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view m-toolbox/classes/@ao/fftfilt.m @ 21:8be9deffe989 database-connection-manager
Update ltpda_uo.update
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
children |
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% FFTFILT overrides the fft filter function for analysis objects. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: FFTFILT overrides the fft filter function for analysis objects. % Applies the input filter to the input analysis % object in the frequency domain. % % % CALL: >> b = fftfilt(a,smodel); b = fftfilt(a,plist('filter',smodel)) % >> b = fftfilt(a,mfir); b = fftfilt(a,plist('filter',mfir)) % >> b = fftfilt(a,miir); b = fftfilt(a,plist('filter',miir)) % >> b = fftfilt(a,ltpda_tf); b = fftfilt(a,plist('filter',ltpda_tf)) % >> b = fftfilt(a,plist('filter',c)) % c is an AO used as a % filter % % INPUTS: % a - input analysis object % one of % smodel - a model to filter with. The x-dependency must % be on frequency ('f'). % mfir - an FIR filter % miir - an IIR filter % tf - an ltpda_tf object % including: % - pzmodel % - rational % - parfrac % ao - a frequency-series AO. This must have the % correct frequency base to match the FFT'd input % data. You must input it in a plist % % OUTPUTS: % b - output analysis object containing the filtered data. % % <a href="matlab:utils.helper.displayMethodInfo('ao', 'fftfilt')">Parameters Description</a> % % VERSION: $Id: fftfilt.m,v 1.35 2011/05/28 05:42:15 mauro Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = fftfilt(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); [filt, f_invars] = utils.helper.collect_objects(varargin(:), 'ltpda_filter', in_names); [mobjs, md_invars] = utils.helper.collect_objects(varargin(:), 'smodel', in_names); [tfobjs, tf_invars] = utils.helper.collect_objects(varargin(:), 'ltpda_tf', in_names); % Make copies or handles to inputs bs = copy(as, nargout); % Apply defaults to plist pl = applyDefaults(getDefaultPlist, varargin{:}); % Filter with a smodel object if ~isempty(mobjs) filt = mobjs; elseif ~isempty(tfobjs) filt = tfobjs; end if isempty(filt) filt = find(pl, 'filter'); end if isempty(filt) error('### A filter must be provided ###') end % get number of Bins for zero padding Npad = find(pl,'Npad'); % get initial conditions inConds = find(pl,'Initial Conditions'); % check initial conditions if ~isempty(inConds) if iscell(inConds) && numel(inConds) ~= numel(bs) error('### Please give the proper number of initial conditions') end if ~iscell(inConds) && numel(bs)>1 error('### Please give the initial conditions in a cell-array') else inConds = {inConds}; end end inCondsMdl = repmat(smodel(), numel(bs), 1); for ii = 1:numel(bs) if ~isempty(inConds) N = numel(inConds{ii}); expr = ''; ix = 1; for jj = N-1:-1:0 expr = [expr,sprintf('+(2*pi*i*f).^%i*%g',jj,inConds{ii}(ix))]; ix = ix+1; end inCondsMdl(ii) = smodel(plist('expression', expr, 'xvar', 'f')); end end for ii = 1:numel(bs) % keep the history to suppress the history of the intermediate steps inhist = bs(ii).hist; % make sure we operate on physical frequencies switch class(filt) case 'smodel' switch filt.xvar{1} case 'f' % Nothing to do case 's' % I need to map from 's' to 'f' filt.setTrans('2*pi*i'); otherwise error('### The filter smodel must have xvar = ''s'' or ''f'''); end otherwise end % call core method of the fftfilt bs(ii).fftfilt_core(filt, Npad, inCondsMdl(ii)); % Set name bs(ii).setName(sprintf('fftfilt(%s)', ao_invars{ii})); % Add history bs(ii).addHistory(getInfo('None'), pl, ao_invars(ii), [inhist filt(:).hist]); end % 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: fftfilt.m,v 1.35 2011/05/28 05:42:15 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() pl = plist(); % Filter p = param({'filter', 'The filter to apply to the data.'}, paramValue.EMPTY_STRING); pl.append(p); % Number of bins for zero padding p = param({'Npad', 'Number of bins for zero padding.'}, paramValue.EMPTY_DOUBLE); pl.append(p); % Initial conditions p = param({'Initial Conditions', ['A cell containing the arrays of initial conditions, one '... 'for each system being solved, '... 'starting from the lower order to the maximum allowed. '... 'It assumed that the underlying system follows a linear differential equation with constant coefficients. '... 'For example, if the system is the Newton '... '2nd-order equation of motion, than the array contains the initial position and the '... 'initial velocity.']}, paramValue.EMPTY_CELL); pl.append(p); end