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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
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% PSD makes power spectral density estimates of the time-series objects %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: PSD makes power spectral density estimates of the % time-series objects in the input analysis objects % using the Welch Overlap method. PSD is computed % using a modified version of MATLAB's welch (>> help welch). % % CALL: bs = psd(a1,a2,a3,...,pl) % bs = psd(as,pl) % bs = as.psd(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', 'psd')">Parameters Description</a> % % VERSION: $Id: psd.m,v 1.68 2011/04/27 05:41:08 mauro Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = psd(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 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names); % Decide on a deep copy or a modify bs = copy(as, nargout); % Apply defaults to plist usepl = applyDefaults(getDefaultPlist, varargin{:}); inhists = []; % Loop over input AOs for jj = 1 : numel(bs) % gather the input history objects inhists = [inhists bs(jj).hist]; % check input data if isa(bs(jj).data, 'tsdata') % Check the time range. time_range = mfind(usepl, 'split', 'times'); if ~isempty(time_range) switch class(time_range) case 'double' bs(jj) = split(bs(jj), plist(... 'times', time_range)); case 'timespan' bs(jj) = split(bs(jj), plist(... 'timespan', time_range)); case 'time' bs(jj) = split(bs(jj), plist(... 'start_time', time_range(1), ... 'end_time', time_range(2))); case 'cell' bs(jj) = split(bs(jj), plist(... 'start_time', time_range{1}, ... 'end_time', time_range{2})); otherwise end end % Check the length of the object if bs(jj).len <= 0 error('### The object is empty! Please revise your settings ...'); end % Utility to deal with nfft, win, olap etc use_pl = utils.helper.process_spectral_options(usepl, 'lin', len(bs(jj)), bs(jj).fs); % Compute PSD using pwelch [pxx, f, info, dev] = welch(bs(jj), 'psd', use_pl); % Keep the data shape of the input AO if size(bs(jj).data.y,1) == 1 pxx = pxx.'; f = f.'; end % create new output fsdata fs = bs(jj).fs; fsd = fsdata(f, pxx, fs); fsd.setXunits('Hz'); fsd.setYunits(info.units); fsd.setEnbw(info.enbw); fsd.setNavs(info.navs); fsd.setT0(bs(jj).data.t0); % update AO bs(jj).data = fsd; % add std deviation bs(jj).data.dy = dev; % set name: scaling of spectrum scale = upper(find(use_pl, 'Scale')); bs(jj).name = sprintf('%s(%s)', lower(scale), ao_invars{jj}); % Add history bs(jj).addHistory(getInfo('None'), use_pl, ao_invars(jj), inhists(jj)); else warning('### Ignoring input AO number %d (%s); it is not a time-series.', jj, bs(jj).name) end end % loop over analysis objects % Set output varargout = utils.helper.setoutputs(nargout, bs); 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: psd.m,v 1.68 2011/04/27 05:41:08 mauro Exp $', sets, pl); end %-------------------------------------------------------------------------- % Get Default Plist %-------------------------------------------------------------------------- function plout = getDefaultPlist() persistent pl; if ~exist('pl', 'var') || isempty(pl) pl = buildplist(); end plout = pl; end function pl = buildplist() % General plist for Welch-based, linearly spaced spectral estimators pl = plist.WELCH_PLIST; % Scale p = param({'Scale',['The scaling of output. Choose from:<ul>', ... '<li>PSD - Power Spectral Density</li>', ... '<li>ASD - Amplitude (linear) Spectral Density</li>', ... '<li>PS - Power Spectrum</li>', ... '<li>AS - Amplitude (linear) Spectrum</li></ul>']}, {1, {'PSD', 'ASD', 'PS', 'AS'}, paramValue.SINGLE}); pl.append(p); end