{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Drift at different depths\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from datetime import datetime, timedelta\nimport numpy as np\nfrom opendrift.models.oceandrift import OceanDrift\n\no = OceanDrift(loglevel=20)  # Set loglevel to 0 for debug information"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Using live data from Thredds\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o.add_readers_from_list([\n    'https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be'])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Adding some diffusion\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o.set_config('drift:horizontal_diffusivity', 10)  # m2/s"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Seed 1000 elements at random depths\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "z = -np.random.rand(2000)*50\no.seed_elements(lon=4.8, lat=60.0, z=z, radius=0, number=2000,\n                time=datetime.utcnow())\n\nprint(o)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Running model\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o.run(duration=timedelta(hours=24), time_step=1800)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Plot results with lines and particles colored by depth\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "print(o)\no.plot(linecolor='z', buffer=.1, show_elements=False, fast=False)\no.animation(color='z', buffer=.1, fast=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<img src=\"file://gallery/animations/example_depth_0.gif\">\n\n"
      ]
    }
  ],
  "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
}