erp_plot_canonical_corr.m

绝对经典,老外制作的功能强大的matlab实现PLS_TOOBOX

function  status = get_brain_scores()

   status = 0;

   old_pointer = get(gcf,'Pointer');
   set(gcf,'Pointer','watch');

   h = findobj(gcf,'Tag','STDatamatPopup');
   popup_string = get(h,'String');
   selected_idx = get(h,'Value');
   selected_data = popup_string{selected_idx};

   last_datamat = getappdata(gcf,'PlottedDatamat');

   if (strcmp(last_datamat,selected_data) == 0)

       set(findobj(gcf,'Tag','MessageLine'),'String','Loading data ... ');

       [behavdata, st_datamat, st_win_size, st_evt_list] = ...
			load_plotted_datamat(selected_idx);

       if isempty(st_datamat)
           set(gcf,'Pointer',old_pointer);
           return;
       end;

       setappdata(gcf,'PlottedDatamat',selected_data);
       setappdata(gcf,'STDatamat',st_datamat);
       setappdata(gcf,'STWinSize',st_win_size);
       setappdata(gcf,'STEvtList',st_evt_list);

       set(findobj(gcf,'Tag','MessageLine'),'String','');
   else
       set(gcf,'Pointer',old_pointer);
       status = 1;
       return;
   end;

   brainlv = getappdata(gcf,'BrainLV');
   curr_lv_state = getappdata(gcf,'CurrLVState');

   num_lvs = length(curr_lv_state);
   num_voxels = sum(getappdata(gcf,'chan_selection'));
   num_evts = length(st_evt_list);
   
   blv = reshape(brainlv,[st_win_size,num_voxels,num_lvs]);
   bs = zeros(st_win_size,num_evts,num_lvs);

   num_subj_lst = getappdata(gcf,'num_subj_lst');

   bscan = getappdata(gcf,'bscan');
   num_bscan = length(bscan);

   num_behav = size(behavdata,2);
   bcorr = zeros(st_win_size,num_bscan*num_behav,num_lvs);

   for i=1:st_win_size,
     bs(i,:,:) = squeeze(st_datamat(:,i,:)) * squeeze(blv(i,:,:)); 
     bcorr(i,:,:) = ...
        rri_corr_maps(behavdata,squeeze(bs(i,:,:)),num_subj_lst(selected_idx),length(bscan));
   end;

%   setappdata(gcf,'CurrBrainScores',bs);
   setappdata(gcf,'CurrBrainCorrelation',bcorr);
   setappdata(gcf,'num_behav',num_behav);

   status = 1;

   set(gcf,'Pointer',old_pointer);

   return;                                              % get_brain_scores


%--------------------------------------------------------------------------
%
function  plot_brain_scores()

   if (get_brain_scores ~= 1);
      return;
   end;

%   st_evt_list = getappdata(gcf,'STEvtList');

   conditions = getappdata(gcf,'Conditions');
   curr_lv_state = getappdata(gcf,'CurrLVState');
   select_lv = find(curr_lv_state == 1);
   bscan = getappdata(gcf,'bscan');
   num_bscan = length(bscan);
   conditions = conditions(bscan);
   time_info = getappdata(gcf,'common_time_info');

   num_behav = getappdata(gcf,'num_behav');
   st_evt = ones(1,num_behav);
   st_evt_list = [];
   for i=1:num_bscan
      st_evt_list = [st_evt_list, st_evt.*i];
   end

   h = findobj(gcf,'Tag','PlotButton');
   if strcmp(lower(get(h,'Enable')),'off'),  return; end;

   bcorr = getappdata(gcf,'CurrBrainCorrelation');
   plotted_data = squeeze(bcorr(:,:,select_lv))';

   condition = cell(1,num_bscan);  

   max_num_stim = 0;
   for i=1:num_bscan,
      condition{i}.st_row_idx  = find(st_evt_list == i);
      condition{i}.num_stim = length(condition{i}.st_row_idx);
      condition{i}.name = conditions{i};
      if (max_num_stim < condition{i}.num_stim)
          max_num_stim = condition{i}.num_stim;
      end;
   end;

   % generate the plots
   %
   plot_cond_idx = [1:num_bscan];

   plot_dims = getappdata(gcf,'PlotDims');
   if isempty(plot_dims) 
       if (num_bscan < 5)
         num_rows = num_bscan;
       else
         num_rows = 5;
       end;
       if (max_num_stim < 4),
         num_cols = max_num_stim;
       else
         num_cols = 4;
       end;
       plot_dims = [num_rows num_cols];
   end;

   f_pos = get(gcf,'Position');
   axes_margin = [.37 .13 .15 .1];

   erp_plot_cond_stim_ui('STARTUP', plotted_data, condition,  time_info, ...
           	                    axes_margin, plot_dims, plot_cond_idx);

   setappdata(gcf,'PLS_PLOT_BS_ACTIVE',1);
%   save('PLS_plotted_bs','plotted_data','condition');
   setappdata(gcf,'PLS_BS_PLOTTED_DATA',plotted_data);
   setappdata(gcf,'PLS_BS_PLOTTED_CONDITON',condition);
%   set(findobj(gcf,'Tag','PlotMenu'),'Enable','on');
%   set(findobj(gcf,'Tag','OptionMenu'),'Enable','on');

   return;


%--------------------------------------------------------------------------
%
function  [selected_files] = get_selected_filename(select_all_flg),

   st_filename = getappdata(gcf,'STFiles');

   if exist('select_all_flg','var') & (select_all_flg == 1)
      data_option = 3;
   else
      h = findobj(gcf,'Tag','STDatamatPopup');
      selected_idx = get(h,'Value');
      data_option = get(h,'Userdata');
   end;

   switch (data_option)
      case {1}, 				% individual file
	 selected_files{1} = st_filename{selected_idx}.fullname;
      case {2},					% all data
         cnt = 0;
         for i=1:length(st_filename),
            selected_files{i} = st_filename{i}.fullname;
         end;
   end; 

   return;					%  get selected filenames


%--------------------------------------------------------------------------
%
function  save_response_fn()

   if (get_brain_scores ~= 1);
      return;
   end;

   st_evt_list = getappdata(gcf,'STEvtList');
   curr_lv_state = getappdata(gcf,'CurrLVState');
   select_lv = find(curr_lv_state == 1);
   bcorr = getappdata(gcf,'CurrBrainCorrelation');
   bcorr_data = squeeze(bcorr(:,:,select_lv))';
   selected_files = get_selected_filename;

   [filename, pathname] = ...
	uiputfile('*_ERP_bcorr_plot.mat','Save the Temporal Correlations');

   if ischar(filename) & isempty(findstr(lower(filename),'_erp_bcorr_plot'))
      [tmp filename] = fileparts(filename);
      filename = [filename, '_ERP_bcorr_plot.mat'];
   end

   if isequal(filename,0)
	return;
   end;
   rf_plot_file = fullfile(pathname,filename);

   try
     save (rf_plot_file, 'selected_files', 'bcorr_data', 'st_evt_list', 'select_lv');
   catch
     msg = sprintf('Cannot save the response function data to %s',rf_plot_file);
     set(findobj(gcf,'Tag','MessageLine'),'String',['ERROR: ', msg]);
     status = 0;
     return;
   end;

   return;                                      % save_response_fn


%--------------------------------------------------------------------------
%
function  save_response_fn2()

   if (get_brain_scores ~= 1);
      return;
   end;

   curr_lv_state = getappdata(gcf,'CurrLVState');
   select_lv = find(curr_lv_state == 1);
   bs = getappdata(gcf,'CurrBrainScores');
   st_data = squeeze(bs(:,:,select_lv))';
   [nr nc] = size(st_data);

%  data_option = 1  - plot individual ST datamat
%  data_option = 2  - plot all data

   popup_h = findobj(gcf,'Tag','STDatamatPopup');
   selected_idx = get(popup_h,'value');
   data_option = get(popup_h,'Userdata');

   st_filenames = getappdata(gcf,'STFiles');

   num_cond = sum(getappdata(gcf,'cond_selection'));
   evt_list = getappdata(gcf,'STEvtList');

   switch (data_option)

      case {1}					% plot individual data

         all_evt_length = {};			% evt length of all datamat

         %  find all_evt_length
         %
         for i = 1:length(st_filenames)
            filename = st_filenames{i}.fullname;
            group = st_filenames{i}.group;
            if group > length(all_evt_length)
               all_evt_length {group} = [];
               old_evt_length = [];
            else
               old_evt_length = all_evt_length{group};
            end

%            load(filename, 'st_evt_list');
            st_evt_list = getappdata(gcf,'STEvtList');
%            old_evt_length = [old_evt_length, length(st_evt_list)];
            cond_selection = getappdata(gcf,'cond_selection');
            [tmp1 tmp2 evt_length] = ...
		fmri_mask_evt_list(st_evt_list, cond_selection);
            old_evt_length = [old_evt_length, evt_length];
            all_evt_length{group} = old_evt_length;
         end

         group = st_filenames{selected_idx}.group;

         %  calc subj position
         %
         pre_group = 0;

         for i = 1:group - 1
            pre_group = pre_group + length(all_evt_length{i});
         end

         subj = selected_idx - pre_group;

         pattern = ...
            ['<ONLY INPUT PREFIX>*_ERP_grp',num2str(group),'_subj', ...
		num2str(group),'_behavdata1.txt'];

         [fn, pn] = uiputfile(pattern,'Save Behav Data');

         if isequal(fn,0)
            return;
         end;

         [tmp fn] = fileparts(fn);

         first = 1;

         i = group;					% we know grp#
            j = subj;					% we know subj#

               behavdata = zeros(num_cond, nc);

               evt_length = all_evt_length{i}(j);
               last = first + evt_length - 1;
               subj_st_data = st_data(first:last,:);

               run = evt_length / num_cond;		% run# in subj

               if run ~= 1				% avg across run
                  head = 1;
                  for k = 1:num_cond
                     tail = head + run - 1;
                     behavdata(k,:) = mean(subj_st_data(head:tail,:), 1);
                     head = head + run;
                  end
               else
                  behavdata = subj_st_data;
               end

               first = first + evt_length;

               %  write behav data to file
               %
               rf_plot_file = fullfile(pn, ...
                  sprintf('%s_ERP_grp%d_subj%d_behavdata1.txt',fn,i,j));
               save (rf_plot_file, '-ascii', 'behavdata');

      case {2}					% plot all data

         pattern = ...
            ['<ONLY INPUT PREFIX>*_ERP_grp1_subj1_behavdata3.txt'];

         [fn, pn] = uiputfile(pattern,'Save Behav Data');

         if isequal(fn,0)
            return;
         end;

         [tmp fn] = fileparts(fn);

         all_evt_length = {};			% evt length of all datamat

         %  find all_evt_length
         %
         for i = 1:length(st_filenames)
            filename = st_filenames{i}.fullname;
            group = st_filenames{i}.group;
            if group > length(all_evt_length)
               all_evt_length {group} = [];
               old_evt_length = [];
            else
               old_evt_length = all_evt_length{group};
            end

%            load(filename, 'st_evt_list');
            filename = getappdata(gcf, 'plsResultFile');
            load(filename, 'num_cond_lst', 'num_subj_lst');
            st_evt_list = [];
            for j = 1:num_cond_lst(1)
               tmp = j*ones(1,num_subj_lst(i));
               st_evt_list = [st_evt_list tmp];
            end
%            old_evt_length = [old_evt_length, length(st_evt_list)];
            cond_selection = getappdata(gcf,'cond_selection');
            [tmp1 tmp2 evt_length] = ...
		fmri_mask_evt_list(st_evt_list, cond_selection);
            old_evt_length = [old_evt_length, evt_length];
            all_evt_length{group} = old_evt_length;
         end

         %  find st_data for the subj
         %
         first = 1;

         for i = 1:length(all_evt_length)		% all grp
            for j = 1:length(all_evt_length{i})		% all subj

               behavdata = zeros(num_cond, nc);

               evt_length = all_evt_length{i}(j);
               last = first + evt_length - 1;
               subj_st_data = st_data(first:last,:);

               run = evt_length / num_cond;		% run# in subj

               if run ~= 1				% avg across run
                  head = 1;
                  for k = 1:num_cond
                     tail = head + run - 1;
                     behavdata(k,:) = mean(subj_st_data(head:tail,:), 1);
                     head = head + run;
                  end
               else
                  behavdata = subj_st_data;
               end

               first = first + evt_length;

               %  write behav data to file
               %
               rf_plot_file = fullfile(pn, ...
                  sprintf('%s_ERP_grp%d_subj%d_behavdata3.txt',fn,i,j));
               save (rf_plot_file, '-ascii', 'behavdata');
         
            end
         end

   end;

   return;                                      % save_response_fn2