def test__1d__via_light_obj_from(lp_0):
visuals_1d = aplt.Visuals1D()
include_1d = aplt.Include1D(half_light_radius=True)
get_visuals = GetVisuals1D(include=include_1d, visuals=visuals_1d)
visuals_1d_via = get_visuals.via_light_obj_from(light_obj=lp_0)
assert visuals_1d_via.half_light_radius == lp_0.half_light_radius
include_1d = aplt.Include1D(half_light_radius=False)
get_visuals = GetVisuals1D(include=include_1d, visuals=visuals_1d)
visuals_1d_via = get_visuals.via_light_obj_from(light_obj=lp_0)
assert visuals_1d_via.half_light_radius is None
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 test__1d__via_mass_obj_from(mp_0, grid_2d_7x7):
visuals_1d = aplt.Visuals1D()
include_1d = aplt.Include1D(einstein_radius=True)
get_visuals = GetVisuals1D(include=include_1d, visuals=visuals_1d)
visuals_1d_via = get_visuals.via_mass_obj_from(mass_obj=mp_0,
grid=grid_2d_7x7)
assert visuals_1d_via.einstein_radius == mp_0.einstein_radius_from(
grid=grid_2d_7x7)
include_1d = aplt.Include1D(einstein_radius=False)
get_visuals = GetVisuals1D(include=include_1d, visuals=visuals_1d)
visuals_1d_via = get_visuals.via_mass_obj_from(mass_obj=mp_0,
grid=grid_2d_7x7)
assert visuals_1d_via.einstein_radius is None
def test__1d__via_light_obj_list_from(lp_0):
visuals_1d = aplt.Visuals1D()
include_1d = aplt.Include1D(half_light_radius=True)
get_visuals = GetVisuals1D(include=include_1d, visuals=visuals_1d)
visuals_1d_via = get_visuals.via_light_obj_list_from(
light_obj_list=[lp_0, lp_0], low_limit=1.0)
assert visuals_1d_via.half_light_radius == lp_0.half_light_radius
assert visuals_1d_via.half_light_radius_errors[0][
0] == lp_0.half_light_radius
include_1d = aplt.Include1D(half_light_radius=False)
get_visuals = GetVisuals1D(include=include_1d, visuals=visuals_1d)
visuals_1d_via = get_visuals.via_light_obj_list_from(
light_obj_list=[lp_0, lp_0], low_limit=1.0)
assert visuals_1d_via.half_light_radius is None
assert visuals_1d_via.half_light_radius_errors is None
def test__1d__via_mass_obj_list_from(mp_0, grid_2d_7x7):
visuals_1d = aplt.Visuals1D()
include_1d = aplt.Include1D(einstein_radius=True)
get_visuals = GetVisuals1D(include=include_1d, visuals=visuals_1d)
visuals_1d_via = get_visuals.via_mass_obj_list_from(
mass_obj_list=[mp_0, mp_0], grid=grid_2d_7x7, low_limit=1.0)
assert visuals_1d_via.einstein_radius == mp_0.einstein_radius_from(
grid=grid_2d_7x7)
assert visuals_1d_via.einstein_radius_errors[0][
0] == mp_0.einstein_radius_from(grid=grid_2d_7x7)
include_1d = aplt.Include1D(einstein_radius=False)
get_visuals = GetVisuals1D(include=include_1d, visuals=visuals_1d)
visuals_1d_via = get_visuals.via_mass_obj_list_from(
mass_obj_list=[mp_0, mp_0], grid=grid_2d_7x7, low_limit=1.0)
assert visuals_1d_via.einstein_radius is None
assert visuals_1d_via.einstein_radius_errors is None
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,
)