It seems like you want to compute the gradient of a function at a given point x. However, you haven't provided the function for which you want to compute the gradient. The gradient is a vector that points in the direction of the greatest rate of increase of the function, and its magnitude is the rate of increase in that direction.

Here is a general way to compute the gradient of a function in Python:

import numpy as np

def f(x):
    # Your function here
    pass

def gradient(f, x):
    h = 1e-7 # This is a small number for numerical differentiation
    grad = np.zeros_like(x) # Initialize a gradient array with the same shape as x

    for idx in range(x.size):
        tmp_val = x[idx]
        
        # Compute f(x+h)
        x[idx] = tmp_val + h
        fxh1 = f(x)
        
        # Compute f(x-h)
        x[idx] = tmp_val - h 
        fxh2 = f(x) 
        
        grad[idx] = (fxh1 - fxh2) / (2*h)
        x[idx] = tmp_val # Restore the value
        
    return grad

You can use the gradient function to compute the gradient of your function at a given point. Just replace f with your function.