% rm_badsamp - Replace bad samples in a burst (ie:replace 1st 5 pressures)
%  replaces fixbadsenors- operates on any sensor specified 
%
% [xclean,Qa]=rm_badsamp(x,settings);
%
% called from cleanhydra for each burst
% Inputs
% x = the dirty data set, a structure defined as
% settings = the fine controls
%   settings.samps = samples to replace
%   settings.rvalue = 1e35;  % replacement value to use instead of NaN (default)
%                             % can be 'mean', 'median' or a value
%
% xclean = the fixed data set
% Qa = the feedback on what happened
%   Qa.idx_rem = index numbers of the samples replaced
%   Qa.n_rem == number of samples replaced

% written by Ellyn Montgomery

function [xclean,Qa] = rd_badsamp(x,settings)
%
%  usage  seta.samps=[1:5 end-10:end]; seta.rvalue=1e35;
%        [xclean,Qa] = rd_badsamp(x,seta)

% check inputs
if exist('settings', 'var'),
    if isfield(settings,'samps'), samp_ng = settings.samps; end
    if isfield(settings, 'rvalue'), rvalue = settings.rvalue; end
end
if exist('rvalue','var')~=1, rvalue = NaN; end

warning off MATLAB:divideByZero;

% make sure the shape is consistent
nrows = size(x, 1);
if nrows == 1, x = x'; end

xclean = x;

if ~ischar(rvalue),			
     ngfill=ones(length(samp_ng),1)*rvalue;	% make a fill array
    elseif strcmp(rvalue,'median')
      ngfill=ones(length(samp_ng),1)*gmedian(setxor(x,x(samp_ng)));
    else 				% use the mean
      ngfill=ones(size(samp_ng))*gmean(setxor(x,x(samp_ng)));
    end
     xclean(samp_ng)=ngfill;		% replace the specified samples

  Qa.n_rep = length(samp_ng);
  Qa.idx_rep = samp_ng;