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   "source": [
    "# Pydeck + Earth Engine: ImageCollection Animation\n",
    "\n",
    "This is an example of using [pydeck](https://pydeck.gl) to animate a Google Earth Engine `ImageCollection` object. To install and run this notebook locally, refer to the [Pydeck Earth Engine documentation](https://earthengine-layers.com/docs/developer-guide/pydeck-integration).\n",
    "\n",
    "To see this example online, view the [JavaScript version][js-example].\n",
    "\n",
    "[js-example]: https://earthengine-layers.com/examples/image-collection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import required packages:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pydeck_earthengine_layers import EarthEngineLayer\n",
    "import pydeck as pdk\n",
    "import ee"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Authenticate with Earth Engine\n",
    "\n",
    "Using Earth Engine requires authentication. If you don't have a Google account approved for use with Earth Engine, you'll need to request access. For more information and to sign up, go to https://signup.earthengine.google.com/."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    ee.Initialize()\n",
    "except Exception as e:\n",
    "    ee.Authenticate()\n",
    "    ee.Initialize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GFS Temperature Forecast Dataset\n",
    "\n",
    "This example uses the [Global Forecast System 384-Hour Predicted Atmosphere Data][gfs] dataset, which contains a weather forecast model produced by the National Centers for Environmental Prediction (NCEP)\n",
    "\n",
    "[gfs]: https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the dataset by creating an Earth Engine object that references it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize an ee.ImageColllection object referencing the Global Forecast System dataset\n",
    "image_collection = ee.ImageCollection('NOAA/GFS0P25')\n",
    "\n",
    "# Select images from December 22, 2018\n",
    "image_collection = image_collection.filterDate('2018-12-22', '2018-12-23')\n",
    "\n",
    "# Choose the first 24 images in the ImageCollection\n",
    "image_collection = image_collection.limit(24)\n",
    "\n",
    "# Select a single band to visualize\n",
    "image_collection = image_collection.select('temperature_2m_above_ground')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a `vis_params` object that defines how EarthEngine should style the `ImageCollection`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Style temperature values between -40C and 35C, \n",
    "# with lower values shades of blue, purple, and cyan, \n",
    "# and higher values shades of green, yellow, and red\n",
    "vis_params = {\n",
    "    'min': -40.0,\n",
    "    'max': 35.0,\n",
    "    'palette': ['blue', 'purple', 'cyan', 'green', 'yellow', 'red']\n",
    "};"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a new `EarthEngineLayer` with this dataset that can then be passed to Pydeck."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "layer = EarthEngineLayer(\n",
    "    image_collection,\n",
    "    vis_params,\n",
    "    animate=True,\n",
    "    id=\"global_weather\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then just pass this layer to a `pydeck.Deck` instance, and call `.show()` to create a map:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fc9ad416126540ee90b4a549a794b8d6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "DeckGLWidget(custom_libraries=[{'libraryName': 'EarthEngineLayerLibrary', 'resourceUri': 'https://unpkg.com/@u…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "view_state = pdk.ViewState(latitude=36, longitude=10, zoom=1)\n",
    "r = pdk.Deck(\n",
    "    layers=[layer], \n",
    "    initial_view_state=view_state\n",
    ")\n",
    "r.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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