Equator-S

The routines in this module can be used to load data from the Equator-S mission.

Fluxgate magnetometer (MAM)

pyspedas.equator_s.mam(trange=['1998-04-06', '1998-04-07'], datatype='pp', 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
mam_vars = pyspedas.equator_s.mam(trange=['1998-04-06', '1998-04-07'])
tplot('B_xyz_gse%eq_pp_mam')
_images/equator_s_mam.png

Electron beam sensing instrument (EDI)

pyspedas.equator_s.edi(trange=['1998-04-06', '1998-04-07'], datatype='pp', 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 beam sensing 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
edi_vars = pyspedas.equator_s.edi(trange=['1998-04-06', '1998-04-07'])
tplot('E_xyz_gse%eq_pp_edi')
_images/equator_s_edi.png

Solid state detector (EPI)

pyspedas.equator_s.epi(trange=['1998-04-06', '1998-04-07'], datatype='pp', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the Solid state detector

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
epi_vars = pyspedas.equator_s.epi(trange=['1998-04-06', '1998-04-30'])
tplot(['J_e_1%eq_pp_epi', 'J_e_2%eq_pp_epi', 'J_e_3%eq_pp_epi'])
_images/equator_s_epi.png

Time-of-fight spectrometer (ICI)

pyspedas.equator_s.ici(trange=['1998-04-06', '1998-04-07'], datatype='pp', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the Time-of-fight spectrometer

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
ici_vars = pyspedas.equator_s.ici(trange=['1998-04-06', '1998-04-07'])
tplot('V_p_xyz_gse%eq_pp_ici')
_images/equator_s_ici.png

Ion emitter (PCD)

pyspedas.equator_s.pcd(trange=['1998-04-06', '1998-04-07'], datatype='pp', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the Ion emitter

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
pcd_vars = pyspedas.equator_s.pcd(trange=['1998-04-06', '1998-04-07'])
tplot('I_ion%eq_pp_pcd')
_images/equator_s_pcd.png

Scintillating fiber detector (SFD)

pyspedas.equator_s.sfd(trange=['1998-01-26', '1998-01-27'], datatype='sp', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads data from the Scintillating fiber detector

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
sfd_vars = pyspedas.equator_s.sfd()
tplot('F_e>0.26%eq_sp_sfd')
_images/equator_s_sfd.png