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"author": "Zachary R. Sailer",
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"description": "\n\n# GPMap\n\n[](https://gitter.im/harmslab/gpmap?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)\n[](http://gpmap.readthedocs.io/en/latest/?badge=latest)\n[](https://travis-ci.org/harmslab/gpmap)\n\n*A Python API for managing genotype-phenotype map data*\n\nGPMap defines a flexible object for managing genotype-phenotype (GP) map data. At it's core,\nit stores all data in Pandas DataFrames and thus, interacts seamlessly with the\nPyData egosystem.\n\nTo visualize genotype-phenotype objects created by GPMap, checkout [GPGraph](https://github.com/Zsailer/gpgraph).\n\n![](\"docs/_img/gpm.png\")
![](\"docs/_img/dataframe.png\")
\n\n## Basic example\n\nImport the package's base object.\n```python\nfrom gpmap import GenotypePhenotypeMap\n```\n\nPass your data to the object.\n```python\n\n# Data\nwildtype = \"AAA\"\ngenotypes = [\"AAA\", \"AAT\", \"ATA\", \"TAA\", \"ATT\", \"TAT\", \"TTA\", \"TTT\"]\nphenotypes = [0.1, 0.2, 0.2, 0.6, 0.4, 0.6, 1.0, 1.1]\nstdeviations = [0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05]\n\n# Initialize the object\ngpm = GenotypePhenotypeMap(wildtype,\n genotypes,\n phenotypes,\n stdeviations=stdeviations)\n\n# Check out the data.\ngpm.data\n```\n\n\n\nOr load a dataset from disk.\n```python\ngpm = GenotypePhenotypeMap.read_json(\"data.json\")\n```\n\n## Installation\n\n**Users**\nThis simplest way to install this package is using pip:\n```\npip install gpmap\n```\n\n**Developers**\nThe recommended way to install this package fro development is using `pipenv`.\n\n1. Clone this repository:\n```\ngit clone https://github.com/harmslab/gpmap\n```\n2. Install the package using pipenv.\n```\ncd gpmap\npipenv install --dev -e .\n```\n3. Run tests using pytest\n```\npytest\n```\n\n## Dependencies\n\nThe following modules are required. Also, the examples/tutorials are written in Jupyter notebooks and require IPython to be install.\n\n* [Numpy](http://www.numpy.org/)\n* [Pandas](https://pandas.pydata.org/)\n\n\n",
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