Mercurial > hg > ltpda
view m-toolbox/classes/@ao/filtfilt.m @ 43:bc767aaa99a8
CVS Update
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Tue, 06 Dec 2011 11:09:25 +0100 |
parents | f0afece42f48 |
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% FILTFILT overrides the filtfilt function for analysis objects. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: FILTFILT overrides the filtfilt function for analysis objects. % Applies the input digital IIR filter to the input analysis object % forwards and backwards. If the input analysis object contains a % time-series (tsdata) then the filter is applied using the normal % recursion algorithm. The output analysis object contains a tsdata % object. % % If the input analysis object contains a frequency-series (fsdata) % then the response of the filter is computed and then multiplied % with the input frequency series. The output analysis object % contains a frequency series. % % CALL: >> [b, filt] = filtfilt(a,pl) % >> b = filtfilt(a,pl) % % INPUTS: pl - a parameter list % a - input analysis object % % OUTPUTS: filt - a copy of the input filter object with the % history values filled in. % b - output analysis object containing the filtered data. % % <a href="matlab:utils.helper.displayMethodInfo('ao', 'filtfilt')">Parameters Description</a> % % VERSION: $Id: filtfilt.m,v 1.48 2011/05/12 13:20:42 luigi Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = filtfilt(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); [fbobjs, f_invars] = utils.helper.collect_objects(varargin(:), 'filterbank', in_names); [fobj, f_invars] = utils.helper.collect_objects(varargin(:), 'ltpda_filter', in_names); % Make copies or handles to inputs bs = copy(as, nargout); % combine plists pl = parse(pl, getDefaultPlist()); if isempty(fobj) && isempty(fbobjs) fobj = find(pl, 'filter'); if isa(fobj, 'filterbank') fbobjs = fobj; end f_invars{1} = class(fobj); end % check inputs if ~isa(fobj, 'miir') && ~isa(fobj, 'mfir') && ~isa(fbobjs, 'filterbank') error('### the filter input should be either an miir/mfir object or a filterbank object.'); end fobj_out = []; fp = []; % Loop over AOs for jj = 1:numel(bs) % Copy filter so we can change it if ~isempty(fobj) fp = copy(fobj, 1); elseif ~isempty(fbobjs) fp = copy(fbobjs, 1); end % keep the history to suppress the history of the intermediate steps inhist = bs(jj).hist; if isa(bs(jj).data, 'tsdata') %------------------------------------------------------------------------ %------------------------ Time-series filter ------------------------ %------------------------------------------------------------------------ %%%%%%%%%%%%%%%%%%%%%%%%%%% filter %%%%%%%%%%%%%%%%%%%%%%%%%%% if isa(fp,'ltpda_filter') % redesign if needed fs = bs(jj).data.fs; if fs ~= fp.fs warning('!!! Filter is designed for a different sample rate of data.'); % Adjust/redesign if this is a standard filter fp = redesign(fp, fs); end % apply filter if isa(fp, 'miir') bs(jj).data.y = filtfilt(fp.a, fp.b, bs(jj).data.y); elseif isa(fp, 'mfir'); bs(jj).data.y = filtfilt(fp.a, 1, bs(jj).data.y); else error('### Unknown filter object [%s]', class(fp)); end % set y-units = yunits.*ounits./iunits bs(jj).data.setYunits(bs(jj).data.yunits.*fp.ounits./fp.iunits); %%%%%%%%%%%%%%%%%%%%%%%%%%% filter bank %%%%%%%%%%%%%%%%%%%%%%%%%%% elseif isa(fp,'filterbank') % redesign not implemented for filterbank %%% % utils.math routine to apply filtfilt properly bs(jj).data.y = utils.math.filtfilt_filterbank(bs(jj),fp); % not setting units yet %%% end elseif isa(bs(jj).data, 'fsdata') %------------------------------------------------------------------------ %---------------------- Frequency-series filter --------------------- %------------------------------------------------------------------------ % apply filter fil_resp = resp(fp, plist('f', bs(jj))); bs(jj) = bs(jj).*fil_resp.*conj(fil_resp); else error('### unknown data type.'); end % name for this object bs(jj).name = sprintf('%s(%s)', fp.name, ao_invars{jj}); % add history bs(jj).addHistory(getInfo('None'), pl, ao_invars(jj), [bs(jj).hist fp.hist]); % clear errors bs(jj).clearErrors; % Collect the filters for the output fobj_out = [fobj_out, fp]; end % Set outputs if nargout == 1 varargout{1} = bs; elseif nargout == 2 varargout{1} = bs; varargout{2} = fobj_out; elseif nargout > 2 error('### wrong number of output arguments.'); end end %-------------------------------------------------------------------------- % Get Info Object %-------------------------------------------------------------------------- function ii = getInfo(varargin) if nargin == 1 && strcmpi(varargin{1}, 'None') sets = {}; pls = []; else sets = {'Default'}; pls = getDefaultPlist; end % Build info object ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: filtfilt.m,v 1.48 2011/05/12 13:20:42 luigi Exp $', sets, pls); 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({'filter', 'The filter to apply to the data.'}, paramValue.EMPTY_STRING); end