def velocity_data(start_date, end_date):
# FPI DIS
sc = 'mms1'
mode = 'srvy'
level = 'l2'
fpi_mode = 'fast'
ni_vname = '_'.join((sc, 'dis', 'numberdensity', fpi_mode))
espec_i_vname = '_'.join((sc, 'dis', 'energyspectr', 'omni', fpi_mode))
BV_vname = '_'.join((sc, 'dis', 'bulkv_gse', fpi_mode))
mms = tto.MrMMS_SDC_API(sc, 'fpi', fpi_mode, level,
optdesc='dis-moms',
start_date=start_date, end_date=end_date)
files = mms.download_files()
files = tto.sort_files(files)[0]
ni_data = ff.cdf_to_df(files,ni_vname)
# start_date, end_date)
# especi_data = tto.from_cdflib(files, espec_i_vname,
# start_date, end_date)
BV_data = ff.cdf_to_df(files, BV_vname) # tto.from_cdflib(files, BV_vname,
# start_date, end_date)
BVX_data = features(BV_data['mms1_dis_bulkv_gse_fast_0'])
BVY_data = features(BV_data['mms1_dis_bulkv_gse_fast_1'])
BVZ_data = features(BV_data['mms1_dis_bulkv_gse_fast_2'])
density = features(ni_data['mms1_dis_numberdensity_fast'])
return BVX_data, BVY_data, BVZ_data, density
def anis_temp(start_date, end_date):
sc = 'mms1'
mode = 'srvy'
level = 'l2'
fpi_mode = 'fast'
Tpara_vname = '_'.join((sc, 'des', 'temppara', 'fast'))
mms = tto.MrMMS_SDC_API(sc, 'fpi', fpi_mode, level, optdesc='des-moms', start_date=start_date,
end_date=end_date)
files = mms.download_files()
files = tto.sort_files(files)[0]
tpara = ff.cdf_to_df(files, Tpara_vname)
sc = 'mms1'
mode = 'srvy'
level = 'l2'
fpi_mode = 'fast'
Tperp_vname = '_'.join((sc, 'des', 'tempperp', 'fast'))
mms = tto.MrMMS_SDC_API(sc, 'fpi', fpi_mode, level, optdesc='des-moms', start_date=start_date,
end_date=end_date)
files = mms.download_files()
files = tto.sort_files(files)[0]
tperp = ff.cdf_to_df(files, Tperp_vname)
tanis = []
tscalar = []
tanis = features((1 - (tperp.div(tpara)))) # features
tscalar = features((tpara.add(tperp).div(3))) # features
return tanis, tscalar
def temp_perp_data(start_date, end_date):
sc = 'mms1'
mode = 'srvy'
level = 'l2'
fpi_mode = 'fast'
Tperp_vname = '_'.join((sc, 'des', 'tempperp', 'fast'))
mms = tto.MrMMS_SDC_API(sc, 'fpi', fpi_mode, level, optdesc='des-moms', start_date=start_date,
end_date=end_date)
files = mms.download_files()
files = tto.sort_files(files)[0]
Tempperp_data = ff.cdf_to_df(files, Tperp_vname) # tto.from_cdflib(files, Tperp_vname, start_date, end_date)
tperp = features(Tempperp_data['mms1_des_tempperp_fast'])
return tperp
def Pressure_data(start_date, end_date):
sc = 'mms1'
mode = 'srvy'
level = 'l2'
fpi_mode = 'fast'
Pressure_vname = '_'.join((sc, 'des', 'prestensor_gse', 'fast'))
mms = tto.MrMMS_SDC_API(sc, 'fpi', fpi_mode, level, optdesc='des-moms', start_date=start_date,
end_date=end_date)
files = mms.download_files()
files = tto.sort_files(files)[0]
Pressure_data = ff.cdf_to_df(files,
Pressure_vname) # tto.from_cdflib(files, Pressure_vname, start_date, end_date)
pscalar = features((Pressure_data['mms1_des_prestensor_gse_fast_1'] + Pressure_data[
'mms1_des_prestensor_gse_fast_2'] + Pressure_data['mms1_des_prestensor_gse_fast_3']) / 3)
return pscalar
def fgm_data(start_date, end_date):
sc = 'mms1'
mode = 'srvy'
level = 'l2'
# FGM
b_vname = '_'.join((sc, 'fgm', 'b', 'gse', mode, level))
mms = tto.MrMMS_SDC_API(sc, 'fgm', mode, level,
start_date=start_date, end_date=end_date)
files = mms.download_files()
files = tto.sort_files(files)[0]
fgm_data = ff.cdf_to_df(files, b_vname) # tto.from_cdflib(files, b_vname,
# start_date, end_date)
# fgm_data['data'] = fgm_data['data'][:, [3, 0, 1, 2]]
# fgm_data['color'] = ['Black', 'Blue', 'Green', 'Red']
# fgm_data[fgm_data['LABL_PTR_1']]['data'] = ['|B|', 'Bx', 'By', 'Bz']
fgmabs_data = features(fgm_data['mms1_fgm_b_gse_srvy_l2_0'])
fgmx_data = features(fgm_data['mms1_fgm_b_gse_srvy_l2_1'])
fgmy_data = features(fgm_data['mms1_fgm_b_gse_srvy_l2_2'])
fgmz_data = features(fgm_data['mms1_fgm_b_gse_srvy_l2_3'])
return fgmabs_data, fgmx_data, fgmy_data, fgmz_data