HeatMapWithTime

In this example we show the basic usage of the HeatMapWithTime plugin.

Data

We generate a random set of points with lat/lon coordinates to draw on the map, and then move these points slowly in a random direction to simulate a time dimension. The points are arranged into a list of sets of data to draw.

import numpy as np

np.random.seed(3141592)
initial_data = np.random.normal(size=(100, 2)) * np.array([[1, 1]]) + np.array(
    [[48, 5]]
)

move_data = np.random.normal(size=(100, 2)) * 0.01

data = [(initial_data + move_data * i).tolist() for i in range(100)]

Weights

In order to control intensity shown on the map, each data entry needs to have a weight. Which should be between 0 and 1. Below we generate weights randomly such that intensity increases over time.

time_ = 0
N = len(data)
itensify_factor = 30
for time_entry in data:
    time_ = time_+1
    for row in time_entry:
        weight = min(np.random.uniform()*(time_/(N))*itensify_factor, 1)
        row.append(weight)

m = folium.Map([48.0, 5.0], zoom_start=6)

hm = folium.plugins.HeatMapWithTime(data)

hm.add_to(m)

m

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Options

Now we show that the time index can be specified, allowing a more meaningful representation of what the time steps mean. We also enable the ‘auto_play’ option and change the maximum opacity. See the documentation for a full list of options that can be used.

from datetime import datetime, timedelta

time_index = [
    (datetime.now() + k * timedelta(1)).strftime("%Y-%m-%d") for k in range(len(data))
]

m = folium.Map([48.0, 5.0], zoom_start=6)

hm = folium.plugins.HeatMapWithTime(data, index=time_index, auto_play=True, max_opacity=0.3)

hm.add_to(m)

m

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