Welcome to plutopy! This is a learning library for scientists new to Python, Git, GitHub or all three.
This repository exists to import, visualize and manipulate an image of Pluto taken by the New Horizons mission in 2015. It also exists to help teach how to navigate and contribute to an open-source scientific coding library.
TODO: Take some screenshots of plutopy in action and add them to the README.
See the tutorial for plutopy here TODO: Create a full worked example of plutopy in action in a Jupyter notebook, and add a link to the README.
The image used is the Pluto New Horizons Global Mosaic 300m July 2017. The data was collected by Moore et al. 2016 and made vailable by the U.S. Geologic Survey here.
The features of interest are stored in the Comma Separated Values (CSV) file format, and were generated by Christian Tai Udovicic.
The image handling is done with Python bindings for GDAL, features of interest are read in with Pandas, the analysis is done with numpy and scipy, and the plotting is done with matplotlib. The tutorial is written in a Jupyter notebook. All of these packages are installed with the Anaconda package manager.
Some useful tutorials/documentation on the above packages:
- Getting started with conda
- Python GDAL/OGR Cookbook
- 10 Minutes to pandas
- Numpy Quickstart tutorial
- Scipy Tutorials
- Matplotlib.pyplot Tutorial
- Running the Jupyter Notebook
All contributors to this project are listed in CONTRIBUTORS.md. If you would like to be a contributor, first read CONTRIBUTING.md and then head over to the issue tracker and start with issue #1: Submitting your first pull request. All are welcome!
This repository is governed by a code of coduct. See CODE_OF_CONDUCT.md for more details.
This repository is released under the MIT license for open and warranty-free use and reproduction. See the LICENSE for more details. To learn more about the imporance of a license, see this explanation. To learn what the legal jargon in a particular license means, check out ChooseALicense.com.