function masking = tbx_config_masking
% Configuration file for Masking toolbox under SPM5 or later
% See also: tbx_config2cfg_masking

if ~isdeployed, addpath(fullfile(spm('dir'), 'toolbox', 'Masking')); end

innames = Files('Input Images', 'innames', 'image', [1 Inf]);

outname = Entry('Output Filename', 'outname', 's', [1 Inf], ...
    {'average.nii'});
outname.help = {'The output image is saved with this name. ' ...
    ['If a path name is given here, the output ' ...
    'directory setting will be ignored. If there is no path and ' ...
    'no output directory, then the current working directory is used']};

outdir = Files('Output Directory', 'outdir', 'dir', [0 1], {''});
outdir.help = {['Output files will be written into this ' ...
    'directory. If no directory is given, images will be ' ...
    'written to current working directory. If both output ' ...
    'filename and output directory contain a directory, then '...
    'output filename takes precedence.']};

%% Make average
avgexpr = Menu('Average Expression', 'avgexpr', ...
    {'Arithmetic mean', 'Median'}, {'mean(X)', 'median(X)'}, {'mean(X)'});
avgexpr.help = {'Type of average to compute'};

makeavg = Branch('Make Average', 'makeavg', ...
    {innames avgexpr outname outdir}, @make_average, @make_average_vout);
makeavg.help = {...
    ['The Masking toolbox contains code for creating a thresholded ' ...
    'binary image that can be specified as an explicit analysis mask ' ...
    'when setting up a statistical model in SPM. '] ...
    ['This user-interface implements a strategy for automatically ' ...
    'computing a threshold for an image which is typically an average ' ...
    'of the scans to be analysed.'] ...
    'This module first creates an average from the selected images.'};

%% Optimal thresholding
inname = Files('Input Image', 'inname', 'image', [1 1]);
outname.val = {'average_optthr.nii'};

optfunc = Menu('Optimality Criterion', 'optfunc', ...
    {'Corr(img, img > thr)', 'Luo-Nichols anti-mode'}, ...
    {'@opt_thr_corr', '@opt_thr_antimode'}, {'@opt_thr_corr'});
optfunc.help = {'Choice of objective. See help on Optimal Thresholding.'};

optthr = Branch('Optimal Thresholding', 'optthr', ...
    {inname optfunc outname outdir}, @opt_thresh, @opt_thresh_vout);
optthr.help   = {...
    ['The Masking toolbox contains code for creating a thresholded ' ...
    'binary image that can be specified as an explicit analysis mask ' ...
    'when setting up a statistical model in SPM. '] ...
    ['This user-interface implements a strategy for automatically ' ...
    'computing a threshold for an image which is typically an average ' ...
    'of the scans to be analysed.'] ...
    ['This module optimally thresholds an image, according to ' ...
    'one of two objective functions.'] ...
    'The first is the one from the paper by Ridgway et al, ' ...
    ' http://dx.doi.org/10.1016/j.neuroimage.2008.08.045 ' ...
    ['It is based on maximising the correlation between the original ' ...
    'and thresholded images. This is equivalent to finding the ' ...
    'threshold that gives the largest two-sample t-statistic between ' ...
    'the above and below threshold parts of the data, ' ...
    'which is similar to the classic Otsu thresholding criterion, ' ...
    'based on maximum between-class separation with the histrogram. '] ...
    ' http://en.wikipedia.org/wiki/Otsu''s_method' ...
    'Please cite Ridgway et al. if you find the toolbox useful.' ...
    '', 'The second is described in appendix B of the paper ' ...
    [' Diagnosis and exploration of massively univariate ' ...
    'neuroimaging models'] ...
    ' Luo & Nichols (2003) Neuroimage 19:1014-1032 ' ...
    ' http://www.sph.umich.edu/ni-stat/SPMd/SPMd.pdf ' ...
    ' http://dx.doi.org/10.1016/S1053-8119(03)00149-6 ' ...
    ['Please cite both Ridgway et al. and Luo & Nichols if you use ' ...
    'this method.']};

%% Main toolbox
masking = Repeat('Mask Creation', 'masking', {makeavg, optthr});
masking.help = {...
    ['The Masking toolbox contains code for creating a thresholded ' ...
    'binary image that can be specified as an explicit analysis mask ' ...
    'when setting up a statistical model in SPM. '] ...
    ['This user-interface implements a strategy for automatically ' ...
    'computing a threshold for an image which is typically an average ' ...
    'of the scans to be analysed.'] ...
    ['Command-line functions are available for some other approaches,' ...
    'for example make_majority_mask.m. '] ...
    'These strategies, and related aspects, are described in the paper' ...
    [' Issues with threshold masking ' ...
    'in Voxel Based Morphometry of atrophied brains. '] ...
    [' Ridgway, G.R.; Omar, R.; Ourselin, S.; Hill, D.L.G.; ' ...
    'Warren, J.D.; and Fox, N.C. (in press) NeuroImage'] ...
    ' http://dx.doi.org/10.1016/j.neuroimage.2008.08.045 ' ...
    ' pre-print available from http://eprints.ucl.ac.uk/13060/' ...
    'Please cite this paper if you find the toolbox useful.'};


%% functions for nodes described in spm5/spm_config.m
% (arguments after the ... and line-break are optional)
function out = Menu(name, tag, labels, values, ...
    val, def, help)
out = struct(...
    'type',   'menu', ...
    'name',   name,   ...
    'tag',    tag,    ...
    'labels', {labels}, ...
    'values', {values} ...
    );
if exist('val', 'var') && ~isempty(val)
    out.val = val;
end
if exist('def', 'var') && ~isempty(def)
    out.def = def;
end
if exist('help', 'var') && ~isempty(help)
    out.help = help;
end

%--------------------------------------------------------------------------
function out = Entry(name, tag, strtype, num, ...
    val, def, extras, help)
out = struct(...
    'type',    'entry', ...
    'name',    name,    ...
    'tag',     tag,     ...
    'strtype', strtype, ...
    'num',     num      ...
    );
if exist('val', 'var') && ~isempty(val)
    out.val = val;
end
if exist('def', 'var') && ~isempty(def)
    out.def = def;
end
if exist('extras', 'var') && ~isempty(extras)
    out.extras = extras;
end
if exist('help', 'var') && ~isempty(help)
    out.help = help;
end

%--------------------------------------------------------------------------
function out = Files(name, tag, filter, num, ...
    val, def, help, dir, ufilter)
out = struct(...
    'type',   'files', ...
    'name',   name,    ...
    'tag',    tag,     ...
    'filter', filter,  ...
    'num',    num      ...
    );
if exist('val', 'var') && ~isempty(val)
    out.val = val;
end
if exist('def', 'var') && ~isempty(def)
    out.def = def;
end
if exist('help', 'var') && ~isempty(help)
    out.help = help;
end
if exist('dir', 'var') && ~isempty(dir)
    out.dir = dir;
end
if exist('ufilter', 'var') && ~isempty(ufilter)
    out.ufilter = ufilter;
end

%--------------------------------------------------------------------------
function out = Branch(name, tag, val, ...
    prog, vfiles, check, modality, help)
out = struct(...
    'type', 'branch', ...
    'name', name,     ...
    'tag',  tag,      ...
    'val',  {val}     ...
    );
if exist('prog', 'var') && ~isempty(prog)
    out.prog = prog;
end
if exist('vfiles', 'var') && ~isempty(vfiles)
    out.vfiles = vfiles;
end
if exist('check', 'var') && ~isempty(check)
    out.check = check;
end
if exist('modality', 'var') && ~isempty(modality)
    out.modality = modality;
end
if exist('help', 'var') && ~isempty(help)
    out.help = help;
end

%--------------------------------------------------------------------------
function out = Repeat(name, tag, values, ...
    num, help)
out = struct(...
    'type',   'repeat', ...
    'name',   name,     ...
    'tag',    tag,      ...
    'values', {values}  ...
    );
if exist('num', 'var') && ~isempty(num)
    out.num = num;
end
if exist('help', 'var') && ~isempty(help)
    out.help = help;
end