wolffd@0: function [d,d2] = mirgetdata(x,varargin)
wolffd@0: %   d = mirgetdata(x) return the data contained in the object x in a
wolffd@0: %       structure that can be used for further computation outside MIRtoolbox.
wolffd@0: %       If x corresponds to one non-segmented audio sequence, the result is 
wolffd@0: %           returned as a matrix. The columns of the matrix usually 
wolffd@0: %           correspond to the successive frames of the audio signal. The 
wolffd@0: %           third dimension of the matrix corresponds to the different
wolffd@0: %           channels of a filterbank.
wolffd@0: %       If x is a keystrength curve, the fourth dimension distinguishes
wolffd@0: %           between major and minor keys. i.e. d(:,:,:,1) is the
wolffd@0: %           keystrength for the major keys, and d(:,:,:,2) is the
wolffd@0: %           keystrength for the minor keys.
wolffd@0: %       If x is a key estimation, two output are returned: the first one
wolffd@0: %           gives the keys (from 1 to 12) and the second one indicates the
wolffd@0: %           modes (1 for major, 2 for minor).
wolffd@0: %
wolffd@0: %       If x corresponds to a set of audio sequences, and if each sequence
wolffd@0: %           has same number of frames, the corresponding resulting matrices 
wolffd@0: %           are concatenated columnwise one after the other. If the number
wolffd@0: %           of raws of the elementary matrices varies, the missing values
wolffd@0: %           are replaced by NaN in the final matrix. On the contrary, if 
wolffd@0: %           the number of columns (i.e., frames) differs, then the result
wolffd@0: %           remains a cell array of matrices.
wolffd@0: %       Idem if x corresponds to one or several segmented audio
wolffd@0: %           sequence(s).
wolffd@0: %
wolffd@0: %   If x is the result of a peak detection,
wolffd@0: %       [px,py] = getdata(x) return the position of the peaks (px) and the
wolffd@0: %           value corresponding to these peaks (py), in the units
wolffd@0: %           predefined for this data.
wolffd@0: 
wolffd@0: if isempty(x)
wolffd@0:     d = {};
wolffd@0:     d2 = {};
wolffd@0:     return
wolffd@0: end
wolffd@0: 
wolffd@0: if isstruct(x)
wolffd@0:     fields = fieldnames(x);
wolffd@0:     for f = 1:length(fields)
wolffd@0:         d.(fields{f}) = mirgetdata(x.(fields{f}));
wolffd@0:     end
wolffd@0:     d2 = {};
wolffd@0:     return
wolffd@0: end
wolffd@0: 
wolffd@0: if iscell(x)
wolffd@0:     x = x{1};
wolffd@0: end
wolffd@0: v = get(x,'Data');
wolffd@0: if isa(x,'mirscalar')
wolffd@0:     m = get(x,'Mode');
wolffd@0: end
wolffd@0: d2 = {};
wolffd@0: 
wolffd@0: if isa(x,'mirclassify')
wolffd@0:     d = get(x,'Data');
wolffd@0:     return
wolffd@0: end
wolffd@0: 
wolffd@0: if isa(x,'mirsimatrix')
wolffd@0:     pt = [];
wolffd@0: else
wolffd@0:     pt = get(x,'PeakPrecisePos');
wolffd@0: end
wolffd@0: pv = get(x,'PeakPreciseVal');
wolffd@0: if not(isempty(pt)) && not(isempty(pt{1})) && not(isempty(pt{1}{1}))
wolffd@0:     d = uncell(pt);
wolffd@0:     d2 = uncell(pv);
wolffd@0:     if not(isempty(d))
wolffd@0:         return
wolffd@0:     end
wolffd@0: end
wolffd@0: 
wolffd@0: if isa(x,'mirsimatrix')
wolffd@0:     pt = [];
wolffd@0: else
wolffd@0:     pt = get(x,'PeakPosUnit');
wolffd@0: end
wolffd@0: pv = get(x,'PeakVal');
wolffd@0: if not(isempty(pt)) && not(isempty(pt{1})) && not(isempty(pt{1}{1}))
wolffd@0:     d = uncell(pt);
wolffd@0:     d2 = uncell(pv);
wolffd@0:     if not(isempty(d))
wolffd@0:         return
wolffd@0:     end
wolffd@0: end
wolffd@0: 
wolffd@0: d = uncell(v,isa(x,'mirscalar'));
wolffd@0: if iscell(d) && not(isempty(d)) && nargin == 1
wolffd@0:     disp('The result is an array of cell.')
wolffd@0:     disp(['If d is the name of the output variable, ',...
wolffd@0:         'the successive cells can be accessed by typing d{1}, d{2}, etc.']);
wolffd@0: end
wolffd@0: if exist('m')==1 && not(isempty(m)) && not(isempty(m{1}))
wolffd@0:     d2 = uncell(m);
wolffd@0: end