Python Space Physics Environment Data Analysis Software (SPEDAS)

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for jameswilburlewis from gravatar.com jameswilburlewis Avatar for nickssl from gravatar.com nickssl Avatar for supervised from gravatar.com supervised

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Project description

pySPEDAS

build Coverage Status Version License Status

pySPEDAS is an implementation of the SPEDAS framework in python.

The Space Physics Environment Data Analysis Software (SPEDAS) framework is written in IDL and contains data loading, data analysis and data plotting tools for various scientific missions (NASA, NOAA, etc.) and ground magnetometers.

Projects Supported

Requirements

Python 3.5+ is required.

We recommend Anaconda which comes with a suite of packages useful for scientific data analysis.

Installation

pySPEDAS supports Windows, macOS and Linux. To get started, install the pyspedas package using PyPI:

PyPI

pip install pyspedas --upgrade

Usage

To get started, import pyspedas and pytplot:

import pyspedas
from pytplot import tplot

You can load data into tplot variables by calling pyspedas.mission.instrument(), e.g.,

To load and plot 1 day of THEMIS FGM data for probe 'd':

thm_fgm = pyspedas.themis.fgm(trange=['2015-10-16', '2015-10-17'], probe='d')

tplot(['thd_fgs_gse', 'thd_fgs_gsm'])

To load and plot 2 minutes of MMS burst mode FGM data:

mms_fgm = pyspedas.mms.fgm(trange=['2015-10-16/13:05:30', '2015-10-16/13:07:30'], data_rate='brst')

tplot(['mms1_fgm_b_gse_brst_l2', 'mms1_fgm_b_gsm_brst_l2'])

Note: by default, pySPEDAS loads all data contained in CDFs found within the requested time range; this can potentially load data outside of your requested trange. To remove the data outside of your requested trange, set the time_clip keyword to True

To load and plot 6 hours of PSP SWEAP/SPAN-i data:

spi_vars = pyspedas.psp.spi(trange=['2018-11-5', '2018-11-5/06:00'], time_clip=True)

tplot(['DENS', 'VEL', 'T_TENSOR', 'TEMP'])

To download 5 days of STEREO magnetometer data (but not load them into tplot variables):

stereo_files = pyspedas.stereo.mag(trange=['2013-11-1', '2013-11-6'], downloadonly=True)

Standard Options

  • trange: two-element list specifying the time range of interest. This keyword accepts a wide range of formats
  • time_clip: if set, clip the variables to the exact time range specified by the trange keyword
  • suffix: string specifying a suffix to append to the loaded variables
  • varformat: string specifying which CDF variables to load; accepts the wild cards * and ?
  • get_support_data: if set, load the support variables from the CDFs
  • downloadonly: if set, download the files but do not load them into tplot
  • no_update: if set, only load the data from the local cache
  • notplot: if set, load the variables into dictionaries containing numpy arrays (instead of creating the tplot variables)

Getting Help

To find the options supported, call help on the instrument function you're interested in:

help(pyspedas.themis.fgm)

You can ask questions by creating an issue or by joining the SPEDAS mailing list.

Contributing

We welcome contributions to pySPEDAS; to learn how you can contribute, please see our Contributing Guide

Code of Conduct

In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation. To learn more, please see our Code of Conduct.

Additional Information

For examples of pyspedas, see: https://github.com/spedas/pyspedas_examples

For MMS examples, see: https://github.com/spedas/mms-examples

For pytplot, see: https://github.com/MAVENSDC/PyTplot

For cdflib, see: https://github.com/MAVENSDC/cdflib

For SPEDAS, see http://spedas.org/

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for jameswilburlewis from gravatar.com jameswilburlewis Avatar for nickssl from gravatar.com nickssl Avatar for supervised from gravatar.com supervised

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

1.7.0

1.6.3

1.6.2

1.6.1 yanked

Reason this release was yanked:

Missing files due to packaging error

1.6.0 yanked

Reason this release was yanked:

Missing files due to packaging error

1.5.18

1.5.17

1.5.16

1.5.15

1.5.14

1.5.13

1.5.12

1.5.11

1.5.10

1.5.9

1.5.8

1.5.7

1.5.6

1.5.5

1.5.4

1.5.3

1.5.1

1.5.0

1.4.47

1.4.46

1.4.45

1.4.44

1.4.43

1.4.42

1.4.41

1.4.40

1.4.39

1.4.38

1.4.37

1.4.36

1.4.35

1.4.34

1.4.33

1.4.32

1.4.31

1.4.30

1.4.29

1.4.28

1.4.27

1.4.26

1.4.25

1.4.24

1.4.23

1.4.22

1.4.21

1.4.20

1.4.19

1.4.18

1.4.17

1.4.16

1.4.15

1.4.14

1.4.13

1.4.12

1.4.11

1.4.10

1.4.9

1.4.8

1.4.7

1.4.6

1.4.4

1.4.3

1.4.2

1.4.1

1.4.0

1.3.24

1.3.23

1.3.22

1.3.21

1.3.20

1.3.19

1.3.18

1.3.17

1.3.16

1.3.15

1.3.14

1.3.13

1.3.12

1.3.11

1.3.10

1.3.9

1.3.8

1.3.7

1.3.6

1.3.5

1.3.4

1.3.3

1.3.2

1.3.1

1.3.0

1.2.10

1.2.9

1.2.8

1.2.7

1.2.6

1.2.5

1.2.4

1.2.3

1.2.2

1.2.1

1.2.0

1.1.6

1.1.5

1.1.4

1.1.3

1.1.2

1.1.1

1.0.17

1.0.16

1.0.15

1.0.14

1.0.13

1.0.12

1.0.11

1.0.10

1.0.9

1.0.8

1.0.7

1.0.6

1.0.5

1.0.4

1.0.3

1.0.2

This version

1.0.1

1.0

0.9.31

0.9.29

0.9.28

0.9.27

0.9.26

0.9.25

0.9.24

0.9.23

0.9.22

0.9.21

0.9.20

0.9.19

0.9.18

0.9.17

0.9.16

0.9.15

0.9.14

0.9.13

0.9.12

0.9.11

0.9.10

0.9.9

0.9.8

0.9.7

0.9.6

0.9.5

0.9.4

0.9.3

0.9.2

0.9.1

0.9.0

0.8.33

0.8.32

0.8.31

0.8.30

0.8.29

0.8.28

0.8.27

0.8.26

0.8.25

0.8.24

0.8.23

0.8.21

0.8.20

0.8.19

0.8.12

0.8.11

0.8.10

0.8.9

0.8.8

0.8.7

0.8.6

0.8.5

0.8.4

0.8.3

0.8.2

0.8.1

0.8.0

0.7.12

0.7.11

0.7.10

0.7.9

0.7.8

0.7.7

0.7.6

0.7.5

0.7.4

0.7.3

0.7.2

0.7.1

0.7.0

0.6.29

0.6.28

0.6.27

0.6.26

0.6.25

0.6.21

0.6.20

0.6.19

0.6.18

0.6.17

0.6.16

0.6.15

0.6.14

0.6.13

0.6.12

0.6.11

0.6.10

0.6.9

0.6.8

0.6.7

0.6.6

0.6.4

0.6.3

0.6.2

0.6.1

0.6.0

0.5.12

0.5.11

0.5.10

0.5.9

0.5.8

0.5.7

0.5.6

0.5.5

0.5.4

0.5.3

0.5.2

0.5.1

0.5.0

0.4.5

0.4.4

0.4.3

0.4.2

0.4.0

0.3.0

0.2.4

0.2.3

0.2.2

Download files

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

Source Distribution

pyspedas-1.0.1.tar.gz (527.0 kB view details)

Uploaded Source

Built Distribution

pyspedas-1.0.1-py2.py3-none-any.whl (631.0 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file pyspedas-1.0.1.tar.gz.

File metadata

  • Download URL: pyspedas-1.0.1.tar.gz
  • Upload date:
  • Size: 527.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.0.0.post20200309 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6

File hashes

Hashes for pyspedas-1.0.1.tar.gz
Algorithm Hash digest
SHA256 4b92007950caf2c26631b5108032b12741e23e7b23b35b80ce8ac7d8ab75d56e
MD5 37a0cf4004110c17d49837a06219ecbd
BLAKE2b-256 01d11346ed8d54289331a2073903fc226fc315eeecce7788a4f09020bf349423

See more details on using hashes here.

File details

Details for the file pyspedas-1.0.1-py2.py3-none-any.whl.

File metadata

  • Download URL: pyspedas-1.0.1-py2.py3-none-any.whl
  • Upload date:
  • Size: 631.0 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.0.0.post20200309 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6

File hashes

Hashes for pyspedas-1.0.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 657bb0b48894247eeea2e779c94b727631fce49a983d82f9f7b21fa94a3148b6
MD5 e14db5b02acab67a1e53f4ffbd455151
BLAKE2b-256 e5dc2f6189b0aa7f2cb65f37c61de8e4cc7c077c560bfc69072702116895ae1c

See more details on using hashes here.

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