PyForceAtlas2 is a Python implementation of the ForceAtlas2 graph layout algorithm. Originally designed for Gephi, this implementation is optimized for reproducible and high-performance network visualization in Python, supporting both NetworkX and igraph.
- High Performance: Barnes-Hut optimization for large networks.
- Customizable: Fine-tune attraction, repulsion, gravity, and speed parameters.
- Versatile: Seamless integration with NetworkX and igraph.
- Reproducible: Easily set random seeds for deterministic layouts.
Install PyForceAtlas2 via pip:
pip install pyforceatlas2The following example demonstrates how to compute a layout for a random geometric graph and visualize it with NetworkX and Matplotlib:
"""
Example: ForceAtlas2 Layout on a Random Geometric Graph
--------------------------------------------------------
This script generates a random geometric graph with 400 nodes,
computes a ForceAtlas2 layout, and visualizes the result.
"""
import random
import networkx as nx
import matplotlib.pyplot as plt
from pyforceatlas2 import ForceAtlas2
# Set a random seed for reproducibility.
random.seed(888)
# Generate a random geometric graph: nodes are connected if they are within radius 0.2.
G = nx.random_geometric_graph(400, 0.2)
# Initialize ForceAtlas2 with custom parameters.
forceatlas2 = ForceAtlas2(
outbound_attraction_distribution=False, # Do not dissuade hubs.
edge_weight_influence=1.0,
lin_log_mode=True, # Use LinLog mode for attraction forces.
jitter_tolerance=10.0, # Tolerance for oscillations.
barnes_hut_optimize=True, # Enable Barnes-Hut optimization.
barnes_hut_theta=2.2, # Trade-off between accuracy and speed.
scaling_ratio=2.0, # Controls overall repulsion strength.
strong_gravity_mode=False, # Use standard gravity.
gravity=1.0, # Gravitational constant.
verbose=True,
)
# Compute the layout. Returns a dict mapping each node to an (x, y) coordinate.
positions = forceatlas2.forceatlas2_networkx_layout(G, pos=None, iterations=100)
# Visualize the graph.
nx.draw_networkx_nodes(G, positions, node_size=20, node_color="blue", alpha=0.4)
nx.draw_networkx_edges(G, positions, edge_color="green", alpha=0.05)
plt.axis("off")
plt.show()The main entry point is the ForceAtlas2 class:
from pyforceatlas2 import ForceAtlas2
# Initialize with desired parameters.
forceatlas2 = ForceAtlas2(
outbound_attraction_distribution=False,
edge_weight_influence=1.0,
lin_log_mode=True,
jitter_tolerance=10.0,
barnes_hut_optimize=True,
barnes_hut_theta=2.2,
scaling_ratio=2.0,
strong_gravity_mode=False,
gravity=1.0,
verbose=True,
)
# For a NetworkX graph:
positions = forceatlas2.forceatlas2_networkx_layout(G, pos=None, iterations=100)
# For an igraph graph:
layout_obj = forceatlas2.forceatlas2_igraph_layout(igraph_graph, pos=None, iterations=100)- ForceAtlas2 Paper:
Jacomy, M., Venturini, T., Heymann, S., & Bastian, M. (2014).
ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software.
PLoS ONE, 9(6), e98679.
DOI: 10.1371/journal.pone.0098679
Contributions, bug reports, and feature requests are welcome! Please open an issue or submit a pull request on GitHub.
This project is licensed under the GNU General Public License v3.0 (GPLv3). See the LICENSE file for details.