Laboratory Intelligence Toolkit - Swarm Intelligence Module
Project description
matplotlab - Laboratory Intelligence Toolkit
A lightweight Python library implementing Swarm Intelligence algorithms from lab coursework.
Features
Swarm Intelligence (SI)
- Particle Swarm Optimization (PSO) - 3 implementations (basic, adaptive, modular)
- Ant Colony Optimization (ACO) for Traveling Salesman Problem
- 6 benchmark fitness functions (sphere, rastrigin, quadratic, oscillating, multi_modal, lab6_custom)
- 5 boundary handling strategies (clamping, reflecting, wraparound, random reset, velocity damping)
- 2 search methods (random search, brute force)
- 7 lab implementation codes
Installation
Local Installation (Development)
pip install -e .
From PyPI (After Publishing)
pip install matplotlab
Quick Start
SI Module
from matplotlab.si import pso_adaptive, rastrigin
import numpy as np
best_x, best_val, history = pso_adaptive(
rastrigin,
dim=10,
bounds=(-5.12, 5.12),
num_particles=30,
iterations=100
)
print(f"Best solution: {best_x}, Value: {best_val}")
Available Functions
from matplotlab.si import show_all_params
# View all 25 available functions and their parameters
show_all_params()
Get Help on Any Function
from matplotlab.si import pso_basic
# View function documentation and parameters
pso_basic.help()
# View quick parameter reference
pso_basic.params()
# View source code
pso_basic.show()
from matplotlab.si import run_aco
best_path, best_distance = run_aco(
distances=distance_matrix,
n_ants=20,
n_iterations=50,
alpha=1,
beta=2,
evaporation=0.5
)
print(f"Best tour: {best_path}, Distance: {best_distance}")
Requirements
- Python 3.8+
- numpy >= 1.19.0
- matplotlib >= 3.3.0
Modules
SI (Swarm Intelligence)
algorithms.pso- PSO implementationsalgorithms.aco- Ant Colony Optimizationalgorithms.search- Random and Brute Force Searchoptimization.fitness- Fitness functionsoptimization.boundaries- Boundary handling strategies
CV (Computer Vision)
- To be implemented
HCI (Human-Computer Interaction)
- To be implemented
License
MIT License
Project details
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