diff --git a/cosipy/__init__.py b/cosipy/__init__.py index f3fdbb05..29114b6e 100644 --- a/cosipy/__init__.py +++ b/cosipy/__init__.py @@ -12,7 +12,7 @@ from .spacecraftfile import SpacecraftFile -from .ts_map import FastTSMap +from .ts_map import FastTSMap, MOCTSMap from .source_injector import SourceInjector diff --git a/cosipy/test_data/test_MOC_Map.fits b/cosipy/test_data/test_MOC_Map.fits new file mode 100644 index 00000000..bcd93223 Binary files /dev/null and b/cosipy/test_data/test_MOC_Map.fits differ diff --git a/cosipy/ts_map/TSMap.py b/cosipy/ts_map/TSMap.py deleted file mode 100644 index c5017aa5..00000000 --- a/cosipy/ts_map/TSMap.py +++ /dev/null @@ -1,332 +0,0 @@ -from cosipy.threeml.COSILike import COSILike - -from threeML import DataList, Powerlaw, PointSource, Model, JointLikelihood - -import numpy as np - -from histpy import Histogram, Axis - -from scipy import stats - -import matplotlib.pyplot as plt - -import astropy.io.fits as fits - -import logging -logger = logging.getLogger(__name__) - -class TSMap: - - """ - Compute the TS map of using `threeML` package. - """ - - def __init__(self, *args, **kwargs): - pass - - def link_model_all_plugins(self, dr, data, bkg, sc_orientation, piv, index, other_plugins=None, norm=1, ra=0, dec=0): - - """ - Load the model and plugins - - Parameters - ---------- - dr : str - Path to full detector response. - data : histpy.Histogram - Binned data. Note: Eventually this should be a cosipy data class. - bkg : histpy.Histogram - Binned background model. Note: Eventually this should be a cosipy data class. - sc_orientation : cosipy.spacecraftfile.SpacecraftFile - Contains the information of the orientation: timestamps (astropy.Time) and attitudes (scoord.Attitude) that describe - the spacecraft for the duration of the data included in the analysis. - piv : float - The pivotal energy of the spectrum. - index : float - The index of the spectrum. - other_plugins : threeML.plugins, optional - The plugins from other instruments. - norm : int, optional - The norm of the spectrum model (the default is 1). - ra : float, optional - The RA of the source model (the default is 0). - dec : float, optional - The Dec of the source model (the default is 0). - """ - - # necessary inputs - self.dr = dr - self.data = data - self.bkg = bkg - self.sc_orientation = sc_orientation - self.piv = piv - self.index = index - - # optional inputs (have default value) - self.other_plugins = other_plugins - self.norm = norm - self.ra = ra - self.dec = dec - - # instantiate plugin by dr, data, bkg and sc_orientation - # only COSI plugin for now - self.instantiate_plugin() - - # gather all plugins - # only COSI plugin for now - self.gather_all_plugins() - - # create model by Powerlaw and PointSource - # Powerlaw needs norm (free parameter), piv and index (free parameter) - # PointSource needs ra and dec - self.create_model() - - # fix index in further 3ML fitting - self.fix_index() - - # put model and all plugins together - self.like = JointLikelihood(self.model, self.all_plugins, verbose = False) - - def instantiate_plugin(self): - - """ - Instantiate the likelihood plugin. - """ - - if self.other_plugins == None: - self.cosi_plugin = COSILike("cosi", - dr = self.dr, - data = self.data, - bkg = self.bkg, - sc_orientation = self.sc_orientation) - else: - raise RuntimeError("Only COSI plugin for now") - - def gather_all_plugins(self): - - """ - Gather all the plugins togather into a DataList. - """ - - if self.other_plugins == None: - self.all_plugins = DataList(self.cosi_plugin) - else: - raise RuntimeError("Only COSI plugin for now") - - def create_model(self): - - """ - Create the source model. - - Returns - ------- - astromodels.core.model.Model - The source model. - - """ - - self.spectrum = Powerlaw() - - self.spectrum.K.value = self.norm # 1/keV/cm2/s - self.spectrum.piv.value = self.piv # keV - self.spectrum.index.value = self.index - - self.source = PointSource("source", # The name of the source is arbitrary, but needs to be unique - ra = self.ra, - dec = self.dec, - spectral_shape = self.spectrum) - - self.model = Model(self.source) - - def fix_index(self): - - """ - Return the index of the source spectrum. - """ - - self.source.spectrum.main.Powerlaw.index.fix = True - - def ts_fitting(self): - - """ - Peform the ts fitting. - """ - - # collect ts_grid_data, ts_grid_bkg and calculate_ts because sometime we may want to skip fiiting - self.ts_grid_data() - self.ts_grid_bkg() - self.calculate_ts() - - # iterate ra and dec to find the best fit of data (time consuming) - def ts_grid_data(self): - - """ - Perform the ts fitting using the data on the different pixels. - """ - - # using rad due to mollweide projection - self.ra_range = (-np.pi , np.pi ) # rad - self.dec_range = (-np.pi/2, np.pi/2) # rad - - self.log_like = Histogram( - [Axis(np.linspace(*self.ra_range , 50), label = "ra" ), - Axis(np.linspace(*self.dec_range, 25), label = "dec"),] - ) - - for i in range(self.log_like.axes['ra'].nbins): - for j in range(self.log_like.axes['dec'].nbins): - - # progress - logger.info(f"\rra = {i:2d}/{self.log_like.axes['ra'].nbins} ", end = "") - logger.info(f"dec = {j:2d}/{self.log_like.axes['dec'].nbins} ", end = "") - - # changing the position parameters - # converting rad to deg due to ra and dec in 3ML PointSource - if self.log_like.axes['ra'].centers[i] < 0: - self.source.position.ra = (self.log_like.axes['ra'].centers[i] + 2*np.pi) * (180/np.pi) # deg - else: - self.source.position.ra = (self.log_like.axes['ra'].centers[i]) * (180/np.pi) # deg - self.source.position.dec = self.log_like.axes['dec'].centers[j] * (180/np.pi) # deg - - # maximum likelihood - self.like.fit(quiet=True) - - # converting the min (- log likelihood) from 3ML to the max log likelihood for TS - self.log_like[i, j] = -self.like._current_minimum - - # iterate ra and dec to find the best fit of bkg - # only see it as constant for now - # set the normalization to 0, that is, background-only null-hypothesis - def ts_grid_bkg(self): - - """ - Perform the ts fitting using the background on the different pixels. - """ - - # spectrum.K.value need to be 1e-10 otherwise you will have a migrad error - self.spectrum.K.value = 1e-10 - - # maximum likelihood - self.like.fit(quiet=True) - - # converting the min (- log likelihood) from 3ML to the max log likelihood for TS - self.log_like0 = -self.like._current_minimum - - # calculate TS by ts_grid_data and ts_grid_bkg - def calculate_ts(self): - - """ - Calculate the TS by the TS of data and background. - """ - - self.ts = 2 * (self.log_like - self.log_like0) - - # getting the maximum - # note that, in our case, since log_like0 is a constant, max(TS) = 2 - self.argmax = np.unravel_index(np.argmax(self.ts), self.ts.nbins) - self.ts_max = self.ts[self.argmax] - - def print_best_fit(self): - - """ - Print the best fit location. - """ - - # report the best fit position - # converting rad to deg due to ra and dec in 3ML PointSource - if self.ts.axes['ra'].centers[self.argmax[0]] < 0: - self.best_ra = (self.ts.axes['ra'].centers[self.argmax[0]] + 2*np.pi) * (180/np.pi) # deg - else: - self.best_ra = (self.ts.axes['ra'].centers[self.argmax[0]]) * (180/np.pi) # deg - self.best_dec = self.ts.axes['dec'].centers[self.argmax[1]] * (180/np.pi) # deg - logger.info(f"Best fit position: RA = {self.best_ra} deg, Dec = {self.best_dec} deg") - - # convert to significance based on Wilk's theorem - logger.info(f"Expected significance: {stats.norm.isf(stats.chi2.sf(self.ts_max, df = 2)):.1f} sigma") - - def save_ts(self, output_file_name): - - """ - Save the TS map. - - Parameters - ---------- - output_file_name : str - The path to save the ts map. - """ - - # save TS to .h5 file - self.ts.write(output_file_name, overwrite = True) - - def load_ts(self, input_file_name): - - """ - Load a ts map from file. - - Parameters - ---------- - input_file_name : str - The path to the saved TS map file. - """ - - # load .h5 file to TS - self.ts = Histogram.open(input_file_name) - - # getting the maximum - self.argmax = np.unravel_index(np.argmax(self.ts), self.ts.nbins) - self.ts_max = self.ts[self.argmax] - - # refit the best fit to check norm - def refit_best_fit(self): - - """ - Refit the best fit to check norm. - """ - - # reset self.spectrum.K.value to self.norm (big initial value) - self.spectrum.K.value = self.norm - - # converting rad to deg due to RA and Dec in 3ML PointSource - if self.ts.axes['ra'].centers[self.argmax[0]] < 0: - self.source.position.ra = (self.ts.axes['ra'].centers[self.argmax[0]] + 2*np.pi) * (180/np.pi) # deg - else: - self.source.position.ra = (self.ts.axes['ra'].centers[self.argmax[0]]) * (180/np.pi) # deg - self.source.position.dec = self.ts.axes['dec'].centers[self.argmax[1]] * (180/np.pi) # deg - - # maximum likelihood - self.like.fit() - - # display the best fit result - self.like.results.display() - - def plot_ts_map(self): - - """ - Plot the TS map. - """ - - fig, ax = plt.subplots(figsize=(16, 8), subplot_kw={'projection': 'mollweide'}, dpi=120) - - _,plot = self.ts.plot(ax, vmin = 0, colorbar = False, zorder=0) - - ax.scatter([self.ts.axes['ra'].centers[self.argmax[0]]],[self.ts.axes['dec'].centers[self.argmax[1]]], label = "Max TS", zorder=3) - - ax.scatter([20/180*np.pi],[40/180*np.pi], marker = "x", label = "Injected", zorder=2) - - # here we also use Wilk's theorem to find the DeltaTS that corresponse to a 90% containment confidence - ts_thresh = self.ts_max - stats.chi2.isf(1-.9, df = 2) - contours = ax.contour(self.ts.axes['ra'].centers, - self.ts.axes['dec'].centers, - self.ts.contents.transpose(), - [ts_thresh], colors = 'red', zorder=1) - contours.collections[0].set_label("90% cont.") - - cbar = fig.colorbar(plot) - cbar.ax.set_ylabel("TS") - - ax.set_xlabel('R.A.', fontsize=15); - ax.set_ylabel('Dec.', fontsize=15); - ax.tick_params(axis='x', colors='White') - ax.legend(fontsize=10) - - \ No newline at end of file diff --git a/cosipy/ts_map/__init__.py b/cosipy/ts_map/__init__.py index 03f650a1..d2b8ec43 100644 --- a/cosipy/ts_map/__init__.py +++ b/cosipy/ts_map/__init__.py @@ -1,3 +1,3 @@ -from .TSMap import TSMap from .fast_ts_fit import FastTSMap -from .fast_norm_fit import FastNormFit \ No newline at end of file +from .fast_norm_fit import FastNormFit +from .moc_ts_fit import MOCTSMap diff --git a/cosipy/ts_map/fast_ts_fit.py b/cosipy/ts_map/fast_ts_fit.py index 323f7003..f119f94e 100644 --- a/cosipy/ts_map/fast_ts_fit.py +++ b/cosipy/ts_map/fast_ts_fit.py @@ -283,7 +283,7 @@ def get_ei_cds_array(hypothesis_coord, energy_channel, response_path, spectrum, def fast_ts_fit(hypothesis_coord, energy_channel, data_cds_array, bkg_model_cds_array, orientation, response_path, spectrum, cds_frame, - ts_nside, ts_scheme): + ts_nside, ts_scheme, pixel_idx = None): """ Perform a TS fit on a single location at `hypothesis_coord`. @@ -320,7 +320,10 @@ def fast_ts_fit(hypothesis_coord, start_fast_ts_fit = time.time() # get the indices of the pixels to fit - pix = hp.ang2pix(nside = ts_nside, theta = hypothesis_coord.l.deg, phi = hypothesis_coord.b.deg, lonlat = True) + if pixel_idx is None: + pix = hp.ang2pix(nside = ts_nside, theta = hypothesis_coord.l.deg, phi = hypothesis_coord.b.deg, lonlat = True) + else: + pix = pixel_idx # get the expected counts in the flattened cds array start_ei_cds_array = time.time() @@ -341,9 +344,55 @@ def fast_ts_fit(hypothesis_coord, time_fast_ts_fit = end_fast_ts_fit - start_fast_ts_fit return [pix, result[0], result[1], result[2], result[3], result[4], time_ei_cds_array, time_fit, time_fast_ts_fit] + + @staticmethod + def zip_comp(*lists): + + """ + Zip the lists in a way that it expands the lists will one element. + + list1 = [1, 2, 3, 4] + list2 = ["a"] + list3 = [11, 21, 31, 41] + + zip_comp will produce a tuple like this: + ([1, "a", 11], + [2, "a", 21], + [3, "a", 31], + [4, "a", 41]) + + As you can see, it only allows lists with two length: 1 or the max length. + + Parameters + ---------- + lists : list + The input lists + + Returns + ------- + zip : + The zippped array. To expand, please use list(returned_object) + + """ + + all_lengths = np.unique([len(i) for i in lists]) + + if len(all_lengths) > 2: + raise ValueError(f"You have input lists with more than two lengths: {all_lengths}. Can't do zip comprehension!") + + + new_lists = [] + for i in lists: + if len(i) == np.min(all_lengths): + new_lists.append(i*np.max(all_lengths)) + else: + new_lists.append(i) + + return zip(*new_lists) - def parallel_ts_fit(self, hypothesis_coords, energy_channel, spectrum, ts_scheme = "RING", start_method = "fork", cpu_cores = None, ts_nside = None): + def parallel_ts_fit(self, hypothesis_coords, energy_channel, spectrum, ts_scheme = "RING", start_method = "fork", cpu_cores = None, ts_nside = None, + pixel_idx = [None]): """ Perform parallel computation on all the hypothesis coordinates. @@ -363,7 +412,9 @@ def parallel_ts_fit(self, hypothesis_coords, energy_channel, spectrum, ts_scheme cpu_cores : int, optional The number of cpu cores you wish to use for the parallel computation (the default is `None`, which implies using all the available number of cores -1 to perform the parallel computation). ts_nside : int, optional - The nside of the ts map. This must be given if the number of hypothesis_coords isn't equal to the number of pixels of the total ts map, which means that you fit only a portion of the total ts map. (the default is `None`, which means that you fit the full ts map). + The nside of the ts map. This must be given if the number of hypothesis_coords isn't equal to the number of pixels of the total ts map, which means that you fit only a portion of the total ts map. (the default is `None`, which means that you fit the full ts map). + pixel_idx : list, optional + The pixel indices of the corresponding hypothesis_coords. This parameter is used to match the pixels and the ts values in a regional fit case. Returns ------- @@ -399,12 +450,12 @@ def parallel_ts_fit(self, hypothesis_coords, energy_channel, spectrum, ts_scheme cores = cpu_cores logger.info(f"You have total {total_cores} CPU cores, using {cores} CPU cores for parallel computation.") - start = time.time() + start = time.time() multiprocessing.set_start_method(start_method, force = True) pool = multiprocessing.Pool(processes = cores) - results = pool.starmap(FastTSMap.fast_ts_fit, product(hypothesis_coords, [energy_channel], [data_cds_array], [bkg_model_cds_array], - [self._orientation], [self._response_path], [spectrum], [self._cds_frame], - [ts_nside], [ts_scheme])) + results = pool.starmap(FastTSMap.fast_ts_fit, FastTSMap.zip_comp(hypothesis_coords, [energy_channel], [data_cds_array], [bkg_model_cds_array], + [self._orientation], [self._response_path], [spectrum], [self._cds_frame], + [ts_nside], [ts_scheme], pixel_idx)) pool.close() pool.join() diff --git a/cosipy/ts_map/moc_ts_fit.py b/cosipy/ts_map/moc_ts_fit.py new file mode 100644 index 00000000..6d6a2d0a --- /dev/null +++ b/cosipy/ts_map/moc_ts_fit.py @@ -0,0 +1,329 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Created on Wed Oct 2 15:39:42 2024 + +@author: shengyong +""" + +import numpy as np +from mhealpy import HealpixMap +from mhealpy.pixelfunc.moc import * +from mhealpy.pixelfunc.single import * +from .fast_ts_fit import FastTSMap +import matplotlib.pyplot as plt +from copy import deepcopy +import astropy.units as u +from astropy.coordinates import SkyCoord +from pathlib import Path +import logging +logger = logging.getLogger(__name__) + + +class MOCTSMap(FastTSMap): + + def __init__(self, data, bkg_model, response_path, orientation = None, cds_frame = "local"): + + """ + Initialize the instance of a MOC TS map fit. + + Parameters + ---------- + data : histpy.Histogram + Observed data, which includes counts from both signal and background. + bkg_model : histpy.Histogram + Background model, which includes the background counts to model the background in the observed data. + response_path : str or pathlib.Path + The path to the response file. + orientation : cosipy.SpacecraftFile, optional + The orientation of the spacecraft when data are collected (the default is `None`, which implies the orientation file is not needed). + cds_frame : str, optional + "local" or "galactic", it's the Compton data space (CDS) frame of the data, bkg_model and the response. In other words, they should have the same cds frame (the default is "local", which implied that a local frame that attached to the spacecraft). + + """ + + super().__init__(data, bkg_model, response_path, orientation = orientation, cds_frame = cds_frame) + + + @staticmethod + def upscale_moc_map(m, uniq_mother, new_order): + + """ + Upscale the MOC map on certain mother pixels. All the child pixels will be filled by the value of the mother pixel. + + Parameters + ---------- + m : mhealpy.containers.healpix_map.HealpixMap + The input map to be upscaled. + uniq_mother_pix : int or array + The uniq number the mother pixels to be upscaled. + new_order : int + The order of the child pixels upscaled from the mother pixels. + + Returns + ------- + tuple + The upscaled the map and the unique numbers of the child pixels. + """ + + if not m.is_moc: + raise TypeError("The input map must be a MOC map.") + + # copy the uniq numbers and the data from the original map + new_uniq = deepcopy(m.uniq) + new_data = deepcopy(m.data) + + new_nside = 2**new_order + + uniq_child_all = [] + + for mother_uniq in uniq_mother: + + # get the index of the mother pixel + idx = np.where(new_uniq == mother_uniq)[0][0] # note that idx is the index of the uniq number, not the uniq number + + # get the start and stop of the child pixel number in the NESTED scheme (also the index in the NESTED scheme case) + start_nest = uniq2range(new_nside, mother_uniq)[0] + stop_nest = uniq2range(new_nside, mother_uniq)[1] + + # convert the child pixel number from NESTED scheme to UNIQ scheme + uniq_child = nest2uniq(new_nside, np.arange(start_nest, stop_nest)) + uniq_child_all += list(uniq_child) + + # update the moc map + new_uniq = np.concatenate((new_uniq[:idx], + uniq_child, + new_uniq[idx+1:])) + + new_data = np.concatenate((new_data[:idx], + np.repeat(new_data[idx], stop_nest-start_nest), + new_data[idx + 1:])) + + m_new = HealpixMap(data = new_data, uniq = new_uniq) + + return m_new, np.array(uniq_child_all) + + @staticmethod + def uniq2skycoord(uniq): + + """ + Convert the uniq number to the corresponding central skycoord. + + Parameters + ---------- + uniq : int, list or numpy.ndarray + The uniq number(s) of the pixel(s) + + Returns + ------- + astropy.Coordinates.SkyCoord + The galactic skycoord of the input uniq pixels. + """ + + nside, pix_num_nested = uniq2nest(uniq) + + lon, lat = pix2ang(nside = nside, ipix = pix_num_nested, nest = True, lonlat = True) + + return SkyCoord(l = lon, b = lat, unit = (u.deg, u.deg), frame = "galactic") + + @staticmethod + def uniq2pixidx(m, uniq): + + """ + Convert the uniq to the pixel index in the map. + + Parameters + ---------- + m : mhealpy.containers.healpix_map.HealpixMap + The map that contains the moc pixels + uniq : int, list or numpy.ndarray: + The uniq number(s) of the pixel(s) + + Returns + ------- + list + The list of the pixel index of the corresponding uniq pixels in the map + """ + + return [np.where(m.uniq == i)[0][0] for i in uniq] + + def fill_up_moc_map(pixidx, m, results): + + """ + Fill up the moc map based on the pixidx. + + Parameters + ---------- + pixidx : int or list + The pixel index, not the uniq number of the pixels + m : mhealpy.containers.healpix_map.HealpixMap + The MOC map to be filled + results : numpy.ndarray + The ts fit results. + + Returns + ------- + mhealpy.containers.healpix_map.HealpixMap + The filled map + """ + + if isinstance(pixidx, int): + pixidx = [pixidx] + + for pixidx_ in pixidx: + pixidx_ = int(pixidx_) + + idx = np.where(results[:,0].astype(int) == pixidx_)[0] # idx is the row idx of the result array where the first column equals to pixidx_ + if idx.shape[0] != 1: + raise ValueError(f"Pixel with pixel index {pixidx_} has {idx.shape[0]} fits! ") + else: + m[pixidx_] = results[idx,1] + + return m + + + def moc_ts_fit(self, max_moc_order, top_number, energy_channel, spectrum, start_method = "fork", cpu_cores = None): + + """ + Fit the MOC map. + + Parameters + ---------- + max_moc_order : int + The order of the MOC map to stop the fitting. + top_number : int + The pixels with the top likelihood to will be upscaled. For example, pixels with top eight likelihoods will be considered as mother pixels to be split into the child pixels. + energy_channel : list + The energy channel to be used for the MOC map fitting. + spectrum : + The spectrum model of the source to fit the model. + start_method : str, optional + The starting method of the parallel computation (the default is "fork", which implies using the fork method to start parallel computation). + cpu_cores : int, optional + The number of cpu cores you wish to use for the parallel computation (the default is `None`, which implies using all the available number of cores -1 to perform the parallel computation). + """ + + # initialize the order + order = 0 + + # initialize the 0th order moc map, which is equlivent to a 0th order single resolution map + uniq = nest2uniq(1, np.arange(12)) + moc_map_ts = HealpixMap(data = np.repeat(0., 12), uniq = uniq) + + # make the 0th order fit over all pixels + hypothesis_coords = MOCTSMap.uniq2skycoord(moc_map_ts.uniq) + hypothesis_coords_list = [i for i in hypothesis_coords] # have to split the SkyCoord object into SkyCoord object + pixidx = MOCTSMap.uniq2pixidx(moc_map_ts, moc_map_ts.uniq) + + print(f"fitting order = {order}") + print(f"fitting {len(hypothesis_coords_list)} hypothesis coordinates") + results = self.parallel_ts_fit(hypothesis_coords = hypothesis_coords_list, energy_channel = energy_channel, spectrum = spectrum, pixel_idx = pixidx) + self.ts_array = results[:,1] + + # fill up the 0th order moc map + moc_map_ts = MOCTSMap.fill_up_moc_map(pixidx, moc_map_ts, results) + self.moc_map_ts = moc_map_ts + + # store all ts maps + self.all_maps = [] + self.all_maps += [moc_map_ts] + + + # # if the user requires higher order fit + # threshold = moc_map_ts[:].max() - MOCTSMap.get_chi_critical_value(split_containment) # the threshold value to decide the mother pixels to be split + order += 1 + print("--------------------------------------------------------------------------------") + + # start the while loop + while order <= max_moc_order: + + # decide the mother pixels to divide + # threshold = moc_map_ts[:].max() - MOCTSMap.get_chi_critical_value(split_containment) + top_number_arg_array = np.argpartition(moc_map_ts, -top_number)[-top_number:] + print(f"The top {top_number} ts values are: {top_number_arg_array} in the last iteration, splitting these pixels...") + threshold = min(moc_map_ts[top_number_arg_array]) + + mother_idx = np.where(moc_map_ts[:] >= threshold)[0] + mother_uniq = moc_map_ts.uniq[mother_idx] + + # upscale the resolution of the mother pixels by 1 order, now the moc map is updated + moc_map_ts, child_uniq = MOCTSMap.upscale_moc_map(moc_map_ts, uniq_mother = mother_uniq, new_order = order) + + # get the sky coordinates of the child pixels + hypothesis_coords = MOCTSMap.uniq2skycoord(child_uniq) + hypothesis_coords_list = [i for i in hypothesis_coords] # have to split the SkyCoord object into SkyCoord object list + child_idx = MOCTSMap.uniq2pixidx(moc_map_ts, child_uniq) # child_idx is used to make sure that the ts values are filled into the correct pixels + print(f"fitting order {order} with {len(hypothesis_coords_list)} hypothesis coordinates") + results = self.parallel_ts_fit(hypothesis_coords = hypothesis_coords_list, energy_channel = energy_channel, spectrum = spectrum, ts_nside = 2**order, pixel_idx = child_idx) + self.ts_array = results[:,1] + + # fill up the child pixels + moc_map_ts = MOCTSMap.fill_up_moc_map(child_idx, moc_map_ts, results) + self.moc_map_ts = moc_map_ts + self.all_maps += [moc_map_ts] + + + order +=1 + print("--------------------------------------------------------------------------------") + + + return moc_map_ts + + def plot_ts(self, moc_map = None, skycoord = None, containment = None, save_plot = False, save_dir = "", save_name = "ts_map.png", dpi = 300): + + """ + Plot the containment region of the TS map. + + Parameters + ---------- + ts_array : numpy.ndarray + The array of ts values from parallel ts fit. + skyoord : astropy.coordinates.SkyCoord, optional + The true location of the source (the default is `None`, which implies that there are no coordiantes to be printed on the TS map). + containment : float, optional + The containment level of the source (the default is `None`, which will plot raw TS values). + save_plot : bool, optional + Set `True` to save the plot (the default is `False`, which means it won't save the plot. + save_dir : str or pathlib.Path, optional + The directory to save the plot. + save_name : str, optional + The file name of the plot to be save. + dpi : int, optional + The dpi for plotting and saving. + """ + + + if moc_map is None: + moc_map = self.moc_map_ts + + # decide the critical value + if containment is not None: + critical = MOCTSMap.get_chi_critical_value(containment = 0.9) + max_ts = np.max(moc_map[:]) + + # get plotting canvas + fig = plt.figure(dpi = dpi) + + axMoll = fig.add_subplot(1,1,1, projection = 'mollview') + + # Plot in one of the axes + if containment is None: + plotMoll, projMoll = moc_map.plot(ax = axMoll) + else: + plotMoll, projMoll = moc_map.plot(ax = axMoll, vmin = max_ts-critical, vmax = max_ts) + + moc_map.plot_grid(ax = plt.gca(), color = 'grey', linewidth = 0.1); + + + # plot the sky cooordinates if given + if skycoord is not None: + + axMoll.text(skycoord.l.deg, skycoord.b.deg, "x", size = 4, + horizontalalignment='center', + verticalalignment='center', + transform = axMoll.get_transform('world'), color = "red") + + if save_plot == True: + + fig.savefig(Path(save_dir)/save_name, dpi = dpi) + diff --git a/docs/tutorials/ts_map/Parallel_TS_map_computation.ipynb b/docs/tutorials/ts_map/Parallel_TS_map_computation.ipynb index 95b08fdf..ffd7b087 100644 --- a/docs/tutorials/ts_map/Parallel_TS_map_computation.ipynb +++ b/docs/tutorials/ts_map/Parallel_TS_map_computation.ipynb @@ -210,12 +210,251 @@ "execution_count": 2, "id": "9485f7bb-ca6e-440e-8d2d-4b4f29d32781", "metadata": {}, - 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+       "                  available                                                                                        \n",
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+       "                  performances in 3ML                                                                              \n",
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+       "                  performances in 3ML                                                                              \n",
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+       "                  performances in 3ML                                                                              \n",
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-228,7 +467,10 @@ "import gc\n", "from cosipy.util import fetch_wasabi_file\n", "import shutil\n", - "import os" + "import os\n", + "\n", + "import logging\n", + "logging.basicConfig(level = logging.INFO)" ] }, { @@ -331,7 +573,7 @@ " fetch_wasabi_file(\"COSI-SMEX/DC2/Responses/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5.zip\", zipped_response_path)\n", "\n", " # unzip the response file\n", - " shutil.unpack_archive(zipped_response_path)\n", + " shutil.unpack_archive(zipped_response_path, extract_dir = data_dir)\n", " \n", " # delete the zipped response to save space\n", " os.remove(zipped_response_path)" @@ -581,7 +823,16 @@ "execution_count": 17, "id": "c3188898-ee3f-4100-b2da-340333f22756", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:cosipy.ts_map.fast_ts_fit:You have total 8 CPU cores, using 7 CPU cores for parallel computation.\n", + "INFO:cosipy.ts_map.fast_ts_fit:The time used for the parallel TS map computation is 13.890416451295216 minutes\n" + ] + } + ], "source": [ "ts_results = ts.parallel_ts_fit(hypothesis_coords = hypothesis_coords, energy_channel = [2,3], spectrum = spectrum, ts_scheme = \"RING\", cpu_cores = 56)" ] @@ -637,7 +888,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "id": "e8538ead-8564-42ab-bb87-0f21c70c7abc", "metadata": {}, "outputs": [ @@ -682,7 +933,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": null, "id": "c1b1ca06-618c-4531-9b98-ef9e5980042d", "metadata": {}, "outputs": [], @@ -702,7 +953,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": null, "id": "75dc1b55-f422-424e-951e-bd266b53e594", "metadata": {}, "outputs": [], @@ -734,17 +985,25 @@ "if not response_path.exists():\n", " fetch_wasabi_file(\"COSI-SMEX/DC2/Responses/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5.zip\", zipped_response_path)\n", " # unzip the response file\n", - " shutil.unpack_archive(zipped_response_path)\n", + " shutil.unpack_archive(zipped_response_path, extract_dir = data_dir)\n", " # delete the zipped response to save space\n", " os.remove(zipped_response_path)" ] }, { "cell_type": "code", - "execution_count": 52, + "execution_count": null, "id": "efea0798-053f-4294-a4fa-d4ac71875f18", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:cosipy.ts_map.fast_ts_fit:You have total 8 CPU cores, using 7 CPU cores for parallel computation.\n", + "INFO:cosipy.ts_map.fast_ts_fit:The time used for the parallel TS map computation is 13.131452250480653 minutes\n" + ] + }, { "data": { "image/png": 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", @@ -827,7 +1086,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": null, "id": "b4337b3e-d99d-4b91-b057-59eff911a5cf", "metadata": {}, "outputs": [], @@ -838,7 +1097,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": null, "id": "f2d84b3b-fd4d-4e42-aaa8-113dd5cb4618", "metadata": {}, "outputs": [ @@ -898,9 +1157,7 @@ { "cell_type": "markdown", "id": "92247366-573f-46e1-8a8a-c1e5db2b5399", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "### Bin data (optional)" ] @@ -923,7 +1180,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 3, "id": "cc73d0d2-a347-4a51-95a9-d75b8405800f", "metadata": {}, "outputs": [], @@ -933,10 +1190,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "931588ad-4c21-4fd5-9c27-2352b30ac2dc", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "DEBUG:awscli.clidriver:OrderedDict([('bucket', ), ('if-match', ), ('if-modified-since', ), ('if-none-match', ), ('if-unmodified-since', ), ('key', ), ('range', ), ('response-cache-control', ), ('response-content-disposition', ), ('response-content-encoding', ), ('response-content-language', ), ('response-content-type', ), ('response-expires', ), ('version-id', ), ('sse-customer-algorithm', ), ('sse-customer-key', ), ('sse-customer-key-md5', ), ('request-payer', ), ('part-number', ), ('expected-bucket-owner', ), ('checksum-mode', )])\n", + "DEBUG:awscli.arguments:Unpacked value of 'cosi-pipeline-public' for parameter \"bucket\": 'cosi-pipeline-public'\n", + "DEBUG:awscli.arguments:Unpacked value of 'COSI-SMEX/DC2/Data/Sources/Crab_DC2_3months_unbinned_data.fits.gz' for parameter \"key\": 'COSI-SMEX/DC2/Data/Sources/Crab_DC2_3months_unbinned_data.fits.gz'\n", + "DEBUG:awscli.formatter:RequestId: 21FE31583B3A8656:B\n" + ] + } + ], "source": [ "%%capture\n", "crab_unbinned_path = data_dir/\"Crab_DC2_3months_unbinned_data.fits.gz\"\n", @@ -1044,7 +1312,7 @@ "id": "993bbc9e-b056-4369-b7f7-3f59f0e26e4f", "metadata": {}, "source": [ - "### Read data and background" + "### Download the binned data" ] }, { @@ -1057,14 +1325,6 @@ "**For the purposes of this tutorial we use data that has already been binned, however, binning of the data is generally performed as part of the standard binned analysis, as demonstrated in the dataIO tutorial.**" ] }, - { - "cell_type": "markdown", - "id": "01980340-c1e7-4ef1-a169-47c7d136852b", - "metadata": {}, - "source": [ - "#### Download the binned data" - ] - }, { "cell_type": "code", "execution_count": 30, @@ -1077,7 +1337,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "id": "8400db09-0c32-4533-9bfc-35729ec3f514", "metadata": {}, "outputs": [], @@ -1092,7 +1352,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "id": "142b9b61-487b-40b5-b2e0-191f4c5f4f07", "metadata": {}, "outputs": [], @@ -1105,9 +1365,17 @@ " fetch_wasabi_file(\"COSI-SMEX/cosipy_tutorials/ts_maps/Albedo_galactic_CDS_binned.hdf5\", albedo_background_path)" ] }, + { + "cell_type": "markdown", + "id": "efd60ec5-d5b6-4c6f-8d26-f8152076532c", + "metadata": {}, + "source": [ + "### Read the data" + ] + }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "id": "720de2f7-222e-4d29-815a-a85c07abca46", "metadata": {}, "outputs": [], @@ -1130,7 +1398,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "id": "109c9aaf-be38-4a10-9c93-add2fdb5bfa9", "metadata": {}, "outputs": [ @@ -1140,7 +1408,7 @@ "Text(0, 0.5, 'Counts')" ] }, - "execution_count": 35, + "execution_count": null, "metadata": {}, "output_type": "execute_result" }, @@ -1170,7 +1438,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "id": "194a38f1-2070-46a3-914a-970ecd41aaeb", "metadata": {}, "outputs": [], @@ -1191,7 +1459,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": null, "id": "72ba732c-37d3-4a43-afbe-24292fbbd3e6", "metadata": {}, "outputs": [], @@ -1211,7 +1479,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "id": "7c39a92b-3016-4b19-b56e-7ac0bbe33f1f", "metadata": {}, "outputs": [], @@ -1226,7 +1494,7 @@ " fetch_wasabi_file(\"COSI-SMEX/DC2/Responses/PointSourceReponse/psr_gal_continuum_DC2.h5.zip\", zipped_response_path)\n", " \n", " # unzip the response\n", - " shutil.unpack_archive(zipped_response_path)\n", + " shutil.unpack_archive(zipped_response_path, extract_dir = data_dir)\n", " \n", " # delete the zipped response to save space\n", " os.remove(zipped_response_path)" @@ -1234,7 +1502,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": null, "id": "de748dc4-97a9-4b44-8531-e56a7be242d5", "metadata": {}, "outputs": [], @@ -1245,7 +1513,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": null, "id": "73ba79d0-a686-453e-b081-46d9462d338f", "metadata": {}, "outputs": [], @@ -1257,10 +1525,19 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": null, "id": "19d55399-0ef5-41dc-9bd6-29281375ccb5", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:cosipy.ts_map.fast_ts_fit:You have total 8 CPU cores, using 7 CPU cores for parallel computation.\n", + "INFO:cosipy.ts_map.fast_ts_fit:The time used for the parallel TS map computation is 9.980225030581156 minutes\n" + ] + } + ], "source": [ "# Perform the parallel fit\n", "ts_results = ts.parallel_ts_fit(hypothesis_coords = hypothesis_coords, energy_channel = [1,2], spectrum = spectrum, ts_scheme = \"RING\", \n", @@ -1277,7 +1554,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": null, "id": "f967ebe1-a1ef-4b4c-a11b-840f33b0f055", "metadata": {}, "outputs": [], @@ -1288,7 +1565,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": null, "id": "887d08d5-ffd0-4f50-af84-a724ac497826", "metadata": {}, "outputs": [ @@ -1310,7 +1587,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": null, "id": "070a537c-d856-4a32-8cb0-f2e8fa7a9706", "metadata": {}, "outputs": [ @@ -1330,6 +1607,277 @@ "ts.plot_ts(skycoord = coord, containment = 0.9)" ] }, + { + "cell_type": "markdown", + "id": "4557cb37-c7c2-4b43-ad0a-27f3e7cd1780", + "metadata": {}, + "source": [ + "# Example 4 Fit a multi-resolustion map" + ] + }, + { + "cell_type": "markdown", + "id": "53850297-a66a-40c6-9017-dbfe5eb84a0f", + "metadata": {}, + "source": [ + "The TS map we fit above loops over all the pixels of the entire sky, which has already taken a long time. If you want to increase the resolution/order of the TS map, the number of pixels will grow exponentially:\n", + "\n", + "$$\n", + "npix=12\\times4^{order}\n", + "$$\n", + "\n", + "\n", + "For a map of order 3, you will fit the entire sky with 768 pixels. For a map of order 4, you will end up with 3072 pixels to fit! To speed up the fitting, we can fit a multi-resolution map (also called multi-order coverage map, MOC map) instead of the single-resolution map we did before.\n", + "\n", + "The multi-resolution map fitting will reduce the number of pixels to fit by fitting the background region with low resolution while keeping the source region with the details we want. We will use Crab as an example to show you how to fit a multi-resolution map to save your time and computational resources." + ] + }, + { + "cell_type": "markdown", + "id": "0179707d-d5cf-48c2-a214-6540a24f89c8", + "metadata": {}, + "source": [ + "## Data processing" + ] + }, + { + "cell_type": "markdown", + "id": "c9adc073-d40b-459f-8509-69bed195de24", + "metadata": {}, + "source": [ + "The data processing part is the same as the Example 3, so I will put the scripts together to save space.\n", + "\n", + "I assume that the data are download already. If not, please go to Example 3 and run the data downloading cells." + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "8e52d977-6729-469b-b02d-6f6418b17e4f", + "metadata": {}, + "outputs": [], + "source": [ + "data_dir = Path(\"\") # Current directory by default. Modify if you want a different path\n", + "\n", + "crab_data_path = data_dir/\"Crab_galactic_CDS_binned.hdf5\" # the crab file path\n", + "\n", + "albedo_background_path = data_dir/\"Albedo_galactic_CDS_binned.hdf5\" # the background file path\n", + "\n", + "response_path = data_dir/\"psr_gal_DC2.h5\" # the response path\n", + "\n", + "# Read background model\n", + "bkg_model = Histogram.open(albedo_background_path) # please make sure you adjust the path to the files by yourself.\n", + "bkg_model = bkg_model.project(['Em', 'PsiChi', 'Phi'])\n", + "\n", + "# Read the signal and bkg to assemble data = bkg + signal\n", + "signal = Histogram.open(crab_data_path)\n", + "signal = signal.project(['Em', 'PsiChi', 'Phi'])\n", + "\n", + "# Here the background is the same as the background model since they are simulations, thus we know the background very well.\n", + "bkg = Histogram.open(albedo_background_path)\n", + "bkg = bkg.project(['Em', 'PsiChi', 'Phi'])\n", + "\n", + "# Assemble the signal and background\n", + "data = bkg + signal\n", + "\n", + "# clear redundant data from RAM\n", + "del signal\n", + "del bkg\n", + "_ = gc.collect()\n", + "\n", + "\n", + "# define a powerlaw spectrum\n", + "index = -3\n", + "K = 10**-3 / u.cm / u.cm / u.s / u.keV\n", + "piv = 100 * u.keV\n", + "spectrum = Powerlaw()\n", + "spectrum.index.value = index\n", + "spectrum.K.value = K.value\n", + "spectrum.piv.value = piv.value \n", + "spectrum.K.unit = K.unit\n", + "spectrum.piv.unit = piv.unit" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "f41597cf-55d2-4aa6-879b-e10a3b59bc37", + "metadata": {}, + "outputs": [], + "source": [ + "# Here we will us MOCTSMap instead of FastTSMap, the parameters are same\n", + "moc_fit = MOCTSMap(data = data, \n", + " bkg_model = bkg_model, \n", + " response_path = response_path, \n", + " orientation = None, # we don't need orientation since we are using the precomputed galactic reaponse\n", + " cds_frame = \"galactic\")" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "3ea2930d-bdcd-4662-86be-92cb7d53088b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "fitting order = 0\n", + "fitting 12 hypothesis coordinates\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:cosipy.ts_map.fast_ts_fit:You have total 8 CPU cores, using 7 CPU cores for parallel computation.\n", + "INFO:cosipy.ts_map.fast_ts_fit:The time used for the parallel TS map computation is 0.04796493848164876 minutes\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "The top 8 ts values are: [11 1 6 7 2 9 10 5] in the last iteration, splitting these pixels...\n", + "fitting order 1 with 32 hypothesis coordinates\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:cosipy.ts_map.fast_ts_fit:You have total 8 CPU cores, using 7 CPU cores for parallel computation.\n", + "INFO:cosipy.ts_map.fast_ts_fit:The time used for the parallel TS map computation is 0.12099777857462565 minutes\n", + "INFO:cosipy.ts_map.fast_ts_fit:You have total 8 CPU cores, using 7 CPU cores for parallel computation.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "The top 8 ts values are: [ 5 1 30 31 18 17 15 16] in the last iteration, splitting these pixels...\n", + "fitting order 2 with 32 hypothesis coordinates\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:cosipy.ts_map.fast_ts_fit:The time used for the parallel TS map computation is 0.12631478706995647 minutes\n", + "INFO:cosipy.ts_map.fast_ts_fit:You have total 8 CPU cores, using 7 CPU cores for parallel computation.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "The top 8 ts values are: [28 22 23 33 27 25 30 24] in the last iteration, splitting these pixels...\n", + "fitting order 3 with 32 hypothesis coordinates\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:cosipy.ts_map.fast_ts_fit:The time used for the parallel TS map computation is 0.1297250509262085 minutes\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "The top 8 ts values are: [49 32 25 30 39 33 31 41] in the last iteration, splitting these pixels...\n", + "fitting order 4 with 32 hypothesis coordinates\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:cosipy.ts_map.fast_ts_fit:You have total 8 CPU cores, using 7 CPU cores for parallel computation.\n", + "INFO:cosipy.ts_map.fast_ts_fit:The time used for the parallel TS map computation is 0.10716596444447836 minutes\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "CPU times: user 1.06 s, sys: 273 ms, total: 1.33 s\n", + "Wall time: 33 s\n" + ] + } + ], + "source": [ + "%%time\n", + "# here we need to give the order of map to stop fitting and the top 8 likelihood to find the pixels to upscale the resolution\n", + "moc_map = moc_fit.moc_ts_fit(max_moc_order = 4, # this is the maximum order of the final map\n", + " top_number = 8, # In each iterations, only the pixels with top 8 likelihood values will be split in the next iteration\n", + " energy_channel = [2,3], # The energy channel used to perform the fit.\n", + " spectrum = spectrum)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "b5d18ee0-3800-4436-9d30-8ac0403f1a81", + "metadata": {}, + "outputs": [], + "source": [ + "# This the true location of Crab\n", + "coord = SkyCoord(l=184.5551, b = -05.7877, unit = (u.deg, u.deg), frame = \"galactic\")" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "9f7f8b01-a1a0-40ae-8fd1-900b8b05a276", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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WcuTIEcM8+TabLeTFtM3s3btXzz//vGnOI0eOaPfu3Y0L5p5xxhm69tprDWs8WGH23Q33+2H2uQb6fA4fPmx4+iUzMzPsYkuo+SN57oHy+ysYRLJvOBwOZWZm+uyzsLAwYDEPAIC2iCmJAACAZdXV1aaDphMnTmzx/9l2u91avXq1br75Zr3wwgtBF1D1VlxcbBhwaRhUC4fZYGSgRZ+bDsT620dz8jed49mb2bFFOn9rnb/D4TDMXR3o3KPhq6++0gMPPKDZs2eroqLCcrtoXif6CH2kpbzzzjuGKWdGjRrld4C4pXz66ae68847tWDBAtXW1obUtun1s9lsYRfTMjMzZbPZAu7fW7S/m62RP5rn73a7VVxcHPb+AAD4NqJgAAAALHvmmWcMj+8nJyfr2muvbdZ+7Xa70tPT1aNHD/Xs2VNpaWl+7550u91asmSJZs2aFXDeY2+lpaWGWHx8fNjHa9bWLEeDsrKyFs9fUlLid/uT8fwTEhIilr+2tlbHjx8Pe3+hSElJUdeuXZWVlaWMjIyAhbI1a9boZz/7melgsJloXqeT8TtCHzk1+4g3j8djOh1RpBc7TktLU7du3dSrVy+lp6cHLHS9/vrruvPOO1VZWWlp38ePH5fL5fKJxcXFhV1Mczqdhqm2An03ov3dbI38J3PfBACgLeK5OwAAYMn777+vV1991RC//fbblZaWFtK+HA6Hhg8frjPOOEMjR45UVlaW2rVr57NNWVmZvvrqK61cuVIffPCB4e7ndevWaeHChbrrrruC5quqqjLE4uLiQjrmYG3NcjQwG5iKdP7q6mq/20f7/M3ei42NjWj+6urqZg2w+tOnTx+dffbZGj16tLKzs5Wamurzfk1NjbZt26YPPvhAb731luGzPnDggGbOnKlFixYZvuNNRfM6Rfs7Qh85dftIIJs2bdKBAwd8YqmpqTr33HObtd8hQ4bozDPP1Omnn64+ffooMTHR5/3Kykp9/fXXWrVqlVatWmV4oiAnJ0dz5szRr3/966AD/5H+bja0916zI9TvxrfxuxlK/uacv9mxBzp/AADaIgoGAAAgqO3bt+uRRx4xxL/zne/o4osvDmlfU6dO1TnnnBN0DuLk5GSdddZZOuuss7Rr1y7Nnj3bsPjhP//5T51++ukaP358wH01vTtUivyAh1mOBmZPQkQ6f6ApNqJ9/q2RP9QpRoI566yzdMUVVwRdzDs2NlbDhg3TsGHDdP311+vRRx/VRx995LPNtm3b9Mc//lHTp08PuK9oXqdof0foI6deH7HC7OmC73//+2EvZn3RRRdpxowZ6tmzZ8Dt4uPjNWrUKI0aNUo//vGPNWfOHOXk5Phs89FHH+nVV1/V1KlTA+4r0p+NVP/5eD9V0prfDbO2oeaPdMHiZO6bAAC0RUxJBAAAAjp48KDuu+8+wx14PXv21MyZM0Pe3xVXXBHygoXZ2dl65pln1LdvX8N7S5YssTw1kbemc0g3VyhrKjQ3v1nb1sxv5lQ7/2AmTJgQtFjQVGpqqh577DFNmjTJ8N7y5cvDWng2mteprX9H2vr5N1dZWZnWrl1riDdnOqJJkyYFLRY01blzZ/3+97/XmDFjDO+99NJLKi8vD/t4wtX082lL341I9KtT+fwBADgVUDAAAAB+FRYW6pe//KVh0cGOHTtq/vz5rTq9RUJCgh599FHD/MP79u0z3NHdlNk884GmQAjGeyqJQDkamE150Zz8Zm0D3bEb6fM3axvo/Fsjf7h3LLeEGTNmaMCAAT4xl8ulZcuWBWwXzetEH6GPRNq7775rOI7Bgwerd+/erXocUv31nTdvnjIzM33ipaWl+te//hW0bVNm3+9QNL0uJ/N3g74BAEDbQ8EAAACYOnbsmH75y1/q0KFDPvH09HQ9+eST6ty5c6sfU6dOnXTllVca4p988knAdmZzx0d6wCHQIoytkT/Q/PihzhkdjNlgWaDzN8vfnAG3UM+/tTmdTt1yyy2G+KeffhqwXTSvE32EPhJprbHYcSgSEhL0k5/8xBAP1i8j/d00ax/qd6M1+4bZe6353Yz2+QMA0BZRMAAAAAYlJSWaPn26Yc2A1NRUPfnkk+rRo0eUjky64IILDLH//ve/AdukpKQYYmYLWVpl1tYsR2vmb7oYb7D3on3+x48fj1j+mJiYVl/MNZhRo0YpPT3dJ5aXl6eCggK/baJ5negj9JFI2rFjh7755hufWHx8vL773e+22jGYmTBhguFpli+//DLgHPaJiYmGu9xramrCmgpPqn/aqOmAe6Dvxsn43WxLfRMAgLaIggEAAPBRVlamu+66S3v27PGJp6Sk6Mknn4zKdBLesrKylJaW5hMLNAgrSWlpabLbff/ZU1RUpLq6urCOwSxf08HhYO8VFhaGldtf/vbt2/vd3uy9SOdvrfN3u90qKiryiQU692ix2WwaPny4IX748GG/baJ5negj9JFIevvttw2xCRMmRL2wl5iYqH79+vnEampqVFxcHLBd0+tXV1enI0eOhHUMR44cMcyZf6p9N4P9zg01fzTP3263G/5NAQBAW0fBAAAANCovL9ddd92lHTt2+MSTkpL0xBNPmC46HA0ZGRk+f66trQ24cGVMTIyhjcvlCnvAx2zQt0uXLn63N3sv0MBxa+TPz8+PWH6Hw6GOHTuGlD/c8z9y5Ijhzt5A5x5NZgNtgQYmo3md6CP0kUiprq7WqlWrDPFoTkfkren3XArcL6XIfj6hfjc7depkKOYVFBREtJjXVvqmWaEnMzMz4BoKAAC0RRQMAACAJKmiokJ33323tm/f7hNPTEzU/PnzDYu4RlM4c0r37NnTEDtw4EBY+c3ame2/QadOnRQbG+sTKygoUG1tbVj5Dx48GFL+SJ57bW2tYcCpa9euAQdczKaw2r9/f1j5Qz33aDKblzzQ3N/Rvk70EV/0kfB88MEHhgJuVlaWhg4d2mrHEIhZvwz2+8Ps8wn3+2H2+fTq1cvv9jExMYZBc5fLFfagfah9M5LnLhnPPy4uTp06dfK7fST75uHDhw3TT52svz8AAIgmCgYAAEDHjx/XjBkztHXrVp94QkKC5s+fr8GDB0fpyMyZ3Q0aaA5kSerfv78hlpOTE1b+r776ytL+GzidTmVnZ/vEamtrDcUZK1wul7Zt2+YTS09PV4cOHfy26devn+EO1e3btwect9ufbdu2GdoFOndJpsWm1rr20RTq9zTa14k+Qh+JBLPpiC6++OJWyx9MOL8/zD4fs+tsxcnWNx0OR8CnBzt27GiYFig/Pz+sp4+OHDlieDqgb9++hnUlvEXz7yUAANoqCgYAALRxDcWCpv8DHh8fr9/+9rcaMmRIlI7MXGVlpeHu3aSkpKBTCpjNJ7958+aQ87vdbsO1Sk9PD7oQ9LBhwwyxLVu2hJz/m2++UVVVlU/M7Ny8xcfHG+btrqysNEw9ZYXZMQfLP2TIEMOAUE5OTliLhpp9ZsHyR8vevXsNsUBzZUf7OtFH6CPNdfDgQW3atMknFhMTowsvvLBV8lsRar+UIvfdlIyfj8PhCPp71ix/OH3z6NGjhidX+vfvb/rUXrD84Zy/2TGb7dtbr169DJ9PXl6ejh07FnL+cPomAABtEQUDAADasMrKSt17772Gu+7i4+P1+OOP67TTTovSkfn3xRdfGKYpsbK2wogRIwxTnvz3v/9VWVlZSPk3bNigyspKn9iYMWNks9kCtjvjjDMMsffffz+k3JK0du1aS/tuauzYsRHJb9bGbN/ekpOTDU+pHD9+XJ999llIuUtLS7Vx40afWKdOnZSVlRXSflpDaWmpvv76a59YbGxswEHzaF8n+gh9pLlWrFhhWNB33LhxJ82isrt27TIsmNu5c2clJSUFbNenTx9lZmb6xHJzc5WbmxtS/tzcXEPBYujQoUpMTAzYzuz7s379+pCfgAm3b0Szb9psNo0ZM8bSvgJxuVxat26dTyw2NlYjRowIaT8AALQFFAwAAGijqqqqdP/99xvu+GvXrp1+85vfnLR33f397383xKwMeCQkJOiss87yidXU1GjlypUh5V++fLkhdv755wdtN3LkSMMiuFu3bg3pDuba2lrD8cbGxurcc88N2vZ73/ueIbZy5cqQ5oj/5ptvDFO9DB48WF27dg3a9rvf/a4hZnYtA3nnnXcMawCYndfJ4OWXXzbcHT5y5EjFxcUFbBfN60QfoY80h9vt1jvvvGOIn0zTEf3tb38zxKz8/pAi8/m8+eabhpiVvtGjRw/DtEiFhYX6+OOPQ8pvdrxWvh/nnXeeYmJifGLr1q0L6S7/o0ePGgbsO3ToYGnA3uwYQ732H330kYqKinxi48aNC/p0BQAAbREFAwAA2qDq6mo98MADhjtR4+Li9Nhjj520d9y9/vrrhqch7Ha7zjvvPEvtL7vsMkNs6dKllu+g3rJli2GAplu3bho9enTQtg6HQ5dccokh/swzz1jKLUn/+Mc/DPNvf+9731NycnLQtn369DFM/VBcXKxXXnnFcn6zY50yZYqltt///veVkJDgE/voo48sT2tRWlqqpUuX+sQcDocmT55sqX1r2rZtm1599VVD/Dvf+U7QttG+TvQR+ki4NmzYYHr3vpXPvjWsX79eq1evNsTHjx9vqf2ll15qWOdixYoVposYmzlw4IBWrFjhE0tKSrJc0DH7Hv3lL3+x/JTB6tWrtWvXLp/YyJEjAy643CAlJUUTJkzwiblcLv3lL3+xlNvfsU6ePNlwTc2MHTtWnTt39ont3LnT9PM0U1tba3qsZn/fAQAACgYAALQ5tbW1mjVrlj7//HOfeEOx4PTTT2+RvBs2bNCnn34advt//etf+v3vf2+IX3TRRUHnRm8watQow1zRRUVFeuKJJ1RXVxewbWlpqR599FHDdtddd13ABRu9XXnllYYBwU8//VSvv/560Lbbt2/X888/7xNzOBy69tprLeWWpBtuuMEQe+655ywtLPvaa69pw4YNPrGuXbvqggsusJQ7OTlZl19+uU+srq5Ojz32WNDB6Lq6Oj3xxBOGu0PPP/98devWzVJ+qw4ePKjly5eHdFe5t61bt+r+++9XdXW1T7xHjx666KKLgraP9nWij9BHwmW22PHEiRMtDQgHs23bNq1evTrod9CfTz75RHPnzjVMlzRy5EiNGjXK0j569OhhGDSvrKzUI488YujvTVVXV+uRRx4xrK3xgx/8IOh0SA0uvPBCw6D5rl27LBXUDh06pAULFhjiZt93f6699lpDP16+fLk++uijoG3Xr19veCIgKSlJP/jBDyzldjqdpv14wYIFhkWUzTzzzDPavXu3T2zYsGEn7c0RAABEGwUDAADaEJfLpdmzZxsG7mNjY/XrX//a8sBJOHJzc3XPPffopptu0rJlywx3ogZqN3v2bD322GOGKV5SU1N10003hXQc06dPNwx6vPfee3rwwQf9Dsrl5ubq9ttvNywWOWjQIE2cONFy7rS0NP30pz81xBcuXKgXXnjB752iH374oaZNm2aYauSHP/yhevbsaTn/2LFjNW7cOJ9YTU2Npk+frvXr15u2cblc+utf/6qFCxca3ps2bVrQxaa9XX/99YZ5wPPy8nTbbbeZLkQqSWVlZZo1a5bWrFnjE09MTNQtt9xiObdVFRUVmj9/vq6++motWbJEO3futNSuuLhYzz77rH7+85/r6NGjPu/Z7Xbdcccdlq9VtK8TfYQ+Eqpjx44Zniyx2+2aNGlSRPZfWFioOXPm6LrrrtNLL72kvLw8S+3y8/P1u9/9Tvfdd59hXY3Y2Fj94he/COk4br31VsXHx/vENm/erLvuuktHjhzxe+zTp083PCnSuXPnkIpZMTExuuOOOwzxl19+Wb/73e/8Fi22bNmi2267TSUlJT7x8ePHh/Q7v3fv3oaClsfj0axZs/T2228bijEN77/11lt68MEHDe/97Gc/U0pKiuX8l1xyifr37+8TKykp0W233WZ48rBBVVWVnnjiCf3jH//wiTscDk2fPt1ybgAA2hqbx+w3OwAA+Fb6z3/+o4cfftgQT0pKMty5GKoBAwbovvvu8/v+K6+8oqeeeqrxzzabTb169VLfvn2VlZWl1NTUxjsty8rKtH//fm3evFnbt283HYho166dFixYYFgo1IqXXnrJ9K7M+Ph4nX/++crOzlZqaqoKCgr05Zdf6pNPPjHc2ZqUlKRnn3025Lt3PR6P7r33XtOnLTIzM3XBBReoe/fuio2N1aFDh7Ru3Tp98803hm0HDBigP/zhD4ZFaoMpLi7WTTfdZFqwGThwoM455xx16dJFNTU1ysvL07vvvmu67RVXXBHWgMuXX36p6dOnG4o/drtdZ599toYNG6bMzEwVFxdr165dWr16tWGgT5Lmzp1reSqRUOzYscNQhMrMzFT//v2VnZ2tjIwMJSYmKjY2VmVlZSosLNRXX32lzZs3GwarG0ybNs3ynbQNon2d6CP0kVAsXbpUixcv9omNHTtW8+fPj8j+161bp1/96lc+sW7duqlfv37q06eP2rdvr4SEBDmdTpWWlurw4cPavHmzcnJyDNdRqh8wnjt3rqW1LZpavXq15syZY4jHxMRo/PjxGjhwoNLT01VUVKRt27bp/fffNxS6nE6nFi1apKFDh4acf/78+abz96empuqCCy5Qr169lJCQoMOHD+uzzz4zTD0o1RcrlixZEtKAvVT/pMTtt99uuq5Iz5499d3vflddunSRVP+01urVqw1FREk6++yz9eijjwZdCL2pvLw83XzzzaqoqDC8d/rpp2vMmDHq1KmTKioqlJubq1WrVqm0tNSw7e23366pU6eGlBsAgLaEggEAAG3IypUr9eijj7bIvkeMGKFFixb5fb9pwaA5MjMz9eCDDzZrOoFFixZp2bJlYbVNSEjQb3/7W5122mlhtT9+/Ljuuecey3OTN9WrVy8tWrRI7du3D6t9bm6upk+fbrgT3qoJEybo//7v/yxPM9PUmjVrNHfuXNOBvGBsNpvuuOMOXXnllWHlDsasYBCu2NhY3X777briiivCah/t60QfoY9Ydd1112nfvn0+sUgWLMwKBuFKTk7WPffc06xja87vM6fTqdmzZ1ta08SMy+XSnDlztHbt2rDaZ2RkaNGiRZan8muqqKhI06ZNM3zeVg0fPlyPP/644UkNq7788kvde++9pkUyK6666qqQnywBAKCtYUoiAABwynA4HLrwwgv1/PPPN3vu4TvvvFPTp09Xu3btQmrXp08f/fGPfwx7IFSqH0z93e9+p8mTJ4d8h+V5552nxYsXhz0QKklZWVn605/+ZFjgNRin06kf//jHmj17dtgDoVL9YOqTTz6pjh07htQuNTVV8+bNa9WB0HANGzZMS5YsCbtYIEX/OtFH6CNWbNmyxTB4nJaWpnPOOafVjsEKm82ms88+W88991yzCxlXXXWV5s6dq9TU1JDade7cWQsWLAi7WCDVf8fmzJmjG2+8MeTv2PDhw/XMM8+EXSyQ6gsOixcvDvnpDJvNpilTpuiJJ54Iu1gg1Z/D4sWL1bt375DaxcfH6+6776ZYAACABTxhAABAGxLNJwyOHz+ujRs3auPGjcrJydHu3bst3SFot9uVlZWlcePGacqUKYb5vZuroKBAS5cu9Tt1QYO+ffvq8ssv18SJE0OakzyYr7/+WkuXLtXHH3/sd0obh8OhUaNG6eqrr9aYMWMiltvj8WjNmjVatmyZcnJyTKd+kuoHWiZMmKBrrrlGvXr1ilj+qqoqvfHGG1q+fLkOHDjgd7vMzExNmjRJV111lZKTkyOW34zL5VJOTo42bdqkzZs3a8eOHSouLrbUtnPnzho9erSmTJmiAQMGROyYon2d6CP0kUAee+wx/etf//KJRfou7urqam3evFmbNm3Sli1btHPnTpWXlwdtZ7PZ1L17d5155pm67LLLmjVQbqa0tFSvvvqqVqxY4XcNA6l++qRLL71UV1xxheLi4iKWf+/evfr73/+u999/3+/vU5vNpqFDh+rKK680LNrcXBs2bNArr7yiL774wu/TMLGxsTr77LN1zTXXaNCgQRHL7XK5tHLlSr3xxhsB15ppmKpp6tSpIRfgAABoqygYAACAqKirq9OhQ4eUn5+vgoIClZWVNS7amJiYqOTkZHXo0EEDBgxQQkJCix+P2+3Wjh07tGfPHh09elQul0vx8fHq3LmzBgwYoE6dOrVo/qqqKn399dfKy8trHJRNTExU9+7dNWjQoBYfBDx27Ji2bt2qgwcPqqKiQg6HQ2lpaerVq5cGDhyomJiYFs2fl5enHTt2qKCgQNXV1YqNjVVGRoays7OVnZ3dormDOXLkiA4dOqSCggIVFxerqqpKLpdLCQkJSk5OVlpamvr376/09PQWP5ZoXif6CH3kZHL48OHGfllSUqLq6mrV1dU1/v5o3769Bg4c2CoFFI/Ho927d2vXrl0qKipSTU2N4uLi1LFjR/Xr1y/ihYqmamtrtW3bNu3du1fFxcVyu91KTExU165dNWjQoGY9bWNFWVmZtm7dqv379zeuL5CSkqIePXpo8ODBIT+lFKrDhw9r+/btys/PV2VlpZxOp9LT09W7d2/1799fdjsTKwAAEAoKBgAAAAAAAAAAgDUMAAAAAAAAAAAABQMAAAAAAAAAACAKBgAAAAAAAAAAQBQMAAAAAAAAAACAKBgAAAAAAAAAAABRMAAAAAAAAAAAAKJgAAAAAAAAAAAARMEAAAAAAAAAAACIggEAAAAAAAAAABAFAwAAAAAAAAAAIAoGAAAAAAAAAABAFAwAAAAAAAAAAIAoGAAAAAAAAAAAAFEwAAAAAAAAAAAAomAAAAAAAAAAAABEwQAAAAAAAAAAAIiCAQAAAAAAAAAAEAUDAAAAAAAAAAAgCgYAAAAAAAAAAEAUDAAAAAAAAAAAgCgYAAAAAAAAAAAAUTAAAAAAAAAAAACiYAAAAAAAAAAAAETBAAAAAAAAAAAAiIIBAAAAAAAAAAAQBQMAAAAAAAAAACAKBgAAAAAAAAAAQBQMAAAAAAAAAACAKBgAAAAAAAAAAABRMAAAAAAAAAAAAKJgAAAAAAAAAAAARMEAAAAAAAAAAACIggEAAAAAAAAAABAFAwAAAAAAAAAAIAoGAAAAAAAAAABAFAwAAAAAAAAAAIAoGAAAAAAAAAAAAFEwAAAAAAAAAAAAkv4fDpMc/8Em7qEAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# plot the raw ts values\n", + "moc_fit.plot_ts(dpi = 300, skycoord=coord)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "8ed93599-54a1-46fe-86c9-c1a41273ea18", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# plot the 90% confidence region\n", + "# You can see from the plot below, we recover the same 90% containment region as we did in Example 3\n", + "moc_fit.plot_ts(dpi = 300, skycoord=coord, containment = 0.9)" + ] + }, { "cell_type": "markdown", "id": "ebb53a69-63be-48b3-9668-f9dae007267c", @@ -1354,9 +1902,9 @@ ], "metadata": { "kernelspec": { - "display_name": "cosipy_dev", + "display_name": "pr248_rebased", "language": "python", - "name": "cosipy_dev" + "name": "pr248_rebased" }, "language_info": { "codemirror_mode": { @@ -1368,7 +1916,97 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.14" + "version": "3.10.16" + }, + "nbdime-conflicts": { + "local_diff": [ + { + "diff": [ + { + "diff": [ + { + "key": 0, + "op": "addrange", + "valuelist": [ + "cosipy_dev" + ] + }, + { + "key": 0, + "length": 1, + "op": "removerange" + } + ], + "key": "display_name", + "op": "patch" + }, + { + "diff": [ + { + "key": 0, + "op": "addrange", + "valuelist": [ + "cosipy_dev" + ] + }, + { + "key": 0, + "length": 1, + "op": "removerange" + } + ], + "key": "name", + "op": "patch" + } + ], + "key": "kernelspec", + "op": "patch" + } + ], + "remote_diff": [ + { + "diff": [ + { + "diff": [ + { + "key": 0, + "op": "addrange", + "valuelist": [ + "Python 3 (ipykernel)" + ] + }, + { + "key": 0, + "length": 1, + "op": "removerange" + } + ], + "key": "display_name", + "op": "patch" + }, + { + "diff": [ + { + "key": 0, + "op": "addrange", + "valuelist": [ + "python3" + ] + }, + { + "key": 0, + "length": 1, + "op": "removerange" + } + ], + "key": "name", + "op": "patch" + } + ], + "key": "kernelspec", + "op": "patch" + } + ] } }, "nbformat": 4, diff --git a/tests/ts_map/test_moc_ts_fit.py b/tests/ts_map/test_moc_ts_fit.py new file mode 100644 index 00000000..83aa4f52 --- /dev/null +++ b/tests/ts_map/test_moc_ts_fit.py @@ -0,0 +1,128 @@ +import numpy as np +from mhealpy import HealpixMap +from mhealpy.pixelfunc.moc import * +from mhealpy.pixelfunc.single import * +from cosipy import MOCTSMap, test_data, SpacecraftFile +import matplotlib.pyplot as plt +from copy import deepcopy +import astropy.units as u +from astropy.coordinates import SkyCoord +from pathlib import Path +from histpy import Histogram +from threeML import Powerlaw +import os + +def test_upscale_moc_map(): + + test_moc_map_path = test_data.path / "test_MOC_Map.fits" + + moc_map_ts = HealpixMap.read_map(test_moc_map_path) + + mother_uniq = np.array([ 5, 6, 9, 10, 13, 14]) + + new_order = 1 + + m_new, uniq_child_all = MOCTSMap.upscale_moc_map(moc_map_ts, uniq_mother = mother_uniq, new_order = new_order) + + assert np.allclose(uniq_child_all, + np.array([20, 21, 22, 23, 24, 25, 26, 27, 36, 37, 38, 39, 40, 41, 42, 43, 52, 53, 54, 55, 56, 57, 58, 59])) + + assert np.allclose(m_new[:], + np.array([205615, 368891, 368891, 368891, 368891, 356267, 356267, 356267, + 356267, 199132, 172127, 268767, 268767, 268767, 268767, 888147, + 888147, 888147, 888147, 252898, 215294, 346345, 346345, 346345, + 346345, 378671, 378671, 378671, 378671, 234107])) + + + +def test_uniq2skycoord(): + + coord = MOCTSMap.uniq2skycoord(20) + + assert type(coord) is SkyCoord + + assert np.allclose(coord.l.deg, 135.0) + + assert np.allclose(coord.b.deg, 19.47122063449069) + + +def test_uniq2pixidx(): + + test_moc_map_path = test_data.path / "test_MOC_Map.fits" + + moc_map_ts = HealpixMap.read_map(test_moc_map_path) + + uniq = np.array([9, 10]) + + idx = MOCTSMap.uniq2pixidx(moc_map_ts, uniq) + + assert np.allclose(idx, + np.array([5,6])) + + +def test_fill_up_moc_map(): + + test_moc_map_path = test_data.path / "test_MOC_Map.fits" + + moc_map_ts = HealpixMap.read_map(test_moc_map_path) + + ts_fit_results = np.array([np.arange(12), np.repeat(1., moc_map_ts.uniq.size)]).T + + new_map = MOCTSMap.fill_up_moc_map(np.arange(12), moc_map_ts, ts_fit_results) + + assert np.allclose(new_map[:], + np.repeat(1., moc_map_ts.uniq.size)) + + + +def test_moc_ts_fit(): + + src_bkg_path = test_data.path / "ts_map_src_bkg.h5" + bkg_path = test_data.path / "ts_map_bkg.h5" + response_path = test_data.path / "test_full_detector_response.h5" + + orientation_path = test_data.path / "20280301_2s.ori" + ori = SpacecraftFile.parse_from_file(orientation_path) + + src_bkg = Histogram.open(src_bkg_path).project(['Em', 'PsiChi', 'Phi']) + bkg = Histogram.open(bkg_path).project(['Em', 'PsiChi', 'Phi']) + + # define a powerlaw spectrum + index = -3 + K = 10**-3 / u.cm / u.cm / u.s / u.keV + piv = 100 * u.keV + spectrum = Powerlaw() + spectrum.index.value = index + spectrum.K.value = K.value + spectrum.piv.value = piv.value + spectrum.K.unit = K.unit + spectrum.piv.unit = piv.unit + + moc_fit = MOCTSMap(data = src_bkg, + bkg_model = bkg, + response_path = response_path, + orientation = ori, # we don't need orientation since we are using the precomputed galactic reaponse + cds_frame = "local") + + moc_map = moc_fit.moc_ts_fit(max_moc_order = 1, # this is the maximum order of the final map + top_number = 3, # In each iterations, only the pixels with top 8 likelihood values will be split in the next iteration + energy_channel = [2,3], # The energy channel used to perform the fit. + spectrum = spectrum) + + assert np.allclose(moc_map[:], + np.array([51.28650334, 51.30366672, 51.30492629, 51.11675696, 51.15264209, + 51.09963846, 51.18497425, 51.25122002, 51.30205529, 51.28966325, + 51.29978837, 51.29973519, 51.07010273, 51.09357204, 51.29127877, + 51.27676366, 51.147458 , 51.30377498, 51.30232323, 51.18908082, + 51.26570991])) + + coord = SkyCoord(0, 0, unit = "deg", frame = "galactic") + + moc_fit.plot_ts(moc_map = moc_map, skycoord = coord, containment = 0.9, save_plot = True) + + plot_path = Path("ts_map.png") + + assert plot_path.exists() + + if plot_path.exists(): + os.remove(plot_path) \ No newline at end of file