Possible fix for plone/Products.CMFPlone#391. Adaptive values were be…

…ing updated in afterTrial(), making get(...,'atTrialTime',Inf) return the wrong (counterintuitive) value for the trial. In this version, the criterion correct/incorrect function is evaluated in afterTrial(), but update() is not called until beforeTrial() in the next trial.

+neurostim/+plugins/adaptive.m

@@ -17,15 +17,18 @@
     end
 
     methods (Abstract)
-        % update(s) should change the internal state of the adaptive object using the outcome of the current
-        % trial (result = TRUE/Correct or FALSE/Incorrect).
-        update(s,result);
+        % update(s) should change the internal state of the adaptive object
+        % using the value (o.lastValue) and outcome of the just-completed trial
+        % (i.e. o.lastOutcome = TRUE/Correct or FALSE/Incorrect).
+        update(s);
         % getAdaptValue returns the current parameter value from the adaptive algorithm.
         v= getAdaptValue(s);
     end
 
     properties (SetAccess=private)
         overruleValue = []; %used to manually set the adaptive parameter value (for the rest of current trial) to something other than that returned by the adaptive algorithm. Ensures update() is based on the actual tested value. 
+        lastOutcome = [];   %True/false, the outcome of the most recent trial
+        lastValue = [];     %The value of the adaptive parameter at the time the outcome was evaluated
     end
 
     methods
@@ -199,30 +202,39 @@ function overrule(x1,newValue)
         function afterTrial(o)
             % This is called after cic sends the AFTERTRIAL event
             % (in cic.run)  
-            % An emply o.design means that the adaptive parameter was
+            % An empty o.design means that the adaptive parameter was
             % assigned directly to a plugin property (probably a jitter)
             % and not part of a design. These get updated after every
             % trial, irrespective of the current condition/design. 
             % Adaptive parameters defined as part of a design only get
             % updated when "their" condition/design is the currently active
             % one.
-
             if isempty(o.design) || (strcmpi(o.cic.design,o.design) && ismember(o.cic.condition,o.conditions))% Check that this adaptive belongs to the current condition
                if o.cic.trial > o.ignoreN 
-                    % Call the derived class function to update it                
-                    correct = o.trialOutcome; % Evaluate the function that the user provided.
-                    if numel(correct)>1 
-                        error(['Your ''correct'' function in the adaptive parameter ' o.name ' does not evaluate to true or false']);
+                    % Evaluate the function that the user provided (returning correct/incorrect) and store it.
+                    %We'll use it to update the adaptive value in beforeTrial()
+                    o.lastOutcome = o.trialOutcome;
+                    if numel(o.lastOutcome)>1 
+                        error(['Your ''trialOutcome'' function in the adaptive parameter ' o.name ' does not evaluate to true or false']);
                     end
-                    update(o,correct); % Pass it to the derived class to update
-                    o.overruleValue = [];
+
+                    %Also store the value used
+                    o.lastValue = o.getValue;
                else
                    % Ignoring this trial                       
                end
             end
         end 
 
         function beforeTrial(o)
+
+            if ~isempty(o.lastOutcome)
+                % Allow the derived class to update (based on lastValue and lastOutcome)
+                update(o); 
+                o.lastOutcome = [];
+                o.lastValue = []; 
+            end
+
             %Reset the overruled value.
             o.overruleValue = [];
         end

+neurostim/+plugins/jitter.m

@@ -57,7 +57,7 @@
             update(o); % Call it once now to initialize.
         end
 
-        function update(o,~)
+        function update(o)
             % The abstract adaptive parent class requires that we implement this
             % This is called after each trial. Update the internal value. The second arg is the success of the current trial, irrelevant here.            
                 if isa(o.distribution,'function_handle')

+neurostim/+plugins/nDown1UpStaircase.m

@@ -66,12 +66,11 @@
             o.value = startValue;
         end
 
-        function update(o,correct)
+        function update(o)
             % calculate and return the updated property value
-
-            % current value
-            v = o.getValue; 
-            if correct
+            v = o.lastValue;
+
+            if o.lastOutcome
                 % increment correct count
                 o.cnt = o.cnt + 1;                
                 if o.cnt >= o.n

+neurostim/+plugins/psyBayes.m

@@ -97,14 +97,10 @@
 
         end
 
-        function update(o,response)
+        function update(o)
             % The abstract adaptive parent class requires that we implement this
-            % This is called after each trial. Update the internal value. The second arg is the success of the current trial, as determined
-            % in the parent class, using the trialResullt function
-            % specified by the user when constructing an object of this
-            % class.
-            parmValue = getValue(o); % This is the value that we used previously
-            [~,o.psy] =  psybayes(o.psy, o.method, o.vars,parmValue,response); % Call to update.
+            % This is called after each trial. Update the internal value.
+            [~,o.psy] =  psybayes(o.psy, o.method, o.vars,o.lastValue,o.lastOutcome); % Call to update.
         end
 
         function v =getAdaptValue(o)

+neurostim/+plugins/quest.m

@@ -73,17 +73,11 @@
             o.momentFun = funs{ismember({'QUANTILE','MEAN','MODE'},p.Results.pdfMoment)};
         end
 
-        function update(o,correct)
+        function update(o)
             % The abstract adaptive parent class requires that we implement this
-            % This is called after each trial. Update the internal value. The second arg is the success of the current trial, as determined
-            % in the parent class, using the trialResullt function
-            % specified by the user when constructing an object of this
-            % class.
-            parmValue = o.getValue; % This is the value that was used previously
-            intensity = o.p2i(parmValue); % Converti it to Quest intensity
-            if ~isempty(correct)
-                o.Q=QuestUpdate(o.Q,intensity,correct); % Add the new datum .
-            end
+            % This is called after each trial. Update the internal value.
+            intensity = o.p2i(o.lastValue); % Converti it to Quest intensity            
+            o.Q=QuestUpdate(o.Q,intensity,o.lastOutcome); % Add the new datum .
         end
 
         function v =getAdaptValue(o)

demos/adaptiveDemo.m

@@ -120,7 +120,7 @@
 
 % Create a block for this design and specify the repeats per design
 myBlock=block('myBlock',d);
-myBlock.nrRepeats = 10; % Because the design has 2 conditions, this results in 2*nrRepeats trials.
+myBlock.nrRepeats = 50; % Because the design has 2 conditions, this results in 2*nrRepeats trials.
 c.run(myBlock);
 
 %% Do some analysis on the data