Python | Numpy np.laggauss() method

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 :

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# 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) 

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Output:



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

 

Code #2 :

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# 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) 

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Output:

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

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