How to Control Colorbar Range in Matplotlib Plots?

Enforcing Colorbar Range

Consider the following code:

<code class="python">import matplotlib.pyplot as plt

cdict = {
  'red'  :  ( (0.0, 0.25, .25), (0.02, .59, .59), (1., 1., 1.)),
  'green':  ( (0.0, 0.0, 0.0), (0.02, .45, .45), (1., .97, .97)),
  'blue' :  ( (0.0, 1.0, 1.0), (0.02, .75, .75), (1., 0.45, 0.45))
}
 
cm = plt.colors.LinearSegmentedColormap('my_colormap', cdict, 1024)
 
plt.pcolor(X, Y, v, cmap=cm)
plt.loglog()
plt.xlabel('X Axis')
plt.ylabel('Y Axis')
 
plt.colorbar()
plt.show()</code>

This script generates a color-coded plot of the values of v over the axes X and Y. The vmin and vmax arguments in plt.pcolor allow you to set the lower and upper bounds for the colorbar range. Here's how it works:

<code class="python">plt.pcolor(X, Y, v, cmap=cm, vmin=0, vmax=1)</code>

By setting vmin to 0 and vmax to 1, you ensure that the colorbar spans the entire range from 0 to 1, regardless of the actual values of v. This ensures that the colors correspond consistently to values across different plots with different value ranges.

In summary, using vmin and vmax allows you to control the range of the colorbar, enabling you to align the color scales of multiple plots for comparison and interpretation.

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