在Python中使用4D系数数组评估x、y和z的笛卡尔积上的3D Hermite_e级数
要评估x、y和z的笛卡尔积上的3D Hermite_e级数,请在Python中使用hermite_e.hermegrid3d(x, y, z, c)方法。该方法返回二维多项式在x、y和z的笛卡尔积中的点的值。
参数是x、y、z。三维级数在x、y和z的笛卡尔积中的点处进行评估。如果x、y或z是列表或元组,则首先将其转换为ndarray,否则保持不变,并且如果它不是ndarray,则将其视为标量。
参数c是一个系数数组,其排序方式使得i、j次项的系数包含在c[i,j]中。如果c的维度大于2,则其余索引枚举多个系数集。如果c的维度小于3,则会隐式地将其形状附加为1,使其成为3D。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4D系数数组 -
c = np.arange(48).reshape(2,2,6,2)
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)
要评估x、y和z的笛卡尔积上的3D Hermite_e级数,请在Python中使用hermite_e.hermegrid3d(x, y, z, c)方法 -
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.]]]]
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