def test__figures_1d__all_are_output(gal_x1_lp_x1_mp, sub_grid_2d_7x7,
mask_2d_7x7, include_1d_all, plot_path,
plot_patch):
galaxy_plotter = aplt.GalaxyPlotter(
galaxy=gal_x1_lp_x1_mp,
grid=sub_grid_2d_7x7,
include_1d=include_1d_all,
mat_plot_1d=aplt.MatPlot1D(
output=aplt.Output(plot_path, format="png")),
)
galaxy_plotter.figures_1d(image=True, convergence=True, potential=True)
assert path.join(plot_path, "image_1d.png") in plot_patch.paths
assert path.join(plot_path, "convergence_1d.png") in plot_patch.paths
assert path.join(plot_path, "potential_1d.png") in plot_patch.paths
plot_patch.paths = []
galaxy_plotter = aplt.GalaxyPDFPlotter(
galaxy_pdf_list=[gal_x1_lp_x1_mp, gal_x1_lp_x1_mp, gal_x1_lp_x1_mp],
grid=sub_grid_2d_7x7,
include_1d=include_1d_all,
mat_plot_1d=aplt.MatPlot1D(
output=aplt.Output(plot_path, format="png")),
)
galaxy_plotter.figures_1d(image=True, convergence=True, potential=True)
assert path.join(plot_path, "image_1d.png") in plot_patch.paths
assert path.join(plot_path, "convergence_1d.png") in plot_patch.paths
assert path.join(plot_path, "potential_1d.png") in plot_patch.paths
def test__figures_1d__all_are_output(
mp_0,
sub_grid_2d_7x7,
grid_2d_irregular_7x7_list,
include_1d_all,
plot_path,
plot_patch,
):
mat_plot_1d = aplt.MatPlot1D(
half_light_radius_axvline=aplt.HalfLightRadiusAXVLine(color="r"),
einstein_radius_axvline=aplt.EinsteinRadiusAXVLine(color="r"),
output=aplt.Output(plot_path, format="png"),
)
mass_profile_plotter = aplt.MassProfilePlotter(
mass_profile=mp_0,
grid=sub_grid_2d_7x7,
include_1d=include_1d_all,
mat_plot_1d=mat_plot_1d,
)
mass_profile_plotter.figures_1d(convergence=True, potential=True)
assert path.join(plot_path, "convergence_1d.png") in plot_patch.paths
assert path.join(plot_path, "potential_1d.png") in plot_patch.paths
def test__figures_1d__all_are_output(
lp_0,
sub_grid_2d_7x7,
grid_2d_irregular_7x7_list,
include_1d_all,
plot_path,
plot_patch,
):
mat_plot_1d = aplt.MatPlot1D(
half_light_radius_axvline=aplt.HalfLightRadiusAXVLine(color="r"),
einstein_radius_axvline=aplt.EinsteinRadiusAXVLine(color="r"),
output=aplt.Output(plot_path, format="png"),
)
light_profile_plotter = aplt.LightProfilePlotter(
light_profile=lp_0,
grid=sub_grid_2d_7x7,
include_1d=include_1d_all,
mat_plot_1d=mat_plot_1d,
)
light_profile_plotter.figures_1d(image=True)
assert path.join(plot_path, "image_1d.png") in plot_patch.paths
def test__figures_1d_decomposed__all_are_output(gal_x1_lp_x1_mp,
sub_grid_2d_7x7, mask_2d_7x7,
include_1d_all, plot_path,
plot_patch):
galaxy_plotter = aplt.GalaxyPlotter(
galaxy=gal_x1_lp_x1_mp,
grid=sub_grid_2d_7x7,
include_1d=include_1d_all,
mat_plot_1d=aplt.MatPlot1D(
output=aplt.Output(plot_path, format="png")),
)
galaxy_plotter.figures_1d_decomposed(convergence=True)
# assert path.join(plot_path, "image_1d.png") in plot_patch.paths
assert path.join(plot_path,
"convergence_1d_decomposed.png") in plot_patch.paths
def __init__(
self,
fit: FitPointDataset,
mat_plot_1d: aplt.MatPlot1D = aplt.MatPlot1D(),
visuals_1d: aplt.Visuals1D = aplt.Visuals1D(),
include_1d: aplt.Include1D = aplt.Include1D(),
mat_plot_2d: aplt.MatPlot2D = aplt.MatPlot2D(),
visuals_2d: aplt.Visuals2D = aplt.Visuals2D(),
include_2d: aplt.Include2D = aplt.Include2D(),
):
super().__init__(
mat_plot_1d=mat_plot_1d,
visuals_1d=visuals_1d,
include_1d=include_1d,
mat_plot_2d=mat_plot_2d,
include_2d=include_2d,
visuals_2d=visuals_2d,
)
self.fit = fit
def __init__(
self,
point_dict: PointDict,
mat_plot_1d: aplt.MatPlot1D = aplt.MatPlot1D(),
visuals_1d: aplt.Visuals1D = aplt.Visuals1D(),
include_1d: aplt.Include1D = aplt.Include1D(),
mat_plot_2d: aplt.MatPlot2D = aplt.MatPlot2D(),
visuals_2d: aplt.Visuals2D = aplt.Visuals2D(),
include_2d: aplt.Include2D = aplt.Include2D(),
):
super().__init__(
mat_plot_1d=mat_plot_1d,
visuals_1d=visuals_1d,
include_1d=include_1d,
mat_plot_2d=mat_plot_2d,
include_2d=include_2d,
visuals_2d=visuals_2d,
)
self.point_dict = point_dict
def __init__(
self,
fit: FitInterferometer,
mat_plot_1d: aplt.MatPlot1D = aplt.MatPlot1D(),
visuals_1d: aplt.Visuals1D = aplt.Visuals1D(),
include_1d: aplt.Include1D = aplt.Include1D(),
mat_plot_2d: aplt.MatPlot2D = aplt.MatPlot2D(),
visuals_2d: aplt.Visuals2D = aplt.Visuals2D(),
include_2d: aplt.Include2D = aplt.Include2D(),
):
"""
Plots the attributes of `FitInterferometer` objects using the matplotlib method `imshow()` and many
other matplotlib functions which customize the plot's appearance.
The `mat_plot_1d` and `mat_plot_2d` attributes wrap matplotlib function calls to make the figure. By default,
the settings passed to every matplotlib function called are those specified in
the `config/visualize/mat_wrap/*.ini` files, but a user can manually input values into `MatPlot2d` to
customize the figure's appearance.
Overlaid on the figure are visuals, contained in the `Visuals1D` and `Visuals2D` objects. Attributes may be
extracted from the `FitInterferometer` and plotted via the visuals object, if the corresponding entry is `True` in
the `Include1D` or `Include2D` object or the `config/visualize/include.ini` file.
Parameters
----------
fit
The fit to an interferometer dataset the plotter plots.
mat_plot_1d
Contains objects which wrap the matplotlib function calls that make 1D plots.
visuals_1d
Contains 1D visuals that can be overlaid on 1D plots.
include_1d
Specifies which attributes of the `FitInterferometer` are extracted and plotted as visuals for 1D plots.
mat_plot_2d
Contains objects which wrap the matplotlib function calls that make 2D plots.
visuals_2d
Contains 2D visuals that can be overlaid on 2D plots.
include_2d
Specifies which attributes of the `FitInterferometer` are extracted and plotted as visuals for 2D plots.
"""
super().__init__(
mat_plot_1d=mat_plot_1d,
include_1d=include_1d,
visuals_1d=visuals_1d,
mat_plot_2d=mat_plot_2d,
include_2d=include_2d,
visuals_2d=visuals_2d,
)
self.fit = fit
self._fit_interferometer_meta_plotter = FitInterferometerPlotterMeta(
fit=self.fit,
get_visuals_2d_real_space=self.get_visuals_2d_real_space,
mat_plot_1d=self.mat_plot_1d,
include_1d=self.include_1d,
visuals_1d=self.visuals_1d,
mat_plot_2d=self.mat_plot_2d,
include_2d=self.include_2d,
visuals_2d=self.visuals_2d,
)
self.subplot = self._fit_interferometer_meta_plotter.subplot
self.subplot_fit_interferometer = (
self._fit_interferometer_meta_plotter.subplot_fit_interferometer)
self.subplot_fit_dirty_images = (
self._fit_interferometer_meta_plotter.subplot_fit_dirty_images)
def __init__(
self,
tracer: Tracer,
grid: aa.type.Grid2DLike,
mat_plot_1d: aplt.MatPlot1D = aplt.MatPlot1D(),
visuals_1d: aplt.Visuals1D = aplt.Visuals1D(),
include_1d: aplt.Include1D = aplt.Include1D(),
mat_plot_2d: aplt.MatPlot2D = aplt.MatPlot2D(),
visuals_2d: aplt.Visuals2D = aplt.Visuals2D(),
include_2d: aplt.Include2D = aplt.Include2D(),
):
"""
Plots the attributes of `Tracer` objects using the matplotlib methods `plot()` and `imshow()` and many
other matplotlib functions which customize the plot's appearance.
The `mat_plot_1d` and `mat_plot_2d` attributes wrap matplotlib function calls to make the figure. By default,
the settings passed to every matplotlib function called are those specified in
the `config/visualize/mat_wrap/*.ini` files, but a user can manually input values into `MatPlot2D` to
customize the figure's appearance.
Overlaid on the figure are visuals, contained in the `Visuals1D` and `Visuals2D` objects. Attributes may be
extracted from the `MassProfile` and plotted via the visuals object, if the corresponding entry is `True` in
the `Include1D` or `Include2D` object or the `config/visualize/include.ini` file.
Parameters
----------
tracer
The tracer the plotter plots.
grid
The 2D (y,x) grid of coordinates used to evaluate the tracer's light and mass quantities that are plotted.
mat_plot_1d
Contains objects which wrap the matplotlib function calls that make 1D plots.
visuals_1d
Contains 1D visuals that can be overlaid on 1D plots.
include_1d
Specifies which attributes of the `MassProfile` are extracted and plotted as visuals for 1D plots.
mat_plot_2d
Contains objects which wrap the matplotlib function calls that make 2D plots.
visuals_2d
Contains 2D visuals that can be overlaid on 2D plots.
include_2d
Specifies which attributes of the `MassProfile` are extracted and plotted as visuals for 2D plots.
"""
super().__init__(
mat_plot_1d=mat_plot_1d,
visuals_1d=visuals_1d,
include_1d=include_1d,
mat_plot_2d=mat_plot_2d,
include_2d=include_2d,
visuals_2d=visuals_2d,
)
self.tracer = tracer
self.grid = grid
self._mass_plotter = MassPlotter(
mass_obj=self.tracer,
grid=self.grid,
get_visuals_2d=self.get_visuals_2d,
mat_plot_2d=self.mat_plot_2d,
include_2d=self.include_2d,
visuals_2d=self.visuals_2d,
)