Mercurial > hg > ltpda
view m-toolbox/classes/@ao/eqmotion.m @ 14:6d43f39633b8 database-connection-manager
Remove unused functions from utils.jmysql
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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% EQMOTION solves numerically a given linear equation of motion %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: EQMOTION solves numerically a given linear equation % of motion: % d^2 x dx % F(t) = alpha2 ------- + alpha1 ------ + alpha0 (x-x0) % dt^2 dt % % CALL: eqmotion(a) % b = eqmotion(a,pl) % % INPUTS: a - analysis object(s) containing data as a function of % time. % pl - parameter list containing input parameters. % % OUTPUTS: b - analysis object(s) containing output data as a function % of time. % % <a href="matlab:utils.helper.displayMethodInfo('ao', 'eqmotion')">Parameters Description</a> % % NOTE: Derivative estimation is performed with the parabolic fit % approximation by default [1, 2]. Try to change D#COEFF to use another % method. D0COEFF is used to calculate a five point data smoother to be % applied to the third term at the second member of the equation above. If % you do not whant to smooth data (before the multiplication with alpha0) % you have to input NaN for D0COEFF. % See also help for ao/diff and utils.math.fpsder. % % REFERENCES: % [1] L. Ferraioli, M. Hueller and S. Vitale, Discrete derivative % estimation in LISA Pathfinder data reduction, Class. Quantum Grav., % 7th LISA Symposium special issue. % [2] L. Ferraioli, M. Hueller and S. Vitale, Discrete derivative % estimation in LISA Pathfinder data reduction % http://arxiv.org/abs/0903.0324v1 % % VERSION: $Id: eqmotion.m,v 1.13 2011/04/11 10:24:45 mauro Exp $ % % SEE ALSO: ao/diff, utils.math.fpsder % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = eqmotion(varargin) % Check if the method was called by another method callerIsMethod = utils.helper.callerIsMethod; %%% Check if this is a call for parameters if utils.helper.isinfocall(varargin{:}) varargout{1} = getInfo(varargin{3}); return end %%% Collect input variable names in_names = cell(size(varargin)); for ii = 1:nargin,in_names{ii} = inputname(ii);end %%% Collect all AOs [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names); pli = utils.helper.collect_objects(varargin(:), 'plist', in_names); %%% Decide on a deep copy or a modify %%% REMARK: If you create a new AO (call the constructor) then %%% it is not necessay to copy the input-AOs !!!!!!!!!!!!!!!!!!!!!!!!! bs = copy(as, nargout); %%% Combine plists pl = combine(pli, getDefaultPlist); %%% Get Parameters alpha0 = find(pl,'ALPHA0'); alpha1 = find(pl,'ALPHA1'); alpha2 = find(pl,'ALPHA2'); X0 = find(pl,'X0'); d0c = find(pl,'D0COEFF'); d1c = find(pl,'D1COEFF'); d2c = find(pl,'D2COEFF'); tunits = find(pl,'TARGETUNITS'); % check if the params are AOs if ~isa(tunits,'unit') tunits = unit(tunits); end if ~isa(alpha0,'ao') alpha0 = cdata(alpha0); alpha0.setYunits(tunits./unit(as.yunits)); alpha0 = ao(alpha0); alpha0.simplifyYunits; end if ~isa(alpha1,'ao') alpha1 = cdata(alpha1); alpha1.setYunits(tunits.*unit('s')./unit(as.yunits)); alpha1 = ao(alpha1); alpha1.simplifyYunits; end if ~isa(alpha2,'ao') alpha2 = cdata(alpha2); alpha2.setYunits(tunits.*(unit('s').^2)./unit(as.yunits)); alpha2 = ao(alpha2); alpha2.simplifyYunits; end if ~isa(X0,'ao') if isempty(X0) X0 = cdata(0); X0.setYunits(as.yunits); X0 = ao(X0); else X0 = cdata(X0); X0.setYunits(as.yunits); X0 = ao(X0); end end if isa(d0c,'ao') d0c = d0c.data.y; end if isa(d1c,'ao') d1c = d1c.data.y; end if isa(d2c,'ao') d2c = d2c.data.y; end %%% go through analysis objects for kk = 1:numel(bs) %%% Calculate derivatives if ~isnan(d0c) % do the smoothing a0 = diff(bs(kk),plist('method', 'FPS', 'ORDER', 'ZERO', 'COEFF', d0c)); else a0 = copy(bs(kk),1); % just use input data as they are end a1 = diff(bs(kk),plist('method', 'FPS', 'ORDER', 'FIRST', 'COEFF', d1c)); a2 = diff(bs(kk),plist('method', 'FPS', 'ORDER', 'SECOND', 'COEFF', d2c)); %%% Calculate Force b0 = (a0 - X0); b0 = b0*alpha0; b1 = a1*alpha1; b2 = a2*alpha2; bs(kk) = b2 + b1 + b0; % simplify units bs(kk).simplifyYunits(plist('prefixes', false)); %%% Set Name bs(kk).name = sprintf('eqmotion(%s)', ao_invars{kk}); if ~callerIsMethod %%% Set Name bs(kk).name = sprintf('eqmotion(%s)', ao_invars{kk}); %%% Add History bs(kk).addHistory(getInfo('None'), pl, ao_invars(kk), [as.hist(kk)]); end end %%% Output if nargout == numel(bs) % List of outputs for ii = 1:numel(bs) varargout{ii} = bs(ii); end else % Single output varargout{1} = bs; end end %-------------------------------------------------------------------------- % Get Info Object %-------------------------------------------------------------------------- function ii = getInfo(varargin) if nargin == 1 && strcmpi(varargin{1}, 'None') sets = {}; pl = []; else sets = {'Default'}; pl = getDefaultPlist; end % Build info object ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: eqmotion.m,v 1.13 2011/04/11 10:24:45 mauro Exp $', sets, pl); 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(); % ALPHA0 p = param({'ALPHA0','Zero order coefficient. Input a cdata ao with the proper units or a number.'}, ... {1, {0}, paramValue.OPTIONAL}); pl.append(p); % ALPHA1 p = param({'ALPHA1','First order coefficient. Input a cdata ao with the proper units or a number.'},... {1, {0}, paramValue.OPTIONAL}); pl.append(p); % ALPHA2 p = param({'ALPHA2','Second order coefficient. Input a cdata ao with the proper units or a number.'}, ... {1, {0}, paramValue.OPTIONAL}); pl.append(p); % X0 p = param({'X0','Data offset. Input a cdata ao with the proper units or a number.'}, ... {1, {0}, paramValue.OPTIONAL}); pl.append(p); % D0COEFF p = param({'D0COEFF','Data smoother coefficient.'}, ... {1, {-3/35}, paramValue.OPTIONAL}); pl.append(p); % D1COEFF p = param({'D1COEFF','First derivative coefficient.'}, ... {1, {-1/5}, paramValue.OPTIONAL}); pl.append(p); % D2COEFF p = param({'D2COEFF','Second derivative coefficient.'}, ... {1, {2/7}, paramValue.OPTIONAL}); pl.append(p); % Target units p = param({'TARGETUNITS','Set this parameter if you input just numbers for the ALPHA# coefficients.'}, ... {1, {'N'}, paramValue.OPTIONAL}); pl.append(p); end % END