Revision: 5352
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5352&view=rev
Author: mmetz_bn
Date: 2008-06-02 03:10:40 -0700 (Mon, 02 Jun 2008)
Log Message:
-----------
Added support for log to hist with histtype='step'
Modified Paths:
--------------
trunk/matplotlib/CHANGELOG
trunk/matplotlib/lib/matplotlib/axes.py
Modified: trunk/matplotlib/CHANGELOG
===================================================================
--- trunk/matplotlib/CHANGELOG 2008-06-01 21:36:50 UTC (rev 5351)
+++ trunk/matplotlib/CHANGELOG 2008-06-02 10:10:40 UTC (rev 5352)
@@ -1,3 +1,5 @@
+2008-06-02 Added support for log to hist with histtype='step' - MM
+
===============================================================
2008-05-29 Released 0.98.0 at revision 5314
Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py 2008-06-01 21:36:50 UTC (rev
5351)
+++ trunk/matplotlib/lib/matplotlib/axes.py 2008-06-02 10:10:40 UTC (rev
5352)
@@ -5739,7 +5739,6 @@
ccount += 1
elif orientation == 'vertical':
for m in n:
-
color = colors[ccount % len(colors)]
patch = self.bar(bins[:-1]+boffset, m, width=width,
bottom=bottom, align='center', log=log,
@@ -5762,6 +5761,13 @@
elif align != 'edge':
raise ValueError, 'invalid align: %s' % align
+ if log:
+ y[0],y[-1] = 1e-100, 1e-100
+ if orientation == 'horizontal':
+ self.set_xscale('log')
+ elif orientation == 'vertical':
+ self.set_yscale('log')
+
for m in n:
y[1:-1:2], y[2::2] = m, m
if orientation == 'horizontal':
@@ -5769,6 +5775,22 @@
elif orientation != 'vertical':
raise ValueError, 'invalid orientation: %s' % orientation
patches.append( self.fill(x,y) )
+
+ # adopted from adjust_x/ylim part of the bar method
+ if orientation == 'horizontal':
+ xmin, xmax = 0, self.dataLim.intervalx[1]
+ for m in n:
+ xmin = np.amin(m[m!=0]) # filter out the 0 height bins
+ xmin = max(xmin*0.9, 1e-100)
+ self.dataLim.intervalx = (xmin, xmax)
+ elif orientation == 'vertical':
+ ymin, ymax = 0, self.dataLim.intervaly[1]
+ for m in n:
+ ymin = np.amin(m[m!=0]) # filter out the 0 height bins
+ ymin = max(ymin*0.9, 1e-100)
+ self.dataLim.intervaly = (ymin, ymax)
+ self.autoscale_view()
+
else:
raise ValueError, 'invalid histtype: %s' % histtype
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