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 :
# Python program explaining # numpy.laggauss() method # importing numpy as np # and numpy.polynomial.laguerre module as geek import numpy as np import numpy.polynomial.laguerre as geek # Input degree = 2 degree = 2 # using np.laggauss() method res = geek.laggauss(degree) # Resulting array of sample point and weight print (res) |
Output:
(array([ 0.58578644, 3.41421356]), array([ 0.85355339, 0.14644661]))
Code #2 :
# Python program explaining # numpy.laggauss() method # importing numpy as np # and numpy.polynomial.laguerre module as geek import numpy as np import numpy.polynomial.laguerre as geek # Input degree degree = 3 # using np.laggauss() method res = geek.laggauss(degree) # Resulting array of sample point and weight print (res) |
Output:
(array([ 0.41577456, 2.29428036, 6.28994508]), array([ 0.71109301, 0.27851773, 0.01038926]))
