#Create class object
dz = Dazer()
script_code = dz.get_script_code()
#Load catalogue dataframe
catalogue_dict = dz.import_catalogue()
catalogue_df = dz.load_excel_DF(
'/home/vital/Dropbox/Astrophysics/Data/WHT_observations/WHT_Galaxies_properties.xlsx'
)
lineslog_extension = '_' + catalogue_dict[
'Datatype'] + '_linesLog_emission.txt' #First data log for reduced spectra
lickIndcs_extension = '_lick_indeces.txt'
# Forcing the remake of new files
dz.RemakeFiles = True
n_objects = len(catalogue_df.index)
#Loop through the objects
for objName in catalogue_df.index:
#Object
objName = catalogue_df.loc[objName].name
fits_file = catalogue_df.loc[objName].emission_fits
ouput_folder = '{}{}/'.format(catalogue_dict['Obj_Folder'], objName)
#Output lines log dataframe
lineslog_df = pd.DataFrame(columns=dz.saving_parameters_list)
lines_log_address = ouput_folder + objName + lineslog_extension
import pandas as pd
from dazer_methods import Dazer
from numpy import isnan
#Create class object
dz = Dazer()
script_code = dz.get_script_code()
#Load catalogue dataframe
catalogue_dict = dz.import_catalogue()
catalogue_df = dz.load_dataframe(catalogue_dict['dataframe'])
lineslog_extension = '_' + catalogue_dict['Datatype'] + '_linesLog_emission.txt'#First data log for reduced spectra
lickIndcs_extension = '_lick_indeces.txt'
# Forcing the remake of new files
dz.RemakeFiles = True
n_objects = len(catalogue_df.index)
#Loop through the objects
for i in range(n_objects):
#Object
objName = catalogue_df.iloc[i].name
fits_file = catalogue_df.iloc[i].stellar_fits
ouput_folder = '{}{}/'.format(catalogue_dict['Obj_Folder'], objName)
if isinstance(fits_file, str):
#Output lines log dataframe
lineslog_df = pd.DataFrame(columns=dz.saving_parameters_list)
