splot.esda.moran_facet¶

splot.esda.moran_facet(moran_matrix, figsize=(16, 12), scatter_bv_kwds=None, fitline_bv_kwds=None, scatter_glob_kwds={'color': '#737373'}, fitline_glob_kwds=None)[source]¶

Moran Facet visualization. Includes BV Morans and Global Morans on the diagonal.

Parameters

moran_matrixesda.moran.Moran_BV_matrix instance: Dictionary of Moran_BV objects
figsizetuple, optional: W, h of figure. Default =(16,12)
scatter_bv_kwdskeyword arguments, optional: Keywords used for creating and designing the scatter points of off-diagonal Moran_BV plots. Default =None.
fitline_bv_kwdskeyword arguments, optional: Keywords used for creating and designing the moran fitline of off-diagonal Moran_BV plots. Default =None.
scatter_glob_kwdskeyword arguments, optional: Keywords used for creating and designing the scatter points of diagonal Moran plots. Default =None.
fitline_glob_kwdskeyword arguments, optional: Keywords used for creating and designing the moran fitline of diagonal Moran plots. Default =None.

Returns

figMatplotlib Figure instance: Bivariate Moran Local scatterplot figure
axarrmatplotlib Axes instance: Axes in which the figure is plotted

Examples

Imports

>>> import matplotlib.pyplot as plt
>>> import libpysal as lp
>>> import numpy as np
>>> import geopandas as gpd
>>> from esda.moran import Moran_BV_matrix
>>> from splot.esda import moran_facet

Load data and calculate Moran Local statistics

>>> f = gpd.read_file(lp.examples.get_path("sids2.dbf"))
>>> varnames = ['SIDR74',  'SIDR79',  'NWR74',  'NWR79']
>>> vars = [numpy.array(f[var]) for var in varnames]
>>> w = lp.io.open(lp.examples.get_path("sids2.gal")).read()
>>> moran_matrix = Moran_BV_matrix(vars,  w,  varnames = varnames)

Plot

>>> fig, axarr = moran_facet(moran_matrix)
>>> plt.show()

Customize plot

>>> fig, axarr = moran_facet(moran_matrix,
...                          fitline_bv_kwds=dict(color='#4393c3'))
>>> plt.show()

(Source code)