| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2008-2012 Gael Guennebaud <gael.guennebaud@inria.fr> |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| |
| /* |
| NOTE: these functions have been adapted from the LDL library: |
| |
| LDL Copyright (c) 2005 by Timothy A. Davis. All Rights Reserved. |
| |
| The author of LDL, Timothy A. Davis., has executed a license with Google LLC |
| to permit distribution of this code and derivative works as part of Eigen under |
| the Mozilla Public License v. 2.0, as stated at the top of this file. |
| */ |
| |
| #ifndef EIGEN_SIMPLICIAL_CHOLESKY_IMPL_H |
| #define EIGEN_SIMPLICIAL_CHOLESKY_IMPL_H |
| |
| // IWYU pragma: private |
| #include "./InternalHeaderCheck.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, bool NonHermitian> |
| 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] = Scalar(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] += getSymm(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) */ |
| |
| DiagonalScalar d = |
| getDiag(y[k]) * m_shiftScale + m_shiftOffset; // get D(k,k), apply the shift function, and clear Y(k) |
| y[k] = Scalar(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] = Scalar(0); |
| |
| /* the nonzero entry L(k,i) */ |
| Scalar l_ki; |
| if (DoLDLT) |
| l_ki = yi / getDiag(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]] -= getSymm(Lx[p]) * yi; |
| d -= getDiag(l_ki * getSymm(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 (NonHermitian ? d == RealScalar(0) : numext::real(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 |