from .load import load
# This routine was originally in stereo/__init__.py, until being moved to its own file.
# Please refer to __init__.py if you need to see the revision history before it was moved.
[docs]
def swea(trange=['2013-1-5', '2013-1-6'],
probe='a',
datatype='spec',
level='l1',
suffix='',
prefix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the Solar Wind Electron Analyzer
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']
probe: str
Spacecraft probe ('a' for ahead, 'b' for behind)
Default: 'a'
datatype: str
Data type; Valid options: disb, dist, spec
Default: 'spec'
level: str
Default: 'l1'
suffix: str
The tplot variable names will be given this suffix.
Default: '', no suffix is added.
prefix: str
The tplot variable names will be given this prefix.
Default: '', no prefix 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 pyspedas
>>> from pyspedas import tplot
>>> swea_vars = pyspedas.projects.stereo.swea(trange=['2013-1-5', '2013-1-6'])
>>> tplot(sit_vars)
"""
return load(instrument='swea', trange=trange, probe=probe, datatype=datatype, suffix=suffix, prefix=prefix, level=level,
get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly,
notplot=notplot, time_clip=time_clip, no_update=no_update)