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How do I exactly specify the colorbar labels in matplotlib? Frequently, I need to create very specific color scales, but the colorbar labels display so poorly you can't tell what the scale is. I would like to manually define the text next to the colorbar tick marks, or at least have them display in scientific notation.

Here is an example plot where you can't tell what the bottom four color bins represent:

scatter plot with ugly legend

And here is a working example of how that plot was created:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors

# mock up some data
x = np.random.random(50)
y = np.random.random(50)
c = np.arange(0, 1, 1.0/50.0)  # color of points
c[0] = 0.00001
c[1] = 0.0001
c[2] = 0.001
c[3] = 0.01
s = 500 * np.random.random(50) + 25  # size of points

# set up some custom color scaling
lcmap = colors.ListedColormap(['#FFFFFF', '#FF99FF', '#8000FF',
                               '#0000FF', '#0080FF', '#58FAF4',
                               '#00FF00', '#FFFF00', '#FF8000',
                               '#FF0000'])
bounds = [0.0, 0.000001, 0.00001, 0.0001,
          0.001, 0.01, 0.1, 0.25, 0.5, 0.75, 1.0]
norm = colors.BoundaryNorm(bounds, lcmap.N)

# create some plot
fig, ax = plt.subplots()
im = ax.scatter(x, y, c=c, s=s, cmap=lcmap, norm=norm)

# add the colorbar
fig.colorbar(im, ax=ax)

fig.savefig('temp.jpg')
john_science
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1 Answers1

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cbar = fig.colorbar(cax, ticks=[-1, 0, 1])
cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])

and use whatever iterable you want instead of ['Low', 'Medium', 'High']

see: http://matplotlib.org/examples/pylab_examples/colorbar_tick_labelling_demo.html

fgoettel
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