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−% INTERPMISSING interpolate missing samples in a time-series.
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−%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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−%
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−% INTERPMISSING interpolate missing samples in a time-series. Missing samples
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−%               are identified as being those where the time-span between one
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−%               sample and the next is larger than d/fs where d is a
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−%               tolerance value. Missing data is then placed in the gap in
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−%               steps of 1/fs. Obviously this is only really correct for
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−%               evenly sampled time-series.
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−%
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−% CALL:        bs = interpmissing(as)
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−%
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−% INPUTS:      as  - array of analysis objects
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−%              pl  - parameter list (see below)
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−%
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−% OUTPUTS:     bs  - array of analysis objects, one for each input
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−%
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−%
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−% <a href="matlab:utils.helper.displayMethodInfo('ao', 'interpmissing')">Parameters Description</a>
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−%
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−% VERSION:     $Id: interpmissing.m,v 1.30 2011/04/08 08:56:16 hewitson Exp $
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−%
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−%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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−
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−function varargout = interpmissing(varargin)
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−
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−  % Check if this is a call for parameters
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−  if utils.helper.isinfocall(varargin{:})
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−    varargout{1} = getInfo(varargin{3});
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−    return
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−  end
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−
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−  import utils.const.*
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−  utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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−  
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−  % Collect input variable names
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−  in_names = cell(size(varargin));
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−  for ii = 1:nargin,in_names{ii} = inputname(ii);end
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−
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−  % Collect all AOs and plists
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−  [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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−  [pl, pl_invars] = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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−
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−  % Decide on a deep copy or a modify
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−  bs = copy(as, nargout);
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−
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−  % Combine plists
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−  pl = parse(pl, getDefaultPlist);
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−
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−
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−  % Get tolerance
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−  dtol = find(pl, 'd');
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−
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−  % Get only tsdata AOs
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−  for j=1:numel(bs)
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−    if isa(bs(j).data, 'tsdata')
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−
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−      % capture input history
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−      ih = bs(j).hist;
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−
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−      % find missing samples
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−      t    = [];
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−      d    = diff(bs(j).data.getX);
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−      idxs = find(d>dtol/bs(j).data.fs);
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−      utils.helper.msg(msg.PROC1, 'found %d data gaps', numel(idxs));
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−
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−      % create new time grid
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−      count = 0;
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−      fs    = bs(j).data.fs;
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−      for k=1:numel(idxs)
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−        idx = idxs(k);
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−        if isempty(t)
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−          t   = bs(j).data.getX(1:idxs(1));
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−        end
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−        % now add samples at 1/fs until we are within 1/fs of the next sample
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−        gap   = bs(j).data.getX(idx+1) - bs(j).data.getX(idx) - 1/fs;
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−        tfill = [[1/fs:1/fs:gap] + bs(j).data.getX(idx)].';
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−        count = count + numel(tfill);
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−        
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−        if k==numel(idxs)
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−          t = [t; tfill; bs(j).data.getX(idx+1:end)];
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−        else
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−          t = [t; tfill; bs(j).data.getX(idx+1:idxs(k+1))];
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−        end
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−      end
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−      utils.helper.msg(msg.PROC1, 'filled with %d samples', count);
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−
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−      % now interpolate onto this new time-grid
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−      if ~isempty(t)
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−        bs(j).interp(plist('vertices', t, 'method', find(pl, 'method')));
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−        bs(j).name = sprintf('interpmissing(%s)', ao_invars{j});
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−        % Add history
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−        bs(j).addHistory(getInfo('None'), pl, ao_invars(j), ih);
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−        % clear errors
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−        bs(j).clearErrors;
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−      else
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−        utils.helper.msg(msg.PROC1, 'no missing samples found in %s - no action performed.', ao_invars{j});
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−      end
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−    else
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−      utils.helper.msg(msg.PROC1, 'skipping AO %s - it''s not a time-series AO.', ao_invars{j});
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−    end
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−  end
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−
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−  % Set output
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−  if nargout == numel(bs)
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−    % List of outputs
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−    for ii = 1:numel(bs)
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−      varargout{ii} = bs(ii);
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−    end
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−  else
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−    % Single output
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−    varargout{1} = bs;
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−  end
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−end
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−
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−%--------------------------------------------------------------------------
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−% Get Info Object
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−%--------------------------------------------------------------------------
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−function ii = getInfo(varargin)
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−  if nargin == 1 && strcmpi(varargin{1}, 'None')
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−    sets = {};
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−    pl   = [];
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−  else
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−    sets = {'Default'};
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−    pl   = getDefaultPlist;
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−  end
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−  % Build info object
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−  ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: interpmissing.m,v 1.30 2011/04/08 08:56:16 hewitson Exp $', sets, pl);
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−end
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−
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−%--------------------------------------------------------------------------
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−% Get Default Plist
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−%--------------------------------------------------------------------------
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−function plout = getDefaultPlist()
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−  persistent pl;  
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−  if exist('pl', 'var')==0 || isempty(pl)
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−    pl = buildplist();
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−  end
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−  plout = pl;  
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−end
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−
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−function pl = buildplist()
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−  pl = plist();
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−  
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−  % d
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−  p = param({'d','The time interval tolerance for finding missing samples.'}, {1, {1.5}, paramValue.OPTIONAL});
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−  pl.append(p);
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−  
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−  % Interpolation method
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−  pli = ao.getInfo('interp').plists;
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−  p = pli.params(pli.getIndexForKey('method'));
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−  pl.append(p);
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−  
+
−end