Stochastic Thermodynamics in Python (STP)

Python library to construct random quantities and track their information-theoretic properties. These objects include continuous time rate matrices, discrete time transition matrices, and matrices representing 3-state self assembly models.

Status: in progress · Documentation

Installation

This package is pip-installable.

1. Install via pip.

   python3 -m pip install stp

2. Import the package

   import stp

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Usage

3-state self-assembly rate matrix (time-dependent)

import numpy as np
import stp

alpha = lambda t: np.cos(t) + 2
W = stp.self_assembly_rate_matrix(alpha)
print(W(0))  # [[-2.  3.  9.] ...]

Stationary distribution

R = stp.rand_transition_matrix(3)
p_star = stp.get_stationary_distribution(R, discrete=True)

Shannon entropy

p = stp.rand_p(3)
H = stp.info.entropy(p)

KMC path sampling

W = stp.self_assembly_rate_matrix(alpha=1.5)
p = stp.rand_p(3)
paths = stp.KMC(W, p, num_paths=100, path_length=10, seed=42)

For more examples, please refer to the Documentation.

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Roadmap

Refer to the Notion Roadmap for the state of the project.

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Contact

Created by Jonathan Delgado.

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