## Copyright (C) 2003 Joerg Huber ## ## This program is free software; you can redistribute it and/or modify ## it under the terms of the GNU General Public License as published by ## the Free Software Foundation; either version 2 of the License, or ## (at your option) any later version. ## ## This program is distributed in the hope that it will be useful, ## but WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ## GNU General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with this program; If not, see <http://www.gnu.org/licenses/>. ## -*- texinfo -*- ## @deftypefn {Function File} {irsa_isregular.m} ## [@var{regular},@var{Tm}] = irsa_isregular (@var{xp}) ## ## Check if the sampling points @var{xp} are regular sampled and compute ## the mean sampling period ## ## Input: ## ## @var{xp} : Columnvector -- sampling points ## ## Output: ## ## @var{regular}: Boolean -- true if the sampling is regular (equidistant) ## ## @var{Tm} : Scalar -- Mean sampling period ## @end deftypefn ## TODO: After some tests it showed up, that the multiplication by N ## seems to be necessary if regular timeseries shouldn't be identified ## as irregular ones occasionaly. Why? May have something to do with ## 'diff'. function [regular, Tm] = irsa_isregular (xp) if( nargin != 1 || isempty( xp ) ) usage( "[regular, Tm] = irsa_isregular (xp)" ); endif ## Compute mean spacing between sampling points N = length( xp ); Tm = (xp(N) - xp(1)) / (N - 1); ## Regular time series? Compare every spacing with the mean spacing if( all( diff(xp) .- Tm < eps*Tm*N ) ) regular = true; else regular = false; endif endfunction ### Local Variables: ### mode: octave ### End:

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