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dft_tools/triqs/arrays/linalg/det_and_inverse.hpp
Olivier Parcollet 47cb8a03f7 [arrays] Important changes in implementation.
- Simplify group_indices
  - Only for C ordered, remove complex compile time.
  - Could be generalized to non C ordered, but no need.
- Fix slice for custom orders.
- Generalize the group_indices for the custom order.
- Add c_ordered_transposed_view (useful ?)
- Improve slice, special for ellipsis (quicker).
- Simplify TraversalOrder
- Assignement. Specialize one case for speed.
- use FORCEINLINE in foreach, according to speed test for clang
- add one speed test
- Modify iterators for better speed.
- along the lines decided for the foreach
- update doc.
2014-10-18 21:20:17 +02:00

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/*******************************************************************************
*
* 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 "../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> struct inverse_lazy;
template <class A>
std14::enable_if_t<ImmutableMatrix<std14::remove_reference_t<A>>::value,
inverse_lazy<typename utility::remove_rvalue_ref<A>::type>>
inverse(A &&a) {
return {std::forward<A>(a)};
}
template <class A>
std14::enable_if_t<ImmutableArray<std14::remove_reference_t<A>>::value> inverse(A &&a) = delete; // arrays can not be inverted.
// ----------------- 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...)
// A can be a matrix, a matrix_view
template <typename A> class det_and_inverse_worker {
typedef typename A::value_type value_type;
typedef matrix_view<value_type> V_type;
A a;
int dim;
triqs::arrays::vector<int> ipiv;
int step, info;
value_type _det;
public:
det_and_inverse_worker(A a_) : a(std::move(a_)), dim(first_dim(a)), ipiv(dim), step(0) {
if (first_dim(a) != second_dim(a))
TRIQS_RUNTIME_ERROR << "Inverse/Det error:non-square matrix. Dimensions are :(" << first_dim(a) << "," << second_dim(a)
<< ")\n ";
if (!(has_contiguous_data(a))) TRIQS_RUNTIME_ERROR << "det_and_inverse_worker only takes a contiguous view";
}
value_type det() {
V_type W = fortran_view(a);
_step1(W);
_compute_det(W);
return _det;
}
A const &inverse() {
if (step < 2) {
V_type W = fortran_view(a);
_step1(W);
_step2(W);
}
return a;
}
private:
// no need of special traversal
template <typename MT> V_type fortran_view(MT const &x) {
if (x.indexmap().memory_layout_is_c())
return x.transpose();
else
return 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";
}
};
//-----------------------------------------------------------
template <typename A> struct inverse_lazy : TRIQS_CONCEPT_TAG_NAME(ImmutableMatrix) {
typedef typename std::remove_reference<A>::type A_t;
typedef typename std::remove_const<typename A_t::value_type>::type value_type;
typedef typename A_t::domain_type domain_type;
typedef matrix<value_type> M_type;
typedef matrix_view<value_type> M_view_type;
template <typename AA> inverse_lazy(AA &&a_) : a(std::forward<AA>(a_)), M{}, computed{false} {
if (first_dim(a) != second_dim(a))
TRIQS_RUNTIME_ERROR << "Inverse : matrix is not square but of size " << first_dim(a) << " x " << second_dim(a);
}
domain_type domain() const { return a.domain(); }
A const & input() const { return a;}
template <typename K0, typename K1> value_type const &operator()(K0 const &k0, K1 const &k1) const {
activate();
return M(k0, k1);
}
M_type const &operator()() const {
activate();
return M;
}
friend std::ostream &operator<<(std::ostream &out, inverse_lazy const &x) { return out << "inverse(" << x.a << ")"; }
private:
A a;
mutable M_type M;
mutable bool computed;
void activate() const {
if (computed) return;
M = a;
auto worker = det_and_inverse_worker<M_view_type> {M};
worker.inverse();
computed = true;
}
};
// Optimized implementation of =
// if M = inverse(M) with the SAME object, then we do not need to copy the data
template <typename A, typename MT>
ENABLE_IF(is_matrix_or_view<typename std::remove_reference<A>::type>)
triqs_arrays_assign_delegation(MT &lhs, inverse_lazy<A> const &rhs) {
static_assert(is_matrix_or_view<MT>::value, "Can only assign an inverse matrix to a matrix or a matrix_view");
bool M_eq_inverse_M = ((lhs.indexmap().get_memory_layout() == rhs.input().indexmap().get_memory_layout()) &&
(lhs.data_start() == rhs.input().data_start()) && (has_contiguous_data(lhs)));
if (!M_eq_inverse_M) {
lhs = rhs();
} else {
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 ...
}
}
//------------------- det ----------------------------------------
template <typename A> typename std::remove_reference<A>::type::value_type determinant(A &&a) {
// makes a temporary copy of A if A is a const &
// If a is a matrix &&, it is moved into the worker.
auto worker = det_and_inverse_worker<matrix<typename std::remove_reference<A>::type::value_type>>(std::forward<A>(a));
return worker.det();
}
}
namespace clef {
TRIQS_CLEF_MAKE_FNT_LAZY(determinant);
}
} // namespace triqs::arrays
#endif