numpy.load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII')

numpy.arccosh(x[, out]) = Inverse hyperbolic cosine, element-wise.

HermiteE.roots()

HermiteE.copy()

RandomState.logistic(loc=0.0, scale=1.0, size=None) Draw samples from a logistic distribution. Samples

MaskedArray.copy(order='C')

numpy.promote_types(type1, type2) Returns the data type with the smallest size and smallest scalar kind to which both type1

numpy.multiply(x1, x2[, out]) = Multiply arguments element-wise.

numpy.polyval(p, x)

numpy.polynomial.hermite.hermvander(x, deg)