Mercurial > hg > ltpda
diff m-toolbox/classes/@ao/.#psd.m.1.68 @ 0:f0afece42f48
Import.
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 23 Nov 2011 19:22:13 +0100 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/m-toolbox/classes/@ao/.#psd.m.1.68 Wed Nov 23 19:22:13 2011 +0100 @@ -0,0 +1,164 @@ +% 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 +