A Python library for simulating collective motion using the 3D Vicsek model with Numba JIT acceleration and spatial entropy metrics.

The Vicsek model (1995) describes self-propelled particles exhibiting collective motion through simple alignment rules. In 3D, each particle $i$ updates its velocity according to:

$$\mathbf{v}_i(t + \Delta t) = v_0 \cdot \hat{\mathbf{u}}\left( \langle \hat{\mathbf{v}}_j \rangle_{|r_{ij}| < r} + \eta \boldsymbol{\xi}_i \right)$$

where:

• $v_0$ is the constant speed of all particles
• $\langle \hat{\mathbf{v}}_j \rangle$ is the normalized average velocity of neighbors within radius $r$
• $\eta$ is the noise amplitude
• $\boldsymbol{\xi}_i$ is a random unit vector
• $\hat{\mathbf{u}}(\cdot)$ denotes normalization to unit vector

Position updates follow:

$$\mathbf{r}_i(t + \Delta t) = \mathbf{r}_i(t) + \mathbf{v}_i(t + \Delta t) \cdot \Delta t$$

with periodic boundary conditions in a cubic box of side $L$.

The collective alignment is quantified by the order parameter:

$$\phi = \frac{1}{N v_0} \left| \sum_{i=1}^{N} \mathbf{v}_i \right|$$

where $\phi \approx 0$ indicates disordered motion and $\phi \approx 1$ indicates collective alignment.

This library includes rigorous information-theoretic measures to quantify spatial order/disorder:

*SCI = (H_positional + H_orientational + H_local_align + H_pair + H_voronoi + (1-MI)) / 6

From PyPI:

pip install manuk-kepudang

From source:

git clone https://github.com/sandyherho/manuk-kepudang.git
cd manuk-kepudang
pip install .

Development installation with Poetry:

git clone https://github.com/sandyherho/manuk-kepudang.git
cd manuk-kepudang
poetry install

CLI:

manuk-kepudang case1          # Run ordered phase scenario
manuk-kepudang case2          # Run disordered phase scenario
manuk-kepudang --all          # Run all test cases
manuk-kepudang case1 --no-entropy  # Skip entropy computation

Python API:

from manuk_kepudang import VicsekSystem, VicsekSolver
from manuk_kepudang import compute_metrics_timeseries

# Create system with 200 particles
system = VicsekSystem(
    n_particles=200,
    box_size=10.0,
    speed=0.5,
    interaction_radius=2.0,
    noise=0.3
)

# Initialize solver with Numba acceleration
solver = VicsekSolver(dt=1.0, use_numba=True)

# Run simulation for 500 steps
result = solver.solve(system, n_steps=500)

# Compute entropy metrics
metrics = compute_metrics_timeseries(
    result['positions'],
    result['velocities'],
    result['time'],
    system.box_size,
    system.speed,
    system.interaction_radius
)

print(f"Final order parameter: {result['final_order_parameter']:.4f}")
print(f"Final SCI (disorder): {metrics['spatial_complexity_index_final']:.4f}")

• High-performance: Numba JIT compilation for 10-100x speedup
• 3D simulation: Full three-dimensional particle dynamics
• Periodic boundaries: Correct handling of boundary conditions
• Order parameter tracking: Real-time collective alignment measurement
• Spatial entropy metrics: Rigorous information-theoretic disorder measures
• Multiple output formats: CSV, NetCDF (CF-compliant), PNG, GIF
• Configurable scenarios: Text-based configuration files

The library generates:

• CSV files:
  • *_order_parameter.csv - Order parameter time series
  • *_entropy_timeseries.csv - All entropy measures over time
  • *_entropy_summary.csv - Statistics (mean, std, min, max, final)
  • *_final_state.csv - Final particle positions and velocities
• NetCDF: Full trajectory data with all metrics and CF-compliant metadata
  • Variables: x, y, z, vx, vy, vz, order_parameter, all entropy metrics
• PNG: Static summary plots with entropy visualization
• GIF: Animated 3D visualization with camera rotation

• numpy >= 1.20.0
• scipy >= 1.7.0
• matplotlib >= 3.3.0
• pandas >= 1.3.0
• netCDF4 >= 1.5.0
• numba >= 0.53.0
• Pillow >= 8.0.0
• tqdm >= 4.60.0

MIT © Sandy H. S. Herho, Gandhi Napitupulu, Iwan P. Anwar, Nurjanna J. Trilaksono, Rusmawan Suwarman, Dasapta E. Irawan

@software{herho2025_manuk_kepudang,
  title   = {manuk-kepudang: A Python library for 3D Vicsek model simulation},
  author  = {Herho, Sandy H. S. and Napitupulu, G. and Anwar, Iwan P. and Trilaksono, Nurjanna J. and Suwarman, Rusmawan and Irawan, Dasapta E.},
  year    = {2025},
  url     = {https://github.com/sandyherho/manuk-kepudang}
}