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Fig7a_tempograms.m
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Name: Fig7a_tempograms
% Date of Revision: 2016-08
% Programmer: Thomas Praetzlich
% Resources: https://dx.doi.org/10.6084/m9.figshare.3398545
%
% Description:
% Code for tempograms in Figure 7
%
% Reference:
% [SPG16] Sebastian Stober; Thomas Prätzlich & Meinard Müller.
% Brain Beats: Tempo Extraction from EEG Data.
% International Society for Music Information Retrieval
% Conference (ISMIR), 2016
%
% License:
% This script is derived from parts of the 'Tempogram Toolbox'.
%
% This script is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 2 of the License, or
% (at your option) any later version.
%
% This script is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with 'Tempogram Toolbox'. If not, see
% <http://www.gnu.org/licenses/>.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
addpath('MATLAB-Tempogram-Toolbox_1.0');
addpath('matlab_helpers');
clear
% close all
vis_audio = 0;
vis_EEG = 1;
% When localization is set to US, matlab uses inches as default units,
% centimeters otherwise
set(0,'DefaultFigurePaperUnits','centimeters')
% ground truth bpm data
bpm_GT = readtable('data/bpm_annotation.txt');
%%
% minBPM = 80;
minBPM = 80;
maxBPM = 240;
dataIdx = 2;
data = {
'raw', 'raw/cond1/';
'sce', 'sce-filtered/cond1/';
};
data_root = 'data/';
data_set = data{dataIdx,2};
% data_set = '';
dirData = [ data_root data_set ];
% %%
printPaperPosition_WAV = [1 10 18 4]; %[left, bottom, width, height]
% printPaperPosition_Tempo = [1 10 18 8];
printPaperPosition_Tempo = [1 10 10 6];
printPaperPosition_Hist = [1 10 8 8];
%% parameters
tempoWindow = 8;
smooth_len = .5; % window for local average in novelty curve
%----------------------------
% Figure 7 tempogram row 1
pID = '09'; % participant
sIDset = {'14'};
trialIdx = 2;
%----------------------------
%----------------------------
% Figure 7 tempogram row 2
% pID = '11'; % participant
% sIDset = {'04'};
% trialIdx = 1;
%----------------------------
%----------------------------
% Figure 7 tempogram row 3
% pID = '12'; % participant
% sIDset = {'24'};
% trialIdx = 3;
%----------------------------
% sIDset = {'14'}; % stimulus
% pID = '09'; % participant
% trialNum = 1;
% channelNum = 64;
% trialIdx = [1:trialNum];
% % trialIdx = [5];
% channelIdx = [11 32 46 47 48];
% sIDset = {'14'};
% channelNum = 64;
%trialIdx = [1:5];
%channelIdx = [1:channelNum];
% trialIdx =2;
% sIDset = {'01';'02';'03';'04';'11';'12';'13';'14';'21';'22';'23';'24'};
% channelIdx = [12,32,47,48,49];
% trialIdx = 2;
% sIDset = {'14'};
sIDsetNum = size(sIDset,1);
for sIDcounter =1:sIDsetNum
sID = sIDset{sIDcounter};
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% configuration: directories, filenames ...
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% dirData = 'data/';
% there are two versions of stimuli:
% v1: has been used for participants <8
% v2: participants > 8
audioVersion = 'v1/';
if str2num( pID ) > 8
audioVersion = 'v2/';
end
dirAudio = [data_root audioVersion];
filenameWav = [ sID '.wav'];
filenameAnn = [ data_root 'beats/cond1/' sID '_P' pID '.txt'];
% filenamePart = '14_P01at';
%filenamePart = '14_P09at';
% filename for specific stimulus and participant
filenamePart = [ sID '_P' pID 'at' ];
FigFilenamePrefix = [ data{dataIdx,1} '_' sID '_P' pID '_' num2str(trialIdx) '_'];
FigDir = 'figure/';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% load annotations
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
annoData = csvread( [filenameAnn] );
if vis_EEG
%% load EEG data
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
dataEEG = load( [dirData filenamePart]);
dataEEG = double(dataEEG.data);
if dataIdx == 2
tmpTensor = sum( dataEEG(trialIdx,:),1);
channelEEG = squeeze( sum( tmpTensor, 1 ));
else
tmpTensor = sum( dataEEG(trialIdx,channelIdx,:),2);
channelEEG = squeeze( sum( tmpTensor, 1 ))';
end
featureRateEEG = 512;
parameterSmooth = [];
parameterSmooth.smooth_len = smooth_len;
[ noveltyCurveEEG, local_average ] = novelty_smoothedSubtraction_EEG( channelEEG,parameterSmooth );
%% tempogram_fourier
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
featureRate = featureRateEEG;
noveltyCurve = noveltyCurveEEG;
parameterTempogram = [];
parameterTempogram.featureRate = featureRate;
parameterTempogram.tempoWindow = tempoWindow; % window length in sec
parameterTempogram.BPM = minBPM:1:maxBPM; % tempo values
[tempogram_fourier, T, BPM] = noveltyCurve_to_tempogram_via_DFT(noveltyCurve,parameterTempogram);
tempogram_fourier = normalizeFeature(tempogram_fourier,2, 0.0001);
visualize_tempogram(tempogram_fourier,T,BPM)
printFile = 'Figure_EEG_Tempogram';
printFile = strcat(FigDir,FigFilenamePrefix,printFile);
set(gcf,'PaperPosition',printPaperPosition_Tempo);
shrinkColorbar;
print('-dpng',strcat(printFile),'-r600');
stepsize = ceil(featureRate./5);
win_len = round(tempoWindow.* featureRate);
win_len = win_len + mod(win_len,2) - 1;
parameter.tempoRate = featureRate ./ stepsize;
% mean tempo histogram
figure;
mean_tempogram = mean(abs(tempogram_fourier),2);
hold on;
bar(BPM, mean_tempogram,'k')
idx = find( bpm_GT.sID == str2num(sID) );
stem( bpm_GT.BPM(idx), 1, 'r','marker','none' );
box on;
xlim([minBPM maxBPM]);
ylim([0 0.31])
printFile = 'Figure_EEG_Tempogram_Hist';
printFile = strcat(FigDir,FigFilenamePrefix,printFile);
set(gcf,'PaperPosition',printPaperPosition_Hist);
print('-dpng',strcat(printFile),'-r600');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% PLP curve
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
parameterPLP = [];
parameterPLP.featureRate = featureRate;
parameterPLP.tempoWindow = parameterTempogram.tempoWindow;
[PLP,featureRate] = tempogram_to_PLPcurve(tempogram_fourier, T, BPM, parameterPLP);
PLP = PLP(1:length(noveltyCurve)); % PLP curve will be longer (zero padding)
parameterVis = [];
parameterVis.featureRate = featureRate;
parameterVis.plotAnn = annoData;
visualize_noveltyCurve(PLP,parameterVis)
title('PLP curve')
set(gcf,'Position',[ 7 6 1589 346]);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
end
if vis_audio
%% load wav file, automatically converted to Fs = 22050 and mono
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
[audio,sideinfo] = wav_to_audio('',[ dirAudio] ,filenameWav);
Fs = sideinfo.wav.fs;
figure;
h = plot((0:length(audio)-1)/Fs,audio,'b');
xlim([0 length(audio)/Fs]);
ylim([-0.8 0.8])
set(h,'LineWidth',1)
printFile = 'Figure_WAV';
printFile = strcat(FigDir,FigFilenamePrefix,printFile);
set(gcf,'PaperPosition',printPaperPosition_WAV);
print('-dpng',strcat(printFile),'-r600');
hold on;
stem(annoData, 1 * ones(1,length(annoData)),'r','marker','none')
stem(annoData, -1 * ones(1,length(annoData)),'r','marker','none')
printFile = 'Figure_WAV_Ann';
printFile = strcat(FigDir,FigFilenamePrefix,printFile);
set(gcf,'PaperPosition',printPaperPosition_WAV);
print('-dpng',strcat(printFile),'-r600');
%% compute novelty curve
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
parameterNovelty = [];
[noveltyCurve,featureRate] = audio_to_noveltyCurve(audio, Fs, parameterNovelty);
parameterVis = [];
parameterVis.featureRate = featureRate;
%parameterVis.plotAnn = annoData;
visualize_noveltyCurve(noveltyCurve,parameterVis)
%title('Novelty curve')
printFile = 'Figure_WAV_Novelty';
printFile = strcat(FigDir,FigFilenamePrefix,printFile);
set(gcf,'PaperPosition',printPaperPosition_WAV);
print('-dpng',strcat(printFile),'-r600');
%% tempogram_fourier
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
parameterTempogram = [];
parameterTempogram.featureRate = featureRate;
parameterTempogram.tempoWindow = tempoWindow; % window length in sec
parameterTempogram.BPM = minBPM:1:maxBPM; % tempo values
[tempogram_fourier, T, BPM] = noveltyCurve_to_tempogram_via_DFT(noveltyCurve,parameterTempogram);
tempogram_fourier = normalizeFeature(tempogram_fourier,2, 0.0001);
visualize_tempogram(tempogram_fourier,T,BPM)
printFile = 'Figure_WAV_Tempogram';
printFile = strcat(FigDir,FigFilenamePrefix,printFile);
set(gcf,'PaperPosition',printPaperPosition_Tempo);
print('-dpng',strcat(printFile),'-r600');
%% mean tempo histogram (audio)
figure;
mean_tempogram = mean(abs(tempogram_fourier),2);
hold on;
bar(BPM, mean_tempogram,'k')
idx = find( bpm_GT.sID == str2num(sID) );
stem( bpm_GT.BPM(idx), 1, 'r','marker','none' );
box on;
% bar(BPM, mean_tempogram,'k')
xlim([minBPM maxBPM]);
ylim([0 0.31])
pause(1)
printFile = 'Figure_WAV_Tempogram_Hist';
printFile = strcat(FigDir,FigFilenamePrefix,printFile);
set(gcf,'PaperPosition',printPaperPosition_Hist);
print('-dpng',strcat(printFile),'-r600');
%% PLP curve
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
parameterPLP = [];
parameterPLP.featureRate = featureRate;
parameterPLP.tempoWindow = parameterTempogram.tempoWindow;
[PLP,featureRate] = tempogram_to_PLPcurve(tempogram_fourier, T, BPM, parameterPLP);
PLP = PLP(1:length(noveltyCurve)); % PLP curve will be longer (zero padding)
parameterVis = [];
parameterVis.featureRate = featureRate;
parameterVis.plotAnn = annoData;
visualize_noveltyCurve(PLP,parameterVis)
title('PLP curve')
end
end