{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring measurements from fews\n",
    "\n",
    "In this notebook, you will experiment how to use the `hydropandas` package to access, visualize and explore meta data from the FEWS database. More information on FEWS can be found on their [website](https://oss.deltares.nl/web/delft-fews/)."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id=top></a>Notebook contents\n",
    "\n",
    "1. [FEWS xml files](#xml)\n",
    "2. [Directory with xml files](#dir)\n",
    "3. [Connect to a FEWS database](#db)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "\n",
    "import hydropandas as hpd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<RootLogger root (INFO)>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hpd.util.get_color_logger(\"INFO\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FEWS xml files <a id=xml></a>\n",
    "\n",
    "You can read FEWS xml files using the code below. First we download the xml files and put them in the 'fewsdata' directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# download test file\n",
    "if not os.path.exists(\"./fewsdata\"):\n",
    "    os.mkdir(\"./fewsdata\")\n",
    "xml_file_url = \"https://raw.githubusercontent.com/ArtesiaWater/hydropandas/refs/heads/master/tests/data/2019-FEWS-test/test_wsvv_fews.xml\"\n",
    "r = requests.get(xml_file_url)\n",
    "with open(\"./fewsdata/test_wsvv_fews.xml\", \"w+\") as f:\n",
    "    f.write(r.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The file 'test_wsvv_fews.xml' contains data from a radar. We can read the data in this file using the `read_fews` function. \n",
    "\n",
    "Note: The `read_fews` function will always return a collection of observations (ObsCollection) because a single xml file can have multiple observations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO:hydropandas.io.fews:1/1 read test_wsvv_fews.xml\u001b[0m\n",
      "\u001b[32mINFO:hydropandas.io.fews:reading FEWS_RADAR_241\u001b[0m\n",
      "\u001b[32mINFO:hydropandas.io.fews:reading FEWS_RADAR_241\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>filename</th>\n",
       "      <th>source</th>\n",
       "      <th>unit</th>\n",
       "      <th>station</th>\n",
       "      <th>meteo_var</th>\n",
       "      <th>obs</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FEWS_RADAR_241_P.radar.h</th>\n",
       "      <td>161278.0</td>\n",
       "      <td>454989.0</td>\n",
       "      <td></td>\n",
       "      <td>FEWS</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>P.radar.h</td>\n",
       "      <td>MeteoObs FEWS_RADAR_241_P.radar.h\n",
       "-----metadat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FEWS_RADAR_241_Eact.d</th>\n",
       "      <td>161278.0</td>\n",
       "      <td>454989.0</td>\n",
       "      <td></td>\n",
       "      <td>FEWS</td>\n",
       "      <td>mm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eact.d</td>\n",
       "      <td>MeteoObs FEWS_RADAR_241_Eact.d\n",
       "-----metadata--...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 x         y filename source unit  station  \\\n",
       "name                                                                         \n",
       "FEWS_RADAR_241_P.radar.h  161278.0  454989.0            FEWS   mm      NaN   \n",
       "FEWS_RADAR_241_Eact.d     161278.0  454989.0            FEWS   mm      NaN   \n",
       "\n",
       "                          meteo_var  \\\n",
       "name                                  \n",
       "FEWS_RADAR_241_P.radar.h  P.radar.h   \n",
       "FEWS_RADAR_241_Eact.d        Eact.d   \n",
       "\n",
       "                                                                        obs  \n",
       "name                                                                         \n",
       "FEWS_RADAR_241_P.radar.h  MeteoObs FEWS_RADAR_241_P.radar.h\n",
       "-----metadat...  \n",
       "FEWS_RADAR_241_Eact.d     MeteoObs FEWS_RADAR_241_Eact.d\n",
       "-----metadata--...  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read a single xml file\n",
    "fname = \"./fewsdata/test_wsvv_fews.xml\"\n",
    "oc = hpd.read_fews(fname, ObsClass=hpd.MeteoObs)\n",
    "oc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can visualise the data like we any ObsCollection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Eact [mm/d]'>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the measurements\n",
    "f, axes = plt.subplots(2, 1, figsize=(10, 6), sharex=True)\n",
    "oc.get_obs(\"FEWS_RADAR_241_P.radar.h\")[\"value\"].plot(\n",
    "    ax=axes[0], marker=\".\", legend=True, ylabel=\"P [mm/d]\"\n",
    ")\n",
    "oc.get_obs(\"FEWS_RADAR_241_Eact.d\")[\"value\"].plot(\n",
    "    ax=axes[1], marker=\".\", legend=True, ylabel=\"Eact [mm/d]\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Directory with xml files <a id=dir></a>\n",
    "\n",
    "We can also read a whole zipfile with xml files at once."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# download zip directory\n",
    "zip_file_url = \"https://github.com/ArtesiaWater/hydropandas/raw/refs/heads/master/tests/data/2019-FEWS-test/WaalenBurg_201810-20190215_prod.zip\"\n",
    "r = requests.get(zip_file_url)\n",
    "with open(\"./fewsdata/WaalenBurg_201810-20190215_prod.zip\", \"wb\") as f:\n",
    "    f.write(r.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO:hydropandas.io.fews:1/1 read WaalenBurg_201810-20190215_prod.xml\u001b[0m\n",
      "\u001b[32mINFO:hydropandas.io.fews:reading MPN-N-1\u001b[0m\n",
      "\u001b[32mINFO:hydropandas.io.fews:reading MPN-N-2\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>filename</th>\n",
       "      <th>source</th>\n",
       "      <th>unit</th>\n",
       "      <th>monitoring_well</th>\n",
       "      <th>tube_nr</th>\n",
       "      <th>screen_top</th>\n",
       "      <th>screen_bottom</th>\n",
       "      <th>ground_level</th>\n",
       "      <th>tube_top</th>\n",
       "      <th>metadata_available</th>\n",
       "      <th>obs</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MPN-N-1_H.meting</th>\n",
       "      <td>115535.9882</td>\n",
       "      <td>567867.7001</td>\n",
       "      <td></td>\n",
       "      <td>FEWS</td>\n",
       "      <td>mNAP</td>\n",
       "      <td>MPN-N-1</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>GroundwaterObs MPN-N-1_H.meting\n",
       "-----metadata-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPN-N-2_H.meting</th>\n",
       "      <td>115294.9832</td>\n",
       "      <td>567758.8142</td>\n",
       "      <td></td>\n",
       "      <td>FEWS</td>\n",
       "      <td>mNAP</td>\n",
       "      <td>MPN-N-2</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>GroundwaterObs MPN-N-2_H.meting\n",
       "-----metadata-...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            x            y filename source  unit  \\\n",
       "name                                                               \n",
       "MPN-N-1_H.meting  115535.9882  567867.7001            FEWS  mNAP   \n",
       "MPN-N-2_H.meting  115294.9832  567758.8142            FEWS  mNAP   \n",
       "\n",
       "                 monitoring_well tube_nr  screen_top  screen_bottom  \\\n",
       "name                                                                  \n",
       "MPN-N-1_H.meting         MPN-N-1                 NaN            NaN   \n",
       "MPN-N-2_H.meting         MPN-N-2                 NaN            NaN   \n",
       "\n",
       "                  ground_level  tube_top  metadata_available  \\\n",
       "name                                                           \n",
       "MPN-N-1_H.meting           NaN       NaN                True   \n",
       "MPN-N-2_H.meting           NaN       NaN                True   \n",
       "\n",
       "                                                                obs  \n",
       "name                                                                 \n",
       "MPN-N-1_H.meting  GroundwaterObs MPN-N-1_H.meting\n",
       "-----metadata-...  \n",
       "MPN-N-2_H.meting  GroundwaterObs MPN-N-2_H.meting\n",
       "-----metadata-...  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read a zipfile\n",
    "fdir = \"./fewsdata/WaalenBurg_201810-20190215_prod.zip\"\n",
    "oc = hpd.read_fews(fdir)\n",
    "oc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='m NAP'>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the measurements\n",
    "f, ax = plt.subplots(figsize=(10, 3))\n",
    "oc.get_obs(\"MPN-N-1_H.meting\")[\"value\"].plot(\n",
    "    ax=ax, marker=\".\", legend=True, ylabel=\"m NAP\"\n",
    ")\n",
    "oc.get_obs(\"MPN-N-2_H.meting\")[\"value\"].plot(\n",
    "    ax=ax, marker=\".\", legend=True, ylabel=\"m NAP\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Connect to a FEWS database <a id=db></a>\n",
    "\n",
    "It is also possible to connect to a FEWS database and obtain the data directly without having to make a file dump. For this you need to have:\n",
    "\n",
    "1. Access to the database\n",
    "2. An endpoint (url) for the database\n",
    "3. A location ID from a measurement point in the database\n",
    "\n",
    "If you have these you can set the variables below and obtain the measurements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# put here the URL of your fews database\n",
    "fews_db_url = \"\"  # enter fews database url here\n",
    "location_id = \"\"  # enter location id here\n",
    "\n",
    "# read as observation objects\n",
    "params = {\n",
    "    \"locationIds\": location_id,\n",
    "    \"documentVersion\": \"1.26\",\n",
    "    \"documentFormat\": \"PI_XML\",\n",
    "}\n",
    "\n",
    "r = requests.get(fews_db_url, params=params, verify=True)\n",
    "xmlstring = r.text\n",
    "\n",
    "oc = hpd.ObsCollection.from_fews_xml(\n",
    "    xmlstring=xmlstring,\n",
    "    ObsClass=hpd.Obs,\n",
    "    low_memory=False,\n",
    ")\n",
    "\n",
    "oc"
   ]
  }
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