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
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Documentation
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Notion Roadmap »
Installation
This package is pip-installable.
- Install via pip.
python3 -m pip install stp
- Import the package
import stp
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.
Roadmap
Refer to the Notion Roadmap for the state of the project.
Contact
Created by Jonathan Delgado.
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)
| File | Size | Uploaded | |
|---|---|---|---|
| stp-0.0.1.7.tar.gz | 27.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| 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
| Download URL | stp-0.0.1.7.tar.gz |
|---|---|
| Size | 27.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
poetry/2.3.2 CPython/3.12.3 Darwin/25.3.0
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Release files / stp-0.0.1.7-py3-none-any.whl
| Download URL | stp-0.0.1.7-py3-none-any.whl |
|---|---|
| Size | 29.3 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
poetry/2.3.2 CPython/3.12.3 Darwin/25.3.0
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