%% Using CasADi for differentiation 
% Download at https://web.casadi.org/

%% Scalar case

import casadi.*

% Create a symbolic scalar variable
x = MX.sym('x',1);

% Use the symbolic variable to define the cost function
y = cos(x^2)

% Compute the derivative of the cost function
grad_y = gradient(y,x)

% Build a function object
f = Function('f',{x},{grad_y});

% Evaluate the function at a given numerical value of the variable
xnum = 2
grad_y_num = f(xnum)


%% Vector case

% Create a symbolic vector
x = MX.sym('x',2);

% Use the symbolic vector to define the cost function
Q = [2 1; 1 4];
y = 1/2*x'*Q*x

% Compute the gradient of the cost function
grad_y = gradient(y,x)

% Build a function object
f = Function('f',{x},{grad_y});

% Evaluate the function at a given numerical value of the vector
xnum = [1;3]
grad_y_num = f(xnum)