diff --git a/resources/3rdparty/eigen/.hg_archival.txt b/resources/3rdparty/eigen/.hg_archival.txt
index 5a08f7257..ed93eed54 100644
--- a/resources/3rdparty/eigen/.hg_archival.txt
+++ b/resources/3rdparty/eigen/.hg_archival.txt
@@ -1,4 +1,5 @@
repo: 8a21fd850624c931e448cbcfb38168cb2717c790
-node: 43d9075b23ef596ddf396101956d06f446fc0765
-branch: 3.1
-tag: 3.1.1
+node: 5945cb388ded120eb6dd3a1dfd2766b8e83237a4
+branch: default
+latesttag: 3.1.0-rc2
+latesttagdistance: 147
diff --git a/resources/3rdparty/eigen/.hgtags b/resources/3rdparty/eigen/.hgtags
index 4068c28b2..cbbcebdae 100644
--- a/resources/3rdparty/eigen/.hgtags
+++ b/resources/3rdparty/eigen/.hgtags
@@ -20,4 +20,3 @@ a810d5dbab47acfe65b3350236efdd98f67d4d8a 3.1.0-alpha1
920fc730b5930daae0a6dbe296d60ce2e3808215 3.1.0-beta1
8383e883ebcc6f14695ff0b5e20bb631abab43fb 3.1.0-rc1
bf4cb8c934fa3a79f45f1e629610f0225e93e493 3.1.0-rc2
-ca142d0540d3384180c5082d24ef056bd3c354b6 3.1.0
diff --git a/resources/3rdparty/eigen/.krazy b/resources/3rdparty/eigen/.krazy
deleted file mode 100644
index d719866a6..000000000
--- a/resources/3rdparty/eigen/.krazy
+++ /dev/null
@@ -1,3 +0,0 @@
-SKIP /disabled/
-SKIP /bench/
-SKIP /build/
diff --git a/resources/3rdparty/eigen/COPYING.LGPL b/resources/3rdparty/eigen/COPYING.LGPL
index 0e4fa8aaf..4362b4915 100644
--- a/resources/3rdparty/eigen/COPYING.LGPL
+++ b/resources/3rdparty/eigen/COPYING.LGPL
@@ -1,165 +1,502 @@
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+conditions either of that version or of any later version published by
+the Free Software Foundation. If the Library does not specify a
+license version number, you may choose any version ever published by
+the Free Software Foundation.
+
+ 14. If you wish to incorporate parts of the Library into other free
+programs whose distribution conditions are incompatible with these,
+write to the author to ask for permission. For software which is
+copyrighted by the Free Software Foundation, write to the Free
+Software Foundation; we sometimes make exceptions for this. Our
+decision will be guided by the two goals of preserving the free status
+of all derivatives of our free software and of promoting the sharing
+and reuse of software generally.
+
+ NO WARRANTY
+
+ 15. BECAUSE THE LIBRARY IS LICENSED FREE OF CHARGE, THERE IS NO
+WARRANTY FOR THE LIBRARY, TO THE EXTENT PERMITTED BY APPLICABLE LAW.
+EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR
+OTHER PARTIES PROVIDE THE LIBRARY "AS IS" WITHOUT WARRANTY OF ANY
+KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE
+LIBRARY IS WITH YOU. SHOULD THE LIBRARY PROVE DEFECTIVE, YOU ASSUME
+THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+ 16. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN
+WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY
+AND/OR REDISTRIBUTE THE LIBRARY AS PERMITTED ABOVE, BE LIABLE TO YOU
+FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR
+CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE
+LIBRARY (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING
+RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A
+FAILURE OF THE LIBRARY TO OPERATE WITH ANY OTHER SOFTWARE), EVEN IF
+SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH
+DAMAGES.
+
+ END OF TERMS AND CONDITIONS
+
+ How to Apply These Terms to Your New Libraries
+
+ If you develop a new library, and you want it to be of the greatest
+possible use to the public, we recommend making it free software that
+everyone can redistribute and change. You can do so by permitting
+redistribution under these terms (or, alternatively, under the terms of the
+ordinary General Public License).
+
+ To apply these terms, attach the following notices to the library. It is
+safest to attach them to the start of each source file to most effectively
+convey the exclusion of warranty; and each file should have at least the
+"copyright" line and a pointer to where the full notice is found.
+
+ <one line to give the library's name and a brief idea of what it does.>
+ Copyright (C) <year> <name of author>
+
+ 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 Street, Fifth Floor, Boston, MA 02110-1301 USA
+
+Also add information on how to contact you by electronic and paper mail.
+
+You should also get your employer (if you work as a programmer) or your
+school, if any, to sign a "copyright disclaimer" for the library, if
+necessary. Here is a sample; alter the names:
+
+ Yoyodyne, Inc., hereby disclaims all copyright interest in the
+ library `Frob' (a library for tweaking knobs) written by James Random Hacker.
+
+ <signature of Ty Coon>, 1 April 1990
+ Ty Coon, President of Vice
+
+That's all there is to it!
diff --git a/resources/3rdparty/eigen/COPYING.README b/resources/3rdparty/eigen/COPYING.README
index 1d706784d..de5b63215 100644
--- a/resources/3rdparty/eigen/COPYING.README
+++ b/resources/3rdparty/eigen/COPYING.README
@@ -5,6 +5,9 @@ Eigen is primarily MPL2 licensed. See COPYING.MPL2 and these links:
Some files contain third-party code under BSD or LGPL licenses, whence the other
COPYING.* files here.
+All the LGPL code is either LGPL 2.1-only, or LGPL 2.1-or-later.
+For this reason, the COPYING.LGPL file contains the LGPL 2.1 text.
+
If you want to guarantee that the Eigen code that you are #including is licensed
under the MPL2 and possibly more permissive licenses (like BSD), #define this
preprocessor symbol:
diff --git a/resources/3rdparty/eigen/Eigen/Core b/resources/3rdparty/eigen/Eigen/Core
index d48017022..502a4fc55 100644
--- a/resources/3rdparty/eigen/Eigen/Core
+++ b/resources/3rdparty/eigen/Eigen/Core
@@ -87,19 +87,25 @@
// so, to avoid compile errors when windows.h is included after Eigen/Core, ensure intrinsics are extern "C" here too.
// notice that since these are C headers, the extern "C" is theoretically needed anyways.
extern "C" {
- #include <emmintrin.h>
- #include <xmmintrin.h>
- #ifdef EIGEN_VECTORIZE_SSE3
- #include <pmmintrin.h>
- #endif
- #ifdef EIGEN_VECTORIZE_SSSE3
- #include <tmmintrin.h>
- #endif
- #ifdef EIGEN_VECTORIZE_SSE4_1
- #include <smmintrin.h>
- #endif
- #ifdef EIGEN_VECTORIZE_SSE4_2
- #include <nmmintrin.h>
+ // In theory we should only include immintrin.h and not the other *mmintrin.h header files directly.
+ // Doing so triggers some issues with ICC. However old gcc versions seems to not have this file, thus:
+ #ifdef __INTEL_COMPILER
+ #include <immintrin.h>
+ #else
+ #include <emmintrin.h>
+ #include <xmmintrin.h>
+ #ifdef EIGEN_VECTORIZE_SSE3
+ #include <pmmintrin.h>
+ #endif
+ #ifdef EIGEN_VECTORIZE_SSSE3
+ #include <tmmintrin.h>
+ #endif
+ #ifdef EIGEN_VECTORIZE_SSE4_1
+ #include <smmintrin.h>
+ #endif
+ #ifdef EIGEN_VECTORIZE_SSE4_2
+ #include <nmmintrin.h>
+ #endif
#endif
} // end extern "C"
#elif defined __ALTIVEC__
@@ -297,6 +303,7 @@ using std::ptrdiff_t;
#include "src/Core/Map.h"
#include "src/Core/Block.h"
#include "src/Core/VectorBlock.h"
+#include "src/Core/Ref.h"
#include "src/Core/Transpose.h"
#include "src/Core/DiagonalMatrix.h"
#include "src/Core/Diagonal.h"
@@ -340,6 +347,13 @@ using std::ptrdiff_t;
#include "src/Core/ArrayBase.h"
#include "src/Core/ArrayWrapper.h"
+#ifdef EIGEN_ENABLE_EVALUATORS
+#include "src/Core/Product.h"
+#include "src/Core/CoreEvaluators.h"
+#include "src/Core/AssignEvaluator.h"
+#include "src/Core/ProductEvaluators.h"
+#endif
+
#ifdef EIGEN_USE_BLAS
#include "src/Core/products/GeneralMatrixMatrix_MKL.h"
#include "src/Core/products/GeneralMatrixVector_MKL.h"
diff --git a/resources/3rdparty/eigen/Eigen/Eigenvalues b/resources/3rdparty/eigen/Eigen/Eigenvalues
index af99ccd1f..53c5a73a2 100644
--- a/resources/3rdparty/eigen/Eigen/Eigenvalues
+++ b/resources/3rdparty/eigen/Eigen/Eigenvalues
@@ -33,6 +33,8 @@
#include "src/Eigenvalues/HessenbergDecomposition.h"
#include "src/Eigenvalues/ComplexSchur.h"
#include "src/Eigenvalues/ComplexEigenSolver.h"
+#include "src/Eigenvalues/RealQZ.h"
+#include "src/Eigenvalues/GeneralizedEigenSolver.h"
#include "src/Eigenvalues/MatrixBaseEigenvalues.h"
#ifdef EIGEN_USE_LAPACKE
#include "src/Eigenvalues/RealSchur_MKL.h"
diff --git a/resources/3rdparty/eigen/Eigen/OrderingMethods b/resources/3rdparty/eigen/Eigen/OrderingMethods
index 1e2d87452..bb43220e8 100644
--- a/resources/3rdparty/eigen/Eigen/OrderingMethods
+++ b/resources/3rdparty/eigen/Eigen/OrderingMethods
@@ -17,7 +17,7 @@
*/
#include "src/OrderingMethods/Amd.h"
-
+#include "src/OrderingMethods/Ordering.h"
#include "src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_ORDERINGMETHODS_MODULE_H
diff --git a/resources/3rdparty/eigen/Eigen/src/Cholesky/LDLT.h b/resources/3rdparty/eigen/Eigen/src/Cholesky/LDLT.h
index 68e54b1d4..a73a9c19f 100644
--- a/resources/3rdparty/eigen/Eigen/src/Cholesky/LDLT.h
+++ b/resources/3rdparty/eigen/Eigen/src/Cholesky/LDLT.h
@@ -281,6 +281,13 @@ template<> struct ldlt_inplace<Lower>
if(sign)
*sign = real(mat.diagonal().coeff(index_of_biggest_in_corner)) > 0 ? 1 : -1;
}
+ else if(sign)
+ {
+ // LDLT is not guaranteed to work for indefinite matrices, but let's try to get the sign right
+ int newSign = real(mat.diagonal().coeff(index_of_biggest_in_corner)) > 0;
+ if(newSign != *sign)
+ *sign = 0;
+ }
// Finish early if the matrix is not full rank.
if(biggest_in_corner < cutoff)
diff --git a/resources/3rdparty/eigen/Eigen/src/CholmodSupport/CholmodSupport.h b/resources/3rdparty/eigen/Eigen/src/CholmodSupport/CholmodSupport.h
index 37f142150..b38821807 100644
--- a/resources/3rdparty/eigen/Eigen/src/CholmodSupport/CholmodSupport.h
+++ b/resources/3rdparty/eigen/Eigen/src/CholmodSupport/CholmodSupport.h
@@ -173,6 +173,7 @@ class CholmodBase : internal::noncopyable
CholmodBase(const MatrixType& matrix)
: m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
{
+ m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
cholmod_start(&m_cholmod);
compute(matrix);
}
@@ -269,9 +270,10 @@ class CholmodBase : internal::noncopyable
{
eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
- cholmod_factorize(&A, m_cholmodFactor, &m_cholmod);
+ cholmod_factorize_p(&A, m_shiftOffset, 0, 0, m_cholmodFactor, &m_cholmod);
- this->m_info = Success;
+ // If the factorization failed, minor is the column at which it did. On success minor == n.
+ this->m_info = (m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue);
m_factorizationIsOk = true;
}
@@ -286,6 +288,7 @@ class CholmodBase : internal::noncopyable
{
eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
const Index size = m_cholmodFactor->n;
+ EIGEN_UNUSED_VARIABLE(size);
eigen_assert(size==b.rows());
// note: cd stands for Cholmod Dense
@@ -321,6 +324,22 @@ class CholmodBase : internal::noncopyable
}
#endif // EIGEN_PARSED_BY_DOXYGEN
+
+ /** Sets the shift parameter that will be used to adjust the diagonal coefficients during the numerical factorization.
+ *
+ * During the numerical factorization, an offset term is added to the diagonal coefficients:\n
+ * \c d_ii = \a offset + \c d_ii
+ *
+ * The default is \a offset=0.
+ *
+ * \returns a reference to \c *this.
+ */
+ Derived& setShift(const RealScalar& offset)
+ {
+ m_shiftOffset[0] = offset;
+ return derived();
+ }
+
template<typename Stream>
void dumpMemory(Stream& s)
{}
@@ -328,6 +347,7 @@ class CholmodBase : internal::noncopyable
protected:
mutable cholmod_common m_cholmod;
cholmod_factor* m_cholmodFactor;
+ RealScalar m_shiftOffset[2];
mutable ComputationInfo m_info;
bool m_isInitialized;
int m_factorizationIsOk;
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Array.h b/resources/3rdparty/eigen/Eigen/src/Core/Array.h
index aaa389978..539e1d22b 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Array.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Array.h
@@ -142,10 +142,10 @@ class Array
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename T0, typename T1>
- EIGEN_STRONG_INLINE Array(const T0& x, const T1& y)
+ EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1)
{
Base::_check_template_params();
- this->template _init2<T0,T1>(x, y);
+ this->template _init2<T0,T1>(val0, val1);
}
#else
/** constructs an uninitialized matrix with \a rows rows and \a cols columns.
@@ -155,27 +155,27 @@ class Array
* Matrix() instead. */
Array(Index rows, Index cols);
/** constructs an initialized 2D vector with given coefficients */
- Array(const Scalar& x, const Scalar& y);
+ Array(const Scalar& val0, const Scalar& val1);
#endif
/** constructs an initialized 3D vector with given coefficients */
- EIGEN_STRONG_INLINE Array(const Scalar& x, const Scalar& y, const Scalar& z)
+ EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
{
Base::_check_template_params();
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
- m_storage.data()[0] = x;
- m_storage.data()[1] = y;
- m_storage.data()[2] = z;
+ m_storage.data()[0] = val0;
+ m_storage.data()[1] = val1;
+ m_storage.data()[2] = val2;
}
/** constructs an initialized 4D vector with given coefficients */
- EIGEN_STRONG_INLINE Array(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
+ EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
{
Base::_check_template_params();
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
- m_storage.data()[0] = x;
- m_storage.data()[1] = y;
- m_storage.data()[2] = z;
- m_storage.data()[3] = w;
+ m_storage.data()[0] = val0;
+ m_storage.data()[1] = val1;
+ m_storage.data()[2] = val2;
+ m_storage.data()[3] = val3;
}
explicit Array(const Scalar *data);
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/ArrayWrapper.h b/resources/3rdparty/eigen/Eigen/src/Core/ArrayWrapper.h
index 87af7fda9..1e021b0b9 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/ArrayWrapper.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/ArrayWrapper.h
@@ -58,19 +58,19 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
inline const Scalar* data() const { return m_expression.data(); }
- inline CoeffReturnType coeff(Index row, Index col) const
+ inline CoeffReturnType coeff(Index rowId, Index colId) const
{
- return m_expression.coeff(row, col);
+ return m_expression.coeff(rowId, colId);
}
- inline Scalar& coeffRef(Index row, Index col)
+ inline Scalar& coeffRef(Index rowId, Index colId)
{
- return m_expression.const_cast_derived().coeffRef(row, col);
+ return m_expression.const_cast_derived().coeffRef(rowId, colId);
}
- inline const Scalar& coeffRef(Index row, Index col) const
+ inline const Scalar& coeffRef(Index rowId, Index colId) const
{
- return m_expression.const_cast_derived().coeffRef(row, col);
+ return m_expression.const_cast_derived().coeffRef(rowId, colId);
}
inline CoeffReturnType coeff(Index index) const
@@ -89,15 +89,15 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
}
template<int LoadMode>
- inline const PacketScalar packet(Index row, Index col) const
+ inline const PacketScalar packet(Index rowId, Index colId) const
{
- return m_expression.template packet<LoadMode>(row, col);
+ return m_expression.template packet<LoadMode>(rowId, colId);
}
template<int LoadMode>
- inline void writePacket(Index row, Index col, const PacketScalar& x)
+ inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
{
- m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
+ m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
}
template<int LoadMode>
@@ -107,9 +107,9 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
}
template<int LoadMode>
- inline void writePacket(Index index, const PacketScalar& x)
+ inline void writePacket(Index index, const PacketScalar& val)
{
- m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
+ m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
}
template<typename Dest>
@@ -121,6 +121,13 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
return m_expression;
}
+ /** Forwards the resizing request to the nested expression
+ * \sa DenseBase::resize(Index) */
+ void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+ /** Forwards the resizing request to the nested expression
+ * \sa DenseBase::resize(Index,Index)*/
+ void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+
protected:
NestedExpressionType m_expression;
};
@@ -161,7 +168,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
- inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
+ inline MatrixWrapper(ExpressionType& a_matrix) : m_expression(a_matrix) {}
inline Index rows() const { return m_expression.rows(); }
inline Index cols() const { return m_expression.cols(); }
@@ -171,19 +178,19 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
inline const Scalar* data() const { return m_expression.data(); }
- inline CoeffReturnType coeff(Index row, Index col) const
+ inline CoeffReturnType coeff(Index rowId, Index colId) const
{
- return m_expression.coeff(row, col);
+ return m_expression.coeff(rowId, colId);
}
- inline Scalar& coeffRef(Index row, Index col)
+ inline Scalar& coeffRef(Index rowId, Index colId)
{
- return m_expression.const_cast_derived().coeffRef(row, col);
+ return m_expression.const_cast_derived().coeffRef(rowId, colId);
}
- inline const Scalar& coeffRef(Index row, Index col) const
+ inline const Scalar& coeffRef(Index rowId, Index colId) const
{
- return m_expression.derived().coeffRef(row, col);
+ return m_expression.derived().coeffRef(rowId, colId);
}
inline CoeffReturnType coeff(Index index) const
@@ -202,15 +209,15 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
}
template<int LoadMode>
- inline const PacketScalar packet(Index row, Index col) const
+ inline const PacketScalar packet(Index rowId, Index colId) const
{
- return m_expression.template packet<LoadMode>(row, col);
+ return m_expression.template packet<LoadMode>(rowId, colId);
}
template<int LoadMode>
- inline void writePacket(Index row, Index col, const PacketScalar& x)
+ inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
{
- m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
+ m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
}
template<int LoadMode>
@@ -220,9 +227,9 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
}
template<int LoadMode>
- inline void writePacket(Index index, const PacketScalar& x)
+ inline void writePacket(Index index, const PacketScalar& val)
{
- m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
+ m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
}
const typename internal::remove_all<NestedExpressionType>::type&
@@ -231,6 +238,13 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
return m_expression;
}
+ /** Forwards the resizing request to the nested expression
+ * \sa DenseBase::resize(Index) */
+ void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+ /** Forwards the resizing request to the nested expression
+ * \sa DenseBase::resize(Index,Index)*/
+ void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+
protected:
NestedExpressionType m_expression;
};
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Assign_MKL.h b/resources/3rdparty/eigen/Eigen/src/Core/Assign_MKL.h
index 428c6367b..7772951b9 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Assign_MKL.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Assign_MKL.h
@@ -210,7 +210,7 @@ EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sqrt, Sqrt)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr)
// The vm*powx functions are not avaibale in the windows version of MKL.
-#ifdef _WIN32
+#ifndef _WIN32
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmspowx_, float, float)
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdpowx_, double, double)
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcpowx_, scomplex, MKL_Complex8)
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Block.h b/resources/3rdparty/eigen/Eigen/src/Core/Block.h
index 5f29cb3d1..9c3f9acb6 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Block.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Block.h
@@ -124,27 +124,27 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
/** Fixed-size constructor
*/
- inline Block(XprType& xpr, Index startRow, Index startCol)
- : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
+ inline Block(XprType& xpr, Index a_startRow, Index a_startCol)
+ : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
m_blockRows(BlockRows), m_blockCols(BlockCols)
{
EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
- eigen_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= xpr.rows()
- && startCol >= 0 && BlockCols >= 1 && startCol + BlockCols <= xpr.cols());
+ eigen_assert(a_startRow >= 0 && BlockRows >= 1 && a_startRow + BlockRows <= xpr.rows()
+ && a_startCol >= 0 && BlockCols >= 1 && a_startCol + BlockCols <= xpr.cols());
}
/** Dynamic-size constructor
*/
inline Block(XprType& xpr,
- Index startRow, Index startCol,
+ Index a_startRow, Index a_startCol,
Index blockRows, Index blockCols)
- : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
+ : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
m_blockRows(blockRows), m_blockCols(blockCols)
{
eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
&& (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
- eigen_assert(startRow >= 0 && blockRows >= 0 && startRow + blockRows <= xpr.rows()
- && startCol >= 0 && blockCols >= 0 && startCol + blockCols <= xpr.cols());
+ eigen_assert(a_startRow >= 0 && blockRows >= 0 && a_startRow + blockRows <= xpr.rows()
+ && a_startCol >= 0 && blockCols >= 0 && a_startCol + blockCols <= xpr.cols());
}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
@@ -152,22 +152,22 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
inline Index rows() const { return m_blockRows.value(); }
inline Index cols() const { return m_blockCols.value(); }
- inline Scalar& coeffRef(Index row, Index col)
+ inline Scalar& coeffRef(Index rowId, Index colId)
{
EIGEN_STATIC_ASSERT_LVALUE(XprType)
return m_xpr.const_cast_derived()
- .coeffRef(row + m_startRow.value(), col + m_startCol.value());
+ .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
}
- inline const Scalar& coeffRef(Index row, Index col) const
+ inline const Scalar& coeffRef(Index rowId, Index colId) const
{
return m_xpr.derived()
- .coeffRef(row + m_startRow.value(), col + m_startCol.value());
+ .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
}
- EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index row, Index col) const
+ EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const
{
- return m_xpr.coeff(row + m_startRow.value(), col + m_startCol.value());
+ return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value());
}
inline Scalar& coeffRef(Index index)
@@ -193,17 +193,17 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
}
template<int LoadMode>
- inline PacketScalar packet(Index row, Index col) const
+ inline PacketScalar packet(Index rowId, Index colId) const
{
return m_xpr.template packet<Unaligned>
- (row + m_startRow.value(), col + m_startCol.value());
+ (rowId + m_startRow.value(), colId + m_startCol.value());
}
template<int LoadMode>
- inline void writePacket(Index row, Index col, const PacketScalar& x)
+ inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
{
m_xpr.const_cast_derived().template writePacket<Unaligned>
- (row + m_startRow.value(), col + m_startCol.value(), x);
+ (rowId + m_startRow.value(), colId + m_startCol.value(), val);
}
template<int LoadMode>
@@ -215,11 +215,11 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
}
template<int LoadMode>
- inline void writePacket(Index index, const PacketScalar& x)
+ inline void writePacket(Index index, const PacketScalar& val)
{
m_xpr.const_cast_derived().template writePacket<Unaligned>
(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
- m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), x);
+ m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val);
}
#ifdef EIGEN_PARSED_BY_DOXYGEN
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/CwiseBinaryOp.h b/resources/3rdparty/eigen/Eigen/src/Core/CwiseBinaryOp.h
index 1b93af31b..686c2afa3 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/CwiseBinaryOp.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/CwiseBinaryOp.h
@@ -122,13 +122,13 @@ class CwiseBinaryOp : internal::no_assignment_operator,
typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
- EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp())
- : m_lhs(lhs), m_rhs(rhs), m_functor(func)
+ EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp())
+ : m_lhs(aLhs), m_rhs(aRhs), m_functor(func)
{
EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar);
// require the sizes to match
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
- eigen_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
+ eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
}
EIGEN_STRONG_INLINE Index rows() const {
@@ -169,17 +169,17 @@ class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Dense>
typedef typename internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE( Derived )
- EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
+ EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
{
- return derived().functor()(derived().lhs().coeff(row, col),
- derived().rhs().coeff(row, col));
+ return derived().functor()(derived().lhs().coeff(rowId, colId),
+ derived().rhs().coeff(rowId, colId));
}
template<int LoadMode>
- EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+ EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
{
- return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(row, col),
- derived().rhs().template packet<LoadMode>(row, col));
+ return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(rowId, colId),
+ derived().rhs().template packet<LoadMode>(rowId, colId));
}
EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/CwiseNullaryOp.h b/resources/3rdparty/eigen/Eigen/src/Core/CwiseNullaryOp.h
index 2635a62b0..edd2bed46 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/CwiseNullaryOp.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/CwiseNullaryOp.h
@@ -54,27 +54,27 @@ class CwiseNullaryOp : internal::no_assignment_operator,
typedef typename internal::dense_xpr_base<CwiseNullaryOp>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
- CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp())
- : m_rows(rows), m_cols(cols), m_functor(func)
+ CwiseNullaryOp(Index nbRows, Index nbCols, const NullaryOp& func = NullaryOp())
+ : m_rows(nbRows), m_cols(nbCols), m_functor(func)
{
- eigen_assert(rows >= 0
- && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
- && cols >= 0
- && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
+ eigen_assert(nbRows >= 0
+ && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
+ && nbCols >= 0
+ && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols));
}
EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); }
EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); }
- EIGEN_STRONG_INLINE const Scalar coeff(Index rows, Index cols) const
+ EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
{
- return m_functor(rows, cols);
+ return m_functor(rowId, colId);
}
template<int LoadMode>
- EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+ EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
{
- return m_functor.packetOp(row, col);
+ return m_functor.packetOp(rowId, colId);
}
EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
@@ -295,11 +295,11 @@ DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
/** \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
template<typename Derived>
bool DenseBase<Derived>::isApproxToConstant
-(const Scalar& value, RealScalar prec) const
+(const Scalar& val, const RealScalar& prec) const
{
for(Index j = 0; j < cols(); ++j)
for(Index i = 0; i < rows(); ++i)
- if(!internal::isApprox(this->coeff(i, j), value, prec))
+ if(!internal::isApprox(this->coeff(i, j), val, prec))
return false;
return true;
}
@@ -309,9 +309,9 @@ bool DenseBase<Derived>::isApproxToConstant
* \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
template<typename Derived>
bool DenseBase<Derived>::isConstant
-(const Scalar& value, RealScalar prec) const
+(const Scalar& val, const RealScalar& prec) const
{
- return isApproxToConstant(value, prec);
+ return isApproxToConstant(val, prec);
}
/** Alias for setConstant(): sets all coefficients in this expression to \a value.
@@ -319,9 +319,9 @@ bool DenseBase<Derived>::isConstant
* \sa setConstant(), Constant(), class CwiseNullaryOp
*/
template<typename Derived>
-EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& value)
+EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
{
- setConstant(value);
+ setConstant(val);
}
/** Sets all coefficients in this expression to \a value.
@@ -329,9 +329,9 @@ EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& value)
* \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
*/
template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& value)
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
{
- return derived() = Constant(rows(), cols(), value);
+ return derived() = Constant(rows(), cols(), val);
}
/** Resizes to the given \a size, and sets all coefficients in this expression to the given \a value.
@@ -345,10 +345,10 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& value
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setConstant(Index size, const Scalar& value)
+PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
{
resize(size);
- return setConstant(value);
+ return setConstant(val);
}
/** Resizes to the given size, and sets all coefficients in this expression to the given \a value.
@@ -364,10 +364,10 @@ PlainObjectBase<Derived>::setConstant(Index size, const Scalar& value)
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& value)
+PlainObjectBase<Derived>::setConstant(Index nbRows, Index nbCols, const Scalar& val)
{
- resize(rows, cols);
- return setConstant(value);
+ resize(nbRows, nbCols);
+ return setConstant(val);
}
/**
@@ -384,10 +384,10 @@ PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& valu
* \sa CwiseNullaryOp
*/
template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index size, const Scalar& low, const Scalar& high)
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
- return derived() = Derived::NullaryExpr(size, internal::linspaced_op<Scalar,false>(low,high,size));
+ return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar,false>(low,high,newSize));
}
/**
@@ -425,9 +425,9 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low,
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Zero(Index rows, Index cols)
+DenseBase<Derived>::Zero(Index nbRows, Index nbCols)
{
- return Constant(rows, cols, Scalar(0));
+ return Constant(nbRows, nbCols, Scalar(0));
}
/** \returns an expression of a zero vector.
@@ -479,7 +479,7 @@ DenseBase<Derived>::Zero()
* \sa class CwiseNullaryOp, Zero()
*/
template<typename Derived>
-bool DenseBase<Derived>::isZero(RealScalar prec) const
+bool DenseBase<Derived>::isZero(const RealScalar& prec) const
{
for(Index j = 0; j < cols(); ++j)
for(Index i = 0; i < rows(); ++i)
@@ -512,9 +512,9 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setZero(Index size)
+PlainObjectBase<Derived>::setZero(Index newSize)
{
- resize(size);
+ resize(newSize);
return setConstant(Scalar(0));
}
@@ -530,9 +530,9 @@ PlainObjectBase<Derived>::setZero(Index size)
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setZero(Index rows, Index cols)
+PlainObjectBase<Derived>::setZero(Index nbRows, Index nbCols)
{
- resize(rows, cols);
+ resize(nbRows, nbCols);
return setConstant(Scalar(0));
}
@@ -554,9 +554,9 @@ PlainObjectBase<Derived>::setZero(Index rows, Index cols)
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones(Index rows, Index cols)
+DenseBase<Derived>::Ones(Index nbRows, Index nbCols)
{
- return Constant(rows, cols, Scalar(1));
+ return Constant(nbRows, nbCols, Scalar(1));
}
/** \returns an expression of a vector where all coefficients equal one.
@@ -577,9 +577,9 @@ DenseBase<Derived>::Ones(Index rows, Index cols)
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones(Index size)
+DenseBase<Derived>::Ones(Index newSize)
{
- return Constant(size, Scalar(1));
+ return Constant(newSize, Scalar(1));
}
/** \returns an expression of a fixed-size matrix or vector where all coefficients equal one.
@@ -609,7 +609,7 @@ DenseBase<Derived>::Ones()
*/
template<typename Derived>
bool DenseBase<Derived>::isOnes
-(RealScalar prec) const
+(const RealScalar& prec) const
{
return isApproxToConstant(Scalar(1), prec);
}
@@ -638,9 +638,9 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setOnes(Index size)
+PlainObjectBase<Derived>::setOnes(Index newSize)
{
- resize(size);
+ resize(newSize);
return setConstant(Scalar(1));
}
@@ -656,9 +656,9 @@ PlainObjectBase<Derived>::setOnes(Index size)
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setOnes(Index rows, Index cols)
+PlainObjectBase<Derived>::setOnes(Index nbRows, Index nbCols)
{
- resize(rows, cols);
+ resize(nbRows, nbCols);
return setConstant(Scalar(1));
}
@@ -680,9 +680,9 @@ PlainObjectBase<Derived>::setOnes(Index rows, Index cols)
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
-MatrixBase<Derived>::Identity(Index rows, Index cols)
+MatrixBase<Derived>::Identity(Index nbRows, Index nbCols)
{
- return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_identity_op<Scalar>());
+ return DenseBase<Derived>::NullaryExpr(nbRows, nbCols, internal::scalar_identity_op<Scalar>());
}
/** \returns an expression of the identity matrix (not necessarily square).
@@ -714,7 +714,7 @@ MatrixBase<Derived>::Identity()
*/
template<typename Derived>
bool MatrixBase<Derived>::isIdentity
-(RealScalar prec) const
+(const RealScalar& prec) const
{
for(Index j = 0; j < cols(); ++j)
{
@@ -785,9 +785,9 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
* \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()
*/
template<typename Derived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index cols)
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index nbRows, Index nbCols)
{
- derived().resize(rows, cols);
+ derived().resize(nbRows, nbCols);
return setIdentity();
}
@@ -798,10 +798,10 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index
* \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/
template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index size, Index i)
+EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index newSize, Index i)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
- return BasisReturnType(SquareMatrixType::Identity(size,size), i);
+ return BasisReturnType(SquareMatrixType::Identity(newSize,newSize), i);
}
/** \returns an expression of the i-th unit (basis) vector.
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/CwiseUnaryOp.h b/resources/3rdparty/eigen/Eigen/src/Core/CwiseUnaryOp.h
index 063355ae5..f2de749f9 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/CwiseUnaryOp.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/CwiseUnaryOp.h
@@ -98,15 +98,15 @@ class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
typedef typename internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
- EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
+ EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
{
- return derived().functor()(derived().nestedExpression().coeff(row, col));
+ return derived().functor()(derived().nestedExpression().coeff(rowId, colId));
}
template<int LoadMode>
- EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+ EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
{
- return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(row, col));
+ return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(rowId, colId));
}
EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/DenseBase.h b/resources/3rdparty/eigen/Eigen/src/Core/DenseBase.h
index 1cc0314ef..8dc593174 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/DenseBase.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/DenseBase.h
@@ -204,21 +204,21 @@ template<typename Derived> class DenseBase
* Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
* nothing else.
*/
- void resize(Index size)
+ void resize(Index newSize)
{
- EIGEN_ONLY_USED_FOR_DEBUG(size);
- eigen_assert(size == this->size()
+ EIGEN_ONLY_USED_FOR_DEBUG(newSize);
+ eigen_assert(newSize == this->size()
&& "DenseBase::resize() does not actually allow to resize.");
}
/** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
* Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
* nothing else.
*/
- void resize(Index rows, Index cols)
+ void resize(Index nbRows, Index nbCols)
{
- EIGEN_ONLY_USED_FOR_DEBUG(rows);
- EIGEN_ONLY_USED_FOR_DEBUG(cols);
- eigen_assert(rows == this->rows() && cols == this->cols()
+ EIGEN_ONLY_USED_FOR_DEBUG(nbRows);
+ EIGEN_ONLY_USED_FOR_DEBUG(nbCols);
+ eigen_assert(nbRows == this->rows() && nbCols == this->cols()
&& "DenseBase::resize() does not actually allow to resize.");
}
@@ -348,17 +348,17 @@ template<typename Derived> class DenseBase
template<typename OtherDerived>
bool isApprox(const DenseBase<OtherDerived>& other,
- RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+ const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
bool isMuchSmallerThan(const RealScalar& other,
- RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+ const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
template<typename OtherDerived>
bool isMuchSmallerThan(const DenseBase<OtherDerived>& other,
- RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+ const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
- bool isApproxToConstant(const Scalar& value, RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
- bool isConstant(const Scalar& value, RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
- bool isZero(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
- bool isOnes(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+ bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+ bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+ bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+ bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
inline Derived& operator*=(const Scalar& other);
inline Derived& operator/=(const Scalar& other);
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/DenseCoeffsBase.h b/resources/3rdparty/eigen/Eigen/src/Core/DenseCoeffsBase.h
index 72704c2d7..3c890f215 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/DenseCoeffsBase.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/DenseCoeffsBase.h
@@ -427,22 +427,22 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
template<int StoreMode>
EIGEN_STRONG_INLINE void writePacket
- (Index row, Index col, const typename internal::packet_traits<Scalar>::type& x)
+ (Index row, Index col, const typename internal::packet_traits<Scalar>::type& val)
{
eigen_internal_assert(row >= 0 && row < rows()
&& col >= 0 && col < cols());
- derived().template writePacket<StoreMode>(row,col,x);
+ derived().template writePacket<StoreMode>(row,col,val);
}
/** \internal */
template<int StoreMode>
EIGEN_STRONG_INLINE void writePacketByOuterInner
- (Index outer, Index inner, const typename internal::packet_traits<Scalar>::type& x)
+ (Index outer, Index inner, const typename internal::packet_traits<Scalar>::type& val)
{
writePacket<StoreMode>(rowIndexByOuterInner(outer, inner),
colIndexByOuterInner(outer, inner),
- x);
+ val);
}
/** \internal
@@ -456,10 +456,10 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
*/
template<int StoreMode>
EIGEN_STRONG_INLINE void writePacket
- (Index index, const typename internal::packet_traits<Scalar>::type& x)
+ (Index index, const typename internal::packet_traits<Scalar>::type& val)
{
eigen_internal_assert(index >= 0 && index < size());
- derived().template writePacket<StoreMode>(index,x);
+ derived().template writePacket<StoreMode>(index,val);
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/DenseStorage.h b/resources/3rdparty/eigen/Eigen/src/Core/DenseStorage.h
index 1fc2daf2c..9d34ec934 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/DenseStorage.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/DenseStorage.h
@@ -35,8 +35,16 @@ template <typename T, int Size, int MatrixOrArrayOptions,
struct plain_array
{
T array[Size];
- plain_array() {}
- plain_array(constructor_without_unaligned_array_assert) {}
+
+ plain_array()
+ {
+ EIGEN_STATIC_ASSERT(Size * sizeof(T) <= 128 * 128 * 8, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+ }
+
+ plain_array(constructor_without_unaligned_array_assert)
+ {
+ EIGEN_STATIC_ASSERT(Size * sizeof(T) <= 128 * 128 * 8, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+ }
};
#ifdef EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
@@ -53,8 +61,17 @@ template <typename T, int Size, int MatrixOrArrayOptions>
struct plain_array<T, Size, MatrixOrArrayOptions, 16>
{
EIGEN_USER_ALIGN16 T array[Size];
- plain_array() { EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf) }
- plain_array(constructor_without_unaligned_array_assert) {}
+
+ plain_array()
+ {
+ EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf);
+ EIGEN_STATIC_ASSERT(Size * sizeof(T) <= 128 * 128 * 8, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+ }
+
+ plain_array(constructor_without_unaligned_array_assert)
+ {
+ EIGEN_STATIC_ASSERT(Size * sizeof(T) <= 128 * 128 * 8, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+ }
};
template <typename T, int MatrixOrArrayOptions, int Alignment>
@@ -135,13 +152,13 @@ template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic
inline explicit DenseStorage() : m_rows(0), m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
- inline DenseStorage(DenseIndex, DenseIndex rows, DenseIndex cols) : m_rows(rows), m_cols(cols) {}
+ inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
inline void swap(DenseStorage& other)
{ std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
- inline DenseIndex rows(void) const {return m_rows;}
- inline DenseIndex cols(void) const {return m_cols;}
- inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
- inline void resize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
+ inline DenseIndex rows() const {return m_rows;}
+ inline DenseIndex cols() const {return m_cols;}
+ inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
+ inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
};
@@ -155,12 +172,12 @@ template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Si
inline explicit DenseStorage() : m_rows(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
- inline DenseStorage(DenseIndex, DenseIndex rows, DenseIndex) : m_rows(rows) {}
+ inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
inline DenseIndex rows(void) const {return m_rows;}
inline DenseIndex cols(void) const {return _Cols;}
- inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
- inline void resize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
+ inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+ inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
};
@@ -174,12 +191,12 @@ template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Si
inline explicit DenseStorage() : m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
- inline DenseStorage(DenseIndex, DenseIndex, DenseIndex cols) : m_cols(cols) {}
+ inline DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
inline DenseIndex rows(void) const {return _Rows;}
inline DenseIndex cols(void) const {return m_cols;}
- inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
- inline void resize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
+ inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
+ inline void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
inline const T *data() const { return m_data.array; }
inline T *data() { return m_data.array; }
};
@@ -194,21 +211,21 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
inline explicit DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert)
: m_data(0), m_rows(0), m_cols(0) {}
- inline DenseStorage(DenseIndex size, DenseIndex rows, DenseIndex cols)
- : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols)
+ inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+ : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows), m_cols(nbCols)
{ EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
inline void swap(DenseStorage& other)
{ std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
inline DenseIndex rows(void) const {return m_rows;}
inline DenseIndex cols(void) const {return m_cols;}
- inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex cols)
+ inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
{
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
- m_rows = rows;
- m_cols = cols;
+ m_rows = nbRows;
+ m_cols = nbCols;
}
- void resize(DenseIndex size, DenseIndex rows, DenseIndex cols)
+ void resize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
{
if(size != m_rows*m_cols)
{
@@ -219,8 +236,8 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
m_data = 0;
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
}
- m_rows = rows;
- m_cols = cols;
+ m_rows = nbRows;
+ m_cols = nbCols;
}
inline const T *data() const { return m_data; }
inline T *data() { return m_data; }
@@ -234,18 +251,18 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
public:
inline explicit DenseStorage() : m_data(0), m_cols(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
- inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
+ inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
{ EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
static inline DenseIndex rows(void) {return _Rows;}
inline DenseIndex cols(void) const {return m_cols;}
- inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex cols)
+ inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
{
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
- m_cols = cols;
+ m_cols = nbCols;
}
- EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex cols)
+ EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex nbCols)
{
if(size != _Rows*m_cols)
{
@@ -256,7 +273,7 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
m_data = 0;
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
}
- m_cols = cols;
+ m_cols = nbCols;
}
inline const T *data() const { return m_data; }
inline T *data() { return m_data; }
@@ -270,18 +287,18 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
public:
inline explicit DenseStorage() : m_data(0), m_rows(0) {}
inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
- inline DenseStorage(DenseIndex size, DenseIndex rows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
+ inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
{ EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
inline DenseIndex rows(void) const {return m_rows;}
static inline DenseIndex cols(void) {return _Cols;}
- inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex)
+ inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
{
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
- m_rows = rows;
+ m_rows = nbRows;
}
- EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex rows, DenseIndex)
+ EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex nbRows, DenseIndex)
{
if(size != m_rows*_Cols)
{
@@ -292,7 +309,7 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
m_data = 0;
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
}
- m_rows = rows;
+ m_rows = nbRows;
}
inline const T *data() const { return m_data; }
inline T *data() { return m_data; }
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Diagonal.h b/resources/3rdparty/eigen/Eigen/src/Core/Diagonal.h
index 16261968a..0927e9969 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Diagonal.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Diagonal.h
@@ -41,12 +41,12 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
typedef typename MatrixType::StorageKind StorageKind;
enum {
- RowsAtCompileTime = (int(DiagIndex) == Dynamic || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
- : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
- MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
+ RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
+ : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+ MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
ColsAtCompileTime = 1,
MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
- : DiagIndex == Dynamic ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
+ : DiagIndex == DynamicIndex ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
MatrixType::MaxColsAtCompileTime)
: (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
@@ -61,15 +61,16 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
};
}
-template<typename MatrixType, int DiagIndex> class Diagonal
- : public internal::dense_xpr_base< Diagonal<MatrixType,DiagIndex> >::type
+template<typename MatrixType, int _DiagIndex> class Diagonal
+ : public internal::dense_xpr_base< Diagonal<MatrixType,_DiagIndex> >::type
{
public:
+ enum { DiagIndex = _DiagIndex };
typedef typename internal::dense_xpr_base<Diagonal>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
- inline Diagonal(MatrixType& matrix, Index index = DiagIndex) : m_matrix(matrix), m_index(index) {}
+ inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
@@ -113,20 +114,20 @@ template<typename MatrixType, int DiagIndex> class Diagonal
return m_matrix.coeff(row+rowOffset(), row+colOffset());
}
- inline Scalar& coeffRef(Index index)
+ inline Scalar& coeffRef(Index idx)
{
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
- return m_matrix.const_cast_derived().coeffRef(index+rowOffset(), index+colOffset());
+ return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
}
- inline const Scalar& coeffRef(Index index) const
+ inline const Scalar& coeffRef(Index idx) const
{
- return m_matrix.const_cast_derived().coeffRef(index+rowOffset(), index+colOffset());
+ return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
}
- inline CoeffReturnType coeff(Index index) const
+ inline CoeffReturnType coeff(Index idx) const
{
- return m_matrix.coeff(index+rowOffset(), index+colOffset());
+ return m_matrix.coeff(idx+rowOffset(), idx+colOffset());
}
const typename internal::remove_all<typename MatrixType::Nested>::type&
@@ -142,7 +143,7 @@ template<typename MatrixType, int DiagIndex> class Diagonal
protected:
typename MatrixType::Nested m_matrix;
- const internal::variable_if_dynamic<Index, DiagIndex> m_index;
+ const internal::variable_if_dynamicindex<Index, DiagIndex> m_index;
private:
// some compilers may fail to optimize std::max etc in case of compile-time constants...
@@ -189,18 +190,18 @@ MatrixBase<Derived>::diagonal() const
*
* \sa MatrixBase::diagonal(), class Diagonal */
template<typename Derived>
-inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Dynamic>::Type
+inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<DynamicIndex>::Type
MatrixBase<Derived>::diagonal(Index index)
{
- return typename DiagonalIndexReturnType<Dynamic>::Type(derived(), index);
+ return typename DiagonalIndexReturnType<DynamicIndex>::Type(derived(), index);
}
/** This is the const version of diagonal(Index). */
template<typename Derived>
-inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Dynamic>::Type
+inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<DynamicIndex>::Type
MatrixBase<Derived>::diagonal(Index index) const
{
- return typename ConstDiagonalIndexReturnType<Dynamic>::Type(derived(), index);
+ return typename ConstDiagonalIndexReturnType<DynamicIndex>::Type(derived(), index);
}
/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/DiagonalMatrix.h b/resources/3rdparty/eigen/Eigen/src/Core/DiagonalMatrix.h
index 88190da68..da0264b0e 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/DiagonalMatrix.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/DiagonalMatrix.h
@@ -20,6 +20,7 @@ class DiagonalBase : public EigenBase<Derived>
public:
typedef typename internal::traits<Derived>::DiagonalVectorType DiagonalVectorType;
typedef typename DiagonalVectorType::Scalar Scalar;
+ typedef typename DiagonalVectorType::RealScalar RealScalar;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Index Index;
@@ -65,6 +66,17 @@ class DiagonalBase : public EigenBase<Derived>
return diagonal().cwiseInverse();
}
+ inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
+ operator*(const Scalar& scalar) const
+ {
+ return diagonal() * scalar;
+ }
+ friend inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
+ operator*(const Scalar& scalar, const DiagonalBase& other)
+ {
+ return other.diagonal() * scalar;
+ }
+
#ifdef EIGEN2_SUPPORT
template<typename OtherDerived>
bool isApprox(const DiagonalBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
@@ -238,7 +250,7 @@ class DiagonalWrapper
#endif
/** Constructor from expression of diagonal coefficients to wrap. */
- inline DiagonalWrapper(DiagonalVectorType& diagonal) : m_diagonal(diagonal) {}
+ inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
/** \returns a const reference to the wrapped expression of diagonal coefficients. */
const DiagonalVectorType& diagonal() const { return m_diagonal; }
@@ -272,7 +284,7 @@ MatrixBase<Derived>::asDiagonal() const
* \sa asDiagonal()
*/
template<typename Derived>
-bool MatrixBase<Derived>::isDiagonal(RealScalar prec) const
+bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
{
if(cols() != rows()) return false;
RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/DiagonalProduct.h b/resources/3rdparty/eigen/Eigen/src/Core/DiagonalProduct.h
index 598c6b3e1..8c7b2d978 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/DiagonalProduct.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/DiagonalProduct.h
@@ -103,9 +103,9 @@ class DiagonalProduct : internal::no_assignment_operator,
template<typename Derived>
template<typename DiagonalDerived>
inline const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
-MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &diagonal) const
+MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &a_diagonal) const
{
- return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), diagonal.derived());
+ return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), a_diagonal.derived());
}
/** \returns the diagonal matrix product of \c *this by the matrix \a matrix.
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Dot.h b/resources/3rdparty/eigen/Eigen/src/Core/Dot.h
index ae9274e36..a7a18c939 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Dot.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Dot.h
@@ -223,7 +223,7 @@ MatrixBase<Derived>::lpNorm() const
template<typename Derived>
template<typename OtherDerived>
bool MatrixBase<Derived>::isOrthogonal
-(const MatrixBase<OtherDerived>& other, RealScalar prec) const
+(const MatrixBase<OtherDerived>& other, const RealScalar& prec) const
{
typename internal::nested<Derived,2>::type nested(derived());
typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
@@ -242,7 +242,7 @@ bool MatrixBase<Derived>::isOrthogonal
* Output: \verbinclude MatrixBase_isUnitary.out
*/
template<typename Derived>
-bool MatrixBase<Derived>::isUnitary(RealScalar prec) const
+bool MatrixBase<Derived>::isUnitary(const RealScalar& prec) const
{
typename Derived::Nested nested(derived());
for(Index i = 0; i < cols(); ++i)
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Functors.h b/resources/3rdparty/eigen/Eigen/src/Core/Functors.h
index 278c46c6b..09388972a 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Functors.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Functors.h
@@ -204,21 +204,28 @@ struct functor_traits<scalar_difference_op<Scalar> > {
*
* \sa class CwiseBinaryOp, Cwise::operator/()
*/
-template<typename Scalar> struct scalar_quotient_op {
+template<typename LhsScalar,typename RhsScalar> struct scalar_quotient_op {
+ enum {
+ // TODO vectorize mixed product
+ Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasDiv && packet_traits<RhsScalar>::HasDiv
+ };
+ typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op)
- EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a / b; }
+ EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a / b; }
template<typename Packet>
EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
{ return internal::pdiv(a,b); }
};
-template<typename Scalar>
-struct functor_traits<scalar_quotient_op<Scalar> > {
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_quotient_op<LhsScalar,RhsScalar> > {
enum {
- Cost = 2 * NumTraits<Scalar>::MulCost,
- PacketAccess = packet_traits<Scalar>::HasDiv
+ Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost), // rough estimate!
+ PacketAccess = scalar_quotient_op<LhsScalar,RhsScalar>::Vectorizable
};
};
+
+
/** \internal
* \brief Template functor to compute the and of two booleans
*
@@ -447,7 +454,7 @@ struct functor_traits<scalar_log_op<Scalar> >
* indeed it seems better to declare m_other as a Packet and do the pset1() once
* in the constructor. However, in practice:
* - GCC does not like m_other as a Packet and generate a load every time it needs it
- * - on the other hand GCC is able to moves the pset1() away the loop :)
+ * - on the other hand GCC is able to moves the pset1() outside the loop :)
* - simpler code ;)
* (ICC and gcc 4.4 seems to perform well in both cases, the issue is visible with y = a*x + b*y)
*/
@@ -478,33 +485,6 @@ template<typename Scalar1,typename Scalar2>
struct functor_traits<scalar_multiple2_op<Scalar1,Scalar2> >
{ enum { Cost = NumTraits<Scalar1>::MulCost, PacketAccess = false }; };
-template<typename Scalar, bool IsInteger>
-struct scalar_quotient1_impl {
- typedef typename packet_traits<Scalar>::type Packet;
- // FIXME default copy constructors seems bugged with std::complex<>
- EIGEN_STRONG_INLINE scalar_quotient1_impl(const scalar_quotient1_impl& other) : m_other(other.m_other) { }
- EIGEN_STRONG_INLINE scalar_quotient1_impl(const Scalar& other) : m_other(static_cast<Scalar>(1) / other) {}
- EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; }
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
- { return internal::pmul(a, pset1<Packet>(m_other)); }
- const Scalar m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_quotient1_impl<Scalar,false> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
-
-template<typename Scalar>
-struct scalar_quotient1_impl<Scalar,true> {
- // FIXME default copy constructors seems bugged with std::complex<>
- EIGEN_STRONG_INLINE scalar_quotient1_impl(const scalar_quotient1_impl& other) : m_other(other.m_other) { }
- EIGEN_STRONG_INLINE scalar_quotient1_impl(const Scalar& other) : m_other(other) {}
- EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
- typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_quotient1_impl<Scalar,true> >
-{ enum { Cost = 2 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
/** \internal
* \brief Template functor to divide a scalar by a fixed other one
*
@@ -514,14 +494,19 @@ struct functor_traits<scalar_quotient1_impl<Scalar,true> >
* \sa class CwiseUnaryOp, MatrixBase::operator/
*/
template<typename Scalar>
-struct scalar_quotient1_op : scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger > {
- EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other)
- : scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger >(other) {}
+struct scalar_quotient1_op {
+ typedef typename packet_traits<Scalar>::type Packet;
+ // FIXME default copy constructors seems bugged with std::complex<>
+ EIGEN_STRONG_INLINE scalar_quotient1_op(const scalar_quotient1_op& other) : m_other(other.m_other) { }
+ EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other) : m_other(other) {}
+ EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+ { return internal::pdiv(a, pset1<Packet>(m_other)); }
+ typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
};
template<typename Scalar>
struct functor_traits<scalar_quotient1_op<Scalar> >
-: functor_traits<scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger> >
-{};
+{ enum { Cost = 2 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
// nullary functors
@@ -660,6 +645,7 @@ template<typename Scalar> struct functor_has_linear_access<scalar_identity_op<Sc
template<typename Functor> struct functor_allows_mixing_real_and_complex { enum { ret = 0 }; };
template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_conj_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
+template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_quotient_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
/** \internal
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Fuzzy.h b/resources/3rdparty/eigen/Eigen/src/Core/Fuzzy.h
index d74edcfdb..8fb9a01dd 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Fuzzy.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Fuzzy.h
@@ -19,7 +19,7 @@ namespace internal
template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
struct isApprox_selector
{
- static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec)
+ static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
{
using std::min;
typename internal::nested<Derived,2>::type nested(x);
@@ -31,7 +31,7 @@ struct isApprox_selector
template<typename Derived, typename OtherDerived>
struct isApprox_selector<Derived, OtherDerived, true>
{
- static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar)
+ static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&)
{
return x.matrix() == y.matrix();
}
@@ -40,7 +40,7 @@ struct isApprox_selector<Derived, OtherDerived, true>
template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
struct isMuchSmallerThan_object_selector
{
- static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec)
+ static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
{
return x.cwiseAbs2().sum() <= abs2(prec) * y.cwiseAbs2().sum();
}
@@ -49,7 +49,7 @@ struct isMuchSmallerThan_object_selector
template<typename Derived, typename OtherDerived>
struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
{
- static bool run(const Derived& x, const OtherDerived&, typename Derived::RealScalar)
+ static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&)
{
return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
}
@@ -58,7 +58,7 @@ struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
template<typename Derived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
struct isMuchSmallerThan_scalar_selector
{
- static bool run(const Derived& x, const typename Derived::RealScalar& y, typename Derived::RealScalar prec)
+ static bool run(const Derived& x, const typename Derived::RealScalar& y, const typename Derived::RealScalar& prec)
{
return x.cwiseAbs2().sum() <= abs2(prec * y);
}
@@ -67,7 +67,7 @@ struct isMuchSmallerThan_scalar_selector
template<typename Derived>
struct isMuchSmallerThan_scalar_selector<Derived, true>
{
- static bool run(const Derived& x, const typename Derived::RealScalar&, typename Derived::RealScalar)
+ static bool run(const Derived& x, const typename Derived::RealScalar&, const typename Derived::RealScalar&)
{
return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
}
@@ -97,7 +97,7 @@ template<typename Derived>
template<typename OtherDerived>
bool DenseBase<Derived>::isApprox(
const DenseBase<OtherDerived>& other,
- RealScalar prec
+ const RealScalar& prec
) const
{
return internal::isApprox_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
@@ -119,7 +119,7 @@ bool DenseBase<Derived>::isApprox(
template<typename Derived>
bool DenseBase<Derived>::isMuchSmallerThan(
const typename NumTraits<Scalar>::Real& other,
- RealScalar prec
+ const RealScalar& prec
) const
{
return internal::isMuchSmallerThan_scalar_selector<Derived>::run(derived(), other, prec);
@@ -139,7 +139,7 @@ template<typename Derived>
template<typename OtherDerived>
bool DenseBase<Derived>::isMuchSmallerThan(
const DenseBase<OtherDerived>& other,
- RealScalar prec
+ const RealScalar& prec
) const
{
return internal::isMuchSmallerThan_object_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/GeneralProduct.h b/resources/3rdparty/eigen/Eigen/src/Core/GeneralProduct.h
index bfc2a67b1..9abc7b286 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/GeneralProduct.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/GeneralProduct.h
@@ -311,7 +311,7 @@ class GeneralProduct<Lhs, Rhs, GemvProduct>
typedef typename Lhs::Scalar LhsScalar;
typedef typename Rhs::Scalar RhsScalar;
- GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
+ GeneralProduct(const Lhs& a_lhs, const Rhs& a_rhs) : Base(a_lhs,a_rhs)
{
// EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
// YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Map.h b/resources/3rdparty/eigen/Eigen/src/Core/Map.h
index 15a19226e..2b0a44697 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Map.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Map.h
@@ -148,8 +148,8 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
* \param size the size of the vector expression
* \param stride optional Stride object, passing the strides.
*/
- inline Map(PointerArgType data, Index size, const StrideType& stride = StrideType())
- : Base(cast_to_pointer_type(data), size), m_stride(stride)
+ inline Map(PointerArgType dataPtr, Index a_size, const StrideType& a_stride = StrideType())
+ : Base(cast_to_pointer_type(dataPtr), a_size), m_stride(a_stride)
{
PlainObjectType::Base::_check_template_params();
}
@@ -161,8 +161,8 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
* \param cols the number of columns of the matrix expression
* \param stride optional Stride object, passing the strides.
*/
- inline Map(PointerArgType data, Index rows, Index cols, const StrideType& stride = StrideType())
- : Base(cast_to_pointer_type(data), rows, cols), m_stride(stride)
+ inline Map(PointerArgType dataPtr, Index nbRows, Index nbCols, const StrideType& a_stride = StrideType())
+ : Base(cast_to_pointer_type(dataPtr), nbRows, nbCols), m_stride(a_stride)
{
PlainObjectType::Base::_check_template_params();
}
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/MapBase.h b/resources/3rdparty/eigen/Eigen/src/Core/MapBase.h
index a388d61ea..6876de588 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/MapBase.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/MapBase.h
@@ -87,9 +87,9 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
*/
inline const Scalar* data() const { return m_data; }
- inline const Scalar& coeff(Index row, Index col) const
+ inline const Scalar& coeff(Index rowId, Index colId) const
{
- return m_data[col * colStride() + row * rowStride()];
+ return m_data[colId * colStride() + rowId * rowStride()];
}
inline const Scalar& coeff(Index index) const
@@ -98,9 +98,9 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
return m_data[index * innerStride()];
}
- inline const Scalar& coeffRef(Index row, Index col) const
+ inline const Scalar& coeffRef(Index rowId, Index colId) const
{
- return this->m_data[col * colStride() + row * rowStride()];
+ return this->m_data[colId * colStride() + rowId * rowStride()];
}
inline const Scalar& coeffRef(Index index) const
@@ -110,10 +110,10 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
}
template<int LoadMode>
- inline PacketScalar packet(Index row, Index col) const
+ inline PacketScalar packet(Index rowId, Index colId) const
{
return internal::ploadt<PacketScalar, LoadMode>
- (m_data + (col * colStride() + row * rowStride()));
+ (m_data + (colId * colStride() + rowId * rowStride()));
}
template<int LoadMode>
@@ -123,29 +123,29 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride());
}
- inline MapBase(PointerType data) : m_data(data), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
+ inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
{
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
checkSanity();
}
- inline MapBase(PointerType data, Index size)
- : m_data(data),
- m_rows(RowsAtCompileTime == Dynamic ? size : Index(RowsAtCompileTime)),
- m_cols(ColsAtCompileTime == Dynamic ? size : Index(ColsAtCompileTime))
+ inline MapBase(PointerType dataPtr, Index vecSize)
+ : m_data(dataPtr),
+ m_rows(RowsAtCompileTime == Dynamic ? vecSize : Index(RowsAtCompileTime)),
+ m_cols(ColsAtCompileTime == Dynamic ? vecSize : Index(ColsAtCompileTime))
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
- eigen_assert(size >= 0);
- eigen_assert(data == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == size);
+ eigen_assert(vecSize >= 0);
+ eigen_assert(dataPtr == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == vecSize);
checkSanity();
}
- inline MapBase(PointerType data, Index rows, Index cols)
- : m_data(data), m_rows(rows), m_cols(cols)
+ inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols)
+ : m_data(dataPtr), m_rows(nbRows), m_cols(nbCols)
{
- eigen_assert( (data == 0)
- || ( rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
- && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)));
+ eigen_assert( (dataPtr == 0)
+ || ( nbRows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
+ && nbCols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols)));
checkSanity();
}
@@ -210,23 +210,23 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
}
template<int StoreMode>
- inline void writePacket(Index row, Index col, const PacketScalar& x)
+ inline void writePacket(Index row, Index col, const PacketScalar& val)
{
internal::pstoret<Scalar, PacketScalar, StoreMode>
- (this->m_data + (col * colStride() + row * rowStride()), x);
+ (this->m_data + (col * colStride() + row * rowStride()), val);
}
template<int StoreMode>
- inline void writePacket(Index index, const PacketScalar& x)
+ inline void writePacket(Index index, const PacketScalar& val)
{
EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
internal::pstoret<Scalar, PacketScalar, StoreMode>
- (this->m_data + index * innerStride(), x);
+ (this->m_data + index * innerStride(), val);
}
- explicit inline MapBase(PointerType data) : Base(data) {}
- inline MapBase(PointerType data, Index size) : Base(data, size) {}
- inline MapBase(PointerType data, Index rows, Index cols) : Base(data, rows, cols) {}
+ explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {}
+ inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {}
+ inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols) : Base(dataPtr, nbRows, nbCols) {}
Derived& operator=(const MapBase& other)
{
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/MathFunctions.h b/resources/3rdparty/eigen/Eigen/src/Core/MathFunctions.h
index 05e913f2f..5b57c2ff2 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/MathFunctions.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/MathFunctions.h
@@ -519,6 +519,53 @@ inline EIGEN_MATHFUNC_RETVAL(atan2, Scalar) atan2(const Scalar& x, const Scalar&
return EIGEN_MATHFUNC_IMPL(atan2, Scalar)::run(x, y);
}
+/****************************************************************************
+* Implementation of atanh2 *
+****************************************************************************/
+
+template<typename Scalar, bool IsInteger>
+struct atanh2_default_impl
+{
+ typedef Scalar retval;
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+ static inline Scalar run(const Scalar& x, const Scalar& y)
+ {
+ using std::abs;
+ using std::log;
+ using std::sqrt;
+ Scalar z = x / y;
+ if (abs(z) > sqrt(NumTraits<RealScalar>::epsilon()))
+ return RealScalar(0.5) * log((y + x) / (y - x));
+ else
+ return z + z*z*z / RealScalar(3);
+ }
+};
+
+template<typename Scalar>
+struct atanh2_default_impl<Scalar, true>
+{
+ static inline Scalar run(const Scalar&, const Scalar&)
+ {
+ EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
+ return Scalar(0);
+ }
+};
+
+template<typename Scalar>
+struct atanh2_impl : atanh2_default_impl<Scalar, NumTraits<Scalar>::IsInteger> {};
+
+template<typename Scalar>
+struct atanh2_retval
+{
+ typedef Scalar type;
+};
+
+template<typename Scalar>
+inline EIGEN_MATHFUNC_RETVAL(atanh2, Scalar) atanh2(const Scalar& x, const Scalar& y)
+{
+ return EIGEN_MATHFUNC_IMPL(atanh2, Scalar)::run(x, y);
+}
+
/****************************************************************************
* Implementation of pow *
****************************************************************************/
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/MatrixBase.h b/resources/3rdparty/eigen/Eigen/src/Core/MatrixBase.h
index c1e0ed132..521bba18a 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/MatrixBase.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/MatrixBase.h
@@ -162,6 +162,9 @@ template<typename Derived> class MatrixBase
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename ProductDerived, typename Lhs, typename Rhs>
Derived& lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other);
+
+ template<typename ProductDerived, typename Lhs, typename Rhs>
+ Derived& lazyAssign(const MatrixPowerProductBase<ProductDerived, Lhs,Rhs>& other);
#endif // not EIGEN_PARSED_BY_DOXYGEN
template<typename OtherDerived>
@@ -224,11 +227,11 @@ template<typename Derived> class MatrixBase
// Note: The "MatrixBase::" prefixes are added to help MSVC9 to match these declarations with the later implementations.
// On the other hand they confuse MSVC8...
#if (defined _MSC_VER) && (_MSC_VER >= 1500) // 2008 or later
- typename MatrixBase::template DiagonalIndexReturnType<Dynamic>::Type diagonal(Index index);
- typename MatrixBase::template ConstDiagonalIndexReturnType<Dynamic>::Type diagonal(Index index) const;
+ typename MatrixBase::template DiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index);
+ typename MatrixBase::template ConstDiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index) const;
#else
- typename DiagonalIndexReturnType<Dynamic>::Type diagonal(Index index);
- typename ConstDiagonalIndexReturnType<Dynamic>::Type diagonal(Index index) const;
+ typename DiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index);
+ typename ConstDiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index) const;
#endif
#ifdef EIGEN2_SUPPORT
@@ -237,7 +240,7 @@ template<typename Derived> class MatrixBase
// huuuge hack. make Eigen2's matrix.part<Diagonal>() work in eigen3. Problem: Diagonal is now a class template instead
// of an integer constant. Solution: overload the part() method template wrt template parameters list.
- template<template<typename T, int n> class U>
+ template<template<typename T, int N> class U>
const DiagonalWrapper<ConstDiagonalReturnType> part() const
{ return diagonal().asDiagonal(); }
#endif // EIGEN2_SUPPORT
@@ -255,7 +258,7 @@ template<typename Derived> class MatrixBase
template<unsigned int UpLo> typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
const SparseView<Derived> sparseView(const Scalar& m_reference = Scalar(0),
- typename NumTraits<Scalar>::Real m_epsilon = NumTraits<Scalar>::dummy_precision()) const;
+ const typename NumTraits<Scalar>::Real& m_epsilon = NumTraits<Scalar>::dummy_precision()) const;
static const IdentityReturnType Identity();
static const IdentityReturnType Identity(Index rows, Index cols);
static const BasisReturnType Unit(Index size, Index i);
@@ -271,16 +274,16 @@ template<typename Derived> class MatrixBase
Derived& setIdentity();
Derived& setIdentity(Index rows, Index cols);
- bool isIdentity(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
- bool isDiagonal(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+ bool isIdentity(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+ bool isDiagonal(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
- bool isUpperTriangular(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
- bool isLowerTriangular(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+ bool isUpperTriangular(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+ bool isLowerTriangular(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
template<typename OtherDerived>
bool isOrthogonal(const MatrixBase<OtherDerived>& other,
- RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
- bool isUnitary(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+ const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+ bool isUnitary(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
/** \returns true if each coefficients of \c *this and \a other are all exactly equal.
* \warning When using floating point scalar values you probably should rather use a
@@ -454,6 +457,7 @@ template<typename Derived> class MatrixBase
const MatrixFunctionReturnValue<Derived> sin() const;
const MatrixSquareRootReturnValue<Derived> sqrt() const;
const MatrixLogarithmReturnValue<Derived> log() const;
+ const MatrixPowerReturnValue<Derived> pow(RealScalar p) const;
#ifdef EIGEN2_SUPPORT
template<typename ProductDerived, typename Lhs, typename Rhs>
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/NoAlias.h b/resources/3rdparty/eigen/Eigen/src/Core/NoAlias.h
index ecb3fa285..0112c865b 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/NoAlias.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/NoAlias.h
@@ -82,6 +82,11 @@ class NoAlias
{ return m_expression.derived() -= CoeffBasedProduct<Lhs,Rhs,NestByRefBit>(other.lhs(), other.rhs()); }
#endif
+ ExpressionType& expression() const
+ {
+ return m_expression;
+ }
+
protected:
ExpressionType& m_expression;
};
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/PermutationMatrix.h b/resources/3rdparty/eigen/Eigen/src/Core/PermutationMatrix.h
index bc29f8142..86b63ea14 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/PermutationMatrix.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/PermutationMatrix.h
@@ -139,9 +139,9 @@ class PermutationBase : public EigenBase<Derived>
/** Resizes to given size.
*/
- inline void resize(Index size)
+ inline void resize(Index newSize)
{
- indices().resize(size);
+ indices().resize(newSize);
}
/** Sets *this to be the identity permutation matrix */
@@ -153,9 +153,9 @@ class PermutationBase : public EigenBase<Derived>
/** Sets *this to be the identity permutation matrix of given size.
*/
- void setIdentity(Index size)
+ void setIdentity(Index newSize)
{
- resize(size);
+ resize(newSize);
setIdentity();
}
@@ -317,7 +317,7 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
* array's size.
*/
template<typename Other>
- explicit inline PermutationMatrix(const MatrixBase<Other>& indices) : m_indices(indices)
+ explicit inline PermutationMatrix(const MatrixBase<Other>& a_indices) : m_indices(a_indices)
{}
/** Convert the Transpositions \a tr to a permutation matrix */
@@ -406,12 +406,12 @@ class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,
typedef typename IndicesType::Scalar Index;
#endif
- inline Map(const Index* indices)
- : m_indices(indices)
+ inline Map(const Index* indicesPtr)
+ : m_indices(indicesPtr)
{}
- inline Map(const Index* indices, Index size)
- : m_indices(indices,size)
+ inline Map(const Index* indicesPtr, Index size)
+ : m_indices(indicesPtr,size)
{}
/** Copies the other permutation into *this */
@@ -490,8 +490,8 @@ class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesTyp
typedef typename Traits::IndicesType IndicesType;
#endif
- inline PermutationWrapper(const IndicesType& indices)
- : m_indices(indices)
+ inline PermutationWrapper(const IndicesType& a_indices)
+ : m_indices(a_indices)
{}
/** const version of indices(). */
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/PlainObjectBase.h b/resources/3rdparty/eigen/Eigen/src/Core/PlainObjectBase.h
index 71c74309a..bef79d3d7 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/PlainObjectBase.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/PlainObjectBase.h
@@ -21,18 +21,26 @@ namespace Eigen {
namespace internal {
-template<typename Index>
-EIGEN_ALWAYS_INLINE void check_rows_cols_for_overflow(Index rows, Index cols)
-{
- // http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
- // we assume Index is signed
- Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
- bool error = (rows < 0 || cols < 0) ? true
- : (rows == 0 || cols == 0) ? false
- : (rows > max_index / cols);
- if (error)
- throw_std_bad_alloc();
-}
+template<int MaxSizeAtCompileTime> struct check_rows_cols_for_overflow {
+ template<typename Index>
+ static EIGEN_ALWAYS_INLINE void run(Index, Index)
+ {
+ }
+};
+
+template<> struct check_rows_cols_for_overflow<Dynamic> {
+ template<typename Index>
+ static EIGEN_ALWAYS_INLINE void run(Index rows, Index cols)
+ {
+ // http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
+ // we assume Index is signed
+ Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
+ bool error = (rows == 0 || cols == 0) ? false
+ : (rows > max_index / cols);
+ if (error)
+ throw_std_bad_alloc();
+ }
+};
template <typename Derived, typename OtherDerived = Derived, bool IsVector = bool(Derived::IsVectorAtCompileTime)> struct conservative_resize_like_impl;
@@ -119,12 +127,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); }
EIGEN_STRONG_INLINE Index cols() const { return m_storage.cols(); }
- EIGEN_STRONG_INLINE const Scalar& coeff(Index row, Index col) const
+ EIGEN_STRONG_INLINE const Scalar& coeff(Index rowId, Index colId) const
{
if(Flags & RowMajorBit)
- return m_storage.data()[col + row * m_storage.cols()];
+ return m_storage.data()[colId + rowId * m_storage.cols()];
else // column-major
- return m_storage.data()[row + col * m_storage.rows()];
+ return m_storage.data()[rowId + colId * m_storage.rows()];
}
EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const
@@ -132,12 +140,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
return m_storage.data()[index];
}
- EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
+ EIGEN_STRONG_INLINE Scalar& coeffRef(Index rowId, Index colId)
{
if(Flags & RowMajorBit)
- return m_storage.data()[col + row * m_storage.cols()];
+ return m_storage.data()[colId + rowId * m_storage.cols()];
else // column-major
- return m_storage.data()[row + col * m_storage.rows()];
+ return m_storage.data()[rowId + colId * m_storage.rows()];
}
EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
@@ -145,12 +153,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
return m_storage.data()[index];
}
- EIGEN_STRONG_INLINE const Scalar& coeffRef(Index row, Index col) const
+ EIGEN_STRONG_INLINE const Scalar& coeffRef(Index rowId, Index colId) const
{
if(Flags & RowMajorBit)
- return m_storage.data()[col + row * m_storage.cols()];
+ return m_storage.data()[colId + rowId * m_storage.cols()];
else // column-major
- return m_storage.data()[row + col * m_storage.rows()];
+ return m_storage.data()[rowId + colId * m_storage.rows()];
}
EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const
@@ -160,12 +168,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** \internal */
template<int LoadMode>
- EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+ EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
{
return internal::ploadt<PacketScalar, LoadMode>
(m_storage.data() + (Flags & RowMajorBit
- ? col + row * m_storage.cols()
- : row + col * m_storage.rows()));
+ ? colId + rowId * m_storage.cols()
+ : rowId + colId * m_storage.rows()));
}
/** \internal */
@@ -177,19 +185,19 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
/** \internal */
template<int StoreMode>
- EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketScalar& x)
+ EIGEN_STRONG_INLINE void writePacket(Index rowId, Index colId, const PacketScalar& val)
{
internal::pstoret<Scalar, PacketScalar, StoreMode>
(m_storage.data() + (Flags & RowMajorBit
- ? col + row * m_storage.cols()
- : row + col * m_storage.rows()), x);
+ ? colId + rowId * m_storage.cols()
+ : rowId + colId * m_storage.rows()), val);
}
/** \internal */
template<int StoreMode>
- EIGEN_STRONG_INLINE void writePacket(Index index, const PacketScalar& x)
+ EIGEN_STRONG_INLINE void writePacket(Index index, const PacketScalar& val)
{
- internal::pstoret<Scalar, PacketScalar, StoreMode>(m_storage.data() + index, x);
+ internal::pstoret<Scalar, PacketScalar, StoreMode>(m_storage.data() + index, val);
}
/** \returns a const pointer to the data array of this matrix */
@@ -216,17 +224,22 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t)
*/
- EIGEN_STRONG_INLINE void resize(Index rows, Index cols)
- {
+ EIGEN_STRONG_INLINE void resize(Index nbRows, Index nbCols)
+ {
+ eigen_assert( EIGEN_IMPLIES(RowsAtCompileTime!=Dynamic,nbRows==RowsAtCompileTime)
+ && EIGEN_IMPLIES(ColsAtCompileTime!=Dynamic,nbCols==ColsAtCompileTime)
+ && EIGEN_IMPLIES(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic,nbRows<=MaxRowsAtCompileTime)
+ && EIGEN_IMPLIES(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic,nbCols<=MaxColsAtCompileTime)
+ && nbRows>=0 && nbCols>=0 && "Invalid sizes when resizing a matrix or array.");
+ internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(nbRows, nbCols);
#ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
- internal::check_rows_cols_for_overflow(rows, cols);
- Index size = rows*cols;
+ Index size = nbRows*nbCols;
bool size_changed = size != this->size();
- m_storage.resize(size, rows, cols);
+ m_storage.resize(size, nbRows, nbCols);
if(size_changed) EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
#else
- internal::check_rows_cols_for_overflow(rows, cols);
- m_storage.resize(rows*cols, rows, cols);
+ internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(nbRows, nbCols);
+ m_storage.resize(nbRows*nbCols, nbRows, nbCols);
#endif
}
@@ -244,7 +257,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
inline void resize(Index size)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(PlainObjectBase)
- eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == size);
+ eigen_assert(((SizeAtCompileTime == Dynamic && (MaxSizeAtCompileTime==Dynamic || size<=MaxSizeAtCompileTime)) || SizeAtCompileTime == size) && size>=0);
#ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
bool size_changed = size != this->size();
#endif
@@ -265,9 +278,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* \sa resize(Index,Index)
*/
- inline void resize(NoChange_t, Index cols)
+ inline void resize(NoChange_t, Index nbCols)
{
- resize(rows(), cols);
+ resize(rows(), nbCols);
}
/** Resizes the matrix, changing only the number of rows. For the parameter of type NoChange_t, just pass the special value \c NoChange
@@ -278,9 +291,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* \sa resize(Index,Index)
*/
- inline void resize(Index rows, NoChange_t)
+ inline void resize(Index nbRows, NoChange_t)
{
- resize(rows, cols());
+ resize(nbRows, cols());
}
/** Resizes \c *this to have the same dimensions as \a other.
@@ -294,7 +307,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
EIGEN_STRONG_INLINE void resizeLike(const EigenBase<OtherDerived>& _other)
{
const OtherDerived& other = _other.derived();
- internal::check_rows_cols_for_overflow(other.rows(), other.cols());
+ internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(other.rows(), other.cols());
const Index othersize = other.rows()*other.cols();
if(RowsAtCompileTime == 1)
{
@@ -318,9 +331,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
* Matrices are resized relative to the top-left element. In case values need to be
* appended to the matrix they will be uninitialized.
*/
- EIGEN_STRONG_INLINE void conservativeResize(Index rows, Index cols)
+ EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, Index nbCols)
{
- internal::conservative_resize_like_impl<Derived>::run(*this, rows, cols);
+ internal::conservative_resize_like_impl<Derived>::run(*this, nbRows, nbCols);
}
/** Resizes the matrix to \a rows x \a cols while leaving old values untouched.
@@ -330,10 +343,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* In case the matrix is growing, new rows will be uninitialized.
*/
- EIGEN_STRONG_INLINE void conservativeResize(Index rows, NoChange_t)
+ EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, NoChange_t)
{
// Note: see the comment in conservativeResize(Index,Index)
- conservativeResize(rows, cols());
+ conservativeResize(nbRows, cols());
}
/** Resizes the matrix to \a rows x \a cols while leaving old values untouched.
@@ -343,10 +356,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
*
* In case the matrix is growing, new columns will be uninitialized.
*/
- EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index cols)
+ EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index nbCols)
{
// Note: see the comment in conservativeResize(Index,Index)
- conservativeResize(rows(), cols);
+ conservativeResize(rows(), nbCols);
}
/** Resizes the vector to \a size while retaining old values.
@@ -416,8 +429,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
}
#endif
- EIGEN_STRONG_INLINE PlainObjectBase(Index size, Index rows, Index cols)
- : m_storage(size, rows, cols)
+ EIGEN_STRONG_INLINE PlainObjectBase(Index a_size, Index nbRows, Index nbCols)
+ : m_storage(a_size, nbRows, nbCols)
{
// _check_template_params();
// EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
@@ -439,7 +452,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
: m_storage(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
{
_check_template_params();
- internal::check_rows_cols_for_overflow(other.derived().rows(), other.derived().cols());
+ internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(other.derived().rows(), other.derived().cols());
Base::operator=(other.derived());
}
@@ -600,23 +613,19 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
}
template<typename T0, typename T1>
- EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
+ EIGEN_STRONG_INLINE void _init2(Index nbRows, Index nbCols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
{
EIGEN_STATIC_ASSERT(bool(NumTraits<T0>::IsInteger) &&
bool(NumTraits<T1>::IsInteger),
FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
- eigen_assert(rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
- && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
- internal::check_rows_cols_for_overflow(rows, cols);
- m_storage.resize(rows*cols,rows,cols);
- EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
+ resize(nbRows,nbCols);
}
template<typename T0, typename T1>
- EIGEN_STRONG_INLINE void _init2(const Scalar& x, const Scalar& y, typename internal::enable_if<Base::SizeAtCompileTime==2,T0>::type* = 0)
+ EIGEN_STRONG_INLINE void _init2(const Scalar& val0, const Scalar& val1, typename internal::enable_if<Base::SizeAtCompileTime==2,T0>::type* = 0)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2)
- m_storage.data()[0] = x;
- m_storage.data()[1] = y;
+ m_storage.data()[0] = val0;
+ m_storage.data()[1] = val1;
}
template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers>
@@ -665,7 +674,7 @@ struct internal::conservative_resize_like_impl
if ( ( Derived::IsRowMajor && _this.cols() == cols) || // row-major and we change only the number of rows
(!Derived::IsRowMajor && _this.rows() == rows) ) // column-major and we change only the number of columns
{
- internal::check_rows_cols_for_overflow(rows, cols);
+ internal::check_rows_cols_for_overflow<Derived::MaxSizeAtCompileTime>::run(rows, cols);
_this.derived().m_storage.conservativeResize(rows*cols,rows,cols);
}
else
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Product.h b/resources/3rdparty/eigen/Eigen/src/Core/Product.h
index 30aa8943b..314851d2e 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Product.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Product.h
@@ -3,13 +3,15 @@
//
// Copyright (C) 2008-2011 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/.
+// 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/.
#ifndef EIGEN_PRODUCT_H
#define EIGEN_PRODUCT_H
+namespace Eigen {
+
template<typename Lhs, typename Rhs> class Product;
template<typename Lhs, typename Rhs, typename StorageKind> class ProductImpl;
@@ -25,25 +27,16 @@ template<typename Lhs, typename Rhs, typename StorageKind> class ProductImpl;
*
*/
+// Use ProductReturnType to get correct traits, in particular vectorization flags
namespace internal {
template<typename Lhs, typename Rhs>
struct traits<Product<Lhs, Rhs> >
-{
- typedef MatrixXpr XprKind;
- typedef typename remove_all<Lhs>::type LhsCleaned;
- typedef typename remove_all<Rhs>::type RhsCleaned;
- typedef typename scalar_product_traits<typename traits<LhsCleaned>::Scalar, typename traits<RhsCleaned>::Scalar>::ReturnType Scalar;
- typedef typename promote_storage_type<typename traits<LhsCleaned>::StorageKind,
- typename traits<RhsCleaned>::StorageKind>::ret StorageKind;
- typedef typename promote_index_type<typename traits<LhsCleaned>::Index,
- typename traits<RhsCleaned>::Index>::type Index;
+ : traits<typename ProductReturnType<Lhs, Rhs>::Type>
+{
+ // We want A+B*C to be of type Product<Matrix, Sum> and not Product<Matrix, Matrix>
+ // TODO: This flag should eventually go in a separate evaluator traits class
enum {
- RowsAtCompileTime = LhsCleaned::RowsAtCompileTime,
- ColsAtCompileTime = RhsCleaned::ColsAtCompileTime,
- MaxRowsAtCompileTime = LhsCleaned::MaxRowsAtCompileTime,
- MaxColsAtCompileTime = RhsCleaned::MaxColsAtCompileTime,
- Flags = (MaxRowsAtCompileTime==1 ? RowMajorBit : 0), // TODO should be no storage order
- CoeffReadCost = 0 // TODO CoeffReadCost should not be part of the expression traits
+ Flags = traits<typename ProductReturnType<Lhs, Rhs>::Type>::Flags & ~EvalBeforeNestingBit
};
};
} // end namespace internal
@@ -95,4 +88,20 @@ class ProductImpl<Lhs,Rhs,Dense> : public internal::dense_xpr_base<Product<Lhs,R
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
};
+/***************************************************************************
+* Implementation of matrix base methods
+***************************************************************************/
+
+
+/** \internal used to test the evaluator only
+ */
+template<typename Lhs,typename Rhs>
+const Product<Lhs,Rhs>
+prod(const Lhs& lhs, const Rhs& rhs)
+{
+ return Product<Lhs,Rhs>(lhs,rhs);
+}
+
+} // end namespace Eigen
+
#endif // EIGEN_PRODUCT_H
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/ProductBase.h b/resources/3rdparty/eigen/Eigen/src/Core/ProductBase.h
index ec12e5c9f..9748167a5 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/ProductBase.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/ProductBase.h
@@ -87,10 +87,10 @@ class ProductBase : public MatrixBase<Derived>
typedef typename Base::PlainObject PlainObject;
- ProductBase(const Lhs& lhs, const Rhs& rhs)
- : m_lhs(lhs), m_rhs(rhs)
+ ProductBase(const Lhs& a_lhs, const Rhs& a_rhs)
+ : m_lhs(a_lhs), m_rhs(a_rhs)
{
- eigen_assert(lhs.cols() == rhs.rows()
+ eigen_assert(a_lhs.cols() == a_rhs.rows()
&& "invalid matrix product"
&& "if you wanted a coeff-wise or a dot product use the respective explicit functions");
}
@@ -201,7 +201,7 @@ operator*(const ProductBase<Derived,Lhs,Rhs>& prod, typename Derived::Scalar x)
template<typename Derived,typename Lhs,typename Rhs>
typename internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value,
const ScaledProduct<Derived> >::type
-operator*(const ProductBase<Derived,Lhs,Rhs>& prod, typename Derived::RealScalar x)
+operator*(const ProductBase<Derived,Lhs,Rhs>& prod, const typename Derived::RealScalar& x)
{ return ScaledProduct<Derived>(prod.derived(), x); }
@@ -213,7 +213,7 @@ operator*(typename Derived::Scalar x,const ProductBase<Derived,Lhs,Rhs>& prod)
template<typename Derived,typename Lhs,typename Rhs>
typename internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value,
const ScaledProduct<Derived> >::type
-operator*(typename Derived::RealScalar x,const ProductBase<Derived,Lhs,Rhs>& prod)
+operator*(const typename Derived::RealScalar& x,const ProductBase<Derived,Lhs,Rhs>& prod)
{ return ScaledProduct<Derived>(prod.derived(), x); }
namespace internal {
@@ -254,7 +254,7 @@ class ScaledProduct
inline void subTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(-1)); }
template<typename Dest>
- inline void scaleAndAddTo(Dest& dst,Scalar alpha) const { m_prod.derived().scaleAndAddTo(dst,alpha * m_alpha); }
+ inline void scaleAndAddTo(Dest& dst,Scalar a_alpha) const { m_prod.derived().scaleAndAddTo(dst,a_alpha * m_alpha); }
const Scalar& alpha() const { return m_alpha; }
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Random.h b/resources/3rdparty/eigen/Eigen/src/Core/Random.h
index a9f7f4346..bba99fc7c 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Random.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Random.h
@@ -141,9 +141,9 @@ PlainObjectBase<Derived>::setRandom(Index size)
*/
template<typename Derived>
EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setRandom(Index rows, Index cols)
+PlainObjectBase<Derived>::setRandom(Index nbRows, Index nbCols)
{
- resize(rows, cols);
+ resize(nbRows, nbCols);
return setRandom();
}
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Replicate.h b/resources/3rdparty/eigen/Eigen/src/Core/Replicate.h
index b61fdc29e..dde86a834 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Replicate.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Replicate.h
@@ -70,8 +70,8 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
EIGEN_DENSE_PUBLIC_INTERFACE(Replicate)
template<typename OriginalMatrixType>
- inline explicit Replicate(const OriginalMatrixType& matrix)
- : m_matrix(matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
+ inline explicit Replicate(const OriginalMatrixType& a_matrix)
+ : m_matrix(a_matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
{
EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
@@ -79,8 +79,8 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
}
template<typename OriginalMatrixType>
- inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor)
- : m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
+ inline Replicate(const OriginalMatrixType& a_matrix, Index rowFactor, Index colFactor)
+ : m_matrix(a_matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
{
EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
@@ -89,27 +89,27 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
inline Index rows() const { return m_matrix.rows() * m_rowFactor.value(); }
inline Index cols() const { return m_matrix.cols() * m_colFactor.value(); }
- inline Scalar coeff(Index row, Index col) const
+ inline Scalar coeff(Index rowId, Index colId) const
{
// try to avoid using modulo; this is a pure optimization strategy
const Index actual_row = internal::traits<MatrixType>::RowsAtCompileTime==1 ? 0
- : RowFactor==1 ? row
- : row%m_matrix.rows();
+ : RowFactor==1 ? rowId
+ : rowId%m_matrix.rows();
const Index actual_col = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
- : ColFactor==1 ? col
- : col%m_matrix.cols();
+ : ColFactor==1 ? colId
+ : colId%m_matrix.cols();
return m_matrix.coeff(actual_row, actual_col);
}
template<int LoadMode>
- inline PacketScalar packet(Index row, Index col) const
+ inline PacketScalar packet(Index rowId, Index colId) const
{
const Index actual_row = internal::traits<MatrixType>::RowsAtCompileTime==1 ? 0
- : RowFactor==1 ? row
- : row%m_matrix.rows();
+ : RowFactor==1 ? rowId
+ : rowId%m_matrix.rows();
const Index actual_col = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
- : ColFactor==1 ? col
- : col%m_matrix.cols();
+ : ColFactor==1 ? colId
+ : colId%m_matrix.cols();
return m_matrix.template packet<LoadMode>(actual_row, actual_col);
}
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Select.h b/resources/3rdparty/eigen/Eigen/src/Core/Select.h
index 2bf6e91d0..7ee8f23ba 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Select.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Select.h
@@ -60,10 +60,10 @@ class Select : internal::no_assignment_operator,
typedef typename internal::dense_xpr_base<Select>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Select)
- Select(const ConditionMatrixType& conditionMatrix,
- const ThenMatrixType& thenMatrix,
- const ElseMatrixType& elseMatrix)
- : m_condition(conditionMatrix), m_then(thenMatrix), m_else(elseMatrix)
+ Select(const ConditionMatrixType& a_conditionMatrix,
+ const ThenMatrixType& a_thenMatrix,
+ const ElseMatrixType& a_elseMatrix)
+ : m_condition(a_conditionMatrix), m_then(a_thenMatrix), m_else(a_elseMatrix)
{
eigen_assert(m_condition.rows() == m_then.rows() && m_condition.rows() == m_else.rows());
eigen_assert(m_condition.cols() == m_then.cols() && m_condition.cols() == m_else.cols());
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/StableNorm.h b/resources/3rdparty/eigen/Eigen/src/Core/StableNorm.h
index d8bf7db70..7499b195e 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/StableNorm.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/StableNorm.h
@@ -131,7 +131,6 @@ MatrixBase<Derived>::blueNorm() const
abig = internal::sqrt(abig);
if(abig > overfl)
{
- eigen_assert(false && "overflow");
return rbig;
}
if(amed > RealScalar(0))
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Swap.h b/resources/3rdparty/eigen/Eigen/src/Core/Swap.h
index fd73cf3ad..bf58bd599 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Swap.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Swap.h
@@ -49,9 +49,9 @@ template<typename ExpressionType> class SwapWrapper
inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
inline const Scalar* data() const { return m_expression.data(); }
- inline Scalar& coeffRef(Index row, Index col)
+ inline Scalar& coeffRef(Index rowId, Index colId)
{
- return m_expression.const_cast_derived().coeffRef(row, col);
+ return m_expression.const_cast_derived().coeffRef(rowId, colId);
}
inline Scalar& coeffRef(Index index)
@@ -59,9 +59,9 @@ template<typename ExpressionType> class SwapWrapper
return m_expression.const_cast_derived().coeffRef(index);
}
- inline Scalar& coeffRef(Index row, Index col) const
+ inline Scalar& coeffRef(Index rowId, Index colId) const
{
- return m_expression.coeffRef(row, col);
+ return m_expression.coeffRef(rowId, colId);
}
inline Scalar& coeffRef(Index index) const
@@ -70,14 +70,14 @@ template<typename ExpressionType> class SwapWrapper
}
template<typename OtherDerived>
- void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
+ void copyCoeff(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
- eigen_internal_assert(row >= 0 && row < rows()
- && col >= 0 && col < cols());
- Scalar tmp = m_expression.coeff(row, col);
- m_expression.coeffRef(row, col) = _other.coeff(row, col);
- _other.coeffRef(row, col) = tmp;
+ eigen_internal_assert(rowId >= 0 && rowId < rows()
+ && colId >= 0 && colId < cols());
+ Scalar tmp = m_expression.coeff(rowId, colId);
+ m_expression.coeffRef(rowId, colId) = _other.coeff(rowId, colId);
+ _other.coeffRef(rowId, colId) = tmp;
}
template<typename OtherDerived>
@@ -91,16 +91,16 @@ template<typename ExpressionType> class SwapWrapper
}
template<typename OtherDerived, int StoreMode, int LoadMode>
- void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
+ void copyPacket(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
{
OtherDerived& _other = other.const_cast_derived();
- eigen_internal_assert(row >= 0 && row < rows()
- && col >= 0 && col < cols());
- Packet tmp = m_expression.template packet<StoreMode>(row, col);
- m_expression.template writePacket<StoreMode>(row, col,
- _other.template packet<LoadMode>(row, col)
+ eigen_internal_assert(rowId >= 0 && rowId < rows()
+ && colId >= 0 && colId < cols());
+ Packet tmp = m_expression.template packet<StoreMode>(rowId, colId);
+ m_expression.template writePacket<StoreMode>(rowId, colId,
+ _other.template packet<LoadMode>(rowId, colId)
);
- _other.template writePacket<LoadMode>(row, col, tmp);
+ _other.template writePacket<LoadMode>(rowId, colId, tmp);
}
template<typename OtherDerived, int StoreMode, int LoadMode>
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Transpose.h b/resources/3rdparty/eigen/Eigen/src/Core/Transpose.h
index 045a1cce6..34944e055 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Transpose.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Transpose.h
@@ -62,7 +62,7 @@ template<typename MatrixType> class Transpose
typedef typename TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
- inline Transpose(MatrixType& matrix) : m_matrix(matrix) {}
+ inline Transpose(MatrixType& a_matrix) : m_matrix(a_matrix) {}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)
@@ -117,10 +117,10 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
inline const Scalar* data() const { return derived().nestedExpression().data(); }
- inline ScalarWithConstIfNotLvalue& coeffRef(Index row, Index col)
+ inline ScalarWithConstIfNotLvalue& coeffRef(Index rowId, Index colId)
{
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
- return derived().nestedExpression().const_cast_derived().coeffRef(col, row);
+ return derived().nestedExpression().const_cast_derived().coeffRef(colId, rowId);
}
inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
@@ -129,9 +129,9 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
return derived().nestedExpression().const_cast_derived().coeffRef(index);
}
- inline const Scalar& coeffRef(Index row, Index col) const
+ inline const Scalar& coeffRef(Index rowId, Index colId) const
{
- return derived().nestedExpression().coeffRef(col, row);
+ return derived().nestedExpression().coeffRef(colId, rowId);
}
inline const Scalar& coeffRef(Index index) const
@@ -139,9 +139,9 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
return derived().nestedExpression().coeffRef(index);
}
- inline CoeffReturnType coeff(Index row, Index col) const
+ inline CoeffReturnType coeff(Index rowId, Index colId) const
{
- return derived().nestedExpression().coeff(col, row);
+ return derived().nestedExpression().coeff(colId, rowId);
}
inline CoeffReturnType coeff(Index index) const
@@ -150,15 +150,15 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
}
template<int LoadMode>
- inline const PacketScalar packet(Index row, Index col) const
+ inline const PacketScalar packet(Index rowId, Index colId) const
{
- return derived().nestedExpression().template packet<LoadMode>(col, row);
+ return derived().nestedExpression().template packet<LoadMode>(colId, rowId);
}
template<int LoadMode>
- inline void writePacket(Index row, Index col, const PacketScalar& x)
+ inline void writePacket(Index rowId, Index colId, const PacketScalar& x)
{
- derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(col, row, x);
+ derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(colId, rowId, x);
}
template<int LoadMode>
@@ -353,7 +353,7 @@ struct check_transpose_aliasing_run_time_selector
{
static bool run(const Scalar* dest, const OtherDerived& src)
{
- return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) && (dest!=0 && dest==(Scalar*)extract_data(src));
+ return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src));
}
};
@@ -362,8 +362,8 @@ struct check_transpose_aliasing_run_time_selector<Scalar,DestIsTransposed,CwiseB
{
static bool run(const Scalar* dest, const CwiseBinaryOp<BinOp,DerivedA,DerivedB>& src)
{
- return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(Scalar*)extract_data(src.lhs())))
- || ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(Scalar*)extract_data(src.rhs())));
+ return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.lhs())))
+ || ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.rhs())));
}
};
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Transpositions.h b/resources/3rdparty/eigen/Eigen/src/Core/Transpositions.h
index 2cd268a5f..e4ba0756f 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Transpositions.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Transpositions.h
@@ -99,9 +99,9 @@ class TranspositionsBase
IndicesType& indices() { return derived().indices(); }
/** Resizes to given size. */
- inline void resize(int size)
+ inline void resize(int newSize)
{
- indices().resize(size);
+ indices().resize(newSize);
}
/** Sets \c *this to represents an identity transformation */
@@ -177,7 +177,7 @@ class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTim
/** Generic constructor from expression of the transposition indices. */
template<typename Other>
- explicit inline Transpositions(const MatrixBase<Other>& indices) : m_indices(indices)
+ explicit inline Transpositions(const MatrixBase<Other>& a_indices) : m_indices(a_indices)
{}
/** Copies the \a other transpositions into \c *this */
@@ -234,12 +234,12 @@ class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType>,Packe
typedef typename Traits::IndicesType IndicesType;
typedef typename IndicesType::Scalar Index;
- inline Map(const Index* indices)
- : m_indices(indices)
+ inline Map(const Index* indicesPtr)
+ : m_indices(indicesPtr)
{}
- inline Map(const Index* indices, Index size)
- : m_indices(indices,size)
+ inline Map(const Index* indicesPtr, Index size)
+ : m_indices(indicesPtr,size)
{}
/** Copies the \a other transpositions into \c *this */
@@ -291,8 +291,8 @@ class TranspositionsWrapper
typedef typename Traits::IndicesType IndicesType;
typedef typename IndicesType::Scalar Index;
- inline TranspositionsWrapper(IndicesType& indices)
- : m_indices(indices)
+ inline TranspositionsWrapper(IndicesType& a_indices)
+ : m_indices(a_indices)
{}
/** Copies the \a other transpositions into \c *this */
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/TriangularMatrix.h b/resources/3rdparty/eigen/Eigen/src/Core/TriangularMatrix.h
index de9540063..fcd40e32f 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/TriangularMatrix.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/TriangularMatrix.h
@@ -511,6 +511,7 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
struct triangular_assignment_selector<Derived1, Derived2, StrictlyUpper, Dynamic, ClearOpposite>
{
typedef typename Derived1::Index Index;
+ typedef typename Derived1::Scalar Scalar;
static inline void run(Derived1 &dst, const Derived2 &src)
{
for(Index j = 0; j < dst.cols(); ++j)
@@ -520,7 +521,7 @@ struct triangular_assignment_selector<Derived1, Derived2, StrictlyUpper, Dynamic
dst.copyCoeff(i, j, src);
if (ClearOpposite)
for(Index i = maxi; i < dst.rows(); ++i)
- dst.coeffRef(i, j) = 0;
+ dst.coeffRef(i, j) = Scalar(0);
}
}
};
@@ -778,7 +779,7 @@ MatrixBase<Derived>::triangularView() const
* \sa isLowerTriangular()
*/
template<typename Derived>
-bool MatrixBase<Derived>::isUpperTriangular(RealScalar prec) const
+bool MatrixBase<Derived>::isUpperTriangular(const RealScalar& prec) const
{
RealScalar maxAbsOnUpperPart = static_cast<RealScalar>(-1);
for(Index j = 0; j < cols(); ++j)
@@ -803,7 +804,7 @@ bool MatrixBase<Derived>::isUpperTriangular(RealScalar prec) const
* \sa isUpperTriangular()
*/
template<typename Derived>
-bool MatrixBase<Derived>::isLowerTriangular(RealScalar prec) const
+bool MatrixBase<Derived>::isLowerTriangular(const RealScalar& prec) const
{
RealScalar maxAbsOnLowerPart = static_cast<RealScalar>(-1);
for(Index j = 0; j < cols(); ++j)
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/VectorBlock.h b/resources/3rdparty/eigen/Eigen/src/Core/VectorBlock.h
index 6f4effca0..d0526dc95 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/VectorBlock.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/VectorBlock.h
@@ -108,19 +108,19 @@ template<typename VectorType, int Size> class VectorBlock
*/
template<typename Derived>
inline typename DenseBase<Derived>::SegmentReturnType
-DenseBase<Derived>::segment(Index start, Index size)
+DenseBase<Derived>::segment(Index start, Index vecSize)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
- return SegmentReturnType(derived(), start, size);
+ return SegmentReturnType(derived(), start, vecSize);
}
/** This is the const version of segment(Index,Index).*/
template<typename Derived>
inline typename DenseBase<Derived>::ConstSegmentReturnType
-DenseBase<Derived>::segment(Index start, Index size) const
+DenseBase<Derived>::segment(Index start, Index vecSize) const
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
- return ConstSegmentReturnType(derived(), start, size);
+ return ConstSegmentReturnType(derived(), start, vecSize);
}
/** \returns a dynamic-size expression of the first coefficients of *this.
@@ -140,19 +140,19 @@ DenseBase<Derived>::segment(Index start, Index size) const
*/
template<typename Derived>
inline typename DenseBase<Derived>::SegmentReturnType
-DenseBase<Derived>::head(Index size)
+DenseBase<Derived>::head(Index vecsize)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
- return SegmentReturnType(derived(), 0, size);
+ return SegmentReturnType(derived(), 0, vecsize);
}
/** This is the const version of head(Index).*/
template<typename Derived>
inline typename DenseBase<Derived>::ConstSegmentReturnType
-DenseBase<Derived>::head(Index size) const
+DenseBase<Derived>::head(Index vecSize) const
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
- return ConstSegmentReturnType(derived(), 0, size);
+ return ConstSegmentReturnType(derived(), 0, vecSize);
}
/** \returns a dynamic-size expression of the last coefficients of *this.
@@ -172,19 +172,19 @@ DenseBase<Derived>::head(Index size) const
*/
template<typename Derived>
inline typename DenseBase<Derived>::SegmentReturnType
-DenseBase<Derived>::tail(Index size)
+DenseBase<Derived>::tail(Index vecSize)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
- return SegmentReturnType(derived(), this->size() - size, size);
+ return SegmentReturnType(derived(), this->size() - vecSize, vecSize);
}
/** This is the const version of tail(Index).*/
template<typename Derived>
inline typename DenseBase<Derived>::ConstSegmentReturnType
-DenseBase<Derived>::tail(Index size) const
+DenseBase<Derived>::tail(Index vecSize) const
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
- return ConstSegmentReturnType(derived(), this->size() - size, size);
+ return ConstSegmentReturnType(derived(), this->size() - vecSize, vecSize);
}
/** \returns a fixed-size expression of a segment (i.e. a vector block) in \c *this
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/Visitor.h b/resources/3rdparty/eigen/Eigen/src/Core/Visitor.h
index 916bfd096..abf8d8e8c 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/Visitor.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/Visitor.h
@@ -172,12 +172,12 @@ struct functor_traits<max_coeff_visitor<Scalar> > {
template<typename Derived>
template<typename IndexType>
typename internal::traits<Derived>::Scalar
-DenseBase<Derived>::minCoeff(IndexType* row, IndexType* col) const
+DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
{
internal::min_coeff_visitor<Derived> minVisitor;
this->visit(minVisitor);
- *row = minVisitor.row;
- if (col) *col = minVisitor.col;
+ *rowId = minVisitor.row;
+ if (colId) *colId = minVisitor.col;
return minVisitor.res;
}
@@ -206,12 +206,12 @@ DenseBase<Derived>::minCoeff(IndexType* index) const
template<typename Derived>
template<typename IndexType>
typename internal::traits<Derived>::Scalar
-DenseBase<Derived>::maxCoeff(IndexType* row, IndexType* col) const
+DenseBase<Derived>::maxCoeff(IndexType* rowPtr, IndexType* colPtr) const
{
internal::max_coeff_visitor<Derived> maxVisitor;
this->visit(maxVisitor);
- *row = maxVisitor.row;
- if (col) *col = maxVisitor.col;
+ *rowPtr = maxVisitor.row;
+ if (colPtr) *colPtr = maxVisitor.col;
return maxVisitor.res;
}
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/arch/NEON/PacketMath.h b/resources/3rdparty/eigen/Eigen/src/Core/arch/NEON/PacketMath.h
index a20250f7c..2662e2ebf 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/arch/NEON/PacketMath.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/arch/NEON/PacketMath.h
@@ -237,15 +237,12 @@ template<> EIGEN_STRONG_INLINE Packet4i pabs(const Packet4i& a) { return vabsq_s
template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
{
float32x2_t a_lo, a_hi, sum;
- float s[2];
a_lo = vget_low_f32(a);
a_hi = vget_high_f32(a);
sum = vpadd_f32(a_lo, a_hi);
sum = vpadd_f32(sum, sum);
- vst1_f32(s, sum);
-
- return s[0];
+ return vget_lane_f32(sum, 0);
}
template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
@@ -271,15 +268,12 @@ template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
{
int32x2_t a_lo, a_hi, sum;
- int32_t s[2];
a_lo = vget_low_s32(a);
a_hi = vget_high_s32(a);
sum = vpadd_s32(a_lo, a_hi);
sum = vpadd_s32(sum, sum);
- vst1_s32(s, sum);
-
- return s[0];
+ return vget_lane_s32(sum, 0);
}
template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
@@ -307,7 +301,6 @@ template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
template<> EIGEN_STRONG_INLINE float predux_mul<Packet4f>(const Packet4f& a)
{
float32x2_t a_lo, a_hi, prod;
- float s[2];
// Get a_lo = |a1|a2| and a_hi = |a3|a4|
a_lo = vget_low_f32(a);
@@ -316,14 +309,12 @@ template<> EIGEN_STRONG_INLINE float predux_mul<Packet4f>(const Packet4f& a)
prod = vmul_f32(a_lo, a_hi);
// Multiply prod with its swapped value |a2*a4|a1*a3|
prod = vmul_f32(prod, vrev64_f32(prod));
- vst1_f32(s, prod);
- return s[0];
+ return vget_lane_f32(prod, 0);
}
template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
{
int32x2_t a_lo, a_hi, prod;
- int32_t s[2];
// Get a_lo = |a1|a2| and a_hi = |a3|a4|
a_lo = vget_low_s32(a);
@@ -332,65 +323,57 @@ template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
prod = vmul_s32(a_lo, a_hi);
// Multiply prod with its swapped value |a2*a4|a1*a3|
prod = vmul_s32(prod, vrev64_s32(prod));
- vst1_s32(s, prod);
- return s[0];
+ return vget_lane_s32(prod, 0);
}
// min
template<> EIGEN_STRONG_INLINE float predux_min<Packet4f>(const Packet4f& a)
{
float32x2_t a_lo, a_hi, min;
- float s[2];
a_lo = vget_low_f32(a);
a_hi = vget_high_f32(a);
min = vpmin_f32(a_lo, a_hi);
min = vpmin_f32(min, min);
- vst1_f32(s, min);
- return s[0];
+ return vget_lane_f32(min, 0);
}
+
template<> EIGEN_STRONG_INLINE int predux_min<Packet4i>(const Packet4i& a)
{
int32x2_t a_lo, a_hi, min;
- int32_t s[2];
a_lo = vget_low_s32(a);
a_hi = vget_high_s32(a);
min = vpmin_s32(a_lo, a_hi);
min = vpmin_s32(min, min);
- vst1_s32(s, min);
-
- return s[0];
+
+ return vget_lane_s32(min, 0);
}
// max
template<> EIGEN_STRONG_INLINE float predux_max<Packet4f>(const Packet4f& a)
{
float32x2_t a_lo, a_hi, max;
- float s[2];
a_lo = vget_low_f32(a);
a_hi = vget_high_f32(a);
max = vpmax_f32(a_lo, a_hi);
max = vpmax_f32(max, max);
- vst1_f32(s, max);
- return s[0];
+ return vget_lane_f32(max, 0);
}
+
template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
{
int32x2_t a_lo, a_hi, max;
- int32_t s[2];
a_lo = vget_low_s32(a);
a_hi = vget_high_s32(a);
max = vpmax_s32(a_lo, a_hi);
- max = vpmax_s32(max, max);
- vst1_s32(s, max);
- return s[0];
+ return vget_lane_s32(max, 0);
}
// this PALIGN_NEON business is to work around a bug in LLVM Clang 3.0 causing incorrect compilation errors,
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/MathFunctions.h b/resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/MathFunctions.h
index 3f41a4e26..557af8455 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/MathFunctions.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/MathFunctions.h
@@ -131,13 +131,16 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
/* express exp(x) as exp(g + n*log(2)) */
fx = pmadd(x, p4f_cephes_LOG2EF, p4f_half);
- /* how to perform a floorf with SSE: just below */
+#ifdef EIGEN_VECTORIZE_SSE4_1
+ fx = _mm_floor_ps(fx);
+#else
emm0 = _mm_cvttps_epi32(fx);
tmp = _mm_cvtepi32_ps(emm0);
/* if greater, substract 1 */
Packet4f mask = _mm_cmpgt_ps(tmp, fx);
mask = _mm_and_ps(mask, p4f_1);
fx = psub(tmp, mask);
+#endif
tmp = pmul(fx, p4f_cephes_exp_C1);
Packet4f z = pmul(fx, p4f_cephes_exp_C2);
@@ -161,6 +164,79 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
emm0 = _mm_slli_epi32(emm0, 23);
return pmul(y, _mm_castsi128_ps(emm0));
}
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d pexp<Packet2d>(const Packet2d& _x)
+{
+ Packet2d x = _x;
+
+ _EIGEN_DECLARE_CONST_Packet2d(1 , 1.0);
+ _EIGEN_DECLARE_CONST_Packet2d(2 , 2.0);
+ _EIGEN_DECLARE_CONST_Packet2d(half, 0.5);
+
+ _EIGEN_DECLARE_CONST_Packet2d(exp_hi, 709.437);
+ _EIGEN_DECLARE_CONST_Packet2d(exp_lo, -709.436139303);
+
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_LOG2EF, 1.4426950408889634073599);
+
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p0, 1.26177193074810590878e-4);
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p1, 3.02994407707441961300e-2);
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p2, 9.99999999999999999910e-1);
+
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q0, 3.00198505138664455042e-6);
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q1, 2.52448340349684104192e-3);
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q2, 2.27265548208155028766e-1);
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q3, 2.00000000000000000009e0);
+
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C1, 0.693145751953125);
+ _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
+ static const __m128i p4i_1023_0 = _mm_setr_epi32(1023, 1023, 0, 0);
+
+ Packet2d tmp = _mm_setzero_pd(), fx;
+ Packet4i emm0;
+
+ // clamp x
+ x = pmax(pmin(x, p2d_exp_hi), p2d_exp_lo);
+ /* express exp(x) as exp(g + n*log(2)) */
+ fx = pmadd(p2d_cephes_LOG2EF, x, p2d_half);
+
+#ifdef EIGEN_VECTORIZE_SSE4_1
+ fx = _mm_floor_pd(fx);
+#else
+ emm0 = _mm_cvttpd_epi32(fx);
+ tmp = _mm_cvtepi32_pd(emm0);
+ /* if greater, substract 1 */
+ Packet2d mask = _mm_cmpgt_pd(tmp, fx);
+ mask = _mm_and_pd(mask, p2d_1);
+ fx = psub(tmp, mask);
+#endif
+
+ tmp = pmul(fx, p2d_cephes_exp_C1);
+ Packet2d z = pmul(fx, p2d_cephes_exp_C2);
+ x = psub(x, tmp);
+ x = psub(x, z);
+
+ Packet2d x2 = pmul(x,x);
+
+ Packet2d px = p2d_cephes_exp_p0;
+ px = pmadd(px, x2, p2d_cephes_exp_p1);
+ px = pmadd(px, x2, p2d_cephes_exp_p2);
+ px = pmul (px, x);
+
+ Packet2d qx = p2d_cephes_exp_q0;
+ qx = pmadd(qx, x2, p2d_cephes_exp_q1);
+ qx = pmadd(qx, x2, p2d_cephes_exp_q2);
+ qx = pmadd(qx, x2, p2d_cephes_exp_q3);
+
+ x = pdiv(px,psub(qx,px));
+ x = pmadd(p2d_2,x,p2d_1);
+
+ // build 2^n
+ emm0 = _mm_cvttpd_epi32(fx);
+ emm0 = _mm_add_epi32(emm0, p4i_1023_0);
+ emm0 = _mm_slli_epi32(emm0, 20);
+ emm0 = _mm_shuffle_epi32(emm0, _MM_SHUFFLE(1,2,0,3));
+ return pmul(x, _mm_castsi128_pd(emm0));
+}
/* evaluation of 4 sines at onces, using SSE2 intrinsics.
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/PacketMath.h b/resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/PacketMath.h
index 10d918219..f84e5b3ec 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/PacketMath.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/PacketMath.h
@@ -48,6 +48,9 @@ template<> struct is_arithmetic<__m128d> { enum { value = true }; };
#define _EIGEN_DECLARE_CONST_Packet4f(NAME,X) \
const Packet4f p4f_##NAME = pset1<Packet4f>(X)
+#define _EIGEN_DECLARE_CONST_Packet2d(NAME,X) \
+ const Packet2d p2d_##NAME = pset1<Packet2d>(X)
+
#define _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(NAME,X) \
const Packet4f p4f_##NAME = _mm_castsi128_ps(pset1<Packet4i>(X))
@@ -63,7 +66,7 @@ template<> struct packet_traits<float> : default_packet_traits
AlignedOnScalar = 1,
size=4,
- HasDiv = 1,
+ HasDiv = 1,
HasSin = EIGEN_FAST_MATH,
HasCos = EIGEN_FAST_MATH,
HasLog = 1,
@@ -79,7 +82,8 @@ template<> struct packet_traits<double> : default_packet_traits
AlignedOnScalar = 1,
size=2,
- HasDiv = 1
+ HasDiv = 1,
+ HasExp = 1
};
};
template<> struct packet_traits<int> : default_packet_traits
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h b/resources/3rdparty/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h
index 5eb03c98c..09912fafb 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h
@@ -527,7 +527,7 @@ struct gebp_kernel
ResPacketSize = Traits::ResPacketSize
};
- EIGEN_DONT_INLINE EIGEN_FLATTEN_ATTRIB
+ EIGEN_DONT_INLINE
void operator()(ResScalar* res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index rows, Index depth, Index cols, ResScalar alpha,
Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0, RhsScalar* unpackedB = 0)
{
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixVector.h b/resources/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixVector.h
index ba1f73957..8895d3ab2 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixVector.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixVector.h
@@ -81,14 +81,14 @@ EIGEN_DONT_INLINE static void run(
const Index peels = 2;
const Index LhsPacketAlignedMask = LhsPacketSize-1;
const Index ResPacketAlignedMask = ResPacketSize-1;
- const Index PeelAlignedMask = ResPacketSize*peels-1;
+// const Index PeelAlignedMask = ResPacketSize*peels-1;
const Index size = rows;
// How many coeffs of the result do we have to skip to be aligned.
// Here we assume data are at least aligned on the base scalar type.
Index alignedStart = internal::first_aligned(res,size);
Index alignedSize = ResPacketSize>1 ? alignedStart + ((size-alignedStart) & ~ResPacketAlignedMask) : 0;
- const Index peeledSize = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
+ const Index peeledSize = alignedSize - RhsPacketSize*peels - RhsPacketSize + 1;
const Index alignmentStep = LhsPacketSize>1 ? (LhsPacketSize - lhsStride % LhsPacketSize) & LhsPacketAlignedMask : 0;
Index alignmentPattern = alignmentStep==0 ? AllAligned
@@ -177,6 +177,8 @@ EIGEN_DONT_INLINE static void run(
_EIGEN_ACCUMULATE_PACKETS(d,du,d);
break;
case FirstAligned:
+ {
+ Index j = alignedStart;
if(peels>1)
{
LhsPacket A00, A01, A02, A03, A10, A11, A12, A13;
@@ -186,7 +188,7 @@ EIGEN_DONT_INLINE static void run(
A02 = pload<LhsPacket>(&lhs2[alignedStart-2]);
A03 = pload<LhsPacket>(&lhs3[alignedStart-3]);
- for (Index j = alignedStart; j<peeledSize; j+=peels*ResPacketSize)
+ for (; j<peeledSize; j+=peels*ResPacketSize)
{
A11 = pload<LhsPacket>(&lhs1[j-1+LhsPacketSize]); palign<1>(A01,A11);
A12 = pload<LhsPacket>(&lhs2[j-2+LhsPacketSize]); palign<2>(A02,A12);
@@ -210,9 +212,10 @@ EIGEN_DONT_INLINE static void run(
pstore(&res[j+ResPacketSize],T1);
}
}
- for (Index j = peeledSize; j<alignedSize; j+=ResPacketSize)
+ for (; j<alignedSize; j+=ResPacketSize)
_EIGEN_ACCUMULATE_PACKETS(d,du,du);
break;
+ }
default:
for (Index j = alignedStart; j<alignedSize; j+=ResPacketSize)
_EIGEN_ACCUMULATE_PACKETS(du,du,du);
@@ -332,7 +335,7 @@ EIGEN_DONT_INLINE static void run(
const Index peels = 2;
const Index RhsPacketAlignedMask = RhsPacketSize-1;
const Index LhsPacketAlignedMask = LhsPacketSize-1;
- const Index PeelAlignedMask = RhsPacketSize*peels-1;
+// const Index PeelAlignedMask = RhsPacketSize*peels-1;
const Index depth = cols;
// How many coeffs of the result do we have to skip to be aligned.
@@ -340,7 +343,7 @@ EIGEN_DONT_INLINE static void run(
// if that's not the case then vectorization is discarded, see below.
Index alignedStart = internal::first_aligned(rhs, depth);
Index alignedSize = RhsPacketSize>1 ? alignedStart + ((depth-alignedStart) & ~RhsPacketAlignedMask) : 0;
- const Index peeledSize = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
+ const Index peeledSize = alignedSize - RhsPacketSize*peels - RhsPacketSize + 1;
const Index alignmentStep = LhsPacketSize>1 ? (LhsPacketSize - lhsStride % LhsPacketSize) & LhsPacketAlignedMask : 0;
Index alignmentPattern = alignmentStep==0 ? AllAligned
@@ -430,10 +433,12 @@ EIGEN_DONT_INLINE static void run(
_EIGEN_ACCUMULATE_PACKETS(d,du,d);
break;
case FirstAligned:
+ {
+ Index j = alignedStart;
if (peels>1)
{
/* Here we proccess 4 rows with with two peeled iterations to hide
- * tghe overhead of unaligned loads. Moreover unaligned loads are handled
+ * the overhead of unaligned loads. Moreover unaligned loads are handled
* using special shift/move operations between the two aligned packets
* overlaping the desired unaligned packet. This is *much* more efficient
* than basic unaligned loads.
@@ -443,7 +448,7 @@ EIGEN_DONT_INLINE static void run(
A02 = pload<LhsPacket>(&lhs2[alignedStart-2]);
A03 = pload<LhsPacket>(&lhs3[alignedStart-3]);
- for (Index j = alignedStart; j<peeledSize; j+=peels*RhsPacketSize)
+ for (; j<peeledSize; j+=peels*RhsPacketSize)
{
RhsPacket b = pload<RhsPacket>(&rhs[j]);
A11 = pload<LhsPacket>(&lhs1[j-1+LhsPacketSize]); palign<1>(A01,A11);
@@ -465,9 +470,10 @@ EIGEN_DONT_INLINE static void run(
ptmp3 = pcj.pmadd(A13, b, ptmp3);
}
}
- for (Index j = peeledSize; j<alignedSize; j+=RhsPacketSize)
+ for (; j<alignedSize; j+=RhsPacketSize)
_EIGEN_ACCUMULATE_PACKETS(d,du,du);
break;
+ }
default:
for (Index j = alignedStart; j<alignedSize; j+=RhsPacketSize)
_EIGEN_ACCUMULATE_PACKETS(du,du,du);
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h b/resources/3rdparty/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
index 8173da5bb..4d20de617 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
@@ -57,11 +57,11 @@ template <typename Index, int Mode, \
struct product_triangular_matrix_matrix<Scalar,Index, Mode, LhsIsTriangular, \
LhsStorageOrder,ConjugateLhs, RhsStorageOrder,ConjugateRhs,ColMajor,Specialized> { \
static inline void run(Index _rows, Index _cols, Index _depth, const Scalar* _lhs, Index lhsStride,\
- const Scalar* _rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha) { \
+ const Scalar* _rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha, level3_blocking<Scalar,Scalar>& blocking) { \
product_triangular_matrix_matrix_trmm<Scalar,Index,Mode, \
LhsIsTriangular,LhsStorageOrder,ConjugateLhs, \
RhsStorageOrder, ConjugateRhs, ColMajor>::run( \
- _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \
+ _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
} \
};
@@ -96,7 +96,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
const EIGTYPE* _lhs, Index lhsStride, \
const EIGTYPE* _rhs, Index rhsStride, \
EIGTYPE* res, Index resStride, \
- EIGTYPE alpha) \
+ EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
{ \
Index diagSize = (std::min)(_rows,_depth); \
Index rows = IsLower ? _rows : diagSize; \
@@ -115,16 +115,16 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
/* Most likely no benefit to call TRMM or GEMM from MKL*/ \
product_triangular_matrix_matrix<EIGTYPE,Index,Mode,true, \
LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
- _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \
+ _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
/*std::cout << "TRMM_L: A is not square! Go to Eigen TRMM implementation!\n";*/ \
} else { \
/* Make sense to call GEMM */ \
Map<const MatrixLhs, 0, OuterStride<> > lhsMap(_lhs,rows,depth,OuterStride<>(lhsStride)); \
MatrixLhs aa_tmp=lhsMap.template triangularView<Mode>(); \
MKL_INT aStride = aa_tmp.outerStride(); \
- gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> blocking(_rows,_cols,_depth); \
+ gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> gemm_blocking(_rows,_cols,_depth); \
general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
- rows, cols, depth, aa_tmp.data(), aStride, _rhs, rhsStride, res, resStride, alpha, blocking, 0); \
+ rows, cols, depth, aa_tmp.data(), aStride, _rhs, rhsStride, res, resStride, alpha, gemm_blocking, 0); \
\
/*std::cout << "TRMM_L: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \
} \
@@ -210,7 +210,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
const EIGTYPE* _lhs, Index lhsStride, \
const EIGTYPE* _rhs, Index rhsStride, \
EIGTYPE* res, Index resStride, \
- EIGTYPE alpha) \
+ EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
{ \
Index diagSize = (std::min)(_cols,_depth); \
Index rows = _rows; \
@@ -229,16 +229,16 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
/* Most likely no benefit to call TRMM or GEMM from MKL*/ \
product_triangular_matrix_matrix<EIGTYPE,Index,Mode,false, \
LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
- _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \
+ _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
/*std::cout << "TRMM_R: A is not square! Go to Eigen TRMM implementation!\n";*/ \
} else { \
/* Make sense to call GEMM */ \
Map<const MatrixRhs, 0, OuterStride<> > rhsMap(_rhs,depth,cols, OuterStride<>(rhsStride)); \
MatrixRhs aa_tmp=rhsMap.template triangularView<Mode>(); \
MKL_INT aStride = aa_tmp.outerStride(); \
- gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> blocking(_rows,_cols,_depth); \
+ gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> gemm_blocking(_rows,_cols,_depth); \
general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
- rows, cols, depth, _lhs, lhsStride, aa_tmp.data(), aStride, res, resStride, alpha, blocking, 0); \
+ rows, cols, depth, _lhs, lhsStride, aa_tmp.data(), aStride, res, resStride, alpha, gemm_blocking, 0); \
\
/*std::cout << "TRMM_R: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \
} \
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h b/resources/3rdparty/eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h
index 3589b8c5e..3c2c3049a 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h
@@ -82,11 +82,11 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
LowUp = IsLower ? Lower : Upper \
}; \
static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
- const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+ const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
{ \
if (ConjLhs || IsZeroDiag) { \
triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor,BuiltIn>::run( \
- _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
+ _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
return; \
}\
Index size = (std::min)(_rows,_cols); \
@@ -167,11 +167,11 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
LowUp = IsLower ? Lower : Upper \
}; \
static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
- const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+ const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
{ \
if (IsZeroDiag) { \
triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor,BuiltIn>::run( \
- _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
+ _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
return; \
}\
Index size = (std::min)(_rows,_cols); \
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/util/Constants.h b/resources/3rdparty/eigen/Eigen/src/Core/util/Constants.h
index 3fd45e84f..1732c1d80 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/util/Constants.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/util/Constants.h
@@ -13,13 +13,18 @@
namespace Eigen {
-/** This value means that a quantity is not known at compile-time, and that instead the value is
+/** This value means that a positive quantity (e.g., a size) is not known at compile-time, and that instead the value is
* stored in some runtime variable.
*
* Changing the value of Dynamic breaks the ABI, as Dynamic is often used as a template parameter for Matrix.
*/
const int Dynamic = -1;
+/** This value means that a signed quantity (e.g., a signed index) is not known at compile-time, and that instead its value
+ * has to be specified at runtime.
+ */
+const int DynamicIndex = 0xffffff;
+
/** This value means +Infinity; it is currently used only as the p parameter to MatrixBase::lpNorm<int>().
* The value Infinity there means the L-infinity norm.
*/
@@ -227,7 +232,9 @@ enum {
* scalar loops to handle the unaligned boundaries */
SliceVectorizedTraversal,
/** \internal Special case to properly handle incompatible scalar types or other defecting cases*/
- InvalidTraversal
+ InvalidTraversal,
+ /** \internal Evaluate all entries at once */
+ AllAtOnceTraversal
};
/** \internal \ingroup enums
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/util/ForwardDeclarations.h b/resources/3rdparty/eigen/Eigen/src/Core/util/ForwardDeclarations.h
index bcdfe3914..58e1d87dc 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/util/ForwardDeclarations.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/util/ForwardDeclarations.h
@@ -154,7 +154,6 @@ template<typename LhsScalar, typename RhsScalar, bool ConjLhs=false, bool ConjRh
template<typename Scalar> struct scalar_sum_op;
template<typename Scalar> struct scalar_difference_op;
template<typename LhsScalar,typename RhsScalar> struct scalar_conj_product_op;
-template<typename Scalar> struct scalar_quotient_op;
template<typename Scalar> struct scalar_opposite_op;
template<typename Scalar> struct scalar_conjugate_op;
template<typename Scalar> struct scalar_real_op;
@@ -185,6 +184,7 @@ template<typename Scalar> struct scalar_identity_op;
template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_product_op;
template<typename LhsScalar,typename RhsScalar> struct scalar_multiple2_op;
+template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_quotient_op;
} // end namespace internal
@@ -271,6 +271,8 @@ template<typename Derived> struct MatrixExponentialReturnValue;
template<typename Derived> class MatrixFunctionReturnValue;
template<typename Derived> class MatrixSquareRootReturnValue;
template<typename Derived> class MatrixLogarithmReturnValue;
+template<typename Derived> class MatrixPowerReturnValue;
+template<typename Derived, typename Lhs, typename Rhs> class MatrixPowerProductBase;
namespace internal {
template <typename Scalar>
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/util/Macros.h b/resources/3rdparty/eigen/Eigen/src/Core/util/Macros.h
index d973a6837..1bbd24b8b 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/util/Macros.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/util/Macros.h
@@ -13,7 +13,7 @@
#define EIGEN_WORLD_VERSION 3
#define EIGEN_MAJOR_VERSION 1
-#define EIGEN_MINOR_VERSION 1
+#define EIGEN_MINOR_VERSION 90
#define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
(EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
@@ -115,12 +115,6 @@
#define EIGEN_MAKESTRING2(a) #a
#define EIGEN_MAKESTRING(a) EIGEN_MAKESTRING2(a)
-#if EIGEN_GNUC_AT_LEAST(4,1) && !defined(__clang__) && !defined(__INTEL_COMPILER)
-#define EIGEN_FLATTEN_ATTRIB __attribute__((flatten))
-#else
-#define EIGEN_FLATTEN_ATTRIB
-#endif
-
// EIGEN_STRONG_INLINE is a stronger version of the inline, using __forceinline on MSVC,
// but it still doesn't use GCC's always_inline. This is useful in (common) situations where MSVC needs forceinline
// but GCC is still doing fine with just inline.
@@ -301,6 +295,12 @@
#if defined(_MSC_VER) && (!defined(__INTEL_COMPILER))
#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
using Base::operator =;
+#elif defined(__clang__) // workaround clang bug (see http://forum.kde.org/viewtopic.php?f=74&t=102653)
+#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
+ using Base::operator =; \
+ EIGEN_STRONG_INLINE Derived& operator=(const Derived& other) { Base::operator=(other); return *this; } \
+ template <typename OtherDerived> \
+ EIGEN_STRONG_INLINE Derived& operator=(const DenseBase<OtherDerived>& other) { Base::operator=(other.derived()); return *this; }
#else
#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
using Base::operator =; \
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/util/StaticAssert.h b/resources/3rdparty/eigen/Eigen/src/Core/util/StaticAssert.h
index b46a75b37..8872c5b64 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/util/StaticAssert.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/util/StaticAssert.h
@@ -89,7 +89,8 @@
YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED,
YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED,
THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE,
- THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH
+ THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH,
+ OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG
};
};
diff --git a/resources/3rdparty/eigen/Eigen/src/Core/util/XprHelper.h b/resources/3rdparty/eigen/Eigen/src/Core/util/XprHelper.h
index 2a65c7cbf..3d1290cd2 100644
--- a/resources/3rdparty/eigen/Eigen/src/Core/util/XprHelper.h
+++ b/resources/3rdparty/eigen/Eigen/src/Core/util/XprHelper.h
@@ -65,6 +65,27 @@ template<typename T> class variable_if_dynamic<T, Dynamic>
void setValue(T value) { m_value = value; }
};
+/** \internal like variable_if_dynamic but for DynamicIndex
+ */
+template<typename T, int Value> class variable_if_dynamicindex
+{
+ public:
+ EIGEN_EMPTY_STRUCT_CTOR(variable_if_dynamicindex)
+ explicit variable_if_dynamicindex(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); assert(v == T(Value)); }
+ static T value() { return T(Value); }
+ void setValue(T) {}
+};
+
+template<typename T> class variable_if_dynamicindex<T, DynamicIndex>
+{
+ T m_value;
+ variable_if_dynamicindex() { assert(false); }
+ public:
+ explicit variable_if_dynamicindex(T value) : m_value(value) {}
+ T value() const { return m_value; }
+ void setValue(T value) { m_value = value; }
+};
+
template<typename T> struct functor_traits
{
enum
@@ -301,9 +322,9 @@ template<typename T, int n=1, typename PlainObject = typename eval<T>::type> str
// it's important that this value can still be squared without integer overflowing.
DynamicAsInteger = 10000,
ScalarReadCost = NumTraits<typename traits<T>::Scalar>::ReadCost,
- ScalarReadCostAsInteger = ScalarReadCost == Dynamic ? DynamicAsInteger : ScalarReadCost,
+ ScalarReadCostAsInteger = ScalarReadCost == Dynamic ? int(DynamicAsInteger) : int(ScalarReadCost),
CoeffReadCost = traits<T>::CoeffReadCost,
- CoeffReadCostAsInteger = CoeffReadCost == Dynamic ? DynamicAsInteger : CoeffReadCost,
+ CoeffReadCostAsInteger = CoeffReadCost == Dynamic ? int(DynamicAsInteger) : int(CoeffReadCost),
NAsInteger = n == Dynamic ? int(DynamicAsInteger) : n,
CostEvalAsInteger = (NAsInteger+1) * ScalarReadCostAsInteger + CoeffReadCostAsInteger,
CostNoEvalAsInteger = NAsInteger * CoeffReadCostAsInteger
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
index 5c928e8fc..7b2b865eb 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AngleAxis.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
index 20f1fceeb..af598a403 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
index 19cc1bfd8..49e37392d 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
index 6e4a168a8..3523611ee 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h
index ec87da054..4b6390cf1 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
index 3e02b7a4f..19b8582a1 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h
index 78ad73b60..b1c8f38da 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h
index a07c1c7c7..b8fa6cd3f 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Transform.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Transform.h
index dceb80203..fab60b251 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Transform.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Transform.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Translation.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Translation.h
index 0fb9a9f9a..2b9859f6f 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Translation.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Translation.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/LeastSquares.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/LeastSquares.h
index 7aff428dc..0e6fdb488 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/LeastSquares.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/LeastSquares.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
//
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/SVD.h b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/SVD.h
index 3d2eeb445..a08b695a4 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigen2Support/SVD.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigen2Support/SVD.h
@@ -1,5 +1,5 @@
// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h
index c4b8a308c..95c70aecb 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h
@@ -3,7 +3,7 @@
//
// Copyright (C) 2009 Claire Maurice
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// 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
@@ -220,6 +220,19 @@ template<typename _MatrixType> class ComplexEigenSolver
return m_schur.info();
}
+ /** \brief Sets the maximum number of iterations allowed. */
+ ComplexEigenSolver& setMaxIterations(Index maxIters)
+ {
+ m_schur.setMaxIterations(maxIters);
+ return *this;
+ }
+
+ /** \brief Returns the maximum number of iterations. */
+ Index getMaxIterations()
+ {
+ return m_schur.getMaxIterations();
+ }
+
protected:
EigenvectorType m_eivec;
EigenvalueType m_eivalues;
@@ -235,7 +248,8 @@ template<typename _MatrixType> class ComplexEigenSolver
template<typename MatrixType>
-ComplexEigenSolver<MatrixType>& ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
+ComplexEigenSolver<MatrixType>&
+ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
{
// this code is inspired from Jampack
assert(matrix.cols() == matrix.rows());
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexSchur.h b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexSchur.h
index 16a9a03d2..62cbbb14f 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexSchur.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexSchur.h
@@ -3,7 +3,7 @@
//
// Copyright (C) 2009 Claire Maurice
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// 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
@@ -96,7 +96,8 @@ template<typename _MatrixType> class ComplexSchur
m_matU(size,size),
m_hess(size),
m_isInitialized(false),
- m_matUisUptodate(false)
+ m_matUisUptodate(false),
+ m_maxIters(-1)
{}
/** \brief Constructor; computes Schur decomposition of given matrix.
@@ -109,11 +110,12 @@ template<typename _MatrixType> class ComplexSchur
* \sa matrixT() and matrixU() for examples.
*/
ComplexSchur(const MatrixType& matrix, bool computeU = true)
- : m_matT(matrix.rows(),matrix.cols()),
- m_matU(matrix.rows(),matrix.cols()),
- m_hess(matrix.rows()),
- m_isInitialized(false),
- m_matUisUptodate(false)
+ : m_matT(matrix.rows(),matrix.cols()),
+ m_matU(matrix.rows(),matrix.cols()),
+ m_hess(matrix.rows()),
+ m_isInitialized(false),
+ m_matUisUptodate(false),
+ m_maxIters(-1)
{
compute(matrix, computeU);
}
@@ -166,6 +168,7 @@ template<typename _MatrixType> class ComplexSchur
*
* \param[in] matrix Square matrix whose Schur decomposition is to be computed.
* \param[in] computeU If true, both T and U are computed; if false, only T is computed.
+
* \returns Reference to \c *this
*
* The Schur decomposition is computed by first reducing the
@@ -180,6 +183,8 @@ template<typename _MatrixType> class ComplexSchur
*
* Example: \include ComplexSchur_compute.cpp
* Output: \verbinclude ComplexSchur_compute.out
+ *
+ * \sa compute(const MatrixType&, bool, Index)
*/
ComplexSchur& compute(const MatrixType& matrix, bool computeU = true);
@@ -189,15 +194,33 @@ template<typename _MatrixType> class ComplexSchur
*/
ComputationInfo info() const
{
- eigen_assert(m_isInitialized && "RealSchur is not initialized.");
+ eigen_assert(m_isInitialized && "ComplexSchur is not initialized.");
return m_info;
}
- /** \brief Maximum number of iterations.
+ /** \brief Sets the maximum number of iterations allowed.
*
- * Maximum number of iterations allowed for an eigenvalue to converge.
+ * If not specified by the user, the maximum number of iterations is m_maxIterationsPerRow times the size
+ * of the matrix.
*/
- static const int m_maxIterations = 30;
+ ComplexSchur& setMaxIterations(Index maxIters)
+ {
+ m_maxIters = maxIters;
+ return *this;
+ }
+
+ /** \brief Returns the maximum number of iterations. */
+ Index getMaxIterations()
+ {
+ return m_maxIters;
+ }
+
+ /** \brief Maximum number of iterations per row.
+ *
+ * If not otherwise specified, the maximum number of iterations is this number times the size of the
+ * matrix. It is currently set to 30.
+ */
+ static const int m_maxIterationsPerRow = 30;
protected:
ComplexMatrixType m_matT, m_matU;
@@ -205,6 +228,7 @@ template<typename _MatrixType> class ComplexSchur
ComputationInfo m_info;
bool m_isInitialized;
bool m_matUisUptodate;
+ Index m_maxIters;
private:
bool subdiagonalEntryIsNeglegible(Index i);
@@ -329,6 +353,10 @@ struct complex_schur_reduce_to_hessenberg<MatrixType, false>
template<typename MatrixType>
void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
{
+ Index maxIters = m_maxIters;
+ if (maxIters == -1)
+ maxIters = m_maxIterationsPerRow * m_matT.rows();
+
// The matrix m_matT is divided in three parts.
// Rows 0,...,il-1 are decoupled from the rest because m_matT(il,il-1) is zero.
// Rows il,...,iu is the part we are working on (the active submatrix).
@@ -336,6 +364,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
Index iu = m_matT.cols() - 1;
Index il;
Index iter = 0; // number of iterations we are working on the (iu,iu) element
+ Index totalIter = 0; // number of iterations for whole matrix
while(true)
{
@@ -350,9 +379,10 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
// if iu is zero then we are done; the whole matrix is triangularized
if(iu==0) break;
- // if we spent too many iterations on the current element, we give up
+ // if we spent too many iterations, we give up
iter++;
- if(iter > m_maxIterations * m_matT.cols()) break;
+ totalIter++;
+ if(totalIter > maxIters) break;
// find il, the top row of the active submatrix
il = iu-1;
@@ -382,7 +412,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
}
}
- if(iter <= m_maxIterations * m_matT.cols())
+ if(totalIter <= maxIters)
m_info = Success;
else
m_info = NoConvergence;
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
index aa18e6963..ada7a24e3 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
@@ -40,7 +40,7 @@ namespace Eigen {
/** \internal Specialization for the data types supported by MKL */
#define EIGEN_MKL_SCHUR_COMPLEX(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \
-template<> inline\
+template<> inline \
ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, bool computeU) \
{ \
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/EigenSolver.h b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/EigenSolver.h
index c16ff2b74..9c3bba1e5 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/EigenSolver.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/EigenSolver.h
@@ -2,7 +2,7 @@
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// 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
@@ -281,6 +281,19 @@ template<typename _MatrixType> class EigenSolver
return m_realSchur.info();
}
+ /** \brief Sets the maximum number of iterations allowed. */
+ EigenSolver& setMaxIterations(Index maxIters)
+ {
+ m_realSchur.setMaxIterations(maxIters);
+ return *this;
+ }
+
+ /** \brief Returns the maximum number of iterations. */
+ Index getMaxIterations()
+ {
+ return m_realSchur.getMaxIterations();
+ }
+
private:
void doComputeEigenvectors();
@@ -348,12 +361,14 @@ typename EigenSolver<MatrixType>::EigenvectorsType EigenSolver<MatrixType>::eige
}
template<typename MatrixType>
-EigenSolver<MatrixType>& EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
+EigenSolver<MatrixType>&
+EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
{
assert(matrix.cols() == matrix.rows());
// Reduce to real Schur form.
m_realSchur.compute(matrix, computeEigenvectors);
+
if (m_realSchur.info() == Success)
{
m_matT = m_realSchur.matrixT();
@@ -532,7 +547,7 @@ void EigenSolver<MatrixType>::doComputeEigenvectors()
if ((vr == 0.0) && (vi == 0.0))
vr = eps * norm * (internal::abs(w) + internal::abs(q) + internal::abs(x) + internal::abs(y) + internal::abs(lastw));
- std::complex<Scalar> cc = cdiv(x*lastra-lastw*ra+q*sa,x*lastsa-lastw*sa-q*ra,vr,vi);
+ std::complex<Scalar> cc = cdiv(x*lastra-lastw*ra+q*sa,x*lastsa-lastw*sa-q*ra,vr,vi);
m_matT.coeffRef(i,n-1) = internal::real(cc);
m_matT.coeffRef(i,n) = internal::imag(cc);
if (internal::abs(x) > (internal::abs(lastw) + internal::abs(q)))
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/RealSchur.h b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/RealSchur.h
index 781692ecc..da069bc55 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/RealSchur.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/RealSchur.h
@@ -2,7 +2,7 @@
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// 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
@@ -86,7 +86,8 @@ template<typename _MatrixType> class RealSchur
m_workspaceVector(size),
m_hess(size),
m_isInitialized(false),
- m_matUisUptodate(false)
+ m_matUisUptodate(false),
+ m_maxIters(-1)
{ }
/** \brief Constructor; computes real Schur decomposition of given matrix.
@@ -105,7 +106,8 @@ template<typename _MatrixType> class RealSchur
m_workspaceVector(matrix.rows()),
m_hess(matrix.rows()),
m_isInitialized(false),
- m_matUisUptodate(false)
+ m_matUisUptodate(false),
+ m_maxIters(-1)
{
compute(matrix, computeU);
}
@@ -160,6 +162,8 @@ template<typename _MatrixType> class RealSchur
*
* Example: \include RealSchur_compute.cpp
* Output: \verbinclude RealSchur_compute.out
+ *
+ * \sa compute(const MatrixType&, bool, Index)
*/
RealSchur& compute(const MatrixType& matrix, bool computeU = true);
@@ -173,11 +177,29 @@ template<typename _MatrixType> class RealSchur
return m_info;
}
- /** \brief Maximum number of iterations.
+ /** \brief Sets the maximum number of iterations allowed.
+ *
+ * If not specified by the user, the maximum number of iterations is m_maxIterationsPerRow times the size
+ * of the matrix.
+ */
+ RealSchur& setMaxIterations(Index maxIters)
+ {
+ m_maxIters = maxIters;
+ return *this;
+ }
+
+ /** \brief Returns the maximum number of iterations. */
+ Index getMaxIterations()
+ {
+ return m_maxIters;
+ }
+
+ /** \brief Maximum number of iterations per row.
*
- * Maximum number of iterations allowed for an eigenvalue to converge.
+ * If not otherwise specified, the maximum number of iterations is this number times the size of the
+ * matrix. It is currently set to 40.
*/
- static const int m_maxIterations = 40;
+ static const int m_maxIterationsPerRow = 40;
private:
@@ -188,6 +210,7 @@ template<typename _MatrixType> class RealSchur
ComputationInfo m_info;
bool m_isInitialized;
bool m_matUisUptodate;
+ Index m_maxIters;
typedef Matrix<Scalar,3,1> Vector3s;
@@ -204,6 +227,9 @@ template<typename MatrixType>
RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix, bool computeU)
{
assert(matrix.cols() == matrix.rows());
+ Index maxIters = m_maxIters;
+ if (maxIters == -1)
+ maxIters = m_maxIterationsPerRow * matrix.rows();
// Step 1. Reduce to Hessenberg form
m_hess.compute(matrix);
@@ -220,8 +246,9 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix,
// Rows il,...,iu is the part we are working on (the active window).
// Rows iu+1,...,end are already brought in triangular form.
Index iu = m_matT.cols() - 1;
- Index iter = 0; // iteration count
- Scalar exshift(0); // sum of exceptional shifts
+ Index iter = 0; // iteration count for current eigenvalue
+ Index totalIter = 0; // iteration count for whole matrix
+ Scalar exshift(0); // sum of exceptional shifts
Scalar norm = computeNormOfT();
if(norm!=0)
@@ -251,14 +278,15 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix,
Vector3s firstHouseholderVector(0,0,0), shiftInfo;
computeShift(iu, iter, exshift, shiftInfo);
iter = iter + 1;
- if (iter > m_maxIterations * m_matT.cols()) break;
+ totalIter = totalIter + 1;
+ if (totalIter > maxIters) break;
Index im;
initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace);
}
}
}
- if(iter <= m_maxIterations * m_matT.cols())
+ if(totalIter <= maxIters)
m_info = Success;
else
m_info = NoConvergence;
@@ -278,7 +306,7 @@ inline typename MatrixType::Scalar RealSchur<MatrixType>::computeNormOfT()
// + m_matT.bottomLeftCorner(size-1,size-1).diagonal().cwiseAbs().sum();
Scalar norm(0);
for (Index j = 0; j < size; ++j)
- norm += m_matT.row(j).segment((std::max)(j-1,Index(0)), size-(std::max)(j-1,Index(0))).cwiseAbs().sum();
+ norm += m_matT.col(j).segment(0, (std::min)(size,j+2)).cwiseAbs().sum();
return norm;
}
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
index acc5576fe..24c78b4b2 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
@@ -743,7 +743,16 @@ static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index sta
// RealScalar e2 = abs2(subdiag[end-1]);
// RealScalar mu = diag[end] - e2 / (td + (td>0 ? 1 : -1) * sqrt(td*td + e2));
// This explain the following, somewhat more complicated, version:
- RealScalar mu = diag[end] - (e / (td + (td>0 ? 1 : -1))) * (e / hypot(td,e));
+ RealScalar mu = diag[end];
+ if(td==0)
+ mu -= abs(e);
+ else
+ {
+ RealScalar e2 = abs2(subdiag[end-1]);
+ RealScalar h = hypot(td,e);
+ if(e2==0) mu -= (e / (td + (td>0 ? 1 : -1))) * (e / h);
+ else mu -= e2 / (td + (td>0 ? h : -h));
+ }
RealScalar x = diag[start] - mu;
RealScalar z = subdiag[start];
diff --git a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
index 9380956b5..5de5f15d6 100644
--- a/resources/3rdparty/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
+++ b/resources/3rdparty/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
@@ -40,7 +40,7 @@ namespace Eigen {
/** \internal Specialization for the data types supported by MKL */
#define EIGEN_MKL_EIG_SELFADJ(EIGTYPE, MKLTYPE, MKLRTYPE, MKLNAME, EIGCOLROW, MKLCOLROW ) \
-template<> inline\
+template<> inline \
SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, int options) \
{ \
diff --git a/resources/3rdparty/eigen/Eigen/src/Geometry/AngleAxis.h b/resources/3rdparty/eigen/Eigen/src/Geometry/AngleAxis.h
index 67197ac78..eee2cd0e1 100644
--- a/resources/3rdparty/eigen/Eigen/src/Geometry/AngleAxis.h
+++ b/resources/3rdparty/eigen/Eigen/src/Geometry/AngleAxis.h
@@ -76,7 +76,7 @@ public:
* \warning If the \a axis vector is not normalized, then the angle-axis object
* represents an invalid rotation. */
template<typename Derived>
- inline AngleAxis(Scalar angle, const MatrixBase<Derived>& axis) : m_axis(axis), m_angle(angle) {}
+ inline AngleAxis(const Scalar& angle, const MatrixBase<Derived>& axis) : m_axis(axis), m_angle(angle) {}
/** Constructs and initialize the angle-axis rotation from a quaternion \a q. */
template<typename QuatDerived> inline explicit AngleAxis(const QuaternionBase<QuatDerived>& q) { *this = q; }
/** Constructs and initialize the angle-axis rotation from a 3x3 rotation matrix. */
@@ -137,7 +137,7 @@ public:
* determined by \a prec.
*
* \sa MatrixBase::isApprox() */
- bool isApprox(const AngleAxis& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+ bool isApprox(const AngleAxis& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
{ return m_axis.isApprox(other.m_axis, prec) && internal::isApprox(m_angle,other.m_angle, prec); }
};
diff --git a/resources/3rdparty/eigen/Eigen/src/Geometry/Hyperplane.h b/resources/3rdparty/eigen/Eigen/src/Geometry/Hyperplane.h
index 1b7c7c78c..8b45c89e6 100644
--- a/resources/3rdparty/eigen/Eigen/src/Geometry/Hyperplane.h
+++ b/resources/3rdparty/eigen/Eigen/src/Geometry/Hyperplane.h
@@ -75,7 +75,7 @@ public:
* such that the algebraic equation of the plane is \f$ n \cdot x + d = 0 \f$.
* \warning the vector normal is assumed to be normalized.
*/
- inline Hyperplane(const VectorType& n, Scalar d)
+ inline Hyperplane(const VectorType& n, const Scalar& d)
: m_coeffs(n.size()+1)
{
normal() = n;
@@ -256,7 +256,7 @@ public:
*
* \sa MatrixBase::isApprox() */
template<int OtherOptions>
- bool isApprox(const Hyperplane<Scalar,AmbientDimAtCompileTime,OtherOptions>& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+ bool isApprox(const Hyperplane<Scalar,AmbientDimAtCompileTime,OtherOptions>& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
{ return m_coeffs.isApprox(other.m_coeffs, prec); }
protected:
diff --git a/resources/3rdparty/eigen/Eigen/src/Geometry/ParametrizedLine.h b/resources/3rdparty/eigen/Eigen/src/Geometry/ParametrizedLine.h
index 719a90441..ab5203e55 100644
--- a/resources/3rdparty/eigen/Eigen/src/Geometry/ParametrizedLine.h
+++ b/resources/3rdparty/eigen/Eigen/src/Geometry/ParametrizedLine.h
@@ -93,7 +93,7 @@ public:
VectorType projection(const VectorType& p) const
{ return origin() + direction().dot(p-origin()) * direction(); }
- VectorType pointAt( Scalar t ) const;
+ VectorType pointAt(const Scalar& t) const;
template <int OtherOptions>
Scalar intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
@@ -154,7 +154,7 @@ inline ParametrizedLine<_Scalar, _AmbientDim,_Options>::ParametrizedLine(const H
*/
template <typename _Scalar, int _AmbientDim, int _Options>
inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType
-ParametrizedLine<_Scalar, _AmbientDim,_Options>::pointAt( _Scalar t ) const
+ParametrizedLine<_Scalar, _AmbientDim,_Options>::pointAt(const _Scalar& t) const
{
return origin() + (direction()*t);
}
diff --git a/resources/3rdparty/eigen/Eigen/src/Geometry/Quaternion.h b/resources/3rdparty/eigen/Eigen/src/Geometry/Quaternion.h
index 8792e2da2..c4a3cbf51 100644
--- a/resources/3rdparty/eigen/Eigen/src/Geometry/Quaternion.h
+++ b/resources/3rdparty/eigen/Eigen/src/Geometry/Quaternion.h
@@ -161,7 +161,7 @@ public:
*
* \sa MatrixBase::isApprox() */
template<class OtherDerived>
- bool isApprox(const QuaternionBase<OtherDerived>& other, RealScalar prec = NumTraits<Scalar>::dummy_precision()) const
+ bool isApprox(const QuaternionBase<OtherDerived>& other, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const
{ return coeffs().isApprox(other.coeffs(), prec); }
/** return the result vector of \a v through the rotation*/
@@ -248,7 +248,7 @@ public:
* while internally the coefficients are stored in the following order:
* [\c x, \c y, \c z, \c w]
*/
- inline Quaternion(Scalar w, Scalar x, Scalar y, Scalar z) : m_coeffs(x, y, z, w){}
+ inline Quaternion(const Scalar& w, const Scalar& x, const Scalar& y, const Scalar& z) : m_coeffs(x, y, z, w){}
/** Constructs and initialize a quaternion from the array data */
inline Quaternion(const Scalar* data) : m_coeffs(data) {}
diff --git a/resources/3rdparty/eigen/Eigen/src/Geometry/Rotation2D.h b/resources/3rdparty/eigen/Eigen/src/Geometry/Rotation2D.h
index 868e2ef31..060ab10f3 100644
--- a/resources/3rdparty/eigen/Eigen/src/Geometry/Rotation2D.h
+++ b/resources/3rdparty/eigen/Eigen/src/Geometry/Rotation2D.h
@@ -59,7 +59,7 @@ protected:
public:
/** Construct a 2D counter clock wise rotation from the angle \a a in radian. */
- inline Rotation2D(Scalar a) : m_angle(a) {}
+ inline Rotation2D(const Scalar& a) : m_angle(a) {}
/** \returns the rotation angle */
inline Scalar angle() const { return m_angle; }
@@ -89,7 +89,7 @@ public:
/** \returns the spherical interpolation between \c *this and \a other using
* parameter \a t. It is in fact equivalent to a linear interpolation.
*/
- inline Rotation2D slerp(Scalar t, const Rotation2D& other) const
+ inline Rotation2D slerp(const Scalar& t, const Rotation2D& other) const
{ return m_angle * (1-t) + other.angle() * t; }
/** \returns \c *this with scalar type casted to \a NewScalarType
@@ -114,7 +114,7 @@ public:
* determined by \a prec.
*
* \sa MatrixBase::isApprox() */
- bool isApprox(const Rotation2D& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+ bool isApprox(const Rotation2D& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
{ return internal::isApprox(m_angle,other.m_angle, prec); }
};
diff --git a/resources/3rdparty/eigen/Eigen/src/Geometry/Scaling.h b/resources/3rdparty/eigen/Eigen/src/Geometry/Scaling.h
index 8edcac31c..1c25f36fe 100644
--- a/resources/3rdparty/eigen/Eigen/src/Geometry/Scaling.h
+++ b/resources/3rdparty/eigen/Eigen/src/Geometry/Scaling.h
@@ -99,7 +99,7 @@ public:
* determined by \a prec.
*
* \sa MatrixBase::isApprox() */
- bool isApprox(const UniformScaling& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+ bool isApprox(const UniformScaling& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
{ return internal::isApprox(m_factor, other.factor(), prec); }
};
@@ -122,11 +122,11 @@ static inline UniformScaling<std::complex<RealScalar> > Scaling(const std::compl
/** Constructs a 2D axis aligned scaling */
template<typename Scalar>
-static inline DiagonalMatrix<Scalar,2> Scaling(Scalar sx, Scalar sy)
+static inline DiagonalMatrix<Scalar,2> Scaling(const Scalar& sx, const Scalar& sy)
{ return DiagonalMatrix<Scalar,2>(sx, sy); }
/** Constructs a 3D axis aligned scaling */
template<typename Scalar>
-static inline DiagonalMatrix<Scalar,3> Scaling(Scalar sx, Scalar sy, Scalar sz)
+static inline DiagonalMatrix<Scalar,3> Scaling(const Scalar& sx, const Scalar& sy, const Scalar& sz)
{ return DiagonalMatrix<Scalar,3>(sx, sy, sz); }
/** Constructs an axis aligned scaling expression from vector expression \a coeffs
diff --git a/resources/3rdparty/eigen/Eigen/src/Geometry/Transform.h b/resources/3rdparty/eigen/Eigen/src/Geometry/Transform.h
index 4c1ef8eaa..887e718d6 100644
--- a/resources/3rdparty/eigen/Eigen/src/Geometry/Transform.h
+++ b/resources/3rdparty/eigen/Eigen/src/Geometry/Transform.h
@@ -506,8 +506,8 @@ public:
template<typename OtherDerived>
inline Transform& prescale(const MatrixBase<OtherDerived> &other);
- inline Transform& scale(Scalar s);
- inline Transform& prescale(Scalar s);
+ inline Transform& scale(const Scalar& s);
+ inline Transform& prescale(const Scalar& s);
template<typename OtherDerived>
inline Transform& translate(const MatrixBase<OtherDerived> &other);
@@ -521,8 +521,8 @@ public:
template<typename RotationType>
inline Transform& prerotate(const RotationType& rotation);
- Transform& shear(Scalar sx, Scalar sy);
- Transform& preshear(Scalar sx, Scalar sy);
+ Transform& shear(const Scalar& sx, const Scalar& sy);
+ Transform& preshear(const Scalar& sx, const Scalar& sy);
inline Transform& operator=(const TranslationType& t);
inline Transform& operator*=(const TranslationType& t) { return translate(t.vector()); }
@@ -584,7 +584,7 @@ public:
* determined by \a prec.
*
* \sa MatrixBase::isApprox() */
- bool isApprox(const Transform& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+ bool isApprox(const Transform& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
{ return m_matrix.isApprox(other.m_matrix, prec); }
/** Sets the last row to [0 ... 0 1]
@@ -794,7 +794,7 @@ Transform<Scalar,Dim,Mode,Options>::scale(const MatrixBase<OtherDerived> &other)
* \sa prescale(Scalar)
*/
template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::scale(Scalar s)
+inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::scale(const Scalar& s)
{
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
linearExt() *= s;
@@ -821,7 +821,7 @@ Transform<Scalar,Dim,Mode,Options>::prescale(const MatrixBase<OtherDerived> &oth
* \sa scale(Scalar)
*/
template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::prescale(Scalar s)
+inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::prescale(const Scalar& s)
{
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
m_matrix.template topRows<Dim>() *= s;
@@ -909,7 +909,7 @@ Transform<Scalar,Dim,Mode,Options>::prerotate(const RotationType& rotation)
*/
template<typename Scalar, int Dim, int Mode, int Options>
Transform<Scalar,Dim,Mode,Options>&
-Transform<Scalar,Dim,Mode,Options>::shear(Scalar sx, Scalar sy)
+Transform<Scalar,Dim,Mode,Options>::shear(const Scalar& sx, const Scalar& sy)
{
EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
@@ -925,7 +925,7 @@ Transform<Scalar,Dim,Mode,Options>::shear(Scalar sx, Scalar sy)
*/
template<typename Scalar, int Dim, int Mode, int Options>
Transform<Scalar,Dim,Mode,Options>&
-Transform<Scalar,Dim,Mode,Options>::preshear(Scalar sx, Scalar sy)
+Transform<Scalar,Dim,Mode,Options>::preshear(const Scalar& sx, const Scalar& sy)
{
EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
diff --git a/resources/3rdparty/eigen/Eigen/src/Geometry/Umeyama.h b/resources/3rdparty/eigen/Eigen/src/Geometry/Umeyama.h
index ac0939cde..345b47e0c 100644
--- a/resources/3rdparty/eigen/Eigen/src/Geometry/Umeyama.h
+++ b/resources/3rdparty/eigen/Eigen/src/Geometry/Umeyama.h
@@ -153,16 +153,21 @@ umeyama(const MatrixBase<Derived>& src, const MatrixBase<OtherDerived>& dst, boo
Rt.block(0,0,m,m).noalias() = svd.matrixU() * S.asDiagonal() * svd.matrixV().transpose();
}
- // Eq. (42)
- const Scalar c = 1/src_var * svd.singularValues().dot(S);
-
- // Eq. (41)
- // Note that we first assign dst_mean to the destination so that there no need
- // for a temporary.
- Rt.col(m).head(m) = dst_mean;
- Rt.col(m).head(m).noalias() -= c*Rt.topLeftCorner(m,m)*src_mean;
-
- if (with_scaling) Rt.block(0,0,m,m) *= c;
+ if (with_scaling)
+ {
+ // Eq. (42)
+ const Scalar c = 1/src_var * svd.singularValues().dot(S);
+
+ // Eq. (41)
+ Rt.col(m).head(m) = dst_mean;
+ Rt.col(m).head(m).noalias() -= c*Rt.topLeftCorner(m,m)*src_mean;
+ Rt.block(0,0,m,m) *= c;
+ }
+ else
+ {
+ Rt.col(m).head(m) = dst_mean;
+ Rt.col(m).head(m).noalias() -= Rt.topLeftCorner(m,m)*src_mean;
+ }
return Rt;
}
diff --git a/resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h b/resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
index 126341be8..5a822e0ea 100644
--- a/resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
+++ b/resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
@@ -39,10 +39,11 @@ bool bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
int maxIters = iters;
int n = mat.cols();
+ x = precond.solve(x);
VectorType r = rhs - mat * x;
VectorType r0 = r;
- RealScalar r0_sqnorm = r0.squaredNorm();
+ RealScalar r0_sqnorm = rhs.squaredNorm();
Scalar rho = 1;
Scalar alpha = 1;
Scalar w = 1;
@@ -223,7 +224,8 @@ public:
template<typename Rhs,typename Dest>
void _solve(const Rhs& b, Dest& x) const
{
- x.setZero();
+// x.setZero();
+ x = b;
_solveWithGuess(b,x);
}
diff --git a/resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h b/resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
index 224304f0e..5a71531cd 100644
--- a/resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
+++ b/resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
@@ -10,8 +10,56 @@
#ifndef EIGEN_INCOMPLETE_LUT_H
#define EIGEN_INCOMPLETE_LUT_H
+
namespace Eigen {
+namespace internal {
+
+/**
+ * Compute a quick-sort split of a vector
+ * On output, the vector row is permuted such that its elements satisfy
+ * abs(row(i)) >= abs(row(ncut)) if i<ncut
+ * abs(row(i)) <= abs(row(ncut)) if i>ncut
+ * \param row The vector of values
+ * \param ind The array of index for the elements in @p row
+ * \param ncut The number of largest elements to keep
+ **/
+template <typename VectorV, typename VectorI>
+int QuickSplit(VectorV &row, VectorI &ind, int ncut)
+{
+ typedef typename VectorV::RealScalar RealScalar;
+ using std::swap;
+ int mid;
+ int n = row.size(); /* length of the vector */
+ int first, last ;
+
+ ncut--; /* to fit the zero-based indices */
+ first = 0;
+ last = n-1;
+ if (ncut < first || ncut > last ) return 0;
+
+ do {
+ mid = first;
+ RealScalar abskey = std::abs(row(mid));
+ for (int j = first + 1; j <= last; j++) {
+ if ( std::abs(row(j)) > abskey) {
+ ++mid;
+ swap(row(mid), row(j));
+ swap(ind(mid), ind(j));
+ }
+ }
+ /* Interchange for the pivot element */
+ swap(row(mid), row(first));
+ swap(ind(mid), ind(first));
+
+ if (mid > ncut) last = mid - 1;
+ else if (mid < ncut ) first = mid + 1;
+ } while (mid != ncut );
+
+ return 0; /* mid is equal to ncut */
+}
+
+}// end namespace internal
/**
* \brief Incomplete LU factorization with dual-threshold strategy
* During the numerical factorization, two dropping rules are used :
@@ -126,10 +174,6 @@ class IncompleteLUT : internal::noncopyable
protected:
- template <typename VectorV, typename VectorI>
- int QuickSplit(VectorV &row, VectorI &ind, int ncut);
-
-
/** keeps off-diagonal entries; drops diagonal entries */
struct keep_diag {
inline bool operator() (const Index& row, const Index& col, const Scalar&) const
@@ -171,51 +215,6 @@ void IncompleteLUT<Scalar>::setFillfactor(int fillfactor)
this->m_fillfactor = fillfactor;
}
-
-/**
- * Compute a quick-sort split of a vector
- * On output, the vector row is permuted such that its elements satisfy
- * abs(row(i)) >= abs(row(ncut)) if i<ncut
- * abs(row(i)) <= abs(row(ncut)) if i>ncut
- * \param row The vector of values
- * \param ind The array of index for the elements in @p row
- * \param ncut The number of largest elements to keep
- **/
-template <typename Scalar>
-template <typename VectorV, typename VectorI>
-int IncompleteLUT<Scalar>::QuickSplit(VectorV &row, VectorI &ind, int ncut)
-{
- using std::swap;
- int mid;
- int n = row.size(); /* length of the vector */
- int first, last ;
-
- ncut--; /* to fit the zero-based indices */
- first = 0;
- last = n-1;
- if (ncut < first || ncut > last ) return 0;
-
- do {
- mid = first;
- RealScalar abskey = std::abs(row(mid));
- for (int j = first + 1; j <= last; j++) {
- if ( std::abs(row(j)) > abskey) {
- ++mid;
- swap(row(mid), row(j));
- swap(ind(mid), ind(j));
- }
- }
- /* Interchange for the pivot element */
- swap(row(mid), row(first));
- swap(ind(mid), ind(first));
-
- if (mid > ncut) last = mid - 1;
- else if (mid < ncut ) first = mid + 1;
- } while (mid != ncut );
-
- return 0; /* mid is equal to ncut */
-}
-
template <typename Scalar>
template<typename _MatrixType>
void IncompleteLUT<Scalar>::analyzePattern(const _MatrixType& amat)
@@ -400,7 +399,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
len = (std::min)(sizel, nnzL);
typename Vector::SegmentReturnType ul(u.segment(0, sizel));
typename VectorXi::SegmentReturnType jul(ju.segment(0, sizel));
- QuickSplit(ul, jul, len);
+ internal::QuickSplit(ul, jul, len);
// store the largest m_fill elements of the L part
m_lu.startVec(ii);
@@ -429,7 +428,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
len = (std::min)(sizeu, nnzU);
typename Vector::SegmentReturnType uu(u.segment(ii+1, sizeu-1));
typename VectorXi::SegmentReturnType juu(ju.segment(ii+1, sizeu-1));
- QuickSplit(uu, juu, len);
+ internal::QuickSplit(uu, juu, len);
// store the largest elements of the U part
for(int k = ii + 1; k < ii + len; k++)
diff --git a/resources/3rdparty/eigen/Eigen/src/Jacobi/Jacobi.h b/resources/3rdparty/eigen/Eigen/src/Jacobi/Jacobi.h
index a9c17dcdf..7eb19a023 100644
--- a/resources/3rdparty/eigen/Eigen/src/Jacobi/Jacobi.h
+++ b/resources/3rdparty/eigen/Eigen/src/Jacobi/Jacobi.h
@@ -207,7 +207,6 @@ void JacobiRotation<Scalar>::makeGivens(const Scalar& p, const Scalar& q, Scalar
template<typename Scalar>
void JacobiRotation<Scalar>::makeGivens(const Scalar& p, const Scalar& q, Scalar* r, internal::false_type)
{
-
if(q==Scalar(0))
{
m_c = p<Scalar(0) ? Scalar(-1) : Scalar(1);
@@ -303,6 +302,11 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
Scalar* EIGEN_RESTRICT x = &_x.coeffRef(0);
Scalar* EIGEN_RESTRICT y = &_y.coeffRef(0);
+
+ OtherScalar c = j.c();
+ OtherScalar s = j.s();
+ if (c==OtherScalar(1) && s==OtherScalar(0))
+ return;
/*** dynamic-size vectorized paths ***/
@@ -316,16 +320,16 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
Index alignedStart = internal::first_aligned(y, size);
Index alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize;
- const Packet pc = pset1<Packet>(j.c());
- const Packet ps = pset1<Packet>(j.s());
+ const Packet pc = pset1<Packet>(c);
+ const Packet ps = pset1<Packet>(s);
conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex,false> pcj;
for(Index i=0; i<alignedStart; ++i)
{
Scalar xi = x[i];
Scalar yi = y[i];
- x[i] = j.c() * xi + conj(j.s()) * yi;
- y[i] = -j.s() * xi + conj(j.c()) * yi;
+ x[i] = c * xi + conj(s) * yi;
+ y[i] = -s * xi + conj(c) * yi;
}
Scalar* EIGEN_RESTRICT px = x + alignedStart;
@@ -372,8 +376,8 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
{
Scalar xi = x[i];
Scalar yi = y[i];
- x[i] = j.c() * xi + conj(j.s()) * yi;
- y[i] = -j.s() * xi + conj(j.c()) * yi;
+ x[i] = c * xi + conj(s) * yi;
+ y[i] = -s * xi + conj(c) * yi;
}
}
@@ -382,8 +386,8 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
(VectorX::Flags & VectorY::Flags & PacketAccessBit) &&
(VectorX::Flags & VectorY::Flags & AlignedBit))
{
- const Packet pc = pset1<Packet>(j.c());
- const Packet ps = pset1<Packet>(j.s());
+ const Packet pc = pset1<Packet>(c);
+ const Packet ps = pset1<Packet>(s);
conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex,false> pcj;
Scalar* EIGEN_RESTRICT px = x;
Scalar* EIGEN_RESTRICT py = y;
@@ -405,8 +409,8 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
{
Scalar xi = *x;
Scalar yi = *y;
- *x = j.c() * xi + conj(j.s()) * yi;
- *y = -j.s() * xi + conj(j.c()) * yi;
+ *x = c * xi + conj(s) * yi;
+ *y = -s * xi + conj(c) * yi;
x += incrx;
y += incry;
}
diff --git a/resources/3rdparty/eigen/Eigen/src/MetisSupport/CMakeLists.txt b/resources/3rdparty/eigen/Eigen/src/MetisSupport/CMakeLists.txt
new file mode 100644
index 000000000..2bad31416
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/MetisSupport/CMakeLists.txt
@@ -0,0 +1,6 @@
+FILE(GLOB Eigen_MetisSupport_SRCS "*.h")
+
+INSTALL(FILES
+ ${Eigen_MetisSupport_SRCS}
+ DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/MetisSupport COMPONENT Devel
+ )
diff --git a/resources/3rdparty/eigen/Eigen/src/MetisSupport/MetisSupport.h b/resources/3rdparty/eigen/Eigen/src/MetisSupport/MetisSupport.h
new file mode 100644
index 000000000..a762d96f6
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/MetisSupport/MetisSupport.h
@@ -0,0 +1,138 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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/.
+#ifndef METIS_SUPPORT_H
+#define METIS_SUPPORT_H
+
+namespace Eigen {
+/**
+ * Get the fill-reducing ordering from the METIS package
+ *
+ * If A is the original matrix and Ap is the permuted matrix,
+ * the fill-reducing permutation is defined as follows :
+ * Row (column) i of A is the matperm(i) row (column) of Ap.
+ * WARNING: As computed by METIS, this corresponds to the vector iperm (instead of perm)
+ */
+template <typename Index>
+class MetisOrdering
+{
+public:
+ typedef PermutationMatrix<Dynamic,Dynamic,Index> PermutationType;
+ typedef Matrix<Index,Dynamic,1> IndexVector;
+
+ template <typename MatrixType>
+ void get_symmetrized_graph(const MatrixType& A)
+ {
+ Index m = A.cols();
+
+ // Get the transpose of the input matrix
+ MatrixType At = A.transpose();
+ // Get the number of nonzeros elements in each row/col of At+A
+ Index TotNz = 0;
+ IndexVector visited(m);
+ visited.setConstant(-1);
+ for (int j = 0; j < m; j++)
+ {
+ // Compute the union structure of of A(j,:) and At(j,:)
+ visited(j) = j; // Do not include the diagonal element
+ // Get the nonzeros in row/column j of A
+ for (typename MatrixType::InnerIterator it(A, j); it; ++it)
+ {
+ Index idx = it.index(); // Get the row index (for column major) or column index (for row major)
+ if (visited(idx) != j )
+ {
+ visited(idx) = j;
+ ++TotNz;
+ }
+ }
+ //Get the nonzeros in row/column j of At
+ for (typename MatrixType::InnerIterator it(At, j); it; ++it)
+ {
+ Index idx = it.index();
+ if(visited(idx) != j)
+ {
+ visited(idx) = j;
+ ++TotNz;
+ }
+ }
+ }
+ // Reserve place for A + At
+ m_indexPtr.resize(m+1);
+ m_innerIndices.resize(TotNz);
+
+ // Now compute the real adjacency list of each column/row
+ visited.setConstant(-1);
+ Index CurNz = 0;
+ for (int j = 0; j < m; j++)
+ {
+ m_indexPtr(j) = CurNz;
+
+ visited(j) = j; // Do not include the diagonal element
+ // Add the pattern of row/column j of A to A+At
+ for (typename MatrixType::InnerIterator it(A,j); it; ++it)
+ {
+ Index idx = it.index(); // Get the row index (for column major) or column index (for row major)
+ if (visited(idx) != j )
+ {
+ visited(idx) = j;
+ m_innerIndices(CurNz) = idx;
+ CurNz++;
+ }
+ }
+ //Add the pattern of row/column j of At to A+At
+ for (typename MatrixType::InnerIterator it(At, j); it; ++it)
+ {
+ Index idx = it.index();
+ if(visited(idx) != j)
+ {
+ visited(idx) = j;
+ m_innerIndices(CurNz) = idx;
+ ++CurNz;
+ }
+ }
+ }
+ m_indexPtr(m) = CurNz;
+ }
+
+ template <typename MatrixType>
+ void operator() (const MatrixType& A, PermutationType& matperm)
+ {
+ Index m = A.cols();
+ IndexVector perm(m),iperm(m);
+ // First, symmetrize the matrix graph.
+ get_symmetrized_graph(A);
+ int output_error;
+
+ // Call the fill-reducing routine from METIS
+ output_error = METIS_NodeND(&m, m_indexPtr.data(), m_innerIndices.data(), NULL, NULL, perm.data(), iperm.data());
+
+ if(output_error != METIS_OK)
+ {
+ //FIXME The ordering interface should define a class of possible errors
+ std::cerr << "ERROR WHILE CALLING THE METIS PACKAGE \n";
+ return;
+ }
+
+ // Get the fill-reducing permutation
+ //NOTE: If Ap is the permuted matrix then perm and iperm vectors are defined as follows
+ // Row (column) i of Ap is the perm(i) row(column) of A, and row (column) i of A is the iperm(i) row(column) of Ap
+
+ // To be consistent with the use of the permutation in SparseLU module, we thus keep the iperm vector
+ matperm.resize(m);
+ for (int j = 0; j < m; j++)
+ matperm.indices()(j) = iperm(j);
+
+ }
+
+ protected:
+ IndexVector m_indexPtr; // Pointer to the adjacenccy list of each row/column
+ IndexVector m_innerIndices; // Adjacency list
+};
+
+}// end namespace eigen
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/OrderingMethods/Eigen_Colamd.h b/resources/3rdparty/eigen/Eigen/src/OrderingMethods/Eigen_Colamd.h
new file mode 100644
index 000000000..6dc1f280d
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/OrderingMethods/Eigen_Colamd.h
@@ -0,0 +1,1849 @@
+// // This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Desire Nuentsa Wakam <desire.nuentsa_wakam@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/.
+
+// This file is modified from the colamd/symamd library. The copyright is below
+
+// The authors of the code itself are Stefan I. Larimore and Timothy A.
+// Davis (davis@cise.ufl.edu), University of Florida. The algorithm was
+// developed in collaboration with John Gilbert, Xerox PARC, and Esmond
+// Ng, Oak Ridge National Laboratory.
+//
+// Date:
+//
+// September 8, 2003. Version 2.3.
+//
+// Acknowledgements:
+//
+// This work was supported by the National Science Foundation, under
+// grants DMS-9504974 and DMS-9803599.
+//
+// Notice:
+//
+// Copyright (c) 1998-2003 by the University of Florida.
+// All Rights Reserved.
+//
+// THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+// EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+//
+// Permission is hereby granted to use, copy, modify, and/or distribute
+// this program, provided that the Copyright, this License, and the
+// Availability of the original version is retained on all copies and made
+// accessible to the end-user of any code or package that includes COLAMD
+// or any modified version of COLAMD.
+//
+// Availability:
+//
+// The colamd/symamd library is available at
+//
+// http://www.cise.ufl.edu/research/sparse/colamd/
+
+// This is the http://www.cise.ufl.edu/research/sparse/colamd/colamd.h
+// file. It is required by the colamd.c, colamdmex.c, and symamdmex.c
+// files, and by any C code that calls the routines whose prototypes are
+// listed below, or that uses the colamd/symamd definitions listed below.
+
+#ifndef EIGEN_COLAMD_H
+#define EIGEN_COLAMD_H
+namespace internal {
+/* Ensure that debugging is turned off: */
+#ifndef COLAMD_NDEBUG
+#define COLAMD_NDEBUG
+#endif /* NDEBUG */
+/* ========================================================================== */
+/* === Knob and statistics definitions ====================================== */
+/* ========================================================================== */
+
+/* size of the knobs [ ] array. Only knobs [0..1] are currently used. */
+#define COLAMD_KNOBS 20
+
+/* number of output statistics. Only stats [0..6] are currently used. */
+#define COLAMD_STATS 20
+
+/* knobs [0] and stats [0]: dense row knob and output statistic. */
+#define COLAMD_DENSE_ROW 0
+
+/* knobs [1] and stats [1]: dense column knob and output statistic. */
+#define COLAMD_DENSE_COL 1
+
+/* stats [2]: memory defragmentation count output statistic */
+#define COLAMD_DEFRAG_COUNT 2
+
+/* stats [3]: colamd status: zero OK, > 0 warning or notice, < 0 error */
+#define COLAMD_STATUS 3
+
+/* stats [4..6]: error info, or info on jumbled columns */
+#define COLAMD_INFO1 4
+#define COLAMD_INFO2 5
+#define COLAMD_INFO3 6
+
+/* error codes returned in stats [3]: */
+#define COLAMD_OK (0)
+#define COLAMD_OK_BUT_JUMBLED (1)
+#define COLAMD_ERROR_A_not_present (-1)
+#define COLAMD_ERROR_p_not_present (-2)
+#define COLAMD_ERROR_nrow_negative (-3)
+#define COLAMD_ERROR_ncol_negative (-4)
+#define COLAMD_ERROR_nnz_negative (-5)
+#define COLAMD_ERROR_p0_nonzero (-6)
+#define COLAMD_ERROR_A_too_small (-7)
+#define COLAMD_ERROR_col_length_negative (-8)
+#define COLAMD_ERROR_row_index_out_of_bounds (-9)
+#define COLAMD_ERROR_out_of_memory (-10)
+#define COLAMD_ERROR_internal_error (-999)
+
+/* ========================================================================== */
+/* === Definitions ========================================================== */
+/* ========================================================================== */
+
+#define COLAMD_MAX(a,b) (((a) > (b)) ? (a) : (b))
+#define COLAMD_MIN(a,b) (((a) < (b)) ? (a) : (b))
+
+#define ONES_COMPLEMENT(r) (-(r)-1)
+
+/* -------------------------------------------------------------------------- */
+
+#define COLAMD_EMPTY (-1)
+
+/* Row and column status */
+#define ALIVE (0)
+#define DEAD (-1)
+
+/* Column status */
+#define DEAD_PRINCIPAL (-1)
+#define DEAD_NON_PRINCIPAL (-2)
+
+/* Macros for row and column status update and checking. */
+#define ROW_IS_DEAD(r) ROW_IS_MARKED_DEAD (Row[r].shared2.mark)
+#define ROW_IS_MARKED_DEAD(row_mark) (row_mark < ALIVE)
+#define ROW_IS_ALIVE(r) (Row [r].shared2.mark >= ALIVE)
+#define COL_IS_DEAD(c) (Col [c].start < ALIVE)
+#define COL_IS_ALIVE(c) (Col [c].start >= ALIVE)
+#define COL_IS_DEAD_PRINCIPAL(c) (Col [c].start == DEAD_PRINCIPAL)
+#define KILL_ROW(r) { Row [r].shared2.mark = DEAD ; }
+#define KILL_PRINCIPAL_COL(c) { Col [c].start = DEAD_PRINCIPAL ; }
+#define KILL_NON_PRINCIPAL_COL(c) { Col [c].start = DEAD_NON_PRINCIPAL ; }
+
+/* ========================================================================== */
+/* === Colamd reporting mechanism =========================================== */
+/* ========================================================================== */
+
+ // == Row and Column structures ==
+typedef struct colamd_col_struct
+{
+ int start ; /* index for A of first row in this column, or DEAD */
+ /* if column is dead */
+ int length ; /* number of rows in this column */
+ union
+ {
+ int thickness ; /* number of original columns represented by this */
+ /* col, if the column is alive */
+ int parent ; /* parent in parent tree super-column structure, if */
+ /* the column is dead */
+ } shared1 ;
+ union
+ {
+ int score ; /* the score used to maintain heap, if col is alive */
+ int order ; /* pivot ordering of this column, if col is dead */
+ } shared2 ;
+ union
+ {
+ int headhash ; /* head of a hash bucket, if col is at the head of */
+ /* a degree list */
+ int hash ; /* hash value, if col is not in a degree list */
+ int prev ; /* previous column in degree list, if col is in a */
+ /* degree list (but not at the head of a degree list) */
+ } shared3 ;
+ union
+ {
+ int degree_next ; /* next column, if col is in a degree list */
+ int hash_next ; /* next column, if col is in a hash list */
+ } shared4 ;
+
+} colamd_col ;
+
+typedef struct Colamd_Row_struct
+{
+ int start ; /* index for A of first col in this row */
+ int length ; /* number of principal columns in this row */
+ union
+ {
+ int degree ; /* number of principal & non-principal columns in row */
+ int p ; /* used as a row pointer in init_rows_cols () */
+ } shared1 ;
+ union
+ {
+ int mark ; /* for computing set differences and marking dead rows*/
+ int first_column ;/* first column in row (used in garbage collection) */
+ } shared2 ;
+
+} Colamd_Row ;
+
+/* ========================================================================== */
+/* === Colamd recommended memory size ======================================= */
+/* ========================================================================== */
+
+/*
+ The recommended length Alen of the array A passed to colamd is given by
+ the COLAMD_RECOMMENDED (nnz, n_row, n_col) macro. It returns -1 if any
+ argument is negative. 2*nnz space is required for the row and column
+ indices of the matrix. colamd_c (n_col) + colamd_r (n_row) space is
+ required for the Col and Row arrays, respectively, which are internal to
+ colamd. An additional n_col space is the minimal amount of "elbow room",
+ and nnz/5 more space is recommended for run time efficiency.
+
+ This macro is not needed when using symamd.
+
+ Explicit typecast to int added Sept. 23, 2002, COLAMD version 2.2, to avoid
+ gcc -pedantic warning messages.
+*/
+
+inline int colamd_c(int n_col)
+{ return int( ((n_col) + 1) * sizeof (colamd_col) / sizeof (int) ) ; }
+
+inline int colamd_r(int n_row)
+{ return int(((n_row) + 1) * sizeof (Colamd_Row) / sizeof (int)); }
+
+ // Various routines
+inline int colamd_recommended (int nnz, int n_row, int n_col) ;
+
+static inline void colamd_set_defaults (double knobs [COLAMD_KNOBS]) ;
+
+static bool colamd (int n_row, int n_col, int Alen, int A [], int p [], double knobs[COLAMD_KNOBS], int stats [COLAMD_STATS]) ;
+
+static int init_rows_cols (int n_row, int n_col, Colamd_Row Row [], colamd_col col [], int A [], int p [], int stats[COLAMD_STATS] );
+
+static void init_scoring (int n_row, int n_col, Colamd_Row Row [], colamd_col Col [], int A [], int head [], double knobs[COLAMD_KNOBS], int *p_n_row2, int *p_n_col2, int *p_max_deg);
+
+static int find_ordering (int n_row, int n_col, int Alen, Colamd_Row Row [], colamd_col Col [], int A [], int head [], int n_col2, int max_deg, int pfree);
+
+static void order_children (int n_col, colamd_col Col [], int p []);
+
+static void detect_super_cols (
+ colamd_col Col [],
+ int A [],
+ int head [],
+ int row_start,
+ int row_length ) ;
+
+static int garbage_collection (int n_row, int n_col, Colamd_Row Row [], colamd_col Col [], int A [], int *pfree) ;
+
+static inline int clear_mark (int n_row, Colamd_Row Row [] ) ;
+
+/* === No debugging ========================================================= */
+
+#define COLAMD_DEBUG0(params) ;
+#define COLAMD_DEBUG1(params) ;
+#define COLAMD_DEBUG2(params) ;
+#define COLAMD_DEBUG3(params) ;
+#define COLAMD_DEBUG4(params) ;
+
+#define COLAMD_ASSERT(expression) ((void) 0)
+
+
+/**
+ * \brief Returns the recommended value of Alen
+ *
+ * Returns recommended value of Alen for use by colamd.
+ * Returns -1 if any input argument is negative.
+ * The use of this routine or macro is optional.
+ * Note that the macro uses its arguments more than once,
+ * so be careful for side effects, if you pass expressions as arguments to COLAMD_RECOMMENDED.
+ *
+ * \param nnz nonzeros in A
+ * \param n_row number of rows in A
+ * \param n_col number of columns in A
+ * \return recommended value of Alen for use by colamd
+ */
+inline int colamd_recommended ( int nnz, int n_row, int n_col)
+{
+ if ((nnz) < 0 || (n_row) < 0 || (n_col) < 0)
+ return (-1);
+ else
+ return (2 * (nnz) + colamd_c (n_col) + colamd_r (n_row) + (n_col) + ((nnz) / 5));
+}
+
+/**
+ * \brief set default parameters The use of this routine is optional.
+ *
+ * Colamd: rows with more than (knobs [COLAMD_DENSE_ROW] * n_col)
+ * entries are removed prior to ordering. Columns with more than
+ * (knobs [COLAMD_DENSE_COL] * n_row) entries are removed prior to
+ * ordering, and placed last in the output column ordering.
+ *
+ * COLAMD_DENSE_ROW and COLAMD_DENSE_COL are defined as 0 and 1,
+ * respectively, in colamd.h. Default values of these two knobs
+ * are both 0.5. Currently, only knobs [0] and knobs [1] are
+ * used, but future versions may use more knobs. If so, they will
+ * be properly set to their defaults by the future version of
+ * colamd_set_defaults, so that the code that calls colamd will
+ * not need to change, assuming that you either use
+ * colamd_set_defaults, or pass a (double *) NULL pointer as the
+ * knobs array to colamd or symamd.
+ *
+ * \param knobs parameter settings for colamd
+ */
+static inline void colamd_set_defaults(double knobs[COLAMD_KNOBS])
+{
+ /* === Local variables ================================================== */
+
+ int i ;
+
+ if (!knobs)
+ {
+ return ; /* no knobs to initialize */
+ }
+ for (i = 0 ; i < COLAMD_KNOBS ; i++)
+ {
+ knobs [i] = 0 ;
+ }
+ knobs [COLAMD_DENSE_ROW] = 0.5 ; /* ignore rows over 50% dense */
+ knobs [COLAMD_DENSE_COL] = 0.5 ; /* ignore columns over 50% dense */
+}
+
+/**
+ * \brief Computes a column ordering using the column approximate minimum degree ordering
+ *
+ * Computes a column ordering (Q) of A such that P(AQ)=LU or
+ * (AQ)'AQ=LL' have less fill-in and require fewer floating point
+ * operations than factorizing the unpermuted matrix A or A'A,
+ * respectively.
+ *
+ *
+ * \param n_row number of rows in A
+ * \param n_col number of columns in A
+ * \param Alen, size of the array A
+ * \param A row indices of the matrix, of size ALen
+ * \param p column pointers of A, of size n_col+1
+ * \param knobs parameter settings for colamd
+ * \param stats colamd output statistics and error codes
+ */
+static bool colamd(int n_row, int n_col, int Alen, int *A, int *p, double knobs[COLAMD_KNOBS], int stats[COLAMD_STATS])
+{
+ /* === Local variables ================================================== */
+
+ int i ; /* loop index */
+ int nnz ; /* nonzeros in A */
+ int Row_size ; /* size of Row [], in integers */
+ int Col_size ; /* size of Col [], in integers */
+ int need ; /* minimum required length of A */
+ Colamd_Row *Row ; /* pointer into A of Row [0..n_row] array */
+ colamd_col *Col ; /* pointer into A of Col [0..n_col] array */
+ int n_col2 ; /* number of non-dense, non-empty columns */
+ int n_row2 ; /* number of non-dense, non-empty rows */
+ int ngarbage ; /* number of garbage collections performed */
+ int max_deg ; /* maximum row degree */
+ double default_knobs [COLAMD_KNOBS] ; /* default knobs array */
+
+
+ /* === Check the input arguments ======================================== */
+
+ if (!stats)
+ {
+ COLAMD_DEBUG0 (("colamd: stats not present\n")) ;
+ return (false) ;
+ }
+ for (i = 0 ; i < COLAMD_STATS ; i++)
+ {
+ stats [i] = 0 ;
+ }
+ stats [COLAMD_STATUS] = COLAMD_OK ;
+ stats [COLAMD_INFO1] = -1 ;
+ stats [COLAMD_INFO2] = -1 ;
+
+ if (!A) /* A is not present */
+ {
+ stats [COLAMD_STATUS] = COLAMD_ERROR_A_not_present ;
+ COLAMD_DEBUG0 (("colamd: A not present\n")) ;
+ return (false) ;
+ }
+
+ if (!p) /* p is not present */
+ {
+ stats [COLAMD_STATUS] = COLAMD_ERROR_p_not_present ;
+ COLAMD_DEBUG0 (("colamd: p not present\n")) ;
+ return (false) ;
+ }
+
+ if (n_row < 0) /* n_row must be >= 0 */
+ {
+ stats [COLAMD_STATUS] = COLAMD_ERROR_nrow_negative ;
+ stats [COLAMD_INFO1] = n_row ;
+ COLAMD_DEBUG0 (("colamd: nrow negative %d\n", n_row)) ;
+ return (false) ;
+ }
+
+ if (n_col < 0) /* n_col must be >= 0 */
+ {
+ stats [COLAMD_STATUS] = COLAMD_ERROR_ncol_negative ;
+ stats [COLAMD_INFO1] = n_col ;
+ COLAMD_DEBUG0 (("colamd: ncol negative %d\n", n_col)) ;
+ return (false) ;
+ }
+
+ nnz = p [n_col] ;
+ if (nnz < 0) /* nnz must be >= 0 */
+ {
+ stats [COLAMD_STATUS] = COLAMD_ERROR_nnz_negative ;
+ stats [COLAMD_INFO1] = nnz ;
+ COLAMD_DEBUG0 (("colamd: number of entries negative %d\n", nnz)) ;
+ return (false) ;
+ }
+
+ if (p [0] != 0)
+ {
+ stats [COLAMD_STATUS] = COLAMD_ERROR_p0_nonzero ;
+ stats [COLAMD_INFO1] = p [0] ;
+ COLAMD_DEBUG0 (("colamd: p[0] not zero %d\n", p [0])) ;
+ return (false) ;
+ }
+
+ /* === If no knobs, set default knobs =================================== */
+
+ if (!knobs)
+ {
+ colamd_set_defaults (default_knobs) ;
+ knobs = default_knobs ;
+ }
+
+ /* === Allocate the Row and Col arrays from array A ===================== */
+
+ Col_size = colamd_c (n_col) ;
+ Row_size = colamd_r (n_row) ;
+ need = 2*nnz + n_col + Col_size + Row_size ;
+
+ if (need > Alen)
+ {
+ /* not enough space in array A to perform the ordering */
+ stats [COLAMD_STATUS] = COLAMD_ERROR_A_too_small ;
+ stats [COLAMD_INFO1] = need ;
+ stats [COLAMD_INFO2] = Alen ;
+ COLAMD_DEBUG0 (("colamd: Need Alen >= %d, given only Alen = %d\n", need,Alen));
+ return (false) ;
+ }
+
+ Alen -= Col_size + Row_size ;
+ Col = (colamd_col *) &A [Alen] ;
+ Row = (Colamd_Row *) &A [Alen + Col_size] ;
+
+ /* === Construct the row and column data structures ===================== */
+
+ if (!init_rows_cols (n_row, n_col, Row, Col, A, p, stats))
+ {
+ /* input matrix is invalid */
+ COLAMD_DEBUG0 (("colamd: Matrix invalid\n")) ;
+ return (false) ;
+ }
+
+ /* === Initialize scores, kill dense rows/columns ======================= */
+
+ init_scoring (n_row, n_col, Row, Col, A, p, knobs,
+ &n_row2, &n_col2, &max_deg) ;
+
+ /* === Order the supercolumns =========================================== */
+
+ ngarbage = find_ordering (n_row, n_col, Alen, Row, Col, A, p,
+ n_col2, max_deg, 2*nnz) ;
+
+ /* === Order the non-principal columns ================================== */
+
+ order_children (n_col, Col, p) ;
+
+ /* === Return statistics in stats ======================================= */
+
+ stats [COLAMD_DENSE_ROW] = n_row - n_row2 ;
+ stats [COLAMD_DENSE_COL] = n_col - n_col2 ;
+ stats [COLAMD_DEFRAG_COUNT] = ngarbage ;
+ COLAMD_DEBUG0 (("colamd: done.\n")) ;
+ return (true) ;
+}
+
+/* ========================================================================== */
+/* === NON-USER-CALLABLE ROUTINES: ========================================== */
+/* ========================================================================== */
+
+/* There are no user-callable routines beyond this point in the file */
+
+
+/* ========================================================================== */
+/* === init_rows_cols ======================================================= */
+/* ========================================================================== */
+
+/*
+ Takes the column form of the matrix in A and creates the row form of the
+ matrix. Also, row and column attributes are stored in the Col and Row
+ structs. If the columns are un-sorted or contain duplicate row indices,
+ this routine will also sort and remove duplicate row indices from the
+ column form of the matrix. Returns false if the matrix is invalid,
+ true otherwise. Not user-callable.
+*/
+
+ static int init_rows_cols /* returns true if OK, or false otherwise */
+(
+ /* === Parameters ======================================================= */
+
+ int n_row, /* number of rows of A */
+ int n_col, /* number of columns of A */
+ Colamd_Row Row [], /* of size n_row+1 */
+ colamd_col Col [], /* of size n_col+1 */
+ int A [], /* row indices of A, of size Alen */
+ int p [], /* pointers to columns in A, of size n_col+1 */
+ int stats [COLAMD_STATS] /* colamd statistics */
+)
+{
+ /* === Local variables ================================================== */
+
+ int col ; /* a column index */
+ int row ; /* a row index */
+ int *cp ; /* a column pointer */
+ int *cp_end ; /* a pointer to the end of a column */
+ int *rp ; /* a row pointer */
+ int *rp_end ; /* a pointer to the end of a row */
+ int last_row ; /* previous row */
+
+ /* === Initialize columns, and check column pointers ==================== */
+
+ for (col = 0 ; col < n_col ; col++)
+ {
+ Col [col].start = p [col] ;
+ Col [col].length = p [col+1] - p [col] ;
+
+ if (Col [col].length < 0)
+ {
+ /* column pointers must be non-decreasing */
+ stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ;
+ stats [COLAMD_INFO1] = col ;
+ stats [COLAMD_INFO2] = Col [col].length ;
+ COLAMD_DEBUG0 (("colamd: col %d length %d < 0\n", col, Col [col].length)) ;
+ return (false) ;
+ }
+
+ Col [col].shared1.thickness = 1 ;
+ Col [col].shared2.score = 0 ;
+ Col [col].shared3.prev = COLAMD_EMPTY ;
+ Col [col].shared4.degree_next = COLAMD_EMPTY ;
+ }
+
+ /* p [0..n_col] no longer needed, used as "head" in subsequent routines */
+
+ /* === Scan columns, compute row degrees, and check row indices ========= */
+
+ stats [COLAMD_INFO3] = 0 ; /* number of duplicate or unsorted row indices*/
+
+ for (row = 0 ; row < n_row ; row++)
+ {
+ Row [row].length = 0 ;
+ Row [row].shared2.mark = -1 ;
+ }
+
+ for (col = 0 ; col < n_col ; col++)
+ {
+ last_row = -1 ;
+
+ cp = &A [p [col]] ;
+ cp_end = &A [p [col+1]] ;
+
+ while (cp < cp_end)
+ {
+ row = *cp++ ;
+
+ /* make sure row indices within range */
+ if (row < 0 || row >= n_row)
+ {
+ stats [COLAMD_STATUS] = COLAMD_ERROR_row_index_out_of_bounds ;
+ stats [COLAMD_INFO1] = col ;
+ stats [COLAMD_INFO2] = row ;
+ stats [COLAMD_INFO3] = n_row ;
+ COLAMD_DEBUG0 (("colamd: row %d col %d out of bounds\n", row, col)) ;
+ return (false) ;
+ }
+
+ if (row <= last_row || Row [row].shared2.mark == col)
+ {
+ /* row index are unsorted or repeated (or both), thus col */
+ /* is jumbled. This is a notice, not an error condition. */
+ stats [COLAMD_STATUS] = COLAMD_OK_BUT_JUMBLED ;
+ stats [COLAMD_INFO1] = col ;
+ stats [COLAMD_INFO2] = row ;
+ (stats [COLAMD_INFO3]) ++ ;
+ COLAMD_DEBUG1 (("colamd: row %d col %d unsorted/duplicate\n",row,col));
+ }
+
+ if (Row [row].shared2.mark != col)
+ {
+ Row [row].length++ ;
+ }
+ else
+ {
+ /* this is a repeated entry in the column, */
+ /* it will be removed */
+ Col [col].length-- ;
+ }
+
+ /* mark the row as having been seen in this column */
+ Row [row].shared2.mark = col ;
+
+ last_row = row ;
+ }
+ }
+
+ /* === Compute row pointers ============================================= */
+
+ /* row form of the matrix starts directly after the column */
+ /* form of matrix in A */
+ Row [0].start = p [n_col] ;
+ Row [0].shared1.p = Row [0].start ;
+ Row [0].shared2.mark = -1 ;
+ for (row = 1 ; row < n_row ; row++)
+ {
+ Row [row].start = Row [row-1].start + Row [row-1].length ;
+ Row [row].shared1.p = Row [row].start ;
+ Row [row].shared2.mark = -1 ;
+ }
+
+ /* === Create row form ================================================== */
+
+ if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED)
+ {
+ /* if cols jumbled, watch for repeated row indices */
+ for (col = 0 ; col < n_col ; col++)
+ {
+ cp = &A [p [col]] ;
+ cp_end = &A [p [col+1]] ;
+ while (cp < cp_end)
+ {
+ row = *cp++ ;
+ if (Row [row].shared2.mark != col)
+ {
+ A [(Row [row].shared1.p)++] = col ;
+ Row [row].shared2.mark = col ;
+ }
+ }
+ }
+ }
+ else
+ {
+ /* if cols not jumbled, we don't need the mark (this is faster) */
+ for (col = 0 ; col < n_col ; col++)
+ {
+ cp = &A [p [col]] ;
+ cp_end = &A [p [col+1]] ;
+ while (cp < cp_end)
+ {
+ A [(Row [*cp++].shared1.p)++] = col ;
+ }
+ }
+ }
+
+ /* === Clear the row marks and set row degrees ========================== */
+
+ for (row = 0 ; row < n_row ; row++)
+ {
+ Row [row].shared2.mark = 0 ;
+ Row [row].shared1.degree = Row [row].length ;
+ }
+
+ /* === See if we need to re-create columns ============================== */
+
+ if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED)
+ {
+ COLAMD_DEBUG0 (("colamd: reconstructing column form, matrix jumbled\n")) ;
+
+
+ /* === Compute col pointers ========================================= */
+
+ /* col form of the matrix starts at A [0]. */
+ /* Note, we may have a gap between the col form and the row */
+ /* form if there were duplicate entries, if so, it will be */
+ /* removed upon the first garbage collection */
+ Col [0].start = 0 ;
+ p [0] = Col [0].start ;
+ for (col = 1 ; col < n_col ; col++)
+ {
+ /* note that the lengths here are for pruned columns, i.e. */
+ /* no duplicate row indices will exist for these columns */
+ Col [col].start = Col [col-1].start + Col [col-1].length ;
+ p [col] = Col [col].start ;
+ }
+
+ /* === Re-create col form =========================================== */
+
+ for (row = 0 ; row < n_row ; row++)
+ {
+ rp = &A [Row [row].start] ;
+ rp_end = rp + Row [row].length ;
+ while (rp < rp_end)
+ {
+ A [(p [*rp++])++] = row ;
+ }
+ }
+ }
+
+ /* === Done. Matrix is not (or no longer) jumbled ====================== */
+
+ return (true) ;
+}
+
+
+/* ========================================================================== */
+/* === init_scoring ========================================================= */
+/* ========================================================================== */
+
+/*
+ Kills dense or empty columns and rows, calculates an initial score for
+ each column, and places all columns in the degree lists. Not user-callable.
+*/
+
+static void init_scoring
+(
+ /* === Parameters ======================================================= */
+
+ int n_row, /* number of rows of A */
+ int n_col, /* number of columns of A */
+ Colamd_Row Row [], /* of size n_row+1 */
+ colamd_col Col [], /* of size n_col+1 */
+ int A [], /* column form and row form of A */
+ int head [], /* of size n_col+1 */
+ double knobs [COLAMD_KNOBS],/* parameters */
+ int *p_n_row2, /* number of non-dense, non-empty rows */
+ int *p_n_col2, /* number of non-dense, non-empty columns */
+ int *p_max_deg /* maximum row degree */
+)
+{
+ /* === Local variables ================================================== */
+
+ int c ; /* a column index */
+ int r, row ; /* a row index */
+ int *cp ; /* a column pointer */
+ int deg ; /* degree of a row or column */
+ int *cp_end ; /* a pointer to the end of a column */
+ int *new_cp ; /* new column pointer */
+ int col_length ; /* length of pruned column */
+ int score ; /* current column score */
+ int n_col2 ; /* number of non-dense, non-empty columns */
+ int n_row2 ; /* number of non-dense, non-empty rows */
+ int dense_row_count ; /* remove rows with more entries than this */
+ int dense_col_count ; /* remove cols with more entries than this */
+ int min_score ; /* smallest column score */
+ int max_deg ; /* maximum row degree */
+ int next_col ; /* Used to add to degree list.*/
+
+
+ /* === Extract knobs ==================================================== */
+
+ dense_row_count = COLAMD_MAX (0, COLAMD_MIN (knobs [COLAMD_DENSE_ROW] * n_col, n_col)) ;
+ dense_col_count = COLAMD_MAX (0, COLAMD_MIN (knobs [COLAMD_DENSE_COL] * n_row, n_row)) ;
+ COLAMD_DEBUG1 (("colamd: densecount: %d %d\n", dense_row_count, dense_col_count)) ;
+ max_deg = 0 ;
+ n_col2 = n_col ;
+ n_row2 = n_row ;
+
+ /* === Kill empty columns =============================================== */
+
+ /* Put the empty columns at the end in their natural order, so that LU */
+ /* factorization can proceed as far as possible. */
+ for (c = n_col-1 ; c >= 0 ; c--)
+ {
+ deg = Col [c].length ;
+ if (deg == 0)
+ {
+ /* this is a empty column, kill and order it last */
+ Col [c].shared2.order = --n_col2 ;
+ KILL_PRINCIPAL_COL (c) ;
+ }
+ }
+ COLAMD_DEBUG1 (("colamd: null columns killed: %d\n", n_col - n_col2)) ;
+
+ /* === Kill dense columns =============================================== */
+
+ /* Put the dense columns at the end, in their natural order */
+ for (c = n_col-1 ; c >= 0 ; c--)
+ {
+ /* skip any dead columns */
+ if (COL_IS_DEAD (c))
+ {
+ continue ;
+ }
+ deg = Col [c].length ;
+ if (deg > dense_col_count)
+ {
+ /* this is a dense column, kill and order it last */
+ Col [c].shared2.order = --n_col2 ;
+ /* decrement the row degrees */
+ cp = &A [Col [c].start] ;
+ cp_end = cp + Col [c].length ;
+ while (cp < cp_end)
+ {
+ Row [*cp++].shared1.degree-- ;
+ }
+ KILL_PRINCIPAL_COL (c) ;
+ }
+ }
+ COLAMD_DEBUG1 (("colamd: Dense and null columns killed: %d\n", n_col - n_col2)) ;
+
+ /* === Kill dense and empty rows ======================================== */
+
+ for (r = 0 ; r < n_row ; r++)
+ {
+ deg = Row [r].shared1.degree ;
+ COLAMD_ASSERT (deg >= 0 && deg <= n_col) ;
+ if (deg > dense_row_count || deg == 0)
+ {
+ /* kill a dense or empty row */
+ KILL_ROW (r) ;
+ --n_row2 ;
+ }
+ else
+ {
+ /* keep track of max degree of remaining rows */
+ max_deg = COLAMD_MAX (max_deg, deg) ;
+ }
+ }
+ COLAMD_DEBUG1 (("colamd: Dense and null rows killed: %d\n", n_row - n_row2)) ;
+
+ /* === Compute initial column scores ==================================== */
+
+ /* At this point the row degrees are accurate. They reflect the number */
+ /* of "live" (non-dense) columns in each row. No empty rows exist. */
+ /* Some "live" columns may contain only dead rows, however. These are */
+ /* pruned in the code below. */
+
+ /* now find the initial matlab score for each column */
+ for (c = n_col-1 ; c >= 0 ; c--)
+ {
+ /* skip dead column */
+ if (COL_IS_DEAD (c))
+ {
+ continue ;
+ }
+ score = 0 ;
+ cp = &A [Col [c].start] ;
+ new_cp = cp ;
+ cp_end = cp + Col [c].length ;
+ while (cp < cp_end)
+ {
+ /* get a row */
+ row = *cp++ ;
+ /* skip if dead */
+ if (ROW_IS_DEAD (row))
+ {
+ continue ;
+ }
+ /* compact the column */
+ *new_cp++ = row ;
+ /* add row's external degree */
+ score += Row [row].shared1.degree - 1 ;
+ /* guard against integer overflow */
+ score = COLAMD_MIN (score, n_col) ;
+ }
+ /* determine pruned column length */
+ col_length = (int) (new_cp - &A [Col [c].start]) ;
+ if (col_length == 0)
+ {
+ /* a newly-made null column (all rows in this col are "dense" */
+ /* and have already been killed) */
+ COLAMD_DEBUG2 (("Newly null killed: %d\n", c)) ;
+ Col [c].shared2.order = --n_col2 ;
+ KILL_PRINCIPAL_COL (c) ;
+ }
+ else
+ {
+ /* set column length and set score */
+ COLAMD_ASSERT (score >= 0) ;
+ COLAMD_ASSERT (score <= n_col) ;
+ Col [c].length = col_length ;
+ Col [c].shared2.score = score ;
+ }
+ }
+ COLAMD_DEBUG1 (("colamd: Dense, null, and newly-null columns killed: %d\n",
+ n_col-n_col2)) ;
+
+ /* At this point, all empty rows and columns are dead. All live columns */
+ /* are "clean" (containing no dead rows) and simplicial (no supercolumns */
+ /* yet). Rows may contain dead columns, but all live rows contain at */
+ /* least one live column. */
+
+ /* === Initialize degree lists ========================================== */
+
+
+ /* clear the hash buckets */
+ for (c = 0 ; c <= n_col ; c++)
+ {
+ head [c] = COLAMD_EMPTY ;
+ }
+ min_score = n_col ;
+ /* place in reverse order, so low column indices are at the front */
+ /* of the lists. This is to encourage natural tie-breaking */
+ for (c = n_col-1 ; c >= 0 ; c--)
+ {
+ /* only add principal columns to degree lists */
+ if (COL_IS_ALIVE (c))
+ {
+ COLAMD_DEBUG4 (("place %d score %d minscore %d ncol %d\n",
+ c, Col [c].shared2.score, min_score, n_col)) ;
+
+ /* === Add columns score to DList =============================== */
+
+ score = Col [c].shared2.score ;
+
+ COLAMD_ASSERT (min_score >= 0) ;
+ COLAMD_ASSERT (min_score <= n_col) ;
+ COLAMD_ASSERT (score >= 0) ;
+ COLAMD_ASSERT (score <= n_col) ;
+ COLAMD_ASSERT (head [score] >= COLAMD_EMPTY) ;
+
+ /* now add this column to dList at proper score location */
+ next_col = head [score] ;
+ Col [c].shared3.prev = COLAMD_EMPTY ;
+ Col [c].shared4.degree_next = next_col ;
+
+ /* if there already was a column with the same score, set its */
+ /* previous pointer to this new column */
+ if (next_col != COLAMD_EMPTY)
+ {
+ Col [next_col].shared3.prev = c ;
+ }
+ head [score] = c ;
+
+ /* see if this score is less than current min */
+ min_score = COLAMD_MIN (min_score, score) ;
+
+
+ }
+ }
+
+
+ /* === Return number of remaining columns, and max row degree =========== */
+
+ *p_n_col2 = n_col2 ;
+ *p_n_row2 = n_row2 ;
+ *p_max_deg = max_deg ;
+}
+
+
+/* ========================================================================== */
+/* === find_ordering ======================================================== */
+/* ========================================================================== */
+
+/*
+ Order the principal columns of the supercolumn form of the matrix
+ (no supercolumns on input). Uses a minimum approximate column minimum
+ degree ordering method. Not user-callable.
+*/
+
+static int find_ordering /* return the number of garbage collections */
+(
+ /* === Parameters ======================================================= */
+
+ int n_row, /* number of rows of A */
+ int n_col, /* number of columns of A */
+ int Alen, /* size of A, 2*nnz + n_col or larger */
+ Colamd_Row Row [], /* of size n_row+1 */
+ colamd_col Col [], /* of size n_col+1 */
+ int A [], /* column form and row form of A */
+ int head [], /* of size n_col+1 */
+ int n_col2, /* Remaining columns to order */
+ int max_deg, /* Maximum row degree */
+ int pfree /* index of first free slot (2*nnz on entry) */
+)
+{
+ /* === Local variables ================================================== */
+
+ int k ; /* current pivot ordering step */
+ int pivot_col ; /* current pivot column */
+ int *cp ; /* a column pointer */
+ int *rp ; /* a row pointer */
+ int pivot_row ; /* current pivot row */
+ int *new_cp ; /* modified column pointer */
+ int *new_rp ; /* modified row pointer */
+ int pivot_row_start ; /* pointer to start of pivot row */
+ int pivot_row_degree ; /* number of columns in pivot row */
+ int pivot_row_length ; /* number of supercolumns in pivot row */
+ int pivot_col_score ; /* score of pivot column */
+ int needed_memory ; /* free space needed for pivot row */
+ int *cp_end ; /* pointer to the end of a column */
+ int *rp_end ; /* pointer to the end of a row */
+ int row ; /* a row index */
+ int col ; /* a column index */
+ int max_score ; /* maximum possible score */
+ int cur_score ; /* score of current column */
+ unsigned int hash ; /* hash value for supernode detection */
+ int head_column ; /* head of hash bucket */
+ int first_col ; /* first column in hash bucket */
+ int tag_mark ; /* marker value for mark array */
+ int row_mark ; /* Row [row].shared2.mark */
+ int set_difference ; /* set difference size of row with pivot row */
+ int min_score ; /* smallest column score */
+ int col_thickness ; /* "thickness" (no. of columns in a supercol) */
+ int max_mark ; /* maximum value of tag_mark */
+ int pivot_col_thickness ; /* number of columns represented by pivot col */
+ int prev_col ; /* Used by Dlist operations. */
+ int next_col ; /* Used by Dlist operations. */
+ int ngarbage ; /* number of garbage collections performed */
+
+
+ /* === Initialization and clear mark ==================================== */
+
+ max_mark = INT_MAX - n_col ; /* INT_MAX defined in <limits.h> */
+ tag_mark = clear_mark (n_row, Row) ;
+ min_score = 0 ;
+ ngarbage = 0 ;
+ COLAMD_DEBUG1 (("colamd: Ordering, n_col2=%d\n", n_col2)) ;
+
+ /* === Order the columns ================================================ */
+
+ for (k = 0 ; k < n_col2 ; /* 'k' is incremented below */)
+ {
+
+ /* === Select pivot column, and order it ============================ */
+
+ /* make sure degree list isn't empty */
+ COLAMD_ASSERT (min_score >= 0) ;
+ COLAMD_ASSERT (min_score <= n_col) ;
+ COLAMD_ASSERT (head [min_score] >= COLAMD_EMPTY) ;
+
+ /* get pivot column from head of minimum degree list */
+ while (head [min_score] == COLAMD_EMPTY && min_score < n_col)
+ {
+ min_score++ ;
+ }
+ pivot_col = head [min_score] ;
+ COLAMD_ASSERT (pivot_col >= 0 && pivot_col <= n_col) ;
+ next_col = Col [pivot_col].shared4.degree_next ;
+ head [min_score] = next_col ;
+ if (next_col != COLAMD_EMPTY)
+ {
+ Col [next_col].shared3.prev = COLAMD_EMPTY ;
+ }
+
+ COLAMD_ASSERT (COL_IS_ALIVE (pivot_col)) ;
+ COLAMD_DEBUG3 (("Pivot col: %d\n", pivot_col)) ;
+
+ /* remember score for defrag check */
+ pivot_col_score = Col [pivot_col].shared2.score ;
+
+ /* the pivot column is the kth column in the pivot order */
+ Col [pivot_col].shared2.order = k ;
+
+ /* increment order count by column thickness */
+ pivot_col_thickness = Col [pivot_col].shared1.thickness ;
+ k += pivot_col_thickness ;
+ COLAMD_ASSERT (pivot_col_thickness > 0) ;
+
+ /* === Garbage_collection, if necessary ============================= */
+
+ needed_memory = COLAMD_MIN (pivot_col_score, n_col - k) ;
+ if (pfree + needed_memory >= Alen)
+ {
+ pfree = garbage_collection (n_row, n_col, Row, Col, A, &A [pfree]) ;
+ ngarbage++ ;
+ /* after garbage collection we will have enough */
+ COLAMD_ASSERT (pfree + needed_memory < Alen) ;
+ /* garbage collection has wiped out the Row[].shared2.mark array */
+ tag_mark = clear_mark (n_row, Row) ;
+
+ }
+
+ /* === Compute pivot row pattern ==================================== */
+
+ /* get starting location for this new merged row */
+ pivot_row_start = pfree ;
+
+ /* initialize new row counts to zero */
+ pivot_row_degree = 0 ;
+
+ /* tag pivot column as having been visited so it isn't included */
+ /* in merged pivot row */
+ Col [pivot_col].shared1.thickness = -pivot_col_thickness ;
+
+ /* pivot row is the union of all rows in the pivot column pattern */
+ cp = &A [Col [pivot_col].start] ;
+ cp_end = cp + Col [pivot_col].length ;
+ while (cp < cp_end)
+ {
+ /* get a row */
+ row = *cp++ ;
+ COLAMD_DEBUG4 (("Pivot col pattern %d %d\n", ROW_IS_ALIVE (row), row)) ;
+ /* skip if row is dead */
+ if (ROW_IS_DEAD (row))
+ {
+ continue ;
+ }
+ rp = &A [Row [row].start] ;
+ rp_end = rp + Row [row].length ;
+ while (rp < rp_end)
+ {
+ /* get a column */
+ col = *rp++ ;
+ /* add the column, if alive and untagged */
+ col_thickness = Col [col].shared1.thickness ;
+ if (col_thickness > 0 && COL_IS_ALIVE (col))
+ {
+ /* tag column in pivot row */
+ Col [col].shared1.thickness = -col_thickness ;
+ COLAMD_ASSERT (pfree < Alen) ;
+ /* place column in pivot row */
+ A [pfree++] = col ;
+ pivot_row_degree += col_thickness ;
+ }
+ }
+ }
+
+ /* clear tag on pivot column */
+ Col [pivot_col].shared1.thickness = pivot_col_thickness ;
+ max_deg = COLAMD_MAX (max_deg, pivot_row_degree) ;
+
+
+ /* === Kill all rows used to construct pivot row ==================== */
+
+ /* also kill pivot row, temporarily */
+ cp = &A [Col [pivot_col].start] ;
+ cp_end = cp + Col [pivot_col].length ;
+ while (cp < cp_end)
+ {
+ /* may be killing an already dead row */
+ row = *cp++ ;
+ COLAMD_DEBUG3 (("Kill row in pivot col: %d\n", row)) ;
+ KILL_ROW (row) ;
+ }
+
+ /* === Select a row index to use as the new pivot row =============== */
+
+ pivot_row_length = pfree - pivot_row_start ;
+ if (pivot_row_length > 0)
+ {
+ /* pick the "pivot" row arbitrarily (first row in col) */
+ pivot_row = A [Col [pivot_col].start] ;
+ COLAMD_DEBUG3 (("Pivotal row is %d\n", pivot_row)) ;
+ }
+ else
+ {
+ /* there is no pivot row, since it is of zero length */
+ pivot_row = COLAMD_EMPTY ;
+ COLAMD_ASSERT (pivot_row_length == 0) ;
+ }
+ COLAMD_ASSERT (Col [pivot_col].length > 0 || pivot_row_length == 0) ;
+
+ /* === Approximate degree computation =============================== */
+
+ /* Here begins the computation of the approximate degree. The column */
+ /* score is the sum of the pivot row "length", plus the size of the */
+ /* set differences of each row in the column minus the pattern of the */
+ /* pivot row itself. The column ("thickness") itself is also */
+ /* excluded from the column score (we thus use an approximate */
+ /* external degree). */
+
+ /* The time taken by the following code (compute set differences, and */
+ /* add them up) is proportional to the size of the data structure */
+ /* being scanned - that is, the sum of the sizes of each column in */
+ /* the pivot row. Thus, the amortized time to compute a column score */
+ /* is proportional to the size of that column (where size, in this */
+ /* context, is the column "length", or the number of row indices */
+ /* in that column). The number of row indices in a column is */
+ /* monotonically non-decreasing, from the length of the original */
+ /* column on input to colamd. */
+
+ /* === Compute set differences ====================================== */
+
+ COLAMD_DEBUG3 (("** Computing set differences phase. **\n")) ;
+
+ /* pivot row is currently dead - it will be revived later. */
+
+ COLAMD_DEBUG3 (("Pivot row: ")) ;
+ /* for each column in pivot row */
+ rp = &A [pivot_row_start] ;
+ rp_end = rp + pivot_row_length ;
+ while (rp < rp_end)
+ {
+ col = *rp++ ;
+ COLAMD_ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ;
+ COLAMD_DEBUG3 (("Col: %d\n", col)) ;
+
+ /* clear tags used to construct pivot row pattern */
+ col_thickness = -Col [col].shared1.thickness ;
+ COLAMD_ASSERT (col_thickness > 0) ;
+ Col [col].shared1.thickness = col_thickness ;
+
+ /* === Remove column from degree list =========================== */
+
+ cur_score = Col [col].shared2.score ;
+ prev_col = Col [col].shared3.prev ;
+ next_col = Col [col].shared4.degree_next ;
+ COLAMD_ASSERT (cur_score >= 0) ;
+ COLAMD_ASSERT (cur_score <= n_col) ;
+ COLAMD_ASSERT (cur_score >= COLAMD_EMPTY) ;
+ if (prev_col == COLAMD_EMPTY)
+ {
+ head [cur_score] = next_col ;
+ }
+ else
+ {
+ Col [prev_col].shared4.degree_next = next_col ;
+ }
+ if (next_col != COLAMD_EMPTY)
+ {
+ Col [next_col].shared3.prev = prev_col ;
+ }
+
+ /* === Scan the column ========================================== */
+
+ cp = &A [Col [col].start] ;
+ cp_end = cp + Col [col].length ;
+ while (cp < cp_end)
+ {
+ /* get a row */
+ row = *cp++ ;
+ row_mark = Row [row].shared2.mark ;
+ /* skip if dead */
+ if (ROW_IS_MARKED_DEAD (row_mark))
+ {
+ continue ;
+ }
+ COLAMD_ASSERT (row != pivot_row) ;
+ set_difference = row_mark - tag_mark ;
+ /* check if the row has been seen yet */
+ if (set_difference < 0)
+ {
+ COLAMD_ASSERT (Row [row].shared1.degree <= max_deg) ;
+ set_difference = Row [row].shared1.degree ;
+ }
+ /* subtract column thickness from this row's set difference */
+ set_difference -= col_thickness ;
+ COLAMD_ASSERT (set_difference >= 0) ;
+ /* absorb this row if the set difference becomes zero */
+ if (set_difference == 0)
+ {
+ COLAMD_DEBUG3 (("aggressive absorption. Row: %d\n", row)) ;
+ KILL_ROW (row) ;
+ }
+ else
+ {
+ /* save the new mark */
+ Row [row].shared2.mark = set_difference + tag_mark ;
+ }
+ }
+ }
+
+
+ /* === Add up set differences for each column ======================= */
+
+ COLAMD_DEBUG3 (("** Adding set differences phase. **\n")) ;
+
+ /* for each column in pivot row */
+ rp = &A [pivot_row_start] ;
+ rp_end = rp + pivot_row_length ;
+ while (rp < rp_end)
+ {
+ /* get a column */
+ col = *rp++ ;
+ COLAMD_ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ;
+ hash = 0 ;
+ cur_score = 0 ;
+ cp = &A [Col [col].start] ;
+ /* compact the column */
+ new_cp = cp ;
+ cp_end = cp + Col [col].length ;
+
+ COLAMD_DEBUG4 (("Adding set diffs for Col: %d.\n", col)) ;
+
+ while (cp < cp_end)
+ {
+ /* get a row */
+ row = *cp++ ;
+ COLAMD_ASSERT(row >= 0 && row < n_row) ;
+ row_mark = Row [row].shared2.mark ;
+ /* skip if dead */
+ if (ROW_IS_MARKED_DEAD (row_mark))
+ {
+ continue ;
+ }
+ COLAMD_ASSERT (row_mark > tag_mark) ;
+ /* compact the column */
+ *new_cp++ = row ;
+ /* compute hash function */
+ hash += row ;
+ /* add set difference */
+ cur_score += row_mark - tag_mark ;
+ /* integer overflow... */
+ cur_score = COLAMD_MIN (cur_score, n_col) ;
+ }
+
+ /* recompute the column's length */
+ Col [col].length = (int) (new_cp - &A [Col [col].start]) ;
+
+ /* === Further mass elimination ================================= */
+
+ if (Col [col].length == 0)
+ {
+ COLAMD_DEBUG4 (("further mass elimination. Col: %d\n", col)) ;
+ /* nothing left but the pivot row in this column */
+ KILL_PRINCIPAL_COL (col) ;
+ pivot_row_degree -= Col [col].shared1.thickness ;
+ COLAMD_ASSERT (pivot_row_degree >= 0) ;
+ /* order it */
+ Col [col].shared2.order = k ;
+ /* increment order count by column thickness */
+ k += Col [col].shared1.thickness ;
+ }
+ else
+ {
+ /* === Prepare for supercolumn detection ==================== */
+
+ COLAMD_DEBUG4 (("Preparing supercol detection for Col: %d.\n", col)) ;
+
+ /* save score so far */
+ Col [col].shared2.score = cur_score ;
+
+ /* add column to hash table, for supercolumn detection */
+ hash %= n_col + 1 ;
+
+ COLAMD_DEBUG4 ((" Hash = %d, n_col = %d.\n", hash, n_col)) ;
+ COLAMD_ASSERT (hash <= n_col) ;
+
+ head_column = head [hash] ;
+ if (head_column > COLAMD_EMPTY)
+ {
+ /* degree list "hash" is non-empty, use prev (shared3) of */
+ /* first column in degree list as head of hash bucket */
+ first_col = Col [head_column].shared3.headhash ;
+ Col [head_column].shared3.headhash = col ;
+ }
+ else
+ {
+ /* degree list "hash" is empty, use head as hash bucket */
+ first_col = - (head_column + 2) ;
+ head [hash] = - (col + 2) ;
+ }
+ Col [col].shared4.hash_next = first_col ;
+
+ /* save hash function in Col [col].shared3.hash */
+ Col [col].shared3.hash = (int) hash ;
+ COLAMD_ASSERT (COL_IS_ALIVE (col)) ;
+ }
+ }
+
+ /* The approximate external column degree is now computed. */
+
+ /* === Supercolumn detection ======================================== */
+
+ COLAMD_DEBUG3 (("** Supercolumn detection phase. **\n")) ;
+
+ detect_super_cols (
+
+ Col, A, head, pivot_row_start, pivot_row_length) ;
+
+ /* === Kill the pivotal column ====================================== */
+
+ KILL_PRINCIPAL_COL (pivot_col) ;
+
+ /* === Clear mark =================================================== */
+
+ tag_mark += (max_deg + 1) ;
+ if (tag_mark >= max_mark)
+ {
+ COLAMD_DEBUG2 (("clearing tag_mark\n")) ;
+ tag_mark = clear_mark (n_row, Row) ;
+ }
+
+ /* === Finalize the new pivot row, and column scores ================ */
+
+ COLAMD_DEBUG3 (("** Finalize scores phase. **\n")) ;
+
+ /* for each column in pivot row */
+ rp = &A [pivot_row_start] ;
+ /* compact the pivot row */
+ new_rp = rp ;
+ rp_end = rp + pivot_row_length ;
+ while (rp < rp_end)
+ {
+ col = *rp++ ;
+ /* skip dead columns */
+ if (COL_IS_DEAD (col))
+ {
+ continue ;
+ }
+ *new_rp++ = col ;
+ /* add new pivot row to column */
+ A [Col [col].start + (Col [col].length++)] = pivot_row ;
+
+ /* retrieve score so far and add on pivot row's degree. */
+ /* (we wait until here for this in case the pivot */
+ /* row's degree was reduced due to mass elimination). */
+ cur_score = Col [col].shared2.score + pivot_row_degree ;
+
+ /* calculate the max possible score as the number of */
+ /* external columns minus the 'k' value minus the */
+ /* columns thickness */
+ max_score = n_col - k - Col [col].shared1.thickness ;
+
+ /* make the score the external degree of the union-of-rows */
+ cur_score -= Col [col].shared1.thickness ;
+
+ /* make sure score is less or equal than the max score */
+ cur_score = COLAMD_MIN (cur_score, max_score) ;
+ COLAMD_ASSERT (cur_score >= 0) ;
+
+ /* store updated score */
+ Col [col].shared2.score = cur_score ;
+
+ /* === Place column back in degree list ========================= */
+
+ COLAMD_ASSERT (min_score >= 0) ;
+ COLAMD_ASSERT (min_score <= n_col) ;
+ COLAMD_ASSERT (cur_score >= 0) ;
+ COLAMD_ASSERT (cur_score <= n_col) ;
+ COLAMD_ASSERT (head [cur_score] >= COLAMD_EMPTY) ;
+ next_col = head [cur_score] ;
+ Col [col].shared4.degree_next = next_col ;
+ Col [col].shared3.prev = COLAMD_EMPTY ;
+ if (next_col != COLAMD_EMPTY)
+ {
+ Col [next_col].shared3.prev = col ;
+ }
+ head [cur_score] = col ;
+
+ /* see if this score is less than current min */
+ min_score = COLAMD_MIN (min_score, cur_score) ;
+
+ }
+
+ /* === Resurrect the new pivot row ================================== */
+
+ if (pivot_row_degree > 0)
+ {
+ /* update pivot row length to reflect any cols that were killed */
+ /* during super-col detection and mass elimination */
+ Row [pivot_row].start = pivot_row_start ;
+ Row [pivot_row].length = (int) (new_rp - &A[pivot_row_start]) ;
+ Row [pivot_row].shared1.degree = pivot_row_degree ;
+ Row [pivot_row].shared2.mark = 0 ;
+ /* pivot row is no longer dead */
+ }
+ }
+
+ /* === All principal columns have now been ordered ====================== */
+
+ return (ngarbage) ;
+}
+
+
+/* ========================================================================== */
+/* === order_children ======================================================= */
+/* ========================================================================== */
+
+/*
+ The find_ordering routine has ordered all of the principal columns (the
+ representatives of the supercolumns). The non-principal columns have not
+ yet been ordered. This routine orders those columns by walking up the
+ parent tree (a column is a child of the column which absorbed it). The
+ final permutation vector is then placed in p [0 ... n_col-1], with p [0]
+ being the first column, and p [n_col-1] being the last. It doesn't look
+ like it at first glance, but be assured that this routine takes time linear
+ in the number of columns. Although not immediately obvious, the time
+ taken by this routine is O (n_col), that is, linear in the number of
+ columns. Not user-callable.
+*/
+
+static inline void order_children
+(
+ /* === Parameters ======================================================= */
+
+ int n_col, /* number of columns of A */
+ colamd_col Col [], /* of size n_col+1 */
+ int p [] /* p [0 ... n_col-1] is the column permutation*/
+)
+{
+ /* === Local variables ================================================== */
+
+ int i ; /* loop counter for all columns */
+ int c ; /* column index */
+ int parent ; /* index of column's parent */
+ int order ; /* column's order */
+
+ /* === Order each non-principal column ================================== */
+
+ for (i = 0 ; i < n_col ; i++)
+ {
+ /* find an un-ordered non-principal column */
+ COLAMD_ASSERT (COL_IS_DEAD (i)) ;
+ if (!COL_IS_DEAD_PRINCIPAL (i) && Col [i].shared2.order == COLAMD_EMPTY)
+ {
+ parent = i ;
+ /* once found, find its principal parent */
+ do
+ {
+ parent = Col [parent].shared1.parent ;
+ } while (!COL_IS_DEAD_PRINCIPAL (parent)) ;
+
+ /* now, order all un-ordered non-principal columns along path */
+ /* to this parent. collapse tree at the same time */
+ c = i ;
+ /* get order of parent */
+ order = Col [parent].shared2.order ;
+
+ do
+ {
+ COLAMD_ASSERT (Col [c].shared2.order == COLAMD_EMPTY) ;
+
+ /* order this column */
+ Col [c].shared2.order = order++ ;
+ /* collaps tree */
+ Col [c].shared1.parent = parent ;
+
+ /* get immediate parent of this column */
+ c = Col [c].shared1.parent ;
+
+ /* continue until we hit an ordered column. There are */
+ /* guarranteed not to be anymore unordered columns */
+ /* above an ordered column */
+ } while (Col [c].shared2.order == COLAMD_EMPTY) ;
+
+ /* re-order the super_col parent to largest order for this group */
+ Col [parent].shared2.order = order ;
+ }
+ }
+
+ /* === Generate the permutation ========================================= */
+
+ for (c = 0 ; c < n_col ; c++)
+ {
+ p [Col [c].shared2.order] = c ;
+ }
+}
+
+
+/* ========================================================================== */
+/* === detect_super_cols ==================================================== */
+/* ========================================================================== */
+
+/*
+ Detects supercolumns by finding matches between columns in the hash buckets.
+ Check amongst columns in the set A [row_start ... row_start + row_length-1].
+ The columns under consideration are currently *not* in the degree lists,
+ and have already been placed in the hash buckets.
+
+ The hash bucket for columns whose hash function is equal to h is stored
+ as follows:
+
+ if head [h] is >= 0, then head [h] contains a degree list, so:
+
+ head [h] is the first column in degree bucket h.
+ Col [head [h]].headhash gives the first column in hash bucket h.
+
+ otherwise, the degree list is empty, and:
+
+ -(head [h] + 2) is the first column in hash bucket h.
+
+ For a column c in a hash bucket, Col [c].shared3.prev is NOT a "previous
+ column" pointer. Col [c].shared3.hash is used instead as the hash number
+ for that column. The value of Col [c].shared4.hash_next is the next column
+ in the same hash bucket.
+
+ Assuming no, or "few" hash collisions, the time taken by this routine is
+ linear in the sum of the sizes (lengths) of each column whose score has
+ just been computed in the approximate degree computation.
+ Not user-callable.
+*/
+
+static void detect_super_cols
+(
+ /* === Parameters ======================================================= */
+
+ colamd_col Col [], /* of size n_col+1 */
+ int A [], /* row indices of A */
+ int head [], /* head of degree lists and hash buckets */
+ int row_start, /* pointer to set of columns to check */
+ int row_length /* number of columns to check */
+)
+{
+ /* === Local variables ================================================== */
+
+ int hash ; /* hash value for a column */
+ int *rp ; /* pointer to a row */
+ int c ; /* a column index */
+ int super_c ; /* column index of the column to absorb into */
+ int *cp1 ; /* column pointer for column super_c */
+ int *cp2 ; /* column pointer for column c */
+ int length ; /* length of column super_c */
+ int prev_c ; /* column preceding c in hash bucket */
+ int i ; /* loop counter */
+ int *rp_end ; /* pointer to the end of the row */
+ int col ; /* a column index in the row to check */
+ int head_column ; /* first column in hash bucket or degree list */
+ int first_col ; /* first column in hash bucket */
+
+ /* === Consider each column in the row ================================== */
+
+ rp = &A [row_start] ;
+ rp_end = rp + row_length ;
+ while (rp < rp_end)
+ {
+ col = *rp++ ;
+ if (COL_IS_DEAD (col))
+ {
+ continue ;
+ }
+
+ /* get hash number for this column */
+ hash = Col [col].shared3.hash ;
+ COLAMD_ASSERT (hash <= n_col) ;
+
+ /* === Get the first column in this hash bucket ===================== */
+
+ head_column = head [hash] ;
+ if (head_column > COLAMD_EMPTY)
+ {
+ first_col = Col [head_column].shared3.headhash ;
+ }
+ else
+ {
+ first_col = - (head_column + 2) ;
+ }
+
+ /* === Consider each column in the hash bucket ====================== */
+
+ for (super_c = first_col ; super_c != COLAMD_EMPTY ;
+ super_c = Col [super_c].shared4.hash_next)
+ {
+ COLAMD_ASSERT (COL_IS_ALIVE (super_c)) ;
+ COLAMD_ASSERT (Col [super_c].shared3.hash == hash) ;
+ length = Col [super_c].length ;
+
+ /* prev_c is the column preceding column c in the hash bucket */
+ prev_c = super_c ;
+
+ /* === Compare super_c with all columns after it ================ */
+
+ for (c = Col [super_c].shared4.hash_next ;
+ c != COLAMD_EMPTY ; c = Col [c].shared4.hash_next)
+ {
+ COLAMD_ASSERT (c != super_c) ;
+ COLAMD_ASSERT (COL_IS_ALIVE (c)) ;
+ COLAMD_ASSERT (Col [c].shared3.hash == hash) ;
+
+ /* not identical if lengths or scores are different */
+ if (Col [c].length != length ||
+ Col [c].shared2.score != Col [super_c].shared2.score)
+ {
+ prev_c = c ;
+ continue ;
+ }
+
+ /* compare the two columns */
+ cp1 = &A [Col [super_c].start] ;
+ cp2 = &A [Col [c].start] ;
+
+ for (i = 0 ; i < length ; i++)
+ {
+ /* the columns are "clean" (no dead rows) */
+ COLAMD_ASSERT (ROW_IS_ALIVE (*cp1)) ;
+ COLAMD_ASSERT (ROW_IS_ALIVE (*cp2)) ;
+ /* row indices will same order for both supercols, */
+ /* no gather scatter nessasary */
+ if (*cp1++ != *cp2++)
+ {
+ break ;
+ }
+ }
+
+ /* the two columns are different if the for-loop "broke" */
+ if (i != length)
+ {
+ prev_c = c ;
+ continue ;
+ }
+
+ /* === Got it! two columns are identical =================== */
+
+ COLAMD_ASSERT (Col [c].shared2.score == Col [super_c].shared2.score) ;
+
+ Col [super_c].shared1.thickness += Col [c].shared1.thickness ;
+ Col [c].shared1.parent = super_c ;
+ KILL_NON_PRINCIPAL_COL (c) ;
+ /* order c later, in order_children() */
+ Col [c].shared2.order = COLAMD_EMPTY ;
+ /* remove c from hash bucket */
+ Col [prev_c].shared4.hash_next = Col [c].shared4.hash_next ;
+ }
+ }
+
+ /* === Empty this hash bucket ======================================= */
+
+ if (head_column > COLAMD_EMPTY)
+ {
+ /* corresponding degree list "hash" is not empty */
+ Col [head_column].shared3.headhash = COLAMD_EMPTY ;
+ }
+ else
+ {
+ /* corresponding degree list "hash" is empty */
+ head [hash] = COLAMD_EMPTY ;
+ }
+ }
+}
+
+
+/* ========================================================================== */
+/* === garbage_collection =================================================== */
+/* ========================================================================== */
+
+/*
+ Defragments and compacts columns and rows in the workspace A. Used when
+ all avaliable memory has been used while performing row merging. Returns
+ the index of the first free position in A, after garbage collection. The
+ time taken by this routine is linear is the size of the array A, which is
+ itself linear in the number of nonzeros in the input matrix.
+ Not user-callable.
+*/
+
+static int garbage_collection /* returns the new value of pfree */
+(
+ /* === Parameters ======================================================= */
+
+ int n_row, /* number of rows */
+ int n_col, /* number of columns */
+ Colamd_Row Row [], /* row info */
+ colamd_col Col [], /* column info */
+ int A [], /* A [0 ... Alen-1] holds the matrix */
+ int *pfree /* &A [0] ... pfree is in use */
+)
+{
+ /* === Local variables ================================================== */
+
+ int *psrc ; /* source pointer */
+ int *pdest ; /* destination pointer */
+ int j ; /* counter */
+ int r ; /* a row index */
+ int c ; /* a column index */
+ int length ; /* length of a row or column */
+
+ /* === Defragment the columns =========================================== */
+
+ pdest = &A[0] ;
+ for (c = 0 ; c < n_col ; c++)
+ {
+ if (COL_IS_ALIVE (c))
+ {
+ psrc = &A [Col [c].start] ;
+
+ /* move and compact the column */
+ COLAMD_ASSERT (pdest <= psrc) ;
+ Col [c].start = (int) (pdest - &A [0]) ;
+ length = Col [c].length ;
+ for (j = 0 ; j < length ; j++)
+ {
+ r = *psrc++ ;
+ if (ROW_IS_ALIVE (r))
+ {
+ *pdest++ = r ;
+ }
+ }
+ Col [c].length = (int) (pdest - &A [Col [c].start]) ;
+ }
+ }
+
+ /* === Prepare to defragment the rows =================================== */
+
+ for (r = 0 ; r < n_row ; r++)
+ {
+ if (ROW_IS_ALIVE (r))
+ {
+ if (Row [r].length == 0)
+ {
+ /* this row is of zero length. cannot compact it, so kill it */
+ COLAMD_DEBUG3 (("Defrag row kill\n")) ;
+ KILL_ROW (r) ;
+ }
+ else
+ {
+ /* save first column index in Row [r].shared2.first_column */
+ psrc = &A [Row [r].start] ;
+ Row [r].shared2.first_column = *psrc ;
+ COLAMD_ASSERT (ROW_IS_ALIVE (r)) ;
+ /* flag the start of the row with the one's complement of row */
+ *psrc = ONES_COMPLEMENT (r) ;
+
+ }
+ }
+ }
+
+ /* === Defragment the rows ============================================== */
+
+ psrc = pdest ;
+ while (psrc < pfree)
+ {
+ /* find a negative number ... the start of a row */
+ if (*psrc++ < 0)
+ {
+ psrc-- ;
+ /* get the row index */
+ r = ONES_COMPLEMENT (*psrc) ;
+ COLAMD_ASSERT (r >= 0 && r < n_row) ;
+ /* restore first column index */
+ *psrc = Row [r].shared2.first_column ;
+ COLAMD_ASSERT (ROW_IS_ALIVE (r)) ;
+
+ /* move and compact the row */
+ COLAMD_ASSERT (pdest <= psrc) ;
+ Row [r].start = (int) (pdest - &A [0]) ;
+ length = Row [r].length ;
+ for (j = 0 ; j < length ; j++)
+ {
+ c = *psrc++ ;
+ if (COL_IS_ALIVE (c))
+ {
+ *pdest++ = c ;
+ }
+ }
+ Row [r].length = (int) (pdest - &A [Row [r].start]) ;
+
+ }
+ }
+ /* ensure we found all the rows */
+ COLAMD_ASSERT (debug_rows == 0) ;
+
+ /* === Return the new value of pfree ==================================== */
+
+ return ((int) (pdest - &A [0])) ;
+}
+
+
+/* ========================================================================== */
+/* === clear_mark =========================================================== */
+/* ========================================================================== */
+
+/*
+ Clears the Row [].shared2.mark array, and returns the new tag_mark.
+ Return value is the new tag_mark. Not user-callable.
+*/
+
+static inline int clear_mark /* return the new value for tag_mark */
+(
+ /* === Parameters ======================================================= */
+
+ int n_row, /* number of rows in A */
+ Colamd_Row Row [] /* Row [0 ... n_row-1].shared2.mark is set to zero */
+)
+{
+ /* === Local variables ================================================== */
+
+ int r ;
+
+ for (r = 0 ; r < n_row ; r++)
+ {
+ if (ROW_IS_ALIVE (r))
+ {
+ Row [r].shared2.mark = 0 ;
+ }
+ }
+ return (1) ;
+}
+
+
+} // namespace internal
+#endif
diff --git a/resources/3rdparty/eigen/Eigen/src/OrderingMethods/Ordering.h b/resources/3rdparty/eigen/Eigen/src/OrderingMethods/Ordering.h
new file mode 100644
index 000000000..f5757b319
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/OrderingMethods/Ordering.h
@@ -0,0 +1,158 @@
+
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+//
+// Eigen 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 3 of the License, or (at your option) any later version.
+//
+// Alternatively, 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 2 of
+// the License, or (at your option) any later version.
+//
+// Eigen 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 or the
+// GNU General Public License for more details.
+//
+// You should have received a copy of the GNU Lesser General Public
+// License and a copy of the GNU General Public License along with
+// Eigen. If not, see <http://www.gnu.org/licenses/>.
+
+#ifndef EIGEN_ORDERING_H
+#define EIGEN_ORDERING_H
+
+#include "Amd.h"
+namespace Eigen {
+
+#include "Eigen_Colamd.h"
+
+namespace internal {
+
+ /**
+ * Get the symmetric pattern A^T+A from the input matrix A.
+ * FIXME: The values should not be considered here
+ */
+ template<typename MatrixType>
+ void ordering_helper_at_plus_a(const MatrixType& mat, MatrixType& symmat)
+ {
+ MatrixType C;
+ C = mat.transpose(); // NOTE: Could be costly
+ for (int i = 0; i < C.rows(); i++)
+ {
+ for (typename MatrixType::InnerIterator it(C, i); it; ++it)
+ it.valueRef() = 0.0;
+ }
+ symmat = C + mat;
+ }
+
+}
+
+/**
+ * Get the approximate minimum degree ordering
+ * If the matrix is not structurally symmetric, an ordering of A^T+A is computed
+ * \tparam Index The type of indices of the matrix
+ */
+template <typename Index>
+class AMDOrdering
+{
+ public:
+ typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+
+ /** Compute the permutation vector from a sparse matrix
+ * This routine is much faster if the input matrix is column-major
+ */
+ template <typename MatrixType>
+ void operator()(const MatrixType& mat, PermutationType& perm)
+ {
+ // Compute the symmetric pattern
+ SparseMatrix<typename MatrixType::Scalar, ColMajor, Index> symm;
+ internal::ordering_helper_at_plus_a(mat,symm);
+
+ // Call the AMD routine
+ //m_mat.prune(keep_diag());
+ internal::minimum_degree_ordering(symm, perm);
+ }
+
+ /** Compute the permutation with a selfadjoint matrix */
+ template <typename SrcType, unsigned int SrcUpLo>
+ void operator()(const SparseSelfAdjointView<SrcType, SrcUpLo>& mat, PermutationType& perm)
+ {
+ SparseMatrix<typename SrcType::Scalar, ColMajor, Index> C = mat;
+
+ // Call the AMD routine
+ // m_mat.prune(keep_diag()); //Remove the diagonal elements
+ internal::minimum_degree_ordering(C, perm);
+ }
+};
+
+/**
+ * Get the natural ordering
+ *
+ *NOTE Returns an empty permutation matrix
+ * \tparam Index The type of indices of the matrix
+ */
+template <typename Index>
+class NaturalOrdering
+{
+ public:
+ typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+
+ /** Compute the permutation vector from a column-major sparse matrix */
+ template <typename MatrixType>
+ void operator()(const MatrixType& mat, PermutationType& perm)
+ {
+ perm.resize(0);
+ }
+
+};
+
+/**
+ * Get the column approximate minimum degree ordering
+ * The matrix should be in column-major format
+ */
+template<typename Index>
+class COLAMDOrdering;
+#include "Eigen_Colamd.h"
+
+template<typename Index>
+class COLAMDOrdering
+{
+ public:
+ typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+ typedef Matrix<Index, Dynamic, 1> IndexVector;
+ /** Compute the permutation vector form a sparse matrix */
+ template <typename MatrixType>
+ void operator() (const MatrixType& mat, PermutationType& perm)
+ {
+ int m = mat.rows();
+ int n = mat.cols();
+ int nnz = mat.nonZeros();
+ // Get the recommended value of Alen to be used by colamd
+ int Alen = internal::colamd_recommended(nnz, m, n);
+ // Set the default parameters
+ double knobs [COLAMD_KNOBS];
+ int stats [COLAMD_STATS];
+ internal::colamd_set_defaults(knobs);
+
+ int info;
+ IndexVector p(n+1), A(Alen);
+ for(int i=0; i <= n; i++) p(i) = mat.outerIndexPtr()[i];
+ for(int i=0; i < nnz; i++) A(i) = mat.innerIndexPtr()[i];
+ // Call Colamd routine to compute the ordering
+ info = internal::colamd(m, n, Alen, A.data(), p.data(), knobs, stats);
+ eigen_assert( info && "COLAMD failed " );
+
+ perm.resize(n);
+ for (int i = 0; i < n; i++) perm.indices()(p(i)) = i;
+
+ }
+
+};
+
+} // end namespace Eigen
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h b/resources/3rdparty/eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h
index 745ecf8be..ebcafe7da 100644
--- a/resources/3rdparty/eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h
+++ b/resources/3rdparty/eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h
@@ -41,7 +41,7 @@ namespace Eigen {
/** \internal Specialization for the data types supported by MKL */
#define EIGEN_MKL_QR_COLPIV(EIGTYPE, MKLTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \
-template<> inline\
+template<> inline \
ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >& \
ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >::compute( \
const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix) \
diff --git a/resources/3rdparty/eigen/Eigen/src/QR/HouseholderQR.h b/resources/3rdparty/eigen/Eigen/src/QR/HouseholderQR.h
index 5bcb32c1e..c45d697f7 100644
--- a/resources/3rdparty/eigen/Eigen/src/QR/HouseholderQR.h
+++ b/resources/3rdparty/eigen/Eigen/src/QR/HouseholderQR.h
@@ -113,6 +113,14 @@ template<typename _MatrixType> class HouseholderQR
return internal::solve_retval<HouseholderQR, Rhs>(*this, b.derived());
}
+ /** This method returns an expression of the unitary matrix Q as a sequence of Householder transformations.
+ *
+ * The returned expression can directly be used to perform matrix products. It can also be assigned to a dense Matrix object.
+ * Here is an example showing how to recover the full or thin matrix Q, as well as how to perform matrix products using operator*:
+ *
+ * Example: \include HouseholderQR_householderQ.cpp
+ * Output: \verbinclude HouseholderQR_householderQ.out
+ */
HouseholderSequenceType householderQ() const
{
eigen_assert(m_isInitialized && "HouseholderQR is not initialized.");
diff --git a/resources/3rdparty/eigen/Eigen/src/SVD/JacobiSVD.h b/resources/3rdparty/eigen/Eigen/src/SVD/JacobiSVD.h
index a7dbf0737..4d525beb5 100644
--- a/resources/3rdparty/eigen/Eigen/src/SVD/JacobiSVD.h
+++ b/resources/3rdparty/eigen/Eigen/src/SVD/JacobiSVD.h
@@ -709,12 +709,14 @@ void JacobiSVD<MatrixType, QRPreconditioner>::allocate(Index rows, Index cols, u
}
m_diagSize = (std::min)(m_rows, m_cols);
m_singularValues.resize(m_diagSize);
- m_matrixU.resize(m_rows, m_computeFullU ? m_rows
- : m_computeThinU ? m_diagSize
- : 0);
- m_matrixV.resize(m_cols, m_computeFullV ? m_cols
- : m_computeThinV ? m_diagSize
- : 0);
+ if(RowsAtCompileTime==Dynamic)
+ m_matrixU.resize(m_rows, m_computeFullU ? m_rows
+ : m_computeThinU ? m_diagSize
+ : 0);
+ if(ColsAtCompileTime==Dynamic)
+ m_matrixV.resize(m_cols, m_computeFullV ? m_cols
+ : m_computeThinV ? m_diagSize
+ : 0);
m_workMatrix.resize(m_diagSize, m_diagSize);
if(m_cols>m_rows) m_qr_precond_morecols.allocate(*this);
diff --git a/resources/3rdparty/eigen/Eigen/src/SVD/JacobiSVD_MKL.h b/resources/3rdparty/eigen/Eigen/src/SVD/JacobiSVD_MKL.h
index 4d479f6b2..decda7540 100644
--- a/resources/3rdparty/eigen/Eigen/src/SVD/JacobiSVD_MKL.h
+++ b/resources/3rdparty/eigen/Eigen/src/SVD/JacobiSVD_MKL.h
@@ -40,7 +40,7 @@ namespace Eigen {
/** \internal Specialization for the data types supported by MKL */
#define EIGEN_MKL_SVD(EIGTYPE, MKLTYPE, MKLRTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \
-template<> inline\
+template<> inline \
JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>& \
JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix, unsigned int computationOptions) \
{ \
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/CompressedStorage.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/CompressedStorage.h
index 85a998aff..3321fab4a 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/CompressedStorage.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/CompressedStorage.h
@@ -139,7 +139,7 @@ class CompressedStorage
/** \returns the stored value at index \a key
* If the value does not exist, then the value \a defaultValue is returned without any insertion. */
- inline Scalar at(Index key, Scalar defaultValue = Scalar(0)) const
+ inline Scalar at(Index key, const Scalar& defaultValue = Scalar(0)) const
{
if (m_size==0)
return defaultValue;
@@ -152,7 +152,7 @@ class CompressedStorage
}
/** Like at(), but the search is performed in the range [start,end) */
- inline Scalar atInRange(size_t start, size_t end, Index key, Scalar defaultValue = Scalar(0)) const
+ inline Scalar atInRange(size_t start, size_t end, Index key, const Scalar& defaultValue = Scalar(0)) const
{
if (start>=end)
return Scalar(0);
@@ -167,7 +167,7 @@ class CompressedStorage
/** \returns a reference to the value at index \a key
* If the value does not exist, then the value \a defaultValue is inserted
* such that the keys are sorted. */
- inline Scalar& atWithInsertion(Index key, Scalar defaultValue = Scalar(0))
+ inline Scalar& atWithInsertion(Index key, const Scalar& defaultValue = Scalar(0))
{
size_t id = searchLowerIndex(0,m_size,key);
if (id>=m_size || m_indices[id]!=key)
@@ -184,7 +184,7 @@ class CompressedStorage
return m_values[id];
}
- void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
+ void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision())
{
size_t k = 0;
size_t n = size();
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseDenseProduct.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseDenseProduct.h
index 6f32940d6..8c608a622 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseDenseProduct.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseDenseProduct.h
@@ -39,7 +39,7 @@ struct traits<SparseDenseOuterProduct<Lhs,Rhs,Tr> >
{
typedef Sparse StorageKind;
typedef typename scalar_product_traits<typename traits<Lhs>::Scalar,
- typename traits<Rhs>::Scalar>::ReturnType Scalar;
+ typename traits<Rhs>::Scalar>::ReturnType Scalar;
typedef typename Lhs::Index Index;
typedef typename Lhs::Nested LhsNested;
typedef typename Rhs::Nested RhsNested;
@@ -150,7 +150,7 @@ struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, R
typedef typename internal::remove_all<DenseResType>::type Res;
typedef typename Lhs::Index Index;
typedef typename Lhs::InnerIterator LhsInnerIterator;
- static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
+ static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha)
{
for(Index c=0; c<rhs.cols(); ++c)
{
@@ -174,7 +174,7 @@ struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, C
typedef typename internal::remove_all<DenseResType>::type Res;
typedef typename Lhs::InnerIterator LhsInnerIterator;
typedef typename Lhs::Index Index;
- static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
+ static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha)
{
for(Index c=0; c<rhs.cols(); ++c)
{
@@ -196,7 +196,7 @@ struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, R
typedef typename internal::remove_all<DenseResType>::type Res;
typedef typename Lhs::InnerIterator LhsInnerIterator;
typedef typename Lhs::Index Index;
- static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
+ static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha)
{
for(Index j=0; j<lhs.outerSize(); ++j)
{
@@ -215,7 +215,7 @@ struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, C
typedef typename internal::remove_all<DenseResType>::type Res;
typedef typename Lhs::InnerIterator LhsInnerIterator;
typedef typename Lhs::Index Index;
- static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
+ static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const typename Res::Scalar& alpha)
{
for(Index j=0; j<lhs.outerSize(); ++j)
{
@@ -244,7 +244,7 @@ class SparseTimeDenseProduct
SparseTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
{}
- template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
+ template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
{
internal::sparse_time_dense_product(m_lhs, m_rhs, dest, alpha);
}
@@ -274,7 +274,7 @@ class DenseTimeSparseProduct
DenseTimeSparseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
{}
- template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
+ template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
{
Transpose<const _LhsNested> lhs_t(m_lhs);
Transpose<const _RhsNested> rhs_t(m_rhs);
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseMatrix.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseMatrix.h
index efb774f03..573804837 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseMatrix.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseMatrix.h
@@ -286,7 +286,8 @@ class SparseMatrix
{
std::size_t totalReserveSize = 0;
// turn the matrix into non-compressed mode
- m_innerNonZeros = new Index[m_outerSize];
+ m_innerNonZeros = static_cast<Index*>(std::malloc(m_outerSize * sizeof(Index)));
+ if (!m_innerNonZeros) internal::throw_std_bad_alloc();
// temporarily use m_innerSizes to hold the new starting points.
Index* newOuterIndex = m_innerNonZeros;
@@ -318,7 +319,9 @@ class SparseMatrix
}
else
{
- Index* newOuterIndex = new Index[m_outerSize+1];
+ Index* newOuterIndex = static_cast<Index*>(std::malloc((m_outerSize+1)*sizeof(Index)));
+ if (!newOuterIndex) internal::throw_std_bad_alloc();
+
Index count = 0;
for(Index j=0; j<m_outerSize; ++j)
{
@@ -345,7 +348,7 @@ class SparseMatrix
}
std::swap(m_outerIndex, newOuterIndex);
- delete[] newOuterIndex;
+ std::free(newOuterIndex);
}
}
@@ -460,14 +463,26 @@ class SparseMatrix
m_outerIndex[j+1] = m_outerIndex[j] + m_innerNonZeros[j];
oldStart = nextOldStart;
}
- delete[] m_innerNonZeros;
+ std::free(m_innerNonZeros);
m_innerNonZeros = 0;
m_data.resize(m_outerIndex[m_outerSize]);
m_data.squeeze();
}
+ /** Turns the matrix into the uncompressed mode */
+ void uncompress()
+ {
+ if(m_innerNonZeros != 0)
+ return;
+ m_innerNonZeros = new Index[m_outerSize];
+ for (int i = 0; i < m_outerSize; i++)
+ {
+ m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i];
+ }
+ }
+
/** Suppresses all nonzeros which are \b much \b smaller \b than \a reference under the tolerence \a epsilon */
- void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
+ void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision())
{
prune(default_prunning_func(reference,epsilon));
}
@@ -506,6 +521,66 @@ class SparseMatrix
m_data.resize(k,0);
}
+ /** Resizes the matrix to a \a rows x \a cols matrix leaving old values untouched.
+ * \sa resizeNonZeros(Index), reserve(), setZero()
+ */
+ void conservativeResize(Index rows, Index cols)
+ {
+ // No change
+ if (this->rows() == rows && this->cols() == cols) return;
+
+ Index innerChange = IsRowMajor ? cols - this->cols() : rows - this->rows();
+ Index outerChange = IsRowMajor ? rows - this->rows() : cols - this->cols();
+ Index newInnerSize = IsRowMajor ? cols : rows;
+
+ // Deals with inner non zeros
+ if (m_innerNonZeros)
+ {
+ // Resize m_innerNonZeros
+ Index *newInnerNonZeros = static_cast<Index*>(std::realloc(m_innerNonZeros, (m_outerSize + outerChange) * sizeof(Index)));
+ if (!newInnerNonZeros) internal::throw_std_bad_alloc();
+ m_innerNonZeros = newInnerNonZeros;
+
+ for(Index i=m_outerSize; i<m_outerSize+outerChange; i++)
+ m_innerNonZeros[i] = 0;
+ }
+ else if (innerChange < 0)
+ {
+ // Inner size decreased: allocate a new m_innerNonZeros
+ m_innerNonZeros = static_cast<Index*>(std::malloc((m_outerSize+outerChange+1) * sizeof(Index)));
+ if (!m_innerNonZeros) internal::throw_std_bad_alloc();
+ for(Index i = 0; i < m_outerSize; i++)
+ m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i];
+ }
+
+ // Change the m_innerNonZeros in case of a decrease of inner size
+ if (m_innerNonZeros && innerChange < 0) {
+ for(Index i = 0; i < m_outerSize + (std::min)(outerChange, Index(0)); i++)
+ {
+ Index &n = m_innerNonZeros[i];
+ Index start = m_outerIndex[i];
+ while (n > 0 && m_data.index(start+n-1) >= newInnerSize) --n;
+ }
+ }
+
+ m_innerSize = newInnerSize;
+
+ // Re-allocate outer index structure if necessary
+ if (outerChange == 0)
+ return;
+
+ Index *newOuterIndex = static_cast<Index*>(std::realloc(m_outerIndex, (m_outerSize + outerChange + 1) * sizeof(Index)));
+ if (!newOuterIndex) internal::throw_std_bad_alloc();
+ m_outerIndex = newOuterIndex;
+ if (outerChange > 0) {
+ Index last = m_outerSize == 0 ? 0 : m_outerIndex[m_outerSize];
+ for(Index i=m_outerSize; i<m_outerSize+outerChange+1; i++)
+ m_outerIndex[i] = last;
+ }
+ m_outerSize += outerChange;
+
+ }
+
/** Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero.
* \sa resizeNonZeros(Index), reserve(), setZero()
*/
@@ -516,13 +591,15 @@ class SparseMatrix
m_data.clear();
if (m_outerSize != outerSize || m_outerSize==0)
{
- delete[] m_outerIndex;
- m_outerIndex = new Index [outerSize+1];
+ std::free(m_outerIndex);
+ m_outerIndex = static_cast<Index*>(std::malloc((outerSize + 1) * sizeof(Index)));
+ if (!m_outerIndex) internal::throw_std_bad_alloc();
+
m_outerSize = outerSize;
}
if(m_innerNonZeros)
{
- delete[] m_innerNonZeros;
+ std::free(m_innerNonZeros);
m_innerNonZeros = 0;
}
memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index));
@@ -572,6 +649,16 @@ class SparseMatrix
*this = other.derived();
}
+ /** \brief Copy constructor with in-place evaluation */
+ template<typename OtherDerived>
+ SparseMatrix(const ReturnByValue<OtherDerived>& other)
+ : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
+ {
+ check_template_parameters();
+ initAssignment(other);
+ other.evalTo(*this);
+ }
+
/** Swaps the content of two sparse matrices of the same type.
* This is a fast operation that simply swaps the underlying pointers and parameters. */
inline void swap(SparseMatrix& other)
@@ -613,7 +700,10 @@ class SparseMatrix
template<typename OtherDerived>
inline SparseMatrix& operator=(const ReturnByValue<OtherDerived>& other)
- { return Base::operator=(other.derived()); }
+ {
+ initAssignment(other);
+ return Base::operator=(other.derived());
+ }
template<typename OtherDerived>
inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other)
@@ -623,7 +713,6 @@ class SparseMatrix
template<typename OtherDerived>
EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other)
{
- initAssignment(other.derived());
const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
if (needToTranspose)
{
@@ -635,40 +724,45 @@ class SparseMatrix
typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
OtherCopy otherCopy(other.derived());
- Eigen::Map<Matrix<Index, Dynamic, 1> > (m_outerIndex,outerSize()).setZero();
+ SparseMatrix dest(other.rows(),other.cols());
+ Eigen::Map<Matrix<Index, Dynamic, 1> > (dest.m_outerIndex,dest.outerSize()).setZero();
+
// pass 1
// FIXME the above copy could be merged with that pass
for (Index j=0; j<otherCopy.outerSize(); ++j)
for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
- ++m_outerIndex[it.index()];
+ ++dest.m_outerIndex[it.index()];
// prefix sum
Index count = 0;
- VectorXi positions(outerSize());
- for (Index j=0; j<outerSize(); ++j)
+ VectorXi positions(dest.outerSize());
+ for (Index j=0; j<dest.outerSize(); ++j)
{
- Index tmp = m_outerIndex[j];
- m_outerIndex[j] = count;
+ Index tmp = dest.m_outerIndex[j];
+ dest.m_outerIndex[j] = count;
positions[j] = count;
count += tmp;
}
- m_outerIndex[outerSize()] = count;
+ dest.m_outerIndex[dest.outerSize()] = count;
// alloc
- m_data.resize(count);
+ dest.m_data.resize(count);
// pass 2
for (Index j=0; j<otherCopy.outerSize(); ++j)
{
for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
{
Index pos = positions[it.index()]++;
- m_data.index(pos) = j;
- m_data.value(pos) = it.value();
+ dest.m_data.index(pos) = j;
+ dest.m_data.value(pos) = it.value();
}
}
+ this->swap(dest);
return *this;
}
else
{
+ if(other.isRValue())
+ initAssignment(other.derived());
// there is no special optimization
return Base::operator=(other.derived());
}
@@ -714,8 +808,8 @@ class SparseMatrix
/** Destructor */
inline ~SparseMatrix()
{
- delete[] m_outerIndex;
- delete[] m_innerNonZeros;
+ std::free(m_outerIndex);
+ std::free(m_innerNonZeros);
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
@@ -735,7 +829,7 @@ protected:
resize(other.rows(), other.cols());
if(m_innerNonZeros)
{
- delete[] m_innerNonZeros;
+ std::free(m_innerNonZeros);
m_innerNonZeros = 0;
}
}
@@ -898,7 +992,7 @@ protected:
public:
/** \internal
* \sa insert(Index,Index) */
- inline Scalar& insertBackUncompressed(Index row, Index col)
+ EIGEN_STRONG_INLINE Scalar& insertBackUncompressed(Index row, Index col)
{
const Index outer = IsRowMajor ? row : col;
const Index inner = IsRowMajor ? col : row;
@@ -906,8 +1000,7 @@ public:
eigen_assert(!isCompressed());
eigen_assert(m_innerNonZeros[outer]<=(m_outerIndex[outer+1] - m_outerIndex[outer]));
- Index p = m_outerIndex[outer] + m_innerNonZeros[outer];
- m_innerNonZeros[outer]++;
+ Index p = m_outerIndex[outer] + m_innerNonZeros[outer]++;
m_data.index(p) = inner;
return (m_data.value(p) = 0);
}
@@ -919,7 +1012,7 @@ private:
}
struct default_prunning_func {
- default_prunning_func(Scalar ref, RealScalar eps) : reference(ref), epsilon(eps) {}
+ default_prunning_func(const Scalar& ref, const RealScalar& eps) : reference(ref), epsilon(eps) {}
inline bool operator() (const Index&, const Index&, const Scalar& value) const
{
return !internal::isMuchSmallerThan(value, reference, epsilon);
@@ -1106,7 +1199,7 @@ void SparseMatrix<Scalar,_Options,_Index>::sumupDuplicates()
m_outerIndex[m_outerSize] = count;
// turn the matrix into compressed form
- delete[] m_innerNonZeros;
+ std::free(m_innerNonZeros);
m_innerNonZeros = 0;
m_data.resize(m_outerIndex[m_outerSize]);
}
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseMatrixBase.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseMatrixBase.h
index 55666fa67..39332a178 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseMatrixBase.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseMatrixBase.h
@@ -164,11 +164,7 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
/** \returns the size of the inner dimension according to the storage order,
* i.e., the number of rows for a columns major matrix, and the number of cols otherwise */
Index innerSize() const { return (int(Flags)&RowMajorBit) ? this->cols() : this->rows(); }
-
- bool isRowMajorMatrix() const {
- return (int(Flags)&RowMajorBit);
- }
-
+
bool isRValue() const { return m_isRValue; }
Derived& markAsRValue() { m_isRValue = true; return derived(); }
@@ -434,12 +430,12 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
template<typename OtherDerived>
bool isApprox(const SparseMatrixBase<OtherDerived>& other,
- RealScalar prec = NumTraits<Scalar>::dummy_precision()) const
+ const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const
{ return toDense().isApprox(other.toDense(),prec); }
template<typename OtherDerived>
bool isApprox(const MatrixBase<OtherDerived>& other,
- RealScalar prec = NumTraits<Scalar>::dummy_precision()) const
+ const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const
{ return toDense().isApprox(other,prec); }
/** \returns the matrix or vector obtained by evaluating this expression.
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseProduct.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseProduct.h
index 6a555b834..34dd7de69 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseProduct.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseProduct.h
@@ -99,13 +99,13 @@ class SparseSparseProduct : internal::no_assignment_operator,
}
template<typename Lhs, typename Rhs>
- EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs, RealScalar tolerance)
+ EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs, const RealScalar& tolerance)
: m_lhs(lhs), m_rhs(rhs), m_tolerance(tolerance), m_conservative(false)
{
init();
}
- SparseSparseProduct pruned(Scalar reference = 0, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision()) const
+ SparseSparseProduct pruned(const Scalar& reference = 0, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) const
{
return SparseSparseProduct(m_lhs,m_rhs,internal::abs(reference)*epsilon);
}
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h
index 86ec0a6c5..55ec69886 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h
@@ -94,7 +94,7 @@ template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
* call this function with u.adjoint().
*/
template<typename DerivedU>
- SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
+ SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha = Scalar(1));
/** \internal triggered by sparse_matrix = SparseSelfadjointView; */
template<typename DestScalar,int StorageOrder> void evalTo(SparseMatrix<DestScalar,StorageOrder,Index>& _dest) const
@@ -173,7 +173,7 @@ SparseSelfAdjointView<Derived, UpLo> SparseMatrixBase<Derived>::selfadjointView(
template<typename MatrixType, unsigned int UpLo>
template<typename DerivedU>
SparseSelfAdjointView<MatrixType,UpLo>&
-SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const SparseMatrixBase<DerivedU>& u, Scalar alpha)
+SparseSelfAdjointView<MatrixType,UpLo>::rankUpdate(const SparseMatrixBase<DerivedU>& u, const Scalar& alpha)
{
SparseMatrix<Scalar,MatrixType::Flags&RowMajorBit?RowMajor:ColMajor> tmp = u * u.adjoint();
if(alpha==Scalar(0))
@@ -207,7 +207,7 @@ class SparseSelfAdjointTimeDenseProduct
SparseSelfAdjointTimeDenseProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
{}
- template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
+ template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
{
// TODO use alpha
eigen_assert(alpha==Scalar(1) && "alpha != 1 is not implemented yet, sorry");
@@ -268,7 +268,7 @@ class DenseTimeSparseSelfAdjointProduct
DenseTimeSparseSelfAdjointProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
{}
- template<typename Dest> void scaleAndAddTo(Dest& /*dest*/, Scalar /*alpha*/) const
+ template<typename Dest> void scaleAndAddTo(Dest& /*dest*/, const Scalar& /*alpha*/) const
{
// TODO
}
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h
index 2438ac573..70857c7b6 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h
@@ -17,7 +17,7 @@ namespace internal {
// perform a pseudo in-place sparse * sparse product assuming all matrices are col major
template<typename Lhs, typename Rhs, typename ResultType>
-static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res, typename ResultType::RealScalar tolerance)
+static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res, const typename ResultType::RealScalar& tolerance)
{
// return sparse_sparse_product_with_pruning_impl2(lhs,rhs,res);
@@ -85,7 +85,7 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,C
typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
typedef typename ResultType::RealScalar RealScalar;
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance)
+ static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
{
typename remove_all<ResultType>::type _res(res.rows(), res.cols());
internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,ResultType>(lhs, rhs, _res, tolerance);
@@ -97,7 +97,7 @@ template<typename Lhs, typename Rhs, typename ResultType>
struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,RowMajor>
{
typedef typename ResultType::RealScalar RealScalar;
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance)
+ static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
{
// we need a col-major matrix to hold the result
typedef SparseMatrix<typename ResultType::Scalar> SparseTemporaryType;
@@ -111,7 +111,7 @@ template<typename Lhs, typename Rhs, typename ResultType>
struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,RowMajor>
{
typedef typename ResultType::RealScalar RealScalar;
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance)
+ static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
{
// let's transpose the product to get a column x column product
typename remove_all<ResultType>::type _res(res.rows(), res.cols());
@@ -124,7 +124,7 @@ template<typename Lhs, typename Rhs, typename ResultType>
struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,ColMajor>
{
typedef typename ResultType::RealScalar RealScalar;
- static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance)
+ static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
{
typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
ColMajorMatrix colLhs(lhs);
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseTranspose.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseTranspose.h
index 273f9de68..c78c20a2f 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseTranspose.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseTranspose.h
@@ -18,7 +18,7 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>
typedef typename internal::remove_all<typename MatrixType::Nested>::type _MatrixTypeNested;
public:
- EIGEN_SPARSE_PUBLIC_INTERFACE(Transpose<MatrixType>)
+ EIGEN_SPARSE_PUBLIC_INTERFACE(Transpose<MatrixType> )
class InnerIterator;
class ReverseInnerIterator;
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseUtil.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseUtil.h
index 6062a086f..a686e08da 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseUtil.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseUtil.h
@@ -113,9 +113,10 @@ template<typename T,int Rows> struct sparse_eval<T,Rows,1> {
template<typename T,int Rows,int Cols> struct sparse_eval {
typedef typename traits<T>::Scalar _Scalar;
- enum { _Flags = traits<T>::Flags };
+ typedef typename traits<T>::Index _Index;
+ enum { _Options = ((traits<T>::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor };
public:
- typedef SparseMatrix<_Scalar, _Flags> type;
+ typedef SparseMatrix<_Scalar, _Options, _Index> type;
};
template<typename T> struct sparse_eval<T,1,1> {
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseVector.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseVector.h
index c952f6540..a6a92d8aa 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseVector.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseVector.h
@@ -169,7 +169,7 @@ class SparseVector
inline void finalize() {}
- void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
+ void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision())
{
m_data.prune(reference,epsilon);
}
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseView.h b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseView.h
index 8b0b9ea03..4fd0cb3d8 100644
--- a/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseView.h
+++ b/resources/3rdparty/eigen/Eigen/src/SparseCore/SparseView.h
@@ -88,7 +88,7 @@ private:
template<typename Derived>
const SparseView<Derived> MatrixBase<Derived>::sparseView(const Scalar& m_reference,
- typename NumTraits<Scalar>::Real m_epsilon) const
+ const typename NumTraits<Scalar>::Real& m_epsilon) const
{
return SparseView<Derived>(derived(), m_reference, m_epsilon);
}
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/CMakeLists.txt b/resources/3rdparty/eigen/Eigen/src/SparseLU/CMakeLists.txt
new file mode 100644
index 000000000..69729ee89
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/CMakeLists.txt
@@ -0,0 +1,6 @@
+FILE(GLOB Eigen_SparseLU_SRCS "*.h")
+
+INSTALL(FILES
+ ${Eigen_SparseLU_SRCS}
+ DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SparseLU COMPONENT Devel
+ )
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU.h
new file mode 100644
index 000000000..9ea121ce5
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU.h
@@ -0,0 +1,630 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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/.
+
+
+#ifndef EIGEN_SPARSE_LU_H
+#define EIGEN_SPARSE_LU_H
+
+namespace Eigen {
+
+
+// Data structure needed by all routines
+#include "SparseLU_Structs.h"
+#include "SparseLU_Matrix.h"
+
+// Base structure containing all the factorization routines
+#include "SparseLUBase.h"
+/**
+ * \ingroup SparseLU_Module
+ * \brief Sparse supernodal LU factorization for general matrices
+ *
+ * This class implements the supernodal LU factorization for general matrices.
+ * It uses the main techniques from the sequential SuperLU package
+ * (http://crd-legacy.lbl.gov/~xiaoye/SuperLU/). It handles transparently real
+ * and complex arithmetics with single and double precision, depending on the
+ * scalar type of your input matrix.
+ * The code has been optimized to provide BLAS-3 operations during supernode-panel updates.
+ * It benefits directly from the built-in high-performant Eigen BLAS routines.
+ * Moreover, when the size of a supernode is very small, the BLAS calls are avoided to
+ * enable a better optimization from the compiler. For best performance,
+ * you should compile it with NDEBUG flag to avoid the numerous bounds checking on vectors.
+ *
+ * An important parameter of this class is the ordering method. It is used to reorder the columns
+ * (and eventually the rows) of the matrix to reduce the number of new elements that are created during
+ * numerical factorization. The cheapest method available is COLAMD.
+ * See \link Ordering_Modules the Ordering module \endlink for the list of
+ * built-in and external ordering methods.
+ *
+ * Simple example with key steps
+ * \code
+ * VectorXd x(n), b(n);
+ * SparseMatrix<double, ColMajor> A;
+ * SparseLU<SparseMatrix<scalar, ColMajor>, COLAMDOrdering<int> > solver;
+ * // fill A and b;
+ * // Compute the ordering permutation vector from the structural pattern of A
+ * solver.analyzePattern(A);
+ * // Compute the numerical factorization
+ * solver.factorize(A);
+ * //Use the factors to solve the linear system
+ * x = solver.solve(b);
+ * \endcode
+ *
+ * \WARNING The input matrix A should be in a \b compressed and \b column-major form.
+ * Otherwise an expensive copy will be made. You can call the inexpensive makeCompressed() to get a compressed matrix.
+ *
+ * \NOTE Unlike the initial SuperLU implementation, there is no step to equilibrate the matrix.
+ * For badly scaled matrices, this step can be useful to reduce the pivoting during factorization.
+ * If this is the case for your matrices, you can try the basic scaling method at
+ * "unsupported/Eigen/src/IterativeSolvers/Scaling.h"
+ *
+ * \tparam _MatrixType The type of the sparse matrix. It must be a column-major SparseMatrix<>
+ * \tparam _OrderingType The ordering method to use, either AMD, COLAMD or METIS
+ *
+ *
+ * \sa \ref TutorialSparseDirectSolvers
+ * \sa \ref Ordering_Modules
+ */
+template <typename _MatrixType, typename _OrderingType>
+class SparseLU
+{
+ public:
+ typedef _MatrixType MatrixType;
+ typedef _OrderingType OrderingType;
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename MatrixType::RealScalar RealScalar;
+ typedef typename MatrixType::Index Index;
+ typedef SparseMatrix<Scalar,ColMajor,Index> NCMatrix;
+ typedef SuperNodalMatrix<Scalar, Index> SCMatrix;
+ typedef Matrix<Scalar,Dynamic,1> ScalarVector;
+ typedef Matrix<Index,Dynamic,1> IndexVector;
+ typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+
+ public:
+ SparseLU():m_isInitialized(true),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1.0)
+ {
+ initperfvalues();
+ }
+ SparseLU(const MatrixType& matrix):m_isInitialized(true),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1.0)
+ {
+ initperfvalues();
+ compute(matrix);
+ }
+
+ ~SparseLU()
+ {
+ // Free all explicit dynamic pointers
+ }
+
+ void analyzePattern (const MatrixType& matrix);
+ void factorize (const MatrixType& matrix);
+ void simplicialfactorize(const MatrixType& matrix);
+
+ /**
+ * Compute the symbolic and numeric factorization of the input sparse matrix.
+ * The input matrix should be in column-major storage.
+ */
+ void compute (const MatrixType& matrix)
+ {
+ // Analyze
+ analyzePattern(matrix);
+ //Factorize
+ factorize(matrix);
+ }
+
+ inline Index rows() const { return m_mat.rows(); }
+ inline Index cols() const { return m_mat.cols(); }
+ /** Indicate that the pattern of the input matrix is symmetric */
+ void isSymmetric(bool sym)
+ {
+ m_symmetricmode = sym;
+ }
+
+ /** Set the threshold used for a diagonal entry to be an acceptable pivot. */
+ void diagPivotThresh(RealScalar thresh)
+ {
+ m_diagpivotthresh = thresh;
+ }
+
+ /** Return the number of nonzero elements in the L factor */
+ int nnzL()
+ {
+ if (m_factorizationIsOk)
+ return m_nnzL;
+ else
+ {
+ std::cerr<<"Numerical factorization should be done before\n";
+ return 0;
+ }
+ }
+ /** Return the number of nonzero elements in the U factor */
+ int nnzU()
+ {
+ if (m_factorizationIsOk)
+ return m_nnzU;
+ else
+ {
+ std::cerr<<"Numerical factorization should be done before\n";
+ return 0;
+ }
+ }
+ /** \returns the solution X of \f$ A X = B \f$ using the current decomposition of A.
+ *
+ * \sa compute()
+ */
+ template<typename Rhs>
+ inline const internal::solve_retval<SparseLU, Rhs> solve(const MatrixBase<Rhs>& B) const
+ {
+ eigen_assert(m_factorizationIsOk && "SparseLU is not initialized.");
+ eigen_assert(rows()==B.rows()
+ && "SparseLU::solve(): invalid number of rows of the right hand side matrix B");
+ return internal::solve_retval<SparseLU, Rhs>(*this, B.derived());
+ }
+
+
+ /** \brief Reports whether previous computation was successful.
+ *
+ * \returns \c Success if computation was succesful,
+ * \c NumericalIssue if the PaStiX reports a problem
+ * \c InvalidInput if the input matrix is invalid
+ *
+ * \sa iparm()
+ */
+ ComputationInfo info() const
+ {
+ eigen_assert(m_isInitialized && "Decomposition is not initialized.");
+ return m_info;
+ }
+
+ template<typename Rhs, typename Dest>
+ bool _solve(const MatrixBase<Rhs> &B, MatrixBase<Dest> &_X) const
+ {
+ Dest& X(_X.derived());
+ eigen_assert(m_factorizationIsOk && "The matrix should be factorized first");
+ EIGEN_STATIC_ASSERT((Dest::Flags&RowMajorBit)==0,
+ THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+
+
+ int nrhs = B.cols();
+ Index n = B.rows();
+
+ // Permute the right hand side to form X = Pr*B
+ // on return, X is overwritten by the computed solution
+ X.resize(n,nrhs);
+ for(int j = 0; j < nrhs; ++j)
+ X.col(j) = m_perm_r * B.col(j);
+
+ //Forward substitution with L
+ m_Lstore.solveInPlace(X);
+
+ // Backward solve with U
+ for (int k = m_Lstore.nsuper(); k >= 0; k--)
+ {
+ Index fsupc = m_Lstore.supToCol()[k];
+ Index istart = m_Lstore.rowIndexPtr()[fsupc];
+ Index nsupr = m_Lstore.rowIndexPtr()[fsupc+1] - istart;
+ Index nsupc = m_Lstore.supToCol()[k+1] - fsupc;
+ Index luptr = m_Lstore.colIndexPtr()[fsupc];
+
+ if (nsupc == 1)
+ {
+ for (int j = 0; j < nrhs; j++)
+ {
+ X(fsupc, j) /= m_Lstore.valuePtr()[luptr];
+ }
+ }
+ else
+ {
+ Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(m_Lstore.valuePtr()[luptr]), nsupc, nsupc, OuterStride<>(nsupr) );
+ Map< Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) );
+ U = A.template triangularView<Upper>().solve(U);
+ }
+
+ for (int j = 0; j < nrhs; ++j)
+ {
+ for (int jcol = fsupc; jcol < fsupc + nsupc; jcol++)
+ {
+ typename MappedSparseMatrix<Scalar>::InnerIterator it(m_Ustore, jcol);
+ for ( ; it; ++it)
+ {
+ Index irow = it.index();
+ X(irow, j) -= X(jcol, j) * it.value();
+ }
+ }
+ }
+ } // End For U-solve
+
+ // Permute back the solution
+ for (int j = 0; j < nrhs; ++j)
+ X.col(j) = m_perm_c.inverse() * X.col(j);
+
+ return true;
+ }
+
+ protected:
+ // Functions
+ void initperfvalues()
+ {
+ m_perfv.panel_size = 12;
+ m_perfv.relax = 1;
+ m_perfv.maxsuper = 100;
+ m_perfv.rowblk = 200;
+ m_perfv.colblk = 60;
+ m_perfv.fillfactor = 20;
+ }
+
+ // Variables
+ mutable ComputationInfo m_info;
+ bool m_isInitialized;
+ bool m_factorizationIsOk;
+ bool m_analysisIsOk;
+ NCMatrix m_mat; // The input (permuted ) matrix
+ SCMatrix m_Lstore; // The lower triangular matrix (supernodal)
+ MappedSparseMatrix<Scalar> m_Ustore; // The upper triangular matrix
+ PermutationType m_perm_c; // Column permutation
+ PermutationType m_perm_r ; // Row permutation
+ IndexVector m_etree; // Column elimination tree
+
+ LU_GlobalLU_t<IndexVector, ScalarVector> m_glu;
+
+ // SuperLU/SparseLU options
+ bool m_symmetricmode;
+
+ // values for performance
+ LU_perfvalues m_perfv;
+ RealScalar m_diagpivotthresh; // Specifies the threshold used for a diagonal entry to be an acceptable pivot
+ int m_nnzL, m_nnzU; // Nonzeros in L and U factors
+
+ private:
+ // Copy constructor
+ SparseLU (SparseLU& ) {}
+
+}; // End class SparseLU
+
+
+// Functions needed by the anaysis phase
+/**
+ * Compute the column permutation to minimize the fill-in
+ *
+ * - Apply this permutation to the input matrix -
+ *
+ * - Compute the column elimination tree on the permuted matrix
+ *
+ * - Postorder the elimination tree and the column permutation
+ *
+ */
+template <typename MatrixType, typename OrderingType>
+void SparseLU<MatrixType, OrderingType>::analyzePattern(const MatrixType& mat)
+{
+
+ //TODO It is possible as in SuperLU to compute row and columns scaling vectors to equilibrate the matrix mat.
+
+ OrderingType ord;
+ ord(mat,m_perm_c);
+
+ // Apply the permutation to the column of the input matrix
+// m_mat = mat * m_perm_c.inverse(); //FIXME It should be less expensive here to permute only the structural pattern of the matrix
+
+ //First copy the whole input matrix.
+ m_mat = mat;
+ m_mat.uncompress(); //NOTE: The effect of this command is only to create the InnerNonzeros pointers. FIXME : This vector is filled but not subsequently used.
+ //Then, permute only the column pointers
+ for (int i = 0; i < mat.cols(); i++)
+ {
+ m_mat.outerIndexPtr()[m_perm_c.indices()(i)] = mat.outerIndexPtr()[i];
+ m_mat.innerNonZeroPtr()[m_perm_c.indices()(i)] = mat.outerIndexPtr()[i+1] - mat.outerIndexPtr()[i];
+ }
+
+ // Compute the column elimination tree of the permuted matrix
+ /*if (m_etree.size() == 0) */m_etree.resize(m_mat.cols());
+
+ SparseLUBase<Scalar,Index>::LU_sp_coletree(m_mat, m_etree);
+
+ // In symmetric mode, do not do postorder here
+ if (!m_symmetricmode) {
+ IndexVector post, iwork;
+ // Post order etree
+ SparseLUBase<Scalar,Index>::LU_TreePostorder(m_mat.cols(), m_etree, post);
+
+
+ // Renumber etree in postorder
+ int m = m_mat.cols();
+ iwork.resize(m+1);
+ for (int i = 0; i < m; ++i) iwork(post(i)) = post(m_etree(i));
+ m_etree = iwork;
+
+ // Postmultiply A*Pc by post, i.e reorder the matrix according to the postorder of the etree
+ PermutationType post_perm(m); //FIXME Use directly a constructor with post
+ for (int i = 0; i < m; i++)
+ post_perm.indices()(i) = post(i);
+
+ // Combine the two permutations : postorder the permutation for future use
+ m_perm_c = post_perm * m_perm_c;
+
+ } // end postordering
+
+ m_analysisIsOk = true;
+}
+
+// Functions needed by the numerical factorization phase
+
+
+/**
+ * - Numerical factorization
+ * - Interleaved with the symbolic factorization
+ * On exit, info is
+ *
+ * = 0: successful factorization
+ *
+ * > 0: if info = i, and i is
+ *
+ * <= A->ncol: U(i,i) is exactly zero. The factorization has
+ * been completed, but the factor U is exactly singular,
+ * and division by zero will occur if it is used to solve a
+ * system of equations.
+ *
+ * > A->ncol: number of bytes allocated when memory allocation
+ * failure occurred, plus A->ncol. If lwork = -1, it is
+ * the estimated amount of space needed, plus A->ncol.
+ */
+template <typename MatrixType, typename OrderingType>
+void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix)
+{
+
+ eigen_assert(m_analysisIsOk && "analyzePattern() should be called first");
+ eigen_assert((matrix.rows() == matrix.cols()) && "Only for squared matrices");
+
+ typedef typename IndexVector::Scalar Index;
+
+
+ // Apply the column permutation computed in analyzepattern()
+ // m_mat = matrix * m_perm_c.inverse();
+ m_mat = matrix;
+ m_mat.uncompress(); //NOTE: The effect of this command is only to create the InnerNonzeros pointers.
+ //Then, permute only the column pointers
+ for (int i = 0; i < matrix.cols(); i++)
+ {
+ m_mat.outerIndexPtr()[m_perm_c.indices()(i)] = matrix.outerIndexPtr()[i];
+ m_mat.innerNonZeroPtr()[m_perm_c.indices()(i)] = matrix.outerIndexPtr()[i+1] - matrix.outerIndexPtr()[i];
+ }
+
+ int m = m_mat.rows();
+ int n = m_mat.cols();
+ int nnz = m_mat.nonZeros();
+ int maxpanel = m_perfv.panel_size * m;
+ // Allocate working storage common to the factor routines
+ int lwork = 0;
+ int info = SparseLUBase<Scalar,Index>::LUMemInit(m, n, nnz, lwork, m_perfv.fillfactor, m_perfv.panel_size, m_glu);
+ if (info)
+ {
+ std::cerr << "UNABLE TO ALLOCATE WORKING MEMORY\n\n" ;
+ m_factorizationIsOk = false;
+ return ;
+ }
+
+ // Set up pointers for integer working arrays
+ IndexVector segrep(m); segrep.setZero();
+ IndexVector parent(m); parent.setZero();
+ IndexVector xplore(m); xplore.setZero();
+ IndexVector repfnz(maxpanel);
+ IndexVector panel_lsub(maxpanel);
+ IndexVector xprune(n); xprune.setZero();
+ IndexVector marker(m*LU_NO_MARKER); marker.setZero();
+
+ repfnz.setConstant(-1);
+ panel_lsub.setConstant(-1);
+
+ // Set up pointers for scalar working arrays
+ ScalarVector dense;
+ dense.setZero(maxpanel);
+ ScalarVector tempv;
+ tempv.setZero(LU_NUM_TEMPV(m, m_perfv.panel_size, m_perfv.maxsuper, m_perfv.rowblk) );
+
+ // Compute the inverse of perm_c
+ PermutationType iperm_c(m_perm_c.inverse());
+
+ // Identify initial relaxed snodes
+ IndexVector relax_end(n);
+ if ( m_symmetricmode == true )
+ SparseLUBase<Scalar,Index>::LU_heap_relax_snode(n, m_etree, m_perfv.relax, marker, relax_end);
+ else
+ SparseLUBase<Scalar,Index>::LU_relax_snode(n, m_etree, m_perfv.relax, marker, relax_end);
+
+
+ m_perm_r.resize(m);
+ m_perm_r.indices().setConstant(-1);
+ marker.setConstant(-1);
+
+ m_glu.supno(0) = IND_EMPTY; m_glu.xsup.setConstant(0);
+ m_glu.xsup(0) = m_glu.xlsub(0) = m_glu.xusub(0) = m_glu.xlusup(0) = Index(0);
+
+ // Work on one 'panel' at a time. A panel is one of the following :
+ // (a) a relaxed supernode at the bottom of the etree, or
+ // (b) panel_size contiguous columns, <panel_size> defined by the user
+ int jcol,kcol;
+ IndexVector panel_histo(n);
+ Index nextu, nextlu, jsupno, fsupc, new_next;
+ Index pivrow; // Pivotal row number in the original row matrix
+ int nseg1; // Number of segments in U-column above panel row jcol
+ int nseg; // Number of segments in each U-column
+ int irep, icol;
+ int i, k, jj;
+ for (jcol = 0; jcol < n; )
+ {
+ if (relax_end(jcol) != IND_EMPTY)
+ { // Starting a relaxed node from jcol
+ kcol = relax_end(jcol); // End index of the relaxed snode
+
+ // Factorize the relaxed supernode(jcol:kcol)
+ // First, determine the union of the row structure of the snode
+ info = SparseLUBase<Scalar,Index>::LU_snode_dfs(jcol, kcol, m_mat, xprune, marker, m_glu);
+ if ( info )
+ {
+ std::cerr << "MEMORY ALLOCATION FAILED IN SNODE_DFS() \n";
+ m_info = NumericalIssue;
+ m_factorizationIsOk = false;
+ return;
+ }
+ nextu = m_glu.xusub(jcol); //starting location of column jcol in ucol
+ nextlu = m_glu.xlusup(jcol); //Starting location of column jcol in lusup (rectangular supernodes)
+ jsupno = m_glu.supno(jcol); // Supernode number which column jcol belongs to
+ fsupc = m_glu.xsup(jsupno); //First column number of the current supernode
+ new_next = nextlu + (m_glu.xlsub(fsupc+1)-m_glu.xlsub(fsupc)) * (kcol - jcol + 1);
+ int mem;
+ while (new_next > m_glu.nzlumax )
+ {
+ mem = SparseLUBase<Scalar,Index>::LUMemXpand(m_glu.lusup, m_glu.nzlumax, nextlu, LUSUP, m_glu.num_expansions);
+ if (mem)
+ {
+ std::cerr << "MEMORY ALLOCATION FAILED FOR L FACTOR \n";
+ m_factorizationIsOk = false;
+ return;
+ }
+ }
+
+ // Now, left-looking factorize each column within the snode
+ for (icol = jcol; icol<=kcol; icol++){
+ m_glu.xusub(icol+1) = nextu;
+ // Scatter into SPA dense(*)
+ for (typename MatrixType::InnerIterator it(m_mat, icol); it; ++it)
+ dense(it.row()) = it.value();
+
+ // Numeric update within the snode
+ SparseLUBase<Scalar,Index>::LU_snode_bmod(icol, fsupc, dense, m_glu);
+
+ // Eliminate the current column
+ info = SparseLUBase<Scalar,Index>::LU_pivotL(icol, m_diagpivotthresh, m_perm_r.indices(), iperm_c.indices(), pivrow, m_glu);
+ if ( info )
+ {
+ m_info = NumericalIssue;
+ std::cerr<< "THE MATRIX IS STRUCTURALLY SINGULAR ... ZERO COLUMN AT " << info <<std::endl;
+ m_factorizationIsOk = false;
+ return;
+ }
+ }
+ jcol = icol; // The last column te be eliminated
+ }
+ else
+ { // Work on one panel of panel_size columns
+
+ // Adjust panel size so that a panel won't overlap with the next relaxed snode.
+ int panel_size = m_perfv.panel_size; // upper bound on panel width
+ for (k = jcol + 1; k < (std::min)(jcol+panel_size, n); k++)
+ {
+ if (relax_end(k) != IND_EMPTY)
+ {
+ panel_size = k - jcol;
+ break;
+ }
+ }
+ if (k == n)
+ panel_size = n - jcol;
+
+ // Symbolic outer factorization on a panel of columns
+ SparseLUBase<Scalar,Index>::LU_panel_dfs(m, panel_size, jcol, m_mat, m_perm_r.indices(), nseg1, dense, panel_lsub, segrep, repfnz, xprune, marker, parent, xplore, m_glu);
+
+ // Numeric sup-panel updates in topological order
+ SparseLUBase<Scalar,Index>::LU_panel_bmod(m, panel_size, jcol, nseg1, dense, tempv, segrep, repfnz, m_perfv, m_glu);
+
+ // Sparse LU within the panel, and below the panel diagonal
+ for ( jj = jcol; jj< jcol + panel_size; jj++)
+ {
+ k = (jj - jcol) * m; // Column index for w-wide arrays
+
+ nseg = nseg1; // begin after all the panel segments
+ //Depth-first-search for the current column
+ VectorBlock<IndexVector> panel_lsubk(panel_lsub, k, m);
+ VectorBlock<IndexVector> repfnz_k(repfnz, k, m);
+ info = SparseLUBase<Scalar,Index>::LU_column_dfs(m, jj, m_perm_r.indices(), m_perfv.maxsuper, nseg, panel_lsubk, segrep, repfnz_k, xprune, marker, parent, xplore, m_glu);
+ if ( info )
+ {
+ std::cerr << "UNABLE TO EXPAND MEMORY IN COLUMN_DFS() \n";
+ m_info = NumericalIssue;
+ m_factorizationIsOk = false;
+ return;
+ }
+ // Numeric updates to this column
+ VectorBlock<ScalarVector> dense_k(dense, k, m);
+ VectorBlock<IndexVector> segrep_k(segrep, nseg1, m-nseg1);
+ info = SparseLUBase<Scalar,Index>::LU_column_bmod(jj, (nseg - nseg1), dense_k, tempv, segrep_k, repfnz_k, jcol, m_glu);
+ if ( info )
+ {
+ std::cerr << "UNABLE TO EXPAND MEMORY IN COLUMN_BMOD() \n";
+ m_info = NumericalIssue;
+ m_factorizationIsOk = false;
+ return;
+ }
+
+ // Copy the U-segments to ucol(*)
+ info = SparseLUBase<Scalar,Index>::LU_copy_to_ucol(jj, nseg, segrep, repfnz_k ,m_perm_r.indices(), dense_k, m_glu);
+ if ( info )
+ {
+ std::cerr << "UNABLE TO EXPAND MEMORY IN COPY_TO_UCOL() \n";
+ m_info = NumericalIssue;
+ m_factorizationIsOk = false;
+ return;
+ }
+
+ // Form the L-segment
+ info = SparseLUBase<Scalar,Index>::LU_pivotL(jj, m_diagpivotthresh, m_perm_r.indices(), iperm_c.indices(), pivrow, m_glu);
+ if ( info )
+ {
+ std::cerr<< "THE MATRIX IS STRUCTURALLY SINGULAR ... ZERO COLUMN AT " << info <<std::endl;
+ m_info = NumericalIssue;
+ m_factorizationIsOk = false;
+ return;
+ }
+
+ // Prune columns (0:jj-1) using column jj
+ SparseLUBase<Scalar,Index>::LU_pruneL(jj, m_perm_r.indices(), pivrow, nseg, segrep, repfnz_k, xprune, m_glu);
+
+ // Reset repfnz for this column
+ for (i = 0; i < nseg; i++)
+ {
+ irep = segrep(i);
+ repfnz_k(irep) = IND_EMPTY;
+ }
+ } // end SparseLU within the panel
+ jcol += panel_size; // Move to the next panel
+ } // end else
+ } // end for -- end elimination
+
+ // Count the number of nonzeros in factors
+ SparseLUBase<Scalar,Index>::LU_countnz(n, m_nnzL, m_nnzU, m_glu);
+ // Apply permutation to the L subscripts
+ SparseLUBase<Scalar,Index>::LU_fixupL(n, m_perm_r.indices(), m_glu);
+
+ // Create supernode matrix L
+ m_Lstore.setInfos(m, n, m_glu.lusup, m_glu.xlusup, m_glu.lsub, m_glu.xlsub, m_glu.supno, m_glu.xsup);
+ // Create the column major upper sparse matrix U;
+ new (&m_Ustore) MappedSparseMatrix<Scalar> ( m, n, m_nnzU, m_glu.xusub.data(), m_glu.usub.data(), m_glu.ucol.data() );
+
+ m_info = Success;
+ m_factorizationIsOk = true;
+}
+
+// #include "SparseLU_simplicialfactorize.h"
+namespace internal {
+
+template<typename _MatrixType, typename Derived, typename Rhs>
+struct solve_retval<SparseLU<_MatrixType,Derived>, Rhs>
+ : solve_retval_base<SparseLU<_MatrixType,Derived>, Rhs>
+{
+ typedef SparseLU<_MatrixType,Derived> Dec;
+ EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+ template<typename Dest> void evalTo(Dest& dst) const
+ {
+ dec()._solve(rhs(),dst);
+ }
+};
+
+} // end namespace internal
+
+} // End namespace Eigen
+#endif
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLUBase.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLUBase.h
new file mode 100644
index 000000000..c00bc0532
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLUBase.h
@@ -0,0 +1,74 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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/.
+#ifndef SPARSELUBASE_H
+#define SPARSELUBASE_H
+/**
+ * Base class for sparseLU
+ */
+template <typename Scalar, typename Index>
+struct SparseLUBase
+{
+ typedef Matrix<Scalar,Dynamic,1> ScalarVector;
+ typedef Matrix<Index,Dynamic,1> IndexVector;
+ typedef typename ScalarVector::RealScalar RealScalar;
+ typedef VectorBlock<Matrix<Scalar,Dynamic,1> > BlockScalarVector;
+ typedef VectorBlock<Matrix<Index,Dynamic,1> > BlockIndexVector;
+// typedef Ref<Matrix<Scalar,Dynamic,1> > BlockScalarVector;
+// typedef Ref<Matrix<Index,Dynamic,1> > BlockIndexVector;
+ typedef LU_GlobalLU_t<IndexVector, ScalarVector> GlobalLU_t;
+ typedef SparseMatrix<Scalar,ColMajor,Index> MatrixType;
+
+ static int etree_find (int i, IndexVector& pp);
+ static int LU_sp_coletree(const MatrixType& mat, IndexVector& parent);
+ static void LU_nr_etdfs (int n, IndexVector& parent, IndexVector& first_kid, IndexVector& next_kid, IndexVector& post, int postnum);
+ static void LU_TreePostorder(int n, IndexVector& parent, IndexVector& post);
+ template <typename VectorType>
+ static int expand(VectorType& vec, int& length, int nbElts, int keep_prev, int& num_expansions);
+ static int LUMemInit(int m, int n, int annz, int lwork, int fillratio, int panel_size, GlobalLU_t& glu);
+ template <typename VectorType>
+ static int LUMemXpand(VectorType& vec, int& maxlen, int nbElts, LU_MemType memtype, int& num_expansions);
+ static void LU_heap_relax_snode (const int n, IndexVector& et, const int relax_columns, IndexVector& descendants, IndexVector& relax_end);
+ static void LU_relax_snode (const int n, IndexVector& et, const int relax_columns, IndexVector& descendants, IndexVector& relax_end);
+ static int LU_snode_dfs(const int jcol, const int kcol,const MatrixType& mat, IndexVector& xprune, IndexVector& marker, LU_GlobalLU_t<IndexVector, ScalarVector>& glu);
+ static int LU_snode_bmod (const int jcol, const int fsupc, ScalarVector& dense, GlobalLU_t& glu);
+ static int LU_pivotL(const int jcol, const RealScalar diagpivotthresh, IndexVector& perm_r, IndexVector& iperm_c, int& pivrow, GlobalLU_t& glu);
+ template <typename Traits>
+ static void LU_dfs_kernel(const int jj, IndexVector& perm_r,
+ int& nseg, IndexVector& panel_lsub, IndexVector& segrep,
+ Ref<IndexVector> repfnz_col, IndexVector& xprune, Ref<IndexVector> marker, IndexVector& parent,
+ IndexVector& xplore, GlobalLU_t& glu, int& nextl_col, int krow, Traits& traits);
+ static void LU_panel_dfs(const int m, const int w, const int jcol, MatrixType& A, IndexVector& perm_r, int& nseg, ScalarVector& dense, IndexVector& panel_lsub, IndexVector& segrep, IndexVector& repfnz, IndexVector& xprune, IndexVector& marker, IndexVector& parent, IndexVector& xplore, GlobalLU_t& glu);
+
+ static void LU_panel_bmod(const int m, const int w, const int jcol, const int nseg, ScalarVector& dense, ScalarVector& tempv, IndexVector& segrep, IndexVector& repfnz, LU_perfvalues& perfv, GlobalLU_t& glu);
+ static int LU_column_dfs(const int m, const int jcol, IndexVector& perm_r, int maxsuper, int& nseg, BlockIndexVector& lsub_col, IndexVector& segrep, BlockIndexVector& repfnz, IndexVector& xprune, IndexVector& marker, IndexVector& parent, IndexVector& xplore, GlobalLU_t& glu);
+ static int LU_column_bmod(const int jcol, const int nseg, BlockScalarVector& dense, ScalarVector& tempv, BlockIndexVector& segrep, BlockIndexVector& repfnz, int fpanelc, GlobalLU_t& glu);
+ static int LU_copy_to_ucol(const int jcol, const int nseg, IndexVector& segrep, BlockIndexVector& repfnz ,IndexVector& perm_r, BlockScalarVector& dense, GlobalLU_t& glu);
+ static void LU_pruneL(const int jcol, const IndexVector& perm_r, const int pivrow, const int nseg, const IndexVector& segrep, BlockIndexVector& repfnz, IndexVector& xprune, GlobalLU_t& glu);
+ static void LU_countnz(const int n, int& nnzL, int& nnzU, GlobalLU_t& glu);
+ static void LU_fixupL(const int n, const IndexVector& perm_r, GlobalLU_t& glu);
+
+};
+
+#include "SparseLU_Coletree.h"
+#include "SparseLU_Memory.h"
+#include "SparseLU_heap_relax_snode.h"
+#include "SparseLU_relax_snode.h"
+#include "SparseLU_snode_dfs.h"
+#include "SparseLU_snode_bmod.h"
+#include "SparseLU_pivotL.h"
+#include "SparseLU_panel_dfs.h"
+#include "SparseLU_kernel_bmod.h"
+#include "SparseLU_panel_bmod.h"
+#include "SparseLU_column_dfs.h"
+#include "SparseLU_column_bmod.h"
+#include "SparseLU_copy_to_ucol.h"
+#include "SparseLU_pruneL.h"
+#include "SparseLU_Utils.h"
+
+#endif
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Coletree.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Coletree.h
new file mode 100644
index 000000000..d3bc36ea4
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Coletree.h
@@ -0,0 +1,180 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file is the modified version of sp_coletree.c file in SuperLU
+
+ * -- SuperLU routine (version 3.1) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * August 1, 2008
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_COLETREE_H
+#define SPARSELU_COLETREE_H
+/** Find the root of the tree/set containing the vertex i : Use Path halving */
+template< typename Scalar,typename Index>
+int SparseLUBase<Scalar,Index>::etree_find (int i, IndexVector& pp)
+{
+ int p = pp(i); // Parent
+ int gp = pp(p); // Grand parent
+ while (gp != p)
+ {
+ pp(i) = gp; // Parent pointer on find path is changed to former grand parent
+ i = gp;
+ p = pp(i);
+ gp = pp(p);
+ }
+ return p;
+}
+
+/** Compute the column elimination tree of a sparse matrix
+ * NOTE : The matrix is supposed to be in column-major format.
+ *
+ */
+template <typename Scalar, typename Index>
+int SparseLUBase<Scalar,Index>::LU_sp_coletree(const MatrixType& mat, IndexVector& parent)
+{
+ int nc = mat.cols(); // Number of columns
+ int nr = mat.rows(); // Number of rows
+
+ IndexVector root(nc); // root of subtree of etree
+ root.setZero();
+ IndexVector pp(nc); // disjoint sets
+ pp.setZero(); // Initialize disjoint sets
+ IndexVector firstcol(nr); // First nonzero column in each row
+
+ //Compute first nonzero column in each row
+ int row,col;
+ firstcol.setConstant(nc); //for (row = 0; row < nr; firstcol(row++) = nc);
+ for (col = 0; col < nc; col++)
+ {
+ for (typename MatrixType::InnerIterator it(mat, col); it; ++it)
+ { // Is it necessary to browse the whole matrix, the lower part should do the job ??
+ row = it.row();
+ firstcol(row) = (std::min)(firstcol(row), col);
+ }
+ }
+ /* Compute etree by Liu's algorithm for symmetric matrices,
+ except use (firstcol[r],c) in place of an edge (r,c) of A.
+ Thus each row clique in A'*A is replaced by a star
+ centered at its first vertex, which has the same fill. */
+ int rset, cset, rroot;
+ for (col = 0; col < nc; col++)
+ {
+ pp(col) = col;
+ cset = col;
+ root(cset) = col;
+ parent(col) = nc;
+ for (typename MatrixType::InnerIterator it(mat, col); it; ++it)
+ { // A sequence of interleaved find and union is performed
+ row = firstcol(it.row());
+ if (row >= col) continue;
+ rset = etree_find(row, pp); // Find the name of the set containing row
+ rroot = root(rset);
+ if (rroot != col)
+ {
+ parent(rroot) = col;
+ pp(cset) = rset;
+ cset = rset;
+ root(cset) = col;
+ }
+ }
+ }
+ return 0;
+}
+
+/**
+ * Depth-first search from vertex n. No recursion.
+ * This routine was contributed by Cédric Doucet, CEDRAT Group, Meylan, France.
+*/
+template <typename Scalar, typename Index>
+void SparseLUBase<Scalar,Index>::LU_nr_etdfs (int n, IndexVector& parent, IndexVector& first_kid, IndexVector& next_kid, IndexVector& post, int postnum)
+{
+ int current = n, first, next;
+ while (postnum != n)
+ {
+ // No kid for the current node
+ first = first_kid(current);
+
+ // no kid for the current node
+ if (first == -1)
+ {
+ // Numbering this node because it has no kid
+ post(current) = postnum++;
+
+ // looking for the next kid
+ next = next_kid(current);
+ while (next == -1)
+ {
+ // No more kids : back to the parent node
+ current = parent(current);
+ // numbering the parent node
+ post(current) = postnum++;
+
+ // Get the next kid
+ next = next_kid(current);
+ }
+ // stopping criterion
+ if (postnum == n+1) return;
+
+ // Updating current node
+ current = next;
+ }
+ else
+ {
+ current = first;
+ }
+ }
+}
+
+
+/**
+ * Post order a tree
+ * \param parent Input tree
+ * \param post postordered tree
+ */
+template <typename Scalar, typename Index>
+void SparseLUBase<Scalar,Index>::LU_TreePostorder(int n, IndexVector& parent, IndexVector& post)
+{
+ IndexVector first_kid, next_kid; // Linked list of children
+ int postnum;
+ // Allocate storage for working arrays and results
+ first_kid.resize(n+1);
+ next_kid.setZero(n+1);
+ post.setZero(n+1);
+
+ // Set up structure describing children
+ int v, dad;
+ first_kid.setConstant(-1);
+ for (v = n-1; v >= 0; v--)
+ {
+ dad = parent(v);
+ next_kid(v) = first_kid(dad);
+ first_kid(dad) = v;
+ }
+
+ // Depth-first search from dummy root vertex #n
+ postnum = 0;
+ LU_nr_etdfs(n, parent, first_kid, next_kid, post, postnum);
+}
+
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Matrix.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Matrix.h
new file mode 100644
index 000000000..31aeee64d
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Matrix.h
@@ -0,0 +1,313 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+// Copyright (C) 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/.
+
+#ifndef EIGEN_SPARSELU_MATRIX_H
+#define EIGEN_SPARSELU_MATRIX_H
+
+/** \ingroup SparseLU_Module
+ * \brief a class to manipulate the L supernodal factor from the SparseLU factorization
+ *
+ * This class contain the data to easily store
+ * and manipulate the supernodes during the factorization and solution phase of Sparse LU.
+ * Only the lower triangular matrix has supernodes.
+ *
+ * NOTE : This class corresponds to the SCformat structure in SuperLU
+ *
+ */
+/* TO DO
+ * InnerIterator as for sparsematrix
+ * SuperInnerIterator to iterate through all supernodes
+ * Function for triangular solve
+ */
+template <typename _Scalar, typename _Index>
+class SuperNodalMatrix
+{
+ public:
+ typedef _Scalar Scalar;
+ typedef _Index Index;
+ typedef Matrix<Index,Dynamic,1> IndexVector;
+ typedef Matrix<Scalar,Dynamic,1> ScalarVector;
+ public:
+ SuperNodalMatrix()
+ {
+
+ }
+ SuperNodalMatrix(int m, int n, ScalarVector& nzval, IndexVector& nzval_colptr, IndexVector& rowind,
+ IndexVector& rowind_colptr, IndexVector& col_to_sup, IndexVector& sup_to_col )
+ {
+ setInfos(m, n, nzval, nzval_colptr, rowind, rowind_colptr, col_to_sup, sup_to_col);
+ }
+
+ ~SuperNodalMatrix()
+ {
+
+ }
+ /**
+ * Set appropriate pointers for the lower triangular supernodal matrix
+ * These infos are available at the end of the numerical factorization
+ * FIXME This class will be modified such that it can be use in the course
+ * of the factorization.
+ */
+ void setInfos(int m, int n, ScalarVector& nzval, IndexVector& nzval_colptr, IndexVector& rowind,
+ IndexVector& rowind_colptr, IndexVector& col_to_sup, IndexVector& sup_to_col )
+ {
+ m_row = m;
+ m_col = n;
+ m_nzval = nzval.data();
+ m_nzval_colptr = nzval_colptr.data();
+ m_rowind = rowind.data();
+ m_rowind_colptr = rowind_colptr.data();
+ m_nsuper = col_to_sup(n);
+ m_col_to_sup = col_to_sup.data();
+ m_sup_to_col = sup_to_col.data();
+
+ }
+
+ /**
+ * Number of rows
+ */
+ int rows()
+ {
+ return m_row;
+ }
+
+ /**
+ * Number of columns
+ */
+ int cols()
+ {
+ return m_col;
+ }
+
+ /**
+ * Return the array of nonzero values packed by column
+ *
+ * The size is nnz
+ */
+ Scalar* valuePtr()
+ {
+ return m_nzval;
+ }
+
+ const Scalar* valuePtr() const
+ {
+ return m_nzval;
+ }
+ /**
+ * Return the pointers to the beginning of each column in \ref valuePtr()
+ */
+ Index* colIndexPtr()
+ {
+ return m_nzval_colptr;
+ }
+
+ const Index* colIndexPtr() const
+ {
+ return m_nzval_colptr;
+ }
+
+ /**
+ * Return the array of compressed row indices of all supernodes
+ */
+ Index* rowIndex()
+ {
+ return m_rowind;
+ }
+
+ const Index* rowIndex() const
+ {
+ return m_rowind;
+ }
+
+ /**
+ * Return the location in \em rowvaluePtr() which starts each column
+ */
+ Index* rowIndexPtr()
+ {
+ return m_rowind_colptr;
+ }
+
+ const Index* rowIndexPtr() const
+ {
+ return m_rowind_colptr;
+ }
+
+ /**
+ * Return the array of column-to-supernode mapping
+ */
+ Index* colToSup()
+ {
+ return m_col_to_sup;
+ }
+
+ const Index* colToSup() const
+ {
+ return m_col_to_sup;
+ }
+ /**
+ * Return the array of supernode-to-column mapping
+ */
+ Index* supToCol()
+ {
+ return m_sup_to_col;
+ }
+
+ const Index* supToCol() const
+ {
+ return m_sup_to_col;
+ }
+
+ /**
+ * Return the number of supernodes
+ */
+ int nsuper() const
+ {
+ return m_nsuper;
+ }
+
+ class InnerIterator;
+ template<typename Dest>
+ void solveInPlace( MatrixBase<Dest>&X) const;
+
+
+
+
+ protected:
+ Index m_row; // Number of rows
+ Index m_col; // Number of columns
+ Index m_nsuper; // Number of supernodes
+ Scalar* m_nzval; //array of nonzero values packed by column
+ Index* m_nzval_colptr; //nzval_colptr[j] Stores the location in nzval[] which starts column j
+ Index* m_rowind; // Array of compressed row indices of rectangular supernodes
+ Index* m_rowind_colptr; //rowind_colptr[j] stores the location in rowind[] which starts column j
+ Index* m_col_to_sup; // col_to_sup[j] is the supernode number to which column j belongs
+ Index* m_sup_to_col; //sup_to_col[s] points to the starting column of the s-th supernode
+
+ private :
+};
+
+/**
+ * \brief InnerIterator class to iterate over nonzero values of the current column in the supernode
+ *
+ */
+template<typename Scalar, typename Index>
+class SuperNodalMatrix<Scalar,Index>::InnerIterator
+{
+ public:
+ InnerIterator(const SuperNodalMatrix& mat, Index outer)
+ : m_matrix(mat),
+ m_outer(outer),
+ m_idval(mat.colIndexPtr()[outer]),
+ m_startval(m_idval),
+ m_endval(mat.colIndexPtr()[outer+1]),
+ m_idrow(mat.rowIndexPtr()[outer]),
+ m_startidrow(m_idrow),
+ m_endidrow(mat.rowIndexPtr()[outer+1])
+ {}
+ inline InnerIterator& operator++()
+ {
+ m_idval++;
+ m_idrow++;
+ return *this;
+ }
+ inline Scalar value() const { return m_matrix.valuePtr()[m_idval]; }
+
+ inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix.valuePtr()[m_idval]); }
+
+ inline Index index() const { return m_matrix.rowIndex()[m_idrow]; }
+ inline Index row() const { return index(); }
+ inline Index col() const { return m_outer; }
+
+ inline Index supIndex() const { return m_matrix.colToSup()[m_outer]; }
+
+ inline operator bool() const
+ {
+ return ( (m_idval < m_endval) && (m_idval > m_startval) &&
+ (m_idrow < m_endidrow) && (m_idrow > m_startidrow) );
+ }
+
+ protected:
+ const SuperNodalMatrix& m_matrix; // Supernodal lower triangular matrix
+ const Index m_outer; // Current column
+ Index m_idval; //Index to browse the values in the current column
+ const Index m_startval; // Start of the column value
+ const Index m_endval; // End of the column value
+ Index m_idrow; //Index to browse the row indices
+ const Index m_startidrow; // Start of the row indices of the current column value
+ const Index m_endidrow; // End of the row indices of the current column value
+};
+
+/**
+ * \brief Solve with the supernode triangular matrix
+ *
+ */
+template<typename Scalar, typename Index>
+template<typename Dest>
+void SuperNodalMatrix<Scalar,Index>::solveInPlace( MatrixBase<Dest>&X) const
+{
+ Index n = X.rows();
+ int nrhs = X.cols();
+ const Scalar * Lval = valuePtr(); // Nonzero values
+ Matrix<Scalar,Dynamic,Dynamic> work(n, nrhs); // working vector
+ work.setZero();
+ for (int k = 0; k <= nsuper(); k ++)
+ {
+ Index fsupc = supToCol()[k]; // First column of the current supernode
+ Index istart = rowIndexPtr()[fsupc]; // Pointer index to the subscript of the current column
+ Index nsupr = rowIndexPtr()[fsupc+1] - istart; // Number of rows in the current supernode
+ Index nsupc = supToCol()[k+1] - fsupc; // Number of columns in the current supernode
+ Index nrow = nsupr - nsupc; // Number of rows in the non-diagonal part of the supernode
+ Index irow; //Current index row
+
+ if (nsupc == 1 )
+ {
+ for (int j = 0; j < nrhs; j++)
+ {
+ InnerIterator it(*this, fsupc);
+ ++it; // Skip the diagonal element
+ for (; it; ++it)
+ {
+ irow = it.row();
+ X(irow, j) -= X(fsupc, j) * it.value();
+ }
+ }
+ }
+ else
+ {
+ // The supernode has more than one column
+ Index luptr = colIndexPtr()[fsupc];
+
+ // Triangular solve
+ Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(Lval[luptr]), nsupc, nsupc, OuterStride<>(nsupr) );
+ Map< Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > U (&(X(fsupc,0)), nsupc, nrhs, OuterStride<>(n) );
+ U = A.template triangularView<UnitLower>().solve(U);
+
+ // Matrix-vector product
+ new (&A) Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > ( &(Lval[luptr+nsupc]), nrow, nsupc, OuterStride<>(nsupr) );
+ work.block(0, 0, nrow, nrhs) = A * U;
+
+ //Begin Scatter
+ for (int j = 0; j < nrhs; j++)
+ {
+ Index iptr = istart + nsupc;
+ for (int i = 0; i < nrow; i++)
+ {
+ irow = rowIndex()[iptr];
+ X(irow, j) -= work(i, j); // Scatter operation
+ work(i, j) = Scalar(0);
+ iptr++;
+ }
+ }
+ }
+ }
+}
+
+
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Memory.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Memory.h
new file mode 100644
index 000000000..7b9f01355
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Memory.h
@@ -0,0 +1,204 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file is the modified version of [s,d,c,z]memory.c files in SuperLU
+
+ * -- SuperLU routine (version 3.1) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * August 1, 2008
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+
+#ifndef EIGEN_SPARSELU_MEMORY
+#define EIGEN_SPARSELU_MEMORY
+
+#define LU_NO_MARKER 3
+#define LU_NUM_TEMPV(m,w,t,b) ((std::max)(m, (t+b)*w) )
+#define IND_EMPTY (-1)
+
+#define LU_Reduce(alpha) ((alpha + 1) / 2) // i.e (alpha-1)/2 + 1
+#define LU_GluIntArray(n) (5* (n) + 5)
+#define LU_TempSpace(m, w) ( (2*w + 4 + LU_NO_MARKER) * m * sizeof(Index) \
+ + (w + 1) * m * sizeof(Scalar) )
+
+
+/**
+ * Expand the existing storage to accomodate more fill-ins
+ * \param vec Valid pointer to the vector to allocate or expand
+ * \param [in,out]length At input, contain the current length of the vector that is to be increased. At output, length of the newly allocated vector
+ * \param [in]nbElts Current number of elements in the factors
+ * \param keep_prev 1: use length and do not expand the vector; 0: compute new_len and expand
+ * \param [in,out]num_expansions Number of times the memory has been expanded
+ */
+template <typename Scalar, typename Index>
+template <typename VectorType>
+int SparseLUBase<Scalar,Index>::expand(VectorType& vec, int& length, int nbElts, int keep_prev, int& num_expansions)
+{
+
+ float alpha = 1.5; // Ratio of the memory increase
+ int new_len; // New size of the allocated memory
+
+ if(num_expansions == 0 || keep_prev)
+ new_len = length ; // First time allocate requested
+ else
+ new_len = alpha * length ;
+
+ VectorType old_vec; // Temporary vector to hold the previous values
+ if (nbElts > 0 )
+ old_vec = vec.segment(0,nbElts);
+
+ //Allocate or expand the current vector
+ try
+ {
+ vec.resize(new_len);
+ }
+ catch(std::bad_alloc& )
+ {
+ if ( !num_expansions )
+ {
+ // First time to allocate from LUMemInit()
+ throw; // Pass the exception to LUMemInit() which has a try... catch block
+ }
+ if (keep_prev)
+ {
+ // In this case, the memory length should not not be reduced
+ return new_len;
+ }
+ else
+ {
+ // Reduce the size and increase again
+ int tries = 0; // Number of attempts
+ do
+ {
+ alpha = LU_Reduce(alpha);
+ new_len = alpha * length ;
+ try
+ {
+ vec.resize(new_len);
+ }
+ catch(std::bad_alloc& )
+ {
+ tries += 1;
+ if ( tries > 10) return new_len;
+ }
+ } while (!vec.size());
+ }
+ }
+ //Copy the previous values to the newly allocated space
+ if (nbElts > 0)
+ vec.segment(0, nbElts) = old_vec;
+
+
+ length = new_len;
+ if(num_expansions) ++num_expansions;
+ return 0;
+}
+
+/**
+ * \brief Allocate various working space for the numerical factorization phase.
+ * \param m number of rows of the input matrix
+ * \param n number of columns
+ * \param annz number of initial nonzeros in the matrix
+ * \param lwork if lwork=-1, this routine returns an estimated size of the required memory
+ * \param glu persistent data to facilitate multiple factors : will be deleted later ??
+ * \return an estimated size of the required memory if lwork = -1; otherwise, return the size of actually allocated memory when allocation failed, and 0 on success
+ * NOTE Unlike SuperLU, this routine does not support successive factorization with the same pattern and the same row permutation
+ */
+template <typename Scalar, typename Index>
+int SparseLUBase<Scalar,Index>::LUMemInit(int m, int n, int annz, int lwork, int fillratio, int panel_size, GlobalLU_t& glu)
+{
+ int& num_expansions = glu.num_expansions; //No memory expansions so far
+ num_expansions = 0;
+ glu.nzumax = glu.nzlumax = (std::max)(fillratio * annz, m*n); // estimated number of nonzeros in U
+ glu.nzlmax = (std::max)(1., fillratio/4.) * annz; // estimated nnz in L factor
+
+ // Return the estimated size to the user if necessary
+ if (lwork == IND_EMPTY)
+ {
+ int estimated_size;
+ estimated_size = LU_GluIntArray(n) * sizeof(Index) + LU_TempSpace(m, panel_size)
+ + (glu.nzlmax + glu.nzumax) * sizeof(Index) + (glu.nzlumax+glu.nzumax) * sizeof(Scalar) + n;
+ return estimated_size;
+ }
+
+ // Setup the required space
+
+ // First allocate Integer pointers for L\U factors
+ glu.xsup.resize(n+1);
+ glu.supno.resize(n+1);
+ glu.xlsub.resize(n+1);
+ glu.xlusup.resize(n+1);
+ glu.xusub.resize(n+1);
+
+ // Reserve memory for L/U factors
+ do
+ {
+ try
+ {
+ expand<ScalarVector>(glu.lusup, glu.nzlumax, 0, 0, num_expansions);
+ expand<ScalarVector>(glu.ucol,glu.nzumax, 0, 0, num_expansions);
+ expand<IndexVector>(glu.lsub,glu.nzlmax, 0, 0, num_expansions);
+ expand<IndexVector>(glu.usub,glu.nzumax, 0, 1, num_expansions);
+ }
+ catch(std::bad_alloc& )
+ {
+ //Reduce the estimated size and retry
+ glu.nzlumax /= 2;
+ glu.nzumax /= 2;
+ glu.nzlmax /= 2;
+ if (glu.nzlumax < annz ) return glu.nzlumax;
+ }
+
+ } while (!glu.lusup.size() || !glu.ucol.size() || !glu.lsub.size() || !glu.usub.size());
+
+
+
+ ++num_expansions;
+ return 0;
+
+} // end LuMemInit
+
+/**
+ * \brief Expand the existing storage
+ * \param vec vector to expand
+ * \param [in,out]maxlen On input, previous size of vec (Number of elements to copy ). on output, new size
+ * \param nbElts current number of elements in the vector.
+ * \param glu Global data structure
+ * \return 0 on success, > 0 size of the memory allocated so far
+ */
+template <typename Scalar, typename Index>
+template <typename VectorType>
+int SparseLUBase<Scalar,Index>::LUMemXpand(VectorType& vec, int& maxlen, int nbElts, LU_MemType memtype, int& num_expansions)
+{
+ int failed_size;
+ if (memtype == USUB)
+ failed_size = expand<VectorType>(vec, maxlen, nbElts, 1, num_expansions);
+ else
+ failed_size = expand<VectorType>(vec, maxlen, nbElts, 0, num_expansions);
+
+ if (failed_size)
+ return failed_size;
+
+ return 0 ;
+
+}
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Structs.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Structs.h
new file mode 100644
index 000000000..7b3aa250c
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Structs.h
@@ -0,0 +1,103 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file comes from a partly modified version of files slu_[s,d,c,z]defs.h
+ * -- SuperLU routine (version 4.1) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * November, 2010
+ *
+ * Global data structures used in LU factorization -
+ *
+ * nsuper: #supernodes = nsuper + 1, numbered [0, nsuper].
+ * (xsup,supno): supno[i] is the supernode no to which i belongs;
+ * xsup(s) points to the beginning of the s-th supernode.
+ * e.g. supno 0 1 2 2 3 3 3 4 4 4 4 4 (n=12)
+ * xsup 0 1 2 4 7 12
+ * Note: dfs will be performed on supernode rep. relative to the new
+ * row pivoting ordering
+ *
+ * (xlsub,lsub): lsub[*] contains the compressed subscript of
+ * rectangular supernodes; xlsub[j] points to the starting
+ * location of the j-th column in lsub[*]. Note that xlsub
+ * is indexed by column.
+ * Storage: original row subscripts
+ *
+ * During the course of sparse LU factorization, we also use
+ * (xlsub,lsub) for the purpose of symmetric pruning. For each
+ * supernode {s,s+1,...,t=s+r} with first column s and last
+ * column t, the subscript set
+ * lsub[j], j=xlsub[s], .., xlsub[s+1]-1
+ * is the structure of column s (i.e. structure of this supernode).
+ * It is used for the storage of numerical values.
+ * Furthermore,
+ * lsub[j], j=xlsub[t], .., xlsub[t+1]-1
+ * is the structure of the last column t of this supernode.
+ * It is for the purpose of symmetric pruning. Therefore, the
+ * structural subscripts can be rearranged without making physical
+ * interchanges among the numerical values.
+ *
+ * However, if the supernode has only one column, then we
+ * only keep one set of subscripts. For any subscript interchange
+ * performed, similar interchange must be done on the numerical
+ * values.
+ *
+ * The last column structures (for pruning) will be removed
+ * after the numercial LU factorization phase.
+ *
+ * (xlusup,lusup): lusup[*] contains the numerical values of the
+ * rectangular supernodes; xlusup[j] points to the starting
+ * location of the j-th column in storage vector lusup[*]
+ * Note: xlusup is indexed by column.
+ * Each rectangular supernode is stored by column-major
+ * scheme, consistent with Fortran 2-dim array storage.
+ *
+ * (xusub,ucol,usub): ucol[*] stores the numerical values of
+ * U-columns outside the rectangular supernodes. The row
+ * subscript of nonzero ucol[k] is stored in usub[k].
+ * xusub[i] points to the starting location of column i in ucol.
+ * Storage: new row subscripts; that is subscripts of PA.
+ */
+#ifndef EIGEN_LU_STRUCTS
+#define EIGEN_LU_STRUCTS
+typedef enum {LUSUP, UCOL, LSUB, USUB, LLVL, ULVL} LU_MemType;
+
+
+template <typename IndexVector, typename ScalarVector>
+struct LU_GlobalLU_t {
+ typedef typename IndexVector::Scalar Index;
+ IndexVector xsup; //First supernode column ... xsup(s) points to the beginning of the s-th supernode
+ IndexVector supno; // Supernode number corresponding to this column (column to supernode mapping)
+ ScalarVector lusup; // nonzero values of L ordered by columns
+ IndexVector lsub; // Compressed row indices of L rectangular supernodes.
+ IndexVector xlusup; // pointers to the beginning of each column in lusup
+ IndexVector xlsub; // pointers to the beginning of each column in lsub
+ Index nzlmax; // Current max size of lsub
+ Index nzlumax; // Current max size of lusup
+ ScalarVector ucol; // nonzero values of U ordered by columns
+ IndexVector usub; // row indices of U columns in ucol
+ IndexVector xusub; // Pointers to the beginning of each column of U in ucol
+ Index nzumax; // Current max size of ucol
+ Index n; // Number of columns in the matrix
+ int num_expansions;
+};
+
+// Values to set for performance
+struct LU_perfvalues {
+ int panel_size; // a panel consists of at most <panel_size> consecutive columns
+ int relax; // To control degree of relaxing supernodes. If the number of nodes (columns)
+ // in a subtree of the elimination tree is less than relax, this subtree is considered
+ // as one supernode regardless of the row structures of those columns
+ int maxsuper; // The maximum size for a supernode in complete LU
+ int rowblk; // The minimum row dimension for 2-D blocking to be used;
+ int colblk; // The minimum column dimension for 2-D blocking to be used;
+ int fillfactor; // The estimated fills factors for L and U, compared with A
+};
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Utils.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Utils.h
new file mode 100644
index 000000000..b13930dbb
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_Utils.h
@@ -0,0 +1,75 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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/.
+
+
+#ifndef EIGEN_SPARSELU_UTILS_H
+#define EIGEN_SPARSELU_UTILS_H
+
+
+/**
+ * \brief Count Nonzero elements in the factors
+ */
+template <typename Scalar, typename Index>
+void SparseLUBase<Scalar,Index>::LU_countnz(const int n, int& nnzL, int& nnzU, GlobalLU_t& glu)
+{
+ nnzL = 0;
+ nnzU = (glu.xusub)(n);
+ int nsuper = (glu.supno)(n);
+ int jlen;
+ int i, j, fsupc;
+ if (n <= 0 ) return;
+ // For each supernode
+ for (i = 0; i <= nsuper; i++)
+ {
+ fsupc = glu.xsup(i);
+ jlen = glu.xlsub(fsupc+1) - glu.xlsub(fsupc);
+
+ for (j = fsupc; j < glu.xsup(i+1); j++)
+ {
+ nnzL += jlen;
+ nnzU += j - fsupc + 1;
+ jlen--;
+ }
+ }
+
+}
+/**
+ * \brief Fix up the data storage lsub for L-subscripts.
+ *
+ * It removes the subscripts sets for structural pruning,
+ * and applies permutation to the remaining subscripts
+ *
+ */
+template <typename Scalar, typename Index>
+void SparseLUBase<Scalar,Index>::LU_fixupL(const int n, const IndexVector& perm_r, GlobalLU_t& glu)
+{
+ int fsupc, i, j, k, jstart;
+
+ int nextl = 0;
+ int nsuper = (glu.supno)(n);
+
+ // For each supernode
+ for (i = 0; i <= nsuper; i++)
+ {
+ fsupc = glu.xsup(i);
+ jstart = glu.xlsub(fsupc);
+ glu.xlsub(fsupc) = nextl;
+ for (j = jstart; j < glu.xlsub(fsupc + 1); j++)
+ {
+ glu.lsub(nextl) = perm_r(glu.lsub(j)); // Now indexed into P*A
+ nextl++;
+ }
+ for (k = fsupc+1; k < glu.xsup(i+1); k++)
+ glu.xlsub(k) = nextl; // other columns in supernode i
+ }
+
+ glu.xlsub(n) = nextl;
+}
+
+#endif
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_column_bmod.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_column_bmod.h
new file mode 100644
index 000000000..94f18fb73
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_column_bmod.h
@@ -0,0 +1,162 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+// Copyright (C) 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: This file is the modified version of xcolumn_bmod.c file in SuperLU
+
+ * -- SuperLU routine (version 3.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * October 15, 2003
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_COLUMN_BMOD_H
+#define SPARSELU_COLUMN_BMOD_H
+
+/**
+ * \brief Performs numeric block updates (sup-col) in topological order
+ *
+ * \param jcol current column to update
+ * \param nseg Number of segments in the U part
+ * \param dense Store the full representation of the column
+ * \param tempv working array
+ * \param segrep segment representative ...
+ * \param repfnz ??? First nonzero column in each row ??? ...
+ * \param fpanelc First column in the current panel
+ * \param glu Global LU data.
+ * \return 0 - successful return
+ * > 0 - number of bytes allocated when run out of space
+ *
+ */
+template <typename Scalar, typename Index>
+int SparseLUBase<Scalar,Index>::LU_column_bmod(const int jcol, const int nseg, BlockScalarVector& dense, ScalarVector& tempv, BlockIndexVector& segrep, BlockIndexVector& repfnz, int fpanelc, GlobalLU_t& glu)
+{
+ int jsupno, k, ksub, krep, ksupno;
+ int lptr, nrow, isub, irow, nextlu, new_next, ufirst;
+ int fsupc, nsupc, nsupr, luptr, kfnz, no_zeros;
+ /* krep = representative of current k-th supernode
+ * fsupc = first supernodal column
+ * nsupc = number of columns in a supernode
+ * nsupr = number of rows in a supernode
+ * luptr = location of supernodal LU-block in storage
+ * kfnz = first nonz in the k-th supernodal segment
+ * no_zeros = no lf leading zeros in a supernodal U-segment
+ */
+
+ jsupno = glu.supno(jcol);
+ // For each nonzero supernode segment of U[*,j] in topological order
+ k = nseg - 1;
+ int d_fsupc; // distance between the first column of the current panel and the
+ // first column of the current snode
+ int fst_col; // First column within small LU update
+ int segsize;
+ for (ksub = 0; ksub < nseg; ksub++)
+ {
+ krep = segrep(k); k--;
+ ksupno = glu.supno(krep);
+ if (jsupno != ksupno )
+ {
+ // outside the rectangular supernode
+ fsupc = glu.xsup(ksupno);
+ fst_col = (std::max)(fsupc, fpanelc);
+
+ // Distance from the current supernode to the current panel;
+ // d_fsupc = 0 if fsupc > fpanelc
+ d_fsupc = fst_col - fsupc;
+
+ luptr = glu.xlusup(fst_col) + d_fsupc;
+ lptr = glu.xlsub(fsupc) + d_fsupc;
+
+ kfnz = repfnz(krep);
+ kfnz = (std::max)(kfnz, fpanelc);
+
+ segsize = krep - kfnz + 1;
+ nsupc = krep - fst_col + 1;
+ nsupr = glu.xlsub(fsupc+1) - glu.xlsub(fsupc);
+ nrow = nsupr - d_fsupc - nsupc;
+
+ // Perform a triangular solver and block update,
+ // then scatter the result of sup-col update to dense
+ no_zeros = kfnz - fst_col;
+ if(segsize==1)
+ LU_kernel_bmod<1>::run(segsize, dense, tempv, glu.lusup, luptr, nsupr, nrow, glu.lsub, lptr, no_zeros);
+ else
+ LU_kernel_bmod<Dynamic>::run(segsize, dense, tempv, glu.lusup, luptr, nsupr, nrow, glu.lsub, lptr, no_zeros);
+ } // end if jsupno
+ } // end for each segment
+
+ // Process the supernodal portion of L\U[*,j]
+ nextlu = glu.xlusup(jcol);
+ fsupc = glu.xsup(jsupno);
+
+ // copy the SPA dense into L\U[*,j]
+ int mem;
+ new_next = nextlu + glu.xlsub(fsupc + 1) - glu.xlsub(fsupc);
+ while (new_next > glu.nzlumax )
+ {
+ mem = LUMemXpand<ScalarVector>(glu.lusup, glu.nzlumax, nextlu, LUSUP, glu.num_expansions);
+ if (mem) return mem;
+ }
+
+ for (isub = glu.xlsub(fsupc); isub < glu.xlsub(fsupc+1); isub++)
+ {
+ irow = glu.lsub(isub);
+ glu.lusup(nextlu) = dense(irow);
+ dense(irow) = Scalar(0.0);
+ ++nextlu;
+ }
+
+ glu.xlusup(jcol + 1) = nextlu; // close L\U(*,jcol);
+
+ /* For more updates within the panel (also within the current supernode),
+ * should start from the first column of the panel, or the first column
+ * of the supernode, whichever is bigger. There are two cases:
+ * 1) fsupc < fpanelc, then fst_col <-- fpanelc
+ * 2) fsupc >= fpanelc, then fst_col <-- fsupc
+ */
+ fst_col = (std::max)(fsupc, fpanelc);
+
+ if (fst_col < jcol)
+ {
+ // Distance between the current supernode and the current panel
+ // d_fsupc = 0 if fsupc >= fpanelc
+ d_fsupc = fst_col - fsupc;
+
+ lptr = glu.xlsub(fsupc) + d_fsupc;
+ luptr = glu.xlusup(fst_col) + d_fsupc;
+ nsupr = glu.xlsub(fsupc+1) - glu.xlsub(fsupc); // leading dimension
+ nsupc = jcol - fst_col; // excluding jcol
+ nrow = nsupr - d_fsupc - nsupc;
+
+ // points to the beginning of jcol in snode L\U(jsupno)
+ ufirst = glu.xlusup(jcol) + d_fsupc;
+ Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(glu.lusup.data()[luptr]), nsupc, nsupc, OuterStride<>(nsupr) );
+ VectorBlock<ScalarVector> u(glu.lusup, ufirst, nsupc);
+ u = A.template triangularView<UnitLower>().solve(u);
+
+ new (&A) Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > ( &(glu.lusup.data()[luptr+nsupc]), nrow, nsupc, OuterStride<>(nsupr) );
+ VectorBlock<ScalarVector> l(glu.lusup, ufirst+nsupc, nrow);
+ l.noalias() -= A * u;
+
+ } // End if fst_col
+ return 0;
+}
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_column_dfs.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_column_dfs.h
new file mode 100644
index 000000000..fa8dcf18d
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_column_dfs.h
@@ -0,0 +1,164 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file is the modified version of [s,d,c,z]column_dfs.c file in SuperLU
+
+ * -- SuperLU routine (version 2.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * November 15, 1997
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_COLUMN_DFS_H
+#define SPARSELU_COLUMN_DFS_H
+/**
+ * \brief Performs a symbolic factorization on column jcol and decide the supernode boundary
+ *
+ * A supernode representative is the last column of a supernode.
+ * The nonzeros in U[*,j] are segments that end at supernodes representatives.
+ * The routine returns a list of the supernodal representatives
+ * in topological order of the dfs that generates them.
+ * The location of the first nonzero in each supernodal segment
+ * (supernodal entry location) is also returned.
+ *
+ * \param m number of rows in the matrix
+ * \param jcol Current column
+ * \param perm_r Row permutation
+ * \param maxsuper Maximum number of column allowed in a supernode
+ * \param [in,out] nseg Number of segments in current U[*,j] - new segments appended
+ * \param lsub_col defines the rhs vector to start the dfs
+ * \param [in,out] segrep Segment representatives - new segments appended
+ * \param repfnz First nonzero location in each row
+ * \param xprune
+ * \param marker marker[i] == jj, if i was visited during dfs of current column jj;
+ * \param parent
+ * \param xplore working array
+ * \param glu global LU data
+ * \return 0 success
+ * > 0 number of bytes allocated when run out of space
+ *
+ */
+template<typename IndexVector, typename ScalarVector>
+struct LU_column_dfs_traits
+{
+ typedef typename IndexVector::Scalar Index;
+ typedef typename ScalarVector::Scalar Scalar;
+ LU_column_dfs_traits(Index jcol, Index& jsuper, LU_GlobalLU_t<IndexVector, ScalarVector>& glu)
+ : m_jcol(jcol), m_jsuper_ref(jsuper), m_glu(glu)
+ {}
+ bool update_segrep(Index /*krep*/, Index /*jj*/)
+ {
+ return true;
+ }
+ void mem_expand(IndexVector& lsub, int& nextl, int chmark)
+ {
+ if (nextl >= m_glu.nzlmax)
+ SparseLUBase<Scalar,Index>::LUMemXpand(lsub, m_glu.nzlmax, nextl, LSUB, m_glu.num_expansions);
+ if (chmark != (m_jcol-1)) m_jsuper_ref = IND_EMPTY;
+ }
+ enum { ExpandMem = true };
+
+ int m_jcol;
+ int& m_jsuper_ref;
+ LU_GlobalLU_t<IndexVector, ScalarVector>& m_glu;
+};
+
+template <typename Scalar, typename Index>
+int SparseLUBase<Scalar,Index>::LU_column_dfs(const int m, const int jcol, IndexVector& perm_r, int maxsuper, int& nseg, BlockIndexVector& lsub_col, IndexVector& segrep, BlockIndexVector& repfnz, IndexVector& xprune, IndexVector& marker, IndexVector& parent, IndexVector& xplore, GlobalLU_t& glu)
+{
+
+ int jsuper = glu.supno(jcol);
+ int nextl = glu.xlsub(jcol);
+ VectorBlock<IndexVector> marker2(marker, 2*m, m);
+
+
+ LU_column_dfs_traits<IndexVector, ScalarVector> traits(jcol, jsuper, glu);
+
+ // For each nonzero in A(*,jcol) do dfs
+ for (int k = 0; lsub_col[k] != IND_EMPTY; k++)
+ {
+ int krow = lsub_col(k);
+ lsub_col(k) = IND_EMPTY;
+ int kmark = marker2(krow);
+
+ // krow was visited before, go to the next nonz;
+ if (kmark == jcol) continue;
+
+ LU_dfs_kernel(jcol, perm_r, nseg, glu.lsub, segrep, repfnz, xprune, marker2, parent,
+ xplore, glu, nextl, krow, traits);
+ } // for each nonzero ...
+
+ int fsupc, jptr, jm1ptr, ito, ifrom, istop;
+ int nsuper = glu.supno(jcol);
+ int jcolp1 = jcol + 1;
+ int jcolm1 = jcol - 1;
+
+ // check to see if j belongs in the same supernode as j-1
+ if ( jcol == 0 )
+ { // Do nothing for column 0
+ nsuper = glu.supno(0) = 0 ;
+ }
+ else
+ {
+ fsupc = glu.xsup(nsuper);
+ jptr = glu.xlsub(jcol); // Not yet compressed
+ jm1ptr = glu.xlsub(jcolm1);
+
+ // Use supernodes of type T2 : see SuperLU paper
+ if ( (nextl-jptr != jptr-jm1ptr-1) ) jsuper = IND_EMPTY;
+
+ // Make sure the number of columns in a supernode doesn't
+ // exceed threshold
+ if ( (jcol - fsupc) >= maxsuper) jsuper = IND_EMPTY;
+
+ /* If jcol starts a new supernode, reclaim storage space in
+ * glu.lsub from previous supernode. Note we only store
+ * the subscript set of the first and last columns of
+ * a supernode. (first for num values, last for pruning)
+ */
+ if (jsuper == IND_EMPTY)
+ { // starts a new supernode
+ if ( (fsupc < jcolm1-1) )
+ { // >= 3 columns in nsuper
+ ito = glu.xlsub(fsupc+1);
+ glu.xlsub(jcolm1) = ito;
+ istop = ito + jptr - jm1ptr;
+ xprune(jcolm1) = istop; // intialize xprune(jcol-1)
+ glu.xlsub(jcol) = istop;
+
+ for (ifrom = jm1ptr; ifrom < nextl; ++ifrom, ++ito)
+ glu.lsub(ito) = glu.lsub(ifrom);
+ nextl = ito; // = istop + length(jcol)
+ }
+ nsuper++;
+ glu.supno(jcol) = nsuper;
+ } // if a new supernode
+ } // end else: jcol > 0
+
+ // Tidy up the pointers before exit
+ glu.xsup(nsuper+1) = jcolp1;
+ glu.supno(jcolp1) = nsuper;
+ xprune(jcol) = nextl; // Intialize upper bound for pruning
+ glu.xlsub(jcolp1) = nextl;
+
+ return 0;
+}
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h
new file mode 100644
index 000000000..d3227469d
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h
@@ -0,0 +1,100 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file is the modified version of [s,d,c,z]copy_to_ucol.c file in SuperLU
+
+ * -- SuperLU routine (version 2.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * November 15, 1997
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_COPY_TO_UCOL_H
+#define SPARSELU_COPY_TO_UCOL_H
+
+/**
+ * \brief Performs numeric block updates (sup-col) in topological order
+ *
+ * \param jcol current column to update
+ * \param nseg Number of segments in the U part
+ * \param segrep segment representative ...
+ * \param repfnz First nonzero column in each row ...
+ * \param perm_r Row permutation
+ * \param dense Store the full representation of the column
+ * \param glu Global LU data.
+ * \return 0 - successful return
+ * > 0 - number of bytes allocated when run out of space
+ *
+ */
+template <typename Scalar, typename Index>
+int SparseLUBase<Scalar,Index>::LU_copy_to_ucol(const int jcol, const int nseg, IndexVector& segrep, BlockIndexVector& repfnz ,IndexVector& perm_r, BlockScalarVector& dense, GlobalLU_t& glu)
+{
+ Index ksub, krep, ksupno;
+
+ Index jsupno = glu.supno(jcol);
+
+ // For each nonzero supernode segment of U[*,j] in topological order
+ int k = nseg - 1, i;
+ Index nextu = glu.xusub(jcol);
+ Index kfnz, isub, segsize;
+ Index new_next,irow;
+ Index fsupc, mem;
+ for (ksub = 0; ksub < nseg; ksub++)
+ {
+ krep = segrep(k); k--;
+ ksupno = glu.supno(krep);
+ if (jsupno != ksupno ) // should go into ucol();
+ {
+ kfnz = repfnz(krep);
+ if (kfnz != IND_EMPTY)
+ { // Nonzero U-segment
+ fsupc = glu.xsup(ksupno);
+ isub = glu.xlsub(fsupc) + kfnz - fsupc;
+ segsize = krep - kfnz + 1;
+ new_next = nextu + segsize;
+ while (new_next > glu.nzumax)
+ {
+ mem = LUMemXpand<ScalarVector>(glu.ucol, glu.nzumax, nextu, UCOL, glu.num_expansions);
+ if (mem) return mem;
+ mem = LUMemXpand<IndexVector>(glu.usub, glu.nzumax, nextu, USUB, glu.num_expansions);
+ if (mem) return mem;
+
+ }
+
+ for (i = 0; i < segsize; i++)
+ {
+ irow = glu.lsub(isub);
+ glu.usub(nextu) = perm_r(irow); // Unlike the L part, the U part is stored in its final order
+ glu.ucol(nextu) = dense(irow);
+ dense(irow) = Scalar(0.0);
+ nextu++;
+ isub++;
+ }
+
+ } // end nonzero U-segment
+
+ } // end if jsupno
+
+ } // end for each segment
+ glu.xusub(jcol + 1) = nextu; // close U(*,jcol)
+ return 0;
+}
+
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h
new file mode 100644
index 000000000..69e1d4da9
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h
@@ -0,0 +1,119 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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/.
+
+/* This file is a modified version of heap_relax_snode.c file in SuperLU
+ * -- SuperLU routine (version 3.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * October 15, 2003
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+
+#ifndef SPARSELU_HEAP_RELAX_SNODE_H
+#define SPARSELU_HEAP_RELAX_SNODE_H
+#include "SparseLU_Coletree.h"
+/**
+ * \brief Identify the initial relaxed supernodes
+ *
+ * This routine applied to a symmetric elimination tree.
+ * It assumes that the matrix has been reordered according to the postorder of the etree
+ * \param et elimination tree
+ * \param relax_columns Maximum number of columns allowed in a relaxed snode
+ * \param descendants Number of descendants of each node in the etree
+ * \param relax_end last column in a supernode
+ */
+template <typename Scalar, typename Index>
+void SparseLUBase<Scalar,Index>::LU_heap_relax_snode (const int n, IndexVector& et, const int relax_columns, IndexVector& descendants, IndexVector& relax_end)
+{
+
+ // The etree may not be postordered, but its heap ordered
+ IndexVector post;
+ LU_TreePostorder(n, et, post); // Post order etree
+ IndexVector inv_post(n+1);
+ int i;
+ for (i = 0; i < n+1; ++i) inv_post(post(i)) = i; // inv_post = post.inverse()???
+
+ // Renumber etree in postorder
+ IndexVector iwork(n);
+ IndexVector et_save(n+1);
+ for (i = 0; i < n; ++i)
+ {
+ iwork(post(i)) = post(et(i));
+ }
+ et_save = et; // Save the original etree
+ et = iwork;
+
+ // compute the number of descendants of each node in the etree
+ relax_end.setConstant(IND_EMPTY);
+ int j, parent;
+ descendants.setZero();
+ for (j = 0; j < n; j++)
+ {
+ parent = et(j);
+ if (parent != n) // not the dummy root
+ descendants(parent) += descendants(j) + 1;
+ }
+ // Identify the relaxed supernodes by postorder traversal of the etree
+ int snode_start; // beginning of a snode
+ int k;
+ int nsuper_et_post = 0; // Number of relaxed snodes in postordered etree
+ int nsuper_et = 0; // Number of relaxed snodes in the original etree
+ int l;
+ for (j = 0; j < n; )
+ {
+ parent = et(j);
+ snode_start = j;
+ while ( parent != n && descendants(parent) < relax_columns )
+ {
+ j = parent;
+ parent = et(j);
+ }
+ // Found a supernode in postordered etree, j is the last column
+ ++nsuper_et_post;
+ k = n;
+ for (i = snode_start; i <= j; ++i)
+ k = (std::min)(k, inv_post(i));
+ l = inv_post(j);
+ if ( (l - k) == (j - snode_start) ) // Same number of columns in the snode
+ {
+ // This is also a supernode in the original etree
+ relax_end(k) = l; // Record last column
+ ++nsuper_et;
+ }
+ else
+ {
+ for (i = snode_start; i <= j; ++i)
+ {
+ l = inv_post(i);
+ if (descendants(i) == 0)
+ {
+ relax_end(l) = l;
+ ++nsuper_et;
+ }
+ }
+ }
+ j++;
+ // Search for a new leaf
+ while (descendants(j) != 0 && j < n) j++;
+ } // End postorder traversal of the etree
+
+ // Recover the original etree
+ et = et_save;
+}
+#endif
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_kernel_bmod.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_kernel_bmod.h
new file mode 100644
index 000000000..b15ff9c50
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_kernel_bmod.h
@@ -0,0 +1,109 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+// Copyright (C) 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/.
+
+#ifndef SPARSELU_KERNEL_BMOD_H
+#define SPARSELU_KERNEL_BMOD_H
+
+/**
+ * \brief Performs numeric block updates from a given supernode to a single column
+ *
+ * \param segsize Size of the segment (and blocks ) to use for updates
+ * \param [in,out]dense Packed values of the original matrix
+ * \param tempv temporary vector to use for updates
+ * \param lusup array containing the supernodes
+ * \param nsupr Number of rows in the supernode
+ * \param nrow Number of rows in the rectangular part of the supernode
+ * \param lsub compressed row subscripts of supernodes
+ * \param lptr pointer to the first column of the current supernode in lsub
+ * \param no_zeros Number of nonzeros elements before the diagonal part of the supernode
+ * \return 0 on success
+ */
+template <int SegSizeAtCompileTime> struct LU_kernel_bmod
+{
+ template <typename BlockScalarVector, typename ScalarVector, typename IndexVector>
+ EIGEN_DONT_INLINE static void run(const int segsize, BlockScalarVector& dense, ScalarVector& tempv, ScalarVector& lusup, int& luptr, const int nsupr, const int nrow, IndexVector& lsub, const int lptr, const int no_zeros)
+ {
+ typedef typename ScalarVector::Scalar Scalar;
+ // First, copy U[*,j] segment from dense(*) to tempv(*)
+ // The result of triangular solve is in tempv[*];
+ // The result of matric-vector update is in dense[*]
+ int isub = lptr + no_zeros;
+ int i, irow;
+ for (i = 0; i < ((SegSizeAtCompileTime==Dynamic)?segsize:SegSizeAtCompileTime); i++)
+ {
+ irow = lsub(isub);
+ tempv(i) = dense(irow);
+ ++isub;
+ }
+ // Dense triangular solve -- start effective triangle
+ luptr += nsupr * no_zeros + no_zeros;
+ // Form Eigen matrix and vector
+ Map<Matrix<Scalar,SegSizeAtCompileTime,SegSizeAtCompileTime>, 0, OuterStride<> > A( &(lusup.data()[luptr]), segsize, segsize, OuterStride<>(nsupr) );
+ Map<Matrix<Scalar,SegSizeAtCompileTime,1> > u(tempv.data(), segsize);
+
+ u = A.template triangularView<UnitLower>().solve(u);
+
+ // Dense matrix-vector product y <-- B*x
+ luptr += segsize;
+ Map<Matrix<Scalar,Dynamic,SegSizeAtCompileTime>, 0, OuterStride<> > B( &(lusup.data()[luptr]), nrow, segsize, OuterStride<>(nsupr) );
+ Map<Matrix<Scalar,Dynamic,1> > l(tempv.data()+segsize, nrow);
+ if(SegSizeAtCompileTime==2)
+ l = u(0) * B.col(0) + u(1) * B.col(1);
+ else if(SegSizeAtCompileTime==3)
+ l = u(0) * B.col(0) + u(1) * B.col(1) + u(2) * B.col(2);
+ else
+ l.noalias() = B * u;
+
+ // Scatter tempv[] into SPA dense[] as a temporary storage
+ isub = lptr + no_zeros;
+ for (i = 0; i < ((SegSizeAtCompileTime==Dynamic)?segsize:SegSizeAtCompileTime); i++)
+ {
+ irow = lsub(isub++);
+ dense(irow) = tempv(i);
+ }
+
+ // Scatter l into SPA dense[]
+ for (i = 0; i < nrow; i++)
+ {
+ irow = lsub(isub++);
+ dense(irow) -= l(i);
+ }
+ }
+};
+
+template <> struct LU_kernel_bmod<1>
+{
+ template <typename BlockScalarVector, typename ScalarVector, typename IndexVector>
+ EIGEN_DONT_INLINE static void run(const int /*segsize*/, BlockScalarVector& dense, ScalarVector& /*tempv*/, ScalarVector& lusup, int& luptr, const int nsupr, const int nrow, IndexVector& lsub, const int lptr, const int no_zeros)
+ {
+ typedef typename ScalarVector::Scalar Scalar;
+ Scalar f = dense(lsub(lptr + no_zeros));
+ luptr += nsupr * no_zeros + no_zeros + 1;
+ const Scalar* a(lusup.data() + luptr);
+ const typename IndexVector::Scalar* irow(lsub.data()+lptr + no_zeros + 1);
+ int i = 0;
+ for (; i+1 < nrow; i+=2)
+ {
+ int i0 = *(irow++);
+ int i1 = *(irow++);
+ Scalar a0 = *(a++);
+ Scalar a1 = *(a++);
+ Scalar d0 = dense.coeff(i0);
+ Scalar d1 = dense.coeff(i1);
+ d0 -= f*a0;
+ d1 -= f*a1;
+ dense.coeffRef(i0) = d0;
+ dense.coeffRef(i1) = d1;
+ }
+ if(i<nrow)
+ dense.coeffRef(*(irow++)) -= f * *(a++);
+ }
+};
+#endif
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_panel_bmod.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_panel_bmod.h
new file mode 100644
index 000000000..6688b4e3e
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_panel_bmod.h
@@ -0,0 +1,204 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+// Copyright (C) 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: This file is the modified version of [s,d,c,z]panel_bmod.c file in SuperLU
+
+ * -- SuperLU routine (version 3.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * October 15, 2003
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_PANEL_BMOD_H
+#define SPARSELU_PANEL_BMOD_H
+/**
+ * \brief Performs numeric block updates (sup-panel) in topological order.
+ *
+ * Before entering this routine, the original nonzeros in the panel
+ * were already copied i nto the spa[m,w]
+ *
+ * \param m number of rows in the matrix
+ * \param w Panel size
+ * \param jcol Starting column of the panel
+ * \param nseg Number of segments in the U part
+ * \param dense Store the full representation of the panel
+ * \param tempv working array
+ * \param segrep segment representative... first row in the segment
+ * \param repfnz First nonzero rows
+ * \param glu Global LU data.
+ *
+ *
+ */
+template <typename Scalar, typename Index>
+void SparseLUBase<Scalar,Index>::LU_panel_bmod(const int m, const int w, const int jcol, const int nseg, ScalarVector& dense, ScalarVector& tempv, IndexVector& segrep, IndexVector& repfnz, LU_perfvalues& perfv, GlobalLU_t& glu)
+{
+
+ int ksub,jj,nextl_col;
+ int fsupc, nsupc, nsupr, nrow;
+ int krep, kfnz;
+ int lptr; // points to the row subscripts of a supernode
+ int luptr; // ...
+ int segsize,no_zeros ;
+ // For each nonz supernode segment of U[*,j] in topological order
+ int k = nseg - 1;
+ for (ksub = 0; ksub < nseg; ksub++)
+ { // For each updating supernode
+
+ /* krep = representative of current k-th supernode
+ * fsupc = first supernodal column
+ * nsupc = number of columns in a supernode
+ * nsupr = number of rows in a supernode
+ */
+ krep = segrep(k); k--;
+ fsupc = glu.xsup(glu.supno(krep));
+ nsupc = krep - fsupc + 1;
+ nsupr = glu.xlsub(fsupc+1) - glu.xlsub(fsupc);
+ nrow = nsupr - nsupc;
+ lptr = glu.xlsub(fsupc);
+
+ // loop over the panel columns to detect the actual number of columns and rows
+ int u_rows = 0;
+ int u_cols = 0;
+ for (jj = jcol; jj < jcol + w; jj++)
+ {
+ nextl_col = (jj-jcol) * m;
+ VectorBlock<IndexVector> repfnz_col(repfnz, nextl_col, m); // First nonzero column index for each row
+
+ kfnz = repfnz_col(krep);
+ if ( kfnz == IND_EMPTY )
+ continue; // skip any zero segment
+
+ segsize = krep - kfnz + 1;
+ u_cols++;
+ u_rows = (std::max)(segsize,u_rows);
+ }
+
+ // if the blocks are large enough, use level 3
+ // TODO find better heuristics!
+ if( nsupc >= perfv.colblk && nrow > perfv.rowblk && u_cols>perfv.relax)
+ {
+ Map<Matrix<Scalar,Dynamic,Dynamic> > U(tempv.data(), u_rows, u_cols);
+
+ // gather U
+ int u_col = 0;
+ for (jj = jcol; jj < jcol + w; jj++)
+ {
+ nextl_col = (jj-jcol) * m;
+ VectorBlock<IndexVector> repfnz_col(repfnz, nextl_col, m); // First nonzero column index for each row
+ VectorBlock<ScalarVector> dense_col(dense, nextl_col, m); // Scatter/gather entire matrix column from/to here
+
+ kfnz = repfnz_col(krep);
+ if ( kfnz == IND_EMPTY )
+ continue; // skip any zero segment
+
+ segsize = krep - kfnz + 1;
+ luptr = glu.xlusup(fsupc);
+ no_zeros = kfnz - fsupc;
+
+ int isub = lptr + no_zeros;
+ int off = u_rows-segsize;
+ for (int i = 0; i < off; i++) U(i,u_col) = 0;
+ for (int i = 0; i < segsize; i++)
+ {
+ int irow = glu.lsub(isub);
+ U(i+off,u_col) = dense_col(irow);
+ ++isub;
+ }
+ u_col++;
+ }
+ // solve U = A^-1 U
+ luptr = glu.xlusup(fsupc);
+ no_zeros = (krep - u_rows + 1) - fsupc;
+ luptr += nsupr * no_zeros + no_zeros;
+ Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A(glu.lusup.data()+luptr, u_rows, u_rows, OuterStride<>(nsupr) );
+ U = A.template triangularView<UnitLower>().solve(U);
+
+ // update
+ luptr += u_rows;
+ Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > B(glu.lusup.data()+luptr, nrow, u_rows, OuterStride<>(nsupr) );
+ assert(tempv.size()>w*u_rows + nrow*w);
+ Map<Matrix<Scalar,Dynamic,Dynamic> > L(tempv.data()+w*u_rows, nrow, u_cols);
+ L.noalias() = B * U;
+
+ // scatter U and L
+ u_col = 0;
+ for (jj = jcol; jj < jcol + w; jj++)
+ {
+ nextl_col = (jj-jcol) * m;
+ VectorBlock<IndexVector> repfnz_col(repfnz, nextl_col, m); // First nonzero column index for each row
+ VectorBlock<ScalarVector> dense_col(dense, nextl_col, m); // Scatter/gather entire matrix column from/to here
+
+ kfnz = repfnz_col(krep);
+ if ( kfnz == IND_EMPTY )
+ continue; // skip any zero segment
+
+ segsize = krep - kfnz + 1;
+ no_zeros = kfnz - fsupc;
+ int isub = lptr + no_zeros;
+
+ int off = u_rows-segsize;
+ for (int i = 0; i < segsize; i++)
+ {
+ int irow = glu.lsub(isub++);
+ dense_col(irow) = U.coeff(i+off,u_col);
+ U.coeffRef(i+off,u_col) = 0;
+ }
+
+ // Scatter l into SPA dense[]
+ for (int i = 0; i < nrow; i++)
+ {
+ int irow = glu.lsub(isub++);
+ dense_col(irow) -= L.coeff(i,u_col);
+ L.coeffRef(i,u_col) = 0;
+ }
+ u_col++;
+ }
+ }
+ else // level 2 only
+ {
+ // Sequence through each column in the panel
+ for (jj = jcol; jj < jcol + w; jj++)
+ {
+ nextl_col = (jj-jcol) * m;
+ VectorBlock<IndexVector> repfnz_col(repfnz, nextl_col, m); // First nonzero column index for each row
+ VectorBlock<ScalarVector> dense_col(dense, nextl_col, m); // Scatter/gather entire matrix column from/to here
+
+ kfnz = repfnz_col(krep);
+ if ( kfnz == IND_EMPTY )
+ continue; // skip any zero segment
+
+ segsize = krep - kfnz + 1;
+ luptr = glu.xlusup(fsupc);
+
+ // Perform a trianglar solve and block update,
+ // then scatter the result of sup-col update to dense[]
+ no_zeros = kfnz - fsupc;
+ if(segsize==1) LU_kernel_bmod<1>::run(segsize, dense_col, tempv, glu.lusup, luptr, nsupr, nrow, glu.lsub, lptr, no_zeros);
+ else if(segsize==2) LU_kernel_bmod<2>::run(segsize, dense_col, tempv, glu.lusup, luptr, nsupr, nrow, glu.lsub, lptr, no_zeros);
+ else if(segsize==3) LU_kernel_bmod<3>::run(segsize, dense_col, tempv, glu.lusup, luptr, nsupr, nrow, glu.lsub, lptr, no_zeros);
+ else LU_kernel_bmod<Dynamic>::run(segsize, dense_col, tempv, glu.lusup, luptr, nsupr, nrow, glu.lsub, lptr, no_zeros);
+ } // End for each column in the panel
+ }
+
+ } // End for each updating supernode
+}
+#endif
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_panel_dfs.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_panel_dfs.h
new file mode 100644
index 000000000..5d3025388
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_panel_dfs.h
@@ -0,0 +1,247 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file is the modified version of [s,d,c,z]panel_dfs.c file in SuperLU
+
+ * -- SuperLU routine (version 2.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * November 15, 1997
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_PANEL_DFS_H
+#define SPARSELU_PANEL_DFS_H
+template <typename Scalar, typename Index>
+template <typename Traits>
+void SparseLUBase<Scalar,Index>::LU_dfs_kernel(const int jj, IndexVector& perm_r,
+ int& nseg, IndexVector& panel_lsub, IndexVector& segrep,
+ Ref<IndexVector> repfnz_col, IndexVector& xprune, Ref<IndexVector> marker, IndexVector& parent,
+ IndexVector& xplore, GlobalLU_t& glu,
+ int& nextl_col, int krow, Traits& traits
+ )
+{
+
+ int kmark = marker(krow);
+
+ // For each unmarked krow of jj
+ marker(krow) = jj;
+ int kperm = perm_r(krow);
+ if (kperm == IND_EMPTY ) {
+ // krow is in L : place it in structure of L(*, jj)
+ panel_lsub(nextl_col++) = krow; // krow is indexed into A
+
+ traits.mem_expand(panel_lsub, nextl_col, kmark);
+ }
+ else
+ {
+ // krow is in U : if its supernode-representative krep
+ // has been explored, update repfnz(*)
+ // krep = supernode representative of the current row
+ int krep = glu.xsup(glu.supno(kperm)+1) - 1;
+ // First nonzero element in the current column:
+ int myfnz = repfnz_col(krep);
+
+ if (myfnz != IND_EMPTY )
+ {
+ // Representative visited before
+ if (myfnz > kperm ) repfnz_col(krep) = kperm;
+
+ }
+ else
+ {
+ // Otherwise, perform dfs starting at krep
+ int oldrep = IND_EMPTY;
+ parent(krep) = oldrep;
+ repfnz_col(krep) = kperm;
+ int xdfs = glu.xlsub(krep);
+ int maxdfs = xprune(krep);
+
+ int kpar;
+ do
+ {
+ // For each unmarked kchild of krep
+ while (xdfs < maxdfs)
+ {
+ int kchild = glu.lsub(xdfs);
+ xdfs++;
+ int chmark = marker(kchild);
+
+ if (chmark != jj )
+ {
+ marker(kchild) = jj;
+ int chperm = perm_r(kchild);
+
+ if (chperm == IND_EMPTY)
+ {
+ // case kchild is in L: place it in L(*, j)
+ panel_lsub(nextl_col++) = kchild;
+ traits.mem_expand(panel_lsub, nextl_col, chmark);
+ }
+ else
+ {
+ // case kchild is in U :
+ // chrep = its supernode-rep. If its rep has been explored,
+ // update its repfnz(*)
+ int chrep = glu.xsup(glu.supno(chperm)+1) - 1;
+ myfnz = repfnz_col(chrep);
+
+ if (myfnz != IND_EMPTY)
+ { // Visited before
+ if (myfnz > chperm)
+ repfnz_col(chrep) = chperm;
+ }
+ else
+ { // Cont. dfs at snode-rep of kchild
+ xplore(krep) = xdfs;
+ oldrep = krep;
+ krep = chrep; // Go deeper down G(L)
+ parent(krep) = oldrep;
+ repfnz_col(krep) = chperm;
+ xdfs = glu.xlsub(krep);
+ maxdfs = xprune(krep);
+
+ } // end if myfnz != -1
+ } // end if chperm == -1
+
+ } // end if chmark !=jj
+ } // end while xdfs < maxdfs
+
+ // krow has no more unexplored nbrs :
+ // Place snode-rep krep in postorder DFS, if this
+ // segment is seen for the first time. (Note that
+ // "repfnz(krep)" may change later.)
+ // Baktrack dfs to its parent
+ if(traits.update_segrep(krep,jj))
+ //if (marker1(krep) < jcol )
+ {
+ segrep(nseg) = krep;
+ ++nseg;
+ //marker1(krep) = jj;
+ }
+
+ kpar = parent(krep); // Pop recursion, mimic recursion
+ if (kpar == IND_EMPTY)
+ break; // dfs done
+ krep = kpar;
+ xdfs = xplore(krep);
+ maxdfs = xprune(krep);
+
+ } while (kpar != IND_EMPTY); // Do until empty stack
+
+ } // end if (myfnz = -1)
+
+ } // end if (kperm == -1)
+}
+
+/**
+ * \brief Performs a symbolic factorization on a panel of columns [jcol, jcol+w)
+ *
+ * A supernode representative is the last column of a supernode.
+ * The nonzeros in U[*,j] are segments that end at supernodes representatives
+ *
+ * The routine returns a list of the supernodal representatives
+ * in topological order of the dfs that generates them. This list is
+ * a superset of the topological order of each individual column within
+ * the panel.
+ * The location of the first nonzero in each supernodal segment
+ * (supernodal entry location) is also returned. Each column has
+ * a separate list for this purpose.
+ *
+ * Two markers arrays are used for dfs :
+ * marker[i] == jj, if i was visited during dfs of current column jj;
+ * marker1[i] >= jcol, if i was visited by earlier columns in this panel;
+ *
+ * \param [in]m number of rows in the matrix
+ * \param [in]w Panel size
+ * \param [in]jcol Starting column of the panel
+ * \param [in]A Input matrix in column-major storage
+ * \param [in]perm_r Row permutation
+ * \param [out]nseg Number of U segments
+ * \param [out]dense Accumulate the column vectors of the panel
+ * \param [out]panel_lsub Subscripts of the row in the panel
+ * \param [out]segrep Segment representative i.e first nonzero row of each segment
+ * \param [out]repfnz First nonzero location in each row
+ * \param [out]xprune
+ * \param [out]marker
+ *
+ *
+ */
+
+template<typename IndexVector>
+struct LU_panel_dfs_traits
+{
+ typedef typename IndexVector::Scalar Index;
+ LU_panel_dfs_traits(Index jcol, Index* marker)
+ : m_jcol(jcol), m_marker(marker)
+ {}
+ bool update_segrep(Index krep, Index jj)
+ {
+ if(m_marker[krep]<m_jcol)
+ {
+ m_marker[krep] = jj;
+ return true;
+ }
+ return false;
+ }
+ void mem_expand(IndexVector& /*glu.lsub*/, int /*nextl*/, int /*chmark*/) {}
+ enum { ExpandMem = false };
+ Index m_jcol;
+ Index* m_marker;
+};
+
+template <typename Scalar, typename Index>
+void SparseLUBase<Scalar,Index>::LU_panel_dfs(const int m, const int w, const int jcol, MatrixType& A, IndexVector& perm_r, int& nseg, ScalarVector& dense, IndexVector& panel_lsub, IndexVector& segrep, IndexVector& repfnz, IndexVector& xprune, IndexVector& marker, IndexVector& parent, IndexVector& xplore, GlobalLU_t& glu)
+{
+ int nextl_col; // Next available position in panel_lsub[*,jj]
+
+ // Initialize pointers
+ VectorBlock<IndexVector> marker1(marker, m, m);
+ nseg = 0;
+
+ LU_panel_dfs_traits<IndexVector> traits(jcol, marker1.data());
+
+ // For each column in the panel
+ for (int jj = jcol; jj < jcol + w; jj++)
+ {
+ nextl_col = (jj - jcol) * m;
+
+ VectorBlock<IndexVector> repfnz_col(repfnz, nextl_col, m); // First nonzero location in each row
+ VectorBlock<ScalarVector> dense_col(dense,nextl_col, m); // Accumulate a column vector here
+
+
+ // For each nnz in A[*, jj] do depth first search
+ for (typename MatrixType::InnerIterator it(A, jj); it; ++it)
+ {
+ int krow = it.row();
+ dense_col(krow) = it.value();
+
+ int kmark = marker(krow);
+ if (kmark == jj)
+ continue; // krow visited before, go to the next nonzero
+
+ LU_dfs_kernel(jj, perm_r, nseg, panel_lsub, segrep, repfnz_col, xprune, marker, parent,
+ xplore, glu, nextl_col, krow, traits);
+ }// end for nonzeros in column jj
+
+ } // end for column jj
+
+}
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_pivotL.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_pivotL.h
new file mode 100644
index 000000000..c4a9f1c74
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_pivotL.h
@@ -0,0 +1,125 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file is the modified version of xpivotL.c file in SuperLU
+
+ * -- SuperLU routine (version 3.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * October 15, 2003
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_PIVOTL_H
+#define SPARSELU_PIVOTL_H
+/**
+ * \brief Performs the numerical pivotin on the current column of L, and the CDIV operation.
+ *
+ * Pivot policy :
+ * (1) Compute thresh = u * max_(i>=j) abs(A_ij);
+ * (2) IF user specifies pivot row k and abs(A_kj) >= thresh THEN
+ * pivot row = k;
+ * ELSE IF abs(A_jj) >= thresh THEN
+ * pivot row = j;
+ * ELSE
+ * pivot row = m;
+ *
+ * Note: If you absolutely want to use a given pivot order, then set u=0.0.
+ *
+ * \param jcol The current column of L
+ * \param u diagonal pivoting threshold
+ * \param [in,out]perm_r Row permutation (threshold pivoting)
+ * \param [in] iperm_c column permutation - used to finf diagonal of Pc*A*Pc'
+ * \param [out]pivrow The pivot row
+ * \param glu Global LU data
+ * \return 0 if success, i > 0 if U(i,i) is exactly zero
+ *
+ */
+template <typename Scalar, typename Index>
+int SparseLUBase<Scalar,Index>::LU_pivotL(const int jcol, const RealScalar diagpivotthresh, IndexVector& perm_r, IndexVector& iperm_c, int& pivrow, GlobalLU_t& glu)
+{
+
+ Index fsupc = (glu.xsup)((glu.supno)(jcol)); // First column in the supernode containing the column jcol
+ Index nsupc = jcol - fsupc; // Number of columns in the supernode portion, excluding jcol; nsupc >=0
+ Index lptr = glu.xlsub(fsupc); // pointer to the starting location of the row subscripts for this supernode portion
+ Index nsupr = glu.xlsub(fsupc+1) - lptr; // Number of rows in the supernode
+ Scalar* lu_sup_ptr = &(glu.lusup.data()[glu.xlusup(fsupc)]); // Start of the current supernode
+ Scalar* lu_col_ptr = &(glu.lusup.data()[glu.xlusup(jcol)]); // Start of jcol in the supernode
+ Index* lsub_ptr = &(glu.lsub.data()[lptr]); // Start of row indices of the supernode
+
+ // Determine the largest abs numerical value for partial pivoting
+ Index diagind = iperm_c(jcol); // diagonal index
+ RealScalar pivmax = 0.0;
+ Index pivptr = nsupc;
+ Index diag = IND_EMPTY;
+ RealScalar rtemp;
+ Index isub, icol, itemp, k;
+ for (isub = nsupc; isub < nsupr; ++isub) {
+ rtemp = std::abs(lu_col_ptr[isub]);
+ if (rtemp > pivmax) {
+ pivmax = rtemp;
+ pivptr = isub;
+ }
+ if (lsub_ptr[isub] == diagind) diag = isub;
+ }
+
+ // Test for singularity
+ if ( pivmax == 0.0 ) {
+ pivrow = lsub_ptr[pivptr];
+ perm_r(pivrow) = jcol;
+ return (jcol+1);
+ }
+
+ RealScalar thresh = diagpivotthresh * pivmax;
+
+ // Choose appropriate pivotal element
+
+ {
+ // Test if the diagonal element can be used as a pivot (given the threshold value)
+ if (diag >= 0 )
+ {
+ // Diagonal element exists
+ rtemp = std::abs(lu_col_ptr[diag]);
+ if (rtemp != 0.0 && rtemp >= thresh) pivptr = diag;
+ }
+ pivrow = lsub_ptr[pivptr];
+ }
+
+ // Record pivot row
+ perm_r(pivrow) = jcol;
+ // Interchange row subscripts
+ if (pivptr != nsupc )
+ {
+ std::swap( lsub_ptr[pivptr], lsub_ptr[nsupc] );
+ // Interchange numerical values as well, for the two rows in the whole snode
+ // such that L is indexed the same way as A
+ for (icol = 0; icol <= nsupc; icol++)
+ {
+ itemp = pivptr + icol * nsupr;
+ std::swap(lu_sup_ptr[itemp], lu_sup_ptr[nsupc + icol * nsupr]);
+ }
+ }
+ // cdiv operations
+ Scalar temp = Scalar(1.0) / lu_col_ptr[nsupc];
+ for (k = nsupc+1; k < nsupr; k++)
+ lu_col_ptr[k] *= temp;
+ return 0;
+}
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_pruneL.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_pruneL.h
new file mode 100644
index 000000000..d8c58e039
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_pruneL.h
@@ -0,0 +1,129 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file is the modified version of [s,d,c,z]pruneL.c file in SuperLU
+
+ * -- SuperLU routine (version 2.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * November 15, 1997
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_PRUNEL_H
+#define SPARSELU_PRUNEL_H
+
+/**
+ * \brief Prunes the L-structure.
+ *
+ * It prunes the L-structure of supernodes whose L-structure contains the current pivot row "pivrow"
+ *
+ *
+ * \param jcol The current column of L
+ * \param [in]perm_r Row permutation
+ * \param [out]pivrow The pivot row
+ * \param nseg Number of segments
+ * \param segrep
+ * \param repfnz
+ * \param [out]xprune
+ * \param glu Global LU data
+ *
+ */
+template <typename Scalar, typename Index>
+void SparseLUBase<Scalar,Index>::LU_pruneL(const int jcol, const IndexVector& perm_r, const int pivrow, const int nseg, const IndexVector& segrep, BlockIndexVector& repfnz, IndexVector& xprune, GlobalLU_t& glu)
+{
+ // For each supernode-rep irep in U(*,j]
+ int jsupno = glu.supno(jcol);
+ int i,irep,irep1;
+ bool movnum, do_prune = false;
+ Index kmin, kmax, minloc, maxloc,krow;
+ for (i = 0; i < nseg; i++)
+ {
+ irep = segrep(i);
+ irep1 = irep + 1;
+ do_prune = false;
+
+ // Don't prune with a zero U-segment
+ if (repfnz(irep) == IND_EMPTY) continue;
+
+ // If a snode overlaps with the next panel, then the U-segment
+ // is fragmented into two parts -- irep and irep1. We should let
+ // pruning occur at the rep-column in irep1s snode.
+ if (glu.supno(irep) == glu.supno(irep1) ) continue; // don't prune
+
+ // If it has not been pruned & it has a nonz in row L(pivrow,i)
+ if (glu.supno(irep) != jsupno )
+ {
+ if ( xprune (irep) >= glu.xlsub(irep1) )
+ {
+ kmin = glu.xlsub(irep);
+ kmax = glu.xlsub(irep1) - 1;
+ for (krow = kmin; krow <= kmax; krow++)
+ {
+ if (glu.lsub(krow) == pivrow)
+ {
+ do_prune = true;
+ break;
+ }
+ }
+ }
+
+ if (do_prune)
+ {
+ // do a quicksort-type partition
+ // movnum=true means that the num values have to be exchanged
+ movnum = false;
+ if (irep == glu.xsup(glu.supno(irep)) ) // Snode of size 1
+ movnum = true;
+
+ while (kmin <= kmax)
+ {
+ if (perm_r(glu.lsub(kmax)) == IND_EMPTY)
+ kmax--;
+ else if ( perm_r(glu.lsub(kmin)) != IND_EMPTY)
+ kmin++;
+ else
+ {
+ // kmin below pivrow (not yet pivoted), and kmax
+ // above pivrow: interchange the two suscripts
+ std::swap(glu.lsub(kmin), glu.lsub(kmax));
+
+ // If the supernode has only one column, then we
+ // only keep one set of subscripts. For any subscript
+ // intercnahge performed, similar interchange must be
+ // done on the numerical values.
+ if (movnum)
+ {
+ minloc = glu.xlusup(irep) + ( kmin - glu.xlsub(irep) );
+ maxloc = glu.xlusup(irep) + ( kmax - glu.xlsub(irep) );
+ std::swap(glu.lusup(minloc), glu.lusup(maxloc));
+ }
+ kmin++;
+ kmax--;
+ }
+ } // end while
+
+ xprune(irep) = kmin; //Pruning
+ } // end if do_prune
+ } // end pruning
+ } // End for each U-segment
+}
+
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_relax_snode.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_relax_snode.h
new file mode 100644
index 000000000..8db8619c1
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_relax_snode.h
@@ -0,0 +1,73 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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/.
+
+/* This file is a modified version of heap_relax_snode.c file in SuperLU
+ * -- SuperLU routine (version 3.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * October 15, 2003
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+
+#ifndef SPARSELU_RELAX_SNODE_H
+#define SPARSELU_RELAX_SNODE_H
+/**
+ * \brief Identify the initial relaxed supernodes
+ *
+ * This routine is applied to a column elimination tree.
+ * It assumes that the matrix has been reordered according to the postorder of the etree
+ * \param et elimination tree
+ * \param relax_columns Maximum number of columns allowed in a relaxed snode
+ * \param descendants Number of descendants of each node in the etree
+ * \param relax_end last column in a supernode
+ */
+template <typename Scalar, typename Index>
+void SparseLUBase<Scalar,Index>::LU_relax_snode (const int n, IndexVector& et, const int relax_columns, IndexVector& descendants, IndexVector& relax_end)
+{
+
+ // compute the number of descendants of each node in the etree
+ int j, parent;
+ relax_end.setConstant(IND_EMPTY);
+ descendants.setZero();
+ for (j = 0; j < n; j++)
+ {
+ parent = et(j);
+ if (parent != n) // not the dummy root
+ descendants(parent) += descendants(j) + 1;
+ }
+ // Identify the relaxed supernodes by postorder traversal of the etree
+ int snode_start; // beginning of a snode
+ for (j = 0; j < n; )
+ {
+ parent = et(j);
+ snode_start = j;
+ while ( parent != n && descendants(parent) < relax_columns )
+ {
+ j = parent;
+ parent = et(j);
+ }
+ // Found a supernode in postordered etree, j is the last column
+ relax_end(snode_start) = j; // Record last column
+ j++;
+ // Search for a new leaf
+ while (descendants(j) != 0 && j < n) j++;
+ } // End postorder traversal of the etree
+
+}
+#endif
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_snode_bmod.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_snode_bmod.h
new file mode 100644
index 000000000..beea71e31
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_snode_bmod.h
@@ -0,0 +1,72 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file is the modified version of [s,d,c,z]snode_bmod.c file in SuperLU
+
+ * -- SuperLU routine (version 3.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * October 15, 2003
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_SNODE_BMOD_H
+#define SPARSELU_SNODE_BMOD_H
+template <typename Scalar, typename Index>
+int SparseLUBase<Scalar,Index>::LU_snode_bmod (const int jcol, const int fsupc, ScalarVector& dense, GlobalLU_t& glu)
+{
+ /* lsub : Compressed row subscripts of ( rectangular supernodes )
+ * xlsub : xlsub[j] is the starting location of the j-th column in lsub(*)
+ * lusup : Numerical values of the rectangular supernodes
+ * xlusup[j] is the starting location of the j-th column in lusup(*)
+ */
+ int nextlu = glu.xlusup(jcol); // Starting location of the next column to add
+ int irow, isub;
+ // Process the supernodal portion of L\U[*,jcol]
+ for (isub = glu.xlsub(fsupc); isub < glu.xlsub(fsupc+1); isub++)
+ {
+ irow = glu.lsub(isub);
+ glu.lusup(nextlu) = dense(irow);
+ dense(irow) = 0;
+ ++nextlu;
+ }
+ glu.xlusup(jcol + 1) = nextlu; // Initialize xlusup for next column ( jcol+1 )
+
+ if (fsupc < jcol ){
+ int luptr = glu.xlusup(fsupc); // points to the first column of the supernode
+ int nsupr = glu.xlsub(fsupc + 1) -glu.xlsub(fsupc); //Number of rows in the supernode
+ int nsupc = jcol - fsupc; // Number of columns in the supernodal portion of L\U[*,jcol]
+ int ufirst = glu.xlusup(jcol); // points to the beginning of column jcol in supernode L\U(jsupno)
+
+ int nrow = nsupr - nsupc; // Number of rows in the off-diagonal blocks
+
+ // Solve the triangular system for U(fsupc:jcol, jcol) with L(fspuc:jcol, fsupc:jcol)
+ Map<Matrix<Scalar,Dynamic,Dynamic>,0,OuterStride<> > A( &(glu.lusup.data()[luptr]), nsupc, nsupc, OuterStride<>(nsupr) );
+ VectorBlock<ScalarVector> u(glu.lusup, ufirst, nsupc);
+ u = A.template triangularView<UnitLower>().solve(u); // Call the Eigen dense triangular solve interface
+
+ // Update the trailing part of the column jcol U(jcol:jcol+nrow, jcol) using L(jcol:jcol+nrow, fsupc:jcol) and U(fsupc:jcol)
+ new (&A) Map<Matrix<Scalar,Dynamic,Dynamic>,0,OuterStride<> > ( &(glu.lusup.data()[luptr+nsupc]), nrow, nsupc, OuterStride<>(nsupr) );
+ VectorBlock<ScalarVector> l(glu.lusup, ufirst+nsupc, nrow);
+ l.noalias() -= A * u;
+ }
+ return 0;
+}
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_snode_dfs.h b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_snode_dfs.h
new file mode 100644
index 000000000..199436cd7
--- /dev/null
+++ b/resources/3rdparty/eigen/Eigen/src/SparseLU/SparseLU_snode_dfs.h
@@ -0,0 +1,95 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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: This file is the modified version of [s,d,c,z]snode_dfs.c file in SuperLU
+
+ * -- SuperLU routine (version 2.0) --
+ * Univ. of California Berkeley, Xerox Palo Alto Research Center,
+ * and Lawrence Berkeley National Lab.
+ * November 15, 1997
+ *
+ * Copyright (c) 1994 by Xerox Corporation. All rights reserved.
+ *
+ * THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+ * EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK.
+ *
+ * Permission is hereby granted to use or copy this program for any
+ * purpose, provided the above notices are retained on all copies.
+ * Permission to modify the code and to distribute modified code is
+ * granted, provided the above notices are retained, and a notice that
+ * the code was modified is included with the above copyright notice.
+ */
+#ifndef SPARSELU_SNODE_DFS_H
+#define SPARSELU_SNODE_DFS_H
+ /**
+ * \brief Determine the union of the row structures of those columns within the relaxed snode.
+ * NOTE: The relaxed snodes are leaves of the supernodal etree, therefore,
+ * the portion outside the rectangular supernode must be zero.
+ *
+ * \param jcol start of the supernode
+ * \param kcol end of the supernode
+ * \param asub Row indices
+ * \param colptr Pointer to the beginning of each column
+ * \param xprune (out) The pruned tree ??
+ * \param marker (in/out) working vector
+ * \return 0 on success, > 0 size of the memory when memory allocation failed
+ */
+template <typename Scalar, typename Index>
+int SparseLUBase<Scalar,Index>::LU_snode_dfs(const int jcol, const int kcol,const MatrixType& mat, IndexVector& xprune, IndexVector& marker, GlobalLU_t& glu)
+{
+ int mem;
+ Index nsuper = ++glu.supno(jcol); // Next available supernode number
+ int nextl = glu.xlsub(jcol); //Index of the starting location of the jcol-th column in lsub
+ int krow,kmark;
+ for (int i = jcol; i <=kcol; i++)
+ {
+ // For each nonzero in A(*,i)
+ for (typename MatrixType::InnerIterator it(mat, i); it; ++it)
+ {
+ krow = it.row();
+ kmark = marker(krow);
+ if ( kmark != kcol )
+ {
+ // First time to visit krow
+ marker(krow) = kcol;
+ glu.lsub(nextl++) = krow;
+ if( nextl >= glu.nzlmax )
+ {
+ mem = LUMemXpand<IndexVector>(glu.lsub, glu.nzlmax, nextl, LSUB, glu.num_expansions);
+ if (mem) return mem; // Memory expansion failed... Return the memory allocated so far
+ }
+ }
+ }
+ glu.supno(i) = nsuper;
+ }
+
+ // If supernode > 1, then make a copy of the subscripts for pruning
+ if (jcol < kcol)
+ {
+ Index new_next = nextl + (nextl - glu.xlsub(jcol));
+ while (new_next > glu.nzlmax)
+ {
+ mem = LUMemXpand<IndexVector>(glu.lsub, glu.nzlmax, nextl, LSUB, glu.num_expansions);
+ if (mem) return mem; // Memory expansion failed... Return the memory allocated so far
+ }
+ Index ifrom, ito = nextl;
+ for (ifrom = glu.xlsub(jcol); ifrom < nextl;)
+ glu.lsub(ito++) = glu.lsub(ifrom++);
+ for (int i = jcol+1; i <=kcol; i++) glu.xlsub(i) = nextl;
+ nextl = ito;
+ }
+ glu.xsup(nsuper+1) = kcol + 1; // Start of next available supernode
+ glu.supno(kcol+1) = nsuper;
+ xprune(kcol) = nextl;
+ glu.xlsub(kcol+1) = nextl;
+ return 0;
+}
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h b/resources/3rdparty/eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h
index 11fb014dd..cd6c4b91f 100644
--- a/resources/3rdparty/eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h
+++ b/resources/3rdparty/eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h
@@ -496,8 +496,8 @@ class SuperLU : public SuperLUBase<_MatrixType,SuperLU<_MatrixType> >
SuperLU(const MatrixType& matrix) : Base()
{
- Base::init();
- compute(matrix);
+ init();
+ Base::compute(matrix);
}
~SuperLU()
@@ -612,6 +612,7 @@ void SuperLU<MatrixType>::factorize(const MatrixType& a)
this->initFactorization(a);
+ m_sluOptions.ColPerm = COLAMD;
int info = 0;
RealScalar recip_pivot_growth, rcond;
RealScalar ferr, berr;
@@ -833,7 +834,7 @@ class SuperILU : public SuperLUBase<_MatrixType,SuperILU<_MatrixType> >
SuperILU(const MatrixType& matrix) : Base()
{
init();
- compute(matrix);
+ Base::compute(matrix);
}
~SuperILU()
diff --git a/resources/3rdparty/eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h b/resources/3rdparty/eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h
index 5b979ebf8..1e751ad62 100644
--- a/resources/3rdparty/eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h
+++ b/resources/3rdparty/eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h
@@ -33,7 +33,8 @@ EIGEN_MAKE_CWISE_BINARY_OP(min,internal::scalar_min_op)
*
* \sa max()
*/
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const ConstantReturnType>
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived,
+ const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> >
(min)(const Scalar &other) const
{
return (min)(Derived::PlainObject::Constant(rows(), cols(), other));
@@ -52,7 +53,8 @@ EIGEN_MAKE_CWISE_BINARY_OP(max,internal::scalar_max_op)
*
* \sa min()
*/
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const ConstantReturnType>
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived,
+ const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> >
(max)(const Scalar &other) const
{
return (max)(Derived::PlainObject::Constant(rows(), cols(), other));
diff --git a/resources/3rdparty/eigen/Eigen/src/plugins/ArrayCwiseUnaryOps.h b/resources/3rdparty/eigen/Eigen/src/plugins/ArrayCwiseUnaryOps.h
index 0dffaf413..a59636790 100644
--- a/resources/3rdparty/eigen/Eigen/src/plugins/ArrayCwiseUnaryOps.h
+++ b/resources/3rdparty/eigen/Eigen/src/plugins/ArrayCwiseUnaryOps.h
@@ -200,3 +200,4 @@ EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator<=, std::less_equal)
EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator>, std::greater)
EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator>=, std::greater_equal)
+
diff --git a/resources/3rdparty/eigen/bench/bench_gemm.cpp b/resources/3rdparty/eigen/bench/bench_gemm.cpp
index 98ac34e20..41ca8b3b6 100644
--- a/resources/3rdparty/eigen/bench/bench_gemm.cpp
+++ b/resources/3rdparty/eigen/bench/bench_gemm.cpp
@@ -24,7 +24,7 @@ typedef Matrix<RealScalar,Dynamic,Dynamic> M;
#ifdef HAVE_BLAS
extern "C" {
- #include <bench/btl/libs/C_BLAS/blas.h>
+ #include <Eigen/src/misc/blas.h>
}
static float fone = 1;
diff --git a/resources/3rdparty/eigen/bench/spbench/CMakeLists.txt b/resources/3rdparty/eigen/bench/spbench/CMakeLists.txt
index 079912266..6e0e1b103 100644
--- a/resources/3rdparty/eigen/bench/spbench/CMakeLists.txt
+++ b/resources/3rdparty/eigen/bench/spbench/CMakeLists.txt
@@ -55,6 +55,12 @@ if(PASTIX_FOUND AND BLAS_FOUND)
set(PASTIX_ALL_LIBS ${PASTIX_LIBRARIES} ${BLAS_LIBRARIES})
endif(PASTIX_FOUND AND BLAS_FOUND)
+if(METIS_FOUND)
+ include_directories(${METIS_INCLUDES})
+ set (SPARSE_LIBS ${SPARSE_LIBS} ${METIS_LIBRARIES})
+ add_definitions("-DEIGEN_METIS_SUPPORT")
+endif(METIS_FOUND)
+
find_library(RT_LIBRARY rt)
if(RT_LIBRARY)
set(SPARSE_LIBS ${SPARSE_LIBS} ${RT_LIBRARY})
@@ -63,3 +69,10 @@ endif(RT_LIBRARY)
add_executable(spbenchsolver spbenchsolver.cpp)
target_link_libraries (spbenchsolver ${SPARSE_LIBS})
+add_executable(spsolver sp_solver.cpp)
+target_link_libraries (spsolver ${SPARSE_LIBS})
+
+
+add_executable(test_sparseLU test_sparseLU.cpp)
+target_link_libraries (test_sparseLU ${SPARSE_LIBS})
+
diff --git a/resources/3rdparty/eigen/bench/spbench/sp_solver.cpp b/resources/3rdparty/eigen/bench/spbench/sp_solver.cpp
new file mode 100644
index 000000000..a1f4bac8a
--- /dev/null
+++ b/resources/3rdparty/eigen/bench/spbench/sp_solver.cpp
@@ -0,0 +1,125 @@
+// Small bench routine for Eigen available in Eigen
+// (C) Desire NUENTSA WAKAM, INRIA
+
+#include <iostream>
+#include <fstream>
+#include <iomanip>
+#include <Eigen/Jacobi>
+#include <Eigen/Householder>
+#include <Eigen/IterativeLinearSolvers>
+#include <Eigen/LU>
+#include <unsupported/Eigen/SparseExtra>
+//#include <Eigen/SparseLU>
+#include <Eigen/SuperLUSupport>
+// #include <unsupported/Eigen/src/IterativeSolvers/Scaling.h>
+#include <bench/BenchTimer.h>
+#include <unsupported/Eigen/IterativeSolvers>
+using namespace std;
+using namespace Eigen;
+
+int main(int argc, char **args)
+{
+ SparseMatrix<double, ColMajor> A;
+ typedef SparseMatrix<double, ColMajor>::Index Index;
+ typedef Matrix<double, Dynamic, Dynamic> DenseMatrix;
+ typedef Matrix<double, Dynamic, 1> DenseRhs;
+ VectorXd b, x, tmp;
+ BenchTimer timer,totaltime;
+ //SparseLU<SparseMatrix<double, ColMajor> > solver;
+// SuperLU<SparseMatrix<double, ColMajor> > solver;
+ ConjugateGradient<SparseMatrix<double, ColMajor>, Lower,IncompleteCholesky<double,Lower> > solver;
+ ifstream matrix_file;
+ string line;
+ int n;
+ // Set parameters
+// solver.iparm(IPARM_THREAD_NBR) = 4;
+ /* Fill the matrix with sparse matrix stored in Matrix-Market coordinate column-oriented format */
+ if (argc < 2) assert(false && "please, give the matrix market file ");
+
+ timer.start();
+ totaltime.start();
+ loadMarket(A, args[1]);
+ cout << "End charging matrix " << endl;
+ bool iscomplex=false, isvector=false;
+ int sym;
+ getMarketHeader(args[1], sym, iscomplex, isvector);
+ if (iscomplex) { cout<< " Not for complex matrices \n"; return -1; }
+ if (isvector) { cout << "The provided file is not a matrix file\n"; return -1;}
+ if (sym != 0) { // symmetric matrices, only the lower part is stored
+ SparseMatrix<double, ColMajor> temp;
+ temp = A;
+ A = temp.selfadjointView<Lower>();
+ }
+ timer.stop();
+
+ n = A.cols();
+ // ====== TESTS FOR SPARSE TUTORIAL ======
+// cout<< "OuterSize " << A.outerSize() << " inner " << A.innerSize() << endl;
+// SparseMatrix<double, RowMajor> mat1(A);
+// SparseMatrix<double, RowMajor> mat2;
+// cout << " norm of A " << mat1.norm() << endl; ;
+// PermutationMatrix<Dynamic, Dynamic, int> perm(n);
+// perm.resize(n,1);
+// perm.indices().setLinSpaced(n, 0, n-1);
+// mat2 = perm * mat1;
+// mat.subrows();
+// mat2.resize(n,n);
+// mat2.reserve(10);
+// mat2.setConstant();
+// std::cout<< "NORM " << mat1.squaredNorm()<< endl;
+
+ cout<< "Time to load the matrix " << timer.value() <<endl;
+ /* Fill the right hand side */
+
+// solver.set_restart(374);
+ if (argc > 2)
+ loadMarketVector(b, args[2]);
+ else
+ {
+ b.resize(n);
+ tmp.resize(n);
+// tmp.setRandom();
+ for (int i = 0; i < n; i++) tmp(i) = i;
+ b = A * tmp ;
+ }
+// Scaling<SparseMatrix<double> > scal;
+// scal.computeRef(A);
+// b = scal.LeftScaling().cwiseProduct(b);
+
+ /* Compute the factorization */
+ cout<< "Starting the factorization "<< endl;
+ timer.reset();
+ timer.start();
+ cout<< "Size of Input Matrix "<< b.size()<<"\n\n";
+ cout<< "Rows and columns "<< A.rows() <<" " <<A.cols() <<"\n";
+ solver.compute(A);
+// solver.analyzePattern(A);
+// solver.factorize(A);
+ if (solver.info() != Success) {
+ std::cout<< "The solver failed \n";
+ return -1;
+ }
+ timer.stop();
+ float time_comp = timer.value();
+ cout <<" Compute Time " << time_comp<< endl;
+
+ timer.reset();
+ timer.start();
+ x = solver.solve(b);
+// x = scal.RightScaling().cwiseProduct(x);
+ timer.stop();
+ float time_solve = timer.value();
+ cout<< " Time to solve " << time_solve << endl;
+
+ /* Check the accuracy */
+ VectorXd tmp2 = b - A*x;
+ double tempNorm = tmp2.norm()/b.norm();
+ cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
+// cout << "Iterations : " << solver.iterations() << "\n";
+
+ totaltime.stop();
+ cout << "Total time " << totaltime.value() << "\n";
+// std::cout<<x.transpose()<<"\n";
+
+ return 0;
+}
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/bench/spbench/spbench.dtd b/resources/3rdparty/eigen/bench/spbench/spbench.dtd
new file mode 100644
index 000000000..0fb51b89a
--- /dev/null
+++ b/resources/3rdparty/eigen/bench/spbench/spbench.dtd
@@ -0,0 +1,31 @@
+<!ELEMENT BENCH (AVAILSOLVER+,LINEARSYSTEM+)>
+ <!ELEMENT AVAILSOLVER (SOLVER+)>
+ <!ELEMENT SOLVER (TYPE,PACKAGE)>
+ <!ELEMENT TYPE (#PCDATA)> <!-- One of LU, LLT, LDLT, ITER -->
+ <!ELEMENT PACKAGE (#PCDATA)> <!-- Derived from a library -->
+ <!ELEMENT LINEARSYSTEM (MATRIX,SOLVER_STAT+,BEST_SOLVER,GLOBAL_PARAMS*)>
+ <!ELEMENT MATRIX (NAME,SIZE,ENTRIES,PATTERN?,SYMMETRY,POSDEF?,ARITHMETIC,RHS*)>
+ <!ELEMENT NAME (#PCDATA)>
+ <!ELEMENT SIZE (#PCDATA)>
+ <!ELEMENT ENTRIES (#PCDATA)> <!-- The number of nonzeros elements -->
+ <!ELEMENT PATTERN (#PCDATA)> <!-- Is structural pattern symmetric or not -->
+ <!ELEMENT SYMMETRY (#PCDATA)> <!-- symmmetry with numerical values -->
+ <!ELEMENT POSDEF (#PCDATA)> <!-- Is the matrix positive definite or not -->
+ <!ELEMENT ARITHMETIC (#PCDATA)>
+ <!ELEMENT RHS (SOURCE)> <!-- A matrix can have one or more right hand side associated. -->
+ <!ELEMENT SOURCE (#PCDATA)> <!-- Source of the right hand side, either generated or provided -->
+ <!ELEMENT SOLVER_STAT (PARAMS*,TIME,ERROR,ITER?)>
+ <!ELEMENT PARAMS (#PCDATA)>
+ <!ELEMENT TIME (COMPUTE,SOLVE,TOTAL)>
+ <!ELEMENT COMPUTE (#PCDATA)> <!-- Time to analyze,to factorize, or to setup the preconditioner-->
+ <!ELEMENT SOLVE (#PCDATA)> <!-- Time to solve with all the available rhs -->
+ <!ELEMENT TOTAL (#PCDATA)>
+ <!ELEMENT ERROR (#PCDATA)> <!-- Either the relative error or the relative residual norm -->
+ <!ELEMENT ITER (#PCDATA)> <!-- Number of iterations -->
+ <!ELEMENT BEST_SOLVER CDATA> <!-- Id of the best solver -->
+ <!ELEMENT GLOBAL_PARAMS (#PCDATA)> <!-- Parameters shared by all solvers -->
+
+<!ATTLIST SOLVER ID CDATA #REQUIRED>
+<!ATTLIST SOLVER_STAT ID CDATA #REQUIRED>
+<!ATTLIST BEST_SOLVER ID CDATA #REQUIRED>
+<!ATTLIST RHS ID CDATA #IMPLIED>
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/bench/spbench/spbenchsolver.cpp b/resources/3rdparty/eigen/bench/spbench/spbenchsolver.cpp
index 830542ff1..4acd0039c 100644
--- a/resources/3rdparty/eigen/bench/spbench/spbenchsolver.cpp
+++ b/resources/3rdparty/eigen/bench/spbench/spbenchsolver.cpp
@@ -5,7 +5,6 @@ void bench_printhelp()
cout<< " \nbenchsolver : performs a benchmark of all the solvers available in Eigen \n\n";
cout<< " MATRIX FOLDER : \n";
cout<< " The matrices for the benchmark should be collected in a folder specified with an environment variable EIGEN_MATRIXDIR \n";
- cout<< " This folder should contain the subfolders real/ and complex/ : \n";
cout<< " The matrices are stored using the matrix market coordinate format \n";
cout<< " The matrix and associated right-hand side (rhs) files are named respectively \n";
cout<< " as MatrixName.mtx and MatrixName_b.mtx. If the rhs does not exist, a random one is generated. \n";
@@ -15,7 +14,7 @@ void bench_printhelp()
cout<< " OPTIONS : \n";
cout<< " -h or --help \n print this help and return\n\n";
cout<< " -d matrixdir \n Use matrixdir as the matrix folder instead of the one specified in the environment variable EIGEN_MATRIXDIR\n\n";
- cout<< " -o outputfile.html \n Output the statistics to a html file \n\n";
+ cout<< " -o outputfile.xml \n Output the statistics to a xml file \n\n";
cout<< " --eps <RelErr> Sets the relative tolerance for iterative solvers (default 1e-08) \n\n";
cout<< " --maxits <MaxIts> Sets the maximum number of iterations (default 1000) \n\n";
@@ -68,18 +67,16 @@ int main(int argc, char ** args)
maxiters = atoi(inval.c_str());
string current_dir;
- // Test the matrices in %EIGEN_MATRIXDIR/real
- current_dir = matrix_dir + "/real";
- Browse_Matrices<double>(current_dir, statFileExists, statFile,maxiters, tol);
+ // Test the real-arithmetics matrices
+ Browse_Matrices<double>(matrix_dir, statFileExists, statFile,maxiters, tol);
- // Test the matrices in %EIGEN_MATRIXDIR/complex
- current_dir = matrix_dir + "/complex";
- Browse_Matrices<std::complex<double> >(current_dir, statFileExists, statFile, maxiters, tol);
+ // Test the complex-arithmetics matrices
+ Browse_Matrices<std::complex<double> >(matrix_dir, statFileExists, statFile, maxiters, tol);
if(statFileExists)
{
statbuf.open(statFile.c_str(), std::ios::app);
- statbuf << "</TABLE> \n";
+ statbuf << "</BENCH> \n";
cout << "\n Output written in " << statFile << " ...\n";
statbuf.close();
}
diff --git a/resources/3rdparty/eigen/bench/spbench/spbenchsolver.h b/resources/3rdparty/eigen/bench/spbench/spbenchsolver.h
index 609c7c39d..19c719c04 100644
--- a/resources/3rdparty/eigen/bench/spbench/spbenchsolver.h
+++ b/resources/3rdparty/eigen/bench/spbench/spbenchsolver.h
@@ -10,7 +10,7 @@
#include <iostream>
#include <fstream>
-#include "Eigen/SparseCore"
+#include <Eigen/SparseCore>
#include <bench/BenchTimer.h>
#include <cstdlib>
#include <string>
@@ -21,6 +21,13 @@
#include <unsupported/Eigen/IterativeSolvers>
#include <Eigen/LU>
#include <unsupported/Eigen/SparseExtra>
+#include <Eigen/SparseLU>
+
+#include "spbenchstyle.h"
+
+#ifdef EIGEN_METIS_SUPPORT
+#include <Eigen/MetisSupport>
+#endif
#ifdef EIGEN_CHOLMOD_SUPPORT
#include <Eigen/CholmodSupport>
@@ -43,45 +50,37 @@
#endif
// CONSTANTS
-#define EIGEN_UMFPACK 0
-#define EIGEN_SUPERLU 1
-#define EIGEN_PASTIX 2
-#define EIGEN_PARDISO 3
-#define EIGEN_BICGSTAB 4
-#define EIGEN_BICGSTAB_ILUT 5
-#define EIGEN_GMRES 6
-#define EIGEN_GMRES_ILUT 7
-#define EIGEN_SIMPLICIAL_LDLT 8
-#define EIGEN_CHOLMOD_LDLT 9
-#define EIGEN_PASTIX_LDLT 10
-#define EIGEN_PARDISO_LDLT 11
-#define EIGEN_SIMPLICIAL_LLT 12
-#define EIGEN_CHOLMOD_SUPERNODAL_LLT 13
-#define EIGEN_CHOLMOD_SIMPLICIAL_LLT 14
-#define EIGEN_PASTIX_LLT 15
-#define EIGEN_PARDISO_LLT 16
-#define EIGEN_CG 17
-#define EIGEN_CG_PRECOND 18
-#define EIGEN_ALL_SOLVERS 19
+#define EIGEN_UMFPACK 10
+#define EIGEN_SUPERLU 20
+#define EIGEN_PASTIX 30
+#define EIGEN_PARDISO 40
+#define EIGEN_SPARSELU_COLAMD 50
+#define EIGEN_SPARSELU_METIS 51
+#define EIGEN_BICGSTAB 60
+#define EIGEN_BICGSTAB_ILUT 61
+#define EIGEN_GMRES 70
+#define EIGEN_GMRES_ILUT 71
+#define EIGEN_SIMPLICIAL_LDLT 80
+#define EIGEN_CHOLMOD_LDLT 90
+#define EIGEN_PASTIX_LDLT 100
+#define EIGEN_PARDISO_LDLT 110
+#define EIGEN_SIMPLICIAL_LLT 120
+#define EIGEN_CHOLMOD_SUPERNODAL_LLT 130
+#define EIGEN_CHOLMOD_SIMPLICIAL_LLT 140
+#define EIGEN_PASTIX_LLT 150
+#define EIGEN_PARDISO_LLT 160
+#define EIGEN_CG 170
+#define EIGEN_CG_PRECOND 180
using namespace Eigen;
using namespace std;
-struct Stats{
- ComputationInfo info;
- double total_time;
- double compute_time;
- double solve_time;
- double rel_error;
- int memory_used;
- int iterations;
- int isavail;
- int isIterative;
-};
// Global variables for input parameters
int MaximumIters; // Maximum number of iterations
double RelErr; // Relative error of the computed solution
+double best_time_val; // Current best time overall solvers
+int best_time_id; // id of the best solver for the current system
template<typename T> inline typename NumTraits<T>::Real test_precision() { return NumTraits<T>::dummy_precision(); }
template<> inline float test_precision<float>() { return 1e-3f; }
@@ -91,41 +90,134 @@ template<> inline double test_precision<std::complex<double> >() { return test_p
void printStatheader(std::ofstream& out)
{
- int LUcnt = 0;
- string LUlist =" ", LLTlist = "<TH > LLT", LDLTlist = "<TH > LDLT ";
+ // Print XML header
+ // NOTE It would have been much easier to write these XML documents using external libraries like tinyXML or Xerces-C++.
+
+ out << "<?xml version='1.0' encoding='UTF-8'?> \n";
+ out << "<?xml-stylesheet type='text/xsl' href='#stylesheet' ?> \n";
+ out << "<!DOCTYPE BENCH [\n<!ATTLIST xsl:stylesheet\n id\t ID #REQUIRED>\n]>";
+ out << "\n\n<!-- Generated by the Eigen library -->\n";
+ out << "\n<BENCH> \n" ; //root XML element
+ // Print the xsl style section
+ printBenchStyle(out);
+ // List all available solvers
+ out << " <AVAILSOLVER> \n";
#ifdef EIGEN_UMFPACK_SUPPORT
- LUlist += "<TH > UMFPACK "; LUcnt++;
+ out <<" <SOLVER ID='" << EIGEN_UMFPACK << "'>\n";
+ out << " <TYPE> LU </TYPE> \n";
+ out << " <PACKAGE> UMFPACK </PACKAGE> \n";
+ out << " </SOLVER> \n";
#endif
#ifdef EIGEN_SUPERLU_SUPPORT
- LUlist += "<TH > SUPERLU "; LUcnt++;
+ out <<" <SOLVER ID='" << EIGEN_SUPERLU << "'>\n";
+ out << " <TYPE> LU </TYPE> \n";
+ out << " <PACKAGE> SUPERLU </PACKAGE> \n";
+ out << " </SOLVER> \n";
#endif
#ifdef EIGEN_CHOLMOD_SUPPORT
- LLTlist += "<TH > CHOLMOD SP LLT<TH > CHOLMOD LLT";
- LDLTlist += "<TH>CHOLMOD LDLT";
+ out <<" <SOLVER ID='" << EIGEN_CHOLMOD_SIMPLICIAL_LLT << "'>\n";
+ out << " <TYPE> LLT SP</TYPE> \n";
+ out << " <PACKAGE> CHOLMOD </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_CHOLMOD_SUPERNODAL_LLT << "'>\n";
+ out << " <TYPE> LLT</TYPE> \n";
+ out << " <PACKAGE> CHOLMOD </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_CHOLMOD_LDLT << "'>\n";
+ out << " <TYPE> LDLT </TYPE> \n";
+ out << " <PACKAGE> CHOLMOD </PACKAGE> \n";
+ out << " </SOLVER> \n";
#endif
#ifdef EIGEN_PARDISO_SUPPORT
- LUlist += "<TH > PARDISO LU"; LUcnt++;
- LLTlist += "<TH > PARDISO LLT";
- LDLTlist += "<TH > PARDISO LDLT";
+ out <<" <SOLVER ID='" << EIGEN_PARDISO << "'>\n";
+ out << " <TYPE> LU </TYPE> \n";
+ out << " <PACKAGE> PARDISO </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_PARDISO_LLT << "'>\n";
+ out << " <TYPE> LLT </TYPE> \n";
+ out << " <PACKAGE> PARDISO </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_PARDISO_LDLT << "'>\n";
+ out << " <TYPE> LDLT </TYPE> \n";
+ out << " <PACKAGE> PARDISO </PACKAGE> \n";
+ out << " </SOLVER> \n";
#endif
#ifdef EIGEN_PASTIX_SUPPORT
- LUlist += "<TH > PASTIX LU"; LUcnt++;
- LLTlist += "<TH > PASTIX LLT";
- LDLTlist += "<TH > PASTIX LDLT";
+ out <<" <SOLVER ID='" << EIGEN_PASTIX << "'>\n";
+ out << " <TYPE> LU </TYPE> \n";
+ out << " <PACKAGE> PASTIX </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_PASTIX_LLT << "'>\n";
+ out << " <TYPE> LLT </TYPE> \n";
+ out << " <PACKAGE> PASTIX </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_PASTIX_LDLT << "'>\n";
+ out << " <TYPE> LDLT </TYPE> \n";
+ out << " <PACKAGE> PASTIX </PACKAGE> \n";
+ out << " </SOLVER> \n";
+#endif
+
+ out <<" <SOLVER ID='" << EIGEN_BICGSTAB << "'>\n";
+ out << " <TYPE> BICGSTAB </TYPE> \n";
+ out << " <PACKAGE> EIGEN </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_BICGSTAB_ILUT << "'>\n";
+ out << " <TYPE> BICGSTAB_ILUT </TYPE> \n";
+ out << " <PACKAGE> EIGEN </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_GMRES_ILUT << "'>\n";
+ out << " <TYPE> GMRES_ILUT </TYPE> \n";
+ out << " <PACKAGE> EIGEN </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_SIMPLICIAL_LDLT << "'>\n";
+ out << " <TYPE> LDLT </TYPE> \n";
+ out << " <PACKAGE> EIGEN </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_SIMPLICIAL_LLT << "'>\n";
+ out << " <TYPE> LLT </TYPE> \n";
+ out << " <PACKAGE> EIGEN </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_CG << "'>\n";
+ out << " <TYPE> CG </TYPE> \n";
+ out << " <PACKAGE> EIGEN </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+ out <<" <SOLVER ID='" << EIGEN_SPARSELU_COLAMD << "'>\n";
+ out << " <TYPE> LU_COLAMD </TYPE> \n";
+ out << " <PACKAGE> EIGEN </PACKAGE> \n";
+ out << " </SOLVER> \n";
+
+#ifdef EIGEN_METIS_SUPPORT
+ out <<" <SOLVER ID='" << EIGEN_SPARSELU_METIS << "'>\n";
+ out << " <TYPE> LU_METIS </TYPE> \n";
+ out << " <PACKAGE> EIGEN </PACKAGE> \n";
+ out << " </SOLVER> \n";
#endif
+ out << " </AVAILSOLVER> \n";
- out << "<TABLE border=\"1\" >\n ";
- out << "<TR><TH>Matrix <TH> N <TH> NNZ <TH> ";
- if (LUcnt) out << LUlist;
- out << " <TH >BiCGSTAB <TH >BiCGSTAB+ILUT"<< "<TH >GMRES+ILUT" <<LDLTlist << LLTlist << "<TH> CG "<< std::endl;
}
template<typename Solver, typename Scalar>
-Stats call_solver(Solver &solver, const typename Solver::MatrixType& A, const Matrix<Scalar, Dynamic, 1>& b, const Matrix<Scalar, Dynamic, 1>& refX)
+void call_solver(Solver &solver, const int solver_id, const typename Solver::MatrixType& A, const Matrix<Scalar, Dynamic, 1>& b, const Matrix<Scalar, Dynamic, 1>& refX,std::ofstream& statbuf)
{
- Stats stat;
+
+ double total_time;
+ double compute_time;
+ double solve_time;
+ double rel_error;
Matrix<Scalar, Dynamic, 1> x;
BenchTimer timer;
timer.reset();
@@ -133,170 +225,95 @@ Stats call_solver(Solver &solver, const typename Solver::MatrixType& A, const Ma
solver.compute(A);
if (solver.info() != Success)
{
- stat.info = NumericalIssue;
std::cerr << "Solver failed ... \n";
- return stat;
+ return;
}
- timer.stop();
- stat.compute_time = timer.value();
-
+ timer.stop();
+ compute_time = timer.value();
+ statbuf << " <TIME>\n";
+ statbuf << " <COMPUTE> " << timer.value() << "</COMPUTE>\n";
+ std::cout<< "COMPUTE TIME : " << timer.value() <<std::endl;
+
timer.reset();
timer.start();
x = solver.solve(b);
if (solver.info() == NumericalIssue)
{
- stat.info = NumericalIssue;
std::cerr << "Solver failed ... \n";
- return stat;
+ return;
}
-
timer.stop();
- stat.solve_time = timer.value();
- stat.total_time = stat.solve_time + stat.compute_time;
- stat.memory_used = 0;
+ solve_time = timer.value();
+ statbuf << " <SOLVE> " << timer.value() << "</SOLVE>\n";
+ std::cout<< "SOLVE TIME : " << timer.value() <<std::endl;
+
+ total_time = solve_time + compute_time;
+ statbuf << " <TOTAL> " << total_time << "</TOTAL>\n";
+ std::cout<< "TOTAL TIME : " << total_time <<std::endl;
+ statbuf << " </TIME>\n";
+
// Verify the relative error
if(refX.size() != 0)
- stat.rel_error = (refX - x).norm()/refX.norm();
+ rel_error = (refX - x).norm()/refX.norm();
else
{
// Compute the relative residual norm
Matrix<Scalar, Dynamic, 1> temp;
temp = A * x;
- stat.rel_error = (b-temp).norm()/b.norm();
- }
- if ( stat.rel_error > RelErr )
- {
- stat.info = NoConvergence;
- return stat;
+ rel_error = (b-temp).norm()/b.norm();
}
- else
+ statbuf << " <ERROR> " << rel_error << "</ERROR>\n";
+ std::cout<< "REL. ERROR : " << rel_error << "\n\n" ;
+ if ( rel_error <= RelErr )
{
- stat.info = Success;
- return stat;
+ // check the best time if convergence
+ if(!best_time_val || (best_time_val > total_time))
+ {
+ best_time_val = total_time;
+ best_time_id = solver_id;
+ }
}
}
template<typename Solver, typename Scalar>
-Stats call_directsolver(Solver& solver, const typename Solver::MatrixType& A, const Matrix<Scalar, Dynamic, 1>& b, const Matrix<Scalar, Dynamic, 1>& refX)
+void call_directsolver(Solver& solver, const int solver_id, const typename Solver::MatrixType& A, const Matrix<Scalar, Dynamic, 1>& b, const Matrix<Scalar, Dynamic, 1>& refX, std::string& statFile)
{
- Stats stat;
- stat = call_solver(solver, A, b, refX);
- return stat;
+ std::ofstream statbuf(statFile.c_str(), std::ios::app);
+ statbuf << " <SOLVER_STAT ID='" << solver_id <<"'>\n";
+ call_solver(solver, solver_id, A, b, refX,statbuf);
+ statbuf << " </SOLVER_STAT>\n";
+ statbuf.close();
}
template<typename Solver, typename Scalar>
-Stats call_itersolver(Solver &solver, const typename Solver::MatrixType& A, const Matrix<Scalar, Dynamic, 1>& b, const Matrix<Scalar, Dynamic, 1>& refX)
+void call_itersolver(Solver &solver, const int solver_id, const typename Solver::MatrixType& A, const Matrix<Scalar, Dynamic, 1>& b, const Matrix<Scalar, Dynamic, 1>& refX, std::string& statFile)
{
- Stats stat;
solver.setTolerance(RelErr);
solver.setMaxIterations(MaximumIters);
- stat = call_solver(solver, A, b, refX);
- stat.iterations = solver.iterations();
- return stat;
-}
-
-inline void printStatItem(Stats *stat, int solver_id, int& best_time_id, double& best_time_val)
-{
- stat[solver_id].isavail = 1;
-
- if (stat[solver_id].info == NumericalIssue)
- {
- cout << " SOLVER FAILED ... Probably a numerical issue \n";
- return;
- }
- if (stat[solver_id].info == NoConvergence){
- cout << "REL. ERROR " << stat[solver_id].rel_error;
- if(stat[solver_id].isIterative == 1)
- cout << " (" << stat[solver_id].iterations << ") \n";
- return;
- }
+ std::ofstream statbuf(statFile.c_str(), std::ios::app);
+ statbuf << " <SOLVER_STAT ID='" << solver_id <<"'>\n";
+ call_solver(solver, solver_id, A, b, refX,statbuf);
+ statbuf << " <ITER> "<< solver.iterations() << "</ITER>\n";
+ statbuf << " </SOLVER_STAT>\n";
+ std::cout << "ITERATIONS : " << solver.iterations() <<"\n\n\n";
- // Record the best CPU time
- if (!best_time_val)
- {
- best_time_val = stat[solver_id].total_time;
- best_time_id = solver_id;
- }
- else if (stat[solver_id].total_time < best_time_val)
- {
- best_time_val = stat[solver_id].total_time;
- best_time_id = solver_id;
- }
- // Print statistics to standard output
- if (stat[solver_id].info == Success){
- cout<< "COMPUTE TIME : " << stat[solver_id].compute_time<< " \n";
- cout<< "SOLVE TIME : " << stat[solver_id].solve_time<< " \n";
- cout<< "TOTAL TIME : " << stat[solver_id].total_time<< " \n";
- cout << "REL. ERROR : " << stat[solver_id].rel_error ;
- if(stat[solver_id].isIterative == 1) {
- cout << " (" << stat[solver_id].iterations << ") ";
- }
- cout << std::endl;
- }
-
}
-/* Print the results from all solvers corresponding to a particular matrix
- * The best CPU time is printed in bold
- */
-inline void printHtmlStatLine(Stats *stat, int best_time_id, string& statline)
-{
-
- string markup;
- ostringstream compute,solve,total,error;
- for (int i = 0; i < EIGEN_ALL_SOLVERS; i++)
- {
- if (stat[i].isavail == 0) continue;
- if(i == best_time_id)
- markup = "<TD style=\"background-color:red\">";
- else
- markup = "<TD>";
-
- if (stat[i].info == Success){
- compute << markup << stat[i].compute_time;
- solve << markup << stat[i].solve_time;
- total << markup << stat[i].total_time;
- error << " <TD> " << stat[i].rel_error;
- if(stat[i].isIterative == 1) {
- error << " (" << stat[i].iterations << ") ";
- }
- }
- else {
- compute << " <TD> -" ;
- solve << " <TD> -" ;
- total << " <TD> -" ;
- if(stat[i].info == NoConvergence){
- error << " <TD> "<< stat[i].rel_error ;
- if(stat[i].isIterative == 1)
- error << " (" << stat[i].iterations << ") ";
- }
- else error << " <TD> - ";
- }
- }
-
- statline = "<TH>Compute Time " + compute.str() + "\n"
- + "<TR><TH>Solve Time " + solve.str() + "\n"
- + "<TR><TH>Total Time " + total.str() + "\n"
- +"<TR><TH>Error(Iter)" + error.str() + "\n";
-
-}
-
template <typename Scalar>
-int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar, Dynamic, 1>& b, const Matrix<Scalar, Dynamic, 1>& refX, Stats *stat)
+void SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar, Dynamic, 1>& b, const Matrix<Scalar, Dynamic, 1>& refX, std::string& statFile)
{
typedef SparseMatrix<Scalar, ColMajor> SpMat;
// First, deal with Nonsymmetric and symmetric matrices
- int best_time_id = 0;
- double best_time_val = 0.0;
+ best_time_id = 0;
+ best_time_val = 0.0;
//UMFPACK
#ifdef EIGEN_UMFPACK_SUPPORT
{
cout << "Solving with UMFPACK LU ... \n";
UmfPackLU<SpMat> solver;
- stat[EIGEN_UMFPACK] = call_directsolver(solver, A, b, refX);
- printStatItem(stat, EIGEN_UMFPACK, best_time_id, best_time_val);
+ call_directsolver(solver, EIGEN_UMFPACK, A, b, refX,statFile);
}
#endif
//SuperLU
@@ -304,8 +321,7 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with SUPERLU ... \n";
SuperLU<SpMat> solver;
- stat[EIGEN_SUPERLU] = call_directsolver(solver, A, b, refX);
- printStatItem(stat, EIGEN_SUPERLU, best_time_id, best_time_val);
+ call_directsolver(solver, EIGEN_SUPERLU, A, b, refX,statFile);
}
#endif
@@ -314,8 +330,7 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with PASTIX LU ... \n";
PastixLU<SpMat> solver;
- stat[EIGEN_PASTIX] = call_directsolver(solver, A, b, refX) ;
- printStatItem(stat, EIGEN_PASTIX, best_time_id, best_time_val);
+ call_directsolver(solver, EIGEN_PASTIX, A, b, refX,statFile) ;
}
#endif
@@ -324,28 +339,34 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with PARDISO LU ... \n";
PardisoLU<SpMat> solver;
- stat[EIGEN_PARDISO] = call_directsolver(solver, A, b, refX);
- printStatItem(stat, EIGEN_PARDISO, best_time_id, best_time_val);
+ call_directsolver(solver, EIGEN_PARDISO, A, b, refX,statFile);
+ }
+ #endif
+
+ // Eigen SparseLU METIS
+ cout << "\n Solving with Sparse LU AND COLAMD ... \n";
+ SparseLU<SpMat, COLAMDOrdering<int> > solver;
+ call_directsolver(solver, EIGEN_SPARSELU_COLAMD, A, b, refX, statFile);
+ // Eigen SparseLU METIS
+ #ifdef EIGEN_METIS_SUPPORT
+ {
+ cout << "\n Solving with Sparse LU AND METIS ... \n";
+ SparseLU<SpMat, MetisOrdering<int> > solver;
+ call_directsolver(solver, EIGEN_SPARSELU_METIS, A, b, refX, statFile);
}
#endif
-
-
//BiCGSTAB
{
cout << "\nSolving with BiCGSTAB ... \n";
BiCGSTAB<SpMat> solver;
- stat[EIGEN_BICGSTAB] = call_itersolver(solver, A, b, refX);
- stat[EIGEN_BICGSTAB].isIterative = 1;
- printStatItem(stat, EIGEN_BICGSTAB, best_time_id, best_time_val);
+ call_itersolver(solver, EIGEN_BICGSTAB, A, b, refX,statFile);
}
//BiCGSTAB+ILUT
{
cout << "\nSolving with BiCGSTAB and ILUT ... \n";
BiCGSTAB<SpMat, IncompleteLUT<Scalar> > solver;
- stat[EIGEN_BICGSTAB_ILUT] = call_itersolver(solver, A, b, refX);
- stat[EIGEN_BICGSTAB_ILUT].isIterative = 1;
- printStatItem(stat, EIGEN_BICGSTAB_ILUT, best_time_id, best_time_val);
+ call_itersolver(solver, EIGEN_BICGSTAB_ILUT, A, b, refX,statFile);
}
@@ -353,17 +374,13 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
// {
// cout << "\nSolving with GMRES ... \n";
// GMRES<SpMat> solver;
-// stat[EIGEN_GMRES] = call_itersolver(solver, A, b, refX);
-// stat[EIGEN_GMRES].isIterative = 1;
-// printStatItem(stat, EIGEN_GMRES, best_time_id, best_time_val);
+// call_itersolver(solver, EIGEN_GMRES, A, b, refX,statFile);
// }
//GMRES+ILUT
{
cout << "\nSolving with GMRES and ILUT ... \n";
GMRES<SpMat, IncompleteLUT<Scalar> > solver;
- stat[EIGEN_GMRES_ILUT] = call_itersolver(solver, A, b, refX);
- stat[EIGEN_GMRES_ILUT].isIterative = 1;
- printStatItem(stat, EIGEN_GMRES_ILUT, best_time_id, best_time_val);
+ call_itersolver(solver, EIGEN_GMRES_ILUT, A, b, refX,statFile);
}
// Hermitian and not necessarily positive-definites
@@ -373,8 +390,7 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with Simplicial LDLT ... \n";
SimplicialLDLT<SpMat, Lower> solver;
- stat[EIGEN_SIMPLICIAL_LDLT] = call_directsolver(solver, A, b, refX);
- printStatItem(stat, EIGEN_SIMPLICIAL_LDLT, best_time_id, best_time_val);
+ call_directsolver(solver, EIGEN_SIMPLICIAL_LDLT, A, b, refX,statFile);
}
// CHOLMOD
@@ -383,8 +399,7 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
cout << "\nSolving with CHOLMOD LDLT ... \n";
CholmodDecomposition<SpMat, Lower> solver;
solver.setMode(CholmodLDLt);
- stat[EIGEN_CHOLMOD_LDLT] = call_directsolver(solver, A, b, refX);
- printStatItem(stat,EIGEN_CHOLMOD_LDLT, best_time_id, best_time_val);
+ call_directsolver(solver,EIGEN_CHOLMOD_LDLT, A, b, refX,statFile);
}
#endif
@@ -393,8 +408,7 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with PASTIX LDLT ... \n";
PastixLDLT<SpMat, Lower> solver;
- stat[EIGEN_PASTIX_LDLT] = call_directsolver(solver, A, b, refX);
- printStatItem(stat,EIGEN_PASTIX_LDLT, best_time_id, best_time_val);
+ call_directsolver(solver,EIGEN_PASTIX_LDLT, A, b, refX,statFile);
}
#endif
@@ -403,8 +417,7 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with PARDISO LDLT ... \n";
PardisoLDLT<SpMat, Lower> solver;
- stat[EIGEN_PARDISO_LDLT] = call_directsolver(solver, A, b, refX);
- printStatItem(stat,EIGEN_PARDISO_LDLT, best_time_id, best_time_val);
+ call_directsolver(solver,EIGEN_PARDISO_LDLT, A, b, refX,statFile);
}
#endif
}
@@ -417,8 +430,7 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with SIMPLICIAL LLT ... \n";
SimplicialLLT<SpMat, Lower> solver;
- stat[EIGEN_SIMPLICIAL_LLT] = call_directsolver(solver, A, b, refX);
- printStatItem(stat,EIGEN_SIMPLICIAL_LLT, best_time_id, best_time_val);
+ call_directsolver(solver,EIGEN_SIMPLICIAL_LLT, A, b, refX,statFile);
}
// CHOLMOD
@@ -428,13 +440,11 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
cout << "\nSolving with CHOLMOD LLT (Supernodal)... \n";
CholmodDecomposition<SpMat, Lower> solver;
solver.setMode(CholmodSupernodalLLt);
- stat[EIGEN_CHOLMOD_SUPERNODAL_LLT] = call_directsolver(solver, A, b, refX);
- printStatItem(stat,EIGEN_CHOLMOD_SUPERNODAL_LLT, best_time_id, best_time_val);
+ call_directsolver(solver,EIGEN_CHOLMOD_SUPERNODAL_LLT, A, b, refX,statFile);
// CholMod Simplicial LLT
cout << "\nSolving with CHOLMOD LLT (Simplicial) ... \n";
solver.setMode(CholmodSimplicialLLt);
- stat[EIGEN_CHOLMOD_SIMPLICIAL_LLT] = call_directsolver(solver, A, b, refX);
- printStatItem(stat,EIGEN_CHOLMOD_SIMPLICIAL_LLT, best_time_id, best_time_val);
+ call_directsolver(solver,EIGEN_CHOLMOD_SIMPLICIAL_LLT, A, b, refX,statFile);
}
#endif
@@ -443,8 +453,7 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with PASTIX LLT ... \n";
PastixLLT<SpMat, Lower> solver;
- stat[EIGEN_PASTIX_LLT] = call_directsolver(solver, A, b, refX);
- printStatItem(stat,EIGEN_PASTIX_LLT, best_time_id, best_time_val);
+ call_directsolver(solver,EIGEN_PASTIX_LLT, A, b, refX,statFile);
}
#endif
@@ -453,8 +462,7 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with PARDISO LLT ... \n";
PardisoLLT<SpMat, Lower> solver;
- stat[EIGEN_PARDISO_LLT] = call_directsolver(solver, A, b, refX);
- printStatItem(stat,EIGEN_PARDISO_LLT, best_time_id, best_time_val);
+ call_directsolver(solver,EIGEN_PARDISO_LLT, A, b, refX,statFile);
}
#endif
@@ -462,21 +470,15 @@ int SelectSolvers(const SparseMatrix<Scalar>&A, unsigned int sym, Matrix<Scalar,
{
cout << "\nSolving with CG ... \n";
ConjugateGradient<SpMat, Lower> solver;
- stat[EIGEN_CG] = call_itersolver(solver, A, b, refX);
- stat[EIGEN_CG].isIterative = 1;
- printStatItem(stat,EIGEN_CG, best_time_id, best_time_val);
+ call_itersolver(solver,EIGEN_CG, A, b, refX,statFile);
}
//CG+IdentityPreconditioner
// {
// cout << "\nSolving with CG and IdentityPreconditioner ... \n";
// ConjugateGradient<SpMat, Lower, IdentityPreconditioner> solver;
-// stat[EIGEN_CG_PRECOND] = call_itersolver(solver, A, b, refX);
-// stat[EIGEN_CG_PRECOND].isIterative = 1;
-// printStatItem(stat,EIGEN_CG_PRECOND, best_time_id, best_time_val);
+// call_itersolver(solver,EIGEN_CG_PRECOND, A, b, refX,statFile);
// }
} // End SPD matrices
-
- return best_time_id;
}
/* Browse all the matrices available in the specified folder
@@ -490,30 +492,49 @@ void Browse_Matrices(const string folder, bool statFileExists, std::string& stat
MaximumIters = maxiters; // Maximum number of iterations, global variable
RelErr = tol; //Relative residual error as stopping criterion for iterative solvers
MatrixMarketIterator<Scalar> it(folder);
- Stats stat[EIGEN_ALL_SOLVERS];
for ( ; it; ++it)
- {
- for (int i = 0; i < EIGEN_ALL_SOLVERS; i++)
+ {
+ //print the infos for this linear system
+ if(statFileExists)
{
- stat[i].isavail = 0;
- stat[i].isIterative = 0;
+ std::ofstream statbuf(statFile.c_str(), std::ios::app);
+ statbuf << "<LINEARSYSTEM> \n";
+ statbuf << " <MATRIX> \n";
+ statbuf << " <NAME> " << it.matname() << " </NAME>\n";
+ statbuf << " <SIZE> " << it.matrix().rows() << " </SIZE>\n";
+ statbuf << " <ENTRIES> " << it.matrix().nonZeros() << "</ENTRIES>\n";
+ if (it.sym()!=NonSymmetric)
+ {
+ statbuf << " <SYMMETRY> Symmetric </SYMMETRY>\n" ;
+ if (it.sym() == SPD)
+ statbuf << " <POSDEF> YES </POSDEF>\n";
+ else
+ statbuf << " <POSDEF> NO </POSDEF>\n";
+
+ }
+ else
+ {
+ statbuf << " <SYMMETRY> NonSymmetric </SYMMETRY>\n" ;
+ statbuf << " <POSDEF> NO </POSDEF>\n";
+ }
+ statbuf << " </MATRIX> \n";
+ statbuf.close();
}
- int best_time_id;
cout<< "\n\n===================================================== \n";
cout<< " ====== SOLVING WITH MATRIX " << it.matname() << " ====\n";
cout<< " =================================================== \n\n";
Matrix<Scalar, Dynamic, 1> refX;
if(it.hasrefX()) refX = it.refX();
- best_time_id = SelectSolvers<Scalar>(it.matrix(), it.sym(), it.rhs(), refX, &stat[0]);
+ // Call all suitable solvers for this linear system
+ SelectSolvers<Scalar>(it.matrix(), it.sym(), it.rhs(), refX, statFile);
if(statFileExists)
{
- string statline;
- printHtmlStatLine(&stat[0], best_time_id, statline);
std::ofstream statbuf(statFile.c_str(), std::ios::app);
- statbuf << "<TR><TH rowspan=\"4\">" << it.matname() << " <TD rowspan=\"4\"> "
- << it.matrix().rows() << " <TD rowspan=\"4\"> " << it.matrix().nonZeros()<< " "<< statline ;
+ statbuf << " <BEST_SOLVER ID='"<< best_time_id
+ << "'></BEST_SOLVER>\n";
+ statbuf << " </LINEARSYSTEM> \n";
statbuf.close();
}
}
diff --git a/resources/3rdparty/eigen/bench/spbench/spbenchstyle.h b/resources/3rdparty/eigen/bench/spbench/spbenchstyle.h
new file mode 100644
index 000000000..17a05ce71
--- /dev/null
+++ b/resources/3rdparty/eigen/bench/spbench/spbenchstyle.h
@@ -0,0 +1,94 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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/.
+
+#ifndef SPBENCHSTYLE_H
+#define SPBENCHSTYLE_H
+
+void printBenchStyle(std::ofstream& out)
+{
+ out << "<xsl:stylesheet id='stylesheet' version='1.0' \
+ xmlns:xsl='http://www.w3.org/1999/XSL/Transform' >\n \
+ <xsl:template match='xsl:stylesheet' />\n \
+ <xsl:template match='/'> <!-- Root of the document -->\n \
+ <html>\n \
+ <head> \n \
+ <style type='text/css'> \n \
+ td { white-space: nowrap;}\n \
+ </style>\n \
+ </head>\n \
+ <body>";
+ out<<"<table border='1' width='100%' height='100%'>\n \
+ <TR> <!-- Write the table header -->\n \
+ <TH>Matrix</TH> <TH>N</TH> <TH> NNZ</TH> <TH> Sym</TH> <TH> SPD</TH> <TH> </TH>\n \
+ <xsl:for-each select='BENCH/AVAILSOLVER/SOLVER'>\n \
+ <xsl:sort select='@ID' data-type='number'/>\n \
+ <TH>\n \
+ <xsl:value-of select='TYPE' />\n \
+ <xsl:text></xsl:text>\n \
+ <xsl:value-of select='PACKAGE' />\n \
+ <xsl:text></xsl:text>\n \
+ </TH>\n \
+ </xsl:for-each>\n \
+ </TR>";
+
+ out<<" <xsl:for-each select='BENCH/LINEARSYSTEM'>\n \
+ <TR> <!-- print statistics for one linear system-->\n \
+ <TH rowspan='4'> <xsl:value-of select='MATRIX/NAME' /> </TH>\n \
+ <TD rowspan='4'> <xsl:value-of select='MATRIX/SIZE' /> </TD>\n \
+ <TD rowspan='4'> <xsl:value-of select='MATRIX/ENTRIES' /> </TD>\n \
+ <TD rowspan='4'> <xsl:value-of select='MATRIX/SYMMETRY' /> </TD>\n \
+ <TD rowspan='4'> <xsl:value-of select='MATRIX/POSDEF' /> </TD>\n \
+ <TH> Compute Time </TH>\n \
+ <xsl:for-each select='SOLVER_STAT'>\n \
+ <xsl:sort select='@ID' data-type='number'/>\n \
+ <TD> <xsl:value-of select='TIME/COMPUTE' /> </TD>\n \
+ </xsl:for-each>\n \
+ </TR>";
+ out<<" <TR>\n \
+ <TH> Solve Time </TH>\n \
+ <xsl:for-each select='SOLVER_STAT'>\n \
+ <xsl:sort select='@ID' data-type='number'/>\n \
+ <TD> <xsl:value-of select='TIME/SOLVE' /> </TD>\n \
+ </xsl:for-each>\n \
+ </TR>\n \
+ <TR>\n \
+ <TH> Total Time </TH>\n \
+ <xsl:for-each select='SOLVER_STAT'>\n \
+ <xsl:sort select='@ID' data-type='number'/>\n \
+ <xsl:choose>\n \
+ <xsl:when test='@ID=../BEST_SOLVER/@ID'>\n \
+ <TD style='background-color:red'> <xsl:value-of select='TIME/TOTAL' /> </TD>\n \
+ </xsl:when>\n \
+ <xsl:otherwise>\n \
+ <TD> <xsl:value-of select='TIME/TOTAL' /></TD>\n \
+ </xsl:otherwise>\n \
+ </xsl:choose>\n \
+ </xsl:for-each>\n \
+ </TR>";
+ out<<" <TR>\n \
+ <TH> Error </TH>\n \
+ <xsl:for-each select='SOLVER_STAT'>\n \
+ <xsl:sort select='@ID' data-type='number'/>\n \
+ <TD> <xsl:value-of select='ERROR' />\n \
+ <xsl:if test='ITER'>\n \
+ <xsl:text>(</xsl:text>\n \
+ <xsl:value-of select='ITER' />\n \
+ <xsl:text>)</xsl:text>\n \
+ </xsl:if> </TD>\n \
+ </xsl:for-each>\n \
+ </TR>\n \
+ </xsl:for-each>\n \
+ </table>\n \
+ </body>\n \
+ </html>\n \
+ </xsl:template>\n \
+ </xsl:stylesheet>\n\n";
+
+}
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/bench/spbench/test_sparseLU.cpp b/resources/3rdparty/eigen/bench/spbench/test_sparseLU.cpp
new file mode 100644
index 000000000..f8ecbe69b
--- /dev/null
+++ b/resources/3rdparty/eigen/bench/spbench/test_sparseLU.cpp
@@ -0,0 +1,93 @@
+// Small bench routine for Eigen available in Eigen
+// (C) Desire NUENTSA WAKAM, INRIA
+
+#include <iostream>
+#include <fstream>
+#include <iomanip>
+#include <unsupported/Eigen/SparseExtra>
+#include <Eigen/SparseLU>
+#include <bench/BenchTimer.h>
+#ifdef EIGEN_METIS_SUPPORT
+#include <Eigen/MetisSupport>
+#endif
+
+using namespace std;
+using namespace Eigen;
+
+int main(int argc, char **args)
+{
+// typedef complex<double> scalar;
+ typedef double scalar;
+ SparseMatrix<scalar, ColMajor> A;
+ typedef SparseMatrix<scalar, ColMajor>::Index Index;
+ typedef Matrix<scalar, Dynamic, Dynamic> DenseMatrix;
+ typedef Matrix<scalar, Dynamic, 1> DenseRhs;
+ Matrix<scalar, Dynamic, 1> b, x, tmp;
+// SparseLU<SparseMatrix<scalar, ColMajor>, AMDOrdering<int> > solver;
+// #ifdef EIGEN_METIS_SUPPORT
+// SparseLU<SparseMatrix<scalar, ColMajor>, MetisOrdering<int> > solver;
+// std::cout<< "ORDERING : METIS\n";
+// #else
+ SparseLU<SparseMatrix<scalar, ColMajor>, COLAMDOrdering<int> > solver;
+ std::cout<< "ORDERING : COLAMD\n";
+// #endif
+
+ ifstream matrix_file;
+ string line;
+ int n;
+ BenchTimer timer;
+
+ // Set parameters
+ /* Fill the matrix with sparse matrix stored in Matrix-Market coordinate column-oriented format */
+ if (argc < 2) assert(false && "please, give the matrix market file ");
+ loadMarket(A, args[1]);
+ cout << "End charging matrix " << endl;
+ bool iscomplex=false, isvector=false;
+ int sym;
+ getMarketHeader(args[1], sym, iscomplex, isvector);
+// if (iscomplex) { cout<< " Not for complex matrices \n"; return -1; }
+ if (isvector) { cout << "The provided file is not a matrix file\n"; return -1;}
+ if (sym != 0) { // symmetric matrices, only the lower part is stored
+ SparseMatrix<scalar, ColMajor> temp;
+ temp = A;
+ A = temp.selfadjointView<Lower>();
+ }
+ n = A.cols();
+ /* Fill the right hand side */
+
+ if (argc > 2)
+ loadMarketVector(b, args[2]);
+ else
+ {
+ b.resize(n);
+ tmp.resize(n);
+// tmp.setRandom();
+ for (int i = 0; i < n; i++) tmp(i) = i;
+ b = A * tmp ;
+ }
+
+ /* Compute the factorization */
+// solver.isSymmetric(true);
+ timer.start();
+// solver.compute(A);
+ solver.analyzePattern(A);
+ timer.stop();
+ cout << "Time to analyze " << timer.value() << std::endl;
+ timer.reset();
+ timer.start();
+ solver.factorize(A);
+ timer.stop();
+ cout << "Factorize Time " << timer.value() << std::endl;
+ timer.reset();
+ timer.start();
+ x = solver.solve(b);
+ timer.stop();
+ cout << "solve time " << timer.value() << std::endl;
+ /* Check the accuracy */
+ Matrix<scalar, Dynamic, 1> tmp2 = b - A*x;
+ scalar tempNorm = tmp2.norm()/b.norm();
+ cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
+ cout << "Number of nonzeros in the factor : " << solver.nnzL() + solver.nnzU() << std::endl;
+
+ return 0;
+}
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/blas/CMakeLists.txt b/resources/3rdparty/eigen/blas/CMakeLists.txt
index 453d5874c..c35a2fdbe 100644
--- a/resources/3rdparty/eigen/blas/CMakeLists.txt
+++ b/resources/3rdparty/eigen/blas/CMakeLists.txt
@@ -18,10 +18,10 @@ if(EIGEN_Fortran_COMPILER_WORKS)
set(EigenBlas_SRCS ${EigenBlas_SRCS}
complexdots.f
srotm.f srotmg.f drotm.f drotmg.f
- lsame.f chpr2.f dspmv.f dtpsv.f ssbmv.f sspr.f stpmv.f
- zhpr2.f chbmv.f chpr.f ctpmv.f dspr2.f sspmv.f stpsv.f
- zhbmv.f zhpr.f ztpmv.f chpmv.f ctpsv.f dsbmv.f dspr.f dtpmv.f sspr2.f
- zhpmv.f ztpsv.f
+ lsame.f dspmv.f ssbmv.f
+ chbmv.f sspmv.f
+ zhbmv.f chpmv.f dsbmv.f
+ zhpmv.f
dtbmv.f stbmv.f ctbmv.f ztbmv.f
)
else()
diff --git a/resources/3rdparty/eigen/blas/GeneralRank1Update.h b/resources/3rdparty/eigen/blas/GeneralRank1Update.h
new file mode 100644
index 000000000..07d388c88
--- /dev/null
+++ b/resources/3rdparty/eigen/blas/GeneralRank1Update.h
@@ -0,0 +1,44 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
+//
+// 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/.
+
+#ifndef EIGEN_GENERAL_RANK1UPDATE_H
+#define EIGEN_GENERAL_RANK1UPDATE_H
+
+namespace internal {
+
+/* Optimized matrix += alpha * uv' */
+template<typename Scalar, typename Index, int StorageOrder, bool ConjLhs, bool ConjRhs>
+struct general_rank1_update;
+
+template<typename Scalar, typename Index, bool ConjLhs, bool ConjRhs>
+struct general_rank1_update<Scalar,Index,ColMajor,ConjLhs,ConjRhs>
+{
+ static void run(Index rows, Index cols, Scalar* mat, Index stride, const Scalar* u, const Scalar* v, Scalar alpha)
+ {
+ typedef Map<const Matrix<Scalar,Dynamic,1> > OtherMap;
+ typedef typename conj_expr_if<ConjLhs,OtherMap>::type ConjRhsType;
+ conj_if<ConjRhs> cj;
+
+ for (Index i=0; i<cols; ++i)
+ Map<Matrix<Scalar,Dynamic,1> >(mat+stride*i,rows) += alpha * cj(v[i]) * ConjRhsType(OtherMap(u,rows));
+ }
+};
+
+template<typename Scalar, typename Index, bool ConjLhs, bool ConjRhs>
+struct general_rank1_update<Scalar,Index,RowMajor,ConjLhs,ConjRhs>
+{
+ static void run(Index rows, Index cols, Scalar* mat, Index stride, const Scalar* u, const Scalar* v, Scalar alpha)
+ {
+ general_rank1_update<Scalar,Index,ColMajor,ConjRhs,ConjRhs>::run(rows,cols,mat,stride,u,v,alpha);
+ }
+};
+
+} // end namespace internal
+
+#endif // EIGEN_GENERAL_RANK1UPDATE_H
diff --git a/resources/3rdparty/eigen/blas/PackedSelfadjointProduct.h b/resources/3rdparty/eigen/blas/PackedSelfadjointProduct.h
new file mode 100644
index 000000000..f7c9b9341
--- /dev/null
+++ b/resources/3rdparty/eigen/blas/PackedSelfadjointProduct.h
@@ -0,0 +1,54 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
+//
+// 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/.
+
+#ifndef EIGEN_SELFADJOINT_PACKED_PRODUCT_H
+#define EIGEN_SELFADJOINT_PACKED_PRODUCT_H
+
+namespace internal {
+
+/* Optimized matrix += alpha * uv'
+ * The matrix is in packed form.
+ */
+template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjLhs, bool ConjRhs>
+struct selfadjoint_packed_rank1_update;
+
+template<typename Scalar, typename Index, int UpLo, bool ConjLhs, bool ConjRhs>
+struct selfadjoint_packed_rank1_update<Scalar,Index,ColMajor,UpLo,ConjLhs,ConjRhs>
+{
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+ static void run(Index size, Scalar* mat, const Scalar* vec, RealScalar alpha)
+ {
+ typedef Map<const Matrix<Scalar,Dynamic,1> > OtherMap;
+ typedef typename conj_expr_if<ConjLhs,OtherMap>::type ConjRhsType;
+ conj_if<ConjRhs> cj;
+
+ for (Index i=0; i<size; ++i)
+ {
+ Map<Matrix<Scalar,Dynamic,1> >(mat, UpLo==Lower ? size-i : (i+1))
+ += alpha * cj(vec[i]) * ConjRhsType(OtherMap(vec+(UpLo==Lower ? i : 0), UpLo==Lower ? size-i : (i+1)));
+ //FIXME This should be handled outside.
+ mat[UpLo==Lower ? 0 : i] = real(mat[UpLo==Lower ? 0 : i]);
+ mat += UpLo==Lower ? size-i : (i+1);
+ }
+ }
+};
+
+template<typename Scalar, typename Index, int UpLo, bool ConjLhs, bool ConjRhs>
+struct selfadjoint_packed_rank1_update<Scalar,Index,RowMajor,UpLo,ConjLhs,ConjRhs>
+{
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+ static void run(Index size, Scalar* mat, const Scalar* vec, RealScalar alpha)
+ {
+ selfadjoint_packed_rank1_update<Scalar,Index,ColMajor,UpLo==Lower?Upper:Lower,ConjRhs,ConjLhs>::run(size,mat,vec,alpha);
+ }
+};
+
+} // end namespace internal
+
+#endif // EIGEN_SELFADJOINT_PACKED_PRODUCT_H
diff --git a/resources/3rdparty/eigen/blas/PackedTriangularMatrixVector.h b/resources/3rdparty/eigen/blas/PackedTriangularMatrixVector.h
new file mode 100644
index 000000000..e9886d56f
--- /dev/null
+++ b/resources/3rdparty/eigen/blas/PackedTriangularMatrixVector.h
@@ -0,0 +1,79 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
+//
+// 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/.
+
+#ifndef EIGEN_PACKED_TRIANGULAR_MATRIX_VECTOR_H
+#define EIGEN_PACKED_TRIANGULAR_MATRIX_VECTOR_H
+
+namespace internal {
+
+template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder>
+struct packed_triangular_matrix_vector_product;
+
+template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
+struct packed_triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor>
+{
+ typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+ enum {
+ IsLower = (Mode & Lower) ==Lower,
+ HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
+ HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
+ };
+ static void run(Index size, const LhsScalar* lhs, const RhsScalar* rhs, ResScalar* res, ResScalar alpha)
+ {
+ internal::conj_if<ConjRhs> cj;
+ typedef Map<const Matrix<LhsScalar,Dynamic,1> > LhsMap;
+ typedef typename conj_expr_if<ConjLhs,LhsMap>::type ConjLhsType;
+ typedef Map<Matrix<ResScalar,Dynamic,1> > ResMap;
+
+ for (Index i=0; i<size; ++i)
+ {
+ Index s = IsLower&&(HasUnitDiag||HasZeroDiag) ? 1 : 0;
+ Index r = IsLower ? size-i: i+1;
+ if (EIGEN_IMPLIES(HasUnitDiag||HasZeroDiag, (--r)>0))
+ ResMap(res+(IsLower ? s+i : 0),r) += alpha * cj(rhs[i]) * ConjLhsType(LhsMap(lhs+s,r));
+ if (HasUnitDiag)
+ res[i] += alpha * cj(rhs[i]);
+ lhs += IsLower ? size-i: i+1;
+ }
+ };
+};
+
+template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
+struct packed_triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor>
+{
+ typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
+ enum {
+ IsLower = (Mode & Lower) ==Lower,
+ HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
+ HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
+ };
+ static void run(Index size, const LhsScalar* lhs, const RhsScalar* rhs, ResScalar* res, ResScalar alpha)
+ {
+ internal::conj_if<ConjRhs> cj;
+ typedef Map<const Matrix<LhsScalar,Dynamic,1> > LhsMap;
+ typedef typename conj_expr_if<ConjLhs,LhsMap>::type ConjLhsType;
+ typedef Map<const Matrix<RhsScalar,Dynamic,1> > RhsMap;
+ typedef typename conj_expr_if<ConjRhs,RhsMap>::type ConjRhsType;
+
+ for (Index i=0; i<size; ++i)
+ {
+ Index s = !IsLower&&(HasUnitDiag||HasZeroDiag) ? 1 : 0;
+ Index r = IsLower ? i+1 : size-i;
+ if (EIGEN_IMPLIES(HasUnitDiag||HasZeroDiag, (--r)>0))
+ res[i] += alpha * (ConjLhsType(LhsMap(lhs+s,r)).cwiseProduct(ConjRhsType(RhsMap(rhs+(IsLower ? 0 : s+i),r)))).sum();
+ if (HasUnitDiag)
+ res[i] += alpha * cj(rhs[i]);
+ lhs += IsLower ? i+1 : size-i;
+ }
+ };
+};
+
+} // end namespace internal
+
+#endif // EIGEN_PACKED_TRIANGULAR_MATRIX_VECTOR_H
diff --git a/resources/3rdparty/eigen/blas/PackedTriangularSolverVector.h b/resources/3rdparty/eigen/blas/PackedTriangularSolverVector.h
new file mode 100644
index 000000000..5c0bb4bd6
--- /dev/null
+++ b/resources/3rdparty/eigen/blas/PackedTriangularSolverVector.h
@@ -0,0 +1,88 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
+//
+// 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/.
+
+#ifndef EIGEN_PACKED_TRIANGULAR_SOLVER_VECTOR_H
+#define EIGEN_PACKED_TRIANGULAR_SOLVER_VECTOR_H
+
+namespace internal {
+
+template<typename LhsScalar, typename RhsScalar, typename Index, int Side, int Mode, bool Conjugate, int StorageOrder>
+struct packed_triangular_solve_vector;
+
+// forward and backward substitution, row-major, rhs is a vector
+template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate>
+struct packed_triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Conjugate, RowMajor>
+{
+ enum {
+ IsLower = (Mode&Lower)==Lower
+ };
+ static void run(Index size, const LhsScalar* lhs, RhsScalar* rhs)
+ {
+ internal::conj_if<Conjugate> cj;
+ typedef Map<const Matrix<LhsScalar,Dynamic,1> > LhsMap;
+ typedef typename conj_expr_if<Conjugate,LhsMap>::type ConjLhsType;
+
+ lhs += IsLower ? 0 : (size*(size+1)>>1)-1;
+ for(Index pi=0; pi<size; ++pi)
+ {
+ Index i = IsLower ? pi : size-pi-1;
+ Index s = IsLower ? 0 : 1;
+ if (pi>0)
+ rhs[i] -= (ConjLhsType(LhsMap(lhs+s,pi))
+ .cwiseProduct(Map<const Matrix<RhsScalar,Dynamic,1> >(rhs+(IsLower ? 0 : i+1),pi))).sum();
+ if (!(Mode & UnitDiag))
+ rhs[i] /= cj(lhs[IsLower ? i : 0]);
+ IsLower ? lhs += pi+1 : lhs -= pi+2;
+ }
+ }
+};
+
+// forward and backward substitution, column-major, rhs is a vector
+template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate>
+struct packed_triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Conjugate, ColMajor>
+{
+ enum {
+ IsLower = (Mode&Lower)==Lower
+ };
+ static void run(Index size, const LhsScalar* lhs, RhsScalar* rhs)
+ {
+ internal::conj_if<Conjugate> cj;
+ typedef Map<const Matrix<LhsScalar,Dynamic,1> > LhsMap;
+ typedef typename conj_expr_if<Conjugate,LhsMap>::type ConjLhsType;
+
+ lhs += IsLower ? 0 : size*(size-1)>>1;
+ for(Index pi=0; pi<size; ++pi)
+ {
+ Index i = IsLower ? pi : size-pi-1;
+ Index r = size - pi - 1;
+ if (!(Mode & UnitDiag))
+ rhs[i] /= cj(lhs[IsLower ? 0 : i]);
+ if (r>0)
+ Map<Matrix<RhsScalar,Dynamic,1> >(rhs+(IsLower? i+1 : 0),r) -=
+ rhs[i] * ConjLhsType(LhsMap(lhs+(IsLower? 1 : 0),r));
+ IsLower ? lhs += size-pi : lhs -= r;
+ }
+ }
+};
+
+template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate, int StorageOrder>
+struct packed_triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheRight, Mode, Conjugate, StorageOrder>
+{
+ static void run(Index size, const LhsScalar* lhs, RhsScalar* rhs)
+ {
+ packed_triangular_solve_vector<LhsScalar,RhsScalar,Index,OnTheLeft,
+ ((Mode&Upper)==Upper ? Lower : Upper) | (Mode&UnitDiag),
+ Conjugate,StorageOrder==RowMajor?ColMajor:RowMajor
+ >::run(size, lhs, rhs);
+ }
+};
+
+} // end namespace internal
+
+#endif // EIGEN_PACKED_TRIANGULAR_SOLVER_VECTOR_H
diff --git a/resources/3rdparty/eigen/blas/Rank2Update.h b/resources/3rdparty/eigen/blas/Rank2Update.h
new file mode 100644
index 000000000..8e1a676ee
--- /dev/null
+++ b/resources/3rdparty/eigen/blas/Rank2Update.h
@@ -0,0 +1,57 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
+//
+// 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/.
+
+#ifndef EIGEN_RANK2UPDATE_H
+#define EIGEN_RANK2UPDATE_H
+
+namespace internal {
+
+/* Optimized selfadjoint matrix += alpha * uv' + conj(alpha)*vu'
+ * This is the low-level version of SelfadjointRank2Update.h
+ */
+template<typename Scalar, typename Index, int UpLo>
+struct rank2_update_selector
+{
+ static void run(Index size, Scalar* mat, Index stride, const Scalar* u, const Scalar* v, Scalar alpha)
+ {
+ typedef Map<const Matrix<Scalar,Dynamic,1> > OtherMap;
+ for (Index i=0; i<size; ++i)
+ {
+ Map<Matrix<Scalar,Dynamic,1> >(mat+stride*i+(UpLo==Lower ? i : 0), UpLo==Lower ? size-i : (i+1)) +=
+ conj(alpha) * conj(u[i]) * OtherMap(v+(UpLo==Lower ? i : 0), UpLo==Lower ? size-i : (i+1))
+ + alpha * conj(v[i]) * OtherMap(u+(UpLo==Lower ? i : 0), UpLo==Lower ? size-i : (i+1));
+ }
+ }
+};
+
+/* Optimized selfadjoint matrix += alpha * uv' + conj(alpha)*vu'
+ * The matrix is in packed form.
+ */
+template<typename Scalar, typename Index, int UpLo>
+struct packed_rank2_update_selector
+{
+ static void run(Index size, Scalar* mat, const Scalar* u, const Scalar* v, Scalar alpha)
+ {
+ typedef Map<const Matrix<Scalar,Dynamic,1> > OtherMap;
+ Index offset = 0;
+ for (Index i=0; i<size; ++i)
+ {
+ Map<Matrix<Scalar,Dynamic,1> >(mat+offset, UpLo==Lower ? size-i : (i+1)) +=
+ conj(alpha) * conj(u[i]) * OtherMap(v+(UpLo==Lower ? i : 0), UpLo==Lower ? size-i : (i+1))
+ + alpha * conj(v[i]) * OtherMap(u+(UpLo==Lower ? i : 0), UpLo==Lower ? size-i : (i+1));
+ //FIXME This should be handled outside.
+ mat[offset+(UpLo==Lower ? 0 : i)] = real(mat[offset+(UpLo==Lower ? 0 : i)]);
+ offset += UpLo==Lower ? size-i : (i+1);
+ }
+ }
+};
+
+} // end namespace internal
+
+#endif // EIGEN_RANK2UPDATE_H
diff --git a/resources/3rdparty/eigen/blas/chpr.f b/resources/3rdparty/eigen/blas/chpr.f
deleted file mode 100644
index 11bd5c6ee..000000000
--- a/resources/3rdparty/eigen/blas/chpr.f
+++ /dev/null
@@ -1,220 +0,0 @@
- SUBROUTINE CHPR(UPLO,N,ALPHA,X,INCX,AP)
-* .. Scalar Arguments ..
- REAL ALPHA
- INTEGER INCX,N
- CHARACTER UPLO
-* ..
-* .. Array Arguments ..
- COMPLEX AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* CHPR performs the hermitian rank 1 operation
-*
-* A := alpha*x*conjg( x' ) + A,
-*
-* where alpha is a real scalar, x is an n element vector and A is an
-* n by n hermitian matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the upper or lower
-* triangular part of the matrix A is supplied in the packed
-* array AP as follows:
-*
-* UPLO = 'U' or 'u' The upper triangular part of A is
-* supplied in AP.
-*
-* UPLO = 'L' or 'l' The lower triangular part of A is
-* supplied in AP.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* ALPHA - REAL .
-* On entry, ALPHA specifies the scalar alpha.
-* Unchanged on exit.
-*
-* X - COMPLEX array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x.
-* Unchanged on exit.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* AP - COMPLEX array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular part of the hermitian matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-* and a( 2, 2 ) respectively, and so on. On exit, the array
-* AP is overwritten by the upper triangular part of the
-* updated matrix.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular part of the hermitian matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-* and a( 3, 1 ) respectively, and so on. On exit, the array
-* AP is overwritten by the lower triangular part of the
-* updated matrix.
-* Note that the imaginary parts of the diagonal elements need
-* not be set, they are assumed to be zero, and on exit they
-* are set to zero.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- COMPLEX ZERO
- PARAMETER (ZERO= (0.0E+0,0.0E+0))
-* ..
-* .. Local Scalars ..
- COMPLEX TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-* .. Intrinsic Functions ..
- INTRINSIC CONJG,REAL
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (N.LT.0) THEN
- INFO = 2
- ELSE IF (INCX.EQ.0) THEN
- INFO = 5
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('CHPR ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF ((N.EQ.0) .OR. (ALPHA.EQ.REAL(ZERO))) RETURN
-*
-* Set the start point in X if the increment is not unity.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of the array AP
-* are accessed sequentially with one pass through AP.
-*
- KK = 1
- IF (LSAME(UPLO,'U')) THEN
-*
-* Form A when upper triangle is stored in AP.
-*
- IF (INCX.EQ.1) THEN
- DO 20 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = ALPHA*CONJG(X(J))
- K = KK
- DO 10 I = 1,J - 1
- AP(K) = AP(K) + X(I)*TEMP
- K = K + 1
- 10 CONTINUE
- AP(KK+J-1) = REAL(AP(KK+J-1)) + REAL(X(J)*TEMP)
- ELSE
- AP(KK+J-1) = REAL(AP(KK+J-1))
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- JX = KX
- DO 40 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = ALPHA*CONJG(X(JX))
- IX = KX
- DO 30 K = KK,KK + J - 2
- AP(K) = AP(K) + X(IX)*TEMP
- IX = IX + INCX
- 30 CONTINUE
- AP(KK+J-1) = REAL(AP(KK+J-1)) + REAL(X(JX)*TEMP)
- ELSE
- AP(KK+J-1) = REAL(AP(KK+J-1))
- END IF
- JX = JX + INCX
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
-*
-* Form A when lower triangle is stored in AP.
-*
- IF (INCX.EQ.1) THEN
- DO 60 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = ALPHA*CONJG(X(J))
- AP(KK) = REAL(AP(KK)) + REAL(TEMP*X(J))
- K = KK + 1
- DO 50 I = J + 1,N
- AP(K) = AP(K) + X(I)*TEMP
- K = K + 1
- 50 CONTINUE
- ELSE
- AP(KK) = REAL(AP(KK))
- END IF
- KK = KK + N - J + 1
- 60 CONTINUE
- ELSE
- JX = KX
- DO 80 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = ALPHA*CONJG(X(JX))
- AP(KK) = REAL(AP(KK)) + REAL(TEMP*X(JX))
- IX = JX
- DO 70 K = KK + 1,KK + N - J
- IX = IX + INCX
- AP(K) = AP(K) + X(IX)*TEMP
- 70 CONTINUE
- ELSE
- AP(KK) = REAL(AP(KK))
- END IF
- JX = JX + INCX
- KK = KK + N - J + 1
- 80 CONTINUE
- END IF
- END IF
-*
- RETURN
-*
-* End of CHPR .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/chpr2.f b/resources/3rdparty/eigen/blas/chpr2.f
deleted file mode 100644
index a0020ef3e..000000000
--- a/resources/3rdparty/eigen/blas/chpr2.f
+++ /dev/null
@@ -1,255 +0,0 @@
- SUBROUTINE CHPR2(UPLO,N,ALPHA,X,INCX,Y,INCY,AP)
-* .. Scalar Arguments ..
- COMPLEX ALPHA
- INTEGER INCX,INCY,N
- CHARACTER UPLO
-* ..
-* .. Array Arguments ..
- COMPLEX AP(*),X(*),Y(*)
-* ..
-*
-* Purpose
-* =======
-*
-* CHPR2 performs the hermitian rank 2 operation
-*
-* A := alpha*x*conjg( y' ) + conjg( alpha )*y*conjg( x' ) + A,
-*
-* where alpha is a scalar, x and y are n element vectors and A is an
-* n by n hermitian matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the upper or lower
-* triangular part of the matrix A is supplied in the packed
-* array AP as follows:
-*
-* UPLO = 'U' or 'u' The upper triangular part of A is
-* supplied in AP.
-*
-* UPLO = 'L' or 'l' The lower triangular part of A is
-* supplied in AP.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* ALPHA - COMPLEX .
-* On entry, ALPHA specifies the scalar alpha.
-* Unchanged on exit.
-*
-* X - COMPLEX array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x.
-* Unchanged on exit.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Y - COMPLEX array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCY ) ).
-* Before entry, the incremented array Y must contain the n
-* element vector y.
-* Unchanged on exit.
-*
-* INCY - INTEGER.
-* On entry, INCY specifies the increment for the elements of
-* Y. INCY must not be zero.
-* Unchanged on exit.
-*
-* AP - COMPLEX array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular part of the hermitian matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-* and a( 2, 2 ) respectively, and so on. On exit, the array
-* AP is overwritten by the upper triangular part of the
-* updated matrix.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular part of the hermitian matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-* and a( 3, 1 ) respectively, and so on. On exit, the array
-* AP is overwritten by the lower triangular part of the
-* updated matrix.
-* Note that the imaginary parts of the diagonal elements need
-* not be set, they are assumed to be zero, and on exit they
-* are set to zero.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- COMPLEX ZERO
- PARAMETER (ZERO= (0.0E+0,0.0E+0))
-* ..
-* .. Local Scalars ..
- COMPLEX TEMP1,TEMP2
- INTEGER I,INFO,IX,IY,J,JX,JY,K,KK,KX,KY
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-* .. Intrinsic Functions ..
- INTRINSIC CONJG,REAL
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (N.LT.0) THEN
- INFO = 2
- ELSE IF (INCX.EQ.0) THEN
- INFO = 5
- ELSE IF (INCY.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('CHPR2 ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF ((N.EQ.0) .OR. (ALPHA.EQ.ZERO)) RETURN
-*
-* Set up the start points in X and Y if the increments are not both
-* unity.
-*
- IF ((INCX.NE.1) .OR. (INCY.NE.1)) THEN
- IF (INCX.GT.0) THEN
- KX = 1
- ELSE
- KX = 1 - (N-1)*INCX
- END IF
- IF (INCY.GT.0) THEN
- KY = 1
- ELSE
- KY = 1 - (N-1)*INCY
- END IF
- JX = KX
- JY = KY
- END IF
-*
-* Start the operations. In this version the elements of the array AP
-* are accessed sequentially with one pass through AP.
-*
- KK = 1
- IF (LSAME(UPLO,'U')) THEN
-*
-* Form A when upper triangle is stored in AP.
-*
- IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
- DO 20 J = 1,N
- IF ((X(J).NE.ZERO) .OR. (Y(J).NE.ZERO)) THEN
- TEMP1 = ALPHA*CONJG(Y(J))
- TEMP2 = CONJG(ALPHA*X(J))
- K = KK
- DO 10 I = 1,J - 1
- AP(K) = AP(K) + X(I)*TEMP1 + Y(I)*TEMP2
- K = K + 1
- 10 CONTINUE
- AP(KK+J-1) = REAL(AP(KK+J-1)) +
- + REAL(X(J)*TEMP1+Y(J)*TEMP2)
- ELSE
- AP(KK+J-1) = REAL(AP(KK+J-1))
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- DO 40 J = 1,N
- IF ((X(JX).NE.ZERO) .OR. (Y(JY).NE.ZERO)) THEN
- TEMP1 = ALPHA*CONJG(Y(JY))
- TEMP2 = CONJG(ALPHA*X(JX))
- IX = KX
- IY = KY
- DO 30 K = KK,KK + J - 2
- AP(K) = AP(K) + X(IX)*TEMP1 + Y(IY)*TEMP2
- IX = IX + INCX
- IY = IY + INCY
- 30 CONTINUE
- AP(KK+J-1) = REAL(AP(KK+J-1)) +
- + REAL(X(JX)*TEMP1+Y(JY)*TEMP2)
- ELSE
- AP(KK+J-1) = REAL(AP(KK+J-1))
- END IF
- JX = JX + INCX
- JY = JY + INCY
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
-*
-* Form A when lower triangle is stored in AP.
-*
- IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
- DO 60 J = 1,N
- IF ((X(J).NE.ZERO) .OR. (Y(J).NE.ZERO)) THEN
- TEMP1 = ALPHA*CONJG(Y(J))
- TEMP2 = CONJG(ALPHA*X(J))
- AP(KK) = REAL(AP(KK)) +
- + REAL(X(J)*TEMP1+Y(J)*TEMP2)
- K = KK + 1
- DO 50 I = J + 1,N
- AP(K) = AP(K) + X(I)*TEMP1 + Y(I)*TEMP2
- K = K + 1
- 50 CONTINUE
- ELSE
- AP(KK) = REAL(AP(KK))
- END IF
- KK = KK + N - J + 1
- 60 CONTINUE
- ELSE
- DO 80 J = 1,N
- IF ((X(JX).NE.ZERO) .OR. (Y(JY).NE.ZERO)) THEN
- TEMP1 = ALPHA*CONJG(Y(JY))
- TEMP2 = CONJG(ALPHA*X(JX))
- AP(KK) = REAL(AP(KK)) +
- + REAL(X(JX)*TEMP1+Y(JY)*TEMP2)
- IX = JX
- IY = JY
- DO 70 K = KK + 1,KK + N - J
- IX = IX + INCX
- IY = IY + INCY
- AP(K) = AP(K) + X(IX)*TEMP1 + Y(IY)*TEMP2
- 70 CONTINUE
- ELSE
- AP(KK) = REAL(AP(KK))
- END IF
- JX = JX + INCX
- JY = JY + INCY
- KK = KK + N - J + 1
- 80 CONTINUE
- END IF
- END IF
-*
- RETURN
-*
-* End of CHPR2 .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/common.h b/resources/3rdparty/eigen/blas/common.h
index b598c4e45..2bf642c6b 100644
--- a/resources/3rdparty/eigen/blas/common.h
+++ b/resources/3rdparty/eigen/blas/common.h
@@ -10,6 +10,9 @@
#ifndef EIGEN_BLAS_COMMON_H
#define EIGEN_BLAS_COMMON_H
+#include <Eigen/Core>
+#include <Eigen/Jacobi>
+
#include <iostream>
#include <complex>
@@ -48,7 +51,7 @@
: ((X)=='L' || (X)=='l') ? LO \
: INVALID)
-#define DIAG(X) ( ((X)=='N' || (X)=='N') ? NUNIT \
+#define DIAG(X) ( ((X)=='N' || (X)=='n') ? NUNIT \
: ((X)=='U' || (X)=='u') ? UNIT \
: INVALID)
@@ -68,12 +71,14 @@ inline bool check_uplo(const char* uplo)
return UPLO(*uplo)!=0xff;
}
-#include <Eigen/Core>
-#include <Eigen/Jacobi>
-
namespace Eigen {
#include "BandTriangularSolver.h"
+#include "GeneralRank1Update.h"
+#include "PackedSelfadjointProduct.h"
+#include "PackedTriangularMatrixVector.h"
+#include "PackedTriangularSolverVector.h"
+#include "Rank2Update.h"
}
using namespace Eigen;
diff --git a/resources/3rdparty/eigen/blas/ctpmv.f b/resources/3rdparty/eigen/blas/ctpmv.f
deleted file mode 100644
index b63742ccb..000000000
--- a/resources/3rdparty/eigen/blas/ctpmv.f
+++ /dev/null
@@ -1,329 +0,0 @@
- SUBROUTINE CTPMV(UPLO,TRANS,DIAG,N,AP,X,INCX)
-* .. Scalar Arguments ..
- INTEGER INCX,N
- CHARACTER DIAG,TRANS,UPLO
-* ..
-* .. Array Arguments ..
- COMPLEX AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* CTPMV performs one of the matrix-vector operations
-*
-* x := A*x, or x := A'*x, or x := conjg( A' )*x,
-*
-* where x is an n element vector and A is an n by n unit, or non-unit,
-* upper or lower triangular matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the matrix is an upper or
-* lower triangular matrix as follows:
-*
-* UPLO = 'U' or 'u' A is an upper triangular matrix.
-*
-* UPLO = 'L' or 'l' A is a lower triangular matrix.
-*
-* Unchanged on exit.
-*
-* TRANS - CHARACTER*1.
-* On entry, TRANS specifies the operation to be performed as
-* follows:
-*
-* TRANS = 'N' or 'n' x := A*x.
-*
-* TRANS = 'T' or 't' x := A'*x.
-*
-* TRANS = 'C' or 'c' x := conjg( A' )*x.
-*
-* Unchanged on exit.
-*
-* DIAG - CHARACTER*1.
-* On entry, DIAG specifies whether or not A is unit
-* triangular as follows:
-*
-* DIAG = 'U' or 'u' A is assumed to be unit triangular.
-*
-* DIAG = 'N' or 'n' A is not assumed to be unit
-* triangular.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* AP - COMPLEX array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 1, 2 ) and a( 2, 2 )
-* respectively, and so on.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 2, 1 ) and a( 3, 1 )
-* respectively, and so on.
-* Note that when DIAG = 'U' or 'u', the diagonal elements of
-* A are not referenced, but are assumed to be unity.
-* Unchanged on exit.
-*
-* X - COMPLEX array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x. On exit, X is overwritten with the
-* tranformed vector x.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- COMPLEX ZERO
- PARAMETER (ZERO= (0.0E+0,0.0E+0))
-* ..
-* .. Local Scalars ..
- COMPLEX TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
- LOGICAL NOCONJ,NOUNIT
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-* .. Intrinsic Functions ..
- INTRINSIC CONJG
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
- + .NOT.LSAME(TRANS,'C')) THEN
- INFO = 2
- ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
- INFO = 3
- ELSE IF (N.LT.0) THEN
- INFO = 4
- ELSE IF (INCX.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('CTPMV ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF (N.EQ.0) RETURN
-*
- NOCONJ = LSAME(TRANS,'T')
- NOUNIT = LSAME(DIAG,'N')
-*
-* Set up the start point in X if the increment is not unity. This
-* will be ( N - 1 )*INCX too small for descending loops.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of AP are
-* accessed sequentially with one pass through AP.
-*
- IF (LSAME(TRANS,'N')) THEN
-*
-* Form x:= A*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 20 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = X(J)
- K = KK
- DO 10 I = 1,J - 1
- X(I) = X(I) + TEMP*AP(K)
- K = K + 1
- 10 CONTINUE
- IF (NOUNIT) X(J) = X(J)*AP(KK+J-1)
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- JX = KX
- DO 40 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = X(JX)
- IX = KX
- DO 30 K = KK,KK + J - 2
- X(IX) = X(IX) + TEMP*AP(K)
- IX = IX + INCX
- 30 CONTINUE
- IF (NOUNIT) X(JX) = X(JX)*AP(KK+J-1)
- END IF
- JX = JX + INCX
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 60 J = N,1,-1
- IF (X(J).NE.ZERO) THEN
- TEMP = X(J)
- K = KK
- DO 50 I = N,J + 1,-1
- X(I) = X(I) + TEMP*AP(K)
- K = K - 1
- 50 CONTINUE
- IF (NOUNIT) X(J) = X(J)*AP(KK-N+J)
- END IF
- KK = KK - (N-J+1)
- 60 CONTINUE
- ELSE
- KX = KX + (N-1)*INCX
- JX = KX
- DO 80 J = N,1,-1
- IF (X(JX).NE.ZERO) THEN
- TEMP = X(JX)
- IX = KX
- DO 70 K = KK,KK - (N- (J+1)),-1
- X(IX) = X(IX) + TEMP*AP(K)
- IX = IX - INCX
- 70 CONTINUE
- IF (NOUNIT) X(JX) = X(JX)*AP(KK-N+J)
- END IF
- JX = JX - INCX
- KK = KK - (N-J+1)
- 80 CONTINUE
- END IF
- END IF
- ELSE
-*
-* Form x := A'*x or x := conjg( A' )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 110 J = N,1,-1
- TEMP = X(J)
- K = KK - 1
- IF (NOCONJ) THEN
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 90 I = J - 1,1,-1
- TEMP = TEMP + AP(K)*X(I)
- K = K - 1
- 90 CONTINUE
- ELSE
- IF (NOUNIT) TEMP = TEMP*CONJG(AP(KK))
- DO 100 I = J - 1,1,-1
- TEMP = TEMP + CONJG(AP(K))*X(I)
- K = K - 1
- 100 CONTINUE
- END IF
- X(J) = TEMP
- KK = KK - J
- 110 CONTINUE
- ELSE
- JX = KX + (N-1)*INCX
- DO 140 J = N,1,-1
- TEMP = X(JX)
- IX = JX
- IF (NOCONJ) THEN
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 120 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- TEMP = TEMP + AP(K)*X(IX)
- 120 CONTINUE
- ELSE
- IF (NOUNIT) TEMP = TEMP*CONJG(AP(KK))
- DO 130 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- TEMP = TEMP + CONJG(AP(K))*X(IX)
- 130 CONTINUE
- END IF
- X(JX) = TEMP
- JX = JX - INCX
- KK = KK - J
- 140 CONTINUE
- END IF
- ELSE
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 170 J = 1,N
- TEMP = X(J)
- K = KK + 1
- IF (NOCONJ) THEN
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 150 I = J + 1,N
- TEMP = TEMP + AP(K)*X(I)
- K = K + 1
- 150 CONTINUE
- ELSE
- IF (NOUNIT) TEMP = TEMP*CONJG(AP(KK))
- DO 160 I = J + 1,N
- TEMP = TEMP + CONJG(AP(K))*X(I)
- K = K + 1
- 160 CONTINUE
- END IF
- X(J) = TEMP
- KK = KK + (N-J+1)
- 170 CONTINUE
- ELSE
- JX = KX
- DO 200 J = 1,N
- TEMP = X(JX)
- IX = JX
- IF (NOCONJ) THEN
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 180 K = KK + 1,KK + N - J
- IX = IX + INCX
- TEMP = TEMP + AP(K)*X(IX)
- 180 CONTINUE
- ELSE
- IF (NOUNIT) TEMP = TEMP*CONJG(AP(KK))
- DO 190 K = KK + 1,KK + N - J
- IX = IX + INCX
- TEMP = TEMP + CONJG(AP(K))*X(IX)
- 190 CONTINUE
- END IF
- X(JX) = TEMP
- JX = JX + INCX
- KK = KK + (N-J+1)
- 200 CONTINUE
- END IF
- END IF
- END IF
-*
- RETURN
-*
-* End of CTPMV .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/ctpsv.f b/resources/3rdparty/eigen/blas/ctpsv.f
deleted file mode 100644
index 1804797ea..000000000
--- a/resources/3rdparty/eigen/blas/ctpsv.f
+++ /dev/null
@@ -1,332 +0,0 @@
- SUBROUTINE CTPSV(UPLO,TRANS,DIAG,N,AP,X,INCX)
-* .. Scalar Arguments ..
- INTEGER INCX,N
- CHARACTER DIAG,TRANS,UPLO
-* ..
-* .. Array Arguments ..
- COMPLEX AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* CTPSV solves one of the systems of equations
-*
-* A*x = b, or A'*x = b, or conjg( A' )*x = b,
-*
-* where b and x are n element vectors and A is an n by n unit, or
-* non-unit, upper or lower triangular matrix, supplied in packed form.
-*
-* No test for singularity or near-singularity is included in this
-* routine. Such tests must be performed before calling this routine.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the matrix is an upper or
-* lower triangular matrix as follows:
-*
-* UPLO = 'U' or 'u' A is an upper triangular matrix.
-*
-* UPLO = 'L' or 'l' A is a lower triangular matrix.
-*
-* Unchanged on exit.
-*
-* TRANS - CHARACTER*1.
-* On entry, TRANS specifies the equations to be solved as
-* follows:
-*
-* TRANS = 'N' or 'n' A*x = b.
-*
-* TRANS = 'T' or 't' A'*x = b.
-*
-* TRANS = 'C' or 'c' conjg( A' )*x = b.
-*
-* Unchanged on exit.
-*
-* DIAG - CHARACTER*1.
-* On entry, DIAG specifies whether or not A is unit
-* triangular as follows:
-*
-* DIAG = 'U' or 'u' A is assumed to be unit triangular.
-*
-* DIAG = 'N' or 'n' A is not assumed to be unit
-* triangular.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* AP - COMPLEX array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 1, 2 ) and a( 2, 2 )
-* respectively, and so on.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 2, 1 ) and a( 3, 1 )
-* respectively, and so on.
-* Note that when DIAG = 'U' or 'u', the diagonal elements of
-* A are not referenced, but are assumed to be unity.
-* Unchanged on exit.
-*
-* X - COMPLEX array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element right-hand side vector b. On exit, X is overwritten
-* with the solution vector x.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- COMPLEX ZERO
- PARAMETER (ZERO= (0.0E+0,0.0E+0))
-* ..
-* .. Local Scalars ..
- COMPLEX TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
- LOGICAL NOCONJ,NOUNIT
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-* .. Intrinsic Functions ..
- INTRINSIC CONJG
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
- + .NOT.LSAME(TRANS,'C')) THEN
- INFO = 2
- ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
- INFO = 3
- ELSE IF (N.LT.0) THEN
- INFO = 4
- ELSE IF (INCX.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('CTPSV ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF (N.EQ.0) RETURN
-*
- NOCONJ = LSAME(TRANS,'T')
- NOUNIT = LSAME(DIAG,'N')
-*
-* Set up the start point in X if the increment is not unity. This
-* will be ( N - 1 )*INCX too small for descending loops.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of AP are
-* accessed sequentially with one pass through AP.
-*
- IF (LSAME(TRANS,'N')) THEN
-*
-* Form x := inv( A )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 20 J = N,1,-1
- IF (X(J).NE.ZERO) THEN
- IF (NOUNIT) X(J) = X(J)/AP(KK)
- TEMP = X(J)
- K = KK - 1
- DO 10 I = J - 1,1,-1
- X(I) = X(I) - TEMP*AP(K)
- K = K - 1
- 10 CONTINUE
- END IF
- KK = KK - J
- 20 CONTINUE
- ELSE
- JX = KX + (N-1)*INCX
- DO 40 J = N,1,-1
- IF (X(JX).NE.ZERO) THEN
- IF (NOUNIT) X(JX) = X(JX)/AP(KK)
- TEMP = X(JX)
- IX = JX
- DO 30 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- X(IX) = X(IX) - TEMP*AP(K)
- 30 CONTINUE
- END IF
- JX = JX - INCX
- KK = KK - J
- 40 CONTINUE
- END IF
- ELSE
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 60 J = 1,N
- IF (X(J).NE.ZERO) THEN
- IF (NOUNIT) X(J) = X(J)/AP(KK)
- TEMP = X(J)
- K = KK + 1
- DO 50 I = J + 1,N
- X(I) = X(I) - TEMP*AP(K)
- K = K + 1
- 50 CONTINUE
- END IF
- KK = KK + (N-J+1)
- 60 CONTINUE
- ELSE
- JX = KX
- DO 80 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- IF (NOUNIT) X(JX) = X(JX)/AP(KK)
- TEMP = X(JX)
- IX = JX
- DO 70 K = KK + 1,KK + N - J
- IX = IX + INCX
- X(IX) = X(IX) - TEMP*AP(K)
- 70 CONTINUE
- END IF
- JX = JX + INCX
- KK = KK + (N-J+1)
- 80 CONTINUE
- END IF
- END IF
- ELSE
-*
-* Form x := inv( A' )*x or x := inv( conjg( A' ) )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 110 J = 1,N
- TEMP = X(J)
- K = KK
- IF (NOCONJ) THEN
- DO 90 I = 1,J - 1
- TEMP = TEMP - AP(K)*X(I)
- K = K + 1
- 90 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK+J-1)
- ELSE
- DO 100 I = 1,J - 1
- TEMP = TEMP - CONJG(AP(K))*X(I)
- K = K + 1
- 100 CONTINUE
- IF (NOUNIT) TEMP = TEMP/CONJG(AP(KK+J-1))
- END IF
- X(J) = TEMP
- KK = KK + J
- 110 CONTINUE
- ELSE
- JX = KX
- DO 140 J = 1,N
- TEMP = X(JX)
- IX = KX
- IF (NOCONJ) THEN
- DO 120 K = KK,KK + J - 2
- TEMP = TEMP - AP(K)*X(IX)
- IX = IX + INCX
- 120 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK+J-1)
- ELSE
- DO 130 K = KK,KK + J - 2
- TEMP = TEMP - CONJG(AP(K))*X(IX)
- IX = IX + INCX
- 130 CONTINUE
- IF (NOUNIT) TEMP = TEMP/CONJG(AP(KK+J-1))
- END IF
- X(JX) = TEMP
- JX = JX + INCX
- KK = KK + J
- 140 CONTINUE
- END IF
- ELSE
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 170 J = N,1,-1
- TEMP = X(J)
- K = KK
- IF (NOCONJ) THEN
- DO 150 I = N,J + 1,-1
- TEMP = TEMP - AP(K)*X(I)
- K = K - 1
- 150 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK-N+J)
- ELSE
- DO 160 I = N,J + 1,-1
- TEMP = TEMP - CONJG(AP(K))*X(I)
- K = K - 1
- 160 CONTINUE
- IF (NOUNIT) TEMP = TEMP/CONJG(AP(KK-N+J))
- END IF
- X(J) = TEMP
- KK = KK - (N-J+1)
- 170 CONTINUE
- ELSE
- KX = KX + (N-1)*INCX
- JX = KX
- DO 200 J = N,1,-1
- TEMP = X(JX)
- IX = KX
- IF (NOCONJ) THEN
- DO 180 K = KK,KK - (N- (J+1)),-1
- TEMP = TEMP - AP(K)*X(IX)
- IX = IX - INCX
- 180 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK-N+J)
- ELSE
- DO 190 K = KK,KK - (N- (J+1)),-1
- TEMP = TEMP - CONJG(AP(K))*X(IX)
- IX = IX - INCX
- 190 CONTINUE
- IF (NOUNIT) TEMP = TEMP/CONJG(AP(KK-N+J))
- END IF
- X(JX) = TEMP
- JX = JX - INCX
- KK = KK - (N-J+1)
- 200 CONTINUE
- END IF
- END IF
- END IF
-*
- RETURN
-*
-* End of CTPSV .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/double.cpp b/resources/3rdparty/eigen/blas/double.cpp
index cad2f63ec..8fd0709ba 100644
--- a/resources/3rdparty/eigen/blas/double.cpp
+++ b/resources/3rdparty/eigen/blas/double.cpp
@@ -2,6 +2,7 @@
// for linear algebra.
//
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
//
// 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
@@ -17,3 +18,16 @@
#include "level2_impl.h"
#include "level2_real_impl.h"
#include "level3_impl.h"
+
+double BLASFUNC(dsdot)(int* n, float* x, int* incx, float* y, int* incy)
+{
+ if(*n<=0) return 0;
+
+ if(*incx==1 && *incy==1) return (vector(x,*n).cast<double>().cwiseProduct(vector(y,*n).cast<double>())).sum();
+ else if(*incx>0 && *incy>0) return (vector(x,*n,*incx).cast<double>().cwiseProduct(vector(y,*n,*incy).cast<double>())).sum();
+ else if(*incx<0 && *incy>0) return (vector(x,*n,-*incx).reverse().cast<double>().cwiseProduct(vector(y,*n,*incy).cast<double>())).sum();
+ else if(*incx>0 && *incy<0) return (vector(x,*n,*incx).cast<double>().cwiseProduct(vector(y,*n,-*incy).reverse().cast<double>())).sum();
+ else if(*incx<0 && *incy<0) return (vector(x,*n,-*incx).reverse().cast<double>().cwiseProduct(vector(y,*n,-*incy).reverse().cast<double>())).sum();
+ else return 0;
+}
+
diff --git a/resources/3rdparty/eigen/blas/dspr.f b/resources/3rdparty/eigen/blas/dspr.f
deleted file mode 100644
index 538e4f76b..000000000
--- a/resources/3rdparty/eigen/blas/dspr.f
+++ /dev/null
@@ -1,202 +0,0 @@
- SUBROUTINE DSPR(UPLO,N,ALPHA,X,INCX,AP)
-* .. Scalar Arguments ..
- DOUBLE PRECISION ALPHA
- INTEGER INCX,N
- CHARACTER UPLO
-* ..
-* .. Array Arguments ..
- DOUBLE PRECISION AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* DSPR performs the symmetric rank 1 operation
-*
-* A := alpha*x*x' + A,
-*
-* where alpha is a real scalar, x is an n element vector and A is an
-* n by n symmetric matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the upper or lower
-* triangular part of the matrix A is supplied in the packed
-* array AP as follows:
-*
-* UPLO = 'U' or 'u' The upper triangular part of A is
-* supplied in AP.
-*
-* UPLO = 'L' or 'l' The lower triangular part of A is
-* supplied in AP.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* ALPHA - DOUBLE PRECISION.
-* On entry, ALPHA specifies the scalar alpha.
-* Unchanged on exit.
-*
-* X - DOUBLE PRECISION array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x.
-* Unchanged on exit.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* AP - DOUBLE PRECISION array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular part of the symmetric matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-* and a( 2, 2 ) respectively, and so on. On exit, the array
-* AP is overwritten by the upper triangular part of the
-* updated matrix.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular part of the symmetric matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-* and a( 3, 1 ) respectively, and so on. On exit, the array
-* AP is overwritten by the lower triangular part of the
-* updated matrix.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- DOUBLE PRECISION ZERO
- PARAMETER (ZERO=0.0D+0)
-* ..
-* .. Local Scalars ..
- DOUBLE PRECISION TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (N.LT.0) THEN
- INFO = 2
- ELSE IF (INCX.EQ.0) THEN
- INFO = 5
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('DSPR ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF ((N.EQ.0) .OR. (ALPHA.EQ.ZERO)) RETURN
-*
-* Set the start point in X if the increment is not unity.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of the array AP
-* are accessed sequentially with one pass through AP.
-*
- KK = 1
- IF (LSAME(UPLO,'U')) THEN
-*
-* Form A when upper triangle is stored in AP.
-*
- IF (INCX.EQ.1) THEN
- DO 20 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = ALPHA*X(J)
- K = KK
- DO 10 I = 1,J
- AP(K) = AP(K) + X(I)*TEMP
- K = K + 1
- 10 CONTINUE
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- JX = KX
- DO 40 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = ALPHA*X(JX)
- IX = KX
- DO 30 K = KK,KK + J - 1
- AP(K) = AP(K) + X(IX)*TEMP
- IX = IX + INCX
- 30 CONTINUE
- END IF
- JX = JX + INCX
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
-*
-* Form A when lower triangle is stored in AP.
-*
- IF (INCX.EQ.1) THEN
- DO 60 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = ALPHA*X(J)
- K = KK
- DO 50 I = J,N
- AP(K) = AP(K) + X(I)*TEMP
- K = K + 1
- 50 CONTINUE
- END IF
- KK = KK + N - J + 1
- 60 CONTINUE
- ELSE
- JX = KX
- DO 80 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = ALPHA*X(JX)
- IX = JX
- DO 70 K = KK,KK + N - J
- AP(K) = AP(K) + X(IX)*TEMP
- IX = IX + INCX
- 70 CONTINUE
- END IF
- JX = JX + INCX
- KK = KK + N - J + 1
- 80 CONTINUE
- END IF
- END IF
-*
- RETURN
-*
-* End of DSPR .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/dspr2.f b/resources/3rdparty/eigen/blas/dspr2.f
deleted file mode 100644
index 6f6b54a8c..000000000
--- a/resources/3rdparty/eigen/blas/dspr2.f
+++ /dev/null
@@ -1,233 +0,0 @@
- SUBROUTINE DSPR2(UPLO,N,ALPHA,X,INCX,Y,INCY,AP)
-* .. Scalar Arguments ..
- DOUBLE PRECISION ALPHA
- INTEGER INCX,INCY,N
- CHARACTER UPLO
-* ..
-* .. Array Arguments ..
- DOUBLE PRECISION AP(*),X(*),Y(*)
-* ..
-*
-* Purpose
-* =======
-*
-* DSPR2 performs the symmetric rank 2 operation
-*
-* A := alpha*x*y' + alpha*y*x' + A,
-*
-* where alpha is a scalar, x and y are n element vectors and A is an
-* n by n symmetric matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the upper or lower
-* triangular part of the matrix A is supplied in the packed
-* array AP as follows:
-*
-* UPLO = 'U' or 'u' The upper triangular part of A is
-* supplied in AP.
-*
-* UPLO = 'L' or 'l' The lower triangular part of A is
-* supplied in AP.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* ALPHA - DOUBLE PRECISION.
-* On entry, ALPHA specifies the scalar alpha.
-* Unchanged on exit.
-*
-* X - DOUBLE PRECISION array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x.
-* Unchanged on exit.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Y - DOUBLE PRECISION array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCY ) ).
-* Before entry, the incremented array Y must contain the n
-* element vector y.
-* Unchanged on exit.
-*
-* INCY - INTEGER.
-* On entry, INCY specifies the increment for the elements of
-* Y. INCY must not be zero.
-* Unchanged on exit.
-*
-* AP - DOUBLE PRECISION array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular part of the symmetric matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-* and a( 2, 2 ) respectively, and so on. On exit, the array
-* AP is overwritten by the upper triangular part of the
-* updated matrix.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular part of the symmetric matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-* and a( 3, 1 ) respectively, and so on. On exit, the array
-* AP is overwritten by the lower triangular part of the
-* updated matrix.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- DOUBLE PRECISION ZERO
- PARAMETER (ZERO=0.0D+0)
-* ..
-* .. Local Scalars ..
- DOUBLE PRECISION TEMP1,TEMP2
- INTEGER I,INFO,IX,IY,J,JX,JY,K,KK,KX,KY
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (N.LT.0) THEN
- INFO = 2
- ELSE IF (INCX.EQ.0) THEN
- INFO = 5
- ELSE IF (INCY.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('DSPR2 ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF ((N.EQ.0) .OR. (ALPHA.EQ.ZERO)) RETURN
-*
-* Set up the start points in X and Y if the increments are not both
-* unity.
-*
- IF ((INCX.NE.1) .OR. (INCY.NE.1)) THEN
- IF (INCX.GT.0) THEN
- KX = 1
- ELSE
- KX = 1 - (N-1)*INCX
- END IF
- IF (INCY.GT.0) THEN
- KY = 1
- ELSE
- KY = 1 - (N-1)*INCY
- END IF
- JX = KX
- JY = KY
- END IF
-*
-* Start the operations. In this version the elements of the array AP
-* are accessed sequentially with one pass through AP.
-*
- KK = 1
- IF (LSAME(UPLO,'U')) THEN
-*
-* Form A when upper triangle is stored in AP.
-*
- IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
- DO 20 J = 1,N
- IF ((X(J).NE.ZERO) .OR. (Y(J).NE.ZERO)) THEN
- TEMP1 = ALPHA*Y(J)
- TEMP2 = ALPHA*X(J)
- K = KK
- DO 10 I = 1,J
- AP(K) = AP(K) + X(I)*TEMP1 + Y(I)*TEMP2
- K = K + 1
- 10 CONTINUE
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- DO 40 J = 1,N
- IF ((X(JX).NE.ZERO) .OR. (Y(JY).NE.ZERO)) THEN
- TEMP1 = ALPHA*Y(JY)
- TEMP2 = ALPHA*X(JX)
- IX = KX
- IY = KY
- DO 30 K = KK,KK + J - 1
- AP(K) = AP(K) + X(IX)*TEMP1 + Y(IY)*TEMP2
- IX = IX + INCX
- IY = IY + INCY
- 30 CONTINUE
- END IF
- JX = JX + INCX
- JY = JY + INCY
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
-*
-* Form A when lower triangle is stored in AP.
-*
- IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
- DO 60 J = 1,N
- IF ((X(J).NE.ZERO) .OR. (Y(J).NE.ZERO)) THEN
- TEMP1 = ALPHA*Y(J)
- TEMP2 = ALPHA*X(J)
- K = KK
- DO 50 I = J,N
- AP(K) = AP(K) + X(I)*TEMP1 + Y(I)*TEMP2
- K = K + 1
- 50 CONTINUE
- END IF
- KK = KK + N - J + 1
- 60 CONTINUE
- ELSE
- DO 80 J = 1,N
- IF ((X(JX).NE.ZERO) .OR. (Y(JY).NE.ZERO)) THEN
- TEMP1 = ALPHA*Y(JY)
- TEMP2 = ALPHA*X(JX)
- IX = JX
- IY = JY
- DO 70 K = KK,KK + N - J
- AP(K) = AP(K) + X(IX)*TEMP1 + Y(IY)*TEMP2
- IX = IX + INCX
- IY = IY + INCY
- 70 CONTINUE
- END IF
- JX = JX + INCX
- JY = JY + INCY
- KK = KK + N - J + 1
- 80 CONTINUE
- END IF
- END IF
-*
- RETURN
-*
-* End of DSPR2 .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/dtpmv.f b/resources/3rdparty/eigen/blas/dtpmv.f
deleted file mode 100644
index c5bc112dc..000000000
--- a/resources/3rdparty/eigen/blas/dtpmv.f
+++ /dev/null
@@ -1,293 +0,0 @@
- SUBROUTINE DTPMV(UPLO,TRANS,DIAG,N,AP,X,INCX)
-* .. Scalar Arguments ..
- INTEGER INCX,N
- CHARACTER DIAG,TRANS,UPLO
-* ..
-* .. Array Arguments ..
- DOUBLE PRECISION AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* DTPMV performs one of the matrix-vector operations
-*
-* x := A*x, or x := A'*x,
-*
-* where x is an n element vector and A is an n by n unit, or non-unit,
-* upper or lower triangular matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the matrix is an upper or
-* lower triangular matrix as follows:
-*
-* UPLO = 'U' or 'u' A is an upper triangular matrix.
-*
-* UPLO = 'L' or 'l' A is a lower triangular matrix.
-*
-* Unchanged on exit.
-*
-* TRANS - CHARACTER*1.
-* On entry, TRANS specifies the operation to be performed as
-* follows:
-*
-* TRANS = 'N' or 'n' x := A*x.
-*
-* TRANS = 'T' or 't' x := A'*x.
-*
-* TRANS = 'C' or 'c' x := A'*x.
-*
-* Unchanged on exit.
-*
-* DIAG - CHARACTER*1.
-* On entry, DIAG specifies whether or not A is unit
-* triangular as follows:
-*
-* DIAG = 'U' or 'u' A is assumed to be unit triangular.
-*
-* DIAG = 'N' or 'n' A is not assumed to be unit
-* triangular.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* AP - DOUBLE PRECISION array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 1, 2 ) and a( 2, 2 )
-* respectively, and so on.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 2, 1 ) and a( 3, 1 )
-* respectively, and so on.
-* Note that when DIAG = 'U' or 'u', the diagonal elements of
-* A are not referenced, but are assumed to be unity.
-* Unchanged on exit.
-*
-* X - DOUBLE PRECISION array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x. On exit, X is overwritten with the
-* tranformed vector x.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- DOUBLE PRECISION ZERO
- PARAMETER (ZERO=0.0D+0)
-* ..
-* .. Local Scalars ..
- DOUBLE PRECISION TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
- LOGICAL NOUNIT
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
- + .NOT.LSAME(TRANS,'C')) THEN
- INFO = 2
- ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
- INFO = 3
- ELSE IF (N.LT.0) THEN
- INFO = 4
- ELSE IF (INCX.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('DTPMV ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF (N.EQ.0) RETURN
-*
- NOUNIT = LSAME(DIAG,'N')
-*
-* Set up the start point in X if the increment is not unity. This
-* will be ( N - 1 )*INCX too small for descending loops.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of AP are
-* accessed sequentially with one pass through AP.
-*
- IF (LSAME(TRANS,'N')) THEN
-*
-* Form x:= A*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 20 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = X(J)
- K = KK
- DO 10 I = 1,J - 1
- X(I) = X(I) + TEMP*AP(K)
- K = K + 1
- 10 CONTINUE
- IF (NOUNIT) X(J) = X(J)*AP(KK+J-1)
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- JX = KX
- DO 40 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = X(JX)
- IX = KX
- DO 30 K = KK,KK + J - 2
- X(IX) = X(IX) + TEMP*AP(K)
- IX = IX + INCX
- 30 CONTINUE
- IF (NOUNIT) X(JX) = X(JX)*AP(KK+J-1)
- END IF
- JX = JX + INCX
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 60 J = N,1,-1
- IF (X(J).NE.ZERO) THEN
- TEMP = X(J)
- K = KK
- DO 50 I = N,J + 1,-1
- X(I) = X(I) + TEMP*AP(K)
- K = K - 1
- 50 CONTINUE
- IF (NOUNIT) X(J) = X(J)*AP(KK-N+J)
- END IF
- KK = KK - (N-J+1)
- 60 CONTINUE
- ELSE
- KX = KX + (N-1)*INCX
- JX = KX
- DO 80 J = N,1,-1
- IF (X(JX).NE.ZERO) THEN
- TEMP = X(JX)
- IX = KX
- DO 70 K = KK,KK - (N- (J+1)),-1
- X(IX) = X(IX) + TEMP*AP(K)
- IX = IX - INCX
- 70 CONTINUE
- IF (NOUNIT) X(JX) = X(JX)*AP(KK-N+J)
- END IF
- JX = JX - INCX
- KK = KK - (N-J+1)
- 80 CONTINUE
- END IF
- END IF
- ELSE
-*
-* Form x := A'*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 100 J = N,1,-1
- TEMP = X(J)
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- K = KK - 1
- DO 90 I = J - 1,1,-1
- TEMP = TEMP + AP(K)*X(I)
- K = K - 1
- 90 CONTINUE
- X(J) = TEMP
- KK = KK - J
- 100 CONTINUE
- ELSE
- JX = KX + (N-1)*INCX
- DO 120 J = N,1,-1
- TEMP = X(JX)
- IX = JX
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 110 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- TEMP = TEMP + AP(K)*X(IX)
- 110 CONTINUE
- X(JX) = TEMP
- JX = JX - INCX
- KK = KK - J
- 120 CONTINUE
- END IF
- ELSE
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 140 J = 1,N
- TEMP = X(J)
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- K = KK + 1
- DO 130 I = J + 1,N
- TEMP = TEMP + AP(K)*X(I)
- K = K + 1
- 130 CONTINUE
- X(J) = TEMP
- KK = KK + (N-J+1)
- 140 CONTINUE
- ELSE
- JX = KX
- DO 160 J = 1,N
- TEMP = X(JX)
- IX = JX
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 150 K = KK + 1,KK + N - J
- IX = IX + INCX
- TEMP = TEMP + AP(K)*X(IX)
- 150 CONTINUE
- X(JX) = TEMP
- JX = JX + INCX
- KK = KK + (N-J+1)
- 160 CONTINUE
- END IF
- END IF
- END IF
-*
- RETURN
-*
-* End of DTPMV .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/dtpsv.f b/resources/3rdparty/eigen/blas/dtpsv.f
deleted file mode 100644
index c7e58d32f..000000000
--- a/resources/3rdparty/eigen/blas/dtpsv.f
+++ /dev/null
@@ -1,296 +0,0 @@
- SUBROUTINE DTPSV(UPLO,TRANS,DIAG,N,AP,X,INCX)
-* .. Scalar Arguments ..
- INTEGER INCX,N
- CHARACTER DIAG,TRANS,UPLO
-* ..
-* .. Array Arguments ..
- DOUBLE PRECISION AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* DTPSV solves one of the systems of equations
-*
-* A*x = b, or A'*x = b,
-*
-* where b and x are n element vectors and A is an n by n unit, or
-* non-unit, upper or lower triangular matrix, supplied in packed form.
-*
-* No test for singularity or near-singularity is included in this
-* routine. Such tests must be performed before calling this routine.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the matrix is an upper or
-* lower triangular matrix as follows:
-*
-* UPLO = 'U' or 'u' A is an upper triangular matrix.
-*
-* UPLO = 'L' or 'l' A is a lower triangular matrix.
-*
-* Unchanged on exit.
-*
-* TRANS - CHARACTER*1.
-* On entry, TRANS specifies the equations to be solved as
-* follows:
-*
-* TRANS = 'N' or 'n' A*x = b.
-*
-* TRANS = 'T' or 't' A'*x = b.
-*
-* TRANS = 'C' or 'c' A'*x = b.
-*
-* Unchanged on exit.
-*
-* DIAG - CHARACTER*1.
-* On entry, DIAG specifies whether or not A is unit
-* triangular as follows:
-*
-* DIAG = 'U' or 'u' A is assumed to be unit triangular.
-*
-* DIAG = 'N' or 'n' A is not assumed to be unit
-* triangular.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* AP - DOUBLE PRECISION array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 1, 2 ) and a( 2, 2 )
-* respectively, and so on.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 2, 1 ) and a( 3, 1 )
-* respectively, and so on.
-* Note that when DIAG = 'U' or 'u', the diagonal elements of
-* A are not referenced, but are assumed to be unity.
-* Unchanged on exit.
-*
-* X - DOUBLE PRECISION array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element right-hand side vector b. On exit, X is overwritten
-* with the solution vector x.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- DOUBLE PRECISION ZERO
- PARAMETER (ZERO=0.0D+0)
-* ..
-* .. Local Scalars ..
- DOUBLE PRECISION TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
- LOGICAL NOUNIT
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
- + .NOT.LSAME(TRANS,'C')) THEN
- INFO = 2
- ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
- INFO = 3
- ELSE IF (N.LT.0) THEN
- INFO = 4
- ELSE IF (INCX.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('DTPSV ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF (N.EQ.0) RETURN
-*
- NOUNIT = LSAME(DIAG,'N')
-*
-* Set up the start point in X if the increment is not unity. This
-* will be ( N - 1 )*INCX too small for descending loops.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of AP are
-* accessed sequentially with one pass through AP.
-*
- IF (LSAME(TRANS,'N')) THEN
-*
-* Form x := inv( A )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 20 J = N,1,-1
- IF (X(J).NE.ZERO) THEN
- IF (NOUNIT) X(J) = X(J)/AP(KK)
- TEMP = X(J)
- K = KK - 1
- DO 10 I = J - 1,1,-1
- X(I) = X(I) - TEMP*AP(K)
- K = K - 1
- 10 CONTINUE
- END IF
- KK = KK - J
- 20 CONTINUE
- ELSE
- JX = KX + (N-1)*INCX
- DO 40 J = N,1,-1
- IF (X(JX).NE.ZERO) THEN
- IF (NOUNIT) X(JX) = X(JX)/AP(KK)
- TEMP = X(JX)
- IX = JX
- DO 30 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- X(IX) = X(IX) - TEMP*AP(K)
- 30 CONTINUE
- END IF
- JX = JX - INCX
- KK = KK - J
- 40 CONTINUE
- END IF
- ELSE
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 60 J = 1,N
- IF (X(J).NE.ZERO) THEN
- IF (NOUNIT) X(J) = X(J)/AP(KK)
- TEMP = X(J)
- K = KK + 1
- DO 50 I = J + 1,N
- X(I) = X(I) - TEMP*AP(K)
- K = K + 1
- 50 CONTINUE
- END IF
- KK = KK + (N-J+1)
- 60 CONTINUE
- ELSE
- JX = KX
- DO 80 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- IF (NOUNIT) X(JX) = X(JX)/AP(KK)
- TEMP = X(JX)
- IX = JX
- DO 70 K = KK + 1,KK + N - J
- IX = IX + INCX
- X(IX) = X(IX) - TEMP*AP(K)
- 70 CONTINUE
- END IF
- JX = JX + INCX
- KK = KK + (N-J+1)
- 80 CONTINUE
- END IF
- END IF
- ELSE
-*
-* Form x := inv( A' )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 100 J = 1,N
- TEMP = X(J)
- K = KK
- DO 90 I = 1,J - 1
- TEMP = TEMP - AP(K)*X(I)
- K = K + 1
- 90 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK+J-1)
- X(J) = TEMP
- KK = KK + J
- 100 CONTINUE
- ELSE
- JX = KX
- DO 120 J = 1,N
- TEMP = X(JX)
- IX = KX
- DO 110 K = KK,KK + J - 2
- TEMP = TEMP - AP(K)*X(IX)
- IX = IX + INCX
- 110 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK+J-1)
- X(JX) = TEMP
- JX = JX + INCX
- KK = KK + J
- 120 CONTINUE
- END IF
- ELSE
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 140 J = N,1,-1
- TEMP = X(J)
- K = KK
- DO 130 I = N,J + 1,-1
- TEMP = TEMP - AP(K)*X(I)
- K = K - 1
- 130 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK-N+J)
- X(J) = TEMP
- KK = KK - (N-J+1)
- 140 CONTINUE
- ELSE
- KX = KX + (N-1)*INCX
- JX = KX
- DO 160 J = N,1,-1
- TEMP = X(JX)
- IX = KX
- DO 150 K = KK,KK - (N- (J+1)),-1
- TEMP = TEMP - AP(K)*X(IX)
- IX = IX - INCX
- 150 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK-N+J)
- X(JX) = TEMP
- JX = JX - INCX
- KK = KK - (N-J+1)
- 160 CONTINUE
- END IF
- END IF
- END IF
-*
- RETURN
-*
-* End of DTPSV .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/level2_cplx_impl.h b/resources/3rdparty/eigen/blas/level2_cplx_impl.h
index 7878f2a16..f52d384a9 100644
--- a/resources/3rdparty/eigen/blas/level2_cplx_impl.h
+++ b/resources/3rdparty/eigen/blas/level2_cplx_impl.h
@@ -18,6 +18,21 @@
*/
int EIGEN_BLAS_FUNC(hemv)(char *uplo, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *px, int *incx, RealScalar *pbeta, RealScalar *py, int *incy)
{
+ typedef void (*functype)(int, const Scalar*, int, const Scalar*, int, Scalar*, Scalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Upper,false,false>::run);
+ func[LO] = (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Lower,false,false>::run);
+
+ init = true;
+ }
+
Scalar* a = reinterpret_cast<Scalar*>(pa);
Scalar* x = reinterpret_cast<Scalar*>(px);
Scalar* y = reinterpret_cast<Scalar*>(py);
@@ -48,9 +63,11 @@ int EIGEN_BLAS_FUNC(hemv)(char *uplo, int *n, RealScalar *palpha, RealScalar *pa
if(alpha!=Scalar(0))
{
- // TODO performs a direct call to the underlying implementation function
- if(UPLO(*uplo)==UP) vector(actual_y,*n).noalias() += matrix(a,*n,*n,*lda).selfadjointView<Upper>() * (alpha * vector(actual_x,*n));
- else if(UPLO(*uplo)==LO) vector(actual_y,*n).noalias() += matrix(a,*n,*n,*lda).selfadjointView<Lower>() * (alpha * vector(actual_x,*n));
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
+
+ func[code](*n, a, *lda, actual_x, 1, actual_y, alpha);
}
if(actual_x!=x) delete[] actual_x;
@@ -91,10 +108,49 @@ int EIGEN_BLAS_FUNC(hemv)(char *uplo, int *n, RealScalar *palpha, RealScalar *pa
* where alpha is a real scalar, x is an n element vector and A is an
* n by n hermitian matrix, supplied in packed form.
*/
-// int EIGEN_BLAS_FUNC(hpr)(char *uplo, int *n, RealScalar *alpha, RealScalar *x, int *incx, RealScalar *ap)
-// {
-// return 1;
-// }
+int EIGEN_BLAS_FUNC(hpr)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *pap)
+{
+ typedef void (*functype)(int, Scalar*, const Scalar*, RealScalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Upper,false,Conj>::run);
+ func[LO] = (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Lower,false,Conj>::run);
+
+ init = true;
+ }
+
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+ Scalar* ap = reinterpret_cast<Scalar*>(pap);
+ RealScalar alpha = *palpha;
+
+ int info = 0;
+ if(UPLO(*uplo)==INVALID) info = 1;
+ else if(*n<0) info = 2;
+ else if(*incx==0) info = 5;
+ if(info)
+ return xerbla_(SCALAR_SUFFIX_UP"HPR ",&info,6);
+
+ if(alpha==Scalar(0))
+ return 1;
+
+ Scalar* x_cpy = get_compact_vector(x, *n, *incx);
+
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
+
+ func[code](*n, ap, x_cpy, alpha);
+
+ if(x_cpy!=x) delete[] x_cpy;
+
+ return 1;
+}
/** ZHPR2 performs the hermitian rank 2 operation
*
@@ -103,10 +159,53 @@ int EIGEN_BLAS_FUNC(hemv)(char *uplo, int *n, RealScalar *palpha, RealScalar *pa
* where alpha is a scalar, x and y are n element vectors and A is an
* n by n hermitian matrix, supplied in packed form.
*/
-// int EIGEN_BLAS_FUNC(hpr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *x, int *incx, RealScalar *y, int *incy, RealScalar *ap)
-// {
-// return 1;
-// }
+int EIGEN_BLAS_FUNC(hpr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar *pap)
+{
+ typedef void (*functype)(int, Scalar*, const Scalar*, const Scalar*, Scalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (internal::packed_rank2_update_selector<Scalar,int,Upper>::run);
+ func[LO] = (internal::packed_rank2_update_selector<Scalar,int,Lower>::run);
+
+ init = true;
+ }
+
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+ Scalar* y = reinterpret_cast<Scalar*>(py);
+ Scalar* ap = reinterpret_cast<Scalar*>(pap);
+ Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
+
+ int info = 0;
+ if(UPLO(*uplo)==INVALID) info = 1;
+ else if(*n<0) info = 2;
+ else if(*incx==0) info = 5;
+ else if(*incy==0) info = 7;
+ if(info)
+ return xerbla_(SCALAR_SUFFIX_UP"HPR2 ",&info,6);
+
+ if(alpha==Scalar(0))
+ return 1;
+
+ Scalar* x_cpy = get_compact_vector(x, *n, *incx);
+ Scalar* y_cpy = get_compact_vector(y, *n, *incy);
+
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
+
+ func[code](*n, ap, x_cpy, y_cpy, alpha);
+
+ if(x_cpy!=x) delete[] x_cpy;
+ if(y_cpy!=y) delete[] y_cpy;
+
+ return 1;
+}
/** ZHER performs the hermitian rank 1 operation
*
@@ -117,6 +216,21 @@ int EIGEN_BLAS_FUNC(hemv)(char *uplo, int *n, RealScalar *palpha, RealScalar *pa
*/
int EIGEN_BLAS_FUNC(her)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *pa, int *lda)
{
+ typedef void (*functype)(int, Scalar*, int, const Scalar*, Scalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (selfadjoint_rank1_update<Scalar,int,ColMajor,Upper,false,Conj>::run);
+ func[LO] = (selfadjoint_rank1_update<Scalar,int,ColMajor,Lower,false,Conj>::run);
+
+ init = true;
+ }
+
Scalar* x = reinterpret_cast<Scalar*>(px);
Scalar* a = reinterpret_cast<Scalar*>(pa);
RealScalar alpha = *reinterpret_cast<RealScalar*>(palpha);
@@ -134,16 +248,11 @@ int EIGEN_BLAS_FUNC(her)(char *uplo, int *n, RealScalar *palpha, RealScalar *px,
Scalar* x_cpy = get_compact_vector(x, *n, *incx);
- // TODO perform direct calls to underlying implementation
-// if(UPLO(*uplo)==LO) matrix(a,*n,*n,*lda).selfadjointView<Lower>().rankUpdate(vector(x_cpy,*n), alpha);
-// else if(UPLO(*uplo)==UP) matrix(a,*n,*n,*lda).selfadjointView<Upper>().rankUpdate(vector(x_cpy,*n), alpha);
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
- if(UPLO(*uplo)==LO)
- for(int j=0;j<*n;++j)
- matrix(a,*n,*n,*lda).col(j).tail(*n-j) += alpha * internal::conj(x_cpy[j]) * vector(x_cpy+j,*n-j);
- else
- for(int j=0;j<*n;++j)
- matrix(a,*n,*n,*lda).col(j).head(j+1) += alpha * internal::conj(x_cpy[j]) * vector(x_cpy,j+1);
+ func[code](*n, a, *lda, x_cpy, alpha);
matrix(a,*n,*n,*lda).diagonal().imag().setZero();
@@ -161,6 +270,21 @@ int EIGEN_BLAS_FUNC(her)(char *uplo, int *n, RealScalar *palpha, RealScalar *px,
*/
int EIGEN_BLAS_FUNC(her2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar *pa, int *lda)
{
+ typedef void (*functype)(int, Scalar*, int, const Scalar*, const Scalar*, Scalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (internal::rank2_update_selector<Scalar,int,Upper>::run);
+ func[LO] = (internal::rank2_update_selector<Scalar,int,Lower>::run);
+
+ init = true;
+ }
+
Scalar* x = reinterpret_cast<Scalar*>(px);
Scalar* y = reinterpret_cast<Scalar*>(py);
Scalar* a = reinterpret_cast<Scalar*>(pa);
@@ -181,9 +305,11 @@ int EIGEN_BLAS_FUNC(her2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px
Scalar* x_cpy = get_compact_vector(x, *n, *incx);
Scalar* y_cpy = get_compact_vector(y, *n, *incy);
- // TODO perform direct calls to underlying implementation
- if(UPLO(*uplo)==LO) matrix(a,*n,*n,*lda).selfadjointView<Lower>().rankUpdate(vector(x_cpy,*n),vector(y_cpy,*n),alpha);
- else if(UPLO(*uplo)==UP) matrix(a,*n,*n,*lda).selfadjointView<Upper>().rankUpdate(vector(x_cpy,*n),vector(y_cpy,*n),alpha);
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
+
+ func[code](*n, a, *lda, x_cpy, y_cpy, alpha);
matrix(a,*n,*n,*lda).diagonal().imag().setZero();
@@ -222,8 +348,7 @@ int EIGEN_BLAS_FUNC(geru)(int *m, int *n, RealScalar *palpha, RealScalar *px, in
Scalar* x_cpy = get_compact_vector(x,*m,*incx);
Scalar* y_cpy = get_compact_vector(y,*n,*incy);
- // TODO perform direct calls to underlying implementation
- matrix(a,*m,*n,*lda) += alpha * vector(x_cpy,*m) * vector(y_cpy,*n).transpose();
+ internal::general_rank1_update<Scalar,int,ColMajor,false,false>::run(*m, *n, a, *lda, x_cpy, y_cpy, alpha);
if(x_cpy!=x) delete[] x_cpy;
if(y_cpy!=y) delete[] y_cpy;
@@ -260,8 +385,7 @@ int EIGEN_BLAS_FUNC(gerc)(int *m, int *n, RealScalar *palpha, RealScalar *px, in
Scalar* x_cpy = get_compact_vector(x,*m,*incx);
Scalar* y_cpy = get_compact_vector(y,*n,*incy);
- // TODO perform direct calls to underlying implementation
- matrix(a,*m,*n,*lda) += alpha * vector(x_cpy,*m) * vector(y_cpy,*n).adjoint();
+ internal::general_rank1_update<Scalar,int,ColMajor,false,Conj>::run(*m, *n, a, *lda, x_cpy, y_cpy, alpha);
if(x_cpy!=x) delete[] x_cpy;
if(y_cpy!=y) delete[] y_cpy;
diff --git a/resources/3rdparty/eigen/blas/level2_impl.h b/resources/3rdparty/eigen/blas/level2_impl.h
index 7099cf96d..bd41f7e60 100644
--- a/resources/3rdparty/eigen/blas/level2_impl.h
+++ b/resources/3rdparty/eigen/blas/level2_impl.h
@@ -49,7 +49,8 @@ int EIGEN_BLAS_FUNC(gemv)(char *opa, int *m, int *n, RealScalar *palpha, RealSca
int actual_m = *m;
int actual_n = *n;
- if(OP(*opa)!=NOTR)
+ int code = OP(*opa);
+ if(code!=NOTR)
std::swap(actual_m,actual_n);
Scalar* actual_b = get_compact_vector(b,actual_n,*incb);
@@ -61,7 +62,9 @@ int EIGEN_BLAS_FUNC(gemv)(char *opa, int *m, int *n, RealScalar *palpha, RealSca
else vector(actual_c, actual_m) *= beta;
}
- int code = OP(*opa);
+ if(code>=4 || func[code]==0)
+ return 0;
+
func[code](actual_m, actual_n, a, *lda, actual_b, 1, actual_c, 1, alpha);
if(actual_b!=b) delete[] actual_b;
@@ -184,7 +187,7 @@ int EIGEN_BLAS_FUNC(trmv)(char *uplo, char *opa, char *diag, int *n, RealScalar
copy_back(res.data(),b,*n,*incb);
if(actual_b!=b) delete[] actual_b;
- return 0;
+ return 1;
}
/** GBMV performs one of the matrix-vector operations
@@ -396,10 +399,66 @@ int EIGEN_BLAS_FUNC(tbsv)(char *uplo, char *op, char *diag, int *n, int *k, Real
* where x is an n element vector and A is an n by n unit, or non-unit,
* upper or lower triangular matrix, supplied in packed form.
*/
-// int EIGEN_BLAS_FUNC(tpmv)(char *uplo, char *trans, char *diag, int *n, RealScalar *ap, RealScalar *x, int *incx)
-// {
-// return 1;
-// }
+int EIGEN_BLAS_FUNC(tpmv)(char *uplo, char *opa, char *diag, int *n, RealScalar *pap, RealScalar *px, int *incx)
+{
+ typedef void (*functype)(int, const Scalar*, const Scalar*, Scalar*, Scalar);
+ static functype func[16];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<16; ++k)
+ func[k] = 0;
+
+ func[NOTR | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|0, Scalar,false,Scalar,false,ColMajor>::run);
+ func[TR | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|0, Scalar,false,Scalar,false,RowMajor>::run);
+ func[ADJ | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|0, Scalar,Conj, Scalar,false,RowMajor>::run);
+
+ func[NOTR | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|0, Scalar,false,Scalar,false,ColMajor>::run);
+ func[TR | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|0, Scalar,false,Scalar,false,RowMajor>::run);
+ func[ADJ | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|0, Scalar,Conj, Scalar,false,RowMajor>::run);
+
+ func[NOTR | (UP << 2) | (UNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run);
+ func[TR | (UP << 2) | (UNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run);
+ func[ADJ | (UP << 2) | (UNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run);
+
+ func[NOTR | (LO << 2) | (UNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Lower|UnitDiag,Scalar,false,Scalar,false,ColMajor>::run);
+ func[TR | (LO << 2) | (UNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,false,Scalar,false,RowMajor>::run);
+ func[ADJ | (LO << 2) | (UNIT << 3)] = (internal::packed_triangular_matrix_vector_product<int,Upper|UnitDiag,Scalar,Conj, Scalar,false,RowMajor>::run);
+
+ init = true;
+ }
+
+ Scalar* ap = reinterpret_cast<Scalar*>(pap);
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+
+ int info = 0;
+ if(UPLO(*uplo)==INVALID) info = 1;
+ else if(OP(*opa)==INVALID) info = 2;
+ else if(DIAG(*diag)==INVALID) info = 3;
+ else if(*n<0) info = 4;
+ else if(*incx==0) info = 7;
+ if(info)
+ return xerbla_(SCALAR_SUFFIX_UP"TPMV ",&info,6);
+
+ if(*n==0)
+ return 1;
+
+ Scalar* actual_x = get_compact_vector(x,*n,*incx);
+ Matrix<Scalar,Dynamic,1> res(*n);
+ res.setZero();
+
+ int code = OP(*opa) | (UPLO(*uplo) << 2) | (DIAG(*diag) << 3);
+ if(code>=16 || func[code]==0)
+ return 0;
+
+ func[code](*n, ap, actual_x, res.data(), Scalar(1));
+
+ copy_back(res.data(),x,*n,*incx);
+ if(actual_x!=x) delete[] actual_x;
+
+ return 1;
+}
/** DTPSV solves one of the systems of equations
*
@@ -411,47 +470,55 @@ int EIGEN_BLAS_FUNC(tbsv)(char *uplo, char *op, char *diag, int *n, int *k, Real
* No test for singularity or near-singularity is included in this
* routine. Such tests must be performed before calling this routine.
*/
-// int EIGEN_BLAS_FUNC(tpsv)(char *uplo, char *trans, char *diag, int *n, RealScalar *ap, RealScalar *x, int *incx)
-// {
-// return 1;
-// }
-
-/** DGER performs the rank 1 operation
- *
- * A := alpha*x*y' + A,
- *
- * where alpha is a scalar, x is an m element vector, y is an n element
- * vector and A is an m by n matrix.
- */
-int EIGEN_BLAS_FUNC(ger)(int *m, int *n, Scalar *palpha, Scalar *px, int *incx, Scalar *py, int *incy, Scalar *pa, int *lda)
+int EIGEN_BLAS_FUNC(tpsv)(char *uplo, char *opa, char *diag, int *n, RealScalar *pap, RealScalar *px, int *incx)
{
+ typedef void (*functype)(int, const Scalar*, Scalar*);
+ static functype func[16];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<16; ++k)
+ func[k] = 0;
+
+ func[NOTR | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0, false,ColMajor>::run);
+ func[TR | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0, false,RowMajor>::run);
+ func[ADJ | (UP << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0, Conj, RowMajor>::run);
+
+ func[NOTR | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|0, false,ColMajor>::run);
+ func[TR | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0, false,RowMajor>::run);
+ func[ADJ | (LO << 2) | (NUNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|0, Conj, RowMajor>::run);
+
+ func[NOTR | (UP << 2) | (UNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,ColMajor>::run);
+ func[TR | (UP << 2) | (UNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,RowMajor>::run);
+ func[ADJ | (UP << 2) | (UNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,Conj, RowMajor>::run);
+
+ func[NOTR | (LO << 2) | (UNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Lower|UnitDiag,false,ColMajor>::run);
+ func[TR | (LO << 2) | (UNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,false,RowMajor>::run);
+ func[ADJ | (LO << 2) | (UNIT << 3)] = (internal::packed_triangular_solve_vector<Scalar,Scalar,int,OnTheLeft, Upper|UnitDiag,Conj, RowMajor>::run);
+
+ init = true;
+ }
+
+ Scalar* ap = reinterpret_cast<Scalar*>(pap);
Scalar* x = reinterpret_cast<Scalar*>(px);
- Scalar* y = reinterpret_cast<Scalar*>(py);
- Scalar* a = reinterpret_cast<Scalar*>(pa);
- Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
int info = 0;
- if(*m<0) info = 1;
- else if(*n<0) info = 2;
- else if(*incx==0) info = 5;
- else if(*incy==0) info = 7;
- else if(*lda<std::max(1,*m)) info = 9;
+ if(UPLO(*uplo)==INVALID) info = 1;
+ else if(OP(*opa)==INVALID) info = 2;
+ else if(DIAG(*diag)==INVALID) info = 3;
+ else if(*n<0) info = 4;
+ else if(*incx==0) info = 7;
if(info)
- return xerbla_(SCALAR_SUFFIX_UP"GER ",&info,6);
+ return xerbla_(SCALAR_SUFFIX_UP"TPSV ",&info,6);
- if(alpha==Scalar(0))
- return 1;
-
- Scalar* x_cpy = get_compact_vector(x,*m,*incx);
- Scalar* y_cpy = get_compact_vector(y,*n,*incy);
+ Scalar* actual_x = get_compact_vector(x,*n,*incx);
- // TODO perform direct calls to underlying implementation
- matrix(a,*m,*n,*lda) += alpha * vector(x_cpy,*m) * vector(y_cpy,*n).adjoint();
+ int code = OP(*opa) | (UPLO(*uplo) << 2) | (DIAG(*diag) << 3);
+ func[code](*n, ap, actual_x);
- if(x_cpy!=x) delete[] x_cpy;
- if(y_cpy!=y) delete[] y_cpy;
+ if(actual_x!=x) delete[] copy_back(actual_x,x,*n,*incx);
return 1;
}
-
diff --git a/resources/3rdparty/eigen/blas/level2_real_impl.h b/resources/3rdparty/eigen/blas/level2_real_impl.h
index cd8332973..febf08d1f 100644
--- a/resources/3rdparty/eigen/blas/level2_real_impl.h
+++ b/resources/3rdparty/eigen/blas/level2_real_impl.h
@@ -12,6 +12,21 @@
// y = alpha*A*x + beta*y
int EIGEN_BLAS_FUNC(symv) (char *uplo, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *px, int *incx, RealScalar *pbeta, RealScalar *py, int *incy)
{
+ typedef void (*functype)(int, const Scalar*, int, const Scalar*, int, Scalar*, Scalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Upper,false,false>::run);
+ func[LO] = (internal::selfadjoint_matrix_vector_product<Scalar,int,ColMajor,Lower,false,false>::run);
+
+ init = true;
+ }
+
Scalar* a = reinterpret_cast<Scalar*>(pa);
Scalar* x = reinterpret_cast<Scalar*>(px);
Scalar* y = reinterpret_cast<Scalar*>(py);
@@ -40,9 +55,11 @@ int EIGEN_BLAS_FUNC(symv) (char *uplo, int *n, RealScalar *palpha, RealScalar *p
else vector(actual_y, *n) *= beta;
}
- // TODO performs a direct call to the underlying implementation function
- if(UPLO(*uplo)==UP) vector(actual_y,*n).noalias() += matrix(a,*n,*n,*lda).selfadjointView<Upper>() * (alpha * vector(actual_x,*n));
- else if(UPLO(*uplo)==LO) vector(actual_y,*n).noalias() += matrix(a,*n,*n,*lda).selfadjointView<Lower>() * (alpha * vector(actual_x,*n));
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
+
+ func[code](*n, a, *lda, actual_x, 1, actual_y, alpha);
if(actual_x!=x) delete[] actual_x;
if(actual_y!=y) delete[] copy_back(actual_y,y,*n,*incy);
@@ -68,6 +85,20 @@ int EIGEN_BLAS_FUNC(syr)(char *uplo, int *n, RealScalar *palpha, RealScalar *px,
// init = true;
// }
+ typedef void (*functype)(int, Scalar*, int, const Scalar*, Scalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (selfadjoint_rank1_update<Scalar,int,ColMajor,Upper,false,Conj>::run);
+ func[LO] = (selfadjoint_rank1_update<Scalar,int,ColMajor,Lower,false,Conj>::run);
+
+ init = true;
+ }
Scalar* x = reinterpret_cast<Scalar*>(px);
Scalar* c = reinterpret_cast<Scalar*>(pc);
@@ -86,18 +117,11 @@ int EIGEN_BLAS_FUNC(syr)(char *uplo, int *n, RealScalar *palpha, RealScalar *px,
// if the increment is not 1, let's copy it to a temporary vector to enable vectorization
Scalar* x_cpy = get_compact_vector(x,*n,*incx);
- Matrix<Scalar,Dynamic,Dynamic> m2(matrix(c,*n,*n,*ldc));
-
- // TODO check why this is not accurate enough for lapack tests
-// if(UPLO(*uplo)==LO) matrix(c,*n,*n,*ldc).selfadjointView<Lower>().rankUpdate(vector(x_cpy,*n), alpha);
-// else if(UPLO(*uplo)==UP) matrix(c,*n,*n,*ldc).selfadjointView<Upper>().rankUpdate(vector(x_cpy,*n), alpha);
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
- if(UPLO(*uplo)==LO)
- for(int j=0;j<*n;++j)
- matrix(c,*n,*n,*ldc).col(j).tail(*n-j) += alpha * x_cpy[j] * vector(x_cpy+j,*n-j);
- else
- for(int j=0;j<*n;++j)
- matrix(c,*n,*n,*ldc).col(j).head(j+1) += alpha * x_cpy[j] * vector(x_cpy,j+1);
+ func[code](*n, c, *ldc, x_cpy, alpha);
if(x_cpy!=x) delete[] x_cpy;
@@ -121,6 +145,20 @@ int EIGEN_BLAS_FUNC(syr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px
//
// init = true;
// }
+ typedef void (*functype)(int, Scalar*, int, const Scalar*, const Scalar*, Scalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (internal::rank2_update_selector<Scalar,int,Upper>::run);
+ func[LO] = (internal::rank2_update_selector<Scalar,int,Lower>::run);
+
+ init = true;
+ }
Scalar* x = reinterpret_cast<Scalar*>(px);
Scalar* y = reinterpret_cast<Scalar*>(py);
@@ -141,10 +179,12 @@ int EIGEN_BLAS_FUNC(syr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px
Scalar* x_cpy = get_compact_vector(x,*n,*incx);
Scalar* y_cpy = get_compact_vector(y,*n,*incy);
+
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
- // TODO perform direct calls to underlying implementation
- if(UPLO(*uplo)==LO) matrix(c,*n,*n,*ldc).selfadjointView<Lower>().rankUpdate(vector(x_cpy,*n), vector(y_cpy,*n), alpha);
- else if(UPLO(*uplo)==UP) matrix(c,*n,*n,*ldc).selfadjointView<Upper>().rankUpdate(vector(x_cpy,*n), vector(y_cpy,*n), alpha);
+ func[code](*n, c, *ldc, x_cpy, y_cpy, alpha);
if(x_cpy!=x) delete[] x_cpy;
if(y_cpy!=y) delete[] y_cpy;
@@ -191,10 +231,49 @@ int EIGEN_BLAS_FUNC(syr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px
* where alpha is a real scalar, x is an n element vector and A is an
* n by n symmetric matrix, supplied in packed form.
*/
-// int EIGEN_BLAS_FUNC(spr)(char *uplo, int *n, Scalar *alpha, Scalar *x, int *incx, Scalar *ap)
-// {
-// return 1;
-// }
+int EIGEN_BLAS_FUNC(spr)(char *uplo, int *n, Scalar *palpha, Scalar *px, int *incx, Scalar *pap)
+{
+ typedef void (*functype)(int, Scalar*, const Scalar*, Scalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Upper,false,false>::run);
+ func[LO] = (internal::selfadjoint_packed_rank1_update<Scalar,int,ColMajor,Lower,false,false>::run);
+
+ init = true;
+ }
+
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+ Scalar* ap = reinterpret_cast<Scalar*>(pap);
+ Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
+
+ int info = 0;
+ if(UPLO(*uplo)==INVALID) info = 1;
+ else if(*n<0) info = 2;
+ else if(*incx==0) info = 5;
+ if(info)
+ return xerbla_(SCALAR_SUFFIX_UP"SPR ",&info,6);
+
+ if(alpha==Scalar(0))
+ return 1;
+
+ Scalar* x_cpy = get_compact_vector(x, *n, *incx);
+
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
+
+ func[code](*n, ap, x_cpy, alpha);
+
+ if(x_cpy!=x) delete[] x_cpy;
+
+ return 1;
+}
/** DSPR2 performs the symmetric rank 2 operation
*
@@ -203,8 +282,89 @@ int EIGEN_BLAS_FUNC(syr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px
* where alpha is a scalar, x and y are n element vectors and A is an
* n by n symmetric matrix, supplied in packed form.
*/
-// int EIGEN_BLAS_FUNC(spr2)(char *uplo, int *n, RealScalar *alpha, RealScalar *x, int *incx, RealScalar *y, int *incy, RealScalar *ap)
-// {
-// return 1;
-// }
+int EIGEN_BLAS_FUNC(spr2)(char *uplo, int *n, RealScalar *palpha, RealScalar *px, int *incx, RealScalar *py, int *incy, RealScalar *pap)
+{
+ typedef void (*functype)(int, Scalar*, const Scalar*, const Scalar*, Scalar);
+ static functype func[2];
+
+ static bool init = false;
+ if(!init)
+ {
+ for(int k=0; k<2; ++k)
+ func[k] = 0;
+
+ func[UP] = (internal::packed_rank2_update_selector<Scalar,int,Upper>::run);
+ func[LO] = (internal::packed_rank2_update_selector<Scalar,int,Lower>::run);
+
+ init = true;
+ }
+
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+ Scalar* y = reinterpret_cast<Scalar*>(py);
+ Scalar* ap = reinterpret_cast<Scalar*>(pap);
+ Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
+
+ int info = 0;
+ if(UPLO(*uplo)==INVALID) info = 1;
+ else if(*n<0) info = 2;
+ else if(*incx==0) info = 5;
+ else if(*incy==0) info = 7;
+ if(info)
+ return xerbla_(SCALAR_SUFFIX_UP"SPR2 ",&info,6);
+
+ if(alpha==Scalar(0))
+ return 1;
+
+ Scalar* x_cpy = get_compact_vector(x, *n, *incx);
+ Scalar* y_cpy = get_compact_vector(y, *n, *incy);
+
+ int code = UPLO(*uplo);
+ if(code>=2 || func[code]==0)
+ return 0;
+
+ func[code](*n, ap, x_cpy, y_cpy, alpha);
+
+ if(x_cpy!=x) delete[] x_cpy;
+ if(y_cpy!=y) delete[] y_cpy;
+
+ return 1;
+}
+
+/** DGER performs the rank 1 operation
+ *
+ * A := alpha*x*y' + A,
+ *
+ * where alpha is a scalar, x is an m element vector, y is an n element
+ * vector and A is an m by n matrix.
+ */
+int EIGEN_BLAS_FUNC(ger)(int *m, int *n, Scalar *palpha, Scalar *px, int *incx, Scalar *py, int *incy, Scalar *pa, int *lda)
+{
+ Scalar* x = reinterpret_cast<Scalar*>(px);
+ Scalar* y = reinterpret_cast<Scalar*>(py);
+ Scalar* a = reinterpret_cast<Scalar*>(pa);
+ Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
+
+ int info = 0;
+ if(*m<0) info = 1;
+ else if(*n<0) info = 2;
+ else if(*incx==0) info = 5;
+ else if(*incy==0) info = 7;
+ else if(*lda<std::max(1,*m)) info = 9;
+ if(info)
+ return xerbla_(SCALAR_SUFFIX_UP"GER ",&info,6);
+
+ if(alpha==Scalar(0))
+ return 1;
+
+ Scalar* x_cpy = get_compact_vector(x,*m,*incx);
+ Scalar* y_cpy = get_compact_vector(y,*n,*incy);
+
+ internal::general_rank1_update<Scalar,int,ColMajor,false,false>::run(*m, *n, a, *lda, x_cpy, y_cpy, alpha);
+
+ if(x_cpy!=x) delete[] x_cpy;
+ if(y_cpy!=y) delete[] y_cpy;
+
+ return 1;
+}
+
diff --git a/resources/3rdparty/eigen/blas/level3_impl.h b/resources/3rdparty/eigen/blas/level3_impl.h
index 2371f25c3..84c9f4f2b 100644
--- a/resources/3rdparty/eigen/blas/level3_impl.h
+++ b/resources/3rdparty/eigen/blas/level3_impl.h
@@ -305,6 +305,7 @@ int EIGEN_BLAS_FUNC(symm)(char *side, char *uplo, int *m, int *n, RealScalar *pa
int EIGEN_BLAS_FUNC(syrk)(char *uplo, char *op, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pbeta, RealScalar *pc, int *ldc)
{
// std::cerr << "in syrk " << *uplo << " " << *op << " " << *n << " " << *k << " " << *palpha << " " << *lda << " " << *pbeta << " " << *ldc << "\n";
+ #if !ISCOMPLEX
typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, Scalar);
static functype func[8];
@@ -324,6 +325,7 @@ int EIGEN_BLAS_FUNC(syrk)(char *uplo, char *op, int *n, int *k, RealScalar *palp
init = true;
}
+ #endif
Scalar* a = reinterpret_cast<Scalar*>(pa);
Scalar* c = reinterpret_cast<Scalar*>(pc);
diff --git a/resources/3rdparty/eigen/blas/single.cpp b/resources/3rdparty/eigen/blas/single.cpp
index 1b7775aed..836e3eee2 100644
--- a/resources/3rdparty/eigen/blas/single.cpp
+++ b/resources/3rdparty/eigen/blas/single.cpp
@@ -17,3 +17,6 @@
#include "level2_impl.h"
#include "level2_real_impl.h"
#include "level3_impl.h"
+
+float BLASFUNC(sdsdot)(int* n, float* alpha, float* x, int* incx, float* y, int* incy)
+{ return *alpha + BLASFUNC(dsdot)(n, x, incx, y, incy); }
diff --git a/resources/3rdparty/eigen/blas/sspr.f b/resources/3rdparty/eigen/blas/sspr.f
deleted file mode 100644
index bae92612e..000000000
--- a/resources/3rdparty/eigen/blas/sspr.f
+++ /dev/null
@@ -1,202 +0,0 @@
- SUBROUTINE SSPR(UPLO,N,ALPHA,X,INCX,AP)
-* .. Scalar Arguments ..
- REAL ALPHA
- INTEGER INCX,N
- CHARACTER UPLO
-* ..
-* .. Array Arguments ..
- REAL AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* SSPR performs the symmetric rank 1 operation
-*
-* A := alpha*x*x' + A,
-*
-* where alpha is a real scalar, x is an n element vector and A is an
-* n by n symmetric matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the upper or lower
-* triangular part of the matrix A is supplied in the packed
-* array AP as follows:
-*
-* UPLO = 'U' or 'u' The upper triangular part of A is
-* supplied in AP.
-*
-* UPLO = 'L' or 'l' The lower triangular part of A is
-* supplied in AP.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* ALPHA - REAL .
-* On entry, ALPHA specifies the scalar alpha.
-* Unchanged on exit.
-*
-* X - REAL array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x.
-* Unchanged on exit.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* AP - REAL array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular part of the symmetric matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-* and a( 2, 2 ) respectively, and so on. On exit, the array
-* AP is overwritten by the upper triangular part of the
-* updated matrix.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular part of the symmetric matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-* and a( 3, 1 ) respectively, and so on. On exit, the array
-* AP is overwritten by the lower triangular part of the
-* updated matrix.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- REAL ZERO
- PARAMETER (ZERO=0.0E+0)
-* ..
-* .. Local Scalars ..
- REAL TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (N.LT.0) THEN
- INFO = 2
- ELSE IF (INCX.EQ.0) THEN
- INFO = 5
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('SSPR ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF ((N.EQ.0) .OR. (ALPHA.EQ.ZERO)) RETURN
-*
-* Set the start point in X if the increment is not unity.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of the array AP
-* are accessed sequentially with one pass through AP.
-*
- KK = 1
- IF (LSAME(UPLO,'U')) THEN
-*
-* Form A when upper triangle is stored in AP.
-*
- IF (INCX.EQ.1) THEN
- DO 20 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = ALPHA*X(J)
- K = KK
- DO 10 I = 1,J
- AP(K) = AP(K) + X(I)*TEMP
- K = K + 1
- 10 CONTINUE
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- JX = KX
- DO 40 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = ALPHA*X(JX)
- IX = KX
- DO 30 K = KK,KK + J - 1
- AP(K) = AP(K) + X(IX)*TEMP
- IX = IX + INCX
- 30 CONTINUE
- END IF
- JX = JX + INCX
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
-*
-* Form A when lower triangle is stored in AP.
-*
- IF (INCX.EQ.1) THEN
- DO 60 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = ALPHA*X(J)
- K = KK
- DO 50 I = J,N
- AP(K) = AP(K) + X(I)*TEMP
- K = K + 1
- 50 CONTINUE
- END IF
- KK = KK + N - J + 1
- 60 CONTINUE
- ELSE
- JX = KX
- DO 80 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = ALPHA*X(JX)
- IX = JX
- DO 70 K = KK,KK + N - J
- AP(K) = AP(K) + X(IX)*TEMP
- IX = IX + INCX
- 70 CONTINUE
- END IF
- JX = JX + INCX
- KK = KK + N - J + 1
- 80 CONTINUE
- END IF
- END IF
-*
- RETURN
-*
-* End of SSPR .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/sspr2.f b/resources/3rdparty/eigen/blas/sspr2.f
deleted file mode 100644
index cd27c734b..000000000
--- a/resources/3rdparty/eigen/blas/sspr2.f
+++ /dev/null
@@ -1,233 +0,0 @@
- SUBROUTINE SSPR2(UPLO,N,ALPHA,X,INCX,Y,INCY,AP)
-* .. Scalar Arguments ..
- REAL ALPHA
- INTEGER INCX,INCY,N
- CHARACTER UPLO
-* ..
-* .. Array Arguments ..
- REAL AP(*),X(*),Y(*)
-* ..
-*
-* Purpose
-* =======
-*
-* SSPR2 performs the symmetric rank 2 operation
-*
-* A := alpha*x*y' + alpha*y*x' + A,
-*
-* where alpha is a scalar, x and y are n element vectors and A is an
-* n by n symmetric matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the upper or lower
-* triangular part of the matrix A is supplied in the packed
-* array AP as follows:
-*
-* UPLO = 'U' or 'u' The upper triangular part of A is
-* supplied in AP.
-*
-* UPLO = 'L' or 'l' The lower triangular part of A is
-* supplied in AP.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* ALPHA - REAL .
-* On entry, ALPHA specifies the scalar alpha.
-* Unchanged on exit.
-*
-* X - REAL array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x.
-* Unchanged on exit.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Y - REAL array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCY ) ).
-* Before entry, the incremented array Y must contain the n
-* element vector y.
-* Unchanged on exit.
-*
-* INCY - INTEGER.
-* On entry, INCY specifies the increment for the elements of
-* Y. INCY must not be zero.
-* Unchanged on exit.
-*
-* AP - REAL array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular part of the symmetric matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-* and a( 2, 2 ) respectively, and so on. On exit, the array
-* AP is overwritten by the upper triangular part of the
-* updated matrix.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular part of the symmetric matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-* and a( 3, 1 ) respectively, and so on. On exit, the array
-* AP is overwritten by the lower triangular part of the
-* updated matrix.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- REAL ZERO
- PARAMETER (ZERO=0.0E+0)
-* ..
-* .. Local Scalars ..
- REAL TEMP1,TEMP2
- INTEGER I,INFO,IX,IY,J,JX,JY,K,KK,KX,KY
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (N.LT.0) THEN
- INFO = 2
- ELSE IF (INCX.EQ.0) THEN
- INFO = 5
- ELSE IF (INCY.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('SSPR2 ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF ((N.EQ.0) .OR. (ALPHA.EQ.ZERO)) RETURN
-*
-* Set up the start points in X and Y if the increments are not both
-* unity.
-*
- IF ((INCX.NE.1) .OR. (INCY.NE.1)) THEN
- IF (INCX.GT.0) THEN
- KX = 1
- ELSE
- KX = 1 - (N-1)*INCX
- END IF
- IF (INCY.GT.0) THEN
- KY = 1
- ELSE
- KY = 1 - (N-1)*INCY
- END IF
- JX = KX
- JY = KY
- END IF
-*
-* Start the operations. In this version the elements of the array AP
-* are accessed sequentially with one pass through AP.
-*
- KK = 1
- IF (LSAME(UPLO,'U')) THEN
-*
-* Form A when upper triangle is stored in AP.
-*
- IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
- DO 20 J = 1,N
- IF ((X(J).NE.ZERO) .OR. (Y(J).NE.ZERO)) THEN
- TEMP1 = ALPHA*Y(J)
- TEMP2 = ALPHA*X(J)
- K = KK
- DO 10 I = 1,J
- AP(K) = AP(K) + X(I)*TEMP1 + Y(I)*TEMP2
- K = K + 1
- 10 CONTINUE
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- DO 40 J = 1,N
- IF ((X(JX).NE.ZERO) .OR. (Y(JY).NE.ZERO)) THEN
- TEMP1 = ALPHA*Y(JY)
- TEMP2 = ALPHA*X(JX)
- IX = KX
- IY = KY
- DO 30 K = KK,KK + J - 1
- AP(K) = AP(K) + X(IX)*TEMP1 + Y(IY)*TEMP2
- IX = IX + INCX
- IY = IY + INCY
- 30 CONTINUE
- END IF
- JX = JX + INCX
- JY = JY + INCY
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
-*
-* Form A when lower triangle is stored in AP.
-*
- IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
- DO 60 J = 1,N
- IF ((X(J).NE.ZERO) .OR. (Y(J).NE.ZERO)) THEN
- TEMP1 = ALPHA*Y(J)
- TEMP2 = ALPHA*X(J)
- K = KK
- DO 50 I = J,N
- AP(K) = AP(K) + X(I)*TEMP1 + Y(I)*TEMP2
- K = K + 1
- 50 CONTINUE
- END IF
- KK = KK + N - J + 1
- 60 CONTINUE
- ELSE
- DO 80 J = 1,N
- IF ((X(JX).NE.ZERO) .OR. (Y(JY).NE.ZERO)) THEN
- TEMP1 = ALPHA*Y(JY)
- TEMP2 = ALPHA*X(JX)
- IX = JX
- IY = JY
- DO 70 K = KK,KK + N - J
- AP(K) = AP(K) + X(IX)*TEMP1 + Y(IY)*TEMP2
- IX = IX + INCX
- IY = IY + INCY
- 70 CONTINUE
- END IF
- JX = JX + INCX
- JY = JY + INCY
- KK = KK + N - J + 1
- 80 CONTINUE
- END IF
- END IF
-*
- RETURN
-*
-* End of SSPR2 .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/stpmv.f b/resources/3rdparty/eigen/blas/stpmv.f
deleted file mode 100644
index 71ea49a36..000000000
--- a/resources/3rdparty/eigen/blas/stpmv.f
+++ /dev/null
@@ -1,293 +0,0 @@
- SUBROUTINE STPMV(UPLO,TRANS,DIAG,N,AP,X,INCX)
-* .. Scalar Arguments ..
- INTEGER INCX,N
- CHARACTER DIAG,TRANS,UPLO
-* ..
-* .. Array Arguments ..
- REAL AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* STPMV performs one of the matrix-vector operations
-*
-* x := A*x, or x := A'*x,
-*
-* where x is an n element vector and A is an n by n unit, or non-unit,
-* upper or lower triangular matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the matrix is an upper or
-* lower triangular matrix as follows:
-*
-* UPLO = 'U' or 'u' A is an upper triangular matrix.
-*
-* UPLO = 'L' or 'l' A is a lower triangular matrix.
-*
-* Unchanged on exit.
-*
-* TRANS - CHARACTER*1.
-* On entry, TRANS specifies the operation to be performed as
-* follows:
-*
-* TRANS = 'N' or 'n' x := A*x.
-*
-* TRANS = 'T' or 't' x := A'*x.
-*
-* TRANS = 'C' or 'c' x := A'*x.
-*
-* Unchanged on exit.
-*
-* DIAG - CHARACTER*1.
-* On entry, DIAG specifies whether or not A is unit
-* triangular as follows:
-*
-* DIAG = 'U' or 'u' A is assumed to be unit triangular.
-*
-* DIAG = 'N' or 'n' A is not assumed to be unit
-* triangular.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* AP - REAL array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 1, 2 ) and a( 2, 2 )
-* respectively, and so on.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 2, 1 ) and a( 3, 1 )
-* respectively, and so on.
-* Note that when DIAG = 'U' or 'u', the diagonal elements of
-* A are not referenced, but are assumed to be unity.
-* Unchanged on exit.
-*
-* X - REAL array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x. On exit, X is overwritten with the
-* tranformed vector x.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- REAL ZERO
- PARAMETER (ZERO=0.0E+0)
-* ..
-* .. Local Scalars ..
- REAL TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
- LOGICAL NOUNIT
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
- + .NOT.LSAME(TRANS,'C')) THEN
- INFO = 2
- ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
- INFO = 3
- ELSE IF (N.LT.0) THEN
- INFO = 4
- ELSE IF (INCX.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('STPMV ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF (N.EQ.0) RETURN
-*
- NOUNIT = LSAME(DIAG,'N')
-*
-* Set up the start point in X if the increment is not unity. This
-* will be ( N - 1 )*INCX too small for descending loops.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of AP are
-* accessed sequentially with one pass through AP.
-*
- IF (LSAME(TRANS,'N')) THEN
-*
-* Form x:= A*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 20 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = X(J)
- K = KK
- DO 10 I = 1,J - 1
- X(I) = X(I) + TEMP*AP(K)
- K = K + 1
- 10 CONTINUE
- IF (NOUNIT) X(J) = X(J)*AP(KK+J-1)
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- JX = KX
- DO 40 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = X(JX)
- IX = KX
- DO 30 K = KK,KK + J - 2
- X(IX) = X(IX) + TEMP*AP(K)
- IX = IX + INCX
- 30 CONTINUE
- IF (NOUNIT) X(JX) = X(JX)*AP(KK+J-1)
- END IF
- JX = JX + INCX
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 60 J = N,1,-1
- IF (X(J).NE.ZERO) THEN
- TEMP = X(J)
- K = KK
- DO 50 I = N,J + 1,-1
- X(I) = X(I) + TEMP*AP(K)
- K = K - 1
- 50 CONTINUE
- IF (NOUNIT) X(J) = X(J)*AP(KK-N+J)
- END IF
- KK = KK - (N-J+1)
- 60 CONTINUE
- ELSE
- KX = KX + (N-1)*INCX
- JX = KX
- DO 80 J = N,1,-1
- IF (X(JX).NE.ZERO) THEN
- TEMP = X(JX)
- IX = KX
- DO 70 K = KK,KK - (N- (J+1)),-1
- X(IX) = X(IX) + TEMP*AP(K)
- IX = IX - INCX
- 70 CONTINUE
- IF (NOUNIT) X(JX) = X(JX)*AP(KK-N+J)
- END IF
- JX = JX - INCX
- KK = KK - (N-J+1)
- 80 CONTINUE
- END IF
- END IF
- ELSE
-*
-* Form x := A'*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 100 J = N,1,-1
- TEMP = X(J)
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- K = KK - 1
- DO 90 I = J - 1,1,-1
- TEMP = TEMP + AP(K)*X(I)
- K = K - 1
- 90 CONTINUE
- X(J) = TEMP
- KK = KK - J
- 100 CONTINUE
- ELSE
- JX = KX + (N-1)*INCX
- DO 120 J = N,1,-1
- TEMP = X(JX)
- IX = JX
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 110 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- TEMP = TEMP + AP(K)*X(IX)
- 110 CONTINUE
- X(JX) = TEMP
- JX = JX - INCX
- KK = KK - J
- 120 CONTINUE
- END IF
- ELSE
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 140 J = 1,N
- TEMP = X(J)
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- K = KK + 1
- DO 130 I = J + 1,N
- TEMP = TEMP + AP(K)*X(I)
- K = K + 1
- 130 CONTINUE
- X(J) = TEMP
- KK = KK + (N-J+1)
- 140 CONTINUE
- ELSE
- JX = KX
- DO 160 J = 1,N
- TEMP = X(JX)
- IX = JX
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 150 K = KK + 1,KK + N - J
- IX = IX + INCX
- TEMP = TEMP + AP(K)*X(IX)
- 150 CONTINUE
- X(JX) = TEMP
- JX = JX + INCX
- KK = KK + (N-J+1)
- 160 CONTINUE
- END IF
- END IF
- END IF
-*
- RETURN
-*
-* End of STPMV .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/stpsv.f b/resources/3rdparty/eigen/blas/stpsv.f
deleted file mode 100644
index 7d95efbde..000000000
--- a/resources/3rdparty/eigen/blas/stpsv.f
+++ /dev/null
@@ -1,296 +0,0 @@
- SUBROUTINE STPSV(UPLO,TRANS,DIAG,N,AP,X,INCX)
-* .. Scalar Arguments ..
- INTEGER INCX,N
- CHARACTER DIAG,TRANS,UPLO
-* ..
-* .. Array Arguments ..
- REAL AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* STPSV solves one of the systems of equations
-*
-* A*x = b, or A'*x = b,
-*
-* where b and x are n element vectors and A is an n by n unit, or
-* non-unit, upper or lower triangular matrix, supplied in packed form.
-*
-* No test for singularity or near-singularity is included in this
-* routine. Such tests must be performed before calling this routine.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the matrix is an upper or
-* lower triangular matrix as follows:
-*
-* UPLO = 'U' or 'u' A is an upper triangular matrix.
-*
-* UPLO = 'L' or 'l' A is a lower triangular matrix.
-*
-* Unchanged on exit.
-*
-* TRANS - CHARACTER*1.
-* On entry, TRANS specifies the equations to be solved as
-* follows:
-*
-* TRANS = 'N' or 'n' A*x = b.
-*
-* TRANS = 'T' or 't' A'*x = b.
-*
-* TRANS = 'C' or 'c' A'*x = b.
-*
-* Unchanged on exit.
-*
-* DIAG - CHARACTER*1.
-* On entry, DIAG specifies whether or not A is unit
-* triangular as follows:
-*
-* DIAG = 'U' or 'u' A is assumed to be unit triangular.
-*
-* DIAG = 'N' or 'n' A is not assumed to be unit
-* triangular.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* AP - REAL array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 1, 2 ) and a( 2, 2 )
-* respectively, and so on.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 2, 1 ) and a( 3, 1 )
-* respectively, and so on.
-* Note that when DIAG = 'U' or 'u', the diagonal elements of
-* A are not referenced, but are assumed to be unity.
-* Unchanged on exit.
-*
-* X - REAL array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element right-hand side vector b. On exit, X is overwritten
-* with the solution vector x.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- REAL ZERO
- PARAMETER (ZERO=0.0E+0)
-* ..
-* .. Local Scalars ..
- REAL TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
- LOGICAL NOUNIT
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
- + .NOT.LSAME(TRANS,'C')) THEN
- INFO = 2
- ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
- INFO = 3
- ELSE IF (N.LT.0) THEN
- INFO = 4
- ELSE IF (INCX.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('STPSV ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF (N.EQ.0) RETURN
-*
- NOUNIT = LSAME(DIAG,'N')
-*
-* Set up the start point in X if the increment is not unity. This
-* will be ( N - 1 )*INCX too small for descending loops.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of AP are
-* accessed sequentially with one pass through AP.
-*
- IF (LSAME(TRANS,'N')) THEN
-*
-* Form x := inv( A )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 20 J = N,1,-1
- IF (X(J).NE.ZERO) THEN
- IF (NOUNIT) X(J) = X(J)/AP(KK)
- TEMP = X(J)
- K = KK - 1
- DO 10 I = J - 1,1,-1
- X(I) = X(I) - TEMP*AP(K)
- K = K - 1
- 10 CONTINUE
- END IF
- KK = KK - J
- 20 CONTINUE
- ELSE
- JX = KX + (N-1)*INCX
- DO 40 J = N,1,-1
- IF (X(JX).NE.ZERO) THEN
- IF (NOUNIT) X(JX) = X(JX)/AP(KK)
- TEMP = X(JX)
- IX = JX
- DO 30 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- X(IX) = X(IX) - TEMP*AP(K)
- 30 CONTINUE
- END IF
- JX = JX - INCX
- KK = KK - J
- 40 CONTINUE
- END IF
- ELSE
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 60 J = 1,N
- IF (X(J).NE.ZERO) THEN
- IF (NOUNIT) X(J) = X(J)/AP(KK)
- TEMP = X(J)
- K = KK + 1
- DO 50 I = J + 1,N
- X(I) = X(I) - TEMP*AP(K)
- K = K + 1
- 50 CONTINUE
- END IF
- KK = KK + (N-J+1)
- 60 CONTINUE
- ELSE
- JX = KX
- DO 80 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- IF (NOUNIT) X(JX) = X(JX)/AP(KK)
- TEMP = X(JX)
- IX = JX
- DO 70 K = KK + 1,KK + N - J
- IX = IX + INCX
- X(IX) = X(IX) - TEMP*AP(K)
- 70 CONTINUE
- END IF
- JX = JX + INCX
- KK = KK + (N-J+1)
- 80 CONTINUE
- END IF
- END IF
- ELSE
-*
-* Form x := inv( A' )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 100 J = 1,N
- TEMP = X(J)
- K = KK
- DO 90 I = 1,J - 1
- TEMP = TEMP - AP(K)*X(I)
- K = K + 1
- 90 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK+J-1)
- X(J) = TEMP
- KK = KK + J
- 100 CONTINUE
- ELSE
- JX = KX
- DO 120 J = 1,N
- TEMP = X(JX)
- IX = KX
- DO 110 K = KK,KK + J - 2
- TEMP = TEMP - AP(K)*X(IX)
- IX = IX + INCX
- 110 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK+J-1)
- X(JX) = TEMP
- JX = JX + INCX
- KK = KK + J
- 120 CONTINUE
- END IF
- ELSE
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 140 J = N,1,-1
- TEMP = X(J)
- K = KK
- DO 130 I = N,J + 1,-1
- TEMP = TEMP - AP(K)*X(I)
- K = K - 1
- 130 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK-N+J)
- X(J) = TEMP
- KK = KK - (N-J+1)
- 140 CONTINUE
- ELSE
- KX = KX + (N-1)*INCX
- JX = KX
- DO 160 J = N,1,-1
- TEMP = X(JX)
- IX = KX
- DO 150 K = KK,KK - (N- (J+1)),-1
- TEMP = TEMP - AP(K)*X(IX)
- IX = IX - INCX
- 150 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK-N+J)
- X(JX) = TEMP
- JX = JX - INCX
- KK = KK - (N-J+1)
- 160 CONTINUE
- END IF
- END IF
- END IF
-*
- RETURN
-*
-* End of STPSV .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/testing/dblat1.f b/resources/3rdparty/eigen/blas/testing/dblat1.f
index 5a45d69f4..30691f9bf 100644
--- a/resources/3rdparty/eigen/blas/testing/dblat1.f
+++ b/resources/3rdparty/eigen/blas/testing/dblat1.f
@@ -1,12 +1,54 @@
+*> \brief \b DBLAT1
+*
+* =========== DOCUMENTATION ===========
+*
+* Online html documentation available at
+* http://www.netlib.org/lapack/explore-html/
+*
+* Definition:
+* ===========
+*
+* PROGRAM DBLAT1
+*
+*
+*> \par Purpose:
+* =============
+*>
+*> \verbatim
+*>
+*> Test program for the DOUBLE PRECISION Level 1 BLAS.
+*>
+*> Based upon the original BLAS test routine together with:
+*> F06EAF Example Program Text
+*> \endverbatim
+*
+* Authors:
+* ========
+*
+*> \author Univ. of Tennessee
+*> \author Univ. of California Berkeley
+*> \author Univ. of Colorado Denver
+*> \author NAG Ltd.
+*
+*> \date April 2012
+*
+*> \ingroup double_blas_testing
+*
+* =====================================================================
PROGRAM DBLAT1
-* Test program for the DOUBLE PRECISION Level 1 BLAS.
-* Based upon the original BLAS test routine together with:
-* F06EAF Example Program Text
+*
+* -- Reference BLAS test routine (version 3.4.1) --
+* -- Reference BLAS is a software package provided by Univ. of Tennessee, --
+* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+* April 2012
+*
+* =====================================================================
+*
* .. Parameters ..
INTEGER NOUT
PARAMETER (NOUT=6)
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
DOUBLE PRECISION SFAC
@@ -14,31 +56,30 @@
* .. External Subroutines ..
EXTERNAL CHECK0, CHECK1, CHECK2, CHECK3, HEADER
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
DATA SFAC/9.765625D-4/
* .. Executable Statements ..
WRITE (NOUT,99999)
- DO 20 IC = 1, 10
+ DO 20 IC = 1, 13
ICASE = IC
CALL HEADER
*
-* .. Initialize PASS, INCX, INCY, and MODE for a new case. ..
-* .. the value 9999 for INCX, INCY or MODE will appear in the ..
+* .. Initialize PASS, INCX, and INCY for a new case. ..
+* .. the value 9999 for INCX or INCY will appear in the ..
* .. detailed output, if any, for cases that do not involve ..
* .. these parameters ..
*
PASS = .TRUE.
INCX = 9999
INCY = 9999
- MODE = 9999
- IF (ICASE.EQ.3) THEN
+ IF (ICASE.EQ.3 .OR. ICASE.EQ.11) THEN
CALL CHECK0(SFAC)
ELSE IF (ICASE.EQ.7 .OR. ICASE.EQ.8 .OR. ICASE.EQ.9 .OR.
+ ICASE.EQ.10) THEN
CALL CHECK1(SFAC)
ELSE IF (ICASE.EQ.1 .OR. ICASE.EQ.2 .OR. ICASE.EQ.5 .OR.
- + ICASE.EQ.6) THEN
+ + ICASE.EQ.6 .OR. ICASE.EQ.12 .OR. ICASE.EQ.13) THEN
CALL CHECK2(SFAC)
ELSE IF (ICASE.EQ.4) THEN
CALL CHECK3(SFAC)
@@ -56,12 +97,12 @@
INTEGER NOUT
PARAMETER (NOUT=6)
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Arrays ..
- CHARACTER*6 L(10)
+ CHARACTER*6 L(13)
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
DATA L(1)/' DDOT '/
DATA L(2)/'DAXPY '/
@@ -73,6 +114,9 @@
DATA L(8)/'DASUM '/
DATA L(9)/'DSCAL '/
DATA L(10)/'IDAMAX'/
+ DATA L(11)/'DROTMG'/
+ DATA L(12)/'DROTM '/
+ DATA L(13)/'DSDOT '/
* .. Executable Statements ..
WRITE (NOUT,99999) ICASE, L(ICASE)
RETURN
@@ -86,18 +130,18 @@
* .. Scalar Arguments ..
DOUBLE PRECISION SFAC
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
- DOUBLE PRECISION D12, SA, SB, SC, SS
- INTEGER K
+ DOUBLE PRECISION SA, SB, SC, SS, D12
+ INTEGER I, K
* .. Local Arrays ..
DOUBLE PRECISION DA1(8), DATRUE(8), DB1(8), DBTRUE(8), DC1(8),
- + DS1(8)
+ $ DS1(8), DAB(4,9), DTEMP(9), DTRUE(9,9)
* .. External Subroutines ..
- EXTERNAL DROTG, STEST1
+ EXTERNAL DROTG, DROTMG, STEST1
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
DATA DA1/0.3D0, 0.4D0, -0.3D0, -0.4D0, -0.3D0, 0.0D0,
+ 0.0D0, 1.0D0/
@@ -111,7 +155,52 @@
+ 0.0D0, 1.0D0, 1.0D0/
DATA DBTRUE/0.0D0, 0.6D0, 0.0D0, -0.6D0, 0.0D0,
+ 0.0D0, 1.0D0, 0.0D0/
- DATA D12/4096.0D0/
+* INPUT FOR MODIFIED GIVENS
+ DATA DAB/ .1D0,.3D0,1.2D0,.2D0,
+ A .7D0, .2D0, .6D0, 4.2D0,
+ B 0.D0,0.D0,0.D0,0.D0,
+ C 4.D0, -1.D0, 2.D0, 4.D0,
+ D 6.D-10, 2.D-2, 1.D5, 10.D0,
+ E 4.D10, 2.D-2, 1.D-5, 10.D0,
+ F 2.D-10, 4.D-2, 1.D5, 10.D0,
+ G 2.D10, 4.D-2, 1.D-5, 10.D0,
+ H 4.D0, -2.D0, 8.D0, 4.D0 /
+* TRUE RESULTS FOR MODIFIED GIVENS
+ DATA DTRUE/0.D0,0.D0, 1.3D0, .2D0, 0.D0,0.D0,0.D0, .5D0, 0.D0,
+ A 0.D0,0.D0, 4.5D0, 4.2D0, 1.D0, .5D0, 0.D0,0.D0,0.D0,
+ B 0.D0,0.D0,0.D0,0.D0, -2.D0, 0.D0,0.D0,0.D0,0.D0,
+ C 0.D0,0.D0,0.D0, 4.D0, -1.D0, 0.D0,0.D0,0.D0,0.D0,
+ D 0.D0, 15.D-3, 0.D0, 10.D0, -1.D0, 0.D0, -1.D-4,
+ E 0.D0, 1.D0,
+ F 0.D0,0.D0, 6144.D-5, 10.D0, -1.D0, 4096.D0, -1.D6,
+ G 0.D0, 1.D0,
+ H 0.D0,0.D0,15.D0,10.D0,-1.D0, 5.D-5, 0.D0,1.D0,0.D0,
+ I 0.D0,0.D0, 15.D0, 10.D0, -1. D0, 5.D5, -4096.D0,
+ J 1.D0, 4096.D-6,
+ K 0.D0,0.D0, 7.D0, 4.D0, 0.D0,0.D0, -.5D0, -.25D0, 0.D0/
+* 4096 = 2 ** 12
+ DATA D12 /4096.D0/
+ DTRUE(1,1) = 12.D0 / 130.D0
+ DTRUE(2,1) = 36.D0 / 130.D0
+ DTRUE(7,1) = -1.D0 / 6.D0
+ DTRUE(1,2) = 14.D0 / 75.D0
+ DTRUE(2,2) = 49.D0 / 75.D0
+ DTRUE(9,2) = 1.D0 / 7.D0
+ DTRUE(1,5) = 45.D-11 * (D12 * D12)
+ DTRUE(3,5) = 4.D5 / (3.D0 * D12)
+ DTRUE(6,5) = 1.D0 / D12
+ DTRUE(8,5) = 1.D4 / (3.D0 * D12)
+ DTRUE(1,6) = 4.D10 / (1.5D0 * D12 * D12)
+ DTRUE(2,6) = 2.D-2 / 1.5D0
+ DTRUE(8,6) = 5.D-7 * D12
+ DTRUE(1,7) = 4.D0 / 150.D0
+ DTRUE(2,7) = (2.D-10 / 1.5D0) * (D12 * D12)
+ DTRUE(7,7) = -DTRUE(6,5)
+ DTRUE(9,7) = 1.D4 / D12
+ DTRUE(1,8) = DTRUE(1,7)
+ DTRUE(2,8) = 2.D10 / (1.5D0 * D12 * D12)
+ DTRUE(1,9) = 32.D0 / 7.D0
+ DTRUE(2,9) = -16.D0 / 7.D0
* .. Executable Statements ..
*
* Compute true values which cannot be prestored
@@ -134,6 +223,15 @@
CALL STEST1(SB,DBTRUE(K),DBTRUE(K),SFAC)
CALL STEST1(SC,DC1(K),DC1(K),SFAC)
CALL STEST1(SS,DS1(K),DS1(K),SFAC)
+ ELSEIF (ICASE.EQ.11) THEN
+* .. DROTMG ..
+ DO I=1,4
+ DTEMP(I)= DAB(I,K)
+ DTEMP(I+4) = 0.0
+ END DO
+ DTEMP(9) = 0.0
+ CALL DROTMG(DTEMP(1),DTEMP(2),DTEMP(3),DTEMP(4),DTEMP(5))
+ CALL STEST(9,DTEMP,DTRUE(1,K),DTRUE(1,K),SFAC)
ELSE
WRITE (NOUT,*) ' Shouldn''t be here in CHECK0'
STOP
@@ -148,7 +246,7 @@
* .. Scalar Arguments ..
DOUBLE PRECISION SFAC
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
INTEGER I, LEN, NP1
@@ -165,7 +263,7 @@
* .. Intrinsic Functions ..
INTRINSIC MAX
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
DATA SA/0.3D0, -1.0D0, 0.0D0, 1.0D0, 0.3D0, 0.3D0,
+ 0.3D0, 0.3D0, 0.3D0, 0.3D0/
@@ -212,11 +310,11 @@
IF (ICASE.EQ.7) THEN
* .. DNRM2 ..
STEMP(1) = DTRUE1(NP1)
- CALL STEST1(DNRM2(N,SX,INCX),STEMP,STEMP,SFAC)
+ CALL STEST1(DNRM2(N,SX,INCX),STEMP(1),STEMP,SFAC)
ELSE IF (ICASE.EQ.8) THEN
* .. DASUM ..
STEMP(1) = DTRUE3(NP1)
- CALL STEST1(DASUM(N,SX,INCX),STEMP,STEMP,SFAC)
+ CALL STEST1(DASUM(N,SX,INCX),STEMP(1),STEMP,SFAC)
ELSE IF (ICASE.EQ.9) THEN
* .. DSCAL ..
CALL DSCAL(N,SA((INCX-1)*5+NP1),SX,INCX)
@@ -242,27 +340,39 @@
* .. Scalar Arguments ..
DOUBLE PRECISION SFAC
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
- DOUBLE PRECISION SA, SC, SS
- INTEGER I, J, KI, KN, KSIZE, LENX, LENY, MX, MY
+ DOUBLE PRECISION SA
+ INTEGER I, J, KI, KN, KNI, KPAR, KSIZE, LENX, LENY,
+ $ MX, MY
* .. Local Arrays ..
DOUBLE PRECISION DT10X(7,4,4), DT10Y(7,4,4), DT7(4,4),
- + DT8(7,4,4), DT9X(7,4,4), DT9Y(7,4,4), DX1(7),
- + DY1(7), SSIZE1(4), SSIZE2(14,2), STX(7), STY(7),
- + SX(7), SY(7)
+ $ DT8(7,4,4), DX1(7),
+ $ DY1(7), SSIZE1(4), SSIZE2(14,2), SSIZE(7),
+ $ STX(7), STY(7), SX(7), SY(7),
+ $ DPAR(5,4), DT19X(7,4,16),DT19XA(7,4,4),
+ $ DT19XB(7,4,4), DT19XC(7,4,4),DT19XD(7,4,4),
+ $ DT19Y(7,4,16), DT19YA(7,4,4),DT19YB(7,4,4),
+ $ DT19YC(7,4,4), DT19YD(7,4,4), DTEMP(5)
INTEGER INCXS(4), INCYS(4), LENS(4,2), NS(4)
* .. External Functions ..
- DOUBLE PRECISION DDOT
- EXTERNAL DDOT
+ DOUBLE PRECISION DDOT, DSDOT
+ EXTERNAL DDOT, DSDOT
* .. External Subroutines ..
- EXTERNAL DAXPY, DCOPY, DSWAP, STEST, STEST1
+ EXTERNAL DAXPY, DCOPY, DROTM, DSWAP, STEST, STEST1
* .. Intrinsic Functions ..
INTRINSIC ABS, MIN
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
+ EQUIVALENCE (DT19X(1,1,1),DT19XA(1,1,1)),(DT19X(1,1,5),
+ A DT19XB(1,1,1)),(DT19X(1,1,9),DT19XC(1,1,1)),
+ B (DT19X(1,1,13),DT19XD(1,1,1))
+ EQUIVALENCE (DT19Y(1,1,1),DT19YA(1,1,1)),(DT19Y(1,1,5),
+ A DT19YB(1,1,1)),(DT19Y(1,1,9),DT19YC(1,1,1)),
+ B (DT19Y(1,1,13),DT19YD(1,1,1))
+
DATA SA/0.3D0/
DATA INCXS/1, 2, -2, -1/
DATA INCYS/1, -2, 1, -2/
@@ -272,7 +382,6 @@
+ -0.4D0/
DATA DY1/0.5D0, -0.9D0, 0.3D0, 0.7D0, -0.6D0, 0.2D0,
+ 0.8D0/
- DATA SC, SS/0.8D0, 0.6D0/
DATA DT7/0.0D0, 0.30D0, 0.21D0, 0.62D0, 0.0D0,
+ 0.30D0, -0.07D0, 0.85D0, 0.0D0, 0.30D0, -0.79D0,
+ -0.74D0, 0.0D0, 0.30D0, 0.33D0, 1.27D0/
@@ -295,44 +404,6 @@
+ 0.0D0, 0.68D0, -0.9D0, 0.33D0, 0.0D0, 0.0D0,
+ 0.0D0, 0.0D0, 0.68D0, -0.9D0, 0.33D0, 0.7D0,
+ -0.75D0, 0.2D0, 1.04D0/
- DATA DT9X/0.6D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.78D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.78D0, -0.46D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.78D0, -0.46D0, -0.22D0,
- + 1.06D0, 0.0D0, 0.0D0, 0.0D0, 0.6D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.78D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.66D0, 0.1D0, -0.1D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.96D0, 0.1D0, -0.76D0, 0.8D0, 0.90D0,
- + -0.3D0, -0.02D0, 0.6D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.78D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.0D0, -0.06D0, 0.1D0,
- + -0.1D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.90D0,
- + 0.1D0, -0.22D0, 0.8D0, 0.18D0, -0.3D0, -0.02D0,
- + 0.6D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.78D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.78D0, 0.26D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.78D0, 0.26D0, -0.76D0, 1.12D0,
- + 0.0D0, 0.0D0, 0.0D0/
- DATA DT9Y/0.5D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.04D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.04D0, -0.78D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.04D0, -0.78D0, 0.54D0,
- + 0.08D0, 0.0D0, 0.0D0, 0.0D0, 0.5D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.04D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.7D0,
- + -0.9D0, -0.12D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.64D0, -0.9D0, -0.30D0, 0.7D0, -0.18D0, 0.2D0,
- + 0.28D0, 0.5D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.04D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.7D0, -1.08D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.64D0, -1.26D0,
- + 0.54D0, 0.20D0, 0.0D0, 0.0D0, 0.0D0, 0.5D0,
- + 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.04D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.04D0, -0.9D0, 0.18D0, 0.0D0, 0.0D0,
- + 0.0D0, 0.0D0, 0.04D0, -0.9D0, 0.18D0, 0.7D0,
- + -0.18D0, 0.2D0, 0.16D0/
DATA DT10X/0.6D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
+ 0.0D0, 0.5D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0,
+ 0.0D0, 0.5D0, -0.9D0, 0.0D0, 0.0D0, 0.0D0,
@@ -375,6 +446,150 @@
+ 0.0D0, 1.17D0, 1.17D0, 1.17D0, 1.17D0, 1.17D0,
+ 1.17D0, 1.17D0, 1.17D0, 1.17D0, 1.17D0, 1.17D0,
+ 1.17D0, 1.17D0, 1.17D0/
+*
+* FOR DROTM
+*
+ DATA DPAR/-2.D0, 0.D0,0.D0,0.D0,0.D0,
+ A -1.D0, 2.D0, -3.D0, -4.D0, 5.D0,
+ B 0.D0, 0.D0, 2.D0, -3.D0, 0.D0,
+ C 1.D0, 5.D0, 2.D0, 0.D0, -4.D0/
+* TRUE X RESULTS F0R ROTATIONS DROTM
+ DATA DT19XA/.6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ A .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ B .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ C .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ D .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ E -.8D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ F -.9D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ G 3.5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ H .6D0, .1D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ I -.8D0, 3.8D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ J -.9D0, 2.8D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ K 3.5D0, -.4D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ L .6D0, .1D0, -.5D0, .8D0, 0.D0,0.D0,0.D0,
+ M -.8D0, 3.8D0, -2.2D0, -1.2D0, 0.D0,0.D0,0.D0,
+ N -.9D0, 2.8D0, -1.4D0, -1.3D0, 0.D0,0.D0,0.D0,
+ O 3.5D0, -.4D0, -2.2D0, 4.7D0, 0.D0,0.D0,0.D0/
+*
+ DATA DT19XB/.6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ A .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ B .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ C .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ D .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ E -.8D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ F -.9D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ G 3.5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ H .6D0, .1D0, -.5D0, 0.D0,0.D0,0.D0,0.D0,
+ I 0.D0, .1D0, -3.0D0, 0.D0,0.D0,0.D0,0.D0,
+ J -.3D0, .1D0, -2.0D0, 0.D0,0.D0,0.D0,0.D0,
+ K 3.3D0, .1D0, -2.0D0, 0.D0,0.D0,0.D0,0.D0,
+ L .6D0, .1D0, -.5D0, .8D0, .9D0, -.3D0, -.4D0,
+ M -2.0D0, .1D0, 1.4D0, .8D0, .6D0, -.3D0, -2.8D0,
+ N -1.8D0, .1D0, 1.3D0, .8D0, 0.D0, -.3D0, -1.9D0,
+ O 3.8D0, .1D0, -3.1D0, .8D0, 4.8D0, -.3D0, -1.5D0 /
+*
+ DATA DT19XC/.6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ A .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ B .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ C .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ D .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ E -.8D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ F -.9D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ G 3.5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ H .6D0, .1D0, -.5D0, 0.D0,0.D0,0.D0,0.D0,
+ I 4.8D0, .1D0, -3.0D0, 0.D0,0.D0,0.D0,0.D0,
+ J 3.3D0, .1D0, -2.0D0, 0.D0,0.D0,0.D0,0.D0,
+ K 2.1D0, .1D0, -2.0D0, 0.D0,0.D0,0.D0,0.D0,
+ L .6D0, .1D0, -.5D0, .8D0, .9D0, -.3D0, -.4D0,
+ M -1.6D0, .1D0, -2.2D0, .8D0, 5.4D0, -.3D0, -2.8D0,
+ N -1.5D0, .1D0, -1.4D0, .8D0, 3.6D0, -.3D0, -1.9D0,
+ O 3.7D0, .1D0, -2.2D0, .8D0, 3.6D0, -.3D0, -1.5D0 /
+*
+ DATA DT19XD/.6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ A .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ B .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ C .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ D .6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ E -.8D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ F -.9D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ G 3.5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ H .6D0, .1D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ I -.8D0, -1.0D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ J -.9D0, -.8D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ K 3.5D0, .8D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ L .6D0, .1D0, -.5D0, .8D0, 0.D0,0.D0,0.D0,
+ M -.8D0, -1.0D0, 1.4D0, -1.6D0, 0.D0,0.D0,0.D0,
+ N -.9D0, -.8D0, 1.3D0, -1.6D0, 0.D0,0.D0,0.D0,
+ O 3.5D0, .8D0, -3.1D0, 4.8D0, 0.D0,0.D0,0.D0/
+* TRUE Y RESULTS FOR ROTATIONS DROTM
+ DATA DT19YA/.5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ A .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ B .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ C .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ D .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ E .7D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ F 1.7D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ G -2.6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ H .5D0, -.9D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ I .7D0, -4.8D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ J 1.7D0, -.7D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ K -2.6D0, 3.5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ L .5D0, -.9D0, .3D0, .7D0, 0.D0,0.D0,0.D0,
+ M .7D0, -4.8D0, 3.0D0, 1.1D0, 0.D0,0.D0,0.D0,
+ N 1.7D0, -.7D0, -.7D0, 2.3D0, 0.D0,0.D0,0.D0,
+ O -2.6D0, 3.5D0, -.7D0, -3.6D0, 0.D0,0.D0,0.D0/
+*
+ DATA DT19YB/.5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ A .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ B .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ C .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ D .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ E .7D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ F 1.7D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ G -2.6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ H .5D0, -.9D0, .3D0, 0.D0,0.D0,0.D0,0.D0,
+ I 4.0D0, -.9D0, -.3D0, 0.D0,0.D0,0.D0,0.D0,
+ J -.5D0, -.9D0, 1.5D0, 0.D0,0.D0,0.D0,0.D0,
+ K -1.5D0, -.9D0, -1.8D0, 0.D0,0.D0,0.D0,0.D0,
+ L .5D0, -.9D0, .3D0, .7D0, -.6D0, .2D0, .8D0,
+ M 3.7D0, -.9D0, -1.2D0, .7D0, -1.5D0, .2D0, 2.2D0,
+ N -.3D0, -.9D0, 2.1D0, .7D0, -1.6D0, .2D0, 2.0D0,
+ O -1.6D0, -.9D0, -2.1D0, .7D0, 2.9D0, .2D0, -3.8D0 /
+*
+ DATA DT19YC/.5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ A .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ B .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ C .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ D .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ E .7D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ F 1.7D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ G -2.6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ H .5D0, -.9D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ I 4.0D0, -6.3D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ J -.5D0, .3D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ K -1.5D0, 3.0D0, 0.D0,0.D0,0.D0,0.D0,0.D0,
+ L .5D0, -.9D0, .3D0, .7D0, 0.D0,0.D0,0.D0,
+ M 3.7D0, -7.2D0, 3.0D0, 1.7D0, 0.D0,0.D0,0.D0,
+ N -.3D0, .9D0, -.7D0, 1.9D0, 0.D0,0.D0,0.D0,
+ O -1.6D0, 2.7D0, -.7D0, -3.4D0, 0.D0,0.D0,0.D0/
+*
+ DATA DT19YD/.5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ A .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ B .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ C .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ D .5D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ E .7D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ F 1.7D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ G -2.6D0, 0.D0,0.D0,0.D0,0.D0,0.D0,0.D0,
+ H .5D0, -.9D0, .3D0, 0.D0,0.D0,0.D0,0.D0,
+ I .7D0, -.9D0, 1.2D0, 0.D0,0.D0,0.D0,0.D0,
+ J 1.7D0, -.9D0, .5D0, 0.D0,0.D0,0.D0,0.D0,
+ K -2.6D0, -.9D0, -1.3D0, 0.D0,0.D0,0.D0,0.D0,
+ L .5D0, -.9D0, .3D0, .7D0, -.6D0, .2D0, .8D0,
+ M .7D0, -.9D0, 1.2D0, .7D0, -1.5D0, .2D0, 1.6D0,
+ N 1.7D0, -.9D0, .5D0, .7D0, -1.6D0, .2D0, 2.4D0,
+ O -2.6D0, -.9D0, -1.3D0, .7D0, 2.9D0, .2D0, -4.0D0 /
+*
* .. Executable Statements ..
*
DO 120 KI = 1, 4
@@ -421,6 +636,39 @@
80 CONTINUE
CALL STEST(LENX,SX,STX,SSIZE2(1,1),1.0D0)
CALL STEST(LENY,SY,STY,SSIZE2(1,1),1.0D0)
+ ELSE IF (ICASE.EQ.12) THEN
+* .. DROTM ..
+ KNI=KN+4*(KI-1)
+ DO KPAR=1,4
+ DO I=1,7
+ SX(I) = DX1(I)
+ SY(I) = DY1(I)
+ STX(I)= DT19X(I,KPAR,KNI)
+ STY(I)= DT19Y(I,KPAR,KNI)
+ END DO
+*
+ DO I=1,5
+ DTEMP(I) = DPAR(I,KPAR)
+ END DO
+*
+ DO I=1,LENX
+ SSIZE(I)=STX(I)
+ END DO
+* SEE REMARK ABOVE ABOUT DT11X(1,2,7)
+* AND DT11X(5,3,8).
+ IF ((KPAR .EQ. 2) .AND. (KNI .EQ. 7))
+ $ SSIZE(1) = 2.4D0
+ IF ((KPAR .EQ. 3) .AND. (KNI .EQ. 8))
+ $ SSIZE(5) = 1.8D0
+*
+ CALL DROTM(N,SX,INCX,SY,INCY,DTEMP)
+ CALL STEST(LENX,SX,STX,SSIZE,SFAC)
+ CALL STEST(LENY,SY,STY,STY,SFAC)
+ END DO
+ ELSE IF (ICASE.EQ.13) THEN
+* .. DSDOT ..
+ CALL TESTDSDOT(REAL(DSDOT(N,REAL(SX),INCX,REAL(SY),INCY)),
+ $ REAL(DT7(KN,KI)),REAL(SSIZE1(KN)), .3125E-1)
ELSE
WRITE (NOUT,*) ' Shouldn''t be here in CHECK2'
STOP
@@ -436,10 +684,10 @@
* .. Scalar Arguments ..
DOUBLE PRECISION SFAC
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
- DOUBLE PRECISION SA, SC, SS
+ DOUBLE PRECISION SC, SS
INTEGER I, K, KI, KN, KSIZE, LENX, LENY, MX, MY
* .. Local Arrays ..
DOUBLE PRECISION COPYX(5), COPYY(5), DT9X(7,4,4), DT9Y(7,4,4),
@@ -454,9 +702,8 @@
* .. Intrinsic Functions ..
INTRINSIC ABS, MIN
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
- DATA SA/0.3D0/
DATA INCXS/1, 2, -2, -1/
DATA INCYS/1, -2, 1, -2/
DATA LENS/1, 1, 2, 4, 1, 1, 3, 7/
@@ -647,14 +894,15 @@
*
* .. Parameters ..
INTEGER NOUT
- PARAMETER (NOUT=6)
+ DOUBLE PRECISION ZERO
+ PARAMETER (NOUT=6, ZERO=0.0D0)
* .. Scalar Arguments ..
DOUBLE PRECISION SFAC
INTEGER LEN
* .. Array Arguments ..
DOUBLE PRECISION SCOMP(LEN), SSIZE(LEN), STRUE(LEN)
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
DOUBLE PRECISION SD
@@ -665,12 +913,12 @@
* .. Intrinsic Functions ..
INTRINSIC ABS
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Executable Statements ..
*
DO 40 I = 1, LEN
SD = SCOMP(I) - STRUE(I)
- IF (SDIFF(ABS(SSIZE(I))+ABS(SFAC*SD),ABS(SSIZE(I))).EQ.0.0D0)
+ IF (ABS(SFAC*SD) .LE. ABS(SSIZE(I))*EPSILON(ZERO))
+ GO TO 40
*
* HERE SCOMP(I) IS NOT CLOSE TO STRUE(I).
@@ -680,16 +928,64 @@
PASS = .FALSE.
WRITE (NOUT,99999)
WRITE (NOUT,99998)
- 20 WRITE (NOUT,99997) ICASE, N, INCX, INCY, MODE, I, SCOMP(I),
+ 20 WRITE (NOUT,99997) ICASE, N, INCX, INCY, I, SCOMP(I),
+ STRUE(I), SD, SSIZE(I)
40 CONTINUE
RETURN
*
99999 FORMAT (' FAIL')
-99998 FORMAT (/' CASE N INCX INCY MODE I ',
+99998 FORMAT (/' CASE N INCX INCY I ',
+ + ' COMP(I) TRUE(I) DIFFERENCE',
+ + ' SIZE(I)',/1X)
+99997 FORMAT (1X,I4,I3,2I5,I3,2D36.8,2D12.4)
+ END
+ SUBROUTINE TESTDSDOT(SCOMP,STRUE,SSIZE,SFAC)
+* ********************************* STEST **************************
+*
+* THIS SUBR COMPARES ARRAYS SCOMP() AND STRUE() OF LENGTH LEN TO
+* SEE IF THE TERM BY TERM DIFFERENCES, MULTIPLIED BY SFAC, ARE
+* NEGLIGIBLE.
+*
+* C. L. LAWSON, JPL, 1974 DEC 10
+*
+* .. Parameters ..
+ INTEGER NOUT
+ REAL ZERO
+ PARAMETER (NOUT=6, ZERO=0.0E0)
+* .. Scalar Arguments ..
+ REAL SFAC, SCOMP, SSIZE, STRUE
+* .. Scalars in Common ..
+ INTEGER ICASE, INCX, INCY, N
+ LOGICAL PASS
+* .. Local Scalars ..
+ REAL SD
+* .. Intrinsic Functions ..
+ INTRINSIC ABS
+* .. Common blocks ..
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
+* .. Executable Statements ..
+*
+ SD = SCOMP - STRUE
+ IF (ABS(SFAC*SD) .LE. ABS(SSIZE) * EPSILON(ZERO))
+ + GO TO 40
+*
+* HERE SCOMP(I) IS NOT CLOSE TO STRUE(I).
+*
+ IF ( .NOT. PASS) GO TO 20
+* PRINT FAIL MESSAGE AND HEADER.
+ PASS = .FALSE.
+ WRITE (NOUT,99999)
+ WRITE (NOUT,99998)
+ 20 WRITE (NOUT,99997) ICASE, N, INCX, INCY, SCOMP,
+ + STRUE, SD, SSIZE
+ 40 CONTINUE
+ RETURN
+*
+99999 FORMAT (' FAIL')
+99998 FORMAT (/' CASE N INCX INCY ',
+ ' COMP(I) TRUE(I) DIFFERENCE',
+ ' SIZE(I)',/1X)
-99997 FORMAT (1X,I4,I3,3I5,I3,2D36.8,2D12.4)
+99997 FORMAT (1X,I4,I3,1I5,I3,2E36.8,2E12.4)
END
SUBROUTINE STEST1(SCOMP1,STRUE1,SSIZE,SFAC)
* ************************* STEST1 *****************************
@@ -739,12 +1035,12 @@
* .. Scalar Arguments ..
INTEGER ICOMP, ITRUE
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
INTEGER ID
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Executable Statements ..
*
IF (ICOMP.EQ.ITRUE) GO TO 40
@@ -757,13 +1053,13 @@
WRITE (NOUT,99999)
WRITE (NOUT,99998)
20 ID = ICOMP - ITRUE
- WRITE (NOUT,99997) ICASE, N, INCX, INCY, MODE, ICOMP, ITRUE, ID
+ WRITE (NOUT,99997) ICASE, N, INCX, INCY, ICOMP, ITRUE, ID
40 CONTINUE
RETURN
*
99999 FORMAT (' FAIL')
-99998 FORMAT (/' CASE N INCX INCY MODE ',
+99998 FORMAT (/' CASE N INCX INCY ',
+ ' COMP TRUE DIFFERENCE',
+ /1X)
-99997 FORMAT (1X,I4,I3,3I5,2I36,I12)
+99997 FORMAT (1X,I4,I3,2I5,2I36,I12)
END
diff --git a/resources/3rdparty/eigen/blas/testing/sblat1.f b/resources/3rdparty/eigen/blas/testing/sblat1.f
index a982d1852..6657c2693 100644
--- a/resources/3rdparty/eigen/blas/testing/sblat1.f
+++ b/resources/3rdparty/eigen/blas/testing/sblat1.f
@@ -1,12 +1,54 @@
+*> \brief \b SBLAT1
+*
+* =========== DOCUMENTATION ===========
+*
+* Online html documentation available at
+* http://www.netlib.org/lapack/explore-html/
+*
+* Definition:
+* ===========
+*
+* PROGRAM SBLAT1
+*
+*
+*> \par Purpose:
+* =============
+*>
+*> \verbatim
+*>
+*> Test program for the REAL Level 1 BLAS.
+*>
+*> Based upon the original BLAS test routine together with:
+*> F06EAF Example Program Text
+*> \endverbatim
+*
+* Authors:
+* ========
+*
+*> \author Univ. of Tennessee
+*> \author Univ. of California Berkeley
+*> \author Univ. of Colorado Denver
+*> \author NAG Ltd.
+*
+*> \date April 2012
+*
+*> \ingroup single_blas_testing
+*
+* =====================================================================
PROGRAM SBLAT1
-* Test program for the REAL Level 1 BLAS.
-* Based upon the original BLAS test routine together with:
-* F06EAF Example Program Text
+*
+* -- Reference BLAS test routine (version 3.4.1) --
+* -- Reference BLAS is a software package provided by Univ. of Tennessee, --
+* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+* April 2012
+*
+* =====================================================================
+*
* .. Parameters ..
INTEGER NOUT
PARAMETER (NOUT=6)
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
REAL SFAC
@@ -14,31 +56,30 @@
* .. External Subroutines ..
EXTERNAL CHECK0, CHECK1, CHECK2, CHECK3, HEADER
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
DATA SFAC/9.765625E-4/
* .. Executable Statements ..
WRITE (NOUT,99999)
- DO 20 IC = 1, 10
+ DO 20 IC = 1, 13
ICASE = IC
CALL HEADER
*
-* .. Initialize PASS, INCX, INCY, and MODE for a new case. ..
-* .. the value 9999 for INCX, INCY or MODE will appear in the ..
+* .. Initialize PASS, INCX, and INCY for a new case. ..
+* .. the value 9999 for INCX or INCY will appear in the ..
* .. detailed output, if any, for cases that do not involve ..
* .. these parameters ..
*
PASS = .TRUE.
INCX = 9999
INCY = 9999
- MODE = 9999
- IF (ICASE.EQ.3) THEN
+ IF (ICASE.EQ.3 .OR. ICASE.EQ.11) THEN
CALL CHECK0(SFAC)
ELSE IF (ICASE.EQ.7 .OR. ICASE.EQ.8 .OR. ICASE.EQ.9 .OR.
+ ICASE.EQ.10) THEN
CALL CHECK1(SFAC)
ELSE IF (ICASE.EQ.1 .OR. ICASE.EQ.2 .OR. ICASE.EQ.5 .OR.
- + ICASE.EQ.6) THEN
+ + ICASE.EQ.6 .OR. ICASE.EQ.12 .OR. ICASE.EQ.13) THEN
CALL CHECK2(SFAC)
ELSE IF (ICASE.EQ.4) THEN
CALL CHECK3(SFAC)
@@ -56,12 +97,12 @@
INTEGER NOUT
PARAMETER (NOUT=6)
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Arrays ..
- CHARACTER*6 L(10)
+ CHARACTER*6 L(13)
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
DATA L(1)/' SDOT '/
DATA L(2)/'SAXPY '/
@@ -73,6 +114,9 @@
DATA L(8)/'SASUM '/
DATA L(9)/'SSCAL '/
DATA L(10)/'ISAMAX'/
+ DATA L(11)/'SROTMG'/
+ DATA L(12)/'SROTM '/
+ DATA L(13)/'SDSDOT'/
* .. Executable Statements ..
WRITE (NOUT,99999) ICASE, L(ICASE)
RETURN
@@ -86,18 +130,18 @@
* .. Scalar Arguments ..
REAL SFAC
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
REAL D12, SA, SB, SC, SS
- INTEGER K
+ INTEGER I, K
* .. Local Arrays ..
REAL DA1(8), DATRUE(8), DB1(8), DBTRUE(8), DC1(8),
- + DS1(8)
+ + DS1(8), DAB(4,9), DTEMP(9), DTRUE(9,9)
* .. External Subroutines ..
- EXTERNAL SROTG, STEST1
+ EXTERNAL SROTG, SROTMG, STEST1
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
DATA DA1/0.3E0, 0.4E0, -0.3E0, -0.4E0, -0.3E0, 0.0E0,
+ 0.0E0, 1.0E0/
@@ -111,7 +155,52 @@
+ 0.0E0, 1.0E0, 1.0E0/
DATA DBTRUE/0.0E0, 0.6E0, 0.0E0, -0.6E0, 0.0E0,
+ 0.0E0, 1.0E0, 0.0E0/
- DATA D12/4096.0E0/
+* INPUT FOR MODIFIED GIVENS
+ DATA DAB/ .1E0,.3E0,1.2E0,.2E0,
+ A .7E0, .2E0, .6E0, 4.2E0,
+ B 0.E0,0.E0,0.E0,0.E0,
+ C 4.E0, -1.E0, 2.E0, 4.E0,
+ D 6.E-10, 2.E-2, 1.E5, 10.E0,
+ E 4.E10, 2.E-2, 1.E-5, 10.E0,
+ F 2.E-10, 4.E-2, 1.E5, 10.E0,
+ G 2.E10, 4.E-2, 1.E-5, 10.E0,
+ H 4.E0, -2.E0, 8.E0, 4.E0 /
+* TRUE RESULTS FOR MODIFIED GIVENS
+ DATA DTRUE/0.E0,0.E0, 1.3E0, .2E0, 0.E0,0.E0,0.E0, .5E0, 0.E0,
+ A 0.E0,0.E0, 4.5E0, 4.2E0, 1.E0, .5E0, 0.E0,0.E0,0.E0,
+ B 0.E0,0.E0,0.E0,0.E0, -2.E0, 0.E0,0.E0,0.E0,0.E0,
+ C 0.E0,0.E0,0.E0, 4.E0, -1.E0, 0.E0,0.E0,0.E0,0.E0,
+ D 0.E0, 15.E-3, 0.E0, 10.E0, -1.E0, 0.E0, -1.E-4,
+ E 0.E0, 1.E0,
+ F 0.E0,0.E0, 6144.E-5, 10.E0, -1.E0, 4096.E0, -1.E6,
+ G 0.E0, 1.E0,
+ H 0.E0,0.E0,15.E0,10.E0,-1.E0, 5.E-5, 0.E0,1.E0,0.E0,
+ I 0.E0,0.E0, 15.E0, 10.E0, -1. E0, 5.E5, -4096.E0,
+ J 1.E0, 4096.E-6,
+ K 0.E0,0.E0, 7.E0, 4.E0, 0.E0,0.E0, -.5E0, -.25E0, 0.E0/
+* 4096 = 2 ** 12
+ DATA D12 /4096.E0/
+ DTRUE(1,1) = 12.E0 / 130.E0
+ DTRUE(2,1) = 36.E0 / 130.E0
+ DTRUE(7,1) = -1.E0 / 6.E0
+ DTRUE(1,2) = 14.E0 / 75.E0
+ DTRUE(2,2) = 49.E0 / 75.E0
+ DTRUE(9,2) = 1.E0 / 7.E0
+ DTRUE(1,5) = 45.E-11 * (D12 * D12)
+ DTRUE(3,5) = 4.E5 / (3.E0 * D12)
+ DTRUE(6,5) = 1.E0 / D12
+ DTRUE(8,5) = 1.E4 / (3.E0 * D12)
+ DTRUE(1,6) = 4.E10 / (1.5E0 * D12 * D12)
+ DTRUE(2,6) = 2.E-2 / 1.5E0
+ DTRUE(8,6) = 5.E-7 * D12
+ DTRUE(1,7) = 4.E0 / 150.E0
+ DTRUE(2,7) = (2.E-10 / 1.5E0) * (D12 * D12)
+ DTRUE(7,7) = -DTRUE(6,5)
+ DTRUE(9,7) = 1.E4 / D12
+ DTRUE(1,8) = DTRUE(1,7)
+ DTRUE(2,8) = 2.E10 / (1.5E0 * D12 * D12)
+ DTRUE(1,9) = 32.E0 / 7.E0
+ DTRUE(2,9) = -16.E0 / 7.E0
* .. Executable Statements ..
*
* Compute true values which cannot be prestored
@@ -134,6 +223,15 @@
CALL STEST1(SB,DBTRUE(K),DBTRUE(K),SFAC)
CALL STEST1(SC,DC1(K),DC1(K),SFAC)
CALL STEST1(SS,DS1(K),DS1(K),SFAC)
+ ELSEIF (ICASE.EQ.11) THEN
+* .. SROTMG ..
+ DO I=1,4
+ DTEMP(I)= DAB(I,K)
+ DTEMP(I+4) = 0.0
+ END DO
+ DTEMP(9) = 0.0
+ CALL SROTMG(DTEMP(1),DTEMP(2),DTEMP(3),DTEMP(4),DTEMP(5))
+ CALL STEST(9,DTEMP,DTRUE(1,K),DTRUE(1,K),SFAC)
ELSE
WRITE (NOUT,*) ' Shouldn''t be here in CHECK0'
STOP
@@ -148,7 +246,7 @@
* .. Scalar Arguments ..
REAL SFAC
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
INTEGER I, LEN, NP1
@@ -165,7 +263,7 @@
* .. Intrinsic Functions ..
INTRINSIC MAX
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
DATA SA/0.3E0, -1.0E0, 0.0E0, 1.0E0, 0.3E0, 0.3E0,
+ 0.3E0, 0.3E0, 0.3E0, 0.3E0/
@@ -212,11 +310,11 @@
IF (ICASE.EQ.7) THEN
* .. SNRM2 ..
STEMP(1) = DTRUE1(NP1)
- CALL STEST1(SNRM2(N,SX,INCX),STEMP,STEMP,SFAC)
+ CALL STEST1(SNRM2(N,SX,INCX),STEMP(1),STEMP,SFAC)
ELSE IF (ICASE.EQ.8) THEN
* .. SASUM ..
STEMP(1) = DTRUE3(NP1)
- CALL STEST1(SASUM(N,SX,INCX),STEMP,STEMP,SFAC)
+ CALL STEST1(SASUM(N,SX,INCX),STEMP(1),STEMP,SFAC)
ELSE IF (ICASE.EQ.9) THEN
* .. SSCAL ..
CALL SSCAL(N,SA((INCX-1)*5+NP1),SX,INCX)
@@ -242,27 +340,40 @@
* .. Scalar Arguments ..
REAL SFAC
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
- REAL SA, SC, SS
- INTEGER I, J, KI, KN, KSIZE, LENX, LENY, MX, MY
+ REAL SA
+ INTEGER I, J, KI, KN, KNI, KPAR, KSIZE, LENX, LENY,
+ $ MX, MY
* .. Local Arrays ..
REAL DT10X(7,4,4), DT10Y(7,4,4), DT7(4,4),
- + DT8(7,4,4), DT9X(7,4,4), DT9Y(7,4,4), DX1(7),
- + DY1(7), SSIZE1(4), SSIZE2(14,2), STX(7), STY(7),
- + SX(7), SY(7)
+ $ DT8(7,4,4), DX1(7),
+ $ DY1(7), SSIZE1(4), SSIZE2(14,2), SSIZE3(4),
+ $ SSIZE(7), STX(7), STY(7), SX(7), SY(7),
+ $ DPAR(5,4), DT19X(7,4,16),DT19XA(7,4,4),
+ $ DT19XB(7,4,4), DT19XC(7,4,4),DT19XD(7,4,4),
+ $ DT19Y(7,4,16), DT19YA(7,4,4),DT19YB(7,4,4),
+ $ DT19YC(7,4,4), DT19YD(7,4,4), DTEMP(5),
+ $ ST7B(4,4)
INTEGER INCXS(4), INCYS(4), LENS(4,2), NS(4)
* .. External Functions ..
- REAL SDOT
- EXTERNAL SDOT
+ REAL SDOT, SDSDOT
+ EXTERNAL SDOT, SDSDOT
* .. External Subroutines ..
- EXTERNAL SAXPY, SCOPY, SSWAP, STEST, STEST1
+ EXTERNAL SAXPY, SCOPY, SROTM, SSWAP, STEST, STEST1
* .. Intrinsic Functions ..
INTRINSIC ABS, MIN
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
+ EQUIVALENCE (DT19X(1,1,1),DT19XA(1,1,1)),(DT19X(1,1,5),
+ A DT19XB(1,1,1)),(DT19X(1,1,9),DT19XC(1,1,1)),
+ B (DT19X(1,1,13),DT19XD(1,1,1))
+ EQUIVALENCE (DT19Y(1,1,1),DT19YA(1,1,1)),(DT19Y(1,1,5),
+ A DT19YB(1,1,1)),(DT19Y(1,1,9),DT19YC(1,1,1)),
+ B (DT19Y(1,1,13),DT19YD(1,1,1))
+
DATA SA/0.3E0/
DATA INCXS/1, 2, -2, -1/
DATA INCYS/1, -2, 1, -2/
@@ -272,10 +383,11 @@
+ -0.4E0/
DATA DY1/0.5E0, -0.9E0, 0.3E0, 0.7E0, -0.6E0, 0.2E0,
+ 0.8E0/
- DATA SC, SS/0.8E0, 0.6E0/
DATA DT7/0.0E0, 0.30E0, 0.21E0, 0.62E0, 0.0E0,
+ 0.30E0, -0.07E0, 0.85E0, 0.0E0, 0.30E0, -0.79E0,
+ -0.74E0, 0.0E0, 0.30E0, 0.33E0, 1.27E0/
+ DATA ST7B/ .1, .4, .31, .72, .1, .4, .03, .95,
+ + .1, .4, -.69, -.64, .1, .4, .43, 1.37/
DATA DT8/0.5E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
+ 0.0E0, 0.68E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
+ 0.0E0, 0.0E0, 0.68E0, -0.87E0, 0.0E0, 0.0E0,
@@ -295,44 +407,6 @@
+ 0.0E0, 0.68E0, -0.9E0, 0.33E0, 0.0E0, 0.0E0,
+ 0.0E0, 0.0E0, 0.68E0, -0.9E0, 0.33E0, 0.7E0,
+ -0.75E0, 0.2E0, 1.04E0/
- DATA DT9X/0.6E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.78E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.78E0, -0.46E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.78E0, -0.46E0, -0.22E0,
- + 1.06E0, 0.0E0, 0.0E0, 0.0E0, 0.6E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.78E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.66E0, 0.1E0, -0.1E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.96E0, 0.1E0, -0.76E0, 0.8E0, 0.90E0,
- + -0.3E0, -0.02E0, 0.6E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.78E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.0E0, -0.06E0, 0.1E0,
- + -0.1E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.90E0,
- + 0.1E0, -0.22E0, 0.8E0, 0.18E0, -0.3E0, -0.02E0,
- + 0.6E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.78E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.78E0, 0.26E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.78E0, 0.26E0, -0.76E0, 1.12E0,
- + 0.0E0, 0.0E0, 0.0E0/
- DATA DT9Y/0.5E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.04E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.04E0, -0.78E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.04E0, -0.78E0, 0.54E0,
- + 0.08E0, 0.0E0, 0.0E0, 0.0E0, 0.5E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.04E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.7E0,
- + -0.9E0, -0.12E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.64E0, -0.9E0, -0.30E0, 0.7E0, -0.18E0, 0.2E0,
- + 0.28E0, 0.5E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.04E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.7E0, -1.08E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.64E0, -1.26E0,
- + 0.54E0, 0.20E0, 0.0E0, 0.0E0, 0.0E0, 0.5E0,
- + 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.04E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.04E0, -0.9E0, 0.18E0, 0.0E0, 0.0E0,
- + 0.0E0, 0.0E0, 0.04E0, -0.9E0, 0.18E0, 0.7E0,
- + -0.18E0, 0.2E0, 0.16E0/
DATA DT10X/0.6E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
+ 0.0E0, 0.5E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0, 0.0E0,
+ 0.0E0, 0.5E0, -0.9E0, 0.0E0, 0.0E0, 0.0E0,
@@ -375,6 +449,151 @@
+ 0.0E0, 1.17E0, 1.17E0, 1.17E0, 1.17E0, 1.17E0,
+ 1.17E0, 1.17E0, 1.17E0, 1.17E0, 1.17E0, 1.17E0,
+ 1.17E0, 1.17E0, 1.17E0/
+ DATA SSIZE3/ .1, .4, 1.7, 3.3 /
+*
+* FOR DROTM
+*
+ DATA DPAR/-2.E0, 0.E0,0.E0,0.E0,0.E0,
+ A -1.E0, 2.E0, -3.E0, -4.E0, 5.E0,
+ B 0.E0, 0.E0, 2.E0, -3.E0, 0.E0,
+ C 1.E0, 5.E0, 2.E0, 0.E0, -4.E0/
+* TRUE X RESULTS F0R ROTATIONS DROTM
+ DATA DT19XA/.6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ A .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ B .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ C .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ D .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ E -.8E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ F -.9E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ G 3.5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ H .6E0, .1E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ I -.8E0, 3.8E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ J -.9E0, 2.8E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ K 3.5E0, -.4E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ L .6E0, .1E0, -.5E0, .8E0, 0.E0,0.E0,0.E0,
+ M -.8E0, 3.8E0, -2.2E0, -1.2E0, 0.E0,0.E0,0.E0,
+ N -.9E0, 2.8E0, -1.4E0, -1.3E0, 0.E0,0.E0,0.E0,
+ O 3.5E0, -.4E0, -2.2E0, 4.7E0, 0.E0,0.E0,0.E0/
+*
+ DATA DT19XB/.6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ A .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ B .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ C .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ D .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ E -.8E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ F -.9E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ G 3.5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ H .6E0, .1E0, -.5E0, 0.E0,0.E0,0.E0,0.E0,
+ I 0.E0, .1E0, -3.0E0, 0.E0,0.E0,0.E0,0.E0,
+ J -.3E0, .1E0, -2.0E0, 0.E0,0.E0,0.E0,0.E0,
+ K 3.3E0, .1E0, -2.0E0, 0.E0,0.E0,0.E0,0.E0,
+ L .6E0, .1E0, -.5E0, .8E0, .9E0, -.3E0, -.4E0,
+ M -2.0E0, .1E0, 1.4E0, .8E0, .6E0, -.3E0, -2.8E0,
+ N -1.8E0, .1E0, 1.3E0, .8E0, 0.E0, -.3E0, -1.9E0,
+ O 3.8E0, .1E0, -3.1E0, .8E0, 4.8E0, -.3E0, -1.5E0 /
+*
+ DATA DT19XC/.6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ A .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ B .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ C .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ D .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ E -.8E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ F -.9E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ G 3.5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ H .6E0, .1E0, -.5E0, 0.E0,0.E0,0.E0,0.E0,
+ I 4.8E0, .1E0, -3.0E0, 0.E0,0.E0,0.E0,0.E0,
+ J 3.3E0, .1E0, -2.0E0, 0.E0,0.E0,0.E0,0.E0,
+ K 2.1E0, .1E0, -2.0E0, 0.E0,0.E0,0.E0,0.E0,
+ L .6E0, .1E0, -.5E0, .8E0, .9E0, -.3E0, -.4E0,
+ M -1.6E0, .1E0, -2.2E0, .8E0, 5.4E0, -.3E0, -2.8E0,
+ N -1.5E0, .1E0, -1.4E0, .8E0, 3.6E0, -.3E0, -1.9E0,
+ O 3.7E0, .1E0, -2.2E0, .8E0, 3.6E0, -.3E0, -1.5E0 /
+*
+ DATA DT19XD/.6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ A .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ B .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ C .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ D .6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ E -.8E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ F -.9E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ G 3.5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ H .6E0, .1E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ I -.8E0, -1.0E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ J -.9E0, -.8E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ K 3.5E0, .8E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ L .6E0, .1E0, -.5E0, .8E0, 0.E0,0.E0,0.E0,
+ M -.8E0, -1.0E0, 1.4E0, -1.6E0, 0.E0,0.E0,0.E0,
+ N -.9E0, -.8E0, 1.3E0, -1.6E0, 0.E0,0.E0,0.E0,
+ O 3.5E0, .8E0, -3.1E0, 4.8E0, 0.E0,0.E0,0.E0/
+* TRUE Y RESULTS FOR ROTATIONS DROTM
+ DATA DT19YA/.5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ A .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ B .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ C .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ D .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ E .7E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ F 1.7E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ G -2.6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ H .5E0, -.9E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ I .7E0, -4.8E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ J 1.7E0, -.7E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ K -2.6E0, 3.5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ L .5E0, -.9E0, .3E0, .7E0, 0.E0,0.E0,0.E0,
+ M .7E0, -4.8E0, 3.0E0, 1.1E0, 0.E0,0.E0,0.E0,
+ N 1.7E0, -.7E0, -.7E0, 2.3E0, 0.E0,0.E0,0.E0,
+ O -2.6E0, 3.5E0, -.7E0, -3.6E0, 0.E0,0.E0,0.E0/
+*
+ DATA DT19YB/.5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ A .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ B .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ C .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ D .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ E .7E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ F 1.7E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ G -2.6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ H .5E0, -.9E0, .3E0, 0.E0,0.E0,0.E0,0.E0,
+ I 4.0E0, -.9E0, -.3E0, 0.E0,0.E0,0.E0,0.E0,
+ J -.5E0, -.9E0, 1.5E0, 0.E0,0.E0,0.E0,0.E0,
+ K -1.5E0, -.9E0, -1.8E0, 0.E0,0.E0,0.E0,0.E0,
+ L .5E0, -.9E0, .3E0, .7E0, -.6E0, .2E0, .8E0,
+ M 3.7E0, -.9E0, -1.2E0, .7E0, -1.5E0, .2E0, 2.2E0,
+ N -.3E0, -.9E0, 2.1E0, .7E0, -1.6E0, .2E0, 2.0E0,
+ O -1.6E0, -.9E0, -2.1E0, .7E0, 2.9E0, .2E0, -3.8E0 /
+*
+ DATA DT19YC/.5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ A .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ B .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ C .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ D .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ E .7E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ F 1.7E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ G -2.6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ H .5E0, -.9E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ I 4.0E0, -6.3E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ J -.5E0, .3E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ K -1.5E0, 3.0E0, 0.E0,0.E0,0.E0,0.E0,0.E0,
+ L .5E0, -.9E0, .3E0, .7E0, 0.E0,0.E0,0.E0,
+ M 3.7E0, -7.2E0, 3.0E0, 1.7E0, 0.E0,0.E0,0.E0,
+ N -.3E0, .9E0, -.7E0, 1.9E0, 0.E0,0.E0,0.E0,
+ O -1.6E0, 2.7E0, -.7E0, -3.4E0, 0.E0,0.E0,0.E0/
+*
+ DATA DT19YD/.5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ A .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ B .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ C .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ D .5E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ E .7E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ F 1.7E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ G -2.6E0, 0.E0,0.E0,0.E0,0.E0,0.E0,0.E0,
+ H .5E0, -.9E0, .3E0, 0.E0,0.E0,0.E0,0.E0,
+ I .7E0, -.9E0, 1.2E0, 0.E0,0.E0,0.E0,0.E0,
+ J 1.7E0, -.9E0, .5E0, 0.E0,0.E0,0.E0,0.E0,
+ K -2.6E0, -.9E0, -1.3E0, 0.E0,0.E0,0.E0,0.E0,
+ L .5E0, -.9E0, .3E0, .7E0, -.6E0, .2E0, .8E0,
+ M .7E0, -.9E0, 1.2E0, .7E0, -1.5E0, .2E0, 1.6E0,
+ N 1.7E0, -.9E0, .5E0, .7E0, -1.6E0, .2E0, 2.4E0,
+ O -2.6E0, -.9E0, -1.3E0, .7E0, 2.9E0, .2E0, -4.0E0 /
+*
* .. Executable Statements ..
*
DO 120 KI = 1, 4
@@ -421,6 +640,39 @@
80 CONTINUE
CALL STEST(LENX,SX,STX,SSIZE2(1,1),1.0E0)
CALL STEST(LENY,SY,STY,SSIZE2(1,1),1.0E0)
+ ELSEIF (ICASE.EQ.12) THEN
+* .. SROTM ..
+ KNI=KN+4*(KI-1)
+ DO KPAR=1,4
+ DO I=1,7
+ SX(I) = DX1(I)
+ SY(I) = DY1(I)
+ STX(I)= DT19X(I,KPAR,KNI)
+ STY(I)= DT19Y(I,KPAR,KNI)
+ END DO
+*
+ DO I=1,5
+ DTEMP(I) = DPAR(I,KPAR)
+ END DO
+*
+ DO I=1,LENX
+ SSIZE(I)=STX(I)
+ END DO
+* SEE REMARK ABOVE ABOUT DT11X(1,2,7)
+* AND DT11X(5,3,8).
+ IF ((KPAR .EQ. 2) .AND. (KNI .EQ. 7))
+ $ SSIZE(1) = 2.4E0
+ IF ((KPAR .EQ. 3) .AND. (KNI .EQ. 8))
+ $ SSIZE(5) = 1.8E0
+*
+ CALL SROTM(N,SX,INCX,SY,INCY,DTEMP)
+ CALL STEST(LENX,SX,STX,SSIZE,SFAC)
+ CALL STEST(LENY,SY,STY,STY,SFAC)
+ END DO
+ ELSEIF (ICASE.EQ.13) THEN
+* .. SDSROT ..
+ CALL STEST1 (SDSDOT(N,.1,SX,INCX,SY,INCY),
+ $ ST7B(KN,KI),SSIZE3(KN),SFAC)
ELSE
WRITE (NOUT,*) ' Shouldn''t be here in CHECK2'
STOP
@@ -436,10 +688,10 @@
* .. Scalar Arguments ..
REAL SFAC
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
- REAL SA, SC, SS
+ REAL SC, SS
INTEGER I, K, KI, KN, KSIZE, LENX, LENY, MX, MY
* .. Local Arrays ..
REAL COPYX(5), COPYY(5), DT9X(7,4,4), DT9Y(7,4,4),
@@ -454,9 +706,8 @@
* .. Intrinsic Functions ..
INTRINSIC ABS, MIN
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Data statements ..
- DATA SA/0.3E0/
DATA INCXS/1, 2, -2, -1/
DATA INCYS/1, -2, 1, -2/
DATA LENS/1, 1, 2, 4, 1, 1, 3, 7/
@@ -647,14 +898,15 @@
*
* .. Parameters ..
INTEGER NOUT
- PARAMETER (NOUT=6)
+ REAL ZERO
+ PARAMETER (NOUT=6, ZERO=0.0E0)
* .. Scalar Arguments ..
REAL SFAC
INTEGER LEN
* .. Array Arguments ..
REAL SCOMP(LEN), SSIZE(LEN), STRUE(LEN)
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
REAL SD
@@ -665,12 +917,12 @@
* .. Intrinsic Functions ..
INTRINSIC ABS
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Executable Statements ..
*
DO 40 I = 1, LEN
SD = SCOMP(I) - STRUE(I)
- IF (SDIFF(ABS(SSIZE(I))+ABS(SFAC*SD),ABS(SSIZE(I))).EQ.0.0E0)
+ IF (ABS(SFAC*SD) .LE. ABS(SSIZE(I))*EPSILON(ZERO))
+ GO TO 40
*
* HERE SCOMP(I) IS NOT CLOSE TO STRUE(I).
@@ -680,16 +932,16 @@
PASS = .FALSE.
WRITE (NOUT,99999)
WRITE (NOUT,99998)
- 20 WRITE (NOUT,99997) ICASE, N, INCX, INCY, MODE, I, SCOMP(I),
+ 20 WRITE (NOUT,99997) ICASE, N, INCX, INCY, I, SCOMP(I),
+ STRUE(I), SD, SSIZE(I)
40 CONTINUE
RETURN
*
99999 FORMAT (' FAIL')
-99998 FORMAT (/' CASE N INCX INCY MODE I ',
+99998 FORMAT (/' CASE N INCX INCY I ',
+ ' COMP(I) TRUE(I) DIFFERENCE',
+ ' SIZE(I)',/1X)
-99997 FORMAT (1X,I4,I3,3I5,I3,2E36.8,2E12.4)
+99997 FORMAT (1X,I4,I3,2I5,I3,2E36.8,2E12.4)
END
SUBROUTINE STEST1(SCOMP1,STRUE1,SSIZE,SFAC)
* ************************* STEST1 *****************************
@@ -739,12 +991,12 @@
* .. Scalar Arguments ..
INTEGER ICOMP, ITRUE
* .. Scalars in Common ..
- INTEGER ICASE, INCX, INCY, MODE, N
+ INTEGER ICASE, INCX, INCY, N
LOGICAL PASS
* .. Local Scalars ..
INTEGER ID
* .. Common blocks ..
- COMMON /COMBLA/ICASE, N, INCX, INCY, MODE, PASS
+ COMMON /COMBLA/ICASE, N, INCX, INCY, PASS
* .. Executable Statements ..
*
IF (ICOMP.EQ.ITRUE) GO TO 40
@@ -757,13 +1009,13 @@
WRITE (NOUT,99999)
WRITE (NOUT,99998)
20 ID = ICOMP - ITRUE
- WRITE (NOUT,99997) ICASE, N, INCX, INCY, MODE, ICOMP, ITRUE, ID
+ WRITE (NOUT,99997) ICASE, N, INCX, INCY, ICOMP, ITRUE, ID
40 CONTINUE
RETURN
*
99999 FORMAT (' FAIL')
-99998 FORMAT (/' CASE N INCX INCY MODE ',
+99998 FORMAT (/' CASE N INCX INCY ',
+ ' COMP TRUE DIFFERENCE',
+ /1X)
-99997 FORMAT (1X,I4,I3,3I5,2I36,I12)
+99997 FORMAT (1X,I4,I3,2I5,2I36,I12)
END
diff --git a/resources/3rdparty/eigen/blas/zhpr.f b/resources/3rdparty/eigen/blas/zhpr.f
deleted file mode 100644
index 40efbc7d5..000000000
--- a/resources/3rdparty/eigen/blas/zhpr.f
+++ /dev/null
@@ -1,220 +0,0 @@
- SUBROUTINE ZHPR(UPLO,N,ALPHA,X,INCX,AP)
-* .. Scalar Arguments ..
- DOUBLE PRECISION ALPHA
- INTEGER INCX,N
- CHARACTER UPLO
-* ..
-* .. Array Arguments ..
- DOUBLE COMPLEX AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* ZHPR performs the hermitian rank 1 operation
-*
-* A := alpha*x*conjg( x' ) + A,
-*
-* where alpha is a real scalar, x is an n element vector and A is an
-* n by n hermitian matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the upper or lower
-* triangular part of the matrix A is supplied in the packed
-* array AP as follows:
-*
-* UPLO = 'U' or 'u' The upper triangular part of A is
-* supplied in AP.
-*
-* UPLO = 'L' or 'l' The lower triangular part of A is
-* supplied in AP.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* ALPHA - DOUBLE PRECISION.
-* On entry, ALPHA specifies the scalar alpha.
-* Unchanged on exit.
-*
-* X - COMPLEX*16 array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x.
-* Unchanged on exit.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* AP - COMPLEX*16 array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular part of the hermitian matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-* and a( 2, 2 ) respectively, and so on. On exit, the array
-* AP is overwritten by the upper triangular part of the
-* updated matrix.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular part of the hermitian matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-* and a( 3, 1 ) respectively, and so on. On exit, the array
-* AP is overwritten by the lower triangular part of the
-* updated matrix.
-* Note that the imaginary parts of the diagonal elements need
-* not be set, they are assumed to be zero, and on exit they
-* are set to zero.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- DOUBLE COMPLEX ZERO
- PARAMETER (ZERO= (0.0D+0,0.0D+0))
-* ..
-* .. Local Scalars ..
- DOUBLE COMPLEX TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-* .. Intrinsic Functions ..
- INTRINSIC DBLE,DCONJG
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (N.LT.0) THEN
- INFO = 2
- ELSE IF (INCX.EQ.0) THEN
- INFO = 5
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('ZHPR ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF ((N.EQ.0) .OR. (ALPHA.EQ.DBLE(ZERO))) RETURN
-*
-* Set the start point in X if the increment is not unity.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of the array AP
-* are accessed sequentially with one pass through AP.
-*
- KK = 1
- IF (LSAME(UPLO,'U')) THEN
-*
-* Form A when upper triangle is stored in AP.
-*
- IF (INCX.EQ.1) THEN
- DO 20 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = ALPHA*DCONJG(X(J))
- K = KK
- DO 10 I = 1,J - 1
- AP(K) = AP(K) + X(I)*TEMP
- K = K + 1
- 10 CONTINUE
- AP(KK+J-1) = DBLE(AP(KK+J-1)) + DBLE(X(J)*TEMP)
- ELSE
- AP(KK+J-1) = DBLE(AP(KK+J-1))
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- JX = KX
- DO 40 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = ALPHA*DCONJG(X(JX))
- IX = KX
- DO 30 K = KK,KK + J - 2
- AP(K) = AP(K) + X(IX)*TEMP
- IX = IX + INCX
- 30 CONTINUE
- AP(KK+J-1) = DBLE(AP(KK+J-1)) + DBLE(X(JX)*TEMP)
- ELSE
- AP(KK+J-1) = DBLE(AP(KK+J-1))
- END IF
- JX = JX + INCX
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
-*
-* Form A when lower triangle is stored in AP.
-*
- IF (INCX.EQ.1) THEN
- DO 60 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = ALPHA*DCONJG(X(J))
- AP(KK) = DBLE(AP(KK)) + DBLE(TEMP*X(J))
- K = KK + 1
- DO 50 I = J + 1,N
- AP(K) = AP(K) + X(I)*TEMP
- K = K + 1
- 50 CONTINUE
- ELSE
- AP(KK) = DBLE(AP(KK))
- END IF
- KK = KK + N - J + 1
- 60 CONTINUE
- ELSE
- JX = KX
- DO 80 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = ALPHA*DCONJG(X(JX))
- AP(KK) = DBLE(AP(KK)) + DBLE(TEMP*X(JX))
- IX = JX
- DO 70 K = KK + 1,KK + N - J
- IX = IX + INCX
- AP(K) = AP(K) + X(IX)*TEMP
- 70 CONTINUE
- ELSE
- AP(KK) = DBLE(AP(KK))
- END IF
- JX = JX + INCX
- KK = KK + N - J + 1
- 80 CONTINUE
- END IF
- END IF
-*
- RETURN
-*
-* End of ZHPR .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/zhpr2.f b/resources/3rdparty/eigen/blas/zhpr2.f
deleted file mode 100644
index 99977462e..000000000
--- a/resources/3rdparty/eigen/blas/zhpr2.f
+++ /dev/null
@@ -1,255 +0,0 @@
- SUBROUTINE ZHPR2(UPLO,N,ALPHA,X,INCX,Y,INCY,AP)
-* .. Scalar Arguments ..
- DOUBLE COMPLEX ALPHA
- INTEGER INCX,INCY,N
- CHARACTER UPLO
-* ..
-* .. Array Arguments ..
- DOUBLE COMPLEX AP(*),X(*),Y(*)
-* ..
-*
-* Purpose
-* =======
-*
-* ZHPR2 performs the hermitian rank 2 operation
-*
-* A := alpha*x*conjg( y' ) + conjg( alpha )*y*conjg( x' ) + A,
-*
-* where alpha is a scalar, x and y are n element vectors and A is an
-* n by n hermitian matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the upper or lower
-* triangular part of the matrix A is supplied in the packed
-* array AP as follows:
-*
-* UPLO = 'U' or 'u' The upper triangular part of A is
-* supplied in AP.
-*
-* UPLO = 'L' or 'l' The lower triangular part of A is
-* supplied in AP.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* ALPHA - COMPLEX*16 .
-* On entry, ALPHA specifies the scalar alpha.
-* Unchanged on exit.
-*
-* X - COMPLEX*16 array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x.
-* Unchanged on exit.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Y - COMPLEX*16 array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCY ) ).
-* Before entry, the incremented array Y must contain the n
-* element vector y.
-* Unchanged on exit.
-*
-* INCY - INTEGER.
-* On entry, INCY specifies the increment for the elements of
-* Y. INCY must not be zero.
-* Unchanged on exit.
-*
-* AP - COMPLEX*16 array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular part of the hermitian matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 1, 2 )
-* and a( 2, 2 ) respectively, and so on. On exit, the array
-* AP is overwritten by the upper triangular part of the
-* updated matrix.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular part of the hermitian matrix
-* packed sequentially, column by column, so that AP( 1 )
-* contains a( 1, 1 ), AP( 2 ) and AP( 3 ) contain a( 2, 1 )
-* and a( 3, 1 ) respectively, and so on. On exit, the array
-* AP is overwritten by the lower triangular part of the
-* updated matrix.
-* Note that the imaginary parts of the diagonal elements need
-* not be set, they are assumed to be zero, and on exit they
-* are set to zero.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- DOUBLE COMPLEX ZERO
- PARAMETER (ZERO= (0.0D+0,0.0D+0))
-* ..
-* .. Local Scalars ..
- DOUBLE COMPLEX TEMP1,TEMP2
- INTEGER I,INFO,IX,IY,J,JX,JY,K,KK,KX,KY
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-* .. Intrinsic Functions ..
- INTRINSIC DBLE,DCONJG
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (N.LT.0) THEN
- INFO = 2
- ELSE IF (INCX.EQ.0) THEN
- INFO = 5
- ELSE IF (INCY.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('ZHPR2 ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF ((N.EQ.0) .OR. (ALPHA.EQ.ZERO)) RETURN
-*
-* Set up the start points in X and Y if the increments are not both
-* unity.
-*
- IF ((INCX.NE.1) .OR. (INCY.NE.1)) THEN
- IF (INCX.GT.0) THEN
- KX = 1
- ELSE
- KX = 1 - (N-1)*INCX
- END IF
- IF (INCY.GT.0) THEN
- KY = 1
- ELSE
- KY = 1 - (N-1)*INCY
- END IF
- JX = KX
- JY = KY
- END IF
-*
-* Start the operations. In this version the elements of the array AP
-* are accessed sequentially with one pass through AP.
-*
- KK = 1
- IF (LSAME(UPLO,'U')) THEN
-*
-* Form A when upper triangle is stored in AP.
-*
- IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
- DO 20 J = 1,N
- IF ((X(J).NE.ZERO) .OR. (Y(J).NE.ZERO)) THEN
- TEMP1 = ALPHA*DCONJG(Y(J))
- TEMP2 = DCONJG(ALPHA*X(J))
- K = KK
- DO 10 I = 1,J - 1
- AP(K) = AP(K) + X(I)*TEMP1 + Y(I)*TEMP2
- K = K + 1
- 10 CONTINUE
- AP(KK+J-1) = DBLE(AP(KK+J-1)) +
- + DBLE(X(J)*TEMP1+Y(J)*TEMP2)
- ELSE
- AP(KK+J-1) = DBLE(AP(KK+J-1))
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- DO 40 J = 1,N
- IF ((X(JX).NE.ZERO) .OR. (Y(JY).NE.ZERO)) THEN
- TEMP1 = ALPHA*DCONJG(Y(JY))
- TEMP2 = DCONJG(ALPHA*X(JX))
- IX = KX
- IY = KY
- DO 30 K = KK,KK + J - 2
- AP(K) = AP(K) + X(IX)*TEMP1 + Y(IY)*TEMP2
- IX = IX + INCX
- IY = IY + INCY
- 30 CONTINUE
- AP(KK+J-1) = DBLE(AP(KK+J-1)) +
- + DBLE(X(JX)*TEMP1+Y(JY)*TEMP2)
- ELSE
- AP(KK+J-1) = DBLE(AP(KK+J-1))
- END IF
- JX = JX + INCX
- JY = JY + INCY
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
-*
-* Form A when lower triangle is stored in AP.
-*
- IF ((INCX.EQ.1) .AND. (INCY.EQ.1)) THEN
- DO 60 J = 1,N
- IF ((X(J).NE.ZERO) .OR. (Y(J).NE.ZERO)) THEN
- TEMP1 = ALPHA*DCONJG(Y(J))
- TEMP2 = DCONJG(ALPHA*X(J))
- AP(KK) = DBLE(AP(KK)) +
- + DBLE(X(J)*TEMP1+Y(J)*TEMP2)
- K = KK + 1
- DO 50 I = J + 1,N
- AP(K) = AP(K) + X(I)*TEMP1 + Y(I)*TEMP2
- K = K + 1
- 50 CONTINUE
- ELSE
- AP(KK) = DBLE(AP(KK))
- END IF
- KK = KK + N - J + 1
- 60 CONTINUE
- ELSE
- DO 80 J = 1,N
- IF ((X(JX).NE.ZERO) .OR. (Y(JY).NE.ZERO)) THEN
- TEMP1 = ALPHA*DCONJG(Y(JY))
- TEMP2 = DCONJG(ALPHA*X(JX))
- AP(KK) = DBLE(AP(KK)) +
- + DBLE(X(JX)*TEMP1+Y(JY)*TEMP2)
- IX = JX
- IY = JY
- DO 70 K = KK + 1,KK + N - J
- IX = IX + INCX
- IY = IY + INCY
- AP(K) = AP(K) + X(IX)*TEMP1 + Y(IY)*TEMP2
- 70 CONTINUE
- ELSE
- AP(KK) = DBLE(AP(KK))
- END IF
- JX = JX + INCX
- JY = JY + INCY
- KK = KK + N - J + 1
- 80 CONTINUE
- END IF
- END IF
-*
- RETURN
-*
-* End of ZHPR2 .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/ztpmv.f b/resources/3rdparty/eigen/blas/ztpmv.f
deleted file mode 100644
index 5a7b3b8b7..000000000
--- a/resources/3rdparty/eigen/blas/ztpmv.f
+++ /dev/null
@@ -1,329 +0,0 @@
- SUBROUTINE ZTPMV(UPLO,TRANS,DIAG,N,AP,X,INCX)
-* .. Scalar Arguments ..
- INTEGER INCX,N
- CHARACTER DIAG,TRANS,UPLO
-* ..
-* .. Array Arguments ..
- DOUBLE COMPLEX AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* ZTPMV performs one of the matrix-vector operations
-*
-* x := A*x, or x := A'*x, or x := conjg( A' )*x,
-*
-* where x is an n element vector and A is an n by n unit, or non-unit,
-* upper or lower triangular matrix, supplied in packed form.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the matrix is an upper or
-* lower triangular matrix as follows:
-*
-* UPLO = 'U' or 'u' A is an upper triangular matrix.
-*
-* UPLO = 'L' or 'l' A is a lower triangular matrix.
-*
-* Unchanged on exit.
-*
-* TRANS - CHARACTER*1.
-* On entry, TRANS specifies the operation to be performed as
-* follows:
-*
-* TRANS = 'N' or 'n' x := A*x.
-*
-* TRANS = 'T' or 't' x := A'*x.
-*
-* TRANS = 'C' or 'c' x := conjg( A' )*x.
-*
-* Unchanged on exit.
-*
-* DIAG - CHARACTER*1.
-* On entry, DIAG specifies whether or not A is unit
-* triangular as follows:
-*
-* DIAG = 'U' or 'u' A is assumed to be unit triangular.
-*
-* DIAG = 'N' or 'n' A is not assumed to be unit
-* triangular.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* AP - COMPLEX*16 array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 1, 2 ) and a( 2, 2 )
-* respectively, and so on.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 2, 1 ) and a( 3, 1 )
-* respectively, and so on.
-* Note that when DIAG = 'U' or 'u', the diagonal elements of
-* A are not referenced, but are assumed to be unity.
-* Unchanged on exit.
-*
-* X - COMPLEX*16 array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element vector x. On exit, X is overwritten with the
-* tranformed vector x.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- DOUBLE COMPLEX ZERO
- PARAMETER (ZERO= (0.0D+0,0.0D+0))
-* ..
-* .. Local Scalars ..
- DOUBLE COMPLEX TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
- LOGICAL NOCONJ,NOUNIT
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-* .. Intrinsic Functions ..
- INTRINSIC DCONJG
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
- + .NOT.LSAME(TRANS,'C')) THEN
- INFO = 2
- ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
- INFO = 3
- ELSE IF (N.LT.0) THEN
- INFO = 4
- ELSE IF (INCX.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('ZTPMV ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF (N.EQ.0) RETURN
-*
- NOCONJ = LSAME(TRANS,'T')
- NOUNIT = LSAME(DIAG,'N')
-*
-* Set up the start point in X if the increment is not unity. This
-* will be ( N - 1 )*INCX too small for descending loops.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of AP are
-* accessed sequentially with one pass through AP.
-*
- IF (LSAME(TRANS,'N')) THEN
-*
-* Form x:= A*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 20 J = 1,N
- IF (X(J).NE.ZERO) THEN
- TEMP = X(J)
- K = KK
- DO 10 I = 1,J - 1
- X(I) = X(I) + TEMP*AP(K)
- K = K + 1
- 10 CONTINUE
- IF (NOUNIT) X(J) = X(J)*AP(KK+J-1)
- END IF
- KK = KK + J
- 20 CONTINUE
- ELSE
- JX = KX
- DO 40 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- TEMP = X(JX)
- IX = KX
- DO 30 K = KK,KK + J - 2
- X(IX) = X(IX) + TEMP*AP(K)
- IX = IX + INCX
- 30 CONTINUE
- IF (NOUNIT) X(JX) = X(JX)*AP(KK+J-1)
- END IF
- JX = JX + INCX
- KK = KK + J
- 40 CONTINUE
- END IF
- ELSE
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 60 J = N,1,-1
- IF (X(J).NE.ZERO) THEN
- TEMP = X(J)
- K = KK
- DO 50 I = N,J + 1,-1
- X(I) = X(I) + TEMP*AP(K)
- K = K - 1
- 50 CONTINUE
- IF (NOUNIT) X(J) = X(J)*AP(KK-N+J)
- END IF
- KK = KK - (N-J+1)
- 60 CONTINUE
- ELSE
- KX = KX + (N-1)*INCX
- JX = KX
- DO 80 J = N,1,-1
- IF (X(JX).NE.ZERO) THEN
- TEMP = X(JX)
- IX = KX
- DO 70 K = KK,KK - (N- (J+1)),-1
- X(IX) = X(IX) + TEMP*AP(K)
- IX = IX - INCX
- 70 CONTINUE
- IF (NOUNIT) X(JX) = X(JX)*AP(KK-N+J)
- END IF
- JX = JX - INCX
- KK = KK - (N-J+1)
- 80 CONTINUE
- END IF
- END IF
- ELSE
-*
-* Form x := A'*x or x := conjg( A' )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 110 J = N,1,-1
- TEMP = X(J)
- K = KK - 1
- IF (NOCONJ) THEN
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 90 I = J - 1,1,-1
- TEMP = TEMP + AP(K)*X(I)
- K = K - 1
- 90 CONTINUE
- ELSE
- IF (NOUNIT) TEMP = TEMP*DCONJG(AP(KK))
- DO 100 I = J - 1,1,-1
- TEMP = TEMP + DCONJG(AP(K))*X(I)
- K = K - 1
- 100 CONTINUE
- END IF
- X(J) = TEMP
- KK = KK - J
- 110 CONTINUE
- ELSE
- JX = KX + (N-1)*INCX
- DO 140 J = N,1,-1
- TEMP = X(JX)
- IX = JX
- IF (NOCONJ) THEN
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 120 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- TEMP = TEMP + AP(K)*X(IX)
- 120 CONTINUE
- ELSE
- IF (NOUNIT) TEMP = TEMP*DCONJG(AP(KK))
- DO 130 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- TEMP = TEMP + DCONJG(AP(K))*X(IX)
- 130 CONTINUE
- END IF
- X(JX) = TEMP
- JX = JX - INCX
- KK = KK - J
- 140 CONTINUE
- END IF
- ELSE
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 170 J = 1,N
- TEMP = X(J)
- K = KK + 1
- IF (NOCONJ) THEN
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 150 I = J + 1,N
- TEMP = TEMP + AP(K)*X(I)
- K = K + 1
- 150 CONTINUE
- ELSE
- IF (NOUNIT) TEMP = TEMP*DCONJG(AP(KK))
- DO 160 I = J + 1,N
- TEMP = TEMP + DCONJG(AP(K))*X(I)
- K = K + 1
- 160 CONTINUE
- END IF
- X(J) = TEMP
- KK = KK + (N-J+1)
- 170 CONTINUE
- ELSE
- JX = KX
- DO 200 J = 1,N
- TEMP = X(JX)
- IX = JX
- IF (NOCONJ) THEN
- IF (NOUNIT) TEMP = TEMP*AP(KK)
- DO 180 K = KK + 1,KK + N - J
- IX = IX + INCX
- TEMP = TEMP + AP(K)*X(IX)
- 180 CONTINUE
- ELSE
- IF (NOUNIT) TEMP = TEMP*DCONJG(AP(KK))
- DO 190 K = KK + 1,KK + N - J
- IX = IX + INCX
- TEMP = TEMP + DCONJG(AP(K))*X(IX)
- 190 CONTINUE
- END IF
- X(JX) = TEMP
- JX = JX + INCX
- KK = KK + (N-J+1)
- 200 CONTINUE
- END IF
- END IF
- END IF
-*
- RETURN
-*
-* End of ZTPMV .
-*
- END
diff --git a/resources/3rdparty/eigen/blas/ztpsv.f b/resources/3rdparty/eigen/blas/ztpsv.f
deleted file mode 100644
index b56e1d8c4..000000000
--- a/resources/3rdparty/eigen/blas/ztpsv.f
+++ /dev/null
@@ -1,332 +0,0 @@
- SUBROUTINE ZTPSV(UPLO,TRANS,DIAG,N,AP,X,INCX)
-* .. Scalar Arguments ..
- INTEGER INCX,N
- CHARACTER DIAG,TRANS,UPLO
-* ..
-* .. Array Arguments ..
- DOUBLE COMPLEX AP(*),X(*)
-* ..
-*
-* Purpose
-* =======
-*
-* ZTPSV solves one of the systems of equations
-*
-* A*x = b, or A'*x = b, or conjg( A' )*x = b,
-*
-* where b and x are n element vectors and A is an n by n unit, or
-* non-unit, upper or lower triangular matrix, supplied in packed form.
-*
-* No test for singularity or near-singularity is included in this
-* routine. Such tests must be performed before calling this routine.
-*
-* Arguments
-* ==========
-*
-* UPLO - CHARACTER*1.
-* On entry, UPLO specifies whether the matrix is an upper or
-* lower triangular matrix as follows:
-*
-* UPLO = 'U' or 'u' A is an upper triangular matrix.
-*
-* UPLO = 'L' or 'l' A is a lower triangular matrix.
-*
-* Unchanged on exit.
-*
-* TRANS - CHARACTER*1.
-* On entry, TRANS specifies the equations to be solved as
-* follows:
-*
-* TRANS = 'N' or 'n' A*x = b.
-*
-* TRANS = 'T' or 't' A'*x = b.
-*
-* TRANS = 'C' or 'c' conjg( A' )*x = b.
-*
-* Unchanged on exit.
-*
-* DIAG - CHARACTER*1.
-* On entry, DIAG specifies whether or not A is unit
-* triangular as follows:
-*
-* DIAG = 'U' or 'u' A is assumed to be unit triangular.
-*
-* DIAG = 'N' or 'n' A is not assumed to be unit
-* triangular.
-*
-* Unchanged on exit.
-*
-* N - INTEGER.
-* On entry, N specifies the order of the matrix A.
-* N must be at least zero.
-* Unchanged on exit.
-*
-* AP - COMPLEX*16 array of DIMENSION at least
-* ( ( n*( n + 1 ) )/2 ).
-* Before entry with UPLO = 'U' or 'u', the array AP must
-* contain the upper triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 1, 2 ) and a( 2, 2 )
-* respectively, and so on.
-* Before entry with UPLO = 'L' or 'l', the array AP must
-* contain the lower triangular matrix packed sequentially,
-* column by column, so that AP( 1 ) contains a( 1, 1 ),
-* AP( 2 ) and AP( 3 ) contain a( 2, 1 ) and a( 3, 1 )
-* respectively, and so on.
-* Note that when DIAG = 'U' or 'u', the diagonal elements of
-* A are not referenced, but are assumed to be unity.
-* Unchanged on exit.
-*
-* X - COMPLEX*16 array of dimension at least
-* ( 1 + ( n - 1 )*abs( INCX ) ).
-* Before entry, the incremented array X must contain the n
-* element right-hand side vector b. On exit, X is overwritten
-* with the solution vector x.
-*
-* INCX - INTEGER.
-* On entry, INCX specifies the increment for the elements of
-* X. INCX must not be zero.
-* Unchanged on exit.
-*
-* Further Details
-* ===============
-*
-* Level 2 Blas routine.
-*
-* -- Written on 22-October-1986.
-* Jack Dongarra, Argonne National Lab.
-* Jeremy Du Croz, Nag Central Office.
-* Sven Hammarling, Nag Central Office.
-* Richard Hanson, Sandia National Labs.
-*
-* =====================================================================
-*
-* .. Parameters ..
- DOUBLE COMPLEX ZERO
- PARAMETER (ZERO= (0.0D+0,0.0D+0))
-* ..
-* .. Local Scalars ..
- DOUBLE COMPLEX TEMP
- INTEGER I,INFO,IX,J,JX,K,KK,KX
- LOGICAL NOCONJ,NOUNIT
-* ..
-* .. External Functions ..
- LOGICAL LSAME
- EXTERNAL LSAME
-* ..
-* .. External Subroutines ..
- EXTERNAL XERBLA
-* ..
-* .. Intrinsic Functions ..
- INTRINSIC DCONJG
-* ..
-*
-* Test the input parameters.
-*
- INFO = 0
- IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN
- INFO = 1
- ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND.
- + .NOT.LSAME(TRANS,'C')) THEN
- INFO = 2
- ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN
- INFO = 3
- ELSE IF (N.LT.0) THEN
- INFO = 4
- ELSE IF (INCX.EQ.0) THEN
- INFO = 7
- END IF
- IF (INFO.NE.0) THEN
- CALL XERBLA('ZTPSV ',INFO)
- RETURN
- END IF
-*
-* Quick return if possible.
-*
- IF (N.EQ.0) RETURN
-*
- NOCONJ = LSAME(TRANS,'T')
- NOUNIT = LSAME(DIAG,'N')
-*
-* Set up the start point in X if the increment is not unity. This
-* will be ( N - 1 )*INCX too small for descending loops.
-*
- IF (INCX.LE.0) THEN
- KX = 1 - (N-1)*INCX
- ELSE IF (INCX.NE.1) THEN
- KX = 1
- END IF
-*
-* Start the operations. In this version the elements of AP are
-* accessed sequentially with one pass through AP.
-*
- IF (LSAME(TRANS,'N')) THEN
-*
-* Form x := inv( A )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 20 J = N,1,-1
- IF (X(J).NE.ZERO) THEN
- IF (NOUNIT) X(J) = X(J)/AP(KK)
- TEMP = X(J)
- K = KK - 1
- DO 10 I = J - 1,1,-1
- X(I) = X(I) - TEMP*AP(K)
- K = K - 1
- 10 CONTINUE
- END IF
- KK = KK - J
- 20 CONTINUE
- ELSE
- JX = KX + (N-1)*INCX
- DO 40 J = N,1,-1
- IF (X(JX).NE.ZERO) THEN
- IF (NOUNIT) X(JX) = X(JX)/AP(KK)
- TEMP = X(JX)
- IX = JX
- DO 30 K = KK - 1,KK - J + 1,-1
- IX = IX - INCX
- X(IX) = X(IX) - TEMP*AP(K)
- 30 CONTINUE
- END IF
- JX = JX - INCX
- KK = KK - J
- 40 CONTINUE
- END IF
- ELSE
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 60 J = 1,N
- IF (X(J).NE.ZERO) THEN
- IF (NOUNIT) X(J) = X(J)/AP(KK)
- TEMP = X(J)
- K = KK + 1
- DO 50 I = J + 1,N
- X(I) = X(I) - TEMP*AP(K)
- K = K + 1
- 50 CONTINUE
- END IF
- KK = KK + (N-J+1)
- 60 CONTINUE
- ELSE
- JX = KX
- DO 80 J = 1,N
- IF (X(JX).NE.ZERO) THEN
- IF (NOUNIT) X(JX) = X(JX)/AP(KK)
- TEMP = X(JX)
- IX = JX
- DO 70 K = KK + 1,KK + N - J
- IX = IX + INCX
- X(IX) = X(IX) - TEMP*AP(K)
- 70 CONTINUE
- END IF
- JX = JX + INCX
- KK = KK + (N-J+1)
- 80 CONTINUE
- END IF
- END IF
- ELSE
-*
-* Form x := inv( A' )*x or x := inv( conjg( A' ) )*x.
-*
- IF (LSAME(UPLO,'U')) THEN
- KK = 1
- IF (INCX.EQ.1) THEN
- DO 110 J = 1,N
- TEMP = X(J)
- K = KK
- IF (NOCONJ) THEN
- DO 90 I = 1,J - 1
- TEMP = TEMP - AP(K)*X(I)
- K = K + 1
- 90 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK+J-1)
- ELSE
- DO 100 I = 1,J - 1
- TEMP = TEMP - DCONJG(AP(K))*X(I)
- K = K + 1
- 100 CONTINUE
- IF (NOUNIT) TEMP = TEMP/DCONJG(AP(KK+J-1))
- END IF
- X(J) = TEMP
- KK = KK + J
- 110 CONTINUE
- ELSE
- JX = KX
- DO 140 J = 1,N
- TEMP = X(JX)
- IX = KX
- IF (NOCONJ) THEN
- DO 120 K = KK,KK + J - 2
- TEMP = TEMP - AP(K)*X(IX)
- IX = IX + INCX
- 120 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK+J-1)
- ELSE
- DO 130 K = KK,KK + J - 2
- TEMP = TEMP - DCONJG(AP(K))*X(IX)
- IX = IX + INCX
- 130 CONTINUE
- IF (NOUNIT) TEMP = TEMP/DCONJG(AP(KK+J-1))
- END IF
- X(JX) = TEMP
- JX = JX + INCX
- KK = KK + J
- 140 CONTINUE
- END IF
- ELSE
- KK = (N* (N+1))/2
- IF (INCX.EQ.1) THEN
- DO 170 J = N,1,-1
- TEMP = X(J)
- K = KK
- IF (NOCONJ) THEN
- DO 150 I = N,J + 1,-1
- TEMP = TEMP - AP(K)*X(I)
- K = K - 1
- 150 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK-N+J)
- ELSE
- DO 160 I = N,J + 1,-1
- TEMP = TEMP - DCONJG(AP(K))*X(I)
- K = K - 1
- 160 CONTINUE
- IF (NOUNIT) TEMP = TEMP/DCONJG(AP(KK-N+J))
- END IF
- X(J) = TEMP
- KK = KK - (N-J+1)
- 170 CONTINUE
- ELSE
- KX = KX + (N-1)*INCX
- JX = KX
- DO 200 J = N,1,-1
- TEMP = X(JX)
- IX = KX
- IF (NOCONJ) THEN
- DO 180 K = KK,KK - (N- (J+1)),-1
- TEMP = TEMP - AP(K)*X(IX)
- IX = IX - INCX
- 180 CONTINUE
- IF (NOUNIT) TEMP = TEMP/AP(KK-N+J)
- ELSE
- DO 190 K = KK,KK - (N- (J+1)),-1
- TEMP = TEMP - DCONJG(AP(K))*X(IX)
- IX = IX - INCX
- 190 CONTINUE
- IF (NOUNIT) TEMP = TEMP/DCONJG(AP(KK-N+J))
- END IF
- X(JX) = TEMP
- JX = JX - INCX
- KK = KK - (N-J+1)
- 200 CONTINUE
- END IF
- END IF
- END IF
-*
- RETURN
-*
-* End of ZTPSV .
-*
- END
diff --git a/resources/3rdparty/eigen/cmake/FindMetis.cmake b/resources/3rdparty/eigen/cmake/FindMetis.cmake
index e4d6ef258..627c3e9ae 100644
--- a/resources/3rdparty/eigen/cmake/FindMetis.cmake
+++ b/resources/3rdparty/eigen/cmake/FindMetis.cmake
@@ -12,10 +12,11 @@ find_path(METIS_INCLUDES
${INCLUDE_INSTALL_DIR}
PATH_SUFFIXES
metis
+ include
)
-find_library(METIS_LIBRARIES metis PATHS $ENV{METISDIR} ${LIB_INSTALL_DIR})
+find_library(METIS_LIBRARIES metis PATHS $ENV{METISDIR} ${LIB_INSTALL_DIR} PATH_SUFFIXES lib)
include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(METIS DEFAULT_MSG
diff --git a/resources/3rdparty/eigen/cmake/FindUmfpack.cmake b/resources/3rdparty/eigen/cmake/FindUmfpack.cmake
index d42c3c4a2..3df3a0a94 100644
--- a/resources/3rdparty/eigen/cmake/FindUmfpack.cmake
+++ b/resources/3rdparty/eigen/cmake/FindUmfpack.cmake
@@ -19,8 +19,9 @@ find_path(UMFPACK_INCLUDES
find_library(UMFPACK_LIBRARIES umfpack PATHS $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
if(UMFPACK_LIBRARIES)
-
- get_filename_component(UMFPACK_LIBDIR ${UMFPACK_LIBRARIES} PATH)
+ if (NOT UMFPACK_LIBDIR)
+ get_filename_component(UMFPACK_LIBDIR ${UMFPACK_LIBRARIES} PATH)
+ endif(NOT UMFPACK_LIBDIR)
find_library(AMD_LIBRARY amd PATHS ${UMFPACK_LIBDIR} $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
if (AMD_LIBRARY)
diff --git a/resources/3rdparty/eigen/debug/gdb/printers.py b/resources/3rdparty/eigen/debug/gdb/printers.py
index 9187acb33..86996a4f9 100644
--- a/resources/3rdparty/eigen/debug/gdb/printers.py
+++ b/resources/3rdparty/eigen/debug/gdb/printers.py
@@ -51,12 +51,12 @@ class EigenMatrixPrinter:
template_params = m.split(',')
template_params = map(lambda x:x.replace(" ", ""), template_params)
- if template_params[1] == '-0x00000000000000001' or template_params[1] == '-0x000000001':
+ if template_params[1] == '-0x00000000000000001' or template_params[1] == '-0x000000001' or template_params[1] == '-1':
self.rows = val['m_storage']['m_rows']
else:
self.rows = int(template_params[1])
- if template_params[2] == '-0x00000000000000001' or template_params[2] == '-0x000000001':
+ if template_params[2] == '-0x00000000000000001' or template_params[2] == '-0x000000001' or template_params[2] == '-1':
self.cols = val['m_storage']['m_cols']
else:
self.cols = int(template_params[2])
diff --git a/resources/3rdparty/eigen/doc/C09_TutorialSparse.dox b/resources/3rdparty/eigen/doc/C09_TutorialSparse.dox
index 34154bd0d..6a16c3ae2 100644
--- a/resources/3rdparty/eigen/doc/C09_TutorialSparse.dox
+++ b/resources/3rdparty/eigen/doc/C09_TutorialSparse.dox
@@ -211,7 +211,7 @@ Here is a typical usage example:
\code
typedef Eigen::Triplet<double> T;
std::vector<T> tripletList;
-triplets.reserve(estimation_of_entries);
+tripletList.reserve(estimation_of_entries);
for(...)
{
// ...
@@ -291,12 +291,12 @@ VectorXd b, x;
// solve Ax = b
SolverClassName<SparseMatrix<double> > solver;
solver.compute(A);
-if(solver.info()!=Succeeded) {
+if(solver.info()!=Success) {
// decomposition failed
return;
}
x = solver.solve(b);
-if(solver.info()!=Succeeded) {
+if(solver.info()!=Success) {
// solving failed
return;
}
diff --git a/resources/3rdparty/eigen/doc/CMakeLists.txt b/resources/3rdparty/eigen/doc/CMakeLists.txt
index 96bff41bf..33bc1d45d 100644
--- a/resources/3rdparty/eigen/doc/CMakeLists.txt
+++ b/resources/3rdparty/eigen/doc/CMakeLists.txt
@@ -34,6 +34,7 @@ set(examples_targets "")
set(snippets_targets "")
add_definitions("-DEIGEN_MAKING_DOCS")
+add_custom_target(all_examples)
add_subdirectory(examples)
add_subdirectory(special_examples)
@@ -71,7 +72,8 @@ add_custom_target(doc ALL
COMMAND doxygen
COMMAND doxygen Doxyfile-unsupported # run doxygen twice to get proper eigen <=> unsupported cross references
COMMAND ${CMAKE_COMMAND} -E rename html eigen-doc
- COMMAND ${CMAKE_COMMAND} -E tar cvfz eigen-doc/eigen-doc.tgz eigen-doc/*.html eigen-doc/*.map eigen-doc/*.png eigen-doc/*.css eigen-doc/*.js eigen-doc/*.txt eigen-doc/unsupported
+ COMMAND ${CMAKE_COMMAND} -E remove eigen-doc/eigen-doc.tgz
+ COMMAND ${CMAKE_COMMAND} -E tar cvfz eigen-doc/eigen-doc.tgz eigen-doc
COMMAND ${CMAKE_COMMAND} -E rename eigen-doc html
WORKING_DIRECTORY ${Eigen_BINARY_DIR}/doc)
diff --git a/resources/3rdparty/eigen/doc/D01_StlContainers.dox b/resources/3rdparty/eigen/doc/D01_StlContainers.dox
index b5dbf0698..f55db3125 100644
--- a/resources/3rdparty/eigen/doc/D01_StlContainers.dox
+++ b/resources/3rdparty/eigen/doc/D01_StlContainers.dox
@@ -38,7 +38,7 @@ The situation with std::vector was even worse (explanation below) so we had to s
Here is an example:
\code
#include<Eigen/StdVector>
-\/* ... *\/
+/* ... */
std::vector<Eigen::Vector4f,Eigen::aligned_allocator<Eigen::Vector4f> >
\endcode
@@ -52,7 +52,7 @@ the compiler will compile that particular instance with the default std::allocat
Here is an example:
\code
#include<Eigen/StdVector>
-\/* ... *\/
+/* ... */
EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Matrix2d)
std::vector<Eigen::Vector2d>
\endcode
diff --git a/resources/3rdparty/eigen/doc/Doxyfile.in b/resources/3rdparty/eigen/doc/Doxyfile.in
index e9e89d486..167e65067 100644
--- a/resources/3rdparty/eigen/doc/Doxyfile.in
+++ b/resources/3rdparty/eigen/doc/Doxyfile.in
@@ -302,7 +302,7 @@ TYPEDEF_HIDES_STRUCT = NO
# Private class members and static file members will be hidden unless
# the EXTRACT_PRIVATE and EXTRACT_STATIC tags are set to YES
-EXTRACT_ALL = YES
+EXTRACT_ALL = NO
# If the EXTRACT_PRIVATE tag is set to YES all private members of a class
# will be included in the documentation.
@@ -797,9 +797,7 @@ HTML_HEADER = "${Eigen_BINARY_DIR}/doc/eigendoxy_header.html"
# each generated HTML page. If it is left blank doxygen will generate a
# standard footer.
-# the footer has not been customized yet, so let's use the default one
-# ${Eigen_BINARY_DIR}/doc/eigendoxy_footer.html
-HTML_FOOTER =
+HTML_FOOTER = "${Eigen_BINARY_DIR}/doc/eigendoxy_footer.html"
# The HTML_STYLESHEET tag can be used to specify a user-defined cascading
# style sheet that is used by each HTML page. It can be used to
diff --git a/resources/3rdparty/eigen/doc/I02_HiPerformance.dox b/resources/3rdparty/eigen/doc/I02_HiPerformance.dox
index ac1c2ca2b..ab6cdfd44 100644
--- a/resources/3rdparty/eigen/doc/I02_HiPerformance.dox
+++ b/resources/3rdparty/eigen/doc/I02_HiPerformance.dox
@@ -79,7 +79,7 @@ temp = m2 * m3;
m1 += temp.adjoint(); \endcode</td>
<td>\code
m1.noalias() += m3.adjoint()
- * m2.adjoint(); \endcode</td>
+* * m2.adjoint(); \endcode</td>
<td>This is because the product expression has the EvalBeforeNesting bit which
enforces the evaluation of the product by the Tranpose expression.</td>
</tr>
diff --git a/resources/3rdparty/eigen/doc/I10_Assertions.dox b/resources/3rdparty/eigen/doc/I10_Assertions.dox
index d5697fcee..e5bcbe536 100644
--- a/resources/3rdparty/eigen/doc/I10_Assertions.dox
+++ b/resources/3rdparty/eigen/doc/I10_Assertions.dox
@@ -2,12 +2,113 @@ namespace Eigen {
/** \page TopicAssertions Assertions
+\b Table \b of \b contents
+ - \ref PlainAssert
+ - \ref RedefineAssert
+ - \ref DisableAssert
+ - \ref StaticAssert
+ - \ref DerivedStaticAssert
+ - \ref DisableStaticAssert
-TODO: write this dox page!
+\section PlainAssert Assertions
-Is linked from the tutorial on matrix arithmetic.
+The macro eigen_assert is defined to be \c eigen_plain_assert by default. We use eigen_plain_assert instead of \c assert to work around a known bug for GCC <= 4.3. Basically, eigen_plain_assert \a is \c assert.
-\sa Section \ref TopicPreprocessorDirectivesAssertions on page \ref TopicPreprocessorDirectives.
+\subsection RedefineAssert Redefining assertions
+
+Both eigen_assert and eigen_plain_assert are defined in Macros.h. Defining eigen_assert indirectly gives you a chance to change its behavior. You can redefine this macro if you want to do something else such as throwing an exception, and fall back to its default behavior with eigen_plain_assert. The code below tells Eigen to throw an std::runtime_error:
+
+\code
+#include <stdexcept>
+#undef eigen_assert
+#define eigen_assert(x) \
+ if (!x) { throw (std::runtime_error("Put your message here")); }
+\endcode
+
+\subsection DisableAssert Disabling assertions
+
+Assertions cost run time and can be turned off. You can suppress eigen_assert by defining \c EIGEN_NO_DEBUG \b before including Eigen headers. \c EIGEN_NO_DEBUG is undefined by default unless \c NDEBUG is defined.
+
+\section StaticAssert Static assertions
+
+Static assertions are not standardized until C++11. However, in the Eigen library, there are many conditions can and should be detectedat compile time. For instance, we use static assertions to prevent the code below from compiling.
+
+\code
+Matrix3d() + Matrix4d(); // adding matrices of different sizes
+Matrix4cd() * Vector3cd(); // invalid product known at compile time
+\endcode
+
+Static assertions are defined in StaticAssert.h. If there is native static_assert, we use it. Otherwise, we have implemented an assertion macro that can show a limited range of messages.
+
+One can easily come up with static assertions without messages, such as:
+
+\code
+#define STATIC_ASSERT(x) \
+ switch(0) { case 0: case x:; }
+\endcode
+
+However, the example above obviously cannot tell why the assertion failed. Therefore, we define a \c struct in namespace Eigen::internal to handle available messages.
+
+\code
+template<bool condition>
+struct static_assertion {};
+
+template<>
+struct static_assertion<true>
+{
+ enum {
+ YOU_TRIED_CALLING_A_VECTOR_METHOD_ON_A_MATRIX,
+ YOU_MIXED_VECTORS_OF_DIFFERENT_SIZES,
+ // see StaticAssert.h for all enums.
+ };
+};
+\endcode
+
+And then, we define EIGEN_STATIC_ASSERT(CONDITION,MSG) to access Eigen::internal::static_assertion<bool(CONDITION)>::MSG. If the condition evaluates into \c false, your compiler displays a lot of messages explaining there is no MSG in static_assert<false>. Nevertheless, this is \a not in what we are interested. As you can see, all members of static_assert<true> are ALL_CAPS_AND_THEY_ARE_SHOUTING.
+
+\warning
+When using this macro, MSG should be a member of static_assertion<true>, or the static assertion \b always fails.
+Currently, it can only be used in function scope.
+
+\subsection DerivedStaticAssert Derived static assertions
+
+There are other macros derived from EIGEN_STATIC_ASSERT to enhance readability. Their names are self-explanatory.
+
+- \b EIGEN_STATIC_ASSERT_FIXED_SIZE(TYPE) - passes if \a TYPE is fixed size.
+- \b EIGEN_STATIC_ASSERT_DYNAMIC_SIZE(TYPE) - passes if \a TYPE is dynamic size.
+- \b EIGEN_STATIC_ASSERT_LVALUE(Derived) - failes if \a Derived is read-only.
+- \b EIGEN_STATIC_ASSERT_ARRAYXPR(Derived) - passes if \a Derived is an array expression.
+- <b>EIGEN_STATIC_ASSERT_SAME_XPR_KIND(Derived1, Derived2)</b> - failes if the two expressions are an array one and a matrix one.
+
+Because Eigen handles both fixed-size and dynamic-size expressions, some conditions cannot be clearly determined at compile time. We classify them into strict assertions and permissive assertions.
+
+\subsubsection StrictAssertions Strict assertions
+
+These assertions fail if the condition <b>may not</b> be met. For example, MatrixXd may not be a vector, so it fails EIGEN_STATIC_ASSERT_VECTOR_ONLY.
+
+- \b EIGEN_STATIC_ASSERT_VECTOR_ONLY(TYPE) - passes if \a TYPE must be a vector type.
+- <b>EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(TYPE, SIZE)</b> - passes if \a TYPE must be a vector of the given size.
+- <b>EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(TYPE, ROWS, COLS)</b> - passes if \a TYPE must be a matrix with given rows and columns.
+
+\subsubsection PermissiveAssertions Permissive assertions
+
+These assertions fail if the condition \b cannot be met. For example, MatrixXd and Matrix4d may have the same size, so they pass EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE.
+
+- \b EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(TYPE0,TYPE1) - fails if the two vector expression types must have different sizes.
+- \b EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(TYPE0,TYPE1) - fails if the two matrix expression types must have different sizes.
+- \b EIGEN_STATIC_ASSERT_SIZE_1x1(TYPE) - fails if \a TYPE cannot be an 1x1 expression.
+
+See StaticAssert.h for details such as what messages they throw.
+
+\subsection DisableStaticAssert Disabling static assertions
+
+If \c EIGEN_NO_STATIC_ASSERT is defined, static assertions turn into <tt>eigen_assert</tt>'s, working like:
+
+\code
+#define EIGEN_STATIC_ASSERT(CONDITION,MSG) eigen_assert((CONDITION) && #MSG);
+\endcode
+
+This saves compile time but consumes more run time. \c EIGEN_NO_STATIC_ASSERT is undefined by default.
*/
}
diff --git a/resources/3rdparty/eigen/doc/I17_SparseLinearSystems.dox b/resources/3rdparty/eigen/doc/I17_SparseLinearSystems.dox
new file mode 100644
index 000000000..cc8987d8a
--- /dev/null
+++ b/resources/3rdparty/eigen/doc/I17_SparseLinearSystems.dox
@@ -0,0 +1,110 @@
+namespace Eigen {
+/** \page TopicSparseSystems Solving Sparse Linear Systems
+In Eigen, there are several methods available to solve linear systems when the coefficient matrix is sparse. Because of the special representation of this class of matrices, special care should be taken in order to get a good performance. See \ref TutorialSparse for a detailed introduction about sparse matrices in Eigen. In this page, we briefly present the main steps that are common to all the linear solvers in Eigen together with the main concepts behind them. Depending on the properties of the matrix, the desired accuracy, the end-user is able to tune these steps in order to improve the performance of its code. However, an impatient user does not need to know deeply what's hiding behind these steps: the last section presents a benchmark routine that can be easily used to get an insight on the performance of all the available solvers.
+
+\b Table \b of \b contents \n
+ - \ref TheSparseCompute
+ - \ref TheSparseSolve
+ - \ref BenchmarkRoutine
+
+ As summarized in \ref TutorialSparseDirectSolvers, there are many built-in solvers in Eigen as well as interface to external solvers libraries. All these solvers follow the same calling sequence. The basic steps are as follows :
+\code
+#include <Eigen/RequiredModuleName>
+// ...
+SparseMatrix<double> A;
+// fill A
+VectorXd b, x;
+// fill b
+// solve Ax = b
+SolverClassName<SparseMatrix<double> > solver;
+solver.compute(A);
+if(solver.info()!=Succeeded) {
+ // decomposition failed
+ return;
+}
+x = solver.solve(b);
+if(solver.info()!=Succeeded) {
+ // solving failed
+ return;
+}
+\endcode
+
+\section TheSparseCompute The Compute Step
+In the compute() function, the matrix is generally factorized: LLT for self-adjoint matrices, LDLT for general hermitian matrices and LU for non hermitian matrices. These are the results of using direct solvers. For this class of solvers precisely, the compute step is further subdivided into analyzePattern() and factorize().
+
+The goal of analyzePattern() is to reorder the nonzero elements of the matrix, such that the factorization step creates less fill-in. This step exploits only the structure of the matrix. Hence, the results of this step can be used for other linear systems where the matrix has the same structure. Note however that sometimes, some external solvers (like SuperLU) require that the values of the matrix are set in this step, for instance to equilibrate the rows and columns of the matrix. In this situation, the results of this step can note be used with other matrices.
+
+Eigen provides a limited set of methods to reorder the matrix in this step, either built-in (COLAMD, AMD) or external (METIS). These methods are set in template parameter list of the solver :
+\code
+DirectSolverClassName<SparseMatrix<double>, OrderingMethod<IndexType> > solver;
+\endcode
+
+See \link Ordering_Modules the Ordering module \endlink for the list of available methods and the associated options.
+
+In factorize(), the factors of the coefficient matrix are computed. This step should be called each time the values of the matrix change. However, the structural pattern of the matrix should not change between multiple calls.
+
+For iterative solvers, the compute step is used to eventually setup a preconditioner. Remember that, basically, the goal of the preconditioner is to speedup the convergence of an iterative method by solving a modified linear system where the coefficient matrix has more clustered eigenvalues. For real problems, an iterative solver should always be used with a preconditioner. In Eigen, a preconditioner is selected by simply adding it as a template parameter to the iterative solver object.
+\code
+IterativeSolverClassName<SparseMatrix<double>, PreconditionerName<SparseMatrix<double> > solver;
+\endcode
+The member function preconditioner() returns a read-write reference to the preconditioner
+ to directly interact with it.
+
+For instance, with the ILUT preconditioner, the incomplete factors L and U are computed in this step.
+See \link Sparse_modules the Sparse module \endlink for the list of available preconditioners in Eigen.
+\section TheSparseSolve The Solve step
+The solve() function computes the solution of the linear systems with one or many right hand sides.
+\code
+X = solver.solve(B);
+\endcode
+Here, B can be a vector or a matrix where the columns form the different right hand sides. The solve() function can be called several times as well, for instance When all the right hand sides are not available at once.
+\code
+x1 = solver.solve(b1);
+// Get the second right hand side b2
+x2 = solver.solve(b2);
+// ...
+\endcode
+For direct methods, the solution are computed at the machine precision. Sometimes, the solution need not be too accurate. In this case, the iterative methods are more suitable and the desired accuracy can be set before the solve step using setTolerance(). For all the available functions, please, refer to the documentation of the \link IterativeLinearSolvers_module Iterative solvers module \endlink.
+
+\section BenchmarkRoutine
+Most of the time, all you need is to know how much time it will take to qolve your system, and hopefully, what is the most suitable solver. In Eigen, we provide a benchmark routine that can be used for this purpose. It is very easy to use. First, it should be activated at the configuration step with the flag TEST_REAL_CASES. Then, in bench/spbench, you can compile the routine by typing \b make \e spbenchsolver. You can then run it with --help option to get the list of all available options. Basically, the matrices to test should be in \link http://math.nist.gov/MatrixMarket/formats.html MatrixMarket Coordinate format \endlink, and the routine returns the statistics from all available solvers in Eigen.
+
+The following table gives an example of XHTML statistics from several Eigen built-in and external solvers.
+<TABLE border="1">
+ <TR><TH>Matrix <TH> N <TH> NNZ <TH> <TH > UMFPACK <TH > SUPERLU <TH > PASTIX LU <TH >BiCGSTAB <TH > BiCGSTAB+ILUT <TH >GMRES+ILUT<TH > LDLT <TH> CHOLMOD LDLT <TH > PASTIX LDLT <TH > LLT <TH > CHOLMOD SP LLT <TH > CHOLMOD LLT <TH > PASTIX LLT <TH> CG</TR>
+<TR><TH rowspan="4">vector_graphics <TD rowspan="4"> 12855 <TD rowspan="4"> 72069 <TH>Compute Time <TD>0.0254549<TD>0.0215677<TD>0.0701827<TD>0.000153388<TD>0.0140107<TD>0.0153709<TD>0.0101601<TD style="background-color:red">0.00930502<TD>0.0649689
+<TR><TH>Solve Time <TD>0.00337835<TD>0.000951826<TD>0.00484373<TD>0.0374886<TD>0.0046445<TD>0.00847754<TD>0.000541813<TD style="background-color:red">0.000293696<TD>0.00485376
+<TR><TH>Total Time <TD>0.0288333<TD>0.0225195<TD>0.0750265<TD>0.037642<TD>0.0186552<TD>0.0238484<TD>0.0107019<TD style="background-color:red">0.00959871<TD>0.0698227
+<TR><TH>Error(Iter) <TD> 1.299e-16 <TD> 2.04207e-16 <TD> 4.83393e-15 <TD> 3.94856e-11 (80) <TD> 1.03861e-12 (3) <TD> 5.81088e-14 (6) <TD> 1.97578e-16 <TD> 1.83927e-16 <TD> 4.24115e-15
+<TR><TH rowspan="4">poisson_SPD <TD rowspan="4"> 19788 <TD rowspan="4"> 308232 <TH>Compute Time <TD>0.425026<TD>1.82378<TD>0.617367<TD>0.000478921<TD>1.34001<TD>1.33471<TD>0.796419<TD>0.857573<TD>0.473007<TD>0.814826<TD style="background-color:red">0.184719<TD>0.861555<TD>0.470559<TD>0.000458188
+<TR><TH>Solve Time <TD>0.0280053<TD>0.0194402<TD>0.0268747<TD>0.249437<TD>0.0548444<TD>0.0926991<TD>0.00850204<TD>0.0053171<TD>0.0258932<TD>0.00874603<TD style="background-color:red">0.00578155<TD>0.00530361<TD>0.0248942<TD>0.239093
+<TR><TH>Total Time <TD>0.453031<TD>1.84322<TD>0.644241<TD>0.249916<TD>1.39486<TD>1.42741<TD>0.804921<TD>0.862891<TD>0.4989<TD>0.823572<TD style="background-color:red">0.190501<TD>0.866859<TD>0.495453<TD>0.239551
+<TR><TH>Error(Iter) <TD> 4.67146e-16 <TD> 1.068e-15 <TD> 1.3397e-15 <TD> 6.29233e-11 (201) <TD> 3.68527e-11 (6) <TD> 3.3168e-15 (16) <TD> 1.86376e-15 <TD> 1.31518e-16 <TD> 1.42593e-15 <TD> 3.45361e-15 <TD> 3.14575e-16 <TD> 2.21723e-15 <TD> 7.21058e-16 <TD> 9.06435e-12 (261)
+<TR><TH rowspan="4">sherman2 <TD rowspan="4"> 1080 <TD rowspan="4"> 23094 <TH>Compute Time <TD style="background-color:red">0.00631754<TD>0.015052<TD>0.0247514 <TD> -<TD>0.0214425<TD>0.0217988
+<TR><TH>Solve Time <TD style="background-color:red">0.000478424<TD>0.000337998<TD>0.0010291 <TD> -<TD>0.00243152<TD>0.00246152
+<TR><TH>Total Time <TD style="background-color:red">0.00679597<TD>0.01539<TD>0.0257805 <TD> -<TD>0.023874<TD>0.0242603
+<TR><TH>Error(Iter) <TD> 1.83099e-15 <TD> 8.19351e-15 <TD> 2.625e-14 <TD> 1.3678e+69 (1080) <TD> 4.1911e-12 (7) <TD> 5.0299e-13 (12)
+<TR><TH rowspan="4">bcsstk01_SPD <TD rowspan="4"> 48 <TD rowspan="4"> 400 <TH>Compute Time <TD>0.000169079<TD>0.00010789<TD>0.000572538<TD>1.425e-06<TD>9.1612e-05<TD>8.3985e-05<TD style="background-color:red">5.6489e-05<TD>7.0913e-05<TD>0.000468251<TD>5.7389e-05<TD>8.0212e-05<TD>5.8394e-05<TD>0.000463017<TD>1.333e-06
+<TR><TH>Solve Time <TD>1.2288e-05<TD>1.1124e-05<TD>0.000286387<TD>8.5896e-05<TD>1.6381e-05<TD>1.6984e-05<TD style="background-color:red">3.095e-06<TD>4.115e-06<TD>0.000325438<TD>3.504e-06<TD>7.369e-06<TD>3.454e-06<TD>0.000294095<TD>6.0516e-05
+<TR><TH>Total Time <TD>0.000181367<TD>0.000119014<TD>0.000858925<TD>8.7321e-05<TD>0.000107993<TD>0.000100969<TD style="background-color:red">5.9584e-05<TD>7.5028e-05<TD>0.000793689<TD>6.0893e-05<TD>8.7581e-05<TD>6.1848e-05<TD>0.000757112<TD>6.1849e-05
+<TR><TH>Error(Iter) <TD> 1.03474e-16 <TD> 2.23046e-16 <TD> 2.01273e-16 <TD> 4.87455e-07 (48) <TD> 1.03553e-16 (2) <TD> 3.55965e-16 (2) <TD> 2.48189e-16 <TD> 1.88808e-16 <TD> 1.97976e-16 <TD> 2.37248e-16 <TD> 1.82701e-16 <TD> 2.71474e-16 <TD> 2.11322e-16 <TD> 3.547e-09 (48)
+<TR><TH rowspan="4">sherman1 <TD rowspan="4"> 1000 <TD rowspan="4"> 3750 <TH>Compute Time <TD>0.00228805<TD>0.00209231<TD>0.00528268<TD>9.846e-06<TD>0.00163522<TD>0.00162155<TD>0.000789259<TD style="background-color:red">0.000804495<TD>0.00438269
+<TR><TH>Solve Time <TD>0.000213788<TD>9.7983e-05<TD>0.000938831<TD>0.00629835<TD>0.000361764<TD>0.00078794<TD>4.3989e-05<TD style="background-color:red">2.5331e-05<TD>0.000917166
+<TR><TH>Total Time <TD>0.00250184<TD>0.00219029<TD>0.00622151<TD>0.0063082<TD>0.00199698<TD>0.00240949<TD>0.000833248<TD style="background-color:red">0.000829826<TD>0.00529986
+<TR><TH>Error(Iter) <TD> 1.16839e-16 <TD> 2.25968e-16 <TD> 2.59116e-16 <TD> 3.76779e-11 (248) <TD> 4.13343e-11 (4) <TD> 2.22347e-14 (10) <TD> 2.05861e-16 <TD> 1.83555e-16 <TD> 1.02917e-15
+<TR><TH rowspan="4">young1c <TD rowspan="4"> 841 <TD rowspan="4"> 4089 <TH>Compute Time <TD>0.00235843<TD style="background-color:red">0.00217228<TD>0.00568075<TD>1.2735e-05<TD>0.00264866<TD>0.00258236
+<TR><TH>Solve Time <TD>0.000329599<TD style="background-color:red">0.000168634<TD>0.00080118<TD>0.0534738<TD>0.00187193<TD>0.00450211
+<TR><TH>Total Time <TD>0.00268803<TD style="background-color:red">0.00234091<TD>0.00648193<TD>0.0534865<TD>0.00452059<TD>0.00708447
+<TR><TH>Error(Iter) <TD> 1.27029e-16 <TD> 2.81321e-16 <TD> 5.0492e-15 <TD> 8.0507e-11 (706) <TD> 3.00447e-12 (8) <TD> 1.46532e-12 (16)
+<TR><TH rowspan="4">mhd1280b <TD rowspan="4"> 1280 <TD rowspan="4"> 22778 <TH>Compute Time <TD>0.00234898<TD>0.00207079<TD>0.00570918<TD>2.5976e-05<TD>0.00302563<TD>0.00298036<TD>0.00144525<TD style="background-color:red">0.000919922<TD>0.00426444
+<TR><TH>Solve Time <TD>0.00103392<TD>0.000211911<TD>0.00105<TD>0.0110432<TD>0.000628287<TD>0.00392089<TD>0.000138303<TD style="background-color:red">6.2446e-05<TD>0.00097564
+<TR><TH>Total Time <TD>0.0033829<TD>0.0022827<TD>0.00675918<TD>0.0110692<TD>0.00365392<TD>0.00690124<TD>0.00158355<TD style="background-color:red">0.000982368<TD>0.00524008
+<TR><TH>Error(Iter) <TD> 1.32953e-16 <TD> 3.08646e-16 <TD> 6.734e-16 <TD> 8.83132e-11 (40) <TD> 1.51153e-16 (1) <TD> 6.08556e-16 (8) <TD> 1.89264e-16 <TD> 1.97477e-16 <TD> 6.68126e-09
+<TR><TH rowspan="4">crashbasis <TD rowspan="4"> 160000 <TD rowspan="4"> 1750416 <TH>Compute Time <TD>3.2019<TD>5.7892<TD>15.7573<TD style="background-color:red">0.00383515<TD>3.1006<TD>3.09921
+<TR><TH>Solve Time <TD>0.261915<TD>0.106225<TD>0.402141<TD style="background-color:red">1.49089<TD>0.24888<TD>0.443673
+<TR><TH>Total Time <TD>3.46381<TD>5.89542<TD>16.1594<TD style="background-color:red">1.49473<TD>3.34948<TD>3.54288
+<TR><TH>Error(Iter) <TD> 1.76348e-16 <TD> 4.58395e-16 <TD> 1.67982e-14 <TD> 8.64144e-11 (61) <TD> 8.5996e-12 (2) <TD> 6.04042e-14 (5)
+
+</TABLE>
+*/
+}
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/doc/QuickReference.dox b/resources/3rdparty/eigen/doc/QuickReference.dox
index 3310d390a..31b8030f4 100644
--- a/resources/3rdparty/eigen/doc/QuickReference.dox
+++ b/resources/3rdparty/eigen/doc/QuickReference.dox
@@ -490,7 +490,7 @@ Read-write access to sub-vectors:
<tr><td>\code vec1.head(n)\endcode</td><td>\code vec1.head<n>()\endcode</td><td>the first \c n coeffs </td></tr>
<tr><td>\code vec1.tail(n)\endcode</td><td>\code vec1.tail<n>()\endcode</td><td>the last \c n coeffs </td></tr>
<tr><td>\code vec1.segment(pos,n)\endcode</td><td>\code vec1.segment<n>(pos)\endcode</td>
- <td>the \c n coeffs in \n the range [\c pos : \c pos + \c n [</td></tr>
+ <td>the \c n coeffs in the \n range [\c pos : \c pos + \c n - 1]</td></tr>
<tr class="alt"><td colspan="3">
Read-write access to sub-matrices:</td></tr>
diff --git a/resources/3rdparty/eigen/doc/eigendoxy_footer.html.in b/resources/3rdparty/eigen/doc/eigendoxy_footer.html.in
index e70829fb0..ebb187b31 100644
--- a/resources/3rdparty/eigen/doc/eigendoxy_footer.html.in
+++ b/resources/3rdparty/eigen/doc/eigendoxy_footer.html.in
@@ -1,5 +1,17 @@
+<hr class="footer"/>
+
+<!-- Piwik -->
+<script type="text/javascript">
+var pkBaseURL = (("https:" == document.location.protocol) ? "https://stats.sylphide-consulting.com/piwik/" : "http://stats.sylphide-consulting.com/piwik/");
+document.write(unescape("%3Cscript src='" + pkBaseURL + "piwik.js' type='text/javascript'%3E%3C/script%3E"));
+</script><script type="text/javascript">
+try {
+var piwikTracker = Piwik.getTracker(pkBaseURL + "piwik.php", 20);
+piwikTracker.trackPageView();
+piwikTracker.enableLinkTracking();
+} catch( err ) {}
+</script><noscript><p><img src="http://stats.sylphide-consulting.com/piwik/piwik.php?idsite=20" style="border:0" alt="" /></p></noscript>
+<!-- End Piwik Tracking Code -->
-<hr class="footer"/><address class="footer"><small>
-<a href="http://www.doxygen.org/index.html"><img class="footer" src="$relpath$doxygen.png" alt="doxygen"/></a></small></address>
</body>
-</html>
\ No newline at end of file
+</html>
diff --git a/resources/3rdparty/eigen/doc/examples/CMakeLists.txt b/resources/3rdparty/eigen/doc/examples/CMakeLists.txt
index 13ec0c123..71b272a15 100644
--- a/resources/3rdparty/eigen/doc/examples/CMakeLists.txt
+++ b/resources/3rdparty/eigen/doc/examples/CMakeLists.txt
@@ -1,7 +1,5 @@
file(GLOB examples_SRCS "*.cpp")
-add_custom_target(all_examples)
-
foreach(example_src ${examples_SRCS})
get_filename_component(example ${example_src} NAME_WE)
add_executable(${example} ${example_src})
diff --git a/resources/3rdparty/eigen/doc/examples/QuickStart_example2_dynamic.cpp b/resources/3rdparty/eigen/doc/examples/QuickStart_example2_dynamic.cpp
index 672ac82e9..ff6746e21 100644
--- a/resources/3rdparty/eigen/doc/examples/QuickStart_example2_dynamic.cpp
+++ b/resources/3rdparty/eigen/doc/examples/QuickStart_example2_dynamic.cpp
@@ -6,10 +6,10 @@ using namespace std;
int main()
{
- MatrixXf m = MatrixXf::Random(3,3);
- m = (m + MatrixXf::Constant(3,3,1.2)) * 50;
+ MatrixXd m = MatrixXd::Random(3,3);
+ m = (m + MatrixXd::Constant(3,3,1.2)) * 50;
cout << "m =" << endl << m << endl;
- VectorXf v(3);
+ VectorXd v(3);
v << 1, 2, 3;
cout << "m * v =" << endl << m * v << endl;
}
diff --git a/resources/3rdparty/eigen/doc/examples/QuickStart_example2_fixed.cpp b/resources/3rdparty/eigen/doc/examples/QuickStart_example2_fixed.cpp
index edf3268cd..d91175273 100644
--- a/resources/3rdparty/eigen/doc/examples/QuickStart_example2_fixed.cpp
+++ b/resources/3rdparty/eigen/doc/examples/QuickStart_example2_fixed.cpp
@@ -6,10 +6,10 @@ using namespace std;
int main()
{
- Matrix3f m = Matrix3f::Random();
- m = (m + Matrix3f::Constant(1.2)) * 50;
+ Matrix3d m = Matrix3d::Random();
+ m = (m + Matrix3d::Constant(1.2)) * 50;
cout << "m =" << endl << m << endl;
- Vector3f v(1,2,3);
+ Vector3d v(1,2,3);
cout << "m * v =" << endl << m * v << endl;
}
diff --git a/resources/3rdparty/eigen/doc/snippets/GeneralizedEigenSolver.cpp b/resources/3rdparty/eigen/doc/snippets/GeneralizedEigenSolver.cpp
new file mode 100644
index 000000000..2acda45fa
--- /dev/null
+++ b/resources/3rdparty/eigen/doc/snippets/GeneralizedEigenSolver.cpp
@@ -0,0 +1,7 @@
+GeneralizedEigenSolver<MatrixXf> ges;
+MatrixXf A = MatrixXf::Random(4,4);
+MatrixXf B = MatrixXf::Random(4,4);
+ges.compute(A, B);
+cout << "The (complex) numerators of the generalzied eigenvalues are: " << ges.alphas().transpose() << endl;
+cout << "The (real) denominatore of the generalzied eigenvalues are: " << ges.betas().transpose() << endl;
+cout << "The (complex) generalzied eigenvalues are (alphas./beta): " << ges.eigenvalues().transpose() << endl;
diff --git a/resources/3rdparty/eigen/doc/snippets/HouseholderQR_householderQ.cpp b/resources/3rdparty/eigen/doc/snippets/HouseholderQR_householderQ.cpp
new file mode 100644
index 000000000..e859ce55b
--- /dev/null
+++ b/resources/3rdparty/eigen/doc/snippets/HouseholderQR_householderQ.cpp
@@ -0,0 +1,7 @@
+MatrixXf A(MatrixXf::Random(5,3)), thinQ(MatrixXf::Identity(5,3)), Q;
+A.setRandom();
+HouseholderQR<MatrixXf> qr(A);
+Q = qr.householderQ();
+thinQ = qr.householderQ() * thinQ;
+std::cout << "The complete unitary matrix Q is:\n" << Q << "\n\n";
+std::cout << "The thin matrix Q is:\n" << thinQ << "\n\n";
diff --git a/resources/3rdparty/eigen/doc/snippets/RealQZ_compute.cpp b/resources/3rdparty/eigen/doc/snippets/RealQZ_compute.cpp
new file mode 100644
index 000000000..a18da42e8
--- /dev/null
+++ b/resources/3rdparty/eigen/doc/snippets/RealQZ_compute.cpp
@@ -0,0 +1,17 @@
+MatrixXf A = MatrixXf::Random(4,4);
+MatrixXf B = MatrixXf::Random(4,4);
+RealQZ<MatrixXf> qz(4); // preallocate space for 4x4 matrices
+qz.compute(A,B); // A = Q S Z, B = Q T Z
+
+// print original matrices and result of decomposition
+cout << "A:\n" << A << "\n" << "B:\n" << B << "\n";
+cout << "S:\n" << qz.matrixS() << "\n" << "T:\n" << qz.matrixT() << "\n";
+cout << "Q:\n" << qz.matrixQ() << "\n" << "Z:\n" << qz.matrixZ() << "\n";
+
+// verify precision
+cout << "\nErrors:"
+ << "\n|A-QSZ|: " << (A-qz.matrixQ()*qz.matrixS()*qz.matrixZ()).norm()
+ << ", |B-QTZ|: " << (B-qz.matrixQ()*qz.matrixT()*qz.matrixZ()).norm()
+ << "\n|QQ* - I|: " << (qz.matrixQ()*qz.matrixQ().adjoint() - MatrixXf::Identity(4,4)).norm()
+ << ", |ZZ* - I|: " << (qz.matrixZ()*qz.matrixZ().adjoint() - MatrixXf::Identity(4,4)).norm()
+ << "\n";
diff --git a/resources/3rdparty/eigen/doc/special_examples/CMakeLists.txt b/resources/3rdparty/eigen/doc/special_examples/CMakeLists.txt
index eeeae1d2a..138a2f6ef 100644
--- a/resources/3rdparty/eigen/doc/special_examples/CMakeLists.txt
+++ b/resources/3rdparty/eigen/doc/special_examples/CMakeLists.txt
@@ -17,4 +17,5 @@ if(QT4_FOUND)
COMMAND Tutorial_sparse_example
ARGS ${CMAKE_CURRENT_BINARY_DIR}/../html/Tutorial_sparse_example.jpeg
)
+ add_dependencies(all_examples Tutorial_sparse_example)
endif(QT4_FOUND)
diff --git a/resources/3rdparty/eigen/test/CMakeLists.txt b/resources/3rdparty/eigen/test/CMakeLists.txt
index 6f8fc4ae3..cbea4dd0a 100644
--- a/resources/3rdparty/eigen/test/CMakeLists.txt
+++ b/resources/3rdparty/eigen/test/CMakeLists.txt
@@ -162,6 +162,8 @@ ei_add_test(schur_complex)
ei_add_test(eigensolver_selfadjoint)
ei_add_test(eigensolver_generic)
ei_add_test(eigensolver_complex)
+ei_add_test(real_qz)
+ei_add_test(eigensolver_generalized_real)
ei_add_test(jacobi)
ei_add_test(jacobisvd)
ei_add_test(geo_orthomethods)
@@ -195,6 +197,7 @@ ei_add_test(nullary)
ei_add_test(nesting_ops "${CMAKE_CXX_FLAGS_DEBUG}")
ei_add_test(zerosized)
ei_add_test(dontalign)
+ei_add_test(evaluators)
ei_add_test(sizeoverflow)
ei_add_test(prec_inverse_4x4)
ei_add_test(vectorwiseop)
@@ -202,7 +205,7 @@ ei_add_test(vectorwiseop)
ei_add_test(simplicial_cholesky)
ei_add_test(conjugate_gradient)
ei_add_test(bicgstab)
-
+ei_add_test(sparselu)
if(UMFPACK_FOUND)
ei_add_test(umfpack_support "" "${UMFPACK_ALL_LIBS}")
diff --git a/resources/3rdparty/eigen/test/array_for_matrix.cpp b/resources/3rdparty/eigen/test/array_for_matrix.cpp
index 4b637c3a6..5a599c321 100644
--- a/resources/3rdparty/eigen/test/array_for_matrix.cpp
+++ b/resources/3rdparty/eigen/test/array_for_matrix.cpp
@@ -168,6 +168,38 @@ template<typename MatrixType> void cwise_min_max(const MatrixType& m)
VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax( maxM1));
VERIFY_IS_APPROX(m1, m1.cwiseMax( minM1));
+ VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, minM1).array(), (m1.array().min)( minM1));
+ VERIFY_IS_APPROX(m1.array(), (m1.array().min)( maxM1));
+
+ VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1).array(), (m1.array().max)( maxM1));
+ VERIFY_IS_APPROX(m1.array(), (m1.array().max)( minM1));
+
+}
+
+template<typename MatrixTraits> void resize(const MatrixTraits& t)
+{
+ typedef typename MatrixTraits::Index Index;
+ typedef typename MatrixTraits::Scalar Scalar;
+ typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType;
+ typedef Array<Scalar,Dynamic,Dynamic> Array2DType;
+ typedef Matrix<Scalar,Dynamic,1> VectorType;
+ typedef Array<Scalar,Dynamic,1> Array1DType;
+
+ Index rows = t.rows(), cols = t.cols();
+
+ MatrixType m(rows,cols);
+ VectorType v(rows);
+ Array2DType a2(rows,cols);
+ Array1DType a1(rows);
+
+ m.array().resize(rows+1,cols+1);
+ VERIFY(m.rows()==rows+1 && m.cols()==cols+1);
+ a2.matrix().resize(rows+1,cols+1);
+ VERIFY(a2.rows()==rows+1 && a2.cols()==cols+1);
+ v.array().resize(cols);
+ VERIFY(v.size()==cols);
+ a1.matrix().resize(cols);
+ VERIFY(a1.size()==cols);
}
void test_array_for_matrix()
@@ -202,4 +234,9 @@ void test_array_for_matrix()
CALL_SUBTEST_5( lpNorm(VectorXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_4( lpNorm(VectorXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
}
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_4( resize(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+ CALL_SUBTEST_5( resize(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+ CALL_SUBTEST_6( resize(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+ }
}
diff --git a/resources/3rdparty/eigen/test/cholesky.cpp b/resources/3rdparty/eigen/test/cholesky.cpp
index 14e01c006..49c79f9c8 100644
--- a/resources/3rdparty/eigen/test/cholesky.cpp
+++ b/resources/3rdparty/eigen/test/cholesky.cpp
@@ -262,6 +262,19 @@ template<typename MatrixType> void cholesky_bug241(const MatrixType& m)
VERIFY_IS_APPROX(matA * vecX, vecB);
}
+// LDLT is not guaranteed to work for indefinite matrices, but happens to work fine if matrix is diagonal.
+// This test checks that LDLT reports correctly that matrix is indefinite.
+// See http://forum.kde.org/viewtopic.php?f=74&t=106942
+template<typename MatrixType> void cholesky_indefinite(const MatrixType& m)
+{
+ eigen_assert(m.rows() == 2 && m.cols() == 2);
+ MatrixType mat;
+ mat << 1, 0, 0, -1;
+ LDLT<MatrixType> ldlt(mat);
+ VERIFY(!ldlt.isNegative());
+ VERIFY(!ldlt.isPositive());
+}
+
template<typename MatrixType> void cholesky_verify_assert()
{
MatrixType tmp;
@@ -289,6 +302,7 @@ void test_cholesky()
CALL_SUBTEST_1( cholesky(Matrix<double,1,1>()) );
CALL_SUBTEST_3( cholesky(Matrix2d()) );
CALL_SUBTEST_3( cholesky_bug241(Matrix2d()) );
+ CALL_SUBTEST_3( cholesky_indefinite(Matrix2d()) );
CALL_SUBTEST_4( cholesky(Matrix3f()) );
CALL_SUBTEST_5( cholesky(Matrix4d()) );
s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
diff --git a/resources/3rdparty/eigen/test/diagonal.cpp b/resources/3rdparty/eigen/test/diagonal.cpp
index 95cd10372..0f09a9dfe 100644
--- a/resources/3rdparty/eigen/test/diagonal.cpp
+++ b/resources/3rdparty/eigen/test/diagonal.cpp
@@ -31,17 +31,14 @@ template<typename MatrixType> void diagonal(const MatrixType& m)
if (rows>2)
{
enum {
- N1 = MatrixType::RowsAtCompileTime>1 ? 1 : 0,
- N2 = MatrixType::RowsAtCompileTime>2 ? -2 : 0
+ N1 = MatrixType::RowsAtCompileTime>2 ? 2 : 0,
+ N2 = MatrixType::RowsAtCompileTime>1 ? -1 : 0
};
// check sub/super diagonal
- if(m1.template diagonal<N1>().RowsAtCompileTime!=Dynamic)
+ if(MatrixType::SizeAtCompileTime!=Dynamic)
{
VERIFY(m1.template diagonal<N1>().RowsAtCompileTime == m1.diagonal(N1).size());
- }
- if(m1.template diagonal<N2>().RowsAtCompileTime!=Dynamic)
- {
VERIFY(m1.template diagonal<N2>().RowsAtCompileTime == m1.diagonal(N2).size());
}
diff --git a/resources/3rdparty/eigen/test/diagonalmatrices.cpp b/resources/3rdparty/eigen/test/diagonalmatrices.cpp
index 3f5776dfc..7e9c80d7b 100644
--- a/resources/3rdparty/eigen/test/diagonalmatrices.cpp
+++ b/resources/3rdparty/eigen/test/diagonalmatrices.cpp
@@ -32,6 +32,8 @@ template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
rv2 = RowVectorType::Random(cols);
LeftDiagonalMatrix ldm1(v1), ldm2(v2);
RightDiagonalMatrix rdm1(rv1), rdm2(rv2);
+
+ Scalar s1 = internal::random<Scalar>();
SquareMatrixType sq_m1 (v1.asDiagonal());
VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
@@ -76,6 +78,13 @@ template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
big.block(i,j,rows,cols) = big.block(i,j,rows,cols) * rv1.asDiagonal();
VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , m1 * rv1.asDiagonal() );
+
+ // scalar multiple
+ VERIFY_IS_APPROX(LeftDiagonalMatrix(ldm1*s1).diagonal(), ldm1.diagonal() * s1);
+ VERIFY_IS_APPROX(LeftDiagonalMatrix(s1*ldm1).diagonal(), s1 * ldm1.diagonal());
+
+ VERIFY_IS_APPROX(m1 * (rdm1 * s1), (m1 * rdm1) * s1);
+ VERIFY_IS_APPROX(m1 * (s1 * rdm1), (m1 * rdm1) * s1);
}
void test_diagonalmatrices()
diff --git a/resources/3rdparty/eigen/test/eigensolver_complex.cpp b/resources/3rdparty/eigen/test/eigensolver_complex.cpp
index 0c2059512..aef125739 100644
--- a/resources/3rdparty/eigen/test/eigensolver_complex.cpp
+++ b/resources/3rdparty/eigen/test/eigensolver_complex.cpp
@@ -59,6 +59,17 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
// another algorithm so results may differ slightly
verify_is_approx_upto_permutation(a.eigenvalues(), ei1.eigenvalues());
+ ComplexEigenSolver<MatrixType> ei2;
+ ei2.setMaxIterations(ComplexSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
+ VERIFY_IS_EQUAL(ei2.info(), Success);
+ VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
+ VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
+ if (rows > 2) {
+ ei2.setMaxIterations(1).compute(a);
+ VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
+ VERIFY_IS_EQUAL(ei2.getMaxIterations(), 1);
+ }
+
ComplexEigenSolver<MatrixType> eiNoEivecs(a, false);
VERIFY_IS_EQUAL(eiNoEivecs.info(), Success);
VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues());
diff --git a/resources/3rdparty/eigen/test/eigensolver_generalized_real.cpp b/resources/3rdparty/eigen/test/eigensolver_generalized_real.cpp
new file mode 100644
index 000000000..e3edbb772
--- /dev/null
+++ b/resources/3rdparty/eigen/test/eigensolver_generalized_real.cpp
@@ -0,0 +1,63 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 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/.
+
+#include "main.h"
+#include <limits>
+#include <Eigen/Eigenvalues>
+
+template<typename MatrixType> void generalized_eigensolver_real(const MatrixType& m)
+{
+ typedef typename MatrixType::Index Index;
+ /* this test covers the following files:
+ GeneralizedEigenSolver.h
+ */
+ Index rows = m.rows();
+ Index cols = m.cols();
+
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+ typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
+ typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
+ typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
+
+ MatrixType a = MatrixType::Random(rows,cols);
+ MatrixType b = MatrixType::Random(rows,cols);
+ MatrixType a1 = MatrixType::Random(rows,cols);
+ MatrixType b1 = MatrixType::Random(rows,cols);
+ MatrixType spdA = a.adjoint() * a + a1.adjoint() * a1;
+ MatrixType spdB = b.adjoint() * b + b1.adjoint() * b1;
+
+ // lets compare to GeneralizedSelfAdjointEigenSolver
+ GeneralizedSelfAdjointEigenSolver<MatrixType> symmEig(spdA, spdB);
+ GeneralizedEigenSolver<MatrixType> eig(spdA, spdB);
+
+ VERIFY_IS_EQUAL(eig.eigenvalues().imag().cwiseAbs().maxCoeff(), 0);
+
+ VectorType realEigenvalues = eig.eigenvalues().real();
+ std::sort(realEigenvalues.data(), realEigenvalues.data()+realEigenvalues.size());
+ VERIFY_IS_APPROX(realEigenvalues, symmEig.eigenvalues());
+}
+
+void test_eigensolver_generalized_real()
+{
+ int s;
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1( generalized_eigensolver_real(Matrix4f()) );
+ s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
+ CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(s,s)) );
+
+ // some trivial but implementation-wise tricky cases
+ CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(1,1)) );
+ CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(2,2)) );
+ CALL_SUBTEST_3( generalized_eigensolver_real(Matrix<double,1,1>()) );
+ CALL_SUBTEST_4( generalized_eigensolver_real(Matrix2d()) );
+ }
+
+ EIGEN_UNUSED_VARIABLE(s)
+}
diff --git a/resources/3rdparty/eigen/test/eigensolver_generic.cpp b/resources/3rdparty/eigen/test/eigensolver_generic.cpp
index 0b55ccd93..ef499a989 100644
--- a/resources/3rdparty/eigen/test/eigensolver_generic.cpp
+++ b/resources/3rdparty/eigen/test/eigensolver_generic.cpp
@@ -2,7 +2,7 @@
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// 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
@@ -45,6 +45,17 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
VERIFY_IS_APPROX(ei1.eigenvectors().colwise().norm(), RealVectorType::Ones(rows).transpose());
VERIFY_IS_APPROX(a.eigenvalues(), ei1.eigenvalues());
+ EigenSolver<MatrixType> ei2;
+ ei2.setMaxIterations(RealSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
+ VERIFY_IS_EQUAL(ei2.info(), Success);
+ VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
+ VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
+ if (rows > 2) {
+ ei2.setMaxIterations(1).compute(a);
+ VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
+ VERIFY_IS_EQUAL(ei2.getMaxIterations(), 1);
+ }
+
EigenSolver<MatrixType> eiNoEivecs(a, false);
VERIFY_IS_EQUAL(eiNoEivecs.info(), Success);
VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues());
diff --git a/resources/3rdparty/eigen/test/evaluators.cpp b/resources/3rdparty/eigen/test/evaluators.cpp
new file mode 100644
index 000000000..3081d7858
--- /dev/null
+++ b/resources/3rdparty/eigen/test/evaluators.cpp
@@ -0,0 +1,321 @@
+#define EIGEN_ENABLE_EVALUATORS
+#include "main.h"
+
+using internal::copy_using_evaluator;
+using namespace std;
+
+#define VERIFY_IS_APPROX_EVALUATOR(DEST,EXPR) VERIFY_IS_APPROX(copy_using_evaluator(DEST,(EXPR)), (EXPR).eval());
+#define VERIFY_IS_APPROX_EVALUATOR2(DEST,EXPR,REF) VERIFY_IS_APPROX(copy_using_evaluator(DEST,(EXPR)), (REF).eval());
+
+void test_evaluators()
+{
+ // Testing Matrix evaluator and Transpose
+ Vector2d v = Vector2d::Random();
+ const Vector2d v_const(v);
+ Vector2d v2;
+ RowVector2d w;
+
+ VERIFY_IS_APPROX_EVALUATOR(v2, v);
+ VERIFY_IS_APPROX_EVALUATOR(v2, v_const);
+
+ // Testing Transpose
+ VERIFY_IS_APPROX_EVALUATOR(w, v.transpose()); // Transpose as rvalue
+ VERIFY_IS_APPROX_EVALUATOR(w, v_const.transpose());
+
+ copy_using_evaluator(w.transpose(), v); // Transpose as lvalue
+ VERIFY_IS_APPROX(w,v.transpose().eval());
+
+ copy_using_evaluator(w.transpose(), v_const);
+ VERIFY_IS_APPROX(w,v_const.transpose().eval());
+
+ // Testing Array evaluator
+ ArrayXXf a(2,3);
+ ArrayXXf b(3,2);
+ a << 1,2,3, 4,5,6;
+ const ArrayXXf a_const(a);
+
+ VERIFY_IS_APPROX_EVALUATOR(b, a.transpose());
+
+ VERIFY_IS_APPROX_EVALUATOR(b, a_const.transpose());
+
+ // Testing CwiseNullaryOp evaluator
+ copy_using_evaluator(w, RowVector2d::Random());
+ VERIFY((w.array() >= -1).all() && (w.array() <= 1).all()); // not easy to test ...
+
+ VERIFY_IS_APPROX_EVALUATOR(w, RowVector2d::Zero());
+
+ VERIFY_IS_APPROX_EVALUATOR(w, RowVector2d::Constant(3));
+
+ // mix CwiseNullaryOp and transpose
+ VERIFY_IS_APPROX_EVALUATOR(w, Vector2d::Zero().transpose());
+
+ {
+ // test product expressions
+ int s = internal::random<int>(1,100);
+ MatrixXf a(s,s), b(s,s), c(s,s), d(s,s);
+ a.setRandom();
+ b.setRandom();
+ c.setRandom();
+ d.setRandom();
+ VERIFY_IS_APPROX_EVALUATOR(d, (a + b));
+ VERIFY_IS_APPROX_EVALUATOR(d, (a + b).transpose());
+ VERIFY_IS_APPROX_EVALUATOR2(d, prod(a,b), a*b);
+ VERIFY_IS_APPROX_EVALUATOR2(d.noalias(), prod(a,b), a*b);
+ VERIFY_IS_APPROX_EVALUATOR2(d, prod(a,b) + c, a*b + c);
+ VERIFY_IS_APPROX_EVALUATOR2(d, s * prod(a,b), s * a*b);
+ VERIFY_IS_APPROX_EVALUATOR2(d, prod(a,b).transpose(), (a*b).transpose());
+ VERIFY_IS_APPROX_EVALUATOR2(d, prod(a,b) + prod(b,c), a*b + b*c);
+
+ // check that prod works even with aliasing present
+ c = a*a;
+ copy_using_evaluator(a, prod(a,a));
+ VERIFY_IS_APPROX(a,c);
+ }
+
+ {
+ // test product with all possible sizes
+ int s = internal::random<int>(1,100);
+ Matrix<float, 1, 1> m11, res11; m11.setRandom(1,1);
+ Matrix<float, 1, 4> m14, res14; m14.setRandom(1,4);
+ Matrix<float, 1,Dynamic> m1X, res1X; m1X.setRandom(1,s);
+ Matrix<float, 4, 1> m41, res41; m41.setRandom(4,1);
+ Matrix<float, 4, 4> m44, res44; m44.setRandom(4,4);
+ Matrix<float, 4,Dynamic> m4X, res4X; m4X.setRandom(4,s);
+ Matrix<float,Dynamic, 1> mX1, resX1; mX1.setRandom(s,1);
+ Matrix<float,Dynamic, 4> mX4, resX4; mX4.setRandom(s,4);
+ Matrix<float,Dynamic,Dynamic> mXX, resXX; mXX.setRandom(s,s);
+
+ VERIFY_IS_APPROX_EVALUATOR2(res11, prod(m11,m11), m11*m11);
+ VERIFY_IS_APPROX_EVALUATOR2(res11, prod(m14,m41), m14*m41);
+ VERIFY_IS_APPROX_EVALUATOR2(res11, prod(m1X,mX1), m1X*mX1);
+ VERIFY_IS_APPROX_EVALUATOR2(res14, prod(m11,m14), m11*m14);
+ VERIFY_IS_APPROX_EVALUATOR2(res14, prod(m14,m44), m14*m44);
+ VERIFY_IS_APPROX_EVALUATOR2(res14, prod(m1X,mX4), m1X*mX4);
+ VERIFY_IS_APPROX_EVALUATOR2(res1X, prod(m11,m1X), m11*m1X);
+ VERIFY_IS_APPROX_EVALUATOR2(res1X, prod(m14,m4X), m14*m4X);
+ VERIFY_IS_APPROX_EVALUATOR2(res1X, prod(m1X,mXX), m1X*mXX);
+ VERIFY_IS_APPROX_EVALUATOR2(res41, prod(m41,m11), m41*m11);
+ VERIFY_IS_APPROX_EVALUATOR2(res41, prod(m44,m41), m44*m41);
+ VERIFY_IS_APPROX_EVALUATOR2(res41, prod(m4X,mX1), m4X*mX1);
+ VERIFY_IS_APPROX_EVALUATOR2(res44, prod(m41,m14), m41*m14);
+ VERIFY_IS_APPROX_EVALUATOR2(res44, prod(m44,m44), m44*m44);
+ VERIFY_IS_APPROX_EVALUATOR2(res44, prod(m4X,mX4), m4X*mX4);
+ VERIFY_IS_APPROX_EVALUATOR2(res4X, prod(m41,m1X), m41*m1X);
+ VERIFY_IS_APPROX_EVALUATOR2(res4X, prod(m44,m4X), m44*m4X);
+ VERIFY_IS_APPROX_EVALUATOR2(res4X, prod(m4X,mXX), m4X*mXX);
+ VERIFY_IS_APPROX_EVALUATOR2(resX1, prod(mX1,m11), mX1*m11);
+ VERIFY_IS_APPROX_EVALUATOR2(resX1, prod(mX4,m41), mX4*m41);
+ VERIFY_IS_APPROX_EVALUATOR2(resX1, prod(mXX,mX1), mXX*mX1);
+ VERIFY_IS_APPROX_EVALUATOR2(resX4, prod(mX1,m14), mX1*m14);
+ VERIFY_IS_APPROX_EVALUATOR2(resX4, prod(mX4,m44), mX4*m44);
+ VERIFY_IS_APPROX_EVALUATOR2(resX4, prod(mXX,mX4), mXX*mX4);
+ VERIFY_IS_APPROX_EVALUATOR2(resXX, prod(mX1,m1X), mX1*m1X);
+ VERIFY_IS_APPROX_EVALUATOR2(resXX, prod(mX4,m4X), mX4*m4X);
+ VERIFY_IS_APPROX_EVALUATOR2(resXX, prod(mXX,mXX), mXX*mXX);
+ }
+
+ // this does not work because Random is eval-before-nested:
+ // copy_using_evaluator(w, Vector2d::Random().transpose());
+
+ // test CwiseUnaryOp
+ VERIFY_IS_APPROX_EVALUATOR(v2, 3 * v);
+ VERIFY_IS_APPROX_EVALUATOR(w, (3 * v).transpose());
+ VERIFY_IS_APPROX_EVALUATOR(b, (a + 3).transpose());
+ VERIFY_IS_APPROX_EVALUATOR(b, (2 * a_const + 3).transpose());
+
+ // test CwiseBinaryOp
+ VERIFY_IS_APPROX_EVALUATOR(v2, v + Vector2d::Ones());
+ VERIFY_IS_APPROX_EVALUATOR(w, (v + Vector2d::Ones()).transpose().cwiseProduct(RowVector2d::Constant(3)));
+
+ // dynamic matrices and arrays
+ MatrixXd mat1(6,6), mat2(6,6);
+ VERIFY_IS_APPROX_EVALUATOR(mat1, MatrixXd::Identity(6,6));
+ VERIFY_IS_APPROX_EVALUATOR(mat2, mat1);
+ copy_using_evaluator(mat2.transpose(), mat1);
+ VERIFY_IS_APPROX(mat2.transpose(), mat1);
+
+ ArrayXXd arr1(6,6), arr2(6,6);
+ VERIFY_IS_APPROX_EVALUATOR(arr1, ArrayXXd::Constant(6,6, 3.0));
+ VERIFY_IS_APPROX_EVALUATOR(arr2, arr1);
+
+ // test automatic resizing
+ mat2.resize(3,3);
+ VERIFY_IS_APPROX_EVALUATOR(mat2, mat1);
+ arr2.resize(9,9);
+ VERIFY_IS_APPROX_EVALUATOR(arr2, arr1);
+
+ // test direct traversal
+ Matrix3f m3;
+ Array33f a3;
+ VERIFY_IS_APPROX_EVALUATOR(m3, Matrix3f::Identity()); // matrix, nullary
+ // TODO: find a way to test direct traversal with array
+ VERIFY_IS_APPROX_EVALUATOR(m3.transpose(), Matrix3f::Identity().transpose()); // transpose
+ VERIFY_IS_APPROX_EVALUATOR(m3, 2 * Matrix3f::Identity()); // unary
+ VERIFY_IS_APPROX_EVALUATOR(m3, Matrix3f::Identity() + Matrix3f::Zero()); // binary
+ VERIFY_IS_APPROX_EVALUATOR(m3.block(0,0,2,2), Matrix3f::Identity().block(1,1,2,2)); // block
+
+ // test linear traversal
+ VERIFY_IS_APPROX_EVALUATOR(m3, Matrix3f::Zero()); // matrix, nullary
+ VERIFY_IS_APPROX_EVALUATOR(a3, Array33f::Zero()); // array
+ VERIFY_IS_APPROX_EVALUATOR(m3.transpose(), Matrix3f::Zero().transpose()); // transpose
+ VERIFY_IS_APPROX_EVALUATOR(m3, 2 * Matrix3f::Zero()); // unary
+ VERIFY_IS_APPROX_EVALUATOR(m3, Matrix3f::Zero() + m3); // binary
+
+ // test inner vectorization
+ Matrix4f m4, m4src = Matrix4f::Random();
+ Array44f a4, a4src = Matrix4f::Random();
+ VERIFY_IS_APPROX_EVALUATOR(m4, m4src); // matrix
+ VERIFY_IS_APPROX_EVALUATOR(a4, a4src); // array
+ VERIFY_IS_APPROX_EVALUATOR(m4.transpose(), m4src.transpose()); // transpose
+ // TODO: find out why Matrix4f::Zero() does not allow inner vectorization
+ VERIFY_IS_APPROX_EVALUATOR(m4, 2 * m4src); // unary
+ VERIFY_IS_APPROX_EVALUATOR(m4, m4src + m4src); // binary
+
+ // test linear vectorization
+ MatrixXf mX(6,6), mXsrc = MatrixXf::Random(6,6);
+ ArrayXXf aX(6,6), aXsrc = ArrayXXf::Random(6,6);
+ VERIFY_IS_APPROX_EVALUATOR(mX, mXsrc); // matrix
+ VERIFY_IS_APPROX_EVALUATOR(aX, aXsrc); // array
+ VERIFY_IS_APPROX_EVALUATOR(mX.transpose(), mXsrc.transpose()); // transpose
+ VERIFY_IS_APPROX_EVALUATOR(mX, MatrixXf::Zero(6,6)); // nullary
+ VERIFY_IS_APPROX_EVALUATOR(mX, 2 * mXsrc); // unary
+ VERIFY_IS_APPROX_EVALUATOR(mX, mXsrc + mXsrc); // binary
+
+ // test blocks and slice vectorization
+ VERIFY_IS_APPROX_EVALUATOR(m4, (mXsrc.block<4,4>(1,0)));
+ VERIFY_IS_APPROX_EVALUATOR(aX, ArrayXXf::Constant(10, 10, 3.0).block(2, 3, 6, 6));
+
+ Matrix4f m4ref = m4;
+ copy_using_evaluator(m4.block(1, 1, 2, 3), m3.bottomRows(2));
+ m4ref.block(1, 1, 2, 3) = m3.bottomRows(2);
+ VERIFY_IS_APPROX(m4, m4ref);
+
+ mX.setIdentity(20,20);
+ MatrixXf mXref = MatrixXf::Identity(20,20);
+ mXsrc = MatrixXf::Random(9,12);
+ copy_using_evaluator(mX.block(4, 4, 9, 12), mXsrc);
+ mXref.block(4, 4, 9, 12) = mXsrc;
+ VERIFY_IS_APPROX(mX, mXref);
+
+ // test Map
+ const float raw[3] = {1,2,3};
+ float buffer[3] = {0,0,0};
+ Vector3f v3;
+ Array3f a3f;
+ VERIFY_IS_APPROX_EVALUATOR(v3, Map<const Vector3f>(raw));
+ VERIFY_IS_APPROX_EVALUATOR(a3f, Map<const Array3f>(raw));
+ Vector3f::Map(buffer) = 2*v3;
+ VERIFY(buffer[0] == 2);
+ VERIFY(buffer[1] == 4);
+ VERIFY(buffer[2] == 6);
+
+ // test CwiseUnaryView
+ mat1.setRandom();
+ mat2.setIdentity();
+ MatrixXcd matXcd(6,6), matXcd_ref(6,6);
+ copy_using_evaluator(matXcd.real(), mat1);
+ copy_using_evaluator(matXcd.imag(), mat2);
+ matXcd_ref.real() = mat1;
+ matXcd_ref.imag() = mat2;
+ VERIFY_IS_APPROX(matXcd, matXcd_ref);
+
+ // test Select
+ VERIFY_IS_APPROX_EVALUATOR(aX, (aXsrc > 0).select(aXsrc, -aXsrc));
+
+ // test Replicate
+ mXsrc = MatrixXf::Random(6, 6);
+ VectorXf vX = VectorXf::Random(6);
+ mX.resize(6, 6);
+ VERIFY_IS_APPROX_EVALUATOR(mX, mXsrc.colwise() + vX);
+ matXcd.resize(12, 12);
+ VERIFY_IS_APPROX_EVALUATOR(matXcd, matXcd_ref.replicate(2,2));
+ VERIFY_IS_APPROX_EVALUATOR(matXcd, (matXcd_ref.replicate<2,2>()));
+
+ // test partial reductions
+ VectorXd vec1(6);
+ VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.rowwise().sum());
+ VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.colwise().sum().transpose());
+
+ // test MatrixWrapper and ArrayWrapper
+ mat1.setRandom(6,6);
+ arr1.setRandom(6,6);
+ VERIFY_IS_APPROX_EVALUATOR(mat2, arr1.matrix());
+ VERIFY_IS_APPROX_EVALUATOR(arr2, mat1.array());
+ VERIFY_IS_APPROX_EVALUATOR(mat2, (arr1 + 2).matrix());
+ VERIFY_IS_APPROX_EVALUATOR(arr2, mat1.array() + 2);
+ mat2.array() = arr1 * arr1;
+ VERIFY_IS_APPROX(mat2, (arr1 * arr1).matrix());
+ arr2.matrix() = MatrixXd::Identity(6,6);
+ VERIFY_IS_APPROX(arr2, MatrixXd::Identity(6,6).array());
+
+ // test Reverse
+ VERIFY_IS_APPROX_EVALUATOR(arr2, arr1.reverse());
+ VERIFY_IS_APPROX_EVALUATOR(arr2, arr1.colwise().reverse());
+ VERIFY_IS_APPROX_EVALUATOR(arr2, arr1.rowwise().reverse());
+ arr2.reverse() = arr1;
+ VERIFY_IS_APPROX(arr2, arr1.reverse());
+ mat2.array() = mat1.array().reverse();
+ VERIFY_IS_APPROX(mat2.array(), mat1.array().reverse());
+
+ // test Diagonal
+ VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.diagonal());
+ vec1.resize(5);
+ VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.diagonal(1));
+ VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.diagonal<-1>());
+ vec1.setRandom();
+
+ mat2 = mat1;
+ copy_using_evaluator(mat1.diagonal(1), vec1);
+ mat2.diagonal(1) = vec1;
+ VERIFY_IS_APPROX(mat1, mat2);
+
+ copy_using_evaluator(mat1.diagonal<-1>(), mat1.diagonal(1));
+ mat2.diagonal<-1>() = mat2.diagonal(1);
+ VERIFY_IS_APPROX(mat1, mat2);
+
+ {
+ // test swapping
+ MatrixXd mat1, mat2, mat1ref, mat2ref;
+ mat1ref = mat1 = MatrixXd::Random(6, 6);
+ mat2ref = mat2 = 2 * mat1 + MatrixXd::Identity(6, 6);
+ swap_using_evaluator(mat1, mat2);
+ mat1ref.swap(mat2ref);
+ VERIFY_IS_APPROX(mat1, mat1ref);
+ VERIFY_IS_APPROX(mat2, mat2ref);
+
+ swap_using_evaluator(mat1.block(0, 0, 3, 3), mat2.block(3, 3, 3, 3));
+ mat1ref.block(0, 0, 3, 3).swap(mat2ref.block(3, 3, 3, 3));
+ VERIFY_IS_APPROX(mat1, mat1ref);
+ VERIFY_IS_APPROX(mat2, mat2ref);
+
+ swap_using_evaluator(mat1.row(2), mat2.col(3).transpose());
+ mat1.row(2).swap(mat2.col(3).transpose());
+ VERIFY_IS_APPROX(mat1, mat1ref);
+ VERIFY_IS_APPROX(mat2, mat2ref);
+ }
+
+ {
+ // test compound assignment
+ const Matrix4d mat_const = Matrix4d::Random();
+ Matrix4d mat, mat_ref;
+ mat = mat_ref = Matrix4d::Identity();
+ add_assign_using_evaluator(mat, mat_const);
+ mat_ref += mat_const;
+ VERIFY_IS_APPROX(mat, mat_ref);
+
+ subtract_assign_using_evaluator(mat.row(1), 2*mat.row(2));
+ mat_ref.row(1) -= 2*mat_ref.row(2);
+ VERIFY_IS_APPROX(mat, mat_ref);
+
+ const ArrayXXf arr_const = ArrayXXf::Random(5,3);
+ ArrayXXf arr, arr_ref;
+ arr = arr_ref = ArrayXXf::Constant(5, 3, 0.5);
+ multiply_assign_using_evaluator(arr, arr_const);
+ arr_ref *= arr_const;
+ VERIFY_IS_APPROX(arr, arr_ref);
+
+ divide_assign_using_evaluator(arr.row(1), arr.row(2) + 1);
+ arr_ref.row(1) /= (arr_ref.row(2) + 1);
+ VERIFY_IS_APPROX(arr, arr_ref);
+ }
+}
diff --git a/resources/3rdparty/eigen/test/product_extra.cpp b/resources/3rdparty/eigen/test/product_extra.cpp
index 9a6bf0792..6f962159e 100644
--- a/resources/3rdparty/eigen/test/product_extra.cpp
+++ b/resources/3rdparty/eigen/test/product_extra.cpp
@@ -135,6 +135,35 @@ void zero_sized_objects()
a*b;
}
+void unaligned_objects()
+{
+ // Regression test for the bug reported here:
+ // http://forum.kde.org/viewtopic.php?f=74&t=107541
+ // Recall the matrix*vector kernel avoid unaligned loads by loading two packets and then reassemble then.
+ // There was a mistake in the computation of the valid range for fully unaligned objects: in some rare cases,
+ // memory was read outside the allocated matrix memory. Though the values were not used, this might raise segfault.
+ for(int m=450;m<460;++m)
+ {
+ for(int n=8;n<12;++n)
+ {
+ MatrixXf M(m, n);
+ VectorXf v1(n), r1(500);
+ RowVectorXf v2(m), r2(16);
+
+ M.setRandom();
+ v1.setRandom();
+ v2.setRandom();
+ for(int o=0; o<4; ++o)
+ {
+ r1.segment(o,m).noalias() = M * v1;
+ VERIFY_IS_APPROX(r1.segment(o,m), M * MatrixXf(v1));
+ r2.segment(o,n).noalias() = v2 * M;
+ VERIFY_IS_APPROX(r2.segment(o,n), MatrixXf(v2) * M);
+ }
+ }
+ }
+}
+
void test_product_extra()
{
for(int i = 0; i < g_repeat; i++) {
@@ -143,6 +172,7 @@ void test_product_extra()
CALL_SUBTEST_2( mat_mat_scalar_scalar_product() );
CALL_SUBTEST_3( product_extra(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
CALL_SUBTEST_4( product_extra(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
- CALL_SUBTEST_5( zero_sized_objects() );
}
+ CALL_SUBTEST_5( zero_sized_objects() );
+ CALL_SUBTEST_6( unaligned_objects() );
}
diff --git a/resources/3rdparty/eigen/test/real_qz.cpp b/resources/3rdparty/eigen/test/real_qz.cpp
new file mode 100644
index 000000000..951cf5b31
--- /dev/null
+++ b/resources/3rdparty/eigen/test/real_qz.cpp
@@ -0,0 +1,69 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Alexey Korepanov <kaikaikai@yandex.ru>
+//
+// 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/.
+
+#include "main.h"
+#include <limits>
+#include <Eigen/Eigenvalues>
+
+template<typename MatrixType> void real_qz(const MatrixType& m)
+{
+ /* this test covers the following files:
+ RealQZ.h
+ */
+
+ typedef typename MatrixType::Index Index;
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+ typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
+ typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
+ typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
+
+ Index dim = m.cols();
+
+ MatrixType A = MatrixType::Random(dim,dim),
+ B = MatrixType::Random(dim,dim);
+
+ RealQZ<MatrixType> qz(A,B);
+
+ VERIFY_IS_EQUAL(qz.info(), Success);
+ // check for zeros
+ bool all_zeros = true;
+ for (Index i=0; i<A.cols(); i++)
+ for (Index j=0; j<i; j++) {
+ if (internal::abs(qz.matrixT()(i,j))!=Scalar(0.0))
+ all_zeros = false;
+ if (j<i-1 && internal::abs(qz.matrixS()(i,j))!=Scalar(0.0))
+ all_zeros = false;
+ if (j==i-1 && j>0 && internal::abs(qz.matrixS()(i,j))!=Scalar(0.0) && internal::abs(qz.matrixS()(i-1,j-1))!=Scalar(0.0))
+ all_zeros = false;
+ }
+ VERIFY_IS_EQUAL(all_zeros, true);
+ VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixS()*qz.matrixZ(), A);
+ VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixT()*qz.matrixZ(), B);
+ VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixQ().adjoint(), MatrixType::Identity(dim,dim));
+ VERIFY_IS_APPROX(qz.matrixZ()*qz.matrixZ().adjoint(), MatrixType::Identity(dim,dim));
+}
+
+void test_real_qz()
+{
+ int s;
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1( real_qz(Matrix4f()) );
+ s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
+ CALL_SUBTEST_2( real_qz(MatrixXd(s,s)) );
+
+ // some trivial but implementation-wise tricky cases
+ CALL_SUBTEST_2( real_qz(MatrixXd(1,1)) );
+ CALL_SUBTEST_2( real_qz(MatrixXd(2,2)) );
+ CALL_SUBTEST_3( real_qz(Matrix<double,1,1>()) );
+ CALL_SUBTEST_4( real_qz(Matrix2d()) );
+ }
+
+ EIGEN_UNUSED_VARIABLE(s)
+}
diff --git a/resources/3rdparty/eigen/test/schur_complex.cpp b/resources/3rdparty/eigen/test/schur_complex.cpp
index a6f66ab02..5e869790f 100644
--- a/resources/3rdparty/eigen/test/schur_complex.cpp
+++ b/resources/3rdparty/eigen/test/schur_complex.cpp
@@ -1,7 +1,7 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// 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
@@ -47,6 +47,23 @@ template<typename MatrixType> void schur(int size = MatrixType::ColsAtCompileTim
VERIFY_IS_EQUAL(cs1.matrixT(), cs2.matrixT());
VERIFY_IS_EQUAL(cs1.matrixU(), cs2.matrixU());
+ // Test maximum number of iterations
+ ComplexSchur<MatrixType> cs3;
+ cs3.setMaxIterations(ComplexSchur<MatrixType>::m_maxIterationsPerRow * size).compute(A);
+ VERIFY_IS_EQUAL(cs3.info(), Success);
+ VERIFY_IS_EQUAL(cs3.matrixT(), cs1.matrixT());
+ VERIFY_IS_EQUAL(cs3.matrixU(), cs1.matrixU());
+ cs3.setMaxIterations(1).compute(A);
+ VERIFY_IS_EQUAL(cs3.info(), size > 1 ? NoConvergence : Success);
+ VERIFY_IS_EQUAL(cs3.getMaxIterations(), 1);
+
+ MatrixType Atriangular = A;
+ Atriangular.template triangularView<StrictlyLower>().setZero();
+ cs3.setMaxIterations(1).compute(Atriangular); // triangular matrices do not need any iterations
+ VERIFY_IS_EQUAL(cs3.info(), Success);
+ VERIFY_IS_EQUAL(cs3.matrixT(), Atriangular.template cast<ComplexScalar>());
+ VERIFY_IS_EQUAL(cs3.matrixU(), ComplexMatrixType::Identity(size, size));
+
// Test computation of only T, not U
ComplexSchur<MatrixType> csOnlyT(A, false);
VERIFY_IS_EQUAL(csOnlyT.info(), Success);
diff --git a/resources/3rdparty/eigen/test/schur_real.cpp b/resources/3rdparty/eigen/test/schur_real.cpp
index e6351d94a..36b9c24d1 100644
--- a/resources/3rdparty/eigen/test/schur_real.cpp
+++ b/resources/3rdparty/eigen/test/schur_real.cpp
@@ -1,7 +1,7 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// 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
@@ -66,6 +66,25 @@ template<typename MatrixType> void schur(int size = MatrixType::ColsAtCompileTim
VERIFY_IS_EQUAL(rs1.matrixT(), rs2.matrixT());
VERIFY_IS_EQUAL(rs1.matrixU(), rs2.matrixU());
+ // Test maximum number of iterations
+ RealSchur<MatrixType> rs3;
+ rs3.setMaxIterations(RealSchur<MatrixType>::m_maxIterationsPerRow * size).compute(A);
+ VERIFY_IS_EQUAL(rs3.info(), Success);
+ VERIFY_IS_EQUAL(rs3.matrixT(), rs1.matrixT());
+ VERIFY_IS_EQUAL(rs3.matrixU(), rs1.matrixU());
+ if (size > 2) {
+ rs3.setMaxIterations(1).compute(A);
+ VERIFY_IS_EQUAL(rs3.info(), NoConvergence);
+ VERIFY_IS_EQUAL(rs3.getMaxIterations(), 1);
+ }
+
+ MatrixType Atriangular = A;
+ Atriangular.template triangularView<StrictlyLower>().setZero();
+ rs3.setMaxIterations(1).compute(Atriangular); // triangular matrices do not need any iterations
+ VERIFY_IS_EQUAL(rs3.info(), Success);
+ VERIFY_IS_EQUAL(rs3.matrixT(), Atriangular);
+ VERIFY_IS_EQUAL(rs3.matrixU(), MatrixType::Identity(size, size));
+
// Test computation of only T, not U
RealSchur<MatrixType> rsOnlyT(A, false);
VERIFY_IS_EQUAL(rsOnlyT.info(), Success);
diff --git a/resources/3rdparty/eigen/test/sparse_basic.cpp b/resources/3rdparty/eigen/test/sparse_basic.cpp
index 8897a9dca..4566de9f2 100644
--- a/resources/3rdparty/eigen/test/sparse_basic.cpp
+++ b/resources/3rdparty/eigen/test/sparse_basic.cpp
@@ -193,6 +193,12 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// sparse cwise* dense
VERIFY_IS_APPROX(m3.cwiseProduct(refM4), refM3.cwiseProduct(refM4));
// VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
+
+ // test aliasing
+ VERIFY_IS_APPROX((m1 = -m1), (refM1 = -refM1));
+ VERIFY_IS_APPROX((m1 = m1.transpose()), (refM1 = refM1.transpose().eval()));
+ VERIFY_IS_APPROX((m1 = -m1.transpose()), (refM1 = -refM1.transpose().eval()));
+ VERIFY_IS_APPROX((m1 += -m1), (refM1 += -refM1));
}
// test transpose
@@ -379,6 +385,41 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
initSparse<Scalar>(density, refMat2, m2);
VERIFY_IS_APPROX(m2.diagonal(), refMat2.diagonal().eval());
}
+
+ // test conservative resize
+ {
+ std::vector< std::pair<int,int> > inc;
+ inc.push_back(std::pair<int,int>(-3,-2));
+ inc.push_back(std::pair<int,int>(0,0));
+ inc.push_back(std::pair<int,int>(3,2));
+ inc.push_back(std::pair<int,int>(3,0));
+ inc.push_back(std::pair<int,int>(0,3));
+
+ for(size_t i = 0; i< inc.size(); i++) {
+ int incRows = inc[i].first;
+ int incCols = inc[i].second;
+ SparseMatrixType m1(rows, cols);
+ DenseMatrix refMat1 = DenseMatrix::Zero(rows, cols);
+ initSparse<Scalar>(density, refMat1, m1);
+
+ m1.conservativeResize(rows+incRows, cols+incCols);
+ refMat1.conservativeResize(rows+incRows, cols+incCols);
+ if (incRows > 0) refMat1.bottomRows(incRows).setZero();
+ if (incCols > 0) refMat1.rightCols(incCols).setZero();
+
+ VERIFY_IS_APPROX(m1, refMat1);
+
+ // Insert new values
+ if (incRows > 0)
+ m1.insert(refMat1.rows()-1, 0) = refMat1(refMat1.rows()-1, 0) = 1;
+ if (incCols > 0)
+ m1.insert(0, refMat1.cols()-1) = refMat1(0, refMat1.cols()-1) = 1;
+
+ VERIFY_IS_APPROX(m1, refMat1);
+
+
+ }
+ }
}
void test_sparse_basic()
diff --git a/resources/3rdparty/eigen/test/sparse_solver.h b/resources/3rdparty/eigen/test/sparse_solver.h
index 75fa85082..73d92874c 100644
--- a/resources/3rdparty/eigen/test/sparse_solver.h
+++ b/resources/3rdparty/eigen/test/sparse_solver.h
@@ -158,9 +158,9 @@ inline std::string get_matrixfolder()
{
std::string mat_folder = TEST_REAL_CASES;
if( internal::is_same<Scalar, std::complex<float> >::value || internal::is_same<Scalar, std::complex<double> >::value )
- mat_folder = mat_folder + static_cast<string>("/complex/");
+ mat_folder = mat_folder + static_cast<std::string>("/complex/");
else
- mat_folder = mat_folder + static_cast<string>("/real/");
+ mat_folder = mat_folder + static_cast<std::string>("/real/");
return mat_folder;
}
#endif
diff --git a/resources/3rdparty/eigen/test/sparse_vector.cpp b/resources/3rdparty/eigen/test/sparse_vector.cpp
index 7201afe5b..9d559f5bf 100644
--- a/resources/3rdparty/eigen/test/sparse_vector.cpp
+++ b/resources/3rdparty/eigen/test/sparse_vector.cpp
@@ -78,6 +78,11 @@ template<typename Scalar> void sparse_vector(int rows, int cols)
VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm());
+ // test aliasing
+ VERIFY_IS_APPROX((v1 = -v1), (refV1 = -refV1));
+ VERIFY_IS_APPROX((v1 = v1.transpose()), (refV1 = refV1.transpose().eval()));
+ VERIFY_IS_APPROX((v1 += -v1), (refV1 += -refV1));
+
}
void test_sparse_vector()
diff --git a/resources/3rdparty/eigen/test/sparselu.cpp b/resources/3rdparty/eigen/test/sparselu.cpp
new file mode 100644
index 000000000..e960f9c93
--- /dev/null
+++ b/resources/3rdparty/eigen/test/sparselu.cpp
@@ -0,0 +1,43 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+//
+// Eigen 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 3 of the License, or (at your option) any later version.
+//
+// Alternatively, 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 2 of
+// the License, or (at your option) any later version.
+//
+// Eigen 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 or the
+// GNU General Public License for more details.
+//
+// You should have received a copy of the GNU Lesser General Public
+// License and a copy of the GNU General Public License along with
+// Eigen. If not, see <http://www.gnu.org/licenses/>.
+#include "sparse_solver.h"
+#include <Eigen/SparseLU>
+#include <unsupported/Eigen/SparseExtra>
+
+template<typename T> void test_sparselu_T()
+{
+ SparseLU<SparseMatrix<T, ColMajor>, COLAMDOrdering<int> > sparselu_colamd;
+ SparseLU<SparseMatrix<T, ColMajor>, AMDOrdering<int> > sparselu_amd;
+
+ check_sparse_square_solving(sparselu_colamd);
+ check_sparse_square_solving(sparselu_amd);
+}
+
+void test_sparselu()
+{
+ CALL_SUBTEST_1(test_sparselu_T<float>());
+ CALL_SUBTEST_2(test_sparselu_T<double>());
+ CALL_SUBTEST_3(test_sparselu_T<std::complex<float> >());
+ CALL_SUBTEST_4(test_sparselu_T<std::complex<double> >());
+}
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/IterativeSolvers b/resources/3rdparty/eigen/unsupported/Eigen/IterativeSolvers
index 6c6946d91..c3cc97cd2 100644
--- a/resources/3rdparty/eigen/unsupported/Eigen/IterativeSolvers
+++ b/resources/3rdparty/eigen/unsupported/Eigen/IterativeSolvers
@@ -33,6 +33,7 @@
#include "../../Eigen/Jacobi"
#include "../../Eigen/Householder"
#include "src/IterativeSolvers/GMRES.h"
+#include "src/IterativeSolvers/IncompleteCholesky.h"
//#include "src/IterativeSolvers/SSORPreconditioner.h"
//@}
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/MatrixFunctions b/resources/3rdparty/eigen/unsupported/Eigen/MatrixFunctions
index 56ab71cd3..1a4d42de0 100644
--- a/resources/3rdparty/eigen/unsupported/Eigen/MatrixFunctions
+++ b/resources/3rdparty/eigen/unsupported/Eigen/MatrixFunctions
@@ -2,6 +2,7 @@
// for linear algebra.
//
// Copyright (C) 2009 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
//
// 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
@@ -35,6 +36,7 @@
* - \ref matrixbase_cosh "MatrixBase::cosh()", for computing the matrix hyperbolic cosine
* - \ref matrixbase_exp "MatrixBase::exp()", for computing the matrix exponential
* - \ref matrixbase_log "MatrixBase::log()", for computing the matrix logarithm
+ * - \ref matrixbase_pow "MatrixBase::pow()", for computing the matrix power
* - \ref matrixbase_matrixfunction "MatrixBase::matrixFunction()", for computing general matrix functions
* - \ref matrixbase_sin "MatrixBase::sin()", for computing the matrix sine
* - \ref matrixbase_sinh "MatrixBase::sinh()", for computing the matrix hyperbolic sine
@@ -57,7 +59,8 @@
#include "src/MatrixFunctions/MatrixFunction.h"
#include "src/MatrixFunctions/MatrixSquareRoot.h"
#include "src/MatrixFunctions/MatrixLogarithm.h"
-
+#include "src/MatrixFunctions/MatrixPowerBase.h"
+#include "src/MatrixFunctions/MatrixPower.h"
/**
@@ -209,13 +212,76 @@ documentation of \ref matrixbase_exp "exp()".
\include MatrixLogarithm.cpp
Output: \verbinclude MatrixLogarithm.out
-\note \p M has to be a matrix of \c float, \c double, \c long double
-\c complex<float>, \c complex<double>, or \c complex<long double> .
+\note \p M has to be a matrix of \c float, \c double, <tt>long
+double</tt>, \c complex<float>, \c complex<double>, or \c complex<long
+double> .
\sa MatrixBase::exp(), MatrixBase::matrixFunction(),
class MatrixLogarithmAtomic, MatrixBase::sqrt().
+\section matrixbase_pow MatrixBase::pow()
+
+Compute the matrix raised to arbitrary real power.
+
+\code
+const MatrixPowerReturnValue<Derived> MatrixBase<Derived>::pow(RealScalar p) const
+\endcode
+
+\param[in] M base of the matrix power, should be a square matrix.
+\param[in] p exponent of the matrix power, should be real.
+
+The matrix power \f$ M^p \f$ is defined as \f$ \exp(p \log(M)) \f$,
+where exp denotes the matrix exponential, and log denotes the matrix
+logarithm.
+
+The matrix \f$ M \f$ should meet the conditions to be an argument of
+matrix logarithm. If \p p is not of the real scalar type of \p M, it
+is casted into the real scalar type of \p M.
+
+This function computes the matrix power using the Schur-Padé
+algorithm as implemented by class MatrixPower. The exponent is split
+into integral part and fractional part, where the fractional part is
+in the interval \f$ (-1, 1) \f$. The main diagonal and the first
+super-diagonal is directly computed.
+
+Details of the algorithm can be found in: Nicholas J. Higham and
+Lijing Lin, "A Schur-Padé algorithm for fractional powers of a
+matrix," <em>SIAM J. %Matrix Anal. Applic.</em>,
+<b>32(3)</b>:1056–1078, 2011.
+
+Example: The following program checks that
+\f[ \left[ \begin{array}{ccc}
+ \cos1 & -\sin1 & 0 \\
+ \sin1 & \cos1 & 0 \\
+ 0 & 0 & 1
+ \end{array} \right]^{\frac14\pi} = \left[ \begin{array}{ccc}
+ \frac12\sqrt2 & -\frac12\sqrt2 & 0 \\
+ \frac12\sqrt2 & \frac12\sqrt2 & 0 \\
+ 0 & 0 & 1
+ \end{array} \right]. \f]
+This corresponds to \f$ \frac14\pi \f$ rotations of 1 radian around
+the z-axis.
+
+\include MatrixPower.cpp
+Output: \verbinclude MatrixPower.out
+
+MatrixBase::pow() is user-friendly. However, there are some
+circumstances under which you should use class MatrixPower directly.
+MatrixPower can save the result of Schur decomposition, so it's
+better for computing various powers for the same matrix.
+
+Example:
+\include MatrixPower_optimal.cpp
+Output: \verbinclude MatrixPower_optimal.out
+
+\note \p M has to be a matrix of \c float, \c double, <tt>long
+double</tt>, \c complex<float>, \c complex<double>, or \c complex<long
+double> .
+
+\sa MatrixBase::exp(), MatrixBase::log(), class MatrixPower.
+
+
\section matrixbase_matrixfunction MatrixBase::matrixFunction()
Compute a matrix function.
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h b/resources/3rdparty/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h
new file mode 100644
index 000000000..5bc41c0f8
--- /dev/null
+++ b/resources/3rdparty/eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h
@@ -0,0 +1,221 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@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/.
+
+#ifndef EIGEN_INCOMPLETE_CHOlESKY_H
+#define EIGEN_INCOMPLETE_CHOlESKY_H
+#include "Eigen/src/IterativeLinearSolvers/IncompleteLUT.h"
+#include <Eigen/OrderingMethods>
+#include <list>
+
+namespace Eigen {
+/**
+ * \brief Modified Incomplete Cholesky with dual threshold
+ *
+ * References : C-J. Lin and J. J. Moré, Incomplete Cholesky Factorizations with
+ * Limited memory, SIAM J. Sci. Comput. 21(1), pp. 24-45, 1999
+ *
+ * \tparam _MatrixType The type of the sparse matrix. It should be a symmetric
+ * matrix. It is advised to give a row-oriented sparse matrix
+ * \tparam _UpLo The triangular part of the matrix to reference.
+ * \tparam _OrderingType
+ */
+
+template <typename Scalar, int _UpLo = Lower, typename _OrderingType = NaturalOrdering<int> >
+class IncompleteCholesky : internal::noncopyable
+{
+ public:
+ typedef SparseMatrix<Scalar,ColMajor> MatrixType;
+ typedef _OrderingType OrderingType;
+ typedef typename MatrixType::RealScalar RealScalar;
+ typedef typename MatrixType::Index Index;
+ typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+ typedef Matrix<Scalar,Dynamic,1> VectorType;
+ typedef Matrix<Index,Dynamic, 1> IndexType;
+
+ public:
+ IncompleteCholesky() {}
+ IncompleteCholesky(const MatrixType& matrix)
+ {
+ compute(matrix);
+ }
+
+ Index rows() const { return m_L.rows(); }
+
+ Index cols() const { return m_L.cols(); }
+
+
+ /** \brief Reports whether previous computation was successful.
+ *
+ * \returns \c Success if computation was succesful,
+ * \c NumericalIssue if the matrix appears to be negative.
+ */
+ ComputationInfo info() const
+ {
+ eigen_assert(m_isInitialized && "IncompleteLLT is not initialized.");
+ return m_info;
+ }
+ /**
+ * \brief Computes the fill reducing permutation vector.
+ */
+ template<typename MatrixType>
+ void analyzePattern(const MatrixType& mat)
+ {
+ OrderingType ord;
+ ord(mat, m_perm);
+ m_analysisIsOk = true;
+ }
+
+ template<typename MatrixType>
+ void factorize(const MatrixType& amat);
+
+ template<typename MatrixType>
+ void compute (const MatrixType& matrix)
+ {
+ analyzePattern(matrix);
+ factorize(matrix);
+ }
+
+ template<typename Rhs, typename Dest>
+ void _solve(const Rhs& b, Dest& x) const
+ {
+ eigen_assert(m_factorizationIsOk && "factorize() should be called first");
+ if (m_perm.rows() == b.rows())
+ x = m_perm.inverse() * b;
+ else
+ x = b;
+ x = m_L.template triangularView<UnitLower>().solve(x);
+ x = m_L.adjoint().template triangularView<Upper>().solve(x);
+ if (m_perm.rows() == b.rows())
+ x = m_perm * x;
+ }
+ template<typename Rhs> inline const internal::solve_retval<IncompleteCholesky, Rhs>
+ solve(const MatrixBase<Rhs>& b) const
+ {
+ eigen_assert(m_isInitialized && "IncompleteLLT is not initialized.");
+ eigen_assert(cols()==b.rows()
+ && "IncompleteLLT::solve(): invalid number of rows of the right hand side matrix b");
+ return internal::solve_retval<IncompleteCholesky, Rhs>(*this, b.derived());
+ }
+ protected:
+ SparseMatrix<Scalar,ColMajor> m_L; // The lower part stored in CSC
+ bool m_analysisIsOk;
+ bool m_factorizationIsOk;
+ bool m_isInitialized;
+ ComputationInfo m_info;
+ PermutationType m_perm;
+
+};
+
+template<typename Scalar, int _UpLo, typename OrderingType>
+template<typename _MatrixType>
+void IncompleteCholesky<Scalar,_UpLo, OrderingType>::factorize(const _MatrixType& mat)
+{
+ eigen_assert(m_analysisIsOk && "analyzePattern() should be called first");
+
+ // FIXME Stability: We should probably compute the scaling factors and the shifts that are needed to ensure a succesful LLT factorization and an efficient preconditioner.
+
+ // Dropping strategies : Keep only the p largest elements per column, where p is the number of elements in the column of the original matrix. Other strategies will be added
+
+ // Apply the fill-reducing permutation computed in analyzePattern()
+ if (m_perm.rows() == mat.rows() )
+ m_L.template selfadjointView<Lower>() = mat.template selfadjointView<_UpLo>().twistedBy(m_perm);
+ else
+ m_L.template selfadjointView<Lower>() = mat.template selfadjointView<_UpLo>();
+
+ int n = mat.cols();
+
+ Scalar *vals = m_L.valuePtr(); //Values
+ Index *rowIdx = m_L.innerIndexPtr(); //Row indices
+ Index *colPtr = m_L.outerIndexPtr(); // Pointer to the beginning of each row
+ VectorType firstElt(n-1); // for each j, points to the next entry in vals that will be used in the factorization
+ // Initialize firstElt;
+ for (int j = 0; j < n-1; j++) firstElt(j) = colPtr[j]+1;
+ std::vector<std::list<Index> > listCol(n); // listCol(j) is a linked list of columns to update column j
+ VectorType curCol(n); // Store a nonzero values in each column
+ VectorType irow(n); // Row indices of nonzero elements in each column
+ // jki version of the Cholesky factorization
+ for (int j=0; j < n; j++)
+ {
+ //Left-looking factorize the column j
+ // First, load the jth column into curCol
+ Scalar diag = vals[colPtr[j]]; // Lower diagonal matrix with
+ curCol.setZero();
+ irow.setLinSpaced(n,0,n-1);
+ for (int i = colPtr[j] + 1; i < colPtr[j+1]; i++)
+ {
+ curCol(rowIdx[i]) = vals[i];
+ irow(rowIdx[i]) = rowIdx[i];
+ }
+
+ std::list<int>::iterator k;
+ // Browse all previous columns that will update column j
+ for(k = listCol[j].begin(); k != listCol[j].end(); k++)
+ {
+ int jk = firstElt(*k); // First element to use in the column
+ Scalar a_jk = vals[jk];
+ diag -= a_jk * a_jk;
+ jk += 1;
+ for (int i = jk; i < colPtr[*k]; i++)
+ {
+ curCol(rowIdx[i]) -= vals[i] * a_jk ;
+ }
+ firstElt(*k) = jk;
+ if (jk < colPtr[*k+1])
+ {
+ // Add this column to the updating columns list for column *k+1
+ listCol[rowIdx[jk]].push_back(*k);
+ }
+ }
+
+ // Select the largest p elements
+ // p is the original number of elements in the column (without the diagonal)
+ int p = colPtr[j+1] - colPtr[j] - 2 ;
+ internal::QuickSplit(curCol, irow, p);
+ if(RealScalar(diag) <= 0)
+ { //FIXME We can use heuristics (Kershaw, 1978 or above reference ) to get a dynamic shift
+ m_info = NumericalIssue;
+ return;
+ }
+ RealScalar rdiag = internal::sqrt(RealScalar(diag));
+ Scalar scal = Scalar(1)/rdiag;
+ vals[colPtr[j]] = rdiag;
+ // Insert the largest p elements in the matrix and scale them meanwhile
+ int cpt = 0;
+ for (int i = colPtr[j]+1; i < colPtr[j+1]; i++)
+ {
+ vals[i] = curCol(cpt) * scal;
+ rowIdx[i] = irow(cpt);
+ cpt ++;
+ }
+ }
+ m_factorizationIsOk = true;
+ m_isInitialized = true;
+ m_info = Success;
+}
+
+namespace internal {
+
+template<typename _MatrixType, typename Rhs>
+struct solve_retval<IncompleteCholesky<_MatrixType>, Rhs>
+ : solve_retval_base<IncompleteCholesky<_MatrixType>, Rhs>
+{
+ typedef IncompleteCholesky<_MatrixType> Dec;
+ EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+ template<typename Dest> void evalTo(Dest& dst) const
+ {
+ dec()._solve(rhs(),dst);
+ }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif
\ No newline at end of file
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
index 642916764..6825a7882 100644
--- a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
+++ b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
@@ -13,12 +13,7 @@
#include "StemFunction.h"
-namespace Eigen {
-
-#if defined(_MSC_VER) || defined(__FreeBSD__)
- template <typename Scalar> Scalar log2(Scalar v) { using std::log; return log(v)/log(Scalar(2)); }
-#endif
-
+namespace Eigen {
/** \ingroup MatrixFunctions_Module
* \brief Class for computing the matrix exponential.
@@ -233,7 +228,7 @@ template <typename MatrixType>
EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade9(const MatrixType &A)
{
const RealScalar b[] = {17643225600., 8821612800., 2075673600., 302702400., 30270240.,
- 2162160., 110880., 3960., 90., 1.};
+ 2162160., 110880., 3960., 90., 1.};
MatrixType A2 = A * A;
MatrixType A4 = A2 * A2;
MatrixType A6 = A4 * A2;
@@ -247,8 +242,8 @@ template <typename MatrixType>
EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade13(const MatrixType &A)
{
const RealScalar b[] = {64764752532480000., 32382376266240000., 7771770303897600.,
- 1187353796428800., 129060195264000., 10559470521600., 670442572800.,
- 33522128640., 1323241920., 40840800., 960960., 16380., 182., 1.};
+ 1187353796428800., 129060195264000., 10559470521600., 670442572800.,
+ 33522128640., 1323241920., 40840800., 960960., 16380., 182., 1.};
MatrixType A2 = A * A;
MatrixType A4 = A2 * A2;
m_tmp1.noalias() = A4 * A2;
@@ -266,11 +261,11 @@ template <typename MatrixType>
EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade17(const MatrixType &A)
{
const RealScalar b[] = {830034394580628357120000.L, 415017197290314178560000.L,
- 100610229646136770560000.L, 15720348382208870400000.L,
- 1774878043152614400000.L, 153822763739893248000.L, 10608466464820224000.L,
- 595373117923584000.L, 27563570274240000.L, 1060137318240000.L,
- 33924394183680.L, 899510451840.L, 19554575040.L, 341863200.L, 4651200.L,
- 46512.L, 306.L, 1.L};
+ 100610229646136770560000.L, 15720348382208870400000.L,
+ 1774878043152614400000.L, 153822763739893248000.L, 10608466464820224000.L,
+ 595373117923584000.L, 27563570274240000.L, 1060137318240000.L,
+ 33924394183680.L, 899510451840.L, 19554575040.L, 341863200.L, 4651200.L,
+ 46512.L, 306.L, 1.L};
MatrixType A2 = A * A;
MatrixType A4 = A2 * A2;
MatrixType A6 = A4 * A2;
@@ -288,16 +283,16 @@ EIGEN_STRONG_INLINE void MatrixExponential<MatrixType>::pade17(const MatrixType
template <typename MatrixType>
void MatrixExponential<MatrixType>::computeUV(float)
{
- using std::max;
+ using std::frexp;
using std::pow;
- using std::ceil;
if (m_l1norm < 4.258730016922831e-001) {
pade3(m_M);
} else if (m_l1norm < 1.880152677804762e+000) {
pade5(m_M);
} else {
const float maxnorm = 3.925724783138660f;
- m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm)));
+ frexp(m_l1norm / maxnorm, &m_squarings);
+ if (m_squarings < 0) m_squarings = 0;
MatrixType A = m_M / pow(Scalar(2), m_squarings);
pade7(A);
}
@@ -306,9 +301,8 @@ void MatrixExponential<MatrixType>::computeUV(float)
template <typename MatrixType>
void MatrixExponential<MatrixType>::computeUV(double)
{
- using std::max;
+ using std::frexp;
using std::pow;
- using std::ceil;
if (m_l1norm < 1.495585217958292e-002) {
pade3(m_M);
} else if (m_l1norm < 2.539398330063230e-001) {
@@ -319,7 +313,8 @@ void MatrixExponential<MatrixType>::computeUV(double)
pade9(m_M);
} else {
const double maxnorm = 5.371920351148152;
- m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm)));
+ frexp(m_l1norm / maxnorm, &m_squarings);
+ if (m_squarings < 0) m_squarings = 0;
MatrixType A = m_M / pow(Scalar(2), m_squarings);
pade13(A);
}
@@ -328,9 +323,8 @@ void MatrixExponential<MatrixType>::computeUV(double)
template <typename MatrixType>
void MatrixExponential<MatrixType>::computeUV(long double)
{
- using std::max;
+ using std::frexp;
using std::pow;
- using std::ceil;
#if LDBL_MANT_DIG == 53 // double precision
computeUV(double());
#elif LDBL_MANT_DIG <= 64 // extended precision
@@ -344,7 +338,8 @@ void MatrixExponential<MatrixType>::computeUV(long double)
pade9(m_M);
} else {
const long double maxnorm = 4.0246098906697353063L;
- m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm)));
+ frexp(m_l1norm / maxnorm, &m_squarings);
+ if (m_squarings < 0) m_squarings = 0;
MatrixType A = m_M / pow(Scalar(2), m_squarings);
pade13(A);
}
@@ -361,7 +356,8 @@ void MatrixExponential<MatrixType>::computeUV(long double)
pade13(m_M);
} else {
const long double maxnorm = 3.2579440895405400856599663723517L;
- m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm)));
+ frexp(m_l1norm / maxnorm, &m_squarings);
+ if (m_squarings < 0) m_squarings = 0;
MatrixType A = m_M / pow(Scalar(2), m_squarings);
pade17(A);
}
@@ -378,7 +374,8 @@ void MatrixExponential<MatrixType>::computeUV(long double)
pade13(m_M);
} else {
const long double maxnorm = 2.884233277829519311757165057717815L;
- m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm)));
+ frexp(m_l1norm / maxnorm, &m_squarings);
+ if (m_squarings < 0) m_squarings = 0;
MatrixType A = m_M / pow(Scalar(2), m_squarings);
pade17(A);
}
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
index c57ca87ed..e87a28f6c 100644
--- a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
+++ b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
@@ -209,7 +209,7 @@ void MatrixFunction<MatrixType,AtomicType,1>::compute(ResultType& result)
permuteSchur();
computeBlockAtomic();
computeOffDiagonal();
- result = m_U * m_fT * m_U.adjoint();
+ result = m_U * (m_fT.template triangularView<Upper>() * m_U.adjoint());
}
/** \brief Store the Schur decomposition of #m_A in #m_T and #m_U */
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
index 3a50514b9..e1e5b770c 100644
--- a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
+++ b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
@@ -51,7 +51,6 @@ private:
void compute2x2(const MatrixType& A, MatrixType& result);
void computeBig(const MatrixType& A, MatrixType& result);
- static Scalar atanh(Scalar x);
int getPadeDegree(float normTminusI);
int getPadeDegree(double normTminusI);
int getPadeDegree(long double normTminusI);
@@ -67,10 +66,11 @@ private:
void computePade11(MatrixType& result, const MatrixType& T);
static const int minPadeDegree = 3;
- static const int maxPadeDegree = std::numeric_limits<RealScalar>::digits<= 24? 5: // single precision
- std::numeric_limits<RealScalar>::digits<= 53? 7: // double precision
- std::numeric_limits<RealScalar>::digits<= 64? 8: // extended precision
- std::numeric_limits<RealScalar>::digits<=106? 10: 11; // double-double or quadruple precision
+ static const int maxPadeDegree = std::numeric_limits<RealScalar>::digits<= 24? 5: // single precision
+ std::numeric_limits<RealScalar>::digits<= 53? 7: // double precision
+ std::numeric_limits<RealScalar>::digits<= 64? 8: // extended precision
+ std::numeric_limits<RealScalar>::digits<=106? 10: // double-double
+ 11; // quadruple precision
// Prevent copying
MatrixLogarithmAtomic(const MatrixLogarithmAtomic&);
@@ -92,18 +92,6 @@ MatrixType MatrixLogarithmAtomic<MatrixType>::compute(const MatrixType& A)
return result;
}
-/** \brief Compute atanh (inverse hyperbolic tangent). */
-template <typename MatrixType>
-typename MatrixType::Scalar MatrixLogarithmAtomic<MatrixType>::atanh(typename MatrixType::Scalar x)
-{
- using std::abs;
- using std::sqrt;
- if (abs(x) > sqrt(NumTraits<Scalar>::epsilon()))
- return Scalar(0.5) * log((Scalar(1) + x) / (Scalar(1) - x));
- else
- return x + x*x*x / Scalar(3);
-}
-
/** \brief Compute logarithm of 2x2 triangular matrix. */
template <typename MatrixType>
void MatrixLogarithmAtomic<MatrixType>::compute2x2(const MatrixType& A, MatrixType& result)
@@ -127,8 +115,8 @@ void MatrixLogarithmAtomic<MatrixType>::compute2x2(const MatrixType& A, MatrixTy
} else {
// computation in previous branch is inaccurate if A(1,1) \approx A(0,0)
int unwindingNumber = static_cast<int>(ceil((imag(logA11 - logA00) - M_PI) / (2*M_PI)));
- Scalar z = (A(1,1) - A(0,0)) / (A(1,1) + A(0,0));
- result(0,1) = A(0,1) * (Scalar(2) * atanh(z) + Scalar(0,2*M_PI*unwindingNumber)) / (A(1,1) - A(0,0));
+ Scalar y = A(1,1) - A(0,0), x = A(1,1) + A(0,0);
+ result(0,1) = A(0,1) * (Scalar(2) * internal::atanh2(y,x) + Scalar(0,2*M_PI*unwindingNumber)) / y;
}
}
@@ -172,10 +160,11 @@ int MatrixLogarithmAtomic<MatrixType>::getPadeDegree(float normTminusI)
{
const float maxNormForPade[] = { 2.5111573934555054e-1 /* degree = 3 */ , 4.0535837411880493e-1,
5.3149729967117310e-1 };
- for (int degree = 3; degree <= maxPadeDegree; ++degree)
+ int degree = 3;
+ for (; degree <= maxPadeDegree; ++degree)
if (normTminusI <= maxNormForPade[degree - minPadeDegree])
- return degree;
- assert(false); // this line should never be reached
+ break;
+ return degree;
}
/* \brief Get suitable degree for Pade approximation. (specialized for RealScalar = double) */
@@ -184,10 +173,11 @@ int MatrixLogarithmAtomic<MatrixType>::getPadeDegree(double normTminusI)
{
const double maxNormForPade[] = { 1.6206284795015624e-2 /* degree = 3 */ , 5.3873532631381171e-2,
1.1352802267628681e-1, 1.8662860613541288e-1, 2.642960831111435e-1 };
- for (int degree = 3; degree <= maxPadeDegree; ++degree)
+ int degree = 3;
+ for (; degree <= maxPadeDegree; ++degree)
if (normTminusI <= maxNormForPade[degree - minPadeDegree])
- return degree;
- assert(false); // this line should never be reached
+ break;
+ return degree;
}
/* \brief Get suitable degree for Pade approximation. (specialized for RealScalar = long double) */
@@ -195,29 +185,30 @@ template <typename MatrixType>
int MatrixLogarithmAtomic<MatrixType>::getPadeDegree(long double normTminusI)
{
#if LDBL_MANT_DIG == 53 // double precision
- const double maxNormForPade[] = { 1.6206284795015624e-2 /* degree = 3 */ , 5.3873532631381171e-2,
- 1.1352802267628681e-1, 1.8662860613541288e-1, 2.642960831111435e-1 };
+ const long double maxNormForPade[] = { 1.6206284795015624e-2L /* degree = 3 */ , 5.3873532631381171e-2L,
+ 1.1352802267628681e-1L, 1.8662860613541288e-1L, 2.642960831111435e-1L };
#elif LDBL_MANT_DIG <= 64 // extended precision
- const double maxNormForPade[] = { 5.48256690357782863103e-3 /* degree = 3 */, 2.34559162387971167321e-2,
- 5.84603923897347449857e-2, 1.08486423756725170223e-1, 1.68385767881294446649e-1,
- 2.32777776523703892094e-1 };
+ const long double maxNormForPade[] = { 5.48256690357782863103e-3L /* degree = 3 */, 2.34559162387971167321e-2L,
+ 5.84603923897347449857e-2L, 1.08486423756725170223e-1L, 1.68385767881294446649e-1L,
+ 2.32777776523703892094e-1L };
#elif LDBL_MANT_DIG <= 106 // double-double
- const double maxNormForPade[] = { 8.58970550342939562202529664318890e-5 /* degree = 3 */,
- 9.34074328446359654039446552677759e-4, 4.26117194647672175773064114582860e-3,
- 1.21546224740281848743149666560464e-2, 2.61100544998339436713088248557444e-2,
- 4.66170074627052749243018566390567e-2, 7.32585144444135027565872014932387e-2,
- 1.05026503471351080481093652651105e-1 };
+ const long double maxNormForPade[] = { 8.58970550342939562202529664318890e-5L /* degree = 3 */,
+ 9.34074328446359654039446552677759e-4L, 4.26117194647672175773064114582860e-3L,
+ 1.21546224740281848743149666560464e-2L, 2.61100544998339436713088248557444e-2L,
+ 4.66170074627052749243018566390567e-2L, 7.32585144444135027565872014932387e-2L,
+ 1.05026503471351080481093652651105e-1L };
#else // quadruple precision
- const double maxNormForPade[] = { 4.7419931187193005048501568167858103e-5 /* degree = 3 */,
- 5.8853168473544560470387769480192666e-4, 2.9216120366601315391789493628113520e-3,
- 8.8415758124319434347116734705174308e-3, 1.9850836029449446668518049562565291e-2,
- 3.6688019729653446926585242192447447e-2, 5.9290962294020186998954055264528393e-2,
- 8.6998436081634343903250580992127677e-2, 1.1880960220216759245467951592883642e-1 };
+ const long double maxNormForPade[] = { 4.7419931187193005048501568167858103e-5L /* degree = 3 */,
+ 5.8853168473544560470387769480192666e-4L, 2.9216120366601315391789493628113520e-3L,
+ 8.8415758124319434347116734705174308e-3L, 1.9850836029449446668518049562565291e-2L,
+ 3.6688019729653446926585242192447447e-2L, 5.9290962294020186998954055264528393e-2L,
+ 8.6998436081634343903250580992127677e-2L, 1.1880960220216759245467951592883642e-1L };
#endif
- for (int degree = 3; degree <= maxPadeDegree; ++degree)
+ int degree = 3;
+ for (; degree <= maxPadeDegree; ++degree)
if (normTminusI <= maxNormForPade[degree - minPadeDegree])
- return degree;
- assert(false); // this line should never be reached
+ break;
+ return degree;
}
/* \brief Compute Pade approximation to matrix logarithm */
@@ -294,10 +285,10 @@ void MatrixLogarithmAtomic<MatrixType>::computePade6(MatrixType& result, const M
const int degree = 6;
const RealScalar nodes[] = { 0.0337652428984239860938492227530027L, 0.1693953067668677431693002024900473L,
0.3806904069584015456847491391596440L, 0.6193095930415984543152508608403560L,
- 0.8306046932331322568306997975099527L, 0.9662347571015760139061507772469973L };
+ 0.8306046932331322568306997975099527L, 0.9662347571015760139061507772469973L };
const RealScalar weights[] = { 0.0856622461895851725201480710863665L, 0.1803807865240693037849167569188581L,
0.2339569672863455236949351719947755L, 0.2339569672863455236949351719947755L,
- 0.1803807865240693037849167569188581L, 0.0856622461895851725201480710863665L };
+ 0.1803807865240693037849167569188581L, 0.0856622461895851725201480710863665L };
assert(degree <= maxPadeDegree);
MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows());
result.setZero(T.rows(), T.rows());
@@ -423,8 +414,8 @@ void MatrixLogarithmAtomic<MatrixType>::computePade11(MatrixType& result, const
* This class holds the argument to the matrix function until it is
* assigned or evaluated for some other reason (so the argument
* should not be changed in the meantime). It is the return type of
- * matrixBase::matrixLogarithm() and most of the time this is the
- * only way it is used.
+ * MatrixBase::log() and most of the time this is the only way it
+ * is used.
*/
template<typename Derived> class MatrixLogarithmReturnValue
: public ReturnByValue<MatrixLogarithmReturnValue<Derived> >
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h
new file mode 100644
index 000000000..bf8bc4424
--- /dev/null
+++ b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPower.h
@@ -0,0 +1,386 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
+//
+// 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/.
+
+#ifndef EIGEN_MATRIX_POWER
+#define EIGEN_MATRIX_POWER
+
+namespace Eigen {
+
+template<typename MatrixType> class MatrixPowerEvaluator;
+
+/**
+ * \ingroup MatrixFunctions_Module
+ *
+ * \brief Class for computing matrix powers.
+ *
+ * \tparam MatrixType type of the base, expected to be an instantiation
+ * of the Matrix class template.
+ *
+ * This class is capable of computing real/complex matrices raised to
+ * an arbitrary real power. Meanwhile, it saves the result of Schur
+ * decomposition if an non-integral power has even been calculated.
+ * Therefore, if you want to compute multiple (>= 2) matrix powers
+ * for the same matrix, using the class directly is more efficient than
+ * calling MatrixBase::pow().
+ *
+ * Example:
+ * \include MatrixPower_optimal.cpp
+ * Output: \verbinclude MatrixPower_optimal.out
+ */
+template<typename MatrixType>
+class MatrixPower : public MatrixPowerBase<MatrixPower<MatrixType>,MatrixType>
+{
+ public:
+ EIGEN_MATRIX_POWER_PUBLIC_INTERFACE(MatrixPower)
+
+ /**
+ * \brief Constructor.
+ *
+ * \param[in] A the base of the matrix power.
+ *
+ * \warning Construct with a matrix, not a matrix expression!
+ */
+ explicit MatrixPower(const MatrixType& A) : Base(A,0)
+ { }
+
+ /**
+ * \brief Return the expression \f$ A^p \f$.
+ *
+ * \param[in] p exponent, a real scalar.
+ */
+ const MatrixPowerEvaluator<MatrixType> operator()(RealScalar p)
+ { return MatrixPowerEvaluator<MatrixType>(*this, p); }
+
+ /**
+ * \brief Compute the matrix power.
+ *
+ * \param[in] p exponent, a real scalar.
+ * \param[out] res \f$ A^p \f$ where A is specified in the
+ * constructor.
+ */
+ void compute(MatrixType& res, RealScalar p);
+
+ /**
+ * \brief Compute the matrix power multiplied by another matrix.
+ *
+ * \param[in] b a matrix with the same rows as A.
+ * \param[in] p exponent, a real scalar.
+ * \param[out] res \f$ A^p b \f$, where A is specified in the
+ * constructor.
+ */
+ template<typename Derived, typename ResultType>
+ void compute(const Derived& b, ResultType& res, RealScalar p);
+
+ private:
+ EIGEN_MATRIX_POWER_PROTECTED_MEMBERS(MatrixPower)
+
+ typedef Matrix<std::complex<RealScalar>, RowsAtCompileTime, ColsAtCompileTime,
+ Options,MaxRowsAtCompileTime,MaxColsAtCompileTime> ComplexMatrix;
+ ComplexMatrix m_T, m_U, m_fT;
+
+ RealScalar modfAndInit(RealScalar, RealScalar*);
+
+ template<typename Derived, typename ResultType>
+ void apply(const Derived&, ResultType&, bool&);
+
+ template<typename ResultType>
+ void computeIntPower(ResultType&, RealScalar);
+
+ template<typename Derived, typename ResultType>
+ void computeIntPower(const Derived&, ResultType&, RealScalar);
+
+ template<typename ResultType>
+ void computeFracPower(ResultType&, RealScalar);
+};
+
+template<typename MatrixType>
+void MatrixPower<MatrixType>::compute(MatrixType& res, RealScalar p)
+{
+ switch (m_A.cols()) {
+ case 0:
+ break;
+ case 1:
+ res(0,0) = std::pow(m_A.coeff(0,0), p);
+ break;
+ default:
+ RealScalar intpart, x = modfAndInit(p, &intpart);
+ res = m_Id;
+ computeIntPower(res, intpart);
+ computeFracPower(res, x);
+ }
+}
+
+template<typename MatrixType>
+template<typename Derived, typename ResultType>
+void MatrixPower<MatrixType>::compute(const Derived& b, ResultType& res, RealScalar p)
+{
+ switch (m_A.cols()) {
+ case 0:
+ break;
+ case 1:
+ res = std::pow(m_A.coeff(0,0), p) * b;
+ break;
+ default:
+ RealScalar intpart, x = modfAndInit(p, &intpart);
+ computeIntPower(b, res, intpart);
+ computeFracPower(res, x);
+ }
+}
+
+template<typename MatrixType>
+typename MatrixPower<MatrixType>::Base::RealScalar MatrixPower<MatrixType>::modfAndInit(RealScalar x, RealScalar* intpart)
+{
+ *intpart = std::floor(x);
+ RealScalar res = x - *intpart;
+
+ if (!m_conditionNumber && res) {
+ const ComplexSchur<MatrixType> schurOfA(m_A);
+ m_T = schurOfA.matrixT();
+ m_U = schurOfA.matrixU();
+
+ const RealArray absTdiag = m_T.diagonal().array().abs();
+ m_conditionNumber = absTdiag.maxCoeff() / absTdiag.minCoeff();
+ }
+
+ if (res>RealScalar(0.5) && res>(1-res)*std::pow(m_conditionNumber, res)) {
+ --res;
+ ++*intpart;
+ }
+ return res;
+}
+
+template<typename MatrixType>
+template<typename Derived, typename ResultType>
+void MatrixPower<MatrixType>::apply(const Derived& b, ResultType& res, bool& init)
+{
+ if (init)
+ res = m_tmp1 * res;
+ else {
+ init = true;
+ res.noalias() = m_tmp1 * b;
+ }
+}
+
+template<typename MatrixType>
+template<typename ResultType>
+void MatrixPower<MatrixType>::computeIntPower(ResultType& res, RealScalar p)
+{
+ RealScalar pp = std::abs(p);
+
+ if (p<0) m_tmp1 = m_A.inverse();
+ else m_tmp1 = m_A;
+
+ while (pp >= 1) {
+ if (std::fmod(pp, 2) >= 1)
+ res = m_tmp1 * res;
+ m_tmp1 *= m_tmp1;
+ pp /= 2;
+ }
+}
+
+template<typename MatrixType>
+template<typename Derived, typename ResultType>
+void MatrixPower<MatrixType>::computeIntPower(const Derived& b, ResultType& res, RealScalar p)
+{
+ if (b.cols() >= m_A.cols()) {
+ m_tmp2 = m_Id;
+ computeIntPower(m_tmp2, p);
+ res.noalias() = m_tmp2 * b;
+ }
+ else {
+ RealScalar pp = std::abs(p);
+ int squarings, applyings = internal::binary_powering_cost(pp, &squarings);
+ bool init = false;
+
+ if (p==0) {
+ res = b;
+ return;
+ }
+ else if (p>0) {
+ m_tmp1 = m_A;
+ }
+ else if (m_A.cols() > 2 && b.cols()*(pp-applyings) <= m_A.cols()*squarings) {
+ PartialPivLU<MatrixType> A(m_A);
+ res = A.solve(b);
+ for (--pp; pp >= 1; --pp)
+ res = A.solve(res);
+ return;
+ }
+ else {
+ m_tmp1 = m_A.inverse();
+ }
+
+ while (b.cols()*(pp-applyings) > m_A.cols()*squarings) {
+ if (std::fmod(pp, 2) >= 1) {
+ apply(b, res, init);
+ --applyings;
+ }
+ m_tmp1 *= m_tmp1;
+ --squarings;
+ pp /= 2;
+ }
+ for (; pp >= 1; --pp)
+ apply(b, res, init);
+ }
+}
+
+template<typename MatrixType>
+template<typename ResultType>
+void MatrixPower<MatrixType>::computeFracPower(ResultType& res, RealScalar p)
+{
+ if (p) {
+ eigen_assert(m_conditionNumber);
+ MatrixPowerTriangularAtomic<ComplexMatrix>(m_T).compute(m_fT, p);
+ internal::recompose_complex_schur<NumTraits<Scalar>::IsComplex>::run(m_tmp1, m_fT, m_U);
+ res = m_tmp1 * res;
+ }
+}
+
+template<typename Lhs, typename Rhs>
+class MatrixPowerMatrixProduct : public MatrixPowerProductBase<MatrixPowerMatrixProduct<Lhs,Rhs>,Lhs,Rhs>
+{
+ public:
+ EIGEN_MATRIX_POWER_PRODUCT_PUBLIC_INTERFACE(MatrixPowerMatrixProduct)
+
+ MatrixPowerMatrixProduct(MatrixPower<Lhs>& pow, const Rhs& b, RealScalar p) :
+ m_pow(pow),
+ m_b(b),
+ m_p(p)
+ { }
+
+ template<typename ResultType>
+ inline void evalTo(ResultType& res) const
+ { m_pow.compute(m_b, res, m_p); }
+
+ Index rows() const { return m_pow.rows(); }
+ Index cols() const { return m_b.cols(); }
+
+ private:
+ MatrixPower<Lhs>& m_pow;
+ const Rhs& m_b;
+ const RealScalar m_p;
+ MatrixPowerMatrixProduct& operator=(const MatrixPowerMatrixProduct&);
+};
+
+/**
+ * \ingroup MatrixFunctions_Module
+ *
+ * \brief Proxy for the matrix power of some matrix (expression).
+ *
+ * \tparam Derived type of the base, a matrix (expression).
+ *
+ * This class holds the arguments to the matrix power until it is
+ * assigned or evaluated for some other reason (so the argument
+ * should not be changed in the meantime). It is the return type of
+ * MatrixBase::pow() and related functions and most of the
+ * time this is the only way it is used.
+ */
+template<typename Derived>
+class MatrixPowerReturnValue : public ReturnByValue<MatrixPowerReturnValue<Derived> >
+{
+ public:
+ typedef typename Derived::PlainObject PlainObject;
+ typedef typename Derived::RealScalar RealScalar;
+ typedef typename Derived::Index Index;
+
+ /**
+ * \brief Constructor.
+ *
+ * \param[in] A %Matrix (expression), the base of the matrix power.
+ * \param[in] p scalar, the exponent of the matrix power.
+ */
+ MatrixPowerReturnValue(const Derived& A, RealScalar p) : m_A(A), m_p(p)
+ { }
+
+ /**
+ * \brief Compute the matrix power.
+ *
+ * \param[out] result \f$ A^p \f$ where \p A and \p p are as in the
+ * constructor.
+ */
+ template<typename ResultType>
+ inline void evalTo(ResultType& res) const
+ { MatrixPower<PlainObject>(m_A.eval()).compute(res, m_p); }
+
+ /**
+ * \brief Return the expression \f$ A^p b \f$.
+ *
+ * \p A and \p p are specified in the constructor.
+ *
+ * \param[in] b the matrix (expression) to be applied.
+ */
+ template<typename OtherDerived>
+ const MatrixPowerMatrixProduct<PlainObject,OtherDerived> operator*(const MatrixBase<OtherDerived>& b) const
+ {
+ MatrixPower<PlainObject> Apow(m_A.eval());
+ return MatrixPowerMatrixProduct<PlainObject,OtherDerived>(Apow, b.derived(), m_p);
+ }
+
+ Index rows() const { return m_A.rows(); }
+ Index cols() const { return m_A.cols(); }
+
+ private:
+ const Derived& m_A;
+ const RealScalar m_p;
+ MatrixPowerReturnValue& operator=(const MatrixPowerReturnValue&);
+};
+
+template<typename MatrixType>
+class MatrixPowerEvaluator : public ReturnByValue<MatrixPowerEvaluator<MatrixType> >
+{
+ public:
+ typedef typename MatrixType::RealScalar RealScalar;
+ typedef typename MatrixType::Index Index;
+
+ MatrixPowerEvaluator(MatrixPower<MatrixType>& pow, RealScalar p) : m_pow(pow), m_p(p)
+ { }
+
+ template<typename ResultType>
+ inline void evalTo(ResultType& res) const
+ { m_pow.compute(res, m_p); }
+
+ template<typename Derived>
+ const MatrixPowerMatrixProduct<MatrixType,Derived> operator*(const MatrixBase<Derived>& b) const
+ { return MatrixPowerMatrixProduct<MatrixType,Derived>(m_pow, b.derived(), m_p); }
+
+ Index rows() const { return m_pow.rows(); }
+ Index cols() const { return m_pow.cols(); }
+
+ private:
+ MatrixPower<MatrixType>& m_pow;
+ const RealScalar m_p;
+ MatrixPowerEvaluator& operator=(const MatrixPowerEvaluator&);
+};
+
+namespace internal {
+template<typename Lhs, typename Rhs>
+struct nested<MatrixPowerMatrixProduct<Lhs,Rhs> >
+{ typedef typename MatrixPowerMatrixProduct<Lhs,Rhs>::PlainObject const& type; };
+
+template<typename Derived>
+struct traits<MatrixPowerReturnValue<Derived> >
+{ typedef typename Derived::PlainObject ReturnType; };
+
+template<typename MatrixType>
+struct traits<MatrixPowerEvaluator<MatrixType> >
+{ typedef MatrixType ReturnType; };
+
+template<typename Lhs, typename Rhs>
+struct traits<MatrixPowerMatrixProduct<Lhs,Rhs> >
+: traits<MatrixPowerProductBase<MatrixPowerMatrixProduct<Lhs,Rhs>,Lhs,Rhs> >
+{ };
+} // namespace internal
+
+template<typename Derived>
+const MatrixPowerReturnValue<Derived> MatrixBase<Derived>::pow(RealScalar p) const
+{ return MatrixPowerReturnValue<Derived>(derived(), p); }
+
+} // namespace Eigen
+
+#endif // EIGEN_MATRIX_POWER
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPowerBase.h b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPowerBase.h
new file mode 100644
index 000000000..9616659ca
--- /dev/null
+++ b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixPowerBase.h
@@ -0,0 +1,359 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
+//
+// 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/.
+
+#ifndef EIGEN_MATRIX_POWER_BASE
+#define EIGEN_MATRIX_POWER_BASE
+
+namespace Eigen {
+
+namespace internal {
+template<int IsComplex>
+struct recompose_complex_schur
+{
+ template<typename ResultType, typename MatrixType>
+ static inline void run(ResultType& res, const MatrixType& T, const MatrixType& U)
+ { res.noalias() = U * (T.template triangularView<Upper>() * U.adjoint()); }
+};
+
+template<>
+struct recompose_complex_schur<0>
+{
+ template<typename ResultType, typename MatrixType>
+ static inline void run(ResultType& res, const MatrixType& T, const MatrixType& U)
+ { res.noalias() = (U * (T.template triangularView<Upper>() * U.adjoint())).real(); }
+};
+
+template<typename Scalar, int IsComplex=NumTraits<Scalar>::IsComplex>
+struct matrix_power_unwinder
+{
+ static inline Scalar run(const Scalar& eival, const Scalar& eival0, int unwindingNumber)
+ { return internal::atanh2(eival-eival0, eival+eival0) + Scalar(0, M_PI*unwindingNumber); }
+};
+
+template<typename Scalar>
+struct matrix_power_unwinder<Scalar,0>
+{
+ static inline Scalar run(Scalar eival, Scalar eival0, int)
+ { return internal::atanh2(eival-eival0, eival+eival0); }
+};
+
+template<typename T>
+inline int binary_powering_cost(T p, int* squarings)
+{
+ int applyings=0, tmp;
+
+ frexp(p, squarings);
+ --*squarings;
+
+ while (std::frexp(p, &tmp), tmp > 0) {
+ p -= std::ldexp(static_cast<T>(0.5), tmp);
+ ++applyings;
+ }
+ return applyings;
+}
+
+inline int matrix_power_get_pade_degree(float normIminusT)
+{
+ const float maxNormForPade[] = { 2.8064004e-1f /* degree = 3 */ , 4.3386528e-1f };
+ int degree = 3;
+ for (; degree <= 4; ++degree)
+ if (normIminusT <= maxNormForPade[degree - 3])
+ break;
+ return degree;
+}
+
+inline int matrix_power_get_pade_degree(double normIminusT)
+{
+ const double maxNormForPade[] = { 1.884160592658218e-2 /* degree = 3 */ , 6.038881904059573e-2, 1.239917516308172e-1,
+ 1.999045567181744e-1, 2.789358995219730e-1 };
+ int degree = 3;
+ for (; degree <= 7; ++degree)
+ if (normIminusT <= maxNormForPade[degree - 3])
+ break;
+ return degree;
+}
+
+inline int matrix_power_get_pade_degree(long double normIminusT)
+{
+#if LDBL_MANT_DIG == 53
+ const int maxPadeDegree = 7;
+ const double maxNormForPade[] = { 1.884160592658218e-2L /* degree = 3 */ , 6.038881904059573e-2L, 1.239917516308172e-1L,
+ 1.999045567181744e-1L, 2.789358995219730e-1L };
+#elif LDBL_MANT_DIG <= 64
+ const int maxPadeDegree = 8;
+ const double maxNormForPade[] = { 6.3854693117491799460e-3L /* degree = 3 */ , 2.6394893435456973676e-2L,
+ 6.4216043030404063729e-2L, 1.1701165502926694307e-1L, 1.7904284231268670284e-1L, 2.4471944416607995472e-1L };
+#elif LDBL_MANT_DIG <= 106
+ const int maxPadeDegree = 10;
+ const double maxNormForPade[] = { 1.0007161601787493236741409687186e-4L /* degree = 3 */ ,
+ 1.0007161601787493236741409687186e-3L, 4.7069769360887572939882574746264e-3L, 1.3220386624169159689406653101695e-2L,
+ 2.8063482381631737920612944054906e-2L, 4.9625993951953473052385361085058e-2L, 7.7367040706027886224557538328171e-2L,
+ 1.1016843812851143391275867258512e-1L };
+#else
+ const int maxPadeDegree = 10;
+ const double maxNormForPade[] = { 5.524506147036624377378713555116378e-5L /* degree = 3 */ ,
+ 6.640600568157479679823602193345995e-4L, 3.227716520106894279249709728084626e-3L,
+ 9.619593944683432960546978734646284e-3L, 2.134595382433742403911124458161147e-2L,
+ 3.908166513900489428442993794761185e-2L, 6.266780814639442865832535460550138e-2L,
+ 9.134603732914548552537150753385375e-2L };
+#endif
+ int degree = 3;
+ for (; degree <= maxPadeDegree; ++degree)
+ if (normIminusT <= maxNormForPade[degree - 3])
+ break;
+ return degree;
+}
+} // namespace internal
+
+template<typename MatrixType>
+class MatrixPowerTriangularAtomic
+{
+ private:
+ enum {
+ RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+ MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime
+ };
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename MatrixType::RealScalar RealScalar;
+ typedef Array<Scalar,RowsAtCompileTime,1,ColMajor,MaxRowsAtCompileTime> ArrayType;
+
+ const MatrixType& m_T;
+ const MatrixType m_Id;
+
+ void computePade(int degree, const MatrixType& IminusT, MatrixType& res, RealScalar p) const;
+ void compute2x2(MatrixType& res, RealScalar p) const;
+ void computeBig(MatrixType& res, RealScalar p) const;
+
+ public:
+ explicit MatrixPowerTriangularAtomic(const MatrixType& T);
+ void compute(MatrixType& res, RealScalar p) const;
+};
+
+template<typename MatrixType>
+MatrixPowerTriangularAtomic<MatrixType>::MatrixPowerTriangularAtomic(const MatrixType& T) :
+ m_T(T),
+ m_Id(MatrixType::Identity(T.rows(), T.cols()))
+{ eigen_assert(T.rows() == T.cols()); }
+
+template<typename MatrixType>
+void MatrixPowerTriangularAtomic<MatrixType>::compute(MatrixType& res, RealScalar p) const
+{
+ switch (m_T.rows()) {
+ case 0:
+ break;
+ case 1:
+ res(0,0) = std::pow(m_T(0,0), p);
+ break;
+ case 2:
+ compute2x2(res, p);
+ break;
+ default:
+ computeBig(res, p);
+ }
+}
+
+template<typename MatrixType>
+void MatrixPowerTriangularAtomic<MatrixType>::computePade(int degree, const MatrixType& IminusT, MatrixType& res,
+ RealScalar p) const
+{
+ int i = degree<<1;
+ res = (p-degree) / ((i-1)<<1) * IminusT;
+ for (--i; i; --i) {
+ res = (m_Id + res).template triangularView<Upper>().solve((i==1 ? -p : i&1 ? (-p-(i>>1))/(i<<1) :
+ (p-(i>>1))/((i-1)<<1)) * IminusT).eval();
+ }
+ res += m_Id;
+}
+
+template<typename MatrixType>
+void MatrixPowerTriangularAtomic<MatrixType>::compute2x2(MatrixType& res, RealScalar p) const
+{
+ using std::abs;
+ using std::pow;
+
+ ArrayType logTdiag = m_T.diagonal().array().log();
+ res.coeffRef(0,0) = pow(m_T.coeff(0,0), p);
+
+ for (int i=1; i < m_T.cols(); ++i) {
+ res.coeffRef(i,i) = pow(m_T.coeff(i,i), p);
+ if (m_T.coeff(i-1,i-1) == m_T.coeff(i,i)) {
+ res.coeffRef(i-1,i) = p * pow(m_T.coeff(i-1,i), p-1);
+ }
+ else if (2*abs(m_T.coeff(i-1,i-1)) < abs(m_T.coeff(i,i)) || 2*abs(m_T.coeff(i,i)) < abs(m_T.coeff(i-1,i-1))) {
+ res.coeffRef(i-1,i) = m_T.coeff(i-1,i) * (res.coeff(i,i)-res.coeff(i-1,i-1)) / (m_T.coeff(i,i)-m_T.coeff(i-1,i-1));
+ }
+ else {
+ int unwindingNumber = std::ceil((internal::imag(logTdiag[i]-logTdiag[i-1]) - M_PI) / (2*M_PI));
+ Scalar w = internal::matrix_power_unwinder<Scalar>::run(m_T.coeff(i,i), m_T.coeff(i-1,i-1), unwindingNumber);
+ res.coeffRef(i-1,i) = m_T.coeff(i-1,i) * RealScalar(2) * std::exp(RealScalar(0.5)*p*(logTdiag[i]+logTdiag[i-1])) *
+ std::sinh(p * w) / (m_T.coeff(i,i) - m_T.coeff(i-1,i-1));
+ }
+ }
+}
+
+template<typename MatrixType>
+void MatrixPowerTriangularAtomic<MatrixType>::computeBig(MatrixType& res, RealScalar p) const
+{
+ const int digits = std::numeric_limits<RealScalar>::digits;
+ const RealScalar maxNormForPade = digits <= 24? 4.3386528e-1f: // sigle precision
+ digits <= 53? 2.789358995219730e-1: // double precision
+ digits <= 64? 2.4471944416607995472e-1L: // extended precision
+ digits <= 106? 1.1016843812851143391275867258512e-1L: // double-double
+ 9.134603732914548552537150753385375e-2L; // quadruple precision
+ MatrixType IminusT, sqrtT, T=m_T;
+ RealScalar normIminusT;
+ int degree, degree2, numberOfSquareRoots=0;
+ bool hasExtraSquareRoot=false;
+
+ while (true) {
+ IminusT = MatrixType::Identity(m_T.rows(), m_T.cols()) - T;
+ normIminusT = IminusT.cwiseAbs().colwise().sum().maxCoeff();
+ if (normIminusT < maxNormForPade) {
+ degree = internal::matrix_power_get_pade_degree(normIminusT);
+ degree2 = internal::matrix_power_get_pade_degree(normIminusT/2);
+ if (degree - degree2 <= 1 || hasExtraSquareRoot)
+ break;
+ hasExtraSquareRoot = true;
+ }
+ MatrixSquareRootTriangular<MatrixType>(T).compute(sqrtT);
+ T = sqrtT;
+ ++numberOfSquareRoots;
+ }
+ computePade(degree, IminusT, res, p);
+
+ for (; numberOfSquareRoots; --numberOfSquareRoots) {
+ compute2x2(res, std::ldexp(p,-numberOfSquareRoots));
+ res *= res;
+ }
+ compute2x2(res, p);
+}
+
+#define EIGEN_MATRIX_POWER_PUBLIC_INTERFACE(Derived) \
+ typedef MatrixPowerBase<Derived, MatrixType> Base; \
+ using Base::RowsAtCompileTime; \
+ using Base::ColsAtCompileTime; \
+ using Base::Options; \
+ using Base::MaxRowsAtCompileTime; \
+ using Base::MaxColsAtCompileTime; \
+ typedef typename Base::Scalar Scalar; \
+ typedef typename Base::RealScalar RealScalar; \
+ typedef typename Base::RealArray RealArray;
+
+#define EIGEN_MATRIX_POWER_PROTECTED_MEMBERS(Derived) \
+ using Base::m_A; \
+ using Base::m_Id; \
+ using Base::m_tmp1; \
+ using Base::m_tmp2; \
+ using Base::m_conditionNumber;
+
+#define EIGEN_MATRIX_POWER_PRODUCT_PUBLIC_INTERFACE(Derived) \
+ typedef MatrixPowerProductBase<Derived, Lhs, Rhs> Base; \
+ EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
+
+namespace internal {
+template<typename Derived, typename _Lhs, typename _Rhs>
+struct traits<MatrixPowerProductBase<Derived,_Lhs,_Rhs> >
+{
+ typedef MatrixXpr XprKind;
+ typedef typename remove_all<_Lhs>::type Lhs;
+ typedef typename remove_all<_Rhs>::type Rhs;
+ typedef typename remove_all<Derived>::type PlainObject;
+ typedef typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
+ typedef typename promote_storage_type<typename traits<Lhs>::StorageKind,
+ typename traits<Rhs>::StorageKind>::ret StorageKind;
+ typedef typename promote_index_type<typename traits<Lhs>::Index,
+ typename traits<Rhs>::Index>::type Index;
+
+ enum {
+ RowsAtCompileTime = traits<Lhs>::RowsAtCompileTime,
+ ColsAtCompileTime = traits<Rhs>::ColsAtCompileTime,
+ MaxRowsAtCompileTime = traits<Lhs>::MaxRowsAtCompileTime,
+ MaxColsAtCompileTime = traits<Rhs>::MaxColsAtCompileTime,
+ Flags = (MaxRowsAtCompileTime==1 ? RowMajorBit : 0)
+ | EvalBeforeNestingBit | EvalBeforeAssigningBit | NestByRefBit,
+ CoeffReadCost = 0
+ };
+};
+} // namespace internal
+
+template<typename Derived, typename MatrixType>
+class MatrixPowerBase
+{
+ public:
+ enum {
+ RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+ ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+ Options = MatrixType::Options,
+ MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+ MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+ };
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename MatrixType::RealScalar RealScalar;
+ typedef typename MatrixType::Index Index;
+
+ explicit MatrixPowerBase(const MatrixType& A, RealScalar cond);
+
+ void compute(MatrixType& res, RealScalar p);
+
+ template<typename OtherDerived, typename ResultType>
+ void compute(const OtherDerived& b, ResultType& res, RealScalar p);
+
+ Index rows() const { return m_A.rows(); }
+ Index cols() const { return m_A.cols(); }
+
+ protected:
+ typedef Array<RealScalar,RowsAtCompileTime,1,ColMajor,MaxRowsAtCompileTime> RealArray;
+
+ const MatrixType& m_A;
+ const MatrixType m_Id;
+ MatrixType m_tmp1, m_tmp2;
+ RealScalar m_conditionNumber;
+};
+
+template<typename Derived, typename MatrixType>
+MatrixPowerBase<Derived,MatrixType>::MatrixPowerBase(const MatrixType& A, RealScalar cond) :
+ m_A(A),
+ m_Id(MatrixType::Identity(A.rows(),A.cols())),
+ m_conditionNumber(cond)
+{ eigen_assert(A.rows() == A.cols()); }
+
+template<typename Derived, typename MatrixType>
+void MatrixPowerBase<Derived,MatrixType>::compute(MatrixType& res, RealScalar p)
+{ static_cast<Derived*>(this)->compute(res,p); }
+
+template<typename Derived, typename MatrixType>
+template<typename OtherDerived, typename ResultType>
+void MatrixPowerBase<Derived,MatrixType>::compute(const OtherDerived& b, ResultType& res, RealScalar p)
+{ static_cast<Derived*>(this)->compute(b,res,p); }
+
+template<typename Derived, typename Lhs, typename Rhs>
+class MatrixPowerProductBase : public MatrixBase<Derived>
+{
+ public:
+ typedef MatrixBase<Derived> Base;
+ EIGEN_DENSE_PUBLIC_INTERFACE(MatrixPowerProductBase)
+
+ inline Index rows() const { return derived().rows(); }
+ inline Index cols() const { return derived().cols(); }
+
+ template<typename ResultType>
+ inline void evalTo(ResultType& res) const { derived().evalTo(res); }
+};
+
+template<typename Derived>
+template<typename ProductDerived, typename Lhs, typename Rhs>
+Derived& MatrixBase<Derived>::lazyAssign(const MatrixPowerProductBase<ProductDerived,Lhs,Rhs>& other)
+{
+ other.derived().evalTo(derived());
+ return derived();
+}
+
+} // namespace Eigen
+
+#endif // EIGEN_MATRIX_POWER
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h
index 10319fa17..3786510c0 100644
--- a/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h
+++ b/resources/3rdparty/eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h
@@ -60,17 +60,17 @@ class MatrixSquareRootQuasiTriangular
void computeOffDiagonalPartOfSqrt(MatrixType& sqrtT, const MatrixType& T);
void compute2x2diagonalBlock(MatrixType& sqrtT, const MatrixType& T, typename MatrixType::Index i);
void compute1x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T,
- typename MatrixType::Index i, typename MatrixType::Index j);
+ typename MatrixType::Index i, typename MatrixType::Index j);
void compute1x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T,
- typename MatrixType::Index i, typename MatrixType::Index j);
+ typename MatrixType::Index i, typename MatrixType::Index j);
void compute2x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T,
- typename MatrixType::Index i, typename MatrixType::Index j);
+ typename MatrixType::Index i, typename MatrixType::Index j);
void compute2x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T,
- typename MatrixType::Index i, typename MatrixType::Index j);
+ typename MatrixType::Index i, typename MatrixType::Index j);
template <typename SmallMatrixType>
static void solveAuxiliaryEquation(SmallMatrixType& X, const SmallMatrixType& A,
- const SmallMatrixType& B, const SmallMatrixType& C);
+ const SmallMatrixType& B, const SmallMatrixType& C);
const MatrixType& m_A;
};
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h b/resources/3rdparty/eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h
index 4716b68e7..bf13cf21f 100644
--- a/resources/3rdparty/eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h
+++ b/resources/3rdparty/eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h
@@ -184,9 +184,20 @@ class MatrixMarketIterator
// if (S_ISDIR(st_buf.st_mode)) continue;
// Determine from the header if it is a matrix or a right hand side
- bool isvector,iscomplex;
+ bool isvector,iscomplex=false;
if(!getMarketHeader(curfile,m_sym,iscomplex,isvector)) continue;
if(isvector) continue;
+ if (!iscomplex)
+ {
+ if(internal::is_same<Scalar, std::complex<float> >::value || internal::is_same<Scalar, std::complex<double> >::value)
+ continue;
+ }
+ if (iscomplex)
+ {
+ if(internal::is_same<Scalar, float>::value || internal::is_same<Scalar, double>::value)
+ continue;
+ }
+
// Get the matrix name
std::string filename = m_curs_id->d_name;
diff --git a/resources/3rdparty/eigen/unsupported/Eigen/src/Splines/Spline.h b/resources/3rdparty/eigen/unsupported/Eigen/src/Splines/Spline.h
index 3680f013a..74048834a 100644
--- a/resources/3rdparty/eigen/unsupported/Eigen/src/Splines/Spline.h
+++ b/resources/3rdparty/eigen/unsupported/Eigen/src/Splines/Spline.h
@@ -50,6 +50,21 @@ namespace Eigen
/** \brief The data type representing the spline's control points. */
typedef typename SplineTraits<Spline>::ControlPointVectorType ControlPointVectorType;
+
+ /**
+ * \brief Creates a (constant) zero spline.
+ * For Splines with dynamic degree, the resulting degree will be 0.
+ **/
+ Spline()
+ : m_knots(1, (Degree==Dynamic ? 2 : 2*Degree+2))
+ , m_ctrls(ControlPointVectorType::Zero(2,(Degree==Dynamic ? 1 : Degree+1)))
+ {
+ // in theory this code can go to the initializer list but it will get pretty
+ // much unreadable ...
+ enum { MinDegree = (Degree==Dynamic ? 0 : Degree) };
+ m_knots.template segment<MinDegree+1>(0) = Array<Scalar,1,MinDegree+1>::Zero();
+ m_knots.template segment<MinDegree+1>(MinDegree+1) = Array<Scalar,1,MinDegree+1>::Ones();
+ }
/**
* \brief Creates a spline from a knot vector and control points.
diff --git a/resources/3rdparty/eigen/unsupported/doc/examples/MatrixPower.cpp b/resources/3rdparty/eigen/unsupported/doc/examples/MatrixPower.cpp
new file mode 100644
index 000000000..222452476
--- /dev/null
+++ b/resources/3rdparty/eigen/unsupported/doc/examples/MatrixPower.cpp
@@ -0,0 +1,16 @@
+#include <unsupported/Eigen/MatrixFunctions>
+#include <iostream>
+
+using namespace Eigen;
+
+int main()
+{
+ const double pi = std::acos(-1.0);
+ Matrix3d A;
+ A << cos(1), -sin(1), 0,
+ sin(1), cos(1), 0,
+ 0 , 0 , 1;
+ std::cout << "The matrix A is:\n" << A << "\n\n"
+ "The matrix power A^(pi/4) is:\n" << A.pow(pi/4) << std::endl;
+ return 0;
+}
diff --git a/resources/3rdparty/eigen/unsupported/doc/examples/MatrixPower_optimal.cpp b/resources/3rdparty/eigen/unsupported/doc/examples/MatrixPower_optimal.cpp
new file mode 100644
index 000000000..86470ba0a
--- /dev/null
+++ b/resources/3rdparty/eigen/unsupported/doc/examples/MatrixPower_optimal.cpp
@@ -0,0 +1,17 @@
+#include <unsupported/Eigen/MatrixFunctions>
+#include <iostream>
+
+using namespace Eigen;
+
+int main()
+{
+ Matrix4cd A = Matrix4cd::Random();
+ MatrixPower<Matrix4cd> Apow(A);
+
+ std::cout << "The matrix A is:\n" << A << "\n\n"
+ "A^3.1 is:\n" << Apow(3.1) << "\n\n"
+ "A^3.3 is:\n" << Apow(3.3) << "\n\n"
+ "A^3.7 is:\n" << Apow(3.7) << "\n\n"
+ "A^3.9 is:\n" << Apow(3.9) << std::endl;
+ return 0;
+}
diff --git a/resources/3rdparty/eigen/unsupported/test/CMakeLists.txt b/resources/3rdparty/eigen/unsupported/test/CMakeLists.txt
index b34b151b1..ff0137ec6 100644
--- a/resources/3rdparty/eigen/unsupported/test/CMakeLists.txt
+++ b/resources/3rdparty/eigen/unsupported/test/CMakeLists.txt
@@ -33,6 +33,7 @@ endif()
ei_add_test(matrix_exponential)
ei_add_test(matrix_function)
+ei_add_test(matrix_power)
ei_add_test(matrix_square_root)
ei_add_test(alignedvector3)
ei_add_test(FFT)
diff --git a/resources/3rdparty/eigen/unsupported/test/matrix_exponential.cpp b/resources/3rdparty/eigen/unsupported/test/matrix_exponential.cpp
index 695472f91..50dec083d 100644
--- a/resources/3rdparty/eigen/unsupported/test/matrix_exponential.cpp
+++ b/resources/3rdparty/eigen/unsupported/test/matrix_exponential.cpp
@@ -7,8 +7,7 @@
// 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/.
-#include "main.h"
-#include <unsupported/Eigen/MatrixFunctions>
+#include "matrix_functions.h"
double binom(int n, int k)
{
@@ -18,12 +17,6 @@ double binom(int n, int k)
return res;
}
-template <typename Derived, typename OtherDerived>
-double relerr(const MatrixBase<Derived>& A, const MatrixBase<OtherDerived>& B)
-{
- return std::sqrt((A - B).cwiseAbs2().sum() / (std::min)(A.cwiseAbs2().sum(), B.cwiseAbs2().sum()));
-}
-
template <typename T>
T expfn(T x, int)
{
@@ -109,8 +102,7 @@ void randomTest(const MatrixType& m, double tol)
*/
typename MatrixType::Index rows = m.rows();
typename MatrixType::Index cols = m.cols();
- MatrixType m1(rows, cols), m2(rows, cols), m3(rows, cols),
- identity = MatrixType::Identity(rows, rows);
+ MatrixType m1(rows, cols), m2(rows, cols), identity = MatrixType::Identity(rows, cols);
typedef typename NumTraits<typename internal::traits<MatrixType>::Scalar>::Real RealScalar;
diff --git a/resources/3rdparty/eigen/unsupported/test/matrix_functions.h b/resources/3rdparty/eigen/unsupported/test/matrix_functions.h
new file mode 100644
index 000000000..5817caef6
--- /dev/null
+++ b/resources/3rdparty/eigen/unsupported/test/matrix_functions.h
@@ -0,0 +1,47 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009-2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
+//
+// 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/.
+
+#include "main.h"
+#include <unsupported/Eigen/MatrixFunctions>
+
+template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
+struct generateTestMatrix;
+
+// for real matrices, make sure none of the eigenvalues are negative
+template <typename MatrixType>
+struct generateTestMatrix<MatrixType,0>
+{
+ static void run(MatrixType& result, typename MatrixType::Index size)
+ {
+ MatrixType mat = MatrixType::Random(size, size);
+ EigenSolver<MatrixType> es(mat);
+ typename EigenSolver<MatrixType>::EigenvalueType eivals = es.eigenvalues();
+ for (typename MatrixType::Index i = 0; i < size; ++i) {
+ if (eivals(i).imag() == 0 && eivals(i).real() < 0)
+ eivals(i) = -eivals(i);
+ }
+ result = (es.eigenvectors() * eivals.asDiagonal() * es.eigenvectors().inverse()).real();
+ }
+};
+
+// for complex matrices, any matrix is fine
+template <typename MatrixType>
+struct generateTestMatrix<MatrixType,1>
+{
+ static void run(MatrixType& result, typename MatrixType::Index size)
+ {
+ result = MatrixType::Random(size, size);
+ }
+};
+
+template <typename Derived, typename OtherDerived>
+double relerr(const MatrixBase<Derived>& A, const MatrixBase<OtherDerived>& B)
+{
+ return std::sqrt((A - B).cwiseAbs2().sum() / (std::min)(A.cwiseAbs2().sum(), B.cwiseAbs2().sum()));
+}
diff --git a/resources/3rdparty/eigen/unsupported/test/matrix_power.cpp b/resources/3rdparty/eigen/unsupported/test/matrix_power.cpp
new file mode 100644
index 000000000..95c63c574
--- /dev/null
+++ b/resources/3rdparty/eigen/unsupported/test/matrix_power.cpp
@@ -0,0 +1,136 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
+//
+// 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/.
+
+#include "matrix_functions.h"
+
+template<typename T>
+void test2dRotation(double tol)
+{
+ Matrix<T,2,2> A, B, C;
+ T angle, c, s;
+
+ A << 0, 1, -1, 0;
+ MatrixPower<Matrix<T,2,2> > Apow(A);
+
+ for (int i=0; i<=20; ++i) {
+ angle = pow(10, (i-10) / 5.);
+ c = std::cos(angle);
+ s = std::sin(angle);
+ B << c, s, -s, c;
+
+ C = Apow(std::ldexp(angle,1) / M_PI);
+ std::cout << "test2dRotation: i = " << i << " error powerm = " << relerr(C,B) << '\n';
+ VERIFY(C.isApprox(B, static_cast<T>(tol)));
+ }
+}
+
+template<typename T>
+void test2dHyperbolicRotation(double tol)
+{
+ Matrix<std::complex<T>,2,2> A, B, C;
+ T angle, ch = std::cosh((T)1);
+ std::complex<T> ish(0, std::sinh((T)1));
+
+ A << ch, ish, -ish, ch;
+ MatrixPower<Matrix<std::complex<T>,2,2> > Apow(A);
+
+ for (int i=0; i<=20; ++i) {
+ angle = std::ldexp(static_cast<T>(i-10), -1);
+ ch = std::cosh(angle);
+ ish = std::complex<T>(0, std::sinh(angle));
+ B << ch, ish, -ish, ch;
+
+ C = Apow(angle);
+ std::cout << "test2dHyperbolicRotation: i = " << i << " error powerm = " << relerr(C,B) << '\n';
+ VERIFY(C.isApprox(B, static_cast<T>(tol)));
+ }
+}
+
+template<typename MatrixType>
+void testExponentLaws(const MatrixType& m, double tol)
+{
+ typedef typename MatrixType::RealScalar RealScalar;
+ MatrixType m1, m2, m3, m4, m5;
+ RealScalar x, y;
+
+ for (int i=0; i<g_repeat; ++i) {
+ generateTestMatrix<MatrixType>::run(m1, m.rows());
+ MatrixPower<MatrixType> mpow(m1);
+
+ x = internal::random<RealScalar>();
+ y = internal::random<RealScalar>();
+ m2 = mpow(x);
+ m3 = mpow(y);
+
+ m4 = mpow(x+y);
+ m5.noalias() = m2 * m3;
+ VERIFY(m4.isApprox(m5, static_cast<RealScalar>(tol)));
+
+ m4 = mpow(x*y);
+ m5 = m2.pow(y);
+ VERIFY(m4.isApprox(m5, static_cast<RealScalar>(tol)));
+
+ m4 = (std::abs(x) * m1).pow(y);
+ m5 = std::pow(std::abs(x), y) * m3;
+ VERIFY(m4.isApprox(m5, static_cast<RealScalar>(tol)));
+ }
+}
+
+template<typename MatrixType, typename VectorType>
+void testProduct(const MatrixType& m, const VectorType& v, double tol)
+{
+ typedef typename MatrixType::RealScalar RealScalar;
+ MatrixType m1;
+ VectorType v1, v2, v3;
+ RealScalar p;
+
+ for (int i=0; i<g_repeat; ++i) {
+ generateTestMatrix<MatrixType>::run(m1, m.rows());
+ MatrixPower<MatrixType> mpow(m1);
+
+ v1 = VectorType::Random(v.rows(), v.cols());
+ p = internal::random<RealScalar>();
+
+ v2.noalias() = mpow(p) * v1;
+ v3.noalias() = mpow(p).eval() * v1;
+ std::cout << "testMatrixVectorProduct: error powerm = " << relerr(v2, v3) << '\n';
+ VERIFY(v2.isApprox(v3, static_cast<RealScalar>(tol)));
+ }
+}
+
+template<typename MatrixType, typename VectorType>
+void testMatrixVector(const MatrixType& m, const VectorType& v, double tol)
+{
+ testExponentLaws(m,tol);
+ testProduct(m,v,tol);
+}
+
+void test_matrix_power()
+{
+ typedef Matrix<double,3,3,RowMajor> Matrix3dRowMajor;
+ typedef Matrix<long double,Dynamic,Dynamic> MatrixXe;
+ typedef Matrix<long double,Dynamic,1> VectorXe;
+
+ CALL_SUBTEST_2(test2dRotation<double>(1e-13));
+ CALL_SUBTEST_1(test2dRotation<float>(2e-5)); // was 1e-5, relaxed for clang 2.8 / linux / x86-64
+ CALL_SUBTEST_9(test2dRotation<long double>(1e-13));
+ CALL_SUBTEST_2(test2dHyperbolicRotation<double>(1e-14));
+ CALL_SUBTEST_1(test2dHyperbolicRotation<float>(1e-5));
+ CALL_SUBTEST_9(test2dHyperbolicRotation<long double>(1e-14));
+
+ CALL_SUBTEST_2(testMatrixVector(Matrix2d(), Vector2d(), 1e-13));
+ CALL_SUBTEST_7(testMatrixVector(Matrix3dRowMajor(), MatrixXd(3,5), 1e-13));
+ CALL_SUBTEST_3(testMatrixVector(Matrix4cd(), Vector4cd(), 1e-13));
+ CALL_SUBTEST_4(testMatrixVector(MatrixXd(8,8), VectorXd(8), 1e-13));
+ CALL_SUBTEST_1(testMatrixVector(Matrix2f(), Vector2f(), 1e-4));
+ CALL_SUBTEST_5(testMatrixVector(Matrix3cf(), Vector3cf(), 1e-4));
+ CALL_SUBTEST_8(testMatrixVector(Matrix4f(), Vector4f(), 1e-4));
+ CALL_SUBTEST_6(testMatrixVector(MatrixXf(8,8), VectorXf(8), 1e-4));
+ CALL_SUBTEST_9(testMatrixVector(MatrixXe(7,7), VectorXe(7), 1e-13));
+}
diff --git a/resources/3rdparty/eigen/unsupported/test/matrix_square_root.cpp b/resources/3rdparty/eigen/unsupported/test/matrix_square_root.cpp
index 508619a7a..ea541e1ea 100644
--- a/resources/3rdparty/eigen/unsupported/test/matrix_square_root.cpp
+++ b/resources/3rdparty/eigen/unsupported/test/matrix_square_root.cpp
@@ -7,38 +7,7 @@
// 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/.
-#include "main.h"
-#include <unsupported/Eigen/MatrixFunctions>
-
-template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
-struct generateTestMatrix;
-
-// for real matrices, make sure none of the eigenvalues are negative
-template <typename MatrixType>
-struct generateTestMatrix<MatrixType,0>
-{
- static void run(MatrixType& result, typename MatrixType::Index size)
- {
- MatrixType mat = MatrixType::Random(size, size);
- EigenSolver<MatrixType> es(mat);
- typename EigenSolver<MatrixType>::EigenvalueType eivals = es.eigenvalues();
- for (typename MatrixType::Index i = 0; i < size; ++i) {
- if (eivals(i).imag() == 0 && eivals(i).real() < 0)
- eivals(i) = -eivals(i);
- }
- result = (es.eigenvectors() * eivals.asDiagonal() * es.eigenvectors().inverse()).real();
- }
-};
-
-// for complex matrices, any matrix is fine
-template <typename MatrixType>
-struct generateTestMatrix<MatrixType,1>
-{
- static void run(MatrixType& result, typename MatrixType::Index size)
- {
- result = MatrixType::Random(size, size);
- }
-};
+#include "matrix_functions.h"
template<typename MatrixType>
void testMatrixSqrt(const MatrixType& m)