Python | Numpy np.laggauss() method (original) (raw)

Last Updated : 29 Dec, 2019

**np.laggauss()** 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)

Syntax : np.laggauss(deg)
Parameters:
**deg :**[int] Number of sample points and weights. It must be >= 1.

Return : 1.[ndarray] 1-D ndarray containing the sample points.
2.[ndarray] 1-D ndarray containing the weights.

Code #1 :

import numpy as np

import numpy.polynomial.laguerre as geek

degree = 2

res = geek.laggauss(degree)

print (res)

Output:

(array([ 0.58578644, 3.41421356]), array([ 0.85355339, 0.14644661]))

Code #2 :

import numpy as np

import numpy.polynomial.laguerre as geek

degree = 3

res = geek.laggauss(degree)

print (res)

Output:

(array([ 0.41577456, 2.29428036, 6.28994508]), array([ 0.71109301, 0.27851773, 0.01038926]))

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