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1221 Commits
before-eva
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3.3-alpha1
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230f5c3aa9 |
@@ -1,6 +1,6 @@
|
||||
project(Eigen)
|
||||
|
||||
cmake_minimum_required(VERSION 2.8.2)
|
||||
cmake_minimum_required(VERSION 2.8.4)
|
||||
|
||||
# guard against in-source builds
|
||||
|
||||
@@ -147,6 +147,12 @@ if(NOT MSVC)
|
||||
ei_add_cxx_compiler_flag("-Wenum-conversion")
|
||||
ei_add_cxx_compiler_flag("-Wc++11-extensions")
|
||||
|
||||
# -Wshadow is insanely too strict with gcc, hopefully it will become usable with gcc 6
|
||||
# if(NOT CMAKE_COMPILER_IS_GNUCXX OR (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER "5.0.0"))
|
||||
if(NOT CMAKE_COMPILER_IS_GNUCXX)
|
||||
ei_add_cxx_compiler_flag("-Wshadow")
|
||||
endif()
|
||||
|
||||
ei_add_cxx_compiler_flag("-Wno-psabi")
|
||||
ei_add_cxx_compiler_flag("-Wno-variadic-macros")
|
||||
ei_add_cxx_compiler_flag("-Wno-long-long")
|
||||
@@ -168,6 +174,11 @@ if(NOT MSVC)
|
||||
else()
|
||||
ei_add_cxx_compiler_flag("-ansi")
|
||||
endif()
|
||||
|
||||
if(ANDROID_NDK)
|
||||
ei_add_cxx_compiler_flag("-pie")
|
||||
ei_add_cxx_compiler_flag("-fPIE")
|
||||
endif()
|
||||
|
||||
set(CMAKE_REQUIRED_FLAGS "")
|
||||
|
||||
@@ -208,7 +219,7 @@ if(NOT MSVC)
|
||||
endif()
|
||||
|
||||
option(EIGEN_TEST_FMA "Enable/Disable FMA in tests/examples" OFF)
|
||||
if(EIGEN_TEST_FMA)
|
||||
if(EIGEN_TEST_FMA AND NOT EIGEN_TEST_NEON)
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfma")
|
||||
message(STATUS "Enabling FMA in tests/examples")
|
||||
endif()
|
||||
@@ -219,12 +230,31 @@ if(NOT MSVC)
|
||||
message(STATUS "Enabling AltiVec in tests/examples")
|
||||
endif()
|
||||
|
||||
option(EIGEN_TEST_VSX "Enable/Disable VSX in tests/examples" OFF)
|
||||
if(EIGEN_TEST_VSX)
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -m64 -mvsx")
|
||||
message(STATUS "Enabling VSX in tests/examples")
|
||||
endif()
|
||||
|
||||
option(EIGEN_TEST_NEON "Enable/Disable Neon in tests/examples" OFF)
|
||||
if(EIGEN_TEST_NEON)
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon -mcpu=cortex-a8")
|
||||
if(EIGEN_TEST_FMA)
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon-vfpv4")
|
||||
else()
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon")
|
||||
endif()
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfloat-abi=softfp")
|
||||
message(STATUS "Enabling NEON in tests/examples")
|
||||
endif()
|
||||
|
||||
option(EIGEN_TEST_NEON64 "Enable/Disable Neon in tests/examples" OFF)
|
||||
if(EIGEN_TEST_NEON64)
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
|
||||
message(STATUS "Enabling NEON in tests/examples")
|
||||
endif()
|
||||
|
||||
|
||||
|
||||
check_cxx_compiler_flag("-fopenmp" COMPILER_SUPPORT_OPENMP)
|
||||
if(COMPILER_SUPPORT_OPENMP)
|
||||
option(EIGEN_TEST_OPENMP "Enable/Disable OpenMP in tests/examples" OFF)
|
||||
@@ -307,7 +337,7 @@ if(EIGEN_TEST_NO_EXCEPTIONS)
|
||||
message(STATUS "Disabling exceptions in tests/examples")
|
||||
endif()
|
||||
|
||||
option(EIGEN_TEST_C++0x "Enables all C++0x features." OFF)
|
||||
option(EIGEN_TEST_CXX11 "Enable testing with C++11 and C++11 features (e.g. Tensor module)." OFF)
|
||||
|
||||
include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR})
|
||||
|
||||
@@ -434,6 +464,7 @@ if(cmake_generator_tolower MATCHES "makefile")
|
||||
message(STATUS "make check | Build and run the unit-tests. Read this page:")
|
||||
message(STATUS " | http://eigen.tuxfamily.org/index.php?title=Tests")
|
||||
message(STATUS "make blas | Build BLAS library (not the same thing as Eigen)")
|
||||
message(STATUS "make uninstall| Removes files installed by make install")
|
||||
message(STATUS "--------------+--------------------------------------------------------------")
|
||||
else()
|
||||
message(STATUS "To build/run the unit tests, read this page:")
|
||||
@@ -469,3 +500,7 @@ install ( FILES ${CMAKE_CURRENT_SOURCE_DIR}/cmake/UseEigen3.cmake
|
||||
${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
|
||||
DESTINATION ${EIGEN_CONFIG_CMAKE_PATH}
|
||||
)
|
||||
|
||||
# Add uninstall target
|
||||
add_custom_target ( uninstall
|
||||
COMMAND ${CMAKE_COMMAND} -P ${CMAKE_CURRENT_SOURCE_DIR}/cmake/EigenUninstall.cmake)
|
||||
|
||||
@@ -21,7 +21,6 @@
|
||||
* \endcode
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/Cholesky/LLT.h"
|
||||
#include "src/Cholesky/LDLT.h"
|
||||
#ifdef EIGEN_USE_LAPACKE
|
||||
|
||||
@@ -33,12 +33,8 @@ extern "C" {
|
||||
*
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/SparseSolve.h"
|
||||
|
||||
#include "src/CholmodSupport/CholmodSupport.h"
|
||||
|
||||
|
||||
#include "src/Core/util/ReenableStupidWarnings.h"
|
||||
|
||||
#endif // EIGEN_CHOLMODSUPPORT_MODULE_H
|
||||
|
||||
86
Eigen/Core
86
Eigen/Core
@@ -24,9 +24,15 @@
|
||||
#ifdef EIGEN_INTERNAL_DEBUGGING
|
||||
#undef EIGEN_INTERNAL_DEBUGGING
|
||||
#endif
|
||||
|
||||
|
||||
// Do not try to vectorize on CUDA!
|
||||
#ifndef EIGEN_DONT_VECTORIZE
|
||||
#define EIGEN_DONT_VECTORIZE
|
||||
#endif
|
||||
|
||||
#ifdef EIGEN_EXCEPTIONS
|
||||
#undef EIGEN_EXCEPTIONS
|
||||
#endif
|
||||
|
||||
// All functions callable from CUDA code must be qualified with __device__
|
||||
#define EIGEN_DEVICE_FUNC __host__ __device__
|
||||
@@ -57,7 +63,7 @@
|
||||
|
||||
// Disable the ipa-cp-clone optimization flag with MinGW 6.x or newer (enabled by default with -O3)
|
||||
// See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details.
|
||||
#if defined(__MINGW32__) && EIGEN_GNUC_AT_LEAST(4,6)
|
||||
#if EIGEN_COMP_MINGW && EIGEN_GNUC_AT_LEAST(4,6)
|
||||
#pragma GCC optimize ("-fno-ipa-cp-clone")
|
||||
#endif
|
||||
|
||||
@@ -67,26 +73,26 @@
|
||||
// and inclusion of their respective header files
|
||||
#include "src/Core/util/MKL_support.h"
|
||||
|
||||
// if alignment is disabled, then disable vectorization. Note: EIGEN_ALIGN is the proper check, it takes into
|
||||
// account both the user's will (EIGEN_DONT_ALIGN) and our own platform checks
|
||||
#if !EIGEN_ALIGN
|
||||
// if alignment is disabled, then disable vectorization. Note: EIGEN_MAX_ALIGN_BYTES is the proper check, it takes into
|
||||
// account both the user's will (EIGEN_MAX_ALIGN_BYTES,EIGEN_DONT_ALIGN) and our own platform checks
|
||||
#if EIGEN_MAX_ALIGN_BYTES==0
|
||||
#ifndef EIGEN_DONT_VECTORIZE
|
||||
#define EIGEN_DONT_VECTORIZE
|
||||
#endif
|
||||
#endif
|
||||
|
||||
#ifdef _MSC_VER
|
||||
#if EIGEN_COMP_MSVC
|
||||
#include <malloc.h> // for _aligned_malloc -- need it regardless of whether vectorization is enabled
|
||||
#if (_MSC_VER >= 1500) // 2008 or later
|
||||
#if (EIGEN_COMP_MSVC >= 1500) // 2008 or later
|
||||
// Remember that usage of defined() in a #define is undefined by the standard.
|
||||
// a user reported that in 64-bit mode, MSVC doesn't care to define _M_IX86_FP.
|
||||
#if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || defined(_M_X64)
|
||||
#if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || EIGEN_ARCH_x86_64
|
||||
#define EIGEN_SSE2_ON_MSVC_2008_OR_LATER
|
||||
#endif
|
||||
#endif
|
||||
#else
|
||||
// Remember that usage of defined() in a #define is undefined by the standard
|
||||
#if (defined __SSE2__) && ( (!defined __GNUC__) || (defined __INTEL_COMPILER) || EIGEN_GNUC_AT_LEAST(4,2) )
|
||||
#if (defined __SSE2__) && ( (!EIGEN_COMP_GNUC) || EIGEN_COMP_ICC || EIGEN_GNUC_AT_LEAST(4,2) )
|
||||
#define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC
|
||||
#endif
|
||||
#endif
|
||||
@@ -125,9 +131,13 @@
|
||||
#define EIGEN_VECTORIZE_SSE4_1
|
||||
#define EIGEN_VECTORIZE_SSE4_2
|
||||
#endif
|
||||
#ifdef __AVX2__
|
||||
#define EIGEN_VECTORIZE_AVX2
|
||||
#endif
|
||||
#ifdef __FMA__
|
||||
#define EIGEN_VECTORIZE_FMA
|
||||
#endif
|
||||
|
||||
// include files
|
||||
|
||||
// This extern "C" works around a MINGW-w64 compilation issue
|
||||
@@ -140,7 +150,7 @@
|
||||
extern "C" {
|
||||
// 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:
|
||||
#if defined(__INTEL_COMPILER) && __INTEL_COMPILER >= 1110
|
||||
#if EIGEN_COMP_ICC >= 1110
|
||||
#include <immintrin.h>
|
||||
#else
|
||||
#include <emmintrin.h>
|
||||
@@ -162,6 +172,15 @@
|
||||
#endif
|
||||
#endif
|
||||
} // end extern "C"
|
||||
#elif defined __VSX__
|
||||
#define EIGEN_VECTORIZE
|
||||
#define EIGEN_VECTORIZE_VSX
|
||||
#include <altivec.h>
|
||||
// We need to #undef all these ugly tokens defined in <altivec.h>
|
||||
// => use __vector instead of vector
|
||||
#undef bool
|
||||
#undef vector
|
||||
#undef pixel
|
||||
#elif defined __ALTIVEC__
|
||||
#define EIGEN_VECTORIZE
|
||||
#define EIGEN_VECTORIZE_ALTIVEC
|
||||
@@ -171,13 +190,18 @@
|
||||
#undef bool
|
||||
#undef vector
|
||||
#undef pixel
|
||||
#elif defined __ARM_NEON__
|
||||
#elif (defined __ARM_NEON) || (defined __ARM_NEON__)
|
||||
#define EIGEN_VECTORIZE
|
||||
#define EIGEN_VECTORIZE_NEON
|
||||
#include <arm_neon.h>
|
||||
#endif
|
||||
#endif
|
||||
|
||||
#if defined __CUDACC__
|
||||
#define EIGEN_VECTORIZE_CUDA
|
||||
#include <vector_types.h>
|
||||
#endif
|
||||
|
||||
#if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE)
|
||||
#define EIGEN_HAS_OPENMP
|
||||
#endif
|
||||
@@ -187,7 +211,7 @@
|
||||
#endif
|
||||
|
||||
// MSVC for windows mobile does not have the errno.h file
|
||||
#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION)
|
||||
#if !(EIGEN_COMP_MSVC && EIGEN_OS_WINCE) && !EIGEN_COMP_ARM
|
||||
#define EIGEN_HAS_ERRNO
|
||||
#endif
|
||||
|
||||
@@ -213,7 +237,7 @@
|
||||
#endif
|
||||
|
||||
// required for __cpuid, needs to be included after cmath
|
||||
#if defined(_MSC_VER) && (defined(_M_IX86)||defined(_M_X64)) && (!defined(_WIN32_WCE))
|
||||
#if EIGEN_COMP_MSVC && EIGEN_ARCH_i386_OR_x86_64 && !EIGEN_OS_WINCE
|
||||
#include <intrin.h>
|
||||
#endif
|
||||
|
||||
@@ -235,6 +259,8 @@ inline static const char *SimdInstructionSetsInUse(void) {
|
||||
return "SSE, SSE2";
|
||||
#elif defined(EIGEN_VECTORIZE_ALTIVEC)
|
||||
return "AltiVec";
|
||||
#elif defined(EIGEN_VECTORIZE_VSX)
|
||||
return "VSX";
|
||||
#elif defined(EIGEN_VECTORIZE_NEON)
|
||||
return "ARM NEON";
|
||||
#else
|
||||
@@ -266,8 +292,8 @@ using std::ptrdiff_t;
|
||||
*/
|
||||
|
||||
#include "src/Core/util/Constants.h"
|
||||
#include "src/Core/util/ForwardDeclarations.h"
|
||||
#include "src/Core/util/Meta.h"
|
||||
#include "src/Core/util/ForwardDeclarations.h"
|
||||
#include "src/Core/util/StaticAssert.h"
|
||||
#include "src/Core/util/XprHelper.h"
|
||||
#include "src/Core/util/Memory.h"
|
||||
@@ -280,39 +306,47 @@ using std::ptrdiff_t;
|
||||
// Use AVX for floats and doubles, SSE for integers
|
||||
#include "src/Core/arch/SSE/PacketMath.h"
|
||||
#include "src/Core/arch/SSE/Complex.h"
|
||||
#include "src/Core/arch/SSE/MathFunctions.h"
|
||||
#include "src/Core/arch/AVX/PacketMath.h"
|
||||
#include "src/Core/arch/AVX/MathFunctions.h"
|
||||
#include "src/Core/arch/AVX/Complex.h"
|
||||
#include "src/Core/arch/AVX/TypeCasting.h"
|
||||
#elif defined EIGEN_VECTORIZE_SSE
|
||||
#include "src/Core/arch/SSE/PacketMath.h"
|
||||
#include "src/Core/arch/SSE/MathFunctions.h"
|
||||
#include "src/Core/arch/SSE/Complex.h"
|
||||
#elif defined EIGEN_VECTORIZE_ALTIVEC
|
||||
#include "src/Core/arch/SSE/TypeCasting.h"
|
||||
#elif defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
|
||||
#include "src/Core/arch/AltiVec/PacketMath.h"
|
||||
#include "src/Core/arch/AltiVec/MathFunctions.h"
|
||||
#include "src/Core/arch/AltiVec/Complex.h"
|
||||
#elif defined EIGEN_VECTORIZE_NEON
|
||||
#include "src/Core/arch/NEON/PacketMath.h"
|
||||
#include "src/Core/arch/NEON/MathFunctions.h"
|
||||
#include "src/Core/arch/NEON/Complex.h"
|
||||
#endif
|
||||
|
||||
#if defined EIGEN_VECTORIZE_CUDA
|
||||
#include "src/Core/arch/CUDA/PacketMath.h"
|
||||
#include "src/Core/arch/CUDA/MathFunctions.h"
|
||||
#endif
|
||||
|
||||
#include "src/Core/arch/Default/Settings.h"
|
||||
|
||||
#include "src/Core/functors/BinaryFunctors.h"
|
||||
#include "src/Core/functors/UnaryFunctors.h"
|
||||
#include "src/Core/functors/NullaryFunctors.h"
|
||||
#include "src/Core/functors/StlFunctors.h"
|
||||
#include "src/Core/functors/AssignmentFunctors.h"
|
||||
|
||||
#include "src/Core/DenseCoeffsBase.h"
|
||||
#include "src/Core/DenseBase.h"
|
||||
#include "src/Core/MatrixBase.h"
|
||||
#include "src/Core/EigenBase.h"
|
||||
|
||||
#ifdef EIGEN_ENABLE_EVALUATORS
|
||||
#include "src/Core/functors/AssignmentFunctors.h"
|
||||
#include "src/Core/Product.h"
|
||||
#include "src/Core/CoreEvaluators.h"
|
||||
#include "src/Core/AssignEvaluator.h"
|
||||
#include "src/Core/ProductEvaluators.h"
|
||||
#endif
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN // work around Doxygen bug triggered by Assign.h r814874
|
||||
// at least confirmed with Doxygen 1.5.5 and 1.5.6
|
||||
@@ -323,7 +357,9 @@ using std::ptrdiff_t;
|
||||
#include "src/Core/util/BlasUtil.h"
|
||||
#include "src/Core/DenseStorage.h"
|
||||
#include "src/Core/NestByValue.h"
|
||||
#include "src/Core/ForceAlignedAccess.h"
|
||||
|
||||
// #include "src/Core/ForceAlignedAccess.h"
|
||||
|
||||
#include "src/Core/ReturnByValue.h"
|
||||
#include "src/Core/NoAlias.h"
|
||||
#include "src/Core/PlainObjectBase.h"
|
||||
@@ -336,12 +372,12 @@ using std::ptrdiff_t;
|
||||
#include "src/Core/SelfCwiseBinaryOp.h"
|
||||
#include "src/Core/Dot.h"
|
||||
#include "src/Core/StableNorm.h"
|
||||
#include "src/Core/MapBase.h"
|
||||
#include "src/Core/Stride.h"
|
||||
#include "src/Core/MapBase.h"
|
||||
#include "src/Core/Map.h"
|
||||
#include "src/Core/Ref.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"
|
||||
@@ -354,14 +390,14 @@ using std::ptrdiff_t;
|
||||
#include "src/Core/IO.h"
|
||||
#include "src/Core/Swap.h"
|
||||
#include "src/Core/CommaInitializer.h"
|
||||
#include "src/Core/Flagged.h"
|
||||
#include "src/Core/ProductBase.h"
|
||||
#include "src/Core/GeneralProduct.h"
|
||||
#include "src/Core/Solve.h"
|
||||
#include "src/Core/Inverse.h"
|
||||
#include "src/Core/TriangularMatrix.h"
|
||||
#include "src/Core/SelfAdjointView.h"
|
||||
#include "src/Core/products/GeneralBlockPanelKernel.h"
|
||||
#include "src/Core/products/Parallelizer.h"
|
||||
#include "src/Core/products/CoeffBasedProduct.h"
|
||||
#include "src/Core/ProductEvaluators.h"
|
||||
#include "src/Core/products/GeneralMatrixVector.h"
|
||||
#include "src/Core/products/GeneralMatrixMatrix.h"
|
||||
#include "src/Core/SolveTriangular.h"
|
||||
|
||||
@@ -9,10 +9,6 @@
|
||||
#include "LU"
|
||||
#include <limits>
|
||||
|
||||
#ifndef M_PI
|
||||
#define M_PI 3.14159265358979323846
|
||||
#endif
|
||||
|
||||
/** \defgroup Geometry_Module Geometry module
|
||||
*
|
||||
*
|
||||
|
||||
@@ -12,26 +12,26 @@
|
||||
* This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse.
|
||||
* Those solvers are accessible via the following classes:
|
||||
* - ConjugateGradient for selfadjoint (hermitian) matrices,
|
||||
* - LeastSquaresConjugateGradient for rectangular least-square problems,
|
||||
* - BiCGSTAB for general square matrices.
|
||||
*
|
||||
* These iterative solvers are associated with some preconditioners:
|
||||
* - IdentityPreconditioner - not really useful
|
||||
* - DiagonalPreconditioner - also called JAcobi preconditioner, work very well on diagonal dominant matrices.
|
||||
* - IncompleteILUT - incomplete LU factorization with dual thresholding
|
||||
* - DiagonalPreconditioner - also called Jacobi preconditioner, work very well on diagonal dominant matrices.
|
||||
* - IncompleteLUT - incomplete LU factorization with dual thresholding
|
||||
*
|
||||
* Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport.
|
||||
*
|
||||
* \code
|
||||
* #include <Eigen/IterativeLinearSolvers>
|
||||
* \endcode
|
||||
\code
|
||||
#include <Eigen/IterativeLinearSolvers>
|
||||
\endcode
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/SparseSolve.h"
|
||||
|
||||
#include "src/IterativeLinearSolvers/SolveWithGuess.h"
|
||||
#include "src/IterativeLinearSolvers/IterativeSolverBase.h"
|
||||
#include "src/IterativeLinearSolvers/BasicPreconditioners.h"
|
||||
#include "src/IterativeLinearSolvers/ConjugateGradient.h"
|
||||
#include "src/IterativeLinearSolvers/LeastSquareConjugateGradient.h"
|
||||
#include "src/IterativeLinearSolvers/BiCGSTAB.h"
|
||||
#include "src/IterativeLinearSolvers/IncompleteLUT.h"
|
||||
|
||||
|
||||
3
Eigen/LU
3
Eigen/LU
@@ -16,7 +16,6 @@
|
||||
* \endcode
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/Kernel.h"
|
||||
#include "src/misc/Image.h"
|
||||
#include "src/LU/FullPivLU.h"
|
||||
@@ -25,7 +24,7 @@
|
||||
#include "src/LU/PartialPivLU_MKL.h"
|
||||
#endif
|
||||
#include "src/LU/Determinant.h"
|
||||
#include "src/LU/Inverse.h"
|
||||
#include "src/LU/InverseImpl.h"
|
||||
|
||||
// Use the SSE optimized version whenever possible. At the moment the
|
||||
// SSE version doesn't compile when AVX is enabled
|
||||
|
||||
@@ -35,12 +35,8 @@ extern "C" {
|
||||
*
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/SparseSolve.h"
|
||||
|
||||
#include "src/PaStiXSupport/PaStiXSupport.h"
|
||||
|
||||
|
||||
#include "src/Core/util/ReenableStupidWarnings.h"
|
||||
|
||||
#endif // EIGEN_PASTIXSUPPORT_MODULE_H
|
||||
|
||||
1
Eigen/QR
1
Eigen/QR
@@ -24,7 +24,6 @@
|
||||
* \endcode
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/QR/HouseholderQR.h"
|
||||
#include "src/QR/FullPivHouseholderQR.h"
|
||||
#include "src/QR/ColPivHouseholderQR.h"
|
||||
|
||||
@@ -21,8 +21,6 @@
|
||||
*
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/SparseSolve.h"
|
||||
#include "src/CholmodSupport/CholmodSupport.h"
|
||||
#include "src/SPQRSupport/SuiteSparseQRSupport.h"
|
||||
|
||||
|
||||
10
Eigen/SVD
10
Eigen/SVD
@@ -12,21 +12,25 @@
|
||||
*
|
||||
*
|
||||
* This module provides SVD decomposition for matrices (both real and complex).
|
||||
* This decomposition is accessible via the following MatrixBase method:
|
||||
* Two decomposition algorithms are provided:
|
||||
* - JacobiSVD implementing two-sided Jacobi iterations is numerically very accurate, fast for small matrices, but very slow for larger ones.
|
||||
* - BDCSVD implementing a recursive divide & conquer strategy on top of an upper-bidiagonalization which remains fast for large problems.
|
||||
* These decompositions are accessible via the respective classes and following MatrixBase methods:
|
||||
* - MatrixBase::jacobiSvd()
|
||||
* - MatrixBase::bdcSvd()
|
||||
*
|
||||
* \code
|
||||
* #include <Eigen/SVD>
|
||||
* \endcode
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/SVD/UpperBidiagonalization.h"
|
||||
#include "src/SVD/SVDBase.h"
|
||||
#include "src/SVD/JacobiSVD.h"
|
||||
#include "src/SVD/BDCSVD.h"
|
||||
#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
|
||||
#include "src/SVD/JacobiSVD_MKL.h"
|
||||
#endif
|
||||
#include "src/SVD/UpperBidiagonalization.h"
|
||||
|
||||
#include "src/Core/util/ReenableStupidWarnings.h"
|
||||
|
||||
|
||||
@@ -11,9 +11,9 @@
|
||||
* - \ref SparseQR_Module
|
||||
* - \ref IterativeLinearSolvers_Module
|
||||
*
|
||||
* \code
|
||||
* #include <Eigen/Sparse>
|
||||
* \endcode
|
||||
\code
|
||||
#include <Eigen/Sparse>
|
||||
\endcode
|
||||
*/
|
||||
|
||||
#include "SparseCore"
|
||||
|
||||
@@ -34,8 +34,6 @@
|
||||
#error The SparseCholesky module has nothing to offer in MPL2 only mode
|
||||
#endif
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/SparseSolve.h"
|
||||
#include "src/SparseCholesky/SimplicialCholesky.h"
|
||||
|
||||
#ifndef EIGEN_MPL2_ONLY
|
||||
|
||||
@@ -26,37 +26,35 @@
|
||||
* This module depends on: Core.
|
||||
*/
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
/** The type used to identify a general sparse storage. */
|
||||
struct Sparse {};
|
||||
|
||||
}
|
||||
|
||||
#include "src/SparseCore/SparseUtil.h"
|
||||
#include "src/SparseCore/SparseMatrixBase.h"
|
||||
#include "src/SparseCore/SparseAssign.h"
|
||||
#include "src/SparseCore/CompressedStorage.h"
|
||||
#include "src/SparseCore/AmbiVector.h"
|
||||
#include "src/SparseCore/SparseCompressedBase.h"
|
||||
#include "src/SparseCore/SparseMatrix.h"
|
||||
#include "src/SparseCore/SparseMap.h"
|
||||
#include "src/SparseCore/MappedSparseMatrix.h"
|
||||
#include "src/SparseCore/SparseVector.h"
|
||||
#include "src/SparseCore/SparseBlock.h"
|
||||
#include "src/SparseCore/SparseTranspose.h"
|
||||
#include "src/SparseCore/SparseRef.h"
|
||||
#include "src/SparseCore/SparseCwiseUnaryOp.h"
|
||||
#include "src/SparseCore/SparseCwiseBinaryOp.h"
|
||||
#include "src/SparseCore/SparseTranspose.h"
|
||||
#include "src/SparseCore/SparseBlock.h"
|
||||
#include "src/SparseCore/SparseDot.h"
|
||||
#include "src/SparseCore/SparsePermutation.h"
|
||||
#include "src/SparseCore/SparseRedux.h"
|
||||
#include "src/SparseCore/SparseFuzzy.h"
|
||||
#include "src/SparseCore/SparseView.h"
|
||||
#include "src/SparseCore/SparseDiagonalProduct.h"
|
||||
#include "src/SparseCore/ConservativeSparseSparseProduct.h"
|
||||
#include "src/SparseCore/SparseSparseProductWithPruning.h"
|
||||
#include "src/SparseCore/SparseProduct.h"
|
||||
#include "src/SparseCore/SparseDenseProduct.h"
|
||||
#include "src/SparseCore/SparseDiagonalProduct.h"
|
||||
#include "src/SparseCore/SparseTriangularView.h"
|
||||
#include "src/SparseCore/SparseSelfAdjointView.h"
|
||||
#include "src/SparseCore/SparseTriangularView.h"
|
||||
#include "src/SparseCore/TriangularSolver.h"
|
||||
#include "src/SparseCore/SparseView.h"
|
||||
#include "src/SparseCore/SparsePermutation.h"
|
||||
#include "src/SparseCore/SparseFuzzy.h"
|
||||
#include "src/SparseCore/SparseSolverBase.h"
|
||||
|
||||
#include "src/Core/util/ReenableStupidWarnings.h"
|
||||
|
||||
|
||||
@@ -20,9 +20,6 @@
|
||||
* Please, see the documentation of the SparseLU class for more details.
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/SparseSolve.h"
|
||||
|
||||
// Ordering interface
|
||||
#include "OrderingMethods"
|
||||
|
||||
|
||||
@@ -21,9 +21,6 @@
|
||||
*
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/SparseSolve.h"
|
||||
|
||||
#include "OrderingMethods"
|
||||
#include "src/SparseCore/SparseColEtree.h"
|
||||
#include "src/SparseQR/SparseQR.h"
|
||||
|
||||
@@ -14,7 +14,7 @@
|
||||
#include "Core"
|
||||
#include <deque>
|
||||
|
||||
#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
|
||||
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 /* MSVC auto aligns in 64 bit builds */
|
||||
|
||||
#define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...)
|
||||
|
||||
|
||||
@@ -13,7 +13,7 @@
|
||||
#include "Core"
|
||||
#include <list>
|
||||
|
||||
#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
|
||||
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 /* MSVC auto aligns in 64 bit builds */
|
||||
|
||||
#define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...)
|
||||
|
||||
|
||||
@@ -14,7 +14,7 @@
|
||||
#include "Core"
|
||||
#include <vector>
|
||||
|
||||
#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
|
||||
#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 /* MSVC auto aligns in 64 bit builds */
|
||||
|
||||
#define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...)
|
||||
|
||||
|
||||
@@ -48,12 +48,8 @@ namespace Eigen { struct SluMatrix; }
|
||||
*
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/SparseSolve.h"
|
||||
|
||||
#include "src/SuperLUSupport/SuperLUSupport.h"
|
||||
|
||||
|
||||
#include "src/Core/util/ReenableStupidWarnings.h"
|
||||
|
||||
#endif // EIGEN_SUPERLUSUPPORT_MODULE_H
|
||||
|
||||
@@ -26,9 +26,6 @@ extern "C" {
|
||||
*
|
||||
*/
|
||||
|
||||
#include "src/misc/Solve.h"
|
||||
#include "src/misc/SparseSolve.h"
|
||||
|
||||
#include "src/UmfPackSupport/UmfPackSupport.h"
|
||||
|
||||
#include "src/Core/util/ReenableStupidWarnings.h"
|
||||
|
||||
@@ -59,7 +59,8 @@ template<typename _MatrixType, int _UpLo> class LDLT
|
||||
};
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
|
||||
typedef typename MatrixType::Index Index;
|
||||
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
|
||||
typedef typename MatrixType::StorageIndex StorageIndex;
|
||||
typedef Matrix<Scalar, RowsAtCompileTime, 1, Options, MaxRowsAtCompileTime, 1> TmpMatrixType;
|
||||
|
||||
typedef Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> TranspositionType;
|
||||
@@ -85,7 +86,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
|
||||
* according to the specified problem \a size.
|
||||
* \sa LDLT()
|
||||
*/
|
||||
LDLT(Index size)
|
||||
explicit LDLT(Index size)
|
||||
: m_matrix(size, size),
|
||||
m_transpositions(size),
|
||||
m_temporary(size),
|
||||
@@ -98,7 +99,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
|
||||
* This calculates the decomposition for the input \a matrix.
|
||||
* \sa LDLT(Index size)
|
||||
*/
|
||||
LDLT(const MatrixType& matrix)
|
||||
explicit LDLT(const MatrixType& matrix)
|
||||
: m_matrix(matrix.rows(), matrix.cols()),
|
||||
m_transpositions(matrix.rows()),
|
||||
m_temporary(matrix.rows()),
|
||||
@@ -175,13 +176,13 @@ template<typename _MatrixType, int _UpLo> class LDLT
|
||||
* \sa MatrixBase::ldlt(), SelfAdjointView::ldlt()
|
||||
*/
|
||||
template<typename Rhs>
|
||||
inline const internal::solve_retval<LDLT, Rhs>
|
||||
inline const Solve<LDLT, Rhs>
|
||||
solve(const MatrixBase<Rhs>& b) const
|
||||
{
|
||||
eigen_assert(m_isInitialized && "LDLT is not initialized.");
|
||||
eigen_assert(m_matrix.rows()==b.rows()
|
||||
&& "LDLT::solve(): invalid number of rows of the right hand side matrix b");
|
||||
return internal::solve_retval<LDLT, Rhs>(*this, b.derived());
|
||||
return Solve<LDLT, Rhs>(*this, b.derived());
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
@@ -217,8 +218,19 @@ template<typename _MatrixType, int _UpLo> class LDLT
|
||||
eigen_assert(m_isInitialized && "LDLT is not initialized.");
|
||||
return Success;
|
||||
}
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename RhsType, typename DstType>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void _solve_impl(const RhsType &rhs, DstType &dst) const;
|
||||
#endif
|
||||
|
||||
protected:
|
||||
|
||||
static void check_template_parameters()
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
|
||||
}
|
||||
|
||||
/** \internal
|
||||
* Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U.
|
||||
@@ -245,8 +257,7 @@ template<> struct ldlt_inplace<Lower>
|
||||
using std::abs;
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename MatrixType::RealScalar RealScalar;
|
||||
typedef typename MatrixType::Index Index;
|
||||
typedef typename TranspositionType::StorageIndexType IndexType;
|
||||
typedef typename TranspositionType::StorageIndex IndexType;
|
||||
eigen_assert(mat.rows()==mat.cols());
|
||||
const Index size = mat.rows();
|
||||
|
||||
@@ -303,9 +314,9 @@ template<> struct ldlt_inplace<Lower>
|
||||
}
|
||||
|
||||
// In some previous versions of Eigen (e.g., 3.2.1), the scaling was omitted if the pivot
|
||||
// was smaller than the cutoff value. However, soince LDLT is not rank-revealing
|
||||
// we should only make sure we do not introduce INF or NaN values.
|
||||
// LAPACK also uses 0 as the cutoff value.
|
||||
// was smaller than the cutoff value. However, since LDLT is not rank-revealing
|
||||
// we should only make sure that we do not introduce INF or NaN values.
|
||||
// Remark that LAPACK also uses 0 as the cutoff value.
|
||||
RealScalar realAkk = numext::real(mat.coeffRef(k,k));
|
||||
if((rs>0) && (abs(realAkk) > RealScalar(0)))
|
||||
A21 /= realAkk;
|
||||
@@ -336,7 +347,6 @@ template<> struct ldlt_inplace<Lower>
|
||||
using numext::isfinite;
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename MatrixType::RealScalar RealScalar;
|
||||
typedef typename MatrixType::Index Index;
|
||||
|
||||
const Index size = mat.rows();
|
||||
eigen_assert(mat.cols() == size && w.size()==size);
|
||||
@@ -400,16 +410,16 @@ template<typename MatrixType> struct LDLT_Traits<MatrixType,Lower>
|
||||
{
|
||||
typedef const TriangularView<const MatrixType, UnitLower> MatrixL;
|
||||
typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
|
||||
static inline MatrixL getL(const MatrixType& m) { return m; }
|
||||
static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
|
||||
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
|
||||
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
|
||||
};
|
||||
|
||||
template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
|
||||
{
|
||||
typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
|
||||
typedef const TriangularView<const MatrixType, UnitUpper> MatrixU;
|
||||
static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
|
||||
static inline MatrixU getU(const MatrixType& m) { return m; }
|
||||
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); }
|
||||
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
@@ -419,6 +429,8 @@ template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
|
||||
template<typename MatrixType, int _UpLo>
|
||||
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
|
||||
{
|
||||
check_template_parameters();
|
||||
|
||||
eigen_assert(a.rows()==a.cols());
|
||||
const Index size = a.rows();
|
||||
|
||||
@@ -427,6 +439,7 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
|
||||
m_transpositions.resize(size);
|
||||
m_isInitialized = false;
|
||||
m_temporary.resize(size);
|
||||
m_sign = internal::ZeroSign;
|
||||
|
||||
internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign);
|
||||
|
||||
@@ -441,9 +454,9 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
|
||||
*/
|
||||
template<typename MatrixType, int _UpLo>
|
||||
template<typename Derived>
|
||||
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename NumTraits<typename MatrixType::Scalar>::Real& sigma)
|
||||
LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename LDLT<MatrixType,_UpLo>::RealScalar& sigma)
|
||||
{
|
||||
typedef typename TranspositionType::StorageIndexType IndexType;
|
||||
typedef typename TranspositionType::StorageIndex IndexType;
|
||||
const Index size = w.rows();
|
||||
if (m_isInitialized)
|
||||
{
|
||||
@@ -466,52 +479,45 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Deri
|
||||
return *this;
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
template<typename _MatrixType, int _UpLo, typename Rhs>
|
||||
struct solve_retval<LDLT<_MatrixType,_UpLo>, Rhs>
|
||||
: solve_retval_base<LDLT<_MatrixType,_UpLo>, Rhs>
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename _MatrixType, int _UpLo>
|
||||
template<typename RhsType, typename DstType>
|
||||
void LDLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
|
||||
{
|
||||
typedef LDLT<_MatrixType,_UpLo> LDLTType;
|
||||
EIGEN_MAKE_SOLVE_HELPERS(LDLTType,Rhs)
|
||||
eigen_assert(rhs.rows() == rows());
|
||||
// dst = P b
|
||||
dst = m_transpositions * rhs;
|
||||
|
||||
template<typename Dest> void evalTo(Dest& dst) const
|
||||
// dst = L^-1 (P b)
|
||||
matrixL().solveInPlace(dst);
|
||||
|
||||
// dst = D^-1 (L^-1 P b)
|
||||
// more precisely, use pseudo-inverse of D (see bug 241)
|
||||
using std::abs;
|
||||
const typename Diagonal<const MatrixType>::RealReturnType vecD(vectorD());
|
||||
// In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon
|
||||
// as motivated by LAPACK's xGELSS:
|
||||
// RealScalar tolerance = numext::maxi(vecD.array().abs().maxCoeff() * NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
|
||||
// However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
|
||||
// diagonal element is not well justified and leads to numerical issues in some cases.
|
||||
// Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
|
||||
RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest();
|
||||
|
||||
for (Index i = 0; i < vecD.size(); ++i)
|
||||
{
|
||||
eigen_assert(rhs().rows() == dec().matrixLDLT().rows());
|
||||
// dst = P b
|
||||
dst = dec().transpositionsP() * rhs();
|
||||
|
||||
// dst = L^-1 (P b)
|
||||
dec().matrixL().solveInPlace(dst);
|
||||
|
||||
// dst = D^-1 (L^-1 P b)
|
||||
// more precisely, use pseudo-inverse of D (see bug 241)
|
||||
using std::abs;
|
||||
EIGEN_USING_STD_MATH(max);
|
||||
typedef typename LDLTType::MatrixType MatrixType;
|
||||
typedef typename LDLTType::RealScalar RealScalar;
|
||||
const typename Diagonal<const MatrixType>::RealReturnType vectorD(dec().vectorD());
|
||||
// In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon
|
||||
// as motivated by LAPACK's xGELSS:
|
||||
// RealScalar tolerance = (max)(vectorD.array().abs().maxCoeff() *NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
|
||||
// However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
|
||||
// diagonal element is not well justified and to numerical issues in some cases.
|
||||
// Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
|
||||
RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest();
|
||||
for (Index i = 0; i < vectorD.size(); ++i) {
|
||||
if(abs(vectorD(i)) > tolerance)
|
||||
dst.row(i) /= vectorD(i);
|
||||
else
|
||||
dst.row(i).setZero();
|
||||
}
|
||||
|
||||
// dst = L^-T (D^-1 L^-1 P b)
|
||||
dec().matrixU().solveInPlace(dst);
|
||||
|
||||
// dst = P^-1 (L^-T D^-1 L^-1 P b) = A^-1 b
|
||||
dst = dec().transpositionsP().transpose() * dst;
|
||||
if(abs(vecD(i)) > tolerance)
|
||||
dst.row(i) /= vecD(i);
|
||||
else
|
||||
dst.row(i).setZero();
|
||||
}
|
||||
};
|
||||
|
||||
// dst = L^-T (D^-1 L^-1 P b)
|
||||
matrixU().solveInPlace(dst);
|
||||
|
||||
// dst = P^-1 (L^-T D^-1 L^-1 P b) = A^-1 b
|
||||
dst = m_transpositions.transpose() * dst;
|
||||
}
|
||||
#endif
|
||||
|
||||
/** \internal use x = ldlt_object.solve(x);
|
||||
*
|
||||
|
||||
@@ -59,7 +59,8 @@ template<typename _MatrixType, int _UpLo> class LLT
|
||||
};
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
|
||||
typedef typename MatrixType::Index Index;
|
||||
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
|
||||
typedef typename MatrixType::StorageIndex StorageIndex;
|
||||
|
||||
enum {
|
||||
PacketSize = internal::packet_traits<Scalar>::size,
|
||||
@@ -83,10 +84,10 @@ template<typename _MatrixType, int _UpLo> class LLT
|
||||
* according to the specified problem \a size.
|
||||
* \sa LLT()
|
||||
*/
|
||||
LLT(Index size) : m_matrix(size, size),
|
||||
explicit LLT(Index size) : m_matrix(size, size),
|
||||
m_isInitialized(false) {}
|
||||
|
||||
LLT(const MatrixType& matrix)
|
||||
explicit LLT(const MatrixType& matrix)
|
||||
: m_matrix(matrix.rows(), matrix.cols()),
|
||||
m_isInitialized(false)
|
||||
{
|
||||
@@ -118,13 +119,13 @@ template<typename _MatrixType, int _UpLo> class LLT
|
||||
* \sa solveInPlace(), MatrixBase::llt(), SelfAdjointView::llt()
|
||||
*/
|
||||
template<typename Rhs>
|
||||
inline const internal::solve_retval<LLT, Rhs>
|
||||
inline const Solve<LLT, Rhs>
|
||||
solve(const MatrixBase<Rhs>& b) const
|
||||
{
|
||||
eigen_assert(m_isInitialized && "LLT is not initialized.");
|
||||
eigen_assert(m_matrix.rows()==b.rows()
|
||||
&& "LLT::solve(): invalid number of rows of the right hand side matrix b");
|
||||
return internal::solve_retval<LLT, Rhs>(*this, b.derived());
|
||||
return Solve<LLT, Rhs>(*this, b.derived());
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
@@ -161,8 +162,20 @@ template<typename _MatrixType, int _UpLo> class LLT
|
||||
|
||||
template<typename VectorType>
|
||||
LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename RhsType, typename DstType>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void _solve_impl(const RhsType &rhs, DstType &dst) const;
|
||||
#endif
|
||||
|
||||
protected:
|
||||
|
||||
static void check_template_parameters()
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
|
||||
}
|
||||
|
||||
/** \internal
|
||||
* Used to compute and store L
|
||||
* The strict upper part is not used and even not initialized.
|
||||
@@ -177,12 +190,11 @@ namespace internal {
|
||||
template<typename Scalar, int UpLo> struct llt_inplace;
|
||||
|
||||
template<typename MatrixType, typename VectorType>
|
||||
static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
|
||||
static Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
|
||||
{
|
||||
using std::sqrt;
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename MatrixType::RealScalar RealScalar;
|
||||
typedef typename MatrixType::Index Index;
|
||||
typedef typename MatrixType::ColXpr ColXpr;
|
||||
typedef typename internal::remove_all<ColXpr>::type ColXprCleaned;
|
||||
typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
|
||||
@@ -251,10 +263,9 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
|
||||
{
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
template<typename MatrixType>
|
||||
static typename MatrixType::Index unblocked(MatrixType& mat)
|
||||
static Index unblocked(MatrixType& mat)
|
||||
{
|
||||
using std::sqrt;
|
||||
typedef typename MatrixType::Index Index;
|
||||
|
||||
eigen_assert(mat.rows()==mat.cols());
|
||||
const Index size = mat.rows();
|
||||
@@ -278,9 +289,8 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
|
||||
}
|
||||
|
||||
template<typename MatrixType>
|
||||
static typename MatrixType::Index blocked(MatrixType& m)
|
||||
static Index blocked(MatrixType& m)
|
||||
{
|
||||
typedef typename MatrixType::Index Index;
|
||||
eigen_assert(m.rows()==m.cols());
|
||||
Index size = m.rows();
|
||||
if(size<32)
|
||||
@@ -311,7 +321,7 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
|
||||
}
|
||||
|
||||
template<typename MatrixType, typename VectorType>
|
||||
static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
|
||||
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
|
||||
{
|
||||
return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
|
||||
}
|
||||
@@ -322,19 +332,19 @@ template<typename Scalar> struct llt_inplace<Scalar, Upper>
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
|
||||
template<typename MatrixType>
|
||||
static EIGEN_STRONG_INLINE typename MatrixType::Index unblocked(MatrixType& mat)
|
||||
static EIGEN_STRONG_INLINE Index unblocked(MatrixType& mat)
|
||||
{
|
||||
Transpose<MatrixType> matt(mat);
|
||||
return llt_inplace<Scalar, Lower>::unblocked(matt);
|
||||
}
|
||||
template<typename MatrixType>
|
||||
static EIGEN_STRONG_INLINE typename MatrixType::Index blocked(MatrixType& mat)
|
||||
static EIGEN_STRONG_INLINE Index blocked(MatrixType& mat)
|
||||
{
|
||||
Transpose<MatrixType> matt(mat);
|
||||
return llt_inplace<Scalar, Lower>::blocked(matt);
|
||||
}
|
||||
template<typename MatrixType, typename VectorType>
|
||||
static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
|
||||
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
|
||||
{
|
||||
Transpose<MatrixType> matt(mat);
|
||||
return llt_inplace<Scalar, Lower>::rankUpdate(matt, vec.conjugate(), sigma);
|
||||
@@ -345,8 +355,8 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
|
||||
{
|
||||
typedef const TriangularView<const MatrixType, Lower> MatrixL;
|
||||
typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU;
|
||||
static inline MatrixL getL(const MatrixType& m) { return m; }
|
||||
static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
|
||||
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
|
||||
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
|
||||
static bool inplace_decomposition(MatrixType& m)
|
||||
{ return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; }
|
||||
};
|
||||
@@ -355,8 +365,8 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
|
||||
{
|
||||
typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL;
|
||||
typedef const TriangularView<const MatrixType, Upper> MatrixU;
|
||||
static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
|
||||
static inline MatrixU getU(const MatrixType& m) { return m; }
|
||||
static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); }
|
||||
static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
|
||||
static bool inplace_decomposition(MatrixType& m)
|
||||
{ return llt_inplace<typename MatrixType::Scalar, Upper>::blocked(m)==-1; }
|
||||
};
|
||||
@@ -373,6 +383,8 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
|
||||
template<typename MatrixType, int _UpLo>
|
||||
LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
|
||||
{
|
||||
check_template_parameters();
|
||||
|
||||
eigen_assert(a.rows()==a.cols());
|
||||
const Index size = a.rows();
|
||||
m_matrix.resize(size, size);
|
||||
@@ -404,22 +416,16 @@ LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, c
|
||||
|
||||
return *this;
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
template<typename _MatrixType, int UpLo, typename Rhs>
|
||||
struct solve_retval<LLT<_MatrixType, UpLo>, Rhs>
|
||||
: solve_retval_base<LLT<_MatrixType, UpLo>, Rhs>
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename _MatrixType,int _UpLo>
|
||||
template<typename RhsType, typename DstType>
|
||||
void LLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
|
||||
{
|
||||
typedef LLT<_MatrixType,UpLo> LLTType;
|
||||
EIGEN_MAKE_SOLVE_HELPERS(LLTType,Rhs)
|
||||
|
||||
template<typename Dest> void evalTo(Dest& dst) const
|
||||
{
|
||||
dst = rhs();
|
||||
dec().solveInPlace(dst);
|
||||
}
|
||||
};
|
||||
dst = rhs;
|
||||
solveInPlace(dst);
|
||||
}
|
||||
#endif
|
||||
|
||||
/** \internal use x = llt_object.solve(x);
|
||||
*
|
||||
|
||||
@@ -46,7 +46,7 @@ template<typename Scalar> struct mkl_llt;
|
||||
template<> struct mkl_llt<EIGTYPE> \
|
||||
{ \
|
||||
template<typename MatrixType> \
|
||||
static inline typename MatrixType::Index potrf(MatrixType& m, char uplo) \
|
||||
static inline Index potrf(MatrixType& m, char uplo) \
|
||||
{ \
|
||||
lapack_int matrix_order; \
|
||||
lapack_int size, lda, info, StorageOrder; \
|
||||
@@ -60,30 +60,30 @@ template<> struct mkl_llt<EIGTYPE> \
|
||||
lda = m.outerStride(); \
|
||||
\
|
||||
info = LAPACKE_##MKLPREFIX##potrf( matrix_order, uplo, size, (MKLTYPE*)a, lda ); \
|
||||
info = (info==0) ? Success : NumericalIssue; \
|
||||
info = (info==0) ? -1 : info>0 ? info-1 : size; \
|
||||
return info; \
|
||||
} \
|
||||
}; \
|
||||
template<> struct llt_inplace<EIGTYPE, Lower> \
|
||||
{ \
|
||||
template<typename MatrixType> \
|
||||
static typename MatrixType::Index blocked(MatrixType& m) \
|
||||
static Index blocked(MatrixType& m) \
|
||||
{ \
|
||||
return mkl_llt<EIGTYPE>::potrf(m, 'L'); \
|
||||
} \
|
||||
template<typename MatrixType, typename VectorType> \
|
||||
static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
|
||||
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
|
||||
{ return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \
|
||||
}; \
|
||||
template<> struct llt_inplace<EIGTYPE, Upper> \
|
||||
{ \
|
||||
template<typename MatrixType> \
|
||||
static typename MatrixType::Index blocked(MatrixType& m) \
|
||||
static Index blocked(MatrixType& m) \
|
||||
{ \
|
||||
return mkl_llt<EIGTYPE>::potrf(m, 'U'); \
|
||||
} \
|
||||
template<typename MatrixType, typename VectorType> \
|
||||
static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
|
||||
static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
|
||||
{ \
|
||||
Transpose<MatrixType> matt(mat); \
|
||||
return llt_inplace<EIGTYPE, Lower>::rankUpdate(matt, vec.conjugate(), sigma); \
|
||||
|
||||
@@ -48,8 +48,8 @@ void cholmod_configure_matrix(CholmodType& mat)
|
||||
/** Wraps the Eigen sparse matrix \a mat into a Cholmod sparse matrix object.
|
||||
* Note that the data are shared.
|
||||
*/
|
||||
template<typename _Scalar, int _Options, typename _Index>
|
||||
cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat)
|
||||
template<typename _Scalar, int _Options, typename _StorageIndex>
|
||||
cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_StorageIndex>& mat)
|
||||
{
|
||||
cholmod_sparse res;
|
||||
res.nzmax = mat.nonZeros();
|
||||
@@ -74,11 +74,11 @@ cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat)
|
||||
res.dtype = 0;
|
||||
res.stype = -1;
|
||||
|
||||
if (internal::is_same<_Index,int>::value)
|
||||
if (internal::is_same<_StorageIndex,int>::value)
|
||||
{
|
||||
res.itype = CHOLMOD_INT;
|
||||
}
|
||||
else if (internal::is_same<_Index,UF_long>::value)
|
||||
else if (internal::is_same<_StorageIndex,UF_long>::value)
|
||||
{
|
||||
res.itype = CHOLMOD_LONG;
|
||||
}
|
||||
@@ -105,7 +105,7 @@ const cholmod_sparse viewAsCholmod(const SparseMatrix<_Scalar,_Options,_Index>&
|
||||
/** Returns a view of the Eigen sparse matrix \a mat as Cholmod sparse matrix.
|
||||
* The data are not copied but shared. */
|
||||
template<typename _Scalar, int _Options, typename _Index, unsigned int UpLo>
|
||||
cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
|
||||
cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<const SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
|
||||
{
|
||||
cholmod_sparse res = viewAsCholmod(mat.matrix().const_cast_derived());
|
||||
|
||||
@@ -138,12 +138,12 @@ cholmod_dense viewAsCholmod(MatrixBase<Derived>& mat)
|
||||
|
||||
/** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix.
|
||||
* The data are not copied but shared. */
|
||||
template<typename Scalar, int Flags, typename Index>
|
||||
MappedSparseMatrix<Scalar,Flags,Index> viewAsEigen(cholmod_sparse& cm)
|
||||
template<typename Scalar, int Flags, typename StorageIndex>
|
||||
MappedSparseMatrix<Scalar,Flags,StorageIndex> viewAsEigen(cholmod_sparse& cm)
|
||||
{
|
||||
return MappedSparseMatrix<Scalar,Flags,Index>
|
||||
(cm.nrow, cm.ncol, static_cast<Index*>(cm.p)[cm.ncol],
|
||||
static_cast<Index*>(cm.p), static_cast<Index*>(cm.i),static_cast<Scalar*>(cm.x) );
|
||||
return MappedSparseMatrix<Scalar,Flags,StorageIndex>
|
||||
(cm.nrow, cm.ncol, static_cast<StorageIndex*>(cm.p)[cm.ncol],
|
||||
static_cast<StorageIndex*>(cm.p), static_cast<StorageIndex*>(cm.i),static_cast<Scalar*>(cm.x) );
|
||||
}
|
||||
|
||||
enum CholmodMode {
|
||||
@@ -157,27 +157,31 @@ enum CholmodMode {
|
||||
* \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT
|
||||
*/
|
||||
template<typename _MatrixType, int _UpLo, typename Derived>
|
||||
class CholmodBase : internal::noncopyable
|
||||
class CholmodBase : public SparseSolverBase<Derived>
|
||||
{
|
||||
protected:
|
||||
typedef SparseSolverBase<Derived> Base;
|
||||
using Base::derived;
|
||||
using Base::m_isInitialized;
|
||||
public:
|
||||
typedef _MatrixType MatrixType;
|
||||
enum { UpLo = _UpLo };
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename MatrixType::RealScalar RealScalar;
|
||||
typedef MatrixType CholMatrixType;
|
||||
typedef typename MatrixType::Index Index;
|
||||
typedef typename MatrixType::StorageIndex StorageIndex;
|
||||
|
||||
public:
|
||||
|
||||
CholmodBase()
|
||||
: m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
|
||||
: m_cholmodFactor(0), m_info(Success)
|
||||
{
|
||||
m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
|
||||
cholmod_start(&m_cholmod);
|
||||
}
|
||||
|
||||
CholmodBase(const MatrixType& matrix)
|
||||
: m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
|
||||
explicit CholmodBase(const MatrixType& matrix)
|
||||
: m_cholmodFactor(0), m_info(Success)
|
||||
{
|
||||
m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
|
||||
cholmod_start(&m_cholmod);
|
||||
@@ -191,11 +195,8 @@ class CholmodBase : internal::noncopyable
|
||||
cholmod_finish(&m_cholmod);
|
||||
}
|
||||
|
||||
inline Index cols() const { return m_cholmodFactor->n; }
|
||||
inline Index rows() const { return m_cholmodFactor->n; }
|
||||
|
||||
Derived& derived() { return *static_cast<Derived*>(this); }
|
||||
const Derived& derived() const { return *static_cast<const Derived*>(this); }
|
||||
inline StorageIndex cols() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
|
||||
inline StorageIndex rows() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
|
||||
|
||||
/** \brief Reports whether previous computation was successful.
|
||||
*
|
||||
@@ -216,34 +217,6 @@ class CholmodBase : internal::noncopyable
|
||||
return derived();
|
||||
}
|
||||
|
||||
/** \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<CholmodBase, Rhs>
|
||||
solve(const MatrixBase<Rhs>& b) const
|
||||
{
|
||||
eigen_assert(m_isInitialized && "LLT is not initialized.");
|
||||
eigen_assert(rows()==b.rows()
|
||||
&& "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
|
||||
return internal::solve_retval<CholmodBase, Rhs>(*this, b.derived());
|
||||
}
|
||||
|
||||
/** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
|
||||
*
|
||||
* \sa compute()
|
||||
*/
|
||||
template<typename Rhs>
|
||||
inline const internal::sparse_solve_retval<CholmodBase, Rhs>
|
||||
solve(const SparseMatrixBase<Rhs>& b) const
|
||||
{
|
||||
eigen_assert(m_isInitialized && "LLT is not initialized.");
|
||||
eigen_assert(rows()==b.rows()
|
||||
&& "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
|
||||
return internal::sparse_solve_retval<CholmodBase, Rhs>(*this, b.derived());
|
||||
}
|
||||
|
||||
/** Performs a symbolic decomposition on the sparsity pattern of \a matrix.
|
||||
*
|
||||
* This function is particularly useful when solving for several problems having the same structure.
|
||||
@@ -290,7 +263,7 @@ class CholmodBase : internal::noncopyable
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
/** \internal */
|
||||
template<typename Rhs,typename Dest>
|
||||
void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
|
||||
void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
|
||||
{
|
||||
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;
|
||||
@@ -304,6 +277,7 @@ class CholmodBase : internal::noncopyable
|
||||
if(!x_cd)
|
||||
{
|
||||
this->m_info = NumericalIssue;
|
||||
return;
|
||||
}
|
||||
// TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
|
||||
dest = Matrix<Scalar,Dest::RowsAtCompileTime,Dest::ColsAtCompileTime>::Map(reinterpret_cast<Scalar*>(x_cd->x),b.rows(),b.cols());
|
||||
@@ -312,7 +286,7 @@ class CholmodBase : internal::noncopyable
|
||||
|
||||
/** \internal */
|
||||
template<typename RhsScalar, int RhsOptions, typename RhsIndex, typename DestScalar, int DestOptions, typename DestIndex>
|
||||
void _solve(const SparseMatrix<RhsScalar,RhsOptions,RhsIndex> &b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
|
||||
void _solve_impl(const SparseMatrix<RhsScalar,RhsOptions,RhsIndex> &b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
|
||||
{
|
||||
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;
|
||||
@@ -325,6 +299,7 @@ class CholmodBase : internal::noncopyable
|
||||
if(!x_cs)
|
||||
{
|
||||
this->m_info = NumericalIssue;
|
||||
return;
|
||||
}
|
||||
// TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
|
||||
dest = viewAsEigen<DestScalar,DestOptions,DestIndex>(*x_cs);
|
||||
@@ -357,7 +332,6 @@ class CholmodBase : internal::noncopyable
|
||||
cholmod_factor* m_cholmodFactor;
|
||||
RealScalar m_shiftOffset[2];
|
||||
mutable ComputationInfo m_info;
|
||||
bool m_isInitialized;
|
||||
int m_factorizationIsOk;
|
||||
int m_analysisIsOk;
|
||||
};
|
||||
@@ -395,7 +369,7 @@ class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimpl
|
||||
CholmodSimplicialLLT(const MatrixType& matrix) : Base()
|
||||
{
|
||||
init();
|
||||
compute(matrix);
|
||||
this->compute(matrix);
|
||||
}
|
||||
|
||||
~CholmodSimplicialLLT() {}
|
||||
@@ -442,7 +416,7 @@ class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimp
|
||||
CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
|
||||
{
|
||||
init();
|
||||
compute(matrix);
|
||||
this->compute(matrix);
|
||||
}
|
||||
|
||||
~CholmodSimplicialLDLT() {}
|
||||
@@ -487,7 +461,7 @@ class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSuper
|
||||
CholmodSupernodalLLT(const MatrixType& matrix) : Base()
|
||||
{
|
||||
init();
|
||||
compute(matrix);
|
||||
this->compute(matrix);
|
||||
}
|
||||
|
||||
~CholmodSupernodalLLT() {}
|
||||
@@ -534,7 +508,7 @@ class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecom
|
||||
CholmodDecomposition(const MatrixType& matrix) : Base()
|
||||
{
|
||||
init();
|
||||
compute(matrix);
|
||||
this->compute(matrix);
|
||||
}
|
||||
|
||||
~CholmodDecomposition() {}
|
||||
@@ -572,36 +546,6 @@ class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecom
|
||||
}
|
||||
};
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
|
||||
struct solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
|
||||
: solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
|
||||
{
|
||||
typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
|
||||
EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
|
||||
|
||||
template<typename Dest> void evalTo(Dest& dst) const
|
||||
{
|
||||
dec()._solve(rhs(),dst);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
|
||||
struct sparse_solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
|
||||
: sparse_solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
|
||||
{
|
||||
typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
|
||||
EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
|
||||
|
||||
template<typename Dest> void evalTo(Dest& dst) const
|
||||
{
|
||||
dec()._solve(rhs(),dst);
|
||||
}
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_CHOLMODSUPPORT_H
|
||||
|
||||
@@ -24,6 +24,9 @@ namespace Eigen {
|
||||
* API for the %Matrix class provides easy access to linear-algebra
|
||||
* operations.
|
||||
*
|
||||
* See documentation of class Matrix for detailed information on the template parameters
|
||||
* storage layout.
|
||||
*
|
||||
* This class can be extended with the help of the plugin mechanism described on the page
|
||||
* \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
|
||||
*
|
||||
@@ -75,6 +78,21 @@ class Array
|
||||
return Base::operator=(other);
|
||||
}
|
||||
|
||||
/** Set all the entries to \a value.
|
||||
* \sa DenseBase::setConstant(), DenseBase::fill()
|
||||
*/
|
||||
/* This overload is needed because the usage of
|
||||
* using Base::operator=;
|
||||
* fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
|
||||
* the usage of 'using'. This should be done only for operator=.
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Array& operator=(const Scalar &value)
|
||||
{
|
||||
Base::setConstant(value);
|
||||
return *this;
|
||||
}
|
||||
|
||||
/** Copies the value of the expression \a other into \c *this with automatic resizing.
|
||||
*
|
||||
* *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
|
||||
@@ -86,7 +104,7 @@ class Array
|
||||
*/
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Array& operator=(const ArrayBase<OtherDerived>& other)
|
||||
EIGEN_STRONG_INLINE Array& operator=(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
return Base::_set(other);
|
||||
}
|
||||
@@ -99,7 +117,7 @@ class Array
|
||||
{
|
||||
return Base::_set(other);
|
||||
}
|
||||
|
||||
|
||||
/** Default constructor.
|
||||
*
|
||||
* For fixed-size matrices, does nothing.
|
||||
@@ -130,6 +148,7 @@ class Array
|
||||
#endif
|
||||
|
||||
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
|
||||
EIGEN_DEVICE_FUNC
|
||||
Array(Array&& other)
|
||||
: Base(std::move(other))
|
||||
{
|
||||
@@ -137,6 +156,7 @@ class Array
|
||||
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
|
||||
Base::_set_noalias(other);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
Array& operator=(Array&& other)
|
||||
{
|
||||
other.swap(*this);
|
||||
@@ -144,7 +164,6 @@ class Array
|
||||
}
|
||||
#endif
|
||||
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -206,50 +225,18 @@ class Array
|
||||
m_storage.data()[3] = val3;
|
||||
}
|
||||
|
||||
/** Constructor copying the value of the expression \a other */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Array(const ArrayBase<OtherDerived>& other)
|
||||
: Base(other.rows() * other.cols(), other.rows(), other.cols())
|
||||
{
|
||||
Base::_check_template_params();
|
||||
Base::_set_noalias(other);
|
||||
}
|
||||
/** Copy constructor */
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Array(const Array& other)
|
||||
: Base(other.rows() * other.cols(), other.rows(), other.cols())
|
||||
{
|
||||
Base::_check_template_params();
|
||||
Base::_set_noalias(other);
|
||||
}
|
||||
/** Copy constructor with in-place evaluation */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Array(const ReturnByValue<OtherDerived>& other)
|
||||
{
|
||||
Base::_check_template_params();
|
||||
Base::resize(other.rows(), other.cols());
|
||||
other.evalTo(*this);
|
||||
}
|
||||
: Base(other)
|
||||
{ }
|
||||
|
||||
/** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other)
|
||||
: Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
|
||||
{
|
||||
Base::_check_template_params();
|
||||
Base::_resize_to_match(other);
|
||||
*this = other;
|
||||
}
|
||||
|
||||
/** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the
|
||||
* data pointers.
|
||||
*/
|
||||
template<typename OtherDerived>
|
||||
void swap(ArrayBase<OtherDerived> const & other)
|
||||
{ this->_swap(other.derived()); }
|
||||
: Base(other.derived())
|
||||
{ }
|
||||
|
||||
EIGEN_DEVICE_FUNC inline Index innerStride() const { return 1; }
|
||||
EIGEN_DEVICE_FUNC inline Index outerStride() const { return this->innerSize(); }
|
||||
|
||||
@@ -50,7 +50,6 @@ template<typename Derived> class ArrayBase
|
||||
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
|
||||
|
||||
typedef typename internal::traits<Derived>::StorageKind StorageKind;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
@@ -64,8 +63,7 @@ template<typename Derived> class ArrayBase
|
||||
using Base::MaxSizeAtCompileTime;
|
||||
using Base::IsVectorAtCompileTime;
|
||||
using Base::Flags;
|
||||
using Base::CoeffReadCost;
|
||||
|
||||
|
||||
using Base::derived;
|
||||
using Base::const_cast_derived;
|
||||
using Base::rows;
|
||||
@@ -85,22 +83,10 @@ template<typename Derived> class ArrayBase
|
||||
#endif // not EIGEN_PARSED_BY_DOXYGEN
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
/** \internal the plain matrix type corresponding to this expression. Note that is not necessarily
|
||||
* exactly the return type of eval(): in the case of plain matrices, the return type of eval() is a const
|
||||
* reference to a matrix, not a matrix! It is however guaranteed that the return type of eval() is either
|
||||
* PlainObject or const PlainObject&.
|
||||
*/
|
||||
typedef Array<typename internal::traits<Derived>::Scalar,
|
||||
internal::traits<Derived>::RowsAtCompileTime,
|
||||
internal::traits<Derived>::ColsAtCompileTime,
|
||||
AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
|
||||
internal::traits<Derived>::MaxRowsAtCompileTime,
|
||||
internal::traits<Derived>::MaxColsAtCompileTime
|
||||
> PlainObject;
|
||||
|
||||
typedef typename Base::PlainObject PlainObject;
|
||||
|
||||
/** \internal Represents a matrix with all coefficients equal to one another*/
|
||||
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
|
||||
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType;
|
||||
#endif // not EIGEN_PARSED_BY_DOXYGEN
|
||||
|
||||
#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::ArrayBase
|
||||
@@ -121,8 +107,15 @@ template<typename Derived> class ArrayBase
|
||||
EIGEN_DEVICE_FUNC
|
||||
Derived& operator=(const ArrayBase& other)
|
||||
{
|
||||
return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
|
||||
internal::call_assignment(derived(), other.derived());
|
||||
return derived();
|
||||
}
|
||||
|
||||
/** Set all the entries to \a value.
|
||||
* \sa DenseBase::setConstant(), DenseBase::fill() */
|
||||
EIGEN_DEVICE_FUNC
|
||||
Derived& operator=(const Scalar &value)
|
||||
{ Base::setConstant(value); return derived(); }
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
Derived& operator+=(const Scalar& scalar);
|
||||
@@ -153,9 +146,9 @@ template<typename Derived> class ArrayBase
|
||||
/** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array
|
||||
* \sa MatrixBase::array() */
|
||||
EIGEN_DEVICE_FUNC
|
||||
MatrixWrapper<Derived> matrix() { return derived(); }
|
||||
MatrixWrapper<Derived> matrix() { return MatrixWrapper<Derived>(derived()); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const MatrixWrapper<const Derived> matrix() const { return derived(); }
|
||||
const MatrixWrapper<const Derived> matrix() const { return MatrixWrapper<const Derived>(derived()); }
|
||||
|
||||
// template<typename Dest>
|
||||
// inline void evalTo(Dest& dst) const { dst = matrix(); }
|
||||
@@ -186,8 +179,7 @@ template<typename OtherDerived>
|
||||
EIGEN_STRONG_INLINE Derived &
|
||||
ArrayBase<Derived>::operator-=(const ArrayBase<OtherDerived> &other)
|
||||
{
|
||||
SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
|
||||
tmp = other.derived();
|
||||
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
@@ -200,8 +192,7 @@ template<typename OtherDerived>
|
||||
EIGEN_STRONG_INLINE Derived &
|
||||
ArrayBase<Derived>::operator+=(const ArrayBase<OtherDerived>& other)
|
||||
{
|
||||
SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
|
||||
tmp = other.derived();
|
||||
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
@@ -214,8 +205,7 @@ template<typename OtherDerived>
|
||||
EIGEN_STRONG_INLINE Derived &
|
||||
ArrayBase<Derived>::operator*=(const ArrayBase<OtherDerived>& other)
|
||||
{
|
||||
SelfCwiseBinaryOp<internal::scalar_product_op<Scalar>, Derived, OtherDerived> tmp(derived());
|
||||
tmp = other.derived();
|
||||
call_assignment(derived(), other.derived(), internal::mul_assign_op<Scalar,typename OtherDerived::Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
@@ -228,8 +218,7 @@ template<typename OtherDerived>
|
||||
EIGEN_STRONG_INLINE Derived &
|
||||
ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other)
|
||||
{
|
||||
SelfCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, Derived, OtherDerived> tmp(derived());
|
||||
tmp = other.derived();
|
||||
call_assignment(derived(), other.derived(), internal::div_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
|
||||
@@ -44,6 +44,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
|
||||
typedef ArrayBase<ArrayWrapper> Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
|
||||
typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
|
||||
|
||||
typedef typename internal::conditional<
|
||||
internal::is_lvalue<ExpressionType>::value,
|
||||
@@ -51,10 +52,10 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
|
||||
const Scalar
|
||||
>::type ScalarWithConstIfNotLvalue;
|
||||
|
||||
typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
|
||||
typedef typename internal::ref_selector<ExpressionType>::type NestedExpressionType;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
|
||||
explicit EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index rows() const { return m_expression.rows(); }
|
||||
@@ -148,7 +149,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
|
||||
/** Forwards the resizing request to the nested expression
|
||||
* \sa DenseBase::resize(Index,Index)*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
|
||||
void resize(Index rows, Index cols) { m_expression.const_cast_derived().resize(rows,cols); }
|
||||
|
||||
protected:
|
||||
NestedExpressionType m_expression;
|
||||
@@ -186,6 +187,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
|
||||
typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
|
||||
typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
|
||||
|
||||
typedef typename internal::conditional<
|
||||
internal::is_lvalue<ExpressionType>::value,
|
||||
@@ -193,10 +195,10 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
|
||||
const Scalar
|
||||
>::type ScalarWithConstIfNotLvalue;
|
||||
|
||||
typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
|
||||
typedef typename internal::ref_selector<ExpressionType>::type NestedExpressionType;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline MatrixWrapper(ExpressionType& a_matrix) : m_expression(a_matrix) {}
|
||||
explicit inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index rows() const { return m_expression.rows(); }
|
||||
@@ -286,7 +288,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
|
||||
/** Forwards the resizing request to the nested expression
|
||||
* \sa DenseBase::resize(Index,Index)*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
|
||||
void resize(Index rows, Index cols) { m_expression.const_cast_derived().resize(rows,cols); }
|
||||
|
||||
protected:
|
||||
NestedExpressionType m_expression;
|
||||
|
||||
@@ -14,485 +14,6 @@
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
|
||||
/***************************************************************************
|
||||
* Part 1 : the logic deciding a strategy for traversal and unrolling *
|
||||
***************************************************************************/
|
||||
|
||||
template <typename Derived, typename OtherDerived>
|
||||
struct assign_traits
|
||||
{
|
||||
public:
|
||||
enum {
|
||||
DstIsAligned = Derived::Flags & AlignedBit,
|
||||
DstHasDirectAccess = Derived::Flags & DirectAccessBit,
|
||||
SrcIsAligned = OtherDerived::Flags & AlignedBit,
|
||||
JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned
|
||||
};
|
||||
|
||||
private:
|
||||
enum {
|
||||
InnerSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::SizeAtCompileTime)
|
||||
: int(Derived::Flags)&RowMajorBit ? int(Derived::ColsAtCompileTime)
|
||||
: int(Derived::RowsAtCompileTime),
|
||||
InnerMaxSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::MaxSizeAtCompileTime)
|
||||
: int(Derived::Flags)&RowMajorBit ? int(Derived::MaxColsAtCompileTime)
|
||||
: int(Derived::MaxRowsAtCompileTime),
|
||||
MaxSizeAtCompileTime = Derived::SizeAtCompileTime,
|
||||
PacketSize = packet_traits<typename Derived::Scalar>::size
|
||||
};
|
||||
|
||||
enum {
|
||||
StorageOrdersAgree = (int(Derived::IsRowMajor) == int(OtherDerived::IsRowMajor)),
|
||||
MightVectorize = StorageOrdersAgree
|
||||
&& (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit),
|
||||
MayInnerVectorize = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0
|
||||
&& int(DstIsAligned) && int(SrcIsAligned),
|
||||
MayLinearize = StorageOrdersAgree && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit),
|
||||
MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
|
||||
&& (DstIsAligned || MaxSizeAtCompileTime == Dynamic),
|
||||
/* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
|
||||
so it's only good for large enough sizes. */
|
||||
MaySliceVectorize = MightVectorize && DstHasDirectAccess
|
||||
&& (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=3*PacketSize)
|
||||
/* slice vectorization can be slow, so we only want it if the slices are big, which is
|
||||
indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
|
||||
in a fixed-size matrix */
|
||||
};
|
||||
|
||||
public:
|
||||
enum {
|
||||
Traversal = int(MayInnerVectorize) ? int(InnerVectorizedTraversal)
|
||||
: int(MayLinearVectorize) ? int(LinearVectorizedTraversal)
|
||||
: int(MaySliceVectorize) ? int(SliceVectorizedTraversal)
|
||||
: int(MayLinearize) ? int(LinearTraversal)
|
||||
: int(DefaultTraversal),
|
||||
Vectorized = int(Traversal) == InnerVectorizedTraversal
|
||||
|| int(Traversal) == LinearVectorizedTraversal
|
||||
|| int(Traversal) == SliceVectorizedTraversal
|
||||
};
|
||||
|
||||
private:
|
||||
enum {
|
||||
UnrollingLimit = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1),
|
||||
MayUnrollCompletely = int(Derived::SizeAtCompileTime) != Dynamic
|
||||
&& int(OtherDerived::CoeffReadCost) != Dynamic
|
||||
&& int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit),
|
||||
MayUnrollInner = int(InnerSize) != Dynamic
|
||||
&& int(OtherDerived::CoeffReadCost) != Dynamic
|
||||
&& int(InnerSize) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit)
|
||||
};
|
||||
|
||||
public:
|
||||
enum {
|
||||
Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
|
||||
? (
|
||||
int(MayUnrollCompletely) ? int(CompleteUnrolling)
|
||||
: int(MayUnrollInner) ? int(InnerUnrolling)
|
||||
: int(NoUnrolling)
|
||||
)
|
||||
: int(Traversal) == int(LinearVectorizedTraversal)
|
||||
? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(CompleteUnrolling) : int(NoUnrolling) )
|
||||
: int(Traversal) == int(LinearTraversal)
|
||||
? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling) : int(NoUnrolling) )
|
||||
: int(NoUnrolling)
|
||||
};
|
||||
|
||||
#ifdef EIGEN_DEBUG_ASSIGN
|
||||
static void debug()
|
||||
{
|
||||
EIGEN_DEBUG_VAR(DstIsAligned)
|
||||
EIGEN_DEBUG_VAR(SrcIsAligned)
|
||||
EIGEN_DEBUG_VAR(JointAlignment)
|
||||
EIGEN_DEBUG_VAR(Derived::SizeAtCompileTime)
|
||||
EIGEN_DEBUG_VAR(OtherDerived::CoeffReadCost)
|
||||
EIGEN_DEBUG_VAR(InnerSize)
|
||||
EIGEN_DEBUG_VAR(InnerMaxSize)
|
||||
EIGEN_DEBUG_VAR(PacketSize)
|
||||
EIGEN_DEBUG_VAR(StorageOrdersAgree)
|
||||
EIGEN_DEBUG_VAR(MightVectorize)
|
||||
EIGEN_DEBUG_VAR(MayLinearize)
|
||||
EIGEN_DEBUG_VAR(MayInnerVectorize)
|
||||
EIGEN_DEBUG_VAR(MayLinearVectorize)
|
||||
EIGEN_DEBUG_VAR(MaySliceVectorize)
|
||||
EIGEN_DEBUG_VAR(Traversal)
|
||||
EIGEN_DEBUG_VAR(UnrollingLimit)
|
||||
EIGEN_DEBUG_VAR(MayUnrollCompletely)
|
||||
EIGEN_DEBUG_VAR(MayUnrollInner)
|
||||
EIGEN_DEBUG_VAR(Unrolling)
|
||||
}
|
||||
#endif
|
||||
};
|
||||
|
||||
/***************************************************************************
|
||||
* Part 2 : meta-unrollers
|
||||
***************************************************************************/
|
||||
|
||||
/************************
|
||||
*** Default traversal ***
|
||||
************************/
|
||||
|
||||
template<typename Derived1, typename Derived2, int Index, int Stop>
|
||||
struct assign_DefaultTraversal_CompleteUnrolling
|
||||
{
|
||||
enum {
|
||||
outer = Index / Derived1::InnerSizeAtCompileTime,
|
||||
inner = Index % Derived1::InnerSizeAtCompileTime
|
||||
};
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
dst.copyCoeffByOuterInner(outer, inner, src);
|
||||
assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Stop>
|
||||
struct assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Index, int Stop>
|
||||
struct assign_DefaultTraversal_InnerUnrolling
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
|
||||
{
|
||||
dst.copyCoeffByOuterInner(outer, Index, src);
|
||||
assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src, outer);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Stop>
|
||||
struct assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Stop, Stop>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
|
||||
};
|
||||
|
||||
/***********************
|
||||
*** Linear traversal ***
|
||||
***********************/
|
||||
|
||||
template<typename Derived1, typename Derived2, int Index, int Stop>
|
||||
struct assign_LinearTraversal_CompleteUnrolling
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
dst.copyCoeff(Index, src);
|
||||
assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Stop>
|
||||
struct assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
|
||||
};
|
||||
|
||||
/**************************
|
||||
*** Inner vectorization ***
|
||||
**************************/
|
||||
|
||||
template<typename Derived1, typename Derived2, int Index, int Stop>
|
||||
struct assign_innervec_CompleteUnrolling
|
||||
{
|
||||
enum {
|
||||
outer = Index / Derived1::InnerSizeAtCompileTime,
|
||||
inner = Index % Derived1::InnerSizeAtCompileTime,
|
||||
JointAlignment = assign_traits<Derived1,Derived2>::JointAlignment
|
||||
};
|
||||
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
dst.template copyPacketByOuterInner<Derived2, Aligned, JointAlignment>(outer, inner, src);
|
||||
assign_innervec_CompleteUnrolling<Derived1, Derived2,
|
||||
Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Stop>
|
||||
struct assign_innervec_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Index, int Stop>
|
||||
struct assign_innervec_InnerUnrolling
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
|
||||
{
|
||||
dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, Index, src);
|
||||
assign_innervec_InnerUnrolling<Derived1, Derived2,
|
||||
Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src, outer);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Stop>
|
||||
struct assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
|
||||
};
|
||||
|
||||
/***************************************************************************
|
||||
* Part 3 : implementation of all cases
|
||||
***************************************************************************/
|
||||
|
||||
template<typename Derived1, typename Derived2,
|
||||
int Traversal = assign_traits<Derived1, Derived2>::Traversal,
|
||||
int Unrolling = assign_traits<Derived1, Derived2>::Unrolling,
|
||||
int Version = Specialized>
|
||||
struct assign_impl;
|
||||
|
||||
/************************
|
||||
*** Default traversal ***
|
||||
************************/
|
||||
|
||||
template<typename Derived1, typename Derived2, int Unrolling, int Version>
|
||||
struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling, Version>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(Derived1 &, const Derived2 &) { }
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling, Version>
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
const Index innerSize = dst.innerSize();
|
||||
const Index outerSize = dst.outerSize();
|
||||
for(Index outer = 0; outer < outerSize; ++outer)
|
||||
for(Index inner = 0; inner < innerSize; ++inner)
|
||||
dst.copyCoeffByOuterInner(outer, inner, src);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling, Version>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
|
||||
::run(dst, src);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling, Version>
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
const Index outerSize = dst.outerSize();
|
||||
for(Index outer = 0; outer < outerSize; ++outer)
|
||||
assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
|
||||
::run(dst, src, outer);
|
||||
}
|
||||
};
|
||||
|
||||
/***********************
|
||||
*** Linear traversal ***
|
||||
***********************/
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling, Version>
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
const Index size = dst.size();
|
||||
for(Index i = 0; i < size; ++i)
|
||||
dst.copyCoeff(i, src);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling, Version>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
|
||||
::run(dst, src);
|
||||
}
|
||||
};
|
||||
|
||||
/**************************
|
||||
*** Inner vectorization ***
|
||||
**************************/
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling, Version>
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
static inline void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
const Index innerSize = dst.innerSize();
|
||||
const Index outerSize = dst.outerSize();
|
||||
const Index packetSize = packet_traits<typename Derived1::Scalar>::size;
|
||||
for(Index outer = 0; outer < outerSize; ++outer)
|
||||
for(Index inner = 0; inner < innerSize; inner+=packetSize)
|
||||
dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, inner, src);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling, Version>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
|
||||
::run(dst, src);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling, Version>
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
const Index outerSize = dst.outerSize();
|
||||
for(Index outer = 0; outer < outerSize; ++outer)
|
||||
assign_innervec_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
|
||||
::run(dst, src, outer);
|
||||
}
|
||||
};
|
||||
|
||||
/***************************
|
||||
*** Linear vectorization ***
|
||||
***************************/
|
||||
|
||||
template <bool IsAligned = false>
|
||||
struct unaligned_assign_impl
|
||||
{
|
||||
template <typename Derived, typename OtherDerived>
|
||||
static EIGEN_STRONG_INLINE void run(const Derived&, OtherDerived&, typename Derived::Index, typename Derived::Index) {}
|
||||
};
|
||||
|
||||
template <>
|
||||
struct unaligned_assign_impl<false>
|
||||
{
|
||||
// MSVC must not inline this functions. If it does, it fails to optimize the
|
||||
// packet access path.
|
||||
#ifdef _MSC_VER
|
||||
template <typename Derived, typename OtherDerived>
|
||||
static EIGEN_DONT_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
|
||||
#else
|
||||
template <typename Derived, typename OtherDerived>
|
||||
static EIGEN_STRONG_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
|
||||
#endif
|
||||
{
|
||||
for (typename Derived::Index index = start; index < end; ++index)
|
||||
dst.copyCoeff(index, src);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling, Version>
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
const Index size = dst.size();
|
||||
typedef packet_traits<typename Derived1::Scalar> PacketTraits;
|
||||
enum {
|
||||
packetSize = PacketTraits::size,
|
||||
dstAlignment = PacketTraits::AlignedOnScalar ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
|
||||
srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
|
||||
};
|
||||
const Index alignedStart = assign_traits<Derived1,Derived2>::DstIsAligned ? 0
|
||||
: internal::first_aligned(&dst.coeffRef(0), size);
|
||||
const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
|
||||
|
||||
unaligned_assign_impl<assign_traits<Derived1,Derived2>::DstIsAligned!=0>::run(src,dst,0,alignedStart);
|
||||
|
||||
for(Index index = alignedStart; index < alignedEnd; index += packetSize)
|
||||
{
|
||||
dst.template copyPacket<Derived2, dstAlignment, srcAlignment>(index, src);
|
||||
}
|
||||
|
||||
unaligned_assign_impl<>::run(src,dst,alignedEnd,size);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling, Version>
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
enum { size = Derived1::SizeAtCompileTime,
|
||||
packetSize = packet_traits<typename Derived1::Scalar>::size,
|
||||
alignedSize = (size/packetSize)*packetSize };
|
||||
|
||||
assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, alignedSize>::run(dst, src);
|
||||
assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, alignedSize, size>::run(dst, src);
|
||||
}
|
||||
};
|
||||
|
||||
/**************************
|
||||
*** Slice vectorization ***
|
||||
***************************/
|
||||
|
||||
template<typename Derived1, typename Derived2, int Version>
|
||||
struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Version>
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
static inline void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
typedef packet_traits<typename Derived1::Scalar> PacketTraits;
|
||||
enum {
|
||||
packetSize = PacketTraits::size,
|
||||
alignable = PacketTraits::AlignedOnScalar,
|
||||
dstAlignment = alignable ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
|
||||
srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
|
||||
};
|
||||
const Index packetAlignedMask = packetSize - 1;
|
||||
const Index innerSize = dst.innerSize();
|
||||
const Index outerSize = dst.outerSize();
|
||||
const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0;
|
||||
Index alignedStart = ((!alignable) || assign_traits<Derived1,Derived2>::DstIsAligned) ? 0
|
||||
: internal::first_aligned(&dst.coeffRef(0,0), innerSize);
|
||||
|
||||
for(Index outer = 0; outer < outerSize; ++outer)
|
||||
{
|
||||
const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
|
||||
// do the non-vectorizable part of the assignment
|
||||
for(Index inner = 0; inner<alignedStart ; ++inner)
|
||||
dst.copyCoeffByOuterInner(outer, inner, src);
|
||||
|
||||
// do the vectorizable part of the assignment
|
||||
for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
|
||||
dst.template copyPacketByOuterInner<Derived2, dstAlignment, Unaligned>(outer, inner, src);
|
||||
|
||||
// do the non-vectorizable part of the assignment
|
||||
for(Index inner = alignedEnd; inner<innerSize ; ++inner)
|
||||
dst.copyCoeffByOuterInner(outer, inner, src);
|
||||
|
||||
alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
/***************************************************************************
|
||||
* Part 4 : implementation of DenseBase methods
|
||||
***************************************************************************/
|
||||
|
||||
template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
|
||||
@@ -506,91 +27,35 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
|
||||
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
|
||||
EIGEN_STATIC_ASSERT(SameType,YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
|
||||
|
||||
#ifdef EIGEN_TEST_EVALUATORS
|
||||
|
||||
#ifdef EIGEN_DEBUG_ASSIGN
|
||||
internal::copy_using_evaluator_traits<Derived, OtherDerived>::debug();
|
||||
#endif
|
||||
eigen_assert(rows() == other.rows() && cols() == other.cols());
|
||||
internal::call_dense_assignment_loop(derived(),other.derived());
|
||||
internal::call_assignment_no_alias(derived(),other.derived());
|
||||
|
||||
#else // EIGEN_TEST_EVALUATORS
|
||||
|
||||
#ifdef EIGEN_DEBUG_ASSIGN
|
||||
internal::assign_traits<Derived, OtherDerived>::debug();
|
||||
#endif
|
||||
eigen_assert(rows() == other.rows() && cols() == other.cols());
|
||||
internal::assign_impl<Derived, OtherDerived, int(SameType) ? int(internal::assign_traits<Derived, OtherDerived>::Traversal)
|
||||
: int(InvalidTraversal)>::run(derived(),other.derived());
|
||||
|
||||
#endif // EIGEN_TEST_EVALUATORS
|
||||
|
||||
#ifndef EIGEN_NO_DEBUG
|
||||
checkTransposeAliasing(other.derived());
|
||||
#endif
|
||||
return derived();
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename Derived, typename OtherDerived,
|
||||
bool EvalBeforeAssigning = (int(internal::traits<OtherDerived>::Flags) & EvalBeforeAssigningBit) != 0,
|
||||
bool NeedToTranspose = ((int(Derived::RowsAtCompileTime) == 1 && int(OtherDerived::ColsAtCompileTime) == 1)
|
||||
| // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
|
||||
// revert to || as soon as not needed anymore.
|
||||
(int(Derived::ColsAtCompileTime) == 1 && int(OtherDerived::RowsAtCompileTime) == 1))
|
||||
&& int(Derived::SizeAtCompileTime) != 1>
|
||||
struct assign_selector;
|
||||
|
||||
template<typename Derived, typename OtherDerived>
|
||||
struct assign_selector<Derived,OtherDerived,false,false> {
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
|
||||
template<typename ActualDerived, typename ActualOtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { other.evalTo(dst); return dst; }
|
||||
};
|
||||
template<typename Derived, typename OtherDerived>
|
||||
struct assign_selector<Derived,OtherDerived,true,false> {
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
|
||||
};
|
||||
template<typename Derived, typename OtherDerived>
|
||||
struct assign_selector<Derived,OtherDerived,false,true> {
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
|
||||
template<typename ActualDerived, typename ActualOtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { Transpose<ActualDerived> dstTrans(dst); other.evalTo(dstTrans); return dst; }
|
||||
};
|
||||
template<typename Derived, typename OtherDerived>
|
||||
struct assign_selector<Derived,OtherDerived,true,true> {
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
|
||||
internal::call_assignment(derived(), other.derived());
|
||||
return derived();
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other)
|
||||
{
|
||||
return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
|
||||
internal::call_assignment(derived(), other.derived());
|
||||
return derived();
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other)
|
||||
{
|
||||
return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
|
||||
internal::call_assignment(derived(), other.derived());
|
||||
return derived();
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
@@ -598,7 +63,8 @@ template <typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
|
||||
internal::call_assignment(derived(), other.derived());
|
||||
return derived();
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
@@ -606,7 +72,8 @@ template <typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other)
|
||||
{
|
||||
return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
|
||||
internal::call_assignment(derived(), other.derived());
|
||||
return derived();
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
@@ -614,7 +81,8 @@ template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
|
||||
{
|
||||
return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
|
||||
other.derived().evalTo(derived());
|
||||
return derived();
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
|
||||
// Copyright (C) 2011-2013 Gael Guennebaud <gael.guennebaud@inria.fr>
|
||||
// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
|
||||
// Copyright (C) 2011-2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
|
||||
//
|
||||
// This Source Code Form is subject to the terms of the Mozilla
|
||||
@@ -24,39 +24,52 @@ namespace internal {
|
||||
|
||||
// copy_using_evaluator_traits is based on assign_traits
|
||||
|
||||
template <typename Derived, typename OtherDerived>
|
||||
template <typename DstEvaluator, typename SrcEvaluator, typename AssignFunc>
|
||||
struct copy_using_evaluator_traits
|
||||
{
|
||||
typedef typename DstEvaluator::XprType Dst;
|
||||
typedef typename Dst::Scalar DstScalar;
|
||||
// TODO distinguish between linear traversal and inner-traversals
|
||||
typedef typename find_best_packet<DstScalar,Dst::SizeAtCompileTime>::type PacketType;
|
||||
|
||||
enum {
|
||||
DstFlags = DstEvaluator::Flags,
|
||||
SrcFlags = SrcEvaluator::Flags,
|
||||
RequiredAlignment = unpacket_traits<PacketType>::alignment
|
||||
};
|
||||
|
||||
public:
|
||||
enum {
|
||||
DstIsAligned = Derived::Flags & AlignedBit,
|
||||
DstHasDirectAccess = Derived::Flags & DirectAccessBit,
|
||||
SrcIsAligned = OtherDerived::Flags & AlignedBit,
|
||||
JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned,
|
||||
SrcEvalBeforeAssign = (evaluator_traits<OtherDerived>::HasEvalTo == 1)
|
||||
DstAlignment = DstEvaluator::Alignment,
|
||||
SrcAlignment = SrcEvaluator::Alignment,
|
||||
DstHasDirectAccess = DstFlags & DirectAccessBit,
|
||||
JointAlignment = EIGEN_PLAIN_ENUM_MIN(DstAlignment,SrcAlignment)
|
||||
};
|
||||
|
||||
private:
|
||||
enum {
|
||||
InnerSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::SizeAtCompileTime)
|
||||
: int(Derived::Flags)&RowMajorBit ? int(Derived::ColsAtCompileTime)
|
||||
: int(Derived::RowsAtCompileTime),
|
||||
InnerMaxSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::MaxSizeAtCompileTime)
|
||||
: int(Derived::Flags)&RowMajorBit ? int(Derived::MaxColsAtCompileTime)
|
||||
: int(Derived::MaxRowsAtCompileTime),
|
||||
MaxSizeAtCompileTime = Derived::SizeAtCompileTime,
|
||||
PacketSize = packet_traits<typename Derived::Scalar>::size
|
||||
InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
|
||||
: int(DstFlags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
|
||||
: int(Dst::RowsAtCompileTime),
|
||||
InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
|
||||
: int(DstFlags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
|
||||
: int(Dst::MaxRowsAtCompileTime),
|
||||
MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
|
||||
PacketSize = unpacket_traits<PacketType>::size
|
||||
};
|
||||
|
||||
enum {
|
||||
StorageOrdersAgree = (int(Derived::IsRowMajor) == int(OtherDerived::IsRowMajor)),
|
||||
DstIsRowMajor = DstFlags&RowMajorBit,
|
||||
SrcIsRowMajor = SrcFlags&RowMajorBit,
|
||||
StorageOrdersAgree = (int(DstIsRowMajor) == int(SrcIsRowMajor)),
|
||||
MightVectorize = StorageOrdersAgree
|
||||
&& (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit),
|
||||
&& (int(DstFlags) & int(SrcFlags) & ActualPacketAccessBit)
|
||||
&& (functor_traits<AssignFunc>::PacketAccess),
|
||||
MayInnerVectorize = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0
|
||||
&& int(DstIsAligned) && int(SrcIsAligned),
|
||||
MayLinearize = StorageOrdersAgree && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit),
|
||||
&& int(JointAlignment)>=int(RequiredAlignment),
|
||||
MayLinearize = StorageOrdersAgree && (int(DstFlags) & int(SrcFlags) & LinearAccessBit),
|
||||
MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
|
||||
&& (DstIsAligned || MaxSizeAtCompileTime == Dynamic),
|
||||
&& ((int(DstAlignment)>=int(RequiredAlignment)) || MaxSizeAtCompileTime == Dynamic),
|
||||
/* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
|
||||
so it's only good for large enough sizes. */
|
||||
MaySliceVectorize = MightVectorize && DstHasDirectAccess
|
||||
@@ -68,8 +81,7 @@ private:
|
||||
|
||||
public:
|
||||
enum {
|
||||
Traversal = int(SrcEvalBeforeAssign) ? int(AllAtOnceTraversal)
|
||||
: int(MayInnerVectorize) ? int(InnerVectorizedTraversal)
|
||||
Traversal = int(MayInnerVectorize) ? int(InnerVectorizedTraversal)
|
||||
: int(MayLinearVectorize) ? int(LinearVectorizedTraversal)
|
||||
: int(MaySliceVectorize) ? int(SliceVectorizedTraversal)
|
||||
: int(MayLinearize) ? int(LinearTraversal)
|
||||
@@ -82,12 +94,12 @@ public:
|
||||
private:
|
||||
enum {
|
||||
UnrollingLimit = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1),
|
||||
MayUnrollCompletely = int(Derived::SizeAtCompileTime) != Dynamic
|
||||
&& int(OtherDerived::CoeffReadCost) != Dynamic
|
||||
&& int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit),
|
||||
MayUnrollCompletely = int(Dst::SizeAtCompileTime) != Dynamic
|
||||
&& int(SrcEvaluator::CoeffReadCost) != Dynamic
|
||||
&& int(Dst::SizeAtCompileTime) * int(SrcEvaluator::CoeffReadCost) <= int(UnrollingLimit),
|
||||
MayUnrollInner = int(InnerSize) != Dynamic
|
||||
&& int(OtherDerived::CoeffReadCost) != Dynamic
|
||||
&& int(InnerSize) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit)
|
||||
&& int(SrcEvaluator::CoeffReadCost) != Dynamic
|
||||
&& int(InnerSize) * int(SrcEvaluator::CoeffReadCost) <= int(UnrollingLimit)
|
||||
};
|
||||
|
||||
public:
|
||||
@@ -99,8 +111,8 @@ public:
|
||||
: int(NoUnrolling)
|
||||
)
|
||||
: int(Traversal) == int(LinearVectorizedTraversal)
|
||||
? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(CompleteUnrolling)
|
||||
: int(NoUnrolling) )
|
||||
? ( bool(MayUnrollCompletely) && (int(DstAlignment)>=int(RequiredAlignment)) ? int(CompleteUnrolling)
|
||||
: int(NoUnrolling) )
|
||||
: int(Traversal) == int(LinearTraversal)
|
||||
? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling)
|
||||
: int(NoUnrolling) )
|
||||
@@ -110,8 +122,15 @@ public:
|
||||
#ifdef EIGEN_DEBUG_ASSIGN
|
||||
static void debug()
|
||||
{
|
||||
EIGEN_DEBUG_VAR(DstIsAligned)
|
||||
EIGEN_DEBUG_VAR(SrcIsAligned)
|
||||
std::cerr << "DstXpr: " << typeid(typename DstEvaluator::XprType).name() << std::endl;
|
||||
std::cerr << "SrcXpr: " << typeid(typename SrcEvaluator::XprType).name() << std::endl;
|
||||
std::cerr.setf(std::ios::hex, std::ios::basefield);
|
||||
EIGEN_DEBUG_VAR(DstFlags)
|
||||
EIGEN_DEBUG_VAR(SrcFlags)
|
||||
std::cerr.unsetf(std::ios::hex);
|
||||
EIGEN_DEBUG_VAR(DstAlignment)
|
||||
EIGEN_DEBUG_VAR(SrcAlignment)
|
||||
EIGEN_DEBUG_VAR(RequiredAlignment)
|
||||
EIGEN_DEBUG_VAR(JointAlignment)
|
||||
EIGEN_DEBUG_VAR(InnerSize)
|
||||
EIGEN_DEBUG_VAR(InnerMaxSize)
|
||||
@@ -127,6 +146,7 @@ public:
|
||||
EIGEN_DEBUG_VAR(MayUnrollCompletely)
|
||||
EIGEN_DEBUG_VAR(MayUnrollInner)
|
||||
EIGEN_DEBUG_VAR(Unrolling)
|
||||
std::cerr << std::endl;
|
||||
}
|
||||
#endif
|
||||
};
|
||||
@@ -142,6 +162,7 @@ public:
|
||||
template<typename Kernel, int Index, int Stop>
|
||||
struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling
|
||||
{
|
||||
// FIXME: this is not very clean, perhaps this information should be provided by the kernel?
|
||||
typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
|
||||
typedef typename DstEvaluatorType::XprType DstXprType;
|
||||
|
||||
@@ -150,7 +171,7 @@ struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling
|
||||
inner = Index % DstXprType::InnerSizeAtCompileTime
|
||||
};
|
||||
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
{
|
||||
kernel.assignCoeffByOuterInner(outer, inner);
|
||||
copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Index+1, Stop>::run(kernel);
|
||||
@@ -160,23 +181,23 @@ struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling
|
||||
template<typename Kernel, int Stop>
|
||||
struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Stop, Stop>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel&) { }
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
|
||||
};
|
||||
|
||||
template<typename Kernel, int Index, int Stop>
|
||||
template<typename Kernel, int Index_, int Stop>
|
||||
struct copy_using_evaluator_DefaultTraversal_InnerUnrolling
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel, int outer)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel, Index outer)
|
||||
{
|
||||
kernel.assignCoeffByOuterInner(outer, Index);
|
||||
copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Index+1, Stop>::run(kernel, outer);
|
||||
kernel.assignCoeffByOuterInner(outer, Index_);
|
||||
copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Index_+1, Stop>::run(kernel, outer);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Kernel, int Stop>
|
||||
struct copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Stop, Stop>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel&, int) { }
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&, Index) { }
|
||||
};
|
||||
|
||||
/***********************
|
||||
@@ -186,7 +207,7 @@ struct copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Stop, Stop>
|
||||
template<typename Kernel, int Index, int Stop>
|
||||
struct copy_using_evaluator_LinearTraversal_CompleteUnrolling
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel& kernel)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel)
|
||||
{
|
||||
kernel.assignCoeff(Index);
|
||||
copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Index+1, Stop>::run(kernel);
|
||||
@@ -196,7 +217,7 @@ struct copy_using_evaluator_LinearTraversal_CompleteUnrolling
|
||||
template<typename Kernel, int Stop>
|
||||
struct copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Stop, Stop>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel&) { }
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
|
||||
};
|
||||
|
||||
/**************************
|
||||
@@ -206,19 +227,21 @@ struct copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Stop, Stop
|
||||
template<typename Kernel, int Index, int Stop>
|
||||
struct copy_using_evaluator_innervec_CompleteUnrolling
|
||||
{
|
||||
// FIXME: this is not very clean, perhaps this information should be provided by the kernel?
|
||||
typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
|
||||
typedef typename DstEvaluatorType::XprType DstXprType;
|
||||
|
||||
typedef typename Kernel::PacketType PacketType;
|
||||
|
||||
enum {
|
||||
outer = Index / DstXprType::InnerSizeAtCompileTime,
|
||||
inner = Index % DstXprType::InnerSizeAtCompileTime,
|
||||
JointAlignment = Kernel::AssignmentTraits::JointAlignment
|
||||
};
|
||||
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
{
|
||||
kernel.template assignPacketByOuterInner<Aligned, JointAlignment>(outer, inner);
|
||||
enum { NextIndex = Index + packet_traits<typename DstXprType::Scalar>::size };
|
||||
kernel.template assignPacketByOuterInner<Aligned, JointAlignment, PacketType>(outer, inner);
|
||||
enum { NextIndex = Index + unpacket_traits<PacketType>::size };
|
||||
copy_using_evaluator_innervec_CompleteUnrolling<Kernel, NextIndex, Stop>::run(kernel);
|
||||
}
|
||||
};
|
||||
@@ -226,17 +249,17 @@ struct copy_using_evaluator_innervec_CompleteUnrolling
|
||||
template<typename Kernel, int Stop>
|
||||
struct copy_using_evaluator_innervec_CompleteUnrolling<Kernel, Stop, Stop>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel&) { }
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
|
||||
};
|
||||
|
||||
template<typename Kernel, int Index, int Stop>
|
||||
template<typename Kernel, int Index_, int Stop>
|
||||
struct copy_using_evaluator_innervec_InnerUnrolling
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel, int outer)
|
||||
typedef typename Kernel::PacketType PacketType;
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel, Index outer)
|
||||
{
|
||||
kernel.template assignPacketByOuterInner<Aligned, Aligned>(outer, Index);
|
||||
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
|
||||
enum { NextIndex = Index + packet_traits<typename DstXprType::Scalar>::size };
|
||||
kernel.template assignPacketByOuterInner<Aligned, Aligned, PacketType>(outer, Index_);
|
||||
enum { NextIndex = Index_ + unpacket_traits<PacketType>::size };
|
||||
copy_using_evaluator_innervec_InnerUnrolling<Kernel, NextIndex, Stop>::run(kernel, outer);
|
||||
}
|
||||
};
|
||||
@@ -244,7 +267,7 @@ struct copy_using_evaluator_innervec_InnerUnrolling
|
||||
template<typename Kernel, int Stop>
|
||||
struct copy_using_evaluator_innervec_InnerUnrolling<Kernel, Stop, Stop>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &, int) { }
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &, Index) { }
|
||||
};
|
||||
|
||||
/***************************************************************************
|
||||
@@ -265,10 +288,8 @@ struct dense_assignment_loop;
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, DefaultTraversal, NoUnrolling>
|
||||
{
|
||||
static void run(Kernel &kernel)
|
||||
EIGEN_DEVICE_FUNC static void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::Index Index;
|
||||
|
||||
for(Index outer = 0; outer < kernel.outerSize(); ++outer) {
|
||||
for(Index inner = 0; inner < kernel.innerSize(); ++inner) {
|
||||
kernel.assignCoeffByOuterInner(outer, inner);
|
||||
@@ -280,7 +301,7 @@ struct dense_assignment_loop<Kernel, DefaultTraversal, NoUnrolling>
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, DefaultTraversal, CompleteUnrolling>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
|
||||
copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
|
||||
@@ -290,8 +311,8 @@ struct dense_assignment_loop<Kernel, DefaultTraversal, CompleteUnrolling>
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, DefaultTraversal, InnerUnrolling>
|
||||
{
|
||||
typedef typename Kernel::Index Index;
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
typedef typename Kernel::StorageIndex StorageIndex;
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
|
||||
|
||||
@@ -314,7 +335,7 @@ struct unaligned_dense_assignment_loop
|
||||
{
|
||||
// if IsAligned = true, then do nothing
|
||||
template <typename Kernel>
|
||||
static EIGEN_STRONG_INLINE void run(Kernel&, typename Kernel::Index, typename Kernel::Index) {}
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&, Index, Index) {}
|
||||
};
|
||||
|
||||
template <>
|
||||
@@ -323,19 +344,19 @@ struct unaligned_dense_assignment_loop<false>
|
||||
// MSVC must not inline this functions. If it does, it fails to optimize the
|
||||
// packet access path.
|
||||
// FIXME check which version exhibits this issue
|
||||
#ifdef _MSC_VER
|
||||
#if EIGEN_COMP_MSVC
|
||||
template <typename Kernel>
|
||||
static EIGEN_DONT_INLINE void run(Kernel &kernel,
|
||||
typename Kernel::Index start,
|
||||
typename Kernel::Index end)
|
||||
Index start,
|
||||
Index end)
|
||||
#else
|
||||
template <typename Kernel>
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel,
|
||||
typename Kernel::Index start,
|
||||
typename Kernel::Index end)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel,
|
||||
Index start,
|
||||
Index end)
|
||||
#endif
|
||||
{
|
||||
for (typename Kernel::Index index = start; index < end; ++index)
|
||||
for (Index index = start; index < end; ++index)
|
||||
kernel.assignCoeff(index);
|
||||
}
|
||||
};
|
||||
@@ -343,25 +364,26 @@ struct unaligned_dense_assignment_loop<false>
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, NoUnrolling>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::Index Index;
|
||||
|
||||
const Index size = kernel.size();
|
||||
typedef packet_traits<typename Kernel::Scalar> PacketTraits;
|
||||
typedef typename Kernel::Scalar Scalar;
|
||||
typedef typename Kernel::PacketType PacketType;
|
||||
enum {
|
||||
packetSize = PacketTraits::size,
|
||||
dstIsAligned = int(Kernel::AssignmentTraits::DstIsAligned),
|
||||
dstAlignment = PacketTraits::AlignedOnScalar ? Aligned : dstIsAligned,
|
||||
requestedAlignment = Kernel::AssignmentTraits::RequiredAlignment,
|
||||
packetSize = unpacket_traits<PacketType>::size,
|
||||
dstIsAligned = int(Kernel::AssignmentTraits::DstAlignment)>=int(requestedAlignment),
|
||||
dstAlignment = packet_traits<Scalar>::AlignedOnScalar ? int(requestedAlignment)
|
||||
: int(Kernel::AssignmentTraits::DstAlignment),
|
||||
srcAlignment = Kernel::AssignmentTraits::JointAlignment
|
||||
};
|
||||
const Index alignedStart = dstIsAligned ? 0 : internal::first_aligned(&kernel.dstEvaluator().coeffRef(0), size);
|
||||
const Index alignedStart = dstIsAligned ? 0 : internal::first_aligned<requestedAlignment>(&kernel.dstEvaluator().coeffRef(0), size);
|
||||
const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
|
||||
|
||||
unaligned_dense_assignment_loop<dstIsAligned!=0>::run(kernel, 0, alignedStart);
|
||||
|
||||
for(Index index = alignedStart; index < alignedEnd; index += packetSize)
|
||||
kernel.template assignPacket<dstAlignment, srcAlignment>(index);
|
||||
kernel.template assignPacket<dstAlignment, srcAlignment, PacketType>(index);
|
||||
|
||||
unaligned_dense_assignment_loop<>::run(kernel, alignedEnd, size);
|
||||
}
|
||||
@@ -370,8 +392,8 @@ struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, NoUnrolling>
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, CompleteUnrolling>
|
||||
{
|
||||
typedef typename Kernel::Index Index;
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
typedef typename Kernel::StorageIndex StorageIndex;
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
|
||||
|
||||
@@ -391,23 +413,22 @@ struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, CompleteUnrollin
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, NoUnrolling>
|
||||
{
|
||||
static inline void run(Kernel &kernel)
|
||||
typedef typename Kernel::PacketType PacketType;
|
||||
EIGEN_DEVICE_FUNC static inline void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::Index Index;
|
||||
|
||||
const Index innerSize = kernel.innerSize();
|
||||
const Index outerSize = kernel.outerSize();
|
||||
const Index packetSize = packet_traits<typename Kernel::Scalar>::size;
|
||||
const Index packetSize = unpacket_traits<PacketType>::size;
|
||||
for(Index outer = 0; outer < outerSize; ++outer)
|
||||
for(Index inner = 0; inner < innerSize; inner+=packetSize)
|
||||
kernel.template assignPacketByOuterInner<Aligned, Aligned>(outer, inner);
|
||||
kernel.template assignPacketByOuterInner<Aligned, Aligned, PacketType>(outer, inner);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, CompleteUnrolling>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
|
||||
copy_using_evaluator_innervec_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
|
||||
@@ -417,8 +438,8 @@ struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, CompleteUnrolling
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, InnerUnrolling>
|
||||
{
|
||||
typedef typename Kernel::Index Index;
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
typedef typename Kernel::StorageIndex StorageIndex;
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
|
||||
const Index outerSize = kernel.outerSize();
|
||||
@@ -434,9 +455,8 @@ struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, InnerUnrolling>
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, LinearTraversal, NoUnrolling>
|
||||
{
|
||||
static inline void run(Kernel &kernel)
|
||||
EIGEN_DEVICE_FUNC static inline void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::Index Index;
|
||||
const Index size = kernel.size();
|
||||
for(Index i = 0; i < size; ++i)
|
||||
kernel.assignCoeff(i);
|
||||
@@ -446,7 +466,7 @@ struct dense_assignment_loop<Kernel, LinearTraversal, NoUnrolling>
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, LinearTraversal, CompleteUnrolling>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
|
||||
copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
|
||||
@@ -460,21 +480,29 @@ struct dense_assignment_loop<Kernel, LinearTraversal, CompleteUnrolling>
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
|
||||
{
|
||||
static inline void run(Kernel &kernel)
|
||||
EIGEN_DEVICE_FUNC static inline void run(Kernel &kernel)
|
||||
{
|
||||
typedef typename Kernel::Index Index;
|
||||
typedef packet_traits<typename Kernel::Scalar> PacketTraits;
|
||||
typedef typename Kernel::Scalar Scalar;
|
||||
typedef typename Kernel::PacketType PacketType;
|
||||
enum {
|
||||
packetSize = PacketTraits::size,
|
||||
alignable = PacketTraits::AlignedOnScalar,
|
||||
dstAlignment = alignable ? Aligned : int(Kernel::AssignmentTraits::DstIsAligned)
|
||||
packetSize = unpacket_traits<PacketType>::size,
|
||||
requestedAlignment = int(Kernel::AssignmentTraits::RequiredAlignment),
|
||||
alignable = packet_traits<Scalar>::AlignedOnScalar || int(Kernel::AssignmentTraits::DstAlignment)>=sizeof(Scalar),
|
||||
dstIsAligned = int(Kernel::AssignmentTraits::DstAlignment)>=int(requestedAlignment),
|
||||
dstAlignment = alignable ? int(requestedAlignment)
|
||||
: int(Kernel::AssignmentTraits::DstAlignment)
|
||||
};
|
||||
const Scalar *dst_ptr = &kernel.dstEvaluator().coeffRef(0,0);
|
||||
if((!bool(dstIsAligned)) && (size_t(dst_ptr) % sizeof(Scalar))>0)
|
||||
{
|
||||
// the pointer is not aligend-on scalar, so alignment is not possible
|
||||
return dense_assignment_loop<Kernel,DefaultTraversal,NoUnrolling>::run(kernel);
|
||||
}
|
||||
const Index packetAlignedMask = packetSize - 1;
|
||||
const Index innerSize = kernel.innerSize();
|
||||
const Index outerSize = kernel.outerSize();
|
||||
const Index alignedStep = alignable ? (packetSize - kernel.outerStride() % packetSize) & packetAlignedMask : 0;
|
||||
Index alignedStart = ((!alignable) || Kernel::AssignmentTraits::DstIsAligned) ? 0
|
||||
: internal::first_aligned(&kernel.dstEvaluator().coeffRef(0,0), innerSize);
|
||||
Index alignedStart = ((!alignable) || bool(dstIsAligned)) ? 0 : internal::first_aligned<requestedAlignment>(dst_ptr, innerSize);
|
||||
|
||||
for(Index outer = 0; outer < outerSize; ++outer)
|
||||
{
|
||||
@@ -485,7 +513,7 @@ struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
|
||||
|
||||
// do the vectorizable part of the assignment
|
||||
for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
|
||||
kernel.template assignPacketByOuterInner<dstAlignment, Unaligned>(outer, inner);
|
||||
kernel.template assignPacketByOuterInner<dstAlignment, Unaligned, PacketType>(outer, inner);
|
||||
|
||||
// do the non-vectorizable part of the assignment
|
||||
for(Index inner = alignedEnd; inner<innerSize ; ++inner)
|
||||
@@ -496,25 +524,8 @@ struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
|
||||
}
|
||||
};
|
||||
|
||||
/****************************
|
||||
*** All-at-once traversal ***
|
||||
****************************/
|
||||
|
||||
// TODO: this 'AllAtOnceTraversal' should be dropped or caught earlier (Gael)
|
||||
// Indeed, what to do with the kernel's functor??
|
||||
template<typename Kernel>
|
||||
struct dense_assignment_loop<Kernel, AllAtOnceTraversal, NoUnrolling>
|
||||
{
|
||||
static inline void run(Kernel & kernel)
|
||||
{
|
||||
// Evaluate rhs in temporary to prevent aliasing problems in a = a * a;
|
||||
// TODO: Do not pass the xpr object to evalTo() (Jitse)
|
||||
kernel.srcEvaluator().evalTo(kernel.dstEvaluator(), kernel.dstExpression());
|
||||
}
|
||||
};
|
||||
|
||||
/***************************************************************************
|
||||
* Part 4 : Generic Assignment routine
|
||||
* Part 4 : Generic dense assignment kernel
|
||||
***************************************************************************/
|
||||
|
||||
// This class generalize the assignment of a coefficient (or packet) from one dense evaluator
|
||||
@@ -523,7 +534,7 @@ struct dense_assignment_loop<Kernel, AllAtOnceTraversal, NoUnrolling>
|
||||
// This abstraction level permits to keep the evaluation loops as simple and as generic as possible.
|
||||
// One can customize the assignment using this generic dense_assignment_kernel with different
|
||||
// functors, or by completely overloading it, by-passing a functor.
|
||||
template<typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor>
|
||||
template<typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor, int Version = Specialized>
|
||||
class generic_dense_assignment_kernel
|
||||
{
|
||||
protected:
|
||||
@@ -534,36 +545,46 @@ public:
|
||||
typedef DstEvaluatorTypeT DstEvaluatorType;
|
||||
typedef SrcEvaluatorTypeT SrcEvaluatorType;
|
||||
typedef typename DstEvaluatorType::Scalar Scalar;
|
||||
typedef typename DstEvaluatorType::Index Index;
|
||||
typedef copy_using_evaluator_traits<DstXprType, SrcXprType> AssignmentTraits;
|
||||
typedef typename DstEvaluatorType::StorageIndex StorageIndex;
|
||||
typedef copy_using_evaluator_traits<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor> AssignmentTraits;
|
||||
typedef typename AssignmentTraits::PacketType PacketType;
|
||||
|
||||
|
||||
generic_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
|
||||
EIGEN_DEVICE_FUNC generic_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
|
||||
: m_dst(dst), m_src(src), m_functor(func), m_dstExpr(dstExpr)
|
||||
{}
|
||||
{
|
||||
#ifdef EIGEN_DEBUG_ASSIGN
|
||||
AssignmentTraits::debug();
|
||||
#endif
|
||||
}
|
||||
|
||||
Index size() const { return m_dstExpr.size(); }
|
||||
Index innerSize() const { return m_dstExpr.innerSize(); }
|
||||
Index outerSize() const { return m_dstExpr.outerSize(); }
|
||||
Index outerStride() const { return m_dstExpr.outerStride(); }
|
||||
EIGEN_DEVICE_FUNC Index size() const { return m_dstExpr.size(); }
|
||||
EIGEN_DEVICE_FUNC Index innerSize() const { return m_dstExpr.innerSize(); }
|
||||
EIGEN_DEVICE_FUNC Index outerSize() const { return m_dstExpr.outerSize(); }
|
||||
EIGEN_DEVICE_FUNC Index rows() const { return m_dstExpr.rows(); }
|
||||
EIGEN_DEVICE_FUNC Index cols() const { return m_dstExpr.cols(); }
|
||||
EIGEN_DEVICE_FUNC Index outerStride() const { return m_dstExpr.outerStride(); }
|
||||
|
||||
// TODO get rid of this one:
|
||||
DstXprType& dstExpression() const { return m_dstExpr; }
|
||||
EIGEN_DEVICE_FUNC DstXprType& dstExpression() const { return m_dstExpr; }
|
||||
|
||||
DstEvaluatorType& dstEvaluator() { return m_dst; }
|
||||
const SrcEvaluatorType& srcEvaluator() const { return m_src; }
|
||||
EIGEN_DEVICE_FUNC DstEvaluatorType& dstEvaluator() { return m_dst; }
|
||||
EIGEN_DEVICE_FUNC const SrcEvaluatorType& srcEvaluator() const { return m_src; }
|
||||
|
||||
void assignCoeff(Index row, Index col)
|
||||
/// Assign src(row,col) to dst(row,col) through the assignment functor.
|
||||
EIGEN_DEVICE_FUNC void assignCoeff(Index row, Index col)
|
||||
{
|
||||
m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
|
||||
}
|
||||
|
||||
void assignCoeff(Index index)
|
||||
/// \sa assignCoeff(Index,Index)
|
||||
EIGEN_DEVICE_FUNC void assignCoeff(Index index)
|
||||
{
|
||||
m_functor.assignCoeff(m_dst.coeffRef(index), m_src.coeff(index));
|
||||
}
|
||||
|
||||
void assignCoeffByOuterInner(Index outer, Index inner)
|
||||
/// \sa assignCoeff(Index,Index)
|
||||
EIGEN_DEVICE_FUNC void assignCoeffByOuterInner(Index outer, Index inner)
|
||||
{
|
||||
Index row = rowIndexByOuterInner(outer, inner);
|
||||
Index col = colIndexByOuterInner(outer, inner);
|
||||
@@ -571,41 +592,41 @@ public:
|
||||
}
|
||||
|
||||
|
||||
template<int StoreMode, int LoadMode>
|
||||
void assignPacket(Index row, Index col)
|
||||
template<int StoreMode, int LoadMode, typename PacketType>
|
||||
EIGEN_DEVICE_FUNC void assignPacket(Index row, Index col)
|
||||
{
|
||||
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(row,col), m_src.template packet<LoadMode>(row,col));
|
||||
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(row,col), m_src.template packet<LoadMode,PacketType>(row,col));
|
||||
}
|
||||
|
||||
template<int StoreMode, int LoadMode>
|
||||
void assignPacket(Index index)
|
||||
template<int StoreMode, int LoadMode, typename PacketType>
|
||||
EIGEN_DEVICE_FUNC void assignPacket(Index index)
|
||||
{
|
||||
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(index), m_src.template packet<LoadMode>(index));
|
||||
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(index), m_src.template packet<LoadMode,PacketType>(index));
|
||||
}
|
||||
|
||||
template<int StoreMode, int LoadMode>
|
||||
void assignPacketByOuterInner(Index outer, Index inner)
|
||||
template<int StoreMode, int LoadMode, typename PacketType>
|
||||
EIGEN_DEVICE_FUNC void assignPacketByOuterInner(Index outer, Index inner)
|
||||
{
|
||||
Index row = rowIndexByOuterInner(outer, inner);
|
||||
Index col = colIndexByOuterInner(outer, inner);
|
||||
assignPacket<StoreMode,LoadMode>(row, col);
|
||||
assignPacket<StoreMode,LoadMode,PacketType>(row, col);
|
||||
}
|
||||
|
||||
static Index rowIndexByOuterInner(Index outer, Index inner)
|
||||
EIGEN_DEVICE_FUNC static Index rowIndexByOuterInner(Index outer, Index inner)
|
||||
{
|
||||
typedef typename DstEvaluatorType::ExpressionTraits Traits;
|
||||
return int(Traits::RowsAtCompileTime) == 1 ? 0
|
||||
: int(Traits::ColsAtCompileTime) == 1 ? inner
|
||||
: int(Traits::Flags)&RowMajorBit ? outer
|
||||
: int(DstEvaluatorType::Flags)&RowMajorBit ? outer
|
||||
: inner;
|
||||
}
|
||||
|
||||
static Index colIndexByOuterInner(Index outer, Index inner)
|
||||
EIGEN_DEVICE_FUNC static Index colIndexByOuterInner(Index outer, Index inner)
|
||||
{
|
||||
typedef typename DstEvaluatorType::ExpressionTraits Traits;
|
||||
return int(Traits::ColsAtCompileTime) == 1 ? 0
|
||||
: int(Traits::RowsAtCompileTime) == 1 ? inner
|
||||
: int(Traits::Flags)&RowMajorBit ? inner
|
||||
: int(DstEvaluatorType::Flags)&RowMajorBit ? inner
|
||||
: outer;
|
||||
}
|
||||
|
||||
@@ -617,17 +638,17 @@ protected:
|
||||
DstXprType& m_dstExpr;
|
||||
};
|
||||
|
||||
/***************************************************************************
|
||||
* Part 5 : Entry point for dense rectangular assignment
|
||||
***************************************************************************/
|
||||
|
||||
template<typename DstXprType, typename SrcXprType, typename Functor>
|
||||
void call_dense_assignment_loop(const DstXprType& dst, const SrcXprType& src, const Functor &func)
|
||||
EIGEN_DEVICE_FUNC void call_dense_assignment_loop(const DstXprType& dst, const SrcXprType& src, const Functor &func)
|
||||
{
|
||||
#ifdef EIGEN_DEBUG_ASSIGN
|
||||
// TODO these traits should be computed from information provided by the evaluators
|
||||
internal::copy_using_evaluator_traits<DstXprType, SrcXprType>::debug();
|
||||
#endif
|
||||
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
|
||||
|
||||
typedef typename evaluator<DstXprType>::type DstEvaluatorType;
|
||||
typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
|
||||
typedef evaluator<DstXprType> DstEvaluatorType;
|
||||
typedef evaluator<SrcXprType> SrcEvaluatorType;
|
||||
|
||||
DstEvaluatorType dstEvaluator(dst);
|
||||
SrcEvaluatorType srcEvaluator(src);
|
||||
@@ -639,201 +660,166 @@ void call_dense_assignment_loop(const DstXprType& dst, const SrcXprType& src, co
|
||||
}
|
||||
|
||||
template<typename DstXprType, typename SrcXprType>
|
||||
void call_dense_assignment_loop(const DstXprType& dst, const SrcXprType& src)
|
||||
EIGEN_DEVICE_FUNC void call_dense_assignment_loop(const DstXprType& dst, const SrcXprType& src)
|
||||
{
|
||||
call_dense_assignment_loop(dst, src, internal::assign_op<typename DstXprType::Scalar>());
|
||||
}
|
||||
|
||||
/***************************************************************************
|
||||
* Part 5 : Entry points
|
||||
* Part 6 : Generic assignment
|
||||
***************************************************************************/
|
||||
|
||||
// Based on DenseBase::LazyAssign()
|
||||
// The following functions are just for testing and they are meant to be moved to operator= and the likes.
|
||||
// Based on the respective shapes of the destination and source,
|
||||
// the class AssignmentKind determine the kind of assignment mechanism.
|
||||
// AssignmentKind must define a Kind typedef.
|
||||
template<typename DstShape, typename SrcShape> struct AssignmentKind;
|
||||
|
||||
template<typename DstXprType, template <typename> class StorageBase, typename SrcXprType>
|
||||
EIGEN_STRONG_INLINE
|
||||
const DstXprType& copy_using_evaluator(const NoAlias<DstXprType, StorageBase>& dst,
|
||||
const EigenBase<SrcXprType>& src)
|
||||
{
|
||||
return noalias_copy_using_evaluator(dst.expression(), src.derived(), internal::assign_op<typename DstXprType::Scalar>());
|
||||
}
|
||||
// Assignement kind defined in this file:
|
||||
struct Dense2Dense {};
|
||||
struct EigenBase2EigenBase {};
|
||||
|
||||
template<typename XprType, int AssumeAliasing = evaluator_traits<XprType>::AssumeAliasing>
|
||||
struct AddEvalIfAssumingAliasing;
|
||||
|
||||
template<typename XprType>
|
||||
struct AddEvalIfAssumingAliasing<XprType, 0>
|
||||
{
|
||||
static const XprType& run(const XprType& xpr)
|
||||
{
|
||||
return xpr;
|
||||
}
|
||||
};
|
||||
|
||||
template<typename XprType>
|
||||
struct AddEvalIfAssumingAliasing<XprType, 1>
|
||||
{
|
||||
static const EvalToTemp<XprType> run(const XprType& xpr)
|
||||
{
|
||||
return EvalToTemp<XprType>(xpr);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename DstXprType, typename SrcXprType, typename Functor>
|
||||
EIGEN_STRONG_INLINE
|
||||
const DstXprType& copy_using_evaluator(const EigenBase<DstXprType>& dst, const EigenBase<SrcXprType>& src, const Functor &func)
|
||||
{
|
||||
return noalias_copy_using_evaluator(dst.const_cast_derived(),
|
||||
AddEvalIfAssumingAliasing<SrcXprType>::run(src.derived()),
|
||||
func
|
||||
);
|
||||
}
|
||||
|
||||
// this mimics operator=
|
||||
template<typename DstXprType, typename SrcXprType>
|
||||
EIGEN_STRONG_INLINE
|
||||
const DstXprType& copy_using_evaluator(const EigenBase<DstXprType>& dst, const EigenBase<SrcXprType>& src)
|
||||
{
|
||||
return copy_using_evaluator(dst.const_cast_derived(), src.derived(), internal::assign_op<typename DstXprType::Scalar>());
|
||||
}
|
||||
|
||||
template<typename DstXprType, typename SrcXprType, typename Functor>
|
||||
EIGEN_STRONG_INLINE
|
||||
const DstXprType& noalias_copy_using_evaluator(const PlainObjectBase<DstXprType>& dst, const EigenBase<SrcXprType>& src, const Functor &func)
|
||||
{
|
||||
#ifdef EIGEN_DEBUG_ASSIGN
|
||||
internal::copy_using_evaluator_traits<DstXprType, SrcXprType>::debug();
|
||||
#endif
|
||||
#ifdef EIGEN_NO_AUTOMATIC_RESIZING
|
||||
eigen_assert((dst.size()==0 || (IsVectorAtCompileTime ? (dst.size() == src.size())
|
||||
: (dst.rows() == src.rows() && dst.cols() == src.cols())))
|
||||
&& "Size mismatch. Automatic resizing is disabled because EIGEN_NO_AUTOMATIC_RESIZING is defined");
|
||||
#else
|
||||
dst.const_cast_derived().resizeLike(src.derived());
|
||||
#endif
|
||||
call_dense_assignment_loop(dst.const_cast_derived(), src.derived(), func);
|
||||
return dst.derived();
|
||||
}
|
||||
|
||||
template<typename DstXprType, typename SrcXprType, typename Functor>
|
||||
EIGEN_STRONG_INLINE
|
||||
const DstXprType& noalias_copy_using_evaluator(const EigenBase<DstXprType>& dst, const EigenBase<SrcXprType>& src, const Functor &func)
|
||||
{
|
||||
call_dense_assignment_loop(dst.const_cast_derived(), src.derived(), func);
|
||||
return dst.derived();
|
||||
}
|
||||
|
||||
// Based on DenseBase::swap()
|
||||
// TODO: Check whether we need to do something special for swapping two
|
||||
// Arrays or Matrices. (Jitse)
|
||||
|
||||
// Overload default assignPacket behavior for swapping them
|
||||
template<typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT>
|
||||
class swap_kernel : public generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar> >
|
||||
{
|
||||
typedef generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar> > Base;
|
||||
typedef typename DstEvaluatorTypeT::PacketScalar PacketScalar;
|
||||
using Base::m_dst;
|
||||
using Base::m_src;
|
||||
using Base::m_functor;
|
||||
|
||||
public:
|
||||
typedef typename Base::Scalar Scalar;
|
||||
typedef typename Base::Index Index;
|
||||
typedef typename Base::DstXprType DstXprType;
|
||||
|
||||
swap_kernel(DstEvaluatorTypeT &dst, const SrcEvaluatorTypeT &src, DstXprType& dstExpr)
|
||||
: Base(dst, src, swap_assign_op<Scalar>(), dstExpr)
|
||||
{}
|
||||
|
||||
template<int StoreMode, int LoadMode>
|
||||
void assignPacket(Index row, Index col)
|
||||
{
|
||||
m_functor.template swapPacket<StoreMode,LoadMode,PacketScalar>(&m_dst.coeffRef(row,col), &const_cast<SrcEvaluatorTypeT&>(m_src).coeffRef(row,col));
|
||||
}
|
||||
|
||||
template<int StoreMode, int LoadMode>
|
||||
void assignPacket(Index index)
|
||||
{
|
||||
m_functor.template swapPacket<StoreMode,LoadMode,PacketScalar>(&m_dst.coeffRef(index), &const_cast<SrcEvaluatorTypeT&>(m_src).coeffRef(index));
|
||||
}
|
||||
|
||||
// TODO find a simple way not to have to copy/paste this function from generic_dense_assignment_kernel, by simple I mean no CRTP (Gael)
|
||||
template<int StoreMode, int LoadMode>
|
||||
void assignPacketByOuterInner(Index outer, Index inner)
|
||||
{
|
||||
Index row = Base::rowIndexByOuterInner(outer, inner);
|
||||
Index col = Base::colIndexByOuterInner(outer, inner);
|
||||
assignPacket<StoreMode,LoadMode>(row, col);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename DstXprType, typename SrcXprType>
|
||||
void swap_using_evaluator(const DstXprType& dst, const SrcXprType& src)
|
||||
{
|
||||
// TODO there is too much redundancy with call_dense_assignment_loop
|
||||
|
||||
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
|
||||
|
||||
typedef typename evaluator<DstXprType>::type DstEvaluatorType;
|
||||
typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
|
||||
|
||||
DstEvaluatorType dstEvaluator(dst);
|
||||
SrcEvaluatorType srcEvaluator(src);
|
||||
template<typename,typename> struct AssignmentKind { typedef EigenBase2EigenBase Kind; };
|
||||
template<> struct AssignmentKind<DenseShape,DenseShape> { typedef Dense2Dense Kind; };
|
||||
|
||||
typedef swap_kernel<DstEvaluatorType,SrcEvaluatorType> Kernel;
|
||||
Kernel kernel(dstEvaluator, srcEvaluator, dst.const_cast_derived());
|
||||
// This is the main assignment class
|
||||
template< typename DstXprType, typename SrcXprType, typename Functor,
|
||||
typename Kind = typename AssignmentKind< typename evaluator_traits<DstXprType>::Shape , typename evaluator_traits<SrcXprType>::Shape >::Kind,
|
||||
typename Scalar = typename DstXprType::Scalar>
|
||||
struct Assignment;
|
||||
|
||||
|
||||
// The only purpose of this call_assignment() function is to deal with noalias() / AssumeAliasing and automatic transposition.
|
||||
// Indeed, I (Gael) think that this concept of AssumeAliasing was a mistake, and it makes thing quite complicated.
|
||||
// So this intermediate function removes everything related to AssumeAliasing such that Assignment
|
||||
// does not has to bother about these annoying details.
|
||||
|
||||
template<typename Dst, typename Src>
|
||||
EIGEN_DEVICE_FUNC void call_assignment(Dst& dst, const Src& src)
|
||||
{
|
||||
call_assignment(dst, src, internal::assign_op<typename Dst::Scalar>());
|
||||
}
|
||||
template<typename Dst, typename Src>
|
||||
EIGEN_DEVICE_FUNC void call_assignment(const Dst& dst, const Src& src)
|
||||
{
|
||||
call_assignment(dst, src, internal::assign_op<typename Dst::Scalar>());
|
||||
}
|
||||
|
||||
// Deal with AssumeAliasing
|
||||
template<typename Dst, typename Src, typename Func>
|
||||
EIGEN_DEVICE_FUNC void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if<evaluator_traits<Src>::AssumeAliasing==1, void*>::type = 0)
|
||||
{
|
||||
typename plain_matrix_type<Src>::type tmp(src);
|
||||
call_assignment_no_alias(dst, tmp, func);
|
||||
}
|
||||
|
||||
template<typename Dst, typename Src, typename Func>
|
||||
EIGEN_DEVICE_FUNC void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if<evaluator_traits<Src>::AssumeAliasing==0, void*>::type = 0)
|
||||
{
|
||||
call_assignment_no_alias(dst, src, func);
|
||||
}
|
||||
|
||||
// by-pass AssumeAliasing
|
||||
// FIXME the const version should probably not be needed
|
||||
// When there is no aliasing, we require that 'dst' has been properly resized
|
||||
template<typename Dst, template <typename> class StorageBase, typename Src, typename Func>
|
||||
EIGEN_DEVICE_FUNC void call_assignment(const NoAlias<Dst,StorageBase>& dst, const Src& src, const Func& func)
|
||||
{
|
||||
call_assignment_no_alias(dst.expression(), src, func);
|
||||
}
|
||||
template<typename Dst, template <typename> class StorageBase, typename Src, typename Func>
|
||||
EIGEN_DEVICE_FUNC void call_assignment(NoAlias<Dst,StorageBase>& dst, const Src& src, const Func& func)
|
||||
{
|
||||
call_assignment_no_alias(dst.expression(), src, func);
|
||||
}
|
||||
|
||||
|
||||
template<typename Dst, typename Src, typename Func>
|
||||
EIGEN_DEVICE_FUNC void call_assignment_no_alias(Dst& dst, const Src& src, const Func& func)
|
||||
{
|
||||
enum {
|
||||
NeedToTranspose = ( (int(Dst::RowsAtCompileTime) == 1 && int(Src::ColsAtCompileTime) == 1)
|
||||
| // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
|
||||
// revert to || as soon as not needed anymore.
|
||||
(int(Dst::ColsAtCompileTime) == 1 && int(Src::RowsAtCompileTime) == 1))
|
||||
&& int(Dst::SizeAtCompileTime) != 1
|
||||
};
|
||||
|
||||
Index dstRows = NeedToTranspose ? src.cols() : src.rows();
|
||||
Index dstCols = NeedToTranspose ? src.rows() : src.cols();
|
||||
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
|
||||
dst.resize(dstRows, dstCols);
|
||||
|
||||
dense_assignment_loop<Kernel>::run(kernel);
|
||||
}
|
||||
typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst>::type ActualDstTypeCleaned;
|
||||
typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst&>::type ActualDstType;
|
||||
ActualDstType actualDst(dst);
|
||||
|
||||
// TODO check whether this is the right place to perform these checks:
|
||||
EIGEN_STATIC_ASSERT_LVALUE(Dst)
|
||||
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned,Src)
|
||||
|
||||
// Based on MatrixBase::operator+= (in CwiseBinaryOp.h)
|
||||
template<typename DstXprType, typename SrcXprType>
|
||||
void add_assign_using_evaluator(const MatrixBase<DstXprType>& dst, const MatrixBase<SrcXprType>& src)
|
||||
// TODO this line is commented to allow matrix = permutation
|
||||
// Actually, the "Scalar" type for a permutation matrix does not really make sense,
|
||||
// perhaps it could be void, and EIGEN_CHECK_BINARY_COMPATIBILIY could allow micing void with anything...?
|
||||
// EIGEN_CHECK_BINARY_COMPATIBILIY(Func,typename ActualDstTypeCleaned::Scalar,typename Src::Scalar);
|
||||
|
||||
Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
|
||||
}
|
||||
template<typename Dst, typename Src>
|
||||
EIGEN_DEVICE_FUNC void call_assignment_no_alias(Dst& dst, const Src& src)
|
||||
{
|
||||
typedef typename DstXprType::Scalar Scalar;
|
||||
copy_using_evaluator(dst.derived(), src.derived(), add_assign_op<Scalar>());
|
||||
call_assignment_no_alias(dst, src, internal::assign_op<typename Dst::Scalar>());
|
||||
}
|
||||
|
||||
// Based on ArrayBase::operator+=
|
||||
template<typename DstXprType, typename SrcXprType>
|
||||
void add_assign_using_evaluator(const ArrayBase<DstXprType>& dst, const ArrayBase<SrcXprType>& src)
|
||||
template<typename Dst, typename Src, typename Func>
|
||||
EIGEN_DEVICE_FUNC void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src, const Func& func)
|
||||
{
|
||||
typedef typename DstXprType::Scalar Scalar;
|
||||
copy_using_evaluator(dst.derived(), src.derived(), add_assign_op<Scalar>());
|
||||
Index dstRows = src.rows();
|
||||
Index dstCols = src.cols();
|
||||
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
|
||||
dst.resize(dstRows, dstCols);
|
||||
|
||||
// TODO check whether this is the right place to perform these checks:
|
||||
EIGEN_STATIC_ASSERT_LVALUE(Dst)
|
||||
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Dst,Src)
|
||||
|
||||
Assignment<Dst,Src,Func>::run(dst, src, func);
|
||||
}
|
||||
|
||||
// TODO: Add add_assign_using_evaluator for EigenBase ? (Jitse)
|
||||
|
||||
template<typename DstXprType, typename SrcXprType>
|
||||
void subtract_assign_using_evaluator(const MatrixBase<DstXprType>& dst, const MatrixBase<SrcXprType>& src)
|
||||
template<typename Dst, typename Src>
|
||||
EIGEN_DEVICE_FUNC void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src)
|
||||
{
|
||||
typedef typename DstXprType::Scalar Scalar;
|
||||
copy_using_evaluator(dst.derived(), src.derived(), sub_assign_op<Scalar>());
|
||||
call_assignment_no_alias_no_transpose(dst, src, internal::assign_op<typename Dst::Scalar>());
|
||||
}
|
||||
|
||||
template<typename DstXprType, typename SrcXprType>
|
||||
void subtract_assign_using_evaluator(const ArrayBase<DstXprType>& dst, const ArrayBase<SrcXprType>& src)
|
||||
// forward declaration
|
||||
template<typename Dst, typename Src> void check_for_aliasing(const Dst &dst, const Src &src);
|
||||
|
||||
// Generic Dense to Dense assignment
|
||||
template< typename DstXprType, typename SrcXprType, typename Functor, typename Scalar>
|
||||
struct Assignment<DstXprType, SrcXprType, Functor, Dense2Dense, Scalar>
|
||||
{
|
||||
typedef typename DstXprType::Scalar Scalar;
|
||||
copy_using_evaluator(dst.derived(), src.derived(), sub_assign_op<Scalar>());
|
||||
}
|
||||
EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
|
||||
{
|
||||
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
|
||||
|
||||
#ifndef EIGEN_NO_DEBUG
|
||||
internal::check_for_aliasing(dst, src);
|
||||
#endif
|
||||
|
||||
call_dense_assignment_loop(dst, src, func);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename DstXprType, typename SrcXprType>
|
||||
void multiply_assign_using_evaluator(const ArrayBase<DstXprType>& dst, const ArrayBase<SrcXprType>& src)
|
||||
// Generic assignment through evalTo.
|
||||
// TODO: not sure we have to keep that one, but it helps porting current code to new evaluator mechanism.
|
||||
template< typename DstXprType, typename SrcXprType, typename Functor, typename Scalar>
|
||||
struct Assignment<DstXprType, SrcXprType, Functor, EigenBase2EigenBase, Scalar>
|
||||
{
|
||||
typedef typename DstXprType::Scalar Scalar;
|
||||
copy_using_evaluator(dst.derived(), src.derived(), mul_assign_op<Scalar>());
|
||||
}
|
||||
|
||||
template<typename DstXprType, typename SrcXprType>
|
||||
void divide_assign_using_evaluator(const ArrayBase<DstXprType>& dst, const ArrayBase<SrcXprType>& src)
|
||||
{
|
||||
typedef typename DstXprType::Scalar Scalar;
|
||||
copy_using_evaluator(dst.derived(), src.derived(), div_assign_op<Scalar>());
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar> &/*func*/)
|
||||
{
|
||||
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
|
||||
src.evalTo(dst);
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace internal
|
||||
|
||||
|
||||
255
Eigen/src/Core/Assign_MKL.h
Normal file → Executable file
255
Eigen/src/Core/Assign_MKL.h
Normal file → Executable file
@@ -1,6 +1,7 @@
|
||||
/*
|
||||
Copyright (c) 2011, Intel Corporation. All rights reserved.
|
||||
|
||||
Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
|
||||
|
||||
Redistribution and use in source and binary forms, with or without modification,
|
||||
are permitted provided that the following conditions are met:
|
||||
|
||||
@@ -37,17 +38,13 @@ namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename Op> struct vml_call
|
||||
{ enum { IsSupported = 0 }; };
|
||||
|
||||
template<typename Dst, typename Src, typename UnaryOp>
|
||||
template<typename Dst, typename Src>
|
||||
class vml_assign_traits
|
||||
{
|
||||
private:
|
||||
enum {
|
||||
DstHasDirectAccess = Dst::Flags & DirectAccessBit,
|
||||
SrcHasDirectAccess = Src::Flags & DirectAccessBit,
|
||||
|
||||
StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
|
||||
InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
|
||||
: int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
|
||||
@@ -57,166 +54,118 @@ class vml_assign_traits
|
||||
: int(Dst::MaxRowsAtCompileTime),
|
||||
MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
|
||||
|
||||
MightEnableVml = vml_call<UnaryOp>::IsSupported && StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess
|
||||
&& Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1,
|
||||
MightEnableVml = StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1,
|
||||
MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
|
||||
VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize,
|
||||
LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD,
|
||||
MayEnableVml = MightEnableVml && LargeEnough,
|
||||
MayLinearize = MayEnableVml && MightLinearize
|
||||
LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD
|
||||
};
|
||||
public:
|
||||
enum {
|
||||
Traversal = MayLinearize ? LinearVectorizedTraversal
|
||||
: MayEnableVml ? InnerVectorizedTraversal
|
||||
: DefaultTraversal
|
||||
EnableVml = MightEnableVml && LargeEnough,
|
||||
Traversal = MightLinearize ? LinearTraversal : DefaultTraversal
|
||||
};
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling,
|
||||
int VmlTraversal = vml_assign_traits<Derived1, Derived2, UnaryOp>::Traversal >
|
||||
struct vml_assign_impl
|
||||
: assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>
|
||||
{
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
|
||||
struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, InnerVectorizedTraversal>
|
||||
{
|
||||
typedef typename Derived1::Scalar Scalar;
|
||||
typedef typename Derived1::Index Index;
|
||||
static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
|
||||
{
|
||||
// in case we want to (or have to) skip VML at runtime we can call:
|
||||
// assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
|
||||
const Index innerSize = dst.innerSize();
|
||||
const Index outerSize = dst.outerSize();
|
||||
for(Index outer = 0; outer < outerSize; ++outer) {
|
||||
const Scalar *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) :
|
||||
&(src.nestedExpression().coeffRef(0, outer));
|
||||
Scalar *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer));
|
||||
vml_call<UnaryOp>::run(src.functor(), innerSize, src_ptr, dst_ptr );
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
|
||||
struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, LinearVectorizedTraversal>
|
||||
{
|
||||
static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
|
||||
{
|
||||
// in case we want to (or have to) skip VML at runtime we can call:
|
||||
// assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
|
||||
vml_call<UnaryOp>::run(src.functor(), dst.size(), src.nestedExpression().data(), dst.data() );
|
||||
}
|
||||
};
|
||||
|
||||
// Macroses
|
||||
|
||||
#define EIGEN_MKL_VML_SPECIALIZE_ASSIGN(TRAVERSAL,UNROLLING) \
|
||||
template<typename Derived1, typename Derived2, typename UnaryOp> \
|
||||
struct assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>, TRAVERSAL, UNROLLING, Specialized> { \
|
||||
static inline void run(Derived1 &dst, const Eigen::CwiseUnaryOp<UnaryOp, Derived2> &src) { \
|
||||
vml_assign_impl<Derived1,Derived2,UnaryOp,TRAVERSAL,UNROLLING>::run(dst, src); \
|
||||
} \
|
||||
};
|
||||
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,NoUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,CompleteUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,InnerUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,NoUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,CompleteUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,NoUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,CompleteUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,InnerUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,CompleteUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,NoUnrolling)
|
||||
EIGEN_MKL_VML_SPECIALIZE_ASSIGN(SliceVectorizedTraversal,NoUnrolling)
|
||||
|
||||
|
||||
#define EIGEN_PP_EXPAND(ARG) ARG
|
||||
#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
|
||||
#define EIGEN_MKL_VML_MODE VML_HA
|
||||
#define EIGEN_VMLMODE_EXPAND_LA , VML_HA
|
||||
#else
|
||||
#define EIGEN_MKL_VML_MODE VML_LA
|
||||
#define EIGEN_VMLMODE_EXPAND_LA , VML_LA
|
||||
#endif
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE) \
|
||||
template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > { \
|
||||
enum { IsSupported = 1 }; \
|
||||
static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/, \
|
||||
int size, const EIGENTYPE* src, EIGENTYPE* dst) { \
|
||||
VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst); \
|
||||
} \
|
||||
#define EIGEN_VMLMODE_EXPAND__
|
||||
|
||||
#define EIGEN_VMLMODE_PREFIX_LA vm
|
||||
#define EIGEN_VMLMODE_PREFIX__ v
|
||||
#define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_,VMLMODE)
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \
|
||||
template< typename DstXprType, typename SrcXprNested> \
|
||||
struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE>, \
|
||||
Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml,EIGENTYPE>::type> { \
|
||||
typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \
|
||||
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE> &/*func*/) { \
|
||||
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
|
||||
if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) { \
|
||||
VMLOP(dst.size(), (const VMLTYPE*)src.nestedExpression().data(), \
|
||||
(VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE) ); \
|
||||
} else { \
|
||||
const Index outerSize = dst.outerSize(); \
|
||||
for(Index outer = 0; outer < outerSize; ++outer) { \
|
||||
const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) : \
|
||||
&(src.nestedExpression().coeffRef(0, outer)); \
|
||||
EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); \
|
||||
VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, \
|
||||
(VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE)); \
|
||||
} \
|
||||
} \
|
||||
} \
|
||||
}; \
|
||||
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),s##VMLOP), float, float, VMLMODE) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),d##VMLOP), double, double, VMLMODE)
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),c##VMLOP), scomplex, MKL_Complex8, VMLMODE) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),z##VMLOP), dcomplex, MKL_Complex16, VMLMODE)
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)
|
||||
|
||||
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin, Sin, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin, Asin, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh, Sinh, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos, Cos, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos, Acos, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh, Cosh, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan, Tan, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan, Atan, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh, Tanh, LA)
|
||||
// EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs, _)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp, Exp, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log, Ln, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt, Sqrt, _)
|
||||
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr, _)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg, _)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round, _)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor, _)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _)
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \
|
||||
template< typename DstXprType, typename SrcXprNested> \
|
||||
struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE>, \
|
||||
Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml,EIGENTYPE>::type> { \
|
||||
typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \
|
||||
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE> &/*func*/) { \
|
||||
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
|
||||
VMLTYPE exponent = reinterpret_cast<const VMLTYPE&>(src.functor().m_exponent); \
|
||||
if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) \
|
||||
{ \
|
||||
VMLOP( dst.size(), (const VMLTYPE*)src.nestedExpression().data(), exponent, \
|
||||
(VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE) ); \
|
||||
} else { \
|
||||
const Index outerSize = dst.outerSize(); \
|
||||
for(Index outer = 0; outer < outerSize; ++outer) { \
|
||||
const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) : \
|
||||
&(src.nestedExpression().coeffRef(0, outer)); \
|
||||
EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); \
|
||||
VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, exponent, \
|
||||
(VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE)); \
|
||||
} \
|
||||
} \
|
||||
} \
|
||||
};
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE) \
|
||||
template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > { \
|
||||
enum { IsSupported = 1 }; \
|
||||
static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/, \
|
||||
int size, const EIGENTYPE* src, EIGENTYPE* dst) { \
|
||||
MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE; \
|
||||
VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst, vmlMode); \
|
||||
} \
|
||||
};
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE) \
|
||||
template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > { \
|
||||
enum { IsSupported = 1 }; \
|
||||
static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& func, \
|
||||
int size, const EIGENTYPE* src, EIGENTYPE* dst) { \
|
||||
EIGENTYPE exponent = func.m_exponent; \
|
||||
MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE; \
|
||||
VMLOP(&size, (const VMLTYPE*)src, (const VMLTYPE*)&exponent, \
|
||||
(VMLTYPE*)dst, &vmlMode); \
|
||||
} \
|
||||
};
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vs##VMLOP, float, float) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vd##VMLOP, double, double)
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vc##VMLOP, scomplex, MKL_Complex8) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vz##VMLOP, dcomplex, MKL_Complex16)
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP)
|
||||
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vms##VMLOP, float, float) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmd##VMLOP, double, double)
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmc##VMLOP, scomplex, MKL_Complex8) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmz##VMLOP, dcomplex, MKL_Complex16)
|
||||
|
||||
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(EIGENOP, VMLOP) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP) \
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP)
|
||||
|
||||
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sin, Sin)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(asin, Asin)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(cos, Cos)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(acos, Acos)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(tan, Tan)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(atan, Atan)
|
||||
//EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(exp, Exp)
|
||||
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(log, Ln)
|
||||
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.
|
||||
#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)
|
||||
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzpowx_, dcomplex, MKL_Complex16)
|
||||
#endif
|
||||
|
||||
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float, float, LA)
|
||||
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double, double, LA)
|
||||
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8, LA)
|
||||
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA)
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
|
||||
@@ -32,7 +32,7 @@ class BandMatrixBase : public EigenBase<Derived>
|
||||
};
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
|
||||
typedef typename DenseMatrixType::Index Index;
|
||||
typedef typename DenseMatrixType::StorageIndex StorageIndex;
|
||||
typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
|
||||
typedef EigenBase<Derived> Base;
|
||||
|
||||
@@ -179,7 +179,7 @@ struct traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
|
||||
{
|
||||
typedef _Scalar Scalar;
|
||||
typedef Dense StorageKind;
|
||||
typedef DenseIndex Index;
|
||||
typedef Eigen::Index StorageIndex;
|
||||
enum {
|
||||
CoeffReadCost = NumTraits<Scalar>::ReadCost,
|
||||
RowsAtCompileTime = _Rows,
|
||||
@@ -201,10 +201,10 @@ class BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Sub
|
||||
public:
|
||||
|
||||
typedef typename internal::traits<BandMatrix>::Scalar Scalar;
|
||||
typedef typename internal::traits<BandMatrix>::Index Index;
|
||||
typedef typename internal::traits<BandMatrix>::StorageIndex StorageIndex;
|
||||
typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
|
||||
|
||||
inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
|
||||
explicit inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
|
||||
: m_coeffs(1+supers+subs,cols),
|
||||
m_rows(rows), m_supers(supers), m_subs(subs)
|
||||
{
|
||||
@@ -241,7 +241,7 @@ struct traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Opt
|
||||
{
|
||||
typedef typename _CoefficientsType::Scalar Scalar;
|
||||
typedef typename _CoefficientsType::StorageKind StorageKind;
|
||||
typedef typename _CoefficientsType::Index Index;
|
||||
typedef typename _CoefficientsType::StorageIndex StorageIndex;
|
||||
enum {
|
||||
CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost,
|
||||
RowsAtCompileTime = _Rows,
|
||||
@@ -264,9 +264,9 @@ class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsT
|
||||
|
||||
typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
|
||||
typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType;
|
||||
typedef typename internal::traits<BandMatrixWrapper>::Index Index;
|
||||
typedef typename internal::traits<BandMatrixWrapper>::StorageIndex StorageIndex;
|
||||
|
||||
inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
|
||||
explicit inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
|
||||
: m_coeffs(coeffs),
|
||||
m_rows(rows), m_supers(supers), m_subs(subs)
|
||||
{
|
||||
@@ -312,9 +312,9 @@ template<typename Scalar, int Size, int Options>
|
||||
class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor>
|
||||
{
|
||||
typedef BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor> Base;
|
||||
typedef typename Base::Index Index;
|
||||
typedef typename Base::StorageIndex StorageIndex;
|
||||
public:
|
||||
TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
|
||||
explicit TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
|
||||
|
||||
inline typename Base::template DiagonalIntReturnType<1>::Type super()
|
||||
{ return Base::template diagonal<1>(); }
|
||||
@@ -327,6 +327,25 @@ class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint
|
||||
protected:
|
||||
};
|
||||
|
||||
|
||||
struct BandShape {};
|
||||
|
||||
template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
|
||||
struct evaluator_traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
|
||||
: public evaluator_traits_base<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
|
||||
{
|
||||
typedef BandShape Shape;
|
||||
};
|
||||
|
||||
template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
|
||||
struct evaluator_traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
|
||||
: public evaluator_traits_base<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
|
||||
{
|
||||
typedef BandShape Shape;
|
||||
};
|
||||
|
||||
template<> struct AssignmentKind<DenseShape,BandShape> { typedef EigenBase2EigenBase Kind; };
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -55,7 +55,7 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
|
||||
typedef typename traits<XprType>::Scalar Scalar;
|
||||
typedef typename traits<XprType>::StorageKind StorageKind;
|
||||
typedef typename traits<XprType>::XprKind XprKind;
|
||||
typedef typename nested<XprType>::type XprTypeNested;
|
||||
typedef typename ref_selector<XprType>::type XprTypeNested;
|
||||
typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
|
||||
enum{
|
||||
MatrixRows = traits<XprType>::RowsAtCompileTime,
|
||||
@@ -68,6 +68,7 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
|
||||
MaxColsAtCompileTime = BlockCols==0 ? 0
|
||||
: ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
|
||||
: int(traits<XprType>::MaxColsAtCompileTime),
|
||||
|
||||
XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
|
||||
IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
|
||||
: (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
|
||||
@@ -80,18 +81,16 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
|
||||
OuterStrideAtCompileTime = HasSameStorageOrderAsXprType
|
||||
? int(outer_stride_at_compile_time<XprType>::ret)
|
||||
: int(inner_stride_at_compile_time<XprType>::ret),
|
||||
MaskPacketAccessBit = (InnerSize == Dynamic || (InnerSize % packet_traits<Scalar>::size) == 0)
|
||||
&& (InnerStrideAtCompileTime == 1)
|
||||
? PacketAccessBit : 0,
|
||||
MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % EIGEN_ALIGN_BYTES) == 0)) ? AlignedBit : 0,
|
||||
FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 || (InnerPanel && (traits<XprType>::Flags&LinearAccessBit))) ? LinearAccessBit : 0,
|
||||
|
||||
// FIXME, this traits is rather specialized for dense object and it needs to be cleaned further
|
||||
FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
|
||||
FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
|
||||
Flags0 = traits<XprType>::Flags & ( (HereditaryBits & ~RowMajorBit) |
|
||||
DirectAccessBit |
|
||||
MaskPacketAccessBit |
|
||||
MaskAlignedBit),
|
||||
Flags = Flags0 | FlagsLinearAccessBit | FlagsLvalueBit | FlagsRowMajorBit
|
||||
Flags = (traits<XprType>::Flags & (DirectAccessBit | (InnerPanel?CompressedAccessBit:0))) | FlagsLvalueBit | FlagsRowMajorBit,
|
||||
// FIXME DirectAccessBit should not be handled by expressions
|
||||
//
|
||||
// Alignment is needed by MapBase's assertions
|
||||
// We can sefely set it to false here. Internal alignment errors will be detected by an eigen_internal_assert in the respective evaluator
|
||||
Alignment = 0
|
||||
};
|
||||
};
|
||||
|
||||
@@ -111,6 +110,8 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class
|
||||
typedef Impl Base;
|
||||
EIGEN_GENERIC_PUBLIC_INTERFACE(Block)
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
|
||||
|
||||
typedef typename internal::remove_all<XprType>::type NestedExpression;
|
||||
|
||||
/** Column or Row constructor
|
||||
*/
|
||||
@@ -125,26 +126,26 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class
|
||||
/** Fixed-size constructor
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Block(XprType& xpr, Index a_startRow, Index a_startCol)
|
||||
: Impl(xpr, a_startRow, a_startCol)
|
||||
inline Block(XprType& xpr, Index startRow, Index startCol)
|
||||
: Impl(xpr, startRow, startCol)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
|
||||
eigen_assert(a_startRow >= 0 && BlockRows >= 1 && a_startRow + BlockRows <= xpr.rows()
|
||||
&& a_startCol >= 0 && BlockCols >= 1 && a_startCol + BlockCols <= xpr.cols());
|
||||
eigen_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= xpr.rows()
|
||||
&& startCol >= 0 && BlockCols >= 1 && startCol + BlockCols <= xpr.cols());
|
||||
}
|
||||
|
||||
/** Dynamic-size constructor
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Block(XprType& xpr,
|
||||
Index a_startRow, Index a_startCol,
|
||||
Index startRow, Index startCol,
|
||||
Index blockRows, Index blockCols)
|
||||
: Impl(xpr, a_startRow, a_startCol, blockRows, blockCols)
|
||||
: Impl(xpr, startRow, startCol, blockRows, blockCols)
|
||||
{
|
||||
eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
|
||||
&& (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
|
||||
eigen_assert(a_startRow >= 0 && blockRows >= 0 && a_startRow <= xpr.rows() - blockRows
|
||||
&& a_startCol >= 0 && blockCols >= 0 && a_startCol <= xpr.cols() - blockCols);
|
||||
eigen_assert(startRow >= 0 && blockRows >= 0 && startRow <= xpr.rows() - blockRows
|
||||
&& startCol >= 0 && blockCols >= 0 && startCol <= xpr.cols() - blockCols);
|
||||
}
|
||||
};
|
||||
|
||||
@@ -155,15 +156,15 @@ class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
|
||||
: public internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel>
|
||||
{
|
||||
typedef internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel> Impl;
|
||||
typedef typename XprType::Index Index;
|
||||
typedef typename XprType::StorageIndex StorageIndex;
|
||||
public:
|
||||
typedef Impl Base;
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
|
||||
EIGEN_DEVICE_FUNC inline BlockImpl(XprType& xpr, Index i) : Impl(xpr,i) {}
|
||||
EIGEN_DEVICE_FUNC inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol) : Impl(xpr, a_startRow, a_startCol) {}
|
||||
EIGEN_DEVICE_FUNC inline BlockImpl(XprType& xpr, Index startRow, Index startCol) : Impl(xpr, startRow, startCol) {}
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol, Index blockRows, Index blockCols)
|
||||
: Impl(xpr, a_startRow, a_startCol, blockRows, blockCols) {}
|
||||
inline BlockImpl(XprType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
|
||||
: Impl(xpr, startRow, startCol, blockRows, blockCols) {}
|
||||
};
|
||||
|
||||
namespace internal {
|
||||
@@ -179,7 +180,7 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
|
||||
|
||||
class InnerIterator;
|
||||
// class InnerIterator; // FIXME apparently never used
|
||||
|
||||
/** Column or Row constructor
|
||||
*/
|
||||
@@ -199,8 +200,8 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
|
||||
/** Fixed-size constructor
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline BlockImpl_dense(XprType& xpr, Index a_startRow, Index a_startCol)
|
||||
: m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
|
||||
inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
|
||||
: m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
|
||||
m_blockRows(BlockRows), m_blockCols(BlockCols)
|
||||
{}
|
||||
|
||||
@@ -208,9 +209,9 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline BlockImpl_dense(XprType& xpr,
|
||||
Index a_startRow, Index a_startCol,
|
||||
Index startRow, Index startCol,
|
||||
Index blockRows, Index blockCols)
|
||||
: m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
|
||||
: m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
|
||||
m_blockRows(blockRows), m_blockCols(blockCols)
|
||||
{}
|
||||
|
||||
@@ -307,13 +308,13 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
Index startRow() const
|
||||
StorageIndex startRow() const
|
||||
{
|
||||
return m_startRow.value();
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
Index startCol() const
|
||||
StorageIndex startCol() const
|
||||
{
|
||||
return m_startCol.value();
|
||||
}
|
||||
@@ -321,10 +322,10 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
|
||||
protected:
|
||||
|
||||
const typename XprType::Nested m_xpr;
|
||||
const internal::variable_if_dynamic<Index, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow;
|
||||
const internal::variable_if_dynamic<Index, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
|
||||
const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_blockRows;
|
||||
const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_blockCols;
|
||||
const internal::variable_if_dynamic<StorageIndex, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow;
|
||||
const internal::variable_if_dynamic<StorageIndex, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
|
||||
const internal::variable_if_dynamic<StorageIndex, RowsAtCompileTime> m_blockRows;
|
||||
const internal::variable_if_dynamic<StorageIndex, ColsAtCompileTime> m_blockCols;
|
||||
};
|
||||
|
||||
/** \internal Internal implementation of dense Blocks in the direct access case.*/
|
||||
@@ -333,6 +334,9 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
|
||||
: public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel> >
|
||||
{
|
||||
typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
|
||||
enum {
|
||||
XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0
|
||||
};
|
||||
public:
|
||||
|
||||
typedef MapBase<BlockType> Base;
|
||||
@@ -343,9 +347,8 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline BlockImpl_dense(XprType& xpr, Index i)
|
||||
: Base(internal::const_cast_ptr(&xpr.coeffRef(
|
||||
(BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0,
|
||||
(BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0)),
|
||||
: Base(xpr.data() + i * ( ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && (!XprTypeIsRowMajor))
|
||||
|| ((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && ( XprTypeIsRowMajor)) ? xpr.innerStride() : xpr.outerStride()),
|
||||
BlockRows==1 ? 1 : xpr.rows(),
|
||||
BlockCols==1 ? 1 : xpr.cols()),
|
||||
m_xpr(xpr)
|
||||
@@ -357,7 +360,8 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
|
||||
: Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol))), m_xpr(xpr)
|
||||
: Base(xpr.data()+xpr.innerStride()*(XprTypeIsRowMajor?startCol:startRow) + xpr.outerStride()*(XprTypeIsRowMajor?startRow:startCol)),
|
||||
m_xpr(xpr)
|
||||
{
|
||||
init();
|
||||
}
|
||||
@@ -368,7 +372,7 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
|
||||
inline BlockImpl_dense(XprType& xpr,
|
||||
Index startRow, Index startCol,
|
||||
Index blockRows, Index blockCols)
|
||||
: Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol)), blockRows, blockCols),
|
||||
: Base(xpr.data()+xpr.innerStride()*(XprTypeIsRowMajor?startCol:startRow) + xpr.outerStride()*(XprTypeIsRowMajor?startRow:startCol), blockRows, blockCols),
|
||||
m_xpr(xpr)
|
||||
{
|
||||
init();
|
||||
|
||||
@@ -17,9 +17,10 @@ namespace internal {
|
||||
template<typename Derived, int UnrollCount>
|
||||
struct all_unroller
|
||||
{
|
||||
typedef typename Derived::ExpressionTraits Traits;
|
||||
enum {
|
||||
col = (UnrollCount-1) / Derived::RowsAtCompileTime,
|
||||
row = (UnrollCount-1) % Derived::RowsAtCompileTime
|
||||
col = (UnrollCount-1) / Traits::RowsAtCompileTime,
|
||||
row = (UnrollCount-1) % Traits::RowsAtCompileTime
|
||||
};
|
||||
|
||||
static inline bool run(const Derived &mat)
|
||||
@@ -43,11 +44,12 @@ struct all_unroller<Derived, Dynamic>
|
||||
template<typename Derived, int UnrollCount>
|
||||
struct any_unroller
|
||||
{
|
||||
typedef typename Derived::ExpressionTraits Traits;
|
||||
enum {
|
||||
col = (UnrollCount-1) / Derived::RowsAtCompileTime,
|
||||
row = (UnrollCount-1) % Derived::RowsAtCompileTime
|
||||
col = (UnrollCount-1) / Traits::RowsAtCompileTime,
|
||||
row = (UnrollCount-1) % Traits::RowsAtCompileTime
|
||||
};
|
||||
|
||||
|
||||
static inline bool run(const Derived &mat)
|
||||
{
|
||||
return any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col);
|
||||
@@ -78,19 +80,21 @@ struct any_unroller<Derived, Dynamic>
|
||||
template<typename Derived>
|
||||
inline bool DenseBase<Derived>::all() const
|
||||
{
|
||||
typedef internal::evaluator<Derived> Evaluator;
|
||||
enum {
|
||||
unroll = SizeAtCompileTime != Dynamic
|
||||
&& CoeffReadCost != Dynamic
|
||||
&& Evaluator::CoeffReadCost != Dynamic
|
||||
&& NumTraits<Scalar>::AddCost != Dynamic
|
||||
&& SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
|
||||
&& SizeAtCompileTime * (Evaluator::CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
|
||||
};
|
||||
Evaluator evaluator(derived());
|
||||
if(unroll)
|
||||
return internal::all_unroller<Derived, unroll ? int(SizeAtCompileTime) : Dynamic>::run(derived());
|
||||
return internal::all_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(evaluator);
|
||||
else
|
||||
{
|
||||
for(Index j = 0; j < cols(); ++j)
|
||||
for(Index i = 0; i < rows(); ++i)
|
||||
if (!coeff(i, j)) return false;
|
||||
if (!evaluator.coeff(i, j)) return false;
|
||||
return true;
|
||||
}
|
||||
}
|
||||
@@ -102,19 +106,21 @@ inline bool DenseBase<Derived>::all() const
|
||||
template<typename Derived>
|
||||
inline bool DenseBase<Derived>::any() const
|
||||
{
|
||||
typedef internal::evaluator<Derived> Evaluator;
|
||||
enum {
|
||||
unroll = SizeAtCompileTime != Dynamic
|
||||
&& CoeffReadCost != Dynamic
|
||||
&& Evaluator::CoeffReadCost != Dynamic
|
||||
&& NumTraits<Scalar>::AddCost != Dynamic
|
||||
&& SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
|
||||
&& SizeAtCompileTime * (Evaluator::CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
|
||||
};
|
||||
Evaluator evaluator(derived());
|
||||
if(unroll)
|
||||
return internal::any_unroller<Derived, unroll ? int(SizeAtCompileTime) : Dynamic>::run(derived());
|
||||
return internal::any_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(evaluator);
|
||||
else
|
||||
{
|
||||
for(Index j = 0; j < cols(); ++j)
|
||||
for(Index i = 0; i < rows(); ++i)
|
||||
if (coeff(i, j)) return true;
|
||||
if (evaluator.coeff(i, j)) return true;
|
||||
return false;
|
||||
}
|
||||
}
|
||||
@@ -124,7 +130,7 @@ inline bool DenseBase<Derived>::any() const
|
||||
* \sa all(), any()
|
||||
*/
|
||||
template<typename Derived>
|
||||
inline typename DenseBase<Derived>::Index DenseBase<Derived>::count() const
|
||||
inline Eigen::Index DenseBase<Derived>::count() const
|
||||
{
|
||||
return derived().template cast<bool>().template cast<Index>().sum();
|
||||
}
|
||||
|
||||
@@ -28,7 +28,6 @@ template<typename XprType>
|
||||
struct CommaInitializer
|
||||
{
|
||||
typedef typename XprType::Scalar Scalar;
|
||||
typedef typename XprType::Index Index;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline CommaInitializer(XprType& xpr, const Scalar& s)
|
||||
@@ -106,6 +105,9 @@ struct CommaInitializer
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline ~CommaInitializer()
|
||||
#if defined VERIFY_RAISES_ASSERT && (!defined EIGEN_NO_ASSERTION_CHECKING) && defined EIGEN_EXCEPTIONS
|
||||
throw(Eigen::eigen_assert_exception)
|
||||
#endif
|
||||
{
|
||||
eigen_assert((m_row+m_currentBlockRows) == m_xpr.rows()
|
||||
&& m_col == m_xpr.cols()
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,7 +1,7 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
|
||||
// Copyright (C) 2008-2014 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
|
||||
@@ -15,47 +15,113 @@ namespace Eigen {
|
||||
/* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
|
||||
*/
|
||||
|
||||
/** \ingroup SparseCore_Module
|
||||
* \class InnerIterator
|
||||
* \brief An InnerIterator allows to loop over the element of a sparse (or dense) matrix or expression
|
||||
*
|
||||
* todo
|
||||
namespace internal {
|
||||
|
||||
template<typename XprType, typename EvaluatorKind>
|
||||
class inner_iterator_selector;
|
||||
|
||||
}
|
||||
|
||||
/** \class InnerIterator
|
||||
* \brief An InnerIterator allows to loop over the element of any matrix expression.
|
||||
*
|
||||
* \warning To be used with care because an evaluator is constructed every time an InnerIterator iterator is constructed.
|
||||
*
|
||||
* TODO: add a usage example
|
||||
*/
|
||||
|
||||
// generic version for dense matrix and expressions
|
||||
template<typename Derived> class DenseBase<Derived>::InnerIterator
|
||||
template<typename XprType>
|
||||
class InnerIterator
|
||||
{
|
||||
protected:
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
typedef typename Derived::Index Index;
|
||||
|
||||
enum { IsRowMajor = (Derived::Flags&RowMajorBit)==RowMajorBit };
|
||||
public:
|
||||
EIGEN_STRONG_INLINE InnerIterator(const Derived& expr, Index outer)
|
||||
: m_expression(expr), m_inner(0), m_outer(outer), m_end(expr.innerSize())
|
||||
{}
|
||||
|
||||
EIGEN_STRONG_INLINE Scalar value() const
|
||||
{
|
||||
return (IsRowMajor) ? m_expression.coeff(m_outer, m_inner)
|
||||
: m_expression.coeff(m_inner, m_outer);
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE InnerIterator& operator++() { m_inner++; return *this; }
|
||||
|
||||
EIGEN_STRONG_INLINE Index index() const { return m_inner; }
|
||||
inline Index row() const { return IsRowMajor ? m_outer : index(); }
|
||||
inline Index col() const { return IsRowMajor ? index() : m_outer; }
|
||||
|
||||
EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
|
||||
|
||||
protected:
|
||||
const Derived& m_expression;
|
||||
Index m_inner;
|
||||
const Index m_outer;
|
||||
const Index m_end;
|
||||
protected:
|
||||
typedef internal::inner_iterator_selector<XprType, typename internal::evaluator_traits<XprType>::Kind> IteratorType;
|
||||
typedef internal::evaluator<XprType> EvaluatorType;
|
||||
typedef typename internal::traits<XprType>::Scalar Scalar;
|
||||
public:
|
||||
/** Construct an iterator over the \a outerId -th row or column of \a xpr */
|
||||
InnerIterator(const XprType &xpr, const Index &outerId)
|
||||
: m_eval(xpr), m_iter(m_eval, outerId, xpr.innerSize())
|
||||
{}
|
||||
|
||||
/// \returns the value of the current coefficient.
|
||||
EIGEN_STRONG_INLINE Scalar value() const { return m_iter.value(); }
|
||||
/** Increment the iterator \c *this to the next non-zero coefficient.
|
||||
* Explicit zeros are not skipped over. To skip explicit zeros, see class SparseView
|
||||
*/
|
||||
EIGEN_STRONG_INLINE InnerIterator& operator++() { m_iter.operator++(); return *this; }
|
||||
/// \returns the column or row index of the current coefficient.
|
||||
EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
|
||||
/// \returns the row index of the current coefficient.
|
||||
EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
|
||||
/// \returns the column index of the current coefficient.
|
||||
EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
|
||||
/// \returns \c true if the iterator \c *this still references a valid coefficient.
|
||||
EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
|
||||
|
||||
protected:
|
||||
EvaluatorType m_eval;
|
||||
IteratorType m_iter;
|
||||
private:
|
||||
// If you get here, then you're not using the right InnerIterator type, e.g.:
|
||||
// SparseMatrix<double,RowMajor> A;
|
||||
// SparseMatrix<double>::InnerIterator it(A,0);
|
||||
template<typename T> InnerIterator(const EigenBase<T>&,Index outer);
|
||||
};
|
||||
|
||||
namespace internal {
|
||||
|
||||
// Generic inner iterator implementation for dense objects
|
||||
template<typename XprType>
|
||||
class inner_iterator_selector<XprType, IndexBased>
|
||||
{
|
||||
protected:
|
||||
typedef evaluator<XprType> EvaluatorType;
|
||||
typedef typename traits<XprType>::Scalar Scalar;
|
||||
enum { IsRowMajor = (XprType::Flags&RowMajorBit)==RowMajorBit };
|
||||
|
||||
public:
|
||||
EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &innerSize)
|
||||
: m_eval(eval), m_inner(0), m_outer(outerId), m_end(innerSize)
|
||||
{}
|
||||
|
||||
EIGEN_STRONG_INLINE Scalar value() const
|
||||
{
|
||||
return (IsRowMajor) ? m_eval.coeff(m_outer, m_inner)
|
||||
: m_eval.coeff(m_inner, m_outer);
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE inner_iterator_selector& operator++() { m_inner++; return *this; }
|
||||
|
||||
EIGEN_STRONG_INLINE Index index() const { return m_inner; }
|
||||
inline Index row() const { return IsRowMajor ? m_outer : index(); }
|
||||
inline Index col() const { return IsRowMajor ? index() : m_outer; }
|
||||
|
||||
EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
|
||||
|
||||
protected:
|
||||
const EvaluatorType& m_eval;
|
||||
Index m_inner;
|
||||
const Index m_outer;
|
||||
const Index m_end;
|
||||
};
|
||||
|
||||
// For iterator-based evaluator, inner-iterator is already implemented as
|
||||
// evaluator<>::InnerIterator
|
||||
template<typename XprType>
|
||||
class inner_iterator_selector<XprType, IteratorBased>
|
||||
: public evaluator<XprType>::InnerIterator
|
||||
{
|
||||
protected:
|
||||
typedef typename evaluator<XprType>::InnerIterator Base;
|
||||
typedef evaluator<XprType> EvaluatorType;
|
||||
|
||||
public:
|
||||
EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &/*innerSize*/)
|
||||
: Base(eval, outerId)
|
||||
{}
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_COREITERATORS_H
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
|
||||
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
|
||||
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
|
||||
//
|
||||
// This Source Code Form is subject to the terms of the Mozilla
|
||||
@@ -56,69 +56,47 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
|
||||
typename Rhs::Scalar
|
||||
)
|
||||
>::type 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;
|
||||
typedef typename cwise_promote_storage_type<typename traits<Lhs>::StorageKind,
|
||||
typename traits<Rhs>::StorageKind,
|
||||
BinaryOp>::ret StorageKind;
|
||||
typedef typename promote_index_type<typename traits<Lhs>::StorageIndex,
|
||||
typename traits<Rhs>::StorageIndex>::type StorageIndex;
|
||||
typedef typename Lhs::Nested LhsNested;
|
||||
typedef typename Rhs::Nested RhsNested;
|
||||
typedef typename remove_reference<LhsNested>::type _LhsNested;
|
||||
typedef typename remove_reference<RhsNested>::type _RhsNested;
|
||||
enum {
|
||||
LhsCoeffReadCost = _LhsNested::CoeffReadCost,
|
||||
RhsCoeffReadCost = _RhsNested::CoeffReadCost,
|
||||
LhsFlags = _LhsNested::Flags,
|
||||
RhsFlags = _RhsNested::Flags,
|
||||
SameType = is_same<typename _LhsNested::Scalar,typename _RhsNested::Scalar>::value,
|
||||
StorageOrdersAgree = (int(Lhs::Flags)&RowMajorBit)==(int(Rhs::Flags)&RowMajorBit),
|
||||
Flags0 = (int(LhsFlags) | int(RhsFlags)) & (
|
||||
HereditaryBits
|
||||
| (int(LhsFlags) & int(RhsFlags) &
|
||||
( AlignedBit
|
||||
| (StorageOrdersAgree ? LinearAccessBit : 0)
|
||||
| (functor_traits<BinaryOp>::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)
|
||||
)
|
||||
)
|
||||
),
|
||||
Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
|
||||
CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + functor_traits<BinaryOp>::Cost
|
||||
Flags = _LhsNested::Flags & RowMajorBit
|
||||
};
|
||||
};
|
||||
} // end namespace internal
|
||||
|
||||
// we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor
|
||||
// that would take two operands of different types. If there were such an example, then this check should be
|
||||
// moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as
|
||||
// currently they take only one typename Scalar template parameter.
|
||||
// It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths.
|
||||
// So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to
|
||||
// add together a float matrix and a double matrix.
|
||||
#define EIGEN_CHECK_BINARY_COMPATIBILIY(BINOP,LHS,RHS) \
|
||||
EIGEN_STATIC_ASSERT((internal::functor_is_product_like<BINOP>::ret \
|
||||
? int(internal::scalar_product_traits<LHS, RHS>::Defined) \
|
||||
: int(internal::is_same<LHS, RHS>::value)), \
|
||||
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
|
||||
|
||||
template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
|
||||
class CwiseBinaryOpImpl;
|
||||
|
||||
template<typename BinaryOp, typename Lhs, typename Rhs>
|
||||
class CwiseBinaryOp : internal::no_assignment_operator,
|
||||
template<typename BinaryOp, typename LhsType, typename RhsType>
|
||||
class CwiseBinaryOp :
|
||||
public CwiseBinaryOpImpl<
|
||||
BinaryOp, Lhs, Rhs,
|
||||
typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
|
||||
typename internal::traits<Rhs>::StorageKind>::ret>
|
||||
BinaryOp, LhsType, RhsType,
|
||||
typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
|
||||
typename internal::traits<RhsType>::StorageKind,
|
||||
BinaryOp>::ret>,
|
||||
internal::no_assignment_operator
|
||||
{
|
||||
public:
|
||||
|
||||
typedef typename internal::remove_all<LhsType>::type Lhs;
|
||||
typedef typename internal::remove_all<RhsType>::type Rhs;
|
||||
|
||||
typedef typename CwiseBinaryOpImpl<
|
||||
BinaryOp, Lhs, Rhs,
|
||||
typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
|
||||
typename internal::traits<Rhs>::StorageKind>::ret>::Base Base;
|
||||
BinaryOp, LhsType, RhsType,
|
||||
typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
|
||||
typename internal::traits<Rhs>::StorageKind,
|
||||
BinaryOp>::ret>::Base Base;
|
||||
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
|
||||
|
||||
typedef typename internal::nested<Lhs>::type LhsNested;
|
||||
typedef typename internal::nested<Rhs>::type RhsNested;
|
||||
typedef typename internal::ref_selector<LhsType>::type LhsNested;
|
||||
typedef typename internal::ref_selector<RhsType>::type RhsNested;
|
||||
typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
|
||||
typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
|
||||
|
||||
@@ -165,43 +143,13 @@ class CwiseBinaryOp : internal::no_assignment_operator,
|
||||
const BinaryOp m_functor;
|
||||
};
|
||||
|
||||
template<typename BinaryOp, typename Lhs, typename Rhs>
|
||||
class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Dense>
|
||||
: public internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
|
||||
// Generic API dispatcher
|
||||
template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
|
||||
class CwiseBinaryOpImpl
|
||||
: public internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
|
||||
{
|
||||
typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> Derived;
|
||||
public:
|
||||
|
||||
typedef typename internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE( Derived )
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
|
||||
{
|
||||
return derived().functor()(derived().lhs().coeff(rowId, colId),
|
||||
derived().rhs().coeff(rowId, colId));
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
|
||||
{
|
||||
return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(rowId, colId),
|
||||
derived().rhs().template packet<LoadMode>(rowId, colId));
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
|
||||
{
|
||||
return derived().functor()(derived().lhs().coeff(index),
|
||||
derived().rhs().coeff(index));
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
|
||||
{
|
||||
return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(index),
|
||||
derived().rhs().template packet<LoadMode>(index));
|
||||
}
|
||||
public:
|
||||
typedef typename internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
|
||||
};
|
||||
|
||||
/** replaces \c *this by \c *this - \a other.
|
||||
@@ -213,8 +161,7 @@ template<typename OtherDerived>
|
||||
EIGEN_STRONG_INLINE Derived &
|
||||
MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived> &other)
|
||||
{
|
||||
SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
|
||||
tmp = other.derived();
|
||||
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
@@ -227,8 +174,7 @@ template<typename OtherDerived>
|
||||
EIGEN_STRONG_INLINE Derived &
|
||||
MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
|
||||
{
|
||||
SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
|
||||
tmp = other.derived();
|
||||
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
|
||||
@@ -35,19 +35,13 @@ template<typename NullaryOp, typename PlainObjectType>
|
||||
struct traits<CwiseNullaryOp<NullaryOp, PlainObjectType> > : traits<PlainObjectType>
|
||||
{
|
||||
enum {
|
||||
Flags = (traits<PlainObjectType>::Flags
|
||||
& ( HereditaryBits
|
||||
| (functor_has_linear_access<NullaryOp>::ret ? LinearAccessBit : 0)
|
||||
| (functor_traits<NullaryOp>::PacketAccess ? PacketAccessBit : 0)))
|
||||
| (functor_traits<NullaryOp>::IsRepeatable ? 0 : EvalBeforeNestingBit),
|
||||
CoeffReadCost = functor_traits<NullaryOp>::Cost
|
||||
Flags = traits<PlainObjectType>::Flags & RowMajorBit
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
template<typename NullaryOp, typename PlainObjectType>
|
||||
class CwiseNullaryOp : internal::no_assignment_operator,
|
||||
public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type
|
||||
class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
|
||||
{
|
||||
public:
|
||||
|
||||
@@ -55,13 +49,13 @@ class CwiseNullaryOp : internal::no_assignment_operator,
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
CwiseNullaryOp(Index nbRows, Index nbCols, const NullaryOp& func = NullaryOp())
|
||||
: m_rows(nbRows), m_cols(nbCols), m_functor(func)
|
||||
CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp())
|
||||
: m_rows(rows), m_cols(cols), m_functor(func)
|
||||
{
|
||||
eigen_assert(nbRows >= 0
|
||||
&& (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
|
||||
&& nbCols >= 0
|
||||
&& (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols));
|
||||
eigen_assert(rows >= 0
|
||||
&& (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
|
||||
&& cols >= 0
|
||||
&& (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -119,10 +113,10 @@ class CwiseNullaryOp : internal::no_assignment_operator,
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename CustomNullaryOp>
|
||||
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
|
||||
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
|
||||
DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func)
|
||||
{
|
||||
return CwiseNullaryOp<CustomNullaryOp, Derived>(rows, cols, func);
|
||||
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(rows, cols, func);
|
||||
}
|
||||
|
||||
/** \returns an expression of a matrix defined by a custom functor \a func
|
||||
@@ -145,12 +139,12 @@ DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& f
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename CustomNullaryOp>
|
||||
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
|
||||
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
|
||||
DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
|
||||
if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, Derived>(1, size, func);
|
||||
else return CwiseNullaryOp<CustomNullaryOp, Derived>(size, 1, func);
|
||||
if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, PlainObject>(1, size, func);
|
||||
else return CwiseNullaryOp<CustomNullaryOp, PlainObject>(size, 1, func);
|
||||
}
|
||||
|
||||
/** \returns an expression of a matrix defined by a custom functor \a func
|
||||
@@ -164,19 +158,19 @@ DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename CustomNullaryOp>
|
||||
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
|
||||
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
|
||||
DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
|
||||
{
|
||||
return CwiseNullaryOp<CustomNullaryOp, Derived>(RowsAtCompileTime, ColsAtCompileTime, func);
|
||||
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(RowsAtCompileTime, ColsAtCompileTime, func);
|
||||
}
|
||||
|
||||
/** \returns an expression of a constant matrix of value \a value
|
||||
*
|
||||
* The parameters \a nbRows and \a nbCols are the number of rows and of columns of
|
||||
* The parameters \a rows and \a cols are the number of rows and of columns of
|
||||
* the returned matrix. Must be compatible with this DenseBase type.
|
||||
*
|
||||
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
|
||||
* it is redundant to pass \a nbRows and \a nbCols as arguments, so Zero() should be used
|
||||
* it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
|
||||
* instead.
|
||||
*
|
||||
* The template parameter \a CustomNullaryOp is the type of the functor.
|
||||
@@ -185,9 +179,9 @@ DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
|
||||
*/
|
||||
template<typename Derived>
|
||||
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
|
||||
DenseBase<Derived>::Constant(Index nbRows, Index nbCols, const Scalar& value)
|
||||
DenseBase<Derived>::Constant(Index rows, Index cols, const Scalar& value)
|
||||
{
|
||||
return DenseBase<Derived>::NullaryExpr(nbRows, nbCols, internal::scalar_constant_op<Scalar>(value));
|
||||
return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_constant_op<Scalar>(value));
|
||||
}
|
||||
|
||||
/** \returns an expression of a constant matrix of value \a value
|
||||
@@ -251,7 +245,7 @@ EIGEN_STRONG_INLINE const typename DenseBase<Derived>::SequentialLinSpacedReturn
|
||||
DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
|
||||
return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,false>(low,high,size));
|
||||
return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,PacketScalar,false>(low,high,size));
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -264,7 +258,7 @@ DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& hig
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
|
||||
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
|
||||
return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,false>(low,high,Derived::SizeAtCompileTime));
|
||||
return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,PacketScalar,false>(low,high,Derived::SizeAtCompileTime));
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -285,7 +279,7 @@ EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedRetu
|
||||
DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
|
||||
return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,true>(low,high,size));
|
||||
return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,PacketScalar,true>(low,high,size));
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -298,7 +292,7 @@ DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
|
||||
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
|
||||
return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,true>(low,high,Derived::SizeAtCompileTime));
|
||||
return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,PacketScalar,true>(low,high,Derived::SizeAtCompileTime));
|
||||
}
|
||||
|
||||
/** \returns true if all coefficients in this matrix are approximately equal to \a val, to within precision \a prec */
|
||||
@@ -306,9 +300,10 @@ template<typename Derived>
|
||||
bool DenseBase<Derived>::isApproxToConstant
|
||||
(const Scalar& val, const RealScalar& prec) const
|
||||
{
|
||||
typename internal::nested_eval<Derived,1>::type self(derived());
|
||||
for(Index j = 0; j < cols(); ++j)
|
||||
for(Index i = 0; i < rows(); ++i)
|
||||
if(!internal::isApprox(this->coeff(i, j), val, prec))
|
||||
if(!internal::isApprox(self.coeff(i, j), val, prec))
|
||||
return false;
|
||||
return true;
|
||||
}
|
||||
@@ -362,8 +357,8 @@ PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
|
||||
|
||||
/** Resizes to the given size, and sets all coefficients in this expression to the given \a value.
|
||||
*
|
||||
* \param nbRows the new number of rows
|
||||
* \param nbCols the new number of columns
|
||||
* \param rows the new number of rows
|
||||
* \param cols the new number of columns
|
||||
* \param val the value to which all coefficients are set
|
||||
*
|
||||
* Example: \include Matrix_setConstant_int_int.cpp
|
||||
@@ -373,9 +368,9 @@ PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
|
||||
*/
|
||||
template<typename Derived>
|
||||
EIGEN_STRONG_INLINE Derived&
|
||||
PlainObjectBase<Derived>::setConstant(Index nbRows, Index nbCols, const Scalar& val)
|
||||
PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& val)
|
||||
{
|
||||
resize(nbRows, nbCols);
|
||||
resize(rows, cols);
|
||||
return setConstant(val);
|
||||
}
|
||||
|
||||
@@ -396,7 +391,7 @@ template<typename Derived>
|
||||
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(newSize, internal::linspaced_op<Scalar,false>(low,high,newSize));
|
||||
return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar,PacketScalar,false>(low,high,newSize));
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -434,9 +429,9 @@ 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 nbRows, Index nbCols)
|
||||
DenseBase<Derived>::Zero(Index rows, Index cols)
|
||||
{
|
||||
return Constant(nbRows, nbCols, Scalar(0));
|
||||
return Constant(rows, cols, Scalar(0));
|
||||
}
|
||||
|
||||
/** \returns an expression of a zero vector.
|
||||
@@ -490,9 +485,10 @@ DenseBase<Derived>::Zero()
|
||||
template<typename Derived>
|
||||
bool DenseBase<Derived>::isZero(const RealScalar& prec) const
|
||||
{
|
||||
typename internal::nested_eval<Derived,1>::type self(derived());
|
||||
for(Index j = 0; j < cols(); ++j)
|
||||
for(Index i = 0; i < rows(); ++i)
|
||||
if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast<Scalar>(1), prec))
|
||||
if(!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<Scalar>(1), prec))
|
||||
return false;
|
||||
return true;
|
||||
}
|
||||
@@ -529,8 +525,8 @@ PlainObjectBase<Derived>::setZero(Index newSize)
|
||||
|
||||
/** Resizes to the given size, and sets all coefficients in this expression to zero.
|
||||
*
|
||||
* \param nbRows the new number of rows
|
||||
* \param nbCols the new number of columns
|
||||
* \param rows the new number of rows
|
||||
* \param cols the new number of columns
|
||||
*
|
||||
* Example: \include Matrix_setZero_int_int.cpp
|
||||
* Output: \verbinclude Matrix_setZero_int_int.out
|
||||
@@ -539,9 +535,9 @@ PlainObjectBase<Derived>::setZero(Index newSize)
|
||||
*/
|
||||
template<typename Derived>
|
||||
EIGEN_STRONG_INLINE Derived&
|
||||
PlainObjectBase<Derived>::setZero(Index nbRows, Index nbCols)
|
||||
PlainObjectBase<Derived>::setZero(Index rows, Index cols)
|
||||
{
|
||||
resize(nbRows, nbCols);
|
||||
resize(rows, cols);
|
||||
return setConstant(Scalar(0));
|
||||
}
|
||||
|
||||
@@ -549,7 +545,7 @@ PlainObjectBase<Derived>::setZero(Index nbRows, Index nbCols)
|
||||
|
||||
/** \returns an expression of a matrix where all coefficients equal one.
|
||||
*
|
||||
* The parameters \a nbRows and \a nbCols are the number of rows and of columns of
|
||||
* The parameters \a rows and \a cols are the number of rows and of columns of
|
||||
* the returned matrix. Must be compatible with this MatrixBase type.
|
||||
*
|
||||
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
|
||||
@@ -563,9 +559,9 @@ PlainObjectBase<Derived>::setZero(Index nbRows, Index nbCols)
|
||||
*/
|
||||
template<typename Derived>
|
||||
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
|
||||
DenseBase<Derived>::Ones(Index nbRows, Index nbCols)
|
||||
DenseBase<Derived>::Ones(Index rows, Index cols)
|
||||
{
|
||||
return Constant(nbRows, nbCols, Scalar(1));
|
||||
return Constant(rows, cols, Scalar(1));
|
||||
}
|
||||
|
||||
/** \returns an expression of a vector where all coefficients equal one.
|
||||
@@ -655,8 +651,8 @@ PlainObjectBase<Derived>::setOnes(Index newSize)
|
||||
|
||||
/** Resizes to the given size, and sets all coefficients in this expression to one.
|
||||
*
|
||||
* \param nbRows the new number of rows
|
||||
* \param nbCols the new number of columns
|
||||
* \param rows the new number of rows
|
||||
* \param cols the new number of columns
|
||||
*
|
||||
* Example: \include Matrix_setOnes_int_int.cpp
|
||||
* Output: \verbinclude Matrix_setOnes_int_int.out
|
||||
@@ -665,9 +661,9 @@ PlainObjectBase<Derived>::setOnes(Index newSize)
|
||||
*/
|
||||
template<typename Derived>
|
||||
EIGEN_STRONG_INLINE Derived&
|
||||
PlainObjectBase<Derived>::setOnes(Index nbRows, Index nbCols)
|
||||
PlainObjectBase<Derived>::setOnes(Index rows, Index cols)
|
||||
{
|
||||
resize(nbRows, nbCols);
|
||||
resize(rows, cols);
|
||||
return setConstant(Scalar(1));
|
||||
}
|
||||
|
||||
@@ -675,7 +671,7 @@ PlainObjectBase<Derived>::setOnes(Index nbRows, Index nbCols)
|
||||
|
||||
/** \returns an expression of the identity matrix (not necessarily square).
|
||||
*
|
||||
* The parameters \a nbRows and \a nbCols are the number of rows and of columns of
|
||||
* The parameters \a rows and \a cols are the number of rows and of columns of
|
||||
* the returned matrix. Must be compatible with this MatrixBase type.
|
||||
*
|
||||
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
|
||||
@@ -689,9 +685,9 @@ PlainObjectBase<Derived>::setOnes(Index nbRows, Index nbCols)
|
||||
*/
|
||||
template<typename Derived>
|
||||
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
|
||||
MatrixBase<Derived>::Identity(Index nbRows, Index nbCols)
|
||||
MatrixBase<Derived>::Identity(Index rows, Index cols)
|
||||
{
|
||||
return DenseBase<Derived>::NullaryExpr(nbRows, nbCols, internal::scalar_identity_op<Scalar>());
|
||||
return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_identity_op<Scalar>());
|
||||
}
|
||||
|
||||
/** \returns an expression of the identity matrix (not necessarily square).
|
||||
@@ -725,18 +721,19 @@ template<typename Derived>
|
||||
bool MatrixBase<Derived>::isIdentity
|
||||
(const RealScalar& prec) const
|
||||
{
|
||||
typename internal::nested_eval<Derived,1>::type self(derived());
|
||||
for(Index j = 0; j < cols(); ++j)
|
||||
{
|
||||
for(Index i = 0; i < rows(); ++i)
|
||||
{
|
||||
if(i == j)
|
||||
{
|
||||
if(!internal::isApprox(this->coeff(i, j), static_cast<Scalar>(1), prec))
|
||||
if(!internal::isApprox(self.coeff(i, j), static_cast<Scalar>(1), prec))
|
||||
return false;
|
||||
}
|
||||
else
|
||||
{
|
||||
if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast<RealScalar>(1), prec))
|
||||
if(!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<RealScalar>(1), prec))
|
||||
return false;
|
||||
}
|
||||
}
|
||||
@@ -759,7 +756,6 @@ struct setIdentity_impl
|
||||
template<typename Derived>
|
||||
struct setIdentity_impl<Derived, true>
|
||||
{
|
||||
typedef typename Derived::Index Index;
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE Derived& run(Derived& m)
|
||||
{
|
||||
@@ -787,8 +783,8 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
|
||||
|
||||
/** \brief Resizes to the given size, and writes the identity expression (not necessarily square) into *this.
|
||||
*
|
||||
* \param nbRows the new number of rows
|
||||
* \param nbCols the new number of columns
|
||||
* \param rows the new number of rows
|
||||
* \param cols the new number of columns
|
||||
*
|
||||
* Example: \include Matrix_setIdentity_int_int.cpp
|
||||
* Output: \verbinclude Matrix_setIdentity_int_int.out
|
||||
@@ -796,9 +792,9 @@ 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 nbRows, Index nbCols)
|
||||
EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index cols)
|
||||
{
|
||||
derived().resize(nbRows, nbCols);
|
||||
derived().resize(rows, cols);
|
||||
return setIdentity();
|
||||
}
|
||||
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
|
||||
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
|
||||
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
|
||||
//
|
||||
// This Source Code Form is subject to the terms of the Mozilla
|
||||
@@ -44,10 +44,7 @@ struct traits<CwiseUnaryOp<UnaryOp, XprType> >
|
||||
typedef typename XprType::Nested XprTypeNested;
|
||||
typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
|
||||
enum {
|
||||
Flags = _XprTypeNested::Flags & (
|
||||
HereditaryBits | LinearAccessBit | AlignedBit
|
||||
| (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
|
||||
CoeffReadCost = _XprTypeNested::CoeffReadCost + functor_traits<UnaryOp>::Cost
|
||||
Flags = _XprTypeNested::Flags & RowMajorBit
|
||||
};
|
||||
};
|
||||
}
|
||||
@@ -56,16 +53,16 @@ template<typename UnaryOp, typename XprType, typename StorageKind>
|
||||
class CwiseUnaryOpImpl;
|
||||
|
||||
template<typename UnaryOp, typename XprType>
|
||||
class CwiseUnaryOp : internal::no_assignment_operator,
|
||||
public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>
|
||||
class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
|
||||
{
|
||||
public:
|
||||
|
||||
typedef typename CwiseUnaryOpImpl<UnaryOp, XprType,typename internal::traits<XprType>::StorageKind>::Base Base;
|
||||
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
|
||||
typedef typename internal::remove_all<XprType>::type NestedExpression;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
|
||||
explicit inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
|
||||
: m_xpr(xpr), m_functor(func) {}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -92,42 +89,13 @@ class CwiseUnaryOp : internal::no_assignment_operator,
|
||||
const UnaryOp m_functor;
|
||||
};
|
||||
|
||||
// This is the generic implementation for dense storage.
|
||||
// It can be used for any expression types implementing the dense concept.
|
||||
template<typename UnaryOp, typename XprType>
|
||||
class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
|
||||
: public internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
|
||||
// Generic API dispatcher
|
||||
template<typename UnaryOp, typename XprType, typename StorageKind>
|
||||
class CwiseUnaryOpImpl
|
||||
: public internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
|
||||
{
|
||||
public:
|
||||
|
||||
typedef CwiseUnaryOp<UnaryOp, XprType> Derived;
|
||||
typedef typename internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
|
||||
{
|
||||
return derived().functor()(derived().nestedExpression().coeff(rowId, colId));
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
|
||||
{
|
||||
return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(rowId, colId));
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
|
||||
{
|
||||
return derived().functor()(derived().nestedExpression().coeff(index));
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
|
||||
{
|
||||
return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(index));
|
||||
}
|
||||
public:
|
||||
typedef typename internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
|
||||
};
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -37,8 +37,8 @@ struct traits<CwiseUnaryView<ViewOp, MatrixType> >
|
||||
typedef typename MatrixType::Nested MatrixTypeNested;
|
||||
typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested;
|
||||
enum {
|
||||
Flags = (traits<_MatrixTypeNested>::Flags & (HereditaryBits | LvalueBit | LinearAccessBit | DirectAccessBit)),
|
||||
CoeffReadCost = traits<_MatrixTypeNested>::CoeffReadCost + functor_traits<ViewOp>::Cost,
|
||||
FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
|
||||
Flags = traits<_MatrixTypeNested>::Flags & (RowMajorBit | FlagsLvalueBit | DirectAccessBit), // FIXME DirectAccessBit should not be handled by expressions
|
||||
MatrixTypeInnerStride = inner_stride_at_compile_time<MatrixType>::ret,
|
||||
// need to cast the sizeof's from size_t to int explicitly, otherwise:
|
||||
// "error: no integral type can represent all of the enumerator values
|
||||
@@ -62,8 +62,9 @@ class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename in
|
||||
|
||||
typedef typename CwiseUnaryViewImpl<ViewOp, MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
|
||||
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView)
|
||||
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
|
||||
|
||||
inline CwiseUnaryView(const MatrixType& mat, const ViewOp& func = ViewOp())
|
||||
explicit inline CwiseUnaryView(MatrixType& mat, const ViewOp& func = ViewOp())
|
||||
: m_matrix(mat), m_functor(func) {}
|
||||
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
|
||||
@@ -83,11 +84,19 @@ class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename in
|
||||
nestedExpression() { return m_matrix.const_cast_derived(); }
|
||||
|
||||
protected:
|
||||
// FIXME changed from MatrixType::Nested because of a weird compilation error with sun CC
|
||||
typename internal::nested<MatrixType>::type m_matrix;
|
||||
typename internal::ref_selector<MatrixType>::type m_matrix;
|
||||
ViewOp m_functor;
|
||||
};
|
||||
|
||||
// Generic API dispatcher
|
||||
template<typename ViewOp, typename XprType, typename StorageKind>
|
||||
class CwiseUnaryViewImpl
|
||||
: public internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type
|
||||
{
|
||||
public:
|
||||
typedef typename internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type Base;
|
||||
};
|
||||
|
||||
template<typename ViewOp, typename MatrixType>
|
||||
class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
|
||||
: public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type
|
||||
@@ -100,38 +109,18 @@ class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
|
||||
|
||||
inline Scalar* data() { return &coeffRef(0); }
|
||||
inline const Scalar* data() const { return &coeff(0); }
|
||||
EIGEN_DEVICE_FUNC inline Scalar* data() { return &(this->coeffRef(0)); }
|
||||
EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(this->coeff(0)); }
|
||||
|
||||
inline Index innerStride() const
|
||||
EIGEN_DEVICE_FUNC inline Index innerStride() const
|
||||
{
|
||||
return derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
|
||||
}
|
||||
|
||||
inline Index outerStride() const
|
||||
EIGEN_DEVICE_FUNC inline Index outerStride() const
|
||||
{
|
||||
return derived().nestedExpression().outerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
|
||||
{
|
||||
return derived().functor()(derived().nestedExpression().coeff(row, col));
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
|
||||
{
|
||||
return derived().functor()(derived().nestedExpression().coeff(index));
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
|
||||
{
|
||||
return derived().functor()(const_cast_derived().nestedExpression().coeffRef(row, col));
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
|
||||
{
|
||||
return derived().functor()(const_cast_derived().nestedExpression().coeffRef(index));
|
||||
}
|
||||
};
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -49,22 +49,37 @@ template<typename Derived> class DenseBase
|
||||
public:
|
||||
using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
|
||||
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
|
||||
using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
|
||||
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator/;
|
||||
|
||||
class InnerIterator;
|
||||
|
||||
/** Inner iterator type to iterate over the coefficients of a row or column.
|
||||
* \sa class InnerIterator
|
||||
*/
|
||||
typedef Eigen::InnerIterator<Derived> InnerIterator;
|
||||
|
||||
typedef typename internal::traits<Derived>::StorageKind StorageKind;
|
||||
|
||||
/** \brief The type of indices
|
||||
* \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
|
||||
* \sa \ref TopicPreprocessorDirectives.
|
||||
*/
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
/**
|
||||
* \brief The type used to store indices
|
||||
* \details This typedef is relevant for types that store multiple indices such as
|
||||
* PermutationMatrix or Transpositions, otherwise it defaults to Eigen::Index
|
||||
* \sa \ref TopicPreprocessorDirectives, Eigen::Index, SparseMatrixBase.
|
||||
*/
|
||||
typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
|
||||
|
||||
/** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc. */
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
|
||||
|
||||
/** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
|
||||
*
|
||||
* It is an alias for the Scalar type */
|
||||
typedef Scalar value_type;
|
||||
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
|
||||
typedef DenseCoeffsBase<Derived> Base;
|
||||
typedef internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
|
||||
typename NumTraits<typename internal::traits<Derived>::Scalar>::Real> Base;
|
||||
using Base::derived;
|
||||
using Base::const_cast_derived;
|
||||
using Base::rows;
|
||||
@@ -74,16 +89,6 @@ template<typename Derived> class DenseBase
|
||||
using Base::colIndexByOuterInner;
|
||||
using Base::coeff;
|
||||
using Base::coeffByOuterInner;
|
||||
using Base::packet;
|
||||
using Base::packetByOuterInner;
|
||||
using Base::writePacket;
|
||||
using Base::writePacketByOuterInner;
|
||||
using Base::coeffRef;
|
||||
using Base::coeffRefByOuterInner;
|
||||
using Base::copyCoeff;
|
||||
using Base::copyCoeffByOuterInner;
|
||||
using Base::copyPacket;
|
||||
using Base::copyPacketByOuterInner;
|
||||
using Base::operator();
|
||||
using Base::operator[];
|
||||
using Base::x;
|
||||
@@ -169,16 +174,42 @@ template<typename Derived> class DenseBase
|
||||
InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
|
||||
: int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
|
||||
|
||||
CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
|
||||
/**< This is a rough measure of how expensive it is to read one coefficient from
|
||||
* this expression.
|
||||
*/
|
||||
|
||||
InnerStrideAtCompileTime = internal::inner_stride_at_compile_time<Derived>::ret,
|
||||
OuterStrideAtCompileTime = internal::outer_stride_at_compile_time<Derived>::ret
|
||||
};
|
||||
|
||||
typedef typename internal::find_best_packet<Scalar,SizeAtCompileTime>::type PacketScalar;
|
||||
|
||||
enum { ThisConstantIsPrivateInPlainObjectBase };
|
||||
enum { IsPlainObjectBase = 0 };
|
||||
|
||||
/** The plain matrix type corresponding to this expression.
|
||||
* \sa PlainObject */
|
||||
typedef Matrix<typename internal::traits<Derived>::Scalar,
|
||||
internal::traits<Derived>::RowsAtCompileTime,
|
||||
internal::traits<Derived>::ColsAtCompileTime,
|
||||
AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
|
||||
internal::traits<Derived>::MaxRowsAtCompileTime,
|
||||
internal::traits<Derived>::MaxColsAtCompileTime
|
||||
> PlainMatrix;
|
||||
|
||||
/** The plain array type corresponding to this expression.
|
||||
* \sa PlainObject */
|
||||
typedef Array<typename internal::traits<Derived>::Scalar,
|
||||
internal::traits<Derived>::RowsAtCompileTime,
|
||||
internal::traits<Derived>::ColsAtCompileTime,
|
||||
AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
|
||||
internal::traits<Derived>::MaxRowsAtCompileTime,
|
||||
internal::traits<Derived>::MaxColsAtCompileTime
|
||||
> PlainArray;
|
||||
|
||||
/** \brief The plain matrix or array type corresponding to this expression.
|
||||
*
|
||||
* This is not necessarily exactly the return type of eval(). In the case of plain matrices,
|
||||
* the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed
|
||||
* that the return type of eval() is either PlainObject or const PlainObject&.
|
||||
*/
|
||||
typedef typename internal::conditional<internal::is_same<typename internal::traits<Derived>::XprKind,MatrixXpr >::value,
|
||||
PlainMatrix, PlainArray>::type PlainObject;
|
||||
|
||||
/** \returns the number of nonzero coefficients which is in practice the number
|
||||
* of stored coefficients. */
|
||||
@@ -229,22 +260,21 @@ template<typename Derived> class DenseBase
|
||||
* nothing else.
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
void resize(Index nbRows, Index nbCols)
|
||||
void resize(Index rows, Index cols)
|
||||
{
|
||||
EIGEN_ONLY_USED_FOR_DEBUG(nbRows);
|
||||
EIGEN_ONLY_USED_FOR_DEBUG(nbCols);
|
||||
eigen_assert(nbRows == this->rows() && nbCols == this->cols()
|
||||
EIGEN_ONLY_USED_FOR_DEBUG(rows);
|
||||
EIGEN_ONLY_USED_FOR_DEBUG(cols);
|
||||
eigen_assert(rows == this->rows() && cols == this->cols()
|
||||
&& "DenseBase::resize() does not actually allow to resize.");
|
||||
}
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
|
||||
/** \internal Represents a matrix with all coefficients equal to one another*/
|
||||
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
|
||||
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType;
|
||||
/** \internal Represents a vector with linearly spaced coefficients that allows sequential access only. */
|
||||
typedef CwiseNullaryOp<internal::linspaced_op<Scalar,false>,Derived> SequentialLinSpacedReturnType;
|
||||
typedef CwiseNullaryOp<internal::linspaced_op<Scalar,PacketScalar,false>,PlainObject> SequentialLinSpacedReturnType;
|
||||
/** \internal Represents a vector with linearly spaced coefficients that allows random access. */
|
||||
typedef CwiseNullaryOp<internal::linspaced_op<Scalar,true>,Derived> RandomAccessLinSpacedReturnType;
|
||||
typedef CwiseNullaryOp<internal::linspaced_op<Scalar,PacketScalar,true>,PlainObject> RandomAccessLinSpacedReturnType;
|
||||
/** \internal the return type of MatrixBase::eigenvalues() */
|
||||
typedef Matrix<typename NumTraits<typename internal::traits<Derived>::Scalar>::Real, internal::traits<Derived>::ColsAtCompileTime, 1> EigenvaluesReturnType;
|
||||
|
||||
@@ -277,37 +307,34 @@ template<typename Derived> class DenseBase
|
||||
EIGEN_DEVICE_FUNC
|
||||
Derived& operator=(const ReturnByValue<OtherDerived>& func);
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
/** Copies \a other into *this without evaluating other. \returns a reference to *this. */
|
||||
/** \ínternal
|
||||
* Copies \a other into *this without evaluating other. \returns a reference to *this.
|
||||
* \deprecated */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
Derived& lazyAssign(const DenseBase<OtherDerived>& other);
|
||||
#endif // not EIGEN_PARSED_BY_DOXYGEN
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
CommaInitializer<Derived> operator<< (const Scalar& s);
|
||||
|
||||
/** \deprecated it now returns \c *this */
|
||||
template<unsigned int Added,unsigned int Removed>
|
||||
const Flagged<Derived, Added, Removed> flagged() const;
|
||||
EIGEN_DEPRECATED
|
||||
const Derived& flagged() const
|
||||
{ return derived(); }
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
CommaInitializer<Derived> operator<< (const DenseBase<OtherDerived>& other);
|
||||
|
||||
typedef Transpose<Derived> TransposeReturnType;
|
||||
EIGEN_DEVICE_FUNC
|
||||
Eigen::Transpose<Derived> transpose();
|
||||
TransposeReturnType transpose();
|
||||
typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
|
||||
EIGEN_DEVICE_FUNC
|
||||
ConstTransposeReturnType transpose() const;
|
||||
EIGEN_DEVICE_FUNC
|
||||
void transposeInPlace();
|
||||
#ifndef EIGEN_NO_DEBUG
|
||||
protected:
|
||||
template<typename OtherDerived>
|
||||
void checkTransposeAliasing(const OtherDerived& other) const;
|
||||
public:
|
||||
#endif
|
||||
|
||||
|
||||
EIGEN_DEVICE_FUNC static const ConstantReturnType
|
||||
Constant(Index rows, Index cols, const Scalar& value);
|
||||
@@ -326,13 +353,13 @@ template<typename Derived> class DenseBase
|
||||
LinSpaced(const Scalar& low, const Scalar& high);
|
||||
|
||||
template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
|
||||
static const CwiseNullaryOp<CustomNullaryOp, Derived>
|
||||
static const CwiseNullaryOp<CustomNullaryOp, PlainObject>
|
||||
NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func);
|
||||
template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
|
||||
static const CwiseNullaryOp<CustomNullaryOp, Derived>
|
||||
static const CwiseNullaryOp<CustomNullaryOp, PlainObject>
|
||||
NullaryExpr(Index size, const CustomNullaryOp& func);
|
||||
template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
|
||||
static const CwiseNullaryOp<CustomNullaryOp, Derived>
|
||||
static const CwiseNullaryOp<CustomNullaryOp, PlainObject>
|
||||
NullaryExpr(const CustomNullaryOp& func);
|
||||
|
||||
EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(Index rows, Index cols);
|
||||
@@ -378,6 +405,8 @@ template<typename Derived> class DenseBase
|
||||
*
|
||||
* Notice that in the case of a plain matrix or vector (not an expression) this function just returns
|
||||
* a const reference, in order to avoid a useless copy.
|
||||
*
|
||||
* \warning Be carefull with eval() and the auto C++ keyword, as detailed in this \link TopicPitfalls_auto_keyword page \endlink.
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE EvalReturnType eval() const
|
||||
@@ -387,16 +416,17 @@ template<typename Derived> class DenseBase
|
||||
// size types on MSVC.
|
||||
return typename internal::eval<Derived>::type(derived());
|
||||
}
|
||||
|
||||
|
||||
/** swaps *this with the expression \a other.
|
||||
*
|
||||
*/
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void swap(const DenseBase<OtherDerived>& other,
|
||||
int = OtherDerived::ThisConstantIsPrivateInPlainObjectBase)
|
||||
void swap(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
|
||||
EIGEN_STATIC_ASSERT(!OtherDerived::IsPlainObjectBase,THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
|
||||
eigen_assert(rows()==other.rows() && cols()==other.cols());
|
||||
call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
|
||||
}
|
||||
|
||||
/** swaps *this with the matrix or array \a other.
|
||||
@@ -406,10 +436,10 @@ template<typename Derived> class DenseBase
|
||||
EIGEN_DEVICE_FUNC
|
||||
void swap(PlainObjectBase<OtherDerived>& other)
|
||||
{
|
||||
SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
|
||||
eigen_assert(rows()==other.rows() && cols()==other.cols());
|
||||
call_assignment(derived(), other.derived(), internal::swap_assign_op<Scalar>());
|
||||
}
|
||||
|
||||
|
||||
EIGEN_DEVICE_FUNC inline const NestByValue<Derived> nestByValue() const;
|
||||
EIGEN_DEVICE_FUNC inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
|
||||
EIGEN_DEVICE_FUNC inline ForceAlignedAccess<Derived> forceAlignedAccess();
|
||||
@@ -438,8 +468,7 @@ template<typename Derived> class DenseBase
|
||||
|
||||
template<typename BinaryOp>
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename internal::result_of<BinaryOp(typename internal::traits<Derived>::Scalar)>::type
|
||||
redux(const BinaryOp& func) const;
|
||||
Scalar redux(const BinaryOp& func) const;
|
||||
|
||||
template<typename Visitor>
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -465,14 +494,35 @@ template<typename Derived> class DenseBase
|
||||
typedef VectorwiseOp<Derived, Vertical> ColwiseReturnType;
|
||||
typedef const VectorwiseOp<const Derived, Vertical> ConstColwiseReturnType;
|
||||
|
||||
ConstRowwiseReturnType rowwise() const;
|
||||
RowwiseReturnType rowwise();
|
||||
ConstColwiseReturnType colwise() const;
|
||||
ColwiseReturnType colwise();
|
||||
/** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
|
||||
*
|
||||
* Example: \include MatrixBase_rowwise.cpp
|
||||
* Output: \verbinclude MatrixBase_rowwise.out
|
||||
*
|
||||
* \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
|
||||
*/
|
||||
//Code moved here due to a CUDA compiler bug
|
||||
EIGEN_DEVICE_FUNC inline ConstRowwiseReturnType rowwise() const {
|
||||
return ConstRowwiseReturnType(derived());
|
||||
}
|
||||
EIGEN_DEVICE_FUNC RowwiseReturnType rowwise();
|
||||
|
||||
static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(Index rows, Index cols);
|
||||
static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(Index size);
|
||||
static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random();
|
||||
/** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
|
||||
*
|
||||
* Example: \include MatrixBase_colwise.cpp
|
||||
* Output: \verbinclude MatrixBase_colwise.out
|
||||
*
|
||||
* \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC inline ConstColwiseReturnType colwise() const {
|
||||
return ConstColwiseReturnType(derived());
|
||||
}
|
||||
EIGEN_DEVICE_FUNC ColwiseReturnType colwise();
|
||||
|
||||
typedef CwiseNullaryOp<internal::scalar_random_op<Scalar>,PlainObject> RandomReturnType;
|
||||
static const RandomReturnType Random(Index rows, Index cols);
|
||||
static const RandomReturnType Random(Index size);
|
||||
static const RandomReturnType Random();
|
||||
|
||||
template<typename ThenDerived,typename ElseDerived>
|
||||
const Select<Derived,ThenDerived,ElseDerived>
|
||||
@@ -490,14 +540,33 @@ template<typename Derived> class DenseBase
|
||||
template<int p> RealScalar lpNorm() const;
|
||||
|
||||
template<int RowFactor, int ColFactor>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const Replicate<Derived,RowFactor,ColFactor> replicate() const;
|
||||
const Replicate<Derived,Dynamic,Dynamic> replicate(Index rowFacor,Index colFactor) const;
|
||||
/**
|
||||
* \return an expression of the replication of \c *this
|
||||
*
|
||||
* Example: \include MatrixBase_replicate_int_int.cpp
|
||||
* Output: \verbinclude MatrixBase_replicate_int_int.out
|
||||
*
|
||||
* \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
|
||||
*/
|
||||
//Code moved here due to a CUDA compiler bug
|
||||
EIGEN_DEVICE_FUNC
|
||||
const Replicate<Derived, Dynamic, Dynamic> replicate(Index rowFactor, Index colFactor) const
|
||||
{
|
||||
return Replicate<Derived, Dynamic, Dynamic>(derived(), rowFactor, colFactor);
|
||||
}
|
||||
|
||||
typedef Reverse<Derived, BothDirections> ReverseReturnType;
|
||||
typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType;
|
||||
ReverseReturnType reverse();
|
||||
ConstReverseReturnType reverse() const;
|
||||
void reverseInPlace();
|
||||
EIGEN_DEVICE_FUNC ReverseReturnType reverse();
|
||||
/** This is the const version of reverse(). */
|
||||
//Code moved here due to a CUDA compiler bug
|
||||
EIGEN_DEVICE_FUNC ConstReverseReturnType reverse() const
|
||||
{
|
||||
return ConstReverseReturnType(derived());
|
||||
}
|
||||
EIGEN_DEVICE_FUNC void reverseInPlace();
|
||||
|
||||
#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::DenseBase
|
||||
# include "../plugins/BlockMethods.h"
|
||||
|
||||
@@ -35,7 +35,6 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
|
||||
{
|
||||
public:
|
||||
typedef typename internal::traits<Derived>::StorageKind StorageKind;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
|
||||
|
||||
@@ -97,8 +96,8 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
|
||||
EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
|
||||
{
|
||||
eigen_internal_assert(row >= 0 && row < rows()
|
||||
&& col >= 0 && col < cols());
|
||||
return derived().coeff(row, col);
|
||||
&& col >= 0 && col < cols());
|
||||
return internal::evaluator<Derived>(derived()).coeff(row,col);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -117,7 +116,7 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
|
||||
{
|
||||
eigen_assert(row >= 0 && row < rows()
|
||||
&& col >= 0 && col < cols());
|
||||
return derived().coeff(row, col);
|
||||
return coeff(row, col);
|
||||
}
|
||||
|
||||
/** Short version: don't use this function, use
|
||||
@@ -140,7 +139,7 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
|
||||
coeff(Index index) const
|
||||
{
|
||||
eigen_internal_assert(index >= 0 && index < size());
|
||||
return derived().coeff(index);
|
||||
return internal::evaluator<Derived>(derived()).coeff(index);
|
||||
}
|
||||
|
||||
|
||||
@@ -159,7 +158,7 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
|
||||
EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
|
||||
THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
|
||||
eigen_assert(index >= 0 && index < size());
|
||||
return derived().coeff(index);
|
||||
return coeff(index);
|
||||
}
|
||||
|
||||
/** \returns the coefficient at given index.
|
||||
@@ -177,7 +176,7 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
|
||||
operator()(Index index) const
|
||||
{
|
||||
eigen_assert(index >= 0 && index < size());
|
||||
return derived().coeff(index);
|
||||
return coeff(index);
|
||||
}
|
||||
|
||||
/** equivalent to operator[](0). */
|
||||
@@ -217,9 +216,9 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
|
||||
template<int LoadMode>
|
||||
EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const
|
||||
{
|
||||
eigen_internal_assert(row >= 0 && row < rows()
|
||||
&& col >= 0 && col < cols());
|
||||
return derived().template packet<LoadMode>(row,col);
|
||||
typedef typename internal::packet_traits<Scalar>::type DefaultPacketType;
|
||||
eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
|
||||
return internal::evaluator<Derived>(derived()).template packet<LoadMode,DefaultPacketType>(row,col);
|
||||
}
|
||||
|
||||
|
||||
@@ -244,8 +243,9 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
|
||||
template<int LoadMode>
|
||||
EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
|
||||
{
|
||||
typedef typename internal::packet_traits<Scalar>::type DefaultPacketType;
|
||||
eigen_internal_assert(index >= 0 && index < size());
|
||||
return derived().template packet<LoadMode>(index);
|
||||
return internal::evaluator<Derived>(derived()).template packet<LoadMode,DefaultPacketType>(index);
|
||||
}
|
||||
|
||||
protected:
|
||||
@@ -288,7 +288,6 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
|
||||
typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
|
||||
|
||||
typedef typename internal::traits<Derived>::StorageKind StorageKind;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
@@ -325,8 +324,8 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
|
||||
EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
|
||||
{
|
||||
eigen_internal_assert(row >= 0 && row < rows()
|
||||
&& col >= 0 && col < cols());
|
||||
return derived().coeffRef(row, col);
|
||||
&& col >= 0 && col < cols());
|
||||
return internal::evaluator<Derived>(derived()).coeffRef(row,col);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -348,7 +347,7 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
|
||||
{
|
||||
eigen_assert(row >= 0 && row < rows()
|
||||
&& col >= 0 && col < cols());
|
||||
return derived().coeffRef(row, col);
|
||||
return coeffRef(row, col);
|
||||
}
|
||||
|
||||
|
||||
@@ -372,7 +371,7 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
|
||||
coeffRef(Index index)
|
||||
{
|
||||
eigen_internal_assert(index >= 0 && index < size());
|
||||
return derived().coeffRef(index);
|
||||
return internal::evaluator<Derived>(derived()).coeffRef(index);
|
||||
}
|
||||
|
||||
/** \returns a reference to the coefficient at given index.
|
||||
@@ -389,7 +388,7 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
|
||||
EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
|
||||
THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
|
||||
eigen_assert(index >= 0 && index < size());
|
||||
return derived().coeffRef(index);
|
||||
return coeffRef(index);
|
||||
}
|
||||
|
||||
/** \returns a reference to the coefficient at given index.
|
||||
@@ -406,7 +405,7 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
|
||||
operator()(Index index)
|
||||
{
|
||||
eigen_assert(index >= 0 && index < size());
|
||||
return derived().coeffRef(index);
|
||||
return coeffRef(index);
|
||||
}
|
||||
|
||||
/** equivalent to operator[](0). */
|
||||
@@ -432,144 +431,6 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Scalar&
|
||||
w() { return (*this)[3]; }
|
||||
|
||||
/** \internal
|
||||
* Stores the given packet of coefficients, at the given row and column of this expression. It is your responsibility
|
||||
* to ensure that a packet really starts there. This method is only available on expressions having the
|
||||
* PacketAccessBit.
|
||||
*
|
||||
* The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
|
||||
* the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
|
||||
* starting at an address which is a multiple of the packet size.
|
||||
*/
|
||||
|
||||
template<int StoreMode>
|
||||
EIGEN_STRONG_INLINE void writePacket
|
||||
(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,val);
|
||||
}
|
||||
|
||||
|
||||
/** \internal */
|
||||
template<int StoreMode>
|
||||
EIGEN_STRONG_INLINE void writePacketByOuterInner
|
||||
(Index outer, Index inner, const typename internal::packet_traits<Scalar>::type& val)
|
||||
{
|
||||
writePacket<StoreMode>(rowIndexByOuterInner(outer, inner),
|
||||
colIndexByOuterInner(outer, inner),
|
||||
val);
|
||||
}
|
||||
|
||||
/** \internal
|
||||
* Stores the given packet of coefficients, at the given index in this expression. It is your responsibility
|
||||
* to ensure that a packet really starts there. This method is only available on expressions having the
|
||||
* PacketAccessBit and the LinearAccessBit.
|
||||
*
|
||||
* The \a LoadMode parameter may have the value \a Aligned or \a Unaligned. Its effect is to select
|
||||
* the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
|
||||
* starting at an address which is a multiple of the packet size.
|
||||
*/
|
||||
template<int StoreMode>
|
||||
EIGEN_STRONG_INLINE void writePacket
|
||||
(Index index, const typename internal::packet_traits<Scalar>::type& val)
|
||||
{
|
||||
eigen_internal_assert(index >= 0 && index < size());
|
||||
derived().template writePacket<StoreMode>(index,val);
|
||||
}
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
|
||||
/** \internal Copies the coefficient at position (row,col) of other into *this.
|
||||
*
|
||||
* This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
|
||||
* with usual assignments.
|
||||
*
|
||||
* Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
|
||||
*/
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
eigen_internal_assert(row >= 0 && row < rows()
|
||||
&& col >= 0 && col < cols());
|
||||
derived().coeffRef(row, col) = other.derived().coeff(row, col);
|
||||
}
|
||||
|
||||
/** \internal Copies the coefficient at the given index of other into *this.
|
||||
*
|
||||
* This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
|
||||
* with usual assignments.
|
||||
*
|
||||
* Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
|
||||
*/
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
eigen_internal_assert(index >= 0 && index < size());
|
||||
derived().coeffRef(index) = other.derived().coeff(index);
|
||||
}
|
||||
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void copyCoeffByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
const Index row = rowIndexByOuterInner(outer,inner);
|
||||
const Index col = colIndexByOuterInner(outer,inner);
|
||||
// derived() is important here: copyCoeff() may be reimplemented in Derived!
|
||||
derived().copyCoeff(row, col, other);
|
||||
}
|
||||
|
||||
/** \internal Copies the packet at position (row,col) of other into *this.
|
||||
*
|
||||
* This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
|
||||
* with usual assignments.
|
||||
*
|
||||
* Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
|
||||
*/
|
||||
|
||||
template<typename OtherDerived, int StoreMode, int LoadMode>
|
||||
EIGEN_STRONG_INLINE void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
eigen_internal_assert(row >= 0 && row < rows()
|
||||
&& col >= 0 && col < cols());
|
||||
derived().template writePacket<StoreMode>(row, col,
|
||||
other.derived().template packet<LoadMode>(row, col));
|
||||
}
|
||||
|
||||
/** \internal Copies the packet at the given index of other into *this.
|
||||
*
|
||||
* This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
|
||||
* with usual assignments.
|
||||
*
|
||||
* Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
|
||||
*/
|
||||
|
||||
template<typename OtherDerived, int StoreMode, int LoadMode>
|
||||
EIGEN_STRONG_INLINE void copyPacket(Index index, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
eigen_internal_assert(index >= 0 && index < size());
|
||||
derived().template writePacket<StoreMode>(index,
|
||||
other.derived().template packet<LoadMode>(index));
|
||||
}
|
||||
|
||||
/** \internal */
|
||||
template<typename OtherDerived, int StoreMode, int LoadMode>
|
||||
EIGEN_STRONG_INLINE void copyPacketByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
const Index row = rowIndexByOuterInner(outer,inner);
|
||||
const Index col = colIndexByOuterInner(outer,inner);
|
||||
// derived() is important here: copyCoeff() may be reimplemented in Derived!
|
||||
derived().template copyPacket< OtherDerived, StoreMode, LoadMode>(row, col, other);
|
||||
}
|
||||
#endif
|
||||
|
||||
};
|
||||
|
||||
/** \brief Base class providing direct read-only coefficient access to matrices and arrays.
|
||||
@@ -589,7 +450,6 @@ class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived
|
||||
public:
|
||||
|
||||
typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
|
||||
@@ -664,7 +524,6 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
|
||||
public:
|
||||
|
||||
typedef DenseCoeffsBase<Derived, WriteAccessors> Base;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
|
||||
@@ -723,33 +582,42 @@ class DenseCoeffsBase<Derived, DirectWriteAccessors>
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename Derived, bool JustReturnZero>
|
||||
template<int Alignment, typename Derived, bool JustReturnZero>
|
||||
struct first_aligned_impl
|
||||
{
|
||||
static inline typename Derived::Index run(const Derived&)
|
||||
static inline Index run(const Derived&)
|
||||
{ return 0; }
|
||||
};
|
||||
|
||||
template<typename Derived>
|
||||
struct first_aligned_impl<Derived, false>
|
||||
template<int Alignment, typename Derived>
|
||||
struct first_aligned_impl<Alignment, Derived, false>
|
||||
{
|
||||
static inline typename Derived::Index run(const Derived& m)
|
||||
static inline Index run(const Derived& m)
|
||||
{
|
||||
return internal::first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
|
||||
return internal::first_aligned<Alignment>(&m.const_cast_derived().coeffRef(0,0), m.size());
|
||||
}
|
||||
};
|
||||
|
||||
/** \internal \returns the index of the first element of the array that is well aligned for vectorization.
|
||||
/** \internal \returns the index of the first element of the array stored by \a m that is properly aligned with respect to \a Alignment for vectorization.
|
||||
*
|
||||
* \tparam Alignment requested alignment in Bytes.
|
||||
*
|
||||
* There is also the variant first_aligned(const Scalar*, Integer) defined in Memory.h. See it for more
|
||||
* documentation.
|
||||
*/
|
||||
template<typename Derived>
|
||||
static inline typename Derived::Index first_aligned(const Derived& m)
|
||||
template<int Alignment, typename Derived>
|
||||
static inline Index first_aligned(const DenseBase<Derived>& m)
|
||||
{
|
||||
return first_aligned_impl
|
||||
<Derived, (Derived::Flags & AlignedBit) || !(Derived::Flags & DirectAccessBit)>
|
||||
::run(m);
|
||||
enum { ReturnZero = (int(evaluator<Derived>::Alignment) >= Alignment) || !(Derived::Flags & DirectAccessBit) };
|
||||
return first_aligned_impl<Alignment, Derived, ReturnZero>::run(m.derived());
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
static inline Index first_default_aligned(const DenseBase<Derived>& m)
|
||||
{
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
typedef typename packet_traits<Scalar>::type DefaultPacketType;
|
||||
return first_aligned<unpacket_traits<DefaultPacketType>::alignment>(m);
|
||||
}
|
||||
|
||||
template<typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret>
|
||||
|
||||
@@ -40,8 +40,7 @@ void check_static_allocation_size()
|
||||
*/
|
||||
template <typename T, int Size, int MatrixOrArrayOptions,
|
||||
int Alignment = (MatrixOrArrayOptions&DontAlign) ? 0
|
||||
: (((Size*sizeof(T))%EIGEN_ALIGN_BYTES)==0) ? EIGEN_ALIGN_BYTES
|
||||
: 0 >
|
||||
: compute_default_alignment<T,Size>::value >
|
||||
struct plain_array
|
||||
{
|
||||
T array[Size];
|
||||
@@ -81,14 +80,71 @@ struct plain_array
|
||||
#endif
|
||||
|
||||
template <typename T, int Size, int MatrixOrArrayOptions>
|
||||
struct plain_array<T, Size, MatrixOrArrayOptions, EIGEN_ALIGN_BYTES>
|
||||
struct plain_array<T, Size, MatrixOrArrayOptions, 8>
|
||||
{
|
||||
EIGEN_USER_ALIGN_DEFAULT T array[Size];
|
||||
EIGEN_ALIGN_TO_BOUNDARY(8) T array[Size];
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
plain_array()
|
||||
{
|
||||
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(7);
|
||||
check_static_allocation_size<T,Size>();
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
plain_array(constructor_without_unaligned_array_assert)
|
||||
{
|
||||
check_static_allocation_size<T,Size>();
|
||||
}
|
||||
};
|
||||
|
||||
template <typename T, int Size, int MatrixOrArrayOptions>
|
||||
struct plain_array<T, Size, MatrixOrArrayOptions, 16>
|
||||
{
|
||||
EIGEN_ALIGN_TO_BOUNDARY(16) T array[Size];
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
plain_array()
|
||||
{
|
||||
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(EIGEN_ALIGN_BYTES-1);
|
||||
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(15);
|
||||
check_static_allocation_size<T,Size>();
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
plain_array(constructor_without_unaligned_array_assert)
|
||||
{
|
||||
check_static_allocation_size<T,Size>();
|
||||
}
|
||||
};
|
||||
|
||||
template <typename T, int Size, int MatrixOrArrayOptions>
|
||||
struct plain_array<T, Size, MatrixOrArrayOptions, 32>
|
||||
{
|
||||
EIGEN_ALIGN_TO_BOUNDARY(32) T array[Size];
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
plain_array()
|
||||
{
|
||||
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(31);
|
||||
check_static_allocation_size<T,Size>();
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
plain_array(constructor_without_unaligned_array_assert)
|
||||
{
|
||||
check_static_allocation_size<T,Size>();
|
||||
}
|
||||
};
|
||||
|
||||
template <typename T, int Size, int MatrixOrArrayOptions>
|
||||
struct plain_array<T, Size, MatrixOrArrayOptions, 64>
|
||||
{
|
||||
EIGEN_ALIGN_TO_BOUNDARY(64) T array[Size];
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
plain_array()
|
||||
{
|
||||
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(63);
|
||||
check_static_allocation_size<T,Size>();
|
||||
}
|
||||
|
||||
@@ -102,7 +158,7 @@ struct plain_array<T, Size, MatrixOrArrayOptions, EIGEN_ALIGN_BYTES>
|
||||
template <typename T, int MatrixOrArrayOptions, int Alignment>
|
||||
struct plain_array<T, 0, MatrixOrArrayOptions, Alignment>
|
||||
{
|
||||
EIGEN_USER_ALIGN_DEFAULT T array[1];
|
||||
T array[1];
|
||||
EIGEN_DEVICE_FUNC plain_array() {}
|
||||
EIGEN_DEVICE_FUNC plain_array(constructor_without_unaligned_array_assert) {}
|
||||
};
|
||||
@@ -130,7 +186,7 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
|
||||
public:
|
||||
EIGEN_DEVICE_FUNC DenseStorage() {}
|
||||
EIGEN_DEVICE_FUNC
|
||||
DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
: m_data(internal::constructor_without_unaligned_array_assert()) {}
|
||||
EIGEN_DEVICE_FUNC
|
||||
DenseStorage(const DenseStorage& other) : m_data(other.m_data) {}
|
||||
@@ -140,12 +196,18 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
|
||||
if (this != &other) m_data = other.m_data;
|
||||
return *this;
|
||||
}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) {
|
||||
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
|
||||
eigen_internal_assert(size==rows*cols && rows==_Rows && cols==_Cols);
|
||||
EIGEN_UNUSED_VARIABLE(size);
|
||||
EIGEN_UNUSED_VARIABLE(rows);
|
||||
EIGEN_UNUSED_VARIABLE(cols);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
|
||||
EIGEN_DEVICE_FUNC static DenseIndex rows(void) {return _Rows;}
|
||||
EIGEN_DEVICE_FUNC static DenseIndex cols(void) {return _Cols;}
|
||||
EIGEN_DEVICE_FUNC void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
|
||||
EIGEN_DEVICE_FUNC void resize(DenseIndex,DenseIndex,DenseIndex) {}
|
||||
EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
|
||||
EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
|
||||
EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
|
||||
EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
|
||||
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
|
||||
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
|
||||
};
|
||||
@@ -155,15 +217,15 @@ template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0
|
||||
{
|
||||
public:
|
||||
EIGEN_DEVICE_FUNC DenseStorage() {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(internal::constructor_without_unaligned_array_assert) {}
|
||||
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage&) {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage&) { return *this; }
|
||||
EIGEN_DEVICE_FUNC DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(Index,Index,Index) {}
|
||||
EIGEN_DEVICE_FUNC void swap(DenseStorage& ) {}
|
||||
EIGEN_DEVICE_FUNC static DenseIndex rows(void) {return _Rows;}
|
||||
EIGEN_DEVICE_FUNC static DenseIndex cols(void) {return _Cols;}
|
||||
EIGEN_DEVICE_FUNC void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
|
||||
EIGEN_DEVICE_FUNC void resize(DenseIndex,DenseIndex,DenseIndex) {}
|
||||
EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
|
||||
EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
|
||||
EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
|
||||
EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
|
||||
EIGEN_DEVICE_FUNC const T *data() const { return 0; }
|
||||
EIGEN_DEVICE_FUNC T *data() { return 0; }
|
||||
};
|
||||
@@ -182,14 +244,14 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, 0, Dynamic,
|
||||
template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options>
|
||||
{
|
||||
internal::plain_array<T,Size,_Options> m_data;
|
||||
DenseIndex m_rows;
|
||||
DenseIndex m_cols;
|
||||
Index m_rows;
|
||||
Index m_cols;
|
||||
public:
|
||||
EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0), m_cols(0) {}
|
||||
DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
|
||||
DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {}
|
||||
DenseStorage& operator=(const DenseStorage& other)
|
||||
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
|
||||
{
|
||||
if (this != &other)
|
||||
{
|
||||
@@ -199,13 +261,13 @@ template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic
|
||||
}
|
||||
return *this;
|
||||
}
|
||||
DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
|
||||
void swap(DenseStorage& other)
|
||||
EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index cols) : m_rows(rows), m_cols(cols) {}
|
||||
EIGEN_DEVICE_FUNC 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); }
|
||||
EIGEN_DEVICE_FUNC DenseIndex rows() const {return m_rows;}
|
||||
EIGEN_DEVICE_FUNC DenseIndex cols() const {return m_cols;}
|
||||
void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
|
||||
void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
|
||||
EIGEN_DEVICE_FUNC Index rows() const {return m_rows;}
|
||||
EIGEN_DEVICE_FUNC Index cols() const {return m_cols;}
|
||||
EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; }
|
||||
EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; }
|
||||
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
|
||||
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
|
||||
};
|
||||
@@ -214,13 +276,13 @@ template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic
|
||||
template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Size, Dynamic, _Cols, _Options>
|
||||
{
|
||||
internal::plain_array<T,Size,_Options> m_data;
|
||||
DenseIndex m_rows;
|
||||
Index m_rows;
|
||||
public:
|
||||
EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0) {}
|
||||
DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
: m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
|
||||
DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {}
|
||||
DenseStorage& operator=(const DenseStorage& other)
|
||||
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
|
||||
{
|
||||
if (this != &other)
|
||||
{
|
||||
@@ -229,12 +291,12 @@ template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Si
|
||||
}
|
||||
return *this;
|
||||
}
|
||||
DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
|
||||
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
|
||||
EIGEN_DEVICE_FUNC DenseIndex rows(void) const {return m_rows;}
|
||||
EIGEN_DEVICE_FUNC DenseIndex cols(void) const {return _Cols;}
|
||||
void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
|
||||
void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
|
||||
EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index) : m_rows(rows) {}
|
||||
EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
|
||||
EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
|
||||
EIGEN_DEVICE_FUNC Index cols(void) const {return _Cols;}
|
||||
EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index) { m_rows = rows; }
|
||||
EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index) { m_rows = rows; }
|
||||
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
|
||||
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
|
||||
};
|
||||
@@ -243,13 +305,13 @@ template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Si
|
||||
template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Size, _Rows, Dynamic, _Options>
|
||||
{
|
||||
internal::plain_array<T,Size,_Options> m_data;
|
||||
DenseIndex m_cols;
|
||||
Index m_cols;
|
||||
public:
|
||||
EIGEN_DEVICE_FUNC DenseStorage() : m_cols(0) {}
|
||||
DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
: m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
|
||||
DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {}
|
||||
DenseStorage& operator=(const DenseStorage& other)
|
||||
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
|
||||
{
|
||||
if (this != &other)
|
||||
{
|
||||
@@ -258,12 +320,12 @@ template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Si
|
||||
}
|
||||
return *this;
|
||||
}
|
||||
DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
|
||||
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
|
||||
EIGEN_DEVICE_FUNC DenseIndex rows(void) const {return _Rows;}
|
||||
EIGEN_DEVICE_FUNC DenseIndex cols(void) const {return m_cols;}
|
||||
void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
|
||||
void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
|
||||
EIGEN_DEVICE_FUNC DenseStorage(Index, Index, Index cols) : m_cols(cols) {}
|
||||
EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
|
||||
EIGEN_DEVICE_FUNC Index rows(void) const {return _Rows;}
|
||||
EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
|
||||
void conservativeResize(Index, Index, Index cols) { m_cols = cols; }
|
||||
void resize(Index, Index, Index cols) { m_cols = cols; }
|
||||
EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
|
||||
EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
|
||||
};
|
||||
@@ -272,23 +334,26 @@ template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Si
|
||||
template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options>
|
||||
{
|
||||
T *m_data;
|
||||
DenseIndex m_rows;
|
||||
DenseIndex m_cols;
|
||||
Index m_rows;
|
||||
Index m_cols;
|
||||
public:
|
||||
EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
|
||||
DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
|
||||
: m_data(0), m_rows(0), m_cols(0) {}
|
||||
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 }
|
||||
DenseStorage(const DenseStorage& other)
|
||||
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols)
|
||||
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols)
|
||||
{
|
||||
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
|
||||
eigen_internal_assert(size==rows*cols && rows>=0 && cols >=0);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
|
||||
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*other.m_cols))
|
||||
, m_rows(other.m_rows)
|
||||
, m_cols(other.m_cols)
|
||||
{
|
||||
internal::smart_copy(other.m_data, other.m_data+other.m_rows*other.m_cols, m_data);
|
||||
}
|
||||
DenseStorage& operator=(const DenseStorage& other)
|
||||
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
|
||||
{
|
||||
if (this != &other)
|
||||
{
|
||||
@@ -298,13 +363,17 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
|
||||
return *this;
|
||||
}
|
||||
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
|
||||
EIGEN_DEVICE_FUNC
|
||||
DenseStorage(DenseStorage&& other)
|
||||
: m_data(std::move(other.m_data))
|
||||
, m_rows(std::move(other.m_rows))
|
||||
, m_cols(std::move(other.m_cols))
|
||||
{
|
||||
other.m_data = nullptr;
|
||||
other.m_rows = 0;
|
||||
other.m_cols = 0;
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
DenseStorage& operator=(DenseStorage&& other)
|
||||
{
|
||||
using std::swap;
|
||||
@@ -314,18 +383,18 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
|
||||
return *this;
|
||||
}
|
||||
#endif
|
||||
~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
|
||||
void swap(DenseStorage& other)
|
||||
EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
|
||||
EIGEN_DEVICE_FUNC 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); }
|
||||
EIGEN_DEVICE_FUNC DenseIndex rows(void) const {return m_rows;}
|
||||
EIGEN_DEVICE_FUNC DenseIndex cols(void) const {return m_cols;}
|
||||
void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
|
||||
EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
|
||||
EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
|
||||
void conservativeResize(Index size, Index rows, Index cols)
|
||||
{
|
||||
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
|
||||
m_rows = nbRows;
|
||||
m_cols = nbCols;
|
||||
m_rows = rows;
|
||||
m_cols = cols;
|
||||
}
|
||||
void resize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
|
||||
EIGEN_DEVICE_FUNC void resize(Index size, Index rows, Index cols)
|
||||
{
|
||||
if(size != m_rows*m_cols)
|
||||
{
|
||||
@@ -336,8 +405,8 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
|
||||
m_data = 0;
|
||||
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
|
||||
}
|
||||
m_rows = nbRows;
|
||||
m_cols = nbCols;
|
||||
m_rows = rows;
|
||||
m_cols = cols;
|
||||
}
|
||||
EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
|
||||
EIGEN_DEVICE_FUNC T *data() { return m_data; }
|
||||
@@ -347,19 +416,23 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
|
||||
template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Rows, Dynamic, _Options>
|
||||
{
|
||||
T *m_data;
|
||||
DenseIndex m_cols;
|
||||
Index m_cols;
|
||||
public:
|
||||
EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_cols(0) {}
|
||||
DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
|
||||
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 }
|
||||
DenseStorage(const DenseStorage& other)
|
||||
explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
|
||||
{
|
||||
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
|
||||
eigen_internal_assert(size==rows*cols && rows==_Rows && cols >=0);
|
||||
EIGEN_UNUSED_VARIABLE(rows);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
|
||||
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(_Rows*other.m_cols))
|
||||
, m_cols(other.m_cols)
|
||||
{
|
||||
internal::smart_copy(other.m_data, other.m_data+_Rows*m_cols, m_data);
|
||||
}
|
||||
DenseStorage& operator=(const DenseStorage& other)
|
||||
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
|
||||
{
|
||||
if (this != &other)
|
||||
{
|
||||
@@ -369,12 +442,15 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
|
||||
return *this;
|
||||
}
|
||||
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
|
||||
EIGEN_DEVICE_FUNC
|
||||
DenseStorage(DenseStorage&& other)
|
||||
: m_data(std::move(other.m_data))
|
||||
, m_cols(std::move(other.m_cols))
|
||||
{
|
||||
other.m_data = nullptr;
|
||||
other.m_cols = 0;
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
DenseStorage& operator=(DenseStorage&& other)
|
||||
{
|
||||
using std::swap;
|
||||
@@ -383,16 +459,16 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
|
||||
return *this;
|
||||
}
|
||||
#endif
|
||||
~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
|
||||
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
|
||||
EIGEN_DEVICE_FUNC static DenseIndex rows(void) {return _Rows;}
|
||||
EIGEN_DEVICE_FUNC DenseIndex cols(void) const {return m_cols;}
|
||||
void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
|
||||
EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
|
||||
EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
|
||||
EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
|
||||
EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
|
||||
EIGEN_DEVICE_FUNC void conservativeResize(Index size, Index, Index cols)
|
||||
{
|
||||
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
|
||||
m_cols = nbCols;
|
||||
m_cols = cols;
|
||||
}
|
||||
EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex nbCols)
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index, Index cols)
|
||||
{
|
||||
if(size != _Rows*m_cols)
|
||||
{
|
||||
@@ -403,7 +479,7 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
|
||||
m_data = 0;
|
||||
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
|
||||
}
|
||||
m_cols = nbCols;
|
||||
m_cols = cols;
|
||||
}
|
||||
EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
|
||||
EIGEN_DEVICE_FUNC T *data() { return m_data; }
|
||||
@@ -413,19 +489,23 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
|
||||
template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dynamic, _Cols, _Options>
|
||||
{
|
||||
T *m_data;
|
||||
DenseIndex m_rows;
|
||||
Index m_rows;
|
||||
public:
|
||||
EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0) {}
|
||||
DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
|
||||
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 }
|
||||
DenseStorage(const DenseStorage& other)
|
||||
explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
|
||||
{
|
||||
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
|
||||
eigen_internal_assert(size==rows*cols && rows>=0 && cols == _Cols);
|
||||
EIGEN_UNUSED_VARIABLE(cols);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
|
||||
: m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*_Cols))
|
||||
, m_rows(other.m_rows)
|
||||
{
|
||||
internal::smart_copy(other.m_data, other.m_data+other.m_rows*_Cols, m_data);
|
||||
}
|
||||
DenseStorage& operator=(const DenseStorage& other)
|
||||
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
|
||||
{
|
||||
if (this != &other)
|
||||
{
|
||||
@@ -435,12 +515,15 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
|
||||
return *this;
|
||||
}
|
||||
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
|
||||
EIGEN_DEVICE_FUNC
|
||||
DenseStorage(DenseStorage&& other)
|
||||
: m_data(std::move(other.m_data))
|
||||
, m_rows(std::move(other.m_rows))
|
||||
{
|
||||
other.m_data = nullptr;
|
||||
other.m_rows = 0;
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
DenseStorage& operator=(DenseStorage&& other)
|
||||
{
|
||||
using std::swap;
|
||||
@@ -449,16 +532,16 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
|
||||
return *this;
|
||||
}
|
||||
#endif
|
||||
~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
|
||||
void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
|
||||
EIGEN_DEVICE_FUNC DenseIndex rows(void) const {return m_rows;}
|
||||
EIGEN_DEVICE_FUNC static DenseIndex cols(void) {return _Cols;}
|
||||
void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
|
||||
EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
|
||||
EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
|
||||
EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
|
||||
EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
|
||||
void conservativeResize(Index size, Index rows, Index)
|
||||
{
|
||||
m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
|
||||
m_rows = nbRows;
|
||||
m_rows = rows;
|
||||
}
|
||||
EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex nbRows, DenseIndex)
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index rows, Index)
|
||||
{
|
||||
if(size != m_rows*_Cols)
|
||||
{
|
||||
@@ -469,7 +552,7 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
|
||||
m_data = 0;
|
||||
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
|
||||
}
|
||||
m_rows = nbRows;
|
||||
m_rows = rows;
|
||||
}
|
||||
EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
|
||||
EIGEN_DEVICE_FUNC T *data() { return m_data; }
|
||||
|
||||
@@ -37,7 +37,7 @@ template<typename MatrixType, int DiagIndex>
|
||||
struct traits<Diagonal<MatrixType,DiagIndex> >
|
||||
: traits<MatrixType>
|
||||
{
|
||||
typedef typename nested<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
|
||||
typedef typename MatrixType::StorageKind StorageKind;
|
||||
enum {
|
||||
@@ -52,8 +52,7 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
|
||||
MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
|
||||
MaxColsAtCompileTime = 1,
|
||||
MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
|
||||
Flags = (unsigned int)_MatrixTypeNested::Flags & (HereditaryBits | LinearAccessBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit,
|
||||
CoeffReadCost = _MatrixTypeNested::CoeffReadCost,
|
||||
Flags = (unsigned int)_MatrixTypeNested::Flags & (RowMajorBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit, // FIXME DirectAccessBit should not be handled by expressions
|
||||
MatrixTypeOuterStride = outer_stride_at_compile_time<MatrixType>::ret,
|
||||
InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1,
|
||||
OuterStrideAtCompileTime = 0
|
||||
@@ -71,17 +70,15 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
|
||||
explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
|
||||
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index rows() const
|
||||
{
|
||||
EIGEN_USING_STD_MATH(min);
|
||||
return m_index.value()<0 ? (min)(Index(m_matrix.cols()),Index(m_matrix.rows()+m_index.value()))
|
||||
: (min)(Index(m_matrix.rows()),Index(m_matrix.cols()-m_index.value()));
|
||||
|
||||
return m_index.value()<0 ? numext::mini<Index>(m_matrix.cols(),m_matrix.rows()+m_index.value())
|
||||
: numext::mini<Index>(m_matrix.rows(),m_matrix.cols()-m_index.value());
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -149,14 +146,14 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
const typename internal::remove_all<typename MatrixType::Nested>::type&
|
||||
inline const typename internal::remove_all<typename MatrixType::Nested>::type&
|
||||
nestedExpression() const
|
||||
{
|
||||
return m_matrix;
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
int index() const
|
||||
inline Index index() const
|
||||
{
|
||||
return m_index.value();
|
||||
}
|
||||
@@ -173,7 +170,7 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
|
||||
EIGEN_STRONG_INLINE Index rowOffset() const { return m_index.value()>0 ? 0 : -m_index.value(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value()>0 ? m_index.value() : 0; }
|
||||
// triger a compile time error is someone try to call packet
|
||||
// trigger a compile-time error if someone try to call packet
|
||||
template<int LoadMode> typename MatrixType::PacketReturnType packet(Index) const;
|
||||
template<int LoadMode> typename MatrixType::PacketReturnType packet(Index,Index) const;
|
||||
};
|
||||
@@ -190,7 +187,7 @@ template<typename Derived>
|
||||
inline typename MatrixBase<Derived>::DiagonalReturnType
|
||||
MatrixBase<Derived>::diagonal()
|
||||
{
|
||||
return derived();
|
||||
return DiagonalReturnType(derived());
|
||||
}
|
||||
|
||||
/** This is the const version of diagonal(). */
|
||||
@@ -213,18 +210,18 @@ MatrixBase<Derived>::diagonal() const
|
||||
*
|
||||
* \sa MatrixBase::diagonal(), class Diagonal */
|
||||
template<typename Derived>
|
||||
inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<DynamicIndex>::Type
|
||||
inline typename MatrixBase<Derived>::DiagonalDynamicIndexReturnType
|
||||
MatrixBase<Derived>::diagonal(Index index)
|
||||
{
|
||||
return typename DiagonalIndexReturnType<DynamicIndex>::Type(derived(), index);
|
||||
return DiagonalDynamicIndexReturnType(derived(), index);
|
||||
}
|
||||
|
||||
/** This is the const version of diagonal(Index). */
|
||||
template<typename Derived>
|
||||
inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<DynamicIndex>::Type
|
||||
inline typename MatrixBase<Derived>::ConstDiagonalDynamicIndexReturnType
|
||||
MatrixBase<Derived>::diagonal(Index index) const
|
||||
{
|
||||
return typename ConstDiagonalIndexReturnType<DynamicIndex>::Type(derived(), index);
|
||||
return ConstDiagonalDynamicIndexReturnType(derived(), index);
|
||||
}
|
||||
|
||||
/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
|
||||
@@ -239,20 +236,20 @@ MatrixBase<Derived>::diagonal(Index index) const
|
||||
*
|
||||
* \sa MatrixBase::diagonal(), class Diagonal */
|
||||
template<typename Derived>
|
||||
template<int Index>
|
||||
inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index>::Type
|
||||
template<int Index_>
|
||||
inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index_>::Type
|
||||
MatrixBase<Derived>::diagonal()
|
||||
{
|
||||
return derived();
|
||||
return typename DiagonalIndexReturnType<Index_>::Type(derived());
|
||||
}
|
||||
|
||||
/** This is the const version of diagonal<int>(). */
|
||||
template<typename Derived>
|
||||
template<int Index>
|
||||
inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index>::Type
|
||||
template<int Index_>
|
||||
inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index_>::Type
|
||||
MatrixBase<Derived>::diagonal() const
|
||||
{
|
||||
return derived();
|
||||
return typename ConstDiagonalIndexReturnType<Index_>::Type(derived());
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -22,7 +22,7 @@ class DiagonalBase : public EigenBase<Derived>
|
||||
typedef typename DiagonalVectorType::Scalar Scalar;
|
||||
typedef typename DiagonalVectorType::RealScalar RealScalar;
|
||||
typedef typename internal::traits<Derived>::StorageKind StorageKind;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
|
||||
|
||||
enum {
|
||||
RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
|
||||
@@ -30,7 +30,7 @@ class DiagonalBase : public EigenBase<Derived>
|
||||
MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
|
||||
MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
|
||||
IsVectorAtCompileTime = 0,
|
||||
Flags = 0
|
||||
Flags = NoPreferredStorageOrderBit
|
||||
};
|
||||
|
||||
typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime> DenseMatrixType;
|
||||
@@ -44,18 +44,7 @@ class DiagonalBase : public EigenBase<Derived>
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
DenseMatrixType toDenseMatrix() const { return derived(); }
|
||||
template<typename DenseDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void evalTo(MatrixBase<DenseDerived> &other) const;
|
||||
template<typename DenseDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void addTo(MatrixBase<DenseDerived> &other) const
|
||||
{ other.diagonal() += diagonal(); }
|
||||
template<typename DenseDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void subTo(MatrixBase<DenseDerived> &other) const
|
||||
{ other.diagonal() -= diagonal(); }
|
||||
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -66,44 +55,37 @@ class DiagonalBase : public EigenBase<Derived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index cols() const { return diagonal().size(); }
|
||||
|
||||
/** \returns the diagonal matrix product of \c *this by the matrix \a matrix.
|
||||
*/
|
||||
template<typename MatrixDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
|
||||
const Product<Derived,MatrixDerived,LazyProduct>
|
||||
operator*(const MatrixBase<MatrixDerived> &matrix) const
|
||||
{
|
||||
return DiagonalProduct<MatrixDerived, Derived, OnTheLeft>(matrix.derived(), derived());
|
||||
return Product<Derived, MatrixDerived, LazyProduct>(derived(),matrix.derived());
|
||||
}
|
||||
|
||||
typedef DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> > InverseReturnType;
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
|
||||
inline const InverseReturnType
|
||||
inverse() const
|
||||
{
|
||||
return diagonal().cwiseInverse();
|
||||
return InverseReturnType(diagonal().cwiseInverse());
|
||||
}
|
||||
|
||||
typedef DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> > ScalarMultipleReturnType;
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
|
||||
inline const ScalarMultipleReturnType
|
||||
operator*(const Scalar& scalar) const
|
||||
{
|
||||
return diagonal() * scalar;
|
||||
return ScalarMultipleReturnType(diagonal() * scalar);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
friend inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
|
||||
friend inline const ScalarMultipleReturnType
|
||||
operator*(const Scalar& scalar, const DiagonalBase& other)
|
||||
{
|
||||
return other.diagonal() * scalar;
|
||||
return ScalarMultipleReturnType(other.diagonal() * scalar);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived>
|
||||
template<typename DenseDerived>
|
||||
void DiagonalBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
|
||||
{
|
||||
other.setZero();
|
||||
other.diagonal() = diagonal();
|
||||
}
|
||||
#endif
|
||||
|
||||
/** \class DiagonalMatrix
|
||||
@@ -125,10 +107,9 @@ struct traits<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
|
||||
: traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
|
||||
{
|
||||
typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
|
||||
typedef Dense StorageKind;
|
||||
typedef DenseIndex Index;
|
||||
typedef DiagonalShape StorageKind;
|
||||
enum {
|
||||
Flags = LvalueBit
|
||||
Flags = LvalueBit | NoPreferredStorageOrderBit
|
||||
};
|
||||
};
|
||||
}
|
||||
@@ -142,7 +123,7 @@ class DiagonalMatrix
|
||||
typedef const DiagonalMatrix& Nested;
|
||||
typedef _Scalar Scalar;
|
||||
typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind;
|
||||
typedef typename internal::traits<DiagonalMatrix>::Index Index;
|
||||
typedef typename internal::traits<DiagonalMatrix>::StorageIndex StorageIndex;
|
||||
#endif
|
||||
|
||||
protected:
|
||||
@@ -164,7 +145,7 @@ class DiagonalMatrix
|
||||
|
||||
/** Constructs a diagonal matrix with given dimension */
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
|
||||
explicit inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
|
||||
|
||||
/** 2D constructor. */
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -248,14 +229,15 @@ struct traits<DiagonalWrapper<_DiagonalVectorType> >
|
||||
{
|
||||
typedef _DiagonalVectorType DiagonalVectorType;
|
||||
typedef typename DiagonalVectorType::Scalar Scalar;
|
||||
typedef typename DiagonalVectorType::Index Index;
|
||||
typedef typename DiagonalVectorType::StorageKind StorageKind;
|
||||
typedef typename DiagonalVectorType::StorageIndex StorageIndex;
|
||||
typedef DiagonalShape StorageKind;
|
||||
typedef typename traits<DiagonalVectorType>::XprKind XprKind;
|
||||
enum {
|
||||
RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
|
||||
ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
|
||||
MaxRowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
|
||||
MaxColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
|
||||
Flags = traits<DiagonalVectorType>::Flags & LvalueBit
|
||||
MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
|
||||
MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
|
||||
Flags = (traits<DiagonalVectorType>::Flags & LvalueBit) | NoPreferredStorageOrderBit
|
||||
};
|
||||
};
|
||||
}
|
||||
@@ -272,7 +254,7 @@ class DiagonalWrapper
|
||||
|
||||
/** Constructor from expression of diagonal coefficients to wrap. */
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
|
||||
explicit inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
|
||||
|
||||
/** \returns a const reference to the wrapped expression of diagonal coefficients. */
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -295,7 +277,7 @@ template<typename Derived>
|
||||
inline const DiagonalWrapper<const Derived>
|
||||
MatrixBase<Derived>::asDiagonal() const
|
||||
{
|
||||
return derived();
|
||||
return DiagonalWrapper<const Derived>(derived());
|
||||
}
|
||||
|
||||
/** \returns true if *this is approximately equal to a diagonal matrix,
|
||||
@@ -326,6 +308,33 @@ bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
|
||||
return true;
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<> struct storage_kind_to_shape<DiagonalShape> { typedef DiagonalShape Shape; };
|
||||
|
||||
struct Diagonal2Dense {};
|
||||
|
||||
template<> struct AssignmentKind<DenseShape,DiagonalShape> { typedef Diagonal2Dense Kind; };
|
||||
|
||||
// Diagonal matrix to Dense assignment
|
||||
template< typename DstXprType, typename SrcXprType, typename Functor, typename Scalar>
|
||||
struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Dense, Scalar>
|
||||
{
|
||||
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar> &/*func*/)
|
||||
{
|
||||
dst.setZero();
|
||||
dst.diagonal() = src.diagonal();
|
||||
}
|
||||
|
||||
static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar> &/*func*/)
|
||||
{ dst.diagonal() += src.diagonal(); }
|
||||
|
||||
static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar> &/*func*/)
|
||||
{ dst.diagonal() -= src.diagonal(); }
|
||||
};
|
||||
|
||||
} // namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_DIAGONALMATRIX_H
|
||||
|
||||
@@ -13,116 +13,14 @@
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
template<typename MatrixType, typename DiagonalType, int ProductOrder>
|
||||
struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
|
||||
: traits<MatrixType>
|
||||
{
|
||||
typedef typename scalar_product_traits<typename MatrixType::Scalar, typename DiagonalType::Scalar>::ReturnType Scalar;
|
||||
enum {
|
||||
RowsAtCompileTime = MatrixType::RowsAtCompileTime,
|
||||
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
|
||||
MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
|
||||
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
|
||||
|
||||
_StorageOrder = MatrixType::Flags & RowMajorBit ? RowMajor : ColMajor,
|
||||
_ScalarAccessOnDiag = !((int(_StorageOrder) == ColMajor && int(ProductOrder) == OnTheLeft)
|
||||
||(int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheRight)),
|
||||
_SameTypes = is_same<typename MatrixType::Scalar, typename DiagonalType::Scalar>::value,
|
||||
// FIXME currently we need same types, but in the future the next rule should be the one
|
||||
//_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && ((!_PacketOnDiag) || (_SameTypes && bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
|
||||
_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
|
||||
_LinearAccessMask = (RowsAtCompileTime==1 || ColsAtCompileTime==1) ? LinearAccessBit : 0,
|
||||
|
||||
Flags = ((HereditaryBits|_LinearAccessMask) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0) | AlignedBit,//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit),
|
||||
CoeffReadCost = NumTraits<Scalar>::MulCost + MatrixType::CoeffReadCost + DiagonalType::DiagonalVectorType::CoeffReadCost
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
template<typename MatrixType, typename DiagonalType, int ProductOrder>
|
||||
class DiagonalProduct : internal::no_assignment_operator,
|
||||
public MatrixBase<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
|
||||
{
|
||||
public:
|
||||
|
||||
typedef MatrixBase<DiagonalProduct> Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(DiagonalProduct)
|
||||
|
||||
inline DiagonalProduct(const MatrixType& matrix, const DiagonalType& diagonal)
|
||||
: m_matrix(matrix), m_diagonal(diagonal)
|
||||
{
|
||||
eigen_assert(diagonal.diagonal().size() == (ProductOrder == OnTheLeft ? matrix.rows() : matrix.cols()));
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
|
||||
EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); }
|
||||
|
||||
EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
|
||||
{
|
||||
return m_diagonal.diagonal().coeff(ProductOrder == OnTheLeft ? row : col) * m_matrix.coeff(row, col);
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const
|
||||
{
|
||||
enum {
|
||||
StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
|
||||
};
|
||||
return coeff(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
|
||||
{
|
||||
enum {
|
||||
StorageOrder = Flags & RowMajorBit ? RowMajor : ColMajor
|
||||
};
|
||||
const Index indexInDiagonalVector = ProductOrder == OnTheLeft ? row : col;
|
||||
return packet_impl<LoadMode>(row,col,indexInDiagonalVector,typename internal::conditional<
|
||||
((int(StorageOrder) == RowMajor && int(ProductOrder) == OnTheLeft)
|
||||
||(int(StorageOrder) == ColMajor && int(ProductOrder) == OnTheRight)), internal::true_type, internal::false_type>::type());
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
EIGEN_STRONG_INLINE PacketScalar packet(Index idx) const
|
||||
{
|
||||
enum {
|
||||
StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
|
||||
};
|
||||
return packet<LoadMode>(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
|
||||
}
|
||||
|
||||
protected:
|
||||
template<int LoadMode>
|
||||
EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::true_type) const
|
||||
{
|
||||
return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
|
||||
internal::pset1<PacketScalar>(m_diagonal.diagonal().coeff(id)));
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::false_type) const
|
||||
{
|
||||
enum {
|
||||
InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
|
||||
DiagonalVectorPacketLoadMode = (LoadMode == Aligned && (((InnerSize%16) == 0) || (int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit)==AlignedBit) ? Aligned : Unaligned)
|
||||
};
|
||||
return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
|
||||
m_diagonal.diagonal().template packet<DiagonalVectorPacketLoadMode>(id));
|
||||
}
|
||||
|
||||
typename MatrixType::Nested m_matrix;
|
||||
typename DiagonalType::Nested m_diagonal;
|
||||
};
|
||||
|
||||
/** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename DiagonalDerived>
|
||||
inline const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
|
||||
inline const Product<Derived, DiagonalDerived, LazyProduct>
|
||||
MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &a_diagonal) const
|
||||
{
|
||||
return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), a_diagonal.derived());
|
||||
return Product<Derived, DiagonalDerived, LazyProduct>(derived(),a_diagonal.derived());
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -99,7 +99,7 @@ EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scala
|
||||
template<typename Derived>
|
||||
inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
|
||||
{
|
||||
using std::sqrt;
|
||||
EIGEN_USING_STD_MATH(sqrt)
|
||||
return sqrt(squaredNorm());
|
||||
}
|
||||
|
||||
@@ -113,8 +113,7 @@ template<typename Derived>
|
||||
inline const typename MatrixBase<Derived>::PlainObject
|
||||
MatrixBase<Derived>::normalized() const
|
||||
{
|
||||
typedef typename internal::nested<Derived>::type Nested;
|
||||
typedef typename internal::remove_reference<Nested>::type _Nested;
|
||||
typedef typename internal::nested_eval<Derived,2>::type _Nested;
|
||||
_Nested n(derived());
|
||||
return n / n.norm();
|
||||
}
|
||||
@@ -142,7 +141,7 @@ struct lpNorm_selector
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline RealScalar run(const MatrixBase<Derived>& m)
|
||||
{
|
||||
using std::pow;
|
||||
EIGEN_USING_STD_MATH(pow)
|
||||
return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p);
|
||||
}
|
||||
};
|
||||
@@ -206,8 +205,8 @@ template<typename OtherDerived>
|
||||
bool MatrixBase<Derived>::isOrthogonal
|
||||
(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());
|
||||
typename internal::nested_eval<Derived,2>::type nested(derived());
|
||||
typename internal::nested_eval<OtherDerived,2>::type otherNested(other.derived());
|
||||
return numext::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
|
||||
}
|
||||
|
||||
@@ -225,13 +224,13 @@ bool MatrixBase<Derived>::isOrthogonal
|
||||
template<typename Derived>
|
||||
bool MatrixBase<Derived>::isUnitary(const RealScalar& prec) const
|
||||
{
|
||||
typename Derived::Nested nested(derived());
|
||||
typename internal::nested_eval<Derived,1>::type self(derived());
|
||||
for(Index i = 0; i < cols(); ++i)
|
||||
{
|
||||
if(!internal::isApprox(nested.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
|
||||
if(!internal::isApprox(self.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
|
||||
return false;
|
||||
for(Index j = 0; j < i; ++j)
|
||||
if(!internal::isMuchSmallerThan(nested.col(i).dot(nested.col(j)), static_cast<Scalar>(1), prec))
|
||||
if(!internal::isMuchSmallerThan(self.col(i).dot(self.col(j)), static_cast<Scalar>(1), prec))
|
||||
return false;
|
||||
}
|
||||
return true;
|
||||
|
||||
@@ -13,7 +13,9 @@
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
/** Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
|
||||
/** \class EigenBase
|
||||
*
|
||||
* Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
|
||||
*
|
||||
* In other words, an EigenBase object is an object that can be copied into a MatrixBase.
|
||||
*
|
||||
@@ -26,9 +28,16 @@ namespace Eigen {
|
||||
template<typename Derived> struct EigenBase
|
||||
{
|
||||
// typedef typename internal::plain_matrix_type<Derived>::type PlainObject;
|
||||
|
||||
/** \brief The interface type of indices
|
||||
* \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
|
||||
* \deprecated Since Eigen 3.3, its usage is deprecated. Use Eigen::Index instead.
|
||||
* \sa StorageIndex, \ref TopicPreprocessorDirectives.
|
||||
*/
|
||||
typedef Eigen::Index Index;
|
||||
|
||||
// FIXME is it needed?
|
||||
typedef typename internal::traits<Derived>::StorageKind StorageKind;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
|
||||
/** \returns a reference to the derived object */
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -121,7 +130,7 @@ template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
|
||||
{
|
||||
other.derived().evalTo(derived());
|
||||
call_assignment(derived(), other.derived());
|
||||
return derived();
|
||||
}
|
||||
|
||||
@@ -129,7 +138,7 @@ template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
|
||||
{
|
||||
other.derived().addTo(derived());
|
||||
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
@@ -137,7 +146,7 @@ template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other)
|
||||
{
|
||||
other.derived().subTo(derived());
|
||||
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
|
||||
@@ -1,140 +0,0 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
|
||||
//
|
||||
// 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_FLAGGED_H
|
||||
#define EIGEN_FLAGGED_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
/** \class Flagged
|
||||
* \ingroup Core_Module
|
||||
*
|
||||
* \brief Expression with modified flags
|
||||
*
|
||||
* \param ExpressionType the type of the object of which we are modifying the flags
|
||||
* \param Added the flags added to the expression
|
||||
* \param Removed the flags removed from the expression (has priority over Added).
|
||||
*
|
||||
* This class represents an expression whose flags have been modified.
|
||||
* It is the return type of MatrixBase::flagged()
|
||||
* and most of the time this is the only way it is used.
|
||||
*
|
||||
* \sa MatrixBase::flagged()
|
||||
*/
|
||||
|
||||
namespace internal {
|
||||
template<typename ExpressionType, unsigned int Added, unsigned int Removed>
|
||||
struct traits<Flagged<ExpressionType, Added, Removed> > : traits<ExpressionType>
|
||||
{
|
||||
enum { Flags = (ExpressionType::Flags | Added) & ~Removed };
|
||||
};
|
||||
}
|
||||
|
||||
template<typename ExpressionType, unsigned int Added, unsigned int Removed> class Flagged
|
||||
: public MatrixBase<Flagged<ExpressionType, Added, Removed> >
|
||||
{
|
||||
public:
|
||||
|
||||
typedef MatrixBase<Flagged> Base;
|
||||
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Flagged)
|
||||
typedef typename internal::conditional<internal::must_nest_by_value<ExpressionType>::ret,
|
||||
ExpressionType, const ExpressionType&>::type ExpressionTypeNested;
|
||||
typedef typename ExpressionType::InnerIterator InnerIterator;
|
||||
|
||||
inline Flagged(const ExpressionType& matrix) : m_matrix(matrix) {}
|
||||
|
||||
inline Index rows() const { return m_matrix.rows(); }
|
||||
inline Index cols() const { return m_matrix.cols(); }
|
||||
inline Index outerStride() const { return m_matrix.outerStride(); }
|
||||
inline Index innerStride() const { return m_matrix.innerStride(); }
|
||||
|
||||
inline CoeffReturnType coeff(Index row, Index col) const
|
||||
{
|
||||
return m_matrix.coeff(row, col);
|
||||
}
|
||||
|
||||
inline CoeffReturnType coeff(Index index) const
|
||||
{
|
||||
return m_matrix.coeff(index);
|
||||
}
|
||||
|
||||
inline const Scalar& coeffRef(Index row, Index col) const
|
||||
{
|
||||
return m_matrix.const_cast_derived().coeffRef(row, col);
|
||||
}
|
||||
|
||||
inline const Scalar& coeffRef(Index index) const
|
||||
{
|
||||
return m_matrix.const_cast_derived().coeffRef(index);
|
||||
}
|
||||
|
||||
inline Scalar& coeffRef(Index row, Index col)
|
||||
{
|
||||
return m_matrix.const_cast_derived().coeffRef(row, col);
|
||||
}
|
||||
|
||||
inline Scalar& coeffRef(Index index)
|
||||
{
|
||||
return m_matrix.const_cast_derived().coeffRef(index);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline const PacketScalar packet(Index row, Index col) const
|
||||
{
|
||||
return m_matrix.template packet<LoadMode>(row, col);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline void writePacket(Index row, Index col, const PacketScalar& x)
|
||||
{
|
||||
m_matrix.const_cast_derived().template writePacket<LoadMode>(row, col, x);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline const PacketScalar packet(Index index) const
|
||||
{
|
||||
return m_matrix.template packet<LoadMode>(index);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline void writePacket(Index index, const PacketScalar& x)
|
||||
{
|
||||
m_matrix.const_cast_derived().template writePacket<LoadMode>(index, x);
|
||||
}
|
||||
|
||||
const ExpressionType& _expression() const { return m_matrix; }
|
||||
|
||||
template<typename OtherDerived>
|
||||
typename ExpressionType::PlainObject solveTriangular(const MatrixBase<OtherDerived>& other) const;
|
||||
|
||||
template<typename OtherDerived>
|
||||
void solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const;
|
||||
|
||||
protected:
|
||||
ExpressionTypeNested m_matrix;
|
||||
};
|
||||
|
||||
/** \returns an expression of *this with added and removed flags
|
||||
*
|
||||
* This is mostly for internal use.
|
||||
*
|
||||
* \sa class Flagged
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<unsigned int Added,unsigned int Removed>
|
||||
inline const Flagged<Derived, Added, Removed>
|
||||
DenseBase<Derived>::flagged() const
|
||||
{
|
||||
return derived();
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_FLAGGED_H
|
||||
@@ -39,29 +39,29 @@ template<typename ExpressionType> class ForceAlignedAccess
|
||||
typedef typename internal::dense_xpr_base<ForceAlignedAccess>::type Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(ForceAlignedAccess)
|
||||
|
||||
inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {}
|
||||
EIGEN_DEVICE_FUNC explicit inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {}
|
||||
|
||||
inline Index rows() const { return m_expression.rows(); }
|
||||
inline Index cols() const { return m_expression.cols(); }
|
||||
inline Index outerStride() const { return m_expression.outerStride(); }
|
||||
inline Index innerStride() const { return m_expression.innerStride(); }
|
||||
EIGEN_DEVICE_FUNC inline Index rows() const { return m_expression.rows(); }
|
||||
EIGEN_DEVICE_FUNC inline Index cols() const { return m_expression.cols(); }
|
||||
EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_expression.outerStride(); }
|
||||
EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_expression.innerStride(); }
|
||||
|
||||
inline const CoeffReturnType coeff(Index row, Index col) const
|
||||
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const
|
||||
{
|
||||
return m_expression.coeff(row, col);
|
||||
}
|
||||
|
||||
inline Scalar& coeffRef(Index row, Index col)
|
||||
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
|
||||
{
|
||||
return m_expression.const_cast_derived().coeffRef(row, col);
|
||||
}
|
||||
|
||||
inline const CoeffReturnType coeff(Index index) const
|
||||
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const
|
||||
{
|
||||
return m_expression.coeff(index);
|
||||
}
|
||||
|
||||
inline Scalar& coeffRef(Index index)
|
||||
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
|
||||
{
|
||||
return m_expression.const_cast_derived().coeffRef(index);
|
||||
}
|
||||
@@ -90,7 +90,7 @@ template<typename ExpressionType> class ForceAlignedAccess
|
||||
m_expression.const_cast_derived().template writePacket<Aligned>(index, x);
|
||||
}
|
||||
|
||||
operator const ExpressionType&() const { return m_expression; }
|
||||
EIGEN_DEVICE_FUNC operator const ExpressionType&() const { return m_expression; }
|
||||
|
||||
protected:
|
||||
const ExpressionType& m_expression;
|
||||
@@ -127,7 +127,7 @@ template<bool Enable>
|
||||
inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type
|
||||
MatrixBase<Derived>::forceAlignedAccessIf() const
|
||||
{
|
||||
return derived();
|
||||
return derived(); // FIXME This should not work but apparently is never used
|
||||
}
|
||||
|
||||
/** \returns an expression of *this with forced aligned access if \a Enable is true.
|
||||
@@ -138,7 +138,7 @@ template<bool Enable>
|
||||
inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type
|
||||
MatrixBase<Derived>::forceAlignedAccessIf()
|
||||
{
|
||||
return derived();
|
||||
return derived(); // FIXME This should not work but apparently is never used
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -22,10 +22,9 @@ struct isApprox_selector
|
||||
EIGEN_DEVICE_FUNC
|
||||
static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
|
||||
{
|
||||
EIGEN_USING_STD_MATH(min);
|
||||
typename internal::nested<Derived,2>::type nested(x);
|
||||
typename internal::nested<OtherDerived,2>::type otherNested(y);
|
||||
return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * (min)(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
|
||||
typename internal::nested_eval<Derived,2>::type nested(x);
|
||||
typename internal::nested_eval<OtherDerived,2>::type otherNested(y);
|
||||
return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * numext::mini(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
@@ -11,29 +11,7 @@
|
||||
#ifndef EIGEN_GENERAL_PRODUCT_H
|
||||
#define EIGEN_GENERAL_PRODUCT_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
/** \class GeneralProduct
|
||||
* \ingroup Core_Module
|
||||
*
|
||||
* \brief Expression of the product of two general matrices or vectors
|
||||
*
|
||||
* \param LhsNested the type used to store the left-hand side
|
||||
* \param RhsNested the type used to store the right-hand side
|
||||
* \param ProductMode the type of the product
|
||||
*
|
||||
* This class represents an expression of the product of two general matrices.
|
||||
* We call a general matrix, a dense matrix with full storage. For instance,
|
||||
* This excludes triangular, selfadjoint, and sparse matrices.
|
||||
* It is the return type of the operator* between general matrices. Its template
|
||||
* arguments are determined automatically by ProductReturnType. Therefore,
|
||||
* GeneralProduct should never be used direclty. To determine the result type of a
|
||||
* function which involves a matrix product, use ProductReturnType::Type.
|
||||
*
|
||||
* \sa ProductReturnType, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
|
||||
*/
|
||||
template<typename Lhs, typename Rhs, int ProductType = internal::product_type<Lhs,Rhs>::value>
|
||||
class GeneralProduct;
|
||||
namespace Eigen {
|
||||
|
||||
enum {
|
||||
Large = 2,
|
||||
@@ -59,14 +37,14 @@ template<typename Lhs, typename Rhs> struct product_type
|
||||
typedef typename remove_all<Lhs>::type _Lhs;
|
||||
typedef typename remove_all<Rhs>::type _Rhs;
|
||||
enum {
|
||||
MaxRows = _Lhs::MaxRowsAtCompileTime,
|
||||
Rows = _Lhs::RowsAtCompileTime,
|
||||
MaxCols = _Rhs::MaxColsAtCompileTime,
|
||||
Cols = _Rhs::ColsAtCompileTime,
|
||||
MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime,
|
||||
_Rhs::MaxRowsAtCompileTime),
|
||||
Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime,
|
||||
_Rhs::RowsAtCompileTime)
|
||||
MaxRows = traits<_Lhs>::MaxRowsAtCompileTime,
|
||||
Rows = traits<_Lhs>::RowsAtCompileTime,
|
||||
MaxCols = traits<_Rhs>::MaxColsAtCompileTime,
|
||||
Cols = traits<_Rhs>::ColsAtCompileTime,
|
||||
MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::MaxColsAtCompileTime,
|
||||
traits<_Rhs>::MaxRowsAtCompileTime),
|
||||
Depth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::ColsAtCompileTime,
|
||||
traits<_Rhs>::RowsAtCompileTime)
|
||||
};
|
||||
|
||||
// the splitting into different lines of code here, introducing the _select enums and the typedef below,
|
||||
@@ -81,7 +59,8 @@ private:
|
||||
|
||||
public:
|
||||
enum {
|
||||
value = selector::ret
|
||||
value = selector::ret,
|
||||
ret = selector::ret
|
||||
};
|
||||
#ifdef EIGEN_DEBUG_PRODUCT
|
||||
static void debug()
|
||||
@@ -97,6 +76,31 @@ public:
|
||||
#endif
|
||||
};
|
||||
|
||||
// template<typename Lhs, typename Rhs> struct product_tag
|
||||
// {
|
||||
// private:
|
||||
//
|
||||
// typedef typename remove_all<Lhs>::type _Lhs;
|
||||
// typedef typename remove_all<Rhs>::type _Rhs;
|
||||
// enum {
|
||||
// Rows = _Lhs::RowsAtCompileTime,
|
||||
// Cols = _Rhs::ColsAtCompileTime,
|
||||
// Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime, _Rhs::RowsAtCompileTime)
|
||||
// };
|
||||
//
|
||||
// enum {
|
||||
// rows_select = Rows==1 ? int(Rows) : int(Large),
|
||||
// cols_select = Cols==1 ? int(Cols) : int(Large),
|
||||
// depth_select = Depth==1 ? int(Depth) : int(Large)
|
||||
// };
|
||||
// typedef product_type_selector<rows_select, cols_select, depth_select> selector;
|
||||
//
|
||||
// public:
|
||||
// enum {
|
||||
// ret = selector::ret
|
||||
// };
|
||||
//
|
||||
// };
|
||||
|
||||
/* The following allows to select the kind of product at compile time
|
||||
* based on the three dimensions of the product.
|
||||
@@ -127,54 +131,6 @@ template<> struct product_type_selector<Large,Large,Small> { enum
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
/** \class ProductReturnType
|
||||
* \ingroup Core_Module
|
||||
*
|
||||
* \brief Helper class to get the correct and optimized returned type of operator*
|
||||
*
|
||||
* \param Lhs the type of the left-hand side
|
||||
* \param Rhs the type of the right-hand side
|
||||
* \param ProductMode the type of the product (determined automatically by internal::product_mode)
|
||||
*
|
||||
* This class defines the typename Type representing the optimized product expression
|
||||
* between two matrix expressions. In practice, using ProductReturnType<Lhs,Rhs>::Type
|
||||
* is the recommended way to define the result type of a function returning an expression
|
||||
* which involve a matrix product. The class Product should never be
|
||||
* used directly.
|
||||
*
|
||||
* \sa class Product, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
|
||||
*/
|
||||
template<typename Lhs, typename Rhs, int ProductType>
|
||||
struct ProductReturnType
|
||||
{
|
||||
// TODO use the nested type to reduce instanciations ????
|
||||
// typedef typename internal::nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
|
||||
// typedef typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
|
||||
|
||||
typedef GeneralProduct<Lhs/*Nested*/, Rhs/*Nested*/, ProductType> Type;
|
||||
};
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
struct ProductReturnType<Lhs,Rhs,CoeffBasedProductMode>
|
||||
{
|
||||
typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
|
||||
typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
|
||||
typedef CoeffBasedProduct<LhsNested, RhsNested, EvalBeforeAssigningBit | EvalBeforeNestingBit> Type;
|
||||
};
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
struct ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
|
||||
{
|
||||
typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
|
||||
typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
|
||||
typedef CoeffBasedProduct<LhsNested, RhsNested, NestByRefBit> Type;
|
||||
};
|
||||
|
||||
// this is a workaround for sun CC
|
||||
template<typename Lhs, typename Rhs>
|
||||
struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
|
||||
{};
|
||||
|
||||
/***********************************************************************
|
||||
* Implementation of Inner Vector Vector Product
|
||||
***********************************************************************/
|
||||
@@ -186,119 +142,10 @@ struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedPr
|
||||
// product ends up to a row-vector times col-vector product... To tackle this use
|
||||
// case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
struct traits<GeneralProduct<Lhs,Rhs,InnerProduct> >
|
||||
: traits<Matrix<typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> >
|
||||
{};
|
||||
|
||||
}
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
class GeneralProduct<Lhs, Rhs, InnerProduct>
|
||||
: internal::no_assignment_operator,
|
||||
public Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1>
|
||||
{
|
||||
typedef Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> Base;
|
||||
public:
|
||||
GeneralProduct(const Lhs& lhs, const Rhs& rhs)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
|
||||
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
|
||||
|
||||
Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
|
||||
}
|
||||
|
||||
/** Convertion to scalar */
|
||||
operator const typename Base::Scalar() const {
|
||||
return Base::coeff(0,0);
|
||||
}
|
||||
};
|
||||
|
||||
/***********************************************************************
|
||||
* Implementation of Outer Vector Vector Product
|
||||
***********************************************************************/
|
||||
|
||||
namespace internal {
|
||||
|
||||
// Column major
|
||||
template<typename ProductType, typename Dest, typename Func>
|
||||
EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const false_type&)
|
||||
{
|
||||
typedef typename Dest::Index Index;
|
||||
// FIXME make sure lhs is sequentially stored
|
||||
// FIXME not very good if rhs is real and lhs complex while alpha is real too
|
||||
const Index cols = dest.cols();
|
||||
for (Index j=0; j<cols; ++j)
|
||||
func(dest.col(j), prod.rhs().coeff(0,j) * prod.lhs());
|
||||
}
|
||||
|
||||
// Row major
|
||||
template<typename ProductType, typename Dest, typename Func>
|
||||
EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const true_type&) {
|
||||
typedef typename Dest::Index Index;
|
||||
// FIXME make sure rhs is sequentially stored
|
||||
// FIXME not very good if lhs is real and rhs complex while alpha is real too
|
||||
const Index rows = dest.rows();
|
||||
for (Index i=0; i<rows; ++i)
|
||||
func(dest.row(i), prod.lhs().coeff(i,0) * prod.rhs());
|
||||
}
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
|
||||
: traits<ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> >
|
||||
{};
|
||||
|
||||
}
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
class GeneralProduct<Lhs, Rhs, OuterProduct>
|
||||
: public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
|
||||
{
|
||||
template<typename T> struct IsRowMajor : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
|
||||
|
||||
public:
|
||||
EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
|
||||
|
||||
GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
|
||||
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
|
||||
}
|
||||
|
||||
struct set { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() = src; } };
|
||||
struct add { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } };
|
||||
struct sub { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() -= src; } };
|
||||
struct adds {
|
||||
Scalar m_scale;
|
||||
adds(const Scalar& s) : m_scale(s) {}
|
||||
template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const {
|
||||
dst.const_cast_derived() += m_scale * src;
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Dest>
|
||||
inline void evalTo(Dest& dest) const {
|
||||
internal::outer_product_selector_run(*this, dest, set(), IsRowMajor<Dest>());
|
||||
}
|
||||
|
||||
template<typename Dest>
|
||||
inline void addTo(Dest& dest) const {
|
||||
internal::outer_product_selector_run(*this, dest, add(), IsRowMajor<Dest>());
|
||||
}
|
||||
|
||||
template<typename Dest>
|
||||
inline void subTo(Dest& dest) const {
|
||||
internal::outer_product_selector_run(*this, dest, sub(), IsRowMajor<Dest>());
|
||||
}
|
||||
|
||||
template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
|
||||
{
|
||||
internal::outer_product_selector_run(*this, dest, adds(alpha), IsRowMajor<Dest>());
|
||||
}
|
||||
};
|
||||
|
||||
/***********************************************************************
|
||||
* Implementation of General Matrix Vector Product
|
||||
***********************************************************************/
|
||||
@@ -312,60 +159,13 @@ class GeneralProduct<Lhs, Rhs, OuterProduct>
|
||||
*/
|
||||
namespace internal {
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
struct traits<GeneralProduct<Lhs,Rhs,GemvProduct> >
|
||||
: traits<ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs> >
|
||||
{};
|
||||
|
||||
template<int Side, int StorageOrder, bool BlasCompatible>
|
||||
struct gemv_selector;
|
||||
struct gemv_dense_sense_selector;
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
class GeneralProduct<Lhs, Rhs, GemvProduct>
|
||||
: public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
|
||||
{
|
||||
public:
|
||||
EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
|
||||
|
||||
typedef typename Lhs::Scalar LhsScalar;
|
||||
typedef typename Rhs::Scalar RhsScalar;
|
||||
|
||||
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)
|
||||
}
|
||||
|
||||
enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
|
||||
typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
|
||||
|
||||
template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
|
||||
{
|
||||
eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
|
||||
internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
|
||||
bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
|
||||
}
|
||||
};
|
||||
|
||||
namespace internal {
|
||||
|
||||
// The vector is on the left => transposition
|
||||
template<int StorageOrder, bool BlasCompatible>
|
||||
struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
|
||||
{
|
||||
template<typename ProductType, typename Dest>
|
||||
static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
|
||||
{
|
||||
Transpose<Dest> destT(dest);
|
||||
enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
|
||||
gemv_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
|
||||
::run(GeneralProduct<Transpose<const typename ProductType::_RhsNested>,Transpose<const typename ProductType::_LhsNested>, GemvProduct>
|
||||
(prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
|
||||
|
||||
template<typename Scalar,int Size,int MaxSize>
|
||||
@@ -383,7 +183,7 @@ struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
|
||||
template<typename Scalar,int Size,int MaxSize>
|
||||
struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
|
||||
{
|
||||
#if EIGEN_ALIGN_STATICALLY
|
||||
#if EIGEN_MAX_STATIC_ALIGN_BYTES!=0
|
||||
internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
|
||||
EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
|
||||
#else
|
||||
@@ -396,33 +196,48 @@ struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
|
||||
internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?PacketSize:0),0> m_data;
|
||||
EIGEN_STRONG_INLINE Scalar* data() {
|
||||
return ForceAlignment
|
||||
? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(EIGEN_ALIGN_BYTES-1))) + EIGEN_ALIGN_BYTES)
|
||||
? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(EIGEN_MAX_ALIGN_BYTES-1))) + EIGEN_MAX_ALIGN_BYTES)
|
||||
: m_data.array;
|
||||
}
|
||||
#endif
|
||||
};
|
||||
|
||||
template<> struct gemv_selector<OnTheRight,ColMajor,true>
|
||||
// The vector is on the left => transposition
|
||||
template<int StorageOrder, bool BlasCompatible>
|
||||
struct gemv_dense_sense_selector<OnTheLeft,StorageOrder,BlasCompatible>
|
||||
{
|
||||
template<typename ProductType, typename Dest>
|
||||
static inline void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
|
||||
template<typename Lhs, typename Rhs, typename Dest>
|
||||
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
|
||||
{
|
||||
typedef typename ProductType::Index Index;
|
||||
typedef typename ProductType::LhsScalar LhsScalar;
|
||||
typedef typename ProductType::RhsScalar RhsScalar;
|
||||
typedef typename ProductType::Scalar ResScalar;
|
||||
typedef typename ProductType::RealScalar RealScalar;
|
||||
typedef typename ProductType::ActualLhsType ActualLhsType;
|
||||
typedef typename ProductType::ActualRhsType ActualRhsType;
|
||||
typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
|
||||
typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
|
||||
Transpose<Dest> destT(dest);
|
||||
enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
|
||||
gemv_dense_sense_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
|
||||
::run(rhs.transpose(), lhs.transpose(), destT, alpha);
|
||||
}
|
||||
};
|
||||
|
||||
template<> struct gemv_dense_sense_selector<OnTheRight,ColMajor,true>
|
||||
{
|
||||
template<typename Lhs, typename Rhs, typename Dest>
|
||||
static inline void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
|
||||
{
|
||||
typedef typename Lhs::Scalar LhsScalar;
|
||||
typedef typename Rhs::Scalar RhsScalar;
|
||||
typedef typename Dest::Scalar ResScalar;
|
||||
typedef typename Dest::RealScalar RealScalar;
|
||||
|
||||
typedef internal::blas_traits<Lhs> LhsBlasTraits;
|
||||
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
|
||||
typedef internal::blas_traits<Rhs> RhsBlasTraits;
|
||||
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
|
||||
|
||||
typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
|
||||
|
||||
ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
|
||||
ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
|
||||
ActualLhsType actualLhs = LhsBlasTraits::extract(lhs);
|
||||
ActualRhsType actualRhs = RhsBlasTraits::extract(rhs);
|
||||
|
||||
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
|
||||
* RhsBlasTraits::extractScalarFactor(prod.rhs());
|
||||
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
|
||||
* RhsBlasTraits::extractScalarFactor(rhs);
|
||||
|
||||
enum {
|
||||
// FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
|
||||
@@ -434,14 +249,14 @@ template<> struct gemv_selector<OnTheRight,ColMajor,true>
|
||||
|
||||
gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
|
||||
|
||||
bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
|
||||
bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
|
||||
|
||||
const bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
|
||||
const bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
|
||||
|
||||
RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
|
||||
|
||||
ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
|
||||
evalToDest ? dest.data() : static_dest.data());
|
||||
|
||||
|
||||
if(!evalToDest)
|
||||
{
|
||||
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
|
||||
@@ -457,11 +272,13 @@ template<> struct gemv_selector<OnTheRight,ColMajor,true>
|
||||
MappedDest(actualDestPtr, dest.size()) = dest;
|
||||
}
|
||||
|
||||
typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper;
|
||||
typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper;
|
||||
general_matrix_vector_product
|
||||
<Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
|
||||
<Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
|
||||
actualLhs.rows(), actualLhs.cols(),
|
||||
actualLhs.data(), actualLhs.outerStride(),
|
||||
actualRhs.data(), actualRhs.innerStride(),
|
||||
LhsMapper(actualLhs.data(), actualLhs.outerStride()),
|
||||
RhsMapper(actualRhs.data(), actualRhs.innerStride()),
|
||||
actualDestPtr, 1,
|
||||
compatibleAlpha);
|
||||
|
||||
@@ -475,34 +292,34 @@ template<> struct gemv_selector<OnTheRight,ColMajor,true>
|
||||
}
|
||||
};
|
||||
|
||||
template<> struct gemv_selector<OnTheRight,RowMajor,true>
|
||||
template<> struct gemv_dense_sense_selector<OnTheRight,RowMajor,true>
|
||||
{
|
||||
template<typename ProductType, typename Dest>
|
||||
static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
|
||||
template<typename Lhs, typename Rhs, typename Dest>
|
||||
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
|
||||
{
|
||||
typedef typename ProductType::LhsScalar LhsScalar;
|
||||
typedef typename ProductType::RhsScalar RhsScalar;
|
||||
typedef typename ProductType::Scalar ResScalar;
|
||||
typedef typename ProductType::Index Index;
|
||||
typedef typename ProductType::ActualLhsType ActualLhsType;
|
||||
typedef typename ProductType::ActualRhsType ActualRhsType;
|
||||
typedef typename ProductType::_ActualRhsType _ActualRhsType;
|
||||
typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
|
||||
typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
|
||||
typedef typename Lhs::Scalar LhsScalar;
|
||||
typedef typename Rhs::Scalar RhsScalar;
|
||||
typedef typename Dest::Scalar ResScalar;
|
||||
|
||||
typedef internal::blas_traits<Lhs> LhsBlasTraits;
|
||||
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
|
||||
typedef internal::blas_traits<Rhs> RhsBlasTraits;
|
||||
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
|
||||
typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
|
||||
|
||||
typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
|
||||
typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
|
||||
typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
|
||||
typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
|
||||
|
||||
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
|
||||
* RhsBlasTraits::extractScalarFactor(prod.rhs());
|
||||
ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
|
||||
* RhsBlasTraits::extractScalarFactor(rhs);
|
||||
|
||||
enum {
|
||||
// FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
|
||||
// on, the other hand it is good for the cache to pack the vector anyways...
|
||||
DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
|
||||
DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime==1
|
||||
};
|
||||
|
||||
gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
|
||||
gemv_static_vector_if<RhsScalar,ActualRhsTypeCleaned::SizeAtCompileTime,ActualRhsTypeCleaned::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
|
||||
|
||||
ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
|
||||
DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
|
||||
@@ -513,42 +330,42 @@ template<> struct gemv_selector<OnTheRight,RowMajor,true>
|
||||
Index size = actualRhs.size();
|
||||
EIGEN_DENSE_STORAGE_CTOR_PLUGIN
|
||||
#endif
|
||||
Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
|
||||
Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
|
||||
}
|
||||
|
||||
typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper;
|
||||
typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper;
|
||||
general_matrix_vector_product
|
||||
<Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
|
||||
<Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
|
||||
actualLhs.rows(), actualLhs.cols(),
|
||||
actualLhs.data(), actualLhs.outerStride(),
|
||||
actualRhsPtr, 1,
|
||||
LhsMapper(actualLhs.data(), actualLhs.outerStride()),
|
||||
RhsMapper(actualRhsPtr, 1),
|
||||
dest.data(), dest.innerStride(),
|
||||
actualAlpha);
|
||||
}
|
||||
};
|
||||
|
||||
template<> struct gemv_selector<OnTheRight,ColMajor,false>
|
||||
template<> struct gemv_dense_sense_selector<OnTheRight,ColMajor,false>
|
||||
{
|
||||
template<typename ProductType, typename Dest>
|
||||
static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
|
||||
template<typename Lhs, typename Rhs, typename Dest>
|
||||
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
|
||||
{
|
||||
typedef typename Dest::Index Index;
|
||||
// TODO makes sure dest is sequentially stored in memory, otherwise use a temp
|
||||
const Index size = prod.rhs().rows();
|
||||
const Index size = rhs.rows();
|
||||
for(Index k=0; k<size; ++k)
|
||||
dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
|
||||
dest += (alpha*rhs.coeff(k)) * lhs.col(k);
|
||||
}
|
||||
};
|
||||
|
||||
template<> struct gemv_selector<OnTheRight,RowMajor,false>
|
||||
template<> struct gemv_dense_sense_selector<OnTheRight,RowMajor,false>
|
||||
{
|
||||
template<typename ProductType, typename Dest>
|
||||
static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
|
||||
template<typename Lhs, typename Rhs, typename Dest>
|
||||
static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
|
||||
{
|
||||
typedef typename Dest::Index Index;
|
||||
// TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
|
||||
const Index rows = prod.rows();
|
||||
const Index rows = dest.rows();
|
||||
for(Index i=0; i<rows; ++i)
|
||||
dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
|
||||
dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(rhs.transpose())).sum();
|
||||
}
|
||||
};
|
||||
|
||||
@@ -566,7 +383,6 @@ template<> struct gemv_selector<OnTheRight,RowMajor,false>
|
||||
*/
|
||||
#ifndef __CUDACC__
|
||||
|
||||
#ifdef EIGEN_TEST_EVALUATORS
|
||||
template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
inline const Product<Derived, OtherDerived>
|
||||
@@ -594,42 +410,12 @@ MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
|
||||
#ifdef EIGEN_DEBUG_PRODUCT
|
||||
internal::product_type<Derived,OtherDerived>::debug();
|
||||
#endif
|
||||
|
||||
|
||||
return Product<Derived, OtherDerived>(derived(), other.derived());
|
||||
}
|
||||
#else
|
||||
template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
inline const typename ProductReturnType<Derived, OtherDerived>::Type
|
||||
MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
|
||||
{
|
||||
// A note regarding the function declaration: In MSVC, this function will sometimes
|
||||
// not be inlined since DenseStorage is an unwindable object for dynamic
|
||||
// matrices and product types are holding a member to store the result.
|
||||
// Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
|
||||
enum {
|
||||
ProductIsValid = Derived::ColsAtCompileTime==Dynamic
|
||||
|| OtherDerived::RowsAtCompileTime==Dynamic
|
||||
|| int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
|
||||
AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
|
||||
SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
|
||||
};
|
||||
// note to the lost user:
|
||||
// * for a dot product use: v1.dot(v2)
|
||||
// * for a coeff-wise product use: v1.cwiseProduct(v2)
|
||||
EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
|
||||
INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
|
||||
EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
|
||||
INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
|
||||
EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
|
||||
#ifdef EIGEN_DEBUG_PRODUCT
|
||||
internal::product_type<Derived,OtherDerived>::debug();
|
||||
#endif
|
||||
return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
|
||||
}
|
||||
#endif
|
||||
|
||||
#endif
|
||||
#endif // __CUDACC__
|
||||
|
||||
/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
|
||||
*
|
||||
* The returned product will behave like any other expressions: the coefficients of the product will be
|
||||
@@ -643,7 +429,7 @@ MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
const typename LazyProductReturnType<Derived,OtherDerived>::Type
|
||||
const Product<Derived,OtherDerived,LazyProduct>
|
||||
MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
|
||||
{
|
||||
enum {
|
||||
@@ -662,7 +448,7 @@ MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
|
||||
INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
|
||||
EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
|
||||
|
||||
return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
|
||||
return Product<Derived,OtherDerived,LazyProduct>(derived(), other.derived());
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -49,16 +49,20 @@ struct default_packet_traits
|
||||
HasMul = 1,
|
||||
HasNegate = 1,
|
||||
HasAbs = 1,
|
||||
HasArg = 0,
|
||||
HasAbs2 = 1,
|
||||
HasMin = 1,
|
||||
HasMax = 1,
|
||||
HasConj = 1,
|
||||
HasSetLinear = 1,
|
||||
HasBlend = 0,
|
||||
|
||||
HasDiv = 0,
|
||||
HasSqrt = 0,
|
||||
HasRsqrt = 0,
|
||||
HasExp = 0,
|
||||
HasLog = 0,
|
||||
HasLog10 = 0,
|
||||
HasPow = 0,
|
||||
|
||||
HasSin = 0,
|
||||
@@ -66,7 +70,14 @@ struct default_packet_traits
|
||||
HasTan = 0,
|
||||
HasASin = 0,
|
||||
HasACos = 0,
|
||||
HasATan = 0
|
||||
HasATan = 0,
|
||||
HasSinh = 0,
|
||||
HasCosh = 0,
|
||||
HasTanh = 0,
|
||||
|
||||
HasRound = 0,
|
||||
HasFloor = 0,
|
||||
HasCeil = 0
|
||||
};
|
||||
};
|
||||
|
||||
@@ -94,6 +105,30 @@ template<typename T> struct packet_traits : default_packet_traits
|
||||
};
|
||||
};
|
||||
|
||||
template<typename T> struct packet_traits<const T> : packet_traits<T> { };
|
||||
|
||||
template <typename Src, typename Tgt> struct type_casting_traits {
|
||||
enum {
|
||||
VectorizedCast = 0,
|
||||
SrcCoeffRatio = 1,
|
||||
TgtCoeffRatio = 1
|
||||
};
|
||||
};
|
||||
|
||||
|
||||
/** \internal \returns static_cast<TgtType>(a) (coeff-wise) */
|
||||
template <typename SrcPacket, typename TgtPacket>
|
||||
EIGEN_DEVICE_FUNC inline TgtPacket
|
||||
pcast(const SrcPacket& a) {
|
||||
return static_cast<TgtPacket>(a);
|
||||
}
|
||||
template <typename SrcPacket, typename TgtPacket>
|
||||
EIGEN_DEVICE_FUNC inline TgtPacket
|
||||
pcast(const SrcPacket& a, const SrcPacket& /*b*/) {
|
||||
return static_cast<TgtPacket>(a);
|
||||
}
|
||||
|
||||
|
||||
/** \internal \returns a + b (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
|
||||
padd(const Packet& a,
|
||||
@@ -126,17 +161,21 @@ pdiv(const Packet& a,
|
||||
/** \internal \returns the min of \a a and \a b (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
|
||||
pmin(const Packet& a,
|
||||
const Packet& b) { EIGEN_USING_STD_MATH(min); return (min)(a, b); }
|
||||
const Packet& b) { return numext::mini(a, b); }
|
||||
|
||||
/** \internal \returns the max of \a a and \a b (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
|
||||
pmax(const Packet& a,
|
||||
const Packet& b) { EIGEN_USING_STD_MATH(max); return (max)(a, b); }
|
||||
const Packet& b) { return numext::maxi(a, b); }
|
||||
|
||||
/** \internal \returns the absolute value of \a a */
|
||||
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
|
||||
pabs(const Packet& a) { using std::abs; return abs(a); }
|
||||
|
||||
/** \internal \returns the phase angle of \a a */
|
||||
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
|
||||
parg(const Packet& a) { using numext::arg; return arg(a); }
|
||||
|
||||
/** \internal \returns the bitwise and of \a a and \a b */
|
||||
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
|
||||
pand(const Packet& a, const Packet& b) { return a & b; }
|
||||
@@ -222,8 +261,8 @@ inline void pbroadcast2(const typename unpacket_traits<Packet>::type *a,
|
||||
}
|
||||
|
||||
/** \internal \brief Returns a packet with coefficients (a,a+1,...,a+packet_size-1). */
|
||||
template<typename Scalar> inline typename packet_traits<Scalar>::type
|
||||
plset(const Scalar& a) { return a; }
|
||||
template<typename Packet> inline Packet
|
||||
plset(const typename unpacket_traits<Packet>::type& a) { return a; }
|
||||
|
||||
/** \internal copy the packet \a from to \a *to, \a to must be 16 bytes aligned */
|
||||
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstore(Scalar* to, const Packet& from)
|
||||
@@ -233,17 +272,25 @@ template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstore(
|
||||
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstoreu(Scalar* to, const Packet& from)
|
||||
{ (*to) = from; }
|
||||
|
||||
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline Packet pgather(const Scalar* from, DenseIndex /*stride*/)
|
||||
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline Packet pgather(const Scalar* from, Index /*stride*/)
|
||||
{ return ploadu<Packet>(from); }
|
||||
|
||||
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pscatter(Scalar* to, const Packet& from, DenseIndex /*stride*/)
|
||||
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pscatter(Scalar* to, const Packet& from, Index /*stride*/)
|
||||
{ pstore(to, from); }
|
||||
|
||||
/** \internal tries to do cache prefetching of \a addr */
|
||||
template<typename Scalar> inline void prefetch(const Scalar* addr)
|
||||
{
|
||||
#if !defined(_MSC_VER)
|
||||
__builtin_prefetch(addr);
|
||||
#ifdef __CUDA_ARCH__
|
||||
#if defined(__LP64__)
|
||||
// 64-bit pointer operand constraint for inlined asm
|
||||
asm(" prefetch.L1 [ %1 ];" : "=l"(addr) : "l"(addr));
|
||||
#else
|
||||
// 32-bit pointer operand constraint for inlined asm
|
||||
asm(" prefetch.L1 [ %1 ];" : "=r"(addr) : "r"(addr));
|
||||
#endif
|
||||
#elif !EIGEN_COMP_MSVC
|
||||
__builtin_prefetch(addr);
|
||||
#endif
|
||||
}
|
||||
|
||||
@@ -284,6 +331,21 @@ template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Pack
|
||||
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet preverse(const Packet& a)
|
||||
{ return a; }
|
||||
|
||||
template<size_t offset, typename Packet>
|
||||
struct protate_impl
|
||||
{
|
||||
// Empty so attempts to use this unimplemented path will fail to compile.
|
||||
// Only specializations of this template should be used.
|
||||
};
|
||||
|
||||
/** \internal \returns a packet with the coefficients rotated to the right in little-endian convention,
|
||||
* by the given offset, e.g. for offset == 1:
|
||||
* (packet[3], packet[2], packet[1], packet[0]) becomes (packet[0], packet[3], packet[2], packet[1])
|
||||
*/
|
||||
template<size_t offset, typename Packet> EIGEN_DEVICE_FUNC inline Packet protate(const Packet& a)
|
||||
{
|
||||
return offset ? protate_impl<offset, Packet>::run(a) : a;
|
||||
}
|
||||
|
||||
/** \internal \returns \a a with real and imaginary part flipped (for complex type only) */
|
||||
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet pcplxflip(const Packet& a)
|
||||
@@ -318,10 +380,22 @@ Packet pasin(const Packet& a) { using std::asin; return asin(a); }
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet pacos(const Packet& a) { using std::acos; return acos(a); }
|
||||
|
||||
/** \internal \returns the atan of \a a (coeff-wise) */
|
||||
/** \internal \returns the arc tangent of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet patan(const Packet& a) { using std::atan; return atan(a); }
|
||||
|
||||
/** \internal \returns the hyperbolic sine of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet psinh(const Packet& a) { using std::sinh; return sinh(a); }
|
||||
|
||||
/** \internal \returns the hyperbolic cosine of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet pcosh(const Packet& a) { using std::cosh; return cosh(a); }
|
||||
|
||||
/** \internal \returns the hyperbolic tan of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet ptanh(const Packet& a) { using std::tanh; return tanh(a); }
|
||||
|
||||
/** \internal \returns the exp of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet pexp(const Packet& a) { using std::exp; return exp(a); }
|
||||
@@ -330,10 +404,32 @@ Packet pexp(const Packet& a) { using std::exp; return exp(a); }
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet plog(const Packet& a) { using std::log; return log(a); }
|
||||
|
||||
/** \internal \returns the log10 of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet plog10(const Packet& a) { using std::log10; return log10(a); }
|
||||
|
||||
/** \internal \returns the square-root of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet psqrt(const Packet& a) { using std::sqrt; return sqrt(a); }
|
||||
|
||||
/** \internal \returns the reciprocal square-root of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet prsqrt(const Packet& a) {
|
||||
return pdiv(pset1<Packet>(1), psqrt(a));
|
||||
}
|
||||
|
||||
/** \internal \returns the rounded value of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet pround(const Packet& a) { using numext::round; return round(a); }
|
||||
|
||||
/** \internal \returns the floor of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet pfloor(const Packet& a) { using numext::floor; return floor(a); }
|
||||
|
||||
/** \internal \returns the ceil of \a a (coeff-wise) */
|
||||
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
|
||||
Packet pceil(const Packet& a) { using numext::ceil; return ceil(a); }
|
||||
|
||||
/***************************************************************************
|
||||
* The following functions might not have to be overwritten for vectorized types
|
||||
***************************************************************************/
|
||||
@@ -354,27 +450,38 @@ pmadd(const Packet& a,
|
||||
{ return padd(pmul(a, b),c); }
|
||||
|
||||
/** \internal \returns a packet version of \a *from.
|
||||
* If LoadMode equals #Aligned, \a from must be 16 bytes aligned */
|
||||
template<typename Packet, int LoadMode>
|
||||
inline Packet ploadt(const typename unpacket_traits<Packet>::type* from)
|
||||
* The pointer \a from must be aligned on a \a Alignment bytes boundary. */
|
||||
template<typename Packet, int Alignment>
|
||||
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt(const typename unpacket_traits<Packet>::type* from)
|
||||
{
|
||||
if(LoadMode == Aligned)
|
||||
if(Alignment >= unpacket_traits<Packet>::alignment)
|
||||
return pload<Packet>(from);
|
||||
else
|
||||
return ploadu<Packet>(from);
|
||||
}
|
||||
|
||||
/** \internal copy the packet \a from to \a *to.
|
||||
* If StoreMode equals #Aligned, \a to must be 16 bytes aligned */
|
||||
template<typename Scalar, typename Packet, int LoadMode>
|
||||
inline void pstoret(Scalar* to, const Packet& from)
|
||||
* The pointer \a from must be aligned on a \a Alignment bytes boundary. */
|
||||
template<typename Scalar, typename Packet, int Alignment>
|
||||
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret(Scalar* to, const Packet& from)
|
||||
{
|
||||
if(LoadMode == Aligned)
|
||||
if(Alignment >= unpacket_traits<Packet>::alignment)
|
||||
pstore(to, from);
|
||||
else
|
||||
pstoreu(to, from);
|
||||
}
|
||||
|
||||
/** \internal \returns a packet version of \a *from.
|
||||
* Unlike ploadt, ploadt_ro takes advantage of the read-only memory path on the
|
||||
* hardware if available to speedup the loading of data that won't be modified
|
||||
* by the current computation.
|
||||
*/
|
||||
template<typename Packet, int LoadMode>
|
||||
inline Packet ploadt_ro(const typename unpacket_traits<Packet>::type* from)
|
||||
{
|
||||
return ploadt<Packet, LoadMode>(from);
|
||||
}
|
||||
|
||||
/** \internal default implementation of palign() allowing partial specialization */
|
||||
template<int Offset,typename PacketType>
|
||||
struct palign_impl
|
||||
@@ -433,6 +540,19 @@ ptranspose(PacketBlock<Packet,1>& /*kernel*/) {
|
||||
// Nothing to do in the scalar case, i.e. a 1x1 matrix.
|
||||
}
|
||||
|
||||
/***************************************************************************
|
||||
* Selector, i.e. vector of N boolean values used to select (i.e. blend)
|
||||
* words from 2 packets.
|
||||
***************************************************************************/
|
||||
template <size_t N> struct Selector {
|
||||
bool select[N];
|
||||
};
|
||||
|
||||
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
|
||||
pblend(const Selector<unpacket_traits<Packet>::size>& ifPacket, const Packet& thenPacket, const Packet& elsePacket) {
|
||||
return ifPacket.select[0] ? thenPacket : elsePacket;
|
||||
}
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -14,8 +14,8 @@
|
||||
#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME,FUNCTOR) \
|
||||
template<typename Derived> \
|
||||
inline const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> \
|
||||
NAME(const Eigen::ArrayBase<Derived>& x) { \
|
||||
return x.derived(); \
|
||||
(NAME)(const Eigen::ArrayBase<Derived>& x) { \
|
||||
return Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived>(x.derived()); \
|
||||
}
|
||||
|
||||
#define EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(NAME,FUNCTOR) \
|
||||
@@ -30,26 +30,40 @@
|
||||
{ \
|
||||
static inline typename NAME##_retval<ArrayBase<Derived> >::type run(const Eigen::ArrayBase<Derived>& x) \
|
||||
{ \
|
||||
return x.derived(); \
|
||||
return typename NAME##_retval<ArrayBase<Derived> >::type(x.derived()); \
|
||||
} \
|
||||
};
|
||||
|
||||
|
||||
namespace Eigen
|
||||
{
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(real,scalar_real_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(imag,scalar_imag_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(conj,scalar_conjugate_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(inverse,scalar_inverse_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sin,scalar_sin_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cos,scalar_cos_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin,scalar_asin_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos,scalar_acos_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tan,scalar_tan_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(atan,scalar_atan_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin,scalar_asin_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos,scalar_acos_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sinh,scalar_sinh_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cosh,scalar_cosh_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tanh,scalar_tanh_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp,scalar_exp_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log,scalar_log_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log10,scalar_log10_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs,scalar_abs_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs2,scalar_abs2_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(arg,scalar_arg_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sqrt,scalar_sqrt_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(square,scalar_square_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cube,scalar_cube_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(round,scalar_round_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(floor,scalar_floor_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(ceil,scalar_ceil_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isnan,scalar_isnan_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isinf,scalar_isinf_op)
|
||||
EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isfinite,scalar_isfinite_op)
|
||||
|
||||
template<typename Derived>
|
||||
inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar>, const Derived>
|
||||
@@ -57,16 +71,46 @@ namespace Eigen
|
||||
return x.derived().pow(exponent);
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const Derived, const Derived>
|
||||
pow(const Eigen::ArrayBase<Derived>& x, const Eigen::ArrayBase<Derived>& exponents)
|
||||
/** \returns an expression of the coefficient-wise power of \a x to the given array of \a exponents.
|
||||
*
|
||||
* This function computes the coefficient-wise power.
|
||||
*
|
||||
* Example: \include Cwise_array_power_array.cpp
|
||||
* Output: \verbinclude Cwise_array_power_array.out
|
||||
*
|
||||
* \sa ArrayBase::pow()
|
||||
*/
|
||||
template<typename Derived,typename ExponentDerived>
|
||||
inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename ExponentDerived::Scalar>, const Derived, const ExponentDerived>
|
||||
pow(const Eigen::ArrayBase<Derived>& x, const Eigen::ArrayBase<ExponentDerived>& exponents)
|
||||
{
|
||||
return Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const Derived, const Derived>(
|
||||
return Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename ExponentDerived::Scalar>, const Derived, const ExponentDerived>(
|
||||
x.derived(),
|
||||
exponents.derived()
|
||||
);
|
||||
}
|
||||
|
||||
/** \returns an expression of the coefficient-wise power of the scalar \a x to the given array of \a exponents.
|
||||
*
|
||||
* This function computes the coefficient-wise power between a scalar and an array of exponents.
|
||||
* Beaware that the scalar type of the input scalar \a x and the exponents \a exponents must be the same.
|
||||
*
|
||||
* Example: \include Cwise_scalar_power_array.cpp
|
||||
* Output: \verbinclude Cwise_scalar_power_array.out
|
||||
*
|
||||
* \sa ArrayBase::pow()
|
||||
*/
|
||||
template<typename Derived>
|
||||
inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const typename Derived::ConstantReturnType, const Derived>
|
||||
pow(const typename Derived::Scalar& x, const Eigen::ArrayBase<Derived>& exponents)
|
||||
{
|
||||
typename Derived::ConstantReturnType constant_x(exponents.rows(), exponents.cols(), x);
|
||||
return Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const typename Derived::ConstantReturnType, const Derived>(
|
||||
constant_x,
|
||||
exponents.derived()
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* \brief Component-wise division of a scalar by array elements.
|
||||
**/
|
||||
|
||||
@@ -164,7 +164,6 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat&
|
||||
|
||||
typename Derived::Nested m = _m;
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
typedef typename Derived::Index Index;
|
||||
|
||||
Index width = 0;
|
||||
|
||||
|
||||
126
Eigen/src/Core/Inverse.h
Normal file
126
Eigen/src/Core/Inverse.h
Normal file
@@ -0,0 +1,126 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2014 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_INVERSE_H
|
||||
#define EIGEN_INVERSE_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
// TODO move the general declaration in Core, and rename this file DenseInverseImpl.h, or something like this...
|
||||
|
||||
template<typename XprType,typename StorageKind> class InverseImpl;
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename XprType>
|
||||
struct traits<Inverse<XprType> >
|
||||
: traits<typename XprType::PlainObject>
|
||||
{
|
||||
typedef typename XprType::PlainObject PlainObject;
|
||||
typedef traits<PlainObject> BaseTraits;
|
||||
enum {
|
||||
Flags = BaseTraits::Flags & RowMajorBit
|
||||
};
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
/** \class Inverse
|
||||
*
|
||||
* \brief Expression of the inverse of another expression
|
||||
*
|
||||
* \tparam XprType the type of the expression we are taking the inverse
|
||||
*
|
||||
* This class represents an abstract expression of A.inverse()
|
||||
* and most of the time this is the only way it is used.
|
||||
*
|
||||
*/
|
||||
template<typename XprType>
|
||||
class Inverse : public InverseImpl<XprType,typename internal::traits<XprType>::StorageKind>
|
||||
{
|
||||
public:
|
||||
typedef typename XprType::StorageIndex StorageIndex;
|
||||
typedef typename XprType::PlainObject PlainObject;
|
||||
typedef typename internal::ref_selector<XprType>::type XprTypeNested;
|
||||
typedef typename internal::remove_all<XprTypeNested>::type XprTypeNestedCleaned;
|
||||
|
||||
explicit Inverse(const XprType &xpr)
|
||||
: m_xpr(xpr)
|
||||
{}
|
||||
|
||||
EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
|
||||
EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
|
||||
|
||||
EIGEN_DEVICE_FUNC const XprTypeNestedCleaned& nestedExpression() const { return m_xpr; }
|
||||
|
||||
protected:
|
||||
XprTypeNested m_xpr;
|
||||
};
|
||||
|
||||
/** \internal
|
||||
* Specialization of the Inverse expression for dense expressions.
|
||||
* Direct access to the coefficients are discared.
|
||||
* FIXME this intermediate class is probably not needed anymore.
|
||||
*/
|
||||
template<typename XprType>
|
||||
class InverseImpl<XprType,Dense>
|
||||
: public MatrixBase<Inverse<XprType> >
|
||||
{
|
||||
typedef Inverse<XprType> Derived;
|
||||
|
||||
public:
|
||||
|
||||
typedef MatrixBase<Derived> Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
|
||||
typedef typename internal::remove_all<XprType>::type NestedExpression;
|
||||
|
||||
private:
|
||||
|
||||
Scalar coeff(Index row, Index col) const;
|
||||
Scalar coeff(Index i) const;
|
||||
};
|
||||
|
||||
namespace internal {
|
||||
|
||||
/** \internal
|
||||
* \brief Default evaluator for Inverse expression.
|
||||
*
|
||||
* This default evaluator for Inverse expression simply evaluate the inverse into a temporary
|
||||
* by a call to internal::call_assignment_no_alias.
|
||||
* Therefore, inverse implementers only have to specialize Assignment<Dst,Inverse<...>, ...> for
|
||||
* there own nested expression.
|
||||
*
|
||||
* \sa class Inverse
|
||||
*/
|
||||
template<typename ArgType>
|
||||
struct unary_evaluator<Inverse<ArgType> >
|
||||
: public evaluator<typename Inverse<ArgType>::PlainObject>
|
||||
{
|
||||
typedef Inverse<ArgType> InverseType;
|
||||
typedef typename InverseType::PlainObject PlainObject;
|
||||
typedef evaluator<PlainObject> Base;
|
||||
|
||||
enum { Flags = Base::Flags | EvalBeforeNestingBit };
|
||||
|
||||
unary_evaluator(const InverseType& inv_xpr)
|
||||
: m_result(inv_xpr.rows(), inv_xpr.cols())
|
||||
{
|
||||
::new (static_cast<Base*>(this)) Base(m_result);
|
||||
internal::call_assignment_no_alias(m_result, inv_xpr);
|
||||
}
|
||||
|
||||
protected:
|
||||
PlainObject m_result;
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_INVERSE_H
|
||||
@@ -19,7 +19,7 @@ namespace Eigen {
|
||||
* \brief A matrix or vector expression mapping an existing array of data.
|
||||
*
|
||||
* \tparam PlainObjectType the equivalent matrix type of the mapped data
|
||||
* \tparam MapOptions specifies whether the pointer is \c #Aligned, or \c #Unaligned.
|
||||
* \tparam MapOptions specifies the pointer alignment in bytes. It can be: \c #Aligned128, , \c #Aligned64, \c #Aligned32, \c #Aligned16, \c #Aligned8 or \c #Unaligned.
|
||||
* The default is \c #Unaligned.
|
||||
* \tparam StrideType optionally specifies strides. By default, Map assumes the memory layout
|
||||
* of an ordinary, contiguous array. This can be overridden by specifying strides.
|
||||
@@ -70,8 +70,6 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> >
|
||||
: public traits<PlainObjectType>
|
||||
{
|
||||
typedef traits<PlainObjectType> TraitsBase;
|
||||
typedef typename PlainObjectType::Index Index;
|
||||
typedef typename PlainObjectType::Scalar Scalar;
|
||||
enum {
|
||||
InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
|
||||
? int(PlainObjectType::InnerStrideAtCompileTime)
|
||||
@@ -79,22 +77,9 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> >
|
||||
OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
|
||||
? int(PlainObjectType::OuterStrideAtCompileTime)
|
||||
: int(StrideType::OuterStrideAtCompileTime),
|
||||
HasNoInnerStride = InnerStrideAtCompileTime == 1,
|
||||
HasNoOuterStride = StrideType::OuterStrideAtCompileTime == 0,
|
||||
HasNoStride = HasNoInnerStride && HasNoOuterStride,
|
||||
IsAligned = bool(EIGEN_ALIGN) && ((int(MapOptions)&Aligned)==Aligned),
|
||||
IsDynamicSize = PlainObjectType::SizeAtCompileTime==Dynamic,
|
||||
KeepsPacketAccess = bool(HasNoInnerStride)
|
||||
&& ( bool(IsDynamicSize)
|
||||
|| HasNoOuterStride
|
||||
|| ( OuterStrideAtCompileTime!=Dynamic
|
||||
&& ((static_cast<int>(sizeof(Scalar))*OuterStrideAtCompileTime)%EIGEN_ALIGN_BYTES)==0 ) ),
|
||||
Alignment = int(MapOptions)&int(AlignedMask),
|
||||
Flags0 = TraitsBase::Flags & (~NestByRefBit),
|
||||
Flags1 = IsAligned ? (int(Flags0) | AlignedBit) : (int(Flags0) & ~AlignedBit),
|
||||
Flags2 = (bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime))
|
||||
? int(Flags1) : int(Flags1 & ~LinearAccessBit),
|
||||
Flags3 = is_lvalue<PlainObjectType>::value ? int(Flags2) : (int(Flags2) & ~LvalueBit),
|
||||
Flags = KeepsPacketAccess ? int(Flags3) : (int(Flags3) & ~PacketAccessBit)
|
||||
Flags = is_lvalue<PlainObjectType>::value ? int(Flags0) : (int(Flags0) & ~LvalueBit)
|
||||
};
|
||||
private:
|
||||
enum { Options }; // Expressions don't have Options
|
||||
@@ -132,11 +117,11 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
|
||||
/** Constructor in the fixed-size case.
|
||||
*
|
||||
* \param dataPtr pointer to the array to map
|
||||
* \param a_stride optional Stride object, passing the strides.
|
||||
* \param stride optional Stride object, passing the strides.
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Map(PointerArgType dataPtr, const StrideType& a_stride = StrideType())
|
||||
: Base(cast_to_pointer_type(dataPtr)), m_stride(a_stride)
|
||||
explicit inline Map(PointerArgType dataPtr, const StrideType& stride = StrideType())
|
||||
: Base(cast_to_pointer_type(dataPtr)), m_stride(stride)
|
||||
{
|
||||
PlainObjectType::Base::_check_template_params();
|
||||
}
|
||||
@@ -144,12 +129,12 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
|
||||
/** Constructor in the dynamic-size vector case.
|
||||
*
|
||||
* \param dataPtr pointer to the array to map
|
||||
* \param a_size the size of the vector expression
|
||||
* \param a_stride optional Stride object, passing the strides.
|
||||
* \param size the size of the vector expression
|
||||
* \param stride optional Stride object, passing the strides.
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Map(PointerArgType dataPtr, Index a_size, const StrideType& a_stride = StrideType())
|
||||
: Base(cast_to_pointer_type(dataPtr), a_size), m_stride(a_stride)
|
||||
inline Map(PointerArgType dataPtr, Index size, const StrideType& stride = StrideType())
|
||||
: Base(cast_to_pointer_type(dataPtr), size), m_stride(stride)
|
||||
{
|
||||
PlainObjectType::Base::_check_template_params();
|
||||
}
|
||||
@@ -157,13 +142,13 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
|
||||
/** Constructor in the dynamic-size matrix case.
|
||||
*
|
||||
* \param dataPtr pointer to the array to map
|
||||
* \param nbRows the number of rows of the matrix expression
|
||||
* \param nbCols the number of columns of the matrix expression
|
||||
* \param a_stride optional Stride object, passing the strides.
|
||||
* \param rows the number of rows of the matrix expression
|
||||
* \param cols the number of columns of the matrix expression
|
||||
* \param stride optional Stride object, passing the strides.
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
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)
|
||||
inline Map(PointerArgType dataPtr, Index rows, Index cols, const StrideType& stride = StrideType())
|
||||
: Base(cast_to_pointer_type(dataPtr), rows, cols), m_stride(stride)
|
||||
{
|
||||
PlainObjectType::Base::_check_template_params();
|
||||
}
|
||||
|
||||
@@ -12,7 +12,7 @@
|
||||
#define EIGEN_MAPBASE_H
|
||||
|
||||
#define EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) \
|
||||
EIGEN_STATIC_ASSERT((int(internal::traits<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
|
||||
EIGEN_STATIC_ASSERT((int(internal::evaluator<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
|
||||
YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT)
|
||||
|
||||
namespace Eigen {
|
||||
@@ -37,7 +37,6 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
|
||||
};
|
||||
|
||||
typedef typename internal::traits<Derived>::StorageKind StorageKind;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
@@ -85,7 +84,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
|
||||
*
|
||||
* \sa innerStride(), outerStride()
|
||||
*/
|
||||
inline const Scalar* data() const { return m_data; }
|
||||
EIGEN_DEVICE_FUNC inline const Scalar* data() const { return m_data; }
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline const Scalar& coeff(Index rowId, Index colId) const
|
||||
@@ -128,7 +127,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
|
||||
explicit inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
|
||||
checkSanity();
|
||||
@@ -147,12 +146,12 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols)
|
||||
: m_data(dataPtr), m_rows(nbRows), m_cols(nbCols)
|
||||
inline MapBase(PointerType dataPtr, Index rows, Index cols)
|
||||
: m_data(dataPtr), m_rows(rows), m_cols(cols)
|
||||
{
|
||||
eigen_assert( (dataPtr == 0)
|
||||
|| ( nbRows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
|
||||
&& nbCols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols)));
|
||||
|| ( rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
|
||||
&& cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)));
|
||||
checkSanity();
|
||||
}
|
||||
|
||||
@@ -161,11 +160,9 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void checkSanity() const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(internal::traits<Derived>::Flags&PacketAccessBit,
|
||||
internal::inner_stride_at_compile_time<Derived>::ret==1),
|
||||
PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1);
|
||||
eigen_assert(EIGEN_IMPLIES(internal::traits<Derived>::Flags&AlignedBit, (size_t(m_data) % EIGEN_ALIGN_BYTES) == 0)
|
||||
&& "data is not aligned");
|
||||
#if EIGEN_MAX_ALIGN_BYTES>0
|
||||
eigen_assert(((size_t(m_data) % EIGEN_PLAIN_ENUM_MAX(1,internal::traits<Derived>::Alignment)) == 0) && "data is not aligned");
|
||||
#endif
|
||||
}
|
||||
|
||||
PointerType m_data;
|
||||
@@ -176,13 +173,14 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
|
||||
template<typename Derived> class MapBase<Derived, WriteAccessors>
|
||||
: public MapBase<Derived, ReadOnlyAccessors>
|
||||
{
|
||||
typedef MapBase<Derived, ReadOnlyAccessors> ReadOnlyMapBase;
|
||||
public:
|
||||
|
||||
typedef MapBase<Derived, ReadOnlyAccessors> Base;
|
||||
|
||||
typedef typename Base::Scalar Scalar;
|
||||
typedef typename Base::PacketScalar PacketScalar;
|
||||
typedef typename Base::Index Index;
|
||||
typedef typename Base::StorageIndex StorageIndex;
|
||||
typedef typename Base::PointerType PointerType;
|
||||
|
||||
using Base::derived;
|
||||
@@ -238,16 +236,18 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
|
||||
|
||||
EIGEN_DEVICE_FUNC explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {}
|
||||
EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {}
|
||||
EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols) : Base(dataPtr, nbRows, nbCols) {}
|
||||
EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index rows, Index cols) : Base(dataPtr, rows, cols) {}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
Derived& operator=(const MapBase& other)
|
||||
{
|
||||
Base::Base::operator=(other);
|
||||
ReadOnlyMapBase::Base::operator=(other);
|
||||
return derived();
|
||||
}
|
||||
|
||||
using Base::Base::operator=;
|
||||
// In theory we could simply refer to Base:Base::operator=, but MSVC does not like Base::Base,
|
||||
// see bugs 821 and 920.
|
||||
using ReadOnlyMapBase::Base::operator=;
|
||||
};
|
||||
|
||||
#undef EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS
|
||||
|
||||
@@ -10,11 +10,14 @@
|
||||
#ifndef EIGEN_MATHFUNCTIONS_H
|
||||
#define EIGEN_MATHFUNCTIONS_H
|
||||
|
||||
// source: http://www.geom.uiuc.edu/~huberty/math5337/groupe/digits.html
|
||||
#define EIGEN_PI 3.141592653589793238462643383279502884197169399375105820974944592307816406
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
// On WINCE, std::abs is defined for int only, so let's defined our own overloads:
|
||||
// This issue has been confirmed with MSVC 2008 only, but the issue might exist for more recent versions too.
|
||||
#if defined(_WIN32_WCE) && defined(_MSC_VER) && _MSC_VER<=1500
|
||||
#if EIGEN_OS_WINCE && EIGEN_COMP_MSVC && EIGEN_COMP_MSVC<=1500
|
||||
long abs(long x) { return (labs(x)); }
|
||||
double abs(double x) { return (fabs(x)); }
|
||||
float abs(float x) { return (fabsf(x)); }
|
||||
@@ -276,7 +279,7 @@ struct norm1_default_impl
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline RealScalar run(const Scalar& x)
|
||||
{
|
||||
using std::abs;
|
||||
EIGEN_USING_STD_MATH(abs);
|
||||
return abs(real(x)) + abs(imag(x));
|
||||
}
|
||||
};
|
||||
@@ -287,7 +290,7 @@ struct norm1_default_impl<Scalar, false>
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline Scalar run(const Scalar& x)
|
||||
{
|
||||
using std::abs;
|
||||
EIGEN_USING_STD_MATH(abs);
|
||||
return abs(x);
|
||||
}
|
||||
};
|
||||
@@ -313,8 +316,8 @@ struct hypot_impl
|
||||
{
|
||||
EIGEN_USING_STD_MATH(max);
|
||||
EIGEN_USING_STD_MATH(min);
|
||||
using std::abs;
|
||||
using std::sqrt;
|
||||
EIGEN_USING_STD_MATH(abs);
|
||||
EIGEN_USING_STD_MATH(sqrt);
|
||||
RealScalar _x = abs(x);
|
||||
RealScalar _y = abs(y);
|
||||
Scalar p, qp;
|
||||
@@ -328,6 +331,7 @@ struct hypot_impl
|
||||
p = _y;
|
||||
qp = _x / p;
|
||||
}
|
||||
if(p==RealScalar(0)) return RealScalar(0);
|
||||
return p * sqrt(RealScalar(1) + qp*qp);
|
||||
}
|
||||
};
|
||||
@@ -345,6 +349,7 @@ struct hypot_retval
|
||||
template<typename OldType, typename NewType>
|
||||
struct cast_impl
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline NewType run(const OldType& x)
|
||||
{
|
||||
return static_cast<NewType>(x);
|
||||
@@ -354,56 +359,121 @@ struct cast_impl
|
||||
// here, for once, we're plainly returning NewType: we don't want cast to do weird things.
|
||||
|
||||
template<typename OldType, typename NewType>
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline NewType cast(const OldType& x)
|
||||
{
|
||||
return cast_impl<OldType, NewType>::run(x);
|
||||
}
|
||||
|
||||
/****************************************************************************
|
||||
* Implementation of atanh2 *
|
||||
* Implementation of round *
|
||||
****************************************************************************/
|
||||
|
||||
#if EIGEN_HAS_CXX11_MATH
|
||||
template<typename Scalar>
|
||||
struct round_impl {
|
||||
static inline Scalar run(const Scalar& x)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex), NUMERIC_TYPE_MUST_BE_REAL)
|
||||
using std::round;
|
||||
return round(x);
|
||||
}
|
||||
};
|
||||
#else
|
||||
template<typename Scalar>
|
||||
struct round_impl
|
||||
{
|
||||
static inline Scalar run(const Scalar& x)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex), NUMERIC_TYPE_MUST_BE_REAL)
|
||||
EIGEN_USING_STD_MATH(floor);
|
||||
EIGEN_USING_STD_MATH(ceil);
|
||||
return (x > Scalar(0)) ? floor(x + Scalar(0.5)) : ceil(x - Scalar(0.5));
|
||||
}
|
||||
};
|
||||
#endif
|
||||
|
||||
template<typename Scalar>
|
||||
struct atanh2_impl
|
||||
struct round_retval
|
||||
{
|
||||
static inline Scalar run(const Scalar& x, const Scalar& r)
|
||||
typedef Scalar type;
|
||||
};
|
||||
|
||||
/****************************************************************************
|
||||
* Implementation of arg *
|
||||
****************************************************************************/
|
||||
|
||||
#if EIGEN_HAS_CXX11_MATH
|
||||
template<typename Scalar>
|
||||
struct arg_impl {
|
||||
static inline Scalar run(const Scalar& x)
|
||||
{
|
||||
EIGEN_USING_STD_MATH(arg);
|
||||
return arg(x);
|
||||
}
|
||||
};
|
||||
#else
|
||||
template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
|
||||
struct arg_default_impl
|
||||
{
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline RealScalar run(const Scalar& x)
|
||||
{
|
||||
return (x < Scalar(0)) ? Scalar(EIGEN_PI) : Scalar(0); }
|
||||
};
|
||||
|
||||
template<typename Scalar>
|
||||
struct arg_default_impl<Scalar,true>
|
||||
{
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline RealScalar run(const Scalar& x)
|
||||
{
|
||||
EIGEN_USING_STD_MATH(arg);
|
||||
return arg(x);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Scalar> struct arg_impl : arg_default_impl<Scalar> {};
|
||||
#endif
|
||||
|
||||
template<typename Scalar>
|
||||
struct arg_retval
|
||||
{
|
||||
typedef typename NumTraits<Scalar>::Real type;
|
||||
};
|
||||
|
||||
/****************************************************************************
|
||||
* Implementation of log1p *
|
||||
****************************************************************************/
|
||||
template<typename Scalar, bool isComplex = NumTraits<Scalar>::IsComplex >
|
||||
struct log1p_impl
|
||||
{
|
||||
static inline Scalar run(const Scalar& x)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
|
||||
#if (__cplusplus >= 201103L) && !defined(__CYGWIN__)
|
||||
using std::log1p;
|
||||
return log1p(2 * x / (r - x)) / 2;
|
||||
#else
|
||||
using std::abs;
|
||||
using std::log;
|
||||
using std::sqrt;
|
||||
Scalar z = x / r;
|
||||
if (r == 0 || abs(z) > sqrt(NumTraits<Scalar>::epsilon()))
|
||||
return log((r + x) / (r - x)) / 2;
|
||||
else
|
||||
return z + z*z*z / 3;
|
||||
#endif
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
EIGEN_USING_STD_MATH(log);
|
||||
Scalar x1p = RealScalar(1) + x;
|
||||
return ( x1p == Scalar(1) ) ? x : x * ( log(x1p) / (x1p - RealScalar(1)) );
|
||||
}
|
||||
};
|
||||
|
||||
template<typename RealScalar>
|
||||
struct atanh2_impl<std::complex<RealScalar> >
|
||||
{
|
||||
typedef std::complex<RealScalar> Scalar;
|
||||
static inline Scalar run(const Scalar& x, const Scalar& r)
|
||||
#if EIGEN_HAS_CXX11_MATH
|
||||
template<typename Scalar>
|
||||
struct log1p_impl<Scalar, false> {
|
||||
static inline Scalar run(const Scalar& x)
|
||||
{
|
||||
using std::log;
|
||||
using std::norm;
|
||||
using std::sqrt;
|
||||
Scalar z = x / r;
|
||||
if (r == Scalar(0) || norm(z) > NumTraits<RealScalar>::epsilon())
|
||||
return RealScalar(0.5) * log((r + x) / (r - x));
|
||||
else
|
||||
return z + z*z*z / RealScalar(3);
|
||||
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
|
||||
using std::log1p;
|
||||
return log1p(x);
|
||||
}
|
||||
};
|
||||
#endif
|
||||
|
||||
template<typename Scalar>
|
||||
struct atanh2_retval
|
||||
struct log1p_retval
|
||||
{
|
||||
typedef Scalar type;
|
||||
};
|
||||
@@ -418,7 +488,7 @@ struct pow_default_impl
|
||||
typedef Scalar retval;
|
||||
static inline Scalar run(const Scalar& x, const Scalar& y)
|
||||
{
|
||||
using std::pow;
|
||||
EIGEN_USING_STD_MATH(pow);
|
||||
return pow(x, y);
|
||||
}
|
||||
};
|
||||
@@ -486,48 +556,48 @@ struct random_default_impl<Scalar, false, false>
|
||||
};
|
||||
|
||||
enum {
|
||||
floor_log2_terminate,
|
||||
floor_log2_move_up,
|
||||
floor_log2_move_down,
|
||||
floor_log2_bogus
|
||||
meta_floor_log2_terminate,
|
||||
meta_floor_log2_move_up,
|
||||
meta_floor_log2_move_down,
|
||||
meta_floor_log2_bogus
|
||||
};
|
||||
|
||||
template<unsigned int n, int lower, int upper> struct floor_log2_selector
|
||||
template<unsigned int n, int lower, int upper> struct meta_floor_log2_selector
|
||||
{
|
||||
enum { middle = (lower + upper) / 2,
|
||||
value = (upper <= lower + 1) ? int(floor_log2_terminate)
|
||||
: (n < (1 << middle)) ? int(floor_log2_move_down)
|
||||
: (n==0) ? int(floor_log2_bogus)
|
||||
: int(floor_log2_move_up)
|
||||
value = (upper <= lower + 1) ? int(meta_floor_log2_terminate)
|
||||
: (n < (1 << middle)) ? int(meta_floor_log2_move_down)
|
||||
: (n==0) ? int(meta_floor_log2_bogus)
|
||||
: int(meta_floor_log2_move_up)
|
||||
};
|
||||
};
|
||||
|
||||
template<unsigned int n,
|
||||
int lower = 0,
|
||||
int upper = sizeof(unsigned int) * CHAR_BIT - 1,
|
||||
int selector = floor_log2_selector<n, lower, upper>::value>
|
||||
struct floor_log2 {};
|
||||
int selector = meta_floor_log2_selector<n, lower, upper>::value>
|
||||
struct meta_floor_log2 {};
|
||||
|
||||
template<unsigned int n, int lower, int upper>
|
||||
struct floor_log2<n, lower, upper, floor_log2_move_down>
|
||||
struct meta_floor_log2<n, lower, upper, meta_floor_log2_move_down>
|
||||
{
|
||||
enum { value = floor_log2<n, lower, floor_log2_selector<n, lower, upper>::middle>::value };
|
||||
enum { value = meta_floor_log2<n, lower, meta_floor_log2_selector<n, lower, upper>::middle>::value };
|
||||
};
|
||||
|
||||
template<unsigned int n, int lower, int upper>
|
||||
struct floor_log2<n, lower, upper, floor_log2_move_up>
|
||||
struct meta_floor_log2<n, lower, upper, meta_floor_log2_move_up>
|
||||
{
|
||||
enum { value = floor_log2<n, floor_log2_selector<n, lower, upper>::middle, upper>::value };
|
||||
enum { value = meta_floor_log2<n, meta_floor_log2_selector<n, lower, upper>::middle, upper>::value };
|
||||
};
|
||||
|
||||
template<unsigned int n, int lower, int upper>
|
||||
struct floor_log2<n, lower, upper, floor_log2_terminate>
|
||||
struct meta_floor_log2<n, lower, upper, meta_floor_log2_terminate>
|
||||
{
|
||||
enum { value = (n >= ((unsigned int)(1) << (lower+1))) ? lower+1 : lower };
|
||||
};
|
||||
|
||||
template<unsigned int n, int lower, int upper>
|
||||
struct floor_log2<n, lower, upper, floor_log2_bogus>
|
||||
struct meta_floor_log2<n, lower, upper, meta_floor_log2_bogus>
|
||||
{
|
||||
// no value, error at compile time
|
||||
};
|
||||
@@ -535,11 +605,24 @@ struct floor_log2<n, lower, upper, floor_log2_bogus>
|
||||
template<typename Scalar>
|
||||
struct random_default_impl<Scalar, false, true>
|
||||
{
|
||||
typedef typename NumTraits<Scalar>::NonInteger NonInteger;
|
||||
|
||||
static inline Scalar run(const Scalar& x, const Scalar& y)
|
||||
{
|
||||
return x + Scalar((NonInteger(y)-x+1) * std::rand() / (RAND_MAX + NonInteger(1)));
|
||||
{
|
||||
using std::max;
|
||||
using std::min;
|
||||
typedef typename conditional<NumTraits<Scalar>::IsSigned,std::ptrdiff_t,std::size_t>::type ScalarX;
|
||||
if(y<x)
|
||||
return x;
|
||||
std::size_t range = ScalarX(y)-ScalarX(x);
|
||||
std::size_t offset = 0;
|
||||
// rejection sampling
|
||||
std::size_t divisor = (range+RAND_MAX-1)/(range+1);
|
||||
std::size_t multiplier = (range+RAND_MAX-1)/std::size_t(RAND_MAX);
|
||||
|
||||
do {
|
||||
offset = ( (std::size_t(std::rand()) * multiplier) / divisor );
|
||||
} while (offset > range);
|
||||
|
||||
return Scalar(ScalarX(x) + offset);
|
||||
}
|
||||
|
||||
static inline Scalar run()
|
||||
@@ -547,7 +630,7 @@ struct random_default_impl<Scalar, false, true>
|
||||
#ifdef EIGEN_MAKING_DOCS
|
||||
return run(Scalar(NumTraits<Scalar>::IsSigned ? -10 : 0), Scalar(10));
|
||||
#else
|
||||
enum { rand_bits = floor_log2<(unsigned int)(RAND_MAX)+1>::value,
|
||||
enum { rand_bits = meta_floor_log2<(unsigned int)(RAND_MAX)+1>::value,
|
||||
scalar_bits = sizeof(Scalar) * CHAR_BIT,
|
||||
shift = EIGEN_PLAIN_ENUM_MAX(0, int(rand_bits) - int(scalar_bits)),
|
||||
offset = NumTraits<Scalar>::IsSigned ? (1 << (EIGEN_PLAIN_ENUM_MIN(rand_bits,scalar_bits)-1)) : 0
|
||||
@@ -587,11 +670,55 @@ inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random()
|
||||
} // end namespace internal
|
||||
|
||||
/****************************************************************************
|
||||
* Generic math function *
|
||||
* Generic math functions *
|
||||
****************************************************************************/
|
||||
|
||||
namespace numext {
|
||||
|
||||
#ifndef __CUDA_ARCH__
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_ALWAYS_INLINE T mini(const T& x, const T& y)
|
||||
{
|
||||
EIGEN_USING_STD_MATH(min);
|
||||
return min EIGEN_NOT_A_MACRO (x,y);
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y)
|
||||
{
|
||||
EIGEN_USING_STD_MATH(max);
|
||||
return max EIGEN_NOT_A_MACRO (x,y);
|
||||
}
|
||||
#else
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_ALWAYS_INLINE T mini(const T& x, const T& y)
|
||||
{
|
||||
return y < x ? y : x;
|
||||
}
|
||||
template<>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_ALWAYS_INLINE float mini(const float& x, const float& y)
|
||||
{
|
||||
return fmin(x, y);
|
||||
}
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y)
|
||||
{
|
||||
return x < y ? y : x;
|
||||
}
|
||||
template<>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_ALWAYS_INLINE float maxi(const float& x, const float& y)
|
||||
{
|
||||
return fmax(x, y);
|
||||
}
|
||||
#endif
|
||||
|
||||
|
||||
template<typename Scalar>
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline EIGEN_MATHFUNC_RETVAL(real, Scalar) real(const Scalar& x)
|
||||
@@ -620,6 +747,13 @@ inline EIGEN_MATHFUNC_RETVAL(imag, Scalar) imag(const Scalar& x)
|
||||
return EIGEN_MATHFUNC_IMPL(imag, Scalar)::run(x);
|
||||
}
|
||||
|
||||
template<typename Scalar>
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline EIGEN_MATHFUNC_RETVAL(arg, Scalar) arg(const Scalar& x)
|
||||
{
|
||||
return EIGEN_MATHFUNC_IMPL(arg, Scalar)::run(x);
|
||||
}
|
||||
|
||||
template<typename Scalar>
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) >::type imag_ref(const Scalar& x)
|
||||
@@ -664,9 +798,9 @@ inline EIGEN_MATHFUNC_RETVAL(hypot, Scalar) hypot(const Scalar& x, const Scalar&
|
||||
|
||||
template<typename Scalar>
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline EIGEN_MATHFUNC_RETVAL(atanh2, Scalar) atanh2(const Scalar& x, const Scalar& y)
|
||||
inline EIGEN_MATHFUNC_RETVAL(log1p, Scalar) log1p(const Scalar& x)
|
||||
{
|
||||
return EIGEN_MATHFUNC_IMPL(atanh2, Scalar)::run(x, y);
|
||||
return EIGEN_MATHFUNC_IMPL(log1p, Scalar)::run(x);
|
||||
}
|
||||
|
||||
template<typename Scalar>
|
||||
@@ -676,22 +810,96 @@ inline EIGEN_MATHFUNC_RETVAL(pow, Scalar) pow(const Scalar& x, const Scalar& y)
|
||||
return EIGEN_MATHFUNC_IMPL(pow, Scalar)::run(x, y);
|
||||
}
|
||||
|
||||
// std::isfinite is non standard, so let's define our own version,
|
||||
// even though it is not very efficient.
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
bool (isfinite)(const T& x)
|
||||
{
|
||||
return x<NumTraits<T>::highest() && x>NumTraits<T>::lowest();
|
||||
#if EIGEN_HAS_CXX11_MATH
|
||||
using std::isfinite;
|
||||
return isfinite EIGEN_NOT_A_MACRO (x);
|
||||
#else
|
||||
return x<NumTraits<T>::highest() && x>NumTraits<T>::lowest();
|
||||
#endif
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
bool (isnan)(const T& x)
|
||||
{
|
||||
#if EIGEN_HAS_CXX11_MATH
|
||||
using std::isnan;
|
||||
return isnan EIGEN_NOT_A_MACRO (x);
|
||||
#else
|
||||
return x != x;
|
||||
#endif
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
bool (isinf)(const T& x)
|
||||
{
|
||||
#if EIGEN_HAS_CXX11_MATH
|
||||
using std::isinf;
|
||||
return isinf EIGEN_NOT_A_MACRO (x);
|
||||
#else
|
||||
return x>NumTraits<T>::highest() || x<NumTraits<T>::lowest();
|
||||
#endif
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
bool (isfinite)(const std::complex<T>& x)
|
||||
{
|
||||
using std::real;
|
||||
using std::imag;
|
||||
return isfinite(real(x)) && isfinite(imag(x));
|
||||
return (numext::isfinite)(numext::real(x)) && (numext::isfinite)(numext::imag(x));
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
bool (isnan)(const std::complex<T>& x)
|
||||
{
|
||||
return (numext::isnan)(numext::real(x)) || (numext::isnan)(numext::imag(x));
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
bool (isinf)(const std::complex<T>& x)
|
||||
{
|
||||
return ((numext::isinf)(numext::real(x)) || (numext::isinf)(numext::imag(x))) && (!(numext::isnan)(x));
|
||||
}
|
||||
|
||||
template<typename Scalar>
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline EIGEN_MATHFUNC_RETVAL(round, Scalar) round(const Scalar& x)
|
||||
{
|
||||
return EIGEN_MATHFUNC_IMPL(round, Scalar)::run(x);
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
T (floor)(const T& x)
|
||||
{
|
||||
EIGEN_USING_STD_MATH(floor);
|
||||
return floor(x);
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
T (ceil)(const T& x)
|
||||
{
|
||||
EIGEN_USING_STD_MATH(ceil);
|
||||
return ceil(x);
|
||||
}
|
||||
|
||||
// Log base 2 for 32 bits positive integers.
|
||||
// Conveniently returns 0 for x==0.
|
||||
inline int log2(int x)
|
||||
{
|
||||
eigen_assert(x>=0);
|
||||
unsigned int v(x);
|
||||
static const int table[32] = { 0, 9, 1, 10, 13, 21, 2, 29, 11, 14, 16, 18, 22, 25, 3, 30, 8, 12, 20, 28, 15, 17, 24, 7, 19, 27, 23, 6, 26, 5, 4, 31 };
|
||||
v |= v >> 1;
|
||||
v |= v >> 2;
|
||||
v |= v >> 4;
|
||||
v |= v >> 8;
|
||||
v |= v >> 16;
|
||||
return table[(v * 0x07C4ACDDU) >> 27];
|
||||
}
|
||||
|
||||
} // end namespace numext
|
||||
@@ -714,14 +922,14 @@ struct scalar_fuzzy_default_impl<Scalar, false, false>
|
||||
template<typename OtherScalar> EIGEN_DEVICE_FUNC
|
||||
static inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y, const RealScalar& prec)
|
||||
{
|
||||
using std::abs;
|
||||
EIGEN_USING_STD_MATH(abs);
|
||||
return abs(x) <= abs(y) * prec;
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec)
|
||||
{
|
||||
EIGEN_USING_STD_MATH(min);
|
||||
using std::abs;
|
||||
EIGEN_USING_STD_MATH(abs);
|
||||
return abs(x - y) <= (min)(abs(x), abs(y)) * prec;
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
|
||||
@@ -24,13 +24,13 @@ namespace Eigen {
|
||||
* The %Matrix class encompasses \em both fixed-size and dynamic-size objects (\ref fixedsize "note").
|
||||
*
|
||||
* The first three template parameters are required:
|
||||
* \tparam _Scalar \anchor matrix_tparam_scalar Numeric type, e.g. float, double, int or std::complex<float>.
|
||||
* User defined sclar types are supported as well (see \ref user_defined_scalars "here").
|
||||
* \tparam _Scalar Numeric type, e.g. float, double, int or std::complex<float>.
|
||||
* User defined scalar types are supported as well (see \ref user_defined_scalars "here").
|
||||
* \tparam _Rows Number of rows, or \b Dynamic
|
||||
* \tparam _Cols Number of columns, or \b Dynamic
|
||||
*
|
||||
* The remaining template parameters are optional -- in most cases you don't have to worry about them.
|
||||
* \tparam _Options \anchor matrix_tparam_options A combination of either \b #RowMajor or \b #ColMajor, and of either
|
||||
* \tparam _Options A combination of either \b #RowMajor or \b #ColMajor, and of either
|
||||
* \b #AutoAlign or \b #DontAlign.
|
||||
* The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required
|
||||
* for vectorization. It defaults to aligning matrices except for fixed sizes that aren't a multiple of the packet size.
|
||||
@@ -97,6 +97,40 @@ namespace Eigen {
|
||||
* are the dimensions of the original matrix, while _Rows and _Cols are Dynamic.</dd>
|
||||
* </dl>
|
||||
*
|
||||
* <i><b>ABI and storage layout</b></i>
|
||||
*
|
||||
* The table below summarizes the ABI of some possible Matrix instances which is fixed thorough the lifetime of Eigen 3.
|
||||
* <table class="manual">
|
||||
* <tr><th>Matrix type</th><th>Equivalent C structure</th></tr>
|
||||
* <tr><td>\code Matrix<T,Dynamic,Dynamic> \endcode</td><td>\code
|
||||
* struct {
|
||||
* T *data; // with (size_t(data)%EIGEN_MAX_ALIGN_BYTES)==0
|
||||
* Eigen::Index rows, cols;
|
||||
* };
|
||||
* \endcode</td></tr>
|
||||
* <tr class="alt"><td>\code
|
||||
* Matrix<T,Dynamic,1>
|
||||
* Matrix<T,1,Dynamic> \endcode</td><td>\code
|
||||
* struct {
|
||||
* T *data; // with (size_t(data)%EIGEN_MAX_ALIGN_BYTES)==0
|
||||
* Eigen::Index size;
|
||||
* };
|
||||
* \endcode</td></tr>
|
||||
* <tr><td>\code Matrix<T,Rows,Cols> \endcode</td><td>\code
|
||||
* struct {
|
||||
* T data[Rows*Cols]; // with (size_t(data)%A(Rows*Cols*sizeof(T)))==0
|
||||
* };
|
||||
* \endcode</td></tr>
|
||||
* <tr class="alt"><td>\code Matrix<T,Dynamic,Dynamic,0,MaxRows,MaxCols> \endcode</td><td>\code
|
||||
* struct {
|
||||
* T data[MaxRows*MaxCols]; // with (size_t(data)%A(MaxRows*MaxCols*sizeof(T)))==0
|
||||
* Eigen::Index rows, cols;
|
||||
* };
|
||||
* \endcode</td></tr>
|
||||
* </table>
|
||||
* Note that in this table Rows, Cols, MaxRows and MaxCols are all positive integers. A(S) is defined to the largest possible power-of-two
|
||||
* smaller to EIGEN_MAX_STATIC_ALIGN_BYTES.
|
||||
*
|
||||
* \see MatrixBase for the majority of the API methods for matrices, \ref TopicClassHierarchy,
|
||||
* \ref TopicStorageOrders
|
||||
*/
|
||||
@@ -105,9 +139,23 @@ namespace internal {
|
||||
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
|
||||
struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
|
||||
{
|
||||
private:
|
||||
enum { size = internal::size_at_compile_time<_Rows,_Cols>::ret };
|
||||
typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
|
||||
enum {
|
||||
row_major_bit = _Options&RowMajor ? RowMajorBit : 0,
|
||||
is_dynamic_size_storage = _MaxRows==Dynamic || _MaxCols==Dynamic,
|
||||
max_size = is_dynamic_size_storage ? Dynamic : _MaxRows*_MaxCols,
|
||||
default_alignment = compute_default_alignment<_Scalar,max_size>::value,
|
||||
actual_alignment = ((_Options&DontAlign)==0) ? default_alignment : 0,
|
||||
required_alignment = unpacket_traits<PacketScalar>::alignment,
|
||||
packet_access_bit = packet_traits<_Scalar>::Vectorizable && (actual_alignment>=required_alignment) ? PacketAccessBit : 0
|
||||
};
|
||||
|
||||
public:
|
||||
typedef _Scalar Scalar;
|
||||
typedef Dense StorageKind;
|
||||
typedef DenseIndex Index;
|
||||
typedef Eigen::Index StorageIndex;
|
||||
typedef MatrixXpr XprKind;
|
||||
enum {
|
||||
RowsAtCompileTime = _Rows,
|
||||
@@ -115,10 +163,13 @@ struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
|
||||
MaxRowsAtCompileTime = _MaxRows,
|
||||
MaxColsAtCompileTime = _MaxCols,
|
||||
Flags = compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
|
||||
CoeffReadCost = NumTraits<Scalar>::ReadCost,
|
||||
Options = _Options,
|
||||
InnerStrideAtCompileTime = 1,
|
||||
OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime
|
||||
OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime,
|
||||
|
||||
// FIXME, the following flag in only used to define NeedsToAlign in PlainObjectBase
|
||||
EvaluatorFlags = LinearAccessBit | DirectAccessBit | packet_access_bit | row_major_bit,
|
||||
Alignment = actual_alignment
|
||||
};
|
||||
};
|
||||
}
|
||||
@@ -169,7 +220,7 @@ class Matrix
|
||||
*/
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Matrix& operator=(const MatrixBase<OtherDerived>& other)
|
||||
EIGEN_STRONG_INLINE Matrix& operator=(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
return Base::_set(other);
|
||||
}
|
||||
@@ -213,11 +264,12 @@ class Matrix
|
||||
|
||||
// FIXME is it still needed
|
||||
EIGEN_DEVICE_FUNC
|
||||
Matrix(internal::constructor_without_unaligned_array_assert)
|
||||
explicit Matrix(internal::constructor_without_unaligned_array_assert)
|
||||
: Base(internal::constructor_without_unaligned_array_assert())
|
||||
{ Base::_check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
|
||||
|
||||
#ifdef EIGEN_HAVE_RVALUE_REFERENCES
|
||||
EIGEN_DEVICE_FUNC
|
||||
Matrix(Matrix&& other)
|
||||
: Base(std::move(other))
|
||||
{
|
||||
@@ -225,6 +277,7 @@ class Matrix
|
||||
if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
|
||||
Base::_set_noalias(other);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
Matrix& operator=(Matrix&& other)
|
||||
{
|
||||
other.swap(*this);
|
||||
@@ -263,8 +316,8 @@ class Matrix
|
||||
*
|
||||
* \warning This constructor is disabled for fixed-size \c 1x1 matrices. For instance,
|
||||
* calling Matrix<double,1,1>(1) will call the initialization constructor: Matrix(const Scalar&).
|
||||
* For fixed-size \c 1x1 matrices it is thefore recommended to use the default
|
||||
* constructor Matrix() instead, especilly when using one of the non standard
|
||||
* For fixed-size \c 1x1 matrices it is therefore recommended to use the default
|
||||
* constructor Matrix() instead, especially when using one of the non standard
|
||||
* \c EIGEN_INITIALIZE_MATRICES_BY_{ZERO,\c NAN} macros (see \ref TopicPreprocessorDirectives).
|
||||
*/
|
||||
EIGEN_STRONG_INLINE explicit Matrix(Index dim);
|
||||
@@ -278,8 +331,8 @@ class Matrix
|
||||
*
|
||||
* \warning This constructor is disabled for fixed-size \c 1x2 and \c 2x1 vectors. For instance,
|
||||
* calling Matrix2f(2,1) will call the initialization constructor: Matrix(const Scalar& x, const Scalar& y).
|
||||
* For fixed-size \c 1x2 or \c 2x1 vectors it is thefore recommended to use the default
|
||||
* constructor Matrix() instead, especilly when using one of the non standard
|
||||
* For fixed-size \c 1x2 or \c 2x1 vectors it is therefore recommended to use the default
|
||||
* constructor Matrix() instead, especially when using one of the non standard
|
||||
* \c EIGEN_INITIALIZE_MATRICES_BY_{ZERO,\c NAN} macros (see \ref TopicPreprocessorDirectives).
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -312,37 +365,10 @@ class Matrix
|
||||
}
|
||||
|
||||
|
||||
/** \brief Constructor copying the value of the expression \a other */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Matrix(const MatrixBase<OtherDerived>& other)
|
||||
: Base(other.rows() * other.cols(), other.rows(), other.cols())
|
||||
{
|
||||
// This test resides here, to bring the error messages closer to the user. Normally, these checks
|
||||
// are performed deeply within the library, thus causing long and scary error traces.
|
||||
EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
|
||||
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
|
||||
|
||||
Base::_check_template_params();
|
||||
Base::_set_noalias(other);
|
||||
}
|
||||
/** \brief Copy constructor */
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Matrix(const Matrix& other)
|
||||
: Base(other.rows() * other.cols(), other.rows(), other.cols())
|
||||
{
|
||||
Base::_check_template_params();
|
||||
Base::_set_noalias(other);
|
||||
}
|
||||
/** \brief Copy constructor with in-place evaluation */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Matrix(const ReturnByValue<OtherDerived>& other)
|
||||
{
|
||||
Base::_check_template_params();
|
||||
Base::resize(other.rows(), other.cols());
|
||||
other.evalTo(*this);
|
||||
}
|
||||
EIGEN_STRONG_INLINE Matrix(const Matrix& other) : Base(other)
|
||||
{ }
|
||||
|
||||
/** \brief Copy constructor for generic expressions.
|
||||
* \sa MatrixBase::operator=(const EigenBase<OtherDerived>&)
|
||||
@@ -350,23 +376,8 @@ class Matrix
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Matrix(const EigenBase<OtherDerived> &other)
|
||||
: Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
|
||||
{
|
||||
Base::_check_template_params();
|
||||
Base::_resize_to_match(other);
|
||||
// FIXME/CHECK: isn't *this = other.derived() more efficient. it allows to
|
||||
// go for pure _set() implementations, right?
|
||||
*this = other;
|
||||
}
|
||||
|
||||
/** \internal
|
||||
* \brief Override MatrixBase::swap() since for dynamic-sized matrices
|
||||
* of same type it is enough to swap the data pointers.
|
||||
*/
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void swap(MatrixBase<OtherDerived> const & other)
|
||||
{ this->_swap(other.derived()); }
|
||||
: Base(other.derived())
|
||||
{ }
|
||||
|
||||
EIGEN_DEVICE_FUNC inline Index innerStride() const { return 1; }
|
||||
EIGEN_DEVICE_FUNC inline Index outerStride() const { return this->innerSize(); }
|
||||
|
||||
@@ -52,7 +52,7 @@ template<typename Derived> class MatrixBase
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
typedef MatrixBase StorageBaseType;
|
||||
typedef typename internal::traits<Derived>::StorageKind StorageKind;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
@@ -66,8 +66,7 @@ template<typename Derived> class MatrixBase
|
||||
using Base::MaxSizeAtCompileTime;
|
||||
using Base::IsVectorAtCompileTime;
|
||||
using Base::Flags;
|
||||
using Base::CoeffReadCost;
|
||||
|
||||
|
||||
using Base::derived;
|
||||
using Base::const_cast_derived;
|
||||
using Base::rows;
|
||||
@@ -82,6 +81,7 @@ template<typename Derived> class MatrixBase
|
||||
using Base::operator*=;
|
||||
using Base::operator/=;
|
||||
using Base::operator*;
|
||||
using Base::operator/;
|
||||
|
||||
typedef typename Base::CoeffReturnType CoeffReturnType;
|
||||
typedef typename Base::ConstTransposeReturnType ConstTransposeReturnType;
|
||||
@@ -102,23 +102,11 @@ template<typename Derived> class MatrixBase
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index diagonalSize() const { return (std::min)(rows(),cols()); }
|
||||
|
||||
/** \brief The plain matrix type corresponding to this expression.
|
||||
*
|
||||
* This is not necessarily exactly the return type of eval(). In the case of plain matrices,
|
||||
* the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed
|
||||
* that the return type of eval() is either PlainObject or const PlainObject&.
|
||||
*/
|
||||
typedef Matrix<typename internal::traits<Derived>::Scalar,
|
||||
internal::traits<Derived>::RowsAtCompileTime,
|
||||
internal::traits<Derived>::ColsAtCompileTime,
|
||||
AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
|
||||
internal::traits<Derived>::MaxRowsAtCompileTime,
|
||||
internal::traits<Derived>::MaxColsAtCompileTime
|
||||
> PlainObject;
|
||||
typedef typename Base::PlainObject PlainObject;
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
/** \internal Represents a matrix with all coefficients equal to one another*/
|
||||
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
|
||||
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType;
|
||||
/** \internal the return type of MatrixBase::adjoint() */
|
||||
typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
|
||||
CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, ConstTransposeReturnType>,
|
||||
@@ -127,7 +115,7 @@ template<typename Derived> class MatrixBase
|
||||
/** \internal Return type of eigenvalues() */
|
||||
typedef Matrix<std::complex<RealScalar>, internal::traits<Derived>::ColsAtCompileTime, 1, ColMajor> EigenvaluesReturnType;
|
||||
/** \internal the return type of identity */
|
||||
typedef CwiseNullaryOp<internal::scalar_identity_op<Scalar>,Derived> IdentityReturnType;
|
||||
typedef CwiseNullaryOp<internal::scalar_identity_op<Scalar>,PlainObject> IdentityReturnType;
|
||||
/** \internal the return type of unit vectors */
|
||||
typedef Block<const CwiseNullaryOp<internal::scalar_identity_op<Scalar>, SquareMatrixType>,
|
||||
internal::traits<Derived>::RowsAtCompileTime,
|
||||
@@ -165,12 +153,6 @@ template<typename Derived> class MatrixBase
|
||||
EIGEN_DEVICE_FUNC
|
||||
Derived& operator=(const ReturnByValue<OtherDerived>& other);
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename ProductDerived, typename Lhs, typename Rhs>
|
||||
EIGEN_DEVICE_FUNC
|
||||
Derived& lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other);
|
||||
#endif // not EIGEN_PARSED_BY_DOXYGEN
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
Derived& operator+=(const MatrixBase<OtherDerived>& other);
|
||||
@@ -181,26 +163,20 @@ template<typename Derived> class MatrixBase
|
||||
#ifdef __CUDACC__
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const typename LazyProductReturnType<Derived,OtherDerived>::Type
|
||||
const Product<Derived,OtherDerived,LazyProduct>
|
||||
operator*(const MatrixBase<OtherDerived> &other) const
|
||||
{ return this->lazyProduct(other); }
|
||||
#else
|
||||
|
||||
#ifdef EIGEN_TEST_EVALUATORS
|
||||
template<typename OtherDerived>
|
||||
const Product<Derived,OtherDerived>
|
||||
operator*(const MatrixBase<OtherDerived> &other) const;
|
||||
#else
|
||||
template<typename OtherDerived>
|
||||
const typename ProductReturnType<Derived,OtherDerived>::Type
|
||||
operator*(const MatrixBase<OtherDerived> &other) const;
|
||||
#endif
|
||||
|
||||
#endif
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const typename LazyProductReturnType<Derived,OtherDerived>::Type
|
||||
const Product<Derived,OtherDerived,LazyProduct>
|
||||
lazyProduct(const MatrixBase<OtherDerived> &other) const;
|
||||
|
||||
template<typename OtherDerived>
|
||||
@@ -214,7 +190,7 @@ template<typename Derived> class MatrixBase
|
||||
|
||||
template<typename DiagonalDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
|
||||
const Product<Derived, DiagonalDerived, LazyProduct>
|
||||
operator*(const DiagonalBase<DiagonalDerived> &diagonal) const;
|
||||
|
||||
template<typename OtherDerived>
|
||||
@@ -251,19 +227,14 @@ template<typename Derived> class MatrixBase
|
||||
template<int Index>
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename ConstDiagonalIndexReturnType<Index>::Type diagonal() const;
|
||||
|
||||
// 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<DynamicIndex>::Type diagonal(Index index);
|
||||
typename MatrixBase::template ConstDiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index) const;
|
||||
#else
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename DiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index);
|
||||
|
||||
typedef Diagonal<Derived,DynamicIndex> DiagonalDynamicIndexReturnType;
|
||||
typedef typename internal::add_const<Diagonal<const Derived,DynamicIndex> >::type ConstDiagonalDynamicIndexReturnType;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename ConstDiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index) const;
|
||||
#endif
|
||||
DiagonalDynamicIndexReturnType diagonal(Index index);
|
||||
EIGEN_DEVICE_FUNC
|
||||
ConstDiagonalDynamicIndexReturnType diagonal(Index index) const;
|
||||
|
||||
template<unsigned int Mode> struct TriangularViewReturnType { typedef TriangularView<Derived, Mode> Type; };
|
||||
template<unsigned int Mode> struct ConstTriangularViewReturnType { typedef const TriangularView<const Derived, Mode> Type; };
|
||||
@@ -334,12 +305,14 @@ template<typename Derived> class MatrixBase
|
||||
|
||||
NoAlias<Derived,Eigen::MatrixBase > noalias();
|
||||
|
||||
inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
|
||||
inline ForceAlignedAccess<Derived> forceAlignedAccess();
|
||||
template<bool Enable> inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type forceAlignedAccessIf() const;
|
||||
template<bool Enable> inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
|
||||
// TODO forceAlignedAccess is temporarily disabled
|
||||
// Need to find a nicer workaround.
|
||||
inline const Derived& forceAlignedAccess() const { return derived(); }
|
||||
inline Derived& forceAlignedAccess() { return derived(); }
|
||||
template<bool Enable> inline const Derived& forceAlignedAccessIf() const { return derived(); }
|
||||
template<bool Enable> inline Derived& forceAlignedAccessIf() { return derived(); }
|
||||
|
||||
Scalar trace() const;
|
||||
EIGEN_DEVICE_FUNC Scalar trace() const;
|
||||
|
||||
template<int p> EIGEN_DEVICE_FUNC RealScalar lpNorm() const;
|
||||
|
||||
@@ -348,10 +321,10 @@ template<typename Derived> class MatrixBase
|
||||
|
||||
/** \returns an \link Eigen::ArrayBase Array \endlink expression of this matrix
|
||||
* \sa ArrayBase::matrix() */
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ArrayWrapper<Derived> array() { return derived(); }
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ArrayWrapper<Derived> array() { return ArrayWrapper<Derived>(derived()); }
|
||||
/** \returns a const \link Eigen::ArrayBase Array \endlink expression of this matrix
|
||||
* \sa ArrayBase::matrix() */
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const ArrayWrapper<const Derived> array() const { return derived(); }
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const ArrayWrapper<const Derived> array() const { return ArrayWrapper<const Derived>(derived()); }
|
||||
|
||||
/////////// LU module ///////////
|
||||
|
||||
@@ -361,7 +334,8 @@ template<typename Derived> class MatrixBase
|
||||
const PartialPivLU<PlainObject> lu() const;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
const internal::inverse_impl<Derived> inverse() const;
|
||||
const Inverse<Derived> inverse() const;
|
||||
|
||||
template<typename ResultType>
|
||||
void computeInverseAndDetWithCheck(
|
||||
ResultType& inverse,
|
||||
@@ -394,6 +368,7 @@ template<typename Derived> class MatrixBase
|
||||
/////////// SVD module ///////////
|
||||
|
||||
JacobiSVD<PlainObject> jacobiSvd(unsigned int computationOptions = 0) const;
|
||||
BDCSVD<PlainObject> bdcSvd(unsigned int computationOptions = 0) const;
|
||||
|
||||
/////////// Geometry module ///////////
|
||||
|
||||
@@ -420,7 +395,8 @@ template<typename Derived> class MatrixBase
|
||||
|
||||
ScalarMultipleReturnType operator*(const UniformScaling<Scalar>& s) const;
|
||||
// put this as separate enum value to work around possible GCC 4.3 bug (?)
|
||||
enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1?Vertical:Horizontal };
|
||||
enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1&&RowsAtCompileTime==1 ? ((internal::traits<Derived>::Flags&RowMajorBit)==RowMajorBit ? Horizontal : Vertical)
|
||||
: ColsAtCompileTime==1 ? Vertical : Horizontal };
|
||||
typedef Homogeneous<Derived, HomogeneousReturnTypeDirection> HomogeneousReturnType;
|
||||
HomogeneousReturnType homogeneous() const;
|
||||
|
||||
|
||||
@@ -40,29 +40,29 @@ template<typename ExpressionType> class NestByValue
|
||||
typedef typename internal::dense_xpr_base<NestByValue>::type Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(NestByValue)
|
||||
|
||||
inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
|
||||
EIGEN_DEVICE_FUNC explicit inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
|
||||
|
||||
inline Index rows() const { return m_expression.rows(); }
|
||||
inline Index cols() const { return m_expression.cols(); }
|
||||
inline Index outerStride() const { return m_expression.outerStride(); }
|
||||
inline Index innerStride() const { return m_expression.innerStride(); }
|
||||
EIGEN_DEVICE_FUNC inline Index rows() const { return m_expression.rows(); }
|
||||
EIGEN_DEVICE_FUNC inline Index cols() const { return m_expression.cols(); }
|
||||
EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_expression.outerStride(); }
|
||||
EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_expression.innerStride(); }
|
||||
|
||||
inline const CoeffReturnType coeff(Index row, Index col) const
|
||||
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const
|
||||
{
|
||||
return m_expression.coeff(row, col);
|
||||
}
|
||||
|
||||
inline Scalar& coeffRef(Index row, Index col)
|
||||
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
|
||||
{
|
||||
return m_expression.const_cast_derived().coeffRef(row, col);
|
||||
}
|
||||
|
||||
inline const CoeffReturnType coeff(Index index) const
|
||||
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const
|
||||
{
|
||||
return m_expression.coeff(index);
|
||||
}
|
||||
|
||||
inline Scalar& coeffRef(Index index)
|
||||
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
|
||||
{
|
||||
return m_expression.const_cast_derived().coeffRef(index);
|
||||
}
|
||||
@@ -91,7 +91,7 @@ template<typename ExpressionType> class NestByValue
|
||||
m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
|
||||
}
|
||||
|
||||
operator const ExpressionType&() const { return m_expression; }
|
||||
EIGEN_DEVICE_FUNC operator const ExpressionType&() const { return m_expression; }
|
||||
|
||||
protected:
|
||||
const ExpressionType m_expression;
|
||||
|
||||
@@ -30,68 +30,35 @@ namespace Eigen {
|
||||
template<typename ExpressionType, template <typename> class StorageBase>
|
||||
class NoAlias
|
||||
{
|
||||
typedef typename ExpressionType::Scalar Scalar;
|
||||
public:
|
||||
NoAlias(ExpressionType& expression) : m_expression(expression) {}
|
||||
|
||||
/** Behaves like MatrixBase::lazyAssign(other)
|
||||
* \sa MatrixBase::lazyAssign() */
|
||||
typedef typename ExpressionType::Scalar Scalar;
|
||||
|
||||
explicit NoAlias(ExpressionType& expression) : m_expression(expression) {}
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE ExpressionType& operator=(const StorageBase<OtherDerived>& other)
|
||||
{ return internal::assign_selector<ExpressionType,OtherDerived,false>::run(m_expression,other.derived()); }
|
||||
|
||||
/** \sa MatrixBase::operator+= */
|
||||
{
|
||||
call_assignment_no_alias(m_expression, other.derived(), internal::assign_op<Scalar>());
|
||||
return m_expression;
|
||||
}
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE ExpressionType& operator+=(const StorageBase<OtherDerived>& other)
|
||||
{
|
||||
typedef SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, ExpressionType, OtherDerived> SelfAdder;
|
||||
SelfAdder tmp(m_expression);
|
||||
typedef typename internal::nested<OtherDerived>::type OtherDerivedNested;
|
||||
typedef typename internal::remove_all<OtherDerivedNested>::type _OtherDerivedNested;
|
||||
internal::assign_selector<SelfAdder,_OtherDerivedNested,false>::run(tmp,OtherDerivedNested(other.derived()));
|
||||
call_assignment_no_alias(m_expression, other.derived(), internal::add_assign_op<Scalar>());
|
||||
return m_expression;
|
||||
}
|
||||
|
||||
/** \sa MatrixBase::operator-= */
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE ExpressionType& operator-=(const StorageBase<OtherDerived>& other)
|
||||
{
|
||||
typedef SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, ExpressionType, OtherDerived> SelfAdder;
|
||||
SelfAdder tmp(m_expression);
|
||||
typedef typename internal::nested<OtherDerived>::type OtherDerivedNested;
|
||||
typedef typename internal::remove_all<OtherDerivedNested>::type _OtherDerivedNested;
|
||||
internal::assign_selector<SelfAdder,_OtherDerivedNested,false>::run(tmp,OtherDerivedNested(other.derived()));
|
||||
call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op<Scalar>());
|
||||
return m_expression;
|
||||
}
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename ProductDerived, typename Lhs, typename Rhs>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE ExpressionType& operator+=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
|
||||
{ other.derived().addTo(m_expression); return m_expression; }
|
||||
|
||||
template<typename ProductDerived, typename Lhs, typename Rhs>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE ExpressionType& operator-=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
|
||||
{ other.derived().subTo(m_expression); return m_expression; }
|
||||
|
||||
template<typename Lhs, typename Rhs, int NestingFlags>
|
||||
EIGEN_STRONG_INLINE ExpressionType& operator+=(const CoeffBasedProduct<Lhs,Rhs,NestingFlags>& other)
|
||||
{ return m_expression.derived() += CoeffBasedProduct<Lhs,Rhs,NestByRefBit>(other.lhs(), other.rhs()); }
|
||||
|
||||
template<typename Lhs, typename Rhs, int NestingFlags>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE ExpressionType& operator-=(const CoeffBasedProduct<Lhs,Rhs,NestingFlags>& other)
|
||||
{ return m_expression.derived() -= CoeffBasedProduct<Lhs,Rhs,NestByRefBit>(other.lhs(), other.rhs()); }
|
||||
|
||||
template<typename OtherDerived>
|
||||
ExpressionType& operator=(const ReturnByValue<OtherDerived>& func)
|
||||
{ return m_expression = func; }
|
||||
#endif
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
ExpressionType& expression() const
|
||||
{
|
||||
@@ -133,7 +100,7 @@ class NoAlias
|
||||
template<typename Derived>
|
||||
NoAlias<Derived,MatrixBase> MatrixBase<Derived>::noalias()
|
||||
{
|
||||
return derived();
|
||||
return NoAlias<Derived, Eigen::MatrixBase >(derived());
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -83,8 +83,25 @@ template<typename T> struct GenericNumTraits
|
||||
// make sure to override this for floating-point types
|
||||
return Real(0);
|
||||
}
|
||||
static inline T highest() { return (std::numeric_limits<T>::max)(); }
|
||||
static inline T lowest() { return IsInteger ? (std::numeric_limits<T>::min)() : (-(std::numeric_limits<T>::max)()); }
|
||||
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline T highest() {
|
||||
#if defined(__CUDA_ARCH__)
|
||||
return (internal::device::numeric_limits<T>::max)();
|
||||
#else
|
||||
return (std::numeric_limits<T>::max)();
|
||||
#endif
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline T lowest() {
|
||||
#if defined(__CUDA_ARCH__)
|
||||
return IsInteger ? (internal::device::numeric_limits<T>::min)() : (-(internal::device::numeric_limits<T>::max)());
|
||||
#else
|
||||
return IsInteger ? (std::numeric_limits<T>::min)() : (-(std::numeric_limits<T>::max)());
|
||||
#endif
|
||||
}
|
||||
};
|
||||
|
||||
template<typename T> struct NumTraits : GenericNumTraits<T>
|
||||
|
||||
@@ -13,7 +13,8 @@
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKind> class PermutedImpl;
|
||||
// TODO: this does not seems to be needed at all:
|
||||
// template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKind> class PermutedImpl;
|
||||
|
||||
/** \class PermutationBase
|
||||
* \ingroup Core_Module
|
||||
@@ -41,10 +42,6 @@ template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKi
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename PermutationType, typename MatrixType, int Side, bool Transposed=false>
|
||||
struct permut_matrix_product_retval;
|
||||
template<typename PermutationType, typename MatrixType, int Side, bool Transposed=false>
|
||||
struct permut_sparsematrix_product_retval;
|
||||
enum PermPermProduct_t {PermPermProduct};
|
||||
|
||||
} // end namespace internal
|
||||
@@ -60,19 +57,18 @@ class PermutationBase : public EigenBase<Derived>
|
||||
typedef typename Traits::IndicesType IndicesType;
|
||||
enum {
|
||||
Flags = Traits::Flags,
|
||||
CoeffReadCost = Traits::CoeffReadCost,
|
||||
RowsAtCompileTime = Traits::RowsAtCompileTime,
|
||||
ColsAtCompileTime = Traits::ColsAtCompileTime,
|
||||
MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime,
|
||||
MaxColsAtCompileTime = Traits::MaxColsAtCompileTime
|
||||
};
|
||||
typedef typename Traits::StorageIndexType StorageIndexType;
|
||||
typedef typename Traits::Index Index;
|
||||
typedef Matrix<StorageIndexType,RowsAtCompileTime,ColsAtCompileTime,0,MaxRowsAtCompileTime,MaxColsAtCompileTime>
|
||||
typedef typename Traits::StorageIndex StorageIndex;
|
||||
typedef Matrix<StorageIndex,RowsAtCompileTime,ColsAtCompileTime,0,MaxRowsAtCompileTime,MaxColsAtCompileTime>
|
||||
DenseMatrixType;
|
||||
typedef PermutationMatrix<IndicesType::SizeAtCompileTime,IndicesType::MaxSizeAtCompileTime,StorageIndexType>
|
||||
typedef PermutationMatrix<IndicesType::SizeAtCompileTime,IndicesType::MaxSizeAtCompileTime,StorageIndex>
|
||||
PlainPermutationType;
|
||||
using Base::derived;
|
||||
typedef Transpose<PermutationBase> TransposeReturnType;
|
||||
#endif
|
||||
|
||||
/** Copies the other permutation into *this */
|
||||
@@ -118,7 +114,7 @@ class PermutationBase : public EigenBase<Derived>
|
||||
void evalTo(MatrixBase<DenseDerived>& other) const
|
||||
{
|
||||
other.setZero();
|
||||
for (int i=0; i<rows();++i)
|
||||
for (Index i=0; i<rows(); ++i)
|
||||
other.coeffRef(indices().coeff(i),i) = typename DenseDerived::Scalar(1);
|
||||
}
|
||||
#endif
|
||||
@@ -147,7 +143,8 @@ class PermutationBase : public EigenBase<Derived>
|
||||
/** Sets *this to be the identity permutation matrix */
|
||||
void setIdentity()
|
||||
{
|
||||
for(StorageIndexType i = 0; i < size(); ++i)
|
||||
StorageIndex n = StorageIndex(size());
|
||||
for(StorageIndex i = 0; i < n; ++i)
|
||||
indices().coeffRef(i) = i;
|
||||
}
|
||||
|
||||
@@ -163,18 +160,18 @@ class PermutationBase : public EigenBase<Derived>
|
||||
*
|
||||
* \returns a reference to *this.
|
||||
*
|
||||
* \warning This is much slower than applyTranspositionOnTheRight(int,int):
|
||||
* \warning This is much slower than applyTranspositionOnTheRight(Index,Index):
|
||||
* this has linear complexity and requires a lot of branching.
|
||||
*
|
||||
* \sa applyTranspositionOnTheRight(int,int)
|
||||
* \sa applyTranspositionOnTheRight(Index,Index)
|
||||
*/
|
||||
Derived& applyTranspositionOnTheLeft(Index i, Index j)
|
||||
{
|
||||
eigen_assert(i>=0 && j>=0 && i<size() && j<size());
|
||||
for(Index k = 0; k < size(); ++k)
|
||||
{
|
||||
if(indices().coeff(k) == i) indices().coeffRef(k) = StorageIndexType(j);
|
||||
else if(indices().coeff(k) == j) indices().coeffRef(k) = StorageIndexType(i);
|
||||
if(indices().coeff(k) == i) indices().coeffRef(k) = StorageIndex(j);
|
||||
else if(indices().coeff(k) == j) indices().coeffRef(k) = StorageIndex(i);
|
||||
}
|
||||
return derived();
|
||||
}
|
||||
@@ -185,7 +182,7 @@ class PermutationBase : public EigenBase<Derived>
|
||||
*
|
||||
* This is a fast operation, it only consists in swapping two indices.
|
||||
*
|
||||
* \sa applyTranspositionOnTheLeft(int,int)
|
||||
* \sa applyTranspositionOnTheLeft(Index,Index)
|
||||
*/
|
||||
Derived& applyTranspositionOnTheRight(Index i, Index j)
|
||||
{
|
||||
@@ -198,14 +195,14 @@ class PermutationBase : public EigenBase<Derived>
|
||||
*
|
||||
* \note \note_try_to_help_rvo
|
||||
*/
|
||||
inline Transpose<PermutationBase> inverse() const
|
||||
{ return derived(); }
|
||||
inline TransposeReturnType inverse() const
|
||||
{ return TransposeReturnType(derived()); }
|
||||
/** \returns the tranpose permutation matrix.
|
||||
*
|
||||
* \note \note_try_to_help_rvo
|
||||
*/
|
||||
inline Transpose<PermutationBase> transpose() const
|
||||
{ return derived(); }
|
||||
inline TransposeReturnType transpose() const
|
||||
{ return TransposeReturnType(derived()); }
|
||||
|
||||
/**** multiplication helpers to hopefully get RVO ****/
|
||||
|
||||
@@ -215,13 +212,13 @@ class PermutationBase : public EigenBase<Derived>
|
||||
template<typename OtherDerived>
|
||||
void assignTranspose(const PermutationBase<OtherDerived>& other)
|
||||
{
|
||||
for (int i=0; i<rows();++i) indices().coeffRef(other.indices().coeff(i)) = i;
|
||||
for (Index i=0; i<rows();++i) indices().coeffRef(other.indices().coeff(i)) = i;
|
||||
}
|
||||
template<typename Lhs,typename Rhs>
|
||||
void assignProduct(const Lhs& lhs, const Rhs& rhs)
|
||||
{
|
||||
eigen_assert(lhs.cols() == rhs.rows());
|
||||
for (int i=0; i<rows();++i) indices().coeffRef(i) = lhs.indices().coeff(rhs.indices().coeff(i));
|
||||
for (Index i=0; i<rows();++i) indices().coeffRef(i) = lhs.indices().coeff(rhs.indices().coeff(i));
|
||||
}
|
||||
#endif
|
||||
|
||||
@@ -250,6 +247,35 @@ class PermutationBase : public EigenBase<Derived>
|
||||
template<typename Other> friend
|
||||
inline PlainPermutationType operator*(const Transpose<PermutationBase<Other> >& other, const PermutationBase& perm)
|
||||
{ return PlainPermutationType(internal::PermPermProduct, other.eval(), perm); }
|
||||
|
||||
/** \returns the determinant of the permutation matrix, which is either 1 or -1 depending on the parity of the permutation.
|
||||
*
|
||||
* This function is O(\c n) procedure allocating a buffer of \c n booleans.
|
||||
*/
|
||||
Index determinant() const
|
||||
{
|
||||
Index res = 1;
|
||||
Index n = size();
|
||||
Matrix<bool,RowsAtCompileTime,1,0,MaxRowsAtCompileTime> mask(n);
|
||||
mask.fill(false);
|
||||
Index r = 0;
|
||||
while(r < n)
|
||||
{
|
||||
// search for the next seed
|
||||
while(r<n && mask[r]) r++;
|
||||
if(r>=n)
|
||||
break;
|
||||
// we got one, let's follow it until we are back to the seed
|
||||
Index k0 = r++;
|
||||
mask.coeffRef(k0) = true;
|
||||
for(Index k=indices().coeff(k0); k!=k0; k=indices().coeff(k))
|
||||
{
|
||||
mask.coeffRef(k) = true;
|
||||
res = -res;
|
||||
}
|
||||
}
|
||||
return res;
|
||||
}
|
||||
|
||||
protected:
|
||||
|
||||
@@ -262,7 +288,7 @@ class PermutationBase : public EigenBase<Derived>
|
||||
*
|
||||
* \param SizeAtCompileTime the number of rows/cols, or Dynamic
|
||||
* \param MaxSizeAtCompileTime the maximum number of rows/cols, or Dynamic. This optional parameter defaults to SizeAtCompileTime. Most of the time, you should not have to specify it.
|
||||
* \param StorageIndexType the integer type of the indices
|
||||
* \param StorageIndex the integer type of the indices
|
||||
*
|
||||
* This class represents a permutation matrix, internally stored as a vector of integers.
|
||||
*
|
||||
@@ -270,27 +296,28 @@ class PermutationBase : public EigenBase<Derived>
|
||||
*/
|
||||
|
||||
namespace internal {
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndexType>
|
||||
struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndexType> >
|
||||
: traits<Matrix<_StorageIndexType,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
|
||||
struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> >
|
||||
: traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
|
||||
{
|
||||
typedef Matrix<_StorageIndexType, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
|
||||
typedef typename IndicesType::Index Index;
|
||||
typedef _StorageIndexType StorageIndexType;
|
||||
typedef PermutationStorage StorageKind;
|
||||
typedef Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
|
||||
typedef _StorageIndex StorageIndex;
|
||||
};
|
||||
}
|
||||
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndexType>
|
||||
class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndexType> >
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
|
||||
class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> >
|
||||
{
|
||||
typedef PermutationBase<PermutationMatrix> Base;
|
||||
typedef internal::traits<PermutationMatrix> Traits;
|
||||
public:
|
||||
|
||||
typedef const PermutationMatrix& Nested;
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
typedef typename Traits::IndicesType IndicesType;
|
||||
typedef typename Traits::StorageIndexType StorageIndexType;
|
||||
typedef typename Traits::Index Index;
|
||||
typedef typename Traits::StorageIndex StorageIndex;
|
||||
#endif
|
||||
|
||||
inline PermutationMatrix()
|
||||
@@ -298,8 +325,10 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
|
||||
|
||||
/** Constructs an uninitialized permutation matrix of given size.
|
||||
*/
|
||||
inline PermutationMatrix(Index size) : m_indices(size)
|
||||
{}
|
||||
explicit inline PermutationMatrix(Index size) : m_indices(size)
|
||||
{
|
||||
eigen_internal_assert(size <= NumTraits<StorageIndex>::highest());
|
||||
}
|
||||
|
||||
/** Copy constructor. */
|
||||
template<typename OtherDerived>
|
||||
@@ -320,7 +349,7 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
|
||||
* array's size.
|
||||
*/
|
||||
template<typename Other>
|
||||
explicit inline PermutationMatrix(const MatrixBase<Other>& a_indices) : m_indices(a_indices)
|
||||
explicit inline PermutationMatrix(const MatrixBase<Other>& indices) : m_indices(indices)
|
||||
{}
|
||||
|
||||
/** Convert the Transpositions \a tr to a permutation matrix */
|
||||
@@ -368,9 +397,12 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename Other>
|
||||
PermutationMatrix(const Transpose<PermutationBase<Other> >& other)
|
||||
: m_indices(other.nestedPermutation().size())
|
||||
: m_indices(other.nestedExpression().size())
|
||||
{
|
||||
for (int i=0; i<m_indices.size();++i) m_indices.coeffRef(other.nestedPermutation().indices().coeff(i)) = i;
|
||||
eigen_internal_assert(m_indices.size() <= NumTraits<StorageIndex>::highest());
|
||||
StorageIndex end = StorageIndex(m_indices.size());
|
||||
for (StorageIndex i=0; i<end;++i)
|
||||
m_indices.coeffRef(other.nestedExpression().indices().coeff(i)) = i;
|
||||
}
|
||||
template<typename Lhs,typename Rhs>
|
||||
PermutationMatrix(internal::PermPermProduct_t, const Lhs& lhs, const Rhs& rhs)
|
||||
@@ -387,19 +419,19 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
|
||||
|
||||
|
||||
namespace internal {
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndexType, int _PacketAccess>
|
||||
struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndexType>,_PacketAccess> >
|
||||
: traits<Matrix<_StorageIndexType,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
|
||||
struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> >
|
||||
: traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
|
||||
{
|
||||
typedef Map<const Matrix<_StorageIndexType, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, _PacketAccess> IndicesType;
|
||||
typedef typename IndicesType::Index Index;
|
||||
typedef _StorageIndexType StorageIndexType;
|
||||
typedef PermutationStorage StorageKind;
|
||||
typedef Map<const Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, _PacketAccess> IndicesType;
|
||||
typedef _StorageIndex StorageIndex;
|
||||
};
|
||||
}
|
||||
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndexType, int _PacketAccess>
|
||||
class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndexType>,_PacketAccess>
|
||||
: public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndexType>,_PacketAccess> >
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
|
||||
class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess>
|
||||
: public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> >
|
||||
{
|
||||
typedef PermutationBase<Map> Base;
|
||||
typedef internal::traits<Map> Traits;
|
||||
@@ -407,15 +439,14 @@ class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageInd
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
typedef typename Traits::IndicesType IndicesType;
|
||||
typedef typename IndicesType::Scalar StorageIndexType;
|
||||
typedef typename IndicesType::Index Index;
|
||||
typedef typename IndicesType::Scalar StorageIndex;
|
||||
#endif
|
||||
|
||||
inline Map(const StorageIndexType* indicesPtr)
|
||||
inline Map(const StorageIndex* indicesPtr)
|
||||
: m_indices(indicesPtr)
|
||||
{}
|
||||
|
||||
inline Map(const StorageIndexType* indicesPtr, Index size)
|
||||
inline Map(const StorageIndex* indicesPtr, Index size)
|
||||
: m_indices(indicesPtr,size)
|
||||
{}
|
||||
|
||||
@@ -462,8 +493,6 @@ class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageInd
|
||||
* \sa class PermutationBase, class PermutationMatrix
|
||||
*/
|
||||
|
||||
struct PermutationStorage {};
|
||||
|
||||
template<typename _IndicesType> class TranspositionsWrapper;
|
||||
namespace internal {
|
||||
template<typename _IndicesType>
|
||||
@@ -471,16 +500,14 @@ struct traits<PermutationWrapper<_IndicesType> >
|
||||
{
|
||||
typedef PermutationStorage StorageKind;
|
||||
typedef typename _IndicesType::Scalar Scalar;
|
||||
typedef typename _IndicesType::Scalar StorageIndexType;
|
||||
typedef typename _IndicesType::Index Index;
|
||||
typedef typename _IndicesType::Scalar StorageIndex;
|
||||
typedef _IndicesType IndicesType;
|
||||
enum {
|
||||
RowsAtCompileTime = _IndicesType::SizeAtCompileTime,
|
||||
ColsAtCompileTime = _IndicesType::SizeAtCompileTime,
|
||||
MaxRowsAtCompileTime = IndicesType::MaxRowsAtCompileTime,
|
||||
MaxColsAtCompileTime = IndicesType::MaxColsAtCompileTime,
|
||||
Flags = 0,
|
||||
CoeffReadCost = _IndicesType::CoeffReadCost
|
||||
MaxRowsAtCompileTime = IndicesType::MaxSizeAtCompileTime,
|
||||
MaxColsAtCompileTime = IndicesType::MaxSizeAtCompileTime,
|
||||
Flags = 0
|
||||
};
|
||||
};
|
||||
}
|
||||
@@ -496,8 +523,8 @@ class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesTyp
|
||||
typedef typename Traits::IndicesType IndicesType;
|
||||
#endif
|
||||
|
||||
inline PermutationWrapper(const IndicesType& a_indices)
|
||||
: m_indices(a_indices)
|
||||
inline PermutationWrapper(const IndicesType& indices)
|
||||
: m_indices(indices)
|
||||
{}
|
||||
|
||||
/** const version of indices(). */
|
||||
@@ -509,105 +536,33 @@ class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesTyp
|
||||
typename IndicesType::Nested m_indices;
|
||||
};
|
||||
|
||||
|
||||
/** \returns the matrix with the permutation applied to the columns.
|
||||
*/
|
||||
template<typename Derived, typename PermutationDerived>
|
||||
inline const internal::permut_matrix_product_retval<PermutationDerived, Derived, OnTheRight>
|
||||
operator*(const MatrixBase<Derived>& matrix,
|
||||
const PermutationBase<PermutationDerived> &permutation)
|
||||
template<typename MatrixDerived, typename PermutationDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const Product<MatrixDerived, PermutationDerived, AliasFreeProduct>
|
||||
operator*(const MatrixBase<MatrixDerived> &matrix,
|
||||
const PermutationBase<PermutationDerived>& permutation)
|
||||
{
|
||||
return internal::permut_matrix_product_retval
|
||||
<PermutationDerived, Derived, OnTheRight>
|
||||
(permutation.derived(), matrix.derived());
|
||||
return Product<MatrixDerived, PermutationDerived, AliasFreeProduct>
|
||||
(matrix.derived(), permutation.derived());
|
||||
}
|
||||
|
||||
/** \returns the matrix with the permutation applied to the rows.
|
||||
*/
|
||||
template<typename Derived, typename PermutationDerived>
|
||||
inline const internal::permut_matrix_product_retval
|
||||
<PermutationDerived, Derived, OnTheLeft>
|
||||
template<typename PermutationDerived, typename MatrixDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const Product<PermutationDerived, MatrixDerived, AliasFreeProduct>
|
||||
operator*(const PermutationBase<PermutationDerived> &permutation,
|
||||
const MatrixBase<Derived>& matrix)
|
||||
const MatrixBase<MatrixDerived>& matrix)
|
||||
{
|
||||
return internal::permut_matrix_product_retval
|
||||
<PermutationDerived, Derived, OnTheLeft>
|
||||
(permutation.derived(), matrix.derived());
|
||||
return Product<PermutationDerived, MatrixDerived, AliasFreeProduct>
|
||||
(permutation.derived(), matrix.derived());
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
|
||||
struct traits<permut_matrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
|
||||
{
|
||||
typedef typename MatrixType::PlainObject ReturnType;
|
||||
};
|
||||
|
||||
template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
|
||||
struct permut_matrix_product_retval
|
||||
: public ReturnByValue<permut_matrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
|
||||
{
|
||||
typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
|
||||
typedef typename MatrixType::Index Index;
|
||||
|
||||
permut_matrix_product_retval(const PermutationType& perm, const MatrixType& matrix)
|
||||
: m_permutation(perm), m_matrix(matrix)
|
||||
{}
|
||||
|
||||
inline Index rows() const { return m_matrix.rows(); }
|
||||
inline Index cols() const { return m_matrix.cols(); }
|
||||
|
||||
template<typename Dest> inline void evalTo(Dest& dst) const
|
||||
{
|
||||
const Index n = Side==OnTheLeft ? rows() : cols();
|
||||
// FIXME we need an is_same for expression that is not sensitive to constness. For instance
|
||||
// is_same_xpr<Block<const Matrix>, Block<Matrix> >::value should be true.
|
||||
if(is_same<MatrixTypeNestedCleaned,Dest>::value && extract_data(dst) == extract_data(m_matrix))
|
||||
{
|
||||
// apply the permutation inplace
|
||||
Matrix<bool,PermutationType::RowsAtCompileTime,1,0,PermutationType::MaxRowsAtCompileTime> mask(m_permutation.size());
|
||||
mask.fill(false);
|
||||
Index r = 0;
|
||||
while(r < m_permutation.size())
|
||||
{
|
||||
// search for the next seed
|
||||
while(r<m_permutation.size() && mask[r]) r++;
|
||||
if(r>=m_permutation.size())
|
||||
break;
|
||||
// we got one, let's follow it until we are back to the seed
|
||||
Index k0 = r++;
|
||||
Index kPrev = k0;
|
||||
mask.coeffRef(k0) = true;
|
||||
for(Index k=m_permutation.indices().coeff(k0); k!=k0; k=m_permutation.indices().coeff(k))
|
||||
{
|
||||
Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>(dst, k)
|
||||
.swap(Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>
|
||||
(dst,((Side==OnTheLeft) ^ Transposed) ? k0 : kPrev));
|
||||
|
||||
mask.coeffRef(k) = true;
|
||||
kPrev = k;
|
||||
}
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
for(int i = 0; i < n; ++i)
|
||||
{
|
||||
Block<Dest, Side==OnTheLeft ? 1 : Dest::RowsAtCompileTime, Side==OnTheRight ? 1 : Dest::ColsAtCompileTime>
|
||||
(dst, ((Side==OnTheLeft) ^ Transposed) ? m_permutation.indices().coeff(i) : i)
|
||||
|
||||
=
|
||||
|
||||
Block<const MatrixTypeNestedCleaned,Side==OnTheLeft ? 1 : MatrixType::RowsAtCompileTime,Side==OnTheRight ? 1 : MatrixType::ColsAtCompileTime>
|
||||
(m_matrix, ((Side==OnTheRight) ^ Transposed) ? m_permutation.indices().coeff(i) : i);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
protected:
|
||||
const PermutationType& m_permutation;
|
||||
typename MatrixType::Nested m_matrix;
|
||||
};
|
||||
|
||||
/* Template partial specialization for transposed/inverse permutations */
|
||||
|
||||
template<typename Derived>
|
||||
@@ -617,6 +572,8 @@ struct traits<Transpose<PermutationBase<Derived> > >
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
// TODO: the specificties should be handled by the evaluator,
|
||||
// at the very least we should only specialize TransposeImpl
|
||||
template<typename Derived>
|
||||
class Transpose<PermutationBase<Derived> >
|
||||
: public EigenBase<Transpose<PermutationBase<Derived> > >
|
||||
@@ -631,26 +588,26 @@ class Transpose<PermutationBase<Derived> >
|
||||
typedef typename Derived::DenseMatrixType DenseMatrixType;
|
||||
enum {
|
||||
Flags = Traits::Flags,
|
||||
CoeffReadCost = Traits::CoeffReadCost,
|
||||
RowsAtCompileTime = Traits::RowsAtCompileTime,
|
||||
ColsAtCompileTime = Traits::ColsAtCompileTime,
|
||||
MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime,
|
||||
MaxColsAtCompileTime = Traits::MaxColsAtCompileTime
|
||||
};
|
||||
typedef typename Traits::Scalar Scalar;
|
||||
typedef typename Traits::StorageIndex StorageIndex;
|
||||
#endif
|
||||
|
||||
Transpose(const PermutationType& p) : m_permutation(p) {}
|
||||
|
||||
inline int rows() const { return m_permutation.rows(); }
|
||||
inline int cols() const { return m_permutation.cols(); }
|
||||
inline Index rows() const { return m_permutation.rows(); }
|
||||
inline Index cols() const { return m_permutation.cols(); }
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename DenseDerived>
|
||||
void evalTo(MatrixBase<DenseDerived>& other) const
|
||||
{
|
||||
other.setZero();
|
||||
for (int i=0; i<rows();++i)
|
||||
for (Index i=0; i<rows();++i)
|
||||
other.coeffRef(i, m_permutation.indices().coeff(i)) = typename DenseDerived::Scalar(1);
|
||||
}
|
||||
#endif
|
||||
@@ -663,22 +620,22 @@ class Transpose<PermutationBase<Derived> >
|
||||
/** \returns the matrix with the inverse permutation applied to the columns.
|
||||
*/
|
||||
template<typename OtherDerived> friend
|
||||
inline const internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheRight, true>
|
||||
const Product<OtherDerived, Transpose, AliasFreeProduct>
|
||||
operator*(const MatrixBase<OtherDerived>& matrix, const Transpose& trPerm)
|
||||
{
|
||||
return internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheRight, true>(trPerm.m_permutation, matrix.derived());
|
||||
return Product<OtherDerived, Transpose, AliasFreeProduct>(matrix.derived(), trPerm.derived());
|
||||
}
|
||||
|
||||
/** \returns the matrix with the inverse permutation applied to the rows.
|
||||
*/
|
||||
template<typename OtherDerived>
|
||||
inline const internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheLeft, true>
|
||||
const Product<Transpose, OtherDerived, AliasFreeProduct>
|
||||
operator*(const MatrixBase<OtherDerived>& matrix) const
|
||||
{
|
||||
return internal::permut_matrix_product_retval<PermutationType, OtherDerived, OnTheLeft, true>(m_permutation, matrix.derived());
|
||||
return Product<Transpose, OtherDerived, AliasFreeProduct>(*this, matrix.derived());
|
||||
}
|
||||
|
||||
const PermutationType& nestedPermutation() const { return m_permutation; }
|
||||
const PermutationType& nestedExpression() const { return m_permutation; }
|
||||
|
||||
protected:
|
||||
const PermutationType& m_permutation;
|
||||
@@ -690,6 +647,12 @@ const PermutationWrapper<const Derived> MatrixBase<Derived>::asPermutation() con
|
||||
return derived();
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<> struct AssignmentKind<DenseShape,PermutationShape> { typedef EigenBase2EigenBase Kind; };
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_PERMUTATIONMATRIX_H
|
||||
|
||||
@@ -69,8 +69,9 @@ template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct m
|
||||
#ifdef EIGEN_PARSED_BY_DOXYGEN
|
||||
namespace internal {
|
||||
|
||||
// this is a warkaround to doxygen not being able to understand the inheritence logic
|
||||
// this is a workaround to doxygen not being able to understand the inheritance logic
|
||||
// when it is hidden by the dense_xpr_base helper struct.
|
||||
/** This class is just a workaround for Doxygen and it does not not actually exist. */
|
||||
template<typename Derived> struct dense_xpr_base_dispatcher_for_doxygen;// : public MatrixBase<Derived> {};
|
||||
/** This class is just a workaround for Doxygen and it does not not actually exist. */
|
||||
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
|
||||
@@ -95,8 +96,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
typedef typename internal::dense_xpr_base<Derived>::type Base;
|
||||
|
||||
typedef typename internal::traits<Derived>::StorageKind StorageKind;
|
||||
typedef typename internal::traits<Derived>::Index Index;
|
||||
typedef typename internal::traits<Derived>::Scalar Scalar;
|
||||
|
||||
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
|
||||
typedef typename NumTraits<Scalar>::Real RealScalar;
|
||||
typedef Derived DenseType;
|
||||
@@ -115,20 +116,23 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
typedef Eigen::Map<Derived, Unaligned> MapType;
|
||||
friend class Eigen::Map<const Derived, Unaligned>;
|
||||
typedef const Eigen::Map<const Derived, Unaligned> ConstMapType;
|
||||
friend class Eigen::Map<Derived, Aligned>;
|
||||
typedef Eigen::Map<Derived, Aligned> AlignedMapType;
|
||||
friend class Eigen::Map<const Derived, Aligned>;
|
||||
typedef const Eigen::Map<const Derived, Aligned> ConstAlignedMapType;
|
||||
#if EIGEN_MAX_ALIGN_BYTES>0
|
||||
// for EIGEN_MAX_ALIGN_BYTES==0, AlignedMax==Unaligned, and many compilers generate warnings for friend-ing a class twice.
|
||||
friend class Eigen::Map<Derived, AlignedMax>;
|
||||
friend class Eigen::Map<const Derived, AlignedMax>;
|
||||
#endif
|
||||
typedef Eigen::Map<Derived, AlignedMax> AlignedMapType;
|
||||
typedef const Eigen::Map<const Derived, AlignedMax> ConstAlignedMapType;
|
||||
template<typename StrideType> struct StridedMapType { typedef Eigen::Map<Derived, Unaligned, StrideType> type; };
|
||||
template<typename StrideType> struct StridedConstMapType { typedef Eigen::Map<const Derived, Unaligned, StrideType> type; };
|
||||
template<typename StrideType> struct StridedAlignedMapType { typedef Eigen::Map<Derived, Aligned, StrideType> type; };
|
||||
template<typename StrideType> struct StridedConstAlignedMapType { typedef Eigen::Map<const Derived, Aligned, StrideType> type; };
|
||||
template<typename StrideType> struct StridedAlignedMapType { typedef Eigen::Map<Derived, AlignedMax, StrideType> type; };
|
||||
template<typename StrideType> struct StridedConstAlignedMapType { typedef Eigen::Map<const Derived, AlignedMax, StrideType> type; };
|
||||
|
||||
protected:
|
||||
DenseStorage<Scalar, Base::MaxSizeAtCompileTime, Base::RowsAtCompileTime, Base::ColsAtCompileTime, Options> m_storage;
|
||||
|
||||
public:
|
||||
enum { NeedsToAlign = SizeAtCompileTime != Dynamic && (internal::traits<Derived>::Flags & AlignedBit) != 0 };
|
||||
enum { NeedsToAlign = (SizeAtCompileTime != Dynamic) && (internal::traits<Derived>::Alignment>0) };
|
||||
EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -221,11 +225,11 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
}
|
||||
|
||||
/** \returns a const pointer to the data array of this matrix */
|
||||
EIGEN_STRONG_INLINE const Scalar *data() const
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar *data() const
|
||||
{ return m_storage.data(); }
|
||||
|
||||
/** \returns a pointer to the data array of this matrix */
|
||||
EIGEN_STRONG_INLINE Scalar *data()
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar *data()
|
||||
{ return m_storage.data(); }
|
||||
|
||||
/** Resizes \c *this to a \a rows x \a cols matrix.
|
||||
@@ -245,22 +249,22 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
* \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t)
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void resize(Index nbRows, Index nbCols)
|
||||
EIGEN_STRONG_INLINE void resize(Index rows, Index cols)
|
||||
{
|
||||
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);
|
||||
eigen_assert( EIGEN_IMPLIES(RowsAtCompileTime!=Dynamic,rows==RowsAtCompileTime)
|
||||
&& EIGEN_IMPLIES(ColsAtCompileTime!=Dynamic,cols==ColsAtCompileTime)
|
||||
&& EIGEN_IMPLIES(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic,rows<=MaxRowsAtCompileTime)
|
||||
&& EIGEN_IMPLIES(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic,cols<=MaxColsAtCompileTime)
|
||||
&& rows>=0 && cols>=0 && "Invalid sizes when resizing a matrix or array.");
|
||||
internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(rows, cols);
|
||||
#ifdef EIGEN_INITIALIZE_COEFFS
|
||||
Index size = nbRows*nbCols;
|
||||
Index size = rows*cols;
|
||||
bool size_changed = size != this->size();
|
||||
m_storage.resize(size, nbRows, nbCols);
|
||||
m_storage.resize(size, rows, cols);
|
||||
if(size_changed) EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
|
||||
#else
|
||||
internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(nbRows, nbCols);
|
||||
m_storage.resize(nbRows*nbCols, nbRows, nbCols);
|
||||
internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(rows, cols);
|
||||
m_storage.resize(rows*cols, rows, cols);
|
||||
#endif
|
||||
}
|
||||
|
||||
@@ -301,9 +305,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
* \sa resize(Index,Index)
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline void resize(NoChange_t, Index nbCols)
|
||||
inline void resize(NoChange_t, Index cols)
|
||||
{
|
||||
resize(rows(), nbCols);
|
||||
resize(rows(), cols);
|
||||
}
|
||||
|
||||
/** Resizes the matrix, changing only the number of rows. For the parameter of type NoChange_t, just pass the special value \c NoChange
|
||||
@@ -315,9 +319,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
* \sa resize(Index,Index)
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline void resize(Index nbRows, NoChange_t)
|
||||
inline void resize(Index rows, NoChange_t)
|
||||
{
|
||||
resize(nbRows, cols());
|
||||
resize(rows, cols());
|
||||
}
|
||||
|
||||
/** Resizes \c *this to have the same dimensions as \a other.
|
||||
@@ -357,9 +361,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
* appended to the matrix they will be uninitialized.
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, Index nbCols)
|
||||
EIGEN_STRONG_INLINE void conservativeResize(Index rows, Index cols)
|
||||
{
|
||||
internal::conservative_resize_like_impl<Derived>::run(*this, nbRows, nbCols);
|
||||
internal::conservative_resize_like_impl<Derived>::run(*this, rows, cols);
|
||||
}
|
||||
|
||||
/** Resizes the matrix to \a rows x \a cols while leaving old values untouched.
|
||||
@@ -370,10 +374,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
* In case the matrix is growing, new rows will be uninitialized.
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, NoChange_t)
|
||||
EIGEN_STRONG_INLINE void conservativeResize(Index rows, NoChange_t)
|
||||
{
|
||||
// Note: see the comment in conservativeResize(Index,Index)
|
||||
conservativeResize(nbRows, cols());
|
||||
conservativeResize(rows, cols());
|
||||
}
|
||||
|
||||
/** Resizes the matrix to \a rows x \a cols while leaving old values untouched.
|
||||
@@ -384,10 +388,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
* In case the matrix is growing, new columns will be uninitialized.
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index nbCols)
|
||||
EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index cols)
|
||||
{
|
||||
// Note: see the comment in conservativeResize(Index,Index)
|
||||
conservativeResize(rows(), nbCols);
|
||||
conservativeResize(rows(), cols);
|
||||
}
|
||||
|
||||
/** Resizes the vector to \a size while retaining old values.
|
||||
@@ -457,7 +461,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
// FIXME is it still needed ?
|
||||
/** \internal */
|
||||
EIGEN_DEVICE_FUNC
|
||||
PlainObjectBase(internal::constructor_without_unaligned_array_assert)
|
||||
explicit PlainObjectBase(internal::constructor_without_unaligned_array_assert)
|
||||
: m_storage(internal::constructor_without_unaligned_array_assert())
|
||||
{
|
||||
// _check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
|
||||
@@ -480,9 +484,13 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
}
|
||||
#endif
|
||||
|
||||
/** Copy constructor */
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE PlainObjectBase(Index a_size, Index nbRows, Index nbCols)
|
||||
: m_storage(a_size, nbRows, nbCols)
|
||||
EIGEN_STRONG_INLINE PlainObjectBase(const PlainObjectBase& other)
|
||||
: Base(), m_storage(other.m_storage) { }
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE PlainObjectBase(Index size, Index rows, Index cols)
|
||||
: m_storage(size, rows, cols)
|
||||
{
|
||||
// _check_template_params();
|
||||
// EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
|
||||
@@ -499,15 +507,36 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
return this->derived();
|
||||
}
|
||||
|
||||
/** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
|
||||
/** \sa PlainObjectBase::operator=(const EigenBase<OtherDerived>&) */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE PlainObjectBase(const DenseBase<OtherDerived> &other)
|
||||
: m_storage()
|
||||
{
|
||||
_check_template_params();
|
||||
resizeLike(other);
|
||||
_set_noalias(other);
|
||||
}
|
||||
|
||||
/** \sa PlainObjectBase::operator=(const EigenBase<OtherDerived>&) */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE PlainObjectBase(const EigenBase<OtherDerived> &other)
|
||||
: m_storage(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
|
||||
: m_storage()
|
||||
{
|
||||
_check_template_params();
|
||||
internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(other.derived().rows(), other.derived().cols());
|
||||
Base::operator=(other.derived());
|
||||
resizeLike(other);
|
||||
*this = other.derived();
|
||||
}
|
||||
/** \brief Copy constructor with in-place evaluation */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE PlainObjectBase(const ReturnByValue<OtherDerived>& other)
|
||||
{
|
||||
_check_template_params();
|
||||
// FIXME this does not automatically transpose vectors if necessary
|
||||
resize(other.rows(), other.cols());
|
||||
other.evalTo(this->derived());
|
||||
}
|
||||
|
||||
/** \name Map
|
||||
@@ -639,22 +668,16 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
*
|
||||
* \internal
|
||||
*/
|
||||
// aliasing is dealt once in internall::call_assignment
|
||||
// so at this stage we have to assume aliasing... and resising has to be done later.
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE Derived& _set(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
_set_selector(other.derived(), typename internal::conditional<static_cast<bool>(int(OtherDerived::Flags) & EvalBeforeAssigningBit), internal::true_type, internal::false_type>::type());
|
||||
internal::call_assignment(this->derived(), other.derived());
|
||||
return this->derived();
|
||||
}
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const internal::true_type&) { _set_noalias(other.eval()); }
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const internal::false_type&) { _set_noalias(other); }
|
||||
|
||||
/** \internal Like _set() but additionally makes the assumption that no aliasing effect can happen (which
|
||||
* is the case when creating a new matrix) so one can enforce lazy evaluation.
|
||||
*
|
||||
@@ -669,17 +692,18 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
//_resize_to_match(other);
|
||||
// the 'false' below means to enforce lazy evaluation. We don't use lazyAssign() because
|
||||
// it wouldn't allow to copy a row-vector into a column-vector.
|
||||
return internal::assign_selector<Derived,OtherDerived,false>::run(this->derived(), other.derived());
|
||||
internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar>());
|
||||
return this->derived();
|
||||
}
|
||||
|
||||
template<typename T0, typename T1>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _init2(Index nbRows, Index nbCols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
|
||||
EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, 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)
|
||||
resize(nbRows,nbCols);
|
||||
resize(rows,cols);
|
||||
}
|
||||
|
||||
template<typename T0, typename T1>
|
||||
@@ -704,9 +728,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
m_storage.data()[1] = Scalar(val1);
|
||||
}
|
||||
|
||||
// The argument is convertible to the Index type and we either have a non 1x1 Matrix, or a dynamic-sized Array,
|
||||
// then the argument is meant to be the size of the object.
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _init1(Index size, typename internal::enable_if<Base::SizeAtCompileTime!=1 || !internal::is_convertible<T, Scalar>::value,T>::type* = 0)
|
||||
EIGEN_STRONG_INLINE void _init1(Index size, typename internal::enable_if< (Base::SizeAtCompileTime!=1 || !internal::is_convertible<T, Scalar>::value)
|
||||
&& ((!internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value || Base::SizeAtCompileTime==Dynamic)),T>::type* = 0)
|
||||
{
|
||||
// NOTE MSVC 2008 complains if we directly put bool(NumTraits<T>::IsInteger) as the EIGEN_STATIC_ASSERT argument.
|
||||
const bool is_integer = NumTraits<T>::IsInteger;
|
||||
@@ -714,6 +741,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
|
||||
resize(size);
|
||||
}
|
||||
|
||||
// We have a 1x1 matrix/array => the argument is interpreted as the value of the unique coefficient (case where scalar type can be implicitely converted)
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _init1(const Scalar& val0, typename internal::enable_if<Base::SizeAtCompileTime==1 && internal::is_convertible<T, Scalar>::value,T>::type* = 0)
|
||||
@@ -722,6 +751,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
m_storage.data()[0] = val0;
|
||||
}
|
||||
|
||||
// We have a 1x1 matrix/array => the argument is interpreted as the value of the unique coefficient (case where scalar type match the index type)
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _init1(const Index& val0,
|
||||
@@ -734,18 +764,21 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
m_storage.data()[0] = Scalar(val0);
|
||||
}
|
||||
|
||||
// Initialize a fixed size matrix from a pointer to raw data
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _init1(const Scalar* data){
|
||||
this->_set_noalias(ConstMapType(data));
|
||||
}
|
||||
|
||||
// Initialize an arbitrary matrix from a dense expression
|
||||
template<typename T, typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _init1(const DenseBase<OtherDerived>& other){
|
||||
this->_set_noalias(other);
|
||||
}
|
||||
|
||||
// Initialize an arbitrary matrix from a generic Eigen expression
|
||||
template<typename T, typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _init1(const EigenBase<OtherDerived>& other){
|
||||
@@ -766,23 +799,58 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
{
|
||||
this->derived() = r;
|
||||
}
|
||||
|
||||
|
||||
// For fixed -size arrays:
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _init1(const Scalar& val0,
|
||||
typename internal::enable_if< Base::SizeAtCompileTime!=Dynamic
|
||||
&& Base::SizeAtCompileTime!=1
|
||||
&& internal::is_convertible<T, Scalar>::value
|
||||
&& internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T>::type* = 0)
|
||||
{
|
||||
Base::setConstant(val0);
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE void _init1(const Index& val0,
|
||||
typename internal::enable_if< (!internal::is_same<Index,Scalar>::value)
|
||||
&& (internal::is_same<Index,T>::value)
|
||||
&& Base::SizeAtCompileTime!=Dynamic
|
||||
&& Base::SizeAtCompileTime!=1
|
||||
&& internal::is_convertible<T, Scalar>::value
|
||||
&& internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T*>::type* = 0)
|
||||
{
|
||||
Base::setConstant(val0);
|
||||
}
|
||||
|
||||
template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers>
|
||||
friend struct internal::matrix_swap_impl;
|
||||
|
||||
/** \internal generic implementation of swap for dense storage since for dynamic-sized matrices of same type it is enough to swap the
|
||||
* data pointers.
|
||||
public:
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
/** \internal
|
||||
* \brief Override DenseBase::swap() since for dynamic-sized matrices
|
||||
* of same type it is enough to swap the data pointers.
|
||||
*/
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void _swap(DenseBase<OtherDerived> const & other)
|
||||
void swap(DenseBase<OtherDerived> & other)
|
||||
{
|
||||
enum { SwapPointers = internal::is_same<Derived, OtherDerived>::value && Base::SizeAtCompileTime==Dynamic };
|
||||
internal::matrix_swap_impl<Derived, OtherDerived, bool(SwapPointers)>::run(this->derived(), other.const_cast_derived());
|
||||
internal::matrix_swap_impl<Derived, OtherDerived, bool(SwapPointers)>::run(this->derived(), other.derived());
|
||||
}
|
||||
|
||||
public:
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
|
||||
/** \internal
|
||||
* \brief const version forwarded to DenseBase::swap
|
||||
*/
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void swap(DenseBase<OtherDerived> const & other)
|
||||
{ Base::swap(other.derived()); }
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE void _check_template_params()
|
||||
{
|
||||
@@ -797,10 +865,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
|
||||
&& (Options & (DontAlign|RowMajor)) == Options),
|
||||
INVALID_MATRIX_TEMPLATE_PARAMETERS)
|
||||
}
|
||||
#endif
|
||||
|
||||
private:
|
||||
enum { ThisConstantIsPrivateInPlainObjectBase };
|
||||
enum { IsPlainObjectBase = 1 };
|
||||
#endif
|
||||
};
|
||||
|
||||
namespace internal {
|
||||
@@ -808,7 +875,6 @@ namespace internal {
|
||||
template <typename Derived, typename OtherDerived, bool IsVector>
|
||||
struct conservative_resize_like_impl
|
||||
{
|
||||
typedef typename Derived::Index Index;
|
||||
static void run(DenseBase<Derived>& _this, Index rows, Index cols)
|
||||
{
|
||||
if (_this.rows() == rows && _this.cols() == cols) return;
|
||||
@@ -874,7 +940,6 @@ struct conservative_resize_like_impl<Derived,OtherDerived,true>
|
||||
{
|
||||
using conservative_resize_like_impl<Derived,OtherDerived,false>::run;
|
||||
|
||||
typedef typename Derived::Index Index;
|
||||
static void run(DenseBase<Derived>& _this, Index size)
|
||||
{
|
||||
const Index new_rows = Derived::RowsAtCompileTime==1 ? 1 : size;
|
||||
|
||||
@@ -12,8 +12,7 @@
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
template<typename Lhs, typename Rhs> class Product;
|
||||
template<typename Lhs, typename Rhs, typename StorageKind> class ProductImpl;
|
||||
template<typename Lhs, typename Rhs, int Option, typename StorageKind> class ProductImpl;
|
||||
|
||||
/** \class Product
|
||||
* \ingroup Core_Module
|
||||
@@ -24,53 +23,121 @@ template<typename Lhs, typename Rhs, typename StorageKind> class ProductImpl;
|
||||
* \param Rhs the type of the right-hand side expression
|
||||
*
|
||||
* This class represents an expression of the product of two arbitrary matrices.
|
||||
*
|
||||
* The other template parameters are:
|
||||
* \tparam Option can be DefaultProduct, AliasFreeProduct, or LazyProduct
|
||||
*
|
||||
*/
|
||||
|
||||
// Use ProductReturnType to get correct traits, in particular vectorization flags
|
||||
|
||||
namespace internal {
|
||||
template<typename Lhs, typename Rhs>
|
||||
struct traits<Product<Lhs, Rhs> >
|
||||
: 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
|
||||
|
||||
// Determine the scalar of Product<Lhs, Rhs>. This is normally the same as Lhs::Scalar times
|
||||
// Rhs::Scalar, but product with permutation matrices inherit the scalar of the other factor.
|
||||
template<typename Lhs, typename Rhs, typename LhsShape = typename evaluator_traits<Lhs>::Shape,
|
||||
typename RhsShape = typename evaluator_traits<Rhs>::Shape >
|
||||
struct product_result_scalar
|
||||
{
|
||||
typedef typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType Scalar;
|
||||
};
|
||||
|
||||
template<typename Lhs, typename Rhs, typename RhsShape>
|
||||
struct product_result_scalar<Lhs, Rhs, PermutationShape, RhsShape>
|
||||
{
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
};
|
||||
|
||||
template<typename Lhs, typename Rhs, typename LhsShape>
|
||||
struct product_result_scalar<Lhs, Rhs, LhsShape, PermutationShape>
|
||||
{
|
||||
typedef typename Lhs::Scalar Scalar;
|
||||
};
|
||||
|
||||
template<typename Lhs, typename Rhs, typename RhsShape>
|
||||
struct product_result_scalar<Lhs, Rhs, TranspositionsShape, RhsShape>
|
||||
{
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
};
|
||||
|
||||
template<typename Lhs, typename Rhs, typename LhsShape>
|
||||
struct product_result_scalar<Lhs, Rhs, LhsShape, TranspositionsShape>
|
||||
{
|
||||
typedef typename Lhs::Scalar Scalar;
|
||||
};
|
||||
|
||||
template<typename Lhs, typename Rhs, int Option>
|
||||
struct traits<Product<Lhs, Rhs, Option> >
|
||||
{
|
||||
typedef typename remove_all<Lhs>::type LhsCleaned;
|
||||
typedef typename remove_all<Rhs>::type RhsCleaned;
|
||||
typedef traits<LhsCleaned> LhsTraits;
|
||||
typedef traits<RhsCleaned> RhsTraits;
|
||||
|
||||
typedef MatrixXpr XprKind;
|
||||
|
||||
typedef typename product_result_scalar<LhsCleaned,RhsCleaned>::Scalar Scalar;
|
||||
typedef typename product_promote_storage_type<typename LhsTraits::StorageKind,
|
||||
typename RhsTraits::StorageKind,
|
||||
internal::product_type<Lhs,Rhs>::ret>::ret StorageKind;
|
||||
typedef typename promote_index_type<typename LhsTraits::StorageIndex,
|
||||
typename RhsTraits::StorageIndex>::type StorageIndex;
|
||||
|
||||
enum {
|
||||
Flags = traits<typename ProductReturnType<Lhs, Rhs>::Type>::Flags & ~(EvalBeforeNestingBit | DirectAccessBit)
|
||||
RowsAtCompileTime = LhsTraits::RowsAtCompileTime,
|
||||
ColsAtCompileTime = RhsTraits::ColsAtCompileTime,
|
||||
MaxRowsAtCompileTime = LhsTraits::MaxRowsAtCompileTime,
|
||||
MaxColsAtCompileTime = RhsTraits::MaxColsAtCompileTime,
|
||||
|
||||
// FIXME: only needed by GeneralMatrixMatrixTriangular
|
||||
InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(LhsTraits::ColsAtCompileTime, RhsTraits::RowsAtCompileTime),
|
||||
|
||||
// The storage order is somewhat arbitrary here. The correct one will be determined through the evaluator.
|
||||
Flags = (MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1) ? RowMajorBit
|
||||
: (MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1) ? 0
|
||||
: ( ((LhsTraits::Flags&NoPreferredStorageOrderBit) && (RhsTraits::Flags&RowMajorBit))
|
||||
|| ((RhsTraits::Flags&NoPreferredStorageOrderBit) && (LhsTraits::Flags&RowMajorBit)) ) ? RowMajorBit
|
||||
: NoPreferredStorageOrderBit
|
||||
};
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
class Product : public ProductImpl<Lhs,Rhs,typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
|
||||
typename internal::traits<Rhs>::StorageKind>::ret>
|
||||
template<typename _Lhs, typename _Rhs, int Option>
|
||||
class Product : public ProductImpl<_Lhs,_Rhs,Option,
|
||||
typename internal::product_promote_storage_type<typename internal::traits<_Lhs>::StorageKind,
|
||||
typename internal::traits<_Rhs>::StorageKind,
|
||||
internal::product_type<_Lhs,_Rhs>::ret>::ret>
|
||||
{
|
||||
public:
|
||||
|
||||
typedef _Lhs Lhs;
|
||||
typedef _Rhs Rhs;
|
||||
|
||||
typedef typename ProductImpl<
|
||||
Lhs, Rhs,
|
||||
typename internal::promote_storage_type<typename Lhs::StorageKind,
|
||||
typename Rhs::StorageKind>::ret>::Base Base;
|
||||
Lhs, Rhs, Option,
|
||||
typename internal::product_promote_storage_type<typename internal::traits<Lhs>::StorageKind,
|
||||
typename internal::traits<Rhs>::StorageKind,
|
||||
internal::product_type<Lhs,Rhs>::ret>::ret>::Base Base;
|
||||
EIGEN_GENERIC_PUBLIC_INTERFACE(Product)
|
||||
|
||||
typedef typename Lhs::Nested LhsNested;
|
||||
typedef typename Rhs::Nested RhsNested;
|
||||
typedef typename internal::ref_selector<Lhs>::type LhsNested;
|
||||
typedef typename internal::ref_selector<Rhs>::type RhsNested;
|
||||
typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
|
||||
typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
|
||||
|
||||
Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs)
|
||||
EIGEN_DEVICE_FUNC Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs)
|
||||
{
|
||||
eigen_assert(lhs.cols() == rhs.rows()
|
||||
&& "invalid matrix product"
|
||||
&& "if you wanted a coeff-wise or a dot product use the respective explicit functions");
|
||||
}
|
||||
|
||||
inline Index rows() const { return m_lhs.rows(); }
|
||||
inline Index cols() const { return m_rhs.cols(); }
|
||||
EIGEN_DEVICE_FUNC inline Index rows() const { return m_lhs.rows(); }
|
||||
EIGEN_DEVICE_FUNC inline Index cols() const { return m_rhs.cols(); }
|
||||
|
||||
const LhsNestedCleaned& lhs() const { return m_lhs; }
|
||||
const RhsNestedCleaned& rhs() const { return m_rhs; }
|
||||
EIGEN_DEVICE_FUNC const LhsNestedCleaned& lhs() const { return m_lhs; }
|
||||
EIGEN_DEVICE_FUNC const RhsNestedCleaned& rhs() const { return m_rhs; }
|
||||
|
||||
protected:
|
||||
|
||||
@@ -78,14 +145,76 @@ class Product : public ProductImpl<Lhs,Rhs,typename internal::promote_storage_ty
|
||||
RhsNested m_rhs;
|
||||
};
|
||||
|
||||
template<typename Lhs, typename Rhs>
|
||||
class ProductImpl<Lhs,Rhs,Dense> : public internal::dense_xpr_base<Product<Lhs,Rhs> >::type
|
||||
{
|
||||
typedef Product<Lhs, Rhs> Derived;
|
||||
public:
|
||||
namespace internal {
|
||||
|
||||
template<typename Lhs, typename Rhs, int Option, int ProductTag = internal::product_type<Lhs,Rhs>::ret>
|
||||
class dense_product_base
|
||||
: public internal::dense_xpr_base<Product<Lhs,Rhs,Option> >::type
|
||||
{};
|
||||
|
||||
typedef typename internal::dense_xpr_base<Product<Lhs, Rhs> >::type Base;
|
||||
/** Convertion to scalar for inner-products */
|
||||
template<typename Lhs, typename Rhs, int Option>
|
||||
class dense_product_base<Lhs, Rhs, Option, InnerProduct>
|
||||
: public internal::dense_xpr_base<Product<Lhs,Rhs,Option> >::type
|
||||
{
|
||||
typedef Product<Lhs,Rhs,Option> ProductXpr;
|
||||
typedef typename internal::dense_xpr_base<ProductXpr>::type Base;
|
||||
public:
|
||||
using Base::derived;
|
||||
typedef typename Base::Scalar Scalar;
|
||||
|
||||
operator const Scalar() const
|
||||
{
|
||||
return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace internal
|
||||
|
||||
// Generic API dispatcher
|
||||
template<typename Lhs, typename Rhs, int Option, typename StorageKind>
|
||||
class ProductImpl : public internal::generic_xpr_base<Product<Lhs,Rhs,Option>, MatrixXpr, StorageKind>::type
|
||||
{
|
||||
public:
|
||||
typedef typename internal::generic_xpr_base<Product<Lhs,Rhs,Option>, MatrixXpr, StorageKind>::type Base;
|
||||
};
|
||||
|
||||
template<typename Lhs, typename Rhs, int Option>
|
||||
class ProductImpl<Lhs,Rhs,Option,Dense>
|
||||
: public internal::dense_product_base<Lhs,Rhs,Option>
|
||||
{
|
||||
typedef Product<Lhs, Rhs, Option> Derived;
|
||||
|
||||
public:
|
||||
|
||||
typedef typename internal::dense_product_base<Lhs, Rhs, Option> Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
|
||||
protected:
|
||||
enum {
|
||||
IsOneByOne = (RowsAtCompileTime == 1 || RowsAtCompileTime == Dynamic) &&
|
||||
(ColsAtCompileTime == 1 || ColsAtCompileTime == Dynamic),
|
||||
EnableCoeff = IsOneByOne || Option==LazyProduct
|
||||
};
|
||||
|
||||
public:
|
||||
|
||||
EIGEN_DEVICE_FUNC Scalar coeff(Index row, Index col) const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
|
||||
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );
|
||||
|
||||
return internal::evaluator<Derived>(derived()).coeff(row,col);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC Scalar coeff(Index i) const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
|
||||
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );
|
||||
|
||||
return internal::evaluator<Derived>(derived()).coeff(i);
|
||||
}
|
||||
|
||||
|
||||
};
|
||||
|
||||
/***************************************************************************
|
||||
@@ -102,6 +231,15 @@ prod(const Lhs& lhs, const Rhs& rhs)
|
||||
return Product<Lhs,Rhs>(lhs,rhs);
|
||||
}
|
||||
|
||||
/** \internal used to test the evaluator only
|
||||
*/
|
||||
template<typename Lhs,typename Rhs>
|
||||
const Product<Lhs,Rhs,LazyProduct>
|
||||
lazyprod(const Lhs& lhs, const Rhs& rhs)
|
||||
{
|
||||
return Product<Lhs,Rhs,LazyProduct>(lhs,rhs);
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_PRODUCT_H
|
||||
|
||||
@@ -1,274 +0,0 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2009-2010 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_PRODUCTBASE_H
|
||||
#define EIGEN_PRODUCTBASE_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
/** \class ProductBase
|
||||
* \ingroup Core_Module
|
||||
*
|
||||
*/
|
||||
|
||||
namespace internal {
|
||||
template<typename Derived, typename _Lhs, typename _Rhs>
|
||||
struct traits<ProductBase<Derived,_Lhs,_Rhs> >
|
||||
{
|
||||
typedef MatrixXpr XprKind;
|
||||
typedef typename remove_all<_Lhs>::type Lhs;
|
||||
typedef typename remove_all<_Rhs>::type Rhs;
|
||||
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,
|
||||
// Note that EvalBeforeNestingBit and NestByRefBit
|
||||
// are not used in practice because nested is overloaded for products
|
||||
CoeffReadCost = 0 // FIXME why is it needed ?
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
#define EIGEN_PRODUCT_PUBLIC_INTERFACE(Derived) \
|
||||
typedef ProductBase<Derived, Lhs, Rhs > Base; \
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Derived) \
|
||||
typedef typename Base::LhsNested LhsNested; \
|
||||
typedef typename Base::_LhsNested _LhsNested; \
|
||||
typedef typename Base::LhsBlasTraits LhsBlasTraits; \
|
||||
typedef typename Base::ActualLhsType ActualLhsType; \
|
||||
typedef typename Base::_ActualLhsType _ActualLhsType; \
|
||||
typedef typename Base::RhsNested RhsNested; \
|
||||
typedef typename Base::_RhsNested _RhsNested; \
|
||||
typedef typename Base::RhsBlasTraits RhsBlasTraits; \
|
||||
typedef typename Base::ActualRhsType ActualRhsType; \
|
||||
typedef typename Base::_ActualRhsType _ActualRhsType; \
|
||||
using Base::m_lhs; \
|
||||
using Base::m_rhs;
|
||||
|
||||
template<typename Derived, typename Lhs, typename Rhs>
|
||||
class ProductBase : public MatrixBase<Derived>
|
||||
{
|
||||
public:
|
||||
typedef MatrixBase<Derived> Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(ProductBase)
|
||||
|
||||
typedef typename Lhs::Nested LhsNested;
|
||||
typedef typename internal::remove_all<LhsNested>::type _LhsNested;
|
||||
typedef internal::blas_traits<_LhsNested> LhsBlasTraits;
|
||||
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
|
||||
typedef typename internal::remove_all<ActualLhsType>::type _ActualLhsType;
|
||||
typedef typename internal::traits<Lhs>::Scalar LhsScalar;
|
||||
|
||||
typedef typename Rhs::Nested RhsNested;
|
||||
typedef typename internal::remove_all<RhsNested>::type _RhsNested;
|
||||
typedef internal::blas_traits<_RhsNested> RhsBlasTraits;
|
||||
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
|
||||
typedef typename internal::remove_all<ActualRhsType>::type _ActualRhsType;
|
||||
typedef typename internal::traits<Rhs>::Scalar RhsScalar;
|
||||
|
||||
// Diagonal of a product: no need to evaluate the arguments because they are going to be evaluated only once
|
||||
typedef CoeffBasedProduct<LhsNested, RhsNested, 0> FullyLazyCoeffBaseProductType;
|
||||
|
||||
public:
|
||||
|
||||
typedef typename Base::PlainObject PlainObject;
|
||||
|
||||
ProductBase(const Lhs& a_lhs, const Rhs& a_rhs)
|
||||
: m_lhs(a_lhs), m_rhs(a_rhs)
|
||||
{
|
||||
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");
|
||||
}
|
||||
|
||||
inline Index rows() const { return m_lhs.rows(); }
|
||||
inline Index cols() const { return m_rhs.cols(); }
|
||||
|
||||
template<typename Dest>
|
||||
inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst,Scalar(1)); }
|
||||
|
||||
template<typename Dest>
|
||||
inline void addTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(1)); }
|
||||
|
||||
template<typename Dest>
|
||||
inline void subTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(-1)); }
|
||||
|
||||
template<typename Dest>
|
||||
inline void scaleAndAddTo(Dest& dst, const Scalar& alpha) const { derived().scaleAndAddTo(dst,alpha); }
|
||||
|
||||
const _LhsNested& lhs() const { return m_lhs; }
|
||||
const _RhsNested& rhs() const { return m_rhs; }
|
||||
|
||||
// Implicit conversion to the nested type (trigger the evaluation of the product)
|
||||
operator const PlainObject& () const
|
||||
{
|
||||
m_result.resize(m_lhs.rows(), m_rhs.cols());
|
||||
derived().evalTo(m_result);
|
||||
return m_result;
|
||||
}
|
||||
|
||||
const Diagonal<const FullyLazyCoeffBaseProductType,0> diagonal() const
|
||||
{ return FullyLazyCoeffBaseProductType(m_lhs, m_rhs); }
|
||||
|
||||
template<int Index>
|
||||
const Diagonal<FullyLazyCoeffBaseProductType,Index> diagonal() const
|
||||
{ return FullyLazyCoeffBaseProductType(m_lhs, m_rhs); }
|
||||
|
||||
const Diagonal<FullyLazyCoeffBaseProductType,Dynamic> diagonal(Index index) const
|
||||
{ return FullyLazyCoeffBaseProductType(m_lhs, m_rhs).diagonal(index); }
|
||||
|
||||
// restrict coeff accessors to 1x1 expressions. No need to care about mutators here since this isn't an Lvalue expression
|
||||
typename Base::CoeffReturnType coeff(Index row, Index col) const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
|
||||
eigen_assert(this->rows() == 1 && this->cols() == 1);
|
||||
Matrix<Scalar,1,1> result = *this;
|
||||
return result.coeff(row,col);
|
||||
}
|
||||
|
||||
typename Base::CoeffReturnType coeff(Index i) const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
|
||||
eigen_assert(this->rows() == 1 && this->cols() == 1);
|
||||
Matrix<Scalar,1,1> result = *this;
|
||||
return result.coeff(i);
|
||||
}
|
||||
|
||||
const Scalar& coeffRef(Index row, Index col) const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
|
||||
eigen_assert(this->rows() == 1 && this->cols() == 1);
|
||||
return derived().coeffRef(row,col);
|
||||
}
|
||||
|
||||
const Scalar& coeffRef(Index i) const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
|
||||
eigen_assert(this->rows() == 1 && this->cols() == 1);
|
||||
return derived().coeffRef(i);
|
||||
}
|
||||
|
||||
protected:
|
||||
|
||||
LhsNested m_lhs;
|
||||
RhsNested m_rhs;
|
||||
|
||||
mutable PlainObject m_result;
|
||||
};
|
||||
|
||||
// here we need to overload the nested rule for products
|
||||
// such that the nested type is a const reference to a plain matrix
|
||||
namespace internal {
|
||||
template<typename Lhs, typename Rhs, int Mode, int N, typename PlainObject>
|
||||
struct nested<GeneralProduct<Lhs,Rhs,Mode>, N, PlainObject>
|
||||
{
|
||||
typedef PlainObject const& type;
|
||||
};
|
||||
}
|
||||
|
||||
template<typename NestedProduct>
|
||||
class ScaledProduct;
|
||||
|
||||
// Note that these two operator* functions are not defined as member
|
||||
// functions of ProductBase, because, otherwise we would have to
|
||||
// define all overloads defined in MatrixBase. Furthermore, Using
|
||||
// "using Base::operator*" would not work with MSVC.
|
||||
//
|
||||
// Also note that here we accept any compatible scalar types
|
||||
template<typename Derived,typename Lhs,typename Rhs>
|
||||
const ScaledProduct<Derived>
|
||||
operator*(const ProductBase<Derived,Lhs,Rhs>& prod, const typename Derived::Scalar& x)
|
||||
{ return ScaledProduct<Derived>(prod.derived(), 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, const typename Derived::RealScalar& x)
|
||||
{ return ScaledProduct<Derived>(prod.derived(), x); }
|
||||
|
||||
|
||||
template<typename Derived,typename Lhs,typename Rhs>
|
||||
const ScaledProduct<Derived>
|
||||
operator*(const typename Derived::Scalar& x,const ProductBase<Derived,Lhs,Rhs>& prod)
|
||||
{ return ScaledProduct<Derived>(prod.derived(), 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 typename Derived::RealScalar& x,const ProductBase<Derived,Lhs,Rhs>& prod)
|
||||
{ return ScaledProduct<Derived>(prod.derived(), x); }
|
||||
|
||||
namespace internal {
|
||||
template<typename NestedProduct>
|
||||
struct traits<ScaledProduct<NestedProduct> >
|
||||
: traits<ProductBase<ScaledProduct<NestedProduct>,
|
||||
typename NestedProduct::_LhsNested,
|
||||
typename NestedProduct::_RhsNested> >
|
||||
{
|
||||
typedef typename traits<NestedProduct>::StorageKind StorageKind;
|
||||
};
|
||||
}
|
||||
|
||||
template<typename NestedProduct>
|
||||
class ScaledProduct
|
||||
: public ProductBase<ScaledProduct<NestedProduct>,
|
||||
typename NestedProduct::_LhsNested,
|
||||
typename NestedProduct::_RhsNested>
|
||||
{
|
||||
public:
|
||||
typedef ProductBase<ScaledProduct<NestedProduct>,
|
||||
typename NestedProduct::_LhsNested,
|
||||
typename NestedProduct::_RhsNested> Base;
|
||||
typedef typename Base::Scalar Scalar;
|
||||
typedef typename Base::PlainObject PlainObject;
|
||||
// EIGEN_PRODUCT_PUBLIC_INTERFACE(ScaledProduct)
|
||||
|
||||
ScaledProduct(const NestedProduct& prod, const Scalar& x)
|
||||
: Base(prod.lhs(),prod.rhs()), m_prod(prod), m_alpha(x) {}
|
||||
|
||||
template<typename Dest>
|
||||
inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst, Scalar(1)); }
|
||||
|
||||
template<typename Dest>
|
||||
inline void addTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(1)); }
|
||||
|
||||
template<typename Dest>
|
||||
inline void subTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(-1)); }
|
||||
|
||||
template<typename Dest>
|
||||
inline void scaleAndAddTo(Dest& dst, const Scalar& a_alpha) const { m_prod.derived().scaleAndAddTo(dst,a_alpha * m_alpha); }
|
||||
|
||||
const Scalar& alpha() const { return m_alpha; }
|
||||
|
||||
protected:
|
||||
const NestedProduct& m_prod;
|
||||
Scalar m_alpha;
|
||||
};
|
||||
|
||||
/** \internal
|
||||
* Overloaded to perform an efficient C = (A*B).lazy() */
|
||||
template<typename Derived>
|
||||
template<typename ProductDerived, typename Lhs, typename Rhs>
|
||||
Derived& MatrixBase<Derived>::lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other)
|
||||
{
|
||||
other.derived().evalTo(derived());
|
||||
return derived();
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_PRODUCTBASE_H
|
||||
1116
Eigen/src/Core/ProductEvaluators.h
Normal file → Executable file
1116
Eigen/src/Core/ProductEvaluators.h
Normal file → Executable file
File diff suppressed because it is too large
Load Diff
@@ -53,7 +53,7 @@ struct functor_traits<scalar_random_op<Scalar> >
|
||||
* \sa DenseBase::setRandom(), DenseBase::Random(Index), DenseBase::Random()
|
||||
*/
|
||||
template<typename Derived>
|
||||
inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
|
||||
inline const typename DenseBase<Derived>::RandomReturnType
|
||||
DenseBase<Derived>::Random(Index rows, Index cols)
|
||||
{
|
||||
return NullaryExpr(rows, cols, internal::scalar_random_op<Scalar>());
|
||||
@@ -84,7 +84,7 @@ DenseBase<Derived>::Random(Index rows, Index cols)
|
||||
* \sa DenseBase::setRandom(), DenseBase::Random(Index,Index), DenseBase::Random()
|
||||
*/
|
||||
template<typename Derived>
|
||||
inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
|
||||
inline const typename DenseBase<Derived>::RandomReturnType
|
||||
DenseBase<Derived>::Random(Index size)
|
||||
{
|
||||
return NullaryExpr(size, internal::scalar_random_op<Scalar>());
|
||||
@@ -110,7 +110,7 @@ DenseBase<Derived>::Random(Index size)
|
||||
* \sa DenseBase::setRandom(), DenseBase::Random(Index,Index), DenseBase::Random(Index)
|
||||
*/
|
||||
template<typename Derived>
|
||||
inline const CwiseNullaryOp<internal::scalar_random_op<typename internal::traits<Derived>::Scalar>, Derived>
|
||||
inline const typename DenseBase<Derived>::RandomReturnType
|
||||
DenseBase<Derived>::Random()
|
||||
{
|
||||
return NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_random_op<Scalar>());
|
||||
@@ -162,8 +162,8 @@ PlainObjectBase<Derived>::setRandom(Index newSize)
|
||||
*
|
||||
* \not_reentrant
|
||||
*
|
||||
* \param nbRows the new number of rows
|
||||
* \param nbCols the new number of columns
|
||||
* \param rows the new number of rows
|
||||
* \param cols the new number of columns
|
||||
*
|
||||
* Example: \include Matrix_setRandom_int_int.cpp
|
||||
* Output: \verbinclude Matrix_setRandom_int_int.out
|
||||
@@ -172,9 +172,9 @@ PlainObjectBase<Derived>::setRandom(Index newSize)
|
||||
*/
|
||||
template<typename Derived>
|
||||
EIGEN_STRONG_INLINE Derived&
|
||||
PlainObjectBase<Derived>::setRandom(Index nbRows, Index nbCols)
|
||||
PlainObjectBase<Derived>::setRandom(Index rows, Index cols)
|
||||
{
|
||||
resize(nbRows, nbCols);
|
||||
resize(rows, cols);
|
||||
return setRandom();
|
||||
}
|
||||
|
||||
|
||||
@@ -65,6 +65,25 @@ public:
|
||||
? CompleteUnrolling
|
||||
: NoUnrolling
|
||||
};
|
||||
|
||||
#ifdef EIGEN_DEBUG_ASSIGN
|
||||
static void debug()
|
||||
{
|
||||
std::cerr << "Xpr: " << typeid(typename Derived::XprType).name() << std::endl;
|
||||
std::cerr.setf(std::ios::hex, std::ios::basefield);
|
||||
EIGEN_DEBUG_VAR(Derived::Flags)
|
||||
std::cerr.unsetf(std::ios::hex);
|
||||
EIGEN_DEBUG_VAR(InnerMaxSize)
|
||||
EIGEN_DEBUG_VAR(PacketSize)
|
||||
EIGEN_DEBUG_VAR(MightVectorize)
|
||||
EIGEN_DEBUG_VAR(MayLinearVectorize)
|
||||
EIGEN_DEBUG_VAR(MaySliceVectorize)
|
||||
EIGEN_DEBUG_VAR(Traversal)
|
||||
EIGEN_DEBUG_VAR(UnrollingLimit)
|
||||
EIGEN_DEBUG_VAR(Unrolling)
|
||||
std::cerr << std::endl;
|
||||
}
|
||||
#endif
|
||||
};
|
||||
|
||||
/***************************************************************************
|
||||
@@ -146,7 +165,7 @@ struct redux_vec_unroller<Func, Derived, Start, 1>
|
||||
index = Start * packet_traits<typename Derived::Scalar>::size,
|
||||
outer = index / int(Derived::InnerSizeAtCompileTime),
|
||||
inner = index % int(Derived::InnerSizeAtCompileTime),
|
||||
alignment = (Derived::Flags & AlignedBit) ? Aligned : Unaligned
|
||||
alignment = Derived::Alignment
|
||||
};
|
||||
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
@@ -154,7 +173,7 @@ struct redux_vec_unroller<Func, Derived, Start, 1>
|
||||
|
||||
static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func&)
|
||||
{
|
||||
return mat.template packetByOuterInner<alignment>(outer, inner);
|
||||
return mat.template packetByOuterInner<alignment,PacketScalar>(outer, inner);
|
||||
}
|
||||
};
|
||||
|
||||
@@ -172,9 +191,8 @@ template<typename Func, typename Derived>
|
||||
struct redux_impl<Func, Derived, DefaultTraversal, NoUnrolling>
|
||||
{
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
typedef typename Derived::Index Index;
|
||||
EIGEN_DEVICE_FUNC
|
||||
static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func)
|
||||
static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func)
|
||||
{
|
||||
eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
|
||||
Scalar res;
|
||||
@@ -198,18 +216,18 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
|
||||
{
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
typedef typename packet_traits<Scalar>::type PacketScalar;
|
||||
typedef typename Derived::Index Index;
|
||||
|
||||
static Scalar run(const Derived& mat, const Func& func)
|
||||
static Scalar run(const Derived &mat, const Func& func)
|
||||
{
|
||||
const Index size = mat.size();
|
||||
eigen_assert(size && "you are using an empty matrix");
|
||||
|
||||
const Index packetSize = packet_traits<Scalar>::size;
|
||||
const Index alignedStart = internal::first_aligned(mat);
|
||||
const int packetAlignment = unpacket_traits<PacketScalar>::alignment;
|
||||
enum {
|
||||
alignment = (bool(Derived::Flags & DirectAccessBit) && bool(packet_traits<Scalar>::AlignedOnScalar)) || bool(Derived::Flags & AlignedBit)
|
||||
? Aligned : Unaligned
|
||||
alignment0 = (bool(Derived::Flags & DirectAccessBit) && bool(packet_traits<Scalar>::AlignedOnScalar)) ? int(packetAlignment) : int(Unaligned),
|
||||
alignment = EIGEN_PLAIN_ENUM_MAX(alignment0, Derived::Alignment)
|
||||
};
|
||||
const Index alignedStart = internal::first_default_aligned(mat.nestedExpression());
|
||||
const Index alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize);
|
||||
const Index alignedSize = ((size-alignedStart)/(packetSize))*(packetSize);
|
||||
const Index alignedEnd2 = alignedStart + alignedSize2;
|
||||
@@ -217,19 +235,19 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
|
||||
Scalar res;
|
||||
if(alignedSize)
|
||||
{
|
||||
PacketScalar packet_res0 = mat.template packet<alignment>(alignedStart);
|
||||
PacketScalar packet_res0 = mat.template packet<alignment,PacketScalar>(alignedStart);
|
||||
if(alignedSize>packetSize) // we have at least two packets to partly unroll the loop
|
||||
{
|
||||
PacketScalar packet_res1 = mat.template packet<alignment>(alignedStart+packetSize);
|
||||
PacketScalar packet_res1 = mat.template packet<alignment,PacketScalar>(alignedStart+packetSize);
|
||||
for(Index index = alignedStart + 2*packetSize; index < alignedEnd2; index += 2*packetSize)
|
||||
{
|
||||
packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment>(index));
|
||||
packet_res1 = func.packetOp(packet_res1, mat.template packet<alignment>(index+packetSize));
|
||||
packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment,PacketScalar>(index));
|
||||
packet_res1 = func.packetOp(packet_res1, mat.template packet<alignment,PacketScalar>(index+packetSize));
|
||||
}
|
||||
|
||||
packet_res0 = func.packetOp(packet_res0,packet_res1);
|
||||
if(alignedEnd>alignedEnd2)
|
||||
packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment>(alignedEnd2));
|
||||
packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment,PacketScalar>(alignedEnd2));
|
||||
}
|
||||
res = func.predux(packet_res0);
|
||||
|
||||
@@ -255,10 +273,9 @@ template<typename Func, typename Derived>
|
||||
struct redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling>
|
||||
{
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
typedef typename packet_traits<Scalar>::type PacketScalar;
|
||||
typedef typename Derived::Index Index;
|
||||
typedef typename packet_traits<Scalar>::type PacketType;
|
||||
|
||||
static Scalar run(const Derived& mat, const Func& func)
|
||||
EIGEN_DEVICE_FUNC static Scalar run(const Derived &mat, const Func& func)
|
||||
{
|
||||
eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
|
||||
const Index innerSize = mat.innerSize();
|
||||
@@ -270,10 +287,10 @@ struct redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling>
|
||||
Scalar res;
|
||||
if(packetedInnerSize)
|
||||
{
|
||||
PacketScalar packet_res = mat.template packet<Unaligned>(0,0);
|
||||
PacketType packet_res = mat.template packet<Unaligned,PacketType>(0,0);
|
||||
for(Index j=0; j<outerSize; ++j)
|
||||
for(Index i=(j==0?packetSize:0); i<packetedInnerSize; i+=Index(packetSize))
|
||||
packet_res = func.packetOp(packet_res, mat.template packetByOuterInner<Unaligned>(j,i));
|
||||
packet_res = func.packetOp(packet_res, mat.template packetByOuterInner<Unaligned,PacketType>(j,i));
|
||||
|
||||
res = func.predux(packet_res);
|
||||
for(Index j=0; j<outerSize; ++j)
|
||||
@@ -300,7 +317,7 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling>
|
||||
Size = Derived::SizeAtCompileTime,
|
||||
VectorizedSize = (Size / PacketSize) * PacketSize
|
||||
};
|
||||
static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func)
|
||||
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func)
|
||||
{
|
||||
eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
|
||||
if (VectorizedSize > 0) {
|
||||
@@ -315,6 +332,68 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling>
|
||||
}
|
||||
};
|
||||
|
||||
// evaluator adaptor
|
||||
template<typename _XprType>
|
||||
class redux_evaluator
|
||||
{
|
||||
public:
|
||||
typedef _XprType XprType;
|
||||
EIGEN_DEVICE_FUNC explicit redux_evaluator(const XprType &xpr) : m_evaluator(xpr), m_xpr(xpr) {}
|
||||
|
||||
typedef typename XprType::Scalar Scalar;
|
||||
typedef typename XprType::CoeffReturnType CoeffReturnType;
|
||||
typedef typename XprType::PacketScalar PacketScalar;
|
||||
typedef typename XprType::PacketReturnType PacketReturnType;
|
||||
|
||||
enum {
|
||||
MaxRowsAtCompileTime = XprType::MaxRowsAtCompileTime,
|
||||
MaxColsAtCompileTime = XprType::MaxColsAtCompileTime,
|
||||
// TODO we should not remove DirectAccessBit and rather find an elegant way to query the alignment offset at runtime from the evaluator
|
||||
Flags = evaluator<XprType>::Flags & ~DirectAccessBit,
|
||||
IsRowMajor = XprType::IsRowMajor,
|
||||
SizeAtCompileTime = XprType::SizeAtCompileTime,
|
||||
InnerSizeAtCompileTime = XprType::InnerSizeAtCompileTime,
|
||||
CoeffReadCost = evaluator<XprType>::CoeffReadCost,
|
||||
Alignment = evaluator<XprType>::Alignment
|
||||
};
|
||||
|
||||
EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
|
||||
EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
|
||||
EIGEN_DEVICE_FUNC Index size() const { return m_xpr.size(); }
|
||||
EIGEN_DEVICE_FUNC Index innerSize() const { return m_xpr.innerSize(); }
|
||||
EIGEN_DEVICE_FUNC Index outerSize() const { return m_xpr.outerSize(); }
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
CoeffReturnType coeff(Index row, Index col) const
|
||||
{ return m_evaluator.coeff(row, col); }
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
CoeffReturnType coeff(Index index) const
|
||||
{ return m_evaluator.coeff(index); }
|
||||
|
||||
template<int LoadMode, typename PacketType>
|
||||
PacketReturnType packet(Index row, Index col) const
|
||||
{ return m_evaluator.template packet<LoadMode,PacketType>(row, col); }
|
||||
|
||||
template<int LoadMode, typename PacketType>
|
||||
PacketReturnType packet(Index index) const
|
||||
{ return m_evaluator.template packet<LoadMode,PacketType>(index); }
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
|
||||
{ return m_evaluator.coeff(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
|
||||
|
||||
template<int LoadMode, typename PacketType>
|
||||
PacketReturnType packetByOuterInner(Index outer, Index inner) const
|
||||
{ return m_evaluator.template packet<LoadMode,PacketType>(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
|
||||
|
||||
const XprType & nestedExpression() const { return m_xpr; }
|
||||
|
||||
protected:
|
||||
internal::evaluator<XprType> m_evaluator;
|
||||
const XprType &m_xpr;
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
/***************************************************************************
|
||||
@@ -325,18 +404,31 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling>
|
||||
/** \returns the result of a full redux operation on the whole matrix or vector using \a func
|
||||
*
|
||||
* The template parameter \a BinaryOp is the type of the functor \a func which must be
|
||||
* an associative operator. Both current STL and TR1 functor styles are handled.
|
||||
* an associative operator. Both current C++98 and C++11 functor styles are handled.
|
||||
*
|
||||
* \sa DenseBase::sum(), DenseBase::minCoeff(), DenseBase::maxCoeff(), MatrixBase::colwise(), MatrixBase::rowwise()
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename Func>
|
||||
EIGEN_STRONG_INLINE typename internal::result_of<Func(typename internal::traits<Derived>::Scalar)>::type
|
||||
typename internal::traits<Derived>::Scalar
|
||||
DenseBase<Derived>::redux(const Func& func) const
|
||||
{
|
||||
typedef typename internal::remove_all<typename Derived::Nested>::type ThisNested;
|
||||
return internal::redux_impl<Func, ThisNested>
|
||||
::run(derived(), func);
|
||||
eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");
|
||||
|
||||
// FIXME, eval_nest should be handled by redux_evaluator, however:
|
||||
// - it is currently difficult to provide the right Flags since they are still handled by the expressions
|
||||
// - handling it here might reduce the number of template instantiations
|
||||
// typedef typename internal::nested_eval<Derived,1>::type ThisNested;
|
||||
// typedef typename internal::remove_all<ThisNested>::type ThisNestedCleaned;
|
||||
// typedef typename internal::redux_evaluator<ThisNestedCleaned> ThisEvaluator;
|
||||
//
|
||||
// ThisNested thisNested(derived());
|
||||
// ThisEvaluator thisEval(thisNested);
|
||||
|
||||
typedef typename internal::redux_evaluator<Derived> ThisEvaluator;
|
||||
ThisEvaluator thisEval(derived());
|
||||
|
||||
return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func);
|
||||
}
|
||||
|
||||
/** \returns the minimum of all coefficients of \c *this.
|
||||
@@ -346,7 +438,7 @@ template<typename Derived>
|
||||
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
|
||||
DenseBase<Derived>::minCoeff() const
|
||||
{
|
||||
return this->redux(Eigen::internal::scalar_min_op<Scalar>());
|
||||
return derived().redux(Eigen::internal::scalar_min_op<Scalar>());
|
||||
}
|
||||
|
||||
/** \returns the maximum of all coefficients of \c *this.
|
||||
@@ -356,7 +448,7 @@ template<typename Derived>
|
||||
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
|
||||
DenseBase<Derived>::maxCoeff() const
|
||||
{
|
||||
return this->redux(Eigen::internal::scalar_max_op<Scalar>());
|
||||
return derived().redux(Eigen::internal::scalar_max_op<Scalar>());
|
||||
}
|
||||
|
||||
/** \returns the sum of all coefficients of *this
|
||||
@@ -369,7 +461,7 @@ DenseBase<Derived>::sum() const
|
||||
{
|
||||
if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
|
||||
return Scalar(0);
|
||||
return this->redux(Eigen::internal::scalar_sum_op<Scalar>());
|
||||
return derived().redux(Eigen::internal::scalar_sum_op<Scalar>());
|
||||
}
|
||||
|
||||
/** \returns the mean of all coefficients of *this
|
||||
@@ -380,7 +472,7 @@ template<typename Derived>
|
||||
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
|
||||
DenseBase<Derived>::mean() const
|
||||
{
|
||||
return Scalar(this->redux(Eigen::internal::scalar_sum_op<Scalar>())) / Scalar(this->size());
|
||||
return Scalar(derived().redux(Eigen::internal::scalar_sum_op<Scalar>())) / Scalar(this->size());
|
||||
}
|
||||
|
||||
/** \returns the product of all coefficients of *this
|
||||
@@ -396,7 +488,7 @@ DenseBase<Derived>::prod() const
|
||||
{
|
||||
if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
|
||||
return Scalar(1);
|
||||
return this->redux(Eigen::internal::scalar_product_op<Scalar>());
|
||||
return derived().redux(Eigen::internal::scalar_product_op<Scalar>());
|
||||
}
|
||||
|
||||
/** \returns the trace of \c *this, i.e. the sum of the coefficients on the main diagonal.
|
||||
|
||||
@@ -12,17 +12,13 @@
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
template<typename Derived> class RefBase;
|
||||
template<typename PlainObjectType, int Options = 0,
|
||||
typename StrideType = typename internal::conditional<PlainObjectType::IsVectorAtCompileTime,InnerStride<1>,OuterStride<> >::type > class Ref;
|
||||
|
||||
/** \class Ref
|
||||
* \ingroup Core_Module
|
||||
*
|
||||
* \brief A matrix or vector expression mapping an existing expression
|
||||
*
|
||||
* \tparam PlainObjectType the equivalent matrix type of the mapped data
|
||||
* \tparam Options specifies whether the pointer is \c #Aligned, or \c #Unaligned.
|
||||
* \tparam MapOptions specifies the pointer alignment in bytes. It can be: \c #Aligned128, , \c #Aligned64, \c #Aligned32, \c #Aligned16, \c #Aligned8 or \c #Unaligned.
|
||||
* The default is \c #Unaligned.
|
||||
* \tparam StrideType optionally specifies strides. By default, Ref implies a contiguous storage along the inner dimension (inner stride==1),
|
||||
* but accepts a variable outer stride (leading dimension).
|
||||
@@ -52,8 +48,9 @@ template<typename PlainObjectType, int Options = 0,
|
||||
* VectorXf a;
|
||||
* foo1(a.head()); // OK
|
||||
* foo1(A.col()); // OK
|
||||
* foo1(A.row()); // compilation error because here innerstride!=1
|
||||
* foo2(A.row()); // The row is copied into a contiguous temporary
|
||||
* foo1(A.row()); // Compilation error because here innerstride!=1
|
||||
* foo2(A.row()); // Compilation error because A.row() is a 1xN object while foo2 is expecting a Nx1 object
|
||||
* foo2(A.row().transpose()); // The row is copied into a contiguous temporary
|
||||
* foo2(2*a); // The expression is evaluated into a temporary
|
||||
* foo2(A.col().segment(2,4)); // No temporary
|
||||
* \endcode
|
||||
@@ -95,7 +92,8 @@ struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
|
||||
typedef _StrideType StrideType;
|
||||
enum {
|
||||
Options = _Options,
|
||||
Flags = traits<Map<_PlainObjectType, _Options, _StrideType> >::Flags | NestByRefBit
|
||||
Flags = traits<Map<_PlainObjectType, _Options, _StrideType> >::Flags | NestByRefBit,
|
||||
Alignment = traits<Map<_PlainObjectType, _Options, _StrideType> >::Alignment
|
||||
};
|
||||
|
||||
template<typename Derived> struct match {
|
||||
@@ -107,8 +105,9 @@ struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
|
||||
|| (int(StrideType::InnerStrideAtCompileTime)==0 && int(Derived::InnerStrideAtCompileTime)==1),
|
||||
OuterStrideMatch = Derived::IsVectorAtCompileTime
|
||||
|| int(StrideType::OuterStrideAtCompileTime)==int(Dynamic) || int(StrideType::OuterStrideAtCompileTime)==int(Derived::OuterStrideAtCompileTime),
|
||||
AlignmentMatch = (_Options!=Aligned) || ((PlainObjectType::Flags&AlignedBit)==0) || ((traits<Derived>::Flags&AlignedBit)==AlignedBit),
|
||||
MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch
|
||||
AlignmentMatch = (int(traits<PlainObjectType>::Alignment)==int(Unaligned)) || (int(evaluator<Derived>::Alignment) >= int(Alignment)), // FIXME the first condition is not very clear, it should be replaced by the required alignment
|
||||
ScalarTypeMatch = internal::is_same<typename PlainObjectType::Scalar, typename Derived::Scalar>::value,
|
||||
MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch && ScalarTypeMatch
|
||||
};
|
||||
typedef typename internal::conditional<MatchAtCompileTime,internal::true_type,internal::false_type>::type type;
|
||||
};
|
||||
@@ -131,12 +130,12 @@ public:
|
||||
typedef MapBase<Derived> Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(RefBase)
|
||||
|
||||
inline Index innerStride() const
|
||||
EIGEN_DEVICE_FUNC inline Index innerStride() const
|
||||
{
|
||||
return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1;
|
||||
}
|
||||
|
||||
inline Index outerStride() const
|
||||
EIGEN_DEVICE_FUNC inline Index outerStride() const
|
||||
{
|
||||
return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
|
||||
: IsVectorAtCompileTime ? this->size()
|
||||
@@ -144,7 +143,7 @@ public:
|
||||
: this->rows();
|
||||
}
|
||||
|
||||
RefBase()
|
||||
EIGEN_DEVICE_FUNC RefBase()
|
||||
: Base(0,RowsAtCompileTime==Dynamic?0:RowsAtCompileTime,ColsAtCompileTime==Dynamic?0:ColsAtCompileTime),
|
||||
// Stride<> does not allow default ctor for Dynamic strides, so let' initialize it with dummy values:
|
||||
m_stride(StrideType::OuterStrideAtCompileTime==Dynamic?0:StrideType::OuterStrideAtCompileTime,
|
||||
@@ -158,7 +157,7 @@ protected:
|
||||
typedef Stride<StrideType::OuterStrideAtCompileTime,StrideType::InnerStrideAtCompileTime> StrideBase;
|
||||
|
||||
template<typename Expression>
|
||||
void construct(Expression& expr)
|
||||
EIGEN_DEVICE_FUNC void construct(Expression& expr)
|
||||
{
|
||||
if(PlainObjectType::RowsAtCompileTime==1)
|
||||
{
|
||||
@@ -187,7 +186,11 @@ protected:
|
||||
template<typename PlainObjectType, int Options, typename StrideType> class Ref
|
||||
: public RefBase<Ref<PlainObjectType, Options, StrideType> >
|
||||
{
|
||||
private:
|
||||
typedef internal::traits<Ref> Traits;
|
||||
template<typename Derived>
|
||||
EIGEN_DEVICE_FUNC inline Ref(const PlainObjectBase<Derived>& expr,
|
||||
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0);
|
||||
public:
|
||||
|
||||
typedef RefBase<Ref> Base;
|
||||
@@ -196,20 +199,23 @@ template<typename PlainObjectType, int Options, typename StrideType> class Ref
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
template<typename Derived>
|
||||
inline Ref(PlainObjectBase<Derived>& expr,
|
||||
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
|
||||
EIGEN_DEVICE_FUNC inline Ref(PlainObjectBase<Derived>& expr,
|
||||
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
|
||||
{
|
||||
Base::construct(expr);
|
||||
EIGEN_STATIC_ASSERT(bool(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
|
||||
Base::construct(expr.derived());
|
||||
}
|
||||
template<typename Derived>
|
||||
inline Ref(const DenseBase<Derived>& expr,
|
||||
typename internal::enable_if<bool(internal::is_lvalue<Derived>::value&&bool(Traits::template match<Derived>::MatchAtCompileTime)),Derived>::type* = 0,
|
||||
int = Derived::ThisConstantIsPrivateInPlainObjectBase)
|
||||
EIGEN_DEVICE_FUNC inline Ref(const DenseBase<Derived>& expr,
|
||||
typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
|
||||
#else
|
||||
template<typename Derived>
|
||||
inline Ref(DenseBase<Derived>& expr)
|
||||
#endif
|
||||
{
|
||||
EIGEN_STATIC_ASSERT(bool(internal::is_lvalue<Derived>::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
|
||||
EIGEN_STATIC_ASSERT(bool(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
|
||||
EIGEN_STATIC_ASSERT(!Derived::IsPlainObjectBase,THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
|
||||
Base::construct(expr.const_cast_derived());
|
||||
}
|
||||
|
||||
@@ -228,7 +234,8 @@ template<typename TPlainObjectType, int Options, typename StrideType> class Ref<
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
|
||||
|
||||
template<typename Derived>
|
||||
inline Ref(const DenseBase<Derived>& expr)
|
||||
EIGEN_DEVICE_FUNC inline Ref(const DenseBase<Derived>& expr,
|
||||
typename internal::enable_if<bool(Traits::template match<Derived>::ScalarTypeMatch),Derived>::type* = 0)
|
||||
{
|
||||
// std::cout << match_helper<Derived>::HasDirectAccess << "," << match_helper<Derived>::OuterStrideMatch << "," << match_helper<Derived>::InnerStrideMatch << "\n";
|
||||
// std::cout << int(StrideType::OuterStrideAtCompileTime) << " - " << int(Derived::OuterStrideAtCompileTime) << "\n";
|
||||
@@ -236,18 +243,27 @@ template<typename TPlainObjectType, int Options, typename StrideType> class Ref<
|
||||
construct(expr.derived(), typename Traits::template match<Derived>::type());
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC inline Ref(const Ref& other) : Base(other) {
|
||||
// copy constructor shall not copy the m_object, to avoid unnecessary malloc and copy
|
||||
}
|
||||
|
||||
template<typename OtherRef>
|
||||
EIGEN_DEVICE_FUNC inline Ref(const RefBase<OtherRef>& other) {
|
||||
construct(other.derived(), typename Traits::template match<OtherRef>::type());
|
||||
}
|
||||
|
||||
protected:
|
||||
|
||||
template<typename Expression>
|
||||
void construct(const Expression& expr,internal::true_type)
|
||||
EIGEN_DEVICE_FUNC void construct(const Expression& expr,internal::true_type)
|
||||
{
|
||||
Base::construct(expr);
|
||||
}
|
||||
|
||||
template<typename Expression>
|
||||
void construct(const Expression& expr, internal::false_type)
|
||||
EIGEN_DEVICE_FUNC void construct(const Expression& expr, internal::false_type)
|
||||
{
|
||||
m_object.lazyAssign(expr);
|
||||
internal::call_assignment_no_alias(m_object,expr,internal::assign_op<Scalar>());
|
||||
Base::construct(m_object);
|
||||
}
|
||||
|
||||
|
||||
@@ -35,10 +35,7 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename traits<MatrixType>::StorageKind StorageKind;
|
||||
typedef typename traits<MatrixType>::XprKind XprKind;
|
||||
enum {
|
||||
Factor = (RowFactor==Dynamic || ColFactor==Dynamic) ? Dynamic : RowFactor*ColFactor
|
||||
};
|
||||
typedef typename nested<MatrixType,Factor>::type MatrixTypeNested;
|
||||
typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
|
||||
enum {
|
||||
RowsAtCompileTime = RowFactor==Dynamic || int(MatrixType::RowsAtCompileTime)==Dynamic
|
||||
@@ -53,8 +50,9 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
|
||||
IsRowMajor = MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1 ? 1
|
||||
: MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1 ? 0
|
||||
: (MatrixType::Flags & RowMajorBit) ? 1 : 0,
|
||||
Flags = (_MatrixTypeNested::Flags & HereditaryBits & ~RowMajorBit) | (IsRowMajor ? RowMajorBit : 0),
|
||||
CoeffReadCost = _MatrixTypeNested::CoeffReadCost
|
||||
|
||||
// FIXME enable DirectAccess with negative strides?
|
||||
Flags = IsRowMajor ? RowMajorBit : 0
|
||||
};
|
||||
};
|
||||
}
|
||||
@@ -68,10 +66,12 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
|
||||
|
||||
typedef typename internal::dense_xpr_base<Replicate>::type Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Replicate)
|
||||
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
|
||||
|
||||
template<typename OriginalMatrixType>
|
||||
inline explicit Replicate(const OriginalMatrixType& a_matrix)
|
||||
: m_matrix(a_matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline explicit Replicate(const OriginalMatrixType& matrix)
|
||||
: m_matrix(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)
|
||||
@@ -79,41 +79,20 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
|
||||
}
|
||||
|
||||
template<typename OriginalMatrixType>
|
||||
inline Replicate(const OriginalMatrixType& a_matrix, Index rowFactor, Index colFactor)
|
||||
: m_matrix(a_matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor)
|
||||
: m_matrix(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)
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index rows() const { return m_matrix.rows() * m_rowFactor.value(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index cols() const { return m_matrix.cols() * m_colFactor.value(); }
|
||||
|
||||
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 ? rowId
|
||||
: rowId%m_matrix.rows();
|
||||
const Index actual_col = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
|
||||
: ColFactor==1 ? colId
|
||||
: colId%m_matrix.cols();
|
||||
|
||||
return m_matrix.coeff(actual_row, actual_col);
|
||||
}
|
||||
template<int LoadMode>
|
||||
inline PacketScalar packet(Index rowId, Index colId) const
|
||||
{
|
||||
const Index actual_row = internal::traits<MatrixType>::RowsAtCompileTime==1 ? 0
|
||||
: RowFactor==1 ? rowId
|
||||
: rowId%m_matrix.rows();
|
||||
const Index actual_col = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
|
||||
: ColFactor==1 ? colId
|
||||
: colId%m_matrix.cols();
|
||||
|
||||
return m_matrix.template packet<LoadMode>(actual_row, actual_col);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
const _MatrixTypeNested& nestedExpression() const
|
||||
{
|
||||
return m_matrix;
|
||||
@@ -135,27 +114,12 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<int RowFactor, int ColFactor>
|
||||
inline const Replicate<Derived,RowFactor,ColFactor>
|
||||
const Replicate<Derived,RowFactor,ColFactor>
|
||||
DenseBase<Derived>::replicate() const
|
||||
{
|
||||
return Replicate<Derived,RowFactor,ColFactor>(derived());
|
||||
}
|
||||
|
||||
/**
|
||||
* \return an expression of the replication of \c *this
|
||||
*
|
||||
* Example: \include MatrixBase_replicate_int_int.cpp
|
||||
* Output: \verbinclude MatrixBase_replicate_int_int.out
|
||||
*
|
||||
* \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
|
||||
*/
|
||||
template<typename Derived>
|
||||
inline const Replicate<Derived,Dynamic,Dynamic>
|
||||
DenseBase<Derived>::replicate(Index rowFactor,Index colFactor) const
|
||||
{
|
||||
return Replicate<Derived,Dynamic,Dynamic>(derived(),rowFactor,colFactor);
|
||||
}
|
||||
|
||||
/**
|
||||
* \return an expression of the replication of each column (or row) of \c *this
|
||||
*
|
||||
|
||||
@@ -38,9 +38,10 @@ struct traits<ReturnByValue<Derived> >
|
||||
* So internal::nested always gives the plain return matrix type.
|
||||
*
|
||||
* FIXME: I don't understand why we need this specialization: isn't this taken care of by the EvalBeforeNestingBit ??
|
||||
* Answer: EvalBeforeNestingBit should be deprecated since we have the evaluators
|
||||
*/
|
||||
template<typename Derived,int n,typename PlainObject>
|
||||
struct nested<ReturnByValue<Derived>, n, PlainObject>
|
||||
struct nested_eval<ReturnByValue<Derived>, n, PlainObject>
|
||||
{
|
||||
typedef typename traits<Derived>::ReturnType type;
|
||||
};
|
||||
@@ -48,7 +49,7 @@ struct nested<ReturnByValue<Derived>, n, PlainObject>
|
||||
} // end namespace internal
|
||||
|
||||
template<typename Derived> class ReturnByValue
|
||||
: internal::no_assignment_operator, public internal::dense_xpr_base< ReturnByValue<Derived> >::type
|
||||
: public internal::dense_xpr_base< ReturnByValue<Derived> >::type, internal::no_assignment_operator
|
||||
{
|
||||
public:
|
||||
typedef typename internal::traits<Derived>::ReturnType ReturnType;
|
||||
@@ -73,6 +74,7 @@ template<typename Derived> class ReturnByValue
|
||||
const Unusable& coeff(Index,Index) const { return *reinterpret_cast<const Unusable*>(this); }
|
||||
Unusable& coeffRef(Index) { return *reinterpret_cast<Unusable*>(this); }
|
||||
Unusable& coeffRef(Index,Index) { return *reinterpret_cast<Unusable*>(this); }
|
||||
#undef Unusable
|
||||
#endif
|
||||
};
|
||||
|
||||
@@ -84,6 +86,33 @@ Derived& DenseBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
|
||||
return derived();
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
|
||||
// Expression is evaluated in a temporary; default implementation of Assignment is bypassed so that
|
||||
// when a ReturnByValue expression is assigned, the evaluator is not constructed.
|
||||
// TODO: Finalize port to new regime; ReturnByValue should not exist in the expression world
|
||||
|
||||
template<typename Derived>
|
||||
struct evaluator<ReturnByValue<Derived> >
|
||||
: public evaluator<typename internal::traits<Derived>::ReturnType>
|
||||
{
|
||||
typedef ReturnByValue<Derived> XprType;
|
||||
typedef typename internal::traits<Derived>::ReturnType PlainObject;
|
||||
typedef evaluator<PlainObject> Base;
|
||||
|
||||
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
|
||||
: m_result(xpr.rows(), xpr.cols())
|
||||
{
|
||||
::new (static_cast<Base*>(this)) Base(m_result);
|
||||
xpr.evalTo(m_result);
|
||||
}
|
||||
|
||||
protected:
|
||||
PlainObject m_result;
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_RETURNBYVALUE_H
|
||||
|
||||
@@ -37,32 +37,25 @@ struct traits<Reverse<MatrixType, Direction> >
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename traits<MatrixType>::StorageKind StorageKind;
|
||||
typedef typename traits<MatrixType>::XprKind XprKind;
|
||||
typedef typename nested<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
|
||||
enum {
|
||||
RowsAtCompileTime = MatrixType::RowsAtCompileTime,
|
||||
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
|
||||
MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
|
||||
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
|
||||
|
||||
// let's enable LinearAccess only with vectorization because of the product overhead
|
||||
LinearAccess = ( (Direction==BothDirections) && (int(_MatrixTypeNested::Flags)&PacketAccessBit) )
|
||||
? LinearAccessBit : 0,
|
||||
|
||||
Flags = int(_MatrixTypeNested::Flags) & (HereditaryBits | LvalueBit | PacketAccessBit | LinearAccess),
|
||||
|
||||
CoeffReadCost = _MatrixTypeNested::CoeffReadCost
|
||||
Flags = _MatrixTypeNested::Flags & (RowMajorBit | LvalueBit)
|
||||
};
|
||||
};
|
||||
|
||||
template<typename PacketScalar, bool ReversePacket> struct reverse_packet_cond
|
||||
template<typename PacketType, bool ReversePacket> struct reverse_packet_cond
|
||||
{
|
||||
static inline PacketScalar run(const PacketScalar& x) { return preverse(x); }
|
||||
static inline PacketType run(const PacketType& x) { return preverse(x); }
|
||||
};
|
||||
|
||||
template<typename PacketScalar> struct reverse_packet_cond<PacketScalar,false>
|
||||
template<typename PacketType> struct reverse_packet_cond<PacketType,false>
|
||||
{
|
||||
static inline PacketScalar run(const PacketScalar& x) { return x; }
|
||||
static inline PacketType run(const PacketType& x) { return x; }
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
@@ -74,12 +67,9 @@ template<typename MatrixType, int Direction> class Reverse
|
||||
|
||||
typedef typename internal::dense_xpr_base<Reverse>::type Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Reverse)
|
||||
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
|
||||
using Base::IsRowMajor;
|
||||
|
||||
// next line is necessary because otherwise const version of operator()
|
||||
// is hidden by non-const version defined in this file
|
||||
using Base::operator();
|
||||
|
||||
protected:
|
||||
enum {
|
||||
PacketSize = internal::packet_traits<Scalar>::size,
|
||||
@@ -95,82 +85,19 @@ template<typename MatrixType, int Direction> class Reverse
|
||||
typedef internal::reverse_packet_cond<PacketScalar,ReversePacket> reverse_packet;
|
||||
public:
|
||||
|
||||
inline Reverse(const MatrixType& matrix) : m_matrix(matrix) { }
|
||||
EIGEN_DEVICE_FUNC explicit inline Reverse(const MatrixType& matrix) : m_matrix(matrix) { }
|
||||
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Reverse)
|
||||
|
||||
inline Index rows() const { return m_matrix.rows(); }
|
||||
inline Index cols() const { return m_matrix.cols(); }
|
||||
EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.rows(); }
|
||||
EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.cols(); }
|
||||
|
||||
inline Index innerStride() const
|
||||
EIGEN_DEVICE_FUNC inline Index innerStride() const
|
||||
{
|
||||
return -m_matrix.innerStride();
|
||||
}
|
||||
|
||||
inline Scalar& operator()(Index row, Index col)
|
||||
{
|
||||
eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
|
||||
return coeffRef(row, col);
|
||||
}
|
||||
|
||||
inline Scalar& coeffRef(Index row, Index col)
|
||||
{
|
||||
return m_matrix.const_cast_derived().coeffRef(ReverseRow ? m_matrix.rows() - row - 1 : row,
|
||||
ReverseCol ? m_matrix.cols() - col - 1 : col);
|
||||
}
|
||||
|
||||
inline CoeffReturnType coeff(Index row, Index col) const
|
||||
{
|
||||
return m_matrix.coeff(ReverseRow ? m_matrix.rows() - row - 1 : row,
|
||||
ReverseCol ? m_matrix.cols() - col - 1 : col);
|
||||
}
|
||||
|
||||
inline CoeffReturnType coeff(Index index) const
|
||||
{
|
||||
return m_matrix.coeff(m_matrix.size() - index - 1);
|
||||
}
|
||||
|
||||
inline Scalar& coeffRef(Index index)
|
||||
{
|
||||
return m_matrix.const_cast_derived().coeffRef(m_matrix.size() - index - 1);
|
||||
}
|
||||
|
||||
inline Scalar& operator()(Index index)
|
||||
{
|
||||
eigen_assert(index >= 0 && index < m_matrix.size());
|
||||
return coeffRef(index);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline const PacketScalar packet(Index row, Index col) const
|
||||
{
|
||||
return reverse_packet::run(m_matrix.template packet<LoadMode>(
|
||||
ReverseRow ? m_matrix.rows() - row - OffsetRow : row,
|
||||
ReverseCol ? m_matrix.cols() - col - OffsetCol : col));
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline void writePacket(Index row, Index col, const PacketScalar& x)
|
||||
{
|
||||
m_matrix.const_cast_derived().template writePacket<LoadMode>(
|
||||
ReverseRow ? m_matrix.rows() - row - OffsetRow : row,
|
||||
ReverseCol ? m_matrix.cols() - col - OffsetCol : col,
|
||||
reverse_packet::run(x));
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline const PacketScalar packet(Index index) const
|
||||
{
|
||||
return internal::preverse(m_matrix.template packet<LoadMode>( m_matrix.size() - index - PacketSize ));
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline void writePacket(Index index, const PacketScalar& x)
|
||||
{
|
||||
m_matrix.const_cast_derived().template writePacket<LoadMode>(m_matrix.size() - index - PacketSize, internal::preverse(x));
|
||||
}
|
||||
|
||||
const typename internal::remove_all<typename MatrixType::Nested>::type&
|
||||
EIGEN_DEVICE_FUNC const typename internal::remove_all<typename MatrixType::Nested>::type&
|
||||
nestedExpression() const
|
||||
{
|
||||
return m_matrix;
|
||||
@@ -190,33 +117,93 @@ template<typename Derived>
|
||||
inline typename DenseBase<Derived>::ReverseReturnType
|
||||
DenseBase<Derived>::reverse()
|
||||
{
|
||||
return derived();
|
||||
return ReverseReturnType(derived());
|
||||
}
|
||||
|
||||
/** This is the const version of reverse(). */
|
||||
template<typename Derived>
|
||||
inline const typename DenseBase<Derived>::ConstReverseReturnType
|
||||
DenseBase<Derived>::reverse() const
|
||||
{
|
||||
return derived();
|
||||
}
|
||||
|
||||
//reverse const overload moved DenseBase.h due to a CUDA compiler bug
|
||||
|
||||
/** This is the "in place" version of reverse: it reverses \c *this.
|
||||
*
|
||||
* In most cases it is probably better to simply use the reversed expression
|
||||
* of a matrix. However, when reversing the matrix data itself is really needed,
|
||||
* then this "in-place" version is probably the right choice because it provides
|
||||
* the following additional features:
|
||||
* the following additional benefits:
|
||||
* - less error prone: doing the same operation with .reverse() requires special care:
|
||||
* \code m = m.reverse().eval(); \endcode
|
||||
* - this API allows to avoid creating a temporary (the current implementation creates a temporary, but that could be avoided using swap)
|
||||
* - this API enables reverse operations without the need for a temporary
|
||||
* - it allows future optimizations (cache friendliness, etc.)
|
||||
*
|
||||
* \sa reverse() */
|
||||
* \sa VectorwiseOp::reverseInPlace(), reverse() */
|
||||
template<typename Derived>
|
||||
inline void DenseBase<Derived>::reverseInPlace()
|
||||
{
|
||||
derived() = derived().reverse().eval();
|
||||
if(cols()>rows())
|
||||
{
|
||||
Index half = cols()/2;
|
||||
leftCols(half).swap(rightCols(half).reverse());
|
||||
if((cols()%2)==1)
|
||||
{
|
||||
Index half2 = rows()/2;
|
||||
col(half).head(half2).swap(col(half).tail(half2).reverse());
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
Index half = rows()/2;
|
||||
topRows(half).swap(bottomRows(half).reverse());
|
||||
if((rows()%2)==1)
|
||||
{
|
||||
Index half2 = cols()/2;
|
||||
row(half).head(half2).swap(row(half).tail(half2).reverse());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<int Direction>
|
||||
struct vectorwise_reverse_inplace_impl;
|
||||
|
||||
template<>
|
||||
struct vectorwise_reverse_inplace_impl<Vertical>
|
||||
{
|
||||
template<typename ExpressionType>
|
||||
static void run(ExpressionType &xpr)
|
||||
{
|
||||
Index half = xpr.rows()/2;
|
||||
xpr.topRows(half).swap(xpr.bottomRows(half).colwise().reverse());
|
||||
}
|
||||
};
|
||||
|
||||
template<>
|
||||
struct vectorwise_reverse_inplace_impl<Horizontal>
|
||||
{
|
||||
template<typename ExpressionType>
|
||||
static void run(ExpressionType &xpr)
|
||||
{
|
||||
Index half = xpr.cols()/2;
|
||||
xpr.leftCols(half).swap(xpr.rightCols(half).rowwise().reverse());
|
||||
}
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
/** This is the "in place" version of VectorwiseOp::reverse: it reverses each column or row of \c *this.
|
||||
*
|
||||
* In most cases it is probably better to simply use the reversed expression
|
||||
* of a matrix. However, when reversing the matrix data itself is really needed,
|
||||
* then this "in-place" version is probably the right choice because it provides
|
||||
* the following additional benefits:
|
||||
* - less error prone: doing the same operation with .reverse() requires special care:
|
||||
* \code m = m.reverse().eval(); \endcode
|
||||
* - this API enables reverse operations without the need for a temporary
|
||||
*
|
||||
* \sa DenseBase::reverseInPlace(), reverse() */
|
||||
template<typename ExpressionType, int Direction>
|
||||
void VectorwiseOp<ExpressionType,Direction>::reverseInPlace()
|
||||
{
|
||||
internal::vectorwise_reverse_inplace_impl<Direction>::run(_expression().const_cast_derived());
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -43,23 +43,21 @@ struct traits<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >
|
||||
ColsAtCompileTime = ConditionMatrixType::ColsAtCompileTime,
|
||||
MaxRowsAtCompileTime = ConditionMatrixType::MaxRowsAtCompileTime,
|
||||
MaxColsAtCompileTime = ConditionMatrixType::MaxColsAtCompileTime,
|
||||
Flags = (unsigned int)ThenMatrixType::Flags & ElseMatrixType::Flags & HereditaryBits,
|
||||
CoeffReadCost = traits<typename remove_all<ConditionMatrixNested>::type>::CoeffReadCost
|
||||
+ EIGEN_SIZE_MAX(traits<typename remove_all<ThenMatrixNested>::type>::CoeffReadCost,
|
||||
traits<typename remove_all<ElseMatrixNested>::type>::CoeffReadCost)
|
||||
Flags = (unsigned int)ThenMatrixType::Flags & ElseMatrixType::Flags & RowMajorBit
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
template<typename ConditionMatrixType, typename ThenMatrixType, typename ElseMatrixType>
|
||||
class Select : internal::no_assignment_operator,
|
||||
public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::type
|
||||
class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::type,
|
||||
internal::no_assignment_operator
|
||||
{
|
||||
public:
|
||||
|
||||
typedef typename internal::dense_xpr_base<Select>::type Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Select)
|
||||
|
||||
inline EIGEN_DEVICE_FUNC
|
||||
Select(const ConditionMatrixType& a_conditionMatrix,
|
||||
const ThenMatrixType& a_thenMatrix,
|
||||
const ElseMatrixType& a_elseMatrix)
|
||||
@@ -69,9 +67,10 @@ class Select : internal::no_assignment_operator,
|
||||
eigen_assert(m_condition.cols() == m_then.cols() && m_condition.cols() == m_else.cols());
|
||||
}
|
||||
|
||||
Index rows() const { return m_condition.rows(); }
|
||||
Index cols() const { return m_condition.cols(); }
|
||||
inline EIGEN_DEVICE_FUNC Index rows() const { return m_condition.rows(); }
|
||||
inline EIGEN_DEVICE_FUNC Index cols() const { return m_condition.cols(); }
|
||||
|
||||
inline EIGEN_DEVICE_FUNC
|
||||
const Scalar coeff(Index i, Index j) const
|
||||
{
|
||||
if (m_condition.coeff(i,j))
|
||||
@@ -80,6 +79,7 @@ class Select : internal::no_assignment_operator,
|
||||
return m_else.coeff(i,j);
|
||||
}
|
||||
|
||||
inline EIGEN_DEVICE_FUNC
|
||||
const Scalar coeff(Index i) const
|
||||
{
|
||||
if (m_condition.coeff(i))
|
||||
@@ -88,17 +88,17 @@ class Select : internal::no_assignment_operator,
|
||||
return m_else.coeff(i);
|
||||
}
|
||||
|
||||
const ConditionMatrixType& conditionMatrix() const
|
||||
inline EIGEN_DEVICE_FUNC const ConditionMatrixType& conditionMatrix() const
|
||||
{
|
||||
return m_condition;
|
||||
}
|
||||
|
||||
const ThenMatrixType& thenMatrix() const
|
||||
inline EIGEN_DEVICE_FUNC const ThenMatrixType& thenMatrix() const
|
||||
{
|
||||
return m_then;
|
||||
}
|
||||
|
||||
const ElseMatrixType& elseMatrix() const
|
||||
inline EIGEN_DEVICE_FUNC const ElseMatrixType& elseMatrix() const
|
||||
{
|
||||
return m_else;
|
||||
}
|
||||
|
||||
@@ -32,45 +32,42 @@ namespace internal {
|
||||
template<typename MatrixType, unsigned int UpLo>
|
||||
struct traits<SelfAdjointView<MatrixType, UpLo> > : traits<MatrixType>
|
||||
{
|
||||
typedef typename nested<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
|
||||
typedef MatrixType ExpressionType;
|
||||
typedef typename MatrixType::PlainObject DenseMatrixType;
|
||||
typedef typename MatrixType::PlainObject FullMatrixType;
|
||||
enum {
|
||||
Mode = UpLo | SelfAdjoint,
|
||||
Flags = MatrixTypeNestedCleaned::Flags & (HereditaryBits)
|
||||
& (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)), // FIXME these flags should be preserved
|
||||
CoeffReadCost = MatrixTypeNestedCleaned::CoeffReadCost
|
||||
FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
|
||||
Flags = MatrixTypeNestedCleaned::Flags & (HereditaryBits|FlagsLvalueBit)
|
||||
& (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)) // FIXME these flags should be preserved
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
template <typename Lhs, int LhsMode, bool LhsIsVector,
|
||||
typename Rhs, int RhsMode, bool RhsIsVector>
|
||||
struct SelfadjointProductMatrix;
|
||||
|
||||
// FIXME could also be called SelfAdjointWrapper to be consistent with DiagonalWrapper ??
|
||||
template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
|
||||
: public TriangularBase<SelfAdjointView<MatrixType, UpLo> >
|
||||
template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
|
||||
: public TriangularBase<SelfAdjointView<_MatrixType, UpLo> >
|
||||
{
|
||||
public:
|
||||
|
||||
typedef _MatrixType MatrixType;
|
||||
typedef TriangularBase<SelfAdjointView> Base;
|
||||
typedef typename internal::traits<SelfAdjointView>::MatrixTypeNested MatrixTypeNested;
|
||||
typedef typename internal::traits<SelfAdjointView>::MatrixTypeNestedCleaned MatrixTypeNestedCleaned;
|
||||
|
||||
/** \brief The type of coefficients in this matrix */
|
||||
typedef typename internal::traits<SelfAdjointView>::Scalar Scalar;
|
||||
|
||||
typedef typename MatrixType::Index Index;
|
||||
typedef typename MatrixType::StorageIndex StorageIndex;
|
||||
|
||||
enum {
|
||||
Mode = internal::traits<SelfAdjointView>::Mode
|
||||
Mode = internal::traits<SelfAdjointView>::Mode,
|
||||
Flags = internal::traits<SelfAdjointView>::Flags
|
||||
};
|
||||
typedef typename MatrixType::PlainObject PlainObject;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
|
||||
explicit inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
|
||||
{}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
@@ -98,6 +95,7 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Scalar& coeffRef(Index row, Index col)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_LVALUE(SelfAdjointView);
|
||||
Base::check_coordinates_internal(row, col);
|
||||
return m_matrix.const_cast_derived().coeffRef(row, col);
|
||||
}
|
||||
@@ -111,26 +109,29 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
|
||||
EIGEN_DEVICE_FUNC
|
||||
MatrixTypeNestedCleaned& nestedExpression() { return *const_cast<MatrixTypeNestedCleaned*>(&m_matrix); }
|
||||
|
||||
/** Efficient self-adjoint matrix times vector/matrix product */
|
||||
/** Efficient triangular matrix times vector/matrix product */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
SelfadjointProductMatrix<MatrixType,Mode,false,OtherDerived,0,OtherDerived::IsVectorAtCompileTime>
|
||||
const Product<SelfAdjointView,OtherDerived>
|
||||
operator*(const MatrixBase<OtherDerived>& rhs) const
|
||||
{
|
||||
return SelfadjointProductMatrix
|
||||
<MatrixType,Mode,false,OtherDerived,0,OtherDerived::IsVectorAtCompileTime>
|
||||
(m_matrix, rhs.derived());
|
||||
return Product<SelfAdjointView,OtherDerived>(*this, rhs.derived());
|
||||
}
|
||||
|
||||
/** Efficient vector/matrix times self-adjoint matrix product */
|
||||
/** Efficient vector/matrix times triangular matrix product */
|
||||
template<typename OtherDerived> friend
|
||||
EIGEN_DEVICE_FUNC
|
||||
SelfadjointProductMatrix<OtherDerived,0,OtherDerived::IsVectorAtCompileTime,MatrixType,Mode,false>
|
||||
const Product<OtherDerived,SelfAdjointView>
|
||||
operator*(const MatrixBase<OtherDerived>& lhs, const SelfAdjointView& rhs)
|
||||
{
|
||||
return SelfadjointProductMatrix
|
||||
<OtherDerived,0,OtherDerived::IsVectorAtCompileTime,MatrixType,Mode,false>
|
||||
(lhs.derived(),rhs.m_matrix);
|
||||
return Product<OtherDerived,SelfAdjointView>(lhs.derived(),rhs);
|
||||
}
|
||||
|
||||
friend EIGEN_DEVICE_FUNC
|
||||
const SelfAdjointView<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>,MatrixType>,UpLo>
|
||||
operator*(const Scalar& s, const SelfAdjointView& mat)
|
||||
{
|
||||
return (s*mat.nestedExpression()).template selfadjointView<UpLo>();
|
||||
}
|
||||
|
||||
/** Perform a symmetric rank 2 update of the selfadjoint matrix \c *this:
|
||||
@@ -194,96 +195,56 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename Derived1, typename Derived2, int UnrollCount, bool ClearOpposite>
|
||||
struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), UnrollCount, ClearOpposite>
|
||||
// TODO currently a selfadjoint expression has the form SelfAdjointView<.,.>
|
||||
// in the future selfadjoint-ness should be defined by the expression traits
|
||||
// such that Transpose<SelfAdjointView<.,.> > is valid. (currently TriangularBase::transpose() is overloaded to make it work)
|
||||
template<typename MatrixType, unsigned int Mode>
|
||||
struct evaluator_traits<SelfAdjointView<MatrixType,Mode> >
|
||||
{
|
||||
enum {
|
||||
col = (UnrollCount-1) / Derived1::RowsAtCompileTime,
|
||||
row = (UnrollCount-1) % Derived1::RowsAtCompileTime
|
||||
};
|
||||
typedef typename storage_kind_to_evaluator_kind<typename MatrixType::StorageKind>::Kind Kind;
|
||||
typedef SelfAdjointShape Shape;
|
||||
|
||||
static const int AssumeAliasing = 0;
|
||||
};
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(Derived1 &dst, const Derived2 &src)
|
||||
template<int UpLo, int SetOpposite, typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor, int Version>
|
||||
class triangular_dense_assignment_kernel<UpLo,SelfAdjoint,SetOpposite,DstEvaluatorTypeT,SrcEvaluatorTypeT,Functor,Version>
|
||||
: public generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>
|
||||
{
|
||||
protected:
|
||||
typedef generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version> Base;
|
||||
typedef typename Base::DstXprType DstXprType;
|
||||
typedef typename Base::SrcXprType SrcXprType;
|
||||
using Base::m_dst;
|
||||
using Base::m_src;
|
||||
using Base::m_functor;
|
||||
public:
|
||||
|
||||
typedef typename Base::DstEvaluatorType DstEvaluatorType;
|
||||
typedef typename Base::SrcEvaluatorType SrcEvaluatorType;
|
||||
typedef typename Base::Scalar Scalar;
|
||||
typedef typename Base::AssignmentTraits AssignmentTraits;
|
||||
|
||||
|
||||
EIGEN_DEVICE_FUNC triangular_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
|
||||
: Base(dst, src, func, dstExpr)
|
||||
{}
|
||||
|
||||
EIGEN_DEVICE_FUNC void assignCoeff(Index row, Index col)
|
||||
{
|
||||
triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), UnrollCount-1, ClearOpposite>::run(dst, src);
|
||||
|
||||
if(row == col)
|
||||
dst.coeffRef(row, col) = numext::real(src.coeff(row, col));
|
||||
else if(row < col)
|
||||
dst.coeffRef(col, row) = numext::conj(dst.coeffRef(row, col) = src.coeff(row, col));
|
||||
eigen_internal_assert(row!=col);
|
||||
Scalar tmp = m_src.coeff(row,col);
|
||||
m_functor.assignCoeff(m_dst.coeffRef(row,col), tmp);
|
||||
m_functor.assignCoeff(m_dst.coeffRef(col,row), numext::conj(tmp));
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, 0, ClearOpposite>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(Derived1 &, const Derived2 &) {}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, int UnrollCount, bool ClearOpposite>
|
||||
struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), UnrollCount, ClearOpposite>
|
||||
{
|
||||
enum {
|
||||
col = (UnrollCount-1) / Derived1::RowsAtCompileTime,
|
||||
row = (UnrollCount-1) % Derived1::RowsAtCompileTime
|
||||
};
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(Derived1 &dst, const Derived2 &src)
|
||||
|
||||
EIGEN_DEVICE_FUNC void assignDiagonalCoeff(Index id)
|
||||
{
|
||||
triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), UnrollCount-1, ClearOpposite>::run(dst, src);
|
||||
|
||||
if(row == col)
|
||||
dst.coeffRef(row, col) = numext::real(src.coeff(row, col));
|
||||
else if(row > col)
|
||||
dst.coeffRef(col, row) = numext::conj(dst.coeffRef(row, col) = src.coeff(row, col));
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Lower, 0, ClearOpposite>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(Derived1 &, const Derived2 &) {}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, Dynamic, ClearOpposite>
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
for(Index j = 0; j < dst.cols(); ++j)
|
||||
{
|
||||
for(Index i = 0; i < j; ++i)
|
||||
{
|
||||
dst.copyCoeff(i, j, src);
|
||||
dst.coeffRef(j,i) = numext::conj(dst.coeff(i,j));
|
||||
}
|
||||
dst.copyCoeff(j, j, src);
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Derived1, typename Derived2, bool ClearOpposite>
|
||||
struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Lower, Dynamic, ClearOpposite>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(Derived1 &dst, const Derived2 &src)
|
||||
{
|
||||
typedef typename Derived1::Index Index;
|
||||
for(Index i = 0; i < dst.rows(); ++i)
|
||||
{
|
||||
for(Index j = 0; j < i; ++j)
|
||||
{
|
||||
dst.copyCoeff(i, j, src);
|
||||
dst.coeffRef(j,i) = numext::conj(dst.coeff(i,j));
|
||||
}
|
||||
dst.copyCoeff(i, i, src);
|
||||
}
|
||||
Base::assignCoeff(id,id);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC void assignOppositeCoeff(Index, Index)
|
||||
{ eigen_internal_assert(false && "should never be called"); }
|
||||
};
|
||||
|
||||
} // end namespace internal
|
||||
@@ -297,7 +258,7 @@ template<unsigned int UpLo>
|
||||
typename MatrixBase<Derived>::template ConstSelfAdjointViewReturnType<UpLo>::Type
|
||||
MatrixBase<Derived>::selfadjointView() const
|
||||
{
|
||||
return derived();
|
||||
return typename ConstSelfAdjointViewReturnType<UpLo>::Type(derived());
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
@@ -305,7 +266,7 @@ template<unsigned int UpLo>
|
||||
typename MatrixBase<Derived>::template SelfAdjointViewReturnType<UpLo>::Type
|
||||
MatrixBase<Derived>::selfadjointView()
|
||||
{
|
||||
return derived();
|
||||
return typename SelfAdjointViewReturnType<UpLo>::Type(derived());
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -12,179 +12,11 @@
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
/** \class SelfCwiseBinaryOp
|
||||
* \ingroup Core_Module
|
||||
*
|
||||
* \internal
|
||||
*
|
||||
* \brief Internal helper class for optimizing operators like +=, -=
|
||||
*
|
||||
* This is a pseudo expression class re-implementing the copyCoeff/copyPacket
|
||||
* method to directly performs a +=/-= operations in an optimal way. In particular,
|
||||
* this allows to make sure that the input/output data are loaded only once using
|
||||
* aligned packet loads.
|
||||
*
|
||||
* \sa class SwapWrapper for a similar trick.
|
||||
*/
|
||||
|
||||
namespace internal {
|
||||
template<typename BinaryOp, typename Lhs, typename Rhs>
|
||||
struct traits<SelfCwiseBinaryOp<BinaryOp,Lhs,Rhs> >
|
||||
: traits<CwiseBinaryOp<BinaryOp,Lhs,Rhs> >
|
||||
{
|
||||
enum {
|
||||
// Note that it is still a good idea to preserve the DirectAccessBit
|
||||
// so that assign can correctly align the data.
|
||||
Flags = traits<CwiseBinaryOp<BinaryOp,Lhs,Rhs> >::Flags | (Lhs::Flags&AlignedBit) | (Lhs::Flags&DirectAccessBit) | (Lhs::Flags&LvalueBit),
|
||||
OuterStrideAtCompileTime = Lhs::OuterStrideAtCompileTime,
|
||||
InnerStrideAtCompileTime = Lhs::InnerStrideAtCompileTime
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
template<typename BinaryOp, typename Lhs, typename Rhs> class SelfCwiseBinaryOp
|
||||
: public internal::dense_xpr_base< SelfCwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
|
||||
{
|
||||
public:
|
||||
|
||||
typedef typename internal::dense_xpr_base<SelfCwiseBinaryOp>::type Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(SelfCwiseBinaryOp)
|
||||
|
||||
typedef typename internal::packet_traits<Scalar>::type Packet;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline SelfCwiseBinaryOp(Lhs& xpr, const BinaryOp& func = BinaryOp()) : m_matrix(xpr), m_functor(func) {}
|
||||
|
||||
EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.rows(); }
|
||||
EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.cols(); }
|
||||
EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_matrix.outerStride(); }
|
||||
EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_matrix.innerStride(); }
|
||||
EIGEN_DEVICE_FUNC inline const Scalar* data() const { return m_matrix.data(); }
|
||||
|
||||
// note that this function is needed by assign to correctly align loads/stores
|
||||
// TODO make Assign use .data()
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Scalar& coeffRef(Index row, Index col)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_LVALUE(Lhs)
|
||||
return m_matrix.const_cast_derived().coeffRef(row, col);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline const Scalar& coeffRef(Index row, Index col) const
|
||||
{
|
||||
return m_matrix.coeffRef(row, col);
|
||||
}
|
||||
|
||||
// note that this function is needed by assign to correctly align loads/stores
|
||||
// TODO make Assign use .data()
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Scalar& coeffRef(Index index)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_LVALUE(Lhs)
|
||||
return m_matrix.const_cast_derived().coeffRef(index);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline const Scalar& coeffRef(Index index) const
|
||||
{
|
||||
return m_matrix.const_cast_derived().coeffRef(index);
|
||||
}
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
OtherDerived& _other = other.const_cast_derived();
|
||||
eigen_internal_assert(row >= 0 && row < rows()
|
||||
&& col >= 0 && col < cols());
|
||||
Scalar& tmp = m_matrix.coeffRef(row,col);
|
||||
tmp = m_functor(tmp, _other.coeff(row,col));
|
||||
}
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
OtherDerived& _other = other.const_cast_derived();
|
||||
eigen_internal_assert(index >= 0 && index < m_matrix.size());
|
||||
Scalar& tmp = m_matrix.coeffRef(index);
|
||||
tmp = m_functor(tmp, _other.coeff(index));
|
||||
}
|
||||
|
||||
template<typename OtherDerived, int StoreMode, int LoadMode>
|
||||
void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
OtherDerived& _other = other.const_cast_derived();
|
||||
eigen_internal_assert(row >= 0 && row < rows()
|
||||
&& col >= 0 && col < cols());
|
||||
m_matrix.template writePacket<StoreMode>(row, col,
|
||||
m_functor.packetOp(m_matrix.template packet<StoreMode>(row, col),_other.template packet<LoadMode>(row, col)) );
|
||||
}
|
||||
|
||||
template<typename OtherDerived, int StoreMode, int LoadMode>
|
||||
void copyPacket(Index index, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
OtherDerived& _other = other.const_cast_derived();
|
||||
eigen_internal_assert(index >= 0 && index < m_matrix.size());
|
||||
m_matrix.template writePacket<StoreMode>(index,
|
||||
m_functor.packetOp(m_matrix.template packet<StoreMode>(index),_other.template packet<LoadMode>(index)) );
|
||||
}
|
||||
|
||||
// reimplement lazyAssign to handle complex *= real
|
||||
// see CwiseBinaryOp ctor for details
|
||||
template<typename RhsDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_STRONG_INLINE SelfCwiseBinaryOp& lazyAssign(const DenseBase<RhsDerived>& rhs)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs,RhsDerived)
|
||||
EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename RhsDerived::Scalar);
|
||||
|
||||
#ifdef EIGEN_DEBUG_ASSIGN
|
||||
internal::assign_traits<SelfCwiseBinaryOp, RhsDerived>::debug();
|
||||
#endif
|
||||
eigen_assert(rows() == rhs.rows() && cols() == rhs.cols());
|
||||
internal::assign_impl<SelfCwiseBinaryOp, RhsDerived>::run(*this,rhs.derived());
|
||||
#ifndef EIGEN_NO_DEBUG
|
||||
this->checkTransposeAliasing(rhs.derived());
|
||||
#endif
|
||||
return *this;
|
||||
}
|
||||
|
||||
// overloaded to honor evaluation of special matrices
|
||||
// maybe another solution would be to not use SelfCwiseBinaryOp
|
||||
// at first...
|
||||
EIGEN_DEVICE_FUNC
|
||||
SelfCwiseBinaryOp& operator=(const Rhs& _rhs)
|
||||
{
|
||||
typename internal::nested<Rhs>::type rhs(_rhs);
|
||||
return Base::operator=(rhs);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
Lhs& expression() const
|
||||
{
|
||||
return m_matrix;
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
const BinaryOp& functor() const
|
||||
{
|
||||
return m_functor;
|
||||
}
|
||||
|
||||
protected:
|
||||
Lhs& m_matrix;
|
||||
const BinaryOp& m_functor;
|
||||
|
||||
private:
|
||||
SelfCwiseBinaryOp& operator=(const SelfCwiseBinaryOp&);
|
||||
};
|
||||
|
||||
template<typename Derived>
|
||||
inline Derived& DenseBase<Derived>::operator*=(const Scalar& other)
|
||||
{
|
||||
typedef typename Derived::PlainObject PlainObject;
|
||||
SelfCwiseBinaryOp<internal::scalar_product_op<Scalar>, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
|
||||
tmp = PlainObject::Constant(rows(),cols(),other);
|
||||
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::mul_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
@@ -192,8 +24,7 @@ template<typename Derived>
|
||||
inline Derived& ArrayBase<Derived>::operator+=(const Scalar& other)
|
||||
{
|
||||
typedef typename Derived::PlainObject PlainObject;
|
||||
SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
|
||||
tmp = PlainObject::Constant(rows(),cols(),other);
|
||||
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
@@ -201,8 +32,7 @@ template<typename Derived>
|
||||
inline Derived& ArrayBase<Derived>::operator-=(const Scalar& other)
|
||||
{
|
||||
typedef typename Derived::PlainObject PlainObject;
|
||||
SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
|
||||
tmp = PlainObject::Constant(rows(),cols(),other);
|
||||
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::sub_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
@@ -210,8 +40,7 @@ template<typename Derived>
|
||||
inline Derived& DenseBase<Derived>::operator/=(const Scalar& other)
|
||||
{
|
||||
typedef typename Derived::PlainObject PlainObject;
|
||||
SelfCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
|
||||
tmp = PlainObject::Constant(rows(),cols(), other);
|
||||
internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar>());
|
||||
return derived();
|
||||
}
|
||||
|
||||
|
||||
150
Eigen/src/Core/Solve.h
Normal file
150
Eigen/src/Core/Solve.h
Normal file
@@ -0,0 +1,150 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2014 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_SOLVE_H
|
||||
#define EIGEN_SOLVE_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
template<typename Decomposition, typename RhsType, typename StorageKind> class SolveImpl;
|
||||
|
||||
/** \class Solve
|
||||
* \ingroup Core_Module
|
||||
*
|
||||
* \brief Pseudo expression representing a solving operation
|
||||
*
|
||||
* \tparam Decomposition the type of the matrix or decomposion object
|
||||
* \tparam Rhstype the type of the right-hand side
|
||||
*
|
||||
* This class represents an expression of A.solve(B)
|
||||
* and most of the time this is the only way it is used.
|
||||
*
|
||||
*/
|
||||
namespace internal {
|
||||
|
||||
// this solve_traits class permits to determine the evaluation type with respect to storage kind (Dense vs Sparse)
|
||||
template<typename Decomposition, typename RhsType,typename StorageKind> struct solve_traits;
|
||||
|
||||
template<typename Decomposition, typename RhsType>
|
||||
struct solve_traits<Decomposition,RhsType,Dense>
|
||||
{
|
||||
typedef typename Decomposition::MatrixType MatrixType;
|
||||
typedef Matrix<typename RhsType::Scalar,
|
||||
MatrixType::ColsAtCompileTime,
|
||||
RhsType::ColsAtCompileTime,
|
||||
RhsType::PlainObject::Options,
|
||||
MatrixType::MaxColsAtCompileTime,
|
||||
RhsType::MaxColsAtCompileTime> PlainObject;
|
||||
};
|
||||
|
||||
template<typename Decomposition, typename RhsType>
|
||||
struct traits<Solve<Decomposition, RhsType> >
|
||||
: traits<typename solve_traits<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>::PlainObject>
|
||||
{
|
||||
typedef typename solve_traits<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>::PlainObject PlainObject;
|
||||
typedef typename promote_index_type<typename Decomposition::StorageIndex, typename RhsType::StorageIndex>::type StorageIndex;
|
||||
typedef traits<PlainObject> BaseTraits;
|
||||
enum {
|
||||
Flags = BaseTraits::Flags & RowMajorBit,
|
||||
CoeffReadCost = Dynamic
|
||||
};
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
|
||||
template<typename Decomposition, typename RhsType>
|
||||
class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::StorageKind>
|
||||
{
|
||||
public:
|
||||
typedef typename internal::traits<Solve>::PlainObject PlainObject;
|
||||
typedef typename internal::traits<Solve>::StorageIndex StorageIndex;
|
||||
|
||||
Solve(const Decomposition &dec, const RhsType &rhs)
|
||||
: m_dec(dec), m_rhs(rhs)
|
||||
{}
|
||||
|
||||
EIGEN_DEVICE_FUNC Index rows() const { return m_dec.cols(); }
|
||||
EIGEN_DEVICE_FUNC Index cols() const { return m_rhs.cols(); }
|
||||
|
||||
EIGEN_DEVICE_FUNC const Decomposition& dec() const { return m_dec; }
|
||||
EIGEN_DEVICE_FUNC const RhsType& rhs() const { return m_rhs; }
|
||||
|
||||
protected:
|
||||
const Decomposition &m_dec;
|
||||
const RhsType &m_rhs;
|
||||
};
|
||||
|
||||
|
||||
// Specialization of the Solve expression for dense results
|
||||
template<typename Decomposition, typename RhsType>
|
||||
class SolveImpl<Decomposition,RhsType,Dense>
|
||||
: public MatrixBase<Solve<Decomposition,RhsType> >
|
||||
{
|
||||
typedef Solve<Decomposition,RhsType> Derived;
|
||||
|
||||
public:
|
||||
|
||||
typedef MatrixBase<Solve<Decomposition,RhsType> > Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
|
||||
|
||||
private:
|
||||
|
||||
Scalar coeff(Index row, Index col) const;
|
||||
Scalar coeff(Index i) const;
|
||||
};
|
||||
|
||||
// Generic API dispatcher
|
||||
template<typename Decomposition, typename RhsType, typename StorageKind>
|
||||
class SolveImpl : public internal::generic_xpr_base<Solve<Decomposition,RhsType>, MatrixXpr, StorageKind>::type
|
||||
{
|
||||
public:
|
||||
typedef typename internal::generic_xpr_base<Solve<Decomposition,RhsType>, MatrixXpr, StorageKind>::type Base;
|
||||
};
|
||||
|
||||
namespace internal {
|
||||
|
||||
// Evaluator of Solve -> eval into a temporary
|
||||
template<typename Decomposition, typename RhsType>
|
||||
struct evaluator<Solve<Decomposition,RhsType> >
|
||||
: public evaluator<typename Solve<Decomposition,RhsType>::PlainObject>
|
||||
{
|
||||
typedef Solve<Decomposition,RhsType> SolveType;
|
||||
typedef typename SolveType::PlainObject PlainObject;
|
||||
typedef evaluator<PlainObject> Base;
|
||||
|
||||
EIGEN_DEVICE_FUNC explicit evaluator(const SolveType& solve)
|
||||
: m_result(solve.rows(), solve.cols())
|
||||
{
|
||||
::new (static_cast<Base*>(this)) Base(m_result);
|
||||
solve.dec()._solve_impl(solve.rhs(), m_result);
|
||||
}
|
||||
|
||||
protected:
|
||||
PlainObject m_result;
|
||||
};
|
||||
|
||||
// Specialization for "dst = dec.solve(rhs)"
|
||||
// NOTE we need to specialize it for Dense2Dense to avoid ambiguous specialization error and a Sparse2Sparse specialization must exist somewhere
|
||||
template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
|
||||
struct Assignment<DstXprType, Solve<DecType,RhsType>, internal::assign_op<Scalar>, Dense2Dense, Scalar>
|
||||
{
|
||||
typedef Solve<DecType,RhsType> SrcXprType;
|
||||
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar> &)
|
||||
{
|
||||
// FIXME shall we resize dst here?
|
||||
src.dec()._solve_impl(src.rhs(), dst);
|
||||
}
|
||||
};
|
||||
|
||||
} // end namepsace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_SOLVE_H
|
||||
@@ -68,7 +68,7 @@ struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,1>
|
||||
if(!useRhsDirectly)
|
||||
MappedRhs(actualRhs,rhs.size()) = rhs;
|
||||
|
||||
triangular_solve_vector<LhsScalar, RhsScalar, typename Lhs::Index, Side, Mode, LhsProductTraits::NeedToConjugate,
|
||||
triangular_solve_vector<LhsScalar, RhsScalar, Index, Side, Mode, LhsProductTraits::NeedToConjugate,
|
||||
(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor>
|
||||
::run(actualLhs.cols(), actualLhs.data(), actualLhs.outerStride(), actualRhs);
|
||||
|
||||
@@ -82,7 +82,6 @@ template<typename Lhs, typename Rhs, int Side, int Mode>
|
||||
struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,Dynamic>
|
||||
{
|
||||
typedef typename Rhs::Scalar Scalar;
|
||||
typedef typename Rhs::Index Index;
|
||||
typedef blas_traits<Lhs> LhsProductTraits;
|
||||
typedef typename LhsProductTraits::DirectLinearAccessType ActualLhsType;
|
||||
|
||||
@@ -96,7 +95,7 @@ struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,Dynamic>
|
||||
typedef internal::gemm_blocking_space<(Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
|
||||
Rhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxRowsAtCompileTime,4> BlockingType;
|
||||
|
||||
BlockingType blocking(rhs.rows(), rhs.cols(), size);
|
||||
BlockingType blocking(rhs.rows(), rhs.cols(), size, 1, false);
|
||||
|
||||
triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
|
||||
(Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor>
|
||||
@@ -171,10 +170,10 @@ struct triangular_solver_selector<Lhs,Rhs,OnTheRight,Mode,CompleteUnrolling,1> {
|
||||
*/
|
||||
template<typename MatrixType, unsigned int Mode>
|
||||
template<int Side, typename OtherDerived>
|
||||
void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
|
||||
void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
|
||||
{
|
||||
OtherDerived& other = _other.const_cast_derived();
|
||||
eigen_assert( cols() == rows() && ((Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols())) );
|
||||
eigen_assert( derived().cols() == derived().rows() && ((Side==OnTheLeft && derived().cols() == other.rows()) || (Side==OnTheRight && derived().cols() == other.cols())) );
|
||||
eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
|
||||
|
||||
enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit && OtherDerived::IsVectorAtCompileTime };
|
||||
@@ -183,7 +182,7 @@ void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived
|
||||
OtherCopy otherCopy(other);
|
||||
|
||||
internal::triangular_solver_selector<MatrixType, typename internal::remove_reference<OtherCopy>::type,
|
||||
Side, Mode>::run(nestedExpression(), otherCopy);
|
||||
Side, Mode>::run(derived().nestedExpression(), otherCopy);
|
||||
|
||||
if (copy)
|
||||
other = otherCopy;
|
||||
@@ -199,8 +198,8 @@ void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived
|
||||
* diagonal must be non zero). It works as a forward (resp. backward) substitution if \c *this
|
||||
* is an upper (resp. lower) triangular matrix.
|
||||
*
|
||||
* Example: \include MatrixBase_marked.cpp
|
||||
* Output: \verbinclude MatrixBase_marked.out
|
||||
* Example: \include Triangular_solve.cpp
|
||||
* Output: \verbinclude Triangular_solve.out
|
||||
*
|
||||
* This function returns an expression of the inverse-multiply and can works in-place if it is assigned
|
||||
* to the same matrix or vector \a other.
|
||||
@@ -213,9 +212,9 @@ void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived
|
||||
template<typename Derived, unsigned int Mode>
|
||||
template<int Side, typename Other>
|
||||
const internal::triangular_solve_retval<Side,TriangularView<Derived,Mode>,Other>
|
||||
TriangularView<Derived,Mode>::solve(const MatrixBase<Other>& other) const
|
||||
TriangularViewImpl<Derived,Mode,Dense>::solve(const MatrixBase<Other>& other) const
|
||||
{
|
||||
return internal::triangular_solve_retval<Side,TriangularView,Other>(*this, other.derived());
|
||||
return internal::triangular_solve_retval<Side,TriangularViewType,Other>(derived(), other.derived());
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
@@ -232,7 +231,6 @@ template<int Side, typename TriangularType, typename Rhs> struct triangular_solv
|
||||
{
|
||||
typedef typename remove_all<typename Rhs::Nested>::type RhsNestedCleaned;
|
||||
typedef ReturnByValue<triangular_solve_retval> Base;
|
||||
typedef typename Base::Index Index;
|
||||
|
||||
triangular_solve_retval(const TriangularType& tri, const Rhs& rhs)
|
||||
: m_triangularMatrix(tri), m_rhs(rhs)
|
||||
|
||||
@@ -17,7 +17,6 @@ namespace internal {
|
||||
template<typename ExpressionType, typename Scalar>
|
||||
inline void stable_norm_kernel(const ExpressionType& bl, Scalar& ssq, Scalar& scale, Scalar& invScale)
|
||||
{
|
||||
using std::max;
|
||||
Scalar maxCoeff = bl.cwiseAbs().maxCoeff();
|
||||
|
||||
if(maxCoeff>scale)
|
||||
@@ -56,10 +55,7 @@ inline typename NumTraits<typename traits<Derived>::Scalar>::Real
|
||||
blueNorm_impl(const EigenBase<Derived>& _vec)
|
||||
{
|
||||
typedef typename Derived::RealScalar RealScalar;
|
||||
typedef typename Derived::Index Index;
|
||||
using std::pow;
|
||||
EIGEN_USING_STD_MATH(min);
|
||||
EIGEN_USING_STD_MATH(max);
|
||||
using std::sqrt;
|
||||
using std::abs;
|
||||
const Derived& vec(_vec.derived());
|
||||
@@ -136,8 +132,8 @@ blueNorm_impl(const EigenBase<Derived>& _vec)
|
||||
}
|
||||
else
|
||||
return sqrt(amed);
|
||||
asml = (min)(abig, amed);
|
||||
abig = (max)(abig, amed);
|
||||
asml = numext::mini(abig, amed);
|
||||
abig = numext::maxi(abig, amed);
|
||||
if(asml <= abig*relerr)
|
||||
return abig;
|
||||
else
|
||||
@@ -160,21 +156,33 @@ template<typename Derived>
|
||||
inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
|
||||
MatrixBase<Derived>::stableNorm() const
|
||||
{
|
||||
EIGEN_USING_STD_MATH(min);
|
||||
using std::sqrt;
|
||||
using std::abs;
|
||||
const Index blockSize = 4096;
|
||||
RealScalar scale(0);
|
||||
RealScalar invScale(1);
|
||||
RealScalar ssq(0); // sum of square
|
||||
|
||||
typedef typename internal::nested_eval<Derived,2>::type DerivedCopy;
|
||||
typedef typename internal::remove_all<DerivedCopy>::type DerivedCopyClean;
|
||||
DerivedCopy copy(derived());
|
||||
|
||||
enum {
|
||||
Alignment = (int(Flags)&DirectAccessBit) || (int(Flags)&AlignedBit) ? 1 : 0
|
||||
CanAlign = (int(Flags)&DirectAccessBit) || (int(internal::evaluator<DerivedCopyClean>::Alignment)>0) // FIXME
|
||||
};
|
||||
typedef typename internal::conditional<CanAlign, Ref<const Matrix<Scalar,Dynamic,1,0,blockSize,1>, internal::evaluator<DerivedCopyClean>::Alignment>,
|
||||
typename DerivedCopyClean
|
||||
::ConstSegmentReturnType>::type SegmentWrapper;
|
||||
Index n = size();
|
||||
Index bi = internal::first_aligned(derived());
|
||||
|
||||
if(n==1)
|
||||
return abs(this->coeff(0));
|
||||
|
||||
Index bi = internal::first_default_aligned(copy);
|
||||
if (bi>0)
|
||||
internal::stable_norm_kernel(this->head(bi), ssq, scale, invScale);
|
||||
internal::stable_norm_kernel(copy.head(bi), ssq, scale, invScale);
|
||||
for (; bi<n; bi+=blockSize)
|
||||
internal::stable_norm_kernel(this->segment(bi,(min)(blockSize, n - bi)).template forceAlignedAccessIf<Alignment>(), ssq, scale, invScale);
|
||||
internal::stable_norm_kernel(SegmentWrapper(copy.segment(bi,numext::mini(blockSize, n - bi))), ssq, scale, invScale);
|
||||
return scale * sqrt(ssq);
|
||||
}
|
||||
|
||||
|
||||
@@ -44,7 +44,7 @@ template<int _OuterStrideAtCompileTime, int _InnerStrideAtCompileTime>
|
||||
class Stride
|
||||
{
|
||||
public:
|
||||
typedef DenseIndex Index;
|
||||
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
|
||||
enum {
|
||||
InnerStrideAtCompileTime = _InnerStrideAtCompileTime,
|
||||
OuterStrideAtCompileTime = _OuterStrideAtCompileTime
|
||||
@@ -86,26 +86,24 @@ class Stride
|
||||
|
||||
/** \brief Convenience specialization of Stride to specify only an inner stride
|
||||
* See class Map for some examples */
|
||||
template<int Value = Dynamic>
|
||||
template<int Value>
|
||||
class InnerStride : public Stride<0, Value>
|
||||
{
|
||||
typedef Stride<0, Value> Base;
|
||||
public:
|
||||
typedef DenseIndex Index;
|
||||
EIGEN_DEVICE_FUNC InnerStride() : Base() {}
|
||||
EIGEN_DEVICE_FUNC InnerStride(Index v) : Base(0, v) {}
|
||||
EIGEN_DEVICE_FUNC InnerStride(Index v) : Base(0, v) {} // FIXME making this explicit could break valid code
|
||||
};
|
||||
|
||||
/** \brief Convenience specialization of Stride to specify only an outer stride
|
||||
* See class Map for some examples */
|
||||
template<int Value = Dynamic>
|
||||
template<int Value>
|
||||
class OuterStride : public Stride<Value, 0>
|
||||
{
|
||||
typedef Stride<Value, 0> Base;
|
||||
public:
|
||||
typedef DenseIndex Index;
|
||||
EIGEN_DEVICE_FUNC OuterStride() : Base() {}
|
||||
EIGEN_DEVICE_FUNC OuterStride(Index v) : Base(v,0) {}
|
||||
EIGEN_DEVICE_FUNC OuterStride(Index v) : Base(v,0) {} // FIXME making this explicit could break valid code
|
||||
};
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -12,129 +12,56 @@
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
/** \class SwapWrapper
|
||||
* \ingroup Core_Module
|
||||
*
|
||||
* \internal
|
||||
*
|
||||
* \brief Internal helper class for swapping two expressions
|
||||
*/
|
||||
namespace internal {
|
||||
template<typename ExpressionType>
|
||||
struct traits<SwapWrapper<ExpressionType> > : traits<ExpressionType> {};
|
||||
}
|
||||
|
||||
template<typename ExpressionType> class SwapWrapper
|
||||
: public internal::dense_xpr_base<SwapWrapper<ExpressionType> >::type
|
||||
// Overload default assignPacket behavior for swapping them
|
||||
template<typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT>
|
||||
class generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar>, Specialized>
|
||||
: public generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar>, BuiltIn>
|
||||
{
|
||||
public:
|
||||
|
||||
typedef typename internal::dense_xpr_base<SwapWrapper>::type Base;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(SwapWrapper)
|
||||
typedef typename internal::packet_traits<Scalar>::type Packet;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline SwapWrapper(ExpressionType& xpr) : m_expression(xpr) {}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index rows() const { return m_expression.rows(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index cols() const { return m_expression.cols(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index outerStride() const { return m_expression.outerStride(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Index innerStride() const { return m_expression.innerStride(); }
|
||||
|
||||
typedef typename internal::conditional<
|
||||
internal::is_lvalue<ExpressionType>::value,
|
||||
Scalar,
|
||||
const Scalar
|
||||
>::type ScalarWithConstIfNotLvalue;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline const Scalar* data() const { return m_expression.data(); }
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Scalar& coeffRef(Index rowId, Index colId)
|
||||
{
|
||||
return m_expression.const_cast_derived().coeffRef(rowId, colId);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Scalar& coeffRef(Index index)
|
||||
{
|
||||
return m_expression.const_cast_derived().coeffRef(index);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Scalar& coeffRef(Index rowId, Index colId) const
|
||||
{
|
||||
return m_expression.coeffRef(rowId, colId);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Scalar& coeffRef(Index index) const
|
||||
{
|
||||
return m_expression.coeffRef(index);
|
||||
}
|
||||
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void copyCoeff(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
OtherDerived& _other = other.const_cast_derived();
|
||||
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>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
OtherDerived& _other = other.const_cast_derived();
|
||||
eigen_internal_assert(index >= 0 && index < m_expression.size());
|
||||
Scalar tmp = m_expression.coeff(index);
|
||||
m_expression.coeffRef(index) = _other.coeff(index);
|
||||
_other.coeffRef(index) = tmp;
|
||||
}
|
||||
|
||||
template<typename OtherDerived, int StoreMode, int LoadMode>
|
||||
void copyPacket(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
OtherDerived& _other = other.const_cast_derived();
|
||||
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>(rowId, colId, tmp);
|
||||
}
|
||||
|
||||
template<typename OtherDerived, int StoreMode, int LoadMode>
|
||||
void copyPacket(Index index, const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
OtherDerived& _other = other.const_cast_derived();
|
||||
eigen_internal_assert(index >= 0 && index < m_expression.size());
|
||||
Packet tmp = m_expression.template packet<StoreMode>(index);
|
||||
m_expression.template writePacket<StoreMode>(index,
|
||||
_other.template packet<LoadMode>(index)
|
||||
);
|
||||
_other.template writePacket<LoadMode>(index, tmp);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
ExpressionType& expression() const { return m_expression; }
|
||||
|
||||
protected:
|
||||
ExpressionType& m_expression;
|
||||
protected:
|
||||
typedef generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, swap_assign_op<typename DstEvaluatorTypeT::Scalar>, BuiltIn> Base;
|
||||
using Base::m_dst;
|
||||
using Base::m_src;
|
||||
using Base::m_functor;
|
||||
|
||||
public:
|
||||
typedef typename Base::Scalar Scalar;
|
||||
typedef typename Base::DstXprType DstXprType;
|
||||
typedef swap_assign_op<Scalar> Functor;
|
||||
|
||||
EIGEN_DEVICE_FUNC generic_dense_assignment_kernel(DstEvaluatorTypeT &dst, const SrcEvaluatorTypeT &src, const Functor &func, DstXprType& dstExpr)
|
||||
: Base(dst, src, func, dstExpr)
|
||||
{}
|
||||
|
||||
template<int StoreMode, int LoadMode, typename PacketType>
|
||||
void assignPacket(Index row, Index col)
|
||||
{
|
||||
PacketType tmp = m_src.template packet<LoadMode,PacketType>(row,col);
|
||||
const_cast<SrcEvaluatorTypeT&>(m_src).template writePacket<LoadMode>(row,col, m_dst.template packet<StoreMode,PacketType>(row,col));
|
||||
m_dst.template writePacket<StoreMode>(row,col,tmp);
|
||||
}
|
||||
|
||||
template<int StoreMode, int LoadMode, typename PacketType>
|
||||
void assignPacket(Index index)
|
||||
{
|
||||
PacketType tmp = m_src.template packet<LoadMode,PacketType>(index);
|
||||
const_cast<SrcEvaluatorTypeT&>(m_src).template writePacket<LoadMode>(index, m_dst.template packet<StoreMode,PacketType>(index));
|
||||
m_dst.template writePacket<StoreMode>(index,tmp);
|
||||
}
|
||||
|
||||
// TODO find a simple way not to have to copy/paste this function from generic_dense_assignment_kernel, by simple I mean no CRTP (Gael)
|
||||
template<int StoreMode, int LoadMode, typename PacketType>
|
||||
void assignPacketByOuterInner(Index outer, Index inner)
|
||||
{
|
||||
Index row = Base::rowIndexByOuterInner(outer, inner);
|
||||
Index col = Base::colIndexByOuterInner(outer, inner);
|
||||
assignPacket<StoreMode,LoadMode,PacketType>(row, col);
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_SWAP_H
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
|
||||
// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
|
||||
// Copyright (C) 2009-2014 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
|
||||
@@ -29,13 +29,10 @@ namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
template<typename MatrixType>
|
||||
struct traits<Transpose<MatrixType> > : traits<MatrixType>
|
||||
struct traits<Transpose<MatrixType> > : public traits<MatrixType>
|
||||
{
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename nested<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedPlain;
|
||||
typedef typename traits<MatrixType>::StorageKind StorageKind;
|
||||
typedef typename traits<MatrixType>::XprKind XprKind;
|
||||
enum {
|
||||
RowsAtCompileTime = MatrixType::ColsAtCompileTime,
|
||||
ColsAtCompileTime = MatrixType::RowsAtCompileTime,
|
||||
@@ -45,7 +42,6 @@ struct traits<Transpose<MatrixType> > : traits<MatrixType>
|
||||
Flags0 = MatrixTypeNestedPlain::Flags & ~(LvalueBit | NestByRefBit),
|
||||
Flags1 = Flags0 | FlagsLvalueBit,
|
||||
Flags = Flags1 ^ RowMajorBit,
|
||||
CoeffReadCost = MatrixTypeNestedPlain::CoeffReadCost,
|
||||
InnerStrideAtCompileTime = inner_stride_at_compile_time<MatrixType>::ret,
|
||||
OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret
|
||||
};
|
||||
@@ -61,9 +57,10 @@ template<typename MatrixType> class Transpose
|
||||
|
||||
typedef typename TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
|
||||
EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
|
||||
typedef typename internal::remove_all<MatrixType>::type NestedExpression;
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline Transpose(MatrixType& a_matrix) : m_matrix(a_matrix) {}
|
||||
explicit inline Transpose(MatrixType& matrix) : m_matrix(matrix) {}
|
||||
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)
|
||||
|
||||
@@ -100,12 +97,22 @@ struct TransposeImpl_base<MatrixType, false>
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
// Generic API dispatcher
|
||||
template<typename XprType, typename StorageKind>
|
||||
class TransposeImpl
|
||||
: public internal::generic_xpr_base<Transpose<XprType> >::type
|
||||
{
|
||||
public:
|
||||
typedef typename internal::generic_xpr_base<Transpose<XprType> >::type Base;
|
||||
};
|
||||
|
||||
template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
|
||||
: public internal::TransposeImpl_base<MatrixType>::type
|
||||
{
|
||||
public:
|
||||
|
||||
typedef typename internal::TransposeImpl_base<MatrixType>::type Base;
|
||||
using Base::coeffRef;
|
||||
EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>)
|
||||
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl)
|
||||
|
||||
@@ -118,23 +125,10 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
|
||||
const Scalar
|
||||
>::type ScalarWithConstIfNotLvalue;
|
||||
|
||||
inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
|
||||
inline const Scalar* data() const { return derived().nestedExpression().data(); }
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline ScalarWithConstIfNotLvalue& coeffRef(Index rowId, Index colId)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
|
||||
return derived().nestedExpression().const_cast_derived().coeffRef(colId, rowId);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
|
||||
return derived().nestedExpression().const_cast_derived().coeffRef(index);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
|
||||
EIGEN_DEVICE_FUNC inline const Scalar* data() const { return derived().nestedExpression().data(); }
|
||||
|
||||
// FIXME: shall we keep the const version of coeffRef?
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline const Scalar& coeffRef(Index rowId, Index colId) const
|
||||
{
|
||||
@@ -146,42 +140,6 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
|
||||
{
|
||||
return derived().nestedExpression().coeffRef(index);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline CoeffReturnType coeff(Index rowId, Index colId) const
|
||||
{
|
||||
return derived().nestedExpression().coeff(colId, rowId);
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline CoeffReturnType coeff(Index index) const
|
||||
{
|
||||
return derived().nestedExpression().coeff(index);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline const PacketScalar packet(Index rowId, Index colId) const
|
||||
{
|
||||
return derived().nestedExpression().template packet<LoadMode>(colId, rowId);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline void writePacket(Index rowId, Index colId, const PacketScalar& x)
|
||||
{
|
||||
derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(colId, rowId, x);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline const PacketScalar packet(Index index) const
|
||||
{
|
||||
return derived().nestedExpression().template packet<LoadMode>(index);
|
||||
}
|
||||
|
||||
template<int LoadMode>
|
||||
inline void writePacket(Index index, const PacketScalar& x)
|
||||
{
|
||||
derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(index, x);
|
||||
}
|
||||
};
|
||||
|
||||
/** \returns an expression of the transpose of *this.
|
||||
@@ -207,7 +165,7 @@ template<typename Derived>
|
||||
inline Transpose<Derived>
|
||||
DenseBase<Derived>::transpose()
|
||||
{
|
||||
return derived();
|
||||
return TransposeReturnType(derived());
|
||||
}
|
||||
|
||||
/** This is the const version of transpose().
|
||||
@@ -245,8 +203,7 @@ template<typename Derived>
|
||||
inline const typename MatrixBase<Derived>::AdjointReturnType
|
||||
MatrixBase<Derived>::adjoint() const
|
||||
{
|
||||
return this->transpose(); // in the complex case, the .conjugate() is be implicit here
|
||||
// due to implicit conversion to return type
|
||||
return AdjointReturnType(this->transpose());
|
||||
}
|
||||
|
||||
/***************************************************************************
|
||||
@@ -256,18 +213,38 @@ MatrixBase<Derived>::adjoint() const
|
||||
namespace internal {
|
||||
|
||||
template<typename MatrixType,
|
||||
bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime!=Dynamic>
|
||||
bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime!=Dynamic,
|
||||
bool MatchPacketSize =
|
||||
(int(MatrixType::RowsAtCompileTime) == int(internal::packet_traits<typename MatrixType::Scalar>::size))
|
||||
&& (internal::evaluator<MatrixType>::Flags&PacketAccessBit) >
|
||||
struct inplace_transpose_selector;
|
||||
|
||||
template<typename MatrixType>
|
||||
struct inplace_transpose_selector<MatrixType,true> { // square matrix
|
||||
struct inplace_transpose_selector<MatrixType,true,false> { // square matrix
|
||||
static void run(MatrixType& m) {
|
||||
m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
|
||||
}
|
||||
};
|
||||
|
||||
// TODO: vectorized path is currently limited to LargestPacketSize x LargestPacketSize cases only.
|
||||
template<typename MatrixType>
|
||||
struct inplace_transpose_selector<MatrixType,false> { // non square matrix
|
||||
struct inplace_transpose_selector<MatrixType,true,true> { // PacketSize x PacketSize
|
||||
static void run(MatrixType& m) {
|
||||
typedef typename MatrixType::Scalar Scalar;
|
||||
typedef typename internal::packet_traits<typename MatrixType::Scalar>::type Packet;
|
||||
const Index PacketSize = internal::packet_traits<Scalar>::size;
|
||||
const Index Alignment = internal::evaluator<MatrixType>::Alignment;
|
||||
PacketBlock<Packet> A;
|
||||
for (Index i=0; i<PacketSize; ++i)
|
||||
A.packet[i] = m.template packetByOuterInner<Alignment>(i,0);
|
||||
internal::ptranspose(A);
|
||||
for (Index i=0; i<PacketSize; ++i)
|
||||
m.template writePacket<Alignment>(m.rowIndexByOuterInner(i,0), m.colIndexByOuterInner(i,0), A.packet[i]);
|
||||
}
|
||||
};
|
||||
|
||||
template<typename MatrixType,bool MatchPacketSize>
|
||||
struct inplace_transpose_selector<MatrixType,false,MatchPacketSize> { // non square matrix
|
||||
static void run(MatrixType& m) {
|
||||
if (m.rows()==m.cols())
|
||||
m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
|
||||
@@ -340,14 +317,6 @@ inline void MatrixBase<Derived>::adjointInPlace()
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename BinOp,typename NestedXpr,typename Rhs>
|
||||
struct blas_traits<SelfCwiseBinaryOp<BinOp,NestedXpr,Rhs> >
|
||||
: blas_traits<NestedXpr>
|
||||
{
|
||||
typedef SelfCwiseBinaryOp<BinOp,NestedXpr,Rhs> XprType;
|
||||
static inline const XprType extract(const XprType& x) { return x; }
|
||||
};
|
||||
|
||||
template<bool DestIsTransposed, typename OtherDerived>
|
||||
struct check_transpose_aliasing_compile_time_selector
|
||||
{
|
||||
@@ -413,15 +382,15 @@ struct checkTransposeAliasing_impl<Derived, OtherDerived, false>
|
||||
}
|
||||
};
|
||||
|
||||
template<typename Dst, typename Src>
|
||||
void check_for_aliasing(const Dst &dst, const Src &src)
|
||||
{
|
||||
internal::checkTransposeAliasing_impl<Dst, Src>::run(dst, src);
|
||||
}
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
template<typename Derived>
|
||||
template<typename OtherDerived>
|
||||
void DenseBase<Derived>::checkTransposeAliasing(const OtherDerived& other) const
|
||||
{
|
||||
internal::checkTransposeAliasing_impl<Derived, OtherDerived>::run(derived(), other);
|
||||
}
|
||||
#endif
|
||||
#endif // EIGEN_NO_DEBUG
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
|
||||
@@ -41,10 +41,6 @@ namespace Eigen {
|
||||
* \sa class PermutationMatrix
|
||||
*/
|
||||
|
||||
namespace internal {
|
||||
template<typename TranspositionType, typename MatrixType, int Side, bool Transposed=false> struct transposition_matrix_product_retval;
|
||||
}
|
||||
|
||||
template<typename Derived>
|
||||
class TranspositionsBase
|
||||
{
|
||||
@@ -53,8 +49,8 @@ class TranspositionsBase
|
||||
public:
|
||||
|
||||
typedef typename Traits::IndicesType IndicesType;
|
||||
typedef typename IndicesType::Scalar StorageIndexType;
|
||||
typedef typename IndicesType::Index Index;
|
||||
typedef typename IndicesType::Scalar StorageIndex;
|
||||
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
|
||||
|
||||
Derived& derived() { return *static_cast<Derived*>(this); }
|
||||
const Derived& derived() const { return *static_cast<const Derived*>(this); }
|
||||
@@ -66,7 +62,7 @@ class TranspositionsBase
|
||||
indices() = other.indices();
|
||||
return derived();
|
||||
}
|
||||
|
||||
|
||||
#ifndef EIGEN_PARSED_BY_DOXYGEN
|
||||
/** This is a special case of the templated operator=. Its purpose is to
|
||||
* prevent a default operator= from hiding the templated operator=.
|
||||
@@ -79,20 +75,24 @@ class TranspositionsBase
|
||||
#endif
|
||||
|
||||
/** \returns the number of transpositions */
|
||||
inline Index size() const { return indices().size(); }
|
||||
Index size() const { return indices().size(); }
|
||||
/** \returns the number of rows of the equivalent permutation matrix */
|
||||
Index rows() const { return indices().size(); }
|
||||
/** \returns the number of columns of the equivalent permutation matrix */
|
||||
Index cols() const { return indices().size(); }
|
||||
|
||||
/** Direct access to the underlying index vector */
|
||||
inline const StorageIndexType& coeff(Index i) const { return indices().coeff(i); }
|
||||
inline const StorageIndex& coeff(Index i) const { return indices().coeff(i); }
|
||||
/** Direct access to the underlying index vector */
|
||||
inline StorageIndexType& coeffRef(Index i) { return indices().coeffRef(i); }
|
||||
inline StorageIndex& coeffRef(Index i) { return indices().coeffRef(i); }
|
||||
/** Direct access to the underlying index vector */
|
||||
inline const StorageIndexType& operator()(Index i) const { return indices()(i); }
|
||||
inline const StorageIndex& operator()(Index i) const { return indices()(i); }
|
||||
/** Direct access to the underlying index vector */
|
||||
inline StorageIndexType& operator()(Index i) { return indices()(i); }
|
||||
inline StorageIndex& operator()(Index i) { return indices()(i); }
|
||||
/** Direct access to the underlying index vector */
|
||||
inline const StorageIndexType& operator[](Index i) const { return indices()(i); }
|
||||
inline const StorageIndex& operator[](Index i) const { return indices()(i); }
|
||||
/** Direct access to the underlying index vector */
|
||||
inline StorageIndexType& operator[](Index i) { return indices()(i); }
|
||||
inline StorageIndex& operator[](Index i) { return indices()(i); }
|
||||
|
||||
/** const version of indices(). */
|
||||
const IndicesType& indices() const { return derived().indices(); }
|
||||
@@ -108,7 +108,7 @@ class TranspositionsBase
|
||||
/** Sets \c *this to represents an identity transformation */
|
||||
void setIdentity()
|
||||
{
|
||||
for(StorageIndexType i = 0; i < indices().size(); ++i)
|
||||
for(StorageIndex i = 0; i < indices().size(); ++i)
|
||||
coeffRef(i) = i;
|
||||
}
|
||||
|
||||
@@ -145,26 +145,24 @@ class TranspositionsBase
|
||||
};
|
||||
|
||||
namespace internal {
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndexType>
|
||||
struct traits<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndexType> >
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
|
||||
struct traits<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
|
||||
: traits<PermutationMatrix<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
|
||||
{
|
||||
typedef Matrix<_StorageIndexType, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
|
||||
typedef typename IndicesType::Index Index;
|
||||
typedef _StorageIndexType StorageIndexType;
|
||||
typedef Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
|
||||
typedef TranspositionsStorage StorageKind;
|
||||
};
|
||||
}
|
||||
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndexType>
|
||||
class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndexType> >
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
|
||||
class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
|
||||
{
|
||||
typedef internal::traits<Transpositions> Traits;
|
||||
public:
|
||||
|
||||
typedef TranspositionsBase<Transpositions> Base;
|
||||
typedef typename Traits::IndicesType IndicesType;
|
||||
typedef typename IndicesType::Scalar StorageIndexType;
|
||||
typedef typename IndicesType::Index Index;
|
||||
|
||||
typedef typename IndicesType::Scalar StorageIndex;
|
||||
|
||||
inline Transpositions() {}
|
||||
|
||||
@@ -181,7 +179,7 @@ class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTim
|
||||
|
||||
/** Generic constructor from expression of the transposition indices. */
|
||||
template<typename Other>
|
||||
explicit inline Transpositions(const MatrixBase<Other>& a_indices) : m_indices(a_indices)
|
||||
explicit inline Transpositions(const MatrixBase<Other>& indices) : m_indices(indices)
|
||||
{}
|
||||
|
||||
/** Copies the \a other transpositions into \c *this */
|
||||
@@ -219,32 +217,32 @@ class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTim
|
||||
|
||||
|
||||
namespace internal {
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndexType, int _PacketAccess>
|
||||
struct traits<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndexType>,_PacketAccess> >
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
|
||||
struct traits<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,_PacketAccess> >
|
||||
: traits<PermutationMatrix<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
|
||||
{
|
||||
typedef Map<const Matrix<_StorageIndexType,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1>, _PacketAccess> IndicesType;
|
||||
typedef typename IndicesType::Index Index;
|
||||
typedef _StorageIndexType StorageIndexType;
|
||||
typedef Map<const Matrix<_StorageIndex,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1>, _PacketAccess> IndicesType;
|
||||
typedef _StorageIndex StorageIndex;
|
||||
typedef TranspositionsStorage StorageKind;
|
||||
};
|
||||
}
|
||||
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndexType, int PacketAccess>
|
||||
class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndexType>,PacketAccess>
|
||||
: public TranspositionsBase<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndexType>,PacketAccess> >
|
||||
template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int PacketAccess>
|
||||
class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,PacketAccess>
|
||||
: public TranspositionsBase<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,PacketAccess> >
|
||||
{
|
||||
typedef internal::traits<Map> Traits;
|
||||
public:
|
||||
|
||||
typedef TranspositionsBase<Map> Base;
|
||||
typedef typename Traits::IndicesType IndicesType;
|
||||
typedef typename IndicesType::Scalar StorageIndexType;
|
||||
typedef typename IndicesType::Index Index;
|
||||
typedef typename IndicesType::Scalar StorageIndex;
|
||||
|
||||
inline Map(const StorageIndexType* indicesPtr)
|
||||
explicit inline Map(const StorageIndex* indicesPtr)
|
||||
: m_indices(indicesPtr)
|
||||
{}
|
||||
|
||||
inline Map(const StorageIndexType* indicesPtr, Index size)
|
||||
inline Map(const StorageIndex* indicesPtr, Index size)
|
||||
: m_indices(indicesPtr,size)
|
||||
{}
|
||||
|
||||
@@ -280,10 +278,9 @@ class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndexTyp
|
||||
namespace internal {
|
||||
template<typename _IndicesType>
|
||||
struct traits<TranspositionsWrapper<_IndicesType> >
|
||||
: traits<PermutationWrapper<_IndicesType> >
|
||||
{
|
||||
typedef typename _IndicesType::Scalar StorageIndexType;
|
||||
typedef typename _IndicesType::Index Index;
|
||||
typedef _IndicesType IndicesType;
|
||||
typedef TranspositionsStorage StorageKind;
|
||||
};
|
||||
}
|
||||
|
||||
@@ -296,11 +293,10 @@ class TranspositionsWrapper
|
||||
|
||||
typedef TranspositionsBase<TranspositionsWrapper> Base;
|
||||
typedef typename Traits::IndicesType IndicesType;
|
||||
typedef typename IndicesType::Scalar StorageIndexType;
|
||||
typedef typename IndicesType::Index Index;
|
||||
typedef typename IndicesType::Scalar StorageIndex;
|
||||
|
||||
inline TranspositionsWrapper(IndicesType& a_indices)
|
||||
: m_indices(a_indices)
|
||||
explicit inline TranspositionsWrapper(IndicesType& indices)
|
||||
: m_indices(indices)
|
||||
{}
|
||||
|
||||
/** Copies the \a other transpositions into \c *this */
|
||||
@@ -332,81 +328,43 @@ class TranspositionsWrapper
|
||||
const typename IndicesType::Nested m_indices;
|
||||
};
|
||||
|
||||
|
||||
|
||||
/** \returns the \a matrix with the \a transpositions applied to the columns.
|
||||
*/
|
||||
template<typename Derived, typename TranspositionsDerived>
|
||||
inline const internal::transposition_matrix_product_retval<TranspositionsDerived, Derived, OnTheRight>
|
||||
operator*(const MatrixBase<Derived>& matrix,
|
||||
const TranspositionsBase<TranspositionsDerived> &transpositions)
|
||||
template<typename MatrixDerived, typename TranspositionsDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const Product<MatrixDerived, TranspositionsDerived, AliasFreeProduct>
|
||||
operator*(const MatrixBase<MatrixDerived> &matrix,
|
||||
const TranspositionsBase<TranspositionsDerived>& transpositions)
|
||||
{
|
||||
return internal::transposition_matrix_product_retval
|
||||
<TranspositionsDerived, Derived, OnTheRight>
|
||||
(transpositions.derived(), matrix.derived());
|
||||
return Product<MatrixDerived, TranspositionsDerived, AliasFreeProduct>
|
||||
(matrix.derived(), transpositions.derived());
|
||||
}
|
||||
|
||||
/** \returns the \a matrix with the \a transpositions applied to the rows.
|
||||
*/
|
||||
template<typename Derived, typename TranspositionDerived>
|
||||
inline const internal::transposition_matrix_product_retval
|
||||
<TranspositionDerived, Derived, OnTheLeft>
|
||||
operator*(const TranspositionsBase<TranspositionDerived> &transpositions,
|
||||
const MatrixBase<Derived>& matrix)
|
||||
template<typename TranspositionsDerived, typename MatrixDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const Product<TranspositionsDerived, MatrixDerived, AliasFreeProduct>
|
||||
operator*(const TranspositionsBase<TranspositionsDerived> &transpositions,
|
||||
const MatrixBase<MatrixDerived>& matrix)
|
||||
{
|
||||
return internal::transposition_matrix_product_retval
|
||||
<TranspositionDerived, Derived, OnTheLeft>
|
||||
(transpositions.derived(), matrix.derived());
|
||||
return Product<TranspositionsDerived, MatrixDerived, AliasFreeProduct>
|
||||
(transpositions.derived(), matrix.derived());
|
||||
}
|
||||
|
||||
// Template partial specialization for transposed/inverse transpositions
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<typename TranspositionType, typename MatrixType, int Side, bool Transposed>
|
||||
struct traits<transposition_matrix_product_retval<TranspositionType, MatrixType, Side, Transposed> >
|
||||
{
|
||||
typedef typename MatrixType::PlainObject ReturnType;
|
||||
};
|
||||
|
||||
template<typename TranspositionType, typename MatrixType, int Side, bool Transposed>
|
||||
struct transposition_matrix_product_retval
|
||||
: public ReturnByValue<transposition_matrix_product_retval<TranspositionType, MatrixType, Side, Transposed> >
|
||||
{
|
||||
typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
|
||||
typedef typename TranspositionType::Index Index;
|
||||
typedef typename TranspositionType::StorageIndexType StorageIndexType;
|
||||
|
||||
transposition_matrix_product_retval(const TranspositionType& tr, const MatrixType& matrix)
|
||||
: m_transpositions(tr), m_matrix(matrix)
|
||||
{}
|
||||
|
||||
inline Index rows() const { return m_matrix.rows(); }
|
||||
inline Index cols() const { return m_matrix.cols(); }
|
||||
|
||||
template<typename Dest> inline void evalTo(Dest& dst) const
|
||||
{
|
||||
const Index size = m_transpositions.size();
|
||||
StorageIndexType j = 0;
|
||||
|
||||
if(!(is_same<MatrixTypeNestedCleaned,Dest>::value && extract_data(dst) == extract_data(m_matrix)))
|
||||
dst = m_matrix;
|
||||
|
||||
for(Index k=(Transposed?size-1:0) ; Transposed?k>=0:k<size ; Transposed?--k:++k)
|
||||
if(Index(j=m_transpositions.coeff(k))!=k)
|
||||
{
|
||||
if(Side==OnTheLeft)
|
||||
dst.row(k).swap(dst.row(j));
|
||||
else if(Side==OnTheRight)
|
||||
dst.col(k).swap(dst.col(j));
|
||||
}
|
||||
}
|
||||
|
||||
protected:
|
||||
const TranspositionType& m_transpositions;
|
||||
typename MatrixType::Nested m_matrix;
|
||||
};
|
||||
template<typename Derived>
|
||||
struct traits<Transpose<TranspositionsBase<Derived> > >
|
||||
: traits<Derived>
|
||||
{};
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
/* Template partial specialization for transposed/inverse transpositions */
|
||||
|
||||
template<typename TranspositionsDerived>
|
||||
class Transpose<TranspositionsBase<TranspositionsDerived> >
|
||||
{
|
||||
@@ -414,27 +372,31 @@ class Transpose<TranspositionsBase<TranspositionsDerived> >
|
||||
typedef typename TranspositionType::IndicesType IndicesType;
|
||||
public:
|
||||
|
||||
Transpose(const TranspositionType& t) : m_transpositions(t) {}
|
||||
explicit Transpose(const TranspositionType& t) : m_transpositions(t) {}
|
||||
|
||||
inline int size() const { return m_transpositions.size(); }
|
||||
Index size() const { return m_transpositions.size(); }
|
||||
Index rows() const { return m_transpositions.size(); }
|
||||
Index cols() const { return m_transpositions.size(); }
|
||||
|
||||
/** \returns the \a matrix with the inverse transpositions applied to the columns.
|
||||
*/
|
||||
template<typename Derived> friend
|
||||
inline const internal::transposition_matrix_product_retval<TranspositionType, Derived, OnTheRight, true>
|
||||
operator*(const MatrixBase<Derived>& matrix, const Transpose& trt)
|
||||
template<typename OtherDerived> friend
|
||||
const Product<OtherDerived, Transpose, AliasFreeProduct>
|
||||
operator*(const MatrixBase<OtherDerived>& matrix, const Transpose& trt)
|
||||
{
|
||||
return internal::transposition_matrix_product_retval<TranspositionType, Derived, OnTheRight, true>(trt.m_transpositions, matrix.derived());
|
||||
return Product<OtherDerived, Transpose, AliasFreeProduct>(matrix.derived(), trt.derived());
|
||||
}
|
||||
|
||||
/** \returns the \a matrix with the inverse transpositions applied to the rows.
|
||||
*/
|
||||
template<typename Derived>
|
||||
inline const internal::transposition_matrix_product_retval<TranspositionType, Derived, OnTheLeft, true>
|
||||
operator*(const MatrixBase<Derived>& matrix) const
|
||||
template<typename OtherDerived>
|
||||
const Product<Transpose, OtherDerived, AliasFreeProduct>
|
||||
operator*(const MatrixBase<OtherDerived>& matrix) const
|
||||
{
|
||||
return internal::transposition_matrix_product_retval<TranspositionType, Derived, OnTheLeft, true>(m_transpositions, matrix.derived());
|
||||
return Product<Transpose, OtherDerived, AliasFreeProduct>(*this, matrix.derived());
|
||||
}
|
||||
|
||||
const TranspositionType& nestedExpression() const { return m_transpositions; }
|
||||
|
||||
protected:
|
||||
const TranspositionType& m_transpositions;
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -41,32 +41,22 @@ struct traits<PartialReduxExpr<MatrixType, MemberOp, Direction> >
|
||||
typedef typename traits<MatrixType>::StorageKind StorageKind;
|
||||
typedef typename traits<MatrixType>::XprKind XprKind;
|
||||
typedef typename MatrixType::Scalar InputScalar;
|
||||
typedef typename nested<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
|
||||
typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested;
|
||||
enum {
|
||||
RowsAtCompileTime = Direction==Vertical ? 1 : MatrixType::RowsAtCompileTime,
|
||||
ColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::ColsAtCompileTime,
|
||||
MaxRowsAtCompileTime = Direction==Vertical ? 1 : MatrixType::MaxRowsAtCompileTime,
|
||||
MaxColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::MaxColsAtCompileTime,
|
||||
Flags0 = (unsigned int)_MatrixTypeNested::Flags & HereditaryBits,
|
||||
Flags = (Flags0 & ~RowMajorBit) | (RowsAtCompileTime == 1 ? RowMajorBit : 0),
|
||||
Flags = RowsAtCompileTime == 1 ? RowMajorBit : 0,
|
||||
TraversalSize = Direction==Vertical ? MatrixType::RowsAtCompileTime : MatrixType::ColsAtCompileTime
|
||||
};
|
||||
#if EIGEN_GNUC_AT_LEAST(3,4)
|
||||
typedef typename MemberOp::template Cost<InputScalar,int(TraversalSize)> CostOpType;
|
||||
#else
|
||||
typedef typename MemberOp::template Cost<InputScalar,TraversalSize> CostOpType;
|
||||
#endif
|
||||
enum {
|
||||
CoeffReadCost = TraversalSize==Dynamic ? Dynamic
|
||||
: TraversalSize * traits<_MatrixTypeNested>::CoeffReadCost + int(CostOpType::value)
|
||||
};
|
||||
};
|
||||
}
|
||||
|
||||
template< typename MatrixType, typename MemberOp, int Direction>
|
||||
class PartialReduxExpr : internal::no_assignment_operator,
|
||||
public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type
|
||||
class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type,
|
||||
internal::no_assignment_operator
|
||||
{
|
||||
public:
|
||||
|
||||
@@ -75,13 +65,16 @@ class PartialReduxExpr : internal::no_assignment_operator,
|
||||
typedef typename internal::traits<PartialReduxExpr>::MatrixTypeNested MatrixTypeNested;
|
||||
typedef typename internal::traits<PartialReduxExpr>::_MatrixTypeNested _MatrixTypeNested;
|
||||
|
||||
PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp())
|
||||
EIGEN_DEVICE_FUNC
|
||||
explicit PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp())
|
||||
: m_matrix(mat), m_functor(func) {}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
Index rows() const { return (Direction==Vertical ? 1 : m_matrix.rows()); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
Index cols() const { return (Direction==Horizontal ? 1 : m_matrix.cols()); }
|
||||
|
||||
EIGEN_STRONG_INLINE const Scalar coeff(Index i, Index j) const
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index i, Index j) const
|
||||
{
|
||||
if (Direction==Vertical)
|
||||
return m_functor(m_matrix.col(j));
|
||||
@@ -89,7 +82,7 @@ class PartialReduxExpr : internal::no_assignment_operator,
|
||||
return m_functor(m_matrix.row(i));
|
||||
}
|
||||
|
||||
const Scalar coeff(Index index) const
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
|
||||
{
|
||||
if (Direction==Vertical)
|
||||
return m_functor(m_matrix.col(index));
|
||||
@@ -110,7 +103,8 @@ class PartialReduxExpr : internal::no_assignment_operator,
|
||||
template<typename Scalar, int Size> struct Cost \
|
||||
{ enum { value = COST }; }; \
|
||||
template<typename XprType> \
|
||||
EIGEN_STRONG_INLINE ResultType operator()(const XprType& mat) const \
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE \
|
||||
ResultType operator()(const XprType& mat) const \
|
||||
{ return mat.MEMBER(); } \
|
||||
}
|
||||
|
||||
@@ -134,13 +128,13 @@ EIGEN_MEMBER_FUNCTOR(prod, (Size-1)*NumTraits<Scalar>::MulCost);
|
||||
template <typename BinaryOp, typename Scalar>
|
||||
struct member_redux {
|
||||
typedef typename result_of<
|
||||
BinaryOp(Scalar)
|
||||
BinaryOp(Scalar,Scalar)
|
||||
>::type result_type;
|
||||
template<typename _Scalar, int Size> struct Cost
|
||||
{ enum { value = (Size-1) * functor_traits<BinaryOp>::Cost }; };
|
||||
member_redux(const BinaryOp func) : m_functor(func) {}
|
||||
EIGEN_DEVICE_FUNC explicit member_redux(const BinaryOp func) : m_functor(func) {}
|
||||
template<typename Derived>
|
||||
inline result_type operator()(const DenseBase<Derived>& mat) const
|
||||
EIGEN_DEVICE_FUNC inline result_type operator()(const DenseBase<Derived>& mat) const
|
||||
{ return mat.redux(m_functor); }
|
||||
const BinaryOp m_functor;
|
||||
};
|
||||
@@ -169,16 +163,15 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
|
||||
typedef typename ExpressionType::Scalar Scalar;
|
||||
typedef typename ExpressionType::RealScalar RealScalar;
|
||||
typedef typename ExpressionType::Index Index;
|
||||
typedef typename internal::conditional<internal::must_nest_by_value<ExpressionType>::ret,
|
||||
ExpressionType, ExpressionType&>::type ExpressionTypeNested;
|
||||
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
|
||||
typedef typename internal::ref_selector<ExpressionType>::non_const_type ExpressionTypeNested;
|
||||
typedef typename internal::remove_all<ExpressionTypeNested>::type ExpressionTypeNestedCleaned;
|
||||
|
||||
template<template<typename _Scalar> class Functor,
|
||||
typename Scalar=typename internal::traits<ExpressionType>::Scalar> struct ReturnType
|
||||
typename Scalar_=Scalar> struct ReturnType
|
||||
{
|
||||
typedef PartialReduxExpr<ExpressionType,
|
||||
Functor<Scalar>,
|
||||
Functor<Scalar_>,
|
||||
Direction
|
||||
> Type;
|
||||
};
|
||||
@@ -186,23 +179,24 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
template<typename BinaryOp> struct ReduxReturnType
|
||||
{
|
||||
typedef PartialReduxExpr<ExpressionType,
|
||||
internal::member_redux<BinaryOp,typename internal::traits<ExpressionType>::Scalar>,
|
||||
internal::member_redux<BinaryOp,Scalar>,
|
||||
Direction
|
||||
> Type;
|
||||
};
|
||||
|
||||
enum {
|
||||
IsVertical = (Direction==Vertical) ? 1 : 0,
|
||||
IsHorizontal = (Direction==Horizontal) ? 1 : 0
|
||||
isVertical = (Direction==Vertical) ? 1 : 0,
|
||||
isHorizontal = (Direction==Horizontal) ? 1 : 0
|
||||
};
|
||||
|
||||
protected:
|
||||
|
||||
/** \internal
|
||||
* \returns the i-th subvector according to the \c Direction */
|
||||
typedef typename internal::conditional<Direction==Vertical,
|
||||
typedef typename internal::conditional<isVertical,
|
||||
typename ExpressionType::ColXpr,
|
||||
typename ExpressionType::RowXpr>::type SubVector;
|
||||
EIGEN_DEVICE_FUNC
|
||||
SubVector subVector(Index i)
|
||||
{
|
||||
return SubVector(m_matrix.derived(),i);
|
||||
@@ -210,58 +204,62 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
|
||||
/** \internal
|
||||
* \returns the number of subvectors in the direction \c Direction */
|
||||
EIGEN_DEVICE_FUNC
|
||||
Index subVectors() const
|
||||
{ return Direction==Vertical?m_matrix.cols():m_matrix.rows(); }
|
||||
{ return isVertical?m_matrix.cols():m_matrix.rows(); }
|
||||
|
||||
template<typename OtherDerived> struct ExtendedType {
|
||||
typedef Replicate<OtherDerived,
|
||||
Direction==Vertical ? 1 : ExpressionType::RowsAtCompileTime,
|
||||
Direction==Horizontal ? 1 : ExpressionType::ColsAtCompileTime> Type;
|
||||
isVertical ? 1 : ExpressionType::RowsAtCompileTime,
|
||||
isHorizontal ? 1 : ExpressionType::ColsAtCompileTime> Type;
|
||||
};
|
||||
|
||||
/** \internal
|
||||
* Replicates a vector to match the size of \c *this */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename ExtendedType<OtherDerived>::Type
|
||||
extendedTo(const DenseBase<OtherDerived>& other) const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Vertical, OtherDerived::MaxColsAtCompileTime==1),
|
||||
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isVertical, OtherDerived::MaxColsAtCompileTime==1),
|
||||
YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED)
|
||||
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Horizontal, OtherDerived::MaxRowsAtCompileTime==1),
|
||||
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isHorizontal, OtherDerived::MaxRowsAtCompileTime==1),
|
||||
YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED)
|
||||
return typename ExtendedType<OtherDerived>::Type
|
||||
(other.derived(),
|
||||
Direction==Vertical ? 1 : m_matrix.rows(),
|
||||
Direction==Horizontal ? 1 : m_matrix.cols());
|
||||
isVertical ? 1 : m_matrix.rows(),
|
||||
isHorizontal ? 1 : m_matrix.cols());
|
||||
}
|
||||
|
||||
template<typename OtherDerived> struct OppositeExtendedType {
|
||||
typedef Replicate<OtherDerived,
|
||||
Direction==Horizontal ? 1 : ExpressionType::RowsAtCompileTime,
|
||||
Direction==Vertical ? 1 : ExpressionType::ColsAtCompileTime> Type;
|
||||
isHorizontal ? 1 : ExpressionType::RowsAtCompileTime,
|
||||
isVertical ? 1 : ExpressionType::ColsAtCompileTime> Type;
|
||||
};
|
||||
|
||||
/** \internal
|
||||
* Replicates a vector in the opposite direction to match the size of \c *this */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename OppositeExtendedType<OtherDerived>::Type
|
||||
extendedToOpposite(const DenseBase<OtherDerived>& other) const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Horizontal, OtherDerived::MaxColsAtCompileTime==1),
|
||||
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isHorizontal, OtherDerived::MaxColsAtCompileTime==1),
|
||||
YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED)
|
||||
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Vertical, OtherDerived::MaxRowsAtCompileTime==1),
|
||||
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isVertical, OtherDerived::MaxRowsAtCompileTime==1),
|
||||
YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED)
|
||||
return typename OppositeExtendedType<OtherDerived>::Type
|
||||
(other.derived(),
|
||||
Direction==Horizontal ? 1 : m_matrix.rows(),
|
||||
Direction==Vertical ? 1 : m_matrix.cols());
|
||||
isHorizontal ? 1 : m_matrix.rows(),
|
||||
isVertical ? 1 : m_matrix.cols());
|
||||
}
|
||||
|
||||
public:
|
||||
|
||||
inline VectorwiseOp(ExpressionType& matrix) : m_matrix(matrix) {}
|
||||
EIGEN_DEVICE_FUNC
|
||||
explicit inline VectorwiseOp(ExpressionType& matrix) : m_matrix(matrix) {}
|
||||
|
||||
/** \internal */
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline const ExpressionType& _expression() const { return m_matrix; }
|
||||
|
||||
/** \returns a row or column vector expression of \c *this reduxed by \a func
|
||||
@@ -272,9 +270,25 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* \sa class VectorwiseOp, DenseBase::colwise(), DenseBase::rowwise()
|
||||
*/
|
||||
template<typename BinaryOp>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const typename ReduxReturnType<BinaryOp>::Type
|
||||
redux(const BinaryOp& func = BinaryOp()) const
|
||||
{ return typename ReduxReturnType<BinaryOp>::Type(_expression(), func); }
|
||||
{ return typename ReduxReturnType<BinaryOp>::Type(_expression(), internal::member_redux<BinaryOp,Scalar>(func)); }
|
||||
|
||||
typedef typename ReturnType<internal::member_minCoeff>::Type MinCoeffReturnType;
|
||||
typedef typename ReturnType<internal::member_maxCoeff>::Type MaxCoeffReturnType;
|
||||
typedef typename ReturnType<internal::member_squaredNorm,RealScalar>::Type SquaredNormReturnType;
|
||||
typedef typename ReturnType<internal::member_norm,RealScalar>::Type NormReturnType;
|
||||
typedef typename ReturnType<internal::member_blueNorm,RealScalar>::Type BlueNormReturnType;
|
||||
typedef typename ReturnType<internal::member_stableNorm,RealScalar>::Type StableNormReturnType;
|
||||
typedef typename ReturnType<internal::member_hypotNorm,RealScalar>::Type HypotNormReturnType;
|
||||
typedef typename ReturnType<internal::member_sum>::Type SumReturnType;
|
||||
typedef typename ReturnType<internal::member_mean>::Type MeanReturnType;
|
||||
typedef typename ReturnType<internal::member_all>::Type AllReturnType;
|
||||
typedef typename ReturnType<internal::member_any>::Type AnyReturnType;
|
||||
typedef PartialReduxExpr<ExpressionType, internal::member_count<Index>, Direction> CountReturnType;
|
||||
typedef typename ReturnType<internal::member_prod>::Type ProdReturnType;
|
||||
typedef Reverse<ExpressionType, Direction> ReverseReturnType;
|
||||
|
||||
/** \returns a row (or column) vector expression of the smallest coefficient
|
||||
* of each column (or row) of the referenced expression.
|
||||
@@ -285,8 +299,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* Output: \verbinclude PartialRedux_minCoeff.out
|
||||
*
|
||||
* \sa DenseBase::minCoeff() */
|
||||
const typename ReturnType<internal::member_minCoeff>::Type minCoeff() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const MinCoeffReturnType minCoeff() const
|
||||
{ return MinCoeffReturnType(_expression()); }
|
||||
|
||||
/** \returns a row (or column) vector expression of the largest coefficient
|
||||
* of each column (or row) of the referenced expression.
|
||||
@@ -297,8 +312,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* Output: \verbinclude PartialRedux_maxCoeff.out
|
||||
*
|
||||
* \sa DenseBase::maxCoeff() */
|
||||
const typename ReturnType<internal::member_maxCoeff>::Type maxCoeff() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const MaxCoeffReturnType maxCoeff() const
|
||||
{ return MaxCoeffReturnType(_expression()); }
|
||||
|
||||
/** \returns a row (or column) vector expression of the squared norm
|
||||
* of each column (or row) of the referenced expression.
|
||||
@@ -308,8 +324,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* Output: \verbinclude PartialRedux_squaredNorm.out
|
||||
*
|
||||
* \sa DenseBase::squaredNorm() */
|
||||
const typename ReturnType<internal::member_squaredNorm,RealScalar>::Type squaredNorm() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const SquaredNormReturnType squaredNorm() const
|
||||
{ return SquaredNormReturnType(_expression()); }
|
||||
|
||||
/** \returns a row (or column) vector expression of the norm
|
||||
* of each column (or row) of the referenced expression.
|
||||
@@ -319,8 +336,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* Output: \verbinclude PartialRedux_norm.out
|
||||
*
|
||||
* \sa DenseBase::norm() */
|
||||
const typename ReturnType<internal::member_norm,RealScalar>::Type norm() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const NormReturnType norm() const
|
||||
{ return NormReturnType(_expression()); }
|
||||
|
||||
|
||||
/** \returns a row (or column) vector expression of the norm
|
||||
@@ -329,8 +347,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* This is a vector with real entries, even if the original matrix has complex entries.
|
||||
*
|
||||
* \sa DenseBase::blueNorm() */
|
||||
const typename ReturnType<internal::member_blueNorm,RealScalar>::Type blueNorm() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const BlueNormReturnType blueNorm() const
|
||||
{ return BlueNormReturnType(_expression()); }
|
||||
|
||||
|
||||
/** \returns a row (or column) vector expression of the norm
|
||||
@@ -339,8 +358,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* This is a vector with real entries, even if the original matrix has complex entries.
|
||||
*
|
||||
* \sa DenseBase::stableNorm() */
|
||||
const typename ReturnType<internal::member_stableNorm,RealScalar>::Type stableNorm() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const StableNormReturnType stableNorm() const
|
||||
{ return StableNormReturnType(_expression()); }
|
||||
|
||||
|
||||
/** \returns a row (or column) vector expression of the norm
|
||||
@@ -349,8 +369,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* This is a vector with real entries, even if the original matrix has complex entries.
|
||||
*
|
||||
* \sa DenseBase::hypotNorm() */
|
||||
const typename ReturnType<internal::member_hypotNorm,RealScalar>::Type hypotNorm() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const HypotNormReturnType hypotNorm() const
|
||||
{ return HypotNormReturnType(_expression()); }
|
||||
|
||||
/** \returns a row (or column) vector expression of the sum
|
||||
* of each column (or row) of the referenced expression.
|
||||
@@ -359,31 +380,35 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* Output: \verbinclude PartialRedux_sum.out
|
||||
*
|
||||
* \sa DenseBase::sum() */
|
||||
const typename ReturnType<internal::member_sum>::Type sum() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const SumReturnType sum() const
|
||||
{ return SumReturnType(_expression()); }
|
||||
|
||||
/** \returns a row (or column) vector expression of the mean
|
||||
* of each column (or row) of the referenced expression.
|
||||
*
|
||||
* \sa DenseBase::mean() */
|
||||
const typename ReturnType<internal::member_mean>::Type mean() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const MeanReturnType mean() const
|
||||
{ return MeanReturnType(_expression()); }
|
||||
|
||||
/** \returns a row (or column) vector expression representing
|
||||
* whether \b all coefficients of each respective column (or row) are \c true.
|
||||
* This expression can be assigned to a vector with entries of type \c bool.
|
||||
*
|
||||
* \sa DenseBase::all() */
|
||||
const typename ReturnType<internal::member_all>::Type all() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const AllReturnType all() const
|
||||
{ return AllReturnType(_expression()); }
|
||||
|
||||
/** \returns a row (or column) vector expression representing
|
||||
* whether \b at \b least one coefficient of each respective column (or row) is \c true.
|
||||
* This expression can be assigned to a vector with entries of type \c bool.
|
||||
*
|
||||
* \sa DenseBase::any() */
|
||||
const typename ReturnType<internal::member_any>::Type any() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const AnyReturnType any() const
|
||||
{ return Any(_expression()); }
|
||||
|
||||
/** \returns a row (or column) vector expression representing
|
||||
* the number of \c true coefficients of each respective column (or row).
|
||||
@@ -394,8 +419,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* Output: \verbinclude PartialRedux_count.out
|
||||
*
|
||||
* \sa DenseBase::count() */
|
||||
const PartialReduxExpr<ExpressionType, internal::member_count<Index>, Direction> count() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const CountReturnType count() const
|
||||
{ return CountReturnType(_expression()); }
|
||||
|
||||
/** \returns a row (or column) vector expression of the product
|
||||
* of each column (or row) of the referenced expression.
|
||||
@@ -404,8 +430,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* Output: \verbinclude PartialRedux_prod.out
|
||||
*
|
||||
* \sa DenseBase::prod() */
|
||||
const typename ReturnType<internal::member_prod>::Type prod() const
|
||||
{ return _expression(); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const ProdReturnType prod() const
|
||||
{ return ProdReturnType(_expression()); }
|
||||
|
||||
|
||||
/** \returns a matrix expression
|
||||
@@ -415,10 +442,12 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* Output: \verbinclude Vectorwise_reverse.out
|
||||
*
|
||||
* \sa DenseBase::reverse() */
|
||||
const Reverse<ExpressionType, Direction> reverse() const
|
||||
{ return Reverse<ExpressionType, Direction>( _expression() ); }
|
||||
EIGEN_DEVICE_FUNC
|
||||
const ReverseReturnType reverse() const
|
||||
{ return ReverseReturnType( _expression() ); }
|
||||
|
||||
typedef Replicate<ExpressionType,Direction==Vertical?Dynamic:1,Direction==Horizontal?Dynamic:1> ReplicateReturnType;
|
||||
typedef Replicate<ExpressionType,(isVertical?Dynamic:1),(isHorizontal?Dynamic:1)> ReplicateReturnType;
|
||||
EIGEN_DEVICE_FUNC
|
||||
const ReplicateReturnType replicate(Index factor) const;
|
||||
|
||||
/**
|
||||
@@ -430,17 +459,20 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* \sa VectorwiseOp::replicate(Index), DenseBase::replicate(), class Replicate
|
||||
*/
|
||||
// NOTE implemented here because of sunstudio's compilation errors
|
||||
template<int Factor> const Replicate<ExpressionType,(IsVertical?Factor:1),(IsHorizontal?Factor:1)>
|
||||
// isVertical*Factor+isHorizontal instead of (isVertical?Factor:1) to handle CUDA bug with ternary operator
|
||||
template<int Factor> const Replicate<ExpressionType,isVertical*Factor+isHorizontal,isHorizontal*Factor+isVertical>
|
||||
EIGEN_DEVICE_FUNC
|
||||
replicate(Index factor = Factor) const
|
||||
{
|
||||
return Replicate<ExpressionType,Direction==Vertical?Factor:1,Direction==Horizontal?Factor:1>
|
||||
(_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1);
|
||||
return Replicate<ExpressionType,(isVertical?Factor:1),(isHorizontal?Factor:1)>
|
||||
(_expression(),isVertical?factor:1,isHorizontal?factor:1);
|
||||
}
|
||||
|
||||
/////////// Artithmetic operators ///////////
|
||||
|
||||
/** Copies the vector \a other to each subvector of \c *this */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
ExpressionType& operator=(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
|
||||
@@ -451,6 +483,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
|
||||
/** Adds the vector \a other to each subvector of \c *this */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
ExpressionType& operator+=(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
|
||||
@@ -460,6 +493,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
|
||||
/** Substracts the vector \a other to each subvector of \c *this */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
ExpressionType& operator-=(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
|
||||
@@ -469,6 +503,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
|
||||
/** Multiples each subvector of \c *this by the vector \a other */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
ExpressionType& operator*=(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
|
||||
@@ -480,6 +515,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
|
||||
/** Divides each subvector of \c *this by the vector \a other */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
ExpressionType& operator/=(const DenseBase<OtherDerived>& other)
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
|
||||
@@ -490,7 +526,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
}
|
||||
|
||||
/** Returns the expression of the sum of the vector \a other to each subvector of \c *this */
|
||||
template<typename OtherDerived> EIGEN_STRONG_INLINE
|
||||
template<typename OtherDerived> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC
|
||||
CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
|
||||
const ExpressionTypeNestedCleaned,
|
||||
const typename ExtendedType<OtherDerived>::Type>
|
||||
@@ -503,6 +539,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
|
||||
/** Returns the expression of the difference between each subvector of \c *this and the vector \a other */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
CwiseBinaryOp<internal::scalar_difference_op<Scalar>,
|
||||
const ExpressionTypeNestedCleaned,
|
||||
const typename ExtendedType<OtherDerived>::Type>
|
||||
@@ -515,10 +552,11 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
|
||||
/** Returns the expression where each subvector is the product of the vector \a other
|
||||
* by the corresponding subvector of \c *this */
|
||||
template<typename OtherDerived> EIGEN_STRONG_INLINE
|
||||
template<typename OtherDerived> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC
|
||||
CwiseBinaryOp<internal::scalar_product_op<Scalar>,
|
||||
const ExpressionTypeNestedCleaned,
|
||||
const typename ExtendedType<OtherDerived>::Type>
|
||||
EIGEN_DEVICE_FUNC
|
||||
operator*(const DenseBase<OtherDerived>& other) const
|
||||
{
|
||||
EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
|
||||
@@ -530,6 +568,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
/** Returns the expression where each subvector is the quotient of the corresponding
|
||||
* subvector of \c *this by the vector \a other */
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
CwiseBinaryOp<internal::scalar_quotient_op<Scalar>,
|
||||
const ExpressionTypeNestedCleaned,
|
||||
const typename ExtendedType<OtherDerived>::Type>
|
||||
@@ -545,6 +584,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
* The referenced matrix is \b not modified.
|
||||
* \sa MatrixBase::normalized(), normalize()
|
||||
*/
|
||||
EIGEN_DEVICE_FUNC
|
||||
CwiseBinaryOp<internal::scalar_quotient_op<Scalar>,
|
||||
const ExpressionTypeNestedCleaned,
|
||||
const typename OppositeExtendedType<typename ReturnType<internal::member_norm,RealScalar>::Type>::Type>
|
||||
@@ -554,16 +594,20 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
/** Normalize in-place each row or columns of the referenced matrix.
|
||||
* \sa MatrixBase::normalize(), normalized()
|
||||
*/
|
||||
void normalize() {
|
||||
EIGEN_DEVICE_FUNC void normalize() {
|
||||
m_matrix = this->normalized();
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC inline void reverseInPlace();
|
||||
|
||||
/////////// Geometry module ///////////
|
||||
|
||||
Homogeneous<ExpressionType,Direction> homogeneous() const;
|
||||
typedef Homogeneous<ExpressionType,Direction> HomogeneousReturnType;
|
||||
HomogeneousReturnType homogeneous() const;
|
||||
|
||||
typedef typename ExpressionType::PlainObject CrossReturnType;
|
||||
template<typename OtherDerived>
|
||||
EIGEN_DEVICE_FUNC
|
||||
const CrossReturnType cross(const MatrixBase<OtherDerived>& other) const;
|
||||
|
||||
enum {
|
||||
@@ -594,19 +638,8 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
|
||||
ExpressionTypeNested m_matrix;
|
||||
};
|
||||
|
||||
/** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
|
||||
*
|
||||
* Example: \include MatrixBase_colwise.cpp
|
||||
* Output: \verbinclude MatrixBase_colwise.out
|
||||
*
|
||||
* \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
|
||||
*/
|
||||
template<typename Derived>
|
||||
inline const typename DenseBase<Derived>::ConstColwiseReturnType
|
||||
DenseBase<Derived>::colwise() const
|
||||
{
|
||||
return derived();
|
||||
}
|
||||
//const colwise moved to DenseBase.h due to CUDA compiler bug
|
||||
|
||||
|
||||
/** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
|
||||
*
|
||||
@@ -616,22 +649,11 @@ template<typename Derived>
|
||||
inline typename DenseBase<Derived>::ColwiseReturnType
|
||||
DenseBase<Derived>::colwise()
|
||||
{
|
||||
return derived();
|
||||
return ColwiseReturnType(derived());
|
||||
}
|
||||
|
||||
/** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
|
||||
*
|
||||
* Example: \include MatrixBase_rowwise.cpp
|
||||
* Output: \verbinclude MatrixBase_rowwise.out
|
||||
*
|
||||
* \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
|
||||
*/
|
||||
template<typename Derived>
|
||||
inline const typename DenseBase<Derived>::ConstRowwiseReturnType
|
||||
DenseBase<Derived>::rowwise() const
|
||||
{
|
||||
return derived();
|
||||
}
|
||||
//const rowwise moved to DenseBase.h due to CUDA compiler bug
|
||||
|
||||
|
||||
/** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
|
||||
*
|
||||
@@ -641,7 +663,7 @@ template<typename Derived>
|
||||
inline typename DenseBase<Derived>::RowwiseReturnType
|
||||
DenseBase<Derived>::rowwise()
|
||||
{
|
||||
return derived();
|
||||
return RowwiseReturnType(derived());
|
||||
}
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -22,6 +22,7 @@ struct visitor_impl
|
||||
row = (UnrollCount-1) % Derived::RowsAtCompileTime
|
||||
};
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(const Derived &mat, Visitor& visitor)
|
||||
{
|
||||
visitor_impl<Visitor, Derived, UnrollCount-1>::run(mat, visitor);
|
||||
@@ -32,6 +33,7 @@ struct visitor_impl
|
||||
template<typename Visitor, typename Derived>
|
||||
struct visitor_impl<Visitor, Derived, 1>
|
||||
{
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(const Derived &mat, Visitor& visitor)
|
||||
{
|
||||
return visitor.init(mat.coeff(0, 0), 0, 0);
|
||||
@@ -41,7 +43,7 @@ struct visitor_impl<Visitor, Derived, 1>
|
||||
template<typename Visitor, typename Derived>
|
||||
struct visitor_impl<Visitor, Derived, Dynamic>
|
||||
{
|
||||
typedef typename Derived::Index Index;
|
||||
EIGEN_DEVICE_FUNC
|
||||
static inline void run(const Derived& mat, Visitor& visitor)
|
||||
{
|
||||
visitor.init(mat.coeff(0,0), 0, 0);
|
||||
@@ -53,6 +55,33 @@ struct visitor_impl<Visitor, Derived, Dynamic>
|
||||
}
|
||||
};
|
||||
|
||||
// evaluator adaptor
|
||||
template<typename XprType>
|
||||
class visitor_evaluator
|
||||
{
|
||||
public:
|
||||
EIGEN_DEVICE_FUNC
|
||||
explicit visitor_evaluator(const XprType &xpr) : m_evaluator(xpr), m_xpr(xpr) {}
|
||||
|
||||
typedef typename XprType::Scalar Scalar;
|
||||
typedef typename XprType::CoeffReturnType CoeffReturnType;
|
||||
|
||||
enum {
|
||||
RowsAtCompileTime = XprType::RowsAtCompileTime,
|
||||
CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
|
||||
};
|
||||
|
||||
EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
|
||||
EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
|
||||
EIGEN_DEVICE_FUNC Index size() const { return m_xpr.size(); }
|
||||
|
||||
EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index row, Index col) const
|
||||
{ return m_evaluator.coeff(row, col); }
|
||||
|
||||
protected:
|
||||
internal::evaluator<XprType> m_evaluator;
|
||||
const XprType &m_xpr;
|
||||
};
|
||||
} // end namespace internal
|
||||
|
||||
/** Applies the visitor \a visitor to the whole coefficients of the matrix or vector.
|
||||
@@ -74,16 +103,20 @@ struct visitor_impl<Visitor, Derived, Dynamic>
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename Visitor>
|
||||
EIGEN_DEVICE_FUNC
|
||||
void DenseBase<Derived>::visit(Visitor& visitor) const
|
||||
{
|
||||
enum { unroll = SizeAtCompileTime != Dynamic
|
||||
&& CoeffReadCost != Dynamic
|
||||
&& (SizeAtCompileTime == 1 || internal::functor_traits<Visitor>::Cost != Dynamic)
|
||||
&& SizeAtCompileTime * CoeffReadCost + (SizeAtCompileTime-1) * internal::functor_traits<Visitor>::Cost
|
||||
<= EIGEN_UNROLLING_LIMIT };
|
||||
return internal::visitor_impl<Visitor, Derived,
|
||||
typedef typename internal::visitor_evaluator<Derived> ThisEvaluator;
|
||||
ThisEvaluator thisEval(derived());
|
||||
|
||||
enum { unroll = SizeAtCompileTime != Dynamic
|
||||
&& ThisEvaluator::CoeffReadCost != Dynamic
|
||||
&& (SizeAtCompileTime == 1 || internal::functor_traits<Visitor>::Cost != Dynamic)
|
||||
&& SizeAtCompileTime * ThisEvaluator::CoeffReadCost + (SizeAtCompileTime-1) * internal::functor_traits<Visitor>::Cost
|
||||
<= EIGEN_UNROLLING_LIMIT };
|
||||
return internal::visitor_impl<Visitor, ThisEvaluator,
|
||||
unroll ? int(SizeAtCompileTime) : Dynamic
|
||||
>::run(derived(), visitor);
|
||||
>::run(thisEval, visitor);
|
||||
}
|
||||
|
||||
namespace internal {
|
||||
@@ -94,10 +127,10 @@ namespace internal {
|
||||
template <typename Derived>
|
||||
struct coeff_visitor
|
||||
{
|
||||
typedef typename Derived::Index Index;
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
Index row, col;
|
||||
Scalar res;
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline void init(const Scalar& value, Index i, Index j)
|
||||
{
|
||||
res = value;
|
||||
@@ -114,8 +147,8 @@ struct coeff_visitor
|
||||
template <typename Derived>
|
||||
struct min_coeff_visitor : coeff_visitor<Derived>
|
||||
{
|
||||
typedef typename Derived::Index Index;
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
EIGEN_DEVICE_FUNC
|
||||
void operator() (const Scalar& value, Index i, Index j)
|
||||
{
|
||||
if(value < this->res)
|
||||
@@ -142,8 +175,8 @@ struct functor_traits<min_coeff_visitor<Scalar> > {
|
||||
template <typename Derived>
|
||||
struct max_coeff_visitor : coeff_visitor<Derived>
|
||||
{
|
||||
typedef typename Derived::Index Index;
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
typedef typename Derived::Scalar Scalar;
|
||||
EIGEN_DEVICE_FUNC
|
||||
void operator() (const Scalar& value, Index i, Index j)
|
||||
{
|
||||
if(value > this->res)
|
||||
@@ -171,6 +204,7 @@ struct functor_traits<max_coeff_visitor<Scalar> > {
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename IndexType>
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename internal::traits<Derived>::Scalar
|
||||
DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
|
||||
{
|
||||
@@ -188,6 +222,7 @@ DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename IndexType>
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename internal::traits<Derived>::Scalar
|
||||
DenseBase<Derived>::minCoeff(IndexType* index) const
|
||||
{
|
||||
@@ -205,6 +240,7 @@ DenseBase<Derived>::minCoeff(IndexType* index) const
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename IndexType>
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename internal::traits<Derived>::Scalar
|
||||
DenseBase<Derived>::maxCoeff(IndexType* rowPtr, IndexType* colPtr) const
|
||||
{
|
||||
@@ -222,6 +258,7 @@ DenseBase<Derived>::maxCoeff(IndexType* rowPtr, IndexType* colPtr) const
|
||||
*/
|
||||
template<typename Derived>
|
||||
template<typename IndexType>
|
||||
EIGEN_DEVICE_FUNC
|
||||
typename internal::traits<Derived>::Scalar
|
||||
DenseBase<Derived>::maxCoeff(IndexType* index) const
|
||||
{
|
||||
|
||||
@@ -45,7 +45,7 @@ template<> struct packet_traits<std::complex<float> > : default_packet_traits
|
||||
};
|
||||
};
|
||||
|
||||
template<> struct unpacket_traits<Packet4cf> { typedef std::complex<float> type; enum {size=4}; typedef Packet2cf half; };
|
||||
template<> struct unpacket_traits<Packet4cf> { typedef std::complex<float> type; enum {size=4, alignment=Aligned32}; typedef Packet2cf half; };
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet4cf padd<Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_add_ps(a.v,b.v)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4cf psub<Packet4cf>(const Packet4cf& a, const Packet4cf& b) { return Packet4cf(_mm256_sub_ps(a.v,b.v)); }
|
||||
@@ -92,7 +92,7 @@ template<> EIGEN_STRONG_INLINE Packet4cf ploaddup<Packet4cf>(const std::complex<
|
||||
template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float>* to, const Packet4cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore(&numext::real_ref(*to), from.v); }
|
||||
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float>* to, const Packet4cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(&numext::real_ref(*to), from.v); }
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet4cf pgather<std::complex<float>, Packet4cf>(const std::complex<float>* from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet4cf pgather<std::complex<float>, Packet4cf>(const std::complex<float>* from, Index stride)
|
||||
{
|
||||
return Packet4cf(_mm256_set_ps(std::imag(from[3*stride]), std::real(from[3*stride]),
|
||||
std::imag(from[2*stride]), std::real(from[2*stride]),
|
||||
@@ -100,7 +100,7 @@ template<> EIGEN_DEVICE_FUNC inline Packet4cf pgather<std::complex<float>, Packe
|
||||
std::imag(from[0*stride]), std::real(from[0*stride])));
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet4cf>(std::complex<float>* to, const Packet4cf& from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet4cf>(std::complex<float>* to, const Packet4cf& from, Index stride)
|
||||
{
|
||||
__m128 low = _mm256_extractf128_ps(from.v, 0);
|
||||
to[stride*0] = std::complex<float>(_mm_cvtss_f32(_mm_shuffle_ps(low, low, 0)),
|
||||
@@ -267,7 +267,7 @@ template<> struct packet_traits<std::complex<double> > : default_packet_traits
|
||||
};
|
||||
};
|
||||
|
||||
template<> struct unpacket_traits<Packet2cd> { typedef std::complex<double> type; enum {size=2}; typedef Packet1cd half; };
|
||||
template<> struct unpacket_traits<Packet2cd> { typedef std::complex<double> type; enum {size=2, alignment=Aligned32}; typedef Packet1cd half; };
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2cd padd<Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_add_pd(a.v,b.v)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet2cd psub<Packet2cd>(const Packet2cd& a, const Packet2cd& b) { return Packet2cd(_mm256_sub_pd(a.v,b.v)); }
|
||||
@@ -310,13 +310,13 @@ template<> EIGEN_STRONG_INLINE Packet2cd ploaddup<Packet2cd>(const std::complex<
|
||||
template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> * to, const Packet2cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
|
||||
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> * to, const Packet2cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet2cd pgather<std::complex<double>, Packet2cd>(const std::complex<double>* from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet2cd pgather<std::complex<double>, Packet2cd>(const std::complex<double>* from, Index stride)
|
||||
{
|
||||
return Packet2cd(_mm256_set_pd(std::imag(from[1*stride]), std::real(from[1*stride]),
|
||||
std::imag(from[0*stride]), std::real(from[0*stride])));
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet2cd>(std::complex<double>* to, const Packet2cd& from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet2cd>(std::complex<double>* to, const Packet2cd& from, Index stride)
|
||||
{
|
||||
__m128d low = _mm256_extractf128_pd(from.v, 0);
|
||||
to[stride*0] = std::complex<double>(_mm_cvtsd_f64(low), _mm_cvtsd_f64(_mm_shuffle_pd(low, low, 1)));
|
||||
|
||||
441
Eigen/src/Core/arch/AVX/MathFunctions.h
Normal file
441
Eigen/src/Core/arch/AVX/MathFunctions.h
Normal file
@@ -0,0 +1,441 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2014 Pedro Gonnet (pedro.gonnet@gmail.com)
|
||||
//
|
||||
// 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_MATH_FUNCTIONS_AVX_H
|
||||
#define EIGEN_MATH_FUNCTIONS_AVX_H
|
||||
|
||||
// For some reason, this function didn't make it into the avxintirn.h
|
||||
// used by the compiler, so we'll just wrap it.
|
||||
#define _mm256_setr_m128(lo, hi) \
|
||||
_mm256_insertf128_si256(_mm256_castsi128_si256(lo), (hi), 1)
|
||||
|
||||
/* The sin, cos, exp, and log functions of this file are loosely derived from
|
||||
* Julien Pommier's sse math library: http://gruntthepeon.free.fr/ssemath/
|
||||
*/
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
|
||||
// Sine function
|
||||
// Computes sin(x) by wrapping x to the interval [-Pi/4,3*Pi/4] and
|
||||
// evaluating interpolants in [-Pi/4,Pi/4] or [Pi/4,3*Pi/4]. The interpolants
|
||||
// are (anti-)symmetric and thus have only odd/even coefficients
|
||||
template <>
|
||||
EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
|
||||
psin<Packet8f>(const Packet8f& _x) {
|
||||
Packet8f x = _x;
|
||||
|
||||
// Some useful values.
|
||||
_EIGEN_DECLARE_CONST_Packet8i(one, 1);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(one, 1.0f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(two, 2.0f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(one_over_four, 0.25f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(one_over_pi, 3.183098861837907e-01f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(neg_pi_first, -3.140625000000000e+00);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(neg_pi_second, -9.670257568359375e-04);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(neg_pi_third, -6.278329571784980e-07);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(four_over_pi, 1.273239544735163e+00);
|
||||
|
||||
// Map x from [-Pi/4,3*Pi/4] to z in [-1,3] and subtract the shifted period.
|
||||
Packet8f z = pmul(x, p8f_one_over_pi);
|
||||
Packet8f shift = _mm256_floor_ps(padd(z, p8f_one_over_four));
|
||||
x = pmadd(shift, p8f_neg_pi_first, x);
|
||||
x = pmadd(shift, p8f_neg_pi_second, x);
|
||||
x = pmadd(shift, p8f_neg_pi_third, x);
|
||||
z = pmul(x, p8f_four_over_pi);
|
||||
|
||||
// Make a mask for the entries that need flipping, i.e. wherever the shift
|
||||
// is odd.
|
||||
Packet8i shift_ints = _mm256_cvtps_epi32(shift);
|
||||
Packet8i shift_isodd =
|
||||
(__m256i)_mm256_and_ps((__m256)shift_ints, (__m256)p8i_one);
|
||||
#ifdef EIGEN_VECTORIZE_AVX2
|
||||
Packet8i sign_flip_mask = _mm256_slli_epi32(shift_isodd, 31);
|
||||
#else
|
||||
__m128i lo =
|
||||
_mm_slli_epi32(_mm256_extractf128_si256((__m256i)shift_isodd, 0), 31);
|
||||
__m128i hi =
|
||||
_mm_slli_epi32(_mm256_extractf128_si256((__m256i)shift_isodd, 1), 31);
|
||||
Packet8i sign_flip_mask = _mm256_setr_m128(lo, hi);
|
||||
#endif
|
||||
|
||||
// Create a mask for which interpolant to use, i.e. if z > 1, then the mask
|
||||
// is set to ones for that entry.
|
||||
Packet8f ival_mask = _mm256_cmp_ps(z, p8f_one, _CMP_GT_OQ);
|
||||
|
||||
// Evaluate the polynomial for the interval [1,3] in z.
|
||||
_EIGEN_DECLARE_CONST_Packet8f(coeff_right_0, 9.999999724233232e-01f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(coeff_right_2, -3.084242535619928e-01);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(coeff_right_4, 1.584991525700324e-02);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(coeff_right_6, -3.188805084631342e-04);
|
||||
Packet8f z_minus_two = psub(z, p8f_two);
|
||||
Packet8f z_minus_two2 = pmul(z_minus_two, z_minus_two);
|
||||
Packet8f right = pmadd(p8f_coeff_right_6, z_minus_two2, p8f_coeff_right_4);
|
||||
right = pmadd(right, z_minus_two2, p8f_coeff_right_2);
|
||||
right = pmadd(right, z_minus_two2, p8f_coeff_right_0);
|
||||
|
||||
// Evaluate the polynomial for the interval [-1,1] in z.
|
||||
_EIGEN_DECLARE_CONST_Packet8f(coeff_left_1, 7.853981525427295e-01);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(coeff_left_3, -8.074536727092352e-02);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(coeff_left_5, 2.489871967827018e-03);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(coeff_left_7, -3.587725841214251e-05);
|
||||
Packet8f z2 = pmul(z, z);
|
||||
Packet8f left = pmadd(p8f_coeff_left_7, z2, p8f_coeff_left_5);
|
||||
left = pmadd(left, z2, p8f_coeff_left_3);
|
||||
left = pmadd(left, z2, p8f_coeff_left_1);
|
||||
left = pmul(left, z);
|
||||
|
||||
// Assemble the results, i.e. select the left and right polynomials.
|
||||
left = _mm256_andnot_ps(ival_mask, left);
|
||||
right = _mm256_and_ps(ival_mask, right);
|
||||
Packet8f res = _mm256_or_ps(left, right);
|
||||
|
||||
// Flip the sign on the odd intervals and return the result.
|
||||
res = _mm256_xor_ps(res, (__m256)sign_flip_mask);
|
||||
return res;
|
||||
}
|
||||
|
||||
// Natural logarithm
|
||||
// Computes log(x) as log(2^e * m) = C*e + log(m), where the constant C =log(2)
|
||||
// and m is in the range [sqrt(1/2),sqrt(2)). In this range, the logarithm can
|
||||
// be easily approximated by a polynomial centered on m=1 for stability.
|
||||
// TODO(gonnet): Further reduce the interval allowing for lower-degree
|
||||
// polynomial interpolants -> ... -> profit!
|
||||
template <>
|
||||
EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
|
||||
plog<Packet8f>(const Packet8f& _x) {
|
||||
Packet8f x = _x;
|
||||
_EIGEN_DECLARE_CONST_Packet8f(1, 1.0f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(half, 0.5f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(126f, 126.0f);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet8f_FROM_INT(inv_mant_mask, ~0x7f800000);
|
||||
|
||||
// The smallest non denormalized float number.
|
||||
_EIGEN_DECLARE_CONST_Packet8f_FROM_INT(min_norm_pos, 0x00800000);
|
||||
_EIGEN_DECLARE_CONST_Packet8f_FROM_INT(minus_inf, 0xff800000);
|
||||
|
||||
// Polynomial coefficients.
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_SQRTHF, 0.707106781186547524f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_p0, 7.0376836292E-2f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_p1, -1.1514610310E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_p2, 1.1676998740E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_p3, -1.2420140846E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_p4, +1.4249322787E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_p5, -1.6668057665E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_p6, +2.0000714765E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_p7, -2.4999993993E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_p8, +3.3333331174E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_q1, -2.12194440e-4f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_log_q2, 0.693359375f);
|
||||
|
||||
Packet8f invalid_mask = _mm256_cmp_ps(x, _mm256_setzero_ps(), _CMP_NGE_UQ); // not greater equal is true if x is NaN
|
||||
Packet8f iszero_mask = _mm256_cmp_ps(x, _mm256_setzero_ps(), _CMP_EQ_OQ);
|
||||
|
||||
// Truncate input values to the minimum positive normal.
|
||||
x = pmax(x, p8f_min_norm_pos);
|
||||
|
||||
// Extract the shifted exponents (No bitwise shifting in regular AVX, so
|
||||
// convert to SSE and do it there).
|
||||
#ifdef EIGEN_VECTORIZE_AVX2
|
||||
Packet8f emm0 = _mm256_cvtepi32_ps(_mm256_srli_epi32((__m256i)x, 23));
|
||||
#else
|
||||
__m128i lo = _mm_srli_epi32(_mm256_extractf128_si256((__m256i)x, 0), 23);
|
||||
__m128i hi = _mm_srli_epi32(_mm256_extractf128_si256((__m256i)x, 1), 23);
|
||||
Packet8f emm0 = _mm256_cvtepi32_ps(_mm256_setr_m128(lo, hi));
|
||||
#endif
|
||||
Packet8f e = _mm256_sub_ps(emm0, p8f_126f);
|
||||
|
||||
// Set the exponents to -1, i.e. x are in the range [0.5,1).
|
||||
x = _mm256_and_ps(x, p8f_inv_mant_mask);
|
||||
x = _mm256_or_ps(x, p8f_half);
|
||||
|
||||
// part2: Shift the inputs from the range [0.5,1) to [sqrt(1/2),sqrt(2))
|
||||
// and shift by -1. The values are then centered around 0, which improves
|
||||
// the stability of the polynomial evaluation.
|
||||
// if( x < SQRTHF ) {
|
||||
// e -= 1;
|
||||
// x = x + x - 1.0;
|
||||
// } else { x = x - 1.0; }
|
||||
Packet8f mask = _mm256_cmp_ps(x, p8f_cephes_SQRTHF, _CMP_LT_OQ);
|
||||
Packet8f tmp = _mm256_and_ps(x, mask);
|
||||
x = psub(x, p8f_1);
|
||||
e = psub(e, _mm256_and_ps(p8f_1, mask));
|
||||
x = padd(x, tmp);
|
||||
|
||||
Packet8f x2 = pmul(x, x);
|
||||
Packet8f x3 = pmul(x2, x);
|
||||
|
||||
// Evaluate the polynomial approximant of degree 8 in three parts, probably
|
||||
// to improve instruction-level parallelism.
|
||||
Packet8f y, y1, y2;
|
||||
y = pmadd(p8f_cephes_log_p0, x, p8f_cephes_log_p1);
|
||||
y1 = pmadd(p8f_cephes_log_p3, x, p8f_cephes_log_p4);
|
||||
y2 = pmadd(p8f_cephes_log_p6, x, p8f_cephes_log_p7);
|
||||
y = pmadd(y, x, p8f_cephes_log_p2);
|
||||
y1 = pmadd(y1, x, p8f_cephes_log_p5);
|
||||
y2 = pmadd(y2, x, p8f_cephes_log_p8);
|
||||
y = pmadd(y, x3, y1);
|
||||
y = pmadd(y, x3, y2);
|
||||
y = pmul(y, x3);
|
||||
|
||||
// Add the logarithm of the exponent back to the result of the interpolation.
|
||||
y1 = pmul(e, p8f_cephes_log_q1);
|
||||
tmp = pmul(x2, p8f_half);
|
||||
y = padd(y, y1);
|
||||
x = psub(x, tmp);
|
||||
y2 = pmul(e, p8f_cephes_log_q2);
|
||||
x = padd(x, y);
|
||||
x = padd(x, y2);
|
||||
|
||||
// Filter out invalid inputs, i.e. negative arg will be NAN, 0 will be -INF.
|
||||
return _mm256_or_ps(
|
||||
_mm256_andnot_ps(iszero_mask, _mm256_or_ps(x, invalid_mask)),
|
||||
_mm256_and_ps(iszero_mask, p8f_minus_inf));
|
||||
}
|
||||
|
||||
// Exponential function. Works by writing "x = m*log(2) + r" where
|
||||
// "m = floor(x/log(2)+1/2)" and "r" is the remainder. The result is then
|
||||
// "exp(x) = 2^m*exp(r)" where exp(r) is in the range [-1,1).
|
||||
template <>
|
||||
EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
|
||||
pexp<Packet8f>(const Packet8f& _x) {
|
||||
_EIGEN_DECLARE_CONST_Packet8f(1, 1.0f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(half, 0.5f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(127, 127.0f);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet8f(exp_hi, 88.3762626647950f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(exp_lo, -88.3762626647949f);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_LOG2EF, 1.44269504088896341f);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p0, 1.9875691500E-4f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p1, 1.3981999507E-3f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p2, 8.3334519073E-3f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p3, 4.1665795894E-2f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p4, 1.6666665459E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_exp_p5, 5.0000001201E-1f);
|
||||
|
||||
// Clamp x.
|
||||
Packet8f x = pmax(pmin(_x, p8f_exp_hi), p8f_exp_lo);
|
||||
|
||||
// Express exp(x) as exp(m*ln(2) + r), start by extracting
|
||||
// m = floor(x/ln(2) + 0.5).
|
||||
Packet8f m = _mm256_floor_ps(pmadd(x, p8f_cephes_LOG2EF, p8f_half));
|
||||
|
||||
// Get r = x - m*ln(2). If no FMA instructions are available, m*ln(2) is
|
||||
// subtracted out in two parts, m*C1+m*C2 = m*ln(2), to avoid accumulating
|
||||
// truncation errors. Note that we don't use the "pmadd" function here to
|
||||
// ensure that a precision-preserving FMA instruction is used.
|
||||
#ifdef EIGEN_VECTORIZE_FMA
|
||||
_EIGEN_DECLARE_CONST_Packet8f(nln2, -0.6931471805599453f);
|
||||
Packet8f r = _mm256_fmadd_ps(m, p8f_nln2, x);
|
||||
#else
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_exp_C1, 0.693359375f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(cephes_exp_C2, -2.12194440e-4f);
|
||||
Packet8f r = psub(x, pmul(m, p8f_cephes_exp_C1));
|
||||
r = psub(r, pmul(m, p8f_cephes_exp_C2));
|
||||
#endif
|
||||
|
||||
Packet8f r2 = pmul(r, r);
|
||||
|
||||
// TODO(gonnet): Split into odd/even polynomials and try to exploit
|
||||
// instruction-level parallelism.
|
||||
Packet8f y = p8f_cephes_exp_p0;
|
||||
y = pmadd(y, r, p8f_cephes_exp_p1);
|
||||
y = pmadd(y, r, p8f_cephes_exp_p2);
|
||||
y = pmadd(y, r, p8f_cephes_exp_p3);
|
||||
y = pmadd(y, r, p8f_cephes_exp_p4);
|
||||
y = pmadd(y, r, p8f_cephes_exp_p5);
|
||||
y = pmadd(y, r2, r);
|
||||
y = padd(y, p8f_1);
|
||||
|
||||
// Build emm0 = 2^m.
|
||||
Packet8i emm0 = _mm256_cvttps_epi32(padd(m, p8f_127));
|
||||
#ifdef EIGEN_VECTORIZE_AVX2
|
||||
emm0 = _mm256_slli_epi32(emm0, 23);
|
||||
#else
|
||||
__m128i lo = _mm_slli_epi32(_mm256_extractf128_si256(emm0, 0), 23);
|
||||
__m128i hi = _mm_slli_epi32(_mm256_extractf128_si256(emm0, 1), 23);
|
||||
emm0 = _mm256_setr_m128(lo, hi);
|
||||
#endif
|
||||
|
||||
// Return 2^m * exp(r).
|
||||
return pmax(pmul(y, _mm256_castsi256_ps(emm0)), _x);
|
||||
}
|
||||
|
||||
template <>
|
||||
EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet4d
|
||||
pexp<Packet4d>(const Packet4d& _x) {
|
||||
Packet4d x = _x;
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4d(1, 1.0);
|
||||
_EIGEN_DECLARE_CONST_Packet4d(2, 2.0);
|
||||
_EIGEN_DECLARE_CONST_Packet4d(half, 0.5);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4d(exp_hi, 709.437);
|
||||
_EIGEN_DECLARE_CONST_Packet4d(exp_lo, -709.436139303);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_LOG2EF, 1.4426950408889634073599);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_exp_p0, 1.26177193074810590878e-4);
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_exp_p1, 3.02994407707441961300e-2);
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_exp_p2, 9.99999999999999999910e-1);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_exp_q0, 3.00198505138664455042e-6);
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_exp_q1, 2.52448340349684104192e-3);
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_exp_q2, 2.27265548208155028766e-1);
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_exp_q3, 2.00000000000000000009e0);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_exp_C1, 0.693145751953125);
|
||||
_EIGEN_DECLARE_CONST_Packet4d(cephes_exp_C2, 1.42860682030941723212e-6);
|
||||
_EIGEN_DECLARE_CONST_Packet4i(1023, 1023);
|
||||
|
||||
Packet4d tmp, fx;
|
||||
|
||||
// clamp x
|
||||
x = pmax(pmin(x, p4d_exp_hi), p4d_exp_lo);
|
||||
// Express exp(x) as exp(g + n*log(2)).
|
||||
fx = pmadd(p4d_cephes_LOG2EF, x, p4d_half);
|
||||
|
||||
// Get the integer modulus of log(2), i.e. the "n" described above.
|
||||
fx = _mm256_floor_pd(fx);
|
||||
|
||||
// Get the remainder modulo log(2), i.e. the "g" described above. Subtract
|
||||
// n*log(2) out in two steps, i.e. n*C1 + n*C2, C1+C2=log2 to get the last
|
||||
// digits right.
|
||||
tmp = pmul(fx, p4d_cephes_exp_C1);
|
||||
Packet4d z = pmul(fx, p4d_cephes_exp_C2);
|
||||
x = psub(x, tmp);
|
||||
x = psub(x, z);
|
||||
|
||||
Packet4d x2 = pmul(x, x);
|
||||
|
||||
// Evaluate the numerator polynomial of the rational interpolant.
|
||||
Packet4d px = p4d_cephes_exp_p0;
|
||||
px = pmadd(px, x2, p4d_cephes_exp_p1);
|
||||
px = pmadd(px, x2, p4d_cephes_exp_p2);
|
||||
px = pmul(px, x);
|
||||
|
||||
// Evaluate the denominator polynomial of the rational interpolant.
|
||||
Packet4d qx = p4d_cephes_exp_q0;
|
||||
qx = pmadd(qx, x2, p4d_cephes_exp_q1);
|
||||
qx = pmadd(qx, x2, p4d_cephes_exp_q2);
|
||||
qx = pmadd(qx, x2, p4d_cephes_exp_q3);
|
||||
|
||||
// I don't really get this bit, copied from the SSE2 routines, so...
|
||||
// TODO(gonnet): Figure out what is going on here, perhaps find a better
|
||||
// rational interpolant?
|
||||
x = _mm256_div_pd(px, psub(qx, px));
|
||||
x = pmadd(p4d_2, x, p4d_1);
|
||||
|
||||
// Build e=2^n by constructing the exponents in a 128-bit vector and
|
||||
// shifting them to where they belong in double-precision values.
|
||||
__m128i emm0 = _mm256_cvtpd_epi32(fx);
|
||||
emm0 = _mm_add_epi32(emm0, p4i_1023);
|
||||
emm0 = _mm_shuffle_epi32(emm0, _MM_SHUFFLE(3, 1, 2, 0));
|
||||
__m128i lo = _mm_slli_epi64(emm0, 52);
|
||||
__m128i hi = _mm_slli_epi64(_mm_srli_epi64(emm0, 32), 52);
|
||||
__m256i e = _mm256_insertf128_si256(_mm256_setzero_si256(), lo, 0);
|
||||
e = _mm256_insertf128_si256(e, hi, 1);
|
||||
|
||||
// Construct the result 2^n * exp(g) = e * x. The max is used to catch
|
||||
// non-finite values in the input.
|
||||
return pmax(pmul(x, Packet4d(e)), _x);
|
||||
}
|
||||
|
||||
// Functions for sqrt.
|
||||
// The EIGEN_FAST_MATH version uses the _mm_rsqrt_ps approximation and one step
|
||||
// of Newton's method, at a cost of 1-2 bits of precision as opposed to the
|
||||
// exact solution. The main advantage of this approach is not just speed, but
|
||||
// also the fact that it can be inlined and pipelined with other computations,
|
||||
// further reducing its effective latency.
|
||||
#if EIGEN_FAST_MATH
|
||||
template <>
|
||||
EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
|
||||
psqrt<Packet8f>(const Packet8f& _x) {
|
||||
_EIGEN_DECLARE_CONST_Packet8f(one_point_five, 1.5f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(minus_half, -0.5f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f_FROM_INT(flt_min, 0x00800000);
|
||||
|
||||
Packet8f neg_half = pmul(_x, p8f_minus_half);
|
||||
|
||||
// select only the inverse sqrt of positive normal inputs (denormals are
|
||||
// flushed to zero and cause infs as well).
|
||||
Packet8f non_zero_mask = _mm256_cmp_ps(_x, p8f_flt_min, _CMP_GE_OQ);
|
||||
Packet8f x = _mm256_and_ps(non_zero_mask, _mm256_rsqrt_ps(_x));
|
||||
|
||||
// Do a single step of Newton's iteration.
|
||||
x = pmul(x, pmadd(neg_half, pmul(x, x), p8f_one_point_five));
|
||||
|
||||
// Multiply the original _x by it's reciprocal square root to extract the
|
||||
// square root.
|
||||
return pmul(_x, x);
|
||||
}
|
||||
#else
|
||||
template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
|
||||
Packet8f psqrt<Packet8f>(const Packet8f& x) {
|
||||
return _mm256_sqrt_ps(x);
|
||||
}
|
||||
#endif
|
||||
template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
|
||||
Packet4d psqrt<Packet4d>(const Packet4d& x) {
|
||||
return _mm256_sqrt_pd(x);
|
||||
}
|
||||
#if EIGEN_FAST_MATH
|
||||
|
||||
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
|
||||
Packet8f prsqrt<Packet8f>(const Packet8f& _x) {
|
||||
_EIGEN_DECLARE_CONST_Packet8f_FROM_INT(inf, 0x7f800000);
|
||||
_EIGEN_DECLARE_CONST_Packet8f_FROM_INT(nan, 0x7fc00000);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(one_point_five, 1.5f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f(minus_half, -0.5f);
|
||||
_EIGEN_DECLARE_CONST_Packet8f_FROM_INT(flt_min, 0x00800000);
|
||||
|
||||
Packet8f neg_half = pmul(_x, p8f_minus_half);
|
||||
|
||||
// select only the inverse sqrt of positive normal inputs (denormals are
|
||||
// flushed to zero and cause infs as well).
|
||||
Packet8f le_zero_mask = _mm256_cmp_ps(_x, p8f_flt_min, _CMP_LT_OQ);
|
||||
Packet8f x = _mm256_andnot_ps(le_zero_mask, _mm256_rsqrt_ps(_x));
|
||||
|
||||
// Fill in NaNs and Infs for the negative/zero entries.
|
||||
Packet8f neg_mask = _mm256_cmp_ps(_x, _mm256_setzero_ps(), _CMP_LT_OQ);
|
||||
Packet8f zero_mask = _mm256_andnot_ps(neg_mask, le_zero_mask);
|
||||
Packet8f infs_and_nans = _mm256_or_ps(_mm256_and_ps(neg_mask, p8f_nan),
|
||||
_mm256_and_ps(zero_mask, p8f_inf));
|
||||
|
||||
// Do a single step of Newton's iteration.
|
||||
x = pmul(x, pmadd(neg_half, pmul(x, x), p8f_one_point_five));
|
||||
|
||||
// Insert NaNs and Infs in all the right places.
|
||||
return _mm256_or_ps(x, infs_and_nans);
|
||||
}
|
||||
|
||||
#else
|
||||
template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
|
||||
Packet8f prsqrt<Packet8f>(const Packet8f& x) {
|
||||
_EIGEN_DECLARE_CONST_Packet8f(one, 1.0f);
|
||||
return _mm256_div_ps(p8f_one, _mm256_sqrt_ps(x));
|
||||
}
|
||||
#endif
|
||||
|
||||
template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
|
||||
Packet4d prsqrt<Packet4d>(const Packet4d& x) {
|
||||
_EIGEN_DECLARE_CONST_Packet4d(one, 1.0);
|
||||
return _mm256_div_pd(p4d_one, _mm256_sqrt_pd(x));
|
||||
}
|
||||
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_MATH_FUNCTIONS_AVX_H
|
||||
@@ -22,9 +22,9 @@ namespace internal {
|
||||
#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS (2*sizeof(void*))
|
||||
#endif
|
||||
|
||||
#ifdef EIGEN_VECTORIZE_FMA
|
||||
#ifndef EIGEN_HAS_FUSED_MADD
|
||||
#define EIGEN_HAS_FUSED_MADD 1
|
||||
#ifdef __FMA__
|
||||
#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
|
||||
#define EIGEN_HAS_SINGLE_INSTRUCTION_MADD
|
||||
#endif
|
||||
#endif
|
||||
|
||||
@@ -42,6 +42,12 @@ template<> struct is_arithmetic<__m256d> { enum { value = true }; };
|
||||
#define _EIGEN_DECLARE_CONST_Packet4d(NAME,X) \
|
||||
const Packet4d p4d_##NAME = pset1<Packet4d>(X)
|
||||
|
||||
#define _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(NAME,X) \
|
||||
const Packet8f p8f_##NAME = (__m256)pset1<Packet8i>(X)
|
||||
|
||||
#define _EIGEN_DECLARE_CONST_Packet8i(NAME,X) \
|
||||
const Packet8i p8i_##NAME = pset1<Packet8i>(X)
|
||||
|
||||
|
||||
template<> struct packet_traits<float> : default_packet_traits
|
||||
{
|
||||
@@ -54,13 +60,15 @@ template<> struct packet_traits<float> : default_packet_traits
|
||||
HasHalfPacket = 1,
|
||||
|
||||
HasDiv = 1,
|
||||
HasSin = 0,
|
||||
HasSin = EIGEN_FAST_MATH,
|
||||
HasCos = 0,
|
||||
HasLog = 0,
|
||||
HasExp = 0,
|
||||
HasSqrt = 0
|
||||
HasLog = 1,
|
||||
HasExp = 1,
|
||||
HasSqrt = 1,
|
||||
HasRsqrt = 1,
|
||||
HasBlend = 1
|
||||
};
|
||||
};
|
||||
};
|
||||
template<> struct packet_traits<double> : default_packet_traits
|
||||
{
|
||||
typedef Packet4d type;
|
||||
@@ -72,7 +80,10 @@ template<> struct packet_traits<double> : default_packet_traits
|
||||
HasHalfPacket = 1,
|
||||
|
||||
HasDiv = 1,
|
||||
HasExp = 0
|
||||
HasExp = 1,
|
||||
HasSqrt = 1,
|
||||
HasRsqrt = 1,
|
||||
HasBlend = 1
|
||||
};
|
||||
};
|
||||
|
||||
@@ -89,9 +100,9 @@ template<> struct packet_traits<int> : default_packet_traits
|
||||
};
|
||||
*/
|
||||
|
||||
template<> struct unpacket_traits<Packet8f> { typedef float type; typedef Packet4f half; enum {size=8}; };
|
||||
template<> struct unpacket_traits<Packet4d> { typedef double type; typedef Packet2d half; enum {size=4}; };
|
||||
template<> struct unpacket_traits<Packet8i> { typedef int type; typedef Packet4i half; enum {size=8}; };
|
||||
template<> struct unpacket_traits<Packet8f> { typedef float type; typedef Packet4f half; enum {size=8, alignment=Aligned32}; };
|
||||
template<> struct unpacket_traits<Packet4d> { typedef double type; typedef Packet2d half; enum {size=4, alignment=Aligned32}; };
|
||||
template<> struct unpacket_traits<Packet8i> { typedef int type; typedef Packet4i half; enum {size=8, alignment=Aligned32}; };
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet8f pset1<Packet8f>(const float& from) { return _mm256_set1_ps(from); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4d pset1<Packet4d>(const double& from) { return _mm256_set1_pd(from); }
|
||||
@@ -100,8 +111,8 @@ template<> EIGEN_STRONG_INLINE Packet8i pset1<Packet8i>(const int& from) { re
|
||||
template<> EIGEN_STRONG_INLINE Packet8f pload1<Packet8f>(const float* from) { return _mm256_broadcast_ss(from); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4d pload1<Packet4d>(const double* from) { return _mm256_broadcast_sd(from); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet8f plset<float>(const float& a) { return _mm256_add_ps(_mm256_set1_ps(a), _mm256_set_ps(7.0,6.0,5.0,4.0,3.0,2.0,1.0,0.0)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4d plset<double>(const double& a) { return _mm256_add_pd(_mm256_set1_pd(a), _mm256_set_pd(3.0,2.0,1.0,0.0)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet8f plset<Packet8f>(const float& a) { return _mm256_add_ps(_mm256_set1_ps(a), _mm256_set_ps(7.0,6.0,5.0,4.0,3.0,2.0,1.0,0.0)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4d plset<Packet4d>(const double& a) { return _mm256_add_pd(_mm256_set1_pd(a), _mm256_set_pd(3.0,2.0,1.0,0.0)); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet8f padd<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_add_ps(a,b); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4d padd<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_add_pd(a,b); }
|
||||
@@ -133,9 +144,9 @@ template<> EIGEN_STRONG_INLINE Packet8i pdiv<Packet8i>(const Packet8i& /*a*/, co
|
||||
return pset1<Packet8i>(0);
|
||||
}
|
||||
|
||||
#ifdef EIGEN_VECTORIZE_FMA
|
||||
#ifdef __FMA__
|
||||
template<> EIGEN_STRONG_INLINE Packet8f pmadd(const Packet8f& a, const Packet8f& b, const Packet8f& c) {
|
||||
#if defined(__clang__) || defined(__GNUC__)
|
||||
#if EIGEN_COMP_GNUC || EIGEN_COMP_CLANG
|
||||
// clang stupidly generates a vfmadd213ps instruction plus some vmovaps on registers,
|
||||
// and gcc stupidly generates a vfmadd132ps instruction,
|
||||
// so let's enforce it to generate a vfmadd231ps instruction since the most common use case is to accumulate
|
||||
@@ -148,7 +159,7 @@ template<> EIGEN_STRONG_INLINE Packet8f pmadd(const Packet8f& a, const Packet8f&
|
||||
#endif
|
||||
}
|
||||
template<> EIGEN_STRONG_INLINE Packet4d pmadd(const Packet4d& a, const Packet4d& b, const Packet4d& c) {
|
||||
#if defined(__clang__) || defined(__GNUC__)
|
||||
#if EIGEN_COMP_GNUC || EIGEN_COMP_CLANG
|
||||
// see above
|
||||
Packet4d res = c;
|
||||
__asm__("vfmadd231pd %[a], %[b], %[c]" : [c] "+x" (res) : [a] "x" (a), [b] "x" (b));
|
||||
@@ -224,17 +235,17 @@ template<> EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet8i&
|
||||
|
||||
// NOTE: leverage _mm256_i32gather_ps and _mm256_i32gather_pd if AVX2 instructions are available
|
||||
// NOTE: for the record the following seems to be slower: return _mm256_i32gather_ps(from, _mm256_set1_epi32(stride), 4);
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet8f pgather<float, Packet8f>(const float* from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet8f pgather<float, Packet8f>(const float* from, Index stride)
|
||||
{
|
||||
return _mm256_set_ps(from[7*stride], from[6*stride], from[5*stride], from[4*stride],
|
||||
from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
|
||||
}
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet4d pgather<double, Packet4d>(const double* from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet4d pgather<double, Packet4d>(const double* from, Index stride)
|
||||
{
|
||||
return _mm256_set_pd(from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet8f>(float* to, const Packet8f& from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet8f>(float* to, const Packet8f& from, Index stride)
|
||||
{
|
||||
__m128 low = _mm256_extractf128_ps(from, 0);
|
||||
to[stride*0] = _mm_cvtss_f32(low);
|
||||
@@ -248,7 +259,7 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet8f>(float* to, co
|
||||
to[stride*6] = _mm_cvtss_f32(_mm_shuffle_ps(high, high, 2));
|
||||
to[stride*7] = _mm_cvtss_f32(_mm_shuffle_ps(high, high, 3));
|
||||
}
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet4d>(double* to, const Packet4d& from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet4d>(double* to, const Packet4d& from, Index stride)
|
||||
{
|
||||
__m128d low = _mm256_extractf128_pd(from, 0);
|
||||
to[stride*0] = _mm_cvtsd_f64(low);
|
||||
@@ -423,26 +434,30 @@ struct palign_impl<Offset,Packet8f>
|
||||
if (Offset==1)
|
||||
{
|
||||
first = _mm256_blend_ps(first, second, 1);
|
||||
Packet8f tmp = _mm256_permute_ps (first, _MM_SHUFFLE(0,3,2,1));
|
||||
first = _mm256_blend_ps(tmp, _mm256_permute2f128_ps (tmp, tmp, 1), 0x88);
|
||||
Packet8f tmp1 = _mm256_permute_ps (first, _MM_SHUFFLE(0,3,2,1));
|
||||
Packet8f tmp2 = _mm256_permute2f128_ps (tmp1, tmp1, 1);
|
||||
first = _mm256_blend_ps(tmp1, tmp2, 0x88);
|
||||
}
|
||||
else if (Offset==2)
|
||||
{
|
||||
first = _mm256_blend_ps(first, second, 3);
|
||||
Packet8f tmp = _mm256_permute_ps (first, _MM_SHUFFLE(1,0,3,2));
|
||||
first = _mm256_blend_ps(tmp, _mm256_permute2f128_ps (tmp, tmp, 1), 0xcc);
|
||||
Packet8f tmp1 = _mm256_permute_ps (first, _MM_SHUFFLE(1,0,3,2));
|
||||
Packet8f tmp2 = _mm256_permute2f128_ps (tmp1, tmp1, 1);
|
||||
first = _mm256_blend_ps(tmp1, tmp2, 0xcc);
|
||||
}
|
||||
else if (Offset==3)
|
||||
{
|
||||
first = _mm256_blend_ps(first, second, 7);
|
||||
Packet8f tmp = _mm256_permute_ps (first, _MM_SHUFFLE(2,1,0,3));
|
||||
first = _mm256_blend_ps(tmp, _mm256_permute2f128_ps (tmp, tmp, 1), 0xee);
|
||||
Packet8f tmp1 = _mm256_permute_ps (first, _MM_SHUFFLE(2,1,0,3));
|
||||
Packet8f tmp2 = _mm256_permute2f128_ps (tmp1, tmp1, 1);
|
||||
first = _mm256_blend_ps(tmp1, tmp2, 0xee);
|
||||
}
|
||||
else if (Offset==4)
|
||||
{
|
||||
first = _mm256_blend_ps(first, second, 15);
|
||||
Packet8f tmp = _mm256_permute_ps (first, _MM_SHUFFLE(3,2,1,0));
|
||||
first = _mm256_permute_ps(_mm256_permute2f128_ps (tmp, tmp, 1), _MM_SHUFFLE(3,2,1,0));
|
||||
Packet8f tmp1 = _mm256_permute_ps (first, _MM_SHUFFLE(3,2,1,0));
|
||||
Packet8f tmp2 = _mm256_permute2f128_ps (tmp1, tmp1, 1);
|
||||
first = _mm256_permute_ps(tmp2, _MM_SHUFFLE(3,2,1,0));
|
||||
}
|
||||
else if (Offset==5)
|
||||
{
|
||||
@@ -557,6 +572,19 @@ ptranspose(PacketBlock<Packet4d,4>& kernel) {
|
||||
kernel.packet[2] = _mm256_permute2f128_pd(T1, T3, 49);
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet8f pblend(const Selector<8>& ifPacket, const Packet8f& thenPacket, const Packet8f& elsePacket) {
|
||||
const __m256 zero = _mm256_setzero_ps();
|
||||
const __m256 select = _mm256_set_ps(ifPacket.select[7], ifPacket.select[6], ifPacket.select[5], ifPacket.select[4], ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
|
||||
__m256 false_mask = _mm256_cmp_ps(select, zero, _CMP_EQ_UQ);
|
||||
return _mm256_blendv_ps(thenPacket, elsePacket, false_mask);
|
||||
}
|
||||
template<> EIGEN_STRONG_INLINE Packet4d pblend(const Selector<4>& ifPacket, const Packet4d& thenPacket, const Packet4d& elsePacket) {
|
||||
const __m256d zero = _mm256_setzero_pd();
|
||||
const __m256d select = _mm256_set_pd(ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
|
||||
__m256d false_mask = _mm256_cmp_pd(select, zero, _CMP_EQ_UQ);
|
||||
return _mm256_blendv_pd(thenPacket, elsePacket, false_mask);
|
||||
}
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
51
Eigen/src/Core/arch/AVX/TypeCasting.h
Normal file
51
Eigen/src/Core/arch/AVX/TypeCasting.h
Normal file
@@ -0,0 +1,51 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com>
|
||||
//
|
||||
// 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_TYPE_CASTING_AVX_H
|
||||
#define EIGEN_TYPE_CASTING_AVX_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
|
||||
// For now we use SSE to handle integers, so we can't use AVX instructions to cast
|
||||
// from int to float
|
||||
template <>
|
||||
struct type_casting_traits<float, int> {
|
||||
enum {
|
||||
VectorizedCast = 0,
|
||||
SrcCoeffRatio = 1,
|
||||
TgtCoeffRatio = 1
|
||||
};
|
||||
};
|
||||
|
||||
template <>
|
||||
struct type_casting_traits<int, float> {
|
||||
enum {
|
||||
VectorizedCast = 0,
|
||||
SrcCoeffRatio = 1,
|
||||
TgtCoeffRatio = 1
|
||||
};
|
||||
};
|
||||
|
||||
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet8i pcast<Packet8f, Packet8i>(const Packet8f& a) {
|
||||
return _mm256_cvtps_epi32(a);
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet8f pcast<Packet8i, Packet8f>(const Packet8i& a) {
|
||||
return _mm256_cvtepi32_ps(a);
|
||||
}
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_TYPE_CASTING_AVX_H
|
||||
@@ -7,23 +7,21 @@
|
||||
// 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_COMPLEX_ALTIVEC_H
|
||||
#define EIGEN_COMPLEX_ALTIVEC_H
|
||||
#ifndef EIGEN_COMPLEX32_ALTIVEC_H
|
||||
#define EIGEN_COMPLEX32_ALTIVEC_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
|
||||
static Packet4ui p4ui_CONJ_XOR = vec_mergeh((Packet4ui)p4i_ZERO, (Packet4ui)p4f_ZERO_);//{ 0x00000000, 0x80000000, 0x00000000, 0x80000000 };
|
||||
static Packet16uc p16uc_COMPLEX_RE = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 2), 8);//{ 0,1,2,3, 0,1,2,3, 8,9,10,11, 8,9,10,11 };
|
||||
static Packet16uc p16uc_COMPLEX_IM = vec_sld(p16uc_DUPLICATE, (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 };
|
||||
static Packet16uc p16uc_COMPLEX_REV = vec_sld(p16uc_REVERSE, p16uc_REVERSE, 8);//{ 4,5,6,7, 0,1,2,3, 12,13,14,15, 8,9,10,11 };
|
||||
static Packet16uc p16uc_COMPLEX_REV2 = vec_sld(p16uc_FORWARD, p16uc_FORWARD, 8);//{ 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
|
||||
static Packet16uc p16uc_PSET_HI = (Packet16uc) vec_mergeh((Packet4ui)p16uc_COMPLEX_RE, (Packet4ui)p16uc_COMPLEX_IM);//{ 0,1,2,3, 4,5,6,7, 0,1,2,3, 4,5,6,7 };
|
||||
static Packet16uc p16uc_PSET_LO = (Packet16uc) vec_mergel((Packet4ui)p16uc_COMPLEX_RE, (Packet4ui)p16uc_COMPLEX_IM);//{ 8,9,10,11, 12,13,14,15, 8,9,10,11, 12,13,14,15 };
|
||||
static Packet16uc p16uc_COMPLEX_MASK16 = vec_sld((Packet16uc)p4i_ZERO, vec_splat((Packet16uc) vec_abs(p4i_MINUS16), 3), 8);//{ 0,0,0,0, 0,0,0,0, 16,16,16,16, 16,16,16,16};
|
||||
static Packet16uc p16uc_COMPLEX_TRANSPOSE_0 = vec_add(p16uc_PSET_HI, p16uc_COMPLEX_MASK16);//{ 0,1,2,3, 4,5,6,7, 16,17,18,19, 20,21,22,23};
|
||||
static Packet16uc p16uc_COMPLEX_TRANSPOSE_1 = vec_add(p16uc_PSET_LO, p16uc_COMPLEX_MASK16);//{ 8,9,10,11, 12,13,14,15, 24,25,26,27, 28,29,30,31};
|
||||
#ifdef _BIG_ENDIAN
|
||||
static Packet2ul p2ul_CONJ_XOR1 = (Packet2ul) vec_sld((Packet4ui) p2d_ZERO_, (Packet4ui) p2l_ZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
|
||||
static Packet2ul p2ul_CONJ_XOR2 = (Packet2ul) vec_sld((Packet4ui) p2l_ZERO, (Packet4ui) p2d_ZERO_, 8);//{ 0x8000000000000000, 0x0000000000000000 };
|
||||
#else
|
||||
static Packet2ul p2ul_CONJ_XOR1 = (Packet2ul) vec_sld((Packet4ui) p2l_ZERO, (Packet4ui) p2d_ZERO_, 8);//{ 0x8000000000000000, 0x0000000000000000 };
|
||||
static Packet2ul p2ul_CONJ_XOR2 = (Packet2ul) vec_sld((Packet4ui) p2d_ZERO_, (Packet4ui) p2l_ZERO, 8);//{ 0x8000000000000000, 0x0000000000000000 };
|
||||
#endif
|
||||
|
||||
//---------- float ----------
|
||||
struct Packet2cf
|
||||
@@ -55,7 +53,7 @@ template<> struct packet_traits<std::complex<float> > : default_packet_traits
|
||||
};
|
||||
};
|
||||
|
||||
template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; enum {size=2}; typedef Packet2cf half; };
|
||||
template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; enum {size=2, alignment=Aligned16}; typedef Packet2cf half; };
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<float>& from)
|
||||
{
|
||||
@@ -65,18 +63,18 @@ template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<flo
|
||||
res.v = pload<Packet4f>((const float *)&from);
|
||||
else
|
||||
res.v = ploadu<Packet4f>((const float *)&from);
|
||||
res.v = vec_perm(res.v, res.v, p16uc_PSET_HI);
|
||||
res.v = vec_perm(res.v, res.v, p16uc_PSET64_HI);
|
||||
return res;
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet2cf pgather<std::complex<float>, Packet2cf>(const std::complex<float>* from, Index stride)
|
||||
{
|
||||
std::complex<float> EIGEN_ALIGN16 af[2];
|
||||
af[0] = from[0*stride];
|
||||
af[1] = from[1*stride];
|
||||
return Packet2cf(vec_ld(0, (const float*)af));
|
||||
}
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf>(std::complex<float>* to, const Packet2cf& from, Index stride)
|
||||
{
|
||||
std::complex<float> EIGEN_ALIGN16 af[2];
|
||||
vec_st(from.v, 0, (float*)af);
|
||||
@@ -95,16 +93,16 @@ template<> EIGEN_STRONG_INLINE Packet2cf pmul<Packet2cf>(const Packet2cf& a, con
|
||||
Packet4f v1, v2;
|
||||
|
||||
// Permute and multiply the real parts of a and b
|
||||
v1 = vec_perm(a.v, a.v, p16uc_COMPLEX_RE);
|
||||
v1 = vec_perm(a.v, a.v, p16uc_PSET32_WODD);
|
||||
// Get the imaginary parts of a
|
||||
v2 = vec_perm(a.v, a.v, p16uc_COMPLEX_IM);
|
||||
v2 = vec_perm(a.v, a.v, p16uc_PSET32_WEVEN);
|
||||
// multiply a_re * b
|
||||
v1 = vec_madd(v1, b.v, p4f_ZERO);
|
||||
// multiply a_im * b and get the conjugate result
|
||||
v2 = vec_madd(v2, b.v, p4f_ZERO);
|
||||
v2 = (Packet4f) vec_xor((Packet4ui)v2, p4ui_CONJ_XOR);
|
||||
// permute back to a proper order
|
||||
v2 = vec_perm(v2, v2, p16uc_COMPLEX_REV);
|
||||
v2 = vec_perm(v2, v2, p16uc_COMPLEX32_REV);
|
||||
|
||||
return Packet2cf(vec_add(v1, v2));
|
||||
}
|
||||
@@ -138,7 +136,7 @@ template<> EIGEN_STRONG_INLINE std::complex<float> pfirst<Packet2cf>(const Pack
|
||||
template<> EIGEN_STRONG_INLINE Packet2cf preverse(const Packet2cf& a)
|
||||
{
|
||||
Packet4f rev_a;
|
||||
rev_a = vec_perm(a.v, a.v, p16uc_COMPLEX_REV2);
|
||||
rev_a = vec_perm(a.v, a.v, p16uc_COMPLEX32_REV2);
|
||||
return Packet2cf(rev_a);
|
||||
}
|
||||
|
||||
@@ -153,9 +151,13 @@ template<> EIGEN_STRONG_INLINE std::complex<float> predux<Packet2cf>(const Packe
|
||||
template<> EIGEN_STRONG_INLINE Packet2cf preduxp<Packet2cf>(const Packet2cf* vecs)
|
||||
{
|
||||
Packet4f b1, b2;
|
||||
|
||||
#ifdef _BIG_ENDIAN
|
||||
b1 = (Packet4f) vec_sld(vecs[0].v, vecs[1].v, 8);
|
||||
b2 = (Packet4f) vec_sld(vecs[1].v, vecs[0].v, 8);
|
||||
#else
|
||||
b1 = (Packet4f) vec_sld(vecs[1].v, vecs[0].v, 8);
|
||||
b2 = (Packet4f) vec_sld(vecs[0].v, vecs[1].v, 8);
|
||||
#endif
|
||||
b2 = (Packet4f) vec_sld(b2, b2, 8);
|
||||
b2 = padd(b1, b2);
|
||||
|
||||
@@ -179,7 +181,11 @@ struct palign_impl<Offset,Packet2cf>
|
||||
{
|
||||
if (Offset==1)
|
||||
{
|
||||
#ifdef _BIG_ENDIAN
|
||||
first.v = vec_sld(first.v, second.v, 8);
|
||||
#else
|
||||
first.v = vec_sld(second.v, first.v, 8);
|
||||
#endif
|
||||
}
|
||||
}
|
||||
};
|
||||
@@ -222,23 +228,203 @@ template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, con
|
||||
// TODO optimize it for AltiVec
|
||||
Packet2cf res = conj_helper<Packet2cf,Packet2cf,false,true>().pmul(a,b);
|
||||
Packet4f s = vec_madd(b.v, b.v, p4f_ZERO);
|
||||
return Packet2cf(pdiv(res.v, vec_add(s,vec_perm(s, s, p16uc_COMPLEX_REV))));
|
||||
return Packet2cf(pdiv(res.v, vec_add(s,vec_perm(s, s, p16uc_COMPLEX32_REV))));
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2cf pcplxflip<Packet2cf>(const Packet2cf& x)
|
||||
{
|
||||
return Packet2cf(vec_perm(x.v, x.v, p16uc_COMPLEX_REV));
|
||||
return Packet2cf(vec_perm(x.v, x.v, p16uc_COMPLEX32_REV));
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet2cf,2>& kernel)
|
||||
{
|
||||
Packet4f tmp = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_COMPLEX_TRANSPOSE_0);
|
||||
kernel.packet[1].v = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_COMPLEX_TRANSPOSE_1);
|
||||
Packet4f tmp = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_HI);
|
||||
kernel.packet[1].v = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_LO);
|
||||
kernel.packet[0].v = tmp;
|
||||
}
|
||||
|
||||
//---------- double ----------
|
||||
#ifdef __VSX__
|
||||
struct Packet1cd
|
||||
{
|
||||
EIGEN_STRONG_INLINE Packet1cd() {}
|
||||
EIGEN_STRONG_INLINE explicit Packet1cd(const Packet2d& a) : v(a) {}
|
||||
Packet2d v;
|
||||
};
|
||||
|
||||
template<> struct packet_traits<std::complex<double> > : default_packet_traits
|
||||
{
|
||||
typedef Packet1cd type;
|
||||
typedef Packet1cd half;
|
||||
enum {
|
||||
Vectorizable = 1,
|
||||
AlignedOnScalar = 0,
|
||||
size = 1,
|
||||
HasHalfPacket = 0,
|
||||
|
||||
HasAdd = 1,
|
||||
HasSub = 1,
|
||||
HasMul = 1,
|
||||
HasDiv = 1,
|
||||
HasNegate = 1,
|
||||
HasAbs = 0,
|
||||
HasAbs2 = 0,
|
||||
HasMin = 0,
|
||||
HasMax = 0,
|
||||
HasSetLinear = 0
|
||||
};
|
||||
};
|
||||
|
||||
template<> struct unpacket_traits<Packet1cd> { typedef std::complex<double> type; enum {size=1, alignment=Aligned16}; typedef Packet1cd half; };
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd pload <Packet1cd>(const std::complex<double>* from) { EIGEN_DEBUG_ALIGNED_LOAD return Packet1cd(pload<Packet2d>((const double*)from)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd ploadu<Packet1cd>(const std::complex<double>* from) { EIGEN_DEBUG_UNALIGNED_LOAD return Packet1cd(ploadu<Packet2d>((const double*)from)); }
|
||||
template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); }
|
||||
template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd pset1<Packet1cd>(const std::complex<double>& from)
|
||||
{ /* here we really have to use unaligned loads :( */ return ploadu<Packet1cd>(&from); }
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet1cd pgather<std::complex<double>, Packet1cd>(const std::complex<double>* from, Index stride)
|
||||
{
|
||||
std::complex<double> EIGEN_ALIGN16 af[2];
|
||||
af[0] = from[0*stride];
|
||||
af[1] = from[1*stride];
|
||||
return pload<Packet1cd>(af);
|
||||
}
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<double>, Packet1cd>(std::complex<double>* to, const Packet1cd& from, Index stride)
|
||||
{
|
||||
std::complex<double> EIGEN_ALIGN16 af[2];
|
||||
pstore<std::complex<double> >(af, from);
|
||||
to[0*stride] = af[0];
|
||||
to[1*stride] = af[1];
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd padd<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_add(a.v,b.v)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd psub<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_sub(a.v,b.v)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd pnegate(const Packet1cd& a) { return Packet1cd(pnegate(Packet2d(a.v))); }
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd pconj(const Packet1cd& a) { return Packet1cd((Packet2d)vec_xor((Packet2d)a.v, (Packet2d)p2ul_CONJ_XOR2)); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd pmul<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
|
||||
{
|
||||
Packet2d a_re, a_im, v1, v2;
|
||||
|
||||
// Permute and multiply the real parts of a and b
|
||||
a_re = vec_perm(a.v, a.v, p16uc_PSET64_HI);
|
||||
// Get the imaginary parts of a
|
||||
a_im = vec_perm(a.v, a.v, p16uc_PSET64_LO);
|
||||
// multiply a_re * b
|
||||
v1 = vec_madd(a_re, b.v, p2d_ZERO);
|
||||
// multiply a_im * b and get the conjugate result
|
||||
v2 = vec_madd(a_im, b.v, p2d_ZERO);
|
||||
v2 = (Packet2d) vec_sld((Packet4ui)v2, (Packet4ui)v2, 8);
|
||||
v2 = (Packet2d) vec_xor((Packet2d)v2, (Packet2d) p2ul_CONJ_XOR1);
|
||||
|
||||
return Packet1cd(vec_add(v1, v2));
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd pand <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_and(a.v,b.v)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd por <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_or(a.v,b.v)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd pxor <Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_xor(a.v,b.v)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd pandnot<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { return Packet1cd(vec_and(a.v, vec_nor(b.v,b.v))); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex<double>* from)
|
||||
{
|
||||
return pset1<Packet1cd>(*from);
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { vec_dstt((long *)addr, DST_CTRL(2,2,32), DST_CHAN); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE std::complex<double> pfirst<Packet1cd>(const Packet1cd& a)
|
||||
{
|
||||
std::complex<double> EIGEN_ALIGN16 res[2];
|
||||
pstore<std::complex<double> >(res, a);
|
||||
|
||||
return res[0];
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd preverse(const Packet1cd& a) { return a; }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE std::complex<double> predux<Packet1cd>(const Packet1cd& a)
|
||||
{
|
||||
return pfirst(a);
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd preduxp<Packet1cd>(const Packet1cd* vecs)
|
||||
{
|
||||
return vecs[0];
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE std::complex<double> predux_mul<Packet1cd>(const Packet1cd& a)
|
||||
{
|
||||
return pfirst(a);
|
||||
}
|
||||
|
||||
template<int Offset>
|
||||
struct palign_impl<Offset,Packet1cd>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Packet1cd& /*first*/, const Packet1cd& /*second*/)
|
||||
{
|
||||
// FIXME is it sure we never have to align a Packet1cd?
|
||||
// Even though a std::complex<double> has 16 bytes, it is not necessarily aligned on a 16 bytes boundary...
|
||||
}
|
||||
};
|
||||
|
||||
template<> struct conj_helper<Packet1cd, Packet1cd, false,true>
|
||||
{
|
||||
EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
|
||||
{ return padd(pmul(x,y),c); }
|
||||
|
||||
EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
|
||||
{
|
||||
return internal::pmul(a, pconj(b));
|
||||
}
|
||||
};
|
||||
|
||||
template<> struct conj_helper<Packet1cd, Packet1cd, true,false>
|
||||
{
|
||||
EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
|
||||
{ return padd(pmul(x,y),c); }
|
||||
|
||||
EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
|
||||
{
|
||||
return internal::pmul(pconj(a), b);
|
||||
}
|
||||
};
|
||||
|
||||
template<> struct conj_helper<Packet1cd, Packet1cd, true,true>
|
||||
{
|
||||
EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet1cd& y, const Packet1cd& c) const
|
||||
{ return padd(pmul(x,y),c); }
|
||||
|
||||
EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& a, const Packet1cd& b) const
|
||||
{
|
||||
return pconj(internal::pmul(a, b));
|
||||
}
|
||||
};
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b)
|
||||
{
|
||||
// TODO optimize it for AltiVec
|
||||
Packet1cd res = conj_helper<Packet1cd,Packet1cd,false,true>().pmul(a,b);
|
||||
Packet2d s = vec_madd(b.v, b.v, p2d_ZERO_);
|
||||
return Packet1cd(pdiv(res.v, vec_add(s,vec_perm(s, s, p16uc_REVERSE64))));
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE Packet1cd pcplxflip/*<Packet1cd>*/(const Packet1cd& x)
|
||||
{
|
||||
return Packet1cd(preverse(Packet2d(x.v)));
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE void ptranspose(PacketBlock<Packet1cd,2>& kernel)
|
||||
{
|
||||
Packet2d tmp = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_HI);
|
||||
kernel.packet[1].v = vec_perm(kernel.packet[0].v, kernel.packet[1].v, p16uc_TRANSPOSE64_LO);
|
||||
kernel.packet[0].v = tmp;
|
||||
}
|
||||
#endif // __VSX__
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_COMPLEX_ALTIVEC_H
|
||||
#endif // EIGEN_COMPLEX32_ALTIVEC_H
|
||||
|
||||
290
Eigen/src/Core/arch/AltiVec/MathFunctions.h
Normal file
290
Eigen/src/Core/arch/AltiVec/MathFunctions.h
Normal file
@@ -0,0 +1,290 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2007 Julien Pommier
|
||||
// Copyright (C) 2009 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/.
|
||||
|
||||
/* The sin, cos, exp, and log functions of this file come from
|
||||
* Julien Pommier's sse math library: http://gruntthepeon.free.fr/ssemath/
|
||||
*/
|
||||
|
||||
#ifndef EIGEN_MATH_FUNCTIONS_ALTIVEC_H
|
||||
#define EIGEN_MATH_FUNCTIONS_ALTIVEC_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
|
||||
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
|
||||
Packet4f plog<Packet4f>(const Packet4f& _x)
|
||||
{
|
||||
Packet4f x = _x;
|
||||
_EIGEN_DECLARE_CONST_Packet4f(1 , 1.0f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(half, 0.5f);
|
||||
_EIGEN_DECLARE_CONST_Packet4i(0x7f, 0x7f);
|
||||
_EIGEN_DECLARE_CONST_Packet4i(23, 23);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4f_FROM_INT(inv_mant_mask, ~0x7f800000);
|
||||
|
||||
/* the smallest non denormalized float number */
|
||||
_EIGEN_DECLARE_CONST_Packet4f_FROM_INT(min_norm_pos, 0x00800000);
|
||||
_EIGEN_DECLARE_CONST_Packet4f_FROM_INT(minus_inf, 0xff800000); // -1.f/0.f
|
||||
_EIGEN_DECLARE_CONST_Packet4f_FROM_INT(minus_nan, 0xffffffff);
|
||||
|
||||
/* natural logarithm computed for 4 simultaneous float
|
||||
return NaN for x <= 0
|
||||
*/
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_SQRTHF, 0.707106781186547524f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_p0, 7.0376836292E-2f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_p1, - 1.1514610310E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_p2, 1.1676998740E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_p3, - 1.2420140846E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_p4, + 1.4249322787E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_p5, - 1.6668057665E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_p6, + 2.0000714765E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_p7, - 2.4999993993E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_p8, + 3.3333331174E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_q1, -2.12194440e-4f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_log_q2, 0.693359375f);
|
||||
|
||||
|
||||
Packet4i emm0;
|
||||
|
||||
/* isvalid_mask is 0 if x < 0 or x is NaN. */
|
||||
Packet4ui isvalid_mask = reinterpret_cast<Packet4ui>(vec_cmpge(x, p4f_ZERO));
|
||||
Packet4ui iszero_mask = reinterpret_cast<Packet4ui>(vec_cmpeq(x, p4f_ZERO));
|
||||
|
||||
x = pmax(x, p4f_min_norm_pos); /* cut off denormalized stuff */
|
||||
emm0 = vec_sr(reinterpret_cast<Packet4i>(x),
|
||||
reinterpret_cast<Packet4ui>(p4i_23));
|
||||
|
||||
/* keep only the fractional part */
|
||||
x = pand(x, p4f_inv_mant_mask);
|
||||
x = por(x, p4f_half);
|
||||
|
||||
emm0 = psub(emm0, p4i_0x7f);
|
||||
Packet4f e = padd(vec_ctf(emm0, 0), p4f_1);
|
||||
|
||||
/* part2:
|
||||
if( x < SQRTHF ) {
|
||||
e -= 1;
|
||||
x = x + x - 1.0;
|
||||
} else { x = x - 1.0; }
|
||||
*/
|
||||
Packet4f mask = reinterpret_cast<Packet4f>(vec_cmplt(x, p4f_cephes_SQRTHF));
|
||||
Packet4f tmp = pand(x, mask);
|
||||
x = psub(x, p4f_1);
|
||||
e = psub(e, pand(p4f_1, mask));
|
||||
x = padd(x, tmp);
|
||||
|
||||
Packet4f x2 = pmul(x,x);
|
||||
Packet4f x3 = pmul(x2,x);
|
||||
|
||||
Packet4f y, y1, y2;
|
||||
y = pmadd(p4f_cephes_log_p0, x, p4f_cephes_log_p1);
|
||||
y1 = pmadd(p4f_cephes_log_p3, x, p4f_cephes_log_p4);
|
||||
y2 = pmadd(p4f_cephes_log_p6, x, p4f_cephes_log_p7);
|
||||
y = pmadd(y , x, p4f_cephes_log_p2);
|
||||
y1 = pmadd(y1, x, p4f_cephes_log_p5);
|
||||
y2 = pmadd(y2, x, p4f_cephes_log_p8);
|
||||
y = pmadd(y, x3, y1);
|
||||
y = pmadd(y, x3, y2);
|
||||
y = pmul(y, x3);
|
||||
|
||||
y1 = pmul(e, p4f_cephes_log_q1);
|
||||
tmp = pmul(x2, p4f_half);
|
||||
y = padd(y, y1);
|
||||
x = psub(x, tmp);
|
||||
y2 = pmul(e, p4f_cephes_log_q2);
|
||||
x = padd(x, y);
|
||||
x = padd(x, y2);
|
||||
// negative arg will be NAN, 0 will be -INF
|
||||
x = vec_sel(x, p4f_minus_inf, iszero_mask);
|
||||
x = vec_sel(p4f_minus_nan, x, isvalid_mask);
|
||||
return x;
|
||||
}
|
||||
|
||||
template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
|
||||
Packet4f pexp<Packet4f>(const Packet4f& _x)
|
||||
{
|
||||
Packet4f x = _x;
|
||||
_EIGEN_DECLARE_CONST_Packet4f(1 , 1.0f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(half, 0.5f);
|
||||
_EIGEN_DECLARE_CONST_Packet4i(0x7f, 0x7f);
|
||||
_EIGEN_DECLARE_CONST_Packet4i(23, 23);
|
||||
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4f(exp_hi, 88.3762626647950f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(exp_lo, -88.3762626647949f);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_LOG2EF, 1.44269504088896341f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_C1, 0.693359375f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_C2, -2.12194440e-4f);
|
||||
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p0, 1.9875691500E-4f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p1, 1.3981999507E-3f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p2, 8.3334519073E-3f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p3, 4.1665795894E-2f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p4, 1.6666665459E-1f);
|
||||
_EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p5, 5.0000001201E-1f);
|
||||
|
||||
Packet4f tmp, fx;
|
||||
Packet4i emm0;
|
||||
|
||||
// clamp x
|
||||
x = vec_max(vec_min(x, p4f_exp_hi), p4f_exp_lo);
|
||||
|
||||
/* express exp(x) as exp(g + n*log(2)) */
|
||||
fx = pmadd(x, p4f_cephes_LOG2EF, p4f_half);
|
||||
|
||||
fx = vec_floor(fx);
|
||||
|
||||
tmp = pmul(fx, p4f_cephes_exp_C1);
|
||||
Packet4f z = pmul(fx, p4f_cephes_exp_C2);
|
||||
x = psub(x, tmp);
|
||||
x = psub(x, z);
|
||||
|
||||
z = pmul(x,x);
|
||||
|
||||
Packet4f y = p4f_cephes_exp_p0;
|
||||
y = pmadd(y, x, p4f_cephes_exp_p1);
|
||||
y = pmadd(y, x, p4f_cephes_exp_p2);
|
||||
y = pmadd(y, x, p4f_cephes_exp_p3);
|
||||
y = pmadd(y, x, p4f_cephes_exp_p4);
|
||||
y = pmadd(y, x, p4f_cephes_exp_p5);
|
||||
y = pmadd(y, z, x);
|
||||
y = padd(y, p4f_1);
|
||||
|
||||
// build 2^n
|
||||
emm0 = vec_cts(fx, 0);
|
||||
emm0 = vec_add(emm0, p4i_0x7f);
|
||||
emm0 = vec_sl(emm0, reinterpret_cast<Packet4ui>(p4i_23));
|
||||
|
||||
// Altivec's max & min operators just drop silent NaNs. Check NaNs in
|
||||
// inputs and return them unmodified.
|
||||
Packet4ui isnumber_mask = reinterpret_cast<Packet4ui>(vec_cmpeq(_x, _x));
|
||||
return vec_sel(_x, pmax(pmul(y, reinterpret_cast<Packet4f>(emm0)), _x),
|
||||
isnumber_mask);
|
||||
}
|
||||
|
||||
#ifdef __VSX__
|
||||
// VSX support varies between different compilers and even different
|
||||
// versions of the same compiler. For gcc version >= 4.9.3, we can use
|
||||
// vec_cts to efficiently convert Packet2d to Packet2l. Otherwise, use
|
||||
// a slow version that works with older compilers.
|
||||
static inline Packet2l ConvertToPacket2l(const Packet2d& x) {
|
||||
#if EIGEN_GNUC_AT_LEAST(5, 0) || \
|
||||
(EIGEN_GNUC_AT(4, 9) && __GNUC_PATCHLEVEL__ >= 3)
|
||||
return vec_cts(x, 0); // TODO: check clang version.
|
||||
#else
|
||||
double tmp[2];
|
||||
memcpy(tmp, &x, sizeof(tmp));
|
||||
Packet2l l = { static_cast<long long>(tmp[0]),
|
||||
static_cast<long long>(tmp[1]) };
|
||||
return l;
|
||||
#endif
|
||||
}
|
||||
|
||||
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);
|
||||
|
||||
Packet2d tmp, fx;
|
||||
Packet2l 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);
|
||||
|
||||
fx = vec_floor(fx);
|
||||
|
||||
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 = ConvertToPacket2l(fx);
|
||||
|
||||
#ifdef __POWER8_VECTOR__
|
||||
static const Packet2l p2l_1023 = { 1023, 1023 };
|
||||
static const Packet2ul p2ul_52 = { 52, 52 };
|
||||
|
||||
emm0 = vec_add(emm0, p2l_1023);
|
||||
emm0 = vec_sl(emm0, p2ul_52);
|
||||
#else
|
||||
// Code is a bit complex for POWER7. There is actually a
|
||||
// vec_xxsldi intrinsic but it is not supported by some gcc versions.
|
||||
// So we shift (52-32) bits and do a word swap with zeros.
|
||||
_EIGEN_DECLARE_CONST_Packet4i(1023, 1023);
|
||||
_EIGEN_DECLARE_CONST_Packet4i(20, 20); // 52 - 32
|
||||
|
||||
Packet4i emm04i = reinterpret_cast<Packet4i>(emm0);
|
||||
emm04i = vec_add(emm04i, p4i_1023);
|
||||
emm04i = vec_sl(emm04i, reinterpret_cast<Packet4ui>(p4i_20));
|
||||
static const Packet16uc perm = {
|
||||
0x14, 0x15, 0x16, 0x17, 0x00, 0x01, 0x02, 0x03,
|
||||
0x1c, 0x1d, 0x1e, 0x1f, 0x08, 0x09, 0x0a, 0x0b };
|
||||
#ifdef _BIG_ENDIAN
|
||||
emm0 = reinterpret_cast<Packet2l>(vec_perm(p4i_ZERO, emm04i, perm));
|
||||
#else
|
||||
emm0 = reinterpret_cast<Packet2l>(vec_perm(emm04i, p4i_ZERO, perm));
|
||||
#endif
|
||||
|
||||
#endif
|
||||
|
||||
// Altivec's max & min operators just drop silent NaNs. Check NaNs in
|
||||
// inputs and return them unmodified.
|
||||
Packet2ul isnumber_mask = reinterpret_cast<Packet2ul>(vec_cmpeq(_x, _x));
|
||||
return vec_sel(_x, pmax(pmul(x, reinterpret_cast<Packet2d>(emm0)), _x),
|
||||
isnumber_mask);
|
||||
}
|
||||
#endif
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_MATH_FUNCTIONS_ALTIVEC_H
|
||||
@@ -18,17 +18,17 @@ namespace internal {
|
||||
#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 4
|
||||
#endif
|
||||
|
||||
#ifndef EIGEN_HAS_FUSED_MADD
|
||||
#define EIGEN_HAS_FUSED_MADD 1
|
||||
#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_MADD
|
||||
#define EIGEN_HAS_SINGLE_INSTRUCTION_MADD
|
||||
#endif
|
||||
|
||||
#ifndef EIGEN_HAS_FUSE_CJMADD
|
||||
#define EIGEN_HAS_FUSE_CJMADD 1
|
||||
#ifndef EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
|
||||
#define EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD
|
||||
#endif
|
||||
|
||||
// NOTE Altivec has 32 registers, but Eigen only accepts a value of 8 or 16
|
||||
#ifndef EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS
|
||||
#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 16
|
||||
#define EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS 32
|
||||
#endif
|
||||
|
||||
typedef __vector float Packet4f;
|
||||
@@ -50,30 +50,77 @@ typedef __vector unsigned char Packet16uc;
|
||||
#define _EIGEN_DECLARE_CONST_Packet4f(NAME,X) \
|
||||
Packet4f p4f_##NAME = pset1<Packet4f>(X)
|
||||
|
||||
#define _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(NAME,X) \
|
||||
Packet4f p4f_##NAME = vreinterpretq_f32_u32(pset1<int>(X))
|
||||
|
||||
#define _EIGEN_DECLARE_CONST_Packet4i(NAME,X) \
|
||||
Packet4i p4i_##NAME = pset1<Packet4i>(X)
|
||||
|
||||
#define _EIGEN_DECLARE_CONST_Packet2d(NAME,X) \
|
||||
Packet2d p2d_##NAME = pset1<Packet2d>(X)
|
||||
|
||||
#define _EIGEN_DECLARE_CONST_Packet2l(NAME,X) \
|
||||
Packet2l p2l_##NAME = pset1<Packet2l>(X)
|
||||
|
||||
#define _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(NAME,X) \
|
||||
const Packet4f p4f_##NAME = reinterpret_cast<Packet4f>(pset1<Packet4i>(X))
|
||||
|
||||
#define DST_CHAN 1
|
||||
#define DST_CTRL(size, count, stride) (((size) << 24) | ((count) << 16) | (stride))
|
||||
|
||||
// Define global static constants:
|
||||
static Packet4f p4f_COUNTDOWN = { 0.0, 1.0, 2.0, 3.0 };
|
||||
static Packet4i p4i_COUNTDOWN = { 0, 1, 2, 3 };
|
||||
static Packet16uc p16uc_REVERSE = { 12,13,14,15, 8,9,10,11, 4,5,6,7, 0,1,2,3};
|
||||
static Packet16uc p16uc_FORWARD = vec_lvsl(0, (float*)0); //{ 0,1,2,3, 4,5,6,7, 8,9,10,11, 12,13,14,15}
|
||||
static Packet16uc p16uc_DUPLICATE = { 0,1,2,3, 0,1,2,3, 4,5,6,7, 4,5,6,7};
|
||||
|
||||
// These constants are endian-agnostic
|
||||
static _EIGEN_DECLARE_CONST_FAST_Packet4f(ZERO, 0); //{ 0.0, 0.0, 0.0, 0.0}
|
||||
static _EIGEN_DECLARE_CONST_FAST_Packet4i(ZERO, 0); //{ 0, 0, 0, 0,}
|
||||
#ifndef __VSX__
|
||||
static _EIGEN_DECLARE_CONST_FAST_Packet4i(ONE,1); //{ 1, 1, 1, 1}
|
||||
static Packet4f p4f_ONE = vec_ctf(p4i_ONE, 0); //{ 1.0, 1.0, 1.0, 1.0}
|
||||
#endif
|
||||
static _EIGEN_DECLARE_CONST_FAST_Packet4i(MINUS16,-16); //{ -16, -16, -16, -16}
|
||||
static _EIGEN_DECLARE_CONST_FAST_Packet4i(MINUS1,-1); //{ -1, -1, -1, -1}
|
||||
static Packet4f p4f_ONE = vec_ctf(p4i_ONE, 0); //{ 1.0, 1.0, 1.0, 1.0}
|
||||
static Packet4f p4f_ZERO_ = (Packet4f) vec_sl((Packet4ui)p4i_MINUS1, (Packet4ui)p4i_MINUS1); //{ 0x80000000, 0x80000000, 0x80000000, 0x80000000}
|
||||
|
||||
static Packet4f p4f_COUNTDOWN = { 0.0, 1.0, 2.0, 3.0 };
|
||||
static Packet4i p4i_COUNTDOWN = { 0, 1, 2, 3 };
|
||||
|
||||
static Packet16uc p16uc_REVERSE32 = { 12,13,14,15, 8,9,10,11, 4,5,6,7, 0,1,2,3 };
|
||||
static Packet16uc p16uc_DUPLICATE32_HI = { 0,1,2,3, 0,1,2,3, 4,5,6,7, 4,5,6,7 };
|
||||
|
||||
// Mask alignment
|
||||
#ifdef __PPC64__
|
||||
#define _EIGEN_MASK_ALIGNMENT 0xfffffffffffffff0
|
||||
#else
|
||||
#define _EIGEN_MASK_ALIGNMENT 0xfffffff0
|
||||
#endif
|
||||
|
||||
#define _EIGEN_ALIGNED_PTR(x) ((ptrdiff_t)(x) & _EIGEN_MASK_ALIGNMENT)
|
||||
|
||||
// Handle endianness properly while loading constants
|
||||
// Define global static constants:
|
||||
#ifdef _BIG_ENDIAN
|
||||
static Packet16uc p16uc_FORWARD = vec_lvsl(0, (float*)0);
|
||||
static Packet16uc p16uc_REVERSE64 = { 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
|
||||
static Packet16uc p16uc_PSET32_WODD = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 2), 8);//{ 0,1,2,3, 0,1,2,3, 8,9,10,11, 8,9,10,11 };
|
||||
static Packet16uc p16uc_PSET32_WEVEN = vec_sld(p16uc_DUPLICATE32_HI, (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 };
|
||||
static Packet16uc p16uc_HALF64_0_16 = vec_sld((Packet16uc)p4i_ZERO, vec_splat((Packet16uc) vec_abs(p4i_MINUS16), 3), 8); //{ 0,0,0,0, 0,0,0,0, 16,16,16,16, 16,16,16,16};
|
||||
#else
|
||||
static Packet16uc p16uc_FORWARD = p16uc_REVERSE32;
|
||||
static Packet16uc p16uc_REVERSE64 = { 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
|
||||
static Packet16uc p16uc_PSET32_WODD = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 1), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 0,1,2,3, 0,1,2,3, 8,9,10,11, 8,9,10,11 };
|
||||
static Packet16uc p16uc_PSET32_WEVEN = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 2), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 };
|
||||
static Packet16uc p16uc_HALF64_0_16 = vec_sld(vec_splat((Packet16uc) vec_abs(p4i_MINUS16), 0), (Packet16uc)p4i_ZERO, 8); //{ 0,0,0,0, 0,0,0,0, 16,16,16,16, 16,16,16,16};
|
||||
#endif // _BIG_ENDIAN
|
||||
|
||||
static Packet16uc p16uc_PSET64_HI = (Packet16uc) vec_mergeh((Packet4ui)p16uc_PSET32_WODD, (Packet4ui)p16uc_PSET32_WEVEN); //{ 0,1,2,3, 4,5,6,7, 0,1,2,3, 4,5,6,7 };
|
||||
static Packet16uc p16uc_PSET64_LO = (Packet16uc) vec_mergel((Packet4ui)p16uc_PSET32_WODD, (Packet4ui)p16uc_PSET32_WEVEN); //{ 8,9,10,11, 12,13,14,15, 8,9,10,11, 12,13,14,15 };
|
||||
static Packet16uc p16uc_TRANSPOSE64_HI = vec_add(p16uc_PSET64_HI, p16uc_HALF64_0_16); //{ 0,1,2,3, 4,5,6,7, 16,17,18,19, 20,21,22,23};
|
||||
static Packet16uc p16uc_TRANSPOSE64_LO = vec_add(p16uc_PSET64_LO, p16uc_HALF64_0_16); //{ 8,9,10,11, 12,13,14,15, 24,25,26,27, 28,29,30,31};
|
||||
|
||||
static Packet16uc p16uc_COMPLEX32_REV = vec_sld(p16uc_REVERSE32, p16uc_REVERSE32, 8); //{ 4,5,6,7, 0,1,2,3, 12,13,14,15, 8,9,10,11 };
|
||||
|
||||
#ifdef _BIG_ENDIAN
|
||||
static Packet16uc p16uc_COMPLEX32_REV2 = vec_sld(p16uc_FORWARD, p16uc_FORWARD, 8); //{ 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
|
||||
#else
|
||||
static Packet16uc p16uc_COMPLEX32_REV2 = vec_sld(p16uc_PSET64_HI, p16uc_PSET64_LO, 8); //{ 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 };
|
||||
#endif // _BIG_ENDIAN
|
||||
|
||||
template<> struct packet_traits<float> : default_packet_traits
|
||||
{
|
||||
typedef Packet4f type;
|
||||
@@ -88,8 +135,8 @@ template<> struct packet_traits<float> : default_packet_traits
|
||||
HasDiv = 1,
|
||||
HasSin = 0,
|
||||
HasCos = 0,
|
||||
HasLog = 0,
|
||||
HasExp = 0,
|
||||
HasLog = 1,
|
||||
HasExp = 1,
|
||||
HasSqrt = 0
|
||||
};
|
||||
};
|
||||
@@ -105,9 +152,22 @@ template<> struct packet_traits<int> : default_packet_traits
|
||||
};
|
||||
};
|
||||
|
||||
template<> struct unpacket_traits<Packet4f> { typedef float type; enum {size=4}; typedef Packet4f half; };
|
||||
template<> struct unpacket_traits<Packet4i> { typedef int type; enum {size=4}; typedef Packet4i half; };
|
||||
/*
|
||||
|
||||
template<> struct unpacket_traits<Packet4f> { typedef float type; enum {size=4, alignment=Aligned16}; typedef Packet4f half; };
|
||||
template<> struct unpacket_traits<Packet4i> { typedef int type; enum {size=4, alignment=Aligned16}; typedef Packet4i half; };
|
||||
|
||||
inline std::ostream & operator <<(std::ostream & s, const Packet16uc & v)
|
||||
{
|
||||
union {
|
||||
Packet16uc v;
|
||||
unsigned char n[16];
|
||||
} vt;
|
||||
vt.v = v;
|
||||
for (int i=0; i< 16; i++)
|
||||
s << (int)vt.n[i] << ", ";
|
||||
return s;
|
||||
}
|
||||
|
||||
inline std::ostream & operator <<(std::ostream & s, const Packet4f & v)
|
||||
{
|
||||
union {
|
||||
@@ -140,7 +200,7 @@ inline std::ostream & operator <<(std::ostream & s, const Packet4ui & v)
|
||||
s << vt.n[0] << ", " << vt.n[1] << ", " << vt.n[2] << ", " << vt.n[3];
|
||||
return s;
|
||||
}
|
||||
|
||||
/*
|
||||
inline std::ostream & operator <<(std::ostream & s, const Packetbi & v)
|
||||
{
|
||||
union {
|
||||
@@ -150,14 +210,21 @@ inline std::ostream & operator <<(std::ostream & s, const Packetbi & v)
|
||||
vt.v = v;
|
||||
s << vt.n[0] << ", " << vt.n[1] << ", " << vt.n[2] << ", " << vt.n[3];
|
||||
return s;
|
||||
}
|
||||
*/
|
||||
}*/
|
||||
|
||||
|
||||
// Need to define them first or we get specialization after instantiation errors
|
||||
template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float* from) { EIGEN_DEBUG_ALIGNED_LOAD return vec_ld(0, from); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int* from) { EIGEN_DEBUG_ALIGNED_LOAD return vec_ld(0, from); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE void pstore<float>(float* to, const Packet4f& from) { EIGEN_DEBUG_ALIGNED_STORE vec_st(from, 0, to); }
|
||||
template<> EIGEN_STRONG_INLINE void pstore<int>(int* to, const Packet4i& from) { EIGEN_DEBUG_ALIGNED_STORE vec_st(from, 0, to); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float& from) {
|
||||
// Taken from http://developer.apple.com/hardwaredrivers/ve/alignment.html
|
||||
float EIGEN_ALIGN16 af[4];
|
||||
af[0] = from;
|
||||
Packet4f vc = vec_ld(0, af);
|
||||
Packet4f vc = pload<Packet4f>(af);
|
||||
vc = vec_splat(vc, 0);
|
||||
return vc;
|
||||
}
|
||||
@@ -165,17 +232,15 @@ template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float& from) {
|
||||
template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int& from) {
|
||||
int EIGEN_ALIGN16 ai[4];
|
||||
ai[0] = from;
|
||||
Packet4i vc = vec_ld(0, ai);
|
||||
Packet4i vc = pload<Packet4i>(ai);
|
||||
vc = vec_splat(vc, 0);
|
||||
return vc;
|
||||
}
|
||||
|
||||
|
||||
template<> EIGEN_STRONG_INLINE void
|
||||
pbroadcast4<Packet4f>(const float *a,
|
||||
Packet4f& a0, Packet4f& a1, Packet4f& a2, Packet4f& a3)
|
||||
{
|
||||
a3 = vec_ld(0,a);
|
||||
a3 = pload<Packet4f>(a);
|
||||
a0 = vec_splat(a3, 0);
|
||||
a1 = vec_splat(a3, 1);
|
||||
a2 = vec_splat(a3, 2);
|
||||
@@ -185,52 +250,52 @@ template<> EIGEN_STRONG_INLINE void
|
||||
pbroadcast4<Packet4i>(const int *a,
|
||||
Packet4i& a0, Packet4i& a1, Packet4i& a2, Packet4i& a3)
|
||||
{
|
||||
a3 = vec_ld(0,a);
|
||||
a3 = pload<Packet4i>(a);
|
||||
a0 = vec_splat(a3, 0);
|
||||
a1 = vec_splat(a3, 1);
|
||||
a2 = vec_splat(a3, 2);
|
||||
a3 = vec_splat(a3, 3);
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, Index stride)
|
||||
{
|
||||
float EIGEN_ALIGN16 af[4];
|
||||
af[0] = from[0*stride];
|
||||
af[1] = from[1*stride];
|
||||
af[2] = from[2*stride];
|
||||
af[3] = from[3*stride];
|
||||
return vec_ld(0, af);
|
||||
return pload<Packet4f>(af);
|
||||
}
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet4i pgather<int, Packet4i>(const int* from, Index stride)
|
||||
{
|
||||
int EIGEN_ALIGN16 ai[4];
|
||||
ai[0] = from[0*stride];
|
||||
ai[1] = from[1*stride];
|
||||
ai[2] = from[2*stride];
|
||||
ai[3] = from[3*stride];
|
||||
return vec_ld(0, ai);
|
||||
return pload<Packet4i>(ai);
|
||||
}
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet4f>(float* to, const Packet4f& from, Index stride)
|
||||
{
|
||||
float EIGEN_ALIGN16 af[4];
|
||||
vec_st(from, 0, af);
|
||||
pstore<float>(af, from);
|
||||
to[0*stride] = af[0];
|
||||
to[1*stride] = af[1];
|
||||
to[2*stride] = af[2];
|
||||
to[3*stride] = af[3];
|
||||
}
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, DenseIndex stride)
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet4i>(int* to, const Packet4i& from, Index stride)
|
||||
{
|
||||
int EIGEN_ALIGN16 ai[4];
|
||||
vec_st(from, 0, ai);
|
||||
pstore<int>((int *)ai, from);
|
||||
to[0*stride] = ai[0];
|
||||
to[1*stride] = ai[1];
|
||||
to[2*stride] = ai[2];
|
||||
to[3*stride] = ai[3];
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet4f plset<float>(const float& a) { return vec_add(pset1<Packet4f>(a), p4f_COUNTDOWN); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i plset<int>(const int& a) { return vec_add(pset1<Packet4i>(a), p4i_COUNTDOWN); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4f plset<Packet4f>(const float& a) { return vec_add(pset1<Packet4f>(a), p4f_COUNTDOWN); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i plset<Packet4i>(const int& a) { return vec_add(pset1<Packet4i>(a), p4i_COUNTDOWN); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet4f padd<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_add(a,b); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i padd<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_add(a,b); }
|
||||
@@ -283,7 +348,8 @@ template<> EIGEN_STRONG_INLINE Packet4i pmul<Packet4i>(const Packet4i& a, const
|
||||
*/
|
||||
template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const Packet4f& b)
|
||||
{
|
||||
Packet4f t, y_0, y_1, res;
|
||||
#ifndef __VSX__ // VSX actually provides a div instruction
|
||||
Packet4f t, y_0, y_1;
|
||||
|
||||
// Altivec does not offer a divide instruction, we have to do a reciprocal approximation
|
||||
y_0 = vec_re(b);
|
||||
@@ -292,8 +358,10 @@ template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const
|
||||
t = vec_nmsub(y_0, b, p4f_ONE);
|
||||
y_1 = vec_madd(y_0, t, y_0);
|
||||
|
||||
res = vec_madd(a, y_1, p4f_ZERO);
|
||||
return res;
|
||||
return vec_madd(a, y_1, p4f_ZERO);
|
||||
#else
|
||||
return vec_div(a, b);
|
||||
#endif
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet4i pdiv<Packet4i>(const Packet4i& /*a*/, const Packet4i& /*b*/)
|
||||
@@ -311,7 +379,6 @@ template<> EIGEN_STRONG_INLINE Packet4i pmin<Packet4i>(const Packet4i& a, const
|
||||
template<> EIGEN_STRONG_INLINE Packet4f pmax<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_max(a, b); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i pmax<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_max(a, b); }
|
||||
|
||||
// Logical Operations are not supported for float, so we have to reinterpret casts using NEON intrinsics
|
||||
template<> EIGEN_STRONG_INLINE Packet4f pand<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_and(a, b); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i pand<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_and(a, b); }
|
||||
|
||||
@@ -324,13 +391,10 @@ template<> EIGEN_STRONG_INLINE Packet4i pxor<Packet4i>(const Packet4i& a, const
|
||||
template<> EIGEN_STRONG_INLINE Packet4f pandnot<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_and(a, vec_nor(b, b)); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i pandnot<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_and(a, vec_nor(b, b)); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet4f pload<Packet4f>(const float* from) { EIGEN_DEBUG_ALIGNED_LOAD return vec_ld(0, from); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i pload<Packet4i>(const int* from) { EIGEN_DEBUG_ALIGNED_LOAD return vec_ld(0, from); }
|
||||
|
||||
#ifdef _BIG_ENDIAN
|
||||
template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from)
|
||||
{
|
||||
EIGEN_DEBUG_ALIGNED_LOAD
|
||||
// Taken from http://developer.apple.com/hardwaredrivers/ve/alignment.html
|
||||
Packet16uc MSQ, LSQ;
|
||||
Packet16uc mask;
|
||||
MSQ = vec_ld(0, (unsigned char *)from); // most significant quadword
|
||||
@@ -350,25 +414,36 @@ template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int* from)
|
||||
mask = vec_lvsl(0, from); // create the permute mask
|
||||
return (Packet4i) vec_perm(MSQ, LSQ, mask); // align the data
|
||||
}
|
||||
#else
|
||||
// We also need ot redefine little endian loading of Packet4i/Packet4f using VSX
|
||||
template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int* from)
|
||||
{
|
||||
EIGEN_DEBUG_ALIGNED_LOAD
|
||||
return (Packet4i) vec_vsx_ld((long)from & 15, (const int*) _EIGEN_ALIGNED_PTR(from));
|
||||
}
|
||||
template<> EIGEN_STRONG_INLINE Packet4f ploadu<Packet4f>(const float* from)
|
||||
{
|
||||
EIGEN_DEBUG_ALIGNED_LOAD
|
||||
return (Packet4f) vec_vsx_ld((long)from & 15, (const float*) _EIGEN_ALIGNED_PTR(from));
|
||||
}
|
||||
#endif
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float* from)
|
||||
{
|
||||
Packet4f p;
|
||||
if((ptrdiff_t(from) % 16) == 0) p = pload<Packet4f>(from);
|
||||
else p = ploadu<Packet4f>(from);
|
||||
return vec_perm(p, p, p16uc_DUPLICATE);
|
||||
return vec_perm(p, p, p16uc_DUPLICATE32_HI);
|
||||
}
|
||||
template<> EIGEN_STRONG_INLINE Packet4i ploaddup<Packet4i>(const int* from)
|
||||
{
|
||||
Packet4i p;
|
||||
if((ptrdiff_t(from) % 16) == 0) p = pload<Packet4i>(from);
|
||||
else p = ploadu<Packet4i>(from);
|
||||
return vec_perm(p, p, p16uc_DUPLICATE);
|
||||
return vec_perm(p, p, p16uc_DUPLICATE32_HI);
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE void pstore<float>(float* to, const Packet4f& from) { EIGEN_DEBUG_ALIGNED_STORE vec_st(from, 0, to); }
|
||||
template<> EIGEN_STRONG_INLINE void pstore<int>(int* to, const Packet4i& from) { EIGEN_DEBUG_ALIGNED_STORE vec_st(from, 0, to); }
|
||||
|
||||
#ifdef _BIG_ENDIAN
|
||||
template<> EIGEN_STRONG_INLINE void pstoreu<float>(float* to, const Packet4f& from)
|
||||
{
|
||||
EIGEN_DEBUG_UNALIGNED_STORE
|
||||
@@ -405,15 +480,30 @@ template<> EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet4i& f
|
||||
vec_st( LSQ, 15, (unsigned char *)to ); // Store the LSQ part first
|
||||
vec_st( MSQ, 0, (unsigned char *)to ); // Store the MSQ part
|
||||
}
|
||||
#else
|
||||
// We also need ot redefine little endian loading of Packet4i/Packet4f using VSX
|
||||
template<> EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet4i& from)
|
||||
{
|
||||
EIGEN_DEBUG_ALIGNED_STORE
|
||||
vec_vsx_st(from, (long)to & 15, (int*) _EIGEN_ALIGNED_PTR(to));
|
||||
}
|
||||
template<> EIGEN_STRONG_INLINE void pstoreu<float>(float* to, const Packet4f& from)
|
||||
{
|
||||
EIGEN_DEBUG_ALIGNED_STORE
|
||||
vec_vsx_st(from, (long)to & 15, (float*) _EIGEN_ALIGNED_PTR(to));
|
||||
}
|
||||
#endif
|
||||
|
||||
#ifndef __VSX__
|
||||
template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { vec_dstt(addr, DST_CTRL(2,2,32), DST_CHAN); }
|
||||
template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { vec_dstt(addr, DST_CTRL(2,2,32), DST_CHAN); }
|
||||
#endif
|
||||
|
||||
template<> EIGEN_STRONG_INLINE float pfirst<Packet4f>(const Packet4f& a) { float EIGEN_ALIGN16 x[4]; vec_st(a, 0, x); return x[0]; }
|
||||
template<> EIGEN_STRONG_INLINE int pfirst<Packet4i>(const Packet4i& a) { int EIGEN_ALIGN16 x[4]; vec_st(a, 0, x); return x[0]; }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet4f preverse(const Packet4f& a) { return (Packet4f)vec_perm((Packet16uc)a,(Packet16uc)a, p16uc_REVERSE); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i preverse(const Packet4i& a) { return (Packet4i)vec_perm((Packet16uc)a,(Packet16uc)a, p16uc_REVERSE); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4f preverse(const Packet4f& a) { return (Packet4f)vec_perm((Packet16uc)a,(Packet16uc)a, p16uc_REVERSE32); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i preverse(const Packet4i& a) { return (Packet4i)vec_perm((Packet16uc)a,(Packet16uc)a, p16uc_REVERSE32); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet4f pabs(const Packet4f& a) { return vec_abs(a); }
|
||||
template<> EIGEN_STRONG_INLINE Packet4i pabs(const Packet4i& a) { return vec_abs(a); }
|
||||
@@ -460,7 +550,11 @@ template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
|
||||
{
|
||||
Packet4i sum;
|
||||
sum = vec_sums(a, p4i_ZERO);
|
||||
#ifdef _BIG_ENDIAN
|
||||
sum = vec_sld(sum, p4i_ZERO, 12);
|
||||
#else
|
||||
sum = vec_sld(p4i_ZERO, sum, 4);
|
||||
#endif
|
||||
return pfirst(sum);
|
||||
}
|
||||
|
||||
@@ -547,8 +641,25 @@ struct palign_impl<Offset,Packet4f>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second)
|
||||
{
|
||||
if (Offset!=0)
|
||||
first = vec_sld(first, second, Offset*4);
|
||||
#ifdef _BIG_ENDIAN
|
||||
switch (Offset % 4) {
|
||||
case 1:
|
||||
first = vec_sld(first, second, 4); break;
|
||||
case 2:
|
||||
first = vec_sld(first, second, 8); break;
|
||||
case 3:
|
||||
first = vec_sld(first, second, 12); break;
|
||||
}
|
||||
#else
|
||||
switch (Offset % 4) {
|
||||
case 1:
|
||||
first = vec_sld(second, first, 12); break;
|
||||
case 2:
|
||||
first = vec_sld(second, first, 8); break;
|
||||
case 3:
|
||||
first = vec_sld(second, first, 4); break;
|
||||
}
|
||||
#endif
|
||||
}
|
||||
};
|
||||
|
||||
@@ -557,8 +668,25 @@ struct palign_impl<Offset,Packet4i>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second)
|
||||
{
|
||||
if (Offset!=0)
|
||||
first = vec_sld(first, second, Offset*4);
|
||||
#ifdef _BIG_ENDIAN
|
||||
switch (Offset % 4) {
|
||||
case 1:
|
||||
first = vec_sld(first, second, 4); break;
|
||||
case 2:
|
||||
first = vec_sld(first, second, 8); break;
|
||||
case 3:
|
||||
first = vec_sld(first, second, 12); break;
|
||||
}
|
||||
#else
|
||||
switch (Offset % 4) {
|
||||
case 1:
|
||||
first = vec_sld(second, first, 12); break;
|
||||
case 2:
|
||||
first = vec_sld(second, first, 8); break;
|
||||
case 3:
|
||||
first = vec_sld(second, first, 4); break;
|
||||
}
|
||||
#endif
|
||||
}
|
||||
};
|
||||
|
||||
@@ -588,6 +716,222 @@ ptranspose(PacketBlock<Packet4i,4>& kernel) {
|
||||
kernel.packet[3] = vec_mergel(t1, t3);
|
||||
}
|
||||
|
||||
|
||||
//---------- double ----------
|
||||
#ifdef __VSX__
|
||||
typedef __vector double Packet2d;
|
||||
typedef __vector unsigned long long Packet2ul;
|
||||
typedef __vector long long Packet2l;
|
||||
|
||||
static Packet2l p2l_ZERO = (Packet2l) p4i_ZERO;
|
||||
static Packet2d p2d_ONE = { 1.0, 1.0 };
|
||||
static Packet2d p2d_ZERO = (Packet2d) p4f_ZERO;
|
||||
static Packet2d p2d_ZERO_ = { -0.0, -0.0 };
|
||||
|
||||
#ifdef _BIG_ENDIAN
|
||||
static Packet2d p2d_COUNTDOWN = (Packet2d) vec_sld((Packet16uc) p2d_ZERO, (Packet16uc) p2d_ONE, 8);
|
||||
#else
|
||||
static Packet2d p2d_COUNTDOWN = (Packet2d) vec_sld((Packet16uc) p2d_ONE, (Packet16uc) p2d_ZERO, 8);
|
||||
#endif
|
||||
|
||||
static EIGEN_STRONG_INLINE Packet2d vec_splat_dbl(Packet2d& a, int index)
|
||||
{
|
||||
switch (index) {
|
||||
case 0:
|
||||
return (Packet2d) vec_perm(a, a, p16uc_PSET64_HI);
|
||||
case 1:
|
||||
return (Packet2d) vec_perm(a, a, p16uc_PSET64_LO);
|
||||
}
|
||||
return a;
|
||||
}
|
||||
|
||||
template<> struct packet_traits<double> : default_packet_traits
|
||||
{
|
||||
typedef Packet2d type;
|
||||
typedef Packet2d half;
|
||||
enum {
|
||||
Vectorizable = 1,
|
||||
AlignedOnScalar = 1,
|
||||
size=2,
|
||||
HasHalfPacket = 0,
|
||||
|
||||
HasDiv = 1,
|
||||
HasExp = 1,
|
||||
HasSqrt = 0
|
||||
};
|
||||
};
|
||||
|
||||
template<> struct unpacket_traits<Packet2d> { typedef double type; enum {size=2, alignment=Aligned16}; typedef Packet2d half; };
|
||||
|
||||
|
||||
inline std::ostream & operator <<(std::ostream & s, const Packet2d & v)
|
||||
{
|
||||
union {
|
||||
Packet2d v;
|
||||
double n[2];
|
||||
} vt;
|
||||
vt.v = v;
|
||||
s << vt.n[0] << ", " << vt.n[1];
|
||||
return s;
|
||||
}
|
||||
|
||||
// Need to define them first or we get specialization after instantiation errors
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pload<Packet2d>(const double* from) { EIGEN_DEBUG_ALIGNED_LOAD return (Packet2d) vec_ld(0, (const float *) from); } //FIXME
|
||||
|
||||
template<> EIGEN_STRONG_INLINE void pstore<double>(double* to, const Packet2d& from) { EIGEN_DEBUG_ALIGNED_STORE vec_st((Packet4f)from, 0, (float *)to); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pset1<Packet2d>(const double& from) {
|
||||
double EIGEN_ALIGN16 af[2];
|
||||
af[0] = from;
|
||||
Packet2d vc = pload<Packet2d>(af);
|
||||
vc = vec_splat_dbl(vc, 0);
|
||||
return vc;
|
||||
}
|
||||
template<> EIGEN_STRONG_INLINE void
|
||||
pbroadcast4<Packet2d>(const double *a,
|
||||
Packet2d& a0, Packet2d& a1, Packet2d& a2, Packet2d& a3)
|
||||
{
|
||||
a1 = pload<Packet2d>(a);
|
||||
a0 = vec_splat_dbl(a1, 0);
|
||||
a1 = vec_splat_dbl(a1, 1);
|
||||
a3 = pload<Packet2d>(a+2);
|
||||
a2 = vec_splat_dbl(a3, 0);
|
||||
a3 = vec_splat_dbl(a3, 1);
|
||||
}
|
||||
template<> EIGEN_DEVICE_FUNC inline Packet2d pgather<double, Packet2d>(const double* from, Index stride)
|
||||
{
|
||||
double EIGEN_ALIGN16 af[2];
|
||||
af[0] = from[0*stride];
|
||||
af[1] = from[1*stride];
|
||||
return pload<Packet2d>(af);
|
||||
}
|
||||
template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet2d>(double* to, const Packet2d& from, Index stride)
|
||||
{
|
||||
double EIGEN_ALIGN16 af[2];
|
||||
pstore<double>(af, from);
|
||||
to[0*stride] = af[0];
|
||||
to[1*stride] = af[1];
|
||||
}
|
||||
template<> EIGEN_STRONG_INLINE Packet2d plset<Packet2d>(const double& a) { return vec_add(pset1<Packet2d>(a), p2d_COUNTDOWN); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d padd<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_add(a,b); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d psub<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_sub(a,b); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pnegate(const Packet2d& a) { return psub<Packet2d>(p2d_ZERO, a); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pconj(const Packet2d& a) { return a; }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pmul<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_madd(a,b,p2d_ZERO); }
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_div(a,b); }
|
||||
|
||||
// for some weird raisons, it has to be overloaded for packet of integers
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return vec_madd(a, b, c); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_min(a, b); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pmax<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_max(a, b); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pand<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, b); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d por<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_or(a, b); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pxor<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_xor(a, b); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pandnot<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, vec_nor(b, b)); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d ploadu<Packet2d>(const double* from)
|
||||
{
|
||||
EIGEN_DEBUG_ALIGNED_LOAD
|
||||
return (Packet2d) vec_vsx_ld((long)from & 15, (const float*) _EIGEN_ALIGNED_PTR(from));
|
||||
}
|
||||
template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double* from)
|
||||
{
|
||||
Packet2d p;
|
||||
if((ptrdiff_t(from) % 16) == 0) p = pload<Packet2d>(from);
|
||||
else p = ploadu<Packet2d>(from);
|
||||
return vec_perm(p, p, p16uc_PSET64_HI);
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const Packet2d& from)
|
||||
{
|
||||
EIGEN_DEBUG_ALIGNED_STORE
|
||||
vec_vsx_st((Packet4f)from, (long)to & 15, (float*) _EIGEN_ALIGNED_PTR(to));
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { vec_dstt((const float *) addr, DST_CTRL(2,2,32), DST_CHAN); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE double pfirst<Packet2d>(const Packet2d& a) { double EIGEN_ALIGN16 x[2]; pstore(x, a); return x[0]; }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d preverse(const Packet2d& a) { return (Packet2d)vec_perm((Packet16uc)a,(Packet16uc)a, p16uc_REVERSE64); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d pabs(const Packet2d& a) { return vec_abs(a); }
|
||||
|
||||
template<> EIGEN_STRONG_INLINE double predux<Packet2d>(const Packet2d& a)
|
||||
{
|
||||
Packet2d b, sum;
|
||||
b = (Packet2d) vec_sld((Packet4ui) a, (Packet4ui)a, 8);
|
||||
sum = vec_add(a, b);
|
||||
return pfirst(sum);
|
||||
}
|
||||
|
||||
template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs)
|
||||
{
|
||||
Packet2d v[2], sum;
|
||||
v[0] = vec_add(vecs[0], (Packet2d) vec_sld((Packet4ui) vecs[0], (Packet4ui) vecs[0], 8));
|
||||
v[1] = vec_add(vecs[1], (Packet2d) vec_sld((Packet4ui) vecs[1], (Packet4ui) vecs[1], 8));
|
||||
|
||||
#ifdef _BIG_ENDIAN
|
||||
sum = (Packet2d) vec_sld((Packet4ui) v[0], (Packet4ui) v[1], 8);
|
||||
#else
|
||||
sum = (Packet2d) vec_sld((Packet4ui) v[1], (Packet4ui) v[0], 8);
|
||||
#endif
|
||||
|
||||
return sum;
|
||||
}
|
||||
// Other reduction functions:
|
||||
// mul
|
||||
template<> EIGEN_STRONG_INLINE double predux_mul<Packet2d>(const Packet2d& a)
|
||||
{
|
||||
return pfirst(pmul(a, (Packet2d)vec_sld((Packet4ui) a, (Packet4ui) a, 8)));
|
||||
}
|
||||
|
||||
// min
|
||||
template<> EIGEN_STRONG_INLINE double predux_min<Packet2d>(const Packet2d& a)
|
||||
{
|
||||
return pfirst(vec_min(a, (Packet2d) vec_sld((Packet4ui) a, (Packet4ui) a, 8)));
|
||||
}
|
||||
|
||||
// max
|
||||
template<> EIGEN_STRONG_INLINE double predux_max<Packet2d>(const Packet2d& a)
|
||||
{
|
||||
return pfirst(vec_max(a, (Packet2d) vec_sld((Packet4ui) a, (Packet4ui) a, 8)));
|
||||
}
|
||||
|
||||
template<int Offset>
|
||||
struct palign_impl<Offset,Packet2d>
|
||||
{
|
||||
static EIGEN_STRONG_INLINE void run(Packet2d& first, const Packet2d& second)
|
||||
{
|
||||
if (Offset == 1)
|
||||
#ifdef _BIG_ENDIAN
|
||||
first = (Packet2d) vec_sld((Packet4ui) first, (Packet4ui) second, 8);
|
||||
#else
|
||||
first = (Packet2d) vec_sld((Packet4ui) second, (Packet4ui) first, 8);
|
||||
#endif
|
||||
}
|
||||
};
|
||||
|
||||
EIGEN_DEVICE_FUNC inline void
|
||||
ptranspose(PacketBlock<Packet2d,2>& kernel) {
|
||||
Packet2d t0, t1;
|
||||
t0 = vec_perm(kernel.packet[0], kernel.packet[1], p16uc_TRANSPOSE64_HI);
|
||||
t1 = vec_perm(kernel.packet[0], kernel.packet[1], p16uc_TRANSPOSE64_LO);
|
||||
kernel.packet[0] = t0;
|
||||
kernel.packet[1] = t1;
|
||||
}
|
||||
|
||||
#endif // __VSX__
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
@@ -1,5 +1,9 @@
|
||||
ADD_SUBDIRECTORY(SSE)
|
||||
ADD_SUBDIRECTORY(AltiVec)
|
||||
ADD_SUBDIRECTORY(NEON)
|
||||
ADD_SUBDIRECTORY(AVX)
|
||||
ADD_SUBDIRECTORY(CUDA)
|
||||
ADD_SUBDIRECTORY(Default)
|
||||
ADD_SUBDIRECTORY(NEON)
|
||||
ADD_SUBDIRECTORY(SSE)
|
||||
|
||||
|
||||
|
||||
|
||||
6
Eigen/src/Core/arch/CUDA/CMakeLists.txt
Normal file
6
Eigen/src/Core/arch/CUDA/CMakeLists.txt
Normal file
@@ -0,0 +1,6 @@
|
||||
FILE(GLOB Eigen_Core_arch_CUDA_SRCS "*.h")
|
||||
|
||||
INSTALL(FILES
|
||||
${Eigen_Core_arch_CUDA_SRCS}
|
||||
DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core/arch/CUDA COMPONENT Devel
|
||||
)
|
||||
75
Eigen/src/Core/arch/CUDA/MathFunctions.h
Normal file
75
Eigen/src/Core/arch/CUDA/MathFunctions.h
Normal file
@@ -0,0 +1,75 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
|
||||
//
|
||||
// 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_MATH_FUNCTIONS_CUDA_H
|
||||
#define EIGEN_MATH_FUNCTIONS_CUDA_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
|
||||
// Make sure this is only available when targeting a GPU: we don't want to
|
||||
// introduce conflicts between these packet_traits definitions and the ones
|
||||
// we'll use on the host side (SSE, AVX, ...)
|
||||
#if defined(__CUDACC__) && defined(EIGEN_USE_GPU)
|
||||
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
float4 plog<float4>(const float4& a)
|
||||
{
|
||||
return make_float4(logf(a.x), logf(a.y), logf(a.z), logf(a.w));
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
double2 plog<double2>(const double2& a)
|
||||
{
|
||||
return make_double2(log(a.x), log(a.y));
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
float4 pexp<float4>(const float4& a)
|
||||
{
|
||||
return make_float4(expf(a.x), expf(a.y), expf(a.z), expf(a.w));
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
double2 pexp<double2>(const double2& a)
|
||||
{
|
||||
return make_double2(exp(a.x), exp(a.y));
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
float4 psqrt<float4>(const float4& a)
|
||||
{
|
||||
return make_float4(sqrtf(a.x), sqrtf(a.y), sqrtf(a.z), sqrtf(a.w));
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
double2 psqrt<double2>(const double2& a)
|
||||
{
|
||||
return make_double2(sqrt(a.x), sqrt(a.y));
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
float4 prsqrt<float4>(const float4& a)
|
||||
{
|
||||
return make_float4(rsqrtf(a.x), rsqrtf(a.y), rsqrtf(a.z), rsqrtf(a.w));
|
||||
}
|
||||
|
||||
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
|
||||
double2 prsqrt<double2>(const double2& a)
|
||||
{
|
||||
return make_double2(rsqrt(a.x), rsqrt(a.y));
|
||||
}
|
||||
|
||||
#endif
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_MATH_FUNCTIONS_CUDA_H
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user