make_swan_input_idalia.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "30ccdffc-7215-4058-8ed2-02ed229898d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "make_swan_input_idalia\n",
    "\n",
    "Code to make SWAN input requesting SPEC2D output for drifters during Hurricane Idalia\n",
    "\n",
    "This notebook is based on the really nice example provided by Jacob Davis (davisjr@uw.edu)\n",
    "\n",
    "Revised on 11/7/2023 to extend the time period a little\n",
    "\n",
    "Example code for loading and working with Spotter data from the NHCI\n",
    "aggregated drifter dataset in Python .pickle format. Since all datasets\n",
    "have the same variable names and structure, this example framework can\n",
    "also be used for DWSD and microSWIFT drifters.\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "import os\n",
    "import pickle\n",
    "from datetime import datetime, timezone\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "DATA_DIRECTORY = '/vortexfs1/home/csherwood/proj/NOPP_Idalia/'\n",
    "DATA_FILENAME = 'hurricane_idalia_drifter_data_v1.pickle'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "742435e7-b12b-44a7-9748-f946541fef62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SPOT-30025D\n",
      "SPOT-30052D\n",
      "SPOT-30055D\n",
      "SPOT-30061D\n",
      "SPOT-30066D\n",
      "SPOT-30095D\n",
      "SPOT-30101D\n",
      "SPOT-30102D\n",
      "SPOT-30103D\n",
      "SPOT-30164D\n",
      "300534060649690\n",
      "300534060941280\n",
      "300534064703160\n",
      "300534064703730\n",
      "300534064800060\n",
      "300534064800070\n",
      "300534064800090\n",
      "300534064800250\n",
      "300534061518160\n",
      "300534060949490\n",
      "300534061518010\n",
      "029\n",
      "037\n",
      "046\n",
      "048\n"
     ]
    }
   ],
   "source": [
    "with open(os.path.join(DATA_DIRECTORY, DATA_FILENAME), 'rb') as handle:\n",
    "    drifters = pickle.load(handle)\n",
    "\n",
    "# `drifters` is a python dictionary keyed by drifter type (spotter,\n",
    "# dwsd, or microswift)\n",
    "# `spotter` is a python dictionary of Pandas DataFrames, keyed by\n",
    "# each drifter ID. The drifter ids can then be accessed as follows:\n",
    "spotter = drifters['spotter']\n",
    "spotter_ids = list(spotter.keys())\n",
    "for id in spotter_ids:\n",
    "    print(id)\n",
    "\n",
    "dwsd = drifters['dwsd']\n",
    "dwsd_ids = list(dwsd.keys())\n",
    "for id in dwsd_ids:\n",
    "    print(id)\n",
    "    \n",
    "mswift = drifters['microswift']\n",
    "mswift_ids = list(mswift.keys())\n",
    "for id in mswift_ids:\n",
    "    print(id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "337b14d4-9ad8-412c-bfcb-51fdd8975526",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Make nicknames for these drifters to conform with the max. 8 char limit in SWAN filesname\n",
    "# after adding three characters for a counter (to differentiate the POINTS).\n",
    "# This is a manual step but could be automated.\n",
    "snames = ['S025D','S052D','S055D','S061D','S066D','S095D','S101D','S102D','S103D','S164D']\n",
    "dnames = ['D9690','D1280','D3160', 'D3730','D0060','D0070','D0090','D0250','D8160','D9490','D8010']\n",
    "mnames = ['M0029','M0037','M0046','M0048']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3214d383-66c8-4455-b20c-fd69e20feeb3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SPOT-30025D S025D 28.68153\n",
      "SPOT-30052D S052D 29.45272\n",
      "SPOT-30055D S055D 29.03298\n",
      "SPOT-30061D S061D 28.1355333\n",
      "SPOT-30066D S066D 28.2158167\n",
      "SPOT-30095D S095D 29.50005\n",
      "SPOT-30101D S101D 28.66552\n",
      "SPOT-30102D S102D 29.2237\n",
      "SPOT-30103D S103D 29.1431333\n",
      "SPOT-30164D S164D 29.16865\n",
      "300534060649690 D9690 24.4137594\n",
      "300534060941280 D1280 24.6290572\n",
      "300534064703160 D3160 24.4763976\n",
      "300534064703730 D3730 24.6249148\n",
      "300534064800060 D0060 28.1468332\n",
      "300534064800070 D0070 28.6242082\n",
      "300534064800090 D0090 28.9925352\n",
      "300534064800250 D0250 29.3691349\n",
      "300534061518160 D8160 29.9038304\n",
      "300534060949490 D9490 30.4017255\n",
      "300534061518010 D8010 29.2378842\n",
      "029 M0029 28.146244049072266\n",
      "037 M0037 27.548124313354492\n",
      "046 M0046 28.950855255126953\n",
      "048 M0048 28.79196548461914\n"
     ]
    }
   ],
   "source": [
    "# Check to see if they are correct and check out latitudes\n",
    "for i, id in enumerate( spotter_ids) :\n",
    "    maxlat = spotter[id]['latitude'].max()\n",
    "    print(id,snames[i], maxlat)\n",
    "for i, id in enumerate( dwsd_ids) :\n",
    "    maxlat = dwsd[id]['latitude'].max()\n",
    "    print(id,dnames[i], maxlat)\n",
    "for i, id in enumerate( mswift_ids) :\n",
    "    maxlat = mswift[id]['latitude'].max()\n",
    "    print(id,mnames[i], maxlat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fae83de2-021b-461a-99d7-363bf66ef53a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 222 entries, 2023-08-28 22:06:01+00:00 to 2023-08-31 23:47:55+00:00\n",
      "Data columns (total 18 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   latitude                 222 non-null    float64\n",
      " 1   longitude                222 non-null    float64\n",
      " 2   significant_height       74 non-null     float64\n",
      " 3   peak_period              74 non-null     float64\n",
      " 4   peak_direction           74 non-null     float64\n",
      " 5   peak_directional_spread  74 non-null     float64\n",
      " 6   mean_period              74 non-null     float64\n",
      " 7   mean_direction           74 non-null     float64\n",
      " 8   mean_directional_spread  74 non-null     float64\n",
      " 9   frequency                74 non-null     object \n",
      " 10  energy_density           74 non-null     object \n",
      " 11  a1                       74 non-null     object \n",
      " 12  b1                       74 non-null     object \n",
      " 13  a2                       74 non-null     object \n",
      " 14  b2                       74 non-null     object \n",
      " 15  wave_check_factor        0 non-null      float64\n",
      " 16  sea_surface_temperature  222 non-null    float64\n",
      " 17  sea_level_pressure       222 non-null    float64\n",
      "dtypes: float64(12), object(6)\n",
      "memory usage: 33.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# The data for a single id (e.g. the first) can be accessed as:\n",
    "spotter_id = spotter_ids[0] # = 'SPOT-30068D'\n",
    "spotter[spotter_id].info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "24c3fd0b-80c7-45f9-90ee-ff1a834ac85f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "time\n",
       "2023-08-29 12:06:01+00:00   -83.214833\n",
       "2023-08-29 12:26:01+00:00   -83.217083\n",
       "2023-08-29 12:46:01+00:00   -83.219370\n",
       "2023-08-29 13:06:01+00:00   -83.221900\n",
       "2023-08-29 13:26:01+00:00   -83.224350\n",
       "                               ...    \n",
       "2023-08-30 21:26:01+00:00   -83.346100\n",
       "2023-08-30 21:46:01+00:00   -83.345070\n",
       "2023-08-30 22:06:01+00:00   -83.343650\n",
       "2023-08-30 22:26:01+00:00   -83.342133\n",
       "2023-08-30 22:46:01+00:00   -83.340280\n",
       "Name: longitude, Length: 105, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check time\n",
    "spotter[spotter_id]['longitude'].loc['2023-08-29 1200':'2023-08-30 2300']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "04df9e8e-7815-46fd-8778-e1b8f10d1a6a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# example: plot lat, lon for positions with valid wave data\n",
    "import numpy as np\n",
    "fig, ax = plt.subplots(figsize=(6,4))\n",
    "for spotter_id in spotter.keys():\n",
    "    only_waves = spotter[spotter_id]['energy_density'].notnull()\n",
    "    ax.plot(\n",
    "        spotter[spotter_id][only_waves]['longitude'].loc['2023-08-29 1200':'2023-08-30 2300'],\n",
    "        spotter[spotter_id][only_waves]['latitude'].loc['2023-08-29 1200':'2023-08-30 2300'],'.',\n",
    "        label = spotter_id,\n",
    "    )\n",
    "for mswift_id in mswift.keys():\n",
    "    ax.plot(\n",
    "        mswift[mswift_id]['longitude'].loc['2023-08-29 1200':'2023-08-30 2300'],\n",
    "        mswift[mswift_id]['latitude'].loc['2023-08-29 1200':'2023-08-30 2300'],'o',\n",
    "        label = mswift_id,\n",
    "    )\n",
    "for dwsd_id in dwsd.keys():\n",
    "    # some of these are too far south\n",
    "    if dwsd[dwsd_id]['latitude'].max() > 25.:\n",
    "        ax.plot(\n",
    "            dwsd[dwsd_id]['longitude'].loc['2023-08-29 1200':'2023-08-30 2300'],\n",
    "            dwsd[dwsd_id]['latitude'].loc['2023-08-29 1200':'2023-08-30 2300'],'+',\n",
    "            label = dwsd_id,\n",
    "        )\n",
    "ax.set_ylabel('Latitude')\n",
    "ax.set_xlabel('Longitude')\n",
    "ax.legend()\n",
    "ax.tick_params(axis='x', rotation=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "621c4cce-6446-4a06-9bd1-3ba2081fbd21",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Open a file text to be cut+pasted into SWAN input file for spotters\n",
    "f = open(DATA_DIRECTORY+'idalia_spotter_spec2d_v2.txt', 'w')\n",
    "for nid, spotter_id in enumerate( spotter.keys() ):\n",
    "\n",
    "    # Some rows have times with other data but no wave info (Spotters only)\n",
    "    only_waves = spotter[spotter_id]['energy_density'].notnull()\n",
    "\n",
    "    ipt = 0 # index must stay below 100 or file names will be too long\n",
    "    for index, row in spotter[spotter_id][only_waves].loc['2023-08-29 1200':'2023-08-30 2300'].iterrows():\n",
    "        #print(index, row['latitude'])\n",
    "        spectime = index.strftime('%Y%m%d.%H%m')\n",
    "        pname = \"{}{:03d}\".format(snames[nid], ipt)\n",
    "        pline = (\"POINTS '{}' {:.4f} {:.4f}\".format(pname, row['longitude'], row['latitude'] )) \n",
    "        sline = \"SPECOUT '{}' SPEC2D ABS '{}.spc2d' OUTPUT {} 1000 HR\".format( pname, pname, spectime )\n",
    "        # print(pline)\n",
    "        # print(sline)\n",
    "        f.write(pline+'\\n')\n",
    "        f.write(sline+'\\n')\n",
    "        ipt +=1\n",
    "        if(ipt >= 100):\n",
    "            print(\"Warning: SWAN output filename prefix exceeds 8 chars.\")\n",
    "\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e0cc2f62-3049-44ec-869b-86b7ceba5075",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Open a file text to be cut+pasted into SWAN input file for microswifts\n",
    "f1 = open(DATA_DIRECTORY+'idalia_mswift_spec2d_v2.txt', 'w')\n",
    "for nid, mswift_id in enumerate (mswift.keys() ):\n",
    "    ipt = 0 # index must stay below 100 or file names will be too long\n",
    "    for index, row in mswift[mswift_id].loc['2023-08-29 1200':'2023-08-30 2300'].iterrows():\n",
    "        #print(index, row['latitude'])\n",
    "        pname = \"{}{:03d}\".format(mnames[nid], ipt)\n",
    "        starttime = index.strftime('%Y%m%d.%H%m')\n",
    "        pline = (\"POINTS '{}' {:.4f} {:.4f}\".format(pname, row['longitude'], row['latitude'] )) \n",
    "        sline = \"SPECOUT '{}' SPEC2D ABS '{}.spc2d' OUTPUT {} 1000 HR\".format( pname, pname, starttime )\n",
    "        # print(pline)\n",
    "        # print(sline)\n",
    "        f1.write(pline+'\\n')\n",
    "        f1.write(sline+'\\n')\n",
    "        ipt +=1\n",
    "        if(ipt >= 100):\n",
    "            print(\"Warning: SWAN output filename prefix exceeds 8 chars.\")\n",
    "    \n",
    "f1.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6f26faae-ca17-494a-b3c6-94dd4979ccb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Open a file text to be cut+pasted into SWAN input file for dwsd drifters\n",
    "# These have ids that are too long, so make a shorter name for SWAN\n",
    "f2 = open(DATA_DIRECTORY+'idalia_dwsd_spec2d_v2.txt', 'w')\n",
    "for nid, dwsd_id in enumerate( dwsd.keys() ):\n",
    "    # some of these are too far south\n",
    "    if dwsd[dwsd_id]['latitude'].max() > 25.:\n",
    "        ipt = 0  # index must stay below 100 or file names will be too long\n",
    "        for index, row in dwsd[dwsd_id].loc['2023-08-29 1200':'2023-08-30 2300'].iterrows():\n",
    "            pname = \"{}{:03d}\".format(dnames[nid], ipt)\n",
    "            starttime = index.strftime('%Y%m%d.%H%m')\n",
    "            pline = (\"POINTS '{}' {:.4f} {:.4f}\".format(pname, row['longitude'], row['latitude'] )) \n",
    "            sline = \"SPECOUT '{}' SPEC2D ABS '{}.spc2d' OUTPUT {} 1000 HR\".format( pname, pname, starttime )\n",
    "            # print(pline)\n",
    "            # print(sline)\n",
    "            f2.write(pline+'\\n')\n",
    "            f2.write(sline+'\\n')\n",
    "            ipt +=1\n",
    "            if(ipt >= 1000):\n",
    "                print(\"Warning: SWAN output filename prefix exceeds 8 chars.\")\n",
    "    \n",
    "f2.close()"
   ]
  }
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