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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 · Notion Roadmap »

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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

Generating a 3-state time-dependent self-assembly model with this package is as simple as writing

import numpy as np
import stp
# Dimensionless, time-dependent parameter for self assembly matrix
alpha = lambda t : np.cos(t) + 2
W = stp.self_assembly_rate_matrix(alpha)

# The initial matrix
print(W(0))
# [[-2.  3.  9.]
# [ 1. -3.  0.]
# [ 1.  0. -9.]]

# A later matrix
print(W(1))
# [[-2.          2.54030231  6.45313581]
# [ 1.         -2.54030231  0.        ]
# [ 1.          0.         -6.45313581]]

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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Release files for stp 0.0.1.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for stp 0.0.1.7
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stp-0.0.1.7.tar.gz 27.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for stp 0.0.1.7
File Interpreter ABI Platform
stp-0.0.1.7-py3-none-any.whl Python 3 none any Details

Total release size: 57.2 kB

Release files / stp-0.0.1.7.tar.gz

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Size 27.9 kB
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Release files / stp-0.0.1.7-py3-none-any.whl

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