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='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=['2017-03-27', '2017-03-28'],
pathformat=None,
instrument='mgf',
datatype='8sec',
mode=None,
site=None,
model=None,
level='l2',
prefix='',
suffix='',
file_res=24 * 3600.,
get_support_data=False,
varformat=None,
varnames=[],
downloadonly=False,
notplot=False,
no_update=False,
uname=None,
passwd=None,
time_clip=False,
version=None):
"""
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()
"""
# 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:
if len(out_files) > 0:
cdf_file = cdflib.CDF(out_files[-1])
cdf_info = cdf_file.cdf_info()
all_cdf_variables = cdf_info['rVariables'] + cdf_info['zVariables']
gatt = cdf_file.globalattsget()
for var in all_cdf_variables:
t_plot_name = prefix + var + suffix
if t_plot_name in tvars:
vatt = cdf_file.varattsget(var)
tvars[t_plot_name]['CDF'] = {
'VATT': vatt,
'GATT': gatt,
'FILENAME': out_files[-1]
}
return tvars
if time_clip:
for new_var in tvars:
tclip(new_var, trange[0], trange[1], suffix='')
return tvars
def mms_load_att_tplot(filenames,
level='def',
probe='1',
datatypes=['spinras', 'spindec'],
suffix='',
trange=None):
"""
Helper routine for loading state data (ASCII files from the SDC); not meant to be called directly; see pyspedas.mms.state instead
"""
prefix = 'mms' + probe
file_times = []
file_lras = []
file_ldecs = []
tvalues = {}
logging.info(
'Loading attitude files can take some time; please be patient...')
for file in filenames:
logging.info('Loading ' + file)
rows = pd.read_csv(file,
delim_whitespace=True,
header=None,
skiprows=49)
times = rows.shape[0] - 1
time_values = np.empty(times)
lra_values = np.empty(times)
ldec_values = np.empty(times)
for time_idx in range(0, times):
# these files can overlap, so avoid duplicates
if tvalues.get(time_values[time_idx]):
continue
time_values[time_idx] = pd.to_datetime(
rows[0][time_idx], format='%Y-%jT%H:%M:%S.%f').timestamp()
tvalues[time_values[time_idx]] = 1
lra_values[time_idx] = rows[13][time_idx]
ldec_values[time_idx] = rows[14][time_idx]
file_times.append(time_values)
file_lras.append(lra_values)
file_ldecs.append(ldec_values)
file_times_array = np.concatenate(file_times)
file_lras_array = np.concatenate(file_lras)
file_ldecs_array = np.concatenate(file_ldecs)
file_times_sorted_idx = np.argsort(file_times_array)
file_times_sorted = file_times_array[file_times_sorted_idx]
file_lras_sorted = file_lras_array[file_times_sorted_idx]
file_ldecs_sorted = file_ldecs_array[file_times_sorted_idx]
file_times_uniq = np.unique(file_times_sorted, return_index=True)
file_lras_out = file_lras_sorted[file_times_uniq[1]]
file_ldecs_out = file_ldecs_sorted[file_times_uniq[1]]
if 'spinras' in datatypes:
store_data(prefix + '_' + level + 'att_spinras' + suffix,
data={
'x': file_times_uniq[0],
'y': file_lras_out
})
tclip(prefix + '_' + level + 'att_spinras' + suffix,
trange[0],
trange[1],
suffix='')
if 'spindec' in datatypes:
store_data(prefix + '_' + level + 'att_spindec' + suffix,
data={
'x': file_times_uniq[0],
'y': file_ldecs_out
})
tclip(prefix + '_' + level + 'att_spindec' + suffix,
trange[0],
trange[1],
suffix='')
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 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'],
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 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=['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=['2018-10-16', '2018-10-17'],
instrument='mag',
datatype='h0',
suffix='',
get_support_data=False,
varformat=None,
downloadonly=False,
notplot=False,
no_update=False,
time_clip=False):
"""
This function loads DSCOVR data into tplot variables; this function is not
meant to be called directly; instead, see the wrappers:
dscovr.mag: Fluxgate Magnetometer data
dscovr.fc: Faraday Cup data
dscovr.orb: Ephemeris data
dscovr.att: Attitude data
dscovr.all: Load all data
"""
remote_path = datatype + '/' + instrument + '/%Y/'
if instrument == 'mag':
if datatype == 'h0':
pathformat = remote_path + 'dscovr_h0_mag_%Y%m%d_v??.cdf'
elif instrument == 'faraday_cup':
if datatype == 'h1':
pathformat = remote_path + 'dscovr_h1_fc_%Y%m%d_v??.cdf'
elif instrument == 'pre_or':
if datatype == 'orbit':
pathformat = remote_path + 'dscovr_orbit_pre_%Y%m%d_v??.cdf'
elif instrument == 'def_at':
if datatype == 'orbit':
pathformat = remote_path + 'dscovr_at_def_%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=['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
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
pyspedas.goes.eps
pyspedas.goes.epead
pyspedas.goes.maged
pyspedas.goes.magpd
pyspedas.goes.hepad
pyspedas.goes.xrs
"""
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'
elif instrument == 'eps':
# energetic particle sensor -- only valid for GOES-08 through GOES-12, only averaged data available
if datatype == '1min':
pathformat = remote_path + 'g' + str(
prb) + '_eps_1m_%Y%m01_%Y%m??.nc'
else:
pathformat = remote_path + 'g' + str(
prb) + '_eps_5m_%Y%m01_%Y%m??.nc'
elif instrument == 'epead':
# electron, proton, alpha detector -- only valid on GOES-13, 14, 15
if datatype == '1min':
pathformat = [
remote_path + 'g' + str(prb) +
'_epead_e13ew_1m_%Y%m01_%Y%m??.nc',
'_epead_p17ew_1m_%Y%m01_%Y%m??.c',
'_epead_a16ew_1m_%Y%m01_%Y%m??.nc'
]
elif datatype == '5min':
pathformat = [
remote_path + 'g' + str(prb) +
'_epead_e13ew_5m_%Y%m01_%Y%m??.nc',
'_epead_p17ew_5m_%Y%m01_%Y%m??.c',
'_epead_a16ew_5m_%Y%m01_%Y%m??.nc'
]
else:
pathformat = [
remote_path + 'g' + str(prb) +
'_epead_e1ew_4s_%Y%m%d_%Y%m%d.nc',
'_epead_e2ew_16s_%Y%m%d_%Y%m%d.nc',
'_epead_e3ew_16s_%Y%m%d_%Y%m%d.nc',
'_epead_p1ew_8s_%Y%m%d_%Y%m%d.nc',
'_epead_p27e_32s_%Y%m%d_%Y%m%d.nc',
'_epead_p27w_32s_%Y%m%d_%Y%m%d.nc',
'_epead_a16e_32s_%Y%m%d_%Y%m%d.nc',
'_epead_a16w_32s_%Y%m%d_%Y%m%d.nc'
]
elif instrument == 'maged':
# magnetospheric electron detector -- only valid on GOES 13, 14, 15
if datatype == '1min':
pathformat = remote_path + 'g' + str(
prb) + '_maged_19me15_1m_%Y%m01_%Y%m??.nc'
elif datatype == '5min':
pathformat = remote_path + 'g' + str(
prb) + '_maged_19me15_5m_%Y%m01_%Y%m??.nc'
else:
channels = ['me1', 'me2', 'me3', 'me4', 'me5']
resolution = ['2', '2', '4', '16', '32']
pathformat = []
for idx, channel in enumerate(channels):
pathformat.append(remote_path + 'g' + str(prb) +
'_maged_19' + channel + '_' +
resolution[idx] + 's_%Y%m%d_%Y%m%d.nc')
elif instrument == 'magpd':
# magnetospheric proton detector -- only valid on GOES 13, 14, 15
if datatype == '1min':
pathformat = remote_path + 'g' + str(
prb) + '_magpd_19mp15_1m_%Y%m01_%Y%m??.nc'
elif datatype == '5min':
pathformat = remote_path + 'g' + str(
prb) + '_magpd_19mp15_5m_%Y%m01_%Y%m??.nc'
else:
channels = ['mp1', 'mp2', 'mp3', 'mp4', 'mp5']
resolution = ['16', '16', '16', '32', '32']
pathformat = []
for idx, channel in enumerate(channels):
pathformat.append(remote_path + 'g' + str(prb) +
'_magpd_19' + channel + '_' +
resolution[idx] + 's_%Y%m%d_%Y%m%d.nc')
elif instrument == 'hepad':
# high energy proton and alpha detector -- valid for GOES 08-15
if datatype == '1min':
pathformat = [
remote_path + 'g' + str(prb) +
'_hepad_ap_1m_%Y%m01_%Y%m??.nc',
'_hepad_s15_1m_%Y%m01_%Y%m??.nc'
]
elif datatype == '5min':
pathformat = [
remote_path + 'g' + str(prb) +
'_hepad_ap_5m_%Y%m01_%Y%m??.nc',
'_hepad_s15_5m_%Y%m01_%Y%m??.nc'
]
else:
pathformat = [
remote_path + 'g' + str(prb) +
'_hepad_ap_32s_%Y%m%d_%Y%m%d.nc',
'_hepad_s15_4s_%Y%m%d_%Y%m%d.nc'
]
elif instrument == 'xrs':
# x-ray sensor -- valid for GOES 08-15
if datatype == '1min':
pathformat = remote_path + 'g' + str(
prb) + '_xrs_1m_%Y%m01_%Y%m??.nc'
elif datatype == '5min':
pathformat = remote_path + 'g' + str(
prb) + '_xrs_5m_%Y%m01_%Y%m??.nc'
else:
pathformat = remote_path + 'g' + str(
prb) + '_xrs_2s_%Y%m%d_%Y%m%d.nc'
# find the full remote path names using the trange
if isinstance(pathformat, list):
remote_names = []
for path in pathformat:
remote_names.extend(dailynames(file_format=path,
trange=trange))
else:
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 mms_load_eph_tplot(filenames,
level='def',
probe='1',
datatypes=['pos', 'vel'],
suffix='',
trange=None):
"""
Helper routine for loading state data (ASCII files from the SDC); not meant to be called directly; see pyspedas.mms.state instead
"""
prefix = 'mms' + probe
time_values = []
date_values = []
x_values = []
y_values = []
z_values = []
vx_values = []
vy_values = []
vz_values = []
for file in filenames:
rows = pd.read_csv(file,
delim_whitespace=True,
header=None,
skiprows=14)
times = rows.shape[0] - 1
for time_idx in range(0, times):
# these files can overlap, so avoid duplicates
if rows[0][time_idx] in date_values:
continue
time_values.append(
pd.to_datetime(rows[0][time_idx],
format='%Y-%j/%H:%M:%S.%f').timestamp())
x_values.append(rows[2][time_idx])
y_values.append(rows[3][time_idx])
z_values.append(rows[4][time_idx])
vx_values.append(rows[5][time_idx])
vy_values.append(rows[6][time_idx])
vz_values.append(rows[7][time_idx])
date_values.append(rows[0][time_idx])
if 'pos' in datatypes:
store_data(prefix + '_' + level + 'eph_pos' + suffix,
data={
'x': time_values,
'y':
np.transpose(np.array([x_values, y_values, z_values]))
})
tclip(prefix + '_' + level + 'eph_pos' + suffix,
trange[0],
trange[1],
suffix='')
options(prefix + '_' + level + 'eph_pos' + suffix, 'ytitle',
'MMS' + str(probe) + ' position [km]')
options(prefix + '_' + level + 'eph_pos' + suffix, 'legend_names',
['X ECI', 'Y ECI', 'Z ECI'])
options(prefix + '_' + level + 'eph_pos' + suffix, 'color',
['b', 'g', 'r'])
if 'vel' in datatypes:
store_data(prefix + '_' + level + 'eph_vel' + suffix,
data={
'x':
time_values,
'y':
np.transpose(np.array([vx_values, vy_values,
vz_values]))
})
tclip(prefix + '_' + level + 'eph_vel' + suffix,
trange[0],
trange[1],
suffix='')
options(prefix + '_' + level + 'eph_vel' + suffix, 'ytitle',
'MMS' + str(probe) + ' velocity [km/s]')
options(prefix + '_' + level + 'eph_vel' + suffix, 'legend_names',
['Vx ECI', 'Vy ECI', 'Vz ECI'])
options(prefix + '_' + level + 'eph_vel' + suffix, 'color',
['b', 'g', 'r'])
def load(
trange=['2018-11-5', '2018-11-6'],
instrument='fields',
datatype='mag_rtn',
spec_types=None, # for DFB AC spectral data
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
"""
# remote path formats are going to be all lowercase
datatype = datatype.lower()
file_resolution = 24 * 3600.
if instrument == 'fields':
# 4_per_cycle and 1min are daily, not 6h like the full resolution 'mag_(rtn|sc)'
if datatype == 'mag_rtn_1min' or datatype == 'mag_sc_1min':
pathformat = instrument + '/' + level + '/' + datatype + '/%Y/psp_fld_' + level + '_' + datatype + '_%Y%m%d_v??.cdf'
elif datatype == 'mag_rtn_4_per_cycle' or datatype == 'mag_rtn_4_sa_per_cyc':
pathformat = instrument + '/' + level + '/mag_rtn_4_per_cycle/%Y/psp_fld_' + level + '_mag_rtn_4_sa_per_cyc_%Y%m%d_v??.cdf'
elif datatype == 'mag_sc_4_per_cycle' or datatype == 'mag_sc_4_sa_per_cyc':
pathformat = instrument + '/' + level + '/mag_sc_4_per_cycle/%Y/psp_fld_' + level + '_mag_sc_4_sa_per_cyc_%Y%m%d_v??.cdf'
elif datatype == 'rfs_hfr' or datatype == 'rfs_lfr' or datatype == 'rfs_burst' or datatype == 'f2_100bps':
pathformat = instrument + '/' + level + '/' + datatype + '/%Y/psp_fld_' + level + '_' + datatype + '_%Y%m%d_v??.cdf'
elif datatype == 'dfb_dc_spec' or datatype == 'dfb_ac_spec' or datatype == 'dfb_dc_xspec' or datatype == 'dfb_ac_xspec':
out_vars = []
for item in spec_types:
loaded_data = load(trange=trange,
instrument=instrument,
datatype=datatype + '_' + item,
level=level,
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 loaded_data != []:
out_vars.extend(loaded_data)
return out_vars
elif datatype[:
12] == 'dfb_dc_spec_' or datatype[:
12] == 'dfb_ac_spec_' or datatype[:
13] == 'dfb_dc_xspec_' or datatype[:
13] == 'dfb_ac_xspec_':
if datatype[:
13] == 'dfb_dc_xspec_' or datatype[:
13] == 'dfb_ac_xspec_':
dtype_tmp = datatype[:12]
stype_tmp = datatype[13:]
else:
dtype_tmp = datatype[:11]
stype_tmp = datatype[12:]
pathformat = instrument + '/' + level + '/' + dtype_tmp + '/' + stype_tmp + '/%Y/psp_fld_' + level + '_' + datatype + '_%Y%m%d_v??.cdf'
else:
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=['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=['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 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 load_csa(trange=['2001-02-01', '2001-02-03'],
probes=['C1'],
datatypes=['CP_CIS-CODIF_HS_H1_MOMENTS'],
downloadonly=False,
time_clip=True,
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
notplot=False):
"""Load data using the Cluster Science Data archive.
Parameters:
trange : list of str
Time range [start, end].
probes : list of str
List of Cluster probes.
Use ['*'] to load all. See cl_master_probes().
datatypes : list of str
List of Cluster data types.
Use ['*'] to load all. See cl_master_datatypes().
downloadonly: bool
If true, do not use cdf_to_tplot.
time_clip: bool
If true, apply time clip to data.
suffix: str (for pytplot)
The tplot variable names will be given this suffix. By default,
no suffix is added.
get_support_data: bool (for pytplot)
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 (for pytplot)
The file variable formats to load into tplot. Wildcard character
"*" is accepted. By default, all variables are loaded in.
varnames: str or list of str (for pytplot)
Load these variables only. If [] or ['*'], then load everything.
notplot: bool (for pytplot)
If True, then data are returned in a hash table instead of
being stored in tplot variables (useful for debugging, and
access to multi-dimensional data products)
Returns:
List of tplot variables created (unless notplot keyword is used).
"""
# Empty output in case of errors.
tvars = []
# Start and end dates
start_date = cl_format_time(trange[0])
end_date = cl_format_time(trange[1])
# Delivery format
delivery_format = 'CDF_ISTP'
# Delivery interval
delivery_interval = 'ALL'
# TODO: Create a function that can resolve wildcards
# similar to IDL spedas ssl_check_valid_name
# my_datatypes=ssl_check_valid_name(uc_datatypes,master_datatypes)
# my_probes=ssl_check_valid_name(uc_probes,master_probes)
if not probes: # list is empty
return tvars
elif probes[0] == '*': # load all probes
probes = cl_master_probes()
if not datatypes: # list is empty
return tvars
elif datatypes[0] == '*': # load all probes
datatypes = cl_master_datatypes()
# Construct the query string
base_url = 'https://csa.esac.esa.int/csa-sl-tap/data?'
query_string = ('retrieval_type=PRODUCT&START_DATE=' + start_date +
'&END_DATE=' + end_date +
'&DELIVERY_FORMAT=' + delivery_format +
'&DELIVERY_INTERVAL=' + delivery_interval +
'&NON_BROWSER')
for p in probes:
for d in datatypes:
query_string += '&DATASET_ID=' + p + '_' + d
# Encode the url urllib.parse.quote
url = base_url + (query_string)
local_path = CONFIG['local_data_dir']
Path(local_path).mkdir(parents=True, exist_ok=True)
out_gz = local_path + 'temp_cluster_file.tar.gz' # Temp file name
# Download the file.
print("Downloading Cluster data, please wait....")
try:
r = requests.get(url, allow_redirects=True)
r.raise_for_status()
except requests.exceptions.HTTPError as err:
print("Download HTTP error: ", err)
return tvars
except requests.exceptions.RequestException as e:
print("Download error: ", e)
return tvars
print("Download complete.")
# Open the downloaded file.
with open(out_gz, 'wb') as w:
w.write(r.content)
# Extract the tar archive.
tar = tarfile.open(out_gz, "r:gz")
f = tar.getnames()
tar.extractall(path=local_path)
tar.close()
# Remove the tar.gz file but keep the extracted.
os.remove(out_gz)
# Get unique set of files.
f_set = set(f)
# File list with full path.
out_files = [local_path+s for s in list(f_set)]
out_files = sorted(out_files)
if downloadonly:
return out_files
# Load data into tplot
try:
tvars = cdf_to_tplot(out_files,
suffix=suffix,
get_support_data=get_support_data,
varformat=varformat,
varnames=varnames,
notplot=notplot)
except IndexError as e:
print("cdf_to_tplot cannot load Cluster cdf file.")
print("File: ", out_files[0])
print("IndexError:", e)
return tvars
except TypeError as e:
print("cdf_to_tplot cannot load Cluster cdf file.")
print("File: ", out_files[0])
print("TypeError:", e)
return tvars
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,
varnames=[],
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':
if level == 'k0':
pathformat = 'dcf/' + level + '/%Y/fa_k0_dcf_%Y%m%d_v??.cdf'
else:
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 = []
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=['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=['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=['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'],
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=['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=['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 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=['2019-02-01', '2019-02-02'],
site=None,
suffix='',
get_support_data=False,
varformat=None,
varnames=[],
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 is 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,
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
