def plot_fit_individuals(
fit,
should_plot_mask=True,
extract_array_from_mask=False,
zoom_around_mask=False,
positions=None,
should_plot_image=False,
should_plot_noise_map=False,
should_plot_model_image=False,
should_plot_residual_map=False,
should_plot_chi_squared_map=False,
units="kpc",
output_path=None,
output_format="show",
):
mask = lens_plotter_util.get_mask(fit=fit,
should_plot_mask=should_plot_mask)
kpc_per_arcsec = None
if should_plot_image:
plot_galaxy_data_array(
galaxy_data=fit.galaxy_data,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_noise_map:
lens_plotter_util.plot_noise_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_model_image:
lens_plotter_util.plot_model_data(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_residual_map:
lens_plotter_util.plot_residual_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_chi_squared_map:
lens_plotter_util.plot_chi_squared_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
def plot_fit_subplot(
fit,
should_plot_mask=True,
extract_array_from_mask=False,
zoom_around_mask=False,
positions=None,
units="arcsec",
kpc_per_arcsec=None,
figsize=None,
aspect="square",
cmap="jet",
norm="linear",
norm_min=None,
norm_max=None,
linthresh=0.05,
linscale=0.01,
cb_ticksize=10,
cb_fraction=0.047,
cb_pad=0.01,
cb_tick_values=None,
cb_tick_labels=None,
titlesize=10,
xlabelsize=10,
ylabelsize=10,
xyticksize=10,
mask_pointsize=10,
position_pointsize=10.0,
grid_pointsize=1,
output_path=None,
output_filename="galaxy_fit",
output_format="show",
):
rows, columns, figsize_tool = plotter_util.get_subplot_rows_columns_figsize(
number_subplots=4)
mask = lens_plotter_util.get_mask(fit=fit,
should_plot_mask=should_plot_mask)
if figsize is None:
figsize = figsize_tool
plt.figure(figsize=figsize)
plt.subplot(rows, columns, 1)
plot_galaxy_data_array(
galaxy_data=fit.galaxy_data,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
cb_tick_values=cb_tick_values,
cb_tick_labels=cb_tick_labels,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
grid_pointsize=grid_pointsize,
position_pointsize=position_pointsize,
mask_pointsize=mask_pointsize,
output_path=output_path,
output_filename=output_filename,
output_format=output_format,
)
plt.subplot(rows, columns, 2)
lens_plotter_util.plot_model_data(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
cb_tick_values=cb_tick_values,
cb_tick_labels=cb_tick_labels,
title="Model Galaxy",
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
position_pointsize=position_pointsize,
mask_pointsize=mask_pointsize,
output_path=output_path,
output_filename="",
output_format=output_format,
)
plt.subplot(rows, columns, 3)
lens_plotter_util.plot_residual_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
cb_tick_values=cb_tick_values,
cb_tick_labels=cb_tick_labels,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
position_pointsize=position_pointsize,
mask_pointsize=mask_pointsize,
output_path=output_path,
output_filename="",
output_format=output_format,
)
plt.subplot(rows, columns, 4)
lens_plotter_util.plot_chi_squared_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
cb_tick_values=cb_tick_values,
cb_tick_labels=cb_tick_labels,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
position_pointsize=position_pointsize,
mask_pointsize=mask_pointsize,
output_path=output_path,
output_filename="",
output_format=output_format,
)
plotter_util.output_subplot_array(
output_path=output_path,
output_filename=output_filename,
output_format=output_format,
)
plt.close()
def plot_fit_subplot_lens_plane_only(fit,
should_plot_mask=True,
extract_array_from_mask=False,
zoom_around_mask=False,
positions=None,
should_plot_image_plane_pix=False,
units='arcsec',
figsize=None,
aspect='equal',
cmap='jet',
norm='linear',
norm_min=None,
norm_max=None,
linthresh=0.05,
linscale=0.01,
cb_ticksize=10,
cb_fraction=0.047,
cb_pad=0.01,
titlesize=10,
xlabelsize=10,
ylabelsize=10,
xyticksize=10,
mask_pointsize=10,
position_pointsize=10,
grid_pointsize=1,
output_path=None,
output_filename='lens_fit',
output_format='show'):
"""Plot the model datas_ of an analysis, using the *Fitter* class object.
The visualization and output type can be fully customized.
Parameters
-----------
fit : autolens.lens.fitting.Fitter
Class containing fit between the model datas_ and observed lens datas_ (including residual_map, chi_squared_map etc.)
output_path : str
The path where the datas_ is output if the output_type is a file format (e.g. png, fits)
output_filename : str
The name of the file that is output, if the output_type is a file format (e.g. png, fits)
output_format : str
How the datas_ is output. File formats (e.g. png, fits) output the datas_ to harddisk. 'show' displays the datas_ \
in the python interpreter window.
"""
rows, columns, figsize_tool = plotter_util.get_subplot_rows_columns_figsize(
number_subplots=6)
mask = lens_plotter_util.get_mask(fit=fit,
should_plot_mask=should_plot_mask)
if figsize is None:
figsize = figsize_tool
plt.figure(figsize=figsize)
plt.subplot(rows, columns, 1)
kpc_per_arcsec = fit.tracer.image_plane.kpc_per_arcsec_proper
image_plane_pix_grid = lens_plotter_util.get_image_plane_pix_grid(
should_plot_image_plane_pix, fit)
lens_plotter_util.plot_image(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
image_plane_pix_grid=image_plane_pix_grid,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
grid_pointsize=grid_pointsize,
position_pointsize=position_pointsize,
mask_pointsize=mask_pointsize,
output_path=output_path,
output_filename='',
output_format=output_format)
plt.subplot(rows, columns, 2)
lens_plotter_util.plot_noise_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
position_pointsize=position_pointsize,
mask_pointsize=mask_pointsize,
output_path=output_path,
output_filename='',
output_format=output_format)
plt.subplot(rows, columns, 3)
lens_plotter_util.plot_signal_to_noise_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
position_pointsize=position_pointsize,
mask_pointsize=mask_pointsize,
output_path=output_path,
output_filename='',
output_format=output_format)
plt.subplot(rows, columns, 4)
lens_plotter_util.plot_model_data(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
output_path=output_path,
output_filename='',
output_format=output_format)
plt.subplot(rows, columns, 5)
lens_plotter_util.plot_residual_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
output_path=output_path,
output_filename='',
output_format=output_format)
plt.subplot(rows, columns, 6)
lens_plotter_util.plot_chi_squared_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
figsize=figsize,
aspect=aspect,
cmap=cmap,
norm=norm,
norm_min=norm_min,
norm_max=norm_max,
linthresh=linthresh,
linscale=linscale,
cb_ticksize=cb_ticksize,
cb_fraction=cb_fraction,
cb_pad=cb_pad,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
output_path=output_path,
output_filename='',
output_format=output_format)
plotter_util.output_subplot_array(output_path=output_path,
output_filename=output_filename,
output_format=output_format)
plt.close()
def plot_fit_individuals_lens_and_source_planes(
fit,
should_plot_mask=True,
extract_array_from_mask=False,
zoom_around_mask=False,
positions=None,
should_plot_image_plane_pix=False,
should_plot_image=False,
should_plot_noise_map=False,
should_plot_signal_to_noise_map=False,
should_plot_lens_subtracted_image=False,
should_plot_model_image=False,
should_plot_lens_model_image=False,
should_plot_source_model_image=False,
should_plot_source_plane_image=False,
should_plot_residual_map=False,
should_plot_chi_squared_map=False,
units='arcsec',
output_path=None,
output_format='show'):
"""Plot the model datas_ of an analysis, using the *Fitter* class object.
The visualization and output type can be fully customized.
Parameters
-----------
fit : autolens.lens.fitting.Fitter
Class containing fit between the model datas_ and observed lens datas_ (including residual_map, chi_squared_map etc.)
output_path : str
The path where the datas_ is output if the output_type is a file format (e.g. png, fits)
output_format : str
How the datas_ is output. File formats (e.g. png, fits) output the datas_ to harddisk. 'show' displays the datas_ \
in the python interpreter window.
"""
mask = lens_plotter_util.get_mask(fit=fit,
should_plot_mask=should_plot_mask)
kpc_per_arcsec = fit.tracer.image_plane.kpc_per_arcsec_proper
if should_plot_image:
image_plane_pix_grid = lens_plotter_util.get_image_plane_pix_grid(
should_plot_image_plane_pix, fit)
lens_plotter_util.plot_image(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
image_plane_pix_grid=image_plane_pix_grid,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format)
if should_plot_noise_map:
lens_plotter_util.plot_noise_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format)
if should_plot_signal_to_noise_map:
lens_plotter_util.plot_signal_to_noise_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format)
if should_plot_lens_subtracted_image:
lens_plotter_util.plot_lens_subtracted_image(
fit=fit,
mask=mask,
positions=positions,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format)
if should_plot_model_image:
lens_plotter_util.plot_model_data(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format)
if should_plot_lens_model_image:
lens_plotter_util.plot_model_image_of_planes(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
plot_foreground=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_filename='fit_lens_plane_model_image',
output_format=output_format)
if should_plot_source_model_image:
lens_plotter_util.plot_model_image_of_planes(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
plot_source=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_filename='fit_source_plane_model_image',
output_format=output_format)
if should_plot_source_plane_image:
if fit.total_inversions == 0:
plane_plotters.plot_plane_image(plane=fit.tracer.source_plane,
plot_grid=True,
units=units,
figsize=(20, 20),
output_path=output_path,
output_filename='fit_source_plane',
output_format=output_format)
elif fit.total_inversions == 1:
inversion_plotters.plot_reconstructed_pixelization(
inversion=fit.inversion,
should_plot_grid=True,
units=units,
figsize=(20, 20),
output_path=output_path,
output_filename='fit_source_plane',
output_format=output_format)
if should_plot_residual_map:
lens_plotter_util.plot_residual_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format)
if should_plot_chi_squared_map:
lens_plotter_util.plot_chi_squared_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format)
def plot_fit_individuals(
fit,
should_plot_mask=True,
extract_array_from_mask=False,
zoom_around_mask=False,
positions=None,
should_plot_image_plane_pix=False,
should_plot_image=False,
should_plot_noise_map=False,
should_plot_signal_to_noise_map=False,
should_plot_model_image=False,
should_plot_residual_map=False,
should_plot_normalized_residual_map=False,
should_plot_chi_squared_map=False,
should_plot_pixelization_residual_map=False,
should_plot_pixelization_normalized_residual_map=False,
should_plot_pixelization_chi_squared_map=False,
should_plot_pixelization_regularization_weight_map=False,
should_plot_subtracted_images_of_planes=False,
should_plot_model_images_of_planes=False,
should_plot_plane_images_of_planes=False,
units="arcsec",
output_path=None,
output_format="show",
):
"""Plot the model datas_ of an analysis, using the *Fitter* class object.
The visualization and output type can be fully customized.
Parameters
-----------
fit : autolens.lens.fitting.Fitter
Class containing fit between the model datas_ and observed lens datas_ (including residual_map, chi_squared_map etc.)
output_path : str
The path where the datas_ is output if the output_type is a file format (e.g. png, fits)
output_format : str
How the datas_ is output. File formats (e.g. png, fits) output the datas_ to harddisk. 'show' displays the datas_ \
in the python interpreter window.
"""
mask = lens_plotter_util.get_mask(fit=fit, should_plot_mask=should_plot_mask)
image_plane_pix_grid = lens_plotter_util.get_image_plane_pix_grid(
should_plot_image_plane_pix, fit
)
traced_grids = fit.tracer.traced_grids_of_planes_from_grid(grid=fit.grid)
kpc_per_arcsec = fit.tracer.image_plane.kpc_per_arcsec
if should_plot_image:
lens_plotter_util.plot_image(
fit=fit,
mask=mask,
positions=positions,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_noise_map:
lens_plotter_util.plot_noise_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_signal_to_noise_map:
lens_plotter_util.plot_signal_to_noise_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_model_image:
lens_plotter_util.plot_model_data(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_residual_map:
lens_plotter_util.plot_residual_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_normalized_residual_map:
lens_plotter_util.plot_normalized_residual_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_chi_squared_map:
lens_plotter_util.plot_chi_squared_map(
fit=fit,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_pixelization_residual_map:
if fit.total_inversions == 1:
inversion_plotters.plot_pixelization_residual_map(
inversion=fit.inversion,
should_plot_grid=True,
units=units,
figsize=(20, 20),
output_path=output_path,
output_format=output_format,
)
if should_plot_pixelization_normalized_residual_map:
if fit.total_inversions == 1:
inversion_plotters.plot_pixelization_normalized_residual_map(
inversion=fit.inversion,
should_plot_grid=True,
units=units,
figsize=(20, 20),
output_path=output_path,
output_format=output_format,
)
if should_plot_pixelization_chi_squared_map:
if fit.total_inversions == 1:
inversion_plotters.plot_pixelization_chi_squared_map(
inversion=fit.inversion,
should_plot_grid=True,
units=units,
figsize=(20, 20),
output_path=output_path,
output_format=output_format,
)
if should_plot_pixelization_regularization_weight_map:
if fit.total_inversions == 1:
inversion_plotters.plot_pixelization_regularization_weights(
inversion=fit.inversion,
should_plot_grid=True,
units=units,
figsize=(20, 20),
output_path=output_path,
output_format=output_format,
)
if should_plot_subtracted_images_of_planes:
for plane_index in range(fit.tracer.total_planes):
lens_plotter_util.plot_subtracted_image_of_plane(
fit=fit,
plane_index=plane_index,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_model_images_of_planes:
for plane_index in range(fit.tracer.total_planes):
lens_plotter_util.plot_model_image_of_plane(
fit=fit,
plane_index=plane_index,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
output_path=output_path,
output_format=output_format,
)
if should_plot_plane_images_of_planes:
for plane_index in range(fit.tracer.total_planes):
if fit.tracer.planes[plane_index].has_light_profile:
output_filename = "fit_plane_image_of_plane_" + str(plane_index)
plane_plotters.plot_plane_image(
plane=fit.tracer.planes[plane_index],
grid=traced_grids[plane_index],
plot_grid=True,
units=units,
output_path=output_path,
output_filename=output_filename,
output_format=output_format,
)