visualise_wpcf

visualise_wpcf(radii, wPCF, mark_min_pop_B=0, mark_max_pop_B=1, ax=None, colorbar_limit=None, nonlin_cbar_scalefactor=1.5, cbar_kwargs={'label': 'wPCF(r,M,B)'}, figure_kwargs={}, axis_kwargs={})

Visualise the weighted Pair Correlation Function (wPCF) as a heatmap.

Parameters:

radiiarray-like

Array of radius values.

wPCFarray-like

2D array representing the weighted Pair Correlation Function values.

mark_min_pop_Bfloat, optional

Minimum value of the target mark. Default is 0.

mark_max_pop_Bfloat, optional

Maximum value of the target mark. Default is 1.

axmatplotlib.axes.Axes, optional

Axes object to draw the heatmap on. If None, a new figure and axes will be created. Default is None.

colorbar_limitfloat, optional

Value of the maximum values for the colorbar. Default is None.

nonlin_cbar_scalefactorfloat, optional

The scale factor for the exlusion part of the colorbar. Default is 1.5.

cbar_kwargsdict, optional

Additional keyword arguments to pass to the colorbar. Default is dict(label=’wPCF(r,M,B)’).

figure_kwargsdict, optional

Additional keyword arguments to pass to the figure creation. Default is an empty dictionary.

axis_kwargsdict, optional

Additional keyword arguments to customize the axes labels and ticks. Default is an empty dictionary.

Returns:

figmatplotlib.figure.Figure

The figure object containing the heatmap.

axmatplotlib.axes.Axes

The axes object containing the heatmap.