[diary #5] numerical derivate

😁START

# if feature exists x 3
def function(y):
	x = y[0]
    w = y[1]
    z = y[2]
    
    return  x*w + x**2 + wz + w * np.power(z, 3)

def numerical_derivate(function, x):
	delta_x = 1e-4		# 10^-4 could call near '0'
    grad = np.zeros_like(x)
    
    iterator = np.nditer(x, flags=['multi_index'])
    
    while not iterator.finished:
    	idx = iterator.multi_index
        tmp_val = x[idx]
        
        x[idx] = float(tmp_val) + delta_x
        f1 = function(x)
        
        x[idx] = float(tmp_val) - delta_x
        f2 = function(x)
        
        grad[idx] = (f1 - f2) / (2 * delta_x)
        
        x[idx] = tmp_val
        
        iterator.iternext()
        
	return grad

😂END

no descirption, I don ready visualize elements

2022.10.15. first commit