def test_scale_bar(self):
f, ax = plt.subplots(1, 1, figsize=(4, 4))
plot_util.scale_bar(ax, 3, dist=1, text='1"', flipped=True)
plt.close()
f, ax = plt.subplots(1, 1, figsize=(4, 4))
plot_util.text_description(ax, d=3, text='test', color='w', backgroundcolor='k', flipped=True)
plt.close()
def subtract_from_data_plot(self, ax, text='Subtracted', v_min=None,
v_max=None, point_source_add=False,
source_add=False, lens_light_add=False,
font_size=15
):
model = self.bandmodel.image(self._kwargs_lens_partial, self._kwargs_source_partial, self._kwargs_lens_light_partial,
self._kwargs_ps_partial, unconvolved=False, source_add=source_add,
lens_light_add=lens_light_add, point_source_add=point_source_add)
if v_min is None:
v_min = self._v_min_default
if v_max is None:
v_max = self._v_max_default
im = ax.matshow(np.log10(self._data - model), origin='lower', vmin=v_min, vmax=v_max,
extent=[0, self._frame_size, 0, self._frame_size], cmap=self._cmap)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
plot_util.scale_bar(ax, self._frame_size, dist=1, text='1"', font_size=font_size)
plot_util.text_description(ax, self._frame_size, text=text, color="w",
backgroundcolor='k', font_size=font_size)
plot_util.coordinate_arrows(ax, self._frame_size, self._coords,
arrow_size=self._arrow_size, font_size=font_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(r'log$_{10}$ flux', fontsize=font_size)
return ax
def model_plot(self,
ax,
v_min=None,
v_max=None,
image_names=False,
colorbar_label=r'log$_{10}$ flux',
font_size=15,
text='Reconstructed',
**kwargs):
"""
:param ax:
:param model:
:param v_min:
:param v_max:
:return:
"""
if v_min is None:
v_min = self._v_min_default
if v_max is None:
v_max = self._v_max_default
im = ax.matshow(np.log10(self._model),
origin='lower',
vmin=v_min,
vmax=v_max,
extent=[0, self._frame_size, 0, self._frame_size],
cmap=self._cmap)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
plot_util.scale_bar(ax,
self._frame_size,
dist=1,
text='1"',
font_size=font_size)
plot_util.text_description(ax,
self._frame_size,
text=text,
color="w",
backgroundcolor='k',
font_size=font_size)
if 'no_arrow' not in kwargs or not kwargs['no_arrow']:
plot_util.coordinate_arrows(ax,
self._frame_size,
self._coords,
color='w',
arrow_size=self._arrow_size,
font_size=font_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(colorbar_label, fontsize=font_size)
#plot_line_set(ax, self._coords, self._ra_caustic_list, self._dec_caustic_list, color='b')
#plot_line_set(ax, self._coords, self._ra_crit_list, self._dec_crit_list, color='r')
if image_names is True:
ra_image, dec_image = self.bandmodel.PointSource.image_position(
self._kwargs_ps_partial, self._kwargs_lens_partial)
plot_util.image_position_plot(ax, self._coords, ra_image,
dec_image)
def data_plot(self, ax, v_min=None, v_max=None, text='Observed',
font_size=15, colorbar_label=r'log$_{10}$ flux', **kwargs):
"""
:param ax:
:return:
"""
if v_min is None:
v_min = self._v_min_default
if v_max is None:
v_max = self._v_max_default
im = ax.matshow(np.log10(self._data), origin='lower',
extent=[0, self._frame_size, 0, self._frame_size], cmap=self._cmap, vmin=v_min, vmax=v_max) # , vmin=0, vmax=2
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
plot_util.scale_bar(ax, self._frame_size, dist=1, text='1"', font_size=font_size)
plot_util.text_description(ax, self._frame_size, text=text, color="w",
backgroundcolor='k', font_size=font_size)
if 'no_arrow' not in kwargs or not kwargs['no_arrow']:
plot_util.coordinate_arrows(ax, self._frame_size, self._coords, color='w',
arrow_size=self._arrow_size, font_size=font_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax, orientation='vertical')
cb.set_label(colorbar_label, fontsize=font_size)
return ax
def absolute_residual_plot(self, ax, v_min=-1, v_max=1, font_size=15,
text="Residuals",
colorbar_label=r'(f$_{model}$-f$_{data}$)'):
"""
:param ax:
:param residuals:
:return:
"""
im = ax.matshow(self._model - self._data, vmin=v_min, vmax=v_max,
extent=[0, self._frame_size, 0, self._frame_size], cmap='bwr', origin='lower')
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
plot_util.scale_bar(ax, self._frame_size, dist=1, text='1"', color='k',
font_size=font_size)
plot_util.text_description(ax, self._frame_size, text=text, color="k",
backgroundcolor='w', font_size=font_size)
plot_util.coordinate_arrows(ax, self._frame_size, self._coords,
font_size=font_size,
color='k',
arrow_size=self._arrow_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(colorbar_label, fontsize=font_size)
return ax
def normalized_residual_plot(self, ax, v_min=-6, v_max=6, font_size=15, text="Normalized Residuals",
colorbar_label=r'(f${}_{\rm model}$ - f${}_{\rm data}$)/$\sigma$',
no_arrow=False, **kwargs):
"""
:param ax:
:param v_min:
:param v_max:
:param kwargs: kwargs to send to matplotlib.pyplot.matshow()
:return:
"""
if not 'cmap' in kwargs:
kwargs['cmap'] = 'bwr'
im = ax.matshow(self._norm_residuals, vmin=v_min, vmax=v_max,
extent=[0, self._frame_size, 0, self._frame_size], origin='lower',
**kwargs)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
plot_util.scale_bar(ax, self._frame_size, dist=1, text='1"', color='k',
font_size=font_size)
plot_util.text_description(ax, self._frame_size, text=text, color="k",
backgroundcolor='w', font_size=font_size)
if not no_arrow:
plot_util.coordinate_arrows(ax, self._frame_size, self._coords, color='w',
arrow_size=self._arrow_size, font_size=font_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(colorbar_label,
fontsize=font_size)
return ax
def convergence_plot(self, ax, text='Convergence', v_min=None, v_max=None,
font_size=15, colorbar_label=r'$\log_{10}\ \kappa$',
**kwargs):
"""
:param x_grid:
:param y_grid:
:param kwargs_lens:
:param kwargs_else:
:return:
"""
if not 'cmap' in kwargs:
kwargs['cmap'] = self._cmap
kappa_result = util.array2image(self._lensModel.kappa(self._x_grid, self._y_grid, self._kwargs_lens_partial))
im = ax.matshow(np.log10(kappa_result), origin='lower',
extent=[0, self._frame_size, 0, self._frame_size],
cmap=kwargs['cmap'], vmin=v_min, vmax=v_max)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
plot_util.scale_bar(ax, self._frame_size, dist=1, text='1"', color='w', font_size=font_size)
if 'no_arrow' not in kwargs or not kwargs['no_arrow']:
plot_util.coordinate_arrows(ax, self._frame_size, self._coords, color='w',
arrow_size=self._arrow_size, font_size=font_size)
plot_util.text_description(ax, self._frame_size, text=text,
color="w", backgroundcolor='k', flipped=False,
font_size=font_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(colorbar_label, fontsize=font_size)
return ax
def _plot(self, ax, image, coords, log_scale=True, v_min=None, v_max=None, text='Observed', font_size=15,
colorbar_label=r'log$_{10}$ flux', arrow_size=0.02, cmap=None, dist_scale=1., white_on_black=True,
no_support=False, **kwargs):
"""
:param ax: matplotlib axis instance
:param image: 2d numpy array to be plotted
:param coords: Coordinate() instance with the coordinate system
:param white_on_black: boolean, if True, prints white text on black background, otherwise the opposite
:return: matplotlib axis instance
"""
if white_on_black:
text_k = 'w'
bkg_k = 'k'
else:
text_k = 'k'
bkg_k = 'w'
if cmap is None:
cmap = self._cmap
frame_size = np.max(coords.width)
if log_scale:
if v_min is None:
v_min = self._v_min_default
if v_max is None:
v_max = self._v_max_default
image_plot = np.log10(image)
else:
image_plot = image
im = ax.matshow(image_plot, origin='lower', extent=[0, frame_size, 0, frame_size],
cmap=cmap, vmin=v_min, vmax=v_max) # , vmin=0, vmax=2
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
if not no_support:
text_dist = "{:.1f}".format(dist_scale) + '"'
if 'no_scale_bar' not in kwargs or not kwargs['no_scale_bar']:
plot_util.scale_bar(ax, frame_size, dist=dist_scale, text=text_dist, font_size=font_size, color=text_k)
if 'no_text' not in kwargs or not kwargs['no_text']:
plot_util.text_description(ax, frame_size, text=text, color=text_k, backgroundcolor=bkg_k, font_size=font_size)
if 'no_arrow' not in kwargs or not kwargs['no_arrow']:
plot_util.coordinate_arrows(ax, frame_size, coords, color=text_k, arrow_size=arrow_size, font_size=font_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax, orientation='vertical')
cb.set_label(colorbar_label, fontsize=font_size)
return ax
def error_map_source_plot(self, ax, numPix, deltaPix_source, v_min=None, v_max=None, with_caustics=False,
font_size=15, point_source_position=True):
"""
plots the uncertainty in the surface brightness in the source from the linear inversion by taking the diagonal
elements of the covariance matrix of the inversion of the basis set to be propagated to the source plane.
#TODO illustration of the uncertainties in real space with the full covariance matrix is subtle. The best way is probably to draw realizations from the covariance matrix.
:param ax: matplotlib axis instance
:param numPix: number of pixels in plot per axis
:param deltaPix_source: pixel spacing in the source resolution illustrated in plot
:param v_min: minimum plotting scale of the map
:param v_max: maximum plotting scale of the map
:param with_caustics: plot the caustics on top of the source reconstruction (may take some time)
:param font_size: font size of labels
:param point_source_position: boolean, if True, plots a point at the position of the point source
:return: plot of source surface brightness errors in the reconstruction on the axis instance
"""
x_grid_source, y_grid_source = util.make_grid_transformed(numPix,
self._coords.transform_pix2angle * deltaPix_source / self._deltaPix)
x_center = self._kwargs_source_partial[0]['center_x']
y_center = self._kwargs_source_partial[0]['center_y']
x_grid_source += x_center
y_grid_source += y_center
coords_source = Coordinates(self._coords.transform_pix2angle * deltaPix_source / self._deltaPix, ra_at_xy_0=x_grid_source[0],
dec_at_xy_0=y_grid_source[0])
error_map_source = self.bandmodel.error_map_source(self._kwargs_source_partial, x_grid_source, y_grid_source,
self._cov_param, model_index_select=False)
error_map_source = util.array2image(error_map_source)
d_s = numPix * deltaPix_source
im = ax.matshow(error_map_source, origin='lower', extent=[0, d_s, 0, d_s],
cmap=self._cmap, vmin=v_min, vmax=v_max) # source
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(r'error variance', fontsize=font_size)
if with_caustics:
ra_caustic_list, dec_caustic_list = self._caustics()
plot_util.plot_line_set(ax, coords_source, ra_caustic_list, dec_caustic_list, color='b')
plot_util.scale_bar(ax, d_s, dist=0.1, text='0.1"', color='w', flipped=False, font_size=font_size)
plot_util.coordinate_arrows(ax, d_s, coords_source,
arrow_size=self._arrow_size, color='w', font_size=font_size)
plot_util.text_description(ax, d_s, text="Error map in source", color="w",
backgroundcolor='k', flipped=False, font_size=font_size)
if point_source_position is True:
ra_source, dec_source = self.bandmodel.PointSource.source_position(self._kwargs_ps_partial, self._kwargs_lens_partial)
plot_util.source_position_plot(ax, coords_source, ra_source, dec_source)
return ax
def decomposition_plot(self, ax, text='Reconstructed', v_min=None, v_max=None,
unconvolved=False, point_source_add=False,
font_size=15,
source_add=False, lens_light_add=False, **kwargs):
"""
:param ax:
:param text:
:param v_min:
:param v_max:
:param unconvolved:
:param point_source_add:
:param source_add:
:param lens_light_add:
:param kwargs: kwargs to send matplotlib.pyplot.matshow()
:return:
"""
model = self.bandmodel.image(self._kwargs_lens_partial, self._kwargs_source_partial, self._kwargs_lens_light_partial,
self._kwargs_ps_partial, unconvolved=unconvolved, source_add=source_add,
lens_light_add=lens_light_add, point_source_add=point_source_add)
if v_min is None:
v_min = self._v_min_default
if v_max is None:
v_max = self._v_max_default
if not 'cmap' in kwargs:
kwargs['cmap'] = self._cmap
im = ax.matshow(np.log10(model), origin='lower', vmin=v_min, vmax=v_max,
extent=[0, self._frame_size, 0, self._frame_size], **kwargs)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
plot_util.scale_bar(ax, self._frame_size, dist=1, text='1"', font_size=font_size)
plot_util.text_description(ax, self._frame_size, text=text, color="w", backgroundcolor='k')
plot_util.coordinate_arrows(ax, self._frame_size, self._coords,
arrow_size=self._arrow_size, font_size=font_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(r'log$_{10}$ flux', fontsize=font_size)
return ax
def deflection_plot(self, ax, v_min=None, v_max=None, axis=0,
with_caustics=False, image_name_list=None,
text="Deflection model", font_size=15,
colorbar_label=r'arcsec'):
"""
:param kwargs_lens:
:param kwargs_else:
:return:
"""
alpha1, alpha2 = self._lensModel.alpha(self._x_grid, self._y_grid, self._kwargs_lens_partial)
alpha1 = util.array2image(alpha1)
alpha2 = util.array2image(alpha2)
if axis == 0:
alpha = alpha1
else:
alpha = alpha2
im = ax.matshow(alpha, origin='lower', extent=[0, self._frame_size, 0, self._frame_size],
vmin=v_min, vmax=v_max, cmap=self._cmap, alpha=0.5)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
plot_util.scale_bar(ax, self._frame_size, dist=1, text='1"', color='k', font_size=font_size)
plot_util.coordinate_arrows(ax, self._frame_size, self._coords, color='k',
arrow_size=self._arrow_size, font_size=font_size)
plot_util.text_description(ax, self._frame_size, text=text, color="k",
backgroundcolor='w', font_size=font_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(colorbar_label, fontsize=font_size)
if with_caustics is True:
ra_crit_list, dec_crit_list = self._critical_curves()
ra_caustic_list, dec_caustic_list = self._caustics()
plot_util.plot_line_set(ax, self._coords, ra_caustic_list, dec_caustic_list, color='b')
plot_util.plot_line_set(ax, self._coords, ra_crit_list, dec_crit_list, color='r')
ra_image, dec_image = self.bandmodel.PointSource.image_position(self._kwargs_ps_partial, self._kwargs_lens_partial)
plot_util.image_position_plot(ax, self._coords, ra_image, dec_image, image_name_list=image_name_list)
return ax
def magnification_plot(self, ax, v_min=-10, v_max=10,
image_name_list=None, font_size=15, no_arrow=False,
text="Magnification model",
colorbar_label=r"$\det\ (\mathsf{A}^{-1})$",
**kwargs):
"""
:param ax: matplotib axis instance
:param v_min: minimum range of plotting
:param v_max: maximum range of plotting
:param kwargs: kwargs to send to matplotlib.pyplot.matshow()
:return:
"""
if not 'cmap' in kwargs:
kwargs['cmap'] = self._cmap
if not 'alpha' in kwargs:
kwargs['alpha'] = 0.5
mag_result = util.array2image(self._lensModel.magnification(self._x_grid, self._y_grid, self._kwargs_lens_partial))
im = ax.matshow(mag_result, origin='lower', extent=[0, self._frame_size, 0, self._frame_size],
vmin=v_min, vmax=v_max, **kwargs)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
plot_util.scale_bar(ax, self._frame_size, dist=1, text='1"', color='k', font_size=font_size)
if not no_arrow:
plot_util.coordinate_arrows(ax, self._frame_size, self._coords, color='k', arrow_size=self._arrow_size,
font_size=font_size)
plot_util.text_description(ax, self._frame_size, text=text, color="k",
backgroundcolor='w', font_size=font_size)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(colorbar_label, fontsize=font_size)
ra_image, dec_image = self.bandmodel.PointSource.image_position(self._kwargs_ps_partial, self._kwargs_lens_partial)
plot_util.image_position_plot(ax, self._coords, ra_image, dec_image, color='k', image_name_list=image_name_list)
return ax
def source_plot(self,
ax,
numPix,
deltaPix_source,
center=None,
v_min=None,
v_max=None,
with_caustics=False,
caustic_color='yellow',
font_size=15,
plot_scale='log',
scale_size=0.1,
text="Reconstructed source",
colorbar_label=r'log$_{10}$ flux',
point_source_position=True,
**kwargs):
"""
:param ax:
:param numPix:
:param deltaPix_source:
:param center: [center_x, center_y], if specified, uses this as the center
:param v_min:
:param v_max:
:param caustic_color:
:param font_size:
:param plot_scale: string, log or linear, scale of surface brightness plot
:param kwargs:
:return:
"""
if v_min is None:
v_min = self._v_min_default
if v_max is None:
v_max = self._v_max_default
d_s = numPix * deltaPix_source
source, coords_source = self.source(numPix,
deltaPix_source,
center=center)
if plot_scale == 'log':
source[source < 10**v_min] = 10**(
v_min) # to remove weird shadow in plot
source_scale = np.log10(source)
elif plot_scale == 'linear':
source_scale = source
else:
raise ValueError(
'variable plot_scale needs to be "log" or "linear", not %s.' %
plot_scale)
im = ax.matshow(source_scale,
origin='lower',
extent=[0, d_s, 0, d_s],
cmap=self._cmap,
vmin=v_min,
vmax=v_max) # source
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(colorbar_label, fontsize=font_size)
if with_caustics is True:
ra_caustic_list, dec_caustic_list = self._caustics()
plot_util.plot_line_set(ax,
coords_source,
ra_caustic_list,
dec_caustic_list,
color=caustic_color,
points_only=self._caustic_points_only)
plot_util.plot_line_set(ax,
coords_source,
ra_caustic_list,
dec_caustic_list,
color=caustic_color,
points_only=self._caustic_points_only,
**kwargs.get('kwargs_caustic', {}))
plot_util.scale_bar(ax,
d_s,
dist=scale_size,
text='{:.1f}"'.format(scale_size),
color='w',
flipped=False,
font_size=font_size)
if 'no_arrow' not in kwargs or not kwargs['no_arrow']:
plot_util.coordinate_arrows(ax,
self._frame_size,
self._coords,
color='w',
arrow_size=self._arrow_size,
font_size=font_size)
plot_util.text_description(ax,
d_s,
text=text,
color="w",
backgroundcolor='k',
flipped=False,
font_size=font_size)
if point_source_position is True:
ra_source, dec_source = self._bandmodel.PointSource.source_position(
self._kwargs_ps_partial, self._kwargs_lens_partial)
plot_util.source_position_plot(ax, coords_source, ra_source,
dec_source)
return ax
def error_map_source_plot(self,
ax,
numPix,
deltaPix_source,
v_min=None,
v_max=None,
with_caustics=False,
font_size=15,
point_source_position=True):
x_grid_source, y_grid_source = util.make_grid_transformed(
numPix, self._coords.transform_pix2angle * deltaPix_source /
self._deltaPix)
x_center = self._kwargs_source_partial[0]['center_x']
y_center = self._kwargs_source_partial[0]['center_y']
x_grid_source += x_center
y_grid_source += y_center
coords_source = Coordinates(self._coords.transform_pix2angle *
deltaPix_source / self._deltaPix,
ra_at_xy_0=x_grid_source[0],
dec_at_xy_0=y_grid_source[0])
error_map_source = self.bandmodel.error_map_source(
self._kwargs_source_partial, x_grid_source, y_grid_source,
self._cov_param)
error_map_source = util.array2image(error_map_source)
d_s = numPix * deltaPix_source
im = ax.matshow(error_map_source,
origin='lower',
extent=[0, d_s, 0, d_s],
cmap=self._cmap,
vmin=v_min,
vmax=v_max) # source
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(im, cax=cax)
cb.set_label(r'error variance', fontsize=font_size)
if with_caustics:
ra_caustic_list, dec_caustic_list = self._caustics()
plot_util.plot_line_set(ax,
coords_source,
ra_caustic_list,
dec_caustic_list,
color='b')
plot_util.scale_bar(ax,
d_s,
dist=0.1,
text='0.1"',
color='w',
flipped=False,
font_size=font_size)
plot_util.coordinate_arrows(ax,
d_s,
coords_source,
arrow_size=self._arrow_size,
color='w',
font_size=font_size)
plot_util.text_description(ax,
d_s,
text="Error map in source",
color="w",
backgroundcolor='k',
flipped=False,
font_size=font_size)
if point_source_position is True:
ra_source, dec_source = self.bandmodel.PointSource.source_position(
self._kwargs_ps_partial, self._kwargs_lens_partial)
plot_util.source_position_plot(ax, coords_source, ra_source,
dec_source)
return ax