atemplateobj.asv

classdef atemplateobj < handle
% Add networks and overlays to a smoothed brain mesh or gifti object.
%
% Plots: volumes, surfaces, overlays, networks, labels, videos. 
% Examples and usages below.
%
% If you get errors using the mex files, delete them. 
% Now uses fieldtrip to read nifti's.
%
% General usage:
%  - Specify inputs as 'PropertyName', 'PropoertyValue' pairs.
%  - Things you can define:
%
%    (a.) The brain mesh, using the 'mesh' flag, followed by one of these:
%            (1) a triangulated mesh
%            (2) gifti object
%            (3) nifti volume
%            (4) nifti/gifti filename
%            (5) flag for a built in default mesh: use 'def1' to 'def6'
%
%    (b.) A functional overlay, using the 'overlay' flag, followed by the
%    overlay values. (This should also be accompanied by the 'method' flag,
%    describing the method to use to project onto the surface, see [c] ).
%            (1) a 3D functional volume or the name of a nifti. atemplate
%            will automatically define some source positions.
%            (2) A vector of overlay values, along with a list of source
%            vertices (nx3) for each corresponding functional values. this
%            option also requires the 'sourcemodel' flag, for example:
%              atemplate('mesh','def1','overlay',OverlayVector,'sourcemodel',MyNx3ListOfPositions)
%            (3) Both an overlay vector AND curvature, with a theshold
%            supplied. This will project colour for the overlay and 
%            grayscale curvature elsewhere (like freesurfer):
%            atemplate('overlay',{'curvature',FunVol},'method','spheres','thresh',thr)
%
%    (c.) For overlays, there are multiple options for projecting from
%    source positions/volumes ontoa surface. This can be specified by the
%    'method' flag, followed by:
%            (1) 'raycast' - a ray casting routine (default)
%            (2) 'spheres' - inflated spheres
%            (3) 'euclidean' - a trap-radius distance method
%
%    (d.) Functional overlay values belonging to the AAL, HCP250 or
%    HarvardOxford atlas. Use the 'overlay' flag, followed by a vector of
%    functional values to plot. Also provide the 'method' flag, followed by
%    the name of the atlas:
%            (1) atemplate('overlay',randi([-4 4],90,1),'method',{'AAL90','raycast'})
%                - note must still provide a projection method in most cases
%            (2) as above, but using 'method',{'harvard_oxford','raycast'}
%            (3) as above, but using 'method',{'aal116','raycast'}
%            (4) as above, but using 'method',{'hoa_cerebellum','raycast'} - HarOx with cerebellum
%            (5) as above, but using 'method',{'hcp250','raycast'}
%
%            (6*) special case: when using AAL90 atlas data with default mesh 1 or 4
%                 there are precomputed parcels, use:
%                 atemplate('overlay',t,'method',{'aal_super',[]})
%
%    (e.) A Network, using the flag 'network' and provide:
%            (1) an NxN matrix, along with a sourcemodel using the
%            'sourcemodel' flag
%            (2) filename of a .edge file
%            (3) example call:  atemplate('network',N,'sourcemodel',v)
%            (4) Provide additional flag 'curved' and 1/0 to make the lines bendy
%
%    (f.) Nodes to accompany a network, using flag 'nodes': 
%           (1) atemplate('nodes',Vector/Matrix,'sourcemodel',Sources...)
%
%    (.g) OTHER OPTIONS (see bottom of script and example in folder):
%            (1) display only one hemisphere, flag 'hemi'  and 'l'/'r'
%            (2) provide both sources and list of ROI indices in the
%            sourcemodel flag, e.g. {v,vi}
%            (3) project to atlas space
%            (4) provide a parcellation and have functional overlay
%            registered to it / return parcellated data from non, use flag
%            'post_parcel',{v vi}
%            (5) if rendering overlay and network from different
%            sourcemodels, provide network sources using 'net_pos' flag
%
% SCROLL TO THE BOTTOM OF THIS FILE FOR A LONGER HELP AND MORE METHODS.
% Alexander Shaw [alexandershaw4@gmail.com | github.com/alexandershaw4]

properties

    in
    data

end


    methods

        function obj = atemplateobj(varargin)

        % defaults
        %--------------------------------------------------------------------------
        data         = struct;     % main output structure
        in.pmesh     = 1;          % flag to display the mesh or not
        in.labels    = 0;          % flag to display labels on rois
        in.write     = 0;          % flag to write mesh & overlay
        in.fname     = [];         % filename for saves (e.g. for sae gifti)
        in.fighnd    = [];         % put the plot into an existing figure handle
        in.colbar    = 1;          % display colourbar
        in.template  = 0;          % register source model to a template using ICP
        in.orthog    = 0;          % orthogonalise [ignore]
        in.inflate   = 0;          % inflate the mesh [just calls spm_mesh_inflate]
        in.inflate_n = 200;
        in.peaks     = 0;          % compute peaks on surface functional overlay
        in.components = 0;         % compute local maxima on functional overlay
        in.pca        = 0;         % compute pca on surface functional overlay
        in.flip       = 0;         % ignore
        in.affine     = 0;         % supply affine transformation matrix
        in.netcmap    = 0;         % colormap for network
        in.method     = 'raycast'; % volume to surface algorithm
        in.depth      = [];        % depth for raycasting
        in.all_roi_tissueindex = []; % indices of roi each voxel belongs to
        in.thelabels  = [];        % supply cell array of labels for rois
        in.tf_interactive = 0;     % ignore
        in.checkori       = 0;     % interactively check/adjust orientation of mesh
        in.fillholes      = 0;     % fill holes in mesh 
        in.hemi = 'both';          % hemisphere to plot
        in.roi  = [];              % roi list
        in.optimise = 0;           % explicitly optimise the alignments (gradient descent)
        in.post_parcel = [];       % parcellate an overlay post-projection
        in.thresh      = [];       % only display top % /threshold
        in.open        = 0;        % open the 2 hemispheres, i.e 2 plots
        in.verbose     = 0;         % print everything it does...
        in.dosphere    = 0;
        in.allsides    = 0;
        in.curvednet   = 0;
        in.netscale    = [];
        in.netthresh   = [];
        in.netthresh_nonzero = [];
        in.boundary = [];
        
        % specified inputs [override defaults]
        %--------------------------------------------------------------------------
        for i  = 1:length(varargin)
            if strcmp(varargin{i},'overlay');     in.L   = varargin{i+1}; end
            if strcmp(varargin{i},'verbose');     in.verbose = varargin{i+1}; end
            if strcmp(varargin{i},'dosphere');    in.dosphere = 1;        end
            if strcmp(varargin{i},'open');        in.open= 1;             end
            if strcmp(varargin{i},'allsides');    in.allsides= 1;         end
            if strcmp(varargin{i},'hemi');        in.hemi= varargin{i+1}; end
            if strcmp(varargin{i},'peaks');       in.peaks = 1;           end
            if strcmp(varargin{i},'sourcemodel'); in.pos = varargin{i+1}; end
            if strcmp(varargin{i},'netthresh');   in.netthresh = varargin{i+1}; end
            if strcmp(varargin{i},'netthresh_nonzero');   in.netthresh_nonzero = varargin{i+1}; end
            if strcmp(varargin{i},'roi');         in.roi = varargin{i+1}; end
            if strcmp(varargin{i},'network');     in.A   = varargin{i+1}; end
            if strcmp(varargin{i},'netscale');    in.netscale = varargin{i+1};end
            if strcmp(varargin{i},'net_pos');     in.net_pos = varargin{i+1}; end
            if strcmp(varargin{i},'curved');      in.curvednet = varargin{i+1}; end
            if strcmp(varargin{i},'tracks');      in.T   = varargin{i+1}; in.H = varargin{i+2}; end
            if strcmp(varargin{i},'nosurf');      in.pmesh  = 0;            end
            if strcmp(varargin{i},'nodes');       in.N = varargin{i+1};     end
            if strcmp(varargin{i},'gifti');       in.g = varargin{i+1};     end
            if strcmp(varargin{i},'mesh');        in.g = varargin{i+1};     end
            if strcmp(varargin{i},'boundary');    in.boundary = varargin{i+1};end
            if strcmp(varargin{i},'optimise');    in.optimise = varargin{i+1};end
            if strcmp(varargin{i},'post_parcel'); in.post_parcel = varargin{i+1};end
            if strcmp(varargin{i},'fillholes');   in.fillholes = 1;         end
            if strcmp(varargin{i},'thresh');      in.thresh = varargin{i+1};end
            if strcmp(varargin{i},'affine');      in.affine = varargin{i+1};end
            if strcmp(varargin{i},'funcaffine');  in.funcaffine = varargin{i+1}; end
            if strcmp(varargin{i},'inflate');     in.inflate = 1;           end
            if strcmp(varargin{i},'orthog');      in.orthog = varargin{i+1};end
            if strcmp(varargin{i},'components');  in.components = 1;        end
            if strcmp(varargin{i},'pca');         in.pca = 1;               end    
            if strcmp(varargin{i},'flip');        in.flip = 1;              end
            if strcmp(varargin{i},'checkori');    in.checkori = 1;          end
            if strcmp(varargin{i},'netcmap');     in.netcmap= varargin{i+1};end
            if strcmp(varargin{i},'write');       in.write  = 1; in.fname = varargin{i+1}; end
            if strcmp(varargin{i},'writestl');    in.write  = 2; in.fname = varargin{i+1}; end
            if strcmp(varargin{i},'writevrml');   in.write  = 3; in.fname = varargin{i+1}; end
            if strcmp(varargin{i},'writenii');    in.write  = 4; in.fname = varargin{i+1}; end
            if strcmp(varargin{i},'fighnd');      in.fighnd = varargin{i+1}; end
            if strcmp(varargin{i},'nocolbar');    in.colbar = 0;             end
            if strcmp(varargin{i},'method');      in.method = varargin{i+1}; end
            if strcmp(varargin{i},'depth');       in.depth  = varargin{i+1}; end
            if strcmp(varargin{i},'video');       in.V     = varargin{i+1}; 
                                                  in.fpath = varargin{i+2}; 
                                                  in.times = varargin{i+3}; end
            if strcmp(varargin{i},'inflate') 
                try 
                    if isnumeric(varargin{i+1});in.inflate_n = varargin{i+1};end
                end
            end                                  
            if strcmp(varargin{i},'othermesh');   in.M = varargin{i+1}; in.O = varargin{i+2};   end  
            if strcmp(varargin{i},'tf_interactive');in.tf_interactive = varargin{i+1}; end
            if strcmp(varargin{i},'labels');      in.labels = 1;
                try in.all_roi_tissueindex = varargin{i+1};
                    in.thelabels = varargin{i+2};
                end
            end
            if strcmp(varargin{i},'template')
                in.template = 1;
                in.model    = varargin{i+1};
            end  

            obj.in = in;
            obj.data = data;
            
%             % Allow passing of existing atemplate-returned structure 
%             if isstruct(varargin{i}) && isfield(varargin{i},'in')
%                 fprintf('User specified plot structure\n');
%                 data = varargin{i};
%                 mesh = parse_mesh(data.mesh,data.in,data);
%                 data = parse_plots(data,data.in);
%                 return
%             end
        end
        
        end

        function run(obj)
        
            in = obj.in;
            data = obj.data;

        
            % Preliminaries & parse functions for plots
            %--------------------------------------------------------------------------
            data.verbose = in.verbose; % make sure every subfunction knows if verbose mode
            
            if in.open
                data = isopen(data,in);
                return;
            end
            
            if in.allsides
                data = allsides(data,in);
                return;
            end
            
            data = obj.sort_sourcemodel(data,in);       % Sourcemodel vertices
            
            [mesh,data] = obj.get_mesh(in,data);        % Get Surface
            
            [data,in] = obj.sort_template(data,in);     % Template space? (aal90/78/58)
            
            [mesh,data] = obj.parse_mesh(mesh,in,data); % Mesh to put stuff on
            data.mesh   = mesh;
            
            data = obj.parse_plots(data,in); % Overlays, networks, tracts, nodes, videos etc.
            
            data.in = in; % Return the input options for re-run
            
            % draw boundaries of ROIs
            if ~isempty(in.boundary)
                
                iv = in.boundary;
                p  = [];
                
            end
        
        end
    
    
    
    
    
    % FUNCTIONS
    %--------------------------------------------------------------------------
    %--------------------------------------------------------------------------
    function data = isopen(obj,data,in)
        % a wrapper on atemplate for generating the same plot for the left and
        % right hemis separately in different sublots
        s(1) = subplot(121);
        s(2) = subplot(122);
        
        data_in     = data;
        
        % Plot 1.
        in.hemi     = 'l';
        in.fighnd   = s(1);
        data        = sort_sourcemodel(data_in,in); % Sourcemodel vertices
        [mesh,data] = get_mesh(in,data);         % Get Surface
        [data,in]   = sort_template(data,in);    % Template space? (aal90/78/58)
        [mesh,data] = parse_mesh(mesh,in,data);  % Mesh to put stuff on
        data.mesh   = mesh;
        data        = parse_plots(data,in);      % Overlays, networks, etc
        data.in     = in;                        % Return everything
        data_l      = data;
        
        view([90 0]);
        
        % Plot 2.
        in.hemi     = 'r';
        in.fighnd   = s(2);
        data        = sort_sourcemodel(data_in,in); % Sourcemodel vertices
        [mesh,data] = get_mesh(in,data);         % Get Surface
        [data,in]   = sort_template(data,in);    % Template space? (aal90/78/58)
        [mesh,data] = parse_mesh(mesh,in,data);  % Mesh to put stuff on
        data.mesh   = mesh;
        data        = parse_plots(data,in);      % Overlays, networks, etc
        data.in     = in;                        % Return everything
        data_r      = data;
        
        view([270 0]);
        
        data   = [];
        data.l = data_l;
        data.r = data_r;
    
    end
    
    function data = allsides(obj,data,in)
        % a wrapper on atemplate for generating the same plot for the left and
        % right hemis separately in different sublots
    
        s           = in.fighnd;
        data_in     = data;
        
        % Plot 1.
        in.hemi     = 'r';
        in.fighnd   = s(1);
        data        = sort_sourcemodel(data_in,in); % Sourcemodel vertices
        [mesh,data] = get_mesh(in,data);         % Get Surface
        [data,in]   = sort_template(data,in);    % Template space? (aal90/78/58)
        [mesh,data] = parse_mesh(mesh,in,data);  % Mesh to put stuff on
        data.mesh   = mesh;
        data        = parse_plots(data,in);      % Overlays, networks, etc
        data.in     = in;                        % Return everything
        data_l      = data;
        
        view([90 0]);
        
        % Plot 2.
        in.hemi     = 'r';
        in.fighnd   = s(2);
        data        = sort_sourcemodel(data_in,in); % Sourcemodel vertices
        [mesh,data] = get_mesh(in,data);         % Get Surface
        [data,in]   = sort_template(data,in);    % Template space? (aal90/78/58)
        [mesh,data] = parse_mesh(mesh,in,data);  % Mesh to put stuff on
        data.mesh   = mesh;
        data        = parse_plots(data,in);      % Overlays, networks, etc
        data.in     = in;                        % Return everything
        data_l      = data;
        
        view([-90 0]);
        
        % Plot 3.
        in.hemi     = 'l';
        in.fighnd   = s(3);
        data        = sort_sourcemodel(data_in,in); % Sourcemodel vertices
        [mesh,data] = get_mesh(in,data);         % Get Surface
        [data,in]   = sort_template(data,in);    % Template space? (aal90/78/58)
        [mesh,data] = parse_mesh(mesh,in,data);  % Mesh to put stuff on
        data.mesh   = mesh;
        data        = parse_plots(data,in);      % Overlays, networks, etc
        data.in     = in;                        % Return everything
        data_r      = data;
        
        view([-270 0]);
        
        % Plot 4.
        in.hemi     = 'l';
        in.fighnd   = s(4);
        data        = sort_sourcemodel(data_in,in); % Sourcemodel vertices
        [mesh,data] = get_mesh(in,data);         % Get Surface
        [data,in]   = sort_template(data,in);    % Template space? (aal90/78/58)
        [mesh,data] = parse_mesh(mesh,in,data);  % Mesh to put stuff on
        data.mesh   = mesh;
        data        = parse_plots(data,in);      % Overlays, networks, etc
        data.in     = in;                        % Return everything
        data_r      = data;
        
        view([270 0]);
    
        data   = [];
        data.l = data_l;
        data.r = data_r;
    
    end
    
    
    function data = parse_plots(obj,data,i)
    
    % unpack triggers
    inputs = i;
    
    % overlays
    if isfield(inputs,'L')
        % copy over overlay options
        data.overlay.peaks      = i.peaks;
        data.overlay.components = i.components;
        data.overlay.pca        = i.pca;
        data.overlay.method     = i.method;
        data.overlay.depth      = i.depth;
        data.overlay.thresh     = i.thresh;
        data.overlay.tf_interactive = i.tf_interactive;
        
        if isfield(i,'funcaffine')
            data.overlay.affine = i.funcaffine;
        end
        
        data = overlay(data, (i.L),i.write,i.fname,i.colbar);
    end 
    
    isover = exist('L','var') || exist('V','var');
    if  isover && exist('A','var') 
        i.colbar = 0;
        alpha(.2);
    end
    
    % networks
    if isfield(inputs,'A')
        data.network.scale = i.netscale;
        data.network.netthresh = i.netthresh;
        data.network.netthresh_nonzero = i.netthresh_nonzero;
        data = connections(data,i.A,i.colbar,i.write,i.fname,i.netcmap,i.curvednet); 
    end 
    
    % tracts
    if isfield(inputs,'T')
        data = drawtracks(data,i.T,i.H);                  
    end 
    
    % nodes
    if isfield(inputs,'N')
        data = drawnodes(data, i.N);                 
    end 
    
    % labels
    data = parse_labels(i,data);
    
    % video
    if isfield(inputs,'V')
        tv = 1:size(i.V,2);
        try tv = i.times; end
        data = video(data,i.V,1,i.fpath,tv); 
    end
    
    
    end
    
    function data = parse_labels(obj,i,data)
    % decide which labels to include depending on what we're plotting
    if i.labels 
        if     isfield(i,'A')
                    if isnumeric(i.A)
                        data = addlabels(data,i.A,i.all_roi_tissueindex,i.thelabels);
                    elseif ischar(i.A)
                        E = data.network.edge;
                        data = addlabels(data,E,i.all_roi_tissueindex,i.thelabels);
                    end
               
        elseif isfield(i,'N')
            if sum(ismember(size(i.N),[1 90])) == 2
                data = addlabels(data, diag(i.N),i.all_roi_tissueindex,i.thelabels);
            elseif sum(ismember(size(i.N),[1 90])) == 1
                data = addlabels(data, diag(sum(i.N,2)),i.all_roi_tissueindex,i.thelabels);
            end
            
        else;  n    = length(data.sourcemodel.pos);
               data = addlabels(data, ones(n,n),i.all_roi_tissueindex,i.thelabels);
        end
    end
    end
    
    function data = sort_sourcemodel(obj,data,i)
    % Sort out what source model vertices we're going to use
    
    if      isfield(i,'pos')
                 if i.verbose
                    fprintf('+Using supplied sourcemodel vertices\n');
                 end
                pos = i.pos;
            
    elseif  isfield(i,'A') && ischar(i.A)
            if i.verbose
                fprintf('+Using coords in node-file as sourcemodel\n');
            end
            
            [~,pos] = rw_edgenode(i.A); 
            pos = pos(:,1:3);
            
    %  elseif  isfield(i,'L') && ischar(i.L)
    %          %IF USING A NIFTI OVERLAY AS SOURCEMODEL, NEED THIS *before* TRYING TO DO
    %          %TEMPLATE SPACE CONVERSION!
    %          
    %          [mesh,data] = get_mesh(i,data);
    %          data.mesh = mesh;
    %          [~,data]  = parse_overlay(i.L,data);
    %          pos       = data.sourcemodel.pos;
             
    else
            if i.verbose
                fprintf('+Assuming AAL90 source vertices by default\n');
            end
            load('AAL_SOURCEMOD');
            pos  = template_sourcemodel.pos;
    end
    
    if iscell(pos)
        % store 2nd input - vector descrbinig which vertices belong to which rois
        data.sourcemodel.vi = pos{2};
        pos                 = pos{1};
    end
    
    % Centre sourcemodel
    dpos = pos - repmat(spherefit(pos),[size(pos,1),1]);
    
    % Ensure stability if approaching centre (very tiny values)
    if ~any(isnan(dpos(:)))
        pos = dpos;
    end
    
    data.sourcemodel.pos = pos;
    
    % add ability to have network on a separate sourcemodel to overlay
    if isfield(i,'net_pos') && size(i.net_pos,2)==3
        if i.verbose
            fprintf('++Also found a set of source vertices for a network\n');
        end
        data.sourcemodel.net_pos = i.net_pos;
    end
    
    % not hugely revelant here, but use this func to also store data for the
    % post-hoc atlas-registration function if required
    if iscell(i.post_parcel)
        data.post_parcel = i.post_parcel;
    end
    
    
    end
    
    function [mesh,data] = parse_mesh(obj,mesh,i,data)
    % Figure out whether we actually want to plot a glass brain mesh, or not
    
    % if only one hemisphere plot
    hemi      = i.hemi;
    data.hemi = hemi;
    
    % if affine supplied or flip flag
    affine = i.affine;
    flip   = i.flip;
    
    % if inflate, pass flag
    inflate = i.inflate;
    
    mesh.inflate = i.inflate_n; % allow passing amount to inflate
    mesh.do_ball = i.dosphere;
    
    % check orientation?
    checkori = i.checkori;
    
    % fill holes during hemisphere separation?
    dofillholes = i.fillholes;
    
    % explicitly optimise the alignment of the cloud points?
    optimise = i.optimise;
    
    if     i.pmesh && ~isfield(i,'T')
           [mesh,data.sourcemodel.pos,h,p] = obj.meshmesh(mesh,i.write,i.fname,i.fighnd,...
               .3,data.sourcemodel.pos,hemi,affine,flip,inflate,checkori,dofillholes,optimise,i.verbose);
    elseif i.pmesh
           [mesh,data.sourcemodel.pos,h,p] = obj.meshmesh(mesh,i.write,i.fname,i.fighnd,...
               .3,data.sourcemodel.pos,hemi,affine,flip,inflate,checkori,dofillholes,optimise,i.verbose);
    else
        h = [];
        p = [];
    end
    
    mesh.h = h;
    mesh.p = p;
    end
    
    function [mesh, data] = convert_mesh(obj,mesh,data)
    % Convert a STRUCTURAL volume to a surface mesh using an isosurface. Take
    % some liberties with downsampling and rescaling 
    
    if ischar(mesh)
        [fp,fn,fe] = fileparts(mesh);
        
        switch fe
            
            case{'.gz'}
                if data.verbose
                    fprintf('-Unpacking .gz\n');
                end
                gunzip(mesh);
                mesh = strrep(mesh,'.gz','');
                [mesh, data] = obj.convert_mesh(mesh,data);
                return;
                
            case{'.nii','.mri'}
                %wb = waitbar(0,'Reading nifti volume...');
                
                % mini switch for load type
                switch fe
                    case '.nii'
                        % load nifti volume file
                        if data.verbose
                            fprintf('-Reading Nifti volume\n');
                        end
    %                     ni    = load_nii(mesh);
    %                     vol   = ni.img;
    %                     
    %                     % recover rotation matrix
    %                     b = ni.hdr.hist.quatern_b;
    %                     c = ni.hdr.hist.quatern_c;
    %                     d = ni.hdr.hist.quatern_d;
    %                     x = ni.hdr.hist.qoffset_x;
    %                     y = ni.hdr.hist.qoffset_y;
    %                     z = ni.hdr.hist.qoffset_z;
    %                     a = sqrt(1.0-(b^2+c^2+d^2));
    %                     
    %                     R =  [ a*a+b*b-c*c-d*d   2*b*c-2*a*d       2*b*d+2*a*c     ;
    %                            2*b*c+2*a*d       a*a+c*c-b*b-d*d   2*c*d-2*a*b     ;
    %                            2*b*d-2*a*c       2*c*d+2*a*b       a*a+d*d-c*c-b*b ];
    %                     t = [x; y; z];
    
                        % just use fieldtrip
                        ni  = ft_read_mri(mesh);
                        vol = ni.anatomy; 
                        
                        R = ni.transform(1:3,1:3);
                        t = ni.transform(1:3,end);
                        
                        % real-world coordinates = 
                        %[x; y; z] = R * [i; j; k] + t
                        
                        [nx,ny,nz] = size(vol);
                        
                        % compute edges and linearly interp grid coordinates
                        E1 = R*[1 ;1 ;1 ]+t;
                        E2 = R*[nx;ny;nz]+t;
                        
                        xarr = linspace(E1(1),E2(1),nx);
                        yarr = linspace(E1(2),E2(2),ny);
                        zarr = linspace(E1(3),E2(3),nz);
                                            
                        % NEW: subsample volume by 2. This speeds up subsequent patch
                        % reduction enormously with at relatively little cost to
                        % resolution
                        if data.verbose
                            fprintf('-Subsampling structural volume\n');
                        end
                        [xg,yg,zg] = meshgrid(yarr,xarr,zarr);
                        [NX, NY, NZ, vol] = reducevolume(xg,yg,zg,vol,4);
                        xarr = linspace(xarr(1),xarr(end),size(vol,1));
                        yarr = linspace(yarr(1),yarr(end),size(vol,2));
                        zarr = linspace(zarr(1),zarr(end),size(vol,3));
    
                        [X,Y,Z] = meshgrid(yarr,xarr,zarr);
                        
                        
                    case '.mri'
                        % load ctf mri file
                        if data.verbose
                            fprintf('-Reading CTF_MRI4 volume\n');
                        end
                        ni  = ft_read_mri(mesh,'dataformat','ctf_mri4');
                        vol = ni.anatomy;
                        vol = vol - mean(vol(:));                    
                end
                
                
                if ndims(vol) ~= 3
                    fprintf('-Volume has wrong number of dimensions!\nUsing default mesh\n');
                    mesh = read_nv;
                    return
                end
                
                % bounds:
                %waitbar(0.2,wb,'Reading nifti volume: Extracting isosurface');
                if data.verbose
                    fprintf('-Extracting ISO surface\n');
                end
                B   = [min(data.sourcemodel.pos); max(data.sourcemodel.pos)];
                
                try    fv  = isosurface(X,Y,Z,vol,0.5); % nifti's 
                catch; fv  = isosurface(vol,0.5);       % .mri's / other volumes
                end
                
                % swap x y
                v  = fv.vertices;
                v  = [v(:,2) v(:,1) v(:,3)];
                fv.vertices = v;
                 
                % reduce vertex density
                %waitbar(0.6,wb,'Reading nifti volume: Reducing density');
                if data.verbose
                    fprintf('-Reducing patch density\n');
                end
                nv  = length(fv.vertices);
                count  = 0;
                            
                while nv > 60000
                   fv    = reducepatch(fv, 0.5);
                   nv    = length(fv.vertices);
                   count = count + 1;
                end
                
                %if count > 0
                %    fprintf('Smoothing surface\n');
                %    fv.vertices = sms(fv.vertices,fv.faces,1,2);
                %end
    
                % print
                %waitbar(0.9,wb,'Reading nifti volume: Rescaling');
                if data.verbose
                    fprintf('-Patch reduction finished\n');
                    fprintf('-Rescaling mesh to sourcemodel\n');
                end
                
                v = fv.vertices;
                for i = 1:3
                    v(:,i) = obj.rescale(v(:,i),B(:,i));
                end
                
                % return scaled mesh
                mesh            = [];
                mesh.nifti      = [fn fe];
                mesh.faces      = fv.faces;
                mesh.vertices   = v;
                mesh.vol        = vol;
                data.mesh       = mesh;
                
                %close(wb);
                
            case{'.gii'}
                % load the gifti
                gi   = gifti(mesh);
                mesh          = [];
                mesh.faces    = gi.faces;
                mesh.vertices = gi.vertices;
                data.mesh     = mesh;
            
            otherwise
                
                % allow shorthands call for default meshes
                %-----------------------------------------
                if strcmp(lower(mesh),'def') || strcmp(lower(mesh),'def1')
                    % ICBM152 - smoothed
                    nmesh         = read_nv;
                    mesh          = [];
                    mesh.vertices = nmesh.vertices;
                    mesh.faces    = nmesh.faces;
                end
                if strcmp(lower(mesh),'def2')
                    % Ch2
                    nmesh         = gifti('BrainMesh_Ch2.gii');
                    mesh          = [];
                    mesh.vertices = nmesh.vertices;
                    mesh.faces    = nmesh.faces;
                end
                if strcmp(lower(mesh),'def3')
                    % mni152_2009
                    nmesh         = load('mni152_2009','faces','vertices');
                    mesh          = [];
                    mesh.vertices = nmesh.vertices;
                    mesh.faces    = nmesh.faces;
                end
                if strcmp(lower(mesh),'def4')
                    nmesh         = gifti('BrainMesh_ICBM152.gii');
                    mesh          = [];
                    mesh.vertices = nmesh.vertices;
                    mesh.faces    = nmesh.faces;
                end
                if strcmp(lower(mesh),'def5')
                    nmesh         = load('ft_mesh_mni');
                    mesh          = [];
                    mesh.vertices = nmesh.vertices;
                    mesh.faces    = nmesh.faces;
                end
                if strcmp(lower(mesh),'def6')
                    nmesh         = gifti('cortex_8196.surf.gii');
                    mesh          = [];
                    mesh.vertices = nmesh.vertices;
                    mesh.faces    = nmesh.faces;
                end
                if strcmp(lower(mesh),'def7')
                    nmesh         = gifti('bh.headbrain.TPM.gii');
                    mesh          = [];
                    mesh.vertices = nmesh.vertices;
                    mesh.faces    = nmesh.faces;
                end
        end
        
    elseif isnumeric(mesh) && ndims(mesh)==3
               
                % bounds:
                %wb = waitbar(0,'Reading nifti volume...');
                %waitbar(0.2,wb,'Reading nifti volume: Extracting isosurface');
                
                % NEW: subsample volume by 2. This speeds up subsequent patch
                % reduction enormously with at relatively little cost to
                % resolution
                if data.verbose
                    fprintf('-Subsampling structural volume\n');
                end
                [NX, NY, NZ, mesh] = reducevolume(mesh,2);
    
                if data.verbose
                    fprintf('-Extracting ISO surface\n');
                end
                B   = [min(data.sourcemodel.pos); max(data.sourcemodel.pos)];
                fv  = isosurface(mesh,0.5);            
                
                % swap x y
                v  = fv.vertices;
                v  = [v(:,2) v(:,1) v(:,3)];
                fv.vertices = v;
                 
                % reduce vertex density
                if data.verbose
                    fprintf('-Reducing patch density\n');
                end
                nv  = length(fv.vertices);
                count  = 0;
                
                %waitbar(0.6,wb,'Reading nifti volume: Reducing density');
                while nv > 60000
                    fv    = reducepatch(fv, 0.5);
                    nv    = length(fv.vertices);
                    count = count + 1;
                end
    
                % print
                if data.verbose
                    fprintf('-Patch reduction finished\n');
                    fprintf('-Rescaling mesh to sourcemodel\n');
                end
                
                %waitbar(0.9,wb,'Reading nifti volume: Rescaling');
                v = fv.vertices;
                for i = 1:3
                    v(:,i) = obj.rescale(v(:,i),B(:,i));
                end
                
                % return scaled mesh
                mesh            = [];
                mesh.faces      = fv.faces;
                mesh.vertices   = v;
                data.mesh       = mesh;    
                
                %close(wb);        
    end
    
    end
    
    function [data,i] = sort_template(obj,data,i)
    % If specified a template model, register data to it and return splined data as
    % well as weights
    
    if ~isfield(i,'pos')
        i.pos = data.sourcemodel.pos;
    end
    try
        data.template.model  = i.model;
        data.template.labels = i.labels;
    end
    if i.template
        atlas = obj.dotemplate(i.model);
        rois  = obj.get_roi_centres(atlas.template_sourcemodel.pos,atlas.all_roi_tissueindex);
        
        atlas.template_sourcemodel.pos = rois;
        atlas = rmfield(atlas,'all_roi_tissueindex');
        
        reg = obj.interp_template(data.sourcemodel,rois);
        atlas.M    = reg.M;
        data.atlas = atlas;
        NM         = atlas.M;
        
        % rescale so not change amplitudes
        m  = max(NM(:));
        NM = NM/m; 
        
        data.atlas.M = NM;
        
        % generate & apply a ROI mask if requested
        %----------------------------------------------------
        if isfield(i,'roi') && ~isempty(i.roi)
            
            % should be cell array of labels
            if ischar(i.roi)
                i.roi = {i.roi};
            end
            
            % check rois exist
            labs     = atlas.AAL_Labels;
            for iroi = 1:length(i.roi)
                ROI_ind(iroi) = find(strcmp(i.roi{iroi},labs));
                
                if isempty( ROI_ind(iroi) )
                    fprintf('Requested ROI (%s) not found\n');
                end
            end
            
            % apply mask!
            newM = NM*0;
            newM(:,ROI_ind) = NM(:,ROI_ind);
            NM   = newM;
        end
        
        % update sourcemodel and labels
        data.sourcemodel = atlas.template_sourcemodel;
        if i.labels; i.thelabels = atlas.AAL_Labels; end
        
        % overlay data
        if isfield(i,'L')
            if isnumeric(i.L) && ndims(i.L) ~= 3
                S  = [min(i.L(:)) max(i.L(:))];
                NL = i.L(:)'*NM;
                L  = S(1) + ((S(2)-S(1))).*(NL - min(NL))./(max(NL) - min(NL));
                L(isnan(L))=0;
                i.L = L;
            end
        end
        
        % network
        if isfield(i,'A')
            if isnumeric(i.A)
                S  = [min(i.A(:)) max(i.A(:))];
                NL = NM'*i.A*NM;
                A  = S(1) + ((S(2)-S(1))).*(NL - min(NL(:)))./(max(NL(:)) - min(NL(:)));
                A(isnan(A)) = 0;
                i.A = A;
            end
        end
        
        % video data
        if isfield(i,'V')
            S  = [min(i.V(:)) max(i.V(:))];
            for j = 1:size(i.V,2) % over time points
                NL(:,j) = i.V(:,j)'*NM;
            end
            V  = S(1) + ((S(2)-S(1))).*(NL - min(NL))./(max(NL) - min(NL));
            V(isnan(V))=0;
            if orthog
                % dont use this
                V = obj.symm_orthog(V);
            end
            V(isnan(V))=0;
            i.V = V;
        end
            
    end
    
    end
    
    function [mesh,data] = get_mesh(obj,i,data)
    % Decide what brain we're actually using, return it
    
    try   mesh = i.g;
        if i.verbose
            fprintf('+Using user provided mesh\n');
        end
        
          if ischar(mesh) || isnumeric(mesh)
              [mesh,data] = obj.convert_mesh(mesh,data);
          end
          
    catch mesh = read_nv();
          if i.verbose
              fprintf('+Using template brain mesh\n');
          end
    end
    
    % if i.inflate
    %     try fprintf('Trying to inflate mesh\n');
    %         dmesh.vertices = mesh.vertices;
    %         dmesh.faces    = mesh.faces;
    %         dmesh = spm_mesh_inflate(dmesh,100);
    %         mesh.vertices = dmesh.vertices;
    %         mesh.faces    = dmesh.faces;
    %     catch
    %         fprintf('Couldnt find spm_mesh_inflate: is SPM installed?\n');
    %     end
    % end
    
    
    end
    
    function atlas = dotemplate(obj,model)
    % Put dense sourcemodel into an atlas space using ICP and linear
    % interpolation
    %
    %
    %
    
    if ischar(model)
        switch model
            case lower({'aal','aal90'});   load New_AALROI_6mm.mat
            case lower('aal58');           load New_58cortical_AALROI_6mm
            case lower('aal78');           load New_AALROI_Cortical78_6mm
            otherwise
                fprintf('Model not found.\n');
                return;
        end
    elseif iscell(model)
        template_sourcemodel.pos = model{1};
        all_roi_tissueindex      = model{2};
        AAL_Labels = [];
    end
    
    atlas.AAL_Labels = AAL_Labels;
    atlas.all_roi_tissueindex = all_roi_tissueindex;
    atlas.template_sourcemodel = template_sourcemodel;
    
    end
    
    function atlas = interp_template(obj,atlas,pos)
    % The Euclidean/ICP routine for atlas registration
    
    if length(atlas.pos) == length(pos)
        fprintf('Overlay and atlas Vectors already match!\n');
        atlas.M = eye(length(pos));
        return;
    end
    
    fprintf('Scanning points:\n');
    M = zeros( length(atlas.pos), length(pos) )';
    r = round( pi*floor( length(atlas.pos) / length(pos) ) );%1;
    %w = 1;
    w = (1:r)/r;
    
    dist  = cdist(pos,atlas.pos)';    
    %for i = 1:length(atlas.pos)
    for i = 1:length(pos)    
        if i > 1; fprintf(repmat('\b',[size(str)])); end
        str = sprintf('%d/%d',i,(length(pos)));
        fprintf(str);
    
        [junk,ind] = maxpoints(dist(:,i),r,'min');
        M (i,ind)  = w;
    end
    fprintf('\n');
    atlas.M = M';
    
    end
    
    function y = symm_orthog(obj,x)
    % Efficient symmetric orthogonalisation method for matrices, using:
    %
    % y = x * real(inv(x' * x)^(1/2));
    %
    % AS
    
    fprintf('\nOrthogonalising\n');
    y = [x] * real(inv([x]' * [x])^(1/2));
    y = (max(x(:)) - min(x(:))) * ( (y - min(y(:))) / (max(y(:)) - min(y(:))) );
    
    end
    
    function data = connections(obj,data,A,colbar,write,fname,netcmap,curved)
    % Network (Node & Edges) plotter function
    %
    %
    
    if isfield(data.sourcemodel,'net_pos')
        pos = data.sourcemodel.net_pos;
    else
        pos = data.sourcemodel.pos;
    end
    
    if isfield(data.sourcemodel,'vi')
        % if pos is cell, it's because we've passed both a vertex set and a
        % vector that describes which vertex belongs to which roi
        v  = pos;
        vi = data.sourcemodel.vi;
        n  = unique(vi);
        roi = zeros(max(n),3);
        for i = 1:length(n)
            these = find(vi==n(i));
            roi(n(i),:) = spherefit(v(these,:));
        end
        pos = roi;
        for ip = 1:length(pos)
            if any(pos(ip,:))
                [~,this]  = min(cdist(pos(ip,:),data.mesh.vertices));
                pos(ip,:) = data.mesh.vertices(this,:);
            end
        end
    end
    
    
    % Read edge/node files if string
    %--------------------------------------------------------------------------
    if ischar(A)
        [fp,fn,fe]  = fileparts(A);
        [edge,node] = rw_edgenode(fn);
        A           = edge;
        
        if isfield(data,'template')
            if isfield(data.template,'model')
               fprintf('Doing atlas registration\n');
               i.template = 1;
               i.model    = data.template.model;
               i.labels   = data.template.labels;
               i.A        = A;
               data.sourcemodel.pos = node(:,1:3);
               [data,i]   = sort_template(data,i);
               A          = i.A;
            end
        end
    end
    
    A(isnan(A)) = 0;
    A(isinf(A)) = 0;
    
    % rescale network positions inside box boundaries of mesh
    % (i thought meshmesh had already done this?)
    if ~isempty(data.mesh.h)
        bounds = [min(data.mesh.vertices); max(data.mesh.vertices)];
        offset = 0.99;
        for ip = 1:3
            pos(:,ip) = bounds(1,ip) + ((bounds(2,ip)-bounds(1,ip))) .* ...
                        (pos(:,ip) - min(pos(:,ip)))./(max(pos(:,ip)) - min(pos(:,ip)));
            pos(:,ip) = pos(:,ip)*offset;
        end
    
        % redirect to closest mesh point (vertex)
        for ip = 1:length(pos)
            [~,this]  = min(cdist(pos(ip,:),data.mesh.vertices));
            pos(ip,:) = data.mesh.vertices(this,:);
        end
    end
            
    A = A.*~eye(length(A));
    if ~any(spm_vec(triu(A))) && any(spm_vec(tril(A)))
        A = tril(A)';
        fprintf('Rendering lower triangular portion\n');
    end
    
    % threshold top n-percent
    if ~isempty(data.network.netthresh)
        fprintf('Thresholding to top %d percent\n',data.network.netthresh*100);
        nthr = data.network.netthresh;
        tA   = triu(A);
        vA   = spm_vec(tA);
        [~,ord] = sort(abs(vA),'descend');
        nc = round(length(ord)*nthr);
        nA = vA*0;
        nA(ord(1:nc)) = vA(ord(1:nc));
        tA = spm_unvec(nA,tA);
        A = tA + triu(tA)';
    end
    
    % threshold top n-percent
    if ~isempty(data.network.netthresh_nonzero)
        fprintf('Thresholding to top %d percent of non-zero\n',data.network.netthresh*100);
        nthr = data.network.netthresh_nonzero;
        tA   = triu(A);
        vA   = spm_vec(tA);
        [~,ord] = sort(abs(vA),'descend');
        nc = round(length(find(vA))*nthr);
        nA = vA*0;
        nA(ord(1:nc)) = vA(ord(1:nc));
        tA = spm_unvec(nA,tA);
        A = tA + triu(tA)';
    end
    
    % Edges
    %--------------------------------------------------------------------------
    [node1,node2,strng] = obj.matrix2nodes(triu(A),pos);
    
    % New addition December 2020
    switch lower(data.hemi)
        case 'left' ; 
            n1 = find( node1(:,1) > max(data.mesh.h.Vertices(:,1)) );
            n2 = find( node2(:,1) > max(data.mesh.h.Vertices(:,1)) );
            pnt = max(data.mesh.h.Vertices(:,1));
            node1(n1,1) = pnt;
            node2(n2,1) = pnt;
        case 'right' ;
            n1 = find( node1(:,1) < min(data.mesh.h.Vertices(:,1)) );
            n2 = find( node2(:,1) < min(data.mesh.h.Vertices(:,1)) );
            pnt = min(data.mesh.h.Vertices(:,1));
            node1(n1,1) = pnt;
            node2(n2,1) = pnt;
    end
    
    % COLOUR BAR SCALING:
    if ~isempty(data.network.scale)
        thescale = [-data.network.scale;data.network.scale];
    else
        thescale = [-max(abs(strng)); max(abs(strng))];
    end
    
    %strng2 = linspace(thescale(1),thescale(2),length(strng));
    
    % place both signed absmax value in overlay so that colorbar is symmetrical
    
    % rescale the data to the colorbar edges (?)
    if ~isempty(data.network.scale)
        strng2 = strng;
        strng2( strng2<=(thescale(1)) ) = thescale(1);
        strng2( strng2>=(thescale(2)) ) = thescale(2);
        %strng2 = [strng2 ; thescale(1); thescale(2)];
    else
        strng2 = [strng];%; -max(abs(strng)); max(abs(strng))];
        data.network.scale = max(abs(strng2));
    end
    
    % also scale the opacity to the color
    opacity = obj.rescale(abs(strng2),[.2 1]);
    
    % (June2020:) catch when var(net)==0 & rescaling produces nans
    if length(unique(strng)) == 1 && any(isnan(opacity))
        opacity = ones(size(opacity));
    end
    
    
    %strng2 = [strng; thescale'];
    
    if any(any(netcmap ~= 0))
        Colors = colormap(netcmap);
    else
        Colors   = jet;
    end
    
    Ct = (strng2 + data.network.scale) ./ (2*data.network.scale);
    Ci = 1+(Ct*(size(Colors,1)-1));
    
    % get the actual colours from the color palette (nx3 rgb matrix)
    RGB = Colors(round(Ci),:);
    
    %RGB = makecolbar((strng2 + data.network.scale) ./ (2*data.network.scale),netcmap);
    %RGB    = makecolbar(strng2,netcmap);
    
    R = thescale;
    
    % LineWidth (scaled) for strength
    if any(strng)
        R1 = [-max(abs(strng)),max(abs(strng))];
        S = ( abs(strng) - R1(1) ) + 1e-3;
        
        % If all edges same value, make thicker
        if  max(S(:)) == 1e-3;
            S = 3*ones(size(S));
        end
        
    else
        S = [0 0];
    end
    
    % If too few strengths, just use red edges
    %--------------------------------------------------------------------------
    LimC = 1;
    if all(all(isnan(RGB)))
        RGB  = repmat([1 0 0],[size(RGB,1) 1]);
        LimC = 0;
    end
    
    data.network.edge = A;
    data.network.node = pos;
    data.network.RGB  = RGB;
    data.network.tofrom.node1 = node1;
    data.network.tofrom.node2 = node2;
    
    %force width boundaries if stable
    if ~any(isnan( (S - min(S)) ./ (max(S) - min(S)) ))
        S = 1 + (1.5 - 1) .* (S - min(S)) ./ (max(S) - min(S));
    else
        S = (S*0) + 1;
    end
    
    
    % see if user specified width scale, else 1
    %S = [];
    
    %A = spm_mesh_adjacency(data.mesh.faces);
    %[N, D] = spm_mesh_utils('neighbours',A);
    
    if isnan(opacity)
        opacity = ones(size(opacity));
    end
    
    %curve = 1;
    % Paint edges
    %--------------------------------------------------------------------------
    start = [];
    ends  = [];
    for i = 1:size(node1,1)
        
        if ~curved
            l0(i)=line( [node1(i,1),node2(i,1)],...
                        [node1(i,2),node2(i,2)],...
                        [node1(i,3),node2(i,3)],...
                        'LineWidth',S(i),'Color',[RGB(i,:) opacity(i)*.9]);
    
        else
            % to-from in xyz:
            tf = [ [node1(i,1),node2(i,1)];...
                   [node1(i,2),node2(i,2)];...
                   [node1(i,3),node2(i,3)] ];
    
            v = data.mesh.vertices;
    
            % closest mesh start and end points
            [~,Is]=min(cdist(tf(:,1)',v));
            [~,Ie]=min(cdist(tf(:,2)',v));
    
            % generate straight lines
            n  = 50;
            xp = linspace( v(Is,1), v(Ie,1), n )';
            yp = linspace( v(Is,2), v(Ie,2), n )';
            zp = linspace( v(Is,3), v(Ie,3), n )';
    
            % use hanning for some curves -
            c = data.mesh.centre;
            r = max(abs(v - c));         
            s = 1 - ( abs(v(Is,:) - c)./(r) ); % curviness f(relative radius)
            s = s/2;           % change this number to control the bendiness
            h = hanning(n);
    
            hx = h*s(1);
            hy = h*s(2);
            hz = h*s(3);
            
            % normalise edges to 1
            hx = (hx - hx(1)) + 1;
            hy = (hy - hy(1)) + 1;
            hz = (hz - hz(1)) + 1;
    
            xp = xp.*hx;
            yp = yp.*hy;%(h*s(2));
            zp = zp.*hz;%h*s(3));
            
            start = [start; [xp(1) yp(1) zp(1)] ];
            ends  = [ends ; [xp(end) yp(end) zp(end)] ];
    
            l0(i) = line(xp,yp,zp,'LineWidth',S(i),'Color',[RGB(i,:)]);
        end
    end
        
    if curved
        % save these (slightly different ends to straight lines)
        data.network.tofrom.node1 = start;
        data.network.tofrom.node2 = ends;
    end
       
    % Set colorbar only if there are valid edges
    %--------------------------------------------------------------------------
    if any(i) && colbar
        set(gcf,'DefaultAxesColorOrder',RGB)
        set(gcf,'Colormap',RGB)
        if colbar
            %colormap(jet)
            %colorbar
            drawnow; pause(.5);
            a1  = gca;
            axb = axes('position', get(a1, 'position'));
            set(axb,'visible','off')
            axes(axb);
            %set(a1,'DefaultAxesColorOrder',RGB)
            set(gca,'Colormap',RGB) % gcf
            
            if any(any(netcmap ~= 0)); 
                        colormap(netcmap);
            else;       colormap(jet);
            end
            
            colorbar('peer',a1,'South');
        end
    end
    if LimC && colbar
        axes(a1);
        caxis(R);
    end
    
    drawnow;
    
    
    % Nodes (of edges only)
    %--------------------------------------------------------------------------
    % hold on;
    % for i = 1:size(node1,1)
    %     scatter3(node1(i,1),node1(i,2),node1(i,3),'filled','k');
    %     scatter3(node2(i,1),node2(i,2),node2(i,3),'filled','k');
    % end
    
    drawnow;
    
    if write;
       fprintf('Writing network: .edge & .node files\n');
       conmat2nodes(A,fname,'sourcemodel',pos);
    end
    
    
    end
    
    function tap = hanning(obj,n)
    
    % compute taper
    N   = n+1;
    tap = 0.5*(1-cos((2*pi*(1:n))./N))';
    
    % make symmetric
    halfn = floor(n/2);
    tap( (n+1-halfn):n ) = flipud(tap(1:halfn));
    
    end
    
    function [node1,node2,strng] = matrix2nodes(obj,A,pos)
    % Write node & edge files for the AAL90 atlas
    % Also returns node-to-node coordinates for the matrix specified.
    %
    % Input is the n-by-n connectivity matrix
    % Input 2 is the sourcemodel vertices, n-by-3
    %
    % AS2017
    
    
    
    node1 = []; node2 = []; strng = [];
    for i = 1:length(A)
        [ix,iy,iv] = find(A(i,:));
        
        if ~isempty(ix)
            conns = max(length(ix),length(iy));
            for nc = 1:conns
                node1 = [node1; pos(i(1),:)];
                node2 = [node2; pos(iy(nc),:)];
                strng = [strng; iv(nc)];
            end
        end
    end
    
    end
    
    function data = drawnodes(obj,data, N)
    % Node plotter. 
    %
    %
    
    hold on;
    if isfield(data.sourcemodel,'net_pos')
        pos = data.sourcemodel.net_pos;
    elseif isfield(data,'network') && isfield(data.network,'node')
        pos = data.network.node;
    else
        pos = data.sourcemodel.pos;
    end
    
    %--------------------------
    
    % rescale network positions inside box boundaries of mesh
    % (i thought meshmesh had already done this?)
    if ~isempty(data.mesh.h)
        bounds = [min(data.mesh.vertices); max(data.mesh.vertices)];
        offset = .99;
        for ip = 1:3
            pos(:,ip) = bounds(1,ip) + ((bounds(2,ip)-bounds(1,ip))) .* ...
                        (pos(:,ip) - min(pos(:,ip)))./(max(pos(:,ip)) - min(pos(:,ip)));
            pos(:,ip) = pos(:,ip)*offset;
        end
    
        % redirect to closest mesh point (vertex)
        for ip = 1:length(pos)
            [~,this]  = min(cdist(pos(ip,:),data.mesh.vertices));
            pos(ip,:) = data.mesh.vertices(this,:);
        end
    end
    v=pos;
    %--------------------------
    
    if isfield(data,'network') && isfield(data.network,'tofrom')
        % if N is empty, automatically select networked (edge connected) nodes
        pos = [ data.network.tofrom.node1 ; data.network.tofrom.node2 ];
        pos = unique(pos,'rows');
        N   = diag(ones(length(pos),1));
        v   = pos;
    end
    % else
    % 
    % 
    %     if isfield(data.sourcemodel,'vi')
    %         % if pos is cell, it's because we've passed both a vertex set and a
    %         % vector that describes which vertex belongs to which roi
    %         v  = pos;
    %         vi = data.sourcemodel.vi;
    %         n  = unique(vi);
    %         for i = 1:length(n)
    %             these = find(vi==n(i));
    %             roi(i,:) = spherefit(v(these,:));
    %         end
    %         pos = roi;
    %         for ip = 1:length(pos)
    %             [~,this]  = min(cdist(pos(ip,:),data.mesh.vertices));
    %             pos(ip,:) = data.mesh.vertices(this,:);
    %         end
    %     end
    % 
    % 
    %     bounds = [min(data.mesh.vertices); max(data.mesh.vertices)];
    %     offset = 0.99;
    %     for ip = 1:3
    %         pos(:,ip) = bounds(1,ip) + ((bounds(2,ip)-bounds(1,ip))) .* ...
    %                     (pos(:,ip) - min(pos(:,ip)))./(max(pos(:,ip)) - min(pos(:,ip)));
    %         pos(:,ip) = pos(:,ip)*offset;
    %     end
    % 
    %     % redirect to clseast mesh point (vertex?)
    %     for ip = 1:length(pos)
    %         [~,this]  = min(cdist(pos(ip,:),data.mesh.vertices));
    %         pos(ip,:) = data.mesh.vertices(this,:);
    %     end
    % 
    %     v = pos;
    % end
    
    if size(N,1) > 1 && size(N,2) > 1
        %cols = {'r' 'm','y','g','c','b'};
        %if size(size(N,2)) == 90
        %    N = N';
        %end
        
        N = ~~sum(N)';
        
        %for j = 1:size(N,2)
            %ForPlot = v(find(N(:,j)),:) ; %+ (1e-2 * (2*j) ) ;
            %s       = find(N);
            %col     = cols{j};
            
            for i   = 1:length(N)
               % scatter3(ForPlot(i,1),ForPlot(i,2),ForPlot(i,3),70,col,'filled',...
                %    'MarkerFaceAlpha',.6,'MarkerEdgeAlpha',.6);        hold on;
                
                if N(i)
                    vx = v(i,:); 
                    scatter3(v(i,1),v(i,2),v(i,3),70,'k','filled',...
                        'MarkerFaceAlpha',.6,'MarkerEdgeAlpha',.6);  hold on;
                end
                ForPlot = v(find(N),:) ;
            end
        
    elseif iscell(N)
        % pass a cell of length sm with color strings
        % e.g. N=cell(90,1);
        %      N{1} = 'r';
        ForPlot = [];
        for j = 1:length(N)
            if any(N{j})
                v0 = v(j,:);
                ForPlot = [ForPlot v0];
                scatter3(v0(1),v0(2),v0(3),150,N{j},'filled');
            end
        end
        
    else
        ForPlot = v(find(N),:);
        %s       = find(N);
        s = ones(length(find(N)),1)*200;%40;%150;
        for i   = 1:size(ForPlot,1)
            col = 'r';
            scatter3(ForPlot(i,1),ForPlot(i,2),ForPlot(i,3),s(i),'r','filled');
        end
    end
    %RGB = makecolbar(ForPlot);
    %set(gcf,'DefaultAxesColorOrder',RGB); jet;
    %colorbar
    
    data.drawnodes.data = ForPlot;
    
    end
    
    function RGB = makecolbar(obj,I,netcmap)
    % Register colorbar values to an overlay /  T-vector
    %
    
    if any(any(netcmap ~= 0))
        Colors = colormap(netcmap);
    else
        Colors   = jet;
    end
    
    NoColors = length(Colors);
    
    Ireduced = (I-min(I))/(max(I)-min(I))*(NoColors-1)+1;
    RGB      = interp1(1:NoColors,Colors,Ireduced);
    
    end
    
    
    function [y,data] = parse_overlay(obj,x,data)
    % Functinal overlay data parser: volumes, filenames, statements
    %
    %
    %
    
    if iscell(x)
        % multiple overlays (e.g. {'curvature','nif.nii'} )
       for i = 1:length(x)
           [y{i},data] = obj.parse_overlay(x{i},data);
       end
       return;
    end
    
    if ischar(x)
        [fp,fn,fe] = fileparts(x);
        
        
        switch fn
            case 'curvature'
                % since we've precomputed curvature anyway, allow calling 
                % ['overlay', 'curvature'] & return it as y
                y = data.mesh.curvature;
                return;
        end
           
        switch fe
            
            case{'.gz'}
                if data.verbose
                    fprintf('+Unpacking functional .gz\n');
                end
                gunzip(x);
                x = strrep(x,'.gz','');
                
                [y,data] = parse_overlay(x,data);
                return;
                
            case{'.nii'}
                
                % add waitbar
               %wb = waitbar(0,'Reading volume: Please wait...');
                
                % load nifti volume file
                if data.verbose
                    fprintf('+Reading Nifti volume\n');
                end
    %             ni    = load_nii(x);
    %             vol   = ni.img;
    
                ni  = ft_read_mri(x);
                vol = ni.anatomy; 
    
                R = ni.transform(1:3,1:3);
                t = ni.transform(1:3,end);
    
                % real-world cooredinates = 
                %[x; y; z] = R * [i; j; k] + t
    
                [nx,ny,nz] = size(vol);
    
                % compute edges
                E1 = R*[1 ;1 ;1 ]+t;
                E2 = R*[nx;ny;nz]+t;
    
                % real-world cartesian coordinates
                xarr = linspace(E1(1),E2(1),nx);
                yarr = linspace(E1(2),E2(2),ny);
                zarr = linspace(E1(3),E2(3),nz);
                
                % retain header info?
                data.volume.fname     = x;
                data.volume.hdr       = ni.hdr;
                data.volume.vol       = vol;
                
                % NEW: subsample volume by 2. This speeds up subsequent patch
                % reduction enormously without at relatively little cost to
                % resolution
                if data.verbose
                    fprintf('+Subsampling volume\n');
                end
                [xg,yg,zg] = meshgrid(yarr,xarr,zarr);
                [NX, NY, NZ, vol] = reducevolume(xg,yg,zg,vol,4);
                xarr = linspace(xarr(1),xarr(end),size(vol,1));
                yarr = linspace(yarr(1),yarr(end),size(vol,2));
                zarr = linspace(zarr(1),zarr(end),size(vol,3));
    
                % retain coordinate system to pass to vol2surf
                data.volume.grid.x = xarr;
                data.volume.grid.y = yarr;
                data.volume.grid.z = zarr;
                
                wb=0;
                [y,data] = vol2surf(vol,data,wb);
                
                data.sourcemodel.pos = fit_check_source2mesh(data.sourcemodel.pos,data.mesh);
                % ensure sourcemodel (pos) is around same scale as mesh boundaries
                %m = min(data.mesh.vertices);% *1.1;
                %M = max(data.mesh.vertices);% *1.1;
    
                %pos      = data.sourcemodel.pos;
                %V        = pos - repmat(spherefit(pos),[size(pos,1),1]);
                %V(:,1)   = m(1) + ((M(1)-m(1))).*(V(:,1) - min(V(:,1)))./(max(V(:,1)) - min(V(:,1)));
                %V(:,2)   = m(2) + ((M(2)-m(2))).*(V(:,2) - min(V(:,2)))./(max(V(:,2)) - min(V(:,2)));
                %V(:,3)   = m(3) + ((M(3)-m(3))).*(V(:,3) - min(V(:,3)))./(max(V(:,3)) - min(V(:,3)));
                %data.sourcemodel.pos = V;
                
            case{'.gii'}
                % load gifti functional
                gi = gifti(x);
                y  = double(gi.cdata);
                if length(y) ~= length(data.sourcemodel.pos)
                    fprintf('Gifti overlay does not match sourcemodel!\n');
                    if length(y) == length(data.mesh.vertices)
                        fprintf(['...but it does match the mesh size.\nUsing '...
                        'mesh vertices as sourcemodel\n']);
                        data.sourcemodel.pos = data.mesh.vertices;
                    end     
                end
        end
    end
    
    if isnumeric(x) && ndims(x)==3
        % this is a pre-loaded nifti volume
        if data.verbose
            fprintf('+This is a pre-loaded 3D nifti volume: extracting...\n');
        end
        
        % add waitbar
        %wb = waitbar(0,'Preloaded volume: Please wait...');
        
        % NEW: subsample volume by 2 to speed up patch reduction
        if data.verbose
            fprintf('+Subsampling structural volume\n');
        end
        [NX, NY, NZ, x] = reducevolume(x,4);
    
        wb=0;
        [y,data] = vol2surf(x,data,wb);
        
    end
    
    if isnumeric(x) && any(ismember(size(x),1))
        % it's atlas data, e.g. aal90
        y = x;
    end
    
    if isnumeric(x) && length(x)==length(data.mesh.vertices)
        y = x;
    end
    
    end
    
    function y = sym_pad_vector(obj,x,n)
    % Symmetrically pad a vector with zeros
    
    if length(x) ~= n
        k = n - length(x);
        k = floor(k/2);
        y = [zeros(1,k) x zeros(1,k)];
        
    else y = x;
    end
    
    end
    
    function [y,data] = vol2surf(obj,vol,data,wb)
    % Convert a FUNCTIONAL volume to surface. Delauay triangulate, compute a
    % set of 'source' vertices. Take liberties with downsampling and smoothing
    
    
    % bounds:
    S = size(vol);
    
    % check if it's a 'full' volume!
    if length(find(vol)) == prod(S)
        vol = vol - mode(vol(:));
    end
    
    % waitbar
    %waitbar(.15,wb,'Reading volume: Smoothing volume');
    
    % a little smoothing
    vol = smooth3(vol,'gaussian');
    
    % New --- only exists is vol was loaded by atemplate
    try
        pixdim = data.volume.hdr.dime.pixdim(2:4);
    end
    
    if ~isfield(data,'volume') || ~isfield(data.volume,'grid')
        if data.verbose
            fprintf('+Using computed voxel coordinates\n');
        end
        x = 1:size(vol,1);
        y = 1:size(vol,2);
        z = 1:size(vol,3);
    elseif isfield(data.volume,'grid')
        if data.verbose
            fprintf('+Using real-world voxel coordintes from nifti\n');
        end
        x = data.volume.grid.x;
        y = data.volume.grid.y;
        z = data.volume.grid.z;
    end
    
    % waitbar
    %waitbar(.30,wb,'Reading volume: Indexing volume');
    
    % find indices of tissue in old grid
    [nix,niy,niz] = ind2sub(size(vol),find(vol));
    [~,~,C]       = find(vol);
    
    % waitbar
    %waitbar(.45,wb,'Reading volume: Compiling new vertex list');
    
    % compile a new vertex list
    if data.verbose
        fprintf('+Compiling new vertex list (%d verts)\n',length(nix));
    end
    v = [x(nix); y(niy); z(niz)]';
    v = double(v);
    try
        v = v*diag(pixdim);
    end
    
    % apply affine if req.
    if isfield(data.overlay,'affine')
        affine = data.overlay.affine;
        if length(affine) == 4
            if data.verbose
                fprintf('+Applying affine transform\n');
            end
            va = [v ones(length(v),1)]*affine;
            v  = va(:,1:3);
        end
    end
    
    % Fit this gridded-volume inside the box extremes of the mesh
    v = fit_check_source2mesh(v,data.mesh);
    
    %B        = [min(data.mesh.vertices); max(data.mesh.vertices)];
    %V        = v - repmat(spherefit(v),[size(v,1),1]);
    %V(:,1)   = B(1,1) + ((B(2,1)-B(1,1))).*(V(:,1) - min(V(:,1)))./(max(V(:,1)) - min(V(:,1)));
    %V(:,2)   = B(1,2) + ((B(2,2)-B(1,2))).*(V(:,2) - min(V(:,2)))./(max(V(:,2)) - min(V(:,2)));
    %V(:,3)   = B(1,3) + ((B(2,3)-B(1,3))).*(V(:,3) - min(V(:,3)))./(max(V(:,3)) - min(V(:,3)));
    %v        = V;
    
    
    % % new grid
    % fprintf('Generating grid for volume data\n');
    % x = linspace(B(1,1),B(2,1),S(1));
    % y = linspace(B(1,2),B(2,2),S(2));
    % z = linspace(B(1,3),B(2,3),S(3));
    % 
    % % find indiced of tissue in old grid
    % [nix,niy,niz] = ind2sub(size(vol),find(vol));
    % [~,~,C]       = find(vol);
    % 
    % % compile a new vertex list
    % fprintf('Compiling new vertex list (%d verts)\n',length(nix));
    % v = [x(nix); y(niy); z(niz)]';
    % v = double(v);
    
    
    % reduce patch
    if data.verbose
        fprintf('+Reducing patch density\n');
    end
    
    % waitbar
    %waitbar(.50,wb,'Reading volume: Triangulating');
    
    nv  = length(v);
    tri = delaunay(v(:,1),v(:,2),v(:,3));
    fv  = struct('faces',tri,'vertices',v);
    count  = 0;
    
    % waitbar
    %waitbar(.60,wb,'Reading volume: Smoothing');
    
    % smooth overlay at triangulated points first
    Cbound = [min(C) max(C)];
    C      = spm_mesh_smooth(fv,double(C),4);
    C      = Cbound(1) + (Cbound(2)-Cbound(1)).*(C - min(C))./(max(C) - min(C));
    
    % waitbar
    %waitbar(.70,wb,'Reading volume: Reducing patch density');
    
    while nv > 10000
       fv  = reducepatch(fv, 0.5);
       nv  = length(fv.vertices);
       count = count + 1;
    end
    
    % print
    if data.verbose
        fprintf('+Patch reduction finished\n');
        fprintf('+Using nifti volume as sourcemodel and overlay!\n');
        fprintf('+New sourcemodel has %d vertices\n',nv);
    end
    
    % waitbar
    %waitbar(.90,wb,'Reading volume: Computing colours for reduced patch');
    
    % find the indices of the retained vertexes only
    if data.verbose
        fprintf('+Retrieving vertex colours\n');
    end
    Ci = compute_reduced_indices(v, fv.vertices);
    
    % waitbar
    %waitbar(1,wb,'Reading volume: eComplete');
    %close(wb);
    
    
    % Update sourcemodel and ovelray data
    v                    = fv.vertices;
    data.sourcemodel.pos = v;
    y                    = C(Ci);
    
    end
    
    
    function indices = compute_reduced_indices(obj,before, after)
    % Compute the retained functional (colour) values after patch reduction
    %
    
    indices = zeros(length(after), 1);
    for i = 1:length(after)
        dotprods = (before * after(i, :)') ./ sqrt(sum(before.^2, 2));
        [~, indices(i)] = max(dotprods);
    end
    end
    
    function y = rescale(obj,x,S)
    
    y = S(1) + (S(2)-S(1)) .* (x - min(x) ) / ...
        ( max(x) - min(x) );
    
    end
    
    function data = overlay(obj,data,L,write,fname,colbar)
    
    persistent themap
    % Functional overlay plotter
    %
    % mesh is the gifti / patch
    % L is the overlay (90,1)
    % write is boolean flag
    % fname is filename is write = 1;
    %
    
    
    % Add this special case, where using default 81k mesh and 90-node AAL
    % overlay, we'll use pre-computed weights for speed
    %--------------------------------------------------------------------------
    if isnumeric(L) && ndims(L)==2 && length(L)==90 && length(data.mesh.vertices)== 81924 && ...
            ischar(data.overlay.method) && strcmp(data.overlay.method,'euclidean')
        
         if data.verbose
             fprintf('-Using default AAL90 weights for this mesh\n');
         end
         load('AAL90DefaultWeights','M','NumComp','indz','w');
         
         % incorporate overlay into precomputed weights matrix
         for k = 1:length(L)
             M(k,indz(k,:)) = L(k) * M(k,indz(k,:));
         end
         
         % normalise by number of overlapping points at this vertex
         for i = 1:size(M,2)
             y(i) = sum( M(:,i) ) / length(find(M(:,i))) ;
         end   
         
         % rescale y by L limits
         S  = [min(L(:)),max(L(:))];   
         y  = S(1) + ((S(2)-S(1))).*(y - min(y))./(max(y) - min(y));
         y(isnan(y)) = 0;
         L  = y;
         data.method = 'precomputed (AAL)';
    end
    
    
    % deal with the overlay if it's a filename or volume
    %-------------------------------------------------------------
    if ~isnumeric(L) || (isnumeric(L) && ndims(L)==3)
        % is this is filename of a nifti or gifti file
       [L,data] = parse_overlay(L,data);
       
       if isempty(L)
            fprintf('Overlay does not match sourcemodel!\n');
            return;
       end
       if isfield(data,'template')
           if isfield(data.template,'model')
               fprintf('Doing atlas registration\n');
               i.template = 1;
               i.model    = data.template.model;
               i.labels   = data.template.labels;
               i.L        = L;
               [data,i]   = sort_template(data,i);
               L          = i.L;
           end
       end
    end
    
    % method for searching between the 3D coordinate systems
    %-------------------------------------------------------------
    if ischar(data.overlay.method)
        method = data.overlay.method;
        %if ismember(data.overlay.method,{'euclidean','spheres','precomputed (AAL)','raycast','aal','aal_light'})
        %     method = data.overlay.method;
        %else,method = 'euclidean';  
        %end
    else
        method = data.overlay.method{1};
    end
    
    % If requested multi-overlay, where one is curvature, draw the curvature
    %--------------------------------------------------------------------------
    if iscell(L)
        % curvature is first
        C = L{1};
            
        % spm mesh smoothing
        if data.verbose
            fprintf('-Smoothing overlay...\n');
        end
        C = round(C*10)/10;
        
        if sum(C) == 0
            % revert
            C = L{1};
        end
        
        y = spm_mesh_smooth(data.mesh, double(C(:)), 2);   % smoth it
        percNaN = length(find(isnan(C)))/length(C)*100;
        newpNaN = length(find(isnan(y)))/length(y)*100;
        
        % when using a NaN-masked overlay, smoothing can result in all(nan) or
        % an increase in the number of nans: enforce a 5% tolerance on this, which
        % forces reverting to the uns-smoothed version if reached
        if all(isnan(y)) || newpNaN > (percNaN*1.05)
            fprintf('Reverting to non-smoothed overlay due to too many NaNs\n');
            y = C(:);
        end
        
        set(data.mesh.h,'FaceVertexCData',y(:),'FaceColor','interp');
        
        drawnow;
        shading interp
        % force symmetric caxis bounds
        s = max(abs(y(:))); caxis([-s s]);
        
    %     try
    %         themap = [flipud(othercolor('Greys9',256))];
    %     catch
    %         themap = [flipud(gray(256))];
    %     end
    %     colormap(themap);
        
        if data.verbose
            fprintf('-Generating combined function+curvature colormap\n');
        end
        
        
        try
            % if othercolor installed
            %themap = [flipud(othercolor('Greys9',256)); flipud(jet(256))];
            
            %themap = [flipud(othercolor('Greys9',256)); flipud(cmocean('balance',256))];
            themap = [(gray(256)); flipud(cmocean('balance',256))];
            
    %         [map2,map3,map4]=cubric_meg_palettes;
    %         
    %         kmap(:,1) = spm_vec([map3(:,1) map3(:,1)]');
    %         kmap(:,2) = spm_vec([map3(:,2) map3(:,2)]');
    %         kmap(:,3) = spm_vec([map3(:,3) map3(:,3)]');
    %         
    %         themap = [(gray(256)); flipud(kmap)];
            
            %themap = [flipud(gray(256)); flipud(jet(256))];
        catch
            themap = [flipud(gray(256)); flipud(jet(256))];
        end
        alpha 1;
    
        % replace L and flag requirement for a new axis
        L = L{2};
        NewAx = 1;
    elseif isfield(data.overlay,'NewAx')
        NewAx = data.overlay.NewAx;
    else
        NewAx = 0;
    end
    
    
    data.overlay.NewAx = NewAx; % save this in case of recursive calls
    
    % If atlas data and peaks frequested, label them
    %-------------------------------------------------------------
    data.overlay.orig = L;
    if data.overlay.peaks
        n     = mean(L)+(2*std(L));
        [V,I] = find(abs(L) > n);
    
        if isfield(data,'atlas')
            Lab = data.atlas.AAL_Labels;
            data.overlay.Peaks.Labels = Lab(I);
            data.overlay.Peaks.Values = L(I);
        end
        
    end
    
    % interp shading between nodes or just use mean value?
    %--------------------------------------------------------------------------
    interpl = 1; 
    pos     = data.sourcemodel.pos;
    mesh    = data.mesh;
    
    if NewAx
        % if overlaying functional and curvature
        % *no longer generates new axes!*
        ax1     =  gca;
        ax1_pos = get(ax1,'Position'); 
        %ax2 = axes('Position',ax1_pos,'visible',0);  
        h0  = findobj(ax1,'type','patch');
    %     h1  = copyobj(h0,ax2);             % put colour data on h1!
    %     %h1.Vertices = h1.Vertices*1.02;
    %         
    %     axis equal;
    %     Link = linkprop([ax1, ax2],{'View' 'CameraUpVector', 'CameraPosition', ...
    %         'CameraTarget', 'XLim', 'YLim', 'ZLim',  ...
    %           'CameraViewAngle',...
    %         'XAxisLocation','YAxisLocation', 'ActivePositionProperty',...
    %         'OuterPosition', 'Clipping'}); %'XAxis', 'YAxis', 'ZAxis','Box' 'DataAspectRatio', 'TightInset','DataAspectRatioMode','PlotBoxAspectRatioMode','PlotBoxAspectRatio',
    %     setappdata(gcf, 'StoreTheLink', Link);
    end
        
    % if overlay,L, is same length as mesh verts, just plot!
    %--------------------------------------------------------------------------
    if length(L) == length(mesh.vertices)
        if data.verbose
            fprintf('-Overlay already fits mesh! Plotting...\n');
        end
        
        if ~NewAx
            % spm mesh smoothing
            if data.verbose
                fprintf('-Smoothing overlay...\n');
            end
            y = spm_mesh_smooth(mesh, double(L(:)), 4);
            percNaN = length(find(isnan(L)))/length(L)*100;
            newpNaN = length(find(isnan(y)))/length(y)*100;
    
            % when using a NaN-masked overlay, smoothing can result in all(nan) or
            % an increase in the number of nans: enforce a 5% tolerance on this, which
            % forces reverting to the uns-smoothed version if reached
            if all(isnan(y)) || newpNaN > (percNaN*1.05)
                fprintf('Reverting to non-smoothed overlay due to too many NaNs\n');
                y = L(:);
            end
    
            set(mesh.h,'FaceVertexCData',y(:),'FaceColor','interp');
    
            drawnow;
            shading interp
            % force symmetric caxis bounds
            s = max(abs(y(:))); caxis([-s s]);
            
            [map2,map3,map4]=cubric_meg_palettes;
            
            kmap(:,1) = spm_vec([map3(:,1) map3(:,1)]');
            kmap(:,2) = spm_vec([map3(:,2) map3(:,2)]');
            kmap(:,3) = spm_vec([map3(:,3) map3(:,3)]');
            
            colormap(kmap);
            
            %colormap('jet');
            alpha 1;
            
            data.mesh.h.FaceColor = 'flat';
            
            if colbar
                %colorbar('peer',a1,'South');
                data.overlay.cb = InteractiveColorbar;
            end
            colormap(kmap);
        else % if newax (curvature + function)
            
            if ~isempty(data.overlay.thresh)
                thrsh = data.overlay.thresh;
            else; thrsh = .4;
            end
            fcol  = L;
            S     = [min(L(:)),max(L(:))];
            S0    = max(abs(L(:)));
            fcol  = S(1) + ((S(2)-S(1))).*(fcol - min(fcol))./(max(fcol) - min(fcol));
            
            fcol_orig = fcol;
            thr  = max(abs(fcol))*thrsh;
            inan = find(abs(fcol) < thr);
            falpha = 1*ones(size(fcol));
            falpha(inan)=0;
            %fcol = fcol.*falpha;
            
            if data.verbose
                fprintf('-Rescaling overlay values\n');
            end
            
            % get curvature colours
            y0 = data.mesh.h.FaceVertexCData;
            
            % rescale y0 into colour map part 1:
            % 1:256
            y0 = 255 * (y0-min(y0))./(max(y0)-min(y0));
            %y0(isnan(y0))=1;
            
            % rescale fcol into colour map part 2:
            % 257:512
            m = 258;%257;
            n = 512;
            fcol = [fcol; -S0; S0];
            fcol = n + (m - n) .* (fcol-min(fcol))./(max(fcol)-min(fcol));
            fcol = fcol(1:end-2);
            
            iszero = (fcol==385);
            falpha = falpha .* ~iszero;
            
            % mask new functional colours
            fcol = fcol.*falpha;
            
            new_over = y0;
            these    = find(fcol);
            %iszero = fcol(these) == 385;
            %these(iszero)=0;
            %these = find(these);
            new_over(these) = fcol(these);
            
            %new_over = spm_mesh_smooth(maker(data.mesh.faces,data.mesh.vertices),new_over,2);
            
            set(data.mesh.h,'FaceVertexCData',new_over(:),'FaceColor','interp');
            colormap(themap);
            data.overlay.themap=themap;
            
            caxis([0 512]);
            data.mesh.h.FaceColor = 'flat';
            
        end
        
        if write == 1
            fprintf('Writing overlay gifti file: %s\n',[fname 'Overlay.gii']);
            g       = gifti;
            g.cdata = double(y);
            g.private.metadata(1).name  = 'SurfaceID';
            g.private.metadata(1).value = [fname 'Overlay.gii'];
            save(g, [fname  'Overlay.gii']);
        elseif write == 2
                fprintf('Writing mesh and overlay as STL object\n');
            % write STL
            m.vertices = double(mesh.vertices);
            m.faces    = double(mesh.faces);
            y          = double(y);
            cdata      = mean(y(m.faces),2);
    
            % Write binary STL with coloured faces
            cLims = [min(cdata) max(cdata)];      % Transform height values
            nCols = 255;  cMap = jet(nCols);    % onto an 8-bit colour map
            fColsDbl = interp1(linspace(cLims(1),cLims(2),nCols),cMap,cdata);
    
            fCols8bit = fColsDbl*255; % Pass cols in 8bit (0-255) RGB triplets
            stlwrite([fname '.stl'],m,'FaceColor',fCols8bit)
            
        elseif write == 3 
            % write vrml
            fprintf('Writing vrml (.wrl) 3D object\n');
            vrml(gcf,[fname]);
            
        elseif write == 4
    %         fprintf('Generating nifti volume for writing\n');
    %         V = sm2vol(mesh.vertices,256,y,50);
    %         fprintf('Writing nifti volume\n');
    %         niftiwrite(V, [fname '.nii']);
        end
    
    
    else
    
    % otherwise find closest points (assume both in mm)
    %--------------------------------------------------------------------------
    
    % first-pass attempt at ensuring alignment of sourcemodel and outer mesh
    %pos = fixmesh(mesh,pos);
    
    % Overlay
    v  = pos;                       % sourcemodel vertices
    x  = v(:,1);                    % AAL x verts
    mv = mesh.vertices;             % brain mesh vertices
    nv = length(mv);                % number of brain vertices
    S  = [min(L(:)),max(L(:))];     % min max values
    S0 = max(abs(L(:)));
    MS = mean(L);
    
    switch method
        case{'raycast'}
        otherwise
        if write == 2
            r = (nv/length(pos))*5;
            w  = linspace(.1,1,r);          % 
            w  = fliplr(w);                 % 
        elseif write == 3
            r = (nv/length(pos))*3;
            w  = linspace(.1,1,r);          % 
            w  = fliplr(w);                 % 
        end
    end
    
    % Get centre point of cortical mesh so we know left/right for hemispheric
    % separation
    cnt = spherefit(mv);
    Lft = mv(:,1) < cnt(1);
    Rht = mv(:,1) > cnt(1);
    Lft = find(Lft);
    Rht = find(Rht);
    
    if data.verbose
        fprintf('+Determining closest points between sourcemodel & template vertices\n');
    end
    mr = mean(mean(abs(mv)-repmat(spherefit(mv),[size(mv,1),1])));
    
    
    % Switch which projection method to use:
    %--------------------------------------------------------------------------
    switch lower(method)
        
        case 'raycast'
            % This is an attempt at employing the ray casting method
            % implemented in mri3dX. It grids the functional data and searches
            % along each face's normal from -1.5 to 1.5 in 0.05 mm steps.
            %
            % The functional overlay vector returned in the overlay substructure 
            % has one value per FACE of the mesh, although this is converted to
            % vertex values by taking the maximum value of each triangle
            
            %wb = waitbar(0,'Ray casting: Please wait...');
            
            % Ray cast from FACES or from VERTICES: SET 'face' / 'vertex'
            UseFaceVertex = 'vertex'; 
            RND = 1;
            
            % Grid resolution
            nmesh.vertices = data.mesh.vertices * .5;
            dv             = v * .5;
                    
            % make new mesh and overlay points, decimated / rounded to integers (mm)
            nmesh.vertices = double(round(nmesh.vertices*RND)/RND);
            nmesh.faces    = double(data.mesh.faces);
            dv             = round(dv*RND)/RND;
               
            %waitbar(.2,wb,'Ray casting: Gridding data');
            
            % volume the data so vertices are (offset) indices
            if data.verbose
                fprintf(' +Gridding data for ray cast\n');
            end
            vol = zeros( (max(dv) - min(dv))+1 );
            ndv = min(dv)-1;
            
            for i = 1:length(dv)
                if L(i) ~= 0
                    a(1)  = L(i);
                    a(2)  = vol(dv(i,1)-ndv(1),dv(i,2)-ndv(2),dv(i,3)-ndv(3));
                    [~,I] = max(abs(a));
                    vol(dv(i,1)-ndv(1),dv(i,2)-ndv(2),dv(i,3)-ndv(3)) = ...
                    + a(I);
                    %vol(dv(i,1)-ndv(1),dv(i,2)-ndv(2),dv(i,3)-ndv(3)) + a(I);
                
                end
            end
            
            % now manually smooth without changing distirbution: ie. just rep
            % the same number over neighbouring voxels
            vsize = (max(dv) - min(dv))+1;
            ovol  = vol;
            
            for i = 1:vsize(1)
                for j = 1:vsize(2)
                    for k  = 1:vsize(3)
                        
                        if any(ovol(i,j,k))
                            val = ovol(i,j,k);
                            
                            % immediately besdies
                            try; vol(i-1,j+0,k+0) = val; end
                            try; vol(i+1,j+0,k+0) = val; end
                            try; vol(i+0,j-1,k+0) = val; end
                            try; vol(i+0,j+1,k+0) = val; end
                            try; vol(i+0,j+0,k-1) = val; end
                            try; vol(i+0,j+0,k+1) = val; end
                            
                            % off the corners
                            try; vol(i-1,j-1,k+0) = val; end
                            try; vol(i+1,j+1,k+0) = val; end
                            
                            try; vol(i-1,j+0,k-1) = val; end
                            try; vol(i+1,j+0,k+1) = val; end
                            
                            try; vol(i+0,j-1,k-1) = val; end
                            try; vol(i+0,j+1,k+1) = val; end
                        end
                    end
                end
            end
            
            
                    
            %waitbar(.4,wb,'Ray casting: Smoothing');
            
            % Smooth volume
            if data.verbose
                fprintf(' +Volume Smoothing & Rescaling  ');tic;
            end
            %tic      
            V    = spm_vec(vol);
            fun  = @(V) abs(min(V)-S(1)) + abs(max(V)-S(2)) + abs(mean(V)-MS);
            nfun = 0;
            while fun(V) >= 1e-2 && nfun < 100
                nfun = nfun + 1;
                V    = S(1) + (S(2)-S(1)).*(V(:,1) - min(V(:,1)))./(max(V(:,1)) - min(V(:,1)));
                V    = V - mean(V);
                V    = V + MS;
                V    = S(1) + (S(2)-S(1)).*(V(:,1) - min(V(:,1)))./(max(V(:,1)) - min(V(:,1)));
                V    = V - median(V);
            end
    
            %V    = S(1) + (S(2)-S(1)).*(V(:,1) - min(V(:,1)))./(max(V(:,1)) - min(V(:,1)));
    
            vol  = spm_unvec(V, vol); 
            if data.verbose
                fprintf('-- done (%d seconds)\n',round(toc)); 
            end
            
            data.overlay.lr_volume = vol;
            
            switch UseFaceVertex
                
                case 'face'
                    
                    % Load or compute FACE normals and centroids
                    %----------------------------------------------------------
                    if length(mv) == 81924
                        % use precomputed for deault mesh
                        load('DefaultMeshCentroidsNormals','FaceCent','FaceNorm')
                        if data.verbose
                            fprintf(' +Using precomputed centroids & normals for default mesh\n');
                        end
                        f = nmesh.faces;
                    else
                        
                        %waitbar(.6,wb,'Ray casting: Computing face norms and centroids');
                        
                        % Compute face normals
                        %------------------------------------------------------
                        if data.verbose
                            fprintf(' +Computing FACE Normals & Centroids  '); tic;
                        end
                        tr = triangulation(nmesh.faces,nmesh.vertices(:,1),...
                                            nmesh.vertices(:,2),nmesh.vertices(:,3));
                        FaceNorm = tr.faceNormal;
    
                        % Compute triangle centroids
                        %------------------------------------------------------
                        f        = nmesh.faces;
                        for If   = 1:length(f)
                            pnts = [nmesh.vertices(f(If,1),:);... 
                                    nmesh.vertices(f(If,2),:);...
                                    nmesh.vertices(f(If,3),:)];
                                
                            % Triangle centroid
                            FaceCent(If,:) = mean(pnts,1);
                        end
                        
                        if data.verbose
                            fprintf('-- done (%d seconds)\n',round(toc));
                        end
                    end
                    
                    % If a depth vector was specified use that, otherwise
                    % deault
                    if isfield(data.overlay,'depth') && ~isempty(data.overlay.depth)
                          step = data.overlay.depth;
                    else; step   = -1.5:0.05:1.5;
                    end
                    if data.verbose
                        fprintf(' +Using depths: %d to %d mm in increments %d\n',...
                        step(1), step(end), round((step(2)-step(1))*1000)/1000 );
                    end
                    fcol   = zeros(length(step),length(f));
                    
                    
                case 'vertex'
                    
                    % Compute VERTEX normals
                    if data.verbose
                        fprintf(' +Computing VERTEX normals\n');
                    end
                    FaceNorm = spm_mesh_normals(nmesh,1);
                    
                    % In this case, centroids are the vertices themselves
                    FaceCent = nmesh.vertices;
                    
                    step    = -1.5:0.05:1.5;
                    fcol    = zeros(length(step),length(mv));
            end
        
            % Now search outwards along normal line
            %-----------------------------------------------------------------
            %waitbar(.8,wb,'Ray casting: casting');
            
            nhits  = 0; tic    ;
            perc   = round(linspace(1,length(step),10));
            for i  = 1:length(step)
                
                % keep count of num hits
                hits{i} = 0;
                
                % print progress
                if ismember(i,perc)
                    if data.verbose
                        fprintf(' +Ray casting: %d%% done\n',(10*find(i==perc)));
                    end
                end
                
                % the new points
                these = FaceCent + (step(i)*FaceNorm);
                
                % convert these points to indices of the volume
                these(:,1) = these(:,1) - ndv(1);
                these(:,2) = these(:,2) - ndv(2);
                these(:,3) = these(:,3) - ndv(3);
                these      = round(these*RND)/RND;
                
                % retain these
                FaceNormLine(i,:,:) = these;
                
                % values at volume indices
                for j = 1:length(these)
                    try
                        fcol(i,j) = vol(these(j,1),these(j,2),these(j,3));
                        hits{i}   = hits{i} + 1;
                    end
                end
            end
    
            if data.verbose
                fprintf(' +Finished in %d sec\n',round(toc));
            end
            
            %[u,s,v]=spm_svd(fcol);
            %nc = min(find( cumsum(diag(s))./sum(diag(s)) >= 0.9 ) );
            %fprintf('Using %d (of %d) spatial components explaining 90% variance\n',nc,length(s));
            %fcol = u(:,1:nc)*s(1:nc,1:nc)*v(:,1:nc)';
            
            % Retain largest absolute value for each face (from each depth)
            [~,I] = max(abs(fcol));
            for i = 1:length(I)
                nfcol(i) = fcol(I(i),i);
            end
            fcol = nfcol;
            
            % add the values - either 1 per face or 1 per vertex - to the mesh
            %------------------------------------------------------------------
            %waitbar(.9,wb,'Ray casting: sorting...');
            switch UseFaceVertex
                case 'face'
                    % Set face colour data on mesh, requires setting FaceColor= 'flat'
                    
                    %set(mesh.h,'FaceVertexCData',fcol(:));
                    %mesh.h.FaceColor = 'flat';
                    
                    % Or calculate vertex maxima from faces and use interp'd
                    % vertex colouring
                    f  = nmesh.faces;
                    ev = mv*0;
                    
                    % these are the vals at the three corners of each triangle
                    ev(f(:,1),1) = fcol;
                    ev(f(:,2),2) = fcol;
                    ev(f(:,3),3) = fcol;
                    y            = max(ev')';
                    
                    % vertex interpolated colour
                    mesh.h.FaceVertexCData = y;
                    mesh.h.FaceColor = 'interp';
                    
                    data.overlay.vertexcdata = y;
                    data.overlay.facecdata   = fcol;
                    
                case 'vertex'
                    % Set vertex color, using interpolated face colours
                    fcol  = spm_mesh_smooth(mesh, fcol(:), 4);
                    fcol(isnan(fcol)) = 0;
                    %fcol = [fcol; S(1); S(2)];
                    %fcol  = S(1) + ((S(2)-S(1))).*(fcol - min(fcol))./(max(fcol) - min(fcol));
                    %fcol = fcol(1:end-2);
                    
                    if ~NewAx
                        set(mesh.h,'FaceVertexCData',fcol(:),'FaceColor','interp');
                    else
                        % if we're overlaying the functional ray-casted colours on top of the curvature
                        computethresh = 1;
                        if ~isempty(data.overlay.thresh) && ischar(data.overlay.thresh)
                              thrsh = str2num(data.overlay.thresh);
                        elseif ~isempty(data.overlay.thresh) && isnumeric(data.overlay.thresh)
                              thr   = data.overlay.thresh;
                              thrsh = thr;
                              computethresh = 0;
                        else; thrsh = .4;
                        end
                                            
                        %fcol  = S(1) + ((S(2)-S(1))).*(fcol - min(fcol))./(max(fcol) - min(fcol));
                        
                        fcol_orig = fcol;
                        
                        if computethresh
                            thr  = max(abs(fcol))*thrsh;
                        end
                        
                        inan = find(abs(fcol) < thr);
                        
    %                     if thrsh == .4 % the default
    %                         % see how much of the overlay is empty:
    %                         % if it's already 80% sparse, just thrshold by
    %                         % non-zero
    %                         if length(find(fcol)) / length(fcol) < .2
    %                             fprintf('Overlay already sparse, not thresholding\n');
    %                             inan = find(~fcol);
    %                         end
    %                         
    %                     end
                        
                        falpha = 1*ones(size(fcol));
                        falpha(inan)=0;
                        
                        %fcol = fcol.*falpha;
                         
                        %null = find(abs(fcol) < thr);
                        %notnull = (abs(fcol) >= thr);
                        
                        % for controlling alpha
                        %falpha = ones(size(fcol));
                        %falpha(null) = 0;
                        
                        % set null space as nan
                        %fcol(null) = NaN;
                        
                        
                        if data.verbose
                            fprintf(' +Rescaling overlay values\n');
                        end
                        
                        % get curvature colours
                        y0 = data.mesh.h.FaceVertexCData;
                        
                        % rescale y0 into colour map part 1:
                        % 1:256
                        y0 = 255 * (y0-min(y0))./(max(y0)-min(y0));
                        
                        % rescale fcol into colour map part 2:
                        % 257:512
                        m = 258;     % more stable than 257
                        n = 512;
                        fcol = [fcol(:); -S0; S0];
                        fcol = n + (m - n) .* (fcol-min(fcol))./(max(fcol)-min(fcol));
                        fcol = fcol(1:end-2);
                        
                        iszero = (fcol==385);
                        falpha = falpha(:) .* ~iszero(:);
    
                        % mask new functional colours
                        fcol = fcol.*falpha(:);
                        
                        new_over = y0;
                        these    = find(fcol);
                        new_over(these) = fcol(these); 
                        
                        set(data.mesh.h,'FaceVertexCData',new_over(:),'FaceColor','interp');
                        colormap(themap);
                        data.overlay.themap=themap;
                        
                        cbarvals = [ zeros(256,1) ; ...
                                     linspace(-S0,S0,256)' ];
                        data.overlay.colbar_values = cbarvals;
                        
                    end
            end
            
            % Use symmetric colourbar and jet as defaults
            if NewAx
                %colormap(ax2,'jet');
                %s = max(abs(fcol(:))); caxis(ax2,[-s s]);
                caxis([0 512]);
            else
                %colormap('jet');
                [map2,map3,map4]=cubric_meg_palettes;
                kmap(:,1) = spm_vec([map3(:,1) map3(:,1)]');
                kmap(:,2) = spm_vec([map3(:,2) map3(:,2)]');
                kmap(:,3) = spm_vec([map3(:,3) map3(:,3)]');
                colormap(kmap);
    
                s = max(abs(fcol(:))); caxis([-s s]);
                alpha 1;
            end
            %alpha 1;
            
            % Return the face colours
            data.overlay.data  = fcol(:);       % the functional vector
            data.overlay.steps = step;          % the depths at which searched
            data.overlay.hits  = hits;          % num hits / intersects at each depth
            data.overlay.cast  = UseFaceVertex; % whether computed for faces or vertices
            
            if NewAx
                data.overlay.data_nonan = fcol_orig;
            end
            
            data.overlay.FaceNormals   = FaceNorm;
            data.overlay.FaceCentroids = FaceCent;
            data.overlay.FaceNormLines = FaceNormLine;
            
            %waitbar(1,wb,'Complete');
            %close(wb);
        
            
        
        case 'spheres' % this would be better called 'box' in its current form
            
            % This method places a box (boundaries) around a sphere inflated around each
            % vertex point (a 'trap window') by a fixed radius. Mesh points
            % within these bounds are assigned to this vertex
            %
            % The functional overlay vector returned in the overlay
            % substructure contains 1 value per VERTEX and faces colours are
            % interpolated
            %
            
            debugplot = 0;
            
            r  = (nv/length(pos))*.5;      % radius - number of closest points on mesh
            r  = max(r,1);                  % catch when the overlay is over specified!
            OL = sparse(length(L),nv);      % this will be overlay matrix we average
            w  = linspace(.1,1,r);          % weights for closest points
            w  = fliplr(w);                 % 
            M  = zeros( length(x), nv);     % weights matrix: size(len(mesh),len(AAL))
            
            if data.verbose
                fprintf(' +Using inside-spheres search algorithm\n');
            end
            tic
            for i = 1:length(x)
                if any(L(i))      
                    newv = [];
    
                    % Determine whether this point if left or right hemisphere
                    LR     = v(i,1);
                    IsLeft = (LR-cnt(1)) < 0;
                    
                    if IsLeft; lri = Lft;
                    else;      lri = Rht;
                    end
                    
                    % the point
                    cx = v(i,1); cy = v(i,2); cz = v(i,3);
                    
                    % find points inside or touching sphere with radius r 
                    theinds = ( mv(lri,1)-cx ).^2 + ( mv(lri,2)-cy ).^2 + ( mv(lri,3)-cz ).^ 2 <= r^2;
                    
                    ind = lri(find( theinds ));
    
                    OL(i,ind) = L(i);
                    M (i,ind) = 1;
                    indz{i}   = ind;
                    w         = 1;
                end
            end
            stime = toc;
            if data.verbose
                fprintf(' +Routine took %d seconds\n',stime);
            end
                    
            
        case 'euclidean'
            
            % Computes (vectorised) euclidean distance from each vertex to
            % every mesh point. Selects closest n to represent vertex values and 
            % weights by distabnce. n is defined by nmeshpoints / nvertex *1.3
            %
            % The functional overlay vector returned in the overlay
            % substructure contains 1 value per VERTEX and face colours are
            % interpolated
            %
            
            debugplot = 0;
            
            OL = sparse(length(L),nv);      % this will be overlay matrix we average
            r  = (nv/length(pos))*1.3;      % radius - number of closest points on mesh
            r  = max(r,1);                  % catch when the overlay is over specified!
            w  = linspace(.1,1,r);          % weights for closest points
            w  = fliplr(w);                 % 
            M  = zeros( length(x), nv);     % weights matrix: size(len(mesh),len(AAL))
    
            % for no interpolation, set w = 1;
            % w = 1;
            
            if data.verbose
                fprintf(' +Using euclidean search algorithm\n');
            end
            tic
            for i = 1:length(x)
                
                % Print progress
                if data.verbose
                    if i > 1; fprintf(repmat('\b',[size(str)])); end
                    str = sprintf('%d/%d',i,(length(x)));
                    fprintf(str);
                end
    
                % Restrict search to this hemisphere
                LR     = v(i,1);
                IsLeft = (LR-cnt(1)) < 0;
                
                if IsLeft; lri = Lft;
                else;      lri = Rht;
                end
    
                % Compute euclidean distances
                dist       = cdist(mv(lri,:),v(i,:));
                [junk,ind] = maxpoints(dist,max(r,1),'min');
                ind        = lri(ind);
                OL(i,ind)  = w*L(i);
                M (i,ind)  = w;
                indz(i,:)  = ind;
    
                if debugplot
                    hold on;
                    s1 = scatter3(v(i,1),v(i,2),v(i,3),200,'r','filled');
                    s2 = scatter3(mv(ind,1),mv(ind,2),mv(ind,3),150,'b','filled');
                    drawnow;
                end
    
            end
            stime = toc;
            if data.verbose
                fprintf(' +Routine took %d seconds\n',stime);
            end
            
        case {'aal','aal90','aal_90'}
            % project into pre-computed AAL parcellation - 1 value per region
            %
            
            % new method for AAL90: wrapper on ray casting routine
            load DenseAAL.mat
    
            v = v - repmat(spherefit(v),[size(v,1),1]);
            v = fit_check_source2mesh(v,data.mesh);
            v = v - repmat(spherefit(v),[size(v,1),1]);
            
            % parcellation hemisphere registration
            [v,vi] = parcellation_hemispheres(v,vi,cnt);
                            
            ol    = zeros(length(v),1);
            for i = 1:length(L)
                these = find(vi==i);
                ol(these) = L(i);
            end
                    
            data.sourcemodel.pos = v;
            data.overlay.orig    = ol;
            data.overlay.method  = data.overlay.method{2};
            
            data = overlay(data,ol,write,fname,colbar);
            return;
            
        case {'aal_light','aal_reduced','aal_red','aal90_light'};
            % project into pre-computed AAL parcellation - 1 value per region
            % - reduce dversion
            
            % new method for AAL90: wrapper on ray casting routine
            load LightAAL.mat
    
            % update sourcemodel
            v = v - repmat(spherefit(v),[size(v,1),1]);
            v = fit_check_source2mesh(v,data.mesh); 
            v = v - repmat(spherefit(v),[size(v,1),1]);
    
            % parcellation hemisphere registration
            [v,vi] = parcellation_hemispheres(v,vi,cnt);
            
            ol    = zeros(length(v),1);
            for i = 1:length(L)
                these = find(vi==i);
                ol(these) = L(i);
            end
            
            data.sourcemodel.pos = v;
            data.overlay.orig    = ol;
            data.overlay.method  = data.overlay.method{2};
            data.overlay.atlasvalues = L;
            data = overlay(data,ol,write,fname,colbar);
            return;
            
        case {'aal_super'};
            % project into pre-computed AAL parcellation - already computed
            % face values for defaut mesh 1
            
            % new method for AAL90: wrapper on ray casting routine
            load('SuperAAL.mat','MeshVertexParcelID');
            
            v  = data.mesh.vertices;
            vi = MeshVertexParcelID;
    
            ol    = zeros(length(v),1);
            for i = 1:length(L)
                these = find(vi==i);
                ol(these) = L(i);
            end
            
            if NewAx
                data.dosmooth = 0;
            end
            
            data.sourcemodel.pos = v;
            data.overlay.orig    = ol;
            data.overlay.method  = ' ';%data.overlay.method{2};
            data.overlay.atlasvalues = L;
            data = overlay(data,ol,write,fname,colbar);
            return;        
            
        case {'harvox','ho','harvardoxford','hoa','harvard_oxford'}
            % project into pre-computed Harvard-Oxford Atlas
            % parcellation - 1 value per region
            % then use interp/project method above to render on user mesh
            
            % new method for AAL90: wrapper on above routine
            load HarvOx.mat
    
            % update sourcemodel
            v = v - repmat(spherefit(v),[size(v,1),1]);
            v = fit_check_source2mesh(v,data.mesh); 
            v = v - repmat(spherefit(v),[size(v,1),1]);
    
            % parcellation hemisphere registration
            [v,vi] = parcellation_hemispheres(v,vi,cnt);
            
            ol    = zeros(length(v),1);
            for i = 1:length(L)
                these = find(vi==i);
                ol(these) = L(i);
            end
            
            data.sourcemodel.pos = v;
            data.overlay.orig    = ol;
            data.overlay.method  = data.overlay.method{2};
            
    %         % compute roi centres for labelling if req
    %         data.overlay.atlas_flag = 1;
    %         %v_roi = get_roi_centres0(v,vi);
    %         data.overlay.atlas.labels = labels(:,2);
    %         %data.overlay.rois = v_roi;
    %         data.overlay.atlas.v  = v;
    %         data.overlay.atlas.vi = vi;
            
            %v_roi(isnan(v_roi)) = 0;
            
            data = overlay(data,ol,write,fname,colbar);
            return;
            
        case {'aal116','aal_116'};
            % project into pre-computed AAL parcellation - 1 value per region
            %
            
            load AAL116.mat
    
            % update sourcemodel
            v = v - repmat(spherefit(v),[size(v,1),1]);
            v = fit_check_source2mesh(v,data.mesh); 
            v = v - repmat(spherefit(v),[size(v,1),1]);
    
            % parcellation hemisphere registration
            [v,vi] = parcellation_hemispheres(v,vi,cnt);
            
            ol    = zeros(length(v),1);
            for i = 1:length(L)
                these = find(vi==i);
                ol(these) = L(i);
            end
            
            data.sourcemodel.pos = v;
            data.overlay.orig    = ol;
            data.overlay.method  = data.overlay.method{2};
            
            data = overlay(data,ol,write,fname,colbar);
            return;
            
        case {'hoa_cerebellum','hoac','hoa_c'};
            % project into pre-computed AAL parcellation - 1 value per region
            %
            
            load HOA_Cerebellum.mat
    
            % update sourcemodel
            v = v - repmat(spherefit(v),[size(v,1),1]);
            v = fit_check_source2mesh(v,data.mesh);
            v = v - repmat(spherefit(v),[size(v,1),1]);
    
            % parcellation hemisphere registration
            [v,vi] = parcellation_hemispheres(v,vi,cnt);
            
            ol    = zeros(length(v),1);
            for i = 1:length(L)
                these = find(vi==i);
                ol(these) = L(i);
            end
            
            data.sourcemodel.pos = v;
            data.overlay.orig    = ol;
            data.overlay.method  = data.overlay.method{2};
            
            data = overlay(data,ol,write,fname,colbar);
            return;
        case {'hoa_cerebellum','hoac','hoa_c'};
            % project into pre-computed AAL parcellation - 1 value per region
            %
            
            load HOA_Cerebellum.mat
    
            % update sourcemodel
            v = v - repmat(spherefit(v),[size(v,1),1]);
            v = fit_check_source2mesh(v,data.mesh);
            v = v - repmat(spherefit(v),[size(v,1),1]);
    
            % parcellation hemisphere registration
            [v,vi] = parcellation_hemispheres(v,vi,cnt);
            
            ol    = zeros(length(v),1);
            for i = 1:length(L)
                these = find(vi==i);
                ol(these) = L(i);
            end
            
            data.sourcemodel.pos = v;
            data.overlay.orig    = ol;
            data.overlay.method  = data.overlay.method{2};
            
            data = overlay(data,ol,write,fname,colbar);
            return;
            
            
        case {'hcp250' 'hcp_250'}
            % project into HCP250 parcellation - 1 value per region
            %
            
            load HCP250.mat
            
            if length(mesh.vertices) == 81924
                % invoke pre-registered brain mesh 
                
                v  = data.mesh.vertices;
                vi = MeshVertexParcelID;
    
                ol    = zeros(length(v),1);
                for i = 1:length(L)
                    these = find(vi==i);
                    ol(these) = L(i);
                end
    
                if NewAx
                    data.dosmooth = 0;
                end
    
                data.sourcemodel.pos = v;
                data.overlay.orig    = ol;
                data.overlay.method  = ' ';%data.overlay.method{2};
                data.overlay.atlasvalues = L;
                data = overlay(data,ol,write,fname,colbar);
                return;        
                
            else
                % if using a different mesh, mov to next step - 
                % i.e. projecting atlas sources onto brain
                
                % update sourcemodel
                v = v - repmat(spherefit(v),[size(v,1),1]);
                v = fit_check_source2mesh(v,data.mesh);
                v = v - repmat(spherefit(v),[size(v,1),1]);
                
                % parcellation hemisphere registration
                [v,vi] = parcellation_hemispheres(v,vi,cnt);
                
                ol    = zeros(length(v),1);
                for i = 1:length(L)
                    these = find(vi==i);
                    ol(these) = L(i);
                end
                
                % update sourcemodel
                %v = fit_check_source2mesh(v,data.mesh);
                data.sourcemodel.pos = v;
                data.overlay.orig    = ol;
                data.overlay.method  = data.overlay.method{2};
                
                data = overlay(data,ol,write,fname,colbar);
                return;
            end
    end
    
    % Switch to do some post hoc stuff before applying the overlay to the
    % mesh....
    %---------------------------------------------------------------------
    switch method
        case {'raycast','aal'}
            % Don't do anything        
        otherwise
            
            % kill interhems!
            VL = find(v(:,1) < 0);
            VR = find(v(:,1) > 0);
            %ML = find(mv(:,1) < 0);
            %MR = find(mv(:,1) > 0);
            
            ML = find(~isnan(data.mesh.vleft(:,1)));
            MR = find(~isnan(data.mesh.vright(:,1)));
                    
            OL(VL,MR) = 0;
            OL(VR,ML) = 0;
            
    %         % eigendecomposition
    %         [u,s,v]=spm_svd(OL);
    %         nc = min(find( cumsum(diag(s))./sum(diag(s)) >= 0.9 ) );
    %         fprintf('Using %d (of %d) spatial components\n',nc,length(s));
    %         OL = u(:,1:nc)*s(1:nc,1:nc)*v(:,1:nc)';
                    
            fprintf('\n'); %clear L;
    %         if ~interpl
    %              % mean value of a given vertex
    %             OL = mean((OL),1);
    %         else
    %             for i = 1:size(OL,2)
    %                 % average overlapping voxels
    %                 L(i) = sum( OL(:,i) ) / length(find(OL(:,i))) ;
    %                 NumComp(i) =  length(find(OL(:,i)));
    %             end
    %             OL = L;
    %         end
    
            %OL = mean(OL,1);
            
            [~,I]=max(abs(OL));
            
            for i = 1:size(OL,2)
                Li(i) = OL(I(i),i);
            end
            OL=full(Li);
            
            
            % THIS WAS MISSING: DE-NaN BEFORE ANYTHING
            % ADDED AUGUST 2019
            OL(isnan(OL))=0;
    
            % normalise and rescale
            OL = double(full(OL));
            
            %y  = S(1) + ((S(2)-S(1))).*(OL - min(OL))./(max(OL) - min(OL));
            
            y = OL;
            y(isnan(y)) = 0;
            y  = full(y);
            y  = double(y);
    
            % spm mesh smoothing
            %------------------------------------------------------------------
            %if data.verbose
            %    fprintf(' +Smoothing overlay...\n');
            %end
            %y  = spm_mesh_smooth(mesh, y(:), 4);
            %y(isnan(y)) = 0;
            %y  = S(1) + ((S(2)-S(1))).*(OL - min(OL))./(max(OL) - min(OL));
            %y(isnan(y)) = 0;
    
            % return these in data structre
            try data.overlay.data           = y; end
            try data.overlay.smooth_weights = M; end
            try data.overlay.NumComp        = NumComp; end
            try data.overlay.indz           = indz;    end
            try data.overlay.w              = w;       end
    
            if ~NewAx
                set(mesh.h,'FaceVertexCData',y(:),'FaceColor','interp');
                
                [map2,map3,map4]=cubric_meg_palettes;
                kmap(:,1) = spm_vec([map3(:,1) map3(:,1)]');
                kmap(:,2) = spm_vec([map3(:,2) map3(:,2)]');
                kmap(:,3) = spm_vec([map3(:,3) map3(:,3)]');
                colormap(kmap);
                
            else
                
    %             if ~isempty(data.overlay.thresh)
    %                 thrsh = data.overlay.thresh;
    %             else; thrsh = .4;
    %             end
                 fcol  = y;
    %             %fcol  = S(1) + ((S(2)-S(1))).*(fcol - min(fcol))./(max(fcol) - min(fcol));
                        
                
                computethresh = 1;
                if ~isempty(data.overlay.thresh) && ischar(data.overlay.thresh)
                    thrsh = str2num(data.overlay.thresh);
                elseif ~isempty(data.overlay.thresh) && isnumeric(data.overlay.thresh)
                    thr   = data.overlay.thresh;
                    thrsh = thr;
                    computethresh = 0;
                else; thrsh = .4;
                end
                
                %fcol  = S(1) + ((S(2)-S(1))).*(fcol - min(fcol))./(max(fcol) - min(fcol));
                
                fcol_orig = fcol;
                
                if computethresh
                    thr  = max(abs(fcol))*thrsh;
                end
                
                inan = find(abs(fcol) < thr);
                
                
                falpha = 1*ones(size(fcol));
                falpha(inan)=0;
                
                            
                if data.verbose
                    fprintf(' +Rescaling overlay values\n');
                end
                
                % get curvature colours
                y0 = data.mesh.h.FaceVertexCData;
                
                % rescale y0 into colour map part 1:
                % 1:256
                y0 = 255 * (y0-min(y0))./(max(y0)-min(y0));
                
                % rescale fcol into colour map part 2:
                % 257:512
                m = 258;
                n = 512;
                fcol = [fcol(:); -S0; S0];
                fcol = n + (m - n) .* (fcol-min(fcol))./(max(fcol)-min(fcol));
                fcol = fcol(1:end-2);
                
                iszero = (fcol==385);
                falpha = falpha(:) .* ~iszero(:);
    
                % mask new functional colours
                fcol = fcol.*falpha(:);
                
                new_over = y0;
                these    = find(fcol);
                new_over(these) = fcol(these);
                
                set(data.mesh.h,'FaceVertexCData',new_over(:),'FaceColor','interp');
                colormap(themap);
                data.overlay.themap=themap;
                
                cbarvals = [ zeros(256,1) ; ...
                                     linspace(-S0,S0,256)' ];
                data.overlay.colbar_values = cbarvals;
                
                
                
            end
            drawnow;
            shading interp
            % force symmetric caxis bounds
            s = max(abs(y(:))); caxis([-s s]);
            if ~NewAx
                %colormap('jet');
                
                [map2,map3,map4]=cubric_meg_palettes;
                kmap(:,1) = spm_vec([map3(:,1) map3(:,1)]');
                kmap(:,2) = spm_vec([map3(:,2) map3(:,2)]');
                kmap(:,3) = spm_vec([map3(:,3) map3(:,3)]');
                colormap(kmap);
            else
                %colormap(ax2,'jet');
                caxis([0 512]);
            end
            alpha 1;
            
    end
    
    %S = [-s s];
    
    % post-hoc template reduction here?
    %--------------------------------------------------------------------------
    if isfield(data,'post_parcel')
        if data.verbose
            fprintf('  -Also computing requested (parcellated) atlas transform\n');
        end
            newv = data.post_parcel{1};
        newv = fit_check_source2mesh(newv,struct('vertices',data.sourcemodel.pos));
        D0   = cdist(data.sourcemodel.pos,newv);
        D1   = D0*0;
        % assume the vertex value of the closest mesh point
        for i = 1:size(D0,2)
            [~,ind] = min(D0(:,i));
            newL(i) = data.overlay.orig(ind);
            D1(ind,i) = 1;
        end
        newL = [newL S(1) S(2)];
        newL = S(1) + ((S(2)-S(1))).*(newL - min(newL))./(max(newL) - min(newL));
        newL = newL(1:end-2);
        
        % if the second input was supplied, compute average atlas value as mean
        % of parcel vertices
        try 
            iv = data.post_parcel{2};
            if data.verbose
                fprintf('  -Computing parcel means\n');
            end
            n = unique(iv);
            n(n==0) = [];
            ParVal  = iv*0; 
            for i = 1:length(n)
                these = find(iv==n(i));
                ParcelMean(i) = mean( newL(these) );
                MeanLoc(i,:)  = mean([spherefit( newv(these,:) ) ; mean( newv(these,:) )]);
                ParVal(these) = ParcelMean(i);
            end
            ParcelMean = S(1) + ((S(2)-S(1))).*(ParcelMean - min(ParcelMean))./(max(ParcelMean) - min(ParcelMean));
            ParVal     = S(1) + ((S(2)-S(1))).*(ParVal - min(ParVal))./(max(ParVal) - min(ParVal));
        end
        
        % box bound new set
        %MeanLoc = fit_check_source2mesh(MeanLoc,data.mesh);
        
        % return the new v and data
        data.post_parcel      = [];
        data.post_parcel.pos  = newv;
        data.post_parcel.data = newL;  
        data.post_parcel.M    = D1;
    
        try 
            % return atlas data as means
            data.post_parcel.ParcelMean = ParcelMean;
            data.post_parcel.ParcelCent = MeanLoc;
            data.post_parcel.ParVal     = ParVal;
            data.post_parcel.ParcelID   = iv;
        end 
    end
    
    
    
    if colbar && ~NewAx
        data.overlay.cb = InteractiveColorbar;
                    [map2,map3,map4]=cubric_meg_palettes;
                kmap(:,1) = spm_vec([map3(:,1) map3(:,1)]');
                kmap(:,2) = spm_vec([map3(:,2) map3(:,2)]');
                kmap(:,3) = spm_vec([map3(:,3) map3(:,3)]');
                colormap(kmap);
    
        
        
    end
        
    % switches for writing out other file formats
    %-------------------------------------------------------------------------
    if write == 1;
        fprintf('Writing overlay gifti file: %s\n',[fname 'Overlay.gii']);
        g       = gifti;
        g.cdata = double(y);
        g.private.metadata(1).name  = 'SurfaceID';
        g.private.metadata(1).value = [fname 'Overlay.gii'];
        save(g, [fname  'Overlay.gii']);
    elseif write == 2 
            % write STL
            fprintf('Writing mesh and overlay as STL object\n');
            m.vertices = double(mesh.vertices);
            m.faces    = double(mesh.faces);
            y = spm_mesh_smooth(mesh, y(:), 8); % hard smoothing
            y          = double(y);
            cdata      = mean(y(m.faces),2);
            
            I = cdata;
            Colors   = jet;
            NoColors = length(Colors);
    
            Ireduced = (I-min(I))/(max(I)-min(I))*(NoColors-1)+1;
            RGB      = interp1(1:NoColors,Colors,Ireduced);
            
            fCols8bit= RGB*255;
            stlwrite([fname '.stl'],m,'FaceColor',fCols8bit)
    elseif write == 3 
        % write vrml
        fprintf('Writing vrml (.wrl) 3D object\n');
        vrml(gcf,[fname]);
    elseif write == 4
        fprintf('Generating nifti volume for writing\n');    
        V = genvol(data.mesh.vertices,data.overlay.data,[256 256 256]);
        %new = mesh;
        %dim = ceil(nthroot(length(y),3));
        %V   = sm2vol(new.vertices,dim*3,y,256);
        % just return the volume in the output for now
        data.overlay.volume = V;
    end
    
    end
    drawnow;
    
    
    % if a timefreqanal structure was passed: allow click-for-plot (see Mylcmv)
    %--------------------------------------------------------------------------
    if isfield(data.overlay,'tf_interactive') && isstruct(data.overlay.tf_interactive)
        tf   = data.overlay.tf_interactive;
        f0   = get(gca,'parent');
        f    = figure('position',[1531         560         560         420]);
        %waitfor(f) % while the box is open
        fprintf('Waiting: Click in table to view corresponding time-freq!\n');
    
        %while isvalid(f)
        H    = datacursormode(f0);
        H.DisplayStyle = 'datatip';
    
        ch = get(f0,'children');
        waitfor(f0.WindowButtonMotionFcn)
                H    = datacursormode(f0);
                INFO = getCursorInfo(H);
                
                if isstruct(INFO) && isfield(INFO,'Position')
                    current      = INFO.Position;
                    fprintf('Got point: fetching time-freq plot\n');
                    [this,thisi] = find( cdist(current,INFO.Target.Vertices) == 0);
                    
                    figure(f);
                    tf.index = thisi; % choose vertex (source) index to plot, rerun for plot
                    timefreqanal(tf);
                    drawnow;
                end
        %end
    end
    
    % if a spatial PCA was requested
    %--------------------------------------------------------------------------
    if isfield(data.overlay,'pca')
        if data.overlay.pca
            f  = mesh.faces;
            A  = spm_mesh_adjacency(f);
            sy = double(y(:));
            sy = sy - mean(abs(sy(:))); 
            ya = sy.*A;
            
            % hardwire an assumption that you wouldnt look for more than 4
            pks = findpeaks(y);
            pks = min(length(pks),4); 
            
            %[U,S,V] = svds(ya,pks);
            %for pc = 1:length(S)
            %    comp(pc,:) = sparse(U(:,pc)*S(pc,pc)*mean(V(:,pc))');
            %end
            
            [comp,D] = eigs(ya,pks); % use eigs instead
            pc   = size(comp,2);
            comp = comp';
            comp = D*comp;
            
            ncomp = pc;
            fprintf('Found %d principal components\n',pc);
            data.overlay.pca = comp;
            
            f0 = get(gca,'parent');
            f  = figure('position',[1531         560         560         420]);
            t  = uitable(f);
            for i = 1:ncomp
                d{i,1} = sprintf('Component %d',i);
                d{i,2} = false;
            end
            d = [ {'All' , false }; d];
    
            t.Data = d;
            t.ColumnName = {'PC'};
            t.ColumnEditable = true;
    
            %waitfor(f) % while the peaks box is open
            fprintf('Waiting: Click in table to view components!\n');
            while isvalid(f)
                try
                    waitfor(t,'Data')
                    i = find(cell2mat(t.Data(:,2)));
                    if any(i)
                        if i > 1
                            i  = i - 1;
                            if size(comp,2) == length(mesh.vertices)
                                this = full(comp(i,:));
                            else
                                this = full(comp(i,:)*M');
                            end
                            if all(size(this) > 1)
                                this = sum(this,1);
                            end
    
                            Y = spm_mesh_smooth(mesh, this(:), 8);
    
                            thefig = get(f0,'children');
                            hh = get(thefig(end),'children');
                            set(hh(end),'FaceVertexCData',Y(:),'FaceColor','interp');
                            set(hh(end),'FaceAlpha',1);
                            drawnow;
                            shading interp
                        else
                            %otherwise just plot the whole lot
                            thefig = get(f0,'children');
                            hh = get(thefig(end),'children');
                            set(hh(end),'FaceVertexCData',y(:),'FaceColor','interp');
                            drawnow;
                            shading interp
                        end
                    end
                catch
                    return;
                end
            
            end  
        end
    end
    
    % if search of local maxima was requested
    %--------------------------------------------------------------------------
    if isfield(data.overlay,'components')
        if data.overlay.components
                    
            fprintf('Computing local maxima on surface\n');
            if length(data.overlay.orig) ~= length(mesh.vertices);
                msh.vertices = data.sourcemodel.pos;
                msh.faces    = delaunayTriangulation(msh.vertices);
                msh.faces    = msh.faces(:,1:3);
                useM = 1;
            else
                msh  = mesh;
                useM = 0;
            end
            A   = spm_mesh_adjacency(msh);
            T   = data.overlay.orig;
            out = isnan(T(:)');
            Lm  = [];
            for i=find(~out)
                v = T(logical(A(i,:)));
                if ~any(v>T(i))
                    Lm = [Lm i];
                end
            end
            
            % sort these by size
            fprintf('Sorting...\n');
            maxs   = T(Lm);
            [~,Ii] = sort(abs(maxs),'descend');
            P      = Lm(Ii);
            ncomp  = length(P);
            
            
            f0 = get(gca,'parent');
            f  = figure('position',[1531         560         560         420]);
            t  = uitable(f);
            for i = 1:ncomp
                d{i,1} = sprintf('Comp %d',i);
                d{i,2} = false;
            end
            d = [ {'All' , false }; d];
    
            t.Data = d;
            t.ColumnName = {'Component'};
            t.ColumnEditable = true;
    
            %waitfor(f) % while the peaks box is open
            fprintf('Waiting: Click in peaks table to view peaks!\n');
            while isvalid(f)
    
                waitfor(t,'Data')
                i = find(cell2mat(t.Data(:,2)));
                if any(i)
                    if i > 1
                        i  = i - 1;
                        if useM
                            dM = M*0;
                            dM(P(i),:) = M(P(i),:);
                        else
                            dM = zeros(length(T),1);
                            dM(P(i)) = 1;
                        end
                        try    this = data.overlay.orig*dM;
                        catch; this = dM*T;
                        end
                        Y = spm_mesh_smooth(mesh, this(:), 4);
    
                        thefig = get(f0,'children');
                        hh = get(thefig(end),'children');
                        set(hh(end),'FaceVertexCData',Y(:),'FaceColor','interp');
                        drawnow;
                        shading interp
                    else
                        %otherwise just plot the whole lot
                        thefig = get(f0,'children');
                        hh = get(thefig(end),'children');
                        set(hh(end),'FaceVertexCData',y(:),'FaceColor','interp');
                        drawnow;
                        shading interp
                    end
                end
    
            end  
        end
    end
    
    % If 'Peaks' was requested while using an AAL atlas
    %--------------------------------------------------------------------------
    if isfield(data.overlay,'Peaks')
        if isfield(data.overlay.Peaks,'Labels')
            f0 = get(gca,'parent');
            f = figure('position',[1531         560         560         420]);
            t = uitable(f);
            for i = 1:length(data.overlay.Peaks.Labels)
                d{i,1} = data.overlay.Peaks.Labels{i};
                d{i,2} = data.overlay.Peaks.Values(i);
                d{i,3} = false;
            end
            d{i+1,1} = 'All';
            d{i+1,2} = '--';
            d{i+1,3} = false;
            
            t.Data = d;
            t.ColumnName = {'Position','Val','Spotlight'};
            t.ColumnEditable = true;
            
            %waitfor(f) % while the peaks box is open
            fprintf('Waiting: Click in peaks table to view peaks!\n');
            while isvalid(f)
                
                waitfor(t,'Data')
                i = find(cell2mat(t.Data(:,3)));
                if any(i)
                    if i < length(d)
                        this = t.Data(i,:);
                        % work backwards to project only this component
                        thislab = find(strcmp(this{1},data.atlas.AAL_Labels));
                        dM      = M;
                        n       = 1:size(dM,1);
                        dM(find(~ismember(n,thislab)),:) = 0;
                        dM = dM'*data.overlay.orig(:);
                        dM = full(double(dM));
                        Y = spm_mesh_smooth(mesh, dM(:), 4);
                        
                        thefig = get(f0,'children');
                        hh = get(thefig(end),'children');
                        set(hh(end),'FaceVertexCData',Y(:),'FaceColor','interp');
                        set(hh(end),'FaceAlpha',1);
                        drawnow;
                        shading interp
                    else
                        % otherwise just plot the whole lot
                        thefig = get(f0,'children');
                        hh = get(thefig(end),'children');
                        set(hh(end),'FaceVertexCData',y(:),'FaceColor','interp');
                        drawnow;
                        shading interp
                    end
                end
            
            end
            
        end
    end
    
    end
    
    
    function [v,vi] = parcellation_hemispheres(obj,v,vi,cnt)
    
    % identify parcels which straddle hemispheres
    %------------------------------------------------------------------
    parc_id = unique(vi);
    newv  = []; % new version of v
    newvi = []; % new version of vi
    for i = 1:length(parc_id)
        parc_verts = v( find(vi==parc_id(i)) , :);
        
        % location of point cluster: percentage on the left
        PercOnLeft = sum( parc_verts(:,1) < cnt(1) ) ./ length(parc_verts);
        
        if      PercOnLeft == 1 || PercOnLeft == 0
            newv  = [newv; parc_verts];
            newvi = [newvi; i*ones(size(parc_verts,1),1)];
            
        elseif  PercOnLeft >= 0.65                  % >=65% on left
            these = find(parc_verts(:,1) > cnt(1));
            parc_verts(these,:) = [];
            newv  = [newv; parc_verts];
            newvi = [newvi; i*ones(size(parc_verts,1),1)];
        elseif  PercOnLeft <= 0.35
            these = find(parc_verts(:,1) < cnt(1));
            parc_verts(these,:) = [];
            newv  = [newv; parc_verts];
            newvi = [newvi; i*ones(size(parc_verts,1),1)];
        end
        
    end
    
    % return the new lists
    v  = newv;
    vi = newvi;
    
    end
    
    
    
    
    function pos = fit_check_source2mesh(obj,pos,g)
    % check box bounds of sourcemodel and mesh are matched
    %
    % pos = nx3 source model, g = mesh gifti/struct
    
    % v = g.vertices;
    % 
    % m = min(g.vertices);% *1.1;
    % M = max(g.vertices);% *1.1;
    % 
    % % refit box boundaries
    % V        = pos - repmat(spherefit(pos),[size(pos,1),1]);
    % V(:,1)   = m(1) + ((M(1)-m(1))).*(V(:,1) - min(V(:,1)))./(max(V(:,1)) - min(V(:,1)));
    % V(:,2)   = m(2) + ((M(2)-m(2))).*(V(:,2) - min(V(:,2)))./(max(V(:,2)) - min(V(:,2)));
    % V(:,3)   = m(3) + ((M(3)-m(3))).*(V(:,3) - min(V(:,3)))./(max(V(:,3)) - min(V(:,3)));
    % pos = V;
    % 
    % b0 = boundary(double(full(v)));
    % b1 = boundary(double(full(pos)));
    % 
    % npnt = min([ length(v) length(pos) ]);
    % npnt = round(npnt/2);
    % npnt = min([npnt 5000]);
    % 
    % SamPt0 = randi(length(b0),[npnt 1]);
    % SamPt1 = randi(length(b1),[npnt 1]);
    % 
    % SamPt0 = sort(SamPt0);
    % SamPt1 = sort(SamPt1);
    % 
    % Pnts0 = v(b0(SamPt0),:);
    % Pnts1 = pos(b1(SamPt1),:);
    % 
    % [dcloud1] = align_clouds_3d_xyz(Pnts0, Pnts1);
    
    % ensure correct orientation
    %pos1 = find_rot_svd(pos,g.vertices);
    
    % ensure sourcemodel (pos) is around same scale as mesh boundaries
    m = min(g.vertices);% *1.1;
    M = max(g.vertices);% *1.1;
    
    % refit box boundaries
    V        = pos - repmat(spherefit(pos),[size(pos,1),1]);
    V(:,1)   = m(1) + ((M(1)-m(1))).*(V(:,1) - min(V(:,1)))./(max(V(:,1)) - min(V(:,1)));
    V(:,2)   = m(2) + ((M(2)-m(2))).*(V(:,2) - min(V(:,2)))./(max(V(:,2)) - min(V(:,2)));
    V(:,3)   = m(3) + ((M(3)-m(3))).*(V(:,3) - min(V(:,3)))./(max(V(:,3)) - min(V(:,3)));
    pos      = V;
    
    end
    
    function y = makeodd(obj,x)
    % nearest odd number
    %
    %
    
    y = 2*floor(x/2)+1;
    
    end
    
    
    function x = killinterhems(obj,x);
    % kill interhemispherics, assuming a square adjacency matrix
    %
    %
    
    S  = size(x);
    xb = (S(1)/2)+1:S(1);
    yb = (S(2)/2)+1:S(2);
    xa = 1:S(1)/2;
    ya = 1:S(2)/2;
    
    x(round(xa),round(yb)) = 0;
    x(round(xb),round(ya)) = 0;
    
    end
    
    
    
    
    function newpos = fixmesh(obj,g,pos)
    % redirect sourcemodel points onto closest mesh vertex
    %
    % AS
    
    v = g.vertices;
    v = v - repmat(spherefit(v),[size(v,1),1]); % Centre on ~0
    g.vertices=v;
    
    % Centre on ~0
    pos = pos - repmat(spherefit(pos),[size(pos,1),1]);
    
    newpos = pos;
    for i = 1:length(pos)
        this  = pos(i,:);
        [t,I] = maxpoints(cdist(v,this),1,'max');
        newpos(i,:) = v(I,:);    
    end
    
    end
    
    function [g,pos,h,p] = meshmesh(obj,g,write,fname,fighnd,a,pos,hemisphere,affine,flip,inflate,checkori,dofillholes,optimise,verb)
    % Main brain-mesh plot. 
    %
    % Separates hemispheres, computes curvature, check orientation, inflate, 
    % centre & fill holes. Plots the patch as a semi-transparent glass brain 
    % for other plot functiopns to add to. 
    %
    % Returns everything in data.mesh
    %
    
    if iscell(pos)
       orig_pos = pos;
       pos      = pos{1};
    end
    
    if isempty(a);
        a = .6;
    end
    
    v        = g.vertices;
    dosphere = g.do_ball;
    
    % apply affine if req.
    if length(affine) == 4
        if verb
            fprintf('-Applying affine transform\n');
        end
        va = [v ones(length(v),1)]*affine;
        v  = va(:,1:3);
        g.vertices = v;
    end
    
    % flip x/y if required but POST affine transform
    if flip
        v = g.vertices;
        v = v(:,[2 1 3]);
        g.vertices = v;
    end
    
    
    % check rotation
    yl = max(v(:,2)) - min(v(:,2));
    xl = max(v(:,1)) - min(v(:,1));
    
    if xl > yl
        fprintf('Re-oreintating\n');
        v       = v(:,[2 1 3]);
        g.faces = g.faces(:,[2 1 3]);
    end
    
    % centre and scale mesh
    g.vertices = v - repmat(spherefit(v),[size(v,1),1]);
    
    
    % ensure sourcemodel (pos) is around same scale as mesh boundaries
    pos = fit_check_source2mesh(pos,g);
    
    % explicitly optimise the alignment of the cloud points?
    % (source model vertices and mesh vertices)
    if optimise
        pos = align_clouds_3d(g.vertices,pos);
        clf; drawnow;
    end
    
    
    % m = min(g.vertices);% *1.1;
    % M = max(g.vertices);% *1.1;
    % 
    % V        = pos - repmat(spherefit(pos),[size(pos,1),1]);
    % V(:,1)   = m(1) + ((M(1)-m(1))).*(V(:,1) - min(V(:,1)))./(max(V(:,1)) - min(V(:,1)));
    % V(:,2)   = m(2) + ((M(2)-m(2))).*(V(:,2) - min(V(:,2)))./(max(V(:,2)) - min(V(:,2)));
    % V(:,3)   = m(3) + ((M(3)-m(3))).*(V(:,3) - min(V(:,3)))./(max(V(:,3)) - min(V(:,3)));
    % pos      = V;
    
    % % calculate curvature for shading
    curv  = docurvature(struct('vertices',g.vertices,'faces',g.faces));
    curv  = spm_mesh_smooth( struct('vertices',g.vertices,'faces',g.faces) , curv ,4 );
    %cvar  = var(curv);
    %dcurv = curv;
    
    % Compute graph laplacian for later smoothing
    A  = spm_mesh_distmtx(struct('vertices',g.vertices,'faces',g.faces),0);
    N  = size(A,1);
    GL = speye(N,N) + (A - spdiags(sum(A,2),0,N,N))/16;
    
    % inflate
    if inflate
        if verb
            fprintf('-Inflating mesh\n'); 
        end
        if isfield(g,'inflate')
            inflate_n = g.inflate;
        else
            inflate_n = 200;
        end
        
        nrep = 0;
        %while cvar / var(dcurv) < 50
            %nrep = nrep + 1;
            g = spm_mesh_inflate(struct('vertices',g.vertices,'faces',g.faces),inflate_n);
            %dcurv = docurvature(struct('vertices',g.vertices,'faces',g.faces));
        %end
        %fprintf('Finished inflation after %d reps\n',nrep);
        g.inflation = inflate_n;
    end
    
    % compute and return face vertex normals
    tr = triangulation(double(g.faces),double(g.vertices(:,1)),...
                                       double(g.vertices(:,2)),...
                                       double(g.vertices(:,3)) );
    g.FaceNorm   = tr.faceNormal;
    N            = -double(tr.vertexNormal);           
    
    normN = sqrt(sum(N.^2,2));
    normN(normN < eps) = 1;
    N     = N ./ repmat(normN,1,3);
    g.VertexNorm = N;
    
    if checkori
        b = CheckOrientationMesh(g);
        waitfor(b)
        g = b;
    end
    
    % % allow user to request that the brain is inflated right out to a sphere
    if dosphere
        % if we know radius of each vertex from cent, we know how to make a sphere...
        Bnd = [min(min(g.vertices)); max(max(g.vertices))]*1.1;
        Ed  = cdist(g.vertices,spherefit(g.vertices));
        v   = g.vertices ./ [Ed/3 Ed/3 Ed/3];
        for i = 1:3
            v(:,i) = rescale(v(:,i),[Bnd(1) Bnd(2)]);
        end
        g.vertices = v;
        if verb
            fprintf('-inflating brain to full sphere\n');
        end
    end
    g.dosphere = dosphere;
    
    % only one hemisphere?
    v = double(g.vertices);
    f = g.faces;
    c = spherefit(v);
    
    % save centre point for later - e.g. label setting
    g.centre = c;
    
    [A,D] = spm_mesh_clusters(g,ones(1,length(v)));
    
    if length(unique(A)) == 2
        left  = find(A==1);
        right = find(A==2);
    else
        % The mesh can't be fully separated without holes
        left  = find(v(:,1) < c(1));
        right = find(v(:,1) > c(1));
        dofillholes = 1;
    end
    
    lfaces = find(sum(ismember(f,left),2)==3);
    rfaces = find(sum(ismember(f,right),2)==3);
    
    % return left/right indices
    g.vleft            = v*NaN;
    g.vleft(left,:)    = v(left,:);
    g.vright           = v*NaN;
    g.vright(right,:)  = v(right,:);
    g.fleft            = f*NaN;
    g.fleft(lfaces,:)  = f(lfaces,:);
    g.fright           = f*NaN;
    g.fright(rfaces,:) = f(rfaces,:);
    g.curvature        = curv;
    g.A                = A;
    g.GL               = GL;
    
    % Left and Riht Hemi Centres
    g.left_centre = spherefit( g.vleft(~all(isnan(g.vleft)')',:) );
    g.right_centre = spherefit( g.vright(~all(isnan(g.vright)')',:) );
    
    
    % fill holes stemming from hemisphere separation - if requested
    %---------------------------------------------------------------
    if dofillholes
        if verb
            fprintf('-Filling holes resulting from hemisphere separation..\n');
        end
        
        % left side
        x = [];
        holecellarray = findTriMeshHoles(g.fleft,g.vleft);
        for i = 1:length(holecellarray)
            edges   = holecellarray{i};  % indices of vertices around edge
            %ek      = nchoosek(edges,3); % triangles at all perimiter points
            
            dt = delaunayTriangulation(v(edges,:));
            try
                %ek = dt.ConnectivityList(:,1:3);
                ek = dt.convexHull;
                ek = edges(ek);
                x  = [x; ek];           % new faces
            catch;
                
            end
        end
        
        x0 = x;
        
        % update faces
        g.fleft = [g.fleft; x];
                
        % right side
        x = [];
        holecellarray = findTriMeshHoles(g.fright,g.vright);
        for i = 1:length(holecellarray)
            edges   = holecellarray{i};  % indices of vertices around edge
            dt = delaunayTriangulation(v(edges,:));
            try
                %ek = dt.ConnectivityList(:,1:3);
                ek = dt.convexHull;
                ek = edges(ek);
                x  = [x; ek];           % new faces
            catch;
                
            end
        end
        
        % update faces
        g.fright = [g.fright; x];
        
        % update full-model faces
        g.faces = [g.faces; x0; x];
        
    end
    
    
    switch hemisphere
        case{'left','L','l'}
            pg.vertices = g.vleft;
            pg.faces    = g.fleft;
            
            %pg.vertices         = v*NaN;
            %pg.vertices(left,:) = v(left,:);
            %pg.faces           = f*NaN;
            %pg.faces(lfaces,:) = f(lfaces,:);
      
        case{'right','R','r'}
            pg.vertices = g.vright;
            pg.faces    = g.fright;
            
            %pg.vertices          = v*NaN;
            %pg.vertices(right,:) = v(right,:);
            %pg.faces           = f*NaN;
            %pg.faces(rfaces,:) = f(rfaces,:);        
            
        otherwise
            pg = g;
    end
    
    % sanity check
    if any( min(pg.faces(:)) == 0)
        bad = find(pg.faces == 0);
        pg.faces(bad) = NaN;
    end
    
    pg.faces = double(pg.faces);
    pg.faces(pg.faces==0) = NaN;
    
    % plot
    if ~isempty(fighnd)
        if isnumeric(fighnd)
            % Old-type numeric axes handle
            h = plot(fighnd,gifti(pg));
        elseif ishandle(fighnd)
            % new for matlab2017b etc
            % [note editted gifti plot function]
            h = plot(gty.gifti.gifti(pg),'fighnd',fighnd);
            
    %     h = patch(struct(...
    %         'vertices',  pg.vertices,...
    %         'faces',     pg.faces),...
    %         'FaceColor', [.5 .5 .5],...%'b',...
    %         'EdgeColor', 'none',...
    %         'Parent',fighnd);        
    %         
    %         axis equal;
            
        end
    else
        h  = plot(gifti(pg));
    end
    C = [.5 .5 .5];
    
    set(h,'FaceColor',[C]); box off;
    grid off;  set(h,'EdgeColor','none');
    alpha(a); 
    set(gca,'visible','off');
    
    if ~isempty(fighnd)
        % Addition December 2020: Get and set axis boundaries for full model
        % regardless of whether this is a single hemisphere plot -
        g.AXLIM = [min(g.vertices); max(g.vertices)]*1.2; % 20% space
    
        fighnd.XLim = g.AXLIM(:,1)';
        fighnd.YLim = g.AXLIM(:,2)';
        fighnd.ZLim = g.AXLIM(:,3)';
    end
    
    %h = get(gcf,'Children');
    %set(h(end),'visible','off');
    
    %set(gca,'visible','off')
    
    drawnow; hold on;
    
    p = [];
    
    if write == 1
        fprintf('Writing mesh gifti file: %s\n',[fname '.gii']);
        gout.vertices = g.vertices;
        gout.faces    = g.faces;
        gout = gifti(gout);
        save(gout,fname);
    end
    
    
    
    if exist('orig_pos')
        % is pos was a cell, re-instate 
        orig_pos{1} = pos;
        pos         = orig_pos;
    end
    
    end
    
    function C = docurvature(obj,M)
    % Computes the curvature of a mesh
    %
    %
    
    A = spm_mesh_adjacency(M);
    A = sparse(1:size(M.vertices,1),1:size(M.vertices,1),1./sum(A,2)) * A;
    
    C = (A-speye(size(A))) * double(M.vertices);
    N = spm_mesh_normals(M);
    C = sign(sum(N.*C,2)) .* sqrt(sum(C.*C,2));
    
    end
    
    function data = addlabels(obj,data,V,all_roi_tissueindex,thelabels)
    % Add labels to the plot.
    %
    % If using AAL90 sourcemodle, these are automatic.
    %
    % If using another sourcemodel:
    % - provide the all_roi_tissueindex from fieldtirp. This is a
    % 1xnum_vertices vector containing indices of rois (i,e. which verts belong
    % to which rois).
    % Also provide labels!
    %
    pos = data.sourcemodel.pos;
    
    if ( ~isempty(thelabels) && ~isempty(all_roi_tissueindex) ) &&...
       ( length(pos) == length(all_roi_tissueindex) ) &&...
       ( length(thelabels) == length(unique(all_roi_tissueindex(all_roi_tissueindex~=0))) )
        
        labels = strrep(thelabels,'_',' ');
        v      = get_roi_centres(pos,all_roi_tissueindex);
        roi    = all_roi_tissueindex;
        
    elseif length(V) == 90
        
        load('AAL_labels');
        labels = strrep(labels,'_',' ');
        v      = pos*0.95;
        roi    = 1:90;
    elseif (length(V) == length(thelabels)) &&...
           (length(V) == length(pos))
        
       labels = strrep(thelabels,'_',' ');
        v = pos*0.95;
        roi = 1:length(V);
    
    % elseif isfield(data,'overlay') && isfield(data.overlay,'atlas_flag') 
    %     % user is calling one of the built-in atlas parcellations, for which we
    %     % already know the labels and label locations... (AAL or HOA)
    %     
    %     v  = data.overlay.atlas.v;
    %     vi = data.overlay.atlas.vi;
    %     labels = data.overlay.atlas.labels;
    %     
    %     fprintf('Translating label positions to centres of parcellated ROIs\n');
    %     fprintf('(this can take a minute)\n');
    %     label_rois = diag(vi)*data.overlay.smooth_weights;
    %     
    %     for i = 1:length(vi)
    %         roin = find(vi==i);
    %         [x,y]=find(label_rois(roin,:));
    %         these(unique(y)) = i;
    %     end
    %     
    %     % now compute parcel centres for each roi
    %     rois = get_roi_centres(data.mesh.vertices,these);
    %     v = rois;
    %     roi = 1:length(v);
    %     n = length(v);
    %     V = ones(n,n);
    %     v = double(v);
            
    else
        fprintf('Labels info not right!\n');
        return
    end
    
    data.labels.roi     = roi;
    data.labels.labels  = labels;
    data.labels.centres = v;
    
    % compile list of in-use node indices
    %--------------------------------------------------------------------------
    to = []; from = []; V(isnan(V)) = 0;
    for i  = 1:size(V,1)
        ni = find(logical(V(i,:)));
        if any(ni)
            to   = [to   roi(ni)];
            from = [from roi(repmat(i,[1,length(ni)])) ];
        end
    end
    
    AN  = unique([to,from]);
    AN  = AN(AN~=0);
    off = 1.5;
    data.labels.in_use = AN;
    
    if sum(v(:,3)) == 0
         off3 = 0;
    else;off3 = off;
    end
    
    % recompute brain centre
    c = spherefit(data.mesh.vertices);
    
    % add these to plot with offset
    %--------------------------------------------------------------------------
    for i = 1:length(AN)
        L = labels{AN(i)};
        pos = v(AN(i),:);
        
        if pos(1) < c(1)
            hemi = 'L';
        elseif pos(1) > c(1)
            hemi = 'R';
        else
            hemi = ' ';
        end
        
        switch hemi
            case 'L';
                t(i) = text(v(AN(i),1)-(off*5),v(AN(i),2)-(off*5),v(AN(i),3)+off3,L);
            case 'R';
                t(i) = text(v(AN(i),1)+(off*2),+v(AN(i),2)+(off*2),v(AN(i),3)+off3,L);
            otherwise
                t(i) = text(v(AN(i),1),v(AN(i),2),v(AN(i),3),L);
        end
    end
    try
        % this fails if the network was empty!
        set(t,'Fontsize',14)
    end
    
    end
    
    function [C,verts] = get_roi_centres(obj,pos,all_roi_tissueindex)
    % Find centre points of rois
    %
    %
    v   = pos;
    roi = all_roi_tissueindex;
    
    i   = unique(roi);
    i(find(i==0))=[];
    
    fprintf('Finding centre points of ROIs for labels...');
    for j = 1:length(i)
        vox    = find(roi==i(j));
        verts{j}  = v(vox,:);
        C(j,:) = spherefit(verts{j});
    end
    fprintf('  ... done! \n');
    % % Plot the first roi, mark centre and label:
    % scatter3(v(:,1),v(:,2),v(:,3),'k'); hold on
    % scatter3(verts(:,1),verts(:,2),verts(:,3),'r')
    % scatter3(C(:,1),C(:,2),C(:,3),'b*')
    
    end
    
    function [C,verts] = get_roi_centres0(obj,pos,all_roi_tissueindex)
    % Find centre points of rois
    %
    % starting at 0
    v   = pos;
    roi = all_roi_tissueindex;
    
    i   = unique(roi);
    %i(find(i==0))=[];
    i = i(1):i(end); % don't skip empties
    fprintf('Finding centre points of ROIs for labels...');
    for j = 1:length(i)
        vox    = find(roi==i(j));
        verts{j}  = v(vox,:);
        C(j,:) = spherefit(verts{j});
    end
    fprintf('  ... done! \n');
    % % Plot the first roi, mark centre and label:
    % scatter3(v(:,1),v(:,2),v(:,3),'k'); hold on
    % scatter3(verts(:,1),verts(:,2),verts(:,3),'r')
    % scatter3(C(:,1),C(:,2),C(:,3),'b*')
    
    end
    
    
    
    function [Centre,A,B,A0] = spherefit(obj,X)
    % Fit sphere to centre of vertices, return centre points
    %
    %
    
    A =  [mean(X(:,1).*(X(:,1)-mean(X(:,1)))), ...
        2*mean(X(:,1).*(X(:,2)-mean(X(:,2)))), ...
        2*mean(X(:,1).*(X(:,3)-mean(X(:,3)))); ...
        0, ...
        mean(X(:,2).*(X(:,2)-mean(X(:,2)))), ...
        2*mean(X(:,2).*(X(:,3)-mean(X(:,3)))); ...
        0, ...
        0, ...
        mean(X(:,3).*(X(:,3)-mean(X(:,3))))];
    A0 = A;
    A = A+A.';
    B = [mean((X(:,1).^2+X(:,2).^2+X(:,3).^2).*(X(:,1)-mean(X(:,1))));...
         mean((X(:,1).^2+X(:,2).^2+X(:,3).^2).*(X(:,2)-mean(X(:,2))));...
         mean((X(:,1).^2+X(:,2).^2+X(:,3).^2).*(X(:,3)-mean(X(:,3))))];
    Centre=(A\B).';
    end
    
    
    function data = video(obj,data,L,colbar,fpath,tv)
    %
    
    % OPTIONS
    %--------------------------------------------------------------------------
    num         = 1;   % number of brains, 1 or 2
    interpl     = 1;   % interpolate
    brainview   = 'T'; % [T]op, [L]eft or [R]ight
    videolength = 10;  % length in seconds
    extendvideo = 0;   % smooth/extend video by factor of
    
    pos  = data.sourcemodel.pos;
    mesh = data.mesh; 
    
    data.video.opt.num         = num;
    data.video.opt.interpl     = interpl;
    data.video.opt.brainview   = brainview;
    data.video.opt.videolength = videolength;
    data.video.opt.extendvideo = extendvideo;
    
    % Extend and temporally smooth video by linear interp between points
    %--------------------------------------------------------------------------
    if extendvideo > 0
        fprintf('Extending and smoothing video sequence by linear interpolation\n');
        time  = tv;
        for i = 1:size(L,1)
            dL(i,:) = interp(L(i,:),4);
        end
        L  = dL;
        tv = linspace(time(1),time(end),size(L,2));
    end
    
    data.video.t = tv;
    %data.video.data = L;
    
    % Overlay
    %--------------------------------------------------------------------------
    v  = pos;
    x  = v(:,1);                    % AAL x verts
    mv = mesh.vertices;             % brain mesh vertices
    nv = length(mv);                % number of brain vertices
    ntime = size(L,2);
    try
        OL = zeros(size(L,1),nv,ntime); % this will be overlay matrix we average
    catch
        fprintf('------------------------ ERROR ------------------------\n');
        fprintf('_______________________________________________________\n');
        fprintf('Projection matrix too big: M(Sources*MeshVertices*Time)\n');
        fprintf('M = size( %d , %d, %d )\n',size(L,1),nv,ntime);
        fprintf('Try: (1). Reducing source by using AAL template flag: ''template'',''aal'' \n');
        fprintf('     (2). Subsample time\n');
        return;
    end
    r  = 1200;                      % radius - number of closest points on mesh
    r  = (nv/length(pos))*1.3;
    w  = linspace(.1,1,r);          % weights for closest points
    w  = fliplr(w);                 % 
    M  = zeros( length(x), nv);     % weights matrix: size(len(mesh),len(AAL))
    S  = [min(L)',max(L)'];
    
    % Get centre point of cortical mesh so we know left/right
    cnt = spherefit(mv);
    Lft = mv(:,1) < cnt(1);
    Rht = mv(:,1) > cnt(1);
    
    Lft = find(Lft);
    Rht = find(Rht);
    
    % find closest points (assume both in mm)
    %--------------------------------------------------------------------------
    fprintf('Determining closest points between sourcemodel & template vertices\n');
    for i = 1:length(x)
    
        % reporting
        if i > 1; fprintf(repmat('\b',[size(str)])); end
        str = sprintf('%d/%d',i,(length(x)));
        fprintf(str);    
        
        LR     = v(i,1);
        IsLeft = (LR-cnt(1)) < 0;
        
        if IsLeft; lri = Lft;
        else;      lri = Rht;
        end
        
        dist       = cdist(mv(lri,:),v(i,:));    
        [junk,ind] = maxpoints(dist,max(r,1),'min');   
        ind        = lri(ind);    
        OL(i,ind,:)= w'*L(i,:);
        M (i,ind)  = w;  
        
    end
    fprintf('\n');
    
    
    if ~interpl
        OL = mean((OL),1); % mean value of a given vertex
    else
        fprintf('Averaging local & overlapping vertices (wait...)');
        for i = 1:size(OL,2)
            for j = 1:size(OL,3)
                % average overlapping voxels 
                L(i,j) = sum( OL(:,i,j) ) / length(find(OL(:,i,j))) ;
            end
        end
        fprintf(' ...Done\n');
        OL = L;
    end
    
    % normalise and rescale
    for i = 1:size(OL,2)
        this    = OL(:,i);
        y(:,i)  = S(i,1) + ((S(i,2)-S(i,1))).*(this - min(this))./(max(this) - min(this));
    end
    
    y(isnan(y)) = 0;
    y  = full(y);
    
    % spm mesh smoothing
    fprintf('Smoothing overlay...\n');
    for i = 1:ntime
        y(:,i) = spm_mesh_smooth(mesh, double(y(:,i)), 4);
    end
    
    data.video.data = y;
    data.video.weights = M;
    
    % close image so can reopen with subplots
    if num == 2;
        close
        f  = figure;
        set(f, 'Position', [100, 100, 2000, 1000])
        h1 = subplot(121);
        h2 = subplot(122);
    else
        switch brainview
            case 'T'; bigimg;view(0,90);
            case 'R'; bigimg;view(90,0);  
            case 'L'; bigimg;view(270,0); 
        end
        f = gcf;
    end
    
    
    % only project requested hemisphere
    % switch data.hemi
    %     case{'left','L','l'}; vi = data.mesh.vleft;
    %     case{'right','R','r'};vi = data.mesh.vright;
    %     otherwise;            vi = 1:length(data.mesh.vertices);
    % end
    
    
    % MAKE THE GRAPH / VIDEO
    %--------------------------------------------------------------------------
    try    vidObj   = VideoWriter(fpath,'MPEG-4');          % CHANGE PROFILE
    catch  vidObj   = VideoWriter(fpath,'Motion JPEG AVI');
    end
    
    set(vidObj,'Quality',100);
    set(vidObj,'FrameRate',size(y,2)/(videolength));
    open(vidObj);
    
    for i = 1:ntime
        
        if i > 1; fprintf(repmat('\b',[1 length(str)])); end
        str = sprintf('building: %d of %d\n',i,ntime);
        fprintf(str);
        
        switch num
            case 2
                plot(h1,gifti(mesh));
                hh       = get(h1,'children');
                set(hh(end),'FaceVertexCData',y(:,i), 'FaceColor','interp');    
                shading interp
                view(270,0);
                caxis([min(S(:,1)) max(S(:,2))]);
                material dull
                camlight left 
    
                plot(h2,gifti(mesh));
                hh       = get(h2,'children');
                set(hh(3),'FaceVertexCData',y(:,i), 'FaceColor','interp');    
                shading interp
                view(90,0);
                caxis([min(S(:,1)) max(S(:,2))]);
                material dull
                camlight right 
            
            case 1
                hh = get(gca,'children');
                set(hh(end),'FaceVertexCData',y(:,i), 'FaceColor','interp');
                caxis([min(S(:,1)) max(S(:,2))]);
                shading interp
        end
        
        try
            tt = title(num2str(tv(i)),'fontsize',20);
            P = get(tt,'Position') ;
            P = P/max(P(:));
            set(tt,'Position',[P(1) P(2)+70 P(3)]) ;
        end
        
        set(findall(gca, 'type', 'text'), 'visible', 'on');
        
        if colbar
            drawnow; pause(.5);
            a1 = gca;
            axb = axes('position', get(a1, 'position'));
            set(axb,'visible','off')
            axes(axb);
            colorbar('peer',a1,'South');
        end
        drawnow;
                
                  
    
        currFrame = getframe(f);
        writeVideo(vidObj,currFrame);
    end
    close(vidObj);
    
    
        
    end

    end

end




% MESHES:
%--------------------------------------------------------------------------
%
%  % Plot the default template mesh:
%  atemplate()         
%
%  % Plot a supplied (gifti) mesh:
%  atemplate('gifti',mesh)   
%
%  % Plot mesh & write out gifti:
%  atemplate('gifti',mesh, 'write',name);  
%  
%  % Plot mesh from nifti volume:
%  atemplate('mesh','mymri.nii')
%
%  % Plot only one hemisphere:
%  atemplate('hemi','left'); atemplate('hemi','L'); atemplate('hemi','l');
%  atemplate('hemi','right');atemplate('hemi','R'); atemplate('hemi','r');
%  atemplate('gifti',mesh,'hemi','left') 
%
%  % Fill holes that appear from hemisphere separation
%  atemplate('gifti',mesh,'hemi','left','fillholes') 
%
%  Plot volume and supply affine transformation matrix:
%  atemplate('mesh','mymri.nii','affine',affinematrix)
%
%
% OVERLAYS:
%--------------------------------------------------------------------------
%
%  % Plot template mesh with overlay from AAL90. L is [90x1]
%  atemplate('overlay',L,'method,{'aal','spheres'});   
%
%  % Plot overlay aligned to mesh using a Euclidean ICP search:
%  atemplate('overlay',L,'sourcemodel',pos,'method','euclidean');  
%
%  % Plot overlay aligned to mesh using a sphere-based trap radius method (def):
%  atemplate('overlay',L,'sourcemodel',pos,'method','spheres');  
%
%  % Plot overlay aligned to mesh using ray casting
%  atemplate('overlay',L,'sourcemodel',pos,'method','raycast');  
%  atemplate('overlay',L,'sourcemodel',pos,'method','raycast','depth',-1.5:.05:1.5);  
%
%  % Plot template with overlay values L at sourcemodel values sormod, interpolated on surface.
%  % Sormod is n-by-3, L is n-by-1.
%  atemplate('sourcemodel',sormod,'overlay',L)  
%
%  % Plot the supplied gifti mesh with overlay values L at sourcemodel locations 
%  % sormod interpolated on surface. 
%  % Sormod is n-by-3, L is n-by-1.
%  atemplate('gifti',mesh,'sourcemodel',sormod,'overlay',L)  
%
%  %  - Plot as above but write out TWO gifti files:
%  %  1. MYGifti.gii is the gifti mesh 
%  %  2. MYGiftiOverlay.gii is the corresponding overlay data
%  atemplate('gifti',mesh,'sourcemodel',sormod,'overlay',L,'write','MYGifti')  
%
%  % Return nifti volume:
%  atemplate('gifti',mesh,'sourcemodel',sormod,'overlay',L,'writenii','mynifti')
%
%  % Plot overlay from nifti volume
%  atemplate('overlay','overlay_volume.nii')
%
%
% % Plot overlay (e.g. from nifti volume) along with curvature on an
% inflated mesh:
%  afigure;D=atemplate('mesh','def2','inflate',...
%                      'overlay',{'curvature','Vis100B_Av.nii'},...
%                      'thresh',.4,'open');
%
%
%  *Note on sourcemodel option: Some fieldtrip sourcemodels have x & y
%  swapped (?), undo by doing sm = [sm(:,2),sm(:,1),sm(:,3)];
%
%  % Co-register the surfaces of the nii volumes in mesh and overlay,
%  % put in aal90 space and add labels:
%  atemplate('mesh',t1.nii,'overlay',functional.nii,'template','aal90','labels')
%
%
%  % Put overlay in AAL space and use interactive 'peaks' (clickable)
%  atemplate('sourcemodel',sormod,'overlay',randi([0 9],1000,1),'template','aal90','peaks')
%
%
%  % Find local maxima in overlay:
%  atemplate('sourcemodel',sormod,'overlay',randi([0 9],1000,1),'components','nocolbar')
%
%  % Do PCA on overlay
%  atemplate('sourcemodel',sormod,'overlay',randi([0 9],1000,1),'pca','nocolbar')
%
%
%
% VIDEO OVERLAY:
%--------------------------------------------------------------------------
%
%  % Plot a video overlay and write it out:
%  atemplate('gifti',g,'sourcemodel',sormod,'video',m,'name',times); 
%
%  % Where:
%  - g      = the gifti surface to plot
%  - sormod = sourcemodel vertices
%  - m      = overlay values [vertices * ntimes] 
%  - name   = video savename
%  - times  = vector of titles (time values?)
%
%
% NETWORKS:
%--------------------------------------------------------------------------
%
%
%  % Plot template mesh with 90x90 AAL network, A:
%  atemplate('network',A); 
%
%  % Plot network A  at sourcemodel locations in 'sormod'. 
%  % Sormod is n-by-3, network is n-by-n.
%  atemplate('sourcemodel',sormod,'network',A);  
%
%  % As above but writes out .node and .edge files for the network, and the gifti mesh file.
%  atemplate('sourcemodel',sormod,'network',A,'write','savename'); 
%  
%  % Plot network defined by .edge and .node files*:
%  atemplate('network','edgefile.edge');
%  % Note, this option sets the 'sourcemodel' coordinates to the vertices
%  defined in the .node file, unless flag to register to atlas space
%
%
% Project to ATLAS
%--------------------------------------------------------------------------
%
%  % Put overlay into atlas space: [choose aal90, aal78 or aal58]
%  atemplate('sourcemodel',sormod,'overlay',o,'template','aal58')
%
%  % Put network into atlas space: 
%  atemplate('sourcemodel',sormod,'network',N,'template','aal78')
%
%  % Put video into atlas space: 
%  atemplate('sourcemodel',sormod,'video',m,'name',times,'template','aal78')
%
%
% OTHER:
%--------------------------------------------------------------------------
%
%  % Export 3D images (overlays, meshes, networks) as VRML & .stl:
%  atemplate( ... ,'writestl','filename.stl');
%  atemplate( ... ,'writevrml','filename.wrl');
%
%
%  % Plot default AAL90 node labels on default mesh:
%  atemplate('labels');         
%
%  % Plot specified labels at centre of roi's specified by all_roi_tissueindex:
%  atemplate('labels', all_roi_tissueindex, labels); 
%
%  % Where:
%  % all_roi_tissue = a 1-by-num-vertices vector containing indices of the
% roi this vertex belongs to
%  % 'labels' = the labels for each roi. 
%  % The text labels are added at the centre of the ROI.
%  
%  Labels notes:
%     - If plotting a network, only edge-connected nodes are labelled.
%     - If plotting a set of nodes (below), only those are labelled.
%     - Otherwise, all ROIs/node labels are added!
%
%  % Plot dots at node==1, i.e. N=[90,1]:
%  atemplate('nodes', N);             
%
%  % Plot tracks loaded with trk_read, from along-tract-stats toolbox.
%  % This function requires some work...
%  atemplate('tracks',tracks,header); 
%
%  Any combination of the inputs should be possible.
%  See scripts in 'Examples' folder for more help.
%
% 
%
%
%
% AN EXAMPLE NETWORK [1]: from 5061 vertex sourcemodel with AAL90 labels
%--------------------------------------------------------------------------
% load New_AALROI_6mm.mat          % load ft source model, labels and roi_inds
% net  = randi([0 1],5061,5061);   % generate a network for this sourmod
% pos  = template_sourcemodel.pos; % get sourcemodel vertices
% labs = AAL_Labels;               % roi labels
% rois = all_roi_tissueindex;      % roi vertex indices
%
% atemplate('sourcemodel',pos,'network',net,'labels',rois,labs);
%
%
% AN EXAMPLE NETWORK [2]: from volume and node/edge files, put in aal58 space:
%--------------------------------------------------------------------------
% atemplate('mesh',t1.nii,'network','test_sourcemod.edge','template','aal58')
%
%
% Requirements: SPM (for spm_vec.m), fieldtrip (for ft_read_mri.m)
%
% AS17














% Notes / Workings
%---------------------------------------------------
    %rotations - because x is orientated backward?
%     t  = 90;
%     Rx = [ 1       0       0      ;
%            0       cos(t) -sin(t) ;
%            0       sin(t)  cos(t) ];
%     Ry = [ cos(t)  0      sin(t)  ;
%            0       1      0       ;
%           -sin(t)  0      cos(t)  ];
%     Rz = [ cos(t) -sin(t) 0       ;
%            sin(t)  cos(t) 0       ;
%            0       0      1       ];
   %M = (Rx*(M'))';
   %M = (Ry*(M'))';
   %M = (Rz*(M'))';