在Python中使用4D系数数组计算三维Hermite级数在点(x,y,z)处的值
要计算在点(x, y, z)处的三维Hermite级数的值,可以使用Python的Numpy库中的hermite.hermval3d()方法。该方法返回由x、y和z的对应值组成的点上多维多项式的值。第一个参数是x、y和z。在点(x, y, z)处计算三维级数时,x、y和z必须具有相同的形状。如果x、y或z中的任何一个是列表或元组,则首先将其转换为ndarray,否则将保持不变,如果它不是ndarray,则将其视为标量。
第二个参数C是一个系数数组,其顺序排列,使得多重度为i、j、k的项的系数包含在c[i,j,k]中。如果c的维度大于3,则其余的索引将枚举多组系数。
步骤
首先,导入所需的库 –
import numpy as np
from numpy.polynomial import hermite as H
创建一个系数的4维数组 −
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)
获得形状 −
print("\nShape of our Array object...\n",c.shape)
要在点(x, y, z)处评估3D Hermite series,请使用Python Numpy中的hermite.hermval3d()方法。
print("\nResult...\n",H.hermval3d([1,2],[1,2],[1,2],c))
示例
import numpy as np
from numpy.polynomial import hermite 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 3D Hermite series at points (x, y, z), use the hermite.hermval3d() method in Python Numpy
# The method returns the values of the multidimensional polynomial on points formed with triples of corresponding values from x, y, and z.
print("\nResult...\n",H.hermval3d([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...
[[ -8100. 104480.]
[ -8343. 107455.]]