Python Numpy np.laggauss()方法

np.laggauss() 计算Gauss-Laguerre正交的样本点和权重。这些样本点和权重将正确地在区间[0, inf]上整合度数为2*度-1或更小的多项式，权重函数f(x) = exp(-x)

语法: np.laggauss(deg)
参数:
deg : [int] 样本点和权重的数量。它必须>=1。

返回：

1. [ndarray] 包含样本点的1-D ndarray。
2. [ndarray] 包含权重的1-D ndarray。

代码#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) 

输出:

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

代码#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) 

输出:

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