High-performance network-constrained spatial point pattern analysis in Python
Project description
FastNSA
FastNSA is a high-performance toolkit for network-constrained spatial analysis, designed for large-scale road networks and massive point datasets. It provides a Python interface backed by a native implementation for efficient spatial indexing and network-based statistical computation.
Installation
FastNSA is distributed via PyPI with prebuilt native backends.
pip install fastnsa
Supported platforms:
-
Linux (x86_64)
-
Python ≥ 3.9
Quick Example
import fastnsa as nsa
# 1. Build a road network from OpenStreetMap
# (internally constructs spatial and network indexes)
net = nsa.Network.from_osm(place="Central Park, NY")
# 2. Load event points and project them onto the network
gdf = nsa.load_points("accidents.csv")
events = nsa.PointEvents(gdf, target_network=net)
# 3. Compute a network-based K-function
results = nsa.network_k_function(
network=net,
points=events,
r_values=[10, 50, 100]
)
print(results)
Spatiotemporal Network K-function
import fastnsa as nsa
import numpy as np
net = nsa.Network.from_osm(place="Central Park, NY")
gdf = nsa.load_points("accidents_with_time.csv", time_col="event_time")
events = nsa.PointEvents(gdf, target_network=net, time_col="event_time")
st_result = nsa.spatiotemporal_network_k_function(
network=net,
points=events,
s_values=np.array([50.0, 100.0, 150.0]),
t_values=np.array([1.0, 3.0, 7.0]),
method="EARTH",
simulations=99,
alpha=0.05,
)
print(st_result.k_obs.shape) # (n_s, n_t)
Design Overview
The Python layer provides:
-
Network construction and I/O
-
Event projection to networks
-
tatistical analysis interfaces
Performance-critical components such as spatial indexing, point-to-network mapping, and distance evaluation are implemented in a native backend and exposed through Python bindings.
License
FastNSA is licensed under the GNU Lesser General Public License v3.0 (LGPL-2.1).
You are free to use this library in proprietary and open-source software, but any modifications to the FastNSA library itself must be released under LGPL.
Project details
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