PyRandomLoop 0.1.2

Provides a simulation framework for a random loop model in statistical mechanics, including initialization, simulation, and visualization capabilities.

PyRandomLoop

PyRandomLoop is a Python package designed for simulating and visualizing a random loop model on a 2d grid. 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.

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")