Integrate `mapclassify`

[kylebarron]

From the geopandas.plot docstring

Name of a choropleth classification scheme (requires mapclassify). A mapclassify.MapClassifier object will be used under the hood. Supported are all schemes provided by mapclassify (e.g. ‘BoxPlot’, ‘EqualInterval’, ‘FisherJenks’, ‘FisherJenksSampled’, ‘HeadTailBreaks’, ‘JenksCaspall’, ‘JenksCaspallForced’, ‘JenksCaspallSampled’, ‘MaxP’, ‘MaximumBreaks’, ‘NaturalBreaks’, ‘Quantiles’, ‘Percentiles’, ‘StdMean’, ‘UserDefined’). Arguments can be passed in classification_kwds.

[davidbailey]

The following worked for me:

import numpy

from lonboard import Map, SolidPolygonLayer
from mapclassify import JenksCaspall

layer = SolidPolygonLayer.from_geopandas(zones_interpolated, opacity=0.2)
jc = JenksCaspall(
    zones_interpolated["ProductionAttractionSum Density"].fillna(0),
    k=20
)
colors = []
for color in jc.yb:
    colors.append(Viridis_20.colors[color])
layer.get_fill_color = numpy.uint8(colors)

Map(layers=[layer])

[kylebarron]

Thanks! By the way, I'm not sure where Viridis_20 comes from, but doing an array lookup would be much faster than a loop. You should probably be able to do something like

Viridis_20.colors[jc.yb]