from .load import load
from pyspedas.utilities.datasets import find_datasets
[docs]
def mag(trange=['2006-06-01', '2006-06-02'],
probe='094',
datatype='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 Magnetometer (MAG)
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: ['2006-06-01', '2006-06-02']
probe: str
Probe #; Valid options: '094', '224', '155'
Default: '094'
datatype: str
Data type; options: '1sec'
Default: '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
>>> mag_vars = pyspedas.st5.mag(trange=['2006-06-01', '2006-06-02'])
>>> tplot(['B_SM', 'SC_POS_SM'])
"""
tvars = load(instrument='mag', trange=trange, datatype=datatype, probe=probe, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update)
if tvars is None or notplot or downloadonly:
return tvars
return mag_postprocessing(tvars)
def mag_postprocessing(variables):
"""
Placeholder for MAG post-processing
"""
return variables
def datasets(instrument=None, label=True):
return find_datasets(mission='ST5', instrument=instrument, label=label)