numpy.polynomial.legendre.legline(off, scl)

numpy.info(object=None, maxwidth=76, output=', mode 'w' at 0x402ae078>, toplevel='numpy')

chararray.rsplit(sep=None, maxsplit=None)

class numpy.polynomial.legendre.Legendre(coef, domain=None, window=None)

numpy.polynomial.hermite_e.hermevander3d(x, y, z, deg)

numpy.find_common_type(array_types, scalar_types)

There is a general need for looping over not only functions on scalars but also over functions on vectors (or arrays). This concept is realized in Numpy by generalizing the universal functions (ufuncs)

recarray.dtype Data-type of the array?s elements.

numpy.polynomial.chebyshev.chebweight(x)

numpy.polynomial.laguerre.lagzero = array([0])