{ "info": { "author": "The vivarium developers", "author_email": "vivarium.dev@gmail.com", "bugtrack_url": null, "classifiers": [], "description": "Vivarium Cluster Tools\n=======================\n\n.. image:: https://badge.fury.io/py/vivarium-cluster-tools.svg\n :target: https://badge.fury.io/py/vivarium-cluster-tools\n\n.. image:: https://travis-ci.org/ihmeuw/vivarium_cluster_tools.svg?branch=master\n :target: https://travis-ci.org/ihmeuw/vivarium_cluster_tools\n :alt: Latest Version\n\n.. image:: https://readthedocs.org/projects/vivarium-cluster-tools/badge/?version=latest\n :target: https://vivarium-cluster-tools.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\nVivarium cluster tools is a python package that makes running ``vivarium``\nsimulations at scale on a Univa Grid Engine cluster easy.\n\nInstallation\n------------\n\nYou can install this package with\n\n.. code-block:: console\n\n pip install vivarium-cluster-tools\n\nIn addition, this tool needs the redis client. This must be installed using conda.\n\n.. code-block:: console\n\n conda install redis\n\nA simple example\n----------------\n\nIf you have a ``vivarium`` model specifcation file defining a particular model,\nyou can use that along side a **branches file** to launch a run of many\nsimulations at once with variations in the input data, random seed, or with\ndifferent parameter settings.\n\n.. code-block:: console\n\n psimulate run /path/to/model_specification.yaml /path/to/branches_file.yaml\n\nThe simplest branches file defines a count of input data draws and random seeds\nto launch.\n\n.. code-block:: yaml\n\n input_draw_count: 25\n random_seed_count: 10\n\n\nThis branches file defines a set of simulations for all combinations of 25\ninput draws and 10 random seeds and so would run, in total, 250 simulations.\n\nYou can also define a set of parameter variations to run your model over. Say\nyour original model specification looked something like\n\n.. code-block:: yaml\n\n plugins:\n optional: ...\n\n components:\n vivarium_public_health:\n population:\n - BasePopulation()\n - Mortality()\n disease.models:\n - SIS('lower_respiratory_infections')\n my_lri_intervention:\n components:\n - GiveKidsVaccines()\n\n configuration:\n population:\n population_size: 1000\n age_start: 0\n age_end: 5\n lri_vaccine:\n coverage: 0.2\n efficacy: 0.8\n\nDefining a simple model of lower respiratory infections and a vaccine\nintervention. You could then write a branches file that varied over both\ninput data draws and random seeds, but also over different levels of coverage\nand efficacy for the vaccine. That file would look like\n\n.. code-block:: yaml\n\n input_draw_count: 25\n random_seed_count: 10\n\n branches:\n lri_vaccine:\n coverage: [0.0, 0.2, 0.4, 0.8, 1.0]\n efficacy: [0.4, 0.6, 0.8]\n\nThe branches file would overwrite your original ``lri_vaccine`` configuration\nwith each combination of coverage and efficacy in the branches file and launch\na simulation. More, it would run each coverage-efficacy pair in the branches\nfor each combination of input draw and random seed to produce 25 * 10 * 5 * 3 =\n3750 unique simulations.\n\nTo read about more of the available features and get a better understanding\nof how to correctly write your own branches files, check out the\n`vivarium cluster tools documentation `_.", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://stash.ihme.washington.edu/projects/CSTE/repos/vivarium_cluster_tools", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "vivarium-cluster-tools", "package_url": "https://pypi.org/project/vivarium-cluster-tools/", "platform": "", "project_url": "https://pypi.org/project/vivarium-cluster-tools/", "project_urls": { "Homepage": "https://stash.ihme.washington.edu/projects/CSTE/repos/vivarium_cluster_tools" }, "release_url": 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