{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "[](https://demo.leafmap.org/lab/index.html?path=maplibre/add_image_generated.ipynb)\n", "[](https://colab.research.google.com/github/opengeos/leafmap/blob/master/docs/maplibre/add_image_generated.ipynb)\n", "[](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": [ "" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.11.9" } }, "nbformat": 4, "nbformat_minor": 4 }