ltpda: m-toolbox/classes/@ao/filter.m comparison

comparison m-toolbox/classes/@ao/filter.m @ 0:f0afece42f48

Import.

author	Daniele Nicolodi <nicolodi@science.unitn.it>
date	Wed, 23 Nov 2011 19:22:13 +0100
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+:f0afece42f48
+% 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.

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comparison m-toolbox/classes/@ao/filter.m @ 0:f0afece42f48