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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[![image](https://jupyterlite.rtfd.io/en/latest/_static/badge.svg)](https://demo.leafmap.org/lab/index.html?path=maplibre/add_image_generated.ipynb)\n",
    "[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/opengeos/leafmap/blob/master/docs/maplibre/add_image_generated.ipynb)\n",
    "[![image](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/opengeos/leafmap/HEAD)\n",
    "\n",
    "**Add a generated icon to the map**\n",
    "\n",
    "This source code of this example is adapted from the MapLibre GL JS example - [Add a generated icon to the map](https://maplibre.org/maplibre-gl-js/docs/examples/add-image-generated/).\n",
    "\n",
    "Uncomment the following line to install [leafmap](https://leafmap.org) if needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %pip install \"leafmap[maplibre]\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import leafmap.maplibregl as leafmap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To run this notebook, you will need an [API key](https://docs.maptiler.com/cloud/api/authentication-key/) from [MapTiler](https://www.maptiler.com/cloud/). Once you have the API key, you can uncomment the following code block and replace `YOUR_API_KEY` with your actual API key. Then, run the code block code to set the API key as an environment variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import os\n",
    "# os.environ[\"MAPTILER_KEY\"] = \"YOUR_API_KEY\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate the icon data\n",
    "width = 64  # The image will be 64 pixels square\n",
    "height = 64\n",
    "bytes_per_pixel = 4  # Each pixel is represented by 4 bytes: red, green, blue, and alpha\n",
    "data = np.zeros((width, width, bytes_per_pixel), dtype=np.uint8)\n",
    "\n",
    "for x in range(width):\n",
    "    for y in range(width):\n",
    "        data[y, x, 0] = int((y / width) * 255)  # red\n",
    "        data[y, x, 1] = int((x / width) * 255)  # green\n",
    "        data[y, x, 2] = 128  # blue\n",
    "        data[y, x, 3] = 255  # alpha\n",
    "\n",
    "# Flatten the data array\n",
    "flat_data = data.flatten()\n",
    "\n",
    "# Create the image dictionary\n",
    "image_dict = {\n",
    "    \"width\": width,\n",
    "    \"height\": height,\n",
    "    \"data\": flat_data.tolist(),\n",
    "}\n",
    "\n",
    "m = leafmap.Map(center=[0, 0], zoom=1, style=\"streets\")\n",
    "m.add_image(\"gradient\", image_dict)\n",
    "source = {\n",
    "    \"type\": \"geojson\",\n",
    "    \"data\": {\n",
    "        \"type\": \"FeatureCollection\",\n",
    "        \"features\": [\n",
    "            {\"type\": \"Feature\", \"geometry\": {\"type\": \"Point\", \"coordinates\": [0, 0]}}\n",
    "        ],\n",
    "    },\n",
    "}\n",
    "\n",
    "layer = {\n",
    "    \"id\": \"points\",\n",
    "    \"type\": \"symbol\",\n",
    "    \"source\": \"point\",\n",
    "    \"layout\": {\"icon-image\": \"gradient\"},\n",
    "}\n",
    "\n",
    "m.add_source(\"point\", source)\n",
    "m.add_layer(layer)\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](https://i.imgur.com/qWWlnAm.png)"
   ]
  }
 ],
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