main_notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0354c02d-2ad6-46a0-ae77-734668a1ccb3",
   "metadata": {},
   "source": [
    "# Testing the relationship between COTS outbreaks and post-cyclone salinity plumes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6eacbe2-dc93-4127-935e-f7d8074f92e5",
   "metadata": {},
   "source": [
    "***Group 1, ENVI5809, Semester 2 2022***"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0912b05a-63e1-410b-80a8-53d7f7efb2db",
   "metadata": {},
   "source": [
    "*Beatriz Boggiani, Md. Yousef Gazi, Lachlan Perris, Jonathon Leonard*\n",
    "\n",
    "*Note this code has been adapted from tutorials provided by Tristan Salles and the Ocean Parcels Development Team*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8074b4e9-e16c-47ad-accc-33949531727a",
   "metadata": {},
   "source": [
    "This notebook is to accompany the report and presentation for the ENVI5809 project. In this notebook we demonstrate how we use manta-tow survey data and eReefs modelling to derive and plot information on the relationship between COTS outbreaks and low-salinity plumes. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b76fffe-f0c9-4648-814f-96de23b3da28",
   "metadata": {},
   "source": [
    "## Initialising"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfe433a2-f9bd-466b-9fb1-4c6cd9bcdaa3",
   "metadata": {},
   "source": [
    "### Importing libraries"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d224f4b1-760d-49c5-ade7-2e14e02fecf5",
   "metadata": {},
   "source": [
    "***IMPORTANT*** <br>\n",
    "The ocean parcels package may occassionally cause some headaches. On an M1 Apple Macbook, before opening jupyter lab from the terminal, you need to type 'export CC=gcc'. This may help on other architectures too. <br>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3dbf6d0c-b6a0-459b-aa69-5d4ddf675275",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys, os, random, itertools\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import netCDF4 as nc\n",
    "\n",
    "import cartopy\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER\n",
    "import cartopy.io.shapereader as shpreader\n",
    "cartopy.config['data_dir'] = os.getenv('CARTOPY_DIR', cartopy.config.get('data_dir'))\n",
    "\n",
    "import cmocean\n",
    "import imageio\n",
    "\n",
    "from parcels import FieldSet, Field, ParticleSet, Variable, JITParticle\n",
    "from parcels import AdvectionRK4, plotTrajectoriesFile, ErrorCode\n",
    "\n",
    "import math\n",
    "import datetime as dtime\n",
    "from datetime import datetime\n",
    "from datetime import timedelta\n",
    "from operator import attrgetter\n",
    "\n",
    "import matplotlib as mpl\n",
    "from matplotlib import pyplot as plt\n",
    "plt.ion()  # To trigger the interactive inline mode\n",
    "plt.style.use(\"seaborn\")\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (20,15) # Change default figure size\n",
    "plt.rcParams.update({'axes.titlesize':16})\n",
    "plt.rcParams.update({'axes.labelsize':16})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fce87b75-7a22-487b-99e4-63a851ceaae2",
   "metadata": {},
   "source": [
    "### Global variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "059abac0-561c-470b-af6d-41ece4b22c45",
   "metadata": {},
   "outputs": [],
   "source": [
    "# The coordinates of some North Queensland towns (for plotting)\n",
    "cairnsLat, cairnsLon = -16.92, 145.77\n",
    "rockhamptonLat, rockhamptonLon = -23.38, 150.51\n",
    "bowenLat, bowenLon = -20.01, 148.25"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "430c3f23-43a2-4377-a4aa-d54aa4b727b8",
   "metadata": {},
   "source": [
    "### Common functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e7c338ad-80c8-467a-803f-430677c43e88",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_town(townname='cairns'):\n",
    "    lat = f'{townname}Lat'\n",
    "    lon = f'{townname}Lon'\n",
    "    plt.plot(globals()[lon], globals()[lat], color='red', marker='s', linewidth=2, mew=0.1, mec='black', transform=ccrs.PlateCarree())\n",
    "    plt.text(globals()[lon]-0.2, globals()[lat]-0.1, f'{townname.capitalize()}', horizontalalignment='right', transform=ccrs.PlateCarree())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e231a850-68a0-44eb-9939-e60e912ca8ad",
   "metadata": {},
   "source": [
    "### Create output directories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a2454a58-e8df-4ee6-91b4-ca3d94efca6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parcels output\n",
    "parcels_directory = 'parcels_output'\n",
    "os.makedirs(parcels_directory, exist_ok=True)\n",
    "\n",
    "# Parcels images\n",
    "parcels_figs = 'parcels_figs'\n",
    "os.makedirs(parcels_figs, exist_ok=True)\n",
    "\n",
    "# eReefs animations\n",
    "dir_name = f'eReefs_animations'\n",
    "os.makedirs(dir_name, exist_ok=True) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92970a61-0b12-4601-b36b-613c503a4da3",
   "metadata": {},
   "source": [
    "## AIMS Manta-Tow COTS data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd2aa0f5-b2ed-4e26-8a75-f4779b7a44d2",
   "metadata": {},
   "source": [
    "First we use manta-tow data from the Australian Institute of Marine Science to locate where and when COTS outbreaks were recorded."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2b2ca4a7-34cc-494a-b131-679be8ad2dcd",
   "metadata": {},
   "outputs": [
    {
     "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>REEF_NAME</th>\n",
       "      <th>LATITUDE</th>\n",
       "      <th>LONGITUDE</th>\n",
       "      <th>YEAR_CODE</th>\n",
       "      <th>SAMPLE_DATE</th>\n",
       "      <th>TOTAL_COTS</th>\n",
       "      <th>MEAN_COTS_PER_TOW</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LOW ISLANDS REEF</td>\n",
       "      <td>-16.383333</td>\n",
       "      <td>145.566667</td>\n",
       "      <td>199293</td>\n",
       "      <td>1993-06-11</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1993</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LOW ISLANDS REEF</td>\n",
       "      <td>-16.383333</td>\n",
       "      <td>145.566667</td>\n",
       "      <td>199596</td>\n",
       "      <td>1996-01-15</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1996</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          REEF_NAME   LATITUDE   LONGITUDE  YEAR_CODE SAMPLE_DATE  TOTAL_COTS  \\\n",
       "0  LOW ISLANDS REEF -16.383333  145.566667     199293  1993-06-11           0   \n",
       "1  LOW ISLANDS REEF -16.383333  145.566667     199596  1996-01-15           0   \n",
       "\n",
       "   MEAN_COTS_PER_TOW  YEAR  MONTH  \n",
       "0                0.0  1993      6  \n",
       "1                0.0  1996      1  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = 'datasets/manta-tow-by-reef/manta-tow-by-reef.csv' # path to manta-tow data saved locally\n",
    "df = pd.read_csv(data) # Read the manta-tow data into pandas\n",
    "\n",
    "# Drop unneeded columns\n",
    "df = df.drop(columns=['SECTOR','SHELF','REEF_ID','P_CODE','VISIT_NO', 'REPORT_YEAR','MEDIAN_LIVE_CORAL','MEDIAN_SOFT_CORAL', 'MEDIAN_DEAD_CORAL',\n",
    "       'MEAN_LIVE_CORAL', 'MEAN_SOFT_CORAL', 'MEAN_DEAD_CORAL', 'TOTAL_TROUT', 'MEAN_TROUT_PER_TOW', 'TOWS'])\n",
    "\n",
    "# Convert date column to datetime\n",
    "df['SAMPLE_DATE'] = pd.to_datetime(df['SAMPLE_DATE']) \n",
    "\n",
    "# Add year and month columns for easier processing later on\n",
    "df['YEAR'] = df['SAMPLE_DATE'].dt.year\n",
    "df['MONTH'] = df['SAMPLE_DATE'].dt.month\n",
    "\n",
    "df.head(2) # Check the data has loaded correctly"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dd75655-5493-4698-9575-362cbce71791",
   "metadata": {},
   "source": [
    "### Plot all COTS data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "001b5d78-c044-4fc6-8498-648b912ef1f5",
   "metadata": {},
   "source": [
    "Now we can plot all our data to get a rough idea of some of the patterns and how it looks. The below graph shows that COTS outbreaks are seasonal, with most appearing at the beginning of the year. We can also see clusters of very high outbreaks around the year 2000 and 2018."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ab0c3f1e-dda8-4623-be9b-a0bda6dd1330",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set up our colour palette and boundaries\n",
    "cmap = plt.cm.rainbow # Use rainbow to easily distinguish between discrete colour bins\n",
    "norm = mpl.colors.BoundaryNorm(np.arange(-22, -12, 2), cmap.N, extend='both') # Set the boundaries of the discrete colour paletter\n",
    "\n",
    "# Plot the mean-cots-per-tow against date, coloured by the reef's latitude\n",
    "fig = plt.figure(1, figsize=(20,8))\n",
    "plt.scatter(df['SAMPLE_DATE'], df['MEAN_COTS_PER_TOW'], c=df['LATITUDE'], cmap=cmap, norm=norm, alpha=0.7, edgecolors='black', linewidth=0.2)\n",
    "\n",
    "plt.ylim(-1.5,max(df['MEAN_COTS_PER_TOW'])+5)\n",
    "plt.xlim(min(df['SAMPLE_DATE'])-timedelta(days=90), max(df['SAMPLE_DATE'])+timedelta(days=90))\n",
    "plt.minorticks_on()\n",
    "plt.grid(which ='both', color='w')\n",
    "plt.title(\"COTS Observations from Manta-Tow Data\")\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Mean COTS per tow')\n",
    "cbar = plt.colorbar()\n",
    "cbar.set_label('Latitude (deg)')\n",
    "\n",
    "plt.savefig('Plots_Final/COTS_distribution.png', dpi=300, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b84141b1-bc3a-4bed-9ff5-2eb4a5c37c0d",
   "metadata": {},
   "source": [
    "### Identify COTS outbreaks"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8cfb69c5-b983-475c-96b1-34604049e2af",
   "metadata": {},
   "source": [
    "As a rough identification of large outbreaks, let's identify only outbreaks that are significantly larger than the mean value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "14049d28-5856-424b-9787-d2d9d5b59301",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The average COTS per tow detected across the whole dataset is 0.295\n"
     ]
    }
   ],
   "source": [
    "mean = df['MEAN_COTS_PER_TOW'].mean()\n",
    "print(f\"The average COTS per tow detected across the whole dataset is {round(mean,3)}\")\n",
    "\n",
    "# Let's work with all data that has recorded at least some COTS (so we can get closer to a normal distribution and using standard deviation makes a bit more sense)\n",
    "df_nonzero = df[df['MEAN_COTS_PER_TOW'] > 0]\n",
    "mean_nonzero = df_nonzero['MEAN_COTS_PER_TOW'].mean()\n",
    "std_nonzero = df_nonzero['MEAN_COTS_PER_TOW'].std()\n",
    "\n",
    "# Now add a new column to the original dataset that displays the standard deviation for non-zero Mean-COTS-per-tow data\n",
    "df['DEVIATION'] = np.abs(df['MEAN_COTS_PER_TOW']/std_nonzero)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47e80ad0-811e-43c4-b36e-b2a85ffc0c83",
   "metadata": {},
   "source": [
    "### Plot COTS outbreaks"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c04a9c7-9e07-4f11-8624-6f896d0c2cb2",
   "metadata": {},
   "source": [
    "Now let's define a function that plots COTS outbreaks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "456ee16d-aa74-405c-8604-4bac32c2a3b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_outbreaks(x,y,z,w):\n",
    "    \"\"\"Plots the spatial and temporal extent of COTS outbreaks\"\"\"\n",
    "    fig = plt.figure(facecolor='w', edgecolor='k')\n",
    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "    \n",
    "    cmap = cmocean.cm.thermal # Use rainbow to easily distinguish between discrete colour bins\n",
    "    norm = mpl.colors.BoundaryNorm(np.arange(w.min(), w.max(),1), cmap.N, extend='both') # Set the boundaries of the discrete colour paletter\n",
    "    \n",
    "    # Add features from a shapefile, this shapefile is of reef features in the GBR\n",
    "    ax.add_feature(cartopy.feature.ShapelyFeature(shpreader.Reader('datasets/Shapefiles/GBR_Features.shp').geometries(), \n",
    "                                                   ccrs.PlateCarree(), facecolor=\"lightgrey\", edgecolor='black', lw=0.05))\n",
    "\n",
    "    # Add map features from cartopy\n",
    "    ax.coastlines(linewidth=1)\n",
    "    ax.add_feature(cfeature.NaturalEarthFeature('physical', 'land', '10m', \n",
    "                                                edgecolor='face', \n",
    "                                                facecolor='lightgray'))\n",
    "    ax.add_feature(cfeature.NaturalEarthFeature('physical', 'rivers_lake_centerlines', '10m', \n",
    "                                                edgecolor='darkblue', \n",
    "                                                facecolor='none'))\n",
    "    \n",
    "    plot = plt.scatter(x, y, s=z*30, c=w, cmap=cmap, norm = norm, zorder=10, alpha=0.7)\n",
    "    \n",
    "    \n",
    "    plt.title('Spatial and temporal extent of COTS observations')\n",
    "    \n",
    "    # produce a legend with a cross section of sizes from the scatter\n",
    "    handles, labels = plot.legend_elements(prop=\"sizes\", alpha=0.6,  func = lambda x: x/15)\n",
    "    legend2 = ax.legend(handles, labels, loc=\"upper right\", title=\"Number of observed COTS\")\n",
    "    \n",
    "    # Add gridlines\n",
    "    gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=0.5, color='grey', alpha=0.5, linestyle='-', draw_labels=True)\n",
    "    gl.top_labels = False\n",
    "    gl.left_labels = False\n",
    "    gl.right_labels=True\n",
    "    gl.xlines = True\n",
    "    gl.xformatter = LONGITUDE_FORMATTER\n",
    "    gl.yformatter = LATITUDE_FORMATTER\n",
    "    \n",
    "    # Plot towns\n",
    "    plot_town(townname='cairns')\n",
    "    plot_town(townname='rockhampton')\n",
    "    plot_town(townname='bowen')\n",
    "    \n",
    "    # Color bar\n",
    "    cbar = fig.colorbar(plot, ax=ax, fraction=0.027, pad=0.035, orientation='horizontal')\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77fc397a-2b61-4998-9fa5-ff3f36855874",
   "metadata": {},
   "source": [
    "#### Outbreaks with a mean of more than one COTS sighting per tow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c4b39dd5-c2c9-4a8b-a998-849266f81829",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x1500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The AIMS website shows high COTS number are when the mean per tow is > 1\n",
    "highishCOTS = df[df['MEAN_COTS_PER_TOW'] > 1] \n",
    "highishCOTS = highishCOTS.reset_index() # reset the index for exporting \n",
    "\n",
    "x = highishCOTS[\"LONGITUDE\"]\n",
    "y = highishCOTS[\"LATITUDE\"]\n",
    "z = highishCOTS['MEAN_COTS_PER_TOW']\n",
    "w = highishCOTS['YEAR']\n",
    "\n",
    "plot_outbreaks(x,y,z,w)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b32e6c8-3bca-465a-b2f1-14d3acad33d1",
   "metadata": {},
   "source": [
    "#### Largest outbreaks"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ceffddd-3b84-423b-b4ee-ddc1c06ac19d",
   "metadata": {},
   "source": [
    "Now let's look at only the most significant COTS outbreaks. We judged this as those outbreaks that were more than a standard deviation higher than the mean COT sighting. Note: we only calculated the standard deviation for where there were COTS sighted, i.e. values of zero COTS sighted were excluded."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9f74fa4b-3f14-4f83-8748-d8a3daa77a34",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 REEF_NAME SAMPLE_DATE  MEAN_COTS_PER_TOW  DEVIATION\n",
      "0  FARQUHARSON REEF (NO 1)  2018-02-21              8.269   1.802895\n",
      "1              TAYLOR REEF  2018-02-22             13.102   2.856637\n",
      "2         GANNETT CAY REEF  2020-09-03             14.542   3.170602\n",
      "3                 RIB REEF  2018-02-26              5.909   1.288343\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "highCOTS = df[(df['DEVIATION'] > 1) & (df['YEAR'] >= 2010)] # Limit high COTS to years after 2010 as this is when eReefs data starts\n",
    "highCOTS = highCOTS.reset_index(drop=True) # reset the index for exporting \n",
    "\n",
    "# Let's look at the data. For simplicity we only print some columns\n",
    "print(highCOTS[['REEF_NAME', 'SAMPLE_DATE', 'MEAN_COTS_PER_TOW', 'DEVIATION']])\n",
    "\n",
    "# Now plot the data\n",
    "x = highCOTS[\"LONGITUDE\"]\n",
    "y = highCOTS[\"LATITUDE\"]\n",
    "z = highCOTS['MEAN_COTS_PER_TOW']\n",
    "w = highCOTS['YEAR']\n",
    "\n",
    "plot_outbreaks(x,y,z,w)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "48093da0-9b73-45c4-a791-7cdfd2583947",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For the purposes of plotting with parcels let's create a data set just of the 2018 outbreak\n",
    "feb2018 = df[(df['DEVIATION'] > 1) & (df['YEAR'] == 2018)] # Limit high COTS to years after 2010 as this is when eReefs data starts\n",
    "feb2018 = highCOTS.reset_index(drop=True) # reset the index for exporting "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3676520-be8f-4f40-9449-d57aabdc7c1b",
   "metadata": {},
   "source": [
    "### Export to csv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80cdf3a5-e74b-442d-b2a3-4adbf658d3ad",
   "metadata": {},
   "source": [
    "Export our high COTS dataframe to a csv for reusing later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "329196eb-b0af-4621-8588-df2733bf313d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Export a table for the final report\n",
    "exportDF = highCOTS[['REEF_NAME', 'SAMPLE_DATE', 'MEAN_COTS_PER_TOW', 'DEVIATION']]\n",
    "csv_filepath = 'datasets/highCOTS2.csv'\n",
    "if os.path.isfile(csv_filepath):\n",
    "    os.remove(csv_filepath)\n",
    "exportDF.to_csv(csv_filepath, index=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bb854e2-f7ef-4523-9153-20b00ab00b03",
   "metadata": {},
   "source": [
    "## eReefs Salinity Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b94b52ec-7f6a-4cb0-b9fe-e35e562f3f7e",
   "metadata": {},
   "source": [
    "Now that we have identified times and locations on COTS outbreaks, we can use eReefs to plot salinity levels around those times."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c877ea76-aa2b-4bab-92bf-53879e8270f2",
   "metadata": {},
   "source": [
    "### Plotting eReefs data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "96d951cd-97c5-44dc-8ecb-98c4d0b35ac1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def ereefs_map(nc_data, tindex, depthIndex, variable, extent, color, size, figname='untitled', zoom=None, show=False, save=True):\n",
    "    \"\"\"\"Plots ereefs data\"\"\"\n",
    "    \n",
    "    # Set up a directory to put the produced images into\n",
    "    dir_name = f'{figname}_images'\n",
    "    os.makedirs(dir_name, exist_ok=True) # Make directory to put the images in \n",
    "    \n",
    "    # Define variables based on the input netcdf grid (ncdata)\n",
    "    data = nc_data[variable][tindex, :,:] \n",
    "    lat = nc_data['latitude'][:]\n",
    "    lon = nc_data['longitude'][:]\n",
    "    time = nc_data.variables['time']\n",
    "    depth = ds_hydro.zc.values[depthIndex]\n",
    "    \n",
    "    fig = plt.figure(figsize=size, facecolor='w', edgecolor='k')\n",
    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "    # ax.set_extent([np.min(lon), np.max(lon), np.max(lat), np.min(lat)], ccrs.PlateCarree()) # Set the extent based on ncdata's extent\n",
    "    ax.set_extent([143, 153, -9.5, -25], ccrs.PlateCarree())\n",
    "    \n",
    "    plot = plt.pcolormesh(lon, lat, data, cmap=color, shading='auto', vmin=extent[0], vmax=extent[1], transform=ccrs.PlateCarree())\n",
    "    \n",
    "    # Plot towns\n",
    "    plot_town(townname='cairns')\n",
    "    plot_town(townname='rockhampton')\n",
    "    plot_town(townname='bowen')\n",
    "    \n",
    "    # Color bar\n",
    "    cbar = fig.colorbar(plot, ax=ax, fraction=0.027, pad=0.035, orientation='horizontal')\n",
    "    cbar.set_label(nc_data[variable].units, fontsize=12)\n",
    "    cbar.ax.tick_params(labelsize=10)\n",
    "    \n",
    "    # Title\n",
    "    dtime = nc.num2date(nc_data['time'][tindex],nc_data['time'].units)\n",
    "    time_format = dtime.strftime('%b %d %Y %I%p')\n",
    "    plt.title(f\"{nc_data[variable].long_name} {time_format}\", fontsize=14, pad=4)\n",
    "    \n",
    "    # Plot lat/lon grid\n",
    "    gridlines = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True, linewidth=0.1, color='k', alpha=1, linestyle='--')\n",
    "    gridlines.top_labels =  False\n",
    "    gridlines.right_labels = False\n",
    "    \n",
    "    gridlines.xformatter = LONGITUDE_FORMATTER # from cartopy mpl gridliner class\n",
    "    gridlines.yformatter = LATITUDE_FORMATTER\n",
    "    \n",
    "    gridlines.xlabel_style = {'size': 8}\n",
    "    gridlines.ylabel_style = {'size': 8}\n",
    "    \n",
    "    # Add map features from cartopy\n",
    "    ax.add_feature(cfeature.NaturalEarthFeature('physical', 'land', '10m', \n",
    "                                                edgecolor='face', \n",
    "                                                facecolor='lightgray'))\n",
    "    ax.add_feature(cfeature.NaturalEarthFeature('physical', 'rivers_lake_centerlines', '10m', \n",
    "                                                edgecolor='darkblue', \n",
    "                                                facecolor='none'))\n",
    "    ax.coastlines(linewidth=1)\n",
    "    \n",
    "    if zoom is not None:\n",
    "        plt.xlim(zoom[0],zoom[2])\n",
    "        plt.ylim(zoom[1],zoom[3])\n",
    "    \n",
    "    # Save figure\n",
    "    imname = f\"{figname}_{dtime.strftime('%b_%d_%Y_%I%p')}_zc{depth:04}m.png\"\n",
    "    impath = f'{dir_name}/{imname}'\n",
    "    if os.path.isfile(impath):\n",
    "        os.remove(impath)\n",
    "    \n",
    "    if show:\n",
    "        if save:\n",
    "            plt.savefig(impath,dpi=300, \n",
    "                    bbox_inches='tight')\n",
    "            # images.append(imageio.imread(imname))\n",
    "        plt.tight_layout()\n",
    "        plt.show()\n",
    "    else:\n",
    "        plt.savefig(impath,dpi=300, \n",
    "                    bbox_inches='tight')\n",
    "        # images.append(imageio.imread(imname))\n",
    "\n",
    "    fig.clear()\n",
    "    plt.close(fig)\n",
    "    plt.clf()\n",
    "    \n",
    "    return impath # Return the path to the saved figure"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25cee5e8-6cc5-4943-98fa-4833f2fbfb76",
   "metadata": {},
   "source": [
    "### Retrieving eReefs Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "65be1553-a819-48c6-806a-5904b7d921b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# The stem of a url where ereefs data will be retrieved\n",
    "base_url = \"http://thredds.ereefs.aims.gov.au/thredds/dodsC/s3://aims-ereefs-public-prod/derived/ncaggregate/ereefs/gbr4_v2/daily-monthly/EREEFS_AIMS-CSIRO_gbr4_v2_hydro_daily-monthly-\"\n",
    "\n",
    "# Choose the variable and depth to plot\n",
    "variable = 'salt' # Salinity data\n",
    "depthIndex = -2 # Depth does from deepest-shallowest, so -1 will be the shallowest layer (i.e. the surface)\n",
    "\n",
    "# Choose the time frame to plot\n",
    "cots_months = [11,12,1,2] # The months where cots larvae breed\n",
    "year_st = 2017 # Starting year (so Dec 2018 for example)\n",
    "\n",
    "# Use indexing to get the month-year .nc files \n",
    "years = []\n",
    "hydrofiles = [] # Empty list where the desired eReefs filenames will be appended\n",
    "for m in range(len(cots_months)): \n",
    "    month = cots_months[m]\n",
    "    if m == 0: # For the first month in our list, the year is the start year\n",
    "        year = year_st\n",
    "        years.append(year)\n",
    "    elif cots_months[m] > cots_months[m-1]:\n",
    "        year = years[m-1]\n",
    "        years.append(year)\n",
    "    else:\n",
    "        year = year_st + 1\n",
    "        years.append(year)\n",
    "    \n",
    "    hydrofile = f\"{base_url}{year}-{month:02}.nc\"\n",
    "    hydrofiles.append(hydrofile)\n",
    "\n",
    "ds_hydro = xr.open_mfdataset(hydrofiles)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5af5ced1-68bf-4db2-acdc-180ab7d5d311",
   "metadata": {},
   "source": [
    "The eReefs files are large, so we slide them to the areas we are mainly interested in"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "91437a72-04fd-488e-b749-3e6a39665512",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Only plot data where high amounts of COTS are found. Here we use the manta-tow COTS data- all the occasions where mean-cot-per-tow was recorded\n",
    "min_lon = df['LONGITUDE'].min() - 1     # lower left longitude\n",
    "min_lat = df['LATITUDE'].min() - 1      # lower left latitude\n",
    "max_lon = df['LONGITUDE'].max() + 1      # upper right longitude\n",
    "max_lat = df['LATITUDE'].max() + 1      # upper right latitude\n",
    "\n",
    "# Defining the boundaries\n",
    "lon_bnds = [min_lon, max_lon]\n",
    "lat_bnds = [min_lat, max_lat]\n",
    "\n",
    "# Depth in metres\n",
    "depthM = ds_hydro.zc.values[depthIndex]\n",
    "\n",
    "# Slicing the grid and only taking the surface dataset (k=-1)\n",
    "ds_hydro_clip = ds_hydro.sel(latitude=slice(*lat_bnds), longitude=slice(*lon_bnds), k=depthIndex)\n",
    "\n",
    "# Dropping unused variables\n",
    "surf_data = ds_hydro_clip.drop(['zc','mean_wspeed','temp',\n",
    "                    'eta','wspeed_u','wspeed_v', \n",
    "                    'mean_cur'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3e8ed1d-aa26-4d23-a71e-7661ddec0ddf",
   "metadata": {},
   "source": [
    "We save our combined and sliced dataset to a netCDF file. Note: the below cell takes ~3 minutes to run. Only re-run this when changing the times or bounds of the area you're looking at."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c99f56cd-f6d6-44f8-9b2c-1fe7b00517e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_name =f'ereefdata_{depthM}m.nc' # The name of the combined .nc grid of all the months of salinity data combined\n",
    "\n",
    "# Remove a previously saved netcdf file if needed\n",
    "try:\n",
    "    os.remove(data_name)\n",
    "except OSError:\n",
    "    pass\n",
    "\n",
    "# Save to netcdf file\n",
    "surf_data.to_netcdf(path=data_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4395e357-5dc0-408d-b1f7-d18287e4e4ef",
   "metadata": {},
   "source": [
    "Plot the netcdf grids and create an animation of the change over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "aa7d18e2-57d3-441d-9132-fb7f7713a5c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read in netCDF grid (created above)\n",
    "ncdata = nc.Dataset(data_name, 'r')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "967ca4f0-87ed-47af-bc39-67df5b03f1f0",
   "metadata": {},
   "source": [
    "### Plot salinity and create animation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1f9e357-b225-44cc-acd0-7ba2d4920e41",
   "metadata": {},
   "source": [
    "Now we will loop over all the times in the netcdf data and create an image of the salinity. We then combine these into a gif animation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32efedab-412e-4cd7-85b6-7af902c0020d",
   "metadata": {},
   "outputs": [],
   "source": [
    "color = cmocean.cm.haline # Custom colour paletter for salinity\n",
    "extent = [26,35] # Salinity extent\n",
    "size = (9, 10) # Figsize\n",
    "\n",
    "time = ncdata.variables['time']\n",
    "images = []\n",
    "\n",
    "# Loop over each day and create a plot of the salinity\n",
    "for t in range(len(time)):\n",
    "    im = ereefs_map(ncdata, t, depthIndex, variable, extent, color, size, figname='salinity', show=False)\n",
    "    images.append(imageio.v2.imread(im)) # Append each image created to a list for conversion into animation\n",
    "\n",
    "# Convert images to animation\n",
    "animation_name = f'{variable}_{depthM}m_{str(year_st)}_{str(year_st+1)}_months_{cots_months[0]}_to_{cots_months[-1]}.gif'\n",
    "animation_path = f'{dir_name}/{animation_name}'\n",
    "if os.path.isfile(animation_path):\n",
    "    os.remove(animation_path)\n",
    "imageio.mimwrite(animation_path,images)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2355cdcd-0583-452e-b203-1e1aa0613e45",
   "metadata": {},
   "source": [
    "## Tracking with parcels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "994cd1cc-a6e3-4a11-9e24-3162deecdf43",
   "metadata": {},
   "source": [
    "### Setting up parcels tracking"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "742258f8-59fe-4024-b6fc-f0bc42d41327",
   "metadata": {},
   "source": [
    "We take our netcdf eReefs data and prime it for use in parcels tracking. For more details on these steps, please refer to the tutorials on the Ocean Parcels website."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b093a3a6-2a9e-41e5-b033-ff2b28e59fdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a function to delete particles that go out of bounds\n",
    "def DeleteParticle(particle, fieldset, time):\n",
    "     particle.delete()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "78a8ca17-d75b-46af-bb74-b61bd46d51c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "filenames = {'U': data_name,\n",
    "             'V': data_name,\n",
    "            }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4b67a04e-8ed1-4dff-a437-2b2fb7be19b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "variables = {'U': 'u',\n",
    "             'V': 'v',\n",
    "            }\n",
    "\n",
    "dimensions = {'lat': 'latitude',\n",
    "              'lon': 'longitude',\n",
    "              'time': 'time'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "bc25a537-9555-419d-9eea-46b40621bd5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "fieldset = FieldSet.from_netcdf(filenames, variables, dimensions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "bfc704ed-364e-4869-81c7-70fa6b8a3d4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "filenames = {'lat': data_name,\n",
    "             'lon': data_name,\n",
    "             'data': data_name}\n",
    "\n",
    "variable = ('S', 'salt')\n",
    "\n",
    "dimensions = {'lat': 'latitude',\n",
    "              'lon': 'longitude',\n",
    "              'time': 'time'}\n",
    "\n",
    "field = Field.from_netcdf(filenames, variable, dimensions)\n",
    "fieldset.add_field(field)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "92cb4613-ac0e-430d-b107-89fdabc1c667",
   "metadata": {},
   "outputs": [],
   "source": [
    "class SampleParticle(JITParticle):          # Define a new particle class\n",
    "    t = Variable('s', initial=fieldset.S)  # Variable 't' initialised by sampling the temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7d5adc46-77a3-4634-9c5f-c428fd8e2a19",
   "metadata": {},
   "outputs": [],
   "source": [
    "def SampleS(particle, fieldset, time):  # Custom function that samples fieldset2.T at particle location\n",
    "    particle.s = fieldset.S[time, particle.depth, particle.lat, particle.lon]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0df44c0a-de0e-4f8b-9e65-da4921c30e6f",
   "metadata": {},
   "source": [
    "### Plotting Parcel Tracking"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f51a4dee-bb8a-446b-8183-e3bbf8ca5f47",
   "metadata": {},
   "source": [
    "Define a function that plots the particle tracks through time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "09d58305-237b-4a41-bc6f-cce15b50b9ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_parcels(output_nc, start_lons, start_lats, reef_names, variable='salinity',dt='backwards',start_date='unknown_start', end_date='unknown_end', depth='unknown'):\n",
    "    print('Plotting Parcels')\n",
    "    \n",
    "    parcels = xr.open_dataset(output_nc)\n",
    "    \n",
    "    # Figure size\n",
    "    size = (9, 12)\n",
    "\n",
    "    # Color from cmocean\n",
    "    color = cmocean.cm.speed\n",
    "\n",
    "    # Defining the figure\n",
    "    fig = plt.figure(figsize=size, facecolor='w', edgecolor='k')\n",
    "\n",
    "    # Axes with Cartopy projection\n",
    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "    \n",
    "    # Extent\n",
    "    # min_lon=df['LONGITUDE'].min()\n",
    "    # max_lon=df['LONGITUDE'].max()\n",
    "    # min_lat=df['LATITUDE'].min()\n",
    "    # max_lat=df['LATITUDE'].max()\n",
    "    \n",
    "    min_lon=143\n",
    "    max_lon=149\n",
    "    min_lat=-21\n",
    "    max_lat=-10\n",
    "    ax.set_extent([min_lon, max_lon, min_lat, max_lat], ccrs.PlateCarree())\n",
    "\n",
    "    # Plotting using Matplotlib \n",
    "    # We plot the PH at the surface at the final recorded time interval\n",
    "    cf = ds_hydro_clip.mean_cur.isel(time=10).plot( \n",
    "        transform=ccrs.PlateCarree(), cmap=color,\n",
    "        vmin = 0.1, vmax = 1.0, alpha=0.2, \n",
    "        add_colorbar=False\n",
    "    )\n",
    "\n",
    "    # Color bar\n",
    "    cbar = fig.colorbar(cf, ax=ax, fraction=0.027, pad=0.045, \n",
    "                        orientation=\"horizontal\")\n",
    "    cbar.set_label(ds_hydro_clip.mean_cur.long_name+' '+ds_hydro_clip.mean_cur.units, rotation=0, labelpad=5, fontsize=10)\n",
    "    cbar.ax.tick_params(labelsize=8)\n",
    "\n",
    "    # Title\n",
    "    plt.title(f'Parcels {dt} evolution coloured by salinity',fontsize=13)\n",
    "\n",
    "    # Plot lat/lon grid \n",
    "    gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True,linewidth=0.1, color='k', alpha=1,linestyle='--')\n",
    "    gl.top_labels = False\n",
    "    gl.right_labels = False\n",
    "    gl.xformatter = LONGITUDE_FORMATTER\n",
    "    gl.yformatter = LATITUDE_FORMATTER\n",
    "    gl.xlabel_style = {'size': 8}\n",
    "    gl.ylabel_style = {'size': 8} \n",
    "    \n",
    "    ## Add GBR Shapefile\n",
    "    ax.add_feature(cartopy.feature.ShapelyFeature(shpreader.Reader('datasets/Shapefiles/GBR_Features.shp').geometries(), \n",
    "                                                   ccrs.PlateCarree(), facecolor=\"lightgrey\", edgecolor='black', lw=0.5))\n",
    "\n",
    "    # Add map features with Cartopy \n",
    "    ax.add_feature(cfeature.NaturalEarthFeature('physical', 'land', '10m', \n",
    "                                                edgecolor='face', \n",
    "                                                facecolor='lightgray'))\n",
    "    ax.add_feature(cfeature.NaturalEarthFeature('physical', 'rivers_lake_centerlines', '10m', \n",
    "                                                    edgecolor='darkblue', \n",
    "                                                    facecolor='none'))\n",
    "    ax.coastlines(linewidth=1)\n",
    "    \n",
    "    # Colour palette extents\n",
    "    distmin = 26.0\n",
    "    distmax = parcels.s.max().item()\n",
    "\n",
    "    # To distinguish different parcel tracks, we loop over different marker styles for each track\n",
    "    mStyles = [\"o\",\"v\",\"^\",\"<\",\">\",\"8\",\"s\",\"p\",\"P\",\"*\",\"h\",\"H\",\"X\",\"D\",\"d\"] # List of markerstykles to loop through\n",
    "    m = itertools.cycle(mStyles)\n",
    "    \n",
    "    # The forwards modelling has many potential starting points, so we only plot 1 in 5 starting points (for clarity)\n",
    "    if dt == \"forwards\":\n",
    "        divider=5\n",
    "    elif dt == \"backwards\":\n",
    "        divider=1\n",
    "    \n",
    "    for k in range(parcels.lon.shape[0]):\n",
    "        if (k % divider == 0):\n",
    "            mark = next(m) # Get next marker style\n",
    "            sc = plt.scatter(parcels.lon.isel(trajectory=k), parcels.lat.isel(trajectory=k), s=60, marker=mark, c=parcels.s.isel(trajectory=k), edgecolors='k',cmap=cmocean.cm.haline, vmin=distmin, vmax=distmax, linewidth=0.2, transform=ccrs.PlateCarree()).set_zorder(11)\n",
    "            start_lon = parcels.lon.values[k][0]\n",
    "            start_lat = parcels.lat.values[k][0]\n",
    "            start_sal = parcels.s.values[k][0]\n",
    "            plt.scatter(start_lon, start_lat, s=80, marker=mark, facecolor='none', edgecolors='black',cmap=cmocean.cm.haline, vmin=distmin, vmax=distmax, linewidth=1, transform=ccrs.PlateCarree(), zorder=12)\n",
    "    \n",
    "    # Color bar\n",
    "    norm = mpl.colors.Normalize(vmin=distmin,vmax=distmax)\n",
    "    sc = plt.cm.ScalarMappable(cmap=cmocean.cm.haline, norm=norm)\n",
    "    \n",
    "    cbar2 = plt.colorbar(sc, ax=ax, fraction=0.027, pad=0.045)\n",
    "    cbar2.set_label('Surface salinity in PSU', rotation=90, labelpad=5, fontsize=10)\n",
    "    cbar2.ax.tick_params(labelsize=8)\n",
    "\n",
    "    # Plot towns\n",
    "    plot_town(townname='cairns')\n",
    "    # plot_town(townname='rockhampton')\n",
    "    plot_town(townname='bowen')\n",
    "\n",
    "    # Annotate times\n",
    "    date_st = parcels['time'][0].min(skipna=True).dt.strftime('%b %d %Y %I%p').item()\n",
    "    date_ed = parcels['time'].max(skipna=True).dt.strftime('%b %d %Y %I%p').item()\n",
    "    \n",
    "    if dt=='backwards':\n",
    "        plt.text(min_lon+0.3, min_lat+0.4, f\"Start time: {date_ed}\")\n",
    "        plt.text(min_lon+0.3, min_lat+0.2, f\"End time: {date_st}\")\n",
    "    else:\n",
    "        plt.text(min_lon+0.3, min_lat+0.4, f\"Start time: {date_st}\")\n",
    "        plt.text(min_lon+0.3, min_lat+0.2, f\"End time: {date_ed}\")\n",
    "        \n",
    "    # Add depth value\n",
    "    plt.text(max_lon-1.2, max_lat-0.6, f\"Depth: {depth}m\")\n",
    "    \n",
    "    # Plot starting positions with a thick pen outline for prominence\n",
    "    for i in range(len(highCOTS)):\n",
    "        if highCOTS['LONGITUDE'][i] < min_lon or highCOTS['LONGITUDE'][i] > max_lon or highCOTS['LATITUDE'][i] < min_lat or highCOTS['LATITUDE'][i] > max_lat:\n",
    "            continue # Skip if falls outside the extent\n",
    "        if dt==\"forwards\":\n",
    "            plt.plot(highCOTS['LONGITUDE'][i], highCOTS['LATITUDE'][i], color='red', linewidth=4, marker='X', mec='black', mew=0.5, ms=15, transform=ccrs.PlateCarree(), zorder=14)\n",
    "        plt.text(highCOTS['LONGITUDE'][i]+(0.2), highCOTS['LATITUDE'][i]+(np.cbrt(np.sin(i))/3), highCOTS['REEF_NAME'][i], horizontalalignment='left', transform=ccrs.PlateCarree(), zorder=12)\n",
    "    \n",
    "    # Save the figure\n",
    "    figname = f\"{variable}_{depth}m_{dt}_{start_date}.png\"\n",
    "    if os.path.isfile(f\"{parcels_figs}/{figname}\"):\n",
    "        os.remove(f\"{parcels_figs}/{figname}\")\n",
    "        \n",
    "    plt.savefig(f\"{parcels_figs}/{figname}\", dpi=300,bbox_inches='tight')\n",
    "    plt.tight_layout()\n",
    "    # plt.show()\n",
    "\n",
    "    fig.clear()\n",
    "    plt.close(fig)\n",
    "    plt.clf()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e35c5d3c-d975-4d02-bd4d-1ae6bfb1001a",
   "metadata": {},
   "source": [
    "### Forward modelling"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5f8b5e4-28e6-4bf7-90e6-76117e53f505",
   "metadata": {},
   "source": [
    "According to Maria Byrne and Matthew Clements, the reefs North of Cairns are initiation reefs for Bippannaria (COTS larvae). To compile a list of potential starting points for forward modelling, let's use the reefs sampled in the manta-tow data that have a latitude higher than that of Cairns at -16.92 degrees."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e35560f2-85f4-4e1d-ab27-4fd419d0b918",
   "metadata": {},
   "outputs": [],
   "source": [
    "north_reefs = df[df['LATITUDE'] > -16.91].groupby('REEF_NAME')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f8f2fb4a-3662-433c-a89c-ed0825806b12",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Group all northern reefs by reef name and append their lat, lon and name to a list\n",
    "north_lats = []\n",
    "north_lons = []\n",
    "north_names = []\n",
    "for key, group in north_reefs:\n",
    "    # Because each group will have the same lat and lon for each entry, let's retrieve it by taking the first index from a list\n",
    "    reef_lat = round(list(group['LATITUDE'])[0], 4)\n",
    "    reef_lon = round(list(group['LONGITUDE'])[0], 4)\n",
    "    #print(f\"{key} has latitude {reef_lat} and longitude {reef_lon}\")\n",
    "    \n",
    "    north_lats.append(reef_lat)\n",
    "    north_lons.append(reef_lon)\n",
    "    north_names.append(key)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4ed576d-3946-4f1f-a2cb-3ea691f3251e",
   "metadata": {},
   "source": [
    "Choose the start times for the model. Parcels wants this in seconds and the runtime can't exceed the data timeframe, so this requires a bit of calculation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "63f2f9c3-f577-4ff5-a9e6-d8ade05ff81a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Earliest time for this dataset is 2017-10-31 14:00:00\n",
      "\n",
      "Latest time for this dataset is 2018-02-27 14:00:00\n",
      "\n",
      "Adjust the cell below to change the forward modelling start time\n"
     ]
    }
   ],
   "source": [
    "# Remember in the setting up parcels section, 'time' was defined as the time variable for ncdata\n",
    "calendar_time = nc.num2date(time[:], units=time.units, calendar=time.calendar)\n",
    "print(f'Earliest time for this dataset is {calendar_time[0]}\\n')\n",
    "print(f'Latest time for this dataset is {calendar_time[-1]}\\n')\n",
    "print('Adjust the cell below to change the forward modelling start time')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9dab90d-bb7d-4233-8581-5a3cc3995ba5",
   "metadata": {},
   "source": [
    "The start date will start parcels tracking at this day and loop through one day at a time until it is 14 days from the end date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e0a0f85e-5f1a-471f-85c9-3a448c72faa2",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_year = 2017\n",
    "start_month = 12\n",
    "start_day = 25\n",
    "\n",
    "end_year = 2018\n",
    "end_month = 2\n",
    "end_day = 27\n",
    "\n",
    "# Convert the above start and end dates to a formatted datetime string\n",
    "start_date=f'{str(start_year)}-{str(start_month)}-{str(start_day)} 14:00:00'\n",
    "start_date = datetime.strptime(start_date, '%Y-%m-%d %H:%M:%S')\n",
    "\n",
    "end_date=f'{str(end_year)}-{str(end_month)}-{str(end_day)} 14:00:00'\n",
    "end_date = datetime.strptime(end_date, '%Y-%m-%d %H:%M:%S')\n",
    "\n",
    "# COTS larvae take 14-22 days to develop and settle, so we run parcels from our start date to 14 days before our end date\n",
    "end_parcels = end_date - dtime.timedelta(days=14)\n",
    "\n",
    "delta = dtime.timedelta(days=1) # Iterate one day at a time\n",
    "\n",
    "times_runtimes = [] # Empty list to add parcels execution info to\n",
    "while start_date <= end_parcels:\n",
    "\n",
    "    time_diff = start_date - calendar_time[0]\n",
    "    time_secs = timedelta.total_seconds(time_diff)\n",
    "    \n",
    "    runtime_secs = timedelta.total_seconds(calendar_time[-1] - start_date)\n",
    "    \n",
    "    times_runtimes.append((time_secs, runtime_secs, start_date, end_date))\n",
    "    start_date += delta"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a3c2f81-f489-4bb5-8cd2-749982885cb9",
   "metadata": {},
   "source": [
    "Run the parcels tracking for the set of times defined above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5147a229",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: Particle initialisation from field can be very slow as it is computed in scipy mode.\n",
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib04afd7eb097087e03e54623c9af4101f_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libc6364cfb93378a1a1908714c02e776ca_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libef944bd93e96669fb0db571989794a81_0.so\n"
     ]
    },
    {
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     "output_type": "stream",
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      "Plotting Parcels\n"
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    },
    {
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     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib19a00b92c04fa7d8a4d4ff9864658dfe_0.so\n"
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      "Plotting Parcels\n"
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      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libfbded54b8acca9efecb41ef37b8ba7d4_0.so\n"
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      "Plotting Parcels\n"
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      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libf39086900fc4ae0022e35c7c4407ff64_0.so\n"
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      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libf4483a3733a9dd417c8e33fbd76d605b_0.so\n"
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      "Plotting Parcels\n"
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      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib1087d92ec6a2ca80978acbeb7424435b_0.so\n"
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      "Plotting Parcels\n"
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      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libb6fc7f8a0a5e5a4fb8aed5ec4364b0f3_0.so\n"
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      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libfebe79e490274a4955998d43e9045acd_0.so\n"
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      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libed8e9ed628bdd1e5d6adc651f78b9188_0.so\n"
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      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib168f72a1ca149ff143add881dbc57eda_0.so\n"
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      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib3516d7417193c9f0fa4ba402c13e4bd5_0.so\n"
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libca9ce70baf71f972fc942be7301ad331_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libdcf61fe914ffd1f5bc56c11c3aed6ce7_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libb09a66000c5d1b6d20696597e0b3775a_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib6e7fe35e0b1bccfe8ccb99f499f314df_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libb03c756617ac8436650867a44986ff68_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib9fd134f10c0d50553ab3de1247b3e130_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libd2de726c7d1b46abfb0f93bce2f8d876_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib076d0f1cfb855b46f2f7481e326af85b_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libb9441a93596209e0984e7e1321479057_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/liba429fcd2123451403d15b2e76c73da4e_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib0b2c33985e65554205f555ae6b8c711a_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib9ee036e8b0ff2ddb6b4ccf9732dec98e_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib844e1ce930e97d29d9d7e19531dc35db_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib84147fde7cc0c6aef8b1f653391b56c8_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib017c58424dc48d93a03b63d51a377c27_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib91836b5613f4294b42e90e916f7b0c56_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib66fe845dafd0e9d4a387fcefb668ee66_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib6ace150c0b29a34b4290a54cfd82096b_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Compiled ArraySampleParticleAdvectionRK4SampleS ==> /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/lib125c108d80edcffabc0038d06b2fab35_0.so\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Parcels\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x1500 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for t in times_runtimes:\n",
    "    time_secs = t[0] # times_runtimes is a list of tuples and the time is the first element of the tuple\n",
    "    runtime_secs = t[1]\n",
    "    start_date = t[2].strftime('%d-%m-%Y')\n",
    "    end_date = t[3].strftime('%d-%m-%Y')\n",
    "\n",
    "    \n",
    "    pset = ParticleSet.from_list(fieldset=fieldset, pclass=SampleParticle,\n",
    "                                 lon=north_lons,   # releasing on a line: the start longitude and latitude\n",
    "                                 lat=north_lats,  # releasing on a line: the end longitude and latitude\n",
    "                                 time=time_secs)\n",
    "    # print('s values before execution:', [p.s for p in pset])\n",
    "    k_sample = pset.Kernel(SampleS)    # Casting the SampleT function to a kernel.\n",
    "    \n",
    "    output_zarr_salinity_forwards = f'{parcels_directory}/SalinityForwards_{start_date}.zarr'\n",
    "    try:\n",
    "        os.remove(output_zarr_salinity_forwards)\n",
    "    except OSError:\n",
    "        pass\n",
    "\n",
    "    output_file_salinity_forwards = pset.ParticleFile(name=output_zarr_salinity_forwards, \n",
    "                                    outputdt=timedelta(hours=12))\n",
    "    \n",
    "    # Execute parcels\n",
    "    pset.execute(AdvectionRK4 + k_sample,    # Add kernels using the + operator.\n",
    "                 runtime=timedelta(seconds=runtime_secs),\n",
    "                 dt=timedelta(minutes=5),\n",
    "                 output_file=output_file_salinity_forwards,\n",
    "                 recovery={ErrorCode.ErrorOutOfBounds: DeleteParticle})\n",
    "    \n",
    "    output_nc_salinity_forwards = f\"{output_zarr_salinity_forwards.rstrip('.zarr')}.nc\"\n",
    "    \n",
    "    parcels_salinity_forwards = xr.open_zarr(output_zarr_salinity_forwards)\n",
    "    \n",
    "    if os.path.isfile(output_nc_salinity_forwards):\n",
    "        os.remove(output_nc_salinity_forwards)\n",
    "    parcels_salinity_forwards.to_netcdf(output_nc_salinity_forwards)\n",
    "    \n",
    "    # Plot the output\n",
    "    plot_parcels(output_nc=output_nc_salinity_forwards, start_lons=north_lons, start_lats=north_lats, reef_names=north_names, variable='salinity',dt='forwards',start_date=start_date, end_date=end_date, depth=depthM)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f04aa839-3904-40b2-95f8-e63f128a5c11",
   "metadata": {},
   "source": [
    "### Backwards Modelling"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb48df53-025b-465d-b05c-b2de2fef7aeb",
   "metadata": {},
   "source": [
    "For backwards modelling we start at the COTS outbreak period and go back 22 days from there"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4f09d9d0-cf2b-44e4-a72c-5939924e290f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[146.516667, 146.55, 152.475, 146.883333]\n"
     ]
    }
   ],
   "source": [
    "start_lons_backwards = list(highCOTS['LONGITUDE'])\n",
    "start_lats_backwards = list(highCOTS['LATITUDE'])\n",
    "names_backwards = list(highCOTS['REEF_NAME'])\n",
    "print(start_lons_backwards)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3058bc4-52be-458d-ae48-4fce2cd196f1",
   "metadata": {},
   "source": [
    "Choose the start times for the model. Parcels wants this in seconds and the runtime can't exceed the data timeframe, so this requires a bit of calculation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "44562b1d-c008-4fc3-9dc9-37cae3e08df8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Earliest time for this dataset is 2017-10-31 14:00:00\n",
      "\n",
      "Latest time for this dataset is 2018-02-27 14:00:00\n",
      "\n",
      "Adjust the cell below to change the backward modelling end time\n"
     ]
    }
   ],
   "source": [
    "time = ncdata.variables['time']\n",
    "\n",
    "# Remember in the setting up parcels section, 'time' was defined as the time variable for ncdata\n",
    "calendar_time = nc.num2date(time[:], units=time.units, calendar=time.calendar)\n",
    "print(f'Earliest time for this dataset is {calendar_time[0]}\\n')\n",
    "print(f'Latest time for this dataset is {calendar_time[-1]}\\n')\n",
    "print('Adjust the cell below to change the backward modelling end time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7892c199-5362-431b-bdb0-b0229ce377c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_year = 2018\n",
    "start_month = 2\n",
    "start_day = 27\n",
    "\n",
    "end_year = 2018\n",
    "end_month = 2\n",
    "end_day = 1\n",
    "\n",
    "\n",
    "start_date=f'{str(start_year)}-{str(start_month)}-{str(start_day)} 14:00:00'\n",
    "start_date = datetime.strptime(start_date, '%Y-%m-%d %H:%M:%S')\n",
    "\n",
    "end_date=f'{str(end_year)}-{str(end_month)}-{str(end_day)} 14:00:00'\n",
    "end_date = datetime.strptime(end_date, '%Y-%m-%d %H:%M:%S')\n",
    "# start_date = dtime.date(start_year, start_month, start_day)\n",
    "# end_date = dtime.date(end_year, end_month, end_day)\n",
    "\n",
    "# COTS larvae take 14-22 days to develop and settle, so we run parcels back 22 days from various start dates\n",
    "end_parcels = end_date - dtime.timedelta(days=22)\n",
    "\n",
    "delta = dtime.timedelta(days=1)\n",
    "\n",
    "times_runtimes = []\n",
    "while start_date >= end_date:\n",
    "\n",
    "    time_diff = start_date - calendar_time[0]\n",
    "    time_secs = timedelta.total_seconds(time_diff)\n",
    "    \n",
    "    runtime_secs = timedelta.total_seconds(dtime.timedelta(days=22))\n",
    "    \n",
    "    if start_date - dtime.timedelta(days=22) < calendar_time[0]:\n",
    "        print('Runtime goes to before the start of the dataset')\n",
    "    \n",
    "    times_runtimes.append((time_secs, runtime_secs, start_date, end_date))\n",
    "    start_date -= delta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "f770b232-e519-4b1f-a77f-41e2e04b7a5f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: Particle initialisation from field can be very slow as it is computed in scipy mode.\n"
     ]
    },
    {
     "ename": "RuntimeError",
     "evalue": "Error during compilation:\nCompilation command: x86_64-apple-darwin13.4.0-clang -Wall -fPIC -std=gnu11 -I/Users/jono/opt/anaconda3/envs/envi5809/lib/python3.10/site-packages/parcels/include -I. -g -O3 -DDOUBLE_COORD_VARIABLES -m64 -o /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libd7c98a16c7eebb3443bd008d2a035083_0.so /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/d7c98a16c7eebb3443bd008d2a035083_0.c -shared -lm -m64\nSource/Destination file: /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/d7c98a16c7eebb3443bd008d2a035083_0.c\nLog file: /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/d7c98a16c7eebb3443bd008d2a035083_0.log\n\nLog output: ld: unsupported tapi file type '!tapi-tbd' in YAML file '/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk/usr/lib/libm.tbd' for architecture x86_64\nclang-12: error: linker command failed with exit code 1 (use -v to see invocation)\n\nIf you are on macOS, it might help to type 'export CC=gcc'\n\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mCalledProcessError\u001b[0m                        Traceback (most recent call last)",
      "File \u001b[0;32m~/opt/anaconda3/envs/envi5809/lib/python3.10/site-packages/parcels/compilation/codecompiler.py:228\u001b[0m, in \u001b[0;36mCCompiler._create_compile_process_\u001b[0;34m(self, cmd, src, log)\u001b[0m\n\u001b[1;32m    227\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 228\u001b[0m     \u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcheck_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcmd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstdout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlogfile\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstderr\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlogfile\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    229\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m:\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/envi5809/lib/python3.10/subprocess.py:369\u001b[0m, in \u001b[0;36mcheck_call\u001b[0;34m(*popenargs, **kwargs)\u001b[0m\n\u001b[1;32m    368\u001b[0m         cmd \u001b[38;5;241m=\u001b[39m popenargs[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m--> 369\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m CalledProcessError(retcode, cmd)\n\u001b[1;32m    370\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n",
      "\u001b[0;31mCalledProcessError\u001b[0m: Command '['x86_64-apple-darwin13.4.0-clang', '-Wall', '-fPIC', '-std=gnu11', '-I/Users/jono/opt/anaconda3/envs/envi5809/lib/python3.10/site-packages/parcels/include', '-I.', '-g', '-O3', '-DDOUBLE_COORD_VARIABLES', '-m64', '-o', '/var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libd7c98a16c7eebb3443bd008d2a035083_0.so', '/var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/d7c98a16c7eebb3443bd008d2a035083_0.c', '-shared', '-lm', '-m64']' returned non-zero exit status 1.",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[0;32mIn [32], line 24\u001b[0m\n\u001b[1;32m     19\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[1;32m     21\u001b[0m output_file_salinity_backwards \u001b[38;5;241m=\u001b[39m pset\u001b[38;5;241m.\u001b[39mParticleFile(name\u001b[38;5;241m=\u001b[39moutput_zarr_salinity_backwards, \n\u001b[1;32m     22\u001b[0m                                 outputdt\u001b[38;5;241m=\u001b[39mtimedelta(hours\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m12\u001b[39m))\n\u001b[0;32m---> 24\u001b[0m \u001b[43mpset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute\u001b[49m\u001b[43m(\u001b[49m\u001b[43mAdvectionRK4\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mk_sample\u001b[49m\u001b[43m,\u001b[49m\u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# Add kernels using the + operator.\u001b[39;49;00m\n\u001b[1;32m     25\u001b[0m \u001b[43m             \u001b[49m\u001b[43mruntime\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimedelta\u001b[49m\u001b[43m(\u001b[49m\u001b[43mseconds\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mruntime_secs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     26\u001b[0m \u001b[43m             \u001b[49m\u001b[43mdt\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43mtimedelta\u001b[49m\u001b[43m(\u001b[49m\u001b[43mminutes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     27\u001b[0m \u001b[43m             \u001b[49m\u001b[43moutput_file\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_file_salinity_backwards\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     28\u001b[0m \u001b[43m             \u001b[49m\u001b[43mrecovery\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[43mErrorCode\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mErrorOutOfBounds\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mDeleteParticle\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     30\u001b[0m output_nc_salinity_backwards \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00moutput_zarr_salinity_backwards\u001b[38;5;241m.\u001b[39mrstrip(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m.zarr\u001b[39m\u001b[38;5;124m'\u001b[39m)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.nc\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     32\u001b[0m parcels_salinity_backwards \u001b[38;5;241m=\u001b[39m xr\u001b[38;5;241m.\u001b[39mopen_zarr(output_zarr_salinity_backwards)\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/envi5809/lib/python3.10/site-packages/parcels/particleset/baseparticleset.py:340\u001b[0m, in \u001b[0;36mBaseParticleSet.execute\u001b[0;34m(self, pyfunc, pyfunc_inter, endtime, runtime, dt, moviedt, recovery, output_file, movie_background_field, verbose_progress, postIterationCallbacks, callbackdt)\u001b[0m\n\u001b[1;32m    338\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkernel\u001b[38;5;241m.\u001b[39mremove_lib()\n\u001b[1;32m    339\u001b[0m         cppargs \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m-DDOUBLE_COORD_VARIABLES\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcollection\u001b[38;5;241m.\u001b[39mlonlatdepth_dtype \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m--> 340\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkernel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompile\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcompiler\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mGNUCompiler\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcppargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcppargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mincdirs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mget_package_dir\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43minclude\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m.\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    341\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkernel\u001b[38;5;241m.\u001b[39mload_lib()\n\u001b[1;32m    343\u001b[0m \u001b[38;5;66;03m# Set up the interaction kernel(s) if not set and given.\u001b[39;00m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/envi5809/lib/python3.10/site-packages/parcels/kernel/basekernel.py:253\u001b[0m, in \u001b[0;36mBaseKernel.compile\u001b[0;34m(self, compiler)\u001b[0m\n\u001b[1;32m    251\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msrc_file \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    252\u001b[0m             all_files_array\u001b[38;5;241m.\u001b[39mappend(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msrc_file)\n\u001b[0;32m--> 253\u001b[0m         \u001b[43mcompiler\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompile\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msrc_file\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlib_file\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog_file\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    254\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(all_files_array) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m    255\u001b[0m     logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCompiled \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m ==> \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlib_file))\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/envi5809/lib/python3.10/site-packages/parcels/compilation/codecompiler.py:292\u001b[0m, in \u001b[0;36mGNUCompiler_SS.compile\u001b[0;34m(self, src, obj, log)\u001b[0m\n\u001b[1;32m    289\u001b[0m lib_pathdir \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mdirname(obj)\n\u001b[1;32m    290\u001b[0m obj \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(lib_pathdir, lib_pathfile)\n\u001b[0;32m--> 292\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mGNUCompiler_SS\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompile\u001b[49m\u001b[43m(\u001b[49m\u001b[43msrc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mobj\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlog\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/envi5809/lib/python3.10/site-packages/parcels/compilation/codecompiler.py:270\u001b[0m, in \u001b[0;36mCCompiler_SS.compile\u001b[0;34m(self, src, obj, log)\u001b[0m\n\u001b[1;32m    268\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(log, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mw\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m logfile:\n\u001b[1;32m    269\u001b[0m     logfile\u001b[38;5;241m.\u001b[39mwrite(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCompiling: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(cc))\n\u001b[0;32m--> 270\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_create_compile_process_\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msrc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlog\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/opt/anaconda3/envs/envi5809/lib/python3.10/site-packages/parcels/compilation/codecompiler.py:244\u001b[0m, in \u001b[0;36mCCompiler._create_compile_process_\u001b[0;34m(self, cmd, src, log)\u001b[0m\n\u001b[1;32m    234\u001b[0m                 \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(log, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m logfile2:\n\u001b[1;32m    235\u001b[0m                     err \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\"\"\u001b[39m\u001b[38;5;124mError during compilation:\u001b[39m\n\u001b[1;32m    236\u001b[0m \u001b[38;5;124mCompilation command: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\n\u001b[1;32m    237\u001b[0m \u001b[38;5;124mSource/Destination file: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    242\u001b[0m \n\u001b[1;32m    243\u001b[0m \u001b[38;5;124m\"\"\"\u001b[39m \u001b[38;5;241m%\u001b[39m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(cmd), src, logfile\u001b[38;5;241m.\u001b[39mname, logfile2\u001b[38;5;241m.\u001b[39mread())\n\u001b[0;32m--> 244\u001b[0m                 \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(err)\n\u001b[1;32m    245\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
      "\u001b[0;31mRuntimeError\u001b[0m: Error during compilation:\nCompilation command: x86_64-apple-darwin13.4.0-clang -Wall -fPIC -std=gnu11 -I/Users/jono/opt/anaconda3/envs/envi5809/lib/python3.10/site-packages/parcels/include -I. -g -O3 -DDOUBLE_COORD_VARIABLES -m64 -o /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/libd7c98a16c7eebb3443bd008d2a035083_0.so /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/d7c98a16c7eebb3443bd008d2a035083_0.c -shared -lm -m64\nSource/Destination file: /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/d7c98a16c7eebb3443bd008d2a035083_0.c\nLog file: /var/folders/hp/drslwmbd3r7502z1wfd_w7bw0000gr/T/parcels-504/d7c98a16c7eebb3443bd008d2a035083_0.log\n\nLog output: ld: unsupported tapi file type '!tapi-tbd' in YAML file '/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk/usr/lib/libm.tbd' for architecture x86_64\nclang-12: error: linker command failed with exit code 1 (use -v to see invocation)\n\nIf you are on macOS, it might help to type 'export CC=gcc'\n\n"
     ]
    }
   ],
   "source": [
    "for t in times_runtimes:\n",
    "    time_secs = t[0] # times_runtimes is a list of tuples and the time is the first element of the tuple\n",
    "    runtime_secs = t[1]\n",
    "    start_date = t[2].strftime('%d-%m-%Y')\n",
    "    end_date = t[3].strftime('%d-%m-%Y')\n",
    "\n",
    "    \n",
    "    pset = ParticleSet.from_list(fieldset=fieldset, pclass=SampleParticle,\n",
    "                                 lon=start_lons_backwards,   # releasing on a line: the start longitude and latitude\n",
    "                                 lat=start_lats_backwards,  # releasing on a line: the end longitude and latitude\n",
    "                                 time=time_secs)\n",
    "    # print('s values before execution:', [p.s for p in pset])\n",
    "    k_sample = pset.Kernel(SampleS)    # Casting the SampleT function to a kernel.\n",
    "    \n",
    "    output_zarr_salinity_backwards = f'{parcels_directory}/SalinityBackwards_{start_date}.zarr'\n",
    "    try:\n",
    "        os.remove(output_zarr_salinity_backwards)\n",
    "    except OSError:\n",
    "        pass\n",
    "\n",
    "    output_file_salinity_backwards = pset.ParticleFile(name=output_zarr_salinity_backwards, \n",
    "                                    outputdt=timedelta(hours=12))\n",
    "\n",
    "    pset.execute(AdvectionRK4 + k_sample,    # Add kernels using the + operator.\n",
    "                 runtime=timedelta(seconds=runtime_secs),\n",
    "                 dt=-timedelta(minutes=5),\n",
    "                 output_file=output_file_salinity_backwards,\n",
    "                 recovery={ErrorCode.ErrorOutOfBounds: DeleteParticle})\n",
    "    \n",
    "    output_nc_salinity_backwards = f\"{output_zarr_salinity_backwards.rstrip('.zarr')}.nc\"\n",
    "    \n",
    "    parcels_salinity_backwards = xr.open_zarr(output_zarr_salinity_backwards)\n",
    "    \n",
    "    if os.path.isfile(output_nc_salinity_backwards):\n",
    "        os.remove(output_nc_salinity_backwards)\n",
    "    parcels_salinity_backwards.to_netcdf(output_nc_salinity_backwards)\n",
    "    \n",
    "    plot_parcels(output_nc=output_nc_salinity_backwards, start_lons=start_lons_backwards, start_lats=start_lats_backwards, reef_names=names_backwards, variable='salinity',dt='backwards',start_date=start_date, end_date=end_date, depth=depthM)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e573a708-1f8d-49bf-9c48-514183ee4e31",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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