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Pysotope is an open-source package meant to processes raw data measured from the OSIBL GC-IRMS. Corrections are automatically calculated but the user must verify and confirm their application.

Project description

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pysotope (v.1.6.0).

Pysotope is an open-source package meant to processes raw data measured from the OSIBL GC-IRMS. Corrections are automatically calculated but the user must verify and confirm their application.

Note: pysotope was tested using jupyter lab and jupyter notebook. Compatibility with alternative python IDEs may require custom configuration.

Data Corrections

  • Drift (weighted means least squares)
  • Linearity (log, exponential, or linear fit)
  • Methanol derivitization - user is asked for methanol values
  • PAME - calculates the isotopic composition of PAME, if run in the sequence (set argument pame=True)
  • VSMOW - calculated using C18, C20, and C28 standards, tested on C24 standard.

Features

  • Uncertainty/error associted with each correction is automatically calculated and included in each data output.
  • Compatible with hydrogen and carbon isotope measurements
  • Modifiable standard isotopic values
  • Due to non-linear linearity expression, a exponential or logarithmic curve is automatically fit to the linearity standards.
  • Assign chain lengths using interactive plot (requires Jupyter Lab or Jupyter Notebook)

Installation

pip install pysotope

Arguments

  • pame (default False) - if True, the package will automatically identify and correct PAME values in the sequence.
  • user_linearity_conditions (default False) - if True, during linearity correction, user will be asked for a cutoff value under which samples with peak areas lower than the cutoff will be excluded from the analysis.
  • alt_stds (default False) - if True, the user can modify the default standard values. These changes will be saved for the user, but will reset upon package update.

e.g.,

import pysotope

# Edit standard data
pysotope.standard_editor()

# Process IRMS data
pysotope.iso_process(pame=True, user_linearity_conditions = False)

# Assign chain lengths
%matplotlib widget
pysotope.assign_chain_lengths()

Use

  • Run pysotope and provide the file path to the IRMS output data
  • Answer questions
  • Data output is split into mean of samples, individual samples, and standards in three .csv files
  • Output log contains all user decisions, equations used for corrections, descriptive statistics, and time codes for user actions
  • Figures are saved locally

Contributing

Contributions to pysotope are welcome! If you encounter any issues or have suggestions for improvements, please open an issue or submit a pull request on the GitHub repository.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For questions or inquiries, please contact:

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