wolffd@0: function varargout = miraudio(orig,varargin)
wolffd@0: %   a = miraudio('filename') loads the sound file 'filename' (in WAV or AU
wolffd@0: %       format) into a miraudio object.
wolffd@0: %   a = miraudio('Folder') loads all the sound files in the CURRENT folder
wolffd@0: %       into a miraudio object.
wolffd@0: %   a = miraudio(v,sr), where v is a column vector, translates the vector v
wolffd@0: %       into a miraudio object. The sampling frequency is set to sr Hertz.
wolffd@0: %           Default value for sr: 44100 Hz.
wolffd@0: %   a = miraudio(b, ...), where b is already a miraudio object, performs 
wolffd@0: %       operations on b specified by the optional arguments (see below).
wolffd@0: %
wolffd@0: %   Transformation options:
wolffd@0: %       miraudio(...,'Mono',0) does not perform the default summing of
wolffd@0: %           channels into one single mono track, but instead stores each 
wolffd@0: %           channel of the initial soundfile separately.       
wolffd@0: %       miraudio(...,'Center') centers the signals.
wolffd@0: %       miraudio(...,'Sampling',r) resamples at sampling rate r (in Hz).
wolffd@0: %           (Requires the Signal Processing Toolbox.)
wolffd@0: %       miraudio(...,'Normal') normalizes with respect to RMS energy.
wolffd@0: %   Extraction options:
wolffd@0: %       miraudio(...,'Extract',t1,t2,u,f) extracts the signal between dates
wolffd@0: %           t1 and t2, expressed in the unit u.
wolffd@0: %           Possible values for u:
wolffd@0: %               's' (seconds, by default),
wolffd@0: %               'sp' (sample index, starting from 1).
wolffd@0: %           The additional optional argument f indicates the referential
wolffd@0: %               origin of the temporal positions. Possible values for f:
wolffd@0: %               'Start' (by default)
wolffd@0: %               'Middle' (of the sequence)
wolffd@0: %               'End' of the sequence
wolffd@0: %               When using 'Middle' or 'End', negative values for t1 or t2
wolffd@0: %               indicate values before the middle or the end of the audio
wolffd@0: %               sequence.
wolffd@0: %       miraudio(...,'Trim') trims the pseudo-silence beginning and end off
wolffd@0: %           the audio file. Silent frames are frames with RMS below t times
wolffd@0: %           the medium RMS of the whole audio file.
wolffd@0: %               Default value: t = 0.06
wolffd@0: %           instead of 'Trim':
wolffd@0: %              'TrimStart' only trims the beginning of the audio file,
wolffd@0: %              'TrimEnd' only trims the end.
wolffd@0: %           miraudio(...,'TrimThreshold',t) specifies the trimming threshold t.
wolffd@0: %       miraudio(...,'Channel',c) or miraudio(...,'Channels',c) selects the
wolffd@0: %           channels indicated by the (array of) integer(s) c.
wolffd@0: %   Labeling option:
wolffd@0: %       miraudio(...,'Label',l) labels the audio signal(s) following the 
wolffd@0: %           label(s) l.
wolffd@0: %           If l is a (series of) number(s), the audio signal(s) are
wolffd@0: %           labelled using the substring of their respective file name of 
wolffd@0: %           index l. If l=0, the audio signal(s) are labelled using the
wolffd@0: %           whole file name.
wolffd@0: 
wolffd@0: 
wolffd@0: if isnumeric(orig)
wolffd@0:     if size(orig,2) > 1 || size(orig,3) > 1
wolffd@0:         mirerror('MIRAUDIO','Only column vectors can be imported into mirtoolbox.');
wolffd@0:     end
wolffd@0:     if nargin == 1
wolffd@0:         f = 44100;
wolffd@0:     else
wolffd@0:         f = varargin{1};
wolffd@0:     end
wolffd@0:     b = 32;
wolffd@0:     if size(orig,1) == 1
wolffd@0:         orig = orig';
wolffd@0:     end
wolffd@0:     tp = (0:size(orig,1)-1)'/f;
wolffd@0:     t = mirtemporal([],'Time',{{tp}},'Data',{{orig}},...
wolffd@0:                     'FramePos',{{tp([1 end])}},'Sampling',{f},...
wolffd@0:                     'Name',{inputname(1)},'Label',{{}},'Clusters',{{}},...
wolffd@0:                     'Channels',[],'Centered',0,'NBits',{b},...
wolffd@0:                     'Title','Audio signal',...
wolffd@0:                     'PeakPos',{{{}}},'PeakVal',{{{}}},'PeakMode',{{{}}});
wolffd@0:     aa.fresh = 1;
wolffd@0:     varargout = {class(aa,'miraudio',t)};
wolffd@0:     return
wolffd@0: end
wolffd@0: 
wolffd@0: 
wolffd@0:         center.key = 'Center';
wolffd@0:         center.type = 'Boolean';
wolffd@0:         center.default = 0;
wolffd@0:         center.when = 'After';
wolffd@0:     option.center = center;
wolffd@0:         
wolffd@0:         normal.key = 'Normal';
wolffd@0:         normal.type = 'Boolean';
wolffd@0:         normal.default = 0;
wolffd@0:         normal.when = 'After';
wolffd@0:     option.normal = normal;
wolffd@0:     
wolffd@0:         extract.key = {'Extract','Excerpt'};
wolffd@0:         extract.type = 'Integer';
wolffd@0:         extract.number = 2;
wolffd@0:         extract.default = [];
wolffd@0:         extract.unit = {'s','sp'};
wolffd@0:         extract.defaultunit = 's';
wolffd@0:         extract.from = {'Start','Middle','End'};
wolffd@0:         extract.defaultfrom = 'Start';
wolffd@0:     option.extract = extract;
wolffd@0:         
wolffd@0:         trim.type = 'String';
wolffd@0:         trim.choice = {'NoTrim','Trim','TrimBegin','TrimStart','TrimEnd'};
wolffd@0:         trim.default = 'NoTrim';
wolffd@0:         trim.when = 'After';
wolffd@0:     option.trim = trim;
wolffd@0:         
wolffd@0:         trimthreshold.key = 'TrimThreshold';
wolffd@0:         trimthreshold.type = 'Integer';
wolffd@0:         trimthreshold.default = .06;
wolffd@0:         trimthreshold.when = 'After';
wolffd@0:     option.trimthreshold = trimthreshold;
wolffd@0:         
wolffd@0:         label.key = 'Label';
wolffd@0:         label.default = '';
wolffd@0:         label.when = 'After';
wolffd@0:     option.label = label;
wolffd@0:         
wolffd@0:         sampling.key = 'Sampling';
wolffd@0:         sampling.type = 'Integer';
wolffd@0:         sampling.default = 0;
wolffd@0:         sampling.when = 'Both';
wolffd@0:     option.sampling = sampling;
wolffd@0:         
wolffd@0:    %     segment.key = 'Segment';
wolffd@0:    %     segment.type = 'Integer';
wolffd@0:    %     segment.default = [];
wolffd@0:    %     segment.when = 'After';
wolffd@0:    % option.segment = segment;
wolffd@0: 
wolffd@0:         reverse.key = 'Reverse';
wolffd@0:         reverse.type = 'Boolean';
wolffd@0:         reverse.default = 0;
wolffd@0:         reverse.when = 'After';
wolffd@0:     option.reverse = reverse;
wolffd@0: 
wolffd@0:         mono.key = 'Mono';
wolffd@0:         mono.type = 'Boolean';
wolffd@0:         mono.default = NaN;
wolffd@0:         mono.when = 'After';
wolffd@0:     option.mono = mono;    
wolffd@0: 
wolffd@0:         separate.key = 'SeparateChannels';
wolffd@0:         separate.type = 'Boolean';
wolffd@0:         separate.default = 0;
wolffd@0:     option.separate = separate;    
wolffd@0:     
wolffd@0:         Ch.key = {'Channel','Channels'};
wolffd@0:         Ch.type = 'Integer';
wolffd@0:         Ch.default = [];
wolffd@0:         Ch.when = 'After';
wolffd@0:     option.Ch = Ch;
wolffd@0:         
wolffd@0: specif.option = option;
wolffd@0: 
wolffd@0: specif.beforechunk = {@beforechunk,'normal'};
wolffd@0: specif.eachchunk = @eachchunk;
wolffd@0: specif.combinechunk = @combinechunk;
wolffd@0: 
wolffd@0: if nargin > 1 && ischar(varargin{1}) && strcmp(varargin{1},'Now')
wolffd@0:     if nargin > 2
wolffd@0:         extract = varargin{2};
wolffd@0:     else
wolffd@0:         extract = [];
wolffd@0:     end
wolffd@0:     para = [];
wolffd@0:     varargout = {main(orig,[],para,[],extract)};
wolffd@0: else
wolffd@0:     varargout = mirfunction(@miraudio,orig,varargin,nargout,specif,@init,@main);
wolffd@0: end
wolffd@0: if isempty(varargout)
wolffd@0:     varargout = {{}};
wolffd@0: end
wolffd@0: 
wolffd@0: 
wolffd@0: function [x type] = init(x,option)
wolffd@0: if isa(x,'mirdesign')
wolffd@0:     if option.sampling
wolffd@0:         x = setresampling(x,option.sampling);
wolffd@0:     end
wolffd@0: end
wolffd@0: type = 'miraudio';
wolffd@0: 
wolffd@0: 
wolffd@0: function a = main(orig,option,after,index,extract)
wolffd@0: if iscell(orig)
wolffd@0:     orig = orig{1};
wolffd@0: end
wolffd@0: if ischar(orig)
wolffd@0:     if nargin < 5
wolffd@0:         extract = [];
wolffd@0:     end
wolffd@0:     [d{1},tp{1},fp{1},f{1},b{1},n{1},ch{1}] = mirread(extract,orig,1,0);
wolffd@0:     t = mirtemporal([],'Time',tp,'Data',d,'FramePos',fp,'Sampling',f,...
wolffd@0:                        'Name',n,'Label',cell(1,length(d)),...
wolffd@0:                        'Clusters',cell(1,length(d)),...
wolffd@0:                        'Channels',ch,'Centered',0,'NBits',b);
wolffd@0:     t = set(t,'Title','Audio waveform');
wolffd@0:     a.fresh = 1;
wolffd@0:     a = class(a,'miraudio',t);
wolffd@0: else
wolffd@0:     if not(isempty(option)) && not(isempty(option.extract))
wolffd@0:         if not(isstruct(after))
wolffd@0:             after = struct;
wolffd@0:         end
wolffd@0:         after.extract = option.extract;
wolffd@0:     end
wolffd@0:     if isa(orig,'miraudio')
wolffd@0:         a = orig;
wolffd@0:     else
wolffd@0:         a.fresh = 1;
wolffd@0:         a = class(a,'miraudio',orig);
wolffd@0:     end
wolffd@0: end      
wolffd@0: if not(isempty(after))
wolffd@0:     a = post(a,after);
wolffd@0: end    
wolffd@0: 
wolffd@0: 
wolffd@0: function a = post(a,para)
wolffd@0: if a.fresh && isfield(para,'mono')
wolffd@0:     a.fresh = 0;
wolffd@0:     if isnan(para.mono)
wolffd@0:         para.mono = 1;
wolffd@0:     end
wolffd@0: end
wolffd@0: if isfield(para,'mono') && para.mono == 1
wolffd@0:     a = mirsum(a,'Mean');
wolffd@0: end
wolffd@0: d = get(a,'Data');
wolffd@0: t = get(a,'Time');
wolffd@0: ac = get(a,'AcrossChunks');
wolffd@0: f = get(a,'Sampling');
wolffd@0: cl = get(a,'Clusters');
wolffd@0: for h = 1:length(d)
wolffd@0:     for k = 1:length(d{h})
wolffd@0:         tk = t{h}{k};
wolffd@0:         dk = d{h}{k};
wolffd@0:         if isfield(para,'extract') && not(isempty(para.extract))
wolffd@0:             t1 = para.extract(1);
wolffd@0:             t2 = para.extract(2);
wolffd@0:             if para.extract(4)
wolffd@0:                 if para.extract(4) == 1
wolffd@0:                     shift = round(size(tk,1)/2);
wolffd@0:                 elseif para.extract(4) == 2
wolffd@0:                     shift = size(tk,1);
wolffd@0:                 end
wolffd@0:                 if para.extract(3)
wolffd@0:                     shift = tk(shift,1,1);
wolffd@0:                 end
wolffd@0:                 t1 = t1+shift;
wolffd@0:                 t2 = t2+shift;
wolffd@0:             end                
wolffd@0:             if para.extract(3) % in seconds
wolffd@0:                 ft = find(tk>=t1 & tk<=t2);
wolffd@0:             else               % in samples
wolffd@0:                 if not(t1)
wolffd@0:                     warning('WARNING IN MIRAUDIO: Extract sample positions should be real positive integers.')
wolffd@0:                     display('Positions incremented by one.');
wolffd@0:                     t1 = t1+1;
wolffd@0:                     t2 = t2+1;
wolffd@0:                 end
wolffd@0:                 ft = t1:t2;
wolffd@0:             end
wolffd@0:             tk = tk(ft,:,:);
wolffd@0:             dk = dk(ft,:,:);
wolffd@0:         end
wolffd@0:         if isfield(para,'Ch') && not(isempty(para.Ch))
wolffd@0:             dk = dk(:,:,para.Ch);
wolffd@0:         end
wolffd@0:         if isfield(para,'center') && para.center
wolffd@0:             dk = center(dk);
wolffd@0:             a = set(a,'Centered',1);
wolffd@0:         end
wolffd@0:         if isfield(para,'normal') && para.normal
wolffd@0:             nl = size(dk,1);
wolffd@0:             nc = size(dk,3);
wolffd@0:             if isempty(ac)
wolffd@0:                 ee = 0;
wolffd@0:                 for j = 1:nc
wolffd@0:                     ee = ee+sum(dk(:,:,j).^2);
wolffd@0:                 end
wolffd@0:                 ee = sqrt(ee/nl/nc);
wolffd@0:             else
wolffd@0:                 ee = sqrt(sum(ac.sqrsum.^2)/ac.samples);
wolffd@0:             end
wolffd@0:             dk = dk./repmat(ee,[nl,1,nc]);
wolffd@0:         end
wolffd@0:         if isfield(para,'trim') && not(isequal(para.trim,0)) ...
wolffd@0:                 && not(strcmpi(para.trim,'NoTrim'))
wolffd@0:             if not(para.trimthreshold)
wolffd@0:                 para.trimthreshold = 0.06;
wolffd@0:             end
wolffd@0:             trimframe = 100;
wolffd@0:             trimhop = 10;
wolffd@0:             nframes = floor((length(tk)-trimframe)/trimhop)+1;
wolffd@0:             rms = zeros(1,nframes);
wolffd@0:             for j = 1:nframes
wolffd@0:                 st = floor((j-1)*trimhop)+1;
wolffd@0:                 for z = 1:size(dk,3)
wolffd@0:                     rms(1,j,z) = norm(dk(st:st+trimframe-1,1,z))/sqrt(trimframe);
wolffd@0:                 end
wolffd@0:             end
wolffd@0:             rms = (rms-repmat(min(rms),[1,size(rms,2),1]))...
wolffd@0:                      ./repmat(max(rms)-min(rms),[1,size(rms,2),1]);
wolffd@0:             nosil = find(rms>para.trimthreshold);
wolffd@0:             if strcmpi(para.trim,'Trim') || strcmpi(para.trim,'TrimStart') ...
wolffd@0:                                          || strcmpi(para.trim,'TrimBegin')
wolffd@0:                 nosil1 = min(nosil);
wolffd@0:                 if nosil1 > 1
wolffd@0:                     nosil1 = nosil1-1;
wolffd@0:                 end
wolffd@0:                 n1 = floor((nosil1-1)*trimhop)+1;
wolffd@0:             else
wolffd@0:                 n1 = 1;
wolffd@0:             end
wolffd@0:             if strcmpi(para.trim,'Trim') || strcmpi(para.trim,'TrimEnd')
wolffd@0:                 nosil2 = max(nosil);
wolffd@0:                 if nosil2 < length(rms)
wolffd@0:                     nosil2 = nosil2+1;
wolffd@0:                 end
wolffd@0:                 n2 = floor((nosil2-1)*trimhop)+1;
wolffd@0:             else
wolffd@0:                 n2 = length(tk);
wolffd@0:             end
wolffd@0:             wh = ones(n2-n1+1,1);
wolffd@0:             dt = round(.02*f{h});
wolffd@0:             ha = hann(dt*2);
wolffd@0:             wh(1:dt) = ha(1:dt);
wolffd@0:             wh(end-dt+1:end) = ha(dt+1:end);
wolffd@0:             tk = tk(n1:n2);
wolffd@0:             dk = dk(n1:n2,1,:);%.*repmat(wh,[1 1 size(dk,3)]);
wolffd@0:         end
wolffd@0:         if isfield(para,'sampling') && para.sampling
wolffd@0:             if and(f{k}, not(f{k} == para.sampling))
wolffd@0:                 for j = 1:size(dk,3)
wolffd@0:                     rk(:,:,j) = resample(dk(:,:,j),para.sampling,f{k});
wolffd@0:                 end
wolffd@0:                 dk = rk;
wolffd@0:                 tk = repmat((0:size(dk,1)-1)',[1 1 size(tk,3)])...
wolffd@0:                             /para.sampling + tk(1,:,:);
wolffd@0:             end
wolffd@0:             f{k} = para.sampling;
wolffd@0:         end
wolffd@0:         d{h}{k} = dk;
wolffd@0:         t{h}{k} = tk;
wolffd@0:         %if isfield(para,'reverse') && para.reverse
wolffd@0:         %    d{h}{k} = flipdim(d{h}{k},1);
wolffd@0:         %end
wolffd@0:     end
wolffd@0: end
wolffd@0: a = set(a,'Data',d,'Time',t,'Sampling',f,'Clusters',cl);
wolffd@0: if isfield(para,'label') 
wolffd@0:     if isnumeric(para.label)
wolffd@0:         n = get(a,'Name');
wolffd@0:         l = cell(1,length(d));
wolffd@0:         for k = 1:length(d)
wolffd@0:             if para.label
wolffd@0:                 l{k} = n{k}(para.label);
wolffd@0:             else
wolffd@0:                 l{k} = n{k};
wolffd@0:             end
wolffd@0:         end
wolffd@0:         a = set(a,'Label',l);
wolffd@0:     elseif iscell(para.label)
wolffd@0:         idx = mod(get(a,'Index'),length(para.label));
wolffd@0:         if not(idx)
wolffd@0:             idx = length(para.label);
wolffd@0:         end
wolffd@0:         a = set(a,'Label',para.label{idx});
wolffd@0:     elseif ischar(para.label)
wolffd@0:         l = cell(1,length(d));
wolffd@0:         for k = 1:length(d)
wolffd@0:             l{k} = para.label;
wolffd@0:         end
wolffd@0:         a = set(a,'Label',l);
wolffd@0:     end
wolffd@0: end
wolffd@0: 
wolffd@0: 
wolffd@0: function [new orig] = beforechunk(orig,option,missing)
wolffd@0: option.normal = 0;
wolffd@0: a = miraudio(orig,option);
wolffd@0: d = get(a,'Data');
wolffd@0: old = get(orig,'AcrossChunks');
wolffd@0: if isempty(old)
wolffd@0:     old.sqrsum = 0;
wolffd@0:     old.samples = 0;
wolffd@0: end
wolffd@0: new = mircompute(@crossum,d);
wolffd@0: new = new{1}{1};
wolffd@0: new.sqrsum = old.sqrsum + new.sqrsum;
wolffd@0: new.samples = old.samples + new.samples;
wolffd@0: 
wolffd@0: 
wolffd@0: function s = crossum(d)
wolffd@0: s.sqrsum = sum(d.^2);
wolffd@0: s.samples = length(d);
wolffd@0: 
wolffd@0: 
wolffd@0: function [y orig] = eachchunk(orig,option,missing)
wolffd@0: y = miraudio(orig,option);
wolffd@0: 
wolffd@0: 
wolffd@0: function y = combinechunk(old,new)
wolffd@0: do = get(old,'Data');
wolffd@0: to = get(old,'Time');
wolffd@0: dn = get(new,'Data');
wolffd@0: tn = get(new,'Time');
wolffd@0: y = set(old,'Data',{{[do{1}{1};dn{1}{1}]}},...
wolffd@0:             'Time',{{[to{1}{1};tn{1}{1}]}});