{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use this to read the ALL jarkus transects and make json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import io\n",
    "import re\n",
    "import itertools\n",
    "\n",
    "import geojson\n",
    "import netCDF4\n",
    "import pandas\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = netCDF4.Dataset('../data/transect.nc')\n",
    "\n",
    "ids = ds.variables['id'][:]\n",
    "\n",
    "id_ = 7003900\n",
    "\n",
    "def transect2features(id_):\n",
    "    transect_idx = np.searchsorted(ids, id_)\n",
    "    \n",
    "    variables = {\n",
    "        'lat': {\"var\": 'lat', \"slice\": np.s_[transect_idx, :]},\n",
    "        'lon': {\"var\": 'lon', \"slice\": np.s_[transect_idx, :]}\n",
    "\n",
    "    }\n",
    "    data = {}\n",
    "    for var, props in variables.items():\n",
    "        data[var] = ds.variables[props['var']][props['slice']]\n",
    "\n",
    "    #for t, row in zip(data['t'], data['z']):\n",
    "    coords = pandas.DataFrame(data=dict(\n",
    "        lon0=data['lon'][:1], \n",
    "        lat0=data['lat'][:1],\n",
    "        lon1=data['lon'][-1:],\n",
    "        lat1=data['lat'][-1:]\n",
    "    ))\n",
    "    coordinates = [coords.dropna().values[0][0:2].tolist(),coords.dropna().values[0][2:4].tolist()]\n",
    "    geometry = geojson.LineString(coordinates=coordinates)\n",
    "    properties = {\n",
    "        \"id\": \"{}\".format(id_)\n",
    "    }\n",
    "    yield geojson.Feature(id=\"{}\".format(id_), geometry=geometry, properties=properties)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import itertools\n",
    "import more_itertools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "038867a44be14233a3481d72da01a1c3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=2285), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "import tqdm\n",
    "\n",
    "features = []\n",
    "\n",
    "for id_ in tqdm.tqdm_notebook(ids):\n",
    "    features.extend(transect2features(id_))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i, chunk in enumerate(more_itertools.chunked(features, 10000)):\n",
    "    collection = geojson.FeatureCollection(chunk)\n",
    "    with open('jarkus4mapbox.json'.format(i), 'w') as f:\n",
    "        geojson.dump(collection, f)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Automatic pdb calling has been turned OFF\n"
     ]
    }
   ],
   "source": [
    "%pdb off\n"
   ]
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
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 "nbformat": 4,
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