comparison src/matlab/nmf_euclidean.m @ 0:c52bc3e8d3ad tip

user: boblsturm
branch 'default'
added README.md
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added data/.DS_Store
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added src/matlab/SA_B_NMF.m
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added src/matlab/nmfFn.m
added src/matlab/nmf_beta.m
added src/matlab/nmf_divergence.m
added src/matlab/nmf_euclidean.m
added src/matlab/prune_corpus.m
added src/matlab/rot_kernel.m
added src/matlab/templateAdditionResynth.m
added src/matlab/templateDelCb.m
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+function [Y, cost] = nmf_euclidean(V, W, varargin)
+
+if nargin > 2
+    nmf_params = varargin{1};
+    L = nmf_params.Iterations;
+    convergence = nmf_params.Convergence_criteria;
+    r = nmf_params.Repition_restriction;
+    p = nmf_params.Polyphony_restriction;
+    c = nmf_params.Continuity_enhancement;
+    rot = nmf_params.Continuity_enhancement_rot;
+    pattern = nmf_params.Diagonal_pattern;
+    endtime = nmf_params.Modification_application;
+    
+    if nmf_params.Random_seed <= 0
+        rng('shuffle');
+    else
+        rng(nmf_params.Random_seed);
+    end
+elseif nargin == 2
+    L = 10;
+    convergence = 0;
+    r = 3;
+    p = 10;
+    c = 3;
+    pattern = 'Diagonal';
+    endtime = false;
+    rng('shuffle');
+end
+
+waitbarHandle = waitbar(0, 'Starting NMF synthesis...'); 
+
+cost=0;
+targetDim=size(V);
+sourceDim=size(W);
+K=sourceDim(2);
+M=targetDim(2);
+
+H=random('unif',0, 1, K, M);
+
+num=W'*V;
+WTW = W'*W;
+
+for l=1:L-1
+    waitbar(l/(L-1), waitbarHandle, ['Computing approximation...Iteration: ', num2str(l), '/', num2str(L-1)])
+    
+    den=WTW*H;
+    H=H.*(num./den);
+    H(isnan(H))=0;
+    
+    if((r > 0 && ~endtime) || (r > 0 && endtime && l==L-1))
+        waitbar(l/(L-1), waitbarHandle, ['Repition Restriction...Iteration: ', num2str(l), '/', num2str(L-1)])
+        for k=1:K
+            %Updating H
+            for m=1:M
+                if(m>r && (m+r)<=M && H(k,m)==max(H(k,m-r:m+r)))
+                    R(k,m)=H(k,m);
+                else
+                    R(k,m)=H(k,m)*(1-(l+1)/L);
+                end
+            end
+        end
+        
+        H = R;
+    end
+    
+    if((p > 0 && ~endtime) || (p > 0 && endtime && l==L-1))
+        waitbar(l/(L-1), waitbarHandle, ['Polyphony Restriction...Iteration: ', num2str(l), '/', num2str(L-1)])
+        P = zeros(size(H));
+        mask = zeros(size(H,1),1);
+        for m = 1:size(H, 2)
+            [~, sortedIndices] = sort(H(:, m),'descend');
+            mask(sortedIndices(1:p)) = 1;
+            mask(sortedIndices(p+1:end)) = (1-(l+1)/L);
+            P(:,m)=H(:,m).*mask;
+        end
+        H = P;
+    end
+    
+    if((c > 0 && ~endtime) || (c > 0 && endtime && l==L-1))
+        waitbar(l/(L-1), waitbarHandle, ['Continuity Enhancement...Iteration: ', num2str(l), '/', num2str(L-1)])
+        switch pattern
+            case 'Diagonal'
+                C = conv2(H, rot_kernel( eye(c), rot ), 'same'); %Default
+            case 'Reverse'
+                C = conv2(H, flip(eye(c)), 'same'); %Reverse
+            case 'Blur'
+                C = conv2(H, flip(ones(c)), 'same'); %Blurring
+            case 'Vertical'
+                M = zeros(c, c); %Vertical
+                M(:, floor(c/2)) = 1;
+                C = conv2(P, M, 'same');
+        end
+        H = C;
+    end
+    
+    if ~endtime
+        den=WTW*H;
+        H=H.*(num./den);
+        H(isnan(H))=0;
+    end
+    
+    cost(l)=norm(V-W*H, 'fro'); %Frobenius norm of a matrix
+    if(l > 5 && (cost(l) > cost(l-1) || abs(((cost(l)-cost(l-1)))/max(cost))<convergence))
+        break;
+    end
+end
+
+fprintf('Iterations: %i/%i\n', l, L);
+fprintf('Convergence Criteria: %i\n', convergence*100);
+fprintf('Repitition: %i\n', r);
+fprintf('Polyphony: %i\n', p);
+fprintf('Continuity: %i\n', c);
+
+Y=H;
+Y = Y./max(max(Y));
+
+close(waitbarHandle);
+end