diff --git a/evalhyd-cli.ipynb b/evalhyd-cli.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..00e5a8044e3596a9ac7eee4ac76f44c70d4eeebe --- /dev/null +++ b/evalhyd-cli.ipynb @@ -0,0 +1,208 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "source": [ + "## `evalhyd-cli` demonstration" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "! evalhyd --help" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "### Deterministic evaluation" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "Visualise streamflow observations" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "# shape: {1, time: 4}\n", + "! cat \"data/obs.csv\"" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "Visualise streamflow predictions" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "# shape: {series: 1, time: 4}\n", + "! cat \"data/prd.csv\"" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "Compute Nash-Sutcliffe efficiency" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# shape: {series: 1, subsets: 1, samples: 1}\n", + "! evalhyd evald \"data/obs.csv\" \"data/prd.csv\" \"NSE\"" + ] + }, + { + "cell_type": "markdown", + "source": [ + "### Probabilistic evaluation" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "Visualise streamflow observations" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "# shape: {sites: 1, time: 5}\n", + "! cat \"data/obs/site_a.csv\"" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "Visualise streamflow predictions" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "# shape: {sites: 1, lead times: 1, members: 3, time: 5}\n", + "! cat \"data/prd/leadtime_1/site_a.csv\"" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "Visualise streamflow thresholds" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "# shape: {sites: 1, thresholds: 2}\n", + "! cat \"data/thr/site_a.csv\"" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "Compute Brier score" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "# shape: {sites: 1, lead times: 1, subsets: 1, samples: 1, thresholds: 2}\n", + "! evalhyd evalp \"data/obs\" \"data/prd\" \"BS\" --q_thr \"data/thr\" --events \"high\"" + ], + "metadata": { + "collapsed": false + } + } + ], + "metadata": { + "kernelspec": { + "display_name": "python", + "language": "python", + "name": "python" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.13" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}