numpy.polynomial.polynomial.polyvander2d(x, y, deg)

Legendre.has_samewindow(other)

numpy.polynomial.laguerre.lagint(c, m=1, k=[], lbnd=0, scl=1, axis=0)

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

numpy.sctype2char(sctype)

numpy.arccos(x[, out]) = Trigonometric inverse cosine, element-wise. The inverse of

numpy.linalg.cond(x, p=None)

numpy.polynomial.laguerre.laggrid3d(x, y, z, c)

numpy.random.logistic(loc=0.0, scale=1.0, size=None) Draw samples from a logistic distribution. Samples are drawn

numpy.mgrid = nd_grid instance which returns a dense multi-dimensional ?meshgrid?. An instance of numpy