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Diffstat (limited to 'eigen/Eigen/src/SparseCholesky/SimplicialCholesky_impl.h')
-rw-r--r-- | eigen/Eigen/src/SparseCholesky/SimplicialCholesky_impl.h | 199 |
1 files changed, 0 insertions, 199 deletions
diff --git a/eigen/Eigen/src/SparseCholesky/SimplicialCholesky_impl.h b/eigen/Eigen/src/SparseCholesky/SimplicialCholesky_impl.h deleted file mode 100644 index 31e0699..0000000 --- a/eigen/Eigen/src/SparseCholesky/SimplicialCholesky_impl.h +++ /dev/null @@ -1,199 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2012 Gael Guennebaud <gael.guennebaud@inria.fr> - -/* - -NOTE: thes functions vave been adapted from the LDL library: - -LDL Copyright (c) 2005 by Timothy A. Davis. All Rights Reserved. - -LDL License: - - Your use or distribution of LDL or any modified version of - LDL implies that you agree to this License. - - This library is free software; you can redistribute it and/or - modify it under the terms of the GNU Lesser General Public - License as published by the Free Software Foundation; either - version 2.1 of the License, or (at your option) any later version. - - This library 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 - Lesser General Public License for more details. - - You should have received a copy of the GNU Lesser General Public - License along with this library; if not, write to the Free Software - Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 - USA - - Permission is hereby granted to use or copy this program under the - terms of the GNU LGPL, provided that the Copyright, this License, - and the Availability of the original version is retained on all copies. - User documentation of any code that uses this code or any modified - version of this code must cite the Copyright, this License, the - Availability note, and "Used by permission." Permission to modify - the code and to distribute modified code is granted, provided the - Copyright, this License, and the Availability note are retained, - and a notice that the code was modified is included. - */ - -#include "../Core/util/NonMPL2.h" - -#ifndef EIGEN_SIMPLICIAL_CHOLESKY_IMPL_H -#define EIGEN_SIMPLICIAL_CHOLESKY_IMPL_H - -namespace Eigen { - -template<typename Derived> -void SimplicialCholeskyBase<Derived>::analyzePattern_preordered(const CholMatrixType& ap, bool doLDLT) -{ - const StorageIndex size = StorageIndex(ap.rows()); - m_matrix.resize(size, size); - m_parent.resize(size); - m_nonZerosPerCol.resize(size); - - ei_declare_aligned_stack_constructed_variable(StorageIndex, tags, size, 0); - - for(StorageIndex k = 0; k < size; ++k) - { - /* L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) */ - m_parent[k] = -1; /* parent of k is not yet known */ - tags[k] = k; /* mark node k as visited */ - m_nonZerosPerCol[k] = 0; /* count of nonzeros in column k of L */ - for(typename CholMatrixType::InnerIterator it(ap,k); it; ++it) - { - StorageIndex i = it.index(); - if(i < k) - { - /* follow path from i to root of etree, stop at flagged node */ - for(; tags[i] != k; i = m_parent[i]) - { - /* find parent of i if not yet determined */ - if (m_parent[i] == -1) - m_parent[i] = k; - m_nonZerosPerCol[i]++; /* L (k,i) is nonzero */ - tags[i] = k; /* mark i as visited */ - } - } - } - } - - /* construct Lp index array from m_nonZerosPerCol column counts */ - StorageIndex* Lp = m_matrix.outerIndexPtr(); - Lp[0] = 0; - for(StorageIndex k = 0; k < size; ++k) - Lp[k+1] = Lp[k] + m_nonZerosPerCol[k] + (doLDLT ? 0 : 1); - - m_matrix.resizeNonZeros(Lp[size]); - - m_isInitialized = true; - m_info = Success; - m_analysisIsOk = true; - m_factorizationIsOk = false; -} - - -template<typename Derived> -template<bool DoLDLT> -void SimplicialCholeskyBase<Derived>::factorize_preordered(const CholMatrixType& ap) -{ - using std::sqrt; - - eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); - eigen_assert(ap.rows()==ap.cols()); - eigen_assert(m_parent.size()==ap.rows()); - eigen_assert(m_nonZerosPerCol.size()==ap.rows()); - - const StorageIndex size = StorageIndex(ap.rows()); - const StorageIndex* Lp = m_matrix.outerIndexPtr(); - StorageIndex* Li = m_matrix.innerIndexPtr(); - Scalar* Lx = m_matrix.valuePtr(); - - ei_declare_aligned_stack_constructed_variable(Scalar, y, size, 0); - ei_declare_aligned_stack_constructed_variable(StorageIndex, pattern, size, 0); - ei_declare_aligned_stack_constructed_variable(StorageIndex, tags, size, 0); - - bool ok = true; - m_diag.resize(DoLDLT ? size : 0); - - for(StorageIndex k = 0; k < size; ++k) - { - // compute nonzero pattern of kth row of L, in topological order - y[k] = 0.0; // Y(0:k) is now all zero - StorageIndex top = size; // stack for pattern is empty - tags[k] = k; // mark node k as visited - m_nonZerosPerCol[k] = 0; // count of nonzeros in column k of L - for(typename CholMatrixType::InnerIterator it(ap,k); it; ++it) - { - StorageIndex i = it.index(); - if(i <= k) - { - y[i] += numext::conj(it.value()); /* scatter A(i,k) into Y (sum duplicates) */ - Index len; - for(len = 0; tags[i] != k; i = m_parent[i]) - { - pattern[len++] = i; /* L(k,i) is nonzero */ - tags[i] = k; /* mark i as visited */ - } - while(len > 0) - pattern[--top] = pattern[--len]; - } - } - - /* compute numerical values kth row of L (a sparse triangular solve) */ - - RealScalar d = numext::real(y[k]) * m_shiftScale + m_shiftOffset; // get D(k,k), apply the shift function, and clear Y(k) - y[k] = 0.0; - for(; top < size; ++top) - { - Index i = pattern[top]; /* pattern[top:n-1] is pattern of L(:,k) */ - Scalar yi = y[i]; /* get and clear Y(i) */ - y[i] = 0.0; - - /* the nonzero entry L(k,i) */ - Scalar l_ki; - if(DoLDLT) - l_ki = yi / m_diag[i]; - else - yi = l_ki = yi / Lx[Lp[i]]; - - Index p2 = Lp[i] + m_nonZerosPerCol[i]; - Index p; - for(p = Lp[i] + (DoLDLT ? 0 : 1); p < p2; ++p) - y[Li[p]] -= numext::conj(Lx[p]) * yi; - d -= numext::real(l_ki * numext::conj(yi)); - Li[p] = k; /* store L(k,i) in column form of L */ - Lx[p] = l_ki; - ++m_nonZerosPerCol[i]; /* increment count of nonzeros in col i */ - } - if(DoLDLT) - { - m_diag[k] = d; - if(d == RealScalar(0)) - { - ok = false; /* failure, D(k,k) is zero */ - break; - } - } - else - { - Index p = Lp[k] + m_nonZerosPerCol[k]++; - Li[p] = k ; /* store L(k,k) = sqrt (d) in column k */ - if(d <= RealScalar(0)) { - ok = false; /* failure, matrix is not positive definite */ - break; - } - Lx[p] = sqrt(d) ; - } - } - - m_info = ok ? Success : NumericalIssue; - m_factorizationIsOk = true; -} - -} // end namespace Eigen - -#endif // EIGEN_SIMPLICIAL_CHOLESKY_IMPL_H |