from .load import load
from pyspedas.utilities.datasets import find_datasets
[docs]
def cindi(trange=['2013-11-5', '2013-11-6'],
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the Coupled Ion-Neutral Dynamics Investigation (CINDI)
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: ['2013-11-5', '2013-11-6']
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
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.
Example:
----------
>>> import pyspdedas
>>> from pytplot import tplot
>>> cindi_vars = pyspedas.cnofs.cindi(trange=['2013-11-5', '2013-11-6'])
>>> tplot(['ionVelocityX', 'ionVelocityY', 'ionVelocityZ'])
"""
return load(instrument='cindi', trange=trange, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update)
[docs]
def plp(trange=['2013-11-5', '2013-11-6'],
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the Planar Langmuir Probe (PLP)
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: ['2013-11-5', '2013-11-6']
suffix: str
The tplot variable names will be given this suffix.
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.
Default: False. 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.
Default: None. All variables are loaded in.
varnames: list of str
List of variable names to load.
Default: []. 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.
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.
Example:
----------
>>> import pyspdedas
>>> from pytplot import tplot
>>> plp_vars = pyspedas.cnofs.plp(trange=['2010-11-5', '2010-11-6'])
>>> tplot('Ni')
"""
return load(instrument='plp', trange=trange, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update)
[docs]
def vefi(trange=['2010-11-5', '2010-11-6'],
datatype='efield_1sec',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the Vector Electric Field Instrument (VEFI)
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: ['2010-11-5', '2010-11-6']
datatype: str
String specifying datatype (options: 'efield_1sec', 'bfield_1sec', 'ld_500msec')
Default: 'efield_1sec'
suffix: str
The tplot variable names will be given this suffix.
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.
Default: False. 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.
Default: None. All variables are loaded in.
varnames: list of str
List of variable names to load
Default: []. 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
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.
Example:
----------
>>> import pyspdedas
>>> from pytplot import tplot
>>> vefi_vars = pyspedas.cnofs.vefi(trange=['2013-11-5', '2013-11-6'])
>>> tplot(['E_meridional', 'E_zonal'])
"""
return load(instrument='vefi', datatype=datatype, trange=trange, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update)
def datasets(instrument=None, label=True):
return find_datasets(mission='CNOFS', instrument=instrument, label=label)