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improvements & bug fixes #78

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3997b81
bug fixes to canlab scripts, and completely revamped searchlight_disti
lukasvo76 Apr 1, 2026
09524bf
finished searchlight_disti_Lukas function
lukasvo76 Jun 19, 2026
fd2e81d
Merge branch 'master' into labgas
torwager Jun 19, 2026
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183 changes: 138 additions & 45 deletions CanlabCore/@image_vector/hansen_neurotransmitter_maps.m
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Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,10 @@
% Indicates group membership for each image as vector, categorical,
% or string array
%
% **mask**
% Followed by mask on path, default canlab gray matter mask
% Mask will be applied to both fmri_data_obj and hansen maps
%
% :Outputs:
%
% **stats:**
Expand Down Expand Up @@ -128,6 +132,8 @@
% this function, and debugged plotting for multiple groups in
% image_similarity_plot
%
% Lukas: Added mask option
%
% ..

% -------------------------------------------------------------------------
Expand All @@ -137,8 +143,9 @@
colors = [1 0 0];
dofigure = true;
doplot = true;
similarity_metric = 'corr';
similarity_metric = 'correlation';
dofixrange = [];
mask = which('gray_matter_mask.nii');

doAverage=0;
% -------------------------------------------------------------------------
Expand All @@ -150,7 +157,7 @@

allowable_inputs = {'colors' 'doplot' 'similarity_metric' 'dofixrange'};

keyword_inputs = {'noplot' 'nofigure' 'cosine_similarity' 'doAverage' 'compareGroups'};
keyword_inputs = {'noplot' 'nofigure' 'cosine_similarity' 'doAverage' 'compareGroups', 'mask'};

% optional inputs with default values - each keyword entered will create a variable of the same name

Expand Down Expand Up @@ -190,11 +197,22 @@
case 'compareGroups'
compareGroups = true;
group = varargin{i+1};

case 'mask'
mask = varargin{i+1};

end
end
end

% -------------------------------------------------------------------------
% INTIALIZE OUTPUT
% -------------------------------------------------------------------------
stats = struct();
[hh, hhfill] = deal(' ');
table_group = {};
multcomp_group = {};

% -------------------------------------------------------------------------
% MAIN FUNCTION
% -------------------------------------------------------------------------
Expand All @@ -204,69 +222,144 @@
ntmaps = reorder_and_add_metadata(ntmaps);

% These are already gray-matter masked in repo, but make sure:
ntmaps = apply_mask(ntmaps, which('gray_matter_mask.nii'));
ntmaps = apply_mask(ntmaps, mask);

% This may not be masked...so mask with gray matter:
fmri_data_obj = apply_mask(fmri_data_obj, which('gray_matter_mask.nii'));
fmri_data_obj = apply_mask(fmri_data_obj, mask);

% handle tags for figure(s)
if dofigure
tagname = ['Neurotransmitter polar plot ' similarity_metric];
old = findobj('Tag', tagname);
old = old( strcmp( get(old, 'Type'), 'figure' ) );

if dofigure
create_figure('Neurotransmitter polar plot')
if ~isempty(old) % Found existing figure window with this tag
create_figure([tagname ' ' num2str(length(old)+1)])
else
create_figure(tagname)
end
end

if doplot
if ~iscell(colors), colors = {colors}; end

switch similarity_metric

case 'cosine_similarity'

if doAverage==1
if isempty(dofixrange)

if exist('compareGroups','var') % added by Lukas: if we want to analyze & plot multiple groups

groupValues = unique(group, 'stable');
if size(colors,1) ~= size(groupValues,1)
colors = scn_standard_colors(length(groupValues))';
end

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'average','compareGroups', group);

else

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'average','Error_STD');
end

else

if exist('compareGroups','var') % % added by Lukas: if we want to analyze & plot multiple groups

groupValues = unique(group, 'stable');
if size(colors,1) ~= size(groupValues,1)
colors = scn_standard_colors(length(groupValues))';
end

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'dofixrange', dofixrange, 'average', 'compareGroups', group);

else

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'dofixrange', dofixrange,'average','Error_STD');
end

if doAverage==1
if isempty(dofixrange)

if exist('compareGroups','var') % added by Lukas: if we want to analyze & plot multiple groups

groupValues = unique(group, 'stable');
if size(colors,1) ~= size(groupValues,1)
colors = scn_standard_colors(length(groupValues))';
end

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'average','compareGroups', group);


else

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'average','Error_STD');
if isempty(dofixrange)

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure');

else % we have fixed range

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'dofixrange', dofixrange);

end
end

case 'correlation'

else

if exist('compareGroups','var') % % added by Lukas: if we want to analyze & plot multiple groups

groupValues = unique(group, 'stable');
if size(colors,1) ~= size(groupValues,1)
colors = scn_standard_colors(length(groupValues))';
if doAverage==1
if isempty(dofixrange)

if exist('compareGroups','var') % added by Lukas: if we want to analyze & plot multiple groups

groupValues = unique(group, 'stable');
if size(colors,1) ~= size(groupValues,1)
colors = scn_standard_colors(length(groupValues))';
end

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'average','compareGroups', group);

else

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'average','Error_STD');
end

else

if exist('compareGroups','var') % % added by Lukas: if we want to analyze & plot multiple groups

groupValues = unique(group, 'stable');
if size(colors,1) ~= size(groupValues,1)
colors = scn_standard_colors(length(groupValues))';
end

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'dofixrange', dofixrange, 'average', 'compareGroups', group);

else

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'dofixrange', dofixrange,'average','Error_STD');
end

end

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'dofixrange', dofixrange, 'average', 'compareGroups', group);

else

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'dofixrange', dofixrange,'average','Error_STD');
if isempty(dofixrange)

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure');

else % we have fixed range

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'dofixrange', dofixrange);

end
end

end

else
if isempty(dofixrange)

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure');

else % we have fixed range

[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'plotstyle', 'polar', 'networknames', ntmaps.metadata_table.target, 'colors', colors, 'nofigure', 'dofixrange', dofixrange);

end
end
end % switch similarity metric

else
[stats, hh, hhfill, table_group, multcomp_group] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'noplot');

switch similarity_metric

case 'cosine_similarity'

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, similarity_metric, 'noplot');

case 'correlation'

[stats, hh, hhfill] = image_similarity_plot(fmri_data_obj, 'mapset', ntmaps, 'noplot');

end % switch similarity metric

end
end % if doplot

end % main function

Expand Down
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