?? vario2dr.m
字號:
function [np, gam, hm, tm, hv, tv] = vario2dr ( nlag, nx, ny, ndir,...
ixd, iyd, vr, nvarg, ivtail, ivhead, ivtype, nvar )
%
%
% vario2dr : matlab m-file
% gam2 : fortran mex-file (corresponds to gam2 in GSLIB)
% gam2g : fortran gateway function
%
% Variogram of Data on a 2-D regular Grid
% ***************************************
%
% This subroutine computes any of eight different measures of spatial
% continuity for regular spaced 2-D data. Missing values are allowed
% and the grid need not be square. From the GSLIB library.; see
%
% Deutsch, C.V. and A.G. Journel (1992).
% GSLIB: Geostatistical Software Library and User's Guide.
% Oxford University Press, Oxford, 340 p.
%
%
%
% INPUT VARIABLES:
%
% nlag Number of lags to calculate
% nx Number of units in x
% ny Number of units in y
% ndir Number of directions to consider
% ixd(ndir) X indicator of direction - number of X grid columns
% that must be shifted to move from a node on the
% grid to the next nearest node on the grid which
% lies on the directional vector.
% iyd(ndir) Y indicator of direction - similar to ixd, number
% of grid lines that must be shifted to nearest
% node which lies on the directional vector
% nv The number of variables
% vr(nx,ny,nv) Three dimensional array of data in GSLIB. There
% are no 3-D matrices in MATLAB ==> we fool both
% Matlab and Fortran by "stacking" nv 2-array.
% tmin,tmax Trimming limits
% nvarg Number of variograms to compute
% ivtail(nvarg) Variable for the tail of each variogram
% ivhead(nvarg) Variable for the head of each variogram
% ivtype(nvarg) Type of variogram to compute:
% 1. semivariogram
% 2. cross-semivariogram
% 3. covariance
% 4. correlogram
% 5. general relative semivariogram
% 6. pairwise relative semivariogram
% 7. semivariogram of logarithms
% 8. rodogram
% 9. madogram
% 10. indicator semivariogram: an indicator variable
% is constructed in the main program.
% nvar Number of variables
%
% OUTPUT VARIABLES:
%
% np() Number of pairs
% gam() semivariogram, covariance, correlogram,... value
% hm() Mean of the tail data
% tm() Mean of the head data
% hv() Variance of the tail data
% tv() Variance of the head data
%
% INPUT VARIABLES
tmin = -1e021;
tmax = +1e021;
% VARIOGRAMME
[np,gam,hm,tm,hv,tv] =...
gam2 (nlag,nx,ny,ndir,ixd,iyd,vr,tmin,tmax,...
nvarg,ivtail,ivhead,ivtype,nvar);
% OUTPUT VARIABLES
[np, gam, hm, tm, hv, tv] = outvario(nlag,0,ndir,nvarg,np,gam,hm,tm,hv,tv,ivtype);
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