lineslog_address = '{objfolder}{codeName}{lineslog_extension}'.format(objfolder = ouput_folder, codeName=objName, lineslog_extension=AbundancesFileExtension) # if objName == '8': #Load lines frame lineslog_frame = dz.load_lineslog_frame(lineslog_address) #Perform the reddening correction cHbeta = catalogue_df.iloc[i][cHbeta_type] dz.deredden_lines(cHbeta, lineslog_frame) #Set astronomical object dz.DeclareObject(lineslog_frame) #Calculate electron temperature and density for the diverse elements dz.determine_electron_parameters() TSIII = '{:.5u}'.format(ufloat(nanmean(dz.abunData.TeSIII), nanstd(dz.abunData.TeSIII))) if 'TeSIII' in dz.abunData.index else 'Not measured' neSII = '{:.4u}'.format(ufloat(nanmean(dz.abunData.neSII), nanstd(dz.abunData.neSII))) if 'neSII' in dz.abunData.index else 'Not measured' TOIII = '{:f}'.format(ufloat(nanmean(dz.abunData.TeOIII), nanstd(dz.abunData.TeOIII))) if 'TeOIII' in dz.abunData.index else 'Not measured' R_SII = '{:f}'.format(ufloat(nanmean(dz.abunData.R_SII), nanstd(dz.abunData.R_SII))) if 'R_SII' in dz.abunData.index else 'Not measured' cHbeta = '{:f}'.format(cHbeta) print '{:10s} {:15s} {:15s} {:15s} {:15s} {:15s}'.format(objName, R_SII, cHbeta, neSII, TSIII, TOIII) print 'Argon abundance' dz.argon_abundance_scheme() print 'Sulfur abundance' dz.sulfur_abundance_scheme() print 'Oxygen abundance'
lineslog_frame = dz.load_lineslog_frame(lineslog_address) #Perform the reddening correction reddening_law = redding_laws[i] cHbeta = catalogue_df.loc[objName, 'cHbeta_{}'.format(reddening_law)] dz.deredden_lines(lineslog_frame, reddening_curve=redding_laws[i], cHbeta=cHbeta, R_v=R_v) #Set astronomical object dz.declare_object(lineslog_frame) #Calculate electron temperature and density for the diverse elements print '-Electron properties' dz.determine_electron_parameters(catalogue_df.loc[objName]) #Load electron parameter from object characteristic ne = dz.abunData.neSII if 'neSII' in dz.abunData else dz.generate_nan_array( ) Tlow_key = catalogue_df.loc[objName, 'T_low'] Thigh_key = catalogue_df.loc[objName, 'T_high'] T_low = dz.abunData[ Tlow_key] if Tlow_key in dz.abunData else dz.generate_nan_array() T_high = dz.abunData[ Thigh_key] if Thigh_key in dz.abunData else dz.generate_nan_array( ) #Argon dz.argon_abundance_scheme(T_low, T_high, ne)
param_dict, MC_size=dz.MC_array_len, lines_dict=dz.lines_dict, error=0.05) generate_lines_dict('He2', param_dict['Te_high'], param_dict['ne_true'], param_dict, MC_size=dz.MC_array_len, lines_dict=dz.lines_dict, error=0.05) dz.abunData, Data_TestObject = Series(), Series() Data_TestObject['SIII_lines'] = 'BOTH' dz.determine_electron_parameters(Data_TestObject) dz.argon_abundance_scheme(dz.abunData['TeOIII'], dz.abunData['TeSIII'], dz.abunData['neSII']) dz.sulfur_abundance_scheme(dz.abunData['TeSIII'], dz.abunData['neSII'], SIII_lines_to_use=Data_TestObject.SIII_lines) dz.oxygen_abundance_scheme(dz.abunData['TeOIII'], dz.abunData['TeSIII'], dz.abunData['neSII']) dz.nitrogen_abundance_scheme(dz.abunData['TeOIII'], dz.abunData['neSII']) for parameter in dz.abunData.index: mean_value, std_value = mean(dz.abunData[parameter]), std( dz.abunData[parameter]) scientfici_not = True if (mean_value < 1e-4) or ( mean_value > 1e-5) else False