def Preprocessing4(path):
files = []
for filename in glob.glob(path):
files.append(filename)
#spectrum's S/N >= 15
Better_files = []
for input_file in files:
spec = ls.rdspec(input_file)
if spec.snr[0] >= 15:
Better_files.append(input_file)
#read and normalize spectrum
samples = []
for input_file in Better_files:
spec = ls.rdspec(input_file)
flux = np.array(spec.flux)
wavelength = np.array(spec.wave)
flux_norm, flux_cont = norm.normalize_spectrum(wavelength, flux,
(3500., 9500.), 100.)
num_end = 0
num_head = 0
for i in range(len(wavelength)):
if wavelength[i] <= 9500:
num_end += 1
if wavelength[i] <= 3500:
num_head += 1
data_spec = [wavelength[num_head:num_end], flux_norm[num_head:num_end]]
samples.append(data_spec)
return samples
def Preprocessing3(path):
files = []
for filename in glob.glob(path):
files.append(filename)
#spectrum's S/N >= 15
Better_files = []
for input_file in files:
spec = ls.rdspec(input_file)
if spec.snr[0] >= 15:
Better_files.append(input_file)
#read and normalize spectrum
samples = []
for input_file in Better_files:
hdu_list = fits.open(input_file, memmap=True)
data = Table(hdu_list[1].data)
flux = np.array(data['flux'])
wavelength = np.array(10**data['loglam'])
flux_norm, flux_cont = norm.normalize_spectrum(wavelength, flux,
(3500., 9500.), 100.)
num_end = 0
num_head = 0
for i in range(len(wavelength)):
if wavelength[i] <= 9500:
num_end += 1
if wavelength[i] <= 3500:
num_head += 1
data_spec = [wavelength[num_head:num_end], flux_norm[num_head:num_end]]
samples.append(data_spec)
return samples
def Preprocessing6(path):
files = []
for filename in glob.glob(path):
files.append(filename)
samples = []
for input_file in files:
spec = ls.rdspec(input_file)
flux = np.array(spec.flux)
wavelength = np.array(spec.wave)
flux_norm, flux_cont = norm.normalize_spectrum(wavelength, flux,
(3500., 9500.), 100.)
# num_end = 0
# num_head = 0
# for i in range(len(wavelength)):
# if wavelength[i] <= 9500:
# num_end += 1
# if wavelength[i] <= 3500:
# num_head += 1
data_spec = [wavelength, flux_norm]
samples.append(data_spec)
return samples