[FieldTrip] ft_freqstatistics issue (??? Undefined function or method 'randperm' for input arguments of type 'double'.)

[Davide Rivolta]

Dear Roemer and Anna,

Thank you for your help. After setting the path the error disappears.

However I know have an error saying that is "could not determine the
parametric critical value for clustering".

However, in the configuration, I put all the values that are in the
tutorial.

May it be a problem with my design?


Thanks a lot,

Davide

On Tue, Sep 13, 2011 at 11:00 AM, Roemer van der Meij <
r.vandermeij at donders.ru.nl> wrote:

> Hi Davide,
>
> It sounds like you are missing the Statistics Toolbo<http://www.mathworks.nl/products/statistics/index.html>x
> for matlab. I remember some internal discussions in the team about writing
> an internal version of randperm.m with similar functions, but we haven't
> done so far if I recall correctly. Installing the toolbox, or checking
> whether you have it on your path should solve your problem.
>
> Hope it helps,
> Roemer
>
>
>
>
> On 13-09-11 9:38, Davide Rivolta wrote:
>
>   Dear fieldtrippers,
>
> I wish to calculate the stat difference between stimulus and baseline in a
> group of subjects. I use ft_freqgrandaverage to average across subjects and
> then ft_freqstatistics (cluster statistic) to compare the 2 conditions
> (baseline & stimuli).
>
> I get this error:    ??? Undefined function or method 'randperm' for input
> arguments of type 'double'.
>
> I tried even with the newest version (20110911) but the problem persists. I
> am not sure what I have to do.
>
> Any advice would be super. The script is below.
>
> Thanks a lot,
>
> Davide
>
>
>
> datainpath = '/data/home1/drivolta/Out4VG/DATA/';
> dataoutpath = '/data/home1/drivolta/Out4VG/DATA/';
>
> % Controls
> Controls = {
>     'ASS31_TFR_high.mat';
>     'CSA07_TFR_high.mat';
>     'BMR08_TFR_high.mat';
>     'NPD18_TFR_high.mat';
>     %'BSA08_TFR_high.mat';
>     %'ABE08_TFR_high.mat';
>     %'EES05_TFR_high.mat';
>     %'GPS10_TFR_high.mat';
>     %'SDA01_TFR_high.mat';
>     %'CSA17_TFR_high.mat';
>     %'KBZ16_TFR_high.mat';
>
> };
>
> %--------------------------------------------------------------------------
> NControls = length(Controls);
>
> %% CONCATENATE DATA
> for i = 1:length(Controls)
>     fullname = strcat(datainpath, Controls{i,1});
>     load(fullname);
>
>     % Activation time window
>     TFR2 = power_continue_high; %Rename to change (select time window)
>     idx = find((TFR2.time >= 0.5) &(TFR2.time <= 1.5));
>     TFR2.powspctrm = power_continue_high.powspctrm(:, :,idx);
>     TFR2.time = power_continue_high.time(idx);
>     Stimuli{i} = TFR2;
>
>     % Baseline time window
>     TFR3 = power_continue_high;
>     idx = find((TFR3.time >= -1) &(TFR3.time < 0));
>     TFR3.powspctrm = power_continue_high.powspctrm(:,:, idx);
>     TFR3.time = TFR2.time;
>     Baseline{i} = TFR3;
>
>     clear power_continue_high
>     clear TFR2
>     clear TFR3
> end;
> save Controls2Statistics Stimuli Baseline;
>
>
>
> cfg = [];
> cfg.channel = {'MEG', '-MRO31', '-MRO21'};
> cfg.keepindividual = 'yes';
>
> BaselineAll = ft_freqgrandaverage(cfg, Baseline{:});
> StimuliAll = ft_freqgrandaverage(cfg, Stimuli{:});
>
>
>
> load /data/home1/drivolta/Out4VG/DATA/GRAD % File with a structure
> containing grad field
>
> cfg                = [];
> cfg.method         = 'triangulation';
> cfg.neighbourdist  = 5;
> cfg.grad           = TFR.grad;
> cfg.layout         = 'CTF275.lay';
> neighbour          = ft_neighbourselection(cfg, Baseline{1});
> cfg = [];
> cfg.grad             = TFR.grad;
> cfg.channel          = {'MEG', '-MRO31', '-MRO21'};
> cfg.neighbourdist    = 4;
> cfg.minnbchan        = 1;
> cfg.clusteralpha     = 0.05; % control admission to a cluster
> cfg.alpha            = 0.05; % control the false alarm rate of the
> permutation test
> cfg.latency          = [0.5 1.5]; % time interval over which the
> experimental conditions are compared (in sec)
> cfg.frequency        = [50 70];
> cfg.avgovertime      = 'no';
> cfg.avgoverfreq      = 'no';
> cfg.avgoverchan      = 'no';
> cfg.clusterstatistics = 'maxsum';
> cfg.statistic        = 'actvsblT';
> cfg.numrandomization = 1000;
> cfg.correctm         = 'cluster';
> cfg.method           = 'montecarlo';
> cfg.approach         = 'montecarlo';
> cfg.dimord           = 'chan_freq_time';
> cfg.dim              = 'chan_freq_time';
> cfg.neighbours       = neighbour;
> cfg.tail = 0;
> cfg.clustertail = 0;
>
> nSubjects = 2*length(Controls);
>
> a = [1:nSubjects];
> b = ones(1,length(Controls));
> c = 2*(ones(1,length(Controls)));
>
> cfg.design = [a; b c];
> cfg.uvar = 1; % "subject" is unit of observation
> cfg.ivar = 2; % row of the design matrix that contains the independent
> variable
>
> stat = ft_freqstatistics(cfg, BaselineAll, StimuliAll);
>
>
>
>
>
>
>
> _______________________________________________
> fieldtrip mailing listfieldtrip at donders.ru.nlhttp://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> --
> Roemer van der Meij M.Sc.
> PhD student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognition
> P.O. Box 9104
> 6500 HE Nijmegen
> The Netherlands
> Tel: +31(0)24 3655932
> E-mail: r.vandermeij at donders.ru.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Davide Rivolta, PhD
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