Revision: 8207 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8207&view=rev Author: ryanmay Date: 2010-03-21 17:43:11 +0000 (Sun, 21 Mar 2010)
Log Message: ----------- Add multicolored line example based on an example from the scipy.org cookbook cleaned up to use colormaps. Added Paths: ----------- trunk/matplotlib/examples/pylab_examples/multicolored_line.py Added: trunk/matplotlib/examples/pylab_examples/multicolored_line.py =================================================================== --- trunk/matplotlib/examples/pylab_examples/multicolored_line.py (rev 0) +++ trunk/matplotlib/examples/pylab_examples/multicolored_line.py 2010-03-21 17:43:11 UTC (rev 8207) @@ -0,0 +1,36 @@ +#!/usr/bin/env python +''' +Color parts of a line based on its properties, e.g., slope. +''' +import numpy as np +import matplotlib.pyplot as plt +from matplotlib.collections import LineCollection +from matplotlib.colors import ListedColormap, BoundaryNorm + +x = np.linspace(0, 3 * np.pi, 500) +y = np.sin(x) +z = np.cos(0.5 * (x[:-1] + x[1:])) # first derivative + +# Create a colormap for red, green and blue and a norm to color +# f' < -0.5 red, f' > 0.5 blue, and the rest green +cmap = ListedColormap(['r', 'g', 'b']) +norm = BoundaryNorm([-1, -0.5, 0.5, 1], cmap.N) + +# Create a set of line segments so that we can color them individually +# This creates the points as a N x 1 x 2 array so that we can stack points +# together easily to get the segments. The segments array for line collection +# needs to be numlines x points per line x 2 (x and y) +points = np.array([x, y]).T.reshape(-1, 1, 2) +segments = np.concatenate([points[:-1], points[1:]], axis=1) + +# Create the line collection object, setting the colormapping parameters. +# Have to set the actual values used for colormapping separately. +lc = LineCollection(segments, cmap=cmap, norm=norm) +lc.set_array(z) +lc.set_linewidth(3) +plt.gca().add_collection(lc) + +plt.xlim(x.min(), x.max()) +plt.ylim(-1.1, 1.1) +plt.show() + This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site. ------------------------------------------------------------------------------ Download Intel® Parallel Studio Eval Try the new software tools for yourself. Speed compiling, find bugs proactively, and fine-tune applications for parallel performance. See why Intel Parallel Studio got high marks during beta. http://p.sf.net/sfu/intel-sw-dev _______________________________________________ Matplotlib-checkins mailing list Matplotlib-checkins@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-checkins