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()
mcmc_new_list.append([gamma, D_dt, cal_h0(z_l, z_s, D_dt)])
pickle.dump([
multi_band_list, kwargs_model, kwargs_result, chain_list,
fix_setting, mcmc_new_list
], open(folder + savename, 'wb'))
#%%Print fitting result:
multi_band_list, kwargs_model, kwargs_result, chain_list, fix_setting, mcmc_new_list = pickle.load(
open(folder + savename, 'rb'))
fixed_lens, fixed_source, fixed_lens_light, fixed_ps, fixed_cosmo = fix_setting
labels_new = [r"$\gamma$", r"$D_{\Delta t}$", "H$_0$"]
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()
for i in range(len(chain_list)):
chain_plot.plot_chain_list(chain_list, i)
plt.show()
truths = [para_s[0][0]['gamma'], TD_distance, 73.907]
plot = corner.corner(
mcmc_new_list,
labels=labels_new,
show_titles=