visualization - Plotting features#

gammapy.visualization Package#

Functions#

annotate_heatmap(im[, data, valfmt, ...])

A function to annotate a heatmap.

colormap_hess([transition, width])

Colormap often used in H.E.S.S.

colormap_milagro([transition, width, huestart])

Colormap often used in Milagro collaboration publications.

add_colorbar(img, ax[, axes_loc])

Add colorbar to a given axis.

plot_contour_line(ax, x, y, **kwargs)

Plot smooth curve from contour points.

plot_heatmap(data, row_labels, col_labels[, ...])

Create a heatmap from a numpy array and two lists of labels.

plot_map_rgb(map_[, ax])

Plot RGB image on matplotlib WCS axes.

plot_spectrum_datasets_off_regions(datasets)

Plot the off regions of spectrum datasets.

plot_theta_squared_table(table)

Plot the theta2 distribution of counts, excess and significance.

plot_npred_signal(dataset[, ax, ...])

Plot the energy distribution of predicted counts of a selection of models assigned to a dataset.

plot_distribution(wcs_map[, ax, ncols, ...])

Plot the 1D distribution of data inside a map as an histogram.

Classes#

MapPanelPlotter(figure, xlim, ylim[, npanels])

Map panel plotter class.