{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Model landmask\n\nComparing two simulation runs, with landmask from ocean model and GSHHG\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from datetime import timedelta\n\nfrom opendrift.readers import reader_ROMS_native\nfrom opendrift.models.oceandrift import OceanDrift\n\nlon = 14.75; lat = 68.1\n\no = OceanDrift(loglevel=20)\n\nreader_nordic = reader_ROMS_native.Reader(o.test_data_folder() +\n    '2Feb2016_Nordic_sigma_3d/Nordic-4km_SLEVELS_avg_00_subset2Feb2016.nc')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "First run, with default GSHHG vector landmask\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o.add_reader([reader_nordic])\ntime = reader_nordic.start_time\no.set_config('general:use_auto_landmask', True)\no.seed_elements(lon, lat, radius=3000, number=1000, time=time)\no.run(end_time=reader_nordic.end_time, time_step=1800, time_step_output=3*3600)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Second run, with landmask from ocean model\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o2 = OceanDrift(loglevel=20)\no2.add_reader([reader_nordic])\nlon = 14.75; lat = 68.1\no2.set_config('general:use_auto_landmask', False)\no2.seed_elements(lon, lat, radius=3000, number=1000, time=time)\no2.run(end_time=reader_nordic.end_time, time_step=1800, time_step_output=3*3600)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from matplotlib.colors import ListedColormap\nimport cartopy.feature as cfeature\ncmap = ListedColormap([cfeature.COLORS['water'],\n                       cfeature.COLORS['land']])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\nTo only show the landmask from the model, hide the coastline landmask by doing:\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o2.plot(background='land_binary_mask', hide_landmask=True, cmap=cmap)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Animation illustrating that red particles strand at ocean model land cells, and black particles strand at GSHHG land polygons\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o.animation(compare=o2, background='land_binary_mask', cmap=cmap,\n            legend=['Default GSHHG landmask', 'Ocean model landmask'])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<img src=\"file://gallery/animations/example_model_landmask_0.gif\">\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o.plot(compare=o2, background='land_binary_mask', cmap=cmap,\n       legend=['Default GSHHG landmask', 'Ocean model landmask'])"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.11.6"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}