Deep Space Climate Observatory (DSCOVR)

The routines in this module can be used to load data from the Deep Space Climate Observatory (DSCOVR) mission.

Magnetometer (MAG)

pyspedas.dscovr.mag(trange=['2018-10-16', '2018-10-17'], datatype='h0', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads DSCOVR Fluxgate Magnetometer 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:

    ‘h0’: 1-sec Definitive Data (default)

  • 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.dscovr.mag(trange=['2018-11-5', '2018-11-6'])
tplot('dsc_h0_mag_B1GSE')
_images/dscovr_mag.png

Faraday cup (FC)

pyspedas.dscovr.fc(trange=['2018-10-16', '2018-10-17'], datatype='h1', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads DSCOVR Faraday Cup 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:

    ‘h1’: 1-minute Isotropic Maxwellian parameters for solar wind protons (default)

  • 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
fc_vars = pyspedas.dscovr.fc(trange=['2018-11-5', '2018-11-6'])
tplot(['dsc_h1_fc_V_GSE', 'dsc_h1_fc_THERMAL_SPD', 'dsc_h1_fc_Np', 'dsc_h1_fc_THERMAL_TEMP'])
_images/dscovr_fc.png

Orbit data

pyspedas.dscovr.orb(trange=['2018-10-16', '2018-10-17'], datatype='orbit', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads DSCOVR 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’]

  • 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
orb_vars = pyspedas.dscovr.orb(trange=['2018-11-5', '2018-11-6'])
tplot(['dsc_orbit_SUN_R', 'dsc_orbit_GCI_POS', 'dsc_orbit_GCI_VEL', 'dsc_orbit_GSE_POS', 'dsc_orbit_MOON_GSE_POS'])
_images/dscovr_orb.png

Attitude data

pyspedas.dscovr.att(trange=['2018-10-16', '2018-10-17'], datatype='orbit', suffix='', get_support_data=False, varformat=None, varnames=[], downloadonly=False, notplot=False, no_update=False, time_clip=False)

This function loads DSCOVR Attitude 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’]

  • 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
att_vars = pyspedas.dscovr.att(trange=['2018-11-5', '2018-11-6'])
tplot(['dsc_att_GSE_Yaw', 'dsc_att_GSE_Pitch', 'dsc_att_GSE_Roll'])
_images/dscovr_att.png

Load all data at once

pyspedas.dscovr.all(trange=['2018-10-16', '2018-10-17'], downloadonly=False, suffix='', no_update=False, time_clip=False)

This function loads all DSCOVR 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’]

  • downloadonly (bool) – Set this flag to download the CDF files, but not load them into 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
all_vars = pyspedas.dscovr.all(trange=['2018-11-5', '2018-11-6'])
tplot(['dsc_h0_mag_B1GSE', 'dsc_h1_fc_V_GSE', 'dsc_h1_fc_THERMAL_SPD', 'dsc_h1_fc_Np', 'dsc_orbit_GSE_POS'])
_images/dscovr_all.png