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1 function varargout = mireventdensity(x,varargin)
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2 % e = mireventdensity(x) estimate the mean frequency of events (i.e., how
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3 % many note onsets per second) in the temporal data x.
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4
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5 % Optional arguments: Option1, Option2
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6 % Tuomas Eerola, 14.08.2008
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7 %
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8 normal.type = 'String';
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9 normal.choice = {'Option1','Option2'};
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10 normal.default = 'Option1';
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11 option.normal = normal;
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12
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13 frame.key = 'Frame';
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14 frame.type = 'Integer';
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15 frame.number = 2;
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16 frame.default = [0 0];
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17 frame.keydefault = [10 1];
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18 option.frame = frame;
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19
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20 specif.option = option;
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21
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22 specif.defaultframelength = 1.00;
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23 specif.defaultframehop = 0.5;
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24
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25 %specif.eachchunk = 'Normal';
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26 specif.combinechunk = {'Average','Concat'};
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27
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28 varargout = mirfunction(@mireventdensity,x,varargin,nargout,specif,@init,@main);
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29
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30
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31 function [x type] = init(x,option)
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32 if not(isamir(x,'mirenvelope'))
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33 if option.frame.length.val
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34 x = mironsets(x,'Klapuri99', 'Frame',option.frame.length.val,...
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35 option.frame.length.unit,...
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36 option.frame.hop.val,...
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37 option.frame.hop.unit);
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38 else
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39 x = mironsets(x,'Klapuri99');
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40 end
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41 end
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42 type = 'mirscalar';
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43
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44
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45 function e = main(o,option,postoption)
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46 if iscell(o)
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47 o = o{1};
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48 end
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49 sr = get(o,'Sampling');
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50 p = mirpeaks(o); %%%%<<<<<<< MORE OPTIONS HERE
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51 pv = get(p,'PeakVal');
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52 v = mircompute(@algo,pv,o,option,sr);
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53 e = mirscalar(o,'Data',v,'Title','Event density','Unit','per second');
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54 e = {e o};
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55
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56
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57 function e = algo(pv,o,option,sr)
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58 nc = size(o,2);
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59 nch = size(o,3);
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60 e = zeros(1,nc,nch);
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61 % for i = 1:nch
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62 % for j = 1:nc
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63 % if option.root
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64 % e(1,j,i) = norm(d(:,j,i));
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65 % else
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66 % disp('do the calc...')
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67 % % e(1,j,i) = d(:,j,i)'*d(:,j,i);
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68 % %tmp = mironsets(d,'Filterbank',10,'Contrast',0.1); % Change by TE, was only FB=20, no other params
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69 % e2 = mirpeaks(e)
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70 % [o1,o2] = mirgetdata(e);
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71 % e(1,j,i) = length(o2)/mirgetdata(mirlength(d));
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72 % end
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73 % end
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74 % end
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75 for i = 1:nch
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76 for j = 1:nc
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77 e(1,j,i) = length(pv{1,j,i});
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78 if strcmpi(option.normal,'Option1')
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79 e(1,j,i) = e(1,j,i) *sr/size(o,1);
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80 elseif strcmpi(option.normal,'Option2')
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81 pvs = pv{1};
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82 high_pvs = length(find(mean(pvs)>pvs));
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83 e(1,j,i) = high_pvs(1,j,i) *sr/size(o,1); % only those which are larger than mean
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84 end
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85 end
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86 end
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87
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88
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89
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90 %function [y orig] = eachchunk(orig,option,missing,postchunk)
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91 %y = mireventdensity(orig,option);
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92
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93
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94 %function y = combinechunk(old,new)
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95 %do = mirgetdata(old);
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96 %dn = mirgetdata(new);
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97 %y = set(old,'ChunkData',do+dn);
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