Skip to main content

sierras

Github Actions CI Documentation Status PyPI python version mit license downloads diseno_sci_sfw

sierras is a tool for empirical Arrhenius equation fitting for thermally-induced physicochemical processes.

Requirements

You need Python 3.8+ to run sierras.

Installation

You can install the most recent stable release of sierras with pip

python -m pip install -U pip
python -m pip install -U sierras

Usage

A simple example of use:

import sierras

areg = sierras.ArrheniusRegressor()

areg.fit(Temperatures, target_process)

areg.activation_energy_  # in this case in eV
areg.extrapolated_process_  # extrapolated process at room temperature

areg.plot.arrhenius(Temperatures, target_process)  # plot the fitting

For a more detailed explanation you can read the tutorial and the API.

License

MIT License

Contact info

You can contact me at ffernandev@gmail.com

Metadata

Release files for sierras 0.2.4

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

Source distribution (sdist)

Source distribution for sierras 0.2.4
File Size Uploaded Provenance Actions
sierras-0.2.4.tar.gz 6.6 kB Without provenance Details for sierras-0.2.4.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for sierras 0.2.4
File Interpreter ABI Platform Actions
sierras-0.2.4-py3-none-any.whl Python 3 none any Details for sierras-0.2.4-py3-none-any.whl

Total release size: 12.3 kB

Release files / sierras-0.2.4.tar.gz

Download URL sierras-0.2.4.tar.gz
Size 6.6 kB
Tags Source
SHA-256 checksum
How to use checksums
a0a0d93e888b23baf13afbdfab13dbfbad666e96cf373cdee3737a1b158b1e9e
BLAKE2b-256 checksum
How to use checksums
71946c5d673fd5a279c4946347a5c86dc3df1711b3f883cc94dcccffe3a5fe07
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.4

Release files / sierras-0.2.4-py3-none-any.whl

Download URL sierras-0.2.4-py3-none-any.whl
Size 5.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b3dd0029c72d85add8c97d23374e12b5c1a7f617269edc056755fed2f6f36ef0
BLAKE2b-256 checksum
How to use checksums
54bb282c62e56493f048db2f9927e2ad11eff9b2250078fcd1894cd785d90fdd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.4

Security for sierras 0.2.4

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page