numpy.polynomial.hermite_e.hermeline(off, scl)

MaskedArray.prod(axis=None, dtype=None, out=None)

numpy.log(x[, out]) = Natural logarithm, element-wise. The natural logarithm

numpy.matmul(a, b, out=None) Matrix product of two arrays. The behavior depends on the arguments in the following way.

DataSource.abspath(path)

numpy.ma.compress_rowcols(x, axis=None)

numpy.ma.zeros(shape, dtype=float, order='C') = Return a new array of given shape and type, filled with zeros.

numpy.flipud(m)

classmethod Chebyshev.fit(x, y, deg, domain=None, rcond=None, full=False, w=None, window=None)

numpy.less_equal(x1, x2[, out]) = Return the truth value of (x1 =< x2) element-wise.