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import pyfits as pf
import numpy  as np
import pandas as pd
import os
import matplotlib.pyplot as plt


    

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%matplotlib notebook


    

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spec_path = './../../GAMAII_SPEC/WHAN_NA_UVUP/'
spec_list = './../../GAMAII_SPEC/filelist_whan.csv'
cxt_path  = './../../STARLIGHT/OUTPUTS/'


    

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specs = np.loadtxt(spec_list, delimiter=',', dtype=str)


    

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example = pf.getdata(os.path.join(spec_path, specs[3]))
stuff   = pf.open(os.path.join(spec_path, specs[3]))
stuff[0].header

flux    = example[0,:]
flux_e  = example[1,:]
flux_nc = example[2,:]
fnc_e   = example[3,:]

wl_i    = stuff[0].header['WMIN']
wl_step = stuff[0].header['CD1_1']
wl_temp = np.arange(flux.size)*wl_step+wl_i   # wavelength

data = np.column_stack([flux, flux_e, wl_temp])
datadf = pd.DataFrame(data).dropna()
dataf = datadf.values


    

In [25]:

    

plt.subplots(figsize=(10,3))
# plt.plot(wl_temp, flux, '-', label='spectrum')
plt.errorbar(wl_temp, flux, yerr=flux_e, ecolor='pink', alpha=0.5)
plt.xlim([wl_temp.min()-100, wl_temp.max()-100])
plt.show()


    

In [26]:

    

header = ['wavelength', 'flux', 'flux_err']
for spec in specs:
    fit_file      = pf.open(os.path.join(spec_path, spec)) 
    flux_temp     = pf.getdata(os.path.join(spec_path, spec))[0,:]
    flux_err_temp = pf.getdata(os.path.join(spec_path, spec))[1,:]
    cataid        = fit_file[0].header['CATAID']
    wl_i          = fit_file[0].header['WMIN']
    wl_step       = fit_file[0].header['CD1_1']
    wl_temp       = np.arange(flux_temp.size)*wl_step+wl_i   # wavelength
    flag_temp     = np.zeros((flux_temp).shape)
    data_temp     = np.column_stack([wl_temp, flux_temp, flux_err_temp, flag_temp])
    data_df       = pd.DataFrame(data_temp).dropna()
    data          = data_df.values
    basename      = str(cataid)+'.cxt'    
    np.savetxt(os.path.join(cxt_path, basename), data, fmt=('%6.f', '%11.7f', '%11.8f', '%1d'))


    

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