dz.data_plot(Input_Wavelength, Output_Flux, 'Stellar fit')
dz.data_plot(ClippedPixels[0],
ClippedPixels[1],
'Clipped pixels',
color=dz.colorVector['green'],
markerstyle='o')
dz.data_plot(FlagPixels[0],
FlagPixels[1],
'Flagged pixels',
color=dz.colorVector['pink'],
markerstyle='o')
#Check flagged pixels
dz.area_fill(InitialPoints,
FinalPoints,
'Masks',
color=dz.colorVector['orangish'],
alpha=0.2)
# Set titles and legend
PlotTitle = r'Object ' + objName + ' spectrum with masked and flagged pixels'
dz.FigWording(r'Wavelength $(\AA)$',
'Flux' + r'$(erg\,cm^{-2} s^{-1} \AA^{-1})$', PlotTitle)
dz.Axis.set_aspect(3)
dz.display_fig()
# # Save data
# output_pickle = '{objFolder}{stepCode}_{objCode}_{ext}'.format(objFolder=ouput_folder, stepCode=dz.ScriptCode, objCode=objName, ext='Sl_MasksFlags')
# dz.save_manager(output_pickle, save_pickle = True)
#-----------------------------------------------------------------------------------------------------
IntEmi_dered = dz.derreddening_spectrum(Wave_E,
Int_E,
reddening_curve=red_curve,
cHbeta=cHbeta.nominal_value,
R_v=R_v)
Int_Sum = IntEmi_dered + Int_Stellar_Resampled + Int_N
dz.data_plot(Wave_O, IntObs_dered, 'Observed spectrum')
dz.data_plot(Wave_N, Int_N, 'Nebular continuum', linestyle='-')
dz.data_plot(Wave_S, Int_S, 'Stellar continuum', linestyle='-')
# dz.insert_image('/home/vital/Dropbox/Astrophysics/Papers/Yp_AlternativeMethods/images/SHOC579_invert.png', Image_Coordinates = [0.07,0.875], Zoom=0.25, Image_xyCoords = 'axes fraction')
dz.area_fill(metals_regions - 10,
metals_regions + 10,
'Collisional excitation lines',
color=dz.colorVector['olive'],
alpha=0.5)
dz.area_fill(recombination_regions - 10,
recombination_regions + 10,
'Recombination lines',
color=dz.colorVector['pink'],
alpha=0.5)
#Set titles and legend
PlotTitle = ''
dz.FigWording(r'Wavelength $(\AA)$',
'Flux' + r'$(erg\,cm^{-2} s^{-1} \AA^{-1})$',
PlotTitle,
loc='upper right',
ncols_leg=2)
for i in range(len(FilesList)):
#Analyze file address
CodeName, FileName, FileFolder = dz.Analyze_Address(FilesList[i])
#Import fits file
Wave, Int, ExtraData = dz.File_to_data(FileFolder,FileName)
#Getting the masks as a two lists with initial and final points #WARNING the masks generated do not distinguish the absorptions
MaskFileName = CodeName + '_Mask.lineslog'
InitialPoints, FinalPoints = loadtxt(FileFolder + MaskFileName, usecols=(0,1) ,skiprows=1,unpack=True) #Change by new method
#Plot the data
dz.data_plot(Wave, Int, "Input spectrum", dz.ColorVector[2][1])
dz.area_fill(InitialPoints, FinalPoints, 'Masks', dz.ColorVector[2][0], 0.2)
# Set titles and legend
PlotTitle = r'Object ' + CodeName + ' spectrum with masked and flagged pixels'
dz.FigWording(r'Wavelength $(\AA)$', 'Flux' + r'$(erg\,cm^{-2} s^{-1} \AA^{-1})$', PlotTitle)
# Save data
dz.save_manager(FileFolder + dz.ScriptCode + '_' + CodeName + '_Sl_MasksFlags')
print i+1, '/' , len(FilesList)
#-----------------------------------------------------------------------------------------------------
print "All data treated"
