waveletec 0.2.2.0.2

Wavelet-based Eddy Covariance Written by pedrohenriquecoimbra

Citation

Pedro H H Coimbra, Benjamin Loubet, Olivier Laurent, Matthias Mauder, Bernard Heinesch, Jonathan Bitton, Jeremie Depuydt, Pauline Buysse. Improvement of CO2 Flux Quality Through Wavelet-Based Eddy Covariance: A New Method for Partitioning Respiration and Photosynthesis. http://dx.doi.org/10.2139/ssrn.4642939

* corresponding author: [e-mail]

Getting started

1. Setup python.
   (optional) Create python environment, with anaconda prompt run conda create -n wavec
   (optional) Activate new environement, activate wavec
   Install python library, pip install waveletec

2. Run EddyPro, saving level 6 raw data.
   To do this go in Advanced Settings (top menu) > Output Files (left menu) > Processed raw data (bottom);
   Then select Time series on "level 6 (after time lag compensation)";
   Select all variables;
   Proceed as usual running on "Advanced Mode".

3. Follow launcher.ipynb

If directly cloning github

1. Setup python.
   (option 1) install anaconda, and run conda create -n wavec --file requirements.txt
   (option 2) install anaconda, and run conda create -f environment.yml

Example

For an example follow the launcher_sample.ipynb file in folder sample\FR-Gri_20220514.