def test_lensModelPlot(self): multi_band_list = [[ self.kwargs_data, self.kwargs_psf, self.kwargs_numerics ]] lensPlot = ModelPlot(multi_band_list, self.kwargs_model, self.kwargs_params, arrow_size=0.02, cmap_string="gist_heat", multi_band_type='single-band') lensPlot.plot_main(with_caustics=True) plt.close() cmap = plt.get_cmap('gist_heat') lensPlot = ModelPlot(multi_band_list, self.kwargs_model, self.kwargs_params, arrow_size=0.02, cmap_string=cmap) lensPlot.plot_separate() plt.close() lensPlot.plot_subtract_from_data_all() plt.close() f, ax = plt.subplots(1, 1, figsize=(4, 4)) lensPlot.deflection_plot(ax=ax, with_caustics=True, axis=1) plt.close() f, ax = plt.subplots(1, 1, figsize=(4, 4)) lensPlot.subtract_from_data_plot(ax=ax) plt.close() f, ax = plt.subplots(1, 1, figsize=(4, 4)) lensPlot.deflection_plot(ax=ax, with_caustics=True, axis=0) plt.close() numPix = 100 deltaPix_source = 0.01 f, ax = plt.subplots(1, 1, figsize=(4, 4)) lensPlot.error_map_source_plot(ax=ax, numPix=numPix, deltaPix_source=deltaPix_source, with_caustics=True) plt.close() f, ax = plt.subplots(1, 1, figsize=(4, 4)) lensPlot.absolute_residual_plot(ax=ax) plt.close() f, ax = plt.subplots(1, 1, figsize=(4, 4)) lensPlot.plot_extinction_map(ax=ax) plt.close()
], open(folder + savename, 'wb')) #Print fitting result: multi_band_list, kwargs_model, kwargs_result, chain_list, fix_setting, _ = pickle.load( open(folder + savename, 'rb')) fixed_lens, fixed_source, fixed_lens_light, fixed_ps, fixed_cosmo = fix_setting labels_new = [r"$\gamma$", r"$e1$", r"$e2$"] modelPlot = ModelPlot(multi_band_list, kwargs_model, kwargs_result, arrow_size=0.02, cmap_string="gist_heat") f, axes = modelPlot.plot_main() f.show() f, axes = modelPlot.plot_separate() f.show() f, axes = modelPlot.plot_subtract_from_data_all() f.show() sampler_type, samples_mcmc, param_mcmc, dist_mcmc = chain_list[-1] # for i in range(len(chain_list)): # chain_plot.plot_chain_list(chain_list, i) param = Param(kwargs_model, fixed_lens, fixed_source, fixed_lens_light, kwargs_lens_init=kwargs_result['kwargs_lens'], **kwargs_constraints) mcmc_new_list = [] steps = len(samples_mcmc) for i in range(steps):