{
 "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
   }
  }
 ],
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   "display_name": "python",
   "language": "python",
   "name": "python"
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