.. _sphx_glr_gallery_images_contours_and_fields_image_masked.py: ============ Image Masked ============ imshow with masked array input and out-of-range colors. The second subplot illustrates the use of BoundaryNorm to get a filled contour effect. .. image:: /gallery/images_contours_and_fields/images/sphx_glr_image_masked_001.png :align: center .. code-block:: python from copy import copy import numpy as np import matplotlib.pyplot as plt import matplotlib.colors as colors # compute some interesting data x0, x1 = -5, 5 y0, y1 = -3, 3 x = np.linspace(x0, x1, 500) y = np.linspace(y0, y1, 500) X, Y = np.meshgrid(x, y) Z1 = np.exp(-X**2 - Y**2) Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2) Z = (Z1 - Z2) * 2 # Set up a colormap: # use copy so that we do not mutate the global colormap instance palette = copy(plt.cm.gray) palette.set_over('r', 1.0) palette.set_under('g', 1.0) palette.set_bad('b', 1.0) # Alternatively, we could use # palette.set_bad(alpha = 0.0) # to make the bad region transparent. This is the default. # If you comment out all the palette.set* lines, you will see # all the defaults; under and over will be colored with the # first and last colors in the palette, respectively. Zm = np.ma.masked_where(Z > 1.2, Z) # By setting vmin and vmax in the norm, we establish the # range to which the regular palette color scale is applied. # Anything above that range is colored based on palette.set_over, etc. # set up the axes fig, (ax1, ax2) = plt.subplots(nrows=2, figsize=(6, 5.4)) # plot using 'continuous' color map im = ax1.imshow(Zm, interpolation='bilinear', cmap=palette, norm=colors.Normalize(vmin=-1.0, vmax=1.0), aspect='auto', origin='lower', extent=[x0, x1, y0, y1]) ax1.set_title('Green=low, Red=high, Blue=masked') cbar = fig.colorbar(im, extend='both', shrink=0.9, ax=ax1) cbar.set_label('uniform') for ticklabel in ax1.xaxis.get_ticklabels(): ticklabel.set_visible(False) # Plot using a small number of colors, with unevenly spaced boundaries. im = ax2.imshow(Zm, interpolation='nearest', cmap=palette, norm=colors.BoundaryNorm([-1, -0.5, -0.2, 0, 0.2, 0.5, 1], ncolors=palette.N), aspect='auto', origin='lower', extent=[x0, x1, y0, y1]) ax2.set_title('With BoundaryNorm') cbar = fig.colorbar(im, extend='both', spacing='proportional', shrink=0.9, ax=ax2) cbar.set_label('proportional') fig.suptitle('imshow, with out-of-range and masked data') plt.show() .. only :: html .. container:: sphx-glr-footer .. container:: sphx-glr-download :download:`Download Python source code: image_masked.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: image_masked.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_