isocompy’s documentation!

This repository contains an open source Python library that focuses on user defined (such as meteorological, spatial, etc.) and isotopic composition variables analysis and generating the regression – statistical estimation models.

Package information

Name: Isocompy

version: 1.0.2

Author: Ashkan Hassanzadeh

Email: ashkan.hassanzadeh@gmail.com

python: 3.*

License: agpl-3.0

Citation

Hassanzadeh, A., Valdivielso, S., Vázquez-Suñé, E., Criollo, R., Corbella, M., 2023. An open source Python library for environmental isotopic modelling. Sci. Reports 2023 131 13, 1–19. https://doi.org/10.1038/s41598-023-29073-2

Installation

pip can be used for the installation:

pip install isocompy

Alternatively, download the isocompy folder from the github repository and add it to lib folder in python path alongside other python libraries.

Jupyter Notebook

There is a notebook in isocompy’s github repository that explains an example of implementing isocompy on spatial and isotopic data

Contents:

• Isocompy
  • Package information:
  • Installation:
  • Jupyter Notebook:
• class preprocess ( )
  • Parameters
  • Methods
  • Attributes
  • preprocess.fit ( )
  • preprocess.model_pars ( )
• class model ( )
  • Methods
  • Attributes
  • model.st1_fit ( )
  • model.st2_fit ( )
  • model.choose_estimator_by_meteo_line ( )
  • model.stage2_output_report ( )
• class evaluation ( )
  • Methods
  • Attributes
  • evaluation.predict ( )
• class plots ( )
  • Methods
  • plots.best_estimator_plots ( )
  • plots.partial_dep_plots ( )
  • Method plots.isotopes_meteoline_plot ( )
  • Method plots.map_generator ( )
• class session ( )
  • Methods
  • session.save ( )
  • session.load ( )
  • session.save_session ( )
  • session.load_session ( )
• class stats ( )
  • Methods
  • stats.seasonal_stats ( )
  • stats.mensual_stats ( )
• License
  • How to Apply These Terms to Your New Programs

search

• Search Page