Revision: 5812
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5812&view=rev
Author: efiring
Date: 2008-07-22 18:43:38 +0000 (Tue, 22 Jul 2008)
Log Message:
-----------
Moved unmasked_index_ranges from lines.py to cbook.py
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/cbook.py
Modified: trunk/matplotlib/lib/matplotlib/cbook.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/cbook.py 2008-07-22 18:05:32 UTC (rev
5811)
+++ trunk/matplotlib/lib/matplotlib/cbook.py 2008-07-22 18:43:38 UTC (rev
5812)
@@ -1244,7 +1244,57 @@
margs[i] = x.filled()
return margs
+def unmasked_index_ranges(mask, compressed = True):
+ '''
+ Find index ranges where *mask* is *False*.
+ *mask* will be flattened if it is not already 1-D.
+
+ Returns Nx2 :class:`numpy.ndarray` with each row the start and stop
+ indices for slices of the compressed :class:`numpy.ndarray`
+ corresponding to each of *N* uninterrupted runs of unmasked
+ values. If optional argument *compressed* is *False*, it returns
+ the start and stop indices into the original :class:`numpy.ndarray`,
+ not the compressed :class:`numpy.ndarray`. Returns *None* if there
+ are no unmasked values.
+
+ Example::
+
+ y = ma.array(np.arange(5), mask = [0,0,1,0,0])
+ ii = unmasked_index_ranges(ma.getmaskarray(y))
+ # returns array [[0,2,] [2,4,]]
+
+ y.compressed()[ii[1,0]:ii[1,1]]
+ # returns array [3,4,]
+
+ ii = unmasked_index_ranges(ma.getmaskarray(y), compressed=False)
+ # returns array [[0, 2], [3, 5]]
+
+ y.filled()[ii[1,0]:ii[1,1]]
+ # returns array [3,4,]
+
+ Prior to the transforms refactoring, this was used to support
+ masked arrays in Line2D.
+
+ '''
+ mask = mask.reshape(mask.size)
+ m = np.concatenate(((1,), mask, (1,)))
+ indices = np.arange(len(mask) + 1)
+ mdif = m[1:] - m[:-1]
+ i0 = np.compress(mdif == -1, indices)
+ i1 = np.compress(mdif == 1, indices)
+ assert len(i0) == len(i1)
+ if len(i1) == 0:
+ return None # Maybe this should be np.zeros((0,2), dtype=int)
+ if not compressed:
+ return np.concatenate((i0[:, np.newaxis], i1[:, np.newaxis]), axis=1)
+ seglengths = i1 - i0
+ breakpoints = np.cumsum(seglengths)
+ ic0 = np.concatenate(((0,), breakpoints[:-1]))
+ ic1 = breakpoints
+ return np.concatenate((ic0[:, np.newaxis], ic1[:, np.newaxis]), axis=1)
+
+
# a dict to cross-map linestyle arguments
_linestyles = [('-', 'solid'),
('--', 'dashed'),
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