% Note:  the order of the parameters in important
% Problem dimension comes 1st
3d_scalar ola
% 
% output base directory 2nd
./Examples/testdata/testOutput/3d/ola
! base directory for Kernel files
./Examples/testdata/input/3d
! base directory for Map files (input data files)
./Examples/testdata/input/3d
!input Kernel file (Kern1.fits) Map1.fits (input data file, e.g. d.fits)
kernel1.fits map1.fits
kernel2.fits map2.fits
kernel3.fits map3.fits
kernel4.fits map4.fits
kernel5.fits map5.fits
kernel6.fits map6.fits
kernel7.fits map7.fits
kernel8.fits map8.fits
kernel9.fits map9.fits
kernel10.fits map10.fits
kernel11.fits map11.fits
kernel12.fits map12.fits
kernel13.fits map13.fits
kernel14.fits map14.fits
kernel15.fits map15.fits
kernel16.fits map16.fits
kernel17.fits map17.fits
kernel18.fits map18.fits
kernel19.fits map19.fits
kernel20.fits map20.fits
kernel21.fits map21.fits
kernel22.fits map22.fits
kernel23.fits map23.fits
kernel24.fits map24.fits
! noise covariance matrix; must be NxNxMxM, N = 160, M = 1 = # of kernel-map pairs 
./Examples/testdata/input/3d/C24.fits
!input Regularization matrix file (R.fits)  Theta matrix in OLA
./Examples/testdata/input/3d/R.fits
! For OLA inversions, all averaging kernels are calculated 
! MuMin MuMax NMu SigmaMin SigmaMax NSigma
0.0 0.5 2 			5 10 2
! for target function, Fi
./Examples/testdata/input/3d/f.fits

