pytesmo 0.16.1

Python Toolbox for the evaluation of soil moisture observations

pytesmo, the Python Toolbox for the Evaluation of Soil Moisture Observations, is a package/python toolbox which aims to provide a library that can be used for the comparison and validation of geospatial time series datasets with a (initial) focus on soil moisture.

Documentation & Software Citation

To see the latest full documentation click on the docs badge at the top.

If you use the software in a publication then please cite it using the Zenodo DOI. Be aware that this badge links to the latest package version.

Please select your specific version at https://doi.org/10.5281/zenodo.596422 to get the DOI of that version. You should normally always use the DOI for the specific version of your record in citations. This is to ensure that other researchers can access the exact research artefact you used for reproducibility.

You can find additional information regarding DOI versioning at http://help.zenodo.org/#versioning

If you want to contribute, take a look at the developers guide .

Installation

This package should be installable through pip which downloads the package from the python package repository Pypi. However, pytesmo also needs some packages that depend on C or Fortran libraries (like netCDF4). They should be installed first with conda or mamba. We recommend installing Mambaforge. Then the following command should install all dependencies:

mamba install -c conda-forge 'numpy<2.0.0' scipy pandas netCDF4 cython pyresample

Afterwards pytesmo can be installed via pip.

pip install pytesmo

As an alternative (e.g. if you want to contribute to the package), you can clone the Github repository and install from source:

git clone https://github.com/TUW-GEO/pytesmo.git --recursive
cd pytesmo
mamba create -n pytesmo python=3.10 # or any supported python version
conda activate pytesmo
mamba env update -f environment.yml -n pytesmo
pip install -e .

Supported Products

Soil moisture is observed using different methods and instruments, in this version several satellite datasets as well as in situ and reanalysis data are supported through independent and optional (reader) packages:

• ERS & H-SAF ASCAT products

• SMAP

• GLDAS Noah

• ERA5 and ERA5-Land

• SMOS

• C3S SM

• ESA CCI SM

• MERRA

• Data from the International Soil Moisture Network (ISMN)

  In case of the ISMN, two different formats are provided: An example of how to use the dataset in the pytesmo validation framework can be found in the “Examples” chapter. * Variables stored in separate files (CEOP formatted)

Related Packages

Some former pytesmo modules are now provided as separate packages.

• pygeogrids : Creation and handling of Discrete Global Grids or Point collections

• cadati : Calender, Date and Time functions

• repurpose : Time series - image conversion and resampling routines

• colorella : Color maps and color map handling

Contribute

We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. We will also gladly accept pull requests against our master branch for new features or bug fixes.

Please follow the developers guide.