added subjective time function plot, #184, #147

ddToolbox/models/parametric_models/bens_new_model/ExponentialPower.m

@@ -29,11 +29,23 @@ function experimentMultiPanelFigure(obj, ind)
             obj.plot_density_alpha_epsilon(h(1), ind)
             obj.plot_psychometric_function(h(2), ind)
             obj.plot_discount_function_parameters(h(3), ind)
-            % TODO: PLOT OF SUBJECTIVE TIME FUNCTION HERE
+            obj.plot_subjective_time_function(h(4), ind)
             obj.plot_discount_function(h(5), ind)
         end
 
-
 	end
+
+
+    methods (Access = protected)
+
+        function plot_subjective_time_function(obj, subplot_handle, ind)
+            discountFunctionVariables = obj.getGiscountFunctionVariables();
+            subplot(subplot_handle)
+            subjectiveTimeFun = SubjectiveTimePowerFunction('samples',...
+                obj.coda.getSamplesAtIndex_asStochastic(ind, discountFunctionVariables));
+            subjectiveTimeFun.plot(obj.plotOptions.pointEstimateType)
+        end
+
+    end
 
 end

ddToolbox/models/parametric_models/bens_new_model/SubjectiveTimePowerFunction.m

@@ -0,0 +1,55 @@
+classdef SubjectiveTimePowerFunction < DeterministicFunction
+	%SubjectiveTimePowerFunction
+
+	methods (Access = public)
+
+		function obj = SubjectiveTimePowerFunction(varargin)
+			obj = obj@DeterministicFunction(varargin{:});
+		end
+
+		function plot(obj, pointEstimateType)
+
+			%% PLOT N SAMPLES
+			x = [0:1:365];
+			try
+				plot(x, obj.eval(x, 'nExamples', 100), '-', 'Color',[0.5 0.5 0.5 0.1])
+			catch
+				% backward compatability
+				plot(x, obj.eval(x, 'nExamples', 100), '-', 'Color',[0.5 0.5 0.5])
+			end
+
+			hold on
+			%% Plot point estimate
+			y = obj.eval(x, 'pointEstimateType', pointEstimateType);
+			plot(x, y, '-',...
+				'Color', 'k',...
+				'LineWidth', 2)
+
+			%% Formatting
+			xlabel('objective time', 'interpreter','latex')
+			ylabel('subjective time', 'interpreter','latex')
+			box off
+			axis square
+            axis tight
+		end
+
+	end
+
+
+	methods (Static, Access = protected)
+
+		function y = function_evaluation(x, theta)
+			if verLessThan('matlab','9.1')
+                y = bsxfun(@times, ...
+                        bsxfun(@power, x, theta.tau),...
+                        theta.k);
+			else
+				% use new array broadcasting in 2016b
+				y = theta.k * (x ^ theta.tau);
+			end
+		end
+
+	end
+
+
+end

ddToolbox/models/parametric_models/ebert_and_prelec_2007/EbertPrelec.m

@@ -17,7 +17,35 @@
 
             obj.plotOptions.dataPlotType = '2D';
 		end
-
+
+        % Override this function from superclass
+        function experimentMultiPanelFigure(obj, ind)
+            latex_fig(12, 14, 3)
+            h = layout([1 2 3 4 5]);
+            opts.pointEstimateType	= obj.plotOptions.pointEstimateType;
+            opts.timeUnits			= obj.timeUnits;
+            opts.dataPlotType		= obj.plotOptions.dataPlotType;
+
+            obj.plot_density_alpha_epsilon(h(1), ind)
+            obj.plot_psychometric_function(h(2), ind)
+            obj.plot_discount_function_parameters(h(3), ind)
+            obj.plot_subjective_time_function(h(4), ind)
+            obj.plot_discount_function(h(5), ind)
+        end
+
 	end
 
+
+    methods (Access = protected)
+
+        function plot_subjective_time_function(obj, subplot_handle, ind)
+            discountFunctionVariables = obj.getGiscountFunctionVariables();
+            subplot(subplot_handle)
+            subjectiveTimeFun = SubjectiveTimePowerFunction('samples',...
+                obj.coda.getSamplesAtIndex_asStochastic(ind, discountFunctionVariables));
+            subjectiveTimeFun.plot(obj.plotOptions.pointEstimateType)
+        end
+
+    end
+
 end