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        "author": "Joakim Anden, Yoel Shkolnisky, Itay Sason, Robbie Brook, Vineet Bansal, Junchao Xia",
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            "Programming Language :: Python"
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        "description": "![Logo](http://spr.math.princeton.edu/sites/spr.math.princeton.edu/files/ASPIRE_1.jpg)\n\n[![Azure Build Status](https://dev.azure.com/vineetbansal0645/Aspire-Python/_apis/build/status/ComputationalCryoEM.ASPIRE-Python?branchName=master)](https://dev.azure.com/vineetbansal0645/Aspire-Python/_build/latest?definitionId=3&branchName=master)\n[![Travis Build Status](https://travis-ci.org/ComputationalCryoEM/ASPIRE-Python.svg?branch=master)](https://travis-ci.org/ComputationalCryoEM/ASPIRE-Python)\n[![Appveyor Build status](https://ci.appveyor.com/api/projects/status/ywgud2vu9ot330bq/branch/master?svg=true)](https://ci.appveyor.com/project/vineetbansal/aspire-python/branch/master)\n[![Coverage Status](https://coveralls.io/repos/github/ComputationalCryoEM/ASPIRE-Python/badge.svg?branch=master)](https://coveralls.io/github/ComputationalCryoEM/ASPIRE-Python?branch=master)\n[![Documentation Status](https://readthedocs.org/projects/aspire/badge/?version=latest)](https://aspire.readthedocs.io/en/latest/?badge=latest)\n\n# ASPIRE - Algorithms for Single Particle Reconstruction\n\nThis is the Python version to supersede the [Matlab ASPIRE](https://github.com/PrincetonUniversity/aspire). \n\nASPIRE is an open-source software package for processing single-particle cryo-EM data to determine three-dimensional structures of biological macromolecules. The package includes advanced algorithms based on rigorous mathematics and recent developments in\nstatistics and machine learning. It provides unique and improved solutions to important computational challenges of the cryo-EM\nprocessing pipeline, including 3-D *ab-initio* modeling, 2-D class averaging, automatic particle picking, and 3-D heterogeneity analysis.\n\n\n\n## Installation Instructions\n\nFor end-users\n-------------\n\nASPIRE is a pip-installable package that works on Linux/Mac/Windows, and requires Python 3.6. The simplest option is to use Anaconda 64-bit for your platform with a minimum of Python 3.6 and pip, and then use `pip` to install `aspire` in that environment.\n\n```\nconda create -n aspire_env python=3.6 pip\nconda activate aspire_env\npip install aspire\n```\n\nThe final step above should install any dependent packages from `pip` automatically.\n\nNote that this step installs the base `aspire` package for you to work with, but not the unit tests/scripts/documentation. If you need to install ASPIRE for development purposes, read on.\n\nFor developers\n--------------\n\nAfter cloning this repo, the simplest option is to use Anaconda 64-bit for your platform, and use the provided `environment.yml` file to build a Conda environment to run ASPIRE.\n\n```\ncd /path/to/git/clone/folder\nconda env create -f environment.yml\nconda activate aspire\n```\n\n### Make sure everything works\n\nOnce ASPIRE is installed, make sure the unit tests run correctly on your platform by doing:\n```\ncd /path/to/git/clone/folder\npython setup.py test\n```\n\nTests currently take around 2 minutes to run. If some tests fail, you may realize that `python setup.py test` produces too much information.\nYou may want to re-run tests using:\n```\ncd /path/to/git/clone/folder\nPYTHONPATH=./src pytest tests\n```\nThis provides a cleaner output to analyze.\n\n### Install\n\nIf the tests pass, install the ASPIRE package for the currently active Conda environment:\n```\ncd /path/to/git/clone/folder\npython setup.py install\n```",
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