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/dports/science/qmcpack/qmcpack-3.11.0/labs/lab2_qmc_basics/oxygen_dimer/reference/
H A Ddimer_fit.py16 nfit = 2 variable
23 nfit = int(args[1]) variable
/dports/science/qmcpack/qmcpack-3.11.0/labs/lab2_qmc_basics/oxygen_dimer/
H A Ddimer_fit.py16 nfit = 2 variable
23 nfit = int(args[1]) variable
/dports/lang/yorick/yorick-y_2_2_04/i/
H A Drcheby.i160 func rcheby_build(nfit, dfit) in rcheby_build() argument
/dports/devel/R-cran-glmnet/glmnet/R/
H A Dpredict.fishnet.R3 nfit=NextMethod("predict") functionVar
H A Dpredict.lognet.R7 nfit=NextMethod("predict") functionVar
H A Dpredict.coxnet.R27 nfit=as.matrix(newx%*%nbeta) functionVar
H A Dpredict.glmnet.R31 nfit=as.matrix(cbind2(1,newx)%*%nbeta) functionVar
/dports/science/nwchem/nwchem-7b21660b82ebd85ef659f6fba7e1e73433b0bd0a/src/nwdft/coulomb/
H A Ddft_fitcd.F1 Subroutine dft_fitcd(nfit,CD_coef, i3c_ERI, Ecoul1, argument
/dports/science/nwchem-data/nwchem-7.0.2-release/src/nwdft/coulomb/
H A Ddft_fitcd.F1 Subroutine dft_fitcd(nfit,CD_coef, i3c_ERI, Ecoul1, argument
/dports/science/afni/afni-AFNI_21.3.16/src/
H A Dplug_deconvolve.c967 int * nfit, /* number of fit parameters */ in calculate_results()
1200 int nfit; /* number of fit parameters */ in DC_Fit() local
1245 int nfit; /* number of fit parameters */ in DC_Err() local
1286 int nfit; /* number of fit parameters */ in DC_IRF() local
H A Dpfit.c78 void pfit( int nz , complex * z , int nfit , float * psi[] , float * fit ) in pfit()
H A Dmri_stats.c79 double correl_p2t( double pp , double nsam , double nfit , double nort ) in correl_p2t()
94 double correl_t2p( double rho , double nsam , double nfit , double nort ) in correl_t2p()
111 double correl_t2z( double rho , double nsam , double nfit , double nort ) in correl_t2z()
H A D3dfim+.c1371 int nfit, in attach_sub_brick()
1447 int nfit; in write_bucket_data() local
/dports/audio/libbpm/libbpm-0.3/bpmprocess/
H A Dfit_fft.c154 int i, nfit, n1, n2; in fit_fft() local
/dports/science/gromacs/gromacs-2021.4/src/gromacs/correlationfunctions/
H A Dgmx_lmcurve.cpp106 bool lmfit_exp(int nfit, in lmfit_exp()
/dports/science/py-gpaw/gpaw-21.6.0/gpaw/
H A Dunfold.py368 weights_mK=None, color='red', fit=True, nfit=200): argument
/dports/biology/bcftools/bcftools-1.14/
H A Dpeakfit.c151 int i, nfit = 0; in peakfit_add_bounded_gaussian() local
241 int i, nfit = 0; in peakfit_add_gaussian() local
321 int i, nfit = 0; in peakfit_add_exp() local
/dports/biology/bio-mocha/bcftools-1.14/
H A Dpeakfit.c151 int i, nfit = 0; in peakfit_add_bounded_gaussian() local
241 int i, nfit = 0; in peakfit_add_gaussian() local
321 int i, nfit = 0; in peakfit_add_exp() local
/dports/science/gromacs/gromacs-2021.4/src/gromacs/gmxana/
H A Dgmx_covar.cpp172 int d, dj, nfit; in gmx_covar() local
H A Dgmx_make_edi.cpp588 int nfit, in get_structure()
890 int nfit; /* Number of atoms in the reference/fit structure */ in gmx_make_edi() local
H A Dgmx_anaeig.cpp485 int nfit, in project()
1084 int nout, *iout, noutvec, *outvec, nfit; in gmx_anaeig() local
/dports/science/quantum-espresso/q-e-qe-6.7.0/PP/src/
H A Dplotband.f90730 SUBROUTINE splint (nspline, xspline, yspline, d2y, nfit, xfit, yfit) argument
734 INTEGER, INTENT(in) :: nspline, nfit local
/dports/science/nwchem-data/nwchem-7.0.2-release/src/optim/neb/
H A Dneb_utils.F1308 subroutine neb_impose(nion,rion1,rion2,nfit,ifit,wfit,rms1,rms2) argument
1312 integer nfit,ifit(2,*) local
1500 subroutine neb_quatfit(nion,rion1,rion2,nfit,ifit,wfit) argument
1504 integer nfit local
/dports/science/nwchem/nwchem-7b21660b82ebd85ef659f6fba7e1e73433b0bd0a/src/optim/neb/
H A Dneb_utils.F794 integer i,geom,geomlen,movecslen,nion,nfit,i2,i3,pathguess local
1504 subroutine neb_impose(nion,rion1,rion2,nfit,ifit,wfit,rms1,rms2) argument
1508 integer nfit,ifit(2,*) local
1568 integer nfit,ifit(2,*) local
1609 > nfit,ifit,wfit, argument
1614 integer nfit,ifit(2,*) local
1696 subroutine neb_quatfit(nion,rion1,rion2,nfit,ifit,wfit) argument
1700 integer nfit local
1797 integer nfit,ifit(2,*) local
/dports/math/R/R-4.1.2/src/library/stats/R/
H A Dfactanal.R124 nfit <- factanal.fit.mle(cv, factors, start[, i], functionVar

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