lm.fit_dict.zerolev_mean,
flux[lm.fit_dict.idx0:lm.fit_dict.idx1],
facecolor=dz.colorVector['green'],
step='mid',
alpha=0.5)
dz.Axis.fill_between(wave[lm.fit_dict.idx2:lm.fit_dict.idx3],
lm.fit_dict.zerolev_mean,
flux[lm.fit_dict.idx2:lm.fit_dict.idx3],
facecolor=dz.colorVector['dark blue'],
step='mid',
alpha=0.5)
dz.Axis.fill_between(wave[lm.fit_dict.idx4:lm.fit_dict.idx5],
lm.fit_dict.zerolev_mean,
flux[lm.fit_dict.idx4:lm.fit_dict.idx5],
facecolor=dz.colorVector['green'],
step='mid',
alpha=0.5)
dz.Axis.plot(lm.fit_dict.x_resample, lm.fit_dict.y_resample, linestyle='--')
dz.Axis.plot(lm.fit_dict.x_resample,
lm.fit_dict.zerolev_resample,
linestyle='--')
dz.Axis.scatter(lm.Current_TheoLoc, lm.fit_dict.zerolev_mean)
dz.FigWording(r'Wavelength $(\AA)$',
'Flux' + r'$(erg\,cm^{-2} s^{-1} \AA^{-1})$',
r'Object {} emission line: {}'.format(objName, line),
loc='upper right')
dz.display_fig()
print 'DOne'
#Analyze file address
CodeName, FileName, FileFolder = dz.Analyze_Address(FilesList[i])
#Import fits file
fits_file = pf.open(FilesList[i])
Wave = fits_file[1].data['WAVELENGTH']
Int = fits_file[1].data['FLUX']
fits_file.close()
dz.data_plot(Wave, Int, label=FileName.replace('_', ''))
dz.FigWording(r'Wavelength $(\AA)$', 'Flux' + r'$(erg\,cm^{-2} s^{-1} \AA^{-1})$', 'Calspec library')
dz.Axis.set_yscale('log')
dz.Axis.set_xlim(7000, 10000)
dz.display_fig()
# /home/vital/Dropbox/Astrophysics/Telescope Time/Standard_Stars/Calspec_Spectra/bd_17d4708_stisnic_006.fits
# file_address = '/home/vital/Dropbox/Astrophysics/Telescope Time/Standard_Stars/Calspec_Spectra/bd_17d4708_stisnic_006.fits'
#
# fits_file = pf.open(file_address)
# print fits_file[1].data['WAVELENGTH']
# print fits_file[1].data['FLUX']
#
# fits_file.close()
# #Recover objects list
# Table_Address = '/home/vital/Dropbox/Astrophysics/Telescope Time/Standard_Stars/Calspec_list.csv'
# Candiates_frame = pd.read_csv(Table_Address, delimiter = '; ', header = 0, index_col = 0)
#Plot the results
dzp.FigConf()
dzp.data_plot(dz.sspFit_dict['obs_wave'],
dz.sspFit_dict['obs_flux'],
label='obs_flux')
dzp.data_plot(dz.sspFit_dict['obs_wave'],
dz.sspFit_dict['zero_mask'],
label='my mask')
# dzp.data_plot(dz.fit_conf['obs_wave'], mis_cosas[1], label='Hector mask')
# dzp.data_plot(dz.fit_conf['obs_wave'], mis_cosas[2], label='Hector fit')
dzp.data_plot(dz.sspFit_dict['obs_wave'],
fit_products['flux_sspFit'],
label='my fit')
dzp.FigWording('Wave', 'Flux', 'Input spectra')
dzp.display_fig()
# #Plot input spectra and regions
# dzp.FigConf()
# dzp.data_plot(dz.fit_conf['obs_wave'], dz.fit_conf['obs_flux'], label='obs_flux')
# dzp.data_plot(dz.fit_conf['obs_wave'], dz.fit_conf['obs_flux_mask'], label='obs_flux_mask')
# # dzp.data_plot(dz.fit_conf['obs_wave'], dz.fit_conf['Av_mask'], label='Av mask')
# # dzp.data_plot(dz.fit_conf['obs_wave'], dz.fit_conf['obs_flux_err'], label='obs_flux_err')
# # dz.data_plot(wave_unc, flux_unc_input, label='flux_unc_input')
# # dz.data_plot(wave_unc, e_flux_unc, label='e_flux_unc')
# # dz.data_plot(wave_unc, color_unc, label='color_unc')
# # dz.data_plot(wave_unc, masked, label='masked')
# # dz.data_plot(wave_unc, masked2, label='masked2')
# # dz.data_plot(wave_unc, masked_Av, label='masked_Av')
# # dz.data_plot(wave_unc, flux_masked, label='flux_masked')
# # dz.data_plot(wave_unc, flux_masked2, label='flux_masked2')
