![]() |
NumCpp
2.7.0
A Templatized Header Only C++ Implementation of the Python NumPy Library
|
NUMCPP_NO_USE_BOOST
: disables all NumCpp features that require the Boost libraries as a dependency. When this compiler flag is defined NumCpp will have no external dependancies and is completely standaloneNUMCPP_USE_MULTITHREAD
: enables STL parallel execution policies throughout the library. Using multi-threaded algorithms can have negative performace impact for "small" array operations and should usually only be used when dealing with large array operations. Benchmarking should be performed with your system and build tools to determine which works best for your setup and applicationNUMCPP_INCLUDE_PYBIND_PYTHON_INTERFACE
: includes the PyBind11 Python interface helper functionsNUMCPP_INCLUDE_BOOST_PYTHON_INTERFACE
: includes the Boost Python interface helper functions