open source pkg v1

pkg/OpenFace/model_training/CCNF/CCRF/lib/CalculateYqDs.m

@@ -0,0 +1,54 @@
+function [ PrecalcYqDs ] = CalculateYqDs( n_sequences, x, similarityFNs, sparsityFNs, y)
+%CALCULATESIMILARITIES Summary of this function goes here
+%   Detailed explanation goes here
+
+    K = numel(similarityFNs);
+    K2 = numel(sparsityFNs);
+    
+    PrecalcYqDs = zeros(n_sequences, K + K2);
+    
+
+    sample_length = size(y,1);
+
+    similarities = cell(K, 1);
+    sparsities = cell(K2, 1);
+
+    Similarities = zeros([sample_length, sample_length, K+K2]);
+
+    Bs = zeros([sample_length, sample_length, K+K2]);
+
+    for k=1:K
+        similarities{k} = similarityFNs{k}(x);
+        Similarities(:,:,k) = similarities{k};
+        S = Similarities(:,:,k);
+        D =  diag(sum(S));
+        Bs(:,:,k) = D - S;
+
+    end    
+    
+    for k=1:K2
+        % this is constant so don't need to recalc
+        sparsities{k} = sparsityFNs{k}(x);
+        
+        Similarities(:,:,K+k) = sparsities{k};
+        S = Similarities(:,:,K+k);
+        D =  diag(sum(S));
+        %             PrecalcQ2s{q}(:,:,k) = D - S;
+        Bs(:,:,K+k) = D + S;
+        %             PrecalcQ2sFlat{q}{k} = PrecalcQ2s{q}{k}(logical(tril(ones(size(S)))));
+
+    end
+    
+    for q = 1 : n_sequences
+
+        % go over all of the similarity metrics and construct the
+        % similarity matrices
+        yq = y(:,q);
+   
+        for k=1:K+K2
+            PrecalcYqDs(q,k) = -yq'*Bs(:,:,k)*yq;                       
+        end
+
+    end
+end
+