This is a repository containing some trend functionalities for use within the C3S_511 project. The main functionalities are found in the file trends_core3d.py and their usage is shown in the example notebook example_trends_3d_cds-satellite-soil-moisture.ipynb that can be found in the directory notebook. For users who have no experience with the Jupyter notebook, it is recommended to read sections 1.1 and 3 from this tutorial.
- Navigate to the directory where you want the software to be installed and clone this repository.
- Navigate to the
installdirectory - Create a new conda environment named
trend(as specified in environment.yml):conda env create -f environment.yml - Activate the environment:
conda activate trend - Open the example notebook and modify the evaluator specific part for reading in and preprocessing your data
- Navigate to the directory where you want the software to be installed and clone this repository.
- Navigate to the
installdirectory - Create a new conda environment named
trend(as specified in environment.yml):conda env create -f environment.yml - Activate the environment:
conda activate trend - Add rpy2 as package:
conda install rpy2 - Edit the file
installR.rto point to the right installation path (see file) - Run
Rscript installR.r - Wait for the script to be finished
- Check the installation by running the example notebook.
- ATBD document from ECA&D: https://www.ecad.eu/documents/atbd.pdf
- R-package trend documentation: https://cran.r-project.org/web/packages/trend/vignettes/trend.pdf
- R-package iki.dataclim documentation: https://cran.r-project.org/web/packages/iki.dataclim/iki.dataclim.pdf
- Testing the assumptions of linear regression: http://people.duke.edu/~rnau/testing.htm
- Understanding Q-Q Plots: https://data.library.virginia.edu/understanding-q-q-plots/
- Mann-Kendall test https://vsp.pnnl.gov/help/vsample/design_trend_mann_kendall.htm