--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/@ao/fngen.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,181 @@
+% FNGEN creates an arbitrarily long time-series based on the input PSD.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% DESCRIPTION: FNGEN creates an arbitrarily long time-series based on the input PSD.
+%
+% CALL:        b = fngen(axx, pl)
+%
+% PARAMETERS:
+%              'Nsecs'  - The number of seconds to produce
+%                         [default: inverse of PSD length]
+%              'Win'    - The spectral window to use for blending segments
+%                         [default: Kaiser -150dB]
+%
+% 
+% NOTE: this function requires the Statistics Toolbox in order to create
+% a chi^2 distributed random variable.
+% 
+% <a href="matlab:utils.helper.displayMethodInfo('ao', 'fngen')">Parameters Description</a>
+%
+% VERSION:     $Id: fngen.m,v 1.33 2011/04/08 08:56:16 hewitson Exp $
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+function varargout = fngen(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              = utils.helper.collect_objects(varargin(:), 'plist', in_names);
+
+  if nargout == 0
+    error('### fngen cannot be used as a modifier. Please give an output variable.');
+  end
+
+  % combine plists
+  pl = parse(pl, getDefaultPlist());
+
+  % Extract necessary parameters
+  Nsecs = find(pl, 'Nsecs');
+  swin  = find(pl, 'win');
+
+  % Loop over input AOs
+  bs = [];
+  for j=1:numel(as)
+    if ~isa(as(j).data, 'fsdata')
+      warning('!!! %s expects ao/fsdata objects. Skipping AO %s', mfilename, as(j).name);
+    else
+      % Properties of the input PSD
+      N     = 2*(length(as(j).data.y)-1);
+      fs    = as(j).data.x(end)*2;
+      % Extract Fourier components
+      Ak = sqrt(N*as(j).data.getY*fs);
+      Ak = [Ak; Ak(end-1:-1:2)]; % make two-sided
+      % redesign input window for this length
+      switch lower(swin.type)
+        case 'kaiser'
+          swin = specwin('Kaiser', N, swin.psll);
+        otherwise
+          swin = specwin(swin.type, N);
+      end
+      % Compute time-series segments
+      Olap   = 1-swin.rov/100;
+      win    = [swin.win].';
+      segLen = N/fs;
+      if segLen > Nsecs
+        cNsecs = 2*segLen;
+      else
+        cNsecs = Nsecs;
+      end
+      Nsegs  = 1+floor(cNsecs/segLen/Olap);
+
+      % Prepare for generation
+      rphi = zeros(N,1);                   % Empty vector for random phases
+      xs   = zeros(fs*(cNsecs+segLen), 1);  % Large empty vector for new time-series
+      e1   = 1; e2 = segLen*fs;            % Indices into large vector
+      step = round(segLen*fs*Olap);        % step size between each new segment
+      lxs  = length(xs);
+
+      % Loop over segments
+      for s=1:Nsegs
+        % Generate random phase vector
+        rphi(2:N/2) = pi*rand(1,N/2-1);  % First half
+        rphi(N/2+1) = pi*round(rand);    % mid point
+        rphi(N/2+2:N) = -rphi(N/2:-1:2); % reflected half
+        %---- Compute Fourier amplitudes
+        % Use chi^2 distribution to randomize amplitudes.
+        % - from Percival and Walden: S_est = S.*chi2rnd(2)/2
+        %   so A_est = A.*sqrt(chi2rnd(2)/2)
+        % Here we take the measured input data to be a good estimate of
+        % the underlying power spectrum
+        X = (Ak.*sqrt(chi2rnd(2)/2)) .*exp(1i.*rphi);
+        % Inverse FFT
+        x  = ifft(X, 'symmetric');
+        % overlap the segments
+        xs(e1:e2) = xs(e1:e2) + win.*x;
+        % increase step
+        e1 = e1 + step;
+        e2 = e2 + step;
+        if e2>lxs
+          break
+        end
+      end
+      % Make ao from the segment of data we want
+      e1 = fs*segLen/2;
+      e2 = fs*(Nsecs+segLen/2)-1;
+      b  = ao(tsdata(xs(e1:e2).', fs));
+      b.name = sprintf('fngen(%s)', ao_invars{j});
+      b.data.setXunits('s');
+      % Add history
+      b.addHistory(getInfo('None'), pl, ao_invars(j), as(j).hist);
+      % Add to outputs
+      bs = [bs b];
+    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: fngen.m,v 1.33 2011/04/08 08:56:16 hewitson Exp $', sets, pl);
+  ii.setModifier(false);
+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();
+  
+  % Win
+  p = param({'Win', 'The spectral window to use for blending data segments.'}, paramValue.WINDOW);
+  pl.append(p);
+
+  % Nsecs
+  p = param({'Nsecs', 'The number of seconds of data to produce.'}, paramValue.EMPTY_DOUBLE);
+  pl.append(p);
+  
+end
+