Working on 3d verification, add gurobi as solver option

code/nnv/engine/utils/lpsolver.m

@@ -32,8 +32,38 @@
         Aeq = double(Aeq); Beq = double(Beq); ub = double(ub); 
     end
 
+    if strcmp(lp_solver, 'gurobi') % no backup solver, should be better than the others
+        % Create gurobi model
+        model.obj = f; % objective function
+        model.A = [sparse(A); sparse(Aeq)]; % A must be sparse
+        model.sense = [repmat('<',size(A,1),1); repmat('=',size(Aeq,1),1)];
+        model.rhs = full([b(:); Beq(:)]); % rhs must be dense
+        if ~isempty(lb)
+            model.lb = lb;
+        else
+            model.lb = -inf(size(model.A,2),1); % default lb for MATLAB is -inf
+        end
+        if ~isempty(ub)
+            model.ub = ub;
+        end
+        % Define solver parameters
+        params = struct; % for now, leave default options/params
+        params.OutputFlag = 0; % no display
+        result = gurobi(model, params);
+        fval = result.objval; % get fval value from results
+        % get exitflag and match those of linprog for easier parsing
+        if strcmp(result.status,'OPTIMAL')
+            exitflag = "l1"; % converged to a solution
+        elseif strcmp(result.status,'UNBOUNDED')
+            exitflag = "l-5"; % problem is unbounded
+        elseif strcmp(result.status,'ITERATION_LIMIT')
+            exitflag = "l-2"; % maximum number of iterations reached
+        else
+            exitflag = "l-2"; % no feasible point found
+        end
+
     % Solve using linprog (glpk as backup)
-    if strcmp(lp_solver, 'linprog')
+    elseif strcmp(lp_solver, 'linprog')
         options = optimoptions(@linprog, 'Display','none'); 
         options.OptimalityTolerance = 1e-10; % set tolerance
         % first try solving using linprog

code/nnv/examples/Submission/WiP_3d/functions/dark_attack.m

@@ -32,10 +32,10 @@
     % Define input set as VolumeStar
     dif_vol = vol - at_vol;
     noise = -dif_vol;
-    V(:,:,:,:,1) = vol; % center of set
-    V(:,:,:,:,2) = noise; % basis vectors
-    C = [1; -1]; % constraints
-    d = [1; noise_disturbance-1];
+    V(:,:,:,:,1) = vol;            % center of set
+    V(:,:,:,:,2) = noise;          % basis vectors
+    C = [1; -1];                   % constraints
+    d = [1; noise_disturbance-1];  % constraints
     I = VolumeStar(V, C, d, 1-noise_disturbance, 1); % input set
 
 end

code/nnv/examples/Submission/WiP_3d/functions/summarize_results.m

@@ -0,0 +1,2 @@
+
+

code/nnv/examples/Submission/WiP_3d/functions/verify_instance_3d.m

@@ -1,32 +1,19 @@
-function results = verify_instance_3d(net, vol, target, attack, reachOptions, max_value, min_value)
+function results = verify_instance_3d(net, vol, target, attack, reachOptions)
     % verify medmnist with inputs (input images), targets (labels) and attack
     % (struct with adversarial attack info)
     % results =  verify_medmnist(net, matlabNet, inputs, targets, attack, max_value*, min_value*)
 
     % Check what type of attack to consider
-    if strcmp(attack.Name, 'linf')
-        epsilon = attack.epsilon;
-        max_pixels = attack.max_pixels;
-    elseif strcmp(attack.Name, 'dark') || strcmp(attack.Name, 'bright')
+    if strcmp(attack.Name, 'dark') || strcmp(attack.Name, 'bright')
         max_pixels = attack.max_pixels;
         threshold = attack.threshold;
         noise_disturbance = attack.noise_de;
     else
         error("Adversarial attack not supported.");
     end
 
-    % check if max_value and min_value are provided
-    if ~exist("max_value", 'var')
-        max_value = inf;
-    end
-    if ~exist("min_value", 'var')
-        min_value = -inf;
-    end
-
     % Choose attack
-    if strcmp(attack.Name,'linf')
-        I = L_inf_attack(vol, epsilon, max_pixels, max_value, min_value);
-    elseif strcmp(attack.Name, 'dark')
+    if strcmp(attack.Name, 'dark')
         I = dark_attack(vol, max_pixels, threshold, noise_disturbance);
     elseif strcmp(attack.Name, 'bright')
         I = bright_attack(vol, max_pixels, threshold, noise_disturbance);
@@ -48,7 +35,7 @@
         return
     end
 
-    % Check for falsification (TODO)
+    % Check for falsification 
     n_samples = 100; % number of random samples to try for falsification
     xRand = I.sample(n_samples);
     for k = 1:n_samples

code/nnv/examples/Submission/WiP_3d/run_all.m

@@ -1,53 +1,23 @@
-%% Shape only data
+%% Shape only data (3d)
 
-% poolobj = gcp('nocreate');
-% delete(poolobj);
+verify_adrenal;
 
-% verify_adrenal;
+verify_vessel;
 
-% poolobj = gcp('nocreate');
-% delete(poolobj);
+%% Volume data (general 3D)
 
-% verify_vessel;
 
-%% Volume data (general 3D)
+disp("... fracture ...");
+verify_fracture;
+
+
+disp("... nodule ...")
+verify_nodule;
+
+
+disp("... organ ...")
+verify_organ;
 
-% poolobj = gcp('nocreate');
-% delete(poolobj);
-% 
-% disp("... fracture ...");
-% try
-%     verify_fracture;
-% catch ME
-%     warning(ME.message);
-% end
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% poolobj = gcp('nocreate');
-% delete(poolobj);
-% 
-% disp("... nodule ...")
-% try
-%     verify_nodule;
-% catch ME
-%     warning(ME.message);
-% end
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% poolobj = gcp('nocreate');
-% delete(poolobj);
-
-% disp("... organ ...")
-% try
-%     verify_organ;
-% catch ME
-%     warning(ME.message);
-% end
-% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% poolobj = gcp('nocreate');
-% delete(poolobj);
 
 disp("... synapse ...")
-try
-    verify_synapse;
-catch ME
-    warning(ME.message)
-end
+verify_synapse;

code/nnv/examples/Submission/WiP_3d/verify_adrenal.m

@@ -28,6 +28,7 @@
 reachOptions = struct;
 reachOptions.reachMethod = 'relax-star-area';
 reachOptions.relaxFactor = 0.95;
+reachOptions.lp_solver = "gurobi";
 
 
 %% Attack 1