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<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
Thanks alot Xavier. <span style="color: rgb(0, 0, 0); font-family: Calibri, Helvetica, sans-serif; font-size: 12pt;">This worked well and am able to progress.</span></div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
Can I also query on design matrix as I am having difficulty understanding the concept.</div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
I have got two groups I am comparing 2 second epileptiform discharges - 57 subjects in group A and 99 subjects in group B with grandaverage structures - dimord subj_chan_freq structures</div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
I want to compare their powerspectrum using cluster statistics </div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
How do I design a design matrix. </div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
<br>
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<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
cfg = [];
<div>cfg.channel = {'Fp1' 'Fp2' 'F7' 'F3' 'F4' 'F8' 'Fz'};</div>
<div>cfg.latency = 'all';</div>
<div>cfg.frequency = [2 50];</div>
<div>cfg.method = 'montecarlo';</div>
<div>cfg.statistic = 'ft_statfun_indepsamplesT';</div>
<div>cfg.correctm = 'cluster';</div>
<div>cfg.clusteralpha = 0.025;</div>
<div>cfg.clusterstatistic = 'maxsum';</div>
<div>cfg.alpha = 0.05;<br>
</div>
<div>cfg_neighb.method = 'distance';<br>
</div>
<div>cfg.neighbours = neighbours</div>
<div>cfg.design = [ones(1,57) ones(1,99)*2]</div>
<div>cfg.ivar = 1</div>
[stat] = ft_freqstatistics(cfg, results1, results2)<br>
</div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
<br>
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<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
I am getting some problem in the code as all my stat.prob is ones? I am having trouble I think with the cfg.design and ivar. </div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
Its two groups their spontaneous abnormal discharges and comparing the powerspectra of their discharges.</div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
Any assistance will be highly appreciated.</div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
<br>
</div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
Regards,</div>
<div style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
Mubeen J</div>
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<hr style="display:inline-block;width:98%" tabindex="-1">
<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000"><b>From:</b> fieldtrip <fieldtrip-bounces@science.ru.nl> on behalf of Xavier Vrijdag via fieldtrip <fieldtrip@science.ru.nl><br>
<b>Sent:</b> Monday, February 28, 2022 3:31 AM<br>
<b>To:</b> FieldTrip discussion list <fieldtrip@science.ru.nl><br>
<b>Cc:</b> Xavier Vrijdag <x.vrijdag@auckland.ac.nz><br>
<b>Subject:</b> Re: [FieldTrip] multiple subject code</font>
<div> </div>
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<p class="x_MsoNormal"><span style="">Hi Mubeen,</span></p>
<p class="x_MsoNormal"><span style=""> </span></p>
<p class="x_MsoNormal"><span style="">If your code is working fine for each of the data files individually, you can put it in a for loop with an iterator (k) that has the length of the number of data files. You can automatically construct the list of data files
with the dir function. In your code you have to change the line where the cfg.dataset is called to point to the datafile of that iteration. Secondly, you have to add a line at the end of your code (in the loop) to save the results from the calculations into
a datastruct. After the loop you can call ft_freqgrandaverage to perform the grand average</span></p>
<p class="x_MsoNormal"><span style=""> </span></p>
<p class="x_MsoNormal"><span style="">It will all look like this:</span></p>
<p class="x_p1">datapath = 'C:\Users\mubaf\OneDrive\Desktop\MY BRAINSTORM\Cases GGE\’;</p>
<p class="x_p1">datasetlist = dir([datapath <span class="x_s1">'*.edf'</span>]);</p>
<p class="x_p1"> </p>
<p class="x_p1">for k=1:size(datasetlist,1)</p>
<p class="x_p1"> cfg =[]; </p>
<p class="x_p1" style="text-indent:36.0pt">cfg.dataset = [datapath datasetlist(k).name];</p>
<p class="x_p1" style="text-indent:36.0pt"> </p>
<p class="x_p1" style="text-indent:36.0pt">% your code</p>
<p class="x_p1" style="text-indent:36.0pt"> </p>
<p class="x_p1" style="text-indent:36.0pt">data_combined{k}=descrip;</p>
<p class="x_p1">end</p>
<p class="x_p1"> </p>
<p class="x_p1">cfg=[];</p>
<p class="x_p1">cfg.parameter<span class="x_apple-converted-space"> </span>= ; % enter your parameter</p>
<p class="x_p1">results= ft_freqgrandaverage(cfg,data_combined{:});</p>
<p class="x_MsoNormal"><span style=""> </span></p>
<p class="x_MsoNormal"><span style="">It is good habit to call cfg:[]; every time you start configuring the settings for the next step in you analysis as settings of a previous step might influence the next step of your analysis.
</span></p>
<p class="x_MsoNormal"><span style="">To speed up the analysis you might want to consider removing the databrowser step for each iteration to reduce your loop time. Unless you want to see the data in each step.</span></p>
<p class="x_MsoNormal"><span style=""> </span></p>
<p class="x_MsoNormal"><span style="">Happy to help if you have any questions.</span></p>
<p class="x_MsoNormal"><span style=""> </span></p>
<p class="x_MsoNormal"><span style="">Regards,</span></p>
<p class="x_MsoNormal"><span style=""> </span></p>
<p class="x_MsoNormal"><span style="">Xavier</span></p>
<p class="x_MsoNormal"><span style=""> </span></p>
<div style="border:none; border-top:solid #B5C4DF 1.0pt; padding:3.0pt 0cm 0cm 0cm">
<p class="x_MsoNormal"><b><span style="font-size:12.0pt; color:black">From: </span>
</b><span style="font-size:12.0pt; color:black">fieldtrip <fieldtrip-bounces@science.ru.nl> on behalf of mubeen afzal via fieldtrip <fieldtrip@science.ru.nl><br>
<b>Reply to: </b>FieldTrip discussion list <fieldtrip@science.ru.nl><br>
<b>Date: </b>Monday, 28 February 2022 at 9:40 AM<br>
<b>To: </b>"fieldtrip@science.ru.nl" <fieldtrip@science.ru.nl><br>
<b>Cc: </b>mubeen afzal <mubafzal@hotmail.com><br>
<b>Subject: </b>[FieldTrip] multiple subject code</span></p>
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<div>
<p class="x_MsoNormal"> </p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">Hi I have a silly question,</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">How does one use a folder of edf files of subjects to repeat the code below so that I can perform a grand average in the end? Or does each file have to be run seperately with seperate codes? </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">Regards,</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">Mubeen </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg = [];
</span></p>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.dataset = 'C:\Users\mubaf\OneDrive\Desktop\MY BRAINSTORM\Cases GGE\JJ_05-01-2017.edf';</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.channel = {'EEG Fp1' 'EEG Fp2' 'EEG F7' 'EEG F3' 'EEG Fz' 'EEG F4'...</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> 'EEG F8' 'EEG T7' 'EEG C3' 'EEG Cz' 'EEG T8' 'EEG P7' 'EEG P3' 'EEG C4'...
</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> 'EEG Pz' 'EEG P4' 'EEG O1' 'EEG O2', 'EEG T3', 'EEG T5', ...</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> 'EEG T4', 'EEG T6' 'Fp1' 'Fp2' 'F7' 'F3' 'Fz' 'F4' 'F8' 'T7' 'C3'...</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> 'Cz' 'C4' 'T8' 'P7' 'P3' 'Pz' 'P4' 'O1' 'O2', 'T3', 'T5', 'T4', 'T6'};%'P8'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">hdr = ft_read_header(cfg.dataset);</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">event = ft_read_event(cfg.dataset, 'detectflank', []);</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.trialdef.prestim = 0.5; % in seconds</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.trialdef.poststim = 2.5; % in seconds</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.trialdef.eventtype = 'annotation'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.trialdef.eventvalue = 'Ep.sw';
</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg = ft_definetrial(cfg);</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">datatrials = ft_preprocessing(cfg);</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.continuous = 'no'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.blocksize = 10</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.channel = 'eeg'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg = ft_databrowser(cfg, datatrials)</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">%power analysis (calls 1 function)</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.method = 'mtmfft'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.output ='pow'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.channel = 'all';</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.trials = 'all'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.keeptrials = 'yes' %all trials powerspectrum available if yes in freq.powspctrm</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.keeptapers = 'no'</span></p>
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<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.pad = 'maxperlen'</span></p>
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<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.polyremoval = 0 %(0 demeans only/1 demeans and detrends/-1 no removal)</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.taper = 'hann'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.foilim = [2 50]</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">freq = ft_freqanalysis(cfg, datatrials);</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.variance = 'yes'
</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.jackknife = 'no'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.keeptrials = 'yes'
</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.channel = 'all'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.trials = 'all'
</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.frequency = [2 50]
</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">cfg.latency = 'all'</span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black">[descrip] = ft_freqdescriptives(cfg, freq)</span></p>
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<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
</div>
<div>
<p class="x_MsoNormal"><span style="font-size:12.0pt; color:black"> </span></p>
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