문제

I'm converting a Shapely MultiPolygon to a PatchCollection, and first colouring each Polygon like so:

# ldn_mp is a MultiPolygon
cm = plt.get_cmap('RdBu')
num_colours = len(ldn_mp)

fig = plt.figure()
ax = fig.add_subplot(111)
minx, miny, maxx, maxy = ldn_mp.bounds
w, h = maxx - minx, maxy - miny
ax.set_xlim(minx - 0.2 * w, maxx + 0.2 * w)
ax.set_ylim(miny - 0.2 * h, maxy + 0.2 * h)
ax.set_aspect(1)

patches = []
for poly in ldn_mp:
    colour = cm(1. * len(filter(poly.contains, points)) / num_colours)
    patches.append(PolygonPatch(poly, fc=colour, ec='#555555', lw=0.2, alpha=1., zorder=1))
pc = PatchCollection(patches, match_original=True)
ax.add_collection(pc)
ax.set_xticks([])
ax.set_yticks([])
plt.title("Density of NO$^2$ Sensors by Borough")
plt.tight_layout()
plt.show()

But I'd like to add a colorbar to my plot, based upon the PatchCollection colors. I'm not sure how to go about that; do I pass the cmap keyword when creating pc? How do I then call set_array() with the colours I've used?

도움이 되었습니까?

해결책

I had the same problem a little while ago. For each polygon I saved the corresponding color to a list named mycolors:

mycolors=[]
...
mycolors.append(SSTvalue)
path_patch = patches.PathPatch(mypath, lw=1)
mypatches.append(path_patch)

I looped over a series of multipolygons stored in a Shapefile and stored each patch in a collection. After that I plotted the polygons using the color information I had stored in the list, which was converted to an array eventually, and added a colorbar:

p = PatchCollection(mypatches, cmap=plt.get_cmap('RdYlBu_r'), alpha=1.0)
p.set_array(array(mycolors))
p.set_clim([np.ma.min(mycolors),np.ma.max(mycolors)])
plt.colorbar(p,shrink=0.5)

The full script I used to plot temperature values with colors and a colorbar for large marine ecosystems of the world represented by polygons can be found here. Hope this helps. Cheers, Trond

다른 팁

There is no need to create an additional list. Assuming you work in pandas or numpy arrays.

For example:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import PatchCollection
from matplotlib import cm

fig, ax = plt.subplots()
for c_l ,patches in dict_mapindex_mpl_polygon.items():
    color = df_map_elements.loc[c_l, 'stress_level']
    p = PatchCollection(patches,color=cm.Set2(color),lw=.3,edgecolor='k')
    ax.add_collection(p)
ax.autoscale_view()

p.set(array=df_map_elements['stress_level'].values, cmap='Set2')

fig.colorbar(p, label="Stress (index)")

plt.show()
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