使用Python中的2D数组系数在x、y和z的笛卡尔积上评估3D Chebyshev级数

要在x、y和z的笛卡尔积上评估3D Chebyshev级数，可以在Python中使用polynomial.chebgrid3d（x，y，z）方法。如果c的维度少于3个，则隐式地向其形状添加1以使其成为3D。结果的形状将为c.shape [3：] + x.shape + y.shape + z.shape。

参数x、y和z是评估三维级数的点在x、y和z的笛卡尔积上。如果x，y或z是列表或元组，则首先将其转换为ndarray，否则它将保持不变，并且，如果它不是ndarray，则将其视为标量。

参数c是按照系数i，j的级数的顺序排序的系数数组，这些系数包含在c [i，j]中。如果c的维数大于2，则其余索引枚举多个系数集。

步骤

首先，请导入必需的库 –

import numpy as np
from numpy.polynomial import chebyshev as C

创建2D系数数组 –

c = np.arange(4).reshape(2,2)

显示数组 –

print("Our Array...\n",c)

检查维度 –

print("\nDimensions of our Array...\n",c.ndim)

获取数据类型 –

print("\nDatatype of our Array object...\n",c.dtype)

获取形状 –

print("\nShape of our Array object...\n",c.shape)

要在x、y和z的笛卡尔积上评估3D Chebyshev级数，请使用polynomial.chebgrid3d（x，y，z）方法 –

print("\nResult...\n",C.chebgrid3d([1,2],[1,2], [1,2], c))

例子

import numpy as np
from numpy.polynomial import chebyshev as C

# Create a 2d array of coefficients
c = np.arange(4).reshape(2,2)

# Display the array
print("Our Array...\n",c)

# Check the Dimensions
print("\nDimensions of our Array...\n",c.ndim)

# Get the Datatype
print("\nDatatype of our Array object...\n",c.dtype)

# Get the Shape
print("\nShape of our Array object...\n",c.shape)

# To evaluate a 3-D Chebyshev series on the Cartesian product of x, y, z, use the polynomial.chebgrid3d(x, y, z) method in Python
print("\nResult...\n",C.chebgrid3d([1,2],[1,2], [1,2], c))

输出

Our Array...
[[0 1]
   [2 3]]

Dimensions of our Array...
2

Datatype of our Array object...
int64

Shape of our Array object...
(2, 2)

Result...
[[17. 28.]
   [28. 46.]]