MATLAB: Append lines to interrupted CSV file by calculating new values while ignoring lines that have text information

csvtextscan

I have a file that's almost a CSV, except that on a random range between 100 to 200 there exists a line that contains some random text. Each line has 40 floating point values formatted in scientific form, and I need to add 2 columns to the end of each line to be calculated based on the prior 40 floating point values on the same line.
I have attempted to re-format the CSV using sed on Linux via 
sed -i '1,30d' sample.dat
sed -i '/[ZIJF]/d' sample.dat
(which deletes the header as well as any line containing 'Z', 'I', 'J', or 'F') however doing so breaks compatability with anything reading the data.
Currently my code to read the files is of the form 
 disp("Loading (what should be) sample data")
 fin = fopen('sample.dat');
 data = textscan(fin, '%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f', 'HeaderLines',0,'Delimiter', '\n', 'CollectOutput',1);
 modeldata = cell2mat(data);
which ONLY works if I strip out the text lines with sed and will stop short of parsing the whole file otherwise. The rest of my code takes the modeldata matrix and adds the requisite 2 columns (average and standard deviation) before printing a new CSV file.
I would like to see Matlab load the csv file, read line-by-line and add the requisite 2 columns to any line that does not contain text, and print the final file keeping the header and random text entries in place. I know this is possible in matlab (I'm imagining having to write a loop calling fgetl, checking the line for text, running textscan if it doesn't have text and extending it as required before writing a new line to some new file) however I'm not sure what approach will be easiest.

Best Answer

Sorry, nevermind, I got it: 
OutFile = fopen('Output.dat','w');
fin = fopen('sample.dat');
while (1)
      ln = fgetl(fin);
      if ~ischar(ln)
          break
      end
      if (contains(ln,'y') || contains(ln,'\') || contains(ln,'Z') || contains(ln,'I') || contains(ln,'J') || contains(ln,'F')|| contains(ln,'i'))
          fwrite(OutFile,ln);
          fprintf(OutFile,"\n");
          continue
      end
      data = textscan(ln, '%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f', 'HeaderLines',0,'Delimiter', '\n', 'CollectOutput',1);
      modeldata = cell2mat(data);
      mnvar = mean(modeldata);
      devvar = std(modeldata);
      fprintf(OutFile,"%f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f",modeldata(1),modeldata(2),modeldata(3),modeldata(4),modeldata(5),modeldata(6),modeldata(7),modeldata(8),modeldata(9),modeldata(10),modeldata(11),modeldata(12),modeldata(13),modeldata(14),modeldata(15),modeldata(16),modeldata(17),modeldata(18),modeldata(19),modeldata(20),modeldata(21),modeldata(22),modeldata(23),modeldata(24),modeldata(25),modeldata(26),modeldata(27),modeldata(28),modeldata(29),modeldata(30),modeldata(31),modeldata(32),modeldata(33),modeldata(34),modeldata(35),modeldata(36),modeldata(37),modeldata(38),modeldata(39),modeldata(40));
      fprintf(OutFile," %f %f\n",mnvar,devvar);
  end
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