKmlYCSyhI5k/r6esvV8DtPp1IpK88vZwlYjo74PIoYiQTb0tJim5yq2qpQKHDy5EnLQ5IT9KMhSkH4nAc5fEVx1KdL1zM/P18itKhUBRhAKU6Sz0GRgB1gtVN8oriiWBdccAHFYpHh4WGbgvNTHCqfjkQijI6Olihka8w+ITYSiXD++eczMDBgox6xWIx4PE4kEuHw4cNUVVXR3d3N6tWrWb58ue0insvlmJyctHO5b98+BgcHrTp0PB636UZp4ywuLtLZ2cnNN99Md3d3iaaNHLlPbta9UR75UWpV6VcfWPrVgD4oKI8kan1nZ2e58soricfjDAwMWN6ZtgcXafIrD31OjUzgXVFMPwKk8SmFls1mefnll7n33nu57777uO+++3jggQc4fvw4DQ0NluO2uLhIMpm0vLW6urqS3maaD786TPewT9jWd9G//rPGJgB+AsQNQNADsxvDDwBgjX2TNKr9WfvMvzCN+SDt2CJzJOxLKEDsebPNQBwsiWCPOcfqnOujKIqFCqQkJCwKxo0IULUCba4MuQF4NUw3UOAcFushV4OjUbRB751m3zALwCRhfkjkGRxK83Nq3tw0k8f1TgjG35KDo6Zy54wRwMEAxl5oOerSaeI7yyEppXM1zoFuIGBhm7KrAtXUBaXw+4EP8XHk3VLApzmD9WDJMdPHK4tpbLoZ/kPM63egVLlPnjfr/dsGK+Gt/wRTKRYgi/yVmNX8KDz4IvzTP9PPFXwRl20SVSnCfcB1hPk57P4jA2ZuwmXQophIWxtwQZJQR5HeOzHZHDGI/UVXBCVOaaUR3vpkMYjrBhxG86MewTaRDI4vFKSgpqpNqw/2BEuWBt6F/N9nHB5UCwg/5SYTivenVecHB3JUAOe3xwBXwLUdcy/caOaheNPDFHeFKH46RPG/QtB+Dby6FZ7/NPTthBP/CKyBjQ/Djqdh5ysmOOuLKqrbrr/EQRuQkpStfz1l9r5POPFc/Ie4HtTgIg4qyZXz8Euulb6Ro9YbpQ+A1JhyenraOkX/TVSRE78Vg8qUlT4SMVP7qE+S9ICUglAkQ+q1bW1t9toEFObm5hgbGyuJMMihATZFobnQ35VO0LF8wKe0V1NTE9XV1TYFNDMzQzabZXZ21vJplMKIY6RsTQAACNZJREFUxWI2aiNOks6jkn+lBpXayOfzNDc3W5Cq401NTZFIJKipqSGVStmIXSKRsDwdjV1Od+3atfT395NOp21pszgrsViMN954A4Dzzz+furo62tvbS5p7Clg1NTXR29vL+Pj4L62PX6EWjUZZuXIl27dvp7a21t5nWnOlJiUdoJSSgItSdVpr9cNSg06toSJBcvgCIEpxjYyMkM1m6ejooLW1lbvuussKGfqm85Y3HPVBRXn6V7/7YF+AB5z4n687pQqvp556ijvuuIM777yTRx55hJmZGcuZE2hfsWIFy5cvp62tjWw2y9TUVIlwp9ZYYEtpMf//s8qyYBsKyPFEgZohT4n2QvMAX1Oa8cnYg6Sh0TxPJzH+uxPXosjs00nxQe3ZaT447Apy/aLcieB30W7TGP9kU1byICpGUj8kADaTikL4R97O2xzP1ESHUrzAGZeyUqrJdxRBOsN1lpZHy5irzGJHGQVi3Ipt6LQ/2HQdsD7nKpZ9nZgsLly20owbGikSDq4uzb9xaXBWgwb+kuqATTSCIZS8Y0BpTc5cRPscBY4C7wZjuAtXn6+ci0+UGSS3w4xtIX8/0Gs0XlIE23cC58HfHAX+hX528u3gKDraxeSp4kFy/DtNPAF332rAzN9B/bS3aMqobYELXyxy6R5vzrXobTgHrrRkGw7UqPv4JK60/SvBVPTiOp6PmO3yS0zVlgjOdcOw7N+g6vOY+ckAeyFUTMLXvenxvwcCPgI/UonW2P2Iiq5B+/lgLBuMy083DaLQpQNmF5ptipe8SHF3iOL3Q2R7QtA1ZEQv+3bCi9fDP11mXlB29cHdr8CX5oLOt9749f1QA1OC6z7Cr7T/V4THJ2CqBNsXq/Mf0jKftOwr5ephK+dQLBYt10DHk2OR7oocrZygUjkCUUqH+dEAjRec7olUjhU5Ued3RaPAgJlUKmWjGj53xXdUfnRE45mfn7fj8lNS8/Pz1pmqKaoaefpVZqpyEwDIZrMsLCzY9JWiCkp/qXpL855Op1myZAl9fX1Wv0dVZ75TF3FY5F2/Ik5zMDExQW1tLVVVVezbt69EodjvWn/o0CGWLFlCT08Pzc3NdHV1WUe/uLjI1NSUBXJvvvmmnddQyAgF1tbW2rYLAjPnnXceO3bs4PLLL7eijSKfS7BRpG+lRH1Ak8lkGB0dZXJysmQu/ZSj1ry2tpa5uTkymQxTU1OMjIzYCM6115rXL2kNCYAJuItbJKCptfPvZe3jSwtonD4AE1jT8f1oqe5pf/1HRkZ4/PHHueeee7j//vvZs2ePjRINDw8zPGy6FSWTSTtWX8/JTzVrvXQvnFXW/hBGaGfE9ZDKAqShaxoboggaOjZiQIO4maZiqxGyTtG/F9NJSy/r5i4ZgB37gA3wI6NPE5s2n6/DVY1vw/iJS3C+IQ78eKt5To9TjQUWIxgHEYQdJoAqvm+e5weDk3fDT37P9fOsI8OHGDIpH1W16A1ckQVxQazQUCPu1Rnzf1vwP9tJI75M0ETpipzdDHAOsBsX+ZDuXJoAVZmwSIFw0APLmDnuESDLIsOBD1UP+Q1QPVZ6oqF28/kAPEqA+k50Qb7LraX13u8Sqf00jEDsv+G3+bhpPjqBca4nerDkj6EuGNvNL7ib26ljGa7B93YywO9zmt3mAp+7FdbB7G5YNRZEWsBFRf4EXnu4yLfvxIBVcJlG5TY3YG4G3VRK/SnC8iSm7F/Los7jOk8DFKoN6LHruQcDbFSpH1SMFddNO6CS9Y6nG1Brpn2URs145/f1KdU0TSh+EVcR5leircSpASgAtwxzT38T09vjqxB5Boq3dVB8OkTxiRB//JGQ0Y1sBJ5fD69eBi/WQtcr8Df74C+egJ0HHGjT/KoJnX05+GV7Xw6PgIdAiCIJAkIi6YZCIatFAqXhe5/bIMerB7ciJMuXL7dvq0p16Pgqo1W39nJVZlU9qSxc51IVk9JlPocol8uRTCYtwFCKTACjv7+/xGlpDuQQ9MYsUrYPmAALvCRENzk5SVtbW0mkSaBLUTNVUYVCISvsGIvFiMVitqLKd6qKupQTrQUC1Z5AooyATaXV1dUxPj5uUyOaa78cH7Cl//Pz8xw/fpyenh4LUKTXs7i4yLFjx9iwYYNdi1WrVjE1NUUmk7EE65aWFmKxGPv372fLli3E43GrkyOBR12LiLw1NTW0t7fbxqNKuygtKGDpg27Ng7RzfCKzIku++KXmRcRdRT26uroIh8N87Wtf+yWiu5/e9L8jmr/y+17z76eP/PP73zc/BZzNZktkA8q5NuJDVVVV0dfXx7Fjx+y98eEPf5iNGzfa75QEGtWyIpPJ2O+Mvkv++c8eGwAajINTd2kbgn/T/DefhK45eLXWpv99EVfAAh7xK2/EPf/NPg9gnrjdVghQRbZywTfjCk7ke5Tu4gfGZxitmmAUK3GOqM3giUHgqv5gx0XgU+54mLPzcsB3ARyBSKbBBAxsc3eJju0r54EE5xQs8GEV2bBpMTHd4hxZFoNg1EppDU7pN9MFl5rnYZ4lAY9n0A7ToLt1gU8PulzyeZx4XdT8vT0QtbsadszATYk2j6QqGWkPOUw/CPsfYvAr8MIMVCceg8aNXiQgDPGN0N4H96yHXddRIM2fcw9XBVedBi5imp/xJAY8Z+GKp+GJ6+k/BJdfAK8PwZkWLIE7dAvcPFjk5mfvp3jJLSbAtQajldhQNky/j4kULxXFqAsWVdHIoGVFYQ3E3vbWdhDHd/Fu4iuehB+JE6SbpOTGDsxPu/mCyXW4Eva0t03a208SPRqLthsJ5kN9v6Jl2xF8ttn8KyyDEwn4zmvwnXeDFh7dsOJ3YPihIjx/WZDC3Wpuix373HGGtjqNo/ex0Nmnu1GxilWsYhWrWMUqVmpnIUuxYhWrWMUqVrGKVazUKoCnYhWrWMUqVrGKnfVWATwVq1jFKlaxilXsrLcK4KlYxSpWsYpVrGJnvVUAT8UqVrGKVaxiFTvrrQJ4KlaxilWsYhWr2Flv/wspdvLzxLgrJQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax_mag, ax_ang) = plt.subplots(1, 2, figsize=(10, 10))\n", + "ax_mag.imshow(maximum_filter(face, footprint=np.ones((3,3))), cmap='gray')\n", + "ax_mag.set_title('maximum_filter')\n", + "ax_mag.set_axis_off()\n", + "ax_ang.imshow(minimum_filter(face, footprint=np.ones((3,3))), cmap='hsv') # hsv is cyclic, like angles\n", + "ax_ang.set_title('minimum_filter')\n", + "ax_ang.set_axis_off()\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 10-3-3-2 풀링 처리하기 \n" + ] + }, + { + "cell_type": "code", + "execution_count": 427, + "metadata": {}, + "outputs": [], + "source": [ + "import skimage.measure" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "머신러닝 모듈인 skimage 모듈 import" + ] + }, + { + "cell_type": "code", + "execution_count": 428, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 4, 5, 2, 3],\n", + " [3, 5, 1, 2, 7],\n", + " [2, 2, 5, 6, 7]])" + ] + }, + "execution_count": 428, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "B" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "특정 필터를 사용해 배열을 줄이는 block_reduce 함수를 사용한다\n", + "\n", + "필터링하는 배열을 1행 1열로 지정하면 자기자신을 그대로 반환한다" + ] + }, + { + "cell_type": "code", + "execution_count": 429, + "metadata": {}, + "outputs": [], + "source": [ + "sk = skimage.measure.block_reduce(B, (1,1), np.max)" + ] + }, + { + "cell_type": "code", + "execution_count": 430, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 4, 5, 2, 3],\n", + " [3, 5, 1, 2, 7],\n", + " [2, 2, 5, 6, 7]])" + ] + }, + "execution_count": 430, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sk" + ] + }, + { + "cell_type": "code", + "execution_count": 431, + "metadata": {}, + "outputs": [], + "source": [ + "sk = skimage.measure.block_reduce(B, (1,2), np.max)" + ] + }, + { + "cell_type": "code", + "execution_count": 432, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[4, 5, 3],\n", + " [5, 2, 7],\n", + " [2, 6, 7]])" + ] + }, + "execution_count": 432, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sk" + ] + }, + { + "cell_type": "code", + "execution_count": 433, + "metadata": {}, + "outputs": [], + "source": [ + "sk = skimage.measure.block_reduce(B, (2,1), np.max)" + ] + }, + { + "cell_type": "code", + "execution_count": 434, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 5, 5, 2, 7],\n", + " [2, 2, 5, 6, 7]])" + ] + }, + "execution_count": 434, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sk" + ] + }, + { + "cell_type": "code", + "execution_count": 435, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(768, 1024)" + ] + }, + "execution_count": 435, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "face.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 436, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(384, 512)" + ] + }, + "execution_count": 436, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "skimage.measure.block_reduce(face, (2,2), np.max).shape" + ] + }, + { + "cell_type": "code", + "execution_count": 437, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(384, 512)" + ] + }, + "execution_count": 437, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "skimage.measure.block_reduce(face, (2,2), np.min).shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "폴링을 처리해서 이미지의 크기를 줄였지만 최댓값으로 만든 이미지는 동물 이미지가 뚜렷하다\n", + "\n", + "최솟값으로 처리할 경우는 이미지가 희미한 것을 확인할 수 있다" + ] + }, + { + "cell_type": "code", + "execution_count": 438, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax_mag, ax_ang) = plt.subplots(1, 2, figsize=(12, 8))\n", + "ax_mag.imshow(skimage.measure.block_reduce(face, (2,2), np.max), cmap='gray')\n", + "ax_mag.set_title('maximum_pooling')\n", + "ax_mag.set_axis_off()\n", + "ax_ang.imshow(skimage.measure.block_reduce(face, (2,2), np.min), cmap='hsv') # hsv is cyclic, like angles\n", + "ax_ang.set_title('minimum_pooling')\n", + "ax_ang.set_axis_off()\n", + "fig.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/11\354\236\245/.DS_Store" "b/11\354\236\245/.DS_Store" index 5008ddf..095adf2 100644 Binary files "a/11\354\236\245/.DS_Store" and "b/11\354\236\245/.DS_Store" differ diff --git "a/11\354\236\245/.ipynb_checkpoints/11\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214-checkpoint.ipynb" "b/11\354\236\245/.ipynb_checkpoints/11\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214-checkpoint.ipynb" new file mode 100644 index 0000000..2fd6442 --- /dev/null +++ "b/11\354\236\245/.ipynb_checkpoints/11\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214-checkpoint.ipynb" @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/11\354\236\245/11\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214.ipynb" "b/11\354\236\245/11\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214.ipynb" new file mode 100644 index 0000000..b04b53a --- /dev/null +++ "b/11\354\236\245/11\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214.ipynb" @@ -0,0 +1,1677 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.19.2'" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "np.__version__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Chapter 11. 넘파이 특화 함수 알아보기 \n", + "> 넘파이 모듈에는 벡터화 연산을 위한 유니버셜 함수가 만들어져 있습니다. 이 함수에 대해 먼저 알아보고 파일을 읽고 사용하는 처리도 알아봅시다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## [복습] 넘파이 모듈의 함수 특징" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 특징 1. 동일한 이름의 함수와 메소드 지원" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.zeros((5,5))\n", + "(a != 0).any()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.any(a != 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(a != 0).any" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + ")>" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.any" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 특징 2. 유니버셜 함수 제공 \n", + "유니버셜(범용) 함수? ndarray 안에 있는 데이터 원소별로 연산을 수행하는 함수.(브로드캐스팅을 지원하는 함수) \n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ufunc" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.ufunc" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ufunc" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.add) #유니버설 함수" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "function" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.sort) #일반함수" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2, 4, 6, 8])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.array([1,2,3,4]) \n", + "np.add(a, a)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1, 3, 6, 10])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.add.accumulate(a) # 일반함수를 사용하면 순환문을 돌려야 함." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 특징 3. 벡터화 연산 \n", + "브로드캐스팅 : 넘파이에서 shape가 다른 배열간에도 산술 연산이 가능하게 하는 매커니즘. " + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2, 2, 4],\n", + " [5, 5, 7]])" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.array([[1,2,3], [4,5,6]])\n", + "y = np.array([1,0,1])\n", + "x + y # 차원이 다른 y를 np.tile(y, (4, 1))로 처리 (y의 복사본 4개를 쌓음)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "operands could not be broadcast together with shapes (2,3) (2,) ", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m6\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mx\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (2,3) (2,) " + ] + } + ], + "source": [ + "x = np.array([[1,2,3], [4,5,6]])\n", + "y = np.array([1,0])\n", + "x + y" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 01. 일반함수와 람다함수 사용하기. \n", + "ufunc 클래스로 만든 함수를 처리하는 방식을 알아봤습니다. \n", + "이제 이 클래스에서 제공하는 메소드를 알아본 후 함수를 벡터화 연산 처리 하는 방식을 알아봅시다." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 예제 1. 유니버설 함수 클래스 알아보기\n", + "[유니버셜 함수 레퍼런스](https://docs.scipy.org/doc/numpy/reference/ufuncs.html)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ufunc" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.add) # 유니버설 함수의 클래스다." + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accumulate\n", + "at\n", + "identity\n", + "nargs\n", + "nin\n", + "nout\n", + "ntypes\n", + "outer\n", + "reduce\n", + "reduceat\n", + "signature\n", + "types\n" + ] + } + ], + "source": [ + "# 유니버셜 함수의 메소드\n", + "for i in dir(np.ufunc) :\n", + " if not i.startswith(\"_\") :\n", + " print(i)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 예제 2. add 함수를 사용해서 메소드 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.arange(10)\n", + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "45" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import functools as ft # 고차함수를 위한 라이브러리(기존 함수를 모아놓은 모듈)\n", + "\n", + "# reduce(집계함수, 순회 가능한 데이터, [초기값-생략가능])\n", + "# 특정함수와 반복형 객체를 받아 연산을 처리하고 결과를 반환해 줌\n", + "\n", + "ft.reduce(np.add, a) " + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "45" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.add.reduce(a)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "45" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 6, 39])" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# reduceat 메소드로 배열의 특정 위치를 지정해서 합산\n", + "np.add.reduceat(a, [0, 4])" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "6" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.add.reduce(a[:4])" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "39" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.add.reduce(a[4:])" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 6, 4, 10, 35])" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.add.reduceat(a, [0, 4, 1, 5])" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "6\n", + "4\n", + "10\n", + "35\n" + ] + } + ], + "source": [ + "print(np.add.reduce(a[:4]))\n", + "print(np.add.reduce(a[4:5])) # 인덱스 주의!\n", + "print(np.add.reduce(a[1:5]))\n", + "print(np.add.reduce(a[5:]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Quiz 1\n", + "np.add.reduceat(np.arange(8), [0, 4, 1, 5, 2, 6, 3, 7])[::2] \n", + "array([6, 10, 14, 18]) \n", + "위 결과값을 나온 이유를 설명해 주세요." + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 6 22]\n", + "[ 4 28]\n", + "[10 18]\n", + "[ 5 27]\n", + "[14 13]\n", + "[ 6 25]\n", + "[18 7]\n", + "[ 6 4 10 5 14 6 18 7]\n" + ] + }, + { + "data": { + "text/plain": [ + "array([ 6, 10, 14, 18])" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(np.add.reduceat([0,1,2,3,4,5,6,7], [0, 4]))\n", + "print(np.add.reduceat([0,1,2,3,4,5,6,7], [4, 1]))\n", + "print(np.add.reduceat([0,1,2,3,4,5,6,7], [1, 5]))\n", + "print(np.add.reduceat([0,1,2,3,4,5,6,7], [5, 2]))\n", + "print(np.add.reduceat([0,1,2,3,4,5,6,7], [2, 6]))\n", + "print(np.add.reduceat([0,1,2,3,4,5,6,7], [6, 3]))\n", + "print(np.add.reduceat([0,1,2,3,4,5,6,7], [3, 7]))\n", + "\n", + "x = np.add.reduceat([0,1,2,3,4,5,6,7], [0, 4, 1, 5, 2, 6, 3, 7])\n", + "print(x)\n", + "\n", + "x[::2]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 예제3. logical_and 함수로 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ufunc" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.logical_and)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[False, True],\n", + " [ True, False]])" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y = np.array([[2, 5], [7, 8]])\n", + "z = np.array([[2, 3], [2, 8]])\n", + "a = y > z\n", + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([False, False])" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b = np.logical_and.reduce(y>z) # 행에 있는 논리값들을 다시 비교해서 결과 출력\n", + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 논리값의 결과를 더 줄이는 .any와 .all\n", + "(y>z).all()" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(y>z).any()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 사용자 유니버셜 함수 정의 하기" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.frompyfunc # 함수를 등록하는 frompyfunc 함수" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "function" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import operator as op\n", + "\n", + "def add(x, y) :\n", + " return op.add(x, y)\n", + "\n", + "type(add)" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([4, 6, 8])" + ] + }, + "execution_count": 96, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.arange(3)\n", + "b = np.arange(4, 7)\n", + "c = add(a, b)\n", + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ufunc" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "add_ = np.frompyfunc(add, 2, 1) #frompyfunc(함수, 입력 인자 개수, 출력 객체수)\n", + "type(add_)" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([4, 6, 8], dtype=object)" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d = add_(a, b)\n", + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.67 µs ± 19.9 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)\n" + ] + } + ], + "source": [ + "%timeit add_(a, b) # 오브젝트 타입으로 처리되어 느림" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "462 ns ± 4.56 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)\n" + ] + } + ], + "source": [ + "%timeit add(a, b) # 스페셜 메소드로 처리하는것이 빠름" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.vectorize" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.vectorize #벡터화 함수를 만드는 vectorize 클래스" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "function" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def mul(x, y) :\n", + " return op.mul(x, y)\n", + "\n", + "type(mul)" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 5, 12])" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e = mul(a, b)\n", + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.vectorize" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mul_ = np.vectorize(mul) # 참조 https://numpy.org/doc/stable/reference/generated/numpy.vectorize.html\n", + "type(mul_)" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 5, 12])" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "f = mul_(a, b)\n", + "f" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "10.5 µs ± 261 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n" + ] + } + ], + "source": [ + "%timeit mul_(a, b) # 벡터화 오브젝트 타입으로 처리되어 느림" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "455 ns ± 6.4 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)\n" + ] + } + ], + "source": [ + "%timeit mul(a, b) # 스페셜 메소드로 처리하는것이 빠름" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 함수를 전달 받아 배열 생성하기" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + ", **kwargs)>" + ] + }, + "execution_count": 111, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.fromfunction" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "function" + ] + }, + "execution_count": 112, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(np.fromfunction)" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ True, False, False],\n", + " [False, True, False],\n", + " [False, False, True]])" + ] + }, + "execution_count": 113, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.fromfunction(lambda i, j : i == j, (3, 3)) # 람다 매개변수는 배열의 좌표입니다.\n", + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0., 1., 2.],\n", + " [1., 2., 3.],\n", + " [2., 3., 4.]])" + ] + }, + "execution_count": 120, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b = np.fromfunction(lambda i, j : i+j, (3, 3))\n", + "b" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 02. 파일처리" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 02-1. 일반파일 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-1.03920641, 0.25416194, 0.48729407, -0.50420902, -3.58750699],\n", + " [ 2.44926666, 1.24281422, -0.902584 , 0.76763889, -1.8285857 ],\n", + " [-1.10399085, 0.71767767, 1.82920702, -1.09855516, 0.57905975]])" + ] + }, + "execution_count": 121, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "n = np.random.randn(3, 5)\n", + "n" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "metadata": {}, + "outputs": [], + "source": [ + "n.tofile('n.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": 125, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "n.npy\r\n" + ] + } + ], + "source": [ + "%ls n.*" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-1.03920641, 0.25416194, 0.48729407, -0.50420902, -3.58750699,\n", + " 2.44926666, 1.24281422, -0.902584 , 0.76763889, -1.8285857 ,\n", + " -1.10399085, 0.71767767, 1.82920702, -1.09855516, 0.57905975])" + ] + }, + "execution_count": 127, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = np.fromfile('n.npy')\n", + "m" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "m.npy\r\n" + ] + } + ], + "source": [ + "np.save('m.npy', m) # 함수로 처리\n", + "%ls m.*" + ] + }, + { + "cell_type": "code", + "execution_count": 129, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-1.03920641, 0.25416194, 0.48729407, -0.50420902, -3.58750699,\n", + " 2.44926666, 1.24281422, -0.902584 , 0.76763889, -1.8285857 ,\n", + " -1.10399085, 0.71767767, 1.82920702, -1.09855516, 0.57905975])" + ] + }, + "execution_count": 129, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "o = np.load('m.npy')\n", + "o" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 02-2. 텍스트 파일 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.0232927 , -1.01570736, -0.33861738],\n", + " [ 0.88726319, -0.61807078, -0.03592853],\n", + " [ 1.18483685, -1.3631187 , -1.28021693]])" + ] + }, + "execution_count": 130, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.random.randn(3, 3)\n", + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "data.txt\r\n" + ] + } + ], + "source": [ + "np.savetxt('data.txt', a)\n", + "%ls data.*" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# %load data.txt\n", + "2.329270165218954095e-02 -1.015707363147797748e+00 -3.386173777006352692e-01\n", + "8.872631866260904943e-01 -6.180707826644971092e-01 -3.592853432097895677e-02\n", + "1.184836852830924547e+00 -1.363118698625313208e+00 -1.280216926978795522e+00\n" + ] + }, + { + "cell_type": "code", + "execution_count": 137, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.0232927 , -1.01570736, -0.33861738],\n", + " [ 0.88726319, -0.61807078, -0.03592853],\n", + " [ 1.18483685, -1.3631187 , -1.28021693]])" + ] + }, + "execution_count": 137, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b = np.loadtxt('data.txt')\n", + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.0465854 , -2.03141473, -0.67723476],\n", + " [ 1.77452637, -1.23614157, -0.07185707],\n", + " [ 2.36967371, -2.7262374 , -2.56043385]])" + ] + }, + "execution_count": 138, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c = a + b\n", + "np.savetxt('data.txt', c)\n", + "d = np.loadtxt('data.txt')\n", + "d" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 02-3. csv 파일 처리하기" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overwriting file.dat\n" + ] + } + ], + "source": [ + "%%writefile file.dat\n", + "1 2 3\n", + "4 5 6\n", + "7 8 9" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 2., 3.],\n", + " [4., 5., 6.],\n", + " [7., 8., 9.]])" + ] + }, + "execution_count": 141, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = np.genfromtxt('file.dat')\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 142, + "metadata": {}, + "outputs": [], + "source": [ + "np.savetxt('file.csv', data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# %load file.csv\n", + "1.000000000000000000e+00 2.000000000000000000e+00 3.000000000000000000e+00\n", + "4.000000000000000000e+00 5.000000000000000000e+00 6.000000000000000000e+00\n", + "7.000000000000000000e+00 8.000000000000000000e+00 9.000000000000000000e+00\n" + ] + }, + { + "cell_type": "code", + "execution_count": 145, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 2., 3.],\n", + " [4., 5., 6.],\n", + " [7., 8., 9.]])" + ] + }, + "execution_count": 145, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = np.loadtxt('file.csv')\n", + "a" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 02-4 직렬화 처리 \n", + "npz 확장자를 사용하여 다차원 배열을 직렬화 처리하고 저장" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-2.2680059 , 0.52827395, 0.69363968, 1.92301472, -1.7353325 ],\n", + " [-1.34918042, -1.19615115, -0.7221849 , -0.88853132, -0.96246549],\n", + " [-0.52816851, 1.12375436, 1.53145049, 0.4935921 , -0.26263873]])" + ] + }, + "execution_count": 146, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.random.randn(3, 5)\n", + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "xxx.npz\r\n" + ] + } + ], + "source": [ + "np.savez('xxx', x) # 파일이름과 배열을 인자로 전달, npz 확장자를 지정하지 않아도 npz파일이 만들어짐.\n", + "%ls xxx.*" + ] + }, + { + "cell_type": "code", + "execution_count": 148, + "metadata": {}, + "outputs": [], + "source": [ + "y = np.load('xxx.npz')" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.lib.npyio.NpzFile" + ] + }, + "execution_count": 149, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(y)" + ] + }, + { + "cell_type": "code", + "execution_count": 150, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['arr_0']" + ] + }, + "execution_count": 150, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y.files" + ] + }, + { + "cell_type": "code", + "execution_count": 151, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-2.2680059 , 0.52827395, 0.69363968, 1.92301472, -1.7353325 ],\n", + " [-1.34918042, -1.19615115, -0.7221849 , -0.88853132, -0.96246549],\n", + " [-0.52816851, 1.12375436, 1.53145049, 0.4935921 , -0.26263873]])" + ] + }, + "execution_count": 151, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y['arr_0']" + ] + }, + { + "cell_type": "code", + "execution_count": 152, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "allow_pickle\n", + "close\n", + "f\n", + "fid\n", + "files\n", + "get\n", + "items\n", + "iteritems\n", + "iterkeys\n", + "keys\n", + "pickle_kwargs\n", + "values\n", + "zip\n" + ] + } + ], + "source": [ + "# 다양한 속성과 메소드를 제공\n", + "for i in dir(y) :\n", + " if not i.startswith(\"_\") :\n", + " print(i)" + ] + }, + { + "cell_type": "code", + "execution_count": 153, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.34013116, -1.34136584, -2.3307599 ],\n", + " [-1.32950889, -0.0708689 , -2.5587767 ],\n", + " [ 0.43589296, -0.26617065, 0.47097827]])" + ] + }, + "execution_count": 153, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# savez를 쓰는 이유 : Save several arrays into a single file in uncompressed .npz format.\n", + "z = np.random.randn(3, 3)\n", + "z" + ] + }, + { + "cell_type": "code", + "execution_count": 166, + "metadata": {}, + "outputs": [], + "source": [ + "np.savez('xxx', x, z)" + ] + }, + { + "cell_type": "code", + "execution_count": 167, + "metadata": {}, + "outputs": [], + "source": [ + "z = np.load('xxx.npz')" + ] + }, + { + "cell_type": "code", + "execution_count": 168, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['arr_0', 'arr_1']" + ] + }, + "execution_count": 168, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "z.files" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git "a/11\354\236\245/[\353\204\230\355\214\214\354\235\264]11\354\236\245.pptx" "b/11\354\236\245/[\353\204\230\355\214\214\354\235\264]11\354\236\245.pptx" new file mode 100644 index 0000000..f553d7a Binary files /dev/null and "b/11\354\236\245/[\353\204\230\355\214\214\354\235\264]11\354\236\245.pptx" differ diff --git "a/11\354\236\245/data.txt" "b/11\354\236\245/data.txt" index 9c100b5..c9d76c6 100644 --- "a/11\354\236\245/data.txt" +++ "b/11\354\236\245/data.txt" @@ -1,3 +1,3 @@ --8.807673396912342467e-02 1.299891280619033695e+00 -1.702531025254405250e+00 -2.695346024375412375e-01 -6.562890167626656002e-01 -3.256471446663196101e-01 --3.402731251821572656e+00 8.307910520255361586e-01 -1.898912526564466019e-01 +4.658540330437908189e-02 -2.031414726295595496e+00 -6.772347554012705384e-01 +1.774526373252180989e+00 -1.236141565328994218e+00 -7.185706864195791355e-02 +2.369673705661849095e+00 -2.726237397250626415e+00 -2.560433853957591044e+00 diff --git "a/11\354\236\245/file.csv" "b/11\354\236\245/file.csv" index 218f6b5..7b249fc 100644 --- "a/11\354\236\245/file.csv" +++ "b/11\354\236\245/file.csv" @@ -1,3 +1,3 @@ --8.111932400000000376e-01 1.327153299999999925e-01 -5.329174599999999540e-01 --1.786650400000000083e+00 5.388557099999999878e-01 -5.990491000000000010e-01 -1.026376790000000039e+00 -1.755254099999999928e-01 1.739503390000000094e+00 +1.000000000000000000e+00 2.000000000000000000e+00 3.000000000000000000e+00 +4.000000000000000000e+00 5.000000000000000000e+00 6.000000000000000000e+00 +7.000000000000000000e+00 8.000000000000000000e+00 9.000000000000000000e+00 diff --git "a/11\354\236\245/file.dat" "b/11\354\236\245/file.dat" index 107912c..50ecbb5 100644 --- "a/11\354\236\245/file.dat" +++ "b/11\354\236\245/file.dat" @@ -1,3 +1,3 @@ --0.81119324 0.13271533 -0.53291746 --1.7866504 0.53885571 -0.5990491 -1.02637679 -0.17552541 1.73950339 +1 2 3 +4 5 6 +7 8 9 diff --git "a/11\354\236\245/m.npy" "b/11\354\236\245/m.npy" index c60e333..c09993d 100644 Binary files "a/11\354\236\245/m.npy" and "b/11\354\236\245/m.npy" differ diff --git "a/11\354\236\245/n.npy" "b/11\354\236\245/n.npy" index 32101be..f2c678c 100644 --- "a/11\354\236\245/n.npy" +++ "b/11\354\236\245/n.npy" @@ -1,2 +1 @@ -t>Z-}?b&?3>n?CYRdo뿄?p4?F*?#v"\ÿ=gvnnӻV?Y /Ar? -?E{`= \ No newline at end of file +斠[n0D?Q7x/?7Rz"uM6 @m+?%Mwsm?-AjN8]*7?؉nD?zD3)O? \ No newline at end of file diff --git "a/11\354\236\245/numpy_chapter_11_1_1.ipynb" "b/11\354\236\245/numpy_chapter_11_1_1.ipynb" index 36ec9e0..50ffbff 100644 --- "a/11\354\236\245/numpy_chapter_11_1_1.ipynb" +++ "b/11\354\236\245/numpy_chapter_11_1_1.ipynb" @@ -616,7 +616,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.7.5" } }, "nbformat": 4, diff --git "a/11\354\236\245/xxx.npz" "b/11\354\236\245/xxx.npz" new file mode 100644 index 0000000..70ea5d8 Binary files /dev/null and "b/11\354\236\245/xxx.npz" differ diff --git "a/12\354\236\245/12\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214.ipynb" "b/12\354\236\245/12\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214.ipynb" new file mode 100644 index 0000000..d994261 --- /dev/null +++ "b/12\354\236\245/12\354\236\245_\353\260\234\355\221\234\354\236\220\353\243\214.ipynb" @@ -0,0 +1,1371 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.19.2'" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "np.__version__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Chapter 12. 선형대수 알아보기 \n", + "> 수학의 소인수분해처럼 선형대수의 행렬도 여러 분해가 가능합니다. 하나의 행렬을 분해하는 여러가지 함수들을 알아봅시다.\n", + "[넘파이 선형대수 참고](https://rfriend.tistory.com/380)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 01. LU, QR 분해 \n", + "### 01-1. LU 분해 \n", + "LU 분해는 정사각형행렬 A를 하삼각행렬(Lower triangular matrix)과 상삼각행렬(Upper triangular matrix)의 곱으로 표현하는 분해입니다. 여기서 치환행렬(Permutation matrix)도 함께 곱으로 나타내기도 합니다.즉, A=LU\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "import scipy as sp\n", + "from scipy import linalg as LA" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 7, 3, -1, 2],\n", + " [ 3, 8, 1, -4],\n", + " [-1, 1, 4, -1],\n", + " [ 2, -4, -1, 6]])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.array([[7,3,-1,2], [3,8,1,-4], [-1,1,4,-1], [2,-4,-1,6]])\n", + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 0., 0., 0.],\n", + " [0., 1., 0., 0.],\n", + " [0., 0., 1., 0.],\n", + " [0., 0., 0., 1.]])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P, L, U = LA.lu(A) # LU 분해를 lu 함수로 실행\n", + "P" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1. , 0. , 0. , 0. ],\n", + " [ 0.42857143, 1. , 0. , 0. ],\n", + " [-0.14285714, 0.21276596, 1. , 0. ],\n", + " [ 0.28571429, -0.72340426, 0.08982036, 1. ]])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "L" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 7. , 3. , -1. , 2. ],\n", + " [ 0. , 6.71428571, 1.42857143, -4.85714286],\n", + " [ 0. , 0. , 3.55319149, 0.31914894],\n", + " [ 0. , 0. , 0. , 1.88622754]])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "U" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 역행렬이 존재하는 조건 : det(A) ≠ 0 \n", + "[행렬식 계산 참고](http://blog.naver.com/PostView.nhn?blogId=mykepzzang&logNo=221080004072) \n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = LA.det(L)\n", + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "315.0000000000001" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b = LA.det(U)\n", + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "315.0000000000001" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(a, b)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "315.0000000000001" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "LA.det(A)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 7., 3., -1., 2.],\n", + " [ 3., 8., 1., -4.],\n", + " [-1., 1., 4., -1.],\n", + " [ 2., -4., -1., 6.]])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(L, U)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 01-2. LU 분해와 연립방정식 풀기" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 7. , 5. , 6. , 6. ],\n", + " [ 0.28571429, 3.57142857, 6.28571429, 5.28571429],\n", + " [ 0.71428571, 0.12 , -1.04 , 3.08 ],\n", + " [ 0.71428571, -0.44 , -0.46153846, 7.46153846]])" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.array([[2,5,8,7], [5,2,2,8], [7,5,6,6], [5,4,4,8]])\n", + "lu, piv = LA.lu_factor(A)\n", + "lu" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2, 2, 3, 3], dtype=int32)" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "piv" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1. , 0. , 0. , 0. ],\n", + " [ 0.28571429, 1. , 0. , 0. ],\n", + " [ 0.71428571, 0.12 , 1. , 0. ],\n", + " [ 0.71428571, -0.44 , -0.46153846, 1. ]])" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P, L, U = LA.lu(A)\n", + "L" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 7. , 5. , 6. , 6. ],\n", + " [ 0. , 3.57142857, 6.28571429, 5.28571429],\n", + " [ 0. , 0. , -1.04 , 3.08 ],\n", + " [ 0. , 0. , 0. , 7.46153846]])" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "U" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.05154639, -0.08247423, 0.08247423, 0.09278351])" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.array([[2,5,8,7], [5,2,2,8], [7,5,6,6], [5,4,4,8]])\n", + "b = np.array([1,1,1,1])\n", + "lu, piv = LA.lu_factor(A)\n", + "x = LA.lu_solve((lu, piv), b)\n", + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(A @ x - b, np.zeros((4,)))" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.05154639, -0.08247423, 0.08247423, 0.09278351])" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x_ = np.linalg.solve(A, b)\n", + "x_" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.05154639, -0.08247423, 0.08247423, 0.09278351])" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(np.linalg.inv(A), b)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1.])" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(A, x_)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1.])" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A @ x" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 01-2. QR 분해 \n", + "QR 분해(QR decomposition or QR factorization)는 임의의 행렬을 직교행렬과 상삼각행렬의 곱으로 분해합니다. 즉, 행렬 A를 QR로 인수분해합니다. 여기서 Q는 직교 좌표이고 R은 상삼각행렬 입니다. " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 12, -51, 4],\n", + " [ 6, 167, -68],\n", + " [ -4, 24, -41]])" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.array([[12,-51,4], [6,167,-68], [-4,24,-41]])\n", + "A" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ -14., -21., 14.],\n", + " [ 0., -175., 70.],\n", + " [ 0., 0., -35.]])" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Q, R = LA.qr(A)\n", + "R" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.85714286, 0.39428571, 0.33142857],\n", + " [-0.42857143, -0.90285714, -0.03428571],\n", + " [ 0.28571429, -0.17142857, 0.94285714]])" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Q" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.00000000e+00, 9.70056801e-17, -2.53402741e-17],\n", + " [ 9.70056801e-17, 1.00000000e+00, -2.88873234e-17],\n", + " [-2.53402741e-17, -2.88873234e-17, 1.00000000e+00]])" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "i = np.dot(Q, Q.T)\n", + "i" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "I = np.eye(A.shape[0])\n", + "np.allclose(i, I)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9999999999999999" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sq = np.fabs(LA.det(Q))\n", + "# sq = np.fabs(LA.linalg.det(Q)) 교재 본문에 오류가 있음.\n", + "sq" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(sq, 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "qt = LA.inv(Q)\n", + "np.allclose(Q.T, qt)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 02. 고유값, 특이값 분해 \n", + "행렬을 하나의 벡터로 분리 또는 여러개의 행렬로 분해하는 고유값 분해와 3개의 행렬로 분해하는 특이값 분해가 있습니다. \n", + "고유값은 주로 정사각형 행렬에 대한 분에에 사용되며, 차원의 다른 행렬일 때는 특이값 분해를 사용합니다. \n", + "### 02-1. 고유값과 고유벡터 \n", + "고유값 분해(eigen decomposition)는 고유값(eigen value)과 고유벡터(eigen vector)로 유도되는 고유값 행렬과 고유벡터 행렬에 의해 분해 될 수 있는 행렬의 표현입니다. \n", + "고유값과 고유벡터는 정사각행렬일 때문 분해가 가능합니다. " + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [], + "source": [ + "A = np.array([[3,0], [8,-1]])\n", + "x = np.array([1,2])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "고유값을 구하는 산식은 단위행렬에 특정 상수를 곱하고 이를 행렬에 뺀 후에 행렬식을 구하면 0이 나오면 이 상수 값이 고유값이 됩니다. \n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 0.],\n", + " [0., 1.]])" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "E = np.eye(2) # 단위행렬을 eye함수로 하나 만듭니다.\n", + "E" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "LA.det(A - 3*E) # 단위행렬에 3을 곱한 후에 행렬 A에 빽 det 함수로 행렬식을 구하면 0이 나와서 이 상수가 고유값입니다." + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "LA.det(A - -1*E)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "고유값과 고유벡터를 구하는 수학적 산식은 아래와 같습니다. 하나의 행렬과 벡터를 행렬곱으로 계산한 것이 상수에 벡터를 곱한 결과와 동일합니다. \n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 6])" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c = np.dot(A, x)\n", + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 6])" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "3*x" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 넘파이 모듈을 사용해서 행렬의 고유값과 고유벡터를 구해보자. \n", + "LA.eig 함수에 인자로 전달해서 실행하면 끝! 반환되는 결과가 고유값과 고유벡터 \n", + "단, 고유값의 결과가 1차원 배열로 나오는 것은 이 행렬의 고유값이 2개가 있다는 뜻이고 단위벡터도 2차원 배열로 나온것은 두 개의 단위벡터가 있다는 뜻" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 4.+0.j, -2.+0.j])" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "B = np.array([[1,3], [3,1]])\n", + "v, w = LA.eig(B)\n", + "v" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.70710678, -0.70710678],\n", + " [ 0.70710678, 0.70710678]])" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "w" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " 첫번째 예제 처럼 산식으로 검증해보자." + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 0.],\n", + " [0., 1.]])" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "E = np.eye(2, 2)\n", + "E" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "LA.det(B - (4*E))" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "LA.det(B - (-2*E))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3개의 행렬로 분해한 처리 \n", + "하나의 정사각행렬을 분해하면 고유벡터의 행렬과 고유값을 단위벡터에 행렬곱한 행렬 고유벡터의 행렬의 전치행렬을 가지고 행렬곱을 한 결과가 분해하기 전에 행렬이다. \n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[4, 3],\n", + " [3, 5]])" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "C = np.array([[4,3], [3,5]])\n", + "C" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.45861873+0.j, 7.54138127+0.j])" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "e, ev = LA.eig(C) # 고유값과 고유벡터를 eig 함수로 계산\n", + "e" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.76301998, -0.6463749 ],\n", + " [ 0.6463749 , -0.76301998]])" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ev" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1.45861873+0.j, 0. +0.j],\n", + " [0. +0.j, 7.54138127+0.j]])" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 앞의 예에서 만들어진 단위벡터를 사용해서 고유값과 곱셈해서 2차원 행렬로 변환\n", + "e_ = e * E\n", + "e_" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[4.+0.j, 3.+0.j],\n", + " [3.+0.j, 5.+0.j]])" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 3개의 행렬을 가지고 행렬곱을 해서 계산하면 원 행렬이 나옴. \n", + "C_ = np.dot(np.dot(ev, e_), ev.T)\n", + "C_" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.allclose(C_, C) # allclose 함수로 동일한지 확인" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.2 SVD 분해 \n", + "특이값 분해(Singular Value Decomposition, SVD)는 고유값 분해처럼 행렬을 대각화 해서 분해하는 방식입니다. \n", + "고유값 분해는 정사각행렬일 때만 분해가 가능하지만, 특이값 분해는 정사각행렬이 아닐 경우에도 분해가 가능합니다. \n", + "또한 이 행렬이 분해 할 때 구해진 특이값의 개수가 행렬의 랭크를 의미하기도 합니다. \n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.22975292, -0.97324899],\n", + " [-0.97324899, 0.22975292]])" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A = np.array([[1,0], [1,2]])\n", + "U, S, V = np.linalg.svd(A, full_matrices=True) # 분해하는 3개의 행렬을 모두 반환\n", + "U" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2.28824561, 0.87403205])" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "S" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.52573111, -0.85065081],\n", + " [-0.85065081, 0.52573111]])" + ] + }, + "execution_count": 85, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "V" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "보통 3개의 행렬을 확인하면 두개의 특이값 벡터와 하나의 특이값인 것을 알수 있습니다. \n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 다시 분해된 것을 행렬곱으로 계산해서 원 행렬이 나오는지 알아보자." + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.00000000e+00, -6.10622664e-16],\n", + " [ 1.00000000e+00, 2.00000000e+00]])" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 특이값이 하나의 벡터이므로 이 특이값을 대각행렬로 변형, 대각행렬 하나 만들어 특이값 벡터와 곱을 통해 변환하자.\n", + "E = np.eye(2)\n", + "SE = S * E \n", + "\n", + "# 위에서 만들어진 직교행렬과 행렬곱을 구하자.\n", + "np.dot(U, np.dot(SE, V))" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# np.allclose 함수로 동일한지 확인\n", + "np.allclose(A, np.dot(U, np.dot(SE, V)))" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.1404708 , 0.75576256, -0.63960215],\n", + " [-0.44811108, -0.6245843 , -0.63960215],\n", + " [-0.88287282, 0.19676738, 0.42640143]])" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 3행 2열의 배열을 만들고 이 행렬을 특이값 분해\n", + "B = np.array([[1,0], [1,2], [3,3]])\n", + "U_, S_, V_ = np.linalg.svd(B, full_matrices=True)\n", + "U_" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([4.80055841, 0.97705628])" + ] + }, + "execution_count": 92, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "S_" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.67433829, -0.73842256],\n", + " [ 0.73842256, -0.67433829]])" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "V_" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[4.80055841, 0. ],\n", + " [0. , 0.97705628],\n", + " [0. , 0. ]])" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 특이값을 대각행렬로 바꾸려고 할 때 정사각행렬이 아니므로 대각 행렬도 3행 2열에 맞춘 대각선을 반영\n", + "E3 = np.eye(3)[:, :2]\n", + "SE3 = S_ * E3\n", + "SE3" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.00000000e+00, -5.55111512e-16],\n", + " [ 1.00000000e+00, 2.00000000e+00],\n", + " [ 3.00000000e+00, 3.00000000e+00]])" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# 행렬 곱을 통해 원행렬을 만들자.\n", + "np.dot(U_, np.dot(SE3, V_))" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 96, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# np.allclose 함수로 동일한지 확인\n", + "np.allclose(A, np.dot(U, np.dot(SE, V)))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git "a/12\354\236\245/[\353\204\230\355\214\214\354\235\264]12\354\236\245.pptx" "b/12\354\236\245/[\353\204\230\355\214\214\354\235\264]12\354\236\245.pptx" new file mode 100644 index 0000000..b769506 Binary files /dev/null and "b/12\354\236\245/[\353\204\230\355\214\214\354\235\264]12\354\236\245.pptx" differ diff --git "a/12\354\236\245/chapter 11, 12 quiz \352\271\200\353\257\274\352\267\234" "b/12\354\236\245/chapter 11, 12 quiz \352\271\200\353\257\274\352\267\234" new file mode 100644 index 0000000..00112cd --- /dev/null +++ "b/12\354\236\245/chapter 11, 12 quiz \352\271\200\353\257\274\352\267\234" @@ -0,0 +1,17 @@ +기본적으로 그것은 조각난 배열 안에 있는 원소들의 합을 돌려주는 것 + +array = np.arange(10) +indices = np.array([1,3,4,5]) +output = numpy.add.reduceat(array,indices) +print(output) + +output=[ 3 3 4 35] + + + +print("Step1 : ", np.add.reduce(array[1:3])) +print("Step2 : ", np.add.reduce(array[3:4])) +print("Step3 : ", np.add.reduce(array[4:5])) +print("Step4 : ", np.add.reduce(array[5:])) + +.reduce()를 배열을 통해 반복적으로 적용하고 각 단계의 결과를 목록에 추가하고 결과를 표시 diff --git "a/13\354\236\245/13\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" "b/13\354\236\245/13\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" new file mode 100644 index 0000000..778d57b --- /dev/null +++ "b/13\354\236\245/13\354\236\245_\355\200\264\354\246\210_\354\236\245\354\203\201\352\267\274.txt" @@ -0,0 +1,10 @@ +Q1) "오일러 경로"와 "해밀턴 경로"란 무엇인가? +해밀턴 경로 : 모든 꼭짓점들을 딱 한 번만 거치는 경로 +오일러 경로 : 모든 변들을 딱 한 번 지나는 경로 + +Q2) 그래프를 표현하는 3가지 방법 +연결선 리스트(Edge lists), 인접 행렬, 인접 리스트 +https://ko.khanacademy.org/computing/computer-science/algorithms/graph-representation/a/representing-graphs + +Q3) 넘파이 행렬과 배열의 차이 +행렬은 행과 열로 이루어진 우리가 수학적으로 알고 있는 행렬과 동일한 형태이고 배열은 이러한 행렬을 여러장을 쌓아 올린 형태 \ No newline at end of file diff --git "a/13\354\236\245/[\353\204\230\355\214\214\354\235\264]13\354\236\245.pptx" "b/13\354\236\245/[\353\204\230\355\214\214\354\235\264]13\354\236\245.pptx" new file mode 100644 index 0000000..16cd597 Binary files /dev/null and "b/13\354\236\245/[\353\204\230\355\214\214\354\235\264]13\354\236\245.pptx" differ diff --git "a/13\354\236\245/img/s0 (1).PNG" "b/13\354\236\245/img/s0 (1).PNG" new file mode 100644 index 0000000..ce27743 Binary files /dev/null and "b/13\354\236\245/img/s0 (1).PNG" differ diff --git "a/13\354\236\245/img/s0 (10).PNG" "b/13\354\236\245/img/s0 (10).PNG" new file mode 100644 index 0000000..df1a34a Binary files /dev/null and "b/13\354\236\245/img/s0 (10).PNG" differ diff --git "a/13\354\236\245/img/s0 (11).PNG" 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+ } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![s0%20%283%29.PNG](attachment:s0%20%283%29.PNG)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 13-1-1-1 방향없는 그래프 그리기" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# !pip install networkx --upgrade" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "import networkx as nx" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "G = nx.Graph()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "networkx.classes.graph.Graph" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(G)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "G.add_edge(1,2)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
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+ } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![s0%20%284%29.PNG](attachment:s0%20%284%29.PNG)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "G = nx.Graph()\n", + "G.add_node('apple') \n", + "G.add_nodes_from(['banana','kiwi','mango'])\n", + "fruits = ['_banana','_kiwi','_mango']\n", + "G.add_nodes_from(fruits)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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xZMgQlixZwqpVq7q9Z63OICIifVZYWHjkdSAQIL+goKtGlekHuw3icVixFGp+79TgMg4d0RKGnDOc10eHWdah8wCa98Kwoq59lgVDj9pu3ouncDgdhwYojBgxgs7O7nuTKvhERCRpPDhLCx1j3XPwyktwz3IoLHFqetdPgp6MpssfBq82dW0bA/sbj9pfQLxpD5mHhjPs2rULr7f7aFNTp4iIJE2ON4PYR2drsVudJs7cILTb8NSPen7BCy+Bndvg5Rch3gm/q4bwvq79l3yO2LNP0rangYMHD3LnnXcyc+bMbi+p4BMRkaTxWBajsj8yf+bl10HBcLh5Ksy9Bs4b3/ML5uXDwp/A8vvhhs9Cw7twzljwHSrjiv/L0Glf4O8vvYRRo0bh9/t5+OGHu72kZm4REZGkuuUvjSwPtXS7yGyfJRLwTxfDHQ/AuMlYwOySXH75maKTnnqYanwiIpJUs0vzyPb0f6X0I7ash4MtEOuA3zwKhiO1xmyPxZzSvF5dTp1bREQkqSqCfgoyPcmbq/PtOmfcX2cHlJ4D33nE6fkJFGZ5mRL09+pyauoUEZGkWxGKMPeNvbSmcOqyHI/Fo2MLmFXSuxqfmjpFRCTpZhXnMjHPjzeJLZ5H81pwYZ6fquLcXp+r4BMRkaSzLIvq8UUEMlKTfIEMi+oJRb1ajuiwtARfLGEI2TF2tHUQsmPHj/EQEZFBpyTgY3V5SXI7uuB0aFldXkKx33fyg08gJc/4jDHUhqMsb4hQE7apb4vhy7DIwBnRH0sYRmX7uCgYYHZpHhVBf59SW0RETn+1zTbTN4awE6ZfK7J7Laemt7q8hIr8QJ+vk9TgM8awcncLi7bvZ29HnLa46XYch4WT3AWZHhaPHsqs4lwFoIjIIBSyY1TVNbIlEu1Th5ccj8WFeX5Wji+iJNC3mt5hSQu+ZHyoiXl+qpPwoURE5PRjjKH6UOWoqReVo8JDlaOqJFWOkhJ8Nc02V59G1VgRETl9GWPYEI6yrCFCbdhmR1sMn2WRYUHCQMwYyrJ9VAQDzCnNY0qSH4f1O/hqmm2u3BhK6jLz2R6LFxR+IiKuEEsYmto76TCGTMuiMMuLL0W9QaGfwReyY4xZ9z4HUjBA8QyPxdZLRqrZU0REkqrPwxmMMVTWNWKnaGiCnTBU1TWiiWVERCSZ+hx8K3e38Fok2q9net3pNLAlEqV6d0tqChAREVfqU1OnMYaz19YnbwLSbpQFvLx72SgNcxARkaToU42vNhxlb0f8+B1zLoe6DSc+6evXwF9f7V1BP/0eDU8+xIZwtPc3KSIicgJ9WpZoeUOk9704f/Z87wuadzedwLKGiHp4iohIUvSpxlcTtlOzsu4JGKA2bKepNBERGex6HXyxhKG+LXbyAxveg1suh3WHanqHm0E72uGL4yDS7Ly/6mdw7RhoO+hsr1gKj/2783rpQlixlB1tmthaRESSo9fB19TeefKBhe++Cd+7Bb72XbjkmmP3ZWbBuRfAG5uc7Tc3Q8Fw2LrF2X5jM4wtP+YUn2XR1J76jjQiIjL49Tr4Oozp/qQ3N8MP5sI374Pyy058zNhJTvDFO6F+G/zjjc52Rzu88zqcP/HYm7ScckVERPqr18GXaVkkujtg9Sr49AQYN/njj7mgHF5/Fd7dCiNHw4QKeH0TvF0HnxwBefnHHJ4wTrkiIiL91evgK8zydv+87euL4cMP4PF7P/6YT02AUD28/Aen9nfWOfDhHtj8J2f7I2LGUJjVpw6oIiIix+h18PkyLEZldzN/ZnYOLH7CeVb35AMnPsYfgHPGwvPVXc/zPj0BVv8aLjg++MqyfSmdsFRERNyjT8MZLgoG6DaGhuTCPctg859hxY9PfMzYSc4zvvPGHdouB7sVzj8++CqCGsMnIiLJ0acpy2qaba7aGOrTgrO9leOxWKMlikREJEn6VOOrCPopyPQk+15OqDDLy5SgPy1liYjI4NfrHiO7du1izJgxzqoMH+3k8rPnnTF5SZLjsVh8br4mqBYRkaTp80K0xhgufSXEhrCdkqWJvJbzbG/t5BIFn4iIJE2f1+OzLIvq8UUEUtTbMpBhUT2hSKEnIiJJ1efgAygJ+FhdXkK2J7nhlO2xWF1eQrG/m2ETIiIifdDnps6j1TbbTN8Ywk6YfjV7ei2nprdavThFRCRFkhJ8ACE7RlVdI1si0T4Nc8jxWFyY52fl+CJKAqrpiYhIaiQt+MDp8FK9u4VF2/fT1BGnLW66XbfPwmnWLMz0sHj0UKqKc/VMT0REUiqpwXeYMYYN4SjLGiLUhm12tMXwWRYZljMCImYMZdk+KoIB5pTmMSXoV+CJiEhapCT4PiqWMDS1d9JhDJmWRWGWV3NviojIKZGW4BMRETld9Gs4g4iIyECj4BMREVdR8ImIiKso+ERExFUUfCIi4ioKPhERcRUFn4iIuIqCT0REXEXBJyIirqLgExERV1HwiYiIqyj4RETEVRR8IiLiKgo+ERFxFQWfiIi4ioJPRERcRcEnIiKuouATERFXUfCJiIirKPhERMRVFHwiIuIqCj4REXEVBZ+IiLiKgk9ERFxFwSciIq6i4BMREVdR8ImIiKso+ERExFUUfCIi4ioKPhERcRUFn4iIuIqCT0REXEXBJyIirqLgExERV1HwiYiIqyj4RETEVRR8IiLiKgo+ERFxFQWfiIi4ioJPRERcRcEnIiKu4j3VNyAiIqkXSxia2jvpMIZMy6Iwy4svwzrVt3VKKPhERAYhYwy14SjLGyLUhG3q22L4MiwygAROEI7K9nFRMMDs0jwqgn4syx1BaBljzKm+CRERSQ5jDCt3t7Bo+372dsRpixu6+5K3gGyPRUGmh8WjhzKrOHfQB6CCT0RkkAjZMarqGtkSidIa7/1Xe47HYmKen+rxRZQEfCm4w9ODgk9EZBCoaba5emMIO2Ho7Me3uteCQIbF6vISKvIDybvB04iCT0RkgKtptrlyY4i2PtTyPk62x+KFQRp+Cj4RkQEsZMcYs+59DiQx9A47w2Ox9ZKRg67ZU+P4REQGKGMMlXWN2InU1F/shKGqrpHBVj9S8ImIDFArd7fwWiTar2d63ek0sCUSpXp3S2oKOEXU1CkiMgAZYzh7bT31dmfKyyoLeHn3slGDZpiDanwiIqe5kSNH8uKLLx7zXm04yt6OeFrKb+qIsyEcTUtZ6aDgExEZgJY3RJLai7M7bXHDsoZIWspKBwWfiMgAVBO2u52RJZkMUBu201Ra6in4REQGgE2bNjFmzBiCwSA3/9NsdvztoLPjYAQWfw0qJ8PMSc7rfY1dJy68EVb8GL51PcyYAN+dA5Hmrv1LboVZFfDlifDtKtj5Tte+pQvh54vh+19l29VjKf/sZ3nvvfeO7L7tttsoLS0lNzeXiRMnsn79+hT/FZJDwSciMgBUV1ezZs0a3nvvPbZu2wa//rmzI5GAf/giLFsLy9dCZhY8evexJ6/7HXxjCax8GWIx+J9lXfsmXgyPrYHql+HsMfDAHR8593m4YR6B32ymeFQZd91115FdkyZNoq6ujubmZiorK5kxYwbR6On/LFDBJyIyAMybN4/S0lLy8/P5l299m/iffufsyA1CxZXgD0D2EJg5F17fdOzJ//BFKB4FWX6YehXseKtr37QvOef5MqFyPtS/Da0HuvZPuQLOG4fH6+VzX76eurq6I7tmzZrF0KFD8Xq9LFiwgPb2drZt25bCv0JyaFkiEZEBoLS09MjrkSNGYJr3OhtRG55YAlvWO82eAHYrxOPg8TjbwWFdF8oKQLTNeR2Pw4qlUPN7p/kz41BdqCUMOWccOvdMABIGcnNyOHjw4JFLPfjggzzxxBPs2bMHy7JoaWlh3759Sf/syabgExEZABoaGo68bmvcA/kFzsb/LINQPfzoN07A7XgLbr0OetL1Zd1z8MpLcM9yKCxxanrXT4ITDO+OGUPQ5zmyvX79en74wx/y0ksvcf7555ORkUEwGBwQs7yoqVNEZAB45JFHCIVCNDc38x/3LSH/8s85O+xWyMqCnFw48Df41U97flG71WnizA1Cuw1P/ehjDy3L9uE9asX2AwcO4PV6GTZsGJ2dndx99920tAyMGV4UfCIiA0BlZSXTpk2jrKyMsrIyPjf/DiyAz98M7e1Or84FM2Hi1J5f9PLroGA43DwV5l4D540/4WEWUBE8dpWGK6+8kunTpzN69GhGjBiB3+8/pjn2dKYpy0REBqCaZpurNob6tOBsb+V4LNYMoiWKVOMTERmAKoJ+CjI9Jz8wCQqzvEwJ+tNSVjoo+ERETgO7du1iyJAhJ/y3a9eu4463LIvFo4eS40ntxNE5HovF5+YPmgmqQU2dIiIDljGGS18JsSFsp2RpIq/lPNtbO7lkUAWfanwiIgOUZVlUjy8ikJGaUApkWFRPKBpUoQcKPhGRAa0k4GN1eQnZSW7yzPZYrC4vodjvS+p1Twdq6hQRGQRqm22mbwxhJ0y/mj29llPTWz2IenF+lIJPRGSQCNkxquoa2RKJ9mmYQ47H4sI8PyvHF1ESGHw1vcMUfCIig4gxhurdLSzavp+mjjhtcdPt5GUWTrNmYaaHxaOHUlWcO+ie6X2Ugk9EZBAyxrAhHGVZQ4TasM2Othg+yyLDciacjhlDWbaPimCAOaV5TAn6B33gHabgExFxgVjC0NTeSYcxZFoWhVlefCnqDXq6U/CJiIiraDiDiIi4ioJPRERcRcEnIiKuouATERFXUfCJiIirKPhERMRVFHwiIuIqCj4REXEVBZ+IiLiKgk9ERFxFwSciIq6i4BMREVdR8ImIiKso+ERExFUUfCIi4ireU30D4tAikSIi6aHgO0WMMdSGoyxviFATtqlvi+HLsMgAEjhBOCrbx0XBALNL86gI+rEsBaGISH9pBfY0M8awcncLi7bvZ29HnLa4obv/ABaQ7bEoyPSwePRQZhXnKgBFRPpBwZdGITtGVV0jWyJRWuO9/7PneCwm5vmpHl9EScCXgjsUERn8FHxpUtNsc/XGEHbC0NmPv7jXgkCGxeryEiryA8m7QRERl1DwpUFNs82VG0O09aGW93GyPRYvKPxERHpNwZdiITvGmHXvcyCJoXfYGR6LrZeMVLOniEgvaBxfChljqKxrxE6k5reFnTBU1TWi3y4iIj2n4EuhlbtbeC0S7dczve50GtgSiVK9uyU1BYiIDEIKvn4YOXIkL7744gn3GWNYtH1/n3pv9kZr3ClHtT4RkZ5R8KVIbTjK3o54Wspq6oizIRxNS1kiIgOdgi9FljdEktqLszttccOyhkhayhIRGegUfP20adMmxowZQzAYZPbs2USjUcLhML/+l0pM5WSYOQkWfw32NXadtPBGWPFj+Nb1MGMCfHcORJq79i+5FWZVwJcnwrerYOc7XfuWLoSfL4bvf9U59/YZmA92URu2AbjtttsoLS0lNzeXiRMnsn79+jT9JUREBgYFXz9VV1ezZs0a3nvvPbZv384999xDe2ec6OVfgGVrYflayMyCR+8+9sR1v4NvLIGVL0MsBv+zrGvfxIvhsTVQ/TKcPQYeuOMj5z4PN8yDVZvgk2fBU0vZ0RYjljBMmjSJuro6mpubqaysZMaMGUSjagYVETlMwddP8+bNo7S0lPz8fO666y6efvppOofkkTX1KvAHIHsIzJwLr2869sR/+CIUj4IsP0y9Cna81bVv2pec83yZUDkf6t+G1gNd+6dcAeeNA48XLr0W6t/CZ1k0tXcya9Yshg4ditfrZcGCBbS3t7Nt27b0/DFERAYArc7QT6WlpUdejxgxgj179hBpbaXjoe/C5vVw8NCzN7sV4nHweJzt4LCui2QFINrmvI7HYcVSqPm90/yZcei3SUsYcs44dO6ZR53rB7uNDAs6jOHBBx/kiSeeYM+ePViWRUtLC/v27UvRpxcRGXgUfP3U0NBw5PWuXbsYPnw4yx/6MYlQPfzoN07A7XgLbr0Oul2H4ZB1z8ErL8E9y6GwxKnpXT8JTjJcIWHgfzfU8sMf/pCXXnqJ888/n4yMDILBoIY6iIgcRU2d/fTII48QCoVobm7m3nvvZebMmRi7FZOZBTm5cOBv8Kuf9vyCdqvTxJkbhHYbnsMgyegAAAXkSURBVPpRj06LGYMv2obX62XYsGF0dnZy991309Kiwe0iIkdT8PVTZWUl06ZNo6ysjLKyMr7zne+w4JvfxN/ZAZWTYcFMmDi15xe8/DooGA43T4W518B543t0Wlm2j2umX8X06dMZPXo0I0aMwO/3H9MUKyIimqQ6ZW75SyPLQy09adzsNwuYXZLLLz9TlIbSREQGNtX4UmR2aR7ZnvSslJ7tsZhTmpeWskREBjoFX4pUBP0UZHrSUlZhlpcpQX9ayhIRGegUfCliWRaLRw8lJ8W1vhyPxeJz87Gs9NQuRUQGOgVfCs0qzmVinh9vijLJa8GFeX6qinNTU4CIyCCk4Eshy7KoHl9EICM1yRfIsKieUKTanohILyj4Uqwk4GN1eUnSO7pkeyxWl5dQ7Pcl9boiyRJLGEJ2jB1tHYRsZy5ZkdOBhjOkSW2zzfSNIeyE6deK7F7LqemtLi+hIj+QvBsU6SdjDLXhKMsbItSEberbYvgyLDKABE4Qjsr2cVEwwOzSPCqCfrVWyCmh4EujkB2jqq6RLZFon1Zmz/FYXJjnZ+X4IkoCqunJ6cEYw8rdLSzavp+9HXHa4qbb8asWTotFQaaHxaOHMqs4VwEoaaXgSzNjDNWHviSaevElUXjoS6JKXxJyGknGj7mJeX6q9WNO0kjBd4oYY9gQjrKsIUJt2GZHWwyfZZFhORNOx4yhLNtHRTDAnNI8pqhZSE4zNc02V6v5XgYgBd9pIpYwNLV30mEMmZZFYZYXX4p6g4r0V02zzZUbQ7T1oZb3cbI9Fi8o/CQNFHwi0ishO8aYde9zIImhd9gZHoutl4xUs6eklIYziEiPGWOorGvETtHQBDthqKpr1BqSklIKPhHpsZW7W3gtEu3XM73udBrYEolSvVvrSErqKPhEpEeMMSzavt/pvTnncqjbcPxBX78G/vpq7y780+/B048c2WyNO+Wo1iep4j3VNyAiA0NtOMrejnj3B/3s+d5feN7dx73V1BFnQziqji6SEqrxiUiPLG+IJLUXZ3fa4oZlDZG0lCXuo+ATkR6pCdsnnmyh4T245XJY93xXE2hHO3xxHESanWNW/QyuHQNtB53tFUvhsX93Xi9d6GwfxQC1YTtVH0VcTsEnIicVSxjq22LH73j3TfjeLfC178Il13S9n5kF514Ab2xytt/cDAXDYesWZ/uNzTC2vNsyd7RpYmtJDQWfiJxUU3vn8RMqvLkZfjAXvnkflF92/EljJznBF++E+m3wjzc62x3t8M7rcP7Ebsv0WRZN7Z1J/BQiDgWfiJxUhzHHf1msXgWfngDjJp/4pAvK4fVX4d2tMHI0TKiA1zfB23XwyRGQl99tmRmWU65Isin4ROSkMi2LxEff/Ppi+PADePzeE5/0qQkQqoeX/+DU/s46Bz7cA5v/5GyfRMI45Yokm4JPRE6qMMt7/PO27BxY/ITzvO7JB44/yR+Ac8bC89Vdz/M+PQFW/xouOHnwxYyhMEsjriT5FHwiclK+DItR2SeYP3NILtyzDDb/GVb8+Pj9Yyc5z/jOG3douxzsVjj/5MFXlu3TRO2SEpqkWkR65Ja/NLI81NLt+pHJYgGzS3L55WeK0lCauI1qfCLSI7NL88j2pKcGlu2xmFOal5ayxH0UfCLSIxVBPwWZnrSUVZjlZUrQn5ayxH0UfCLSI5ZlsXj0UHJSXOvL8VgsPjcfSz06JUUUfCLSY7OKc5mY58ebokzyWnBhnp+q4tzUFCCCgk9EesGyLKrHFxFIUW/LQIZF9YQi1fYkpRR8ItIrJQEfq8tLkt7RJdtjsbq8hGL/CYZNiCSRhjOISJ/UNttM3xjCTph+rcjutZya3uryEq2/J2mh4BORPgvZMarqGtkSiTors/dSjsfiwjw/K8cXURJQTU/SQ8EnIv1ijKF6dwuLtu+nqSNOW9x0O8jdwmnWLMz0sHj0UKqKc/VMT9JKwSciIq6izi0iIuIqCj4REXEVBZ+IiLiKgk9ERFxFwSciIq7y/wEViEMcjaQC+QAAAABJRU5ErkJggg==\n", 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Eoexj+Jeb7O2mRvjH+3Dh8KMOT7DsdttKwSciIjGTaFlEWztgxXL40jAYMvLkx1xUAO+/C9u3Qv9BMKwQ3t8IH5XCObmQmn7U4VFjt9tWCj4REYmZzCR36/fbbpsL/9wDv33o5Md8cRgEymD9n+3eX7/z4Z+7YdPb9vYxQsaQmdT2RQoKPhERiRlPgsUAfyv1M/3JMHehfa9uyc9PfIzXB+cPhjeKWu7nfWkYrHgRLjo++PL8nnY9sV3BJyIiMXV5mo9WY6hXCjy4CDatgaVPnPiYwSPse3wXDDm0XQDBOrjw+OArTGvfUxpUskxERGKquDLI1RsCHXrgbHsluyxWtvMRRerxiYhITBWmeclIdHVJW5lJbkaledt1jkqWiYhIzOzcuZP8/Hz7qQzHTnJ55g17TV6MJLss5g5Mb1eBatBQp4iIxIExhiveCbCuKhiXRxO5Lfve3qqR2e0OPg11iohIzFmWRdHQvvjaMduyPXwJFkXD+rY79EDBJyIicZLt87CiIBu/K7bh53dZrCjIJsvbyrKJVmioU0RE4qqkMsiEDQGCUdOpYU+3Zff0VrRzFuexFHwiIhJ3gWCIqaV72Vzd0KFlDskui0tSvSwb2pdsX8d6es0UfCIi0iWMMRTtquGBbQeoaIpQHzGtPrfPwh7WzEx0MXdQb6ZmpXTont5xn6vgExGRrmSMYV1VA4vKqympCrKjPoTHskiw7BUQIWPI83soTPMxMyeVUWnemAReMwWfiIicVqGooaIxTJMxJFoWmUnudtXebC8Fn4iIOIqWM4iIiKMo+ERExFEUfCIi4igKPhERcRQFn4iIOIqCT0REHEXBJyIijqLgExERR1HwiYiIoyj4RETEURR8IiLiKAo+ERFxFAWfiIg4ioJPREQcRcEnIiKOouATERFHUfCJiIijKPhERMRRFHwiIuIoCj4REXEUBZ+IiDiKgk9ERBxFwSciIo6i4BMREUdR8ImIiKMo+ERExFEUfCIi4igKPhERcRQFn4iIOIqCT0REHEXBJyIijqLgExERR1HwiYiIoyj4RETEURR8IiLiKAo+ERFxFAWfiIg4ioJPREQcRcEnIiKOouATERFHUfCJiIijKPhERMRRFHwiIuIoCj4REXEUBZ+IiDiKgk9ERBxFwSciIo6i4BMREUdR8ImIiKMo+ERExFEUfCIi4igKPhERcRQFn4iIOIqCT0REHEXBJyIijqLgExERR1HwiYiIoyj4RETEUdyn+wJ6qlDUUNEYpskYEi2LzCQ3ngTrdF+WiIicgoKvjYwxlFQ1sLi8muKqIGX1ITwJFglAFDsIB/g9XJ7mY0ZOKoVpXixLQSgi0t1Yxhhzui+iOzPGsGxXDQ9sO8C+pgj1EUNrfzAL8LssMhJdzB3Um2lZKQpAEZFuRMHXikAwxNTSvWyubqAu0v4/U7LLYniql6Khfcn2eeJwhSIi0l4KvpMorgwycUOAYNQQ7sRfyG2BL8FiRUE2hem+2F2giIh0iILvBIorg1y1IUB9B3p5J+N3Wbyp8BMROe0UfMcIBEPkr/6UgzEMvWZnuSy2ju2vYU8RkdNI6/iOYIxhSulegtH4/BYIRg1TS/ei3xoiIqePgu8Iy3bV8F51Q6fu6bUmbGBzdQNFu2ri04CIiJySgu8QYwwPbDvQMntz5pVQuu74A2+7Bv7+bvs+/Jf3wwtPA1AXsdtRr09E5PTQAvZDSqoa2NcUOfWBz7zR/g+f9dOjNiuaIqyratBEFxGR00A9vkMWl1fHdBZna+ojhkXl1V3SloiIHE3Bd0hxVfDkFVnKP4FbroTVb7QMgTY1wteHQHWlfczyZ+C6fKivtbeXLoDf/Mx+vWCOvX2IAUqqgvH6KiIi0goFH3adzbL60Il3bt8C998C37kPxl7T8n5iEgy8CD7YaG9v2QQZ58LWzfb2B5tgcMFJ29xRHyIUp9mjIiJycgo+oKIxfOInK2zZBP95K3x/PhSMO37/4BF28EXCUPYx/MtN9nZTI/zjfbhw+Enb9FgWFY3hGH4LERFpCwUf0GTMif8QK5bDl4bBkJEnPvGiAnj/Xdi+FfoPgmGF8P5G+KgUzsmF1PSTtplg2e2KiEjXUvABiZZF9EQ7bpsL/9wDv33oxCd+cRgEymD9n+3eX7/z4Z+7YdPb9nYrosZuV0REupaCD8hMcp/4fps/GeYutO/XLfn58fu9Pjh/MLxR1HI/70vDYMWLcFHrwRcyhswkrSYREelqCj7Ak2AxwH+S+pm9UuDBRbBpDSx94vj9g0fY9/guGHJouwCCdXBh68GX5/foie0iIqeBilQfcsvf9rI4UNPqQ2ZjxQJmZKfw3Jf7dkFrIiJyJPX4DpmRk4rf1TU9ML/LYmZOape0JSIiR1PwHVKY5iUj0dUlbWUmuRmV5u2StkRE5GgKvkMsy2LuoN4kx7nXl+yymDswHUszOkVETgsF3xGmZaUwPNWLO06Z5LbgklQvU7NS4tOAiIickoLvCJZlUTS0L744zbb0JVgUDeur3p6IyGmk4DtGts/DioLsmE908bssVhRkk+U9ybIJERHpElrOcBIllUEmbAgQjJpOPZHdbdk9vRUF2Xr+nohIN6Dga0UgGGJq6V42Vze0PJm9HTyREKP6pLBsaF+yfS09vVDUUNEYpskYEi2LzCS3FrOLiHQRBd8pGGMo2lXDA9sOUNEUoT5iWl3kbmEPa/Z2wf4n7+ejXz1CdnY2JVUNLC6vprgqSFl9CE+CRQIQxQ7CAX4Pl6f5mJGTSmGaV/cBRUTiRMHXRsYY1lU1sKi8mpKqIDvqQ3gsiwTLLjgdMoY8v4fCNB8zc1IZleblR/fcw3pvH8pH38C+doRmRqKLuYN6My0rRQEoIhJjCr4OOtVwZSAYYvKmAOv21djFrNsp2WUxPNVL0THDpCIi0jkKvjgorgwyURNjRES6JQVfjBVXBrlqQ4D6DkyGORm/y+JNhZ+ISEwo+GIoEAyRv/pTDsYw9Jqd5bLYOra/hj1FRDpJC9hjxBjDlNK9BE/0QNsYCEYNU0v3ot8pIiKdo+CLkWW7anivuqFT9/RaEzawubqBol018WlARMQhFHwxYIzhgW0HOrTI/YQqAnDtBfaT3Y9QF7HbUa9PRKTjFHwxUFLVwL6mSJe0VdEUYV1VQ5e0BfayjUAwxI76JgLBEKE4DeWKiHQV9+m+gDPB4vLqmM7ibE19xLCovDpuMzyNMaoyIyJnNAVfJ82fP5+lT/0KU7Ufzj4Hbvo+jPoqvPUKrHwJzrsQ/voqpPeB7z4AQy+zT5xzE3xxKPxtPewqg4sK4Hvz4KwvHN9I3UFYOA82rcFYFq9OnMRvljyJyxW7J8YbY1h2qDTbsVVmQseE+ra6EP+oC/HinoOqMiMiPY6GOjspd0AeZv4yeHEz3DgLHvshVO6zd378d+ibA8+/A1Nuh4dmwcHPW07+66twx0Pw+7XgcsOvHzxxIwvutvf/9k34xatUbVjDr3/z25h9h0AwxBXvBLj1g32UBcPUnaK0GoDBvudYFgxz6wf7uOKdAIFgKGbXJCISLwq+Thp93ddI7NMXEhJgzEQ4Nxe2/d3e+YV0uP5mcHvsfVkDYOPbLSdfeT30HwReP0y7A4r/GyLH3Cus2g+b1sC/3WMf94XeeG6YwbLly2Ny/cWVQfJXf8q6qmCHJ+fURQzrquzPKakMxuS6RETiRUOdnbR82VIa5j8KFbvsN4L1UFMFCS7onQlHDv9lnNvSGwR7aPTIfeGQfe6R9u22Z3dOv/zwW03RKPv79+v0tceyykzYwMGIYfyGgKrMiEi3puDrhM8++4x7Z92K52dLaBw0FFwumH09h8cJD1SAMS3h9889cOmVLR+wf0/L63/usXuGKWlHv9+nL3gS7eFSl/2fy59g8dcr+nfq2gPBEBNjXFoN7Mk3EzYEVGVGRLotDXV2Ql1dHZZlEUlJs9/488vw2T9aDvi8El77vd2TK14B5Z/AJWNb9q96DXZuh4YgLHsSCq+yw/NI6RkwrBAWzof6WohGadz1KR+uX9vh61aVGRFxMvX4OiE/P5+77rqL+T/4lt2rG3cD5F/ccsAFQ2D3ZzBlJHzhbPjRL+weXbNx18OCORDYAYML4LafnLihOx+BJT+HWydCsI5I70y+VrmXK6+8kjFjxjBmzBguvvhi3O62/efsyioz07JT49OIiEgHqUh1DNzyt70sDtQcPRPyrVfgzf+CR1448UlzboJx18FVk9rVlgXMyE7hZ5mwdu1aVq9ezZo1a/j000+57LLLGDt2LE899RTPPfccEydOPO58YwznrSqjLBg+/sNjLM/nZvu4AVrmICLdinp8MTAjJ5UX9xyMXcmyVvhdFjNzUumb7mPSpElMmmQH54EDByguLmbNmjVUVlbyjW98g5EjRx7uEY4cOZLk5OTTUmVGE11EpDtx1D2+eJXfKkzz0ivcGJPPOpXMJDej0rzHvd+7d2+uv/56HnvsMc455xyWL1/O3XffTSgU4v777yczM5NRo0Zx2x/eoj4S7ZJrba4yIyLSnZzRPb6uKL9VXl7O7Nmzsfx98U79Hg3NvyW+8nX7fyczf2m7v0+yy2LuwPQ2XePWrVtZunQpe/bs4YYbbuD111+nuLiYf537CGb7Fnu9YP7F8B9z4ey+9klzboILh8Pf34FPP4YvDoMf/BxS0+39826HLZuhqQEGfNG+J5k70N63YA54ffayji0bIed8zA8foyT5PADuuOMOXnnlFaqrqxk4cCBPPPEEo0ePbvffQESks87IHp8xhqWBas5bVcbVGwIsDtSwrS5EyNi9kNqIoT5iCBm7/NbiQA1Xbwhw3qoylgaq2zQbMRKJ8OSTTzJs2DAuvvhiyhY9QUF6Mu443c5yW3BJqpepWSltOr6oqIiVK1fyySefsG3bNh5//HEKLhtF9OpvwqJVsHgVJCbBsz89+sTVf7JLpy1bD6EQ/GFRy77hY+A3K6FoPZyXDz//wTHnvmFXr1m+Ec7pB79fwI56u2c9YsQISktLqaysZMqUKUyaNImGhq4rti0i0uyMC76uKL+1efNmLr30Uv74xz9SUlLC/fffj9frpWhoX3wJ8Uk+X4JF0bC+be6Rzpo1i5ycHNLT07n33nt54YUXCPdKJWn01XbPzN8LJt8K7288+sSvfN2uMJPkhdFXw44PW/aN/1f7PE8iTJkNZR/ZdUSbjfqqPZPV5YYrroOyD/FYFhWNYaZNm0bv3r1xu93cddddNDY28vHHH8fgLyMi0j5n1FBncWWQiRsCBKOmw1P1jyy/teKYCiS1tbXcd999PP/88zzyyCNMnz79qCDK9nlYUZDN+BgvDPe7LFYUZJPlbfuC8JycnMOvc3Nz2b17N9V1dTT94j7YtBZqD917C9bZw57N6wfT+rR8SJIPGurt15EILF1gl1WrrrRLtIFdaSb5rEPnnn3EuV4I1pNgQZMxPPbYYyxcuJDdu3djWRY1NTXs37+/vX8KEZFOO2N6fM3ltw5GOh56zY4sv9Vce/K1114jPz+fzz//nC1btnDzzTefsPdVmO7jzYJsznJZnR72dFtwlsvqUAmw8vLyw6937tzJueeey+JfPEE0UAaPvwT/9R48XHToiDb8wVa/Du/8BR5cDC9thuf+eujU1s+NGvifdSU8/PDDvPTSS1RVVfH555+TmpqqBe4iclqcET2+eJbfuvrdci4veogdG9fzu9/9jnHjxp3yvMJ0H1vH9mdq6V42Vzd0aJlDssviklQvy4b27VDpr6effpprr70Wv9/PQw89xOTJk2kM1mESkyA5xX5KxPO/bPsHBuvsIc6UNGgMwu8fb9NpIWPwNNTjdrvp06cP4XCY+fPnU1NT0+7vJCISCz2+xxfv8lu1TSE+vOYWSktL2xR6zbJ9Ht4emc2zgzPI87lJdlmcqgNoYQdens/Ns4MzWDUyu8P1LqdMmcL48ePJy8sjLy+PH//4x9z1/e/jDTfZlWTumgzD2zGr8sob7ELaN4+GW6+BC4a26bQ8v4drJlzNhAkTGDRoELm5uXi93qOGYkVEulKPr9yyNFDNrR/si+vi8WSXxbODMzpcfssYw7qqBhaVV1NSFWRHfQiPZZFg2UOBIT/YJ1AAAARJSURBVGPI83soTPMxMyeVUXF8qvkJq8zESXOVmee+3LcLWhMRaZseHXw9tfxWKGqoaAzTZAyJlkVmkhtPnGaDHqu4MsjVGwJdUmUm2WWxUo8oEpFupkcPdZ6O8lux4EmwyPZ5yPMnku3zdFnogV1lJiPRdeoDY+BkVWZERE6nHh18i8urYz6h5WTOlPJblmUxd1Bvkl3xDdv2VJkREelKPSL4+vfvz6OPPsqQIUNITk7mlltuoaKiguX//i3MpGFw77db1qXNux2mFcI3h8PdU49+Pt6COfCrufCTf4dJw+DOSbBnZ8v+94rhO1fZ5z7zE5gzDVb+FwAmGuW1XzxKbm4uGRkZTJ8+nerqnhmE07JSGJ7q7TZVZkREulKPCD6Al19+mT//+c9s27aN119/nasnTKBp2vfg+XfBROG1Q7UvO1BWC7AXZc+7HW6+C154165e8uH/tJz31ivsX/H/ePMvf2XHjh3U1tYya9asrvnyMWZZVreqMiMi0pV6TPDNnj2bzMxMsrKyGD16NIOHjyBx4IX22rLLvgo7ttoHdqCsFgCb1kC/gTBqvL3vuulHVyJ5+3U8X5tBclY/evXqxbx581i+fDnhcPwn1sRDc5UZf4yHPDtSZUZEpCv1mAXsmZmZh1/7fD7SMzJaUjvRLo/V0bJaAFTugz5HTLu3LOh9xHblPlyZ59J0aBJsbm4u4XCYiooKsrKyYvtlu0hzlZkJnSzzBvbwpi/BOq7Mm4hId9NjenzHcmE/WugoHSyrBUB6H9hf0bJtDBzYe8T+DCIVu0k8NHy3c+dO3G73UYHcEzVXmRmV5uvwhJdkl0Vhmv05Cj0R6e56bPAluxOOf5BsB8tqAXDJWPjsY1j/FkTC8KciqDqiiPLYawm9uoT63eXU1tZyzz33MHnyZNzuHtNpPqnTXWVGRKQr9djgc1kWA/zH/EPbwbJagP2w1TlPwuJH4cZLoXw7nD8YPIfa+Oo36D3+a/yfK8YyYMAAvF4vTz31VOy+0GlmWRbTslPZPm4AKwuymZGdwgXJHjwW+BMserks/AkWHgsuSPYwIzuFlQXZbB83gGnZqZrIIiI9Ro+u3BLX8lvRKHx7jP0E8iEjHVt+63RWmRERiYce2+MDmJGTGttZiZvXQm0NhJrgpWftp/Uc6jX6XRYzczpWq7MnO51VZkRE4qFH36BqLr8Vs1qdH5Xa6/7CTZBzPvz4aXvmJyq/JSJypujRQ53QM57OICIi3UePHuoEld8SEZH26fHBp/JbIiLSHj0++EDlt0REpO16/D2+I5VUBlV+S0REWnVGBR9AIBhiauleNlc3dGjCS7LL4pJUL8uG9lUlEhGRM9AZF3wAxhiKdtXwwLYDVDRFqI+YVhe5W9jDmpmJLuYO6s3UrBTd0xMROUOdkcEnIiJyMmfE5BYREZG2UvCJiIijKPhERMRRFHwiIuIoCj4REXGU/wVwfIYFAqNF+wAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "G.add_edge('apple', 'banana') \n", + "G.add_edges_from([('apple','mango'),('apple','kiwi')])\n", + "nx.draw(G,with_labels=True, node_size=800,node_color='#00b4d9')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "NodeView(('apple', 'banana', 'kiwi', 'mango', '_banana', '_kiwi', '_mango'))" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "G.nodes" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "EdgeView([('apple', 'banana'), ('apple', 'mango'), ('apple', 'kiwi')])" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "G.edges" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "pos_nodes = nx.spring_layout(G)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'apple': array([-0.01542878, 0.6402547 ]),\n", + " 'banana': array([-0.17742844, 0.54285075]),\n", + " 'kiwi': array([-0.04336795, 0.83813954]),\n", + " 'mango': array([0.17048395, 0.6008908 ]),\n", + " '_banana': array([-0.67610887, -1. ]),\n", + " '_kiwi': array([-0.03505517, -0.90875092]),\n", + " '_mango': array([ 0.77690526, -0.71338487])}" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pos_nodes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nx.draw_random(G, with_labels=True, node_size=800,node_color='#00b4d9')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 13-1-1-2 방향없는 그래프의 노드 꾸미기 " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 노드 개별 색상 및 개별 사이즈 처리" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "Gd = nx.Graph()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "l = [('A', 'B'), ('A', 'C'), ('D', 'B'), ('E', 'C'), ('E', 'F'),\n", + " ('B', 'H'), ('B', 'G'), ('B', 'F'), ('C', 'G')]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "Gd.add_edges_from(l)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "164" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(plt.colormaps())" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt.get_cmap('jet')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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vRf8eekG97wdMvTelhL1RSfjaRWK/1hXdnPEdbMy1H9wVRP0MND/s7qwdpYfxeGDmTFixAvx+HK56vrz+RL698yweH2rlw8lJbJiVQmZrNpEY7eKlxYV4ApFlfYK6ZNWuGqoazN3XDkRbM/aOzn3eXVlCwKQKrSoECzaUdbC13sH8b9Zx44NvU13nxuMLsG7zbs6+4q8s+nYVgzOdTByQxMA+WOrr0P9Sg97oGlUAMmho151AtcExtxt+zeFY42DOPR1sTA+2rp5rh6n72rvvgtsdadSUkklbVnHJt/9jdnqsuGhX4PKajw9FAbe/c2NHEeYCWdD+gJRG/EEd3SQsXA8dOxy5/9lPcXsjH4L1DV4eeOZDEqwCu7VvKh+H/q4yx2I69FQbZI3rdLMzboETH4XkgYa3W/+j4ILPjL8dIiEHLCZPYMUK/ad2un89SlGRoVW3xOUyjsXoEuYdkWO6oJUab6N/aue0OhFK0h8ulBsT93f02XriuH6mfs26Lpk9KqtT/etpiveZm0sVIaioaejm3nQfh15QJ/aHAbMMR+dGVDvkHAkpQzvdrBAw6TK4vhDu8MCl38GAmZ1pSDEWDVV7c8ihaoeEfjDkhE73r0eZPBmcJoIiIcE4FqNL+N0JBWQk2nGEtDiLInBaVR46d/xBzVgahbXDYmydEdIAU4akctqkXJw2FYHhN+2wKvzhlBFkJ3efL39XcuSYQabfhdWqkpuZ3P0d6ibEwboTmTF58mS5cuXK5h1SGkmKihcbZpC8oyFrfO9yDPVWG+lIPVWQMQpyJrYvVnzjRrjlFli8GDIy4Kab4PLLe/bedB2mT4e1a8HrNfbZ7TBqFKxcCWoXRo8FPLD5Ldiz3PjfZk2AMeca1X4PEUKIH6SU3f7EiRrXQL03wFvflbB0WwWDMuL51cyBDMyI7+6utYqUku93VvHpmn3YrQpnHNmfkblJ7Trv1Y++48F/f87+qnomjxnIX64/g/EjejbnwLqte5h90d/weP1Nlr04h40HbvgZl519TJde68eiau59byPrS+pIjbNy2ZwhXHLs4ENmNmxrXHePoO6r7NgBEydCQ0OzPTguDq69Fu6/v2f75nbDfffByy8bfTv/fLjzTkOr7iqkhMV3Q12JseYAgAKOZJhzf+QsqgvpTYK6r/LQ85/zwHOR9uB4p41v/vMHRg9tT1ayQ8e6rXu466kPWbGukP45qdx22YmcNqejXgRts3lvHWc+thSPv3l9zWlV+PUxg7j11FFdeq1GYoL6UHHppfDii6C1WCx12GHvXkhN65FudRuVm+H7R00ST9lh7PmQ37UaTiMxQX1o8foC5M25BZcnctFOCMG8mWN5//Ereqhn3cfVL/7Ap2v3RQUZ2a0KK++eR4Kj60NQ2hrXfXOJtLtYtixaSAMoEl77rZFooy9Tv8e8CILmg5rYouXhyu7SKtPpvZSSBSu285vnVuALmIz7PsTGkjrTSFCLIthT3TlvtYMhJqjbgUSymmL+zRL+yTcsZQcBNBgxwtwW7QvAA/Nh/CS4/75mO3FfIz7H3KFdtUFibvf3J0aHqfUGeHttGfd+uYMnFhexeb+LnIwkAkFzQSw1jTdfeIvxv3iQr5Zv7ubedh8FOQmmbpJBTdIvpfsXYmOCuh28zxo+YQN7qKGMehaxlRdZiv/2m5EtvSsEhu22pA52V8Pdd8PcuZg6tPY0vjojcrSzZIwCRxqI8MVJAYoN+k8/6O7FOLTUegPct2AX3+ysorTez+ZyN/9cXsya/V7OOWkKTnt0dJ8e8BP0uCkq3MPZv3+WVz7ofRUoAppOaY0HXysPm/ZwzbxhUT7ZTqvCz4/K65HcJjFBfQDKqWcjpYYGHSKIThn1PDS5mjffugV/TrLh+6SGohXCZbLXB+vWwaefdnvfW6W2EBbdAQtuhC+uhyX3NWf46whCgRm3QfbEkLAWkD4SZv4RrH0vOqyv8fmWSjwBLaKIgF+T/HfNPixHjGfI+JFG9I4QpjNHt9fPzX/7H8GDEIhdiZSSfy7YwcQ7vmDufYuYeMcXPPTxZvRO5KaeMDCFZ38zmSFZ8QgB8XaVi2cN5q5uTuXayGGb5rS9fFXh594dbgrdOkenWvlTQRzDE9rvnrabaswCdnQkINk9dRi1+RlkVNYjJGA2ZhsaqPrPUt6682Qqt0LqYJj7FxhxWmfvqm0kEh9B7FgQLfvur4dlD0ZGhdbsgKX3w9wHO56EypYIk39r2KqlNC+WEKPL0XVJaa2P8jpjwS8zyUa/FDtKB1zHNpW7TCu9SABFpX/BIDau2oTU9VZnhD5/kF17q8nPzQAOfUrWgKajSXCYlKP57/JiHvt8W4SnxgtfF+K0qlxzwrAOX+uYEZksuG02AU3Hoogejebt04L61T1eLl/XgDs0xnZ7fXxQ5uO7GSmMSmjfrSdgb3PacdY5fyV1TREi0LppQ7fH8f07uewL5cHZvx7eORdOfwHG/KKdN9MOJJIVFLKIbfgJYkPlGAqYxpBmgV282AibjzhRN0qrl6/vfLSoUMyeZzEOAVJKNu5twOVrLjBbUuWlxhVgdP+EdguUZIeFsnrznCSuugYWvPUJMth2KLym6SQlNfuNN6Zk7UjFmPbg8mu8+mMp60vrkUBukp0LJuWSH2YvfvKL7RFCGoyiu88u3Mlv5xV0WtBaO1thoQvp+R4cIjQpuX6jq0lIG/ugQYM7trhbP7EFBWRixVxLjNtXTf6SjVgOkNchGLCwJnBuxL6AG7642eTDO3fCxRfD0KEwezZ8/nm7+/ojxSxgC14C6Ei8BFnENlYS5oHh2h9ZGb0RqYWSU8Xo7dR6ghFCGgwB2eDTqPO0P8fIvGHp2FqEwDe6625bHdKk28Bhs/DTueNJTog2c5mlEvlw4VrmXPR3Rp96F9f+5Q1Kyqrb1U8pJY8vLmJ9aT2aNO61pNbHI98WUettHsvlrRTWdfmC+E2SUx1O9FlBvc+n4zKZ10lgSXU7Ujz6/bB4Mep3K7hQn0o68Vg1DVswgAgN5oTyWnRrK5q5EOB0wOBBvCwW4CW6oG1tEejhCsCOHTBpEvznP4bA/vpr+NnP4PnnDa03vNKuCd+wLcKWDhBA4xu2Ne9IG2YeiCIEpAxute0YvYcGr2aaDlWXUO89sL24tLyWRd9vIV7zcfqYLCyKIBjU0XXZlEPS3eBGb0W4WSwqNquFk2cdweN3nm/6mZbde+SlL7nojhdZvmYnu0oqeOG9pUz75QOUltfiC2i4W6nWAlBY7aW8wR9lptF0yZJdNU3vR/QzT9ubm+rEbjm8TXJ91vSRYlFoTaT1O1B6z/nz4bzzDJurlGQkJHD1B+9T6foAv9CpjE/go/FTSNq9H4vH5CmuKjBnGJw7CXISabhiHJREfsRBFblTV7B0fxxqTi6jRS7Jd90F9fWR9kC3G774B+T+YPgnWxww/HQYdHzU3LIeczdAF34k0jB/9JsC2z4Ad2VzNKFig7ThMUF9mGC1iFYT5tvaKNmjaTpX3/0a//10JXabBX8gyNypIznv/JN4+NMd1Lr9jBuRRbxdIeAPhDyYItsQikLGEROxJ6eRMS7f1DNk4469rN1TS3xKEoOzEihIsXPPMx/jCdN+g0GdBp/Gz//+NfsDFqSE0blJ/PXccYxqEeJe7vJj1pmgLikN06LvOH0UF/3ze7xhZkiHVeGPZ4xu9Ts5XOizgjreIjivn53XS314w+SeQ4FEi+DopTUcm2bl+sFOssMFd3ExnH22ISAbqa9Hn3c8/9v2NPvSk7BpQU6++2VG/+0j1NAcTxIy0VoUiLfBr8dDqh10P7PPfpX5/7yIgNv4ER3DvWh/2cWK60+hyOJF+CtZaNvCyRleJrScbp48Es4a1VzOJuCCzW8bWvGAWREfTSOeSlxR30Uqcc02atUKM/4I296HvSuMfCYDZsHQkzrxLcfoCdITbBRVeKKEqAT21/mpqA+QlWQjPcEaYZf924tf8NbnP+DzB/GFzHVffbcFFxbGzZyOqgrq6j188K+3cdfVmQhpFUdmDiRn4gM+WVPK1fOGN+U2qapp4Nyb/8WAGVNxxsdhqall0a5q4qwqScmJeLyRme8Sxk5mr0dgrMLDupJafvHEMhbdMZv0hOZZX16yPbR4H4lNFQxOaza7TB2azqtXT+Nv87ewpbSegRnx3HDScGYMz+joV9zr6LOCGuAfYxPwS3h7nw+bgIA07NRLq4PowKq6IP8q9rJqZgr5ztDU6OWXwWQBJagFSFuwhn3nzAJPgNEPf4Q1LMTWqDImYHgm3DYbUpoH0IR5ywmmH83CR0eQX/0hQye+xWvX/YlgXLgJQjL/gfMZ9srnxFfUNe/+5XgjhRogdcHm5ZNYt2gail1h0h0w+LhmxXoeo3ibVQTD5hIWFI5nZOTN2OJhzHnGFuOww6IIxvRPZOs+F/6gjpTGGJA0mz7qvUGqXFaG5zQv9P3jja8jtFowwsUXL13H4FnTEUJQtrMIb0ODqdkjYchw4voPbHof0CTnPbmExX8+HiEULr3zRRwDBhKfnIjamPhLqLiDkgnHz+CzVz9sOteanIpqdzZ5GaXG2zhn2gAmDUplx343afH2pnGdm+RgeEYcW8vdBELTCAWwWxSmD4xM/jVpUCqvXj2tU99rb6bP2qgBHKrglQmJlB6XxtLpyaRYBAHZ7Obs06EmoHPXtjDtef9+wz7dAhHUyFm1g6x1heSs2oFmM3nGSWmsoqS0WFyROpPPLeSm/fCLmY+y5ZzJBBzRU0YhVLad1SJXayivsZTw5gNX8+4jl7Jp2WQ2LJrAG2fAFzc1f3Q42fyCyeSQhE2qZLtUzv5kP6MWbOydATcxOk28XWXCgETGD0ikILt5jDSiS6h2BWgIK25Q32BuGtM1nbKiUjwNbkq2FREMRCsqQrWg2OxRnhP13iD+gEZdXT1LVm1nwMghzUK66WRB7uB87GG/GYszvslLqH+qk4//cCxXzC3gmJFZjO6fjE+LNO1cNjWP44alkWRXcVgUMtUgQ3yVlO1v34Lk4U6f1qgbSbUq1Acltb5giyg6CCL4tMwLhBYifvITY/GuITJiz+rxc9STH3HUUx/jTk1A9bWyIBmaBq6lH8+IaZQTz+ls4RfpY7EJENUVCDnI9FShqnDWz+G1UK3GQABqvJDioHDtKHb8OJaAt9EdSSHgghX/gCOvhPSQm2gBmRR4Eoz7WLUq5NusQP/+8M03kHV4JoyPEY0QAodVpazGR1CXUT7UgaBOrSfYlEBo5qShfLFsU1QOCyklX745Hy2okZCSiBAiqpq6RRVY7TZURXDUkHSmDEmjwRdke1k9yXFWdlbWYGnDjU1RBHOmjmDhd1uwWlRU3YtQjM/fcuooEh2WpvMb/wY0sIcklFVVOHV0FllBF6f99imklGi65GZN57fnzuYv15/R6e/xcKBbNOr1b8DjQ+EeKzwxDDa81R1XjSRJauit+ISmV5U3vznxRKMobHzzlLHR/mxz+7C5vCSXVKAENbSWTvdxcfCbs3lJmcp0cQ3/ZBpvi/FcKc7kmPXx+DQJp53GmHeXY/VGC3pdEQyfd76h1S9fDoU7mrTzbSvHEfCaV1be0dKD709/MuolulyGrb2hwfAoueyyA31NMTqAlIYw8QaNza+1XZz2ULGtqAy/iYuoPxCksqq+6f1fbzyLxDgH1pAHRLhcD/j86JpGQ019lD+8EILMlHj65fXjztPHctmcAqYNy2TO6GyuPG44+2p9DMxNJz7OTuHG7WgtIxWlZHR2PO8+fhVbP7mHb16+iftv/xVKSFAfPTzTVMhLImcJwaDGWdc9Q12Dl3qXD7fHj88f5Jk3v2HB8k0d+9IOMw65oF73GnzwG6jeacRZVG2H9y/qfmGdsnMrP1nzLTZ/pJdGvNfF7z96rnmHosAnn8Djjxt+zEOHgiVy4iGAoN2Gd3CeUUklKcnI8/zII7h+9QBXK2fiFjb0kP3NJS2srw/y0h4v/P73JOxuYNJjH2Fx+1B8AVSPHwKSkxlLHDZwOGD0aEhPbbLh2ePdqJZo1yvFYqR/juCllyITQSnCsLt/8gn4zH1NY3QMKQ3BrLUwN/g1TLOuHUq+/GZ1lAYMgJSsWL216XryOPUAACAASURBVO3IITmseOt2rjxnFlPHDcZm4lqqaxoCQWKCg8R4B3FOG8MHZfH5c9fx9nUzKMhJbCrvpYYEbWGFB4ngyTvPZe03K6ivqcPv86PrOgGfn3ibynkTjRzWWWmJjBraDyEUrKF6Yy2DVFpjyY878Jtk7XN7/Lzwv6XtauNw5ZAL6gW3G+6/4QTcsOC2Q33lFqSl8dJj1zF9y0qcXjfJDbU4/F6u/PhFLipskWPYaoVLLoGFC2HuXISJJm6Rgrib7zSqqHz+uaEFX345y2qDWJTor9Wtw5ulfioSUhj22EK+2pbPhF++QMqLq1n7nYN/LJlEyf7sFhdxGkUhEYybvQyhmEuAEae32NFoYz8qH547C977Nbx6Lpw+ynShNEbHkUT7CjfS3XVjkxMd/N/Dr1NX78bl9uJye6mpdXHX314jNSmyAvSAfmk8eNNZLHrpxlZzYEipU/TFfcz/5+9Y8srN/PjOnQwdkInbp6OaVNgVQJ03yOQJw/n7Hy/EtXETRSvWQGUF0/JS+NnIbJJa5G8+fmx2k737v8uLTIW10iLFSKOnCkIhsWAU2cecQPaxJ5J+5NGUe/t2WOwhtVFLCbW7zY/V7DqUVzYhN5eU8WNY9Mez2ZaZT0lGP44o3ESG5oNXXmn9vBNOgNdfj7JZqxKYdSwUFBhbiARVIKWJAyqQbBF8WRHAk5DEg2dfy4ONB0IPsrf2+fhpdgvzxoRLYclfSO1fxxnXP8f7j12Kokqw2EEIfvk+2Fv6+Z92GmxcCH84tsljhCQ7nDsB9nxp+GHHOCjaMnF0t/XjglOn8dDzn3PmpQ8wqqA/Eti8vYTkBCcnzxrb6nlHjRvEklU7ovaPHdYfp8PG5DEDI/abCWkwBLUqoKIhwJCB/bjlt2dFnifA5dNIDBPWeWlx3HDycB75ZCvPLdzO8JxEjhmZhQDsVqPGY8uC4jMmDUXTdFJGj8eelmms6QDWxGQK1WR2lbsYnNl7yqB1JYdUoxYCkvqbH7PGwaOD4dnJhg27W6aLb74JU6YwrLqUOYXryPC74bbb4Iw2FiLOOMMwQ8SFaSbx8XD++bhSh7Ps7/Dp9bDxbdACcFSKhWRr9ICOV+GqgQ6cqjGwHZYgIuwnrQCmuaIS+sFxD8HocxlzYQY3rV/Lma9bOfstwR/2w6BjTc558EH49ZRmId2ITYEdn0bn+ojRYVqRWYAhxLvTZp2fk8rrD11KUryd3XvKKSrZT7/MZD559locJgEpjTz8h58T77SjhuzDqqIQ57DxyK2/QA/Z3wNh95CdbDe9b0URJDktqEIQ1CWBFq59EkyTRV0+Zygf3jiTK+cWsLW0jv21bhLsKjbVWERseUq80859N5+DPb1ZSDeiSfj3op0H/rIOUw6518fse+CT35qbP/yFRsbNDy6F/Rtg7j2HuDMZGbBkCcHtW9gU3EPJ4BTS7amMI4CDVga0xWKEcj/7rKF5O51w5ZXsGfJLXh5qpM0IemHVvyFtKFyyWPD2xEROWVmLPzReAxL+MMTJcRlWFunbuWbuDlRVxx9U+GprHit25+BQ4OK8VhKSW5wwcDYA9X6dd4WXFbVBJhRZuHyAg6yWkZY5OTA8F4LRwS9IzUjAFGXYjtERBKaBexE02qxtatuCvSv4ycwx7F7wAN+sLaLIrZOYFI81JRFdRnuDNDJhZD7LX7+Fh1/8gh837mbssP7cePE8hg3qR7glQtMMrTjJaSEn2c7eGh+NKUKEEIzKjafOp/H5zgp2VBpZGdOcVqbnJZPisGJVFeJs5jphQXYi159oTAkbvEEKK9xouiQ9wUpavDXKHXDsmKEkLK/G1cJUoumwaW8dfZVDLqgnXgRIWHgn1O8FawJo3kilLuCCZQ/D9BvAGZ0So91IJHuowYWPXFJIJFrwufHz74K9uPDjpxQr+1nEVi7iaLIwzxWAw2EUrL32WuM6Et4pMDKGNt1DA5TtkJz+TgOLso2BLCWMiFco9uo8tNNDsaOQwXm7sVsNCW6xafxkZDFSVzknfiCTU9pOSL7DpTF1aQ1uTeLR4eP9fv62y8PSo5OjswEm9YeqrdGNKBYj4CXGQSGEIYAD+oG15qBufPZg8AZ1tle4sCgKwzLiTM0QmyvcfLjHjy4lWkUNy4pqGZIex1XT81s1WxQMzOKZPzfn62h8uLSkwadRVO7CG9QRwtCirQp4ApINexr4YEs5tb5g04Or0hPgsx2VnD06m5G58QfMXLe3xktxpbfpu6x2BUh0WBjV4tyhWQlNQS/hWFXBuPyUqP19hXaZPoQQJwohtgghtgshbu3oRSZeDDfsgT9pkDXafOat2mH/uo623EwdHv7B17zCd7zHGh5nIV+wCdlC51nIFmrx4A8lLwqg4SXI+6xp97VqCqG+NHr/+5c0sCDZCFl3acYC4o/1OhUBcGmSjOxiNBE5LbRadM4btpGb9j4Ie5a3aQO6dmMD1QFDSAN4dagNSq5ab1KlZcRZRg6PcFQbFJxqCOsYB02jsLarhlWpNQ7W/PF9cS23zt/KCyv28tx3Jdw6fys7KyOnqAFN58WVewlokkbLg0+T7Kh0s7Kk/ZqmWR4mTZds29eAJ6A3pr8hoEncAePXVVLro94fnSgqoOk89PkWbn59DdvL6qMbDvvc7jAhDY0JpoJUuSLdWHNSHJw8vh+OFgZsm0XhN7P7bq6aAwpqIYQKPAWcBIwGzhVCdCrLiVBCeX9MHq6aHxJzpVFpxFsT/YED8NeaDby2KZ2PNuVSWGtDQ2clRWwkUqJuYp9p3oAy6vDSjqx6GOkyWjbhc0jWzfERMHd1RhUSp9XcDcltsxqp9Na+CFv+1+p1F1QGohJNSeDbqiB6SwGfPhyOug6S8o0gH0cajD4Xhp7Y1q3F6AStFEBpPg74ghqF5S5cbWSJM2NfvY8lO6uZkJ3IwGQHupS4AzpPLS3GH+ZesqvKvOCqX5N8v7vjv6dwql1+c/e/EPX+oPlxIQgi+GRNKaf/fQlbS82FdZ0naCqIdAmVDdG/yQfPHcflc4aQGm/FqgqmF6Tz9rVHk5cWZ9JK36A9qtVRwHYp5U4AIcQbwOnAxs5ccPqNsPXDSJu1YoPciV7i9t7LkmASOzKySK6Bo5Jm0S9uyAHbvH5zDf8ozCeoG//u74uymTG0lDnD9vAdhYyhudCq0kZ2ewUBDaVQuRlsSUYSfTXaHJGUZ1ScKltDk8D2JOqNuWVM0aRCrddGijM6PD2jITSANR9s+QhufAZGT4Df/Q4GDGj6nF0R+EzUM1trOfszRsOsu1vvVIwuQwhMM9qBZMGGfdz13kbycpKw21Tykuz88ZThJJmkEQgnoOlsK3VzZE4SVlUhqOmMz07k852VeIIa68samNTfyDSnCNGqvdwSOvfbLRXsrfYwYWAKY/LM1yhUxbBJR/ZDtjkrSHNaQ0m/WmS3C+rU1huassevce5Dn5PnL+PnJ0zinJMmN/lxt1WVxsxkY1UVfn/SCH5/0ojWO9XHaI/poz9QHPa+JLQvAiHE5UKIlUKIleXl5S0PNzc2Bc54CeIywBpvmDyGzAly+s1/5pkp4/m6YASFGZmsycrgBft6NmjFrbYFsK4uyD8LgwR0FYlAIgjoKot35FLpskdpyePJw9LitgUwUKZhW/MSfPNn2PgGrP4XfHkD1Jlf/+w3IT7LqERlcUCaV8Em27bDfbZpAP5g5LUtWpDjN61t3uH1w+71RsDN2LGwenXToQv723G0+I/ZFTg3NzoHQ4yuob3jGgx3spZyZX1xDQ/M38rEMTlkZ8STluKkAcEdn2yn/gDadXGlF1U0VxixqEaQyNF5KUhpVC9pZEi6symAJBybKhiR7mTWvQv53curuPf9jZz9+DIueW5FlHcGGP1vmSk1zqa2uRia7rSSFmclvAaBrkv8QY295caCtgTKfYLPl2zk+gfe5MTLHycQ6n9ynImLR6gv2UmtTFH/P6M9gtrsXxStN0j5rJRyspRycmZmZpsNjv453LgPrlwNN5TA+U8vYtWYHOptDoKNUYCKIKiq/E+uR2s1szR8sN+PWRUsKWFrWRqjyInYP4th9CMZKyoWFGxYSMLJ6fs0I+2nHjDsMJrXWCFc8bip3Th9GPx+t/HQmfcQ/OYrwRNT4ohrY9Fo4750PlxbQJIej03Tya2u5NzvlzC0Yn/TZ4I2K9U+ixG0Ul8PV13VdOyBkfEcnWolToVEVRCvwuRkC4+N7mOLg42G0F5AR8Z1hM069Pem11YzYmg6FlVBCUk7RTG03/mb2hb8Va5A1ANYCEGy3YJFEYwM8xlWhODK6fk4LAp2iyHQrYpg6oBknpy/hbJaLy6fhjeg4wloLNtWwfOLzIMZLKG+WxRjy0ywEGdTWzXvCCE4bnAa47ITibMqBAIae8rqWfrjnoigGrsiURSB2+Nn7ZYS3l3wY1PfR+XGoyoCVTQHuuSnO5rylPQV2jIhtUV7BHUJkB/2Pg/Y26mrhV9YhbQCQ7PGU8nm7H5Ik3h/L7DCXdtqO7ZQ8e+WCCGJVyxMJ9J0YkXlIqZzPkdxPKM4kwn8jjkk7frGMD20xF8P9SXR+zHW5kb9DI66BnInw8X5Tt6emMSMVAt5DoWfZdv4WbYVuwIqMDJJZ9aQMjyKl6z6Oi5a9i2DK5t/rD6p8J06kNy/LuUfJ19s7Pzuu6bMd3GqYMHUZBZPSeHh4kSe/jiNv61MwVLXR5IgbtgAs2YZLpHx8XDFFUa+ksMMESZs3EHdtOaeBFbvbX2BDVovQSkEzBycSnp8pLY5OM3JfScN47wJOfzsiCxunTuY44emsaGkLsp04Q3ovLG8lWi00DUaBbWiCEb3T6B/qh176EGQnWQlLhQvIIAGf5BNFS5j4bGwis27KvGHaVA2i8Ilx4/itaduJDcnDZfHz4eLmmeSiQ4LkwcnMSwnnpH9EpgwMJnsJEdveV4fFFJK/vX2YgbPu524Sb9j+Ml/5K1PVx74xDDa87haAQwTQgwG9gC/BLo2kXFqAZ5AoekhRUje36szrcD0MGfn2PnTVneUjq+g8HDOSFP/aIFgAGkMIK15Z2tBIEKY1xhshZOybJyUFfkD0qSkUK/hTXUlATQCQElKCu9OmMJP1/2IHtBR0VgoCjhfOQ+vxclNv7mLmRu/Y1zZrohpob8Bvj/OQtV24/Vup+H6eOFC6Dep3d1sE12DnV8YeVmyjoCBs6JnploAvr4bVj5tuFcOPBZOfBQyRpq3eUBKS+Hoo6Eu5KHg8Ri5wbdvhwULDup+epKCzPgmDbolVkXBG9BwWM2nYZlJNvbW+CKElZQSm0Xh9GHmWRDtFoXJ+c3259IaT6uasL8Dse6qIshPc5KfFpnCV9clr68uZUVxXZPb3IihGehSUlruarIx//yoAcwek4uu69x78wVcetMTpCe3nAmKiIoxAT2UDK0LC+VK2ZyfRW1lEbgx2Kfxa1dDD63O9uG5txZz2yPv4vYa61PFpdVc8X+vYrVaOOO4Ce1q44CCWkoZFEJcA3yGoRg+L6Xc0Lkut0L2BJwbdlGbpGCzNA8eTYfSunisrWSNAxgUp/LE6Hh+t9HVpFlrEp47IpFBjubzJJJ91BFAI5dkLC0L1vafZmjOWovFPqFCUmQobUdRhWC1uiuqnuGm3P68x1g2rE2lRIujUjQPXL/Vxos/OZ+/q3siRsiSB6FisxFkAxD0GNs758JvNx/8gHbth+dnQsM+4/mkWCBjFPx6QWSo+rsXwJYPjWuDkcHvX1Ph6o2tR6O2ydNPRyeM8nqNLILr1xv2+sOQW386ktfX7afer0UIa1UIRmfEm7rDNZKX6qDeE6TB1zxurBaVMXkJEZ/zBjSKa30k2lRykiLrYeYkO8hNdbKrPHJmYrMITpmYy8ES1CXfF9cRDFPZVUUwdngW181LAR0yEu1NswpFUcjOTGHIgGwuOXNG0zmNSa5aIjHkQFeUPAzqkXlYghBaAwi7nkk/NGmUKu2ML7yUknue+bhJSDfi8Qa466kPu05Qhy42H5jf4V62F0XltMEncXnRZqYMKkPTFRQhqXI7+Gj1MF4aa1KMNYxLBzg5NdvOx/v9CODUbBsZYY6t5dTzGitw40cJBW6fxjhG06+5kQGzYc93IWHtMySUUGDiFYad5iCpwdx9KiitbBOZuFtqrKqFuqHD4ZrfR+xf91qzkA6ntthY90weEH2sI3x4meEnHj6JKFsLX90OJz1hvK8phC0ftOiHNN5/9zjM+2snLvzjj+aZ/SwW2Lz5sBXU4wakUO/TmL+tinq/hiKMGdaI9DiGpDpbjdiDZpNDg0/D5dOwWxRS4iwRduuvtlfywcZyVCHQpCQ7wcbVR+eTHPIoEULwyAUTOP8fywnqEl9AJ86mkpPi4Jp5rUxTO4A7oLVqonHaLKSYeLZIKbnjilMYNyKveV8b19DkwUfmNdb0MGtblc2LwK1NMnRpbB2NMPX5g1TVmpvvCvdUtrudXmOpH5AQz/TSUTzxdS5piS7qvVYa3HEcl2FjXkbbbkwSidteRUF+NQnYSaQfjeZ3HZ2XWY6LyCfae6wmm0TSCWknqhWOvg3KVkP5BiPEOn8mONO75P4Gkc4evY4Ktw2nNUi83TC1DE6vjaquDBAvJGdeeBo4I2cTrcaqSBCq5JU9Ph7Z5aE6IDk1y8YdBXFRIeZVO4ykWJljIDHsWaUHYdv8aCuQ5oO1rzQL6vJNhrdOyweG5jfWYzvFkUfCF19EC+tAAMaM6WSjvYOpQ9OIs1nZV+/DFdBId1qJs6oMyzlwxJ43qLNuXwO13iCD05ykxDUPgE37G/hwYzkBTRIIibq9dT6eWVbCLXOagz/GD0hh0R1zeOf7EnZXupkyNI2Txud0SWXuJIcFu0WBoI7TotAQMAJfBODRNFKFNcrOnBhnZ+5P2qdJNhLQdPZUealyBVEV6JfiIDMxMsRcymaBL4icXZr9xpqO6c26WJvJthoT03cAu81CRkoC+6ui1yOG5LW/lmOvEdQAfx4Wx/HpVp4vScBtkfxyuJ1Ts2xt+llq6LzK9+ylBj8aVlS+YBO/Yhq5JLOTCqLDREBHsopi5jGqeaeiQr8jja2L2bs3j79uSCGoCzQpGJxex7kTdvETRz6pw+K4e5sbr26UCYtX4bh0GydmRj+gJl4Ci+5qNjkAIAy/7rvrXDyz24srNHV7ereXt/f5WT8rhVSrgr8B/nsm7F5sLIQGvTD+1/DTZ4zJg9Rbd7bQw6aD6cOiLUQAihWyx3XyC7rqKnjsMcPbpbETDoexuDhqVNvn9nIsimBcfiK59XZq3EHsFkF2sh3nAebSxTVeHvu2CE1K/JrErgryU5xcMyMfq6rw1fYq/C0kkC6htN7H/gY/WQnND/mMRDtXHDe0629OwhmjstCCsinoak1ZPbtqPEwdmEJ5nR9fQG8SgIqAApMHVFvyTyJZW1xPINgcZ7yr3I3LZ2NwphHkYhb6blUMv/CIzh5A0hozHvNjnTErCiG467c/5aaH3okwfzgdVu65tv1ZLHuVoAaYkWZlRlrbGnQ4KyliD9VNwrjRDvw2P/A75uAhgNnESkfSgHkNua7mu5oAV6714tabv+5dFUl88sN4/m9aJnOGCuakW3m+2Is3GOQ2uYDhFd8iPvND5lgYdU7IPQamXQ87v4TipYZ5QrWD1QmzX9P5fZE3ouJ6QEJ1QOfpIi8/z7Hz1SWCim8Emk80Cfp1rxoLgNNvAI/Ni32mH++3CaA3j3DFAiNOa243rcBYPCxaFKlVW+ww9bpOfknZ2YY9+tprjTzgTqeRE/y++zrZYO9CVQzhnJ3cthmvESkl//6+BE/YXNynSYpqPHy9s5rjh6VT7zOPdFWFiEpadKjYWe5GSOP+1JAQnNQviZNHZdI/xUG/JDsVDQFq3AH21Xp4YdFOVuyqItFh5cJjBnHZnCGoimhybWzZbUVAea2PoBaZDEKXUFbnp1+KnYAmsahqlPAP6M3eN1vLGxiQEofFxEUsXJhbTAJ+wBDvnU2sdfGZM7BaVe55ej57ymoYkp/BvdedzinHHtHuNnqdoO4oP1JsqjG78FOJiwGkmZeaR2UYWYb2tngxvPee8dfthpNOgj/8AQ7gNxtBQylUbjEiYLLGGdJt40ZQVR529WvKz9GIJhU21MAut86QOJWjUqwclWI1/LbL1zcbiUt/MNqdfR/YElBtcMFnULLcMKkn5cHwU+HLuiD2YoG3xdzNo8MDO9zcv9HN9e+lYwm0GMxuw6487QbJiyzH9y8J02aAVwGXBRKCxKeqnPBw5HnnvAOf3QBrXoKgz5iE/PRpSD2YdAsjRsBnnx1EA32HCleAGm+0J1JAkywvquH4YemMzY6ntM4XsZAHoEtJ/yQ79S4vHyxcy6ffrGfDzr0kJzi54pxZnHPi5HYHSDVGNJbWeBg/wIhorHd52b67nH5ZyVQ06FGzMEUIXKFq6IoiyEqyEdQ0rnnxBxp8QaQ08lM//tlWCstdPPDLcaHzDP9tXTamRjW2Wm/Q1CQhgDW760mLt5Gb5jR109Uk7Knx8Nx3JUwdkMLJo7JQhfFg0HSJw6JECOCmZFthXh+KiM6N3VEuOHUaF5za+eroh72gPtBwS8bJZAbyA7ubtG0rCukkMKrCCnPHw5YtkZXHt2wxUpquXWukRm0LKWHtC0ZCJSEABTaXw8NLodZwNXskOYNtt77AmqHGE9TmAaTAlgR7vYagBgxhHy6kjQsYauvub6DgZOOeBeRPN7ZG+tsVgq3YLRo0sHtFqyHuvloopNKYYRRosHMhvJoLmxJQjqxn0i/iSHBGLjxZ4wyTySn/MMwiJpH2MQ4xcwvSWb67lnqf1iSsbargzCOyWbBsIxfc/DxeXyAiD8zarXtY+uMOHr/9lwdsv6TKzTlPLKPWE0ALSc+4qt3s3LAZm0XFFwgyY8oobr76TGw2YwCoighFJUZqJs9/vQtvQIsQ6p6Azrs/7OHGk4eTmWRkuhQiOi7CYVEwi6RoFN4ipJGbISV8vrUSvyb5dlc1W8tdTOyfhKoobCqr59Kp/UluMXgVYeTDbuxrbwj6PewF9QTy+YrNUVp1PDbSMdzd5jGKgaSxkiL8aIyhH5MYgHr52YZHQaCFn3QgAFVV8OijcO+9bXdg7/fG1ihc67xwx/vgadaGcl0uFt72M8Y+vI4Tnsohf5PxtZcOD5L3jkqTO3ddsWEnb+m3rQegenub3TgiycLIeJU19RrBFgJZAt54SU2WTvreSLuoUGDQXKjF07wQkxSEq3Y3nVsbnTEg4vw2ik/H6CQZ8VZSHBbKW2SPs6qCaQONdJ5xNpXb5w7h651VrN/XQLLDypyCNNKtkoLz/o3HpICy2+PnP+8v54YLj2dQ/7aVkGtf/pGyWh9aSGK59u6maPtmpK7h9RltL/5+E07nx9xzw9nkpTlRFYGU0OANIGWzkFtVWE3AxPhrtyhsK2toEtRm5KTYKa/3t7rQ1+AJIFMcplqbImB/Q7MSVtbg59MtFYDxAKjxBJs8ZFrSGwR0I4f9T2wyA8kjFSsq9mCAI3cXMXfLJi7Y70SEBphAMIIczmcqF3M0RzEYiy8IH30ULaQb8fmMYrAHomhhZETjt7uilo4VwBIM8tCNCxmwwYKqCVRNkLfJwhtHK80JquKzzFfzFAskHtg5+ZMpyRyTakRCxquQahE4G//DAj78XQN+u0QP1V5UbWBPgnkPQg7JmNnyrajkcRBJwmN0CiEEl07Nw2lVsKkCl9tPYUkNFeUNDA7LfxFnUzlpZCZ/mD2Yy6flMSwjjg8Xrm1zAd5iUVm2uu1qKJUNPjaU1DUJaQB38S6kHmnA9QeCfPHNanISjQIBihCoiiDJaSW8Du2wnETTBEv+oM6A9Laz3sXZVIbnxGNVRZPN2RLWliegU+PyG1p/GI2mkyFpTlP7sqbLiAXX3sxhr1GrKFzAVPbWbSBr2VMouoaiBRDqdkj4Ao6+xVhxa4nWjnLReXltHtaDILRA5IO8ygMmizxOn590UYYSkbhJ4KuBb+8PVbdJHmQI5LrdkT5ywgID57bdVyDTrvDVtGTKfDq1AUmuQ9BvQVXT8cJxAZ59tIYZ7zsYv9/G0cerTLsOEnMBkhhIOoVUEgzNThQETqwc0YZGHePQkZfs4N6fFPCndzcYeTNC1VpO2VzOLaeO5OJZ5gsCbm+00ApHCMhOT2r1uJQQCMoojVIPmLj6hE7weP04wwLMhBDoGNkPFAUunzOED1ftxRMm6O0WhRnDM9qVnjQ13sqRg5LwBowCu3WeIDv2u5t0ot2VHuo8QdITbCQ5LRFC/YTh6awsqcMXbF6tsqmC2UPTcLYSFdrbOOw1ajA05v4/voE14EVtFJyazwhe2d6KVhwXBxPa8OWMi4MbbzQ9tOldeGww3GODB0+9lSXvnoKuCbZ8P553Nz/MR+rT7GFyxDk6NorlMabtrXs17M3UGyF7khERKRRIGmA8bDpQ+ibbrjA8QSXBovC3UfERiaLqB2msvMnDtcsE8/7aKKQNzmEyMykgCQfx2JhAPpcxE9vh/zw/bCmudPPhyj1NBQECmsQX1Pnrh5vZU20eRHXizNb9zoWA5AQnx04ZHnVMhkKnfRqkJNh567qZHJGfTEqclUuOHcLz91/Kdb8+nrQWod+ZaUmkRoWDGzQK0qHZCbxwxRSGZhnJl2wWhdOP7M+TF7Y/74EQAqdNxWZRSEuw4myRKKrOE8DlC+CwCtSwkO/0eBs3zx7EuNxE4m0qWQk2zh6XzWmjO+As0MOIzmZzaovJkyfLlSs7lnTkoPBWw1e3mOfkiMuEuQ9G7wdjsfCYY4yFRG/Iz0xg+O8+8ghccWXUKds/g//+LNKP2WL3k5xZSV1FKgGvA4GGBS/HchczeBg/cexiLm/wAWaGNKHCL94xXOCaBp4eNOobms0GOsg3VQH+vsvDXq/OSZlW7mnWiQAAIABJREFUrhvkJK2tkiS9HCHED1LKyQf+ZNfS7eMaeOLzbTz22daoUHO7RWlTq77n6Y959OUFeHyBpoxtiiIYmJvBR/+4miH50ULKrBivxxckoEusqoLTpuL2+vH5A5xwyd/YsXs/DruV5++7hBOPad3VrGXNSLcviM2iYDnIxQ1dl5TV+aioD6Aogpxkm2mdxcOFtsZ1H1GVBG0HobbCuHGwbRs8/zysWATOchifByOywLbWKCCQHpllaOEfWwSbAEGf7f+xd97hVVRpA/+dmdvSCyEJEHrvIEgRBBQQBAuI7oKKigV7L7v76bquFXtZe0PFXkBQsYEgUpTeO4SW3iDt9jnfH3Mhubk3IQnpzO957pPkzMyZdybnvnPmPW8h50gix5WwRMVNGEt4jAQ2sZNLWM915YohvTD3Chh0O4x5yteomKipf8+IWDMjquCbbtBwKMlPJwM2VKSO/n3zRMYN78lHC/5kydZ0jgobYc3iICScB+btYfbMaCJKLaIdD5Eui82iYoMTyi/UZsFqNvH6w1fy4oe/cs+McfTs2BIpZbkKsmyB31BrzYxrRRG0iLbRIrr8hcimQuOdVpXGFg3hLQLbFTMkDa/42Ph4uO0auK4NTO0D3WNB8ejaePXLAXHSueU6XwQOUkWFz5nPeq7nPO5jEC8jCG7ncxfBXy8Fr8UIelHeNRxgOXtJDeqsZNAUOb9fi6BBGkgY1ycxsL0Ug3q3o03ffmhJXbEktMZtCsHu9rLl8FEe+cY/r1p5L9ZCiAAFrKoKA3q1553Hr6FDUhxnTXuS7LxCv9zTZXFXEH9zMM/Oz7uyWbY/j8Iqlio7XWgaihqg/016iXPVCgj9Z1Q76Hh+hYd53ZC9ZCVaeWnMMjb6/dm8CtHMItTGmKegU58UMuiDlXwG8z+UcpS1atEjDsuylyxe5jd+ZQdL2MWHrGI+mwIK9xo0PTrGh3PP+V2wmhQsvlzQVpPCw5N70CI6pMJjpYTPVh3CUcan2eWRfL8hzW/BsapRd4oCmtfDuu0Hue+68bz04S8sWb2j3MT4wVo1KZm9JoWX/jjI99uzmLc1g3//vJedmY0vB3lt00RMH+irYmOe0yP5HHl6Fd1m3St0hjx6QE/pOWKSnWbneQMnxVILsHOc+yR8MgE8pWo+mmx60EcwE/nWb0Mo2GlhOGvpzly8WCggke38HVnm9sv8AsKumQoLE2HWLGjeHA9evma9X4pUN162k0Y3EulKQmXvkEEjZeY5HRnXO5Fft2agCsF5fRJpFVOxkvZ4wSP1AgFBt2saXk2ecJkrv+ZjcBQEEeFhmEwqHy9Yxa79aSxbs5uh73ci1Bbo8paZk8/4657nvhljmXHJMIQQbEotYHNawYl8Jcd/vrv6CLMmdPFzwTvdaTozatBn0UlnQaeJemHXkywqfHO5Hgy4fXk/XM5gi3YSmvsvkrQbCdMWQEI/fQYc1QYmvArnvaArbEuEXhfXGglnXA+5m+1c4xpGf94jnEyiOMJQXkTFP0ucwEsIObQp/BHmzIHBg8Hh4CC5QW2RbrxsInjlGYOmR9u4MK4f1YEZI9ufVElrkhNBT2d1jgs6W+7dOgqLyf/rby5TLUn42soeLtCTh/2+ehdX3PsWf27cR15+MVv3pDDn25UBuZeL7E7e/GwJySk53P/cXJ54S/fE+vPgsYCkUqC/CezPKQ5oP51pOjPqKlKco0++pQbJm3qwb0NPOvbfhjXEqft+mi3Q/rwTyZBK02E03LQhsM/eU2H/Yj1JUsfz4KOx0NX+GaFkYipVZLcV67iI6/ietxEhNjS7m0gOcTkX6Nmy3W7IyoKvv4Yrx5V7DQU4eI2l5FFMJDZG0YU+VOz7bdD0KT0r/udFPVh/IBe7y4vTo2ExKZhVhSf/FpjmUPiS6JdddlYVX/4NX6ShQHfhe/DFbwKiHx9+5VviYiO4cFRfPF4NRRF8uXANL89ZBOg+3i9+uIh7rh5TruFOSsmy5Dze/usIbq+kS1wol/VNbDTBKbXBaauoNQ+lpgqCr2bdStfBG+l19l8Is4me95wd4PFxMkLjoNffS/42h0BrVmAl0ObWk6/oPjOe9LDhWF59iubujf4zl8JCWLuWtldOCzqgVRTSOcbxuiFHsfMDW/Ai6e9X4tLgdKZ1s1AWPjCKL/88yObDx+jWIoKrhrclIapqnhKK4MT35bgZeveBjID9XG4P1z84m30/P8E9T3/F8vV7yTla6LePqggOpeUypG0Ue7KLAmbVbq9ka1rhidJeOzKLeGZpMv8Z25GIGvIYaWycnlcNhCdAbEfI2u5rkAq7/jyDvRvOYPDt0LMG6gUMuBHSlnbF7bZhLpNSVUSEYbrsIpKcTnh3H5S1b4eFQdeumFC5lP58xTq9LBEaJlQUBE78V8jdaPzGLvqRhKhqhnODJkNZU0dMmIUbR3cGAn2aq8PxWXV8swhSMo4GbI+JCqVlfBTFdmeAkgZweby0aB5FRLiNjSkRbEkv0FOVKrobokScUNKgL0S6vZI/9ucxoXvjCVKpSZqWjbqKXPIJWKPA5DP5WcL1NJ1nP1Qz/Xe/BLQrZ+DF/5VNqioiPh7OPRfGj9cz9JlKPTOF0INurrgCgE7EcwfnMobujKILVzHkRJh3WYpx4i1nm8HpgRIkAx3obTW1PmdR4b4Z4wMWDkNtFu6bMRaAf84cT0iZhEchNjOXTxxEVEQIihDMOLMldwxvy8TuzZncO56/900Muojo0SQHj9ZN/viGyGmtqBP7wZ37YfRTMOgOuPBduGmTXoUrgLQ02LRJr45dSYSAse83x/ntUopb9UIzWZBmC2LUKFi2TPdxUlVYsQLGjgWzWVfYQ4fqbZEl+RjCsDKIdpxNZ1oRTTTBF5RCsKCe3v9WA3Rbs0XVlbPqy7EcLK2Fpmns2JfG3oOZ5brWBUMImHnZMB68cQIRYTZsVjPhoVbuuWYMd181BoCz+nVkzqxradMiBrNJJcRm5vopw3n5X38v1Y+gfWwI53eLY2SHWNrEhPglgjqOSREkVbLoQlOkaYSQ1yb5+TB1Kvz2G1gsuoHuySfh9tur3ldOjq6MI8tJiONw6FlsQitOUiOl5IHDB7C12olZLZk9C01hnNKNQZxK9v6Gz+kUQl6bLF+3l6v+NZv8QjualLROjOGL52fSrUPFgTRlcbu95BwrollUGOYgTwMpJQVFDkJtFkwnqdPo8mg8vSSZzCL/tKY2k8K/x3QgOqTpRthWNK6NqdfJuPxyXUk7nVBQoC/y/fOfsLAaRdmbNStfSYNu7jiJkgZYmefh9R0RzN/cnqN2i57/12nixx1t6OA6xTLkBqcF6dn5TLr9ddKyjlFkd2F3uNlzMJPzrn8Jp6uc1L/lYDarJMZFBlXSoM+aI8NDTqqkAQ5k2xnZJoYO0SUVW5qHmpnUvXmTVtIn47RdTKwUGRmwaFFgZeziYpg8GR59FO6+W59p1yGfpzmxe2FLWhxb0uIQvgWYcBV+jHYzvVUlUjd+/71eGCE7Gy66SL+OGCPv9OnCJ9/9hbdMNK6UkJVXyJl/e4pXH5rKiIGBGfZqm7wiN2ZVYUhSNINbRflKcvly6FSQT+Q4+YV2Xv/sd+Yt3kB0RCg3Tx3Jxef2bbSJmo5jKOqKyMrSlXBZRQ16xr3/+z/4/ffqza5PARX/ND2ylIdHpV6RHn9cj3ws8rkN7typB9ls3AhRwQz0Bk2NlMyjOFzB82rsOZjJhbe8xqfPXl+lAqw1jRAlvkuVUbNFdifDrniGI+l5J65t3baDrNk6gifunFRrctYFhumjIjp3rni7psHixbB+fd3I4+PyVlZsQf5zXgkT408yu8/NhSeeKFHSoD+IMjLgrbdqVlCDBsuIgZ0JCyl/cc7l9nLvM1/VoUQ6zcLNQZVyTCXSl3783V+klnkAFdldvPbpUtKz82tW0DrGUNQVYbXCc8/ptuPycLthzZq6kwkYFG3mnvYh2BSwKBDi+3zUN5zok5VLXrdOv66y2O3www+1I7BBg+OCkb3p2j4BtYKc0AdTc3FXlPauFmgbF4LVXFIZXC80q9C+ecVh8wA/L99GcZA6kRazidVbkmta1DrFMH2cjJkz9ZnzLbeUnwtywQK4/35daU+YAC+9hL11Ahs5QjrHSCSKfrQmJCA4t/o81jWM6a1s/JDlwqbAlEQr8dZKPHfj48ET5JVXCGhtRDSeLphMKr++exfjZr7M2q0Hg+5jNauMvf5F1m8/TExkKHdMP5e7rxpNSr6LPw8dxenR6Ncykh4JYRXWaKwKZlWhX5sIjhZ7KHZ5CTGrxISZKmVjbpUQg6oqQWzvkvjYiBqRr74w3PMqg9cLLVroNuuyqKruD+0rkltMHAt7vMj2P+LB5oVQDZNUMAuV6xlODCf36qhVpIS+fWH7dv26jhMaCkuWwKBB9SdbJTHc82qOpat3cfFtr+MKMnM2mRQ8pVKkjjizC9feMIlVqcV4ND3JrlUVdIsP4/rBSTWmrKvL1j0pjLjqOb/8I4oiaN8qji3zH27wC4qGe1418LpgxbPwv87wUkeVX0evxWFL8M/IFxqqB6j4lLQHC++yiu3Pd0JGuSFUH+QeoeGQbn5ka31cij9CwE8/Qf/+EBKiuwtGRMAbbzQKJW1w6mhSr7ri8MDQM7rw9H1TMJdxnUuMi8RbSkkPO6Mz78y6npWpxbi1kkzoTq9kZ2YROzLqP4d0r86tePfR6URFhBARZiXEZqZnxxb88ObtDV5JnwzD9FEOn0+GA0tK0lH/ld6G3W2OcNP1r6Ie2A0jRkBeHtx664ljdjCFQuKRY3YjynjISQH7ZHbllq9rm5Ytdbv6vn36NfTuHdxubdDkOK6kjyMRXHPJ2Zx3Vi/e/fp3NE1y1UVDuOTON/2SgT1y+8UczncHDUF3eiXrU/LpmRhe6/KfjEvGnsEFo/qwdU8qkWE2OrWNr2+RagRDUQchdR0cXOpfM8DrhPw0E9tb30XvB3yNP/3kZ7dOZSBuIsElwBRoUnJpgnSPRmJlbMl1QceO9S2BQR3jCZoGRtAyMZYn7px84oUxKtx/8a57hxbsO+b0zUwDx7bDVbeLjhVhMZs4o0fTCvxqIBqjYZGyOvi6oasQDi0v1TBmjJ8ppBm7MVOI9kVLPF7/qYfbK9iS0ozn9hsJ0Q3qj4qWpEpvumy8v6k0JTOPbs3Dg+YDUQW0irBhb0DKuqlhKOogRLX2FQEvgykEYjqUbjDBjBn6giLQm08x4ST9lU5kHA3F6VFwehRcHoX0/FB+3NGWX7KrFp5rYFBXlJ5a3DptJOGhJeawp976AbfbzQVdmmNShP7xZePrlxBBsxAzBQ6jMG1tYZg+gtBpvJ5Bz12kV4A5jmKCvleV2fm11/TETd99h9UquNZxDu+7vuXBZT1JiC+iebidrMIQUo6FAYJWDcXsYXBaYlIgWBlFRfivk4fYLCx6/24uvestco8WsWjlNh5/7TtunXE+l3VPIKXAgUeTtAi3EuLL8WGuwCfb4NQwFHUQFBPM+AO+ngrpG/UBHNkGpnwCYWXzltts8NVXkJoKycnEde3KA3Fx/LjyGCuPCVKOlSywhKpwf4eTO+4bGNQWqqKbPzylLBiK0GsjlqVv1yR2L3yUzbtTcHu89OuahEcT5BS6aRPlP45VRRAdaqiT2sK4s+UQ3Q6u/xOKMsHr1oucV+jh07Kl/vHxzcAI/r6hgOV5bsy+A5/tFsq5cadv3TeDhoFJBVXqNmlBxeNaCEHfriV1OE1A1xZh7M0oxuvLQ2o1K3RNDGv0LnANGUNRn4Swanr3xFoUfh0cRYrDS5ZL0j1MxRqs7IaBQT1wvJxWdYgONTOgXSR2l4aigK2c9KYGNUetRCYKIbKA4HGplScOyK4BcRoKTe16oP6uqa2Uss6L59XQuIamNxaa2vVA/VxTueO6VhR1TSCEWFsfYcK1RVO7Hmia11QXNLX71tSuBxreNRnLtAYGBgYNHENRGxgYGDRwGrKifru+Bahhmtr1QNO8prqgqd23pnY90MCuqcHaqA0qRgjxJpAipXysvmUxMKgJhBDtgGTALKWsMMxRCHENcL2UcnjtS1b/NOQZtUEFSClvqqySFkIcEEKMqW2ZDAxKI4T4QAjhEkIUCiFyhRC/CiG6VfLYJ4QQi8u0dRFC5AshAgo5Cp3bhBCbhRDFQoh0IcRSIcTUmrqe+sRQ1AYGBrXJM1LKcKAVkAK8V8njHgUShRA3gK6IgXeAF6SUW4Ls/wpwF3Av0Mx3voeA8acmfsPAUNRBEEK0FkLMFUJkCSFyhBCv+tqvEUKsEEK8KIQ4KoTYL4Q4y9d+WAiRKYS4ulQ/E4UQG3yzgMNCiEdKbWsnhJBCiJlCiFQhRJoQ4t4qyPiBEOLxUn9fIITY6JNrpRCij699DtAG+M43s3mgvD4NGg+NYYyWRkppB74E+pXqXxVCPCeEyBZC7AcmltrfCVwLzBJCtAJmAjHAE0HuRRfgFmCqlPJXKaVdSumVUi6XUl5Tar+lQojHfPenQAjxixAirjrXU9cYiroMQggV+B49sKEd+pP581K7DAY2oz+1P/VtOxPoBFwJvCqEOJ7gowi4CohGH4Q3CyHK1q0/B+gMnAf887iJQggxXAhxtJIynwG8D9zok+stYIEQwiqlnA4cAi6UUoZLKZ+p5K0waKA00jEaBkwD9pZqvgG4AOgPDAQuLX2MlPIv4APgI3QFfa2UMlj6yXOBw1LKytRJuxyYAcQDFuC+yshf70gpjU+pDzAUyAJMQbZdA+wp9Xdv9JQJCaXacoB+5fT9EvCi7/d2vmO7ldr+DPBeJeX8AHjc9/sbwGNltu8CRvp+PwCMqe97a3xq5tPIxqgDOApo6AuFfUpt/w24qdTf5/nOZyrVFoL+QHoxyHUu9/3+EPBnme1HfOd1oEf8ASwFHiq1zy3AT/X9/6zMx5hRB9IaOCjLX3XOKPW7HUBKWbYtHEAIMVgIscT3enoMuAk9NLU0h0v9fhBoSdVpC9zre9U96pvltK5mXwYNn8Y0Rp+TUkajK3070LXUtpZB+vZD6iaTZGBbBefIAVqUOS4J/Tqs+Kc1SS/1ezG++9DQMRR1IIeBNkKImkhY9SmwAGgtpYwC3iQwF07rUr+3AVKrcZ7DwBNSyuhSn1Ap5We+7YYPZtOi0Y1RKeUh4E7gZSHE8RypaUH6rg6/AUlCiAYT8l3TGIo6kNXoA2iWECJMCGETQgyrZl8RQK6U0iGEGIRuHyvLv4UQoUKInui2sy+qcZ53gJt8syPhk3uiECLCtz0D6FDB8QaNi8Y4RpFS/oqu5Gf6mr4E7hBCJAkhYoB/VrPfXejrMp8LIcYKIUJ8dvyzqtNfQ8RQ1GWQUnqBC9EXXg6h27r+Xs3ubgEeFUIUAA+jD8yy/I6+wLIY/TXxFwAhxNlCiMJKyrwWfWHmVSDP1981pXZ5CnjIZxZpHIsnBuXSGMdoKZ4FHhBCWNEnGD8Dm4D1wNzqXQIAt6K76L0A5KLfk8fQ78uhU+i3QWBEJtYTogpRWOUc/xGwV0r5aA2LZmAAnPoYNag5jBl1I8Rnm+yK/iUyMDBo4hiKunGSju569E19C2JgYFD7GKYPAwMDgwaOMaM2MDAwaODUSnHbuLg42a5du9rouklzvCq0QcWsW7cuW9ZDzURjXJ8CUlZc7tygwnFdK4q6Xbt2rF1bmbB7A4AdWTDze1h5BFQBk7vBGxMhNuTkx56OCCFqosBslTHGddXxbvkV78rPwJ4PtgiUIX9D7TseYSjtACoa17WiqA0qT04xnDUbjjn0GbUmYd5O2JkNG280JiEGjRfv9qV4l84Gj1NvsOej/TEHoSiofcbVr3CNDMNGXUMcO+bghRdWceGFn3HvvT+zf39epY6bvRGcHv8Yb7cG+4/C8kbvpm/QFDi6ZRerb/4Pv198M3vf/QqP3VGp47yrPi9R0sfxOPGuChZTY1ARxoy6BsjIKGTAgLfJzbVjt3swmxXefHMdP/xwOaNGtavw2K1ZYA8SSiAl7MmFs9vWjswGBpXhwGff89f1D6I53Uivl/TFq9j10oeM++tLTGGhFR9ckBO8vfgoUmoIYcwTK4txp2qARx5ZSmZmEXafxnW7NYqL3cyYMZ+TuT+e2RLCzMG39Y6vaUkNDCqP1+Fk9Y0P4y12IL1eva3ITuH+Q+x+47OTHA1EJQRvj2xuKOkqYtytGuC773bjdmsB7enphaSkFFR47PQ+EG7RFxGPYzPBGS1goJGk1KAeyd2wPegiidfu5PBXP530eNOIq8BkKdNoQR0+vaZEPG0wFHUNEB5uCdquaZKw8qbLPiKtsPYGuKS7PrOOscFNA+CnK4yFRIP6xRwRdmImHbAtOiJoe2mUjoMwTbwXYluDaoaYVpjOvwu1a3UT/Z2+GDbqGuC22wbxj38sori4pEqQ2awwcmRbYmJO7mOXFAlfXnrS3QwM6pSonp0JTUqkYPcBfdHEhxoWQpfbrqxUH0qHgVg6NNk00XXGSWfUviKaS4QQO4QQ24QQd9aFYI2JW245k8su64HNZiIy0kJYmJnu3Zvz8ceX1LdoBgbVRgjBqB/eJrRNC0wRYZgiw1FsFrrdeTVJF55b3+KdVlRmRu0B7pVSrvclol8nhPhVSrm9lmVrNCiK4IMPJvHII6NYty6VNm2iGDiwpeHUb9DoiejYhov3LyZrxXqcWbnEndWfkMQ6Dwo97TmpopZSpqFXk0BKWSCE2IFe9dhQ1GVo1y6adu2i61sMA4MaRSgK8Wcb5ov6pEqLib5E4v2Bv4JsmymEWCuEWJuVlVUz0hkY1DPGuDZoCFR6MVEIEY6e//guKWV+2e1SyreBtwEGDhzYJHKnut1eFizYxapVR+jQIYbLL+9NdLStvsUyqEOa4rgGsKdnkfzxApyZOSSMHkqLscMQiuEE1lCplKIWQpjRlfQnUspTqWvWaMjPdzJs2PscOHCUwkIXoaFm/u//FrNs2Qz69CnHkT8YUoPsTfrvcX3BcPQ3qGfSF6/i94tuRmoamsPJnjc+o9ngvpzz4zso5ordSUvj8BST7Ugj0hJLpCWmFiU2OKmiFvqK2HvADinlC7UvUsPg8ceXsWdPDk6n7kd63PXuiiu+YcuWWyrXSfoq+HEKuH1BL+YIOH8uJA6pDZENDE6K5vGw/G934S22n2jzFBaTvWoj+2bPpfPMk9fIlVKy5Mi3rMlYjKqY8Goe2kV2Y3LHG7Co1toU/7SlMtO7YcB04FwhxEbfZ0Ity1XvfP751hNKujR79uSSkVGJwsvOo7BgHBSngbtQ/xSnwYLzwHmsFiQ2MDg5ueu2obndAe3eYjsH5syvVB+bsleyNvM3PNKN02vHI90k5+9g4YGPa1pcAx+V8fpYzmmYz15Vy3+GVbTtBHu/BBkkqktq+raeN5yCdFUnLa2AL7/cRlGRm/PP70T//i3q9PwGDQPFpPoFr5RGmCq3ZPVn+i+4NZdfm1d62Jm3Hpf3yjqdVUspyVq+jszfV2NtFk2bv0/AGtv0PK+MyMRyuPbafjz55HIcjpLUdooi6Ncvkbi4k2QNA7BngidIOkivQ99Wh8ydu4Mrr5yLlPoC6eOPL+Pqq/vy+usTDV/v04yY/j0wR4bjKSz2a1fDQuh4feXCY+2e8t8onV5HnSlqzevlj8m3kf7bKrx2J6rNyoYHnmXUwneanDuhoajL4f77h7F4cTJr16bidmtYrSphYRY+/XRK5TpoORJMIeAp8m9Xbfq2OqKgwMn06fOwt+4A48ZCbCz2wiLeX/UHUxYnM2ZMhzqTxaD+EYrCiPmv89uYGfpiosuNUBVaTxpDu2kXVKqPtpHd2Jm7Don/zDzEFE64ObI2xA7KgTnzyVz2Jz1HR9F+SAyqRSEnuZiNN9/DmE1LUFS1zmSpbQxFXQ42m4klS65m5crDrFmjRxtecEEXLJZK/vNbDIdWIyFlKXh8sxdTKLQaBS3qLinNr7/uh44d4aLJYPElj4qMwHXOGP5vwU7GjKkzUQwaCM0G9mZyyjIOf7sIZ3YeCaMGE9O3W6WPP6fVJPYf24bb60LDCwhMipnz211ep29o+2bPZeAlcSR0Dcdk0c2Rce1DGZYUQt7KlTQ7++w6k6W2adSK2u328sMPezh06BiDBrVi8OBWNTpQhBAMG9aGYcPaVOdgmDAfdn4A29/X/+5+LXS7uk7T4gkBjrNHlijp41gsbIrphiZBMawfDQ57WiYp3y0BIWh10bmEJMTVaP+msFDaX3FRtY6NsTVnZs+HWZX+C4cL9hBji2doi3G0DGtXozKeDFuo5qekAYQiUFSJJW01YCjqeic5OY/hw2dTUODE5fJiMikMHZrE999fjtXaQC5LMUGP6/VPPTF2bEe0tcEXjzSTmXwnGDE8DYs9b3/B+jufAF8Ayto7HufMN/9Lx6sn17NkJURaYxnXdmq9ytBxylloWYsC2lWTgioCYvIaNXUTfSE12P0pfDsa5o2CHbNBC1J/qgpMm/YN6emFFBS4cDq9FBW5WbHiMM8/v6p6HR5YCPNGwpxOsORGKDh8SvI1FMLDLXSICq6ow616PmyD6lPozue3w3OZvX0W3+57l7SiUyuQXph8mPV3PYHX4cRbbMdbbEdzOFl7038oTsmocn8ur5M/Ur7nzS3/4Z2tj7Eu43c0GVjkojGSMHkyqjnQFCmFipLQtNZe6kZR/3olLJkJKb9B6u+w7Hb44aJy3YRORlZWERs2pKNp/sfb7R7ee29D1Tvc/Cr8fBmkLoP8fbDjffiiX6NX1jl79rB81ixuds/Hpvh/OcPM8PAIYZg9ToF8Vx5vb/0vqzMWk1qUzPbctXy08zl25VZjDPo49PXPSG9wRXr4m5+r1JdX8/LhjmdYkfYTOY50Mu1HWHzka+bte6fa8jUEvJqX77cs59GVC0mNTUIKf2UtTBavlf+PAAAgAElEQVTU/hPrSbraofZtBFnrIXl+yYIa6J4QaX/oC21J51S5S49HK9fM63YHr0hRfmcO+PNf/vJJD7jyYd2TMOqNKsvXEFj1wgv89uCDaF4vSMmU7l/z+6VvkUosCeHw7xF6JRmD6rMs5TscnmIkumKVSDyai4UHP6FLTN9q1QWUbk9QRS01Dc1dtbfQXUc3kOfMwitLAlzcmou9x7aQUXyYhNDWVZavvil0FDPyhZvZnXmIQqedV60hPBIbxg0xESheN6JlN9RzrkdE1KxNv76p/Rn1kSXBzRzuQjgSaF+qDC1aRNChQ2BuAatVZdq0XlXr7OhugsbzSA8c+a1a8tU3efv389uDD+JxONDcbjSPh85bvuamWUlk/H0XqffAzQONUl+nyv5j208o6dK4NSfHXLnV6rPVxaNRLIH5NoSi0OqiqiXrP5i/C7fmDNwg4Ujh/mrJV9889fOHbE9LptCph8DnOu3cmZbDkHwTlru+xvy3x1Gat6tfIWuB2lfUtmagBqkpqNogpPpltj/9dAqRkVZCQ/VBHR5uoWPHWB58cETVOgqJhzJRVicIT6q2fPXJzvnBq59rbjc7582rB4maJiGmsKDtmtSwqicvwRaM6J6d6XbPNaghNn0xUVVQQ2z0ePAmIju3q1JfUZZmqCLwpVkRKhHmxhm99/Hqn3F4/L+vEsnO9ANk5OfUk1S1T+2bPjpeAn8Eqd4lVOg8rdrd9uuXSHLynXz88Wb278/jrLNaM3lyN8xBFhcqJCwRksbos3tvqdmHKRQG/LPa8tUn5booCmFMo2uQIYlj+fHgJ37h1Kow0SGye7lKvDL0ffxuWk8Zx6EvF4JQaDt1AjF9Ku/nfJw+zYeyPG0hXln6jVZgVix0jKrim2cDobzRKwHRhDNd1L6itkTCRT/Dwkk+O7DQ3dbGfwWh1Z9RA8TGhnDHHYNPXcbzPtUXPA//AopFV2ZnPQutx1bq8KKsLFJWryY8MZEWZ5xR72HZ3SZPZvG//hXQrphM9JhSycjKquCxw+FF+ptJ0miwNs7ZWlXp1WwwWfZUVmcsxqSY8WoeWoa146IO155y37H9exDbv8cp9RFujmJalzuYt+9dHN4ipJTE2OK5tNONqMrJJzRSSjYd2UPK0SwGtOlGYlSzU5KnJrh6yESe+XUODnfJw1EIQe+WHYiPjK3x8x11ZpNSmEyEJYrW4Z2qte5QE4hgr8inysCBA+XatWv9GzUvZK3TExXFn6kr64ZGcSbYsyC6E1QiX4GUkiX//jernn8e1WJB83qJatuW6T//TGRS/ZpN1rzxBr/cc88JE4gQgtFPPcWQu+6q2RMdXgw/TtYfbhLQ3DDqTeh2Vc2epxRCiHVSyjpP5hB0XAN2TxGZxSlEWKKJtZ3a5KM2kFKS68xEFSrR1sotsmXm5zLuf3exJ/MQqqLi9Li5ecRkXrj0rnqdiNhdDka/dBtbUvdhd7sIMVsIMVtZft/bdEmoRmBaOUipsfDgp2zNXoUiTIAkzBzJFV3vIcpa8w8EqHhc152iboLsmDePedOn4y4qyechVJXEfv2Y2QCu/9ihQ+yYNw+paXSfPJnodu1q9gSufJjdMkg+kxCYull/4NUCDU1RN0XOffEWlu/bjNtbYjYJs9h4fdoDXDWkfrMcSyn5bdda1hzcQZuYBCb3G0mIpWajtjZlr+Tng5/5mbUEComhrbm25//V6LlO9F/BuG6A09rGw18vv+ynpAGk10vWlg3k/TGbmLNn1JNkOlFt2jDkziDrAzVF8oLgNm/pgd0fw6BHau/cBrVGRn4OK/dv8VPSAEUuB4/++AYX9R9U6Zl5bSCEYHS3Mxnd7cxaO8fajCUBqVwlGln2VPKduUTW0qy6PIy6UFXgKHlkk30ia5g9N7gLliI00ubcTObH1yO1phEFFhR3YfCc25rPD92gUSDRkBQh0RVTgaMYUzk27Jyio/xn6T/YnL65LkWsc1zeIG6N6A8JV3leYrWIoagrQQ45vMb/eIWXeINXeZ5nOMABuk2ahGoNtGW7XDDvAyfvXvceL7ZuxeFV1Qxrb+i0GRc8utQUCu2rl/DHoG6RpALLgXXASiSb6RCXQJg10L1QAMeK3Lz1ww4GPH4TF75+H4WO4oD9mgLdYs8I6tpoUWw0q4d1CENRnwQvXt7nHTLJwIMHN27yyWcOH2C+dwTmlrGYrPptPGEFkOBxg9sFBanpfDxuHMU5DczHM3sTrHkM1j8L+Qeq10dke+h/n66Yj7tGmcOh7cQ6zbltUD0kucAewOv7SCAXoWzjvek3EmqxnEgxoCoC6dvD6dbweDV+3bGaa+c8Xk/SB8erediRu47fjyxgS/afAeaLyjI08TwiLbGYFT0GREHFrFi4sMM19eL5cVosJqYWQEo+dI2rehKiXezka77ESeCrkIKCVmCn062fkfN9Kh4XOOxQ1tphDg1lzNNPEzV2Ktu3Z9GlSzN69qxH74AV98PW13W/caHqldFHvAY9qulWlrocds7W++s8DdqeX6vV1o3FRB0pNWTOYUAgmrWusjeGZCOQV+72LUfSueyD90nNteNwefF4A3WF1WQm9YkFuNbuxFNYTPyIM7FE113xgNIUuwuZveMpit0FuDQnFsWKRbVxTfd/VstTw+11sSXnT5LzdxBtacYZ8SOJsTWvBcl1TtvFxCIXXD4Xft4HVhO4vXD/WfDIyMrHfRSQjxYkTBjQ21ccIfnrTBSX7oEYDHdxMe+9vIg5DxzDbFZxu70MHdqaBQumEhYWJGrzFNDQ2MNussgijji60BWl9ItTxmpdSR/PbXLcxrzsVmh/IYRUYyC2HK5/DOoMLW03nu+fBafv/2gNw3ThAyiJVfG0CW6HBd2z4rEfF3MosxhHBflzFASf9zmfuDwXIJAuN2e8+C8631T9YLZyZcINZKHP/psh8C+Jt+jwV+Q783zFDMClOXFrbhYe+JhpXe+o8vnMqoUz4kdwRnwVo51rgSZt+pj5PfyyD5xeyHeC3QPPr4JPtlS+j9a0LX+jpqFc9R3YPeUqaQBptvHHwWjsdg/5+U7sdg8rVx7i7ruDZ0NzFRaSum4dBamplRcUKKaYV3mFr/iCRfzC13zJK7xEEaU8U/Z8oQeolEWY4MD3VTqfQf0gHUV45j4Khbngduifwhw83zyCdFbFZhxDebF+S3fv58dtuytU0gCmIheRh/Lw5BfhyS/E63Cy/p5Z5K7fFnT/Q7nprDu4E7srSD3RCpBkAyvRTTX7gDVI9vrtsytvwwklXXKcRnL+DrRgi96NiCarqAtd8M0OcJT5/xS54ekVle8ngQS60BUzpRLlHDcX7cwBuzv4gT5MoaGkaC3Y6fZX+A6HlzlzNgfk5Fg+axbPxsfz0bnn8krHjnwycSLOgoJKybqQH8glBxcuNDRcuDhKHt+zoGQnISg/ELfphuA2JbTdKwLtawCahrZnZRV6agOofuvBx8fjt5u2U+Ss2L4bopq5Zq0HpYxFRHO62PvOV35tOYXHGPXCLXR95G+c+9KtxD9wPm/8/k2lpJR4gG2A5vtI388UJEdL7Rl8/DaFUd1kTR/HHOWXmMo6yaRDaho75s1j66efolqtDLh2Bu1Hd2BNzrt4VQUNQV5kNDLMAp7gZhGzVaFZyxD6TZvEOc91QnoDhXG5PGiaRFX1bdu/+YZljz+Ox27HY9dnvcmLFzP/mun87bnrIG8nxPaANuMhiPvUdrYGmGk0NHawHYnUcyF0ngZb3/BP6wq673P7Cyu+MQYNg+Jj4AmiRL0ufVsFZBXk8eayufyZvI1erTpw5zmTCAk5iJS5FHkcJIbGYBIqEVYLJkXBU+aBoCoKESFmOsbHc1vYmYR+9Dllc2NKTcOV5y/HJW//k1U+3+zj4d/3zf0f7Zs3Jz4OPJqLTtG9ibUlBJE6j+DqVgPSAT1lQffYAWzJ+dNv9ixQ6BjVE0U07kK3TVZRt4jQFw7tZUaRImB4Gzh8TN/HVOadQkrJF5dcwv5Fi04Es+xasICBN9/MlKG/c6hZBIqmsbjTmThm/op0Br5SmS0w8W8afQcXgelbRvS6iV82RJyYuVhwMih2M0OfieSJogex2sIYaBnCvhefDQigsZqdjOk9H/nLYoTXoVc2D2sFU1aArRpO9/EDoN/9sOEZvfKOUAAJ576nZzo0aPCIVt3BbNVNHqUxWSG2NdKejwgJXNDbn5XCmbNmUOx24HC7WLRzDa///g0f33Afmm0bNlVlnykNR76Fd1esCVDSAKoCt1/SGZvZRNbRvSS5/B8YKdEKaVf1oufdgyh2LcKsRpBbFMvqA9sCAmjaJlpYnf8JVrsFKTWWHPmWwYljGJU0qcxZK3J4KNk2uvUUUgr3ke/Kw625MStmbKYwzm93ZQXHNw6atNfH3B0w/VvdOiEBVeiKWhH67zYzPD0arj+j5Jj9ixbx+aRJAQpT2Myw6TpoH4EiNbRzP4PVaUi3//1TTdBvMEycWrJguTunFYNfuBmHE6SjkBut7xG57TJEUri+ygmoHoH4Kw1t+Pt+c4dLr4VuffR+j2P3hKB0vhTrhI/8zv05n7GT7X6zaoGgC125gun+N+fobkj+Ts9p0nEKhLWo0r2tT053rw8pJZ65jyFTd4LHtyComvX8OZpuihNxbTGdfxcipuWJ4ya98QDfbfkDrcx3/ozWrVjxjxtREOzLzmXAE//DXqZIgQAsZoXLR7ejY8uIE+0Jn2QT8c5evHYnm5JUNtzRh3l3XENoqWLKXg1mfPg1H69ed6LNalb4x7SeWErPlKTE4lCZ1u9ekiJLFkV108cKCFjUV4DeCEomLJrU2HdsG1n2FGKt8XSO7lupBFQNgYrGdZO1UQNc0h0WT4eLukKv5tClmT4jcHqh2AO5drjzZ/hhd8kxu7//PkBJA0gh8S5OxmM24zpUhLY+M0BJA3ToChdM8/cq6dI8k51fW/jHP4YxvfMeoqe2QsSHnFDSAF6TRBsQjxjqn8yptJLendGM4S9cS8Q99xNxYTsmTvyE9PTCE/tO5ALCicCC/iWxYCGccC4gSPBJdBfofy/0ua1RKWkDPTrONOn/UEZchUjoCM076G9Gbjt4PeD1IDP34/7iQWQpE8minWsClDTApiOpSA3Mqon3V6wtZyYtmHZuWz8lDZB9ZQLDFr5O2+kX8e74GJ68bIKfktaPhScuHuPX1iUpElmqlF74gjRaj19Jy3OX8EfSJWx76q2ShGKYgG7o6ur4F0sBEtAXREtQhELn6N6c1WK8HrTSSJT0yWjSihpgSBJ8+3dYdR0k50kcZUwhxW547I+Sv0NiY1HMgRU2JMAn2xA3LoRfk8ESfAAUF5VoaE0KXNIMqpWEVs155JFRDAjdixyUABGBDt3CpKIOaet/fl93x+xWhj5/HSuTk/BqCm5N5Zdf9jFs2Pt4faWbIojgTu7mQi5mQHZPEl9PwdrrA3644AqO/Plnpe6XQeNAqCZMfcdjvvwZ1H7j8JYtWCslmtuJtvevE01h5SUuEnDl7C948sff2JGWhTtIKTBVVbCXMvMpmvQtqgsSzx5E4nN34Agx0bNlMBszJMVEERVS4k5nVtUTYzt0USbNntuDKc+N8EpkgZOtj7/B9qdLajsKEoDBINuzNUXjuo9+oPsj/+Ff814nt6hiu3xToE4UtZSSNWtSmDNnE2vXVs3lrKbILgbpCu43mpxV0t5n+nQUUxDTvd2DsuII4p2NKPcu0t1HyqBaLbTvplIsQ7ix8E3CcosIybXTP3s5q0MuA8AWE4PYk6s7eZdBESYu+NfTDLjxRpr37EnnCRNwunSl/ena3jg9JqQs+Zd5PJKsrCJ++WXfiTYzZhI2wrZ2M0m9/T3ytu1izw8/8NHo0exZuLByN8ug0njsDg5/u4gDn32PI6t65bdOlaKsw6jewPHodTvQjpVULp959iRCzEEiviTM3bCNx39cwuKde7GZA8e/lIK28VHEF3q4cuNR7l6Zw90rc/jbAROqx0OENRSv5iX1WHAPJSHMfHn9k5zXfRC9WnRgUNKZWEz6ZCfmrWQUh//DwVtsZ/vTb/vlyhHYuH/ufIY+8xizVy1jV8ZBXvztc8548mry7YFvwU2JWlfUBQVOhg17n3PO+ZBbblnIqFEfcPbZsyksrNvEJtGOLETZxRcAzUvrtBK7Y0z79lz8/vuYQ0OxRkZiCtVnAcfnyUKCsOsFYwkpmfkqJhPWyCiGzPqKS4sW8JHzKhyEoKGy0dOX0Z+FsS8XBt9xB+av94Nbg9JV1D0a4Wo4fZoPZcL//sctW7dy+Tdz8J2enRlxFLkCg2NcLi979/oriF/uuw93UZHfIHcXF7Pw1luDlugyqB4Zv69mXuIwVl39AKtnPsy3bUax639z6lyOX3NzKAhirnBKWOMo+Z79e8K1jO85hBCzlUhbGKovetTrGxMOtweHx4OUYCm1KBJqsXH5wHFMSDyLaZuP0aLQgwKYJCSlZuCZP4v4yFjO6tCHJ39cQmEZtz63VwKtOa/HEH6+4xW2PPwpV48cdiKS0pQRfALlKSzGU1zi859+LIdXl35NUSkfbJfHTVbhUd5dMb9qN62RUeuK+p57fmb9+jSKitwUFrooKnKzZk0KDzzwa22f2g9nZhrn/fFfzK5ST17Ni9ldzNhVT/nt22vqVO7LyOCSTz6h/bnBC4oKq0qX6ZfSYsAAotq1o/9113HTxo2kt57EEu9oHPgntXF64aW/oOvFk9jT90bkOV8gN2cjXV6kSyP1QGsm22/wjyI0R+iLRMDANqmEWwMHtNms0rdvol9byl8lr7st28LA4dCpBxSkHMZVWFi2C4Nq4Cm2s+yim3HnF+rBHoVFaA4nG//5HHmbdtapLL85vOxzebCXUtZ2TbLd5WGTLHm4W0xm5t74NJsemsMHV/8bRQn+9Xd5PNw2agrt41rSu1VHXrz0Lt6b/iDDsk2YKWPy87qR6bvRsg/x2ZRbWLtuM/+d/zNHi+3Y3W4cTifKvgwoEzgWaY7G4suj4W7vH2F4HGtcDKawkm1rD+3AatK/DyZV0LNdFGd2jSXEpvHz9r+C9tFUqFX3PCkln3yyBWcZFzan08tHH23i9dcn1ubp/Yjt3JnBG94hJDuZZSMeIj8qiaQjfzJ6yX8YMiFwodUSHk6XCy7g4B9/sPenn5Aef+O2RbXRZ/Qker71N7/2lXvBqooAW7hbg80ZsD5d8M2wJyDvTlo9+xfu5jGkJAxElTa6jIQHhpU6SDVDzxth21tc1n87D39/Dk6Pitur/9usVpWePZtz9tn+lS1C4+LwOgq5/GZIagcI3RPPXqxh9uYA/gtCBlUn7ac/gr6deJ0u9n8wlwEv1k5y+WAM69yPi9b+xK1hJi6PDEUD5uQX81qhm1/aB9ZG7Bzfhs7xbQi12DhmD3xwW0xmnptyF89ferdfuzf7IEIr6zWN7m1yNI1m+9ayum08m/btYekLuxgQE0mix4MmVNRW4yGsZOGvS0w/fj70BS7NRe5tHUm4ZwuKs+RBo4ba6DvrPr/8JYmRzfBKjZbNQpgxvgNCCBQhEAIchSaklPVeBq+2qPUZtcsVPHTT4fDw119HAl7bawtzSAgj//Mf+hz6lRvfPpP7n23B5V9MoXXxAUY89FC5x/W7+mrUIIuLSOg8MfBB0725Pnsui0WFwUmwI1v3CCkKj2d31wtJjh2Oy23D7oH16UEEGPo0dLsGm83E6v/7lCsH7yAqHJo1C+Hmm89k8eKrAgbnWQ88wIgJJlq3B4sVLBaw2iAyBpSlp17Pz0CfUQdN8erVsKdlkrVqA65y7LU1zZT+5xATHc8Txxx0Ss6gS3IGz+W7GNypPwPall8Ud8bQidhM/uY0q8nM1IFjgyo8kdj5xBueH14PollrZFYyAkk/m4WJYTYSXS49glI1I49m+B1iUsxc1f1+EkKTcA9qTvaL/fH0jEEJsxHZvSNDP3qGjldP9jtmQJtutI9twZVj2xNiNWGzqFjMCmaTQnSMk11HN1bhrjUuat2PesyYj/jtt+SAMa2qgrAwC263l1694lmwYBqJieE1LktZtn/9NcufeorC9HTajhzJOY8+SmynihPZrHv7bX66807dG0PotY7//u23LNwexqxZK8jOLqZfv0ReeOE8hg5tzeXfwLe7SoJtBLqTx7abIa3Qyw2rdhIWlUNmZgL79nVGSoUQE/x3lJ40KiiuQrBnQngrUK24vXqwTtACK1LifCUamylI8n7FAtdmgjWqCnetYdEQ/Kjt6VnMb38umsPfHitUBaGqqCFWNKebbvfOoM9jtV9n8Ji9kCd+/IAv1i3Copq4YdhF3DV6GhZTEMXqw+5ycMHr9/Jn8jZUoaBJjT6tOjH/bw+z56FXODJ/MUJVaDt1Iv2evh+zyYv7wzt8iaB8X2iTBdG2H+aL/oFn6ZugZYCqoO1PhqM+bwzVjPm6NxFhwYseF7iOIdGItMQgpQZSIspxq9uUvoF5yW9gNgXezw6RPauVfKmhUK81E/fsyWHw4HdxODzY7R4sFjVglm0yCfr2TWTt2pk1Lksw9rGPX/iRTLKIJIKRnMMZDKjwGHtuLvsXL8Zks9Fx7FgefXIVzz+/iuLiktX20FAzPy65jo0ygc+3wbZMfXbdJwGu7A0X9c5nbuhbZLuKEaoHj8fEsWPRzPlwJjZC2H0rNAturjvBBxvh/36D9EJoHgb/HQk3DgiisGe3gOIgU3TFAjNSG3UUYkNQ1AA7nn+fzQ+/jOZwITUNoaq6OUQr/Qofwpmv/4cOZWaHtYFEAw4AqegZ5qKBTgjCKjxu05E9bEvdT9eEtvRLaM933cZjT8k8Ye5TLBYiu3dg/M8v4t22CHlgExRmg9mGSOqJ0nssSptEELt0v21foWNt7Tq0tZtQugzDNO62imV3FuNd8h7aruUgvYgWXVFH34gS52/WO1Swhy93v4pTC3QMaBvRhSu73Vvp+9XQqPfitjk5xbz//gY2bEhny5YMtm7NCjgmNNTMunUz6dat+rXYjnCYVazkGMfoRGcGM4SQMot6ySQzhw/xUKJgzZgZy3kMobzprD/FxW6aN3/WT0kDkJiA6YZrsdgsFHsg1AwuD9hMejTkhEvm0LnTblBKvsgej0ruvh7cZx1Kp3YVZOoDPtkMM3/Qfb+PE2qGF87TlbUfy26HbW9D2cTpzfrA1E2Vus6GSkNR1AC567ayb/ZcXEePceiLwLUMgKienZi49Ydqn1eeyGmRgW6tbAnE6blb/PbbBmTjH8GnAoMQVK74a/LH81lz8yN4Cv1zwfS6sBVdz22OON63ELrpx2wFqxXTNVMRZdxapdtN4aYjWPpchs1S8bqI+/N/ITP36wE7+gnAYsN8zat+M3Gv5uHFjffi9PorarNi4bw2f6df88abbveUIxOFEOOFELuEEHuFEP+sqgDNmoVy//3D+PTTKeXmXzabFTIzq+8LuYmNzOY9trKFQxxkGUt5jVf8U3wCi/jFT0kDuHHzG4vLzTtdlsOHj6EEy/h0ySV4VDPFvrFW7AaPhEI3FLg1OnT0V9IAJpOXpPbr6PRTd/hqEBSllXvefy/1V9LHz/HI0iA7D/ovRLQGk282ZQoBSySM+SjIzgbVJXZAL8589WH6P/0Aijn467ozu/zk/CdDr8+5CT2951EgF9ju+7v0fg4ClTS+v49U+nx5G3cEKOnIBCudhkUhpEdflZaannxdauCyI5ISgmbzkyYTu1p7eHnzv1hyZF65rqFaxj5k9sFSSlq/IrwevFt+8dtXVUxc3OE6TIr5RKIls2KlZVh7ejcbWunrbGyc1OtDCKECrwFj0f/ja4QQC6SU26tzwgkTOrNpUwaOMm4RLpeX/q0zkH++TbHFhKXdZZhjA1esg5FW5OHqXxS27/wXQkD37lsYe95PyJAiVvAH5zH+xL5ZZAbtw4MHO3bCTvKaCNCyZQSeslnzwsOgWWyFFQmECD5QpQC8dsjagPz+AuxjfsEWFRUQeHO4nHqx6UW6S7bfs8MWC1O3wr6vIH0VRHWGblc1apNHQyakRXPMURF47f4ulEJRaD5qENtyVpNedJC4kHi6xZ6JVT2JjcuHdmg53mUfQ04uhIWiDDkTpWcPhEhDklQqeX4RwTPMSaDyhYajunfEFBaCp6jEf7llr0gUtQIbe3ljXkq80otHulmT8RthagxdowcSFeK/FiXzUoNXBPK6dQVehs7Rfbip13/ZlL2KYk8BHaN60jGqF0o9lMiqKypzZYOAvVLK/VJKF/A5cHF1T3j77YNo3jwUq7Vk9hEaaubx64o4sus6nutVwHN9HDwVOYf52Y/ipuJ8zy4vDH0ftmzrgdttxeWysmVLP2bPnolb09iFv09rDMEzzimo2IqO6iaDjzvDN8Nh/7dB942IsHLDDWcQGlpqoUar2IQkpcL+/Z3wlkl3qng99Ni3y7eTB0/qej7s34Jn4uJYPmuW3yykQ/C1GFpHlpPS1WSDrtNh5OvQ725DSdciQlE4843/oobaTiguYTZhighj+zUCl3cLZydF06OZG5f3d/Jdu0/SI2hHtuGd/xpkZesz1oJCtCV/oK0/7t1QOhdzKMGzzAkgnAP5O/lk54u8vvkhFuz/gDxHoPkRoM3fJ6CGhSBK+VhLRMX565IPQBCfbI/U2JF7CAC35uKTrbNpfv94ej92BWsOlMzzRFyb4OWRTBZEQvCF/ihrM0a0uoDxbafRObpPk1bSUDlF3Qo4XOrvI742P4QQM4UQa4UQa7Oygg8CgJiYEDZuvIkHHhhG//6JjB/fkXmzz+DS0V/y9ejzKQiPwGsy4TGZWBflYK7z4wqFm78LcopUNK1k9qlpJgryI9m7twuhZWbIoxnjXwQA3UY93NUf9Yv+sO0tOLYX0lfAr1fAullBz/vii+O4++4hRERYUBRBxxZWuka5y82BDfDD92OeXX4AACAASURBVJOwF4cjvL6kSS4nUYUFjF+x+MQ+Xi+EWN04jx1j2WOP8ddLL53Y9sxYCC3zDhRqhqdGV3iLDE6Byo5rgNaTxjBm6RxaTzmP6L5d6XzTVKw/XMPQgX3o2awNZsWESVEJt9gIUQ+VSXofiHfFp3qV5NJ4PGh/rfElNCoZx4IQ9MXDsl9pwa7cbL7Y8xoHCnaS58xia86fvLvtcXIdGZTFHB7GuD+/JP6cwboHi8mEO64HiqWCknF2B97FS5G+qEZNari9HtZn7iW1qMT9NtSq4vZ62Jq6j3NfupWUo/rbrRLXFtGym7/rn1DAZEXtNabs2U5LTrqYKIS4DBgnpbze9/d0YJCU8vbyjqlyOsg/H2JO4h52t+0U8Bbl9aj8Q/kHkUpwk8TDS/yTKpXI7WX0OUt4ZXhLutPDb9tWtvATP1JAPlasnM0Ihq9ciNj0UuDimykEZmRAOYshUkpcLi9Wq4n9eTB8tl5d5rgv9f+3d97xUVXpH37OvVOTkJAQQiehB6QLilSlKYIVRSmuiLrW1V1FF3Vdd3Vtq7vqz9VV7A1RFwQsKE0QqdIh9JYQSCGQhCSTKffe8/vjhiSTmYRISwj34cMHMjP3zrnD4Z1z3/O+36+mU+reHGmXtGtcwB9+N5PorPV0SPmJjrtTsAV1lDkZ99UkLljxAXbNS0R8PI+UCxBzdsCUhbAnFxJj4B+XwZgLwg7tnCQvNZW9CxbgjI6m/ciR2CNCUwS1aTPxRLyx8VF+32U4tgrlZlJKZIFEja78W9b/5q3gC9NJqqrYbp+EiByGKNcpKNGB3ZgbjwYQhZRteWX9M3j1CrK9CDrG9eK6NndU+v5GIACKgqKq6Bt/RF/yQVmaQzOfw9DNoKraUIZeh5LcmpWZa0g5so/s4nJfRIYkOsvDjMVpLCn247TZeXTYBJ6++i5z7JoPfdnnGCmLQAsgErthGzQRUb9xmJGde0gpWbxzHbuyD9ClWRv6tOocUrJ5qua26UCLcj83x6z/OX0oNjJjGoVNdWmajTmHjjGhdfhAnRwPUQ4zOJbHbtfo3yAhJEgDdKYLnemChoaKau6eH3goNEgDKHY4shmahK8IEULgLJErbR0L+x+Eb3ea+eReTcBtg7fXQVaRQULHn2l6wVL2q14i4xwMO5SGgg0w37dIRvDX4qf5duDdrOo4iTvevQRPTo5Z+lVya3l1B2iUl87kyfNZty6DPydEkvdYf+68s+dZ78rSNINFi/aRm1vMoEFJp1wHv+jJJ1nx8ssIVUUoCkIIxn3/PS379TvxwbWUKEeEeZtUIVALIcAoQGoBRCW1zqJ+Y2TW7tAnFAVcFwcFaaDk5w5I2mMmLBTy/TnoMjR9KJGkFVSdfimv4qh2uxylTS+MPWvMXoKkHsiD2zB2rwSXC7VrE0SjBKCABq5ojvoKMNMuEsWQ2A3JmIM+JjRrwKOH83k338O2zLL8s7A5UQf8jl1rJTte+RDf0W3E991Bz3/9mdiulTftnCmKs3LIXrIae0w9Gg/uE1ZRs7ocKcxn0L/vIfVoJoY0EAi6NmvD/AdfJ9LpPvEJqF6g/hVoJ4RoBRwEbgbGnfSow9HuZvRD76JHC1Q1eIWvqAa/7IhjQuvwh17fER5ZYJoDHHezV4WksdvO4+27Vvm2tvKXH9UCctaFvkgP/Ca9Zodqjqk8bzeFX1nDDywuzbkXuRy8edMkLly5lYSNWWQajXjF+yfmBS4HB+TEd2Brp9EMKFodlC9cvz6DwYM/Li0N3L8/jz/96UcOHy7iiSdOj1vysmVpPP30EnbsOEKPHo35298uDdET2bw5i6FDP8Hr1ZBSEgjoTJkygKeeGnRS77l/yRJW/vvfaN7gsqvPR41iclYWalW33rWY5lGdUMJs8kndQGZlg/8AIiH85Fb7jUWb82Kw7ZbNgXLhtShqbNhjgJKyPfM93bZIjIoSqCVE2X9b05OIaoDa7fKyB6IbonYciGQ15mam+T7tY5swocMQlm9ZSa73KM3zA1x0sJhonwGKwosNY5jpNejbpkvQ+dc99Dy73/kKvUSIKWvBcub3G8uI9bOo17bq0tXqYAQC7HxzGnumfokeCJA0dhQdH7kde1TwInDLc2+x5Zk3ShrcQHU4GDz/A2K7d6zkzFVz97QX2JmdFuRws+7ADh6f/V9eG/NQtc5xwhy1lFID7gd+BLYBX0opw1sMnyyxybQ6chG6Zg+q8vH77axcPoBG7jDSjCW4bLByElzexnRtsSkwsp1g5SSF8tVSaaTyNTP4gmlsYXNoKV6PyWCrcJut2KHRRRDd6pQvcRMbQjZGi11u3q5/D/2K1zKi4AczSJcQcNZjb4eRDH/55aBjnnpqMcUVDHU9ngDPP/9LSCXNyfD997sYPvwT5s3bS2pqPrNn76Bv3/dZtaqsxMswJCNGfEZ2dhHHjvkoKPDj9er885/LWLhw70m97/r33iNQHOqOLg2DfT/9dNLXU9MMaHo1xzZtQvrL/s2kYZilZ6vWhLXMOo6S2B31igchOsF8wBmF0ucm1D5l+jISHclBJJuR7EQSnCpxqm6SY3tiExX2ZRQH/ZqMOOXrk/iBUBPSplFxXLPrGBPX5zF0b5EZpEvQJfSKjGJS3zKPTn9uPrve/qI0SJe+tthHygtTT3mcAEtH/4GNj/+b/K27KdyVyrZ/vsv8fmPNFE8J2T//Ssqzb2F4/WgFRWjHivDl5PLTFXdg6L/dyVw3dGZvWhpiQ+bTAny8cm61z1MtUSYp5ffAGRUzvq7fGJ78MIMe/efTsmUaRUWRLFs2kN0pPfng3qqPbRED340zLX/AdJQoz88sYQk/oaEhkexkF2tZwy3cWqZW17Q/DPovLH3QNHo1AtB0EAyfflquT63ko46MLAz7banqfi6+/BI6Xh+8671+fWZYiQkhBAcO5NOuXQN2H4XcYrMj0lmtf+Ey7r//ezyeskklpflF8PDD8/jlF1MnZOXKdI4dC1Xy83gCvPXWGoYMqeT2pwoCHk947QwIWWWfSzhUF2rsILQlc7D17A4REciMDPTlqxGuhoh6VTd4qe36oLbrg9Q1UNSg9JZpUbUOKKasfjoDSXKJ0L7JyKRb0KXGrrxNqMKGxGBgs6tJjuvJqVNFOWpkFDInJ+Rxt6ry0d3PBZXpHdu5H9XpwPAGzyup6xxZvank7wHk4VSEMyLIYqw6HF2XQubCleiesrmke30U7j1A+qwFtLzR/NLa9fZ09OLQ+aZ5ijn8y1oaDbroN72vISV6OMd4IBBGQ7wyao25rUOFGaOacPX03/Gdxyw3synw1Y2QVElZ2nGyyWY+P5KmpBJJJP0ZSA96IhAUUMBiFqGV80oO4CeNNHawPTiHnfw706U7b6dZyhZ5+jYyehi9WbDbxa59iURGFtK16waio4/RqfVB5tkFRf7g4iqny8GjN4SWJrVvH0d6emhdrKYZGFH16DkVtueAXTHP9+aVMKFcBmjfvlxef30127Ydpl+/ltx9dy/i4807Ca9XIy0tvFvGunVljThFRf5K8+HhAnh16Dx2LLt/+CHEBk0PBGh12WUndc7agtq6N/LoIbRp00t8DTVEwyRsVz1a5XFms0smkAaqH4hG0gbB8QB3kOAgTcnfdyBpiChZAthVB6Pb3oUnUEiRdoz6znjsyulJJQnsGMU2jG2/IvOPoTRtjGjbBqHaUS4cjn7wozJfRwBFxdm4HVEtgtMIkUnN0L1h5o6iENOpLfqOZegL/ltyiTrUb4L9mimIkrsNKSWH5v7M3g9mInWNVhOuofm1Q0vThjkrN4RtytEKPWT/vKY0UAfyC8MvGIQIqi2vLnbVRv82XVm6Z2NQqa2qqIzqUv0uyloTqAG6NIK9D5hyoF4NejaBSpq9SjlCDlP5LwECSCTFFPMd35BPHpcxhH3sDdZ4LiGAn62khG42qnZocHrLKPw6PPBpZ1ZnJOP121HVAL8svYzxY77i2TaXcs3vBFdPh4xC8wvKqWh8M/BnWuUVgnsAuMrykU89dSkrV34atOqNiLAz6fYeXP+1gx1HzFvL41Pqru/MDddeTWHFigMMG/YJfr9OIGCweHEqr722ijVr7iQxsT4Oh4rLbaOoMPSbvmHDsjzeJZe0CG34ASIj7dx0U/WalCqSfO21tBo8mH2LFhEoKkKx2VDsdka99RbO6MrTA+cKtl7XILsON1eEkTGI+tXZ90gt+X38sz4K5CPpVdLocpjQTsTjFADBOegIexQR9tMrfGZk70X76i3zDlTT0FO2wcpfsd18B0riAGR/DeOXz0orRIobJZIx8EoiCnbRIqoNoqT+2d0onhbXDyN91sKgFa3qctDl/qvQ570RHPCPHCAw42nsE19HCMGa+/7O3o9noZcE08x5y2k6chD9pr+CEAJ3s0YIuwoVFsuqy0lkUlm1ccsxI8havKr0PMeRAY2E/lXrAVXGOxMe55J/3oFX8+Pxe4l0uIh2R/GvG6ovIFWrAjWY1T/dfsNCdknJBp0stx4NEGApS+lL/xKj1zCSjYgQHZDCrCyKjxwhrl278NKmJ8n762HNIYE3YJ5T1+3oOsyeMY53JguaNoSd98PWw0DOBjqtvByxqdgct+GHfv+CLmb+Z+DARD7/fDQPPPADBw8W4HSq/OEPF3H9fYP54JOyDdXjeDV45mfzruSDO+ZQVM5CzOvV8Pt1HntsIdOmjWaLsoke9/tZ9X8Q8JR9ZhERdqZMKau8iIpy8MYbI7jvvu/x+XR0XRIZaadLl0aMHx+8QVRdFFXl5lmz2DNvHjvmzMEZE0P3iROJ79DhpM5XGxEON6JZ9SoYzFK78kH6ODqm8FInKv/vK4OeMwyDXdkHiHC4aBEX3tPwZNHmvgb+ckEtEIC8AvRVO7AP7IOtx0hk5yHInDSWedaxLHcp6sEvAYnLFsn4Dn8kzmWOqc8HL7C+wYvsee9/GP4AUW1a0PvNvxFZvB6jYppAGlCUi/Hr1+SuWcve92ah+8sWL1qRh0PfLebwsrU07N+TplfGYou0oRWJoOY0YVNpdUtZ/17S2JHsefdLctdtQyvyIFQFxengwlefwB59cl9y7Ru1ZPfT/+Pjld+zJWMvvRI7Mr735US5qtedCrUwUP9WDpAWFKSPo6KQy1Ha0i7srruKjZ5cyKG1a1ny97+bK7niYuwuF6rDwYjXX6frhAnVG0RRBqx9HtLmgrsRsvvDpKbHsWX6dBSbjW9ixuNx9Ak5TDMEaw+ZOtVCwAXxGnw7HIorNFYsfwQaXQwJ5jf61Vcnc9VVHfB4ArjddhRF8MNuM1VUEUOa5YLC50XPCNX+NgzJ3Lm7KaaYWcxk0DMa3gKVDe8pKDbz/8Mdkzty993B5Z0TJ/agZ8+mvPPOWrKzPVx7bQduuKET9hPdAlWBUBTaXnEFba+44sQvrvOUfFGH5Xh6qlnJ3ysGcxeG4eTDFXN4af6n7Dl8EIHp0N25WRtm/P55EhtUr5Jp/7HtLDs0l3z/EVrUa0uPuCF8t2kNy/duJjk2gVuOHCKh4jANDbljGQy8FQBhd7EvQmPFoWXoUkOXZkD1+/1M3/k693R5BiEEqtNBr9efpOerj2P4/NgizIVU4OuF5kSsiOZHX/klmYsykGE2+jSPl0Nzl9KwfxMUeyFDl07mlxuncmx7FkKAq3EMfaf9B1dCWceuYrczZOFHHJg5nwNfz8fZoD5t7xxz0hUfx4mNjObBITef9PHnfKCOowFHOBLyuI5OPaKxYeMWJvIpH5VWeujojOBKiuZt5ovrrjM3skoIeDwEPB6+vesuYlu3pkXfEyjqebLgi27gyzNv//J3M/f2VWxYLQh4NYQQ9FTfw9vnTywa+izk5cG27aYOQtdk7OXLrA7+BFqYjTPdayrhJbxd+pAQIkjgqnfT8IYFUPLfWLFVqskQFeVgFztRMIPziP/oDH5ep+AQ1G8huCRCCVFqA+jatRGvv35l1Z+PxUnipPK0xvE7wXjMYJ1OWQGXDejKTe8+yfdbllMcKJ/31Vl/YAeXvnIve56eUakV13E25axkbupnaCX9Bel5mdzyxvsEAgKP34dDtfGC1FnQPJ6uDjvZu4vITSsmItZOs37BcgVrsn8iENKnICkMHCPLc4DGkWVypoqqokSU3e2KpB7I9JTgMkUwg7duYHcqCBXzZqMcisOOo349IAMwqNc2gRHr/4InPRfDrxHZKgEh2oVct2K3k3jTlSTeVHvm9jkfqAdyKfvZF1T6ZsNGRzqVCiy1oAWP8hj72IsfP61ojUu6eP2etkFBujyB4mKWv/wyN82cWfUANvwbfPlmkAYOpcGGFRqBkjklpcRmFHPJin+zQe3J0V/MII2UeBYu5KdGQ+j5cInql/8YYVdR0gBv6JdReRpEwGP94MXlZQp7DsW0AJMAdhskd4DtO8wGjBLcbhv33dc75HzOeuDsUNWevsWZRGBHkkBoHloBkkpeI4C2SFpgrqwdQAzr03YwN2VFhSBtYkjJkcJ8Fu9cx+Dkyps7DWmwIO3L0iANMG/tIQo8/tLMgV/X8AN3ZOTy4pxC8jO86AGJogo2fHuU4YP3Et3BrAAq1sIrYypChEiWVkTtPARjw1woyDH7GsDshixZZTfrFsOGWaGqk0JRSBp3FcEKGBDR/Pji6NyZ3ed8oE4kkdHcyHd8Q+udqxi45hdiioqxJfSBvu2goVmCpKLSlrJvT19hAflpaZWfWEryU0OVu0JIXxDU0bhzc6g8AwCGTvsl77FSXlzuMfjzn+czcmRbkpMbmuWA4bojbZHQZvQJh/LXQeYG7Kur4IgH+reE99aXOc1w1VVwrAAyM1FtCnapc911yUye3JcAvrAyrzZsdKXbCd/b4kyQDKh4tTSWHNzItqNpCOx0bnCYgc1G4VBNjWmBE0goPWrp7o3o4USOSpDAofyqdUsK/LloFToat6Xmh9Ue2+rXSM/yEuE3nzQ0iT/fw+Irf8/VexYA0DG2J5meNDQj+JyGNGgamVTlWITdhX3cP9HXf4exeyXCGQUOF3LvWkDicKv0uz2R5R+U/H+2OUEK+n72EhHNGpWUMZY15JRhg2qoZdYGzvlADdCJC+i44QdYNQ+hlayQ0xfCzAEwegXEh3Yo2t1uFLsdI4zQO5jdSK2GhheEkVKyatVB1q3LoFXOBQyP3YBaojOt2AUIGSJkJg0IVHRwBnRdMnnyfL79dhy44+Hif8Dqv4JWDEgzSDfsCW1uqNZnMaq9+fs4i/bB9iMl+yduF9wxCfeRLP7QLpe7RzaiVStzdWHDzbVczyzMOwgDAxWVXvQmsWQFZ3F2ESjoRls+2jaNPN9hdKkDPtZk/0RawU5u6zSltGqiPI2j43CodnxhVwygGRp9wpjeglkvfPDbn/Dk5KA0KoCWZc1mYdyvAJCGRNFCI3jh3gPkbdlF/c7t6NFwIBtylpPnO0zA8CMQqIqNK1qOxa6euFRQOCOw9bkR+twIgJGTipa2qTQdktAuiqueTiYnVUcZ8UcaDe6LzX3cLKEJplZ3HmawVjBX053DpvRqI3UiUKP7Eav/DlqFNIZWDKuehJGzQw5RbDZ6TJrE+vffR6vYEacoOGNiuOSh0PZOr1djxIjP+PXXgxiGxKa0J971AB9OmMlT31/Gz7sTEdLgAlIYwVzcJfVAAsk2wm9ILFtW7tasx8PQ+BJTxc+XB21vhLY3hTcVrQZzboYhn8DRYjNF7dfg7pGNeGFYqLZKV7qRRCtS2EKAAB1IphGnt0rA4rexK28jBf7ckiBtokuNI95M9h/bQauY0Dl1ddcB3Ku+FPZ8bruTm3oNpW1Ci5Dnjvy6iUXDJ5nt7bpOU12jYFRjvJ0iiX1rH28e9pMfIfiyt4slHc0gqOqSzukBXJU0xR6YOY/6ndthVx3c1mkKW46sZmfuBqLsMVyYMCgoN/1bUOITUQfdhr74fVDNMKY6Bc0efwKlaXBljUBB0hUzPZSHmSJKQJxD4e+sWHGdcfL3wvSuEC4PFtkMJoZ3uNB8PmbfdhvbZs5EURUCxV6cboUugxoz8PG/UK/fXSEbcE8+uYiXX14R1K6tKKCgo0uBlOYKR0WjIYeZyAcoGMzkeraHEYg6zqBBiUyffsMZMfg1JPycCtlF0LcFND/Hy5LPJfW8U+Wn9K9ZnvFDyOMKKpc2v4ZLmlwe5ijYlL6L697+M5nHjhLQNXRDJz7azZg+vXly2IMkRAZ39hm6zqxmA/BmVdgLsStIJCJQFid8Nvisj4tl7V3EFRn8ZU4B0cUy7NpUsdu54Im76fzX+86IaJj0FiIPbDG1q1t0qVTg6lzgVNXzaj/uBJCV5OSq0OmwOZ2MnjaNoswM8j8dSZy6HZejGDgIKZMhsA4uC9YZeP/9DSGaGoYBRoW0ho6NwzTkK24gnZbY8eOgGD/h1bKWLUtj6NCP2bz5ntM+oRUBlyad1lNanCVinQnYFUdIxYRNsVHfWXn7edfm7dj99AyW7V/NzF3v0qC+DYSB4Bgfbn+ese0fpEW9ss7XI6s3oXnCbOoFjJAA7NRg3EovF+/V6HhIY1tjlY7FethAbQQCbP3nuzgbxtL+3vG/4cqrh3BFIdqFlr7WNeqGLYIjCpJvCxVVskVA76dOeHhk8RqaRu8qCdIlaEWw41PIDXaICdeRV+mwXA6Ko1oghcrtfMA4PseGn3BlV5omSU3NZ/XqgyHPGRgsZxmv8DIv8Bwz+R/5hG/1tqhbdIq7EJsS3LQlUHCoLtrXr3qTVwhBmn8FDWIVEOackxgEDD9zU6cFvdbwB37TAsGpQdsjBtubO3h5VD1+SrbjF+E9ZnRPMVsrEVaSeJFsRfILkhVI0sP2RZzv1I1ADTDgNej0ezM4K06IaAyXvQstqnaImD9/DzNfew0CYQTaAQ4uDvpx9OiOOByhH1u4Oa6oKs+/MZY2SfX4L3ezgr4MZhGxhDc7lYbO6tmL8VfQu5jFTBYyn1xy8VDERjbwFm/gCaNaZlG3cKgubu34KM0ik1CEiiJUWtRry8SOf0ZVKr8h1oq9pDz3Fvtzwgtd5hQfCqrAiO/TPXyArCR4R7ZsysXPPkJSnuSFL/JBCD67pHKnc09WDr/u3xqkd2Eq763BdFcPYPZ37wF2VHqe85W6kfoAc7NtwCvQ90UIFICzaqNZgI8/3sA993zPnwYYXJmk4rJXrJi3gSv49vKZZy7jxx/3kJ1dSGFhgIgIOzabwGZTyM/3oZf0cDudKsnJ8dx773e0LNrAw8xGIhBIdFSWMAiN4N1un8dH+uuP8fJrd3HNhx9ywY03kkcuW9gcJColkfjw8SurGMS5LVhkcWIauBoxsdMUfLrZrehUKw+IYMqoLhpyK7kbtiN69kA2CJUJVoUNVZSl61Sng76fvMSymx9C6jqGP4AtKoLIVs0o3H0gWH8jwkWDi7uy/qn/471L7KxNisSmSzRVMHKzj4SC0IC/N05w16v3kRjXmPkPvk6TmHjMRp2Ku5AGkImkVUnZoQXUpRX1cVSHqXx3giCt6wYPPTQPjyfAR6u6o8swH4Vig6RRQQ81aBBBSsq9vPnmSO69txfPPTeYffv+yLp1dzFyZHucTpV69RzccUdPundvRIQ3i+v5Gid+XPhw4qc3a4igGLXcJLXjpwubiChMJ+DxMOvWW8lLTSWDDNQwZX0aGqmkkkkGG9nAAQ5Yt4x1HKfqPmGQBsiYv4y8zTvRi73ETD+IKA5egNiEnW7x/UJK+5pfPYRR277ngr/cQ/v7J9Dvi1e5csMc+n76EvXaJyHsNqLatuSid/9Bxtyf+fICybpEBwGboNipELAJPukbga/c8s/A3Hz85GIXhb5idmSlceM7j5c8m0/4ZIkCHEOSgySrZOV9flN3VtS/kYyMwlKXlPS8GG54dwzTJs5AERJVkUTFJcDIb0wn7wq4XDZuuaUbt9xSliOMi3Mze3ZwL/9FF71DF309okJO2oWPO5nKKvdwdrt7YuRlcpGxkp6UOcwYus6mTz6h/V9uD9uIIhBkk807vF1aCxpPQ27lthCxKYvziyOrNqIVmmmxmE/SCDRzUTiiEcJvICIctInvzNCW4evyIxOb0eXJ+4Iea3H9cFpcP7z0Z096JtIwWNjJid8evCBa18rBiyMFD++Lw9ifye76Bv/r7WZ/QzPUaIbO2tTtHMo7TJP6ERDW4NfA9Cg5jkSSiDiP6/nP20AdG+sKkp39YWs7EqY8Qq/EQ7Ruk8Bn8/5htqmeAj16NCZjjQdbGEGZaJuPl1+4FKGqzH/kuZBabsPvx5ubS2OakEAjMslAryBmUERh0GNZZPIt33AjY7A4f3E3bYQaGYFe5EEY0PC5ncS9tQ89OY5e991D5z5jT+n8zoZxCEXBZw9/17qjiZ3bZswl+e83s+dwaGmsqqgUeD00oTllRrwVqVjFlYqkPoITiNPXUepe6qOaREY6GDu2M2532XeVZqhsymrN9XdPOOUgDTB5cl/SHMn4CO28Um022l91FW2GDQt7rD0yknajzLTL75hIW9qjlvyKIw47jpDAraOzlS1hV+AW5w+JY0ag2IPXYOrRAFHbvCRfc00lR1Uf1emg4+Tb6ZBthBXZ753YEZtq47puA3GEadSKdLpol9ACQSTQFXBBqc9jNOHDkoEprnR+ct4GaoA33xzJjTd2wulUiYpyUK+eg2efHczo0ZU3pvwW2rVrwNTFz1FQrxV+yiasPTKSXvfcQ2yrVjRo355ed9+NPTIy6Pk2w4eTdOmlALhxM54JTOEJHuZRHuQhZCXB2Cj5ZXH+Yo+OYujiT6jXoRWq24XqchLdqQ1Df/4UW2T1NZCrovNf7+O5i27CrQnUkvZxm1CIcrp5c6zpXDPl8ltpHB2H225uCtoUlQiHi/dv+Uupcp8gFugD9AUGAFV1Kp66J+i5St3oTDxF8vK8ZGcXkZgYgzOMyeCx9HTWvfcex+xiXAAAC91JREFU+WlptBo8mE433IDNWf0daT0QYNOnn7J52jTsbjcX3nUX7a68srRuVUrJ3vnzWf/+++h+P13Gj6fjddcFuY9X5EPtM/Yo2xBKuX8/CS1ES+7krupf/DnI+dSZeCpIKfGkHQIhiGwZ6jEopWTxznV8tXYhTrudWy4eQc+W1TM2OM6Bo1m8unA6v6Zto3vz9vxpyM20ii97r2PFRby3fA4Ltq0mKb4p9w+6gY5NKm9CkwSQxi9hbmgVqOAFWdeoal5bgfoE7F+8mGmjRmFoGrrPhyMqivpJSUxavhxnvXo1MqYiP1z4cS4jx76J3R7A4QgQCNgQ0saDjt/XeX0OK1CfOlJKbv/kWb5cu4AivxdFCFw2B0+OvJ0pl/+uxsZl7F+PvncO6oBLQFURioL0+yHgREQOLPWBrIvU/RbyM4Q0DGaOHx9kuOovLOTIzp3MmzyZUf/9b5Wr3jPFZ5sh/XAsb/znIbp3X0vTZulkZzdix+beXH9jFI2qadBcmJWFLz+f2DZtUNSTd2axOPf4ZffG0iANpk61J+DjqW+mclm7nlzc+uS8L08V7eeP4MgBtIMHUTp3QrhcGLv3IA8X4Zh0abXOYRgGe3LSiXJGlNRrn/tYgboKjuzciTc/tFVb9/tZN3UqO+fMYfzcuTTu3v2sjmvVQTCtD92sWlXmZBxhh41ZppFtVRQdPsyMm28mbdkyFJsNu9vNqKlT6XjddWd03Ba1h1kbl+DxhxoL+HWNvi/dyTXdBzJt0tO47Ge56ST3kPlnzhGMxUuDnpKGjlCqXlDM3bKc2z7+B4U+D5qh0zuxE1/e+ew5H7Dr7n3EacDmciHDWMwfpzAzk48uuwzNF8bm/gzSMR7cYb5iFQGtqlG9NG3kSFKXLkX3+QgUFeHJyeHrCRPI3LDh9A/WolbitjtRK7kbNJDM3riUR2f+5yyPCoiMDf+4O/qEQXp75n5ueOdxsgqOUuT34tMCrNy3hWGv/YEzkeI9m1iBugrqJyXRoH37KtMb/qIidn333VkcFUzsDo4Kc9auQPN6J1bJy05J4XBKCkYgWFRe83pZ+eqrp3egFrWW8Rddjl2t/IbakAZTf5l11gOc2meM6dBSHpsT5aITOxy9sWQG/gpmCZqhs/9oJmtSt1Vy1LmBFahPwJgZM3A3aFDp84amUXDoENtnzyblyy8pPhrs9H0m2rrjI2DpRLiwiek8bldgeBtYMtFcVVdFwaFDKPbQ2lZpGOTt23fax2pRO+nYpBX/Gv0AahX9Aj4twK7sA3y2+gcWbv81yN5Llvw63SgXDEbpPwFcUaaEgyMCpc8Y1B4jT3jsvpyDaGEsyFShcDCvauux2o6Voz4BcW3acOfq1fxf27ZhLekBFkyZYu5OG6YzxqUvvcqeAYkc6LAOn7OIGBHDEIbRnR6nbVxdGsGaO6HAZwZrdzX10ht3744eJlVjc7kqtR6zqJvcM2g0e3MO8fKCz8I+X88ZQbd/TEAtSTk0iIph3ugnaBZ3jIiWiukvSyzQHsHpqc8WQmDrcSWy+xXg84DDfcKUx3GGJvfmpx1r8VQw9fVpAXolhndXOlewVtRVIKVk3boMtmfaaDl4WFihJ6EoBIqK8BcUECgqYpM3iftWprGt7VJ8riIQkE8+3zCbjZz+HHA9Z/WDNEBkw4Zc9MADQQ02it2Oq359LrrvviqOtKhLBI4Vkr10Db9P6lfakFIRvx7Aq/kp8hfjLfZw9Re7iQ1sxtVYL61zljIXWIskvD/jySKEYpoCVDNIA0zqezXxUfWDuiEjHS5u73sVzWMTqjiy9mOtqCthw4ZMrr76c3JzvabVljKIu/o0JPLXz5GGgVBVWg8dyt6FC0tX2nnEMJPR3PusxF7B3DhAgIXMpxtnt0IkHENfeIHG3bqx8pVX8Bw9SvtRoxjw+OO44+JqemgWZ4Etz71FyjNvojjtGH6Njzsm8sQAnT2BPAzDoGG9+sRFRLM9K7X0mKvWexme0Iz6FzRBdZUFQnPtcry9++T8D08X0e5I1j7+ES/++DFfb1hCtDuSBy4bw619Tpw2qe1YgToMXq/GkCEfc/RosFDS6xuT2bB+L/ERAWISE9nw/vvsnju39PlNdMUAokN9QwHIk/nUBtNjIQRdxo2jy7hxNT0Ui7PMgVkLSHnuLXSvD91rpgiMzXt4I7on7We8h8vmICE6jpaPB2uCDEvxET+mSXhVUgzwHwZHzQZqgPio+rw0+gFeGv1ATQ/ltGKlPsLw7bc7CQRC89G6bvDFrH3Etm6NoqoklmhxHMeLCwMb+Wnhz5ufX5+frP06ixpk+8vvoxcFL0BkQCNn5QbivYKEaPOuqkvTNkGvcWqS/K0ZiDC71TIQQF+7GBlmI8/i9GAF6jDk5HjCeiP6fDqZmWWWXXFt2+KMiSn9uS27seNn0TNR+P3BiWO/386CBcN5acWZG7eFxYnw5hwN+7hit+M/Wtbc9ciw8aU65wBbmtk5vGY/3v1ZSK2c25BhgKZhpKQg0zaduYGf51iBOgyDBiWGfTwqysHw4WUrDSEE1370EWqJQFMr9tGGvez4IYZvZ44kNzcWwxDk5sbyzZzr2bq1K+nHzsolWFiEpekVA8KWZwpFoV77pNKfL+1wIUM79i6ttf6sr5tih+DQy9Mwtm5H+gNIXUempqF9/hV4vcii8F6gFqeOlaMOQ8eODRk3rgvTp2+hyOzVJiLCTo8ejRk5sl3Qa5OvuYYJP/7Ikr//nSM7d/KXHh5yB7Tmj9t6kLKzd9BrHSoMa33WLsPCIoROj91F6vTv8ecdw/D5QQhUt4terz+J6gjWTf/23n/x2qIveG/5HPwNNA6+3R81NRv/j4uxLVwcfGKbA6VJh7N3IecZlnpeJUgp+fLLFKZOXYfPpzF+fBduv70njootgZXwygp4cvFxTQ6zKSXGBZvugiY1I7pXZ7DU804N7+Gj7HjtIzLmLSOyZROSH55Ew0uqV+MvtQCBaY9CXgboJZPb5kS0vRj7iAfP4KjrPpbMaQ3x3U54aQVkFJidg4/1h6ZWkD5lrEBds0h/Mfq6bzB2LEPYnCjdLke54LIQs1yL34Ylc1pDjGxv/rawqEsIhxtbnzHQx/LmPFuckRW1EOIwkHrCF1ZNPJBzGoZTW6hr1wM1d02JUsqGZ/tNT9O8hro3F+ra9UDNXFOl8/qMBOrTgRBiTU3c3p4p6tr1QN28prNBXfvc6tr1QO27JiupZGFhYVHLsQK1hYWFRS2nNgfqqTU9gNNMXbseqJvXdDaoa59bXbseqGXXVGtz1BYWFhYWJrV5RW1hYWFhgRWoLSwsLGo9tTpQCyFeEkJsF0JsEkJ8LYSohsd27UMIcYUQYocQYrcQYkpNj+dUEEK0EEL8JITYJoRIEUJYfcO/kboyr8Ga22eLWp2jFkIMBxZJKTUhxIsAUso/1/CwfhNCCBXYCQwD0oFfgbFSyq01OrCTRAjRBGgipVwnhKgHrAWuPVevpyaoC/MarLl9NqnVK2op5Twp5XHx25VA85ocz0lyEbBbSrlXSukHpgPXnOCYWouUMkNKua7k7wXANqBZzY7q3KKOzGuw5vZZo1YH6gpMAuae8FW1j2bAgXI/p1NL/vFPFSFEEtADWFWzIzmnOVfnNVhz+6xR46JMQogFQOMwTz0hpZxd8ponAA0I72tfuwnnklh7803VRAgRBcwA/iiltOwQKnAezGuw5vZZo8YDtZRyaFXPCyFuBUYBQ2RtTqhXTjpQ3u62OXCohsZyWhBC2DEn8mdSypk1PZ7ayHkwr8Ga22eN2r6ZeAXwb2CQlPJwTY/nZBBC2DA3XIYABzE3XMZJKVNqdGAniRBCAB8BR6WUf6zp8ZyL1IV5DdbcPpvU9kC9G3ACR0oeWimlvLsGh3RSCCGuBF4FVOB9KeWzNTykk0YI0R9YCmwGjjsAPy6l/L7mRnVuUVfmNVhz+2xRqwO1hYWFhcW5VfVhYWFhcV5iBWoLCwuLWo4VqC0sLCxqOVagtrCwsKjlWIHawsLCopZjBWoLCwuLWo4VqC0sLCxqOf8Pr4Vfh8pxAr4AAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "X = np.random.normal(0, 1, 100)\n", + "Y = np.random.normal(0, 1, 100)\n", + "C = np.random.randint(0, 5, 100)\n", + "cmap_lst = [plt.cm.rainbow, plt.cm.Blues, plt.cm.jet, plt.cm.RdYlGn]\n", + "\n", + "f, axes = plt.subplots(2, 2, sharex=True, sharey=True)\n", + "f.set_size_inches((6, 4)) \n", + "k= 0\n", + "for i in range(0, 2):\n", + " for j in range(0,2) :\n", + " axes[i,j].scatter(X, Y, c=C, cmap=cmap_lst[k])\n", + " axes[i,j].set_title(\"cmap: {}\".format(cmap_lst[k].name))\n", + " k += 1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "val_map = {'A': 1.0,\n", + " 'D': 0.571,\n", + " 'H': 0.0}\n", + "\n", + "values = [val_map.get(node, 0.25) for node in Gd.nodes()]" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[1.0, 0.25, 0.25, 0.571, 0.25, 0.25, 0.0, 0.25]" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "values" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nx.draw(Gd, node_size=800,with_labels=True,cmap=plt.get_cmap('jet'), node_color=values)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "nodes = range(10)\n", + "node_sizes = []\n", + "labels = {}\n", + "for n in nodes:\n", + " node_sizes.append( 100 * (n+2) )\n", + " labels[n] = 100 * n" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100]" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "node_sizes" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{0: 0, 1: 100, 2: 200, 3: 300, 4: 400, 5: 500, 6: 600, 7: 700, 8: 800, 9: 900}" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "labels" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "edges = [ (i, i+1) for i in range(len(nodes)-1) ]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "g = nx.Graph()\n", + "g.add_nodes_from(nodes)\n", + "g.add_edges_from(edges)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nx.draw_random(g, node_size = node_sizes, labels=labels, with_labels=True, node_color='#00b4d9') " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "A = nx.to_scipy_sparse_matrix(g)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<10x10 sparse matrix of type ''\n", + "\twith 18 stored elements in Compressed Sparse Row format>" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [1, 0, 1, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 1, 0, 1, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 1, 0, 1, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 0, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 1, 0, 1, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 1, 0, 1, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 1, 0, 1],\n", + " [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]], dtype=int32)" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.toarray()" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[0, 1, 0, 0, 0, 0, 0, 0, 0, 0],\n", + " [1, 0, 1, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 1, 0, 1, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 1, 0, 1, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 1, 0, 1, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 1, 0, 1, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 1, 0, 1, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 1, 0, 1],\n", + " [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]], dtype=int32)" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "A.todense()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 예제 13-1-1-3 배열로 가져와서 방향없는 그래프 그리기" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "a = np.random.random_integers(0,1,size=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "na = np.reshape(a,(10,10))" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 1, 0, 1, 1, 1, 1, 1, 1],\n", + " [0, 1, 1, 0, 1, 1, 1, 0, 0, 1],\n", + " [1, 0, 0, 1, 0, 0, 0, 1, 1, 1],\n", + " [1, 1, 0, 1, 0, 0, 0, 1, 0, 1],\n", + " [0, 1, 1, 1, 1, 0, 0, 1, 1, 1],\n", + " [0, 0, 1, 1, 0, 0, 1, 0, 1, 0],\n", + " [1, 1, 0, 0, 1, 0, 0, 1, 0, 1],\n", + " [1, 1, 0, 1, 0, 1, 1, 1, 1, 1],\n", + " [0, 0, 0, 0, 0, 0, 1, 1, 1, 0],\n", + " [0, 1, 1, 1, 0, 0, 0, 1, 0, 1]])" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "na" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "D = nx.Graph(na)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nx.draw(D, with_labels=True, node_size=800,node_color='#00b4d9')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "D = nx.to_networkx_graph(na,create_using=nx.Graph())" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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"code", + "execution_count": 56, + "metadata": {}, + "outputs": [], + "source": [ + "di[1,2] = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [], + "source": [ + "di[1,3] = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 0, 0, 0],\n", + " [1, 2, 1, 1],\n", + " [0, 0, 3, 0],\n", + " [0, 0, 0, 4]])" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "di" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "gdi = nx.to_networkx_graph(di,create_using=nx.Graph())" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![s0%20%286%29.PNG](attachment:s0%20%286%29.PNG)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "Gd = nx.DiGraph()" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "V = [1,2,3,4,5,6]" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "Gd.add_nodes_from(V)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "e= [(1,2),(2,1),(1,2),(1,5),(3,2),(1,1),(2,3),(2,5),(3,4),(4,5),(4,6)]" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "Gd.add_edges_from(e)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "pos_nodes = nx.spring_layout(Gd)" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nx.draw(Gd, pos_nodes,node_size=1500,with_labels=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[1., 1., 0., 0., 1., 0.],\n", + " [1., 0., 1., 0., 1., 0.],\n", + " [0., 1., 0., 1., 0., 0.],\n", + " [0., 0., 0., 0., 1., 1.],\n", + " [0., 0., 0., 0., 0., 0.],\n", + " [0., 0., 0., 0., 0., 0.]])" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nx.to_numpy_matrix(Gd)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "a = nx.adjacency_matrix(Gd)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1], dtype=int32)" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.data" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[1, 1, 0, 0, 1, 0],\n", + " [1, 0, 1, 0, 1, 0],\n", + " [0, 1, 0, 1, 0, 0],\n", + " [0, 0, 0, 0, 1, 1],\n", + " [0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0]], dtype=int32)" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.todense()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 예제 13-1-2-2 방향그래프 꾸미기" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "G = nx.DiGraph()" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "G.add_edges_from([('A', 'B'),('C','D'),('G','D')], weight=1)\n", + "G.add_edges_from([('D','A'),('D','E'),('B','D'),('D','E')], weight=2)\n", + "G.add_edges_from([('B','C'),('E','F')], weight=3)\n", + "G.add_edges_from([('C','F')], weight=4)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "val_map = {'A': 1.0,'D': 0.5714285714285714,'H': 0.0}" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "values = [val_map.get(node, 0.45) for node in G.nodes()]" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "red_edges = [('C','D'),('D','A')]" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "edge_colors = ['black' if not edge in red_edges else 'red' for edge in G.edges()]" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['black', 'black', 'black', 'red', 'black', 'red', 'black', 'black', 'black']" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "edge_colors" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "edge_labels=dict([((u,v,),d['weight'])\n", + " for u,v,d in G.edges(data=True)])" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pos=nx.spring_layout(G)\n", + "nx.draw_networkx_edge_labels(G,pos,edge_labels=edge_labels)\n", + "nx.draw(G,pos, node_color = values, node_size=1500,edge_color=edge_colors, with_labels=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[0., 1., 0., 0., 0., 0., 0.],\n", + " [0., 0., 3., 2., 0., 0., 0.],\n", + " [0., 0., 0., 1., 0., 0., 4.],\n", + " [2., 0., 0., 0., 0., 2., 0.],\n", + " [0., 0., 0., 1., 0., 0., 0.],\n", + " [0., 0., 0., 0., 0., 0., 3.],\n", + " [0., 0., 0., 0., 0., 0., 0.]])" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nx.to_numpy_matrix(G)" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "sp = nx.to_scipy_sparse_matrix(G)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 1, 0, 0, 0, 0, 0],\n", + " [0, 0, 3, 2, 0, 0, 0],\n", + " [0, 0, 0, 1, 0, 0, 4],\n", + " [2, 0, 0, 0, 0, 2, 0],\n", + " [0, 0, 0, 1, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 3],\n", + " [0, 0, 0, 0, 0, 0, 0]], dtype=int32)" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sp.toarray()" + ] + }, + { + "attachments": { + "s0%20%287%29.PNG": { + "image/png": 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H6lRDajfYv5JeeeWVbe8VDE21HAbIMXcw3co4hSuHaMOhImnIcRxcQ8LTwRWAqtROJf/111/vtPoRK/sXlkez7x0sZyxAdqG6BDQe6iuNd6fbQiFFHUy33/X19dTB6vBAHUy7oBxVzrmD9x71XG8LzTvBxx9/LLJ0qAtpFeWoUKdiiYvA0MGy7+lSoA6G4+zl5f64cog+SKiDbcERzHgq3MFeDnewl8Md7OVwB3s53MFezq462PCrF+5sT/MKRKN9jN12cHt7R29f/8zc/OzcfP/AIJZLyytr68/nFxaXV1bhoExf/8CTnCe5uU+jo6ITEhL9Tp66duXqL975eVVVNf3QTvg17XES9QRWYYkN+/r6F5eWUQCrUCcyu3t6x8YncnKeLCwuUWHHzdkOxoG4g4nW7IK9j2A0S012dnWryR2YocKdmbMdjE2mpmdwmcoapmdmZRJNgq/l6JcaLmTK33MTrdkFu+rgVc9BtNhhcHKbW1oxJk1MTtG5xpU6MjoGBx2PzMGh4da2dupyr+1gL2ZyatodTLRmF/jKTdbkpPHbhHyE3XZwWGhYyOWQxqZm9Wy6oe2gg8vLyn70t/9XW2srJdNSUn729v+anZ2Fv7a21tvbS/m1NTXkAPrhJpD39Ck5Locj2MvZVQeveA7y9/F2D0JW/S23qclJcuJitK9BcTcO7iZrB7eycsSTyH4yrzow6KNSuGgoaYu5uTmM5CLhOnbbwcvLyzjp6/qRTE5OzszM1NfV4+DpJyHrauuuXrkSfvVqanJKdlY2/ZBkSlISls83ni8uLpaVlso/AsDm8Gtra+9lZo5ufhP+rZi4xISE4qIiSi4sLOD8ondrqqsp5+Cpr6ubndGUmMAhkJOcmEiOJRXl5V8c+2x6ehqHgPPT39cHB2d/Xn+aQRcNTpRedi85uAj2Gs6eOYPl40ePKQksx//LFy/gYhSJTbQrw7ZYmL84dPfsVwc/fvSoT7/PxHWKZf7mXeWlixfIyb6XhTvSB9n3b8XE0nCHwQDLpsYmfb121qoqK8m/Eho2MDCA29qszHuZGRnIqamuodOK+u9nZcPJeZyDAaC1Rbvp7e/vw3J6aqq+vh56uR+R4SlwBHs53MHW0LN+l5tozS7gDrZGmzpPTdPLLjL57qG3rx/5SMocfhbteeDkdnR2DQ4OyZcNPb19o2PjiKrR0bHh4RF0f1d3z/jEJFZ5bQfjQlbHE3c2fh8scaKD0QJcyLjQ6EKGqWOawVAO5bHEFoZVB2D8iQ6Jcx08MjJKagQfy+ERDGDj6pmFUY+SpOFSoLeqB2w76ODCgoLxsbGaGm0+RlO4vKdP6WUDkZ6qPcwBUdevk2MgNTlZeK6Dh2gvh2+ydkJKUnLukycisZWS4mLhuQd708HrVo/fZqa1Lxf1SsyvOizfK3jDywbfBBF8S/8+JTNdm39gbr4IGhsbm5q0B7GdnZ3t7e1Q9Pm5OSqGS6GnW/tG9vtZWVrRvYM7eCdUV1UJbxN6e2ZgoL9feA5jrnmXcAd7ObvqYNydGmYjbmv8kR2Jcx187eq1D37/QVpqGk7ijRs3s7PvY0qsnlk3Me5gCUewV7GrDi4rr/QUm53bgwf3ngjfZHk5u+3grMxM4TFuCUewl8Md7OVwB3s5u+pgnia5P7vt4Ln5hcSERPogx8LiUkJC4q1bt1dW1/r6B+h7F2BRUdHt7R0J8QnwsSo9LZ2+5mF4ZJQ+EHIAxh0sOaAIPuDo5w6WsAZ7Fbvt4L4e8XfQKoODA8Lb2JB/RmaA/qTFFkODg9FRUeRfvniRHMu/TzTUf/f2HXIiroWXlog/C/NldtvBc3NzWffuicQmz58/vx4RASfm5s30tLT72dmPHz0K9PdHTmhIyMULF3Kf5KKM7LD19fXe3t7CwsKM9HTKGejvDz5zhv42Kdv2O/DFhUX61ER3Z1fIpctwroSGosvPnD5TV1eXlpqql/JpeIj2criDvRzuYC8HGiq8TSw6GGLZ16f9xS3jQRQXF1v+DA9HsJfDHezlcAd7OdzBB0Fig39ig99WQ445U5r2FIGYbTmuWbO+3IHJDeHsuJKW4wttx6k9H5SU6Va+6diybQvoVlquGTnFZR+UVRypqM7pH6R9OchoWMZIaLpmYbqRI5Nqpm7T8Vt+OW+XnMrsNvxm84HZyMwyB/BBQDFpCNHNHOswFlvKADab/YC0tWrbGLZR7bwxgE1GcWjH1AJ2CmPVlpIVTRPiywVtMRqqB7CIzwwZqJoZwlg3DmDGOQzBaTIZzC9MbKkGsBpX5JsjzSr2rM1cm12zCGAtzMg2c4xmWiU2sVqlmSFzS/JIpc3vOhQBLI0CdUvOZlTrSQ5ghmH2HUO4mo0DmGHcF0O4mo0DmGHcF0O4mo0DmGHcF/p2dPtwADOMm5KdnU1fp2mHnQTw9w7lm02sQ4065L/xxhvkMAzjLNHR0eaPxxrYrwAG8BHAx44dI19mYhkcHKwmOzs71eS9e/dkkocAxmdxWQBj+Qd/8AdwbAWwIWINyZCQELU8w/gmP/xtwCcxZYYHV2E5PWK1jrtEiCFcSYRFgmE8k/czX71R77da8e2RnD/GcmPw5jeiY79xOwHLhY3nrT84SsVe+TT/tWO5fxZQFFO45c+IbASw9u3TEg4ShtkvDme+GlX5PhwEMOX8u+jYH2Q/jGzvgN/yIoALDsc1kK+yZwH8l8c8xnIYxluwDuAnrMAM4wl40hyYYRgDf3P4zKe3q09mdql26SErMMN4Avv1Gsk+37vZwraHtry2/efpGK/koAOYLrhno4sirTO+sCqvRYMFFw8bcqTZWWVpKH8if9CQabb3snsMOZ5i4mwyvsSBBrC8zt7N0oLEkEkOrHFskZy158+XVp/LfHN5ygHwH3fNvHWnDQ42pxxplNQLvticfKr/+7Gtn+T0/2tmN2qQZaiYLCNtamlNTbqP6cfE+BauCWBSQkMmOQZTgwchKn0YbU6o+TBDyIlCOpY5csige1HyYeRzADNui+VTaIPt/S305fItX7D/uHNLZLLtzMTZZHyJgw5gwnDlse3SxGllfA/XBDDDMHsCBzDDeDDeEMCNjY3yz5LUHw9B5vz8vEjoScrB8tChQ5QpyyPz1VdflT6Kra6uwqEcoqND+3y56hBUm6GwAVm5HXp6tnwCzsxbb71Fjmw/wH4lIktpzLe+9S1ygNx8ZGTkzTffJH+vkHvMy8vT26Ih90jQTrF3SqoYfoxQNvvYsWPkoDYs1WLh4eHCs4GhThAXFyc8HfXysIR2CiwPCo1sbW2F8/Wvf51yDh53D2CcL8NJN0OnlXpaDeBtOxhQlBJqAEsoh0Dl1FUygNUL1FDYkLSEysjrbHFRewH2la98BUusovyvfe1r2jrboKREZCl7VwNYRQ1gKkx7B3RZv/POO4g02hyrfvzjH8NBSeQbrlfDeUZSa4qODD8V+wFsGFksayC23ZGsE+FHjuM4clAirUM5B49rPom1f1j+fJdEnOyXXqLLEagBDChTJHQox4BBgQlbhQmqjRBZNqAAJmyFn4qoVEdkKTgSwIQM4F2iXuvqsUgsA9gWDgbwtsOcJWJjHZFlA8uDEmkd+xfe/uFtAbxj5CCtDr0yUEUv6d1suKQoEuRWdL+AYKivr//www/hq9EuajFdLlQn8uW9MW6nqSSgHEJkbSJylVbZueJtQfXQUt5T6NULZJ3qyZElZaZ6pPI+Qr3bp9EEmVhKGacxlHwZG6hK27EOkvYnIKKcjshSMsm3k2lrjJMlcfiysDwc3KfIe0MqSVAOEOmt+9pzPD6A0eWIFvT3d7/73aysrLfffhuZGI/lKXvttddIbymToFVShXAt2g9gNSqwuTreoxK1ThnA1dXVCGB1lS3olhUHgpLq5e44tItXXnkFS9lUeXnJI5K3lAZoc1qqkwIzKEPFgBrqtJSrACWBZQATlEmCTOdfBjCgArSUASyPTu0mvTKByNpEjiOUBNI3FzaAMZS6BjuVhemaQXLbAKZd0yWk5u8tXhLAcOgKoH6V3aaOl5SpdjyQoWg5TZIBrHeNBu6U1GAGlgGsIitRMVTy8ssvY6lqkS1wsH5+2q8ihYSEyHtRdReGms0YzgBQ5xGWCkw5QE1SSRlaOHC1GVQS2BqSLB/8UB8R1K2Eg3fI2J3wrHwcprzRhSMLOPIIigqrdaoBLFELALk7Q/4e4p230Op1wDBejDcEsOVdH9382MEwKP70pz8Vng7WSkTW3mHrVhYYbgSwd/WRD8STmgQMSosccmS+zLHE8SnDtpLOuBBvCGD9ehaYcwjKlwFAZSjTDJVRkfnkyGvacGunPqSRhSlUKEkF6OYQOfLmDT4VsLyTJ7CKiknkLZw6IlDbRAkFWit9DmDvwOMDmK5IFcq3pcBS0GRJwn6SwEX/+uuv0/SJCshJDmEOYExuaX6LVbixVwMYNw5ymmdrKm6YrxqSlsh4owYANbwdnPOrUIXUcsbd8M45MMP4CBzADOPBcAAzjAfDAcwwHgwHMMN4MBzADOPBuCyAl5dXJqem2fbcnuYViFPM+ACuDOCZ2TnY/MIi/sEWFpfgUyayyaECWMwvLqk5L/I3N4FDBr+2tg5L5GF588ZN6S/pO21sbFpYWi4oKISvWoCfP2oxZKLCyPCI6ppa+EjNzi9QS2hJ1aIMFmoLn+Q80XIWFicmp7DEvq5dvVZRUSkL7J9xAPsULg7g6ZnZ+oZnzS2tI6NjT57kIqlei2TRUdELi8udXd3ws+5lYXkj+gbKJyUmdXR2FRUVU7GGhmddXd137tytqqpGAE9Nz+Tl5SN4sIQ/Nj4Bv39gECWxCaLrfvZ9Cj9piLqV1TVk9vb2zWyuyi8ozM8vQJ2oJD4+AUNAd08v8tEGKkAx/3xjo7OzC87Dh49QQ35efnt7B3KwNjPzHo5rdGy8t6+fNtlX29cALq+oMuzOl02cFJfiygDGhc6253YAATw+MYmBCSPapYuXiktKl1dWceuuXtk0EGPMQkmsuXDu/OLySkJ8AsZQjHQoD8f/lF9Pb9/DR4/znuahcFJSMpYY47CWKnF/EyfFpfBDLMYJ9lyBEcmGHA8ycVJciisVeHxyim3PbXJySpxixgdw/UMstr019wlg+lONhYWF6elpOOfPnsXys6MWf9tUkJdfU10jEpvMz8/fvHFDJBROnTiB5emgIEr6OC4O4Cc5TwL9A478/oMroWEfffjR9PSMei2y7cAOIIAjwyPOnD4N57e//vXMzMypkyeDzwSPjoyeCz5bV1tLZUCk/rdTs7OzlCQC/fyxDLscSkkiOSk5JycHTldXF+WAyYmJ0EuX4byvfKfH8+fPA/QvJKE/sVpfX9ezfRdWYG8z97yFpjCem7OeN66srAhPwRD5BIm55SrfhB9iMQdBbY12h9za2vpEV1oIqZ6tkZSQGHI5BM7/VL5ZBUre3d0N5/X/9J8oB0BvIfgioVNRXi48X8XFAdzZ0YlewTRpfW2tt6cXObl6B4OzwdqUyf/UKSzPBAWhRz/56OM7t28/a2hAUi+ykRifgHvvtra2urq6f/i7v1taWkpLTV1bW8t9ktv07FnE5p+/R0dFIfOff/xPlMzLfXo9IuLTjz95/7eHL1y4gJyAU9pdmWRyYhKacPbMGfjZWVnY9npkZFdnZ1Ji4pWQUCkjyYlJqckpqSmpt+PiysvLgwICZqan/U6eHBwcHB8bozIXz53H8lxwMJZng4MnJiZSU1L0NeLi+93h9ynJMDvArRUYkTM4MCASew0F1SU9gPeKxcVFhOjw8DDGFJHF6JACY+yL0Z9Lya8iAZfOX8CgDKeosJByAMZEmuVWlFdQDqA7bfW7Vpqbm7GkygnoOZaoKjhIm6WDtlbt10+w7a24uJBLlycnJyEYjc+edSvzbeLCeW20fXD/PiUxFpPjznjGLTQiWXgbG5npGejaFr3nCAQMOcgHUEv4EEMs6UJBJsQ55/FjrdDmKppNQf8xoUIBujdDJnzkIH95eVkrDUGenMSStgIxN2/+/v3fkQ7jYlpdWaWtUAOWyKSqaDmnz9YePXyIJcCV2tHeTqvkfldXVnCAlAmQOdDXDwfX3OLCgsy/dvUqllp5fSvUjBbS2tHR0fmFBfUsMT6Ch82B1bmTxPJRJIWfZXkEM5ZyFTnq1Y+IEp6OZSUSkgWUkcWoKtoLrTXwfLPB6lYy0z6IXnUrOkw51jC+Bj/EYpxgdXUNIwhDiJPiUjiAGSfgP2ZQTZwUl8IBzDgBBfDY+MTc/ML0zOyVsCsFBYXLK6tTW/+MTPwxw/jExORU8JngxaXl/v6BS5cu/+vPf/HgwUNsC/M/5Tc+OfX7w++fPHFyYXEpmf+YYUe4MoDFjQizp4iTuz+wAqsmTopLcWUAz279c1y2PTH+g36fwsUBHHU9CndTPb196WnpT5/mwaersLOr+/79B7ExsQnxCX4nT62ura+tP09LSw/w88ftmfzrU/oLWNiJ419iW9yqIRP/oTwc1EnFVtefJyen1NXVU9K77eADeNtn4M+ePcOS/pghOysby5Li4tqaF5+aJp4/fy4/oqPy2adHhadAn4iWH/vxWTxGgZ0q7Mt2AAH8u0OHb0RFdXV1XTx/ITQkZGR4JPj0mcnJyS8//wJrzwQGhV6+fPLLL6cmJ2c3X2JLHt5/gGXO45zS0lI4DfX1erYGAjjAX/tThzf+P39KOcTJ419i+eMf/T0liUC9pCQjI0N4PgY/xGIODjlFX1m2eD1OH60xMDNtHAIAfYpmbW1Nvg/3WVwfwL292kegp6amroaFUY7kww8+EJ7C48ePKysrr4QaCzPuT0pSMpYQz4S7d+G8+6tf6dkaiF4K4J//y88oh0Dm+vp6o34TLikvK3vWoOXQxyH/s/IHD76G6wOYPtqKofR0oDb/USc8F86dI0cdaIMCAlJTUkqKikWaYXwYvoVmDg5S4LiYmOKiIjhl+jSYaG9rJ6eluYUcSUdHx9rW12MY0B8+0ObSpMB070afXVW5HhmJOzvyExMSFhcXTwcG4sa7sKAAsoHyrW2tLS3a7u5lZlKx4uLivr4+OFTbwsKCm9+lcwAzjAfjygAuK69k23ObtfGtF4xX4soA5jdD+2H8rZQ+hYsD+P79ByWlZcHBZ/1Onrp3L2tyanodc47nG5cuXIy4ei3kckhMTOyVsCu5uU8NlymbLeMA9ilYgb3NOIB9Cn6IxTAejIsD+NGDh9HXr4sEwzBOwgrMMB4MBzDDeDAcwAzjwbgygOfmF2aVH7Zl2xPjp9A+hSsDmC64ickpRPL0zOzY2PjY+AS9C9H/Yl97yYRVyIyLu9XW1o7k4NAwlgODQ1gODY9gKQ0lJ6emaStUhWopH1XJAiOjYzk5T0ZHx5Ds6e1DYWTSWq8xDmCfwsUBTEGFGEPADo+Miridm4c/PDyCVQg2+HCQxLpBPXQpgLFcXFqWEQhHD1utCmyC/yiYEedUz+jYOHwsqfyQPhYYRgEvMA5gn8KVAYxYQ7yx7bFxAPsS/BCLYTwYtwjg/r6+oaEh/1N+a2trnx89ur6+PtCv/TjQhv6nmPn5+ZpvxdTUVMS18MrKSvjDQ+IXknp7e+fm5mZmZgYHBiknLCTk9q1bd27douTkxAT94kmw/ivVKvX6VzTJX0uZnZ1NT0sLv3o14W48/V2oaNhWpqenJyYmREInN+eJ/D0klcePHglPJy4m9l5mJv1MYVRkZEZ6el9vb1JCAtqPXaP92GlmejoVBtSGC2e17zmQXyVXXVVFDuODsAIzjAfDAcwwHsyeBbD6634MwxwMN27c2JsAxvRscFDMORmGOQDCw8Orqqosf15XxYlbaNQ1OTnZ3t7e1NTUyDDM/tDa2jo6OurgT2HxHJhhPBgOYIbxYDiAGcaD4QA+CBIb/BIb/PUlmfTNjmYpLeLXvZ73nphtOX5w1mzK2bSVSe2L2o9U1nxQUv5BSdkLKy3/oFRJOmBHSso+La8Irq1L7+6pHZ+YXNrmBxDtM1fePBKarlmYsiRH5oRlKMsXH57ZE06ktrjG0rWvy+cAPgg2Q5Si1BC0augK/+AC2HbEGkwJYCUatejdGs/2TS0st5WZpeVHqmu/qKia1T8t5yAigLeEqxLDagBv5ogt9whjXB2UneQAPjCUECVDoKphbIxhlymw2TYj3BjAL2JvaxAKexGTSqbMN2Ra25GyCjoJ9tECWAtRNWIzNuNWT5JRUs8RW+4Rhrg6MOMAPjgM8Wnlq0l/NwrgTbNQYGNw2jYZ53ZM1ra12iOVxt8KN7BFgVULRRgrwvsin2+hGSexilKDbcn3jABWzRx+cLaGoj2jwrbLT5l+3EwyV94iQlQo7Za7ZT2MZejqPgcw4yybkWkresmwlsxFAWx3PuxEAAvfdvTaeehljuHNnJx+688CbnmIJW+e1aVwaJUW3mLLPcIYVwdmHMAM47YYw9VsHMAM47YMTS8ZI9ZgHMAM484YI9ZgHMAM484YI9ZgHMAM484YI9ZgHMAM484YI9ZgHMAM484gRO3YycwulOEAZhgPhgOYYdwU+e3CduAAZhg3pbu7W3i2cTqAv/PXwd87lG82sZphmD2ipKRkL7/UjrAfwJGRkS+9JOr8yU9+Qg7DMDsgLy/PNQFMMUwBLJNyCf7gD/5ATZKzuLiIZWdnp56nZQJUSA7D+BquCeC4uDiE35/8yZ/YCWBygoOD1WROTo4h+Ytf/AI+w/gmrglgLCkOtw1gVWzlUnUAfIZhbLF9hNCv5kkcCWAgw48cUldDviGAVQX+/ve/Tw7D+Czv+MV9mdJk+ACWWLfJ9kGyswAOCQmhCNRDUjiGpCGAjx07hiXuwJGkHHIYxjfZlwDeJ8zhWsU/jct4OO9nvrrR/p2p/P9t+PEfr1Z8+w8TUr5x89Yf3k3+xt2k8b/x6z9+E2VmF9e+/VHOnwUUwWgriScFsAGIs/AYxmPRAnhjY+bZB2uV34aDAP6Xp/l/mf0QYWwI4O98Uf6/+zdq2yh4cAAzjBdgDuDvJCT/4P4j+OM/9Bs8pc0WZ5efI4DhmLEK4GaxbhMOYIbZL8wB/EVltb5GC+CWHxxt/cHRsZYBBDAZrZLsWQD/5bENT7EchvEW+BaaYTwYDmCG8WA4gBnGg+EAZhgP5p3AuyfSO05mdJ3M7JJLsW4TDmCGcVP25o8ZOIAZxiVwADOMB+OCAI6rH//ezRa2PTRxZhnf46ADWL3somrG1CTbbkycX8bHONAArh5asLza5FVotuDiYUMO2U9Tu96602bItGPfj23918xuW7WphmKGHI+wobkVcTYZX+JAA5guNTil/XPyyjuWOyBXkellNeCvPX+u5qs+QLCFVoya89WtUD/KGEpKh0rqG2nAH5xdkTnLa9patTa/Au0npGXSrYzazPgUrglgLGeXxV4p528TOmitLEBLGTxIdk4tf5LTT0mE1uOumd8/7EM+laQlOWrILa1qbUMAa+X0Mgjpkv65e23T8GUAyyUFMJk5gGFUzA1NOzzGx3BZAFMOIF+dD8tMLNUAg0kBxBKYFZjsvewe6eNOm+6fZcnDD3qx/Fm6dqus1o9Qlz4ZBTMHMOO2WH4Sy2D7EsA90+InIWSOpanBoxZDTOpba0hZlqZupZaUoSvSGxs0kYYjl1KBKZ5hHMCM2+KaAG6bWJKXHbRXriLTywqkQqpQjnyIRTky3gyGfENJWsIotuHQbTbtS86B5VYcwIzbcqABTFNK86UmL0G2Hdv4wqo4m4wvcaABDP4xuVNec4cf9EmfbZcmzi/jYxx0AAP1/plt9/YXcS8m+Yyv4YIAZhhmr+AAZhgPhgOYYTwYDmCG8WA8PoBfUnjzzTdFrs6xY8eEpxQbGRlBUv66EsjLy8OGWEXJxcVFPz8/OCEhIVRY8uqr2lf4SgcbUp1qbSA8PJwctU5ydoPcHXD816FwCLKMvulL8/Pz8EtKSihzN1CFhMja2HjrrbeEt4ko8dJL2Om3vvUtkasjVuioOdRs9UxKZC9IZDFClNMx5JBPmYaWSKgkIbKsDgp85StfwbK1tfVrX/sa5Rw83qDAX//613/84x/DUQN4dXVV7QBKyhwKAFl+ZwEsMQSwRK2THPvQBWELBLDwlD3qxySgHAMygOXmdOHuVQALT0Fvi0BkbWIOYImhsCGAAY076ilSB2hLDHUeOnQIS5npYEsIZEpEFgfwtnR0dKjnyxJZABeHDEiEtHTq6+vh0CoZSDKA9R7RasC+sFRVjlCDE0la2lFgJLGkHZFvC5R55513cF1i16+//jouR1wQyESbaUOKMXmZmgNY2/dWaK2Kmk8xQEkZwLiO0Qw4uApffvll7A7tgUNX58mTJ5GPTV577TUk4chzC2TNEuQYkPlYIiyxO5mpIiNT30goMKBMQIOpU6FiqBOQT5m2MBfQN92CrcyDx+MDWJVWGcCEvPTtQNsSlINRX6T1XzOlTIAklq+88gqWMoC1FVuhYgDRIn1LEKt04yCLUQCTT5vTsKJiqBNJicjailRgA2oA0xhHlzsVlr/8SsVkDQh1ILclDOcZhSUiS6nBlu7JyFRvLgz3xgb0PQhE1lZkneoNsK3CBhw8KInIOnBwER7oN3LsK/YDWD3L6lUioRzLAMYwQQ5hUGBA+QSSSUlJ5FCOOQ4l2AUVwyYUwAhdCmOqXy/1AvO+JCJrK9sGsISKYUmnkZRWFqP7T5JBA/avdRyLSOjYCmAZY6Kczi4D2FwnOg5LylRvJcxwALsAQwAbkFoNRJZVH6gBLO/BDBjmwLZADeTQrQRhf1upwIQ5zAyISnUsCzsewLYO1lmoMYTIUrAVwGaw+S4D2BJZmKYqBE0u7CDK6YisnTZgb/GqAPYC1AC2f/nuOXsVwMxB4usBLMdOebul3juRWkpNxipzUJGU0Z0w3WcC+FhSSEjJfeONN/RqXqKJtESt03xvTxNUicjVEVlKDehOchwHQwZ28eGHH8KXm8tDJigT0MlBjrojecbkkaozDhyRrAEHPjAwQGdMit5rr7323e9+F466lb5bDdxB2JmAAFFOR2TpUI46KtHzM0Jk6VjKryhnugugDoJ6q30toRwgb/ccvFnbMZ4dwPa7dltwMeEUU//ZD2BKAkN3AssAJugql10oHcOtPjaMjo4mXwawvKqwlhwClztmy1lZWeqlKadzagSSA2Sdlsj6cQawuUziEkSD5V5olUTuCDgYwHITStIBypZjW3UrQKv0vYkmqQcld0oFCMpRUXvTFpYBTKDxOw5gcuQ52SdwVj04gOmGk95zwKElMnt6el5++WX4NBBSJi768+fPIymnf+TQKOB4AKv9BJAE2ApLgwLra7YZg2lOKPvbfrBZQu2nQUEGiTpGqM9yyFGxVGBL6HDIUUsiiUqwVANYK6oXlgEMSIFplf0ARmdhiXsWFJPD9LYBbHjGRpeHCnIcCWkCFWJpCGCcTNqXZQDLBnAAOwT1kHqnivMruw19T9cuzqzMlFcz2G8FdhBsaFbg3XP16lXUTM/DCSQljlzHhoOlE4Wzjc1lAMPHku7z1QAmB6gBbInlLbSKGsBa03Ucab+5DBpvvv0xQPlvv/02OepJQP9SF6sK7Fq8OYCB/QA2lzQgA5i6FpgDmPLtBLC8rCWGSiDCra3a3/SGhIRQkKigWuHpyKSaL3dhX0IJ82WNqiSUgzMj0jqUKX0saUfykTLFnhrAsrCtADYfqSGA5VaG02VZmwFsYnh2AOSGhhrMLbEEzSOBRWw7EsD234nsFd4ZwI8ePaJBnTRWlgS4K5P3OQ4GsIq8mOQILcGO7HeqLdGwH8AG6HAoQigHOBXAZugEAsvNDZc7QI5lSfPpAmoA2z8/5gDu7Owkh3Issb/WERwMYBXDHJgcAxzAO0QNS4bxbrwwgIG8tTPjyNwJYFiViKz9RO7FcCNgaC21hxBZW1HvNunu4/XXXxdpHbmhs3ccjHvi8QFseS9nJ4AtQXnDp+T1GBGIrL3jl7/8pfBMqHHV09Nj2Du1hxBZW7GMN8vCckfqGEEBrFbCAezmeG0A01UObD0WoiWmxPTCCWBiIz9ioW8qoJz9g0KIQgW7Q1INXfl3BUBrzSaUQ2DWQBN7Nd5EOeUMqDviAPYOvCGAxXW6+R5SJBSoJKCkfGdjCyqmQvkUJPLphVnnKSoQEurzGPW+lHSeHhqVlJRQhbQLyrS8syWomIpYsbkKjow3ylFBJkYoOIYdcQB7NB4fwJbgShXeVlRlFlnbIUuqMUl/628OYHonLBWPtlVvzqkAhZCsGfqpNUjHEMBqdKmocYWtyEG1hnxCvlCxfOouCunDnwxgkbXdnxMwLsezA1iVX4I+CGEngIW3I2gXb775Jv11+7YBjGb8+Z//OQUwNsRSBjC9Y6BMO2+zDAG87cc81HgzjCPAzo4ICmAVWaF5FeMOeKcCew22FNgWuxRMOwHMuCccwAzjwXAAM4wHwwHMMB4MBzDDeDAcwAzjwXAAM4wHwwHMMB4MBzDDeDAcwAzjwXAAM4wHwwHMMB4MBzDDeDAuC+DqmrrJqWm2vbWZ2TlxfhnfwGUBXFNbj6uNbW9tfoG/0M+3cHEA44KTS/xHVyEMedJBPkzmUFJuQvlUDA7yl1dWFxaX4MJfWV1bXFqGQ+Vv3riJZWdnV1xs3NDQMHxprW3t2PL69Sg1EwZZW11bpxpov1jSvrAL2gvtHUvaBEeHJZVpbGxCfkdHJ5bDwyNUYP8MjaHTy/gIrgxgXG5LyysIttzcp7j4RsfG6Srs7OpuaHhGflZWdk9ff3JSckZGJuU8fZpXVVV96ssTuGG8cP4C7hqRiUv3/LnzaMSV0LC19eeoEz6WqB/2rLEJUY2Le+35BhwKLexChhwMUY0AjoyIhI+Yp8z09AwURlXYtqOzKzLy+pdfHH/48NHDBw/DwyNQQ11d/fmz527fup2ZkZmRnkFboTyWtXX11dU1paVl2EtTUzOW//aLf6UC+2f7HcA9vX3YCRuZOCkuxcUKDCXERRcdFY1ozM8vUK9Fsubmlvb2jsLCIighYhVnraend2h4JC8vHxvSEsVwYZWXV4xPTKI8yty9cxfSV1ZWXlpWjm1R85OcJyh2//4Drdq5+ZLiEmz4k3/6Z9oLjOTxdGAQlsFngikTZbA5lgnxCVgiHRoSOjk51dbeIeUUA8rjxzlFhUU4BDQSe0dOU3NLbW0dlmghyiDCscQYQZvsn+13AHf39Br26MsmTopL8Yw5MLTUkCMNUQ3FHhkdM+Q7ZIoCb2sIDixttWTedgsP0g4mgLEXGByMWZTEghoAK8gvwGmSa7EahgLIxJIKUyaVp6qOfXoUN0fDI6OU6REmTopLcWUAo+/Y9tYwvojzuz9QAGdnZWNXiLczp8/ACbl0mYKQRrfcJ7lI0s0R7q0uXbx0+LeHkEM3UCe/PAEfk6Zf/uu/wcHkYmhoGE5HRye2xTwIS08xcVJcissCeJXZH8T53R8ogDFV6R8YhMA26nP7waHhsfEJ5GPKQFd2V1c38pHEsqWlFbqKAoODQ1QYE42BwaFR/abpZvQN2uSorsA7vJNykYmT4lJcFsCMJ7Lnc2BoryHHg0ycFJfCAcw4QWdXN/STjUycFJfisgCuqq4dn5xi21ubnJoR55fxDVz5EMtwQ8K2e8MtqTi/jG/AAexV5lYB3NLSguWxTz/FsrioCMuuzs6MtHRt3VY+O3pUeApB/gHCU4iKjJyampqfn+/s0H77m3FlAM/OLwwPj2DLsfEJXHnJScmzzryYZTPbwQTwyPBwc1PT0tLS5OQkkp9+/Mni4uLY6GjC3fjl5WXkjI6O6gU16uvqsLyp/6AcrraBgQE9+wX0EzCTExOUVLlz+7bwNsGVlhAfDyfvqcWvUvogLg3gufncJ7krq2uVlVWTU9N3bt8xXI5sztrBBPDVsDDIY1xMzMVz51dXV/1PnkTmubNn/U+dgvPJRx/ppTYm9JhsfPYMyxtRUVhWlJdHX9ec5KQkLCWB/v5YvvO//oWSxOnAQCxLiospSZwODBro74fzNPcplv/9v/03Pdt34VtorzKX30KvrKxAmUWC2X84gL3K3GoOrLK2tobl3JzFu9OZGYsn5wsLFgciP6ay359X8SBcFsDoA4zWzJ4jzq87MTQ0hGVaSiolzTzJeSI8hZgbN4W3SXFxcWlJKZyoyEjKYVwWwIzvQAHc0tLS1NQE5z+99h/1bMHU1BQuwZ6eHpHWKSosrKyshDOoPPSKv3Mn4JQ2W6YA/vv/6+/0bJ/GhwLYkbkZ3elJ7Aiag4dsWaEh0xdQD9ny1Nm/ZzZAtW174foCLg7glOQULEMuX/7kw48SEhKSEhMpH5w6cSIsNDTn0aPTQUGoPzsrC8szQUG4874VK36o/rOjx/p6+4JPn4Yf4O/f2dF58ssvs+7dQxLLkZERvdRGoJ9/Z2fnlbAwSr73q3fJSbh7N8g/oL6urqOjg3KoqqthV7AvbEWZgQHaC0ladeL4cT1PcPnSZZRsfPbsXHDwsaNHI8PDS4qLb0bfuHrlKhVoamy8FXcrNibmJz/+57GxsbraWpSn57QF+QVUhmF2jIsD+Fzw2bm5OYTx9YiI0ZER+TwDsddQV/fZ0aOI1YX5eSRjb8Ygf35+PiE+HjddVAz7zXv6dG1NG6dxGBiYl5eXobQQOsQMjd8og0xapW+0cT8rG5mRERHDw8NdXV3JScn0wkOCVfcyMmZnZ7EJqkI9qJxqm57e8glYOnfYY9T1qMXFxU8//jgyPIJeUd69cwfL+9nZtTU1ZSUlSQkJaPzszAy99sSG5PgCdAuNu2Jb10mzfmutgv5KSzXOmfNyn965pb0ZxtWC5czWviAmJybRcegsekeNnsXFMzY6WqXfkNdUV6MNuKJI8HHJaZtMTqIv0Nfj4+NI4upCJ8LxCNz6Fvp3hw8Lbx8ICw27eeOGSOwRvzv8PpYffnCEkgxBAfwkJ4eSFeXl5Ega6hsMlxCS6WlpcOZmZykHPH36lDJpDiw/+yEHdIABt19/UUxEXb+en5d36oT2pnptbR0lEa64Y6K30xnp2sfCUGfYpctaaR1EcvhVcQPl/vBDLGbfgdx1d3WLxMZGe1ub8BQ+P3ZMeAqVFRXC28rT3FwsaVIjpz+WlBaXYHk++CwlHYci3P3xjADGPQ9GYrrRxQ0SxlEsaRVuoelmCeAOHLdedB+Oo8LNOW5u6UZLlkdTAT1Mwio4i/rX0GDcpadcD+4/0FZt3szToakPwKgqLNEqLOnOnB6r0FbIxFbIp5tkedeN3bW2tuJqRm30RlTdCnfgWiH9qu3t6cVWasegNhSjMsjHLSL5qKqpqQlrMf3WCzK+hWcEcPa9e5ipYspKSVzKMmhbm1uebQ6WBfn55GRmZOQ+eZKSnAz/Qfb9TmWQ1h6M5eSs6w3OvpfV3dWFrYICgzLTM25ERSfGJxQWFGJVZYU2ZZLcjIqOv3NXJDY26J3Hrbi4stKy5ubm23G3cJ+GuM3KvIdTcf7sWcQV5sD3MjJHR158Knh1ZQXRe+HceYRo/G1thlxYoD3Hgp7ExsRiW73UBubM5KCqiGtbwnJ0dBQ5RQWFGMIeP3rU1tYWezOGGoMTQqMS41N40i007YUUzxLSScN1TEnSOglVpZY0HIEquYajowbITPVei7ayLE/gXIfq0y1IqCxGW8luMLcNIFOWZxgJz4EZxoPhAGacADcOjEScFJfCAcw4Af8yg2ripLgUDmDGCfiXGVQTJ8WlcAAzTiB/mYF+e2FySvtBU8NXw8rfu6G1s/ML+QWFKCV/qAE52lL/9hUqA/vs6DHtlxn2//ff9tDESXEpHMCME4hfZsi+jwhcXl45HRiE6A25HEIxbP5lhtu3bi+trD55knvk9x+cP3d+fGISBTIzMutq6yIjIru6e86eCY6PT0B5/mWGncEBzDgBBfDE5NTg0DC0s13/2VT5ywxI0pXd29ePfLkW5bUQ7exCUvuJhiHtpxpQBiU7u7pJmY9+8unK6pr8hUqPMHFSXIrLAlg8yGP2GnF+9weeA6smTopLcVkA5xcUYTxm21vb7x8346fQqomT4lJcGcCG8WyfDCfakOPFhggW55fxDVwcwDTnwaQIS1x9dBVSzvTMLD2TxKwJk6jxiUkUUMvAZBKX7qT+C+AyCcOGra1tdXX1yIf5QiRzAPsaLr6FXlt/jqW/n78WinqALS4tY4kcXIuoFKH70ZEPo65H4ebwV//6b6dOnsJaGaixN2OweW7u07b2jgvnzqMSitKCgsK0tHRsjgBOiE9ATkpyysDgEG3lxeaSADZcQKe+/FJ4OmOjY1gWbn79yDX9T2399K+SNoAeVD+CTtzPvl9Xq301vMrMzAz9LffF8+cpx2dxsQJDaXHVDeqhRTo8ov9GO3IQpVPTCOoFSGtEeAT5UOyl5RWKUhgcrIXSwhkeGZX5Q8OoZgxLZMJQFQRcvnL0YjuAAEaMtba0xN+5Ozc319LcjK6n751rbW2lP5+8HqH9tf2lCxerq6vh0F9x0S8zAJSf178NY97qK2bDQkOFt8mzhobqqiqR2OTCuXMU6qn6VzL5Mp4xB5aRyWbfDiCAh8HQ8L17966EhdH3HJ0JCiovKwsKCLh7+05vT8/vD7+/urqakpz89j//BGvpL/XplxkkQQHary789J/+mZLE6YDAhfn58fEx9YrEDRR9lSwGY8oB4+Pj9KUZ9FW1fie1X4TwTVx8C822t7bfT6EZd8NlAcz4IPTdI4YvBiQs/8wb15XltxTIL0WhpC/DAcwcHJgkUwybw3V8bOx+drZIbIIp8bD+hXgqMTdu0Ncz8C+MAhcHMH1yqK2tDV179swZylTJe6r9CJ1Kwl3t1yUZT0R+SRgikL7wSJIQH09Pvx49fEQ54O6dO2eDg+H85Mf/RDmgoqKCvhaPAtjy95Z8BxcH8G9//R6WsTHasxDDo4ioyOtomfwuUsmD7PtYPryvLRnPQr3ptbw3dgoKXTtfseQLuDiAS0u0b/0M9A9YWV7OzMiYVr7gF/T19Z3WH1eqA/ClCxeExzA+D8+BmYNjSf/RDDhm2ezt6YnXf8tC5UrYlfw84y/x37l1i35Xoad7y++hqayvP29paYGT8/gxdtrT04PJ2sTERFlpKa5VzLfnZucWFxdxS4+rv7O9HSWHBgfpa6jLS8tQJuJaOL2+atXrcVs4gJmDAwFDoYsbLvXnFEBvby/NitUvar988SLCCQ59kztxMzqaPsVheIhF39FLRG++dm5uaibnXkYmObjRGxsdQ0sGBwbb2tpQ1aI+HDx5/JiejdHvSKQmp9CvsXzk3r+zwQHMHBxB+s/EETeixGezVAzf/mufc2e051vmz2mZ6e/vh/LPz2mqK7K8BQ5ghvFgOIAZxoNxWQAXFBaXlVey7bmJ88v4Bi4LYKf+mIHNQZubt/ide8aL4QD2KuMA9jVcHMDFRcWLS8ujY+PLK6vnzp7D9YfMhcWlrq7upeWVzs6u+YXF0JBQeYGy2TcOYF/DxQHc2to2NDwyPTOLQKXvGf1//T/+PQIYUY2QXlld04K5u0deoGz2jQPY1+BbaK8yDmBfgwPYq4wD2NdwWQAX8muk/TFxfhnfwGUBzDDM7nFxAHPkM8xuYAVmGA+GA5hhPBgOYIbxYDiAGcaD4QBmGA+GA5hhPBgOYIbxYDiAGcaDcVkA5/OPm+2DHcCvEzJuhSsD2PBBfNVwLRpydmx7WJX7G/8xg6/h4gCmn/Om387HxUdXIayxqVnm0w9za//mF7DEf3DMv9Y9NDyCJW2iBm1zcwuKil8SHxqemJyC5T3Nw3JsfAImS3qBcQD7Gi6+hV5bf47l6cAgXHmzegAvLi1jGR+fgBy06+rVa5QzMjp2985d3CJ++MGRox9/8vhxTm9vH6KYLlzth3GXV2Zm5wP8/LVqn28gE3lYJsQnIIDRvosXLk5MTF6+dBnBX1RUjN3l5DzBllSDdxgHsK/hYgWGbGrCqMsmSejo2DiWCFcsSW8hklBLrMXVOT4xiXzELTKx6sd//w9IkkFdsSQFNlSF8rpgz6OeSxcvwYFh7fDIqBwCvMM4gH0NN50D758hdA053mQcwL6GKwMYt7Jse2u4zxDnl/ENXBbADMPsHg5ghvFgXBzAjvxMO9qXnZUFJzjoNOVIxsfGhGeD+6Yf8r8eEbGwsHDu7NnBwUGR5Rh1dXVYRoZHTE1OPtharb+fn/A2ibp+XXg6NTU1rS0t8XfvirSC4z9U3/jsGZZpqalY0i9xMoyLA/jQe7/Bsq+vD0v505KTExO34uKuXbmSEB9POYkJCVimp6ZRkmhoaKBNsPeO9nYEVfDp009znw4PDSUlJAwODExNTfX29lJhCVWSkmQRAMPDw/Pz8/6nTiGosES13V1dYt3GxuULF7FcmJ9PT0vLzMigTALl21rbRMKKsMshGWnplieafuqWoGCODA+vr6tD+wf6+yk/OiqqubmZBgX6beu8p0+xLCvVfoGazh7jm7g4gKsqKxGElZWVbW1t18KupKakIA5vRt+IuHZNlNChSE5OTMJyWvlhaMpH3GK5uLgYf+fu7OxscWGhvKavhoXRKiyD/APQzvArV589exYaErK6uorM+rp6rZzO+eCzSYmJoZcvw78SGoplxLXw9bX1QP9A8rHE3nG+RkZGMtJejCZJCYlY/ubdX1MShFzSKpHMzc0hOOm3rf/7n/03ygT+p/wQhKf1O4uL58/jVBQWFKJ+ajZAMCfcjY+LjcWR5jx+jPEl0N9fy4+IwHLJ637tlnEWngMzjAfDAcwwHgwHMMN4MBzADOPB7E0AMwzjEgoKCvYmgFmEGeaASU1Nra+v3zb0HApgelXDMMyBkZCQMKW8VbWFo7fQk5OTubm5IsEwzP6wvLwcGRkJ+e3v73fkzteJOfDS0hIqbW5ubmQYZn9oamrq6emZn593cN7KD7EYxoPhAGYYD4YDmGE8GA5ghvFgOIAZxoPhAGYYD4YDmPESEhv8TOa/adKX+eRYJi1NK5PSEiB2tsnz3hOzLcc1a9aX0iipLndsTm2+y32R7aKS+bbjK5Pad1EQRyprPigp+6C0/IMSWJmFaassfVOOmoRja0NhphzL8lRPWcWRiio09Uh13ZGqmg/LKoPqG++0d9aPTyxvfhPJvjJX3jwamjESmq5ZmGKUlJlUQGTq5WUmFTCWeeFPx+eLnbkfpzK7T6S2+Jalt4/MaF8hwQLMeAmqUiqGJOWoS0O+9A2rVNNyLAS4Z1OA7Zt9SXNQ8NRiuxFaR+rZ6b6sBdigeeSoRpnaUjqUv7WYZnKVrp2ypDTKkau0JZXcXGXHxCZWJUvLtWOpqLrR2jalf/vOHgIB1gRVSKbukK8tN4WWfM0xFCDb3FxbYpPNMpppNbAAu5exADNehkEsFUdVU5ljmSlzrC2lRfvKMpUXM+A9sW2lzhktdMLM1e60JTYF2HF7IbqKvgpptKWgNvJRXt1km0rsmqEqGObNVTWP+gfEoe4CbQasyeSmiEqTIqr6Mkdmvlhr0mZaagKcJ3bmfvigAJ9kAWa8DF0j7Yuo42vNJbWcfRfgAzOSz32Q84VtBVg8W96aaTApdUZnR9pp05yqzVRY1ePyquCGRnHMziMeQetTVaGgZLp2CsciRxFsQxnNITHW62QBdjdjAWa8DFUpbaup9A2ZlLTMfJHjxDtgB20fJNBR259dWwswaZWqWKrZyjdonlmzLTa0VZUtk+Ud3HCbYkeqa6tGRsXBO8zmDNigoEqScoRjmuaKfCVTM6UYC7C7GQswwzAMw2zL3NJa+/D8xYedRh3dsbEAMwzDMIyzGNV0B8YCzDAMwzA7wCiozhoLMMMwDMPsAKOgOmsswAzDMAyzA4yC6qyxADMMwzDMDjAKqrPGAswwDMMwO8AoqE4afxEHwzAMw+yExoHZXVn/zMqa9pvBLMAMwzAM4wSLi4sO/uq+fViAGYZhGMYJqqqqJicn19fXRXqnHIQAv/mrqO/8dbCDJrZhGIZhGLckPj6+rq5ubm5ul/PggxBgyOr3DuU7aGKbTSIjI1/SwR2HyNL5yU9+8sYbb4gEwzAMwxwUN27cKCgoGB8f3+Uk2GMEGPzJn/yJyGUBZhiGYVxEdHR0Xl6ebwkwQflSgI8dOyZWbK4SCVMSxMXFCU/n3r17wnvppcXFRbXwN7/5TTUJ/ze/+Y1IbNYMVJ9hGIbxBXxLgOFAEXXt06iqqtqBADc2aj/YKRKmZGdnp5rUtlSSv/jFL5D86le/SkkpzyTbDMMwjO/ww0NB7wTc/iS2/MvUlhNpbcLSpdMuM6/m9ohtrNgbAbb/InpPBFj6EmcF2CCx9pPalkoSem/IgRgnJSVRJsMwDOM7/PC3Ae/4xX0SU/ZlSpPhSzYMFpbjLQJMkP4BEmD1MfLg4KDwdAzlnRJget8sEkoDMOWlnLfeektkMQzDML6EMwLcLbax4iAE+P/8h0vQYAdNbOMiSFyBSFtx6tQpTH9FgmEYhjlwDme++n7mq9F1J9crvz2S88cG2xi+84cJKf8uOvYb0bFY/ruomD9MzohuacOG43/j1/qDo/3Hb1I9YHZx7ZVP87/9UY5qoY+7xGorHBbgZtfPgD0IIb9WAhwcHIx8SC+9AGYYhmFcBQnw9YpDlJxt+hS6u171bUqCb+gC7FddC//5xvNv3Ir/xs1bg+srEOAWGwL825h6kbUdnvQImmEYhmH2EKgvNDiq8n1Kzjz7AAK8VvFCgMUM+Ebcv4PpU2FMgpFvR4Bhr3z8BPYfPisW62zAAswwDMP4KBBgbQZsEODKLQIM0T1eVSPSm9Aj6K63Ph/54SkYkuNNfa98WgD1/Q8fP/mPx55KExtY4XbvgP/y2AbbnlsOwzAM42a43QzYoBxse2KitxmGYRi3we1mwMJjGIZhGK+GBZhhGIZhXAALMMMwDMO4ALd7Byw8hmEYhvFqQq9F3nuQ09E3ND67NDm/YsfmltbENlawADMMwzCME7jXryGxADMMwzA+gm8JcHb79PdutrCxuY/9RVxrfs+suEAZhvElfEKA37rTZhj12Njc0NomlsQlyzCMD+DlAvyPyZ3qAPdulvUHyY7lDqjF2NhcZZgQi4uSYRhvx5sFWB3XSvvnKHN2eV3Nh8lph3mVwaDTKPZJTr/MWVp9vvb8uUxKaxxbRElDJkzfzwv+NVP7067QitEp/RNuVOZx14y+8gVUG7DcF4zqoYbJOs1tkKtkjrn95jJIDs6ukG9o2/Ka2NbWeZCGwoYcNlt2+EEfnV6GYbwbrxVgdVILnaBMmRNYNFQ9tHC5/IXMyPdwMsdgtFZCj7Uthef7sWISI3VLGglYZusUlthwrwQ4qmYMa++1aW+4qU6JWgytRQ5VQjcTMkn2s/QX2x5+0EuZ8M0HAkP+tgJMDSMMq9jsmDhlDMN4NV4rwObhjHwIJyUlCY0TajFoMyVVI+mSSamXBuGR0kvqRVuVDczLArQWDtVgKcCqaBmwFDkSbDhY1o0syDrVGfDdZxPwSaEfdGjlqVVq+2U9ZPBJd+EA866R6eAMWD06NkdMP+UMw3g5//TBmd+evRuQWHXhQfvFB50XH3a+WKqOTJLJ5OYqjxFgmZRcqxpT80/kD8qSqpGaSmSmfVG0tPeye2hJpq4iM+xLYkfkyFBbcPGwZZ3SDt3vlWXaJ5Z6ppcpn3ZKvprE0jwDNjyptnUeyFiAnTWcLoZhvB7HvwnLvrmdAGMeKYcz+ZZX5vw8oxsFDj/okznmMo7YDgTYci8GiXJWgKm84cPeUkHJ9AqM+1Uz6aE05tDwqf2kr3AMAmzena3zQMYC7KzhdDEM4/V4rQCDv4hrlSNaYNGQyDUJ1fjCKuXn98yq+Y6YfeGxNPmY2oB85wojxbJEljEYiaIBtU5b+zWcjVsNE/0zK2ktUzIHZaQA/9WttotlI3KVNPvn4UT+IObchkw2W/bh437qGoZhvBtvFmBwtmTLuA9Jlh/IkiDHIEJsbK4yXIriumQYxtvxcgEmMKUwDHNsbG5oQ3Mr4pJlGMYH8AkBlmCAezfL3geU2NgO2H6e0c26yzC+iW8JMMMwDMO4CSzADMMwDOMCWIAZhmEYxgWwALsLHR0dr776qkjovPnmmyUlJSLhJOHh4ceOHROJjY2XXtI66NChQ3FxcZQDUD/yJW+99Rblm1tCHD58+Otf/zoV/uUvfylybWCuxFa1ZlC/8BQMRwTMxRYXFx3chfugn04LxOrt+Na3vjUyMgLHwU12c1G5iry8PDonBtSL2Q7yFO0h2DuW5mvSQbAhHYKBndW2LahZeJvgnMzPz4vE3uFUT/X09Lz++utUAE51dbVY4UuwALsvdsZKSKnUS0fAJY7ljgXYsCGBYDO3wTICv/a1r2GVfQFWd4FNyAEYKagSla985StYBYfKSPZQgFdXV7e9ybCD5cmxPI3mo7CDubAtAUZSjrAY6eRatxJgy2M3Z1qezG2RR+qUAKPfLVtFGM62CwXYfjuBrYAinBVgy32ZMx3vKQcr9HpYgF0PQgWKQvHw4YcfyqvQcqykwRSFKQLr6+vFik3UrSBIJH4oSRgE2HIs3pMZMELRUMnOBBjQkUrkwAGfHAmOl8oY2CtVdhzHBdgpcCzC28RSgM17l8U8UYB3hjxk6TjC7gUYMSJ3JwPQgC0Btixsye4FWN+hEVuqjFXCU7DMdByeAQMW4J2DS5yunl2O74hYdUxEhRQGhrHym9/8Zmdnp0goIBSxSiR0qFUEVQUHy90LgIOQEGJ36oBiEGA7N8vUWgJHR/NdiToIEjhG1CYStlGPHW0zDJ0ooA7TOATaLx0LnUY56mEAlcci16rYao/l+VfHccsxXYIahLeJQRIkdKMmkS20FGAUEJ6O5SGryLXYu+xi+6dUbqKCTEvE6q2o+bbKALkKYSUbqfasfczXG86YuddoL4bOkrenZmSdzl6otjC308GAol3YRxRVECtMiNVbUfNtlWEIL/9Bfo/GzmTF/jANaNw08OMf/1istov9qarEsg007qv5b7zxBnLg7EyAAc4DxhoaTDHGqcpHjsTBlktCQkJQCUZns8yoAqyOdCgmh3X0juXobMDczm2xtQnyVbBrWwJsC1sXFc4Azi2pqeUhk3LIXqCd0knQSwnkKYXvYJPAttezGVubmHfqlADj2A2XkOMCvEucqs3cTscDCsi7E2fZw54y4/gF4zWwALsSS5kkEEvqWCly7UIlCSTNAWYeSsz30ZbsyUDjuDoajsUW5mKO7wKnApu/9tprshISGHomhtNuEGC5Sj2BSJqfGVI99jFUIrwdYRZgnAR9JxZgv2YBpouQjo5GcMtDpmrfeecdLIFZgM2nlDZ5+eWXaWpImQSS2yKK6pef4bp1CksBFvuwiyhqBa1V44I2sQ+VBI4fkdjSLqKobcxlHBdg2oV9RFEnj0t4vg0LsPtiHis9mgMQ4P1AKrEB86TZtTjYGEcuKluH7KE4NQN2ij25MT0AWO3cFhZgX8cQnLgabD3IMuCgoO5mkDK/tIbs0Rzr7bffFlnOSLsdLNt5YG/NbYHuOJghXp5Y9T2F/YvB2Z6lK83BC2wHfWqWGXoejpsJ9cMTDk7+HHw4JNmTi3A3mA/fFo6XdBYHa96nsNq/49o/WIB9EQwWuFjNYKJgHh9tjbOGEcdWsW2HaXVOJgujMVgaAtUwlcFaajYwjH2oxzwaYkfmlmC2J6pQwF6wxFrzSIF8w/Dt4FSY3oW/8sorIm2F+VxZCjB9VF4lKChIrFMQ60yI1QqGE4sTRUdtXyyxlf1P7RoOh3ZtWaf5wC31zCCKVKHsI/XQ0K2GtmlHvonag3QB0Edws7Ky4FO+fQF2pMHmMsAy0xLZEjuoh2mrvDnfnIOudPCJtIo8RfKg1Jrhq1BJuvtxUICxlfAUDP2innbL8m4OC7CXg9iwHEPR67heaWbQ2NgIn1SQ8mUS2Boy3EGAaa3lYE2Cp2JL/LBThDQNQNiKTpfYZuv7WmD4dDFh/mMwAg17/fXXzWsHBgb+/M//3FAzzjyOAgel9hcyDWfPcBII7MigN3RbYIkooeCgAMs65ekiaOoM7A/iKICloU4CR23oQcs+NQy+VKG8DChJWAowOYYZsLoVkBsa9qWCQ0AZnCW1heYG47pC5WbM4YBM4TmJ2nG2KkG+oV/MJVEPMs3Y6VC6cSFfPVLKkRhC2JYAmze0hX0BJijpEbAAuxJcxHQx0dVMAxMFg9QhEicqQJcaCQYcGhBpfMesSK1KXpQobB7vAHodxSwF2FAeNVgqqGHEsVXMVr7ElgAThkDFIdNw/93vfldkbW0JHZd9DHVipzh1NNaoAoylOlLQtvahkoTjLcFe4NNWBMKS2oNKzGcPhXH41Hek5YbNAV0bIuEA8sTaeQSNtdtCJaWEA1RCvSNKKF/5QqD7SM/UIzXrGTAMvqgKSzp7BOVL5CPopKQkkWUSYIoXKrDtDNhOT5kbbHnlGzJR27aIoiawSr1tosLAcC+FFiJTpHUMSWeRf9cgUcOWciTIUTPNAkwF7EMlCbqwVeRph0+OB8EC7EpUAZbRLgcsgCubRiu1AMClhjAzjFm4uJFpKClrMIOShlkCMIy5ADXo1/kW0ML9FmAs1UCVUAMMmMc+sWIr9luC2S2JGXj55Zf9/PzECgVaa0astsHhw4dFOdvfYYLzKUpsxX6bHWHbLgCWemO+GFTsVGtLgCmp1olMmaSxlbTQKQGmfVFSRdVmFVWAbWF5QiQk1Sp2CgMUEJ4VVIMZsdoEIt185s3lkSOPFL6MMjs1Owg6EZVYIkpsliEfDabnT2YBJmhbM2K1Yzhb3h1gAXYlTgkwLi/Kx+VLwkmZNANWM9WxALWZVZagzc3YGXNVLIdIM4ZhGkOz+vkpW6AZWJoDFVAjDRhasgMBxlrhKZg1huoxI1absDwEdIr5JFueT5SUDYAvdmYbKUXbQnVKdiDAKuYKzVAZB+t08OoC8gyb24BV2qGakLIEPaCc17eCfDsCvO3NgeM9RYgsE2K1Yzhe3lySdFEkdsG2bdgrAVbv2j0aFmDPwCCre4JLBNhB0AwsHRdgIFbr2BJg++dwNzNg+8OBa2fAjgD9EPvbilcKsCOn1P4MGDx69Ei+/P7Rj34kcncEVWJGfZi8LSgvvO0wl5Q3IgacVWVsIjwbOCvAts4ABFiU2Ip5uHBzWIAZhmEYxgWwALseWw+szHdz33L4rwUsb2npWTQcKmOJ/bWW7GATt8LW1BN33/ana7iRd3CCKNn2eQD2Kzwdy/K4/cfkTH55fWNjI7pbnS86dUS2mmSYg5ofKtBW2x4RwzC2YAF2PfZHeRXHBRiga8VIqYMk5cMnR4WeQMohFeO75Y4st3UrbLWwp6fH/hNF9ZZFlrTVNeqPVsGxfFi9M2WS1RKWlaCM4U+b6I+jRGITW0dEOeYPvhkwC7BlsZ0dJsMwgAXY9TguwE6BQVZ4OjJpyN8naBL2uv5lwhig6X3zO++889prr5G042bi5MmTyLT1GTFZAEA/aNoHX54rEhjaBckJ+VjSHympu5Av0TFtlZ9Wwyo4lKk+b4Co0F72qWtsgWMMDAxU94iWoJHA8EIUhyZfj+FAzOcQRyRvuYCdI7KloI4LMLXQVj8yDGMLFmCfA2Ol8JT5kB1UZRJZJsTqTWg+LRI6pHbq35hCQux/cEktgG3ljFytubGxEaL+05/+VI7+6lq1BinAgG4ODJJmiUGusNW2iKKKMhmwNV/EKtJUNE821Zbs7SG7F+D9biHDeCsswJ4E5nyOP4IG6jxJgoFeeFZsu9YSsVoBmXLX6tcgYGZG4/UuBVjVeEiFKsCypC0BpjI4meq9heU80jxfVLGvPViLHZmx3MT8p1lHjx7F0nIXqMRwGZjveADd9Jixc0QqBgG2BQsww+wYFmBPQn2rp2JLlaFAosRWxGortl1riVnmPY4dyNXOBNipR7WWu3Dw6zBZgBnGzWEBZlyMpU7wmM4wjNfDAswwDMMwLoAFmGEYhmFcAAswwzAMw7gAFmCGYRiGcQEswAzDMAzjAliAGYZhGMYFsAAzDMMwjAtgAWYYhmEYF8ACzDAMwzAugAWYYRiGYVwACzDDMAzDuACfE+Dl5ZWiopKiYjY2T7CikpLScnHtMgzjXfiiANfU1s/MzrGxub/NLyw+zSsQ1y7DMN4FC7DHGEZjQw7ZxOSUIcds2HZ6ZhbO1NT0yOiYuspsKDw1PQMHm9jaqWooTJU7UnjHhsonsSerfOkMDg1DsuBTe7zAWIAZxovxaQEeGBg8deLkiS9PrK6t37uX5XfKL/5u/Mrq2u8Ov5+SnHLt6jV1cO/o7Kqrb4D19Q9QJhlyAvwDrl652tDw7FbcreOff1FcUqoWwCCalpqGym/ejFlaXgkKDDpx/MvhkdGW1rZbt277nTzV0dEpC5eXlX927LPIiMjLly6jJWeDzwb4+c8tLBYVFf/6V+8GBgTOzi8UFZc8ePDw+BfHx8YnnuY+jbgWvrC4BHH6+MOPenr7TgedRhJVpaWlowY4SF48dx67ho/GVFVV9/T00u7Mtry6Fh19487tO4vLK9jw8sVLa+vPDWWkocCZoNMXzl+ICI9Aq9BCnAptdxcu4uju3Lmbm/v0/PkLn3/2eXpaOvKvR17H+RkeHsG2dDJrauuQj2PEeXj06DHaFhcb98WxzyoqKtUdLS4tXwm7UlFegY7AqQi/Fv7FZ58jMy7u1uHfHjp/9hyaffPGzfHJqRvRN1AhNomOipbd57nm0QJcXV1bWlZRVl7JxmYwcYn4PL4rwBjbTgcGYYiDGmFmVVJcgswroWHIj7oeZZ5sjY2NDw2PwMYnJmUmCkOzURbiisqPfHBkcnIqMvI6tGF6eiY9PQP1QwXhoPCzZ40wTEAh/C0trVBEiAREVNYGQ1Vd3T3nz52HYjU8a+zs7Kqurunu7oHAZGffx1rMd7EhKhwfn0DlyImNjcOGaAluAoqLiutq65APg4iiSViFxhz99CiGcmRS++/ejUc+BC8pKRkb0q7JcOC4OQi9HAIBxqrwq9fQJchHJT/4i78kRZdWVlbe1taOeSduF9aeb2RnZWNzGFqI05KXl7+ytv6zt//X6Nj4pYuXcEIrK6tGR8f6BwapJWTwg88Eo2RMTCwa/PmxzzBNv3j+AvaOqnDUKIB9IZmT8wSH397eAeXG4UCkUfOTJ7nUI5cuXIT0Yr/LK6vYBHc8hkPzRPNoAS6vqOq2favH5ssmLhGfx9cfQWOEo/GdfHKQIzMdMdqwtrbuyO8/gCLKfLUStXLyaS8wKBM0bEg3CAxlqltREkvDhmZfLslR1Z2eVGuFNytpbm6RrTIYVYKGycOB1MmaVdMqVBqACqEZmMW+9+v3oIvY6t9+/ovW1jZZ3nKPcnPcbXx05ENsZVhFjmozW3dKZaSj3iR5tLEAk1FfH4zJm29cRQe5X58ycYn4PPwOmI3Nfc1rBBiHEnU96s7tO59+/EllZdXyyupnR48lJib94mfvIOq7unt+/rN3roZdOXXi5OjomEH2cEP261/+KiggMCgwCOqIcwL/9q3bSMKHTF66eOlWbNzt23cWlpZxH3z8i+OXL146c/pMd3dPYWHR7w6/j/IB/gEY49LT0uNiYv1P+WFDVPv2P/9kaHiktKz8l7/410X9HU1BQWFDwzPa77NnjdnZ91GSkmx7aOIS8Xl8UYAxohUUFrOxub8VFpUUl5SJa9fTMAhwzM2YkdGxzq7uiopK6GJZeQXU9OL5C5hvYu2Z02eghfKZzdLyyj/+6O+lEufkPOnt69ceFA2PNDY2Zd3LGhsbv3vnbn//wI3oG729fROTU+/+8lcQSzi34m6hJM1fYSeOf4lqsS/UgFWY30Kwm1tasWphcSk2Nu5K2BWpshga6usbyIcAP3jwcI4FeB9MXCI+j88JMMMwB8O2j6ClvrrEoMoXzl/wO3lqeGRUbYl8BE1vbdj2w8Ql4vOwADMMsy/wh7DYbJm4RHweXxTglZXVFYbxEDz3rrSmpraouJSNzWziEvF5+ENYbGzua3PzC5OTU+LaZRjGu2ABZmNzX2MBZhgvxqcFGKPbwOAQfQRjYnJqYGAQS/jIHJ+YRL4cB9nYXGJeI8ArKyvNTU2tLa2UnJmZmZ+fHx4eHh0ZQXJsdGxtba2zs3N6ehrJycnJsrKyhfl5+AvzCxMTE1rmxOT8gpYDroZdmdo8LbOzs43PnpEPbkRFkYPBJDU5Gc6zhmf9/f2UaYuFhYWigkI4aalpaBhl2iLk0mUsm5ub0UjKsUVhYeGc/r4zIT6eclZXV5/mPiWfYXxXgDG0XdC/O2l+YXFa/1vDrHtZsTGxEOBbcbeW9G9TUodCNraDN68R4LNnzkDknjU0SLGMDI8gB/T09IwMa0oM2tvaq6uqFhcXkxOTKCc5KQkF7mVmUhL87KdvC08X4Pq6OpHY2LgZHU0ORrTUlBQ4HR0dJMBQ1qrKKn2lEawqLi6G8yQnZ25Ok8yxsTFV11XOBAZh2dfXV1Ag/kS7uKiIHAO5T54sLy/DwSFQztLSUt7TPPJBZWXl0uKiSDC+h0/PgCGxY/oXOtJIBw2mv/lTvwGKjc2F5jUCvGMgjdDXtNRUkdaBjLW1tZEPXT/+2ec0dQYV5eUXz58n30DoZW3m6iC2KjETFBDo4OiJYzl7+nRPdzcl72dlt7aKRwKMb8LvgNnY3NdYgBnGi/FFAa6sqh2fmGRjc3+bnJpmAXaQ4eHhkuLitbU1+O1tbc8aGiorKstKtv+Ll/TUVIyAFy9c2HYQxLT7fnZ2V1dXbW2tyLIBhrKb0TdmZmYC/fwpZ25uLioyknyGIXxOgBmG8UqGhoZqa2rIT0tJpZevN2/coBxga3gJ0R9Nz0xP5zzOoRxb3I6LwxL1xNy8STm2WFlZKS7SXiqXl5bRh8iAQYB5uGNYgBmG8QbUGTCYnp6emhIPD+rq6q5duUK+GQw7GAGXlpYo+fGRD9taxQtmM5jUTk5Okg+9t/OqGHcAY2NjcmCdnZ2Nvn6dfDTsH//+78lnfBlfF2DcqPb19VVWVCB66UZYpaWlJSMtTSQOigfZ94W3Fcf/eiEiPLyivNzQo+onRR3nb/76r4Wn90735udHiIH+AcOnYxwBI+PpwECR2B0YNM3HVaLPPADOQHJiUlhIKF1X/98//VMs5+fnMRTq6zX+6r//hfAYhmEOFt8V4MHBwdSUF+KxsLBw+dIlOO3tHX4nTsLp6OiYmpzKTE/X17/gatiV7i5Nh+7e0X7xvquzE8unubkxN2/SHTfdFONYzgSdrq6uhkiEhYQ8a2jI2FpVU2MTlnW1tQX5+dj7nVu3Y/Vf9Y8MD9fXa1yP0J5Z0Wl5kvNEz9tITUnB7sgnsIsR/e8pqUlxsdqDMgN5m5sU6X8ykZGWjnuO8bFx+Pezs6+GhdXW1oReDtGLvIAuC8wq5J1+wt27WKLBlMzOysJyfW09MyPjyy++gF9eWvbo4UNMFOCfO3u2oeGZuVspp7lJOwPxepvpj1IePngQczMGh4M9lpeV0V9P4hxiiQZDOMc3n+ZJnuRojw1R1dLiUlVlJfwU/a8/wdrqavzdu5fOX6DdybkRKC8vz3uq3dCsra1SDuPpzM/NB/r5d3d1wUdfB585czowCFcmrbXD0NCQ/6lTKZt/KWQHXEiXL1wMCghYdOBvh3IeP/7is8/kDeLF8xce3n9APu4CcQ/a091DSUcIv3YNIxIc+QfQu+eq7acC8uEBwCzl0oWLgf4BcJCsr6+HYNAqZpfwI2jt8kI4ZaZnICqWl5dra2v1P1jU/gRwbm6uplq8VSJWV1aKCgvpTwYf3L+PAtgczcZEEHoGUe/v76+uqu7t6UUBBFh6WhqN+3lP80geJB3tHVAazL9bmpvHxsYgJM1NzchHJuZtkJOR4WFUhbXIRHvQkr7e3oGBAYwXXZ1daoQA7Df3iabQkxMTVZVVjc8aKV9SW1NTUlxMZzjimqbxqGd4aIiUEgeempw8OjKqFbUN2oYlpIvOT1NjI1qFWxAcI4QZFUIjUSeEc3pK+7OQZ8+eQVO1La1obm5G+cZnz7D5QH9/ZUVFe3s7Wo69oFW9vb2PHz2CI4WzcvMEkuqDuto6nKKJiYm21ra52bn6unoMuCiflJhIzwmrq6poRJbs8kJn3Bb1HTBuwlaWNbWIi9Fuau1zNTQMy4X5Bdw4Uo4t7t7WbhaB/GtjW2BYKC0ugYMrUMqV+g4YcYrrXyRs097WlpOTg/DEvXVZaSmu7UB/f4xU9NfDGDdy9RvrO7duIWo+eP932Becc2eCEelhIaG4w8aghJtjZDY2NiJgYfR3UIsLC/LrQdDas2fOYC+ng7Q/cYYTfPr0vD64IYnh8d1/++W/vfNzedt96sQJcphdwgLMMIw3AAGW001oRmBA4Mkvv1xd1Z5wQEj+x1/9Fa0y09nZeSYoKDpKaGrC3fiwEOOjIAKjZICfX8ApP7ptxbj5p6//Z1tDZ3JiYoCff3Hhi+/ouB7x4rtHZqanpQBD2P7bf/2vturB/UHIpcsZqemYgyKJu/8L58+fPP6l/NPnz48dIycyPAL3u8FBp4cGh5Csq609f/bsueBgDPFUQAI9vnju/JEPPjgdEAAtz7qXhXOF/Pd/ewi3wnDiYmNDQ0L8Tp6CPzc7e+7sWf9TftP6UQP1S1SY3cACvF9gvosbSThyAldfW0dfsmMA075bsbEiYQUNIg6CoaG+vl4kTCQnJVOrnEIegi3s/1UGri0MFoh5kd4f0pQXCgTO9uzMzO4vKpx/nFX1zbF9+np7nX01Lhu5yzhkfArEMsRbRPTz57jtAPoaxjNgAd4zoFJtbW2Dg4P0KrettZXkNjMjA7eQGMQRKjeio6uqquSnKImenh7cocuPDhF379yZmJjIz8tDx0Rdvw4hQWZYSCiU4Jb+ivfmjRtlpaW41UXJqamp6OvXUTIxPh77ilH+9AJcvnhxanKKHpqhGXTjfOfW7anJSdxZ93T39PX0REdFxcXEFOQXoKo7t2+jI379y19hX4kJidjk4YOHdCzpaWnjY+M4Cq3eTVC4vKyc/Pd/+1tsdff2bUoS2ff0J8bPxdf79fX2dXR0HP3kk1txcblPclH/ueCz+nHFrq2ufnzkw/GxMdR5PSISjcm6dw9bdXd338vQvokw/Oo1XKwJd+9CD2uqq3GSkYxHcmbmvXff1fayCWpAtZgVwf/82GeQT/o6QJx8en6O/X74wQfYHD7OMPJra2raWtuQ8+jhQ8NAhtupgry8mekZNIO6YH5+vra6pr+vH3MFUUhnZXnlZtQN9DUa8PjhQzQe3YR9ffC736FDUXlhQeGV0FD685jR0dG0VO1TfpgMwacnfuvPn8fcuEkNYxjGi2EB3ks++uAIRtLhIe1lcMS1a7H6Hwu2t7U9zc0NCw1taWlJT03Lz8+nPxCUXLp4kTRb5YPf/R46QS+lMF7nPX0KnYYQQupounz040/oFQ5k40lOTviVq/CDT5/OSEs/+eWWNzQQHmjVNb0AVPZGVBT6u7SkpLCgICwkBMKPGdv1iIjg02eQfz87OyI8HFfD+789hA6hB1MQ/sePHkM//P38Ghoa5F9TELgJuHThAn0463eHDmP5xWef62sEjx89Kikuxr5QLUqifigNBDg9NbW2phaKDlk9deIk5LatpSXQ3/++/ooXTaqrq4uNiRkYGMjKzET7sflvfv3rhvp6OrHIwYEj+fD+A4jchx8cUUVrZGQEXQCdg5ReCQ07HRh459YtXGDpaemnvjxRVFiIu6WggAD6zPmv/u2X9XV1aCSE8+7tO7iPoR8JINCb9Bm0s6fPoBPRKefOBCMZFBDY3NTU0a59NEZSU1X96Ucf484JPm59cPs1jeNqbUXhxw8f9XR35+floz0R18Krq6oqKypwo4MTOzc7hwsDrcXBdm19ac0wjLfCAsy4GIix4093d8bc7CxNLhmGYdwHFmCGYRiGcQEswAzD7Avl5ZUFhcWFRSVsbAYTl4jPwwLMMMy+UF5R1d3Ta/h9JzY2mLhEfB4WYIZh9oU9FGD60W77Njg0bMjZmU1MTmnO3Pz4xKQj+2XbgYlLxOdhAWYYZl9QBRhKFhEekZyUfOzToxUVlcsrq0c/PZqenvGLn72DqO/p6f3Xn/8i5HLI6YDAkdExg+yNjo0f+s1vz509d/7c+cmp6fmFRb9TfomJSYEBgfCHR0b9T/nF3Iw5G3x2cHCoqbnlzOkzN2/cvHcva3VtHSVPHP8yOiq6qKh4YXEJe4yNifX383/yJHdufuH82XMZ6Rmng05Da2lf+fkFDc8ayW9sbMrOysYuKMm2hyYuEZ+HBZhhmH3BIMA3b8ZALDs6u8rKKwoLi4qLSyampi+cO09roZpDwyNj4xNUfml55W/++n9KJc7JeYKqoK+axDY1p6elQ5Vv377T1z8AZS0pKYUwH/n9BygTGRHZ09s3NjZeV98wNT2TmpIKRcfahPiE9ecbnx09Nj0zOzA4dPXKVZRBJqR3YGCwuaUVeowdoWH19Q2004aGZw8fPqJ8tr01cYn4PCzADMPsCx76DhiyTY54Fs22DyYuEZ/HFwX4SW6e4SN5bGxua0XFpeLC9TT4Q1hstkxcIj6PLwpwfkGR4SUTG5t72vzC4tO8AnHhehrVNbWlZRVl5ZVsbAYTl4jPwwK8E5uanhkbGzdkHryNjo1Poimzc1VV1YtLS+oqNu8wjxZghmHs49MCXFtbV5BfEBYSuri0HH09amBo+Pfv/255ZTUiPOL8ufNJiUnq5y8wFF6PvD40PBIUdHp1bf2f//HHrW3tD+4/wIr8/IL0tPS19eeng06npqTGxydMzcxGRl7v6e0L8A9QK1ENFUZHRff09P78X36G4/7yi+Nt7R23b93Gig8/OII23M++b9jk337+i7q6+mfPGtva2rHHy5dD4IyMjgX4+a8/34AW/+rffvnRRx/H340nYWbzdGMBZhgvxqcFOCsrGwJWXl4BWT1/9hwky/+UH4a8rHtZg8Mj9FmMtefP//jf/z/RsKXllY8//GhyciokJHR5dS0yInJldS02JvbBg4f9A4MQbAyWkM8b0TfCr4XPLSyiwMTUdFlZOeqBYP/pf/4vqEEOrLCFxaUL585DPqG1aE9iYhIaEHMzBqvOBJ0eHhmlRnZ19/zs7f+llV5euX//AcokJCSizbh7SEtLr66uGZ+YxFbYF1bdvn0nMSERIt3b1y93xOa55h0CvLKyMjw4VFNdPdDf39PTg5zFxcWysrJu/Wcn1tbWnubmaj+T1deHJEaigYEBFGhuaqYf2kNybGwMDhgdHZ2YmMAmHR0vfgPj+OefC29j40ZUlPB0Ht5/IDzt9/C1HxFBpG87zty9fQe7WFpaSkpIEFk2mJ2ZqSjXfgosOSlp2x/cvHT+ApYN9fXVVVWUY/4NTcan4EfQe2YYKwsKCmtqas2VQxoNOWxsjph3CDB0ND0tHXLb0tKSlpoKbYu5eXNhYaGvt7epsREFmpqa6Ac3ieHhYZQUCZ2YG9rvXxGpKclB/gFS7WZnZ3HjSz6gn92UQIDlqBJx7RqWV0PDKGd0ZKS+vkFfY+TmjRsYEFdXV5MSEymnuKjI8se8ZzYFOPteFv2E5eDAQEODdbWnA4OwbGtrq6yooJzU5BRywMz0TFlpmUgwvgELMBub+xo/gnYEaHBrayv5mFxeOHuOfPA092m4rrsG1lbXzp4+IxLbgSESM2+R2I6rYVeEtx25T56EX9V+JJSIvr5l7s74Ar4owIWFxYaP5LGxua2VlGoTLIZhvA9fFGCGYbyelKTk4eFh8v1PnZqZmYm/c2d9bY1ybIFisTExM9Mz1yMiRZZtEu7GT09Nnw0O3nb0rKmqLiwsbG9ro0fua2trDfUNPforcMaXYQE+CHZ5chmGcRYI8Pz8PBxoal5uLpyy0lL6VJcd2lrbMBrCeXD/PuUAW+PSldBQLIeHhkqKiynHVsmYm9o77LXVtbt37lBOZ0cnfQaN8WV8XYCvhIUJb2Mj4JQfltQGhB/uUvVsC3p6etra2sg/cfw4ObaYmprCMjE+Hsv29vbV1VU9m2GYfSQ1OUXOgBHUU5OTUn3/9Z2f2xnvlpaWKGYBNnzvV78i34xW7dTUysoKJX/z6/f69Q9yW4L7APlBMzED7u6mZPzdu/n5+eQzPoWvC/B7774rvI0NeuhEuruwsEDhQR9cNNDY2FiQX0Cfw0xJSkJhyg8LCTXLdkVZ+eTkJJ1fnOjKCv4WGIZhGIYfQet3puTgFBj+ks+Rjz5CXMnBSZR33LZob2sXHsMw+0lhQUGAn/ZMCzQ3Nx//7PP0tHRK2udWXNznxz7r6tz++XB3d/epk6dSkpNF2jYYW84EBZ0OCBR/2dzfH+jvPzk5QWtrqqs/OnKEfEdYXFwMCgiAYx6ydkxdbd3TJ09EYiurOiKh/x3zyeMn6JEeyM/LI4fZASzADMN4IfId8PT0dFFhIZyy0tKVZfG42BYd7e30pR8PHzykHDuEX9X+wGliYqIwf5s/FbsVG4clBtnbcbcox/AO+KryLswOqcnJs7OziwuLnx09iuTQ0FBVVRUOkx68XY+MXFhYmJqaSk1OgdJ/8P7vIM+zM7P3MjLLy8qaGhvRVLQEJ2RwcLC9rQ3zgdbWVpTBwDsyPJyelqbvZCM2JmZ6ampubo6Oi0piLzQ+P32Se/g3v/U7eUoO1787dJgcxllYgBmG8UKSE198NRWmmCePfym/1urYp59m3btHvpmI8HBMl+UfFv/59/7M1ke3oEyBfv7yc1WRERGQLvINYHj1O3ky4JQffVkH6O7u6e7sJB9cu/Lir4fDQkKvhFrr8ejo6KkvT5w5ffrCuXOQXgyYl85fuHj+fPR17Uu+QM7jx7mbE9mIa+Eohgk95BkNuB4RefH8BWwO/aYCkoKC/ED/gE8+/DAsJATJDz84UlpS0t7e/rku85De04GB54LPZt/LQrKwoACFY27c0LbUvhclpb/f5ptvxj4swAzDMN4A1H1pcZFmw7hpwP0Hf+TTzWEBZhiGYRgXwALMMAzDMC7AFwU4v6Bobn5hdm6ejc3NbX5hcXJS/E0qwzBeho8KMIY2w7fes7G5oeFOkQWYYbwVnxZgLEdGxyYmp2ikGxgcolFvbHwCyfGJSUpKm5qeGRwaluINH8XgoDyMf3OQbc+NBZhhvBjfFWBY1PWotfXnGOPg9/X1B/oHpKSkIpmb+3Rmbp7EFba4tIzlwuJSZEQklnGxcatr61GR19HWhPgErOrt6y8vr5DCzMa2V8YCzDBejE/PgDG6DQ0NYxKM5OTUNGbANItFHvIx34WPVVQAPorCGR4eQTFk0lLLGRnFbJhnwGx7bizADOPF8DtgNjb3NRZghvFifFSAMa5Bg9nY3Nz4U9AM48X4ogAzDMMwjMthAWYYhmEYF+DTApyakhJz4yb9ZArDMAzDHCQ+LcC5OdrPhoReukxJhmEYhjkwfFqA+3p7A/0D+Lk3wzAMc/DwO2CGYRiGcQEswAzDMAzjAliAGYZhGMYFsAAzDMMwjAtgAWYYhmEYF+CLAlxQWFxWXsnG5hE2OzcnLlyGYbwLXxRg/jEGNk8x/jEGhvFiWICdsPmFxeLiEsttx8YnRkbH4DxreEa/Y3hgtri0VFpaZtmqoeGR8YlJNYd/M9GzjAWYYbwYnxbgiorK8vKK65HXF5eWsZyYnDry+w+WVlZjbsacPXsuMyMTw58cCrFJT29fRHjEwuISlPjv/+5Hvb19WfeyoHAomZKUnJiYBHlLTk4ZHRtH+aSk5K7unlMnTi4urwSfPgN5vn3rNioP9A9o7+jUfvNfGWdVe3D/QXNzy5mg02vPn1+8cBGtOv7Z52gh/JDLIakpqYZWdXR23bxxc25hcXJq+mc/fbu5pbW4qLirq7uwsCj86rWSktIvPvsc/o3oG8vLK3Fxt57kPEH9OATkBAYEZmVlW4o3mzsYCzDDeDE+LcAPHz6CFBUVFWOmCMGDfPqdPAVlykjPgIBB+VAGKvjv/+j/jobB7xsYjIyI7OsfwLB46eKlldU1aNjw8EhRYVFOzhPINqQXUtfY2IT6b96MwarMzHsLS8sXzp1HbRC/oaHhjIzM8fGJx49zoKk//9k7hhkq7M7tO909vdnZ91Hg7JlgzKdPfnkCFUZHRQ8ODdP0Gqte/Q/fQdtm5ub7BwajrkehVdjFrbhbS8srSYlJTc0tDfUN8XfjcYxhoWG3bt3GTQC2anzWWF/fUFlRiQpTU9Pa2toh2+re2dzKWIAZxovhR9CutAN4IIwRvKS0DEILqTasYnN/YwFmGC+GBZiNzX2NBZhhvBhfFOCCwuKi4lI2No8wqLC4cBmG8S58UYAZhmEYxuWwAHs2jpwxNzmru7zCiG2PZW1tTXgHhVNNOvjmMQzjtvi6AIdcvETO7bhbN6Ki0YCpycn8/LzEhISZ6emqysrOjo7QyyE4OzXVNWeCglZWVpaXl2NjYlAy5uZN2hb55GArckBGWrrwbJCaknI/+37C3buNz54FBQQkxMcj815m5sTERN7Tp7U1NQUFBWcCgzo7OpFfUlyMpq6tri4tLc3MzMzOzCwuLqIxt2/d0ivbyMzIuBIW1tHeDv/Xv3oXLent7aVVc3Nzg4ODq6ur8Kurq7E5nM8+PaqvtAlaEhYSCmd2djY7K+tBdvbgwEBXV1dDff31yEjU1tXZ6X/KD2cJZW7FxmKJBmhbbmx8fOQIOQP9/ctLS3BSkpOxjLp+Xc+2YHp6GnV2dnYODw2JLBNPcnKwLC0ppaSZSxcuYJm02QuPHz0ixxKcvdOBgdVVVctLy/6nTiUlJdXW1qKjb+mn9OqVK48ePiwtKQm9dBkNg3BevnSpqLAQq+j802lETlVVFZzJiYn8/PzgoNOooaOjA10gLw9sjt6BMz8/j2VEeDiWfX196BRttd7sg7/yGYZxOb4uwO/96ldYVlZWQs/Gx8Zp9E9MSNRXamSmCx2FIi4uLMbqo+ro6GhxURHlA2gVOaoAp6emkQNBTbyriatKTU0NdBEnPTIiAsmKigosaXqUmpxMyvHlF19g7EadQ0ND/X19aCFUCvIPRQRQYpTp7+/HEtyIisIyOVFr+e24OCyxLc4n1VlVUYFktK5/dJL9Tp7EEmjScuEi+ZLW1tbent6+3t6FhQUk1RNyL0McbFxsHBqTkqQpK07I09xcOb07efxLciDAC7rqJMZrZwYahuXi0lL4lavaagUc2tTUVFlpKXQRSf+TpyhfBTKGXXR3dcNPTU7BTilfcvZMMJbJSUlY4txKAcbeUT/5ktibMVg+ePAAAlxRXg6f2t/T03M/O3ttdQ1H96zhGc4zKrwadmV+bg6nHWXo/AOtFu2EaOIKkvVT0drSguX1iEgsUZi6CVqOZXlZOSINHQEfNDU2kpPz+DH0m3yGYXwHfgStTRCF5xgYQCOuhWNSKNIbGxhkqeWjIyM11dVwMNyTAzCdJccRch49fv/QYXQGlO93hw7jnkCs2FNIFYjKikrh7QKckDu3b4vExgbJNsBNA+bu5EuqKrUpox2gfLIGW1SUa7csdqiqrJQK3d7WRs62oHMx9918GnEv5oaYxe45gwNi+gtYfRnGN2EBZhiGYRgXwALMMAzDMC6ABZhhGIZhXIDbCfAu28EwDMMwHgEEOD8/310EGCwvLwuPYRiGYbyX2NjY0tLSqakpdxFgtAOtEQmGYRiG8Tow1YyKirp//353d/fup517JsAAGjw9Pd3U1CTSDMMwDOMVDAwMRERE3L17t6ioaHBwcE8e+u6lABOrq6uQ4c7OzrKysocPH6alpSUlJSUwDMMwjKeRmJiYkpKSlZVVUFDQ2Ng4Ojoqv0Bi9+y9ABP0sSyIMW4T0NxFhmEYhvFAIGErKytra2t7/vc++yXADMMwDMPYgQWYYRiGYVwACzDDMAzDuAAWYIZhGIZxASzADMMwDOMCWIAZhmEYxgWwADNeQmKDf2KD36ZJH47qk2PwDUnL8n5Jz/xrBx+JnemsjD2cbTl+QNZsytmB7Ukldm2x/bg4O+iRzu4PSss/KCkzGmWqy5LyFyUtNzGb3FDNJMMqpZIjJeVH9OXHpRXHyiv9qmou1T+LbW3LGxyqGB1rmpwaXFiYW1lZc90vysxHPBwJTdcsTLcXfoZFplyqSZTUlmq+nqP701ez11fWxM7cjLSq4ROprSdSW3zK/DPa6C+aWIAZL2GrZKqOqqNbNNVk5s2l+Sc986sdfCx2pgMBnoPqkKrtv7a5wJw6KL2whQBLLTRLJuWUbiblKuMmW83OWsvymqEZuoMCahktWfFBWeWRiuojVbVHaurgf1FVG9LYlD841DM7K45kn9EEmORTGuRT1dcXsoqlWWv1TEoaTM+fuebmAmzUJ683FmDG2yCZ3KqaluZIGTIqiaXm6DNgowBvUSCzHaQqy32Zd2qnGXvdQusZsE1dVMyRMkYzbSIrsa5ta+aLMlvzi/UlhLmi6khV3YdlFVGtbS1TM+Ko9oH5cEWANdWUCropq9oqkuStwizFmHJEpswRm09fzWIBditjAWa8DSvVNPvS1LVyaekIs5wBG+TnQBXXKdtZw5zfyvYj6M2pp0EatyS3roLJTcgM+Ra2mW+zwKa9mHbLHLmJuu2mj1lyVe2JmrrSkVFxeHuHmAFLTSVHToI1lVUyX5Tc6qhqTcnNDad5BuxmxgLMeBu6TKqqaVRQPYdMTcq1MlNdvijjkAC7ie3yPsDZzZXyDr0D3jPbTeVWKmswNN5CpyugxOHNLQurq+I4d42YAUv5lJoql1scmvXSUjG5uSgpC2TMuPsMmN8BM4yHY5JPMnOOwcyFrc0FAgxhk9q2S0111na6u70QYGUTdVZqrkrNcXZHsrytDS3yZY7mHKmsCayrn1leEUe7CzQB1lTToKl68oXu2lhaZyqzYe1DWPwI2r0sgAWY8TIUsVRFV2qqIamaIdOwifAd+hT0Acvkfpvzh+OcADux1vQUek/MTp2O7Quz4ZBnu/0B1hczYFV0pYJKxyDJqmC/yFTKb2byDNjdjGfAjLehiKU0S7mFUb55rUF6txTY9w9hOVjYvTXeAQHeKqsvfGlKpuOKu21JtYB14Z3v60h1XePEpDhs59mcAW+aSUG3ZL7Ily+JFbPKcXsBNuqT1xsLMONtbJVMOFvk02RqAXNJixxH/w5YCiQ57q2XwvaukdsI8LYyKQ0lZeEXW21makvKlKscthe1bZdpq3Krwkcqqm62dYgjd5ItAqw5W+fBL/KVpMxUC5jX6kt+BO1uxo+gGW9DKqXJId+gqTJHXSVzDEnNdjID3idzUC9dof0WAkxyZf40k02zIXsWppRURVH6Ytc2KnyRv20B1azq3NzR8epacfDOIL6IgyRTOmpSfdpsNir2ovBm5uYqfgTtbsYzYMbb2FRN1Ug77WSSoy7NDpaaY/UhrEfaF3EYzCl1tF8Ya20VsLNqT8zZyjfLO/QOWM184VuVNJhlbUZTy+i+2Aq3AjLf0uxWvqXNSr60zQKYCtPY6jib74C3/h2RXJJtyTc/fN76enjLWvf/FLRRn7zeWIAZhmEYZnu6xhYe1I8YRHQ3xgLMMAzDME6wVzLMAswwDMMwzlHYOmFQ0x0YCzDDMAzDOI1BTXdgLMAMwzAM4zQl7ZMGQXXWWIAZhmEYxmkWV9YNguqssQAzDMMwzE4wCKqzxgLMMAzDMDvBIKjOGgswwzAMw+wEg6A6ayzADMMwDLMTDILqrLEAMwzDMMxOMAiqs8Y/xsAwDMMwO8EgqM4az4AZhmEYZicYBNVZYwFmGIZhmJ1wIr3dlp20kVTzT7EAMwzDMMwOaByY3Y21Dc9RPSzADMMwDOMCWIAZhmEYxgnW1taEtztYgBmGYRjGCWZnZ9fX10ViF7AAMwzDMIwTdHd3Ly8vi8QuYAFmGIZhGCeoqKiYmpra/ST4IAT4O38d7KC9+asosQ3DMAzDuCWPHz8eHBxcXV0V6Z1yEAL8vUP5Dho0WGzDMAzDMG5JRkZGZ2fn7p9Cu7sAv6Tz1a9+VaQ3QabwGIZhGOYASUlJaW1tXVpaEumd4hkCDI4dOyaydJAjPIZhGIY5QJKSklpaWnxIgMHi4qLIZQFmGIZhXIQvCrD6IBpJ6RCdnZ1I/tEf/REl33jjDSQxb6YkiIuLE95LLw0ODuIMisRLL8FH4Z/85Cci/dJL3//+98lBhVilboskMTk5qSYZhmEYX8CHBPjv/u7vdOHTkA+i4UuH2FaA33rrrW9+85si8dJLkNuXX35ZJPTaVAHGbFuuDQ7WWkU+OHLkCJLgT/7kT37zm9+QzzAMw/gIPiTAtJTQg2g4+nonBHjbpCrASKpTZCQhtyKhJ4F0GIZhGN/BtwR4cHBQFz4NehANR1+/jwKMCkVCT9IDZwLJyMhIzKfhMAzDMD7FP3wScujKw88TG0+k6b8wiKXmtJ1Ia9N+djBNc2Cn7vXOL9n7W2FNS/Ybg8raMVsCDN566y0SP0DCSfmUA/ZbgIFI6I+vsaQ9MgzDMMwOENKyS+z/NIRBZe2YHQEGuva9wJBJcvgHf/AHlNwPAT516pRI61AmwzAM41P8w0eXD4Xe/zyh/kRqix07mdk9u7D/M+CDEWD1QTSgTJHYFGCR2Id3wIRIm/4umWEYhvERfFGAgfzrIEA5IvHSS7/5zW+Cg4NFYi8EWH7q6q233kKSkJ+jFmmGYRjGx/BRAQakf4CSISEhIq3/gdBevQOWGL4Fs6qqCpkvv/yySDMMwzA+hicJMGTVQfs//+GS2MYVGGbAtsDawcFBkWAYhmEOlvczXz2c+eonef/vjaHEkZw/Nth65bf/+WnNN6Jj/92m/eGdxP/bXe3blsai7rf+4OjwD09SPcR/+TL/2x/lqPYnX1aJdTbwJAH2FOwL8L1797AsKiqyXMswDMMcDFBfaLAmwAO3Viu+DRt+rEnvdP7/Bn+j7Ts/eVoL3YUGfyP2zh8mpJL/SnzyVPRDTYD/p5UAf5z7ZwFFZN8/3yDW2YAFeO+xL8DIpOfbPP1lGIZxIVBf2McQ4E0w64UAzzR/QckfPc6B4v5hcgYlX01M1cT45q3FmBxbAvyd4xUi7QAswC6gsbFReAzDMIyLePEIepO1Cl2Amz6h5N8/fqI9eb6bXDg0/FFp+TduxWsCfCt+KfaJzRnwh4+/c7z8O1/AKvKbx8U6G7AAMwzDML7I+/c2H0FvYhDgHz1+AsXVnjzfiNOkV1PfhOzevtHr2XbeAf+Hj5+8ollucduEWGcDFmCGYRjGF3nxDngTyxnwN2Juv5n9EPY/sh+2T88gnz6ENfLDU1SM+C/H8/btEXQXCzDDMAzjPUCAHXoEnZROSQkJcMsPPoUGj/7wFJYj/7/jf3q6TJ8BP/k/Pnv6H48JExvYgGfADMMwjC+y7TvgH9kVYF2DhXW9dexPg0pJgOlBNJnYwAZuNwP+y2MbbHtrOQzDMIz74XYzYIN4sO3eRFczDMMw7gQLsPeb6GqGYRjGneB3wAzDMAzjAliAGYZhGMYFuN2HsITHMAzDMF4Nz4AZhmEYxgWwADMMwzCMC2ABZhiGYRgXwALMMAzDMC7gHz+9cvhqzhcpLSczuoRl6rbVOXV/cGZhRWxjBQswwzAMwzjBzVvx5TXPhiZmJ+dX7Nj47LLYwAYswAzDMAzjBElJSS0tLUtLSyK9U1iAGYZhGMYJWIAZhmEYxgWwADMMwzCMC2ABZhiGYRgX4EMCPLu8fix34Hs3W9jY3MdwTYoLlGEYH8MnBHh57flbd9oMAx8bm/tYYNGQuFgZhvEZvF+Aq4cWDIMdG5sb2t8mdIhLlmEY38DLBTi/Z9YwzMHezeq5XD4Kg2NYxcbmQsMFKS5chmF8AG8W4PGFVcMAh9mwWKfQNrFkKMbG5irDRSuuS4ZhvB1vFmB1XNv2+d4OZsPfj20NLh529u0yNoEZMvfQZP1YHn7Qq67ageEY38vm5wQHauKKZBjG2/FaATY8fBa5GxuXy0fV/A8f94sVGxv/mNyprjIbyqw9fy6T/5rZjZxPcvplDhlEC/l1I8Z3z4bPu6LA0upzOH91qw3Le23TVExf+YLG0UXhWe2LDPXIhlGd1AZZp7pKJi3bbyjzuGsGSXmTAV/l75M6kGnrPEhDJaEVW047mx2jc8swjNfjtQKsjmjLa5qogL+Ia1XzpdFaYMgnI4ExAG2zJTyUj50a8h0UYGkkoo4IMK0l344A66WsBdjyGLFq9wLcOaV9jTgLsONm+aKEYRjvw/sFGKJLOT/P6JaZaS1T2e3Tf5ug6QcZlblWNSZzVIuqGaMCBM1ubQlP45iQTPPTaWRiqkqahA0tBRi+ys4EmFAFWEosVUI+UOukhoGRefH63CDA0uhmYlsB1urSYQF23OLqx8VZYxjGq/FOAVY/fgWhpUxKGl4GS8Ut7Z+jHEqqZnikTNoDvbEUHloLAcNSfV4tV5FowRmcXbEUS/hYRT6M9k5YipxUVhI5WwIssnQox9B+3Deoz7GpDbsUYBjdXrAAO26Guz2GYbwV7xRgqKkczobmtN8xlq+EqYAK5WN+rCZVI4GREiInrGbhedChyRU9fJa6KNWLRAv1UA0OvgNWsRQ55KMqqZRUp/oIWkq4LA9Q0tB++LIN1FSUoWqBYdcswPtnLMAM4yO883nYsaics5nNFx90XnzYqS2lqUmDb1rlXgKMWa8czignrn5cTapQvnxSTUnVSMDkO116wgztUYWHZAZcLBuhYmT0UFfOLKkMgaSlANsyy08jow1yugz5D68aMwsw6q8anKcyZLgdQbPN7ZcyKVfZEmASCbq3YAHeW2MBZhgf4R8+unwo9P7nCfUnUlt2Y+4lwOq3X/VMaxL4bHSRkvIDWRLKlx+HpqTBgrZ+UyAJmx3hQb58ZG020i0IKox81ahaS2yJnDRUeORRn7lOaT9N7aK/U0IZ7Kh/ZoXqpJ0aBBhJW4+gSebJt3MeYCzAzhoLMMP4CN4pwOonkC+Xj1ImJeVMl4DuUj7p9NDci5ev25od4UG+LQGmx9QG5IeebJl9kXOkTvkBKxU5M6YZs2wz6S5m+ZYCbKnWLMB7ZSzADOMjeKcAA3VEo5wT+YMy52zJsPoHwZaflN7WdiDA9OrU8LT5Z+laPbI8VWuJ5b6ofNnAlofMfgWDyJR10pgevvUz3hHVWqaURvjA4JsFmHanfkyMBXhvLaFxAmeMYRivx2sFWP1WjbYJ8Rkz9e+OVKO1wJBPZn9GQsJjRzWBfAdMAowJKyXJDGJJVTmuWFTeoPf0zNwgwAbhv/tMG+gNE1kJHZdBgGkabRB7FuC9Nf47YIbxEbxWgA1fBC1yNzYwvVDzMRUWK2yorx2zLzy2bNvHxaRYltj6oBbNZQ2ok1RYfs+sWKFgkNLvx7b2z6zApOIaBLhl3OJ7s+2fB9QZXDyMMoZ8Nlum9wzDMN6P1wowMMx3Ra4NbH1JFhvbQZrhMwoMw3gx3izAwDC6WT5MNsyJ2dhcaPxrSAzjO3i5AJt/kZDs8IM+mCGTjc21Rh8RYBjGR/ByAQazy+uGYY6NzQ1NfhcbwzA+gvcLMCH/3peNzQ2N//aXYXwQXxFggl/3srmbsfQyjM/iWwLMMAzDMG4CCzDDMAzDuAAWYIZhGIZxASzADMMwDOMCWIAZhmEYxgWwADMMwzCMC2ABZhiGYRgXwALsLnz961+fn58XiY2N1dXVr3zlKyLhPC+99KJHwsPDjx07BkfNRP1IqogVppYQPT09r7/+OpWEU11dLVbYwFyJZbVm8vLy3nrrLZFQUFsI5EGpfOtb33JkF+4DDpZOqYG4uDhRwi6Li4tf+9rX4Bw6dMiRTXZ5UbkKcVJMiNV2kadoD5Fn28E2mKH2mxGr9xRzQOGcvPrqqyKxp4jDMCFWb+Xw4cMYE6jAL3/5S5HrY7AAuxi6/gxAWuyPlSgjvK1AgagGCUYfSwE2gFWqJBtkDNWiMa2t4od64CBy7I9r2wqw2JMC5XuHANMRmRGrN7F1sJZYjqS2BPiNN94Qu3zppbfffpsy3UqAHb/5QKbwbIMzQJtL6EjtCLB5E0JtgOE+1XC2kaOX0jCUNODIZYliwtuKI+0EIleB8ncvwHvbUwANQEk/Pz86LTh1ISEhyBkZGaECvgMLsJtif6x08EIndj8DVtdKbGWaobgyV6uCYuSo4wUFqpmSkpL9FmCMCLupCo0UnoI50zw42sFyJLUUYCTVkjgttNb+RXXAWB674UAIy5NpH3mkdgTYkjfffNPcAMJ8tnfQMAIbWiJWO4CddhKyNsvLxlkB3tuestzWqVjwGliA3YI///M/x7WLIaO+vp5y7IyViL3XX3/dVgh9+OGHWijrUBlbAmyoX5Vkg/bsxwzYAHZKjoNxuN8CjKrS0tJEwnnk4aiYM3Gw2uk2YXkGLEdSSwFGDcLTkcU8V4AtEautcJUA46DUwERtuFkUCQX7jXcEtxVgS8TqTdAAZPIMGLAAux5cedHR0XAGBgbg02Vta6x84403KHgQga+88gplSgxbQUVwTUOrUC0hVtgdiy2V0tl3wCi2VwKMI9V3qyEHDlsCLMptZa9U2XGwU+EpWGY6juVI6gsCvAPkIUvHQXYpwB0dHeruKABFQgEbWuK4Au1SgGl3Bmyp8j71FL8DBizAO0dePSK9IwwXtxwizWPlu+++i30FBQWJ9MZGVlYWcn784x+LtG0BduQRtNQzVSnFOrtQSRWqnI4LgUrFgCqEIkuB8g0nBEnDiEbttBRgx0E9L7/88jvvvCMHHerN1157jVqCAjR3gYPbI2RSAeRgkJUnmY6UfJVtM3FcSNrHMMCZx0F1JFUL45yrgykOgdaaLypAleBU4Nipg8yHDMinmzA6MyRISAJcZuZTiptF7O6nP/0pCpjvgcyHAwzDOlVuH1FUR24uxVKeIvOBWwJhU+eshjCRAizSpl6W+yVwThzXVKcwtBOIBilQvuV5doo97KkdXPbeDQvwzhHXy+4mWOpoDnCB0vhlGCuR7+fnJxJbCQkJUS9ZBx9B7ytyBFdHH1XXga3GGKLdMNDIAU5O6+kYybePXoHAkMRO1XET4BCkAEtFQWPkmaRjQTPkWhV9hxaI1VtR822VAYYzA+TZMIyGQP0QlrxFsxRgbGu4lbE8ZIm8REnbZBfDJ4dQT6ncRAWZeuuMWI6/6v2WnXsveR4QVrKRhp61j6UAi8Qmci/qKuxRb741sk6RtguVtI+lAAtvK+plY+ucq5jP/370FEMkJSW1tLQsLS2J9E5x6KLZFh+cAQOa2koo03KslMhiuwRhTDs1YLilELkmxOqtIOqo5TQkybfaOxNgg7RgLQ2su4xtaIzaNrPMqAIsRzq5d1keB2V/imO/nVirnUcTlpsYzgywI8CWWF5UpKPqcxTLQwaNjY2Y4GJGSzvFhmpthlOKJr3yyisoT5vYuZgBNhSeFdoZsUKsVjCfhx0IsNqhjguwU+jNt0CsdgBDO4Gtzc2XzW6w30j9ICwQqzdx6rL3bliA3ZRdCrClsjo4UzcopS1QofAUaOIlEvqbYyRptNqZANMISO/IHz16BJ8qsRQ2B1tOoGaUp9HZWQEm7bEcnQ3s4EbB1ibYO3ansicCTKifgrE8ZKz9+OOP4eC+ylKAgXpK0STHDxyVC89hLDfZvQDj2NVLyLKLdy/AljhVm6GdwNbmZgGWjwd2wA4O2cFNdhApXgALsJtiZ6wE9q9pXMrmALMcSix1Gphj2xKxWuGHP/yh8EyYBdgMCpjHC0CfEv/ud78r0nshwASqxRK1yWEawxOWqgDL9sCXO8WG58+f33ZuYX9YwVrtsE04OBLtoQADKZnmQ1YvHjsCTFBJ9KPjyicrt0Q7I1aI1XojRdZW0DxnBRiXkPB06MBVUNvuBZiqMiNWO4ChnUBUsRXLgNo/AaadmhGrN9nlZe9NsAC7Elv6B9SxEiEkcm2jjr+4vh0XYDnXsYN5wx3goDpaCrAZS2FzcBd0KujzRHJf2BZJLOm0Y0yXAkwfIyL0shoYhZE0P3+mYvYRRfWjcEQ4bWEpwHQglqgXlYQuQvnpM2B5yKj25Zdfxp0QlmYBtnNKDZnA2esZSeE5j6UAO9sAA2YB3qcj2mU7CXNAOS7A+3RclsHrm7AAuymWY6XjGN4rE2ZxsnUHYAgPkWvCEfGWYDg+AAEWLduKI/u1hVRiA7bmf06BoxBN3IqDNVsKsB0cvKhsHbKrECfFhCONtBTgXbJ/M2D7nyfYGZYCLPa3lR1PiyWiIhOGntrlZe9NsAC7KbsUYDfkAAR4P7ClRrh3cZ+7eO8W4N2wHwIsgWYIz41xMKAYl8ACzDD2sKVGGHx3M7F2Z7xJgBnGnWEB9mnM80jHb+odnNHuZpZg3pY+rItpXGdnp8hyuCX2sWznbhq/JxxYA+SJlX9HBOzv3am2yXmYg1s526fmZwCY7tOLbflbFMDx158OfjxCsicX4Y5x/IHQ/k2IHXwMA5y6chzEQyf6LMA+jSMCbCtaDCMOihmQ+eRYYngoSoVtvWPDzIy+fZO+s1OOj+axj/78yYAqLWZQQHjKaVEzCfULLgjzF4JKcCCikAnLwQL5wtvEnLMf4MSSLKlfhgos22MLUUJBzbQvwOZMSz1TRdHQR4bRf1H/42bq8Q8//FBeY5YCTN8oB9QvWLUUYLSKSkrk8+0dCzAORNS1FUtBNV9R1EhDINPhG6ACZqFCYcff/hpaa6cLCFpFyJOvZgKnzoD5Yyt02lmA9wAW4IPBPI4AGkrgUBmJOYcwjDi2itnKJxwXYPPLPKyVGMY+cw52hEyRUID26BW8AHsxDO4S5JuHKkdeBssbAsdvAghzDh2IinoCJba03zxIGU6seqKkY4aGePsfGlI3P2ABRreqbVPPhqEH5V0dDhw7lefHUoAlqEd4m5gbbC4DLDPNyKOzjzxMW+XNsrRLAVaRp4gOSu0CtAeZKihpS4AtsXVEhn6Rp50FeA/wNQHG1eNImO0T9NQRqF9yaY4Ncw5hGHFsFbOVTzguwOYAk2stxz5Dji0BJujvjF9//XVKGgZ3CfKdEmBMKAMDA1GJnCWjqUgeP35cfYRO0GdTDYO+oQHAXIa+n0Qk7GI5SNk5sXAISkro606np6exNH9Dqr7FFiDwci9IUjEVc6a5T4HjAmyoUO7dMANG0nxXR/u1I8DUU7Q79QbOfBEKT8GcadYqwpGRAcXIsSVX5s415+xYgOXeyTF0ASHLAFsC7NQZYAG2ZMsJ3TE8A95zcB0LbyvIl+/G3n33XamC+pW/ZVKFpPC2csACbDkDJsc8WDv1CBqr1G/agqOOCHqRFzj1CBoNs/wGb7r1EYlNkIOjoKXI2noGgPkkENiRYTKKcQrbmjEPUoY67cyAZZ3qQcnnt/YH8W0F2NCD5j4FjguweQZMaw0CbB615YZ2BBh77O/vN7TZ3GAUsESs3sSWdm6L2nG2KkG+oV8sBVi0bCv2OxQnSp5wsYHVHyUjU3h2BdjxM2BHgPUmOHTj4j6wALsSXMR0MVHY0+BOOoELC8okQ5oK0ESN1IIwf3aGSmJzXOva9aijihwwyB5AeXJQmByJOYcwjDi2imm711EHRAkN9yrItBRggENT3wGrGMY+x8Hoow40FN6Gwf0AwMmkQ6YTgrCkfEMDVHVUMWfiQMyjoS1wYukkbPsO2EFwArEtQWfSjgDT0EnF0BJ9Iw1zn+KgxDodtY8MAkyiQu901Z8nAWp372AGjAK0X7rJk3exhnAAWCs8BXOmeq5ULO+0VHCuZAttaRidT5HQMQvwDpAXDEG7MHQBkJcrVmmHtHnyKVPi1BmwI8C7P66DhwXYlcgQojjBlSSnbsjE3ELKJBUglYVDW+FalK+vZKYsSb+fT1WZQb6tGTA5Els1OC7AwrMCLVdvBaiwDFdA+RJ5wyElCqgtoa3sQyUlyDHPgNXBHcj7azsYRh+RaxdZ0jB6fu973yNHlpHQyZGHT21WP+hLOCXAYNtPQTt+Bgx3CfDRO+rmYsUm6D6aUIq0jlnPgDr4qn1EmEd/+hS0+g2mhhkwQLw4/g4YtdnqKXODUVh4CmrmDi4qCbZV9UlqmJpJHWG4ErDhboTK8npDDpZmAaZrVZ4x8wx4B2cAhyNWbEKnfZfH5SpYgF2JKsAy2uUlRT45agEEm/lGUmaqJYFaxoCcGXjEO+B9xcF3wLtB1rl7cNKowQDqYhYqYB6nJKLErrFVlUHkSMnk+GjYCqeFNEM6hFMCjKV59Hccxz8FbQdLAbZErN4FdJsuEjqWVxcNBSTDImurUO1A/zBomPsFxbA0dwHlY0lPv2w9gt4TWID3ABZggKtTXuLySlUL4FLDUGWIK/kwzXEBRknzY2FzeeSYQQtdIsB0T21mT8a+wMBAHBSVhLCZPyeFYY7WGrCvrI2NjfR9yACOOsqryF0bEKt3gSOVWOqN/Q1trTVcmfDRO5YCTMonEnob5MWwJwKMVWbUmwM72Bdgc2epL4YMWKqjxNmLynDSCPMukCOPFL48sXsiVNRCM2oXIElNIpmH0tgSYGfPgCUswHsACzDAlSeHHvjkqAUw1pjHMhlvey7AtjALsAGKeThUwBIarFWQaUeALbEcrM3YqY1eGfr5+cl6oJqo1pHB2jz2qeAkv/zyy/Q6AMB57bXX1KmexPIoHDwD9nGkEugNipkRqzfB4YgVWzGP/mKFMgobLlo654ZDxgSLHMuzYWgk1QwHS0sBNmOYndvBjgDjJJh7HM2w/JQDsH+FWGJrE+zF8kN/hvI4G+p9LZA5ZqFy/JzYR+0CnD31IsdOsXRqBmznpBnu2gkW4D2ABRjg6pRDj7xSaeBDPikWhToy6YI2ZBoE2Na4QHWaEau3YweyZ5gb2cKOAGOV1kQThpaIXBNitQk7453wdFCM6jFgZ3jFWuEpWGZuK8DanrYDxTASiYRtzFplqTcoKTy72BkrJWYBto+DVxegCtXRX6IdqgkpNtADysFo/vpWUJUdAbZ1c6CG8LZQSbCDi8qMI11AHIwAW2JLgJ09A5YC7KGwALsSKZaqauLKk+ENnxwqoH5MmqD3uLgc5SYGAabXRZYBhpJ7OAO2hVrhngiw/SAnHD8KwsEZsOPDnAQn2eUzYEfwVgEWnvPYEWC6xcHQScmBgQEKTEo6C86eI5e0fTxdgJ06AyzAZnZ+oav4mgA7jkFW9wTUiUgwI1Zvxw4E2EHsC7DeRiOG0UfkmrB/Dnf8Dtj+cODyd8COAL0R+9uKWG0XdxZgS8Rqu9gRYEL+ZDJusKQY7wBbF5XlXZotdinAYpdbcVaVdyPAtEcDts4A3cdbIkp4DizAnsF+CDDDMAzjQliAGYZhGMYFsAB7DIbvbHIQw2MZ8wMoFfsPsmw9KXLw2Zf7Yz58HJ3wrNh2rSVitWPYKh8SEkKPrL/yla9Yftsl4ewRqezfKwaGYQgWYNeDIcwSsXoTxwXY1kudkZER+wJ8aPMPnBzHvmZ7BJYvX+n9ExwqY4n9tZbY38QRvaQXYPLzYkjSl1ipYunUEZlzCIMA63VsQeaTwzCMs7AAux4Hh7CdzYAN2BFg+S2Ytv5syaNnwFApBz/Uo4KjE56Jb33rWz/96U/tfFKGTo4ZsdoKRwTY8o7H8dsgc4W2mmQWYOFtxf4RMQxjBxZg1+PgEOasAKvTIPkxXVsCTH/ORD4cy6eajo/yrgIttHV7Ab1MS0sTCRPR0dH6eRLIbzWCT44KzUHpVGCP6t+AqVhua59Dhw5tK8DoQbPq4+gMH0CVX69IyLWUVD+2jaTwtsICzDD7DQuw63FwCKO/VTVjqcqGoVwqE4Zv2orWylmv4Yv06KkmUP/mGJVQpgE7s8ADxo4A2wdHITwdmdSPT4OS9OeeL7/8MiUJ6DHd6xi+okjfzgJbDxgAdNRwMlFeeArvvvsuVSX58Y9/LNZtgkzh6cikIR+YcwgWYIbZb1iAXc9+DGGGv8lTBXhnEuUspEn0czRIQlqgW++88w7dLuBmAkqDVcBSkGQB+gvagoICLGVtgN5zo04saT6HOR/tFJvgvsGwCzSA/o6LknDUWSMyySFk0pC/r0DIcSDmlhCqFtKhiYR+IOZziE2EpyOThnxgziEcF2DCzo0FwzCWsAC7HjGAmZDDn5y22sH8J/Bihc62j6Dt42wDUN7+TI5m83aGbCpAPs28yX/zzTfNj8Gxls6VOgM27EIKMNqGswH9VltomNzbfwS9LVSJfURRBRwazqGhg9SSTvWCnUfQ5EjMOQTPgBlmv2EB9i3M4/u2iKImlZKYFdEsk9A/lJQPtKGO6mtIM2oBtFk+ZlclFoSEhGBWjZpJaA0CrO5CCjCgibKqLrZAMeE5qX9AZJkQq7eCyuUNAZonm2qr/B5iaxcswAyz37AAewzyi9wchKaAZlQBMwABM6upfSw3sZyn0rtSkpndCzDJISkEqnVKgOk8GObfdItgRqy2wv5aSyw3QbMN+UjSLNyyPL2KVrH8hRwckfkZAwoLbxOqwQBOrFmADVBXwqECDMM4Cwuwx7ADATY8BwbQrR0LMOmEGfMmKCl3jWaTQ6A8lrsXYFXjVQGWJW0JMJWhV8i0inBQrlS2XWuJWK2AAzRMx3GzQq01l1ePUWL++DTYwS2FikGAbeF4hQzDGGABdiU0INpHFHUPAVYfsdoHwzcajyVUkP5uhz5ORXvfvQCTgtLzZ0Daia3gY0dQL0sBppbIHPVg90OAhbcLzJXIM6BiS4CdPSKVHQgwnX9HtmIYBrAAewwkOWZsqTKNhmZ2I8Ciiq2YZd4T2cF8cdu1lphF0Q4oLzwFxx9Bi9VbEau3g2fADLPfsAAzL7AvwIyBA9AeF8obCzDD7DcswIyLsZyoiXUMwzDeCwswwzAMw7gAFmCGYRiGcQEswAzDMAzjAliAGYZhGMYFsAAzDMMwjAtgAWYYhmEYF8ACzDAMwzAugAWYYRiGYVwACzDDMAzDuAAWYIZhGIZxASzADMMwDOMCWIAZhmEYxgWwADMMwzCMC2ABZhiGYRgXwALMMAzDMC6ABZhhGIZhXAALMMMwDMO4ABZghmEYhnEBLMAMwzAM4wJYgBmGYRjGBbAAMwzDMIwLYAFmGIZhGBfAAswwDMMwLsDnBLiktLyoqKSomI3NE6yoZHllRVy7DMN4Fz4nwE/zCmZm5yanptnY3N+qa+pYgBnGW/FFAZ5fWIQGs7G5v9XU1rMAM4y3wgLMxua+xgLMMF4MC7Bn2OzcvCGHbGp6Znpm1pBpNtp8bn5haGjYVlXSZIWO1Awbn5jEcttqd2nYi3kXag5Oxfj4hDnfo40FmGG8GJ8WYAgSfBqs4VA+PKTmF5eojDRkkhny5YbkkG8wmQ9X+guLS5SUxWC0Fqvg01os4efl5S8uLWM1fKyFQxvW1NR2dnbBQa6oTS8P//at22vPn8NfWl65cP4Ctnr06HFbe8eZoNNUj6Wh8Lmz5zo6OlFDRkbm6tq6oYBqKLOwtJyclIy2PXmSu7r+nFpLbcMe4WhN3TyZlCQfKSqMpVZG3wRLMiojDWvCQsOoMVoB/dTBKy4qRoPhwy5dvJSYkIi1yA+5dNlciScaCzDDeDG+K8AYpiMjIv39/HNynsD3O+X3+bHPMJpDpaB2X3z2OWZUchyEX1tXX1ffAJOZMGwYGBh04ssTPT29J0+cDAwI9Dt5iuRTGuaRp06eCvAPgEhUVlahAKQCWvLB735fUlKK/crycL784jgq+fSTTyGrZWXl2PDx45yV1bV/+enb/qf8cnOfwv/te7/Jvv/g0oWLOJBPPv6kt68fzYiIiKyrqz/xxfHe3j5Utf584/jnX2CP8Pv6B7Kz78NBMcwjL56/AIf2aLaqquqa2rqmpmb4A4NDKSmp6lqDNTxr/OLzL1JT09afP//HH/19UGBQYWHR4PDIieNfrq2vH/nd7y9funztWjhOLE4gajt14uStW7fR7K7uHjqZOG84zKtXruLsra+vf3bss7PBZ3FODPKJ+4b3Dx3GsUN6cSaPf3G8qKgYdf78Z+/gtKAZ8LHrivIK1IyjjrkZo3af55rnCvDKymp+QXFZeSUbm8HEJcL4sgCPjo1DmaC4EBsM2ZhgNTU2wVlZW4+/G4+JnToOYjRvaHiGgR5LNR/iejowCJI1MTmFiSCKLa+sYuqJVSRyqDAuNm5t/fmY/nQ0NSUV2glxRX5BfkH/wCAcqooKY6ra3tGJdiYlJg0ODd+KjYMyoaokfZZJhbFKex6rb4Iaamvr4OBAIHuok8pMTExC+eDAUGASLdN9bIhd0Bkw3CjAllfXLly42NbR2aDfZ6AZkDpahWoNso0TBXnG8d67l4W24aifb2yg2OLySmxsHHzcXtTXN2Ar3G3gwI9+8mlFRSUa39nVDZmk89nT24cCLS2t3T29jU3N4dfCcSBobHpaOnYh94hqb0TfgACjzZBwOKEhoag2PT0DDcBa2Pmz5+7cvkO6+6yxCf1L23q0ebQAP87JpYuWjU01cYkwvizAkKKm5hboEkb/4qLi8fGJ8rLykZFRDPpPn+ZBUNVxEMWGhkfI1HyM8shBVZmZ9xISEqHlmNVVV9fgIoPSkBhAOTBvGxoahgo+uP8AmcFngtEGzEohJ6hZ1oatsKq1tQ1zQShubEwsCmDChyYhiQ2HR0ZRLCYmFhViQximhuXlFXCgag8fPsK0mEQLEoXpJlXb2taOyTEcKDpKohiGRejc3/3N32KPVIYMSbQTukiiPr+wgPsSyn/yJBdtkCVhqCH2ZgxaiDIoeivuFnKohZDSoIBAZOJUFJeU4izl5eUHnz4zgpuevn60AbcjdDJx2nFczc0tHR2d9XX11yOvN7e01tbUdnV1Y6e4E6JbByyvXbmqNWhx6aa+04sXLkKAcQeAM4mdokBLaxsqx8wYGz569NjQgx5qni7A6CnDEbGxiUuE8fF3wFCau3fjMVJjHgkFhTpiVohJW35+AeZqGMflFWPLIA55+QUpySnQBiyhcP39A/CxLeZ8WIsy5GM6iHzoJfQY6oJ8yDx2pCo6SiJnZHQMQgJZbWtrT0xIrKysgrpgFaaVmDVOT8/k5j5FMcxxIWz5qCO/QHPyCwYHh0pKy3AsqAoDHxQLk1T40MWTX55ADagZMjmwWYCknXYtDTnYNb1XfvTwEZ0rCPbP/+VnmGvKYmQ4dbgboBmt1sKY2Eb9KQLOM9QaDtQUjcfsFj4sOSkZDTZUgnOCY+zt68fR4eRMTU2jhVReu+3QBRjiitNVUFCIBL0ywEmAPz45FXU9CucTObjJoFWwTz/+xDuGfhZgNu8zcYkwPi7AGOIxWJMPB0nKJKP8bY0qwUBz7NOjEANZoVqDrJx8cuRehjEXHBqGQb9lMXIMG5KPpVpMZsol2eTklEzK6aDcO2aNmLiTbzC5lSyAHMPLb2myQvJREvcBRz/59O6du5DtM2eCr4ZdkaOwejjSkEOZEPjf/+73mPXKDpKVUxkqpi5hhjLk07zZC4wFmEy9zPbbcO3QUl5ObHtr4hJhfFyA99ZQ7c6GiZ6eXkwiyQyr3MecGozm9c9pa47VR5rtGMbrgxxq3d+8SYDRsxA1yiEfF4i8TrCY1Z9eyPLS1p9vhIWELukfd0dSK7npYCmrosJISkNSRqVcQlmlTw7tHQ6W5RWVVVXV8JuaW1KSU/bqBoJNNXGJMCzAbGzubF4iwHPzvX39AX7+MTdj3v7nn6xvbDx69PhG9I2LFy5mZ99fXlk9ffpMakpqUEDg1bArJIrSkHxw/8E//N2Pzpw+k/c0D/dodXX1586eu3j+Ql5ePupPTU6JjYk9F3yWlPXyxUshl0OwL3oG89GRD9PTM1A+M/Pe8PDIpQsX796NT0xIhJxfvXKVPvR3+LeHqvTPbUDpf/JP/7yyuob9rq0/f//QYZoNs+2tiUuE8U0BRtAi2NjY3N+8Q4Chi1A+ZOLed2R0DMcFEQ3wD4i6HkUfVoc85+Y+hV7Km2NsIpX4+cbG+XPnodPIgS4G+gcsr66hMH32Ahv6nTz13ru/pvcsqP/mjZtYS5tXVla1tXfQPBj7guQHnwn29/NHEs2gTw4iE0sUnpya/s2v3yMBRs61q9daWlrhs+2t0RXCAJ8T4Lz8wsKikoLCYjY29zfcL3qBAEP/MN3s7e0bGRvHdHZ6ZjY6KnpsfKJ/YJBE9Nmzxqd5+fIzEJo0xsaFhoSSHq893zgdGITyXd09kGFMW3t6escnJq+EhvX19d+7lwXhjIyI7Ontw4Ztbe2YZ9On8TF/ffo0r7W1bWh4BJKclprW3dM7MTH5xWefY2KLwvkFhZgcoz0oDNsyA36+cei3h6Z5BrwPJi4RxgcFeJVhPApx4XoahnfAUFkIZEtrG3QUyjc2Nt7R0dnZ1U3iB+nVbHCIBBg2MDiEaTH5MGzV3NJKH+CHQUc79A/qozxKQmIx8R0eHkGSqhoaGsZaCDAlocdYhX21trVDs5HEqll9igzlRtuoWpSprKqmd8CNjU2pqWmy/Wx7aOISYXxQgBmGOQDMH8JyK8PcGpPvoIDApMQkpNRV9N5XU+it+Wx7ZeISYViAGYbZD9xcgGEQYXo3bMhn228TlwjDAswwzH7g/gLM5ioTlwjDAswwzH5AAjwzOz85Nc3Gppq4RBjf/BDWCsN4DB78Iaz8guKi4lI2NoOJS4TxQQHOfZo/NT0zPjnFxub+VllVIy5chmG8Dp8TYP4mLDYPsuqaOnHhMgzjdbAAs7G5r7EAM4wXwwLMxua+xgLMMF4MCzAbm/saC7AlD+7fX19fJ//CuXP3s7PJB+fPni0qKiL/emTk6cDTjoxuz58/Px98NuTyZZG2S0py8ufHjvX29Ii0bQYGBvxPnspIS6dkclJS+NVr5DMM8GkBHhkdGxgcoq+8GRwcgsEbG5/Akn7Wno3NteY1Ajw9PV1aUrq4sAgfYT42Ora8vNzS3Kz9VcLyyvj4+Pz8fHtbG9aurKw0NTa1tbbq222Mjo4iZ31tfWhoiHLgJCUmkg8unj8vPJ2HDx6QU1RY2KNr5IWz5yjHDhHhEdBgtCrr3j2RZYOe7p7Ozk44d+/coRw7XA0Lw7IgL7+jo4NyoqOiyWEY4LsCPDU1/eRJ7sTkVFhI6PDIaFlpWUFB4ZL+m6PvH36/W/+2d3UoZGM7ePMaAYbEgqjI64hxTF7v3r6dkpS8sLAAAUbO8c8+r6qsmpudRUnkjIyM1NXWFhQUIIkp4+Li4tTUVGJ8gl7TRnFRUW9PL/nAIMCYHJNz88YNcs4FB5NjB1kJSaYdOjs6xkZH4Tx+9Ihy7BB+5SqWuPnIy82lHBZgRsV3BZi+on1O/1UyTILrG56dPRO8sLi0vLpWUlLKj6nZ3MG8Q4AHBgby8/KgoxBFenSMSSGtIiLDI4S3seF/yg/CDJ17+kSIVkpyUta9LGxOSV2AXzz+tSXAEMjBgQE458+JAg319dBC8g3QryXiDiA9LY1ySoqLLYcjNIz2npaaSjndXV093d3kG7isV1tbU4O5PuWoAow7ksZnz0SC8Ul8V4AhvQF+/k+f5iUmJN6//yAtNQ2xAQEuLCw6G3w2M/MefxU7m8vNOwR4dnY2+PTp82fPQlwbGhqgRp9+9FFw0OkH97XHxeWlpYfeew+3v5j1IgkxDgsJDQ0JOXniBKn1o4cPcx7naBXpjAwPJ8THi4TtR9Dg0oULpwMCsXf4z9ef/x//+6srNn7bETsK8g8IPn3m+fPnSEJQf/CXf0WrzFy9csXf71R9XT0lv/9nf0aP1s1gbD175kzM5lwcqAL8i3d+VlQoXlczvolPvwOGxI6PT9AkeGJyalJ/G4x/ZFSGjc2Fxh/CGh8bi76uPbgWaZ3cJ7kyJyw09H62mPWCyxcvYfIqEgrIrKlx9FtN4mJi5xcWRMIuUO7EBPFsfFtSk5OjrwsBxoZREdfJZ3wWnxZgNjY3NxbgBZ0DGBkY5uBhAWZjc19jAWYYL4YFmI3NfY0F2HFWVlbodS94/vz59PS0g+MJhj9bH84ysP58HSXpzfS2zM3Nzc/Pk4+2IUk+w0h8ToDFjzFMTLKxub9VVFaLC5fZjvg7dyYnJ8k//sUXMzMzcTGxlLTD2Ojondu3UfheZqbIsg0qREm/kyfps1p2KC4qrqyoKMgvGB8fR3J1dbWkqGjGMZlnfAefE2D+OULGg8DlKi5cZjsS7t7FGYMzNDhUUlwCJzU5WV9jj/y8PFLT+Dt3KccO8Xe1Mp2dnU2NjZRji4sXLmC5uLiYcFd8YLumqooFmDHgcwLMMIxXIgV4YGCgvKwcTmpKir7GHlKApVJq2Jjf0p8/dXd3N24nwJcvan8BDAGWus4CzJhhAWYYxhuQAgxBPXXixOzMTOzNm7TqaliY/yk/8g309/Vn3cuamZmRX8Hxg7/8q6qqKvIN3I6LQ8kAP3/S7NwnT35/+H1aZSDn8ePm5qbioqLREe1rs4AqwJDwP/+v3yOf8WVYgBmG8Qbi796dmJggf31tfXR0VD7A/9sf/tDOW9v5+Xl6Uwsmxsc/PvIR+WYwQKnV/uKdd+x8emtychJqTf7qykpJYaEU4JDLl+W3QzO+DAuwBva7YPV39w5+3PEAcOpdIOYBe3ImMWLZPwM7u2728Kxue1rUj8Wah2DkuE8XM7sEF4OtTxo7Hj64HnBRiMR2LDr2ZR0ADZCfiAa7H3AZ78DXBbivV/tW97TU1NqaWnp+pfLRkSPCOygQ/5aDRW7OE8dPTnZWVmlpqUjoNG9+Fa1TDA0O+p88JRIbG4MDA4Y2ZKSl7+CPK/7ub//WrIU7IyvT4rdrOju0H6sBaN70zEyt/v1HT3NzcQ7htLe36ys1lhYXzzvwUzkMwzD7ge8KMHTu4vkLUj9ampqw9zu3b0OSPzt6FH5jY2NhQYGhSZUVlUEBAVn37qWmpFwNu+J3QvuDhIaGhnPBZ+nH1M4EBWVmZD58+BAbwscukJmRlhYYEKBOsuF/fuyzyPDwL459huS5M8Fng4NR1e1btwL8/OiXzi6eP//44cOo61GYpn3y4UckWu/96l0s0UIsJTMzM1BK+r7ckMuXv/zii27l2+HRkt+++17wmTOjIyNlpaU4qJqq6kcPHmDvfidPlpeVoebLly5d0j82ooJG3ozWvsYWBeJiYgYGta+2x+aB/v7JSdrnS7s6u+gR3JOcnNMBgePj4yh5Ljj4xPHji4uLIyMjp4OCoiIjUUDl17/6FZaoHOJ3/PPPcd8TFal9J99nn346MT7xxWef3YqLw35jY2LCQkP9T2l3AGjn8vLSmaDT6k0SjhrnjfwrYWEogyMtKy374He/u6R/BjUdAjw9Tfci1dXV7W2a9GK/p4PEb8Tidudp7lM4DMMwB4/vCvCXx4+rD4VampunpqbgXDx3vlefFkOT8vPylpeX9fWChPiEp0+fzkzPQGxoLhUbE6t93CMmNuq6piI11TUkErOzs9BRiBD8uJjY+vr6yxcvwZfcuXU7PTWt8dkz3Ark5+WHXLo8MzONbTEtowK9Pb0jw9rmoKG+nvQbBX7z7q8pU0IiB3HFEudQvtCSlJVof5UBIJA5OTk4Lvg3dHHFVrlPnqB5JcXFuBT0Ui9YX9Mex10JDR0eHqaculrtqyEgvVhirkkCjMkxDraosBD1nwkMQj1wGp81ZqSny9dyEtnLMfpnZOrq6mb070ygVuHkh1+9iqr6+/ro7GVmZNTVas8nqLxKZUUFOTQVph9mpykvSElOGRsdraqshI/2UCZYXV35/Ogx8tV8xqN5kH3/wjnxPKO6qurE8S/pj5G2Jfp6FG4ZJ0xRY+ZZQwNKOnLThusZgYAxhC6wZ8+eBZ8+IweTgrw8NI98RxgbGwu5pI0eiIK9GiSf5ubirlQktgI9UOOivKwcd7dP9AdI2Lvh6RqzG3z6EXTTs8bsLG3IhlhCRKHBoyOjxUVFMTdu4vqbm53DNFH+CBpRkJ+/srwMwcP0KzUleXxsDDIMYYCI0jQOkU9nszC/AJmYCsOHwqEeEnhJ7M2YtJTU+rq6oaEhTMQxWIyOjmLbyYkJerfU3NRMc0pM1CCT9CUDWVlZI8PDpLWSa1eu4NRhGgofDYOGGXQF01bk0G+2YPigv7j47XvvoTDm3LhpgNKjDYa7DZXBwcHICE3m854+RXt6enqwbGpsIo2Mib6BbdEAnEgcAkQXKngvMxNnINvqKTGBaS5ahTM2NTmJzePv3kWdHR0d4VeuYC84LU+fPBkcGOzr7UPhe5n36EffcB4qyrU/MkHl6A462/cyMlEV9B5+aUkJHUhiQsL62pr8fToCtzKPHz0WCcaLSNCvHzgL8wu4u4VDS/vgaqGbyHgHfmD/7m2tTHZWFi5OyrEF7llxQQ4NDiH0KKeupkb9M6QLjr37QFxDvPv7+yOuXUMSrW1uasLecfHjYBGVcHC1I2dqcgrRV1FRMTQ4SNsODw2Vl5VRgGD8WZifx008Zh1oGKpFnbQKjI+Nd3V1YQDEKoCQQazRPTckn+7vU5PF33TduB617eEzDuLr74BX9dkqrmmSNFzruEYxyaOW1NfVz86IT/EQuPKSEhNxvnBPikuWNHVgYAC3k01NTQgJiBkMDlYhUGmWjMDAVuqEW4urhmeY42IV4ictNRWxipDAqsLCwupK7a8gamtqa6qrURVkEk5tbS380hKtnQYBRsykp6bS4/SG+gY0YGlxS48iShPu3JnRP5HU2dmJeuBkpmegZjpSHHjOo0f2zz+tRYNTkpJwluBoB6tPN5saG6Gj2DVaUldTC/lE5ujISHJSEu4qtI1NoEk4Ihx7W1sbtkpJTsZphHKjea3NzTgbba2t2FaOWfL31ZGD+Toc9AUaQDPyqsoqVNjSrM3gIbHUAIwdmD3TwUrkAwbGy5B/htTX11ddpc3t5E/22qGwoJCukIS72/+oUZL+w0eIU0yFKccWYSGhWOJm/c5tcRNg+Dvg88FnhWcXbI5Yw2By9JNPkKyrq8PtNSIdbUbUnD97FoeMnOzsbEhsUEAAhqbenh7coeKWtLurG3fwaAnKIKwaGxsRp4gOEm+sxahFewnw88PohA3b///s/WeQJcl93o3qk4IR+iJFiLz8pFDEvXFfvFeEDKX3JQWSAiRRAl6JEiEJkggSIAwJYIHFArs7u9iZnd0d39573z3tvZn23nvvvffe++6Z+5yT1bU1dU6dru4+7U4/v/jPmazMrKzMrKz859NVp47xYsS6FjvKt+depaXf//g3IUHBYhP7Qs2LMLkgd90Bn5vszCytbxbeZODUP773Ea5nnPIP3/9AuSa4acTGxMi3pSMjIj795KofiCO3C9kBY1kp3piRnppqTDH8CVfrp+9rqqrFVZCWImXGyli+4aIiLtbwbkv4JywWEYBrlG+CqPAy/jEcbkysBYEFB4wKaP01GEtYERBv9hgcHFT+IQ2+sKy0NMP4QAaIi4nBJwR9ZUUlemBjfWN1ZXV1ZQXdMjI8jB6AdXV2il5CEhpi3O9NkvFPBeil0WHDl6Pgv0UegDVxgfHPhOLPSwD+G45fhMkFoQMmhNgC8p+gQVlJqauzs/zj/D/+wQ8aTh6DUAHB5+nu7mBnB92MTTieP/qDfw0fI1JV1NXVodjMDElYQzhWnohIFZjKUKaHm7tcJdWfoJUO+Onjx69OylQxODDoZO/g4+X9+PMvRkdG9g8OnBwd/X18U5MlvY41gfzakKSERCcHx5Sk5NfHx0eGh0y9ggODHO3tTZuTk5OD6n3x8LMY4x+Wfv3L94YGBxvr6z2M0nZhft7NxdXT3aO2phabWZmZ8LjpqdJSIDQ4RM/9cqIHOmBCiC1QXlYm3sCsAu5HPJ+hh4WFBS1Xbcrjzz+XQqcB6ent5SXLSkhPNxcXEQYvnp/hgSwZuPa52Vm4WKwhsAmnmJqSctlTKMpv1xDr5BzQAV8W8p+eRKNwkeRp/NxKgL+/eAzELPIKWidmvxorGB8bz9DxenoVek6K5bfebxoR08QlMTU5NWv8q6AMDgbBcfGRDba2tjY3NiAqpG2LoJno5LFR6bvIOtGSXIRogZG2s729u7srpggM9Z2dHVuaQu8CdMBWQ9xJQldinYurQmweHR7lZBuedUJYBFQOFct2fEa+fCk2ZZBzy/jMVGtLC7yXWDvDE4hIccJEsTiWCAA48rbWVsSITQF2ke/1hgUbnqUEhqeojHuhyF3jUx4I7+/vi7+S7e/tIR6XN8KlpaVYXIsKbBtdEQJKUJSoFXbHgeRjCYaHh4cGB5cWF8U3lzbWDT1gqPP6Bj5xxpEfDUQhSBUtFSUgg2gm8qCBwkUhg9xYVFU4dWMJhufURLwAagDxYaGhKAQVE0scUZQ4BcpjIRXtlTKYLIaiIqOQWTwEbugiYwXEJ5qg8p0D/f0rxrtuCKNY8ZQfKo0YQ0cZfyNWVAabIoAS4mJicQiEY6Ki5KdYCSG2DR2w1QgLDcN82t3VhakW87J4pgMtys3OFnMrnAEmYvlZBoF404X8NIRgYmKit7unrLQUUzMcKtwbysRJ6u/rHxwcHB4c2t/b/+Kzz5aXlo6PjvJyc5eWlnq6e0pLSuEVnj95quzGRXi+sbHmpqbVVYOLjQgNwyem/rLSsvn5+enpaU9394S4ONR8ZmYmNTkFnrggLw8ZGurra6prkLmsrAweRbiZzFeZyLa+9paLQmPFQxxw25UVlaq/4NXV1Ukho3dBD7wMD8dRhgaH8vPyCwsKvNw94J7FtwybGhoSExJmpqZra2qQJy/H8OWisJAQVKCivBzt6uvtFX0VGhy8troWEhQEj1hVWTk5MVFXa7hfJdPU2FhbXYNUVA8eFD2Tm5OLbkSrxROqKCctNXVycrK/v39ubi4hPh6RgX7+a6ur8g02QWJCIvonwNcPlcFpRRNaWlrycvPm5+aWl5dV/hKlCR+fEBePgPgxnNKSkuzMrNnZWbS9oKAATRsfG0MqKlNSZHj4PD42TqwAAFJ9PL1EmBBiw9ABW43enh6758/rjI8tAPlJDfH1XCC+kJqb/dYfosUPthTmv/VdVUzfU5OT3p5eCEBRiUj4HiHd4NHxKf7I2d/XB2+Rl5OLbEnGLzzA1ypPZ1ZmZm5OTl6O9M3Fl0YZhzz5uXnYa2xsHHuJZ1WGh4Yy0zPgV8SbKyAEe4wPjtbW1orzgqMvLixGRkTApWFTScqJx1pdXe3r7RNhgfw9SOweEWZw/xlpaaghVPXoyGhxUXFIYBAi4ZDgLNvb28Wx4KqLCgoL8vKRE8C5Fhu/Ub2wsBAcEIg8/r6++Xl58F6y35XfvyFATYRjQxgLFHxmZ2ZiuQOP6+rkjE15oYCKjY+Puzk7G2sYjm6pNL4SRAZOFEsoeGicFHhcxAQHBo6OjBTk54uilIjvkoGsV4Zf1xGPy1aUSY/q4FyI941gjYWlD04KWoFN+UFW1AF1njW+dIwQYtvQAVsNyKP6uvqPPvgQYcyzj7/4AgoM4ZcREeVlZfAHjz4zPLLx6f0HhtwnQFnCR8pfche0NDfn5eWFBoegQ+AwIAch+BAfFBgYGf4Su6DkoICAxsZGRPr5+iJQWlzc091dXVn59PGTwYFBYzEGUKvIiJeQkqOjo0j9zb2P8vNyEenr41tXWwdP/On9+yXFxZCGOKift3dHR0dGekZDfUNzU3NSYiKqvTC/gPpHRETMzc7Bg2a+eiX+bCuT9erVFw8/a4MqbG5GxTLS06FopTTjOfXy8MRe8OilxSXw7inJyfBww8NDcFHBgUFwb3BFYcGhyOzh5h4fG3t4cADhDnkKEYnd3/v5L7AUgH41OtTY+Lg46H44P2jcoIBAtMXPxwcOG2FxRMEHv/p1d3cPxD3CEeHhWBvBwb8Mj0DTfv7TnyLS2dERiw80HL0Hee3j7Y2i4KG7OjuxyDCWIfHk0WOcBUj2paVlX2+f4qJCOM6lxaWysrLnT59JmU7AWcNBcY6wIDA8FmTUsvYv7FKTk1H/zx8+bGlq3traLDK8ZDQiJSnJ3dUVGdzd3KCS4ZVFM40lEUJsHDrgSwFTufwJMMuLgFnEX3dVoCvk3eE5RAC8NopgJAlEpJzhQONVVqJjRX7TvZTsG4eCnEdwsC/VH/Gm50guVgTMIu8lhpoyZ5hxnSHCykKUPSAPUAhEeF8RfqtbzB1a7LW1tSXUv0A+F8ZDSXspT4GFi0HkN3u+ZJTFKs+7HGnAGFTmBJYHCSHE9qADJtcMHKTZpYC1QOHy7VVCCLk50AETQggh1wAdMCGEEHIN0AETQi6FQ0LMIY0PQgdMCLkMDg4OS0oramrraTSVSUOE0AETQi4DowMu393b39zaptGUJg0RQgdMCLkMhAPe2d3b2Nyi0ZQmDRFCB0wIuQzogGlaJg0RQgdMCLkMrOuAt7Z3VDEqW1peWV5ZVUWez9bWNwyfa+ubW9vKeJq1TBoihA6YEHIZmDpg+DP4NhEDhyr8nPCs+BR3B8062qPj1/5+/uJ2MjZlvygCoiiEPT089/YPtnd2V9fW8Sny4HDYlItFYHV1TaRiF5hxVykVocam5ra2doQHBodSU1J39vZFEs2KJg0RQgdMCLkMlA4Yjm1sYtLZyTkxMemv/+p7x6/fFBQUJsQnBAYE5uXm7R0cent6paWlu7m4hoaEqnzw5vZOSUkp9vLx9qmuroHvhIP08fENCAgsKzM85BUR8TIuLt7Xx9fD3ePg8AiuOjs7x8HOfnFpubun94d//QMc1MnRCUnzC4uO9g444heffY5yBgYGcdzIl5FZmVminqjYD7//14dHxwjD6//m3kdw3nJNaNYyaYgQOmBCyGWgdMDwqb7ePq/fvIHbW15egT/u6u5xdnQKCQ5ZWFxChsmp6YqKSmSGYhVzNHaRVSx29PL02j84RCT8Irzp/uERXG9GegacaEdnF/ba3NxCntHRsV/98j0PN3dHB8cM48+RIRKuF359Z2cXvhRe3MXZpamp+eDo+Ec/+KGfjy988IP7D+CbcSC42/d/9WvkRxhiGtVD+aIONCuaGCEE0AETQqyP0gHDlYYGh4xPTC4uLuXk5CImIiwcCnV6ZjY9PQPJPT29FZVVs3PzyItUfEZFRXt7eQsffPT6jYuTM/KPjI7BDYeHhY+NTywtrwT4B8BlwqeurK5VVVXbv7Db29uPioxCzpnZuZGR0d39fbhbuGrI4vX1jdbWNhwIO8bGxCLyZXjE0PAIqtQ/MCjuH0MBwyvjEOKgH77/AXw2wjTrmjRECB0wIeQyUN0Dhpedmp4ZHRuH/4N/hY+cmJiE8BUebm5uHt53dnZOOGARA/cswjA4yOGRUWRAGHmmpqbhzkUSfDCKhYTFLigNznh8fALHWlvfwF6IRB6kIoxUHEXUAZGo0szMLJy6kL8wlNzW2tbS0opwb29fTnaOXH+aFU0aIoQOmBByGZg+hHVbTDwdJh7skiNpVjRpiJA76IBxCOmFpITcBqSBe9u4vQ6YdtkmDRFyBx1wW1uH6sWkNNqNtYrK6v39W/lD/XTANC2Thgi5gw64ta1D/HGJRrv51t7RdasdsPjyLo2mNGmIkLvpgPndPtptsVvtgKuq6xqbWmg0lUlDhNAB24ZhUamKodmG3V4HTAg5FTrg89is8bsN127iexq7e3vd3T3KeJrNGB0wITbMnXbAEI5zJ9/9X1ldW1xaRgCJSDZ9sTuyIVJ8g7ChvmFhcUkuB/54y/hCWnwiLN4egFQUaFmbIs+SMQ9sfn5hzVggaoJyRGWUZsi8vIIcCCMDKuDr7bNleL/PxuDgkMigrBXNBowOmBAb5u464N29fR8v77Gx8V+99yvxsrrKyqqp6Rl4PicHx8zMLOHVZJubX0hJSc1IzxgaGm5pbsl8lRkWGnZ4dIy9RsfGw0JC5xcWf/HOz0dGRt1cXOFKoyKjqquqh4dHlIUoDc4yLi4eeYqLS3p7+3p6ep2dnF+/fl1f3xAcFFxQUKh8ETw8rq+Pb0lJqbub+/7BIWqOA/3tj/9mb/+gvaMzOzsHGVCf8vIKfGZlZmFT3pd2e40OmBAb5u464J3dvfqGRjHNwV3FxyfYv7BD0sHRcUJ8AlSsEK9IEs4Mn5EvI+2ev8DOHR2d+MzLyz9+/SYsLDzAz//Jo8dHx6/LysqxI3wqkjzc3OHIY6KiRTkqSY3IxoZGLAJE4avrG8gf6B+AWhle5TMxKeJh8hc5YqJjcAj4ezhd4XF9oIC3d1CHvNw8FIjmLCwstra2paelCxVOu+12RxzwyvKyFDJHeGioFNKgvLRMCr154+HmVltbK8KHBwe/+eij+fl5EXaws3NxctIzybS1tj178qSstFTa1ub4+NjF2dnf10/atkhcbOzTR48nJycRxlLbw929ublZJJG7yd11wFC94aFhS0vLgQGBnZ1dDY1NY+MTULfweLExsbPGP03DIiOjUlNSkb+vrx+iE4q2qbmloaFxaXklI+PV4eFhSnIKtO9HH96Dd/zw/Q/q6uoD/AMgo7OysqFxS0tKUUhlRWVIcAgC8sQKGx+fQOaZ6Zmy0rJQ41vpY2Pjjl6/mZqaHhgcEn+Chh/9f/7jN1Hdja3t8LBwuF4o4/3DI7j85eWVv/ruXyIHmgOPi/qUlVfMzc1DQCclJtEB24bZhgOem5vr7uxaXFhoamoS1/jU5GRDfT2cIsK7u7tPHj1aWFjY2jJ8Q3RjfWNlZWVpcWl0ZMSwubExNjaGAIDTGjFGzs7Obm5uiMiZ6emC/HwRBkWFhVLozZv19fWCPCkpJysLn/sH+1UVlSLGAlmZmfiEA14wOm8LBPr7o16oz6neenhoaHp6GoGkxEQRA1KSkqUQuZPc6XvACMwY3y6LbThR4XQhVeWwyCPnn5tfELd7kQGRcJlQq/B8cHtwh/sHh1DAcJzC+SFevLoW+R/efyB+YkVpKB8lGA5kvH+MAHZBvDg6VgYim3QzeGt7cXEJ2ZC6brxLjZpjE4bAPGKXlg1JG5soRNqFdvvNNhxwTXX18OBgVGTk7MxMc2MTYubn5paXlrw9PBHe3993dXLe3t4+PDS09ODg4Kd/8zdzs3M7OztiMy0lBQEAB/wqI6O3p9fT3R17icjnT56KnILCggIpZHTAeTm5Ipybk4NPrJj16Frh0SGdBwcGRIwWPl5eIhAZESECWgwODK6uriKgXC6kJktNI3eTO+2ArWuGn1QrrzBbOOJUMTSaHrMNB9ze1g75Cw26srzc1toKhwrJuLO94+7qJjJ4urmLgCA+NlYKGcnPy5NCRjHt8MKuoa5O2n7zxu75822jdBZoOeBX6Rn4hAPGagAB+PK62lql51YCN49PaHSsAxDY3NhA2JiixsPdUPPl5eWS4mIRU1Fefnx8LMJKBvoHsP5AICM9XcQApQNuaW5ZX1uXNsjdgA7Ymqb6IzONdkGzDQfs7OTU1NgUGhIMB+zu6jo8POzk4Bjg5/+bjz+GJ0aG8LAwX28f4Y8TEhJ+c+8jaGLh/KIjIx8+eODu4ooSJsbH/+aHP0Kkl4dn7ImTXlpcFOpWoPUnaChpaGV46yPj67UnJib+8i/+QiSZUl1V7Whnn5OdLTafPXna2NAgwiowZTnZO3q5e4jNvt6+v/zfmsUGBQa9ePpsaGhQ2lb8CRoLgq/9wR/iU2ySOwIdMI12c+2OPIR1QRobG6XQmzcBfn6QtiKM+eTxF1+Ih7BU1NXWnXp/VwbLBSl0GlGRkTonMfhaT3f3np4esQkH397aJsLk7nAXHbDR/375YlIa7cYaHTAhNsydc8BdXT2qF5PSaDfW6uob6YAJsVXunAMmhNwFtra2DoxfcwLb29ubm5sifCqbGxs6J8SdnZ31dV2PTWFmQ0754SzUTX6Km9xl6IAJIbYGPG5JcbFwwOtra2WlZYP9A4WK57O0KMwvGB8bi42OOXUumpqYzMrM3NjYUH6tSIuYqGjktLezE49ZoXqhwcEiidxl6IAJIbYGPJz4uhHIz80TOtXHU/rOrgXcXF3xubuzk5GWJmK0KCspEYGUpCQRsEB6muGrRz3dPaOjoyLm1Nd7kbsAHbAZzH6NjxByW1A64JycHKhPBHy8vEUM0PrCj5uLwQFv7+y8Unxb1yzyCz1Skr98m5VWscKdd3d1j2k4YH4B6W5y1x2w8jJINq5k8ZmclDzQ3y8izTI/Px8SFIRAZkaG5SsHvhxrandXN2Tb3Niw/M5bQohVUDrg1dXVysrK4eFh+Xu9/+aP/mhre1uEVeTn5U1OTMRGx4g/X29ubv77r39DJKkYGxsrKiyEtpbfE/KtP/0PfX19IqwiLjYWiwC7Z8/l6UI583zwq18p385B7g533QHLX9uHTx0alL4gv7u7W3ry9yWzRL2MDDu5fmprakTALIfGb/1PTU3NGF8D++CT+8ZoQsglAgeMS/jLh7C2tuSnpSbGxx999rkIm2VjfX1vd1eEXZ2cm5sM7840C44iFzs3O/fi2TMRNgUzG9YByoewZAeM2ea7/+t/izC5a9xpB7y3uyffkokIC5cvj5aWlnrFu+5U9HR3r6ys+PtJv3/i5+MjAlqg2KiIlyIc4OcvAoSQS2VnZ0d2wEqwJtb/9154Ryl0GrjM9RcLzy2W5gB7yTMPuWvcaQeMoT80NCTC6Wlp4sWw+8a+iImKwufw0HB7m/r1NNNT0yPDI/LLcaIjI0VgZmbG9D3vx0dHgf4BhoDxGnM3PuJBCCGE3PU/QYcESV8GgDNuMr7QrrSkRPw2C8Lvvfuu2cUpRHCAUQFvbG7290l3i58/fWZ6i3diYsLHy8vN1XV7awuH8PU+RS4TQgi5I9x1Bzw1NSWF3rwZG5V+dlTm1CcjxG9rCyrLK6SQBgcHB/r/SEUIOTeHh4furq5tJ29XDvD1c7C3l//qa4HNjU1He4eXJ/eMLIBrOdA/wO75i5WVFSlKGyzuXzx7VlVZJTZDQ0KSE6UvL6FW/r6+Wj/2YJbkpKQm453ppaUlEXNxQgKDtGant47y+nVwYJCDnb14scnQ0NDkxJdzIDkrd90BE0Jsj+3tbfknGdrb28VC2ePk1w8t4ONt+KpSf1+fhWevBFWVleIOcerJzxVbIC0lFZ+vMjJkb636GlJ5WZkUssj6+np1dfX+/n5KcvLx8fGjzz9fXFiYnzP8bNTGxoZ40nN2dhZhSIv5+XlkFnfWMLW2tbYO9PeLe9XoH4FIXV5akqXI9tbWwsJCbU2NqOrB/v6jzz5fmJ8Xm8NDw0ODhtt2cmeKH2Qk54MOmBBia8C1yF9Dys7K2jL+YLC/r/TgpAXEDwseHByc6lYrysuFZFR+D1gL8QPDgwODw8PDIkbpgFGOHgc8PT2dm52NupUUl2RnZcKVujg7w4OKdYChzsaaZKSnLy8ve3l4Tk9NwVUHBwUhJ/zl0uIS/Gh0VBSmWfhRYRPjE9hlf28vLydHTL/4/PzTh9jRz3i/DALdydERRxHvznz9+vjjex+9/96vZFkc9TLS7H06ogc6YEKIraF0wE1NTXBFCMhfWGhqaJC/PqTC1ckZn6Ojo+KJEABvJwIqykpLhU8SP/UPWpqaF+YXRFhFYkICPgvy8uEaRYwFB9zZ0TFn/JlkFdDcQoaur62Ju2Pubm9p+qzMzNGR0cKCAoRRvnDMmRkZqKeLoxM20S2bm5vwqUMnjI1J992UD5BGhkfgMzwsTGy6ubiIAKiqrIIjR0C8MgxERdIBnx86YEKIrQFPI/8JGu7N28PT7vkLcQ8Ym9/44z8R4tWU1dVVJweH4EDDa3ZARUX5Zw8+FWEVKMHTzd3u2fPFxUVs7u7s/snXvqY1g8F3OtjZKd8uEBYSIoWMKB3wf/i3/06rnMT4BE93j5zs7Meff4HNwf4BJ3sH+xcvxF+hwecPPxNNy8x41VBf7+rsLFzs1NSUq7MLdHBudo4x41v4+/p98dlnWHygnMaGxs8+/RQ+9enjxz3d3UjNy831cHN3eGF4kTUq5uvt42Bnv7ggLTX0/GGfaEEHTAixNTCT+Pv5yQ9hKWlqaGwz+W6hFuIddtKGRWZnZro6O6WN04D3lX/CAcuCQD9/qF6xubqyoufXHUzZ3NhobGxMP3mFNQ6xMD8vwpfH2OioEMTkfNABE0LIrQeOfPfkTi3AnK7/LSLkuqADJoQQQq4BOmBCCCHkGqADJoQQQq4BOmBCCCHkGrhzDrirq6exqYVGuxVWW3eGNxQSQm4Xd84Bt7Z1rK1vbG5t02g339ra9X6zhRBy67iLDnjV6IFptJtvdMCE2DB0wDTazTU6YEJsGDpgGu3mGh0wITbMnXbAm1vbs3Pz+ER4eWV1YXEJASQieWl5ReSRDXshfnFpGflXVteQX5SDD0TSqdMuw+iACbFh7q4D3t3b9/X2mZqa/vV7vzo4PAoLDautrZuemYXrdbR3yM3JHRocUk6Fvb19jg6Or15lwk/n5ua9yngVFhZ+ePzaz9evsbHJ7vkL4chpNCsaHTAhNszddcA7u3v1DY0IwHFube8kJSXDiULaHhwdJyYkbu/sCoeKJBgCY2Pj8/MLEL4tLa19/QMoIj8v/+j4Ncrx9fHFJ/LQaNY1OmBCbJi764D3D49CQ0IXl1f8/fw7O7vq6htGR8eGh0fgbqOjoqGM4YBhkS8jU5JTkH/A8GPaI7Ozcw0Njc1NzdDBGRmv9vYPsjKzhkdGoYz3Dg7leZNGs4rRARNiw9zpe8D4f2Z2Dl4W2wsLi+J+MDTu/MLi3Mm9YWReM+ZH/OLSMj6hkpEZ8eLWL6KQGWFRJo1mRaMDJsSGudMOmEa74UYHTIgNQwdMo91cowMmxIahA6bRbq7RARNiw9xFB2z0v2+9cZdGu5lGB0yIDXPnHDB/DYl2i4y/hkSIDXPnHDAhhBByE6ADJoQQQq4BOmBCCCHkGqADJoQQQq6Bu+uAX79+7ePl7efjK20TQgghV8jddcD5eXn4HB0dPTw8FDGEEELIlXF3HXDmq1f43NjYODg4EDGEEELIlXF3HXBDff3uzm5dbe3x8bEURQghhFwVd/ohrODAwOamZmmDEEIIuULutAMmhBBCrgs6YEIIIeQaoAMmhBBCrgE6YEIIIeQaoAMmhBBCrgE6YEIIIeQaoAMmhBBCrgE6YEIIIeQaoAMmhBBCrgE6YEIIIeQaoAMmhBBCroE754C7unoam1potFthtXUN0sAlhNgcd84Bt7Z1rK1vbG5t02g339raO6WBSwixOe6iA141emAa7eYbHTAhNgwdsJUNqkUVc9l29UekXZnRARNiw9ABn8HGxicWl5ZVkcJGRkZP/mbYccUesbevH+1RRQobHRtXVUYrJ+1mGh0wITbMnXbAcE6zs3PCRS2vrC4sLiGARCSbdbTjE5Mrq2sIrKysLmEHY3hre2d2br6woPDw6Bhx8MQiM8qZm18QGeYXFsVBcayZ2bk1iysApKFAUStUQ9RE7C5qqLKh4ZF1YwB1QwZkRFgcNCU5ZXdvXxx0e2d3a2c3NTVNNAHZtJpJuzlGB0yIDXN3HTA8k6+PLxzwr3/16/3Do4iIl42NTdMzs/BP9nb2cKhDQ8PKqRCWlZkFbwd/lp9fkJOdExEecXz82s3VbWp65oNfv394/LqzqzsyMgrOb//gMDAgcHh4JMA/oKmp2RD/MhLuuaKiEl756eMnyKwqXBhqFRQYNDE59ezJU/jpzMys/IJCVBje9MXzFxWVVfDNyvxoSnR0DFYDOGh4aFhDQ2NQUPDR8WtHO/vx8Yl7H3yIpF+/9yvUEPWZn1/w8fJGHuwI1+vs6FRcXIJKKguk3SijAybEhrm7Dnhnd6/e6IrgUOG90tIz7J6/gPc9ODpOTEiEXhQaFEkwMRvCV/UPDCLQ1z8AFZmfl48C29rakaGoqBgKGHvFRMdgE45W7LKzt+/u6ubq7OLk6DQ6Ng536OnhGRYahqMjFZsim2xYAQjHv4lDb23HxsQ62Dtg8/j1m+ysbLkmCIjqweBQIXyxWV1VjQpA9R6/eQMhbginpBqa3NqGw716lfn6zRt8IozMB4dH6WnpIizKod1AowMmxIa5uw4YIjUkOARC0NfXr7Ozq7qmFk5r2HgrF2oV8hEBGGRucnIK8mOnhsamuvoGOOn6+gZI0rTUtL2DQzhXFPLLX7wLZzY+MRkcGDQ9PbO7uwcpDLUaFhIKBdzX1w/vC+fq5emF3b09veD/IIX/+nvfl32qMChguHAUDh1cUlLa29vX3tEJP40aJyUmQRkjD3aBhq6pqUUYpRUUFIrbwNnZOahkVGQU1hAuzi7wyr945+fHx8f3PrwHpZuamobVAFTywsIiqoT88bFxExOT8qFpN9DogAmxYe70PWD8P2O8B4xtuCtx51XcDIZ3RBh5kBnZEECe+fkFGDaRAfHwi/hENhSCVISxF5JgyI9EFAhnCYNDFQViX0RiN4RLS8uQW9REaUidnZ3DXoYjLiziiMiMYyEzNuU8SEUA/4nCDU1YWMQmVgP4RBIOZMi0td3Y2ITKCE+P/VA4AnIzEabdWKMDJsSGudMO+HpNuMnLNohyCHfhrWm3zuiACbFh6IBt3yCCVTG022J0wITYMHTANNrNNTpgQmyYu+iAxb1bGu3mG4arNHAJITbHnXPAXV09tXUNNNqtsJraemngEkJsjjvngAkhhJCbAB0wIYQQcg3QARNCCCHXAB3w7eb169dSSANll97w7j21eqc29urRU6Xj42MpRAghCu66Aw4KCJBCFyAnO1sEnBwcd3d2EAjw9RsaGhKRFrB/8QKfw0PDYvMcJCYkSiEFCwsLItDR3p6bk5OUkIBwUmJiVmbmQH8/wv5+fsb0yyI4MEgEHt5/sL62jkCQf0Cgn78Fd9Xd1Z2SlNTd1SVtm3CwfxAWGpqUlCRtm4DCnZ2c/Hx9jeE3ds+ei3gLbG5uvgyPQADXgIg5KwX5BeKMK1lfNzRZ4OXhER0VhRhUD4PNz8dQPbjkwcFBkaG0pJTrTkLuJnfdAZcWF+NzdmbGzcVlcXER4diYmLXV1djoGITT09K6Ojsb6gxPooYGB+fn5SGQk5OD+bSutm7QOGu3t7Vtb20hAFqam0Xg4OCgo8PSF0i2trZwxKrKSoQ/+fjjhIQEuEZEJhqdZUJ8fOarV0gNCw7BxH14eOjh5g5viqTNjQ0YQDg7K0t4rInxidrqGn+j7+ns7IIfSklORhjs7+8Ln7S9vY1P+GB8NtY3WJZuq6urHm5uY2NjCBcWFMzNzYaHhiEcER4+PTUtfoUCfiU1JQWBivLykZGRvr6+ttZWbI6NjsnjKfnEX1ZWVuKIo6OjYtMUUfm0VMOvR5gFHYJPrCfEpik4KRg/fb29qDw2GxsaRLwWpSUlWJSkJCXjvH/84b242FgROT4+3tnRgY5Fwz09PLo6DT2MTXQIOhNnFp2PU4D+PDw4iIiIODYO2rzcXHRIR7vhpHt7eqFn+vsMax2AnGUlpUIHjwwPi563M669BJkZhqYRQu4ad9oB7+7ujhldws729vDQkPABcIQtLS3HR4bpsqS4eGdnR9RqYny8oKAAgbW1taXFxfp66fshds+/VFpNjY0igJItO2DhuhLiDe42IyNDdodJRkVbUVbe0NAgXCbqgIrtbO/AKywtLc2CmdmZ6WmxC0ShYbc3b1pbWqA1Z2ZmEG5uapILhFvy9fIR4cT4eNEWOFHhLLWAqoMf9XT3QBhFyX4UlcEhsCBAeHp6ujC/AJXcWF+fm52trqoW8UofKdYTAO4QHghNEJumQB/jMyszS2yaIpYO6GG5aSrQUnhHrKWmJiexWV9XJ+LN0tfbJ1RpRFg4NtEzolg444X5+eKiInTU/Y9/gxgsL1BzLMLQ0pjoaHziEDgFS4tLSMXFg/GAgFhLhYcZlinizwwyRYWFYpihnPCT8/XwwaciANxcXKUQIeQucacdMOZc8ZfAl+ERmLu9vbwQ7unuMSYaaD3xUtEvI6F+MJOKzbDQsPi4eBEODAiQXYJZB+xubnp9lZGBT+GGXxkFkGh7f19f5qvMo8NDFDU5OYlyoKr9ff2wDoDwwgy+KdjYRGYgO2DIcXiC6akphOGA8YnM4rxmGo8FiYY2iqNgtSG8FIDLhysSYRkIaGSWHYPcJ+Vl5SIAOY7Cy8vKUDFsxkZHQ7WLJGhxEQCyA8bR0YHLy8sIx0RFmx7Ry9MTn+lpaficm52Tu1omI93QisiIl2LTtFdR5tbWFtYB4nQoHbCrs7MUOqG3uwdrGgTEn6AT4uLwKTonOTExIy0dgV/+/BfoBNQcPVlfW4tzgR7GIkOcAdHwocFB0ZbGBsOpj4ww/kHb6IDFckR8Qr6j8KCTv8yDD9//QAoZ/mIfKIUIIXcJ3gM2zH3l5eX+Pj5wIUdHx0EBAaEhIZMTE5h8EYZ/Fc7P2dGxrq6uu6sb+dvb2uSqYtKHKBXh2hrJ9yC/cMBwBv/j2/9NRCpZXV11cXSCbMVkDXfr5uxSeOJykhMNchOHWF1ZaTb+TRvHgn+KevlS9vSCiPDwQH//kqKinp4euMyJiYmCfMMfh9NSUr3cPeA25ubmHO3thfzy8faG/KquqkI4y/jnXMG/+/o3pJACuH8Pd/fsrCwcEceFh+jq7EI1/P380DnwQxgxjg4OdTW1wt1CUMK/in2R2niyEImNjhF1bqivDwsJEZH//b/+uQgogeZ2cnBEnyP8+PMvDk5K+5LXr7FCmhifQLCmpgYiVUQrSUpIkOOFJAXd3d2VFRUirARO8WV4eFyM4V5DTXUNTgGkPMLNjU2iLSFBwdhR/LUfheB89b8tbUdHR4ODgtA5aKOfjw+WF1GRkRgtaAVGi/hLAFZafj6+6LqRkZHQ4GB/X1/RIWnGtRfY39tD54gwIeROcdcd8Pz8vBTSTUlR8S/e+bm0YWRmeloE6mprhQuprqwSCglSac14S1IPyIwFQX6u4U5zgJ9/njFwGcjyF85Az8NilkGr773/AQSitI3yjUIcYEUi+kEGR1T+jcEsEJ1SSANxO9wCOEpNdbUIW/5btAosUD6+99Ge0QH//Kc/mzX+Sd/qYJzv70krDPHkASHkDnLXHTAhhBByLdABE0IIIdcAHTAhhBByDdABE0IIIdcAHTAhhBByDdABE0IIIdcAHTAhhBByDdABE0IIIVfN/v5+enr6DXLAx/zhNkIIIXeAycnJjIyMwcHBG+SAxYv6CCGEEBsmMTExOzt7dHRUfo/vubGOA4b33Tr5aT9CCCHEVnn58mVJScns7Kz4yZaLYB0HDLAWEK9TJoQQQmyS+Ph4KOCWlpb19fWL33u1mgNGVVZWVvg0FiGEEJukvLw8KiqquLh4fHz84n9/BlZzwAAVmp6eXloy/OA5IYQQYjMkJyfD++bm5vb29m5ublrl0WNrOuDXr1/v7u5OTk7W1ta2tbXxrjAhhJBbzczMDFzvy5cvExMTi4qK4H3X1tas9bdeazpggEUBfPD8/Lzh19QrK7FYyMjISE1NTSGEEEJuG2lpaVlZWcXFxc3NzePj4xsbG1a802plBwyggw8PDyF/FxYWUN3BwcG+vj6sGgghhJBbBJxXf3//yMgIdDCE7/7+vlX+8ixjfQcsgBvGMuHg4GBvbw+amBBCCLl1wIXB70JVWtf1Ci7LARNCCCHEAnTAhBBCyDVAB0wIIYRcA3TAhBBCyDVAB0wIIYRcA3TAhBBCyDVAB0wIIYRcA3TAhBBCyDVAB0wIIYRcA3TAhBBCyDVAB0wIIYRcA3TAhBBCyDVAB0wIITeI1G7H1G4HEzONNBtjdl+Y1u5yvDJgmhmmjFRlUO+b1uOQMeDUMVsiNckcB0tFrydfbA48u0TrN4k5t1kuSs+B5DxWrNVV2mVU20KZxqSdoWe7w88OVhukQaMgdXT8fkv7Jw1Nn9TDGs2YIUl7UzI50lyq+V2EWUhSmsimM7PRLFW76ZMGOWy2eshgNIRFoKHZYI3N9xtbPoE1td5vbkW/3W9tv9/Scb+1wxBGTGPzFy2tL9o7ndq73Du6/Ht6o4dGMscnS2bmGuYX+1bXlnZ3dw+PDi7h90huCFtN/duhRYuB2QsBWQYLVJgco/p8K5BtCMumjBHZJEP5xkPISSKs+pRNmcdgKPPtA8FOsq0H560nVx4fWO3HUu8Ima3z9jnjL14N0Gzb7LKGnbKHFjb2X79+LU49BTAhhNwgTpOasqniTQPKPKZhZYyWqQpRmipeuemY1uOYMeB4mgAuNiOAraiyLlLUufe1Yv0t21kPdGUV0286qnSKAG7teEsEKsOSyTEImKZqmJlyzhJpsLMc7vx24UOo6q9U11JME8QzlPP95jaDVIa1ddxv74JmftTU4tXdEzU4XDg5Pba5uba/f3yyrLyNGARw2IkAVgpLpeYUWlSYnEH+lOOFSZvGfQ1h05LlPPKmnBmbivxSqvx5kk3+NAY2QiiAzwMF8F2xrGFHCmBCCLmxKGSnWZGpipRNjlcGlJm14pWmlSQiValiUxVpMKMAPtcd4DPpNMuZkXpDVN9VVsNax7pIOdZr7/YpAljcATaRbSpDHnU2lfA7n5I0t5eZY8lmWoe3Y8zuqIw0zSDHaB3Uwu46kwybirDS6oyfDYbby/ebWgz3k9s6P21qceroih8ZbV5cWtrdk9eaN5wvBbB55amUpieRsl6VdlHoUinD26ZMNYSNeylj5ENLn8oMxsJFkiFGkXQS2OAd4HNBAXxXjAKYEEJuMioxeWKyzlSrzRPTihdmmmo5v5bJe4kAPoUpky4ggGkW7Iboect2pkpqZT6JN94Bfn7aI9AnegxhlXITkaoYYVrxb4nStwuXw/pNudfFSziH6WrmiakyY9P87op4Q8BsHiQ1Gx6ubu/EaXJo70wcGRvd2Dy6qQ9Rm7kDLLSlIeZttSknyZFyjByWN9/KoxS0qvwmx1XlVIaVMYokCuDzQQF8V4wCmBBCbjKyjDwxWWGqIs2GZTObQZVTK14ZowqY5jRjJ49AF0tNMod4BHpLKXv0mFX0lXXN6kdRFYjNq2mIVeysVbWQv/+0O8AGAdx8Ire0ZJhJjLC3JJy5JGW82cymO0pmLrPYFKaKVG4KM5tHijQJf7mpMNMY2cwmIdLCLmZNyq9vrzpj/saW+22dnzS3unV2V8zOre7vS+fyBqC4A/y2zlRuilRZc4qA2bBpTsPn24UrTY6R86hMLkqElfU8SeIj0OeDAviuGAUwIYTcZMyJT1MzlaPKvSzsCFNlUGW2sKlKkk3Ef5l6DXeAL1si6lehcrbLrpK17JLqqadYy3n6db4EyyixLAQsizRDNmMGOWAwxS5flmPRNLMpizUacr6V+e1NPYdTvwpL2Nv7ImzIpopRmBypTBVhKV5sygE5/iSsMinpJMOXORUBObKhyfCN4tYO587u6tm5vaNrlm1vvQRLfMoBpdRUKVsRliMNnwgr8ghTZvgyp0mMHJYynBxdSjUW8tannNmwyTvA54MC+K4YBTAhhNxkZBl5Ylqy09SQU5n51B3lDBb2UuYRYflTufmW6bsDXHR8JgFsFZ2GQi5J76nsao5yQdNTyWttyGkvwdL3HWCDGbOpFJpZ0yrQdF+9h9ZjpxVl9lgiUvlpMNWmPlPlP9PucmY9e5nmqWs0vKS6rfNhU2v62Pja3p50gq+WLwWwEJZCW0phEyEqbYqAcZe3MigMMcpIOf+XB3p7d5FB3pQzyJFyvPx5Ek8BfD5OBPCgWi/RbMwogAkh5CZjTlvKMcpIOSxSlfGmptpLbFreRZicR1WCHFYZkuS3QFsSwPvGO8BnfgTaumZZ3cmpqmxm99IqyjQeMVqZYRaSlCayyZ/KvbRK0Mqjld/UkPN8O8qmZxdFnjM/Ao1PtcRCjCIsAoY8yrCcQcuMeSzkNJsk3YA1VkCZQf8RDfuatshcCSLGbLwcaSbPSYxc1S+TTkyU8NZeClPGW8imNAt5Gprvt3Z81txWODW9f7X3hN++AywLS+UmhKisWk9MpBqyKQTqW/Enm6pUOYMyUmwaUpWi9+RTymM0OSBtGvLwZ5DOB+8A3xGzowAmhJCbjEpMvr0ph+UYVQbTPMJEvCqzHDDdSxkpAqpsZiMlO/Mj0OeQUrJdZN9z2BUf7jaa9bpIhwA2UVN6NJhZ07WjnMdCZtMkZQzCb2ewfFxLclFHkiHwdjadBWplQ/xbSabZtMt/y7TLx2dj8/32Ls+evvGNTel8XzLqO8AGFWoUliJsiJQlrhw4ySbvJZLkVJHBNGw5g/ypTJLjTe0k/0Zw/npyFQXwWeEd4LtiFMCEEHKTMWpIldQ0IzJPTJVTfFrObzZVxIskOYMyp5wkTBmpNp2PQOv9DjAElUpTnVtimRZ1PjtTOSKnMr9V6iCbhdKQpOdYOuujszT9Zlra2zFnEMBfqjKFQhOBL5PMmpxZfL4t8E7Z16yZ7G6mEMTIkSdhrczyDWTDp0mq0qR9FXkQI0yO0bS395LDssmRllOVm8pI0b1fmklp8l1oRc77re2ftbRXz85JZ/3SeOslWAbxKQdOTFKbJ+rX8Inw24JZhE035Ug5oAp/WQ4CykPA3j7EW0knZtzkHeDzwTvAd8UogAkh5CZjIi9NRSZiVJGmeVRmIb+yNNNylKlyjHJTti/jL+slWBdXXyoJp1XgxQ+kMqsXeBmmv5JX1Zyz3AFWaC2lSRmMn0o9JptamBnNNKfZfU83pfg8tQRkOMmDvbSOaLZucqTWXuYNmd8SnArTV47+Sgo7a7zRDD+n1NJeNDUtr1ytjvoRaKEqhSl1prR5Io/lTzlVmNl4OSzHfxkjClTIYKGE5U3DpwichKWkLwMUwOeDd4DvilEAE0IIIYQQQgixOv2zmwElY2oJer1GAUwIIYQQQggh5PJon1hXC9FrMr4EixBCCCGEEELIpZPUMKOSo1dvEMBOFMCEEEIIIYQQQi6buLoplSK9YuMdYEIIIYQQQgghV8HS5r5KkV61UQATQgghhBBCCLka1Ir0io0CmBBCCCGEEELI1aBWpFdrfASaEEIIIYQQQsgVoVKkV20UwIQQQgghhBBCrga1Ir1a41ugCSGEEEIIIYRcESpFesVGAUwIIYQQQggh5IpQKdIrNgpgQgghhBBCCCFXhEqRXrXxO8CEEEIIIYQQQq4GtSK9YqMAJoQQQgghhBByNdhlDsHss4xmDEsxirBZExmwl3JTCp8UpSxTVaC0mTXskje8uEkBTAghhBBCCCHkjkEBTAghhBBCCCHkUjg8PJTvvt4EKIAJIYQQQgghhFwK6+vre3t7R0dHN0QGUwATQgghhBBCCLkUBgcHFxcXt7e3b8itYApgQgghhBBCCCGXQmVlZW9v7/z8/A3RwBTAhBBCCCGEEEIuhVevXlVXVw8MDCwuLu7u7l77s9A2IoD/2X93/9MPq6xuKFY6ACGEEEIIIYSQMxIfH5+fn9/S0jIxMbGxsXFwcEABbAWuSwCHh4f/HQWPHj2SEjT44Q9/iGzf+MY3pG1CCCGEEEIIsV2io6NfvXpVW1s7PDy8srKyv79/fHwspV0HFMCW7KwCGPzzf/7Pd3d3pWQTKIAJIYQQQgghd4eoqKj09PSqqqqBgYHl5eW9vT0KYCtwcwQw+K3f+q3W1lYpx9tQABNCCCGEEELuDpGRkWlpaZWVlRTA1uRGCWCB2cehTQVwaWkpIhEj+Pt//+8jw+joqJT85o27u/u3vvUtkfqHf/iHqt1RAZEExL7y7rOzs++8846I/Mf/+B8j3NvbK/YCkOj3798XBUKx4xCoiZRmBMMUTZCK/sY3vvKVryAn4nd3d/39/b/97W9jL+yOQpS1FXupQKSU/DaoPFLj4uKkbUIIIYQQQohtQQF8KdxAAQxMH4c2FcBQgCKzEqWkhHaVYk84dXezkQLsC/kqbZgAQSuVe1JVFdDJv/u7vyvEsBJUEnobe6G9yCDFKqitrRXFykDYIx763MIT44QQQgghhJBbDQXwpXDtAhjyz6zwUz0OfTUCGMJbpP7FX/yFFKVATr1//74UpUA+tFkBbG9vL1JNj4vmiyS0V4pSgFaIVIGcR3lTmhBCCCGEEGJjUABfCtcugMWmWcEJIBdFhqsRwPLDzOdItSyAV1dXRapZlSvLY7M3md955x2Ruru7+1u/9VuI4cPPhBBCCCGE2Db2nkFeobFRafk5Va013eOtI4udE2vd0xsq6zGJecumvgx0Tm6MLW0fH5/zt5QogC3ZWQUwgKgTMSrE49BXI4Dl3S+SalYAiySAbFKUgm9/+9tSssbfAoT2Fl88vn//vshJCCGEEEIIsVW+86HLX30W8FOnhA+Dij+La36S1vsic/BF1vCLrCF82hkCUvjElGE5g2xD9nmT/iXjG9sH0gHOCAWwJTuHAAazs7Py+6iU/NZv/RZkMAK2KoC/9a1vSclGTGuObnnnnXcQUEplQgghhBBCiK3ynQ+c/upTv586xH0YUPBZTOOTlK7nGX0vXg2c2+xyxgNLxzd3DqUDnJEbJIBfv359dHQkbZyRGyWABVCDIskU/Qp2d3dXilJwjQLY8iPQKFCkCmZnZ6WEt5G/LUwIIYQQQgixbSiANbExAQzkVBVKBWv267Lye7PE/VIV1yiA3d2lDrG3t5eiTvit3/ot8SJoJWlpaVLyCWazEUIIIYQQQmySyxHAExTAN1EAA+hJ8cInJUoFu7q6appB5v33379Rj0ADHB1IGwpUPyMsgyZIOYzk5uZKCYQQQgghhBBbh3eANbmNAhhyTghCaVsDiEmRTQBNKCWcAPX4rW99S2hdfCK//MO5f/EXfyHtdoJydyhwKVaBfIv1IqlmBTDiUVVkE6IdVUX1tKSvjHjrFZBvIBNCCCGEEHJH+Cjn9+/l/L74fFj5f0d22b2ZSz1u+b2F0v/zVEO2N/OJP6ho/+2UjN+OjJXtH57Yb8cn/2VJuXtn9/D6hnS8N2+WXhYs/U+Hwf/6BWz+f9jNPIuWEt5mc/foj59XffXz6t/7tNSC/fPnrQElY9I+Z4d3gDW5iAAmVkdLAJ8D8XVoSGVpmxBCCCGEkDsDdK8waODPIIA7zyOAfycl40vRGxX3D6Pj/yE+FWL4t+OSfic5PWF4BEdcjChYVgjgab0CuOT3Hpb/0y9qVPb7jj2+RdJToufgUgRw2Z2/A0yszrkF8P3795FTvBF6dnZWvPiar30mhBBCCCF3E+kOcO7JHeD2h292J16vZO3NZQpbbfmrnbp/IhTvTv0/WWv9gZyEbG92x/+qtAYCWGjd30lK/3F5VfHUdN7kVPLI6Pu1Db+dkCLJ4Kg4yOCZ44O92LIvBfB3ThXAVUIA/7OnTe9GdhwevVbZwdHrc//oLuAj0JpQAN8o7O3txUPRSqS003jnnXd+93d/1yiZ/84f/uEf9vb2SgmEEEIIIYTcMSCAhUEAf1b5f79s+UhKOGGj55OjZumG8FHL7230fSYlnPDdkrLfPrkD/Dvp2Q7tnVLCmzdre3v/JDn9d+KSDI9GR8fDZo8PdmNKhQAe0PUItCSAv/p59X90qn2eMfA4rf9LyxgeWdiWdjgXFMCaUAATQgghhBBCbAwhfYWdTwD/ZUmZfAcYBpX7D2MTfzs++XdSM38nKe23X8ZIN4eT0/9tVu7e69erLwvP9Qh06e89LPvqZxUKq/xnTxtrB1ekHc4FvwOsCQUwIYQQQgghxMaQ7wDDrCCAIXdjDV/3lSzJ8Pn/ysj+P1MywvsGRH7DS7C+8+UdYJ0C+J8+rv9BUGvn1Ebb+LpsLePrm7vnlJqCSxDAY7wDTAghhBBCCCE3ESF971lJAP9OerZ9W4eUoAEEsPwI9NR/ezb+vv9GWbvSNsvat8o71pe3/ti+RhbA/+xJw49DWkcWt4fmt4yGgBzekoo+O7wDrAkFMCGEEEIIIcTGkNWvEMAR5/oOsHgLNDTw76RlPW1pkxI0kAWwMMhg8SkCsOE/fzT23x4tD8z8G5cG+TvABntY9tXPK82aVPTZ4R1gTSiACSGEEEIIITaG+PavkMGWBHCJVQWw8RFoWf0O/rkkfUWMQQB/WxbAp/wOsDCp6LNjbQHcb2sC+D8/ekOj3XwrJYQQQgghhJzGpTwCXWZDj0CrZAaNdjNNuqAJIYQQQggh2vA7wJrwEWhCCCGEEEIIsSUuRwDzO8CEEEIIIYQQQm4YfAmWJhTAhBBCCCGEEGJL8A6wJhTAhBBCCCGEEGJLXMod4DIKYEIIIYQQQgghNwzeAdaEApgQQgghhBBCbAkKYE0ogAkhhBBCCCHEljAI4Ae+Xwrg5BMBnKFWtpJl9Cs2+w3ZDDnlyH6+BIsQQgghhBBCyE3krz5x+9vHgb9yT3oYUWqX2uqS0+9eMOxROKo0zxN7O35ETlLGuxeOx9XNbO+dUzlSABNCCCGEEEIIuRQiIyPT0tIqKysHBgaWl5f39vaOj4+ltOuAApgQQgghhBBCyKVAAawJBTAhhBBCCCGE2BIUwJpQABNCCCGEEEKILUEBrAkFMCGEEEIIIYTYEhTAmtiGAN4/el0yuvGyfSmkdele4RTse+mjfxo9QKPRaHfQ3subwDT4omoWs2LVxCZmSGmuJIQQQsjdgAJYk1sqgDf3j6F1/1PcoGrZR6PRaDQtgzDuWdyVplFCCCGE2C4UwJrcLgE8t3Xwo1djqiUdjUaj0c5kUMLL5/0he0IIIYTcfCiANbktAjh/eJ33e2k0Gs2K9r30UcpgQgghxCahANbk5gvgoZW9U6Xvg5JpKGStlRzikYo8qr1oNBqN5te0KM2VhBBCCLEVKIA1ueEC+FH5jGqtJhtUcebAmpTvLLTN7Xw7cUhVGo1Go91Zc66dk+ZHQgghhNgEFMCa3GQB/LPscdUqTRjk69zWgZRJgbjTC80sXgQNQxgi2Wzm/aPX7+VNqEo+q/08Z7x+egtWO7V1r3BSlQpDhr1Dw/tXj16//qz09FvQ34odrJrYnN44gDXObKtSLRhaKtqlOhAKdK+bF4bKYPNF1azYNFthnXbWdsmGHYdX9tC6ifV95Y5ygSCgeRH17F2SXtWTO7QuZ1OZXBoMe6lSYcrmW/irx0+yxsvHN8WpNNuckrENUZnZzYOL/PXk3P1Go122xXUti0FOCCGEEBuAAliTGyuAIV9V6zNhpqu0oZW9/5Uyospm1l62L0n7nAAZdqavFit1mmWEbDur4Pmz+KG1Pel06NFasu41S+fCjkpYKstXCUtZ42nRu7gri1KZcwhgsx2iqqdOAaxsvtlseg5nAXkvCwLYcr/tH73+y7QvB6dWffQY+kQ+llm1T6Nd0Db3r9MvEkIIIcSKUABrcjMFcP6wec2T0rsi5TAC+XqO23Ee9fPS/kaWdw516melfVgwObyyJxVxwsL2oU/jgjLbWQWPSqLr0TnQRVUTm9IOJ6Am4nAqYWlBAJs1pRCFnJbjzy3klJJV2TpVPfUIYGUeoJSmpn8XuDwBbNbkClxcAJv+1QZQANMuwzDxSiOMEEIIIbccCmBNbqYANntXVqVqTEXyj16Nmf7E5eb+sXPtnGlOKBMpxxvDt4JVGSyYshqts9viQWKIsbC2JVlTyZrtTILnHFJHpRsRo5K4FpSeSlhewR1gC5JVfz1lM62wLNFPFcDC5INiMIjz+JOscdF7qvzXKICFoeuSer786w8FMO0yzOwURAghhJDbCAWwJjdQAA+t7KmWZcKU4nZ551CV2jC9JaWZAzpE9Y1i1X1gne+INhWcSlOKT5GqU/C41M7JxQrJpDyQhX1loaXMo1RrvymaUlZYzyPQejTeOYScUv3Wn5ws+ViqjlVmNhXAaLWcWaQqF+6hrUtyTgv1lLvOtL1yV8in+NoFMMx0dNFo1jUKYEIIIcRmCAgOj45Lzi0sbWrvGZmcm1veXN7YW906uC6jALaE1vPPUrKRzIE1ZZKsNyyg0tX/K2VESjCClZ8yVcuUOs1UmKlUnDLGVPBA48V3r8j5QevstkpcIY/y8WYUgoYr8yhFEVJxUOUtVmyqqmRBAONYhSOSzNOPHiGHkk0FpFLiIlIl1JWpcj2V5eC4SqErTPl3BHEgrf5Xli/OlNLkvWT5Kh9XcGqrZSFBAUy7RUYBTAghhNgM//Oe2/c+C/ypU9K94NLP49uepg+8yBqxyx6VLGfsy7AZU6Vic8y4iwgok0SqhRhpLwpgS0DyqZZlwpQvaFGJ5J9lj0sJ2qiK/V76qJRgxK9Jr6JQim3IGKhW97r5jP5VWXoBWbNZEDyinIn1/fvFb73uC9rs1/kTMJUYlr91bFawja7tGw5sBMdK61uVk5TvSYaIkjflPFdjP3o1pmqRMNRQfCrriU6Q34Z9kXpq9b8cDywIYDn1THeAzap3YVr10WMUwLTLNgpgQgghxGb4zgdOf/Wp308d4j4MKPgspvFJSpFjiEkAAJe4SURBVNfzjL4XrwauyyiALTG3daBalglT3gvdP3qt+p5wSKulpdvyzqFKt6jeJq31k0taBpET372i/IElIYZVvy10DsEjay3lS6d02k+yxtFLsngzBXpb9ZoupSmFn07OIeRgEMOqu98qTP8uYNYcqmdNX0WmBGfEbDkW7oTD5L9xyK07kwC2kJkCmHaTjQKYEEIIsRkogDW5mS/BgkBSrcxgqnu2pl8VhtgwfYsppJTp7/2qHplWPVBtRbsaAay85QhwrNqpLfe6eWg/cTP5RdVsdOey6i6xaX2uQADLrQPYV9w/F5UU9YQwVtZT9QixMKUUBAvbh4k9K3JjYR8WTKr+PGGqReWaqJqgLFzeS6cAlt+hBcyePgpg2k02CmBCCCHEZqAA1uRmCuCexV3VykyYSrhu7h9DFavynGqQu9L+RrSeuDZr514g6hc85xDAcq3MykWVWdByly2ATe+sWjAL/aBTjsIs3OlV/dVgYn0/tXdVqb2VhVs+ongcQO46C7WiAKbdZCsZlcY5IYQQQm47FMCa3EwBDEJMXnEk7GfZ45B5UiYjc1sHeh5g/k9xg6bLO0hHVTbLZi0BfA6pKWOqnUzvAHfM70AjiZurL6pmxbeUVQ9smwqw89XK9BFiCyYrSYGop3PtnLhta/ptarOS3vIdb7TXq2FB9Si4lig122TTztESwMqaLGwfqh6ANzUKYNqNNcyQqqmVEEIIIbcXCmBNbqwABnFdy6olmmyqu7gybXM70KiQQPcKp/CJMISQ2VVdz+Ku2V8btq79JGu8fHyzfnoLCu1UdXRxE9+tVQpdJRBdWt+JlQ0VVt4F1cOZBLAwccvUcj31dJfl7zwv7xxinEBzqvY6hxWObIg3cqFiWnd39dgVjwcaTb9pTaqEEEIIuY1QAGtykwUw0PpJJGEPSqYhcqSs+tjcP9b/wmcajUa7C4ZZUZoiCSGEEGITUABrcsMFMNg/em36FiuVfTtxyLl2rkrxmmgliEfqRW7c0Wg0mq0a7/0SQgghtgcFsCY3XwALdH7Rl0aj0Wg6zfSVCoQQQgixDSiANbktAliGDzDTaDTaBe1R+czm/rE0qxJCCCHE5qAA1uTWCWCZtrmdUx+NptFoNJpsHvXzZ31vAiGEEEJuIxTAmtxeAawCqzpI4vzh9ZftS1jk3SucotFotLtpj8pnMBOK1+BrvW6dEEIIITYMBbAmNiOACSGEEEIIIYQACmBNKIAJIYQQQgghxJagANaEApgQQgghhBBCbAkKYE0ogAkhhBBCCCHElqAA1oQCmBBCCCGEEEJsCQpgTSiACSGEEEIIIcSWoADWhAL4bjIyMvIP/sE/+P3f//3t7W0p6m0ODw//y3/5L3/37/7d+vp6KeqqCA0N/Tt/5+88evRI2tbmww8/RM64uDhp+2Kc2idXhp6aWL22lZWV6Mxvf/vb0rZFTj1H+k8iuWtY97K9xpmKXBm7u7v/6B/9o7/39/7ewsKCFHUb4DRoRc7koQghAgpgTSiA7ya3VACrkiyspEX9kaqFqR/VKSknJia+8Y1vSKVo89WvfrWrq0va54xcXACLtYJlVP12LQJYrGutKOOJKXoGgxL90lTPmDGVLnoEMK7fvLy8f/kv/6WxRga+/vWvt7W1SckKKICvDCsOJDEGLKM8p9crgC17Ewtj++oFsDiifq6ybkouyUPdOodyGZPzFSxRyC2CAlgTCuC7gJ7VhozwiOdeVp7V5QuPJQ5tAbHIUBWuZyVtiuxHzS5rLPtOUYFT/atcsp5+0O8ClSuti9wBNttvWssLnSdIIA8YncPg1q1XrgCrL4m0zuzF0VOyqXSxfNnK4w3rM1nx4oKCHsaANz3cuWcqm+cWDSQVpufUdBTp4UyOD5zVlZw6ti1Mg2a9jx6sNVue1VODy+5PmTN5KCWX7VBu/jV1GUsUcquhANaEApiY5XzLSqHKMKuebz1aXFz8zW9+E7sLvva1r0VGRkppRlQ+28JK+tTlhanL0SMpr8a7XPwOsGXOvbzQj87V1WWvV86HPIyvZXGg/0RYGP9KrL7GktFT8qkiQYnoeQs6RxxROWDON1PdBW7RQFJhek7PJ4B1Ik/Xp/aAiosIYCWmo1qJzrMjEEfUz2VMcefuTxmzTdY/21yeQ7n519TVLFHILYICWBMK4LsDprwHDx5gyjOLah40XYJYRp5PMfOur6/LYZ1+SMzaOBwUr7wL9LB4kkd2D2a9u1kfo6f+cp2VnFrnW/EItGXOvbwAqj9SfP3rX09LS5PSFOhc+Yn1iihKD+dr7+3iktZY+tG/GtNT1TMJ4FMLNC3trDPV3eEWDSQV4pwqz7LpebcisiM4tQdUnDq2dU6DFibzsw5vnUe8VM7dnzLn9lCX7VBuxTXFR6CJEgpgTSiALxU4NjETCWknxV4HwsVq+VExCyudgU6/i2z+/v4oWbU7QJLQ2yjEwcHBgpsRTkuP+1d5dws+RvbBFlDteBFJaV1EM1WdLxqrQqu2etzqmZYXcn+iVqo/Upg9+9e7DhNjT1QMfOUrX3n48KGUdsLMzIwqjzxKxYBU9r9ypYvlhfwnAOylvK5Fq82eFJGkZ/li9TXW5aGnqqeKBCXiGrSgc849UwksDwydZ1mA8YOpT/UtZdWCUlmg/Ai3XHk9oxR55AlW5NHvR27LQDI9uumYETGGLjhB5xnXw6lDSGSQDmyChbGtcxo0ba+MhSSziCPqR3/J+jm1P4EYnJZRDUj94/nyuC3XFCEyFMCaUABfHmIGVKIlV64AyxO3qcey4MOwNFSuRb7//e9b/jsiihJKWACPa5pfuG0cTiWuzN4B1iOAz4GWANbjqvWgs57Kw1lYQ1iW6+dYK1jexXJXi32VlTFdh13Z4BeHttB2eTmLPHKVxCgVDRSLTmXnK9ffaIg8gOVxK3LKJauWvJb//KRC/7mzcFJEIRfH8qDVU1VT6SLQKlnO/9WvflV+uAAde/HvAJ86MHSeZYATqvqChnJQSVEaBQ4ODuLz3KPU7AAzy20ZSKZHF/2mnDFEzGWoNXDqEJK73fLlAERbVJx6sixUwPI8L7iai10/p/Yn0D84Zc6xi9W5mdfUTRsA5EYBPwVPikEyMDCwvLy8t7d3fHwspV0HFMB3AlNfaNmNXTaiPnBLSpEp7oOJ6imnPz0+zCxiYadnfWaKFb8DLCOvXXRyE86RqIO8ejZbpasUwKcOBtPlqYVhcNneWhzawvNdopMtdI5ojrK9pjEy4nDyiTDVuvII1Lm8OGv/6F+1aJ0UCyfLMnqGmenY0HnZWv0t0KcODP1n2Szi1CtbemqBFiojMpj2relRtLgtA8l0PIg2KttuOoqsyKlDSP8lrGqLhQ4RbUTqWdEz1K8XPZeknqlDhdYuZx3nWugZ/7flmiJEhgJYEwrgSwVO7oY8Ai0jRKbser/yla+YvYWrf1mpwlrz9cTEhLOzs7KqAlQYS2EHB4fR0VEpq5UQKxLLa1zROv3o7Af0ttk/QwB5nYRzoXyS3HJtrbi8EIhUswtQsTZFqrKx1+u20Z/vvfceKiBQygx5LWuhbqa6xYKSMe0ZESOfGtEVZzoXplykPy9p0AI9w8xUuugRwPo500xlYWCAM51l+Y60CmUeCwUCPaNUC7NXoh5u4EDSMx5MR5EVObVw+XScOmj1C+BL4vIudv3oOVl6pg4V59jlarhR19RNGADkRkEBrAkFMDHLmZaVSi7o8oXvRAkQutB7g4ODKoGHivX29mp98diUU5eSKk4tUCf6+0GsmSxnRiugkH/84x9L21cugIGFnsTaXbXW0dl8PX90uCDyiJJXpaLDLbRU7KIc/KYxMmZLE5FovmjgxRfuF7ysdHLWo4gxYwEUZboaVomEC3Lumcp0YOg/y/L5FZsC03NtoUAVppUxO64uzg0cSHrGg+kosiKnzkJ6nIjYXdWWq+nt83F5ddMzq1+GhwJX4FBMuYHXlB5u8uAkVoQCWBMKYNtGXledCfgYrWXlqUtenWgtd840KevJfO71sVnEEfVzed7FsqfXf5rkEs6xIrGAzvNo9fUKTvd3vvMdzPhygeIQqIxK54jGytnEDT1RYVPdoryO5NriWGK9a7ouV113lhf34FIvq+sdtKIrThXA8mmSQf9/zSLIj0J0XuBnGhjA8lkWMcrxI5emRwDrqYxol6iJ8jY14v39/U1flyW44QNJbpSM1lmWkk+e+DUdRVpcag+cih4BfLsu9kuqrf5iz+ShxHVkRYcCbtf5ut7ZntxAKIA1oQAmZhErlVOXlVZHXoNa9w6wtRpidkFzLVjd0+tZXuhHZ0ddxnrF9PXOcABSmgLla34xPH784x/LdTDVLcoY+d1swPTFvzKypLFWl54bcS7Ot6C/OKbSxawAPjf6L/BTB8aZzrLp+FlaWlK11HQgyegcpWid8l3TKAqVwWpGSr5arnEgmY6im4keAXypXO/FfqlclwC+VKx+vq5+yJEbDgWwJhTAxCzXJYBlrPUdYNEQaWd9WHAewrvo5/I60JYEsLGrdHFdKxsLSkYL0Z83YSl2vYP25gjgUznHWb5TXONAogDWyVnP0c3vUhn9Alg0TQ/XPj9b/Zq63tme3EAogDWhACaEEMucVRqJdRjXFrcLCmBCCCG2BAWwJhTAhBBCCCGEEGJLUABrQgFMbJ5Tn0PT82zVWbHuI8pX9iid6hG+U59WRTPlr0oqMXsb7Ux9MjExce/eva8Z33UkFWoEMe+++67Zn4TVj4X+VCXpf173kiosKnBWdA5mPeNKXB1XMPauBgsPSZq28SIzw8WvWQslqCpm3RnMunOX4OZMLHrQ/1y9heGkRPWk8WX08KmI4aSfy7vkL35pmKLnEhCPeFxGt1vuW7lWqobrdC4WsqkG0qkF3pwxYN0pi1iAAlgTCmBiS+hcjgjkRYmeufisPtvyEkePH1Ie66xHV2FhPWfZJVt2qCLVbL/l5eUhySyW1x9ijYJsqK3pW9DQEMTIr0DT+QU2uUzLiNIsd4gpl1HhUxEnFAVecDGnZ1yJq0Pn2EPFgoODVV/dR8+IVzfpr6rodv3oXEhZGLGimaoTpH9mOCt6+tPC2VFVTE89BXrOuH55dosmlomJCbOKGihfgCew0K5TsVYP6ylHoD+nTs5a4KlXq+qysly+zukaKEvQcwlcngDWQrRUHueqhlu+CmQsZDurANbPmcaA7I8soOp2/VMWuSAUwJpQANs2mJiw+H733XevbMa/jeiZi8+6JtAjgPWXdtb8Ki5jnSoaaKHTRK8q66xn2affhV+SB7XcIaZcZYWxiH/vvfdQCMCqfX19/cGDB2Lz+9//vtb7qLWQVy2Wz4jpeTRFuQASWlf5jrqZmZni4mL5ncnWPWX6e1XktNBY06vsfKdMpbW++tWv6jk14linIrSEqmL666lnJtFznQpuy8QiDocyTTPgZAm5payMhXZZRuc1paeH9Zwpgc6cIpt+9Bz6VMy2VH/TBHqGt548VyyATdtu+aKQOfVMySNTdYhTndEljQHL14vZMaB/yiIXhAJYEwpg20Z4d0xMmZmZUtQtRMzaZ5orxc+6GudwNegNlYcQc7GM2Xn8rD7b8hLnrKWdNb+Ka1ynKjNY7hPB5d1Qxb6yXFRxjjWKzKVWWCymZSz8WA4GvPxjOQLL/QxE0376059azizOo4WxJ9fTQi/JiNJOrZt+TIeZFqce2vQqE7soMe0HcYqDg4Nl0YuRoDxNylMDMezj44P8Utp5UbVafyeINlrOqec6FYhTf8MnllM7R1zCymvTQrssI9olfsdYLlCeIlRY7mHRgfqxcIUKTIf3FWD2RJ+1JuIMWu4uPZfAVQpgUR/VhG/2nJ46bZ56scgtspBTcEljwPL1Yvby1HO+iFWgANaEApjcfMSsrX+uFG5Aa5Y3LU3PXHxWz2F5TXbW0i7ot2SJooVcssqDWnaoIhX9ZtrGcz+pKDNh1a/UWvDQquWv6GoVp65RgHUrfKmIwSn3hjw8zJ4acXVYGHum+sEClq8LwanD1RSdk4M8YqVtBaKZqlacOjOI5uAUP3v2TM9t3pmZGX9/f+RHsRYGFcaSfMMcmP4Qsapip9ZTICsx5YVwPnkmuBUTy6mdYzqALUwXWuAo4sIXjZJ71ez9fz1Xgf45X2dOszObBXRe0RbQqpj+pgnEeLB8OvRcAlpDXQs9l4ApOIr4W5hpZVQNt3wVyIhsZrtLNZBOLfCSxoDl68XsaBfnS4n+8UDOBAWwJhTAto2Y8U2XO5jX7OzsxLwjVmMA2aqrq8WCBmH5roVqHpdLwHUlXP5XvvIVEQCqWUx2BgDZ5GMB5U0S01oBcQjsIheOMDBdDqoQbkBZvhLhA5SN0uM7z+qzLS9xzlqaqd/S6ZkEFvyTqiai61RYcKhoptY360zbrtUnpr7wfFiop4UekMee6E+zHaIq+QoqfBmHQCd4eXmJeNOxJ7rINFXUxPJYFZ1mtnuVFBcXi2vZQsOBXBPL2c6HGIQo3BTTNuqZGayLOCJ60sHBQVwm6A35CQK5Q1QV01lPMZgxheLTwgRiee5SYuGyugkTi4w4utkMF3wEGrvL9dR/TenpYVUHWkB/zqvEQq1EkhILo1GMbbHGsNBjV3+pmiKviLTqafaisDzLyfOV3EWml5J8OD0FXgaWrxezo/0mnK87AoYlBbB5KIBtG7G4V05MIsZ06pF9ktJjyf5bGSmXoJrRTDOLOc50WpRzynWQyzTrCEXdzjRXnuMRaMvlW3DnZrG8xDlraWfNr8KCf1KVrPKg1nWoepZ9l8plPAJ9XZxjSOAq++Y3vwlfKG3rQ1wdpx4IY0zWaVpgBLq4uEg7aCPPDzew22VEt1wcZRstXCCiT+Tp0ezRLcxgcpeK86g1Mwv0X6e3aGJRKlUV3//+91U7WmiXCuT8zne+c9ZrSk+FRQfqx+wVehmj9FRE6yz0nv65S9RfdJQyLCUrEKmml8AV9IB8ptBkyyPB8kVhityTzs7OonxVl6oGktkCr6AH5OnFAqoTp3W+iNWhANaEAti20RLApjOpmI9MvYuYspXzlFYJQFmIasmlQuSU13MWygSmdbh69PtsgeUlzllLO2t+FZe9ThXZdKLVJwJRH/2cu0+sxXVV+IJDQoxPUSU9XGU/61lOmaK/hhYuBxUXWaWd4wRZmDREnVUCWK6Y5XqKVKC8kOVORpmqB2osz11KbtHEcib0jxAtiouLf/SjH6m+lv+Vr3zlu9/97lnVspKLXPVXMFPJs4rlfXW2Qpx95agW5Zs9Lxe5VG8mopfkxoo1EmKU41x1qZ56WV3BGNCJ7Z2vGwsFsCYUwLbNXRbAokz5EBbQMxfr9xyi+ZYXkTpLkysv8p/bG8nnQgu55POtU3Wif2Gth4v0yakdImN6d+jcXKTCFu5fKdH5wmGg/1yIq+PcY8+KXPAqkNEvb/TMDGKeMfS+biw0QRwRdbv4I9DYUX7kQetEyxeCsjf0j41TryO5pbdoYgH6R4gKcSIArkQsOpXvQgfidejyhXyO5lvrErDMWY+C2Um8nR49pvXNIyWnli8yaPluMXhwLOWfEvRcqlYfJ6bIA0A/psNANB+YVlUuX/SeqkVWvKzON9L0Xzh6zhexChTAmlAA2zamwlJLaor5yHTCFfOgcp6SF3yIVGaW4+VJU5Rp6sbkZZOcU6tWAlGHs/otuT46se5cbF1fez5vdA7Ot04V2XRiuU9k36+Tc/SJ/uEkD1QLPXBlFVZdbqagtuJE6DmE/vEpruIrGHunYq2rQD6tOrHizKCzCVAUVnkJFs7yOX4D7zJ0wrVPLGdC/zpeif5+O1/54CKXwCXNVGjLgwcP5L/X6MFyKzD4/+zP/uzUP+ThoMrxo3UJKLmMgX0RtK4CLF309ABQtejUy+qSxoDMuQc2uTwogDWhALZtTIWlltQU/sPUN4gZU+lX5BJ+9KMfGSfJL1+jBVSTr5igRdJXvvIV+ZEwVQW0aiUQqWJHHEsrmwqxl7XuAJ8V6/paCysGuXOscqyLrFNPzaYHy2sjqyAOoae7ZKV06pLiJlRYrq2eyugfn+LqMC1TxF8cuW+tXqAW+ldpVp8ZrDVaVBWzbj0vQydcy8Si9D76weHOt46Xp+JTz68YBqa+6VIvAXHQc3emFbmMOVPPJXAZA/siXNxvqlp0aoGXPQYogG8gFMCaUACTs2JZrN4clLJZD7dUAFuXi6xT9WOhIaKl+jnfOISfFs/sncqpj0BfTYUv6RFoaTcdXMHYuzLkvxTohAL44lz7xHImLrKOl191bgGUrHx892o460yl52/H5+My3Jl+AWxsnC4uWyrrvAoscD4BrJ+zjoGzTq3gIs0neqAA1oQCmJyV2yKAr5dbKoBVXNxDE0JkLulCvvkCWMUNn1h4I+tSuS4BfNOw+lVAf01MoQDWhAKYnBUKYEIIIYQQQm4yFMCaUACTm8+pfzC+jX/9JTcBDq1Tua6nD2Su5RzZxhMchBBC7jIUwJpQAJNzI24FX/b3ZMClroAvsjYV++qHK+CbBofWqZXU3wqd36w+6y9LWeUcnfVcWBbAes6O8lhnPTohhBBycSiANaEAvjuIZaJ+Tv0myWUIYLHulGpwGvIbGs6tUuTDXfYT3VwBXzscWmY5dXed5YuOOvWlKfKr6cxOL5d3js7aS6ImlgWw/tIueI4IIYSQc0ABrAkF8N3h3Et5LS77DvDMzMyDBw/kX04CX/nKVxwcHEZHR6UcJ5yjafJSW6xKcSCE9b9EVyDWtfrhCtgqqM7dOeDQkjlVm+kUb/o1ns6cOEf+/v6m58h0tqEAJoQQQkyhANaEAvjucEkCGGXqRL9UFlUFP/7xj5WaZHBwUMgJ1V01Ob+M2bVmb2+v/IimWUFSXFwsfmwG5X//+99va2uTEjTguvbiiD604rC0DIeWEvlXKyz0v86ayEXJDVRe7EgVXST+NGB5KtA6R3InWz5HqlTBWfuTApgQQshthwJYEwrgu4NYJl6Z0jg3p/4EhVibKhtyatOwANUpPGSgWMR63cKyVaxr9aP/V/XELUqhFoDq3he6SJX68OFDkQTEHybEsfLy8kS2M92oV5aA3pZ/gfbrX/+6LO3kktGxECqmhZvewVPuDsz2nnzeLbRCJMk55TuuqqdqRfnKhnNoqVBKR62vPIia6BRv8qn52te+Jk6KQMQgcGo9L+McgTO1AoijWFcAKznf+SKEEEL0QwGsCQXw3UHPMvGGIK/Lz3Sb7mqaJtftgmjpDSEAkAHNUSo3NFzsIhbTFhorRIjxIAb5JzQnuk6k6kFZglyNiYkJORLIq3+oU2yqzgj0AwQPZl5p++12SVFGtJpjoRUqASzHIKdcK/GLiKbF3uWhpULWeOvr6xY0p6l405KFQJwIs+rOQpIKrXNk+Q6w5XN0Vsl6GQJYf35CCCHk4lAAa0IBfHc46/La7OLvKtfoUFxY717wi5pXWWGroKXcZMRi2sJ3Sk314VnRKkF0punAOLXOAiEqVBJINMd0XwutMJskC+w/+7M/EwELeuNuDi0lqm6Xe8+00yyIt0vtAa3vaWtNSpaH31klKAUwIYSQ2w4FsCYUwOSOc5G1qdhXP6cexYIOUYJs4laYQCWGr14Ai35QKRD5uWUVlySAgdx74CaIjRs1tGTk82IqO8X5VXXsWVvR29t779498cCzEsS8++67+h8UF2dZ/x1jPQJYD2J4UwATQgi57VAAa0IBTM6N5TXixRErYOOiVBeWV8BaXM3aVP9RdN5NlZF7SdYzFqSjTrRK0C+ARStU7b3UO8ByP2C6FzLYQh/KmXViG0NLbrWF5hweHopzJ59lneXLhYv7tKaP3CNG/k64HlkrCrSWAD4regTwqchD9GpGAiGEEKKEAlgTCmDbRiwNL47ZZxSvRgBf9gr4ImtTnetgmbOqFLljxV077A598p3vfAczmpwkzgLy30ABrGyCXE/VCRVlmp5lC60wTRKFK2NUKk6FKOGuDa3zobMVosPNThQqdHapOEeGtunjfOdIC+tObhb6UH5s4cc//rEURQghhFgDCmBNKIDJuaEAFvvqWfSflYmJiW9+85soHEDXKV+zbPqCaExwIklgQTrqRKsE0c96BDAwbcLS0pLZE4qc8oumUbhItdAKVZJ4C5dpsaJWiDf9svRdHlpnRWcrRJci5124A3xWLPQhBTAhhJBLggJYEwpgcm7ke3o6OetqUl5S6+S6VIp+9KzmyRXAoaWfs7bCut8BlnbWwS0VwIQQQsglQQGsCQUwIXcB/XKCy3RCCCGEkNsOBbAmFMCEEEIIIYQQYktQAGtCAUwIIYQQQgghtgQFsCYUwIQQQgghhBBiS1AAa0IBTAghhBBCCCG2BAWwJhTAhBBCCCGEEGJLUABrQgFMCCGEEEIIIbYEBbAmFMCEEEIIIYQQYktQAGtCAUwIIYQQQgghtgQFsCYUwIQQQgghhBBiS1AAa0IBTAghhBBCCCG2BAWwJhTAhBBCCCGEEGJLUABrQgFMCCGEEEIIIbYEBbAmFMCEEEIIIYQQYktQAGtCAUwIIYQQQgghtgQFsCYUwIQQQgghhBBiS1AAa0IBTAghhBBCCCG2BAWwJhTAhBBCCCGEEGJLUABrQgFMCCGEEEIIIbYEBbAmFMCEEEIIIYQQYktQAGtCAUwIIYQQQgghtgQFsCYUwIQQQgghhBBiS1AAa0IBTAghhBBCCCG2BAWwJhTAhBBCCCGEEGJLUABrYjMC+JAQQsilIU21hBBCCLkNUABrYhsCeH//oLKqpqKypqa2nkaj0WhWNEytmGD3Dw6kCZcQQgghNx4KYE1sRgBXVFa3d3Tt7O5tbm3TaDQazSqGSRVTKyZYCmBCCCHkFkEBrImNCWAs1jY2t2g0Go1mFcOkSgFMCCGE3DoogDWhAKZdgWEVjXW0KlKPYUdVjMGMN6bkTYRx3q1y6lGU6ojmK3BeQydYt8BrtIu3BbvjrKkGhs30j80YBTAhhBByG6EA1oQCmHYOW11bX1vfUEVq2d7+QVdXd3pa+vjE5M7unipVy5BzZGS0t7dPJZDWNzaHhoZHRscM8VvbK6tr5WXlnu4eQUHBg4NDqsxnMhyxrq6+uKh4aWkZ5WDlj8L7+wemZ2YvUqwwlDAxOZWWmtba1o4jbZ6xD2+aHR4dx8bE1tXWHRweqZJMzbSl6Fucx8rKKndXt8TEpJmZWXHlIr6vfwAdRRl8c4wCmBBCCLmNUABrYtsCGGu3xcWlmdk52PzCIlbhWM7BsCJHBJbd+ITIQSwil5ZXkA3h5ZVVJCG/KOTiJlbzhiMaa7K4tIxNHBd1EjWBxMInaidyahmas4K6GQvBvnLNsSM2UWfEQ7yJSJSMGHwiFaWjfC25hXIWFhaRAYWi7ajMwuKSnGSotrF6KErcekU1YqJjcnJycVDEo9+QE/Gi33A47CVqKApBPCTN9PSM6H8Rie4VzUecCCurB83c3d3j7eXd1taOsIjEvji/RYVFLs4uuyLSeNZg+weH6NW42LimxqZz/BEEJWMIJSclv4x4mRif0NfXL8qHuqutrXN1dkFzzlGsbGgdehX1RHOCg4LRop29/fCw8Oys7FVjX6GLkA19gRMxb+wWVAlDF92LJMQsL6/gpKAQmEhF/k0M76Vl9LkoHOdFPqJZw+BBIYZdjOMB5WBIiXEoPlEO4pFTPk2mhqS1tXVUaXRsHEXJOUXhqAYKQfnStba9Mzk5lZiQWFJcglRxUPQkDufr7TMwMPj6zZvR0bHY2Liu7p7dvX1xwT767POuru6LdDjNioYTQQF8LRwdHh0eHh4QQog+pLmDkBMogDWxVQGMlTeW4OHhESUlpVisY8Ed4B8QEBCIBTfklrube2NjE0RFVVW1n68fBAlWeVjpRUVG/ebeR2mpaWPjEz29fdAe8vpeNhwCq/z8/IKQoOCw0DCDhYTCGhoaseY3zW9Y0y8tQ/bgWBCFWNlDPba3d6DOcXHx7//q1x0dnavrG6iPn39Af/+A1j1SiLFXGa8S4hOE2qmsrHpw/wEOh4PGx8WnpaQuLC2Pj0+4u7qNjY1DS6BRpSWlv/rle6jh8PBIb28fZIlp9RADTfL4i0elZeVowkcf3pucnklPS8/IeHX82tBX4xCvU9MN9Q3enl7oEDQHPRATE5ubk4uOhWoS4g3l4KCJiUm//uV7yckpqAlainoaari+gaPHxyd0dnYJNYsSEOPs6NTa0to/MOjp4VlRUYnd5SqhE2JjYnGacHJFJAz79vb1f/LRxyh8Sz7RRk0eGRn1o7/+QXRkFPbEpryLHhMloMmZrzLXNjahonEWhABG/NHRcXhomKuLq7ImOg3tQBf5+fiidTjF0NWf3n+AkQAhIQRwTnYOOl+oXOTfPzzKzs5BBjQf1tbeEeDnjzHT0tL6w7/+AYYcskHuerh7YCyhpZDrKMGgWRcWMXQxNsRIxpgXY1KMz0D/gPLyCrQFJ+Lhpw8jwiNwXpqamkOCQ1A4KhMcGPTxvY9wvqBsG5uaIfinp2dQjrItsqEcXFkYdYEBgaiGuAOM2mKYvHhhh6vM0NL+gdCQUOjb/YPDyalpjApUCcoWFRXqHZUfGRl9eP/B08dP7v/mEwxstF2Uj7Lq6xsePvgUldSqA+0qDSeLAvjqOTg4bGxqKS4pGxkdw+W2vLpGo9Folk2aPgg5gQJYE1sVwFi1QRf4ePtAG2B1Ltbc+EQSlu9QpJCdWZlZkIuxsXEiAxbrUJJYfO8dHMqZTQ1J2B37ent5Q9vAfI1WU1NrVgALg3QZGh4pKyuHQvD384dGhXKA0oaAQSp0y+Hx67y8fFTg6Pi12AWliQAMR4WGR1UbGpuQAUeRa4hsSBocGi4uLgkKCPTy9IIiQouQrbysHAWifwzP3GpUDPEwX18/yOOhoWFUD/lRK2gS1BBtjI6KhjQqLCh0sHdAl6ImiIfERVtQB2zKNYFgRnxhYdFrHFHxBVG0bmp6JiUlFeUIvWSIPDiErrZ/YQepAzGMeDk/9oVMgoKCxEKZIhKGToKEfvfnv1BKI1EBtBcl1NXVQ+8JjQ2DnEOFxS1xC3Z4dIyT/uv3foXB8OLZ8x/94IcF+QVyo9AbEREv7V7YISDvgiSMImhR5S1QU8M5hSjFecEhcAqg8Bsbm0KDQ1DDo9dvoPBLS0oRQAny4ZATowIGrQiBOjw8gh7AWHV0cMTuaCYyQE7j7ExMTH7w6/dfvoxMSkzCUaDbi4qKMdqRLT8vX4xJMT493NyLi4rFUfx8/cbHJw6OjvGJMwJNjnahq3HWEImKIRuan5GeIboRm5DNcouEIRK1inwZWVtbJ0YjKoYCk1NSBwaHxLmAjG9v70BtFxaXXr3KRA+jYsiIfkBujFhPD8/xiUkcFGczLSW1orxCjI3t3b3Oru733v0l+hY5lcelXYvhLFAAXz0QwE3NrSWl5Wf65giNRrvLJk0fhJxAAayJzd4BNj6pW1pa5uTkXFlZVV1d4+LknJyUjEV2QUHh/fsPsrNzsECPioyC5MPyAooL8umzh595eXhCUeTm5llQszChu5SmlRmFz88vvPeLdyEYoN+ysrKhKru7e6AcIDMghh3s7FE3SC+IEHEXFKVNT8/8p//4zf/8rf8H8kCsfpDU1dnl6uKakfGqqakZSg/lIC/KRLVfRryETIJ0cbR3mJycwi59/QPI/MXnX+AoqSmp0EtmV1E4Vm9f/28++riosKi/f+DZ02cTk1OQ9z7ePiMjo6geyoS2f/702U/+5m9zcnIhXSCN0HXQVyXFJZDBUHRtbe3ortaW1kdfPIJUwxGzs7IhYFBn6Gp0Nar35NHjAD//9PQMiFL0Npr88UcfQ+ChgS+ev7j/m0+GR0ZF82HoHOhGyGMcDlWUq4oyURTEHsQwIpA/PCwcVYUSg/ZGe+eMEh2ZodBQk//47/+0q7tHlsRahqJQICqG6n36yf2qyir0FSKx49DQMIZEVRVW/4ciM6qBxqKfv/Wn/wH1RyXkckwN5eC8+/v6QQFiXH3+8LNP7z/AqUEDUWco/MqKSshgBHp6ekXNkRQXEwtxCzGJg6IOg4NDX3z2uZenl7OD49MnTxMTEpdXVtH21tY2JwdHdBQCYSGhOBBkM6qHcvCpNMSgJsj24fsfYDCI8INP7ufm5OLyiYmO8fb0gk52dnSyf/6ivLwCu6AmOAQG6p//5z/7y+/+5fTMLDbRelwVzU3NKckpDx98il3QYw0NjciMQYKuwyYK7+nt++jDexgt4ui4DN1d3TBIMl9l4vSNjI1DIuNyc3NxRcdGhEdgMKOGKByf6Ftfbx+MGZSJGHzSrtdwBimArx4KYBqNdlaTpg9CTqAA1sS2vwNsWK+ffE1ULK9FJAJQVlBTUGIiEiYe7IQhABOR1jIcxXDneXFpxfhYNQwHEnftxJ0uGCKVu6wrwsKUNcfucmOlwpeWoYsQFuWItsjNQQCR4kAqk/OL0kRAfCJJ9J4oVs4jdhFJ8ua6RgfKFVDGG4oyZhZhYSJJ2OHRcV5uHsTewdGxHAm1OT09AyXZ0tIqFoWoP3ZENQyn8qRDINX6BwahwSA7UY6I1GOiCSKMolEqlHxhYZGsfmFQpH19/T/5m7+FNtazMEU5KBNnB20XYXEIhPEp+hDtgIlsk1PTIcEhZWXl4qBoS3NLq7ub++rqGvKgvWJHGDZFJQ3jwVi4iNcycWhxdLGJT5QP+V1SUordRfn4FBlgolbypjDEiBMqB0SkMFUYJgpZwOA3NkGULwJou+gWkRMB1CQrK1v5hw/a9RqGBAXw1UMBfMUmJkB5E2FOQbRbZ9L0QcgJFMCa2LYAvskGPTM3vyC+wKlKugyDL8eBQoKC3VxcPd09ZHN1dqmprRNqRLXLtRvqbHYJolqpaJnObJZNqxCrFK4yoRLFG6qgDLGJQ+BTGifzC2sQiyZ7XcRQPqTm3Nw8ysehUboqw9UbOhamiqRdo1EAXws6BTDOj9ZEJJK0UmU7NYPSMBowNWGOUsUrzfJxpaQL1MpsklSsSbweQ/dijk1JTes2PoaDcvYPDru7e5KSkjHr3qJFBY0mTR+EnEABrAkF8J0yoS5Udu51A41Gs3mjAL4WLAtgnJXlldX+gcHq6pqG+oax8Ynpk/fDw9Y2NrFXY2MTUjs7u8bHJ+SHL5Bncmoa+REDKdvXP9DR0TkxOaXnj1+GPBub6Wnpz589Hx4ZnZ6eQckLJz8ZIFwJtHFXV3dlZRWKnVX8tAECi4tLY2PjDcZa9fcPoAKyDEZbJg0vW5xBlebm5pGKQtAiJGF3HEJuID7b2zt6+/oXT96/gACKra9vqK6qHhgYFE/KwHBEZEYSqrFmfPIIhaNbRkbHcDixL+zg8Ah7ubq4pqWmIafoaqTu7h/U1ta99+4vla+uoNFuuEnTByEnUABrQgFMo9FoNC2jAL4WtAQwTgc+ggKDEuMTFhYWoeWg9Lp7eh998ai1te349RtspqVneHt6jY6OCQWYmJjU1NS8b3xvAooaHBq2f2H3wa/fz8/LF+9mn19YxF7yIbQMebB/bnaOs6MTxCqUJ8QqKoAkSETo0gA//6qqamhgiFtUK/NVZkhQcF9fPw4Lw1FQJdj8/AJUtLOTM/YVTVtf34D8dXJw/NEPflhRUYliIXpRvvGRF8O7GCrKK/7mhz9Chu7uHvHQytKJAEZOaFo0E42Nj4t/GR6BAA6HqqLMF8+eZ2Zmoe2HR8cdxpdoQH6vGL8rhH1FttzcvHd++rPh4RHl92X2Dg6hur29vIODQ1D+qS+SoNFugknTByEnUABrYksCuK29E9f/6to6jUaj0aximFQxtZZXVFEAXyVaAhiaDQoQwky8wQ76TZjwfThbUJWQj1CP+Aep2drWDhGYk50jXmIHKTg5NR3gH9De0YkwShZSUGWQiChEiFulHR2/Liku8XBzx4Gwuzg0ikV8VWUVhDH22j88QiQUI46elpIKoY7KlJaW+fn4Qocb9Pr2TnZ2DtQsBhfyoVhkh5jPysx6lfFqd/9AVFUcEQGo+paWVjdXN5SDAyE3IlFtlFRWVu5o79DZ1Y0+wSZ09cuIlxOTU0gVeTa2ttHYjIxX6IegwKDOzi5kQwVE4ciAqkIA/+wnPx16WwCjdRDAXp5eYaFhUNcUwLRbYWL2IESGAlgTmxHA9Q1NtXUNNBqNRrOu1dTWQ1tJsy25Eiw8Ag1pNzc3Hxsb9+TRYyhhLy9v+xd24WHho6NjkHBtbe2eHp6Pvnjk7enl7+vnYO8AFQfhd3B4BI3Y2NSMmF/8/Beff/Y5JKjdC7uiomKouy8F5/YONl1dXP+P//f/5+N7HyFGaFRhSIJQDAsLd3RwhKB1cXJ++ugxxO327h6yDQ4OBRh/18DX2wdV8vXxRWUMu29td3V1uzg6OTs5I9LNzf3Zk6cff/Qxqjc1NY0yCwuLnBydcLiPPvgQO3q4e9TXN0DSIgniMz01DbX9+U9/BiUPjR0SEtrb2yfUO8pHEzzdPVAskuyev3j44FPUYWRkFC0Shj5BL73/q1+jekKuy82BQa4j3t3NPTUl9a1HoPf2a6qqf/Xer7q6ew75CDTtlpg0fRByAgWwJrYhgAkhhBCbwfJ3gGHi7qXQeAgY7nYa48WmiEFYzqZMRYEij8gmkpSGSChAfKjiYaJMZeFyCaJw+Q4twgi8lWTcCwHZRKrIjEPKFVPuKKeKJFWqYdOkWGxC7c/MzKL3kpOSgwODWlvbxNHFjkpDyfMLi69eZfb09ok8UNc9Pb2QxAsLiyhNlZ9Gu7EmTR+EnEABrAkFMCGEEHKjOFUA0yzbuvFX5ebmFyBiYeK9+qo8SlPJY4QRI2/SaLfCpOmDkBMogDWhACaEEEJuFBTANBrtrCZNH4ScQAGsCQUwIYQQcqOQBfDE5NSu8aVQNBqNZtmk6YOQEyiANaEAJoQQQm4UBgHc1FJSWlFVXVtTW19dU0ej0WiWTZo+CDmBAlgT2xDAxrdAN9bVNzY2tdBoNBrNilZb17C5xYfrrhq45kNCCNGNNHcQcgIFsCY2I4ArKqvbO7p2dvdUD4TQaDQa7dy2vbPb1t65uromzbaEEEIIuQ1QAGtiYwKYv1hAo9FoVrSt7R0KYEIIIeTWQQGsCQUwjUaj0bSMApgQQgi5jVAAa0IBTKPRaDQtowAmZwIrCtNFBVYauzs7Gxsbu7u7pssv5N/e3t7c3Nzf35eiTkD+9fV1JB0cHEhR1sBwxK0tlIzjom5S7IVBJVFVFItVphRlDfZ2d9F1G+vrqi95ouY7OzubGr1KCCEUwJrYvADe2tlFpLDNk5+5x5JOjpR/7B4B8RViQ+ruHpJEPI1Go91ZowC+sVyG777IkgD7jgyPPHn8uLurS4o6AbLQw82tob4eyy9TwRkTFZWVmbn1tgCGqAsMCEhKTNxY3+jv748IixC7S8nnBUfv7uoODQmtr6uDpCwvK3dzdVtaWjKt1ZnY2d6uKC+PCAsfGRqGVo2NiQkPC7v4CZqfn09PS0tOTFpdXUWxnm7u+bl58voVdUYvLS8thYWGVVVWiUhCCJGhANYEE6itCmCs26ZnZuHn7J+/cHRwfPb0WUlxyeHRMeKzs3Mc7B0c7R0ef/EoISFxb//g4PCopKT043sfVVRUpqamPX70ODgoeG0dxUiamUaj0e6gUQDfKLB26ejoiAgPj4uNzc/LDwoICgkKhrwUqWura3m5eY8+/9zF0Sk9NdXV2Tk0KDgsJHSgfwCpE+Pjjvb2H334YXl5eaCfv5+Pj7ODY0Z6OpKOj48gC4MDg+Jj4woLCnw8PSFKRbGvj48b6up//tOfwZNOT00jBqsobw/PH33/r0uKi5Xrh67Ozp/97U8G+vulbQUoysfLCxmk7beJjozEQaUNIyg2Pi62rLRUvuc5OzPj5uIyOTEhNs/N9taWp7tHe1ubtP3mTUd7R2hwCBSmtH0uhoeHXV1cIaTF5t7+HlqUkpwsNs8NeiDAz1/aePNmcXERYrimulraNoIVbeTLyMqKSmmbEEJOoADWxFYFMBZti0vL3l7eU9Mz0Lew0dGx/v4BcY8X8XAqpaVlPb1909MzQuUeHB0nJiQmJyVjx929fUpfGo1GowC+UcBlQ2tB/UINent5Pfrii4cPPu3s6FDewCwvK0OS2WeGJyYmoHL7enuV+QGWRCPDI9FRUe5url6ennbPnju8sKsoL5eS37yBtMNBK8srEIbE9XR3X1xYFEkyOO4vf/Hu1NSUtK3gHAI4LiYWQv34tbRWm5mZcXU2L4BVbbHM9vY2GtjR3i5tv3nT2dkZEhR8QQE8Mjzs7vqlAEbnFxUWXlwAo0uDAgKkDeOfHpKTk6qr3rrZq0cAn6mLCCE2AwWwJpgWbVUAL6+swl/29fVjc31jc3xisn9gcG19o7a2rq6ufml5BfFNjU1BAYELC4ub2zvY5WXEy/LyipXVNewryqHRaLS7bBTAN4fDw0No3ajIyL6+PqxjdnZ2oFG/ePhZfV0dNkUGCLy8nFwfL++NjQ3Izt3dXVn87O/vd3V1+Xr79Pf1byJ1Y0MWyYhxcXIeGxvb25WKxWZ+bp5SRa+trRXk5z/6/HN/Xz/kkWIVQN++85Of9PX2SdsKziqAAaoXFhKS+eoVGjI2OpaYkABJuaX4Peqqyqp/+2++/uO//sHc3JwUpQMseBrq6qGuOzs6UXJNTY23p+f09LTcSwiggf/i9/6pj6f5PyKYZX19Hd2VlpIK/Y9iUduI8HBlL+3t7r73i3f/5Gt/lJuTI0XpAA1PTkwqKS5GmQCnNTc7W7V+tSCAw0ND/+Bf/qunj59QABNyN6EA1sRWBbBkG5u9Pb0J8QmpqWk9Pb3Lq2tYzM3MzA4MDObl5kVHxxQXlywuLSMSwri7u6eiorKmphbW2toGzcybwDQa7Y4bBfBNY3dnd2lhcW5mdmV5GXIXEheyUDwqjE/DW5FO2NrcwnJHFj8H+/tSwgmywEMeKLSlxcWZmZmVlRUUAlCsSgFmZ2WFhYZqrZ9QyOjo6NNHj0yFLo7l6e4OoW72dU0xUVHZmVnIo3oJFnKiDgsLC2LdJsUaGRkZeXj/wb3330c9paizgHatrq6iZAhX1RLoVUbGT//mb6CQpe2zgNYtLS2hWFRbqTkR9vbwfPedn6ueXtYD9kXPmO0EJKH5OGJ4WLjpd4A7Ozq+992/9Pb0UtaEEHKnoADWBDOjLQtgwwLA8FIrmErNmkYirDQ5nkaj0e6sUQDfcbBCaGttjYqM9PPx8XJ3T4yPHx8fl9LMgdWV6QILKw0svCDklIJcBvmF3jZ9C7QWULD7Vn3TsgxqqL8a+kED5e8zWwv0pOHPHxq9ilbov4NNCLFJKIA1sXkBTKPRaLRzGwUwIYQQchuhANaEAphGo9FoWkYBTAghhNxGKIA1sTEBLF7yTKPRaDSr2PbOLgUwsTpbW1sF+flODg5eHh7jY2NS7Js3R4dHrS2tbq5uL549d3Fyrq+rOz6yznJtbm7uZXi4g53di2fP0tPSsBaUEi4AVlDd3d2+3j4o08XJqby8fHd3V0q7AFiVlZaUuDm7PH382M/Xt6uzU/mEc09Pj4+Xt7urW2FBwWU8rU0IsRkogDWxGQFc39BUV9/Y2NRCo9FoNCtabV3DpuLtu4RcHMjRlKQkSDvlamxne6e2piYxPmFzw/gTxK9fIxwRFiZSL0JDfX1wUOD6+rrYbGxoTE5M7O8z88LqM5GempqUkCgWUdCi+Xl5ma9enemt1KYcHBwEBQRWVlQI0Ts3O4dOqKmuVknrzvZ29MzGSYsIIcQUCmBNbEMAE0IIIeS2IARwR3u78kVNU1NTGenpba1tB/tSJPRkXEyMCF+Emuqa4IBAeeUHpZ2SlFJcVCQ2zw3Ub1pKirTx5s309HR0ZGRPd7e0fS7QIYH+AQ119dLm/n5ba2tiQoLqlnV7a+vL8HAKYEKIBSiANaEAJoQQQshVYlYAb2xslJWWpiQnb508cZCelhYTFSXCgqWlpebGxp6enjM9bFxTVe3r5b29vS02oVHTU9OUShVroe6ubujk+fl5KUoHCXFxcbGx4lbt4eFhdVVVVmbmzMyMSAU7OztNTU3NTU2bm4Z72npAh3h5elZUVIhNrFlRZmVFhVx5gZYAxu6DAwPQz3Ozs9e70iWEXDsUwJpQABNCCCHkKjH7CDSArC0rKXV2cnZ1crJ7/qK4sEj560FQdz/+wQ/+/M/+S0N9gxSlDyx1xkZHvdw93F1cHezsol5GTk9NSWnGYlOSkv/oD/51oL//mX6sCJWvr6tzcnBwcXJ2dHDMfJUJDS+lGbUrkr7+R39cWV5+pkUnVmXQ56ino729h6tbXU2t6e5aj0BXlJX/X7//+67Ozqurq1IUIeSuQgGsCQUwIYQQQq6SnZ2d8rIyDzc3H2/v8TFLPywsA2laUlwSGfFyeGhYirISiwsLTx49bqivF/dyrUVLc/PjL75Q3hC2Cr09PX7e3t5eXhXlFcr75wAiH6q4tKSEL8cihAAKYE3ujgAWpxxeobGhAR4XTnRpcVEkWQB71VRXt7S0SNu2y+HBgX7PX11VVVdba/WRs7G+UVxUlJGW1tHeIUWZA8e9skG7ubmZkZ5eX1cnbZtgecGEBVBsTEynyV2Oy2Brays7KwtVPbrW2U3FzvY2zmmfjpfNYHVr2kvb29tolJeHR1Njo/KkT0xMoGPll8daOAu7u7s4g2e9X0QIIYQQcquhANbE5gXw5sZmXm6et4fn5MQkNg8ODsRfRnd2dgL9A/CJ8O7ODsQDxsTR0fH21pb8zSLElJeVOTk4QO9Z7iXkhFLa2NjAp3iACoVgnOETkeDo5KkqVEDEIKe8akekqMDB/sHa2hp2FPEIiMyQAfKQRf1FpFxPU1Ay9sVe6+vrCKCZqJw4HKpnqOjGhjiiyL+6uurr7T0/N4d4ZJZzIg8+AeLlLyDhuMtLy8rvIx0eGhol/hSNw6FpcslmQYdD6wKULGIQQB0C/f0HBwZQZwtNQ1JJUVFeTg5aITdBdKA4s6K2otWIRz031teVVUIAmVEBfIoYC6wsL//8Zz/zdHeXtk9ANdrb2lydXaqrqkUMRogYA6LTRCR6cnhoOC83V377KJBPq7KZyGmoFQbGxobyj/eG+hvBXlKUBijhr/7iuwF+/vImdgEoFkcXZwegwP19Q1GHBweoMKqNDjGMECPIJvc/IlETfKIDUQHRgciPApEB5Rt2RHHb2wgbijYB8dhxdWVF2aLdnV1sisbKPYAYCFpcaGg+qiGONTU5mZ6WJv5QVVVVVVZWJreitqbmf3/nO02NTWITu0dHRYWFhs7NzakuVRT1F9/5nzFR0dI2IYQQQsgdgAJYE6xQLUu7WwoalZKc7OnuMTY6Ji+aZZISEn74ve8XnbwBcnR0NDgoqLura3hwyN/Pb8r41SDsVVJcUl9f39PdXV5aannEQEu3trSurKx0dHSIN3YsLi4++OST5KQkLOixgg8PDR3oH0A8VuqLCwsL8/PNzc2vMjKELsKx6urqfvj9vy7ML0DM7OwsZPr09HRocPDMzMz62lpRYWFFeTlyQkplvXqFAyGytKQEbUSkKTit9XV1jvYOkHk+Xl75eXm1NbWwo0Mo8UPUbWF+obKiIiszEwIG+aG6/Xx8UCtoD1kAow/7+/ruf/ybl+ERS0tLszMzuHIQD1kP+YHOQU7DwVD//YO0lFQ0dntrKyQoqLzM0ved4mJisTu6ZX5+Pi01FWFE4lgQwGEhYTgXkEYWxiTqUFpcbBDAm5uQXuJAkFg+Xt6oJMIjIyPxcfHoPXTdu++8A00FoTU0OIhWzM/PTU5OxkZH9/b2oskQ2+gcFGIsWBP0pCy0QEtzs4OdfV1trVK+9vX1JSUk4qCoFVrk5OAoJWB0jYyi/2UBjL5FLxlPwXx0ZGSr8eEC9CQGQ011Naan9vb27OzsNePXt7Iys8rLytAuzFxpKSmnPrOAE9rf1y/ChjFQW/ubjz5CrdADUZGRXV1diMd5DA0OQQ9jJKBiGFroQ19vbwwndP5nDx9OTkwUFxV1dnSMj49/fO8jZMDuKCTAz0/ISxwlOytLHCI0JKS7u1sMGFMQj32rKivRCinqzZuO9o6H9x8M9PejT3JzcnEhIBJDKC42Fj2ADsQAkMdPQ0PDZw8+ffz5F072jji6iAQz09OGir39/TccDh0YExOD5qCHRSSKys7MxDUlNgkhNwQ4vi1c8MY/w0lRRnAhiz/bWfYF5wDuAzMSSjZdFZyb168Nf0BEmWiIBcd3VjA/i04w9VCovJgn5b+0yqDr9o1/g5ado9VBsTg03N8llW8tsNbCeTHtoovw+tj4d2rjuVaVjM0b3iHkbkIBrAmmS+s6mBsCGoVJKjU5BdJ0cmLSrLcrLS5pbGwUYWgMw0ss7B0wPkQMJNNHH37o7+MLBfjRBx9AG4h4U9CHGFLTU1MYYThcRlo6IlFgclIy5LfIMzU5mRAfD50WHRmVkZ4+PTVdU10VExUtdA7o7elFbUVYgPkUPgwSFPmhPXp6ehDp6e4OzVZYUAAFkpGRUVVVJTKbAr0tCszNzunq7IS8h5CDN42MeAkJDZFfWFCIKgkJgfpDuO6eCFqZifGJ/Nw8pErbJ6DAivIKVXx2ZtZ7v3i3vl768QazQJDHxcRAfIrNtra2xIQEEUZ7Y2NihYi1AHq7rqamQiGoBFA4EeHhK8vLOVnZ4t2eiImJjkGfiwwQrtB7kHYuzs7QTuhACLn8/PwzvfMTwKc21NV7uLk1NjTIPYZG9fdLylOAeorA+Ng4zhf8pdgcHhr28vDEuYA+DwoIrK2tRaRh1WL8y0hTY2NwYFBSQoIoGeN2dXW1rbUV8jUsNBSnz1iGXgYHBlOSpD+RYDCIbsGQCw8NEzMgpCm6AoG42DhIXKxpol6+xEGh4dFdk5OTaamp8hnpbO8QuhcXF8YkdGxRYRE6QW4pQFi5KUBRlSdvNAV9vb0VZeVi8HS2t6NzRHxqSgpaKsIC5MRFJKo6PDiYk529qXjBjAocd2VlJSUpKSggYHpyCv0pJRBCbh6YeJMTEzETYopTLkKGh4aeP32KyQpKtaWpOS46ptEa319YWlyE4xM/JoSS4UZzc3IuvhAcGhqKjY6FZ0GZY2NjDnZ2HR0dpnPgmcDu6JboyEjMnCi2uqra2cFRXpkA+ErIsPraWtO3QGNfTH1Yb7g6Oatc0sVBq46Oj3EIeKLgwEC4DxE/PjaGJYrs1s8BToTWuUD8+daooyOj9XX1M9OaX8A2WyxOX0hQsKn7QKvhu91cXLAkw0nBCgpuGmseKfnNG/SJq7Mzlh/SNiE3AwpgTXBVn29yuUVgWVxUUNhsvIkH1ePn49tQX5+RlhYeGopxgNHg6e7x8MEDuOHFxcVP738a6O8vC2ZMath0cnSc076DNDM9jd1TkpPhsxMTE8XDlhhnCXHxjnb27i5uTg4OUA7oaojklxEv62prK8rLHe3tf/PRRy1NTeh/qFOs2h99/nl6WnpTY5P4yyIUi8MLu6amJsit0OBgSCNEoi3BAYHZrzK7O7tio2OiXkYaamACXEaKYXf77e0dZINy6OzshIKCh0ZR0KjVVVXPHj/5zb2P0BViF6wGoEDa29piIqMK8vIQM2i4axpu9+x5XGwsdKPok9mZmbzcXB9vb2dHRywm4KERWVZW9s5Pfyq0XHxs3L0PPrDgejva27H4QCdAREEBotsROTE+jrY/+OR+ZEREQUHB+polpYeu8Pb06unueZWe/irjlawtjX+zuNfQILUICyw4aZwCNxdXF0cnocHQ2xlp6egKaPiS4mJfL2+sFUT+swK5WFleIQQkVLG/n196ampHW1tkeERkxEucbgjagvx8CFr7Fy/Qh+Jed19fn6+3d09Pz6uMjF/+/BeuLq5iQfbos8/RdZihcBZioqMRg8zYEV2EluKMhAQGyXc19YDzFRsd/fTRY+y1t7vrZO8QHxeH+O2tLQw2VCY9LRVnLTAwEMMSIw2eGzXBaZ2YMPzVA94dowU1cXF2htdHfFlpqSgZoBufPn4cFRmlnEnb2tr+5T//F1gCSttv3nR1daWnpXl5eDg7OqG9Y8a/ImHYvHj2fMqoUXFxod/EgK+rqcW109zUhAEGHY5DoPCCvHyMWETiIu3t6UWvGgtWg1GExfT4+LgoihBywzH7M0hzs3OZGa+gW+S/rmKShxQU4YuA9R9cvzyBrBlmjKSyUvUfUs9KXExsclKSCKPw0dFRTGJ9vb0i5nygQ7y9vOtqpRdPwNE01DekJCXD+4sYgYXfAV5dWfFy97CWAEa74HPdXVzhNzGNhwaHvAyLwDzf0GD4w8ToyMiLp0+/993vuru6hgQFYW2Qm50tHlbCDI91xY9/+EM4wdVVQ+XhU548evSrX/6yrbUVvvveBx9+fO+en48PVjtJCYnwMmkpqeLvvPt7+3BDcNxYJ2RlZvr7+sZERU1PTyNpfm4+61UmNmHwccIiwsKKCgq2jIsBdBT8l/3z53A9Yoki09jQ8On9Bz//yU8D/fwzX73CIjAoMHBhYQFJcOI11dUPPvnkB9/7HpYo8JK+Pj6tzc3Cx4mT6+zgiFZD6re1GDpfPJcnM9DXj07AAJa2CbkBUABrgqva5gWwKZiXTVstu0YliBRI29qgQAwsudjJyUkomaGhIbGpBEeXl+miZPkQGJciIIPMQNo4QRzrlEGsXWUUKK85lIcTxb4+KdZYKQOqWolNA2/HK8OngjootYqxNMPuxlJPvziRDaJO7m00Z3Njs7KiUr7hiQwjIyNJ8YnK52aVoKVWF0tSB77dJ0YMj04Z/jtBefrkeAQQLzdK5txVFSV/Wb74zwj6X1UBOZsAm52dnVh8zL/dgdgLErqxsTE1Wb0gMwWFyKNFBESkCIiwCAiwadpYRJpeAoSQW41ZATwzMwP90NTYJF/yUFzRb/8OsIxq9rBMdWVVgJ+/vAt0Y3JicmnJl3/UOx8JcXHyF5FQ+Pj4eIzxKzYi5nygQ6DV6xUCuKmhEXLdugJYf+8lJiRAKypzYxkd4Ocn3wGGMoTU1LoDjD6JCA/v7DC82BKr8AB/f/nk+nr7yE8AAcz8pSUl+Xl50KKQpj/43vdDQ0KCAgIDAwIC/AMeffEFpPLU5CQOVFRYCAcES0tJEYYTATm6pXivx+rKKpSz8uEjQVx0DAaVCKMhft4+w4NfrtPa29r8fH2VY1IA/9Xd1YUK9/f1ra+tz0xPx8fGpqelScknPHvy1O75c2mDkBsABbAmmARNF9zk4mCQbRph914BBgFsfAGV/MUkDGw4UUTBI+r39EQGnYbORK+iA5XTJcLbxvdycWwTQs6NWQGMaQerNLsXLwYHBzF79/X1xURFlZWUSMlGggMD/+Bf/itHe/szTezTU9NpKal5uXmQT5i+/P38oY6UM9vExMR//c//5X98+9utb38RwzLQdfFxcbXGt1pA6Tk5OLa0tCgrVl5W9rU/+MNP7n00q/vHkFCrkuISKN6B/n5Uta621sneQdylVHIOAYySITj/9N/+248/vDc3a/5Pw6bMz88nxMdnZmSgMnAHS0tLYSEhH3/4IbSl+GPl6Miot6fn8PCwwV9sbq2too+/fJcnwLlOS0198Mkn6Cul13B1dnnnJz8tLDC8ZgJ6tbys3MXJaXRkBEnV1dVRLyN7e3rgbnZ3DC9bXFxcxDkSMhs9bBaRJDzX2OgYpLt4Oh27i1QkhYeEIl7UfHZ21sPFtbO9Q65Va3OLp5s7joWWohB0Oz4RjwwYq6HBwWNjY4hBmSlJyVDdYi9Bd1e3h5tbXm6utE3IDYACWBNMClzFEkIIIeTKMHwHOCmpvq5uZWVFtQg5PjpeX1+H9lhdXVU9D9LV2fW//sd3goOChJ45E9gFQgj6TawCpVgjK8vLD+8/gA0NDkpRukHlIYcgmUxrC8n0zk9/CnEoHus9E/v7++gZFIvCVQtW8QL/+pqayPAIM98B3tubmpx0c3YxFcDo8//53/+Hm4uLeFRYPygW0nF5aRlSFm05PDjcMf52hnziUEPEI3VxYWF9bQ2ZlScI4ciIl2kpqcpIEBYcUl5adnxs+AEFoDopKBOHWF5agkzFKUM/mN6YNUVUFTpclCmAgBaH3tvd29wwvCFMnCkUiEMoG4JsqAYONzszg0/sq3z+CD2PamBk4tSonktCjLurK9UvuWlQAGuCq50C+AaCk6JypaYggx5/oMTwx1TtXxi6RjAO4U7OcVmio3A9n7UfrhFU+BbV9pIwdML+gViRECUYzOe7EAi5dcCFwSUp5cepYPLEXlafOnDFQdFZvVhU1fTVkhcHxaLT0HWm/SY8KVJ3d3dMpxHhLq9s4sVio6aqOiI83N/Xz8fLOzszC/JYJGHtkpOd7ePt7evjk5GWPj42LuJvL5cxLAm5OBTAmuCK1e97yJXR3NxcUlys/BNjZ0eH+BaNzOjISHRU1LTxR5tOZcP43su+vr7amprIiAgp9izMzMyoXvlgXYoKCvNyc3FxStv6QLu6OjvdXVzP8Sf2s4Le6+vtkzbOS3tbe1JiorRxFjBndRpaaninmrurm4eb+4rivaC3C6x54+PiVO98VoJ5aXx8HM2Eubm6hoeFzZ/xZd2XwdDQ0ONHj549eWKomItrfV2dFVc8GMCe7h7NTU0o9oIv0bHM8spKTU2N0gUuLS2NGX9+TNomhBBCyO2HAlgTCuDrYnZ21sHOPuplpBiLeTm5jz7/oqvT8EutOVlZWGTn5+UdHUk3gcdGx957991fvftLLw8PNxeXwQHDTwpvb29npKX5ens72js4Ojh2d2n+HCuIjowcGzP8JtPOzk5RYVFbW5uINwXjoaqi0skeKsv1xbNndcZ3O8/NzX328OGPf/hDVACHg+YUmacmp3y8fexf2Lm7ubW1tokKVJRXPH30uLWlJSY62uGFXWGB4T3JS0vLsdExaDLqD20vWr25uRkfG/vs6VMUG/nyZWlJiQUB3NHe7u3phRIC/f2VbxdDhSNCw5QCGFo9IjxcvP9Z1L+hvuHhg09dnJyCAgICfP0+/+yziooK1GF/fz8jPd3V2dnBzi49LU38KnJ1ZaWPl5enh4fd8+dBgYGYMhDZ39//6f37v/7le06OjobXOHcbfpUK9PR0I6ebs4uLk3NcbKyF+uNYOITd8xcFeflSFCpWV+/j5e2Fdr2w8zf+0K6UYEJtTU1SwpfKuaW5ZXNjEx0+MTHh5+2Dxro6OUMho1E5WdnPHj958sUjVxeXiPCI50+edXZ09Pb0Ik9sTAzOFNoFSSl6bGR42NnBMT8vPz83D9I6PDTMMCccHuKsYQw4OzriBImXcqPk+vp6ZPZwc/vs04fVJz/BJb74hNP6+cPP0lJTReTg4GCAvz9OlrenJ06ciJyamvLz8cWg8vPxiQgLk0eRKdD2cTEx6A0xoqYmJyHPjO9ON7zLGqcATUhOShJ/IRo1/o43Ti6aJv9iyvDQMPIUFhSgaU4OjhFh4SjqEO0qLHS0t4eC/eLhZ0JnIh5twVBB/MuICAvvewdJiUnDxrGHUYcrVLybHddUclIyzixKQOejoxYWFh4+eJAQFyfqj5wfffhhX5/mX0+aGhqfP336kx//jaHD4+LEqUGTccmgWGdHJzTk2DhRG0T4518UFxUV5hfgBOEQmA1wuh3sHTBo/X19Xzx9lpqSsr9veJsaToeHuzvGdkJ8AqYL7D4yMoLe+Nsf/RhVRX75FaloQlNTk5urW21N7Vn/CEUIIYSQGwgFsCaGxS4F8DWRk5090NeH9S5UwUB/f2qKJB4AFtAZaelbm1/ekykvK4NJG0awSoZUFstxCIbMV68s/ORddGTUxPgEAtAM1ZVV0F0i3pSDgwPoNB9v76rKSmhm+ZFpHCjx5Dd7BePj40kJCfJyubiwMP/kCzBYeUOuyENraHAwJCi4uLAIWgjCGCIBQgLKLTkxcf3k1ZFY06NDtBbfhfn5kREvGxsa2tva8AmhIpQtgKpRCuC21tYAP7/62rq2tlas71Hn4uJiNCQhPh6pRYWF5cb72LFR0aiVj6dXeWkZdkHFUpOT0RxocqSGBAaLn2ju7u5GJAKgoaGhrrZONXfgpEB5FhUUDg8Pra2tnTqz9PX1JydKP5shCA0KFr+1Cz2meqmGEhy6IP9L5SyYnJgICwmRNt68SYyPb29vPzg8iI6MRP0rysqHBoeam5rF3yBwCiCDRc7RkREcC12HcGdnR3JCovx7v9BdSYmJkF6QzeiZ2upqXy9v0bTMjFeQtZUVFcPDw0JQAXRpgJ8/Tm6/4ZUthrOAUw99W19XJ05WfGxcTXUNehhDVPQPph3oW9UPVKhAnvm5eRwL6hrDSWhdb0+vxZPfgoL4RIEI7O7tYjDgKOIXp0QqQIaU5GTxO1sCDJK4mNiw0FDknxgfR5kYooZ3mcTHY1iisahnSFBIf5/m21MxYqFUnz158suf/xydgJj5ubmsjEz5ET5UD2IbF1FPdzfGBrrR3cW1rbWttrrG8rcPZmZm5HeYg5WV5ZTkFFRSbOJ8oVgRrqqsSktJ3T65YYtGZWdlra6sQMaLEYKDjo2OogNHhochhjHeIIML8qW3rU5PT79KzzD7HD4iMcgff/FFk/FH4wghhBBye6EA1oQC+BrZ2dnxdHf38/HBytXB3r621vA7sRiaGKCjo6OJ8QlLi0vyOrWstBSrWygWAImCbCsrKxnp6eKlHfPz86lJyULimqWpoRGrZCzBsVIPDQ4RcsIskOLlZeU47sHBPtbKUS9f4kAiPjoqCqMFFcDiG4GNjY3AgABodYTRlqxXr8TvImBPqHoIABxO1B+pENU11dXbW9sIQ5Ps7uxgd1QJKgUF7u/tBwcFxURH7+2aF8BQAkidnZ1FmdCoKEE04WB/H5uBfv7oAXFhIwC91NHeAYW2s204FuKh3qGZUU/0YUlxMXZ8GRaByLycXAjLrc1NFAuNhyohCfkD/QPELxlCFEEyvTbOF40NjaXFJag/GoXCcayZ6RlIprXVNTRhZXkFwhs6BDnNIs5sa0trTFQ0Dndo7Bm0Isg/QDzfizojCdmM2dV0dXZB42H+Qiv29/aampqw19TUVEhwMHoAe6FiL8PDu7u6UTeIpcWFBdS2r7evob4hNycXGfx9/SBfl5eWNtY3MOTiY2JRLEqrq6uDiEXzUSxiMCfUVFUlJSSiN1DP9bV18UeK5aXlnOxsw7g4OOg1/AhzhtCiWa8yocEODw+GhobQ83OzsxgSkOIYmagSxir6BLtAkiF1fGwMR0SFnz5+jNGi1djZmRlPd4+dHYPGxr4oTdxGtnv2XFRsY309KzOzIC/fmJoApYdiMb/b29khBjmxCf2Jc40KoF1oFCJHhkdKiooN421/v7GxMS83F32FgSpuuqKxKHZtdRX7IrMpqG10VLT4JgLGDGrV19uL0nKycyqkS+YA0hEXAjLgYvzko48rystx5d774EPxG8haHB4cDg0ORUdGocfEwMaxMPCamwy/Cm6obX19WkoK4lG3/Ny80qKSvd1dkROXJ1Tu4oLhjwW5OTloqeGXSPv6MNQxerE7Rl1SfEJ6qvQGGowZCH50C2qL5qNAAInu5uKCElAB5CGEEELIbYcCWBMK4OsFq+SD/QMs0CcmJsQP4W5ubg30D3R1dsK6u7oQL3JiyCJzTlY21vTz83PYhGJpb2uDokAqlCEWu/LNMbNAh2DflqZmLHylKHPg8oCugyjKSEuHJJMz44jQw9mZWcWFhTMzM2LYYHkNnZOV8aq1uQU7ipyoEuQKKt/d3Y2cIhK7o3rFhUUQvRADIjMiJycnc7OzIYOXlpYGBwZWV768X6cCy330DDQ/hNOKUQciEsIYHQVNgs/BwQGxfEcSmgABkJudMzU5iSbgskceiGEwOjqKGEgmcc8T3Qg1CDkH6QgJhBgoBNQfAhLloC3QEpIqeG2444oyIaKg8VB5lAP5gbPwKiMDhYi7x1psb2319vSIM4vKiEdtceIQnp+bF13R19MDZSLym4LehmhHB9bW1ECqCT1zdHg4MNCPbsEAEIoI5UDUoTJz8/MYP6j86MgIkiDY0GpoHmha+dUs6ITODmmw4VSiGiIe2err6gx/SujoEFVCb0xNTjVAiaWmtra2ygMDDWlpbk5PTaurrZXlE1LHxsYMo6WoCH0l1D5kXm9vb2ZmJnQjmozTLTrcFBxrcXGpv68vPS2tsaFBZEPdIsMj0OGoDzS5kOsA5xQDu6igEJ2J/hGXDNrV0dYu2jU8PCzahU7AgMH4yUhLw2kVQwigfJzEtJRUjMNNk3euykB34wzifGHMYBOnY3x8HPlxIjC2iwoLS0tKMNJEZqSi4dgFXSH+cCPizYIMqGeX8USgTHFmUY35ubmCvDyoa/kBh6XFRVRVtAunFXlwpjBcZ2dmERgZGcGZxXWKAlEBXL84BX29fSinv7cXGUQhszMzEO1FRUVzc3PoBCBGDiGEEEJsBgpgTSiACbkLQDU9vP/A/vmLulprvrrpKoEO/PjeRx5u7pB/UhQhhBBCCDEHBbAmFMCEEEIIIYQQYktQAGtCAUwIIYQQQgghtgQFsCYUwIQQQgghhBBiS1AAa0IBTAghhNwoDg4O29o6qqrrausaamvra+toNBrtFJOmD0JOoADWhAKYEEIIuVFAADc1t5aUlo+OjW9uba+urdNoNJplk6YPQk6gANaEApgQQgi5UcgCeHxicmd3b2Nzi0aj0SybNH0QcgIFsCYUwIQQQsiNggKYRqOd1aTpg5ATKIA1oQAmhBBCbhS2LYC3tne2d3bxqYq/RkNlNre25U2Eb1T1aDQ9Jk0fhJxAAawJBTAhhBByo9AjgCHShKnihVlOFXZqBpVBEy4sLk1OTSOstaMoUysVJcDKyyvsX9glJSYtLi3LrbO8I8xCqoV9LSQJQwVm5+ZRma6ubmwg5/7hEcJxcfGIh1BX5afRbqxJ0wchJ1AAa0IBTAghhNwoLAtgiLSVldWe3r7S0rKqqurhkdGJyamV1TWh9NY3NkdHx6qra5Da2tqG1OWVVcRDeSIwPDwyMDC4tLwC8QmZ19zcMjExqSrfrKFYHBRC8enjJ329fSMjo4ODQ3PzCyIVheMQM7NzbW3tJSWlKHZmZnYN+xirhFQcsb9/ANK3rrYO2Roamzw8PKGl9/YPkAmV6ezsKi4uqampHRufwI4bxr2gt8fGxtEJg0PD2LeysgqpyI8yxefq2vrQ0DDisW9HR+f0zCyKEkmG3RcWEYmk2to6dBEyI0lpB4dHqJWzo1NGegbaIroa+6JW2OWXP/8Fuujg6Fi5C412Y02aPgg5gQJYEwpgQggh5EahJYDFDcmgwCBx+xSiF5u9vX3PnjyF1j1+/WZjYzM9Ld3L0wu6ERIUnykpqS2tbfsHh8a994aGRxzsHT54/4PCgsKlpeX5hUUYdKF8CC1DHuyem5Pr7OQMnYmDQzFCEiMJEhG618/XD/IVkdCZUJo5ObmhIaH9A4OoZ2FhUeTLSEjcdWNRkMeog5urm9CcqG1EeATEMGxqeqaxsenJo8d1dfWoM4iLi//g1+9Db2NHFOXj5Z2dlQ2BCu3a1z/g4+1TVlYOVYwdu7u6S0tKW1pakTo7N+/i7JKR8WoUPTg1jc3S0jLUvKO9A+WgK/CJ/tja2c3Nzfv5z94ZHh45VAjdvYNDyG5vL+/goGAcWqh0Gu2GmzR9EHICBbAmFMCEEELIjUJLAEOzQfR6e3pBXr5+8waKVhjUKWQnPqFLIfYgFGELi0vdPb32z19kZWXv7u1D9UFSQg0G+Ae0d3RC46FkFCgXLhuENaQpilLFHx2/LikucXdzx4FQFI4rnhlGfGVllZODI/YS8QYJOjsH7Z2Wlg7JDSUJWYtoJCBpdXUtLzcPuhd55ubmvb19UlPTcDgodhjUNTSrkOVoY0lJqa+PL46OHXGssNAw7LtrrDm6AroXOUV7GxqbggKD0lLTUIfp6Rmo6KLCIkOxs3MoEyUjMzpH3JfGP5SAKuXl5f/sJz9FJZUCGCWMjY17eniGhYUjQAFMuxUmTR+EnEABrAkFMCGEEHKjsPAINMTbwvxCYkLik8dP3F3d3FxcHezso6Oix8YnIOHa2zt8vH2g/Tzc3KHfnj977ufrBxkMRQfh19jU7Gjv8Kt3f/noi0dOjk52L+yKioqFsJQL398/QJn/v//v/3H/N58gZmdvXyTBkHNkdCzyZSSKdXf3gOJ99vRZeVk5dCSU7fDwSHBgkP0LOxwaGQL9A7q6uiGGUX8o1ZzsnBfPXzg6ODo7OgUFBaOQD379fkJ8wsLCIiqWnpb+4tlzN1c3D3cPBDzdPbq7e46Oj+vq6u9//JsP3/+gsLAI2fr7Bx4/evzxvY+qq2uweunr6//is8/RD8jv7en16PMvII/RY4Zbu8bHp5OTklEfV1c31Pbp4ye+3j59/QOimaJF6JahoWF0FHJCHIvGIhUBHOKDX/26p6dXKYxptJts0vRByAkUwJpQABNCCCE3CsvfAYZBoxluwBqVngiIeIg3bCqTYEp9i00UKOJh8o5K2zIKWqSq4oXJRxQlyIUbkk7KNJN0spdsqAY+TVOV++IT2eSccv3lVJFZ3hEVEAUKkyJNilUaSoMIz83JhZzeNH6TGTof4VevMiGhsYsqP412Y02aPgg5gQJYEwpgQggh5EZxqgCmWdeE9P1ykz+DRLuFJk0fhJxAAayJzQjgrq6e6pq62rqG2rp6Go1Go1nHautrauvW1telqZZcCRTANBrtrCZNH4ScQAGsic0I4Na2jqrq2qXllbX1jdW1dRqNRqNd3LCoamvvLK+o2t8/kGZbcvlQANNotLOaNH0QcgIFsCY2JoCxXDP9hg+NRqPRzmfbO7vtHV0VldUUwFcJBHBjU0tRcdnwyNj6xubyyiqNRqNZNmn6IOQECmBNKIBpNBqNpmUUwNcFXPPh4SGU8AEhhOhAmjsIOYECWBMKYOsajo71Il+eIQz9IL+uk0aj3UajACaEEEJuIxTAmtwFAYwVnBClyiTTSATkTQRgIt6yKcvZ2tkdHhm1f2EX+TISMabaT84sNuUjquKlVHOR5zCUr2qpHKkqH2GxKVdMTjJrIg8+UY4qM2L2Dw6LCot++fNfDA4OoS8QidPk5+cfHR2DUSeyGUo42R0BdOCpB6XRaFdpuDwpgAkhhJBbBwWwJrYtgBGG+nr5MtLb0ys3N6+trR0xWNDNzy9kvsr0cHWLioyqrq5ZW9/Y3dsfH5+Ij4tvaGicnp5JTkpOT89YWFxCZrk0lSFpanomJTnFzdUtIT6hubllcWkZorenpzcwIDApMcnTw7O0tAw5DdJue2dkdCwlJdXD3SMxMWlufmFv/2BwaDg1JbW9vSMrM8vDzR2pM7NzyAnDofPzC5A5NiZ2aHjEQjUsGPZClQoLiww1jItHS6dnZnd2d9c3NpuaW/x8fAP8A3Kyc0ZHx3b3DFq9uLgE9Zmbm0dOdFpPd4/Wy1dQMpqALq2vb0hOTvH28q6trUO86F70ZFxsHPq8uqYWXTE8PAI1PDs3j5ogvqe3D5vItrS8kpdfgAogT3l5RWF+QUhwyPDIKN/4QqPdHKMAJoQQQm4jFMCa2LAAPjg8io6KhqiD1NzZ24cMg1jFam7v4DDyZSSE5crq2uTUdFVV9fLKKiTd/uFRZWXVFw8/g/zDmg+REMbyKlBlEGkQq2GhYUVFxRCZIyOjzS2tkI6Ih6D18fZB5Os3b6BsoYSPjl/juMgPqTkxOVVWVu7n7YPqHR4dh4eFwyAFUUlIRGSurauvqKgMDw1D3SCDocahhCHIjW9jlZqG0mAirGWoSV9fP2qCdqA52MzKykbdcNzu7h4nRydITVSyta3doEj39lEgmmz3/EVUZBTicThsqspUGiqPnOnpGZD32IS4zcnJPX79OjsrOyoqGhIXR5yamn7v3V/29vYhjDw4dEJ8Qm5O7uHxa9EWdH5MTCz6LS4uHlq6ra09LTUNHYUKi6PQaLTrNQpgIrO5ubm2tiZtnItDI9LGCViEbG9vo/D9/X0pSsHB/v7GxsbW1pZq3YbNTSSsr2NHrGSk2AuDYlGZdWOxVlwdodVowvra+s72jhVri+UsOgG1RUCKOkEk7Wxv28YajxByDiiANbFtAQyBWlpaBv0pBBh0HT4hLKEMoS1XVlanpmfcXd36BwahF49ev4HyTE9LF+JNLgeGNeD8wuLg0PDi4pKIR8zCwmJraxtUIuTr9MxsUGAQJBykXVdXN9Q1BCRcXF5efmpKKqpXVFySkpKKbNi9rLzC29MLtYJBigf4+c/MzO7s7I5PTGLHtvaO8vKK0NAwRKJk1BOCcHZ2TtQEi1FsQjMnJiYh1YJQRFJHe4e/rx+C0LfYRH6jqN/s7OpGTbCJbJDWOOjB0TEyrK5v+Hh544hQ49hfWRp2g2CGepdjUPmY6Jjq6hoEUCakLKQv+hAyGyoXARSCTnv44NPBgUHUANVAP6QkpxTkFyAgat7Q2JSWlj4/v4BuR2d2dHRmpGfMzs1baBeNRrtKw8VIAXzjeG3w3SJodjUDt27Wsw8PDQX5B0AwSdtnpKmpqbSkRNo4O6HBIUkJifCf0vYJMVFRWZmZW+YEMKpakJeflpKqEsDlpWVwnWNjY5DAg4ODcKntbW1S2gUYHRmJjooqyM9Hsf19/c5OTv19fRfUqzgRTY2NLyNetrW2ojnFRUUebm7rF/s7AoDoLcwviIuNnZiYQG1fRkRERUYqT7pBAG9uJicmofekKELIHYMCWBMbFsAIwIqLSxzs7O2ePYcU7OzsgrKdmJjMyHgFpWeIf/4CahOZscqDlnvx7Ln9CztHB0dnJ2foPehGUdTh0XFOTu5f/cV3y8rKofcQg0Uh1B0UoJenl6O9g4O9AxQgCkckPDFK7urugaD19vK2e2EHwQkFCJ2JakBvQ+z5+fjiE9VGJCR6c3NLTEws5DckOopG4VDmUZFRqB4sIjxibHxCKFLsEuDr99/+/NvQilD4onpahnIGB4f8/PzRLicHR6hxw73u7R20As7Yxcn5+ZOnCEBpo6WjY+NBQcFPnzw1NMfOPjs7Z3f/QJSDXebm5j94/wMnRyfjfeidnb39gcEhtBQljI6OQVc7O7v4ePtAu2KvxsYmF2eXZ0+eJiUlQ2BjmYLmVFdVi+agQ9BdWZlZUPKe7h6+3j6Tk1PojbTUNDQzwD8AShjli0PTaLTrNQrgm8Pi4qKLk9Nff+97vl7ecAT3P/6Nr7f3y/AITO+QgvDmUGpFBYX+fn6FBQXZmZl+Pj7Qq9vbhj8+Qi9VV1XBF/z1974P9xceGhbg59fR0S5Kxqqovq7ez9cXHio4MDDA3x/7RkdG1VbXiNVSU0MDlOH93/wmLCRE7CLAjqEhIXCOqAY2Z2ZmPv/04c/+9ic11VUigwDZoMQC/QNGhoelKAXRkZGosLTxNqg2WpSXk6tUoSgtOysrIy1NbB4cHKQmp5SVlu7s7IiYcxMWGpqflydtvHkzNTUVHBg0NDgkbZ8LiF70and3t9jEiquxsTEmKhrqVMScj4H+fndX19UTIb21tZWXm5uVlSU2ZV6lZ6BzpA1CyB2DAlgTGxbAwrCJBZwwOQlrOtNIZU5lvDCD6tN4qZUqv7wJUybJmRHYMr4jCnrv0RePXJ1dIJ5RcySJEoQp88sxS8srecYvM2N3OadlE4XAxLPKMMSZFi7XVhUvm4iXN+X8CKhS5STEwkS8HCknKfcSOUUMPhCg0Wg3wXBJUgDfEKD02tvaM19lLi0uTk5M5GRl9ff3r62uZmVmNjU2YmWzv79fVVnp7eXl6e4Olevp7vHo88+x7pH2f/NmcGjIx9Nrc2ND2n6bubk5qNm21lZp2wSIw6iXkdKGAiwkaqqr3/v5L54/eTozPS3FKoCOhXhOS0k1u944qwDe3d3NycrOSDf8ERnIAnjXRABjL+WOpxIeFmYigAOHBgel7RPOVObGxoanm3uPLIAPD3GyoiOjTAXwmYrFqfdwc8PZF5tCAGdnZopNmVMF8JkOSgi5XVAAa4K5z7YF8E229Y1NYWvaXzY2NehYSkQajXY1RgF8c4Dwq6muSYiLh8gcHxtLT01tb2tbXlqCFKyuqsLKJurly9Tk5K3NLeRcXVnJyc7+/OFnELSyl+/v63dxcoaug/ra3NhcWFiAwkQ8lkTb29uDg4OhwcGNDQ3QbDvbO/JeCCAVkakpKcGBQQhgb/G4MpI6Ozt9fXxSkpJQgfm5OW9Pz6TERJSsVFbI/Co9HdkG+vukKAVnFcCguKgo0N9/dmYGlRkdHXV1cWluapLSjGowwM/vj/7wD1FbdIUUq4P+vr742LiK8goUi/Wiu4trd1eX8tCQx//qX/yLT+/fX1pclKJOA/q8qrIqIT6+t6dnY329pKTE090DK1Ep2bgMc3Z0/L/+xe+/DI/Qvx5bXV3F+YW+nZmZQS+hD19GRJh+v1pLAKNLv/HHf/Kzn/z0gl/qJoTcZCiANaEAptFoNJqWUQDfHLBwgbSD+ISmgu+GtNvdMbxRCZsQqHDlEGqIwypncXERMhhrHcSLJFECMu/v7UPzIAMUFMrCvqLknZ0dUbgAm8dH0joJu6MQES9yIKfYEUmIgVwUevj18TEqAD2G3XEs495fEhsTkxifsLy8Im2fEBsdnZ2VhWLNfAd4Y0N8BxipqnUbDo0DrSyv4FOV1FBf/x///Z9mZWaa1uFUUCyOtbJiKFalJxsaGt595+d+Pj7neNYaTUO3o1h0naq28bGxP/nx32Zlqp9e1gN6G+cRxSIgRZ2As48Tk5KUnJ4qPSsuMz42/v57v77/8W9UNSGE2BgUwJrAPciu8VZDAUyj0WhWNwpgYkWw3jBdcmBBZpDfGm+BFu9PhgLXv27DLgfmiroghwcHe2e5n6wTLEnNNvyCGATw5iaEsWm/oSHgHH8dIITcLiiANbEZAdzS2o4l2sKi4deL8I9Go9FoF7e19Y2W1o7yiioKYEIIIeQWQQGsic0IYLTC8EdfQgghVgVTK5CmWkIIIYTcBiiANbEZAUwIIYSQ287h4WF1VZW7q6uTg0Nb61u/7tvf1+fv4/v08RMHO/usV5nW+rvM5sZGfFyco739ky8evQyPGBsdlRIuABZXY2Nj/r5+9i/s7J49z0hPX1lRf/n5HGDx2tjY4Obs8uLZM1cnZ6xrlY9Pz0xPh4aEODs4JicmrlrjcISQWw0FsCYUwIQQQgi5IWxvb2ekpdfV1mKtJkWJn4Bqb4dMnZycFDFVlZUerm4X//Ys5K6Pt/fkxITYhMaGelS+U/p8VFVUBgUEyu+mQm1TU1IuLq0T4uJTk1PEEnZnZ+dVRkZBfr5KWk+MT4SHho6PjUnbhJC7CgWwJhTAhBBCCLkhCAFcU12NgBRl/D2k7Kys2pqara0tEdPY0ODv63dw4a+mjwwPe7l7LC0tiU0o7aLCIohVsXluKsrLQ4NDsMQSm9CoKcnJNVXVYvPcxMfGQfSKMBaygwODkMTDw8MiRjA6MkoBTAgBFMCa3BEBvLu7a/ZZKfkFieiHnZ0deJH29vaFhYULjo/V1VWl597d+fIHFc8NSpiYmOjs6ED15NJQbeWBCCGEkFuNWQG8v7/f1NQUFxMzPTUlYupqa/18fJRve4bnbahvqK+vh1qWonQwPDTs6uQs31iGenyVntHU2Cg2Bf39/cWFRcgpbeugrLTU19tbvkHd1NCIYkdGRsQmODw4wFHKy8rg06UoHURHRiYmJAhdjbVsfm5eUWEh1rUiVaAlgLGwgdovLy0dGhzknQ9C7gIUwJrcBQE8OjLi4eZm6hF9fXyqq6rEUICjHR8fhwaGTi4qKIAdGH/k8KygtOTEpJzs7KCAACnK8DzSuL+fH+SrtH125ufnw0LD0ASM3daWFvjR1ZVVxOPc5eflwx2KbIQQQsitBu44PTVN9Qg0wHKlo73d29PzxdNnds+fp6WkKP+ujdQvPvv8G3/8J/l5eUIf6mdtbS08LMzJweHpkychQUHQh1KCkfLy8m/+6Z9+/umnZ3rcGnWAYPZwc0exqHBSYtLi4qKUZviz+G5YaOif/OuvxcXGnmkNhjUG1i2O9vb2dnZO9g6lJaWmvwA8Pj4RFhIybvK49dDQ0L/7N1+/9/77MzMzUhQhxKahANbkLgjge+9/MDDQL22cUFRYGBocvL72lioeGxvz8fJ+8ez5yNsPFOkEnRkZHjE8PLy0tITCpVgjcTExkKkX/7YS/D0Edl5OjjyCFxYWHOzs+nr7xCYhhBBye8GapK21NdDP38XJSfUSLAs0NTZGR0a2t+nNrxNUxsPNLTsr66yi2jKzM7NPnzzt6uyStq3EzPQ0pK+nm3tBfv7m5qYUawQiPz4uLic7+0y3xwkhtxoKYE1sXgBvb219+Ov3R0fUfwqFQI2NjjF1aYiZmZ5JiItX/okUwlXP2yZDAoPcXF0z0tODAgM/vveR8rmmiooKHy+v1VXDbVslKFbnrWYM2arKyhCDaF+TooxsbGwEBQTm5+ZJ24QQQgghhJC7DQWwJjYvgIGjvX1dXZ20cUJ/f7+7q5v8tZ+x0dG0lBQIVOjJ/3979+HcyJWgB/x/sqvOVa61z+Xyne9sX9m+c6rblbZ2pV2vd1UaSavVrtJImtEMc84RDGAAwZw5zAEEM4eZIBgAhiFBggRBJIIgZ/wBr9mCwOkZTpBEYL5fPVHdr7tfv37djemPIMGqysqOtjbpEnn8ODsr6+/+w98YV1YCKz4fAu3y0lJGWnrwwMbHxPb29Egzl5qbmv71X/2r7s4uaV7Zxvo6jmLFYHA6nXt7e9NTU/KnPprN5s/+8qn8uSBERERERPSGYwBW9CYEYJzvhLi43d1daf6SbnCwrrZW/pgNn8/nCAh+S9ZkMr37q18vLS5J89eAdhBHPR6PPLDtbW0tTU0h7/Qiaf/lk0+qKq/167u4XtEgmvVzOLynpzhzqEdvc7NzNta++1wNIiKisCb+GcW/kld/Qsrtctnt9pB/qV+d1+t1nDjEB21IVa+D2+3GUaDZ19jbi/NzDI4YhJBnWTx1BJ4RHDicqz/ghj5gERZf5yfaXgL2iOPFM9UNf6rE4GD0rv7u9KsQx45mcbpDLiGMdsQ/ZtONxQCs6E0IwMLVfwyu44cbH7T8016FRERENw0SVENdfU93t8ViCc6N9uPjmKiovt4+ZAw8zGmrqjo7O1/9n1HHyUnXg85ytdpsMqHlcnVZsUr16v/ub29t1WirW5qaRChKTvL/Xu6r93bm4UxZqVqn06HNtdXVKP8ngCzJjzfoNkZvYX6hIC9v0xz6KdAiAKenpvb19kpVrw9iHrqBbFml0dRUV4tKdDI7KxMnS8y+BByRUlzHYL5ckrfs7U2Mj29sbCg9FmKnV8/U7u5uVkbm1bdSwHZ0lJqSohsawvFardYH7e1lpaVyDEYniwoL8/PylHZH9MNhAFaEG/IHCnhEREREL0QE4JA/g4Ro0dHW3t/XhzwpasZHx9JTUpG4xOxLQ4xMjE84vPw7wG63+0F7R0N9nZh9aX09PTlBfwwCoatGqx298ttYLwrJqqG+Xkzj4W1xYUGr0SDLiRrhGX8HGI98eTk5GEZp/tWgtRXDSmpyCvI24j2SOZJe9P37Lc3NWGqz2ZD63vrnn6NGXVKC/aLn25e/dzY9NfX+H/6ARY92/J+3cnx8nJud/dt33x3o69frhm9/8cV7v/99cmJiXU1NW0trSnJyQX6++FMaOGq9Xh8XE1NfW9fX01tUqMI4z8/NYZHDf5G0oaYwvwBfRcnLya2u0u5b/J/Jcurx9HR1JcUnoOXu7u7gRLq2thYTHf3Or36dnJDY1tqqrapKSUpeXFjEIiRYjDM2efvnv0hOTCotLs7Jyhro75evvZMTe1pySlNjEw55aWGhpLgELQR/72b30aO83FxmYPrxMQArYgAmIiKiG0IpALe2tg7292NC1IyPjaUH/aHdYC8UM1aNgQB8+ad0XQjAHQjAUsgM9kLN9vX2Bv81RH8Arq6+GoDR5gs1W6ZWN9RJ4TwQgBe1mirTaw3A1+9PT3d3SVFR8ClA6qsoL6+tqRGzOFmpqamGK3+GQ0BcrCwvRyOYXjUakTAtFotYhINSl5SKaWFibLypofHo6Ki7s+t//eM/pSQmZaSlI3ZmpKZ99cWXMVFRc3NzuGD6+/s1lZrKCvynEQWxvLmx6SDoQ0k9bndvby9SesjTb3dnpyq/QEwjJBQWFAzrhsUs7O3tIYfv7u1J85cwXEj1udk5I/oRxHj08EF7u6qwMOQHoXE4f/jd/+PzNv3IGIAV4dblDUlEREQ3wVMDMCBaxMXGDg0Ontjt6+vryJOt388wjQ0Nf/2zn73/3nvOF/lUSLvd3t7WjsyGGIPpcnVZUaEq+O07h8Pxu9/89t//23/X3fX8T6yUmUymaq0Wac3/I9B2e3JSUkd7e/Cj59LS0t/9zd/+8hdvvdBfMZycmEDCxFdky7XV1fvffosMHBJZXy4AT09N/4//9t/f+vkv0KxU9TyOE0dba2uJqujQasUoOU5OMIwf3bqFr2IAceBZ6RljI2PoLZYf244PrYc4O3KHsUnngwdffP5Felpa8OnWVFT88q23y9Xqg4MDDODY6FhiXPzY6CgWGQyGkuLiEb0ebboDsHfThkm8x/tsXu8purG3u4v0i7ODBO50OMQlhBjf1NCQk5kl8jxyQnZmZldXl3wl7GzvxMfGGpYN/iN1OPb398U3TXAsm5ubeTm54qRAb09Pfm5u8O8Ym83m3Ozsp/7lEaIfFAOwItyNDMBERER0EyAINdY3IEWE/A4w4InF5XQiRyEUhbz3u2k2I6be/vyLl3u8O/V40CYSUchnI2GPCbFxt957D/FGqro2f29dLrRpPz4OOZC93b0P3r917+7d7e1tqera8MyGlIVmkR4vLr73/IZFiJcL8wsIwBgQqfYS+oBNMtLSrgZgDNrvfvvbj259gIAqVV0bTgSGDs/W9mP/Z315T0/Rh+DjxSAcHR7ajo6Qh90uV/AJwjSyaF52TshZa6ir02qqMIDiM71wdqQFl3CaxE6Pj4+Rw/2fDHoN6KpoEP/5/4evTqfY9Zk38AlhTqe4rjCS6DbWCf41Y0xjHezUP/joVdBOLwLrox79CektInpRoaq0uESaJ/oRMQArYgAmIiKimwO5DrEBGSMkNz6D78z/R/XxSCPNvz7IWq/9MQnPoB63+7X3VoptTudTPx0K44NFGNirh4P+IPj9aE+D2N3C/Hx1VVVhfn5eTk59Xd3WpvS7wTAyMpKfm4v62upqg8Hw0z6vvzqMargfAoUvBmBFDMBERERERESRhAFYEQMwERERERFRJGEAVsQATEREREREFEkYgBUxABMREREREUUSBmBFEROAcRQ+n/8zMIiI6LXy4V8K6aWWiIiIwgEDsKKICcBT0zMDg7oD6+GRzX5oO2ZhYWFhefViOz7Bq6vNdiy91BIREVE4YABWFDEBePrh7JBObzu2O5yuE4eThYWFheXVi9PlfjgzxwBMREQUXhiAFTEAs7CwsLAoFQZgIiKicMQArIgBmIWFhYVFqTAAExERhSMGYEURH4Ax63R7XG4PHuOCF2E2pNK/5uUsJlBEvVKR1xftyPWiEl9RL1oTRVTKRa5nYWFhubEFL1YMwERERGGHAVhRZAdgTBsMK4UFhYnxCY2NTZNT0yJ87u1Zamvr4mJiVYWq/v6BY/vJqffMZDKr1WUjI6NbW9uVlZqamtr9A+tTk6rYxdzcfHNzy/CwPjkxCe2sb5g8p177iaOzs6uvtw+bx8fFd3V12+0nYqeDg0MaTVW1trqivKKxofHAevjUxllYWFhuTsHLFAMwERFR2GEAVhTBAfjMd15aUtrd3YNwi2i6vr5RV1uHhznvma+kuASLDo9s2zuP9PqRI9sxtsL6Q0O6r768jRqXy41KBGP5KTCkuD2nJvNmRnrGwsIiGtzds6hL1TMzs77zi/n5BeRthOfHT560NLcg8Z4/foL2sRR7xNKEuPiVFSPTLwsLy80vDMBEREThiAFYUWQH4MJCVW9v3/nFY+RV1CCUnjhdW1vbi0vLmEbERQBOSkxaNqzgIQ8xdWBgECHZ4z0L+ellLN2z7C8tGyyWfRFc0aDZvKkqVKEG00i2lRWV09MPfRePDSvGYlURwvPjx0862jtqa2ovEIBdbqyDkNzZ2SVa293dC94FCwsLyw0sDMBEREThiAFYUST/CHRgoq+3LzYm9v6393KycxYWlxBWN7e2m5tbMtIzou7dj74fpRscEg95Ot0wVouNjkmIT0hOSBQ/0iya8p1fdHQ8+OVbbyMhI05jF/YTR09P752vv6ms1GAptv3m9lc93T3I1TlZ2XExsbMzs0i5xUXFKckpK8bVs/OLKk0V9piYkIhdZGdlIyeLWM7CwsJyYwsDMBERUThiAFb0JnwIlivwIVjBb+rike5qZfCawfXyUuTV4ErH5cdoiaX+TQLTwZuLHQVPyyW4KRYWFpabWfDCxQBMREQUdhiAFUV8AGZhYWFheenCAExERBSOGIAVMQCzsLCwsCgVBmAiIqJwxACsiAGYhYWFhUWpMAATERGFIwZgRRETgKemZwYGdfsHh0e2Y/zHwsLCwvLqxXZsn5x6yABMREQUXhiAFUVMAMZR+Hy+MyIieq3w0op/KaSXWiIiIgoHDMCKIiYAExERERERETAAK2IAJiIiIiIiiiQMwIoYgImIiIiIiCIJA7CiyA7AXq931WicnZmx2+1SFRERERERUURjAFYUwQHYtLFRWV6xvrbu8Xi0mqrJiQlpARERERERUeRiAFYUwQG4saGhv7dPTNvt9uyMzLOzMzFLREREREQUqRiAFUVwAG5qbOzt6RHTVqs1JyuLAZiIiIiIiCIeA7CiCA7A5z5fcaFqWKfDKU9OTNze3pYWEBERERERRS4GYEWR/SFY4Ha7HQ4HDlOaJyIiIiIiimgMwIoiPgATERERERG9URiAFTEAExERERERRRIGYEUMwERERERERJGEAVgRAzAREREREVEkYQBWxABMREREREQUSRiAFTEAExERERERRRIGYEUMwERERERERJGEAVgRAzAREREREVEkYQBWxABMREREREQUSRiAFTEAExERERERRRIGYEURE4BxFD6f74yIiF4zH/6lkF5qiYiIKBwwACuKmAA8NT0zMKg7sB4e2eyHtmMWFhYWllcvtuMTvLrabMfSSy0RERGFAwZgRRETgKcfzg7p9LZju8PpOnE4WVhYWFhevThd7oczcwzARERE4YUBWBEDMAsLCwuLUmEAJiIiCkcMwIoYgF+92E8cITXPLughnilD+vmijYRpeS1jFVKw9NkrsLCwvHRhACYiIgpHDMCKIj4AY9bl9qCE5CjMinq5EhPyOphAEfXPKL7zi7HxiZTklK3tHbfnVFSKRkT7IY2g5tR7Njc3//Xtrxobm85856Kuob6hTF12eGQLXh+L5B6ihFZ+v2W5PmSPL1SCG5H3iILZkEpMOC+HDhPX2enjJ0+am1syMzKRgeX1RZuifblxUVyeU4xMb08vxmpkZBRDHbyy3AKmTebNZcPKsf0kuBGxppjFhLw+CwvLCxXcOwzAREREYYcBWFFkB2BMLy4t5+XkxsXE1tXWjY9P+LOQ2/Nod09bpY26H5WXm9fT04vshFy6vmEqUhXpdMObm1uIo5pKzf7+ATKV3FpwQcsIclNT09iko+PBweGRiFuobG/v6O7u0Wiqou9HYRqNYxHaQUhWq8viYuOwxy6sUKk5v3h8ZDvG5iXFJeibaBZfsf7xsX1wSJeYmJSakjo4MDg7O4dFqJ9fWMzJyY2Oiu5o7ziwHvoPx+VGI52dXTHRMRnpGc1NzdvbO0iPclevWez2k/GJSewuOSm5rbVtdmbW5fEgEK+tb6gKVTgWdal6eFiPbmCs5ucXMKoPZ2ZXVtcK8gtaW9ue8d47eohsPzQ4VFhQODSkw3CIY9mz7CP59/cPoH2cIN2wHquKI1pZMeZk56AnAwOD9fUN2GpxcamyonJycqq4qDgmKrqxoRGH7z3zra6uJSYkfv7pZzgRlZUa7AV79Jx6V4yrWHN0dGx9faO0pLRaW20NnKPgjrGwsDy34K5hACYiIgo7DMCKIjgAn/nOkXyQRRGTkNk2TGbELTzMnZ75SkpKi4tLrNbDnZ1HyEgIkNjq7PxCN6S78/U3I6NjCJCoRHaVnwKfWtyeU0Q1ZF3DilG8A4z2kVERXBHP0KuWllZEL0wgIjY1NiGDoTM7j3azM7O02mrf+QU2wa4XFhYRL/cPrNgc4c1gWEHYQyVWRg1mu3t6LfsHyPBNgeCHNU3mzeTEJKRTHCZSX0Jc/PbOI9QjIprNm6Iz/saf9uZqSMFSrJaflz8xMSnGamlpGRkYA4Wn3qzMrKamZiRYNIsVkPCxvu/icU11zf1v7+HA0b7/o7ef97PNaFavH9FWaf2HGegSNunp6S0pKsb04ydPNJWa9rZ2TGAokHuxCTqD3It8Ozg4hDFESEZPsDvU48BLiktmZmbPzy+GdcMIybu7e6JNsTsMCxq5+82d8fEJjAYO5Llnk4WF5WphACYiIgpHDMCKIjsAqwpViFjnF48RgRCNEL2wdHNza35+AdOIuAiNKUnJy4YVPORhtf7+AYRM96kXKUt+/kPBUuQrJFuLZR/Tcr1IYoiyK6trCHhiTbRWVKhC3Hr8+AkSXU1NLbpXW1vX3t6BPmATJFh0DFthj+gP+ra8bChTlyEeYxrtINdhFi1jZSzGQWERChpBOTqyoQX0BAdyfOJAjH/4cAazSKFIeHm5eZ2dXWgEDWN32GlCfAK6JEfiqwV9wC5ysnOmpx9i0Pxx8diO8cGuV4yrCMNoGWOFrBsTFe2Pry43YioC8IOOB5gIHhDRGqLywuLS995xRWY+vxgbG8dW/sM89WI1dE83pGtqbBINVmur0VtMFBYUjo6OoRvozOraelpaugjAsTGx5WXl6Aw6Njs7V5BfsLFhOju/0A/r6+rq0TFsgDbRVewRu+vt7WtpbsH0M46dhYXl2QW3JwMwERFR2GEAVhThPwLtcA4MDMbHxt3/9l5eXv7SssHlOd3a2kbQysrMir4fFRMdI36sF0WnG46LjkmMT0hJTklLSUW48px6RTtIU0iV7/76naHBIfG2LTLY7p4lNyc3KSERm+ArGkRaQ+7Ny8lFDRLanmW/tFSdkZZuXF1DlltZMaalpt2/d79KU4Vshl2srq5NTU2np6Vjc8TUhLj4irJyNI7AhjiHQIhuo5OY2Hm0i12iTE0/TE1JvXf3W6w/GHibFHmvN/A+amx0DOobGxqRkLGmePv0H/7Tf1aXqjEtDkSp4IAwdM1NzVH37qOHanWZybyJFG0wrDTUN6SnZ6A+KTFpbm5eBHIMIMJwYkJiSlJyYaEKR4p60Q62Qnp//w/vIQOL/eJwjMZVrCnGKjkxqbio+NHuHgI8prMyMrEvlKysbFWhCkfq8Z5NTE7FxcRiF82NTS0trfm5edgFjhHBGKW2tm52bl4+19g1ojhOJXqOls2bW263Z6B/QPQQu8Ap2NzaFj1kYWF5oYIbjAGYiIgo7DAAK3qDPgTr+5+QJCpRnloZXC8vRZALqQxeH0UsDZ7GjDwtL8L/MCnqxYRcsEisKW8bUhm8PqblypCVxSKE8K7OruDNn12u7jG4ZRR5j8GVGFhRKRexVF4ZBdPy+v5NLtsXs/i/WEGul9dHjcPlPvOd41g+vPUBQrheP4IV5DWl9Z/Wc1EjirwmCwvLCxXcUwzAREREYYcBWFHEB+A3uYhgGVIZ1gVn1/5m/L0oFpYbUhiAiYiIwhEDsCIGYBYWFhYWpcIATEREFI4YgBVFWAAWf3NIvPPJwsLCwvKKxeX2MAATERGFHQZgRRETgB8+nO3rH9QNjwzrR/GVhYWFheXVC15R+weG7Ccn0kstERERhQMGYEURE4BxFD4iIvoB4F8K6aWWiIiIwgEDsKKICcBEREREREQEDMCKGICJiIiIiIgiCQOwIgZgIiIiIiKiSMIArOgNCcBOp9N35pNmfjoYaofDIc0EuFyu7e3tfYtFviK9Xi9q9vb2zs7ORM2rQGs729snlx9gg9MNYvrHgd1trK8vLy1J88/01O5hHHZ3dsZGR+dmZ91ut1QbOLSlxUXUH+zvy6OHEZYPNhz5fD7HyfeuENTgenj06FHwfXpit0+Mj2NUsVSqekEY563NzZGREbT80q+Gbpd7empqbm7Oc3oqVb0g7NpkMo0M6y17luBTb9m34Khxd0jzrwDjtru7e3R0JGYDl9iP/eus/ltgefk6J8vfuYvQ7mGUrFYrLvWpyUm73S7VBm6N9fX1Eb0eBxh8eeDlLnhWwL2Df/mkGSIiIop0DMCK8Lh19VEpwhiNxpTk5OAQ6PF4MBucpnBBoFJcFrg+MC3q8Yjp9fqfGrGVCyn68hEWg4anczQix1SsgGlsiwnMIm8joZ0HPfKizXt37iJ1SPMBNdXVQ4ODWCS2AvQB12htdc3s7KyoeTnYO7qHlvF8rKmoQA06X1tTOzY2hkoQxyK6jZXFsWMKs6IGi3CYaCQkh2BNhDQ8ZMt9VoIVsCOE+YODA6nq8uPKsAgtYEil2kD3KsrKR0dGRPfky9Jms+H5HkvRq/TU1J2dHVTiuV9dUoKOoZ/9/f2dDx6Ih3tsWKPVtrW2BTZ9ed7TUwcOPKh76DB2IQYNPcGuxeGjn9hpYBV/xsAiMY1RwuyJ/QQ9FDUgBlYcGprCdSYfJqDNivLy3p4eaT7g0c5OaUnJodUqj3ZzY2NjfQN2ipFJSkg4Pn7hv0+DkS/ML8B9gSN60NGBi1Bu/Pp6u7vrampwjGgtNSXFYrFIC67N4XDkZGVvms3oRltra21QNzAU/X19XZ2dYvblYGz9t7nLtba2Vllega7ipOACqywv919hbrc4mxB6Xk5PMY2vWB/Qz5CrHdOoQX3w6Xu6x4/RMuL9/v6+3ALaxB4xiy7hVpLr0drC/HxRoSrQu++6h6PA8GIWWlta29vaUel0OMvLyra3ttD+/NycqlAlVgZNeUVHW3tI32xHtsz0jNmZGWmeiIiIIhoDsCI8ez3/GS7MfXTrlnFlRZp58mRtdXVudhbPlJMTk5qKSvGOCi4IPG3HREdnZWQM9PePDOs3A0nVarW2NDX/+eM/5efn4+qZGB9HDerHx8a3t/zvrDY3NbW1tKIGI6mprESEO/X4kxhWiIuJkd93giJVUUN9/cXF90a7tqYGbUozl/D429zY9NIBGMeSl5vb0d6OCIfH/Q9vfaDVVKEeSSkrM7O+tm55acmwbEB8QiW6jSRZWlwiLgM8f0fdu4du93R3/+bX71RrtThGw/JyTFT01tYWWu7u6ipWqRAqMA7ZmZloH5W6oaG01NTU5OS0lBSUhLi4nq4uPKyjcZPJNDgwUFJU5O9ZAJ7X79298/WXtxFrl5aWMtLSRGg8PrYjziGir6/53y5DwBDrA5pCpv34w48wgCGXK1pT5Rcg5MspYsWwcu/u3ZfIYzKz2YxEYT8+XjUacVDYBSrRB7PJnJWe8cnHHz9ob18xGCYnJlCPpVWVVV/f/gqREtdVb3cPRgxjsri4iCsN03U1tUh3onsPp6ej70eJq8Js3kxNTsF1gmlhYnwC7UgzlxCAqzQaDLg0/+RJU2PT6MgoJrCX5ubm+bl5UX99uOZx7nBEmMZ5xDW8vrYmFl0fturr7RXTY6NjyO3yKbgm0Q1x9ne2t9Hgzrb/uxuAQ8OlhYtQzL4oXCTNTc1FKpXDcbK0uPj17dtI2qhEszXVNTinG+sbC/ML8vdlxkZHY6OjxTd6TBsbyQmJc7NzyJb/993fYOVDq9W0vpGdmTWs02GF4SFdUUEhrl70X1tVVV9XhwPH3Yo1Uy5vgcT4eLy2+K/Vx49xKeLqxaWL+zGwN//R4Y7D/WU0rlgPDnKysjbW11HvdLo62jtiY2LWVtfQvaPD71490BT2/uXnn+fl5IoRk/nOfNiqrrZWmg/46P1buG2lmUt4TSjIyw9+D5mIiIgiFQOwIjy6hSSKCIOH2g/fvyWeLwHZEmkwLjoGX0uKi7+9cwcPoGIREou2Snv1ypicnGysr5dmAh49epScmJiXk1Oj1d67czc43eGBGE+ueGIuLioKTr/w7TffIChKM5deKAD736UKejtRSdeDB2NjY9JMIFaVl5WJ6caGxodPewuosqJifGwMV0JmeroIxv6t1GqxFDY2NhrrGxCT3vv979NT05ITk1ISk5BXy9VlJ3Z/zE5PRW1KekoqSmJcfE9Xt8hXsLOzoyosFNNCaXGxSFz2Y3tDXR3Cj6ivrqqanpoS01fh1Gg1GvktLLSPLmnKK+UdCUiM6NjUxKQ0fwlHd507H6u1trTExcRWlJXn5+Z+8P77IhcJVRr/+ZVmLg309+F8STMByBgFeXkZaek12uq739wpVhXJJw79x0XiOz9vaW7WD+tFJaBjSIBZmZnS/KWrAbihrh4ZDBPYBO0vB+UcDMV1jhHZPj0tXdz4CHKNDQ3i2z2C9/Ral1l9Xb14sxqvIYMDA0ODg3IARsu4hq/TDQyR6Ib/AmtokL9tgW2fGoD9JzHoxyWU4OyLb/oIyLRVlRp34Cc+cIHhMhP1wXAb1lRXX5yf11ZXi29tIGemJCXJZ39paQk9xN3xzVdfffnZ57jOcQvglSQ/N8/hcODVIz0lJTUpWdwCSfEJmkqNODRYXV1tb2kJfq8e9xduRjFdWlIsf4du1WhENhbTV+HAEWLRDTGLURobGc3LzT258mP/6CFSvTRzaWZmJiEuDsFemiciIqLIxQCsKOIDMMTHxuoDb90AHn+LCgvxUIuHb7Va/fFHf1wLJDEkh6GBAeQ08fuWuERQicHB8253d7e6VL23u4tLRzx5a/xxcRyNrK+t40ETT73B78kU5OffvXMHjUjzl4Z1OsRLBANpPgABWDxtB0P8aGlqDgnAWO2v/sW/DH6sV3J+cYEchUCCx2I88iLCoUsiJaIPeHq2Wq2Hh0c4BLPJJDbBcZUUF//pj3+U3xNbXFj45OOPc7Oz+/v6NBWVmRkZdvsxVhvo97+di5Zx+AsLC12dnVcfvmVOpxORZmpyKjU5BTFYRGuMVWZaOvI2WsPuVAWF8m8Io28dbe1oEFsNDQ4hMGAvnR0PRob1qERmTklO3n20izWxedT9+2urq/v7++gq0oscVCYnJm9//oU4UzJs/l//yz98+sknIfVXYUw0lZXYFxqsr6391dtvm81m1KPb+5b9okJVX28fui2/QY2ThRxeUVaGUUW3xd00NzdXXFSEFg729+9/+21MVPTR4aFYHx0YGxn50x8/7uvrEzUyHM6fP/5TyP2IAIzAjNQnzeManp4uU6u3trampqYQs0WuA6Ssv//b/5gYn/DcY8Quuru6cO3Z7SflZeVtrf4fYRAa6uv/+mf/BsMrzSszm8y4ZhALjUZjakqK/MvtGId//t//5y+ffPLcFI1rsq2lFXu3HR2Vlao7H3z3A884AOS3kACMV+3/+Y//9OH7t8Tt+Qw4wPq6Oly3OO84oV/fvo0XAewFi+ZmZ3ESj2w2LBrVj2ysb4hN0DhumY8++GBEPyJq0Mhnf/n0zldfoxs11TVpqaniSsCNU1JULH5FGcfu73/gwn4q3O/7Fgvuu4rycozVodV/GWBf2AonEROQk5klbgcsMhgMGWnp6Jvdbh/s7xffG8JdJm7nTfNmkapIfMtsxbCSEBePDXEz4xYY6O+XvxOEV6qvvvzyatDNzcmpq6l57uVBREREEYABWBEehkIeuCOP99SbnJC4e5lIcbziV1hxEYh3zFCJCQQJPK3ioRbEmGBwUCPXY0352RE1eOLHV9SgXnzClvf0FA+pxSrVwvzTfyq1taUFwSP4AbSluRlJaWpyUk4LSH3trW35uXl4FBY1gH3FRkcjb0jz14DIhK3E0fl7ePlwjCCHehChHZ3B+ODocrKyZmekyI1K/fAwMgnWwbYhdwtmxS9A4vClKgXY3O1yYQDRCHaB8UGlf8w9HtRgL2gKjQQnJUyjZbQvdxiwsiPwy5zSfKAPok1BXnlvby89NfXqr8XWVtd8+dnnwW0+w8X5uThArC96iEpcEuJKwNfgPaLD8hWCr/LJ9Y9z4NsEqMG0OEZ8Rc1AX7+mUiNWC4ErITc7W5oJ2NvdjY2OQQTCXqSqQGfQw+AayM7MRFqTO/BcYqhDxvk377wzPDwszT8P9oXDAWk+ALnu00/+LK6u67jaDRgZ1ufn5oZ8j0BbVXXvzl37tX/nWZwCMUrYi9wl/ytAAI5X1Ijz8qDjQW1NjagBrJCWkmI9sGI18YIgEweOFXApPHvAsSHWFFcIVhbXEi4q1GCnmABMYBdyO3L3gsdQjBKaklcTG6IdVAKmRT1kpKZd/TkFROjqKm3INUNERESRigFYER6nQp7t6OVgJHd2dlYMKwiuu7v+dymvCXEr+BSgHYQB+TFXwOwPdMliX+g2+gz7FulzelBpNpmXl5c3NzflkBDWftobXrZvsRiNxqXFRYz59e87dB4rh1wSVz13het49YFCC6/ek8A9ETo+V2teC/TWIs7L0tLuo115BHa2d1Czvr6OeClqiIiIiMIFA7AiPPz9QI+VRERERERE9ONjAFbEAExERERERBRJGIAVMQATERERERFFEgZgRQzAREREREREkYQBWBEDMBERERERUSRhAFbEAExERERERBRJGIAViQCMr9I8ERERERERhTMGYEWIvhiLn3Y4iIiIiIiI6LWw2WylpaX19fVDQ0NGo5EBOBTG4uzsTJohIiIiIiKisKXT6dRqdVNTk16vX1tbQx72er0MwN8RAZgZmIiIiIiIKKxZLBaVSqXRaDo6Oqampra2tk5OTpD1ftpfer1ZAVj8GrA7QKoiIiIiIiKisGIymQoKCsrKyhobG3U63crKitVq9Xg8FxcXDMDfg+Hw+XwOh2N/f58fCk1ERERERBRempubVSpVeXk50u/Q0NDS0pLFYnG5XAh6P236hRsXgEFkYKfTiWEymUynp6fSAiIiIiIiIrqRvF4vom9BQUFpaalWq+3o6BgbGzMajQcHBzck/cJNDMCAoTk/P/d4PDabbWtra35+/uHDhxg4aTERERERERHdAFartaWlBbm3qKiorKyspqYG0Vev1y8uLu7s7Njt9tPT05vz925vaAAWLi4ufD6fiMEYO4PBMDk52d/f397eXl9fr9VqKyoqMMSlpaUlJSXFRERERERE9KNABEMQQxyrrKysrq5ubGxE7h0cHJyenjYajbu7u4i+iHI35I1f2Y0OwIJ4N9jr9TqdzqOjIwzlxsbG8vLyzMzMxMSEXq/X6XQYaARjIiIiIiIi+qENDAwggiGIjY6OTk5Ozs3NGQwGs9lssVhsNpvL5UJ8uznv+gYLgwAsw/CJ94Qxmm632+Fw2O12jO/h4aHVaj0gIiIiIiKiHx7yFyCIIY4hlDmdTo/Hg5iGsPaTf87zs4VTAA6GMRV5mIiIiIiIiH4qIpqBFNVutnANwEREREREREQvhAGYiIiIiIiI3ggMwERERERERPRGYAAmIiIiIiKiNwIDMBEREREREb0RGICJiIiIiIjojcAATERERERERG8EBmAiIiIiIiJ6IzAAExERERER0RuBAZiIiIiIiIjeCAzARERERERE9EZgACYiIiIiIqI3wJMn/x8Z1Ozq5tSEmwAAAABJRU5ErkJggg==" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![s0%20%288%29.PNG](attachment:s0%20%288%29.PNG)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 예제 13-2-1-1 희소행렬 알아보기\n" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy import sparse as sp" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "csr = sp.csr_matrix((3, 4), dtype=np.int8)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<3x4 sparse matrix of type ''\n", + "\twith 0 stored elements in Compressed Sparse Row format>" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((3, 4), 2)" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr.shape, csr.ndim" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr.nnz" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([], dtype=int32), array([0, 0, 0, 0], dtype=int32))" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr.indices, csr.indptr" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0, 0],\n", + " [0, 0, 0, 0],\n", + " [0, 0, 0, 0]], dtype=int8)" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr.toarray()" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[0, 0, 0, 0],\n", + " [0, 0, 0, 0],\n", + " [0, 0, 0, 0]], dtype=int8)" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr.todense()" + ] + }, + { + "attachments": { + "s0%20%289%29.PNG": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![s0%20%289%29.PNG](attachment:s0%20%289%29.PNG)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 실제 데이터와 데이터의 위치를 지정" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "row = np.array([0, 0, 1, 2, 2, 2])\n", + "col = np.array([0, 2, 2, 0, 1, 2])\n", + "data = np.array([1, 2, 3, 4, 5, 6])" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "csr_ = sp. csr_matrix((data, (row, col)), shape=(3, 3))" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<3x3 sparse matrix of type ''\n", + "\twith 6 stored elements in Compressed Sparse Row format>" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr_" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6], dtype=int32)" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr_.data" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "6" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr_.nnz" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([0, 2, 2, 0, 1, 2], dtype=int32), array([0, 2, 3, 6], dtype=int32))" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr_.indices, csr_.indptr" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [], + "source": [ + "csr_1 = csr_.toarray()" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 0, 2],\n", + " [0, 0, 3],\n", + " [4, 5, 6]], dtype=int32)" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "csr_1" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [], + "source": [ + "G = nx.from_scipy_sparse_matrix(csr_, create_using=nx.Graph())" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nx.draw(G, with_labels=True, node_size=800,node_color='#00b4d9')" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.array([[1,0,0,0],[0,3,0,0] ,[0,1,1,0], [1,0,0,1]])" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 0, 0, 0],\n", + " [0, 3, 0, 0],\n", + " [0, 1, 1, 0],\n", + " [1, 0, 0, 1]])" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [], + "source": [ + "a = sp.csr_matrix(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<4x4 sparse matrix of type ''\n", + "\twith 6 stored elements in Compressed Sparse Row format>" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " (0, 0)\t1\n", + " (0, 1)\t3\n", + " (0, 1)\t1\n", + " (0, 2)\t1\n", + " (0, 0)\t1\n", + " (0, 3)\t1\n" + ] + } + ], + "source": [ + "for i in a :\n", + " print(i)" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 0, 0, 0],\n", + " [0, 3, 0, 0],\n", + " [0, 1, 1, 0],\n", + " [1, 0, 0, 1]], dtype=int32)" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a.toarray()" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [], + "source": [ + "Ga = nx.from_scipy_sparse_matrix(a, create_using=nx.Graph())" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nx.draw(Ga, with_labels=True, node_size=800,node_color='#00b4d9')" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [], + "source": [ + "GA = nx.from_scipy_sparse_matrix(a, parallel_edges=True,create_using=nx.MultiDiGraph())" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nx.draw(GA, with_labels=True, node_size=800,node_color='#00b4d9')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# csc" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [], + "source": [ + "b = sp.csc_matrix(x)" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<4x4 sparse matrix of type ''\n", + "\twith 6 stored elements in Compressed Sparse Column format>" + ] + }, + "execution_count": 86, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " (0, 0)\t1\n", + " (0, 1)\t3\n", + " (0, 1)\t1\n", + " (0, 2)\t1\n", + " (0, 0)\t1\n", + " (0, 3)\t1\n" + ] + } + ], + "source": [ + "for i in b :\n", + " print(i)" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[1, 0, 0, 0],\n", + " [0, 3, 0, 0],\n", + " [0, 1, 1, 0],\n", + " [1, 0, 0, 1]], dtype=int32)" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b.todense()" + ] + }, + { + "attachments": { + "s0%20%2810%29.PNG": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![s0%20%2810%29.PNG](attachment:s0%20%2810%29.PNG)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# lil" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [], + "source": [ + "c = sp.lil_matrix((4,4))" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<4x4 sparse matrix of type ''\n", + "\twith 0 stored elements in List of Lists format>" + ] + }, + "execution_count": 90, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([list([]), list([]), list([]), list([])], dtype=object)" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c.data\n" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [], + "source": [ + "c[0,0] = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [], + "source": [ + "c[1,1] = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [], + "source": [ + "c[2,2] = c[2,1] = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [], + "source": [ + "c[3,3] = c[3,0] = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[1., 0., 0., 0.],\n", + " [0., 1., 0., 0.],\n", + " [0., 1., 1., 0.],\n", + " [1., 0., 0., 1.]])" + ] + }, + "execution_count": 96, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c.todense()" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [], + "source": [ + "Gc = nx.from_scipy_sparse_matrix(c, create_using=nx.Graph())" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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j6pWrz1dWPjvz2djY2IMHAQkJiThalpWVnzh2XDYXl5hYA4/Ba0+ydPt920ysgQFdsa0zsbxVvPMkywPRrbnufCoiPEJNbsbE8lbZbAWnpqTqFrCdJlbCjMSEhOAnT0RiZeXB/bXPB42MjIyPj+fl5lKysbERw5rqGvrqd0N9vZa9EvTwIY7qcgc1NliKOY1uzbfOxPJW8dEInpmZqaqsFAmN4qJi4WkY3wBoyqB9330HujXfOhPLW2WzFVxUXOpGEyvhOP19fbqPwPb2WH6WLpm175rURx988PFHu0XCI9lsBXsNBfmW3zpI5I+piEsXLwpPo6mxcWhwCM6F8xcoxx7qVw/+trH2S6QDe/cJzxE2W8FXL18W3spKWEhIUGDgxMQEVnFkeER+lvlZ+bPkpKQeLUTiYmKiIiMpPyY6uq21FQ6V7OrqSoiPv3f3XlJiIpJpqWnYj2mpqcmJSUj29vRiyDiKT0ewjY8QDw1ZAlTy/Ll4bQGdiLW2ts7NzSHz/NlzU1POnwoQebn6qxOS61evCs9ZXFzB3d3dcXFx5KenpdXX1ZF/8fz53t7eC+fPw6+tqTly6BCcU8ctX0Vpa22zlFhZyc3OefgggPyGhgb1IFmo/VZsM7+i1IHNjggPFwmNsJB1H3HMzMgQnoa1j8TjAEMn4R6Lj0YwTrKEtzn8bt2urFh3Nu4EqSkpwtsCfPoQ7VFIFXAIG9drCa5gj6akuER46HMrmmVnNx1wBXsKNs74rFFUWNjd1SUSVuAKdj82OrjqcbtVeQ8EXV0ZHxvf8MDumgrOyy/YfhPL9hmKi4uTEhOp/zYxbnkLpD24poLpKujQ8Ih6n25qeqa3r18myYzPrDhtYtmMTVxTwUFBj4ZHRkNDQhsaGmtr6/7nN745O79w987dOu1RHph82KO5pZWczZtYNmMTV0bwNptYtoG8PP3BfJutrLxCrIoH4IUnWTOzc7qmYGpb99RHvuGDwW7ENRWMU/ztRyzbAD381tjQ2NHZFRUVnZubh+Hc/MLS8vO6unqoxuNHj1ENly5c3KI69sIKpg3DWZXcSLLpmdkNc5w2sWwDdkbw1pkXVvDRw0dQdzjJwhB12NrWju3EjpYnWeHhEVT9s3PzlLN5E8tmbOKFJ1mADuDz8/NVlVVwUlNSFhcXW5qbS4qLn5U/04pY5Wm6+KSUPWRlZArPU/HCkywwN2d5AH1paam4SBwtp6amni8vw1Fv/OkuA9F7JWlaI5ib8DToDqaxsHP3DLYO76xge0hLTcXwof8Dv1u34URHRWvZ5tg4p/NwvPMQbQ+dnZ0YpqelxWhVi+P5x7v3wOnqNLl8j7Fz8+uCtarKcvA3cv6zs8LzDFxTwdU1tfIkC+fJdB47q5xkJSenYBScz06fwRAnXBUVlTSKTrt6Vy9hyp990kmZDRPLdpbm5ubl5WXLYbzQchhXD7ZVlZWUnJyctH27ZnR0VHieiu9GcHBwMIbl5eWZGRkQzoT4+F+99hpyGurrM59aGBsbi4qMRL5WfOX40aPkECPajpPPGHksPqTB8uGHDZ+C2BDdCZcn41snWbk5ORjOzooTad2jk5curHv4WQU1iuM5BBsH7ZTkZOQgiWHG06faeM/Fdw/RPoJrKnh4ZBQnRTjJwn6XdwYTEhLlSVZSYhKdZNFFLpxA1dTU0qjCwqKFxSV5koWS5Gz1Sdbw+vC1TU1NjfB2Gq6MYHmdmeoSZu2ysCywGRPLZmzimgrW7u5sN2LZjE186yTLB+EK9nK4gr0crmAvx/jjR5MKXlxc7NroCXrG08jPz6cv+OngCPZyuIK9HK5gL4creDsIqz4ZVn1ivSHHmCntpJhyZWWy4bDF6rWhEyYnhOP0TBoOzzQdpvX5qKBIs+JVx5ptWECzwmKLkZNf9FFRye6S8vRux97QMngjduB6jMVuaEaOTKqZmo2HZIkpXcHxuHbdN5u3zQYm5jmAtwOKSV2IruaYh7GYUgaw0WwHpLVRG8awldlO6wPYYBSHNkwtYKMwRq0rWVI3ssFzNIPXtQAW8RkrA9ViujDWjAOYcQxdcBpMBvOaiSnVAFbjinxjpJnFnrkZ52bTTALYEmZkqzl6M4wSk5iNspguc11yd2k5rYAREcDSKFDX5axGtZbkAGYYZsvRhavROIAZxnPRhavROIAZxnPRhavROIAZxnOx52fJHMAM46EkJibOz8+LhBWcCeDv7Mo2mhiHOWqQ/9JLL5HDMIyj+Pv7Gx+P1bFVAQzgI4APHDhAvszE8Ny5c2qytbVVTcbHx8skHwIYn8VtAYzhr//6r8OxFsC6iNUlr127ppZnGN/k1XdP7X1YpLtwdSO9Q4zW8JQI0YUribBIMMzO5P24Fx9UnVgs+cpA+u9guNIb8EX/wC8+DsVwZuV54/f3U7Gv7sv+vQMZf3oq72Huup8RWQngdZ/e5CBhmK3ivbgX75e+DwcBTDm/4R/4/cSUu82Wr6w0rAVwzntB1eSruCyA//LAjrF0hvEWzAP4KSsww+wEdlIfmGEYHX/33tl9j8uPxbWpdiWFFZhhdgJbdRvJNt8JaGBzoc0vedZnPphtY7sDmBpczeCsSGsMzyzKtqizc/n9uhxpNkb5pom9yfgS2xrAsp29mdAhG5zMJAdWOzRLztLz53OLz2W+sTzlAPhpbROvPGmCg8kph0zODTIl5yanko4XGG0L41O4J4CPZvfKBiczydGZGsAIUenDaHJCzYepU8G6JxbIkfkyxzjtzjXaFYxPYXoVWmeuP4W+Wjwo0hppresik805E3uT8SW2O4AJXctj26SJ3cr4Hu4JYIZhXAIHMMPsYHZ8APv5+ZHz5S9/GcOBgQFKyh8qqb9Ykv6BAwfIsfF7JjnqxRdfJGfXrl2vvPIK8tWpkEmOzMzKWnsjaVBQkPCsoPtCsTpn1f/CF76A5Oc+9zn4WAfKBFTmxIm1V8zKTdNh53rSrKiMLEkrSXv485//vMwnXn75ZQxlRdCssMKUxNq2tFiey9eh2woCvpyQcmiTZbWqyDnIResWJJO6fNoVtDhguskEJdXdK6GFYm9QUk4oHblWwHQPuARPD2Dsjg1jQMVY03KHUjujPa4GsIRybCDbloRigPLtmYOujHESNcfaDKnhYqwOGisSGpQD7F9PRClNC0SWUwEMaCYE5aCkSGtQpg5aSQxFIa0BULXSKHnIo/1Am0broIuTgoICmkTm644a5JhuskgriBF2sz0B7J4nsVyL2izsjEzTYqaHeSAVWG1VlKOiZlIZINJOoU4+OztLMwRqKwRyWwhRSENkrUfNp2JApNe3ZtNDpzGAddgIYBuIchqUo66JbpMJY6a1ODHNx2zJsb3Jut0L6GCByMEBApNQJk1OUI4KB7BVcJyjvYYdrR7zGMYX8IYAFt5qMIsEw/gA3qPAgBWY8TW8oQ/MMD4LBzDD7GA4gBlmB8MBzDA7GA5ghtnBcAAzzA6GA5hhdjAcwAyzg+EAZpgdDAcww+xgOIAZZgfDAbxjKH9WMTk1PTE55ag5N5XnmNh++8jOyfM+E9tmhpsDeGx8YnRs3DetrLxC7AX7oABubWt/mv60s6tb18qlhQSH5OflWwva2tq63Ny8/v4BXb4nm9h++9BN6x0mts0MNwcw2tnU9IxudWHIlE2wIL8Aw/r6hv1791GOHAWHbHZunnIaG5s6O7uCnwQvLC4h+ejR48WlZYyNjYmlAp5j5c8qxV6wj66u7samZh80sf32gR377tvvqPvZaMMjo48fPyH/xLHjpaVlBw98KsfCxicmyamsrJKZ0mKiY8j5y+/9uczcUhPbZob7Axh7cGZ2TrfGJ46fiImJxX78+U9++jDgIRRj756P932yF6E4O7/wwP/Bndt+1dU1hz49+MF773d0doWEhPb1D2Bu4+MTkRGR0dExc/MLg0PDERGRmGR6ZvbJaoV5jjkawIw96Hayd5jYNjPcHMCktL5pjgYwnULj3FtXu5OGUxgpILYNh0IMMU810wNNbD9jBl/E2jFQAKP3W1ZWTiEaHRWNIQ6CoaFhGJWYkDg1MwsnNye3qbklP7+gtbWtqLAIhXEKU1RU3NzSis7GkyfBFLT79u3HuU9WVjbFicea2H7GDDcHcFFxqc9aQWGR2Av2gZ5bd0+vD5rYfvvQBb93mNg2M9zfB9atq+/YFvWBb16/IbxVGuot316Jj43DcNpymWAczr5P9lrGmbG8vPysrEwkzAh4ENDR3iESBsJCQi9duCgSBmZmZvJz190XuX71qvBcAXbsJ3s+VvezNMr/6IMPsf6wj3fv+ez0GeTseufdf/zh3yMH/vf/8q8wPHf2HIaeY2LbzHB/AM8oF5x9yrbtItbCwgKGY2NjGD5//nxpaUnLdhnT07Za2EB/v/CsMDtr+RxsV1cXJTeJbid7h4ltM4MV2G22/VehW5ott2QSExIoaY0njx4nJyaJhBlRERHCM3DtypXZuXVfb1ehFejp7qEkOH/2nPAYp+CLWIxPc+bUKQw7OzopacpA/8Abv/yVSKyHzmuMtLW1vfPWWyKxnqmpNUWtrakRnrO4P4AfBQWFh4bCqa2pLVvteiUlJnZr51RYOew+nPgtLi5mPH2KnImJidyc3LTU1N6envn5+cHBwdaWFhSorLA82AQHXbi0lFTLXFZW2tva0OnC3kRmXk4uZYLq6mrkTE9PNzc11dXVIae/vz8uJpbGlpWWNTY09vf1dXV3Nzc3t7e3I1NW1dDgYGpKKp34tXd0+N26RR/7iAwP18avLMzPP7h3n3yPAhuLIU6hY6Ki4NTW1mrZK6EhIeQQTU1N2DlwGhosnecf/uAHWrYgJDi4rLQUzt/97d9i+KN//XctW1BTU3Nf2/af/finGGI+c7Nz2hjB0/R0DEdGRua0HUi95ZjoaFScZbQrmJubmxgfz8rMrK+vR7K4uLijo6O+rg4toa62FoumrSN0ASxX49qVdT1zmoQ6IypxsZY2gxaI4X/7v/+zliegWanLIqK1nY/1oST48z/7rvAcx3MV+LEjn0SywYVz5wMDAkTCKa5fu4Yh2gQldy44g8VxBwowMTkpsgwgvKemp2ZnZkTaQEx0jC7gVXCUNDZZyejIiKo/4NN9+4XnbhD2wjNAQW6EDhCmXLl0WXjrqaqsEp7Nye3H00+h6TAGPYTAwqckVBcSqo23gBZDjQZDaDKc3l7LvQd5tQaZNKHK/JylJMCBmRyQm5NTsarkUpDlcRdKi2M5+bQgMD42ZlnQ87WDN4CPfJHwYahedgS3btzEmZpIrOe9d97F8D//p9/C8N233tbyLLz+2i+FZ9hS0gyaRD1IWTsVd5od0Ae2aIJ22EZUqMEG6Kg5OTGBAigG4CPM5rV8nCFjt0JzcNaNIQpPTk5S4Fn8iQnLLDD55CSdD4OpVR8F6MR4cWEBBbSRlpIAqwHk5JgEoDCWhamwhnCQQ2M9CrqGlJxk6wIVbX5W5tqXR43YuIh15dIlXR2p0Dl8T4/JRSya6tyZzyjJ2AlfxGIYC7s/+PDggU9FYj3jY5be0+2btzD8xh/8oZZnF/fu3MHwW9/4JiVBa2vr0NCQSLgCDmCG2cFwADOMwNrFKhsEBQYKbz2DVr41DegqtKvgAGaYHQwHMMNYyM3J3b/X6vPh1rih3WJ0iAD/B8JzBR4UwLonDb3YxAYzzKbxrABOSko+e+Yzej9OaEgohllZ2VPTM363blPThy0sLi0/XwkJDoFfV9+gPk3d0NCYmJAYGxMrf+M+PjHpgT95FRvMMJvGcxV4YHCIglOGqHzRhMzp6e0jZ2eZ2GCG2TQeFMC637t7sYkNdgTja8N8zfILHHv/gY/AF7F2BgjgiPCI0tKyGO31mtMzs2Vl5fX1DcFPgnEaUl1Tiyw6HxkeHklISDx14mRf/8D09ExJaVlgwMPevv7IyKiIiMiR0bG6unr0U+itnTvIOIBN4YtYbjCxwY6AAEaIFpeUInThYCYYIpCPHz1GPg2lg2IYa8lZLY/kLu19qx2dXWPjE4NDw/B3kHEAm+JZATw0PNLW3kFdXLqIhaZ27+49yiGDHxsTS42yobFJHYXCUJiRkVGZg24zpIZUy3NMbLAj5OYV5OTm+7IVFpWIfcEoeFYAWxRj9Q07F86dn9dO80hMEIo496MAsKiQ9mbWPR/tNr5UVTWU0V7DuhbknmBigxlm03hQAKufHfFuExvsIAEPAlKSU7TfPlnIyc65d+dOTfXaKx26u7vJyUi3vPlgeno6KTGxq9PyU/XR0VFtzBr0o3w7yctdexfChtB7F+wkJytbeIxT8EUshtnBeFAA40TXR0xssIugN/5Abym5IdVVVelpaeSnJCXfue2HaeWPeIuLii5fvBQeFkZJt1PxzLFPwPkantgHpo7io6BHaOsVFZXDwyPNLa2UCZtbWKxvaLx39x78wqJilJGj4KtzkJnkhIWGjY6OLSwuVVfXnFde/IsCt2/dpmLoL/f19ctRMN0M5+YXLl64qFuEoyY2mGE2jWcFcEdnV1t7B93hoAAeGBzq7OrGcGZ2zv++P/IRY13dPTD4JSWlMj5NbWx8AmXoY5zBwSFIwrq7e5CDCb/9rf9JkyPZ2dkFB8lem093oQBK0tKdNrHBLsJRBVYZGhqampq6ef06/NycHMpEv/Tg/gPkE/QOjZKSksrKSkg0/KWlpfy8PCQvnDune5tMeqqQd3vIyswUHuMUfArtBhMb7CKeG173tf04tA5bV9gH4YtYO55O7TqzlMHCgoIhnLBofdrysnLKTEpMpBf9bTVQZno1XH1dHdQ1Ozvb8oqy+fm01NTBwUH5JkAJK/Am8aAAzs0r8BETG+wi1DcM26bdylsXTRkdGRGeHSBuhWcH/Rt9bEVlZGTEoZn7Gp7VB1bt3p2784tLU9Mzx44cRcdV5uMU9PSp0/XaDwk/3bcfQznKtpWXPysrf4YZfnb6TPmzCnVUZkZmlPapzqSk5FHtyQ9rhsXFRMd41EWsxsZGDHtWbwLbQ5M2iZ3Qe3btpCA/X3h2QC95ZzaDZwXwiaPHTp04man9fDcsNAzDmtq6R0GPenp6Z2bn/vqvXkbO3PzCrRs3I8Ij4Dc2NasBDB+hpUZXcXHJ/Xv3D356EKOePAmenpmdX1i8cukyXcT+wSt/Q7/yuXzx0vlz5+EsLT/XXcTSzXB2bn7/3n0Xz1+w/8BhNLHBLuKR9lom49mpDei1u3ZC7+61kw0Lq3KKwra7uNwB3hDPVWAvNrHBDLNp+CIWw+xgOIAZZgfDAcwwOxiXBTBf62eY7efBgweuCeDnz59vz6MCDMMQfn5+ZWVlukdZjThwCo15jY6ONjc319XV1TIMszU0NjYODg7SBzQ3hPvADLOD4QBmmB0MBzDD7GA4gLeDsOoTYdUntSGZ9I2OxSIbTtKEzzuPTjYc3j6rN+Ss2sJoIdZnd+mzjwqKPyooWrPC4o8KlaQdtrugaF9xybmKypj2jorhkdE5Bx4UNTJVXD9wPcZiN5QhOTLnRqwyjBFTuoijUQ3usZhmLJ0DeDtYDVGKUl3QqqEr/O0LYOsRqzMlgJVotETv+ni2bWphOa3MLCzeXV5xqKRscmGBNt8eRACvC1clhtUAXs0RU7oIfVxtlx3jAN42lBAlQ6CqYayPYbcpsNFWI1wfwGuxtz4Iha3FpJIp83WZ5rbbvpdFWwLYEqJqxMauxq2WJKOkliOmdBG6uNo24wDePnTxaearyZMeFMCrZqLA+uC0bjLObZic2/rZ7i7d4AeP6xRYtesIY0V41/L5FJpxELMo1dm6/J0RwKoZww/O+lC0ZVTYevkx679knCpuECEqlHbd2bIWxjJ0NZ8DmHGU1ci0Fr1kGEvmpgC22R92IICFbz16bVz0Msbwak56t/mzgOsuYsmTZ3UoHBplCW8xpYvQx9W2GQcww3gs+nA1Ggcww3gsfeNz+ojVGQcww3gy+ojVGQcww3gy+ojVGQcww3gy+ojVGQcww3gy+ojVGQcww3gyCFEbdizO8ip/DmCG2cFwADOMh2LPC/05gBnGQ6GPy9rG4QD+2t+e+86ubKOJ0QzDuIiCggJXvtSOsB3Ad+/efeEFMc8f/ehH5DAM4wRZWVnuCWCKYQpgmZRD8Ou//utqkpzZ2VkMW1tbtTxLJsAMyWEYX8M9ARwUFITw+/rXv24jgMk5d+6cmkxPT9clX3vtNfgM45u4J4AxpDjcMIBVsZVD1QHwGYaxxsYRovuOqz0BDGT4kUPqqsvXBbCqwN/73vfIYRif5ecngo5E1ukewBLjVtk4SJwL4GvXrlEEaiEpHF1SF8AHDhzAEGfgSFIOOQzjm2xJAG8RxnAtKysTHsPsTN6Pe3Gl+Wtj2f+9P+13Fku+8puhkV8MePSbwRFfDA4f/rsT3YcDUGZydukrH6f/6ak8GE0l2UkBrAPiLDyG2bFYAnhlZaLmo6XSr8BBAP9HZvZfJqYgjHUB/LVDxf/fyVrLNAo7OIAZxgswBvDXQiO+n5QKf/jVE73HLb3FyfnnCGA4RswCuF6MW4UDmGG2CmMAHyot18ZYArjh+/sbv79/qKEHAUxGoyQuC+C/PLCyUyydYbwFPoVmmB0MBzDD7GA4gBlmB8MBzDA7mJ+fDj4a03Istu1YXJscinGrcAAzjIfimh8zcAAzjFvgAGaYHYwbAjioavg7AQ1sLjSxZxnfY7sDWG12958NqUm2zZjYv4yPsa0BXN43Y9raZCs02rn8fl0O2Y+j2l550qTL9GXrm1oQe5PxJbY1gKmpwSnsnpIt70BGjxxFppW1AH/p+XM1X/XBL+Par5cMGvONU+nyKRPWO7lAjhcYbSPjU7gngDGcnBdLpZwfhrbQWFmAhmrItY7N703vpuT80vO0tokPU7qQTyVpSI5pAGNI+d8LbETyn8ItS5RTeYFhWxhfw20BTDmAfLU/LDMxpJAjH3Yip1eOBUYFJns7sUP6c4tr60ZzG5hepHzEMCsws6MxfRJLZ1sSwB3j4pMQMsfUjFpKRipKSFmWpk7VPDInfcpXcziAmR2NewK4SQkhaK8cRaaVFUgFVqEceRGLcqColNSZMd9ayZ1u2r5hfIttDWB0XE2bmmyCbE7b8Myi2JuML7GtAQz+JaJVtrn3krukz7ZJE/uX8TG2O4CBev7Mtnn7i6C1ywGMr+GGAGYYxlVwADPMDoYDmGF2MBzADLOD2fEB/IUvfEEOv/zlL2t5FgoKCoSngQIvaHz+85/38/MTuQrG77YQLS0twlPKqIUPHDggvFUwdnp6enFxUS0mF6rOhFAzTaFiRFZWlsjV2LVrl/AM6FbMnvXUlmABewlDygTw6atUs7OzIkuBdjUVkOvzyiuvYIgc8OKLllcfyyRBOSqf+9znMMQqYSgKaajVSluBTHU/yE2TCyJkkhxMQjOU39YClAN0m0wYdy9m0traumfPHvi6vaGbXN3huhVzITs+gOVuQsWrNY36EJ4B0wDW8fLLL1MTVAP4m9/8JoZada/tE7WeCLlodX0kumqmwrpMI9oyLWXUhkvNSJ3WxqbZs540q2vXrpEv50wlsYftD2CC1tbYfNWtALQsNYBlsME37kbkq3OgmgK2A1iiC2AMjZsMjLsXyCS2V+6NqKgoWnnoRHBwMGWqO9xHAxjBo9t9RqgAlZSFqcF99atfpSSBxk37FI4saQqilxwUkwFMk6hDoJMvanyyXgcGBsihMpQvywNMjiFy1EwJMmmGqqzpmr6d2Lmeb775pmVVtJI0JNQAVvMJNYDl2Jdeegk+NVzZfNXIMUKTmwYwOQgSbAh9HV7dDzQW6OKE8jGkfDlPdTWsbbINZHm5A03hALYrgFVMFU+CaiOBUmWKKoMQWdahtgVkYWrZutN1I7I85qAuSLYke5ZOyIaLSXQgk45NhNqA7FxPICbWEFmrk1MAU46KNQWmmQDZfEVag3KM0E4WhTRktdIorAwy1f1AmRiqcUL5dBCXAWwZYcCyjFVE1vpMQoywG+wQ4W1lAGOjtvWNHFuBsV1KCZV8+9vfJuf11193KIDVU2hRTgNJ2SBISCWytnStOTw8nBzKUTHNVKEGCnStUN0WYBrAjq6nRGQp2NYcTGI7gK2hTiWR5wWSjo4OzA0OhrRRau0AuSDTLcUk2upYoHxCZGmIrFV0u5fATqBDCZ02A3W3m55lbLgHnAYbteMDWOw5DcpBAIv0eiEiXBXA1qCzR6A7hydMpzXNVNHmJxBZGjYCWMa8NUzXk3IIkaXgXAADkWUFTCXKvfCC7NCKtAblSJCjO5AR1uLEdvzQIgiRtYppAGMN5aGkqqoKQw5ghmGcYccHsDjuaYdDo9gyjHez4wNYDVoOYMbX8KoAhg5v2PFjGG+CFZhhdjDe0wcuKCjgAGZ8jR0fwCoUwMabwAzjrXhVADOMr8EBzDA7GA5ghtnBcAAzzA6GA5hhdjAcwAyzg+EAZpgdDAcww+xgOIAZZgfDAcwwOxgOYIbZwXAAM8wOhgOYYXYwHMAMs4PhAGaYHQwHMMPsYDiAGWYHwwHMMDsYDmCG2cFwADPMDoYDmGF2MBzAO4aGxubpmVlfM7HxjBU4gHcM9Q1NE5NTaNMY2m+YQJezs0xsvH1k5+R5pYnNM4MDeMdAAfzu2++UlpbNzS9Q+46NiX0Y8LCmppaS4xOTJSWlGFISdujApzLmEf6FBYXxcfFyrOeb2Hj70E3rNSY2zwx3BnBWdu7o2LjPmtgLdkMBnJaWHhQYZE1XR8bGIyMiS8vKdflkCOB7d+8lJibB0Y3yWBMbbx+6ab3GxOaZ4eYA1q2oT5nYC3ZDAexrJjbePmiSjz74UE6OcxN5evL6a7/cv3ffm6+/8dYbb8oCez7ajeGud97F8Ht/+mcjo2Nw2traMXx/13sYGo0m2U4Tm2eG5wawFJns7JzBoWGcNC4tP0eS1APDjs4ucu7euUuZdGKJOjh65CiNgvP0aYZn9gPFXrCbpuaWxqZmXzOx8fYh9y1FoM4unr+A/IAHAZSMjY2To2CpKan7PtlLPvogyckpchTsT/74W2qyvqFRTW61ic0zw80BjBiTewp7ra6+AU5bewc6cnPz8xSWCGAqgAjG8OaNmziHRKa//wNEJg6YqAkEM05Knzx+gv4eMjE5TVJUVLywuATHA2NY7AXGdej2sKn97Kf/ocvxfBObZ4abA7i7p/f8ufO61e3u7ikoKDxz6jQkFwG59+NPUAZxSCUP7D8AyYVfVFiECA8PC9/7yd5Dnx68dfNW+bMK5GCqUydOIqrhnz51Ojc3D86iFvweZWIvMK5Dt4e9xsTmmeG5p9DqpVQyqOipk6dmZud0+aYmJZdk3ANN7AW7aWxqwbb7momNtw/d3RevMbF5Zrj/FNpnTewFu6GLWMbjGmalyxkbn9DlmBpmNeXgXeXtN7HxjBXcGcCLvo3YC3ZDAfzmr17v6e1TA6+4qBgRe8fvTkdHJ5Lolbzz1tvXr15Dsbm5+Tu3/U4cP1FaWtbXPzA+PpGVle132w8xn5KSisKQODkfzzSx8YwV3BnAjENQAFdVVUdHRcNB0NITGjnZOR2dXegypGiXA2OiYxoaGhGZISGhGJY/q8jNzRsYHHry+AnitqGxCcGMYuhjzC0sorBRwD3KxMYzVuAA3jHwfeAN0U3rNSY2zwx3BjB650XFpT5rYi/YTW9fH06Pfc3ExtuHrt17jYnNM8PNF7F0K+pTJvYC4zp0e9g5oweEPMrE5pnBAew2E3thc9TU1AjPChlPn2L4rLx8YmICzumTp7TslY72dnKMXLl0+c5tP5EwMDg4iE64SJhRXFQkPDOuXr6SlJgoEtqKCc8V6PawNHr48dDBQxjW1TfIh7FgeXn5GCKHLg14ponNM8PNATw6Np6bm6dbXR8xsRccZHZmtq+vr+JZRV1tLZLhoWGUn56WTg5x8vgJcmJjYjHMy82lZFxsHIb+9+49DgqiHDA9ve6eVldnV1GhJQiXtJaxuLio1u+5z87qqruvt094q5SVlAhvZaWhoUF4q0RFRmCom0ljY6PwNoFuDzthra1t8oFKzzGxeWa4OYARvf73/XWr6yMm9sK2gDpeWlqCMzo6Sjkq/f39wjNjcGBQeGbMzMwIzwq228bk5KTwXIFuD3uNic0zg0+h3WZiL2wjXV1dGI6Pb/BLRtv3qKuqqoRnRlVlpfDMoIOIZGhoSHguQreHvcbE5pnBAew2E3thG6l49gzD4aHhi+fOU46RuNjYO35WO8DBj54IzzpPHj0WnoHOjo6y0jKRYFyBOwM4J5dvI20rVy9fxlCe9I5pp9N/94MfUJIglQY0NujhQ0pK2rWrX9Ro5ub0zyq3tbaSQzJ+49p1SuoYHh7GsLxMBLPpiT1jD+4MYIZxIzjXwJCOR7XaxfwDe/dZRhigw42R7u7ut15/QyTWQ9f8jTQ2NL7/7i6RcAUcwD5EtdZ9RbM7deIk5RgpLy27a/0UGtBMbBAXZ7nQbQrk/Wn6uqvlLqemupoi8+rlK5QDPnjvPeGtrLSuniPowClDyJNgkbCPT/ftd/TcAceI1pYWkXAF7g/gxYWF2dnZ5sYmkdZ25dLSUnZWVllZGVYOvaa4mFiUobG5OTkYLi0uZaQ/7ejomJqaXJifb2tro7EJ8fET4xO0SejpTYyPo8HFx8XJOyXR0VEYNjc1xWvVDNCqcrKz4cij5vLScq/2DFBdbe3g4GBSYiKaxax25nnjujgnLMjLpxskPT09vb3igaHQ4JAb166R74HU19Vh+CgoqKbaIjh/+b0/x/Dg/v2WcQpntHvF3/vOn2LY0tysVm5nZ+fDgAA4mRkZtJMT4xO0MQK6TQUiIyz3in7v61+nJOF/7350lGX/f+t/fINyiF/87GfC2zSoFGwm1q2q0nKgodWjDUdtQkvrgZYcHBjAUIXy6T62utUJcfEYorFh+F//r/9byxNQMeNlv5hoy63yJq1V/85/+29anoAm2UzIqLg5gBGoiBbs1oT4BMwk5InlGgmSfX19WC15ewPdtqSEBNpNOOdBM0L4DQ0NUVh2dnTEmD1aQG2IOnXJycl0V5NQb34kJyUjONGdi9HaFoGQxvpkPs0gxSgvE88bpCQlkwOam9de+FJXW0erV5BfQDkMsw14+Sn01JRrLvbS80w7HVKSimfPLpw7RzlGcP589rOzImEAIjZgEC6V/Z/sFZ4ZDx88+Oz0aZGwXLsaEZ5boQt1OB+mpI6uzk7hGbh04YLw1kM9alOuXbkqPAhMuEVgNgn3gX0Iuo2Eyrp08SKcslLLlXCcJFvGrYJWRZ3Y0hLL2HkNbYwFeaYzudrd0F2mvn/vHjl04efKJct1b0l5Wdn9u3fhFBUWUg6hRvX2Q7vFGqdPnvzlL34hEnbjd+u28Kxj7ZqZQ+yYAH6+/LxydUfLzirOWiPCw8mXLCwsCG9lJS01VXgatJ5q50ddc7qrcdfvDiUxitoudYrOnxW6hEx5Bi5XSYK9iYX29+mfLmQ8FgpgquX//J9+C8Pf+a9rvVb1WKNr54+0x1Fpko8/2q3lWXj9tV8Kz/DsyoP7/hjSJBTAf/h7v28Z4SyeHsDXrq6dchif8rl4/gICmC5L5OXmfvDee7m5lktcoLGx8eCBA8jc98nehPj45qYmOkdKTkweGR4eHx9H55tKgoK8fHKaGhurKquSE5MoefnSpaTExOLiYvjpaWlUGWdOnpKihNptbGjECTb6xvl5edmZWQcPfEpHDf9VLfIcUpNTMMQ6G+/fSrq7uukpa2tER65dKTBi+7SwsrJSfWyTLhqBrMxMDKurqinJ2I+nBzDJICIHqiuvJEsFnpycpLVHAeruory8Xj0zPS0z0WQBCiMHyMuG8DGW5gxdxbIwTxJYjMKJopzhlPbUriVTcyiYkSQfuZgJLcV4TdJDIKkZHBy8cNZqHzjzaYaNWyOPgx4JzzrB2pVIUzo7OkqV3zlI6MYPwN4mh7ET7gP7EA8fWO4A6Tj86afCMyM2OkZ4ZshjpTVKtJMXa8gnsei4kJwkTny2Gdt94LDQUOEZ6F59as2I6a7W4Vt9YIbZItQAvnXjJoZ/9Pt29UspgOm5lz/+o/+h5VloaGjos3kRxP/+fQwpgO1cljU4gBnGXkZGHL7vNTRo68eYm4cDmGF2MBzAjK9juw/c2dFJT++6HO4DM4wLsB3AaNv37ohHA1wLBzDDuIC333xTeKuMW/n8unzOzH4uaw+9mfLjf/93DDd505EDmGF2MBzAjK9DP/2zpoS73n7HWoTQywCMfPTBB8IzQD8wJOiX/aTqhQVO/oiNA5jxdWz3gcF56w+uWcPGi7Ul1Aemx1fCw8TrgR3FUwI4L7/Ad0xsM+MZUADTM970UKd8qzZQfzqu6ieg3zkkJljeU68+462+T4d+1CWhZEqy5VflagB/dvoMhk7gKQGse2Ojd5vYZobZNJ4bwP39AxiOT0yOjo6p+ZNT0719/WLUmOUj1TZsbGx8eHhEl+l2E9vMMJvGgwJ4dm7+7JnPwsMj4CNEtdicLiwsgr+wtExNH3byxEkMOzu7MDY+Ll7mT8/MJsQn4HympaVVZmIeqalpGCdzPMHENjPMpvGgAK6tq0cY7t+3H74M4MDAIP/7/ojAmpramto6ZD3wf9DW1g5HF8AwiO3wiEWVZQ46Mz29fSgpczzBxDYzzKbxrFNoNdL6tFPotaR22kxGxRDgCFeZuYNMbDPDbBq+iOUGE9tsN2XlFbrr2D5neXzp3hxPCWDdZ0e828Q2201+QZHuEOBrNjNr9R1APo6nBDBjgw0DWO16eFqH3yXGAWwNDuAdAAJ4cnom4EFAeHgExefVK1dr6+pv37p9+tRpJEdHx44fPUZt/d2335mdm+/q6j588FBKckpFRWVaWnpIcAgmTExIxBBjMQwLDaPyO8I4gK3hKQG84EuIbbYbBPD8wiIiFqGIpozwa2/vgFNWVj47O4sk9v78wgKcqemZyMgoxG1EeMTMzCxdkF9YXCopKUX52JjY4ZHR6ZnZmbn5i+cvqBHi4cYBbA2+iOUGE9tsN3QKjeC8evkKzQE+aWl9QyOSvX39CEs5SjrkY0hjR8fGMRWMCuwg4wC2hucGsGyRRpNNcMO2iAKyQXuOiW22G76IxQFsDQ8KYARbR2fXiPbgJD0sCcMp38DgEPkyp/xZBRyU1z3IgWm15zgmZQ4KoxOI6pc5nmBim+2mtOxZTm6+L1su30aygmcpMLp2F7S+GT2JBQd9P3paA0ly5uYXKqqq4egCGIodFhYeHh7R2NgkM5G7uLSMTqDM8QQT28wwm8azAhjySWfOiNWrV67CQQTSOfDZz85SGZkDZY6JiaVMa4a5UWGPMrHNDLNp+CKWG0xss+PMzMwsLCxMTEzIjzMB+vA0vbIYFVFWWpqdlT07O9vZ0ZGWmrr5qnGIxQUH3vA0Z/0TTRL6yiFjDU8JYGiv75jYZkdobW2V9fQ46BE6heQD+giAHFuQX5CflzfQ30+fOBobG6uvq6dR9gSMxKHCC8oBZUMceo0bAtihNfE1PCWAmQ1ZXrIAaYUOt7W1UebS4iK90kkFNYogUds93XxGYFMSoIztWutQXvi0Yf3KZW3YmFToA3G2wQGotaVFJBgDHMAMs4PhAPYS7D8vhabRV3wfPggoLCgg8ayprkYyMOBhenp6+6q8E7s//FB4dnDi6DHh2cGjQMsHsm0wwh3gjfCUAJ7UnhDyERPb7FKmtS8V2wnCFcOuri76aEhNdU1KcnJ0ZBTOxjMzMrQia2RmWL6+bSf0ujY72aJPlvgUnhLAuuu03m1im11KRHi47e8G7PnwIwwh1J0dnQ319ffv3oMOQ42p+oeHh0OehERHRoYGhzxb/5rVB/7+U3avs//9+y3NzSJhxuSE5fPohP+9e5nat/mtwWd2G+JZATy1etu2r6+/Q3vr1eOgR9evXoNDBWBXLl+pqamlYrHr7wMjE6YWnp6ZpRvLc/ML5eXP4Fy7dr2zq1t9Nqu+vuHUyVPkX7tyVZ0cPs1T5kRFResW6oSJbWaYTeNBAYxIO3/23IH9B+DLJ7EmpqaLiorhyLhC7N3xu0M56pNYmD4pKTk5OaVVe2MWWUR4xFuvv4GSCGB62R2WcvPGTZobxTbs5vUb5Ny9c5dGkWVn52CGGRmZMgeWEJ+gJp0wsc0uxZ4ruhJ613Hls2cTExNUd5i8oaGhv7+/ualJ93upLE0kR0csN6UAij1NT29ubJK3jgYGBsgBGzYmFXt+mOXQPScfxIMCGPGUmZnV1d0DHwHc09sHB2pJUnzqxEmSzfaOTmTSA88bimFpaRm9WwsBXFlZBQdzo8kxtyHtjbOjY+PIpOc0r61Xe6P1DwyisPq4tRMmttmlONQHToyPxxDxM60Bv6y09P7du+iUGj8poHs24+6dOz09PTj7peTs7GxQYCD5WwE/yGEb7gO7wcQ2u5Ty8vK//8GrImHG3j0fC29lJTsr+71d71VWVFRXVdEnBSorK+Pj4gIDAtANzkh/SsUIzLmrq4v8sfHxtNTU5ubm5KQkUu++3t7IiAj5ZRB7HrrAQsmZGN/4mRYE8LEjR0WCMeApAQzd8x0T28wwm8ZTAphxCbqKcKhH6hKMXVb0rrd/NXwHDmAvISkhQXgrK1OTkzi/TYxPaG1pycq0IEasIp+OtgecbwvPcegecm9vL4Yd7e2dnZ30LS/74T6wbTiAvQTLZeT6BuqX9nT3TE5OWm75dnamp6WVFBcvLCyo1VxVKXqh9vA0/an9l4Lr6+uxDiJhCf4sJOk6WUtzc2dHR0J8PNaHxtoDAvjGtesiwRjwlADOzSvwHRPb7C1s6eEbx4652VmRYAx4SgDrrtN6t4ltZphN46EBPDo2fk17I0d4WPgD/wfqqMam5hPHT0xNzwwMDj19mqGOsmHTM7Mnjh3Hv86u7iOHj8hHOGAzs3OfHviUrg8f1Bw5ymjDwyO65zqcMLHNLoVOU+1kpzwdkZqSUvHsWWVFhUgzBjwogBE5Tc0tV7Q3p8onsRBdb7/5FrV7MsTeG796HflwdU9iJSYkJiUmtbS2yUyEa+DDQJSUT2Kh2Juvv4GkLJObm4fF3L93H77xSSzMMGP9YcIzn8Sa2SiA1aDd8LEt9Y0fG+LQD+4dKvw0Pb2utnZLT9F3Op6lwKGhYW9oTz4igDGEHTl0GAYnMiKSou78ufPXrl1HGCNT91ZKBCcM+TJ5/rOz7727a3R0DNO2t3cg8+bNW363/RD/WGhQYBBy4N/xu0MPVyGM5eQw+JYZKs9Cx8XF73r7HayezHHCaJNdy/zcnO2w9Lt1S3jaM1i2Cz8OeiQ8LfJtNxH1F0iYre3GUFtTIzw7mk14aOid27eLHbno5Wt4bh9YPcuFIa0myUwzrZluhmqgSkMw63K2wsQ2M8ym4YtYbjCxzQyzaTwlgHFS5zuIbWaYTeMpAcwwjBNwADPMDoYDmGF2MBzADLOD4QBmmB0MBzDD7GBcE8AMw7iFnJwc1wQwizDDbDNRUVFVVVUbhp5dATzLP9pkmO0lNDR0bGxMJKxj7yn06OhohuHDHAzDuJb5+fm7d+9Cfru7u+0583WgDzw3N4eZ1tfX1zIMszXU1dV1dHRMT0/b2W/li1gMs4PhAGaYHQwHMMPsYDiAGWYHwwHMMDsYDmCG2cFwADNeQlj1CYOdXDXpy3xyTJOmZikT2XBKLGyV551HJxsOW6xeG0qjpDp02hyafJPLItvETKabDi+MFoq9s7Kyu/TZRwVFHxUWf1QAKzIxyyhT35CjJuFYm1CYIce0PM2nqGR3SRlWdXd55e6yZ3uKSs9U1T5pbq0aHpl35NPcTjNVXD94PXbgeozFbihGSZlJBUSmVl5mUgF9mTV/PMT5jyhtNcfj2o9GNfiWxTQPTFjeDswCzHgJqlIqhiTlqENdvvR1o1Sz5JgIcMeqANs225Jmp+CpxTYjtPbMx9llmQuwTvPIUY0yLUPpUP76YhaTozTtlCWlUY4cZRlSydVRNkxMYlaysNiyLSVlDxqbxhx5sbo9QIAtgiokU3PItwxXhZZ8i6MrQLY6uWWISVbLWMwyBxZgzzIWYMbL0Iml4qhqKnNMM2WOuUU2nBQLW2WtB+wS21DqHNFCB8w4W2fXxKoA229roqvoq5BGawpqJR/l1Uk2mIlN080Khn5z2bPU7h6xqZvA0gO2yOSqiEqTIqr6Mkdmro01aDMNLQKcJRbmefigAB9jAWa8DE0jbYuo/WONJS05Wy7A22Ykn1sg5zMbCrC4trw+U2dS6vSOU9pp1Ryam6GwqsfFZeeqa8U2O464BK11VYWCkmnaKRyTHEWwdWUsDomxNk8WYE8zFmDGy1CV0rqaSl+XSUnTzLUcB+4B22lbIIH22tYs2lyASatUxVLNWr5O84yabTKhtVlZM1nezgk3KLa7vKJsYFBsvN2s9oB1CqokKUc4hm6uyFcyLaYUYwH2NGMBZhiGYZgNmZpbau6fvpzSqtdRp40FmGEYhmEcRa+mThgLMMMwDMM4gV5QHTUWYIZhGIZxAr2gOmoswAzDMAzjBHpBddRYgBmGYRjGCfSC6qixADMMwzCME+gF1UHjF3EwDMMwjDPU9kxuyronFpYs3wxmAWYYhmEYB5idnbXzq/u2YQFmGIZhGAcoKysbHR1dXl4WaWfZDgF++Y37X/vbc3aamIZhGIZhPJKQkJDKysqpqalN9oO3Q4Ahq9/ZlW2niWlWuXv37gsaOOMQWRo/+tGPXnrpJZFgGIZhmO3iwYMHOTk5w8PDm+wE7xgBBl//+tdFLgswwzAM4yb8/f2zsrJ8S4AJypcCfODAATFidZRIGJIgKChIeBrx8fHCe+GF2dlZtfCXvvQlNQn/nXfeEYnVOQPVZxiGYXwB3xJgOFBETfsslJWVOSHAtbWWD3aKhCHZ2tqqJi1TKsnXXnsNyV/7tV+jpJRnkm2GYRjGd3h115mfn3q8N7D4SFTD0egmYTHSaZaZtzI6xDRmuEaAbd+IdokAS1/iqADrJNZ20jKlkoTe63IgxuHh4ZTJMAzD+A6vvnvq5yeC9j4sOhJZp3vJhs5upHuLABOkf4AEWL2M3NvbKzwNXXmHBJjuN4uEsgLo8lLOK6+8IrIYhmEYX8IRAW4X05ixHQL8jX++Ag2208Q0boLEFYi0GcePH0f3VyQYhmGYbee9uBffj3vRv/LYculXBtJ/R2cr/U9+MzTyN/wDv+gfiOFv3H/4mxGx/g1NmHD47040fn9/9+EAmg+YnF366r7sr3ycrtr1tDYx2gy7Bbje/T3gHYSQXzMBPnfuHPIhvXQDmGEYhnEXJMD3SnZRcrJuH3R3uewrlARf1AT4RHkF/Ocrz7/4KOSLAY96lxcgwA1WBPjdh1UiayN20iVohmEYhnEhUF9o8P3S9yk5UfMRBHipZE2ARQ/4QdBvwLSuMDrByLchwLCvfvIU9ruf5otxVmABZhiGYXwUCLClB6wT4NJ1AgzRPVz2TKRXoUvQba8cHHj1OAzJ4bqur+7Lgfr+7idPf/9ApjQxgRkedw/4Lw+ssLnc0hmGYRgPw+N6wDrlYHOJidpmGIZhPAaP6wELj2EYhmG8GhZghmEYhnEDLMAMwzAM4wY87h6w8BiGYRjGq7l++258cnpLV9/w5Nzo9IINm5pbEtOYwQLMMAzDMA7gWV9DYgFmGIZhfATfEuDE5vHvBDSwsXmO/UVQY3bHpGigDMP4Ej4hwK88adId9djYPNCaRuZEk2UYxgfwcgH+l4hW9QD3ZoL5g2QHMnrUYmxs7jJ0iEWjZBjG2/FmAVaPa4XdU5Q5Ob+s5sNkt8M4SmfQaRTbm94tc+YWny89fy6T0mqHZlFSlwnTlrPGL+MsP+26XjI4pj3hRmXS2ia0kWvQ3IDpsmB3yoeoACjrnaZM47rJxckcJHsnF2SSzRPsveQurSYZhvFyvFaA1U7t/JKYrcw5nddX3jdztXhNiuR9OJmjMxorocvapgL8vUDRiTFqG4lrXOMYhpjQJQJM5WWSShK68rQU7A2ZgyQLsAeaVnsMw3g5XivAxsMZ+RBOSkpCa0fUYtBmSqoGocUomZR6qRNgKb3vJXfSWPhFPaJLCqOxcGgOpgJ8/9lad1aHqQBTvzy+yfJ8GfkStTzlqA75KFPQPUVJNg8xqiOGYbybf/vo7Lvng0+FlV1Kbr6c3Ho5pXVtqDoySSaTq6N2jADLpOR22ZCafzS7V5ZUjdRUIjNNRVHXK9XZ24kdNCRTR5HpliUxXRbZz2LaoaPq2YO1dVMN8+QesAcaVTfDMN6N/W/Csm0eJ8DoR8rDmbzLK3N+EduOAu8ld8kcYxl7zAkBNl2K2gOGOSrAVN6YqZY3LcPmmabVNsMwXo7XCjD4i6BGeURD11DkGn6VNDyzSPnZHZNqvj1mTYBtmLxMrYOuWpORHpsiy6hmT3lrZdRbwmyeYHvSukXdMAzj1XizAIPzBf3qoQ2SLB/IkiCHfyjM5iFmfEaBYRhvxcsFmECXQneYY2PzQOubWhBNlmEYH8AnBFiCA9ybCSYPPbGxuct+EdvOusswvolvCTDDMAzDeAgswAzDMAzjBliAGYZhGMYNsAB7BNeuXXvhhRc+97nPVVVViayVlS9/+csDAwMiscrLL79cUFAgEhqYUHg28fPzO3DggEisgmlNEaPXI8YpvPjii8hvaWkhh/jCF74gRq/y+c9/nkbBJ8c21ophL9HMsaNOnDghcg0Yt9TO5YJNriGhG5uVlfXKK6+IhAHTepFgLOZmxMYkRlBeeOvZhv05OztLtW//JBKaZNeuXUFBQZRDvPTSSxhFyFjQNUInwNyEt7KyuLiIfUI+dtH09DT5ErUAYRqtul1Hi7DdHiS2t8g41v49oG6pxLlatt16JR0dHdTS/vVf/1VkKW3DFHuWrmPzbWD7YQF2M2g0ulaIlicxFWDd8QjFhLceXb5pqGgLMUGMNgOHHl0B03ZvLAZM52xP5JuuvC4TR0BMqIOOknCojCnqWF1JaxPanqEOGwdcHJgwK2CsaALbSAV02DjquWp/Em+++SYtUT10GmcIUOOyJaMuSLTsFGD1tFKuBk2iE2Acx4WngX1Lhe08+NqoC3UNqfVKjAJsRBVgLEVMqYCxGNJY4zoYd77pFpnOmfaw7T2g7kZMQo7E/lpW2bD1Eiig7kC5JtYEmGaLSTBUOyQS04YK7GwDHgULsJsxRqM8xBjPqdF20fJwtFLbnyUCNERag44gars3bbU0oRFrEZWQkICxcDD85JNPKNPY7rFRpHzYFrW/TtPqwGYaT0GEpyCPERL1YEFYO27CJ8eI7viuK2ltQtN8qh2R0HY41aw8aNJYedjy9/fXCgroKghQDzqYCWXqMD1yEa7an9iZuk4eyugclU0KsGUNVqEdBQdDXQUhqcYLlSd0jVA3T4mdAmytB6w7A5CrZ4xWWdGyQmkRpgKMyWmJ2GM0FbAhJ5iJbqxzAuxoLTvUeglsmu54RTtKJ8BY/29/+9vqriawht/97nfVNsACbDSTqnKCnSXAaNPU5jZZ62g3NB9C5K4PaRmfkj179pCjTiKhTHWUrtValrQRougqCA/hrUfX7l999VXhrSKP7MZ5Uoded0hSi0n1sgEFp/FQInegKGfoyiBHd9BEjvA0dEmJjXyJXBnTA+6G2L/hKi7cnzZAGeEpbFKA7ewBW8N48KVdIRJ2YNlyBVl9OgEmbDQ2Qp1K7hkxa8NJAFYVm4yqUedpQ05IpLFndAKmlrfR6jCt8GxiZzGnUQXYoWbpTQLszd8D3kGoByCJLqSB6TEFTVN4GhBmtRViJpS01mqN6GaoghXQYkGPsd2bHrZQUnja+qhJgCSdVuvyCfXOH/HVr35VjFsFq4dDGC0XKyDXCoXJIehs3bjDga6kZTEGKJ8K6FC7Lyo2BNj+epGYTrIV+9MaKCw8BcgMzQdHVbQ68oeGhuwUYCpP0NbBwdBpAVahWW2I6bJMW7IRXbSSmmJC7BbMgWZLq6FKI6IVmer8qQ3DMd0i6oCqtU/1CMctAuxQ61VnaLp11hq2rlKoqevA3FiANwsLsG1QzJ6DkSmmjRsNV3ibwLTdbyjANjAWw8objyY4XNoZ/PZvptNrSOiuqhE2DoXAtF4kxqOPE2xmfxrPAh3Czh6wKTSJqSjanht2OArYxnSv2in2Tu8TLBdD2+1B4qic2F+eVkPF6S2y3XpVsIji4mLZxcc6IEd30DOdm/0hwAK8WXxWgLcB+0PFUVze7o0HiE1i/wztLOnCNdy6epG4fH86gdPrYKco7iA8UICdxp7Wu7i4eObMGZHQniNR7xNbu7HlBCzAm4UFWLINx2WGYRjGjbAAuxlrQssCzDAM492wALsZFmCGYRjfhAXYzbAAMwzD+CYswG6GBZhhGMY3YQH2UHQC/PLLL//kJz8RCYZhGGbnwwLsoXAPmGEYxrthAWYYhmEYN8ACzDAMwzBugAWYYRiGYdwACzDDMAzDuAEWYIZhGIZxAyzADMMwDOMGWIAZhmEYxg2wADMMwzCMG2ABZhiGYRg3wALMMAzDMG6ABZhhGIZh3AALMMMwDMO4ARZghmEYhnEDLMAMwzAM4wZYgBmGYRjGDbAAMwzDMIwbYAFmGIZhGDfAAswwDMMwboAFmGEYhmHcAAswwzAMw7gBFmCGcTE1tfWFRSX5BUUFbD5gotYZxnFYgBnGxZQ/q6hvaJqcmp6YnGLzehO1zjCOwwLMMC5GFeD+waF9H3+CzMWl5anpGfXATYZi0nSjyOYXFjHt7Ny8Lh82PTNbW1sXEx1TWVnV3NJqnANKLCwtW1s0m0uMKn0r0C2IzZNN1JmD+K4AZ+fk5eUXsPmg5ecXikawNagCjAa9+6Pdi8vPFxaXoJTNzS1q0MLS059GRUbBwsLCGxoaVaWED2UNDAxqbW07+9nZ/oFBOUoalgIZnpmd0+WT3bp1u6SktKKiMuhhIIrpxrK5xEStbwG6BbF5sok6cxDfFeCs7FxrfQ4277byZ5WiEWwNJpegrXdwNzRMuJmGStNuZg5stk3U+hagW9DWWVFRsS4HdvvWbV3Oj/7t33U5zllPb9/4xKQuc6ebqDMHYQHW70cnzHiItNYjsWGmFwnV2aKArhMjc2Qx05mw6WwbBLihsRlVg+pg83oTtb4FyBb78e490ldteGS0q6ubTDfq4vkLGLa2tmEY8CCAMt/f9R450iLCIzAcGh7BUI69duUqhvv37qMkWW1tnfRjomMgz5WVVTJnQ4uKiva77Vff0EjJP/1f/1uO8g4TdeYgvi7AsLi4eNPTMZymwWQSkRYbE9vXP1BVVY32h7QctbC0nJ2dg1lVVdcgJJBTV1ePTBqLCZ89q8Co1rZ2TJ6amjY7O3fm1OmKikroNOaWlZWNg3VJSSnmUF1dMzY+0dLSignz8vJn5+aR+Sjo0eLy87Cw8JHRMZonzTYsNIxyysufjY6No2RoaNjyc75ytYFttQAzjEtQG+2jR48LC4vUHNuWn1+Ag0NpaRkOYhBgHOJwiJBj01LTpH/3zl2MKCt/Bh+HuOLiEsrvHxi843dHnWrPR7vJuXf3Xnd3DxYhR5GhKA5WukwyyyQ9vXKSFu3MwJtM1JmD+LoAl5WVT8/MJKekwtft0IaGRphMojWjKQYGPHz86PHS8nMMoZp0W27p+Upubh6cxaVlOiuEAGN30oSY85PHT2ChIaGYClEENQ0MDJrRxPXJk2DqKkGY5xcWIclnTp+ZX1zCqJDgEMwZveljR46iwKgWCm3tHUNDw/X1DZgzMrBOHZ1d0GkoN3IyMzKd6Hz7mrEAMzsCXbtl82QTdeYgfAka0jYLU3elNaOSN67fgBJSDqkdRtAcLAW0HAzhYzRNYvFXL1jBx3gYHJoDMmlaGmuZIY2am+/s7IIzOIQKGpHTRkdFz80vWIqt5qAHTE6BI+fIPmtbfwm6Eq3raUZ2Riab95uo9S1A127ZPNlEnTkIC7B+P7rQIIpkunw299o23APm3wH7jolaZxjH8V0BTn+amZtXkJObz+ZrhnMv0Qi2BlWAxyYm93+yd0m7MW/t7kBNTa18OAUmz9jIoeHY+ITl3sTCom4s/sMZn5iUSZhMohBMFiYb156vWVhcQmZyUnJqahrGy7FsjpqodYZxHN8VYIbZIlQBXn6+8s7b78CB4AU9DKSnVaGmWVnZJI2wZxWV1dU1kOeh4RGI4h2/OxjCHj163NXdExIcMjs3D009cvjI8vLzD9//oLz8WVlZeWFh0ejYeGVVNWxhafnq5SuYVX19w9DQcG1tnd9tP4y9eP5CTk4uyhfkF/T09pE8p6SklpaW0aKx0BPHjpPP5pyJWmcYx2EBZhgX4+GXoKHl6EmTPze/wN3fTZqo9S1AtyA2TzZRZw7CAswwLgYC3NjUgm4r+pdsXm+i1rcA3SGezZNN1JmD+PRDWFPTM3RRjs2njH+GxOwIdId4J6y/fyAzM0uX6ZB19/RiWFBQqGayGU3UmYP4tADjWKzbiWy+YCzAzI5Attizn53FkLTQhiXEJ4xPTA4NjzQ1Nbe2tg2PjMI++uBDjKKXTe56510M//zPvovhe+/uwvDsmc8wTE9/iuG1q9cw7Ontg2zDgf3Z//kOObB7d+9Jn81oos4chAXY8jo3+TgMmy/Ydgrw8SNHw8PCzn32WdDDwPb2duQkJSSmpqREhIfDHxwY+HT/ASRTkpORXFpagvvZ6TPRUVF5uZZHtSuePTtx7DgcGnvowKdjY2NPHj1CAcocGhq6deMm+QBTjY6OisTKyvj4eHxcPPmI8KtXrtbX1be2tFCO/VRXVQ0ODMKpra3t7OykTPs5/9lZcvxu3SLHIWJjYjAcHhpKT0ujHPuROyo+Lg47kHwdt26u7UCPQrbY3Ny81JTU27dut3d0IolD1n/5rf9Ljn0U9CgqKrqjswsKHRIcAh0dG5+AEt+6eevunbv/8Hc/RJm33niztLTsjV+9Dp9yfvrjn2D4t6/8DbT52JGj8Nva2jF5bGxccnIKkjD56iuYVGU2UxN15iC+LsCjY+Mnj5+IiIjk3rDv2HYKsP/9+yPDIzHRMZOTE9CA3p6e0JAQ9FSePH7c1NSEAh3t7WEhoVGRkV2dXXNzc4kJllFpaWmLYGkJ2vzwQQAyW5pbJicmLl28iDK1NbX+9+7LiD2wd5+Ulpzs7L6+PhlHEODwsHA1rCIjIjIzMshvbWl945e/Ih/8/D/+o6W5WSQMZGVkYj1xQkDJycnJX/3iNQwpee3qVawn+aaEBAdHhofPzog3J2NXXDx3nnys3h/9/h+Mjo5R0khjfX1ocEhWZqZIr6zsevudttY28nFO8Obrr5NvSmRkZHhIaHd3NyXra+vefecduU+wm69euUI+ePettxPjE0XC3ejaLZsnm6gzB+EesOWSy8DgkLor2bzb+BI0syPQtVs2TzZRZw7CAqzfj2xeb74gwM1NTfl5ectLlqju6+1FT3p+fv7c6qVg+0HfGh1fOKXFJdVV1ZRpP0/T0xvq6xcWFh4/eiSyHOHWzZtY7ZSk5LY20d+1n+6uroynT3FIuXr5Mrq5IlcBa3X86DGRYBh34NMCzE9B+6b5ggC3NDfLy8VDg4NxMTETExM3rl2nnMGBgcsXL5EPMjMyjh4+IhJmTE9P3797b2hoiJKXLlyQ/tTU1A9ffRUySUkdBfn5hYWF01NTIU+eUA7ODG5cuyYjPfjxk9OnTpFv5K6fH6aNCA8fGBignMCAh3K7wL//y7/09PSIxHr6+vpiomNwXDt/7hwtbmZm5sypU6oYnz97TngrK5jPv/3zv1jbEIbZCnxXgBmGYRjGjbAAM4wXMjw0FPQwkDqOiO2w0LDQ4OCuzi4a6yi1NbVPHj8WCUdob2t7cN8fvV6RdpD2jo6wkFCsuUg7SFhoaEx0dE62+QeLqiorb12/IRIezCd7Pn7vnXexLR9/tBvJwwcP7t+7d2jQ8lD6vk8+gR3Yuw9+dlZWyJPgjz74ID8vj0ZhCAb6Bz7ZvWdiYuK1n/2MchLjE8gBZ5TLD50da8+37/34Y8xNJOyAFievi9gDFoFhlyMP1dNSmhodaE60lKrKKkp6GizAFhYWFh4+eHDh3Nr1KICaKysrEwlXgyUKb5UN73JdvnS5tLhEJBxp6xFh4bJ25+bWXtyTlpLa2dEhEjaZnJzMWn101lFw+Lt54wbW1lo8j42Jx1+jo6KSk5LgPAwQz9PSjUPZKtTf2zC2US9BZzx92tvbC+fsmTOUY8Ra6KHBHPz0UzSht99809ho7aGrq6u2pkYkzLAR9ZcuXMBwfHwsMjKScoxYm7ypsZEO7nm5uf39/ZSpQ70E7bHUVFtuvcfFxuJkgnIAibEOa5vz/ru70ADk79OuXl576tuaAAM1YJMSxZPhOJL88z/8I/kqwY8ttxju+vlREus8s/rEO46rdbW15KvgzAxDuTJornOrrxU7deKE6QP5OJJgePbMZ5QsLSmVtwwOfXrQVMupCR0/cpSSRYWFpg8EFOTn37tzRyS2EV8X4NMnT9FCIUW1Wit5HPQoKiICDoKWHj8hIiMiRoaHl5aW7t29OzM9093dDVEJCgzEqE/37cdxqqWlBU18eGg49Ekw+h+yAQ0NDjXU11MTxI5OiI9Ho+no6MByp6enc3Jy0CBwaGtrbUWBoIcP42Jiteks4GQWY8NCQrDcpqYmdf+EBAdjqqXFxb6+PkyFDgpKYiVDnjzB2TGdIBPjmsKlpqbSj0ZSU1Iwt3ztZ6bUNcGGJCZYAgzHrGfl5Z2dnSMjI3W1dciRUKstyC/A5LTC2JCoyKjYmJjUlNTLly4hp6qyAnuspbllaXntB5ex0TE0bUpyCoaR4RGITOwoLJR+C4vzcRTApvnfv/80PR2h290lOmpSm+/fu6cl137hythmbna2uKhofHxcpG0SH7vW5BwFJ6mzs7Mi4SAIBLQ3kXAcxJTazh2lo72jpKhYJLQzReEx1pGxaT/yt2r2gwOj8OzG6UZIWHuSYKvhHrAF6EFcTMyVS5ehTPfv3jv/2VmsCU6aWjVRJJ48enzi6DHspvS0NO3c7fnRQ4fPnz0L8Ti4/0BNTU1pScnJEycxq4a6uuNHj8oG0aCBAu1tbZjnpYsXkXni+PGszEzo9zHt4ZcbV68d+fTg1NQUTiSPHj6sTWcB63P44MGJiYnMjMxjR46oXZDQ4BA64U1MtFxQwhnctStXUL68rAzrCUcrpQfdERyUUQASe+vGDXr05tTx47dvWt6QcPL4cfRBoco4x0RJbYo1sBoRYWGfnT4NHyuDHYXNCQsNxfkBVPnKJfFQT0mx5aCGTcM+nJqc2vfxJzhG5+bkYC81NTRi7KmTJ1EA63D18mU4gYGBly5Y9snlixexi+DcvnkT+gEHYIc7EY0MwEmhbAaQOgQ5+U4wuPoMlHPIvtf2Y2PN5+fmNnnUY5hNwgLsMB71nCSqjVQZQzfuPblP5ufm+aDmCaiXoMHkxCROCuUrOOxnbnaOpsJ5mxOT47SVHLqq5AQPAwKsnU3aBnuA7rCUlZb1dJv3b3bEJejtQbYWulr74fvvU9IeykpLMaTLVHZC90RoQjuhqx0O/RaOzvwaGxopqUI3zt0OC7DLUG/KYkPouqvKZi6XWVTWbN84cXnHiNqxluCoRwc+6UiM5bG9ahn4VJVjdnR97LxMyjhEa0tL4MOHdA0fsV1eXp6dmSXjCydM2VlZ5IO/+f731darA4VTkpPVlpaVmbUwL9pAeGhYaEgI+aa0tLTk5uSIhNYk5MVexMjffv+vda1LpaG+AQfcymcVExMTlPOs/Fl/Xx/5NdXV7771Nvmm4LiWmpIitxqLS0tNJR+0tbV9+N6azOzd87FDeuBlSAGOirDcbpfPcNmP6W1p2wQ9fCg8u3HiibzoSPE6UhUWYBNkqOwU/O/dW1pcPHLo0PT09OOgIORcu3yVbm3u37tXPSWku61pKWvxHxIcEhFmKfnR++/Hx8Vj2x8FBt67c2dubu7K5cuRERH5uXl5uXk48N2+dRszHxkZoQlRMjwszP/effj0xuCC/ILCggKU/HTf/ovnzw8PDfvdunXHz2/5+fNzZz57FBTY3d2NVe3v7y8pLi4pLhlRrkbiaEhHt6OHDgeuPv1ETK4e9aqrLQ/RvPHLX9HrBrEVhz89ODQ4VJCf/6y8HEfn5KSkkpK1B8SepqeTc0V7wgKCXZhfgN3y9OlT2SUiTp88iS2FExYS8igoCJtw4tixpITE3R98ePjgwby8vKTERFrooU8P0tETh93GhgbLxAzDuIi33nhDeFZAFDt6K8GhPjFx87r4qbr9XNZu6jlEUWHhv//Lv5Lf3dVl2gPZHliANwV0F3VZkJ8H1UQ/AOfy1VVVE+PjcKCI5cpD1OiLQLHoOS/i/t270FT0PMJCQjF2fm6usaEx+PFjTJuVmYlhTHQ05t/d1R38+AnOTwdWn+REVTU3NrW1tsHBCf7MzExyYhJKdnR0QAWxAtTnGBwcRIHenh46pcUZALoOMVGWearP8UPzOjs7sefrauuepgnhBJjtwMAAVBMOBB45OJGkAhBCyHlpaSlm1djYiHxItRRdEBcbC1FHzwnrg/mjYzEzPRMVGUkxjBUT5VZW0tPSUADbjnXDtqOPEh8bi9VOS0nBTsjMyEhPSw96GIic2JgY9JVRGKovJmasg+qmp2dBVWVlQ309HCde/ISGjTYGB6dups+y2ib4yRPUHRycblKOQ9DbQrAtah/aTjAVPdgYERYmO9A6Lqy+j5pIiI+Xz+6uPHfmyM4wDsECzDBeSEtzs/zxD0Q04L4/FDRh9QegOBH8m+9/n3yAbsdnp81/oYSQvH/3Xntb2+lT4vcC4OW/+Et5EQLnhd/+1resXUYeHBjEiSZOH+VvT7MzM//5H/5BHm4+2fOx+k4uHSlJSZgWqyfn/8uf/yJm9QNH4MWvfX1kWFwZ0jE7O3vrxg2cjNKzfmB0ZOT//Mm35fN94OJ5y29UJIkJCWsC7GN3iOVnow7s3YfzYEdPc+XvfOzk0KcHHX2g+qMPPjD9bZINPv5ot+kN4PGx8fff3SUSboUFmGEYxteR94Bzcyx3tfbv3UtJe2huaoKkiYTdOPGLJnDntvipsf0E+D8QngLfAzaBBZhhGGb7kQIM1KeW6GPMxMnjJ4RnAB3NqSnxRaD4uDhymhqbrL3oCuVhE6sPYMoLJJWVldbemjIxMVGs/cSRkO8GKS0ptfYIIeaPsSJheRWB5avbhCrATjwL5ipYgBmGYRjGDbAAMwzD+DryieXu7u5P9+136FBcX19v7RkCa9RUVzt6i318bFx2su3kWXk5vYpSR21NjdMvGHctLMAMwzC+jnoJ+p233pJvgbUfJ742ff3qVeHZh3NvZHugvXRaB98DNoEFmGEYZvuRArz7gw/zcvPkhx/+83/6LXLA7/y3/ya89bz+2i/prfiEnATHc2sPG2MS9dkoOQl0iL5fZMT//v2rl6+gt01JOcnS0tKhTw+SrwNLUR/aUrdFFeD/8ft/ILxthwWYYRiGYdwACzDDMAzDuAEWYIZhGF9HXoKmF599snsPJe3n2hXHbugCJz7BSy+mdQj6VrEO9RI0fYaceO1nPxPetsACzDAM4+uo94AxlHdVb924SQ74o9//feGth36eK19wS982Jb7xB38ovPVUVVZh2NkhfiUsv+QP/viP/ofw1tOgvXytb/VTHKp4f+sb3xTeeuh7svJXwv73Le/PJ6wJsKOv9NokLMB6RsfG2bzPRO0yDOMUThyc5fdj7AdSJDy72cxX5twOC7CeickpNu8zUbsMwzAeAwuwHnnInpqemZ6ZxRAmM/v6+h8+DGxr76DMoeGRs2c+GxgaPnf2XG9fvyymGmaSkpIaExNbVV1z/979mdk5ZI5PTObn5cfGxmG8Wlga8mnRZKbFOjq7/G77YbmBDwMrnlVYmxUbTNQuwzCMx8ACrIeO11DN2tq6ixcunv3s7Kf7D0htg9qFhoSOjU/AR2Z2dk5xcQlKj4yM3rh2fXFpmfJn5+blJAuLS6dPnlp+voKc0NCwjo5OKlNX3xAfFy+LqYYZNjU1Q7ZTU9NgSYlJbW3txpLIgZw/eRKMkqTrbNZM1C7DMIzHwAKsh47XkLb29o6n6U/R2YVkDgwOUT4EOCgwqKe3j+QQw8HBodzcPHRGJ7QcCOGpEyfv3b0HDaZJLDY1XVFR+exZBTq+MrOkpDQ2JtZUgO00rFVrWzvWsLW1rbe3TzeWTTVRuwzDMB4DC7Ae3YGbzTtM1C7DMIzHwAKsB11SNu8zUbtbSX5BERake/qazacMDQDNQDQIhtkIFmCGcQ048vKdeB83NAAWYMZ+WIAZxjVIAZ5afXCdHPUAPT0ziwEZjUUOjVpcWs7IyKQylEOGZFV1Df6po6ZXFwQXRg7lUEnpzM7NBwQ8xLCurh7Jrq7unp5eOGxbYSzAjEOwADOMayABnl9YTIhPqK6ugSKWP6tobGqW3eKmpmbIX1hYOELtwrnz7R2diYmWV/D43/eHWKanP0XrR7GKiso45fdpmGNUVDSc5KTkpeXn4WHhOMyXlZU3NDZhquzsnLHxidq6+oGBwfGJyabmlvv37i8/X4mMiIyIiMS0nV3d/QODUO4rl69g3aDcRw4dljNnc62xADMOwQKsZ3h0jM37TNTuVkICDBV84P8gITGpt6//2bOK5uYWHJfDQsMggTB//wdRkVElJaUtLa3XrlyFjhYWFtGxe3RsHNI7Ojp28vgJqCxm9SjoEf2eDXocFBg0P79w+tTp7p7euvqGu3fuxsbGxcbE3rp+A7MNehiIHPShL164mJKSOjg0PDQ8giFJAibHfDAHJKHBWDotkc3lxgLMOAQLsB5dRLF5h4na3UpIgOUSIZwbdjTpKvFW2NbNmc2GsQAzDsECrEcXUTpDN+Xhg4Bbt26jJ4Ekujv19Q0BAQ/p1RymhqNwX1//o0ePG7VrhpQzMDh0/MjRrKzsDY/RNgzTpqWmnTh2/M6duyMjo7qxbKqJ2t1KcOSlDiubzxoaAAswYz8swHroeI1YGh4ZbW5uaWlpvXzpsuxPqG/CIsM5r/99fwgqJpGZOkOZpMSk8mcVcj4obONNWNMzs3V19THRMbExsbDIiEisyaRZnwbnAXf87rz28190dnXrRrGpJmp3i1lkfJ6lpSXRGhhmI1iA9eBgDQVE1/bE0WOxsXGnTp1+41evZ+fkklJCgMNCw8jHsLW17dqVq2/88lenT54qLi6BcEJro6Ki/+rP/2JufoEO/TgpfvLo8Qfvvf/pgU8fBz1CH5qmbWxqtibAMORDh6WZFuvs7Dp44NPg4BB0giHn1mbFBhO1yzAM4zGwAOvRHbiNRk/T6DJVs6aXOoNUo6Quk22LTNSuxzA3N4fh2NgYdZja29q0bAs11TVdneI7qSAnKxvDIQ04ebm5GFZWVCBYBgYGWltakOzu6pqZnhkdHYVvG0wiPFczuDVfhcOBCYcnkXApCwsL4+Ob/U4l9jl3eRmnYQHWoztws3mHidrdemamp5saG+Fcu3q1pqYGshQTE7O4uNjf348Yi4mOTktNxdgA/wcYQmst0yifGSfk19FBfGwsJo+OjIoIC29tbR0aHIRsjIyMpCQnR0ZE3PHzGxocwhAzt+fzq6UlJcJzNbk5OcJzNU/T04XnarIzs4S3Cbbo/IDxBViA9eTlF7J5n4na3XqKCovyc3OnpqYePngwOTnZ0tzc3NRUV1vb1NTU1tqKLm9HezuKhYaEYCgFWO2Yjqwe0A8fPIjeVXd3d3NTc0JcfHxc3PLSUlhoKEZlZmS2tLQEP34SGxODZGFBQU9Pd3FREcRYm9TC66+9JjyF8NBQ9PywSlgxkeU4J4+fEJ7C40ePEb9RUVGbOZRERUYKb5X5hXk6WTl66DDlOMHQ0FBtTa1IrDI5MfkoKAjOT3/0Y8pxDhLg40ePUZJh7IcFmGG2j66uLuGtZwe1/K1bVZ4z42uwADOMl2N6k1IXa7qkPByoxwW+2ckwroUFWE9RcSmb95moXY+kU3nkanZ2dnrK9XesS4qL09PSnpWXi/TKSm9PT2pKSlJiYkVFxdTUVGdHBzIzMzIWFhbg0E1oehYMExYXFS0vLY2OjtKzY0aytSfFtgK6Zb4V0ONsm6TiWYXwGMZxWID16B7eYfMOE7XrkbRrd4UJaOHU5CQcepLLOeJi44SnxVTG0wx0XhPi4/Py8pDT2NCAIRQ3Pz8/MSGhu7uLgr+mpmZxYSHj6dP5+XnI8OLi4ujICD0AhWL9/f2T2ordvnkLQx1P059iiElwAkE5TnDz+nXhKeAUAcOJiYnNHKGCHz8WnkJ2luUJrN7eXko6BwnwxfPnKckwDsECrEd34Dba4NBwX/8A/dAIw5HRse6eXgxt/PQIo3r7+vv6+mWZ8YnJ3t4++k2wy80y875+rBIlp6ZnsGgszvYaYjg0PKJmItnfP6DmOGFYOjZzi7bUfhO165FA+YTnItpaW4W3BWzRD5kQ+1t0iXti0781ssbMzMz4mOU14zg/oByGcQgWYD10vJ6dm09KSj575rML586HhoYhSfm6N2FBVSyF5xciwiPoRRyUrzPIz9TMbE9v3/37/vJFHBu8Cau+ITY2Li4uHhYVFd3S0mr80fDA4NCVS5evXr5y+tRpzJwy5+YXgoND1PKWpU/PYKnXrl4btvLGSixzYXHp5vUbtEVkyLl7564N5Ua/R65kSkqqqcpi0Q0NjQnxCcb1304TtcswDOMxsADrwcEaUlFXV/8o6BGEByK375O9UrdUAcbYysqqM6fPdHf3oBPc2dWNCWHV1TXf+sY3a2vrSI9nZufOnzv/9GkGZtXa1i6ntSHAMBTDQqXRVKrhnCD4SXBFZRX8O3fuZufkUr5OgJG8fu06BBIddyydusVQ1uNHj73z1ts0CQzzR38XZxvUm6fMDQUYJeUayqlUw4RDQ8MlJaVhoWH0vTxdgW0zUbseSaNytbmnu3t6elokXEptTU1CfDz5CwsLs7OzzU3NaLhYXG9PL/XhRkdH8/PyMtKf5mZb7unS9ef83LyEuHgUq6+rt0xsYGZ6em5uriA/n5KYydTUFOaPWSGZlJhYU109NDQ0Pz/f19dXU1WN1cAKVFZUYJ6Li4ulJSVYelZmJk2uAwVSkpJFwqVgfTIzMkTCWdBrx9FTJBjGQViA9ahHbVPhgY7KS9CmhrEbKg0KoM+6+S8oYDWMawK5Vi9BGw2j+m1uAhkkGfPRZe5QE7Xrkaj3gGfApgUYoiU8hZLiYuFp0Lu3tKVNt7a0TE1OLi8tx0ZHIzM7M6uo0PLL6dW3blUmJ1m+W9zd1Y2h6XNYEeHhwtMgMa6qqsIQ09bVWn6DGx1lmTl8mhvGTk9NQYmLiyxfL6A7shBFDHU8TXPBizhM9wktdJOQAFt7PI1hbMACrEd34GbzDhO165E8CgwUnqZAdCjfzA1Rv1smz0lhzosLFhGiOVOsIXN+zqJ51O3Gomks5AoFkMRQShetmOkbr9DfXV62zFANYWwJTYvlIp+ezxI5i4s0N5wBUBIF0D82PsOFfFLlzRyhTN//hS2lOW9mV7e1tY1pbwDdzItNGJ+FBViP7ucrbN5honYZhmE8BhZghnEzAQ8sr1oknjx+LC/nIhwCHz5MTEiIi4kZHR1FMjw0DMP79+9nZ2c3NTaFhASj2N49H2MYGR4eGxOLTmR0VJQ2tQkf794tPFez58MPhedSFpeWHgUGUT8VREdG3rt7F86eDz/CMD4uLjY6ZmBgIEi7hPAwIKC5qQmZ2Fc4nGGvYhgWGmrtOnNVZeXm7wG3aq8XFQmGcRAWYIZxM+o9YKDerLVcIdYu1Q4NDiE6HgcF0S90IbT1dXVBDx9iVMZTy29wodyQZzi6e70q8tXTLiczw/wRqs2Toz0OJqGfBdMmR0ZEhIVY3oxN5xx3/fzoB12Dg4M4nN3x81taWoITE215XbYp1p78cgi6B8wwTsACrAdHN8b7ELXrkahPQYeHhUWEWXrAD+77Yzg4YPnGX2FB4eNHj+BcuXQZw+DHTxC0UBd6vwS6ekNDQw319U2NjVBrv1u3kfnp/v0Y6ngc9IgejCovK6McJ7hy2bIOOh4GPOzs7JyanOrbxHstjEqJ7cLGYrbNzc3UDx7VvviEzm5Pd3dLS0t1dTXOKp48suyH8NBQ9JgL8vNJla9q6wl/dGS0qalpYd7yhi8VzDMwwHIGg91COU6AWiABjo2JpRyGsR8WYD30XDGbl5moXYZhGI+BBViP7ulZo01Nz6gv3KAk/ejWmkEAUAYGR2ZOz86pSRcaLW7dsgxLN5pWak7dENo0mXTaMB/bi94GE7XrkaDzKjw0v4mJzTyUa4ORkZEtiq/BLfvIf39/v/Bcje4DzE6AndnT0wOnVrvuTY+RM4xDsADroeM1BGNoeKStrb2hsWlEec0kvYhjYjU5Nj4xOja+uLRcVFQcH58wN79A+TrDrEjJHgY8HBgYhIMZYs72vohjeMT4Ig7Y+MRkX/9AXX1DV3cPRlMm1uHJk2CsOS2RNgQSOL+4FPAgoLOr27hE5BQWFqWnP11YWk5ISMzKyoYSI39p+fm9u/fsfBEHTDcWhgkHh4YrKir5TVg2UO8B4zi+FR9jAEODg1t0KZ6+cLwVVFdXC8/V0EtCNgm9qIR+5Yx626KXdDJeDAuwHhysIRsQvGNHjnb39EK9Ll28JI/j6puwyCxvuppfmF9YPHXyFBQLOZDk+obGgcEhWQYzRCnIW4j2jirK2fhVlDGxcbFxsOio6GbDqyiRzM3LfxQYBBXEKlVV19CsdG/CshgtfXEJypqfX0DFenr7ME96YQhysrNzcnPzsBVlZeVYIp1J2PUqytWVTE1Ns/YqysbGpqTEJPk6T7eYqF2PRP0aUk11dbn2zaK//8GrlOME9Fy0DkhOc1MTnPd2vUc5TvCzn/xUeAopySlDg0Nw7t+7RzlO8Np//Fx4CpERETMzM/19fZu5aX1g7z7hKTwKDFxaWsrMzEQAiCzHoWfB6AIGzkIWtA9JMYz9sADrkYdsKCsEBUOol1Qg9PMuX7p87cpVdCiRRD7EDbJD3U0Y/AvnL9TXN1CSjMZOampkcbQ3XH68ew90y5q22WNi2olJrKFcgZm5eQjt0cNHyp9V0OLkKJmsq6s/9OnB5efrrrcj36Kfq7INLzk5Zdc7746MjMKnTCcMM8Sc1TV0i4na9Ug8odkzTsPVxzgNC7Ae3YGbzTtM1C7DMIzHwAKsR72pyeY1JmqXYRjGY2ABZhiGYRg3wALMMAzDMG6ABZhhGIZh3AALMMMwDMO4ARZghmEYhnEDLMAMwzAM4wY8ToA3uR4MwzAMsyOAAGdnZ3uKAAP58W2GYRiG8WICAwMLCwvHxsY8RYCxHlgbkWAYhmEYrwNdzfv37yclJbW3t2++2+kyAQbQ4PHx8bq6OpFmGIZhGK+gp6fnzp07wcHBeXl5vb29Lrno60oBJhYXFyHDra2tRUVFKSkp0dHR4eHhoQzDMAyz0wgLC4uMjExISMjJyamtrR0cHJybm3PVc8euF2CCHsuCGOM0Aas7yzAMwzA7EEjYwsLC0tKSy3/vs1UCzDAMwzCMDViAGYZhGMYNsAAzDMMwjBtgAWYYhmEYN8ACzDAMwzBugAWYYRiGYdwACzDjJYRVnwyrPrFq0oej+uTofF3StPyJ8JqTFb2pYmEaC0Mpkw2Ht8nqDTlOmEtmYtNmmw+LvYMaaW3/qLD4o4IivVGmOiwoXitpOonR5IRqJhlGKTPZXVC8Wxt+UlhyoLj0RNmzK1U1gY1NWb19JYNDdaNjvTMzUwsLS+77osz0nZSB6zEWu6HZmh9rkimHahIlLUM1X8vR/PFbicsLS2JhHkZ0Wf/RqMajUQ0+ZSdjm+gXTSzAjJewXjJVR9XRdZpqMOPk0k6G15yo6E0TC9OAAE9BdUjVtl7b3GAObZRW2ESApRYaJZNyCleTcpR+kvVmY6xpeYthNTQHBdQylmTJR0Wlu0vKd5dV7H5WCf9QWcW12rrs3r6OyUmxJVuMRYBJPqVBPlV9XZNVDI1aq2VSUmda/sRtDxdgvT55vbEAM94GyeR61TQ1e8qQUUkMLY7WA9YL8DoFMtp2qrJclnGhNlbD1Wto3gO2qouK2VNGb4ZJ5EzM57Y+c63M+vx8bQhhLinbXVa5p6jkfmNTw9iE2KotYNpPEWCLakoFXZVVyyiS5PXCLMWYckSmzBGTj99KYAH2KGMBZrwNM9U0+tLUsXJo6ggz7QHr5GdbFdchc27FHJ/K+iXo1a6nThrXJdePgslJyHT5Jraab7XAqq11u2WOnESddtVHL7ms4uizysKBQbF5rkP0gKWmkiM7wRaVVTLXSq53VLWm5OqE49wD9jBjAWa8DU0mVdXUK6iWQ6Ym5ViZqQ7XytglwB5imzwPcHRypbxd94BdZpuZuZnK6gwrb6LTJVBiv/qGmcVFsZ2bRvSApXxKTZXDdQ71emmomJxclJQFYic8vQfM94AZZodjkE8yY47OjIXNzQ0CDGGT2rZJTXXUnF2cKwRYmUTtlRpnpeY4uiBZ3tqEJvkyx+LsLn12urJqYn5BbO0msAiwRTV1mqol13TXytA8U+kNWx7C4kvQnmWnWIAZL0MRS1V0pabqkqrpMnWTCN+up6C3WSa32hzfHMcE2IGxhqvQLjEb87RvWegNX6vZ7AdY13rAquhKBZWOTpJVwV7LVMqvZnIP2NOMe8CMt6GIpTRTuYVRvnGsTnrXFdjyh7DsLOzZGm+HAK+X1TVfmpJpv+JuWFItYF7Y+WXtLq+sHRkVm+04qz3gVTMo6LrMtXx5k1gxsxyPF2C9Pnm9sQAz3sZ6yYSzTj4NphYwljTJsfd3wFIgyfFsvRTmupXcQIA3lElpKCkLr021mmkZUqYcZbetzW2jTGszNyu8u6QsoKlFbLmDrBNgi7O+H7yWryRlplrAOFYb8iVoTzO+BM14G1IpDQ75Ok2VOeoomaNLWsyZHvAWmZ166Q7tNxFgkivj00xWzYrsmZhSUhVF6YtFW5nhWv6GBVQzm+fqgg6XV4iNdwTxIg6STOmoSfVqs9Go2Frh1czVUXwJ2tOMe8CMt7GqmqqRdtrIJEcdGh0MLY7ZQ1iplhdx6MwhdbRdGGOtFbAxyiXm6MxXy9t1D1jNXPPNSurMdG56U8tovpgKpwIy39RsznzdOiv50lYLoCtMx1b7Wb0HvP53RHJIti7fePF5/e3hdWM9/ylovT55vbEAMwzDMMzGtA3NJFcN6ER0M8YCzDAMwzAO4CoZZgFmGIZhGMfIbRzRqakTxgLMMAzDMA6jU1MnjAWYYRiGYRymoHlUJ6iOGgswwzAMwzjM7MKyTlAdNRZghmEYhnEGnaA6aizADMMwDOMMOkF11FiAGYZhGMYZdILqqLEAMwzDMIwz6ATVUWMBZhiGYRhn0Amqo8YfY2AYhmEYZ9AJqqPGPWCGYRiGcQadoDpqLMAMwzAM4wxHY5qt2TErSTX/OAswwzAMwzhBbc/kZqypf4rmwwLMMAzDMG6ABZhhGIZhHGBpaUl4m4MFmGEYhmEcYHJycnl5WSQ2AQswwzAMwzhAe3v7/Py8SGwCFmCGYRiGcYCSkpKxsbHNd4K3Q4C/9rfn7LSX37gvpmEYhmEYjyQtLa23t3dxcVGknWU7BPg7u7LtNGiwmIZhGIZhPJLY2NjW1tbNX4X2dAF+QePXfu3XRHoVZAqPYRiGYbaRyMjIxsbGubk5kXaWnSHA4MCBAyJLAznCYxiGYZhtJDw8vKGhwYcEGMzOzopcFmCGYRjGTfiiAKsXopGUDtHa2orkb/3Wb1HypZdeQhL9ZkqCoKAg4b3wQm9vL/agSLzwAnwU/tGPfiTSL7zwve99jxzMEKPUaZEkRkdH1STDMAzjC/iQAP/DP/yDJnwW5IVo+NIhNhTgV1555Utf+pJIvPAC5Pa3f/u3RUKbmyrA6G3LsefOWdaKfLB7924kwde//vV33nmHfIZhGMZH8CEBpqGELkTD0cY7IMAbJlUBRlLtIiMJuRUJLQmkwzAMw/gOviXAvb29mvBZoAvRcLTxWyjAmKFIaEm64EwgeffuXfSn4TAMwzA+xT/vvbbrZsrBsNqj0doXBjG0OE1Ho5ssnx2Mtjiw4/Gd03O2fits0ZKtRqeyNsyaAINXXnmFxA+QcFI+5YCtFmAgEtrlawxpiQzDMAzjBEJaNontT0PoVNaG2RBgoGnfGrpMksNf//Vfp+RWCPDx48dFWoMyGYZhGJ/inz++uut60sHQqqNRDTbsWFz75MzW94C3R4DVC9GAMkViVYBFYgvuARMibfhdMsMwDOMj+KIAA/nrIEA5IvHCC++88865c+dEwhUCLJ+6euWVV5Ak5HPUIs0wDMP4GD4qwID0D1Dy2rVrIq39QMhV94AlurdglpWVIfO3f/u3RZphGIbxMXaSAENW7bRv/PMVMY070PWArYGxvb29IsEwDMNsL+/Hvfhe3It7s/5wpS9sIP13dLZc+pV/z3z2Rf/A31i133wS9v8Ltrxtaeh+UuP39/e/eozmQ3zrSPZXPk5X7etHysQ4K+wkAd4p2Bbg+Ph4DPPy8kzHMgzDMNsD1BcabBHgnkeLJV+B9adZpHc8+7/DX2n62o8yK6C70OAvBj75zdAo8r8aEjHmn2IR4B+YCfAnGX96Ko/sexerxTgrsAC7HtsCjEy6vs3dX4ZhGDcC9YV9AgFeBb1eCPBE/SFK/mNaOhT3NyNiKfliWJRFjAMezT5MtybAXztcItJ2wALsBmpra4XHMAzDuIm1S9CrLJVoAly3l5L/lPbUcuU5OCK3r//jwuIvPgqxCPCjkLnAp1Z7wHvSvna4+GuHYCXZ9cNinBVYgBmGYRhf5P341UvQq+gE+B/TnkJxLVeeHwRZpNeivqGJnV2D9xJt3AP+3U+eftViGflNI2KcFViAGYZhGF9k7R7wKqY94C8+fPxyYgrsrxNTmscnkE8PYQ28epyKEd86nLVll6DbWIAZhmEY7wECbNcl6PAYSkpIgBu+vw8aPPjqcQwH/ubwn3xWpPWAn/7Bp5m/f0CYmMAK3ANmGIZhfJEN7wH/o00B1jRYWNsrB/7kTCEJMF2IJhMTWMHjesB/eWCFzbWWzjAMw3geHtcD1okH2+ZNVDXDMAzjSbAAe7+JqmYYhmE8Cb4HzDAMwzBugAWYYRiGYdyAxz2EJTyGYRiG8Wq4B8wwDMMwboAFmGEYhmHcAAswwzAMw7gBFmCGYRiGcQP/su/me7fSD0U2HIttExan2XrneFLvxMyCmMYMFmCGYRiGcYCARyHFz2r6RiZHpxds2PDkvJjACizADMMwDOMA4eHhDQ0Nc3NzIu0sLMAMwzAM4wAswAzDMAzjBliAGYZhGMYNsAAzDMMwjBvwIQGenF8+kNHznYAGNjbPMbRJ0UAZhvExfEKA55eev/KkSXfgY2PzHDud1ycaK8MwPoP3C3B534zuYMfG5oH2w9AW0WQZhvENvFyAszsmdYc52JsJHVeLB2FwdKPY2NxoaJCi4TIM4wN4swAPzyzqDnDoDYtxCk0jc7pibGzuMjRa0S4ZhvF2vFmA1ePahtf3nOgNfy+w8Vx+v6N3lzEJTJfJxiZNtEiGYbwdrxVg3cVnkbuycrV4UM3fk9YtRqys/EtEqzrKaCiz9Py5TP4yrh05e9O7ZQ4ZhBn5lQP6e8+6511RYG7xOZy/etSEYXzTOBXTRq5ROzgrPLNlkdF8CDohMF03KiaTaW0Tsjyb55ilFhmG8QG8VoDVI9r8ktCnvwhqVPOl0VigyycjMdMBvbQmwJSPhery7RRgaSTkGwrw2Jxlp5FPxSS68pQpkyzAnmmmN0oYhvE+vF+AIbqU84vYdpkZ3TCW2Dz+w9AWmUNlbpcNyRzV7j8bogIE9W6tCXDtkJBMo7YhE33o1jHLpy0woUt6wMiXvW3deqrlaSngn8LFVrMAe6YFVQ1TTTEM4914pwCrj19BaCmTkrqbwVJxC7unKIeSqukuKVNHFtpmKsA0dmDa8iiNer1ajiL9g9M7uaBeOlYFGKPIh9HSCaMA69aNBBiLMK6bPC2QXXMSYHC9ZN1leTb3mu4simEYb8U7BRhqKg9nfVOW7xjLW8JUQIXy0T9Wk6qRmEmVkh1Wo8glt1gkjRSOxgLZxSQBxnxoDtYuQcO3hlGAYTRK9SWyPB3TsWhaB1oWCXBB95TpbNncZSzADOMj/PzgjQP308/H1V9Obr2c0moZSlOTOt8wyrMEGL1eeTijnKCqYTWpQvnySjUlVaNepuw4UldS18uUF3gvFw1QMTK62iy7wlSGQNL2PWCdvZ1o/py2VHpC9msBrRvlSJWl8uij8yVozzQWYIbxEf7546u7ricdDK06GtWwGfMsAVbfftUxbpHAmsFZSsoHsiSULx+HpqTOzqx/UyCJpbEHLA358rKw0UjzIKgwo/7pBFXFRlf1YuFAdMOYTNpYN2kswJ5pLMAM4yN4pwCrTyBfLR6kTErKni4B3aV80um+qbWbrxuacwJMl6l1oD+qK6YzG8vCqO6JBd19XF150zIswJ5pLMAM4yN4pwAD9YhGOUeze2XO+YJ+9QfBpk9Kb2hOCLB6C1baz2Is85HlabamWBNgjNpQgI1l2DzTQmtHLJXNMIy347UCrL5Vo2lEPGOm/u5INRoLdPlktnskJHI2VBPIe8AkwOgEU5LsRE4vMnUCbL9Y2lOeBXgHGf8OmGF8BK8VYN2LoEXuygq6F2o+usJihBX1tWGkaqa9Uhu24SVo+TyXEdMHtWyUl4pro4z8WTCbh5ioGIZhvB2vFWCg6++KXCtYe0kWG9t2mu4ZBYZhvBhvFmCgO7qZXkzW9YnZ2Nxo/DUkhvEdvFyAjV8kJHsvuQumy2Rjc6/RIwIMw/gIXi7AYHJ+WXeYY2PzQJPvYmMYxkfwfgEm5O992dg80Pi3vwzjg/iKABN8u5fN04yll2F8Ft8SYIZhGIbxEFiAGYZhGMYNsAAzDMMwjBtgAWYYhmEYN8ACzDAMwzBugAWYYRiGYdwACzDDMAzDuAEWYPezuLj4e7/3ey+88MK//uu/iqyVldnZ2c9//vMisQpKfu5znxMJjaysrFdeeUUkbIL5C28VPz8/ZBo5cOCAKKFgWnh6ehqjvvCFL5ADWlpaxDiFgYEBjMKqms5ZBxZkWqynp+eb3/wmzRBOa2urGGEABYSnYW2GRuzcmbZnaByrWx8dG441RYy2A5fvT/ubHPjyl7+M2ndoEmLXrl1BQUFwdEtXG5gaC2ojdAK5OOLll18uKCiAg8W9+OKLlKkiCxCm0QqwksJT9puaaQPbW2Qca+cesFYXurWys8rs3JY333yT6quqqkpkrbYNkViP/TGrssk24BZYgN0MHVDKy8vhX7t2TTZo5wTYhv7BoTK22bDp6w5VwLTdG+eDVTWds27FTFcAxztsOO0lUFtbi4WaHhmB7RliH1p2ioKcj25nWtsVpvlYHzE7BapBOFTGFNtjTXFohs7tT9OGBGyoKeZJZdB0yYFE2SPAulaNCTG0JsBqMiEhwbKYVXSNUOQaEKPXY6cAi1msB7t38wJszLQtJ8axuhzLmq2H8tW6cKKWdaCw8KyDMj/5yU/g4JwPvmyNNgQYo0z3J2Ftobb3mGfCAuxm0GjUVojDJZoXYSrAyBcJDWtxgvnoZFI3IVCXpWKqOhIcm3QFTNs9iulWDKtqOmcsUXgapoKhK0OomfKgrwOHUdMZStS10u1MaxPanqERrIbwDOBA8+Mf/9j2scYUMdoM3Vjn9idBwoz83/7t35Z9F2tNDjVOLRl1IUXLtQIMwdDNR4618+Br3EbCKMAoSVg7z1PRCbCYUgFj5U5AkoqpGDNNt0ibmR7a7bb3AIqRY6wLh2pZZcPWCzAf3Q6Ua2JNgF966SVMghr56le/KrLWI+egw8424FGwALsZXWOSBy/Tc2ocTFFebbXW4kR3QAHGVuuokADZfRRpDRtHCjhYQ/KB6eKQLzwNa4KhXrwCHR0dugmtYXszpWwA3c60NqG1fH9/f8tGroIk5cMnR4X2JM0HM4QCmR47TKe1jW4Sp/cnrRVdmkbfBbVMLUpWqG62O12AMUrF2iVo0ioJ1bJptOqQOwFTUY6KMdP2FhnH2i4v529s5A7VMmFn6wUYa63KdALc2Nj43e9+F2Nl4NAVjm9/+9sYRTmEnIMO23vAM2EBdjO6xiQPMaYhjcLU9EXa5tHQ2omnBLFB0+qwcSjBWMQnTSjburHdYyyOX9gW9cCKVTUGMzYThdU4xMyNxaTwqxiDzbTjYjpDCUoKz+zYZDqhtXx1VkAmLWujQUmc4MNHb4OSBDYQuxH5urN+bToT1D2m4sL9iZ1JIkTInaPbS5LNCLBYg1WQaSrAAEm5njYuQZtuICFKrEd3wiq3XSfA1s4ATKOV5AT6QUm5E4zrQLVGS8Qeg08YW7jEONY5AXa0lh1qvYA2TSS02codpRNgzCE8PFwkFFJTU7/0pS+JhIY6QxXbe8AzYQF2Hmpz1lqDnSDy1YYu5wnUkKYDCrVX6qxQY7UWJ9oM1q0Y5QDn2igtVB7KERUyqbZ7XTEc/ZGk82usqlEJEP+nT59WN4EmAboTCDVcTY93amwDlKfFWdNLgKXL8wlCtyamE1pbQ+QIT0Mmdflbigv3p6kuAmtNDoumGWJuqgDTtKaTEFiQaQ+YJgSUT0ACRa6GbHi6gy+tvEjYgVGAaf5At9/UCAXUQkhmgCwM/8SJE3Dkgx1yv1FSBUv/5je/qasC3Rap0NbR3NQdpZYXWQqUr6s+R2vZCXTnSSLXIMD2o85ExcYe81hYgJ2H2hPYZK3TSSVBTysA9ZhI4a2eqCJsKPJN4wTHXGQiMlX9wByEp02lLc0W6vEIYBLdRUuJ2u6xYrrTWIQfjcUcdHomj5I0JHSyp63LBlBJHDTVXSR3oDUFQr7ukKfbmbo1kdjIpwURti9BbwjNxDai6Cqu3Z/WMG1ywJoAI9PaJARW285L0DbYvABbtlzBtAcssdbYCN1UtGewE8Ss16+YWmvqPG3ICfYq3e9QBUxXXrcUie26kNhZbDOoAoy13RAqCVRfZScKMI6WDQ0Nc3NzIu0s5nvEUXywB2wNXUhbwxgn6qEHjtrEyZHoBENiqi4OYXrYwqrq5oxl0eqhvDwEW5O3DZGHbAKLo3UwnSEy1YM+oduZ1tbE0TXEZgpPW4S2j22hboXIMiBGrwf5LtyfgM78jJgemrdNgI1iSRgF2BSH9obakuGLWRiwU4BpJ6A85RNI0pbSOsvTXGtyIpsurY+18rqlSIx1YX8tO9p6twgsRXjrYQHeLD54DxjoDkCEUYBVZZUYwwllZCuk0KKktVarw8bx2sZBTdfudQcgAquqzhlTqUkcVWknmK4AXdnWoeuR0+pRv5OukNNa6WaIYghU4w4Hup2JCbXlrAPHFxu7CHojyq1HjDbD9lhTTCdBpmv3pzWMTY6AzNB82tvbyUEbsFOAqbwEmTYE2BQbB18b9aXDuCzTlmzEGK2Y1YaXoGnD1flTDvWDTbeIrpaJxGo90o5yWoBNsbOYtaUY0dWC6daZzs2YiRwjmJuNNuCxsAC7H0SdqR7ooOAUCSvgeEG9EAlClBqlcVpTgQF2Hq0kxnZP5+ZG1DnLi+2S/fv3Y2h6uMS0ukVY2xu6J1+AboaYUF4c1mHnQcfGAV29qiYxXU/JhmNNEaMVtmJ/2t83soY9AmzKJnvAKjbqSwdmIjzrGLXWGvY8hPX6668Lz4CpnLz66qvCM2AUYCMoYKyLzdQyiglvI9AS1FMNTKhebye0xZogRm8EC/BmYQG2gT0CbAPjtDgwueR6kakAb9gDtsZmBMMU+4+/ninAwnOWzexP+8XGGlskwLbbLSbZEFF0PdbyVZzeJ6YCbANH5cTO8qYC7HQt27kttAg0Bqo4tMkPP/zQeNAznZudiwAswJvFZwUYjcwUUULDzmLWMBZDGNDkOhyNRlMBFvNaj9MCvJlLpjb0UodLBFis3HrEaDM2HGuKUeatsZn9aa1vBESJjdgiAaZ10GFnLdtAzMiAGK3h9D7xZAGm9TciSljHnjLqud13v/vdhIQEeXNEd5quLdMEMXojWIA3i28K8PZgfzt2FNe2e/v10k62U4CdYOvqhXD5/nQCJwRYstX7Z/uxc4u2TYA3gz3bortsrt4eghjbfyq5ISzAm4UFmGEYhvERWIA9FO878WcYhmFUWIDdDIRWh8wnh2EYhvFKWIDdjDWhZQFmGIbxbliA3QwLMMMwjG/CAuxmWIAZhmF8ExZgN2NDgAkXPqbPMAzDeA4swG4GEiu89VjLZxiGYbwDFmA3wwLMMAzjm7AAuxkWYIZhGN+EBdjNQGh10ItS4VABhmEYxithAfZQVAG2/8s/DMMwzE6BBdhDYQFmGIbxbliAPRRWXIZhGO+GBZhhGIZh3AALMMMwDMO4ARZghmEYhnEDLMAMwzAM4wZYgBmGYRjGDbAAMwzDMIwbYAFmGIZhGDfAAswwDMMwboAFmGEYhmHcAAswwzAMw7gBFmCGYRiGcQMswAzDMAzjBliAGYZhGMYNsAAzDMMwjBtgAWYYhmEYN8ACzDAMwzBugAWYYRiGYdwACzDDMAzDuAEWYIZhGIZxAyzADMMwDOMGWIAZhmEYxg2wADMMwzCMG2ABZhiGYRg3wALMMAzDMG6ABZhhGIZh3AALMMMwDMO4ARZghmEYhnEDLMAMwzAM4wZYgBmGYRjGDbAAMwzDMIwbYAFmGIZhGDfAAswwDMMwboAFmGEYhmHcAAswwzAMw7gBFmCGYRiGcQMswAzDMAzjBliAGYZhGMYNsAAzDMMwjBtgAWYYhmEYN8ACzDAMwzBugAWYYRiGYdwACzDDuBK04fzCovyCogI23zBR8QzjOCzADONK0IZTUtPn5uenZ2bZfMFExTOM47AAM4wrIQGenpmZmJxi8wUTFc8wjsMCzDCuRCfAk1PTMHmw3gqbmmaxd6eJit8CsnPy2HaEiQpzHBZghnElqgBPz8w+eRLc3NyyuLQ8v7CoHrWlkUJb02nMAtMuLC2bju3t7aurq09KTMJwbHxCNxY2h6UuLWOoy2dzoYmK3wJ0C2LzWBMV5jgswAzjSnQ94LKy8mNHjlZWVYeGhFbX1MqIhUFTGxub/O/7Pwx4CIsIj9CJKAp0dHTm5xckJCTm5+Ube7qz8wsJ8Qk/++l/tLS0mvaDKyuriopLLpy/MG4mz2wuMVHxW4BuQWwea6LCHMdHBXhoaDgvvzAvv4DN5yyvQDSCrUEnwIWFReXlz6Zn5/oGBsPDwmfn5mXQQl9b29qRGRUZBUtOTjH2Yi9euPjsWUVOTm5cXDz607qxsJnZOeQb1Xdyeqa5pfXWzVtNzS3nz53v6e0z7UOzbd5ExW8BugWxeayJCnMcHxXggYHBoeGR0bFxNl+zzUSLPagCDHVMSUmtqqp+4P8gKyvbUQmErEK879y5CxVPTEwaGhnVFdjQoOvBT4IxeV5evm4Um6tMVPwWoFsQm8eaqDDH8V0BpmMxm6/ZVv9uRNcDJtHdTO9zM3PAVJtZNJs9Jip+C9AtaOvsnbfe1uWgd6LLwQETfRZdpnP28//4mS5np5uoMMdhAWbzLdtmAWbzehMVvwXIRVy5fOWjDz48dfKUzCGrqakl6+3rV/OfPauICI/AJNDRxITEpKTk3R9+9OjRY7UM2fu73oPt+Wg3/NDQMBTDtPA/fP8DZO77ZK8s+cNX/46c+PgEjAoIeChHbWgx0TGY5PHjJ5QsKyuXo7zDRIU5DguwC2xmdo4c2VkxfSLGthl7KnImNGp6dk5XRubo8tls2PYI8Nz8HJbE5gsmKn4LoBaL4xQ5Rt3q6uomM/ZN6xsaMTxz+gyG0D8MjZ3a2JhYcn7y7z/CkBZUUlKKoXGGf/93PyRnaHjk8qXLkG05akMbGBy6dPHSO2++JXP6Bwal7wUmKsxxWIAdUC9ZUp0E6oszzbn5BRzZ79+7Pzs3jxPSkOAQWQCG8jQJDWVEScO6YCo4siQM560zc5YXKqWmpkFrDx74tKiwiEZRSeQgWjC3xqZm5OAsGIVlATZT22oBXl5ebmhsQo2w+YiJit8CZKMl7Wxr75A5G1qDIsA/+rd/xzAoMIhGoadLTnV1DTmv/s3fYtjU3ILhvbv3MDQK8Hf+1/8mJ0yb/OjhI5RULTIy6slqN1c1Uvr9e/dREnpMjteYqDDH8XUB7uzqzsrOkZonDU0EeoZiMqe7uyfjaQby6+obSkvL1Elyc/Mgw8gpL3+GIcQ4KjJKjsW5Xnr606dPM6DNyckpiKWW1ra8vPzBoeHmltbunt6e3r76+gacV2La2to6zAQqsbC4dOfOXeTAz8zIHBkZxWF9QlkoyiNgUGB+YRElUQzLjYuNkwXYTG2rBZhhXIVstDhE3PG7Yzxxt2aQ6vz8AjhyqGpeXFy89IuLSxITEqlvjUPT7Vu35ahHjx5nZGTKJF2ahjU1NUPLW1vb+vsH5FiyP3zx93Q5ZOiOPwp6hOMedXzf+OWv1LFeYKLCHMfXBRj6l5SYpP44hKy9vQONprWtnZLQ1wcPAmpq63D8jomJraquGVWu52Rn59BV6MiISKgg5qYKMM4lOzo6Ozq7sMSent6wsPChoWEsF8vHqIT4BAyHR8cqKiqhDf73/dFSNZmYowtHiD2sKAyThIaEYgzGIh85Pd09OBtFDs5zsdzFpWW/235IykWzGY0FmNkp6Jquc5aYmPS2cu13Sw3arMvxERMV5jg+LcAQuSePn6B7CvXS7VBIZmNTM2SYkjhuo69cWVkF2cvOysZYqCb6oDQWPWDIH8rgXBIyCB/aSTIJg9CiswuDbOMcMzwsHIuGoQCGpJfTs3PV1TX4H/wkOC0tHTlQ8YjwCDjoiGMqLBcrCQHGEGcMUBHKCQkJxVac/ewsCTBOk+Vy2UyNBZjZKeiaLpvHmqgwx/FpAcax+NzZcxfOnW9uadXtUJ1B5I4fPXb40GGoXEJCYmRkFKa9fPkKjuc4on+8e8/VK1ch2J/s+Tg+Lh6256PdtbV1NG1VVXVZWXl5+TPYscNHTp04CaU89OnB6OiYkOCQY0eOYp7nzp0/sG//xMTk3Tt3kQP1hZ7Cx8yxaPSSp6dnUKCurn55ZeVf//lfkDmp5TTUN2DygAcBtCbqJSM2U2MBZnYKuqbL5rEmKsxxfP0SNA7HMPxX96apUUl0ZFNT06B/lCNGaW8jwn8MkQuj55NpEhpFRkmaVpRcTZIjc2ClJaVUDPptyV995lk+DEk52I6e3j4ksW4oRqPYrBl2qWgEWwPa8NPM7KcZWRmZ2Wy+YKLitwBd02XzWBMV5ji+LsCOGiaSV55tG+Z/FP3dk6fUy9EOmZxKN7lzc2Mj2wYBTklNn19YwFkamy+YqPgtQPfJHTaPNVFhjsMCvIWGYz11YXX5bG607RFgfhGH75ioeIZxHN8VYLoCzeZrtqVdFqAKMBZn/D2l0YwP4RttyHX3F7BWclbYHTKfzTkTFc8wjuO7ApyTm8/mg5a7jV9Dgr7FxsQ2NTXT4wb4k0dtaQuLS1euXJ1f/VowypAoSmmc0pyW1raABwHIxAjMDeNpbjOaeMskTYX/8GRSdeAVFRalpqTCHxkdO3/2nFw0m3MmKp5hHMdHBfj58+eLjK8iGsHWoAowrKSk9NTxE4NDwykpqUVFxSSTqkEaDx86DC3s7x9ACuVDQ0L7BwYfPghoam5paGh8/PgJkrdv3Q4LC2/v6MTY4dGxrOycnJzcxcWl//jJT1taWhMTkxobmyxafvlKRWVVdU1tSnIKOta3btzEtBBv//v+tOil5eV//cd/wnrCx7JjomMsz9ivyjObE0b1zjBO4KMCzDBbhE6A8/Ly09LSZ+cXIJOxsXEzs5Z3RFdWVkEvSREXl5aPHj6CCcfGJyamph8GPOzt7ZubX2hobIqIiAwPC29sbkGyrKw8KDAIE0JKy8vKoeXNzS1Ly8+PHT2GOZQUl1RUVM7NzxcUFHZ19+TnF9y+7YeuLeZcWloGe1ZRSeuzvLz8z6sCDN2NCI9Ab5gFeDOmVTvDOAMLMMO4ElWAIWxQSvRB0W2tqqomnZuamYVAQkpJgGHDI6PBwSHZObnjE5Mog45v8JPg1tY2+LC6unpMPjA4BC3HJJhbSEhoelo6BLu7pxeZyIGcY0Ezc/OQ7ciIyOSkZFoWFD0xIRE5KEPLwjqVlz9LSkyCj273xQsX5/gS9OZMVDzDOA4LMMO4El0P2ANNOzEQ3++y5/kvNtsmKn4L0C2IzWNNVJjjsAAzjCvxfAFmc62Jit8CdAti81gTFeY4LMAM40pIgPlFHL5jouK3AN1Rns1jTVSY4/ioAA8NDRcVl7L5polGsDU8f/68t6+/u6enu6eXzRdMVPwWoDvKs3msiQpzHB8VYH4Rh8/alnZZGMaFqId458z/vr8uxyGrWv1iP5ttExXmOL4rwNvwKko2DzQosGgEDOPZ6Jquqe35aLcux4V25fIVcn76ox/LTDajiQpzHBZgNt8yFmBmpyAbLX1m9K/+/C9kjjRVgM+fO4/hO2+9jeG7b7+D4e4PP8Jw3959GNbVN2AIy8zIxLFvYHAIPn1a7cb1GxhGRkRi+Obrb2AIU9+ievH8BemzGU1UmOOwALP5lnmaAJeXlQnPCuGhocIzY3l5OSQ4WCRWVm5cu1ZSXCwSKyuhISF5ubkisbKSkpxy8/p1kXCE1pbWyPCIwICAyckJkWU3z58/v3vnTnlZ+eVLl0WWI0xOTNy6cSM9La20pERkOUJaSmpuTs71q9dEej0jw8PnP/ts2w47jkItdmR0TLZeoxl7wCSc/f0D0v/pj38S8CAA1tTcQmVgra1tGEKGg58Ex8bGwacyMCrQ0dlFDuze3XvSZzOaqDDH8XUBxgEZ/9Vdyebdtp0CXFZaduTQIb9bt548enTvzh007+bG5rTU1Jjo6NrqaihTQX7+vo8/SU5K6unuRvmO9vYL588/CgqMi4kdHhqamZlJS0nBWJpbSVHxyePH4bz37q6pKRHzD+77t7W1kQ+wFOFpxEbHCm9lpamxERYbHYPliiy7OXv6DDlXLl0ix34gcs/Kn8HBNpaVOvwEHPYeOY8fPSLHIe7c9sNwbHQUG045OpISEz1cgGHolRYVFb/z5luU/C+/9X/J7umpEydLS8tIht/41eslJaX7tf7ux7v3wD9y6HBSUnJxcUl8fAKEtrq6JjwsHDn1DY13/O6g2Lmz5woKCgMfBtLk6BB/8N778Mmo5w37279+RWayGU1UmOP4tADjYBwdHXP3zt2FxSXdDmXzVttOAYaIZmdnV1RUdHd3x8XFzs/P3793Dz3Uqqqq0OAQKhP0MJAcIuTJWneWSExIEN7KSnFR0Se7d4+Pj4v0ysrePR/Pzq5tkTUBRmQdPXwYC/1g13tqeZXGhkZrB4KzZz7DcGlxCXpPOTr6+/qxsSKxnuHhYaw2nOqq6vr6espUTwLQiUc+hiK9npvXb5Aj9xhYVibH3ujo6BAJAzQ5zlFysnMoRwd2r3rY6ezsHBkZEQl3o2u622+HDh4ip6urW2ayGU1UmOP4ugAHBT1Cf4I/COM7tp0CXFlRgeM71Le8rKyosHBgYOBpejq6IJkZGcFPnpAIoUBYSGhqSir80tLSoIcPE+LjW1tbkWxrbY2Pi0PvOT0tDeIXGxOT8fQp8u/cvt2+2usd6O9Hf5p8cOvGjcWFBZFYWYkMj1xQkg319QH+/jgPoOTuDz+U13VxFPjhD36gCpsKJgkNDo6KjHq+IgpgPR8+CCAfG/JHv/8Hs9YPIlhKaEhIQYH4DhXC/PVf/hLCTEn0QdGNI98UTIudJsvn5+V9um8/rSkW/X9e+l90/cCU3p6ekODgNG33Evv37pWX/aH6UZGR8rCDRfzN9/+afE9A13TZPNZEhTmOTwvwzOxcYkKi/31/fiGf75j3PYSlft9pZmZmcnJSJFZW0NlVu8s26O11/veskxOTWK5IOA7OIYTnOAvz8+r2Ogp23ejoqEhoe8/a5QG3oGu6bB5rosIcx9fvAfcPDA4ODfNtYN8x7xNgxlvRNV02jzVRYY7j6wLM5mvmIwKMfmGncmf0WXn59PS0SDjI0NBQbU2NSDhOWWmp091KTOjEc1uSxoaGvr4+kVjPwsJCR0fHVn8cepPomi6bx5qoMMdhAWbzLfMRAQ5+/HhMu7j6/PnzK5cuQWnKSkrramtprP3kZGfX1tZCCI1Ph9nD/bt3EdShwSG9PT0iy26ePXtWVlq2vLzsd/u2+tCWndy+eXNyaqq0pKS6ukpkKWCGdXV1jY2NIs0w7oAFmM23zEcEOCIsbF6L6vHx8fS0dDiD/f1VlSZSZJvpmZlrV66GBAd/+N77IssRHgcFYTg1PR0TFUU59pOVmUld58yMDPmzK/u5cO4chvPz848DzX+/hB5wc3OzSDCMO/BdAdb0V/+iYDavNx95F7QUYHDh7LmFhYWn6ektLS2U88Dfv7Kignx0Mf/p7/++q7OTkjroIeqKigr5c+RnZeUPHzwgH0CeMTeRMHDvzl10vtEPls863bxxo6O9nXzw96/+nbWnqNBfx6nDwsL87Zvip8ADAwPnz56TP1jCFn30/gfkG/G/f394eBgq3rq61TgJoMfICZ0AHz10GDMUCYbZFnxUgPlrSL5sohF4NYEBAeortJoaG9Uf2o6NjclYS01NTYxf+6mxDghwzfobwJhwfEw8WY3u9Ws/+zn51mhqbFIvIE9MTMhkfGxcVEQk+aZgWc1NaxqJCeWPkcB777wrPCt0d3VPTqy9ugv9aepSA6zGndu3m5qaKDk/N//2G2+SzzDbho8KMMMwDMO4FxZghmGYHQm9aNOUX/7iF8IzIN+gAoqVN4cfPXxYvqTlwrlzFc8sLxC1k7def6Onp8ehp8rffvPNzo5O9cLMhux6+53W1laHnsj74L33mhrFdQ6V8bHxd956SyTcBwsww3ghqSmpcbHiPZTPyssjw8OfPHrs0JFL5ca16wMDzrwuIzkpWb5L0gkCHzyMjore8HsVpoyMjDwKDAwLCVXfBSaZmpwMfvwYmiHSngoOiYcPHnz/3V0fvv8+NmR6evrA3n17PvwIoyCQ3/vOn+775BN6C8rHH+2uqa6G3sAPDAj46ANxd/znP/0PFMAk8hWbn50+TQ6YUC7R37pxU3iaPjkkwIQ6Zzu5fNHht4v73botPLtRzzkk+/fuFZ77YAFmGC8EirusRRMO2VGRlvus2kcRyrWRjhHg79/d1e30T4EfBwU5F9dPnz4l7YyPi5f3bu3n9EnL6y0nxsejrTyADfXdEU9BPwoKys2xfNKqUHuX510/v9AQ8VpsiDE5APqqnmB9um+/8FZWdn/wYXdXl0hoL+UWnhUBht5j6IQAow8tPLtxo2azAOtxiwBTkOM0Uz6RAdJSUymAt4JRw9veAwMeCs8Kg4ODJ4+fEAkHd5TaztQQ3a9Er22c+wkKwOKOHzkCDTh+5KjIWo88sGKLcC4PZ/n5ckyU5eXGez+2JNWmqe4BxjbyKeipqam42Dg4w8PDFatPPhux1jk+f/ZcaHDI7Rs3kxITRZYB2x1r9MZsF7A29ml6OsVmanKyE6+6pPhF2wsPC6McHcafITl0OXTbUAWYYmRo9bsXamjrviEhBXhocBD2/i5Lz5gIVb5faa0HDKQAR4SHkwP+4rvfM91LmRkZGMq3pqiC980//CPhraeosBBDeWKHEwtywB//0f8Q3nro0X16Uzq4d/cuOeBb3/im8NYDecNQXurwv3+fHKDuPWsrudX4ugDPTE+HaKeT9D53VO3S0jJqK/PpU13MF+Tn9/b2tra05GRnz8/PLy4sJMTHI7+5qamjvR1r3tTYSL+zzM3NVU/Y0cJamltw+BsfG8vPy0fOrZs3G7VmgUNAcaHlQzE11ZZzUmRiPoMDg/CJvr4+Knn96lUUpkyAIym1RfRpsCyc3ra3tdXXWT41g8OWvJFD4NwCQ8z54vkLONjhoIN1Rk5ujuX7MMina5VoBPRTE2y+rqtEN0va29qTEi0FsJdwsoLlYg55Obn9/f2VlZXYwP6+PvS65O9bQObTDFp/GQAZT59i9RDDWChWJiU5ub6uDvnyKFmQX4B5wjmlHUDRb6PYBlcvXyGH2RD0gIWnNQnsZ8svghYst+iw23/205/Ko2pfb+///MY3lpesas/i4mJkRESB1nRBSHDwaz/7uVTNP/+zP6OPHZmCYDl75kxCXNzY2Bjl/OCVv6GeHECI/a8/+bY1AUbu7Zu3oL7pq78Oaqir/9P//X/kjcYD+/b5W/k6E+jq6goLDX0UGDi3Goyf7NlzTWlCAwMDqgB/9zt/OtA/IBIeA3YOAgRnUTgXqa+vR/LJo8fIp5+NIRNJOmyiGAw9fvh1tbVklI9ww1D+EuztN9ee97YmwDjayE9XZWdlkQP+9q9fEd56cDSQcQrkw+04ZjY2mL/tBOdGaB4isbIiL1Tg8KJ+YVNlcnKSzkWI2BjxiUlsqTzC6MAOke0NJMRZDtqEKsCq/G8nPi3AaNZZmaJtjY+P4yiDCo6Pi4NCIDjRdFQNrqutg8zgWINGHxUZiTI45Zydmenq7EJzgfAEP35cXlbW39c/ODCAyBeTaQ0L88QREDOvr7WITXxcPO3xk8ePk1RTS0I3NzE+gc76ibzc3G7tzCBaWyJlApSkCZ88foytwKjEhISO9o7Ozk4Ioe4Ld/TLjXOfncUQexiKSKFFcYUcbAi2LjQkBFuNHOwHaC0cCb3GCCuJdUNzQZcIeo8OlmVGdfVYGWgwjvI4MccBIl7rbxGWtqWtJ1YMw5bmZqwqjuA4IuBw0NLSUl1dTbviyKFDFLTpaWmpySlw5Bk9CtAtHHq1E2MPba2t5WV2XXDGOSUOhSLhIDh8V1U5/HIPCfpYqgA4SknR2gNEjoLwKSoskj9BRrN07oP/jG3Ub13YCR2vHEJeEnCObdYdFV/vAZeUlEAb6KJKRFg4nEsXLsCns2z1SzKIWPTSqrXDTUpScnxsLJQP6tKviRaYmpzC6RU0Bocz9bCSlZkJqcvJzgkLCW3VzriTk5JplPzhf2qKRXKwUHRSKQdgZTo7OukkIEn5KCyQ/YmhwcG4GEv/FUuBfKK3jfKmB7Up7dwC6yzPKqgHHBYaghXGKSTa/dDg0OjIKLba9AW8mRmZGKIkdhROC7C2XR0WyYdSYomFBZYLSmkpqVglOFgQhu2rr1yg81PqDUNicbqA1cChX55l40xiZnoaAg+Zv3HtGmUCHBnR8bXWSWIYhtm58D1gyyU4SN3Rw4dxsnb+s7MQWv979/Jz886ePiNKaJw8dhx92cqKisCAh9AbqMitmzdzsrOvXrp85uQpFDh75rPrV6+SE6C8G+jIwYPo88EC/B88uO+PrklxUTH6vhh1YO8+aDD6l5/u2/80LR2LQE2Ehqz1nkOCQ27esDxEuu+TT0IeP6FMAEE6fvQoZgUfc8YQuoVVgnP65MmQJ2slVbBpmBAzvHn9OqTu4IEDWq+9/PrVa5j5o8DAE8eOowD6ytgPYhqF06dOYar01DT05q9evlxSXFxbW4szEqg1TinoLUvYQCr80x/9CMMbV6+d1R6yOHzwEF0AP3X8eE1NTVVlJVQWogsVP3b4ME4dINvntK++Yw9cOH/eMgsNugDAOAp2tXr9ZqC/f8nZDw+gjjbTT91k7wQbIjzHQQdXvZ6kgtnSNSSGcSMswI6BTqTsfXoC+Xl5g4OD6DvSDWm3AA3u0p6xHB4auqWdLjBuJ+jhw6bVLw1kZWQuLi3l5uQ01FuuQDgEzq5wytXY2Pg0fe0ljvbjf//+2OjotStXphy/yg3ljgwPT9MuDjlBZEREU1NjYnwCNU4dEGbsELokw7Q0N8sns+7fu5eXm0e+nZw8fsLR2+dHDh2S71Ozk8MHDzp6Injo04N0KU4HokN47oYF2DHQG/ColUTNYX2Wnz9X7xBvM1gB6mdIh3E76rugQVZm5u4PP3TiXu/1K5aLOsD/3trjo/azmY8xgMmJCbpR4gRrH2MI4o8xbIBUX3rwwiE9oM9kyXtJ9kA/PXLouadTJyy/gFBvTm3IsSNHMLx88SIlPRMWYIbxQqQAP189ORsaGixafe1RVWWl+nQMtMq0mwgeBjxEF3ZmZkY+pIpjdLXyVaWM9PT4uLXH7nTcu3sPw9TklNYW8dORqqoq9TwAx2LTPgoxMT6OUwd5FVp7csryqAGB/quNI/KFs+cwYUN9vXyPR1tbm7qZOgGOjoyST3r7GlKA5ctb7Ae9ZwzR16SkPdDPlx26u0STWHs62hT6IRbkjZKeCQuwa1DvtwFjVwNdZ10ZhzDtu2CG9PjYZujt7RXeemRdwFHrZcZsTdTVU8uPjW5wuR6H1M3sFsYalucY8sSFRChoYkJCV+ea9hQWFg6uPjwIhbt4bu2mu5Hamlr1h0YD/QP02zmAuvved/6UfFPQPtPT0tTbwIUFBfIDCdlZ2bonLVQmJyah9NVV1U2NjaTBaGbyuUXw0x/9eMrmt9AL8vLUH/fX19XJ70HNzszilEL22xCeP/zBD8j3QaQAq78LcgiHnnamN3k59HFMmqS0xIEvqdAkMgo8ExbgTSHPzYeHh8kvKS6Gg4Oa7mJseFiY/NUaQQWw62VJcuQ8pbgiX3cFj0pCu3CCD0edhKaSlx+p94NFUz4NVeTLGRaUi9ioiKOHD2OuKH/j+nUcuZBJC6VOg1iiNkThotUjMmhqbKJ4RpnODvGRO1puTFS0XFUiLSWFBBhHQAwxlgpYNFxrDLT+oyOj1E+KiojAkPEQdLXpKJuc3IV4zpq4BSnA4M5tvzd++Svyk5OSfvxv/0b+XT8/0z5rc1MTiqWlplLyn//hH+Q3H//kj/+YHB3jY+O5Obl0iRj87V+/In+q+4e/9/vk6BgZGYGU0oVo8PJf/IX8pcaLv/s1cnTgFLMgP/+s9mgn+O7/+Y76CjDJwQOfmnZvtgcW4E0R/ORJX29vR0fHo6AgxDBayZlTp7FDiwoLcare19cnymlNGc1XjfPUlNRbN25UVVaGBD8ZHx9PSkxMTkzCHkDf5eb1G5CloIcP7925s7S0nJaSqr6wLT4uLj09fVGTQwgw5hng/8Dv1u3Q4JDrV6/eu3u3taW1sKCwra0NIoppUeCT3btjoi2vl8JY9WIRdJHa9PUrV1NTUqan1hqi/Cl9SbHl95GWGEtJbWtt7enuiYuJRZP1u3Xr/v37mHlQYODRwyKWCHr7eVdXF/02/9aNm363LW/G+Xj3ngzlWR5s9aULFxEnWDecYWBlMKuHDx5gQY8CAwO0j84ihLCN2JkYBTHG/rl6+QqpNcMwLiEiPFxqmzW+8Qd/KDy7cei6NLHhahg5f9Zys98h1Pd0/u9vvyQ8d8ACvClSkpLCQkLQNcQepL4a/ZyfTujUV8NAwOhlFBK0m9raWugoqTKdQkIFIclwMLfPzpw59OmnlB8TvdYDPrBv38Xz5+mlWhAnSPW5s2dPHD1WV1dXWlKal5sLVbt08SLOCeJj46BqY2NjsvPtf/deSrL4FTJB732kF5KoL8CKDI+g32kUa687oDfvYN16e3rTUy2/d9r94Yc4h6VremoPGDQ1NlLXnK7/ZGZk0mdbaFkqdE6alWn5hXFNdTU2AU5rSwv62TiBQHs4ffIk9gA2Qf5oJCIsnAV4Q2qqa2Tzw96LCAsrVO6eOkRqcgrO+Zw7RuCUFPXl3DuoAc4joQ3GV7faA1p+dGSUpWmZ9W6np6dSk5PVXzQgWHAyTT4ieqDfmY9PMIxDsABvimOHj5z7zHKJY6B/YFi70QV56+npoUc3VamLCI+ApImEdid1amqKXgeILiAIDw2dGB/v7upCn29yYvL58vPamhok0W9GT1F963poiOXVGehfTk5OlpWWQr+h+uhtlxQXQyyzs7Jyc3JRoLmpiT4FMzQ0FB0VjZnPzc7W1dZFKp9Axw4PfvQE1U/vmFRfBvQ4MIger4B8QvwaGxqwICwC0giQg0lGR0exoIa6+uNHj9JpBJibnasoL38c9AhnBtBO5CcnJtL7KZFJr+kgoKMF+QU4UAYGPMSsent6sDnYLVhWY2Mjlm55r8j0NHYdMrEfsCHXr16jK+GMbaC4z+lmxPw8vWkczcyJzwrdtvyu7Dlm9eSx5Q2IjvJQu4xRWVEpLxjaT2ZmJt13QIN3otLpohE0Vb1trII4RUsWCe21rzh5FYmVldMnTnJLY7YaFuBNAQmhdYYWAjhQHUDdNTiWQhooNj+3dpMVoDz15OBQ75l+5YaDjpwVVJryqYDEWBI+FoqliPWZmICwIRP6h6VgKCdRKxuFKYfugqhLkTPHEAVmZ2YwEyyCNg05C/MLVAAlcahaE+C5OeRQSTjIp9XDKBSjSYilRcvSsZ4oQw/mIIlNxgovaxuCUShPS4RDu4uxB/kUNOo9NcVyEQUCXOnIYy/E1UuXyXHuZ0iPAi0/Q0LdxUavewDCHjKePqW2Cofap0PQmTHmQC9PNqJ7Crqzs1MV4PKycmsTMoyrYAFmGC/E8jGG1VOi+/fuIcj9bt+mK6443Xn9F6/RNwoB1PH3vvZ1a29F6OrqDn78ODs7u3S1CxseGvrm66/L862f/uhH8ut4RjCqsaHh3GdnZfl/+Lsfyp8SIfMPXnxRd3IpGR8fv3XzZn19PT0NABrq6//ye38uz8OuX7u2d8/H5BvJz8vPzcl5HBQkr2Dv37vv5rXr5IPe3l5VgPv7+1UBvnDuPM5ARcLbCQ0OpstdoLCgwNEPwZWVlp45ZXkboJ3cvnlL/SCEPaAZ4Dz+vXfeFWk7qKmuxrk7fSBZh0O/Wt5SWIAZxgtBrzHSvifGccBFX1AkHGRkZCRw/Zc/HCI1JWUz76J64FSnnJiYmMCaq7/Bu3/nrjwu44C4mY9M7DjkU9DyYWaHeJqW7pAAg5vX186E7GHvx5YzrUrt+Rg7oUnoGVKPhQWYYRjGp5EC7MSLOOgh5K0WYHoIpnX1Z9z2QI86008oPRYWYIZhGJ9GCjDda5dPSs7MzMjP8jc1Ntm4NC0FuKy0dG5WyMnRw4flx/N1qAJcVFgob0Ps37vX9NfG9JE6+dPh/Lw8eSdiz4cf9Zs9sv6Z9o6Xg/sPUDI3J8dUXzIzMuhrp26BBZhhGManUV/EAcWVv86CyMkviv7oX8UbOYygvPzqPhRXHsZ/+7/8V3J0QGJRXk7S3NS0vPqCoP/3//ltcoygdy6fJIBoSf93//v/S44R9d1H6ArLSVT4d8BrsAAzDMN4IPRJb4dAB1p4diN7z/azSfUy7T1vGyzADMMwDOMGWIAZhmEYxg2wADMMw/g0jQ2NQYHi52RnTp1Sbwnbw+GDB9UPXtnDwQOfOvQBJaC+SdBODu4/QC8g0nH/nuUrmZ4ACzDDMIxP46jiqtAX7x8FWV55Zif0ltB7d+9S0k4c/bQ+PTJ9ZfVVbp4JCzDDMIxPowpwdVX19/70z0TCDugXuiOOfDDDiQ/yA0cFmD/I7zAswAzDMNuMsQc8PDwsvI2g797TF0jthCZx6LVWwFEB5g/yOwwLMMMwzDYjBTglOTkpMVF+x1f9IL/frdvqmzsl09PTT9PSjxw6REn1g/zf+sY3ydExMT6emZFx8rj49O8PXln7IP8fvPh75OiIjYn56Y9+7H9fvHz05b/4C/lpr//vq79Ljo6hoaHsrKyL589T0toH+dFRduLnUq6CBZhhGManiY6M2ooP8ktVth9HX2kJpMTaj/pB/u/8r/8tPHfAAswwDMMwboAFmGEYhmHcAAswwzAMw7gBFmCGYRifJjQ4WH7pr6iw0KEP8nd2dE5MTLz1+hsibQctzc3T09PvvPWWSNuBaz/ID80TnvYSksyMDPLpm0vbCQswwzCMTyOfgnbig/z03Xv50SR7+GSPZRJoKiXtYUs/yC8FGODkQHjbAgswwzCMTyMF2IkP8tNbNRx6FSVN0tXZSUl72NIP8qsCTG/p2jZYgBmGYXwaKcBOfJCf3igpfwtkzwf5b1y7hqH84dMWfZD/7JnPMNzwg/xAFWAnrgFsBhbgdeTlF7B5pYkKZhjGgBRgAMUdHxsnHyLX0dFBvo0P8ifExctv3dvzQX4QHxcnJ7H/g/zC027cuuqD/EAKcHFRETnbBgvwOkbHxv//7P1ndFzZeeaLz6dZWmu+zF1r7L8/ebzW3OuRr60ZjxyuJMuWnCXZstuSbCtHS2pJ3epusrtJNnMEM0iAJAgQOeecc84555xzLmT+n6p9cPrgVJ1CFVBVAArPb70s7nT23iftdz84ieaUJu1gQsiBcNYP8h8tdMB7WFxapjmlSTuYEEKODXTAe1CN2jSnMWkHE0LIsYEOeA+qUdvYFhaXxsYn5ubxvz66tLwyNT0zOja+tLIql1EZyqD0yOgYFpITsdTE5JQcPZgtr6yiEn3ryyuqLJrKpB1MCCHHBjrgPSiH7JVVHf7hV05ZW99IiE8oK68QDhhZpSWlkRGRPb19z589162tyyVlQ6nxiclHDx7Ozs3fveMie+7Z2Tlvr1dDQ8OoRS6sNCyILGEm/ev65pafn391Te3YxOSDu/eU/aQZm7SDCSHk2EAHvAd5vB4bG3/u/uyZm/s9l7uTU9MiEQ44Li6+vaNTeLut7Z07t25vv34NB5mSnNLZ2SWKKW15VZeWlt7a1g4/OjAwGBQYBMeJ9PWNzZDgkIHBIZMOGG66sKAwPS09Iz0DhrDsuZWGRCyOzrx44TE5OWXST9OESTuYEEKODXTAe5DHa/i2hITEh/cfvPPW2w2NTcJNGjvguy53t3f0DhjOsqOjUyyLXFmPIoKsNoMDhlT19fXbsMwBl5aWZWfn5OTkwqCzkaIqA0MrXd09EN8G70zva86kHUwIIccGOuA9iMEaji02JraxsQlBL0+vsrJy4d5UDhjRiPCI2tq6sfEJT4+Xwkci8frVa+c++HDRsAjqamhojI6KXl5dRZnevn7hcc07YNjM7NzMzKz+12CqXBgagp6OiYlFLrS1yTI02aQdTAghxwY64D3I4zUUcGVlVVVVNZwr3CQUJhKFA66prZOLwTG3tLbV1dXLChW++a++8MXJqWnhs2FImpicKikpHR0ZlRNhPt4+ZhzwvoYu9Q8MDg4N47e/f8Dk36hpskk7mBBCjg10wHtQDtlwlkp/KQx+bmxsXOntVMVm5+bhs40XVKVMTc+Mj08oU2h2NWkHE0LIsYEOeA+qUZvmNCbtYEIIOTbQAe9BNWrTnMakHWw3dnZel5SWK98+TTuFhmNA433DhJiADngP4u/JNOczaQfbDQy77R1dc0bvoKadKsMxQAdMLIcOeA9V1bU0pzRpB9sNDLudXT0q2U07bYZjgA6YWA4dMCE2gA6YBqMDJlZBB0yIDTi8A14yunPeJiaqlZ92O/BjbzRLjA6YWAUdMCE2QHbA8HDiPS36gG5NHpqFiSz84kdvipeNJyenrK1vIFFOETY0PCJeXypnYXmYCIgUOUu0KOfit7W1DdWGhYat6tZgEeERqvppNjQ6YGIVdMCE2ADhgOEBMzOzHj98hEB0VPTN6zeUo/PAwKDLHZet7e1nbu5lZeUdnV2pKameLz3hEeEjXzx/gUBxUbGXIUUsgsCTx66eHi8RrKtveOXptb6xGRwUnJGegay42Linrk+QlZub5/HCY25hES1imdCQUOT6vPLGr9tTN1Tfsfv6trTUNERF5TSbGx0wsQo6YEJsgKyAS0pKNza3IGcD/AMwFAcHhyDR4EnX4BcXFpfKyytaWtu8X3ljKQjTqemZyalpuFV4UJQcGR6Ji4sX4hVL4be+oXFre2dze6cgv2BufgGuFPbS4yV89vNnz7EgAg8fPISYnl9YrK2tq69vqKmp3d7Zqa6uQav3XO6iNjTR0NiE2vp2X4ZKs4fRAROroAPewwZxUqQdbDdkB1xcXAKnmJSY9Mz9mU63BpEKL9jU2IRfPz//6emZ6ZnZvLx8OGMsgjL9A4NwnPDZQqomJyUXFRbB9aJ8c0srKqyrq8eQDi+LpWZm5+CPu7p7fLx90EpiQiIWgXyOjYnFIkkJibq1teqaWtQWHhaOAvC1t2/eQlXDI6P9/QOoram5hQ7YfkYHTKyCDngPM3PzNKc0aQfbDeGA4dvgQaFTY2Pj0tLSCwsK4fzgDl88fwEHOT4xecvwJ2JEIVUHBgZTUlLhX5GFxAA/f+E4s7Nzurq6EYZKxpgOaXvz2nUI5cbGJvhdpD968DAzIxNZXi89szKzhodHEECFff0DkNHw/eIP2kJAp6akwhNDl+MXUdSJXARo9jA6YGIVdMB7UJ1ONKcxaQfbDVkBC30Jb/f+mbOzc/OidVl0wh/ro4absJB7/sNz8hXZiYlJfdbKKrKE71Qthf9FCqJSgVWdSBEViixYQnwC9LTIEn0YHBzCL/IhhRGg2cnogIlV0AHvQXU60ZzGpB1sN2QHLJvwf+bNkjIHMDhaO9VMM290wMQq6ID3oDqdjA1Dm6w/hGGkU0ZNmvGAiKiQNYc0oXj27QBN2sF2w9gB006h0QETq6AD3oPqdFIZXF1jY9P9u/fa2toRg01OTcfFxpm/sWV+YbG5pTU8LHzR8FFhGAqnp2c8fvhoZnbuwL5TtO7u5n7rxs2a2jqbuHMnNmkH2w0Mu13dveKooJ1awzFAB0wshw54D/J4vbC4ND4x2dvXP6b4au/a+kZsbFxHZ5e4bofzDR40NzevvLxiWdv/zc0vwFMG+AfIVwRhG5tbIcEhZj7IPzc3j/LCEFblwtD69Mwsfrd2XoeGhPb29iGsKkOTTdrBdgPDbmFRSUlpOe00G44BOmBiOXTAe1AO2UPDI/39A4H+AfC4wrfBAcfFxbfvvtMAhkBxcYl5BwxDwcCAQKUDXt/YNOOAIZrzcvOSk5JTklNgCMOLq8rAUC387q9+8Ut/P/81wz2uNC2TdrA92SRkc1M6GgixADrgPYjBGo6tsKg4PDwCAhfisnn3L8zGDli3tl5aWlZZWbWqeLQD0hnOW44a3PRacFAwXCjCInEfBzy/kJmZBbWN5mAIa4ngFf07lDZr6+qzs7JNVkUTJu1gQgg5NtAB70EM1nBs0LUeLzzgfd975917LnfFxVrhgLu6e8SfoHXrG/Fx8R+dv3D54qWgwKDpmVkkbm3vvPHVf4qOjhFOGk4RDvuZm/tbv/jlowcPGw0vZED65tZ2WGiYmT9BI11pqlwY/K6fr5/H8xehoWHP3J/JT7PQTJq0gwkh5NhAB7wHebyGu4VghcGxyf4ParOwoPDypcviJixRDA4VJsog0NnZdeXS5a2dHbGIKIMMUUYshUBqatq5Dz6cnJoWKQcz8XdvdFI4dZoZk3YwIYQcG+iA96AatY1NeFwzXlMUUCUaG3wwNasjTdrBxwadToffzo4O/I6OjBjS9MzPL7S3te3s3smD46mrsxOBooJC/I6MDK+vrSG3uakJ0daWFnHKFBUWITA7O4uwGdDomu6wp7pJlpaW7HT5c35+Xt4atmVmZkYKHQKxdwg5GHTAe1CN2jSnMWkH2x84ue3tbXgj/CKKX5xdGxsbhht0NuFLEMZvY0MDcqurqvBbUFCgX9LA3Nwc/Ojq6qqILiwsdLS3z0zPYKnx8fGa6pq8vLyiggIk4mSBc0KZ7KwshDfWN3Kyc8RSWqDyocFBKWJTJicm5ufmpIhNGR4attOwgImOFDoEGenpUogQ66ED3oNq1KY5jUk72P4MDQ1lZmTC1/r6+OC8unnjRndX98DAQGJCQk93DwrU1taOjY2Jwk2NjfgtKSkRUUF9XZ0UMnDn5i04bPenbq93dirKKx7ef1BcVCQ+L/Hc3X1lZSUlOVm4gfzcPMMS5hi0jwPe2tzExEGK2BTMRew0LIyNSnvhMOTl5kohQqyHDngPc/MLNKc0aQfbH48XL4KDghCAa8SvUKXeXq+eubvvvN6pqqyENx0ZHtYX1XDAFeXlUshAb0/PzMzM+vp6T0/P4uJiakpKfl6e/H0nFI6Oiqoz+OyCvHyRCNCKkOAqMD+QQgfFZLXbkOOHVsCYtUghBeIvClLkoGDrSSEF42PjUugQCAd8+B6S0wkd8B7KyitpTmnSDrY/rS0td27dXl5erq2pQTQoMBCjM/zulYsXEX304CF+FxYW5g0faGppbsZvaWkpfmXyDEL2/t27+IW7hbqFL29vb19aWlpYWERVHe3tUL2odrB/YHhoqKiwENoX3ivE4PgFpSWl4jKzkrHRURRG4F+++k8i5QB4e3lJIQXd3d1NDfrJxPe/8x2RcgAufPihFFKAarGOCFy9fEWkHIA3f/pTKaSgpKgYExpMZTCDkZKsB5Mh/Pr7+okoIVZBB0yILRF/MoU7FP4PpxbEKH7hL5GYnZUlitVUVeP3lacnfmOiow1pEiiPX3EuICx0odDT4hcISQc3L6Iog/LK0zgyPFwKKYCzEWVEnQdD9FkFqhVdOkzNL1+8kEIKsBmF3D/M4BAcGCiFFKBm0dvD6Ndnbu74ffHsuYgSYhV0wIQ4CPjm6elpKWJA+Fp7YL+aiRJuZ3IY6IAJIYSQI4AOmJBTgerk2lb8oRsIJSd+5UQREL+UeoTYHDpgQo6SyoqKmd2/S29tbT91fSLCtiInOyc4KAju09fHR3ai42Njfj6+CERFRi4tLQUFBhbk5w/0D4QEByMxIS6+o719c2MjNiYGiwT6ByAxNDikvKxMv7ARuTk5U5OTUsSm+Pv5SyFbc+PaNSl0CHy9faQQIQeCDngPVdW1NKc0aQcfPyoqKqSQAS0nd2A2Nzd7urvhZRFuatS/PwsUFxUhHaws6++vzkzPQIGuzs7RUf07uXAa1tXWwq1iXBBv10IUnrhQ8cIQFRPjE1LIpqAndnrCZ8Swpoekp0f/YDchB4YOeA9LRl/YpjmHSTv4+KFywKV7nwm2CTnZ2XOGh3TF48KgpLgYv/CpIUHByNLpdGWlZXB1y8vLU5NTGxsb1ZVV3q9eNTU2oozr48ctzc3IEpWYxE4OGD2xkwM+/PPQoKurSwoRciDogPegen0SzWlM2sHHD5UDhjbF78LCwmEcT2xMrBQySGpUNTMzg194HdQMn5qfly/exoXEspISOGD4ZsPTPjuTE3pXmpGegZ7MGt6WvG7QwfGxceL0FM83qxAvtWhvaxfRA9DS3GL8ugykiEYP88rlrIxMKaRAfiPYwMCACBwA4YCXlpZs4s7JKYQOeA+qUZvmNCbt4ONHeXn5zrZ0aXZzYzPA339lZQXnpMmXN1kCvGl7+8eOMCU5OcrwoomXLzzw29HeAacLYqNjEPXy9II/rq6q6mjTX/T19HiJxFdeXkJ6RoZHIBe/SAwNCakoL+/o6DDuWFVVVYShjM8rb5FyANyfPpVCCrKzshLi4xEQV6wPxrUrJt7gER8Xl2t4SVl87MeTFWtpaWnBb3pqqogSYi10wHtQjdrGNr+wODY+MYf/DNHlldXxiUmkLGl/HwllZmZmR0bH5KVgU9MzE5NTctS2Nj0zi16JLuF3dm5+dHRs1vBJY2Uxpek7iXILi3IK+or1QpqccjBDo+JLyUdr0g4+fkCSyq/XsAk2+ciPFv19/VLI1rS2tEohWyM+OWUPRJ8xKRFRQqyFDngPyiFb/9lBw3d85ZS19Y34+ISqqmrhqNY3tzxfejY3t/T19UNemHRvqKW8rBxLwZM9efIUjlAUQw0+3j5DQ8MooCwvG4ohS5jJmmHIQvdEGTkR3s7fP2B4ZFQs1d7RGRwcMjE17ePj29XVbbKq9Y3NkKDg2zdvNdQ3YJVFIhxwXX1DQnyCVuvKHsJMFkNnoLHOf3hOq4DDTNrBhBBybKAD3oM8Xo+NjT9zc3/x/MV9l7uyVIUDjouLh0uTvTI0I1wL3Iyvjy8UpEhUmeStNzbDQsOamlvEsnqfFxwyMDiExeWSsmGRvLz8lJTU1NQ0WH5+gVI9C9OtrWdn5zx+9Nj1sWt0VDT6JtLRmZCQUJQWUQRgKJyYmFRdU2uyORgK5ObmNTQ0yg4Y1tPbl5SUbNJxop7Ozi7RPRgq7+7pNVly5/XrZ+7PlgwOW5XlSJN2MCGEHBvogPcgj9cQrDExsQ/vP3j7rbcbGpuE3zJ2wAjAab30eImA7GAQlgvAEIf7hN5tbmkV9cD2dcDFxSWZmVlZWdkwhIUXVxoWbGvvcHvq9tT1yftnzqJCka5ywOgOOhMUFFxeXrG82ytDH9fkDsMQhzu3ygHD44ruwdLTM3r7+k2W3NzadndzpwPWYnHvn6AnDPdA2ZydnR3xGQZBX1+f+BCTaK6/r0+8wrqhXv+V4sKCQpQXN4IhUJCvf/qoorxc6/TU6XTKB3Kam5r6evs2NjYWFxcRFe2iIfG9wqICfXR8XH/TFhbs7u5GEznZ2YiaRP/NY/u8A2RqakoKHYK2Vnv95ZycBuiA9yAGa3ij2JjYxsYmBD09XpaWlQvnoXLAUI1wvWlp6VNT0/0Dg0KkoszVy1fOf3hOLIK6Kiurnrg+GZ+YHB4ZHdn9E7R5BwzDDACSWpjxhVhU0tbWHhUVjSbR7pl335OzVA4YTvrBvftoCK2Lv0vDOjo6P/+Zz7a0tIoVQcrMzCxUbFlp2eT0jLysGQcMw+rKPYQZTxFgqArp9+/dHxsbRxlVriNN2sHHD8NNWB/f8Gyn78vCQYqv9wvge8Q3l/IMH/MpzC9IT0urrqoSd2/Nzs729vQMDgzAifb39ws/ur6+jsMDAWMK8/NbmvW3IwnQEGrb3NhobGjA3GJzc7O+rq6yorIgLx9eX//w8cqKeNw5Iz29pakZDhgn/uCA6Q8Vj42N2WlY6FDcqnZgMtIzpBAh1kMHvAd5vIbbqKmuqampheOE7xI+STjgmto6UQaJcGzwqSgwvFsGLu2vvvDFqekZ2W8J14syg4NDynRoYjMOeF/DgqizuKi4r68ffZicmhbpcMD+/gHyfWETk1MoJlpHGSRCB2Pe8PKFh/C+MCSOj0/ARw8NDY+OjYsVwW9jU7OZa8CWGCrBlkHTqBnrrsp1pEk7+PjhgOeABQN9fVLIQEmR/lFg8SXEQH9/8Vm90hJ91OP5C6hVKGA44KWlJfH5o5rqavFZQJNkZuzxQ62G24ObmvTv/Xjq+gRTMwTgq9bX1p4+dpWzMPnw99N/yM/10SOobQSMwdhkp2FhbHRUCh0CMY8h5GDQAe9BOWTD8Rj7Hgg9iDkhdk0apKB8B7IZgzeCz1MlHsBMNgRHa74P8MomBavSsIZHLlttaNIOPn6oHHDZ3m8DHwyTjzAJFytTVKh/4LjMoESrq6uzs7LhArsMYwGcbndXN4Qv1Gp7Wzs8sWEJ6fUd20YnKZoTf1IWQNH2G5x9c3PzyvIyvHhlZeXQ4CDqhxdHdHl5GVkokJWZ2d7WZljodW9PL5oTYSWoXMs3W47JDTJueBL6kAgHfPgektMJHfAeVKM2zWlM2sHHj70OeCc0JGRreysvJ3fJ8IffgyGeylVSXFTU2NgIP/HEIEABfO3O652w0FD4y8T4+NSUlMiICAhiRJsaG/v6+hobGlpbWyETxWM8HR0dpcUlNdU1OqPv/L/08BB/nf7Wv/87fsV1ZfjvhPgE1FZbUwPp7PXSs6iwcHRkpKG+Xt9iQsLi0lJuTg58MMoPDAzAzV+68JG+ur2gvHDnly9eFCkH4Bc/+5kUUlCQnz83NwevLx50Phj5efoL5OJ12YRYCx3wHlSjNs1pTNrBx4/KigrxvmUD+k/3wz8BKcF6BgcG5A/1y8D1Csep1GpwwKI5cd7hd02nHwhWV1fxC9W4vqYXjquGe8REoskv28OHiRFEKWH1tRkS5dqgfeUoskRh8Ss67PHcxGftUVIseJjBIcDURx3kPhxGvz5x1U9oTPackH2hA96D+LMzzflM2sGngMM4b0KII6ED3oPy+zk0ZzJpBxNCyLGBDpiQY4Tyr7jApJwVp4nqD6diQeeWv6q1U62yyb8kq7YnIccKOmBCjhL9B/l3396M4z8hLk5c8gQpycluT/SfKLhouDspMT4+MSFhcnJSfD8gNDiko70jIT5et7oKJyQ+nh8WGlqQn69f2IiW5ubKykopYlNysrPt9EH+uNjYxMQEKfL6dXBQUHxsXFZW5uzMLNxtSHAwVjkiPKystGxgYCA8LAxlLn+kv1crNSUlLSVldHQ0Nlq/WQxLq7lx7boUOgSuDx9LIUKshw6YkKNEeRe0OP6Vb8wQb5iqKCvHb15eXmZGBiSdeHNWV1eXeIp3eWkJLhznsHhjRnpaGn5N0lBfL4Vsjf0+yC/enCWDaQR+p6emxkZH19fXhwb1jyZnpKWVlJSIu6/Fi7eKi4sLC/T3J09PTWuNbuLDi4ckX2O6Q4gl0AETcpSongPOy81VKrbsrCz8lhnejxEdGRUVqX9gJs7wuV8/H5/mpiYUhgMW2he+eXtrKykxEbkmOXEOGFRW7FHtC4bZCRzwzva2v6/v+vramk43PDzc29MbGKB/Fkj8AQBCGYZATXW1lgLmizjIkUMHTMhRonTA8KCQvHAYC/ML21v6K5rCAYu3VlWUl+dmZ8P3QAHjTIFQLi0p2d7eXlpc7OvtRQEoYDjgrMzM7Z2duloT952JxMN83H56elp8yV+F+CB/6yFejAxpa/y6jPi4ODEmdLTrn0UeGRkR0anJyV7DKsP1RoSHY7thrcWT0+JdnmWlpcVFReKP+fDRXoaXeakYHRkRgcO8FFo44Po6/cPNIoUQy6ED3gPOZOKUSDv4+FFeXi7fPTQxPh4RHoGzsaurS3ijpSX9SxxDgoInJiZ6unva29rgqMJC9Rc7Y6KjsV7lZWVREXpZ/PzZM/zGxsTMz803NjauGD151d3dHRYSikBkeLhIOQDwiFJIQXV1dVREJAK+3j4i5QCIq90qIPoTE/SCXjzIOzM9jd+qyiqkI/DC8PRtaHBIcVExhg7xPg1sq/HxcQxqANvQx+sVEt9/7wx+VYSFhjY36f+gXVtz8Jvkxbug79+9J6KEWAUd8B5KyypoTmnSDj5+qL6GZBPE1VB70NPdLYVsTdvuOyntAaSzFLI1bYa3XttvsxDnhg54D6q3N9CcxqQdTAghxwY64D2o3l9IcxqTdjAhhBwb6ID3oBq1jQ1aakXx7X0YoqoUY0MhlFF+eVCkyFHbmqpy49ZNGsqoumTJUpaYqtojMWkHHz8c80H+7e3tacMFVJuzubmpfG7KhmBUsvkf5wWoVn7Y+sCIPzujk9iDCBzn+wzIsYUOeA+qUXtxr1td1a3V1dXfun6jtbUNbgU2MDj0+MHD27duNzY0arkZFAsLDbt181ZkZBTCSIFHSklOcbnjMj0zK1JsaAuLSwH+AS+ePdetrSOK+hMTk+7cvuPv52/mK4ozs3PPnz13uX1nYGAQ64mlJienbt24mZ2VfUgf3N3d4/bUDXWq0h1s0g4+fjjmg/xwwOJjgjZnfX29uqpKitgUuEk7XRheXFyUb4E+MOJu8B3D554QUH0RmRBLoAPegzxew1ONT0y2t3cMj4zKiWvrG7GxcZ1d3fDEiMJLwYPCPyEKFzuiKKk0uD04vu2d14WFRbm5ecIvbm5th4aEmvkg/+zcPJyiMIRVuTDROvwl+oMysiNHYkhIqFwtmsbiG1vbFRWVWVnZonWVbW7vuD56LGYbvj6+E5NTIr2vfyApKVmuWWWoWe7hzMysyQ8MYzPi9+mTp0uGDiuzHGzSDj5+qJ4Dtt8H+SvK9W/zsAc1Bg9kD9oO8VyTeQ7vgOX3l9XV1uE3Okp/YzYhVkEHvAflkD04NNw/MBgYGNTe0blk8GdwwHFx8YjKYheBhobGd97+dVRklEnfJgzlHtx/8OH7H8gp6xubIcEhWg4Yzqy4qDgjPSMzIxNWVFRs7N7QODxfT0/v4ODQ/Xv30TeRLhyw8HzCkOXx/AU6CVErJypta3vn3t17+EWdqSmpXd09Ir2nt0/LAaPb3T29onuwtNQ0FDZZElMNdzd3OmAtVA7Yfh/kr9zb0MHY3DTxl9taU88cW8WOxpuc5c/1HxhUa/IJ3cO/hUPlgCPCDv5wFzm10AHvQQzWcBX5+QWxMbGQdRERkc0trcJNGjtglIT83djcgrNsamoWiRDN8EYiLExfaH0DvxCacEhI2dcB5+XlpySnwB3CEDb+6zF0Lfzu8PAIMu663DXjgPXNr2+gk5gEwMsiBZV1dHZNTk2LAls7r2/dvIUslIyOjBoaHhHp5h1wZ2eX6B4sKTEJ/thkSQx+z589XzW6wOxgk3bw8WOPA96x1wf5Nzc3xauS5Q/yHwDd6mpjQ6MU2WVxcVGIv5//x09FygFobmqam5uTIrtMTEzgFEDgX776zyLlAERHRho74MGBAfGXhn/72tdFygGQOywccEJcvIgSYjl0wHsQgzUcSVlpmZube4B/wPtnzt68cRPeDolwcrFx8RCI4k/Q65tbL194eLzw8H7lDW8qHAzc2Bv/+NW42DgRhaOqqam9c+t2eFj4rRs34R1FE3DDYaFhZv4EjeaQJcykY4MTffjgYXR0DH5/8fM34aRFMTQRGhomqkUKenvj6rXQkNA7t+9A0yMRWVmZWf/wpS+LMqJYb2/fnZu3nro+yc3NW92V8v0Dg2b+BI100T1hJotBo7s/dfvR93/gcvtOXm6e3KLjTdrBx489H+Tf2Vm3zwf5UaE4yU0KTQsxqaFxzoqaD3PyJiclSSEFmDRgayBwmJr9/fykkIJ1AwhsHeLOKdFnbOoqwyXwpsYmQzIhVkAHvAd5vJbdCXytLN0gY4uLiq9dviJuwkKKnCVcC6JQltevXtve2VMV0iFJlYWhGi+cOw8NKjd0AEM9cMP4RSflepDyzM39xQsP8SdxuXXRQ5Hi6fGyvr5B2TTCsoko+nb1ytWEhER5wYMZWhfbUNR8VCbt4FPAYZy3eU5izfbjJPaZHDfogPegGrWNDV7EvC8RBVSJxga/tGKQ0fYwdMB8H1DCEneISvBPlXhCTdrBhBBybKAD3oNq1KY5jUk7mBBCjg10wHtQjdo0pzFpBxNCyLGBDngPHz/YSnMuk3YwIYQcG+iA97BBnBRpBxNCyLGBDpgQQgg5AuiACSGEkCOADpgQQgg5AuiACSGEkCOADpgQQgg5AuiACSGEkCOADpgQQgg5AuiACSGEkCOADpgQQgg5AuiACSGEkCOADpgQQgg5AuiACSGEkCOADpgQQghxNOvr6/Hx8cfIAW9vb0shQgghxHkZGhpKSEjo6uo6Rg54Z2dHihBCCCFOSmRkZEpKSl9fH6SwlHRQbOOA4X2Xl5elCCGEEOKkBAQE5Obmjo2NbW5uSkkHxTYOGGAuwM+nE0IIcWLCw8OhgGtraxcWFg5/7dVmDhhdmZ2d5d1YhBBCnJKCgoKgoKCcnJyBgYHD//0Z2MwBA3RoZGRkenpaihNCCCFOQXR0NLxvWlpaW1vb0tKSTW49tqUD3tnZ0el0Q0NDZWVl9fX1vCpMCCHkRDM6OgrXGxAQEBkZmZ2dDe87Pz9vq7/12tIBA0wK4IMnJiZaWlqKioowWUhISIiNjY0hhBBCThpxcXHJyck5OTk1NTUDAwOLi4s2vNJqYwcMoIM3NzchfycnJ9Hdrq6u9vZ2zBoIIYSQEwScV0dHR29vL3QwhO/6+rpN/vIsY3sHLIAbxjRhY2NjbW0NmpgQQgg5ccCFwe9CVdrW9Qrs5YAJIYQQYgY6YEIIIeQIoAMmhBBCjgA6YEIIIeQIoAMmhBBCjgA6YEIIIeQIoAMmhBBCjgA6YEIIIeQIoAMmhBBCjgA6YEIIIeQIoAMmhBBCjgA6YEIIIeQIoAMmhJBjRGzLvdiWu0ZmnGgyxeSyMK3F5XRlwLgwTJmoKqBeNq71bkLn/caxXGmVTLExnb0zdHup86YdrcMo5cBmvipLGpLL2LBXjjR7dNtMnYas1e6bup6bG3OV0kGjILZv4Hxtw7nK6nMVsCoTps/SjkomJ5rKNb2IMDNZShPFLCxsMHPdrj5XKYdNdg8FDIawCFTW6K2q5nxV7TlYdd35mjpst/N1DedrG8/XNerDSKmquVJbd7uh6X5Ds2tjs0drW3B3b9LAUO7oeOXEVPvc/LROp9vc2rDD90iOCcvVHSs+2VOeKZMvk/XmqTA5RfW7J5CiD8umTBHFJEP9hibkLBFW/cqmLKM31Lm3IdhusYVX6QvRRdsbNvtY6ikhqW7CJXXgdmInzbntTnLP/ZTuycX1nZ0dsespgAkh5Bixn9SUTZVuHFCWMQ4rU7RMVYnSVOnK6L241nsJnff2E8A5JgSwDVXWYao68LI27L95s7Yhh3XMcrOgS/sI4LrGPSJQGZZMTkHAOFfDTNRjTaLerGnu4HboJlT9V6prKaUa4hnK+XxNvV4qw+obzzc0QzNfra51a2kN6urJGhrpX1qaX1/f3p1WnkT0Ath3VwArhaVScwotKkwuIP/K6cKkqGFZfdi4ZrmMHJULI6ooL+XKv7vF5F9DYNGbAvggUACfFkvuuUcBTAghxxaF7DQpMlWJssnpyoCysFa60rSyRKIqV0RViXozCOADXQG2SqeZL4zcY6L6HNkNW7V1mHpst74r+whgcQXYSLapDGXUxVTC72BK0tRSJtqSzbgPe1NMLqhMNC4gp2g1amZxC7P0UUVYaeWG30r95eXz1bX668n1TR9V195vbA7v7auZmp7WrclzzWPOxwLYtPJUStPdRFmvSosodKlUYK8pc/Vhw1LKFLlp6VdZwFC5yNKnKLJ2A4u8AnwgKIBPi1EAE0LIcUYlJndN1plqtblrWunCjHPNl9cyeSkRwK8wZdYhBDDNjB0TPW/erOqkVuHddMMV4Fv73QK9q8cQVik3kahKEaaVvkeU7q1cDltuyqUOX8MBzKLV3DVVYURNL65I1wdMlkFWjf7m6oYm7Ka7DU2Rvf19i0tbx/UmahNXgIW21KfsVZtylpwop8hhObqnjFLQqsobtasqqQwrUxRZFMAHgwL4tBgFMCGEHGdkGblrssJUJZoMy2aygKqkVroyRRUwLmnCdm+BzpFWyRTiFuhlpeyxxGyir2xrNm9FVSGijlkRm5i1XTVTvmO/K8B6AVyzK7e0ZJhRirA9Es5UljLdZGHjBSUzVVhEhakSlVFhJstIiUbhj6MKM06RzWQWEs0sYtKk8pYtVW4oX1V7vr7pXE3d46aWwrHxufV1aV8eAxRXgPfqTGVU5MqaUwRMho1L6n/3Vq40OUUuozK5KhFW9nM3i7dAHwwK4NNiFMCEEHKcMSU+jc1YjiqXMrMgTFVAVdhMVJUlm0j/OPcIrgDbWyJarkLlYvbukq3MTv20pFrzZTosfAmWQWKZCZgXafpihgJyQG+KRT6ux6xpFlNWazCU3FN4b9SS5tSvwhK2d1mE9cVUKQqTE5W5Iiyli6gckNN3wyqTsnYLfFxSEZATK6v1TxTXNT5oaikZG1/bOmLZtuclWOJXDiilpkrZirCcqP9FWFFGmLLAxyWNUuSwVGC3dSnXUMmeX7mwPsorwAeDAvi0GAUwIYQcZ2QZuWtastPYUFJZeN8F5QJmllKWEWH5VxndY5ZdAc7etkoA20SnoRI76T2VOaaVQ5olnTzSFdnvJViWPQOsN0MxlUIzaVoVGi9radOW2H5VmWxLJCp/9aaKWmaq8lYtLhe2ZCnjMuVV+pdU1zddrK6L7x+YX1uTdrBj+VgAC2EptKUUNhKiUlQEDIvsKaAwpCgT5fIfN7R3cVFAjsoF5EQ5Xf7dTacAPhi7ArhLrZdoTmYUwIQQcpwxpS3lFGWiHBa5ynRjUy0louYXESaXUdUgh1WGLPkt0OYE8LrhCrDVt0Db1syrOzlXVczkUlpVGacjRaswzEyW0kQx+Ve5lFYNWmW0yhsbSh5sQdksWURRxupboPGrllhIUYRFQF9GGZYLaJmhjJmSJrOkC7CGDigLWN6iflnjNTJVg0gxmS4nmiizmyJ39eOsXRM17FlKYcp0M8WUZqZMZc35usZLNfVZwyPrjr0mvPcKsCwslVEIUVm17prI1RdTCNQ96btRVa5cQJkoovpcpejd/ZXKGEwOSFF9GX4G6WDwCvApsTsUwIQQcpxRicm9UTksp6gKGJcRJtJVheWA8VLKRBFQFTOZKJnVt0AfQErJdphlD2AObu4kmu02kQUC2EhNWaLBTJpFC8plzBQ2zlKmILy3gPl2zclFC7L0gb3FLKxQqxjS92QZF9Ouf49p14/fqprzDc1PW9sHFpek/W1n1FeA9SrUICxFWJ8oS1w5sFtMXkpkybmigHHYfAH5V5klpxvbbvnFVxkL0cUUwNbCK8CnxSiACSHkOGPQkCqpaUJk7pqqpPg1X95krkgXWXIBZUk5S5gyUW0W3gJt6TPAEFQqTXVgiWVc1cHMqnpESWV5m/RBNjO1IcuStizsj4W1WW7Gte1NsUIAf6zKFApNBD7OMmlyYfG7V+Dts6xJM1rcRCVIkRN3w1qF5QvI+l+jXKVJyyrKIEWYnKJpe5eSw7LJieZzlVFloti8H5tRbfJVaEXJ83UNl2obSsbGpb1uN/a8BEsvPuXArklqc1f96n8R3iuYRdg4KifKAVX443oQUDYB29vEnqxdM0R5Bfhg8ArwaTEKYEIIOc4YyUtjkYkUVaJxGZWZKa+szbgeZa6coozK9nG6vV6CdXj1pZJwWhUeviGV2bxCe5jlnXTU6lhzBVihtZQmFTD8KvWYbGphZjDjkiaX3d+U4nPfGlBgtwyW0mrRZN/kRK2lTBsK7xGcCrOsHss7KczadIPpP6dU25A9PCLPXG2O+hZooSqFKXWmFN2Vx/KvnCvMZLocltM/ThEVKmSwUMJyVP8rArthKevjAAXwweAV4NNiFMCEEEIIIYQQQmxOx9jSy9x+tQQ9WqMAJoQQQgghhBBiPxoGF9RC9IiML8EihBBCCCGEEGJ3oipHVXLU8QYBfJ8CmBBCCCGEEEKIvQkrH1YpUgcbrwATQgghhBBCCHEE00vrKkXqaKMAJoQQQgghhBDiGNSK1MFGAUwIIYQQQgghxDGoFaljjbdAE0IIIYQQQghxECpF6mijACaEEEIIIYQQ4hjUitSxxrdAE0IIIYQQQghxECpF6mCjACaEEEIIIYQQ4iBUitTBRgFMCCGEEEIIIcRBqBSpo43PABNCCCGEEEIIcQxqRepgowAmhBBCCCGEEOIY7iR1w1ySDWYISymKsEkTBbCUMiqFd6tS1qmqUIom9zxM75laogAmhBBCCCGEEHLKoAAmhBBCCCGEEGIXNjc35auvxwEKYEIIIYQQQgghdmFhYWFtbW1ra+uYyGAKYEIIIYQQQgghdqGrq2tqamplZeWYXAqmACaEEEIIIYQQYheKiora2tomJiaOiQamACaEEEIIIYQQYhcSExNLSko6OzunpqZ0Ot2R3wvtJAL4f3/N9W/OFNvcUK3UACGEEEIIIYQQKwkPD8/IyKitrR0cHFxcXNzY2KAAtgFHJYD9/Pz+k4KrV69KGRr88Ic/RLEvfvGLUpwQQgghhBBCnJfg4ODExMSysrKenp7Z2dn19fXt7W0p7yigADZn1gpg8Id/+Ic6nU7KNoICmBBCCCGEEHJ6CAoKio+PLy4u7uzsnJmZWVtbowC2AcdHAINPfOITdXV1Uom9UAATQgghhBBCTg+BgYFxcXFFRUUUwLbkWAlggcnboY0FcF5eHhKRIviv//W/okBfX5+U/fq1q6vrl770JZH7mc98RrU4OiCygFhWXnxsbOzNN98Uib/zO7+DcFtbm1gKQKKfP39eVAjFjibQEynPAA5TrIJU9Re/+MlPfhIlka7T6Tw8PN544w0shcVRibK3YikVSJSy94LOIzcsLEyKE0IIIYQQQpwLCmC7cAwFMDC+HdpYAEMBisJKlJIS2lVK3WXfxU0mCrAs5KsUMQKCVqp3t6sqoJN/67d+S4hhJegk9DaWwvqigJSqoKysTFQrA2GPdOhzM3eME0IIIYQQQk40FMB24cgFMOSfSeGnuh3aMQIYwlvkfvOb35SSFMi558+fl5IUyE2bFMAuLi4i17hdrL7IwvpKSQqwFiJXIJdRXpQmhBBCCCGEOBkUwHbhyAWwiJoUnAByURRwjACWb2Y+QK55ATw3NydyTapcWR6bvMj85ptvilydTveJT3wCKbz5mRBCCCGEEOfG5amXm09oUFxGanFdactAXe9U0+B8y8iiylqNUvbY8MeBpqHF/umV7e0DfkuJAticWSuAAUSdSFEhbod2jACWFz9MrkkBLLIAiklJCt544w0pW+NvAUJ7iwePz58/L0oSQgghhBBCnJVvnHn4nUsvf3Y/4oxXzqWwmutxbbeTum4n99xO7sbvHX1ACu+aMiwXkK3bJX3II3dgcWVDasBKKIDN2QEEMBgbG5PfR6XkE5/4BGQwAs4qgL/0pS9J2QaMe47N8uabbyKglMqEEEIIIYQQZ+Ub793/zkcvfnY37MzLzEshVddjmm8ltN9O7Dyw3Ukd8MwbWFrdlBqwkmMkgHd2dra2tqSIlRwrASyAGhRZxliuYHU6nZSk4AgFsPlboFGhyBWMjY1JGXuRnxYmhBBCCCGEODcUwJo4mQAGcq4KpYI1+bis/N4scb1UxREKYFdXaYO4uLhISbt84hOfEC+CVhIXFydl72KyGCGEEEIIIcQpsY8AHqQAPo4CGEBPihc+KVEq2Lm5OeMCMu++++6xugUaoHUgRRSoPiMsg1WQShhIS0uTMgghhBBCCCHODq8Aa3ISBTDknBCEUlwDiElRTABNKGXsAvX4pS99SWhd/KK8/OHcb37zm9JiuygXhwKXUhXIl1gPk2tSACMdXUUxIdrRVXRPS/rKiLdeAfkCMiGEEEIIIaeE91M/fTb10+L3YtGfBjbfeT0eu137B5N5v7evodjricgfFDb8RkzCbwSGyvbfdu03wqO/nVvg2tTSs7Aotff69XRA5vS/3u36pyuwia/fGb0ZLGXsZUm39flbxZ+6XPIHH+WZsT+8Vfcyt19axnp4BViTwwhgYnO0BPABEI9DQypLcUIIIYQQQk4N0L3CoIEvQQA3HUQA/2ZMwseiNyjsvwWH/zf8KsTwb4RF/WZ0fERPL1qc8s+cUQjgEUsFcO4fXCz4X1dKVfbpe63Ps6W7RA+AXQRw/qm/AkxszoEF8Pnz51FSvBF6bGxMvPiar30mhBBCCCGnE+kKcNruFeCGi691gzuzyWvjScLmar+zWv77QvGuVvz+fN0P5CwUe60b+E5eKQSw0Lq/GRX/44LinOGR9KHh6N6+d8sqfyMiRpLBQWGQwaPbG2uh+R8L4G/sK4CLhQD+3zeqfxXYuLm1o7KNrZ0Df3QX8BZoTSiAjxUuLi7ipmglUt5+vPnmm7/1W79lkMz/6TOf+UxbW5uUQQghhBBCyCkDAlgYBPCloj8NqH1fythlsfXcVo10QXir9g8W2y9JGbt8Kzf/N3avAP9mfMrdhiYp4/Xr+bW134+O/82wKP2t0cHhsLHtDV1InhDAnRbdAi0J4E9dLvm7+2W3EjqvxXV8bAk9vZMr0gIHggJYEwpgQgghhBBCiJMhpK+wgwngb+fmy1eAYVC5/y008jfCo38zNuk3o+J+IyBEujgcHf+XyWlrOztzAVkHugU67w8u5n/qUqHCiv73jaqyrllpgQPBZ4A1oQAmhBBCCCGEOBnyFWCYDQQw5G6o/nFfyaL0v/+/hJTfi0nwa+8U5fUvwfrGx1eALRTA/+taxQ+86pqGF+sHFmSrHVhY0h1QagrsIID7eQWYEEIIIYQQQo4jQvqetZEA/s34FJf6RilDAwhg+Rbo4X+5OfCux2J+g9KW8huWCxoXZpY/71IqC+D/fb3yx951vVMr3RPLBkNADi9LVVsPrwBrQgFMCCGEEEIIcTJk9SsEsP+BngEWb4GGBv7NuOQbtfVShgayABYGGSx+RQDW889X+//l6kzn6F88rJSfAdbbxfxPXS4yaVLV1sMrwJpQABNCCCGEEEKcDPH0r5DB5gRwrk0FsOEWaFn9dv2zJH1Fil4AvyEL4H2+AyxMqtp6bC2AO5xNAP/D1dc02vG3PEIIIYQQQsh+2OUW6HwnugVaJTNotONp0glNCCGEEEII0YbPAGvCW6AJIYQQQgghxJmwjwDmM8CEEEIIIYQQQo4ZfAmWJhTAhBBCCCGEEOJM8AqwJhTAhBBCCCGEEOJM2OUKcD4FMCGEEEIIIYSQYwavAGtCAUwIIYQQQgghzgQFsCYUwIQQQgghhBDiTOgF8IXnHwvg6F0BnKBWtpIldCiiHfpi+pJyYgdfgkUIIYQQQggh5DjynXOP/+Oa569doy76592JrXuY2uGa2fMkq09pT3dtb3qvnKVMd80aCCsfXVk7oHKkACaEEEIIIYQQYhcCAwPj4uKKioo6OztnZmbW1ta2t7elvKOAApgQQgghhBBCiF2gANaEApgQQgghhBBCnAkKYE0ogAkhhBBCCCHEmaAA1oQCmBBCCCGEEEKcCQpgTZxDAK9v7eT2LQY0THvXTZ/NGoZ9N77vb4I7aTQa7RTa2+mDGAZvF49hVCweXMIIKY2VhBBCCDkdUABrckIF8NL6NrTuV8K6VNM+Go1Go2kZhHHrlE4aRgkhhBDivFAAa3KyBPD48saPEvtVUzoajUajWWVQwjMH/ZA9IYQQQo4/FMCanBQBnNGzwOu9NBqNZkP7bnwfZTAhhBDilFAAa3L8BXD37Nq+0vdC7ggUstZMDunIRRnVUjQajUZ7UT0ljZWEEEIIcRYogDU55gL4asGoaq4mG1RxUue8VM4a6sdX34jsVtVGo9Fop9YelI1L4yMhhBBCnAIKYE2OswD+ecqAapYmDPJ1fHlDKqRAXOmFZhYvgoYhDJFssvD61s7b6YOqmq21X6QOVIwsw8qGl89mDalyYSiwtql//+rWzs6lvP0vQX8ptKt4cGlkcQNWNbqiyjVjWFOxXqqGUKFr+YQwdAbR28VjImqywxaateulNPQhvGW2Z3ZNrKbJTffT5IGCgSUzG1YYuiHX87JmSpULy+1fFJtlbGmDf/Wg0cxYWPOMOFkIIYQQ4gRQAGtybAUw5KtqfibMeJbWPbv2bzG9qmImLaBhWlpml8GFdaseLZaF376kdS8oy1soFP8xvHt+Tdodlmg2WfeapGlyVdlhSERl/aKHsslaUYu2KV3btPr9sVYJYOX2n1zZhL6tHl2R4obeyiUt3G7K1acAptEOaUvrR+kXCSGEEGJDKIA1OZ4COKNnjzaTLaZtViphAPL1AKrmScWEtLyBmdVNC/Wz0s5kDvXMrklV7AJR96xqUlnMWgGskugmRZ3KxEVjaYFd0BPRnOUC2KShcln0HkCgKk1etfWtnW/H7dngZrS3+fqVC5qUuBTANJrlhoFXnC+EEEIIOelQAGtyPAWwyauyqqudxiL5R4n9xp+4XFrfflA2blwSMkwqYXgqWFXAjCm7UTe2Im7QhVD0rZ+WpaasLa0SisYXqIF5DazSt0hRSVxlARWOvAKsJaSFyZtU1saWbDfjq9/Gkp4CmEaz3EwOQYQQQgg5iVAAa3IMBXD37JpqWiZMKW5nVjdVuZUjy1KeKaCsVE8Uq64DW/iOaGPBqTSl+BS5Fgrgh2XjcrVCBCobskQEKssoVd+H2cPKDltyC7QlWtHC9VKaXL+ZK8By0/vWL8/UUeBV7ZS8jip1LdcsY/4PCjTaaTYKYEIIIcRpePnKLzgsOi0rr7qhtXdofHxmaWZxbW5546iMAtgcWvc/S9kGkjrnlVnGFwONUenqf4vplTIMYOanzNUypS41vt6ozN1XAIt3QcnlQd3Yikp5qm5vRiVYcWUZpaBFLhpVXqRFVNUlMwIYbWX1quXivmgJVGNTXgQGgwvrqmeATaKqX9lJZPnUfbzXlH9EgJAWV+atUvU02ik3CmBCCCHEafjXs4+/e8nzZ/ejzr7KuxxefyO+83Zy752UPslS+z8OmzBVLqL9hkVEQJklcs2kSEtRAJsDkk81LROmfEGLSiT/PGVAytBGVe134/ukDAMvqi29MKgU29BgUK2u5RMJHXNKKStrSzMCWNQDHXg+Z8/rvqDx3skYhKkEm/zUsfE1TLTSN7+ub9gA2oprn5OzlO9JhgCWo3IZR5qqqwKVlBXFTG43IeCrRtV/KZBNKGR5KQpgGs1yowAmhBBCnIZvvHf/Ox+9+NndsDMvMy+FVF2Pab6V0H47sfOojALYHOPLG6ppmTDltdD1rR3Vc8LedeambjOrmyr9o3qbtNYnl7QMQiu8ZVb5gSWILvmRYNnMCGAtkzWb8bOy+9pPkwewlZRSXAX0tuo1XUqTe2s5lq+XVXaA7WbSKIBpNMuNApgQQghxGiiANTmeL8H6UWK/amYGU12zNX5UGArH+C2mkHzG3/tV3TKtuqHahuYYAay6uxhtlQ0vu5ZPnM8ZFheTbxePBTfNqK4SG/fH3gJYWb/xdWylmd9ultdzJnNIfPTY+EVoNBpNZRTAhBBCiNNAAazJ8RTArVM61cxMmEq4Lq1vQxWryuxrkLvS8ga07rg2aQeeINpVAMu9Mn6/lLGZuSh6fASwebNVPTQaTWm5fdLgQAghhJCTDgWwJsdTAAPvvQ+FyvbzlAHIPKmQgfHlDUtuYP5KWJfx9A7SUVXMvNlKAB9AasoYa07jK8CNE6tQhq7lE+Lyr3hKWXXDtvkrq5Zj/DIwLTtY/cYS9wD1WPKnARrtNBtGSNXQSgghhJCTCwWwJsdWAIOw5hnVFE021VVcmfrxVWhUSL6zWcP4Rbh4cMnkrK51Smfya8O2tZ8mDxQMLFWMLJcNL6seD7aH/SixX/VkshKI3rqxFdU7t1SGDhu/pMo8lgtgGFS3Vve0MHmN19p6KIBpNPOmNagSQggh5CRCAazJcRbAQOuTSMIu5I7MrG5KRS1jaX3b8hc+02g02mkwjIrSEEkIIYQQp4ACWJNjLoDB+taO8VusVPZGZPeDsnHla6KVIB25fAkwjUajGRuv/RJCCCHOBwWwJsdfAAssfNCXRqPRaBaa8SsVCCGEEOIcUABrclIEsAxvYKbRaLRD2tWC0aX1bWlUJYQQQojTQQGsyYkTwDL146v73hpNo9FoNNmeVExY+94EQgghhJxEKIA1ObkCWAVmdZDEGT0LAQ3TmOSdzRqm0Wi002lXC0YxEorX4Fv73nVCCCGEOAEUwJo4jQAmhBBCCCGEEAIogDWhACaEEEIIIYQQZ4ICWBMKYEIIIYQQQghxJiiANaEAJoQQQgghhBBnggJYEwpgQgghhBBCCHEmKIA1oQAmhBBCCCGEEGeCAlgTCmBiEp1O99u//dv/5b/8l8nJSSnpEBQVFf2n//Sf3njjDSl+aHx8fFDh1atXpfhJoLe39//6v/6vT3/60ysrK1LS4RBb1VYb4cg36b4dsEcPbXtkHqaH+y5r85PoZHH8j0/H7KAjOQzOnDmDRsPCwqS4KTY3Nz08PP7oj/4IJcF//s//+cc//nFfX5+UrcDmI6G9sarD2A5f/epXsfoVFRVS0l5s5VtVR4JtD4zD7CNLlrWTN7Rw9U/DYGvbKZw9OHHjwAmFAlgTCuDTgxhuMKwbY+wJLB899/X3wLw7MdMxJcrOWDgbFsUsx/LptYU1Kwd3M8P9AbYAEFvVwj7vu8Us3KQAe/ztt9/Wd8gs3/ve96xybIfsoTgODS1rYrzxzR+Zlm8TgbXlley77GHmZIfvmOXYafUtX4XDH58Wno8C+ay0agcZH65YNTHqSnGDhsSgqhqKD3MYmBmrVZtXpXjNC2C525/61Keam5tF4ujo6IULF5Bo3JyZkdAxmFkdk5vIqg6b2cgCq5SJmcNedSRYfmBYciodZh9Zsqz5MmJdzKPafVqrLxoSi+yLTc4yFZYPXPsSGBiotS7G9Vt1mCk5cIetXfAwxxixHApgTSiATwnC5Zsc0M14CEtGz339PbDWnYiR1MwFBxs6FcHhK9z3IolVw70l/RFb1cI+71uhhVtANLrvgSHPiU1uEDnXEuRD6zD7SGx84yPQ/JFpbYsWlnfwnExuzvxJengOs4P2XdbCym1yfB4Mq3aQGDZV/RS9Ug0RqonsgQ8DYA8BrOqeMWJZY8yPhFpLaWHVBjGzOmITiTpVmOyw2B0WIjbvvltMiZnDXnUkWH5gWHIqWe6tLN8CylW2yhuqMLn7DnNeGGOr2mw19srjlZkjweRgYuFhJpAP/s997nP4tXbvWDhEyxzmGCCWQwGsCQXwaWDf0VyMRMoClo+e8hBvZuCz1p2IkdTM3NTCoVYUsxzLx24VYgWBmS1m+XBv0mvKTaiwsM/7bjGrNqkljVpe0kIOU6HWlNf8kWltiwfoobhQJt84Cj75yU/evXvX+N5Ra08ioDo3xRU55WU6SxArZTkH20H7bjoLt63lu2DfkpgOii2mxY9//GOpqAGrdpDTCOB9+2NcwPKR0BIOsEHE6phBtYks6TC2rYeHh1AOMojiXFYtZca3inXZF7GsasUt3w6WnCOH2UeWLHuY+g8ggO16LptErCAqEdv5YGOvjNhlZvpjvE8tn8KJjSN6i+0g9oi8xXAuGB/DJrHkuFJymGOAWA4FsCYUwKeBfQcm44mXhaOnXOzOnTtoQmuANvbr5kdJ4eHMlLFwqLV2RD4YohVshJiYGAS0WrRwuBe1odjCwoL4c6zWHwLEVrVk7cTEF4Wt8qAmkauCX/ze975XX1+vXB3ktrW1vf3228KbWujbcnJy/v7v/x7lBV/4whfi4uKkPAUH3ptmZjPmJzrWtmhVefmkUD0q2dXVJc88lLNwC08isf1FAZPzLWztL37xi8iV96CUocGBN7vlHMPjU9Sj2gVKjI8cC3eQQNSvGmCNx2GgGorNH7HmMbNSqs1ruQDe11MYL7vvSCjvRMuxaoOYWR2Tm8h8h8UWQIXGZxPOZahiLKuscN8tZiGqI8HyA0OsvvnB+TDixJJlD1O/yd1nZvXtfS7L2HzslRH9MbO5jLeJmcPM+PySda8xKCzLY4FWN6z1FIc5BojlUABrQgFsV3CGy+NdYGCglOpwxEBjxuMaj1yWOGmxlDx+yfMA48HUct8MRG9Rft8OKzE5jBoXM4+1kxK5fuWmkxPhApUebt/h3kxtJo8fsVUt8TdKd25y2gdEQxZ6L7Gv0avPfe5zStcoUhCwZEvKblisnbxZMEsQdaq2lVU9lFFOHeQtrELryLS2RcvL7zsnE0eL8ZzMzEmE1lGhVfMqbGqhBs30WWujaWHtSQSO5/EpWsQiqgvyo6OjQtUgV9nbfXeQEnEAqLohuq067OVxVYmFragwnviqkDevaj5tRjECuYfKEU9+BlgLMyOh3E+tFg+JmdUxs4m0OiyvvlUCWNQpMK5Z66RTHv+q483Cw095rsm1mTzGgJl9ZAb5xFEObmKbq9CqX9lJLVS7z/zq2/VcBqgfldt87FUibxPlH0yVZ5lqg4h9eoDR+MCIjWzh6oB9Z0TEJlAAa0IBbD+MR/wjPNVNzlHg7OXR3yQmR8/BwUFZ1RtP39GQca7l7kT0E8tmZ2ejY1rDt5mh1hLfaQlm5l6yREc/tf6ugW0LzwRfJcXNDvfyoaLlPMT6qgqINd3X38jtikvKJvcakJuQMXO4mnGulvtd87NqsXbKPljVQ4FowsyBZ/7ItNajW9VD+UC16gqw5XOywyD37ZCYOYlkju3xKVBeMRZ88pOfxEzX+PKOVTtICC1VN0TfVOul6vBhDgPRqMktrDrUTcoV83tTeBPlW6C1buXYd+Ir+rlviwfGzMhjchPt22EgpJT484qMyUPF/BFoZt3Frpe7YfIkNX9giBVB0yMjI6IVrcHNklU2ibJXWucyMF//AQ5ySxax07nsSITilVcBW9hk/4HWYWbysDkAxsente7ywMcYsQrMUTEOY793dnbOzMysra1tb29LeUcBBfCpwHgOceSnuvEcxdrRE2DYwszG5FJaWOhOZPcsGhVRk07U2qH21CI2lLzl5dmV8aYzs0nt4TJNTjSVGB+BVu10UdhM/QLzR6a1h5m15cHg4CDmZId8BtgeO8gxiC12DI9PeyPWVDXAimNe5SZUJ4L5I9Y8Zk461eZVSUQzitEeyIeBVVh+3pmU90pUm8iqmTrOaGtHNiVm2lLtPtWRsO+BIXax8YiKFGNvbtUqy4gNK5YSqylHpRK7mK//AAf5YUOhomsAAIiMSURBVM6LwyDaPTw2P7nMH2b2wMwQbZKDHWPEWiiANaEAtis4w4/DLdAHwLajpyXOSfhO4zJKnyolWTzUimKWY/nYLTjARG3f4d5yryC2qlaf09PTUQ8KGHtWsaBqimat92prazt79qzqigdAyq9+9StL7gQT3TB5jMmTJ2V/LOmhmH2iGNbOkimF+SNT6/iBRsVqyvzWb/2W2JLWbkOHcZiOaW0ELSxs5fgfnwL5ULQQC6fgTimARTELOcDE96jOL60x2dpjA2AbqnaoCtmnaJ0XcjdUR4KZAwPnGrJM5srN4ahQXq63SpygEq0bcUU9on7lu5TM13+Ag9ySRex0LpvHTgetmWot33eW902UND8CiDKWIPpm1TFGDgwFsCYUwKcKMxMgFeadtMCMq1Zhxjmhkp///OfINdOW7ETlGmzuVGxeoTEWDvfyylqIcZ9lN2/Gf2Ozq/6yYOEWkCsXFyq7urqkjF3EY2/ikqb54wfIh5Axn/rUp1TLmu+hPPm2yqEeYKZlhgMcRY6Zkzng8AbWHkLH//i0CquOJeMjH8NyQUGB6mBADwcGBpAod/UwR6yZ000gb16V4lVFD8mBJ742P4wtXC9LOiwOPEuOKEtKijU1RrnuqiPB5IEhnw7mO48DAwpWuR0s30fywGtmv4j6LXwgCBzgID/MeWGMDWuz09grNrvJakXnLTkULe+bKGmrEUBw4HGAWAUFsCYUwKcKMQGyRABbgjydsu2waAkWDtxa0wgtbO6llFg43FvuFYSfs1WfLdyklk+FbTsjAZZ7a8uxbScP0EPL582H6ephNt0xOYmO6viUJYSF2PCAF6iOEJufViZRbUYLt6ooZiHGQ5xYtcNjuT+y/GjZF8tPZFuhOhJse2DYW5xYIoAtQa7BktU/knPZfm5LoKpZuY77Nmrt2G6TM0WGAtgxUABrQgF8qjidAtjx3TOJcwhg2b86/gqb/WYStpo1HqCHls+bD9PVw2y6Y3ISHdXxafkOshOqDtj2iNXiMAL4mIy3lkABrMXRCuADYMnqH8m5bFu3pZp0ic2IqPj0htgIYgVF2PwWtrxv9vAC9j7GiIACWBMK4FOFPHpajpnB0ba1WYWFA7coZjl2dY0WDveyS7MQB29SGVs9Y2k51vbQEmw7azxAD2XBZiEH6+phNt0xOYmO6vi0dgcB204TT5wAthzbnssHwNoOm9nsBzhODrkTVUeCbQ8Me4sTm9dvyeofyblsK7clvzRBaF0p1cDg4OA3vvENZBlf25A/KPDw4UMpSYG1YzsF8EmEAlgTCmBCCCGEEEIIcSYogDWhACaEEEIIIYQQZ4ICWBMKYGKMrW7aIYQQQgghhDgeCmBNKIBPA5Y86aGUuxTAhBBCCCGEnFwogDWhAD4NWCtoKYAJIYQQQgg5uVAAa0IBfBqgACaEEEIIIeT0QAGsCQXwaYACmBBCCCGEkNMDBbAmFMCngYMJYCUO/nY8IYQQQggh5MBQAGtCAXwa4BVgQgghhBBCTg8UwJpQAJ8GKIAJIYQQQgg5PVAAa0IBfBowvqXZJPJ9zhTAhBBCCCGEnFwogDWhACbGUAATQgghhBBycqEA1oQCmBhjRgDrdLrf/u3fRu6nP/3plZUVKZUQQgghhBBybKAA1oQCmBjDK8CEEEIIIYScXCiANaEAJsZQABNCCCGEEHJyoQDWhAKYEEIIIYQQQpwJCmBNKIAJIYQQQgghxJmgANaEApgQQgghhBBCnAkKYE0ogAkhhBBCCCHEmaAA1oQCmBBCCCGEEEKcCQpgTSiACSGEEEIIIcSZoADWhAKYEEIIIYQQQpwJCmBNKIAJIYQQQgghxJmgANaEApgQQgghhBBCnAkKYE0ogAkhhBBCCCHEmaAA1oQCmBBCCCGEEEKcCQpgTSiACSGEEEIIIcSZoADWhAKYEEIIIYQQQpwJCmBNKIAJIYQQQgghxJmgANaEApgQQgghhBBCnAkKYE0ogAkhhBBCCCHEmaAA1oQCmBBCCCGEEEKcCQpgTSiACSGEEEIIIcSZoADWhAKYEEIIIYQQQpwJCmBNKIAJIYQQQgghxJmgANaEApgQQgghhBBCnAkKYE0ogAkhhBBCCCHEmaAA1oQCmBBCCCGEEEKcCQpgTSiACSGEEEIIIcSZoADWhAKYEEIIIYQQQpwJCmBNKIAJIYQQQgghxJmgANaEApgQQgghhBBCnAkKYE0ogAkhhBBCCCHEmaAA1oQCmBBCCCGEEEKcCQpgTSiACSGEEEIIIcSZoADWhAKYEEIIIYQQQpwJCmBNKIAJIYQQQgghxJmgANaEApgQQgghhBBCnAkKYE0ogAkhhBBCCCHEmaAA1oQCmBBCCCGEEEKcCQpgTSiACSGEEEIIIcSZoADWhAKYEEIIIYQQQpwJCmBNKIAJIYQQQgghxJmgANaEApgQQgghhBBCnAkKYE0ogAkhhBBCCCHEmaAA1oQCmBBCjgMYjQkhTol0khNCiAOhANYE4zIFMCGEHC0Yh2vrGrJy8ioqq5uaWxqbaDSa85h0nhNCiAOhANaEApgQQo4cjMP1DY3ZOXkdnd0rq6tLyyuLS8s0Gs05TDrPCSHEgVAAa0IBTAghR455AYwoJTGNdnJNOs8JIcSBUABrQgFMCCFHjpYAXtGtDQwM5uTk5uXlT0xOrerW5Cn1ibDlldX1jc2VVV1f/0BvX//s3DyiJ24taLRDmnSenyhUq0Cj0Q5v0tnlKCiANaEAJoSQI8fMFWA4q6am5gf3H1RWVkEGBwYEhgQFZ2ZmjY9PQFhacmV4YXHJpKmKGRsqRzEI14zMrLDQsODgkKjIqJrqmpnZOTStKmxsKDM6Nl5WVh4RHvHur99582c/f+r6JCszq6Ojcx71mu05cmHDI6MFBYVYPDQkNCwsvKSk9CT+FYBGk87zE4VqFWg02uFNOrscBQWwJk4pgLFSm4SQ04c0BJxAzAngndcVFZXnPzyH3/WNzY3NLaRAWMbFxsVEx/T09OrWN+TCShOVDA4NQ4JmQMJmZcuWkZ5RXFTc29sHHWpGiELBLiwtQ34X5BdgESwYHRV9+9btlOSU8YlJSzSwbm19aGg4MyOzr69/emYWGr6isgrpqFpZzNjQOOrv7OwqLCiEZobgR6O3bt4KCQ4ZGRnF4ma6TaMdN5PO8xOFahVoNNrhTTq7HAUFsCZOKYAnJ6fy8gtLyypoNNrpsaLiUmkIOIFoCeDlVd3s7Gx8fMJPf/yT61evZWdlDwwOtXd0hodHuD52bWltg8I0LwUhI6GZIZpVhkTzl1Kx5PzCYlVV9ZPHroWFRQh3dHQGBwW/++t3Xjx73tTcMm9WPB/GllZWocxb29o9XngkxCfMzS9APycmJp159707t++gS7Ozc/qmqYFpJ8Sk8/xEoVoFGo12eJPOLkdBAayJswpgTIUxXRNXCWg0mtMbtFx9Q5M0BJxAzFwBhokVXF1bx//6W5eRtLK6oltTFbOHoQm0jV+MqIgiDMktUpTF7GGiaTSJphcc2zSNZluTzvMThWoVnMDCwyNSUlJViQe2pqbm8YlJVeIRWv/AYGdnlyqRdtxMOrscBQWwJk4sgOfm9VMm1ZFHo9Gc0qCLnFgA02i0E23SeX6iUK2Cc9iFc+dVKcY2Mzt35dJlVaLKIiMiX3m9UiUeud2945Kbk6tKpB0rk84uR0EBrAkFMI1GcwKjAKbRaMfWpPP8RKFaBdjjR4/z8wtEeGR07B+//BU5y6SVlJQ+c3+mstLSMlUxlbk9efrR+QvilpPMzKygwCCRHhwU/M1//bfRsXGEFxaXUGzfy7mQsm/94pfDwyMIY5GHDx7+8Ps/EFkJ8QkeLzz0N9QsLU9MTr39q7cGBodE1r4CeGp65st/9/eqxImJSVEb7Pq16719/XKWDW1c0cqljy6KVZMNWX/1hS/KBWjH0KSzy1FQAGtCAexIw6iKsXt2bl7uGIb4wcEhpCMFhj6jwPTM7GF6bsmyg0PDolFVutJEf4QTkg0p+rF1eQWdRFdHR8ekh/EUZWTTlxkd05fZXWUElAVQlXJr0GgHNicQwNU1dWkZWVgLnFnDo2PDI6M0Gs05TDrPTxSqMRbO+uKFj1SJ5g1q+Z7LXZUVFhSqiqkMyla+lbe/fwCqVYQhgKGHRRiG+cMHZ9+XoyYtJDhEpbfPvndGBFSXgkdGRm/duCnC+wrg7p7er7/xL8oULPLmz36emJjU3NLa0NB47oMPm5qalQVsYpNT0z//j5+mJKeglfr6hjPvvtdhdM/zX3/xL9EZVSLt+Jh0djkKCmBNTokARgBjN7QcpsnyUWjGUAzzaWFaiyBdWSeaWEKKYdxBQC6mtOVVHYbvwsIi8e4Z0auqqmrMd1EJovhFNC42bmNrW7mgbCiDFsWvnII1hYkaUGFkZNTU9IzIlcsgF8shIJZFK+JNqnIB+VcYVnxicirAz7+3r391bR0pG5tbRYVFkRGRWzs7aCUuLr6ruwcSd86UgsXyyMKK9PT26csY9gVqyMjITEhM2treEWUwmvv7+fcPDPK7JrRD2kkXwIQQcqxQjbEwiMm3f/VWbk5udXWNj7fPu2//Gu5bVeaQVldX/+ZPf/b82XPMQBDFDOEnP/qxkHkQwH6+flB9Vy9fef/MWZTR/zl+d8GR0bH/8d9/5/f+n99VJsLc3dwf3H+ADsfExEIw/+B734+NiUX6wODQW7/4ZXxcfE1N7TP3Zzev31Au+Ks3fyFWExJaFsZKg5BWSmtI4nfe/nVlZVVRUfHlS5chj5+4PsH8Ry6gZe/++p3Pf/ZzmCap0k0atsN777yL+RumkZc+uvi1f34DPe/vH5ALQBvfuX1HjtKOoUlnl6OgANbE6QUw5sUIJMQnpKdneHv7YMCCDFMdjkoT5aEhH9y77/rY9f7de+Fh4dB40K7KMtB0GIhTkpK9XnqKz3JgRMYAmpqahqWqKqvWNzbl8rKtb24VF5fAoPeEaExKTHp4/0F7R+ea4UMmurX1lpbWxIREYwGMLAjOt9962+OFx5VLl188f4GBG5P+jPQMVBIcHJKelo69WVFR+eu33n7l9SosLByeaXNrG6oVffN+5e3m5l5QUIiascjdOy5tbe1oFNV6vvR89PARtOj5c+dTU1KRqBerW9tpqWnwNzsGL4hVhqh++uQphlosAiUd4B9w7crVRw8etrS2ic4rDeXxi02kL/PocVt7B8qgt2gF3gheQYjq7Z3XaWnpQUHBWzvO+bgRzWFGAUwIITZENcYeuWFCUl5eoUo8QoPQHdp7B7K1Bu395b/7e/l6xiENs8f79+6rEmnHzaSzy1FQAGtyGgQwBpeI8Ih7d++9f+ZsfHwCpKkQnyYN5bEgir1wfwZl+NzNPTY2btZwfVUuY5hsr+Xl5d+5dfv5s+fQpagTcrS7pxcBZIaGhE5MTCIAU17bVApgkQI1DuFaX9+wrwBGo2JFpmdmIyMi8YswupqSnHLX5e6H738AeY+9qS8TEYkOo4tYBIYykOgoD80pUiDmc3JyGxub0Bxq3treKSkphWweHBoW3UAZLB5qENWbhqu1iI6Ojt24dl3UgBSxagjHxsT29fXLa6T8G6pUZmk5JjpmwHCZF23dv3uvvqFRNITVLysr9/L0wlIoLC9Io1lrFMCEEGJDVGMsjUY7vElnl6OgANbE6QUwRFdpaVlGRubqympwUHBgYJD+Aqa2ABaGAkpT5aKG9o5OXx9fSDtov+DAIOg3Pz//ey53R0bHoH5zc3KhhLd2Xnu/8j7zzruoQai7+cWlzMws2NT0DBZBD2dmZiEgoT8RRTHI18rKKihbKFjRf7lR1AARG+AfMDY+gSbwCxmMBVNT05CbnJzi9uTp+sYG6sHinV3do2Pjff0DqBAB9G1oeASNokIUGJuYTExMKi8rRxNYl6ys7GCDQn7p8bKhoVGo4s2tbfTT388f21O0PjM79+L5i/b2Dqwa5H1Gesbk1HR5eQXELaqFTm5qav6HL325qqoaq47yY2Pj0M+oFts/LjbOsCvW0Y3nz54PDg4Jwby98xo9DwkJFdeZabQDGwUwIYTYENUYS6PRDm/S2eUoKIA1cXoBLA64ickp6EAINhg0oXwgHsZQFTQeDBVi8h1nuAKMxNm5eUzGUQCtQ3MqPxOHjkG4wsR7/LCgiKKSaYM6xa++TkOiSgAjjBQsODc3D1WJMCpHDfiVV008jquvdmwciSiGBVFANCEEMHLHRaPjE1NT0yiAOtEu+oOthErk5tB8YEBgR0enkMSQtZUVlZHhEYgKPTyKNgxrh8LI9fL0griFppVrEGWglkWKbn0Dcj0jI1M8A4yNhl75+PiiUbHFaLQDmxMI4LW19VWg09FoNCcz6SQ/UajGWBqNdniTzi5HQQGsySkRwHa1Vd3awOBQaEhoSHDI0PCIuLZpE4O8hMaUbHQMClZVwN4GVQyTo9ieqhSl6UW5RpZs+hJ7d8q+i9BolthJF8AYh+vqG7Nz8/Hb19/f0wvro9FozmHSeX6iUI2xNBrt8CadXY6CAlgTCmBbGSbgNr+MOTE5JV8QhgZ2vACm0U6KOYEA5neAaTRnNek8P1EUl5TRaDTbmnR2OQoKYE0ogGk0mhOYEwtghO3x97XDmOjPMRxg0SVVr45hJ2mn0KTznBBCHAgFsCZOLICnZ2bnFxYhg2k0mtMbpph19Y3SEHAC0RLAurX13r7+uNi4yIjIkdGxNcNXyoxl3r4GvTozM4uqZgwvKTBdw27NJisX6cuGL4TnZOeEh4XX1tWv7n7RTS4gTF5KlS5MmSvMfAEzWbJhQ83OzaNj2IyIouTKqm5mdi47O6ehsQlhZWEazcEmneeEEOJAKIA1cUoBPD09U1xSVlZeSaPRTo+VV1RJQ8AJxMwVYDir5uaWuy53M9Iz4uMTPF96enl6RUVGtbW2IXdfaYciC4tLEKsud1y+/c1vPbz/ICgw6OULD1TVPzCIAqgCOhbhlJRU71fer7xe+bzyTk9LHxwaRrrI7evrR/mXHi/FN8br6uoRhgZe39hE7vjEZF5efoB/AHJRQ1xcfGdnF2pGbn//QGJiUlBQcEx0TEhQ8Itnz9F6ZWXVnOFTbah8fmERawd57+vj6+ONf75YtZqaWqSjADrf1tYeExOr75inF5rIzy8YG59Ao/IKwra3d7D1Ll34KCkpeXpmVs5FAML4nsvdu3dcpqZnhPKXl6LRHGbSeU4IIQ6EAlgTpxTAhBBysjAngHdeQzFevnS5vb1j5/VryMKNzS3IvOysbEjQNsOXyeTCkHxr6xvGqnhre6e5pfX+vfsdHZ2iEqE/UR4BiOrAgEA0JJaFaFxZWU1OSobs7O3rhy7NyspGYeSK+iEmIWUjwiM2t7YrKirPvPseasjMzILWTU1JhdZ99OBhWkrq5OQU2oKCfXDvvug8HG99Xb2nx0uIXvQKtaEqrB0EcFxsHORrdFR0bk6ueJsgenL75q0L586jdXQmKTEpOTkF/YRILi0t01/0N6wmOoaSWPY/fvyThoZG5TfVkAVDYWhgLIhFUK2cS6M5zKTznBBCHAgFsCYUwIQQcuRoCWAIttGx8ajIqHff/jXUYEJ8QnVNbXFJaVBAoLfXK6hTyFFREjJ4fGLy7V+99fv/85MPHzzUS1mF2ENuV3ePl6cXdGZ1dQ0qSUhIjI2J7R8YhHocG5+Ij4177v4sLzevtrYOEtTdzR1adG5+AR2YmZkNCQp+/ux5YUFhTU1tRkamxwsP9Mf9qRsWn52bLykpDfAPgDqFrIXMzsvLDw4KLi+vWDJ8+y0mJvb8h+dSUlJnZ+egoVH59avXYmPj0CjEKpb64P0P0JmGxiaIeTTh7+ePXBSGDh8YGEQYKaitpbUNfYuPi09ITOowXGGWt5Je3je33Lh2HYUnJiaxoEgXKtrl9p37d+9hXSCGF3kFmHYUJp3nhBDiQCiANaEAJoSQI8fMFWDINig6GAL60MYmDAGTd/Mie2NrG7mqdGGiqvXNLdQgKpSzUJshcwO5evFsuP1YmSs3LRZEVLe+Idcg1WwooFwcv0hHCrJFiqgI/xDUX8UVVYllNZoWi2wYug0JLTeqNBSBxIUUh05GtUjBUjOzcwUFha1t7aI5ZXkazZEmnecnCuWra2k0mk1MOrscBQWwJhTAhBBy5JgRwDQa7aSbdJ6fKFSrQKPRDm/S2eUoKIA1oQAmhJAjhwKYRnNik87zE4VqFWg02uFNOrscBQWwJk4pgLFSm5ubG4SQ0wTOemkIOIFgHK6prUvPzK6uqevp7evu6e3qptFoTmLSeX6iUE3caTTa4U06uxwFBbAmTimAJyenCgqLp6ZnZucWZubmaTSa09v8wmJtXYM0BBBCCDkcqok7jUY7vElnl6OgANbEWQVwUXHp3PwCbyOk0U6Jrazq6huapCGAEELI4VCNsYcxz5eeqhQLbXZuvry84vyH51TpjrH5hcUf/eCHU9Mzcsqd23dKSkrlKI1mrUlnl6OgANaEAphGozmBUQATQogNUY2xMAjCZ+7Pzn3wIezSRxfv372nKmBsfX39F86d/7u//hv8CmsyfANcWEJC4pl334O+ff/M2erqGjm9oqLy12+9jcLIqqurR0CkQ4uiUUQ/fP+D69euDw2PiPQA/4B7LncfP3yE9PfeeTchPkGkw4aHR0Q9sIsXPkpOShbpC4tLXp5eyPrg7PtIb2pqlheR7Tvf+nZXV7cq8Qff+35ra5sqkUaz0KSzy1FQAGtCAUyj0ZzAKIDtSmlpaVPTYTfv/Pz84sKiFNkF/nhocLClubm7u3t1dVVK3QUeanx8rKG+vqOjY2VlRUrdy9DQYG9Pz/r6uhS3P0tLSzU1NdlZWW1tbZsbG1KqQ8Dmam5uzsrKqq+rW11Rby67gqlCd1dXbnZ2RXn53NyclOoQcBgMDw0XFBQUFRaNj49LqZaBndXT09PY0DA8PCwlEctQjbFQjB+dv6BMgTRVRs2YrGCVBrGKeZochaqEgkXA7clTpUhub++A3kagf2Dw7V+9VVpaJtu1K1fr6htEMWUTDx88hPAW4eLiknd//U5IcEhBQeHExCQaFOn/8eOfKKvy9fGNiIgUWcK6e3q/9s9vKFOEBQeHQGyrEmk0C006uxwFBbAmp0cAY4JMPUyjOas5qwAe6O9vbWmBwIPqgOaZmZ5GGPO1/r4+qcTr19NTU5CIlRV6qquroTNFOoZ3CJXmpqa7d1xuXr9RVakvgn9TU1OiABzh+NhYXW0t6kTh5eXlmprqirLysdFR4SPhLLs6O7Egqp2anBRLCVBgcGCgsryio70dxZAyMjxcWVGJ3qp07PbOztDQ0MXzFzLS041db0lxsc+rV9PT0+iAlKRgYWEhMT4xKTHJOBeeCz0PDgzy9nyVnJTU091tsgbbgt3h7+uHfSHEJzRVXGxsZkYG+ikK2I/FhYXAgICszEzR1uzcXGJ8fEpysrWC8GBER0VHRUTOzs4ivLm5mZqcEhcTgwNA5NqVnOxsb69XE7urmZ+bFxYS0m3N7kbJ1JSUlx4ezjfbsSuqMRb23jvvzszOyVEoUllnCkuIT1BefZXNpAB2ueOivJQaHh4hLs+mpKSGh4XL6Tj2hACGVoYAVnYAKTAR/kghzh8pBPArr1dyOkxUBbt44aP+/gE5HSZrY2Go+W//8q+UEl3Y1ctX0ENVIo1moUlnl6OgANYEjsHpBTCmxgODQwkJiYWFRRjJKINpNOczZxXACwvziQkJcGBwWk1NTf5+fl2dXfML80mJieVlZUJqLi4udnd1QQNDIUPuPnV1jQgLE4sLIFegXqSIEfAC7k+f3r5xE+pOpKzDSRo0rUxQQCC0lhRRAIdaWFDo7eXl+ugx9NhA/4Cxc4VWuXDuXGpqqqpOAcS8v6+vUFbGQOylJKWkpqRKcQPocFOjXtUXFxVDzOM3JCi4qbHRAX69pbnF9eHjyYmP/xaALe/25Mng4KAUtxvYRG6uT+vr6qX469fTk1OvPD1rqquluD3x8/ZJSfr4AMAhFxEenp2ZKcXtCdr19/GVIq9fw6VnpKcnxMVbNXXBIq+8vCiArUI1xgobHRuPiIj08/WrqqqWxadsmZlZMFUiDCXT0tJ9fXxTklMmJibldKjLjPQMH2+fysoqORGG8vn5BShfWlqGaEVFZVtbu8iamp6Ji43DIlhQFsMNDY1ymbHxCYRra+tEFqZ/LS2tAf4BQYFBqkvWaB29RVXxcfFYSpklDAu+f+asMgXTyDu37yhTaDSrTDq7HAUFsCanQQDDRjFmT0xmZWbBdGvr1MA0mpOZswrgnu5uP1/fmOjo+bn52traAH9/yOCxsbHoqKiMtPSF+flAf38/H19xe/D4+HhBfsGFD8+9fP5icWlJ1ADCQkKeubmvrurg+aAYqyqr+nr1F5ARhUfs6uryePY8KDBwZHh4dGRkaXFROEh4h6WlpdHR0aHBwYf37kOmInd0ZBTiB1koU1dX99z92TN3dxRYWV6OiYq+53I3Py9PdTl0fn4e/X/m5gYHLCUpEAJYvmqtQgjgtNQ0KW4Eepiemub10rOqslLly7COly5ceOett2traqUkBaFBwX/xZ5+/df0GtoCUZAHY4Lk5Od5er1pbWtZ0aznZOdiw3V3dyk9woUthoaFv/+qt0JAQ4/VqbGj4yY9+/K9f+3plRYVVE5H1tbXysjJfb++Kioq1NV1dba3ro8dQv8p7v7EF0lNTscro1eTeK/ZgbHT0g7Pvf/nv/j4xPsHab4ZBeAf4+WHdcaQNDAw8eeyamZ6xptNJ2QbKy8pR/80bN7DlcYRIqQbQyfsud//6i1/0eP7C2pvVOzs7ggODkpOS5+bmZqanoflDg4NX994P39Hefv3K1XMffFBfV2dyq2ZmZJgUwFvb2/n5+f/8j1995623+nf/AEQEqjGWRqMd3qSzy1FQAGvi9AJ4VbdWW1sXFRm1srqam5uXlZW9tr5BAUyjOZk5qwDe2NiAx9rc2BBOC7pFSBcM3RASIhG/09PTExMTy8uSc0XWxvqeZ1NRHtJ3YnxcKcmQiMqhJVAeQMSurq6ifqFe8G9jcxOCB6AbKID6UQBh4ThEZ2SHKsqIdFHDx+zsNNQ3xMfGtjQ3Sym7IOXlixfBQUFZmZnGWhTNRUdGXb10OTU5ZXr3zm0laBEd0Pd+fV3dqGHLGCeC8LCwSx9drK6slOLWg00xNTmJFZbiRoitJEV2GRwYePzo8YP799FnKcl6sCzELXaKFDcC29/YrePw8PPxvXHt2vDwiJRkPdi1OIoWF9UPcstgg6OMFNkF5WOio69evgzRLiUdCBwec7Oazx5ja2PFpcguSBwbG8vLzbt57brnixfiQFXS3dX1kx/9KC421uRxcspRjbE0Gu3wJp1djoICWBMM+s4tgDEtHh0bf+r65O4dF3f3Z25P3Xp6+6CKVUckjUY70easApgQQo4E1RhLo9EOb9LZ5SgogDVxegEsDjhMjmWTE2k0mtMYBTAhhNgQ1RhLo9EOb9LZ5SgogDU5JQKYRqM5t1EAOw3j4+PJSUlBgYFpKanyC6sBXFVBfn5IUHBGenpSQoK/r29ba6vxDbd2YWcnMyPT18enIC8/NTnZ19u7y9TzzPYAk5XiomJPD4+szMz0tDQ/X7+6ujopz85getDS3OL10jMlKSknKzvIPyA/N1fKsz/DQ8MBfn5RkVG5OblhoaFJiYm6vY8cm2F5ebm1tTU8LPzRgwcOeD+Zs1JcUkaj0Wxr0tnlKCiANaEAptFoTmAUwE5Db09PfGxsc1PT5ubHjzFD0kD9pqWmyV/9mZmefnj/QUN9g4jaj82tzby8vIS4ePnp2fa29gvnzsfHxYmoXYH2Cw8NlSKvX09NTWHjZGU44vXL+fn5z9zdN3Y/dDw/P5+VlZUYn6D6zJU96O7qgnaVv9yLvV9SXBwXEzsxMSFSLAGLP3V90tPTI8UJIeSUQQGsCQUwjUZzAqMAdhqEAG5saFhXvClqZWWlpLgE6mtkVxTNzs4+vH+/ocE6AQwpNT83t27li4iBTqcbHBzs6uwaGBjo7u52f+qWk50t5VnA5ubmwsLC0tISfK6UZBmhwSEwKWJ4kzOEd35enhS3gO2t7cXFRbRura/Pz81zc30iC2BMnjIzMtJS0yy/Eruzs72i3+DzciUW0tXVdd/lriyAsd0KCgqSk5JMvghNC+yvJ49dtQTwxvr6wvwCjgdr9wghhJwUKIA1cVYBXFBYPDk1Mzs3j380Gs3pbX5hsbbO7hcDiQPo6e6Oi4lpaW7e3uubdra3G+rrIf8SExKio6IiwyOGhoaU6gVhCKd3f/3rb/7rv6Wl7vl0MBjo7//g7Nkv/c3fWiVcAaqdnp4uKynRf5A5NjY2Jqa6qspYBCYnJv7b175+9t33ent7VZqqtaXlL//iCz/9yU8OduN0U2NjYEBAUmJiQnx8THR0d1eXlLFLeWnZD7/3/R/94Ad1tbWqyc3s7Oy/f+Mb//SVf6g60CuvoSEhv7HKSQmJ0ZFR9UZ3X/d095x5592v/fMb6WlpqrnE+vr6h2ff/9z/95m0tDTj9zPvy9zcHLZ2RFh4cmJSTFR0SUmJSkXPz8/fuXXrK3/3977ePsq/lciMjIxoCeCwsNC//au//uj8BTNvtCaEkJMOBbAmTimAsVJwt3CWhJDTwwEm2eQYgv0IwQkZCclqw7ttx8fHa6prcJxIcUexsrLS3d0NMeZ4V4uV7e3pgYg9wBXvwzMwMIDWHXC/tDFY8empKbSOPhivO3LbW9v6+vSfwiaEECeGAlgTpxTAhBBCCCHkJHL54kUpZA2YzTYaPRNRX1cXGhyckZYuxXdZWlpCOmx2dlZK2mV5eRnp09PTUtzW9Pf3u9y+8+jBw6nJSSnJDvR0d9+5dcv10WPIHinJDkBW3bpxw+3JE+UX5m1Oa0vLzevXn7m5LS4sSElm6erswh6MiY6W4qcYCmBNKIAJIYQcK9Y3NuZm5+CtjS/fwX/39vYODgwcledCBzY3N1U3OTsANHokq4w1xdbu6e7BiktJDmRsdBTzNmtvVMaGwiI4flZWVo52tkeuXroshewMxorvfuvbxrv74f37Jo+focGhV55eUkTB4ODgg3v3oiOjjLW0TfD2etXR3i7CSQmJ2VlZImxbnrs/k+9xiAyPKCkuFmHbAnU9MiK9GjAwIKC6ulqEbcv9u3flh/+9PD2bm5pFeF+uXLokhU4xFMCaUAATQgg5PvR0d4eHhhbk5UP8KO9Ynp2ddXv6NClB/xbihYWF/Lw8j+cvIMykbPtTU1Xt+dIzISHhiatre1ublGpnMPNraW5JTUl59OBBQ329I+cuHe0dAX7+udk5iwsLa+tr8XFxr156ToyPO0D8T05MhAQHJyYkTExMQPkXFxZhqo0Dw8LVx6xmdWWlvq7u5vUbDvtglXPT2tLy/ntnsOtzsrNvXr+OFEjEutpaBJC4ppP+OIKT9NaNGyIs0BLAhqfT/xWFdTodduvAwICUYeDa5StSaJeuzq6Pzp1HQysrKxc+PGd8B/v1K1cLCwqkiAKrBHBpSWlYiP6dc/YTwMoNAjVy++ZNKWJTlBtwYX4Bo4cUsSnKdcGp+szNXYrYFGUr/f39Pq+8pch+UAADCmBNTqcAXtPpMCAuLS1pPTSIWRdcPsoop19Ow9TU1OEfCVteXl5cWHTko2Voy6rHyXCeLy0u2vZUx/kC7+v4owIHKg7IZcMrZLFGODIPfzUGa4EpCFZHihu2mHKHIsv8/kX5I3nAjzg3Jt8CDcWbkZ6el5s3My3dzjc1MeHm+sTyqwEHRj877x8IDQ4pLSlBdHpyys/Hp7OjQ+Q6hsHBwZCgoJbmZkf666LCQo/nz+XXfenWdBAYkeERGPxFiv3o6el54uqKtRZRDER1tXURoeGjI6MixRKwuJm3QBOrgAAODwtDABIxNSUFgeSkpMqKCgRiY2Ie3LvX0909Pj7e1Nh48fwF/QK7mBHA2DtSxAhjAQzm5ubOvvveB2fPmhS0v/7VWw319VJEgeUCGOLqFz//OToM+843v/XO22/bw9dfvPCRPPMcGxt75uYmwrblo3PnMVsQ4b6+PpPXug/PhQ/Pya20tbYGBwaJsG1BK1Lo9eu62troyCgpsh8UwIACWJPTI4Cx1zMyMjCBQBizq/HRUZ1uVWvdiwoK6uvrMbnXUsgAy6oGRxRWVoiDbEOhH+RhQnnwqQQGFjfTIhD1K1tBH+QoArk5uRMTE3Jbxo0ipbW11cLnKGRU/YT/a2ho0PoDwfz8PFwjGpJb38NuoqpO1dYzJjw0DM5JiuzS39eXlJQkV6WsE3s8KzNT+cZU9Me4UdUqoIDpbhtA4R9893t5OblS3IBcg7ygsgblLhPp+DW53bQYGx1NiIvDdEEWwO3t7el7n2hSbT0UU65pV1dXfl4eEoFIqaysjIqMXFpawlYSKZgser18mZOdI6IA7h8TfQSwVE52NgSJagc9efT4ykU6GGJjTApgHIQjIyPubm75ubkIY2itra11e/JUvplQgEM6OysrKSFxcO8FJUF9Xd3Zd991ffQIc18pyQLQHGb2A/39qLO7uzs3J+f6latlpaXy2STA7DkhPh5nkLE+1K2uRkdGvvXLX0ZGRKiGoH3BSYdFOjo6X3l6VldVofKN9Q3VDGZifDw9LU3/laDpaVWvADbIO2+99cL9GTaOlGQZ0JyeHh4N9Q0YXlBtTlaWn6/vwMCAsomFhYWC/HxIIKy+cdM11dUfvv/Bres3MIhJSZYxNDTk+cIDelv8iQ37+uWLF21tbUr/uLa+hnEMs2GILtUGEZgRwJgIer30PPPOu4X5BdbukVMIDkJsSWyu6akpCGBIXEwhcLy53L6zpltzf/oUB0BTU1NYaOi5Dz741r/9O84RacnXr5ECj4l9hD11/eo1kQjX7O/n9x8/+nFYSAisu6tbpOMcFynf/vd/FwFUi3T8/uOXv4xjAA5Lp9M9c3P/53/8KhSXWEqASn791ltSRIG1t0CDjLT098+cffTggdJTL8wv/I///jv/7+/+T9Vx3tLcgvT01DQpvh9Yhbd+8UucNfFxcdiSqtp+9pP/QG3iTwxKvvx3f//mT38qRSxgZWXlV2/+oqiwMCYq6trlK6pWvvft76AV1UwG/OWf/wX8vhSxAGxYtFJaUhIRHm58Kftfv/Z1tIIDRoobQE8++yd/ev6DD6W4BWDyg1bKSstCg4Mf3Lsnpe7y1a98Ba2ImxFUmBTAOGj/+A//j8lDwimhANYEx6JqUutkYAWxy328vfNyc2U/h1Hv+rVrz92fia/qhwQHP3vqtqrTXbtyNT8/HympySnnPvjQ9dHjro5OtUs3gIEjJjoao/zTp08xq4gMj8AojylIVERkfGycXqK0tSUlJsK5IgtRdCMpMcntyROP5y8gPMbHxibGJzCa19XV3bl5C74BBWKjY1KSU5ITk+AnjA/Qvt7es+++F+jvf+PaNT8fX/ElD6gaDKOREZFVlVWINjY0XrtyxdfbB55JzHWKi4vhKl48exYcGNhsEP+YUigf28D8Bn4IY8GFc+cxWRGJSjC1wkQhPy/f8+VL4W/gZi5/dNHT42V2ZpYsn2Sg4FOSkzG6YcWLi4qQ0tXZifkiNvXc3NydW7cLCwvRpRtXr2FoRiXYUFj38NBQeESxBRAVValAz8NCQkUY7ZYUF3t5espqH3MjrHhFecXdO3dk54EO9HRLnnVsbAz+Bo3Cp4qxD1sJlpqS+tRV/3doyEtfb2/MazHRxAFgWMgEmD0PD+lnz9hHbq5PXG7fTk9PhzjHedTa0iIcalxMDPwB1veDM2cxZcQu8/fxy87Kxvz7zLvvhYeFYUqKVra3t4qLil1u3cYivT29EJOThgNSCdYOa33l0uXoqKhmw1QAYHaI2kQY3UAWVg2HTWJCAlKmJqdiY2IN3iJkbnYOKf6+ftevXsXmramuQRSTSEzHqyoq83LzhIPHlALHLWaKBXn641+ACvNzP/7cKBxqSFBwSlKSfNU3MyMDB7kIE2IrIDUx0OEEwYhq/N1XTIYwUmHMXFXcvCCD8wVKzOTLh6Gc/+WrX8Xpf+ALmDhZpqamoABHhofn59Wf1V1ZXunp7kHnVSMYhuKIsPB/+/o3lKrAcjBYDQ1CeusbxX99fX0Yk1UDr25tzfCYbrfqL2tweRhqvvOtb/n7+kpJ1rO8tNzY0FBbU2PyJTcbG5ujo2OdHZ3G6rq2uvoXP/v57Zu3DjzHQP8xsFdVVsJdSkkKMPRhd3R2dMDFS0m7YBdjNMZ4dfa9M5j2Sam7YCvBQ/3w+983+VcScnLBvvb2eiVFdsG8CzrT+L5Z+PHvfPObEIdiHnhgvvutb8PbShH7ABGLGaYUsRvBgUFal+ttCHYQJKgUsRu1NbXYs9i/UnyXqcnJL/zZ540nrk4MBbAmcNVOL4AhhyCNFoyueUKfJMbrBQOAs3zvnXfGx8dFVCY6KtrkxVKoqZfPX7g+fFRZUYEmIGwqd7+yCIkFl9zd1QWd+ejhwxvXrgvhjUE2Iz1dnhtBhECQ3L3jgt+tzS1oVww9Tx4/dndzu3jho+5d2SYzMz2LmqF8IPzgtiFdcBCnpaTcv3fv7u07keHhKIPKc3NyMScQiwCIFkwiF/ZOXDAl6lc8P1NeVvbB2bOqMgJ0MiMtbXZG/45ErAUUkUjPTE+XJbQxmLGpdBH6DPHc1dUlJDGkLMIIoHtQyxUVFZc++ggqVO+oLlyw5NWLEIpPXZ9UV1WJCZ/4a7S8beWAUgAPDw8/e+qGXXb3tktXp751bARI8aePXRvq6rHIzvY2RPiDu3eDAgJxbIilzFOQX4A9ggAawiGEAI4odAn7Oic7G1usML8A01asL1rPy9XvmrQU6e/E/X39mekZCGRlZMITYxOJGozB3Dc7c897MpQCGAdbzm4Y6h1RbMDnz9yxPS9+dEE8KIXDKT/vYymLEfDalSsoNjk5CRGLVYf6hYTG8RnoH6A1IOB46+3uwQbElFRKIoQQQgghxxIKYE0w93VuASzA/u7p6XF/+hQ6ZHpqqrK8HHq4qbERqgm5xYWFMdExOp3O39cPeml1dQWKBZqqv78/PjbW5N+KAvz8oIFXlpeTEpMGBwc72tsvnDvX2dEJSRYTHT09PQUFuLS0NDI8cvvGTaGm0IHU5JT5+Xmh2SCHKssroABzc3KqKivRw7CQEAgnpIjD1NDOx0xOTELKQs+gfG9PLwRwX28vWkH5rMwsPx+fLcO9YempqR0dHZCg6J5+qclJrCPEqlgL7OvlpaXEhISWpiakYO9nZmSmpaYuLy/7vPI2eVtgXW0tasDmqq2pgUBCChaMi4lpb2tbXVlFDaKYkqXFxYiwcGxAtC4uGkBIh4eFhYaEiMfJoiIiXW7fhq7GtqqtrUWXQoOD0QTWpbWl1fLrM6gNOy46MhLdyMvJgYZEo9h6pSUlSEE9WRkZjQ0N4kpRTFT06MgI+uP25Kl4bhCNoofYVlCt2EeVlZVQraurq9Dq2O+GFsyBJtLT0qHkEYByxuGERKza3Ows6nn54gW6l5aSOtDfjyjENspgHa9evowo9oiP1yt547i5PomLjZU3ZmRExC9+9nMRxW9ra2tCXDz6KY4ccVUEBx4OMCw7PjaGVZudmcG6YAvjmIyLjYO4xcZ89OCB6BU6mZKcjNbHx8fF5oUexqbGcQsRjiYAqoUCT05MRBgFVKA8jjHUIMUJIYQQQsgxhgJYE0x2T4MAlhGTe8z1ISegEEQiAms6HbIgfsSNc9AVKACpYFIMgI31dcgPlEFViEL31lRXY1kh8ICoATUjRZRZWYY2gdaT3ryFzY7cpcUl0SJAW8tLy1hKZ3TzHtBr1+Vl/OLwFb84iPGL8vhFK2I/4hdNoGeiUVSOOtEKysiViG4gBS3q1303IHdehdhccj/X19ZFDUjR2j5iETQt9wq6HYpL5BbjVOzowOYQmwJgXQy9PtS7ndAf1IAVQVi/MXfXVPRcNIEUsbmQgk4iBa0KYYkC+j1iKIPovkhbz3DkILCxrq9E7He0iK2EalEV1n0du2xzE7+DAwMZ6RloV24Cy25ubESGh6MbIgWoCqBy/WosLckCWHQSiWIDboudbnhCWB/FmhqOXnlNAcL6PbK8jFyRoq9WcYSLhoCcQsiRsLCwUFleER8bl5meofxOJgbGqsrKhLj4hLi42JjY1JSUvr4+nA5Stp1pbmqKjYqOjY6Jj4vDCObIPwYN9PejUTQdFxObl5trfKeSnZibm6uvq0eL4SFhWven2A+MXfm5uVEREbHR0akpqe1tbRjopLz9wMjW0tyMQyUqIlJ5SxQhhJwqKIA1wWRXSBRyYLABCwsKIsLCOzv4uQUTTE5OxsbEhIeFYRqH6OzsLOYlmN1CsIkCpwfMySJCw8vLPn5eqLurKyYqOjE+gbM0QgS9PT2QuFBcOxp+emVlZXpqqr6uzuvlSwd85GZNp/N4/lz5EEF7W3tYaGiDfb6SoiI8VH/vjBQxvCwgJjpavI/aMWxvb0VFRpaVljpyqoCB8cG9e+JtC2B2ZiYjPS0jPd3Ch1MEY2Njbk+e8i3QRElMVBRmIBADUtzA9StXS0tKNzY27t5xqdp9nM22YMLzzttvY/6DsevdX/960T4vYerr6zv77nuoHKPomXfetdOfs7s6uz44e3Z5eRmB9987I6Xamva2tvMffIjRvqO93cJHoDE+wHFgxaU4oQA2AwUwIYSQ44PJt0Cr2NzcbKivf/LYtdFwk79d0el0z5+6FRjejyiYnp4OCggsKS6W4vYEAlh++R9YmJ9PjI9PS02V4vZneWkJChwC2JHTpu7u7scPHoo3LADsgqrKqujIKPFoj4XwM0jEGAhgjC1SxEBeTm521sdv2VB9xslWBPj7y6obYtj4kxY24eKFj6TQ69cdHR2HefudGS599HErTU1NocHBUsSmKFupqa6R30GzLw54ldcJggJYEwpgQgghx4ee7u6EuDjV943gtmuqqyPCwzPS01tbWirKyqIiI6Oj9igiuLOW5uaf/PBHX/rbv42NjpZSd5mdnX304MEf/+H/eeXlJT8aYCHz8/MRYeGB/v71dXXogPvTp6pPsIDIiIi//cu/+umPf9Le3q668DIyNPyNf/mXL/3N32ZnZlk7+VjVv8gw3cvTEwoQk5hnbu5FhYVS3i4FeXlvfPWrX/vnN7BZVPVvbm6+9YtffvaP/wSTVGt9/ezMbG1NbVZG5r07Lr7ePjnZ2YhC/CvXrr2t/Uff/8FffeGL8bGx8iMtMg/u3fvDP/gUpKy19/ugqrbWtleeXulpaTU1Neh8UEDg8t6HU2ZnZs598OFn/+RPsE10qyZ26OTkpPtTN5MCOD8v7x+//JV//8Y3ent7j3Y6SByMsQBOTUlRfqrHfh+PTYxP+Ojc+fMffFhaUnL9ylUp1aYotd/w0NDLFy+kiE1RttLX22v8hm2boPwWNNwBRgApsh8UwEoogDWhAD4SxI2v8lG4srwiPwK6sbHxzN29tkb/uRotsNcKCwowOgT4+eNollLNgkVsdZMtZp/PnrotL1n0oGxcbOztm7dGrfwIpHlmpqeNZ1r74unx0sKvHWC/NDY2ZmdlNTU1iX2EX0ysMWeCad3oHhQYKF4SZh7M4V6+8DB52aqrqys3J7uivHx97ePHGvWN5qo/1ieD3YqtIUU0QOfDQkJu37oVHxcvJR2Orc3Nudk5eRKMAcTCg5AQS4BYgs5MS03Ny82F3JJSD01zU5P3q1eYAUhxRzE3N4fhOi8v1/HvkMOJiZk9VLfDHhtWAi+mf3Fjb68UdyAYZtva2tJTU5OTko33ODZLfFxcZob+JfzktGEsgHG0XPjwnAhjwJE/VizQ6XR+Pj7ixZlKent6Pv+Zzz68f1+KWwxc583r11UVNtTX+/v5GXvSu3dcPv/Zz4mvOViCx/MX8uP66Nvg4KAIC2qqawIDAsTLRJRglf/iz/7MzKc9VLg9eSI+pQFcbt9R3ZdRVVkZHBhkPEm79NFHX/z8n1v+0alHDx70G56bAzeuXVd9Eq+8TP9ZYJP6xaQALi4qwv6y08Xq4wwFsCY4FSmA7Yrhk0j6L/FgVodhd9Hwnqe62rqh3YEJwytUYmhISEtzy9Sk/gzHvAETpqzMzNaWVllmKMHIK5w3pnQ4q0WiipXl5dzsHFQiRo3hoaFH9+9j+GtrbRNXPzAIYpyCzBPTsvX19ZaWltnZ2fa2dlSrPzA2N2tratNS0+QJBHxDRlo6Br6MtDSTt6KhEug38bpjKen1a6RgI4iw4YNPDWkpqWIQHBocqqqoQjfQdGVlJRoFWLukhMSBgQGEUWFPT09rcwtmw7OGbmAzPnV1LcjLx+YSVxUM/axJTkzG6W3yxEY9Pd09aFcc6ijT39uHLqWnpqncgwxKRkdGzc3qv/8kQEpZaRl2nKhkeHi4u7s7Oysbwlg0ig2SlZExPz9fXVW9YngRF1KSEhPb29rEItjgpSUlJcUllRWVtaY+2r69tY3dih0kxTF1np3Fqik1wMT4RHJiEoZ+8QRRe3v7k8euaFH+2pOKzY3NkKDgWP1bu9vFy8D03SgtzcnJEVHdqg4tYhdjRcQnlBrrG8pKS7F2GDHFJRfMnlOSU9ATsabNzU2eHi/LS8u7u7q20OntbUyyXz5/cSSTbEIIIcRCjAWwALMdzMQwBZLiu0DIJcYnGEvQH33/+1Z9zxZzA/FnF+F5VeinPYmJYqogA7f+P//H/601S9ECcwPMoDBdwcxHStoFc6SU5GTVNAlTqd/73d81OaMzw8L8AjYLZnfGrXS0t2PCpkqvq639g0/+nvKlhpaAjZYQF19dVWXcCnQ+pqPG6cCkAP7rL/4l5kJS5DRBAawJjh7VKUdsC3RFUWFhXm4uBlAMr1AU2OZzc3MY7MT7S3Es1lRXl5WU4rgU+0JoSAy79fX1kCKGavaAsVI8soIxCyrXeAhAPRHhESMjI6Ojo+gAstd0uojwcAgzNIryU1NT0FGQqZBDebl5DfX1OBQqy8vvubjMLyygJxDJwUFBoyMj6CpGzI6Odgw3Bfn56JX+g7pubsZ/Vp8YH8cKjo2OwoVglIdWFOni47QIYNxHryDFUWd+Xh4EVX1dHbQTCiCMytHhxIQEdAajXklRca7hymdwYBDOW/QH3VhaWsTmgpxDx+TTGItnpGegzmrDi7j1TRqB1YyNjkYZEU1PS4cIxLoU5udDe4tEFRh2xSeg5c0LnSn/1RZrFODvD3mJPSs+NTQ5Men+9GlYcAi2DBbBfsnPy5+fm2tsbExJSkLTCfHxUOzoiZ+PD3axqEcFahN/WBWNYgUbGhrkF97AsYWFhmLz4ljqMGxSpMREReOgEu+gNgb1FBcV1VTXiM2FPR4ZEYG9i8MAO6u3pxcFUP/Na9exhZHY1dkJp4J9nZ2ZCemO3YRKFubnIcXRZ9ET/deMU1PRDXEsGdrR09/Xd+vGDeNPWBNyMHB0KQ8wGZxExpcXHMP62vpRecyN9XUMOFLEsWBrC2/leDBqHaxprYNHYD6XEPPg4JHf0GY/pg2fM5QidgOiVFwUsSuYIK3pjuxOMYxgtr0P8QRBAawJTmMKYLsyOTnp6+0NsQF1VFst3dgMj56eliZveUg+aGARBuKKKAJQWSYv8EJjQA0i0NjQYFJK4fienprGoDY+NgbhB9mDlBjFQ3GQ0PL9umhdvN8FskevhA1gqAoODMSCqARDMM4ZaCFxcRKdjwgLM76hGnUmJyYuLy1hEfxiEZGOHorrk5B/oSEhcp261dWmpqbW1lbIs+6urpLiYoxQkJ1YO1EAYKm0lFSoL4xfOVnZWBYp+s/27v6ZFusFkYmSkL7RUdFm7hRKSUoWV01BcVHxQP8AApXlFUK+GpOUoP8LBWReakqKSKmtqZUvz44MD2dn6v8GUVpcIu44Gh8fDw8Lw9aeMFwIzcrMxH7EiqBj6N7g4GBSQoJ+ydevs7Oyq6uqRFgFdoS4YzAxIUFM+7q6uiorKgyZermLLYAK62pqkxITkYKNjC0mcrXmc/rDqVkS+UODg1m7N/5lZmSIP0xg48uHGVovLyvDLsBew8asKK9AGchdNIrdJAQwxDzWTt6/aHd+ft7P1xfFoExEIiEHpr+vLywkNDYmpq62TtzlIcDZ9MrTK8DfH0dme2tbSFAQxlUHvD4dgwxGMP0wHhOLs7u2tvb+vfs4TRwjwoeHh8NDQ7GyGEPQjaeuT5ITkzYc0jScCIZB31fe7W3tQ0NDvj7efj4+a/afK4Pl5WV4HOxuDJXwYvGxcU8fu1p++Qijk+GWnMyrly5jfJNSFWA/wgX7+vhg6MNxJaUawMCbkZbu7+vb5vAvPxFCiG2hANaEAtjeYAunJifrL9XqP4Srd6hFhYUP7t2/dvXqw/sPxJeBoB88XrxwuX07JDgYjh9znWfu7tgv3q9eeb58aXKaVVlRefXKlcjwCJO7D8e3j7f3g7v37rq4lJSUCGnU2NB4z8Xl7h2X4kK92kHTTx673r19B/1BASi6u3fu3Lp586mr69io/mYYnCpeL1/eu+PyzP0ZZDzKZGdl3bx+A93zeeWdk52tb2kv+ovD7u5YEfQcknR2Ztbj+Yub16/fun5DCLaFhXksi0bdnz6dmJhA/4MCAiCDkVtTXZ2SnIKVjQgLR6MP793HxAVaC8vm5+ZB+KEececSpr+PHz50uX0HGxa9ys3OefjgIRaJCA83uTWw8Z+7uV+7fOXenbvYC5Cjbq5PoiIiURgrK24mV4I+REdGXb546cmjx7dv3IyLiUFifFzc9atX0QdoP0RDg0MwE0VV4aFhwYFBSIH6hT6EULx88SLqROWQ3Pdc7qJjmCujQH9//+MHD7HNUTLAz1816wLYpFcvX77vcvfR/QcvX3ggJSEuDhscjSIKJTA8NIzjBLmPHz2Un6xLT03Djnv88FFHu3SfuZLenl7UcOfWbWxw8bQwBO2De/oDA8IYW6+rsxObGu16e3pB7VdXVz+8fx/z7JjomPa2tuioqMGBQU+Pl1gEfX7l9QqVYKm83FzsRJTEvsN8EQfM0Q6pxJnoNfUW6MXFRZxWuTkfPxUMOfT08RPjZ/NszppuzePZ88KCAiluGLEDAwKUKfYDw1pEWJgUef16aXk5MT4+JSlJitsTrOCL58/lP3VhyCrIz8fIKf40aVcwBLk+eiw/KIQ+1NbWwjWMjlhxGWfQ7FugIelTU1LKSksxaEtJCjB6w8vIf3wkhJCTCAWwJpjLmtQMhBBCiOMxKYA3NjbaWlv9fH1lxTs2Ovrg3r3GBvUdHBMTE+Nj4yZvRpicnExMSNC/g2Dc0hexAMwYvL1epaemiTrhMUtLSuJiY1XKCrlod9LUK142NzdbW1qiIiLKy8utvUsiJioqKCBQVqE1VdWx0bGqBzdQ//TU1NiY6b9D9fX2xkZH52Rlm1R6ZigqLHR78kS+3QbbPzoqqqamRvk3WWyNubm5kZFhuYdK0KXkpOSkhERMvKQky+ju7n547z5mbCI6PDQkvkWs1N6YvSwuLUESy6+QVHEYAQyp/+TxY8PfeXmntFPR3dWNEyoiPFyKG1jTrfl6+1y9dFnrpSo2JCU5ubbGxEtAbMXi4mJSYuLCvH1fuYdx+PrVaxgf7NoQvMD1K1efubnJt++Zp72tDTtXebcjoQDWhAKYEELI8aG3uzskKAjipKujUyVO1tZ0zYYbRpCrf73cptp5LczPQzxjceNn0asqK//9G9+4dOGCtS+VEczOzEL3JsTF5+bkDg8PG/vNzo7OoMDAhPh41VwNijczPeMLn/9zL0/PjQM9zrq8slJTXY21zkhP7+nuFg9HKEF/oA/DQkLE8xcymOg01Df845e/8tH58+KFdtYCrdvS3JKanJKSlNTS3GysFWdnZ1OSU/x9fbs6OzGdkFINDPT3/+SHP/r+d787PnbA1+NBu2KVE+MTaqtrjGfAEC2FBQXeXvrbpFVTOmzz6enp4qLiyx9dlFW0EkwECwsKA/z8UINqpbBnq6ur3Z48FW9AIE6G8UuwcAzfveMiwji5Pjh7VoRtDo7S98+cnZ6aOsC7o63C6+XLkeFhKWIH7rncle/EwbBmp9tw7ty6NT8/L8LP3NzFe08sgZ9BUkIBrAkFMCGEEKcHnk556dJhoF1jyeoY4N+VV9EdzJHPtAgxxuR3gMtK9Y8pCewkn5Z3P7a0ML9w0gWwchP19/c74DvAEG9B/A7wgaAA1oQCmBBCCCGEOD3GAri0pCQxXnpFJbh88aIUsikfnD0LYQaDDP6nr/yDeCOMnbC3AJY/mwxqa2rtdMuxspXysjLxHhlLoABWQgGsCQUwIYQQQghxekx+B9jX28fL0xMq61dv/kL1iERWZub/+O+/86Pvf1+K74JFDvD53KbGxleeXj/83vdVX6z4zje/iVbE9zhkMD//88/92fvvnZHiFpCRnhEcGPTmT3/6zM0dgY72dinDwNffeAOtqF7tBjn0J5/+o4sXPpLiFjA3N4cNVVJcHBgQ8OjBAyl1l69+5Stopb5O+hCmAELj/3zqf12/ek2KW8D01BRaKS0p8ff1ferqKqXu8vd//TdoRf7ChRKTAvj6lauf+eM/sfY9CE4ABbAmFMCEEEIIIcTpSYxPeOftt+/fvSvFD8TGxsZn/+RP5SdU7USAv/+tGzekiN3w9PCw9y3Z4Jmbm9uTJ1LEblRVVl67fMX4rxUjw8N/85d/dSSPwBw5FMCaUAATQgghhBBCiDNBAawJBTAhhBBCCCGEOBMUwJpQABNCCCGEEEKIM0EBrAkFMCGEEEIIcXpioqJSkpOV76BaXFi4dvnK9NQU5sOpKSleL19KGTZlaHDozDvvLi0tjQwP//pXb9lJhPT29Lx/5uzKysrg4OC7v/411kjKsCmeHh63btx4+5e/mpqclJLsQGtLy8XzF9Z0a91d3RZ+nBm7squzy6rXhjk9FMCaUAATQgghhBCnx+RboGVqa2qfPFa/cNgmXPro49csQ516PH8hRWyK8mXOHR0d/r6+UsQOPHNzs6sAVm4x7JeoiEgpsh/8DJISCmBNKIAJIYQQQojTY14Ad3V2XTx/QYrYFKUqm56etpPMVrYyPDTk6eEhReyAvQXwtctXpBDEfHt7cGCQFNkPCmAlFMCaUAATQgghhBCnx1gAr+nWpJCBK5cuQSRIkdevV1dXvTw9G+rrpfgu3V3df/pHf2z555QC/P2rq6pE2O3JEywuwoLamtpXnl6qnoBbN2585o//RPXRYDNA8TY3NYvwPZe70MAiLKisqPB55b2+vi7Fd7l88eLn/vT/GxkZkeKWoSWAy0rL/Hx8NjY2pPgu5z/48POf+ezExIQU34/HDx/19faK8PUrVyHeRFhQUlzs7+dnUr+YFMAF+fnYXyFBwVL81EABrAkFMCGEEEIIcXpMXgFeWVnJy8lNTkqanp6WknbZ3NxMS00dGtyjJMEPv/d9az8mDC2dkZ5RUV5u/Ghuf39/Rlq6ajYOkfzJ//v/UYnYfVleXk5PTauurjZupbenJzMjQ5Xe1NT0+//zk5brUgCpjL7JtrS0JGUY6Orsys7KUrUChf+//t/fN9685llcWEhNSamvq5PiCjo6OnJzcozXEZgUwH/1hS+GhYZKkdMEBbAmOHoogAkhhBBCCNkXzJzHxsakiN2Ym5vT6XRSxG7oRZHRlWebA+lrfOXZYUDmTE7Y8W7t4wwFsCYUwIQQQgghhBDiTFAAa0IBTAghhBBCCCHOBAWwJhTAhBBCCCHE6enu6g4MCAgPC5PiBtZ0a77ePlcvXS4uKpKS7AAUyM3r1x8/fGTto7BW0dbaeuPa9SePXefm5qQkO9Dc1Hz96jW3J08W5hekJDvQ2NBw/crVZ25ui4uLUpJZ2tvaggICY6KjpfguGxsbwYFByDJ+0VdtTa0UclIogDWhACaEEEIIIU6P8UuwZmdn795xEeH19fUPzp4VYdvi/vSp/CYtyO/SklIRti2PHjwYHx8XYX8/Pzupu3sud2UN7+XpKb932rbcuXVrfn5ehJ+5uXd0dIjwvmh9BikrM7OwoECK7LK4sPCTH/5IijgjFMCaUAATQgghhBCnx1gAp6aklJWWSRG7fUVWWS0kt+ujx1LEpihbGRkZefnihRSxKcpW+vv7fV55SxGbovwOMMRbUECgFNkPqwQw8PZ6ZflHhk8cFMCaUAATQgghhBCnx1gAl5aUJMYnSBHDR3GlkE258OE5zLdFuLur29/XV4RtC1qRQobvG9npwz/KVmprao1vObYJylbKy8qSEhOlyH5YK4CjIiKfublLEaeDAlgTCmCwSQg5OUjnLSGEEGINJr8D7Ofj4/XyZVlp2a/e/MXg4KCUagCq6X/899/50fe/L8V38fX2+b3f/V3LP4a0srKCyvPz8sPDwm5evy6l7vKdb34TrRTk50txA5if//nn/uz9985IcQtYXFhAK0WFhSFBwfJ93TJff+MNtFJZUSHFDUAO/cmn/+jihY+kuAXMzc2hleKiogB//0cPHkipu3z1K19BK6qP90Jo/J9P/a/rV69JcQuYnp5GKyXFxdg7T11dpdRd/v6v/wattDS3SHEF1grgf/3a11dXV6WI00EBrAkFMCgtq6DRaCfFpPOWEEIIsYbE+IR33n77/t27UvxAbGxsfPZP/lR+QtVOQF7eunFDitgNTw+Ph/fvSxG78czNze3JEyliN6oqK69dvvKjH/xAiu+yvr5+49r1N3/609KSEilpF5fbd+z6Hq8jhwJYEwpgsLS8QqPRTopJ5y0hhBBCCNGAAlgTCmCwuLRMo9FOiknnLSGEEEII0YACWBMKYKCaXh/AlpZXlldWV1Z1MIRVuTCpgG4NBRBQ5VplqAqVrBqqMtkWzHxnHGyiw8LQsePQJdqJNum8JYQQQgghGlAAa0IBDFTTa6sMom5ufqGhoTEoMOiuy91Xnl6trW3rG5uyzINSnZubr6ys8n7lff3qNZfbdxITEvsHBpcMGlWuxxJDVVPTM4WFRR4vPK5dufrw/oOMjMyR0TFkCFGNRhGYnJpOS0u/dfPWwwcPC4uKZ2bnkO542SkanZicysvLf+b+DCt+945LRHhEe1v7wiLW3rp1p9Fkk85bQgghhBCiAQWwJhTAQDW9hmyDQpuemR2fmBwcGu7p6e3vHxgbG5+dmxe5ysJr6xtj4xOxsXEx0TGdXd1IgUwVWSi5ubVdU1P7/Nnz7KxsVLixuYXE/ILCAP8ApIyOjevW1kVh8wZZC1EN6QslWVJSOr+wuLW9g/5A6KKq4uISCOPV3arQBBpCZ0KCQ9JS0wYGh5AiFLKFhvpR+ezsnN4Q2DVoafwuLCyqyps0rBpWEBK9qrpGv1HWN9CrpuaW8PCIpMSk7p5edFi1MWk0S0w6bwkhhBBCiAYUwJpQAAPV9FqoMoi9oeERoX57e/ugMyE+Ozo6oSSXFGJSCOC4uHgI4PaOTkhH+dom6oFMhV6953K3qqoaYf2yyyuQkOnpGR7PX7S3d0Ahy1WZMSwI9Qgx+fDBw9a2drmqyckpaG8fbx+oXBQQhZEOtYzOHEAAQ6liFbCaeXn5yckpsJSUVNkSEhKR3tPbh1VAnaplTRraxQaB1p2cms7LzfP0eBkZGTU8MortpipJo1lo0nlLCCGEEEI0oADWhAIYKOfW0HXQdoWFRbdv3oqMiBwcHIIShngLCw17+uRpc0vr4l4xua8ALi4uuXPrdmlpGbQuCiO3u7snPi4+IiKyr38ASlWuCsuOT0z2IXVwaHpmVk6HYamNre20tPS7d1waG5tEVUhvbm5BJ+PjE8bGxmVJieIHFsBoCN1obW3LysrGSsFQuWzR0TFI7+rqnpub37dCVCZqKy8r9/XxDQ4OaWtrX9/cQj8t7AyNZtKk85YQQgghhGhAAawJBTCQJ9bQbLCFxSWoVpdbt188f5GUlAwZee/uvffeefetX/4K+hNZyqdqZQEcGxPb1d2DRPkWaGG6tXVI2mfuz+7cvhMUGOTx/MWD+w9SU1KhDOX7n7EIpHJiYtIbX/2nf/zKP0BLC6ksVwJDzSjf2tb+6MFD1ICqnrm5uz56nJ9fgJLKRlESChmdgWg/2C3QoryWIVdVXmUogC7Nzs3n5ua9/ctf/fLNXzxxfYIt4ObmfvP6jZvXrkdHRvX29aPP+1ZFoxmbdN4SQgghhBANKIA1oQAGquk1TChAKGHDE6+IrUKtQdQZyz+IUujhwsKip0+eXr50+fnzF9Co64ZnfeUyCGNZ/IqnZ4WMlHORhSY6O7ugZq9cutze3rG1syPnqkyuCvoZUX1/FFUhHSmTU9MQ2B+dO3/uw3PJySmIogyy5GIOM9Fbsd0k242qStJolpt03hJCCCGEEA0ogDWhAAaq6fUBTFZ6sINJTaFdD7y4ylCVXrHr1ig1ac5n0nlLCCGEEEI0oADWhAIYqKbXNBrtOJt03p5wNje3NgkhRM9pn4YRQuwBBbAmFMBANb2m0WjH2aTz9iSzs/O6sqqmsKiktKyCRqOdZsM4gNEAYwIhhNgWCmBNKIDBzOwcjUY7KSadtycZTHbLK6q6unt1hq9h02i002kYATAOYDSgACaE2BwKYE0ogMEGIeTkIJ23JxkhgDu7epTvb6fRaKfNMAJgHKAAJoTYAwpgTSiACSHEwVAA02g0GAUwIcR+UABrQgFMCCEO5sgF8LLhe2kTk1OqdDO2sLgEUyU6zObmF0ZHx0R4dGxc7snS8srM7NzExCQCIoVGO0FGAUwIsR8UwJpQABNCiIMxFsCzc/PQeGPjE1PTM1CniAobGR3Dr/Jz30qD6oOIFYIQS6EGLD6/sIhFpqEL5xdmZmYRRbWQu/JH0RBAYoB/QF1d/frGJlJQFJXovxmuISN1a+uVlVUxMbELC4uoGSmipKpmhKUOG3JREmEEUEp8unxqahpdRcdk7Y0OqxZBxxHAL7JEGWyljPSMpKTkjc0t9KSoqDgiInLN0HMYVsH7lTfWZW19Q6TQaCfFKIAJIfaDAlgTCmBCCHEwKgG8vrmVnZ1z/sNzPb19KUnJFRWV0IHXrl6DroMIDAgILC0tg/BTzpshF6Ek/fz86+obBgeHfLx9+vsHICNdHz1uaWktLCzy9PSCMoyMjHrv1+8MDY8gJTAwCEoVC0JGlpWVuz91w5QbUSzV1NQMAZyWlp6RkakzkpEos7KqQw99fXy7e3r7BwbR7YGBQS9Pr+7uHshRfz9/yNGhkdHGxqaxiUlI666ubrSOdt2eut28cbO+vgGGSqqraz58/4OoqOiqqmqsLAQzFoE8DgoMamvv2NjaTohPSExMwiZCtaEhoWhdCPvbt26jh/pvrevW9NU+eYr1FVsPWwaVoCGxdnK3abTjbxTAhBD7QQGsCQUwIYQ4GLUA3tiExC0pKYU0be/oTE5KRmJsbBxE5tb2DoRfcFAwtB8SofFEYG19A6rv3Acf3r3j8uDe/RvXrtfU1KIwFOD1q9deeb3a3NpGtCC/AJoWLUItQ3ZCOmJxNJebm+fxwgNTbnRgZHTsqesTNPHo4aOIiEikCBmJtjA9R0A0BwWblJSMOpGO3/S0dIhYtILacnJy0XplZdX9e/djY2I/On+ho6MT64JGE+Li+/r6sTjqhFLt6OyKiY7R93NlFbJfv8jde1GRUehzdU0tqoIaRw2tbe1QwhD26Aw6PDg0fM/l7sTklFh9yObnz543NDSiPPqGetHEres3KIBpJ84ogAkh9oMCWBMKYFBVXUuj0U6KSeftSUYlgKEMU1NSo6OiV9fWy8rKQ4JDIOR8XnnfvnkLiY8fPurp0X8wCcP1pYuX/vVrX0dYr05XVkNDwwoLiyAaIRebW1q7u3tc7rgMDA7V1TcgML+wWF5e8dYvfwWF6fbkaU52DhZEc5Cjzc0t0JAosLaxWV1dg1bm5uYfPXiItlAbRObWzs6Zd9/7/ne+Cx2LzqBYU3MLOjY5PZOXlw99OzIy6vXSs7Ozq6CgMCgwCFoXwhXVtrV3/PLnbxYWFEKddnZ1+3j7ZGfnQKAKaVpQWPTS42VrSytUN9Y9MSERyr+vf+DMO+8mJ6egXfSwp7cPq4meo2ksggVhro9dURsWQQE0+vjRY1nuolh6eoZ+6+3eT06jnRSjACaE2A8KYE0ogIGYYNFotBNh0nl7klEJYNjM7Jz+2drFJcOju4ujY+NQrV3dPUuGK7FYa1EMecgXYRiypqZnUBiJKINcVILFRQBqMi83L8UgLEVhecHN7Z2kxCTIUchULDgzMzs2No4FUc88/tttC6pYXgTFkIu29P3cfQZY/wjw1PTSbg8RnTQ85Sue40VJdA8FRFT//PD0DAxlULNYBBXAxCL4RaM1NbWREZHIFQVgUOwtLa1BQcHQ4RDAYaFhiIpNh9/R0bHQkNDhkVEKYNqJMwpgQoj9oADWhAIYqBwSjUY7ziadtycZYwGsNAg/SMT2js6enl6oUVWu5YZlIaHb2zugQGUxKZtSYR4fGxwcamvv6OsfUKUvKnpr3PNjuCI0miVGAUwIsR8UwJpQAAOVQ6LRaMfZpPP2JGNeANNotFNiFMCEEPtBAawJBTBQOaQD2MLi0vTM7Pj4xMTk1Nz8gvJyBMLiDkaki5sb5SxrTa4K1ehvF9SoSt+Z6Rn950kMnVHlOtJEh9EH9GV0bHxkdGzK8F0TpCuL0WhWmXTenmQogGk0GowCmBBiPyiANaEABiqHJAzKbWVVB1MGVGVga+sb0L0J8QmhIaGlZeV9/QPQe6IkZB5yu3t6IyOjPF963rp56/Gjx2Vl5ZDKcHpWiUBUqFtbb25uCQ4K9njhcf3adXc39/qGxrmFReNe6QXw7FxpaZmX16uUlNShoWEhRFXFzBjKi0WMTWSpyps0dBgiPD0tPTEhscHwpZOpmdm42LhHDx5iI0DDozbVIjSaJSadtycZTHbLyivbO7oWl/R/GqPRaKfTMAJgHKAAJoTYAwpgTSiAgWp6rVduY+OZmVnP3J89vP/A7akbNNv9e/cTEhKnpmeQqywMiQuZFxcXHxMd097RCXcGraosALmIRdYNnzkJCgwqL6+YnJq2VgALwyJoDlI4Oys7MCAQAtikjEQxNIfOhASHpKWmDQwOIcVCtYmOYRU6O7uKioozMjJVhtqQ3tvXD7dtYf/RLjYInDzWuq9/AN2+e8eltq5eaGlVYRrNEpPO2xPOwsJCaVk5ZDCNRjvNhnEA3pwCmBBicyiANaEABqrpNQQbBF5be0diQuIzN3eoX9fHru++/evrV681NDapxOS+AhiGFKjW4uISyD8zAhgpKAm1jF/jXGGoB1mZGZn2EsArqwsLiz09vWVl5Tk5ubDc3DzZsrKykT4wMGi4sdoi+YpiMJSfMtyVXVhY5OfrlxCfgCbEuqjK02j7mnTeEkIIIYQQDSiANaEABvLEGvIP4rO9vSM2JjY8LLxRyN3llamp6VeeXlcvX4H8m5mdU8o28wJYaL9ZwwdOsjKzvF565uXm9fUPTBmeBoaKFMXQLuppbW2Dxv7zz37uww8+bGltQ7qqKiyCxSYmJiEgUVVpWfnQ8Ij+AyOKT5WIkgcWwMLQZ9SKmo3N0HGLHmNGiyjc2dXd3dM7qb/9eQ7W1d2TkpLq7+dfU1uHVbaqVzSaMOm8JYQQQgghGlAAa0IBDFTTa6gyiLz+gcGKisrc3LzKyqr+/oHxicnBwSEkThq+cikXlgVwWGgYRN3o2DgSIThFLgIQjEgcGBjs6+sXhtqGh0cgqiFbRTHI31Xd2oN79//qL77g7+uHJnRr63IlwkRVIyOjWFxVFXSpsqSw6ppaH2+flOSUAwhgmxgaxYbCag4MDTc2NhUXFVdWVEIAiy+yUPrSDmzSeUsIIYQQQjSgANaEAhiopteyQacJU6UbGwQzVOvY2Dh0MsKWLKIyiFssDC0N0XiAxZWml53TM1DdqHBmdk6VeyRm+Zak0fY16bwltgbuQAoZATehzFV5DaVDRTFlSVUUbG5uqlIIIYQQYnMogDXBRIQCWDW9ptFox9mk85ZoUFNdU11dLcJVlZXuT902NjZENDIiIiY6WoSVVFVVubu5RYaH+/v6rq6sSKm75ObkxMXGhoWGzs3NwWWkp6UFBgQkJyXBjwJU6OfrW1FejpLDw8MB/v6Ijo2NIZoQF+fn45OanAyni+jk+ISnh0d2VtaaToeSLrduJycm6Rs4BIkJCbdu3JgYn5Dixx44XGwEjxcvdDqdlHTsmZ6avudyNybKxJFzbGlqarpx7XpxYZEUPzq6u7sfPXw4Pz8vxQkhxFFQAGtCAQxU02sajXacTTpvnYjNzU0IuccPH8JFIdrZ0QFlCEkZEhyMIbqkuLggPx+yMz0tHbmlJSUP7t0rKy1FuKmxMT42dmVlJS01tay0DClLS0tQpLOzswiD1pbWluZmEQalpaWTk5NSxIienp7amhqTl2fX19ehqttaW6enp/Pz8hBFNyYnJpqbmtrb2lAgJTkZTaOfC/Pzq6urULlYqZzs7O6uLjhdFIAAgJCemZ5GuqFK/Xuw8/PyRfgw1NfVDQ4OSpGTwM72Nnbf3O4+OhFgj2PnnqzZwuTE5HEQwACbTpwFhBDiSCiANaEABvINujQa7fibdN46ERiER0dHS0pKoHKFPgwODOrr7cX4DBYXF319fKAqEUYWfFhDfX1sTAxSoCoLCwp0q6vlpaWjIyPIHRke9vf101dqAAIYIlmKvH6NJsbHx6WIEXW1tRC0UmQvS4uLEeERgwOD6ENifILPK+/Y6BjDBeDtyIiIJ49d3Z8+xVoUFhRCe2MVIICxFFQTxDk6APG8vLx8z8WlpaUFYqCvtw+5KJmfm2eo/lBAtJ8sAby1uVlaUnKyBDAOtvy8vJM1WxgbHTsmAjgvN5cCmBDieCiANcFshgK4pLScRqOdFJPOWycCcqi/r396aiozPWNjfR0p2VnZS0tLIhcBREW4vq6usaFBp9OlJCeLmyqRkpqSWl6mv/wLxkZHAwMCRBhYLoAXDFdoZXcAQT40NCTC4gZmCPLKisqZ6WlIbkT177Tr6jLk66/upqWmbmxs5GRnT01OYllxgVrc5dvT3VNZUQFVXFxUBO1XW1vb2dGBdDjjvJwc/fJGjI2NPXNzs1AzQF0PDAyIMLra1dkpOuxgqquqfL29xR8pzINNUVJcPLu7dnNzcz3d3a+P4rHohPj41ORkKWKWlZUV5eEBbXkkf3TApvP29GpoaJDiZhkdGS0qKBRh7Jfe3t7p6WkRdTBKAVxXW+ft9UqECSHErlAAa0IBDOBTCSEnBem8dSIWFhZ8Xr2KjY6BgBweHu5obw/w9w8OCsKUHbn5efn+fn7RUVEoBtcVHRmFXKgRKGGxOLJWV1dFGEM6spobpQu5zU3N0IciDAoKCmRZqwJ+ccRwDVmQlZklS6OOjo6nj10L8guE40T3nrm7t7e3IwzZ7PPKOzMzU/gR0b3EhARRsrur++njJ5D3QhYuLi6iMDQJohAn4WFhWBFoY2SpiIqIdH/yVIqYBZVj46CqyQn9Y8DTU9NQF1NTUyLXYWCNXG7fzkzPkOLa4ABOSU7GiuNXPG7d0twcFBAoNpEjWV9fP/POOwP90t8OzIBpU0RYOPpcXFQk9mxWZib6L3IdSUd7x/tnzlgyaenu6sIZFBgQ0Gx4BACbNzQ4uK62VuQ6EvQ2Iz1dFsB379xJS0kVYUIIsSsUwJrAK1AAE0LISQSz/MuXLr984SHFDeh0upXdF1nNzsw0NjbKfzUY6O8XjxkfZ+CesV6ypD8RQMqizyfrrzOzs7P9ff1S5IQwNjombvU/QUxPTzc3NYtjA79dXV1HcocCIeQUQgGsCQUwIYQQQgghhDgTFMCaUAATQgghhBBCiDNBAawJBTAhhDg9i4uL3V3dJu8rXlpcmpyYPOaOAG67pLhYPBQNlpaWiouKpqdMvdNoZ6elpaW+vl64efHFJqy7yBwcHGxqbBoa1D8IvbG+gfTmpibxbqSNjY2qyqramprt3U2BjYZ5g7jnFuGSomLxJCdq7mhvrygrt/aeZ6zF2NgYuiTFTwLLy8tm3hx+DMHewW4Se+po0el03V1d8tvsCCHEwVAAa0IBDDDvIYScFKTzllhDeXl5V2enseeDCxgZHs7LzZUfGz6e5OXmoYftbW31dXWQZOlp6fjNz8ubMLz7SklRYWFPd3dnR0dVZSWiaSmpqyurjQ2Nra2tkCI52dmYAQjh2tHRUVlRIU8IUCGOroH+AShbfW57e1ZGBkoid35uLjsrC3oGWhpqGfW3NDdPT88UFhSKt3ZbAjb16upqRnrGxLi6z8cWTA8mJyZTklOOds5kFehzc3NzQb7+XeVHCzYaetJQXy/FCSHEsVAAa0IBDGbm5mk02kkx6bwl1lBRUSF/K0gFhCV03cryshQ/rsBtJyclQX8uLCxAsSOltaWlvk6tLkqKi4cNb7rOzsyCg6uuqvJ66fnK0wurCTUb6Of/8sWLiPAwOL6R4RGP5y+eP3+G2lASizQ1Nl7+6KL4wE9GWlp4WJifjw+WMnyJKgvt+np7y6+trqutg9i29t3N0MwnSACDjY0NrPsJEsBgaGgIh7QUOVK6uroaGz7+DhkhhDgSCmBNKIDB4tIyjUY7KSadt8QazAjg1dXVstJS8UmeowVSU+v2YMhXqN+xsTGE4cVzsvUfRm5pbq43urwGUToyPIxATlY2KszMyMSyPd3d4oKwoLWltbamRoooFgGYH2RlZmFBqF80ND83l5ebh3R0DNobG6qhXv/1qZLikqrKKsMSepCLRaSIWYoKiyYnJqXI0YE5ENZUyH7zYL2wtS0paW8wV7Hw7vHh4WHxJeojRyWAsc054yKEOAwKYE0ogIFqek2j0Y6zSectsQYIYNNfAN553d7WFh4a1tTYKPxiXm7uv3/jXxcXF0W+I7n00UcRYWFSRMGaTuft9aqmuqahvr6jrR1uKzcnp6y0LCkxUQiztNTUH37v++IJ586OjuLCotTklLa2NkQzMzLa29tRYHRkZHZ2NiYqerC/Pz42bmNzE/o5OysLvyiDeiCDsQgEamW5/hpvb29vVmZmZUVFc5P+o8rLy8uFBQXi47cQhHGxsdhuNdXVcKAQ2D/54Y8QRZZ5IKFDgoP1f24wdBU67dv//s26miP4OG1IUNCNa9f2lbU4JHp6evz9/Lo6OzcNTx8U5hd891vfnp2ZFQUcydXLl8NCQqWINlDsJcXF4aGh44Y/lwCP5y/OvPuuCDsYbD1ZAONA+tlP/gMHkogSQoi9oQDWhAIYqKbXB7Cl5ZXlldWVVR0MYVUuTM6FIazKtcqkqnRrZqoy35lja47cjKItmJlN9HFnDteWrUz052TtU3uYdN4Sa4CQiwgPhwKU4jI7+quXcIpAyKHtnR0LL2balsHBQW8vLxzmUnwv6JJOp9N3clvfSXQVGlLWbwgo+4w1Ul4qXDXc/CzC8P1QIPKCKKa89I060YQUMeTKUWUWKkEY/RHVQjPHRseILPNsbGxgQSC7XdQgd8ZhoMWnT56Mjo5KcW1QUmwEIPqJX+WmdhjDw8Mvnj2z5BUA2Duix/IxgJQjmefMzc0FBwbV19aJaHhYWFnJsbguTQg5JVAAawJnRgGsml5bZau6tbn5hbr6hgD/gNu3br/0eNna2ra+sSlUilBZg4NDSYlJjx89vnXj5oP7D+LjE7p7ekWWsirzhvKwru6eqMgoVHLzxs3Hj13T0zMGh4ZlFSfqnJyaTk1Nu3Ht+v279woLi2Zm58SyytqOm0HXLSwuNTQ0BgYG3bt7D5uxrq5et7YuNpHo//DIaEpKKjYjtvN9l7uxMbHd3T1iWbmefQ3F0dD4+ERzc0tISKifn397e4e8AeUysImp6aysbJfbd25ev5GTk4u9rCrmGBMtzszM9vT2paWlP3/2HPsUPRFb5nSadN4SKxEC5thyzLtnhpPY85O7tU8Wyu3MbU4IcTAUwJpgRKYAVk2vITmgkaZnZsfGJ/oHBjshOnt6R0fHZufmRa6y8Nr6BorFxsbFRMegJFIgiUUWSkLCdXR2paeld3V169Y3IIyh1mpqasPDwlOSU4aHR7C4KGzeUNXq2npTU3NGesbAwODaxubm1jY6WVJcEhIckp2VPTE5hfrlwshFZ0JDQtNS0wYGh5BilV6aX1jEykI5GxvSkasqb9LQqNiM4xOT6ENnJ7ZBz8joGCoRuf//9s78qY30zsP/1mYru6naX3ZrU5vKVrYqlWx2a5NNJtekMpOp7NgzGc+RmfE5BhtjMDbmELcECHGfEocQ9y0JIcQpIYSEDi6BAM9+pLfd0Qi3DB4bEHye+hb1vt3v+/bbb3fT/ail7vjCGAeUrKhQQ0oXFhYxN15rsWrYELD9ySkzhnRv/wDlBweHsO4YkKVlJyYmNKgUKAaVhU9iReCTj7KyYd3o5wvv8R4cPptfWMzPy6+trXO7V1H3mEsR8RqH0etbR+mJicl7aenYnTZjd4NP1JmLFNJxSwghhBBCFKAAK0IBBgmX18IrYCnLy85Zxxx8bG5uvqCg8EHGg2nbTFQ84mRJCHB1tRYCjLmwmoQbkmgNVRAQY6haQ0Nj5oPMhvoGaJisyscM0RTah1ijY9VV1VkPswyGTkyPXyiyMG10Bn54UgFGMawCpL2zqxt+iIB2ylFXV9/Z2TU3vxCAk73MvkSB6DA6XQ4HKsHcl+Hkt2/eslqnMW7xLQgBVqs1EGCMdqz5xA6LdYfrwqKxXtlZ2ejPmteHKQklXxqinba29pzsR0kEOLJ/gI7nPc07qQCLzsP4u7q6MW5Hh1GvN6BlDPUxG0TsHxxOT9sy7mdQgKXjlpyQC3YDKskXcZ89O0yysvEVcSkQfzWQ/AvJ8RVx3ny1U2eSWlg0ei5ljoCK8X2L7wymJ2k2SUVyCsQPPiGEnCYUYEWSnzgvCfKFtTAcWAk078vPv6hUa1yuFX8g6PWtl5WWZdy7P2W2bHxTJpMLMFqD5XrWvB0d+kdZ2RpNpdPpgla98I4l6q64V+GKUO7oHb9vzhVNOV0rUGi4X33M/dAUJiY0hewrCzCWgW5Yp23t7R06XS0C7icHVhPT4d7i+8AJdeMDczFuJlPfzRs3S0tKYf7inicU98aX16emzCcSYGTg/CgAb8x5lKNRa6DT0jAe6QaWsrrqccw6UOboMCLQGiqiOjbKk5zH6AyWtf2iLfItBRibAMOFuonDqK1paWmdsc9iGI/fIK6hYNSZDzJbmlt2YgIfv6ddqpCOW3ISBvr7i4uK/OvrUv45+P//KCvrflp6CnnRus+nKiiordG1trZKk56ztbVVXlqG+Or2nWnrNKZkP3yYcf++WLuNjY2K8vIarVa8RWl8fLykqKhSo7FaLMgae3rwv0VdXu7z+XBmzEi/l5X5UNhLMBgsLS6pqdZ2d3UhOzE+Xl5aXl1ZJZ6PdUzQlEGvLystFYuQpj4HG+jJoxycdJ7m5uICxTw1dfX998WjqlERc9FVdUVFKBTa29urrqoqLyurr6tDSayypkJdWlxsMplQcnRk5MOrV8W7Z5HtM5lKiouxxJ3tKFh3bXV1ra72ROd9n9d768YNLF3KpwLYNJ998mlX59m/DXh+bj7tq7vYhaQ8IYScFhRgRXCCpADHX1sLIentNcHTMjMeaKu1hQWFsLj33nn37d+/DSvu7u5ZDwRlF5IFuKqyyj7rwERxXxcJJNf9gYoK9X//7L/e/eM76XfT0tPScVn2ybWPr395HVIE3UV1FEaVg8NnuhrdD//tBz/41++jKUyX9QbtILCU3MdPfvbT/7zyf++jHcTtm7eu/eWjO7dut7W1w/RgRKI8Fr1/cIjOwDxf7SvQKA+xFMtNCEzH3ITyRwMlA6GNwcEhdA9dra6qLlIV3bl9509/fOe3b/36r59+1mnohBJHF/R8GMVXoEtKShcXl1BdrD7mIgHVx4Z465e/+sPbf8CVxL209Lt3vvrow798/tlf6+rqna4V8YECamFrtra2/eiH//79f/6XkuISTBGbQwTKYEGzs46ysnI08t67f/rV//4S7WBbF+QXjIyOYXvFWyU2ysLiEmbBWl/hK9DR8kcGUI5jNoVVQ6+aGpuwN37y8Se/+J+fo9s3r994kPHAYOjEXnH8pi5MiMOWnAjFp0B//XU4HIYmnf/3AMuIW5rocGtzs9K53NRrWpifRyK6dn194tG7q+5VGFEwEGhpbkZWWLF9xo7CSEBuvV6vqbd3fm4O2c3NTaTFU5eWl5b6enuDQakiQB/GRkf7TX0iexzQZ7FE27QNXRITE3A6nUODgyiJtMVimYwJ9s7OTntbG7zXYrYMDw1jlcVZu6e7e9XttpjNsGXMbW1pheLGV0S2raUVs2CDEGNMiU7c2tJ36N3HeAJWPOi5oUOfWlcLax6P+MDizDHoDbj0lDKEEHJaUIAVoQCDhMtrBIwCXoFEIBgSdyPhUVAjRIJsCD/p6uq+f+/+tY+uPcx8aLVO7+0fyMXkukjAdEUjIisKII1FzMzYIYownGnbzOGzF3QJodSUvCwkMCv6EKz6hg+uXL36/hUkkD2mtb72EP1BIhjakIdRrEJCfzCMKNMdG0bocWbmw7GxcUwU1RFIyA++VhpG/MGVZfbDrE8//gTVMYwJSxGBidFGYo4tb1Zk5cJIIDBucOmPr30Maa/R1qyv++PLnHKIPit1+LKFdNySk5DkPcDQpF6jMYUEGOC0VV1V5VRQ+tXV1Z6ubqGR0bXr7RUCHAqFCgsK1BUVzU1NsYJwpLVKjUZ4qUGvL1YVFatUntVVZFEYwyIEOBAI5D/Nqygv72hvj1aLPc+5saHxFV42O22dbmlpEX07yuDAgNUivU4JEis8Fudp9CQvNxfd83mlW8fo7cRE9P06oWAQfc5/+hRuL5qNrwgDzM/LK1KpUCw65euv5+fn1eUV0HuRPSa4bNK3d6TW1QIk/5wIsL5DTwEmhJw+FGBFKMAg4fL6FQIqIrQE8WpaIhvOa7EaNBU1pfAuEgmzznOcw2FEUxjJ1BrGCx/ScUtOQhIBhhz2dHdvPTeiYDA4Y5s5PDiDc2Rdba1GrZYyyuAsrqlQ+/3+/X3p5LWysgKvE2ngcDhgjCIdXbueHuF7uAKANB7sHwiPNZvNDfX1sF+cBOHJkCUkRkdGUAxzMQ4YFvEqnanJSZvNFrvL2oLs3m50IhaKlpFATzLS7730nirOtmiw02DAUgCmYNEWs1m8ExhsbGxAYuXseAwktre2xJ3nWbt9aHAQdSH/cw4HEmgTzozpmIsywvNfWHGgvx/lxeqgG3Oxu9w11VoEEi8lHA63t7aJTwqAy+VamF8Q6dMEq5CTnT0c+2b4S3G5nBhtKRMbhLW1NSlzusQL8Njo6KOsLKVPQAgh5DVCAVaEAgwSLq8ZDMZ5Dum4JSehr6/PbrcfPfPt70cgNsWqotoanVAveEJRoUqY0mmCpV99/4ptOvrD3eTgRK6uqCgrKTXoJb3p6uqCPIs0TmoejwfChnRkPwJlxdrV1dZhCmb1mUwwqPXYT3B7e4zq8oqSomKrNXrTNRAI5D55AmXCKOEqoaWpGRUb6uojkQgqQhofP8oJxF6kjOpPHz+pqqwSQlij1WZmPEAiOShcV1eHJVaqNctL0XvXENS83NxVt1sUwAjIaWyFirJyrCMsHVnY+NPcXEOHHj3xeb2YrqlQNzU2oUq0b13dT3JyhGJhAMWvoMVI+tfXH+fkoPMohvWC5MPVHbOzmIVT/3vvvBv/wYESGJlKjQajYezpEbuQvqOjvq5ezD1NsA//+b33ZA9PgsPhwCiVFpeYp6bElPKyspHn3wM/TTDOzU3NsgDfunEDO5VIE0LIG4UCrAhOihTghMtrBoNxnkM6bslJ2NjYmLHZxG9Ezyc4Ny8uvPge9TlnbnY2EIiKcWoRCoUWFxdxDSDlUwGPx+NyuqRMiuD3+60Wi5B2XG45Zmd3Y5/OEELIm4YCrAgFGKwfeU0rg8E4tyEdt4QQQgghRAEKsCIUYBAhhKQO0nFLCCGEEEIUoAArQgEmhJALz0YohPOf/ICleLxer6FD7/O94Cm1brd7cnJyfHxcPD0oHA5jivwZBM6mHW3t3tgsnEpsNluvsVf8eBin2NHhkZHh6Dt7kA3vhFdcLvmnm6jS0d6+HlsiClgtFoNeL361e3zQDfRqY2NDyqcCuPhYWVk5/d9XfxvWfT59R8fRFxcDrIt44vSqO/rc7N1wGFPidw9UFI/Uxu6B3c/Y0yPWHdnR0dHhoaFnYvfAfhVXETukXq8XuxyuT6at1vhngx0TtIY+BwJn/4UR9MFqsR7nd8uEEPJ6oQArQgEmhJALj9JDsGAs0FRoSWNDQygUkqbGQGFICOTEYrH0dHdjSigYamttEy60ubnZ3tYe2Ys0NTZub29PTU4tLi6iBbSDucPDw47Z2fn5OTgPssFgsLGxUTxoGtXhMzjvoCL0dT+yD7dBRWQx9/jAcAb6+kdHRqX8uQdnWwxmc1OzZ9UjTTr3LC8tDQ4O7u3uQmUXFxIf+7wWe9iY0+lsa21Fdie8g43o83qRXnG5cMkF6+s0dK6urprNU9gfortZfQP+dnd1eTweiK54qjZ2AFREFmksBTsbKhr0+uXlZewnmHuwH91bTvQRCZYizFnKnx1YhfiHYBFCyKlBAVaEAkwIIReeJK9BApsbm3U6nXiJzlGGhoYWnj8r2GTslV9FW11VlZOdXV1ZKZ9EZmw2fXsHEnNzcw8zM3MfP4Z1I4sTTafBIL9pSVNRkf0wq7ZGh+nIrrrdn1z7eHBgQMw9PhazZXxsTMqkCF2dXSkkwAJcNjU3Nim9OtjQ0SHcFWArCwHGlq3V6dLvplVXVsnXW+apKfGBiMvpzMrMzM56KN7GBFBRNIKKOm1N2ld38VfsHgG//4MrV/r7+mIFTwDfA0wIueRQgBXBCYYCTAghF5skAuxcXtZWVwvZOArOl02NjfLcvl6T+Oqyx+Pp7TFGIpG2lhZx6xiKInwDhfv7+t1uN/Sm19gbrRYVv87tmGAvLy0N9PWjYktzy8bze847OzutLa2R2NdE9/b2jvl9UavFOhF74e2Zc/yriu6u7jXP2byNNh70Fn1W2ujxrK6uVsV9xpEAWmhrbZXdGFtZvGJqcWGh1xjdPbBLLC0uYcrIyAhUOVbq6472dr/fj5LtbW1iCiqKbxbMR/eZaEVMERUFDfUN4di3oI+/e6y63eKbC2dOvACLkRdpQgh5o1CAFcHZiwJMCCEXGwjw8nL03bMJTFutqsJCs9kMjRGCqm/v+PGP/mPz+W9rHbOzsmS6XK7SkhI4LU6iOHFoq6vmHHPaqio4CUymTlc7MTGBEy1Kjo2Odhk6BwcG+mI37rBoVUHB8NBQBEX39nTamln7rE6rRXp0ZATFbDabeJGvz+v9za/eOs7bgCFd9XX12mptIBhEFlL09m9/h+6JuafJ0ODg7379m+N8Qdfr9RZF36ZrFO+jcjqdP/nxj0eGh8Xc06SoUPXZp5++VIDtMzO5j5/Y7fZOg0EoXGdn589+8lP/c52bnJhAiPTa2pqqUGUymXbDYewhTQ0N5qmpxoYGjIxBr1eXl+MKTBhpdD/p6hoaGBzo70fW4/GgYp+pby+yt7W13djQODU51dTYiEaw7/WZTNgfmhqi35APBAK/fevXU5OT0eUlZWNjA10tLioOBqTd45c//0VFWbmYe8oY9NLoARwIX/71c5EmhJA3CgVYEQowMPX1MxiMVAnpuCUnAaZRVlrq9ye+rhanAFgoFAV/5SnxJ4V4R4pEIjh9ymdQzILIiQLivhbake/OiZIijYp7sezRigDT5UccGXt6CgsKRDo56GSsyV15iUicyakdStNrNEqZpMjjII8w+hw/wqcDlng//Z57ZUXKK4OSf9s9Yt3EFHnAE4itXXT94reySB/dPcQ4iPQLK+KvmIvp8u4xMjyc//SpSCdH7B5oVl4ippzJ7rGwsJCelhaMfUwDsjIz5xwOkSaEkDcKBVgRnGPir3UuJ4FgiMFgpEpIxy05IbJREJKipOI+zOOOEHJWUIAVoQCDjc0tBoORKiEdt4QQQgghRAEKsCIUYJBwec1gMM5zSMctOSG8E0XIqZFwuPHoI4ScPhRgRSjAIOHy+hUiGNrw+tbd7tVVz1ogGNrc2pZnIY1YX/e7Vz0rK+4V96pv3S+my2WOGaJKdEGrHteKG4tb9wfk6XKENjZRBgvyrHn9gWD8rHMe6LkvtnboOnoev15II7C+0WF0r2Ikv80wIrDJ1rw+DCNaCwSCW0fakToT26ZnPoxb2zvoM3YtdAl/E+ZetpCOW3ISBvr7i4uK5GcXyeD//6OsrPvp6Uo/7DyHBAKBzz/7a5VGI+VTAdv09EcffGDqlZ6JnRK0t7V9+vHHjtlZKZ8KFKlUaXfvyj+4PStwZaWrqamqrBRZnHVyHz8ZGhwUWSTkJ4cRQsibgwKsCAUYJFxei4BybO+EhXjI6YQyiN29CAxJq60pKy0bGhqGUMFOhJXhb3h3zzE339DQ2NbWbrPNwN+WnS5VQWHWw6yxsXFoFZqNb00psOid8K7FOl2rqzUYOmdnHXC2Wcfc45zHT3OfomU4UXz3oGvoTF7u0/r6hqVlp1gFee5LQ5RXCrF2xwyUjw7dTli0mWQYIbSVlVUFBYUTE5Pw2/jPETB3cWkZ69LS3GKbsUNcocElxSXpaekYxoR1TxYoF96F07a3td+/d1+nq4VPYgOl3U17mPlwbc2LBcmFxXYcG5/Axqqp0WErI3uidRerrBTHbCocGxls9yePnzzIePDBlav1dfUnauHihXTckpOg9BRoEA6H+0wm8QjoVCHg90PpU0jagcvpHD6LBz5/G6zAYpEyKQJ2jBWXS8qcHYFAoNNgkDKxV2SPjoyK9NLSUk21NhKJiCwhhLwhKMCKUIBBwuU1rBWO1NLSmpnxAGqUnf0IsnTz+g2NptKz5oWQxBeGMkHGqqu1lZrK6ZiIJjitbEEwOpSE3aV9dTfjfga8S8yKL5w8RHn8hTmvuFcH+gdufHk990kurBuiKesQEnuRfXSmuKi4saER6nj8BaHzWAWrdbqjvQPShairrZNDW63FdIg31uWlDWIYYaowf3kYM+7dv33rdnl5Bfx2N7IfX1gIsFqtKS4umZubj97i/Gb7YhUQYhgtZsuD+xlf3b4zM2PfDu9ibnxhpUCxg8NnRmPvl59/MTAwiP8BYmNhW+hqdKUlpUhg6OTykf0DTMl7mldbW4ddAtWPuSDReZttpqNDj3E7OoytLa12+2y85CcPNPgMl1AzdjhwU2MT1BxTjln34oV03JKTkOQ9wNvb271GY2oJsM/r7e/rSy0BXlpcTDkBNpvNKSfAfSbTeRBgXGsa9HopE3vfmCzAzw4Py0tLlY5HQgh5XVCAFaEAg4TLa6gFDHPKbNGoNXfvpt25dfvuna/+8Pu3r310bXxiUriHXPilAowQ4oQ2fb71ZadLrzcU5BfodLVIx99yRBnU3QnvbinfFhbOg6a8vvWFxaWmpub8vPyW5pZ4M0eZVxZgFMMqQLS6urrROKK5uUWOhoZGTJ+bX0AZ0ZMkgaYgeBbrdFVVdXpa+p3bd/D37d+//ad33h0bG0cP41t4qQAjMAmBNsUXvDGMWHf45OLiEmRbbg0J1MUwvnBDCAG+cf3G4ODQ4TNJgJeXnfV19aqCwtlZB6RXLv8tBRiKi+HCuB0dRnQeLR9nGOXYPzicnrZl3M+gAEvHLTkJSQR4a2urp7t7a3NTZIPBoM1mO5PzQl1trUatljJJWVtbM/X2yvfQIDzz8/Mifco8ycmBikuZpCzMzw8+/xIscDgcHo9Hypwifr//Xlq60+mU8kmZnJw0T02JNEbbZrVibxHZ08RiNj988OA4t0xxSdNrNLqer93m5ua0dfpMduYkAoxTVKVag31YZAkh5A1BAVaEAgzkC2tIBYwI6lhVWVVaUjoB3Y05z5rXl52V/eEHH/b2muBp8eKRXICRhqqZLdb5hUU0su4PrK15LRarukIN3XI45oRuoRzagXJf+8tH3/3O3195/wqaQu34plAGwowyENpoS7Ffw46NT5QUl1SUlbtW3PKtS1R8ZQEWgbWAY6O3CCxIjmg2EMTchPIJgcXBSK3WaawmAsMI0cN01H2a+xQC3NNjRBOwOLlKcgFGGoaPYZx1zEWHcd2PP1NT5uqqamwmrKnQaQTG02ab+eLzL777d99554/vQL9jLUnDiCRKYvwLCworyismJ6ewIGygnEc5mQ8ysY1QFGVEYcQrC7AIMYzSuJ18GEVgiegk1hcVhodHbt28hZ0TncGAoB0xsJctpOOWnIS+vj673X70zLcfibS3tRUXFdXpdOJtq7N2e1GhSn4t8KmBpV99/4ptelrKKxMKhrTV1SVFRV2dnTiFYUpXVxfkWcw9Tebn5v783nvHGavFxcXy0tLS4uKpyUkxpVKjiffhU6OlueX6F1+KcUvO6OhoiUqlLi8Xtox/RoV5+bJbniYZ9+6pyyukTFI62tuxY2BnCIWi70tbWFgoyMs//Z0ZuN1uHFkijdGeGBsbHpLu/09MTLQ0N4s0IYS8OSjAilCAQcLlNSwIcrK87BwZGTUae8fGxuGQ8A1IB2QJnhZvHbIAl5WWDY+MogAmypqEBJpC3aVl58TkVH//AKQLrcF/ZJvCX3HX9+b1G//0j99TFap8vnVMkRuRmwoEQ/CexcUldGlgYNBstkCJMTFB20RAlnKf5NbX1b+CAL+WkIbR6RodG+/tNY2Oji0sLmEoMETRR1j51uMLywKcn1+AIcKQoq68UkggtxYbxskpM4YRg4lxQBV53cU67uyEsx5mfe+7//AoKxtzMbJyI3JgCgIiDUUfHBqeMlvQn6MmiSkohgWJ3wC/ggC/lsAS0RMIsNj9ok/tij24C9mEXfHyhHTckpOwsbExY7Ntb29L+fMHzs2LCyn2pVDY4Jonxe7jwQmFHKYKkUhkbm4uHA5L+VQAV1aO2dmVlRWRxUWn1WIRw45ZW1tbqfXtfUJIikIBVoQCDBIur+UQwnMc54GFQqii9+WOPAVajuStQYkhhwjhXQlzEyJ5U8KX4EjRxxfHHhN9tpG8t/ER/Xpz7AFXR58CLUfy1sQwQpXj/VkxkjaFBmCY2Kboz/o5GEaGHNJxSwghhBBCFKAAK0IBBgmX1wwG4zyHdNwSQgghhBAFKMCKUIBBwuU1g8E4zyEdt4QQQgghRAEKsCIUYCC+B8tgMFIipOOWEEIIIYQoQAFWhAIMBodGGAxGqoR03BJCCCGEEAUowIpQgAkhhBBCCCHkIkEBVoQCTAghhBBCCCEXCQqwIhRgQgghhBBCCLlIUIAVoQATQgghhBBCyEWCAqwIBZgQQgghhBBCLhIUYEUowIQQQgghhBBykaAAK0IBJoQQQgghhJCLBAVYEQowIYQQQgghhFwkKMCKUIAJIYQQQggh5CJBAVaEAkwIIYQQQgghFwkKsCIUYEIIIYQQQgi5SFCAFaEAE0IIIYQQQshFggKsiBBg/JXyhBBCCCGEEEJSGQqwIlBfjMXZDgchhBBCCCGEkNdCIBBQqVRarbanp8dut1OAE8FYRCIRKUMIIYQQQgghJGUxGo1FRUW1tbUmk8nhcMCH9/b2KMB/QwgwHZgQQgghhBBCUhqPx5OXl1deXt7c3DwyMrK8vLyxsQHXO9sfvZ4vARY/A96JIU0ihBBCCCGEEJJSLCws5ObmFhcX63Q6o9E4MzPj8/nC4fDh4SEF+BtgOPb39zc3N9fW1vhQaEIIIYQQQghJLerq6vLy8kpKSmC/PT09VqvV4/Fsb29D9M7WfsG5E2AgHHhrawvDtLCwsLu7K80ghBBCCCGEEHIu2dvbg/rm5uaqVCq1Wt3c3DwwMGC3271e7zmxX3AeBRhgaA4ODsLhcCAQWF5enpqaGhsbw8BJswkhhBBCCCGEnAN8Pl99fT28Nz8/v7i4uLKyEuprMpksFovL5QqFQru7u+fnfbfnVIAFh4eH+/v7QoMxdjabbXh4uLOzs6mpSavVqtXq0tJSDLFKpSosLCwghBBCCCGEEHIqQMEgYtCxsrIyjUaj0+ngvd3d3aOjo3a73e12Q32hcufkxq/MuRZggbgbvLe3t7W15ff7MZTz8/PT09Pj4+NDQ0Mmk8loNGKgIcaEEEIIIYQQQt40XV1dUDCIWH9///Dw8OTkpM1mW1xc9Hg8gUBge3sb+nZ+7vrGkwICLIPhE/eEMZo7Ozubm5uhUAjju76+7vP5vIQQQgghhBBC3jzwLwARg45Byra2tsLhMDQNsnbmz3lOTioJcDwYU+HDhBBCCCGEEELOCqFmQFK1802qCjAhhBBCCCGEEHIiKMCEEEIIIYQQQi4FFGBCCCGEEEIIIZcCCjAhhBBCCCGEkEsBBZgQQgghhBBCyKWAAkwIIYQQQggh5FJAASaEEEIIIYQQcimgABNCCCGEEEIIuRRQgAkhhBBCCCGEXAoowIQQQgghhBBCLgUUYEIIIYQQQgghlwIKMCGEEEIIIYSQS8DXX/8/zmyqHZJcDnUAAAAASUVORK5CYII=" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![s0%20%2811%29.PNG](attachment:s0%20%2811%29.PNG)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 예제 13-2-2-1 희소행렬 연산 알아보기" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [], + "source": [ + "a = sp.lil_matrix((5,5))" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<5x5 sparse matrix of type ''\n", + "\twith 0 stored elements in List of Lists format>" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [], + "source": [ + "a[0,0] = 2" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [], + "source": [ + "a[1,1] = 3" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [], + "source": [ + "a[2,2] = a[2,1] = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": {}, + "outputs": [], + "source": [ + "a[3,3] = a[3,0] = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [], + "source": [ + "b = a * a" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[4., 0., 0., 0., 0.],\n", + " [0., 9., 0., 0., 0.],\n", + " [0., 4., 1., 0., 0.],\n", + " [3., 0., 0., 1., 0.],\n", + " [0., 0., 0., 0., 0.]])" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b.todense()" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 7.3890561 , 1. , 1. , 1. , 1. ],\n", + " [ 1. , 20.08553692, 1. , 1. , 1. ],\n", + " [ 1. , 2.71828183, 2.71828183, 1. , 1. ],\n", + " [ 2.71828183, 1. , 1. , 2.71828183, 1. ],\n", + " [ 1. , 1. , 1. , 1. , 1. ]])" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.exp(a.toarray())" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [], + "source": [ + "c = np.dot(a , a)" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[4., 0., 0., 0., 0.],\n", + " [0., 9., 0., 0., 0.],\n", + " [0., 4., 1., 0., 0.],\n", + " [3., 0., 0., 1., 0.],\n", + " [0., 0., 0., 0., 0.]])" + ] + }, + "execution_count": 109, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c.todense()" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [], + "source": [ + "d = a.todense()" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[2., 0., 0., 0., 0.],\n", + " [0., 3., 0., 0., 0.],\n", + " [0., 1., 1., 0., 0.],\n", + " [1., 0., 0., 1., 0.],\n", + " [0., 0., 0., 0., 0.]])" + ] + }, + "execution_count": 111, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[4., 0., 0., 0., 0.],\n", + " [0., 9., 0., 0., 0.],\n", + " [0., 4., 1., 0., 0.],\n", + " [3., 0., 0., 1., 0.],\n", + " [0., 0., 0., 0., 0.]])" + ] + }, + "execution_count": 112, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.dot(d,d)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/README.md b/README.md index 5dfb010..4838ac0 100644 --- a/README.md +++ b/README.md @@ -1 +1,46 @@ -# numpy_itple \ No newline at end of file +# numpy_itple + + +# 파이썬 넘파이 완전 정복 + +공유드라이브: https://drive.google.com/drive/folders/1bHWLzuU-m-t8V6EJSXeRjbbjyaYGWJF_?usp=sharing + +깃허브: https://github.com/robertchoi/numpy_itple.git + +스터디원: 김민규, 최경웅, 전준용, 정상근, 조현진, 김민건, 백진주, 윤정환, 장춘희 + +스터디장: 최규남 + +인원: 10 + +노션주소: https://www.notion.so/ad6ab8a386cd46ad9263a1e5a639b5c1 + + +- 스터디 일정 + +[Study List](https://www.notion.so/a17d360def754b248c10c449361de556) + +- git PULL request하는 방법 + +[IT Artist : 네이버 블로그](https://blog.naver.com/pcmola/222026183913) + +[01장 참고자료](https://www.notion.so/01-7c512fd101d243f38a3dde2a85e55b28) + +[02장 참고자료](https://www.notion.so/02-5d2ef9ba6179408ea10974a154d64986) + +[03장 참고자료](https://www.notion.so/03-111bc517c4934749b317af561e3be3d6) + +[04장, 05장 참고자료](https://www.notion.so/04-05-1900ac896a784e65b24e995a4659a501) + +[06장, 07장 참고자료](https://www.notion.so/06-07-0a884f59afd2426ca1a67a71b675f385) + +[08장 참고자료](https://www.notion.so/08-902fbbdeaaba46b59413b794474d4f97) + +[09장 참고자료](https://www.notion.so/09-1cbfb2bf0b8f4804b938554c94d6ad5b) + +[10장 참고자료](https://www.notion.so/10-5b893826f0a04217924bc75a5f8b7602) + +[11장, 12장 참고자료](https://www.notion.so/11-12-6e1b74543d1b4c15ae3deea2945cf04b) + +[13장 참고자료](https://www.notion.so/13-ead489627f6045dda3139810859a1311) + diff --git "a/[\353\204\230\355\214\214\354\235\264]PPT \352\265\220\354\234\241\354\236\220\353\243\214_ver0014.pptx" "b/[\353\204\230\355\214\214\354\235\264]PPT \352\265\220\354\234\241\354\236\220\353\243\214_ver0014_20200904.pptx" similarity index 100% rename from "[\353\204\230\355\214\214\354\235\264]PPT \352\265\220\354\234\241\354\236\220\353\243\214_ver0014.pptx" rename to "[\353\204\230\355\214\214\354\235\264]PPT \352\265\220\354\234\241\354\236\220\353\243\214_ver0014_20200904.pptx"