{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "
\n", "**This is a fixed-text formatted version of a Jupyter notebook.**\n", "\n", " You can contribute with your own notebooks in this\n", " [GitHub repository](https://github.com/gammapy/gammapy-extra/tree/master/notebooks).\n", "\n", "**Source files:**\n", "[time_analysis.ipynb](../_static/notebooks/time_analysis.ipynb) |\n", "[time_analysis.py](../_static/notebooks/time_analysis.py)\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Time analysis with Gammapy\n", "\n", "## Introduction\n", "\n", "\n", "TODO: use which example dataset? 2FHL / 3FGL and/or HESS DL3 DR1?\n", "\n", "In this tutorial we'll learn how to use [gammapy.time](http://docs.gammapy.org/dev/time/index.html) to run time analyses with Gammapy.\n", "\n", "We will learn about:\n", "\n", "* [gammapy.time.LightCurve](http://docs.gammapy.org/dev/api/gammapy.time.LightCurve.html)\n", "* [gammapy.time.exptest](http://docs.gammapy.org/dev/api/gammapy.time.exptest.html)\n", "\n", "**\n", "Note: there isn't much functionality in gammapy.time at this point.\n", "Come back soon here, or help us implement it.\n", "**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Setup" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "plt.style.use('ggplot')" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from gammapy.time import LightCurve, exptest" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Light curves\n", "\n", "TODO: maybe use 3FGL and compute `variability_index`? (needs to be implemented!)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Event analysis\n", "\n", "TODO" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercises\n", "\n", "TODO" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Start exercises here!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What next?\n", "\n", "In this tutorial we ... (TODO: summarise.\n", "\n", "Here's some suggestions what you look at next:\n", "- TODO" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" }, "nbsphinx": { "orphan": true } }, "nbformat": 4, "nbformat_minor": 1 }