def region_indeces(wave_min, wave_max, wavenlength_range):
low_trim, up_trim = searchsorted(wavenlength_range, [wave_min, wave_max])
indeces_array = array(range(low_trim, up_trim))
return indeces_array
dz = Dazer()
script_code = dz.get_script_code()
lickIndcs_extension = "_lick_indeces.txt"
# Load catalogue dataframe
catalogue_dict = dz.import_catalogue()
catalogue_df = dz.load_dataframe(catalogue_dict["dataframe"])
SIII_theo = 2.469
H7_H8_ratio_theo = 1.98
# Set figure format
size_dict = {"figure.figsize": (16, 10), "axes.labelsize": 16, "legend.fontsize": 20}
dz.FigConf(plotStyle="seaborn-colorblind", plotSize=size_dict, Figtype="Grid_size", n_columns=1, n_rows=2)
# Sulfur lines to plot
lines_interest = ["S3_9069A", "S3_9531A", "H1_9015A", "H1_9229A", "H1_9546A"]
for i in range(len(catalogue_df.index)):
print "\n-- Treating {} @ {}".format(catalogue_df.iloc[i].name, catalogue_df.iloc[i].Red_file)
from dazer_methods import Dazer
#Create class object
dz = Dazer()
script_code = dz.get_script_code()
#Define operation
catalogue_dict = dz.import_catalogue()
#Load catalogue dataframe
catalogue_df = dz.load_dataframe(catalogue_dict['dataframe'])
#Set figure format
dz.FigConf()
#Loop through the objects
for i in range(len(catalogue_df.index)):
#Treat each arm file
for color in ['Blue', 'Red']:
if (color == 'Red') and (catalogue_df.iloc[i].tell_correction != 'None'):
fits_file = catalogue_df.iloc[i].tellRed_file
else:
fits_file = catalogue_df.iloc[i]['{}_file'.format(color)]
#Read the data
redshift = catalogue_df.iloc[i]['z_{}'.format(color)]
z_fits_file = fits_file.replace('.fits', '_z.fits')
from matplotlib import pyplot as plt
from dazer_methods import Dazer
from uncertainties import ufloat
from numpy import searchsorted, ceil as np_ceil, interp, random, nanmean, nanstd, median
from pylatex import Math, NoEscape, Section
from os.path import isfile
#Create class object
dz = Dazer()
#Load catalogue dataframe
catalogue_dict = dz.import_catalogue()
catalogue_df = dz.load_dataframe(catalogue_dict['dataframe'])
#Grid configuration
n_columns = 4.0
sizing_dict = {
'xtick.labelsize': 8,
'ytick.labelsize': 10,
'axes.titlesize': 14
}
#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']
