bad_from_mask

 [ses_mask, bad_chans, bad_trials] = bad_from_mask(ses_mask, badspecs)

 Returns bad channels and modifies ses_mask based on current ses_mask and
 specs in badspecs
   .prop_bad_chan  -- proportion of bad channels for trial to be declared bad
   .prop_bad_trials  -- proportion of bad trials for channel to be declared bad

 ses_mask is a binary mask.  Ones indicate a good trial/channel.  Zero is
 bad. ses_mask is an M X N matrix in which the M rows represent trials and N
 columns represent channels.

0001 function [ses_mask, bad_chans, bad_trials] = bad_from_mask(ses_mask, bs)
0002 %
0003 % [ses_mask, bad_chans, bad_trials] = bad_from_mask(ses_mask, badspecs)
0004 %
0005 % Returns bad channels and modifies ses_mask based on current ses_mask and
0006 % specs in badspecs
0007 %   .prop_bad_chan  -- proportion of bad channels for trial to be declared bad
0008 %   .prop_bad_trials  -- proportion of bad trials for channel to be declared bad
0009 %
0010 % ses_mask is a binary mask.  Ones indicate a good trial/channel.  Zero is
0011 % bad. ses_mask is an M X N matrix in which the M rows represent trials and N
0012 % columns represent channels.
0013 
0014 % Modification history:
0015 %
0016 %  01/24/00 PJ
0017 %  07/15/01 PJ Added refchan handling
0018 
0019 if bs.add_refchan2mask
0020   ses_mask(:,end+1) = 1;
0021 end
0022 
0023 ses_mask = ~ses_mask;
0024 
0025 bad_chans = find(sum(ses_mask) >= bs.prop_bad_trials*size(ses_mask,1));
0026 bad_trials = find(sum(ses_mask,2) >= bs.prop_bad_chan*size(ses_mask,2));
0027 
0028 ses_mask(bad_trials,:) = 1;
0029 ses_mask(:,bad_chans) = 1;
0030 
0031 ses_mask = ~ses_mask;
0032 
0033 return
0034