numpy.ma.corrcoef(x, y=None, rowvar=True, bias=, allow_masked=True, ddof=)

classmethod Laguerre.cast(series, domain=None, window=None)

numpy.polynomial.chebyshev.chebweight(x)

numpy.around(a, decimals=0, out=None)

can_cast(from, totype, casting = ) Returns True if cast between data types can occur according to the casting rule. promote_types(type1, type2) Returns the data type with the smallest size and smallest scalar kind to which both type1 and type2 may be safely cast. min_scalar_type(a) For scalar a, returns the data type with the smallest size and smallest scalar kind which can hold its value. result_type(*arrays_and_dtypes) Returns the type that results from applying the NumPy type promotion

numpy.polynomial.hermite_e.hermevander(x, deg)

numpy.polynomial.hermite_e.hermezero = array([0])

RandomState.poisson(lam=1.0, size=None) Draw samples from a Poisson distribution. The Poisson distribution

RandomState.gamma(shape, scale=1.0, size=None) Draw samples from a Gamma distribution. Samples are drawn

numpy.ma.choose(indices, choices, out=None, mode='raise')