Diffusion-based smoothers for coarse graining GCM data
Project description
GCM Filters
Diffusion-based smoothers for coarse-graining GCM data.
Documentation and code
URLs for the docs and code.
Installation
For conda users you can
conda install --channel conda-forge gcm_filters
or, if you are a pip users
pip install gcm_filters
Example
from gcm_filters import gcm_filters
gcm_filters.meaning_of_life_url()
Get in touch
Report bugs, suggest features or view the source code on GitHub.
License and copyright
ioos_pkg_skeleton is licensed under BSD 3-Clause "New" or "Revised" License (BSD-3-Clause).
Development occurs on GitHub at https://github.com/ocean-eddy-cpt/gcm-filters.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
gcm_filters-0.1.tar.gz
(4.8 MB
view hashes)
Built Distribution
gcm_filters-0.1-py3-none-any.whl
(11.3 kB
view hashes)
Close
Hashes for gcm_filters-0.1-py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | b5328b9d6b817dca2fcffc03bb95637385187cccfcf240258650384fd4f06014 |
|
| MD5 | dc8773f6e72be0b6818212cb9b263a14 |
|
| BLAKE2b-256 | f93c406154f312563f4bf7b3ffdefc3e42cf908624ca9790cd63ba72895ed84c |
