Advanced Composition Explorer (ACE)

The routines in this module can be used to load data from the Advanced Composition Explorer (ACE) mission.

Magnetometer (MFI)

pyspedas.ace.mfi(trange=['2018-11-5', '2018-11-6'], datatype='h3', 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:
h0: 16-Second Level 2 Data h1: 4-Minute Level 2 Data h2: 1-Hour Level 2 Data h3: (default) 1-Second Level 2 Data k0: 5-Minute Key Parameters [PRELIM] k1: 16-Second Key Parameters [PRELIM] k2: 1-Hour Key Parameters [PRELIM]
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.ace.mfi(trange=['2018-11-5', '2018-11-6'])
tplot(['BGSEc', 'Magnitude'])

Solar Wind Electron, Proton and Alpha Monitor (SWEPAM)

pyspedas.ace.swe(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 Solar Wind Electron, Proton and Alpha Monitor (SWEPAM)

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:
h0: (default) 64-Second Level 2 Data h2: 1-Hour Level 2 Data k0: 5-Minute Key Parameters [PRELIM] k1: 1-Hour Key Parameters [PRELIM]
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.ace.swe(trange=['2018-11-5', '2018-11-6'])
tplot(['Vp', 'Tpr'])

Electron, Proton, and Alpha-particle Monitor (EPAM)

pyspedas.ace.epam(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 Electron Proton Alpha Monitor (EPAM)

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:
h1: 5-Minute Level 2 Data h2: 1-Hour Level 2 Data h3: 12-second Level 2 Data k0: (default) 5-Minute Key Parameters k1: 1-Hour Key Parameters
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
epam_vars = pyspedas.ace.epam(trange=['2018-11-5', '2018-11-6'])
tplot(['H_lo', 'Ion_very_lo', 'Ion_lo', 'Ion_mid', 'Ion_hi', 'Electron_lo', 'Electron_hi'])

Cosmic Ray Isotope Spectrometer (CRIS)

pyspedas.ace.cris(trange=['2018-11-5', '2018-11-6'], datatype='h2', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the Cosmic Ray Isotope Spectrometer (CRIS)

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:
h2: (default) 1-Hour Level 2 Data h3: Daily-averaged Level 2 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
cris_vars = pyspedas.ace.cris(trange=['2018-11-5', '2018-11-6'])
tplot(['flux_B', 'flux_C', 'flux_N', 'flux_O', 'flux_F', 'flux_Ne'])

Solar Isotope Spectrometer (SIS)

pyspedas.ace.sis(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 Solar Isotope Spectrometer (SIS)

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:
h1: (default) 256-sec Level 2 Data h2: 1-Hour Level 2 Data k0: 1-Hour Key Parameters
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
sis_vars = pyspedas.ace.sis(trange=['2018-11-5', '2018-11-6'])
tplot(['H_lo', 'H_hi', 'CNO_lo', 'CNO_hi', 'Z_ge_10'])

Ultra Low Energy Isotope Spectrometer (ULEIS)

pyspedas.ace.uleis(trange=['2018-11-5', '2018-11-6'], datatype='h2', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the Ultra Low Energy Isotope Spectrometer (ULEIS)

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:
h2: 1-Hour Level 2 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
uleis_vars = pyspedas.ace.uleis(trange=['2018-11-5', '2018-11-6'])
tplot(['H_S1', 'H_S2', 'H_S3', 'H_S4', 'H_S5'])

Solar Energetic Particle Ionic Charge Analyzer (SEPICA)

pyspedas.ace.sepica(trange=['2004-11-5', '2004-11-6'], datatype='h2', 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 Energetic Particle Ionic Charge Analyzer (SEPICA)

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:
h2: 1-Hour Level 2 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
sepica_vars = pyspedas.ace.sepica(trange=['2004-11-5', '2004-11-6'])
tplot(['H1', 'H2', 'H3'])

Solar Wind Ion Composition Spectrometer (SWICS)

pyspedas.ace.swics(trange=['2018-11-5', '2018-11-6'], datatype='sw2_h3', 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 Ion Composition Spectrometer (SWICS)

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:
sw2_h3: (default) SWICS 2.0 Solar Wind 2-Hour Level 2 Data swi_h2: SWICS 1.1 Solar Wind 1-Hour Level 2 Data swi_h3: SWICS 1.1 Solar Wind 2-Hour Level 2 Data swi_h4: SWICS 1.1 Solar Wind 1-Day Level 2 Data swi_h5: SWICS 1.1 Solar Wind 2-Hour Level 2 Q-state distributions swi_h6: Solar Wind Protons 12-min Level 2 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
swi_vars = pyspedas.ace.swics(trange=['2018-11-5', '2018-11-6'])
tplot(['vHe2', 'vthHe2'])