numpy.iscomplexobj(x)

numpy.random.logseries(p, size=None) Draw samples from a logarithmic series distribution. Samples are drawn from

MaskedArray.harden_mask()

numpy.average(a, axis=None, weights=None, returned=False)

ndarray.shape Tuple of array dimensions. Notes May be used to ?reshape? the array, as long

recarray.max(axis=None, out=None) Return the maximum along a given axis. Refer to

numpy.matlib.randn(*args)

numpy.gradient(f, *varargs, **kwargs)

numpy.equal(x1, x2[, out]) = Return (x1 == x2) element-wise.

matrix.argmax(axis=None, out=None)