#Declare data for the analisis AbundancesFileExtension = '_' + catalogue_dict['Datatype'] + '_linesLog_emission.txt' cHbeta_type = 'cHbeta_reduc' #Atoms for the abundances MC_length = 500 dz.load_elements() oxygen_emision = ['O2_3726A', 'O3_4363A', 'O3_4959A', 'O3_5007A', 'O2_7330A'] nitrogen_emision = ['N2_6548A', 'N2_6584A'] sulfur_emision = ['S2_6716A', 'S3_6312A', 'S3_9069A', 'S3_9531A'] Te = random.normal(10000, 2000, size = MC_length) ne = random.normal(100, 20, size = MC_length) dz.create_pdfDoc('/home/vital/Desktop/example_line_abundances') #Loop through the objects for i in range(len(catalogue_df.index)): #Object objName = catalogue_df.iloc[i].name print 'Treating object: ', objName #Locate the files ouput_folder = '{}{}/'.format(catalogue_dict['Obj_Folder'], objName) fits_reduc = catalogue_df.iloc[i].reduction_fits fits_emission = catalogue_df.iloc[i].stellar_fits fits_stellar = ouput_folder + objName + '_StellarContinuum.fits' lineslog_address = '{objfolder}{codeName}{lineslog_extension}'.format(objfolder = ouput_folder, codeName=objName, lineslog_extension=AbundancesFileExtension)
header=0, delim_whitespace=True) linformat_df.lambda_theo = round(linformat_df.lambda_theo.values, 2) for objName in catalogue_df.loc[dz.idx_include].index: if objName in ['8', 'SHOC579']: local_reference = objName.replace('_', '-') quick_reference = catalogue_df.loc[objName].quick_index pdf_address = '/home/vital/Dropbox/Astrophysics/Thesis/images/{}_absEffect.png'.format( quick_reference) dz.create_pdfDoc(pdf_address, pdf_type='table') dz.pdf_insert_table(table_format='l' + 'ccc') group_dict = OrderedDict() # Make dict with all the objects lines dataframes ouput_folder = '{}{}/'.format(catalogue_dict['Obj_Folder'], objName) linelog_reducAddress = '{objfolder}{codeName}_WHT_linesLog_reduc.txt'.format( objfolder=ouput_folder, codeName=objName) linelog_emisAddress = '{objfolder}{codeName}_WHT_linesLog_emission_2nd.txt'.format( objfolder=ouput_folder, codeName=objName) reduc_linedf = dz.load_lineslog_frame(linelog_reducAddress) emission_linedf = dz.load_lineslog_frame(linelog_emisAddress) Hbeta_F = reduc_linedf.loc['H1_4861A'].line_Flux
#Declare data for the analisis AbundancesFileExtension = '_' + catalogue_dict[ 'Datatype'] + '_linesLog_reduc.txt' cHbeta_type = 'cHbeta_reduc' #Atoms for the abundances MC_length = 500 dz.load_elements() oxygen_emision = ['O2_3726A', 'O3_4363A', 'O3_4959A', 'O3_5007A', 'O2_7330A'] nitrogen_emision = ['N2_6548A', 'N2_6584A'] sulfur_emision = ['S2_6716A', 'S3_6312A', 'S3_9069A', 'S3_9531A'] Te = random.normal(10000, 2000, size=MC_length) ne = random.normal(100, 20, size=MC_length) dz.create_pdfDoc('/home/vital/Desktop/example_line_abundances') #Loop through the objects for i in range(len(catalogue_df.index)): #Object objName = catalogue_df.iloc[i].name print 'Treating object: ', objName #Locate the files ouput_folder = '{}{}/'.format(catalogue_dict['Obj_Folder'], objName) fits_reduc = catalogue_df.iloc[i].reduction_fits fits_emission = catalogue_df.iloc[i].stellar_fits fits_stellar = ouput_folder + objName + '_StellarContinuum.fits' lineslog_address = '{objfolder}{codeName}{lineslog_extension}'.format(