About

Scientific methods on top of NP library.

Requirements

Any C++20-compatible compiler:

• gcc 10 or higher
• clang 6 or higher
• Visual Studio 2019 or higher

Repo

git clone https://github.com/mgorshkov/scipy.git

Build unit tests and sample

Linux/MacOS

mkdir build && cd build
cmake ..
cmake --build .

Windows

mkdir build && cd build
cmake ..
cmake --build . --config Release

Build docs

cmake --build . --target doc

Open scipy/build/doc/html/index.html in your browser.

Install

cmake .. -DCMAKE_INSTALL_PREFIX:PATH=~/scipy_install
cmake --build . --target install

Usage example (samples/stats)

#include <iostream>

#include <np/Creators.hpp>
#include <scipy/stats/mode.hpp>

int main(int, char **) {
    using namespace np;
    using namespace scipy;

    // Mode calculation
    Size size = 10000000;
    auto r = random::rand(size);
    auto m = stats::mode(r);
    std::cout << "mode=" << m.first << " " << m.second;
    return 0;
}

How to build the sample

1. Clone the repo

git clone https://github.com/mgorshkov/scipy.git

2. cd samples/stats

cd samples/stats

3. Make build dir

mkdir -p build-release && cd build-release

4. Configure cmake

cmake -DCMAKE_BUILD_TYPE=Release ..

5. Build

Linux/MacOS

cmake --build .

Windows

cmake --build . --config Release

6. Run the app

$./stats

Links

• C++ numpy-like template-based array implementation: https://github.com/mgorshkov/np
• Methods from pandas library on top of NP library: https://github.com/mgorshkov/pd
• ML Methods from scikit-learn library: https://github.com/mgorshkov/sklearn