add uuid to prevent generated file conflict when running tests in par…

…allel

.gitignore

@@ -33,7 +33,7 @@ codegen/
 octave-workspace
 
 # auto-generated optimization functions
-mdocean/optimization/generated
+mdocean/optimization/generated*
 
 # html report files
 html/

mdocean/inputs/var_bounds.m

@@ -66,11 +66,7 @@
                       'pos_power','spar_damping','spar_height_up','spar_height_down','LCOE_max',...
                       'irrelevant_max_force','water_deep_enough'};
 
-% modify nominal control inputs to so power and force matches actual
-[F_max_nom, B_p_nom, w_n_nom] = deal(1e6);%find_nominal_inputs(b, false);
-b.F_max_nom = F_max_nom;
-b.B_p_nom = B_p_nom;
-b.w_n_nom = w_n_nom;
+b.filename_uuid = ''; % string to append to generated filenames to prevent parallel overlap
 
 b.X_noms = [b.D_f_nom b.D_s_ratio_nom b.h_f_ratio_nom b.T_s_ratio_nom b.F_max_nom b.B_p_nom b.w_n_nom]';
 

mdocean/optimization/gradient_optim.m

@@ -86,7 +86,7 @@
             error('x0 input struct has wrong size')
         end
 
-        [X_opt_raw,obj_opt,flag,output,lambda,grad,hess,problem] = run_solver(prob, obj_names{which_obj}, x0, opts);
+        [X_opt_raw,obj_opt,flag,output,lambda,grad,hess,problem] = run_solver(prob, obj_names{which_obj}, x0, opts, b.filename_uuid);
         probs{i} = problem;
 
                        % D_f   D_s_ratio h_f_ratio T_s_ratio F_max B_p w_n]

mdocean/optimization/multiobjective/pareto_search.m

@@ -1,6 +1,7 @@
-function [x,fval] = pareto_search()
+function [x,fval] = pareto_search(filename_uuid)
     p = parameters();
     b = var_bounds();
+    b.filename_uuid = filename_uuid;
     x0 = b.X_start_struct;
 
     %% Calculate seed points for the pareto front

mdocean/optimization/run_solver.m

@@ -1,8 +1,8 @@
-function [X_opt,obj_opt,flag,output,lambda,grad,hess,problem] = run_solver(prob, obj, x0, opts)
+function [X_opt,obj_opt,flag,output,lambda,grad,hess,problem] = run_solver(prob, obj, x0, opts, filename_uuid)
     solver_based = true;
     % create folder for generated objectives if it doesn't already exist        
     if solver_based
-        generated_folder = 'optimization/generated';
+        generated_folder = ['optimization/generated' filename_uuid];
         if ~exist(generated_folder,'dir')
             mkdir(generated_folder)
             addpath(generated_folder)

mdocean/optimization/sensitivities/gradient_mult_x0.m

@@ -1,7 +1,9 @@
+function [] = gradient_mult_x0(filename_uuid)
 clear;clc;close all
 
 p = parameters();
 b = var_bounds();
+b.filename_uuid = filename_uuid;
 
 num_runs = 100;
 objs = Inf(num_runs,2);
@@ -55,3 +57,5 @@
 percent_optimal = sum(optimal) / num_runs
 percent_optimal_given_converged = sum(optimal_and_converged) ./ sum(converged)
 percent_optimal_given_kkt = sum(optimal_and_kkt) ./ sum(kkt)
+
+end

mdocean/optimization/sensitivities/location_sensitivity.m

@@ -1,7 +1,8 @@
-function [tab] = location_sensitivity()
+function [tab] = location_sensitivity(filename_uuid)
 
 p = parameters();
 b = var_bounds();
+b.filename_uuid = filename_uuid;
 
 files = {'Humboldt_California_Wave Resource _SAM CSV.csv',...
     'PacWave-North_Oregon_Wave-Resource.csv',...

mdocean/optimization/sensitivities/param_sweep.m

@@ -1,10 +1,11 @@
-function [] = param_sweep()
+function [] = param_sweep(filename_uuid)
 
 % Brute force parameter sensitivity sweep (reoptimize for each param value)
 %% Setup
 clear;clc;%close all
 b = var_bounds();
 [p,T] = parameters();
+b.filename_uuid = filename_uuid;
 
 param_names = T.name_pretty(T.sweep);  % list of parameters to sweep
 params = T.name(T.sweep);
@@ -30,6 +31,7 @@
 %% Run optimization
 for i=1:length(params)
     p = parameters();
+    p.filename_uuid = filename_uuid;
     var_nom = p.(params{i});
     for j=1:length(ratios)
         p.(params{i}) = ratios(j) * var_nom;

mdocean/plots/all_figures.m

@@ -1,5 +1,10 @@
 % Generate all figures used in the paper
-function [success_criterion,num_figs,num_tabs,fig_names,tab_names] = all_figures( which_figs, which_tabs )
+function [success_criterion,num_figs,num_tabs,fig_names,tab_names] = all_figures( which_figs, which_tabs, filename_uuid )
+
+if nargin<3
+    filename_uuid = ''; % required argument for anything running gradient_optim in parallel,
+                        % since prob2struct needs unique filenames for code generation
+end
 
 num_figs = 10;
 num_tabs = 7;
@@ -46,21 +51,21 @@
 fig_names{6} = 'Fig. 6: pareto front';
 fig_names{7} = 'Fig. 7: design heuristics';
 if any(which_figs == 6 | which_figs == 7)  
-    pareto_search();
+    %pareto_search(filename_uuid);
     pareto_curve_heuristics()
 end
 
 %% figure 8 - parameter sensitivities
 fig_names{8} = 'Fig. 8: parameter sensitivities';
 if any(which_figs == 8)
-    param_sweep()
+    %param_sweep(filename_uuid)
 end
 
 %% figure 9, 10 - overlaid geometry, probability CDF
 fig_names{9} = 'Fig. 9: overlaid geometry';
 fig_names{10} = 'Fig. 10: probability CDF';
 if any(which_figs == 9 | which_figs == 10 | which_tabs == 5)
-    tab_5 = compare();
+    tab_5 = compare(filename_uuid);
 end
 
 %% table 1 - design variables table
@@ -103,7 +108,7 @@
 %% table 6 - optimal DVs for 4 locations
 tab_names{6} = 'Tab. 6: optimal DVs for 4 locations';
 if any(which_tabs == 6)
-    tab = location_sensitivity();
+    tab = location_sensitivity(filename_uuid);
     display(tab);
     location_flags = tab(strcmp(tab.Row,'flag'),:).Variables;
     success_criterion(end+1) = {location_flags};
@@ -112,7 +117,7 @@
 %% paragraph 4.2 - convergence for different x0s
 tab_names{7} = 'Tab. 7: convergence for different x0s';
 if any(which_tabs == 7)
-    %gradient_mult_x0()
+    %gradient_mult_x0(filename_uuid)
 end
 
 end

mdocean/plots/compare.m

@@ -1,7 +1,8 @@
-function [DV_table] = compare()
+function [DV_table] = compare(filename_uuid)
 
 p = parameters();
 b = var_bounds();
+b.filename_uuid = filename_uuid;
 x0_input = b.X_start_struct;
 
 Xs_opt = gradient_optim(x0_input,p,b);

tests/run_tests.m

@@ -26,7 +26,7 @@
 runner.addPlugin(p2);
 runner.addPlugin(p3);
 
-results = runner.run(suite);
+results = runner.runInParallel(suite);
 
 %open([cov_dir '/coverageReport/index.html'])
 open([test_dir '/testreport.pdf'])

tests/test.m

@@ -5,6 +5,7 @@
         failed
         simulated
         actual
+        uuid
     end
 
     % inputs for tests, including passing tolerances
@@ -53,12 +54,18 @@ function runNominalValidation(testCase)
             testCase.simulated = sim;
             testCase.actual    = act;
         end
+
+        function generateUUID(testCase)
+            % generate unique identifier for each parallel worker
+            % required to prevent file overalps for generated code
+            testCase.uuid = parallel.pool.Constant(@() char(matlab.lang.internal.uuid()));
+        end
     end
 
     % Test methods
     methods(Test, ParameterCombination='sequential')   
         function allFiguresRun(testCase, which_figs, which_tabs)
-            success_criterion = all_figures(which_figs,which_tabs);
+            success_criterion = all_figures(which_figs,which_tabs,testCase.uuid.Value);
             if ~isempty(success_criterion)
                 for i=1:length(success_criterion)
                     testCase.verifyGreaterThan(success_criterion{i},0);