[NET-260] Clean up plotting

+nla/+net/+result/+plot/PermutationTestPlotter.m

@@ -1,4 +1,9 @@
 classdef PermutationTestPlotter < handle
+    %PERMUTATIONTESTPLOTTER Permutation Test Plotter
+    % This is a class (poorly named) that calls the different plotting functions for plotting results
+    % Collected here are the commands to plot results. They are called by various
+    % different classes and used for different results. Since these are called by different classes
+    % and not on the actual NetworkTestResult, I gathered all the plotting functions here.
 
     properties
         network_atlas

+nla/+net/+result/NetworkResultPlotParameter.m

@@ -35,7 +35,7 @@
             % test_method - 'no permutations', 'within network pair', 'full connectome'
 
             import nla.TriMatrix nla.TriMatrixDiag
-            % We're going to use a default filter here
+            % We're going to use a default filter here, i.e. keep everything
             if isequal(significance_filter, false)
                 significance_filter = TriMatrix(obj.number_of_networks, "logical", TriMatrixDiag.KEEP_DIAGONAL);
                 significance_filter.v = true(numel(significance_filter.v), 1);
@@ -57,6 +57,7 @@
             p_value_breakdown_label = fdr_correction.createLabel(obj.network_atlas, obj.updated_test_options,...
                 statistic_input);
 
+            % More title construction. It's all just string concatenation
             name_label = sprintf("%s %s\nP < %.2g (%s)", obj.network_test_results.test_display_name, plot_title,...
                 p_value_max, p_value_breakdown_label);
             if p_value_max == 0
@@ -145,6 +146,8 @@ function brainFigureButtonCallback(network1, network2)
             result.p_values = p_values;
         end
 
+        %%
+        % Getters for props
         function value = get.test_methods(obj)
             value = obj.network_test_results.test_methods;
         end
@@ -156,6 +159,8 @@ function brainFigureButtonCallback(network1, network2)
         function value = get.number_of_networks(obj)
             value = obj.network_atlas.numNets();
         end
+        %
+        %%
     end
 
     methods (Access = protected)
@@ -199,6 +204,7 @@ function brainFigureButtonCallback(network1, network2)
     end
 
     methods(Static)
+        % We call this in other classes, mainly whenever we rescale a plot
         function color_map = getLogColormap(default_discrete_colors, probabilities_input, p_value_max, color_map)
             log_minimum = log10(min(nonzeros(probabilities_input.v)));
             log_minimum = max([-40, log_minimum]);

+nla/+net/+result/NetworkTestResult.m

@@ -74,20 +74,25 @@
             end
         end
 
-        function output(obj, edge_test_options, updated_test_options, network_atlas, edge_test_result, flags)
-            import nla.NetworkLevelMethod
+        function output(obj, edge_test_options, updated_test_options, edge_test_result, flags)
+            % This function is here to run plots in scripting. GUI doesn't call this.
 
-            if isfield(flags, "show_nonpermuted") && flags.show_nonpermuted
-                test_method = "no_permutations";
-            elseif isfield(flags, "show_full_conn") && flags.show_full_conn
-                test_method = "full_connectome";
-            elseif isfield(flags, "show_within_net_pair") && flags.show_within_net_pair
-                test_method = "within_network_pair";
-            end
+            nla.net.result.plot.NetworkTestPlotApp(obj, edge_test_result, flags, edge_test_options,...
+                updated_test_options);
+
+            % If the above doesn't work in scripts, comment out command above and then uncomment below and use it
+
+            % if isfield(flags, "show_nonpermuted") && flags.show_nonpermuted
+            %     test_method = "no_permutations";
+            % elseif isfield(flags, "show_full_conn") && flags.show_full_conn
+            %     test_method = "full_connectome";
+            % elseif isfield(flags, "show_within_net_pair") && flags.show_within_net_pair
+            %     test_method = "within_network_pair";
+            % end
 
-            network_result_plot = nla.net.result.plot.NetworkTestPlot(obj, edge_test_result, network_atlas,...
-                test_method, edge_test_options, updated_test_options);
-            network_result_plot.drawFigure(nla.PlotType.FIGURE)
+            % network_result_plot = nla.net.result.plot.NetworkTestPlot(obj, edge_test_result, edge_test_options.net_atlas,...
+            %     test_method, edge_test_options, updated_test_options);
+            % network_result_plot.drawFigure(nla.PlotType.FIGURE)
         end
 
         function merge(obj, other_objects)

+nla/ResultPool.m

@@ -44,10 +44,10 @@ function output(obj)
             flags.plot_type = nla.PlotType.FIGURE;
             if ~islogical(obj.permutation_network_test_results)
                 for i = 1:numel(obj.permutation_network_test_results)
-                    obj.network_test_results{i}.output(obj.test_options, obj.network_test_options, obj.network_atlas,...
+                    obj.network_test_results{i}.output(obj.test_options, obj.network_test_options,...
                         obj.edge_test_results, flags);
                     obj.permutation_network_test_results{i}.output(obj.test_options, obj.network_test_options,...
-                        obj.network_atlas, obj.edge_test_results, flags);
+                        obj.edge_test_results, flags);
                 end
             end
         end

main_pipeline.m

@@ -68,7 +68,7 @@
 input_struct.prob_max = 0.05;
 input_struct.permute_method = nla.edge.permutationMethods.BehaviorVec();
 
-net_input_struct = net.genBaseInputs();
+net_input_struct = nla.net.genBaseInputs();
 net_input_struct.prob_max = 0.05;
 net_input_struct.behavior_count = 1;
 net_input_struct.d_max = 0.5;