Magnetospheric Multiscale (MMS)

The routines in this module can be used to load data from the Magnetospheric Multiscale (MMS) mission.

Fluxgate Magnetometer (FGM)

pyspedas.mms.fgm(*args, **kwargs)

Load MMS fluxgate magnetometer data

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’, ‘2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
data_rate (str or list of str) – instrument data rates for FGM include ‘brst’ ‘fast’ ‘slow’ ‘srvy’. The default is ‘srvy’. Default: ‘srvy’
level (str) – indicates level of data processing. the default if no level is specified is ‘l2’ Default: ‘l2’
datatype (str or list of str) – Do not use: defined only for consistency with other load routines. All FGM data will be loaded. Default: ‘’
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: True
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: False
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: None (all variables are loaded)
exclude_format (str) – Variables matching this pattern will not be processed while loading the CDFs. Wildcard character “*” is allowed. Default: ‘rdeltahalf’
varnames (list of str) – List of variable names to load. If list is empty or not specified, all data variables are loaded. Default: []
suffix (str) – The tplot variable names will be given this suffix. Default: None
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval Default: False
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
keep_flagged (bool) – If True, don’t remove flagged data (flagged data are set to NaNs by default, this keyword turns this off) Default: False
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf (bool) – If True, download the data from the SPDF instead of the SDC Default: False
get_fgm_ephemeris (bool) – Keep the ephemeris variables in the FGM files Default: False

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> fgm_vars = pyspedas.mms.mms_load_fgm(trange=[‘2015-10-16’, ‘2015-10-17’]) >>> tplot(‘mms1_fgm_b_gsm_srvy_l2’)

FGM Example

import pyspedas
from pytplot import tplot
pyspedas.mms.fgm(trange=['2015-10-16/12:45', '2015-10-16/13:00'], time_clip=True)
tplot(['mms1_fgm_b_gsm_srvy_l2_btot', 'mms1_fgm_b_gsm_srvy_l2_bvec'])

Search-coil Magnetometer (SCM)

pyspedas.mms.scm(*args, **kwargs)

Load data from the MMS Search Coil Magnetometer (SCM)

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’, ‘2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
data_rate (str or list of str) – instrument data rates for SCM include [‘brst’ ‘fast’ ‘slow’ ‘srvy’]. Default: ‘srvy’
level (str) – indicates level of data processing. the default if no level is specified is ‘l2’ Default: ‘l2’
datatype (str or list of str) – Valid datatypes for SCM are: [‘scsrvy’, ‘cal’, ‘scb’, ‘scf’, ‘schb’, ‘scm’, ‘scs’] Default is ‘scsrvy’ for srvy data, and ‘scb’ for brst data.
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”. Default: False
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: True
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. By default, all variables are loaded in. Default: None (all variables are loaded)
varnames (list of str) – List of variable names to load. If list is empty or not specified, all data variables are loaded Default: [] (all variables are loaded)
suffix (str) – The tplot variable names will be given this suffix. Default: None
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval Default: False
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf (bool) – If True, download the data from the SPDF instead of the SDC

Return type:

List of tplot variables created.

Example

>>> import pyspedas
>>> from pytplot import tplot
>>> scm_vars = pyspedas.mms.mms_load_scm(trange=['2015-10-16', '2015-10-17'])
>>> tplot('mms1_scm_acb_gse_scsrvy_srvy_l2')

SCM Example

import pyspedas
from pytplot import tplot
pyspedas.mms.scm(trange=['2015-10-16/13:06', '2015-10-16/13:07'], time_clip=True)
tplot('mms1_scm_acb_gse_scsrvy_srvy_l2')

Level 3 FGM+SCM Data (FSM)

pyspedas.mms.fsm(*args, **kwargs)

This function loads MMS FSM (FGM + SCM) data into tplot variables

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16/05:59’, ‘2015-10-16/06:01’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
data_rate (str or list of str) – Valid values: ‘brst’ Default: ‘brst’
level (str) – indicates level of data processing. Default: ‘l3’
datatype (str or list of str) – Valid datatype for FSM is: 8khz Default: ‘8khz’
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”. Default: False
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: False
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. By default, all variables are loaded in. Default: None (all variables are loaded)
varnames (list of str) – List of variable names to load (if not specified, all data variables are loaded) Default: [] (all variables are loaded)
suffix (str) – The tplot variable names will be given this suffix. By default, no suffix is added. Default: None
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval Default: False
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf (bool) – If True, download the data from the SPDF instead of the SDC Default: False

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> fsm_data = pyspedas.mms.mms_load_fsm(trange=[‘2015-10-16/05:59’, ‘2015-10-16/06:01’]) >>> tplot([‘mms1_fsm_b_mag_brst_l3’,’mms1_fsm_b_gse_brst_l3’,’mms1_fsm_r_gse_brst_l3’])

FSM Example

import pyspedas
from pytplot import tplot
pyspedas.mms.fsm(trange=['2015-10-16/13:06', '2015-10-16/13:07'], time_clip=True)
tplot(['mms1_fsm_b_mag_brst_l3', 'mms1_fsm_b_gse_brst_l3'])

Electric field Double Probe (EDP)

pyspedas.mms.edp(*args, **kwargs)

Load data from the MMS Electric field Double Probes (EDP) instrument

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’, ‘2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
data_rate (str or list of str) – instrument data rates for EDP include [‘brst’, ‘fast’, ‘slow’, ‘srvy’]. Default: ‘fast’
level (str) – indicates level of data processing. Default: ‘l2’
datatype (str or list of str) – Valid datatypes for EDP are: [‘dce’, ‘dcv’, ‘ace’, ‘hmfe’] Default: ‘dce’
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”. Default: False
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: False
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: None (all variables are loaded)
varnames (list of str) – List of variable names to load. If list is empty or not specified, all data variables are loaded) Default: []
suffix (str) – The tplot variable names will be given this suffix. By default, no suffix is added. Default: None
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval Default: False
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf (bool) – If True, download the data from the SPDF instead of the SDC Default: False

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> edp_vars = pyspedas.mms.mms_load_edp(trange=[‘2015-10-16’, ‘2015-10-17’], probe=’1’) >>> tplot(‘mms1_edp_dce_gse_fast_l2’)

EDP Example

import pyspedas
from pytplot import tplot
pyspedas.mms.edp(trange=['2015-10-16/13:06', '2015-10-16/13:07'], time_clip=True)
tplot('mms1_edp_dce_gse_fast_l2')

Electron Drift Instrument (EDI)

pyspedas.mms.edi(*args, **kwargs)

Load data from the MMS Electron Drift Instrument (EDI)

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2016-10-16’, ‘2016-10’]
- probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
- data_rate (str or list of str) – instrument data rates for EDI include [‘brst’, ‘fast’, ‘slow’, ‘srvy’]. Default: ‘srvy’
- level (str) – indicates level of data processing. Default: ‘l2’
- datatype (str or list of str) – Valid datatypes for EDI are: [‘efield’, ‘amb’] Default: ‘efield’
- get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: False
- time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: False
- varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: None (all variables are loaded)

varnames: list of str: List of variable names to load If list is empty or not specified, all data variables are loaded Default: []
suffix: str: The tplot variable names will be given this suffix. Default: None
notplot: bool: If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available: bool: If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update: bool: Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version: str: Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version: str: Specify a minimum CDF version # to load Default: None
latest_version: bool: Only grab the latest CDF version in the requested time interval Default: False
major_version: bool: Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
always_prompt: bool: Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf: bool: If True, download the data from the SPDF instead of the SDC Default: False

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> edi_vars = pyspedas.mms.mms_load_edi(trange=[‘2016-10-16’, ‘2016-10-17’], probe=’1’) >>> tplot(‘mms1_edi_e_gse_srvy_l2’)

EDI Example

import pyspedas
from pytplot import tplot
pyspedas.mms.edi(trange=['2016-10-16/21:00', '2016-10-16/22:00'], time_clip=True)
tplot(['mms1_edi_vdrift_gse_srvy_l2', 'mms1_edi_e_gse_srvy_l2'])

Fly’s Eye Energetic Particle Sensor (FEEPS)

pyspedas.mms.feeps(*args, **kwargs)

Load data from the MMS Fly’s Eye Energetic Particle Sensor (FEEPS)

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’,’2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
data_rate (str or list of str) – instrument data rates for FEEPS include [‘brst’, ‘srvy’]. Default: ‘srvy’
level (str) – indicates level of data processing. the default if no level is specified is ‘l2’ Default: ‘l2’
datatype (str or list of str) –

Valid datatypes for FEEPS are:
L2, L1b: [‘electron’, ‘ion’] L1a: [‘electron-bottom’, ‘electron-top’, ‘ion-bottom’, ‘ion-top’]

Default: ‘electron’
data_units (str or list of str) – Unit types to be loaded, options are ‘count_rate’, ‘intensity’ Default: [‘count_rate’, ‘intensity’]
no_flatfield_corrections (bool) – If True, no flatfield corrections are performed. Default: False
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: True
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: False
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: None (all variables are loaded)
varnames (list of str) – List of variable names to load. If list is empty or not specified, all data variables are loaded. Default: []
suffix (str) – The tplot variable names will be given this suffix. By default, no suffix is added. Default: None
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed
spdf (bool) – If True, download the data from the SPDF instead of the SDC

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> feeps_data = pyspedas.mms.mms_load_feeps(trange=[‘2015-10-16’, ‘2015-10-17’], probe=’1’, datatype=’electron’) >>> tplot([‘mms1_epd_feeps_srvy_l2_electron_intensity_omni_spin’, ‘mms1_epd_feeps_srvy_l2_electron_intensity_omni’])

FEEPS Example

import pyspedas
from pytplot import tplot
pyspedas.mms.feeps(trange=['2015-10-16', '2015-10-17'])
tplot('mms1_epd_feeps_srvy_l2_electron_intensity_omni_spin')

Energetic Ion Spectrometer (EIS)

pyspedas.mms.eis(*args, **kwargs)

Load data from the MMS Energetic Ion Spectrometer (EIS)

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’, ‘2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
data_rate (str or list of str) – instrument data rates for EIS include [‘brst’, ‘srvy’]. Default: ‘srvy’
level (str) – indicates level of data processing. Default: ‘l2’
datatype (str or list of str) – Valid datatypes for EIS are: [‘extof’, ‘phxtof’, and ‘electronenergy’] Default: ‘extof’
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: ‘True’
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: ‘False’
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: None (all variables are loaded)
varnames (list of str) – List of variable names to load. If list is empty or not specified, all data variables are loaded. Default: []
suffix (str) – The tplot variable names will be given this suffix. Default: None
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval Default: False
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf (bool) – If True, download the data from the SPDF instead of the SDC Default: False

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> eis_vars = pyspedas.mms.mms_load_eis(trange=[‘2015-10-16’, ‘2015-10-17’], probe=’1’, datatype=[‘phxtof’, ‘extof’]) >>> # plot the non-spin averaged flux >>> tplot([‘mms1_epd_eis_srvy_l2_extof_proton_flux_omni’, ‘mms1_epd_eis_srvy_l2_phxtof_proton_flux_omni’]) >>> # plot the spin averaged flux >>> tplot([‘mms1_epd_eis_srvy_l2_extof_proton_flux_omni_spin’, ‘mms1_epd_eis_srvy_l2_phxtof_proton_flux_omni_spin’])

EIS Example

import pyspedas
from pytplot import tplot
pyspedas.mms.eis(trange=['2015-10-16', '2015-10-17'])
tplot(['mms1_epd_eis_srvy_l2_extof_proton_flux_omni', 'mms1_epd_eis_srvy_l2_extof_proton_flux_omni_spin'])

Active Spacecraft Potential Control (ASPOC)

pyspedas.mms.aspoc(*args, **kwargs)

Load data from the MMS Active Spacecraft Potential Control (ASPOC)

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’, ‘2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: 1
data_rate (str or list of str) – instrument data rates for ASPOC include ‘srvy’, ‘sitl’. Default: ‘srvy’.
level (str) – indicates level of data processing. Default: ‘l2’
datatype (str or list of str) – Valid datatypes for ASPOC are: [‘asp1’, ‘asp2’, ‘aspoc’] Default: ‘aspoc’
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: False
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: False
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: None (all variables are loaded in)
varnames (list of str) – List of variable names to load. If list is empty or unspecified, all data variables are loaded. Default: empty list (all data variables are loaded)
suffix (str) – The tplot variable names will be given this suffix. Default: None
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval Default: False
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf (bool) – If True, download the data from the SPDF instead of the SDC Default: False

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> asp_data = pyspedas.mms.mms_load_aspoc(trange=[‘2015-10-16’, ‘2015-10-17’], probe=’1’) >>> tplot(‘mms1_aspoc_ionc_l2’)

ASPOC Example

import pyspedas
from pytplot import tplot
pyspedas.mms.aspoc(trange=['2015-10-16', '2015-10-17'])
tplot(['mms1_aspoc_ionc_l2', 'mms1_asp1_ionc_l2', 'mms1_asp2_ionc_l2'])

Fast Plasma Investigation (FPI)

pyspedas.mms.fpi(*args, **kwargs)

Load data from the MMS Fast Plasma Investigation (FPI)

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’, ‘2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
data_rate (str or list of str) – instrument data rates for FPI include ‘brst’, ‘fast’. Default: ‘fast’
level (str) – indicates level of data processing. Valid options: ‘l2’, ‘ql’ Default: ‘l2’
datatype (str or list of str) –

Valid datatypes for FPI are:
‘des-moms’, ‘dis-moms’, ‘des-dist’, ‘dis-dist’, ‘des’, ‘dis’ Defaults: [‘des-moms’, ‘dis-moms’, ‘des-dist’ , ‘dis-dist’] (for level != ‘ql’ or unspecified) [‘des’, ‘dis’] (for level == ‘ql’)
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: False
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: False
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: None (All variables are loaded)
varnames (list of str) – List of variable names to load. If list is empty or not specified, all data variables are loaded Default: [] (all variables are loaded)
suffix (str) – The tplot variable names will be given this suffix. Default: None
center_measurement (bool) – If True, the CDF epoch variables are time-shifted to the middle of the accumulation interval by their DELTA_PLUS_VAR and DELTA_MINUS_VAR variable attributes Default: False
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval Default: False
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf (bool) – If True, download the data from the SPDF instead of the SDC Default: False

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> fpi_vars = pyspedas.mms.mms_load_fpi(trange=[‘2015-10-16’, ‘2015-10-17’], datatype=’dis-moms’) >>> tplot([‘mms1_dis_bulkv_gse_fast’, ‘mms1_dis_numberdensity_fast’])

FPI Example

import pyspedas
from pytplot import tplot
pyspedas.mms.fpi(trange=['2015-10-16', '2015-10-17'], datatype='des-moms')
tplot(['mms1_des_energyspectr_omni_fast', 'mms1_des_bulkv_gse_fast', 'mms1_des_numberdensity_fast'])

Hot Plasma Composition Analyzer (HPCA)

pyspedas.mms.hpca(*args, **kwargs)

Load data from the MMS Hot Plasma Composition Analyzer (HPCA)

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’, ‘2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
data_rate (str or list of str) – instrument data rates for HPCA include ‘brst’, ‘srvy’. Default: ‘srvy’
level (str) – indicates level of data processing Default: ‘l2’
datatype (str or list of str) – Valid datatypes for HPCA are ‘moments’ and ‘ion’ Default: ‘moments’
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: True
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: None (all variables are loaded)
varnames (list of str) – List of variable names to load. If list is empty or not specified, all data variables are loaded) Default: [] (all variables are loaded)
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: False
suffix (str) – The tplot variable names will be given this suffix. Default: None
center_measurement (bool) – If True, the CDF epoch variables are time-shifted to the middle of the accumulation interval by their DELTA_PLUS_VAR and DELTA_MINUS_VAR variable attributes Default: False
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval Default: False
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf (bool) – If True, download the data from the SPDF instead of the SDC Default: False

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> mom_vars = pyspedas.mms.mms_load_hpca(trange=[‘2015-10-16’, ‘2015-10-17’], datatype=’moments’) >>> tplot([‘mms1_hpca_hplus_number_density’, ‘mms1_hpca_hplus_ion_bulk_velocity’]) >>> # load the ion data (support data, fluxes, phase space densities, all ion data samples are n x m arrays >>> ion_vars = pyspedas.mms.mms_load_hpca(trange=[‘2016-10-16’, ‘2016-10-17’], datatype=’ion’)

HPCA Example

import pyspedas
from pytplot import tplot
pyspedas.mms.hpca(trange=['2015-10-16', '2015-10-17'], datatype='moments')
tplot(['mms1_hpca_hplus_number_density', 'mms1_hpca_hplus_ion_bulk_velocity', 'mms1_hpca_hplus_scalar_temperature'])

Magnetic Ephemeris Coordinates (MEC)

pyspedas.mms.mec(*args, **kwargs)

Load the attitude/ephemeris data from the MMS MEC (Mission Ephemeris and Coordinates) files

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’, ‘2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
data_rate (str or list of str) – instrument data rates for MEC include [‘brst’, ‘srvy’]. Default: ‘srvy’
level (str) – indicates level of data processing. Default: ‘l2’
datatype (str or list of str) – Valid datatypes for MEC are: [‘ephts04d’, ‘epht89q’, ‘epht89d’] Default: ‘epht89q’
get_support_data (bool) – Data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: False
time_clip (bool) – Data will be clipped to the exact trange specified by the trange keyword. Default: False
varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: None (all variables are loaded)
varnames (list of str) – List of variable names to load. If list is empyt or not specified, all data variables are loaded) Default: [] (all variables are loaded)
suffix (str) – The tplot variable names will be given this suffix. Default: None
notplot (bool) – If True, then data are returned in a hash table instead of being stored in tplot variables (useful for debugging, and access to multidimensional data products) Default: False
available (bool) – If True, simply return the available data files (without downloading) for the requested parameters Default: False
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
cdf_version (str) – Specify a specific CDF version # to load (e.g., cdf_version=’4.3.0’) Default: None
min_version (str) – Specify a minimum CDF version # to load Default: None
latest_version (bool) – Only grab the latest CDF version in the requested time interval Default: False
major_version (bool) – Only open the latest major CDF version (e.g., X in vX.Y.Z) in the requested time interval Default: False
always_prompt (bool) – Set this keyword to always prompt for the user’s username and password; useful if you accidentally save an incorrect password, or if your SDC password has changed Default: False
spdf (bool) – If True, download the data from the SPDF instead of the SDC Default: False

Notes

The default datatype was changed to ‘epht89q’ on 15Nov2021. There are sometimes issues with creating the Tsyganenko 04 data products, which leads to the ‘epht04d’ files not being available. The ‘epht89d’ files contain the same ephemeris data - the only difference are the data products that rely on the field model.

Return type:: List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> mec_data = pyspedas.mms.mms_load_mec(trange=[‘2015-10-16’, ‘2015-10-17’], probe=’1’) >>> tplot([‘mms1_mec_r_gsm’, ‘mms1_mec_v_gsm’])

MEC Example

import pyspedas
from pytplot import tplot
pyspedas.mms.mec(trange=['2015-10-16', '2015-10-17'])
tplot(['mms1_mec_r_gsm', 'mms1_mec_v_gsm'])

pyspedas.mms.state(*args, **kwargs)

This function loads the state (ephemeris and attitude) data from the ASCII files into tplot variables

Parameters:

trange (list of str) – time range of interest [start time, end time] 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’] Default: [‘2015-10-16’, ‘2015-10-17’]
probe (str or list of str) – list of probes, valid values for MMS probes are [‘1’,’2’,’3’,’4’]. Default: ‘1’
level (str) – indicates level of data (options: ‘def’ (definitive), ‘pred’ (predicted) Default: ‘def’
datatypes (str or list of str) – Datatypes for state data to be loaded (options: ‘pos’, ‘vel’, ‘spinras’, ‘spindec’) Default: [‘pos’, ‘vel’]
suffix (str) – The tplot variable names will be given this suffix. Default: None
no_update (bool) – Set this flag to preserve the original data. if not set and newer data is found the existing data will be overwritten Default: False
pred_or_def (bool) – Load definitive or predicted (if definitive isn’t available); defaults to True Default: True

Return type:

List of tplot variables created.

Example: >>> import pyspedas >>> from pytplot import tplot >>> pos_data = pyspedas.mms.mms_load_state(trange=[‘2015-10-16’, ‘2015-10-17’], probe=’1’, datatypes=’pos’, level=’def’) >>> tplot(‘mms1_defeph_pos’)

State Example

import pyspedas
from pytplot import tplot
pyspedas.mms.state(trange=['2020-12-16', '2020-12-17'])
tplot(['mms1_defeph_pos', 'mms1_defeph_vel'])