Skip to main content

Python Space Physics Environment Data Analysis

Project description

LicenseMIT LicenseCC PyPi VPython DocSphinx Maintenance Lint

The Python package pyrfu is a software based on the IRFU-MATLAB library to work with space data, particularly the Magnetospheric MultiScale (MMS) mission.

It is distributed under the open-source MIT license.

Full documentation can be found here

Instalation

The package pyrfu has been tested only for Mac OS.

Using PyPi

pyrfu is available for pip.

pip install pyrfu

From sources

The sources are located on GitHub:

https://github.com/louis-richard/irfu-python

  1. Clone the GitHub repo:

Open a terminal and write the below command to clone in your PC the pyrfu repo:

git clone https://github.com/louis-richard/irfu-python.git
cd pyrfu
  1. Create a virtual env

pyrfu needs a significant number of dependencies. The easiest way to get everything installed is to use a virtual environment.

  • Anaconda

You can create a virtual environment and install all the dependencies using conda with the following commands:

pip install conda
conda create -n pyrfu
source activate pyrfu
  • Virtual Env

Virtualenv can also be used:

pip install virtualenv
virtualenv pyrfu
source pyrfu/bin/activate
  1. Install the package via the commands:

python setup.py install

5) (Optional) Generate the docs: install the extra dependencies of doc and run the setup.py file:

pip install pyrfu
python setup.py build_sphinx

Once installed, the doc can be generated with:

cd doc
make html

Dependencies

The required dependencies are:

Testing dependencies are:

Extra testing dependencies:

Usage

To import generic space plasma physics functions

from pyrfu import pyrf

To import functions specific to MMS mission

from pyrfu import mms

To import plotting functions

from pyrfu import plot as pltrf

Configuration

Configuration settings are set in the CONFIG hash table in the mms_config.py file.

Credits

This software was developped by Louis RICHARD (louisr@irfu.se) based on the IRFU-MATLAB library.

Acknowledgement

Please use the following to acknowledge use of pyrfu in your publications: Data analysis was performed using the pyrfu analysis package available at https://github.com/louis-richard/irfu-python

Additional Information

MMS Science Data Center: https://lasp.colorado.edu/mms/sdc/public/

MMS Datasets: https://lasp.colorado.edu/mms/sdc/public/datasets/

MMS - Goddard Space Flight Center: http://mms.gsfc.nasa.gov/

Project details


Release history Release notifications | RSS feed

This version

1.8.6

Download files

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

Source Distribution

pyrfu-1.8.6.tar.gz (120.4 kB view details)

Uploaded Source

Built Distribution

pyrfu-1.8.6-py3-none-any.whl (192.7 kB view details)

Uploaded Python 3

File details

Details for the file pyrfu-1.8.6.tar.gz.

File metadata

  • Download URL: pyrfu-1.8.6.tar.gz
  • Upload date:
  • Size: 120.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.3

File hashes

Hashes for pyrfu-1.8.6.tar.gz
Algorithm Hash digest
SHA256 0f75f54581ae28d28ecbb13683b4ef4c9dbeef036e520b7ab639ca86f4de3f25
MD5 4760c24dab06529add5ac9a93c2ed412
BLAKE2b-256 ac38cedc672df3e686423cb80bb4bcdc8948c690c4919a359e678c79dedb92ed

See more details on using hashes here.

Provenance

File details

Details for the file pyrfu-1.8.6-py3-none-any.whl.

File metadata

  • Download URL: pyrfu-1.8.6-py3-none-any.whl
  • Upload date:
  • Size: 192.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.3

File hashes

Hashes for pyrfu-1.8.6-py3-none-any.whl
Algorithm Hash digest
SHA256 29c83a25ed3ca59bc5d9603bb6b5651daf83ce6abdb0409bbead02f3b8e5d25a
MD5 fa5ba4afb90e5c96e1b47e0ac0c8b5ba
BLAKE2b-256 9384c60a20e317472039b4211db1a285599a27228c4c83314ef80055371e9679

See more details on using hashes here.

Provenance

Supported by

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