def test_dailynames(self):
"""Test dailynames function."""
self.assertTrue(dailynames(trange=['2015-12-1', '2015-12-1/2:00'],
hour_res=True) == ['2015120100',
'2015120101'])
self.assertTrue(dailynames(trange=['2015-12-1', '2015-12-3'])
== ['20151201', '20151202'])
self.assertTrue(dailynames(trange=['2015-12-3', '2015-12-2'])
== ['20151203'])
self.assertTrue(dailynames() is None)
self.assertTrue(dailynames(trange=['2015-12-3', '2019-12-2'],
file_format='%Y') ==
['2015', '2016', '2017', '2018', '2019'])
self.assertTrue(dailynames(trange=['2015-1-1', '2015-3-2'],
file_format='%Y%m') == ['201501', '201502',
'201503'])
self.assertTrue(dailynames(trange=['2015-1-1', '2015-3-2'],
file_format='/%Y/%m/') ==
['/2015/01/', '/2015/02/', '/2015/03/'])
self.assertTrue(dailynames(trange=['2015-1-1', '2015-1-1/3:00'],
file_format='%H', res=60.0) ==
['00', '01', '02'])
self.assertTrue(dailynames(trange=['2015-1-1/2:00', '2015-1-1/3:00'],
file_format='%M', res=600.) ==
['00', '10', '20', '30', '40', '50'])
def load(trange=['2019-02-01', '2019-02-02'],
site=None,
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads Magnetic Induction Coil Array (MICA) data; this function is not meant
to be called directly; instead, see the wrapper:
pyspedas.mica.induction
"""
if site == None:
print('A valid MICA site code name must be entered.')
print('Current site codes include: ')
print(
'NAL, LYR, LOR, ISR, SDY, IQA, SNK, MCM, SPA, JBS, NEV, HAL, PG2[3,4,5]'
)
return
pathformat = site.upper() + '/%Y/%m/mica_ulf_' + site.lower(
) + '_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix='_' + site.upper() + suffix,
merge=True,
get_support_data=get_support_data,
varformat=varformat,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2013-11-5', '2013-11-6'],
datatype='1min',
level='hro2',
suffix='',
get_support_data=False,
get_ignore_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=True):
"""
This function loads OMNI (Combined 1AU IP Data; Magnetic and Solar Indices) data; this function is not meant
to be called directly; instead, see the wrapper:
pyspedas.omni.data
"""
if 'min' in datatype:
pathformat = level + '_' + datatype + '/%Y/omni_' + level + '_' + datatype + '_%Y%m01_v??.cdf'
elif 'hour' in datatype:
pathformat = 'hourly/%Y/omni2_h0_mrg1hr_%Y%m01_v??.cdf'
else:
raise TypeError("%r are invalid keyword arguments" % datatype)
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
get_ignore_data=get_ignore_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2018-11-5', '2018-11-6'],
probe=['noaa19'],
instrument='sem',
datatype='*',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads POES Space Environment Monitor data. This function is
not meant to be called directly; instead, see the wrapper:
pyspedas.poes.sem
"""
if not isinstance(probe, list):
probe = [probe]
out_files = []
for prb in probe:
if instrument == 'sem':
pathformat = prb + '/sem2_fluxes-2sec/%Y/' + prb + '_poes-sem2_fluxes-2sec_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2020-06-01', '2020-06-02'],
instrument='mag',
datatype='rtn-normal',
mode=None,
level='l2',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the Solar Orbiter mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.solo.mag
pyspedas.solo.epd
pyspedas.solo.rpw
pyspedas.solo.swa
"""
if instrument == 'mag':
pathformat = instrument+'/science/'+level+'/'+datatype+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'_%Y%m%d_v??.cdf'
elif instrument == 'epd':
pathformat = instrument+'/science/'+level+'/'+datatype+'/'+mode+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'-'+mode+'_%Y%m%d_v??.cdf'
elif instrument == 'rpw':
pathformat = instrument+'/science/'+level+'/'+datatype+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'_%Y%m%d_v??.cdf'
elif instrument == 'swa':
if datatype == 'pas-eflux':
pathformat = instrument+'/science/'+level+'/'+datatype+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names, remote_path=CONFIG['remote_data_dir'], local_path=CONFIG['local_data_dir'], no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2013-11-5', '2013-11-6'],
instrument='dcb',
datatype='',
level='l2',
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the FAST mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.fast.dcb
pyspedas.fast.acb
pyspedas.fast.esa
pyspedas.fast.teams
"""
file_resolution = 24*3600.
if instrument == 'dcb':
pathformat = 'dcf/'+level+'/'+instrument+'/%Y/%m/fast_hr_'+instrument+'_%Y%m%d%H????_v??.cdf'
file_resolution = 3600.
if instrument == 'acb':
pathformat = 'acf/'+level+'/%Y/fa_'+level+'_acf_%Y%m%d_v??.cdf'
elif instrument == 'esa':
pathformat = instrument+'/'+level+'/'+datatype+'/%Y/%m/fa_'+instrument+'_'+level+'_'+datatype+'_%Y%m%d??????_*_v??.cdf'
if instrument == 'teams':
pathformat = 'teams/'+level+'/%Y/fa_'+level+'_tms_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange, res=file_resolution)
out_files = []
for remote_file in remote_names:
files = download(remote_file=remote_file, remote_path=CONFIG['remote_data_dir'], local_path=CONFIG['local_data_dir'], no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files, suffix=suffix, merge=True, get_support_data=get_support_data, varformat=varformat, notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2013-11-5', '2013-11-6'],
instrument='reptile',
datatype='flux',
level='l2',
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the CSSWE mission; this function is not meant
to be called directly; instead, see the wrapper:
pyspedas.csswe.reptile
"""
if instrument == 'reptile':
pathformat = level + '/' + instrument + '/' + datatype + '/%Y/csswe_' + instrument + '_6sec-' + datatype + '-' + level + '_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
for remote_file in remote_names:
files = download(remote_file=remote_file,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
merge=True,
get_support_data=get_support_data,
varformat=varformat,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=None,
resolution=10,
dtype=None,
no_download=False,
downloadonly=False,
out_type='np',
save_pickle=False):
"""
This function loads SECS/EICS data; this function is not meant
to be called directly; instead, see the wrapper:
pyspedas.secs.data
"""
if dtype == 'EICS' or dtype == 'SECS':
pathformat_prefix = dtype + '/%Y/%m/'
pathformat_zip = pathformat_prefix + dtype + '%Y%m%d.zip'
pathformat_gz = pathformat_prefix + dtype + '%Y%m%d.zip.gz' # only 2007!
pathformat_unzipped = pathformat_prefix + '%d/' + dtype + '%Y%m%d_%H%M%S.dat'
else:
raise TypeError("%r are invalid keyword arguments" % dtype)
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat_zip, trange=trange)
remote_names_gz = dailynames(file_format=pathformat_gz, trange=trange)
remote_names_gz = [s for s in remote_names_gz if s[-15:-11] == '2007']
out_files = []
out_files_zip = []
files_zip = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_download)
files_gz = download(remote_file=remote_names_gz,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_download)
files_zip = files_zip + files_gz
if files_zip is not None:
for rf_zip_zero in files_zip:
if rf_zip_zero.endswith('.gz'):
rf_zip = rf_zip_zero[0:-3]
# unzip .gz file to .zip file
with gzip.open(rf_zip_zero, 'rb') as f_in:
with open(rf_zip, 'wb') as f_out:
shutil.copyfileobj(f_in, f_out)
elif rf_zip_zero.endswith('.zip'):
rf_zip = rf_zip_zero
else:
rf_zip = rf_zip_zero
out_files_zip.append(rf_zip)
#print('Start for unzipping process ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~')
foldername_unzipped = rf_zip[0:-19] + rf_zip[-8:-6] + '/' + rf_zip[
-6:-4]
#print('foldername_unzipped-------: ', foldername_unzipped)
### add??????
if not os.path.isdir(foldername_unzipped):
logging.info('Start unzipping: ' + rf_zip + ' ------')
with zipfile.ZipFile(rf_zip, 'r') as zip_ref:
zip_ref.extractall(rf_zip[0:-16])
if not os.path.isdir(foldername_unzipped):
# for the case of unzipping directly without the %d folder made.
# make %d folder
os.makedirs(foldername_unzipped)
# move .dat files
sourcepath = rf_zip[0:-16]
sourcefiles = os.listdir(sourcepath)
destinationpath = foldername_unzipped
logging.info('start to move files: --------------')
for file in sourcefiles:
if rf_zip[-16:-4] in file and file.endswith('.dat'):
shutil.move(os.path.join(sourcepath, file),
os.path.join(destinationpath, file))
else:
logging.info('Unzipped folder: ' + foldername_unzipped +
' existed, skip unzipping ------')
if files_zip is not None:
for file in files_zip:
out_files.append(file)
out_files = sorted(out_files)
if out_files_zip is not None:
out_files_zip = list(set(out_files_zip))
out_files_zip = sorted(out_files_zip)
if downloadonly:
return out_files_zip #out_files
remote_names_unzipped = dailynames(file_format=pathformat_unzipped,
trange=trange,
res=resolution)
"""
files_unzipped = download(remote_file=remote_names_unzipped, remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'], no_download=True)
"""
remote_names_unzipped_existed = [
rnud for rnud in remote_names_unzipped for ofz in out_files_zip
if ofz[-16:-4] in rnud
]
remote_names_unzipped = remote_names_unzipped_existed
out_files_unzipped = [
CONFIG['local_data_dir'] + rf_res for rf_res in remote_names_unzipped
]
out_files_unzipped = sorted(out_files_unzipped)
if out_files_unzipped == []:
data_vars = []
else:
data_vars = pyspedas.secs.read_data_files(out_files=out_files_unzipped,
dtype=dtype,
out_type=out_type,
save_pickle=save_pickle)
#print('data_vars: ', data_vars, np.shape(data_vars))
return data_vars #tvars
def load(trange=['2018-11-5', '2018-11-6'],
probe='1',
instrument='lad',
datatype='',
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads TWINS data; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.twins.lad
pyspedas.twins.ephemeris
pyspedas.twins.imager
"""
if not isinstance(probe, list):
probe = [probe]
probe = [str(prb) for prb in probe]
out_files = []
for prb in probe:
if instrument == 'lad':
pathformat = 'twins' + prb + '/' + instrument + '/%Y/twins' + prb + '_l1_lad_%Y%m%d_v??.cdf'
elif instrument == 'imager':
pathformat = 'twins' + prb + '/' + instrument + '/%Y/twins' + prb + '_l1_imager_%Y%m%d??_v??.cdf'
elif instrument == 'ephemeris':
pathformat = 'twins' + prb + '/' + instrument + '/' + datatype + '/%Y/twins' + prb + '_' + datatype + '_def_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
for remote_file in remote_names:
files = download(remote_file=remote_file,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
merge=True,
get_support_data=get_support_data,
varformat=varformat,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2013-11-5', '2013-11-6'],
instrument='fgm',
datatype='k0',
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
varnames=[],
time_clip=False):
"""
This function loads data from the ACE mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.ace.mfi
pyspedas.ace.swe
pyspedas.ace.epam
pyspedas.ace.cris
pyspedas.ace.sis
pyspedas.ace.uleis
pyspedas.ace.sepica
pyspedas.ace.swics
"""
if instrument == 'fgm':
pathformat = 'mag/level_2_cdaweb/mfi_' + datatype + '/%Y/ac_' + datatype + '_mfi_%Y%m%d_v??.cdf'
elif instrument == 'swe':
pathformat = 'swepam/level_2_cdaweb/swe_' + datatype + '/%Y/ac_' + datatype + '_swe_%Y%m%d_v??.cdf'
elif instrument == 'epm':
pathformat = 'epam/level_2_cdaweb/epm_' + datatype + '/%Y/ac_' + datatype + '_epm_%Y%m%d_v??.cdf'
elif instrument == 'cris':
pathformat = 'cris/level_2_cdaweb/cris_' + datatype + '/%Y/ac_' + datatype + '_cris_%Y%m%d_v??.cdf'
elif instrument == 'sis':
pathformat = 'sis/level_2_cdaweb/sis_' + datatype + '/%Y/ac_' + datatype + '_sis_%Y%m%d_v??.cdf'
elif instrument == 'ule':
pathformat = 'uleis/level_2_cdaweb/ule_' + datatype + '/%Y/ac_' + datatype + '_ule_%Y%m%d_v??.cdf'
elif instrument == 'sep':
pathformat = 'sepica/level_2_cdaweb/sep_' + datatype + '/%Y/ac_' + datatype + '_sep_%Y%m%d_v??.cdf'
elif instrument == 'swics':
filename_dtype = datatype.split('_')[1] + '_' + datatype.split('_')[0]
pathformat = 'swics/level_2_cdaweb/' + datatype + '/%Y/ac_' + filename_dtype + '_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['1997-01-03', '1997-01-04'],
instrument='mfe',
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 Polar mission; this function is not meant
to be called directly; instead, see the wrappera:
pyspedas.polar.mfe
pyspedas.polar.efi
pyspedas.polar.pwi
pyspedas.polar.hydra
pyspedas.polar.tide
pyspedas.polar.timas
pyspedas.polar.cammice
pyspedas.polar.ceppad
pyspedas.polar.uvi
pyspedas.polar.vis
pyspedas.polar.pixie
pyspedas.polar.orbit
"""
if instrument == 'mfe':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'efi':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'pwi':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'hydra':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_hyd_%Y%m%d_v??.cdf'
elif instrument == 'tide':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_tid_%Y%m%d_v??.cdf'
elif instrument == 'timas':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_tim_%Y%m%d_v??.cdf'
elif instrument == 'cammice':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_cam_%Y%m%d_v??.cdf'
elif instrument == 'ceppad':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_cep_%Y%m%d_v??.cdf'
elif instrument == 'uvi':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'vis':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'pixie':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_pix_%Y%m%d_v??.cdf'
elif instrument == 'spha':
pathformat = 'orbit/' + instrument + '_' + datatype + '/%Y/po_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2013-11-5', '2013-11-6'],
probe='a',
instrument='mag',
level='l2',
datatype='8hz',
coord='RTN',
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the STEREO mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.stereo.mag
pyspedas.stereo.plastic
"""
out_files = []
if not isinstance(probe, list):
probe = [probe]
if datatype == '32hz':
burst = 'B'
else:
burst = ''
for prb in probe:
if prb == 'a':
direction = 'ahead'
elif prb == 'b':
direction = 'behind'
if instrument == 'mag':
pathformat = 'impact/level1/'+direction+'/mag/'+coord+'/%Y/%m/ST'+prb.upper()+'_L1_MAG'+burst+'_'+coord+'_%Y%m%d_V??.cdf'
elif instrument == 'plastic':
CONFIG['remote_data_dir'] = 'http://stereo-ssc.nascom.nasa.gov/data/ins_data/'
if level == 'l2':
pathformat = 'plastic/level2/Protons/Derived_from_1D_Maxwellian/'+direction+'/'+datatype+'/%Y/ST'+prb.upper()+'_L2_PLA_1DMax_'+datatype+'_%Y%m%d_V??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
for remote_file in remote_names:
files = download(remote_file=remote_file, remote_path=CONFIG['remote_data_dir'], local_path=CONFIG['local_data_dir'], no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files, suffix=suffix, merge=True, get_support_data=get_support_data, varformat=varformat, notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def _make_SECS_plots(data=None, dtime=None, contour_den=8, s_loc=False):
"""
@Parameter: dtime input as a string
@Parameter: s_loc input as a bool, which means the locations of the virtual stations.
"""
dtype = 'SECS'
if not os.path.exists(CONFIG['plots_dir']):
os.makedirs(CONFIG['plots_dir'])
dtime_range = [dtime, dtime]
pathformat_prefix = dtype + '/%Y/%m/'
pathformat_unzipped = pathformat_prefix + '%d/' + dtype + '%Y%m%d_%H%M%S.dat'
filename_unzipped = dailynames(file_format=pathformat_unzipped,
trange=dtime_range,
res=10)
out_files_unzipped = [
CONFIG['local_data_dir'] + rf_res for rf_res in filename_unzipped
]
Data_Days_time = read_data_files(out_files=out_files_unzipped,
dtype=dtype,
out_type='df')
J_comp = Data_Days_time['J']
Jc_max, Jc_min = J_comp.max(), J_comp.min()
Jcm_abs = max(abs(Jc_max), abs(Jc_min))
contour_density = np.linspace(-Jcm_abs, Jcm_abs, num=contour_den)
tp = dtime
datetime_tp = tp[0:4] + tp[5:7] + tp[8:10] + '_' + tp[11:13] + tp[
14:16] + tp[17:19]
lon = Data_Days_time['longitude']
lat = Data_Days_time['latitude']
J = Data_Days_time['J']
lon = lon.to_numpy()
lat = lat.to_numpy()
J = J.to_numpy()
# plot 1: contour plot
# plot map ground (North hemisphere)
fig = plt.figure(figsize=(8, 8))
m = Basemap(projection='lcc',
resolution='c',
width=8E6,
height=8E6,
lat_0=60,
lon_0=-100)
# draw coastlines, country boundaries, fill continents.
m.drawcoastlines(linewidth=0.25)
m.drawcountries(linewidth=0.25)
m.fillcontinents(color='None', lake_color='None')
# draw the edge of the map projection region (the projection limb)
m.drawmapboundary(fill_color=None)
m.drawlsmask()
m.shadedrelief()
# draw parallels and meridians.
# label parallels on right and top
# meridians on bottom and left
parallels = np.arange(0., 81, 10.)
m.drawparallels(parallels, labels=[False, True, True, False])
meridians = np.arange(10., 351., 20.)
m.drawmeridians(meridians, labels=[True, False, False, True])
date_nightshade = datetime.strptime(dtime, '%Y-%m-%d/%H:%M:%S')
delta = 0.25
lons_dd, lats_dd, tau, dec = daynight_terminator(date_nightshade, delta,
m.lonmin, m.lonmax)
xy = [lons_dd, lats_dd]
xy = np.array(xy)
xb, yb = xy[0], xy[1]
m.plot(xb, yb, marker=None, color='b', latlon=True)
# Plot the noon-midnight line.
n_interval = len(lons_dd)
ni_half = int(np.floor(len(lons_dd) / 2))
ni_otherhalf = n_interval - ni_half
noon_midnight = noon_midnight_meridian(dtime, delta)
m.plot(noon_midnight['lons_noon'],
noon_midnight['lats_noon'],
marker=None,
color='deepskyblue',
latlon=True) # noon semi-circle
m.plot(noon_midnight['lons_midnight'],
noon_midnight['lats_midnight'],
marker=None,
color='k',
latlon=True) # midnight semi-circle
draw_map(m)
norm_cb = CenteredNorm()
ctrf = m.contourf(lon,
lat,
J,
contour_density,
latlon=True,
tri=True,
cmap=plt.get_cmap('seismic', 20),
norm=norm_cb)
if s_loc:
m.scatter(lon, lat, latlon=True, marker='*', c='black')
cb = m.colorbar(matplotlib.cm.ScalarMappable(norm=norm_cb, cmap='seismic'),
pad='15%')
cb.set_label(r'$\mathit{J} \ (mA/m)$')
ax_cb = cb.ax
text = ax_cb.yaxis.label
font_cb = matplotlib.font_manager.FontProperties(family='times new roman',
style='italic',
size=20)
text.set_font_properties(font_cb)
plt.title(label='SECS ' + tp, fontsize=20, color="black", pad=20)
plt.tight_layout()
plt.savefig(CONFIG['plots_dir'] + 'SECS' + '_' +
date_nightshade.strftime('%Y%m%d%H%M%S') + '.jpeg')
plt.show()
print('SECS plots completed!')
return
def mms_load_data_spdf(trange=['2015-10-16', '2015-10-17'],
probe='1',
data_rate='srvy',
level='l2',
instrument='fgm',
datatype='',
varformat=None,
suffix='',
get_support_data=False,
time_clip=False,
no_update=False,
center_measurement=False,
available=False,
notplot=False,
latest_version=False,
major_version=False,
min_version=None,
cdf_version=None):
tvars_created = []
if not isinstance(probe, list): probe = [probe]
if not isinstance(data_rate, list): data_rate = [data_rate]
if not isinstance(level, list): level = [level]
if not isinstance(datatype, list): datatype = [datatype]
if data_rate == 'brst':
time_format = '%Y%m%d??????'
else:
time_format = '%Y%m%d'
for prb in probe:
for lvl in level:
for drate in data_rate:
for dtype in datatype:
remote_path = 'mms' + prb + '/' + instrument + '/' + drate + '/' + lvl + '/'
if instrument == 'fgm':
pathformat = remote_path + '%Y/%m/mms' + prb + '_fgm_' + drate + '_' + lvl + '_' + time_format + '_v*.cdf'
elif instrument == 'aspoc':
pathformat = remote_path + '%Y/%m/mms' + prb + '_aspoc_' + drate + '_' + lvl + '_' + time_format + '_v*.cdf'
elif instrument == 'edi':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_edi_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'fpi':
if drate != 'brst':
time_format = '%Y%m%d??0000'
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_fpi_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'epd-eis':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_epd-eis_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'feeps':
if drate != 'brst':
time_format = '%Y%m%d000000'
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_feeps_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'hpca':
time_format = '%Y%m%d??????'
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_hpca_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'mec':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_mec_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'scm':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_scm_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'dsp':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_dsp_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'edp':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_edp_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat,
trange=trange)
out_files = []
for remote_file in remote_names:
files = download(remote_file=remote_file,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'])
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
filtered_out_files = mms_file_filter(
out_files,
latest_version=latest_version,
major_version=major_version,
min_version=min_version,
version=cdf_version)
tvars = cdf_to_tplot(filtered_out_files,
merge=True,
varformat=varformat,
get_support_data=get_support_data,
suffix=suffix,
center_measurement=center_measurement,
notplot=notplot)
if tvars is not None:
tvars_created.extend(tvars)
if time_clip:
for new_var in tvars_created:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars_created
def load(trange=['2013-11-5', '2013-11-6'],
instrument='mgf',
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 Geotail mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.geotail.mgf
pyspedas.geotail.efd
pyspedas.geotail.lep
pyspedas.geotail.cpi
pyspedas.geotail.epi
pyspedas.geotail.pwi
"""
tvars_created = []
if instrument == 'mgf':
if datatype == 'k0':
pathformat = 'mgf/mgf_k0/%Y/ge_' + datatype + '_mgf_%Y%m%d_v??.cdf'
elif datatype == 'eda3sec' or datatype == 'edb3sec':
pathformat = 'mgf/' + datatype + '_mgf/%Y/ge_' + datatype + '_mgf_%Y%m%d_v??.cdf'
elif instrument == 'efd':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/ge_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'lep':
if datatype == 'k0':
pathformat = 'lep/lep_k0/%Y/ge_' + datatype + '_lep_%Y%m%d_v??.cdf'
elif instrument == 'cpi':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/ge_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'epi':
pathformat = 'epic/' + instrument + '_' + datatype + '/%Y/ge_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'pwi':
pathformat = instrument + '/' + instrument + '_' + datatype + '/%Y/ge_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2018-11-5', '2018-11-6'],
probe='1',
instrument='fgm',
datatype='up',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the Cluster mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.cluster.fgm
pyspedas.cluster.aspoc
pyspedas.cluster.cis
pyspedas.cluster.dwp
pyspedas.cluster.edi
pyspedas.cluster.efw
pyspedas.cluster.peace
pyspedas.cluster.rapid
pyspedas.cluster.staff
pyspedas.cluster.wbd
pyspedas.cluster.whi
"""
if not isinstance(probe, list):
probe = [probe]
probe = [str(prb)
for prb in probe] # these will need to be strings from now on
out_files = []
res = 24 * 3600
if instrument != 'wbd':
# note: can't use last_version with WBD data due to using wild cards for the times (and not just in the version)
last_version = True
else:
last_version = False
for prb in probe:
if instrument == 'fgm':
if datatype == 'cp':
pathformat = 'c' + prb + '/cp/%Y/c' + prb + '_cp_fgm_spin_%Y%m%d_v??.cdf'
else:
pathformat = 'c' + prb + '/' + datatype + '/' + instrument + '/%Y/c' + prb + '_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'aspoc':
pathformat = 'c' + prb + '/' + datatype + '/asp/%Y/c' + prb + '_' + datatype + '_asp_%Y%m%d_v??.cdf'
elif instrument == 'cis':
pathformat = 'c' + prb + '/' + datatype + '/' + instrument + '/%Y/c' + prb + '_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'dwp':
pathformat = 'c' + prb + '/' + datatype + '/' + instrument + '/%Y/c' + prb + '_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'edi':
pathformat = 'c' + prb + '/' + datatype + '/' + instrument + '/%Y/c' + prb + '_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'efw':
pathformat = 'c' + prb + '/' + datatype + '/' + instrument + '/%Y/c' + prb + '_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'peace':
pathformat = 'c' + prb + '/' + datatype + '/pea/%Y/c' + prb + '_' + datatype + '_pea_%Y%m%d_v??.cdf'
elif instrument == 'rapid':
pathformat = 'c' + prb + '/' + datatype + '/rap/%Y/c' + prb + '_' + datatype + '_rap_%Y%m%d_v??.cdf'
elif instrument == 'staff':
pathformat = 'c' + prb + '/' + datatype + '/sta/%Y/c' + prb + '_' + datatype + '_sta_%Y%m%d_v??.cdf'
elif instrument == 'whi':
pathformat = 'c' + prb + '/' + datatype + '/' + instrument + '/%Y/c' + prb + '_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'wbd':
pathformat = 'c' + prb + '/' + instrument + '/%Y/%m/c' + prb + '_' + datatype + '_' + instrument + '_%Y%m%d%H%M_v??.cdf'
res = 600.0
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat,
trange=trange,
res=res)
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update,
last_version=last_version)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def mms_load_data_spdf(trange=['2015-10-16', '2015-10-17'],
probe='1',
data_rate='srvy',
level='l2',
instrument='fgm',
datatype='',
varformat=None,
suffix='',
get_support_data=False,
time_clip=False,
no_update=False,
center_measurement=False,
available=False,
notplot=False,
latest_version=False,
major_version=False,
min_version=None,
cdf_version=None,
varnames=[]):
"""
This function loads MMS data from NASA SPDF into pyTplot variables
This function is not meant to be called directly. Please see the individual load routines for documentation and use.
"""
tvars_created = []
if not isinstance(probe, list): probe = [probe]
if not isinstance(data_rate, list): data_rate = [data_rate]
if not isinstance(level, list): level = [level]
if not isinstance(datatype, list): datatype = [datatype]
for prb in probe:
for lvl in level:
for drate in data_rate:
if drate == 'brst':
time_format = '%Y%m%d%H%M??'
file_res = 60.
else:
time_format = '%Y%m%d'
file_res = 24 * 3600.
for dtype in datatype:
remote_path = 'mms' + prb + '/' + instrument + '/' + drate + '/' + lvl + '/'
if instrument == 'fgm':
pathformat = remote_path + '%Y/%m/mms' + prb + '_fgm_' + drate + '_' + lvl + '_' + time_format + '_v*.cdf'
elif instrument == 'aspoc':
pathformat = remote_path + '%Y/%m/mms' + prb + '_aspoc_' + drate + '_' + lvl + '_' + time_format + '_v*.cdf'
elif instrument == 'edi':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_edi_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'fpi':
if drate != 'brst':
time_format = '%Y%m%d??0000'
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_fpi_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'epd-eis':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_epd-eis_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'feeps':
if drate != 'brst':
time_format = '%Y%m%d000000'
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_feeps_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'hpca':
time_format = '%Y%m%d??????'
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_hpca_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'mec':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_mec_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'scm':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_scm_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'dsp':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_dsp_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
elif instrument == 'edp':
pathformat = remote_path + dtype + '/%Y/%m/mms' + prb + '_edp_' + drate + '_' + lvl + '_' + dtype + '_' + time_format + '_v*.cdf'
if drate == 'brst':
if isinstance(trange[0], float):
trange = [trange[0] - 300., trange[1]]
else:
trange = [time_double(trange[0]) - 300., trange[1]]
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat,
trange=trange,
res=file_res)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'])
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
filtered_out_files = mms_file_filter(
out_files,
latest_version=latest_version,
major_version=major_version,
min_version=min_version,
version=cdf_version)
tvars = cdf_to_tplot(filtered_out_files,
varformat=varformat,
varnames=varnames,
get_support_data=get_support_data,
suffix=suffix,
center_measurement=center_measurement,
notplot=notplot)
if tvars is not None:
tvars_created.extend(tvars)
if time_clip:
for new_var in tvars_created:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars_created
def load(
trange=['2018-11-5', '2018-11-6'],
probe='a',
instrument='emfisis',
level='l3',
datatype='magnetometer',
suffix='',
cadence='4sec', # for EMFISIS mag data
coord='sm', # for EMFISIS mag data
wavetype='waveform', # for EMFISIS waveform data
rel='rel04', # for ECT data
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads Van Allen Probes (RBSP) data; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.rbsp.emfisis
pyspedas.rbsp.rbspice
pyspedas.rbsp.efw
pyspedas.rbsp.mageis
pyspedas.rbsp.hope
pyspedas.rbsp.rept
pyspedas.rbsp.rps
"""
if not isinstance(probe, list):
probe = [probe]
out_files = []
for prb in probe:
if instrument == 'emfisis':
if datatype == 'density' or datatype == 'housekeeping' or datatype == 'wna-survey':
pathformat = 'rbsp' + prb + '/' + level + '/' + instrument + '/' + datatype + '/%Y/rbsp-' + prb + '_' + datatype + '_' + instrument + '-' + level + '_%Y%m%d_v*.cdf'
elif datatype == 'wfr' or datatype == 'hfr':
pathformat = 'rbsp' + prb + '/' + level + '/' + instrument + '/' + datatype + '/' + wavetype + '/%Y/rbsp-' + prb + '_' + datatype + '-' + wavetype + '_' + instrument + '-' + level + '_%Y%m%d*_v*.cdf'
else:
if level == 'l2' and datatype == 'magnetometer':
pathformat = 'rbsp' + prb + '/' + level + '/' + instrument + '/' + datatype + '/uvw/%Y/rbsp-' + prb + '_' + datatype + '_uvw_' + instrument + '-' + level + '_%Y%m%d*_v*.cdf'
else:
pathformat = 'rbsp' + prb + '/' + level + '/' + instrument + '/' + datatype + '/' + cadence + '/' + coord + '/%Y/rbsp-' + prb + '_' + datatype + '_' + cadence + '-' + coord + '_' + instrument + '-' + level + '_%Y%m%d_v*.cdf'
elif instrument == 'rbspice':
pathformat = 'rbsp' + prb + '/' + level + '/' + instrument + '/' + datatype + '/%Y/rbsp-' + prb + '-' + instrument + '_lev-' + str(
level[-1]) + '?' + datatype + '_%Y%m%d_v*.cdf'
elif instrument == 'efw':
if level == 'l3':
pathformat = 'rbsp' + prb + '/' + level + '/' + instrument + '/%Y/rbsp' + prb + '_' + instrument + '-' + level + '_%Y%m%d_v??.cdf'
else:
pathformat = 'rbsp' + prb + '/' + level + '/' + instrument + '/' + datatype + '/%Y/rbsp' + prb + '_' + instrument + '-' + level + '_' + datatype + '_%Y%m%d_v??.cdf'
elif instrument == 'mageis':
pathformat = 'rbsp' + prb + '/' + level + '/ect/' + instrument + '/sectors/' + rel + '/%Y/rbsp' + prb + '_' + rel + '_ect-mageis-' + level + '_%Y%m%d_v*.cdf'
elif instrument == 'hope':
if datatype == 'moments':
pathformat = 'rbsp' + prb + '/' + level + '/ect/' + instrument + '/' + datatype + '/' + rel + '/%Y/rbsp' + prb + '_' + rel + '_ect-hope-mom-' + level + '_%Y%m%d_v*.cdf'
elif datatype == 'pitchangle':
pathformat = 'rbsp' + prb + '/' + level + '/ect/' + instrument + '/' + datatype + '/' + rel + '/%Y/rbsp' + prb + '_' + rel + '_ect-hope-pa-' + level + '_%Y%m%d_v*.cdf'
elif datatype == 'spinaverage':
pathformat = 'rbsp' + prb + '/' + level + '/ect/' + instrument + '/' + datatype + '/' + rel + '/%Y/rbsp' + prb + '_' + rel + '_ect-hope-sci-' + level + 'sa_%Y%m%d_v*.cdf'
elif instrument == 'rept':
pathformat = 'rbsp' + prb + '/' + level + '/ect/' + instrument + '/sectors/' + rel + '/%Y/rbsp' + prb + '_' + rel + '_ect-rept-sci-' + level + '_%Y%m%d_v*.cdf'
elif instrument == 'rps':
if datatype == 'rps-1min':
pathformat = 'rbsp' + prb + '/' + level + '/rps/psbr-rps-1min/%Y/rbsp' + prb + '_' + level + '-1min_psbr-rps_%Y%m%d_v*.cdf'
elif datatype == 'rps':
pathformat = 'rbsp' + prb + '/' + level + '/rps/psbr-rps/%Y/rbsp' + prb + '_' + level + '_psbr-rps_%Y%m%d_v*.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['1998-04-06', '1998-04-07'],
instrument='mam',
datatype='pp',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the Equator-S mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.equator_s.mam
pyspedas.equator_s.edi
pyspedas.equator_s.esa (3DA)
pyspedas.equator_s.epi
pyspedas.equator_s.ici
pyspedas.equator_s.pcd
pyspedas.equator_s.sfd
"""
if instrument == 'mam':
pathformat = datatype + '/' + instrument + '/%Y/eq_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'edi':
pathformat = datatype + '/' + instrument + '/%Y/eq_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == '3da':
pathformat = datatype + '/' + instrument + '/%Y/eq_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'epi':
pathformat = datatype + '/' + instrument + '/%Y/eq_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'ici':
pathformat = datatype + '/' + instrument + '/%Y/eq_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'pcd':
pathformat = datatype + '/' + instrument + '/%Y/eq_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
elif instrument == 'sfd':
pathformat = datatype + '/' + instrument + '/%Y/eq_' + datatype + '_' + instrument + '_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2009-01-01', '2009-01-02'],
instrument='vhm',
datatype='1min',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function is not meant to be called directly; please see the instrument specific wrappers in __init__.py
"""
if instrument == 'vhm':
pathformat = 'mag_cdaweb/vhm_'+datatype+'/%Y/uy_'+datatype+'_vhm_%Y%m%d_v??.cdf'
elif instrument == 'swoops':
if datatype in ['bai_m0', 'bai_m1', 'bae_m0']:
pathformat = 'plasma/swoops_cdaweb/'+datatype+'/%Y/uy_'+datatype.split('_')[1]+'_'+datatype.split('_')[0]+'_%Y%m%d_v??.cdf'
else:
pathformat = 'plasma/swoops_cdaweb/'+datatype+'/%Y/uy_'+datatype+'_%Y0101_v??.cdf'
elif instrument == 'swics':
pathformat = 'plasma/swics_cdaweb/'+datatype+'/%Y/uy_'+datatype.split('_')[1]+'_'+datatype.split('_')[0]+'_%Y%m%d_v??.cdf'
elif instrument == 'urap':
pathformat = 'radio/urap_cdaweb/'+datatype+'/%Y/uy_'+datatype.split('_')[1]+'_'+datatype.split('_')[0]+'_%Y%m%d_v??.cdf'
elif instrument == 'epac':
if datatype == 'epac_m1':
pathformat = 'particle/epac_cdaweb/'+datatype+'/%Y/uy_m1_epa_%Y%m%d_v??.cdf'
elif instrument == 'hiscale':
pathformat = 'particle/hiscale_cdaweb/'+datatype+'/%Y/uy_'+datatype.split('_')[1]+'_'+datatype.split('_')[0]+'_%Y%m%d_v??.cdf'
elif instrument == 'cospin':
pathformat = 'particle/cospin_cdaweb/'+datatype+'/%Y/uy_m0_'+datatype+'_%Y%m%d_v??.cdf'
elif instrument == 'grb':
pathformat = 'gamma/grb_cdaweb/'+datatype+'/%Y/uy_'+datatype.split('_')[1]+'_'+datatype.split('_')[0]+'_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names, remote_path=CONFIG['remote_data_dir'], local_path=CONFIG['local_data_dir'], no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2013-11-5', '2013-11-6'],
instrument='fgm',
probe='c',
level='l2',
stations=None, # ground mag data
greenland=None, # also for ground mag data
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the THEMIS mission;
this function is not meant to be called directly;
instead, see the wrappers:
pyspedas.themis.fgm
pyspedas.themis.fit
pyspedas.themis.efi
pyspedas.themis.scm
pyspedas.themis.fft
pyspedas.themis.fbk
pyspedas.themis.esa
pyspedas.themis.sst
pyspedas.themis.mom
pyspedas.themis.gmom
pyspedas.themis.gmag
pyspedas.themis.state
"""
if not isinstance(probe, list):
probe = [probe]
out_files = []
for prb in probe:
if instrument == 'fgm':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif instrument == 'fit':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif instrument == 'efi':
if level == 'l2':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif level == 'l1':
pathformat = [('th' + prb + '/' + level + '/vaf/%Y/th' + prb
+ '_' + level + '_vaf_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/vap/%Y/th' + prb
+ '_' + level + '_vap_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/vaw/%Y/th' + prb
+ '_' + level + '_vaw_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/vbf/%Y/th' + prb
+ '_' + level + '_vbf_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/vbp/%Y/th' + prb
+ '_' + level + '_vbp_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/vbw/%Y/th' + prb
+ '_' + level + '_vbw_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/eff/%Y/th' + prb
+ '_' + level + '_eff_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/efw/%Y/th' + prb
+ '_' + level + '_efw_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/efp/%Y/th' + prb
+ '_' + level + '_efp_%Y%m%d_v??.cdf')]
elif instrument == 'scm':
if level == 'l2':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif level == 'l1':
pathformat = [('th' + prb + '/' + level + '/scp/%Y/th' + prb
+ '_' + level + '_scp_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/scf/%Y/th' + prb
+ '_' + level + '_scf_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/scw/%Y/th' + prb
+ '_' + level + '_scw_%Y%m%d_v??.cdf')]
elif instrument == 'fft':
if level == 'l2':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif level == 'l1':
pathformat = [('th' + prb + '/' + level + '/fff_16/%Y/th' + prb
+ '_' + level + '_fff_16_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/fff_32/%Y/th' + prb
+ '_' + level + '_fff_32_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/fff_64/%Y/th' + prb
+ '_' + level + '_fff_64_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/ffp_16/%Y/th' + prb
+ '_' + level + '_ffp_16_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/ffp_32/%Y/th' + prb
+ '_' + level + '_ffp_32_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/ffp_64/%Y/th' + prb
+ '_' + level + '_ffp_64_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/ffw_16/%Y/th' + prb
+ '_' + level + '_ffw_16_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/ffw_32/%Y/th' + prb
+ '_' + level + '_ffw_32_%Y%m%d_v??.cdf'),
('th' + prb + '/' + level + '/ffw_64/%Y/th' + prb
+ '_' + level + '_ffw_64_%Y%m%d_v??.cdf')]
elif instrument == 'fbk':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif instrument == 'esa':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif instrument == 'sst':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif instrument == 'mom':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif instrument == 'gmom':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d_v??.cdf')
elif instrument == 'state':
pathformat = ('th' + prb + '/' + level + '/' + instrument
+ '/%Y/th' + prb + '_' + level + '_' + instrument
+ '_%Y%m%d.cdf')
elif instrument == 'gmag':
if stations is None:
logging.error('No stations specified')
return
else:
pathformat = []
for site, in_greenland in zip(stations, greenland):
if in_greenland:
pathformat.append('thg/greenland_gmag/' + level
+ '/mag/' + site + '/%Y/thg_' + level
+ '_mag_' + site + '_%Y%m%d_v??.cdf')
else:
pathformat.append('thg/' + level + '/mag/' + site
+ '/%Y/thg_' + level + '_mag_' + site
+ '_%Y%m%d_v??.cdf')
if not isinstance(pathformat, list):
pathformat = [pathformat]
for file_format in pathformat:
# find the full remote path names using the trange
remote_names = dailynames(file_format=file_format, trange=trange)
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update,
last_version=True)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
merge=True,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def get_w(trange=None, create_tvar=False, newname=None):
"""
This routine downloads the 6 Tsygeneko (TS05) model
driving variables W1, W2, W3, W4, W5, W6; from:
http://geo.phys.spbu.ru/~tsyganenko/TS05_data_and_stuff
"""
if trange is None:
print('trange keyword must be specified.')
return
years = dailynames(trange=trange, file_format='%Y')
tmpdir = mkdtemp()
if newname is None:
newname = 'Tsy_W_vars_' + '-'.join(years)
ut_out = np.empty(0)
w1_out = np.empty(0)
w2_out = np.empty(0)
w3_out = np.empty(0)
w4_out = np.empty(0)
w5_out = np.empty(0)
w6_out = np.empty(0)
for year in years:
file = download(
remote_path=
'http://geo.phys.spbu.ru/~tsyganenko/TS05_data_and_stuff/',
remote_file=year + '_OMNI_5m_with_TS05_variables.???',
local_path=tmpdir)
if file[0][-3:] == 'zip':
with zipfile.ZipFile(file[0], 'r') as zip_ref:
zip_ref.extractall(tmpdir)
rows = pd.read_csv(tmpdir + '/' + year +
'_OMNI_5m_with_TS05_variables.dat',
delim_whitespace=True,
header=None)
# extract the W variables
w1 = rows.to_numpy()[:, -6]
w2 = rows.to_numpy()[:, -5]
w3 = rows.to_numpy()[:, -4]
w4 = rows.to_numpy()[:, -3]
w5 = rows.to_numpy()[:, -2]
w6 = rows.to_numpy()[:, -1]
# extract the times
years = rows.to_numpy()[:, 0]
doys = rows.to_numpy()[:, 1]
hours = rows.to_numpy()[:, 2]
minutes = rows.to_numpy()[:, 3]
time_strings = [
str(int(year)) + '-' + str(int(doy)).zfill(3) + ' ' +
str(int(hour)).zfill(2) + ':' + str(int(minute)).zfill(2)
for year, doy, hour, minute in zip(years, doys, hours, minutes)
]
unix_times = np.array(time_double(time_strings))
ut_out = np.append(ut_out, unix_times)
w1_out = np.append(w1_out, w1)
w2_out = np.append(w2_out, w2)
w3_out = np.append(w3_out, w3)
w4_out = np.append(w4_out, w4)
w5_out = np.append(w5_out, w5)
w6_out = np.append(w6_out, w6)
in_range = np.argwhere((ut_out >= time_double(trange[0]))
& (ut_out < time_double(trange[1]))).squeeze()
if len(in_range) == 0:
print('No data found in the trange.')
return
if create_tvar:
out = np.array((w1_out[in_range], w2_out[in_range], w3_out[in_range],
w4_out[in_range], w5_out[in_range], w6_out[in_range]))
store_data(newname, data={'x': ut_out[in_range], 'y': out.T})
return newname
return {
'times': ut_out[in_range],
'w1': w1_out[in_range],
'w2': w2_out[in_range],
'w3': w3_out[in_range],
'w4': w4_out[in_range],
'w5': w5_out[in_range],
'w6': w6_out[in_range]
}
def load(trange=['2013-11-5', '2013-11-6'],
probe='15',
instrument='fgm',
datatype='1min',
suffix='',
downloadonly=False,
no_update=False,
time_clip=False):
"""
This function loads data from the GOES mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.goes.fgm
"""
if not isinstance(probe, list):
probe = [probe]
fullavgpath = ['full', 'avg']
goes_path_dir = fullavgpath[datatype == '1min' or datatype == '5min']
for prb in probe:
remote_path = goes_path_dir + '/%Y/%m/goes' + str(prb) + '/netcdf/'
if instrument == 'fgm':
if datatype == '512ms': # full, unaveraged data
pathformat = remote_path + 'g' + str(
prb) + '_magneto_512ms_%Y%m%d_%Y%m%d.nc'
elif datatype == '1min': # 1 min averages
pathformat = remote_path + 'g' + str(
prb) + '_magneto_1m_%Y%m01_%Y%m??.nc'
elif datatype == '5min': # 5 min averages
pathformat = remote_path + 'g' + str(
prb) + '_magneto_5m_%Y%m01_%Y%m??.nc'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = netcdf_to_tplot(out_files,
suffix=suffix,
merge=True,
time='time_tag')
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2018-11-5', '2018-11-6'],
instrument='fields',
datatype='mag_rtn',
level='l2',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads Parker Solar Probe data into tplot variables; this function is not
meant to be called directly; instead, see the wrappers:
psp.fields: FIELDS data
psp.spc: Solar Probe Cup data
psp.spe: SWEAP/SPAN-e data
psp.spi: SWEAP/SPAN-i data
psp.epihi: ISoIS/EPI-Hi data
psp.epilo: ISoIS/EPI-Lo data
psp.epi ISoIS/EPI (merged Hi-Lo) data
"""
file_resolution = 24*3600.
if instrument == 'fields':
pathformat = instrument + '/' + level + '/' + datatype + '/%Y/psp_fld_' + level + '_' + datatype + '_%Y%m%d%H_v??.cdf'
file_resolution = 6*3600.
elif instrument == 'spc':
pathformat = 'sweap/spc/' + level + '/' + datatype + '/%Y/psp_swp_spc_' + datatype + '_%Y%m%d_v??.cdf'
elif instrument == 'spe':
pathformat = 'sweap/spe/' + level + '/' + datatype + '/%Y/psp_swp_sp?_*_%Y%m%d_v??.cdf'
elif instrument == 'spi':
pathformat = 'sweap/spi/' + level + '/' + datatype + '/%Y/psp_swp_spi_*_%Y%m%d_v??.cdf'
elif instrument == 'epihi':
pathformat = 'isois/epihi/' + level + '/' + datatype + '/%Y/psp_isois-epihi_' + level + '*_%Y%m%d_v??.cdf'
elif instrument == 'epilo':
pathformat = 'isois/epilo/' + level + '/' + datatype + '/%Y/psp_isois-epilo_' + level + '*_%Y%m%d_v??.cdf'
elif instrument == 'epi':
pathformat = 'isois/merged/' + level + '/' + datatype + '/%Y/psp_isois_' + level + '-' + datatype + '_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange, res=file_resolution)
out_files = []
files = download(remote_file=remote_names, remote_path=CONFIG['remote_data_dir'], local_path=CONFIG['local_data_dir'], no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2004-11-5', '2004-11-6'],
instrument='lena',
datatype='k0',
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads IMAGE data; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.image.lena
pyspedas.image.mena
pyspedas.image.hena
pyspedas.image.rpi
pyspedas.image.euv
pyspedas.image.fuv
"""
if instrument == 'lena':
pathformat = instrument+'/'+instrument+'_'+datatype+'/%Y/im_'+datatype+'_'+instrument+'_%Y%m%d_v??.cdf'
elif instrument == 'mena':
pathformat = instrument+'/'+instrument+'_'+datatype+'/%Y/im_'+datatype+'_'+instrument+'_%Y%m%d_v??.cdf'
elif instrument == 'hena':
pathformat = instrument+'/'+instrument+'_'+datatype+'/%Y/im_'+datatype+'_'+instrument+'_%Y%m%d_v??.cdf'
elif instrument == 'rpi':
pathformat = instrument+'/'+instrument+'_'+datatype+'/%Y/im_'+datatype+'_'+instrument+'_%Y%m%d_v??.cdf'
elif instrument == 'euv':
pathformat = instrument+'/'+instrument+'_'+datatype+'/%Y/im_'+datatype+'_'+instrument+'_%Y%m%d_v??.cdf'
elif instrument == 'fuv':
pathformat = instrument+'/wic_'+datatype+'/%Y/im_'+datatype+'_wic_%Y%m%d_v??.cdf'
elif instrument == 'orbit':
if datatype == 'def_or':
pathformat = instrument+'/def_or/%Y/im_or_def_%Y%m%d_v??.cdf'
elif datatype == 'pre_or':
pathformat = instrument+'/pre_or/%Y/im_or_pre_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names, remote_path=CONFIG['remote_data_dir'], local_path=CONFIG['local_data_dir'], no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files, suffix=suffix, merge=True, get_support_data=get_support_data, varformat=varformat, notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def _make_EICS_plots(dtime=None,
vplot_sized=False,
contour_den=8,
s_loc=False,
quiver_scale=30):
"""
@Parameter: dtime input as a string
@Parameter: s_loc input as a bool, which means the locations of the virtual stations.
"""
dtype = 'EICS'
if not os.path.exists(CONFIG['plots_dir']):
os.makedirs(CONFIG['plots_dir'])
dtime_range = [dtime, dtime]
pathformat_prefix = dtype + '/%Y/%m/'
pathformat_unzipped = pathformat_prefix + '%d/' + dtype + '%Y%m%d_%H%M%S.dat'
filename_unzipped = dailynames(file_format=pathformat_unzipped,
trange=dtime_range,
res=10)
out_files_unzipped = [
CONFIG['local_data_dir'] + rf_res for rf_res in filename_unzipped
]
Data_Days_time = read_data_files(out_files=out_files_unzipped,
dtype=dtype,
out_type='df')
J_comp = Data_Days_time['Jy']
Jc_max, Jc_min = J_comp.max(), J_comp.min()
Jcm_abs = max(abs(Jc_max), abs(Jc_min))
contour_density = np.linspace(-Jcm_abs, Jcm_abs, num=contour_den)
tp = dtime
datetime_tp = tp[0:4] + tp[5:7] + tp[8:10] + '_' + tp[11:13] + tp[
14:16] + tp[17:19]
lon = Data_Days_time['longitude']
lat = Data_Days_time['latitude']
Jx = Data_Days_time['Jx'] # Note: positive is Northward
Jy = Data_Days_time['Jy'] # Note: positive is Eastward
# plot 1:
# plot map ground (North hemisphere)
fig1 = plt.figure(figsize=(8, 8))
ax1 = plt.gca()
m = Basemap(projection='lcc',
resolution='c',
width=8E6,
height=8E6,
lat_0=60,
lon_0=-100)
# draw coastlines, country boundaries, fill continents.
m.drawcoastlines(linewidth=0.25)
m.drawcountries(linewidth=0.25)
m.fillcontinents(color='None', lake_color='None')
# draw the edge of the map projection region (the projection limb)
m.drawmapboundary(fill_color=None)
# m.drawgreatcircle(-100,0,0,90)
m.drawlsmask()
# m.bluemarble()
m.shadedrelief()
# draw parallels and meridians.
# label parallels on right and top
# meridians on bottom and left
parallels = np.arange(0., 81, 10.)
# labels = [left,right,top,bottom]
m.drawparallels(parallels, labels=[False, True, True, False])
meridians = np.arange(10., 351., 20.)
m.drawmeridians(meridians, labels=[True, False, False, True])
date_nightshade = datetime.strptime(dtime, '%Y-%m-%d/%H:%M:%S')
m.nightshade(date=date_nightshade)
draw_map(m)
# plot vector field:
lon = lon.to_numpy()
lat = lat.to_numpy()
Jx = Jx.to_numpy() # Note: positive is Northward
Jy = Jy.to_numpy() # Note: positive is Eastward
Jx_uni = Jx / np.sqrt(Jx**2 + Jy**2)
Jy_uni = Jy / np.sqrt(Jx**2 + Jy**2)
n = -2
color = np.sqrt(((Jx_uni - n) / 2)**2 + ((Jy_uni - n) / 2)**2)
if vplot_sized == False:
qv = m.quiver(
lon,
lat,
Jx_uni,
Jy_uni,
color,
headlength=7,
latlon=True,
cmap='GnBu') # autumn_r #, color=cm(norm(o)))#, cmap = 'jet')
plt.colorbar()
else:
Jy_rot, Jx_rot, x, y = m.rotate_vector(Jy, Jx, lon, lat, returnxy=True)
qv = m.quiver(lon,
lat,
Jy_rot,
Jx_rot,
headlength=7,
latlon=True,
scale_units='dots',
scale=quiver_scale) # , transform='lcc')
qk = ax1.quiverkey(qv,
0.3,
-0.1,
100,
r'$100 \ mA/m$',
labelpos='E',
coordinates='data') # figure
plt.title(label='EICS ' + tp, fontsize=20, color="black", pad=20)
plt.tight_layout()
plt.savefig(CONFIG['plots_dir'] + 'EICS' + '_vector_' +
date_nightshade.strftime('%Y%m%d%H%M%S') + '.jpeg')
plt.show()
# plot 2: contour plot
# plot map ground (North hemisphere)
fig2 = plt.figure(figsize=(8, 8))
ax2 = plt.gca()
m = Basemap(projection='lcc',
resolution='c',
width=8E6,
height=8E6,
lat_0=60,
lon_0=-100)
# draw coastlines, country boundaries, fill continents.
m.drawcoastlines(linewidth=0.25)
m.drawcountries(linewidth=0.25)
m.fillcontinents(color='None', lake_color='None')
# draw the edge of the map projection region (the projection limb)
m.drawmapboundary(fill_color=None)
m.drawlsmask()
m.shadedrelief()
# draw parallels and meridians.
# label parallels on right and top
# meridians on bottom and left
parallels = np.arange(0., 81, 10.)
m.drawparallels(parallels, labels=[False, True, True, False])
meridians = np.arange(10., 351., 20.)
m.drawmeridians(meridians, labels=[True, False, False, True])
date_nightshade = datetime.strptime(dtime, '%Y-%m-%d/%H:%M:%S')
# m.nightshade(date=date_nightshade, alpha = 0.0)
delta = 0.25
lons_dd, lats_dd, tau, dec = daynight_terminator(date_nightshade, delta,
m.lonmin, m.lonmax)
xy = [lons_dd, lats_dd]
xy = np.array(xy)
xb, yb = xy[0], xy[1]
m.plot(xb, yb, marker=None, color='m',
latlon=True) # for dawn-dusk circle line
# Plot the noon-midnight line.
n_interval = len(lons_dd)
ni_half = int(np.floor(len(lons_dd) / 2))
ni_otherhalf = n_interval - ni_half
noon_midnight = noon_midnight_meridian(dtime, delta)
m.plot(noon_midnight['lons_noon'],
noon_midnight['lats_noon'],
marker=None,
color='deepskyblue',
latlon=True) # noon semi-circle
m.plot(noon_midnight['lons_midnight'],
noon_midnight['lats_midnight'],
marker=None,
color='k',
latlon=True) # midnight semi-circle
draw_map(m)
Jy_log = Jy / np.abs(Jy) * np.log10(np.abs(Jy))
norm_cb = CenteredNorm()
# norm_cb = NoNorm()
# norm_cb = CenteredNorm(vmin=Jy.min(), vcenter=0, vmax=Jy.max())
# use Jy for the contour map, not Jy_rot.
ctrf = m.contourf(lon,
lat,
Jy,
contour_density,
latlon=True,
tri=True,
cmap='jet_r',
norm=norm_cb)
##ctrf = m.contourf(lon, lat, Jy, contour_density, latlon=True, tri=True, cmap='jet_r', norm=norm_cb)
# -------------
if s_loc:
m.scatter(lon, lat, latlon=True, marker='*', c='black')
# -------------
cb = m.colorbar(matplotlib.cm.ScalarMappable(norm=norm_cb, cmap='jet_r'),
pad='15%')
cb.set_label(r'$\mathit{J}_y \ (mA/m)$')
ax_cb = cb.ax
text = ax_cb.yaxis.label
font_cb = matplotlib.font_manager.FontProperties(family='times new roman',
style='italic',
size=20)
text.set_font_properties(font_cb)
plt.title(label='EICS ' + tp, fontsize=20, color="black", pad=20)
plt.tight_layout()
plt.savefig(CONFIG['plots_dir'] + 'EICS' + '_contour_' +
date_nightshade.strftime('%Y%m%d%H%M%S') + '.jpeg')
plt.show()
print('EICS plots completed!')
return
def load(trange=['2017-03-27', '2017-03-28'],
instrument='mgf',
datatype='8sec',
mode=None,
site=None,
level='l2',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
uname=None,
passwd=None,
time_clip=False):
"""
This function is not meant to be called directly; please see the instrument specific wrappers:
pyspedas.erg.mgf()
pyspedas.erg.hep()
pyspedas.erg.orb()
pyspedas.erg.lepe()
pyspedas.erg.lepi()
pyspedas.erg.mepe()
pyspedas.erg.mepi()
pyspedas.erg.pwe_ofa()
pyspedas.erg.pwe_efd()
pyspedas.erg.pwe_hfa()
pyspedas.erg.xep()
"""
prefix = 'erg_' + instrument + '_' + level + '_'
file_res = 24 * 3600.
if instrument == 'mgf':
pathformat = 'satellite/erg/' + instrument + '/' + level + '/' + datatype + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_%Y%m%d_v??.??.cdf'
elif instrument == 'hep':
pathformat = 'satellite/erg/' + instrument + '/' + level + '/' + datatype + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_%Y%m%d_v??_??.cdf'
elif instrument == 'orb':
pathformat = 'satellite/erg/' + instrument + '/' + level + '/opq/%Y/%m/erg_' + instrument + '_' + level + '_op_%Y%m%d_v??.cdf'
elif instrument == 'lepe':
pathformat = 'satellite/erg/' + instrument + '/' + level + '/' + datatype + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_%Y%m%d_v??_??.cdf'
elif instrument == 'lepi':
pathformat = 'satellite/erg/' + instrument + '/' + level + '/' + datatype + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_%Y%m%d_v??_??.cdf'
elif instrument == 'mepe':
pathformat = 'satellite/erg/' + instrument + '/' + level + '/' + datatype + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_%Y%m%d_v??_??.cdf'
elif instrument == 'mepi':
pathformat = 'satellite/erg/' + instrument + '/' + level + '/' + datatype + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_%Y%m%d_v??_??.cdf'
elif instrument == 'pwe_ofa':
pathformat = 'satellite/erg/pwe/ofa/' + level + '/' + datatype + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_%Y%m%d_v??_??.cdf'
elif instrument == 'pwe_efd':
pathformat = 'satellite/erg/pwe/efd/' + level + '/' + datatype + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_%Y%m%d_v??_??.cdf'
elif instrument == 'pwe_hfa':
pathformat = 'satellite/erg/pwe/hfa/' + level + '/' + datatype + '/' + mode + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_' + mode + '_%Y%m%d_v??_??.cdf'
elif instrument == 'xep':
pathformat = 'satellite/erg/' + instrument + '/' + level + '/' + datatype + '/%Y/%m/erg_' + instrument + '_' + level + '_' + datatype + '_%Y%m%d_v??_??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat,
trange=trange,
res=file_res)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update,
last_version=True,
username=uname,
password=passwd)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
prefix=prefix,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2020-06-01', '2020-06-02'],
instrument='mag',
datatype='rtn-normal',
mode=None,
level='l2',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the Solar Orbiter mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.solo.mag
pyspedas.solo.epd
pyspedas.solo.rpw
pyspedas.solo.swa
"""
# Defaults for L2, L3 data
science_or_low_latency = 'science'
date_format = '%Y%m%d'
cdf_version = '??'
res = 24*3600.
if level == 'll02':
science_or_low_latency = 'low_latency'
date_format = '%Y%m%dt%H%M??-*'
cdf_version = '???'
res = 60.0
if instrument == 'mag':
pathformat = instrument+'/'+science_or_low_latency+'/'+level+'/'+datatype+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'_'+date_format+'_v'+cdf_version+'.cdf'
elif instrument == 'epd':
pathformat = instrument+'/'+science_or_low_latency+'/'+level+'/'+datatype+'/'+mode+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'-'+mode+'_'+date_format+'_v'+cdf_version+'.cdf'
elif instrument == 'rpw':
pathformat = instrument+'/'+science_or_low_latency+'/'+level+'/'+datatype+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'_'+date_format+'_v'+cdf_version+'.cdf'
elif instrument == 'swa':
if level == 'l2' or level == 'll02':
if datatype == 'pas-eflux' or datatype == 'pas-grnd-mom' or datatype == 'pas-vdf':
pathformat = instrument+'/'+science_or_low_latency+'/'+level+'/'+datatype+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'_'+date_format+'_v'+cdf_version+'.cdf'
else:
date_format = '%Y%m%dt%H%M??-*'
res = 60.0
pathformat = instrument+'/'+science_or_low_latency+'/'+level+'/'+datatype+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'_'+date_format+'_v'+cdf_version+'.cdf'
elif level == 'l1':
if datatype == 'his-pha' or datatype == 'his-sensorrates' or datatype == 'pas-3d' or datatype == 'pas-cal' or datatype == 'pas-mom':
pathformat = instrument+'/'+science_or_low_latency+'/'+level+'/'+datatype+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'_'+date_format+'_v'+cdf_version+'.cdf'
else:
date_format = '%Y%m%dt%H%M??-*'
res = 60.0
pathformat = instrument+'/'+science_or_low_latency+'/'+level+'/'+datatype+'/%Y/solo_'+level+'_'+instrument+'-'+datatype+'_'+date_format+'_v'+cdf_version+'.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange, res=res)
out_files = []
files = download(remote_file=remote_names, remote_path=CONFIG['remote_data_dir'], local_path=CONFIG['local_data_dir'], no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files, suffix=suffix, get_support_data=get_support_data, varformat=varformat, varnames=varnames, notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2013-11-5', '2013-11-6'],
instrument='fgm',
datatype='h0',
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads data from the WIND mission; this function is not meant
to be called directly; instead, see the wrappers:
pyspedas.wind.mfi
pyspedas.wind.swe
pyspedas.wind.sms
pyspedas.wind.threedp
pyspedas.wind.waves
pyspedas.wind.orbit
"""
if instrument == 'fgm':
pathformat = 'mfi/mfi_' + datatype + '/%Y/wi_' + datatype + '_mfi_%Y%m%d_v??.cdf'
elif instrument == 'swe':
pathformat = 'swe/swe_' + datatype + '/%Y/wi_' + datatype + '_swe_%Y%m%d_v??.cdf'
elif instrument == 'sms':
pathformat = 'sms/' + datatype + '/sms_' + datatype + '/%Y/wi_' + datatype + '_sms_%Y%m%d_v??.cdf'
elif instrument == 'waves':
pathformat = 'waves/wav_' + datatype + '/%Y/wi_' + datatype + '_wav_%Y%m%d_v??.cdf'
elif instrument == 'orbit':
pathformat = 'orbit/' + datatype + '/%Y/wi_' + datatype.split(
'_')[1] + '_' + datatype.split('_')[0] + '_%Y%m%d_v??.cdf'
elif instrument == '3dp':
if datatype == '3dp_emfits_e0':
pathformat = '3dp/' + datatype + '/%Y/wi_' + datatype.split(
'_')[1] + '_' + datatype.split('_')[2] + '_' + datatype.split(
'_')[0] + '_%Y%m%d_v??.cdf'
else:
pathformat = '3dp/' + datatype + '/%Y/wi_' + datatype.split(
'_')[1] + '_' + datatype.split('_')[0] + '_%Y%m%d_v??.cdf'
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update,
last_version=True)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def load(trange=['2013-11-5', '2013-11-6'],
datatype='1min',
level='hro2',
suffix='',
get_support_data=False,
get_ignore_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
time_clip=True):
"""
This function loads OMNI (Combined 1AU IP Data; Magnetic and Solar Indices) data; this function is not meant
to be called directly; instead, see the wrapper:
pyspedas.omni.data
"""
if 'min' in datatype:
pathformat = level + '_' + datatype + '/%Y/omni_' + level + '_' + datatype + '_%Y%m01_v??.cdf'
elif 'hour' in datatype:
pathformat = 'hourly/%Y/omni2_h0_mrg1hr_%Y%m01_v??.cdf'
else:
raise TypeError("%r are invalid keyword arguments" % datatype)
# find the full remote path names using the trange
remote_names = dailynames(file_format=pathformat, trange=trange)
out_files = []
files = download(remote_file=remote_names,
remote_path=CONFIG['remote_data_dir'],
local_path=CONFIG['local_data_dir'],
no_download=no_update)
if files is not None:
for file in files:
out_files.append(file)
out_files = sorted(out_files)
if downloadonly:
return out_files
with warnings.catch_warnings():
# for some reason, OMNI CDFs throw ERFA warnings (likely while converting
# times inside astropy); we're ignoring these here
# see: https://github.com/astropy/astropy/issues/9603
warnings.simplefilter('ignore', astropy.utils.exceptions.ErfaWarning)
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
get_ignore_data=get_ignore_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
if notplot:
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars