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dft_tools/triqs/arrays/linalg/determinant.hpp
Olivier Parcollet f2c7d449cc First commit : triqs libs version 1.0 alpha1
for earlier commits, see TRIQS0.x repository.
2013-07-17 19:24:07 +02:00

188 lines
8.0 KiB
C++

/*******************************************************************************
*
* TRIQS: a Toolbox for Research in Interacting Quantum Systems
*
* Copyright (C) 2011 by O. Parcollet
*
* TRIQS is free software: you can redistribute it and/or modify it under the
* terms of the GNU General Public License as published by the Free Software
* Foundation, either version 3 of the License, or (at your option) any later
* version.
*
* TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
* FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
* details.
*
* You should have received a copy of the GNU General Public License along with
* TRIQS. If not, see <http://www.gnu.org/licenses/>.
*
******************************************************************************/
#ifndef TRIQS_ARRAYS_LINALG_DET_INV_H
#define TRIQS_ARRAYS_LINALG_DET_INV_H
#include <boost/type_traits/is_same.hpp>
#include <boost/typeof/typeof.hpp>
#include <boost/utility/enable_if.hpp>
#include "../impl/common.hpp"
#include "../matrix.hpp"
#include "../blas_lapack/getrf.hpp"
#include "../blas_lapack/getri.hpp"
namespace triqs { namespace arrays {
/// Error which occurs during the matrix inversion
class matrix_inverse_exception : public triqs::runtime_error {};
/**
* Lazy result of inverse(M) where M can be :
* * a matrix, a matrix_view
* * any matrix expression
* The object is lazy, it does not do any computation.
* It can be copied at no cost
* It keeps view of the object A if it a matrix, a copy if it is a formal expression.
*/
template<typename A, class Enable = void> struct inverse_lazy;
///
template<typename A> struct determinant_lazy;
/// Lazy inversion
template<class A> inverse_lazy<A> inverse (A const & a) { return inverse_lazy<A>(a); }
/// Lazy computation of det
template<typename A> determinant_lazy<A> determinant (A const & a) { return determinant_lazy<A>(a); }
// ----------------- implementation -----------------------------------------
//worker takes a contiguous view and compute the det and inverse in two steps.
//it is separated in case of multiple use (no reallocation of ipvi, etc...)
//NB a view does not resize, only its elements can be changed
template<typename ViewType> class det_and_inverse_worker {
static_assert ( (is_matrix_view<ViewType>::value),"class must have be a view");
typedef typename ViewType::value_type VT;
typedef matrix_view<VT> V_type;
ViewType V;
const size_t dim;
triqs::arrays::vector <int> ipiv;
short step;
public:
det_and_inverse_worker (ViewType const & a): V(a), dim(a.dim0()), ipiv(dim), step(0) {
if (a.dim0()!=a.dim1())
TRIQS_RUNTIME_ERROR<<"Inverse/Det error : non-square matrix. Dimensions are : ("<<a.dim0()<<","<<a.dim1()<<")"<<"\n ";
if (!(has_contiguous_data(a))) TRIQS_RUNTIME_ERROR<<"det_and_inverse_worker only takes a contiguous view";
}
VT det() { V_type W = fortran_view(V); _step1(W); _compute_det(W); return _det;}
ViewType const & inverse() { if (step<2) { V_type W = fortran_view(V); _step1(W); _step2(W);} return V;}
private:
int info; VT _det;
// no need of special traversal
template<typename MT> V_type fortran_view (MT const &x) { return (x.indexmap().memory_layout_is_c() ? x.transpose() : x);}
void _step1(V_type & W) {
if (step >0) return;
step=1;
info = lapack::getrf(W, ipiv);
if (info<0) throw matrix_inverse_exception() << "Inverse/Det error : failure of getrf lapack routine ";
}
void _compute_det(V_type const & W) {
if (step>1) return;
_det =1;
for (size_t i =0; i<dim; i++) _det *= W(i,i);
bool flip=false;// compute the sign of the permutation
for (size_t i=0; i<dim; i++) {if (ipiv(i)!=int(i)+1) flip = !(flip);}
_det= (flip ? - _det : _det) ;
}
void _step2(V_type & W) {
assert(step==1); //if (step==1) return;
step=2;
_compute_det(W);
info = lapack::getri(W, ipiv);
if (info!=0) throw matrix_inverse_exception() << "Inverse/Det error : matrix is not invertible";
}
};
//-----------------------------------------------------------
// an implementation class to gather the common part to matrix and expression....
template<typename A> struct inverse_lazy_impl : TRIQS_MODEL_CONCEPT(ImmutableMatrix) {
typedef typename boost::remove_const<typename A::value_type>::type value_type;
typedef typename A::domain_type domain_type;
typedef typename domain_type::index_value_type index_value_type;
typedef typename const_view_type_if_exists_else_type<A>::type A_type;
const A_type a;
inverse_lazy_impl(A const & a_):a (a_) {
if (a.dim0() != a.dim1()) TRIQS_RUNTIME_ERROR<< "Inverse : matrix is not square but of size "<< a.dim0()<<" x "<< a.dim1();
}
domain_type domain() const { return a.domain(); }
size_t dim0() const { return a.dim0();}
size_t dim1() const { return a.dim1();}
template<typename K0, typename K1> value_type operator() (K0 const & k0, K1 const & k1) const { activate(); return _id->M(k0,k1); }
friend std::ostream & operator<<(std::ostream & out,inverse_lazy_impl const&x){return out<<"inverse("<<x.a<<")";}
protected:
struct internal_data { // implementing the pattern LazyPreCompute
//typedef typename A_type::non_view_type M_type;
typedef matrix<value_type> M_type;
typedef matrix_view<value_type> M_view_type;
M_type M;
internal_data(inverse_lazy_impl const & P):M(P.a){det_and_inverse_worker<M_view_type> worker(M); worker.inverse();}
};
friend struct internal_data;
mutable boost::shared_ptr<internal_data> _id;
void activate() const { if (!_id) _id= boost::make_shared<internal_data>(*this);}
};
// The general case
template<typename A>
struct inverse_lazy<A,typename boost::disable_if< is_matrix_or_view<A> >::type > : inverse_lazy_impl<A> {
inverse_lazy(A const & a):inverse_lazy_impl<A>(a) { }
};
// for matrix and matrix_views, we have more optimisation possible ....
template<typename A>
struct inverse_lazy<A,typename boost::enable_if< is_matrix_or_view<A> >::type >:inverse_lazy_impl<A>{
inverse_lazy(A const & a):inverse_lazy_impl<A>(a) { }
template<typename MT> // Optimized implementation of =
friend void triqs_arrays_assign_delegation (MT & lhs, inverse_lazy const & rhs) {
static_assert(is_matrix_or_view<MT>::value, "Internal error");
if ((lhs.indexmap().memory_indices_layout() !=rhs.a.indexmap().memory_indices_layout())||
(lhs.data_start() != rhs.a.data_start()) || !(has_contiguous_data(lhs))) { rhs.activate(); lhs = rhs._id->M;}
else {// if M = inverse(M) with the SAME object, then we do not need to copy the data
blas_lapack_tools::reflexive_qcache<MT> C(lhs);// a reflexive cache will use a temporary "regrouping" copy if and only if needed
det_and_inverse_worker<typename MT::view_type> W(C());// the worker to make the inversion of the lhs...
W.inverse(); // worker is working ...
}
}
friend std::ostream & operator<<(std::ostream & out,inverse_lazy const&x){return out<<"inverse("<<x.a<<")";}
};
//------------------- det ----------------------------------------
template<typename A> struct determinant_lazy { // : { Tag::expression_terminal, Tag::scalar_expression_terminal {
typedef typename A::value_type value_type;
typedef typename const_view_type_if_exists_else_type<A>::type A_type;
A_type a;
determinant_lazy(A const & a_):a(a_){}
operator value_type() { activate(); return _id->det; }
value_type const & operator()() { activate(); return _id->det; }
friend std::ostream & operator<<(std::ostream & out, determinant_lazy const & x){ return out<<"determinant("<<x.a<<")";}
protected:
struct internal_data {
typedef typename A_type::non_view_type M_type;
M_type M; typename A::value_type det;
internal_data(determinant_lazy const & P):M(P.a){det_and_inverse_worker<A_type> worker(M); det = worker.det();}
};
friend struct internal_data;
mutable boost::shared_ptr<internal_data> _id;
void activate() const { if (!_id) _id= boost::make_shared<internal_data>(*this);}
};
}} // namespace triqs::arrays
#endif