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-rw-r--r--Eigen/src/Cholesky/Cholesky.h34
-rw-r--r--Eigen/src/Cholesky/CholeskyWithoutSquareRoot.h37
-rw-r--r--Eigen/src/Core/MatrixBase.h9
-rw-r--r--Eigen/src/Core/Product.h17
-rwxr-xr-xEigen/src/Core/SolveTriangular.h37
-rw-r--r--Eigen/src/Core/util/XprHelper.h12
-rw-r--r--Eigen/src/SVD/SVD.h23
7 files changed, 124 insertions, 45 deletions
diff --git a/Eigen/src/Cholesky/Cholesky.h b/Eigen/src/Cholesky/Cholesky.h
index a64ab7c70..b94fea8dc 100644
--- a/Eigen/src/Cholesky/Cholesky.h
+++ b/Eigen/src/Cholesky/Cholesky.h
@@ -74,6 +74,9 @@ template<typename MatrixType> class Cholesky
template<typename Derived>
typename Derived::Eval solve(const MatrixBase<Derived> &b) const;
+ template<typename Derived>
+ bool solveInPlace(MatrixBase<Derived> &bAndX) const;
+
void compute(const MatrixType& matrix);
protected:
@@ -141,8 +144,37 @@ typename Derived::Eval Cholesky<MatrixType>::solve(const MatrixBase<Derived> &b)
{
const int size = m_matrix.rows();
ei_assert(size==b.rows());
+ typename ei_eval_to_column_major<Derived>::type x(b);
+ solveInPlace(x);
+ return x;
+ //return m_matrix.adjoint().template part<Upper>().solveTriangular(matrixL().solveTriangular(b));
+}
- return m_matrix.adjoint().template part<Upper>().solveTriangular(matrixL().solveTriangular(b));
+/** Computes the solution x of \f$ A x = b \f$ using the current decomposition of A.
+ * The result is stored in \a bAndx
+ *
+ * \returns true in case of success, false otherwise.
+ *
+ * In other words, it computes \f$ b = A^{-1} b \f$ with
+ * \f$ {L^{*}}^{-1} L^{-1} b \f$ from right to left.
+ * \param bAndX stores both the matrix \f$ b \f$ and the result \f$ x \f$
+ *
+ * Example: \include Cholesky_solve.cpp
+ * Output: \verbinclude Cholesky_solve.out
+ *
+ * \sa MatrixBase::cholesky(), Cholesky::solve()
+ */
+template<typename MatrixType>
+template<typename Derived>
+bool Cholesky<MatrixType>::solveInPlace(MatrixBase<Derived> &bAndX) const
+{
+ const int size = m_matrix.rows();
+ ei_assert(size==bAndX.rows());
+ if (!m_isPositiveDefinite)
+ return false;
+ matrixL().solveTriangularInPlace(bAndX);
+ m_matrix.adjoint().template part<Upper>().solveTriangularInPlace(bAndX);
+ return true;
}
/** \cholesky_module
diff --git a/Eigen/src/Cholesky/CholeskyWithoutSquareRoot.h b/Eigen/src/Cholesky/CholeskyWithoutSquareRoot.h
index 4040869b0..fd111fb1f 100644
--- a/Eigen/src/Cholesky/CholeskyWithoutSquareRoot.h
+++ b/Eigen/src/Cholesky/CholeskyWithoutSquareRoot.h
@@ -71,6 +71,9 @@ template<typename MatrixType> class CholeskyWithoutSquareRoot
template<typename Derived>
typename Derived::Eval solve(const MatrixBase<Derived> &b) const;
+ template<typename Derived>
+ bool solveInPlace(MatrixBase<Derived> &bAndX) const;
+
void compute(const MatrixType& matrix);
protected:
@@ -101,7 +104,7 @@ void CholeskyWithoutSquareRoot<MatrixType>::compute(const MatrixType& a)
m_matrix = a;
return;
}
-
+
// Let's preallocate a temporay vector to evaluate the matrix-vector product into it.
// Unlike the standard Cholesky decomposition, here we cannot evaluate it to the destination
// matrix because it a sub-row which is not compatible suitable for efficient packet evaluation.
@@ -144,8 +147,8 @@ void CholeskyWithoutSquareRoot<MatrixType>::compute(const MatrixType& a)
* \param b the column vector \f$ b \f$, which can also be a matrix.
*
* See Cholesky::solve() for a example.
- *
- * \sa MatrixBase::choleskyNoSqrt()
+ *
+ * \sa CholeskyWithoutSquareRoot::solveInPlace(), MatrixBase::choleskyNoSqrt()
*/
template<typename MatrixType>
template<typename Derived>
@@ -161,6 +164,34 @@ typename Derived::Eval CholeskyWithoutSquareRoot<MatrixType>::solve(const Matrix
);
}
+/** Computes the solution x of \f$ A x = b \f$ using the current decomposition of A.
+ * The result is stored in \a bAndx
+ *
+ * \returns true in case of success, false otherwise.
+ *
+ * In other words, it computes \f$ b = A^{-1} b \f$ with
+ * \f$ {L^{*}}^{-1} D^{-1} L^{-1} b \f$ from right to left.
+ * \param bAndX stores both the matrix \f$ b \f$ and the result \f$ x \f$
+ *
+ * Example: \include Cholesky_solve.cpp
+ * Output: \verbinclude Cholesky_solve.out
+ *
+ * \sa MatrixBase::cholesky(), CholeskyWithoutSquareRoot::solve()
+ */
+template<typename MatrixType>
+template<typename Derived>
+bool CholeskyWithoutSquareRoot<MatrixType>::solveInPlace(MatrixBase<Derived> &bAndX) const
+{
+ const int size = m_matrix.rows();
+ ei_assert(size==bAndX.rows());
+ if (!m_isPositiveDefinite)
+ return false;
+ matrixL().solveTriangularInPlace(bAndX);
+ bAndX *= m_matrix.cwise().inverse().template part<Diagonal>();
+ m_matrix.adjoint().template part<UnitUpper>().solveTriangularInPlace(bAndX);
+ return true;
+}
+
/** \cholesky_module
* \returns the Cholesky decomposition without square root of \c *this
*/
diff --git a/Eigen/src/Core/MatrixBase.h b/Eigen/src/Core/MatrixBase.h
index 2e8355f77..944d353d8 100644
--- a/Eigen/src/Core/MatrixBase.h
+++ b/Eigen/src/Core/MatrixBase.h
@@ -320,7 +320,8 @@ template<typename Derived> class MatrixBase
Derived& operator*=(const MatrixBase<OtherDerived>& other);
template<typename OtherDerived>
- typename OtherDerived::Eval solveTriangular(const MatrixBase<OtherDerived>& other) const;
+ typename ei_eval_to_column_major<OtherDerived>::type
+ solveTriangular(const MatrixBase<OtherDerived>& other) const;
template<typename OtherDerived>
void solveTriangularInPlace(MatrixBase<OtherDerived>& other) const;
@@ -544,11 +545,11 @@ template<typename Derived> class MatrixBase
const Select<Derived,ThenDerived,ElseDerived>
select(const MatrixBase<ThenDerived>& thenMatrix,
const MatrixBase<ElseDerived>& elseMatrix) const;
-
+
template<typename ThenDerived>
inline const Select<Derived,ThenDerived, NestByValue<typename ThenDerived::ConstantReturnType> >
select(const MatrixBase<ThenDerived>& thenMatrix, typename ThenDerived::Scalar elseScalar) const;
-
+
template<typename ElseDerived>
inline const Select<Derived, NestByValue<typename ElseDerived::ConstantReturnType>, ElseDerived >
select(typename ElseDerived::Scalar thenScalar, const MatrixBase<ElseDerived>& elseMatrix) const;
@@ -581,7 +582,7 @@ template<typename Derived> class MatrixBase
template<typename OtherDerived>
EvalType cross(const MatrixBase<OtherDerived>& other) const;
EvalType unitOrthogonal(void) const;
-
+
#ifdef EIGEN_MATRIXBASE_PLUGIN
#include EIGEN_MATRIXBASE_PLUGIN
#endif
diff --git a/Eigen/src/Core/Product.h b/Eigen/src/Core/Product.h
index 04deae0ab..429cdc0e9 100644
--- a/Eigen/src/Core/Product.h
+++ b/Eigen/src/Core/Product.h
@@ -36,8 +36,6 @@ struct ei_product_coeff_impl;
template<int StorageOrder, int Index, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
struct ei_product_packet_impl;
-template<typename T> struct ei_product_eval_to_column_major;
-
/** \class ProductReturnType
*
* \brief Helper class to get the correct and optimized returned type of operator*
@@ -70,7 +68,7 @@ struct ProductReturnType<Lhs,Rhs,CacheFriendlyProduct>
typedef typename ei_nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
typedef typename ei_nested<Rhs,Lhs::RowsAtCompileTime,
- typename ei_product_eval_to_column_major<Rhs>::type
+ typename ei_eval_to_column_major<Rhs>::type
>::type RhsNested;
typedef Product<LhsNested, RhsNested, CacheFriendlyProduct> Type;
@@ -706,23 +704,12 @@ inline Derived& MatrixBase<Derived>::lazyAssign(const Product<Lhs,Rhs,CacheFrien
return derived();
}
-template<typename T> struct ei_product_eval_to_column_major
-{
- typedef Matrix<typename ei_traits<T>::Scalar,
- ei_traits<T>::RowsAtCompileTime,
- ei_traits<T>::ColsAtCompileTime,
- ColMajor,
- ei_traits<T>::MaxRowsAtCompileTime,
- ei_traits<T>::MaxColsAtCompileTime
- > type;
-};
-
template<typename T> struct ei_product_copy_rhs
{
typedef typename ei_meta_if<
(ei_traits<T>::Flags & RowMajorBit)
|| (!(ei_traits<T>::Flags & DirectAccessBit)),
- typename ei_product_eval_to_column_major<T>::type,
+ typename ei_eval_to_column_major<T>::type,
const T&
>::ret type;
};
diff --git a/Eigen/src/Core/SolveTriangular.h b/Eigen/src/Core/SolveTriangular.h
index e77d9e238..ea0956ab3 100755
--- a/Eigen/src/Core/SolveTriangular.h
+++ b/Eigen/src/Core/SolveTriangular.h
@@ -88,12 +88,12 @@ struct ei_solve_triangular_selector<Lhs,Rhs,UpLo,RowMajor|IsDense>
other.coeffRef(i,c) = tmp/lhs.coeff(i,i);
}
- // now let process the remaining rows 4 at once
+ // now let's process the remaining rows 4 at once
for(int i=blockyStart; IsLower ? i<size : i>0; )
{
int startBlock = i;
int endBlock = startBlock + (IsLower ? 4 : -4);
-
+
/* Process the i cols times 4 rows block, and keep the result in a temporary vector */
// FIXME use fixed size block but take care to small fixed size matrices...
Matrix<Scalar,Dynamic,1> btmp(4);
@@ -101,7 +101,7 @@ struct ei_solve_triangular_selector<Lhs,Rhs,UpLo,RowMajor|IsDense>
btmp = lhs.block(startBlock,0,4,i) * other.col(c).start(i);
else
btmp = lhs.block(i-3,i+1,4,size-1-i) * other.col(c).end(size-1-i);
-
+
/* Let's process the 4x4 sub-matrix as usual.
* btmp stores the diagonal coefficients used to update the remaining part of the result.
*/
@@ -191,6 +191,12 @@ struct ei_solve_triangular_selector<Lhs,Rhs,UpLo,ColMajor|IsDense>
&(lhs.const_cast_derived().coeffRef(IsLower ? endBlock : 0, IsLower ? startBlock : endBlock+1)),
lhs.stride(),
btmp, &(other.coeffRef(IsLower ? endBlock : 0, c)));
+// if (IsLower)
+// other.col(c).end(size-endBlock) += (lhs.block(endBlock, startBlock, size-endBlock, endBlock-startBlock)
+// * other.col(c).block(startBlock,endBlock-startBlock)).lazy();
+// else
+// other.col(c).end(size-endBlock) += (lhs.block(endBlock, startBlock, size-endBlock, endBlock-startBlock)
+// * other.col(c).block(startBlock,endBlock-startBlock)).lazy();
}
/* Now we have to process the remaining part as usual */
@@ -227,7 +233,15 @@ void MatrixBase<Derived>::solveTriangularInPlace(MatrixBase<OtherDerived>& other
ei_assert(!(Flags & ZeroDiagBit));
ei_assert(Flags & (UpperTriangularBit|LowerTriangularBit));
- ei_solve_triangular_selector<Derived, OtherDerived>::run(derived(), other.derived());
+ const bool copy = ei_traits<OtherDerived>::Flags&RowMajorBit;
+ typedef typename ei_meta_if<copy,
+ typename ei_eval_to_column_major<OtherDerived>::type, OtherDerived&>::ret OtherCopy;
+ OtherCopy otherCopy(other.derived());
+
+ ei_solve_triangular_selector<Derived, typename ei_unref<OtherCopy>::type>::run(derived(), otherCopy);
+
+ if (copy)
+ other = otherCopy;
}
/** \returns the product of the inverse of \c *this with \a other, \a *this being triangular.
@@ -240,17 +254,17 @@ void MatrixBase<Derived>::solveTriangularInPlace(MatrixBase<OtherDerived>& other
* It is required that \c *this be marked as either an upper or a lower triangular matrix, which
* can be done by marked(), and that is automatically the case with expressions such as those returned
* by extract().
- *
+ *
* \addexample SolveTriangular \label How to solve a triangular system (aka. how to multiply the inverse of a triangular matrix by another one)
- *
+ *
* Example: \include MatrixBase_marked.cpp
* Output: \verbinclude MatrixBase_marked.out
- *
+ *
* This function is essentially a wrapper to the faster solveTriangularInPlace() function creating
* a temporary copy of \a other, calling solveTriangularInPlace() on the copy and returning it.
* Therefore, if \a other is not needed anymore, it is quite faster to call solveTriangularInPlace()
* instead of solveTriangular().
- *
+ *
* For users coming from BLAS, this function (and more specifically solveTriangularInPlace()) offer
* all the operations supported by the \c *TRSV and \c *TRSM BLAS routines.
*
@@ -258,14 +272,15 @@ void MatrixBase<Derived>::solveTriangularInPlace(MatrixBase<OtherDerived>& other
* \code
* M * T^1 <=> T.transpose().solveTriangularInPlace(M.transpose());
* \endcode
- *
+ *
* \sa solveTriangularInPlace(), marked(), extract()
*/
template<typename Derived>
template<typename OtherDerived>
-typename OtherDerived::Eval MatrixBase<Derived>::solveTriangular(const MatrixBase<OtherDerived>& other) const
+typename ei_eval_to_column_major<OtherDerived>::type
+MatrixBase<Derived>::solveTriangular(const MatrixBase<OtherDerived>& other) const
{
- typename OtherDerived::Eval res(other);
+ typename ei_eval_to_column_major<OtherDerived>::type res(other);
solveTriangularInPlace(res);
return res;
}
diff --git a/Eigen/src/Core/util/XprHelper.h b/Eigen/src/Core/util/XprHelper.h
index 00f1a39ea..5b8a2c021 100644
--- a/Eigen/src/Core/util/XprHelper.h
+++ b/Eigen/src/Core/util/XprHelper.h
@@ -121,6 +121,18 @@ template<typename T> struct ei_eval<T,IsDense>
> type;
};
+
+template<typename T> struct ei_eval_to_column_major
+{
+ typedef Matrix<typename ei_traits<T>::Scalar,
+ ei_traits<T>::RowsAtCompileTime,
+ ei_traits<T>::ColsAtCompileTime,
+ ColMajor,
+ ei_traits<T>::MaxRowsAtCompileTime,
+ ei_traits<T>::MaxColsAtCompileTime
+ > type;
+};
+
template<typename T> struct ei_must_nest_by_value { enum { ret = false }; };
template<typename T> struct ei_must_nest_by_value<NestByValue<T> > { enum { ret = true }; };
diff --git a/Eigen/src/SVD/SVD.h b/Eigen/src/SVD/SVD.h
index 39020fdfc..c3f3bb235 100644
--- a/Eigen/src/SVD/SVD.h
+++ b/Eigen/src/SVD/SVD.h
@@ -50,16 +50,16 @@ template<typename MatrixType> class SVD
AlignmentMask = int(PacketSize)-1,
MinSize = EIGEN_ENUM_MIN(MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime)
};
-
+
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> ColVector;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> RowVector;
-
+
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MinSize> MatrixUType;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> MatrixVType;
typedef Matrix<Scalar, MinSize, 1> SingularValuesType;
public:
-
+
SVD(const MatrixType& matrix)
: m_matU(matrix.rows(), std::min(matrix.rows(), matrix.cols())),
m_matV(matrix.cols(),matrix.cols()),
@@ -69,7 +69,7 @@ template<typename MatrixType> class SVD
}
template<typename OtherDerived, typename ResultType>
- void solve(const MatrixBase<OtherDerived> &b, ResultType* result) const;
+ bool solve(const MatrixBase<OtherDerived> &b, ResultType* result) const;
const MatrixUType& matrixU() const { return m_matU; }
const SingularValuesType& singularValues() const { return m_sigma; }
@@ -97,7 +97,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
const int m = matrix.rows();
const int n = matrix.cols();
const int nu = std::min(m,n);
-
+
m_matU.resize(m, nu);
m_matU.setZero();
m_sigma.resize(std::min(m,n));
@@ -130,7 +130,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
}
m_sigma[k] = -m_sigma[k];
}
-
+
for (j = k+1; j < n; j++)
{
if ((k < nct) && (m_sigma[k] != 0.0))
@@ -468,18 +468,18 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
template<typename MatrixType>
SVD<MatrixType>& SVD<MatrixType>::sort()
{
- int mu = m_matU.rows();
- int mv = m_matV.rows();
+ int mu = m_matU.rows();
+ int mv = m_matV.rows();
int n = m_matU.cols();
for (int i=0; i<n; i++)
{
- int k = i;
+ int k = i;
Scalar p = m_sigma.coeff(i);
for (int j=i+1; j<n; j++)
{
- if (m_sigma.coeff(j) > p)
+ if (m_sigma.coeff(j) > p)
{
k = j;
p = m_sigma.coeff(j);
@@ -509,7 +509,7 @@ SVD<MatrixType>& SVD<MatrixType>::sort()
*/
template<typename MatrixType>
template<typename OtherDerived, typename ResultType>
-void SVD<MatrixType>::solve(const MatrixBase<OtherDerived> &b, ResultType* result) const
+bool SVD<MatrixType>::solve(const MatrixBase<OtherDerived> &b, ResultType* result) const
{
const int rows = m_matU.rows();
ei_assert(b.rows() == rows);
@@ -530,6 +530,7 @@ void SVD<MatrixType>::solve(const MatrixBase<OtherDerived> &b, ResultType* resul
result->col(j) = m_matV * aux;
}
+ return true;
}
/** \svd_module