wolffd@0: function varargout = mirtempo(x,varargin)
wolffd@0: %   t = mirtempo(x) evaluates the tempo in beats per minute (BPM).
wolffd@0: %   Optional arguments:
wolffd@0: %       mirtempo(...,'Total',m) selects not only the best tempo, but the m
wolffd@0: %           best tempos.
wolffd@0: %       mirtempo(...,'Frame',l,h) orders a frame decomposition of window
wolffd@0: %           length l (in seconds) and hop factor h, expressed relatively to
wolffd@0: %           the window length. For instance h = 1 indicates no overlap.
wolffd@0: %           Default values: l = 3 seconds and h = .1
wolffd@0: %       mirtempo(...,'Min',mi) indicates the lowest tempo taken into
wolffd@0: %           consideration, expressed in bpm.
wolffd@0: %           Default value: 40 bpm.
wolffd@0: %       mirtempo(...,'Max',ma) indicates the highest tempo taken into
wolffd@0: %           consideration, expressed in bpm.
wolffd@0: %           Default value: 200 bpm.
wolffd@0: %       mirtempo(...,s) selects the tempo estimation strategy:
wolffd@0: %           s = 'Autocor': Approach based on the computation of the
wolffd@0: %               autocorrelation. (Default strategy)
wolffd@0: %               Option associated to the mirautocor function can be
wolffd@0: %               passed here as well (see help mirautocor):
wolffd@0: %                   'Enhanced' (toggled on by default here)
wolffd@0: %           s = 'Spectrum': Approach based on the computation of the
wolffd@0: %               spectrum .
wolffd@0: %               Option associated to the mirspectrum function can be
wolffd@0: %               passed here as well (see help mirspectrum):
wolffd@0: %                   'ZeroPad' (set by default to 10000 samples)
wolffd@0: %                   'Prod' (toggled off by default)
wolffd@0: %           These two strategies can be combined: the autocorrelation
wolffd@0: %               function is translated into the frequency domain in order
wolffd@0: %               to be compared to the spectrum curve.
wolffd@0: %               tempo(...,'Autocor','Spectrum') multiplies the two curves.
wolffd@0: %           Alternatively, an autocorrelation function ac or a spectrum sp
wolffd@0: %               can be directly passed to the function tempo:
wolffd@0: %                   mirtempo(ac) or mirtempo(sp)
wolffd@0: %       The options related to the onset detection phase can be specified 
wolffd@0: %               here as well (see help mironsets):
wolffd@0: %               onset detection strategies: 'Envelope', 'DiffEnvelope'
wolffd@0: %               (corresponding to 'Envelope', 'Diff'), 'SpectralFlux,
wolffd@0: %               'Pitch', 'Log', 'Mu', 'Filterbank'
wolffd@0: %               mironsets(...,'Sum',w) specifies when to sum the channels.
wolffd@0: %                   Possible values:
wolffd@0: %                       w = 'Before': sum before the autocorrelation or
wolffd@0: %                           spectrum computation.
wolffd@0: %                       w = 'After': autocorrelation or spectrum computed
wolffd@0: %                           for each band, and summed into a "summary".
wolffd@0: %               mirenvelope options: 'HalfwaveCenter','Diff' (toggled on by
wolffd@0: %                   default here),'HalfwaveDiff','Center','Smooth',
wolffd@0: %                   'Sampling'
wolffd@0: %               mirflux options: 'Inc','Halfwave','Complex','Median'
wolffd@0: %       mirtempo(...,'Resonance',r) specifies the resonance curve, which
wolffd@0: %           emphasizes the periods that are more easily perceived.
wolffd@0: %           Possible values: 'ToiviainenSnyder' (default), 0 (toggled off)
wolffd@0: %   Optional arguments used for the peak picking (cf. help mirpeaks)
wolffd@0: %       mirtempo(...,'Contrast',thr): a threshold value. A given local
wolffd@0: %           maximum will be considered as a peak if its distance with the
wolffd@0: %           previous and successive local minima (if any) is higher than 
wolffd@0: %           this threshold. This distance is expressed with respect to the
wolffd@0: %           total amplitude of the autocorrelation function.
wolffd@0: %               if no value for thr is given, the value thr=0.1 is chosen
wolffd@0: %                   by default.
wolffd@0: %
wolffd@0: %   [t,p] = mirtempo(...) also displays the result of the signal analysis
wolffd@0: %       leading to the tempo estimation, and shows in particular the
wolffd@0: %       peaks corresponding to the tempo values.
wolffd@0:             
wolffd@0:     
wolffd@0:         sum.key = 'Sum';
wolffd@0:         sum.type = 'String';
wolffd@0:         sum.choice = {'Before','After','Adjacent',0};
wolffd@0:         sum.default = 'Before';
wolffd@0:     option.sum = sum;
wolffd@0:         
wolffd@0: %% options related to mironsets:    
wolffd@0: 
wolffd@0:         frame.key = 'Frame';
wolffd@0:         frame.type = 'Integer';
wolffd@0:         frame.number = 2;
wolffd@0:         frame.default = [0 0];
wolffd@0:         frame.keydefault = [3 .1];
wolffd@0:     option.frame = frame;
wolffd@0:     
wolffd@0:         fea.type = 'String';
wolffd@0:         fea.choice = {'Envelope','DiffEnvelope','SpectralFlux','Pitch'};
wolffd@0:         fea.default = 'Envelope';
wolffd@0:     option.fea = fea;
wolffd@0:     
wolffd@0:     %% options related to 'Envelope':
wolffd@0:     
wolffd@0:             envmeth.key = 'Method';
wolffd@0:             envmeth.type = 'String';
wolffd@0:             envmeth.choice = {'Filter','Spectro'};
wolffd@0:             envmeth.default = 'Filter';
wolffd@0:         option.envmeth = envmeth;
wolffd@0:     
wolffd@0:         %% options related to 'Filter':
wolffd@0: 
wolffd@0:                 fb.key = 'Filterbank';
wolffd@0:                 fb.type = 'Integer';
wolffd@0:                 fb.default = 10;
wolffd@0:             option.fb = fb;
wolffd@0: 
wolffd@0:                 fbtype.key = 'FilterbankType';
wolffd@0:                 fbtype.type = 'String';
wolffd@0:                 fbtype.choice = {'Gammatone','Scheirer','Klapuri'};
wolffd@0:                 fbtype.default = 'Gammatone';
wolffd@0:             option.fbtype = fbtype;
wolffd@0: 
wolffd@0:                 ftype.key = 'FilterType';
wolffd@0:                 ftype.type = 'String';
wolffd@0:                 ftype.choice = {'IIR','HalfHann'};
wolffd@0:                 ftype.default = 'IIR';
wolffd@0:             option.ftype = ftype;
wolffd@0: 
wolffd@0:         %% options related to 'Spectro':
wolffd@0:         
wolffd@0:                 band.type = 'String';
wolffd@0:                 band.choice = {'Freq','Mel','Bark','Cents'};
wolffd@0:                 band.default = 'Freq';
wolffd@0:             option.band = band;
wolffd@0: 
wolffd@0:         
wolffd@0:             chwr.key = 'HalfwaveCenter';
wolffd@0:             chwr.type = 'Boolean';
wolffd@0:             chwr.default = 0;
wolffd@0:         option.chwr = chwr;
wolffd@0: 
wolffd@0:             diff.key = 'Diff';
wolffd@0:             diff.type = 'Boolean';
wolffd@0:             diff.default = 1; % Different default for mirtempo
wolffd@0:         option.diff = diff;
wolffd@0: 
wolffd@0:             diffhwr.key = 'HalfwaveDiff';
wolffd@0:             diffhwr.type = 'Integer';
wolffd@0:             diffhwr.default = 0;
wolffd@0:             diffhwr.keydefault = 1;
wolffd@0:         option.diffhwr = diffhwr;
wolffd@0:         
wolffd@0:             lambda.key = 'Lambda';
wolffd@0:             lambda.type = 'Integer';
wolffd@0:             lambda.default = 1;
wolffd@0:         option.lambda = lambda;
wolffd@0: 
wolffd@0:             mu.key = 'Mu'; 
wolffd@0:             mu.type = 'Boolean'; 
wolffd@0:             mu.default = 0; 
wolffd@0: 	        option.mu = mu; 
wolffd@0:         
wolffd@0:             log.key = 'Log';
wolffd@0:             log.type = 'Boolean';
wolffd@0:             log.default = 0;
wolffd@0:         option.log = log;
wolffd@0: 
wolffd@0:             c.key = 'Center';
wolffd@0:             c.type = 'Boolean';
wolffd@0:             c.default = 0;
wolffd@0:         option.c = c;
wolffd@0: 
wolffd@0:             aver.key = 'Smooth';
wolffd@0:             aver.type = 'Integer';
wolffd@0:             aver.default = 0;
wolffd@0:             aver.keydefault = 30;
wolffd@0:         option.aver = aver;
wolffd@0: 
wolffd@0:             sampling.key = 'Sampling';
wolffd@0:             sampling.type = 'Integer';
wolffd@0:             sampling.default = 0;
wolffd@0:         option.sampling = sampling;
wolffd@0: 
wolffd@0:     %% options related to 'SpectralFlux'
wolffd@0:     
wolffd@0:             complex.key = 'Complex';
wolffd@0:             complex.type = 'Boolean';
wolffd@0:             complex.default = 0;
wolffd@0:         option.complex = complex;
wolffd@0: 
wolffd@0:             inc.key = 'Inc';
wolffd@0:             inc.type = 'Boolean';
wolffd@0:             inc.default = 1;
wolffd@0:         option.inc = inc;
wolffd@0: 
wolffd@0:             median.key = 'Median';
wolffd@0:             median.type = 'Integer';
wolffd@0:             median.number = 2;
wolffd@0:             median.default = [.2 1.3];
wolffd@0:         option.median = median;
wolffd@0: 
wolffd@0:             hw.key = 'Halfwave';
wolffd@0:             hw.type = 'Boolean';
wolffd@0:             hw.default = 1;
wolffd@0:         option.hw = hw;                
wolffd@0:         
wolffd@0:         
wolffd@0: %% options related to mirautocor:    
wolffd@0: 
wolffd@0:         aut.key = 'Autocor';
wolffd@0:         aut.type = 'Integer';
wolffd@0:         aut.default = 0;
wolffd@0:         aut.keydefault = 1;
wolffd@0:     option.aut = aut;            
wolffd@0:     
wolffd@0:         nw.key = 'NormalWindow';
wolffd@0:         nw.default = 0;
wolffd@0:     option.nw = nw;
wolffd@0: 
wolffd@0:         enh.key = 'Enhanced';
wolffd@0:         enh.type = 'Integers';
wolffd@0:         enh.default = 2:10;
wolffd@0:         enh.keydefault = 2:10;
wolffd@0:     option.enh = enh;
wolffd@0: 
wolffd@0:         r.key = 'Resonance';
wolffd@0:         r.type = 'String';
wolffd@0:         r.choice = {'ToiviainenSnyder','vanNoorden',0,'off','no'};
wolffd@0:         r.default = 'ToiviainenSnyder';
wolffd@0:     option.r = r;
wolffd@0: 
wolffd@0: 
wolffd@0: %% options related to mirspectrum:
wolffd@0:     
wolffd@0:         spe.key = 'Spectrum';
wolffd@0:         spe.type = 'Integer';
wolffd@0:         spe.default = 0;
wolffd@0:         spe.keydefault = 1;
wolffd@0:     option.spe = spe;
wolffd@0: 
wolffd@0:         zp.key = 'ZeroPad';
wolffd@0:         zp.type = 'Integer';
wolffd@0:         zp.default = 10000;
wolffd@0:         zp.keydefault = Inf;
wolffd@0:     option.zp = zp;
wolffd@0:     
wolffd@0:         prod.key = 'Prod';
wolffd@0:         prod.type = 'Integers';
wolffd@0:         prod.default = 0;
wolffd@0:         prod.keydefault = 2:6;
wolffd@0:     option.prod = prod;
wolffd@0: 
wolffd@0:     
wolffd@0: %% options related to the peak detection
wolffd@0: 
wolffd@0:         m.key = 'Total';
wolffd@0:         m.type = 'Integer';
wolffd@0:         m.default = 1;
wolffd@0:     option.m = m;
wolffd@0:         
wolffd@0:         thr.key = 'Contrast';
wolffd@0:         thr.type = 'Integer';
wolffd@0:         thr.default = 0.1;
wolffd@0:     option.thr = thr;
wolffd@0:         
wolffd@0:         mi.key = 'Min';
wolffd@0:         mi.type = 'Integer';
wolffd@0:         mi.default = 40;
wolffd@0:     option.mi = mi;
wolffd@0:         
wolffd@0:         ma.key = 'Max';
wolffd@0:         ma.type = 'Integer';
wolffd@0:         ma.default = 200;
wolffd@0:     option.ma = ma;
wolffd@0: 
wolffd@0:         track.key = 'Track';
wolffd@0:         track.type = 'Boolean';
wolffd@0:         track.default = 0;
wolffd@0:     option.track = track;
wolffd@0: 
wolffd@0:         pref.key = 'Pref';
wolffd@0:         pref.type = 'Integer';
wolffd@0:         pref.number = 2;
wolffd@0:         pref.default = [0 .2];
wolffd@0:     option.pref = pref;
wolffd@0:             
wolffd@0:         perio.key = 'Periodicity';
wolffd@0:         perio.type = 'Boolean';
wolffd@0:         perio.default = 0;
wolffd@0:     option.perio = perio;
wolffd@0:     
wolffd@0: specif.option = option;
wolffd@0: 
wolffd@0: varargout = mirfunction(@mirtempo,x,varargin,nargout,specif,@init,@main);
wolffd@0: 
wolffd@0: 
wolffd@0: %% INIT
wolffd@0: 
wolffd@0: function [y type] = init(x,option)
wolffd@0: if iscell(x)
wolffd@0:     x = x{1};
wolffd@0: end
wolffd@0: if option.perio
wolffd@0:     option.m = 3;
wolffd@0:     option.enh = 2:10;
wolffd@0: end
wolffd@0: if not(isamir(x,'mirautocor')) && not(isamir(x,'mirspectrum'))
wolffd@0:     if isframed(x) && strcmpi(option.fea,'Envelope') && not(isamir(x,'mirscalar'))
wolffd@0:         warning('WARNING IN MIRTEMPO: The input should not be already decomposed into frames.');
wolffd@0:         disp(['Suggestion: Use the ''Frame'' option instead.'])
wolffd@0:     end
wolffd@0:     if strcmpi(option.sum,'Before')
wolffd@0:         optionsum = 1;
wolffd@0:     elseif strcmpi(option.sum,'Adjacent')
wolffd@0:         optionsum = 5;
wolffd@0:     else
wolffd@0:         optionsum = 0;
wolffd@0:     end
wolffd@0:     if option.frame.length.val
wolffd@0:         x = mironsets(x,option.fea,'Filterbank',option.fb,...
wolffd@0:                     'FilterbankType',option.fbtype,...
wolffd@0:                     'FilterType',option.ftype,...
wolffd@0:                     'Sum',optionsum,'Method',option.envmeth,...
wolffd@0:                     option.band,'Center',option.c,...
wolffd@0:                     'HalfwaveCenter',option.chwr,'Diff',option.diff,...
wolffd@0:                     'HalfwaveDiff',option.diffhwr,'Lambda',option.lambda,...
wolffd@0:                     'Smooth',option.aver,'Sampling',option.sampling,...
wolffd@0:                     'Complex',option.complex,'Inc',option.inc,...
wolffd@0:                     'Median',option.median(1),option.median(2),...
wolffd@0:                     'Halfwave',option.hw,'Detect',0,...
wolffd@0:                     'Mu',option.mu,'Log',option.log,...
wolffd@0:                     'Frame',option.frame.length.val,...
wolffd@0:                             option.frame.length.unit,...
wolffd@0:                             option.frame.hop.val,...
wolffd@0:                             option.frame.hop.unit);
wolffd@0:     else
wolffd@0:         x = mironsets(x,option.fea,'Filterbank',option.fb,...
wolffd@0:                     'FilterbankType',option.fbtype,...
wolffd@0:                     'FilterType',option.ftype,...
wolffd@0:                     'Sum',optionsum,'Method',option.envmeth,...
wolffd@0:                     option.band,'Center',option.c,...
wolffd@0:                     'HalfwaveCenter',option.chwr,'Diff',option.diff,...
wolffd@0:                     'HalfwaveDiff',option.diffhwr,'Lambda',option.lambda,...
wolffd@0:                     'Smooth',option.aver,'Sampling',option.sampling,...
wolffd@0:                     'Complex',option.complex,'Inc',option.inc,...
wolffd@0:                     'Median',option.median(1),option.median(2),...
wolffd@0:                     'Halfwave',option.hw,'Detect',0,...
wolffd@0:                     'Mu',option.mu,'Log',option.log);
wolffd@0:     end
wolffd@0: end
wolffd@0: if option.aut == 0 && option.spe == 0
wolffd@0:     option.aut = 1;
wolffd@0: end
wolffd@0: if isamir(x,'mirautocor') || (option.aut && not(option.spe))
wolffd@0:     y = mirautocor(x,'Min',60/option.ma,'Max',60/option.mi,...
wolffd@0:           'Enhanced',option.enh,...'NormalInput','coeff',...
wolffd@0:           'Resonance',option.r,'NormalWindow',option.nw);
wolffd@0: elseif isamir(x,'mirspectrum') || (option.spe && not(option.aut))
wolffd@0:     y = mirspectrum(x,'Min',option.mi/60,'Max',option.ma/60,...
wolffd@0:                        'Prod',option.prod,...'NormalInput',...
wolffd@0:                        'ZeroPad',option.zp,'Resonance',option.r);
wolffd@0: elseif option.spe && option.aut
wolffd@0:     ac = mirautocor(x,'Min',60/option.ma,'Max',60/option.mi,...
wolffd@0:           'Enhanced',option.enh,...'NormalInput','coeff',...
wolffd@0:           'Resonance',option.r);
wolffd@0:     sp = mirspectrum(x,'Min',option.mi/60,'Max',option.ma/60,...
wolffd@0:                        'Prod',option.prod,...'NormalInput',...
wolffd@0:                        'ZeroPad',option.zp,'Resonance',option.r);
wolffd@0:     y = ac*sp;
wolffd@0: end
wolffd@0: if ischar(option.sum)
wolffd@0:     y = mirsum(y);
wolffd@0: end
wolffd@0: y = mirpeaks(y,'Total',option.m,'Track',option.track,...
wolffd@0:                'Pref',option.pref(1),option.pref(2),...
wolffd@0:                'Contrast',option.thr,'NoBegin','NoEnd',...
wolffd@0:                'Normalize','Local');
wolffd@0: type = {'mirscalar',mirtype(y)};            
wolffd@0: 
wolffd@0: 
wolffd@0: %% MAIN
wolffd@0: 
wolffd@0: function o = main(p,option,postoption)
wolffd@0: if iscell(p)
wolffd@0:     p = p{1};
wolffd@0: end
wolffd@0: pt = get(p,'TrackPrecisePos');
wolffd@0: track = 1;
wolffd@0: if isempty(pt) || isempty(pt{1})
wolffd@0:     pt = get(p,'PeakPrecisePos');
wolffd@0:     track = 0;
wolffd@0: end
wolffd@0: bpm = cell(1,length(pt));
wolffd@0: for j = 1:length(pt)
wolffd@0:     bpm{j} = cell(1,length(pt{j}));
wolffd@0:     for k = 1:length(pt{j})
wolffd@0:         ptk = pt{j}{k};
wolffd@0:         bpmk = cell(1,size(ptk,2));
wolffd@0:         for h = 1:size(ptk,3)
wolffd@0:             for l = 1:size(ptk,2)
wolffd@0:                 ptl = ptk{1,l,h};
wolffd@0:                 if isempty(ptl)
wolffd@0:                     bpmk{1,l,h} = NaN;
wolffd@0:                 else
wolffd@0:                     if isa(p,'mirautocor') && not(get(p,'FreqDomain'))
wolffd@0:                         bpmk{1,l,h} = 60./ptl;
wolffd@0:                     else
wolffd@0:                         bpmk{1,l,h} = ptl*60;
wolffd@0:                     end
wolffd@0:                 end
wolffd@0:             end
wolffd@0:         end
wolffd@0:         if track
wolffd@0:             bpmk = bpmk{1};
wolffd@0:         end
wolffd@0:         bpm{j}{k} = bpmk;
wolffd@0:     end 
wolffd@0: end
wolffd@0: t = mirscalar(p,'Data',bpm,'Title','Tempo','Unit','bpm');
wolffd@0: o = {t,p};