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法律研究在 Python 中生成 Hermite_e 多项式和 x、y、z 样本点的伪范德蒙德矩阵
Hermite_e 多项式和 x、y、z 样本点，使用 Python Numpy 中的 hermite.hermevander3d() 函数。该方法返回伪范德蒙德矩阵。参数 x、y、z 是点坐标数组，形状相同。数据类型将根据元素是否为复数转换为 float64 或 complex128。标量将转换为一维数组。参数 deg 是最大次数的列表，格式为 [x_deg, y_deg, z_deg]。
步骤
首先，导入所需的库 -
import numpy as np from numpy.polynomial import hermite as H
使用 numpy.array() 方法创建形状相同的点坐标数组 -
x = np.array([1, 2]) y = np.array([3, 4]) z = np.array([5, 6])
显示数组 -
print("Array1...\n",x)
print("\nArray2...\n",y)
print("\nArray3...\n",z)显示数据类型 -
print("\nArray1 datatype...\n",x.dtype)
print("\nArray2 datatype...\n",y.dtype)
print("\nArray3 datatype...\n",z.dtype)检查两个数组的维度 -
print("\nDimensions of Array1...\n",x.ndim)
print("\nDimensions of Array2...\n",y.ndim)
print("\nDimensions of Array3...\n",z.ndim)检查两个数组的形状 -
print("\nShape of Array1...\n",x.shape)
print("\nShape of Array2...\n",y.shape)
print("\nShape of Array3...\n",z.shape)要生成 Hermite_e 多项式和 x、y、z 样本点的伪范德蒙德矩阵，请使用 Python Numpy 中的 hermite.hermevander3d() 函数 -
x_deg, y_deg, z_deg = 2, 3, 4
print("\nResult...\n",H.hermevander3d(x,y,z, [x_deg, y_deg, z_deg]))示例
import numpy as np
from numpy.polynomial import hermite_e as H
# Create arrays of point coordinates, all of the same shape using the numpy.array() method
x = np.array([1, 2])
y = np.array([3, 4])
z = np.array([5, 6])
# Display the arrays
print("Array1...\n",x)
print("\nArray2...\n",y)
print("\nArray3...\n",z)
# Display the datatype
print("\nArray1 datatype...\n",x.dtype)
print("\nArray2 datatype...\n",y.dtype)
print("\nArray3 datatype...\n",z.dtype)
# Check the Dimensions of both the arrays
print("\nDimensions of Array1...\n",x.ndim)
print("\nDimensions of Array2...\n",y.ndim)
print("\nDimensions of Array3...\n",z.ndim)
# Check the Shape of both the arrays
print("\nShape of Array1...\n",x.shape)
print("\nShape of Array2...\n",y.shape)
print("\nShape of Array3...\n",z.shape)
# To generate a pseudo Vandermonde matrix of the Hermite_e polynomial and x, y, z sample points, use the hermite.hermevander3d() in Python Numpy
x_deg, y_deg, z_deg = 2, 3, 4
print("\nResult...\n",H.hermevander3d(x,y,z, [x_deg, y_deg, z_deg]))输出
Array1...
[1 2]
Array2...
[3 4]
Array3...
[5 6]
Array1 datatype...
int64
Array2 datatype...
int64
Array3 datatype...
int64
Dimensions of Array1...
1
Dimensions of Array2...
1
Dimensions of Array3...
1
Shape of Array1...
(2,)
Shape of Array2...
(2,)
Shape of Array3...
(2,)
Result...
[[1.00000e+00 5.00000e+00 2.40000e+01 1.10000e+02 4.78000e+02 3.00000e+00
1.50000e+01 7.20000e+01 3.30000e+02 1.43400e+03 8.00000e+00 4.00000e+01
1.92000e+02 8.80000e+02 3.82400e+03 1.80000e+01 9.00000e+01 4.32000e+02
1.98000e+03 8.60400e+03 1.00000e+00 5.00000e+00 2.40000e+01 1.10000e+02
4.78000e+02 3.00000e+00 1.50000e+01 7.20000e+01 3.30000e+02 1.43400e+03
8.00000e+00 4.00000e+01 1.92000e+02 8.80000e+02 3.82400e+03 1.80000e+01
9.00000e+01 4.32000e+02 1.98000e+03 8.60400e+03 0.00000e+00 0.00000e+00
0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00]
[1.00000e+00 6.00000e+00 3.50000e+01 1.98000e+02 1.08300e+03 4.00000e+00
2.40000e+01 1.40000e+02 7.92000e+02 4.33200e+03 1.50000e+01 9.00000e+01
5.25000e+02 2.97000e+03 1.62450e+04 5.20000e+01 3.12000e+02 1.82000e+03
1.02960e+04 5.63160e+04 2.00000e+00 1.20000e+01 7.00000e+01 3.96000e+02
2.16600e+03 8.00000e+00 4.80000e+01 2.80000e+02 1.58400e+03 8.66400e+03
3.00000e+01 1.80000e+02 1.05000e+03 5.94000e+03 3.24900e+04 1.04000e+02
6.24000e+02 3.64000e+03 2.05920e+04 1.12632e+05 3.00000e+00 1.80000e+01
1.05000e+02 5.94000e+02 3.24900e+03 1.20000e+01 7.20000e+01 4.20000e+02
2.37600e+03 1.29960e+04 4.50000e+01 2.70000e+02 1.57500e+03 8.91000e+03
4.87350e+04 1.56000e+02 9.36000e+02 5.46000e+03 3.08880e+04 1.68948e+05]]
更新于: 2022-03-07
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