New custom colormap example; and fix typo in Axes.autoscale_view

efiring · efiring · commit 499d8c9a8839 · 2008-11-18T23:38:53.000Z
svn path=/trunk/matplotlib/; revision=6414
diff --git a/examples/pylab_examples/custom_cmap.py b/examples/pylab_examples/custom_cmap.py
@@ -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()
+
diff --git a/examples/tests/backend_driver.py b/examples/tests/backend_driver.py
@@ -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',
diff --git a/lib/matplotlib/axes.py b/lib/matplotlib/axes.py
@@ -1496,7 +1496,7 @@ def autoscale_view(self, tight=False, scalex=True, scaley=True):
             if scalex:
                 self.set_xbound(x0, x1)
             if scaley:
-                self.set_ybound(y0, 11)
+                self.set_ybound(y0, y1)
             return
 
         if scalex:
