import numpy as np
def numerical_gradient(f, x):
    h = 1e-4  # 0.0001
    grad = np.zeros_like(x)
    for idx in range(x.size):
        tmp_val = x[idx]
        x[idx] = float(tmp_val) + h
        fxh1 = f(x)  # f(x+h)
        x[idx] = tmp_val - h 
        fxh2 = f(x)  # f(x-h)
        grad[idx] = (fxh1 - fxh2) / (2*h)
        x[idx] = tmp_val  # 値を元に戻す
    return grad

xy = np.array([2.0,3.0]) # .0 が大事！
ret = numerical_gradient(lambda x:
      np.sum([i**2 for i in x]), xy)
print(ret)