def plot_signal_to_noise_map(
fit, mask=None, extract_array_from_mask=False, zoom_around_mask=False, positions=None, as_subplot=False,
units='arcsec', kpc_per_arcsec=None, figsize=(7, 7), 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,
title='Fit Signal-to-Noise-Map', titlesize=16, xlabelsize=16, ylabelsize=16, xyticksize=16,
mask_pointsize=10, position_pointsize=10,
output_path=None, output_format='show', output_filename='fit_signal_to_noise_map'):
"""Plot the noise-map of a lens fit.
Set *autolens.datas.array.plotters.array_plotters* for a description of all input parameters not described below.
Parameters
-----------
image : datas.ccd.datas.CCD
The datas-datas, which includes the observed datas, signal_to_noise_map-map, PSF, signal-to-signal_to_noise_map-map, etc.
plot_origin : True
If true, the origin of the datas's coordinate system is plotted as a 'x'.
"""
array_plotters.plot_array(
array=fit.signal_to_noise_map, mask=mask, extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask, positions=positions, as_subplot=as_subplot,
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,
title=title, titlesize=titlesize, xlabelsize=xlabelsize, ylabelsize=ylabelsize, xyticksize=xyticksize,
mask_pointsize=mask_pointsize, position_pointsize=position_pointsize,
output_path=output_path, output_format=output_format, output_filename=output_filename)
def plot_model_data(
fit, mask=None, extract_array_from_mask=False, zoom_around_mask=False, positions=None, as_subplot=False,
units='arcsec', kpc_per_arcsec=None, figsize=(7, 7), 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,
title='Fit Model Image', titlesize=16, xlabelsize=16, ylabelsize=16, xyticksize=16,
mask_pointsize=10, position_pointsize=10,
output_path=None, output_format='show', output_filename='fit_model_image'):
"""Plot the model image of a fit.
Set *autolens.datas.array.plotters.array_plotters* for a description of all input parameters not described below.
Parameters
-----------
fit : datas.fitting.fitting.AbstractFitter
The fit to the datas, which includes a list of every model image, residual_map, chi-squareds, etc.
image_index : int
The index of the datas in the datas-set of which the model image is plotted.
"""
array_plotters.plot_array(
array=fit.model_data, mask=mask, extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask, positions=positions, as_subplot=as_subplot,
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,
title=title, titlesize=titlesize, xlabelsize=xlabelsize, ylabelsize=ylabelsize, xyticksize=xyticksize,
mask_pointsize=mask_pointsize, position_pointsize=position_pointsize,
output_path=output_path, output_format=output_format, output_filename=output_filename)
def plot_image_plane_image(tracer,
mask=None,
extract_array_from_mask=False,
zoom_around_mask=False,
positions=None,
as_subplot=False,
units='arcsec',
figsize=(7, 7),
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,
title='Tracer CCD-Plane CCD',
titlesize=16,
xlabelsize=16,
ylabelsize=16,
xyticksize=16,
mask_pointsize=10,
position_pointsize=10.0,
output_path=None,
output_format='show',
output_filename='tracer_image_plane_image'):
array_plotters.plot_array(
array=tracer.image_plane_image,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
as_subplot=as_subplot,
units=units,
kpc_per_arcsec=tracer.image_plane.kpc_per_arcsec_proper,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
mask_pointsize=mask_pointsize,
position_pointsize=position_pointsize,
output_path=output_path,
output_format=output_format,
output_filename=output_filename)
def plot_reconstructed_image(inversion,
mask=None,
positions=None,
grid=None,
as_subplot=False,
units='arcsec',
kpc_per_arcsec=None,
figsize=(7, 7),
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,
title='Reconstructed CCD',
titlesize=16,
xlabelsize=16,
ylabelsize=16,
xyticksize=16,
output_path=None,
output_format='show',
output_filename='reconstructed_inversion_image'):
array_plotters.plot_array(array=inversion.reconstructed_data,
mask=mask,
positions=positions,
grid=grid,
as_subplot=as_subplot,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
output_path=output_path,
output_format=output_format,
output_filename=output_filename)
def plot_deflections_x(plane,
mask=None,
extract_array_from_mask=False,
zoom_around_mask=False,
as_subplot=False,
units='arcsec',
figsize=(7, 7),
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,
title='Plane Deflections (x)',
titlesize=16,
xlabelsize=16,
ylabelsize=16,
xyticksize=16,
output_path=None,
output_format='show',
output_filename='plane_deflections_x'):
array_plotters.plot_array(array=plane.deflections_x,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
as_subplot=as_subplot,
units=units,
kpc_per_arcsec=plane.kpc_per_arcsec_proper,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
output_path=output_path,
output_format=output_format,
output_filename=output_filename)
def plot_model_image_of_planes(
fit, plot_foreground=False, plot_source=False, mask=None, extract_array_from_mask=False, zoom_around_mask=False,
positions=None, as_subplot=False,
units='arcsec', kpc_per_arcsec=None, figsize=(7, 7), 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,
title='Fit Model Image', titlesize=16, xlabelsize=16, ylabelsize=16, xyticksize=16,
mask_pointsize=10, position_pointsize=10,
output_path=None, output_format='show', output_filename='fit_model_image_of_plane'):
"""Plot the model image of a specific plane of a lens fit.
Set *autolens.datas.array.plotters.array_plotters* for a description of all input parameters not described below.
Parameters
-----------
fit : datas.fitting.fitting.AbstractFitter
The fit to the datas, which includes a list of every model image, residual_map, chi-squareds, etc.
plane_indexes : [int]
The plane from which the model image is generated.
"""
if plot_foreground:
if fit.tracer.total_planes == 2:
model_image = fit.model_image_of_planes[0]
else:
model_image = sum(fit.model_image_of_planes[0:-2])
elif plot_source:
model_image = fit.model_image_of_planes[-1]
else:
raise exc.PlottingException('Both plot_foreground and plot_source were False, one must be True')
array_plotters.plot_array(
array=model_image, mask=mask, extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask, positions=positions, as_subplot=as_subplot,
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,
title=title, titlesize=titlesize, xlabelsize=xlabelsize, ylabelsize=ylabelsize, xyticksize=xyticksize,
mask_pointsize=mask_pointsize, position_pointsize=position_pointsize,
output_path=output_path, output_format=output_format, output_filename=output_filename)
def plot_plane_image(plane,
plot_origin=True,
positions=None,
plot_grid=True,
as_subplot=False,
units='arcsec',
figsize=(7, 7),
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,
title='Plane CCD',
titlesize=16,
xlabelsize=16,
ylabelsize=16,
xyticksize=16,
position_pointsize=10,
grid_pointsize=1,
output_path=None,
output_format='show',
output_filename='plane_image'):
if plot_grid:
grid = plane.grid_stack.regular
else:
grid = None
if plot_origin:
origin = plane.plane_image.origin
else:
origin = None
array_plotters.plot_array(array=plane.plane_image,
origin=origin,
positions=positions,
grid=grid,
as_subplot=as_subplot,
units=units,
kpc_per_arcsec=plane.kpc_per_arcsec_proper,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
position_pointsize=position_pointsize,
grid_pointsize=grid_pointsize,
output_path=output_path,
output_format=output_format,
output_filename=output_filename)
# We have included the .fits data required for this example in the directory
# 'workspace/output/data/example/slacs1430+4105/'.
# First, lets setup the path to the .fits file of the image.
lens_name = 'slacs1430+4105'
path = '{}/../../..'.format(os.path.dirname(os.path.realpath(__file__)))
image_path = path + '/data/example/' + lens_name + '/image.fits'
# Now, lets load this image as a scaled array. A scaled array is an ordinary NumPy array, but it also includes a pixel
# scale which allows us to convert the axes of the image to arc-second coordinates.
image = scaled_array.ScaledSquarePixelArray.from_fits_with_pixel_scale(
file_path=image_path, hdu=0, pixel_scale=0.03)
# We can now use an array plotter to plot the image. Lets first plot it using the default PyAutoLens settings.
array_plotters.plot_array(array=image, title='SLACS1430+4105 Image')
# For a lens like SLACS1430+4105, the lens galaxy's light outshines the background source, making it appear faint.
# we can use a symmetric logarithmic colorbar normalization to better reveal the source galaxy (due to negative values
# in the image, we cannot use a regular logirithmic colorbar normalization).
array_plotters.plot_array(array=image,
title='SLACS1430+4105 Image',
norm='symmetric_log',
linthresh=0.05,
linscale=0.02)
# Alternatively, we can use the default linear colorbar normalization and customize the limits over which the colormap
# spans its dynamic range.
array_plotters.plot_array(array=image,
title='SLACS1430+4105 Image',
norm='linear',
# First, lets setup the path to the .fits file of the residual map.
lens_name = 'slacs1430+4105'
pipeline_name = 'pipeline_lens_light_and_x1_source_parametric'
phase_name = 'phase_3_both'
path = '{}/../../..'.format(os.path.dirname(os.path.realpath(__file__)))
residual_map_path = path+'/output/example/'+lens_name+'/'+pipeline_name+'/'+phase_name+'/image/fits/fit_residual_map.fits'
# Now, lets load this image as a scaled array. A scaled array is an ordinary NumPy array, but it also includes a pixel
# scale which allows us to convert the axes of the image to arc-second coordinates.
residual_map = scaled_array.ScaledSquarePixelArray.from_fits_with_pixel_scale(file_path=residual_map_path, hdu=0,
pixel_scale=0.04)
# We can now use an array plotter to plot the residual map.
array_plotters.plot_array(array=residual_map, title='SLACS1430+4105 Residual Map')
# A useful way to really dig into the residuals is to set upper and lower limits on the normalization of the colorbar.
array_plotters.plot_array(array=residual_map, title='SLACS1430+4105 Residual Map',
norm_min=-0.02, norm_max=0.02)
# Or, alternatively, use a symmetric logarithmic colormap
array_plotters.plot_array(array=residual_map, title='SLACS1430+4105 Residual Map',
norm='symmetric_log', linthresh=0.01, linscale=0.02)
# These tools are equally powerful ways to inspect the chi-squared map of a fit.
chi_squared_map_path = \
path+'/output/example/'+lens_name+'/'+pipeline_name+'/'+phase_name+'/image/fits/fit_chi_squared_map.fits'
chi_squared_map = scaled_array.ScaledSquarePixelArray.from_fits_with_pixel_scale(file_path=chi_squared_map_path, hdu=0,
pixel_scale=0.04)
array_plotters.plot_array(array=chi_squared_map, title='SLACS1430+4105 Chi-Squared Map')
def plot_reconstructed_pixelization(
inversion,
plot_origin=True,
positions=None,
should_plot_centres=False,
should_plot_grid=False,
should_plot_border=False,
image_pixels=None,
source_pixels=None,
as_subplot=False,
units='arcsec',
kpc_per_arcsec=None,
figsize=(7, 7),
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,
title='Reconstructed Pixelization',
titlesize=16,
xlabelsize=16,
ylabelsize=16,
xyticksize=16,
output_path=None,
output_format='show',
output_filename='reconstructed_inversion_image'):
if output_format is 'fits':
return
plotter_util.setup_figure(figsize=figsize, as_subplot=as_subplot)
if isinstance(inversion.mapper, mappers.RectangularMapper):
reconstructed_pixelization = \
inversion.mapper.reconstructed_pixelization_from_solution_vector(inversion.solution_vector)
origin = get_origin(image=reconstructed_pixelization,
plot_origin=plot_origin)
array_plotters.plot_array(array=reconstructed_pixelization,
origin=origin,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
output_filename=output_filename)
mapper_plotters.plot_rectangular_mapper(
mapper=inversion.mapper,
should_plot_centres=should_plot_centres,
should_plot_grid=should_plot_grid,
should_plot_border=should_plot_border,
image_pixels=image_pixels,
source_pixels=source_pixels,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize)
plotter_util.output_figure(array=reconstructed_pixelization,
as_subplot=as_subplot,
output_path=output_path,
output_filename=output_filename,
output_format=output_format)
elif isinstance(inversion.mapper, mappers.VoronoiMapper):
mapper_plotters.plot_voronoi_mapper(
mapper=inversion.mapper,
solution_vector=inversion.solution_vector,
should_plot_centres=should_plot_centres,
should_plot_grid=should_plot_grid,
should_plot_border=should_plot_border,
image_pixels=image_pixels,
source_pixels=source_pixels,
as_subplot=True,
units=units,
kpc_per_arcsec=kpc_per_arcsec,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize)
plotter_util.output_figure(array=None,
as_subplot=as_subplot,
output_path=output_path,
output_filename=output_filename,
output_format=output_format)
plotter_util.close_figure(as_subplot=as_subplot)
def plot_surface_density(mass_profile,
grid,
mask=None,
extract_array_from_mask=False,
zoom_around_mask=False,
positions=None,
as_subplot=False,
units='arcsec',
kpc_per_arcsec=None,
figsize=(7, 7),
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,
title='Surface Density',
titlesize=16,
xlabelsize=16,
ylabelsize=16,
xyticksize=16,
mask_pointsize=10,
position_pointsize=10.0,
grid_pointsize=1,
output_path=None,
output_format='show',
output_filename='surface_density'):
"""Plot the surface density of a mass profile, on a regular grid of (y,x) coordinates.
Set *autolens.hyper.array.plotters.array_plotters* for a description of all innput parameters not described below.
Parameters
-----------
mass_profile : model.profiles.mass_profiles.MassProfile
The mass profile whose surface density is plotted.
grid : ndarray or hyper.array.grid_stacks.RegularGrid
The (y,x) coordinates of the grid, in an array of shape (total_coordinates, 2)
"""
surface_density = mass_profile.surface_density_from_grid(grid=grid)
surface_density = grid.scaled_array_from_array_1d(surface_density)
array_plotters.plot_array(array=surface_density,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
as_subplot=as_subplot,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
mask_pointsize=mask_pointsize,
position_pointsize=position_pointsize,
grid_pointsize=grid_pointsize,
output_path=output_path,
output_format=output_format,
output_filename=output_filename)
def plot_intensities(galaxy,
grid,
mask=None,
extract_array_from_mask=False,
zoom_around_mask=False,
positions=None,
as_subplot=False,
units='arcsec',
kpc_per_arcsec=None,
figsize=(7, 7),
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,
title='Galaxy Intensities',
titlesize=16,
xlabelsize=16,
ylabelsize=16,
xyticksize=16,
mask_pointsize=10,
position_pointsize=10.0,
grid_pointsize=1,
output_path=None,
output_format='show',
output_filename='galaxy_intensities'):
"""Plot the intensities (e.g. the datas) of a galaxy, on a regular grid of (y,x) coordinates.
Set *autolens.datas.array.plotters.array_plotters* for a description of all innput parameters not described below.
Parameters
-----------
galaxy : model.galaxy.galaxy.Galaxy
The galaxy whose intensities are plotted.
grid : ndarray or datas.array.grid_stacks.RegularGrid
The (y,x) coordinates of the grid, in an array of shape (total_coordinates, 2)
"""
intensities = galaxy.intensities_from_grid(grid=grid)
intensities = grid.scaled_array_from_array_1d(intensities)
array_plotters.plot_array(array=intensities,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
as_subplot=as_subplot,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
mask_pointsize=mask_pointsize,
position_pointsize=position_pointsize,
grid_pointsize=grid_pointsize,
output_path=output_path,
output_format=output_format,
output_filename=output_filename)
def plot_noise_map(noise_map,
plot_origin=True,
mask=None,
extract_array_from_mask=False,
zoom_around_mask=False,
as_subplot=False,
units='arcsec',
kpc_per_arcsec=None,
figsize=(7, 7),
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,
title='Noise-Map',
titlesize=16,
xlabelsize=16,
ylabelsize=16,
xyticksize=16,
mask_pointsize=10,
output_path=None,
output_format='show',
output_filename='noise_map'):
"""Plot the noise_map-map of the ccd data.
Set *autolens.data.array.plotters.array_plotters* for a description of all innput parameters not described below.
Parameters
-----------
noise_map : ScaledSquarePixelArray
The noise map of the data.
plot_origin : True
If true, the origin of the data's coordinate system is plotted as a 'x'.
"""
origin = get_origin(array=noise_map, plot_origin=plot_origin)
array_plotters.plot_array(array=noise_map,
origin=origin,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
as_subplot=as_subplot,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
mask_pointsize=mask_pointsize,
output_path=output_path,
output_format=output_format,
output_filename=output_filename)
def plot_image(image,
plot_origin=True,
mask=None,
extract_array_from_mask=False,
zoom_around_mask=False,
should_plot_border=False,
positions=None,
as_subplot=False,
units='arcsec',
kpc_per_arcsec=None,
figsize=(7, 7),
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,
title='Image',
titlesize=16,
xlabelsize=16,
ylabelsize=16,
xyticksize=16,
mask_pointsize=10,
position_pointsize=30,
grid_pointsize=1,
output_path=None,
output_format='show',
output_filename='image'):
"""Plot the observed image of the ccd data.
Set *autolens.data.array.plotters.array_plotters* for a description of all innput parameters not described below.
Parameters
-----------
image : ScaledSquarePixelArray
The image of the data.
plot_origin : True
If true, the origin of the data's coordinate system is plotted as a 'x'.
image_plane_pix_grid : ndarray or data.array.grid_stacks.PixGrid
If an adaptive pixelization whose pixels are formed by tracing pixels from the data, this plots those pixels \
over the immage.
"""
origin = get_origin(array=image, plot_origin=plot_origin)
array_plotters.plot_array(array=image,
origin=origin,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
should_plot_border=should_plot_border,
positions=positions,
as_subplot=as_subplot,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
mask_pointsize=mask_pointsize,
position_pointsize=position_pointsize,
grid_pointsize=grid_pointsize,
output_path=output_path,
output_format=output_format,
output_filename=output_filename)
# scale which allows us to convert the axes of the array to arc-second coordinates.
image = scaled_array.ScaledSquarePixelArray.from_fits_with_pixel_scale(
file_path=file_path, hdu=0, pixel_scale=0.03)
# We can now use an array plotter to plot the array. We customize the plot as follows:
# 1) We make the array's figure size bigger than the default size (7,7).
# 2) Because the figure is bigger, we increase the size of the title, x and y labels / ticks from their default size of
# 16 to 24.
# 3) For the same reason, we increase the size of the colorbar ticks from the default value 10 to 20.
array_plotters.plot_array(array=image,
figsize=(12, 12),
title='SLACS1430+4105 Image',
titlesize=24,
xlabelsize=24,
ylabelsize=24,
xyticksize=24,
cb_ticksize=20)
# The colormap of the array can be changed to any of the standard matplotlib colormaps.
array_plotters.plot_array(array=image,
title='SLACS1430+4105 Image',
cmap='spring')
# We can change the x / y axis units from arc-seconds to kiloparsec, by inputting a kiloparsec to arcsecond conversion
# factor (for SLACS1430+4105, the lens galaxy is at redshift 0.285, corresponding to the conversion factor below).
array_plotters.plot_array(array=image,
title='SLACS1430+4105 Image',
units='kpc',
kpc_per_arcsec=4.335)
def plot_galaxy_data_array(galaxy_data,
mask=None,
extract_array_from_mask=False,
zoom_around_mask=False,
positions=None,
as_subplot=False,
units='arcsec',
kpc_per_arcsec=None,
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=10.0,
grid_pointsize=1,
output_path=None,
output_filename='galaxy_data',
output_format='show'):
if galaxy_data.use_intensities:
title = 'Galaxy Data Intensities'
elif galaxy_data.use_surface_density:
title = 'Galaxy Data Surface Density'
elif galaxy_data.use_potential:
title = 'Galaxy Data Potential'
elif galaxy_data.use_deflections_y:
title = 'Galaxy Data Deflections (y)'
elif galaxy_data.use_deflections_x:
title = 'Galaxy Data Deflections (x)'
else:
raise exc.PlottingException(
'The galaxy data array does not have a True use_profile_type')
array_plotters.plot_array(array=galaxy_data.image,
mask=mask,
extract_array_from_mask=extract_array_from_mask,
zoom_around_mask=zoom_around_mask,
positions=positions,
as_subplot=as_subplot,
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,
title=title,
titlesize=titlesize,
xlabelsize=xlabelsize,
ylabelsize=ylabelsize,
xyticksize=xyticksize,
mask_pointsize=mask_pointsize,
position_pointsize=position_pointsize,
grid_pointsize=grid_pointsize,
output_path=output_path,
output_format=output_format,
output_filename=output_filename)
