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        "author": "Ben Bartlett",
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        "description": "# neuroptica [![Documentation Status](https://readthedocs.org/projects/neuroptica/badge/?version=latest)](https://neuroptica.readthedocs.io/en/latest/?badge=latest) [![Build Status](https://travis-ci.com/fancompute/neuroptica.svg?token=CSoUuvqmixfJpdwkLqet&branch=master)](https://travis-ci.com/fancompute/neuroptica)\n\n`neuroptica` is a flexible chip-level simulation platform for nanophotonic neural networks written in Python/NumPy. It provides a wide range of abstracton levels for simulating optical NN's: the lowest-level functionality allows you to manipulate the arrangement and properties of individual phase shifters on a simulated chip, and the highest-level features provide a Keras-like API for designing optical NN by stacking network layers.\n\n\n## Installation\n\nThe easiest way to get started with `neuroptica` is to install directly from the Python package manager:\n\n```\npip install neuroptica\n```\n\nAlternately, you can clone the repository source code and edit it as needed with \n\n```\ngit clone https://github.com/fancompute/neuroptica.git\n```\n\nand in your program or notebook, add\n\n```python\nimport sys\nsys.path.append('path/to/neuroptica')\n``` \n\n\n## Getting started\n\nFor an overview of `neuroptica`, read the [documentation](https://neuroptica.readthedocs.io). Example notebooks are included in the [`neuroptica-notebooks`](https://github.com/fancompute/neuroptica-notebooks) repository:\n\n- [Planar data classification using electro-optic activation functions](https://github.com/fancompute/neuroptica-notebooks/blob/master/neuroptica_demo.ipynb)\n\n![neuroptica training demo](https://raw.githubusercontent.com/fancompute/neuroptica/master/img/neuroptica_demo.gif)\n\n\n## Authors\n\n`neuroptica` was written by [Ben Bartlett](https://github.com/bencbartlett), [Momchil Minkov](https://github.com/momchilmm), [Tyler Hughes](https://github.com/twhughes), and  [Ian Williamson](https://github.com/ianwilliamson).\n\n\n",
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