PyRandomLoop 0.1.1

The package provides a simulation framework for a random loop model in statistical mechanics, including initialization, simulation, and visualization capabilities. The core of the simulation is the class `stateSpace`. Features include performance optimizations, execution logging, and statistics calculation, alongside visualization tools for detailed analysis. Ideal for researchers and students in physics and related fields.

PyRandomLoop

PyRandomLoop is a Python package designed for simulating and visualizing a random loop model on a 2d grid. Ideal for researchers and hobbyists alike, this package offers an intuitive approach to exploring complex patterns and dynamics through simple and flexible APIs.

Features

• Multiple Initialization Patterns: Choose from random, snake, or donut patterns to start your simulations.
• Flexible Simulation Algorithms: Supports both Metropolis and Glauber algorithms to drive the simulation process.
• Visualization: Easily plot the current state of the grid with support for highlighting color loops.
• State Management: Save and load simulation states, allowing for pause-resume functionality.

Quick Start

from PyRandomLoop import stateSpace

# Initialize and run the simulation
simulation = stateSpace(num_colors=3, grid_size=50, beta=0.5)
simulation.step(num_steps=1000)

# Visualization
simulation.plot_grid()

# Save/load the simulation state
simulation.save_data("simulation_state.json")
simulation.load_data("simulation_state.json")