plot_brain2d(x,meta,nrow,ncol,dim,c,s)

function[] = plot_brain2d(x,meta,nrow,ncol,dim,c,s)
%PLOT_BRAIN2D  Plot slices of a brain image
%
% Usage: plot_brain2d(x,meta,[nrow],[ncol],[dim],[clim],[in_roi])
%
% INPUTS:
%      x: a 1 by nvoxels vector of voxel activations
%
%   meta: a struct with the following fields:
%           dimx: number of voxels in the x dimension
%           dimy: number of voxels in the y dimension
%           dimz: number of voxels in the z dimension
%        nvoxels: total number of voxels containing brain
%     coordToCol: dimx by dimy by dimz matrix of voxel numbers (zeros
%                 indicate no voxel at the corresponding location)
%     colToCoord: nvoxels by 3 matrix of voxel locations
%
%      X: design matrix (ntrials by ncovariates) containing the activation of
%         each covariate on each trial.
%
%   nrow: an optional argument specifying the number of rows of brain
%         images (default: 4)
% 
%   ncol: an optional argument specifying the number of columns of brain
%         images (default: 4)
%
%    dim: optional argument specifying the plane along which the 3d brain
%         image will be sliced. default: 3 (coronal slices).  options: 1
%         (sagittal), 2 (horizontal), 3 (coronal).
%
%   clim: optional argument specifying upper and lower bounds of the color
%         axis.  minimum value is mapped to blue; upper is mapped to red.
%
% in_roi: optional argument specifying a 1 by nvoxels logical vector
%         indicating which voxels are in the ROI.  these voxels will be
%         outlined in black (if unspecified, the entire brain is outlined).
%
% OUTPUTS: [none]
%
% SEE ALSO: PLOT_BRAIN2D_ALT, PLOT_BRAIN3D, SANEPCOLOR, SLICES,
%           GETTIGHTSUBPLOTHANDLES, IMCONTOUR, SUBPLOT, PCOLOR,
%           IMAGESC, JET
%
%  AUTHOR: Jeremy R. Manning
% CONTACT: [e-mail]

% CHANGELOG:
% 4-11-12  jrm  wrote it.
% 2-22-13  jrm  minor edits to comments.

warning('off','MATLAB:contour:ConstantData');

assert(length(x) == meta.nvoxels,'meta.nvoxels not equal to length(data)');
if ~exist('nrow','var') || isempty(nrow)
    nrow = 4;
end
if ~exist('ncol','var') || isempty(ncol)
    ncol = 4;
end
if ~exist('dim','var') || isempty(dim)
    dim = 3;
end
if ~exist('s','var') || isempty(s);
    s = true(size(x));
end
clf;

img = meta.coordToCol;
img(img == 0) = nan;
select_img = nan(size(img));
for i = 1:meta.nvoxels
    img(meta.colToCoord(i,1),meta.colToCoord(i,2),meta.colToCoord(i,3)) = x(i);
    if s(i)
        select_img(meta.colToCoord(i,1),meta.colToCoord(i,2),meta.colToCoord(i,3)) = x(i);
    end
end
nslices = min(nrow*ncol,size(img,dim));
brain_slices = slices(img,dim);
select_slices = slices(select_img,dim);

slice_edges = linspace(1,size(img,dim),nslices+1);
which_slices = mean([slice_edges(1:end-1) ; slice_edges(2:end)],1);
which_slices = unique(round(which_slices));

hs = getTightSubplotHandles(0.01,0.01,0.01,nrow,ncol);

if ~exist('c','var') || isempty(c)
    c = [prctile(img(:),10) prctile(img(:),90)];
end
for i = 1:length(hs)
    axes(hs(i)); %#ok<LAXES>
    if i <= length(which_slices)
        plot_helper(flipud(squeeze(brain_slices{which_slices(i)})'),flipud(squeeze(select_slices{which_slices(i)})'),c);%,xdim,ydim);        
    else        
        axis off;
    end
end

function[] = plot_helper(img,select_img,c)
hold on;
sanePColor(img); 
try
    caxis(c); 
end
colormap jet;
se = strel('arbitrary',ones([1 1]));
[~,h] = imcontour(imdilate(~isnan(select_img),se),1);
set(h,'LineColor','k','LineWidth',2);
hold off;
axis tight;
axis off;