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Setting the midpoint of a matplotlib colormap
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import matplotlib as mpl | |
import matplotlib.pyplot as plt | |
import numpy as np | |
class MidpointNormalize(mpl.colors.Normalize): | |
""" | |
class to help renormalize the color scale | |
""" | |
def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False): | |
self.midpoint = midpoint | |
mpl.colors.Normalize.__init__(self, vmin, vmax, clip) | |
def __call__(self, value, clip=None): | |
# I'm ignoring masked values and all kinds of edge cases to make a | |
# simple example... | |
x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1] | |
return np.ma.masked_array(np.interp(value, x, y)) | |
# generate data for test plots | |
x_values = np.random.normal( 0, 1, 10000) | |
y_values = np.random.normal( 0, 1, 10000) | |
# plot with default midpoint | |
fig, ax = plt.subplots() | |
default_norm = ax.hexbin(x_values, y_values, | |
cmap=plt.cm.seismic) | |
default_norm = ax.hexbin(x_values, y_values, | |
cmap=plt.cm.seismic, | |
gridsize = (25,25)) | |
fig.colorbar(default_norm) | |
plt.savefig('default_norm.png') | |
plt.close() | |
# plot with custom midpoint | |
fig, ax = plt.subplots() | |
norm = MidpointNormalize(midpoint = 20) | |
my_norm = ax.hexbin(x_values, y_values, | |
cmap=plt.cm.seismic, | |
norm = norm, | |
gridsize = (25,25)) | |
fig.colorbar(my_norm) | |
plt.savefig('my_norm.png') | |
plt.close() |
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