CorrRSA is now more general PluginRSA

PluginRSA.m

@@ -0,0 +1,55 @@
+% RSA based on a custom function, applied to each feature in a parfor loop
+% (with optional varargs applied). This is slower than vectorised forms of
+% RSA but enables custom RSA types such as Kendall's tau.
+%
+% gl = PluginRSA(modelrdms,datardms,corrfun,[corrargs])
+classdef PluginRSA < RSA
+    properties
+        corrfun = []; % type input to matlab's corr function
+        corrargs = {};
+    end
+
+    methods
+        function gl = PluginRSA(modelrdms,datardms,corrfun,varargin)
+            % use super-class to initialise            
+            gl = gl@RSA(modelrdms,datardms);
+            assert(gl.npredictors==1,'only 1 model RDM input supported');
+            % must allow undefined corrfun to support resampling
+            % (cloneargs method is only called on new instance _after_ it
+            % has been created)
+            if ieNotDefined('corrfun')
+                corrfun = [];
+            end
+            if ischar(corrfun)
+                % insure function handle
+                corrfun = str2func(corrfun);
+            end
+            gl.corrfun = corrfun;
+            gl.corrargs = varargin;
+        end
+
+        function cloneargs(self,oldinstance)
+            % make sure corrfun and corrargs survive resampling.
+            [self.corrfun] = deal(oldinstance.corrfun);
+            [self.corrargs] = deal(oldinstance.corrargs);
+        end
+
+        function estimates = fit(self)
+        % apply some corrfun to every feature in self.data.
+        % estimates = fit(self)
+            estimates = NaN([1 self(1).nfeatures]);
+            X = vertcat(self.X);
+            data = vertcat(self.data);
+            inds = 1:self(1).nsamples;
+            fun = self.corrfun;
+            args = self.corrargs;
+            % parfor here means we will encounter nested parfor loops when
+            % e.g. bootstrapping or permutation testing. However, if we
+            % don't do this e.g searchlight mapping is likely to turn out
+            % to be ridiculously slow
+            parfor f = 1:self(1).nfeatures
+                estimates(1,f) = fun(X,data(inds,f),args{:});
+            end
+        end
+    end
+end

SplitPluginRSA.m

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+% Split RDM variant of PluginRSA.
+%
+% gl = SplitPluginRSA(modelrdms,datardms,corrtype)
+classdef SplitPluginRSA < PluginRSA & SplitRSA
+    methods
+        function gl = SplitPluginRSA(modelrdms,datardms,varargin)
+            gl = gl@SplitRSA;
+            gl = gl@PluginRSA(modelrdms,datardms,varargin{:});
+            % ideally this should be set by calling SplitRSA constructor
+            gl.nrandsamp = gl.ncon / 2;
+        end
+    end
+end