Plotting

PyAutoLens custom visualization library.

Step-by-step Juypter notebook guides illustrating all objects listed on this page are provided on the autolens_workspace: plot tutorials and it is strongly recommended you use those to learn plot customization.

Examples / Tutorials:

• autolens_workspace: plot tutorials

Plotters [aplt]

Create figures and subplots showing quantities of standard PyAutoLens objects.

Basic Plot Functions:

plot_array(array[, title, output_path, ...])	Plot an autoarray Array2D to file or onto an existing Axes.
plot_grid(grid[, title, output_path, ...])	Plot an autoarray Grid2D as a scatter plot.

Tracer and Galaxies Subplots:

subplot_tracer(tracer, grid[, output_path, ...])	Multi-panel subplot of the tracer: image, source images, and mass quantities.
subplot_lensed_images(tracer, grid[, ...])	Produce a subplot with one panel per tracer plane showing each plane's image.
subplot_galaxies_images(tracer, grid[, ...])	Produce a subplot showing per-galaxy images for every plane in the tracer.

Imaging Fit Subplots:

subplot_fit_imaging(fit[, output_path, ...])	Produce a 12-panel subplot summarising an imaging fit.
subplot_fit_imaging_log10(fit[, ...])	Produce a 12-panel subplot summarising an imaging fit with log10 colour scaling.
subplot_fit_imaging_x1_plane(fit[, ...])	Produce a 6-panel subplot for a single-plane tracer imaging fit.
subplot_fit_imaging_log10_x1_plane(fit[, ...])	Produce a 6-panel log10 subplot for a single-plane tracer imaging fit.
subplot_fit_imaging_of_planes(fit[, ...])	Produce a 4-panel subplot for each plane in the tracer.
subplot_fit_imaging_tracer(fit[, ...])	Produce a 9-panel tracer subplot derived from a FitImaging object.
subplot_fit_combined(fit_list[, ...])	Produce a combined multi-row subplot for a list of FitImaging objects.
subplot_fit_combined_log10(fit_list[, ...])	Produce a combined log10 multi-row subplot for a list of FitImaging objects.

Interferometer Fit Subplots:

subplot_fit_interferometer(fit[, ...])	Produce a 12-panel subplot summarising an interferometer fit.
subplot_fit_interferometer_real_space(fit[, ...])	Produce a real-space subplot for an interferometer fit.

Point Source Subplots:

subplot_fit_point(fit[, output_path, ...])	Produce a subplot summarising a FitPointDataset.
subplot_point_dataset(dataset[, ...])	Produce a subplot visualising a PointDataset.

Subhalo Detection Subplots:

subplot_detection_imaging(result, ...[, ...])	Produce a 4-panel subplot summarising subhalo detection from imaging data.
subplot_detection_fits(...[, output_path, ...])	Produce a 6-panel subplot comparing imaging fits with and without a subhalo.

Sensitivity Mapping Subplots:

subplot_sensitivity_tracer_images(mask, ...)	Produce a 6-panel subplot comparing a perturbed and unperturbed tracer.
subplot_sensitivity(result, data_subtracted)	Produce an 8-panel sensitivity-mapping summary subplot.
subplot_sensitivity_figures_of_merit(result)	Produce a single-panel subplot showing the sensitivity figures-of-merit grid.

Non-linear Search Plot Functions [aplt]

Module-level functions for visualizing non-linear search results.

corner_cornerpy(samples[, path, filename, ...])
corner_anesthetic(samples[, path, filename, ...])
subplot_parameters(samples[, use_log_y, ...])
log_likelihood_vs_iteration(samples[, ...])

Plot Customization [aplt]

Customize figures created via Plotter objects, including changing matplotlib settings and adding visuals to figures.

Matplot Lib Wrappers [aplt]

Wrappers for every matplotlib function used by a Plotter, allowing for detailed customization of every figure and subplot.

Matplotlib Wrapper Base Objects:

Matplotlib Wrapper 1D Objects:

Matplotlib Wrapper 2D Objects: