在Python中评估三维Hermite_e级数在点(x,y,z)处的值
为了评估三维Hermite_e级数在点(x, y, z)处的值,可以使用Python Numpy中的`hermite.hermeval3d()`方法。该方法返回由x、y和z的对应值的三元组构成的点上的多维多项式的值。
第一个参数是x, y, z。三维级数在点(x, y, z)处进行评估,其中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,其排序方式是,多度为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 hermite_e as H
创建一个三维系数数组:
c = np.arange(24).reshape(2,2,6)
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)
为了评估三维Hermite_e级数在点(x, y, z)处的值,可以使用Python Numpy中的`hermite.hermeval3d()`方法:
print("\nResult...\n",H.hermeval3d([1,2],[1,2],[1,2],c))
示例
import numpy as np from numpy.polynomial import hermite_e as H # Create a 3d array of coefficients c = np.arange(24).reshape(2,2,6) # 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_e series at points (x, y, z), use the hermite.hermeval3d() method in Python Numpy print("\nResult...\n",H.hermeval3d([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]]] Dimensions of our Array... 3 Datatype of our Array object... int64 Shape of our Array object... (2, 2, 6) Result... [ 212. -2484.]
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