Dynamics Explorer 2 (DE2)

The routines in this module can be used to load data from the Dynamics Explorer 2 (DE2) mission.

Magnetometer (MAG)

pyspedas.de2.mag(trange=['1983-02-10', '1983-02-11'], datatype='62ms', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads data from the Magnetometer (MAG) for mission DE2

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: ‘62ms’

  • 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
mag_vars = pyspedas.de2.mag(trange=['1983-02-10', '1983-02-11'])
tplot(['bx', 'by', 'bz'])
_images/de2_mag.png

Neutral Atmosphere Composition Spectrometer (NACS)

pyspedas.de2.nacs(trange=['1983-02-01', '1983-02-02'], datatype='neutral1s', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads data from the Neutral Atmosphere Composition Spectrometer (NACS)

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: ‘neutral1s’

  • 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
nacs_vars = pyspedas.de2.nacs(trange=['1983-02-10', '1983-02-11'])
tplot(['O_density', 'N_density'])
_images/de2_nacs.png

Retarding Potential Analyzer (RPA)

pyspedas.de2.rpa(trange=['1983-02-10', '1983-02-11'], datatype='ion2s', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads data from the Retarding Potential Analyzer (RPA)

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: ‘ion2s’

  • 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
rpa_vars = pyspedas.de2.rpa(trange=['1983-02-10', '1983-02-11'])
tplot(['ionDensity', 'ionTemperature'])
_images/de2_rpa.png

Fabry-Pérot Interferometer (FPI)

pyspedas.de2.fpi(trange=['1983-02-10', '1983-02-11'], datatype='8s', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads data from the Fabry-Pérot Interferometer (FPI)

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:

    ‘8s’ for 8-second resolution data

  • 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
fpi_vars = pyspedas.de2.fpi(trange=['1983-02-10', '1983-02-11'])
tplot('TnF')
_images/de2_fpi.png

Ion Drift Meter (IDM)

pyspedas.de2.idm(trange=['1983-02-10', '1983-02-11'], datatype='250ms', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads data from the Ion Drift Meter (IDM)

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: ‘250ms’

  • 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
idm_vars = pyspedas.de2.idm(trange=['1983-02-10', '1983-02-11'])
tplot(['ionVelocityZ', 'ionVelocityY'])
_images/de2_idm.png

Wind and Temperature Spectrometer (WATS)

pyspedas.de2.wats(trange=['1983-02-10', '1983-02-11'], datatype='2s', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads data from the Wind and Temperature Spectrometer (WATS)

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:

    ‘2s’ for 2 second data

  • 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
wats_vars = pyspedas.de2.wats(trange=['1983-02-10', '1983-02-11'])
tplot(['density', 'Tn'])
_images/de2_wats.png

Vector Electric Field Instrument (VEFI)

pyspedas.de2.vefi(trange=['1983-02-10', '1983-02-11'], datatype='ac500ms', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads data from the Vector Electric Field Instrument (VEFI)

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:

    ‘ac500ms’, ‘dca500ms’

  • 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
vefi_vars = pyspedas.de2.vefi(trange=['1983-02-10', '1983-02-11'])
tplot(['spectA', 'spectB', 'spectC'])
_images/de2_vefi.png

Langmuir Probe Instrument (LANG)

pyspedas.de2.lang(trange=['1983-02-10', '1983-02-11'], datatype='500ms', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads data from the Langmuir Probe Instrument (LANG)

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: ‘500ms’

  • 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
lang_vars = pyspedas.de2.lang(trange=['1983-02-10', '1983-02-11'])
tplot(['plasmaDensity', 'electronTemp'])
_images/de2_lang.png