How do I set the colorbar range in Matplotlib to highlight specific data values?

Set Colorbar Range to Specify Data Range

When using Matplotlib's colorbar, it is desirable to manually set the range of values that the colorbar displays. By default, the colorbar spans the minimum and maximum values of the data being plotted. However, you may want to specify a custom range to enhance the visualization of your data.

To set the colorbar range, you can use the vmin and vmax arguments when creating the colorbar. These arguments specify the minimum and maximum values, respectively, that the colorbar should display. Values outside this range will not be shown in the colorbar.

For example, consider the following code:

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

# Create a custom colormap
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)

# Create some data
x = np.arange(0, 10, .1)
y = np.arange(0, 10, .1)
X, Y = np.meshgrid(x,y)
data = 2*( np.sin(X) + np.sin(3*Y) )

# Plot the data with a custom colorbar range
plt.pcolor(X, Y, data, cmap=cm, vmin=-4, vmax=4)
plt.colorbar()
plt.show()</code>

In this example, the colorbar range is set to [-4, 4]. This means that the colorbar will display the full range of the custom colormap, even though the data values range from -5 to 5.

Using vmin and vmax allows you to customize the range of values displayed in the colorbar, giving you more control over the visualization of your data. By specifying a custom range, you can emphasize the values that are relevant to your analysis and make your plots more effective.

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