.. _pylab_examples-image_masked: pylab_examples example code: image_masked.py ============================================ .. plot:: /home/mdboom/Work/builds/matplotlib/doc/mpl_examples/pylab_examples/image_masked.py :: #!/usr/bin/env python '''imshow with masked array input and out-of-range colors. The second subplot illustrates the use of BoundaryNorm to get a filled contour effect. ''' from pylab import * from numpy import ma import matplotlib.colors as colors delta = 0.025 x = y = arange(-3.0, 3.0, delta) X, Y = meshgrid(x, y) Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0) Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1) Z = 10 * (Z2-Z1) # difference of Gaussians # Set up a colormap: palette = 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 = 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. subplot(1,2,1) im = imshow(Zm, interpolation='bilinear', cmap=palette, norm = colors.Normalize(vmin = -1.0, vmax = 1.0, clip = False), origin='lower', extent=[-3,3,-3,3]) title('Green=low, Red=high, Blue=bad') colorbar(im, extend='both', orientation='horizontal', shrink=0.8) subplot(1,2,2) im = imshow(Zm, interpolation='nearest', cmap=palette, norm = colors.BoundaryNorm([-1, -0.5, -0.2, 0, 0.2, 0.5, 1], ncolors=256, clip = False), origin='lower', extent=[-3,3,-3,3]) title('With BoundaryNorm') colorbar(im, extend='both', spacing='proportional', orientation='horizontal', shrink=0.8) show() Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)