| | \n\n \n \n \n bool adj=n [y/n] | \tadjoint flag (for what=linear) \n | \n \n\n \n \n \n float eps=0. | \tregularization parameter \n | \n \n\n \n \n \n string gradient= | \tauxiliary output file name \n | \n \n\n \n \n \n bool l1norm=n [y/n] | \tnorm for minimization (default L2 norm) \n | \n \n\n \n \n \n string misnorm= | \tauxiliary output file name \n | \n \n\n \n \n \n int nfreq=1 | \tl1-norm weighting nfreq \n | \n \n\n \n \n \n int niter=10 | \tnumber of slowness inversion iterations \n | \n \n\n \n \n \n int nmem=1 | \tl1-norm weighting nmem \n | \n \n\n \n \n \n int order=2 | \tfast marching accuracy order \n | \n \n\n \n \n \n float perc=90. | \t \n | \n \n\n \n \n \n string receiver= | \tauxiliary input file name \n | \n \n\n \n \n \n string record= | \tauxiliary input file name \n | \n \n\n \n \n \n string shot= | \tauxiliary input file name \n | \n \n\n \n \n \n int stiter=200 | \tnumber of step iterations \n | \n \n\n \n \n \n string time= | \tauxiliary input file name \n | \n \n\n \n \n \n string topo= | \tauxiliary input file name \n | \n \n\n \n \n \n bool velocity=y [y/n] | \tif y, the input is velocity; n, slowness squared \n | \n \n\n \n \n \n bool verb=n [y/n] | \tverbosity flag \n | \n \n\n \n \n \n string what= | \twhat to compute (default tomography) \n | \n \n |