Python 在x，y和z的笛卡尔积上评估3-D Hermite_e系列

要在x，y和z的笛卡尔积上评估3-D Hermite_e系列，使用Python中的hermite_e.hermegrid3d(x, y, z, c)方法。该方法返回在x，y和z的笛卡尔积中的点处的二维多项式的值。

参数是x，y，z。三维系列在x，y和z的笛卡尔积中的点上进行评估。如果x，y或z是列表或元组，它会首先转换为ndarray，否则保持不变，如果它不是ndarray，则将其视为标量。

参数c是一个按序排列的系数数组，其中i，j次的系数包含在c[i，j]中。如果c的维数大于两个，则其余的索引枚举多个系数集。如果c的维数小于三维，则会隐式地在其形状中添加1以使其成为3-D。结果的形状将为c.shape[3：] + x.shape + y.shape + z.shape。

步骤

首先，导入所需的库−

import numpy as np
from numpy.polynomial import hermite_e as H

创建一个四维系数数组 −

c = np.arange(48).reshape(2,2,6,2)

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)

获取形状 −

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

使用Python中的hermite_e.hermegrid3d(x, y, z, c)方法，在x、y和z的笛卡尔乘积上评估一个三维Hermite_e级数-

print("\nResult...\n",H.hermegrid3d([1,2],[1,2],[1,2],c))

示例

import numpy as np
from numpy.polynomial import hermite_e as H

# Create a 4d array of coefficients
c = np.arange(48).reshape(2,2,6,2)

# 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 Hermite_e series on the Cartesian product of x, y and z, use the hermite_e.hermegrid3d(x, y, z, c) method in Python
print("\nResult...\n",H.hermegrid3d([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]
  [16 17]
  [18 19]
  [20 21]
  [22 23]]]


[[[24 25]
  [26 27]
  [28 29]
  [30 31]
  [32 33]
  [34 35]]

 [[36 37]
  [38 39]
  [40 41]
  [42 43]
  [44 45]
  [46 47]]]]

Dimensions of our Array...
4

Datatype of our Array object...
int64

Shape of our Array object...
(2, 2, 6, 2)

Result...
[[[[ 424. -1848.]
  [ 684. -2952.]]

[[ 732. -3132.]
 [ 1170. -4968.]]]


[[[ 440. -1908.]
  [ 708. -3042.]]

[[ 756. -3222.]
 [ 1206. -5103.]]]]