# HG changeset patch
# User Nicolas Saunier <nicolas.saunier@polymtl.ca>
# Date 1440772688 14400
# Node ID 5b91b8d97cf3f777fa9eb1eed3522ca9994eb914
# Parent  867bab9f317a8377f2dc47488722de493e5b939c
corrected bug

diff -r 867bab9f317a -r 5b91b8d97cf3 python/utils.py
--- a/python/utils.py	Thu Aug 27 23:51:18 2015 -0400
+++ b/python/utils.py	Fri Aug 28 10:38:08 2015 -0400
@@ -7,7 +7,7 @@
 from math import sqrt, ceil, floor
 from scipy.stats import kruskal, shapiro
 from scipy.spatial import distance
-from numpy import zeros, array, exp, sum as npsum, int as npint, arange, cumsum, median, isnan, ones, convolve,  dtype, isnan, NaN, mean, ma
+from numpy import zeros, array, exp, sum as npsum, int as npint, arange, cumsum, median, isnan, ones, convolve,  dtype, isnan, NaN, mean, ma, isinf
 
 
 datetimeFormat = "%Y-%m-%d %H:%M:%S"
@@ -662,7 +662,7 @@
             import sys
             sys.exit()
         else:
-            if similarityFunc is None and metric is not None and not np.isinf(delta):
+            if similarityFunc is None and metric is not None and not isinf(delta):
                 print('Warning: you are using a cdist metric and a finite delta, which will make probably computation slower than using the equivalent similarityFunc (since all pairwise distances will be computed by cdist).')
             self.similarityFunc = similarityFunc
             self.metric = metric