我想创建一个函数- 返回函数在特定点的梯度的载体
我try 过的-
import numpy as np
def function_2(x):
return x[0]**2 + x[1]**2
def numerical_gradient(f, x):
h = 1e-4
grad = np.zeros_like(x)
for idx in range(x.size):
tmp_val = x[idx]
# f(x + h)
x[idx] = tmp_val + h
fxh1 = f(x)
# f(x - h)
x[idx] = tmp_val - h
fxh2 = f(x)
grad[idx] = (fxh1 - fxh2) / (2 * h)
# x[idx] original value
x[idx] = tmp_val
return grad
grd1 = numerical_gradient(function_2, np.array([3,4]))
print(grd1)
它显示[25000 35000] 为什么[6.000xx 7.999x]不符合预期？