MultivariateFNormalSufficientSparse::MultivariateFNormalSufficientSparse(
const VectorXd& Fbar, double JF, const VectorXd& FM, int Nobs,
const SparseMatrix<double>& W, const SparseMatrix<double>& Sigma,
cholmod_common *c)
: Object("Multivariate Normal distribution %1%")
{
c_ = c;
W_=nullptr;
Sigma_=nullptr;
P_=nullptr;
PW_=nullptr;
epsilon_=nullptr;
L_=nullptr;
N_=Nobs;
M_=Fbar.rows();
IMP_LOG(TERSE, "MVNsparse: sufficient statistics init with N=" << N_
<< " and M=" << M_ << std::endl);
IMP_USAGE_CHECK( N_ > 0,
"please provide at least one observation per dimension");
IMP_USAGE_CHECK( M_ > 0,
"please provide at least one variable");
FM_=FM;
set_Fbar(Fbar); //also computes epsilon
set_W(W);
set_JF(JF);
set_Sigma(Sigma);
}
MultivariateFNormalSufficient::MultivariateFNormalSufficient(
const VectorXd& Fbar, double JF, const VectorXd& FM, int Nobs,
const MatrixXd& W, const MatrixXd& Sigma, double factor)
{
reset_flags();
N_=Nobs;
M_=Fbar.rows();
LOG( "MVN: sufficient statistics init with N=" << N_
<< " and M=" << M_ << std::endl);
CHECK( N_ > 0,
"please provide at least one observation per dimension");
CHECK( M_ > 0,
"please provide at least one variable");
set_factor(factor);
set_FM(FM);
set_Fbar(Fbar);
set_W(W);
set_jacobian(JF);
set_Sigma(Sigma);
}
MultivariateFNormalSufficient::MultivariateFNormalSufficient(
const VectorXd& Fbar, double JF, const VectorXd& FM, int Nobs,
const MatrixXd& W, const MatrixXd& Sigma, double factor)
: base::Object("Multivariate Normal distribution %1%")
{
reset_flags();
N_=Nobs;
M_=Fbar.rows();
IMP_LOG_TERSE( "MVN: sufficient statistics init with N=" << N_
<< " and M=" << M_ << std::endl);
IMP_USAGE_CHECK( N_ > 0,
"please provide at least one observation per dimension");
IMP_USAGE_CHECK( M_ > 0,
"please provide at least one variable");
set_factor(factor);
set_FM(FM);
set_Fbar(Fbar);
set_W(W);
set_jacobian(JF);
set_Sigma(Sigma);
use_cg_=false;
}
