splot.mapping.value_by_alpha_cmap¶

splot.mapping.value_by_alpha_cmap(x, y, cmap='GnBu', revert_alpha=False, divergent=False)[source]¶

Calculates Value by Alpha rgba values

Parameters

xarray: Variable determined by color
yarray: Variable determining alpha value
cmapstr or list of str: Matplotlib Colormap or list of colors used to create vba_layer
revert_alphabool, optional: If True, high y values will have a low alpha and low values will be transparent. Default =False.
divergentbool, optional: Creates a divergent alpha array with high values at the extremes and low, transparent values in the middle of the input values.

Returns

rgbandarray (n,4): RGBA colormap, where the alpha channel represents one attribute (x) and the rgb color the other attribute (y)
cmapstr or list of str: Original Matplotlib Colormap or list of colors used to create vba_layer

Examples

Imports

>>> from libpysal import examples
>>> import geopandas as gpd
>>> import matplotlib.pyplot as plt
>>> import matplotlib
>>> import numpy as np
>>> from splot.mapping import value_by_alpha_cmap

Load Example Data

>>> link_to_data = examples.get_path('columbus.shp')
>>> gdf = gpd.read_file(link_to_data)
>>> x = gdf['HOVAL'].values
>>> y = gdf['CRIME'].values

Create rgba values

>>> rgba, _ = value_by_alpha_cmap(x, y)

Create divergent rgba and change Colormap

>>> div_rgba, _ = value_by_alpha_cmap(x, y, cmap='seismic', divergent=True)

Create rgba values with reverted alpha values

>>> rev_rgba, _  = value_by_alpha_cmap(x, y, cmap='RdBu', revert_alpha=True)

(Source code)