SF.net SVN: matplotlib:[6815] trunk/matplotlib

[<jd...@us...>]

Revision: 6815
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=6815&view=rev
Author:   jdh2358
Date:     2009-01-21 19:09:15 +0000 (Wed, 21 Jan 2009)

Log Message:
-----------
changed defaults on acorr and xcorr to norm, usevlines and maxlags=10

Modified Paths:
--------------
    trunk/matplotlib/CHANGELOG
    trunk/matplotlib/doc/api/api_changes.rst
    trunk/matplotlib/lib/matplotlib/axes.py

Modified: trunk/matplotlib/CHANGELOG
===================================================================
--- trunk/matplotlib/CHANGELOG	2009-01-21 14:52:26 UTC (rev 6814)
+++ trunk/matplotlib/CHANGELOG	2009-01-21 19:09:15 UTC (rev 6815)
@@ -1,3 +1,7 @@
+2009-01-21 Changed the defaults of acorr and xcorr to use
+           usevlines=True, maxlags=10 and normed=True since these are
+           the best defaults
+
 2009-01-19 Fix bug in quiver argument handling. - EF
 
 2009-01-19 Fix bug in backend_gtk: don't delete nonexistent toolbar. - EF

Modified: trunk/matplotlib/doc/api/api_changes.rst
===================================================================
--- trunk/matplotlib/doc/api/api_changes.rst	2009-01-21 14:52:26 UTC (rev 6814)
+++ trunk/matplotlib/doc/api/api_changes.rst	2009-01-21 19:09:15 UTC (rev 6815)
@@ -19,20 +19,24 @@
 
 Changes for 0.98.x
 ==================
+
+* Changed the defaults of acorr and xcorr to use usevlines=True,
+  maxlags=10 and normed=True since these are the best defaults
+
 * Following keyword parameters for :class:`matplotlib.label.Label` are now
-  deprecated and new set of parameters are introduced. The new parameters 
-  are given as a fraction of the font-size. Also, *scatteryoffsets*, 
+  deprecated and new set of parameters are introduced. The new parameters
+  are given as a fraction of the font-size. Also, *scatteryoffsets*,
   *fancybox* and *columnspacing* are added as keyword parameters.
 
         ================   ================
         Deprecated         New
         ================   ================
-        pad                borderpad          
-        labelsep           labelspacing       
-        handlelen          handlelength       
-        handlestextsep     handletextpad      
-        axespad	           borderaxespad      
-        ================   ================   
+        pad                borderpad
+        labelsep           labelspacing
+        handlelen          handlelength
+        handlestextsep     handletextpad
+        axespad	           borderaxespad
+        ================   ================
 
 
 * Removed the configobj and experiemtnal traits rc support

Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py	2009-01-21 14:52:26 UTC (rev 6814)
+++ trunk/matplotlib/lib/matplotlib/axes.py	2009-01-21 19:09:15 UTC (rev 6815)
@@ -3543,8 +3543,8 @@
         """
         call signature::
 
-            acorr(x, normed=False, detrend=mlab.detrend_none, usevlines=False,
-                  maxlags=None, **kwargs)
+            acorr(x, normed=True, detrend=mlab.detrend_none, usevlines=True,
+                  maxlags=10, **kwargs)
 
         Plot the autocorrelation of *x*.  If *normed* = *True*,
         normalize the data by the autocorrelation at 0-th lag.  *x* is
@@ -3602,13 +3602,13 @@
         return self.xcorr(x, x, **kwargs)
     acorr.__doc__ = cbook.dedent(acorr.__doc__) % martist.kwdocd
 
-    def xcorr(self, x, y, normed=False, detrend=mlab.detrend_none,
-              usevlines=False, maxlags=None, **kwargs):
+    def xcorr(self, x, y, normed=True, detrend=mlab.detrend_none,
+              usevlines=True, maxlags=10, **kwargs):
         """
         call signature::
 
-          xcorr(x, y, normed=False, detrend=mlab.detrend_none,
-                usevlines=False, **kwargs):
+            def xcorr(self, x, y, normed=True, detrend=mlab.detrend_none,
+              usevlines=True, maxlags=10, **kwargs):
 
         Plot the cross correlation between *x* and *y*.  If *normed* =
         *True*, normalize the data by the cross correlation at 0-th


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