在Python中使用3D系数数组来评估二维切比雪夫级数的(x, y)点
要在点(x, y)处评估二维切比雪夫级数,可以使用Python Numpy库中的polynomial.chebval2d()方法。该方法返回由x和y对应值对形成的点上的二维切比雪夫级数的值,即参数x、y。在点(x, y)处评估二维级数时,x和y必须具有相同的形状。如果x或y是一个列表或元组,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。
参数c是按照使得多重度i,j项的系数位于c[i,j]中的顺序排列的系数数组。如果c的维数大于2,剩余的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 chebyshev as C
创建一个系数的三维数组 −
c = np.arange(24).reshape(2,2,6)
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)处评估2-D Chebyshev系列,使用 polynomial.chebval2d() 方法 −
print("\nResult...\n",C.chebval2d([1,2],[1,2], c))
示例
import numpy as np
from numpy.polynomial import chebyshev as C
# 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 2-D Chebyshev series at points (x, y), use the polynomial.chebval2d() method in Python Numpy
print("\nResult...\n",C.chebval2d([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...
[[ 36. 108.]
[ 40. 117.]
[ 44. 126.]
[ 48. 135.]
[ 52. 144.]
[ 56. 153.]]