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        "author": "Yemini, E; Jucikas, T; Schafer, W; Brown, A; Hokanson, J; Currie, M; Javer, A; OpenWorm",
        "author_email": "mcurrie@openworm.org",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Topic :: Scientific/Engineering :: Bio-Informatics"
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        "description": "See https://github.com/openworm/open-worm-analysis-toolbox\n[![GitHub license](https://img.shields.io/github/license/mashape/apistatus.svg)](LICENSE.md)\n[![Travis-CI](https://travis-ci.org/openworm/open-worm-analysis-toolbox.svg?branch=master)](https://travis-ci.org/openworm/open-worm-analysis-toolbox)\n[![BountySource](https://api.bountysource.com/badge/team?team_id=23852)](https://www.bountysource.com/teams/openworm)\n\n\n| <img src=\"documentation/OpenWorm%20Analysis%20Toolbox%20logo.png\" width=\"125\"> | Open Worm Analysis Toolbox |\n====================\n\nThe **Open Worm Analysis Toolbox** is a Python port of the Schafer Lab's [Worm Analysis Toolbox 1.3.4](http://www.mrc-lmb.cam.ac.uk/wormtracker/index.php?action=analysis).\n\nIt can be used to process videos of *C. elegans* into statistics so the behaviour of individual worms can be compared.\n\nIt is also the package used by the OpenWorm project to determine how closely its simulated worm behaves like real worms. It was started as a sub-project of the [OpenWorm project](https://github.com/openworm).\n\n[OWAT is on PyPI](https://pypi.python.org/pypi/open_worm_analysis_toolbox), so to install, simply type:\n\n```\npip install open_worm_analysis_toolbox\n```\n\nContributors please see:\n\n-   [Installation Guide](documentation/INSTALL.md)\n-   [Installation Guide for OS X](documentation/INSTALL-OSX.md)\n\nUsage Example\n-------------\n\n```Python\nimport open_worm_analysis_toolbox as mv\n\n# Load a \"basic\" worm from a file\nbw = mv.BasicWorm.from_schafer_file_factory(\"example_contour_and_skeleton_info.mat\")\n# Normalize the basic worm\nnw = mv.NormalizedWorm.from_BasicWorm_factory(bw)\n# Plot this normalized worm    \nwp = mv.NormalizedWormPlottable(nw, interactive=False)\nwp.show()\n# Obtain features\nwf = mv.WormFeatures(nw)\n```\n\nLater, if we have control worms, we can run statistics on our worm:\n\n```Python\n# Compute histograms\nexperiment_histograms = mv.HistogramManager([wf, wf])\ncontrol_histograms = mv.HistogramManager(control_worms)\n\n# Compute statistics\nstat = mv.StatisticsManager(experiment_histograms, control_histograms)\n\n# Plot statistics for the first extended feature\nstat[0].plot(ax=None, use_alternate_plot=True)\n\n# Give an overall assessment of the worm's similarity to the control set\nprint(\"Nonparametric p and q values are %.2f and %.2f, respectively.\" %\n      (stat.min_p_wilcoxon, stat.min_q_wilcoxon))\n```\n\n\n",
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