Collection of EOF analysis and related techniques for climate science
Project description
xeofs: EOF analysis and variants
Empirical orthogonal function (EOF) analysis, commonly referred to as principal component analysis (PCA), is a popular decomposition technique in climate science. Over the years, a variety of variants have emerged but the lack of availability of these different methods in the form of easy-to-use software seems to unnecessarily hinder the acceptance and uptake of these EOF variants by the broad climate science community.
Goal (work in progress)
Create a Python package that provides simple access to a variety of different EOF-related techniques through the popular interfaces of NumPy, pandas and xarray.
Documentation
Documentation is work in progress.
Credits
Project details
Release history Release notifications | RSS feed
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 xeofs-0.1.2.tar.gz.
File metadata
- Download URL: xeofs-0.1.2.tar.gz
- Upload date:
- Size: 6.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0fa3b6777c9860a7fb52a8932d41cd71d4b8dde6882f8d3ecbcc51edf68da682
|
|
| MD5 |
5439f3a10d62d2973b7f2127a00058f3
|
|
| BLAKE2b-256 |
7819e4f2e05a189e19c03b93767cf5480a3b48fe61e4480e700e0d8ec2655051
|
File details
Details for the file xeofs-0.1.2-py3-none-any.whl.
File metadata
- Download URL: xeofs-0.1.2-py3-none-any.whl
- Upload date:
- Size: 8.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
55d697d391e4f750f66c5b395d108aeec371ef78a705e4d45ce8a56f556f62e5
|
|
| MD5 |
5b8cdf0875fd5e96692a1217f8d69335
|
|
| BLAKE2b-256 |
81d9072d2e8a3b731a057fc6e0e534eb0fc3347668832fa4bbb9c6ffe3087fc5
|