function test_suite=test_meeg_source()
% tests for MEEG datasets in source space
%
% # For CoSMoMVPA's copyright information and license terms, #
% # see the COPYING file distributed with CoSMoMVPA. #
try % assignment of 'localfunctions' is necessary in Matlab >= 2016
test_functions=localfunctions();
catch % no problem; early Matlab versions can use initTestSuite fine
end
initTestSuite;
function test_meeg_dataset()
tps={'freq_pow','time_mom','rpt_trial_mom','rpt_trial_mom_1d',...
'time_mom_1d',...
'rpt_trial_pow','strange_ft_lcmv_pow'};
for j=1:numel(tps)
is_ft_strange_lcmv_avg_pow=isequal(cosmo_strsplit(tps{j},'_',1),...
'strange');
[ft,fdim,data_label]=generate_ft_source(tps{j});
ds=cosmo_meeg_dataset(ft);
% check fdim
assertEqual(ds.a.fdim,fdim);
key=data_label{1};
sub_key=data_label{2};
ft_first_sample_all=ft.(key).(sub_key);
if is_ft_strange_lcmv_avg_pow
ft_first_sample=ft_first_sample_all(:,ft.inside);
else
ft_first_sample=ft_first_sample_all(ft.inside,:);
end
switch sub_key
case 'mom'
% choose a random sensor
inside_idxs=find(ft.inside);
pos=ceil(rand()*numel(inside_idxs));
inside_idx=inside_idxs(pos);
assertEqual(ds.samples(1,ds.fa.pos==inside_idx),...
ft_first_sample{pos}(:)')
otherwise
assertEqual(ds.samples(1,:),ft_first_sample(:)');
end
[ft_arr, ft_labels, ft_values]=cosmo_unflatten(ds,2,...
'matrix_labels','pos');
if is_ft_strange_lcmv_avg_pow
ft_arr=ft_arr';
end
assertEqual(ft_arr(ft_arr~=0),ds.samples(:));
assertEqual(ft_labels, fdim.labels);
assertEqual(ft_values, fdim.values);
% select single element, and ensure it is the same in the
% fieldtrip struct as in the dataset struct
dim_sizes=cellfun(@(x)size(x,2),fdim.values);
ndim=numel(dim_sizes);
rp=ceil(rand(1,ndim).*dim_sizes(:)');
[nsamples,nfeatures]=size(ds.samples);
ds_msk=false(1,nfeatures);
ft_idx=cell(1,1+ndim);
ft_idx{1}=randperm(nsamples);
for k=1:ndim
dim_label=fdim.labels{k};
ds_msk = ds_msk | rp(k)~=ds.fa.(dim_label);
switch dim_label
case 'mom'
ft_idx{k+1}=rp(k);
case 'pos'
ft_values=ft.(dim_label);
ft_idx{k+1}=find(all(bsxfun(@eq,...
ft_values(rp(k),:),ft_values),2));
otherwise
ft_values=ft.(dim_label);
ft_idx{k+1}=find(ft_values(rp(k))==ft_values);
end
end
ds_sel=cosmo_slice(cosmo_slice(ds,~ds_msk,2),ft_idx{1});
if is_ft_strange_lcmv_avg_pow
ft_idx=ft_idx(2:end);
end
ft_sel=ft_arr(ft_idx{:});
if ft_sel==0
assertTrue(isempty(ds_sel.samples));
else
assertEqual(ds_sel.samples,ft_sel);
end
%re-order features
nfeatures=size(ds.samples,2);
ds2=cosmo_slice(ds,randperm(nfeatures),2);
ft2=cosmo_map2meeg(ds2);
if is_ft_strange_lcmv_avg_pow
ft2.avg.pow=ft2.avg.pow';
ft2.time=ft.time;
end
assertEqual(ft,ft2);
if j==1
% test compatibility with old fieldtrip
ft2.inside=find(ft2.inside);
ds3=cosmo_meeg_dataset(ft2);
assertEqual(ds,ds3);
ft2.inside=struct();
assertExceptionThrown(@()cosmo_meeg_dataset(ft2),'');
end
end
function test_meeg_fmri_dataset()
ds=cosmo_synthetic_dataset('type','source');
ds_fmri=cosmo_fmri_dataset(ds);
ft=cosmo_map2meeg(ds);
ds_ft_fmri=cosmo_fmri_dataset(ft);
ds_vol=cosmo_vol_grid_convert(ds,'tovol');
assertEqual(ds_vol,ds_fmri);
assertTrue(isempty(fieldnames(ds_ft_fmri.sa)))
ds_vol=rmfield(ds_vol,'sa');
ds_ft_fmri=rmfield(ds_ft_fmri,'sa');
assertEqual(ds_vol,ds_ft_fmri);
function test_irregular_source_grid()
ft=generate_ft_source('freq_pow');
ft.pos=ft.pos+randn(size(ft.pos));
ds=cosmo_meeg_dataset(ft);
ft2=cosmo_map2meeg(ds);
assertEqual(ft,ft2);
function [ft,fdim,data_label]=generate_ft_source(tp)
ft=struct();
dim_pos_range={-3:3,-4:4,-5:5};
nsamples=2;
freq=[3 5 7 9];
time=[-1 0 1 2];
mom_labels_3d={'x','y','z'};
mom_labels_1d={'xyz'};
ft.dim=cellfun(@numel,dim_pos_range);
ft.pos=cosmo_cartprod(dim_pos_range);
ft.inside=sum(ft.pos.^2,2)<30;
fdim=struct();
switch tp
case 'freq_pow'
ft.freq=freq;
ft.method='average';
ft.avg=generate_data(ft.inside,numel(freq),1,'pow');
fdim.labels={'pos';'freq'};
fdim.values={ft.pos';freq(:)'};
data_label={'avg','pow'};
case 'time_mom'
ft.time=time;
ft.method='average';
ft.avg=generate_data(ft.inside,numel(time),1,'mom3d');
fdim.labels={'pos';'mom';'time'};
fdim.values={ft.pos';mom_labels_3d;time(:)'};
data_label={'avg','mom'};
case 'time_mom_1d';
ft.time=time;
ft.method='average';
ft.avg=generate_data(ft.inside,numel(time),1,'mom1d');
fdim.labels={'pos';'mom';'time'};
fdim.values={ft.pos';mom_labels_1d;time(:)'};
data_label={'avg','mom'};
case 'rpt_trial_pow';
ft.time=time;
ft.method='rawtrial';
ft.trial=generate_data(ft.inside,numel(time),nsamples,'pow');
fdim.labels={'pos';'time'};
fdim.values={ft.pos';time(:)'};
data_label={'trial','pow'};
case 'rpt_trial_mom';
ft.time=time;
ft.method='rawtrial';
ft.trial=generate_data(ft.inside,numel(time),nsamples,'mom3d');
fdim.labels={'pos';'mom';'time'};
fdim.values={ft.pos';mom_labels_3d;time(:)'};
data_label={'trial','mom'};
case 'rpt_trial_mom_1d';
ft.time=time;
ft.method='rawtrial';
ft.trial=generate_data(ft.inside,numel(time),nsamples,'mom1d');
fdim.labels={'pos';'mom';'time'};
fdim.values={ft.pos';mom_labels_1d;time(:)'};
data_label={'trial','mom'};
case 'strange_ft_lcmv_pow'
% FT with LCMV source puts .avg data in a 1xNSOURCE matrix,
% even with NTIME>1 timepoints. In this case, the output
% dataset structure has the time points averaged.
ft.time=time;
ft.method='average';
ft.avg=generate_data(ft.inside,1,1,'pow');
ft.avg.pow=ft.avg.pow';
fdim.labels={'pos';'time'};
fdim.values={ft.pos';mean(time)};
data_label={'avg','pow'};
otherwise
error('unsupported type %s', tp);
end
function d=generate_data(inside,nfeatures,nsamples,fld)
is_single_trial=nargin<3;
if is_single_trial
nsamples=1;
end
switch fld
case 'mom3d'
d=generate_mom(inside,nfeatures,nsamples,3);
case 'mom1d'
d=generate_mom(inside,nfeatures,nsamples,1);
case 'pow'
d=generate_pow(inside,nfeatures,nsamples);
otherwise
error('not supported: %s', fld);
end
function all_trials=generate_pow(inside,nfeatures,nsamples)
nf=numel(inside);
ni=sum(inside);
all_data=NaN(nf,nfeatures);
trial_data=cosmo_rand(ni,nfeatures);
all_trials_cell=cell(nsamples,1);
for j=1:nsamples
data=all_data;
data(inside,:)=trial_data+j;
all_trials_cell{j}.pow=data;
end
all_trials=cat(1,all_trials_cell{:})';
function all_trials=generate_mom(inside,nfeatures,nsamples,ndim)
nf=numel(inside);
i=find(inside);
ni=numel(i);
data=cosmo_rand(ndim,nfeatures,ni);
all_trials_cell=cell(1,nsamples);
for j=1:nsamples
one_trial=cell(nf,1);
for k=1:ni
one_trial{i(k)}=data(:,:,k)+j;
end
all_trials_cell{j}=one_trial;
end
all_trials=struct('mom',all_trials_cell);
