pranaPIVcode.m

function varargout=pranaPIVcode(Data)

%     This file is part of prana, an open-source GUI-driven program for
%     calculating velocity fields using PIV or PTV.
%
%     Copyright (C) 2012-2013  Virginia Polytechnic Institute and State
%     University
% 
%     Copyright 2014-2015.  Los Alamos National Security, LLC. This material was
%     produced under U.S. Government contract DE-AC52-06NA25396 for Los 
%     Alamos National Laboratory (LANL), which is operated by Los Alamos 
%     National Security, LLC for the U.S. Department of Energy. The U.S. 
%     Government has rights to use, reproduce, and distribute this software.
%     NEITHER THE GOVERNMENT NOR LOS ALAMOS NATIONAL SECURITY, LLC MAKES ANY
%     WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LIABILITY FOR THE USE OF
%     THIS SOFTWARE.  If software is modified to produce derivative works,
%     such modified software should be clearly marked, so as not to confuse
%     it with the version available from LANL.
%
%     prana 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.
% 
%     This program 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 this program.  If not, see <http://www.gnu.org/licenses/>.


if ischar(Data)
    if strcmpi(Data,'version')
        varargout{1} = '2.6.0.beta.r2015.05.24';
    else
        error('Error: String request must be ''version''.\m')
    end
else
    
    
    % Make sure the job file has all the required variables.  This will make
    % sure that jobs created from older versions have the necessary variables.
    [Data] = jobfile_validator(Data);
    
    % Write experimental summary for the given job.  This was previuosly in the
    % GUI but has been moved here so that it is always run even if prana is run
    % via a script.
    % This call also puts the out put on the screen for the user to evaluate.
    write_expsummary(Data);
    
    % Determine whether a parallel job was specified
    run_parallel = str2double(Data.par);
    
    % Determine the current version of Matlab
    matlab_version_string = version('-release');
    
    % Convert the matlab version string to a number indicating
    % the release year
    matlab_version_year = str2double(matlab_version_string(1:4));
    
    %% Set up a parallel job if needed
    if run_parallel
        
        % Define the boolean flag specifying whether a matlab pool is
        % opened. Initialize it to zero.
        pool_opened = 0;

        % Inform the user that a parallel pool is being initialized.
        fprintf('\n--- Initializing Processor Cores for Parallel Job ----\n')
        
        % Attempt to open a matlab pool
        %
        % Choose between matlabpool and parpool paradigms based on the 
        % release year of the currently instance of Matlab.
        if matlab_version_year < 2013
            
            % Write and insert a function for opening parallel processing
            % tools using the paradigm for Matlab versions < 2013a.
            
        else
            
            % Open a Matlab parallel processing pool
            % using the paradigm for Matlab versions >= 2013a
            [Data, pool_opened] = open_prana_pool_2015(Data);
        end
        
        % If a pool wasn't successfully opened,
        % run as single core.
        if ~pool_opened
                    
            % Inform the user that processing has begun
            fprintf(['\n-------------- Processing Single-Core Dataset'...
                '(started at %s) ------------------\n'], datestr(now));

            % Run single-core processing.
            pranaprocessing(Data)
            
        end
        
        % Proceed with parallel processing if a parallel pool is open.
        if pool_opened
            I1=str2double(Data.imfstart):str2double(Data.imfstep):str2double(Data.imfend);
            I2=I1+str2double(Data.imcstep);
            if strcmp(Data.masktype,'dynamic')
                maskfend=str2double(Data.maskfstart)+str2double(Data.maskfstep)*length(str2double(Data.imfstart):str2double(Data.imfstep):str2double(Data.imfend))-1;
                maskname=str2double(Data.maskfstart):str2double(Data.maskfstep):maskfend;
            else
                maskname=nan(1,length(I1));
            end
            
            if any(str2double(Data.method)==[4 5])
                fprintf('\n-------------- Processing Parallel-Core Dataset (started at %s) ------------------\n', datestr(now));
                pranaprocessing(Data)
                fprintf('---------------- Job Completed at %s ---------------------\n', datestr(now));
            else
                fprintf('\n-------------- Processing Parallel-Core Dataset (started at %s) ------------------\n', datestr(now));
                spmd
                    
                    if matlab_version_year >= 2010
                        I1dist=getLocalPart(codistributed(I1,codistributor('1d',2)));
                        I2dist=getLocalPart(codistributed(I2,codistributor('1d',2)));
                        masknamedist=getLocalPart(codistributed(maskname,codistributor('1d',2)));
                    else
                        I1dist=localPart(codistributed(I1,codistributor('1d',2),'convert'));
                        I2dist=localPart(codistributed(I2,codistributor('1d',2),'convert'));
                        masknamedist=localPart(codistributed(maskname,codistributor('1d',2),'convert'));
                    end
                    
                    if str2double(Data.method)==6
                        try
                            if labindex~=1
                                previous = labindex-1;
                            else
                                previous = numlabs;
                            end
                            if labindex~=numlabs
                                next = labindex+1;
                            else
                                next = 1;
                            end
                            
                            I1extra_end=labSendReceive(previous,next,I1dist(1:str2double(Data.framestep)));
                            I2extra_end=labSendReceive(previous,next,I2dist(1:str2double(Data.framestep)));
                            masknameextra_end=labSendReceive(previous,next,masknamedist(1:str2double(Data.framestep)));
                            
                            I1extra_beg=labSendReceive(next,previous,I1dist((end-str2double(Data.framestep)+1):end));
                            I2extra_beg=labSendReceive(next,previous,I2dist((end-str2double(Data.framestep)+1):end));
                            masknameextra_beg=labSendReceive(next,previous,masknamedist((end-str2double(Data.framestep)+1):end));
                            
                            if labindex<numlabs
                                I1dist = [I1dist,I1extra_end];
                                I2dist = [I2dist,I2extra_end];
                                masknamedist = [masknamedist,masknameextra_end];
                            end
                            if 1<labindex
                                I1dist = [I1extra_beg,I1dist];
                                I2dist = [I2extra_beg,I2dist];
                                masknamedist = [masknameextra_beg,masknamedist];
                            end
                        catch
                            beep
                            disp('Error Running Multiframe Job in Parallel (Not Enough Image Pairs) - Defaulting to Single Processor')
                            
                            % This closes the open matlab pool.
                            delete(gcp);
                            
                            % This runs the Prana job.
                            pranaprocessing(Data)
                        end
                        
                    end
                    
                    % Run Prana on parallel cores.
                    pranaprocessing(Data,I1dist,I2dist,masknamedist);
                end
                fprintf('----------------- Job Completed at %s----------------------\n', datestr(now));
            end
            
        end
    else
        
        % Inform the user that the processing is beginning.
        fprintf(['\n-------------- Processing Single-Core Dataset (started at %s)--'...
            '----------------\n'], datestr(now));
        pranaprocessing(Data)
        
        % Inform the user that processing has finished.
        fprintf(['---------------- Single-Core Job Completed at %s----------'...
            '-----------\n'], datestr(now))
        
    end
end


end