diff --git a/.gitignore b/.gitignore index 2054550..3fbea51 100644 --- a/.gitignore +++ b/.gitignore @@ -30,3 +30,4 @@ TAGS /cmake-* *.m~ python/*.egg-info/ +/doc/_build/ diff --git a/.readthedocs.yml b/.readthedocs.yml new file mode 100644 index 0000000..bbefaf0 --- /dev/null +++ b/.readthedocs.yml @@ -0,0 +1,9 @@ +version: 2 + +sphinx: + configuration: doc/conf.py + +python: + version: 3.6 + install: + - requirements: doc/requirements.txt \ No newline at end of file diff --git a/CMakeLists.txt b/CMakeLists.txt index 5ee7b2d..75ec587 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -6,11 +6,11 @@ set(CMAKE_CXX_STANDARD 14) set(CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/modules/" ${CMAKE_MODULE_PATH}) # Check build types -if(NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES) +if (NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES) message(STATUS "Setting build type to 'Release' as none was specified.") set(CMAKE_BUILD_TYPE "Release" CACHE STRING "Choose the type of build." FORCE) -endif() +endif () # Options option(BUILD_TESTS "Build tests" ON) @@ -19,7 +19,8 @@ option(BUILD_MATLAB_BINDINGS "Build MATLAB bindings" OFF) option(BUILD_PYTHON_BINDINGS "Build Python bindings" ON) option(BUILD_DOC "Build documentation" ON) option(BUILD_WITH_MARCH_NATIVE "Build with flag march=native" OFF) -option(ENABLE_DIAGNOSTIC_PRINT "Enable printing of diagnostic messages" OFF) +option(ENABLE_MKL "Try to use Eigen with MKL" OFF) +option(ENABLE_DIAGNOSTIC_PRINT "Enable printing of diagnostic messages" ON) if (ENABLE_DIAGNOSTIC_PRINT) message(STATUS "Enable printing of diagnostic messages.") @@ -34,6 +35,17 @@ endif () # Find dependencies # Eigen3 find_package(Eigen3 3.2 QUIET REQUIRED NO_MODULE) +if (ENABLE_MKL) + find_package(MKL) + if (MKL_FOUND) + message(STATUS "MKL found at: ${MKL_LIBRARIES}") + include_directories(${MKL_INCLUDE_DIR}) + add_definitions(-DEIGEN_USE_MKL_ALL) + list(APPEND TEASERPP_BLAS_LAPACK_LIBS ${MKL_LIBRARIES}) + else () + message(STATUS "MKL not found.") + endif () +endif () if (BUILD_TEASER_FPFH) # Boost @@ -73,6 +85,14 @@ add_subdirectory("${CMAKE_BINARY_DIR}/tinyply-src" target_include_directories(tinyply PUBLIC $) +# spectra +configure_file(cmake/spectra.CMakeLists.txt.in spectra-download/CMakeLists.txt) +execute_process(COMMAND "${CMAKE_COMMAND}" -G "${CMAKE_GENERATOR}" . + WORKING_DIRECTORY "${CMAKE_BINARY_DIR}/spectra-download") +execute_process(COMMAND "${CMAKE_COMMAND}" --build . + WORKING_DIRECTORY "${CMAKE_BINARY_DIR}/spectra-download") +set(SPECTRA_INCLUDE_DIRS "${CMAKE_BINARY_DIR}/spectra-src/include") + # Building Targets set(TEASERPP_ROOT ${CMAKE_CURRENT_LIST_DIR}) add_subdirectory(teaser) @@ -111,5 +131,5 @@ endif () export(TARGETS ${TEASERPP_EXPORTED_TARGETS} FILE teaserpp-exports.cmake) install(FILES cmake/teaserppConfig.cmake - DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/teaserpp -) + DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/teaserpp + ) diff --git a/README.md b/README.md index 54a9252..ed43ed8 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,6 @@ # TEASER++: fast & certifiable 3D registration [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) +[![Documentation Status](https://readthedocs.org/projects/teaser/badge/?version=latest)](https://teaser.readthedocs.io/en/latest/?badge=latest) [](https://github.com/MIT-SPARK/TEASER-plusplus/actions) ![TEASER++ 3DSmooth](examples/teaser_python_3dsmooth/3dsmooth_example.gif) @@ -144,152 +145,22 @@ You should be able to see Open3D windows showing registration results: ![TEASER++ 3DSmooth](examples/teaser_python_3dsmooth/3dsmooth_example.gif) ## Getting Started -### Supported Platforms -TEASER++ has been tested on Ubuntu 18.04 with g++-7/9 and clang++-7/8/9. - -### Installing Dependencies -Building TEASER++ requires the following libraries installed: -1. A compiler that supports OpenMP. See [here](https://www.openmp.org/resources/openmp-compilers-tools/) for a list. -2. CMake >= 3.10 -3. Eigen3 >= 3.3 -4. PCL >= 1.9 (optional) -5. Boost >= 1.58 (optional) - -Run the following script to install all required dependencies: -```shell script -sudo apt install cmake libeigen3-dev libboost-all-dev -``` - -Run the following script to install PCL from source: -```shell script -# Compile and install PCL 1.91 from source -PCL_PACKAGE_DIR="$HOME/pcl" -mkdir "$PCL_PACKAGE_DIR" -cd "$PCL_PACKAGE_DIR" -wget "https://github.com/PointCloudLibrary/pcl/archive/pcl-1.9.1.zip" -unzip pcl-*.zip -rm pcl-*.zip -cd pcl-* && mkdir build && cd build -cmake .. -make -j $(python3 -c 'import multiprocessing as mp; print(int(mp.cpu_count() * 1.5))') -sudo make install -``` -Notice that PCL is not required for the TEASER++ registration library. Installing it merely allows you to build example tests that uses PCL's FPFH features for registration. - -If you want to build Python bindings, you also need: -1. Python 2 or 3 (make sure to include the desired interpreter in your `PATH` variable) - -If you want to build MATLAB bindings, you also need: -1. MATLAB -2. CMake >= 3.13 - -TEASER++ uses the Parallel Maximum Clique ([paper](https://arxiv.org/abs/1302.6256), [code](https://github.com/ryanrossi/pmc)) for maximum clique calculation. It will be downloaded automatically during CMake configuration. In addition, CMake will also download Google Test and pybind11 if necessary. - -### Compilation and Installation -Clone the repo to your local directory. Open a terminal in the repo root directory. Run the following commands: -```shell -# Clone the repo -git clone https://github.com/MIT-SPARK/TEASER-plusplus.git - -# Configure and compile -cd TEASER-plusplus && mkdir build -cd build -cmake .. -make - -# Generate doxygen documentation in doc/ -make doc - -# Run tests -ctest - -# Install shared libraries and headers -sudo make install -``` - -### Available CMake Options -Here are the available CMake options you can turn on/off during configuration: - -| Option Name | Description | Default Value | -|------------------------|---------------------|---------------| -|`BUILD_TESTS` | Build tests | ON | -|`BUILD_TEASER_FPFH` | Build TEASER++ wrappers for PCL FPFH estimation | OFF | -|`BUILD_MATLAB_BINDINGS` | Build MATLAB bindings | OFF | -|`BUILD_PYTHON_BINDINGS` | Build Python bindings | ON | -|`BUILD_DOC` | Build documentation | ON | -|`BUILD_WITH_MARCH_NATIVE`| Build with flag `march=native` | OFF | -|`ENABLE_DIAGNOSTIC_PRINT`| Enable printing of diagnostic messages | OFF | - -For example, if you want to build with the `march=native` flag (potentially faster at a loss of binary portability), run the following script for compilation: -```shell script -cmake -DBUILD_WITH_MARCH_NATIVE=ON .. -make -``` -Notice that by default the library is built in release mode. To build with debug symbols enabled, use the following commands: -```shell script -cmake -DCMAKE_BUILD_TYPE=Debug .. -make -``` - -### Run Tests -By default, the library is built in release mode. If you instead choose to build it in debug mode, some tests are likely to time out. - -To run tests and benchmarks (for speed & accuracy tests), you can execute the following command: -```shell -# Run all tests -ctest - -# Run benchmarks -ctest --verbose -R RegistrationBenchmark.* -``` -The `--verbose` option allows you to see the output, as well as the summary tables generated by each benchmark. - -## How to use TEASER++ -### In CMake-based C++ Projects -When installing TEASER++, CMake will export the following targets that can be included in other CMake projects using `find_package()`: -- `teaserpp::teaser_registration`: the core registration library -- `teaserpp::teaser_io`: library for importing `.ply` files -- `teaserpp::teaser_features`: convenience wrappers around the PCL FPFH library, and simple feature matching functions - -A minimally-working `CMakeList.txt` looks something like this: -```cmake -cmake_minimum_required(VERSION 3.10) -project(teaserpp_example) - -set (CMAKE_CXX_STANDARD 14) - -find_package(Eigen3 REQUIRED) -find_package(teaserpp REQUIRED) - -# Change this line to include your own executable file -add_executable(cpp_example cpp_example.cpp) - -# Link to teaserpp & Eigen3 -target_link_libraries(cpp_example Eigen3::Eigen teaserpp::teaser_registration teaserpp::teaser_io) -``` - -In the `examples/` folder, you can find two C++ examples that can be compiled with CMake: -- [`teaser_cpp_ply`](/examples/teaser_cpp_ply): showing how to import `.ply` files and perform registration with TEASER++ -- [`teaser_cpp_fpfh`](/examples/teaser_cpp_fpfh): showing how to use TEASER++ with FPFH features - -### In Python -In the `examples/` folder, you can find two C++ examples that can be compiled with CMake: -- [`teaser_python_ply`](/examples/teaser_python_ply): showing how to import `.ply` files and perform registration with TEASER++ and Open3D -- [`teaser_python_3dsmooth`](/examples/teaser_python_3dsmooth): showing how to use TEASER++ on descriptors generated by [3DSmoothNet](https://github.com/zgojcic/3DSmoothNet) on the 3DMatch dataset, with Open3D visualization - -For a short documentation on how to use the Python bindings for TEASER++, please refer to [this](python/README.md) document. - -### In MATLAB -For a short documentation on how to use the MATLAB bindings for TEASER++, please refer to [this](matlab/README.md) document. - -### In ROS -To use TEASER++ in a ROS environment, simple clone the repo to your catkin workspace. - -## Known Issues -- If you are encountering segmentation faults from PMC, try add the environmental variable `OMP_NUM_THREADS=${MAX_THREADS}` (replace ${MAX_THREADS} with the maximum number of threads available on your machine) in your current shell. You can also just prepend `OMP_NUM_THREADS=${MAX_THREADS}` when running your executable. -- When using the MATLAB wrapper with MATLAB on terminal (`-nojvm` option enabled), you might encounter errors similar to this: -`/usr/local/MATLAB/R2019a/bin/glnxa64/MATLAB: symbol lookup error: /opt/intel/compilers_and_libraries_2019.4.243/linux/mkl/lib/intel64_lin/libmkl_vml_avx2.so: undefined symbol: mkl_serv_getenv`. One way to get around this is to run the following command in the environment where you start MATLAB: -`export LD_PRELOAD=/opt/intel/mkl/lib/intel64/libmkl_intel_lp64.so:/opt/intel/mkl/lib/intel64/libmkl_gnu_thread.so:/opt/intel/mkl/lib/intel64/libmkl_core.so`. You may need to change the paths according to your MKL installation. +- Installation + - [Dependencies](https://teaser.readthedocs.io/en/latest/installation.html#installing-dependencies) + - [Compilation](https://teaser.readthedocs.io/en/latest/installation.html#compilation-and-installation) + - [Install C++ Libraries](https://teaser.readthedocs.io/en/latest/installation.html#installing-c-libraries-and-headers) + - [Install Python Bindings](https://teaser.readthedocs.io/en/latest/installation.html#installing-python-bindings) + - [Install MATLAB Bindings](https://teaser.readthedocs.io/en/latest/installation.html#installing-matlab-bindings) + - [Run Tests](https://teaser.readthedocs.io/en/latest/installation.html#run-tests) +- Usage + - [In C++](https://teaser.readthedocs.io/en/latest/quickstart.html#usage-in-c-projects) + - [In Python](https://teaser.readthedocs.io/en/latest/quickstart.html#usage-in-python-projects) + - [In MATLAB](https://teaser.readthedocs.io/en/latest/quickstart.html#usage-in-matlab-projects) + - [In ROS](https://teaser.readthedocs.io/en/latest/quickstart.html#usage-in-ros-projects) +- API Documentation + - [C++](https://teaser.readthedocs.io/en/latest/api-cpp.html) + - [Python](https://teaser.readthedocs.io/en/latest/api-python.html) + - [MATLAB](https://teaser.readthedocs.io/en/latest/api-matlab.html) ## Other Publications Other publications related to TEASER include: diff --git a/cmake/modules/FindLAPACK.cmake b/cmake/modules/FindLAPACK.cmake new file mode 100644 index 0000000..4eaee1f --- /dev/null +++ b/cmake/modules/FindLAPACK.cmake @@ -0,0 +1,464 @@ +# Distributed under the OSI-approved BSD 3-Clause License. See accompanying +# file Copyright.txt or https://cmake.org/licensing for details. + +#[=======================================================================[.rst: + +FindLapack +---------- + +* Michael Hirsch, Ph.D. www.scivision.dev +* David Eklund + +Let Michael know if there are more MKL / Lapack / compiler combination you want. +Refer to https://software.intel.com/en-us/articles/intel-mkl-link-line-advisor + +Finds LAPACK libraries for C / C++ / Fortran. +Works with Netlib Lapack / LapackE, Atlas and Intel MKL. +Intel MKL relies on having environment variable MKLROOT set, typically by sourcing +mklvars.sh beforehand. + +Why not the FindLapack.cmake built into CMake? It has a lot of old code for +infrequently used Lapack libraries and is unreliable for me. + +Tested on Linux, MacOS and Windows with: +* GCC / Gfortran +* Clang / Flang +* PGI (pgcc, pgfortran) +* Intel (icc, ifort) + + +Parameters +^^^^^^^^^^ + +COMPONENTS default to Netlib LAPACK / LapackE, otherwise: + +``MKL`` + Intel MKL for MSVC, ICL, ICC, GCC and PGCC -- sequential by default, or add TBB or MPI as well +``OpenMP`` + Intel MPI with OpenMP threading addition to MKL +``TBB`` + Intel MPI + TBB for MKL +``MKL64`` + MKL only: 64-bit integers (default is 32-bit integers) + +``LAPACKE`` + Netlib LapackE for C / C++ +``Netlib`` + Netlib Lapack for Fortran +``OpenBLAS`` + OpenBLAS Lapack for Fortran + +``LAPACK95`` + get Lapack95 interfaces for MKL or Netlib (must also specify one of MKL, Netlib) + + +Result Variables +^^^^^^^^^^^^^^^^ + +``LAPACK_FOUND`` + Lapack libraries were found +``LAPACK__FOUND`` + LAPACK specified was found +``LAPACK_LIBRARIES`` + Lapack library files (including BLAS +``LAPACK_INCLUDE_DIRS`` + Lapack include directories (for C/C++) + + +References +^^^^^^^^^^ + +* Pkg-Config and MKL: https://software.intel.com/en-us/articles/intel-math-kernel-library-intel-mkl-and-pkg-config-tool +* MKL for Windows: https://software.intel.com/en-us/mkl-windows-developer-guide-static-libraries-in-the-lib-intel64-win-directory +* MKL Windows directories: https://software.intel.com/en-us/mkl-windows-developer-guide-high-level-directory-structure +* Atlas http://math-atlas.sourceforge.net/errata.html#LINK +* MKL LAPACKE (C, C++): https://software.intel.com/en-us/mkl-linux-developer-guide-calling-lapack-blas-and-cblas-routines-from-c-c-language-environments +#]=======================================================================] + +# clear to avoid endless appending on subsequent calls +set(LAPACK_LIBRARY) +set(LAPACK_INCLUDE_DIR) + +# ===== functions ========== + +function(atlas_libs) + +find_library(ATLAS_LIB + NAMES atlas + NAMES_PER_DIR + PATH_SUFFIXES atlas) + +pkg_check_modules(pc_atlas_lapack lapack-atlas QUIET) + +find_library(LAPACK_ATLAS + NAMES ptlapack lapack_atlas lapack + NAMES_PER_DIR + PATH_SUFFIXES atlas + HINTS ${pc_atlas_lapack_LIBRARY_DIRS} ${pc_atlas_lapack_LIBDIR}) + +pkg_check_modules(pc_atlas_blas blas-atlas QUIET) + +find_library(BLAS_LIBRARY + NAMES ptf77blas f77blas blas + NAMES_PER_DIR + PATH_SUFFIXES atlas + HINTS ${pc_atlas_blas_LIBRARY_DIRS} ${pc_atlas_blas_LIBDIR}) +# === C === +find_library(BLAS_C_ATLAS + NAMES ptcblas cblas + NAMES_PER_DIR + PATH_SUFFIXES atlas + HINTS ${pc_atlas_blas_LIBRARY_DIRS} ${pc_atlas_blas_LIBDIR}) + +find_path(LAPACK_INCLUDE_DIR + NAMES cblas-atlas.h cblas.h clapack.h + HINTS ${pc_atlas_blas_INCLUDE_DIRS} ${pc_atlas_blas_LIBDIR}) + +#=========== +if(LAPACK_ATLAS AND BLAS_C_ATLAS AND BLAS_LIBRARY AND ATLAS_LIB) + set(LAPACK_Atlas_FOUND true PARENT_SCOPE) + set(LAPACK_LIBRARY ${LAPACK_ATLAS} ${BLAS_C_ATLAS} ${BLAS_LIBRARY} ${ATLAS_LIB}) + if(NOT WIN32) + find_package(Threads) # not required--for example Flang + list(APPEND LAPACK_LIBRARY ${CMAKE_THREAD_LIBS_INIT}) + endif() +endif() + +set(LAPACK_LIBRARY ${LAPACK_LIBRARY} PARENT_SCOPE) +set(LAPACK_INCLUDE_DIR ${LAPACK_INCLUDE_DIR} PARENT_SCOPE) + +endfunction(atlas_libs) + +#======================= + +function(netlib_libs) + +if(LAPACK95 IN_LIST LAPACK_FIND_COMPONENTS) + find_path(LAPACK95_INCLUDE_DIR + NAMES f95_lapack.mod + PATH_SUFFIXES include + PATHS ${LAPACK95_ROOT}) + + find_library(LAPACK95_LIBRARY + NAMES lapack95 + NAMES_PER_DIR + PATH_SUFFIXES lib + PATHS ${LAPACK95_ROOT}) + + if(LAPACK95_LIBRARY AND LAPACK95_INCLUDE_DIR) + set(LAPACK_INCLUDE_DIR ${LAPACK95_INCLUDE_DIR}) + set(LAPACK_LIBRARY ${LAPACK95_LIBRARY}) + else() + return() + endif() +endif(LAPACK95 IN_LIST LAPACK_FIND_COMPONENTS) + +set(_lapack_hints) +if(CMAKE_Fortran_COMPILER_ID STREQUAL PGI) + get_filename_component(_pgi_path ${CMAKE_Fortran_COMPILER} DIRECTORY) + set(_lapack_hints ${_pgi_path}/../) +endif() + +pkg_check_modules(pc_lapack lapack-netlib QUIET) +if(NOT pc_lapack_FOUND) + pkg_check_modules(pc_lapack lapack QUIET) # Netlib on Cygwin, Homebrew and others +endif() +find_library(LAPACK_LIB + NAMES lapack + NAMES_PER_DIR + PATHS /usr/local/opt # homebrew + HINTS ${_lapack_hints} ${pc_lapack_LIBRARY_DIRS} ${pc_lapack_LIBDIR} + PATH_SUFFIXES lib lapack lapack/lib) +if(LAPACK_LIB) + list(APPEND LAPACK_LIBRARY ${LAPACK_LIB}) +else() + return() +endif() + +if(LAPACKE IN_LIST LAPACK_FIND_COMPONENTS) + pkg_check_modules(pc_lapacke lapacke QUIET) + find_library(LAPACKE_LIBRARY + NAMES lapacke + NAMES_PER_DIR + PATHS /usr/local/opt + HINTS ${pc_lapacke_LIBRARY_DIRS} ${pc_lapacke_LIBDIR} + PATH_SUFFIXES lapack lapack/lib) + + # lapack/include for Homebrew + find_path(LAPACKE_INCLUDE_DIR + NAMES lapacke.h + PATHS /usr/local/opt + HINTS ${pc_lapacke_INCLUDE_DIRS} ${pc_lapacke_LIBDIR} + PATH_SUFFIXES lapack lapack/include) + + if(LAPACKE_LIBRARY AND LAPACKE_INCLUDE_DIR) + set(LAPACK_LAPACKE_FOUND true PARENT_SCOPE) + list(APPEND LAPACK_INCLUDE_DIR ${LAPACKE_INCLUDE_DIR}) + list(APPEND LAPACK_LIBRARY ${LAPACKE_LIBRARY}) + else() + message(WARNING "Trouble finding LAPACKE: + include: ${LAPACKE_INCLUDE_DIR} + libs: ${LAPACKE_LIBRARY}") + return() + endif() + + mark_as_advanced(LAPACKE_LIBRARY LAPACKE_INCLUDE_DIR) +endif(LAPACKE IN_LIST LAPACK_FIND_COMPONENTS) + +pkg_check_modules(pc_blas blas-netlib QUIET) +if(NOT pc_blas_FOUND) + pkg_check_modules(pc_blas blas QUIET) # Netlib on Cygwin and others +endif() +find_library(BLAS_LIBRARY + NAMES refblas blas + NAMES_PER_DIR + PATHS /usr/local/opt + HINTS ${_lapack_hints} ${pc_blas_LIBRARY_DIRS} ${pc_blas_LIBDIR} + PATH_SUFFIXES lib lapack lapack/lib blas) + +if(BLAS_LIBRARY) + list(APPEND LAPACK_LIBRARY ${BLAS_LIBRARY}) + set(LAPACK_Netlib_FOUND true PARENT_SCOPE) +else() + return() +endif() + +if(NOT WIN32) + list(APPEND LAPACK_LIBRARY ${CMAKE_THREAD_LIBS_INIT}) +endif() + +if(LAPACK95_LIBRARY) + set(LAPACK_LAPACK95_FOUND true PARENT_SCOPE) +endif() + +set(LAPACK_LIBRARY ${LAPACK_LIBRARY} PARENT_SCOPE) +set(LAPACK_INCLUDE_DIR ${LAPACK_INCLUDE_DIR} PARENT_SCOPE) + +endfunction(netlib_libs) + +#=============================== +function(openblas_libs) + +pkg_check_modules(pc_lapack lapack-openblas QUIET) +find_library(LAPACK_LIBRARY + NAMES lapack + NAMES_PER_DIR + HINTS ${pc_lapack_LIBRARY_DIRS} ${pc_lapack_LIBDIR} + PATH_SUFFIXES openblas) + + +pkg_check_modules(pc_blas blas-openblas QUIET) +find_library(BLAS_LIBRARY + NAMES openblas blas + NAMES_PER_DIR + HINTS ${pc_blas_LIBRARY_DIRS} ${pc_blas_LIBDIR} + PATH_SUFFIXES openblas) + +find_path(LAPACK_INCLUDE_DIR + NAMES cblas-openblas.h cblas.h f77blas.h openblas_config.h + HINTS ${pc_lapack_INCLUDE_DIRS}) + +if(LAPACK_LIBRARY AND BLAS_LIBRARY) + list(APPEND LAPACK_LIBRARY ${BLAS_LIBRARY}) + set(LAPACK_OpenBLAS_FOUND true PARENT_SCOPE) +else() + message(WARNING "Trouble finding OpenBLAS: + include: ${LAPACK_INCLUDE_DIR} + libs: ${LAPACK_LIBRARY} ${BLAS_LIBRARY}") + return() +endif() + +if(NOT WIN32) + find_package(Threads) # not required--for example Flang + list(APPEND LAPACK_LIBRARY ${CMAKE_THREAD_LIBS_INIT}) +endif() + +set(LAPACK_LIBRARY ${LAPACK_LIBRARY} PARENT_SCOPE) +set(LAPACK_INCLUDE_DIR ${LAPACK_INCLUDE_DIR} PARENT_SCOPE) + +endfunction(openblas_libs) + +#=============================== + +function(find_mkl_libs) +# https://software.intel.com/en-us/articles/intel-mkl-link-line-advisor + +set(_mkl_libs ${ARGV}) +if((UNIX AND NOT APPLE) AND CMAKE_Fortran_COMPILER_ID STREQUAL GNU) + list(INSERT _mkl_libs 0 mkl_gf_${_mkl_bitflag}lp64) +else() + list(INSERT _mkl_libs 0 mkl_intel_${_mkl_bitflag}lp64) +endif() + +# Note: Don't remove items from PATH_SUFFIXES unless you're extensively testing, +# each path is there for a specific reason! + +foreach(s ${_mkl_libs}) + find_library(LAPACK_${s}_LIBRARY + NAMES ${s} + NAMES_PER_DIR + PATHS ${MKLROOT} ENV TBBROOT + PATH_SUFFIXES + lib lib/intel64 lib/intel64_win + lib/intel64/gcc4.7 ../tbb/lib/intel64/gcc4.7 + lib/intel64/vc_mt ../tbb/lib/intel64/vc_mt + ../compiler/lib/intel64 + HINTS ${pc_mkl_LIBRARY_DIRS} ${pc_mkl_LIBDIR} + NO_DEFAULT_PATH) + + if(NOT LAPACK_${s}_LIBRARY) + message(STATUS "MKL component not found: " ${s}) + return() + endif() + + list(APPEND LAPACK_LIB ${LAPACK_${s}_LIBRARY}) +endforeach() + +if(NOT BUILD_SHARED_LIBS AND (UNIX AND NOT APPLE)) + set(LAPACK_LIB -Wl,--start-group ${LAPACK_LIB} -Wl,--end-group) +endif() + +set(BLAS_LIBRARY PARENT_SCOPE) +set(LAPACK_LIBRARY ${LAPACK_LIB} PARENT_SCOPE) +set(LAPACK_INCLUDE_DIR + ${MKLROOT}/include + ${MKLROOT}/include/intel64/${_mkl_bitflag}lp64 + PARENT_SCOPE) + # ${pc_mkl_INCLUDE_DIRS} has garbage on Windows + +endfunction(find_mkl_libs) + +# ========== main program + +if(NOT (OpenBLAS IN_LIST LAPACK_FIND_COMPONENTS + OR Netlib IN_LIST LAPACK_FIND_COMPONENTS + OR Atlas IN_LIST LAPACK_FIND_COMPONENTS + OR MKL IN_LIST LAPACK_FIND_COMPONENTS)) + if(DEFINED ENV{MKLROOT}) + list(APPEND LAPACK_FIND_COMPONENTS MKL) + else() + list(APPEND LAPACK_FIND_COMPONENTS Netlib) + endif() +endif() + +find_package(PkgConfig QUIET) + +# ==== generic MKL variables ==== + +if(MKL IN_LIST LAPACK_FIND_COMPONENTS) + # we have to sanitize MKLROOT if it has Windows backslashes (\) otherwise it will break at build time + # double-quotes are necessary per CMake to_cmake_path docs. + file(TO_CMAKE_PATH "$ENV{MKLROOT}" MKLROOT) + + list(APPEND CMAKE_PREFIX_PATH ${MKLROOT}/bin/pkgconfig) + + if(NOT WIN32) + find_package(Threads) + endif() + + if(BUILD_SHARED_LIBS) + set(_mkltype dynamic) + else() + set(_mkltype static) + endif() + + if(MKL64 IN_LIST LAPACK_FIND_COMPONENTS) + set(_mkl_bitflag i) + else() + set(_mkl_bitflag) + endif() + + unset(_mkl_libs) + if(LAPACK95 IN_LIST LAPACK_FIND_COMPONENTS) + list(APPEND _mkl_libs mkl_blas95_${_mkl_bitflag}lp64 mkl_lapack95_${_mkl_bitflag}lp64) + endif() + + unset(_tbb) + if(TBB IN_LIST LAPACK_FIND_COMPONENTS) + list(APPEND _mkl_libs mkl_tbb_thread mkl_core) + set(_tbb tbb stdc++) + if(WIN32) + list(APPEND _mkl_libs tbb.lib) + endif() + elseif(OpenMP IN_LIST LAPACK_FIND_COMPONENTS) + pkg_check_modules(pc_mkl mkl-${_mkltype}-${_mkl_bitflag}lp64-iomp QUIET) + + set(_mp iomp5) + if(WIN32) + set(_mp libiomp5md) # "lib" is indeed necessary, even on CMake 3.14.0 + endif() + list(APPEND _mkl_libs mkl_intel_thread mkl_core ${_mp}) + else() + pkg_check_modules(pc_mkl mkl-${_mkltype}-${_mkl_bitflag}lp64-seq QUIET) + list(APPEND _mkl_libs mkl_sequential mkl_core) + endif() + + find_mkl_libs(${_mkl_libs}) + + if(LAPACK_LIBRARY) + + if(NOT WIN32) + list(APPEND LAPACK_LIBRARY ${_tbb} ${CMAKE_THREAD_LIBS_INIT} ${CMAKE_DL_LIBS} m) + endif() + + set(LAPACK_MKL_FOUND true) + + if(MKL64 IN_LIST LAPACK_FIND_COMPONENTS) + set(LAPACK_MKL64_FOUND true) + endif() + + if(LAPACK95 IN_LIST LAPACK_FIND_COMPONENTS) + set(LAPACK_LAPACK95_FOUND true) + endif() + + if(OpenMP IN_LIST LAPACK_FIND_COMPONENTS) + set(LAPACK_OpenMP_FOUND true) + endif() + + if(TBB IN_LIST LAPACK_FIND_COMPONENTS) + set(LAPACK_TBB_FOUND true) + endif() + endif() + +elseif(Atlas IN_LIST LAPACK_FIND_COMPONENTS) + + atlas_libs() + +elseif(Netlib IN_LIST LAPACK_FIND_COMPONENTS) + + netlib_libs() + +elseif(OpenBLAS IN_LIST LAPACK_FIND_COMPONENTS) + + openblas_libs() + +endif() + +include(FindPackageHandleStandardArgs) +find_package_handle_standard_args(LAPACK + REQUIRED_VARS LAPACK_LIBRARY + HANDLE_COMPONENTS) + +set(BLAS_LIBRARIES ${BLAS_LIBRARY}) +set(LAPACK_LIBRARIES ${LAPACK_LIBRARY}) +set(LAPACK_INCLUDE_DIRS ${LAPACK_INCLUDE_DIR}) + +if(LAPACK_FOUND) +# need if _FOUND guard to allow project to autobuild; can't overwrite imported target even if bad + if(NOT TARGET BLAS::BLAS) + add_library(BLAS::BLAS INTERFACE IMPORTED) + set_target_properties(BLAS::BLAS PROPERTIES + INTERFACE_LINK_LIBRARIES "${BLAS_LIBRARY}" + ) + endif() + + if(NOT TARGET LAPACK::LAPACK) + add_library(LAPACK::LAPACK INTERFACE IMPORTED) + set_target_properties(LAPACK::LAPACK PROPERTIES + INTERFACE_LINK_LIBRARIES "${LAPACK_LIBRARY}" + INTERFACE_INCLUDE_DIRECTORIES "${LAPACK_INCLUDE_DIR}" + ) + endif() +endif() + +mark_as_advanced(LAPACK_LIBRARY LAPACK_INCLUDE_DIR) diff --git a/cmake/modules/FindMKL.cmake b/cmake/modules/FindMKL.cmake new file mode 100644 index 0000000..01ebc23 --- /dev/null +++ b/cmake/modules/FindMKL.cmake @@ -0,0 +1,481 @@ +# From PyTorch: +# +# Copyright (c) 2016- Facebook, Inc (Adam Paszke) +# Copyright (c) 2014- Facebook, Inc (Soumith Chintala) +# Copyright (c) 2011-2014 Idiap Research Institute (Ronan Collobert) +# Copyright (c) 2012-2014 Deepmind Technologies (Koray Kavukcuoglu) +# Copyright (c) 2011-2012 NEC Laboratories America (Koray Kavukcuoglu) +# Copyright (c) 2011-2013 NYU (Clement Farabet) +# Copyright (c) 2006-2010 NEC Laboratories America (Ronan Collobert, Leon Bottou, Iain Melvin, Jason Weston) +# Copyright (c) 2006 Idiap Research Institute (Samy Bengio) +# Copyright (c) 2001-2004 Idiap Research Institute (Ronan Collobert, Samy Bengio, Johnny Mariethoz) +# +# From Caffe2: +# +# Copyright (c) 2016-present, Facebook Inc. All rights reserved. +# +# All contributions by Facebook: +# Copyright (c) 2016 Facebook Inc. +# +# All contributions by Google: +# Copyright (c) 2015 Google Inc. +# All rights reserved. +# +# All contributions by Yangqing Jia: +# Copyright (c) 2015 Yangqing Jia +# All rights reserved. +# +# All contributions from Caffe: +# Copyright(c) 2013, 2014, 2015, the respective contributors +# All rights reserved. +# +# All other contributions: +# Copyright(c) 2015, 2016 the respective contributors +# All rights reserved. +# +# Caffe2 uses a copyright model similar to Caffe: each contributor holds +# copyright over their contributions to Caffe2. The project versioning records +# all such contribution and copyright details. If a contributor wants to further +# mark their specific copyright on a particular contribution, they should +# indicate their copyright solely in the commit message of the change when it is +# committed. +# +# All rights reserved. +# +# Redistribution and use in source and binary forms, with or without +# modification, are permitted provided that the following conditions are met: +# +# 1. Redistributions of source code must retain the above copyright +# notice, this list of conditions and the following disclaimer. +# +# 2. Redistributions in binary form must reproduce the above copyright +# notice, this list of conditions and the following disclaimer in the +# documentation and/or other materials provided with the distribution. +# +# 3. Neither the names of Facebook, Deepmind Technologies, NYU, NEC Laboratories America +# and IDIAP Research Institute nor the names of its contributors may be +# used to endorse or promote products derived from this software without +# specific prior written permission. +# +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE +# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +# POSSIBILITY OF SUCH DAMAGE. +# +# - Find INTEL MKL library +# +# This module sets the following variables: +# MKL_FOUND - set to true if a library implementing the CBLAS interface is found +# MKL_VERSION - best guess of the found mkl version +# MKL_INCLUDE_DIR - path to include dir. +# MKL_LIBRARIES - list of libraries for base mkl +# MKL_OPENMP_TYPE - OpenMP flavor that the found mkl uses: GNU or Intel +# MKL_OPENMP_LIBRARY - path to the OpenMP library the found mkl uses +# MKL_LAPACK_LIBRARIES - list of libraries to add for lapack +# MKL_SCALAPACK_LIBRARIES - list of libraries to add for scalapack +# MKL_SOLVER_LIBRARIES - list of libraries to add for the solvers +# MKL_CDFT_LIBRARIES - list of libraries to add for the solvers + +# Do nothing if MKL_FOUND was set before! +IF (NOT MKL_FOUND) + +SET(MKL_VERSION) +SET(MKL_INCLUDE_DIR) +SET(MKL_LIBRARIES) +SET(MKL_OPENMP_TYPE) +SET(MKL_OPENMP_LIBRARY) +SET(MKL_LAPACK_LIBRARIES) +SET(MKL_SCALAPACK_LIBRARIES) +SET(MKL_SOLVER_LIBRARIES) +SET(MKL_CDFT_LIBRARIES) + +# Includes +INCLUDE(CheckTypeSize) +INCLUDE(CheckFunctionExists) + +# Set default value of INTEL_COMPILER_DIR and INTEL_MKL_DIR +IF (WIN32) + IF(DEFINED ENV{MKLProductDir}) + SET(DEFAULT_INTEL_COMPILER_DIR $ENV{MKLProductDir}) + ELSE() + SET(DEFAULT_INTEL_COMPILER_DIR + "C:/Program Files (x86)/IntelSWTools/compilers_and_libraries/windows") + ENDIF() + SET(DEFAULT_INTEL_MKL_DIR "${INTEL_COMPILER_DIR}/mkl") +ELSE (WIN32) + SET(DEFAULT_INTEL_COMPILER_DIR "/opt/intel") + SET(DEFAULT_INTEL_MKL_DIR "/opt/intel/mkl") +ENDIF (WIN32) + +# Intel Compiler Suite +SET(INTEL_COMPILER_DIR "${DEFAULT_INTEL_COMPILER_DIR}" CACHE STRING + "Root directory of the Intel Compiler Suite (contains ipp, mkl, etc.)") +SET(INTEL_MKL_DIR "${DEFAULT_INTEL_MKL_DIR}" CACHE STRING + "Root directory of the Intel MKL (standalone)") +SET(INTEL_OMP_DIR "${DEFAULT_INTEL_MKL_DIR}" CACHE STRING + "Root directory of the Intel OpenMP (standalone)") +SET(MKL_THREADING "OMP" CACHE STRING "MKL flavor: SEQ, TBB or OMP (default)") + +IF (NOT "${MKL_THREADING}" STREQUAL "SEQ" AND + NOT "${MKL_THREADING}" STREQUAL "TBB" AND + NOT "${MKL_THREADING}" STREQUAL "OMP") + MESSAGE(FATAL_ERROR "Invalid MKL_THREADING (${MKL_THREADING}), should be one of: SEQ, TBB, OMP") +ENDIF() + +IF ("${MKL_THREADING}" STREQUAL "TBB" AND NOT USE_TBB) + MESSAGE(FATAL_ERROR "MKL_THREADING is TBB but USE_TBB is turned off") +ENDIF() + +MESSAGE(STATUS "MKL_THREADING = ${MKL_THREADING}") + +# Checks +CHECK_TYPE_SIZE("void*" SIZE_OF_VOIDP) +IF ("${SIZE_OF_VOIDP}" EQUAL 8) + SET(mklvers "intel64") + SET(iccvers "intel64") + SET(mkl64s "_lp64") +ELSE ("${SIZE_OF_VOIDP}" EQUAL 8) + SET(mklvers "32") + SET(iccvers "ia32") + SET(mkl64s) +ENDIF ("${SIZE_OF_VOIDP}" EQUAL 8) +IF(CMAKE_COMPILER_IS_GNUCC) + IF ("${MKL_THREADING}" STREQUAL "TBB") + SET(mklthreads "mkl_tbb_thread") + SET(mklrtls "tbb") + ELSE() + SET(mklthreads "mkl_gnu_thread" "mkl_intel_thread") + SET(mklrtls "gomp" "iomp5") + ENDIF() + SET(mklifaces "intel" "gf") +ELSE(CMAKE_COMPILER_IS_GNUCC) + IF ("${MKL_THREADING}" STREQUAL "TBB") + SET(mklthreads "mkl_tbb_thread") + SET(mklrtls "tbb") + ELSE() + SET(mklthreads "mkl_intel_thread") + SET(mklrtls "iomp5" "guide") + IF (MSVC) + SET(mklrtls "libiomp5md") + ENDIF (MSVC) + ENDIF() + SET(mklifaces "intel") +ENDIF (CMAKE_COMPILER_IS_GNUCC) + +# Kernel libraries dynamically loaded +SET(mklkerlibs "mc" "mc3" "nc" "p4n" "p4m" "p4m3" "p4p" "def") +SET(mklseq) + +# Paths +SET(saved_CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH}) +SET(saved_CMAKE_INCLUDE_PATH ${CMAKE_INCLUDE_PATH}) +IF(WIN32) + # Change mklvers and iccvers when we are using MSVC instead of ICC + IF(MSVC AND NOT CMAKE_CXX_COMPILER_ID STREQUAL "Intel") + SET(mklvers "${mklvers}_win") + SET(iccvers "${iccvers}_win") + ENDIF() +ENDIF(WIN32) +IF (EXISTS ${INTEL_COMPILER_DIR}) + # TODO: diagnostic if dir does not exist + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_COMPILER_DIR}/lib/${iccvers}") + IF(MSVC) + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_COMPILER_DIR}/compiler/lib/${iccvers}") + ENDIF() + IF (APPLE) + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_COMPILER_DIR}/lib") + ENDIF() + IF (NOT EXISTS ${INTEL_MKL_DIR}) + SET(INTEL_MKL_DIR "${INTEL_COMPILER_DIR}/mkl") + ENDIF() +ENDIF() +IF (EXISTS ${INTEL_MKL_DIR}) + # TODO: diagnostic if dir does not exist + SET(CMAKE_INCLUDE_PATH ${CMAKE_INCLUDE_PATH} + "${INTEL_MKL_DIR}/include") + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_MKL_DIR}/lib/${mklvers}") + IF (MSVC) + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_MKL_DIR}/lib/${iccvers}") + IF ("${SIZE_OF_VOIDP}" EQUAL 8) + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_MKL_DIR}/win-x64") + ENDIF () + ENDIF() + IF (APPLE) + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_MKL_DIR}/lib") + ENDIF() +ENDIF() + +IF (EXISTS ${INTEL_OMP_DIR}) + # TODO: diagnostic if dir does not exist + SET(CMAKE_INCLUDE_PATH ${CMAKE_INCLUDE_PATH} + "${INTEL_OMP_DIR}/include") + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_OMP_DIR}/lib/${mklvers}") + IF (MSVC) + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_OMP_DIR}/lib/${iccvers}") + IF ("${SIZE_OF_VOIDP}" EQUAL 8) + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_OMP_DIR}/win-x64") + ENDIF () + ENDIF() + IF (APPLE) + SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} + "${INTEL_OMP_DIR}/lib") + ENDIF() +ENDIF() + +# Try linking multiple libs +MACRO(CHECK_ALL_LIBRARIES LIBRARIES OPENMP_TYPE OPENMP_LIBRARY _name _list _flags) + # This macro checks for the existence of the combination of libraries given by _list. + # If the combination is found, this macro checks whether we can link against that library + # combination using the name of a routine given by _name using the linker + # flags given by _flags. If the combination of libraries is found and passes + # the link test, LIBRARIES is set to the list of complete library paths that + # have been found. Otherwise, LIBRARIES is set to FALSE. + # N.B. _prefix is the prefix applied to the names of all cached variables that + # are generated internally and marked advanced by this macro. + SET(_prefix "${LIBRARIES}") + # start checking + SET(_libraries_work TRUE) + SET(${LIBRARIES}) + SET(${OPENMP_TYPE}) + SET(${OPENMP_LIBRARY}) + SET(_combined_name) + SET(_openmp_type) + SET(_openmp_library) + SET(_paths) + IF (NOT MKL_FIND_QUIETLY) + set(_str_list) + foreach(_elem ${_list}) + if(_str_list) + set(_str_list "${_str_list} - ${_elem}") + else() + set(_str_list "${_elem}") + endif() + endforeach(_elem) + message(STATUS "Checking for [${_str_list}]") + ENDIF () + SET(_found_tbb FALSE) + FOREACH(_library ${_list}) + SET(_combined_name ${_combined_name}_${_library}) + UNSET(${_prefix}_${_library}_LIBRARY) + IF(_libraries_work) + IF(${_library} MATCHES "omp") + IF(_openmp_type) + MESSAGE(FATAL_ERROR "More than one OpenMP libraries appear in the MKL test: ${_list}") + ELSEIF(${_library} MATCHES "gomp") + SET(_openmp_type "GNU") + # Use FindOpenMP to find gomp + FIND_PACKAGE(OpenMP QUIET) + IF(OPENMP_FOUND) + # Test that none of the found library names contains "iomp" (Intel + # OpenMP). This doesn't necessarily mean that we have gomp... but it + # is probably good enough since on gcc we should already have + # OpenMP_CXX_FLAGS="-fopenmp" and OpenMP_CXX_LIB_NAMES="". + SET(_found_gomp true) + FOREACH(_lib_name ${OpenMP_CXX_LIB_NAMES}) + IF (_found_gomp AND "${_lib_name}" MATCHES "iomp") + SET(_found_gomp false) + ENDIF() + ENDFOREACH() + IF(_found_gomp) + SET(${_prefix}_${_library}_LIBRARY ${OpenMP_CXX_FLAGS}) + SET(_openmp_library "${${_prefix}_${_library}_LIBRARY}") + ENDIF() + ENDIF(OPENMP_FOUND) + ELSEIF(${_library} MATCHES "iomp") + SET(_openmp_type "Intel") + FIND_LIBRARY(${_prefix}_${_library}_LIBRARY NAMES ${_library}) + SET(_openmp_library "${${_prefix}_${_library}_LIBRARY}") + ELSE() + MESSAGE(FATAL_ERROR "Unknown OpenMP flavor: ${_library}") + ENDIF() + ELSEIF(${_library} STREQUAL "tbb") + # Separately handling compiled TBB + SET(_found_tbb TRUE) + ELSE() + SET(lib_names ${_library}) + FIND_LIBRARY(${_prefix}_${_library}_LIBRARY NAMES ${lib_names}) + ENDIF() + MARK_AS_ADVANCED(${_prefix}_${_library}_LIBRARY) + IF(NOT (${_library} STREQUAL "tbb")) + SET(${LIBRARIES} ${${LIBRARIES}} ${${_prefix}_${_library}_LIBRARY}) + SET(_libraries_work ${${_prefix}_${_library}_LIBRARY}) + IF (NOT MKL_FIND_QUIETLY) + IF(${_prefix}_${_library}_LIBRARY) + MESSAGE(STATUS " Library ${_library}: ${${_prefix}_${_library}_LIBRARY}") + ELSE(${_prefix}_${_library}_LIBRARY) + MESSAGE(STATUS " Library ${_library}: not found") + ENDIF(${_prefix}_${_library}_LIBRARY) + ENDIF () + ENDIF() + ENDIF(_libraries_work) + ENDFOREACH(_library ${_list}) + # Test this combination of libraries. + IF(_libraries_work) + IF (NOT _found_tbb) + SET(CMAKE_REQUIRED_LIBRARIES ${_flags} ${${LIBRARIES}}) + SET(CMAKE_REQUIRED_LIBRARIES "${CMAKE_REQUIRED_LIBRARIES};${CMAKE_REQUIRED_LIBRARIES}") + CHECK_FUNCTION_EXISTS(${_name} ${_prefix}${_combined_name}_WORKS) + SET(CMAKE_REQUIRED_LIBRARIES) + MARK_AS_ADVANCED(${_prefix}${_combined_name}_WORKS) + SET(_libraries_work ${${_prefix}${_combined_name}_WORKS}) + ENDIF() + ENDIF(_libraries_work) + # Fin + IF(_libraries_work) + SET(${OPENMP_TYPE} ${_openmp_type}) + MARK_AS_ADVANCED(${OPENMP_TYPE}) + SET(${OPENMP_LIBRARY} ${_openmp_library}) + MARK_AS_ADVANCED(${OPENMP_LIBRARY}) + ELSE (_libraries_work) + SET(${LIBRARIES}) + MARK_AS_ADVANCED(${LIBRARIES}) + ENDIF(_libraries_work) +ENDMACRO(CHECK_ALL_LIBRARIES) + +IF(WIN32) + SET(mkl_m "") + SET(mkl_pthread "") +ELSE(WIN32) + SET(mkl_m "m") + SET(mkl_pthread "pthread") +ENDIF(WIN32) + +IF(UNIX AND NOT APPLE) + SET(mkl_dl "${CMAKE_DL_LIBS}") +ELSE(UNIX AND NOT APPLE) + SET(mkl_dl "") +ENDIF(UNIX AND NOT APPLE) + +# Check for version 10/11 +IF (NOT MKL_LIBRARIES) + SET(MKL_VERSION 1011) +ENDIF (NOT MKL_LIBRARIES) + +# First: search for parallelized ones with intel thread lib +IF (NOT "${MKL_THREADING}" STREQUAL "SEQ") + FOREACH(mklrtl ${mklrtls} "") + FOREACH(mkliface ${mklifaces}) + FOREACH(mkl64 ${mkl64s} "") + FOREACH(mklthread ${mklthreads}) + IF (NOT MKL_LIBRARIES) + CHECK_ALL_LIBRARIES(MKL_LIBRARIES MKL_OPENMP_TYPE MKL_OPENMP_LIBRARY cblas_sgemm + "mkl_${mkliface}${mkl64};${mklthread};mkl_core;${mklrtl};${mkl_pthread};${mkl_m};${mkl_dl}" "") + ENDIF (NOT MKL_LIBRARIES) + ENDFOREACH(mklthread) + ENDFOREACH(mkl64) + ENDFOREACH(mkliface) + ENDFOREACH(mklrtl) +ENDIF (NOT "${MKL_THREADING}" STREQUAL "SEQ") + +# Second: search for sequential ones +FOREACH(mkliface ${mklifaces}) + FOREACH(mkl64 ${mkl64s} "") + IF (NOT MKL_LIBRARIES) + CHECK_ALL_LIBRARIES(MKL_LIBRARIES MKL_OPENMP_TYPE MKL_OPENMP_LIBRARY cblas_sgemm + "mkl_${mkliface}${mkl64};mkl_sequential;mkl_core;${mkl_m};${mkl_dl}" "") + IF (MKL_LIBRARIES) + SET(mklseq "_sequential") + ENDIF (MKL_LIBRARIES) + ENDIF (NOT MKL_LIBRARIES) + ENDFOREACH(mkl64) +ENDFOREACH(mkliface) + +# First: search for parallelized ones with native pthread lib +FOREACH(mklrtl ${mklrtls} "") + FOREACH(mkliface ${mklifaces}) + FOREACH(mkl64 ${mkl64s} "") + IF (NOT MKL_LIBRARIES) + CHECK_ALL_LIBRARIES(MKL_LIBRARIES MKL_OPENMP_TYPE MKL_OPENMP_LIBRARY cblas_sgemm + "mkl_${mkliface}${mkl64};${mklthread};mkl_core;${mklrtl};pthread;${mkl_m};${mkl_dl}" "") + ENDIF (NOT MKL_LIBRARIES) + ENDFOREACH(mkl64) + ENDFOREACH(mkliface) +ENDFOREACH(mklrtl) + +# Check for older versions +IF (NOT MKL_LIBRARIES) + SET(MKL_VERSION 900) + CHECK_ALL_LIBRARIES(MKL_LIBRARIES MKL_OPENMP_TYPE MKL_OPENMP_LIBRARY cblas_sgemm + "mkl;guide;pthread;m" "") +ENDIF (NOT MKL_LIBRARIES) + +# Include files +IF (MKL_LIBRARIES) + FIND_PATH(MKL_INCLUDE_DIR "mkl_cblas.h") + MARK_AS_ADVANCED(MKL_INCLUDE_DIR) +ENDIF (MKL_LIBRARIES) + +# Other libraries +IF (MKL_LIBRARIES) + FOREACH(mkl64 ${mkl64s} "_core" "") + FOREACH(mkls ${mklseq} "") + IF (NOT MKL_LAPACK_LIBRARIES) + FIND_LIBRARY(MKL_LAPACK_LIBRARIES NAMES "mkl_lapack${mkl64}${mkls}") + MARK_AS_ADVANCED(MKL_LAPACK_LIBRARIES) + ENDIF (NOT MKL_LAPACK_LIBRARIES) + IF (NOT MKL_SCALAPACK_LIBRARIES) + FIND_LIBRARY(MKL_SCALAPACK_LIBRARIES NAMES "mkl_scalapack${mkl64}${mkls}") + MARK_AS_ADVANCED(MKL_SCALAPACK_LIBRARIES) + ENDIF (NOT MKL_SCALAPACK_LIBRARIES) + IF (NOT MKL_SOLVER_LIBRARIES) + FIND_LIBRARY(MKL_SOLVER_LIBRARIES NAMES "mkl_solver${mkl64}${mkls}") + MARK_AS_ADVANCED(MKL_SOLVER_LIBRARIES) + ENDIF (NOT MKL_SOLVER_LIBRARIES) + IF (NOT MKL_CDFT_LIBRARIES) + FIND_LIBRARY(MKL_CDFT_LIBRARIES NAMES "mkl_cdft${mkl64}${mkls}") + MARK_AS_ADVANCED(MKL_CDFT_LIBRARIES) + ENDIF (NOT MKL_CDFT_LIBRARIES) + ENDFOREACH(mkls) + ENDFOREACH(mkl64) +ENDIF (MKL_LIBRARIES) + +# Final +SET(CMAKE_LIBRARY_PATH ${saved_CMAKE_LIBRARY_PATH}) +SET(CMAKE_INCLUDE_PATH ${saved_CMAKE_INCLUDE_PATH}) +IF (MKL_LIBRARIES AND MKL_INCLUDE_DIR) + SET(MKL_FOUND TRUE) +ELSE (MKL_LIBRARIES AND MKL_INCLUDE_DIR) + if (MKL_LIBRARIES AND NOT MKL_INCLUDE_DIR) + MESSAGE(WARNING "MKL libraries files are found, but MKL header files are \ + not. You can get them by `conda install mkl-include` if using conda (if \ + it is missing, run `conda upgrade -n root conda` first), and \ + `pip install mkl-devel` if using pip. If build fails with header files \ + available in the system, please make sure that CMake will search the \ + directory containing them, e.g., by setting CMAKE_INCLUDE_PATH.") + endif() + SET(MKL_FOUND FALSE) + SET(MKL_VERSION) # clear MKL_VERSION +ENDIF (MKL_LIBRARIES AND MKL_INCLUDE_DIR) + +# Standard termination +IF(NOT MKL_FOUND AND MKL_FIND_REQUIRED) + MESSAGE(FATAL_ERROR "MKL library not found. Please specify library location \ + by appending the root directory of the MKL installation to the environment variable CMAKE_PREFIX_PATH.") +ENDIF(NOT MKL_FOUND AND MKL_FIND_REQUIRED) +IF(NOT MKL_FIND_QUIETLY) + IF(MKL_FOUND) + MESSAGE(STATUS "MKL library found") + ELSE(MKL_FOUND) + MESSAGE(STATUS "MKL library not found") + ENDIF(MKL_FOUND) +ENDIF(NOT MKL_FIND_QUIETLY) + +# Do nothing if MKL_FOUND was set before! +ENDIF (NOT MKL_FOUND) diff --git a/cmake/modules/FindSphinx.cmake b/cmake/modules/FindSphinx.cmake new file mode 100644 index 0000000..e8e7518 --- /dev/null +++ b/cmake/modules/FindSphinx.cmake @@ -0,0 +1,11 @@ +# Sphinx configuration +# Credit: https://devblogs.microsoft.com/cppblog/clear-functional-c-documentation-with-sphinx-breathe-doxygen-cmake/ +find_program(SPHINX_EXECUTABLE + NAMES sphinx-build + DOC "sphinx-build command") + +include(FindPackageHandleStandardArgs) + +find_package_handle_standard_args(Sphinx + "Failed to find sphinx-build executable" + SPHINX_EXECUTABLE) diff --git a/cmake/spectra.CMakeLists.txt.in b/cmake/spectra.CMakeLists.txt.in new file mode 100644 index 0000000..c4c65f3 --- /dev/null +++ b/cmake/spectra.CMakeLists.txt.in @@ -0,0 +1,15 @@ +cmake_minimum_required(VERSION 3.10) + +project(spectra-download NONE) + +include(ExternalProject) +ExternalProject_Add(spectral + GIT_REPOSITORY https://github.com/jingnanshi/spectra + GIT_TAG 5c4fb1de050847988faaaaa50f60e7d3d5f16143 + SOURCE_DIR "${CMAKE_CURRENT_BINARY_DIR}/spectra-src" + BINARY_DIR "" + CONFIGURE_COMMAND "" + BUILD_COMMAND "" + INSTALL_COMMAND "" + TEST_COMMAND "" + ) \ No newline at end of file diff --git a/doc/CMakeLists.txt b/doc/CMakeLists.txt index 496feec..9176804 100644 --- a/doc/CMakeLists.txt +++ b/doc/CMakeLists.txt @@ -2,14 +2,37 @@ project(teaserpp_doc) set_directory_properties(PROPERTIES EXCLUDE_FROM_ALL TRUE) -set(teaserpp_DOXY_PROJECT_NAME "teaserpp") -set(teaserpp_DOXY_INPUT "\"${teaserpp_SOURCE_DIR}/teaser\" \"${teaserpp_SOURCE_DIR}/doc\"") +file(COPY + ${CMAKE_CURRENT_SOURCE_DIR}/Doxyfile + ${CMAKE_CURRENT_SOURCE_DIR}/conf.py + DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) -configure_file( - ${CMAKE_CURRENT_SOURCE_DIR}/Doxyfile.in - ${CMAKE_CURRENT_BINARY_DIR}/Doxyfile -) +file(COPY . + DESTINATION . + FILES_MATCHING + PATTERN *.rst + ) +# We use TEASERPP_SOURCE_DIR environmental variable as a way to +# control location of teaser source files without using CMake's configure_file, +# so that we can use both in source build and out-of-source build for documentation. add_custom_target(doc ALL - COMMAND doxygen + COMMAND TEASERPP_SOURCE_DIR=${teaserpp_SOURCE_DIR}/teaser doxygen WORKING_DIRECTORY ${teaserpp_BINARY_DIR}/doc) + +# Sphinx +find_package(Sphinx) + +if (Sphinx_FOUND) + message(STATUS "Found Sphinx. Will build Sphinx HTML files.") + set(SPHINX_SOURCE ${teaserpp_BINARY_DIR}/doc) + set(SPHINX_BUILD ${CMAKE_CURRENT_BINARY_DIR}/sphinx_build) + message(STATUS "Sphinx build location: ${CMAKE_CURRENT_BINARY_DIR}/sphinx_build") + + add_custom_target(sphinx ALL + COMMAND + ${SPHINX_EXECUTABLE} -b html + ${SPHINX_SOURCE} ${SPHINX_BUILD} + WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR} + COMMENT "Generating documentation with Sphinx") +endif () \ No newline at end of file diff --git a/doc/Doxyfile.in b/doc/Doxyfile similarity index 99% rename from doc/Doxyfile.in rename to doc/Doxyfile index d25e9e6..34a019b 100644 --- a/doc/Doxyfile.in +++ b/doc/Doxyfile @@ -32,7 +32,7 @@ DOXYFILE_ENCODING = UTF-8 # title of most generated pages and in a few other places. # The default value is: My Project. -PROJECT_NAME = "${teaserpp_DOXY_PROJECT_NAME}" +PROJECT_NAME = "TEASER++" # The PROJECT_NUMBER tag can be used to enter a project or revision number. This # could be handy for archiving the generated documentation or if some version @@ -58,7 +58,7 @@ PROJECT_LOGO = # entered, it will be relative to the location where doxygen was started. If # left blank the current directory will be used. -OUTPUT_DIRECTORY = "${teaserpp_BINARY_DIR}/doc" +OUTPUT_DIRECTORY = "./doxygen/" # If the CREATE_SUBDIRS tag is set to YES then doxygen will create 4096 sub- # directories (in 2 levels) under the output directory of each output format and @@ -790,7 +790,7 @@ WARN_LOGFILE = # spaces. See also FILE_PATTERNS and EXTENSION_MAPPING # Note: If this tag is empty the current directory is searched. -INPUT = ${teaserpp_DOXY_INPUT} +INPUT = $(TEASERPP_SOURCE_DIR) # This tag can be used to specify the character encoding of the source files # that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses @@ -1946,7 +1946,7 @@ MAN_LINKS = NO # captures the structure of the code including all documentation. # The default value is: NO. -GENERATE_XML = NO +GENERATE_XML = YES # The XML_OUTPUT tag is used to specify where the XML pages will be put. If a # relative path is entered the value of OUTPUT_DIRECTORY will be put in front of diff --git a/doc/api-cpp.rst b/doc/api-cpp.rst new file mode 100644 index 0000000..9bbaa84 --- /dev/null +++ b/doc/api-cpp.rst @@ -0,0 +1,88 @@ +.. _api-cpp: + +C++ API +======== + +Solver API +---------- + +``teaser/registration.h`` defines the core registration solver API which provides users with the ability to solve 3D registration problems given correspondences. + +.. _registration-api: + +Registration Solution +^^^^^^^^^^^^^^^^^^^^^ + +.. doxygenstruct:: teaser::RegistrationSolution + :members: + :private-members: + :undoc-members: + +7-DoF Solver +^^^^^^^^^^^^ + +.. doxygenclass:: teaser::RobustRegistrationSolver + :members: + +Translation Solver +^^^^^^^^^^^^^^^^^^ + +.. doxygenclass:: teaser::TLSTranslationSolver + :members: + +.. doxygenclass:: teaser::AbstractTranslationSolver + :members: + +Rotation Solver +^^^^^^^^^^^^^^^ + +.. doxygenclass:: teaser::GNCTLSRotationSolver + :members: + +.. doxygenclass:: teaser::FastGlobalRegistrationSolver + :members: + +.. doxygenclass:: teaser::AbstractRotationSolver + :members: + +Scale Solver +^^^^^^^^^^^^ + +.. doxygenclass:: teaser::TLSScaleSolver + :members: + +.. doxygenclass:: teaser::ScaleInliersSelector + :members: + +.. doxygenclass:: teaser::AbstractScaleSolver + :members: + +TLS Estimator +^^^^^^^^^^^^^ + +.. doxygenclass:: teaser::ScalarTLSEstimator + :members: + +.. _certifier-api: + +Certifier API +------------- + +``teaser/certification.h`` defines the core certification API which provides users with the ability to certify a rotation solution provided by a GNC-TLS rotation solver. + +Certification Result +^^^^^^^^^^^^^^^^^^^^ + +.. doxygenstruct:: teaser::CertificationResult + :members: + :private-members: + :undoc-members: + +Rotation Certifier +^^^^^^^^^^^^^^^^^^ + +.. doxygenclass:: teaser::DRSCertifier + :members: + +.. doxygenclass:: teaser::AbstractRotationCertifier + :members: diff --git a/doc/api-matlab.rst b/doc/api-matlab.rst new file mode 100644 index 0000000..f975bfe --- /dev/null +++ b/doc/api-matlab.rst @@ -0,0 +1,94 @@ +.. _api-matlab: + +MATLAB API +========== +The TEASER++ MATLAB binding provides a wrapper function for users to interface with the TEASER++ library: +- ``teaser_solve``: a MATLAB function that wraps around a MEX function that creates a solver and calls the ``solve()`` function. + +Here we will show you how to use TEASER++'s MATLAB binding to solver 3D registration problems. + +teaser_solve +------------ + +Input arguments: + +- ``src``: a 3-by-N matrix of 3D points representing points to be transformed +- ``dst``: a 3-by-N matrix of 3D points representing points after transformation (each column needs to correspond to the same column in ``src``) + +Input parameters (name-value pairs): + +- ``Cbar2``: square of maximum ratio between noise and noise bound (set to 1 by default). +- ``NoiseBound``: maximum bound on noise (depends on the data, default to 0.03). +- ``EstimateScaling``: true if scale needs to be estimated, false otherwise (default to true). +- ``RotationEstimationAlgorithm``: 0 for GNC-TLS, 1 for FGR (default to 0). +- ``RotationGNCFactor``: factor for increasing/decreasing the GNC function control parameter (default to 1.4): + + - for GNC-TLS method: it's multiplied on the GNC control parameter. + - for FGR method: it's divided on the GNC control parameter. + +- ``RotationMaxIterations``: maximum iterations for the GNC-TLS/FGR loop (default to 100). +- ``RotationCostThreshold``: cost threshold for FGR termination (default to 0.005). + +Outputs: + +- ``s``: estimated scale (scalar) +- ``R``: estimated rotation matrix (3-by-3) +- ``t``: estimated 3D translational vector (3-by-1) +- ``time_taken``: time it takes for the TEASER++ library to compute a solution in seconds. + +For more information, please refer to the comments in the source code directly. + +Examples +-------- + +Estimate a registration problem with known scale +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Assume we have `src` and `dst`, two 3-by-N matrices. And we know that `dst = R * src + t + e`, where `e` is bounded within 0.01. The following is a snippet of how you can use TEASER++ to solve it. + +.. code-block:: matlab + + cbar2 = 1; + noise_bound = 0.01; + estimate_scaling = false; % we know there's no scale difference + rot_alg = 0; % use GNC-TLS, set to 1 for FGR + rot_gnc_factor = 1.4; + rot_max_iters = 100; + rot_cost_threshold = 1e-12; + + % The MEX function version + [s, R, t, time_taken] = teaser_solve_mex(src, dst, cbar2, ... + noise_bound, estimate_scaling, rot_alg, rot_gnc_factor, ... + rot_max_iters, rot_cost_threshold); + + % The MATLAB wrapper version + [s, R, t, time_taken] = teaser_solve(src, dst, 'Cbar2', cbar2, 'NoiseBound', noise_bound, ... + 'EstimateScaling', estimate_scaling, 'RotationEstimationAlgorithm', rot_alg, ... + 'RotationGNCFactor', rot_gnc_factor, 'RotationMaxIterations', 100, ... + 'RotationCostThreshold', rot_cost_threshold); + +Estimate a registration problem with unknown scale +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Assume we have `src` and `dst`, two 3-by-N matrices. And we know that `dst = s * R * src + t + e`, where `e` is bounded within 0.01. The following is a snippet of how you can use TEASER++ to solve it. + +.. code-block:: matlab + + cbar2 = 1; + noise_bound = 0.01; + estimate_scaling = true; + rot_alg = 0; % use GNC-TLS, set to 1 to use FGR + rot_gnc_factor = 1.4; + rot_max_iters = 100; + rot_cost_threshold = 1e-12; + + % The MEX function version + [s, R, t, time_taken] = teaser_solve_mex(src, dst, cbar2, ... + noise_bound, estimate_scaling, rot_alg, rot_gnc_factor, ... + rot_max_iters, rot_cost_threshold); + + % The MATLAB wrapper version + [s, R, t, time_taken] = teaser_solve(src, dst, 'Cbar2', cbar2, 'NoiseBound', noise_bound, ... + 'EstimateScaling', estimate_scaling, 'RotationEstimationAlgorithm', rot_alg, ... + 'RotationGNCFactor', rot_gnc_factor, 'RotationMaxIterations', 100, ... + 'RotationCostThreshold', rot_cost_threshold); diff --git a/doc/api-python.rst b/doc/api-python.rst new file mode 100644 index 0000000..3fcf40c --- /dev/null +++ b/doc/api-python.rst @@ -0,0 +1,13 @@ +.. _api-python: + +Python API +========== + +The TEASER++ Python binding ``teaserpp-python`` uses `pybind11 `_ to allow for minimal-effort interoperability between C++ and Python. To use TEASER++ in Python, the following C++ constructs are exposed: + +- ``teaser::RobustRegistrationSolver``: the main solver class for solving registration problems with TEASER++ +- ``teaser::RobustRegistrationSolver::Params``: a struct for holding the initialization parameters for TEASER++ +- ``teaser::RobustRegistrationSolver::ROTATION_ESTIMATION_ALGORITHM``: an enum for specifying what kind rotation estimation algorithm to use +- ``teaser::RegistrationSolution``: a struct holding the solution to a registration problem + +Please refer to the C++ source code for more detailed documentation. Since Python bindings are directly bound to C++ functions, all the functionalities will be the same. For accessing the results, a general rule of thumb is to just replace all Eigen matrices with ``numpy`` matrices. diff --git a/doc/conf.py b/doc/conf.py new file mode 100644 index 0000000..fc8465e --- /dev/null +++ b/doc/conf.py @@ -0,0 +1,66 @@ +# Configuration file for the Sphinx documentation builder. +# +# This file only contains a selection of the most common options. For a full +# list see the documentation: +# https://www.sphinx-doc.org/en/master/usage/configuration.html + +# -- Path setup -------------------------------------------------------------- + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +# +# import os +# import sys +# sys.path.insert(0, os.path.abspath('.')) +import sphinx_rtd_theme +import subprocess, os + +read_the_docs_build = os.environ.get('READTHEDOCS', None) == 'True' + +# If building for readthedocs, generate doxygen xml files +if read_the_docs_build: + subprocess.call('TEASERPP_SOURCE_DIR=../teaser doxygen', shell=True) + +# -- Project information ----------------------------------------------------- + +project = 'TEASER++' +copyright = '2020, Heng Yang, Jingnan Shi, Luca Carlone' +author = 'Heng Yang, Jingnan Shi, Luca Carlone' + + +# -- General configuration --------------------------------------------------- + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + 'breathe', + 'sphinx_rtd_theme', + ] +source_suffix = ['.rst'] + +# Add any paths that contain templates here, relative to this directory. +templates_path = ['_templates'] + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This pattern also affects html_static_path and html_extra_path. +exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] + + +# -- Options for HTML output ------------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_theme = 'sphinx_rtd_theme' + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = ['_static'] + +# -- Breathe configuration -------------------------------------------------- +breathe_projects = { "teaserpp": "./doxygen/xml" } +breathe_default_project = "teaserpp" diff --git a/doc/index.rst b/doc/index.rst new file mode 100644 index 0000000..220e499 --- /dev/null +++ b/doc/index.rst @@ -0,0 +1,33 @@ +Welcome to TEASER++ +===================== + +**TEASER++** is a fast and certifiably-robust point cloud registration library written in C++, with Python and MATLAB bindings. + +.. toctree:: + + installation + quickstart + known_issues + +API +==== + +If you are looking for information on a specific class or method, please refer to the following pages: + +.. toctree:: + + api-cpp + api-python + api-matlab + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` + +Acknowledgements +================ + +This work was partially funded by ARL DCIST CRA W911NF-17-2-0181, ONR RAIDER N00014-18-1-2828, Lincoln Laboratory “Resilient Perception in Degraded Environments”, and the Google Daydream Research Program. diff --git a/doc/installation.rst b/doc/installation.rst new file mode 100644 index 0000000..8f6f6f0 --- /dev/null +++ b/doc/installation.rst @@ -0,0 +1,180 @@ +.. _installation: + +Installation +============ + +Supported Platforms +------------------- + +TEASER++ has been tested on Ubuntu 18.04 with g++-7/9 and clang++-7/8/9. + +For Python bindings, we recommend using Python 3. + +Installing Dependencies +----------------------- + +Building TEASER++ requires the following libraries installed: + +1. A compiler that supports OpenMP. See `here `_ for a list. +2. CMake >= 3.10 +3. Eigen3 >= 3.3 +4. PCL >= 1.9 (optional) +5. Boost >= 1.58 (optional) + +Run the following script to install all required dependencies: + +.. code-block:: sh + + sudo apt install cmake libeigen3-dev libboost-all-dev + +Run the following script to install PCL from source: + +.. code-block:: sh + + # Compile and install PCL 1.91 from source + PCL_PACKAGE_DIR="$HOME/pcl" + mkdir "$PCL_PACKAGE_DIR" + cd "$PCL_PACKAGE_DIR" + wget "https://github.com/PointCloudLibrary/pcl/archive/pcl-1.9.1.zip" + unzip pcl-*.zip + rm pcl-*.zip + cd pcl-* && mkdir build && cd build + cmake .. + make -j $(python3 -c 'import multiprocessing as mp; print(int(mp.cpu_count() * 1.5))') + sudo make install + +Notice that PCL is not required for the TEASER++ registration library. Installing it merely allows you to build example tests that uses PCL's FPFH features for registration. + +If you want to build Python bindings, you also need: + +1. Python 2 or 3 (make sure to include the desired interpreter in your `PATH` variable) + +If you want to build MATLAB bindings, you also need: + +1. MATLAB +2. CMake >= 3.13 + +TEASER++ uses the Parallel Maximum Clique (`paper `_, `code `_) for maximum clique calculation. It will be downloaded automatically during CMake configuration. In addition, CMake will also download Google Test and pybind11 if necessary. + +Compilation and Installation +---------------------------- + +Clone the repo to your local directory. Open a terminal in the repo root directory. Run the following commands: + +.. code-block:: sh + + # Clone the repo + git clone https://github.com/MIT-SPARK/TEASER-plusplus.git + + # Configure and compile + cd TEASER-plusplus && mkdir build + cd build + cmake .. + make + + # Generate doxygen documentation in doc/ + make doc + + # Run tests + ctest + +Installing C++ libraries and headers +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Make sure you have compiled the project, then run: + +.. code-block:: sh + + # Install shared libraries and headers + sudo make install + +Installing Python bindings +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +TEASER++ uses `pybind11 `_ to allow for minimal-effort interoperability between C++ and Python. To compile Python binding, run the following in the ``build`` folder you just created: + +.. code-block:: sh + + cmake -DTEASERPP_PYTHON_VERSION=3.6 .. + make teaserpp_python + +You can replace ``3.6`` with the desired Python version you want to use TEASER++ with. + +Then, in the `build` folder, there should be a folder named ``python``. You can use the following commands to install the binding with ``pip``: + +.. code-block:: sh + + cd python + pip install . + +If you are using virtual environments or Anaconda, make sure to activate your environment before compiling and during ``pip install``. Make sure the targeted Python interpreter is the one in your desired environment, or otherwise there might be segmentation faults. + +Installing MATLAB Bindings +^^^^^^^^^^^^^^^^^^^^^^^^^^ + +If you have MATLAB installed, you can optionally compile MATLAB bindings: + +.. code-block:: sh + + cmake -DBUILD_MATLAB_BINDINGS=ON .. + make + +To use the compiled MATLAB bindings, just add the path to the generated mex file to your MATLAB script. Assuming your repo is located at ``/repos/TEASER-plusplus``, you can add the following to your MATLAB script: + +.. code-block:: matlab + + addpath('/repos/TEASER-plusplus/build/matlab/') + +Available CMake Options +----------------------- +Here are all available CMake options you can turn on/off during configuration: + ++--------------------------+----------------------------------------+---------------+ +| Option Name | Description | Default Value | ++==========================+========================================+===============+ +|`BUILD_TESTS` | Build tests | ON | ++--------------------------+----------------------------------------+---------------+ +|`BUILD_TEASER_FPFH` | Build TEASER++ wrappers | | +| | for PCL FPFH estimation | OFF | ++--------------------------+----------------------------------------+---------------+ +|`BUILD_MATLAB_BINDINGS` | Build MATLAB bindings | OFF | ++--------------------------+----------------------------------------+---------------+ +|`BUILD_PYTHON_BINDINGS` | Build Python bindings | ON | ++--------------------------+----------------------------------------+---------------+ +|`BUILD_DOC` | Build documentation | ON | ++--------------------------+----------------------------------------+---------------+ +|`BUILD_WITH_MARCH_NATIVE` | Build with flag `march=native` | OFF | ++--------------------------+----------------------------------------+---------------+ +|`ENABLE_DIAGNOSTIC_PRINT` | Enable printing of diagnostic messages | OFF | ++--------------------------+----------------------------------------+---------------+ + +For example, if you want to build with the `march=native` flag (potentially faster at a loss of binary portability), run the following script for compilation: + +.. code-block:: sh + + cmake -DBUILD_WITH_MARCH_NATIVE=ON .. + make + +Notice that by default the library is built in release mode. To build with debug symbols enabled, use the following commands: + +.. code-block:: sh + + cmake -DCMAKE_BUILD_TYPE=Debug .. + make + +Run Tests +--------- + +By default, the library is built in release mode. If you instead choose to build it in debug mode, some tests are likely to time out. + +To run tests and benchmarks (for speed & accuracy tests), you can execute the following command after compilation: + +.. code-block:: sh + + # Run all tests + ctest + + # Run benchmarks + ctest --verbose -R RegistrationBenchmark.* + +The ``--verbose`` option allows you to see the output, as well as the summary tables generated by each benchmark. diff --git a/doc/known_issues.rst b/doc/known_issues.rst new file mode 100644 index 0000000..097654b --- /dev/null +++ b/doc/known_issues.rst @@ -0,0 +1,18 @@ +.. _known_issues: + +Known Issues +============ +- If you are encountering segmentation faults from PMC, try add the environmental variable ``OMP_NUM_THREADS=${MAX_THREADS}`` (replace ``${MAX_THREADS}`` with the maximum number of threads available on your machine) in your current shell. You can also just prepend ``OMP_NUM_THREADS=${MAX_THREADS}`` when running your executable. +- When using the MATLAB wrapper with MATLAB on terminal (``-nojvm`` option enabled), you might encounter errors similar to this: + + .. code-block:: sh + + /usr/local/MATLAB/R2019a/bin/glnxa64/MATLAB: symbol lookup error: /opt/intel/compilers_and_libraries_2019.4.243/linux/mkl/lib/intel64_lin/libmkl_vml_avx2.so: undefined symbol: mkl_serv_getenv. + + One way to get around this is to run the following command in the environment where you start MATLAB: + + .. code-block:: sh + + export LD_PRELOAD=/opt/intel/mkl/lib/intel64/libmkl_intel_lp64.so:/opt/intel/mkl/lib/intel64/libmkl_gnu_thread.so:/opt/intel/mkl/lib/intel64/libmkl_core.so + + You may need to change the paths according to your MKL installation. diff --git a/doc/overview.dox b/doc/overview.dox deleted file mode 100644 index 269e932..0000000 --- a/doc/overview.dox +++ /dev/null @@ -1,28 +0,0 @@ -namespace teaser { - -/** \mainpage notitle - -This is the API documentation for TEASER. - -\section dependency_section Dependencies -1. PCL >= 1.8 (soon to be optional) -2. Eigen3 >= 3.3 -3. Boost >= 1.58 -4. FLANN >= 1.7 - -Please follow their respective installation instructions. - -\section build_section Build -Ensure that your CMake version is at least 3.10. Clone the repo to your local directory. Open a terminal in the repo root directory. Run the following commands: -\code -mkdir build -cd build -cmake .. -make -\endcode - -You can then run the tests by running `ctest` in the `build` directory. Make sure to build it in release to avoid tests timing out. - -**/ - -} diff --git a/doc/quickstart.rst b/doc/quickstart.rst new file mode 100644 index 0000000..0bce750 --- /dev/null +++ b/doc/quickstart.rst @@ -0,0 +1,172 @@ +.. _quickstart: + +Quick Start +=========== + +Usage in C++ Projects +--------------------- + +TEASER++ supports integration with other CMake projects. When installing TEASER++, CMake will export the following targets that can be included in other CMake projects using ``find_package()``: + +- ``teaserpp::teaser_registration``: the core registration library +- ``teaserpp::teaser_io``: library for importing `.ply` files +- ``teaserpp::teaser_features``: convenience wrappers around the PCL FPFH library, and simple feature matching functions + +A minimally-working `CMakeList.txt` looks something like this:: + + cmake_minimum_required(VERSION 3.10) + project(teaserpp_example) + + set (CMAKE_CXX_STANDARD 14) + + find_package(Eigen3 REQUIRED) + find_package(teaserpp REQUIRED) + + # Change this line to include your own executable file + add_executable(cpp_example cpp_example.cpp) + + # Link to teaserpp & Eigen3 + target_link_libraries(cpp_example Eigen3::Eigen teaserpp::teaser_registration teaserpp::teaser_io) + +A minimal TEASER++ C++ program looks something like this: + +.. code-block:: cpp + + #include + + teaser::RobustRegistrationSolver::Params params; + teaser::RobustRegistrationSolver solver(params); + solver.solve(src, dst); // assuming src & dst are 3-by-N Eigen matrices + auto solution = solver.getSolution(); + +So, what did that code do? + +1. First, we included the registration header. +2. Next, we default initialized a parameter struct for controlling the behavior of our solver. +3. Next, we initialized our solver with the parameter struct. +4. We then solve the registration problem by calling the ``solve()`` function. +5. Finally, we obtain the solution. + +In the `examples `_ folder of the project repo, you can find two C++ examples that can be compiled with CMake: + +- ``teaser_cpp_ply``: showing how to import `.ply` files and perform registration with TEASER++, +- ``teaser_cpp_fpfh``: showing how to use TEASER++ with FPFH features. + +For complete C++ API documentation, please refer to :ref:`api-cpp`. + +Usage in Python Projects +------------------------ + +A minimal TEASER++ Python program looks something like this: + +.. code-block:: python + + import numpy as np + import teaserpp_python + + # Generate random data points + src = np.random.rand(3, 20) + + # Apply arbitrary scale, translation and rotation + scale = 1.5 + translation = np.array([[1], [0], [-1]]) + rotation = np.array([[0.98370992, 0.17903344, -0.01618098], + [-0.04165862, 0.13947877, -0.98934839], + [-0.17486954, 0.9739059, 0.14466493]]) + dst = scale * np.matmul(rotation, src) + translation + + # Add two outliers + dst[:, 1] += 10 + dst[:, 9] += 15 + + # Populate the parameters + solver_params = teaserpp_python .RobustRegistrationSolver.Params() + solver_params.cbar2 = 1 + solver_params.noise_bound = 0.01 + solver_params.estimate_scaling = True + solver_params.rotation_estimation_algorithm = ( + teaserpp_python.RobustRegistrationSolver .ROTATION_ESTIMATION_ALGORITHM.GNC_TLS + ) + solver_params.rotation_gnc_factor = 1.4 + solver_params.rotation_max_iterations = 100 + solver_params.rotation_cost_threshold = 1e-12 + print("TEASER++ Parameters are:", solver_params) + teaserpp_solver = teaserpp_python .RobustRegistrationSolver(solver_params) + + solver = teaserpp_python.RobustRegistrationSolver(solver_params) + solver.solve(src, dst) + + solution = solver.getSolution() + + # Print the solution + print("Solution is:", solution) + +So, what did that code do? + +1. First, we imported ``numpy`` and our Python binding, named ``teaserpp_python``. +2. We generated some random correspondences. +3. Next, we initialized a parameter object for controlling the behavior of our solver. We initialized our solver with the parameter object. +4. We then solve the registration problem by calling the ``solve()`` function. +5. Finally, we obtain the solution. + +Note that this is extremely similar to the C++ version by design. + +In the `examples `_ folder of the project repo, you can find two more Python examples that are runnable: + +- ``teaser_python_ply``: showing how to import `.ply` files and perform registration with TEASER++ and Open3D, +- ``teaser_python_3dsmooth``: showing how to use TEASER++ on descriptors generated by `3DSmoothNet `_ on the 3DMatch dataset, with Open3D visualization. + +For more Python API documentation, please refer to :ref:`api-python`. + +Usage in MATLAB Projects +------------------------ + +Contrary to the object-oriented designs in C++ and Python, in MATLAB you only have access to a single solve function, and you can pass in the parameters through named arguments: + +.. code-block:: matlab + + [s, R, t, time_taken] = teaser_solve(src, dst, 'Cbar2', 1, 'NoiseBound', 0.01, ... + 'EstimateScaling', true, 'RotationEstimationAlgorithm', 0, ... + 'RotationGNCFactor', 1.4, 'RotationMaxIterations', 100, ... + 'RotationCostThreshold', 1e-12); + +Assume we have `src` and `dst`, two 3-by-N matrices. And we know that `dst = R * src + t + e`, where `e` is bounded within 0.01. The following is a snippet of how you can use TEASER++'s MATLAB bindings to solve it: + +.. code-block:: matlab + + cbar2 = 1; + noise_bound = 0.01; + estimate_scaling = false; % we know there's no scale difference + rot_alg = 0; % use GNC-TLS, set to 1 for FGR + rot_gnc_factor = 1.4; + rot_max_iters = 100; + rot_cost_threshold = 1e-12; + + [s, R, t, time_taken] = teaser_solve(src, dst, 'Cbar2', cbar2, 'NoiseBound', noise_bound, ... + 'EstimateScaling', estimate_scaling, 'RotationEstimationAlgorithm', rot_alg, ... + 'RotationGNCFactor', rot_gnc_factor, 'RotationMaxIterations', 100, ... + 'RotationCostThreshold', rot_cost_threshold); + +Similarly, if we don't know the scale, here is a snippet for solving the registration problem with MATLAB bindings: + +.. code-block:: matlab + + cbar2 = 1; + noise_bound = 0.01; + estimate_scaling = true; + rot_alg = 0; % use GNC-TLS, set to 1 to use FGR + rot_gnc_factor = 1.4; + rot_max_iters = 100; + rot_cost_threshold = 1e-12; + + [s, R, t, time_taken] = teaser_solve(src, dst, 'Cbar2', cbar2, 'NoiseBound', noise_bound, ... + 'EstimateScaling', estimate_scaling, 'RotationEstimationAlgorithm', rot_alg, ... + 'RotationGNCFactor', rot_gnc_factor, 'RotationMaxIterations', 100, ... + 'RotationCostThreshold', rot_cost_threshold); + +For more MATLAB API documentation, please refer to :ref:`api-matlab`. + +Usage In ROS Projects +--------------------- + +To use TEASER++ in a ROS environment, simple clone the repo to your ``catkin`` workspace. diff --git a/doc/requirements.txt b/doc/requirements.txt new file mode 100644 index 0000000..7ece64a --- /dev/null +++ b/doc/requirements.txt @@ -0,0 +1,2 @@ +breathe +m2r \ No newline at end of file diff --git a/matlab/README.md b/matlab/README.md index ce6fdf9..2997386 100644 --- a/matlab/README.md +++ b/matlab/README.md @@ -1,98 +1,3 @@ # TEASER++ MATLAB Binding -This short document will show you how to use TEASER++'s MATLAB binding to solver 3D registration problems. -## Introduction -The TEASER++ MATLAB binding provides two ways for users to interface with the TEASER++ library: -- `teaser_solve`: a MATLAB function that wraps around the MEX function. - -### teaser_solve_mex -Input arguments: -- `src`: a 3-by-N matrix of 3D points representing points to be transformed -- `dst`: a 3-by-N matrix of 3D points representing points after transformation -- `cbar2`: square of maximum allowed ratio between noise and noise bound (see [1]). -- `noise_bound`: a floating-point number indicating the bound on noise -- `estimate_scaling`: a boolean indicating whether scale needs to be estimated -- `rotation_max_iterations`: maximum iterations for the rotation estimation loop -- `rotation_cost_threshold`: cost threshold for rotation termination -- `rotation_gnc_factor`: gnc factor for rotation estimation - for GNC-TLS method: it's multiplied on the GNC control parameter - for FGR method: it's divided on the GNC control parameter -- `rotation_estimation_method`: a number indicating the rotation estimation method used; - if it's 0: GNC-TLS - if it's 1: FGR - -Output: -- `s_est` estimated scale (scalar) -- `R_est` estimated rotation matrix (3-by-3 matrix) -- `t_est` estimated translation vector (3-by-1 matrix) -- `time_taken` time it takes for the underlying TEASER++ library to compute a solution. - -### teaser_solve -Input arguments: -- `src`: a 3-by-N matrix of 3D points representing points to be transformed -- `dst`: a 3-by-N matrix of 3D points representing points after transformation (each column needs to correspond to the same column in `src`) - -Input parameters (name-value pairs): -- `Cbar2`: square of maximum ratio between noise and noise bound (set to 1 by default). -- `NoiseBound`: maximum bound on noise (depends on the data, default to 0.03) -- `EstimateScaling`: true if scale needs to be estimated, false otherwise (default to true) -- `RotationEstimationAlgorithm`: 0 for GNC-TLS, 1 for FGR (default to 0) -- `RotationGNCFactor`: factor for increasing/decreasing the GNC function control parameter (default to 1.4) - for GNC-TLS method: it's multiplied on the GNC control parameter - for FGR method: it's divided on the GNC control parameter -- `RotationMaxIterations`: maximum iterations for the GNC-TLS/FGR loop (default to 100) -- `RotationCostThreshold`: cost threshold for FGR termination (default to 0.005) - -Outputs: -- `s`: estimated scale (scalar) -- `R`: estimated rotation matrix (3-by-3) -- `t`: estimated 3D translational vector (3-by-1) -- `time_taken`: time it takes for the TEASER++ library to compute a solution in seconds. - -For more information, please refer to the comments in the source code directly. - -## Estimate a registration problem with known scale -Assume we have `src` and `dst`, two 3-by-N matrices. And we know that `dst = R * src + t + e`, where `e` is bounded within 0.01. The following is a snippet of how you can use TEASER++ to solve it. -```matlab -cbar2 = 1; -noise_bound = 0.01; -estimate_scaling = false; % we know there's no scale difference -rot_alg = 0; % use GNC-TLS, set to 1 for FGR -rot_gnc_factor = 1.4; -rot_max_iters = 100; -rot_cost_threshold = 1e-12; - -% The MEX function version -[s, R, t, time_taken] = teaser_solve_mex(src, dst, cbar2, ... - noise_bound, estimate_scaling, rot_alg, rot_gnc_factor, ... - rot_max_iters, rot_cost_threshold); - -% The MATLAB wrapper version -[s, R, t, time_taken] = teaser_solve(src, dst, 'Cbar2', cbar2, 'NoiseBound', noise_bound, ... - 'EstimateScaling', estimate_scaling, 'RotationEstimationAlgorithm', rot_alg, ... - 'RotationGNCFactor', rot_gnc_factor, 'RotationMaxIterations', 100, ... - 'RotationCostThreshold', rot_cost_threshold); -``` - -## Estimate a registration problem with unknown scale -Assume we have `src` and `dst`, two 3-by-N matrices. And we know that `dst = s * R * src + t + e`, where `e` is bounded within 0.01. The following is a snippet of how you can use TEASER++ to solve it. -```matlab -cbar2 = 1; -noise_bound = 0.01; -estimate_scaling = true; -rot_alg = 0; % use GNC-TLS, set to 1 to use FGR -rot_gnc_factor = 1.4; -rot_max_iters = 100; -rot_cost_threshold = 1e-12; - -% The MEX function version -[s, R, t, time_taken] = teaser_solve_mex(src, dst, cbar2, ... - noise_bound, estimate_scaling, rot_alg, rot_gnc_factor, ... - rot_max_iters, rot_cost_threshold); - -% The MATLAB wrapper version -[s, R, t, time_taken] = teaser_solve(src, dst, 'Cbar2', cbar2, 'NoiseBound', noise_bound, ... - 'EstimateScaling', estimate_scaling, 'RotationEstimationAlgorithm', rot_alg, ... - 'RotationGNCFactor', rot_gnc_factor, 'RotationMaxIterations', 100, ... - 'RotationCostThreshold', rot_cost_threshold); -``` +Please refer to [MATLAB API Quick Start](https://teaser.readthedocs.io/en/latest/quickstart.html#usage-in-matlab-projects) and [MATLAB API](https://teaser.readthedocs.io/en/latest/api-matlab.html) for how to use TEASER++'s MATLAB bindings. diff --git a/python/README.md b/python/README.md index 638d042..6d840f8 100644 --- a/python/README.md +++ b/python/README.md @@ -1,77 +1,3 @@ # Python Bindings of TEASER++ -This short document will show you how to use TEASER++'s Python bindings to solver 3D registration problems. - -## Introduction - -The TEASER++ Python binding `teaserpp-python` uses [pybind11](https://github.com/pybind/pybind11) to allow for minimal-effort interoperability between C++ and Python. To use TEASER++ in Python, the following C++ constructs are exposed: -- `teaser::RobustRegistrationSolver`: the main solver class for solving registration problems with TEASER++ -- `teaser::RobustRegistrationSolver::Params`: a struct for holding the initialization parameters for TEASER++ -- `teaser::RobustRegistrationSolver::ROTATION_ESTIMATION_ALGORITHM`: an enum for specifying what kind rotation estimation algorithm to use -- `teaser::RegistrationSolution`: a struct holding the solution to a registration problem - -Please refer to the C++ source code for more detailed documentation. - -## Installation - -You can use `pip` to install `teaserpp-python`, the module that contains all TEASER++ bindings. First, make sure you have compiled `teaserpp-python`. If not, you can use the following commands: -```shell script -mkdir build && cd build -cmake -DCMAKE_BUILD_TYPE=Release -DTEASERPP_PYTHON_VERSION=3.6 .. -make teaserpp_python -j4 -``` -You can replace `3.6` with the desired Python version you want to use TEASER++ with. - -Then, in the `build` folder, there should be a folder named `python`. You can use the following commands to install the binding with `pip`: -```shell script -cd python -pip install . -``` -If you are using virtual environments or Anaconda, make sure to activate your environment before compiling and during `pip install`. Make sure the targeted Python interpreter is the one in your desired environment, or otherwise there might be segmentation faults. - -## Examples - -Please refer to [`examples/`](../examples) for more detailed Python examples. - -For your convenience, here is a short Python script showing TEASER++ registrationn in Python: -```python -import numpy as np -import teaserpp_python - -# Generate random data points -src = np.random.rand(3, 20) - -# Apply arbitrary scale, translation and rotation -scale = 1.5 -translation = np.array([[1], [0], [-1]]) -rotation = np.array([[0.98370992, 0.17903344, -0.01618098], - [-0.04165862, 0.13947877, -0.98934839], - [-0.17486954, 0.9739059, 0.14466493]]) -dst = scale * np.matmul(rotation, src) + translation - -# Add two outliers -dst[:, 1] += 10 -dst[:, 9] += 15 - -# Populate the parameters -solver_params = teaserpp_python.RobustRegistrationSolver.Params() -solver_params.cbar2 = 1 -solver_params.noise_bound = 0.01 -solver_params.estimate_scaling = True -solver_params.rotation_estimation_algorithm = ( - teaserpp_python.RobustRegistrationSolver.ROTATION_ESTIMATION_ALGORITHM.GNC_TLS -) -solver_params.rotation_gnc_factor = 1.4 -solver_params.rotation_max_iterations = 100 -solver_params.rotation_cost_threshold = 1e-12 -print("TEASER++ Parameters are:", solver_params) -teaserpp_solver = teaserpp_python.RobustRegistrationSolver(solver_params) - -solver = teaserpp_python.RobustRegistrationSolver(solver_params) -solver.solve(src, dst) - -solution = solver.getSolution() - -# Print the solution -print("Solution is:", solution) -``` +Please refer to [Python API Quick Start](https://teaser.readthedocs.io/en/latest/quickstart.html#usage-in-python-projects) and [Python API](https://teaser.readthedocs.io/en/latest/api-python.html) for how to use TEASER++'s Python bindings. diff --git a/python/teaserpp_python/teaserpp_python.cc b/python/teaserpp_python/teaserpp_python.cc index 2b643e6..c1885b1 100644 --- a/python/teaserpp_python/teaserpp_python.cc +++ b/python/teaserpp_python/teaserpp_python.cc @@ -14,6 +14,7 @@ #include #include "teaser/registration.h" +#include "teaser/certification.h" namespace py = pybind11; @@ -68,6 +69,8 @@ PYBIND11_MODULE(teaserpp_python, m) { .def("getInlierGraph", &teaser::RobustRegistrationSolver::getInlierGraph) .def("getSrcTIMsMap", &teaser::RobustRegistrationSolver::getSrcTIMsMap) .def("getDstTIMsMap", &teaser::RobustRegistrationSolver::getDstTIMsMap) + .def("getSrcTIMsMapForRotation", &teaser::RobustRegistrationSolver::getSrcTIMsMapForRotation) + .def("getDstTIMsMapForRotation", &teaser::RobustRegistrationSolver::getDstTIMsMapForRotation) .def("getMaxCliqueSrcTIMs", &teaser::RobustRegistrationSolver::getMaxCliqueSrcTIMs) .def("getMaxCliqueDstTIMs", &teaser::RobustRegistrationSolver::getMaxCliqueDstTIMs) .def("getSrcTIMs", &teaser::RobustRegistrationSolver::getSrcTIMs) @@ -79,7 +82,13 @@ PYBIND11_MODULE(teaserpp_python, m) { .value("GNC_TLS", teaser::RobustRegistrationSolver::ROTATION_ESTIMATION_ALGORITHM::GNC_TLS) .value("FGR", teaser::RobustRegistrationSolver::ROTATION_ESTIMATION_ALGORITHM::FGR); - // Python bound for teaser::RobustRegistrationSolver::ROTATION_ESTIMATE_ALGORITHM + // Python bound for teaser::RobustRegistrationSolver::INLIER_GRAPH_FORMULATION + py::enum_(solver, + "INLIER_GRAPH_FORMULATION") + .value("CHAIN", teaser::RobustRegistrationSolver::INLIER_GRAPH_FORMULATION::CHAIN) + .value("COMPLETE", teaser::RobustRegistrationSolver::INLIER_GRAPH_FORMULATION::COMPLETE); + + // Python bound for teaser::RobustRegistrationSolver::INLIER_SELECTION_MODE py::enum_(solver, "INLIER_SELECTION_MODE") .value("PMC_EXACT", teaser::RobustRegistrationSolver::INLIER_SELECTION_MODE::PMC_EXACT) @@ -100,6 +109,8 @@ PYBIND11_MODULE(teaserpp_python, m) { &teaser::RobustRegistrationSolver::Params::rotation_gnc_factor) .def_readwrite("rotation_max_iterations", &teaser::RobustRegistrationSolver::Params::rotation_max_iterations) + .def_readwrite("rotation_tim_graph", + &teaser::RobustRegistrationSolver::Params::rotation_tim_graph) .def_readwrite("inlier_selection_mode", &teaser::RobustRegistrationSolver::Params::inlier_selection_mode) .def_readwrite("kcore_heuristic_threshold", @@ -146,4 +157,52 @@ PYBIND11_MODULE(teaserpp_python, m) { << ">"; return print_string.str(); }); + + // Python bound for CertificationResult + py::class_(m, "CertificationResult") + .def_readwrite("is_optimal", &teaser::CertificationResult::is_optimal) + .def_readwrite("best_suboptimality", &teaser::CertificationResult::best_suboptimality) + .def_readwrite("suboptimality_traj", &teaser::CertificationResult::suboptimality_traj) + .def("__repr__", [](const teaser::CertificationResult& a) { + std::ostringstream print_string; + + print_string << ""; + return print_string.str(); + }); + + // Python bound for DRSCertifier + py::class_ certifier(m, "DRSCertifier"); + certifier.def(py::init()) + .def( + "certify", + py::overload_cast&, + const Eigen::Matrix&, + const Eigen::Matrix&>( + &teaser::DRSCertifier::certify)) + .def( + "certify", + py::overload_cast&, + const Eigen::Matrix&, + const Eigen::Matrix&>( + &teaser::DRSCertifier::certify)); + + // Python bound for DRSCertifier::EIG_SOLVER_TYPE + py::enum_(certifier, "EIG_SOLVER_TYPE") + .value("EIGEN", teaser::DRSCertifier::EIG_SOLVER_TYPE::EIGEN) + .value("SPECTRA", teaser::DRSCertifier::EIG_SOLVER_TYPE::SPECTRA); + + // Python bound for DRSCertifier parameter struct + py::class_(certifier, "Params") + .def(py::init<>()) + .def_readwrite("noise_bound", &teaser::DRSCertifier::Params::noise_bound) + .def_readwrite("cbar2", &teaser::DRSCertifier::Params::cbar2) + .def_readwrite("sub_optimality", &teaser::DRSCertifier::Params::sub_optimality) + .def_readwrite("max_iterations", &teaser::DRSCertifier::Params::max_iterations) + .def_readwrite("gamma_tau", &teaser::DRSCertifier::Params::gamma_tau) + .def_readwrite("eig_decomposition_solver", + &teaser::DRSCertifier::Params::eig_decomposition_solver); } \ No newline at end of file diff --git a/teaser/CMakeLists.txt b/teaser/CMakeLists.txt index a511cbc..f6620dc 100644 --- a/teaser/CMakeLists.txt +++ b/teaser/CMakeLists.txt @@ -19,16 +19,18 @@ add_library(teaserpp::teaser_io ALIAS teaser_io) # teaser_registration library add_library(teaser_registration SHARED + src/certification.cc src/registration.cc src/graph.cc ) target_link_libraries(teaser_registration PUBLIC Eigen3::Eigen - PRIVATE pmc + PRIVATE pmc ${TEASERPP_BLAS_LAPACK_LIBS} ) target_include_directories(teaser_registration PUBLIC $ $ + $ $) find_package(OpenMP) @@ -91,3 +93,4 @@ install(EXPORT teaserpp-export ) install(DIRECTORY include/ DESTINATION ${CMAKE_INSTALL_INCLUDEDIR}) +install(DIRECTORY ${SPECTRA_INCLUDE_DIRS} DESTINATION ${CMAKE_INSTALL_INCLUDEDIR}) diff --git a/teaser/include/teaser/certification.h b/teaser/include/teaser/certification.h new file mode 100644 index 0000000..227d1a2 --- /dev/null +++ b/teaser/include/teaser/certification.h @@ -0,0 +1,240 @@ +/** + * Copyright (c) 2020, Massachusetts Institute of Technology, + * Cambridge, MA 02139 + * All Rights Reserved + * Authors: Jingnan Shi, et al. (see THANKS for the full author list) + * See LICENSE for the license information + */ + +#pragma once + +#include +#include +#include + +namespace teaser { + +using SparseMatrix = Eigen::SparseMatrix; + +struct CertificationResult { + bool is_optimal = false; + double best_suboptimality = -1; + std::vector suboptimality_traj; +}; + +/** + * Abstract virtual class representing certification of registration results + */ +class AbstractRotationCertifier { +public: + virtual ~AbstractRotationCertifier() {} + + /** + * Abstract function for certifying rotation estimation results + * @param rotation_solution [in] a solution to the rotatoin registration problem + * @param src [in] Assume dst = R * src + * @param dst [in] Assume dst = R * src + * @param theta [in] a binary vector indicating inliers vs. outliers + * @return relative sub-optimality gap + */ + virtual CertificationResult certify(const Eigen::Matrix3d& rotation_solution, + const Eigen::Matrix& src, + const Eigen::Matrix& dst, + const Eigen::Matrix& theta) = 0; +}; + +/** + * A rotation registration certifier using Douglas–Rachford Splitting (DRS) + * + * Please refer to: + * [1] H. Yang, J. Shi, and L. Carlone, “TEASER: Fast and Certifiable Point Cloud Registration,” + * arXiv:2001.07715 [cs, math], Jan. 2020. + */ +class DRSCertifier : public AbstractRotationCertifier { +public: + + /** + * Solver for eigendecomposition solver / spectral decomposition. + * + * @brief For most cases, the default solvers in Eigen should be used. + * For extremely large matrices, it may make sense to use Spectra instead. + */ + enum class EIG_SOLVER_TYPE { + EIGEN = 0, ///< Use solvers in the Eigen library + SPECTRA = 1, ///< Use solvers in the Spectra library + }; + + /** + * Parameter struct for DRSCertifier + */ + struct Params { + /** + * Noise bound for the vectors used for certification + */ + double noise_bound = 0.01; + + /** + * Square of the ratio between acceptable noise and noise bound. Usually set to 1. + */ + double cbar2 = 1; + + /** + * Suboptimality gap + * + * This is not a percentage. Multiply by 100 to get a percentage. + */ + double sub_optimality = 1e-3; + + /** + * Maximum iterations allowed + */ + double max_iterations = 2e2; + + /** + * Gamma value (refer to [1] for details) + */ + double gamma_tau = 1.999999; + + /** + * Solver for eigendecomposition / spectral decomposition + */ + EIG_SOLVER_TYPE eig_decomposition_solver = EIG_SOLVER_TYPE::EIGEN; + }; + + DRSCertifier() = delete; + + /** + * Constructor for DRSCertifier that takes in a parameter struct + * @param params [in] struct holding all parameters + */ + DRSCertifier(const Params& params) : params_(params) {}; + + /** + * Constructor for DRSCertifier + * @param noise_bound [in] bound on the noise + * @param cbar2 [in] maximal allowed residual^2 to noise bound^2 ratio, usually set to 1 + */ + DRSCertifier(double noise_bound, double cbar2) { + params_.noise_bound = noise_bound; + params_.cbar2 = cbar2; + }; + + /** + * Main certification function + * + * @param R_solution [in] a feasible rotation solution + * @param src [in] vectors under rotation + * @param dst [in] vectors after rotation + * @param theta [in] binary (1 vs. 0) vector indicating inliers vs. outliers + * @return relative sub-optimality gap + */ + CertificationResult certify(const Eigen::Matrix3d& R_solution, + const Eigen::Matrix& src, + const Eigen::Matrix& dst, + const Eigen::Matrix& theta) override; + + /** + * Main certification function + * + * @param R_solution [in] a feasible rotation solution + * @param src [in] vectors under rotation + * @param dst [in] vectors after rotation + * @param theta [in] binary (1 vs. -1) vector indicating inliers vs. outliers + * @return relative sub-optimality gap + */ + CertificationResult certify(const Eigen::Matrix3d& R_solution, + const Eigen::Matrix& src, + const Eigen::Matrix& dst, + const Eigen::Matrix& theta); + + /** + * Compute sub-optimality gap + * @param M + * @param mu + * @param N + * @return + */ + double computeSubOptimalityGap(const Eigen::MatrixXd& M, double mu, int N); + + /** + * Get the Omega_1 matrix given a quaternion + * @param q an Eigen quaternion + * @param omega1 4-by-4 omega_1 matrix + */ + Eigen::Matrix4d getOmega1(const Eigen::Quaterniond& q); + + /** + * Get a 4-by-4 block diagonal matrix with each block represents omega_1 + * @param q + * @param theta + * @param D_omega + */ + void getBlockDiagOmega(int Npm, const Eigen::Quaterniond& q, + Eigen::Matrix* D_omega); + + /** + * Get Q cost matrix (see Proposition 10 in [1]) + * @param v1 vectors under rotation + * @param v2 vectors after rotation + */ + void getQCost(const Eigen::Matrix& v1, + const Eigen::Matrix& v2, + Eigen::Matrix* Q); + + /** + * Given an arbitrary matrix W, project W to the correct dual structure + (1) off-diagonal blocks must be skew-symmetric + (2) diagonal blocks must satisfy W_00 = - sum(W_ii) + (3) W_dual must also satisfy complementary slackness (because M_init satisfies complementary + slackness) This projection is optimal in the sense of minimum Frobenious norm + */ + void getOptimalDualProjection(const Eigen::Matrix& W, + const Eigen::Matrix& theta_prepended, + const SparseMatrix& A_inv, Eigen::MatrixXd* W_dual); + + /** + * Generate an initial guess (see Appendix U of [1]). + * + * The initial guess satisfies: + * 1. KKT complementary slackness + * 2. diagonal blocks of (Q - Lambda_guess) is PSD (except the first diagonal block) + * + * @param R [in] rotation matrix + * @param theta [in] a binary (1 & -1) vector indicating inliers vs. outliers + * @param src [in] + * @param dst [in] + * @param lambda_guess [out] + */ + void getLambdaGuess(const Eigen::Matrix& R, + const Eigen::Matrix& theta, + const Eigen::Matrix& src, + const Eigen::Matrix& dst, + SparseMatrix* lambda_guess); + + /** + * Calculate the inverse of the linear projection matrix A mentioned in Theorem 35 of our TEASER + * paper [1]. + * + * @param theta_prepended [in] a binary (1 & -1) vector indicating inliers vs. outliers, with 1 + * prepended + * @param A_inv [out] inverse of A + */ + void getLinearProjection(const Eigen::Matrix& theta_prepended, + SparseMatrix* A_inv); + +private: + /** + * Calculate the sum of a block (4-by-N) along the columns + * @param A [in] + * @param row [in] + * @param theta [in] + * @param output [out] + */ + void getBlockRowSum(const Eigen::MatrixXd& A, const int& row, + const Eigen::Matrix& theta, + Eigen::Vector4d* output); + + Params params_; +}; + +} // namespace teaser \ No newline at end of file diff --git a/teaser/include/teaser/geometry.h b/teaser/include/teaser/geometry.h index 5474273..42ed50f 100644 --- a/teaser/include/teaser/geometry.h +++ b/teaser/include/teaser/geometry.h @@ -69,4 +69,5 @@ class PointCloud { std::vector points_; }; + } // namespace teaser diff --git a/teaser/include/teaser/linalg.h b/teaser/include/teaser/linalg.h new file mode 100644 index 0000000..c920ecf --- /dev/null +++ b/teaser/include/teaser/linalg.h @@ -0,0 +1,101 @@ +/** + * Copyright (c) 2020, Massachusetts Institute of Technology, + * Cambridge, MA 02139 + * All Rights Reserved + * Authors: Jingnan Shi, et al. (see THANKS for the full author list) + * See LICENSE for the license information + */ + +#pragma once + +#include + +#include +#include +#include + +namespace teaser { + +/** + * Return the hat map of the provided vector (a skew symmetric matrix). + * @param u 3-by-1 vector + * @param x 3-by-3 skew symmetric matrix + */ +Eigen::Matrix hatmap(const Eigen::Matrix& u) { + Eigen::Matrix x; + // clang-format off + x << 0, -u(2), u(1), + u(2), 0, -u(0), + -u(1), u(0), 0; + // clang-format on + return x; +} + +/** + * Vector-vector kronecker product function with fixed-size output + * @tparam NumT + * @tparam N size of the first vector + * @tparam M size of the second vector + * @param v1 [in] first vector + * @param v2 [in] second vector + * @param output [out] output vector + */ +template +void vectorKron(const Eigen::Matrix& v1, const Eigen::Matrix& v2, + Eigen::Matrix* output) { +#pragma omp parallel for collapse(2) shared(v1, v2, output) default(none) + for (size_t i = 0; i < N; ++i) { + for (size_t j = 0; j < M; ++j) { + (*output)[i * M + j] = v1[i] * v2[j]; + } + } +} + +/** + * Vector-vector kronecker product function with dynamic-size output + * @tparam NumT numerical type for Eigen matrices (double, float, etc.) + * @param v1 [in] first vector + * @param v2 [in] second vector + * @return Result of kronecker product + */ +template +Eigen::Matrix vectorKron(const Eigen::Matrix& v1, + const Eigen::Matrix& v2) { + Eigen::Matrix output(v1.rows() * v2.rows(), 1); +#pragma omp parallel for collapse(2) shared(v1, v2, output) default(none) + for (size_t i = 0; i < v1.rows(); ++i) { + for (size_t j = 0; j < v2.rows(); ++j) { + output[i * v2.rows() + j] = v1[i] * v2[j]; + } + } + return output; +} + +/** + * Find the nearest (in Frobenius norm) Symmetric Positive Definite matrix to A + * + * See: https://www.sciencedirect.com/science/article/pii/0024379588902236 + * + * @tparam NumT numerical type for Eigen matrices (double, float, etc.) + * @param A [in] input matrix + * @param nearestPSD [out] output neaest positive semi-definite matrix + * @param eig_threshold [in] optional threshold of determining the smallest eigen values + */ +template +void getNearestPSD(const Eigen::Matrix& A, + Eigen::Matrix* nearestPSD) { + assert(A.rows() == A.cols()); + nearestPSD->resize(A.rows(), A.cols()); + + // symmetrize A into B + Eigen::MatrixXd B = (A + A.transpose()) / 2; + + // eigendecomposition of B + Eigen::SelfAdjointEigenSolver eig_B(B); + Eigen::VectorXd De = eig_B.eigenvalues(); + Eigen::MatrixXd De_positive = (De.array() < 0).select(0, De).asDiagonal(); + Eigen::MatrixXd Ve = eig_B.eigenvectors(); + *nearestPSD = Ve * De_positive * Ve.transpose(); +} + +} // namespace teaser \ No newline at end of file diff --git a/teaser/include/teaser/macros.h b/teaser/include/teaser/macros.h index 9f21222..b6be4c9 100644 --- a/teaser/include/teaser/macros.h +++ b/teaser/include/teaser/macros.h @@ -10,19 +10,46 @@ #include -#define TEASER_DEBUG_ERROR_VAR(x) \ +#define TEASER_DEBUG_ERROR_VAR(x) \ do { \ std::cerr << #x << " = " << x << std::endl; \ } while (0) +#define TEASER_INFO_MSG(x) \ + do { \ + std::cout << x; \ + } while (0) + +#define TEASER_INFO_MSG_THROTTLE(x, i, N) \ + do { \ + if (i % N == 0) { \ + std::cout << x; \ + } \ + } while (0) + #if defined(NDEBUG) && !defined(TEASER_DIAG_PRINT) +// Use NOOP to turn off the defined debug macros #define TEASER_DEBUG_ERROR_MSG(x) \ do { \ } while (0) #define TEASER_DEBUG_INFO_MSG(x) \ do { \ } while (0) +// Timing macros +#define TEASER_DEBUG_DECLARE_TIMING(s) \ + do { \ + } while (0) +#define TEASER_DEBUG_START_TIMING(s) \ + do { \ + } while (0) +#define TEASER_DEBUG_STOP_TIMING(s) \ + do { \ + } while (0) +#define TEASER_DEBUG_GET_TIMING(s) \ + do { \ + } while (0) #else +// Debug messages #define TEASER_DEBUG_ERROR_MSG(x) \ do { \ std::cerr << x << std::endl; \ @@ -31,4 +58,12 @@ do { \ std::cout << x << std::endl; \ } while (0) +// Timing macros +#define TEASER_DEBUG_DECLARE_TIMING(s) std::chrono::steady_clock clock_##s; +#define TEASER_DEBUG_START_TIMING(s) auto t_start_##s = clock_##s.now(); +#define TEASER_DEBUG_STOP_TIMING(s) \ + auto t_end_##s = clock_##s.now(); \ + std::chrono::duration diff_dur_##s = t_end_##s - t_start_##s; \ + double diff_##s = diff_dur_##s.count(); +#define TEASER_DEBUG_GET_TIMING(s)(double)(diff_##s / 1000.0) #endif \ No newline at end of file diff --git a/teaser/include/teaser/registration.h b/teaser/include/teaser/registration.h index fa5b8cb..dfe0d21 100644 --- a/teaser/include/teaser/registration.h +++ b/teaser/include/teaser/registration.h @@ -355,6 +355,17 @@ class RobustRegistrationSolver { NONE = 3, }; + /** + * Enum representing the formulation of the TIM graph after maximum clique filtering. + * + * CHAIN: formulate TIMs by only calculating the TIMs for consecutive measurements + * COMPLETE: formulate a fully connected TIM graph + */ + enum class INLIER_GRAPH_FORMULATION { + CHAIN = 0, + COMPLETE = 1, + }; + /** * A struct representing params for initializing the RobustRegistrationSolver * @@ -409,6 +420,11 @@ class RobustRegistrationSolver { */ double rotation_cost_threshold = 1e-6; + /** + * Type of TIM graph given to GNC rotation solver + */ + INLIER_GRAPH_FORMULATION rotation_tim_graph = INLIER_GRAPH_FORMULATION::CHAIN; + /** * \brief Type of the inlier selection */ @@ -593,9 +609,9 @@ class RobustRegistrationSolver { * Return a boolean Eigen row vector indicating whether specific measurements are inliers * according to the rotation solver. * - * @return a 1-by-(size of max clique) boolean Eigen matrix. It is equivalent to a binary mask on - * the inlier max clique, with true representing that the measurement is an inlier after - * rotation estimation. + * @return a 1-by-(size of TIMs used in rotation estimation) boolean Eigen matrix. It is + * equivalent to a binary mask on the TIMs used in rotation estimation, with true representing + * that the measurement is an inlier after rotation estimation. */ inline Eigen::Matrix getRotationInliersMask() { return rotation_inliers_mask_; @@ -603,6 +619,7 @@ class RobustRegistrationSolver { /** * Return the index map for translation inliers (equivalent to max clique). + * /TODO: This is obsolete now. Remove or update * * @return a 1-by-(size of max clique) Eigen matrix. Entries represent the indices of the original * measurements. @@ -616,7 +633,9 @@ class RobustRegistrationSolver { /** * Return inliers from rotation estimation * - * @return a vector of indices of measurements deemed as inliers by rotation estimation + * @return a vector of indices of TIMs passed to rotation estimator deemed as inliers by rotation + * estimation. Note that depending on the rotation_tim_graph parameter, number of TIMs passed to + * rotation estimation will be different. */ inline std::vector getRotationInliers() { return rotation_inliers_; } @@ -673,13 +692,13 @@ class RobustRegistrationSolver { inline Eigen::Matrix getDstTIMs() { return dst_tims_; } /** - * Get TIMs built from source point cloud. + * Get src TIMs built after max clique pruning. * @return */ inline Eigen::Matrix getMaxCliqueSrcTIMs() { return pruned_src_tims_; } /** - * Get TIMs built from target point cloud. + * Get dst TIMs built after max clique pruning. * @return */ inline Eigen::Matrix getMaxCliqueDstTIMs() { return pruned_dst_tims_; } @@ -696,6 +715,22 @@ class RobustRegistrationSolver { */ inline Eigen::Matrix getDstTIMsMap() { return dst_tims_map_; } + /** + * Get the index map of the TIMs used in rotation estimation. + * @return + */ + inline Eigen::Matrix getSrcTIMsMapForRotation() { + return src_tims_map_rotation_; + } + + /** + * Get the index map of the TIMs used in rotation estimation. + * @return + */ + inline Eigen::Matrix getDstTIMsMapForRotation() { + return dst_tims_map_rotation_; + } + /** * Reset the solver using the provided params * @param params a Params struct @@ -748,14 +783,20 @@ class RobustRegistrationSolver { Eigen::Matrix translation_inliers_mask_; // TIMs + // TIMs used for scale estimation/pruning Eigen::Matrix src_tims_; Eigen::Matrix dst_tims_; + // TIMs used for rotation estimation Eigen::Matrix pruned_src_tims_; Eigen::Matrix pruned_dst_tims_; // TIM maps + // for scale estimation Eigen::Matrix src_tims_map_; Eigen::Matrix dst_tims_map_; + // for rotation estimation + Eigen::Matrix src_tims_map_rotation_; + Eigen::Matrix dst_tims_map_rotation_; // Max clique vector std::vector max_clique_; diff --git a/teaser/include/teaser/utils.h b/teaser/include/teaser/utils.h index e92f934..6078a7a 100644 --- a/teaser/include/teaser/utils.h +++ b/teaser/include/teaser/utils.h @@ -143,11 +143,28 @@ inline Eigen::Matrix3d svdRot(const Eigen::Matrix& X, */ template inline std::vector maskVector(Eigen::Matrix mask, - std::vector elements) { + const std::vector& elements) { + assert(mask.cols() == elements.size()); std::vector result; for (size_t i = 0; i < mask.cols(); ++i) { if (mask(i)) { - result.push_back(elements[i]); + result.emplace_back(elements[i]); + } + } + return result; +} + +/** + * Get indices of non-zero elements in an Eigen row vector + * @param mask a 1-by-N boolean Eigen matrix + * @return A vector containing indices of the true elements in the row vector + */ +template +inline std::vector findNonzero(Eigen::Matrix mask) { + std::vector result; + for (size_t i = 0; i < mask.cols(); ++i) { + if (mask(i)) { + result.emplace_back(i); } } return result; diff --git a/teaser/src/certification.cc b/teaser/src/certification.cc new file mode 100644 index 0000000..f01bd46 --- /dev/null +++ b/teaser/src/certification.cc @@ -0,0 +1,656 @@ +/** + * Copyright (c) 2020, Massachusetts Institute of Technology, + * Cambridge, MA 02139 + * All Rights Reserved + * Authors: Jingnan Shi, et al. (see THANKS for the full author list) + * See LICENSE for the license information + */ + +#include +#include +#include +#include + +#include +#include +#include +#include + +#include "teaser/certification.h" +#include "teaser/linalg.h" + +teaser::CertificationResult +teaser::DRSCertifier::certify(const Eigen::Matrix3d& R_solution, + const Eigen::Matrix& src, + const Eigen::Matrix& dst, + const Eigen::Matrix& theta) { + // convert theta to a double Eigen matrix + Eigen::Matrix theta_double(1, theta.cols()); + for (size_t i = 0; i < theta.cols(); ++i) { + if (theta(i)) { + theta_double(i) = 1; + } else { + theta_double(i) = -1; + } + } + return certify(R_solution, src, dst, theta_double); +} + +teaser::CertificationResult +teaser::DRSCertifier::certify(const Eigen::Matrix3d& R_solution, + const Eigen::Matrix& src, + const Eigen::Matrix& dst, + const Eigen::Matrix& theta) { + int N = src.cols(); + int Npm = 4 + 4 * N; + + // prepend theta with 1 + Eigen::Matrix theta_prepended(1, theta.cols() + 1); + theta_prepended << 1, theta; + + // get the inverse map + TEASER_INFO_MSG("Starting linear inverse map calculation.\n"); + TEASER_DEBUG_DECLARE_TIMING(LProj); + TEASER_DEBUG_START_TIMING(LProj); + SparseMatrix inverse_map; + getLinearProjection(theta_prepended, &inverse_map); + TEASER_DEBUG_STOP_TIMING(LProj); + TEASER_DEBUG_INFO_MSG("Obtained linear inverse map."); + TEASER_DEBUG_INFO_MSG("Linear projection time: " << TEASER_DEBUG_GET_TIMING(LProj)); + + // recall data matrix from QUASAR + Eigen::MatrixXd Q_cost(Npm, Npm); + getQCost(src, dst, &Q_cost); + TEASER_DEBUG_INFO_MSG("Obtained Q_cost matrix."); + + // convert the estimated rotation to quaternion + Eigen::Quaterniond q_solution(R_solution); + q_solution.normalize(); + Eigen::VectorXd q_solution_vec(4, 1); + q_solution_vec << q_solution.x(), q_solution.y(), q_solution.z(), q_solution.w(); + + // this would have been the rank-1 decomposition of Z if Z were the globally + // optimal solution of the QUASAR SDP + Eigen::VectorXd x = + teaser::vectorKron(theta_prepended, q_solution_vec); + + // build the "rotation matrix" D_omega + Eigen::MatrixXd D_omega; + getBlockDiagOmega(Npm, q_solution, &D_omega); + Eigen::MatrixXd Q_bar = D_omega.transpose() * (Q_cost * D_omega); + Eigen::VectorXd x_bar = D_omega.transpose() * x; + TEASER_DEBUG_INFO_MSG("Obtained D_omega matrix."); + + // build J_bar matrix with a 4-by-4 identity at the top left corner + Eigen::SparseMatrix J_bar(Npm, Npm); + for (size_t i = 0; i < 4; ++i) { + J_bar.insert(i, i) = 1; + } + + // verify optimality in the "rotated" space using projection + // this is the cost of the primal, when strong duality holds, mu is also the cost of the dual + double mu = x.transpose().dot(Q_cost * x); + + // get initial guess + SparseMatrix lambda_bar_init; + getLambdaGuess(R_solution, theta, src, dst, &lambda_bar_init); + + // this initial guess lives in the affine subspace + // use 2 separate steps to limit slow evaluation on only the few non-zeros in the sparse matrix + Eigen::SparseMatrix M_init = Q_bar - mu * J_bar - lambda_bar_init; + + // flag to indicate whether we exceeded iterations or reach the desired sub-optim gap + bool exceeded_maxiters = true; + + // vector to store suboptim trajectory + std::vector suboptim_traj; + + // current suboptimality gap + double current_suboptim = std::numeric_limits::infinity(); + double best_suboptim = std::numeric_limits::infinity(); + + // preallocate some matrices + Eigen::MatrixXd M_PSD; + // TODO: Make M a sparse matrix + Eigen::MatrixXd M = M_init.toDense(); + Eigen::MatrixXd temp_W(M.rows(), M.cols()); + Eigen::MatrixXd W_dual(Npm, Npm); + Eigen::MatrixXd M_affine(Npm, Npm); + + TEASER_INFO_MSG("Starting Douglas-Rachford Splitting.\n"); + for (size_t iter = 0; iter < params_.max_iterations; ++iter) { + // print out iteration every 10 iteration + TEASER_INFO_MSG_THROTTLE("Iteration: " << iter << "\n", iter, 10); + + // to nearest PSD + TEASER_DEBUG_DECLARE_TIMING(PSD); + TEASER_DEBUG_START_TIMING(PSD); + teaser::getNearestPSD(M, &M_PSD); + TEASER_DEBUG_STOP_TIMING(PSD); + TEASER_DEBUG_INFO_MSG("PSD time: " << TEASER_DEBUG_GET_TIMING(PSD)); + + // projection to affine space + temp_W = 2 * M_PSD - M - M_init; + + TEASER_DEBUG_DECLARE_TIMING(DualProjection); + TEASER_DEBUG_START_TIMING(DualProjection); + getOptimalDualProjection(temp_W, theta_prepended, inverse_map, &W_dual); + TEASER_DEBUG_STOP_TIMING(DualProjection); + TEASER_DEBUG_INFO_MSG("Dual Projection time: " << TEASER_DEBUG_GET_TIMING(DualProjection)); + M_affine = M_init + W_dual; + + // compute suboptimality gap + TEASER_DEBUG_DECLARE_TIMING(Gap); + TEASER_DEBUG_START_TIMING(Gap); + current_suboptim = computeSubOptimalityGap(M_affine, mu, N); + TEASER_DEBUG_STOP_TIMING(Gap); + TEASER_DEBUG_INFO_MSG("Sub Optimality Gap time: " << TEASER_DEBUG_GET_TIMING(Gap)); + TEASER_DEBUG_INFO_MSG("Current sub-optimality gap: " << current_suboptim); + + // termination check and update trajectory + suboptim_traj.push_back(current_suboptim); + + // update best optimality + if (current_suboptim < best_suboptim) { + best_suboptim = current_suboptim; + } + + if (current_suboptim < params_.sub_optimality) { + TEASER_DEBUG_INFO_MSG("Suboptimality condition reached in " << iter + 1 + << " iterations. Stopping DRS."); + exceeded_maxiters = false; + break; + } + + // update M + M += params_.gamma_tau * (M_affine - M_PSD); + } + + // prepare results + CertificationResult cert_result; + cert_result.is_optimal = best_suboptim < params_.sub_optimality; + cert_result.best_suboptimality = best_suboptim; + cert_result.suboptimality_traj = suboptim_traj; + return cert_result; +} + +double teaser::DRSCertifier::computeSubOptimalityGap(const Eigen::MatrixXd& M, double mu, int N) { + Eigen::MatrixXd new_M = (M + M.transpose()) / 2; + + bool successful = false; + Eigen::VectorXd eig_vals; + double min_eig; + if (params_.eig_decomposition_solver == EIG_SOLVER_TYPE::EIGEN) { + // Eigen + Eigen::SelfAdjointEigenSolver eigensolver(new_M); + if (eigensolver.info() == Eigen::Success) { + eig_vals = eigensolver.eigenvalues(); + min_eig = eig_vals.minCoeff(); + successful = true; + } + } else { + // Spectra + Spectra::DenseSymMatProd op(new_M); + Spectra::SymEigsSolver> eigs( + &op, 1, 30); + eigs.init(); + int nconv = eigs.compute(); + if (eigs.info() == Spectra::SUCCESSFUL) { + eig_vals = eigs.eigenvalues(); + min_eig = eig_vals(0); + successful = true; + } + } + + if (!successful) { + TEASER_DEBUG_ERROR_MSG( + "Failed to find the minimal eigenvalue for suboptimality gap calculaiton."); + return std::numeric_limits::infinity(); + } + + if (min_eig > 0) { + // already optimal + return 0; + } + return (-min_eig * (N + 1)) / mu; +} + +void teaser::DRSCertifier::getQCost(const Eigen::Matrix& v1, + const Eigen::Matrix& v2, + Eigen::Matrix* Q) { + int N = v1.cols(); + int Npm = 4 + 4 * N; + double noise_bound_scaled = params_.cbar2 * std::pow(params_.noise_bound, 2); + + // coefficient matrix that maps vec(qq\tran) to vec(R) + Eigen::Matrix P(9, 16); + // clang-format off + P << 1, 0, 0, 0, 0, -1, 0, 0, 0, 0, -1, 0, 0, 0, 0, 1, + 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, + 0, 0, 1, 0, 0, 0, 0, -1, 1, 0, 0, 0, 0, -1, 0, 0, + 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0, -1, 0, + -1, 0, 0, 0, 0, 1, 0, 0, 0, 0, -1, 0, 0, 0, 0, 1, + 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, + 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, + 0, 0, 0, -1, 0, 0, 1, 0, 0, 1, 0, 0, -1, 0, 0, 0, + -1, 0, 0, 0, 0, -1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1; + // clang-format on + + // Some temporary vectors to save intermediate matrices + Eigen::Matrix3d temp_A; + Eigen::Matrix temp_B; + Eigen::Matrix temp_map2vec; + Eigen::Matrix4d P_k; + + // Q1 matrix + Eigen::Matrix Q1(Npm, Npm); + Q1.setZero(); + for (size_t k = 0; k < N; ++k) { + int start_idx = k * 4 + 4; + + // P_k = reshape(P'*reshape(v2(:,k)*v1(:,k)',[9,1]),[4,4]); + temp_A = v2.col(k) * (v1.col(k).transpose()); + temp_map2vec = Eigen::Map>(temp_A.data()); + temp_B = P.transpose() * temp_map2vec; + P_k = Eigen::Map(temp_B.data()); + + // ck = 0.5 * ( v1(:,k)'*v1(:,k)+v2(:,k)'*v2(:,k) - barc2 ); + double ck = 0.5 * (v1.col(k).squaredNorm() + v2.col(k).squaredNorm() - noise_bound_scaled); + Q1.block<4, 4>(0, start_idx) = + Q1.block<4, 4>(0, start_idx) - 0.5 * P_k + ck / 2 * Eigen::Matrix4d::Identity(); + Q1.block<4, 4>(start_idx, 0) = + Q1.block<4, 4>(start_idx, 0) - 0.5 * P_k + ck / 2 * Eigen::Matrix4d::Identity(); + } + + // Q2 matrix + Eigen::Matrix Q2(Npm, Npm); + Q2.setZero(); + for (size_t k = 0; k < N; ++k) { + int start_idx = k * 4 + 4; + + // P_k = reshape(P'*reshape(v2(:,k)*v1(:,k)',[9,1]),[4,4]); + temp_A = v2.col(k) * (v1.col(k).transpose()); + temp_map2vec = Eigen::Map>(temp_A.data()); + temp_B = P.transpose() * temp_map2vec; + P_k = Eigen::Map(temp_B.data()); + + // ck = 0.5 * ( v1(:,k)'*v1(:,k)+v2(:,k)'*v2(:,k) + barc2 ); + double ck = 0.5 * (v1.col(k).squaredNorm() + v2.col(k).squaredNorm() + noise_bound_scaled); + Q2.block<4, 4>(start_idx, start_idx) = + Q2.block<4, 4>(start_idx, start_idx) - P_k + ck * Eigen::Matrix4d::Identity(); + } + + *Q = Q1 + Q2; +} + +Eigen::Matrix4d teaser::DRSCertifier::getOmega1(const Eigen::Quaterniond& q) { + Eigen::Matrix4d omega1; + // clang-format off + omega1 << q.w(), -q.z(), q.y(), q.x(), + q.z(), q.w(), -q.x(), q.y(), + -q.y(), q.x(), q.w(), q.z(), + -q.x(), -q.y(), -q.z(), q.w(); + // clang-format on + return omega1; +} + +void teaser::DRSCertifier::getBlockDiagOmega( + int Npm, const Eigen::Quaterniond& q, + Eigen::Matrix* D_omega) { + D_omega->resize(Npm, Npm); + D_omega->setZero(); + for (size_t i = 0; i < Npm / 4; ++i) { + int start_idx = i * 4; + D_omega->block<4, 4>(start_idx, start_idx) = getOmega1(q); + } +} + +void teaser::DRSCertifier::getOptimalDualProjection( + const Eigen::Matrix& W, + const Eigen::Matrix& theta_prepended, const SparseMatrix& A_inv, + Eigen::MatrixXd* W_dual) { + // prepare some variables + int Npm = W.rows(); + int N = Npm / 4 - 1; + assert(theta_prepended.cols() == N + 1); + + // first project the off-diagonal blocks + int nr_off_diag_blks = A_inv.rows(); + + // Compute b_W + Eigen::Matrix b_W(nr_off_diag_blks, 3); + b_W.setZero(); + + int count = 0; + for (size_t i = 0; i < N; ++i) { + // prepare indices + int row_idx_start = i * 4; + int row_idx_end = i * 4 + 3; + for (size_t j = i + 1; j < N + 1; ++j) { + // prepare indices + int col_idx_start = j * 4; + int col_idx_end = j * 4 + 3; + + // current theta value calculation + double theta_ij = theta_prepended.col(i) * theta_prepended.col(j); + + // [-theta_ij 1] + Eigen::Matrix temp_A; + temp_A << -theta_ij, 1; + + // [-1 theta_ij] + Eigen::Matrix temp_B; + temp_B << -1, theta_ij; + + // W([row_idx(4) col_idx(4)],row_idx(1:3)) + Eigen::Matrix temp_C = W.block<1, 3>(row_idx_end, row_idx_start); + Eigen::Matrix temp_D = W.block<1, 3>(col_idx_end, row_idx_start); + Eigen::Matrix temp_CD; + temp_CD << temp_C, temp_D; + + // W([row_idx(4) col_idx(4)], col_idx(1:3)) + Eigen::Matrix temp_E = W.block<1, 3>(row_idx_end, col_idx_start); + Eigen::Matrix temp_F = W.block<1, 3>(col_idx_end, col_idx_start); + Eigen::Matrix temp_EF; + temp_EF << temp_E, temp_F; + + // calculate the current row for b_W with the temporary variables + Eigen::Matrix y_b_Wt = temp_A * temp_CD + temp_B * temp_EF; + + // update b_W + b_W.row(count) = y_b_Wt; + count += 1; + } + } + Eigen::Matrix b_W_dual = A_inv * b_W; + + // Compute W_dual + W_dual->resize(Npm, Npm); + W_dual->setZero(); + count = 0; + // declare matrices to prevent reallocation + Eigen::Matrix4d W_ij = Eigen::Matrix4d::Zero(); + Eigen::Matrix4d W_dual_ij = Eigen::Matrix4d::Zero(); + Eigen::Matrix y_dual_ij = Eigen::Matrix::Zero(); + Eigen::Matrix W_i(4, W.cols()); + Eigen::Matrix W_dual_i(4, Npm); + W_i.setZero(); + W_dual_i.setZero(); + for (size_t i = 0; i < N; ++i) { + int row_idx_start = i * 4; + W_i = W.block(row_idx_start, 0, 4, W.cols()); + + for (size_t j = i + 1; j < N + 1; ++j) { + int col_idx_start = j * 4; + + // take W_ij and break into top-left 3x3 and vectors + W_ij = W_i.block(0, col_idx_start, 4, 4); + y_dual_ij = (b_W_dual.row(count)).transpose(); + + // assemble W_dual_ij + W_dual_ij = (W_ij - W_ij.transpose()) / 2; + W_dual_ij.block<3, 1>(0, 3) = y_dual_ij; + W_dual_ij.block<1, 3>(3, 0) = -y_dual_ij.transpose(); + + // assign W_dual_ij to W_dual_i + W_dual_i.block<4, 4>(0, col_idx_start) = W_dual_ij; + + count += 1; + } + W_dual->block(row_idx_start, 0, 4, Npm) = W_dual_i; + + // clear out temporary variables + W_dual_i.setZero(); + W_i.setZero(); + } + Eigen::MatrixXd temp = W_dual->transpose(); + *W_dual += temp; + + // Project the diagonal blocks + Eigen::Matrix4d W_ii = Eigen::Matrix4d::Zero(); + Eigen::Matrix4d W_diag_mean = Eigen::Matrix4d::Zero(); + Eigen::Matrix3d W_diag_sum_33 = Eigen::Matrix3d::Zero(); + for (size_t i = 0; i < N + 1; ++i) { + int idx_start = i * 4; + // Eigen::Vector4d W_dual_row_sum_last_column= W_dual->middleRows<4>(idx_start).rowwise().sum(); + Eigen::Vector4d W_dual_row_sum_last_column; + // sum 4 rows + getBlockRowSum(*W_dual, idx_start, theta_prepended, &W_dual_row_sum_last_column); + W_ii = W.block<4, 4>(idx_start, idx_start); + // modify W_ii's last column/row to satisfy complementary slackness + W_ii.block<4, 1>(0, 3) = -theta_prepended(i) * W_dual_row_sum_last_column; + W_ii.block<1, 4>(3, 0) = -theta_prepended(i) * W_dual_row_sum_last_column.transpose(); + (*W_dual).block<4, 4>(idx_start, idx_start) = W_ii; + W_diag_sum_33 += W_ii.topLeftCorner<3, 3>(); + } + W_diag_mean.topLeftCorner<3, 3>() = W_diag_sum_33 / (N + 1); + + // update diagonal blocks + Eigen::Matrix temp_A((N + 1) * W_diag_mean.rows(), + (N + 1) * W_diag_mean.cols()); + temp_A.setZero(); + for (int i = 0; i < N + 1; i++) { + temp_A.block(i * W_diag_mean.rows(), i * W_diag_mean.cols(), W_diag_mean.rows(), + W_diag_mean.cols()) = W_diag_mean; + } + *W_dual -= temp_A; +} + +void teaser::DRSCertifier::getLambdaGuess(const Eigen::Matrix& R, + const Eigen::Matrix& theta, + const Eigen::Matrix& src, + const Eigen::Matrix& dst, + SparseMatrix* lambda_guess) { + int K = theta.cols(); + int Npm = 4 * K + 4; + + double noise_bound_scaled = params_.cbar2 * std::pow(params_.noise_bound, 2); + + // prepare the lambda sparse matrix output + lambda_guess->resize(Npm, Npm); + lambda_guess->reserve(Npm * (Npm - 1) * 2); + lambda_guess->setZero(); + + // 4-by-4 Eigen matrix to store the top left 4-by-4 block + Eigen::Matrix topleft_block = Eigen::Matrix4d::Zero(); + + // 4-by-4 Eigen matrix to store the current 4-by-4 block + Eigen::Matrix current_block = Eigen::Matrix4d::Zero(); + + for (size_t i = 0; i < K; ++i) { + // hat maps for later usage + Eigen::Matrix src_i_hatmap = teaser::hatmap(src.col(i)); + if (theta(0, i) > 0) { + // residual + Eigen::Matrix xi = R.transpose() * (dst.col(i) - R * src.col(i)); + Eigen::Matrix xi_hatmap = teaser::hatmap(xi); + + // compute the (4,4) entry of the current block, obtained from KKT complementary slackness + current_block(3, 3) = -0.75 * xi.squaredNorm() - 0.25 * noise_bound_scaled; + + // compute the top-left 3-by-3 block + current_block.topLeftCorner<3, 3>() = + src_i_hatmap * src_i_hatmap - 0.5 * (src.col(i)).dot(xi) * Eigen::Matrix3d::Identity() + + 0.5 * xi_hatmap * src_i_hatmap + 0.5 * xi * src.col(i).transpose() - + 0.75 * xi.squaredNorm() * Eigen::Matrix3d::Identity() - + 0.25 * noise_bound_scaled * Eigen::Matrix3d::Identity(); + + // compute the vector part + current_block.topRightCorner<3, 1>() = -1.5 * xi_hatmap * src.col(i); + current_block.bottomLeftCorner<1, 3>() = (current_block.topRightCorner<3, 1>()).transpose(); + } else { + // residual + Eigen::Matrix phi = R.transpose() * (dst.col(i) - R * src.col(i)); + Eigen::Matrix phi_hatmap = teaser::hatmap(phi); + + // compute lambda_i, (4,4) entry + current_block(3, 3) = -0.25 * phi.squaredNorm() - 0.75 * noise_bound_scaled; + + // compute E_ii, top-left 3-by-3 block + current_block.topLeftCorner<3, 3>() = + src_i_hatmap * src_i_hatmap - 0.5 * (src.col(i)).dot(phi) * Eigen::Matrix3d::Identity() + + 0.5 * phi_hatmap * src_i_hatmap + 0.5 * phi * src.col(i).transpose() - + 0.25 * phi.squaredNorm() * Eigen::Matrix3d::Identity() - + 0.25 * noise_bound_scaled * Eigen::Matrix3d::Identity(); + + // compute x_i + current_block.topRightCorner<3, 1>() = -0.5 * phi_hatmap * src.col(i); + current_block.bottomLeftCorner<1, 3>() = (current_block.topRightCorner<3, 1>()).transpose(); + } + + // put the current block to the sparse triplets + // start idx: i * 4 + // end idx: i * 4 + 3 + // assume current block is column major + for (size_t col = 0; col < 4; ++col) { + for (size_t row = 0; row < 4; ++row) { + lambda_guess->insert((i + 1) * 4 + row, (i + 1) * 4 + col) = -current_block(row, col); + } + } + + // update the first block + topleft_block += current_block; + } + + // put the first block to the sparse matrix + for (size_t col = 0; col < 4; ++col) { + for (size_t row = 0; row < 4; ++row) { + lambda_guess->coeffRef(row, col) += topleft_block(row, col); + } + } +} + +void teaser::DRSCertifier::getLinearProjection( + const Eigen::Matrix& theta_prepended, SparseMatrix* A_inv) { + // number of off-diagonal entries in the inverse map + int N0 = theta_prepended.cols() - 1; + + double y = 1.0 / (2 * static_cast(N0) + 6); + // number of diagonal entries in the inverse map + double x = (static_cast(N0) + 1.0) * y; + + int N = N0 + 1; + + // build the mapping from independent var idx to matrix index + int nr_vals = N * (N - 1) / 2; + Eigen::Matrix mat2vec = Eigen::MatrixXd::Zero(N, N); + int count = 0; + for (size_t i = 0; i < N - 1; ++i) { + for (size_t j = i + 1; j < N; ++j) { + mat2vec(i, j) = count; + count += 1; + } + } + + // creating the inverse map sparse matrix and reserve memory + int nrNZ_per_row_off_diag = 2 * (N0 - 1) + 1; + // int nrNZ_off_diag = nrNZ_per_row_off_diag * nr_vals; + + // resize the inverse matrix to the appropriate size + // this won't reserve any memory for non-zero values + A_inv->resize(nr_vals, nr_vals); + + // temporary vector storing column for holding the non zero entries + std::vector> temp_column; + temp_column.reserve(nrNZ_per_row_off_diag); + + // for creating columns in inv_A + for (size_t i = 0; i < N - 1; ++i) { + TEASER_INFO_MSG_THROTTLE("Linear proj at i=" << i << "\n", i, 10); + for (size_t j = i + 1; j < N; ++j) { + // get current column index + // var_j_idx is unique for all each loop, i.e., each var_j_idx only occurs once and the loops + // won't enter the same column twice + int var_j_idx = mat2vec(i, j); + + // start a inner vector + // A_inv is column major so this will enable us to insert values to the end of column + // var_j_idx + A_inv->startVec(var_j_idx); + + // flag to indicated whether a diagonal entry on this column has been inserted + // this is used to save computation time for adding x to all the diagonal entries + bool diag_inserted = false; + size_t diag_idx = 0; + + for (size_t p = 0; p < N; ++p) { + if ((p != j) && (p != i)) { + int var_i_idx; + double entry_val; + if (p < i) { + // same row i, i,j upper triangular, i,p lower triangular + // flip to upper-triangular + var_i_idx = mat2vec(p, i); + entry_val = y * theta_prepended(j) * theta_prepended(p); + } else { + var_i_idx = mat2vec(i, p); + entry_val = -y * theta_prepended(j) * theta_prepended(p); + } + temp_column.emplace_back(var_i_idx, var_j_idx, entry_val); + if (var_i_idx == var_j_idx) { + diag_inserted = true; + diag_idx = temp_column.size()-1; + } + } + } + for (size_t p = 0; p < N; ++p) { + if ((p != i) && (p != j)) { + int var_i_idx; + double entry_val; + if (p < j) { + // flip to upper-triangular + var_i_idx = mat2vec(p, j); + entry_val = -y * theta_prepended(i) * theta_prepended(p); + } else { + var_i_idx = mat2vec(j, p); + entry_val = y * theta_prepended(i) * theta_prepended(p); + } + temp_column.emplace_back(var_i_idx, var_j_idx, entry_val); + if (var_i_idx == var_j_idx) { + diag_inserted = true; + diag_idx = temp_column.size()-1; + } + } + } + + // insert diagonal entries if not already done so + if (!diag_inserted) { + temp_column.emplace_back(var_j_idx, var_j_idx, x); + } else { + double entry_val = temp_column[diag_idx].value() + x; + temp_column[diag_idx] = {var_j_idx, var_j_idx, entry_val}; + } + + // sort by row index (ascending) + std::sort(temp_column.begin(), temp_column.end(), + [](const Eigen::Triplet& t1, const Eigen::Triplet& t2) { + return t1.row() < t2.row(); + }); + + // populate A_inv with the temporary column + for (size_t tidx = 0; tidx < temp_column.size(); ++tidx) { + // take care of the diagonal entries + A_inv->insertBack(temp_column[tidx].row(), var_j_idx) = temp_column[tidx].value(); + } + temp_column.clear(); + temp_column.reserve(nrNZ_per_row_off_diag); + } + } + TEASER_DEBUG_INFO_MSG("Finalizing A_inv ..."); + A_inv->finalize(); + TEASER_DEBUG_INFO_MSG("A_inv finalized."); +} + +void teaser::DRSCertifier::getBlockRowSum(const Eigen::MatrixXd& A, const int& row, + const Eigen::Matrix& theta, + Eigen::Vector4d* output) { + // unit = sparse(4,1); unit(end) = 1; + // vector = kron(theta,unit); % vector of size 4N+4 by 1 + // entireRow = A(blkIndices(row,4),:); % entireRow of size 4 by 4N+4 + // row_sum_last_column = entireRow * vector; % last column sum has size 4 by 1; + Eigen::Matrix unit = Eigen::Matrix::Zero(); + unit(3, 0) = 1; + Eigen::Matrix vector = + vectorKron(theta.transpose(), unit); + *output = A.middleRows<4>(row) * vector; +} diff --git a/teaser/src/registration.cc b/teaser/src/registration.cc index 31abfe6..3e107a1 100644 --- a/teaser/src/registration.cc +++ b/teaser/src/registration.cc @@ -494,12 +494,22 @@ teaser::RobustRegistrationSolver::solve(const Eigen::Matrix pruned_src(3, max_clique_.size()); - Eigen::Matrix pruned_dst(3, max_clique_.size()); + // Calculate new measurements & TIMs based on max clique inliers + if (params_.rotation_tim_graph == INLIER_GRAPH_FORMULATION::CHAIN) { + // chain graph + TEASER_DEBUG_INFO_MSG("Using chain graph for GNC rotation."); pruned_src_tims_.resize(3, max_clique_.size()); pruned_dst_tims_.resize(3, max_clique_.size()); + src_tims_map_rotation_.resize(2, max_clique_.size()); + dst_tims_map_rotation_.resize(2, max_clique_.size()); for (size_t i = 0; i < max_clique_.size(); ++i) { const auto& root = max_clique_[i]; int leaf; @@ -508,35 +518,35 @@ teaser::RobustRegistrationSolver::solve(const Eigen::Matrix src_inliers(3, max_clique_.size()); + Eigen::Matrix dst_inliers(3, max_clique_.size()); + for (size_t i = 0; i < max_clique_.size(); ++i) { + src_inliers.col(i) = src.col(max_clique_[i]); + dst_inliers.col(i) = dst.col(max_clique_[i]); } + // construct the TIMs + pruned_dst_tims_ = computeTIMs(dst_inliers, &dst_tims_map_rotation_); + pruned_src_tims_ = computeTIMs(src_inliers, &src_tims_map_rotation_); } // Remove scaling for rotation estimation pruned_dst_tims_ *= (1 / solution_.scale); // Update GNC rotation solver's noise bound with the new information - // Note: this implicitly assume that rotation_solver_'s noise bound + // Note: this implicitly assumes that rotation_solver_'s noise bound // is set to the original noise bound of the measurements. auto params = rotation_solver_->getParams(); params.noise_bound *= (2 / solution_.scale); @@ -547,17 +557,17 @@ teaser::RobustRegistrationSolver::solve(const Eigen::Matrix(rotation_inliers_mask_, max_clique_); - Eigen::Matrix rotation_pruned_src(3, rotation_inliers_.size()); - Eigen::Matrix rotation_pruned_dst(3, rotation_inliers_.size()); - for (size_t i = 0; i < rotation_inliers_.size(); ++i) { - rotation_pruned_src.col(i) = src.col(rotation_inliers_[i]); - rotation_pruned_dst.col(i) = dst.col(rotation_inliers_[i]); + // Save indices of inlier TIMs from GNC rotation estimation + for (size_t i = 0; i < rotation_inliers_mask_.cols(); ++i) { + if (rotation_inliers_mask_[i]) { + rotation_inliers_.emplace_back(i); + } + } + Eigen::Matrix rotation_pruned_src(3, max_clique_.size()); + Eigen::Matrix rotation_pruned_dst(3, max_clique_.size()); + for (size_t i = 0; i < max_clique_.size(); ++i) { + rotation_pruned_src.col(i) = src.col(max_clique_[i]); + rotation_pruned_dst.col(i) = dst.col(max_clique_[i]); } // Solve for translation @@ -567,7 +577,7 @@ teaser::RobustRegistrationSolver::solve(const Eigen::Matrix(translation_inliers_mask_, rotation_inliers_); + translation_inliers_ = utils::findNonzero(translation_inliers_mask_); // Update validity flag solution_.valid = true; @@ -633,6 +643,8 @@ void teaser::GNCTLSRotationSolver::solveForRotation( if (noise_bound_sq < 1e-16) { noise_bound_sq = 1e-2; } + TEASER_DEBUG_INFO_MSG("GNC rotation estimation noise bound:" << params_.noise_bound); + TEASER_DEBUG_INFO_MSG("GNC rotation estimation noise bound squared:" << noise_bound_sq); Eigen::Matrix diffs(3, match_size); Eigen::Matrix weights(1, match_size); @@ -696,6 +708,8 @@ void teaser::GNCTLSRotationSolver::solveForRotation( } if (inliers) { - *inliers = weights.cast(); + for (size_t i = 0; i < weights.cols(); ++i) { + (*inliers)(0, i) = weights(0, i) >= 0.5; + } } } diff --git a/test/benchmark/CMakeLists.txt b/test/benchmark/CMakeLists.txt index a5d658f..720d7e1 100644 --- a/test/benchmark/CMakeLists.txt +++ b/test/benchmark/CMakeLists.txt @@ -7,6 +7,7 @@ add_executable(all_benchmarks registration-benchmark.cc) target_link_libraries(all_benchmarks Eigen3::Eigen + ${TEASERPP_BLAS_LAPACK_LIBS} gtest gmock teaser_io diff --git a/test/teaser/CMakeLists.txt b/test/teaser/CMakeLists.txt index 76a11f0..da3bf46 100644 --- a/test/teaser/CMakeLists.txt +++ b/test/teaser/CMakeLists.txt @@ -11,9 +11,12 @@ set(TEST_SRCS rotation-solver-test.cc translation-solver-test.cc registration-test.cc - graph-test.cc) + graph-test.cc + certification-test.cc + linalg-test.cc) set(TEST_LINK_LIBRARIES Eigen3::Eigen + ${TEASERPP_BLAS_LAPACK_LIBS} gtest gmock teaser_io @@ -34,7 +37,7 @@ target_link_libraries(all_tests ${TEST_LINK_LIBRARIES}) gtest_add_tests(TARGET all_tests TEST_LIST allTests) -set_tests_properties(${allTests} PROPERTIES TIMEOUT 10) +set_tests_properties(${allTests} PROPERTIES TIMEOUT 120) # Copy test data files to binary directory file(COPY . diff --git a/test/teaser/certification-test.cc b/test/teaser/certification-test.cc new file mode 100644 index 0000000..e06220b --- /dev/null +++ b/test/teaser/certification-test.cc @@ -0,0 +1,644 @@ +/** + * Copyright 2020, Massachusetts Institute of Technology, + * Cambridge, MA 02139 + * All Rights Reserved + * Authors: Jingnan Shi, et al. (see THANKS for the full author list) + * See LICENSE for the license information + */ + +#include +#include +#include +#include +#include +#include +#include + +#include "gtest/gtest.h" +#include "gmock/gmock.h" + +#include +#include + +#include "teaser/certification.h" +#include "test_utils.h" + +/** + * Acceptable numerical error threshold for all certification tests + */ +const double ACCEPTABLE_ERROR = 1e-7; + +/** + * Test fixture for loading data case by case + */ +class DRSCertifierTest : public ::testing::Test { +protected: + /** + * Inputs for the DRSCertifier + * + * Note that some may be intermediate outputs from other functions. + */ + struct Inputs { + teaser::DRSCertifier::Params params; + Eigen::Matrix v1; + Eigen::Matrix v2; + Eigen::Matrix3d R_est; + Eigen::Quaternion q_est; + Eigen::Matrix theta_est; + Eigen::MatrixXd W; + Eigen::MatrixXd M_affine; + double mu; + }; + + /** + * Expected outputs for methods under the DRSCertifier + */ + struct ExpectedOutputs { + Eigen::Matrix4d omega; + Eigen::MatrixXd block_diag_omega; + Eigen::MatrixXd Q_cost; + Eigen::MatrixXd lambda_guess; + Eigen::MatrixXd A_inv; + Eigen::MatrixXd W_dual; + double suboptimality_1st_iter; + teaser::CertificationResult certification_result; + }; + + struct CaseData { + Inputs inputs; + ExpectedOutputs expected_outputs; + }; + + /** + * Helper function to load parameters + * @param file_path + * @param cbar2 + * @param noise_bound + */ + void loadScalarParameters(std::string file_path, teaser::DRSCertifier::Params* params) { + // Open the file + std::ifstream file; + file.open(file_path); + if (!file) { + std::cerr << "Unable to open file: " << file_path << "." << std::endl; + exit(1); + } + std::string line; + std::string delimiter = ":"; + while (std::getline(file, line)) { + + size_t delim_idx = line.find(delimiter, 0); + std::string param = line.substr(0, delim_idx); + std::string value = line.substr(delim_idx + 2, line.length()); + + if (param == "cbar2") { + params->cbar2 = std::stod(value); + } else if (param == "noise_bound") { + params->noise_bound = std::stod(value); + } else if (param == "max_iterations") { + params->max_iterations = std::stod(value); + } + } + } + + /** + * Helper function to compare two certification results + * @param actual_result + * @param expected_result + */ + void compareCertificationResult(teaser::CertificationResult actual_result, + teaser::CertificationResult expected_result) { + + EXPECT_EQ(actual_result.suboptimality_traj.size(), expected_result.suboptimality_traj.size()) + << "Mismatch in suboptimality trajectory sizes."; + + auto act_itr = actual_result.suboptimality_traj.begin(); + auto act_end_itr = actual_result.suboptimality_traj.end(); + auto exp_itr = expected_result.suboptimality_traj.begin(); + auto exp_end_itr = expected_result.suboptimality_traj.end(); + while (act_itr != act_end_itr && exp_itr != exp_end_itr && + std::abs(*act_itr - *exp_itr) < ACCEPTABLE_ERROR) { + ++act_itr, ++exp_itr; + } + EXPECT_TRUE(act_itr == act_end_itr && exp_itr == exp_end_itr) + << "Mismatch between actual and expected suboptimality trajectory values."; + + ASSERT_TRUE(std::abs(actual_result.best_suboptimality - expected_result.best_suboptimality) < + ACCEPTABLE_ERROR) + << "Incorrect best optimality gap."; + } + + /** + * Helper function to set up small certification test instances + */ + void setupSmallInstances() { + std::string root_dir = "./data/certification_small_instances/"; + auto cases = teaser::test::readSubdirs(root_dir); + for (const auto& c : cases) { + std::string case_dir = root_dir + c; + + CaseData data; + + // Inputs: + // scalar parameters + loadScalarParameters(case_dir + "/parameters.txt", &(data.inputs.params)); + + // v1: 3-by-N matrix + // These are the TIMs + std::ifstream v1_source_file(case_dir + "/v1.csv"); + data.inputs.v1 = + teaser::test::readFileToEigenMatrix(v1_source_file); + + // v2: 3-by-N matrix + // These are the TIMs + std::ifstream v2_source_file(case_dir + "/v2.csv"); + data.inputs.v2 = + teaser::test::readFileToEigenMatrix(v2_source_file); + + // q_est: estimated quaternion + std::ifstream q_source_file(case_dir + "/q_est.csv"); + auto q_mat = teaser::test::readFileToEigenFixedMatrix(q_source_file); + Eigen::Quaternion q(q_mat(3), q_mat(0), q_mat(1), q_mat(2)); + data.inputs.q_est = q; + + // R_est: estimated quaternion + std::ifstream R_est_source_file(case_dir + "/R_est.csv"); + data.inputs.R_est = teaser::test::readFileToEigenFixedMatrix(R_est_source_file); + + // theta_est: binary outlier vector + std::ifstream theta_source_file(case_dir + "/theta_est.csv"); + data.inputs.theta_est = + teaser::test::readFileToEigenMatrix(theta_source_file); + + // W: inputs for optimal dual projection + std::ifstream W_source_file(case_dir + "/W_1st_iter.csv"); + data.inputs.W = teaser::test::readFileToEigenMatrix( + W_source_file); + + // M_affine: for calculating suboptimality + std::ifstream M_affine_source_file(case_dir + "/M_affine_1st_iter.csv"); + data.inputs.M_affine = + teaser::test::readFileToEigenMatrix( + M_affine_source_file); + + // mu: for calculating suboptimality + std::ifstream mu_source_file(case_dir + "/mu.csv"); + data.inputs.mu = teaser::test::readFileToEigenFixedMatrix(mu_source_file)(0); + + // Outputs: + // omega: omega1 matrix + std::ifstream omega_source_file(case_dir + "/omega.csv"); + data.expected_outputs.omega = + teaser::test::readFileToEigenFixedMatrix(omega_source_file); + + // block_diag_omega: block diagonal omega matrix + std::ifstream block_diag_omega_source_file(case_dir + "/block_diag_omega.csv"); + data.expected_outputs.block_diag_omega = + teaser::test::readFileToEigenMatrix( + block_diag_omega_source_file); + + // Q_cost: Q_cost matrix + std::ifstream q_cost_source_file(case_dir + "/Q_cost.csv"); + data.expected_outputs.Q_cost = + teaser::test::readFileToEigenMatrix( + q_cost_source_file); + + // lambda guess: initial guess + std::ifstream lambda_guess_source_file(case_dir + "/lambda_bar_init.csv"); + data.expected_outputs.lambda_guess = + teaser::test::readFileToEigenMatrix( + lambda_guess_source_file); + + // A_inv: inverse map from getLinearProjection + std::ifstream A_inv_source_file(case_dir + "/A_inv.csv"); + data.expected_outputs.A_inv = + teaser::test::readFileToEigenMatrix( + A_inv_source_file); + + // W_dual: output from optimal dual projection + std::ifstream W_dual_source_file(case_dir + "/W_dual_1st_iter.csv"); + data.expected_outputs.W_dual = + teaser::test::readFileToEigenMatrix( + W_dual_source_file); + + // suboptimality: calculated suboptimality after 1st iteration + std::ifstream suboptimality_source_file(case_dir + "/suboptimality_1st_iter.csv"); + data.expected_outputs.suboptimality_1st_iter = + teaser::test::readFileToEigenFixedMatrix(suboptimality_source_file)(0); + + // certification_result: a struct holding certification results. Specifically: + // suboptimality_trajy: suboptimality gaps throughout all the iterations + // best_suboptimality: smallest suboptimality gap + std::ifstream suboptimality_traj_source_file(case_dir + "/suboptimality_traj.csv"); + Eigen::RowVectorXd suboptimality_traj_mat = + teaser::test::readFileToEigenMatrix( + suboptimality_traj_source_file); + for (size_t i = 0; i < suboptimality_traj_mat.cols(); ++i) { + data.expected_outputs.certification_result.suboptimality_traj.push_back( + suboptimality_traj_mat(i)); + } + data.expected_outputs.certification_result.best_suboptimality = + suboptimality_traj_mat.minCoeff(); + data.expected_outputs.certification_result.is_optimal = true; + + small_instances_params_[c] = data; + } + } + + /** + * Helper function to load parameters for large problem instances + * + * Large instances are only used for testing the main certification function + */ + void setupLargeInstances() { + std::string root_dir = "./data/certification_large_instances/"; + auto cases = teaser::test::readSubdirs(root_dir); + for (const auto& c : cases) { + std::string case_dir = root_dir + c; + + CaseData data; + + // Inputs: + // scalar parameters + loadScalarParameters(case_dir + "/parameters.txt", &(data.inputs.params)); + + // v1: 3-by-N matrix + // These are the TIMs + std::ifstream v1_source_file(case_dir + "/v1.csv"); + data.inputs.v1 = + teaser::test::readFileToEigenMatrix(v1_source_file); + + // v2: 3-by-N matrix + // These are the TIMs + std::ifstream v2_source_file(case_dir + "/v2.csv"); + data.inputs.v2 = + teaser::test::readFileToEigenMatrix(v2_source_file); + + // q_est: estimated quaternion + std::ifstream q_source_file(case_dir + "/q_est.csv"); + auto q_mat = teaser::test::readFileToEigenFixedMatrix(q_source_file); + Eigen::Quaternion q(q_mat(3), q_mat(0), q_mat(1), q_mat(2)); + data.inputs.q_est = q; + + // R_est: estimated quaternion + std::ifstream R_est_source_file(case_dir + "/R_est.csv"); + data.inputs.R_est = teaser::test::readFileToEigenFixedMatrix(R_est_source_file); + + // theta_est: binary outlier vector + std::ifstream theta_source_file(case_dir + "/theta_est.csv"); + data.inputs.theta_est = + teaser::test::readFileToEigenMatrix(theta_source_file); + + // suboptimality: calculated suboptimality after 1st iteration + std::ifstream suboptimality_source_file(case_dir + "/suboptimality_1st_iter.csv"); + data.expected_outputs.suboptimality_1st_iter = + teaser::test::readFileToEigenFixedMatrix(suboptimality_source_file)(0); + + // certification_result: a struct holding certification results. Specifically: + // suboptimality_trajy: suboptimality gaps throughout all the iterations + // best_suboptimality: smallest suboptimality gap + std::ifstream suboptimality_traj_source_file(case_dir + "/suboptimality_traj.csv"); + Eigen::RowVectorXd suboptimality_traj_mat = + teaser::test::readFileToEigenMatrix( + suboptimality_traj_source_file); + for (size_t i = 0; i < suboptimality_traj_mat.cols(); ++i) { + data.expected_outputs.certification_result.suboptimality_traj.push_back( + suboptimality_traj_mat(i)); + } + data.expected_outputs.certification_result.best_suboptimality = + suboptimality_traj_mat.minCoeff(); + data.expected_outputs.certification_result.is_optimal = true; + + large_instances_params_[c] = data; + } + } + + void SetUp() override { + // load case parameters for small instances + setupSmallInstances(); + + // load case parameters for large instances + setupLargeInstances(); + } + + /** + * Helper function to run a provided function over a dictionary of case data + * @tparam Functor + * @param functor + */ + template + void testThroughCases(std::string test_case_name, Functor functor, + const std::map& case_params) { + // get all case names + std::string ptr_str = "Timing info for test case: " + test_case_name; + std::string div_str(ptr_str.size(), '='); + std::cout << ptr_str << std::endl; + std::cout << div_str << std::endl; + for (auto const& kv : case_params) { + const auto& case_name = kv.first; + std::chrono::steady_clock clock; + auto t1 = clock.now(); + functor(kv.second); + auto t2 = clock.now(); + std::chrono::duration diff = t2 - t1; + std::cout << "\nN=" << kv.second.inputs.v1.cols() << " | Test took " + << static_cast(diff.count()) / 1000.0 << "seconds." << std::endl; + } + std::cout << div_str << std::endl; + } + + // parameters per case + std::map small_instances_params_; + std::map large_instances_params_; +}; + +TEST_F(DRSCertifierTest, GetOmega1) { + auto test_run = [](CaseData case_data) { + const auto& expected_output = case_data.expected_outputs.omega; + + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + // perform the computation + Eigen::Matrix4d actual_output = certifier.getOmega1(case_data.inputs.q_est); + ASSERT_TRUE(actual_output.isApprox(expected_output)) + << "Actual output: " << actual_output << "Expected output: " << expected_output; + }; + + testThroughCases(test_info_->name(), test_run, small_instances_params_); +} + +TEST_F(DRSCertifierTest, GetBlockDiagOmega) { + auto test_run = [](CaseData case_data) { + // Case 1: N=10 + const auto& expected_output = case_data.expected_outputs.block_diag_omega; + + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + // perform the computation + Eigen::MatrixXd actual_output; + int Npm = (case_data.inputs.v1.cols() + 1) * 4; + certifier.getBlockDiagOmega(Npm, case_data.inputs.q_est, &actual_output); + ASSERT_TRUE(actual_output.isApprox(expected_output)) + << "Actual output: " << actual_output << "Expected output: " << expected_output; + }; + + testThroughCases(test_info_->name(), test_run, small_instances_params_); +} + +TEST_F(DRSCertifierTest, GetQCost) { + auto test_run = [](CaseData case_data) { + const auto& expected_output = case_data.expected_outputs.Q_cost; + + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + // perform the computation + Eigen::MatrixXd actual_output; + certifier.getQCost(case_data.inputs.v1, case_data.inputs.v2, &actual_output); + ASSERT_TRUE(actual_output.isApprox(expected_output)) + << "Actual output: " << actual_output << "Expected output: " << expected_output; + }; + + testThroughCases(test_info_->name(), test_run, small_instances_params_); +} + +TEST_F(DRSCertifierTest, GetLambdaGuess) { + auto test_run = [](CaseData case_data) { + const auto& expected_output = case_data.expected_outputs.lambda_guess; + + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + teaser::SparseMatrix actual_output; + certifier.getLambdaGuess(case_data.inputs.R_est, case_data.inputs.theta_est, + case_data.inputs.v1, case_data.inputs.v2, &actual_output); + + ASSERT_TRUE(actual_output.isApprox(expected_output)) + << "Actual output: " << actual_output << "Expected output: " << expected_output; + }; + + testThroughCases(test_info_->name(), test_run, small_instances_params_); +} + +TEST_F(DRSCertifierTest, GetLinearProjection) { + auto test_run = [](CaseData case_data) { + const auto& expected_output = case_data.expected_outputs.A_inv; + + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + Eigen::Matrix theta_prepended(1, + case_data.inputs.theta_est.cols() + 1); + theta_prepended << 1, case_data.inputs.theta_est; + ASSERT_TRUE(theta_prepended.rows() == 1); + ASSERT_TRUE(theta_prepended.cols() > 0); + + teaser::SparseMatrix actual_output; + certifier.getLinearProjection(theta_prepended, &actual_output); + + ASSERT_TRUE(actual_output.isApprox(expected_output)) + << "Actual output: " << actual_output << "Expected output: " << expected_output; + }; + + testThroughCases(test_info_->name(), test_run, small_instances_params_); +} + +TEST_F(DRSCertifierTest, GetOptimalDualProjection) { + auto test_run = [](CaseData case_data) { + // prepare parameters + // theta prepended + Eigen::Matrix theta_prepended(1, + case_data.inputs.theta_est.cols() + 1); + theta_prepended << 1, case_data.inputs.theta_est; + ASSERT_TRUE(theta_prepended.rows() == 1); + ASSERT_TRUE(theta_prepended.cols() > 0); + + // A_inv + teaser::SparseMatrix A_inv_sparse = case_data.expected_outputs.A_inv.sparseView(); + + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + Eigen::MatrixXd actual_output; + certifier.getOptimalDualProjection(case_data.inputs.W, theta_prepended, A_inv_sparse, + &actual_output); + + const auto& expected_output = case_data.expected_outputs.W_dual; + for (size_t col = 0; col < expected_output.cols(); ++col) { + for (size_t row = 0; row < expected_output.rows(); ++row) { + if (std::abs(actual_output(row, col) - expected_output(row, col)) > ACCEPTABLE_ERROR) { + std::cout << "Row: " << row << " Col: " << col << " Value: " << actual_output(row, col) + << " Expected: " << expected_output(row, col) << std::endl; + } + } + } + ASSERT_TRUE(actual_output.isApprox(expected_output)) + << "Actual output: " << actual_output << "Expected output: " << expected_output; + }; + + testThroughCases(test_info_->name(), test_run, small_instances_params_); +} + +TEST_F(DRSCertifierTest, ComputeSubOptimalityGap) { + auto test_run = [](CaseData case_data) { + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + double actual_output = certifier.computeSubOptimalityGap( + case_data.inputs.M_affine, case_data.inputs.mu, case_data.inputs.v1.cols()); + const auto& expected_output = case_data.expected_outputs.suboptimality_1st_iter; + + ASSERT_TRUE(std::abs(actual_output - expected_output) < ACCEPTABLE_ERROR); + }; + + testThroughCases(test_info_->name(), test_run, small_instances_params_); +} + +TEST_F(DRSCertifierTest, Certify) { + auto test_run = [&](CaseData case_data) { + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + auto actual_output = certifier.certify(case_data.inputs.R_est, case_data.inputs.v1, + case_data.inputs.v2, case_data.inputs.theta_est); + + compareCertificationResult(actual_output, case_data.expected_outputs.certification_result); + }; + + testThroughCases(test_info_->name(), test_run, small_instances_params_); +} + +TEST_F(DRSCertifierTest, LargeInstance) { + auto test_run = [&](CaseData case_data) { + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + auto actual_output = certifier.certify(case_data.inputs.R_est, case_data.inputs.v1, + case_data.inputs.v2, case_data.inputs.theta_est); + + compareCertificationResult(actual_output, case_data.expected_outputs.certification_result); + }; + + testThroughCases(test_info_->name(), test_run, large_instances_params_); +} + +TEST_F(DRSCertifierTest, Random100Points) { + // generate 3 random large problem instances + std::map random_instances_params; + int num_tests = 5; + int N = 100; + + for (size_t i = 0; i < num_tests; ++i) { + std::string case_name = "Random100-" + std::to_string(i) + "-" + std::to_string(N); + + CaseData data; + + // Inputs: + // scalar parameters + data.inputs.params.cbar2 = 1; + data.inputs.params.noise_bound = 0.01; + + // generate random vectors and transformations + data.inputs.v1 = Eigen::Matrix::Random(3, N); + data.inputs.q_est = Eigen::Quaternion::UnitRandom(); + data.inputs.R_est = data.inputs.q_est.toRotationMatrix(); + data.inputs.theta_est = Eigen::Matrix::Ones(1, N); + + // calculate vectors after transformation + // noise bounded by 0.01 + Eigen::Matrix noise = + (Eigen::Matrix::Random(3, N).array() + 1) / 200.0; + data.inputs.v2 = data.inputs.R_est * data.inputs.v1; + + // outliers + double outlier_ratio = 0.1; + int outlier_start_idx = (int)(N * (1 - outlier_ratio)); + for (size_t i = outlier_start_idx; i < N; ++i) { + data.inputs.v2.col(i) = Eigen::Matrix::Random(3, 1) * 5 + + Eigen::Matrix::Ones(3, 1) * 5; + data.inputs.theta_est(0, i) = -1; + } + + // expected outputs + data.expected_outputs.certification_result.is_optimal = true; + data.expected_outputs.certification_result.best_suboptimality = 1e-5; // a very small value + + random_instances_params[case_name] = data; + } + + auto test_run = [](CaseData case_data) { + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + auto actual_output = certifier.certify(case_data.inputs.R_est, case_data.inputs.v1, + case_data.inputs.v2, case_data.inputs.theta_est); + const auto& expected_output = case_data.expected_outputs.certification_result; + + ASSERT_TRUE(expected_output.is_optimal == actual_output.is_optimal); + ASSERT_TRUE(expected_output.best_suboptimality >= actual_output.best_suboptimality); + }; + + testThroughCases(test_info_->name(), test_run, random_instances_params); +} + +TEST_F(DRSCertifierTest, RandomLargeInstsances) { + // generate 3 random large problem instances + std::map random_instances_params; + std::array problem_sizes = {200, 300, 400}; + + for (size_t i = 0; i < problem_sizes.size(); ++i) { + + int N = problem_sizes.at(i); + std::string case_name = "Random-" + std::to_string(N); + + CaseData data; + + // Inputs: + // scalar parameters + data.inputs.params.cbar2 = 1; + data.inputs.params.noise_bound = 0.01; + + // generate random vectors and transformations + data.inputs.v1 = Eigen::Matrix::Random(3, N); + data.inputs.q_est = Eigen::Quaternion::UnitRandom(); + data.inputs.R_est = data.inputs.q_est.toRotationMatrix(); + data.inputs.theta_est = Eigen::Matrix::Ones(1, N); + + // calculate vectors after transformation + // noise bounded by 0.01 + Eigen::Matrix noise = + (Eigen::Matrix::Random(3, N).array() + 1) / 200.0; + data.inputs.v2 = data.inputs.R_est * data.inputs.v1; + + // outliers + double outlier_ratio = 0.1; + int outlier_start_idx = (int)(N * (1 - outlier_ratio)); + for (size_t i = outlier_start_idx; i < N; ++i) { + data.inputs.v2.col(i) = Eigen::Matrix::Random(3, 1) * 5 + + Eigen::Matrix::Ones(3, 1) * 5; + data.inputs.theta_est(0, i) = -1; + } + + // expected outputs + data.expected_outputs.certification_result.is_optimal = true; + data.expected_outputs.certification_result.best_suboptimality = 1e-5; // a very small value + + random_instances_params[case_name] = data; + } + + auto test_run = [](CaseData case_data) { + // construct the certifier + teaser::DRSCertifier certifier(case_data.inputs.params); + + auto actual_output = certifier.certify(case_data.inputs.R_est, case_data.inputs.v1, + case_data.inputs.v2, case_data.inputs.theta_est); + const auto& expected_output = case_data.expected_outputs.certification_result; + + ASSERT_TRUE(expected_output.is_optimal == actual_output.is_optimal); + ASSERT_TRUE(expected_output.best_suboptimality >= actual_output.best_suboptimality); + }; + + testThroughCases(test_info_->name(), test_run, random_instances_params); +} diff --git a/test/teaser/data/certification_large_instances/case_1/R_est.csv b/test/teaser/data/certification_large_instances/case_1/R_est.csv new file mode 100644 index 0000000..b87cb28 --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/R_est.csv @@ -0,0 +1,3 @@ +0.50482929785442,-0.54734171813878,-0.667506122528252 +-0.783235047215238,0.0346419836489219,-0.620759851941645 +0.362891500095493,0.83619194958679,-0.411208928167527 diff --git a/test/teaser/data/certification_large_instances/case_1/R_gt.csv b/test/teaser/data/certification_large_instances/case_1/R_gt.csv new file mode 100644 index 0000000..98ab618 --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/R_gt.csv @@ -0,0 +1,3 @@ +0.506779622381174,-0.545675870510777,-0.667392132618823 +-0.782124002441378,0.0345670081593479,-0.622163295889424 +0.362569247378035,0.83728308611199,-0.409268340537731 diff --git a/test/teaser/data/certification_large_instances/case_1/parameters.txt b/test/teaser/data/certification_large_instances/case_1/parameters.txt new file mode 100644 index 0000000..b6b20a2 --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/parameters.txt @@ -0,0 +1,3 @@ +cbar2: 1 +noise_bound: 4.594291399787397e-02 +max_iterations: 200 \ No newline at end of file diff --git a/test/teaser/data/certification_large_instances/case_1/q_est.csv b/test/teaser/data/certification_large_instances/case_1/q_est.csv new file mode 100644 index 0000000..894297a --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/q_est.csv @@ -0,0 +1,4 @@ +0.685819991392243 +-0.485031342791894 +-0.111040297110025 +0.53109847329281 diff --git a/test/teaser/data/certification_large_instances/case_1/q_gt.csv b/test/teaser/data/certification_large_instances/case_1/q_gt.csv new file mode 100644 index 0000000..8df9fa9 --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/q_gt.csv @@ -0,0 +1,4 @@ +0.685835431200437 +-0.484008193710578 +-0.111113713062056 +0.531995838800171 diff --git a/test/teaser/data/certification_large_instances/case_1/suboptimality_1st_iter.csv b/test/teaser/data/certification_large_instances/case_1/suboptimality_1st_iter.csv new file mode 100644 index 0000000..7ec5177 --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/suboptimality_1st_iter.csv @@ -0,0 +1 @@ +1.51158490235121e-12 diff --git a/test/teaser/data/certification_large_instances/case_1/suboptimality_traj.csv b/test/teaser/data/certification_large_instances/case_1/suboptimality_traj.csv new file mode 100644 index 0000000..655d3d9 --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/suboptimality_traj.csv @@ -0,0 +1 @@ +14.6053739872719,9.86671303692165,6.58715965819189,5.43105682442151,6.32535999985247,5.86433999957475,3.84080925526463,1.84169843521194,2.11987499904277,2.50152782237698,1.99351097953856,0.970743744057637,0.670508833481119,0.856459310265172,1.06495473385722,0.40896911146884,0.070023774079736,0.0838379083491256,0.163375231613332,1.51158490235121e-12 diff --git a/test/teaser/data/certification_large_instances/case_1/theta_est.csv b/test/teaser/data/certification_large_instances/case_1/theta_est.csv new file mode 100644 index 0000000..64a8cf8 --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/theta_est.csv @@ -0,0 +1 @@ +1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1 diff --git a/test/teaser/data/certification_large_instances/case_1/theta_gt.csv b/test/teaser/data/certification_large_instances/case_1/theta_gt.csv new file mode 100644 index 0000000..64a8cf8 --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/theta_gt.csv @@ -0,0 +1 @@ +1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1 diff --git a/test/teaser/data/certification_large_instances/case_1/v1.csv b/test/teaser/data/certification_large_instances/case_1/v1.csv new file mode 100644 index 0000000..511045e --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_1/v1.csv @@ -0,0 +1,3 @@ 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diff --git a/test/teaser/data/certification_large_instances/case_2/R_est.csv b/test/teaser/data/certification_large_instances/case_2/R_est.csv new file mode 100644 index 0000000..fdb5e67 --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_2/R_est.csv @@ -0,0 +1,3 @@ +0.999411166034707,-0.011336262404173,-0.0323853417436278 +0.0139697706058434,0.996510905505688,0.0822852399732492 +0.0313395391537265,-0.082689203424261,0.996082491023055 diff --git a/test/teaser/data/certification_large_instances/case_2/parameters.txt b/test/teaser/data/certification_large_instances/case_2/parameters.txt new file mode 100644 index 0000000..f4984be --- /dev/null +++ b/test/teaser/data/certification_large_instances/case_2/parameters.txt @@ -0,0 +1,3 @@ +cbar2: 1 +noise_bound: 0.2 +max_iterations: 1000 \ No newline at end of file diff --git a/test/teaser/data/certification_large_instances/case_2/q_est.csv b/test/teaser/data/certification_large_instances/case_2/q_est.csv new file mode 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diff --git a/test/teaser/data/certification_small_instances/case_3/M_affine_1st_iter.csv b/test/teaser/data/certification_small_instances/case_3/M_affine_1st_iter.csv new file mode 100644 index 0000000..bab1b68 --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/M_affine_1st_iter.csv @@ -0,0 +1,84 @@ 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diff --git a/test/teaser/data/certification_small_instances/case_3/W_dual_1st_iter.csv b/test/teaser/data/certification_small_instances/case_3/W_dual_1st_iter.csv new file mode 100644 index 0000000..0940cc7 --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/W_dual_1st_iter.csv @@ -0,0 +1,84 @@ 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a/test/teaser/data/certification_small_instances/case_3/mu.csv b/test/teaser/data/certification_small_instances/case_3/mu.csv new file mode 100644 index 0000000..0fe49e2 --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/mu.csv @@ -0,0 +1 @@ +0.00848225483512502 diff --git a/test/teaser/data/certification_small_instances/case_3/omega.csv b/test/teaser/data/certification_small_instances/case_3/omega.csv new file mode 100644 index 0000000..4139a8b --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/omega.csv @@ -0,0 +1,4 @@ +0.0825022946958976,0.165521054624461,0.0943329023725867,-0.978211355166092 +-0.165521054624461,0.0825022946958976,0.978211355166092,0.0943329023725867 +-0.0943329023725867,-0.978211355166092,0.0825022946958976,-0.165521054624461 +0.978211355166092,-0.0943329023725867,0.165521054624461,0.0825022946958976 diff --git a/test/teaser/data/certification_small_instances/case_3/parameters.txt b/test/teaser/data/certification_small_instances/case_3/parameters.txt new file mode 100644 index 0000000..4012703 --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/parameters.txt @@ -0,0 +1,2 @@ +cbar2: 1 +noise_bound: 4.594291399787397e-02 \ No newline at end of file diff --git a/test/teaser/data/certification_small_instances/case_3/q_est.csv b/test/teaser/data/certification_small_instances/case_3/q_est.csv new file mode 100644 index 0000000..e38b090 --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/q_est.csv @@ -0,0 +1,4 @@ +-0.978211355166092 +0.0943329023725867 +-0.165521054624461 +0.0825022946958976 diff --git a/test/teaser/data/certification_small_instances/case_3/q_gt.csv b/test/teaser/data/certification_small_instances/case_3/q_gt.csv new file mode 100644 index 0000000..cee549b --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/q_gt.csv @@ -0,0 +1,4 @@ +-0.977944536652211 +0.0961142698562179 +-0.166357040551256 +0.0819259752528249 diff --git a/test/teaser/data/certification_small_instances/case_3/suboptimality_1st_iter.csv b/test/teaser/data/certification_small_instances/case_3/suboptimality_1st_iter.csv new file mode 100644 index 0000000..cf2253f --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/suboptimality_1st_iter.csv @@ -0,0 +1 @@ +-3.21335802884993e-13 diff --git a/test/teaser/data/certification_small_instances/case_3/suboptimality_traj.csv b/test/teaser/data/certification_small_instances/case_3/suboptimality_traj.csv new file mode 100644 index 0000000..adcf52a --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/suboptimality_traj.csv @@ -0,0 +1 @@ +12.7612127398504,7.06454987174628,7.45851716180247,6.31601630073898,3.01869951744102,2.88532248935881,1.33893742797783,1.0408562635853,0.519864460497746,0.858944619185603,0.292123646898133,0.227197298651013,0.0373769198624004,0.0578715027125026,-3.21335802884993e-13 diff --git a/test/teaser/data/certification_small_instances/case_3/theta_est.csv b/test/teaser/data/certification_small_instances/case_3/theta_est.csv new file mode 100644 index 0000000..59fa896 --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/theta_est.csv @@ -0,0 +1 @@ +1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,-1,-1 diff --git a/test/teaser/data/certification_small_instances/case_3/theta_gt.csv b/test/teaser/data/certification_small_instances/case_3/theta_gt.csv new file mode 100644 index 0000000..59fa896 --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/theta_gt.csv @@ -0,0 +1 @@ +1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,-1,-1 diff --git a/test/teaser/data/certification_small_instances/case_3/v1.csv b/test/teaser/data/certification_small_instances/case_3/v1.csv new file mode 100644 index 0000000..964204f --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/v1.csv @@ -0,0 +1,3 @@ +0.644903701553992,0.0651242949102384,0.139048641435864,0.897966478128994,0.176415901793605,-0.567855391908567,0.872006479463973,-0.377963990433764,0.615805901939555,-0.270831842587248,-0.761811311402259,-0.496068317128393,-0.0189494854806353,0.563330759083531,-0.735406525765653,-0.380417616520509,-0.704787486099302,0.976163811509896,-0.45092393380398,-0.842827361944884 +-0.586422018953169,-0.705389165548628,-0.123058626316363,-0.162534212924033,0.351820931517281,-0.749926782222956,-0.141929767971582,-0.766898404624208,-0.1683590987994,-0.807142518331719,-0.278190777953119,-0.211609198872493,0.333114263758239,-0.802122144639097,-0.170703455388051,-0.490189205525012,0.192868803472107,-0.216093175919769,0.0735302952619377,-0.0160019868057752 +0.490110631805563,0.705822181104458,0.982609815646053,0.408948448812044,0.919292914005466,0.339337700801267,-0.468466264245762,-0.51866179627984,-0.769700139656909,-0.52456750580066,-0.585024287428657,-0.84210318351966,-0.94269602963035,-0.198137631332234,-0.655772500322995,-0.784217431473959,0.682697754562782,-0.0201978320465255,-0.889528471495677,-0.537946070136492 diff --git a/test/teaser/data/certification_small_instances/case_3/v2.csv b/test/teaser/data/certification_small_instances/case_3/v2.csv new file mode 100644 index 0000000..15c3119 --- /dev/null +++ b/test/teaser/data/certification_small_instances/case_3/v2.csv @@ -0,0 +1,3 @@ +0.870663082315099,0.397619930937858,0.487886366579575,1.00231792369423,0.421267365987978,-0.288062548929939,0.665358186700925,-0.396494021940422,0.326341462997093,-0.30801148583602,-0.853169250853982,-0.695830336957837,-0.396532884892458,0.578028196648829,-0.873296921933772,-0.530336793788791,-0.441191654734503,0.934642625504819,-0.349808137776097,0.111529488645101 +0.490970958197753,0.773167639180903,0.201150295855518,0.017928901805044,-0.24776563736413,0.886807370044406,-0.116627844429255,0.747930483589056,-0.0710703719564947,0.770404604996551,0.359626482230483,0.194794785175309,-0.438493612378807,0.623827817959291,0.235755593077656,0.447470935236667,0.0497246308369421,0.0321918820271026,0.902642309140275,-0.381890901226913 +-0.136131687274911,-0.514310165366978,-0.854171469879648,-0.0777410479421922,-0.863719973078909,-0.342845686267908,0.734611531946931,0.509971652914941,0.930538834663978,0.559833912407205,0.373777121044148,0.675541255694231,0.809776858338789,0.519689804006203,0.4216255118179,0.690554712139584,-0.890852922086189,0.358332942964078,-0.250741158359635,-0.917453275498354 diff --git a/test/teaser/graph-test.cc b/test/teaser/graph-test.cc index fdc0400..f4ca854 100644 --- a/test/teaser/graph-test.cc +++ b/test/teaser/graph-test.cc @@ -252,6 +252,12 @@ TEST(PMCTest, FindMaximumClique3) { } EXPECT_GE(in.ub, in.lb); + // for isolated vertices, pmc has lb = 0, which will + // cause a potential segfault in search dense function + if (in.lb == 0) { + in.lb += 1; + } + if (G.num_vertices() < in.adj_limit) { G.create_adj(); pmc::pmcx_maxclique finder(G, in); diff --git a/test/teaser/linalg-test.cc b/test/teaser/linalg-test.cc new file mode 100644 index 0000000..19af286 --- /dev/null +++ b/test/teaser/linalg-test.cc @@ -0,0 +1,242 @@ +/** + * Copyright 2020, Massachusetts Institute of Technology, + * Cambridge, MA 02139 + * All Rights Reserved + * Authors: Jingnan Shi, et al. (see THANKS for the full author list) + * See LICENSE for the license information + */ + +#include "gtest/gtest.h" +#include "gmock/gmock.h" +#include +#include + +#include + +#include "teaser/linalg.h" + +TEST(LinalgTest, HatMap) { + { + // all zeros + Eigen::Matrix v1; + v1 << 0, 0, 0; + Eigen::Matrix3d exp; + exp.setZero(); + const auto act = teaser::hatmap(v1); + ASSERT_TRUE(act.isApprox(exp)); + } + { + // non-zero cases + Eigen::Matrix v1; + v1 << 1, 2, 3; + Eigen::Matrix3d exp; + // clang-format off + exp << 0, -3, 2, + 3, 0,-1, + -2, 1, 0; + // clang-format on + const auto act = teaser::hatmap(v1); + ASSERT_TRUE(act.isApprox(exp)); + } + { + // negative + Eigen::Matrix v1; + v1 << 0, 2, -3; + Eigen::Matrix3d exp; + // clang-format off + exp << 0, 3, 2, + -3, 0, 0, + -2, 0, 0; + // clang-format on + const auto act = teaser::hatmap(v1); + ASSERT_TRUE(act.isApprox(exp)); + } +} + +TEST(LinalgTest, VectorKronFixedSize) { + { + // a simple case + Eigen::Matrix v1; + v1 << 1, 1, 1; + Eigen::Matrix v2; + v2 << 1, 1, 1; + Eigen::Matrix exp = Eigen::Matrix::Ones(9, 1); + + // compute the actual result + Eigen::Matrix act; + teaser::vectorKron(v1, v2, &act); + ASSERT_TRUE(act.isApprox(exp)); + } + { + // non-zero vectors + Eigen::Matrix v1; + v1 << 1, 4; + Eigen::Matrix v2; + v2 << 3, 2; + Eigen::Matrix exp; + exp << 3, 2, 12, 8; + + // compute the actual result + Eigen::Matrix act; + teaser::vectorKron(v1, v2, &act); + ASSERT_TRUE(act.isApprox(exp)); + } + { + // different lengths + Eigen::Matrix v1; + v1 << 1, -3, 3; + Eigen::Matrix v2; + v2 << 3, -1, 9, -10; + Eigen::Matrix exp; + exp << 3, -1, 9, -10, -9, 3, -27, 30, 9, -3, 27, -30; + + // compute the actual result + Eigen::Matrix act; + teaser::vectorKron(v1, v2, &act); + ASSERT_TRUE(act.isApprox(exp)); + } + { + // different lengths (all zero) + Eigen::Matrix v1; + v1 << 0, 0, 0; + Eigen::Matrix v2; + v2 << 3, -1, 9, -10; + Eigen::Matrix exp; + exp.setZero(); + + // compute the actual result + Eigen::Matrix act; + teaser::vectorKron(v1, v2, &act); + ASSERT_TRUE(act.isApprox(exp)); + } +} + +TEST(LinalgTest, VectorKronDynamicSize) { + { + // a simple case + Eigen::VectorXd v1(3, 1); + v1 << 1, 1, 1; + Eigen::VectorXd v2(3, 1); + v2 << 1, 1, 1; + Eigen::VectorXd exp(9, 1); + exp.setOnes(); + + // compute the actual result + Eigen::VectorXd act = teaser::vectorKron(v1, v2); + ASSERT_TRUE(act.isApprox(exp)); + } + { + // non-zero vectors + Eigen::VectorXd v1(2, 1); + v1 << 1, 4; + Eigen::VectorXd v2(2, 1); + v2 << 3, 2; + Eigen::VectorXd exp(4, 1); + exp << 3, 2, 12, 8; + + // compute the actual result + Eigen::VectorXd act = teaser::vectorKron(v1, v2); + ASSERT_TRUE(act.isApprox(exp)); + } + { + // different lengths + Eigen::VectorXd v1(3, 1); + v1 << 1, -3, 3; + Eigen::VectorXd v2(4, 1); + v2 << 3, -1, 9, -10; + Eigen::VectorXd exp(12, 1); + exp << 3, -1, 9, -10, -9, 3, -27, 30, 9, -3, 27, -30; + + // compute the actual result + Eigen::VectorXd act = teaser::vectorKron(v1, v2); + ASSERT_TRUE(act.isApprox(exp)); + } + { + // different lengths (all zero) + Eigen::VectorXd v1(3, 1); + v1 << 0, 0, 0; + Eigen::VectorXd v2(4, 1); + v2 << 3, -1, 9, -10; + Eigen::VectorXd exp(12, 1); + exp.setZero(); + + // compute the actual result + Eigen::VectorXd act = teaser::vectorKron(v1, v2); + ASSERT_TRUE(act.isApprox(exp)); + } +} + +TEST(LinalgTest, GetNearestPSDRandom) { + // random psd matrix + size_t trials = 5; + int MAX_SIZE = 500; + int MIN_SIZE = 100; + std::default_random_engine generator; + std::uniform_int_distribution size_distribution(MIN_SIZE, MAX_SIZE); + + for (size_t i = 0; i < trials; ++i) { + int size = size_distribution(generator); + Eigen::MatrixXd rand_mat = Eigen::MatrixXd::Random(size, size); + // should be a PSD matrix + Eigen::MatrixXd A = rand_mat * rand_mat.transpose(); + Eigen::MatrixXd exp_PSD = A; + Eigen::MatrixXd act_PSD; + teaser::getNearestPSD(A, &act_PSD); + ASSERT_TRUE(act_PSD.isApprox(exp_PSD)); + } +} + +TEST(LinalgTest, GetNearestPSDSimple) { + { + // identity + Eigen::MatrixXd A = Eigen::MatrixXd::Identity(5, 5); + Eigen::MatrixXd exp_PSD = A; + Eigen::MatrixXd act_PSD; + teaser::getNearestPSD(A, &act_PSD); + + std::cout << "Expected: " << exp_PSD << std::endl; + std::cout << "Actual: " << act_PSD << std::endl; + + ASSERT_TRUE(act_PSD.isApprox(exp_PSD)); + } + { + // another simple example + Eigen::MatrixXd A(2, 2); + A << 1, -1, -1, 1; + Eigen::MatrixXd exp_PSD = A; + Eigen::MatrixXd act_PSD; + teaser::getNearestPSD(A, &act_PSD); + + std::cout << "Expected: " << exp_PSD << std::endl; + std::cout << "Actual: " << act_PSD << std::endl; + + ASSERT_TRUE(act_PSD.isApprox(exp_PSD)); + } + { + // a more difficult case + Eigen::MatrixXd A(5, 5); + // clang-format off + A << 4.985750134559297e-02, 6.013987552528092e-01, 6.534568239799645e-01, 2.989641634571971e-01, 9.833730174463773e-02, + 5.458862088908298e-01, 7.896204651230384e-01, 4.896553453284711e-01, 2.561097810618381e-01, 8.595934534752724e-01, + 9.431698396554787e-01, 7.991850350443156e-01, 9.728522370108029e-01, 8.865637944115470e-01, 2.762900816117508e-02, + 3.214730698699890e-01, 4.956476557821099e-02, 7.484899099770820e-01, 4.468008627828005e-01, 8.991564342563644e-01, + 8.064668037933336e-01, 2.831986338409456e-01, 5.678411497388073e-01, 8.159872532962074e-01, 8.999355005261755e-01; + // clang-format on + Eigen::MatrixXd exp_PSD(5, 5); + // clang-format off + exp_PSD << 4.066470610623304e-01, 5.058983010895730e-01, 6.286981536486869e-01, 3.710481485062439e-01, 3.824610939303472e-01, + 5.058983010895730e-01, 8.624505164355950e-01, 6.061105353450932e-01, 2.624371560274579e-01, 5.037336021002040e-01, + 6.286981536486869e-01, 6.061105353450932e-01, 1.136403337757137e+00, 6.461507810773540e-01, 4.261633102468473e-01, + 3.710481485062439e-01, 2.624371560274579e-01, 6.461507810773540e-01, 7.019256648504395e-01, 6.821231201538008e-01, + 3.824610939303472e-01, 5.037336021002040e-01, 4.261633102468473e-01, 6.821231201538008e-01, 1.022899463404716e+00; + // clang-format on + + Eigen::MatrixXd act_PSD; + teaser::getNearestPSD(A, &act_PSD); + + std::cout << "Expected: " << exp_PSD << std::endl; + std::cout << "Actual: " << act_PSD << std::endl; + + ASSERT_TRUE(act_PSD.isApprox(exp_PSD)); + } +} diff --git a/test/teaser/registration-test.cc b/test/teaser/registration-test.cc index d7ce014..6319449 100644 --- a/test/teaser/registration-test.cc +++ b/test/teaser/registration-test.cc @@ -289,6 +289,18 @@ TEST(RegistrationTest, SolveRegistrationProblemDecoupled) { EXPECT_TRUE(expected_scale_inliers(0, i) == actual_scale_inliers(0, i)); } **/ + + // rotation inlier mask and rotation inliers consistency + const auto actual_rotation_inlier_mask = solver.getRotationInliersMask(); + const auto actual_rotation_inliers = solver.getRotationInliers(); + int count = 0; + for (size_t i = 0; i < actual_rotation_inlier_mask.cols(); ++i) { + if (actual_rotation_inlier_mask[i]) { + count++; + } + } + EXPECT_EQ(count, actual_rotation_inliers.size()); + EXPECT_NEAR(expected_solution, actual_solution.scale, 0.0001); EXPECT_LE(teaser::test::getAngularError(expected_rotation_solution, actual_solution.rotation), 0.2); @@ -361,8 +373,7 @@ TEST(RegistrationTest, OutlierDetection) { EXPECT_LE(teaser::test::getAngularError(T.topLeftCorner(3, 3), solution.rotation), 0.2); EXPECT_LE((T.topRightCorner(3, 1) - solution.translation).norm(), 0.1); - auto max_clique = solver.getInlierMaxClique(); - auto final_inliers = solver.getTranslationInliers(); + auto final_inliers = solver.getInlierMaxClique(); EXPECT_EQ(expected_inliers.size(), final_inliers.size()); std::sort(expected_inliers.begin(), expected_inliers.end()); diff --git a/test/test-tools/test_utils.h b/test/test-tools/test_utils.h index 4ee6895..878442a 100644 --- a/test/test-tools/test_utils.h +++ b/test/test-tools/test_utils.h @@ -11,6 +11,7 @@ #include #include #include +#include #include @@ -94,12 +95,41 @@ inline double getAngularError(Eigen::Matrix3d R_exp, Eigen::Matrix3d R_est) { template inline Eigen::Matrix teaserPointCloudToEigenMatrix(PointCloud cloud) { - Eigen::Matrix mat(3, cloud.size()); + Eigen::Matrix mat(3, cloud.size()); for (size_t i = 0; i < cloud.size(); ++i) { mat.col(i) << cloud[i].x, cloud[i].y, cloud[i].z; } return mat; } +/** + * Get immediate subdirectories' names as strings in a vector + * @param path path to the root directory + * @return a vector containing names of the immediate subdirectories + */ +inline std::vector readSubdirs(std::string path) { + // output vector + std::vector subdirs; + + // open the root directory + DIR* root_dir = opendir(path.c_str()); + if (root_dir == NULL) { + std::cerr << "Could not open given directory: " << path << std::endl; + return subdirs; + } + + struct dirent* root_dir_ptr; + while ((root_dir_ptr = readdir(root_dir)) != NULL) { + if (root_dir_ptr->d_type == DT_DIR) { + if (std::strcmp(root_dir_ptr->d_name, ".") != 0 & + std::strcmp(root_dir_ptr->d_name, "..") != 0) { + subdirs.emplace_back(root_dir_ptr->d_name); + } + } + } + closedir(root_dir); + return subdirs; +} + } // namespace test -} \ No newline at end of file +} // namespace teaser \ No newline at end of file