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comparison do_correlation_analyses.m @ 2:624231da830b

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Removed name from comments. Updated readme extensively. Renamed 2 files without significant changes. Added EP data as a bonus.
author Jordan Smith <jordan.smith@eecs.qmul.ac.uk>
date Fri, 20 Sep 2013 17:05:34 +0100
parents 818a4b5f3384
children 92b5a46bc67b
comparison
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1:818a4b5f3384 2:624231da830b
10 % First, generate figure 1a. For that, we call the function DO_CORRELATION. 10 % First, generate figure 1a. For that, we call the function DO_CORRELATION.
11 % Type HELP DO_CORRELATION to understand what all the arguments mean... The short of it 11 % Type HELP DO_CORRELATION to understand what all the arguments mean... The short of it
12 % is that we select the songs, metrics and algorithms to compare, and then choose 12 % is that we select the songs, metrics and algorithms to compare, and then choose
13 % whether to take the median across all songs or across all algorithms. 13 % whether to take the median across all songs or across all algorithms.
14 14
15 [asig pval a a_] = do_correlation3(megadatacube, lab_measures, indexing_info(1).manual_set, [1:9],... 15 [asig pval a a_] = do_correlation(megadatacube, lab_measures, indexing_info(1).manual_set, [1:9],...
16 0, 0, 1, 0, indexing_info(1).labels, 0.05); 16 0, 0, 1, 0, indexing_info(1).labels, 0.05);
17 saveas(gcf,'./plots/fig1a.jpg') 17 saveas(gcf,'./plots/fig1a.jpg')
18 18
19 [asig pval a a_] = do_correlation3(megadatacube, lab_measures, indexing_info(1).manual_set, [1:9],... 19 [asig pval a a_] = do_correlation(megadatacube, lab_measures, indexing_info(1).manual_set, [1:9],...
20 0, 1, 0, 0, indexing_info(1).labels, 0.05); 20 0, 1, 0, 0, indexing_info(1).labels, 0.05);
21 saveas(gcf,'./plots/fig1b.jpg') 21 saveas(gcf,'./plots/fig1b.jpg')
22 22
23 [asig pval a a_] = do_correlation3(megadatacube, seg_measures, indexing_info(2).manual_set, [1:9],... 23 [asig pval a a_] = do_correlation(megadatacube, seg_measures, indexing_info(2).manual_set, [1:9],...
24 0, 0, 1, 0, indexing_info(2).labels, 0.05); 24 0, 0, 1, 0, indexing_info(2).labels, 0.05);
25 saveas(gcf,'./plots/fig2a.jpg') 25 saveas(gcf,'./plots/fig2a.jpg')
26 26
27 [asig pval a a_] = do_correlation3(megadatacube, seg_measures, indexing_info(2).manual_set, [1:9],... 27 [asig pval a a_] = do_correlation(megadatacube, seg_measures, indexing_info(2).manual_set, [1:9],...
28 0, 1, 0, 0, indexing_info(2).labels, 0.05); 28 0, 1, 0, 0, indexing_info(2).labels, 0.05);
29 saveas(gcf,'./plots/fig2b.jpg') 29 saveas(gcf,'./plots/fig2b.jpg')
30 30
31 [asig pval a a_] = do_correlation3_fig3_only(megadatacube, lab_measures, [indexing_info(1).manual_set indexing_info(2).manual_set], [1:9], 0, 1, 0, 0, indexing_info(2).all_labels([indexing_info(1).manual_set indexing_info(2).manual_set]), 1, indexing_info(3).manual_set, indexing_info(3).labels); 31 [asig pval a a_] = do_correlation_fig3_only(megadatacube, lab_measures, [indexing_info(1).manual_set indexing_info(2).manual_set], [1:9], 0, 1, 0, 0, indexing_info(2).all_labels([indexing_info(1).manual_set indexing_info(2).manual_set]), 1, indexing_info(3).manual_set, indexing_info(3).labels);
32 saveas(gcf,'./plots/fig3.jpg') 32 saveas(gcf,'./plots/fig3.jpg')
33 33
34 34
35 do blah 35 do blah
36 % % % % % % % % % % % % The rest of this is still under construction, so I have inserted an error in the previous line to halt the script. 36 % % % % % % % % % % % % The rest of this is still under construction, so I have inserted an error in the previous line to halt the script.
37 37
38 % Are the trends qualitatively similar across datasets? 38 % Are the trends qualitatively similar across datasets?
39 % Fig 1a 39 % Fig 1a
40 figure,[asig pval a a_] = do_correlation3(megadatacube, lab_measures, indexing_info(1).manual_set, [1:9], -1, 0, 1, -1, indexing_info(1).labels, 1); 40 figure,[asig pval a a_] = do_correlation(megadatacube, lab_measures, indexing_info(1).manual_set, [1:9], -1, 0, 1, -1, indexing_info(1).labels, 1);
41 figure,[asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,1), indexing_info(1).manual_set, [1:9], -1, 0, 1, -1, indexing_info(1).labels, 1); 41 figure,[asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,1), indexing_info(1).manual_set, [1:9], -1, 0, 1, -1, indexing_info(1).labels, 1);
42 figure,[asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,3), indexing_info(1).manual_set, [1:9], -1, 0, 1, -1, indexing_info(1).labels, 1); 42 figure,[asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,3), indexing_info(1).manual_set, [1:9], -1, 0, 1, -1, indexing_info(1).labels, 1);
43 figure,[asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,4), indexing_info(1).manual_set, [1:9], -1, 0, 1, -1, indexing_info(1).labels, 1); 43 figure,[asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,4), indexing_info(1).manual_set, [1:9], -1, 0, 1, -1, indexing_info(1).labels, 1);
44 % Fig 1b 44 % Fig 1b
45 figure, [asig pval a a_] = do_correlation3(megadatacube, lab_measures, sind_manual1, [1:9], -1, 1, 0, -1, indexing_info(1).labels, 1); 45 figure, [asig pval a a_] = do_correlation(megadatacube, lab_measures, sind_manual1, [1:9], -1, 1, 0, -1, indexing_info(1).labels, 1);
46 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,1), indexing_info(1).manual_set, [1:9], -1, 1, 0, -1, indexing_info(1).labels, 1); 46 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,1), indexing_info(1).manual_set, [1:9], -1, 1, 0, -1, indexing_info(1).labels, 1);
47 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,3), indexing_info(1).manual_set, [1:9], -1, 1, 0, -1, indexing_info(1).labels, 1); 47 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,3), indexing_info(1).manual_set, [1:9], -1, 1, 0, -1, indexing_info(1).labels, 1);
48 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,4), indexing_info(1).manual_set, [1:9], -1, 1, 0, -1, indexing_info(1).labels, 1); 48 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,4), indexing_info(1).manual_set, [1:9], -1, 1, 0, -1, indexing_info(1).labels, 1);
49 % Fig 2a 49 % Fig 2a
50 figure, [asig pval a a_] = do_correlation3(megadatacube, seg_measures, sind_manual2, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1); 50 figure, [asig pval a a_] = do_correlation(megadatacube, seg_measures, sind_manual2, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1);
51 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,1), indexing_info(2).manual_set, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1); 51 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,1), indexing_info(2).manual_set, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1);
52 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,2), indexing_info(2).manual_set, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1); 52 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,2), indexing_info(2).manual_set, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1);
53 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,3), indexing_info(2).manual_set, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1); 53 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,3), indexing_info(2).manual_set, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1);
54 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,4), indexing_info(2).manual_set, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1); 54 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,4), indexing_info(2).manual_set, [1:9], -1, 0, 1, -1, indexing_info(2).labels, 1);
55 % Fig 2b 55 % Fig 2b
56 figure, [asig pval a a_] = do_correlation3(megadatacube, seg_measures, sind_manual2, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1); 56 figure, [asig pval a a_] = do_correlation(megadatacube, seg_measures, sind_manual2, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1);
57 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,1), indexing_info(2).manual_set, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1); 57 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,1), indexing_info(2).manual_set, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1);
58 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,2), indexing_info(2).manual_set, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1); 58 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,2), indexing_info(2).manual_set, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1);
59 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,3), indexing_info(2).manual_set, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1); 59 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,3), indexing_info(2).manual_set, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1);
60 figure, [asig pval a a_] = do_correlation3(megadatacube, ismember(mirex_dset_origin,4), indexing_info(2).manual_set, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1); 60 figure, [asig pval a a_] = do_correlation(megadatacube, ismember(mirex_dset_origin,4), indexing_info(2).manual_set, [1:9], -1, 1, 0, -1, indexing_info(2).labels, 1);
61 61
62 62
63 % "Does this indicate that the algorithms are better at boundary precision than recall? In fact, the opposite is the case: average bp6 bp.5 was simply consistently worse for most algorithms." 63 % "Does this indicate that the algorithms are better at boundary precision than recall? In fact, the opposite is the case: average bp6 bp.5 was simply consistently worse for most algorithms."
64 % For all algos: 64 % For all algos:
65 mean(median(megadatacube(:,sind_manual2,:),3),1) 65 mean(median(megadatacube(:,sind_manual2,:),3),1)