Wind

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

Magnetic Field Investigation (MFI)

pyspedas.wind.mfi(trange=['2018-11-5', '2018-11-6'], datatype='h0', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the Fluxgate Magnetometer

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
mfi_vars = pyspedas.wind.mfi(trange=['2013-11-5', '2013-11-6'])
tplot('BGSE')

Solar Wind Experiment (SWE)

pyspedas.wind.swe(trange=['2018-11-5', '2018-11-6'], datatype='h5', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the SWE 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
swe_vars = pyspedas.wind.swe(trange=['2013-11-5', '2013-11-6'])
tplot(['N_elec', 'T_elec'])

Radio and Plasma Waves (WAVES)

pyspedas.wind.waves(trange=['2018-11-5', '2018-11-6'], datatype='h1', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads Radio/Plasma Wave (WAVES) data

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
waves_vars = pyspedas.wind.waves(trange=['2013-11-5', '2013-11-6'])
tplot(['E_VOLTAGE_RAD2', 'E_VOLTAGE_RAD1', 'E_VOLTAGE_TNR'])

3D Plasma Analyzer (3DP)

pyspedas.wind.threedp(trange=['1999-11-5', '1999-11-6'], datatype='3dp_emfits_e0', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, berkeley=False, time_clip=False, addmaster=False)

This function loads 3DP data

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
threedp_vars = pyspedas.wind.threedp()
tplot(['V_e_xyz_gse_wi_3dp', 'N_e_dens_wi_3dp', 'T_e_par_wi_3dp'])

Solar Wind and Suprathermal Ion Composition Experiment (SMS)

pyspedas.wind.sms(trange=['1999-11-5', '1999-11-6'], 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 Solar Wind and Suprathermal Ion Composition 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
sms_vars = pyspedas.wind.sms()
tplot(['C_ion_temp', 'O_ion_temp'])

Orbit data

pyspedas.wind.orbit(trange=['1999-11-5', '1999-11-6'], datatype='pre_or', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads orbit data

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
orb_vars = pyspedas.wind.orbit(trange=['2013-11-5', '2013-11-6'])
tplot(['GSE_POS', 'GSE_VEL', 'GSM_POS', 'GSM_VEL'])