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

[Davide Rivolta]

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);
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