Python | Numpy np.laggauss() method
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)
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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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