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