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"