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liknorm-py\n\nLiknorm Python wrapper.\n\n## Install\n\nIt can be done via [pip](https://pypi.org/) or [conda](https://conda.io/).\n\n### Pip\n\n```bash\npip install liknorm\n```\n\n### Conda\n\n```bash\nconda install -c conda-forge liknorm-py\n```\n\n## Running the tests\n\nAfter installation, you can test it\n\n```bash\npython -c \"import liknorm; liknorm.test()\"\n```\n\nas long as you have [pytest](http://docs.pytest.org/en/latest/).\n\n## Example\n\n```python\n\u003e\u003e\u003e from numpy import empty\n\u003e\u003e\u003e from numpy.random import RandomState\n\u003e\u003e\u003e from liknorm import LikNormMachine\n\u003e\u003e\u003e\n\u003e\u003e\u003e machine = LikNormMachine('bernoulli')\n\u003e\u003e\u003e random = RandomState(0)\n\u003e\u003e\u003e outcome = random.randint(0, 2, 5)\n\u003e\u003e\u003e tau = random.rand(5)\n\u003e\u003e\u003e eta = random.randn(5) * tau\n\u003e\u003e\u003e\n\u003e\u003e\u003e log_zeroth = empty(5)\n\u003e\u003e\u003e mean = empty(5)\n\u003e\u003e\u003e variance = empty(5)\n\u003e\u003e\u003e\n\u003e\u003e\u003e moments = {'log_zeroth': log_zeroth, 'mean': mean, 'variance': variance}\n\u003e\u003e\u003e machine.moments(outcome, eta, tau, moments)\n\u003e\u003e\u003e\n\u003e\u003e\u003e print('%.3f %.3f %.3f' % (log_zeroth[0], mean[0], variance[0]))\n-0.671 -0.515 0.946\n```\n\n## Authors\n\n* [Danilo Horta](https://github.com/horta)\n\n## License\n\nThis project is licensed under the\n[MIT License](https://raw.githubusercontent.com/limix/liknorm-py/master/LICENSE.md).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flimix%2Fliknorm-py","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flimix%2Fliknorm-py","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flimix%2Fliknorm-py/lists"}