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2D Array Heatmap

In this example we will display the 5G network coverage in Germany as a Heatmap.

Get the Data

The data is provided by the german Federal Network Agency on their Downloads page. Here we can get a .gpkg file of the current coverage by technology. This file can be read with the GeoPandas library.

Create the app

With the data downloaded we can now create the app. As the tile server we will use OpenStreetMap. When using OpenStreetMap, make sure to include your app and contact details in the header and insert an attribution to the provider in the map, as per their Tile Usage Policy.

from PyQt6 import QtWidgets, QtCore
import geopandas as gpd
import numpy as np
import pyogrio

import pyqtgraph_gis as pggis
import pyqtgraph as pg

path
"Path/To/File.gpkg"

app = QtWidgets.QApplication([])
w = QtWidgets.QWidget()

# Make sure to enter your app name and contact details when using OpenStreetMap
headers = {
    "User-Agent": "MyMapApp/1.0 (contact: email@example.com)"
}

# Set up window and widgets
w.setWindowTitle("PyQtGraph-GIS Heatmap Example")
layout = QtWidgets.QGridLayout()
w.setLayout(layout)

# Use OpenStreetMap Tile Server
widget = pggis.MapWidget("https://tile.openstreetmap.org/{z}/{x}/{y}.png", headers=headers)

# Read data with GeoPandas
layer_names = [info[0] for info in pyogrio.list_layers(file_path)]
coords_list = []
col = 'nr'  # 5G coverage column in the GPKG

for state in layer_names:
    gdf = gpd.read_file(file_path, layer=state, columns=[col], engine="pyogrio")
    gdf = gdf[gdf[col] > 0].to_crs(epsg=3857)

    # Extract centroids as simple floats
    x = gdf.geometry.centroid.x.values
    y = gdf.geometry.centroid.y.values
    vals = gdf[col].values

    # Append as a single numpy block
    coords_list.append(np.column_stack([x, y, vals]))
    print(f"Processed {state} ({len(x)} points)")

# Final array of all German points
stack = np.vstack(coords_list)

heatmap, xedges, yedges = np.histogram2d(
    stack[:, 0],  # x (longitude in Web Mercator)
    stack[:, 1],  # y (latitude in Web Mercator)
    bins=500,
    weights=stack[:, 2]  # 'nr' values
)

# Create a heatmap image using PyQtGraph's colormap
heatmap_cmap = pg.colormap.get('inferno')
max_val = np.max(heatmap)
img = pg.ImageItem(heatmap)
normalized_data = heatmap / max_val
rgba_image = heatmap_cmap.map(normalized_data, mode='byte')
rgba_image[heatmap == 0, 3] = 0
img.setImage(rgba_image, autoLevel=False)

# Set the correct geographic bounds for the heatmap
rect = QtCore.QRectF(xedges[0], yedges[0], xedges[-1] - xedges[0], yedges[-1] - yedges[0])
img.setRect(rect)
img.setOpacity(0.6)  # Semi-transparent heatmap

# Add the heatmap to the map widget
widget.addItem(img)

layout.addWidget(widget, 0, 0)
w.show()
app.exec()

The result should look like this: Result of the Heatmap Example