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        "author": "Sebastian Liem",
        "author_email": "sebastian@liem.se",
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            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: ISC License (ISCL)",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Visualization"
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        "description": "=======\nbarrett\n=======\n\nbarrett is a software package meant to process and visualise the output of the nested sampling\nalgorithm MultiNest. There are several packages already on the market for this, but barrett's\nmain differential feature is out-of-core processing so the code can handle very large datasets.\n\nSpecific technologies: HDF5, and Python (h5py, scipy, numpy, matplotlib).\n\nUsage\n-----\n\nbarrett is split into four submodules:\n\n + barrett.data implements methods for modifying data (e.g. log, change units) or calculate\n   depended variables (e.g. mean squark mass)\n\n + barrett.posterior is for calculating and plot the one or two dimensional marginal\n   posterior distribution.\n\n + barrett.profilelikelihood is for calculating and plot the one or two dimensional profile\n   likelihood.\n\n + barrett.util contain various utility functions most notable convert_chain() which converts\n   the plain text MultiNest output to the HDF5 format used by barrett.\n\nAs for parallelisation; writing to the same hdf5 file is strongly discouraged. Reading the file\nis however perfectly fine. So posterior/profilelikelihood module is perfectly parallelisable.\nThe code itself is not parallelised, instead I recommend using Python's multiprocessing module to\nproducing several plots in parallell. In most system tested the plotting is CPU bound, your\nmileage may vary.\n\nInstallation\n------------\n\nBarrett is available on PyPI and can be installed using pip\n\n  pip install barrett\n\nCite\n----\nIf you use barrett in your research please cite arXiv:1608.00990:\n\n@article{2016arXiv160800990L,\n    author = {Liem, Sebastian},\n    title = \"{Barrett: out-of-core processing of MultiNest output}\",\n    archivePrefix = \"arXiv\",\n    eprint = {1608.00990},\n    primaryClass = \"stat.CO\",\n    year = 2016\n}\n\nExample\n-------\n\nPlease check the example directory for plot.py for an, you guessed it, example.\n\n\n\n",
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        "license": "ISC",
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        "name": "barrett",
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