Python | Numpy np.lagsub() method

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 :

Python3

# 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 :

Python3

# 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]))

Python | Numpy np.lagsub() method

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