--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/@ao/fixfs.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,229 @@
+% FIXFS resamples the input time-series to have a fixed sample rate.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% FIXFS resamples the input time-series to have a fixed sample rate.
+%
+% The new sampling grid is computed from the specified sample rate. If no
+% sample rate is specified, the target is taken from a fit to the input tsdata
+% object. The new sampling grid starts at the time returned from the fit
+% (unless specified) and contains the same number of points or spans the
+% same time as specified.
+%
+% CALL:        bs = fixfs(a1,a2,a3,...,pl)
+%              bs = fixfs(as,pl)
+%              bs = as.fixfs(pl)
+%
+% INPUTS:      aN   - input analysis objects
+%              as   - input analysis objects array
+%              pl   - input parameter list
+%
+% OUTPUTS:     bs   - array of analysis objects, one for each input
+%
+% <a href="matlab:utils.helper.displayMethodInfo('ao', 'fixfs')">Parameters Description</a>
+%
+% $Id: fixfs.m,v 1.40 2011/08/23 13:48:48 hewitson Exp $
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+
+function varargout = fixfs(varargin)
+
+  % Check if this is a call for parameters
+  if utils.helper.isinfocall(varargin{:})
+    varargout{1} = getInfo(varargin{3});
+    return
+  end
+
+  import utils.const.*
+  utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
+  
+  % Collect input variable names
+  in_names = cell(size(varargin));
+  for ii = 1:nargin,in_names{ii} = inputname(ii);end
+
+  % Collect all AOs and plists
+  [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
+  [pl, pl_invars] = utils.helper.collect_objects(varargin(:), 'plist', in_names);
+
+  % Decide on a deep copy or a modify
+  bs = copy(as, nargout);
+
+  % combine plists
+  pl = parse(pl, getDefaultPlist());
+
+
+  % Get fs
+  t0s    = -1; % Please keep the -1. At the moment we don' use the t0.
+  fss    = find(pl, 'fs');
+  method = find(pl, 'method');
+  interp = find(pl, 'interpolation');
+  alias  = find(pl, 'filter');
+  
+  if numel(fss) ~= 1 && numel(fss) < numel(as)
+    error('### Please specify either a no sample rate, a single sample rate, or one for each input time-series.');
+  end
+
+  % Get only tsdata AOs
+  for jj = 1:numel(bs)
+    if isa(bs(jj).data, 'tsdata')
+      % record input hist
+      hin = bs(jj).hist;
+      bs(jj).timeshift;
+      utils.helper.msg(msg.PROC1, 'fixing AO: %s', bs(jj).name);
+      %------------- Fit sample rate and t0
+      [ffs, ft0, unevenly] = tsdata.fitfs(bs(jj).data.getX);
+      %---------------- Get target sample rate
+      if numel(fss) > 1
+        fs = fss(jj);
+      else
+        fs = fss;
+      end
+      if fs < 0
+        utils.helper.msg(msg.PROC1, 'using sample rate from fit: %f', ffs);
+        fs = ffs;
+      end
+      %---------------- Get target start time
+      if numel(t0s) > 1
+        t0 = t0s(jj);
+      else
+        t0 = t0s;
+      end
+      if t0 < 0
+        utils.helper.msg(msg.PROC1, 'using start time from fit: %f', ft0);
+        t0 = ft0;
+      end
+      if unevenly % then the fitted t0 is empty so we need to get it from the first input datum
+        t0 = bs(jj).x(1);
+      end
+      %-------------- Compute new grid
+      switch lower(method)
+        case 'samples'
+          N = length(bs(jj).data.y);
+          t = linspace(t0, t0+(N-1)/fs, N);
+        case 'time'
+          Nsecs = bs(jj).data.nsecs;
+          t = t0 + [0:1/fs:Nsecs-1/fs].';
+        otherwise
+          error('### Unknown interpolation method. Do you want to preserve data duration or number of samples?');
+      end
+      %-------------- Antialiasing filter
+      switch lower(alias)
+        case 'iir'
+          utils.helper.msg(msg.PROC1, 'applying iir antialising filter');
+          pl = plist('type', 'lowpass',...
+            'order', 8,...
+            'fs', bs(jj).data.fs,...
+            'fc', 0.9*(fs/2));
+          f = miir(pl);
+          filtfilt(bs(jj),f);
+        case 'fir'
+          utils.helper.msg(msg.PROC1, 'applying fir antialising filter');
+          pl = plist('type', 'lowpass',...
+            'order', 64,...
+            'fs', bs(jj).data.fs,...
+            'fc', 0.9*(fs/2));
+          f = mfir(pl);
+          filter(bs(jj),f);
+        case 'off'
+        otherwise
+          error('### Unknown filtering  method. Please choose: ''iir'', ''fir'' or ''off'' ');
+      end   
+      %-------------- Interpolate
+      bs(jj).interp(plist('vertices', t, 'method', interp));
+      % Set name
+      bs(jj).name = sprintf('%s(%s)', mfilename, ao_invars{jj});
+      % Add history
+      bs(jj).addHistory(getInfo, pl, ao_invars(jj), hin);
+      % clear errors
+      bs(jj).clearErrors;
+    else
+      warning('!!! Skipping AO %s - it''s not a time-series AO.', ao_invars{jj});
+      bs(jj) = [];
+    end
+  end
+
+  % Set output
+  if nargout == numel(bs)
+    % List of outputs
+    for ii = 1:numel(bs)
+      varargout{ii} = bs(ii);
+    end
+  else
+    % Single output
+    varargout{1} = bs;
+  end
+end
+
+%--------------------------------------------------------------------------
+% Get Info Object
+%--------------------------------------------------------------------------
+function ii = getInfo(varargin)
+  if nargin == 1 && strcmpi(varargin{1}, 'None')
+    sets = {};
+    pl   = [];
+  else
+    sets = {'Default'};
+    pl   = getDefaultPlist;
+  end
+  % Build info object
+  ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: fixfs.m,v 1.40 2011/08/23 13:48:48 hewitson Exp $', sets, pl);
+end
+
+%--------------------------------------------------------------------------
+% Get Default Plist
+%--------------------------------------------------------------------------
+function plout = getDefaultPlist()
+  persistent pl;  
+  if exist('pl', 'var')==0 || isempty(pl)
+    pl = buildplist();
+  end
+  plout = pl;  
+end
+
+function pl = buildplist()
+  pl = plist();
+  
+  % Fs
+  p = param({'fs', 'The target sampling frequency.'}, {1, {-1}, paramValue.OPTIONAL});
+  pl.append(p);
+  
+  % Method
+  p = param({'method','Choose if the new data should span the same time or preserve the number of samples (time/samples)'},...
+    {1, {'time', 'samples'}, paramValue.SINGLE});
+  pl.append(p);
+  
+  % Filter
+  p = param({'filter','Specify options for the antialiasing filter.'},{3, {'iir', 'fir', 'off'}, paramValue.SINGLE});
+  pl.append(p);
+  
+  % Interpolation
+  pli = ao.getInfo('interp').plists;
+  p = setKey(pli.params(pli.getIndexForKey('method')), 'interpolation');
+  pl.append(p);
+  
+end
+
+%   Parameter list:
+%           'fs'   - specify the target sample rate. Either a single value
+%                    for all input time-series, or a vector of values, one
+%                    for each input. To take a fitted value from the data,
+%                    specify a sample rate of -1.
+%                    e.g.: fs = [1 2 -1 4] to work on 4 input time-series
+%                    [default: take from data]
+% 
+%           'method' - Choose the behaviour
+%                      'Time'    - new data span the same time [default]
+%                      'Samples' - new data preserves number of samples
+%
+%           'filter' - specify if antialising filter is applied
+%                      'off' - no filter applied [default]
+%                      'iir' - 8th order iir filter at fc = fs/2
+%                              filter is applied forward and backward (filtfilt)
+%                      'fir' - 64th order fir filter at fc = fs/2
+%                              filter is applied only forward 
+%
+%           'interpolation' - specify interpolation method as for interp method
+%                             'nearest' -
+%                             'linear'  -
+%                             'spline'  - default
+%                             'cubic'   -