在Python中对笛卡尔积x，y和z上的3维Chebyshev级数进行评估

要在笛卡尔积x，y和z上评估3维Chebyshev级数，请在Python中使用polynomial.chebgrid3d(x, y, z)方法。如果c的维度少于三维，则会隐式地将其形状追加为3维。结果的形状将为c.shape[3:] + x.shape + y.shape + z.shape。

参数x，y和z是在笛卡尔积x，y和z的点处评估的三维级数。如果x，y或z是列表或元组，则首先将其转换为ndarray，否则将保持不变，并且如果它不是ndarray，则将其视为标量。

参数c是一个按顺序排列的系数数组，使得i，j次项的系数包含在c[i,j]中。如果c的维数大于两个，则剩余的索引枚举多个系数集。

步骤

首先，导入所需的库−

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

创建一个系数的3D数组−

c = np.arange(16).reshape(2,2,4)

显示数组 –

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

检查尺寸 –

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

获取数据类型 −

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

掌握形状−

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

要在x、y、z的笛卡尔积上评估一个三维切比雪夫级数，请使用polynomial.chebgrid3d(x, y, z)方法-

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

示例

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

# Create a 3D array of coefficients
c = np.arange(16).reshape(2,2,4)

# 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]
   [ 4 5 6 7]]

[[ 8 9 10 11]
   [12 13 14 15]]]

Dimensions of our Array...
3

Datatype of our Array object...
int64

Shape of our Array object...
(2, 2, 4)

Result...
[[[ 120. 1240.]
   [ 196. 2004.]]

[[ 212. 2148.]
   [ 342. 3438.]]]