diff do_correlation.m @ 2:624231da830b

Removed name from comments. Updated readme extensively. Renamed 2 files without significant changes. Added EP data as a bonus.

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/do_correlation.m	Fri Sep 20 17:05:34 2013 +0100
@@ -0,0 +1,111 @@
+function [asig pval a a_] = do_correlation(megacube, songs, metrics, algos, algo_groups, merge_algos, merge_songs, merge_dsets, metric_labels, bonferroni)
+
+% function [asig pval a a_] = do_correlation(megacube, songs, metrics, algos, algo_groups, merge_algos, merge_songs, merge_dsets, metric_labels, bonferroni)
+%
+% Script to make and analyze correlation plot.
+% Example usage:
+%    To run your first experiment (Fig 1a) request:
+%    do_correlation(megacube, lab_measures, sind_manual1, [1:9], -1, 0, 1, -1, s_manual1)
+%
+% MEGACUBE is the giant (N songs) x (M metrics) x (L algorithms) matrix of evaluation results.
+% SONGS, METRICS and ALGOS are the indices into these three dimensions desired.
+% ALGO_GROUPS indicates groups of algorithms that should be averaged together rather than counted separately.
+%    (this has not yet been implemented)
+% Set MERGE_ALGOS > 0 in order to compute the median score across algorithms.
+% Set MERGE_SONGS > 0 in order to compute the median score across songs.
+% MERGE_DSETS is also not yet implemented.
+% METRIC_LABELS is a matrix of strings, one for each of the METRICS, for use in plotting.
+% Set BONFERRONI > 0 in order to apply a bonferroni correction of BONFERRONI. (Default value: 0.05.)
+% Note a few hard-coded decisions, such as:
+%   - significance level hard coded as 0.05.
+%   - in the image, decision that tau > 0.8 is strong, tau > 0.33 is weak, and tau < 0.33 is nothing.
+
+% Defaults and hard coding values:
+if nargin<10,
+    bonferroni = 0.05;
+end
+significant_p = 0.05;
+maxtau = 0.8;
+mintau = 0.33;
+
+
+
+tmpcube = megacube(songs,metrics,algos);
+
+% if exist('algo_groups'),
+%     for i=1:length(algo_groups),
+%         merge the groups somehow...
+%     end
+% end
+
+if merge_algos>0,                   % If we merge algorithms, take the median score across algorithms.
+    tmpcube = median(tmpcube,3);
+elseif merge_songs>0,               % If we merge songs, take the median score across songs.
+    tmpcube = median(tmpcube,1);    % Then, resize the matrix to be 2-d:
+    tmpcube = transpose(reshape(tmpcube,size(tmpcube,2),size(tmpcube,3)));
+end
+
+% Compute Kendall tau correlation:
+[a pval] = corr(tmpcube,'type','Kendall');
+% Apply bonferroni correction:
+m = length(a)*(length(a)-1)/2;
+asig = pval<significant_p;
+if bonferroni>0,
+    fprintf('Bonferroni applied.\n')
+    asig = (pval*m)<bonferroni; % This is the matrix of values that are significant.
+end
+a_ = (abs(a)>=maxtau) + (abs(a)>=mintau);
+a_ = tril(a_,-1);
+
+% A contains the correlation values themselves.
+% ASIG is a binary matrix that states whether the correlation is statistically significant.
+% A_ is a matrix of -2, -1, 0, 1 and 2s that says whether a correlation is qualitatively strong (2), qualitatively weak (1), or nada (0).
+% Sometimes values will be statistically significant, but qualitatively insignificant. We do not want to bother looking at these, so
+% let us make our pretty picture carefully.
+
+% The values we display will always be straight from A. The colour we display, to emphasize the strong correlations,
+% should be the element-wise product of A, ASIG, and A_.
+% Also:
+%   Iff tau>0.33 (a_>0), include text.
+%   Iff tau is significant (asig=1), include background.
+%   Iff tau>0.8 (a_=2), put in bold.
+%   Iff tau>0.8 AND tau is significant, invert the color of the text (because the colour will be darker).
+
+img = a_.*a.*asig;
+img = img(2:end,1:end-1);   % ignore the diagonal
+clf
+imagesc(img, [-1 1])
+for i=1:length(a_),
+    for j=1:length(a_),
+        if a_(i,j)>0,
+            % tau is >0.33 so we definitely write the value. need to determine fontface and colour.
+            % if tau>.8, put in bold
+            if abs(a_(i,j))>1,
+                fontw = 'bold';
+            else
+                fontw = 'normal';
+            end
+            if abs(a_(i,j))>1 & asig(i,j)==1,
+                textcolor = [1 1 1];
+            else
+                textcolor = [0 0 0];
+            end
+            % h = text(j-.35,i-1,num2str(a(i,j),2),'Color',textcolor);
+            h = text(j,i-1,sprintf('%.2f',a(i,j)),'Color',textcolor,'FontWeight',fontw,'FontSize',12,'HorizontalAlignment','center');
+            set(h,'HorizontalAlignment','center')
+        end
+    end
+end
+cmap_el = transpose([linspace(.3,1,50)]);
+cmap = repmat(cmap_el,1,3);
+cmap = [cmap; flipud(cmap)];
+% Alternatively:
+cmap = [ones(size(cmap_el)) cmap_el cmap_el; flipud([cmap_el cmap_el ones(size(cmap_el))])];
+colormap(cmap);
+
+set(gca,'YTickLabel',metric_labels(2:end),'YTick',(1:length(a)-1),'FontAngle','italic','FontSize',12)
+set(gca,'XTickLabel',metric_labels(1:end-1),'XTick',(1:length(a)-1),'FontAngle','italic','FontSize',12)
+% set(gcf,'Position',[1000,1000,700,300])
+% set(gca,'XTickLabel',metric_labels(2:2:end),'YTick',(1:length(a)/2))
+
+% axis([0.5, length(a)-.5, 1.5, length(a)+.5])
\ No newline at end of file