flagGain

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

  function flag = flagTsys(gainVals, flagParams)


   flags on the calculated gains

   sjcm

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

0001 function [gainflag ] = flagGain(gainVals, flagParams)
0002 
0003 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0004 %
0005 %  function flag = flagTsys(gainVals, flagParams)
0006 %
0007 %
0008 %   flags on the calculated gains
0009 %
0010 %   sjcm
0011 %
0012 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0013 
0014 % first we find any values that are imaginary.
0015 indBad1 = imag(gainVals.val)~=0;
0016 
0017 % gains not within range or previously flagged
0018 indBad2 = gainVals.val<flagParams(1) | gainVals.val>flagParams(2) | ...
0019     gainVals.flag;
0020 
0021 indBad = indBad1 | indBad2;
0022 
0023 % outliers
0024 val = gainVals.val;
0025 val(indBad) = nan;
0026 sigs  = nanstd(val);
0027 % if we have less than a handful, don't flag on outliers.
0028 if(length(val)<10)
0029   sigs(:) = 100;
0030 end
0031 means = nanmean(val);
0032 sigs  = repmat(sigs, [size(val,1) 1]);
0033 means = repmat(means, [size(val,1) 1]);
0034 
0035 indBad2 = abs(val - means)./sigs > flagParams(3);
0036 
0037 gainflag = indBad | indBad2;
0038 
0039 return;