SF.net SVN: matplotlib: [5093] trunk/matplotlib

[<ef...@us...>]

Revision: 5093
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5093&view=rev
Author:   efiring
Date:     2008-04-28 11:26:08 -0700 (Mon, 28 Apr 2008)

Log Message:
-----------
Add hexbin_demo, and use log10 for log in hexbin

Modified Paths:
--------------
    trunk/matplotlib/examples/backend_driver.py
    trunk/matplotlib/lib/matplotlib/axes.py

Added Paths:
-----------
    trunk/matplotlib/examples/hexbin_demo.py

Modified: trunk/matplotlib/examples/backend_driver.py
===================================================================
--- trunk/matplotlib/examples/backend_driver.py	2008-04-28 16:52:44 UTC (rev 5092)
+++ trunk/matplotlib/examples/backend_driver.py	2008-04-28 18:26:08 UTC (rev 5093)
@@ -49,6 +49,7 @@
     'fill_demo.py',
     'finance_demo.py',
     'fonts_demo_kw.py',
+    'hexbin_demo.py',
     'histogram_demo.py',
     'hline_demo.py',
     'image_demo.py',

Added: trunk/matplotlib/examples/hexbin_demo.py
===================================================================
--- trunk/matplotlib/examples/hexbin_demo.py	                        (rev 0)
+++ trunk/matplotlib/examples/hexbin_demo.py	2008-04-28 18:26:08 UTC (rev 5093)
@@ -0,0 +1,34 @@
+'''
+hexbin is an axes method or pyplot function that is essentially
+a pcolor of a 2-D histogram with hexagonal cells.  It can be
+much more informative than a scatter plot; in the first subplot
+below, try substituting 'scatter' for 'hexbin'.
+'''
+
+from matplotlib.pyplot import *
+import numpy as np
+
+n = 100000
+x = np.random.standard_normal(n)
+y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
+xmin = x.min()
+xmax = x.max()
+ymin = y.min()
+ymax = y.max()
+
+subplot(121)
+hexbin(x,y)
+axis([xmin, xmax, ymin, ymax])
+title("Hexagon binning")
+cb = colorbar()
+cb.set_label('counts')
+
+subplot(122)
+hexbin(x,y,bins='log')
+axis([xmin, xmax, ymin, ymax])
+title("With a log color scale")
+cb = colorbar()
+cb.set_label('log10(N)')
+
+show()
+

Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py	2008-04-28 16:52:44 UTC (rev 5092)
+++ trunk/matplotlib/lib/matplotlib/axes.py	2008-04-28 18:26:08 UTC (rev 5093)
@@ -4447,7 +4447,7 @@
                              each hexagon directly corresponds to its count
                              value.
             bins='log'     : Use a logarithmic scale for the color map.
-                             Internally, log(count+1) is used to determine
+                             Internally, log10(count+1) is used to determine
                              the hexagon color.
             bins=<integer> : Divide the counts in the specified number of
                              bins, and color the hexagons accordingly
@@ -4456,10 +4456,10 @@
                              to be used.
 
           * xscale = 'linear' | 'log':
-                             Use a logarithmic scale on the horizontal axis.
+                             Use a log10 scale on the horizontal axis.
 
           * yscale = 'linear' | 'log':
-                             Use a logarithmic scale on the vertical axis.
+                             Use a log10 scale on the vertical axis.
 
         Other keyword args; the color mapping and normalization arguments.
 
@@ -4516,9 +4516,9 @@
         x = npy.array(x, float)
         y = npy.array(y, float)
         if xscale=='log':
-            x = npy.log(x)
+            x = npy.log10(x)
         if yscale=='log':
-            y = npy.log(y)
+            y = npy.log10(y)
         xmin = min(x)
         xmax = max(x)
         ymin = min(y)
@@ -4574,14 +4574,14 @@
         polygons[:,:,1] += py
 
         if xscale=='log':
-            polygons[:,:,0] = npy.exp(polygons[:,:,0])
-            xmin = math.exp(xmin)
-            xmax = math.exp(xmax)
+            polygons[:,:,0] = 10**(polygons[:,:,0])
+            xmin = 10**xmin
+            xmax = 10**xmax
             self.set_xscale('log')
         if yscale=='log':
-            polygons[:,:,1] = npy.exp(polygons[:,:,1])
-            ymin = math.exp(ymin)
-            ymax = math.exp(ymax)
+            polygons[:,:,1] = 10**(polygons[:,:,1])
+            ymin = 10**ymin
+            ymax = 10**ymax
             self.set_yscale('log')
 
         class HexagonBinCollection(mcoll.PolyCollection):
@@ -4607,7 +4607,7 @@
 
         # Transform the counts if needed
         if bins=='log':
-            counts = npy.log(counts+1)
+            counts = npy.log10(counts+1)
         elif bins!=None:
             if not iterable(bins):
                 minimum, maximum = min(counts), max(counts)


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