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   "source": [
    "# Pydeck + Earth Engine: Points FeatureCollection\n",
    "\n",
    "This is an example of using [pydeck](https://pydeck.gl) to visualize a Google Earth Engine `FeatureCollection` of points.\n",
    "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/power-plants"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import required packages:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": null,
   "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": [
    "### Power plants dataset\n",
    "\n",
    "This example uses the [Global Power Plant Database][dataset], which contains location of power plants around the world, as well as metadata of which fuel source is used, and how much energy is created.\n",
    "\n",
    "[dataset]: https://developers.google.com/earth-engine/datasets/catalog/WRI_GPPD_power_plants\n",
    "\n",
    "First we'll render using EarthEngine's native capabilities, then we'll render using pydeck's rich data-driven styling capabilities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the FeatureCollection\n",
    "table = ee.FeatureCollection(\"WRI/GPPD/power_plants\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create color palette\n",
    "fuel_color = ee.Dictionary({\n",
    "  'Coal': '000000',\n",
    "  'Oil': '593704',\n",
    "  'Gas': 'BC80BD',\n",
    "  'Hydro': '0565A6',\n",
    "  'Nuclear': 'E31A1C',\n",
    "  'Solar': 'FF7F00',\n",
    "  'Waste': '6A3D9A',\n",
    "  'Wind': '5CA2D1',\n",
    "  'Geothermal': 'FDBF6F',\n",
    "  'Biomass': '229A00'\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# List of fuels to add to the map\n",
    "fuels = ['Coal', 'Oil', 'Gas', 'Hydro', 'Nuclear', 'Solar', 'Waste',\n",
    "    'Wind', 'Geothermal', 'Biomass']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_style(point):\n",
    "    \"\"\"Computes size from capacity and color from fuel type.\n",
    "    \n",
    "    Args:\n",
    "        - point: (ee.Geometry.Point) A Point\n",
    "        \n",
    "    Returns:\n",
    "        (ee.Geometry.Point): Input point with added style dictionary\n",
    "    \"\"\"\n",
    "    size = ee.Number(point.get('capacitymw')).sqrt().divide(10).add(2)\n",
    "    color = fuel_color.get(point.get('fuel1'))\n",
    "    return point.set('styleProperty', ee.Dictionary({'pointSize': size, 'color': color}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a FeatureCollection out of the power plant data table\n",
    "pp = ee.FeatureCollection(table).map(add_style)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a layer for each fuel type\n",
    "layers = []\n",
    "for fuel in fuels:\n",
    "    layer = EarthEngineLayer(\n",
    "        pp.filter(ee.Filter.eq('fuel1', fuel)).style(styleProperty='styleProperty', neighborhood=50),\n",
    "        id=fuel,\n",
    "        opacity=0.65,\n",
    "    )\n",
    "    layers.append(layer)"
   ]
  },
  {
   "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": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "view_state = pdk.ViewState(latitude=36, longitude=-53, zoom=3)\n",
    "r = pdk.Deck(\n",
    "    layers=layers, \n",
    "    initial_view_state=view_state\n",
    ")\n",
    "r.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Vector rendering\n",
    "\n",
    "To experience the full potential of pydeck, we need to explore rendering the data with vector output. Rendering the data as a vector allows for client-side data driven styling and picking objects to get information on each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fuel_color = {\n",
    "  'Coal': [0, 0, 0],\n",
    "  'Oil': [89, 55, 4],\n",
    "  'Gas': [188, 128, 189],\n",
    "  'Hydro': [5, 101, 166],\n",
    "  'Nuclear': [227, 26, 28],\n",
    "  'Solar': [255, 127, 0],\n",
    "  'Waste': [106, 61, 154],\n",
    "  'Wind': [92, 162, 209],\n",
    "  'Geothermal': [253, 191, 111],\n",
    "  'Biomass': [34, 154, 0],\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "layers = []\n",
    "for fuel in fuels:\n",
    "    layer = EarthEngineLayer(\n",
    "        # Create each layer as consisting of a single fuel type\n",
    "        table.filter(ee.Filter.eq('fuel1', fuel)),\n",
    "        vis_params={},\n",
    "        # Define a custom radius\n",
    "        getRadius='.properties.capacitymw ** 1.35',\n",
    "        lineWidthMinPixels=0.5,\n",
    "        pointRadiusMinPixels=2,\n",
    "        # Use dictionary for color mapping\n",
    "        get_fill_color=fuel_color[fuel],\n",
    "        # Provide a list of extra dataset properties that should be downloaded for rendering\n",
    "        # Without this, only the geometry will be downloaded\n",
    "        selectors=['capacitymw'],\n",
    "        # Render as a vector, instead of as a raster generated on EE's servers\n",
    "        as_vector=True,\n",
    "        id=fuel,\n",
    "        opacity=0.65,\n",
    "    )\n",
    "    layers.append(layer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then just as before, we define a `ViewState` and pass these layers to the `Deck` object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "view_state = pdk.ViewState(latitude=36, longitude=-53, zoom=3)\n",
    "r = pdk.Deck(\n",
    "    layers=layers, \n",
    "    initial_view_state=view_state\n",
    ")\n",
    "r.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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