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-rw-r--r--Eigen/Core4
-rw-r--r--Eigen/src/Core/DenseStorageBase.h2
-rw-r--r--Eigen/src/Core/arch/Default/Settings.h65
-rw-r--r--Eigen/src/Core/util/Macros.h24
-rw-r--r--test/lu.cpp14
5 files changed, 74 insertions, 35 deletions
diff --git a/Eigen/Core b/Eigen/Core
index 2908fef2e..01456fe7e 100644
--- a/Eigen/Core
+++ b/Eigen/Core
@@ -214,9 +214,7 @@ struct Dense {};
#include "src/Core/arch/NEON/PacketMath.h"
#endif
-#ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
-#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 8
-#endif
+#include "src/Core/arch/Default/Settings.h"
#include "src/Core/Functors.h"
#include "src/Core/DenseBase.h"
diff --git a/Eigen/src/Core/DenseStorageBase.h b/Eigen/src/Core/DenseStorageBase.h
index c7f903c7a..dac2142a4 100644
--- a/Eigen/src/Core/DenseStorageBase.h
+++ b/Eigen/src/Core/DenseStorageBase.h
@@ -601,7 +601,7 @@ struct ei_conservative_resize_like_impl<Derived,OtherDerived,true>
const int new_rows = Derived::RowsAtCompileTime==1 ? 1 : other.rows();
const int new_cols = Derived::RowsAtCompileTime==1 ? other.cols() : 1;
_this.derived().m_storage.conservativeResize(other.size(),new_rows,new_cols);
-
+
if (num_new_elements > 0)
_this.tail(num_new_elements) = other.tail(num_new_elements);
}
diff --git a/Eigen/src/Core/arch/Default/Settings.h b/Eigen/src/Core/arch/Default/Settings.h
new file mode 100644
index 000000000..1e7cebdba
--- /dev/null
+++ b/Eigen/src/Core/arch/Default/Settings.h
@@ -0,0 +1,65 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+//
+// 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/>.
+
+
+/* All the parameters defined in this file can be specialized in the
+ * architecture specific files, and/or by the user.
+ * More to come... */
+
+#ifndef EIGEN_DEFAULT_SETTINGS_H
+#define EIGEN_DEFAULT_SETTINGS_H
+
+/** Defines the maximal loop size to enable meta unrolling of loops.
+ * Note that the value here is expressed in Eigen's own notion of "number of FLOPS",
+ * it does not correspond to the number of iterations or the number of instructions
+ */
+#ifndef EIGEN_UNROLLING_LIMIT
+#define EIGEN_UNROLLING_LIMIT 100
+#endif
+
+/** Defines the threshold between a "small" and a "large" matrix.
+ * This threshold is mainly used to select the proper product implementation.
+ */
+#ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
+#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 8
+#endif
+
+/** Defines the maximal size in Bytes of blocks fitting in CPU cache.
+ * The current value is set to generate blocks of 256x256 for float
+ *
+ * Typically for a single-threaded application you would set that to 25% of the size of your CPU caches in bytes
+ */
+#ifndef EIGEN_TUNE_FOR_CPU_CACHE_SIZE
+#define EIGEN_TUNE_FOR_CPU_CACHE_SIZE (sizeof(float)*256*256)
+#endif
+
+/** Defines the maximal width of the blocks used in the triangular product and solver
+ * for vectors (level 2 blas xTRMV and xTRSV). The default is 8.
+ */
+#ifndef EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH
+#define EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH 8
+#endif
+
+#endif // EIGEN_DEFAULT_SETTINGS_H
diff --git a/Eigen/src/Core/util/Macros.h b/Eigen/src/Core/util/Macros.h
index 7970b3bb0..19420f610 100644
--- a/Eigen/src/Core/util/Macros.h
+++ b/Eigen/src/Core/util/Macros.h
@@ -78,30 +78,6 @@
#define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION ColMajor
#endif
-/** Defines the maximal loop size to enable meta unrolling of loops.
- * Note that the value here is expressed in Eigen's own notion of "number of FLOPS",
- * it does not correspond to the number of iterations or the number of instructions
- */
-#ifndef EIGEN_UNROLLING_LIMIT
-#define EIGEN_UNROLLING_LIMIT 100
-#endif
-
-/** Defines the maximal size in Bytes of blocks fitting in CPU cache.
- * The current value is set to generate blocks of 256x256 for float
- *
- * Typically for a single-threaded application you would set that to 25% of the size of your CPU caches in bytes
- */
-#ifndef EIGEN_TUNE_FOR_CPU_CACHE_SIZE
-#define EIGEN_TUNE_FOR_CPU_CACHE_SIZE (sizeof(float)*256*256)
-#endif
-
-/** Defines the maximal width of the blocks used in the triangular product and solver
- * for vectors (level 2 blas xTRMV and xTRSV). The default is 8.
- */
-#ifndef EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH
-#define EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH 8
-#endif
-
/** Allows to disable some optimizations which might affect the accuracy of the result.
* Such optimization are enabled by default, and set EIGEN_FAST_MATH to 0 to disable them.
* They currently include:
diff --git a/test/lu.cpp b/test/lu.cpp
index 1ed38cb2b..37e2990d2 100644
--- a/test/lu.cpp
+++ b/test/lu.cpp
@@ -67,7 +67,7 @@ template<typename MatrixType> void lu_non_invertible()
// The image of the zero matrix should consist of a single (zero) column vector
VERIFY((MatrixType::Zero(rows,cols).fullPivLu().image(MatrixType::Zero(rows,cols)).cols() == 1));
-
+
MatrixType m1(rows, cols), m3(rows, cols2);
CMatrixType m2(cols, cols2);
createRandomPIMatrixOfRank(rank, rows, cols, m1);
@@ -85,9 +85,9 @@ template<typename MatrixType> void lu_non_invertible()
RMatrixType l = RMatrixType::Identity(rows,rows);
l.block(0,0,rows,std::min(rows,cols)).template triangularView<StrictlyLower>()
= lu.matrixLU().block(0,0,rows,std::min(rows,cols));
-
+
VERIFY_IS_APPROX(lu.permutationP() * m1 * lu.permutationQ(), l*u);
-
+
KernelMatrixType m1kernel = lu.kernel();
ImageMatrixType m1image = lu.image(m1);
@@ -192,20 +192,20 @@ void test_lu()
CALL_SUBTEST_2( (lu_non_invertible<Matrix<double, 4, 6> >()) );
CALL_SUBTEST_2( (lu_verify_assert<Matrix<double, 4, 6> >()) );
-
+
CALL_SUBTEST_3( lu_non_invertible<MatrixXf>() );
CALL_SUBTEST_3( lu_invertible<MatrixXf>() );
CALL_SUBTEST_3( lu_verify_assert<MatrixXf>() );
-
+
CALL_SUBTEST_4( lu_non_invertible<MatrixXd>() );
CALL_SUBTEST_4( lu_invertible<MatrixXd>() );
CALL_SUBTEST_4( lu_partial_piv<MatrixXd>() );
CALL_SUBTEST_4( lu_verify_assert<MatrixXd>() );
-
+
CALL_SUBTEST_5( lu_non_invertible<MatrixXcf>() );
CALL_SUBTEST_5( lu_invertible<MatrixXcf>() );
CALL_SUBTEST_5( lu_verify_assert<MatrixXcf>() );
-
+
CALL_SUBTEST_6( lu_non_invertible<MatrixXcd>() );
CALL_SUBTEST_6( lu_invertible<MatrixXcd>() );
CALL_SUBTEST_6( lu_partial_piv<MatrixXcd>() );