在Python中使用4d系数阵列,计算笛卡尔积x、y和z上的3-D Chebyshev系列
要在笛卡尔积x、y和z上计算3-D Chebyshev系列,可以使用Python中的polynomial.chebgrid3d(x, y, z)方法。如果c的维度少于三个,将会隐式添加ones(翻译者注:即1)到其形状,使其成为三维。结果的形状将是c.shape [3:] + x.shape + y.shape + z.shape。
参数x、y和z是三维系列,对于笛卡尔积x、y和z中的点进行求值。如果x、y或z是列表或元组,则首先将其转换为ndarray,否则将其保持不变。如果它不是ndarray,则将其视为标量。参数c是按照i,j次项系数的顺序排列的系数数组,其中i,j表示两项的次数。如果c的维度大于2,则其余索引将枚举多个系数集合。
步骤
首先,导入所需的库-
import numpy as np
from numpy.polynomial import chebyshev as C
创建4d系数矩阵 –
c = np.arange(48).reshape(2,2,6,2)
显示矩阵-
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)
要在笛卡尔积x、y和z上计算3-D Chebyshev系列,可以使用Python中的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 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 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]
[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...
[[[[ 552. 53976.]
[ 900. 86904.]]
[[ 972. 92844.]
[ 1566. 148176.]]]
[[[ 576. 55956.]
[ 936. 89874.]]
[[ 1008. 95814.]
[ 1620. 152631.]]]]