Added the use of boost::any

This commit is contained in:
babrodtk 2015-08-28 11:34:46 +02:00
parent 624790e7e3
commit df1d0f795d

View File

@ -24,6 +24,7 @@
#include <Eigen/Eigen>
#include <Eigen/Sparse>
#include <boost/any.hpp>
#include <opm/core/utility/platform_dependent/reenable_warnings.h>
@ -38,6 +39,9 @@ namespace Opm
class AutoDiffMatrix
{
public:
typedef std::vector<double> Diag;
typedef Eigen::SparseMatrix<double> Sparse;
AutoDiffMatrix()
: type_(Z),
rows_(0),
@ -72,7 +76,7 @@ namespace Opm
: type_(D),
rows_(d.rows()),
cols_(d.cols()),
d_(d.diagonal().array().data(), d.diagonal().array().data() + d.rows())
data_(Diag(d.diagonal().array().data(), d.diagonal().array().data() + d.rows()))
{
}
@ -82,7 +86,7 @@ namespace Opm
: type_(S),
rows_(s.rows()),
cols_(s.cols()),
s_(s)
data_(s)
{
}
@ -114,8 +118,7 @@ namespace Opm
std::swap(type_, other.type_);
std::swap(rows_, other.rows_);
std::swap(cols_, other.cols_);
d_.swap(other.d_);
s_.swap(other.s_);
data_.swap(other.data_);
}
@ -258,13 +261,14 @@ namespace Opm
{
AutoDiffMatrix retval(*this);
retval.type_ = D;
retval.d_.assign(rows_, rhs);
retval.data_ = boost::any(Diag(rows_, rhs));
return retval;
}
case D:
{
AutoDiffMatrix retval(*this);
for (double& elem : retval.d_) {
Diag& d = boost::any_cast<Diag&>(retval.data_);
for (double& elem : d) {
elem *= rhs;
}
return retval;
@ -272,7 +276,8 @@ namespace Opm
case S:
{
AutoDiffMatrix retval(*this);
retval.s_ *= rhs;
Sparse& s = boost::any_cast<Sparse&>(retval.data_);
s *= rhs;
return retval;
}
default:
@ -294,13 +299,14 @@ namespace Opm
{
AutoDiffMatrix retval(*this);
retval.type_ = D;
retval.d_.assign(rows_, 1.0/rhs);
boost::any_cast<Diag&>(retval.data_).assign(rows_, 1.0/rhs);
return retval;
}
case D:
{
AutoDiffMatrix retval(*this);
for (double& elem : retval.d_) {
Diag& d = boost::any_cast<Diag&>(retval.data_);
for (double& elem : d) {
elem /= rhs;
}
return retval;
@ -308,7 +314,8 @@ namespace Opm
case S:
{
AutoDiffMatrix retval(*this);
retval.s_ /= rhs;
Sparse& s = boost::any_cast<Sparse&>(retval.data_);
s /= rhs;
return retval;
}
default:
@ -330,9 +337,15 @@ namespace Opm
case I:
return rhs;
case D:
return Eigen::Map<const Eigen::VectorXd>(d_.data(), rows_) * rhs;
{
const Diag& d = boost::any_cast<const Diag&>(data_);
return Eigen::Map<const Eigen::VectorXd>(d.data(), rows_) * rhs;
}
case S:
return s_ * rhs;
{
const Sparse& s = boost::any_cast<const Sparse&>(data_);
return s * rhs;
}
default:
OPM_THROW(std::logic_error, "Invalid AutoDiffMatrix type encountered: " << type_);
}
@ -351,7 +364,7 @@ namespace Opm
retval.type_ = D;
retval.rows_ = lhs.rows_;
retval.cols_ = rhs.cols_;
retval.d_.assign(lhs.rows_, 2.0);
retval.data_ = boost::any(Diag(lhs.rows_, 2.0));
return retval;
}
@ -361,8 +374,9 @@ namespace Opm
assert(lhs.type_ == D);
assert(rhs.type_ == I);
AutoDiffMatrix retval = lhs;
Diag& d = boost::any_cast<Diag&>(retval.data_);
for (int r = 0; r < lhs.rows_; ++r) {
retval.d_[r] += 1.0;
d[r] += 1.0;
}
return retval;
}
@ -372,8 +386,10 @@ namespace Opm
assert(lhs.type_ == D);
assert(rhs.type_ == D);
AutoDiffMatrix retval = lhs;
Diag& d_lhs = boost::any_cast<Diag&>(retval.data_);
const Diag& d_rhs = boost::any_cast<const Diag&>(rhs.data_);
for (int r = 0; r < lhs.rows_; ++r) {
retval.d_[r] += rhs.d_[r];
d_lhs[r] += d_rhs[r];
}
return retval;
}
@ -387,7 +403,8 @@ namespace Opm
retval.type_ = S;
retval.rows_ = lhs.rows_;
retval.cols_ = rhs.cols_;
retval.s_ = lhs.s_ + ident;
const Sparse& s = boost::any_cast<const Sparse&>(lhs.data_);
retval.data_ = static_cast<Sparse>(s + ident);
return retval;
}
@ -396,11 +413,12 @@ namespace Opm
assert(lhs.type_ == S);
assert(rhs.type_ == D);
AutoDiffMatrix retval;
Eigen::SparseMatrix<double> diag = spdiag(rhs.d_);
Sparse diag = spdiag(boost::any_cast<const Diag&>(rhs.data_));
retval.type_ = S;
retval.rows_ = lhs.rows_;
retval.cols_ = rhs.cols_;
retval.s_ = lhs.s_ + diag;
const Sparse& s = boost::any_cast<const Sparse&>(lhs.data_);
retval.data_ = static_cast<Sparse>(s + diag);
return retval;
}
@ -412,7 +430,9 @@ namespace Opm
retval.type_ = S;
retval.rows_ = lhs.rows_;
retval.cols_ = rhs.cols_;
retval.s_ = lhs.s_ + rhs.s_;
const Sparse& s_lhs = boost::any_cast<const Sparse&>(lhs.data_);
const Sparse& s_rhs = boost::any_cast<const Sparse&>(rhs.data_);
retval.data_ = static_cast<Sparse>(s_lhs + s_rhs);
return retval;
}
@ -428,9 +448,12 @@ namespace Opm
retval.type_ = D;
retval.rows_ = lhs.rows_;
retval.cols_ = rhs.cols_;
retval.d_.resize(lhs.rows_);
retval.data_ = boost::any(Diag(lhs.rows_));
Diag& d = boost::any_cast<Diag&>(retval.data_);
const Diag& d_lhs = boost::any_cast<const Diag&>(lhs.data_);
const Diag& d_rhs = boost::any_cast<const Diag&>(rhs.data_);
for (int r = 0; r < lhs.rows_; ++r) {
retval.d_[r] = lhs.d_[r] * rhs.d_[r];
d[r] = d_lhs[r] * d_rhs[r];
}
return retval;
}
@ -443,7 +466,11 @@ namespace Opm
retval.type_ = S;
retval.rows_ = lhs.rows_;
retval.cols_ = rhs.cols_;
fastDiagSparseProduct(lhs.d_, rhs.s_, retval.s_);
retval.data_ = boost::any(Sparse(retval.rows_, retval.cols_)); //FIXME: Superfluous?
const Diag& a = boost::any_cast<const Diag&>(lhs.data_);
const Sparse& b = boost::any_cast<const Sparse&>(rhs.data_);
Sparse& c = boost::any_cast<Sparse&>(retval.data_);
fastDiagSparseProduct(a, b, c);
return retval;
}
@ -455,7 +482,11 @@ namespace Opm
retval.type_ = S;
retval.rows_ = lhs.rows_;
retval.cols_ = rhs.cols_;
fastSparseDiagProduct(lhs.s_, rhs.d_, retval.s_);
retval.data_ = boost::any(Sparse(retval.rows_, retval.cols_)); //FIXME: Superfluous?
const Sparse& a = boost::any_cast<const Sparse&>(lhs.data_);
const Diag& b = boost::any_cast<const Diag&>(rhs.data_);
Sparse& c = boost::any_cast<Sparse&>(retval.data_);
fastSparseDiagProduct(a, b, c);
return retval;
}
@ -467,7 +498,11 @@ namespace Opm
retval.type_ = S;
retval.rows_ = lhs.rows_;
retval.cols_ = rhs.cols_;
fastSparseProduct(lhs.s_, rhs.s_, retval.s_);
retval.data_ = boost::any(Sparse(retval.rows_, retval.cols_)); //FIXME: Superfluous?
const Sparse& a = boost::any_cast<const Sparse&>(lhs.data_);
const Sparse& b = boost::any_cast<const Sparse&>(rhs.data_);
Sparse& c = boost::any_cast<Sparse&>(retval.data_);
fastSparseProduct(a, b, c);
return retval;
}
@ -483,10 +518,10 @@ namespace Opm
s = spdiag(Eigen::VectorXd::Ones(rows_));
return;
case D:
s = spdiag(d_);
s = spdiag(boost::any_cast<const Diag&>(data_));
return;
case S:
s = s_;
s = boost::any_cast<const Sparse&>(data_);
return;
}
}
@ -512,7 +547,7 @@ namespace Opm
case D:
return rows_;
case S:
return s_.nonZeros();
return boost::any_cast<const Sparse&>(data_).nonZeros();
default:
OPM_THROW(std::logic_error, "Invalid AutoDiffMatrix type encountered: " << type_);
}
@ -527,9 +562,9 @@ namespace Opm
case I:
return (row == col) ? 1.0 : 0.0;
case D:
return (row == col) ? d_[row] : 0.0;
return (row == col) ? boost::any_cast<const Diag&>(data_)[row] : 0.0;
case S:
return s_.coeff(row, col);
return boost::any_cast<const Sparse&>(data_).coeff(row, col);
default:
OPM_THROW(std::logic_error, "Invalid AutoDiffMatrix type encountered: " << type_);
}
@ -540,8 +575,11 @@ namespace Opm
MatrixType type_;
int rows_;
int cols_;
boost::any data_;
/*
std::vector<double> d_;
Eigen::SparseMatrix<double> s_;
*/
template <class V>
static inline