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fix too strict option checking in the ft_inverse_ functions #2468

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Merged
schoffelen merged 2 commits into from
Nov 26, 2024
Merged

fix too strict option checking in the ft_inverse_ functions #2468

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FIX - remove options from cfg which otherwise will throw an error in …
schoffelen Nov 26, 2024
fa0c9b0
FIX - too strict option checking
schoffelen Nov 26, 2024
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21 changes: 20 additions & 1 deletion ft_sourceanalysis.m
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Original file line number Diff line number Diff line change
Expand Up @@ -294,6 +294,18 @@
assert(numel(cfg.supchan)>0, 'cfg.supchan is not present in the data');
end

% also do some checks which are conditional on the presence of spatial filters or precomputed leadfields
if isfield(cfg.sourcemodel, 'leadfield') && isempty(cfg.refdip) && isempty(cfg.supdip)
cfg = ft_checkconfig(cfg, 'unused', {'reducerank' 'backproject' 'normalize' 'normalizeparam' 'weight'});
end
if isfield(cfg.sourcemodel, 'filter') && isempty(cfg.refdip) && isempty(cfg.supdip)
% these are options for forward computation
cfg = ft_checkconfig(cfg, 'unused', {'reducerank' 'backproject' 'normalize' 'normalizeparam' 'weight'});

% these are options for inverse computation
cfg.(cfg.method) = ft_checkconfig(cfg.(cfg.method), 'unused', {'lambda' 'kappa' 'tol' 'invmethod' 'fixedori' 'weightnorm' 'subspace'});
end

% spectrally decomposed data can have label and/or labelcmb
if ~isfield(data, 'label') && isfield(data, 'labelcmb')
% the code further down assumes that data.label is present
Expand Down Expand Up @@ -477,6 +489,10 @@
end
sourcemodel = ft_prepare_leadfield(tmpcfg);

% these need to be removed from the cfg, otherwise the low-level inverse
% function may throw an error, see https://github.com/fieldtrip/fieldtrip/pull/2468
cfg = ft_checkconfig(cfg, 'unused', {'reducerank' 'backproject' 'normalize' 'normalizeparam' 'weight'});

% no further forward computations are needed, but keep them in the cfg
needheadmodel = false;
headmodel = [];
Expand Down Expand Up @@ -1122,10 +1138,13 @@
for i=1:Nrepetitions
fprintf('estimating current density distribution for repetition %d\n', i);
squeeze_avg = reshape(avg(i,:,:),[size_avg(2) size_avg(3)]);
if hascovariance
if hascovariance && ~isfield(sourcemodel, 'filter')
squeeze_Cy = reshape(Cy(i,:,:), [size_Cy(2) size_Cy(3)]);
dip(i) = ft_inverse_mne(sourcemodel, sens, headmodel, squeeze_avg, methodopt{:}, leadfieldopt{:}, 'noisecov', squeeze_Cy);
else
if isfield(sourcemodel, 'filter') && hascovariance
ft_warning('spatial filter has been provided, not using the noise covariance matrix for the computations');
end
dip(i) = ft_inverse_mne(sourcemodel, sens, headmodel, squeeze_avg, methodopt{:}, leadfieldopt{:});
end
end
Expand Down
2 changes: 1 addition & 1 deletion inverse/ft_inverse_dics.m
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Expand Up @@ -177,7 +177,7 @@
% check that the options normalize/reducerank/etc are not specified
assert(all(cellfun(@isempty, leadfieldopt(2:2:end))), 'the options for computing the leadfield must all be empty/default');
% check that the options for the inversion are not specified
assert(all(cellfun(@isempty, invopt(2:2:end))), 'the options for computing the inverse solution must all be empty/default');
assert(all(cellfun(@isempty, invopt(4:2:end))) && invopt{2}==0, 'the options for computing the inverse solution must all be empty/default');
ft_info('using precomputed filters\n');
sourcemodel.filter = sourcemodel.filter(originside);
elseif hasleadfield
Expand Down
2 changes: 1 addition & 1 deletion inverse/ft_inverse_lcmv.m
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Original file line number Diff line number Diff line change
Expand Up @@ -166,7 +166,7 @@
% check that the options normalize/reducerank/etc are not specified
assert(all(cellfun(@isempty, leadfieldopt(2:2:end))), 'the options for computing the leadfield must all be empty/default');
% check that the options for the inversion are not specified
assert(all(cellfun(@isempty, invopt(2:2:end))), 'the options for computing the inverse solution must all be empty/default');
assert(all(cellfun(@isempty, invopt(4:2:end))) && invopt{2}==0, 'the options for computing the inverse solution must all be empty/default');
ft_info('using precomputed filters\n');
sourcemodel.filter = sourcemodel.filter(originside);
elseif hasleadfield
Expand Down
2 changes: 1 addition & 1 deletion inverse/ft_inverse_pcc.m
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Original file line number Diff line number Diff line change
Expand Up @@ -151,7 +151,7 @@
% check that the options normalize/reducerank/etc are not specified
assert(all(cellfun(@isempty, leadfieldopt(2:2:end))), 'the options for computing the leadfield must all be empty/default');
% check that the options for the inversion are not specified
assert(all(cellfun(@isempty, invopt(2:2:end))), 'the options for computing the inverse solution must all be empty/default');
assert(all(cellfun(@isempty, invopt(4:2:end))) && invopt{2}==0, 'the options for computing the inverse solution must all be empty/default');
ft_info('using precomputed filters\n');
sourcemodel.filter = sourcemodel.filter(originside);
elseif hasleadfield
Expand Down
14 changes: 7 additions & 7 deletions inverse/ft_inverse_sam.m
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Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,12 @@
invopt = ft_setopt(invopt, 'tolerance', ft_getopt(varargin, 'tol'));
invopt = ft_setopt(invopt, 'method', ft_getopt(varargin, 'invmethod'));

% construct the low-level options for the leadfield computation as key-value pairs, these are passed to FT_COMPUTE_LEADFIELD
leadfieldopt = {};
leadfieldopt = ft_setopt(leadfieldopt, 'normalize', ft_getopt(varargin, 'normalize'));
leadfieldopt = ft_setopt(leadfieldopt, 'normalizeparam', ft_getopt(varargin, 'normalizeparam'));
leadfieldopt = ft_setopt(leadfieldopt, 'weight', ft_getopt(varargin, 'weight'));

% backwards compatibility information
if ~isempty(fixedori)
switch fixedori
Expand Down Expand Up @@ -111,7 +117,7 @@
% check that the options normalize/reducerank/etc are not specified
assert(all(cellfun(@isempty, leadfieldopt(2:2:end))), 'the options for computing the leadfield must all be empty/default');
% check that the options for the inversion are not specified
assert(all(cellfun(@isempty, invopt(2:2:end))), 'the options for computing the inverse solution must all be empty/default');
assert(all(cellfun(@isempty, invopt(4:2:end))) && invopt{2}==0, 'the options for computing the inverse solution must all be empty/default');
ft_info('using precomputed filters\n');
sourcemodel.filter = sourcemodel.filter(sourcemodel.inside);
elseif hasleadfield
Expand All @@ -133,12 +139,6 @@
else
ft_info('computing forward model on the fly\n');

% construct the low-level options for the leadfield computation as key-value pairs, these are passed to FT_COMPUTE_LEADFIELD
leadfieldopt = {};
leadfieldopt = ft_setopt(leadfieldopt, 'normalize', ft_getopt(varargin, 'normalize'));
leadfieldopt = ft_setopt(leadfieldopt, 'normalizeparam', ft_getopt(varargin, 'normalizeparam'));
leadfieldopt = ft_setopt(leadfieldopt, 'weight', ft_getopt(varargin, 'weight'));

% check if a tangential orientation estimation is performed, i.e. if only orientations in the tangential plane are considered.
% if this is the case, we perform the lead field rank reduction directly in this script, since otherwise we would not
% have access to the tangential plane defined by the full leadfield
Expand Down
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