Point Cloud Layer Example¶

This notebook demonstrates the DeckGL PointCloudLayer for visualizing 3D point data.

Point cloud layers are ideal for:

• LiDAR data visualization
• 3D scanning results
• Elevation data
• Any 3D point dataset

Basic Point Cloud with MapLibre¶

In [ ]:

import random
from anymap_ts import MapLibreMap


# Generate sample 3D point cloud data
def generate_points(center_lng, center_lat, num_points=1000, spread=0.01):
    points = []
    for _ in range(num_points):
        lng = center_lng + random.uniform(-spread, spread)
        lat = center_lat + random.uniform(-spread, spread)
        # Elevation based on distance from center (creates a dome shape)
        dist = ((lng - center_lng) ** 2 + (lat - center_lat) ** 2) ** 0.5
        elevation = max(0, 500 - dist * 50000) + random.uniform(0, 50)
        # Color by elevation (blue to red)
        color_ratio = min(elevation / 500, 1)
        color = [
            int(255 * color_ratio),
            int(100 * (1 - color_ratio)),
            int(255 * (1 - color_ratio)),
            255,
        ]
        points.append({"position": [lng, lat, elevation], "color": color})
    return points


# Generate points around San Francisco
point_cloud = generate_points(-122.4194, 37.7749)

m = MapLibreMap(center=[-122.4194, 37.7749], zoom=14, pitch=60)
m.add_basemap("CartoDB.DarkMatter")
m.add_point_cloud_layer(
    data=point_cloud,
    name="pointcloud-demo",
    get_position="position",
    get_color="color",
    point_size=3,
    opacity=0.9,
)
m

import random from anymap_ts import MapLibreMap # Generate sample 3D point cloud data def generate_points(center_lng, center_lat, num_points=1000, spread=0.01): points = [] for _ in range(num_points): lng = center_lng + random.uniform(-spread, spread) lat = center_lat + random.uniform(-spread, spread) # Elevation based on distance from center (creates a dome shape) dist = ((lng - center_lng) ** 2 + (lat - center_lat) ** 2) ** 0.5 elevation = max(0, 500 - dist * 50000) + random.uniform(0, 50) # Color by elevation (blue to red) color_ratio = min(elevation / 500, 1) color = [ int(255 * color_ratio), int(100 * (1 - color_ratio)), int(255 * (1 - color_ratio)), 255, ] points.append({"position": [lng, lat, elevation], "color": color}) return points # Generate points around San Francisco point_cloud = generate_points(-122.4194, 37.7749) m = MapLibreMap(center=[-122.4194, 37.7749], zoom=14, pitch=60) m.add_basemap("CartoDB.DarkMatter") m.add_point_cloud_layer( data=point_cloud, name="pointcloud-demo", get_position="position", get_color="color", point_size=3, opacity=0.9, ) m

Point Cloud with DeckGLMap¶

In [ ]:

from anymap_ts import DeckGLMap

# Generate larger point cloud
large_cloud = generate_points(-122.4194, 37.7749, num_points=5000, spread=0.02)

m2 = DeckGLMap(center=[-122.4194, 37.7749], zoom=13, pitch=50, bearing=30)
m2.add_basemap("CartoDB.DarkMatter")
m2.add_point_cloud_layer(
    data=large_cloud,
    name="large-cloud",
    get_position="position",
    get_color="color",
    point_size=2,
    size_units="pixels",
    opacity=0.8,
)
m2

from anymap_ts import DeckGLMap # Generate larger point cloud large_cloud = generate_points(-122.4194, 37.7749, num_points=5000, spread=0.02) m2 = DeckGLMap(center=[-122.4194, 37.7749], zoom=13, pitch=50, bearing=30) m2.add_basemap("CartoDB.DarkMatter") m2.add_point_cloud_layer( data=large_cloud, name="large-cloud", get_position="position", get_color="color", point_size=2, size_units="pixels", opacity=0.8, ) m2

Point Cloud with Uniform Color¶

In [ ]:

# Simple point cloud with uniform color
simple_points = [
    {"position": [lng, lat, alt]}
    for lng in [-122.42, -122.41, -122.40, -122.39]
    for lat in [37.77, 37.78, 37.79, 37.80]
    for alt in [0, 100, 200, 300]
]

m3 = MapLibreMap(center=[-122.405, 37.785], zoom=13, pitch=60)
m3.add_basemap("CartoDB.Positron")
m3.add_point_cloud_layer(
    data=simple_points,
    name="grid-points",
    get_position="position",
    get_color=[0, 200, 255, 200],  # Uniform cyan color
    point_size=8,
)
m3

# Simple point cloud with uniform color simple_points = [ {"position": [lng, lat, alt]} for lng in [-122.42, -122.41, -122.40, -122.39] for lat in [37.77, 37.78, 37.79, 37.80] for alt in [0, 100, 200, 300] ] m3 = MapLibreMap(center=[-122.405, 37.785], zoom=13, pitch=60) m3.add_basemap("CartoDB.Positron") m3.add_point_cloud_layer( data=simple_points, name="grid-points", get_position="position", get_color=[0, 200, 255, 200], # Uniform cyan color point_size=8, ) m3

Point Cloud with Layer Control¶

In [ ]:

# Generate two point clouds
cloud1 = generate_points(-122.43, 37.78, num_points=500, spread=0.005)
cloud2 = generate_points(-122.40, 37.77, num_points=500, spread=0.005)

m4 = MapLibreMap(center=[-122.415, 37.775], zoom=13, pitch=45)
m4.add_basemap("CartoDB.DarkMatter")

# Add first point cloud (blue theme)
for p in cloud1:
    p["color"] = [100, 150, 255, 200]

m4.add_point_cloud_layer(
    data=cloud1,
    name="pointcloud-north",
    get_position="position",
    get_color="color",
    point_size=4,
)

# Add second point cloud (orange theme)
for p in cloud2:
    p["color"] = [255, 150, 100, 200]

m4.add_point_cloud_layer(
    data=cloud2,
    name="pointcloud-south",
    get_position="position",
    get_color="color",
    point_size=4,
)

# Add layer control
m4.add_layer_control()
m4

# Generate two point clouds cloud1 = generate_points(-122.43, 37.78, num_points=500, spread=0.005) cloud2 = generate_points(-122.40, 37.77, num_points=500, spread=0.005) m4 = MapLibreMap(center=[-122.415, 37.775], zoom=13, pitch=45) m4.add_basemap("CartoDB.DarkMatter") # Add first point cloud (blue theme) for p in cloud1: p["color"] = [100, 150, 255, 200] m4.add_point_cloud_layer( data=cloud1, name="pointcloud-north", get_position="position", get_color="color", point_size=4, ) # Add second point cloud (orange theme) for p in cloud2: p["color"] = [255, 150, 100, 200] m4.add_point_cloud_layer( data=cloud2, name="pointcloud-south", get_position="position", get_color="color", point_size=4, ) # Add layer control m4.add_layer_control() m4

Combined Arc and Point Cloud Layers¶

In [ ]:

# Combine arc and point cloud layers
m5 = MapLibreMap(center=[-122.4, 37.78], zoom=11, pitch=50)
m5.add_basemap("CartoDB.DarkMatter")

# Add point clouds at locations
locations = [
    (-122.45, 37.80),  # Golden Gate
    (-122.40, 37.78),  # Downtown
    (-122.35, 37.75),  # East Bay
]

for i, (lng, lat) in enumerate(locations):
    cloud = generate_points(lng, lat, num_points=200, spread=0.003)
    for p in cloud:
        p["color"] = [100 + 50 * i, 200 - 50 * i, 150, 200]
    m5.add_point_cloud_layer(
        data=cloud,
        name=f"pointcloud-loc{i}",
        get_position="position",
        get_color="color",
        point_size=3,
    )

# Add arcs connecting the locations
arcs = [
    {"source": list(locations[0]), "target": list(locations[1])},
    {"source": list(locations[1]), "target": list(locations[2])},
    {"source": list(locations[0]), "target": list(locations[2])},
]

m5.add_arc_layer(
    data=arcs,
    name="arc-connections",
    get_source_color=[0, 255, 200, 255],
    get_target_color=[255, 200, 0, 255],
    get_width=2,
)

m5.add_layer_control()
m5

# Combine arc and point cloud layers m5 = MapLibreMap(center=[-122.4, 37.78], zoom=11, pitch=50) m5.add_basemap("CartoDB.DarkMatter") # Add point clouds at locations locations = [ (-122.45, 37.80), # Golden Gate (-122.40, 37.78), # Downtown (-122.35, 37.75), # East Bay ] for i, (lng, lat) in enumerate(locations): cloud = generate_points(lng, lat, num_points=200, spread=0.003) for p in cloud: p["color"] = [100 + 50 * i, 200 - 50 * i, 150, 200] m5.add_point_cloud_layer( data=cloud, name=f"pointcloud-loc{i}", get_position="position", get_color="color", point_size=3, ) # Add arcs connecting the locations arcs = [ {"source": list(locations[0]), "target": list(locations[1])}, {"source": list(locations[1]), "target": list(locations[2])}, {"source": list(locations[0]), "target": list(locations[2])}, ] m5.add_arc_layer( data=arcs, name="arc-connections", get_source_color=[0, 255, 200, 255], get_target_color=[255, 200, 0, 255], get_width=2, ) m5.add_layer_control() m5

Remove Point Cloud Layer¶

In [ ]:

# Remove a specific point cloud layer
m4.remove_point_cloud_layer("pointcloud-north")

# Remove a specific point cloud layer m4.remove_point_cloud_layer("pointcloud-north")

Export to HTML¶

In [ ]:

m.to_html("pointcloud_layer_example.html")

m.to_html("pointcloud_layer_example.html")