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)