pyspedas 0.9.16

Python Space Physics Environment Data Analysis Software (SPEDAS)

pySPEDAS

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

• Advanced Composition Explorer (ACE)
• Cluster
• Colorado Student Space Weather Experiment (CSSWE)
• Deep Space Climate Observatory (DSCOVR)
• Equator-S
• Fast Auroral Snapshot Explorer (FAST)
• Geotail
• Imager for Magnetopause-to-Aurora Global Exploration (IMAGE)
• Mars Atmosphere and Volatile Evolution (MAVEN)
• Magnetospheric Multiscale (MMS)
• OMNI
• Polar Orbiting Environmental Satellites (POES)
• Polar
• Parker Solar Probe (PSP)
• Van Allen Probes (RBSP)
• Solar Terrestrial Relations Observatory (STEREO)
• Time History of Events and Macroscale Interactions during Substorms (THEMIS)
• Two Wide-Angle Imaging Neutral-Atom Spectrometers (TWINS)
• Wind

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 or Anaconda:

PyPI

pip install pyspedas --upgrade

Anaconda

conda install -c spedas pyspedas

You can upgrade to the latest version using:

conda update -c spedas pyspedas

Usage

To get started, import pyspedas and pytplot:

import pyspedas
import pytplot

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

Code of Conduct

Additional Information

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

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

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