def __init__(
self,
dataset_line: DatasetLine,
mat_plot_1d: aplt.MatPlot1D = aplt.MatPlot1D(),
visuals_1d: aplt.Visuals1D = aplt.Visuals1D(),
include_1d: aplt.Include1D = aplt.Include1D(),
):
"""
Plots the attributes of `DatasetLine` objects using the matplotlib method `line()` and many other matplotlib
functions which customize the plot's appearance.
The `mat_plot_1d` attribute wraps 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 `MatPlot1d` to customize the figure's appearance.
Overlaid on the figure are visuals, contained in the `Visuals1D` object. Attributes may be extracted from
the `Imaging` and plotted via the visuals object, if the corresponding entry is `True` in the `Include1D`
object or the `config/visualize/include.ini` file.
Parameters
----------
imaging
The charge injection line imaging 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 `ImagingCI` are extracted and plotted as visuals for 1D plots.
"""
super().__init__(mat_plot_1d=mat_plot_1d,
include_1d=include_1d,
visuals_1d=visuals_1d)
self.dataset_line = dataset_line
def test__subplot_of_plotter_list_figure(self, imaging_7x7, plot_path,
plot_patch):
mat_plot_1d = aplt.MatPlot1D(
output=aplt.Output(plot_path, format="png"))
plotter_0 = MockYX1DPlotter(
y=np.array([1.0, 2.0, 3.0]),
x=np.array([0.5, 1.0, 1.5]),
mat_plot_1d=mat_plot_1d,
)
plotter_1 = MockYX1DPlotter(
y=np.array([1.0, 2.0, 4.0]),
x=np.array([0.5, 1.0, 1.5]),
mat_plot_1d=mat_plot_1d,
)
plotter_list = [plotter_0, plotter_1]
multi_plotter = aplt.MultiYX1DPlotter(plotter_list=plotter_list)
multi_plotter.figure_1d(func_name="figures_1d",
figure_name="figure_name")
assert path.join(plot_path,
"multi_figure_name.png") in plot_patch.paths
def __init__(
self,
fit: FitImagingCI,
mat_plot_2d: aplt.MatPlot2D = aplt.MatPlot2D(),
visuals_2d: aplt.Visuals2D = aplt.Visuals2D(),
include_2d: aplt.Include2D = aplt.Include2D(),
mat_plot_1d: aplt.MatPlot1D = aplt.MatPlot1D(),
visuals_1d: aplt.Visuals1D = aplt.Visuals1D(),
include_1d: aplt.Include1D = aplt.Include1D(),
):
"""
Plots the attributes of `FitImagingCI` objects using the matplotlib methods `imshow()`, `plot()` and many other
matplotlib functions which customize the plot's appearance.
The `mat_plot_1d` and `mat_plot_2d` attribute wraps 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 `MatPlot1D` and
`MatPlot2D` to customize the figure's appearance.
Overlaid on the figure are visuals, contained in the `Visuals1D` and `Visuals2D` object. Attributes may be
extracted from the `FitImagingCI` and plotted via the visuals object, if the corresponding entry
is `True` in the `Include1D` and `Include2D` object or the `config/visualize/include.ini` file.
Parameters
----------
fit
The fit to an imaging dataset the plotter plots.
get_visuals_2d
A function which extracts from the `FitImaging` the 2D visuals which are plotted on figures.
mat_plot_2d
Contains objects which wrap the matplotlib function calls that make the plot.
visuals_2d
Contains visuals that can be overlaid on the plot.
include_2d
Specifies which attributes of the `Array2D` are extracted and plotted as visuals.
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 `ImagingCI` are extracted and plotted as visuals for 1D plots.
"""
super().__init__(
mat_plot_2d=mat_plot_2d, include_2d=include_2d, visuals_2d=visuals_2d
)
self.visuals_1d = visuals_1d
self.include_1d = include_1d
self.mat_plot_1d = mat_plot_1d
self.fit = fit
self._fit_imaging_meta_plotter = FitImagingPlotterMeta(
fit=self.fit,
get_visuals_2d=self.get_visuals_2d,
mat_plot_2d=self.mat_plot_2d,
include_2d=self.include_2d,
visuals_2d=self.visuals_2d,
)
def test__individual_attributes_are_output(interferometer_7, plot_path,
plot_patch):
interferometer_plotter = aplt.InterferometerPlotter(
interferometer=interferometer_7,
mat_plot_1d=aplt.MatPlot1D(
output=aplt.Output(path=plot_path, format="png")),
mat_plot_2d=aplt.MatPlot2D(
output=aplt.Output(path=plot_path, format="png")),
)
interferometer_plotter.figures_2d(
visibilities=True,
noise_map=True,
u_wavelengths=True,
v_wavelengths=True,
uv_wavelengths=True,
amplitudes_vs_uv_distances=True,
phases_vs_uv_distances=True,
dirty_image=True,
dirty_noise_map=True,
dirty_signal_to_noise_map=True,
dirty_inverse_noise_map=True,
)
assert path.join(plot_path, "visibilities.png") in plot_patch.paths
assert path.join(plot_path, "noise_map.png") in plot_patch.paths
assert path.join(plot_path, "u_wavelengths.png") in plot_patch.paths
assert path.join(plot_path, "v_wavelengths.png") in plot_patch.paths
assert path.join(plot_path, "uv_wavelengths.png") in plot_patch.paths
assert path.join(plot_path,
"amplitudes_vs_uv_distances.png") in plot_patch.paths
assert path.join(plot_path,
"phases_vs_uv_distances.png") in plot_patch.paths
assert path.join(plot_path, "dirty_image_2d.png") in plot_patch.paths
assert path.join(plot_path, "dirty_noise_map_2d.png") in plot_patch.paths
assert path.join(plot_path,
"dirty_signal_to_noise_map_2d.png") in plot_patch.paths
assert path.join(plot_path,
"dirty_inverse_noise_map_2d.png") in plot_patch.paths
plot_patch.paths = []
interferometer_plotter.figures_2d(
visibilities=True,
u_wavelengths=False,
v_wavelengths=True,
amplitudes_vs_uv_distances=True,
)
assert path.join(plot_path, "visibilities.png") in plot_patch.paths
assert not path.join(plot_path, "u_wavelengths.png") in plot_patch.paths
assert path.join(plot_path, "v_wavelengths.png") in plot_patch.paths
assert path.join(plot_path,
"amplitudes_vs_uv_distances.png") in plot_patch.paths
assert path.join(plot_path,
"phases_vs_uv_distances.png") not in plot_patch.paths
def __init__(
self,
y,
x,
mat_plot_1d: aplt.MatPlot1D = aplt.MatPlot1D(),
visuals_1d: aplt.Visuals1D = aplt.Visuals1D(),
include_1d: aplt.Include1D = aplt.Include1D(),
):
super().__init__(
y=y,
x=x,
mat_plot_1d=mat_plot_1d,
visuals_1d=visuals_1d,
include_1d=include_1d,
)
def test__subplots_are_output(interferometer_7, plot_path, plot_patch):
interferometer_plotter = aplt.InterferometerPlotter(
interferometer=interferometer_7,
mat_plot_1d=aplt.MatPlot1D(
output=aplt.Output(path=plot_path, format="png")),
mat_plot_2d=aplt.MatPlot2D(
output=aplt.Output(path=plot_path, format="png")),
)
interferometer_plotter.subplot_interferometer()
assert path.join(plot_path,
"subplot_interferometer.png") in plot_patch.paths
interferometer_plotter.subplot_dirty_images()
assert path.join(plot_path, "subplot_dirty_images.png") in plot_patch.paths
def test__fit_sub_plots(fit_interferometer_7, plot_path, plot_patch):
fit_interferometer_plotter = aplt.FitInterferometerPlotter(
fit=fit_interferometer_7,
mat_plot_1d=aplt.MatPlot1D(
output=aplt.Output(path=plot_path, format="png")),
mat_plot_2d=aplt.MatPlot2D(
output=aplt.Output(path=plot_path, format="png")),
)
fit_interferometer_plotter.subplot_fit_interferometer()
assert path.join(plot_path,
"subplot_fit_interferometer.png") in plot_patch.paths
fit_interferometer_plotter.subplot_fit_dirty_images()
assert path.join(plot_path,
"subplot_fit_dirty_images.png") in plot_patch.paths
def test__plot_yx_line__works_with_all_extras_included(
self, plot_path, plot_patch):
visuals_1d = aplt.Visuals1D(vertical_line=1.0)
mat_plot_1d = aplt.MatPlot1D(
yx_plot=aplt.YXPlot(plot_axis_type="loglog", c="k"),
vertical_line_axvline=aplt.AXVLine(c="k"),
output=aplt.Output(path=plot_path, filename="yx_1", format="png"),
)
yx_1d_plotter = aplt.YX1DPlotter(
y=np.array([1.0, 2.0, 3.0]),
x=np.array([0.5, 1.0, 1.5]),
mat_plot_1d=mat_plot_1d,
visuals_1d=visuals_1d,
)
yx_1d_plotter.figure_1d()
assert path.join(plot_path, "yx_1.png") in plot_patch.paths
def test__fit_quantities_are_output(fit_interferometer_7, plot_path,
plot_patch):
fit_interferometer_plotter = aplt.FitInterferometerPlotter(
fit=fit_interferometer_7,
mat_plot_1d=aplt.MatPlot1D(
output=aplt.Output(path=plot_path, format="png")),
mat_plot_2d=aplt.MatPlot2D(
output=aplt.Output(path=plot_path, format="png")),
)
fit_interferometer_plotter.figures_2d(
visibilities=True,
noise_map=True,
signal_to_noise_map=True,
model_visibilities=True,
residual_map_real=True,
residual_map_imag=True,
normalized_residual_map_real=True,
normalized_residual_map_imag=True,
chi_squared_map_real=True,
chi_squared_map_imag=True,
dirty_image=True,
dirty_noise_map=True,
dirty_signal_to_noise_map=True,
dirty_model_image=True,
dirty_residual_map=True,
dirty_normalized_residual_map=True,
dirty_chi_squared_map=True,
)
assert path.join(plot_path, "visibilities.png") in plot_patch.paths
assert path.join(plot_path, "noise_map.png") in plot_patch.paths
assert path.join(plot_path, "signal_to_noise_map.png") in plot_patch.paths
assert path.join(plot_path, "model_visibilities.png") in plot_patch.paths
assert (path.join(plot_path, "real_residual_map_vs_uv_distances.png")
in plot_patch.paths)
assert (path.join(plot_path, "real_residual_map_vs_uv_distances.png")
in plot_patch.paths)
assert (path.join(plot_path,
"real_normalized_residual_map_vs_uv_distances.png")
in plot_patch.paths)
assert (path.join(plot_path,
"imag_normalized_residual_map_vs_uv_distances.png")
in plot_patch.paths)
assert (path.join(plot_path, "imag_chi_squared_map_vs_uv_distances.png")
in plot_patch.paths)
assert (path.join(plot_path, "imag_chi_squared_map_vs_uv_distances.png")
in plot_patch.paths)
assert path.join(plot_path, "dirty_image_2d.png") in plot_patch.paths
assert path.join(plot_path, "dirty_noise_map_2d.png") in plot_patch.paths
assert path.join(plot_path,
"dirty_signal_to_noise_map_2d.png") in plot_patch.paths
assert path.join(plot_path, "dirty_model_image_2d.png") in plot_patch.paths
assert path.join(plot_path,
"dirty_residual_map_2d.png") in plot_patch.paths
assert (path.join(plot_path, "dirty_normalized_residual_map_2d.png")
in plot_patch.paths)
assert path.join(plot_path,
"dirty_chi_squared_map_2d.png") in plot_patch.paths
plot_patch.paths = []
fit_interferometer_plotter.figures_2d(
visibilities=True,
noise_map=False,
signal_to_noise_map=False,
model_visibilities=True,
chi_squared_map_real=True,
chi_squared_map_imag=True,
)
assert path.join(plot_path, "visibilities.png") in plot_patch.paths
assert path.join(plot_path, "noise_map.png") not in plot_patch.paths
assert path.join(plot_path,
"signal_to_noise_map.png") not in plot_patch.paths
assert path.join(plot_path, "model_visibilities.png") in plot_patch.paths
assert (path.join(plot_path, "real_residual_map_vs_uv_distances.png")
not in plot_patch.paths)
assert (path.join(plot_path, "imag_residual_map_vs_uv_distances.png")
not in plot_patch.paths)
assert (path.join(plot_path,
"real_normalized_residual_map_vs_uv_distances.png")
not in plot_patch.paths)
assert (path.join(plot_path,
"imag_normalized_residual_map_vs_uv_distances.png")
not in plot_patch.paths)
assert (path.join(plot_path, "real_chi_squared_map_vs_uv_distances.png")
in plot_patch.paths)
assert (path.join(plot_path, "imag_chi_squared_map_vs_uv_distances.png")
in plot_patch.paths)