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checking installation
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Tanusree Chaudhuri
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Tanusree Chaudhuri
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,tchaudhuri,PCR15,25.05.2020 17:56,file:///home/tchaudhuri/.config/libreoffice/4; |
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function Allen_to_GroupSpace(Templates) | ||
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% ------ Transformation of ANO to group template space ------ % | ||
global DataDir; | ||
global TemplatesDir; | ||
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% 1. Increase resolution of allen templates (TPMs,ANO) to match group template resolution% | ||
MC_change_voxel_size(Templates); | ||
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% 2. Register TPMs to group template (Template_6) % | ||
matlabbatch{1}.spm.spatial.coreg.write.ref = cellstr(strcat(DataDir,'Template_6.nii,1')); | ||
matlabbatch{1}.spm.spatial.coreg.write.source = cellstr(Templates); | ||
matlabbatch{1}.spm.spatial.coreg.write.roptions.interp = 0; | ||
matlabbatch{1}.spm.spatial.coreg.write.roptions.wrap = [0 0 0]; | ||
matlabbatch{1}.spm.spatial.coreg.write.roptions.mask = 0; | ||
matlabbatch{1}.spm.spatial.coreg.write.roptions.prefix = 'r'; | ||
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spm_jobman('run',matlabbatch); | ||
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% Generate deformation fields (u_* files) % | ||
Registered_Templates = {strcat(TemplatesDir,'r_b1grey.nii,1');strcat(TemplatesDir,'r_b2white.nii,1')}; | ||
matlabbatch{1}.spm.tools.dartel.warp1.images = cellstr(Registered_Templates); | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.rform = 0; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(1).its = 3; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(1).rparam = [4 2 1e-06]; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(1).K = 0; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(1).template = cellstr(strcat(DataDir,'Template_0.nii')); | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(2).its = 3; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(2).rparam = [2 1 1e-06]; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(2).K = 0; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(2).template = cellstr(strcat(DataDir,'Template_1.nii')); | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(3).its = 3; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(3).rparam = [1 0.5 1e-06]; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(3).K = 1; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(3).template = cellstr(strcat(DataDir,'Template_2.nii')); | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(4).its = 3; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(4).rparam = [0.5 0.25 1e-06]; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(4).K = 2; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(4).template = cellstr(strcat(DataDir,'Template_3.nii')); | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(5).its = 3; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(5).rparam = [0.25 0.125 1e-06]; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(5).K = 4; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(5).template = cellstr(strcat(DataDir,'Template_4.nii')); | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(6).its = 3; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(6).rparam = [0.25 0.125 1e-06]; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(6).K = 6; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.param(6).template = cellstr(strcat(DataDir,'Template_6.nii')); | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.optim.lmreg = 0.01; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.optim.cyc = 3; | ||
matlabbatch{1}.spm.tools.dartel.warp1.settings.optim.its = 3; | ||
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spm_jobman('run',matlabbatch); | ||
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% 3. Normalise registered TPMs & ANO to group template space % | ||
matlabbatch{1}.spm.tools.dartel.crt_warped.flowfields = cellstr(strcat(TemplatesDir,'u_r_b1grey.nii')); | ||
TemplatesToWarp = {strcat(TemplatesDir,'r_b1grey.nii,1'); strcat(TemplatesDir,'r_b2white.nii,1');strcat(TemplatesDir,'ANO.nii')}; | ||
matlabbatch{1}.spm.tools.dartel.crt_warped.images = cellstr(TemplatesToWarp); | ||
matlabbatch{1}.spm.tools.dartel.crt_warped.jactransf = 0; | ||
matlabbatch{1}.spm.tools.dartel.crt_warped.K = 6; | ||
matlabbatch{1}.spm.tools.dartel.crt_warped.interp = 0; | ||
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spm_jobman('run',matlabbatch); |
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function idxLUT = BrAt_ComputeAreaSize(idxLUT,ANO,FIBT) | ||
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iio = find(ANO>0); | ||
F = sparse(ANO(iio),ones(length(iio),1),ones(length(iio),1)); | ||
idx = find(F>0); | ||
sz = full(F(idx)); | ||
for k = 1:length(idx), | ||
%iii = find(idx(k) == [idxLUT.id]); | ||
%idxLUT(iii).voxsz = sz(k); | ||
idxLUT(idx(k) == [idxLUT.id]).voxsz = sz(k); | ||
end | ||
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iio = find(FIBT>0); | ||
F = sparse(FIBT(iio),ones(length(iio),1),ones(length(iio),1)); | ||
idx = find(F>0); | ||
sz = full(F(idx)); | ||
for k = 1:length(idx), | ||
%iii = find(idx(k) == [idxLUT.id]); | ||
%idxLUT(iii).voxsz = sz(k); | ||
idxLUT(idx(k) == [idxLUT.id]).voxsz = sz(k); | ||
end | ||
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voxsz = zeros(1,length(idxLUT)); | ||
for k = 1:length(idxLUT) | ||
if isempty(idxLUT(k).voxsz) | ||
[common, ia, ib] = intersect([idxLUT.id],idxLUT(k).children); | ||
if not(isempty(ia)) | ||
voxsz = sum([idxLUT(ia).voxsz]); | ||
idxLUT(k).voxsz = voxsz; | ||
end | ||
end | ||
end | ||
end |
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function isSubset = CheckSubset(brain_region,ClusterLeaf) | ||
Int_region = annotation_tan(brain_region); | ||
Int_ClusterLeaf = annotation_tan(ClusterLeaf); | ||
isSubset = all(ismember(Int_ClusterLeaf,Int_region)); | ||
end |
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%function NamesOfClusterConstituents = ClusterLeafPath(NamesOfClusterConstituents,tree,ClusterLeaf,decValue) | ||
function single_path = ClusterLeafPath(tree,ClusterLeaf) | ||
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% --Path of cluster leaf-- % | ||
% load TREE | ||
[table idxLUT] = buildtable(tree); | ||
cluster_const = {}; | ||
paths_in_brain = {}; | ||
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for c = 1:length(table) | ||
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paths_in_brain{end + 1} = extractfield(table{c,1},'name'); | ||
end | ||
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for d = 1:length(paths_in_brain) | ||
single_path = paths_in_brain{1,d}; | ||
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indication_of_presence = find(ismember(single_path,ClusterLeaf)); | ||
if(~isempty(indication_of_presence) == 1) | ||
% cluster_const{end + 1} = single_path(end - 1); %% Replace string 'Flocculus' in Cluster_leaves with.. | ||
% disp(strcat('ClusterLeaf in path ',num2str(d))); | ||
% disp(single_path); | ||
%NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,single_path(end - decValue)); | ||
break; | ||
end | ||
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end | ||
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end |
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function NamesOfClusterConstituents = ClusterProportion(tree,brain_region, decValue,NamesOfClusterConstituents) | ||
for z = 2:length(NamesOfClusterConstituents) | ||
ClusterLeaf = NamesOfClusterConstituents{z,1}; | ||
isSubset = CheckSubset(brain_region,ClusterLeaf); | ||
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if(isSubset == 1) | ||
NamesOfClusterConstituents = ClusterLeafPath(NamesOfClusterConstituents,tree,ClusterLeaf,decValue); | ||
end | ||
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end | ||
end | ||
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function combinedtxt = ClusterProportionInPercentages(TemplatesDir,CC,img_cluster) | ||
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% ---------- Annotation Template ------------ % | ||
AnnotatedAllenBrain = spm_vol(strcat(TemplatesDir,'/','wANO.nii')); | ||
AnnotatedAllenBrain = spm_read_vols(AnnotatedAllenBrain); | ||
ClusterIntensitiesArr = AnnotatedAllenBrain(CC.PixelIdxList{1,img_cluster}); | ||
% ---------- Allen table ------------ % | ||
ANO = readtable(strcat(TemplatesDir,'/ANO.xlsx')); | ||
Region = table2array(ANO(:,1)); | ||
ID = table2array(ANO(:,4)); | ||
ID = ID'; | ||
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Region_index = {}; | ||
Labels = {}; | ||
ClusterLabels = {}; | ||
for i = 1:length(ClusterIntensitiesArr) | ||
Region_index{end + 1} = find(ID == ClusterIntensitiesArr(i)); | ||
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Labels{end + 1} = Region(Region_index{end}); | ||
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if(isempty(Labels{i}) == 0) | ||
ClusterLabels{end + 1} = Labels{1,i}{1,1}; | ||
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% ----- DISPLAY RESULTS ----- % | ||
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%x = cell2mat(ClusterConstituents(:,2)); | ||
x = tabulate(ClusterLabels); | ||
x2 = cell2mat(x(:,2)); | ||
p = pie(x2); | ||
% Get the percent contributions for each pie slice from the String | ||
% properties of the text objects.Then, specify the text that you want in the cell array txt. Concatenate the text with the associated percent values in the cell array combinedtxt. | ||
pText = findobj(p,'Type','text'); | ||
percentValues = get(pText,'String'); | ||
NamesOfClusterConstituents = x(:,1); | ||
txt = strcat(NamesOfClusterConstituents,': '); | ||
combinedtxt = strcat(txt,percentValues); | ||
else | ||
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combinedtxt = cellstr('cluster intensities not present in the annotation template'); | ||
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end | ||
end | ||
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%% ----- Old Allen Table ---- % | ||
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%load TREE | ||
%[table idxLUT] = buildtable(allen_brain_tree); | ||
%ID = extractfield(idxLUT,'id'); | ||
%ID = ID'; | ||
%Region = extractfield(idxLUT,'name'); | ||
%Region = Region'; | ||
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% --------------------------- % | ||
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%% | ||
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% %%%%%%%%% ------ Old Allen table --------%%%%%%%%% | ||
% [table idxLUT] = buildtable(allen_brain_tree); | ||
% RegionsHierarchyOfAllenBrain = extractfield(idxLUT,'nameinlist')'; | ||
% ID = {}; | ||
% for j = 1:length(idxLUT) | ||
% ID{end + 1} = extractfield(idxLUT(j),'children'); | ||
% end | ||
% ID = ID'; | ||
% %%%%%%%%% ----------------------------- %%%%%%%%%%%%% | ||
% | ||
% | ||
% % ------ Cluster Known Constituents.------ % | ||
% ClusterKnownConstituents = {}; | ||
% for k = 1:length(ClusterIntensitiesArr) | ||
% for l = 1:length(ID) | ||
% idx = find(ID{l,1} == ClusterIntensitiesArr(k)); | ||
% if(isempty(idx) == 0) | ||
% ClusterKnownConstituents{end + 1} = RegionsHierarchyOfAllenBrain{l,1}; | ||
% end | ||
% end | ||
% end | ||
% ClusterKnownConstituents = ClusterKnownConstituents'; | ||
% % save(strcat('Paths_',ClusterMasks_files{1,i}),'ClusterKnownConstituents'); | ||
% | ||
% % --Proportion of cluster constituents in voxels-- % | ||
% ClusterSizeInVoxels = length(ClusterIntensitiesArr); | ||
% hierarchy = ClusterKnownConstituents; | ||
% idx_nodes = Nodes_Idx(hierarchy); | ||
% KnownCluster_SizeInVoxels = length(idx_nodes{1,1}); | ||
% UnknownCluster_SizeInVoxels = ClusterSizeInVoxels - KnownCluster_SizeInVoxels; | ||
% | ||
% % --Names of Cluster Leaves-- %% | ||
% root_idx = idx_nodes{1,1}; | ||
% leaves_idx = []; | ||
% for m=2:length(root_idx) | ||
% leaves_idx(end + 1) = root_idx(m)-1; | ||
% end | ||
% Cluster_leaves = hierarchy(leaves_idx); | ||
% Cluster_leaves = strip(Cluster_leaves,'left','-'); | ||
% | ||
% name = 'Unknown'; | ||
% [ClusterUnknown{1:UnknownCluster_SizeInVoxels(1),1}] = deal(name); | ||
% SizeOfClusterUnknown = size(ClusterUnknown); | ||
% % disp(strcat('Size of unknown: ',num2str(SizeOfClusterUnknown))); | ||
% % ClusterUnknown = ClusterUnknown'; | ||
% ClusterKnown = Cluster_leaves; | ||
% ClusterConstituents = [ClusterUnknown;ClusterKnown]; | ||
% ClusterConstituents = tabulate(ClusterConstituents); | ||
% NamesOfClusterConstituents = ClusterConstituents(:,1); | ||
% | ||
% for z = 2:length(NamesOfClusterConstituents) | ||
% ClusterLeaf = NamesOfClusterConstituents{z,1}; | ||
% | ||
% isSubset_Cerebrum = CheckSubset('Cerebrum',ClusterLeaf); | ||
% isSubset_BrainStem = CheckSubset('Brain stem',ClusterLeaf); | ||
% isSubset_Cerebellum = CheckSubset('Cerebellum',ClusterLeaf); | ||
% if(isSubset_Cerebrum == 1) | ||
% isSubset_Isocortex = CheckSubset('Isocortex',ClusterLeaf); | ||
% isSubset_OLF = CheckSubset('Olfactory areas',ClusterLeaf); | ||
% isSubset_HPF = CheckSubset('Hippocampal formation',ClusterLeaf); | ||
% if(isSubset_Isocortex == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1)); | ||
% end | ||
% | ||
% if(isSubset_OLF == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1)); | ||
% end | ||
% | ||
% | ||
% if(isSubset_HPF == 1) | ||
% isSubset_HIP = CheckSubset('Hippocampal region',ClusterLeaf); | ||
% isSubset_RHP = CheckSubset('Retrohippocampal region',ClusterLeaf); | ||
% if(isSubset_HIP == 1) | ||
% isSubset_FC = CheckSubset('Fasciola cinerea',ClusterLeaf); | ||
% isSubset_IG = CheckSubset('Induseum griseum',ClusterLeaf); | ||
% if((isSubset_FC == 1) || (isSubset_IG == 1)) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0)); | ||
% else | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1)); | ||
% end | ||
% end | ||
% if(isSubset_RHP == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1)); | ||
% end | ||
% | ||
% end | ||
% | ||
% isSubset_CTXsp = CheckSubset('Cortical subplate',ClusterLeaf); | ||
% if(isSubset_CTXsp == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0)); | ||
% end | ||
% | ||
% isSubset_CNU = CheckSubset('Cerebral nuclei',ClusterLeaf); | ||
% if(isSubset_CNU == 1) | ||
% isSubset_CNU = CheckSubset('Olfactory tubercle',ClusterLeaf); | ||
% if(isSubset_CNU == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1)); | ||
% else | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0)); | ||
% end | ||
% end | ||
% end | ||
% | ||
% if(isSubset_BrainStem == 1) | ||
% isSubset_TH = CheckSubset('Thalamus',ClusterLeaf); | ||
% isSubset_HY = CheckSubset('Hypothalamus',ClusterLeaf); | ||
% isSubset_MB = CheckSubset('Midbrain',ClusterLeaf); | ||
% isSubset_HB = CheckSubset('Hindbrain',ClusterLeaf); | ||
% | ||
% if(isSubset_TH == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0)); | ||
% end | ||
% % if(isSubset_HY == 1) | ||
% % | ||
% % end | ||
% if(isSubset_MB == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0)); | ||
% end | ||
% if(isSubset_HB == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0)); | ||
% end | ||
% end | ||
% | ||
% if(isSubset_Cerebellum == 1) | ||
% isSubset_VERM = CheckSubset('Vermal regions',ClusterLeaf); | ||
% isSubset_HEM = CheckSubset('Hemispheric regions',ClusterLeaf); | ||
% isSubset_CBN = CheckSubset('Cerebellar nuclei',ClusterLeaf); | ||
% if(isSubset_VERM == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% VERM_id = find(contains(Path,'Vermal regions')); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(VERM_id + 1)); | ||
% end | ||
% if(isSubset_HEM == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% HEM_id = find(contains(Path,'Hemispheric regions')); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(HEM_id + 1)); | ||
% end | ||
% if(isSubset_CBN == 1) | ||
% Path = ClusterLeafPath(tree,ClusterLeaf); | ||
% CBN_id = find(contains(Path,'Cerebellar nuclei')); | ||
% NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(CBN_id + 1)); | ||
% end | ||
% end | ||
% end | ||
% ClusterConstituents(:,1) = NamesOfClusterConstituents; | ||
% | ||
% | ||
% | ||
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