scipy.special.he_roots¶
- scipy.special.he_roots(n, mu=False)[source]¶
- Gauss-Hermite (statistician’s) quadrature. - Computes the sample points and weights for Gauss-Hermite quadrature. The sample points are the roots of the n-th degree Hermite polynomial, \(He_n(x)\). These sample points and weights correctly integrate polynomials of degree \(2n - 1\) or less over the interval \([-\infty, \infty]\) with weight function \(f(x) = e^{-(x/2)^2}\). - Parameters: - n : int - quadrature order - mu : bool, optional - If True, return the sum of the weights, optional. - Returns: - x : ndarray - Sample points - w : ndarray - Weights - mu : float - Sum of the weights - See also - scipy.integrate.quadrature, scipy.integrate.fixed_quad, numpy.polynomial.hermite_e.hermegauss - Notes - For small n up to 150 a modified version of the Golub-Welsch algorithm is used. Nodes are computed from the eigenvalue problem and improved by one step of a Newton iteration. The weights are computed from the well-known analytical formula. - For n larger than 150 an optimal asymptotic algorithm is used which computes nodes and weights in a numerical stable manner. The algorithm has linear runtime making computation for very large n (several thousand or more) feasible. 
