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    "info": {
        "author": "Robert Langlois",
        "author_email": "rl2528@columbia.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Environment :: MacOS X",
            "Environment :: X11 Applications",
            "Intended Audience :: Developers",
            "Intended Audience :: End Users/Desktop",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License (GPL)",
            "Natural Language :: English",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: POSIX",
            "Operating System :: Unix",
            "Programming Language :: C",
            "Programming Language :: C++",
            "Programming Language :: Python",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Bio-Informatics",
            "Topic :: Scientific/Engineering :: Image Recognition"
        ],
        "description": "Arachnid\n========\n\nArachnid is an open source software package written primarily in Python that processes\nimages of macromolecules captured by cryo-electron microscopy (cryo-EM). Arachnid is\nfocused on automating the single-particle reconstruction workflow and can be thought \nof as two subpackages:\n\t\n#. Arachnid Prime\n\tA SciPy Toolkit (SciKit) that focuses on every step of the single-particle\n\treconstruction workflow up to orientation assignment and classification. This\n\ttoolkit also includes a set of application scripts and a workflow manager.\n\n#. pySPIDER\n\tThis subpackage functions as an interface to the SPIDER package. It includes\n\tboth a library of SPIDER commands and a set of application scripts to run\n\ta set of procedures for every step of single-particle reconstruction including\n\torientation assignment but not classification.\n\nArachnid Prime currently focuses on automating the pre-processing of the image \ndata captured by cryo-EM. For example, Arachnid has the following highlighted applications \nhandle the particle-picking problem:\n\n- AutoPicker: Automated reference-free particle selection\n\n- ViCer: Automated unsupervised particle verification\n\nThis software is under development by the `Frank Lab`_ and is licensed under \n`GPL 2.0 <http://www.arachnid.us/license.html>`_ or later.\n\nFor more information, see `http://www.arachnid.us <http://www.arachnid.us>`_.\n\nAlternatively, HTML documentation can be built locally using \n`python setup.py build_sphinx`, which assumes you have the prerequisite \nPython libraries. The documents can be found in `build/sphinx/html/`.\n\nHow to cite\n===========\n\nThe main reference to cite is:\n\n\n\tLanglois, R. E., Ho D. N., Frank, J., 2014. Arachnid: Automated \n\tImage-processing for Electron Microscopy. In Preparation.\n\nSee `CITE <http://www.arachnid.us/CITE.html>`_ for more information and downloadable citations.\n\nImportant links\n===============\n\n- Official source code repo: https://github.com/ezralanglois/arachnid\n- HTML documentation (stable release): http://www.arachnid.us/\n- Download releases: https://binstar.org/\n- Issue tracker: https://github.com/ezralanglois/arachnid/issues\n- Mailing list: http://groups.google.com/group/arachnid-general\n- Cite: http://www.arachnid.us/CITE.html\n\nDependencies\n============\n\nThe required dependencies to build the software are Python >= 2.6,\nsetuptools, Numpy >= 1.3, SciPy >= 0.7, matplotlib>=1.1.0, mpi4py>=1.2.2, \nscikit-learn, scikit-image, psutil, sqlalchemy, mysql-python, PIL, basemap,\nFFTW3 or MKL, and both C/C++ and Fortran compilers.\n\nIt is also recommended you install NumPy and SciPy with an optimized Blas\nlibrary such as MKL, ACML, ATLAS or GOTOBlas.\n\nTo build the documentation, Sphinx>=1.0.4 is required.\n\nAll of these dependencies can be found in a single free binary \npackage: `Anaconda`_.\n\nInstall\n=======\n\nThe prefered method of installation is to use Anaconda::\n\t\n\t# If you do not have Anaconda then run the following (assumes bash shell)\n\t\n\twget http://repo.continuum.io/miniconda/Miniconda-3.0.0-Linux-x86_64.sh\n\tsh Miniconda-3.0.0-Linux-x86_64.sh -b -p $PWD/anaconda\n\texport PATH=$PWD/anaconda/bin:$PATH\n\t\n\t# If you have anaconda or just installed it, then run\n\t\n\tconda install -c https://conda.binstar.org/ezralanglois arachnid\n\nAlternatives:\n\n\t# Install from downloaded source\n\t\n\t$ python setup.py install --prefix=$HOME\n\t\n\t# Using Setup tools\n\t\n\t$ easy_install arachnid\n\t\n\t# Using PIP\n\t\n\t$ pip install arachnid\n\t\n\t# Using Anaconda\n\t\n\t$ conda install -c https://conda.binstar.org/ezralanglois arachnid\n\nDevelopment\n===========\n\nYou can check out the latest source with the command::\n\t\n\tgit clone https://github.com/ezralanglois/arachnid/arachnid.git\n\n.. _`Frank Lab`: http://franklab.cpmc.columbia.edu/franklab/\n.. _`Anaconda`: https://store.continuum.io/",
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