function obj = coef_f_q_sym_pTop_func_new(in1,in2,in3)
coefs_tq1_1 = in2(1);
coefs_tq1_2 = in2(4);
coefs_tq1_3 = in2(7);
coefs_tq1_4 = in2(10);
coefs_tq1_5 = in2(13);
coefs_tq1_6 = in2(16);
coefs_tq1_7 = in2(19);
coefs_tq1_8 = in2(22);
coefs_tq1_9 = in2(25);
coefs_tq2_1 = in2(2);
coefs_tq2_2 = in2(5);
coefs_tq2_3 = in2(8);
coefs_tq2_4 = in2(11);
coefs_tq2_5 = in2(14);
coefs_tq2_6 = in2(17);
coefs_tq2_7 = in2(20);
coefs_tq2_8 = in2(23);
coefs_tq2_9 = in2(26);
coefs_tq3_1 = in2(3);
coefs_tq3_2 = in2(6);
coefs_tq3_3 = in2(9);
coefs_tq3_4 = in2(12);
coefs_tq3_5 = in2(15);
coefs_tq3_6 = in2(18);
coefs_tq3_7 = in2(21);
coefs_tq3_8 = in2(24);
coefs_tq3_9 = in2(27);
coefs_tq1_10 = in2(28);
coefs_tq1_11 = in2(31);
coefs_tq2_10 = in2(29);
coefs_tq2_11 = in2(32);
coefs_tq3_10 = in2(30);
coefs_tq3_11 = in2(33);
coef_Jacob1_qt_syms1 = in3(1);
coef_Jacob1_qt_syms2 = in3(5);
coef_Jacob1_qt_syms3 = in3(9);
coef_Jacob1_qt_syms4 = in3(13);
coef_Jacob1_qt_syms5 = in3(17);
coef_Jacob1_qt_syms6 = in3(21);
coef_Jacob1_qt_syms7 = in3(25);
coef_Jacob1_qt_syms8 = in3(29);
coef_Jacob1_qt_syms9 = in3(33);
coef_Jacob2_qt_syms1 = in3(2);
coef_Jacob2_qt_syms2 = in3(6);
coef_Jacob2_qt_syms3 = in3(10);
coef_Jacob2_qt_syms4 = in3(14);
coef_Jacob2_qt_syms5 = in3(18);
coef_Jacob2_qt_syms6 = in3(22);
coef_Jacob2_qt_syms7 = in3(26);
coef_Jacob2_qt_syms8 = in3(30);
coef_Jacob2_qt_syms9 = in3(34);
coef_Jacob3_qt_syms1 = in3(3);
coef_Jacob3_qt_syms2 = in3(7);
coef_Jacob3_qt_syms3 = in3(11);
coef_Jacob3_qt_syms4 = in3(15);
coef_Jacob3_qt_syms5 = in3(19);
coef_Jacob3_qt_syms6 = in3(23);
coef_Jacob3_qt_syms7 = in3(27);
coef_Jacob3_qt_syms8 = in3(31);
coef_Jacob3_qt_syms9 = in3(35);
coef_Jacob4_qt_syms1 = in3(4);
coef_Jacob4_qt_syms2 = in3(8);
coef_Jacob4_qt_syms3 = in3(12);
coef_Jacob4_qt_syms4 = in3(16);
coef_Jacob4_qt_syms5 = in3(20);
coef_Jacob4_qt_syms6 = in3(24);
coef_Jacob4_qt_syms7 = in3(28);
coef_Jacob4_qt_syms8 = in3(32);
coef_Jacob4_qt_syms9 = in3(36);
coef_Jacob1_qt_syms10 = in3(37);
coef_Jacob1_qt_syms11 = in3(41);
coef_Jacob1_qt_syms12 = in3(45);
coef_Jacob1_qt_syms13 = in3(49);
coef_Jacob1_qt_syms14 = in3(53);
coef_Jacob1_qt_syms15 = in3(57);
coef_Jacob1_qt_syms16 = in3(61);
coef_Jacob1_qt_syms17 = in3(65);
coef_Jacob1_qt_syms18 = in3(69);
coef_Jacob1_qt_syms19 = in3(73);
coef_Jacob1_qt_syms20 = in3(77);
coef_Jacob1_qt_syms21 = in3(81);
coef_Jacob1_qt_syms22 = in3(85);
coef_Jacob1_qt_syms23 = in3(89);
coef_Jacob1_qt_syms24 = in3(93);
coef_Jacob1_qt_syms25 = in3(97);
coef_Jacob1_qt_syms26 = in3(101);
coef_Jacob1_qt_syms27 = in3(105);
coef_Jacob1_qt_syms28 = in3(109);
coef_Jacob1_qt_syms29 = in3(113);
coef_Jacob1_qt_syms30 = in3(117);
coef_Jacob1_qt_syms31 = in3(121);
coef_Jacob1_qt_syms32 = in3(125);
coef_Jacob1_qt_syms33 = in3(129);
coef_Jacob1_qt_syms34 = in3(133);
coef_Jacob1_qt_syms35 = in3(137);
coef_Jacob1_qt_syms36 = in3(141);
coef_Jacob2_qt_syms10 = in3(38);
coef_Jacob2_qt_syms11 = in3(42);
coef_Jacob2_qt_syms12 = in3(46);
coef_Jacob2_qt_syms13 = in3(50);
coef_Jacob2_qt_syms14 = in3(54);
coef_Jacob2_qt_syms15 = in3(58);
coef_Jacob2_qt_syms16 = in3(62);
coef_Jacob2_qt_syms17 = in3(66);
coef_Jacob2_qt_syms18 = in3(70);
coef_Jacob2_qt_syms19 = in3(74);
coef_Jacob2_qt_syms20 = in3(78);
coef_Jacob2_qt_syms21 = in3(82);
coef_Jacob2_qt_syms22 = in3(86);
coef_Jacob2_qt_syms23 = in3(90);
coef_Jacob2_qt_syms24 = in3(94);
coef_Jacob2_qt_syms25 = in3(98);
coef_Jacob2_qt_syms26 = in3(102);
coef_Jacob2_qt_syms27 = in3(106);
coef_Jacob2_qt_syms28 = in3(110);
coef_Jacob2_qt_syms29 = in3(114);
coef_Jacob2_qt_syms30 = in3(118);
coef_Jacob2_qt_syms31 = in3(122);
coef_Jacob2_qt_syms32 = in3(126);
coef_Jacob2_qt_syms33 = in3(130);
coef_Jacob2_qt_syms34 = in3(134);
coef_Jacob2_qt_syms35 = in3(138);
coef_Jacob2_qt_syms36 = in3(142);
coef_Jacob3_qt_syms10 = in3(39);
coef_Jacob3_qt_syms11 = in3(43);
coef_Jacob3_qt_syms12 = in3(47);
coef_Jacob3_qt_syms13 = in3(51);
coef_Jacob3_qt_syms14 = in3(55);
coef_Jacob3_qt_syms15 = in3(59);
coef_Jacob3_qt_syms16 = in3(63);
coef_Jacob3_qt_syms17 = in3(67);
coef_Jacob3_qt_syms18 = in3(71);
coef_Jacob3_qt_syms19 = in3(75);
coef_Jacob3_qt_syms20 = in3(79);
coef_Jacob3_qt_syms21 = in3(83);
coef_Jacob3_qt_syms22 = in3(87);
coef_Jacob3_qt_syms23 = in3(91);
coef_Jacob3_qt_syms24 = in3(95);
coef_Jacob3_qt_syms25 = in3(99);
coef_Jacob3_qt_syms26 = in3(103);
coef_Jacob3_qt_syms27 = in3(107);
coef_Jacob3_qt_syms28 = in3(111);
coef_Jacob3_qt_syms29 = in3(115);
coef_Jacob3_qt_syms30 = in3(119);
coef_Jacob3_qt_syms31 = in3(123);
coef_Jacob3_qt_syms32 = in3(127);
coef_Jacob3_qt_syms33 = in3(131);
coef_Jacob3_qt_syms34 = in3(135);
coef_Jacob3_qt_syms35 = in3(139);
coef_Jacob3_qt_syms36 = in3(143);
coef_Jacob4_qt_syms10 = in3(40);
coef_Jacob4_qt_syms11 = in3(44);
coef_Jacob4_qt_syms12 = in3(48);
coef_Jacob4_qt_syms13 = in3(52);
coef_Jacob4_qt_syms14 = in3(56);
coef_Jacob4_qt_syms15 = in3(60);
coef_Jacob4_qt_syms16 = in3(64);
coef_Jacob4_qt_syms17 = in3(68);
coef_Jacob4_qt_syms18 = in3(72);
coef_Jacob4_qt_syms19 = in3(76);
coef_Jacob4_qt_syms20 = in3(80);
coef_Jacob4_qt_syms21 = in3(84);
coef_Jacob4_qt_syms22 = in3(88);
coef_Jacob4_qt_syms23 = in3(92);
coef_Jacob4_qt_syms24 = in3(96);
coef_Jacob4_qt_syms25 = in3(100);
coef_Jacob4_qt_syms26 = in3(104);
coef_Jacob4_qt_syms27 = in3(108);
coef_Jacob4_qt_syms28 = in3(112);
coef_Jacob4_qt_syms29 = in3(116);
coef_Jacob4_qt_syms30 = in3(120);
coef_Jacob4_qt_syms31 = in3(124);
coef_Jacob4_qt_syms32 = in3(128);
coef_Jacob4_qt_syms33 = in3(132);
coef_Jacob4_qt_syms34 = in3(136);
coef_Jacob4_qt_syms35 = in3(140);
coef_Jacob4_qt_syms36 = in3(144);
pinvG1_1 = in1(1);
pinvG1_2 = in1(4);
pinvG1_3 = in1(7);
pinvG2_1 = in1(2);
pinvG2_2 = in1(5);
pinvG2_3 = in1(8);
pinvG3_1 = in1(3);
pinvG3_2 = in1(6);
pinvG3_3 = in1(9);
obj = 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function [cellIndex] = findUIDcellIndex(uidString,cellString)
% WRITTEN BY MARTIN: CREATE HEADER!

cellIndex = find(strcmp(uidString,cellString));
if isempty(cellIndex)
    cellIndex = numel(cellString) + 1; % Not present in cellString, so create a new position in the cell for the new UID
end

end


function model=getMetaCycModelForOrganism(organismID,fastaFile,...
    keepTransportRxns,keepUnbalanced,keepUndetermined,minScore,minPositives,useDiamond)
% getMetaCycModelForOrganism
%   Reconstructs a genome-scale metabolic model based on protein homology to the
%   MetaCyc pathway database
%
%   Input:
%   organismID          the query organism's abbreviation, which is defined
%                       by user
%   fastaFile           a FASTA file that contains the protein sequences of
%                       the organism for which to reconstruct a model
%   keepTransportRxns   include transportation reactions, which often have identical
%                       reactants and products that turn to be all-zero columns in
%                       the S matrix (opt, default false)
%   keepUnbalanced      include reactions cannot be unbalanced reactions, usually
%                       because they are polymeric reactions or because of a
%                       specific difficulty in balancing class structures
%                       (opt, default false)
%   keepUndetermined    include reactions that have substrates lack chemical
%                       structures or with non-numerical coefficients (e.g. n+1)
%                       (opt, default false)
%   minScore            minimum Bit scores of BLASTp search (opt, default 100)
%   minPositives        minimum Positives values of BLASTp search (opt, default 45 %)
%   useDiamond          use DIAMOND alignment tools to perform homology search
%                       if true, otherwise the BLASTP is used (opt, default true)
%
%   Output:
%   model               a model structure for the query organism
%
%   Usage: model=getMetaCycModelForOrganism(organismID,fastaFile,...
%    keepTransportRxns,keepUnbalanced,keepUndetermined,minScore,minPositives,useDiamond)

organismID=char(organismID);
if nargin<2
    EM='No query protein fasta file is specified';
    dispEM(EM);
else
    fastaFile=char(fastaFile);
end
if nargin<3
    keepTransportRxns=false;
end
if nargin<4
    keepUnbalanced=false;
end
if nargin<5
    keepUndetermined=false;
end
if nargin<6
    minScore=100;
end
if nargin<7
    minPositives=45;
end
if nargin<8
    useDiamond=true;
end

if isempty(fastaFile)
    error('*** The query FASTA filename cannot be empty! ***');
else
    fprintf('\nChecking existence of query FASTA file... ');
    %Check if query fasta exists
    fastaFile=checkFileExistence(fastaFile,2); %Copy file to temp dir
    fprintf('done\n');
end

%First generate the full MetaCyc model
metaCycModel=getModelFromMetaCyc([],keepTransportRxns,keepUnbalanced,keepUndetermined);
fprintf('The full MetaCyc model loaded\n');

%Create the draft model from MetaCyc super model model=metaCycModel;
model.id=organismID;
model.name='Generated by homology with MetaCyc database';
model.rxns=metaCycModel.rxns;
model.rxnNames=metaCycModel.rxnNames;
model.eccodes=metaCycModel.eccodes;
model.subSystems=metaCycModel.subSystems;
model.rxnMiriams=metaCycModel.rxnMiriams;
model.rxnReferences=metaCycModel.rxnReferences;
model.lb=metaCycModel.lb;
model.ub=metaCycModel.ub;
model.rev=metaCycModel.rev;
model.c=metaCycModel.c;
model.equations=metaCycModel.equations;

%Get the root directory for RAVEN Toolbox.
ravenPath=findRAVENroot();

%Generate blast strcture by either DIAMOND or BLASTP
if useDiamond
    blastStruc=getDiamond(organismID,fastaFile,{'MetaCyc'},fullfile(ravenPath,'external','metacyc','protseq.fsa'));
else
    blastStruc=getBlast(organismID,fastaFile,{'MetaCyc'},fullfile(ravenPath,'external','metacyc','protseq.fsa'));
end

%Only look the query
blastStructure=blastStruc(2);

%Remove all blast hits that are below the cutoffs
indexes=blastStructure.bitscore>=minScore & blastStructure.ppos>=minPositives;
blastStructure.toGenes(~indexes)=[];
blastStructure.fromGenes(~indexes)=[];
blastStructure.evalue(~indexes)=[];
blastStructure.aligLen(~indexes)=[];
blastStructure.identity(~indexes)=[];
blastStructure.bitscore(~indexes)=[];
blastStructure.ppos(~indexes)=[];
fprintf('Completed searching against MetaCyc protein sequences.\n');

% Get the qualified genes of query organism from blast structure
model.genes=cell(10000,1);
model.proteins=cell(10000,1);
model.bitscore=zeros(10000,1);
model.ppos=zeros(10000,1);
num=1;

%Go through the strucutre and find out the hit with the best bit score
for i=1:numel(blastStructure.fromGenes)
    if num==1
        model.genes(num)=blastStructure.fromGenes(i);
        model.proteins(num)=strrep(blastStructure.toGenes(i), 'gnl|META|', '');
        model.bitscore(num)=blastStructure.bitscore(i);
        model.ppos(num)=blastStructure.ppos(i);
        num=num+1;
        lastGene=blastStructure.fromGenes(i);
    else
        if ~isequal(lastGene,blastStructure.fromGenes(i))
            model.genes(num)=blastStructure.fromGenes(i);
            model.proteins(num)=strrep(blastStructure.toGenes(i), 'gnl|META|', '');
            model.bitscore(num)=blastStructure.bitscore(i);
            model.ppos(num)=blastStructure.ppos(i);
            num=num+1;
            lastGene=blastStructure.fromGenes(i);
        else
            if model.bitscore(num)<blastStructure.bitscore(i)
                model.bitscore(num)=blastStructure.bitscore(i);
                model.proteins(num)=strrep(blastStructure.toGenes(i), 'gnl|META|', '');
                model.ppos(num)=blastStructure.ppos(i);
            end
        end
    end
end
model.genes=model.genes(1:num-1);
model.proteins=model.proteins(1:num-1);
model.bitscore=model.bitscore(1:num-1);
model.ppos=model.ppos(1:num-1);

% Get the indexes of matched genes in the metaCycModel
% because some enzymes in the FASTA file cannot be found in the dump file
[hits, indexes]=ismember(model.proteins,metaCycModel.genes);
found = find(hits);
model.genes=model.genes(found);

% Restructure the rxnGeneMat matrix
model.rxnGeneMat=sparse(metaCycModel.rxnGeneMat(:,indexes(found)));

%Remove all reactions without genes
hasGenes=any(model.rxnGeneMat,2);
model=removeReactions(model,~hasGenes,true);

%Generate grRules, only consider the or relationship here Matched enzymes
%are stored in field rxnScores,
rxnNum=numel(model.rxns);
model.rxnConfidenceScores=NaN(rxnNum,1);
model.rxnConfidenceScores(:)=2;
model.grRules=cell(rxnNum,1);
%model.rxnScores=cell(rxnNum,1);
for j=1:rxnNum
    model.grRules{j}='';
    I=find(model.rxnGeneMat(j,:));
    for k=1:numel(I)
        if isempty(model.grRules{j})
            model.grRules(j)=model.genes(I(k));
            %model.rxnScores(j)=model.proteins(I(k));
        else
            model.grRules(j)=strcat(model.grRules(j),{' or '},model.genes(I(k)));
            %model.rxnScores(j)=strcat(model.rxnScores(j),{' or
            %'},model.proteins(I(k)));
        end
    end
end
%update genes field
model.genes=model.genes(any(model.rxnGeneMat));

%Construct the S matrix and list of metabolites
[S, mets, badRxns]=constructS(model.equations);
model.S=S;
model.mets=mets;

%model=removeReactions(model,badRxns,true,true);

%Then match up metabolites
metaCycMets=getMetsFromMetaCyc([]);

%Add information about all metabolites to the model
[a, b]=ismember(model.mets,metaCycMets.mets);
a=find(a);
b=b(a);

if ~isfield(model,'metNames')
    model.metNames=cell(numel(model.mets),1);
    model.metNames(:)={''};
end
model.metNames(a)=metaCycMets.metNames(b);

if ~isfield(model,'metFormulas')
    model.metFormulas=cell(numel(model.mets),1);
    model.metFormulas(:)={''};
end
model.metFormulas(a)=metaCycMets.metFormulas(b);

if ~isfield(model,'metCharges')
    model.metCharges=zeros(numel(model.mets),1);
end
model.metCharges(a)=metaCycMets.metCharges(b);

if ~isfield(model,'b')
    model.b=zeros(numel(model.mets),1);
end
%model.b(a)=metaCycMets.b(b);

if ~isfield(model,'inchis')
    model.inchis=cell(numel(model.mets),1);
    model.inchis(:)={''};
end
model.inchis(a)=metaCycMets.inchis(b);

if ~isfield(model,'metMiriams')
    model.metMiriams=cell(numel(model.mets),1);
end
model.metMiriams(a)=metaCycMets.metMiriams(b);

%Put all metabolites in one compartment called 's' (for system). This is
%done just to be more compatible with the rest of the code
model.comps={'s'};
model.compNames={'System'};
model.metComps=ones(numel(model.mets),1);

%It could also be that the metabolite names are empty for some reason In
%that case, use the ID instead
I=cellfun(@isempty,model.metNames);
model.metNames(I)=model.mets(I);

%Remove additional fields
model=rmfield(model,{'proteins','bitscore','ppos'});

%In the end fix grRules and rxnGeneMat
[grRules,rxnGeneMat] = standardizeGrRules(model,false); %Get detailed output
model.grRules = grRules;
model.rxnGeneMat = rxnGeneMat;
%Remove the temp fasta file
delete(fastaFile)
end


function value = p07_i4 ( action, name, value )

%*****************************************************************************80
%
%% P07_I4 sets or gets I4 parameters for problem 07.
%
%  Licensing:
%
%    This code is distributed under the GNU LGPL license.
%
%  Modified:
%
%    18 March 2007
%
%  Author:
%
%    John Burkardt
%
%  Parameters:
%
%    Input, string ACTION,
%    'D' to set a parameter to its default value.
%    'S' to set a parameter,
%    'G' to get a parameter,
%    'I' to increment a parameter.
%
%    Input, string NAME, the name of the variable.
%    '#' is the number of calls to the integrand routine.
%
%    Input/output, integer VALUE.
%    * If ACTION = 'I', then VALUE is an input quantity, and is the
%      new value to be added to NAME.
%    * If ACTION = 'S', then VALUE is an input quantity, and is the
%      new value to be assigned to NAME.
%    * If ACTION = 'G', then VALUE is an output quantity, and is the
%      current value of NAME.
%
  persistent calls;

  if ( action == 'D' | action == 'd' )

    if ( name == '#' | name == '*' )
      calls = 0;
    end

  elseif ( action == 'G' | action == 'g' )

    if ( name == '#' )
      value = calls;
    else
      fprintf ( 1, '\n' );
      fprintf ( 1, 'P07_I4 - Fatal error!\n' );
      fprintf ( 1, '  Unrecognized name = "%s".\n', name );
      error ( 'P07_I4 - Fatal error!' );
    end

  elseif ( action == 'I' | action == 'i' )

    if ( name == '#' )
      calls = calls + value;
    else
      fprintf ( 1, '\n' );
      fprintf ( 1, 'P07_I4 - Fatal error!\n' );
      fprintf ( 1, '  Unrecognized name = "%s".\n', name );
      error ( 'P07_I4 - Fatal error!' );
    end

  elseif ( action == 'S' | action == 's' )

    if ( name == '#' )
      calls = value;
    else
      fprintf ( 1, '\n' );
      fprintf ( 1, 'P07_I4 - Fatal error!\n' );
      fprintf ( 1, '  Unrecognized name = "%s".\n', name );
      error ( 'P07_I4 - Fatal error!' );
    end

  else

    fprintf ( 1, '\n' );
    fprintf ( 1, 'P07_I4 - Fatal error!\n' );
    fprintf ( 1, '  Unrecognized action = "%s".\n', action );
    error ( 'P07_I4 - Fatal error!' );

  end

  return
end


function planC = ImportDVH(command, planC)
%
% Copyright 2010, Joseph O. Deasy, on behalf of the CERR development team.
%
% This file is part of The Computational Environment for Radiotherapy Research (CERR).
%
% CERR development has been led by:  Aditya Apte, Divya Khullar, James Alaly, and Joseph O. Deasy.
%
% CERR has been financially supported by the US National Institutes of Health under multiple grants.
%
% CERR is distributed under the terms of the Lesser GNU Public License.
%
%     This version of CERR is free software: you can redistribute it and/or modify
%     it under the terms of the GNU General Public License as published by
%     the Free Software Foundation, either version 3 of the License, or
%     (at your option) any later version.
%
% CERR is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
% without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
% See the GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with CERR.  If not, see <http://www.gnu.org/licenses/>.

%global planC;

indexS = planC{end};

if isempty(planC), return; end;
try cd(command);
catch
end;
% read DVH
[FileName,PathName] = uigetfile({'*.*','All files (*.*)';}, sprintf('Loading DVH files'), 'MultiSelect', 'on');
if isequal(FileName,0), return ; end;

scSize = get(0,'ScreenSize');
x = 220; y = 120;
setupDlg = figure('Name','DVH Data Type','NumberTitle','off', ...
    'Position',[(scSize(3)-x)/2, (scSize(4)-y)/2, x, y], 'windowstyle', 'modal');
h = uibuttongroup();
u0 = uicontrol('Style','Radio','String','differential', 'pos',[10 80 100 30],'parent',h,'HandleVisibility','off');
u1 = uicontrol('Style','Radio','String','cumulative', 'pos',[10 40 100 30],'parent',h,'HandleVisibility','off');
u2 = uicontrol('Style','pushbutton','String','Continue', 'pos',[110 10 100 20],'parent',setupDlg,'HandleVisibility','off', ...
    'callback', @continue_callback);
uiwait(setupDlg);
    function continue_callback(source, eventdata)
        so = get(h,'selectedObject');
        if isequal(so, u0)
            setappdata(findobj('tag', 'CERRStartupFig'), 'dvhVolumeType', get(u0, 'string'));
        else
            setappdata(findobj('tag', 'CERRStartupFig'), 'dvhVolumeType', get(u1, 'string'));

        end
        close;
    end

volumeType = getappdata(findobj('tag', 'CERRStartupFig'), 'dvhVolumeType');

if iscell(FileName)
    fileCount = length(FileName);
else
    fileCount = 1;
end;

DVHIndex = length(planC{indexS.DVH}) + 1;

for i = 1:fileCount
    if iscell(FileName)
        dvhFileName = fullfile(PathName, FileName{i});
    else
        dvhFileName = fullfile(PathName, FileName);
    end

    [pathstr, name, ext] = fileparts(dvhFileName);
    name = [name,'.',ext];
    strName = ext(2:end);
    indName = strfind(name, '.');
    doseName = name((indName(end-1)+1):end);
    doseIndex = 1;
    for j=1:length(planC{indexS.dose})
        if isequal(doseName, planC{indexS.dose}(j).fractionGroupID)
            doseIndex = j;
            break;
        end
    end

    try
        [doseBinsV, doseHistV] = readDVHfile(dvhFileName);
    catch
        continue;
    end

    %     doseIndex = stateS.doseSet;
    planC{indexS.DVH}(DVHIndex).volumeType      = volumeType;
    planC{indexS.DVH}(DVHIndex).doseType        = 'plunc';
    planC{indexS.DVH}(DVHIndex).doseUnits        = 'cGy';
    planC{indexS.DVH}(DVHIndex).structureName   = strName;
    planC{indexS.DVH}(DVHIndex).doseIndex       = doseIndex;

    strNum = '';
    for j = 1:length(planC{indexS.structures})
        if  strcmp(upper(strName), upper(planC{indexS.structures}(j).structureName))
            strNum = j;
            break;
        end
    end
    planC{indexS.DVH}(DVHIndex).assocStrUID=planC{indexS.structures}(strNum).strUID;
    planC{indexS.DVH}(DVHIndex).dvhUID = createUID('dvh');
    planC{indexS.DVH}(DVHIndex).assocDoseUID = planC{indexS.dose}(doseIndex).doseUID;

    planC{indexS.DVH}(DVHIndex).fractionGroupID = planC{indexS.dose}(doseIndex).fractionGroupID;

    %Store computational results
    % planC = saveDVHMatrix(DVHIndex, doseBinsV, doseHistV, planC);

    planC{indexS.DVH}(DVHIndex).DVHMatrix(:,1) = doseBinsV;
    planC{indexS.DVH}(DVHIndex).DVHMatrix(:,2) = doseHistV;

    DVHIndex = DVHIndex +1;
end

end