autolens.plot.FitInterferometerPlotter

class autolens.plot.FitInterferometerPlotter(fit: autolens.interferometer.fit_interferometer.FitInterferometer, mat_plot_1d: autogalaxy.plot.mat_wrap.lensing_mat_plot.MatPlot1D = <autogalaxy.plot.mat_wrap.lensing_mat_plot.MatPlot1D object>, visuals_1d: autogalaxy.plot.mat_wrap.lensing_visuals.Visuals1D = <autogalaxy.plot.mat_wrap.lensing_visuals.Visuals1D object>, include_1d: autogalaxy.plot.mat_wrap.lensing_include.Include1D = <autogalaxy.plot.mat_wrap.lensing_include.Include1D object>, mat_plot_2d: autogalaxy.plot.mat_wrap.lensing_mat_plot.MatPlot2D = <autogalaxy.plot.mat_wrap.lensing_mat_plot.MatPlot2D object>, visuals_2d: autogalaxy.plot.mat_wrap.lensing_visuals.Visuals2D = <autogalaxy.plot.mat_wrap.lensing_visuals.Visuals2D object>, include_2d: autogalaxy.plot.mat_wrap.lensing_include.Include2D = <autogalaxy.plot.mat_wrap.lensing_include.Include2D object>)
__init__(fit: autolens.interferometer.fit_interferometer.FitInterferometer, mat_plot_1d: autogalaxy.plot.mat_wrap.lensing_mat_plot.MatPlot1D = <autogalaxy.plot.mat_wrap.lensing_mat_plot.MatPlot1D object>, visuals_1d: autogalaxy.plot.mat_wrap.lensing_visuals.Visuals1D = <autogalaxy.plot.mat_wrap.lensing_visuals.Visuals1D object>, include_1d: autogalaxy.plot.mat_wrap.lensing_include.Include1D = <autogalaxy.plot.mat_wrap.lensing_include.Include1D object>, mat_plot_2d: autogalaxy.plot.mat_wrap.lensing_mat_plot.MatPlot2D = <autogalaxy.plot.mat_wrap.lensing_mat_plot.MatPlot2D object>, visuals_2d: autogalaxy.plot.mat_wrap.lensing_visuals.Visuals2D = <autogalaxy.plot.mat_wrap.lensing_visuals.Visuals2D object>, include_2d: autogalaxy.plot.mat_wrap.lensing_include.Include2D = <autogalaxy.plot.mat_wrap.lensing_include.Include2D object>)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(fit, mat_plot_1d, visuals_1d, …) Initialize self.
close_subplot_figure()
extract_1d(name, value[, include_name]) Extracts an attribute for plotting in a Visuals1D object based on the following criteria:
extract_2d(name, value[, include_name]) Extracts an attribute for plotting in a Visuals2D object based on the following criteria:
figures_2d(visibilities, noise_map, …) Plot the model data of an analysis, using the Fitter class object.
figures_2d_of_planes(plane_image, plane_index)
get_subplot_figsize(number_subplots) Get the size of a sub plotter in (total_y_pixels, total_x_pixels), based on the number of subplots that are going to be plotted.
open_subplot_figure(number_subplots, …) Setup a figure for plotting an image.
plane_plotter_from(plane)
set_filename(filename)
set_format(format)
set_mat_plot_1d_for_multi_plot(…)
set_mat_plots_for_subplot(is_for_subplot[, …])
set_title(label)
subplot(visibilities, noise_map, …)
subplot_fit_dirty_images()
subplot_fit_interferometer()
subplot_fit_real_space()
subplot_of_plotters_figure(plotter_list, name)

Attributes

inversion_plotter
is_for_subplot
plane
tracer
tracer_plotter
visuals_with_include_2d Extracts from a Structure attributes that can be plotted and return them in a Visuals object.
visuals_with_include_2d_real_space
visuals_with_include_2d

Extracts from a Structure attributes that can be plotted and return them in a Visuals object.

Only attributes with True entries in the Include object are extracted for plotting.

From an AbstractStructure the following attributes can be extracted for plotting:

  • origin: the (y,x) origin of the structure’s coordinate system.
  • mask: the mask of the structure.
  • border: the border of the structure’s mask.
Parameters:structure (abstract_structure.AbstractStructure) – The structure whose attributes are extracted for plotting.
Returns:The collection of attributes that can be plotted by a Plotter2D object.
Return type:vis.Visuals2D
figures_2d(visibilities: bool = False, noise_map: bool = False, signal_to_noise_map: bool = False, model_visibilities: bool = False, residual_map_real: bool = False, residual_map_imag: bool = False, normalized_residual_map_real: bool = False, normalized_residual_map_imag: bool = False, chi_squared_map_real: bool = False, chi_squared_map_imag: bool = False, image: bool = False, dirty_image: bool = False, dirty_noise_map: bool = False, dirty_signal_to_noise_map: bool = False, dirty_model_image: bool = False, dirty_residual_map: bool = False, dirty_normalized_residual_map: bool = False, dirty_chi_squared_map: bool = False)

Plot the model data of an analysis, using the Fitter class object.

The visualization and output type can be fully customized.

Parameters:
  • fit (autolens.lens.fitting.Fitter) – Class containing fit between the model data and observed lens data (including residual_map, chi_squared_map etc.)
  • output_path (str) – The path where the data is output if the output_type is a file format (e.g. png, fits)
  • output_format (str) – How the data is output. File formats (e.g. png, fits) output the data to harddisk. ‘show’ displays the data in the python interpreter window.