Revision: 6699
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=6699&view=rev
Author:   jdh2358
Date:     2008-12-23 19:49:08 +0000 (Tue, 23 Dec 2008)

Log Message:
-----------
added support for mincnt to hexbin

Modified Paths:
--------------
    trunk/matplotlib/lib/matplotlib/axes.py
    trunk/matplotlib/release/osx/Makefile

Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py     2008-12-23 16:06:15 UTC (rev 
6698)
+++ trunk/matplotlib/lib/matplotlib/axes.py     2008-12-23 19:49:08 UTC (rev 
6699)
@@ -5212,7 +5212,7 @@
                     xscale = 'linear', yscale = 'linear',
                     cmap=None, norm=None, vmin=None, vmax=None,
                     alpha=1.0, linewidths=None, edgecolors='none',
-                    reduce_C_function = np.mean,
+                    reduce_C_function = np.mean, mincnt=None,
                     **kwargs):
         """
         call signature::
@@ -5221,7 +5221,7 @@
                  xscale = 'linear', yscale = 'linear',
                  cmap=None, norm=None, vmin=None, vmax=None,
                  alpha=1.0, linewidths=None, edgecolors='none'
-                 reduce_C_function = np.mean,
+                 reduce_C_function = np.mean, mincnt=None,
                  **kwargs)
 
         Make a hexagonal binning plot of *x* versus *y*, where *x*,
@@ -5269,6 +5269,10 @@
           *scale*: [ 'linear' | 'log' ]
             Use a linear or log10 scale on the vertical axis.
 
+          *mincnt*: None | a positive integer
+            If not None, only display cells with at least *mincnt*
+            number of points in the cell
+
         Other keyword arguments controlling color mapping and normalization
         arguments:
 
@@ -5369,6 +5373,8 @@
         d1 = (x-ix1)**2 + 3.0 * (y-iy1)**2
         d2 = (x-ix2-0.5)**2 + 3.0 * (y-iy2-0.5)**2
         bdist = (d1<d2)
+        if mincnt is None:
+            mincnt = 0
 
         if C is None:
             accum = np.zeros(n)
@@ -5400,10 +5406,11 @@
                 else:
                     lattice2[ix2[i], iy2[i]].append( C[i] )
 
+
             for i in xrange(nx1):
                 for j in xrange(ny1):
                     vals = lattice1[i,j]
-                    if len(vals):
+                    if len(vals)>mincnt:
                         lattice1[i,j] = reduce_C_function( vals )
                     else:
                         lattice1[i,j] = np.nan

Modified: trunk/matplotlib/release/osx/Makefile
===================================================================
--- trunk/matplotlib/release/osx/Makefile       2008-12-23 16:06:15 UTC (rev 
6698)
+++ trunk/matplotlib/release/osx/Makefile       2008-12-23 19:49:08 UTC (rev 
6699)
@@ -95,7 +95,7 @@
        rm -rf upload &&\
        mkdir upload &&\
        cp matplotlib-${MPLVERSION}.tar.gz upload/ &&\
-       cp 
matplotlib-${MPLVERSION}/dist/matplotlib-${MPLVERSION}_r0-py2.5-macosx-10.3-fat.egg
 upload/matplotlib-${MPLVERSION}-py2.5.egg &&\
+       cp 
matplotlib-${MPLVERSION}/dist/matplotlib-${MPLVERSION}_r0-py2.5-macosx-10.3-fat.egg
 upload/matplotlib-${MPLVERSION}-macosx-py2.5.egg &&\
        cp 
matplotlib-${MPLVERSION}/dist/matplotlib-${MPLVERSION}-py2.5-macosx10.5.zip 
upload/matplotlib-${MPLVERSION}-py2.5-mpkg.zip&&\
        scp upload/* [email protected]:uploads/
 


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