{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "
\n", "\n", "> Thunder is a library for analyzing spatial and temporal data in Python. It is designed to run locally for small data or against a Spark cluster for large data, using an identical API. These notebooks are tutorials for using Thunder. All the tutorials use small, toy data sets.\n", "\n", "\n", "\n", ">For more information on Thunder, visit the project page or come chat with us.\n", "\n", "### `tutorials`\n", "\n", "### - [`basics`](tutorials/basics.ipynb)\n", "\n", "### - [`images`](tutorials/images.ipynb)\n", "\n", "### - [`series`](tutorials/series.ipynb)\n", "\n", "### - [`registration`](tutorials/registration.ipynb)\n", "\n", "
" ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.11" } }, "nbformat": 4, "nbformat_minor": 0 }