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.