comparison notes/cplcaMT-annotated.m @ 5:ed9e20b6b165

Begin annotating the m files

+function [w,h,z,u,xa] = cplcaMT( x, K, T, R, w, h, z, u, iter, sw, sh, sz, su, lw, lh, lz, lu, pa)
+% function [w,h,xa2] = cplcaMT( x, K, T, R, w, h, z, u, iter, sw, sh, sz, su, lw, lh, lz, lu)
+%
+% Perform multiple-source, multiple-template SIPLCA for transcription
+%
+% Inputs:
+%  x     input distribution
+%  K     number of components
+%  T     size of components
+%  R     size of sources
+%  w     initial value of p(w) [default = random]
+%  h     initial value of p(h) [default = random]
+%  z     initial value of p(z) [default = random]
+%  iter  number of EM iterations [default = 10]
+%  sw    sparsity parameter for w [default = 1]
+%  sh    sparsity parameter for h [default = 1]
+%  sz    sparsity parameter for z [default = 1]
+%  lw    flag to update w [default = 1]
+%  lh    flag to update h [default = 1]
+%  lh    flag to update h [default = 1]
+%  pa    source-component activity range [Rx2]
+%
+% Outputs: 
+%  w   p(w) - spectral bases
+%  h   p(h) - pitch impulse
+%  z   p(z) - mixing matrix for p(h)
+%  xa  approximation of input
+
+% Emmanouil Benetos 2011, based on cplca code by Paris Smaragdis
+
+
+%% for the transcription application,
+%% x -> noise-reduced constant Q. In the application this is a 2-sec,
+%%   100-col segment with 2 zeros at top and bottom, so 549x100
+%% K -> 88, number of notes
+%% T -> [545 1], a two-element array: 545 is the length of each
+%%   template, but why 1?
+%% R -> 10, number of instruments
+%% w -> a 10x88 cell array, in which w{instrument,note} is a 545x1
+%%   array containing the template for the given instrument and note
+%%   number
+%% h -> empty
+%% z -> empty
+%% u -> empty
+%% iter -> a parameter for the program, 12 in the mirex submission
+%% sw -> 1
+%% sh -> 1
+%% sz -> 1.1
+%% su -> 1.3, not documented above, presumably sparsity for u
+%% lw -> 0, don't update w
+%% lh -> 1, do update h
+%% lz -> 1, do update z
+%% lu -> 1, not documented above, presumably do update u
+%% pa -> a 10x2 array in which pa(instrument,1) is the lowest note
+%%   expected for that instrument and pa(instrument,2) is the highest
+
+
+% Sort out the sizes
+
+wc = 2*size(x)-T; %% works out to 553x199
+hc = size(x)+T-1; %% works out to 1093x100
+
+% Default training iterations
+if ~exist( 'iter')
+	iter = 10;
+end
+
+
+% Initialize
+sumx = sum(x); %% for later normalisation
+
+if ~exist( 'w') || isempty( w)
+    %% doesn't happen, w was provided (it's the template data)
+    w = cell(R, K);
+	for k = 1:K
+        for r=1:R
+            w{r,k} = rand( T);
+            w{r,k} = w{r,k} / sum( w{r,k}(:));
+        end
+    end
+end
+if ~exist( 'h') || isempty( h)
+    %% does happen, h was not provided
+    h = cell(1, K);
+	for k = 1:K
+		h{k} = rand( size(x)-T+1);
+		h{k} = h{k};
+	end
+    %% h is now a 1x88 cell, h{note} is a 5x100 array of random values.
+    %% The 5 comes from the height of the CQ array minus the length of
+    %% a template, plus 1. I guess this is space to allow for the
+    %% 5-bins-per-semitone pitch shift.
+end
+if ~exist( 'z') || isempty( z)
+    %% does happen, z was not provided
+    z = cell(1, K);
+	for k = 1:K
+		z{k} = rand( size(x,2),1);
+		z{k} = z{k};
+	end
+    %% z is a 1x88 cell, z{note} is a 100x1 array of random values.
+end
+if ~exist( 'u') || isempty( u)
+    %% does happen, u was not provided
+    u = cell(R, K);
+	for k = 1:K
+        for r=1:R
+            if( (pa(r,1) <= k &&  k <= pa(r,2)) )
+                u{r,k} = ones( size(x,2),1);
+            else
+                u{r,k} = zeros( size(x,2),1);
+            end
+        end;
+	end
+    %% u is a 10x88 cell, u{instrument,note} is a 100x1 double containing
+    %% all 1s if note is in-range for instrument and all 0s otherwise
+end
+
+fh = cell(1, K);
+fw = cell(R, K);
+for k = 1:K
+    fh{k} = ones(wc) + 1i*ones(wc);
+    for r=1:R
+        fw{r,k} = ones(wc) + 1i*ones(wc);
+    end;
+end;
+
+
+
+% Make commands for subsequent multidim operations and initialize fw
+fnh = 'c(hc(1)-(T(1)+(1:size(h{k},1))-2),hc(2)-(T(2)+(1:size(h{k},2))-2))';
+xai = 'xa(1:size(x,1),1:size(x,2))';
+flz = 'xbar(end:-1:1,end:-1:1)';
+
+for k = 1:K
+    for r=1:R
+        if( (pa(r,1) <= k &&  k <= pa(r,2)) )
+            fw{r,k} = fftn( w{r,k}, wc);
+        end;
+    end;
+end;
+
+% Iterate
+for it = 1:iter
+    
+    %disp(['Iteration: ' num2str(it)]);
+    
+    % E-step
+    xa = eps;
+    for k = 16:73
+        fh{k} = fftn( h{k}, wc);
+        for r=1:R
+            if( (pa(r,1) <= k &&  k <= pa(r,2)) )
+                xa1 = abs( real( ifftn( fw{r,k} .* fh{k})));                
+                xa = xa + xa1(1:size(x,1),1:size(x,2)) .*repmat(z{k},1,size(x,1))'.*repmat(u{r,k},1,size(x,1))';
+                clear xa1;
+            end
+        end
+    end
+    
+    xbar = x ./ xa;
+    xbar = eval( flz);
+    fx = fftn( xbar, wc);
+    
+    
+    % M-step
+    for k = 16:73
+        
+        
+        % Update h, z, u
+        nh=eps;
+        for r=1:R
+            if( (pa(r,1) <= k &&  k <= pa(r,2)) )
+                c = abs( real( ifftn( fx .* fw{r,k} )));
+                nh1 = eval( fnh);
+                nh1 = nh1 .*repmat(u{r,k},1,size(h{k},1))';
+                nh = nh + nh1;
+                
+                nhu = eval( fnh);
+                nhu = nhu .* h{k};
+                nu = sum(nhu)';
+                nu = u{r,k} .* nu + eps;
+                if lu
+                    u{r,k} = nu;
+                end;
+                
+            end;
+        end
+        nh = h{k} .* (nh.^sh);
+        nz = sum(nh)';
+        nz = z{k} .* nz + eps;
+        
+        
+        % Assign and normalize
+        if lh
+            h{k} = nh;
+        end
+        if lz
+            z{k} = nz;
+        end
+        
+        
+    end
+    
+    % Normalize z over t
+    if lz
+        Z=[]; for i=1:K Z=[Z z{i}]; end;
+        Z = Z.^sz;
+        Z(1:end,1:15)=0;
+        Z(1:end,74:88)=0;
+        Z = Z./repmat(sum(Z,2),1,K); z = num2cell(Z,1); %figure; imagesc(imrotate(Z,90));
+    end
+    
+    % Normalize u over z,t
+    if lu
+        U=[]; for r=1:R U(r,:,:) = cell2mat(u(r,:)); end;
+        for i=1:size(U,2) for j=1:size(U,3) U(:,i,j) = U(:,i,j).^su; U(:,i,j) = U(:,i,j) ./ sum(U(:,i,j)); end; end;
+        U0 = permute(U,[2 1 3]); u = squeeze(num2cell(U0,1));
+    end
+    
+    % Normalize h over z,t
+    H=[]; for k=1:K H(k,:,:) = cell2mat(h(k)); end; H0 = permute(H,[2 1 3]);
+    for i=1:size(H0,2) for j=1:size(H0,3) H0(:,i,j) = sumx(j)* (H0(:,i,j) ./ sum(H0(:,i,j))); end; end;
+    h = squeeze(num2cell(squeeze(H0),[1 3])); for k=1:K h{k} = squeeze(h{k}); end;
+    
+    %figure; imagesc(imrotate(xa',90));
+    
+end
+
+%figure; imagesc(imrotate(xa',90));