Installation guideΒΆ

C++ supported compilers:

gcc version

clang version

msvc version

The DNetPRO project is written in C++ and it supports also older standard versions (std=c++1+). The package installation can be performed via [CMake](https://github.com/Nico-Curti/DNetPRO/blob/master/CMakeLists.txt). The CMake installer provides also a DNetPRO.pc, useful if you want link to the DNetPRO using pkg-config.

You can also use the DNetPRO package in Python using the Cython wrap provided inside this project. The only requirements are the following:

  • numpy >= 1.16.0

  • networkx >= 2.2

  • cython >= 0.29

  • scikit -learn >= 0.19.1

  • pandas >= 0.24.2

The Cython version can be built and installed via CMake enabling the -DPYWRAP variable. You can use also the DNetPRO package in Python using the Cython wrap provided inside this project. The Python wrap guarantees also a good integration with the other common Machine Learning tools provided by scikit-learn Python package; in this way you can use the DNetPRO algorithm as an equivalent alternative also in other pipelines. Like other Machine Learning algorithm also the DNetPRO one depends on many parameters, i.e its hyper-parameters, which has to be tuned according to the given problem. The Python wrap of the library was written according to scikit-optimize Python package to allow an easy hyper-parameters optimization using the already implemented classical methods.

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