mfbox_pre_varthreshold_run.m

toolbox for spm 5 for data, model free analysis

function [X,mask,grid,timeline,params,private]=mfbox_pre_varthreshold_run(X,mask,grid,timeline,params,runflag,private)
% select voxels by variance
%
% Usage:
%  [X,mask,grid,timeline,params,private]=mfbox_pre_varthreshold_run(X,mask,grid,timeline,params,runflag,private)
%
%  X        - (NxT) data
%             or struct for mfbox_databackend('getdata',X,i),[],1);
%  mask     - data mask (XxYxZ) with sum(mask(:))==N
%  grid     - 3d positions (3xN) of the data values
%  timeline - timeline (1xT)
%  params   - struct with
%             priority - evaluation priority
%             varmin   - min variance
%             varmax   - max variance
%  runflag  - -1 get default parameter
%              0 interactive ask parameters
%              1 interactive ask parameters and run
%              2 run
%  private  - private data to enable plot updates while selecting (see also mfbox_databackend)
%
% Copyright by Peter Gruber and Fabian J. Theis
% Signal Processing & Information Theory group
% Institute of Biophysics, University of Regensburg, Germany
% Homepage: http://research.fabian.theis.name
%           http://www-aglang.uni-regensburg.de
%
% This file is free software, subject to the 
% GNU GENERAL PUBLIC LICENSE, see gpl.txt

error(nargchk(1,7,nargin));
error(nargchk(1,6,nargout));

if (isstruct(X)), s = [X.dim,X.timesteps];
else s = size(X);
end
dim = s(1:(end-1));
if (length(dim)<2), dim = [1,dim]; end
n = s(end);

if (nargin<2), mask = true(dim); end
dim = size(mask);
if (length(dim)==length(s)), n = 1; end

if (nargin<3), grid = mfbox_mkgrid(dim)'; end
if (nargin<4), timeline = 0:(n-1); end
if (nargin<5), params = []; end
if (nargin<6), runflag = 1; end
if (nargin<7), private = []; end

ms = size(mask);
if (any(ms==0)), ms = 0; end
ng = mat2cell(mfbox_mkgrid(ms),prod(ms),ones(1,length(ms)));
g = cell(1,size(grid,1));
for i=1:size(grid,1), g{i} = reshape(grid(i,:),dim); end
if (length(dim)>1&&prod(dim)>0)
    if (isstruct(X))
        oX = X;
        X = zeros([prod(dim),n],'single');
        es = zeros(dim); e = zeros(dim);
        for i=1:n
            v = reshape(mfbox_databackend('getdata',oX,i),dim);
            es = es+v.^2; e = e+v;
            X(mask(:),i) = v(mask);
        end
        mvar = sqrt((es/n)-(e/n).^2);
    else
        es = zeros(dim); e = zeros(dim);
        X = reshape(X,[],n);
        for i=1:n
            v = X(:,i);
            es = es+v.^2; e = e+v;
        end
        mvar = sqrt((es/n)-(e/n).^2);
    end
else
    mvar = [];
end
if (~isempty(mvar))
    mvar = reshape(interpn(g{:},mvar,ng{:}),ms);
end
maxvar = max(mvar(:));

params = mfbox_checkparam(params,'pre','varthreshold', ...
    struct('varmin',0,'varmax',1,'priority',40));

if (abs(runflag-0.5)<1)
    if (exist('OCTAVE_HOME')~=5)% matlab
        [params,private] = mfbox_pre_varthresholdg(X,mask,grid,timeline,params,runflag,private);
    elseif (exist('OCTAVE_HOME')==5) %octave
        [params,runflag] = mfbox_getparam(params,runflag,'mfbox_pre_varthresholdg.py');
    end
end

if (runflag>0 && isstruct(params))
    v = params.varmin; w = params.varmax;
    if (v<w), mask = mask&(mvar>=v*maxvar)&(mvar<=w*maxvar);
    else mask = mask&((mvar<w*maxvar)|(mvar>v*maxvar));
    end

    sgr = size(grid);
    sm = size(mask);
    g = mat2cell(min(repmat(sm',1,sgr(2)),max(ones(sgr), ...
        round(grid))),ones(1,sgr(1)),sgr(2));
    nmask = mask(sub2ind(sm,g{:}));
    grid = grid(:,nmask);
    X = reshape(X,[],n);
    X = X(nmask,:);
end