Wavelet-based Eddy Covariance Written by pedrohenriquecoimbra
Project description
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: pedro-henrique.herig-coimbra@inrae.fr
Getting started
-
Setup python.
(optional) Create python environment, with anaconda prompt runconda create -n wavec
(optional) Activate new environement,activate wavec
Install python library,pip install waveletec
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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". -
Follow launcher.ipynb
If directly cloning github
- Setup python.
(option 1) install anaconda, and runconda create -n wavec --file requirements.txt
(option 2) install anaconda, and runconda create -f environment.yml
Example
For an example follow the launcher_sample.ipynb file in folder sample\FR-Gri_20220514.