% Define environment (functions, gradients etc...) GivenEnv % Define parameters max_iter = 300; % Maximum iterations tol = 1e-4; % Tolerance % Point x0 = (0, 0) % ========================================================================= point = 1; x0 = [0, 0]; f = fun(x0(1), x0(2)); gf = grad_fun(x0(1), x0(2)); hf = hessian_fun(x0(1), x0(2)); fprintf('Initial point (%d, %d), f = %f, grad = [%f;%f], hessian = [%f %f ; %f %f]. Can NOT use method\n', x0, f, gf, hf); disp(' '); % Point x0 = (-1, 1) % ========================================================================= point = 2; x0 = [-1, 1]; point_str = "[" + x0(1) + ", " + x0(2) + "]"; f = fun(-1, 1); gf = grad_fun(x0(1), x0(2)); hf = hessian_fun(x0(1), x0(2)); fprintf('Initial point (%d, %d), f = %f, grad = [%f;%f], hessian = [%f %f ; %f %f]. Can use method\n', x0, f, gf, hf); % Find the best fixed gamma k = zeros(100, 1); j = 1; n = linspace(0.1, 1.5, 100); for g = n gamma_fixed_step = g; [~, ~, k(j)] = method_steepest_descent(fun, grad_fun, x0, tol, max_iter, 'fixed'); j = j + 1; end plotItersOverGamma(n, k, "Iteration for different $\gamma$ values", "figures/StDes_Iter_o_gamma_" + point + ".png"); [~, j] = min(k); gamma_fixed_step = n(j); [x_fixed, f_fixed, kk] = method_steepest_descent(fun, grad_fun, x0, tol, max_iter, 'fixed'); fprintf('Fixed step: Initial point (%f, %f), steps:%d, Final (x,y)=(%f, %f), f(x,y)=%f\n', x0, kk, x_fixed(end, :), f_fixed(end)); plotPointsOverContour(x_fixed, fun, [-2, 0], [-2, 2], 100, point_str + ": Steepest descent $\gamma$ = " + gamma_fixed_step, "figures/StDes_fixed_" + point + ".png"); % Minimized f [x_minimized, f_minimized, kk] = method_steepest_descent(fun, grad_fun, x0, tol, max_iter, 'minimized'); fprintf('Minimized f(g): Initial point (%f, %f), steps:%d, Final (x,y)=(%f, %f), f(x,y)=%f\n', x0, kk, x_minimized(end, :), f_minimized(end)); plotPointsOverContour(x_minimized, fun, [-2, 0], [-2, 2], 100, point_str + ": Steepest descent minimized $f(x_k + \gamma_kd_k)$", "figures/StDes_minimized_" + point + ".png"); % Armijo Rule % Methods tuning amijo_beta = 0.4; % typical range: [0.1, 0.8] amijo_sigma = 0.1; % typical range: [0.01, 0.3] [x_armijo, f_armijo, kk] = method_steepest_descent(fun, grad_fun, x0, tol, max_iter, 'armijo'); fprintf('Armijo step: Initial point (%f, %f), steps:%d, Final (x,y)=(%f, %f), f(x,y)=%f\n', x0, kk, x_armijo(end, :), f_armijo(end)); plotPointsOverContour(x_armijo, fun, [-2, 0], [-2, 2], 100, point_str + ": Steepest descent Armijo method", "figures/StDes_armijo_" + point + ".png"); disp(' '); % Point x0 = (1, -1) % ========================================================================= point = 3; x0 = [1, -1]; point_str = "[" + x0(1) + ", " + x0(2) + "]"; f = fun(-1, 1); gf = grad_fun(x0(1), x0(2)); hf = hessian_fun(x0(1), x0(2)); fprintf('Initial point (%d, %d), f = %f, grad = [%f;%f], hessian = [%f %f ; %f %f]. Can use method\n', x0, f, gf, hf); % Find the best fixed gamma k = zeros(100, 1); j = 1; n = linspace(0.1, 1, 100); for g = n gamma_fixed_step = g; [~, ~, k(j)] = method_steepest_descent(fun, grad_fun, x0, tol, max_iter, 'fixed'); j = j + 1; end %if min(k) == max_iter % fprintf('Fixed step: Initial point (%d, %d). Can NOT use method\n', x0); %end %plotItersOverGamma(n, k, "Iteration for different $\gamma$ values", "figures/StDes_Iter_o_gamma_" + point + ".png"); %gamma_fixed_step = 1; [x_fixed, f_fixed, kk] = method_steepest_descent(fun, grad_fun, x0, tol, max_iter, 'fixed'); fprintf('Fixed step: Initial point (%f, %f), steps:%d, Final (x,y)=(%f, %f), f(x,y)=%f\n', x0, kk, x_fixed(end, :), f_fixed(end)); plotPointsOverContour(x_fixed, fun, [-1, 2], [-2, 2], 100, point_str + ": Steepest descent $\gamma$ = " + gamma_fixed_step, "figures/StDes_fixed_" + point + ".png"); % Minimized f [x_minimized, f_minimized, kk] = method_steepest_descent(fun, grad_fun, x0, tol, max_iter, 'minimized'); fprintf('Minimized f(g): Initial point (%f, %f), steps:%d, Final (x,y)=(%f, %f), f(x,y)=%f\n', x0, kk, x_minimized(end, :), f_minimized(end)); plotPointsOverContour(x_minimized, fun, [-2, 2], [-3, 2], 100, point_str + ": Steepest descent minimized $f(x_k + \gamma_kd_k)$", "figures/StDes_minimized_" + point + ".png"); % Armijo Rule % Methods tuning amijo_beta = 0.4; % typical range: [0.1, 0.8] amijo_sigma = 0.1; % typical range: [0.01, 0.3] [x_armijo, f_armijo, kk] = method_steepest_descent(fun, grad_fun, x0, tol, max_iter, 'armijo'); fprintf('Armijo step: Initial point (%f, %f), steps:%d, Final (x,y)=(%f, %f), f(x,y)=%f\n', x0, kk, x_armijo(end, :), f_armijo(end)); plotPointsOverContour(x_armijo, fun, [-1, 2], [-2, 2], 100, point_str + ": Steepest descent Armijo method", "figures/StDes_armijo_" + point + ".png");