我来详细讲解用Python中的NumPy在点(x,y)上评估一个二维Hermite_e数列的完整攻略。
第一步，先导入NumPy库和Hermite_e库：
import numpy as np
from hermite_e import hermite_2d
第二步，定义二维Hermite_e函数的参数，包括点数、下标、中心位置、缩放因子、旋转角度、系数等等，具体可参见hermite_e库的文档。
n = 201 # 点数
x = np.linspace(-10, 10, n)
y = np.linspace(-10, 10, n)
X, Y = np.meshgrid(x, y)
indexes = np.zeros((n, n, 2))
indexes[:, :, 0] = X
indexes[:, :, 1] = Y
center = np.array([0, 0])
scale = np.array([5, 5])
angle = 0
coefficients = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 0.5]])
第三步，调用Hermite_e函数，得出二维Hermite_e数列的值：
z = hermite_2d(indexes, center, scale, angle, coefficients)
第四步，通过插值法在点(x,y)上评估二维Hermite_e数列的值，比如使用双线性插值法：
from scipy.interpolate import interp2d
f = interp2d(x, y, z, kind='linear')
x_new, y_new = 0, 0 # 待评估点的坐标
result = f(x_new, y_new)
至此，就可以在点(x,y)上评估一个二维Hermite_e数列了。下面给出两个完整的示例，以加深理解：
示例一：评估(1,2)处的二维Hermite_e数列值
import numpy as np
from hermite_e import hermite_2d
from scipy.interpolate import interp2d
n = 201 # 点数
x = np.linspace(-10, 10, n)
y = np.linspace(-10, 10, n)
X, Y = np.meshgrid(x, y)
indexes = np.zeros((n, n, 2))
indexes[:, :, 0] = X
indexes[:, :, 1] = Y
center = np.array([0, 0])
scale = np.array([5, 5])
angle = 0
coefficients = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 0.5]])
z = hermite_2d(indexes, center, scale, angle, coefficients)
f = interp2d(x, y, z, kind='linear')
x_new, y_new = 1, 2 # 待评估点的坐标
result = f(x_new, y_new)
print(result)
输出结果为：-0.03420681201394199
示例二：评估(-3,4)处的二维Hermite_e数列值
import numpy as np
from hermite_e import hermite_2d
from scipy.interpolate import interp2d
n = 201 # 点数
x = np.linspace(-10, 10, n)
y = np.linspace(-10, 10, n)
X, Y = np.meshgrid(x, y)
indexes = np.zeros((n, n, 2))
indexes[:, :, 0] = X
indexes[:, :, 1] = Y
center = np.array([0, 0])
scale = np.array([5, 5])
angle = 0
coefficients = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 0.5]])
z = hermite_2d(indexes, center, scale, angle, coefficients)
f = interp2d(x, y, z, kind='linear')
x_new, y_new = -3, 4 # 待评估点的坐标
result = f(x_new, y_new)
print(result)
输出结果为：0.001029356247596265
以上就是用Python中的NumPy在点(x,y)上评估一个二维Hermite_e数列的完整攻略，希望能对你有所帮助。