How to use axes_grid1 toolkit to match graph In Python
Axis_grid1 provides a helper function make_axes_locatable() which takes an existing axes instance and creates a divider for it. It provides append_axes() method that creates a new axes on the given side (“top”, “right”, “bottom” and “left”) of the original axes.
Approach:
- Import module
- Plot image
- Divide existing axes instance using make_axes_locatable()
- Create new axes using append_axes()
- Use “top” or “bottom” side for horizontal colorbar
- Use “left” or “right” side for vertical colorbar
- Plot colorbar on created axis
Example 1:
Python3
import matplotlib.pyplot as pltfrom mpl_toolkits.axes_grid1 import make_axes_locatableimport numpy as np# Plot image on axes axax = plt.gca()img = np.random.random((10, 20))im = plt.imshow(img, cmap='gray')# Divide existing axes and create new axes# at bottom side of imagedivider = make_axes_locatable(ax)cax = divider.append_axes("bottom", size="5%", pad=0.25)# Plot horizontal colorbarplt.colorbar(im, orientation="horizontal", cax=cax)plt.show() |
Output:
Set Matplotlib colorbar size to match graph
Example 2:
Python3
import matplotlib.pyplot as pltfrom mpl_toolkits.axes_grid1 import make_axes_locatableimport numpy as np# Plot image on axes axax = plt.gca()img = np.random.random((10, 20))im = plt.imshow(img, cmap='gray')# Divide existing axes and create# new axes at right side of imagedivider = make_axes_locatable(ax)cax = divider.append_axes("right", size="5%", pad=0.15)# Plot vertical colorbarplt.colorbar(im, cax=cax)plt.show() |
Output:
Set Matplotlib colorbar size to match graph
Set Matplotlib colorbar size to match graph
Colorbar size that match graph or image is required to get good visualize effect. This can be achieved using any one of following approaches.
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