Aurora

Aurora: An open-source Python implementation of the EMTF package for magnetotelluric data processing using MTH5 and mt_metadata - Published in JOSS (2024)

https://github.com/simpeg/aurora

Science Score: 100.0%

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

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CITATION.cff file
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Found 1 DOI reference(s) in JOSS metadata
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3 of 9 committers (33.3%) from academic institutions
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JOSS paper metadata
Published in Journal of Open Source Software

Last synced: 4 months ago · JSON representation ·

Repository

software for processing natural source electromagnetic data

Basic Info

Host: GitHub
Owner: simpeg
License: mit
Language: Jupyter Notebook
Default Branch: main
Size: 49.6 MB

Statistics

Stars: 23
Watchers: 7
Forks: 6
Open Issues: 87
Releases: 5

Created over 4 years ago · Last pushed 5 months ago

Metadata Files

Readme Contributing License Citation

README.rst

.. image:: docs/figures/aurora_logo.png
:width: 900
:alt: AURORA

.. image:: https://img.shields.io/pypi/v/aurora.svg
:target: https://pypi.python.org/pypi/aurora

.. image:: https://img.shields.io/conda/v/conda-forge/aurora.svg
:target: https://anaconda.org/conda-forge/aurora

.. image:: https://img.shields.io/pypi/l/aurora.svg
:target: https://pypi.python.org/pypi/aurora

Aurora is an open-source package that robustly estimates single station and remote reference electromagnetic transfer functions (TFs) from magnetotelluric (MT) time series. Aurora is part of an open-source processing workflow that leverages the self-describing data container `MTH5 `_, which in turn leverages the general `mt-metadata `_ framework to manage metadata. These pre-existing packages simplify the processing by providing managed data structures, transfer functions to be generated with only a few lines of code. The processing depends on two inputs -- a table defining the data to use for TF estimation, and a JSON file specifying the processing parameters, both of which are generated automatically, and can be modified if desired. Output TFs are returned as mt-metadata objects, and can be exported to a variety of common formats for plotting, modeling and inversion.

Key Features
-------------

- Tabular data indexing and management (Pandas dataframes),
- Dictionary-like processing parameters configuration
- Programmatic or manual editing of inputs
- Largely automated workflow

Documentation for the Aurora project can be found at http://simpeg.xyz/aurora/

Installation
---------------

Suggest using PyPi as the default repository to install from

``pip install aurora``

Can use Conda but that is not updated as often

``conda -c conda-forge install aurora``

General Work Flow
-------------------

1. Convert raw time series data to MTH5 format, see `MTH5 Documentation and Examples `_.
2. Understand the time series data and which runs to process for local station `RunSummary`.
3. Choose remote reference station ``KernelDataset``.
4. Create a recipe for how the data will be processed ``Config``.
5. Estimate transfer function `process_mth5` and out put as a ``mt_metadata.transfer_function.core.TF`` object which can output [ EMTFXML | EDI | ZMM | ZSS | ZRR ] files.

Owner

Name: SimPEG
Login: simpeg
Kind: organization
Email: info@simpeg.xyz

Website: http://simpeg.xyz
Repositories: 37
Profile: https://github.com/simpeg

A community and tools for open geophysics.

JOSS Publication

Aurora: An open-source Python implementation of the EMTF package for magnetotelluric data processing using MTH5 and mt_metadata

Published

August 22, 2024

DOI

10.21105/joss.06832

Volume 9, Issue 100, Page 6832

Authors

Karl N. Kappler

Space Science Institute, USA, DIAS Geophysical, Canada

Jared R. Peacock

U.S. Geological Survey, USA

Gary D. Egbert

Oregon State University, USA

Andrew Frassetto

EarthScope, USA

Lindsey Heagy

University of British Columbia, USA

Anna Kelbert

U.S. Geological Survey, USA

Laura Keyson
EarthScope, USA

Douglas Oldenburg

University of British Columbia, USA

Timothy Ronan

EarthScope, USA

Justin Sweet

EarthScope, USA

Editor

Patrick Diehl

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: aurora
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Karl
    name-particle: N.
    family-names: Kappler
    orcid: 'https://orcid.org/0000-0002-1877-1255'
  - given-names: Jared
    name-particle: R.
    family-names: Peacock
    orcid: 'https://orcid.org/0000-0002-0439-0224'
  - given-names: Gary
    name-particle: D.
    family-names: Egbert
    orcid: 'https://orcid.org/0000-0003-1276-8538'
  - orcid: 'https://orcid.org/0000-0002-8818-3731'
    given-names: Frassetto
    family-names: Andrew
  - given-names: Heagy
    family-names: Lindsey
    orcid: 'https://orcid.org/0000-0002-1551-5926'
  - given-names: Kelbert
    family-names: Anna
    orcid: 'https://orcid.org/0000-0003-4395-398X'
  - given-names: Laura
    family-names: Keyson
  - given-names: Douglas
    family-names: Oldenburg
    orcid: 'https://orcid.org/0000-0002-4327-2124'
  - given-names: Timothy
    family-names: Ronan
    orcid: 'https://orcid.org/0000-0001-8450-9573'
  - given-names: Justin
    family-names: Sweet
    orcid: 'https://orcid.org/0000-0001-7323-9758'
identifiers:
  - type: doi
    value: 10.5281/zenodo.13334589
    description: >-
      Contains the software at time of manuscript
      acceptance.
  - type: doi
    value: 10.21105/joss.06832
    description: The JOSS manuscript
repository-code: 'https://github.com/simpeg/aurora'
url: 'https://simpeg.xyz/aurora/'
abstract: >-
  The Aurora software package robustly estimates single
  station and remote reference electro-

  magnetic transfer functions (TFs) from magnetotelluric
  (MT) time series. Aurora is part of

  an open-source processing workflow that leverages the
  self-describing data container MTH5,

  which in turn leverages the general mt_metadata framework
  to manage metadata. These

  pre-existing packages simplify the processing workflow by
  providing managed data structures,

  transfer functions to be generated with only a few lines
  of code. The processing depends on

  two inputs – a table defining the data to use for TF
  estimation and a JSON file specifying

  the processing parameters, both of which are generated
  automatically and can be modified if

  desired. Output TFs are returned as mt_metadata objects,
  and can be exported to a variety

  of common formats for plotting, modeling, and inversion.
keywords:
  - open-source
  - python
  - 'magnetotelluric '
  - processing
  - transfer function
license: MIT
commit: d62c784a39c96692a3b1e10d50acb869b83d17c9
version: 0.3.14
date-released: '2024-08-30'

Papers & Mentions

Total mentions: 1

Photon Counting Imaging with Low Noise and a Wide Dynamic Range for Aurora Observations

DOI: 10.3390/s20205958
OpenAlex ID: https://openalex.org/W3094013200
Published: October 2020

Last synced: 3 months ago

GitHub Events

Total

Issues event: 8
Watch event: 7
Delete event: 8
Issue comment event: 15
Push event: 119
Pull request review event: 1
Pull request event: 25
Fork event: 4
Create event: 12

Last Year

Issues event: 8
Watch event: 7
Delete event: 8
Issue comment event: 15
Push event: 119
Pull request review event: 1
Pull request event: 25
Fork event: 4
Create event: 12

Committers

Last synced: 5 months ago

All Time

Total Commits: 1,826
Total Committers: 9
Avg Commits per committer: 202.889
Development Distribution Score (DDS): 0.113

Past Year

Commits: 302
Committers: 4
Avg Commits per committer: 75.5
Development Distribution Score (DDS): 0.149

Top Committers

Name	Email	Commits
Karl N. Kappler	m**s@g**m	1,619
JP	p**d@g**m	163
Lindsey Heagy	l**y@g**m	12
Karl Kappler	k**r@d**m	12
Joseph Capriotti	j**i@g**m	10
timronan	t**n@i**u	5
Laura Keyson	l**a@i**u	3
Seogi Kang	s**g@e**a	1
kkappler-st	k**r@s**m	1

Committer Domains (Top 20 + Academic)

iris.washington.edu: 2 soundthinking.com: 1 eos.ubc.ca: 1 diasgeo.com: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 153
Total pull requests: 105
Average time to close issues: 11 months
Average time to close pull requests: 11 days
Total issue authors: 11
Total pull request authors: 5
Average comments per issue: 1.59
Average comments per pull request: 0.86
Merged pull requests: 89
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 16
Pull requests: 29
Average time to close issues: 1 day
Average time to close pull requests: 16 days
Issue authors: 6
Pull request authors: 2
Average comments per issue: 0.38
Average comments per pull request: 0.0
Merged pull requests: 19
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

kkappler (128)
kujaku11 (11)
blsqr (3)
jlsanhueza (1)
sinanozaydin (1)
amiller448 (1)
jlmaurer (1)
jiajiasun (1)
gblsnogueira (1)
jcapriot (1)
timronan (1)

Pull Request Authors

kkappler (97)
kujaku11 (17)
laura-iris (3)
timronan (1)
sgkang (1)

Top Labels

Issue Labels

bug (11) enhancement (8) side quest (7) wontfix (5) documentation (5) question (3) duplicate (2) Phase 3 (1) critical (1)

Pull Request Labels

bug (2)

Packages

Total packages: 2
Total downloads:
- pypi 2,722 last-month

Total dependent packages: 0
(may contain duplicates)
Total dependent repositories: 1
(may contain duplicates)
Total versions: 16
Total maintainers: 3

pypi.org: aurora

Processing Codes for Magnetotelluric Data

Homepage: https://github.com/simpeg/aurora
Documentation: https://aurora.readthedocs.io/
License: MIT license
Latest release: 0.5.2
published 5 months ago

Versions: 15
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 2,722 Last month

Rankings

Dependent packages count: 7.4%

Stargazers count: 17.7%

Forks count: 19.2%

Average: 20.6%

Dependent repos count: 22.2%

Downloads: 36.4%

Maintainers (3)

kujaku11 lheagy kkappler

Last synced: 4 months ago

conda-forge.org: aurora

Homepage: https://github.com/simpeg/aurora
License: MIT
Latest release: 0.0.1
published over 4 years ago

Versions: 1
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent repos count: 34.0%

Average: 48.8%

Dependent packages count: 51.2%

Stargazers count: 52.6%

Forks count: 57.4%

Last synced: 4 months ago

Dependencies

requirements-dev.txt pypi

black *
flake8 *
nbsphinx *
numpydoc *
pre-commit *
sphinx_gallery *
sphinx_rtd_theme *

.github/workflows/tests.yml actions

actions/checkout v2 composite
codecov/codecov-action v1 composite
conda-incubator/setup-miniconda v2.1.1 composite
crazy-max/ghaction-github-pages v2.5.0 composite

Aurora

Science Score: 100.0%

Repository

Basic Info

Statistics

Metadata Files

README.rst

Owner

JOSS Publication

Aurora: An open-source Python implementation of the EMTF package for magnetotelluric data processing using MTH5 and mt_metadata

Authors

Editor

Tags

Citation (CITATION.cff)

Papers & Mentions

Photon Counting Imaging with Low Noise and a Wide Dynamic Range for Aurora Observations

GitHub Events

Total

Last Year

Committers

All Time

Past Year

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Committer Domains (Top 20 + Academic)

Issues and Pull Requests

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Packages

pypi.org: aurora

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conda-forge.org: aurora

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