Tools for producing sweights using classic methods or custom orthogonal weight functions (COWs) and for correcting covariance matrices for weighted data fits.
Project description
sweights
pip install sweights
We provide several tools for projecting component weights sWeights in a control variable(s) using a discriminating variable(s). What we call sWeights is the traditional sPlot method (we think that sPlot is a misnomer and hence call it sWeights), but also the new Custom Orthogonal Weight functions (COWs). If you use this package, please cite our methods as:
If you cannot access this paper for free, checkout the preprint, arXiv:2112.04574.
We also provide tools for correcting the covariance matrix of fits to weighted data, described in section IV of our paper and in more detail in Langenbruch, arXiv:1911.01303.
Documentation
You can find our documentation here.
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
File details
Details for the file sweights-1.4.1.tar.gz
.
File metadata
- Download URL: sweights-1.4.1.tar.gz
- Upload date:
- Size: 1.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.0 CPython/3.12.4
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1aea88c9236e5759ce8c15ba7e4fcb8135d06935db81aa3721c5532db272cc6e |
|
MD5 | 7131e0459c5477a9da6e07da013c900f |
|
BLAKE2b-256 | 66fd8c67e92da7655111c5033ac175cd5f77bf64d34f76423fa44a330df9720a |
File details
Details for the file sweights-1.4.1-py3-none-any.whl
.
File metadata
- Download URL: sweights-1.4.1-py3-none-any.whl
- Upload date:
- Size: 27.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.0 CPython/3.12.4
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4693d5c06a7187edb2f339a1ceea9526f22b4abdbb23b1fef841afbea26d40b3 |
|
MD5 | b458a8699ea8fe664c2596fb3e648675 |
|
BLAKE2b-256 | 8ac6f7f61e883e9176b7cdc8e330f65a9e5c44172345f9223df5cf6b1490e50a |