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bda

Code for averaging together baselines

https://github.com/hera-team/baseline_dependent_averaging

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (11.3%) to scientific vocabulary

Keywords from Contributors

astronomy interferometry radio-astronomy energy-system-model
Last synced: 11 months ago · JSON representation

Repository

Code for averaging together baselines

Basic Info
  • Host: GitHub
  • Owner: HERA-Team
  • License: bsd-2-clause
  • Language: Python
  • Default Branch: main
  • Size: 43 KB
Statistics
  • Stars: 0
  • Watchers: 2
  • Forks: 0
  • Open Issues: 2
  • Releases: 2
Created about 8 years ago · Last pushed 12 months ago
Metadata Files
Readme License

README.md

Run Tests codecov

baselinedependentaveraging

This is code for applying baseline-dependent averaging to a radio astronomy interferometric dataset. It applies the principles and formulas presented in Wijnholds et al. (2018) to average high-cadence data to a lower cadence while introducing a maximum amount of decorrelation specified by the user. In brief, short baselines of an interferometer do not decorrelate as rapidly as long baselines, and so data from shorter baselines can be averaged together without losing as much coherent sky information. The code and routines in this repo are designed to work on already-recorded data (which is typically written at a common cadence for all baselines) and averages together consecutive time samples until a specific threshold. A forthcoming memo will describe the operation in more detail.

Installation

The code can be installed by invoking sh pip install . from the top level of the repo. This will install a module called bda which can be imported. The main user-facing function is bda.apply_bda, which is designed to work on a pyuvdata UVData object. It also provides a script, apply_bda.py, which can be called from the command line for applying BDA to an existing dataset on disk.

Dependencies

The following packages are required: * astropy * setuptools_scm * pyuvdata

pyuvdata can be installed from conda (preferred), or from pip. It is available on the conda-forge channel. To install: sh conda install -c conda-forge pyuvdata

Tests

The testing requirements can be installed by invoking sh pip install .[testing] from the top level of the repo. This will install the package and all dependencies for running tests. The test suite can be run by running pytest after installation.

Dependencies

In addition to the main package dependencies above, the following packages are required for running tests: * pytest >= 6.0

Owner

  • Name: Hydrogen Epoch of Reionization Array (HERA)
  • Login: HERA-Team
  • Kind: organization
  • Location: international

Collection of software used for the HERA radio telescope

GitHub Events

Total
  • Push event: 3
Last Year
  • Push event: 3

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 39
  • Total Committers: 3
  • Avg Commits per committer: 13.0
  • Development Distribution Score (DDS): 0.103
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Paul La Plante p****t@s****u 35
pre-commit-ci[bot] 6****] 3
Bryna Hazelton b****n@g****m 1
Committer Domains (Top 20 + Academic)
sas.upenn.edu: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 3
  • Total pull requests: 7
  • Average time to close issues: 4 months
  • Average time to close pull requests: 10 days
  • Total issue authors: 2
  • Total pull request authors: 4
  • Average comments per issue: 1.0
  • Average comments per pull request: 1.29
  • Merged pull requests: 5
  • Bot issues: 0
  • Bot pull requests: 3
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • steven-murray (2)
  • r-pascua (1)
Pull Request Authors
  • pre-commit-ci[bot] (3)
  • plaplant (2)
  • bhazelton (1)
  • steven-murray (1)
Top Labels
Issue Labels
bug (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 410 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
pypi.org: bda

a tool for applying baseline-dependent averaging to a radio interferometer dataset

  • Versions: 1
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 410 Last month
Rankings
Dependent packages count: 4.7%
Downloads: 25.7%
Forks count: 29.8%
Average: 33.4%
Stargazers count: 38.9%
Dependent repos count: 67.7%
Maintainers (1)
plaplant
Last synced: 11 months ago

Dependencies

.github/workflows/run_tests.yaml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • codecov/codecov-action v1 composite