Python | Numpy np.laggauss()方法
原文:https://www . geesforgeks . org/python-numpy-NP-lag gaus-method/
**np.laggauss()**计算高斯-拉盖尔求积的样本点和权重。这些样本点和权重将在区间[0, inf]上正确地将次数2*deg - 1 或更少的多项式与权重函数f(x) = exp(-x)积分
语法:
np.laggauss(deg)参数: deg:【int】样本点数量和权重。肯定是> = 1。返回: 1。包含样本点的一维数组。 2。包含权重的一维数组。
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)
Output:
(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)
Output:
(array([ 0.41577456, 2.29428036, 6.28994508]), array([ 0.71109301, 0.27851773, 0.01038926]))
