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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
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function pl_out = process_spectral_options(pl, type, varargin) % PROCESS_SPECTRAL_OPTIONS checks the options for the parameters needed % by spectral estimators, recalculating and/or resetting them if needed. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: PROCESS_SPECTRAL_OPTIONS checks the options for: % - olap % - order % - win % - psll % - navs (for linear frequency scaled estimators) % - nfft (for linear frequency scaled estimators) % - kdes (for logarithmic frequency scaled estimators) % - jdes (for logarithmic frequency scaled estimators) % - lmin (for logarithmic frequency scaled estimators) % % CALL: pl = process_spectral_options(pl, type, varargin) % % INPUTS: % pl - the parameter list to scan % type - the type of estimator. Choose between: % 'welch' (or 'lin') for linear frequency scaled % 'lpsd' (or 'log') for logarithmic frequency scaled % Optionals: % obj_len - the length of the object (the shortest in case of x-spec) % obj_fs - the sampling frequency of the object (the highest in case of x-spec) % % % OUTPUTS: pl_out - the revised plist % % VERSION: $Id: process_spectral_options.m,v 1.11 2011/05/23 20:40:46 mauro Exp $ % % HISTORY: 20-08-2009 M Hueller % Creation % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Necessary for debug messages import utils.const.* LIN = 'lin'; LOG = 'log'; pl_out = copy(pl, true); switch length(varargin) case 0 if strcmpi(type, LIN) error('### please provide the object length!'); end case 1 obj_len = varargin{1}; otherwise obj_len = varargin{1}; fs = varargin{2}; end % Check the type of estimator switch lower(type) case {'welch', 'lin', 'linear'} type = LIN; case {'lpsd', 'log', 'logarithmic'} type = LOG; otherwise error(['### Unsupported estimator type ' type]); end if strcmpi(type, LIN) % Check the number of points in FFT. If this is not set (<0) we set it % to be the length of the input data. Nfft = find(pl, 'Nfft'); if isempty(Nfft) Nfft = -1; end setWindow = 0; if ischar(Nfft) nNfft = floor(eval(Nfft)); utils.helper.msg(msg.PROC1, 'setting Nfft to %s = %d', Nfft, nNfft); Nfft = nNfft; end if Nfft <= 0 Nfft = obj_len; utils.helper.msg(msg.PROC1, 'using default Nfft of %g', Nfft); setWindow = 1; end pl_out.pset('Nfft', Nfft); end % Check the window function. Win = find(pl, 'Win'); psll = find(pl, 'psll'); levelcoeff = find(pl, 'level'); if isempty(Win) Win = 'Rectangular'; utils.helper.msg(msg.PROC1, 'using no window (Rectangular)'); end if isempty(psll) psll = 0; utils.helper.msg(msg.PROC1, 'setting psll level to 0'); end if ischar(psll) npsll = floor(eval(psll)); utils.helper.msg(msg.PROC1, 'setting psll to %s = %d', psll, npsll); psll = npsll; end if ischar(Win) % We always want to work with a specwin switch lower(Win) case 'kaiser' Win = specwin(Win, 0, psll); case 'levelledhanning' Win = specwin(Win, 0, levelcoeff); otherwise Win = specwin(Win, 0); end end if strcmpi(type, LIN) % If the length of the window doesn't match NFFT then we resize it. if setWindow || Win.len ~= Nfft Win.len = Nfft; utils.helper.msg(msg.PROC1, 'reset window to %s(%d)', strrep(Win.type, '_', '\_'), Win.len); end else % For log-spaced estimators, let's always reset to a 0-point window Win.len = 0; utils.helper.msg(msg.PROC1, 'reset window to %s(%d)', strrep(Win.type, '_', '\_'), Win.len); end pl_out.pset('Win', Win); pl_out.pset('psll', psll); % Check the overlap. If this is not set, we take the overlap from that % recommended by the window function. Olap = find(pl, 'Olap'); if isempty(Olap) || Olap < 0 Olap = Win.rov; utils.helper.msg(msg.PROC1, 'using default overlap of %2.1f%%', Olap); end pl_out.pset('Olap', Olap); if strcmpi(type, LIN) % Check if the user is asking for a given number of averages % If so, the Nfft and the win values are reset based on the % calculated value: navs = find(pl, 'navs'); if ~isempty(navs) && navs > 1 && setWindow % Compute the number of segments M = obj_len; overlap = Olap/100; L = round(M/(navs*(1-overlap) + overlap)); utils.helper.msg(msg.PROC1, 'Asked for navs = %d', navs); % Checks it will really obtain the correct answer. % This is needed to cope with the need to work with integers while fix((M-round(L*overlap))/(L-round(L*overlap))) < navs L = L - 1; end navs_actual = fix((M-round(L*overlap))/(L-round(L*overlap))); utils.helper.msg(msg.PROC1, 'Expect to get navs_actual = %d', navs_actual); if L > 0 % Reset Nfft Nfft = L; pl_out.pset('Nfft', Nfft); % Reset window Win.len = Nfft; pl_out.pset('Win', Win); pl_out.pset('navs', fix(navs_actual)); utils.helper.msg(msg.PROC1, 'reset navs to %d', fix(navs_actual)); end end end % desired detrending order order = pl.find('Order'); if isempty(order) order = 0; utils.helper.msg(msg.PROC1, 'using default detrending order 0 (mean)'); end if ischar(order) norder = floor(eval(order)); utils.helper.msg(msg.PROC1, 'setting detrending order to %s = %d', order, norder); order = norder; end pl_out.pset('Order', order); if strcmpi(type, LOG) % Desired number of averages Kdes = find(pl, 'Kdes'); if isempty(Kdes) Kdes = 100; utils.helper.msg(msg.PROC1, 'using default Kdes value 100'); end if ischar(Kdes) nKdes = floor(eval(Kdes)); utils.helper.msg(msg.PROC1, 'setting Kdes value to %s = %d', Kdes, nKdes); Kdes = nKdes; end pl_out.pset('Kdes', Kdes); % num desired spectral frequencies Jdes = find(pl, 'Jdes'); if isempty(Jdes) Jdes = 1000; utils.helper.msg(msg.PROC1, 'using default Jdes value 1000'); end if ischar(Jdes) nJdes = floor(eval(Jdes)); utils.helper.msg(msg.PROC1, 'setting Jdes value to %s = %d', Jdes, nJdes); Jdes = nJdes; end pl_out.pset('Jdes', Jdes); % Minimum segment length Lmin = find(pl, 'Lmin'); if isempty(Lmin) Lmin = 0; utils.helper.msg(msg.PROC1, 'using default Lmin value 0'); end if ischar(Lmin) nLmin = floor(eval(Lmin)); utils.helper.msg(msg.PROC1, 'setting Kdes value to %s = %d', Lmin, nLmin); Lmin = nLmin; end pl_out.pset('Lmin', Lmin); end