使用Python和一维系数数组评估二维切比雪夫级数在(x, y)点的值
要评估二维切比雪夫级数在点(x, y)的值,可以使用Python NumPy中的`polynomial.chebval2d()`方法。该方法返回在由x和y中对应值对形成的点上二维切比雪夫级数的值,即参数x, y。二维级数在点(x, y)处进行评估,其中x和y必须具有相同的形状。如果x或y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。
参数c是一个系数数组,其排序方式是:多度为i,j的项的系数包含在c[i,j]中。如果c的维度大于2,则其余索引枚举多组系数。
步骤
首先,导入所需的库:
import numpy as np from numpy.polynomial import chebyshev as C
创建一个一维系数数组:
c = np.array([3, 5])
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)
要评估二维切比雪夫级数在点(x, y)的值,可以使用`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 1d array of coefficients c = np.array([3, 5]) # 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... [3 5] Dimensions of our Array... 1 Datatype of our Array object... int64 Shape of our Array object... (2,) Result... [21. 34.]
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