Mercurial > hg > ltpda
view m-toolbox/classes/@ao/filter.m @ 5:5a49956df427 database-connection-manager
LTPDAPreferences panel for new LTPDADatabaseConnectionManager
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
---|---|
date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
children |
line wrap: on
line source
% FILTER overrides the filter function for analysis objects. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: FILTER overrides the filter function for analysis objects. % Applies the input digital IIR/FIR filter to the input analysis % object. 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] = filter(a,pl) % >> [b, filt] = filter(a,filt,pl) % >> b = filter(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. % (only possible if the ouput is a single AO) % b - output analysis object containing the filtered data. % % PROCINFO: The input filter object with the history values filled in are % always stored with a plist in the 'procinfo' property of the AO. % The key of the plist to get the filter is 'Filter'. % % % <a href="matlab:utils.helper.displayMethodInfo('ao', 'filter')">Parameters Description</a> % % VERSION: $Id: filter.m,v 1.86 2011/04/08 08:56:14 hewitson Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = filter(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); [fobjs, f_invars] = utils.helper.collect_objects(varargin(:), 'ltpda_filter', in_names); [fbobjs, fb_invars] = utils.helper.collect_objects(varargin(:), 'filterbank', in_names); [mobjs, m_invars] = utils.helper.collect_objects(varargin(:), 'matrix', in_names); % Make copies or handles to inputs bs = copy(as, nargout); % combine plists pl = parse(pl, getDefaultPlist()); % Filter with a filterbank object or a matrix if ~isempty(fbobjs) fobjs = fbobjs.filters; pl.pset('bank', fbobjs.type); elseif ~isempty(mobjs) fobjs = mobjs.objs; % check we do not have more than one object into the matrix, if this is % the case the problem is considered a N-dimensional filtering problem % that can be solved by matrix/filter if numel(mobjs.objs)>1 error(['### Filter matrix has more than one object. '... 'This seems to be a N-dimensional filtering problem that has to be solved with matrix/filter. '... 'Type help matrix/filter for more information ###']); end if isa(fobjs,'filterbank') % in case of filterbanks pl.pset('bank', fobjs.type); fobjs = fobjs.filters; end end if isempty(fobjs) fobjs = find(pl, 'filter'); % check if we have filterbank or matrix if isa(fobjs,'filterbank') % in case of filterbank pl.pset('bank', fobjs.type); fobjs = fobjs.filters; elseif isa(fobjs,'matrix') % in case of matrix fobjs = fobjs.objs; % check we do not have more than one object into the matrix, if this is % the case the problem is considered a N-dimensional filtering problem % that can be solved by matrix/filter if numel(fobjs)>1 error(['### Filter matrix has more than one object. '... 'This seems to be a N-dimensional filtering problem that has to be solved with matrix/filter. '... 'Type help matrix/filter for more information ###']); end if isa(fobjs,'filterbank') % in case of filterbanks pl.pset('bank', fobjs.type); fobjs = fobjs.filters; end end end % decide to initialize or not init = utils.prog.yes2true(find(pl, 'initialize')); % check inputs if ~isa(fobjs, 'miir') && ~isa(fobjs, 'mfir') error('### the filter input should be an miir/mfir object.'); end if numel(bs) > 1 && nargout > 1 error('### It is only possible to output a bank of filters when applied to a single AO.'); end for j=1:numel(bs) % Copy filter so we can change it fobjs_copy = copy(fobjs, 1); % keep the history to suppress the history of the intermediate steps inhist = bs(j).hist; if isa(bs(j).data, 'tsdata') %------------------------------------------------------------------------ %------------------------ Time-series filter ------------------------ %------------------------------------------------------------------------ % get input data if isa(fobjs_copy, 'mfir') % apply filter utils.helper.msg(msg.PROC1, 'filtering with FIR filter'); [bs(j).data.y, Zf] = filter(fobjs_copy.a, 1, bs(j).data.y, fobjs_copy.histout); % remove group delay if strcmpi(find(pl, 'gdoff'), 'no') gd = floor(fobjs_copy.gd); bs(j).data.setXY(bs(j).data.getX(1:end-gd),bs(j).data.getY(1+gd:end)); bs(j).data.collapseX; end % set units of the output data as we go bs(j).data.setYunits(bs(j).data.yunits.*fobjs_copy.ounits./fobjs_copy.iunits); else %if isa(fobjs_copy, 'miir') utils.helper.msg(msg.PROC1, 'filtering with IIR filter'); % initialise data vector bank = find(pl, 'bank'); switch lower(bank) case 'parallel' y = zeros(size(bs(j).data.getY)); case 'serial' y = ones(size(bs(j).data.getY)); otherwise error('### Unknown filter bank option. Choose ''serial'' or ''parallel''.'); end % Loop over filters iu = fobjs_copy(1).iunits; ou = fobjs_copy(1).ounits; for ff = 1:numel(fobjs_copy) % check sample rate if bs(j).data.fs ~= fobjs_copy(ff).fs warning('!!! Filter is designed for a different sample rate of data.'); % Adjust/redesign if this is a standard filter fobjs_copy(ff) = fobjs_copy(ff).redesign(bs(j).data.fs); end % Choose filtering type switch lower(bank) case 'parallel' % check units if iu ~= fobjs_copy(ff).iunits error('### Input units of each filter must match for a parallel filter bank.'); end if ou ~= fobjs_copy(ff).ounits error('### Output units of each filter must match for a parallel filter bank.'); end % Initialise the state to avoid transients if necessary and % explicitely required if ((~any(fobjs_copy(ff).histout) || isempty(fobjs_copy(ff).histout)) && init) zi = utils.math.iirinit(fobjs_copy(ff).a,fobjs_copy(ff).b); % setting new histout fobjs_copy(ff).setHistout(zi*bs(j).data.y(1)); end % filter data [yf, Zf] = filter(fobjs_copy(ff).a, fobjs_copy(ff).b, bs(j).data.y, fobjs_copy(ff).histout); if ~isequal(size(yf),size(y)) yf = yf.'; end y = y + yf; case 'serial' if ff == 1 y = bs(j).data.y; end % Initialise the state to avoid transients if necessary if ~any(fobjs_copy(ff).histout) || isempty(fobjs_copy(ff).histout) zi = utils.math.iirinit(fobjs_copy(ff).a,fobjs_copy(ff).b); % setting new histout fobjs_copy(ff).setHistout(zi*y(1)); end % filter data [yf, Zf] = filter(fobjs_copy(ff).a, fobjs_copy(ff).b, y, fobjs_copy(ff).histout); if ~isequal(size(yf),size(y)) y = yf.'; else y = yf; end % set units of the output data as we go bs(j).data.setYunits(bs(j).data.yunits.*fobjs_copy(ff).ounits./fobjs_copy(ff).iunits); otherwise error('### Unknown filter bank option. Choose ''serial'' or ''parallel''.'); end % set filter output history fobjs_copy(ff).setHistout(Zf); end % End loop over filters % set output data bs(j).data.setY(y); % clear errors bs(j).clearErrors; % if this was a parallel filter bank, we should set the units now if strcmpi(bank, 'parallel') % set units of the output data bs(j).data.setYunits(bs(j).data.yunits.*fobjs_copy(1).ounits./fobjs_copy(1).iunits); bs(j).data.yunits.simplify; end end % End filter type elseif isa(bs(j).data, 'fsdata') %------------------------------------------------------------------------ %---------------------- Frequency-series filter --------------------- %------------------------------------------------------------------------ utils.helper.msg(msg.PROC1, 'filtering with %s filter', upper(class(fobjs_copy))); % apply filter if numel(fobjs_copy)==1 bs(j) = bs(j).*resp(fobjs_copy, plist('f', bs(j).x)); else bank = find(pl, 'bank'); iu = fobjs_copy(1).iunits; ou = fobjs_copy(1).ounits; switch lower(bank) case 'parallel' sfr = resp(fobjs_copy, plist('f', bs(j).x)); fr = sfr(1); for jj = 2:numel(fobjs_copy) if iu ~= fobjs_copy(jj).iunits error('### Input units of each filter must match for a parallel filter bank.'); end if ou ~= fobjs_copy(jj).ounits error('### Output units of each filter must match for a parallel filter bank.'); end fr = fr + sfr(jj); end bs(j) = bs(j).*fr; case 'serial' sfr = resp(fobjs_copy, plist('f', bs(j).x)); fr = sfr(1); for jj = 2:numel(fobjs_copy) fr = fr.*sfr(jj); end bs(j) = bs(j).*fr; end end else error('### unknown data type.'); end % name for this object bs(j).name = sprintf('%s(%s)', fobjs_copy.name, ao_invars{j}); % Collect the filters into procinfo bs(j).procinfo = plist('filter', fobjs_copy); % add history bs(j).addHistory(getInfo('None'), pl, ao_invars(j), [inhist fobjs_copy(:).hist]); end % Set outputs if nargout == 1 varargout{1} = bs; elseif nargout == 2 varargout{1} = bs; varargout{2} = fobjs_copy; 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: filter.m,v 1.86 2011/04/08 08:56:14 hewitson 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 p = param({'filter', 'The filter(s) to apply to the data.'}, paramValue.EMPTY_STRING); pl.append(p); % GDoff p = param({'GDOFF', 'Switch off correction for group delay.'}, paramValue.YES_NO); p.val.setValIndex(2); pl.append(p); % Bank p = param({'bank', 'Specify what type of filter bank is being applied.'}, {1, {'parallel', 'serial'}, paramValue.SINGLE}); pl.append(p); % Initialize p = param({'initialize', 'Initialize the filter to avoid startup transients.'}, {1, {false, true}, paramValue.SINGLE}); pl.append(p); end % PARAMETERS: filter - the filter object to use to filter the data % bank - For IIR filtering, specify if the bank of filters % is intended to be 'serial' or 'parallel' [default] % initialize - true or false if you want the filter being % automatically initialized or not.