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        "author": "Chris Mutel",
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            "License :: OSI Approved :: BSD License",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: Microsoft :: Windows",
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            "Programming Language :: Python",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Scientific/Engineering :: Mathematics"
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        "description": "The `stats_arrays` package provides a standard NumPy array interface for defining uncertain parameters used in models, and classes for Monte Carlo sampling. It also plays well with others.\n\n# Motivation\n\n* Want a consistent interface to SciPy and NumPy statistical function\n* Want to be able to quickly load and save many parameter uncertainty distribution definitions in a portable format\n* Want to manipulate and switch parameter uncertainty distributions and variables\n* Want simple Monte Carlo random number generators that return a vector of parameter values to be fed into uncertainty or sensitivity analysis\n* Want something simple, extensible, documented and tested\n\nThe `stats_arrays package was originally developed for the [Brightway2 life cycle assessment framework](http://brightwaylca.org/), but can be applied to any stochastic model.\n\n# Example\n\n```python\n\n>>> from stats_arrays import *\n>>> my_variables = UncertaintyBase.from_dicts(\n...     {'loc': 2, 'scale': 0.5, 'uncertainty_type': NormalUncertainty.id},\n...     {'loc': 1.5, 'minimum': 0, 'maximum': 10, 'uncertainty_type': TriangularUncertainty.id}\n... )\n>>> my_variables\narray([(2.0, 0.5, nan, nan, nan, False, 3),\n       (1.5, nan, nan, 0.0, 10.0, False, 5)],\n    dtype=[('loc', '<f8'), ('scale', '<f8'), ('shape', '<f8'),\n           ('minimum', '<f8'), ('maximum', '<f8'), ('negative', '?'),\n           ('uncertainty_type', 'u1')])\n>>> my_rng = MCRandomNumberGenerator(my_variables)\n>>> my_rng.next()\narray([ 2.74414022,  3.54748507])\n>>> # can also be used as an interator\n>>> zip(my_rng, xrange(10))\n[(array([ 2.96893108,  2.90654471]), 0),\n (array([ 2.31190619,  1.49471845]), 1),\n (array([ 3.02026168,  3.33696367]), 2),\n (array([ 2.04775418,  3.68356226]), 3),\n (array([ 2.61976694,  7.0149952 ]), 4),\n (array([ 1.79914025,  6.55264372]), 5),\n (array([ 2.2389968 ,  1.11165296]), 6),\n (array([ 1.69236527,  3.24463981]), 7),\n (array([ 1.77750176,  1.90119991]), 8),\n (array([ 2.32664152,  0.84490754]), 9)]\n\n```\n\n# More\n\n* Source code: https://bitbucket.org/cmutel/stats_arrays\n* Online documentation: https://stats_arrays.readthedocs.io/en/latest/\n\n\n",
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