added statistics for connectivity dependence on delta Ori and delta xy.

atlab · Jun 23, 2014 · 45c4796 · 45c4796
1 parent 46512a9
commit 45c4796
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Showing 4 changed files with 132 additions and 263 deletions.
diff --git a/+cove/estimate.m b/+cove/estimate.m
@@ -85,7 +85,7 @@
 
     case 'lv-glasso'
         assert(length(hypers)==2)
-        cove.set('max_latent',inf)   % prevent latent variables
+        cove.set('max_latent',inf)   % allow any number of latent variables
         scale = mean(diag(C));
         extras = cove.lvglasso(C/scale,hypers(1),hypers(2),cove.set);
         extras.S = extras.S/scale;  % scale back

diff --git a/+cove/set.m b/+cove/set.m
@@ -11,7 +11,7 @@
 if isempty(STATE) || (nargin>=1 && strcmpi(name,'restore'))
     STATE = struct(...
         'refit', false, ...
-        'max_latent', 0 ...
+        'max_latent', inf ...
         );
 end
 

diff --git a/+covest/QuadLoss.m b/+covest/QuadLoss.m
@@ -2,11 +2,15 @@
 covest.QuadLoss (computed) # my newest table
 -> covest.CovMatrix
 -----
-quad_loss  :  double   #  quadratic loss value
+quad_loss=null  :  double   #  quadratic loss value
 %}
 
 classdef QuadLoss < dj.Relvar & dj.AutoPopulate
 
+    properties(Constant)
+        loss = @(S,Sigma) trace(Sigma/S-eye(size(S,1)))/size(S,1)^2;
+    end
+
     properties
         popRel  = covest.CovMatrix & 'nfolds>1'
     end
@@ -16,12 +20,12 @@
         function makeTuples(self, key)
             opt = fetch(covest.Method & key,'*');
             [k,nFolds] = fetch1(covest.Fold & key, 'k','nfolds');
-            loss = @(S,Sigma) trace(Sigma/S-eye(size(S,1)))/size(S,1)^2;
 
             % X := nBins * nDirs * nTrials * nCells
             [X,selection] = fetch1(covest.Traces*covest.ActiveCells & key, ...
                 'trace_segments', 'selection');
             X = double(X(:,:,:,selection));
+            [nBins, nDirs, nTrials, nCells] = size(X);
 
             % exclude spontaneous activity if necessary
             evokedBins = fetch1(covest.Traces & key, 'evoked_bins');
@@ -35,10 +39,19 @@ function makeTuples(self, key)
             end
 
             % split into training and testing
-            C = fetch1(covest.CovMatrix & key, 'cov_matrix');
+            [M,V,R,delta] = fetch1(covest.CovMatrix & key, ...
+                'means','variances','corr_matrix','delta');
             [~, XTest] = cove.splitTrials(X,k,nFolds);
-            CTest = cove.estimate(XTest,[],evokedBins, 'sample', {});
-            key.quad_loss = loss(C,CTest);
+            assert(~isempty(XTest))
+            X = bsxfun(@minus, X, M);            
+            V0 = reshape(nanmean(reshape(V,[],nCells)),[1 1 1 nCells]);
+            V = bsxfun(@plus,(1-delta)*V,delta*V0);
+            X = bsxfun(@rdivide, X, sqrt(V));
+            RTest = cov(reshape(X,[],nCells));
+
+
+
+            key.quad_loss = self.loss(R,RTest);
             self.insert(key)
         end
     end