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]]
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