|
| 1 | +import typing as tp |
| 2 | + |
| 3 | + |
| 4 | +import numpy as np |
| 5 | + |
| 6 | +from arraymap import AutoMap |
| 7 | +from arraymap import FrozenAutoMap |
| 8 | + |
| 9 | + |
| 10 | +class PayLoad: |
| 11 | + def __init__(self, array: np.ndarray): |
| 12 | + self.array = array |
| 13 | + self.list = list(array) |
| 14 | + self.faml = FrozenAutoMap(self.list) |
| 15 | + self.fama = FrozenAutoMap(self.array) |
| 16 | + self.ama = AutoMap(self.array) |
| 17 | + self.d = dict(zip(self.list, range(len(self.list)))) |
| 18 | + self.sel_array = array[(np.arange(len(array)) % 2) == 0] |
| 19 | + self.sel_scalar = list(self.sel_array) |
| 20 | + |
| 21 | + |
| 22 | +# ------------------------------------------------------------------------------- |
| 23 | +INT_START = 500 # avoid cached ints starting at 256 |
| 24 | + |
| 25 | + |
| 26 | +class FixtureFactory: |
| 27 | + NAME = "" |
| 28 | + SORT = 0 |
| 29 | + CACHE = {} # can be shared for all classes |
| 30 | + |
| 31 | + @staticmethod |
| 32 | + def get_array(size: int) -> np.ndarray: |
| 33 | + raise NotImplementedError() |
| 34 | + |
| 35 | + @classmethod |
| 36 | + def get_label_array(cls, size: int) -> tp.Tuple[str, PayLoad]: |
| 37 | + key = (cls, size) |
| 38 | + if key not in cls.CACHE: |
| 39 | + pl = PayLoad(cls.get_array(size)) |
| 40 | + cls.CACHE[key] = pl |
| 41 | + return cls.NAME, cls.CACHE[key] |
| 42 | + |
| 43 | + |
| 44 | +class FFInt64(FixtureFactory): |
| 45 | + NAME = "int64" |
| 46 | + SORT = 0 |
| 47 | + |
| 48 | + @staticmethod |
| 49 | + def get_array(size: int) -> np.ndarray: |
| 50 | + array = np.arange(INT_START, INT_START + size, dtype=np.int64) |
| 51 | + array.flags.writeable = False |
| 52 | + return array |
| 53 | + |
| 54 | + |
| 55 | +class FFInt32(FixtureFactory): |
| 56 | + NAME = "int32" |
| 57 | + SORT = 1 |
| 58 | + |
| 59 | + @staticmethod |
| 60 | + def get_array(size: int) -> np.ndarray: |
| 61 | + array = np.arange(INT_START, INT_START + size, dtype=np.int32) |
| 62 | + array.flags.writeable = False |
| 63 | + return array |
| 64 | + |
| 65 | + |
| 66 | +class FFUInt64(FixtureFactory): |
| 67 | + NAME = "uint64" |
| 68 | + SORT = 2 |
| 69 | + |
| 70 | + @staticmethod |
| 71 | + def get_array(size: int) -> np.ndarray: |
| 72 | + array = np.arange(INT_START, INT_START + size, dtype=np.uint64) |
| 73 | + array.flags.writeable = False |
| 74 | + return array |
| 75 | + |
| 76 | + |
| 77 | +class FFUInt32(FixtureFactory): |
| 78 | + NAME = "uint32" |
| 79 | + SORT = 3 |
| 80 | + |
| 81 | + @staticmethod |
| 82 | + def get_array(size: int) -> np.ndarray: |
| 83 | + array = np.arange(INT_START, INT_START + size, dtype=np.uint32) |
| 84 | + array.flags.writeable = False |
| 85 | + return array |
| 86 | + |
| 87 | + |
| 88 | +class FFFloat64(FixtureFactory): |
| 89 | + NAME = "float64" |
| 90 | + SORT = 4 |
| 91 | + |
| 92 | + @staticmethod |
| 93 | + def get_array(size: int) -> np.ndarray: |
| 94 | + array = (np.arange(INT_START, INT_START + size) * 0.5).astype(np.float64) |
| 95 | + array.flags.writeable = False |
| 96 | + return array |
| 97 | + |
| 98 | + |
| 99 | +class FFFloat32(FixtureFactory): |
| 100 | + NAME = "float32" |
| 101 | + SORT = 5 |
| 102 | + |
| 103 | + @staticmethod |
| 104 | + def get_array(size: int) -> np.ndarray: |
| 105 | + array = (np.arange(INT_START, INT_START + size) * 0.5).astype(np.float32) |
| 106 | + array.flags.writeable = False |
| 107 | + return array |
| 108 | + |
| 109 | + |
| 110 | +def get_string_array(size: int, char_count: int, kind: str) -> str: |
| 111 | + fmt = f"-<{char_count}" |
| 112 | + array = np.array( |
| 113 | + [ |
| 114 | + f"{hex(e) * (char_count // 8)}".format(fmt) |
| 115 | + for e in range(INT_START, INT_START + size) |
| 116 | + ], |
| 117 | + dtype=f"{kind}{char_count}", |
| 118 | + ) |
| 119 | + array.flags.writeable = False |
| 120 | + return array |
| 121 | + |
| 122 | + |
| 123 | +class FFU8(FixtureFactory): |
| 124 | + NAME = "U8" |
| 125 | + SORT = 6 |
| 126 | + |
| 127 | + @staticmethod |
| 128 | + def get_array(size: int) -> np.ndarray: |
| 129 | + return get_string_array(size, 8, "U") |
| 130 | + |
| 131 | + |
| 132 | +class FFU16(FixtureFactory): |
| 133 | + NAME = "U16" |
| 134 | + SORT = 7 |
| 135 | + |
| 136 | + @staticmethod |
| 137 | + def get_array(size: int) -> np.ndarray: |
| 138 | + return get_string_array(size, 16, "U") |
| 139 | + |
| 140 | + |
| 141 | +class FFU32(FixtureFactory): |
| 142 | + NAME = "U32" |
| 143 | + SORT = 8 |
| 144 | + |
| 145 | + @staticmethod |
| 146 | + def get_array(size: int) -> np.ndarray: |
| 147 | + return get_string_array(size, 32, "U") |
| 148 | + |
| 149 | + |
| 150 | +class FFU64(FixtureFactory): |
| 151 | + NAME = "U64" |
| 152 | + SORT = 9 |
| 153 | + |
| 154 | + @staticmethod |
| 155 | + def get_array(size: int) -> np.ndarray: |
| 156 | + return get_string_array(size, 64, "U") |
| 157 | + |
| 158 | + |
| 159 | +class FFU128(FixtureFactory): |
| 160 | + NAME = "U128" |
| 161 | + SORT = 10 |
| 162 | + |
| 163 | + @staticmethod |
| 164 | + def get_array(size: int) -> np.ndarray: |
| 165 | + return get_string_array(size, 128, "U") |
| 166 | + |
| 167 | + |
| 168 | +class FFS8(FixtureFactory): |
| 169 | + NAME = "S8" |
| 170 | + SORT = 11 |
| 171 | + |
| 172 | + @staticmethod |
| 173 | + def get_array(size: int) -> np.ndarray: |
| 174 | + return get_string_array(size, 8, "S") |
| 175 | + |
| 176 | + |
| 177 | +class FFS16(FixtureFactory): |
| 178 | + NAME = "S16" |
| 179 | + SORT = 12 |
| 180 | + |
| 181 | + @staticmethod |
| 182 | + def get_array(size: int) -> np.ndarray: |
| 183 | + return get_string_array(size, 16, "S") |
| 184 | + |
| 185 | + |
| 186 | +class FFS32(FixtureFactory): |
| 187 | + NAME = "S32" |
| 188 | + SORT = 13 |
| 189 | + |
| 190 | + @staticmethod |
| 191 | + def get_array(size: int) -> np.ndarray: |
| 192 | + return get_string_array(size, 32, "S") |
| 193 | + |
| 194 | + |
| 195 | +class FFS64(FixtureFactory): |
| 196 | + NAME = "S64" |
| 197 | + SORT = 14 |
| 198 | + |
| 199 | + @staticmethod |
| 200 | + def get_array(size: int) -> np.ndarray: |
| 201 | + return get_string_array(size, 64, "S") |
| 202 | + |
| 203 | + |
| 204 | +class FFS128(FixtureFactory): |
| 205 | + NAME = "S128" |
| 206 | + SORT = 15 |
| 207 | + |
| 208 | + @staticmethod |
| 209 | + def get_array(size: int) -> np.ndarray: |
| 210 | + return get_string_array(size, 128, "S") |
| 211 | + |
| 212 | + |
| 213 | +class FFDTY(FixtureFactory): |
| 214 | + NAME = "dt[Y]" |
| 215 | + SORT = 20 |
| 216 | + |
| 217 | + @staticmethod |
| 218 | + def get_array(size: int) -> np.ndarray: |
| 219 | + array = np.arange(INT_START, INT_START + size, dtype="datetime64[Y]") |
| 220 | + array.flags.writeable = False |
| 221 | + return array |
| 222 | + |
| 223 | + |
| 224 | +class FFDTD(FixtureFactory): |
| 225 | + NAME = "dt[D]" |
| 226 | + SORT = 21 |
| 227 | + |
| 228 | + @staticmethod |
| 229 | + def get_array(size: int) -> np.ndarray: |
| 230 | + array = np.arange(INT_START, INT_START + size, dtype="datetime64[D]") |
| 231 | + array.flags.writeable = False |
| 232 | + return array |
| 233 | + |
| 234 | + |
| 235 | +class FFDTs(FixtureFactory): |
| 236 | + NAME = "dt[s]" |
| 237 | + SORT = 22 |
| 238 | + |
| 239 | + @staticmethod |
| 240 | + def get_array(size: int) -> np.ndarray: |
| 241 | + array = np.arange(INT_START, INT_START + size, dtype="datetime64[s]") |
| 242 | + array.flags.writeable = False |
| 243 | + return array |
| 244 | + |
| 245 | + |
| 246 | +class FFDTns(FixtureFactory): |
| 247 | + NAME = "dt[ns]" |
| 248 | + SORT = 23 |
| 249 | + |
| 250 | + @staticmethod |
| 251 | + def get_array(size: int) -> np.ndarray: |
| 252 | + array = np.arange(INT_START, INT_START + size, dtype="datetime64[ns]") |
| 253 | + array.flags.writeable = False |
| 254 | + return array |
| 255 | + |
| 256 | + |
| 257 | +class FFObject(FixtureFactory): |
| 258 | + NAME = "object" |
| 259 | + SORT = 5 |
| 260 | + |
| 261 | + @staticmethod |
| 262 | + def get_array(size: int) -> np.ndarray: |
| 263 | + ints = np.arange(INT_START, INT_START + size) |
| 264 | + array = ints.astype(object) |
| 265 | + |
| 266 | + target = 1 == ints % 3 |
| 267 | + array[target] = ints[target] * 0.5 |
| 268 | + |
| 269 | + target = 2 == ints % 3 |
| 270 | + array[target] = np.array([hex(e) for e in ints[target]]) |
| 271 | + |
| 272 | + array.flags.writeable = False |
| 273 | + return array |
0 commit comments