A python package for estimating the power spectral density (PSD) of correlated multivariate detector noise using variational inference (VI).
Verified details
These details have been verified by PyPIProject links
GitHub Statistics
Maintainers
Project description
SGVB PSD Estimator
This repository contains the code for the paper "Variational inference for correlated gravitational wave detector network noise" by Jianan Liu at al. 2024
Documentation is available at https://nz-gravity.github.io/sgvb_psd/
Development
Install in editable mode with dev dependencies
pip install -e ".[dev]"
pre-commit install
Ensure unit tests are passing locally and on the CI!
pytest tests/
Releasing to PyPI
- Manually change the version number in
pyproject.toml(has to be higher than previous) - Create a tagged commit with the version number
- Push the tag to GitHub
git tag -a v0.1.0 -m "v0.1.0"
git push origin v0.1.0
Project details
Verified details
These details have been verified by PyPIProject links
GitHub Statistics
Maintainers
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 sgvb_psd-0.0.6.tar.gz.
File metadata
- Download URL: sgvb_psd-0.0.6.tar.gz
- Upload date:
- Size: 15.5 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.0.1 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8467c464341dbb93e2fb9f404b2cb687f7d4caf6e7a28715b4e63d7e5148d14d
|
|
| MD5 |
1643e3be2f1b18d3a77dcb9936c6170f
|
|
| BLAKE2b-256 |
65785ba1d5707fa4cbdcb713f7cbd4bfb24513a546b23dfb51ea01f3bbe9b541
|
Provenance
The following attestation bundles were made for sgvb_psd-0.0.6.tar.gz:
Publisher:
publish.yml on nz-gravity/sgvb_psd
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
sgvb_psd-0.0.6.tar.gz -
Subject digest:
8467c464341dbb93e2fb9f404b2cb687f7d4caf6e7a28715b4e63d7e5148d14d - Sigstore transparency entry: 197802509
- Sigstore integration time:
-
Permalink:
nz-gravity/sgvb_psd@e425d8089cde0dff22e8d69919e5b43c0c110c20 -
Branch / Tag:
refs/heads/main - Owner: https://github.com/nz-gravity
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@e425d8089cde0dff22e8d69919e5b43c0c110c20 -
Trigger Event:
push
-
Statement type:
File details
Details for the file sgvb_psd-0.0.6-py3-none-any.whl.
File metadata
- Download URL: sgvb_psd-0.0.6-py3-none-any.whl
- Upload date:
- Size: 32.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.0.1 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8ae205a66f6ac0f1da45b7f5824302bb876074b2b638fea651df3101de28a633
|
|
| MD5 |
84f45e5ea6d3cf905185de99daa43177
|
|
| BLAKE2b-256 |
5d6dca6a26aad877fa7429830e7ff26d34d203b46961ec024a6ea469f1af1ec2
|
Provenance
The following attestation bundles were made for sgvb_psd-0.0.6-py3-none-any.whl:
Publisher:
publish.yml on nz-gravity/sgvb_psd
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
sgvb_psd-0.0.6-py3-none-any.whl -
Subject digest:
8ae205a66f6ac0f1da45b7f5824302bb876074b2b638fea651df3101de28a633 - Sigstore transparency entry: 197802512
- Sigstore integration time:
-
Permalink:
nz-gravity/sgvb_psd@e425d8089cde0dff22e8d69919e5b43c0c110c20 -
Branch / Tag:
refs/heads/main - Owner: https://github.com/nz-gravity
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@e425d8089cde0dff22e8d69919e5b43c0c110c20 -
Trigger Event:
push
-
Statement type:
