Geotail

The routines in this module can be used to load data from the Geotail mission.

Magnetic Field Experiment (MGF)

pyspedas.geotail.mgf(trange=['2018-11-5', '2018-11-6'], datatype='k0', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the MGF instrument

Parameters:

trange (list of str) – time range of interest [starttime, endtime] with the format ‘YYYY-MM-DD’,’YYYY-MM-DD’] or to specify more or less than a day [‘YYYY-MM-DD/hh:mm:ss’,’YYYY-MM-DD/hh:mm:ss’]
datatype (str) – Data type; Valid options:
suffix (str) – The tplot variable names will be given this suffix. By default, no suffix is added.
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. By default, only loads in data with a “VAR_TYPE” attribute of “data”.
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. By default, all variables are loaded in.
varnames (list of str) – List of variable names to load (if not specified, all data variables are loaded)
downloadonly (bool) – Set this flag to download the CDF files, but not load them into tplot variables
notplot (bool) – Return the data in hash tables instead of creating tplot variables
no_update (bool) – If set, only load data from your local cache
time_clip (bool) – Time clip the variables to exactly the range specified in the trange keyword

Return type:

List of tplot variables created.

Example

import pyspedas
from pytplot import tplot
mgf_vars = pyspedas.geotail.mgf(trange=['2018-11-5', '2018-11-6'])
tplot(['IB', 'IB_vector'])

Electric Field Detector (EFD)

pyspedas.geotail.efd(trange=['2018-11-5', '2018-11-6'], datatype='k0', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the EFD instrument

Parameters:

trange (list of str) – time range of interest [starttime, endtime] with the format ‘YYYY-MM-DD’,’YYYY-MM-DD’] or to specify more or less than a day [‘YYYY-MM-DD/hh:mm:ss’,’YYYY-MM-DD/hh:mm:ss’]
datatype (str) – Data type; Valid options:
suffix (str) – The tplot variable names will be given this suffix. By default, no suffix is added.
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. By default, only loads in data with a “VAR_TYPE” attribute of “data”.
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. By default, all variables are loaded in.
varnames (list of str) – List of variable names to load (if not specified, all data variables are loaded)
downloadonly (bool) – Set this flag to download the CDF files, but not load them into tplot variables
notplot (bool) – Return the data in hash tables instead of creating tplot variables
no_update (bool) – If set, only load data from your local cache
time_clip (bool) – Time clip the variables to exactly the range specified in the trange keyword

Return type:

List of tplot variables created.

Example

import pyspedas
from pytplot import tplot
efd_vars = pyspedas.geotail.efd(trange=['2018-11-5', '2018-11-6'])
tplot(['Es', 'Ss', 'Bs', 'Vs', 'Ew', 'Sw', 'Bw', 'Vw'])

Low Energy Particle experiment (LEP)

pyspedas.geotail.lep(trange=['2018-11-5', '2018-11-6'], datatype='k0', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the LEP instrument

Parameters:

trange (list of str) – time range of interest [starttime, endtime] with the format ‘YYYY-MM-DD’,’YYYY-MM-DD’] or to specify more or less than a day [‘YYYY-MM-DD/hh:mm:ss’,’YYYY-MM-DD/hh:mm:ss’]
datatype (str) – Data type; Valid options:
suffix (str) – The tplot variable names will be given this suffix. By default, no suffix is added.
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. By default, only loads in data with a “VAR_TYPE” attribute of “data”.
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. By default, all variables are loaded in.
varnames (list of str) – List of variable names to load (if not specified, all data variables are loaded)
downloadonly (bool) – Set this flag to download the CDF files, but not load them into tplot variables
notplot (bool) – Return the data in hash tables instead of creating tplot variables
no_update (bool) – If set, only load data from your local cache
time_clip (bool) – Time clip the variables to exactly the range specified in the trange keyword

Return type:

List of tplot variables created.

Example

import pyspedas
from pytplot import tplot
lep_vars = pyspedas.geotail.lep(trange=['2018-11-5/05:00', '2018-11-5/06:00'], time_clip=True)
tplot(['N0', 'V0'])

Comprehensive Plasma Instrumentation (CPI)

pyspedas.geotail.cpi(trange=['2018-11-5', '2018-11-6'], datatype='k0', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the CPI instrument

Parameters:

trange (list of str) – time range of interest [starttime, endtime] with the format ‘YYYY-MM-DD’,’YYYY-MM-DD’] or to specify more or less than a day [‘YYYY-MM-DD/hh:mm:ss’,’YYYY-MM-DD/hh:mm:ss’]
datatype (str) – Data type; Valid options:
suffix (str) – The tplot variable names will be given this suffix. By default, no suffix is added.
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. By default, only loads in data with a “VAR_TYPE” attribute of “data”.
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. By default, all variables are loaded in.
varnames (list of str) – List of variable names to load (if not specified, all data variables are loaded)
downloadonly (bool) – Set this flag to download the CDF files, but not load them into tplot variables
notplot (bool) – Return the data in hash tables instead of creating tplot variables
no_update (bool) – If set, only load data from your local cache
time_clip (bool) – Time clip the variables to exactly the range specified in the trange keyword

Return type:

List of tplot variables created.

Example

import pyspedas
from pytplot import tplot
cpi_vars = pyspedas.geotail.cpi(trange=['2018-11-5/15:00', '2018-11-5/18:00'], time_clip=True)
tplot(['SW_P_Den', 'SW_P_AVGE', 'SW_V', 'HP_P_Den'])

Energetic Particles and Ion Composition Instrument (EPIC)

pyspedas.geotail.epic(trange=['2018-11-5', '2018-11-6'], datatype='k0', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the EPIC instrument

Parameters:

trange (list of str) – time range of interest [starttime, endtime] with the format ‘YYYY-MM-DD’,’YYYY-MM-DD’] or to specify more or less than a day [‘YYYY-MM-DD/hh:mm:ss’,’YYYY-MM-DD/hh:mm:ss’]
datatype (str) – Data type; Valid options:
suffix (str) – The tplot variable names will be given this suffix. By default, no suffix is added.
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. By default, only loads in data with a “VAR_TYPE” attribute of “data”.
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. By default, all variables are loaded in.
varnames (list of str) – List of variable names to load (if not specified, all data variables are loaded)
downloadonly (bool) – Set this flag to download the CDF files, but not load them into tplot variables
notplot (bool) – Return the data in hash tables instead of creating tplot variables
no_update (bool) – If set, only load data from your local cache
time_clip (bool) – Time clip the variables to exactly the range specified in the trange keyword

Return type:

List of tplot variables created.

Example

import pyspedas
from pytplot import tplot
epic_vars = pyspedas.geotail.epic(trange=['2018-11-5', '2018-11-6'])
tplot('IDiffI_I')

Plasma Wave Instrument (PWI)

pyspedas.geotail.pwi(trange=['2018-11-5', '2018-11-6'], datatype='k0', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the PWI instrument

Parameters:

trange (list of str) – time range of interest [starttime, endtime] with the format ‘YYYY-MM-DD’,’YYYY-MM-DD’] or to specify more or less than a day [‘YYYY-MM-DD/hh:mm:ss’,’YYYY-MM-DD/hh:mm:ss’]
datatype (str) – Data type; Valid options:
suffix (str) – The tplot variable names will be given this suffix. By default, no suffix is added.
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. By default, only loads in data with a “VAR_TYPE” attribute of “data”.
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. By default, all variables are loaded in.
varnames (list of str) – List of variable names to load (if not specified, all data variables are loaded)
downloadonly (bool) – Set this flag to download the CDF files, but not load them into tplot variables
notplot (bool) – Return the data in hash tables instead of creating tplot variables
no_update (bool) – If set, only load data from your local cache
time_clip (bool) – Time clip the variables to exactly the range specified in the trange keyword

Return type:

List of tplot variables created.

Example

import pyspedas
from pytplot import tplot
pwi_vars = pyspedas.geotail.pwi(trange=['2018-11-5/06:00', '2018-11-5/07:00'], time_clip=True)
tplot(['MCAE_AVE', 'MCAB_AVE'])