import pyspedas
# from pyspedas.projects.rbsp import load, rbsp_load_rbspice_read, rbsp_rbspice_omni, rbsp_rbspice_spin_avg
from .load import load
from .rbspice_lib.rbsp_load_rbspice_read import rbsp_load_rbspice_read
from .rbspice_lib.rbsp_rbspice_omni import rbsp_rbspice_omni
from .rbspice_lib.rbsp_rbspice_spin_avg import rbsp_rbspice_spin_avg
[docs]
def rbspice(trange=['2018-11-5', '2018-11-6'],
probe='a',
datatype='TOFxEH',
level='l3',
prefix='',
suffix='',
force_download=False,
get_support_data=True,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the Radiation Belt Storm Probes Ion Composition Experiment (RBSPICE) instrument
Parameters
----------
trange : list of str, default=['2018-11-5', '2018-11-6']
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']
probe : str or list of str, default='a'
Spacecraft probe name: 'a' or 'b'
datatype: str, default='TOFxEH'
Data type; Valid options are specific to different data levels.
level : str, default='l3'
Data level. Valid options: 'l1', 'l2', 'l3'
prefix : str, optional
The tplot variable names will be given this prefix. By default, no prefix is added.
suffix: str, optional
The tplot variable names will be given this suffix. By default,
no suffix is added.
force_download : bool, default=False
Download file even if local version is more recent than server version.
get_support_data: bool, default=True
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, optional
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, default=False
Set this flag to download the CDF files, but not load them into
tplot variables
notplot: bool, default=False
Return the data in hash tables instead of creating tplot variables
no_update: bool, default=False
If set, only load data from your local cache
time_clip: bool, default=False
Time clip the variables to exactly the range specified in the trange keyword
Returns
-------
tvars : dict or list
List of created tplot variables or dict of data tables if notplot is True.
Examples
--------
>>> rbspice_vars = pyspedas.projects.rbsp.rbspice(trange=['2018-11-5', '2018-11-6'], datatype='TOFxEH', level='l3')
>>> tplot('rbspa_rbspice_l3_TOFxEH_proton_omni_spin')
# Calculate the pitch angle distributions
>>> from pyspedas.projects.rbsp.rbspice_lib.rbsp_rbspice_pad import rbsp_rbspice_pad
>>> rbsp_rbspice_pad(probe='a', datatype='TOFxEH', level='l3')
>>> tplot('rbspa_rbspice_l3_TOFxEH_proton_omni_0-1000keV_pad_spin')
"""
# Valid names
vprobe = ['a', 'b']
vlevels = ['l1', 'l2', 'l3', 'l4']
vdatatypesl1 = ['TOFxEH', 'TOFxEnonH', 'TOFxPHHHELT']
vdatatypesl2 = ['TOFxEH', 'TOFxEnonH', 'TOFxPHHHELT']
vdatatypesl3 = ['TOFxEH', 'TOFxEnonH', 'TOFxPHHHELT']
vdatatypesl3pap = [''] # L3PAP data is not yet supported
vdatatypesl4 = [''] # L4 data is not yet supported
vdatatypes = vdatatypesl1 + vdatatypesl2 + vdatatypesl3 + vdatatypesl3pap + vdatatypesl4
vdatatypes_lower = [vdatatype.lower() for vdatatype in vdatatypes]
tvars = load(instrument='rbspice', trange=trange, probe=probe, datatype=datatype, level=level, prefix=prefix, suffix=suffix, force_download=force_download, 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
if not isinstance(probe, list):
probe = [probe]
if datatype.lower() in vdatatypes_lower:
for prb in probe:
# Add energy channel energy values to primary data variable,
# create variables for individual telescopes, and set appropriate tplot options
rbsp_load_rbspice_read(level=level, probe=prb, datatype=datatype)
# Calculate omni-directional variable
omni_vars = rbsp_rbspice_omni(probe=prb, datatype=datatype, level=level)
if omni_vars:
tvars.extend(omni_vars)
# Calculate spin-averaged variable
sp_avg_vars = rbsp_rbspice_spin_avg(probe=prb, datatype=datatype, level=level)
if sp_avg_vars:
tvars.extend(sp_avg_vars)
return tvars