Graphizy Documentation
A powerful, fast, and flexible Python library for building and analyzing graphs from 2D spatial data
Graphizy specializes in creating comprehensive graph types from point data, with advanced memory-enhanced analysis for temporal patterns, sophisticated weight computation systems, and real-time streaming capabilities. Built on OpenCV and igraph, it provides a modern unified API for graph construction and comprehensive analytics.
Quick Start
from graphizy import Graphing, GraphizyConfig, generate_and_format_positions
# Generate sample data
data = generate_and_format_positions(size_x=800, size_y=600, num_particles=100)
# Configure and create grapher
config = GraphizyConfig(dimension=(800, 600))
grapher = Graphing(config=config)
# Create different graph types using unified interface
delaunay_graph = grapher.make_graph("delaunay", data)
proximity_graph = grapher.make_graph("proximity", data, proximity_thresh=50.0)
knn_graph = grapher.make_graph("knn", data, k=4)
# Advanced analysis with new API
graph_info = grapher.get_graph_info(delaunay_graph)
print(f"Density: {graph_info.density:.3f}")
print(f"Connected: {graph_info.is_connected}")
# Use advanced analyzers
social_roles = graph_info.social_analyzer.identify_social_roles(delaunay_graph)
percolation_result = graph_info.percolation_analyzer.analyze_percolation_threshold(
data, [20, 30, 40, 50, 60]
)
Key Features
One API for All Graphs
Create Delaunay, k-NN, MST, Gabriel, Proximity, and even custom graphs with a single make_graph() call. Plugin-friendly, smart defaults, and fully type-safe.
Temporal Memory System
Track how connections evolve over time. Use built-in memory features for persistence-aware analysis, temporal filtering, and age-based visualization.
Rich Graph Types, Easily Extended
From spatial graphs to domain-specific topologies: support includes Delaunay triangulations, proximity graphs, k-nearest neighbors, MSTs, and custom plugins.
Instant Network Analysis
Access over 200 igraph algorithms with real-time stats: clustering, centrality, components, and more. All robust to disconnections. NetworkX compatible.
Custom Weights, Real-Time Ready
Define weights using distance, inverse, Gaussian, or custom formulas. Memory-aware weight updates and vectorized for performance.
Advanced Tools for Spatial & Temporal Insights
Includes percolation thresholds, service accessibility, social dynamics, and time-aware community tracking — all tailored for dynamic networks.
Visualization & Streaming
Visualize network memory with age-based coloring and transparency. Stream updates in real time, or export static snapshots. Comes with CLI tools and interactive demos.