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        "description": "[![Conda](https://anaconda.org/alartum/ncvis/badges/version.svg)](https://anaconda.org/alartum/ncvis)\n[![PyPI](https://img.shields.io/pypi/v/ncvis.svg)](https://pypi.python.org/pypi/ncvis/)\n[![GitHub](https://img.shields.io/github/license/alartum/ncvis.svg)](https://github.com/alartum/ncvis/blob/master/LICENSE)\n[![Build Status](https://travis-ci.com/alartum/ncvis.svg?branch=master)](https://travis-ci.com/alartum/ncvis)\n# ncvis\n\n**NCVis** is an efficient solution for data visualization. It uses [HNSW](https://github.com/nmslib/hnswlib) for fast nearest neighbors graph construction and a parallel approach for building the graph embedding.\n\n# Installation\n\n## Conda [recommended]\n\nYou do not need to setup the environment if using *conda*, all dependencies are installed automatically. \n```bash\n$ conda install -c alartum ncvis \n```\n\n## Pip\n\n**Important**: be sure to have a compiler with *OpenMP* support. *GCC* has it by default, wich is not the case with *clang*. You may need to install *llvm-openmp* library beforehand.  \n\n1. Install **numpy** and **cython** packages (compile-time dependencies):\n    ```bash\n    $ pip install numpy cython\n    ```\n2. Install **ncvis** package:\n    ```bash\n    $ pip install ncvis\n    ```\n\n## From source\n\n1. Install **numpy** and **cython** packages (compile-time dependencies):\n    ```bash\n    $ pip install numpy cython\n    ```\n2. Use Makefile, it will call *pip* for you\n    ```bash\n    $ make wrapper\n    ```\n# Using\n\n```python\nimport ncvis\n\nvis = ncvis.NCVis()\nY = vis.fit_transform(X)\n```\n\nA more detailed example can be found [here](https://github.com/alartum/ncvis-examples).",
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