Skip to main content

Pysoplot

Pysoplot is a Python library that provides basic functions and routines for geochronology. It implements some of the core functionality of the popular (and now defunct) Isoplot/Ex. software, but also includes new algorithms and routines. Pysoplot is intended to be used by geochronologists to build custom scripts and data processing routines in order to meet individual requirements.

Pysoplot includes functions for:

  • regressing 2-D data using the model 1, 2 and 3 algorithms popularised by Isoplot/Ex.

  • regressing 2-D data using the robust spine algorithm of Powell et al. (2020) and a new "robust model 2" algorithm

  • computing weighted averages using algorithms based on classical and robust statistics

  • computing classical isochron and U-Pb concordia-intercept ages

  • plotting isochron diagrams

  • computing disequilibrium U-Pb ages

  • plotting equilibrium and disequilibriam concordia curves, age ellipses, and uncertainty envelopes

  • computing age uncertainties using Monte Carlo methods

Full code documentation is coming soon.

Installation

Run the following to install:

pip install pysoplot

Example usage

import pysoplot as pp

# get Tera-Wasserburg test dataset 
dp = pp.data.LA0708
# transform data point errors from 2 sigma to 1 sigma absolute
dp = pp.transform.dp_errors(dp, 'abs2s')

# regress data
fit = pp.regression.robust_fit(*dp, plot=True, diagram='tw')
pp.misc.print_result(fit, 'Regression results')
fit['fig'].show()

# compute Tera-Wasserburg concordia-intercept age
result = pp.upb.concint_age(fit, method='Powell')
print(f"age: {result['age']:.2f} +/- {result['age_95pm']:.2f}")

Acknowledgements

Acknowledgement of all third-party algorithms implemented in Pysoplot with links to publications will be added here soon...

License

Pysoplot is distributed under the MIT license.

Contact

Timothy Pollard

Metadata

Release files for pysoplot 0.0.2

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

Source distribution (sdist)

Source distribution for pysoplot 0.0.2
File Size Uploaded Provenance
pysoplot-0.0.2.tar.gz 73.6 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for pysoplot 0.0.2
File Interpreter ABI Platform
pysoplot-0.0.2-py3-none-any.whl Python 3 none any Details

Total release size: 161.1 kB

Release files / pysoplot-0.0.2.tar.gz

Download URL pysoplot-0.0.2.tar.gz
Size 73.6 kB
Tags Source
SHA-256 checksum
How to use checksums
5e5a0cfb5c4101de5606f8aab725826c49ac2c0781250a655d0ecf0b74af230e
BLAKE2b-256 checksum
How to use checksums
2fe1faa9a437830f0408c4150f061dbe5cda8a69ae70f75fb8f3b291dac144d4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.7.9

Release files / pysoplot-0.0.2-py3-none-any.whl

Download URL pysoplot-0.0.2-py3-none-any.whl
Size 87.5 kB
Tags Python 3
SHA-256 checksum
How to use checksums
67dc51c5adf6bf91013062bb44a7d7892770985f3a2d03a668b632300c85c913
BLAKE2b-256 checksum
How to use checksums
fd4ec982f35403e8155d48337547def9d243c8714d58dc9865e7e8d2caffaa84
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.7.9

Security for pysoplot 0.0.2

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