function maskAqaCdf(outFileRoot)
% maskAqACdf.m  A function to mask bad data in Aquascat ABS burst and
%               statistic netCDF files.
%
% usage:    maskAqaCdf(outFileRoot);
%
%       where:  outFileRoot is the name given to the output netCDF files,
%                           surrounded by single quotes without the file
%                           extension .cdf
%
% Copyright 2005 
% USGS Woods Hole Field Center
% Written by Charlene Sullivan
% csullivan@usgs.gov
%
% Dependencies:
%   plot_ABS_stats.m

% C. Sullivan   08/30/05,   version 1.1
% Update code for newer variable names (ie: 'abs_trans#*).  Get rid of 
% 'isunix' loop. Use plot_ABS_stats.m to plot the mean amplitudes. The
% users will use this plot to determine bad data. Create the variable
% 'badBursts'. It is an array of 0's and 1's which indicate bursts that are
% bad.  badBursts = 0 indicates the burst is good; badBursts = 1 indicates
% the burst is bad.
% C. Sullivan   06/29/05,   version 1.0
% This function masks ABS data in the raw data (.cdf) netCDF files.  It
% creates a plot of ABS data for the user to view and asks the user to enter
% the first and last good bursts. All data between the first and last good
% bursts will be left as is, while data prior to the first good burst and 
% after the last good burst will be masked (set to the netCDF fill value of
% 1e35). Masking takes place in copies of the burst and statistic netCDF
% files.


more off

version = '1.1';

tic 

% Check existence of ABS burst and statistic netCDF files
stats = dir(['*s.cdf']);
if isempty(stats)
    fprintf('\n')
    error(['Could not find the ABS statistics netCDF file.  ',...
        'Have you run aqa2cdf.m?']);
else
    statsFile = stats.name;
end
burst = dir('*b.cdf');
if isempty(burst)
    fprintf('\n')
    error(['Could not find the ABS burst netCDF file(s).  ',...
        'Have you run aqa2cdf.m?']);
else
    nBurstFiles = length(burst);
    for n = 1:nBurstFiles
        burstFiles{n} = burst(n).name; % MM 2/1/06
    end
end

% Create a 3-panel pcolor plot of ABS mean amplitudes. This plot is used to
% determine bad data
plot_ABS_stats(statsFile, {'mean'}, 'burst', 0)

% Load the stats file to get the number of bursts.
cdfs = netcdf(statsFile);
burst = cdfs{'burst'}(:);
nBursts = size(burst,1);
close(cdfs)

% Ask the user to look for the first and last good bursts of data.
fprintf('\n')
fprintf('Please view the figure (feel free to zoom!) and look for bad\n')
fprintf('bursts collected during instrument deployment and recovery\n')
answer = input(['Would you like to mask any bad bursts? y/n :  '],'s');
if ~strcmp(answer,'Y') & ~strcmp(answer,'y') & ...
   ~strcmp(answer,'N') & ~strcmp(answer,'n')
        fprintf(['Valid answers are either yes ("y") or no ("n")'])
        answer = input(['Would you like to mask any bad bursts? y/n :  '],'s');
end
if strcmp(answer,'N') || strcmp(answer,'n')
    first_good = 1;
    last_good = nBursts;
    bad_bursts = [];
    fprintf('\n')
    fprintf('Not masking any bursts\n')
    fprintf('All bursts (1:%d) remain un-masked in %s-mask.cdf',nBursts,outFileRoot)
elseif strcmp(answer,'Y') || strcmp(answer,'y')
    first_good = input('Please view the figure and enter the first GOOD burst:  ');
    if isempty(first_good)
        fprintf('Valid answers are numeric only\n')
        first_good = input('Please view the figure and enter the first GOOD burst:  ');
    end
    last_good = input('Please view the figure and enter the last GOOD burst:  ');
    if isempty(last_good)
        fprintf('Valid answers are numeric only\n')
        last_good = input('Please view the figure and enter the last GOOD burst:  ');
    end
    if isequal(first_good,1)
        fprintf(' ')
        fprintf('Bursts %d:%d will be masked in:\n',last_good+1,nBursts)
        badBursts = [last_good+1:nBursts]';
        first = 1;
        last = last_good+1;
    elseif isequal(last_good,nBursts)
        fprintf('Bursts 1:%d will be masked in:\n',first_good-1)
        badBursts = [1:first_good-1]';
        first = first_good-1;
        last = nBursts;
    else
        fprintf('Bursts 1:%d and bursts %d:%d will be masked in:\n',first_good-1,last_good+1,nBursts)
        badBursts = [1:first_good-1 last_good+1:nBursts]';
        first = first_good-1;
        last = last_good+1;
    end
    [fpath, fname, ext] = fileparts(statsFile); % MM 2/1/06
    % fprintf('%s-mask.cdf\n',statsFile(1:end-4))
    fprintf('%s-mask.cdf\n',fname); % MM 2/1/06
    for n=1:length(burstFiles) % MM 2/1/06
        [fpath, fname, ext] = fileparts(burstFiles{n}); % MM 2/1/06
        %fprintf('%s-mask.cdf\n',burstFiles(n,1:end-4))
        fprintf('%s-mask.cdf\n',fname) % MM 2/1/06
    end
end

% Mask the data in the statistics netCDF file.  Be sure to mask data in a
% copy of the statistics netCDF file
statsFileRoot = statsFile(1:end-4);
copyfile([statsFileRoot,'.cdf'],[statsFileRoot,'-mask.cdf'])
fprintf('Working on %s-mask.cdf\n',statsFileRoot)
cdfs = netcdf([statsFileRoot,'-mask.cdf'],'w');
burst = cdfs{'burst'}(:);
% 'badBursts' is an array of 0's and 1's and indicates
% bursts that are bad.  badBursts = 1 indicates the burst
% is good.  badBursts = 0 indicates the burst is bad
cdfs{'badBursts'} = nclong('burst');
cdfs{'badBursts'}.FORTRAN_format = ncchar('F10.2');
cdfs{'badBursts'}.units = ncchar('counts');
cdfs{'badBursts'}.type = ncchar('EVEN');
cdfs{'badBursts'}.FillValue_ = ncfloat(1.00000004091848e+035);
cdfs{'badBursts'}(:) = ones(size(burst)); % initialize w/ all 1's (good bursts)
[TF, LOC] = ismember(badBursts,burst);
cdfs{'badBursts'}(1:first) = 0;
cdfs{'badBursts'}(last:nBursts) = 0;
theVars = var(cdfs);
for v = 1:length(theVars)
    varName = char(ncnames(theVars{v}));
    if ~strcmp(varName,'time') && ...
       ~strcmp(varName,'time2') && ...
       ~strcmp(varName,'r') && ...
       ~strcmp(varName,'pctile') && ...
       ~strcmp(varName,'burst') && ...
       ~strcmp(varName,'badBursts')
            theFillValue = theVars{v}.FillValue_(:);
            dims = size(theVars{v});
            if length(dims) == 1 
                theVars{v}(1:first) = theFillValue;
                theVars{v}(last:nBursts) = theFillValue;
            elseif length(dims) == 2 
                theVars{v}(1:first,:) = theFillValue;
                theVars{v}(last:nBursts,:) = theFillValue;
            elseif length(dims) == 3 
                theVars{v}(1:first,:,:) = theFillValue;
                theVars{v}(last:nBursts,:,:) = theFillValue;
            end
    end
end
hist = cdfs.history(:);
hist_new = ['Bad data masked by maskAqaCdf.m V ',version,'; ',hist];
cdfs.history = ncchar(hist_new);
cdfs.CREATION_DATE = ncchar(datestr(now,0));
close(cdfs)

% Mask the data in the burst netCDF files. Be sure to mask data in a copy
% of the burst netCDF file
for n = 1:nBurstFiles
    [fpath, burstFileRoot, ext] = fileparts(burstFiles{n}); % MM 2/1/06
    %burstFileRoot = burstFiles(n,1:end-4);
    copyfile([burstFileRoot,'.cdf'],[burstFileRoot,'-mask.cdf'])
    fprintf('Working on %s-mask.cdf\n',burstFileRoot)
    cdfb = netcdf([burstFileRoot,'-mask.cdf'],'w');
    burst = cdfb{'burst'}(:);    
    % 'badBursts' is an array of 0's and 1's and indicates
    % bursts that are bad.  badBursts = 1 indicates the burst
    % is good.  badBursts = 0 indicates the burst is bad
    cdfb{'badBursts'} = nclong('burst');
    cdfb{'badBursts'}.FORTRAN_format = ncchar('F10.2');
    cdfb{'badBursts'}.units = ncchar('counts');
    cdfb{'badBursts'}.type = ncchar('EVEN');
    cdfb{'badBursts'}.FillValue_ = ncfloat(1.00000004091848e+035);
    cdfb{'badBursts'}(:) = ones(size(burst)); % initialize w/ all 1's (good bursts)
    [TF, LOC] = ismember(badBursts,burst);
    f = find(LOC ~= 0);
    if ~isempty(f)
        LOC = LOC(f);
        cdfs{'badBursts'}(LOC) = 0;
        theVars = var(cdfb);
        for v = 1:length(theVars)
            varName = char(ncnames(theVars{v}));
            if strcmp(varName,'abs_trans1') || ...
               strcmp(varName,'abs_trans2') || ...
               strcmp(varName,'abs_trans3')
                   theFillValue = theVars{v}.FillValue_(:);
                   theVars{v}(LOC,:,:) = theFillValue;
            end
        end
    end
    hist = cdfb.history(:);
    hist_new = ['Bad data masked by maskAqaCdf.m V ',version,'; ',hist];
    cdfb.history = ncchar(hist_new);
    cdfb.CREATION_DATE = ncchar(datestr(now,0));
    close(cdfb)
end

disp('Finished masking files')
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