Skip to main content

The Birkeland current model presented by Coxon et al. (2016), based on Milan (2013).

Project description

facer-model

PyPI badge Zenodo badge Tests badge

Field-Aligned Currents Estimated from Reconnection (FACER) is a Python implementation of the Birkeland current model presented by Coxon et al. (2016), based on Milan (2013). It is a simple mathematical model of the region 1 and 2 Birkeland current system intensities for differing dayside and nightside magnetic reconnection rates, consistent with the expanding/contracting polar cap paradigm of solar wind-magnetosphere-ionosphere coupling.

Citations

When using this software, please cite the Zenodo record as well as the following two papers:

Funding

John C Coxon was supported during this work by Science and Technology Facilities Council (STFC) Ernest Rutherford Fellowship ST/V004883/1.

Installation

To install and test the model, simply type:

pip install facer-model
pytest tests/test.py

Usage

A very basic instantiation of the model can be seen below. For more examples, check out the notebooks in the repository, which explicitly detail how to use the model to replicate the results from the two papers which define the model.

from facer import Model

dayside_reconnection_rate = 50       # in kV
nightside_reconnection_rate = 50     # in kV
solar_radio_flux = 80                # in SFU
time = datetime.datetime(2010, 1, 1)
hemisphere = "north"
polar_cap_flux = 0.5                 # in GWb

model = Model(dayside_reconnection_rate,
              nightside_reconnection_rate,
              solar_radio_flux,
              time,
              hemisphere,
              polar_cap_flux)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

facer_model-1.0.8.tar.gz (25.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

facer_model-1.0.8-py3-none-any.whl (22.9 kB view details)

Uploaded Python 3

File details

Details for the file facer_model-1.0.8.tar.gz.

File metadata

  • Download URL: facer_model-1.0.8.tar.gz
  • Upload date:
  • Size: 25.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for facer_model-1.0.8.tar.gz
Algorithm Hash digest
SHA256 ae96f88a258a4be8c64639093bafe3f529920699e0ff4af7277500a85959d4cd
MD5 c3b24308c49ac275b096b694e09ac16d
BLAKE2b-256 a8f1086cf75ba115e5afd5c8be1bce740b0e43a0055d429e127b30e258aade6c

See more details on using hashes here.

Provenance

The following attestation bundles were made for facer_model-1.0.8.tar.gz:

Publisher: pypi.yaml on johncoxon/facer-model

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file facer_model-1.0.8-py3-none-any.whl.

File metadata

  • Download URL: facer_model-1.0.8-py3-none-any.whl
  • Upload date:
  • Size: 22.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for facer_model-1.0.8-py3-none-any.whl
Algorithm Hash digest
SHA256 0470e439ca57de7ff597c8896600aa2d19409ae4154d6df2f31b8558218a34cb
MD5 da220290f672f9b9efd1d2a8d774ef29
BLAKE2b-256 6dffb6628c8027207d3d8b20d9d4022667da5ba8bd4dd0c4b413f7aa0c08959d

See more details on using hashes here.

Provenance

The following attestation bundles were made for facer_model-1.0.8-py3-none-any.whl:

Publisher: pypi.yaml on johncoxon/facer-model

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page