Python Space Physics Environment Data Analysis Software (pySPEDAS)

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 Status License

The Python-based Space Physics Environment Data Analysis Software (PySPEDAS) framework supports multi-mission, multi-instrument retrieval, analysis, and visualization of heliophysics time series data.

Projects Supported

Requirements

Python 3.7+ is required.

We recommend Anaconda which comes with a suite of packages useful for scientific data analysis. Step-by-step instructions for installing Anaconda can be found at: Windows, macOS, Linux

Installation

Virtual Environment

To avoid potential dependency issues with other Python packages, we suggest creating a virtual environment for PySPEDAS; you can create a virtual environment in your terminal with:

python -m venv pyspedas

To enter your virtual environment, run the 'activate' script:

Windows

.\pyspedas\Scripts\activate

macOS and Linux

source pyspedas/bin/activate

Using Jupyter notebooks with your virtual environment

To get virtual environments working with Jupyter, in the virtual environment, type:

pip install ipykernel
python -m ipykernel install --user --name pyspedas --display-name "Python (pySPEDAS)"

(note: "pyspedas" is the name of your virtual environment)

Then once you open the notebook, go to "Kernel" then "Change kernel" and select the one named "Python (PySPEDAS)"

Install

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

pip install pyspedas

Upgrade

To upgrade to the latest version of PySPEDAS:

pip install pyspedas --upgrade

Local Data Directories

The recommended way of setting your local data directory is to set the SPEDAS_DATA_DIR environment variable. SPEDAS_DATA_DIR acts as a root data directory for all missions, and will also be used by IDL (if you’re running a recent copy of the bleeding edge).

Mission specific data directories (e.g., MMS_DATA_DIR for MMS, THM_DATA_DIR for THEMIS) can also be set, and these will override SPEDAS_DATA_DIR

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 ?
  • varnames: string specifying which CDF variables to load (exact names)
  • 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)

Examples

Please see the following notebooks for examples of using PySPEDAS

Plotting

Loading Data

Additional examples of loading and plotting data can be found in the documentation for the project you're interested in (PySPEDAS projects), as well as the project's README file.

Dates and Times

Coordinate Transformations

Analysis

Documentation

For more information, please see our HTML documentation at:

https://pyspedas.readthedocs.io/

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

This version

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

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-1.4.15.tar.gz (822.5 kB view details)

Uploaded Source

Built Distribution

pyspedas-1.4.15-py3-none-any.whl (1.0 MB view details)

Uploaded Python 3

File details

Details for the file pyspedas-1.4.15.tar.gz.

File metadata

  • Download URL: pyspedas-1.4.15.tar.gz
  • Upload date:
  • Size: 822.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.10.4

File hashes

Hashes for pyspedas-1.4.15.tar.gz
Algorithm Hash digest
SHA256 cf8aefbf0adff2b06d858331dceed306eaa6b3203e830ddbd76b433020388c21
MD5 e999e577be0bde6c890a364f14c59c15
BLAKE2b-256 a3a6225cae24c3cf51c53e26506f111aee3c24758927ec2a2a775ce74028daed

See more details on using hashes here.

File details

Details for the file pyspedas-1.4.15-py3-none-any.whl.

File metadata

  • Download URL: pyspedas-1.4.15-py3-none-any.whl
  • Upload date:
  • Size: 1.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.10.4

File hashes

Hashes for pyspedas-1.4.15-py3-none-any.whl
Algorithm Hash digest
SHA256 9369cd19fc91af9cea3c142545438f0d7ef33b0d35f500ed8f3e4ed8caa04cc4
MD5 25e8db42faa38b79251a24e1ee5da7fb
BLAKE2b-256 edfe2985845536a7c025e4305fc83d4062301260bd87382473dee4c37e45ba85

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