A computer program whose purpose is to apply deep learning schemes to dynamical systems and ocean remote sensing data.
Project description
4DVarNet
This software is a computer program whose purpose is to apply deep learning schemes to dynamical systems and ocean remote sensing data.
Package installation
- the package is hosted on test.pypi.org, and his dependencies on pypi.org
pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ ocean4dvarnet
- To install a specific version use for example
ocean4dvarnet==0.0.11
### Package utilisation
import ocean4dvarnet
Informations about this package development : package-development
Useful links
- Project getting started : https://github.com/CIA-Oceanix/4dvarnet-starter
- 4DVarNet papers:
- Fablet, R.; Amar, M. M.; Febvre, Q.; Beauchamp, M.; Chapron, B. END-TO-END PHYSICS-INFORMED REPRESENTATION LEARNING FOR SA℡LITE OCEAN REMOTE SENSING DATA: APPLICATIONS TO SA℡LITE ALTIMETRY AND SEA SURFACE CURRENTS. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2021, V-3–2021, 295–302. https://doi.org/10.5194/isprs-annals-v-3-2021-295-2021.
- Fablet, R.; Chapron, B.; Drumetz, L.; Mmin, E.; Pannekoucke, O.; Rousseau, F. Learning Variational Data Assimilation Models and Solvers. Journal of Advances in Modeling Earth Systems n/a (n/a), e2021MS002572. https://doi.org/10.1029/2021MS002572.
- Fablet, R.; Beauchamp, M.; Drumetz, L.; Rousseau, F. Joint Interpolation and Representation Learning for Irregularly Sampled Satellite-Derived Geophysical Fields. Frontiers in Applied Mathematics and Statistics 2021, 7. https://doi.org/10.3389/fams.2021.655224.
Copyright IMT Atlantique/OceaniX, contributor(s) : M. Beauchamp, R. Fablet, Q. Febvre, D. Zhu (IMT Atlantique)
Contact person: ronan.fablet@imt-atlantique.fr.
This software is a computer program whose purpose is to apply deep learning schemes to dynamical systems and ocean remote sensing data. This software is governed by the CeCILL-C license under French law and abiding by the rules of distribution of free software. You can use, modify and/ or redistribute the software under the terms of the CeCILL-C license as circulated by CEA, CNRS and INRIA at the following URL "http://www.cecill.info". As a counterpart to the access to the source code and rights to copy, modify and redistribute granted by the license, users are provided only with a limited warranty and the software's author, the holder of the economic rights, and the successive licensors have only limited liability. In this respect, the user's attention is drawn to the risks associated with loading, using, modifying and/or developing or reproducing the software by the user in light of its specific status of free software, that may mean that it is complicated to manipulate, and that also therefore means that it is reserved for developers and experienced professionals having in-depth computer knowledge. Users are therefore encouraged to load and test the software's suitability as regards their requirements in conditions enabling the security of their systems and/or data to be ensured and, more generally, to use and operate it in the same conditions as regards security. The fact that you are presently reading this means that you have had knowledge of the CeCILL-C license and that you accept its terms.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ocean4dvarnet-1.0.3.tar.gz.
File metadata
- Download URL: ocean4dvarnet-1.0.3.tar.gz
- Upload date:
- Size: 27.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9e69f46b55e69f6e44d21dca37543fd19d49b01575bd71df75a602e9f5d9a2c1
|
|
| MD5 |
6ab4ba0fe6279336b8db127ba57649ed
|
|
| BLAKE2b-256 |
fee3492bab592ea3fd620592b818865f29533fb65c0e869ec106cb3bdc436d71
|
File details
Details for the file ocean4dvarnet-1.0.3-py3-none-any.whl.
File metadata
- Download URL: ocean4dvarnet-1.0.3-py3-none-any.whl
- Upload date:
- Size: 28.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
78047d5f687f1e5130e99e25d40d7b07fff69436814115bc7386c2fdeb020fa5
|
|
| MD5 |
57fd98b47b8dd5a797434ebf9e7de06e
|
|
| BLAKE2b-256 |
5a08d4de667f84302dd726a93ff9dbb7674e7f612a0bf46722746ff72d1574b1
|