Two Wide-Angle Imaging Neutral-Atom Spectrometers (TWINS) Mission

The routines in this module can be used to load data from the Two Wide-Angle Imaging Neutral-Atom Spectrometers (TWINS) Mission mission.

Energetic Neutral Atom (ENA) imager

pyspedas.twins.imager(trange=['2018-11-5', '2018-11-6'], probe='1', datatype='', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads TWINS imager 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: ‘’ Default: ‘’

  • suffix (str) – The tplot variable names will be given this suffix. Default: ‘’

  • get_support_data (bool) – If True, data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: False

  • varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: ‘’ (all variables loaded)

  • varnames (list of str) – List of variable names to load Default: [] (all variables will be loaded)

  • downloadonly (bool) – Set this flag to download the CDF files, but not load them into tplot variables Default: False

  • notplot (bool) – Return the data in hash tables instead of creating tplot variables Default: False

  • no_update (bool) – If set, only load data from your local cache Default: False

  • time_clip (bool) – Time clip the variables to exactly the range specified in the trange keyword Default: False

Returns:

List of tplot variables created.

Return type:

list of str

Examples

>>> import pyspedas
>>> from pytplot import tplot
>>> img_vars = pyspedas.twins.imager(trange=['2018-11-5', '2018-11-6'])
>>> tplot('smooth_image_val')

Lyman-alpha Detector (LAD)

pyspedas.twins.lad(trange=['2018-11-5', '2018-11-6'], probe='1', datatype='', 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 LAD 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’] Default: [‘2018-11-5’, ‘2018-11-6’]

  • datatype (str) – Data type; Valid options: ‘’ Default: ‘’

  • suffix (str) – The tplot variable names will be given this suffix. Default: ‘’

  • get_support_data (bool) – If True, data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: False

  • varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: ‘’ (all variables loaded)

  • varnames (list of str) – List of variable names to load Default: [] (all variables loaded)

  • downloadonly (bool) – Set this flag to download the CDF files, but not load them into tplot variables Default: False

  • notplot (bool) – Return the data in hash tables instead of creating tplot variables Default: False

  • no_update (bool) – If set, only load data from your local cache Default: False

  • time_clip (bool) – Time clip the variables to exactly the range specified in the trange keyword Default: False

Returns:

List of tplot variables created.

Return type:

list of str

Examples

>>> import pyspedas
>>> from pytplot import tplot
>>> lad_vars = pyspedas.twins.lad(trange=['2018-11-5/6:00', '2018-11-5/6:20'], time_clip=True)
>>> tplot(['lad1_data', 'lad2_data'])

Example

import pyspedas
from pytplot import tplot
lad_vars = pyspedas.twins.lad(trange=['2018-11-5/6:00', '2018-11-5/6:20'], time_clip=True)
tplot(['lad1_data', 'lad2_data'])
_images/twins_lad.png

Ephemeris

pyspedas.twins.ephemeris(trange=['2018-11-5', '2018-11-6'], probe='1', datatype='or', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)[source]

This function loads TWINS ephemeris 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’] Default: [‘2018-11-5’, ‘2018-11-6’]

  • probe (str or list of str) – Probe to load. Valid options: ‘1’, ‘2’ Default: ‘1’

  • datatype (str) – Data type; Valid options: Default: ‘or’

  • suffix (str) – The tplot variable names will be given this suffix. Default: ‘’

  • get_support_data (bool) – If True, data with an attribute “VAR_TYPE” with a value of “support_data” will be loaded into tplot. Default: False

  • varformat (str) – The file variable formats to load into tplot. Wildcard character “*” is accepted. Default: ‘’ (all variables will be loaded)

  • varnames (list of str) – List of variable names to load Default: [] (all variables will be loaded)

  • downloadonly (bool) – Set this flag to download the CDF files, but not load them into tplot variables Default: False

  • notplot (bool) – Return the data in hash tables instead of creating tplot variables Default: False

  • no_update (bool) – If set, only load data from your local cache Default: False

  • time_clip (bool) – Time clip the variables to exactly the range specified in the trange keyword Default: False

Returns:

List of tplot variables created.

Return type:

list of str

Examples

>>> import pyspedas
>>> from pytplot import tplot
>>> # Note: variables have the same names for both probes, so only load one at a time
>>> ephem_vars = pyspedas.twins.ephemeris(probe=['1'],trange=['2008-04-01','2008-04-02'])
>>> tplot('FEQUATORIALGSM')

Example

import pyspedas
from pytplot import tplot
ephem_vars = pyspedas.twins.ephemeris(trange=['2018-11-5', '2018-11-6'])
tplot('FSCGSM')
_images/twins_ephemeris.png