numpy.polynomial.laguerre.laggauss()

numpy.polynomial.laguerre.laggauss(deg) [source]

Gauss-Laguerre quadrature.

Computes the sample points and weights for Gauss-Laguerre quadrature. These sample points and weights will correctly integrate polynomials of degree 2*deg - 1 or less over the interval [0, \inf] with the weight function f(x) = \exp(-x).

Parameters:

deg : int

Number of sample points and weights. It must be >= 1.

Returns:

x : ndarray

1-D ndarray containing the sample points.

y : ndarray

1-D ndarray containing the weights.

Notes

The results have only been tested up to degree 100 higher degrees may be problematic. The weights are determined by using the fact that

w_k = c / (L'_n(x_k) * L_{n-1}(x_k))

where c is a constant independent of k and x_k is the k?th root of L_n, and then scaling the results to get the right value when integrating 1.

doc_NumPy
2017-01-10 18:17:17
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