最近需要把一些 python 版本的程序转为 c++ 的程序。 python 中使用了很多 numpy 的调用，于是就再找 c++ 的实现。 找了一圈下来，发现最适合的可能就是 xtensor。 github: https://github.com/xtensor-stack/xtensor 使用: https://xtensor.readthedocs.io/en/latest/numpy.html

其他可选：

    The GNU Scientific Library is a GPL software written in C. Thus, it has a C-like allocation and way of programming (pointers, etc.). With the GSLwrap, you can have a C++ way of programming, while still using the GSL. GSL has a BLAS implementation, but you can use ATLAS instead of the default CBLAS, if you want even more performances.

    The boost/uBLAS library is a BSL library, written in C++ and distributed as a boost package. It is a C++-way of implementing the BLAS standard. uBLAS comes with a few linear algebra functions, and there is an experimental binding to ATLAS.

    eigen is a linear algebra library written in C++, distributed under the MPL2 license (starting from version 3.1.1) or LGPL3/GPL2 (older versions). It's a C++ way of programming, but more integrated than the two others (more algorithms and data structures are available). Eigen claim to be faster than the BLAS implementations above, while not following the de-facto standard BLAS API. Eigen does not seem to put a lot of effort on parallel implementation.

    Armadillo is LGPL3 library for C++. It has binding for LAPACK (the library used by numpy). It uses recursive templates and template meta-programming, which is a good point (I don't know if other libraries are doing it also?).

    xtensor is a C++ library that is BSD licensed. It offers A C++ API very similar to that of NumPy. See https://xtensor.readthedocs.io/en/latest/numpy.html for a cheat sheet.

参考: https://stackoverflow.com/questions/11169418/numpy-style-arrays-for-c https://github.com/dpilger26/NumCpp