from .load import load
from pyspedas.utilities.datasets import find_datasets
from .load_csa import load_csa
from typing import List, Union, Optional
[docs]
def fgm(trange:List[str]=['2018-11-5', '2018-11-6'],
probe:Union[str,List[str]]='1',
datatype:str ='up',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster 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']
Default: ['2018-11-5', '2018-11-6']
probe: str or list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'up'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> fgm_vars = pyspedas.cluster.fgm(trange=['2018-11-5', '2018-11-6'],probe=['1','2'])
"""
return load(instrument='fgm', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def aspoc(trange:List[str]=['2003-11-5', '2003-11-6'],
probe:Union[str,List[str]]='1',
datatype:str='pp',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Active Spacecraft Potential Control experiment
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: ['2003-11-5', '2003-11-6']
probe: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'pp'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> aspoc_vars=pyspedas.cluster.aspoc(trange=['2003-11-05','2003-11-06'],probe=['1','2'])
>>> tplot(['I_ion__C1_PP_ASP','I_ion__C2_PP_ASP'])
"""
return load(instrument='aspoc', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def cis(trange:List[str]=['2018-11-5', '2018-11-6'],
probe:Union[str,List[str]]='1',
datatype:str='pp',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Ion Spectroscopy experiment
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: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'pp'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> cis_vars = pyspedas.cluster.cis(trange=['2003-11-01','2003-11-02'],probe=['1'])
>>> tplot(['N_p__C1_PP_CIS','N_O1__C1_PP_CIS','N_He1__C1_PP_CIS','N_He2__C1_PP_CIS','N_HIA__C1_PP_CIS'])
"""
return load(instrument='cis', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def dwp(trange:List[str]=['2018-11-5', '2018-11-6'],
probe:Union[str,List[str]]='1',
datatype:str='pp',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Digital Wave Processing 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']
probe: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'pp'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> dwp_vars = pyspedas.cluster.dwp(trange=['2003-11-01','2003-11-02'],probe=['1','2'])
>>> tplot(['Correl_freq__C1_PP_DWP','Correl_P__C1_PP_DWP'])
"""
return load(instrument='dwp', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def edi(trange:List[str]=['2018-11-5', '2018-11-6'],
probe:Union[str,List[str]]='1',
datatype:str='pp',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Electron Drift 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']
probe: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'pp'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> edi_vars = pyspedas.cluster.edi(trange=['2003-11-01','2003-11-02'],probe=['1','2'])
>>> tplot(['V_ed_xyz_gse__C1_PP_EDI','V_ed_xyz_gse__C1_PP_EDI'])
"""
return load(instrument='edi', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def efw(trange:List[str]=['2018-11-5', '2018-11-6'],
probe:Union[str,List[str]]='1',
datatype:str='pp',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Electric Field and Wave experiment
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: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'up'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> efw_vars = pyspedas.cluster.efw(trange=['2003-11-01','2003-11-02'],probe=['2'])
>>> tplot('E_pow_f1__C2_PP_EFW')
"""
return load(instrument='efw', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def peace(trange:List[str]=['2016-11-5', '2016-11-6'],
probe:Union[str,List[str]]='1',
datatype:str='pp',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Plasma Electron and Current Experiment
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: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'up'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> peace_vars = pyspedas.cluster.peace(trange=['2003-11-01','2003-11-02'],probe=['1','2'])
>>> tplot([ 'N_e_den__C1_PP_PEA', 'V_e_xyz_gse__C1_PP_PEA', 'N_e_den__C2_PP_PEA', 'V_e_xyz_gse__C2_PP_PEA'])
"""
return load(instrument='peace', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def rapid(trange:List[str]=['2016-11-5', '2016-11-6'],
probe:Union[str,List[str]]='1',
datatype:str='pp',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Research with Adaptive Particle Imaging Detectors
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: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'up'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> rapid_vars = pyspedas.cluster.rapid(trange=['2003-11-01','2003-11-02'],probe=['1','2'])
>>> tplot([ 'J_e_lo__C1_PP_RAP', 'J_e_hi__C1_PP_RAP', 'J_e_lo__C2_PP_RAP', 'J_e_hi__C2_PP_RAP'])
"""
return load(instrument='rapid', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def staff(trange:List[str]=['2012-11-5', '2012-11-6'],
probe:Union[str,List[str]]='1',
datatype:str='pp',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Spatio-Temporal Analysis of Field Fluctuation experiment
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: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'pp'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> staff_vars = pyspedas.cluster.staff(trange=['2003-11-01','2003-11-02'],probe=['1','2'])
>>> tplot(['B_par_f1__C1_PP_STA', 'B_perp_f1__C1_PP_STA', 'B_par_f1__C2_PP_STA', 'B_perp_f1__C2_PP_STA'])
"""
return load(instrument='staff', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def wbd(trange:List[str]=['2003-11-01/14:00:00','2003-11-01/14:05:00'],
probe:Union[str,List[str]]='1',
datatype:str='waveform',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Wide Band Data receiver
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: ['2003-11-01/14:00:00','2003-11-01/14:05:00']
probe: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'waveform'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> wbd_vars = pyspedas.cluster.wbd(trange=['2003-11-01/14:00:00','2003-11-01/14:05:00'],probe=['1'])
>>> # Note lack of probe IDs in the variables loaded -- only load one probe at a time
>>> tplot('WBD_Elec')
"""
return load(instrument='wbd', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
[docs]
def whi(trange:List[str]=['2012-11-5', '2012-11-6'],
probe:Union[str,List[str]]='1',
datatype:str='pp',
suffix:str='',
get_support_data:bool=False,
varformat:str=None,
varnames:List[str]=[],
downloadonly:bool=False,
notplot:bool=False,
no_update:bool=False,
time_clip:bool=False) -> List[str]:
"""
Load data from the Cluster Waves of High Frequency and Sounder for Probing of Density by Relaxation 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']
probe: list of str
List of probes to load. Valid options: '1','2','3','4'
Default: '1'
datatype: str
Data type; Valid options:
Default: 'pp'
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.
varformat: str
The file variable formats to load into tplot. Wildcard character
"*" is accepted. If empty or None, all variables will be loaded.
Default: None (all variables loaded)
varnames: list of str
List of CDF variable names to load (if empty or not specified,
all data variables are loaded)
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 str
List of tplot variables created.
Examples
--------
>>> import pyspedas
>>> from pytplot import tplot
>>> whi_vars = pyspedas.cluster.whi(trange=['2003-11-01','2003-11-02'],probe=['1','2'])
>>> tplot(['N_e_res__C1_PP_WHI','E_pow_f4__C1_PP_WHI','N_e_res__C2_PP_WHI','E_pow_f4__C2_PP_WHI'])
"""
return load(instrument='whi', trange=trange, probe=probe, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, no_update=no_update, time_clip=time_clip)
def datasets(instrument=None, label=True):
"""
Query SPDF for datasets available for a given Cluster instrument
Parameters
----------
instrument : str
Instrument to use in query. Valid options: 'ASP','CIS','DWP','EDI','EFW','FGM','PEA','RAP','STA','WBD','WHI'
Default: None
label: bool
If True, print both the dataset name and label; otherwise print only the dataset name.
Examples
--------
>>> import pyspedas
>>> pyspedas.cluster.datasets('FGM')
"""
return find_datasets(mission='Cluster', instrument=instrument, label=label)