Merge branch 'develop' into feature/LPSolver

Conflicts:
	gtsam_unstable/linear/QPSolver.h

.gitignore

@@ -1,4 +1,5 @@
 /build*
+.idea
 *.pyc
 *.DS_Store
 /examples/Data/dubrovnik-3-7-pre-rewritten.txt

.settings/.gitignore

@@ -0,0 +1 @@
+/org.eclipse.cdt.codan.core.prefs

CMakeLists.txt

@@ -131,7 +131,7 @@ endif()
 
 if(NOT (${Boost_VERSION} LESS 105600))
 	message("Ignoring Boost restriction on optional lvalue assignment from rvalues")
-	add_definitions(-DBOOST_OPTIONAL_ALLOW_BINDING_TO_RVALUES)
+	add_definitions(-DBOOST_OPTIONAL_ALLOW_BINDING_TO_RVALUES -DBOOST_OPTIONAL_CONFIG_ALLOW_BINDING_TO_RVALUES)
 endif()
 
 ###############################################################################
@@ -158,6 +158,12 @@ else()
 	set(GTSAM_USE_TBB 0)  # This will go into config.h
 endif()
 
+###############################################################################
+# Prohibit Timing build mode in combination with TBB
+if(GTSAM_USE_TBB AND (CMAKE_BUILD_TYPE  STREQUAL "Timing"))
+      message(FATAL_ERROR "Timing build mode cannot be used together with TBB. Use a sampling profiler such as Instruments or Intel VTune Amplifier instead.")
+endif()
+
 
 ###############################################################################
 # Find Google perftools
@@ -173,6 +179,11 @@ if(MKL_FOUND AND GTSAM_WITH_EIGEN_MKL)
     set(EIGEN_USE_MKL_ALL 1) # This will go into config.h - it makes Eigen use MKL
     include_directories(${MKL_INCLUDE_DIR})
     list(APPEND GTSAM_ADDITIONAL_LIBRARIES ${MKL_LIBRARIES})
+    
+    # --no-as-needed is required with gcc according to the MKL link advisor
+    if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
+        set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -Wl,--no-as-needed")  
+    endif()
 else()
     set(GTSAM_USE_EIGEN_MKL 0)
     set(EIGEN_USE_MKL_ALL 0)
@@ -192,36 +203,40 @@ endif()
 
 ###############################################################################
 # Option for using system Eigen or GTSAM-bundled Eigen
-### Disabled until our patches are included in Eigen ###
+### These patches only affect usage of MKL. If you want to enable MKL, you *must*
+### use our patched version of Eigen
 ### See:  http://eigen.tuxfamily.org/bz/show_bug.cgi?id=704 (Householder QR MKL selection)
 ###       http://eigen.tuxfamily.org/bz/show_bug.cgi?id=705 (Fix MKL LLT return code)
-###       http://eigen.tuxfamily.org/bz/show_bug.cgi?id=716 (Improved comma initialization)
+option(GTSAM_USE_SYSTEM_EIGEN "Find and use system-installed Eigen. If 'off', use the one bundled with GTSAM" OFF)
-# option(GTSAM_USE_SYSTEM_EIGEN "Find and use system-installed Eigen. If 'off', use the one bundled with GTSAM" OFF)
-set(GTSAM_USE_SYSTEM_EIGEN OFF)
 
 # Switch for using system Eigen or GTSAM-bundled Eigen
 if(GTSAM_USE_SYSTEM_EIGEN)
-	# Use generic Eigen include paths e.g. <Eigen/Core>
-	set(GTSAM_EIGEN_INCLUDE_PREFIX "")
-
 	find_package(Eigen3 REQUIRED)
 	include_directories(AFTER "${EIGEN3_INCLUDE_DIR}")
+	
+	# Use generic Eigen include paths e.g. <Eigen/Core>
+    set(GTSAM_EIGEN_INCLUDE_PREFIX "${EIGEN3_INCLUDE_DIR}")
+	
+	# check if MKL is also enabled - can have one or the other, but not both!
+	if(EIGEN_USE_MKL_ALL)
+	  message(FATAL_ERROR "MKL cannot be used together with system-installed Eigen, as MKL support relies on patches which are not yet in the system-installed Eigen. Disable either GTSAM_USE_SYSTEM_EIGEN or GTSAM_WITH_EIGEN_MKL")
+	endif()
 else()
-	# Use bundled Eigen include paths e.g. <gtsam/3rdparty/Eigen/Eigen/Core>
+	# Use bundled Eigen include path. 
-	set(GTSAM_EIGEN_INCLUDE_PREFIX "gtsam/3rdparty/Eigen/")
-
 	# Clear any variables set by FindEigen3
 	if(EIGEN3_INCLUDE_DIR)
 		set(EIGEN3_INCLUDE_DIR NOTFOUND CACHE STRING "" FORCE)
 	endif()
+	# Add the bundled version of eigen to the include path so that it can still be included
+	# with  #include <Eigen/Core>
+	include_directories(BEFORE "gtsam/3rdparty/Eigen/")
+	
+	# set full path to be used by external projects
+	# this will be added to GTSAM_INCLUDE_DIR by gtsam_extra.cmake.in
+	set(GTSAM_EIGEN_INCLUDE_PREFIX "${CMAKE_INSTALL_PREFIX}/include/gtsam/3rdparty/Eigen/")
+	
 endif()
 
-# Write Eigen include file with the paths for either the system Eigen or the GTSAM-bundled Eigen
-configure_file(gtsam/3rdparty/gtsam_eigen_includes.h.in gtsam/3rdparty/gtsam_eigen_includes.h)
-
-# Install the configuration file for Eigen
-install(FILES ${PROJECT_BINARY_DIR}/gtsam/3rdparty/gtsam_eigen_includes.h DESTINATION include/gtsam/3rdparty)
-
 ###############################################################################
 # Global compile options
 
@@ -262,7 +277,8 @@ endif()
 
 # Include boost - use 'BEFORE' so that a specific boost specified to CMake
 # takes precedence over a system-installed one.
-include_directories(BEFORE ${Boost_INCLUDE_DIR})
+# Use 'SYSTEM' to ignore compiler warnings in Boost headers
+include_directories(BEFORE SYSTEM ${Boost_INCLUDE_DIR})
 
 # Add includes for source directories 'BEFORE' boost and any system include
 # paths so that the compiler uses GTSAM headers in our source directory instead
@@ -289,6 +305,13 @@ if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
   endif()
 endif()
 
+# As of XCode 7, clang also complains about this
+if(CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
+  if (NOT CMAKE_CXX_COMPILER_VERSION VERSION_LESS 7.0)
+    add_definitions(-Wno-unused-local-typedefs)
+  endif()
+endif()
+
 if(GTSAM_ENABLE_CONSISTENCY_CHECKS)
   add_definitions(-DGTSAM_EXTRA_CONSISTENCY_CHECKS)
 endif()
@@ -371,6 +394,8 @@ set(CPACK_DEBIAN_PACKAGE_DEPENDS "libboost-dev (>= 1.43)") #Example: "libc6 (>=
 # Print configuration variables
 message(STATUS "===============================================================")
 message(STATUS "================  Configuration Options  ======================")
+message(STATUS "  CMAKE_CXX_COMPILER_ID type     : ${CMAKE_CXX_COMPILER_ID}")
+message(STATUS "  CMAKE_CXX_COMPILER_VERSION     : ${CMAKE_CXX_COMPILER_VERSION}")
 message(STATUS "Build flags                                               ")
 print_config_flag(${GTSAM_BUILD_TESTS}                 "Build Tests                    ")
 print_config_flag(${GTSAM_BUILD_EXAMPLES_ALWAYS}       "Build examples with 'make all' ")
@@ -389,6 +414,11 @@ if(NOT MSVC AND NOT XCODE_VERSION)
     message(STATUS "  C compilation flags            : ${CMAKE_C_FLAGS} ${CMAKE_C_FLAGS_${cmake_build_type_toupper}}")
     message(STATUS "  C++ compilation flags          : ${CMAKE_CXX_FLAGS} ${CMAKE_CXX_FLAGS_${cmake_build_type_toupper}}")
 endif()
+if(GTSAM_USE_SYSTEM_EIGEN)
+    message(STATUS "  Use System Eigen               : Yes")
+else()
+    message(STATUS "  Use System Eigen               : No")
+endif()
 if(GTSAM_USE_TBB)
 	message(STATUS "  Use Intel TBB                  : Yes")
 elseif(TBB_FOUND)

README.md

@@ -31,6 +31,7 @@ Prerequisites:
 
 - [Boost](http://www.boost.org/users/download/) >= 1.43 (Ubuntu: `sudo apt-get install libboost-all-dev`)
 - [CMake](http://www.cmake.org/cmake/resources/software.html) >= 2.6 (Ubuntu: `sudo apt-get install cmake`)
+- A modern compiler, i.e., at least gcc 4.7.3 on Linux.
 
 Optional prerequisites - used automatically if findable by CMake:
 
@@ -46,6 +47,6 @@ See the [`INSTALL`](INSTALL) file for more detailed installation instructions.
 
 GTSAM is open source under the BSD license, see the [`LICENSE`](LICENSE) and [`LICENSE.BSD`](LICENSE.BSD) files.
 
-Please see the [`examples/`](examples) directory and the [`USAGE`](USAGE.md) file for examples on how to use GTSAM.
+Please see the [`examples/`](examples) directory and the [`USAGE`](USAGE.md) file for examples on how to use GTSAM.
-
+
 GTSAM was developed in the lab of [Frank Dellaert](http://www.cc.gatech.edu/~dellaert) at the [Georgia Institute of Technology](http://www.gatech.edu), with the help of many contributors over the years, see [THANKS](THANKS).

cmake/GtsamBuildTypes.cmake

@@ -34,30 +34,31 @@ if(NOT FIRST_PASS_DONE)
     set(CMAKE_MODULE_LINKER_FLAGS_PROFILING "${CMAKE_MODULE_LINKER_FLAGS_RELEASE}" CACHE STRING "Linker flags during profiling builds." FORCE)
     mark_as_advanced(CMAKE_C_FLAGS_PROFILING CMAKE_CXX_FLAGS_PROFILING CMAKE_EXE_LINKER_FLAGS_PROFILING CMAKE_SHARED_LINKER_FLAGS_PROFILING CMAKE_MODULE_LINKER_FLAGS_PROFILING)
   else()
-    set(CMAKE_C_FLAGS_DEBUG            "${CMAKE_C_FLAGS_DEBUG} -fno-inline -Wall -DEIGEN_INITIALIZE_MATRICES_BY_NAN" CACHE STRING "Flags used by the compiler during debug builds." FORCE)
+    set(CMAKE_C_FLAGS_DEBUG            "${CMAKE_C_FLAGS_DEBUG} -std=c11 -fno-inline -Wall -DEIGEN_INITIALIZE_MATRICES_BY_NAN" CACHE STRING "Flags used by the compiler during debug builds." FORCE)
-    set(CMAKE_CXX_FLAGS_DEBUG          "${CMAKE_CXX_FLAGS_DEBUG} -fno-inline -Wall -DEIGEN_INITIALIZE_MATRICES_BY_NAN" CACHE STRING "Flags used by the compiler during debug builds." FORCE)
+    set(CMAKE_CXX_FLAGS_DEBUG          "${CMAKE_CXX_FLAGS_DEBUG} -std=c++11 -fno-inline -Wall -DEIGEN_INITIALIZE_MATRICES_BY_NAN" CACHE STRING "Flags used by the compiler during debug builds." FORCE)
-    set(CMAKE_C_FLAGS_RELWITHDEBINFO   "-g -O3 -Wall -DNDEBUG" CACHE STRING "Flags used by the compiler during relwithdebinfo builds." FORCE)
+    set(CMAKE_C_FLAGS_RELWITHDEBINFO   "-std=c11 -g -O3 -Wall -DNDEBUG" CACHE STRING "Flags used by the compiler during relwithdebinfo builds." FORCE)
-    set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "-g -O3 -Wall -DNDEBUG" CACHE STRING "Flags used by the compiler during relwithdebinfo builds." FORCE)
+    set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "-std=c++11 -g -O3 -Wall -DNDEBUG" CACHE STRING "Flags used by the compiler during relwithdebinfo builds." FORCE)
-    set(CMAKE_C_FLAGS_RELEASE          "-O3 -Wall -DNDEBUG -Wall" CACHE STRING "Flags used by the compiler during release builds." FORCE)
+    set(CMAKE_C_FLAGS_RELEASE          "-std=c11 -O3 -Wall -DNDEBUG -Wall" CACHE STRING "Flags used by the compiler during release builds." FORCE)
-    set(CMAKE_CXX_FLAGS_RELEASE        "-O3 -Wall -DNDEBUG -Wall" CACHE STRING "Flags used by the compiler during release builds." FORCE)
+    set(CMAKE_CXX_FLAGS_RELEASE        "-std=c++11 -O3 -Wall -DNDEBUG -Wall" CACHE STRING "Flags used by the compiler during release builds." FORCE)
     set(CMAKE_C_FLAGS_TIMING           "${CMAKE_C_FLAGS_RELEASE} -DENABLE_TIMING" CACHE STRING "Flags used by the compiler during timing builds." FORCE)
     set(CMAKE_CXX_FLAGS_TIMING         "${CMAKE_CXX_FLAGS_RELEASE} -DENABLE_TIMING" CACHE STRING "Flags used by the compiler during timing builds." FORCE)
     set(CMAKE_EXE_LINKER_FLAGS_TIMING  "${CMAKE_EXE_LINKER_FLAGS_RELEASE}" CACHE STRING "Linker flags during timing builds." FORCE)
     set(CMAKE_SHARED_LINKER_FLAGS_TIMING  "${CMAKE_EXE_LINKER_FLAGS_RELEASE}" CACHE STRING "Linker flags during timing builds." FORCE)
     mark_as_advanced(CMAKE_C_FLAGS_TIMING CMAKE_CXX_FLAGS_TIMING CMAKE_EXE_LINKER_FLAGS_TIMING CMAKE_SHARED_LINKER_FLAGS_TIMING)
-    set(CMAKE_C_FLAGS_PROFILING        "-g -O3 -Wall -DNDEBUG" CACHE STRING "Flags used by the compiler during profiling builds." FORCE)
+    set(CMAKE_C_FLAGS_PROFILING        "-std=c11 -g -O3 -Wall -DNDEBUG" CACHE STRING "Flags used by the compiler during profiling builds." FORCE)
-    set(CMAKE_CXX_FLAGS_PROFILING      "-g -O3 -Wall -DNDEBUG" CACHE STRING "Flags used by the compiler during profiling builds." FORCE)
+    set(CMAKE_CXX_FLAGS_PROFILING      "-std=c++11 -g -O3 -Wall -DNDEBUG" CACHE STRING "Flags used by the compiler during profiling builds." FORCE)
     set(CMAKE_EXE_LINKER_FLAGS_PROFILING "${CMAKE_EXE_LINKER_FLAGS_RELEASE}" CACHE STRING "Linker flags during profiling builds." FORCE)
 	set(CMAKE_SHARED_LINKER_FLAGS_PROFILING "${CMAKE__LINKER_FLAGS_RELEASE}" CACHE STRING "Linker flags during profiling builds." FORCE)
     mark_as_advanced(CMAKE_C_FLAGS_PROFILING CMAKE_CXX_FLAGS_PROFILING CMAKE_EXE_LINKER_FLAGS_PROFILING CMAKE_SHARED_LINKER_FLAGS_PROFILING)
   endif()
 endif()
 
-# Clang on Mac uses a template depth that is less than standard and is too small
+# Clang uses a template depth that is less than standard and is too small
 if(${CMAKE_CXX_COMPILER_ID} STREQUAL "Clang")
-	if(NOT "${CMAKE_CXX_COMPILER_VERSION}" VERSION_LESS "5.0")
+    # Apple Clang before 5.0 does not support -ftemplate-depth.
-		set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -ftemplate-depth=1024")
+    if(NOT (APPLE AND "${CMAKE_CXX_COMPILER_VERSION}" VERSION_LESS "5.0"))
-	endif()
+        set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -ftemplate-depth=1024")
+    endif()
 endif()
 
 # Set up build type library postfixes
@@ -97,7 +98,8 @@ if(    NOT cmake_build_type_tolower STREQUAL ""
    AND NOT cmake_build_type_tolower STREQUAL "release"
    AND NOT cmake_build_type_tolower STREQUAL "timing"
    AND NOT cmake_build_type_tolower STREQUAL "profiling"
-   AND NOT cmake_build_type_tolower STREQUAL "relwithdebinfo")
+   AND NOT cmake_build_type_tolower STREQUAL "relwithdebinfo"
+   AND NOT cmake_build_type_tolower STREQUAL "minsizerel")
   message(FATAL_ERROR "Unknown build type \"${CMAKE_BUILD_TYPE}\". Allowed values are None, Debug, Release, Timing, Profiling, RelWithDebInfo (case-insensitive).")
 endif()
 

cmake/GtsamMatlabWrap.cmake

@@ -270,7 +270,7 @@ function(install_wrapped_library_internal interfaceHeader)
 	if(GTSAM_BUILD_TYPE_POSTFIXES)
 		foreach(build_type ${CMAKE_CONFIGURATION_TYPES})
 			string(TOUPPER "${build_type}" build_type_upper)
-			if("${build_type_upper}" STREQUAL "RELEASE")
+			if(${build_type_upper} STREQUAL "RELEASE")
 				set(build_type_tag "") # Don't create release mode tag on installed directory
 			else()
 				set(build_type_tag "${build_type}")
@@ -367,13 +367,18 @@ endfunction()
 # should be installed to all build type toolboxes
 function(install_matlab_scripts source_directory patterns)
 	set(patterns_args "")
+	set(exclude_patterns "")
+	if(NOT GTSAM_WRAP_SERIALIZATION)
+	    set(exclude_patterns "testSerialization.m")
+	endif()
+
 	foreach(pattern ${patterns})
 		list(APPEND patterns_args PATTERN "${pattern}")
 	endforeach()
 	if(GTSAM_BUILD_TYPE_POSTFIXES)
 		foreach(build_type ${CMAKE_CONFIGURATION_TYPES})
 			string(TOUPPER "${build_type}" build_type_upper)
-			if("${build_type_upper}" STREQUAL "RELEASE")
+			if(${build_type_upper} STREQUAL "RELEASE")
 				set(build_type_tag "") # Don't create release mode tag on installed directory
 			else()
 				set(build_type_tag "${build_type}")
@@ -381,10 +386,10 @@ function(install_matlab_scripts source_directory patterns)
 			# Split up filename to strip trailing '/' in GTSAM_TOOLBOX_INSTALL_PATH if there is one
 			get_filename_component(location "${GTSAM_TOOLBOX_INSTALL_PATH}" PATH)
 			get_filename_component(name "${GTSAM_TOOLBOX_INSTALL_PATH}" NAME)
-			install(DIRECTORY "${source_directory}" DESTINATION "${location}/${name}${build_type_tag}" CONFIGURATIONS "${build_type}" FILES_MATCHING ${patterns_args} PATTERN ".svn" EXCLUDE)
+			install(DIRECTORY "${source_directory}" DESTINATION "${location}/${name}${build_type_tag}" CONFIGURATIONS "${build_type}" FILES_MATCHING ${patterns_args} PATTERN "${exclude_patterns}" EXCLUDE)
 		endforeach()
 	else()
-		install(DIRECTORY "${source_directory}" DESTINATION "${GTSAM_TOOLBOX_INSTALL_PATH}" FILES_MATCHING ${patterns_args} PATTERN ".svn" EXCLUDE)
+		install(DIRECTORY "${source_directory}" DESTINATION "${GTSAM_TOOLBOX_INSTALL_PATH}" FILES_MATCHING ${patterns_args} PATTERN "${exclude_patterns}" EXCLUDE)
 	endif()
 
 endfunction()

cmake/GtsamTesting.cmake

@@ -195,7 +195,9 @@ macro(gtsamAddTestsGlob_impl groupName globPatterns excludedFiles linkLibraries)
 			add_test(NAME ${target_name} COMMAND ${target_name})
 			add_dependencies(check.${groupName} ${target_name})
 			add_dependencies(check ${target_name})
-			add_dependencies(all.tests ${script_name})
+			if(NOT XCODE_VERSION)
+				add_dependencies(all.tests ${script_name})
+			endif()
 		
 			# Add TOPSRCDIR
 			set_property(SOURCE ${script_srcs} APPEND PROPERTY COMPILE_DEFINITIONS "TOPSRCDIR=\"${PROJECT_SOURCE_DIR}\"")

doc/.gitignore

@@ -0,0 +1,3 @@
+/html/
+*.lyx~
+*.bib~

examples/Data/.gitignore

@@ -0,0 +1 @@
+*.txt

examples/PlanarSLAMExample.cpp

@@ -42,7 +42,7 @@
 // Also, we will initialize the robot at the origin using a Prior factor.
 #include <gtsam/slam/PriorFactor.h>
 #include <gtsam/slam/BetweenFactor.h>
-#include <gtsam/slam/BearingRangeFactor.h>
+#include <gtsam/sam/BearingRangeFactor.h>
 
 // When the factors are created, we will add them to a Factor Graph. As the factors we are using
 // are nonlinear factors, we will need a Nonlinear Factor Graph.

examples/Pose2SLAMExampleExpressions.cpp

@@ -14,20 +14,18 @@
  * @brief Expressions version of Pose2SLAMExample.cpp
  * @date Oct 2, 2014
  * @author Frank Dellaert
- * @author Yong Dian Jian
  */
 
 // The two new headers that allow using our Automatic Differentiation Expression framework
 #include <gtsam/slam/expressions.h>
 #include <gtsam/nonlinear/ExpressionFactorGraph.h>
 
-// Header order is close to far
+// For an explanation of headers below, please see Pose2SLAMExample.cpp
-#include <gtsam/nonlinear/NonlinearFactorGraph.h>
+#include <gtsam/slam/PriorFactor.h>
+#include <gtsam/slam/BetweenFactor.h>
+#include <gtsam/geometry/Pose2.h>
 #include <gtsam/nonlinear/GaussNewtonOptimizer.h>
 #include <gtsam/nonlinear/Marginals.h>
-#include <gtsam/nonlinear/Values.h>
-#include <gtsam/geometry/Pose2.h>
-#include <gtsam/inference/Key.h>
 
 using namespace std;
 using namespace gtsam;

examples/Pose2SLAMExample_g2o.cpp

@@ -20,6 +20,7 @@
 
 #include <gtsam/slam/dataset.h>
 #include <gtsam/slam/PriorFactor.h>
+#include <gtsam/geometry/Pose2.h>
 #include <gtsam/nonlinear/GaussNewtonOptimizer.h>
 #include <fstream>
 

examples/Pose2SLAMExample_graph.cpp

@@ -16,11 +16,15 @@
  * @author Frank Dellaert
  */
 
-#include <gtsam/slam/dataset.h>
+// For an explanation of headers below, please see Pose2SLAMExample.cpp
 #include <gtsam/slam/PriorFactor.h>
-#include <gtsam/nonlinear/Marginals.h>
+#include <gtsam/slam/BetweenFactor.h>
-#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
 #include <gtsam/geometry/Pose2.h>
+#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
+#include <gtsam/nonlinear/Marginals.h>
+
+// This new header allows us to read examples easily from .graph files
+#include <gtsam/slam/dataset.h>
 
 using namespace std;
 using namespace gtsam;

examples/Pose2SLAMExample_graphviz.cpp

@@ -16,11 +16,11 @@
  * @author Frank Dellaert
  */
 
+// For an explanation of headers below, please see Pose2SLAMExample.cpp
 #include <gtsam/slam/PriorFactor.h>
 #include <gtsam/slam/BetweenFactor.h>
-#include <gtsam/nonlinear/Marginals.h>
-#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
 #include <gtsam/geometry/Pose2.h>
+#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
 #include <fstream>
 
 using namespace std;

examples/Pose2SLAMExample_lago.cpp

@@ -22,6 +22,7 @@
 #include <gtsam/slam/lago.h>
 #include <gtsam/slam/dataset.h>
 #include <gtsam/slam/PriorFactor.h>
+#include <gtsam/geometry/Pose2.h>
 #include <fstream>
 
 using namespace std;

examples/Pose2SLAMwSPCG.cpp

@@ -16,47 +16,15 @@
  * @date June 2, 2012
  */
 
-/**
+// For an explanation of headers below, please see Pose2SLAMExample.cpp
- * A simple 2D pose slam example solved using a Conjugate-Gradient method
- *  - The robot moves in a 2 meter square
- *  - The robot moves 2 meters each step, turning 90 degrees after each step
- *  - The robot initially faces along the X axis (horizontal, to the right in 2D)
- *  - We have full odometry between pose
- *  - We have a loop closure constraint when the robot returns to the first position
- */
-
-// As this is a planar SLAM example, we will use Pose2 variables (x, y, theta) to represent
-// the robot positions
-#include <gtsam/geometry/Pose2.h>
-#include <gtsam/geometry/Point2.h>
-
-// Each variable in the system (poses) must be identified with a unique key.
-// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1).
-// Here we will use simple integer keys
-#include <gtsam/inference/Key.h>
-
-// In GTSAM, measurement functions are represented as 'factors'. Several common factors
-// have been provided with the library for solving robotics/SLAM/Bundle Adjustment problems.
-// Here we will use Between factors for the relative motion described by odometry measurements.
-// We will also use a Between Factor to encode the loop closure constraint
-// Also, we will initialize the robot at the origin using a Prior factor.
 #include <gtsam/slam/PriorFactor.h>
 #include <gtsam/slam/BetweenFactor.h>
-
+#include <gtsam/geometry/Pose2.h>
-// When the factors are created, we will add them to a Factor Graph. As the factors we are using
-// are nonlinear factors, we will need a Nonlinear Factor Graph.
-#include <gtsam/nonlinear/NonlinearFactorGraph.h>
-
-// The nonlinear solvers within GTSAM are iterative solvers, meaning they linearize the
-// nonlinear functions around an initial linearization point, then solve the linear system
-// to update the linearization point. This happens repeatedly until the solver converges
-// to a consistent set of variable values. This requires us to specify an initial guess
-// for each variable, held in a Values container.
-#include <gtsam/nonlinear/Values.h>
-
-#include <gtsam/linear/SubgraphSolver.h>
 #include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
 
+// In contrast to that example, however, we will use a PCG solver here
+#include <gtsam/linear/SubgraphSolver.h>
+
 using namespace std;
 using namespace gtsam;
 
@@ -66,32 +34,24 @@ int main(int argc, char** argv) {
   NonlinearFactorGraph graph;
 
   // 2a. Add a prior on the first pose, setting it to the origin
-  // A prior factor consists of a mean and a noise model (covariance matrix)
   Pose2 prior(0.0, 0.0, 0.0); // prior at origin
   noiseModel::Diagonal::shared_ptr priorNoise = noiseModel::Diagonal::Sigmas(Vector3(0.3, 0.3, 0.1));
   graph.push_back(PriorFactor<Pose2>(1, prior, priorNoise));
 
   // 2b. Add odometry factors
-  // For simplicity, we will use the same noise model for each odometry factor
   noiseModel::Diagonal::shared_ptr odometryNoise = noiseModel::Diagonal::Sigmas(Vector3(0.2, 0.2, 0.1));
-  // Create odometry (Between) factors between consecutive poses
   graph.push_back(BetweenFactor<Pose2>(1, 2, Pose2(2.0, 0.0, M_PI_2),    odometryNoise));
   graph.push_back(BetweenFactor<Pose2>(2, 3, Pose2(2.0, 0.0, M_PI_2), odometryNoise));
   graph.push_back(BetweenFactor<Pose2>(3, 4, Pose2(2.0, 0.0, M_PI_2), odometryNoise));
   graph.push_back(BetweenFactor<Pose2>(4, 5, Pose2(2.0, 0.0, M_PI_2), odometryNoise));
 
   // 2c. Add the loop closure constraint
-  // This factor encodes the fact that we have returned to the same pose. In real systems,
-  // these constraints may be identified in many ways, such as appearance-based techniques
-  // with camera images.
-  // We will use another Between Factor to enforce this constraint, with the distance set to zero,
   noiseModel::Diagonal::shared_ptr model = noiseModel::Diagonal::Sigmas(Vector3(0.2, 0.2, 0.1));
   graph.push_back(BetweenFactor<Pose2>(5, 1, Pose2(0.0, 0.0, 0.0), model));
   graph.print("\nFactor Graph:\n"); // print
 
 
   // 3. Create the data structure to hold the initialEstimate estimate to the solution
-  // For illustrative purposes, these have been deliberately set to incorrect values
   Values initialEstimate;
   initialEstimate.insert(1, Pose2(0.5, 0.0, 0.2));
   initialEstimate.insert(2, Pose2(2.3, 0.1, 1.1));
@@ -104,15 +64,18 @@ int main(int argc, char** argv) {
   LevenbergMarquardtParams parameters;
   parameters.verbosity = NonlinearOptimizerParams::ERROR;
   parameters.verbosityLM = LevenbergMarquardtParams::LAMBDA;
-  parameters.linearSolverType = NonlinearOptimizerParams::Iterative;
 
-  {
+  // LM is still the outer optimization loop, but by specifying "Iterative" below
-    parameters.iterativeParams = boost::make_shared<SubgraphSolverParameters>();
+  // We indicate that an iterative linear solver should be used.
-    LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, parameters);
+  // In addition, the *type* of the iterativeParams decides on the type of
-    Values result = optimizer.optimize();
+  // iterative solver, in this case the SPCG (subgraph PCG)
-    result.print("Final Result:\n");
+  parameters.linearSolverType = NonlinearOptimizerParams::Iterative;
-    cout << "subgraph solver final error = " << graph.error(result) << endl;
+  parameters.iterativeParams = boost::make_shared<SubgraphSolverParameters>();
-  }
+
+  LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, parameters);
+  Values result = optimizer.optimize();
+  result.print("Final Result:\n");
+  cout << "subgraph solver final error = " << graph.error(result) << endl;
 
   return 0;
 }

examples/RangeISAMExample_plaza2.cpp

@@ -39,7 +39,7 @@
 // have been provided with the library for solving robotics SLAM problems.
 #include <gtsam/slam/PriorFactor.h>
 #include <gtsam/slam/BetweenFactor.h>
-#include <gtsam/slam/RangeFactor.h>
+#include <gtsam/sam/RangeFactor.h>
 #include <gtsam/slam/dataset.h>
 
 // Standard headers, added last, so we know headers above work on their own

examples/SFMExample.cpp

@@ -15,13 +15,7 @@
  * @author  Duy-Nguyen Ta
  */
 
-/**
+// For loading the data, see the comments therein for scenario (camera rotates around cube)
- * A structure-from-motion example with landmarks
- *  - The landmarks form a 10 meter cube
- *  - The robot rotates around the landmarks, always facing towards the cube
- */
-
-// For loading the data
 #include "SFMdata.h"
 
 // Camera observations of landmarks (i.e. pixel coordinates) will be stored as Point2 (x, y).
@@ -103,7 +97,7 @@ int main(int argc, char* argv[]) {
   // Intentionally initialize the variables off from the ground truth
   Values initialEstimate;
   for (size_t i = 0; i < poses.size(); ++i)
-    initialEstimate.insert(Symbol('x', i), poses[i].compose(Pose3(Rot3::rodriguez(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20))));
+    initialEstimate.insert(Symbol('x', i), poses[i].compose(Pose3(Rot3::Rodrigues(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20))));
   for (size_t j = 0; j < points.size(); ++j)
     initialEstimate.insert(Symbol('l', j), points[j].compose(Point3(-0.25, 0.20, 0.15)));
   initialEstimate.print("Initial Estimates:\n");

examples/SFMExampleExpressions.cpp

@@ -84,7 +84,7 @@ int main(int argc, char* argv[]) {
 
   // Create perturbed initial
   Values initial;
-  Pose3 delta(Rot3::rodriguez(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20));
+  Pose3 delta(Rot3::Rodrigues(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20));
   for (size_t i = 0; i < poses.size(); ++i)
     initial.insert(Symbol('x', i), poses[i].compose(delta));
   for (size_t j = 0; j < points.size(); ++j)

examples/SFMExample_SmartFactor.cpp

@@ -17,51 +17,25 @@
  * @author  Frank Dellaert
  */
 
-/**
- * A structure-from-motion example with landmarks
- *  - The landmarks form a 10 meter cube
- *  - The robot rotates around the landmarks, always facing towards the cube
- */
-
-// For loading the data
-#include "SFMdata.h"
-
-// Camera observations of landmarks (i.e. pixel coordinates) will be stored as Point2 (x, y).
-#include <gtsam/geometry/Point2.h>
-
 // In GTSAM, measurement functions are represented as 'factors'.
-// The factor we used here is SmartProjectionPoseFactor. Every smart factor represent a single landmark,
+// The factor we used here is SmartProjectionPoseFactor.
-// The SmartProjectionPoseFactor only optimize the pose of camera, not the calibration,
+// Every smart factor represent a single landmark, seen from multiple cameras.
-// The calibration should be known.
+// The SmartProjectionPoseFactor only optimizes for the poses of a camera,
+// not the calibration, which is assumed known.
 #include <gtsam/slam/SmartProjectionPoseFactor.h>
 
-// Also, we will initialize the robot at some location using a Prior factor.
+// For an explanation of these headers, see SFMExample.cpp
-#include <gtsam/slam/PriorFactor.h>
+#include "SFMdata.h"
-
+#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
-// When the factors are created, we will add them to a Factor Graph. As the factors we are using
-// are nonlinear factors, we will need a Nonlinear Factor Graph.
-#include <gtsam/nonlinear/NonlinearFactorGraph.h>
-
-// Finally, once all of the factors have been added to our factor graph, we will want to
-// solve/optimize to graph to find the best (Maximum A Posteriori) set of variable values.
-// GTSAM includes several nonlinear optimizers to perform this step. Here we will use a
-// trust-region method known as Powell's Degleg
-#include <gtsam/nonlinear/DoglegOptimizer.h>
-
-// The nonlinear solvers within GTSAM are iterative solvers, meaning they linearize the
-// nonlinear functions around an initial linearization point, then solve the linear system
-// to update the linearization point. This happens repeatedly until the solver converges
-// to a consistent set of variable values. This requires us to specify an initial guess
-// for each variable, held in a Values container.
-#include <gtsam/nonlinear/Values.h>
-
-#include <vector>
 
 using namespace std;
 using namespace gtsam;
 
 // Make the typename short so it looks much cleaner
-typedef gtsam::SmartProjectionPoseFactor<gtsam::Pose3, gtsam::Cal3_S2> SmartFactor;
+typedef SmartProjectionPoseFactor<Cal3_S2> SmartFactor;
+
+// create a typedef to the camera type
+typedef PinholePose<Cal3_S2> Camera;
 
 /* ************************************************************************* */
 int main(int argc, char* argv[]) {
@@ -84,12 +58,12 @@ int main(int argc, char* argv[]) {
   for (size_t j = 0; j < points.size(); ++j) {
 
     // every landmark represent a single landmark, we use shared pointer to init the factor, and then insert measurements.
-    SmartFactor::shared_ptr smartfactor(new SmartFactor());
+    SmartFactor::shared_ptr smartfactor(new SmartFactor(measurementNoise, K));
 
     for (size_t i = 0; i < poses.size(); ++i) {
 
       // generate the 2D measurement
-      SimpleCamera camera(poses[i], *K);
+      Camera camera(poses[i], K);
       Point2 measurement = camera.project(points[j]);
 
       // call add() function to add measurement into a single factor, here we need to add:
@@ -97,7 +71,7 @@ int main(int argc, char* argv[]) {
       //    2. the corresponding camera's key
       //    3. camera noise model
       //    4. camera calibration
-      smartfactor->add(measurement, i, measurementNoise, K);
+      smartfactor->add(measurement, i);
     }
 
     // insert the smart factor in the graph
@@ -106,28 +80,29 @@ int main(int argc, char* argv[]) {
 
   // Add a prior on pose x0. This indirectly specifies where the origin is.
   // 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
-  noiseModel::Diagonal::shared_ptr poseNoise = noiseModel::Diagonal::Sigmas(
+  noiseModel::Diagonal::shared_ptr noise = noiseModel::Diagonal::Sigmas(
       (Vector(6) << Vector3::Constant(0.3), Vector3::Constant(0.1)).finished());
-  graph.push_back(PriorFactor<Pose3>(0, poses[0], poseNoise));
+  graph.push_back(PriorFactor<Camera>(0, Camera(poses[0],K), noise));
 
   // Because the structure-from-motion problem has a scale ambiguity, the problem is
   // still under-constrained. Here we add a prior on the second pose x1, so this will
   // fix the scale by indicating the distance between x0 and x1.
   // Because these two are fixed, the rest of the poses will be also be fixed.
-  graph.push_back(PriorFactor<Pose3>(1, poses[1], poseNoise)); // add directly to graph
+  graph.push_back(PriorFactor<Camera>(1, Camera(poses[1],K), noise)); // add directly to graph
 
   graph.print("Factor Graph:\n");
 
   // Create the initial estimate to the solution
   // Intentionally initialize the variables off from the ground truth
   Values initialEstimate;
-  Pose3 delta(Rot3::rodriguez(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20));
+  Pose3 delta(Rot3::Rodrigues(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20));
   for (size_t i = 0; i < poses.size(); ++i)
-    initialEstimate.insert(i, poses[i].compose(delta));
+    initialEstimate.insert(i, Camera(poses[i].compose(delta), K));
   initialEstimate.print("Initial Estimates:\n");
 
   // Optimize the graph and print results
-  Values result = DoglegOptimizer(graph, initialEstimate).optimize();
+  LevenbergMarquardtOptimizer optimizer(graph, initialEstimate);
+  Values result = optimizer.optimize();
   result.print("Final results:\n");
 
   // A smart factor represent the 3D point inside the factor, not as a variable.
@@ -136,20 +111,20 @@ int main(int argc, char* argv[]) {
   Values landmark_result;
   for (size_t j = 0; j < points.size(); ++j) {
 
-    // The output of point() is in boost::optional<gtsam::Point3>, as sometimes
-    // the triangulation operation inside smart factor will encounter degeneracy.
-    boost::optional<Point3> point;
-
     // The graph stores Factor shared_ptrs, so we cast back to a SmartFactor first
     SmartFactor::shared_ptr smart = boost::dynamic_pointer_cast<SmartFactor>(graph[j]);
     if (smart) {
-      point = smart->point(result);
+      // The output of point() is in boost::optional<Point3>, as sometimes
+      // the triangulation operation inside smart factor will encounter degeneracy.
+      boost::optional<Point3> point = smart->point(result);
       if (point) // ignore if boost::optional return NULL
         landmark_result.insert(j, *point);
     }
   }
 
   landmark_result.print("Landmark results:\n");
+  cout << "final error: " << graph.error(result) << endl;
+  cout << "number of iterations: " << optimizer.iterations() << endl;
 
   return 0;
 }

examples/SFMExample_SmartFactorPCG.cpp

@@ -0,0 +1,129 @@
+/* ----------------------------------------------------------------------------
+
+ * GTSAM Copyright 2010, Georgia Tech Research Corporation,
+ * Atlanta, Georgia 30332-0415
+ * All Rights Reserved
+ * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
+
+ * See LICENSE for the license information
+
+ * -------------------------------------------------------------------------- */
+
+/**
+ * @file    SFMExample_SmartFactorPCG.cpp
+ * @brief   Version of SFMExample_SmartFactor that uses Preconditioned Conjugate Gradient
+ * @author  Frank Dellaert
+ */
+
+// For an explanation of these headers, see SFMExample_SmartFactor.cpp
+#include "SFMdata.h"
+#include <gtsam/slam/SmartProjectionPoseFactor.h>
+
+// These extra headers allow us a LM outer loop with PCG linear solver (inner loop)
+#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
+#include <gtsam/linear/Preconditioner.h>
+#include <gtsam/linear/PCGSolver.h>
+
+using namespace std;
+using namespace gtsam;
+
+// Make the typename short so it looks much cleaner
+typedef SmartProjectionPoseFactor<Cal3_S2> SmartFactor;
+
+// create a typedef to the camera type
+typedef PinholePose<Cal3_S2> Camera;
+
+/* ************************************************************************* */
+int main(int argc, char* argv[]) {
+
+  // Define the camera calibration parameters
+  Cal3_S2::shared_ptr K(new Cal3_S2(50.0, 50.0, 0.0, 50.0, 50.0));
+
+  // Define the camera observation noise model
+  noiseModel::Isotropic::shared_ptr measurementNoise =
+      noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v
+
+  // Create the set of ground-truth landmarks and poses
+  vector<Point3> points = createPoints();
+  vector<Pose3> poses = createPoses();
+
+  // Create a factor graph
+  NonlinearFactorGraph graph;
+
+  // Simulated measurements from each camera pose, adding them to the factor graph
+  for (size_t j = 0; j < points.size(); ++j) {
+
+    // every landmark represent a single landmark, we use shared pointer to init the factor, and then insert measurements.
+    SmartFactor::shared_ptr smartfactor(new SmartFactor(measurementNoise, K));
+
+    for (size_t i = 0; i < poses.size(); ++i) {
+
+      // generate the 2D measurement
+      Camera camera(poses[i], K);
+      Point2 measurement = camera.project(points[j]);
+
+      // call add() function to add measurement into a single factor, here we need to add:
+      smartfactor->add(measurement, i);
+    }
+
+    // insert the smart factor in the graph
+    graph.push_back(smartfactor);
+  }
+
+  // Add a prior on pose x0. This indirectly specifies where the origin is.
+  // 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
+  noiseModel::Diagonal::shared_ptr noise = noiseModel::Diagonal::Sigmas(
+      (Vector(6) << Vector3::Constant(0.3), Vector3::Constant(0.1)).finished());
+  graph.push_back(PriorFactor<Camera>(0, Camera(poses[0],K), noise));
+
+  // Fix the scale ambiguity by adding a prior
+  graph.push_back(PriorFactor<Camera>(1, Camera(poses[0],K), noise));
+
+  // Create the initial estimate to the solution
+  Values initialEstimate;
+  Pose3 delta(Rot3::Rodrigues(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20));
+  for (size_t i = 0; i < poses.size(); ++i)
+    initialEstimate.insert(i, Camera(poses[i].compose(delta),K));
+
+  // We will use LM in the outer optimization loop, but by specifying "Iterative" below
+  // We indicate that an iterative linear solver should be used.
+  // In addition, the *type* of the iterativeParams decides on the type of
+  // iterative solver, in this case the SPCG (subgraph PCG)
+  LevenbergMarquardtParams parameters;
+  parameters.linearSolverType = NonlinearOptimizerParams::Iterative;
+  parameters.absoluteErrorTol = 1e-10;
+  parameters.relativeErrorTol = 1e-10;
+  parameters.maxIterations = 500;
+  PCGSolverParameters::shared_ptr pcg =
+      boost::make_shared<PCGSolverParameters>();
+  pcg->preconditioner_ =
+      boost::make_shared<BlockJacobiPreconditionerParameters>();
+  // Following is crucial:
+  pcg->setEpsilon_abs(1e-10);
+  pcg->setEpsilon_rel(1e-10);
+  parameters.iterativeParams = pcg;
+
+  LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, parameters);
+  Values result = optimizer.optimize();
+
+  // Display result as in SFMExample_SmartFactor.run
+  result.print("Final results:\n");
+  Values landmark_result;
+  for (size_t j = 0; j < points.size(); ++j) {
+    SmartFactor::shared_ptr smart = //
+        boost::dynamic_pointer_cast<SmartFactor>(graph[j]);
+    if (smart) {
+      boost::optional<Point3> point = smart->point(result);
+      if (point) // ignore if boost::optional return NULL
+        landmark_result.insert(j, *point);
+    }
+  }
+
+  landmark_result.print("Landmark results:\n");
+  cout << "final error: " << graph.error(result) << endl;
+  cout << "number of iterations: " << optimizer.iterations() << endl;
+
+  return 0;
+}
+/* ************************************************************************* */
+

examples/SFMExample_bal_COLAMD_METIS.cpp

@@ -0,0 +1,144 @@
+/* ----------------------------------------------------------------------------
+
+ * GTSAM Copyright 2010, Georgia Tech Research Corporation,
+ * Atlanta, Georgia 30332-0415
+ * All Rights Reserved
+ * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
+
+ * See LICENSE for the license information
+
+ * -------------------------------------------------------------------------- */
+
+/**
+ * @file    SFMExample.cpp
+ * @brief   This file is to compare the ordering performance for COLAMD vs METIS.
+ * Example problem is to solve a structure-from-motion problem from a "Bundle Adjustment in the Large" file.
+ * @author  Frank Dellaert, Zhaoyang Lv
+ */
+
+// For an explanation of headers, see SFMExample.cpp
+#include <gtsam/inference/Symbol.h>
+#include <gtsam/inference/Ordering.h>
+#include <gtsam/nonlinear/NonlinearFactorGraph.h>
+#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
+#include <gtsam/slam/PriorFactor.h>
+#include <gtsam/slam/GeneralSFMFactor.h>
+#include <gtsam/slam/dataset.h> // for loading BAL datasets !
+
+#include <gtsam/base/timing.h>
+
+#include <vector>
+
+using namespace std;
+using namespace gtsam;
+using symbol_shorthand::C;
+using symbol_shorthand::P;
+
+// We will be using a projection factor that ties a SFM_Camera to a 3D point.
+// An SFM_Camera is defined in datase.h as a camera with unknown Cal3Bundler calibration
+// and has a total of 9 free parameters
+typedef GeneralSFMFactor<SfM_Camera,Point3> MyFactor;
+
+/* ************************************************************************* */
+int main (int argc, char* argv[]) {
+
+  // Find default file, but if an argument is given, try loading a file
+  string filename = findExampleDataFile("dubrovnik-3-7-pre");
+  if (argc>1) filename = string(argv[1]);
+
+  // Load the SfM data from file
+  SfM_data mydata;
+  readBAL(filename, mydata);
+  cout << boost::format("read %1% tracks on %2% cameras\n") % mydata.number_tracks() % mydata.number_cameras();
+
+  // Create a factor graph
+  NonlinearFactorGraph graph;
+
+  // We share *one* noiseModel between all projection factors
+  noiseModel::Isotropic::shared_ptr noise =
+      noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v
+
+  // Add measurements to the factor graph
+  size_t j = 0;
+  BOOST_FOREACH(const SfM_Track& track, mydata.tracks) {
+    BOOST_FOREACH(const SfM_Measurement& m, track.measurements) {
+      size_t i = m.first;
+      Point2 uv = m.second;
+      graph.push_back(MyFactor(uv, noise, C(i), P(j))); // note use of shorthand symbols C and P
+    }
+    j += 1;
+  }
+
+  // Add a prior on pose x1. This indirectly specifies where the origin is.
+  // and a prior on the position of the first landmark to fix the scale
+  graph.push_back(PriorFactor<SfM_Camera>(C(0), mydata.cameras[0],  noiseModel::Isotropic::Sigma(9, 0.1)));
+  graph.push_back(PriorFactor<Point3>    (P(0), mydata.tracks[0].p, noiseModel::Isotropic::Sigma(3, 0.1)));
+
+  // Create initial estimate
+  Values initial;
+  size_t i = 0; j = 0;
+  BOOST_FOREACH(const SfM_Camera& camera, mydata.cameras) initial.insert(C(i++), camera);
+  BOOST_FOREACH(const SfM_Track& track, mydata.tracks)    initial.insert(P(j++), track.p);
+
+  /** ---------------  COMPARISON  -----------------------**/
+  /** ----------------------------------------------------**/
+
+  LevenbergMarquardtParams params_using_COLAMD, params_using_METIS;
+  try {
+    params_using_METIS.setVerbosity("ERROR");
+    gttic_(METIS_ORDERING);
+    params_using_METIS.ordering = Ordering::Create(Ordering::METIS, graph);
+    gttoc_(METIS_ORDERING);
+
+    params_using_COLAMD.setVerbosity("ERROR");
+    gttic_(COLAMD_ORDERING);
+    params_using_COLAMD.ordering = Ordering::Create(Ordering::COLAMD, graph);
+    gttoc_(COLAMD_ORDERING);
+  } catch (exception& e) {
+    cout << e.what();
+  }
+
+  // expect they have different ordering results
+  if(params_using_COLAMD.ordering == params_using_METIS.ordering) {
+    cout << "COLAMD and METIS produce the same ordering. "
+         << "Problem here!!!" << endl;
+  }
+
+  /* Optimize the graph with METIS and COLAMD and time the results */
+
+  Values result_METIS, result_COLAMD;
+  try {
+    gttic_(OPTIMIZE_WITH_METIS);
+    LevenbergMarquardtOptimizer lm_METIS(graph, initial, params_using_METIS);
+    result_METIS = lm_METIS.optimize();
+    gttoc_(OPTIMIZE_WITH_METIS);
+
+    gttic_(OPTIMIZE_WITH_COLAMD);
+    LevenbergMarquardtOptimizer lm_COLAMD(graph, initial, params_using_COLAMD);
+    result_COLAMD = lm_COLAMD.optimize();
+    gttoc_(OPTIMIZE_WITH_COLAMD);
+  } catch (exception& e) {
+    cout << e.what();
+  }
+
+
+  { // printing the result
+
+    cout << "COLAMD final error: " << graph.error(result_COLAMD) << endl;
+    cout << "METIS final error: " << graph.error(result_METIS) << endl;
+
+    cout << endl << endl;
+
+    cout << "Time comparison by solving " << filename << " results:" << endl;
+    cout << boost::format("%1% point tracks and %2% cameras\n") \
+            % mydata.number_tracks() % mydata.number_cameras() \
+         << endl;
+
+    tictoc_print_();
+  }
+
+
+  return 0;
+}
+/* ************************************************************************* */
+

examples/SelfCalibrationExample.cpp

@@ -82,7 +82,7 @@ int main(int argc, char* argv[]) {
   Values initialEstimate;
   initialEstimate.insert(Symbol('K', 0), Cal3_S2(60.0, 60.0, 0.0, 45.0, 45.0));
   for (size_t i = 0; i < poses.size(); ++i)
-    initialEstimate.insert(Symbol('x', i), poses[i].compose(Pose3(Rot3::rodriguez(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20))));
+    initialEstimate.insert(Symbol('x', i), poses[i].compose(Pose3(Rot3::Rodrigues(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20))));
   for (size_t j = 0; j < points.size(); ++j)
     initialEstimate.insert(Symbol('l', j), points[j].compose(Point3(-0.25, 0.20, 0.15)));
 

examples/SolverComparer.cpp

@@ -31,28 +31,30 @@
 *
 */
 
-#include <gtsam/base/timing.h>
-#include <gtsam/base/treeTraversal-inst.h>
-#include <gtsam/slam/dataset.h>
-#include <gtsam/geometry/Pose2.h>
-#include <gtsam/slam/PriorFactor.h>
 #include <gtsam/slam/BetweenFactor.h>
-#include <gtsam/slam/BearingRangeFactor.h>
+#include <gtsam/sam/BearingRangeFactor.h>
-#include <gtsam/inference/Symbol.h>
+#include <gtsam/slam/dataset.h>
-#include <gtsam/linear/GaussianJunctionTree.h>
+#include <gtsam/slam/PriorFactor.h>
-#include <gtsam/linear/GaussianEliminationTree.h>
+#include <gtsam/geometry/Pose2.h>
 #include <gtsam/nonlinear/ISAM2.h>
 #include <gtsam/nonlinear/GaussNewtonOptimizer.h>
 #include <gtsam/nonlinear/Marginals.h>
+#include <gtsam/linear/GaussianJunctionTree.h>
+#include <gtsam/linear/GaussianEliminationTree.h>
+#include <gtsam/inference/Symbol.h>
+#include <gtsam/base/timing.h>
+#include <gtsam/base/treeTraversal-inst.h>
+#include <gtsam/config.h> // for GTSAM_USE_TBB
 
-#include <fstream>
-#include <iostream>
-#include <boost/archive/binary_oarchive.hpp>
 #include <boost/archive/binary_iarchive.hpp>
-#include <boost/serialization/export.hpp>
+#include <boost/archive/binary_oarchive.hpp>
 #include <boost/program_options.hpp>
 #include <boost/range/algorithm/set_algorithm.hpp>
 #include <boost/random.hpp>
+#include <boost/serialization/export.hpp>
+
+#include <fstream>
+#include <iostream>
 
 #ifdef GTSAM_USE_TBB
 #include <tbb/tbb.h>
@@ -72,23 +74,6 @@ typedef NoiseModelFactor1<Pose> NM1;
 typedef NoiseModelFactor2<Pose,Pose> NM2;
 typedef BearingRangeFactor<Pose,Point2> BR;
 
-//GTSAM_VALUE_EXPORT(Value);
-//GTSAM_VALUE_EXPORT(Pose);
-//GTSAM_VALUE_EXPORT(Rot2);
-//GTSAM_VALUE_EXPORT(Point2);
-//GTSAM_VALUE_EXPORT(NonlinearFactor);
-//GTSAM_VALUE_EXPORT(NoiseModelFactor);
-//GTSAM_VALUE_EXPORT(NM1);
-//GTSAM_VALUE_EXPORT(NM2);
-//GTSAM_VALUE_EXPORT(BetweenFactor<Pose>);
-//GTSAM_VALUE_EXPORT(PriorFactor<Pose>);
-//GTSAM_VALUE_EXPORT(BR);
-//GTSAM_VALUE_EXPORT(noiseModel::Base);
-//GTSAM_VALUE_EXPORT(noiseModel::Isotropic);
-//GTSAM_VALUE_EXPORT(noiseModel::Gaussian);
-//GTSAM_VALUE_EXPORT(noiseModel::Diagonal);
-//GTSAM_VALUE_EXPORT(noiseModel::Unit);
-
 double chi2_red(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& config) {
   // Compute degrees of freedom (observations - variables)
   // In ocaml, +1 was added to the observations to account for the prior, but
@@ -269,12 +254,12 @@ void runIncremental()
       boost::dynamic_pointer_cast<BetweenFactor<Pose> >(datasetMeasurements[nextMeasurement]))
     {
       Key key1 = measurement->key1(), key2 = measurement->key2();
-      if((key1 >= firstStep && key1 < key2) || (key2 >= firstStep && key2 < key1)) {
+      if(((int)key1 >= firstStep && key1 < key2) || ((int)key2 >= firstStep && key2 < key1)) {
         // We found an odometry starting at firstStep
         firstPose = std::min(key1, key2);
         break;
       }
-      if((key2 >= firstStep && key1 < key2) || (key1 >= firstStep && key2 < key1)) {
+      if(((int)key2 >= firstStep && key1 < key2) || ((int)key1 >= firstStep && key2 < key1)) {
         // We found an odometry joining firstStep with a previous pose
         havePreviousPose = true;
         firstPose = std::max(key1, key2);
@@ -303,7 +288,9 @@ void runIncremental()
 
   cout << "Playing forward time steps..." << endl;
 
-  for(size_t step = firstPose; nextMeasurement < datasetMeasurements.size() && (lastStep == -1 || step <= lastStep); ++step)
+  for (size_t step = firstPose;
+      nextMeasurement < datasetMeasurements.size() && (lastStep == -1 || (int)step <= lastStep);
+      ++step)
   {
     Values newVariables;
     NonlinearFactorGraph newFactors;
@@ -589,7 +576,7 @@ void runStats()
 {
   cout << "Gathering statistics..." << endl;
   GaussianFactorGraph linear = *datasetMeasurements.linearize(initial);
-  GaussianJunctionTree jt(GaussianEliminationTree(linear, Ordering::colamd(linear)));
+  GaussianJunctionTree jt(GaussianEliminationTree(linear, Ordering::Colamd(linear)));
   treeTraversal::ForestStatistics statistics = treeTraversal::GatherStatistics(jt);
 
   ofstream file;

examples/TimeTBB.cpp

@@ -17,6 +17,7 @@
 
 #include <gtsam/global_includes.h>
 #include <gtsam/base/Matrix.h>
+
 #include <boost/assign/list_of.hpp>
 #include <boost/foreach.hpp>
 #include <map>

examples/VisualISAM2Example.cpp

@@ -95,7 +95,7 @@ int main(int argc, char* argv[]) {
 
     // Add an initial guess for the current pose
     // Intentionally initialize the variables off from the ground truth
-    initialEstimate.insert(Symbol('x', i), poses[i].compose(Pose3(Rot3::rodriguez(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20))));
+    initialEstimate.insert(Symbol('x', i), poses[i].compose(Pose3(Rot3::Rodrigues(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20))));
 
     // If this is the first iteration, add a prior on the first pose to set the coordinate frame
     // and a prior on the first landmark to set the scale

examples/VisualISAMExample.cpp

@@ -95,7 +95,7 @@ int main(int argc, char* argv[]) {
     }
 
     // Intentionally initialize the variables off from the ground truth
-    Pose3 noise(Rot3::rodriguez(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20));
+    Pose3 noise(Rot3::Rodrigues(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20));
     Pose3 initial_xi = poses[i].compose(noise);
 
     // Add an initial guess for the current pose

gtsam.h

@@ -1,4 +1,5 @@
 /**
+
  * GTSAM Wrap Module Definition
  *
  * These are the current classes available through the matlab toolbox interface,
@@ -156,7 +157,7 @@ virtual class Value {
   size_t dim() const;
 };
 
-#include <gtsam/base/LieScalar.h>
+#include <gtsam/base/deprecated/LieScalar.h>
 class LieScalar {
   // Standard constructors
   LieScalar();
@@ -185,7 +186,7 @@ class LieScalar {
   static Vector Logmap(const gtsam::LieScalar& p);
 };
 
-#include <gtsam/base/LieVector.h>
+#include <gtsam/base/deprecated/LieVector.h>
 class LieVector {
   // Standard constructors
   LieVector();
@@ -217,7 +218,7 @@ class LieVector {
   void serialize() const;
 };
 
-#include <gtsam/base/LieMatrix.h>
+#include <gtsam/base/deprecated/LieMatrix.h>
 class LieMatrix {
   // Standard constructors
   LieMatrix();
@@ -288,6 +289,32 @@ class Point2 {
   void serialize() const;
 };
 
+// std::vector<gtsam::Point2>
+class Point2Vector
+{
+  // Constructors
+  Point2Vector();
+  Point2Vector(const gtsam::Point2Vector& v);
+
+  //Capacity
+  size_t size() const;
+  size_t max_size() const;
+  void resize(size_t sz);
+  size_t capacity() const;
+  bool empty() const;
+  void reserve(size_t n);
+
+  //Element access
+  gtsam::Point2 at(size_t n) const;
+  gtsam::Point2 front() const;
+  gtsam::Point2 back() const;
+
+  //Modifiers
+  void assign(size_t n, const gtsam::Point2& u);
+  void push_back(const gtsam::Point2& x);
+  void pop_back();
+};
+
 class StereoPoint2 {
   // Standard Constructors
   StereoPoint2();
@@ -304,8 +331,6 @@ class StereoPoint2 {
   gtsam::StereoPoint2 between(const gtsam::StereoPoint2& p2) const;
 
   // Manifold
-  static size_t Dim();
-  size_t dim() const;
   gtsam::StereoPoint2 retract(Vector v) const;
   Vector localCoordinates(const gtsam::StereoPoint2& p) const;
 
@@ -414,7 +439,7 @@ class Rot3 {
   static gtsam::Rot3 roll(double t); // positive roll is to right (increasing yaw in aircraft)
   static gtsam::Rot3 ypr(double y, double p, double r);
   static gtsam::Rot3 quaternion(double w, double x, double y, double z);
-  static gtsam::Rot3 rodriguez(Vector v);
+  static gtsam::Rot3 Rodrigues(Vector v);
 
   // Testable
   void print(string s) const;
@@ -550,6 +575,16 @@ class Pose3 {
   void serialize() const;
 };
 
+// std::vector<gtsam::Pose3>
+class Pose3Vector
+{
+  Pose3Vector();
+  size_t size() const;
+  bool empty() const;
+  gtsam::Pose3 at(size_t n) const;
+  void push_back(const gtsam::Pose3& x);
+};
+
 #include <gtsam/geometry/Unit3.h>
 class Unit3 {
   // Standard Constructors
@@ -778,7 +813,7 @@ class CalibratedCamera {
 
   // Action on Point3
   gtsam::Point2 project(const gtsam::Point3& point) const;
-  static gtsam::Point2 project_to_camera(const gtsam::Point3& cameraPoint);
+  static gtsam::Point2 Project(const gtsam::Point3& cameraPoint);
 
   // Standard Interface
   gtsam::Pose3 pose() const;
@@ -788,56 +823,16 @@ class CalibratedCamera {
   void serialize() const;
 };
 
-class SimpleCamera {
+template<CALIBRATION>
-  // Standard Constructors and Named Constructors
-  SimpleCamera();
-  SimpleCamera(const gtsam::Pose3& pose);
-  SimpleCamera(const gtsam::Pose3& pose, const gtsam::Cal3_S2& K);
-  static gtsam::SimpleCamera Level(const gtsam::Cal3_S2& K,
-      const gtsam::Pose2& pose, double height);
-  static gtsam::SimpleCamera Level(const gtsam::Pose2& pose, double height);
-  static gtsam::SimpleCamera Lookat(const gtsam::Point3& eye,
-      const gtsam::Point3& target, const gtsam::Point3& upVector,
-      const gtsam::Cal3_S2& K);
-
-  // Testable
-  void print(string s) const;
-  bool equals(const gtsam::SimpleCamera& camera, double tol) const;
-
-  // Standard Interface
-  gtsam::Pose3 pose() const;
-  gtsam::Cal3_S2 calibration();
-
-  // Manifold
-  gtsam::SimpleCamera retract(const Vector& d) const;
-  Vector localCoordinates(const gtsam::SimpleCamera& T2) const;
-  size_t dim() const;
-  static size_t Dim();
-
-  // Transformations and measurement functions
-  static gtsam::Point2 project_to_camera(const gtsam::Point3& cameraPoint);
-  pair<gtsam::Point2,bool> projectSafe(const gtsam::Point3& pw) const;
-  gtsam::Point2 project(const gtsam::Point3& point);
-  gtsam::Point3 backproject(const gtsam::Point2& p, double depth) const;
-  double range(const gtsam::Point3& point);
-  double range(const gtsam::Pose3& point);
-
-  // enabling serialization functionality
-  void serialize() const;
-};
-
-template<CALIBRATION = {gtsam::Cal3DS2}>
 class PinholeCamera {
   // Standard Constructors and Named Constructors
   PinholeCamera();
   PinholeCamera(const gtsam::Pose3& pose);
-  PinholeCamera(const gtsam::Pose3& pose, const gtsam::Cal3DS2& K);
+  PinholeCamera(const gtsam::Pose3& pose, const CALIBRATION& K);
-  static This Level(const gtsam::Cal3DS2& K,
+  static This Level(const CALIBRATION& K, const gtsam::Pose2& pose, double height);
-    const gtsam::Pose2& pose, double height);
   static This Level(const gtsam::Pose2& pose, double height);
-  static This Lookat(const gtsam::Point3& eye,
+  static This Lookat(const gtsam::Point3& eye, const gtsam::Point3& target,
-    const gtsam::Point3& target, const gtsam::Point3& upVector,
+      const gtsam::Point3& upVector, const CALIBRATION& K);
-    const gtsam::Cal3DS2& K);
 
   // Testable
   void print(string s) const;
@@ -854,7 +849,7 @@ class PinholeCamera {
   static size_t Dim();
 
   // Transformations and measurement functions
-  static gtsam::Point2 project_to_camera(const gtsam::Point3& cameraPoint);
+  static gtsam::Point2 Project(const gtsam::Point3& cameraPoint);
   pair<gtsam::Point2,bool> projectSafe(const gtsam::Point3& pw) const;
   gtsam::Point2 project(const gtsam::Point3& point);
   gtsam::Point3 backproject(const gtsam::Point2& p, double depth) const;
@@ -865,6 +860,50 @@ class PinholeCamera {
   void serialize() const;
 };
 
+virtual class SimpleCamera {
+  // Standard Constructors and Named Constructors
+  SimpleCamera();
+  SimpleCamera(const gtsam::Pose3& pose);
+  SimpleCamera(const gtsam::Pose3& pose, const gtsam::Cal3_S2& K);
+  static gtsam::SimpleCamera Level(const gtsam::Cal3_S2& K, const gtsam::Pose2& pose, double height);
+  static gtsam::SimpleCamera Level(const gtsam::Pose2& pose, double height);
+  static gtsam::SimpleCamera Lookat(const gtsam::Point3& eye, const gtsam::Point3& target,
+      const gtsam::Point3& upVector, const gtsam::Cal3_S2& K);
+
+  // Testable
+  void print(string s) const;
+  bool equals(const gtsam::SimpleCamera& camera, double tol) const;
+
+  // Standard Interface
+  gtsam::Pose3 pose() const;
+  gtsam::Cal3_S2 calibration() const;
+
+  // Manifold
+  gtsam::SimpleCamera retract(const Vector& d) const;
+  Vector localCoordinates(const gtsam::SimpleCamera& T2) const;
+  size_t dim() const;
+  static size_t Dim();
+
+  // Transformations and measurement functions
+  static gtsam::Point2 Project(const gtsam::Point3& cameraPoint);
+  pair<gtsam::Point2,bool> projectSafe(const gtsam::Point3& pw) const;
+  gtsam::Point2 project(const gtsam::Point3& point);
+  gtsam::Point3 backproject(const gtsam::Point2& p, double depth) const;
+  double range(const gtsam::Point3& point);
+  double range(const gtsam::Pose3& point);
+
+  // enabling serialization functionality
+  void serialize() const;
+
+};
+
+// Some typedefs for common camera types
+// PinholeCameraCal3_S2 is the same as SimpleCamera above
+typedef gtsam::PinholeCamera<gtsam::Cal3_S2> PinholeCameraCal3_S2;
+typedef gtsam::PinholeCamera<gtsam::Cal3DS2> PinholeCameraCal3DS2;
+typedef gtsam::PinholeCamera<gtsam::Cal3Unified> PinholeCameraCal3Unified;
+typedef gtsam::PinholeCamera<gtsam::Cal3Bundler> PinholeCameraCal3Bundler;
+
 class StereoCamera {
   // Standard Constructors and Named Constructors
   StereoCamera();
@@ -877,7 +916,7 @@ class StereoCamera {
   // Standard Interface
   gtsam::Pose3 pose() const;
   double baseline() const;
-  gtsam::Cal3_S2Stereo* calibration() const;
+  gtsam::Cal3_S2Stereo calibration() const;
 
   // Manifold
   gtsam::StereoCamera retract(const Vector& d) const;
@@ -893,6 +932,16 @@ class StereoCamera {
   void serialize() const;
 };
 
+#include <gtsam/geometry/triangulation.h>
+
+// Templates appear not yet supported for free functions
+gtsam::Point3 triangulatePoint3(const gtsam::Pose3Vector& poses,
+    gtsam::Cal3_S2* sharedCal, const gtsam::Point2Vector& measurements,
+    double rank_tol, bool optimize);
+gtsam::Point3 triangulatePoint3(const gtsam::Pose3Vector& poses,
+    gtsam::Cal3Bundler* sharedCal, const gtsam::Point2Vector& measurements,
+    double rank_tol, bool optimize);
+
 //*************************************************************************
 // Symbolic
 //*************************************************************************
@@ -1606,12 +1655,12 @@ char symbolChr(size_t key);
 size_t symbolIndex(size_t key);
 
 // Default keyformatter
-void printKeyList  (const gtsam::KeyList& keys);
+void PrintKeyList  (const gtsam::KeyList& keys);
-void printKeyList  (const gtsam::KeyList& keys, string s);
+void PrintKeyList  (const gtsam::KeyList& keys, string s);
-void printKeyVector(const gtsam::KeyVector& keys);
+void PrintKeyVector(const gtsam::KeyVector& keys);
-void printKeyVector(const gtsam::KeyVector& keys, string s);
+void PrintKeyVector(const gtsam::KeyVector& keys, string s);
-void printKeySet   (const gtsam::KeySet& keys);
+void PrintKeySet   (const gtsam::KeySet& keys);
-void printKeySet   (const gtsam::KeySet& keys, string s);
+void PrintKeySet   (const gtsam::KeySet& keys, string s);
 
 #include <gtsam/inference/LabeledSymbol.h>
 class LabeledSymbol {
@@ -1728,7 +1777,7 @@ class Values {
   void swap(gtsam::Values& values);
 
   bool exists(size_t j) const;
-  gtsam::KeyList keys() const;
+  gtsam::KeyVector keys() const;
 
   gtsam::VectorValues zeroVectors() const;
 
@@ -1845,8 +1894,6 @@ class KeySet {
 class KeyVector {
   KeyVector();
   KeyVector(const gtsam::KeyVector& other);
-  KeyVector(const gtsam::KeySet& other);
-  KeyVector(const gtsam::KeyList& other);
 
   // Note: no print function
 
@@ -2176,9 +2223,6 @@ class NonlinearISAM {
 //*************************************************************************
 // Nonlinear factor types
 //*************************************************************************
-#include <gtsam/geometry/Cal3_S2.h>
-#include <gtsam/geometry/Cal3DS2.h>
-#include <gtsam/geometry/Cal3_S2Stereo.h>
 #include <gtsam/geometry/SimpleCamera.h>
 #include <gtsam/geometry/CalibratedCamera.h>
 #include <gtsam/geometry/StereoPoint2.h>
@@ -2219,7 +2263,7 @@ virtual class NonlinearEquality : gtsam::NoiseModelFactor {
 };
 
 
-#include <gtsam/slam/RangeFactor.h>
+#include <gtsam/sam/RangeFactor.h>
 template<POSE, POINT>
 virtual class RangeFactor : gtsam::NoiseModelFactor {
   RangeFactor(size_t key1, size_t key2, double measured, const gtsam::noiseModel::Base* noiseModel);
@@ -2229,20 +2273,16 @@ typedef gtsam::RangeFactor<gtsam::Pose2, gtsam::Point2> RangeFactorPosePoint2;
 typedef gtsam::RangeFactor<gtsam::Pose3, gtsam::Point3> RangeFactorPosePoint3;
 typedef gtsam::RangeFactor<gtsam::Pose2, gtsam::Pose2> RangeFactorPose2;
 typedef gtsam::RangeFactor<gtsam::Pose3, gtsam::Pose3> RangeFactorPose3;
-
+typedef gtsam::RangeFactor<gtsam::CalibratedCamera, gtsam::Point3> RangeFactorCalibratedCameraPoint;
-// Commented out by Frank Dec 2014: not poses!
+typedef gtsam::RangeFactor<gtsam::SimpleCamera, gtsam::Point3> RangeFactorSimpleCameraPoint;
-// If needed, we need a RangeFactor that takes a camera, extracts the pose
+typedef gtsam::RangeFactor<gtsam::CalibratedCamera, gtsam::CalibratedCamera> RangeFactorCalibratedCamera;
-// Should be easy with Expressions
+typedef gtsam::RangeFactor<gtsam::SimpleCamera, gtsam::SimpleCamera> RangeFactorSimpleCamera;
-//typedef gtsam::RangeFactor<gtsam::CalibratedCamera, gtsam::Point3> RangeFactorCalibratedCameraPoint;
-//typedef gtsam::RangeFactor<gtsam::SimpleCamera, gtsam::Point3> RangeFactorSimpleCameraPoint;
-//typedef gtsam::RangeFactor<gtsam::CalibratedCamera, gtsam::CalibratedCamera> RangeFactorCalibratedCamera;
-//typedef gtsam::RangeFactor<gtsam::SimpleCamera, gtsam::SimpleCamera> RangeFactorSimpleCamera;
 
 
-#include <gtsam/slam/BearingFactor.h>
+#include <gtsam/sam/BearingFactor.h>
-template<POSE, POINT, ROTATION>
+template<POSE, POINT, BEARING>
 virtual class BearingFactor : gtsam::NoiseModelFactor {
-  BearingFactor(size_t key1, size_t key2, const ROTATION& measured, const gtsam::noiseModel::Base* noiseModel);
+  BearingFactor(size_t key1, size_t key2, const BEARING& measured, const gtsam::noiseModel::Base* noiseModel);
 
   // enabling serialization functionality
   void serialize() const;
@@ -2250,19 +2290,18 @@ virtual class BearingFactor : gtsam::NoiseModelFactor {
 
 typedef gtsam::BearingFactor<gtsam::Pose2, gtsam::Point2, gtsam::Rot2> BearingFactor2D;
 
-
+#include <gtsam/sam/BearingRangeFactor.h>
-#include <gtsam/slam/BearingRangeFactor.h>
+template<POSE, POINT, BEARING, RANGE>
-template<POSE, POINT, ROTATION>
 virtual class BearingRangeFactor : gtsam::NoiseModelFactor {
-  BearingRangeFactor(size_t poseKey, size_t pointKey, const ROTATION& measuredBearing, double measuredRange, const gtsam::noiseModel::Base* noiseModel);
+  BearingRangeFactor(size_t poseKey, size_t pointKey,
-
+      const BEARING& measuredBearing, const RANGE& measuredRange,
-  pair<ROTATION, double> measured() const;
+      const gtsam::noiseModel::Base* noiseModel);
 
   // enabling serialization functionality
   void serialize() const;
 };
 
-typedef gtsam::BearingRangeFactor<gtsam::Pose2, gtsam::Point2, gtsam::Rot2> BearingRangeFactor2D;
+typedef gtsam::BearingRangeFactor<gtsam::Pose2, gtsam::Point2, gtsam::Rot2, double> BearingRangeFactor2D;
 
 
 #include <gtsam/slam/ProjectionFactor.h>
@@ -2309,24 +2348,39 @@ virtual class GeneralSFMFactor2 : gtsam::NoiseModelFactor {
   void serialize() const;
 };
 
+#include <gtsam/slam/SmartProjectionFactor.h>
+class SmartProjectionParams {
+  SmartProjectionParams();
+  // TODO(frank): make these work:
+  //  void setLinearizationMode(LinearizationMode linMode);
+  //  void setDegeneracyMode(DegeneracyMode degMode);
+  void setRankTolerance(double rankTol);
+  void setEnableEPI(bool enableEPI);
+  void setLandmarkDistanceThreshold(bool landmarkDistanceThreshold);
+  void setDynamicOutlierRejectionThreshold(bool dynOutRejectionThreshold);
+};
+
 #include <gtsam/slam/SmartProjectionPoseFactor.h>
-template<POSE, CALIBRATION>
+template<CALIBRATION>
-virtual class SmartProjectionPoseFactor : gtsam::NonlinearFactor {
+virtual class SmartProjectionPoseFactor: gtsam::NonlinearFactor {
 
-  SmartProjectionPoseFactor(double rankTol, double linThreshold,
+  SmartProjectionPoseFactor(const gtsam::noiseModel::Base* noise,
-      bool manageDegeneracy, bool enableEPI, const POSE& body_P_sensor);
+      const CALIBRATION* K);
+  SmartProjectionPoseFactor(const gtsam::noiseModel::Base* noise,
+      const CALIBRATION* K,
+      const gtsam::Pose3& body_P_sensor);
+  SmartProjectionPoseFactor(const gtsam::noiseModel::Base* noise,
+      const CALIBRATION* K,
+      const gtsam::Pose3& body_P_sensor,
+      const gtsam::SmartProjectionParams& params);
 
-  SmartProjectionPoseFactor(double rankTol);
+  void add(const gtsam::Point2& measured_i, size_t poseKey_i);
-  SmartProjectionPoseFactor();
-
-  void add(const gtsam::Point2& measured_i, size_t poseKey_i, const gtsam::noiseModel::Base* noise_i,
-      const CALIBRATION* K_i);
 
   // enabling serialization functionality
   //void serialize() const;
 };
 
-typedef gtsam::SmartProjectionPoseFactor<gtsam::Pose3, gtsam::Cal3_S2> SmartProjectionPose3Factor;
+typedef gtsam::SmartProjectionPoseFactor<gtsam::Cal3_S2> SmartProjectionPose3Factor;
 
 
 #include <gtsam/slam/StereoFactor.h>
@@ -2429,18 +2483,18 @@ class ConstantBias {
 class PoseVelocityBias{
     PoseVelocityBias(const gtsam::Pose3& pose, Vector velocity, const gtsam::imuBias::ConstantBias& bias);
   };
-class ImuFactorPreintegratedMeasurements {
+class PreintegratedImuMeasurements {
   // Standard Constructor
-  ImuFactorPreintegratedMeasurements(const gtsam::imuBias::ConstantBias& bias, Matrix measuredAccCovariance,Matrix measuredOmegaCovariance, Matrix integrationErrorCovariance, bool use2ndOrderIntegration);
+  PreintegratedImuMeasurements(const gtsam::imuBias::ConstantBias& bias, Matrix measuredAccCovariance,Matrix measuredOmegaCovariance, Matrix integrationErrorCovariance, bool use2ndOrderIntegration);
-  ImuFactorPreintegratedMeasurements(const gtsam::imuBias::ConstantBias& bias, Matrix measuredAccCovariance,Matrix measuredOmegaCovariance, Matrix integrationErrorCovariance);
+  PreintegratedImuMeasurements(const gtsam::imuBias::ConstantBias& bias, Matrix measuredAccCovariance,Matrix measuredOmegaCovariance, Matrix integrationErrorCovariance);
-  // ImuFactorPreintegratedMeasurements(const gtsam::ImuFactorPreintegratedMeasurements& rhs);
+  // PreintegratedImuMeasurements(const gtsam::PreintegratedImuMeasurements& rhs);
 
   // Testable
   void print(string s) const;
-  bool equals(const gtsam::ImuFactorPreintegratedMeasurements& expected, double tol);
+  bool equals(const gtsam::PreintegratedImuMeasurements& expected, double tol);
 
   double deltaTij() const;
-  Matrix deltaRij() const;
+  gtsam::Rot3 deltaRij() const;
   Vector deltaPij() const;
   Vector deltaVij() const;
   Vector biasHatVector() const;
@@ -2453,25 +2507,24 @@ class ImuFactorPreintegratedMeasurements {
 
   // Standard Interface
   void integrateMeasurement(Vector measuredAcc, Vector measuredOmega, double deltaT);
-  void integrateMeasurement(Vector measuredAcc, Vector measuredOmega, double deltaT, const gtsam::Pose3& body_P_sensor);
   gtsam::PoseVelocityBias predict(const gtsam::Pose3& pose_i, Vector vel_i, const gtsam::imuBias::ConstantBias& bias,
       Vector gravity, Vector omegaCoriolis) const;
 };
 
 virtual class ImuFactor : gtsam::NonlinearFactor {
   ImuFactor(size_t pose_i, size_t vel_i, size_t pose_j, size_t vel_j, size_t bias,
-      const gtsam::ImuFactorPreintegratedMeasurements& preintegratedMeasurements, Vector gravity, Vector omegaCoriolis);
+      const gtsam::PreintegratedImuMeasurements& preintegratedMeasurements, Vector gravity, Vector omegaCoriolis);
   ImuFactor(size_t pose_i, size_t vel_i, size_t pose_j, size_t vel_j, size_t bias,
-      const gtsam::ImuFactorPreintegratedMeasurements& preintegratedMeasurements, Vector gravity, Vector omegaCoriolis,
+      const gtsam::PreintegratedImuMeasurements& preintegratedMeasurements, Vector gravity, Vector omegaCoriolis,
       const gtsam::Pose3& body_P_sensor);
   // Standard Interface
-  gtsam::ImuFactorPreintegratedMeasurements preintegratedMeasurements() const;
+  gtsam::PreintegratedImuMeasurements preintegratedMeasurements() const;
 };
 
 #include <gtsam/navigation/CombinedImuFactor.h>
-class CombinedImuFactorPreintegratedMeasurements {
+class PreintegratedCombinedMeasurements {
   // Standard Constructor
-  CombinedImuFactorPreintegratedMeasurements(
+  PreintegratedCombinedMeasurements(
       const gtsam::imuBias::ConstantBias& bias,
       Matrix measuredAccCovariance,
       Matrix measuredOmegaCovariance,
@@ -2479,7 +2532,7 @@ class CombinedImuFactorPreintegratedMeasurements {
       Matrix biasAccCovariance,
       Matrix biasOmegaCovariance,
       Matrix biasAccOmegaInit);
-  CombinedImuFactorPreintegratedMeasurements(
+  PreintegratedCombinedMeasurements(
       const gtsam::imuBias::ConstantBias& bias,
       Matrix measuredAccCovariance,
       Matrix measuredOmegaCovariance,
@@ -2488,14 +2541,14 @@ class CombinedImuFactorPreintegratedMeasurements {
       Matrix biasOmegaCovariance,
       Matrix biasAccOmegaInit,
       bool use2ndOrderIntegration);
-  // CombinedImuFactorPreintegratedMeasurements(const gtsam::CombinedImuFactorPreintegratedMeasurements& rhs);
+  // PreintegratedCombinedMeasurements(const gtsam::PreintegratedCombinedMeasurements& rhs);
 
   // Testable
   void print(string s) const;
-  bool equals(const gtsam::CombinedImuFactorPreintegratedMeasurements& expected, double tol);
+  bool equals(const gtsam::PreintegratedCombinedMeasurements& expected, double tol);
 
   double deltaTij() const;
-  Matrix deltaRij() const;
+  gtsam::Rot3 deltaRij() const;
   Vector deltaPij() const;
   Vector deltaVij() const;
   Vector biasHatVector() const;
@@ -2508,53 +2561,51 @@ class CombinedImuFactorPreintegratedMeasurements {
 
   // Standard Interface
   void integrateMeasurement(Vector measuredAcc, Vector measuredOmega, double deltaT);
-  void integrateMeasurement(Vector measuredAcc, Vector measuredOmega, double deltaT, const gtsam::Pose3& body_P_sensor);
   gtsam::PoseVelocityBias predict(const gtsam::Pose3& pose_i, Vector vel_i, const gtsam::imuBias::ConstantBias& bias,
       Vector gravity, Vector omegaCoriolis) const;
 };
 
 virtual class CombinedImuFactor : gtsam::NonlinearFactor {
   CombinedImuFactor(size_t pose_i, size_t vel_i, size_t pose_j, size_t vel_j, size_t bias_i, size_t bias_j,
-      const gtsam::CombinedImuFactorPreintegratedMeasurements& CombinedPreintegratedMeasurements, Vector gravity, Vector omegaCoriolis);
+      const gtsam::PreintegratedCombinedMeasurements& CombinedPreintegratedMeasurements, Vector gravity, Vector omegaCoriolis);
   // Standard Interface
-  gtsam::CombinedImuFactorPreintegratedMeasurements preintegratedMeasurements() const;
+  gtsam::PreintegratedCombinedMeasurements preintegratedMeasurements() const;
 };
 
 #include <gtsam/navigation/AHRSFactor.h>
-class AHRSFactorPreintegratedMeasurements {
+class PreintegratedAhrsMeasurements {
   // Standard Constructor
-  AHRSFactorPreintegratedMeasurements(Vector bias, Matrix measuredOmegaCovariance);
+  PreintegratedAhrsMeasurements(Vector bias, Matrix measuredOmegaCovariance);
-  AHRSFactorPreintegratedMeasurements(Vector bias, Matrix measuredOmegaCovariance);
+  PreintegratedAhrsMeasurements(Vector bias, Matrix measuredOmegaCovariance);
-  AHRSFactorPreintegratedMeasurements(const gtsam::AHRSFactorPreintegratedMeasurements& rhs);
+  PreintegratedAhrsMeasurements(const gtsam::PreintegratedAhrsMeasurements& rhs);
 
   // Testable
   void print(string s) const;
-  bool equals(const gtsam::AHRSFactorPreintegratedMeasurements& expected, double tol);
+  bool equals(const gtsam::PreintegratedAhrsMeasurements& expected, double tol);
 
   // get Data
-  Matrix deltaRij() const;
+  gtsam::Rot3 deltaRij() const;
   double deltaTij() const;
   Vector biasHat() const;
 
   // Standard Interface
   void integrateMeasurement(Vector measuredOmega, double deltaT);
-  void integrateMeasurement(Vector measuredOmega, double deltaT, const gtsam::Pose3& body_P_sensor);
   void resetIntegration() ;
 };
 
 virtual class AHRSFactor : gtsam::NonlinearFactor {
   AHRSFactor(size_t rot_i, size_t rot_j,size_t bias,
-      const gtsam::AHRSFactorPreintegratedMeasurements& preintegratedMeasurements, Vector omegaCoriolis);
+      const gtsam::PreintegratedAhrsMeasurements& preintegratedMeasurements, Vector omegaCoriolis);
   AHRSFactor(size_t rot_i, size_t rot_j, size_t bias,
-      const gtsam::AHRSFactorPreintegratedMeasurements& preintegratedMeasurements, Vector omegaCoriolis,
+      const gtsam::PreintegratedAhrsMeasurements& preintegratedMeasurements, Vector omegaCoriolis,
       const gtsam::Pose3& body_P_sensor);
 
   // Standard Interface
-  gtsam::AHRSFactorPreintegratedMeasurements preintegratedMeasurements() const;
+  gtsam::PreintegratedAhrsMeasurements preintegratedMeasurements() const;
   Vector evaluateError(const gtsam::Rot3& rot_i, const gtsam::Rot3& rot_j,
       Vector bias) const;
   gtsam::Rot3 predict(const gtsam::Rot3& rot_i, Vector bias,
-      const gtsam::AHRSFactorPreintegratedMeasurements& preintegratedMeasurements,
+      const gtsam::PreintegratedAhrsMeasurements& preintegratedMeasurements,
       Vector omegaCoriolis) const;
 };
 

gtsam/3rdparty/CMakeLists.txt

@@ -58,10 +58,10 @@ add_subdirectory(ceres)
 include(GeographicLib/cmake/FindGeographicLib.cmake)
 
 # Set up the option to install GeographicLib
-if(GEOGRAPHICLIB_FOUND)
+if(GEOGRAPHICLIB-NOTFOUND)
-  set(install_geographiclib_default OFF)
-else()
   set(install_geographiclib_default ON)
+else()
+  set(install_geographiclib_default OFF)
 endif()
 option(GTSAM_INSTALL_GEOGRAPHICLIB "Build and install the 3rd-party library GeographicLib" ${install_geographiclib_default})
 

gtsam/3rdparty/Eigen/.hg_archival.txt

@@ -1,4 +1,4 @@
 repo: 8a21fd850624c931e448cbcfb38168cb2717c790
-node: ffa86ffb557094721ca71dcea6aed2651b9fd610
+node: b30b87236a1b1552af32ac34075ee5696a9b5a33
 branch: 3.2
-tag: 3.2.0
+tag: 3.2.7

gtsam/3rdparty/Eigen/.hgtags

@@ -23,3 +23,10 @@ bf4cb8c934fa3a79f45f1e629610f0225e93e493 3.1.0-rc2
 da195914abcc1d739027cbee7c52077aab30b336 3.2-beta1
 4b687cad1d23066f66863f4f87298447298443df 3.2-rc1
 1eeda7b1258bcd306018c0738e2b6a8543661141 3.2-rc2
+ffa86ffb557094721ca71dcea6aed2651b9fd610 3.2.0
+6b38706d90a9fe182e66ab88477b3dbde34b9f66 3.2.1
+1306d75b4a21891e59ff9bd96678882cf831e39f 3.2.2
+36fd1ba04c120cfdd90f3e4cede47f43b21d19ad 3.2.3
+10219c95fe653d4962aa9db4946f6fbea96dd740 3.2.4
+bdd17ee3b1b3a166cd5ec36dcad4fc1f3faf774a 3.2.5
+c58038c56923e0fd86de3ded18e03df442e66dfb 3.2.6

gtsam/3rdparty/Eigen/CMakeLists.txt

@@ -301,7 +301,7 @@ if(EIGEN_INCLUDE_INSTALL_DIR)
   )
 else()
   set(INCLUDE_INSTALL_DIR
-    "${CMAKE_INSTALL_PREFIX}/include/eigen3"
+    "include/eigen3"
     CACHE INTERNAL
     "The directory where we install the header files (internal)"
   )
@@ -404,7 +404,7 @@ if(cmake_generator_tolower MATCHES "makefile")
   message(STATUS "make install  | Install to ${CMAKE_INSTALL_PREFIX}. To change that:")
   message(STATUS "              |     cmake . -DCMAKE_INSTALL_PREFIX=yourpath")
   message(STATUS "              |   Eigen headers will then be installed to:")
-  message(STATUS "              |     ${INCLUDE_INSTALL_DIR}")
+  message(STATUS "              |     ${CMAKE_INSTALL_PREFIX}/${INCLUDE_INSTALL_DIR}")
   message(STATUS "              |   To install Eigen headers to a separate location, do:")
   message(STATUS "              |     cmake . -DEIGEN_INCLUDE_INSTALL_DIR=yourpath")
   message(STATUS "make doc      | Generate the API documentation, requires Doxygen & LaTeX")

gtsam/3rdparty/Eigen/Eigen/Core

@@ -123,7 +123,7 @@
     #undef bool
     #undef vector
     #undef pixel
-  #elif defined  __ARM_NEON__
+  #elif defined  __ARM_NEON
     #define EIGEN_VECTORIZE
     #define EIGEN_VECTORIZE_NEON
     #include <arm_neon.h>

gtsam/3rdparty/Eigen/Eigen/SparseCore

@@ -14,7 +14,7 @@
 /** 
   * \defgroup SparseCore_Module SparseCore module
   *
-  * This module provides a sparse matrix representation, and basic associatd matrix manipulations
+  * This module provides a sparse matrix representation, and basic associated matrix manipulations
   * and operations.
   *
   * See the \ref TutorialSparse "Sparse tutorial"

gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LDLT.h

@@ -235,6 +235,11 @@ template<typename _MatrixType, int _UpLo> class LDLT
     }
 
   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.
@@ -434,6 +439,8 @@ 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();
 
@@ -442,6 +449,7 @@ 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);
 
@@ -456,7 +464,7 @@ 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)
 {
   const Index size = w.rows();
   if (m_isInitialized)
@@ -502,7 +510,6 @@ struct solve_retval<LDLT<_MatrixType,_UpLo>, Rhs>
     using std::abs;
     using std::max;
     typedef typename LDLTType::MatrixType MatrixType;
-    typedef typename LDLTType::Scalar Scalar;
     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

gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LLT.h

@@ -174,6 +174,12 @@ template<typename _MatrixType, int _UpLo> class LLT
     LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
 
   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.
@@ -283,7 +289,7 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
         return k;
       mat.coeffRef(k,k) = x = sqrt(x);
       if (k>0 && rs>0) A21.noalias() -= A20 * A10.adjoint();
-      if (rs>0) A21 *= RealScalar(1)/x;
+      if (rs>0) A21 /= x;
     }
     return -1;
   }
@@ -384,6 +390,8 @@ 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);

gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LLT_MKL.h

@@ -60,7 +60,7 @@ template<> struct mkl_llt<EIGTYPE> \
     lda = m.outerStride(); \
 \
     info = LAPACKE_##MKLPREFIX##potrf( matrix_order, uplo, size, (MKLTYPE*)a, lda ); \
-    info = (info==0) ? -1 : 1; \
+    info = (info==0) ? -1 : info>0 ? info-1 : size; \
     return info; \
   } \
 }; \

gtsam/3rdparty/Eigen/Eigen/src/CholmodSupport/CholmodSupport.h

@@ -78,7 +78,7 @@ cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat)
   {
     res.itype = CHOLMOD_INT;
   }
-  else if (internal::is_same<_Index,UF_long>::value)
+  else if (internal::is_same<_Index,SuiteSparse_long>::value)
   {
     res.itype = CHOLMOD_LONG;
   }
@@ -395,7 +395,7 @@ class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimpl
     CholmodSimplicialLLT(const MatrixType& matrix) : Base()
     {
       init();
-      compute(matrix);
+      Base::compute(matrix);
     }
 
     ~CholmodSimplicialLLT() {}
@@ -442,7 +442,7 @@ class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimp
     CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
     {
       init();
-      compute(matrix);
+      Base::compute(matrix);
     }
 
     ~CholmodSimplicialLDLT() {}
@@ -487,7 +487,7 @@ class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSuper
     CholmodSupernodalLLT(const MatrixType& matrix) : Base()
     {
       init();
-      compute(matrix);
+      Base::compute(matrix);
     }
 
     ~CholmodSupernodalLLT() {}
@@ -534,7 +534,7 @@ class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecom
     CholmodDecomposition(const MatrixType& matrix) : Base()
     {
       init();
-      compute(matrix);
+      Base::compute(matrix);
     }
 
     ~CholmodDecomposition() {}

gtsam/3rdparty/Eigen/Eigen/src/Core/Array.h

@@ -124,6 +124,21 @@ class Array
     }
 #endif
 
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
+    Array(Array&& other)
+      : Base(std::move(other))
+    {
+      Base::_check_template_params();
+      if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
+        Base::_set_noalias(other);
+    }
+    Array& operator=(Array&& other)
+    {
+      other.swap(*this);
+      return *this;
+    }
+#endif
+
     /** Constructs a vector or row-vector with given dimension. \only_for_vectors
       *
       * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,

gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayBase.h

@@ -46,9 +46,6 @@ template<typename Derived> class ArrayBase
 
     typedef ArrayBase Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl;
 
-    using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
-                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;
@@ -56,6 +53,7 @@ template<typename Derived> class ArrayBase
     typedef typename NumTraits<Scalar>::Real RealScalar;
 
     typedef DenseBase<Derived> Base;
+    using Base::operator*;
     using Base::RowsAtCompileTime;
     using Base::ColsAtCompileTime;
     using Base::SizeAtCompileTime;

gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayWrapper.h

@@ -29,6 +29,11 @@ struct traits<ArrayWrapper<ExpressionType> >
   : public traits<typename remove_all<typename ExpressionType::Nested>::type >
 {
   typedef ArrayXpr XprKind;
+  // Let's remove NestByRefBit
+  enum {
+    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
+    Flags = Flags0 & ~NestByRefBit
+  };
 };
 }
 
@@ -149,6 +154,11 @@ struct traits<MatrixWrapper<ExpressionType> >
  : public traits<typename remove_all<typename ExpressionType::Nested>::type >
 {
   typedef MatrixXpr XprKind;
+  // Let's remove NestByRefBit
+  enum {
+    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
+    Flags = Flags0 & ~NestByRefBit
+  };
 };
 }
 

gtsam/3rdparty/Eigen/Eigen/src/Core/Assign.h

@@ -439,19 +439,26 @@ struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Ve
   typedef typename Derived1::Index Index;
   static inline void run(Derived1 &dst, const Derived2 &src)
   {
-    typedef packet_traits<typename Derived1::Scalar> PacketTraits;
+    typedef typename Derived1::Scalar Scalar;
+    typedef packet_traits<Scalar> PacketTraits;
     enum {
       packetSize = PacketTraits::size,
       alignable = PacketTraits::AlignedOnScalar,
-      dstAlignment = alignable ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
+      dstIsAligned = assign_traits<Derived1,Derived2>::DstIsAligned,
+      dstAlignment = alignable ? Aligned : int(dstIsAligned),
       srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
     };
+    const Scalar *dst_ptr = &dst.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 assign_impl<Derived1,Derived2,DefaultTraversal,NoUnrolling>::run(dst, src);
+    }
     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
+    Index alignedStart = ((!alignable) || bool(dstIsAligned)) ? 0 : internal::first_aligned(dst_ptr, innerSize);
-                       : internal::first_aligned(&dst.coeffRef(0,0), innerSize);
 
     for(Index outer = 0; outer < outerSize; ++outer)
     {

gtsam/3rdparty/Eigen/Eigen/src/Core/Block.h

@@ -66,8 +66,9 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
                          : ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
                          : int(traits<XprType>::MaxColsAtCompileTime),
     XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
-    IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
+    IsDense = is_same<StorageKind,Dense>::value,
-               : (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
+    IsRowMajor = (IsDense&&MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
+               : (IsDense&&MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
                : XprTypeIsRowMajor,
     HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor),
     InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),

gtsam/3rdparty/Eigen/Eigen/src/Core/CommaInitializer.h.orig

@@ -1,154 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 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
-// 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_COMMAINITIALIZER_H
-#define EIGEN_COMMAINITIALIZER_H
-
-namespace Eigen { 
-
-/** \class CommaInitializer
-  * \ingroup Core_Module
-  *
-  * \brief Helper class used by the comma initializer operator
-  *
-  * This class is internally used to implement the comma initializer feature. It is
-  * the return type of MatrixBase::operator<<, and most of the time this is the only
-  * way it is used.
-  *
-  * \sa \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
-  */
-template<typename XprType>
-struct CommaInitializer
-{
-  typedef typename XprType::Scalar Scalar;
-  typedef typename XprType::Index Index;
-
-  inline CommaInitializer(XprType& xpr, const Scalar& s)
-    : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1)
-  {
-    m_xpr.coeffRef(0,0) = s;
-  }
-
-  template<typename OtherDerived>
-  inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
-    : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows())
-  {
-    m_xpr.block(0, 0, other.rows(), other.cols()) = other;
-  }
-
-  /* Copy/Move constructor which transfers ownership. This is crucial in 
-   * absence of return value optimization to avoid assertions during destruction. */
-  // FIXME in C++11 mode this could be replaced by a proper RValue constructor
-  inline CommaInitializer(const CommaInitializer& o)
-  : m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) {
-    // Mark original object as finished. In absence of R-value references we need to const_cast:
-    const_cast<CommaInitializer&>(o).m_row = m_xpr.rows();
-    const_cast<CommaInitializer&>(o).m_col = m_xpr.cols();
-    const_cast<CommaInitializer&>(o).m_currentBlockRows = 0;
-  }
-
-  /* inserts a scalar value in the target matrix */
-  CommaInitializer& operator,(const Scalar& s)
-  {
-    if (m_col==m_xpr.cols())
-    {
-      m_row+=m_currentBlockRows;
-      m_col = 0;
-      m_currentBlockRows = 1;
-      eigen_assert(m_row<m_xpr.rows()
-        && "Too many rows passed to comma initializer (operator<<)");
-    }
-    eigen_assert(m_col<m_xpr.cols()
-      && "Too many coefficients passed to comma initializer (operator<<)");
-    eigen_assert(m_currentBlockRows==1);
-    m_xpr.coeffRef(m_row, m_col++) = s;
-    return *this;
-  }
-
-  /* inserts a matrix expression in the target matrix */
-  template<typename OtherDerived>
-  CommaInitializer& operator,(const DenseBase<OtherDerived>& other)
-  {
-    if(other.cols()==0 || other.rows()==0)
-      return *this;
-    if (m_col==m_xpr.cols())
-    {
-      m_row+=m_currentBlockRows;
-      m_col = 0;
-      m_currentBlockRows = other.rows();
-      eigen_assert(m_row+m_currentBlockRows<=m_xpr.rows()
-        && "Too many rows passed to comma initializer (operator<<)");
-    }
-    eigen_assert(m_col<m_xpr.cols()
-      && "Too many coefficients passed to comma initializer (operator<<)");
-    eigen_assert(m_currentBlockRows==other.rows());
-    if (OtherDerived::SizeAtCompileTime != Dynamic)
-      m_xpr.template block<OtherDerived::RowsAtCompileTime != Dynamic ? OtherDerived::RowsAtCompileTime : 1,
-                              OtherDerived::ColsAtCompileTime != Dynamic ? OtherDerived::ColsAtCompileTime : 1>
-                    (m_row, m_col) = other;
-    else
-      m_xpr.block(m_row, m_col, other.rows(), other.cols()) = other;
-    m_col += other.cols();
-    return *this;
-  }
-
-  inline ~CommaInitializer()
-  {
-    eigen_assert((m_row+m_currentBlockRows) == m_xpr.rows()
-         && m_col == m_xpr.cols()
-         && "Too few coefficients passed to comma initializer (operator<<)");
-  }
-
-  /** \returns the built matrix once all its coefficients have been set.
-    * Calling finished is 100% optional. Its purpose is to write expressions
-    * like this:
-    * \code
-    * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
-    * \endcode
-    */
-  inline XprType& finished() { return m_xpr; }
-
-  XprType& m_xpr;   // target expression
-  Index m_row;              // current row id
-  Index m_col;              // current col id
-  Index m_currentBlockRows; // current block height
-};
-
-/** \anchor MatrixBaseCommaInitRef
-  * Convenient operator to set the coefficients of a matrix.
-  *
-  * The coefficients must be provided in a row major order and exactly match
-  * the size of the matrix. Otherwise an assertion is raised.
-  *
-  * Example: \include MatrixBase_set.cpp
-  * Output: \verbinclude MatrixBase_set.out
-  * 
-  * \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary order.
-  *
-  * \sa CommaInitializer::finished(), class CommaInitializer
-  */
-template<typename Derived>
-inline CommaInitializer<Derived> DenseBase<Derived>::operator<< (const Scalar& s)
-{
-  return CommaInitializer<Derived>(*static_cast<Derived*>(this), s);
-}
-
-/** \sa operator<<(const Scalar&) */
-template<typename Derived>
-template<typename OtherDerived>
-inline CommaInitializer<Derived>
-DenseBase<Derived>::operator<<(const DenseBase<OtherDerived>& other)
-{
-  return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_COMMAINITIALIZER_H

gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseBinaryOp.h

@@ -81,7 +81,8 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
         )
      ),
     Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
-    CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + functor_traits<BinaryOp>::Cost
+    Cost0 = EIGEN_ADD_COST(LhsCoeffReadCost,RhsCoeffReadCost),
+    CoeffReadCost = EIGEN_ADD_COST(Cost0,functor_traits<BinaryOp>::Cost)
   };
 };
 } // end namespace internal

gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseUnaryOp.h

@@ -47,7 +47,7 @@ struct traits<CwiseUnaryOp<UnaryOp, XprType> >
     Flags = _XprTypeNested::Flags & (
       HereditaryBits | LinearAccessBit | AlignedBit
       | (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
-    CoeffReadCost = _XprTypeNested::CoeffReadCost + functor_traits<UnaryOp>::Cost
+    CoeffReadCost = EIGEN_ADD_COST(_XprTypeNested::CoeffReadCost, functor_traits<UnaryOp>::Cost)
   };
 };
 }

gtsam/3rdparty/Eigen/Eigen/src/Core/DenseBase.h

@@ -41,14 +41,13 @@ static inline void check_DenseIndex_is_signed() {
 template<typename Derived> class DenseBase
 #ifndef EIGEN_PARSED_BY_DOXYGEN
   : public internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
-                                     typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>
+                                            typename NumTraits<typename internal::traits<Derived>::Scalar>::Real,
+                                            DenseCoeffsBase<Derived> >
 #else
   : public DenseCoeffsBase<Derived>
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 {
   public:
-    using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
-                typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
 
     class InnerIterator;
 
@@ -63,8 +62,9 @@ template<typename Derived> class DenseBase
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef internal::special_scalar_op_base<Derived,Scalar,RealScalar, DenseCoeffsBase<Derived> > Base;
 
-    typedef DenseCoeffsBase<Derived> Base;
+    using Base::operator*;
     using Base::derived;
     using Base::const_cast_derived;
     using Base::rows;
@@ -183,10 +183,6 @@ template<typename Derived> class DenseBase
     /** \returns the number of nonzero coefficients which is in practice the number
       * of stored coefficients. */
     inline Index nonZeros() const { return size(); }
-    /** \returns true if either the number of rows or the number of columns is equal to 1.
-      * In other words, this function returns
-      * \code rows()==1 || cols()==1 \endcode
-      * \sa rows(), cols(), IsVectorAtCompileTime. */
 
     /** \returns the outer size.
       *
@@ -266,11 +262,13 @@ template<typename Derived> class DenseBase
     template<typename OtherDerived>
     Derived& operator=(const ReturnByValue<OtherDerived>& func);
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal Copies \a other into *this without evaluating other. \returns a reference to *this. */
-    /** Copies \a other into *this without evaluating other. \returns a reference to *this. */
     template<typename OtherDerived>
     Derived& lazyAssign(const DenseBase<OtherDerived>& other);
-#endif // not EIGEN_PARSED_BY_DOXYGEN
+
+    /** \internal Evaluates \a other into *this. \returns a reference to *this. */
+    template<typename OtherDerived>
+    Derived& lazyAssign(const ReturnByValue<OtherDerived>& other);
 
     CommaInitializer<Derived> operator<< (const Scalar& s);
 
@@ -462,8 +460,10 @@ template<typename Derived> class DenseBase
     template<int p> RealScalar lpNorm() const;
 
     template<int RowFactor, int ColFactor>
-    const Replicate<Derived,RowFactor,ColFactor> replicate() const;
+    inline const Replicate<Derived,RowFactor,ColFactor> replicate() const;
-    const Replicate<Derived,Dynamic,Dynamic> replicate(Index rowFacor,Index colFactor) const;
+    
+    typedef Replicate<Derived,Dynamic,Dynamic> ReplicateReturnType;
+    inline const ReplicateReturnType replicate(Index rowFacor,Index colFactor) const;
 
     typedef Reverse<Derived, BothDirections> ReverseReturnType;
     typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType;

gtsam/3rdparty/Eigen/Eigen/src/Core/DenseStorage.h

@@ -122,33 +122,41 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
 {
     internal::plain_array<T,Size,_Options> m_data;
   public:
-    inline DenseStorage() {}
+    DenseStorage() {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()) {}
-    inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
+    DenseStorage(const DenseStorage& other) : m_data(other.m_data) {}
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
+    DenseStorage& operator=(const DenseStorage& other)
-    static inline DenseIndex rows(void) {return _Rows;}
+    {
-    static inline DenseIndex cols(void) {return _Cols;}
+      if (this != &other) m_data = other.m_data;
-    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+      return *this;
-    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    }
-    inline const T *data() const { return m_data.array; }
+    DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
-    inline T *data() { return m_data.array; }
+    void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
+    static DenseIndex rows(void) {return _Rows;}
+    static DenseIndex cols(void) {return _Cols;}
+    void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    const T *data() const { return m_data.array; }
+    T *data() { return m_data.array; }
 };
 
 // null matrix
 template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
 {
   public:
-    inline DenseStorage() {}
+    DenseStorage() {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert) {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert) {}
-    inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
+    DenseStorage(const DenseStorage&) {}
-    inline void swap(DenseStorage& ) {}
+    DenseStorage& operator=(const DenseStorage&) { return *this; }
-    static inline DenseIndex rows(void) {return _Rows;}
+    DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
-    static inline DenseIndex cols(void) {return _Cols;}
+    void swap(DenseStorage& ) {}
-    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    static DenseIndex rows(void) {return _Rows;}
-    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    static DenseIndex cols(void) {return _Cols;}
-    inline const T *data() const { return 0; }
+    void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
-    inline T *data() { return 0; }
+    void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    const T *data() const { return 0; }
+    T *data() { return 0; }
 };
 
 // more specializations for null matrices; these are necessary to resolve ambiguities
@@ -168,18 +176,29 @@ template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic
     DenseIndex m_rows;
     DenseIndex m_cols;
   public:
-    inline DenseStorage() : m_rows(0), m_cols(0) {}
+    DenseStorage() : m_rows(0), m_cols(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
-    inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
+    DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {}
-    inline void swap(DenseStorage& other)
+    DenseStorage& operator=(const DenseStorage& other)
+    {
+      if (this != &other)
+      {
+        m_data = other.m_data;
+        m_rows = other.m_rows;
+        m_cols = other.m_cols;
+      }
+      return *this;
+    }
+    DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
+    void swap(DenseStorage& other)
     { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
-    inline DenseIndex rows() const {return m_rows;}
+    DenseIndex rows() const {return m_rows;}
-    inline DenseIndex cols() const {return m_cols;}
+    DenseIndex cols() const {return m_cols;}
-    inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
+    void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
-    inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
+    void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
-    inline const T *data() const { return m_data.array; }
+    const T *data() const { return m_data.array; }
-    inline T *data() { return m_data.array; }
+    T *data() { return m_data.array; }
 };
 
 // dynamic-size matrix with fixed-size storage and fixed width
@@ -188,17 +207,27 @@ template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Si
     internal::plain_array<T,Size,_Options> m_data;
     DenseIndex m_rows;
   public:
-    inline DenseStorage() : m_rows(0) {}
+    DenseStorage() : m_rows(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
-    inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
+    DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {}
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    DenseStorage& operator=(const DenseStorage& other)
-    inline DenseIndex rows(void) const {return m_rows;}
+    {
-    inline DenseIndex cols(void) const {return _Cols;}
+      if (this != &other)
-    inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+      {
-    inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+        m_data = other.m_data;
-    inline const T *data() const { return m_data.array; }
+        m_rows = other.m_rows;
-    inline T *data() { return m_data.array; }
+      }
+      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); }
+    DenseIndex rows(void) const {return m_rows;}
+    DenseIndex cols(void) const {return _Cols;}
+    void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+    void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+    const T *data() const { return m_data.array; }
+    T *data() { return m_data.array; }
 };
 
 // dynamic-size matrix with fixed-size storage and fixed height
@@ -207,17 +236,27 @@ template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Si
     internal::plain_array<T,Size,_Options> m_data;
     DenseIndex m_cols;
   public:
-    inline DenseStorage() : m_cols(0) {}
+    DenseStorage() : m_cols(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
-    inline DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
+    DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {}
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    DenseStorage& operator=(const DenseStorage& other)
-    inline DenseIndex rows(void) const {return _Rows;}
+    {
-    inline DenseIndex cols(void) const {return m_cols;}
+      if (this != &other)
-    inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
+      {
-    inline void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
+        m_data = other.m_data;
-    inline const T *data() const { return m_data.array; }
+        m_cols = other.m_cols;
-    inline T *data() { return m_data.array; }
+      }
+      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); }
+    DenseIndex rows(void) const {return _Rows;}
+    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; }
+    const T *data() const { return m_data.array; }
+    T *data() { return m_data.array; }
 };
 
 // purely dynamic matrix.
@@ -227,18 +266,35 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
     DenseIndex m_rows;
     DenseIndex m_cols;
   public:
-    inline DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
+    DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
        : m_data(0), m_rows(0), m_cols(0) {}
-    inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+    DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
       : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows), m_cols(nbCols)
     { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
-    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
-    inline void swap(DenseStorage& other)
+    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;
+    }
+    DenseStorage& operator=(DenseStorage&& other)
+    {
+      using std::swap;
+      swap(m_data, other.m_data);
+      swap(m_rows, other.m_rows);
+      swap(m_cols, other.m_cols);
+      return *this;
+    }
+#endif
+    ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
+    void swap(DenseStorage& other)
     { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
-    inline DenseIndex rows(void) const {return m_rows;}
+    DenseIndex rows(void) const {return m_rows;}
-    inline DenseIndex cols(void) const {return m_cols;}
+    DenseIndex cols(void) const {return m_cols;}
-    inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+    void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
       m_rows = nbRows;
@@ -258,8 +314,11 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
       m_rows = nbRows;
       m_cols = nbCols;
     }
-    inline const T *data() const { return m_data; }
+    const T *data() const { return m_data; }
-    inline T *data() { return m_data; }
+    T *data() { return m_data; }
+  private:
+    DenseStorage(const DenseStorage&);
+    DenseStorage& operator=(const DenseStorage&);
 };
 
 // matrix with dynamic width and fixed height (so that matrix has dynamic size).
@@ -268,15 +327,30 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
     T *m_data;
     DenseIndex m_cols;
   public:
-    inline DenseStorage() : m_data(0), m_cols(0) {}
+    DenseStorage() : m_data(0), m_cols(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
-    inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
+    DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
     { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
-    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    DenseStorage(DenseStorage&& other)
-    static inline DenseIndex rows(void) {return _Rows;}
+      : m_data(std::move(other.m_data))
-    inline DenseIndex cols(void) const {return m_cols;}
+      , m_cols(std::move(other.m_cols))
-    inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
+    {
+      other.m_data = nullptr;
+    }
+    DenseStorage& operator=(DenseStorage&& other)
+    {
+      using std::swap;
+      swap(m_data, other.m_data);
+      swap(m_cols, other.m_cols);
+      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); }
+    static DenseIndex rows(void) {return _Rows;}
+    DenseIndex cols(void) const {return m_cols;}
+    void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
       m_cols = nbCols;
@@ -294,8 +368,11 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
       }
       m_cols = nbCols;
     }
-    inline const T *data() const { return m_data; }
+    const T *data() const { return m_data; }
-    inline T *data() { return m_data; }
+    T *data() { return m_data; }
+  private:
+    DenseStorage(const DenseStorage&);
+    DenseStorage& operator=(const DenseStorage&);
 };
 
 // matrix with dynamic height and fixed width (so that matrix has dynamic size).
@@ -304,15 +381,30 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
     T *m_data;
     DenseIndex m_rows;
   public:
-    inline DenseStorage() : m_data(0), m_rows(0) {}
+    DenseStorage() : m_data(0), m_rows(0) {}
-    inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
-    inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
+    DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
     { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
-    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
-    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    DenseStorage(DenseStorage&& other)
-    inline DenseIndex rows(void) const {return m_rows;}
+      : m_data(std::move(other.m_data))
-    static inline DenseIndex cols(void) {return _Cols;}
+      , m_rows(std::move(other.m_rows))
-    inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
+    {
+      other.m_data = nullptr;
+    }
+    DenseStorage& operator=(DenseStorage&& other)
+    {
+      using std::swap;
+      swap(m_data, other.m_data);
+      swap(m_rows, other.m_rows);
+      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); }
+    DenseIndex rows(void) const {return m_rows;}
+    static DenseIndex cols(void) {return _Cols;}
+    void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
       m_rows = nbRows;
@@ -330,8 +422,11 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
       }
       m_rows = nbRows;
     }
-    inline const T *data() const { return m_data; }
+    const T *data() const { return m_data; }
-    inline T *data() { return m_data; }
+    T *data() { return m_data; }
+  private:
+    DenseStorage(const DenseStorage&);
+    DenseStorage& operator=(const DenseStorage&);
 };
 
 } // end namespace Eigen

gtsam/3rdparty/Eigen/Eigen/src/Core/Diagonal.h

@@ -190,18 +190,18 @@ 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

gtsam/3rdparty/Eigen/Eigen/src/Core/DiagonalProduct.h

@@ -34,8 +34,9 @@ struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
     _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),
+    Flags = ((HereditaryBits|_LinearAccessMask|AlignedBit) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0),//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit),
-    CoeffReadCost = NumTraits<Scalar>::MulCost + MatrixType::CoeffReadCost + DiagonalType::DiagonalVectorType::CoeffReadCost
+    Cost0 = EIGEN_ADD_COST(NumTraits<Scalar>::MulCost, MatrixType::CoeffReadCost),
+    CoeffReadCost = EIGEN_ADD_COST(Cost0,DiagonalType::DiagonalVectorType::CoeffReadCost)
   };
 };
 }

gtsam/3rdparty/Eigen/Eigen/src/Core/Functors.h

@@ -259,6 +259,47 @@ template<> struct functor_traits<scalar_boolean_or_op> {
   };
 };
 
+/** \internal
+  * \brief Template functors for comparison of two scalars
+  * \todo Implement packet-comparisons
+  */
+template<typename Scalar, ComparisonName cmp> struct scalar_cmp_op;
+
+template<typename Scalar, ComparisonName cmp>
+struct functor_traits<scalar_cmp_op<Scalar, cmp> > {
+  enum {
+    Cost = NumTraits<Scalar>::AddCost,
+    PacketAccess = false
+  };
+};
+
+template<ComparisonName Cmp, typename Scalar>
+struct result_of<scalar_cmp_op<Scalar, Cmp>(Scalar,Scalar)> {
+  typedef bool type;
+};
+
+
+template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_EQ> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a==b;}
+};
+template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_LT> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a<b;}
+};
+template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_LE> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a<=b;}
+};
+template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_UNORD> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return !(a<=b || b<=a);}
+};
+template<typename Scalar> struct scalar_cmp_op<Scalar, cmp_NEQ> {
+  EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op)
+  EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a!=b;}
+};
+
 // unary functors:
 
 /** \internal

gtsam/3rdparty/Eigen/Eigen/src/Core/GeneralProduct.h

@@ -232,7 +232,7 @@ EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest&
   // 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(j) * prod.lhs());
+    func(dest.col(j), prod.rhs().coeff(0,j) * prod.lhs());
 }
 
 // Row major
@@ -243,7 +243,7 @@ EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest&
   // 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) * prod.rhs());
+    func(dest.row(i), prod.lhs().coeff(i,0) * prod.rhs());
 }
 
 template<typename Lhs, typename Rhs>
@@ -257,7 +257,7 @@ 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 {};
+    template<typename T> struct is_row_major : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
     
   public:
     EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
@@ -281,22 +281,22 @@ class GeneralProduct<Lhs, Rhs, OuterProduct>
     
     template<typename Dest>
     inline void evalTo(Dest& dest) const {
-      internal::outer_product_selector_run(*this, dest, set(), IsRowMajor<Dest>());
+      internal::outer_product_selector_run(*this, dest, set(), is_row_major<Dest>());
     }
     
     template<typename Dest>
     inline void addTo(Dest& dest) const {
-      internal::outer_product_selector_run(*this, dest, add(), IsRowMajor<Dest>());
+      internal::outer_product_selector_run(*this, dest, add(), is_row_major<Dest>());
     }
 
     template<typename Dest>
     inline void subTo(Dest& dest) const {
-      internal::outer_product_selector_run(*this, dest, sub(), IsRowMajor<Dest>());
+      internal::outer_product_selector_run(*this, dest, sub(), is_row_major<Dest>());
     }
 
     template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
     {
-      internal::outer_product_selector_run(*this, dest, adds(alpha), IsRowMajor<Dest>());
+      internal::outer_product_selector_run(*this, dest, adds(alpha), is_row_major<Dest>());
     }
 };
 

gtsam/3rdparty/Eigen/Eigen/src/Core/MapBase.h

@@ -123,7 +123,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
       return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride());
     }
 
-    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();
@@ -157,7 +157,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
                                         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) % 16) == 0)
-                   && "data is not aligned");
+                   && "input pointer is not aligned on a 16 byte boundary");
     }
 
     PointerType m_data;
@@ -168,6 +168,7 @@ 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;
@@ -230,11 +231,13 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
 
     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

gtsam/3rdparty/Eigen/Eigen/src/Core/MathFunctions.h

@@ -294,7 +294,7 @@ struct hypot_impl
     RealScalar _x = abs(x);
     RealScalar _y = abs(y);
     RealScalar p = (max)(_x, _y);
-    if(p==RealScalar(0)) return 0;
+    if(p==RealScalar(0)) return RealScalar(0);
     RealScalar q = (min)(_x, _y);
     RealScalar qp = q/p;
     return p * sqrt(RealScalar(1) + qp*qp);

gtsam/3rdparty/Eigen/Eigen/src/Core/Matrix.h

@@ -211,6 +211,21 @@ class Matrix
       : Base(internal::constructor_without_unaligned_array_assert())
     { Base::_check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
 
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
+    Matrix(Matrix&& other)
+      : Base(std::move(other))
+    {
+      Base::_check_template_params();
+      if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
+        Base::_set_noalias(other);
+    }
+    Matrix& operator=(Matrix&& other)
+    {
+      other.swap(*this);
+      return *this;
+    }
+#endif
+
     /** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors
       *
       * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,

gtsam/3rdparty/Eigen/Eigen/src/Core/MatrixBase.h

@@ -159,13 +159,11 @@ template<typename Derived> class MatrixBase
     template<typename OtherDerived>
     Derived& operator=(const ReturnByValue<OtherDerived>& other);
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename ProductDerived, typename Lhs, typename Rhs>
     Derived& lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other);
 
     template<typename MatrixPower, typename Lhs, typename Rhs>
     Derived& lazyAssign(const MatrixPowerProduct<MatrixPower, Lhs,Rhs>& other);
-#endif // not EIGEN_PARSED_BY_DOXYGEN
 
     template<typename OtherDerived>
     Derived& operator+=(const MatrixBase<OtherDerived>& other);
@@ -215,7 +213,7 @@ template<typename Derived> class MatrixBase
 
     typedef Diagonal<Derived> DiagonalReturnType;
     DiagonalReturnType diagonal();
-	typedef typename internal::add_const<Diagonal<const Derived> >::type ConstDiagonalReturnType;
+    typedef typename internal::add_const<Diagonal<const Derived> >::type ConstDiagonalReturnType;
     ConstDiagonalReturnType diagonal() const;
 
     template<int Index> struct DiagonalIndexReturnType { typedef Diagonal<Derived,Index> Type; };
@@ -223,16 +221,12 @@ template<typename Derived> class MatrixBase
 
     template<int Index> typename DiagonalIndexReturnType<Index>::Type diagonal();
     template<int Index> typename ConstDiagonalIndexReturnType<Index>::Type diagonal() const;
+    
+    typedef Diagonal<Derived,DynamicIndex> DiagonalDynamicIndexReturnType;
+    typedef typename internal::add_const<Diagonal<const Derived,DynamicIndex> >::type ConstDiagonalDynamicIndexReturnType;
 
-    // Note: The "MatrixBase::" prefixes are added to help MSVC9 to match these declarations with the later implementations.
+    DiagonalDynamicIndexReturnType diagonal(Index index);
-    // On the other hand they confuse MSVC8...
+    ConstDiagonalDynamicIndexReturnType diagonal(Index index) const;
-    #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
-    typename DiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index);
-    typename ConstDiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index) const;
-    #endif
 
     #ifdef EIGEN2_SUPPORT
     template<unsigned int Mode> typename internal::eigen2_part_return_type<Derived, Mode>::type part();
@@ -446,6 +440,15 @@ template<typename Derived> class MatrixBase
     template<typename OtherScalar>
     void applyOnTheRight(Index p, Index q, const JacobiRotation<OtherScalar>& j);
 
+///////// SparseCore module /////////
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE const typename SparseMatrixBase<OtherDerived>::template CwiseProductDenseReturnType<Derived>::Type
+    cwiseProduct(const SparseMatrixBase<OtherDerived> &other) const
+    {
+      return other.cwiseProduct(derived());
+    }
+
 ///////// MatrixFunctions module /////////
 
     typedef typename internal::stem_function<Scalar>::type StemFunction;

gtsam/3rdparty/Eigen/Eigen/src/Core/PermutationMatrix.h

@@ -250,6 +250,35 @@ 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:
 
@@ -555,7 +584,10 @@ struct permut_matrix_product_retval
       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))
+      if(    is_same<MatrixTypeNestedCleaned,Dest>::value
+          && blas_traits<MatrixTypeNestedCleaned>::HasUsableDirectAccess
+          && blas_traits<Dest>::HasUsableDirectAccess
+          && extract_data(dst) == extract_data(m_matrix))
       {
         // apply the permutation inplace
         Matrix<bool,PermutationType::RowsAtCompileTime,1,0,PermutationType::MaxRowsAtCompileTime> mask(m_permutation.size());

gtsam/3rdparty/Eigen/Eigen/src/Core/PlainObjectBase.h

@@ -437,6 +437,36 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     }
 #endif
 
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
+    PlainObjectBase(PlainObjectBase&& other)
+      : m_storage( std::move(other.m_storage) )
+    {
+    }
+
+    PlainObjectBase& operator=(PlainObjectBase&& other)
+    {
+      using std::swap;
+      swap(m_storage, other.m_storage);
+      return *this;
+    }
+#endif
+
+    /** Copy constructor */
+    EIGEN_STRONG_INLINE PlainObjectBase(const PlainObjectBase& other)
+      : m_storage()
+    {
+      _check_template_params();
+      lazyAssign(other);
+    }
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE PlainObjectBase(const DenseBase<OtherDerived> &other)
+      : m_storage()
+    {
+      _check_template_params();
+      lazyAssign(other);
+    }
+
     EIGEN_STRONG_INLINE PlainObjectBase(Index a_size, Index nbRows, Index nbCols)
       : m_storage(a_size, nbRows, nbCols)
     {
@@ -573,6 +603,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
                  : (rows() == other.rows() && cols() == other.cols())))
         && "Size mismatch. Automatic resizing is disabled because EIGEN_NO_AUTOMATIC_RESIZING is defined");
       EIGEN_ONLY_USED_FOR_DEBUG(other);
+      if(this->size()==0)
+        resizeLike(other);
       #else
       resizeLike(other);
       #endif

gtsam/3rdparty/Eigen/Eigen/src/Core/ProductBase.h

@@ -85,7 +85,14 @@ class ProductBase : public MatrixBase<Derived>
 
   public:
 
+#ifndef EIGEN_NO_MALLOC
+    typedef typename Base::PlainObject BasePlainObject;
+    typedef Matrix<Scalar,RowsAtCompileTime==1?1:Dynamic,ColsAtCompileTime==1?1:Dynamic,BasePlainObject::Options> DynPlainObject;
+    typedef typename internal::conditional<(BasePlainObject::SizeAtCompileTime==Dynamic) || (BasePlainObject::SizeAtCompileTime*int(sizeof(Scalar)) < int(EIGEN_STACK_ALLOCATION_LIMIT)),
+                                           BasePlainObject, DynPlainObject>::type PlainObject;
+#else
     typedef typename Base::PlainObject PlainObject;
+#endif
 
     ProductBase(const Lhs& a_lhs, const Rhs& a_rhs)
       : m_lhs(a_lhs), m_rhs(a_rhs)
@@ -180,7 +187,12 @@ 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;
+  typedef typename GeneralProduct<Lhs,Rhs,Mode>::PlainObject const& type;
+};
+template<typename Lhs, typename Rhs, int Mode, int N, typename PlainObject>
+struct nested<const GeneralProduct<Lhs,Rhs,Mode>, N, PlainObject>
+{
+  typedef typename GeneralProduct<Lhs,Rhs,Mode>::PlainObject const& type;
 };
 }
 

gtsam/3rdparty/Eigen/Eigen/src/Core/Redux.h

@@ -247,8 +247,9 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
   }
 };
 
-template<typename Func, typename Derived>
+// NOTE: for SliceVectorizedTraversal we simply bypass unrolling
-struct redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling>
+template<typename Func, typename Derived, int Unrolling>
+struct redux_impl<Func, Derived, SliceVectorizedTraversal, Unrolling>
 {
   typedef typename Derived::Scalar Scalar;
   typedef typename packet_traits<Scalar>::type PacketScalar;

gtsam/3rdparty/Eigen/Eigen/src/Core/Ref.h

@@ -108,7 +108,8 @@ struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
       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
+      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;
   };
@@ -187,7 +188,11 @@ 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>
+    inline Ref(const PlainObjectBase<Derived>& expr,
+               typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0);
   public:
 
     typedef RefBase<Ref> Base;
@@ -199,17 +204,20 @@ template<typename PlainObjectType, int Options, typename StrideType> class Ref
     inline Ref(PlainObjectBase<Derived>& expr,
                typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
     {
-      Base::construct(expr);
+      EIGEN_STATIC_ASSERT(static_cast<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,
+               typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
-               int = Derived::ThisConstantIsPrivateInPlainObjectBase)
     #else
     template<typename Derived>
     inline Ref(DenseBase<Derived>& expr)
     #endif
     {
+      EIGEN_STATIC_ASSERT(static_cast<bool>(internal::is_lvalue<Derived>::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
+      EIGEN_STATIC_ASSERT(static_cast<bool>(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
+      enum { THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY = Derived::ThisConstantIsPrivateInPlainObjectBase};
       Base::construct(expr.const_cast_derived());
     }
 
@@ -228,13 +236,23 @@ template<typename TPlainObjectType, int Options, typename StrideType> class Ref<
     EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
 
     template<typename Derived>
-    inline Ref(const DenseBase<Derived>& expr)
+    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";
 //      std::cout << int(StrideType::InnerStrideAtCompileTime) << " - " << int(Derived::InnerStrideAtCompileTime) << "\n";
       construct(expr.derived(), typename Traits::template match<Derived>::type());
     }
+    
+    inline Ref(const Ref& other) : Base(other) {
+      // copy constructor shall not copy the m_object, to avoid unnecessary malloc and copy
+    }
+
+    template<typename OtherRef>
+    inline Ref(const RefBase<OtherRef>& other) {
+      construct(other.derived(), typename Traits::template match<OtherRef>::type());
+    }
 
   protected:
 

gtsam/3rdparty/Eigen/Eigen/src/Core/Replicate.h

@@ -135,7 +135,7 @@ 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());
@@ -150,7 +150,7 @@ DenseBase<Derived>::replicate() const
   * \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
   */
 template<typename Derived>
-inline const Replicate<Derived,Dynamic,Dynamic>
+const typename DenseBase<Derived>::ReplicateReturnType
 DenseBase<Derived>::replicate(Index rowFactor,Index colFactor) const
 {
   return Replicate<Derived,Dynamic,Dynamic>(derived(),rowFactor,colFactor);

gtsam/3rdparty/Eigen/Eigen/src/Core/ReturnByValue.h

@@ -72,6 +72,8 @@ 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); }
+    template<int LoadMode>  Unusable& packet(Index) const;
+    template<int LoadMode>  Unusable& packet(Index, Index) const;
 #endif
 };
 
@@ -83,6 +85,15 @@ Derived& DenseBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
   return derived();
 }
 
+template<typename Derived>
+template<typename OtherDerived>
+Derived& DenseBase<Derived>::lazyAssign(const ReturnByValue<OtherDerived>& other)
+{
+  other.evalTo(derived());
+  return derived();
+}
+
+
 } // end namespace Eigen
 
 #endif // EIGEN_RETURNBYVALUE_H

gtsam/3rdparty/Eigen/Eigen/src/Core/SelfCwiseBinaryOp.h

@@ -180,15 +180,9 @@ inline Derived& DenseBase<Derived>::operator*=(const Scalar& other)
 template<typename Derived>
 inline Derived& DenseBase<Derived>::operator/=(const Scalar& other)
 {
-  typedef typename internal::conditional<NumTraits<Scalar>::IsInteger,
-                                        internal::scalar_quotient_op<Scalar>,
-                                        internal::scalar_product_op<Scalar> >::type BinOp;
   typedef typename Derived::PlainObject PlainObject;
-  SelfCwiseBinaryOp<BinOp, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
+  SelfCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, Derived, typename PlainObject::ConstantReturnType> tmp(derived());
-  Scalar actual_other;
+  tmp = PlainObject::Constant(rows(),cols(), other);
-  if(NumTraits<Scalar>::IsInteger)  actual_other = other;
-  else                              actual_other = Scalar(1)/other;
-  tmp = PlainObject::Constant(rows(),cols(), actual_other);
   return derived();
 }
 

gtsam/3rdparty/Eigen/Eigen/src/Core/TriangularMatrix.h

@@ -380,19 +380,19 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
     EIGEN_STRONG_INLINE TriangularView& operator=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
     {
       setZero();
-      return assignProduct(other,1);
+      return assignProduct(other.derived(),1);
     }
     
     template<typename ProductDerived, typename Lhs, typename Rhs>
     EIGEN_STRONG_INLINE TriangularView& operator+=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
     {
-      return assignProduct(other,1);
+      return assignProduct(other.derived(),1);
     }
     
     template<typename ProductDerived, typename Lhs, typename Rhs>
     EIGEN_STRONG_INLINE TriangularView& operator-=(const ProductBase<ProductDerived, Lhs,Rhs>& other)
     {
-      return assignProduct(other,-1);
+      return assignProduct(other.derived(),-1);
     }
     
     
@@ -400,25 +400,34 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
     EIGEN_STRONG_INLINE TriangularView& operator=(const ScaledProduct<ProductDerived>& other)
     {
       setZero();
-      return assignProduct(other,other.alpha());
+      return assignProduct(other.derived(),other.alpha());
     }
     
     template<typename ProductDerived>
     EIGEN_STRONG_INLINE TriangularView& operator+=(const ScaledProduct<ProductDerived>& other)
     {
-      return assignProduct(other,other.alpha());
+      return assignProduct(other.derived(),other.alpha());
     }
     
     template<typename ProductDerived>
     EIGEN_STRONG_INLINE TriangularView& operator-=(const ScaledProduct<ProductDerived>& other)
     {
-      return assignProduct(other,-other.alpha());
+      return assignProduct(other.derived(),-other.alpha());
     }
     
   protected:
     
     template<typename ProductDerived, typename Lhs, typename Rhs>
     EIGEN_STRONG_INLINE TriangularView& assignProduct(const ProductBase<ProductDerived, Lhs,Rhs>& prod, const Scalar& alpha);
+    
+    template<int Mode, bool LhsIsTriangular,
+         typename Lhs, bool LhsIsVector,
+         typename Rhs, bool RhsIsVector>
+    EIGEN_STRONG_INLINE TriangularView& assignProduct(const TriangularProduct<Mode, LhsIsTriangular, Lhs, LhsIsVector, Rhs, RhsIsVector>& prod, const Scalar& alpha)
+    {
+      lazyAssign(alpha*prod.eval());
+      return *this;
+    }
 
     MatrixTypeNested m_matrix;
 };

gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/Complex.h

@@ -110,7 +110,7 @@ template<> EIGEN_STRONG_INLINE Packet2cf ploaddup<Packet2cf>(const std::complex<
 template<> EIGEN_STRONG_INLINE void pstore <std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((float*)to, from.v); }
 template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<float> >(std::complex<float> *   to, const Packet2cf& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((float*)to, from.v); }
 
-template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> *   addr) { __pld((float *)addr); }
+template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> *   addr) { EIGEN_ARM_PREFETCH((float *)addr); }
 
 template<> EIGEN_STRONG_INLINE std::complex<float>  pfirst<Packet2cf>(const Packet2cf& a)
 {

gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/PacketMath.h

@@ -48,9 +48,18 @@ typedef uint32x4_t  Packet4ui;
   #define EIGEN_INIT_NEON_PACKET2(X, Y)       {X, Y}
   #define EIGEN_INIT_NEON_PACKET4(X, Y, Z, W) {X, Y, Z, W}
 #endif
-    
+
-#ifndef __pld
+// arm64 does have the pld instruction. If available, let's trust the __builtin_prefetch built-in function
-#define __pld(x) asm volatile ( "   pld [%[addr]]\n" :: [addr] "r" (x) : "cc" );
+// which available on LLVM and GCC (at least)
+#if EIGEN_HAS_BUILTIN(__builtin_prefetch) || defined(__GNUC__)
+  #define EIGEN_ARM_PREFETCH(ADDR) __builtin_prefetch(ADDR);
+#elif defined __pld
+  #define EIGEN_ARM_PREFETCH(ADDR) __pld(ADDR)
+#elif !defined(__aarch64__)
+  #define EIGEN_ARM_PREFETCH(ADDR) __asm__ __volatile__ ( "   pld [%[addr]]\n" :: [addr] "r" (ADDR) : "cc" );
+#else
+  // by default no explicit prefetching
+  #define EIGEN_ARM_PREFETCH(ADDR)
 #endif
 
 template<> struct packet_traits<float>  : default_packet_traits
@@ -209,8 +218,8 @@ template<> EIGEN_STRONG_INLINE void pstore<int>(int*       to, const Packet4i& f
 template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*  to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_f32(to, from); }
 template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*      to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE vst1q_s32(to, from); }
 
-template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { __pld(addr); }
+template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { EIGEN_ARM_PREFETCH(addr); }
-template<> EIGEN_STRONG_INLINE void prefetch<int>(const int*     addr) { __pld(addr); }
+template<> EIGEN_STRONG_INLINE void prefetch<int>(const int*     addr) { EIGEN_ARM_PREFETCH(addr); }
 
 // FIXME only store the 2 first elements ?
 template<> EIGEN_STRONG_INLINE float  pfirst<Packet4f>(const Packet4f& a) { float EIGEN_ALIGN16 x[4]; vst1q_f32(x, a); return x[0]; }
@@ -375,6 +384,7 @@ template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
   a_lo = vget_low_s32(a);
   a_hi = vget_high_s32(a);
   max = vpmax_s32(a_lo, a_hi);
+  max = vpmax_s32(max, max);
 
   return vget_lane_s32(max, 0);
 }

gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/MathFunctions.h

@@ -52,7 +52,7 @@ Packet4f plog<Packet4f>(const Packet4f& _x)
 
   Packet4i emm0;
 
-  Packet4f invalid_mask = _mm_cmplt_ps(x, _mm_setzero_ps());
+  Packet4f invalid_mask = _mm_cmpnge_ps(x, _mm_setzero_ps()); // not greater equal is true if x is NaN
   Packet4f iszero_mask = _mm_cmpeq_ps(x, _mm_setzero_ps());
 
   x = pmax(x, p4f_min_norm_pos);  /* cut off denormalized stuff */
@@ -126,7 +126,7 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
   _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p4, 1.6666665459E-1f);
   _EIGEN_DECLARE_CONST_Packet4f(cephes_exp_p5, 5.0000001201E-1f);
 
-  Packet4f tmp = _mm_setzero_ps(), fx;
+  Packet4f tmp, fx;
   Packet4i emm0;
 
   // clamp x
@@ -166,7 +166,7 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
   emm0 = _mm_cvttps_epi32(fx);
   emm0 = _mm_add_epi32(emm0, p4i_0x7f);
   emm0 = _mm_slli_epi32(emm0, 23);
-  return pmul(y, _mm_castsi128_ps(emm0));
+  return pmax(pmul(y, Packet4f(_mm_castsi128_ps(emm0))), _x);
 }
 template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
 Packet2d pexp<Packet2d>(const Packet2d& _x)
@@ -195,7 +195,7 @@ Packet2d pexp<Packet2d>(const Packet2d& _x)
   _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
   static const __m128i p4i_1023_0 = _mm_setr_epi32(1023, 1023, 0, 0);
 
-  Packet2d tmp = _mm_setzero_pd(), fx;
+  Packet2d tmp, fx;
   Packet4i emm0;
 
   // clamp x
@@ -239,7 +239,7 @@ Packet2d pexp<Packet2d>(const Packet2d& _x)
   emm0 = _mm_add_epi32(emm0, p4i_1023_0);
   emm0 = _mm_slli_epi32(emm0, 20);
   emm0 = _mm_shuffle_epi32(emm0, _MM_SHUFFLE(1,2,0,3));
-  return pmul(x, _mm_castsi128_pd(emm0));
+  return pmax(pmul(x, Packet2d(_mm_castsi128_pd(emm0))), _x);
 }
 
 /* evaluation of 4 sines at onces, using SSE2 intrinsics.
@@ -279,7 +279,7 @@ Packet4f psin<Packet4f>(const Packet4f& _x)
   _EIGEN_DECLARE_CONST_Packet4f(coscof_p2,  4.166664568298827E-002f);
   _EIGEN_DECLARE_CONST_Packet4f(cephes_FOPI, 1.27323954473516f); // 4 / M_PI
 
-  Packet4f xmm1, xmm2 = _mm_setzero_ps(), xmm3, sign_bit, y;
+  Packet4f xmm1, xmm2, xmm3, sign_bit, y;
 
   Packet4i emm0, emm2;
   sign_bit = x;
@@ -378,7 +378,7 @@ Packet4f pcos<Packet4f>(const Packet4f& _x)
   _EIGEN_DECLARE_CONST_Packet4f(coscof_p2,  4.166664568298827E-002f);
   _EIGEN_DECLARE_CONST_Packet4f(cephes_FOPI, 1.27323954473516f); // 4 / M_PI
 
-  Packet4f xmm1, xmm2 = _mm_setzero_ps(), xmm3, y;
+  Packet4f xmm1, xmm2, xmm3, y;
   Packet4i emm0, emm2;
 
   x = pabs(x);

gtsam/3rdparty/Eigen/Eigen/src/Core/products/CoeffBasedProduct.h

@@ -90,6 +90,7 @@ struct traits<CoeffBasedProduct<LhsNested,RhsNested,NestingFlags> >
             | (SameType && (CanVectorizeLhs || CanVectorizeRhs) ? PacketAccessBit : 0),
 
       CoeffReadCost = InnerSize == Dynamic ? Dynamic
+                    : InnerSize == 0 ? 0
                     : InnerSize * (NumTraits<Scalar>::MulCost + LhsCoeffReadCost + RhsCoeffReadCost)
                       + (InnerSize - 1) * NumTraits<Scalar>::AddCost,
 
@@ -133,7 +134,7 @@ class CoeffBasedProduct
     };
 
     typedef internal::product_coeff_impl<CanVectorizeInner ? InnerVectorizedTraversal : DefaultTraversal,
-                                   Unroll ? InnerSize-1 : Dynamic,
+                                   Unroll ? InnerSize : Dynamic,
                                    _LhsNested, _RhsNested, Scalar> ScalarCoeffImpl;
 
     typedef CoeffBasedProduct<LhsNested,RhsNested,NestByRefBit> LazyCoeffBasedProductType;
@@ -184,7 +185,7 @@ class CoeffBasedProduct
     {
       PacketScalar res;
       internal::product_packet_impl<Flags&RowMajorBit ? RowMajor : ColMajor,
-                              Unroll ? InnerSize-1 : Dynamic,
+                              Unroll ? InnerSize : Dynamic,
                               _LhsNested, _RhsNested, PacketScalar, LoadMode>
         ::run(row, col, m_lhs, m_rhs, res);
       return res;
@@ -242,12 +243,12 @@ struct product_coeff_impl<DefaultTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
   {
     product_coeff_impl<DefaultTraversal, UnrollingIndex-1, Lhs, Rhs, RetScalar>::run(row, col, lhs, rhs, res);
-    res += lhs.coeff(row, UnrollingIndex) * rhs.coeff(UnrollingIndex, col);
+    res += lhs.coeff(row, UnrollingIndex-1) * rhs.coeff(UnrollingIndex-1, col);
   }
 };
 
 template<typename Lhs, typename Rhs, typename RetScalar>
-struct product_coeff_impl<DefaultTraversal, 0, Lhs, Rhs, RetScalar>
+struct product_coeff_impl<DefaultTraversal, 1, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
@@ -256,16 +257,23 @@ struct product_coeff_impl<DefaultTraversal, 0, Lhs, Rhs, RetScalar>
   }
 };
 
+template<typename Lhs, typename Rhs, typename RetScalar>
+struct product_coeff_impl<DefaultTraversal, 0, Lhs, Rhs, RetScalar>
+{
+  typedef typename Lhs::Index Index;
+  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, RetScalar &res)
+  {
+    res = RetScalar(0);
+  }
+};
+
 template<typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<DefaultTraversal, Dynamic, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar& res)
   {
-    eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
+    res = (lhs.row(row).transpose().cwiseProduct( rhs.col(col) )).sum();
-    res = lhs.coeff(row, 0) * rhs.coeff(0, col);
-      for(Index i = 1; i < lhs.cols(); ++i)
-        res += lhs.coeff(row, i) * rhs.coeff(i, col);
   }
 };
 
@@ -295,6 +303,16 @@ struct product_coeff_vectorized_unroller<0, Lhs, Rhs, Packet>
   }
 };
 
+template<typename Lhs, typename Rhs, typename RetScalar>
+struct product_coeff_impl<InnerVectorizedTraversal, 0, Lhs, Rhs, RetScalar>
+{
+  typedef typename Lhs::Index Index;
+  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, RetScalar &res)
+  {
+    res = 0;
+  }
+};
+
 template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<InnerVectorizedTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
 {
@@ -304,8 +322,7 @@ struct product_coeff_impl<InnerVectorizedTraversal, UnrollingIndex, Lhs, Rhs, Re
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
   {
     Packet pres;
-    product_coeff_vectorized_unroller<UnrollingIndex+1-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, pres);
+    product_coeff_vectorized_unroller<UnrollingIndex-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, pres);
-    product_coeff_impl<DefaultTraversal,UnrollingIndex,Lhs,Rhs,RetScalar>::run(row, col, lhs, rhs, res);
     res = predux(pres);
   }
 };
@@ -373,7 +390,7 @@ struct product_packet_impl<RowMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
   {
     product_packet_impl<RowMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, res);
-    res =  pmadd(pset1<Packet>(lhs.coeff(row, UnrollingIndex)), rhs.template packet<LoadMode>(UnrollingIndex, col), res);
+    res =  pmadd(pset1<Packet>(lhs.coeff(row, UnrollingIndex-1)), rhs.template packet<LoadMode>(UnrollingIndex-1, col), res);
   }
 };
 
@@ -384,12 +401,12 @@ struct product_packet_impl<ColMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
   {
     product_packet_impl<ColMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, res);
-    res =  pmadd(lhs.template packet<LoadMode>(row, UnrollingIndex), pset1<Packet>(rhs.coeff(UnrollingIndex, col)), res);
+    res =  pmadd(lhs.template packet<LoadMode>(row, UnrollingIndex-1), pset1<Packet>(rhs.coeff(UnrollingIndex-1, col)), res);
   }
 };
 
 template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
-struct product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
+struct product_packet_impl<RowMajor, 1, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
@@ -399,7 +416,7 @@ struct product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
 };
 
 template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
-struct product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
+struct product_packet_impl<ColMajor, 1, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
@@ -408,16 +425,35 @@ struct product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
   }
 };
 
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
+{
+  typedef typename Lhs::Index Index;
+  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, Packet &res)
+  {
+    res = pset1<Packet>(0);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
+{
+  typedef typename Lhs::Index Index;
+  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, const Rhs& /*rhs*/, Packet &res)
+  {
+    res = pset1<Packet>(0);
+  }
+};
+
 template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
 struct product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
   {
-    eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
+    res = pset1<Packet>(0);
-    res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
+    for(Index i = 0; i < lhs.cols(); ++i)
-      for(Index i = 1; i < lhs.cols(); ++i)
+      res =  pmadd(pset1<Packet>(lhs.coeff(row, i)), rhs.template packet<LoadMode>(i, col), res);
-        res =  pmadd(pset1<Packet>(lhs.coeff(row, i)), rhs.template packet<LoadMode>(i, col), res);
   }
 };
 
@@ -427,10 +463,9 @@ struct product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
   typedef typename Lhs::Index Index;
   static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
   {
-    eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
+    res = pset1<Packet>(0);
-    res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
+    for(Index i = 0; i < lhs.cols(); ++i)
-      for(Index i = 1; i < lhs.cols(); ++i)
+      res =  pmadd(lhs.template packet<LoadMode>(row, i), pset1<Packet>(rhs.coeff(i, col)), res);
-        res =  pmadd(lhs.template packet<LoadMode>(row, i), pset1<Packet>(rhs.coeff(i, col)), res);
   }
 };
 

gtsam/3rdparty/Eigen/Eigen/src/Core/products/Parallelizer.h

@@ -125,19 +125,22 @@ void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpos
   if(transpose)
     std::swap(rows,cols);
 
-  Index blockCols = (cols / threads) & ~Index(0x3);
-  Index blockRows = (rows / threads) & ~Index(0x7);
-  
   GemmParallelInfo<Index>* info = new GemmParallelInfo<Index>[threads];
 
-  #pragma omp parallel for schedule(static,1) num_threads(threads)
+  #pragma omp parallel num_threads(threads)
-  for(Index i=0; i<threads; ++i)
   {
+    Index i = omp_get_thread_num();
+    // Note that the actual number of threads might be lower than the number of request ones.
+    Index actual_threads = omp_get_num_threads();
+    
+    Index blockCols = (cols / actual_threads) & ~Index(0x3);
+    Index blockRows = (rows / actual_threads) & ~Index(0x7);
+    
     Index r0 = i*blockRows;
-    Index actualBlockRows = (i+1==threads) ? rows-r0 : blockRows;
+    Index actualBlockRows = (i+1==actual_threads) ? rows-r0 : blockRows;
 
     Index c0 = i*blockCols;
-    Index actualBlockCols = (i+1==threads) ? cols-c0 : blockCols;
+    Index actualBlockCols = (i+1==actual_threads) ? cols-c0 : blockCols;
 
     info[i].rhs_start = c0;
     info[i].rhs_length = actualBlockCols;

gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h

@@ -109,7 +109,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
 /* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \
    if (rows != depth) { \
 \
-     int nthr = mkl_domain_get_max_threads(MKL_BLAS); \
+     int nthr = mkl_domain_get_max_threads(EIGEN_MKL_DOMAIN_BLAS); \
 \
      if (((nthr==1) && (((std::max)(rows,depth)-diagSize)/(double)diagSize < 0.5))) { \
      /* Most likely no benefit to call TRMM or GEMM from MKL*/ \
@@ -223,7 +223,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
 /* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \
    if (cols != depth) { \
 \
-     int nthr = mkl_domain_get_max_threads(MKL_BLAS); \
+     int nthr = mkl_domain_get_max_threads(EIGEN_MKL_DOMAIN_BLAS); \
 \
      if ((nthr==1) && (((std::max)(cols,depth)-diagSize)/(double)diagSize < 0.5)) { \
      /* Most likely no benefit to call TRMM or GEMM from MKL*/ \

gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularSolverMatrix.h

@@ -302,9 +302,12 @@ EIGEN_DONT_INLINE void triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conj
                 for (Index i=0; i<actual_mc; ++i)
                   r[i] -= a[i] * b;
               }
-              Scalar b = (Mode & UnitDiag) ? Scalar(1) : Scalar(1)/conj(rhs(j,j));
+              if((Mode & UnitDiag)==0)
-              for (Index i=0; i<actual_mc; ++i)
+              {
-                r[i] *= b;
+                Scalar b = conj(rhs(j,j));
+                for (Index i=0; i<actual_mc; ++i)
+                  r[i] /= b;
+              }
             }
 
             // pack the just computed part of lhs to A

gtsam/3rdparty/Eigen/Eigen/src/Core/util/Constants.h

@@ -433,6 +433,19 @@ struct MatrixXpr {};
 /** The type used to identify an array expression */
 struct ArrayXpr {};
 
+namespace internal {
+  /** \internal
+  * Constants for comparison functors
+  */
+  enum ComparisonName {
+    cmp_EQ = 0,
+    cmp_LT = 1,
+    cmp_LE = 2,
+    cmp_UNORD = 3,
+    cmp_NEQ = 4
+  };
+}
+
 } // end namespace Eigen
 
 #endif // EIGEN_CONSTANTS_H

gtsam/3rdparty/Eigen/Eigen/src/Core/util/ForwardDeclarations.h

@@ -235,6 +235,9 @@ template<typename Scalar> class Rotation2D;
 template<typename Scalar> class AngleAxis;
 template<typename Scalar,int Dim> class Translation;
 
+// Sparse module:
+template<typename Derived> class SparseMatrixBase;
+
 #ifdef EIGEN2_SUPPORT
 template<typename Derived, int _Dim> class eigen2_RotationBase;
 template<typename Lhs, typename Rhs> class eigen2_Cross;

gtsam/3rdparty/Eigen/Eigen/src/Core/util/MKL_support.h

@@ -76,6 +76,38 @@
 #include <mkl_lapacke.h>
 #define EIGEN_MKL_VML_THRESHOLD 128
 
+/* MKL_DOMAIN_BLAS, etc are defined only in 10.3 update 7 */
+/* MKL_BLAS, etc are not defined in 11.2 */
+#ifdef MKL_DOMAIN_ALL
+#define EIGEN_MKL_DOMAIN_ALL MKL_DOMAIN_ALL
+#else
+#define EIGEN_MKL_DOMAIN_ALL MKL_ALL
+#endif
+
+#ifdef MKL_DOMAIN_BLAS
+#define EIGEN_MKL_DOMAIN_BLAS MKL_DOMAIN_BLAS
+#else
+#define EIGEN_MKL_DOMAIN_BLAS MKL_BLAS
+#endif
+
+#ifdef MKL_DOMAIN_FFT
+#define EIGEN_MKL_DOMAIN_FFT MKL_DOMAIN_FFT
+#else
+#define EIGEN_MKL_DOMAIN_FFT MKL_FFT
+#endif
+
+#ifdef MKL_DOMAIN_VML
+#define EIGEN_MKL_DOMAIN_VML MKL_DOMAIN_VML
+#else
+#define EIGEN_MKL_DOMAIN_VML MKL_VML
+#endif
+
+#ifdef MKL_DOMAIN_PARDISO
+#define EIGEN_MKL_DOMAIN_PARDISO MKL_DOMAIN_PARDISO
+#else
+#define EIGEN_MKL_DOMAIN_PARDISO MKL_PARDISO
+#endif
+
 namespace Eigen {
 
 typedef std::complex<double> dcomplex;

gtsam/3rdparty/Eigen/Eigen/src/Core/util/Macros.h

@@ -13,7 +13,7 @@
 
 #define EIGEN_WORLD_VERSION 3
 #define EIGEN_MAJOR_VERSION 2
-#define EIGEN_MINOR_VERSION 2
+#define EIGEN_MINOR_VERSION 7
 
 #define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
                                       (EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
@@ -96,6 +96,27 @@
 #define EIGEN_DEFAULT_DENSE_INDEX_TYPE std::ptrdiff_t
 #endif
 
+// A Clang feature extension to determine compiler features.
+// We use it to determine 'cxx_rvalue_references'
+#ifndef __has_feature
+# define __has_feature(x) 0
+#endif
+
+// Do we support r-value references?
+#if (__has_feature(cxx_rvalue_references) || \
+     defined(__GXX_EXPERIMENTAL_CXX0X__) || \
+     (defined(_MSC_VER) && _MSC_VER >= 1600))
+  #define EIGEN_HAVE_RVALUE_REFERENCES
+#endif
+
+
+// Cross compiler wrapper around LLVM's __has_builtin
+#ifdef __has_builtin
+#  define EIGEN_HAS_BUILTIN(x) __has_builtin(x)
+#else
+#  define EIGEN_HAS_BUILTIN(x) 0
+#endif
+
 /** Allows to disable some optimizations which might affect the accuracy of the result.
   * Such optimization are enabled by default, and set EIGEN_FAST_MATH to 0 to disable them.
   * They currently include:
@@ -247,7 +268,7 @@ namespace Eigen {
 
 #if !defined(EIGEN_ASM_COMMENT)
   #if (defined __GNUC__) && ( defined(__i386__) || defined(__x86_64__) )
-    #define EIGEN_ASM_COMMENT(X)  asm("#" X)
+    #define EIGEN_ASM_COMMENT(X)  __asm__("#" X)
   #else
     #define EIGEN_ASM_COMMENT(X)
   #endif
@@ -271,6 +292,7 @@ namespace Eigen {
   #error Please tell me what is the equivalent of __attribute__((aligned(n))) for your compiler
 #endif
 
+#define EIGEN_ALIGN8  EIGEN_ALIGN_TO_BOUNDARY(8)
 #define EIGEN_ALIGN16 EIGEN_ALIGN_TO_BOUNDARY(16)
 
 #if EIGEN_ALIGN_STATICALLY
@@ -306,7 +328,7 @@ namespace Eigen {
 // just an empty macro !
 #define EIGEN_EMPTY
 
-#if defined(_MSC_VER) && (!defined(__INTEL_COMPILER))
+#if defined(_MSC_VER) && (_MSC_VER < 1900) && (!defined(__INTEL_COMPILER))
 #define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
   using Base::operator =;
 #elif defined(__clang__) // workaround clang bug (see http://forum.kde.org/viewtopic.php?f=74&t=102653)
@@ -325,8 +347,11 @@ namespace Eigen {
   }
 #endif
 
-#define EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Derived) \
+/** \internal
-  EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived)
+ * \brief Macro to manually inherit assignment operators.
+ * This is necessary, because the implicitly defined assignment operator gets deleted when a custom operator= is defined.
+ */
+#define EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Derived) EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived)
 
 /**
 * Just a side note. Commenting within defines works only by documenting
@@ -398,6 +423,8 @@ namespace Eigen {
 #define EIGEN_SIZE_MAX(a,b) (((int)a == Dynamic || (int)b == Dynamic) ? Dynamic \
                            : ((int)a >= (int)b) ? (int)a : (int)b)
 
+#define EIGEN_ADD_COST(a,b) int(a)==Dynamic || int(b)==Dynamic ? Dynamic : int(a)+int(b)
+
 #define EIGEN_LOGICAL_XOR(a,b) (((a) || (b)) && !((a) && (b)))
 
 #define EIGEN_IMPLIES(a,b) (!(a) || (b))

gtsam/3rdparty/Eigen/Eigen/src/Core/util/Memory.h

@@ -63,7 +63,7 @@
 // Currently, let's include it only on unix systems:
 #if defined(__unix__) || defined(__unix)
   #include <unistd.h>
-  #if ((defined __QNXNTO__) || (defined _GNU_SOURCE) || ((defined _XOPEN_SOURCE) && (_XOPEN_SOURCE >= 600))) && (defined _POSIX_ADVISORY_INFO) && (_POSIX_ADVISORY_INFO > 0)
+  #if ((defined __QNXNTO__) || (defined _GNU_SOURCE) || (defined __PGI) || ((defined _XOPEN_SOURCE) && (_XOPEN_SOURCE >= 600))) && (defined _POSIX_ADVISORY_INFO) && (_POSIX_ADVISORY_INFO > 0)
     #define EIGEN_HAS_POSIX_MEMALIGN 1
   #endif
 #endif
@@ -417,6 +417,8 @@ template<typename T, bool Align> inline T* conditional_aligned_realloc_new(T* pt
 
 template<typename T, bool Align> inline T* conditional_aligned_new_auto(size_t size)
 {
+  if(size==0)
+    return 0; // short-cut. Also fixes Bug 884
   check_size_for_overflow<T>(size);
   T *result = reinterpret_cast<T*>(conditional_aligned_malloc<Align>(sizeof(T)*size));
   if(NumTraits<T>::RequireInitialization)
@@ -464,9 +466,8 @@ template<typename T, bool Align> inline void conditional_aligned_delete_auto(T *
 template<typename Scalar, typename Index>
 static inline Index first_aligned(const Scalar* array, Index size)
 {
-  enum { PacketSize = packet_traits<Scalar>::size,
+  static const Index PacketSize = packet_traits<Scalar>::size;
-         PacketAlignedMask = PacketSize-1
+  static const Index PacketAlignedMask = PacketSize-1;
-  };
 
   if(PacketSize==1)
   {
@@ -522,7 +523,7 @@ template<typename T> struct smart_copy_helper<T,false> {
 // you can overwrite Eigen's default behavior regarding alloca by defining EIGEN_ALLOCA
 // to the appropriate stack allocation function
 #ifndef EIGEN_ALLOCA
-  #if (defined __linux__)
+  #if (defined __linux__) || (defined __APPLE__) || (defined alloca)
     #define EIGEN_ALLOCA alloca
   #elif defined(_MSC_VER)
     #define EIGEN_ALLOCA _alloca
@@ -612,7 +613,6 @@ template<typename T> class aligned_stack_memory_handler
       void* operator new(size_t size, const std::nothrow_t&) throw() { \
         try { return Eigen::internal::conditional_aligned_malloc<NeedsToAlign>(size); } \
         catch (...) { return 0; } \
-        return 0; \
       }
   #else
     #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_NOTHROW(NeedsToAlign) \

gtsam/3rdparty/Eigen/Eigen/src/Core/util/StaticAssert.h

@@ -90,7 +90,9 @@
         YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED,
         THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE,
         THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH,
-        OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG
+        OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG,
+        IMPLICIT_CONVERSION_TO_SCALAR_IS_FOR_INNER_PRODUCT_ONLY,
+        STORAGE_LAYOUT_DOES_NOT_MATCH
       };
     };
 

gtsam/3rdparty/Eigen/Eigen/src/Core/util/XprHelper.h

@@ -341,7 +341,7 @@ template<typename T, int n=1, typename PlainObject = typename eval<T>::type> str
 };
 
 template<typename T>
-T* const_cast_ptr(const T* ptr)
+inline T* const_cast_ptr(const T* ptr)
 {
   return const_cast<T*>(ptr);
 }
@@ -366,17 +366,17 @@ struct dense_xpr_base<Derived, ArrayXpr>
 
 /** \internal Helper base class to add a scalar multiple operator
   * overloads for complex types */
-template<typename Derived,typename Scalar,typename OtherScalar,
+template<typename Derived, typename Scalar, typename OtherScalar, typename BaseType,
          bool EnableIt = !is_same<Scalar,OtherScalar>::value >
-struct special_scalar_op_base : public DenseCoeffsBase<Derived>
+struct special_scalar_op_base : public BaseType
 {
   // dummy operator* so that the
   // "using special_scalar_op_base::operator*" compiles
   void operator*() const;
 };
 
-template<typename Derived,typename Scalar,typename OtherScalar>
+template<typename Derived,typename Scalar,typename OtherScalar, typename BaseType>
-struct special_scalar_op_base<Derived,Scalar,OtherScalar,true>  : public DenseCoeffsBase<Derived>
+struct special_scalar_op_base<Derived,Scalar,OtherScalar,BaseType,true>  : public BaseType
 {
   const CwiseUnaryOp<scalar_multiple2_op<Scalar,OtherScalar>, Derived>
   operator*(const OtherScalar& scalar) const

gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/LeastSquares.h

@@ -147,7 +147,6 @@ void fitHyperplane(int numPoints,
 
   // compute the covariance matrix
   CovMatrixType covMat = CovMatrixType::Zero(size, size);
-  VectorType remean = VectorType::Zero(size);
   for(int i = 0; i < numPoints; ++i)
   {
     VectorType diff = (*(points[i]) - mean).conjugate();

gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h

@@ -234,6 +234,12 @@ template<typename _MatrixType> class ComplexEigenSolver
     }
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+    
     EigenvectorType m_eivec;
     EigenvalueType m_eivalues;
     ComplexSchur<MatrixType> m_schur;
@@ -251,6 +257,8 @@ template<typename MatrixType>
 ComplexEigenSolver<MatrixType>& 
 ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
 {
+  check_template_parameters();
+  
   // this code is inspired from Jampack
   eigen_assert(matrix.cols() == matrix.rows());
 

gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/EigenSolver.h

@@ -298,6 +298,13 @@ template<typename _MatrixType> class EigenSolver
     void doComputeEigenvectors();
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+      EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL);
+    }
+    
     MatrixType m_eivec;
     EigenvalueType m_eivalues;
     bool m_isInitialized;
@@ -364,6 +371,8 @@ template<typename MatrixType>
 EigenSolver<MatrixType>& 
 EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
 {
+  check_template_parameters();
+  
   using std::sqrt;
   using std::abs;
   eigen_assert(matrix.cols() == matrix.rows());

gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h

@@ -263,6 +263,13 @@ template<typename _MatrixType> class GeneralizedEigenSolver
     }
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+      EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL);
+    }
+    
     MatrixType m_eivec;
     ComplexVectorType m_alphas;
     VectorType m_betas;
@@ -290,6 +297,8 @@ template<typename MatrixType>
 GeneralizedEigenSolver<MatrixType>&
 GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixType& B, bool computeEigenvectors)
 {
+  check_template_parameters();
+  
   using std::sqrt;
   using std::abs;
   eigen_assert(A.cols() == A.rows() && B.cols() == A.rows() && B.cols() == B.rows());

gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/RealQZ.h

@@ -240,10 +240,10 @@ namespace Eigen {
             m_S.coeffRef(i,j) = Scalar(0.0);
             m_S.rightCols(dim-j-1).applyOnTheLeft(i-1,i,G.adjoint());
             m_T.rightCols(dim-i+1).applyOnTheLeft(i-1,i,G.adjoint());
+            // update Q
+            if (m_computeQZ)
+              m_Q.applyOnTheRight(i-1,i,G);
           }
-          // update Q
-          if (m_computeQZ)
-            m_Q.applyOnTheRight(i-1,i,G);
           // kill T(i,i-1)
           if(m_T.coeff(i,i-1)!=Scalar(0))
           {
@@ -251,10 +251,10 @@ namespace Eigen {
             m_T.coeffRef(i,i-1) = Scalar(0.0);
             m_S.applyOnTheRight(i,i-1,G);
             m_T.topRows(i).applyOnTheRight(i,i-1,G);
+            // update Z
+            if (m_computeQZ)
+              m_Z.applyOnTheLeft(i,i-1,G.adjoint());
           }
-          // update Z
-          if (m_computeQZ)
-            m_Z.applyOnTheLeft(i,i-1,G.adjoint());
         }
       }
     }
@@ -313,7 +313,7 @@ namespace Eigen {
       using std::abs;
       using std::sqrt;
       const Index dim=m_S.cols();
-      if (abs(m_S.coeff(i+1,i)==Scalar(0)))
+      if (abs(m_S.coeff(i+1,i))==Scalar(0))
         return;
       Index z = findSmallDiagEntry(i,i+1);
       if (z==i-1)

gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/RealSchur.h

@@ -234,7 +234,7 @@ template<typename _MatrixType> class RealSchur
     typedef Matrix<Scalar,3,1> Vector3s;
 
     Scalar computeNormOfT();
-    Index findSmallSubdiagEntry(Index iu, const Scalar& norm);
+    Index findSmallSubdiagEntry(Index iu);
     void splitOffTwoRows(Index iu, bool computeU, const Scalar& exshift);
     void computeShift(Index iu, Index iter, Scalar& exshift, Vector3s& shiftInfo);
     void initFrancisQRStep(Index il, Index iu, const Vector3s& shiftInfo, Index& im, Vector3s& firstHouseholderVector);
@@ -286,7 +286,7 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::computeFromHessenberg(const HessMa
   {
     while (iu >= 0)
     {
-      Index il = findSmallSubdiagEntry(iu, norm);
+      Index il = findSmallSubdiagEntry(iu);
 
       // Check for convergence
       if (il == iu) // One root found
@@ -343,16 +343,14 @@ inline typename MatrixType::Scalar RealSchur<MatrixType>::computeNormOfT()
 
 /** \internal Look for single small sub-diagonal element and returns its index */
 template<typename MatrixType>
-inline typename MatrixType::Index RealSchur<MatrixType>::findSmallSubdiagEntry(Index iu, const Scalar& norm)
+inline typename MatrixType::Index RealSchur<MatrixType>::findSmallSubdiagEntry(Index iu)
 {
   using std::abs;
   Index res = iu;
   while (res > 0)
   {
     Scalar s = abs(m_matT.coeff(res-1,res-1)) + abs(m_matT.coeff(res,res));
-    if (s == 0.0)
+    if (abs(m_matT.coeff(res,res-1)) <= NumTraits<Scalar>::epsilon() * s)
-      s = norm;
-    if (abs(m_matT.coeff(res,res-1)) < NumTraits<Scalar>::epsilon() * s)
       break;
     res--;
   }
@@ -457,9 +455,7 @@ inline void RealSchur<MatrixType>::initFrancisQRStep(Index il, Index iu, const V
     const Scalar lhs = m_matT.coeff(im,im-1) * (abs(v.coeff(1)) + abs(v.coeff(2)));
     const Scalar rhs = v.coeff(0) * (abs(m_matT.coeff(im-1,im-1)) + abs(Tmm) + abs(m_matT.coeff(im+1,im+1)));
     if (abs(lhs) < NumTraits<Scalar>::epsilon() * rhs)
-    {
       break;
-    }
   }
 }
 

gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h

@@ -80,6 +80,8 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
     /** \brief Scalar type for matrices of type \p _MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::Index Index;
+    
+    typedef Matrix<Scalar,Size,Size,ColMajor,MaxColsAtCompileTime,MaxColsAtCompileTime> EigenvectorsType;
 
     /** \brief Real scalar type for \p _MatrixType.
       *
@@ -225,7 +227,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       *
       * \sa eigenvalues()
       */
-    const MatrixType& eigenvectors() const
+    const EigenvectorsType& eigenvectors() const
     {
       eigen_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
       eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
@@ -351,7 +353,12 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
     #endif // EIGEN2_SUPPORT
 
   protected:
-    MatrixType m_eivec;
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+    
+    EigenvectorsType m_eivec;
     RealVectorType m_eivalues;
     typename TridiagonalizationType::SubDiagonalType m_subdiag;
     ComputationInfo m_info;
@@ -376,7 +383,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
   * "implicit symmetric QR step with Wilkinson shift"
   */
 namespace internal {
-template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
+template<typename RealScalar, typename Scalar, typename Index>
 static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n);
 }
 
@@ -384,6 +391,8 @@ template<typename MatrixType>
 SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
 ::compute(const MatrixType& matrix, int options)
 {
+  check_template_parameters();
+  
   using std::abs;
   eigen_assert(matrix.cols() == matrix.rows());
   eigen_assert((options&~(EigVecMask|GenEigMask))==0
@@ -406,7 +415,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
 
   // declare some aliases
   RealVectorType& diag = m_eivalues;
-  MatrixType& mat = m_eivec;
+  EigenvectorsType& mat = m_eivec;
 
   // map the matrix coefficients to [-1:1] to avoid over- and underflow.
   mat = matrix.template triangularView<Lower>();
@@ -442,7 +451,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
     while (start>0 && m_subdiag[start-1]!=0)
       start--;
 
-    internal::tridiagonal_qr_step<MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor>(diag.data(), m_subdiag.data(), start, end, computeEigenvectors ? m_eivec.data() : (Scalar*)0, n);
+    internal::tridiagonal_qr_step(diag.data(), m_subdiag.data(), start, end, computeEigenvectors ? m_eivec.data() : (Scalar*)0, n);
   }
 
   if (iter <= m_maxIterations * n)
@@ -490,7 +499,13 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
   typedef typename SolverType::MatrixType MatrixType;
   typedef typename SolverType::RealVectorType VectorType;
   typedef typename SolverType::Scalar Scalar;
+  typedef typename MatrixType::Index Index;
+  typedef typename SolverType::EigenvectorsType EigenvectorsType;
   
+  /** \internal
+   * Computes the roots of the characteristic polynomial of \a m.
+   * For numerical stability m.trace() should be near zero and to avoid over- or underflow m should be normalized.
+   */
   static inline void computeRoots(const MatrixType& m, VectorType& roots)
   {
     using std::sqrt;
@@ -510,148 +525,123 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
     // Construct the parameters used in classifying the roots of the equation
     // and in solving the equation for the roots in closed form.
     Scalar c2_over_3 = c2*s_inv3;
-    Scalar a_over_3 = (c1 - c2*c2_over_3)*s_inv3;
+    Scalar a_over_3 = (c2*c2_over_3 - c1)*s_inv3;
-    if (a_over_3 > Scalar(0))
+    if(a_over_3<Scalar(0))
       a_over_3 = Scalar(0);
 
     Scalar half_b = Scalar(0.5)*(c0 + c2_over_3*(Scalar(2)*c2_over_3*c2_over_3 - c1));
 
-    Scalar q = half_b*half_b + a_over_3*a_over_3*a_over_3;
+    Scalar q = a_over_3*a_over_3*a_over_3 - half_b*half_b;
-    if (q > Scalar(0))
+    if(q<Scalar(0))
       q = Scalar(0);
 
     // Compute the eigenvalues by solving for the roots of the polynomial.
-    Scalar rho = sqrt(-a_over_3);
+    Scalar rho = sqrt(a_over_3);
-    Scalar theta = atan2(sqrt(-q),half_b)*s_inv3;
+    Scalar theta = atan2(sqrt(q),half_b)*s_inv3;  // since sqrt(q) > 0, atan2 is in [0, pi] and theta is in [0, pi/3]
     Scalar cos_theta = cos(theta);
     Scalar sin_theta = sin(theta);
-    roots(0) = c2_over_3 + Scalar(2)*rho*cos_theta;
+    // roots are already sorted, since cos is monotonically decreasing on [0, pi]
-    roots(1) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
+    roots(0) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta); // == 2*rho*cos(theta+2pi/3)
-    roots(2) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
+    roots(1) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta); // == 2*rho*cos(theta+ pi/3)
-
+    roots(2) = c2_over_3 + Scalar(2)*rho*cos_theta;
-    // Sort in increasing order.
-    if (roots(0) >= roots(1))
-      std::swap(roots(0),roots(1));
-    if (roots(1) >= roots(2))
-    {
-      std::swap(roots(1),roots(2));
-      if (roots(0) >= roots(1))
-        std::swap(roots(0),roots(1));
-    }
   }
-  
+
+  static inline bool extract_kernel(MatrixType& mat, Ref<VectorType> res, Ref<VectorType> representative)
+  {
+    using std::abs;
+    Index i0;
+    // Find non-zero column i0 (by construction, there must exist a non zero coefficient on the diagonal):
+    mat.diagonal().cwiseAbs().maxCoeff(&i0);
+    // mat.col(i0) is a good candidate for an orthogonal vector to the current eigenvector,
+    // so let's save it:
+    representative = mat.col(i0);
+    Scalar n0, n1;
+    VectorType c0, c1;
+    n0 = (c0 = representative.cross(mat.col((i0+1)%3))).squaredNorm();
+    n1 = (c1 = representative.cross(mat.col((i0+2)%3))).squaredNorm();
+    if(n0>n1) res = c0/std::sqrt(n0);
+    else      res = c1/std::sqrt(n1);
+
+    return true;
+  }
+
   static inline void run(SolverType& solver, const MatrixType& mat, int options)
   {
-    using std::sqrt;
     eigen_assert(mat.cols() == 3 && mat.cols() == mat.rows());
     eigen_assert((options&~(EigVecMask|GenEigMask))==0
             && (options&EigVecMask)!=EigVecMask
             && "invalid option parameter");
     bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors;
     
-    MatrixType& eivecs = solver.m_eivec;
+    EigenvectorsType& eivecs = solver.m_eivec;
     VectorType& eivals = solver.m_eivalues;
   
-    // map the matrix coefficients to [-1:1] to avoid over- and underflow.
+    // Shift the matrix to the mean eigenvalue and map the matrix coefficients to [-1:1] to avoid over- and underflow.
-    Scalar scale = mat.cwiseAbs().maxCoeff();
+    Scalar shift = mat.trace() / Scalar(3);
-    MatrixType scaledMat = mat / scale;
+    // TODO Avoid this copy. Currently it is necessary to suppress bogus values when determining maxCoeff and for computing the eigenvectors later
+    MatrixType scaledMat = mat.template selfadjointView<Lower>();
+    scaledMat.diagonal().array() -= shift;
+    Scalar scale = scaledMat.cwiseAbs().maxCoeff();
+    if(scale > 0) scaledMat /= scale;   // TODO for scale==0 we could save the remaining operations
 
     // compute the eigenvalues
     computeRoots(scaledMat,eivals);
 
-    // compute the eigen vectors
+    // compute the eigenvectors
     if(computeEigenvectors)
     {
-      Scalar safeNorm2 = Eigen::NumTraits<Scalar>::epsilon();
-      safeNorm2 *= safeNorm2;
       if((eivals(2)-eivals(0))<=Eigen::NumTraits<Scalar>::epsilon())
       {
+        // All three eigenvalues are numerically the same
         eivecs.setIdentity();
       }
       else
       {
-        scaledMat = scaledMat.template selfadjointView<Lower>();
         MatrixType tmp;
         tmp = scaledMat;
 
+        // Compute the eigenvector of the most distinct eigenvalue
         Scalar d0 = eivals(2) - eivals(1);
         Scalar d1 = eivals(1) - eivals(0);
-        int k =  d0 > d1 ? 2 : 0;
+        Index k(0), l(2);
-        d0 = d0 > d1 ? d1 : d0;
+        if(d0 > d1)
-
-        tmp.diagonal().array () -= eivals(k);
-        VectorType cross;
-        Scalar n;
-        n = (cross = tmp.row(0).cross(tmp.row(1))).squaredNorm();
-
-        if(n>safeNorm2)
-          eivecs.col(k) = cross / sqrt(n);
-        else
         {
-          n = (cross = tmp.row(0).cross(tmp.row(2))).squaredNorm();
+          std::swap(k,l);
-
+          d0 = d1;
-          if(n>safeNorm2)
-            eivecs.col(k) = cross / sqrt(n);
-          else
-          {
-            n = (cross = tmp.row(1).cross(tmp.row(2))).squaredNorm();
-
-            if(n>safeNorm2)
-              eivecs.col(k) = cross / sqrt(n);
-            else
-            {
-              // the input matrix and/or the eigenvaues probably contains some inf/NaN,
-              // => exit
-              // scale back to the original size.
-              eivals *= scale;
-
-              solver.m_info = NumericalIssue;
-              solver.m_isInitialized = true;
-              solver.m_eigenvectorsOk = computeEigenvectors;
-              return;
-            }
-          }
         }
 
-        tmp = scaledMat;
+        // Compute the eigenvector of index k
-        tmp.diagonal().array() -= eivals(1);
-
-        if(d0<=Eigen::NumTraits<Scalar>::epsilon())
-          eivecs.col(1) = eivecs.col(k).unitOrthogonal();
-        else
         {
-          n = (cross = eivecs.col(k).cross(tmp.row(0).normalized())).squaredNorm();
+          tmp.diagonal().array () -= eivals(k);
-          if(n>safeNorm2)
+          // By construction, 'tmp' is of rank 2, and its kernel corresponds to the respective eigenvector.
-            eivecs.col(1) = cross / sqrt(n);
+          extract_kernel(tmp, eivecs.col(k), eivecs.col(l));
-          else
-          {
-            n = (cross = eivecs.col(k).cross(tmp.row(1))).squaredNorm();
-            if(n>safeNorm2)
-              eivecs.col(1) = cross / sqrt(n);
-            else
-            {
-              n = (cross = eivecs.col(k).cross(tmp.row(2))).squaredNorm();
-              if(n>safeNorm2)
-                eivecs.col(1) = cross / sqrt(n);
-              else
-              {
-                // we should never reach this point,
-                // if so the last two eigenvalues are likely to ve very closed to each other
-                eivecs.col(1) = eivecs.col(k).unitOrthogonal();
-              }
-            }
-          }
-
-          // make sure that eivecs[1] is orthogonal to eivecs[2]
-          Scalar d = eivecs.col(1).dot(eivecs.col(k));
-          eivecs.col(1) = (eivecs.col(1) - d * eivecs.col(k)).normalized();
         }
 
-        eivecs.col(k==2 ? 0 : 2) = eivecs.col(k).cross(eivecs.col(1)).normalized();
+        // Compute eigenvector of index l
+        if(d0<=2*Eigen::NumTraits<Scalar>::epsilon()*d1)
+        {
+          // If d0 is too small, then the two other eigenvalues are numerically the same,
+          // and thus we only have to ortho-normalize the near orthogonal vector we saved above.
+          eivecs.col(l) -= eivecs.col(k).dot(eivecs.col(l))*eivecs.col(l);
+          eivecs.col(l).normalize();
+        }
+        else
+        {
+          tmp = scaledMat;
+          tmp.diagonal().array () -= eivals(l);
+
+          VectorType dummy;
+          extract_kernel(tmp, eivecs.col(l), dummy);
+        }
+
+        // Compute last eigenvector from the other two
+        eivecs.col(1) = eivecs.col(2).cross(eivecs.col(0)).normalized();
       }
     }
+
     // Rescale back to the original size.
     eivals *= scale;
+    eivals.array() += shift;
     
     solver.m_info = Success;
     solver.m_isInitialized = true;
@@ -665,11 +655,12 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2
   typedef typename SolverType::MatrixType MatrixType;
   typedef typename SolverType::RealVectorType VectorType;
   typedef typename SolverType::Scalar Scalar;
+  typedef typename SolverType::EigenvectorsType EigenvectorsType;
   
   static inline void computeRoots(const MatrixType& m, VectorType& roots)
   {
     using std::sqrt;
-    const Scalar t0 = Scalar(0.5) * sqrt( numext::abs2(m(0,0)-m(1,1)) + Scalar(4)*m(1,0)*m(1,0));
+    const Scalar t0 = Scalar(0.5) * sqrt( numext::abs2(m(0,0)-m(1,1)) + Scalar(4)*numext::abs2(m(1,0)));
     const Scalar t1 = Scalar(0.5) * (m(0,0) + m(1,1));
     roots(0) = t1 - t0;
     roots(1) = t1 + t0;
@@ -678,13 +669,15 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2
   static inline void run(SolverType& solver, const MatrixType& mat, int options)
   {
     using std::sqrt;
+    using std::abs;
+
     eigen_assert(mat.cols() == 2 && mat.cols() == mat.rows());
     eigen_assert((options&~(EigVecMask|GenEigMask))==0
             && (options&EigVecMask)!=EigVecMask
             && "invalid option parameter");
     bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors;
     
-    MatrixType& eivecs = solver.m_eivec;
+    EigenvectorsType& eivecs = solver.m_eivec;
     VectorType& eivals = solver.m_eivalues;
   
     // map the matrix coefficients to [-1:1] to avoid over- and underflow.
@@ -698,22 +691,29 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2
     // compute the eigen vectors
     if(computeEigenvectors)
     {
-      scaledMat.diagonal().array () -= eivals(1);
+      if((eivals(1)-eivals(0))<=abs(eivals(1))*Eigen::NumTraits<Scalar>::epsilon())
-      Scalar a2 = numext::abs2(scaledMat(0,0));
-      Scalar c2 = numext::abs2(scaledMat(1,1));
-      Scalar b2 = numext::abs2(scaledMat(1,0));
-      if(a2>c2)
       {
-        eivecs.col(1) << -scaledMat(1,0), scaledMat(0,0);
+        eivecs.setIdentity();
-        eivecs.col(1) /= sqrt(a2+b2);
       }
       else
       {
-        eivecs.col(1) << -scaledMat(1,1), scaledMat(1,0);
+        scaledMat.diagonal().array () -= eivals(1);
-        eivecs.col(1) /= sqrt(c2+b2);
+        Scalar a2 = numext::abs2(scaledMat(0,0));
-      }
+        Scalar c2 = numext::abs2(scaledMat(1,1));
+        Scalar b2 = numext::abs2(scaledMat(1,0));
+        if(a2>c2)
+        {
+          eivecs.col(1) << -scaledMat(1,0), scaledMat(0,0);
+          eivecs.col(1) /= sqrt(a2+b2);
+        }
+        else
+        {
+          eivecs.col(1) << -scaledMat(1,1), scaledMat(1,0);
+          eivecs.col(1) /= sqrt(c2+b2);
+        }
 
-      eivecs.col(0) << eivecs.col(1).unitOrthogonal();
+        eivecs.col(0) << eivecs.col(1).unitOrthogonal();
+      }
     }
     
     // Rescale back to the original size.
@@ -736,7 +736,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
 }
 
 namespace internal {
-template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
+template<typename RealScalar, typename Scalar, typename Index>
 static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n)
 {
   using std::abs;
@@ -788,8 +788,7 @@ static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index sta
     // apply the givens rotation to the unit matrix Q = Q * G
     if (matrixQ)
     {
-      // FIXME if StorageOrder == RowMajor this operation is not very efficient
+      Map<Matrix<Scalar,Dynamic,Dynamic,ColMajor> > q(matrixQ,n,n);
-      Map<Matrix<Scalar,Dynamic,Dynamic,StorageOrder> > q(matrixQ,n,n);
       q.applyOnTheRight(k,k+1,rot);
     }
   }

gtsam/3rdparty/Eigen/Eigen/src/Geometry/AlignedBox.h

@@ -19,10 +19,12 @@ namespace Eigen {
   *
   * \brief An axis aligned box
   *
-  * \param _Scalar the type of the scalar coefficients
+  * \tparam _Scalar the type of the scalar coefficients
-  * \param _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
+  * \tparam _AmbientDim the dimension of the ambient space, can be a compile time value or Dynamic.
   *
   * This class represents an axis aligned box as a pair of the minimal and maximal corners.
+  * \warning The result of most methods is undefined when applied to an empty box. You can check for empty boxes using isEmpty().
+  * \sa alignedboxtypedefs
   */
 template <typename _Scalar, int _AmbientDim>
 class AlignedBox
@@ -40,18 +42,21 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
   /** Define constants to name the corners of a 1D, 2D or 3D axis aligned bounding box */
   enum CornerType
   {
-    /** 1D names */
+    /** 1D names @{ */
     Min=0, Max=1,
+    /** @} */
 
-    /** Added names for 2D */
+    /** Identifier for 2D corner @{ */
     BottomLeft=0, BottomRight=1,
     TopLeft=2, TopRight=3,
+    /** @} */
 
-    /** Added names for 3D */
+    /** Identifier for 3D corner  @{ */
     BottomLeftFloor=0, BottomRightFloor=1,
     TopLeftFloor=2, TopRightFloor=3,
     BottomLeftCeil=4, BottomRightCeil=5,
     TopLeftCeil=6, TopRightCeil=7
+    /** @} */
   };
 
 
@@ -63,34 +68,33 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
   inline explicit AlignedBox(Index _dim) : m_min(_dim), m_max(_dim)
   { setEmpty(); }
 
-  /** Constructs a box with extremities \a _min and \a _max. */
+  /** Constructs a box with extremities \a _min and \a _max.
+   * \warning If either component of \a _min is larger than the same component of \a _max, the constructed box is empty. */
   template<typename OtherVectorType1, typename OtherVectorType2>
   inline AlignedBox(const OtherVectorType1& _min, const OtherVectorType2& _max) : m_min(_min), m_max(_max) {}
 
   /** Constructs a box containing a single point \a p. */
   template<typename Derived>
-  inline explicit AlignedBox(const MatrixBase<Derived>& a_p)
+  inline explicit AlignedBox(const MatrixBase<Derived>& p) : m_min(p), m_max(m_min)
-  {
+  { }
-    typename internal::nested<Derived,2>::type p(a_p.derived());
-    m_min = p;
-    m_max = p;
-  }
 
   ~AlignedBox() {}
 
   /** \returns the dimension in which the box holds */
   inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size() : Index(AmbientDimAtCompileTime); }
 
-  /** \deprecated use isEmpty */
+  /** \deprecated use isEmpty() */
   inline bool isNull() const { return isEmpty(); }
 
-  /** \deprecated use setEmpty */
+  /** \deprecated use setEmpty() */
   inline void setNull() { setEmpty(); }
 
-  /** \returns true if the box is empty. */
+  /** \returns true if the box is empty.
+   * \sa setEmpty */
   inline bool isEmpty() const { return (m_min.array() > m_max.array()).any(); }
 
-  /** Makes \c *this an empty box. */
+  /** Makes \c *this an empty box.
+   * \sa isEmpty */
   inline void setEmpty()
   {
     m_min.setConstant( ScalarTraits::highest() );
@@ -159,7 +163,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
    * a uniform distribution */
   inline VectorType sample() const
   {
-    VectorType r;
+    VectorType r(dim());
     for(Index d=0; d<dim(); ++d)
     {
       if(!ScalarTraits::IsInteger)
@@ -175,27 +179,34 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
 
   /** \returns true if the point \a p is inside the box \c *this. */
   template<typename Derived>
-  inline bool contains(const MatrixBase<Derived>& a_p) const
+  inline bool contains(const MatrixBase<Derived>& p) const
   {
-    typename internal::nested<Derived,2>::type p(a_p.derived());
+    typename internal::nested<Derived,2>::type p_n(p.derived());
-    return (m_min.array()<=p.array()).all() && (p.array()<=m_max.array()).all();
+    return (m_min.array()<=p_n.array()).all() && (p_n.array()<=m_max.array()).all();
   }
 
   /** \returns true if the box \a b is entirely inside the box \c *this. */
   inline bool contains(const AlignedBox& b) const
   { return (m_min.array()<=(b.min)().array()).all() && ((b.max)().array()<=m_max.array()).all(); }
 
-  /** Extends \c *this such that it contains the point \a p and returns a reference to \c *this. */
+  /** \returns true if the box \a b is intersecting the box \c *this.
+   * \sa intersection, clamp */
+  inline bool intersects(const AlignedBox& b) const
+  { return (m_min.array()<=(b.max)().array()).all() && ((b.min)().array()<=m_max.array()).all(); }
+
+  /** Extends \c *this such that it contains the point \a p and returns a reference to \c *this.
+   * \sa extend(const AlignedBox&) */
   template<typename Derived>
-  inline AlignedBox& extend(const MatrixBase<Derived>& a_p)
+  inline AlignedBox& extend(const MatrixBase<Derived>& p)
   {
-    typename internal::nested<Derived,2>::type p(a_p.derived());
+    typename internal::nested<Derived,2>::type p_n(p.derived());
-    m_min = m_min.cwiseMin(p);
+    m_min = m_min.cwiseMin(p_n);
-    m_max = m_max.cwiseMax(p);
+    m_max = m_max.cwiseMax(p_n);
     return *this;
   }
 
-  /** Extends \c *this such that it contains the box \a b and returns a reference to \c *this. */
+  /** Extends \c *this such that it contains the box \a b and returns a reference to \c *this.
+   * \sa merged, extend(const MatrixBase&) */
   inline AlignedBox& extend(const AlignedBox& b)
   {
     m_min = m_min.cwiseMin(b.m_min);
@@ -203,7 +214,9 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
     return *this;
   }
 
-  /** Clamps \c *this by the box \a b and returns a reference to \c *this. */
+  /** Clamps \c *this by the box \a b and returns a reference to \c *this.
+   * \note If the boxes don't intersect, the resulting box is empty.
+   * \sa intersection(), intersects() */
   inline AlignedBox& clamp(const AlignedBox& b)
   {
     m_min = m_min.cwiseMax(b.m_min);
@@ -211,11 +224,15 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
     return *this;
   }
 
-  /** Returns an AlignedBox that is the intersection of \a b and \c *this */
+  /** Returns an AlignedBox that is the intersection of \a b and \c *this
+   * \note If the boxes don't intersect, the resulting box is empty.
+   * \sa intersects(), clamp, contains()  */
   inline AlignedBox intersection(const AlignedBox& b) const
   {return AlignedBox(m_min.cwiseMax(b.m_min), m_max.cwiseMin(b.m_max)); }
 
-  /** Returns an AlignedBox that is the union of \a b and \c *this */
+  /** Returns an AlignedBox that is the union of \a b and \c *this.
+   * \note Merging with an empty box may result in a box bigger than \c *this. 
+   * \sa extend(const AlignedBox&) */
   inline AlignedBox merged(const AlignedBox& b) const
   { return AlignedBox(m_min.cwiseMin(b.m_min), m_max.cwiseMax(b.m_max)); }
 
@@ -231,20 +248,20 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
 
   /** \returns the squared distance between the point \a p and the box \c *this,
     * and zero if \a p is inside the box.
-    * \sa exteriorDistance()
+    * \sa exteriorDistance(const MatrixBase&), squaredExteriorDistance(const AlignedBox&)
     */
   template<typename Derived>
-  inline Scalar squaredExteriorDistance(const MatrixBase<Derived>& a_p) const;
+  inline Scalar squaredExteriorDistance(const MatrixBase<Derived>& p) const;
 
   /** \returns the squared distance between the boxes \a b and \c *this,
     * and zero if the boxes intersect.
-    * \sa exteriorDistance()
+    * \sa exteriorDistance(const AlignedBox&), squaredExteriorDistance(const MatrixBase&)
     */
   inline Scalar squaredExteriorDistance(const AlignedBox& b) const;
 
   /** \returns the distance between the point \a p and the box \c *this,
     * and zero if \a p is inside the box.
-    * \sa squaredExteriorDistance()
+    * \sa squaredExteriorDistance(const MatrixBase&), exteriorDistance(const AlignedBox&)
     */
   template<typename Derived>
   inline NonInteger exteriorDistance(const MatrixBase<Derived>& p) const
@@ -252,7 +269,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
 
   /** \returns the distance between the boxes \a b and \c *this,
     * and zero if the boxes intersect.
-    * \sa squaredExteriorDistance()
+    * \sa squaredExteriorDistance(const AlignedBox&), exteriorDistance(const MatrixBase&)
     */
   inline NonInteger exteriorDistance(const AlignedBox& b) const
   { using std::sqrt; return sqrt(NonInteger(squaredExteriorDistance(b))); }

gtsam/3rdparty/Eigen/Eigen/src/Geometry/AngleAxis.h

@@ -131,7 +131,7 @@ public:
     m_angle = Scalar(other.angle());
   }
 
-  static inline const AngleAxis Identity() { return AngleAxis(0, Vector3::UnitX()); }
+  static inline const AngleAxis Identity() { return AngleAxis(Scalar(0), Vector3::UnitX()); }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
@@ -165,8 +165,8 @@ AngleAxis<Scalar>& AngleAxis<Scalar>::operator=(const QuaternionBase<QuatDerived
   Scalar n2 = q.vec().squaredNorm();
   if (n2 < NumTraits<Scalar>::dummy_precision()*NumTraits<Scalar>::dummy_precision())
   {
-    m_angle = 0;
+    m_angle = Scalar(0);
-    m_axis << 1, 0, 0;
+    m_axis << Scalar(1), Scalar(0), Scalar(0);
   }
   else
   {

gtsam/3rdparty/Eigen/Eigen/src/Geometry/Homogeneous.h

@@ -79,7 +79,7 @@ template<typename MatrixType,int _Direction> class Homogeneous
     {
       if(  (int(Direction)==Vertical   && row==m_matrix.rows())
         || (int(Direction)==Horizontal && col==m_matrix.cols()))
-        return 1;
+        return Scalar(1);
       return m_matrix.coeff(row, col);
     }
 

gtsam/3rdparty/Eigen/Eigen/src/Geometry/Hyperplane.h

@@ -100,7 +100,17 @@ public:
   {
     EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(VectorType, 3)
     Hyperplane result(p0.size());
-    result.normal() = (p2 - p0).cross(p1 - p0).normalized();
+    VectorType v0(p2 - p0), v1(p1 - p0);
+    result.normal() = v0.cross(v1);
+    RealScalar norm = result.normal().norm();
+    if(norm <= v0.norm() * v1.norm() * NumTraits<RealScalar>::epsilon())
+    {
+      Matrix<Scalar,2,3> m; m << v0.transpose(), v1.transpose();
+      JacobiSVD<Matrix<Scalar,2,3> > svd(m, ComputeFullV);
+      result.normal() = svd.matrixV().col(2);
+    }
+    else
+      result.normal() /= norm;
     result.offset() = -p0.dot(result.normal());
     return result;
   }

gtsam/3rdparty/Eigen/Eigen/src/Geometry/Quaternion.h

@@ -102,11 +102,11 @@ public:
   /** \returns a quaternion representing an identity rotation
     * \sa MatrixBase::Identity()
     */
-  static inline Quaternion<Scalar> Identity() { return Quaternion<Scalar>(1, 0, 0, 0); }
+  static inline Quaternion<Scalar> Identity() { return Quaternion<Scalar>(Scalar(1), Scalar(0), Scalar(0), Scalar(0)); }
 
   /** \sa QuaternionBase::Identity(), MatrixBase::setIdentity()
     */
-  inline QuaternionBase& setIdentity() { coeffs() << 0, 0, 0, 1; return *this; }
+  inline QuaternionBase& setIdentity() { coeffs() << Scalar(0), Scalar(0), Scalar(0), Scalar(1); return *this; }
 
   /** \returns the squared norm of the quaternion's coefficients
     * \sa QuaternionBase::norm(), MatrixBase::squaredNorm()
@@ -161,7 +161,7 @@ public:
   { return coeffs().isApprox(other.coeffs(), prec); }
 
 	/** return the result vector of \a v through the rotation*/
-  EIGEN_STRONG_INLINE Vector3 _transformVector(Vector3 v) const;
+  EIGEN_STRONG_INLINE Vector3 _transformVector(const Vector3& v) const;
 
   /** \returns \c *this with scalar type casted to \a NewScalarType
     *
@@ -231,7 +231,7 @@ class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
 public:
   typedef _Scalar Scalar;
 
-  EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Quaternion)
+  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Quaternion)
   using Base::operator*=;
 
   typedef typename internal::traits<Quaternion>::Coefficients Coefficients;
@@ -341,7 +341,7 @@ class Map<const Quaternion<_Scalar>, _Options >
   public:
     typedef _Scalar Scalar;
     typedef typename internal::traits<Map>::Coefficients Coefficients;
-    EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Map)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
     using Base::operator*=;
 
     /** Constructs a Mapped Quaternion object from the pointer \a coeffs
@@ -378,7 +378,7 @@ class Map<Quaternion<_Scalar>, _Options >
   public:
     typedef _Scalar Scalar;
     typedef typename internal::traits<Map>::Coefficients Coefficients;
-    EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Map)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
     using Base::operator*=;
 
     /** Constructs a Mapped Quaternion object from the pointer \a coeffs
@@ -461,7 +461,7 @@ EIGEN_STRONG_INLINE Derived& QuaternionBase<Derived>::operator*= (const Quaterni
   */
 template <class Derived>
 EIGEN_STRONG_INLINE typename QuaternionBase<Derived>::Vector3
-QuaternionBase<Derived>::_transformVector(Vector3 v) const
+QuaternionBase<Derived>::_transformVector(const Vector3& v) const
 {
     // Note that this algorithm comes from the optimization by hand
     // of the conversion to a Matrix followed by a Matrix/Vector product.
@@ -637,7 +637,7 @@ inline Quaternion<typename internal::traits<Derived>::Scalar> QuaternionBase<Der
 {
   // FIXME should this function be called multiplicativeInverse and conjugate() be called inverse() or opposite()  ??
   Scalar n2 = this->squaredNorm();
-  if (n2 > 0)
+  if (n2 > Scalar(0))
     return Quaternion<Scalar>(conjugate().coeffs() / n2);
   else
   {
@@ -667,12 +667,10 @@ template <class OtherDerived>
 inline typename internal::traits<Derived>::Scalar
 QuaternionBase<Derived>::angularDistance(const QuaternionBase<OtherDerived>& other) const
 {
-  using std::acos;
+  using std::atan2;
   using std::abs;
-  Scalar d = abs(this->dot(other));
+  Quaternion<Scalar> d = (*this) * other.conjugate();
-  if (d>=Scalar(1))
+  return Scalar(2) * atan2( d.vec().norm(), abs(d.w()) );
-    return Scalar(0);
-  return Scalar(2) * acos(d);
 }
 
  
@@ -712,7 +710,7 @@ QuaternionBase<Derived>::slerp(const Scalar& t, const QuaternionBase<OtherDerive
     scale0 = sin( ( Scalar(1) - t ) * theta) / sinTheta;
     scale1 = sin( ( t * theta) ) / sinTheta;
   }
-  if(d<0) scale1 = -scale1;
+  if(d<Scalar(0)) scale1 = -scale1;
 
   return Quaternion<Scalar>(scale0 * coeffs() + scale1 * other.coeffs());
 }

gtsam/3rdparty/Eigen/Eigen/src/Geometry/Rotation2D.h

@@ -60,6 +60,9 @@ public:
 
   /** Construct a 2D counter clock wise rotation from the angle \a a in radian. */
   inline Rotation2D(const Scalar& a) : m_angle(a) {}
+  
+  /** Default constructor wihtout initialization. The represented rotation is undefined. */
+  Rotation2D() {}
 
   /** \returns the rotation angle */
   inline Scalar angle() const { return m_angle; }
@@ -81,10 +84,10 @@ public:
   /** Applies the rotation to a 2D vector */
   Vector2 operator* (const Vector2& vec) const
   { return toRotationMatrix() * vec; }
-
+  
   template<typename Derived>
   Rotation2D& fromRotationMatrix(const MatrixBase<Derived>& m);
-  Matrix2 toRotationMatrix(void) const;
+  Matrix2 toRotationMatrix() const;
 
   /** \returns the spherical interpolation between \c *this and \a other using
     * parameter \a t. It is in fact equivalent to a linear interpolation.

gtsam/3rdparty/Eigen/Eigen/src/Geometry/Transform.h

@@ -62,6 +62,8 @@ struct transform_construct_from_matrix;
 
 template<typename TransformType> struct transform_take_affine_part;
 
+template<int Mode> struct transform_make_affine;
+
 } // end namespace internal
 
 /** \geometry_module \ingroup Geometry_Module
@@ -230,8 +232,7 @@ public:
   inline Transform()
   {
     check_template_params();
-    if (int(Mode)==Affine)
+    internal::transform_make_affine<(int(Mode)==Affine) ? Affine : AffineCompact>::run(m_matrix);
-      makeAffine();
   }
 
   inline Transform(const Transform& other)
@@ -591,11 +592,7 @@ public:
     */
   void makeAffine()
   {
-    if(int(Mode)!=int(AffineCompact))
+    internal::transform_make_affine<int(Mode)>::run(m_matrix);
-    {
-      matrix().template block<1,Dim>(Dim,0).setZero();
-      matrix().coeffRef(Dim,Dim) = Scalar(1);
-    }
   }
 
   /** \internal
@@ -1079,6 +1076,24 @@ Transform<Scalar,Dim,Mode,Options>::fromPositionOrientationScale(const MatrixBas
 
 namespace internal {
 
+template<int Mode>
+struct transform_make_affine
+{
+  template<typename MatrixType>
+  static void run(MatrixType &mat)
+  {
+    static const int Dim = MatrixType::ColsAtCompileTime-1;
+    mat.template block<1,Dim>(Dim,0).setZero();
+    mat.coeffRef(Dim,Dim) = typename MatrixType::Scalar(1);
+  }
+};
+
+template<>
+struct transform_make_affine<AffineCompact>
+{
+  template<typename MatrixType> static void run(MatrixType &) { }
+};
+    
 // selector needed to avoid taking the inverse of a 3x4 matrix
 template<typename TransformType, int Mode=TransformType::Mode>
 struct projective_transform_inverse

gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h

@@ -65,10 +65,10 @@ class DiagonalPreconditioner
       {
         typename MatType::InnerIterator it(mat,j);
         while(it && it.index()!=j) ++it;
-        if(it && it.index()==j)
+        if(it && it.index()==j && it.value()!=Scalar(0))
           m_invdiag(j) = Scalar(1)/it.value();
         else
-          m_invdiag(j) = 0;
+          m_invdiag(j) = Scalar(1);
       }
       m_isInitialized = true;
       return *this;

gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h

@@ -39,7 +39,6 @@ bool bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
   int maxIters = iters;
 
   int n = mat.cols();
-  x = precond.solve(x);
   VectorType r  = rhs - mat * x;
   VectorType r0 = r;
   
@@ -143,7 +142,7 @@ struct traits<BiCGSTAB<_MatrixType,_Preconditioner> >
   * SparseMatrix<double> A(n,n);
   * // fill A and b
   * BiCGSTAB<SparseMatrix<double> > solver;
-  * solver(A);
+  * solver.compute(A);
   * x = solver.solve(b);
   * std::cout << "#iterations:     " << solver.iterations() << std::endl;
   * std::cout << "estimated error: " << solver.error()      << std::endl;
@@ -152,20 +151,7 @@ struct traits<BiCGSTAB<_MatrixType,_Preconditioner> >
   * \endcode
   * 
   * By default the iterations start with x=0 as an initial guess of the solution.
-  * One can control the start using the solveWithGuess() method. Here is a step by
+  * One can control the start using the solveWithGuess() method.
-  * step execution example starting with a random guess and printing the evolution
-  * of the estimated error:
-  * * \code
-  * x = VectorXd::Random(n);
-  * solver.setMaxIterations(1);
-  * int i = 0;
-  * do {
-  *   x = solver.solveWithGuess(b,x);
-  *   std::cout << i << " : " << solver.error() << std::endl;
-  *   ++i;
-  * } while (solver.info()!=Success && i<100);
-  * \endcode
-  * Note that such a step by step excution is slightly slower.
   * 
   * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
   */
@@ -200,7 +186,8 @@ public:
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  BiCGSTAB(const MatrixType& A) : Base(A) {}
+  template<typename MatrixDerived>
+  explicit BiCGSTAB(const EigenBase<MatrixDerived>& A) : Base(A.derived()) {}
 
   ~BiCGSTAB() {}
   

gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h

@@ -112,9 +112,9 @@ struct traits<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
   * This class allows to solve for A.x = b sparse linear problems using a conjugate gradient algorithm.
   * The sparse matrix A must be selfadjoint. The vectors x and b can be either dense or sparse.
   *
-  * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix.
+  * \tparam _MatrixType the type of the matrix A, can be a dense or a sparse matrix.
-  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower,
-  *               or Upper. Default is Lower.
+  *               Upper, or Lower|Upper in which the full matrix entries will be considered. Default is Lower.
   * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
   *
   * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
@@ -137,20 +137,7 @@ struct traits<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
   * \endcode
   * 
   * By default the iterations start with x=0 as an initial guess of the solution.
-  * One can control the start using the solveWithGuess() method. Here is a step by
+  * One can control the start using the solveWithGuess() method.
-  * step execution example starting with a random guess and printing the evolution
-  * of the estimated error:
-  * * \code
-  * x = VectorXd::Random(n);
-  * cg.setMaxIterations(1);
-  * int i = 0;
-  * do {
-  *   x = cg.solveWithGuess(b,x);
-  *   std::cout << i << " : " << cg.error() << std::endl;
-  *   ++i;
-  * } while (cg.info()!=Success && i<100);
-  * \endcode
-  * Note that such a step by step excution is slightly slower.
   * 
   * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
   */
@@ -189,7 +176,8 @@ public:
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  ConjugateGradient(const MatrixType& A) : Base(A) {}
+  template<typename MatrixDerived>
+  explicit ConjugateGradient(const EigenBase<MatrixDerived>& A) : Base(A.derived()) {}
 
   ~ConjugateGradient() {}
   
@@ -213,6 +201,10 @@ public:
   template<typename Rhs,typename Dest>
   void _solveWithGuess(const Rhs& b, Dest& x) const
   {
+    typedef typename internal::conditional<UpLo==(Lower|Upper),
+                                           const MatrixType&,
+                                           SparseSelfAdjointView<const MatrixType, UpLo>
+                                          >::type MatrixWrapperType;
     m_iterations = Base::maxIterations();
     m_error = Base::m_tolerance;
 
@@ -222,8 +214,7 @@ public:
       m_error = Base::m_tolerance;
 
       typename Dest::ColXpr xj(x,j);
-      internal::conjugate_gradient(mp_matrix->template selfadjointView<UpLo>(), b.col(j), xj,
+      internal::conjugate_gradient(MatrixWrapperType(*mp_matrix), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
-                                   Base::m_preconditioner, m_iterations, m_error);
     }
 
     m_isInitialized = true;
@@ -234,7 +225,7 @@ public:
   template<typename Rhs,typename Dest>
   void _solve(const Rhs& b, Dest& x) const
   {
-    x.setOnes();
+    x.setZero();
     _solveWithGuess(b,x);
   }
 

gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h

@@ -150,7 +150,6 @@ class IncompleteLUT : internal::noncopyable
     {
       analyzePattern(amat); 
       factorize(amat);
-      m_isInitialized = m_factorizationIsOk;
       return *this;
     }
 
@@ -160,7 +159,7 @@ class IncompleteLUT : internal::noncopyable
     template<typename Rhs, typename Dest>
     void _solve(const Rhs& b, Dest& x) const
     {
-      x = m_Pinv * b;  
+      x = m_Pinv * b;
       x = m_lu.template triangularView<UnitLower>().solve(x);
       x = m_lu.template triangularView<Upper>().solve(x);
       x = m_P * x; 
@@ -223,18 +222,29 @@ template<typename _MatrixType>
 void IncompleteLUT<Scalar>::analyzePattern(const _MatrixType& amat)
 {
   // Compute the Fill-reducing permutation
+  // Since ILUT does not perform any numerical pivoting,
+  // it is highly preferable to keep the diagonal through symmetric permutations.
+#ifndef EIGEN_MPL2_ONLY
+  // To this end, let's symmetrize the pattern and perform AMD on it.
   SparseMatrix<Scalar,ColMajor, Index> mat1 = amat;
   SparseMatrix<Scalar,ColMajor, Index> mat2 = amat.transpose();
-  // Symmetrize the pattern
   // FIXME for a matrix with nearly symmetric pattern, mat2+mat1 is the appropriate choice.
   //       on the other hand for a really non-symmetric pattern, mat2*mat1 should be prefered...
   SparseMatrix<Scalar,ColMajor, Index> AtA = mat2 + mat1;
-  AtA.prune(keep_diag());
+  AMDOrdering<Index> ordering;
-  internal::minimum_degree_ordering<Scalar, Index>(AtA, m_P);  // Then compute the AMD ordering...
+  ordering(AtA,m_P);
-
+  m_Pinv  = m_P.inverse(); // cache the inverse permutation
-  m_Pinv  = m_P.inverse(); // ... and the inverse permutation
+#else
+  // If AMD is not available, (MPL2-only), then let's use the slower COLAMD routine.
+  SparseMatrix<Scalar,ColMajor, Index> mat1 = amat;
+  COLAMDOrdering<Index> ordering;
+  ordering(mat1,m_Pinv);
+  m_P = m_Pinv.inverse();
+#endif
 
   m_analysisIsOk = true;
+  m_factorizationIsOk = false;
+  m_isInitialized = false;
 }
 
 template <typename Scalar>
@@ -442,6 +452,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
   m_lu.makeCompressed();
 
   m_factorizationIsOk = true;
+  m_isInitialized = m_factorizationIsOk;
   m_info = Success;
 }
 

gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h

@@ -49,10 +49,11 @@ public:
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  IterativeSolverBase(const MatrixType& A)
+  template<typename InputDerived>
+  IterativeSolverBase(const EigenBase<InputDerived>& A)
   {
     init();
-    compute(A);
+    compute(A.derived());
   }
 
   ~IterativeSolverBase() {}
@@ -62,9 +63,11 @@ public:
     * Currently, this function mostly call analyzePattern on the preconditioner. In the future
     * we might, for instance, implement column reodering for faster matrix vector products.
     */
-  Derived& analyzePattern(const MatrixType& A)
+  template<typename InputDerived>
+  Derived& analyzePattern(const EigenBase<InputDerived>& A)
   {
-    m_preconditioner.analyzePattern(A);
+    grabInput(A.derived());
+    m_preconditioner.analyzePattern(*mp_matrix);
     m_isInitialized = true;
     m_analysisIsOk = true;
     m_info = Success;
@@ -80,11 +83,12 @@ public:
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  Derived& factorize(const MatrixType& A)
+  template<typename InputDerived>
+  Derived& factorize(const EigenBase<InputDerived>& A)
   {
+    grabInput(A.derived());
     eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); 
-    mp_matrix = &A;
+    m_preconditioner.factorize(*mp_matrix);
-    m_preconditioner.factorize(A);
     m_factorizationIsOk = true;
     m_info = Success;
     return derived();
@@ -100,10 +104,11 @@ public:
     * this class becomes invalid. Call compute() to update it with the new
     * matrix A, or modify a copy of A.
     */
-  Derived& compute(const MatrixType& A)
+  template<typename InputDerived>
+  Derived& compute(const EigenBase<InputDerived>& A)
   {
-    mp_matrix = &A;
+    grabInput(A.derived());
-    m_preconditioner.compute(A);
+    m_preconditioner.compute(*mp_matrix);
     m_isInitialized = true;
     m_analysisIsOk = true;
     m_factorizationIsOk = true;
@@ -212,6 +217,28 @@ public:
   }
 
 protected:
+
+  template<typename InputDerived>
+  void grabInput(const EigenBase<InputDerived>& A)
+  {
+    // we const cast to prevent the creation of a MatrixType temporary by the compiler.
+    grabInput_impl(A.const_cast_derived());
+  }
+
+  template<typename InputDerived>
+  void grabInput_impl(const EigenBase<InputDerived>& A)
+  {
+    m_copyMatrix = A;
+    mp_matrix = &m_copyMatrix;
+  }
+
+  void grabInput_impl(MatrixType& A)
+  {
+    if(MatrixType::RowsAtCompileTime==Dynamic && MatrixType::ColsAtCompileTime==Dynamic)
+      m_copyMatrix.resize(0,0);
+    mp_matrix = &A;
+  }
+
   void init()
   {
     m_isInitialized = false;
@@ -220,6 +247,7 @@ protected:
     m_maxIterations = -1;
     m_tolerance = NumTraits<Scalar>::epsilon();
   }
+  MatrixType m_copyMatrix;
   const MatrixType* mp_matrix;
   Preconditioner m_preconditioner;
 

gtsam/3rdparty/Eigen/Eigen/src/LU/FullPivLU.h

@@ -374,6 +374,12 @@ template<typename _MatrixType> class FullPivLU
     inline Index cols() const { return m_lu.cols(); }
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+    
     MatrixType m_lu;
     PermutationPType m_p;
     PermutationQType m_q;
@@ -418,6 +424,8 @@ FullPivLU<MatrixType>::FullPivLU(const MatrixType& matrix)
 template<typename MatrixType>
 FullPivLU<MatrixType>& FullPivLU<MatrixType>::compute(const MatrixType& matrix)
 {
+  check_template_parameters();
+  
   // the permutations are stored as int indices, so just to be sure:
   eigen_assert(matrix.rows()<=NumTraits<int>::highest() && matrix.cols()<=NumTraits<int>::highest());