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# contraste

## (Toolbox/contraste.m in BrainStorm 2.0 (Alpha))

### Function Synopsis

    Cmap=contraste(v,v_pos,v_neg,connectivity_cell,I_pos,I_neg,prop_thres,ref_map)

### Help Text

    CONTRASTE - computing the colormap coding deepness
     function Cmap=contraste(v,v_pos,v_neg,connectivity_cell,I_pos,I_neg,prop_thres,ref_map)

      computing the colormap coding deepness

      inputs : v : vertices, v_pos : vertices of the positive part, v_neg : vertices of the negative part,
               connectivity_cell : result of vertices_connectivity, I_pos/I_neg : indices of positive/negative part of the brain
               prop_thres : percentage of gyri and sulci, ref_map : colors of gyri and sulci
      output : Cmap : colormap codind deepness on the vertices

### Cross-Reference Information

This function calls

    embedding                          C:\BrainStorm_2001\Toolbox\embedding.m

This function is called by

    c_activ                            C:\BrainStorm_2001\Toolbox\c_activ.m

### Listing of function C:\BrainStorm_2001\Toolbox\contraste.m

    function Cmap=contraste(v,v_pos,v_neg,connectivity_cell,I_pos,I_neg,prop_thres,ref_map)
    %CONTRASTE - computing the colormap coding deepness
    % function Cmap=contraste(v,v_pos,v_neg,connectivity_cell,I_pos,I_neg,prop_thres,ref_map)
    %
    %  computing the colormap coding deepness
    %
    %  inputs : v : vertices, v_pos : vertices of the positive part, v_neg : vertices of the negative part,
    %           connectivity_cell : result of vertices_connectivity, I_pos/I_neg : indices of positive/negative part of the brain
    %           prop_thres : percentage of gyri and sulci, ref_map : colors of gyri and sulci
    %  output : Cmap : colormap codind deepness on the vertices
    %

    %<autobegin> ---------------------- 26-May-2004 11:29:54 -----------------------
    % --------- Automatically Generated Comments Block Using AUTO_COMMENTS ---------
    %
    % CATEGORY: Visualization
    %
    % Alphabetical list of external functions (non-Matlab):
    %   toolbox\embedding.m
    %
    % At Check-in: $Author: Mosher $  $Revision: 14 $  $Date: 5/26/04 9:59a $
    %
    % This software is part of BrainStorm Toolbox Version 2.0 (Alpha) 24-May-2004
    %
    % Principal Investigators and Developers:
    % ** Richard M. Leahy, PhD, Signal & Image Processing Institute,
    %    University of Southern California, Los Angeles, CA
    % ** John C. Mosher, PhD, Biophysics Group,
    %    Los Alamos National Laboratory, Los Alamos, NM
    % ** Sylvain Baillet, PhD, Cognitive Neuroscience & Brain Imaging Laboratory,
    %    CNRS, Hopital de la Salpetriere, Paris, France
    %
    % See BrainStorm website at http://neuroimage.usc.edu for further information.
    %
    % Copyright (c) 2004 BrainStorm by the University of Southern California
    % This software distributed  under the terms of the GNU General Public License
    % as published by the Free Software Foundation. Further details on the GPL
    % license can be found at http://www.gnu.org/copyleft/gpl.html .
    %
    % FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE
    % UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY
    % WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF
    % MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY
    % LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE.
    %<autoend> ------------------------ 26-May-2004 11:29:54 -----------------------

    % transform connectivity cells into matrix with first column containing the number of neighbors for each row
    connectivity_mattemp=zeros(size(v,1),20);
    maxim=0;
    for i=1:size(v,1)
        clear v_connex;
        v_connex=[i connectivity_cell{i}];
        if size(v_connex,2)>maxim
            maxim=size(v_connex,2);
        end
        connectivity_mattemp(i,2:size(v_connex,2)+1)=v_connex;
        connectivity_mattemp(i,1)=size(v_connex,2);
    end
    connectivity_mat=connectivity_mattemp(:,1:maxim+1);

    % compute "approximative embedding surface"
    v_embedding=embedding(v,connectivity_mat,3,3);
    v_embedding_pos=embedding(v_pos,connectivity_mat,3,3);
    v_embedding_neg=embedding(v_neg,connectivity_mat,3,3);

    % compute deepness coding (contrast)
    d=sqrt(sum((v_embedding-v).^2,2));
    dsort=sort(d);
    d_gs=dsort(floor(size(d,1)*0.5));
    I_gs=find(d>=d_gs);
    Ipos_gs=intersect(I_gs,I_pos);
    Ineg_gs=intersect(I_gs,I_neg);
    d(Ipos_gs)=sqrt(sum((v_embedding_pos(Ipos_gs,:)-v_pos(Ipos_gs,:)).^2,2));
    d(Ineg_gs)=sqrt(sum((v_embedding_neg(Ineg_gs,:)-v_neg(Ineg_gs,:)).^2,2));
    minid=min(min(d));
    maxid=max(max(d));
    C=(ones(size(v_embedding,1),1)-((d)-minid)/(maxid-minid));
    clear d;
    Cmap=ones(size(v_embedding,1),1)*ref_map(1,:);
    C_sort=sort(C);
    prop_max=C_sort(floor(size(C_sort,1)*prop_thres));
    clear C_sort;
    I=find(C<=prop_max);
    Cmap(I,:)=ones(size(I,1),1)*ref_map(2,:);

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