autolens.plot.LightProfilePDFPlotter#

class autolens.plot.LightProfilePDFPlotter(light_profile_pdf_list: List[autogalaxy.profiles.light_profiles.light_profiles.LightProfile], grid: Union[numpy.ndarray, autoarray.structures.grids.uniform_2d.Grid2D, autoarray.structures.grids.iterate_2d.Grid2DIterate, autoarray.structures.grids.irregular_2d.Grid2DIrregular], mat_plot_1d: autogalaxy.plot.mat_wrap.mat_plot.MatPlot1D = <autogalaxy.plot.mat_wrap.mat_plot.MatPlot1D object>, visuals_1d: autogalaxy.plot.mat_wrap.visuals.Visuals1D = <autogalaxy.plot.mat_wrap.visuals.Visuals1D object>, include_1d: autogalaxy.plot.mat_wrap.include.Include1D = <autogalaxy.plot.mat_wrap.include.Include1D object>, mat_plot_2d: autogalaxy.plot.mat_wrap.mat_plot.MatPlot2D = <autogalaxy.plot.mat_wrap.mat_plot.MatPlot2D object>, visuals_2d: autogalaxy.plot.mat_wrap.visuals.Visuals2D = <autogalaxy.plot.mat_wrap.visuals.Visuals2D object>, include_2d: autogalaxy.plot.mat_wrap.include.Include2D = <autogalaxy.plot.mat_wrap.include.Include2D object>, sigma: Optional[float] = 3.0)[source]#
__init__(light_profile_pdf_list: List[autogalaxy.profiles.light_profiles.light_profiles.LightProfile], grid: Union[numpy.ndarray, autoarray.structures.grids.uniform_2d.Grid2D, autoarray.structures.grids.iterate_2d.Grid2DIterate, autoarray.structures.grids.irregular_2d.Grid2DIrregular], mat_plot_1d: autogalaxy.plot.mat_wrap.mat_plot.MatPlot1D = <autogalaxy.plot.mat_wrap.mat_plot.MatPlot1D object>, visuals_1d: autogalaxy.plot.mat_wrap.visuals.Visuals1D = <autogalaxy.plot.mat_wrap.visuals.Visuals1D object>, include_1d: autogalaxy.plot.mat_wrap.include.Include1D = <autogalaxy.plot.mat_wrap.include.Include1D object>, mat_plot_2d: autogalaxy.plot.mat_wrap.mat_plot.MatPlot2D = <autogalaxy.plot.mat_wrap.mat_plot.MatPlot2D object>, visuals_2d: autogalaxy.plot.mat_wrap.visuals.Visuals2D = <autogalaxy.plot.mat_wrap.visuals.Visuals2D object>, include_2d: autogalaxy.plot.mat_wrap.include.Include2D = <autogalaxy.plot.mat_wrap.include.Include2D object>, sigma: Optional[float] = 3.0)[source]#

Plots the attributes of a list of LightProfile objects using the matplotlib methods plot() and imshow() and many other matplotlib functions which customize the plot’s appearance.

Figures plotted by this object average over a list light profiles to computed the average value of each attribute with errors, where the 1D regions within the errors are plotted as a shaded region to show the range of plausible models. Therefore, the input list of galaxies is expected to represent the probability density function of an inferred model-fit.

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 LightProfile 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
  • light_profile_pdf_list – The list of light profiles whose mean and error values the plotter plots.

  • grid – The 2D (y,x) grid of coordinates used to evaluate the light profile 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 LightProfile 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 LightProfile are extracted and plotted as visuals for 2D plots.

  • sigma – The confidence interval in terms of a sigma value at which the errors are computed (e.g. a value of sigma=3.0 uses confidence intevals at ~0.01 and 0.99 the PDF).

Methods

__init__(light_profile_pdf_list, grid[, …])

Plots the attributes of a list of LightProfile objects using the matplotlib methods plot() and imshow() and many other matplotlib functions which customize the plot’s appearance.

close_subplot_figure()

figures_1d([image])

Plots the individual attributes of the plotter’s list of ` LightProfile` object in 1D, which are computed via the plotter’s grid object.

figures_2d([image])

Plots the individual attributes of the plotter’s LightProfile object in 2D, which are computed via the plotter’s 2D grid object.

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.

get_visuals_1d()

get_visuals_2d()

open_subplot_figure(number_subplots[, …])

Setup a figure for plotting an image.

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_of_plotters_figure(plotter_list, name)

Attributes

get_1d

get_2d

is_for_subplot