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PIVMat 3.02

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PIVMat 3.02



27 Apr 2006 (Updated )

A PIV Post-processing and data analysis toolbox

corrf (PIVMat Toolbox)
corrf (PIVMat Toolbox)
PIVMat Function Reference<< Prev | Next >> 
Spatial correlation function of a scalar field

COR = corrf(F, DIM) returns the correlation function of the scalar 
field F along the dimension DIM (with DIM=1, 2, or 'x','y', for 
correlation along the 'X' or 'Y' direction). If F is an array of 
scalar fields, COR returns the average of the correlation functions of 
each field. COR also contains various integral scales computed from the 
correlation function (see below). 
COR is a structure which contains the following fields: 
  r:       separation length 
  f:       correlation function 
  unitr:   unit of separation length 
  unitf:   unit of correlation function 
  namef:   name of correlation function 
  isinf:   integral scale, computed as the integral of f up to infty 
  r5:      scale at which f(r5)=0.5 (linearly interpolated) 
  is5:     integral scale, computed as the integral of f from 0 to r5 
  r2, is2, r1, is1, r0, is0 :  idem as r5, is5, for crossovers 
           at 0.2, 0.1 and 0 respectively 
COR = corrf(F, DIM, 'norm') normalizes the correlation function, so 
that f = 1 at r = 0. 
For a vector field V, corrf(vec2scal(V,'ux'),'x') and 
corrf(vec2scal(V,'uy'),'y') are the longitudinal correlation functions, 
and corrf(vec2scal(V,'ux'),'y') and corrf(vec2scal(V,'uy'),'x') are the 
transverse ones. 
Note that the convergence of the correlation function is not garanteed, 
especially at large separations r, for which very few data points are 
available to compute the correlation. 
If the crossover scales are not defined (i.e. if the correlation 
function does not decrease enough for large r), NaNs (not a number) 
are returned, and a warning is issued. Use corrf(...,'nowarning') to 
ignore these warnings. 
COR = corrf(..., 'verbose') also displays the computation in progress. 
If no output argument, the correlation function is plotted. 
   v = loadvec('B00001.VEC'); 
   cor = corrf(vec2scal(v,'vx'),'x'); 
   plot(cor.r, cor.f, 'o-'); 
See Also
vec2scal, tempcorrf, statf, histf, vsf, specf. 
Published output in the Help browser 
   showdemo corrf 

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