MHland / PyDnA

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

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)