FILTFILT overides the filtfilt function for analysis objects. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% DESCRIPTION: FILTFILT overides 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. PARAMETERS: filter - the filter object to use to filter the data REMARK: Uses ltpda_filtfilt() to do the filtering. VERSION: $Id: filtfilt.m,v 1.8 2007/06/22 10:19:57 ingo Exp $ The following call returns a parameter list object that contains the default parameter values: >> pl = filtfilt(ao, 'Params') HISTORY: 11-02-07 M Hewitson Creation %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0001 function varargout = filtfilt(a, pl) 0002 % FILTFILT overides the filtfilt function for analysis objects. 0003 % 0004 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0005 % 0006 % DESCRIPTION: FILTFILT overides the filtfilt function for analysis objects. 0007 % Applies the input digital IIR filter to the input analysis object 0008 % forwards and backwards. If the input analysis object contains a 0009 % time-series (tsdata) then the filter is applied using the normal 0010 % recursion algorithm. The output analysis object contains a tsdata 0011 % object. 0012 % 0013 % If the input analysis object contains a frequency-series (fsdata) 0014 % then the response of the filter is computed and then multiplied 0015 % with the input frequency series. The output analysis object 0016 % contains a frequency series. 0017 % 0018 % CALL: >> [b, filt] = filtfilt(a,pl) 0019 % >> b = filtfilt(a,pl) 0020 % 0021 % INPUTS: pl - a parameter list 0022 % a - input analysis object 0023 % 0024 % OUTPUTS: filt - a copy of the input filter object with the 0025 % history values filled in. 0026 % b - output analysis object containing the filtered data. 0027 % 0028 % PARAMETERS: filter - the filter object to use to filter the data 0029 % 0030 % REMARK: Uses ltpda_filtfilt() to do the filtering. 0031 % 0032 % VERSION: $Id: filtfilt.m,v 1.8 2007/06/22 10:19:57 ingo Exp $ 0033 % 0034 % The following call returns a parameter list object that contains the 0035 % default parameter values: 0036 % 0037 % >> pl = filtfilt(ao, 'Params') 0038 % 0039 % HISTORY: 11-02-07 M Hewitson 0040 % Creation 0041 % 0042 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0043 0044 %% Check if this is a call for parameters 0045 if nargin == 2 0046 if isa(a, 'ao') && ischar(pl) 0047 in = char(pl); 0048 if strcmp(in, 'Params') 0049 varargout{1} = getDefaultPL(); 0050 return 0051 end 0052 end 0053 end 0054 0055 %% capture input variable names 0056 invars = {}; 0057 for j=1:nargin 0058 invars = [invars cellstr(inputname(j))]; 0059 end 0060 0061 ALGONAME = mfilename; 0062 VERSION = '$Id: filtfilt.m,v 1.8 2007/06/22 10:19:57 ingo Exp $'; 0063 0064 filt = find(pl, 'filter'); 0065 0066 % Initialise output 0067 bs = []; 0068 0069 % check inputs 0070 if ~isa(filt, 'miir') 0071 error('### the first input should be an miir object.'); 0072 end 0073 if ~isa(a, 'ao') 0074 error('### second input should be an analysis object.'); 0075 end 0076 0077 % get input data 0078 d = a.data; 0079 0080 %--------- Time-series filter 0081 % 0082 if isa(d, 'tsdata') 0083 0084 % get input data 0085 x = d.x; 0086 fs = d.fs; 0087 if fs ~= get(filt, 'fs') 0088 warning('!!! Filter is designed for a different sample rate of data.'); 0089 % Adjust/redesign if this is a standard filter 0090 filt = redesign(filt, fs); 0091 end 0092 0093 % get filter coeffs 0094 ac = get(filt,'a'); 0095 bc = get(filt,'b'); 0096 0097 % apply filter 0098 y = filtfilt(ac, bc, x); 0099 % [fstruct, y] = ltpda_filtfilt(struct(filt), d.x, length(d.x)); 0100 % consolodate this structure with miir class before converting. 0101 % filt = set(filt, 'histin', fstruct.histin); 0102 % filt = set(filt, 'histout', fstruct.histout); 0103 0104 %----- Create output analysis object 0105 % make a new tsdata object 0106 ts = tsdata(d.t, y); 0107 ts = set(ts, 'name', sprintf('filtfilt %s with %s', d.name, get(filt,'name'))); 0108 ts = set(ts, 'xunits', d.xunits); 0109 ts = set(ts, 'yunits', d.yunits); 0110 ts = set(ts, 't0', d.t0); 0111 0112 % make a new history object 0113 pl = plist(); 0114 pl = append(pl, param('filter', filt)); 0115 h = history(ALGONAME, VERSION, pl, a.hist); 0116 h = set(h, 'invars', invars); 0117 0118 % make output analysis object 0119 bs = ao(ts, h); 0120 % name for this object 0121 if isempty(invars{1}) 0122 n1 = a.name; 0123 else 0124 n1 = invars{1}; 0125 end 0126 bs = set(bs, 'name', sprintf('%s(%s)', get(filt,'name'), n1)); 0127 0128 if nargout == 1 0129 varargout{1} = bs; 0130 elseif nargout == 2 0131 varargout{1} = bs; 0132 varargout{2} = filt; 0133 else 0134 error('### wrong number of output arguments.'); 0135 end 0136 0137 0138 %--------- Frequency-series filter 0139 % 0140 elseif isa(d, 'fsdata') 0141 error('### I don''t work yet. Please code me up.'); 0142 0143 else 0144 error('### unknown data type.'); 0145 end 0146 0147 %% Get default params 0148 function pl_default = getDefaultPL() 0149 0150 disp('* creating default plist...'); 0151 pl_default = plist(param('filter', '')); 0152 disp('* done.');