numpy.random.f(dfnum, dfden, size=None) Draw samples from an F distribution. Samples are drawn from an F distribution

numpy.polynomial.legendre.leggrid2d(x, y, c)

MaskedArray.__eq__(other)

MaskedArray.__rrshift__ x.__rrshift__(y) <==> y>>x

ndarray.__float__() <==> float(x)

Elementwise bit operations

numpy.nansum(a, axis=None, dtype=None, out=None, keepdims=0)

ndarray.nonzero() Return the indices of the elements that are non-zero. Refer to

generic.__array_wrap__() sc.__array_wrap__(obj) return scalar from array

numpy.r_ = Translates slice objects to concatenation along the first axis. This is a simple way to build up arrays quickly. There