I am plotting a PatchCollection
in matplotlib with coords and patch color values read in from a file.
The problem is that matplotlib seems to automatically scale the color range to the min/max of the data values. How can I manually set the color range? E.g. if my data range is 10-30, but I want to scale this to a color range of 5-50 (e.g. to compare to another plot), how can I do this?
My plotting commands look much the same as in the api example code: patch_collection.py
colors = 100 * pylab.rand(len(patches))
p = PatchCollection(patches, cmap=matplotlib.cm.jet, alpha=0.4)
p.set_array(pylab.array(colors))
ax.add_collection(p)
pylab.colorbar(p)
pylab.show()
Use p.set_clim([5, 50])
to set the color scaling minimums and maximums in the case of your example. Anything in matplotlib that has a colormap has the get_clim
and set_clim
methods.
As a full example:
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.collections import PatchCollection
from matplotlib.patches import Circle
import numpy as np
# (modified from one of the matplotlib gallery examples)
resolution = 50 # the number of vertices
N = 100
x = np.random.random(N)
y = np.random.random(N)
radii = 0.1*np.random.random(N)
patches = []
for x1, y1, r in zip(x, y, radii):
circle = Circle((x1, y1), r)
patches.append(circle)
fig = plt.figure()
ax = fig.add_subplot(111)
colors = 100*np.random.random(N)
p = PatchCollection(patches, cmap=matplotlib.cm.jet, alpha=0.4)
p.set_array(colors)
ax.add_collection(p)
fig.colorbar(p)
fig.show()
Now, if we just add p.set_clim([5, 50])
(where p
is the patch collection) somewhere before we call fig.show(...)
, we get this:
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