def mepi(trange=['2017-03-27', '2017-03-28'],
datatype='omniflux',
level='l2',
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
uname=None,
passwd=None,
time_clip=False):
"""
This function loads data from the MEP-i experiment from the Arase mission
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']
datatype: str
Data type; Valid options:
level: str
Data level; Valid options:
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.
downloadonly: bool
Set this flag to download the CDF files, but not load them into
tplot variables
notplot: bool
Return the data in hash tables instead of creating tplot variables
no_update: bool
If set, only load data from your local cache
time_clip: bool
Time clip the variables to exactly the range specified in the trange keyword
Returns:
List of tplot variables created.
"""
return load(instrument='mepi', trange=trange, level=level, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update, uname=uname, passwd=passwd)
def mgf(trange=['2017-03-27', '2017-03-28'],
datatype='8sec',
level='l2',
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
uname=None,
passwd=None,
time_clip=False):
"""
This function loads data from the MGF experiment from the Arase mission
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']
datatype: str
Data type; Valid options:
level: str
Data level; Valid options:
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.
downloadonly: bool
Set this flag to download the CDF files, but not load them into
tplot variables
notplot: bool
Return the data in hash tables instead of creating tplot variables
no_update: bool
If set, only load data from your local cache
time_clip: bool
Time clip the variables to exactly the range specified in the trange keyword
Returns:
List of tplot variables created.
"""
if datatype == '8s' or datatype == '8':
datatype = '8sec'
elif datatype == '64':
datatype = '64hz'
elif datatype == '128':
datatype = '128hz'
elif datatype == '256':
datatype = '256hz'
loaded_data = load(instrument='mgf',
trange=trange,
level=level,
datatype=datatype,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
downloadonly=downloadonly,
notplot=notplot,
time_clip=time_clip,
no_update=no_update,
uname=uname,
passwd=passwd)
if loaded_data == None or loaded_data == [] or notplot or downloadonly:
return loaded_data
clip('erg_mgf_' + level + '_mag_' + datatype + '_dsi' + suffix, -1e+6, 1e6)
clip('erg_mgf_' + level + '_mag_' + datatype + '_gse' + suffix, -1e+6, 1e6)
clip('erg_mgf_' + level + '_mag_' + datatype + '_gsm' + suffix, -1e+6, 1e6)
clip('erg_mgf_' + level + '_mag_' + datatype + '_sm' + suffix, -1e+6, 1e6)
# set yrange
times, bdata = get_data('erg_mgf_' + level + '_mag_' + datatype + '_dsi' +
suffix)
ylim('erg_mgf_' + level + '_mag_' + datatype + '_dsi' + suffix,
np.nanmin(bdata), np.nanmax(bdata))
times, bdata = get_data('erg_mgf_' + level + '_mag_' + datatype + '_gse' +
suffix)
ylim('erg_mgf_' + level + '_mag_' + datatype + '_gse' + suffix,
np.nanmin(bdata), np.nanmax(bdata))
times, bdata = get_data('erg_mgf_' + level + '_mag_' + datatype + '_gsm' +
suffix)
ylim('erg_mgf_' + level + '_mag_' + datatype + '_gsm' + suffix,
np.nanmin(bdata), np.nanmax(bdata))
times, bdata = get_data('erg_mgf_' + level + '_mag_' + datatype + '_sm' +
suffix)
ylim('erg_mgf_' + level + '_mag_' + datatype + '_sm' + suffix,
np.nanmin(bdata), np.nanmax(bdata))
# set labels
options('erg_mgf_' + level + '_mag_' + datatype + '_dsi' + suffix,
'legend_names', ['Bx', 'By', 'Bz'])
options('erg_mgf_' + level + '_mag_' + datatype + '_gse' + suffix,
'legend_names', ['Bx', 'By', 'Bz'])
options('erg_mgf_' + level + '_mag_' + datatype + '_gsm' + suffix,
'legend_names', ['Bx', 'By', 'Bz'])
options('erg_mgf_' + level + '_mag_' + datatype + '_sm' + suffix,
'legend_names', ['Bx', 'By', 'Bz'])
# set color of the labels
options('erg_mgf_' + level + '_mag_' + datatype + '_dsi' + suffix, 'Color',
['b', 'g', 'r'])
options('erg_mgf_' + level + '_mag_' + datatype + '_gse' + suffix, 'Color',
['b', 'g', 'r'])
options('erg_mgf_' + level + '_mag_' + datatype + '_gsm' + suffix, 'Color',
['b', 'g', 'r'])
options('erg_mgf_' + level + '_mag_' + datatype + '_sm' + suffix, 'Color',
['b', 'g', 'r'])
return loaded_data
