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SF.net SVN: matplotlib:[6414] trunk/matplotlib
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From: <ef...@us...> - 2008-11-18 23:38:59
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Revision: 6414
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=6414&view=rev
Author: efiring
Date: 2008-11-18 23:38:53 +0000 (Tue, 18 Nov 2008)
Log Message:
-----------
New custom colormap example; and fix typo in Axes.autoscale_view
Modified Paths:
--------------
trunk/matplotlib/examples/tests/backend_driver.py
trunk/matplotlib/lib/matplotlib/axes.py
Added Paths:
-----------
trunk/matplotlib/examples/pylab_examples/custom_cmap.py
Added: trunk/matplotlib/examples/pylab_examples/custom_cmap.py
===================================================================
--- trunk/matplotlib/examples/pylab_examples/custom_cmap.py (rev 0)
+++ trunk/matplotlib/examples/pylab_examples/custom_cmap.py 2008-11-18 23:38:53 UTC (rev 6414)
@@ -0,0 +1,134 @@
+#!/usr/bin/env python
+
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib.colors import LinearSegmentedColormap
+
+"""
+
+Example: suppose you want red to increase from 0 to 1 over the bottom
+half, green to do the same over the middle half, and blue over the top
+half. Then you would use:
+
+cdict = {'red': ((0.0, 0.0, 0.0),
+ (0.5, 1.0, 1.0),
+ (1.0, 1.0, 1.0)),
+
+ 'green': ((0.0, 0.0, 0.0),
+ (0.25, 0.0, 0.0),
+ (0.75, 1.0, 1.0),
+ (1.0, 1.0, 1.0)),
+
+ 'blue': ((0.0, 0.0, 0.0),
+ (0.5, 0.0, 0.0),
+ (1.0, 1.0, 1.0))}
+
+If, as in this example, there are no discontinuities in the r, g, and b
+components, then it is quite simple: the second and third element of
+each tuple, above, is the same--call it "y". The first element ("x")
+defines interpolation intervals over the full range of 0 to 1, and it
+must span that whole range. In other words, the values of x divide the
+0-to-1 range into a set of segments, and y gives the end-point color
+values for each segment.
+
+Now consider the green. cdict['green'] is saying that for
+0 <= x <= 0.25, y is zero; no green.
+0.25 < x <= 0.75, y varies linearly from 0 to 1.
+x > 0.75, y remains at 1, full green.
+
+If there are discontinuities, then it is a little more complicated.
+Label the 3 elements in each row in the cdict entry for a given color as
+(x, y0, y1). Then for values of x between x[i] and x[i+1] the color
+value is interpolated between y1[i] and y0[i+1].
+
+Going back to the cookbook example, look at cdict['red']; because y0 !=
+y1, it is saying that for x from 0 to 0.5, red increases from 0 to 1,
+but then it jumps down, so that for x from 0.5 to 1, red increases from
+0.7 to 1. Green ramps from 0 to 1 as x goes from 0 to 0.5, then jumps
+back to 0, and ramps back to 1 as x goes from 0.5 to 1.
+
+row i: x y0 y1
+ /
+ /
+row i+1: x y0 y1
+
+Above is an attempt to show that for x in the range x[i] to x[i+1], the
+interpolation is between y1[i] and y0[i+1]. So, y0[0] and y1[-1] are
+never used.
+
+"""
+
+
+
+cdict1 = {'red': ((0.0, 0.0, 0.0),
+ (0.5, 0.0, 0.1),
+ (1.0, 1.0, 1.0)),
+
+ 'green': ((0.0, 0.0, 0.0),
+ (1.0, 0.0, 0.0)),
+
+ 'blue': ((0.0, 0.0, 1.0),
+ (0.5, 0.1, 0.0),
+ (1.0, 0.0, 0.0))
+ }
+
+cdict2 = {'red': ((0.0, 0.0, 0.0),
+ (0.5, 0.0, 1.0),
+ (1.0, 0.1, 1.0)),
+
+ 'green': ((0.0, 0.0, 0.0),
+ (1.0, 0.0, 0.0)),
+
+ 'blue': ((0.0, 0.0, 0.1),
+ (0.5, 1.0, 0.0),
+ (1.0, 0.0, 0.0))
+ }
+
+cdict3 = {'red': ((0.0, 0.0, 0.0),
+ (0.25,0.0, 0.0),
+ (0.5, 0.8, 1.0),
+ (0.75,1.0, 1.0),
+ (1.0, 0.4, 1.0)),
+
+ 'green': ((0.0, 0.0, 0.0),
+ (0.25,0.0, 0.0),
+ (0.5, 0.9, 0.9),
+ (0.75,0.0, 0.0),
+ (1.0, 0.0, 0.0)),
+
+ 'blue': ((0.0, 0.0, 0.4),
+ (0.25,1.0, 1.0),
+ (0.5, 1.0, 0.8),
+ (0.75,0.0, 0.0),
+ (1.0, 0.0, 0.0))
+ }
+
+
+blue_red1 = LinearSegmentedColormap('BlueRed1', cdict1)
+blue_red2 = LinearSegmentedColormap('BlueRed2', cdict2)
+blue_red3 = LinearSegmentedColormap('BlueRed3', cdict3)
+
+x = np.arange(0, np.pi, 0.1)
+y = np.arange(0, 2*np.pi, 0.1)
+X, Y = np.meshgrid(x,y)
+Z = np.cos(X) * np.sin(Y)
+
+plt.figure(figsize=(10,4))
+plt.subplots_adjust(wspace=0.3)
+
+plt.subplot(1,3,1)
+plt.imshow(Z, interpolation='nearest', cmap=blue_red1)
+plt.colorbar()
+
+plt.subplot(1,3,2)
+plt.imshow(Z, interpolation='nearest', cmap=blue_red2)
+plt.colorbar()
+
+plt.subplot(1,3,3)
+plt.imshow(Z, interpolation='nearest', cmap=blue_red3)
+plt.colorbar()
+
+plt.suptitle('Custom Blue-Red colormaps')
+
+plt.show()
+
Modified: trunk/matplotlib/examples/tests/backend_driver.py
===================================================================
--- trunk/matplotlib/examples/tests/backend_driver.py 2008-11-18 21:37:25 UTC (rev 6413)
+++ trunk/matplotlib/examples/tests/backend_driver.py 2008-11-18 23:38:53 UTC (rev 6414)
@@ -43,6 +43,7 @@
'contour_demo.py',
'contour_label_demo.py',
'contourf_demo.py',
+ 'custom_cmap.py',
'geo_demo.py',
'griddata_demo.py',
'csd_demo.py',
Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py 2008-11-18 21:37:25 UTC (rev 6413)
+++ trunk/matplotlib/lib/matplotlib/axes.py 2008-11-18 23:38:53 UTC (rev 6414)
@@ -1496,7 +1496,7 @@
if scalex:
self.set_xbound(x0, x1)
if scaley:
- self.set_ybound(y0, 11)
+ self.set_ybound(y0, y1)
return
if scalex:
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