from .load import load
from pytplot import options
from pyspedas.utilities.datasets import find_datasets
[docs]
def mgf(trange=['2018-11-5', '2018-11-6'],
datatype='k0',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the MGF 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']
datatype: str
Data type; 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.
varnames: list of str
List of variable names to load (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
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='mgf', trange=trange, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update)
[docs]
def efd(trange=['2018-11-5', '2018-11-6'],
datatype='k0',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the EFD 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']
datatype: str
Data type; 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.
varnames: list of str
List of variable names to load (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
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='efd', trange=trange, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update)
[docs]
def lep(trange=['2018-11-5', '2018-11-6'],
datatype='k0',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the LEP 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']
datatype: str
Data type; 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.
varnames: list of str
List of variable names to load (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
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='lep', trange=trange, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update)
[docs]
def cpi(trange=['2018-11-5', '2018-11-6'],
datatype='k0',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the CPI 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']
datatype: str
Data type; 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.
varnames: list of str
List of variable names to load (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
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='cpi', trange=trange, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update)
[docs]
def epic(trange=['2018-11-5', '2018-11-6'],
datatype='k0',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the EPIC 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']
datatype: str
Data type; 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.
varnames: list of str
List of variable names to load (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
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.
"""
tvars = load(instrument='epi', trange=trange, datatype=datatype, 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:
return tvars
if 'IDiffI_I'+suffix in tvars:
options('IDiffI_I'+suffix, 'spec', True)
options('IDiffI_I'+suffix, 'ylog', True)
options('IDiffI_I'+suffix, 'zlog', True)
return tvars
[docs]
def pwi(trange=['2018-11-5', '2018-11-6'],
datatype='k0',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the PWI 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']
datatype: str
Data type; 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.
varnames: list of str
List of variable names to load (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
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='pwi', trange=trange, datatype=datatype, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, downloadonly=downloadonly, notplot=notplot, time_clip=time_clip, no_update=no_update)
def datasets(instrument=None, label=True):
return find_datasets(mission='Geotail', instrument=instrument, label=label)