def fgm_survey(probe, starttime, endtime):
"""
Import fgm survey mode magnetic field data.
Parameters
----------
probe : string
Probe number, must be 1, 2, 3, or 4
starttime : datetime
Interval start time.
endtime : datetime
Interval end time.
Returns
-------
data : DataFrame
Imported data.
"""
# Directory relative to main MMS data directory
relative_dir = os.path.join('mms' + probe, 'fgm', 'srvy', 'l2')
daylist = util._daysplitinterval(starttime, endtime)
data = []
for day in daylist:
date = day[0]
this_relative_dir = os.path.join(relative_dir, str(date.year),
str(date.month).zfill(2))
filename = 'mms{}_fgm_srvy_l2_{}{:02}{:02}_v4.18.0.cdf'.format(
probe, date.year, date.month, date.day)
# Absolute path to local directory for this data file
local_dir = os.path.join(mms_dir, this_relative_dir)
util._checkdir(local_dir)
remote_url = remote_mms_dir + this_relative_dir
# Load cdf file
cdf = util.load(filename, local_dir, remote_url)
# Convert cdf to dataframe
keys = {
'mms' + probe + '_fgm_b_gsm_srvy_l2': ['Bx', 'By', 'Bz', 'Br'],
'Epoch': 'Time'
}
df = util.cdf2df(cdf, 'Epoch', keys)
data.append(df)
return util.timefilter(data, starttime, endtime)
def threedp_sfpd(starttime, endtime):
"""
Import 'sfpd' wind data.
12 second energetic electron pitch-angle energy spectra from the foil SST
Parameters
----------
starttime : datetime
Interval start time.
endtime : datetime
Interval end time.
Returns
-------
data : DataFrame
"""
# Directory relative to main WIND data directory
relative_dir = path.Path('3dp') / '3dp_sfpd'
daylist = util._daysplitinterval(starttime, endtime)
data = []
mag = []
for (date, _, _) in daylist:
this_relative_dir = relative_dir / str(date.year)
# Absolute path to local directory for this data file
local_dir = wind_dir / this_relative_dir
filename = 'wi_sfpd_3dp_{:{dfmt}}_v02'.format(date, dfmt='%Y%m%d')
hdfname = filename + '.hdf'
hdfloc = local_dir / hdfname
if hdfloc.exists():
df = pd.read_hdf(hdfloc)
data.append(df)
continue
util._checkdir(local_dir)
remote_url = remote_wind_dir + str(this_relative_dir)
cdf = util.load(filename + '.cdf',
local_dir,
remote_url,
guessversion=True)
if cdf is None:
print('File {}/{} not available\n'.format(remote_url, filename))
continue
data_today = []
# Loop through each timestamp to build up fluxes
for i, time in enumerate(cdf['Epoch'][...]):
energies = cdf['ENERGY'][i, :]
angles = cdf['PANGLE'][i, :]
fluxes = cdf['FLUX'][i, :, :]
magfield = cdf['MAGF'][i, :]
index = pd.MultiIndex.from_product(
([time], energies, angles),
names=['Time', 'Energy', 'Pitch angle'])
df = pd.DataFrame(fluxes.ravel(), index=index, columns=['Flux'])
df['Bx'] = magfield[0]
df['By'] = magfield[1]
df['Bz'] = magfield[2]
data_today.append(df)
data_today = pd.concat(data_today)
data_today = data_today.sort_index()
if use_hdf:
data_today.to_hdf(hdfloc, 'sfpd', mode='w')
data.append(data_today)
data = util.timefilter(data, starttime, endtime)
data = data.reset_index(level=['Energy', 'Pitch angle'])
return data
def threedp_pm(starttime, endtime):
"""
Import 'pm' wind data.
3 second time resolution solar wind proton and alpha particle moments from
the PESA LOW sensor, computed on-board the spacecraft
Parameters
----------
starttime : datetime
Interval start time.
endtime : datetime
Interval end time.
Returns
-------
data : DataFrame
"""
# Directory relative to main WIND data directory
relative_dir = path.Path('3dp') / '3dp_pm'
daylist = util._daysplitinterval(starttime, endtime)
data = []
for day in daylist:
date = day[0]
this_relative_dir = relative_dir / str(day[0].year)
# Absolute path to local directory for this data file
local_dir = wind_dir / this_relative_dir
filename = 'wi_pm_3dp_' +\
str(date.year) +\
str(date.month).zfill(2) +\
str(date.day).zfill(2) +\
'_v05.cdf'
hdfname = filename[:-4] + 'hdf'
hdfloc = local_dir / hdfname
if hdfloc.exists():
df = pd.read_hdf(hdfloc)
data.append(df)
continue
util._checkdir(local_dir)
remote_url = remote_wind_dir + str(this_relative_dir)
cdf = util.load(filename, local_dir, remote_url, guessversion=True)
if cdf is None:
print('File {}/{} not available\n'.format(remote_url, filename))
continue
keys = {
'A_DENS': 'n_a',
'A_TEMP': 'T_a',
'A_VELS': ['va_x', 'va_y', 'va_z'],
'P_DENS': 'n_p',
'P_TEMP': 'T_p',
'P_VELS': ['vp_x', 'vp_y', 'vp_z'],
'Epoch': 'Time'
}
df = util.cdf2df(cdf, index_key='Epoch', keys=keys)
if use_hdf:
df.to_hdf(hdfloc, 'pm', mode='w')
data.append(df)
return util.timefilter(data, starttime, endtime)
def _download(probe, starttime, endtime, instrument, product_id):
if cda_cookie == 'none':
raise RuntimeError('Cluster download cookie not set')
daylist = util._daysplitinterval(starttime, endtime)
for day in daylist:
date = day[0]
start = datetime.combine(date, time.min)
end = datetime.combine(date, time.max)
# Add start and end time to request dictionary
request_dict = generic_dict
request_dict['START_DATE'] = start.strftime(cda_time_fmt)
request_dict['END_DATE'] = end.strftime(cda_time_fmt)
# Create request string
request_str = ''
request_str += 'DATASET_ID' + '='
request_str += 'C' + probe + '_' + product_id
for item in request_dict:
request_str += '&'
request_str += item
request_str += '='
request_str += request_dict[item]
# Create request url
request_str += '&NON_BROWSER'
request_url = csa_url + request_str
# Work out local directory to download to
year = str(starttime.year)
month = str(starttime.month).zfill(2)
day = str(starttime.day).zfill(2)
local_dir = cluster_dir / ('c' + probe) / instrument / year
local_fname = 'C' + probe + '_' + product_id + '__' +\
year + month + day + '.cdf'
local_file = local_dir / local_fname
print(request_url)
# Download data
util._checkdir(local_dir)
urlreq.urlretrieve(request_url,
filename=local_file,
reporthook=util._reporthook)
print('\n')
# Extract tar.gz file
tar = tarfile.open(local_file)
tar.extractall(local_dir)
# Delete tar.gz file
os.remove(local_file)
# The CSA timpstamps the downloaded file by when it is downloaded,
# so manually list and retrieve the folder name
dirlist = os.listdir(local_dir)
for d in dirlist:
if d[:13] == 'CSA_Download_':
download_dir = local_dir / d / ('C' + probe + '_' + product_id)
break
# Remove request times from filename
dirlist = os.listdir(download_dir)
# Move to data folder
cutoff = 3 + len(product_id) + 10
for f in dirlist:
os.rename(download_dir / f, local_dir / (f[:cutoff] + '.cdf'))
# Delte extra folders created by tar.gz file
os.rmdir(download_dir)
os.rmdir(os.path.join(local_dir, d))
def mag_rtn(starttime, endtime):
"""
Import magnetic field in RTN coordinates from Messenger.
Parameters
----------
starttime : datetime
Interval start time.
endtime : datetime
Interval end time.
Returns
-------
data : DataFrame
"""
# Directory relative to main WIND data directory
relative_dir = 'rtn'
daylist = util._daysplitinterval(starttime, endtime)
data = []
for day in daylist:
date = day[0]
this_relative_dir = os.path.join(relative_dir, str(date.year))
hdffile = 'messenger_mag_rtn_' +\
str(date.year) +\
str(date.month).zfill(2) +\
str(date.day).zfill(2) +\
'_v01.hdf'
hdfloc = os.path.join(mess_dir, this_relative_dir, hdffile)
# Try to load hdf file
if os.path.isfile(hdfloc):
df = pd.read_hdf(hdfloc)
data.append(df)
continue
filename = hdffile[:-4] + '.cdf'
# Absolute path to local directory for this data file
local_dir = os.path.join(mess_dir, this_relative_dir)
util._checkdir(local_dir)
remote_url = os.path.join(remote_mess_dir, this_relative_dir)
cdf = util.load(filename, local_dir, remote_url, guessversion=True)
if cdf is None:
print('File {}/{} not available\n'.format(remote_url, filename))
continue
keys = {
'B_normal': 'Bn',
'B_radial': 'Br',
'B_tangential': 'Bt',
'Epoch': 'Time',
'azimuth_ecliptic': 'sc_Az',
'latitude_ecliptic': 'sc_Lat',
'radialDistance': 'sc_r',
'MissionElapsedTime': 'mission_time'
}
df = util.cdf2df(cdf, index_key='Epoch', keys=keys)
if use_hdf:
hdffile = filename[:-4] + '.hdf'
df.to_hdf(hdfloc, key='data', mode='w')
data.append(df)
return util.timefilter(data, starttime, endtime)
def fpi_dis_moms(probe, mode, starttime, endtime):
"""
Import fpi ion distribution moment data.
Parameters
----------
probe : string
Probe number, must be 1, 2, 3, or 4
mode : string
Data mode, must be 'fast' or 'brst'
starttime : datetime
Interval start time.
endtime : datetime
Interval end time.
Returns
-------
data : DataFrame
Imported data.
"""
valid_modes = ['fast', 'brst']
if mode not in valid_modes:
raise RuntimeError('Mode must be either fast or brst')
# Directory relative to main MMS data directory
relative_dir = os.path.join('mms' + probe, 'fpi', mode, 'l2', 'dis-moms')
daylist = util._daysplitinterval(starttime, endtime)
data = []
for day in daylist:
date = day[0]
starthour = day[1].hour
endhour = day[2].hour + 1
# fips fast data product has files every two hours, so get nearest two
# hour stamps
starthour -= np.mod(starthour, 2)
endhour += np.mod(endhour, 2)
for h in range(starthour, endhour, 2):
this_relative_dir = os.path.join(relative_dir,
str(date.year),
str(date.month).zfill(2))
filename = ('mms{}_fpi_{}_l2_dis-moms_'
'{}{:02}{:02}{:02}0000_v3.3.0.cdf').format(
probe, mode, date.year, date.month, date.day, h)
# Absolute path to local directory for this data file
local_dir = os.path.join(mms_dir, this_relative_dir)
util._checkdir(local_dir)
remote_url = remote_mms_dir + this_relative_dir
# Load cdf file
try:
cdf = util.load(filename, local_dir, remote_url)
except urllib.error.HTTPError as e:
if str(e) == 'HTTP Error 404: Not Found':
print('No data available for hours', str(h) + '-' +
str(h + 2), 'on', date.strftime('%d/%m/%Y'))
continue
else:
raise
probestr = 'mms' + probe + '_'
# Convert cdf to dataframe
keys = {'Epoch': 'Time',
probestr + 'dis_bulkv_gse_fast': ['bulkv_x',
'bulkv_y',
'bulkv_z'],
probestr + 'dis_heatq_gse_fast': ['heatq_x',
'heatq_y',
'heatq_z'],
probestr + 'dis_numberdensity_fast': 'n',
probestr + 'dis_temppara_fast': 'T_par',
probestr + 'dis_tempperp_fast': 'T_perp'}
df = util.cdf2df(cdf, 'Epoch', keys)
data.append(df)
return util.timefilter(data, starttime, endtime)
def fgm(probe, rate, coords, starttime, endtime):
"""
Import fgm magnetic field data from THEMIS.
Parameters
----------
probe : string
Alowed values are [a, b, c, d, e].
rate : string
Date rate to return. Allowed values are [e, h, l, s].
coords : string
Magnetic field co-ordinate system. Allowed values are
[dsl, gse, gsm, ssl]. NOTE: Add link to co-ordinate system
descriptions.
starttime : datetime
Interval start time.
endtime : datetime
Interval end time.
Returns
-------
data : DataFrame
"""
valid_rates = ['e', 'h', 'l', 's']
valid_coords = ['dsl', 'gse', 'gsm', 'ssl']
_validate_probe(probe)
if rate not in valid_rates:
raise ValueError(('rate argument %s is not in list of allowed'
'rates: %s') % (rate, valid_rates))
if coords not in valid_coords:
raise ValueError(('coords argument %s is not in list of allowed'
'co-ordinate systems: %s') % (rate, valid_rates))
# Directory relative to main THEMIS data directory
relative_dir = os.path.join('th' + probe, 'l2', 'fgm')
daylist = util._daysplitinterval(starttime, endtime)
data = []
for day in daylist:
date = day[0]
this_relative_dir = os.path.join(relative_dir, str(date.year))
filename = 'th' + probe + '_l2_fgm_' +\
str(date.year) +\
str(date.month).zfill(2) +\
str(date.day).zfill(2) +\
'_v01.cdf'
# Absolute path to local directory for this data file
local_dir = os.path.join(themis_dir, this_relative_dir)
util._checkdir(local_dir)
remote_url = remote_themis_dir + this_relative_dir
cdf = util.load(filename, local_dir, remote_url)
if cdf is None:
print('File {}/{} not available\n'.format(remote_url, filename))
continue
probestr = 'th' + probe
ratestr = '_fg' + rate + '_'
keys = {
probestr + ratestr + 'btotal':
'|B|',
probestr + ratestr + coords:
['Bx_' + coords, 'By_' + coords, 'Bz_' + coords],
probestr + ratestr + 'time':
'Time'
}
df = util.cdf2df(cdf,
probestr + ratestr + 'time',
keys,
dtimeindex=False)
df = df.set_index(pd.to_datetime(df.index.values, unit='s'))
df['Time'] = df.index.values
data.append(df)
data = pd.concat(data)
data = data[(data['Time'] > starttime) & (data['Time'] < endtime)]
return data
