Probably a number of scipy places as well
import numpy
import scipy.stats
print numpy.__version__
print scipy.__version__
for s in range(16777214, 16777944):
if scipy.stats.nanmean(numpy.ones((s, 1), numpy.float32))[0]!=1:
print '\nbroke', s, scipy.stats.nanmean(numpy.ones((s, 1),
numpy.float32))
break
else:
print '\r',s,
c:\temp>python np_sum.py
1.8.0b2
0.11.0
16777216
broke 16777217 [ 0.99999994]
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