I was surprised to see that numarray.mlab.cov is returning a rank-0
complex number when given two 1D arrays as inputs rather than the
standard 2x2 covariance array I am used to seeing. Is this a feature
or a bug?
In [2]: import numarray.mlab as nam
In [3]: x = nam.rand(10)
In [4]: y = nam.rand(10)
In [5]: nam.cov(x, y)
Out[5]: array((0.014697855954587828+0j))
In [6]: import numpy.oldnumeric.mlab as npm
In [7]: x = npm.rand(10)
In [8]: y = npm.rand(10)
In [9]: npm.cov(x, y)
Out[9]:
array([[ 0.13243082, 0.0520454 ],
[ 0.0520454 , 0.07435816]])
In [10]: import numarray
In [11]: numarray.__version__
Out[11]: '1.3.3'
In [12]: import numpy
In [13]: numpy.__version__
Out[13]: '1.0b2.dev2999'
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