Skip to content

Latest commit

 

History

History
39 lines (28 loc) · 1.19 KB

README.md

File metadata and controls

39 lines (28 loc) · 1.19 KB
Raw

PyDnA

Detection and Attribution framework in python using the Optimal Fingerprinting Approach (Hasselmann, 1993; Ribes et al. 2013)

Disclamer

This package is still under development and has not been fully tested yet.

Overview

Core framework

  • PyDnA.py - collection of functions needed by ROF_main.py (based on A. Ribes scilab code)

  • ROF_main.py - DA routine (based on A. Ribes scilab code)

Helper functions (written by Friederike Fröb)

  • load_fil_data.py - load data and filter data

  • plot_da_res.py - plot results of da routine

  • run_da_routine.py - wrapper function, calls all other routines

Dependencies

Core framework

  • numpy (tested for version 1.17.4)
  • scipy (tested for version 1.3.1)

Helper functions

  • argparse
  • multiprocessing
  • subprocess
  • xarray
  • pandas
  • matplotlib

Run the example

  1. Download the example* data archive and unzip into the data directory
  2. python run_da_routine.py ph -s 5 -b 15
  3. python run_da_routine.py --help to display all options.

*example data shows hydrogen ion concentration (measure of pH) for an ocean alkalinization experiment (Gonzalez & Ilyina, 2016)