MOTrainer
Measurement Operator Trainer for data assimilation purposes.
Cite this software
Description
MOTrainer: Measurement Operator Trainer
Measurement Operator Trainer is a Python package training measurement operators (MO) for data assimilations purposes. It is specifically designed for the applications where one needs to split large spatio-temporal data into independent partitions, and then train separate ML models for each partition.
Please refer to the MOtrainer documentation for more details.
Installation
Python version >=3.10 is required to install MOTrainer.
MOTrainer can be installed from PyPI:
pip install motrainer
We suggest using mamba to create an isolated environment for the installation to avoid conflicts.
For more details and trouble shooting of the installation process, please refer to the installation guide for more details.
Contributing to MOTrainer
We welcome any kind of contribution to our software. Please refer to the Contributing Guidelines or Contributing.md.
License
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License.
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Credits
This package was created with Cookiecutter and the NLeSC/python-template.
Participating organisations
Reference papers
Mentions
- 1.Author(s): Xu Shan, Susan Steele-Dunne, Sebastian Hahn, Wolfgang Wagner, Bertrand Bonan, Clement Albergel, Jean-Christophe Calvet, Ou KuPublished in Remote Sensing of Environment by Elsevier BV in 2024, page: 11416710.1016/j.rse.2024.114167
- 2.Author(s): Xu Shan, Susan Steele-Dunne, Manuel Huber, Sebastian Hahn, Wolfgang Wagner, Bertrand Bonan, Clement Albergel, Jean-Christophe Calvet, Ou Ku, Sonja GeorgievskaPublished in Remote Sensing of Environment by Elsevier BV in 2022, page: 11311610.1016/j.rse.2022.113116
Contributors
Contact person
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