Revision: 8039
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8039&view=rev
Author: astraw
Date: 2009-12-18 22:25:26 +0000 (Fri, 18 Dec 2009)
Log Message:
-----------
bugfix: mlab.prctile handles even-length data
Modified Paths:
--------------
trunk/matplotlib/CHANGELOG
trunk/matplotlib/lib/matplotlib/mlab.py
Modified: trunk/matplotlib/CHANGELOG
===================================================================
--- trunk/matplotlib/CHANGELOG 2009-12-18 22:25:16 UTC (rev 8038)
+++ trunk/matplotlib/CHANGELOG 2009-12-18 22:25:26 UTC (rev 8039)
@@ -1,3 +1,6 @@
+2009-12-18 mlab.prctile handles even-length data, such that the median
+ is the mean of the two middle values. - ADS
+
2009-12-15 Add raw-image (unsampled) support for the ps backend. - JJL
2009-12-14 Add patch_artist kwarg to boxplot, but keep old default.
Modified: trunk/matplotlib/lib/matplotlib/mlab.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/mlab.py 2009-12-18 22:25:16 UTC (rev
8038)
+++ trunk/matplotlib/lib/matplotlib/mlab.py 2009-12-18 22:25:26 UTC (rev
8039)
@@ -904,19 +904,39 @@
the *p* percentage point in the sequence is returned.
"""
+ # This implementation derived from scipy.stats.scoreatpercentile
+ def _interpolate(a, b, fraction):
+ """Returns the point at the given fraction between a and b, where
+ 'fraction' must be between 0 and 1.
+ """
+ return a + (b - a)*fraction
- x = np.array(x).ravel() # we need a copy
- x.sort()
- Nx = len(x)
+ scalar = True
+ if cbook.iterable(p):
+ scalar = False
+ per = np.array(p)
+ values = np.array(x).ravel() # copy
+ values.sort()
- if not cbook.iterable(p):
- return x[int(p*Nx/100.0)]
+ idxs = per /100. * (values.shape[0] - 1)
+ ai = idxs.astype(np.int)
+ bi = ai + 1
+ frac = idxs % 1
- p = np.asarray(p)* Nx/100.0
- ind = p.astype(int)
- ind = np.where(ind>=Nx, Nx-1, ind)
- return x.take(ind)
+ # handle cases where attempting to interpolate past last index
+ cond = bi >= len(values)
+ if scalar:
+ if cond:
+ ai -= 1
+ bi -= 1
+ frac += 1
+ else:
+ ai[cond] -= 1
+ bi[cond] -= 1
+ frac[cond] += 1
+ return _interpolate(values[ai],values[bi],frac)
+
def prctile_rank(x, p):
"""
Return the rank for each element in *x*, return the rank
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