"""
Module for AMES-Dusty atmospheric model spectra.
"""
import os
import gzip
import tarfile
import warnings
import urllib.request
import spectres
import numpy as np
from species.util import data_util
[docs]def add_ames_dusty(input_path,
database,
wavel_range,
teff_range,
spec_res):
"""
Function for adding the AMES-Dusty atmospheric models to the database.
Parameters
----------
input_path : str
Folder where the data is located.
database : h5py._hl.files.File
Database.
wavel_range : tuple(float, float)
Wavelength range (um).
teff_range : tuple(float, float), None
Effective temperature range (K).
spec_res : float
Spectral resolution.
Returns
-------
NoneType
None
"""
if not os.path.exists(input_path):
os.makedirs(input_path)
data_folder = os.path.join(input_path, 'ames-dusty/')
if not os.path.exists(data_folder):
os.makedirs(data_folder)
input_file = 'SPECTRA.tar'
label = '[Fe/H]=0.0 (106 MB)'
url = 'https://phoenix.ens-lyon.fr/Grids/AMES-Dusty/SPECTRA.tar'
data_file = os.path.join(data_folder, input_file)
if not os.path.isfile(data_file):
print(f'Downloading AMES-Dusty model spectra {label}...', end='', flush=True)
urllib.request.urlretrieve(url, data_file)
print(' [DONE]')
print(f'Unpacking AMES-Dusty model spectra {label}...', end='', flush=True)
tar = tarfile.open(data_file)
tar.extractall(data_folder)
tar.close()
print(' [DONE]')
data_folder += 'SPECTRA/'
teff = []
logg = []
flux = []
wavelength = [wavel_range[0]]
while wavelength[-1] <= wavel_range[1]:
wavelength.append(wavelength[-1] + wavelength[-1]/(2.*spec_res))
wavelength = np.asarray(wavelength[:-1])
for _, _, file_list in os.walk(data_folder):
for filename in sorted(file_list):
if filename.startswith('lte') and filename.endswith('.7.gz'):
teff_val = float(filename[3:5])*100.
logg_val = float(filename[6:9])
feh_val = float(filename[10:13])
if feh_val != 0.:
continue
if teff_range is not None:
if teff_val < teff_range[0] or teff_val > teff_range[1]:
continue
print_message = f'Adding AMES-Dusty model spectra... {filename}'
print(f'\r{print_message:<75}', end='')
data_wavel = []
data_flux = []
with gzip.open(data_folder+filename, 'rt') as gz_file:
for line in gz_file:
line_split = line.split()
if len(line_split) > 1:
tmp_wavel = line_split[0].strip()
tmp_flux = line_split[1].strip()
if len(tmp_wavel) == 21 and tmp_wavel[-4] == 'D' \
and tmp_flux[-4] == 'D':
data_wavel.append(float(line[1:23].replace('D', 'E')))
data_flux.append(float(line[25:35].replace('D', 'E')))
elif len(tmp_wavel) == 21 and tmp_wavel[-4] == 'E' \
and tmp_flux[-4] == 'E':
data_wavel.append(float(line[1:23]))
data_flux.append(float(line[25:35]))
# See https://phoenix.ens-lyon.fr/Grids/FORMAT
data_wavel = np.asarray(data_wavel)*1e-4 # (Angstrom) -> (um)
data_flux = 10.**(np.asarray(data_flux)-8.) # (erg s-1 cm-2 Angstrom-1)
# (erg s-1 cm-2 Angstrom-1) -> (W m-2 um-1)
data_flux = data_flux*1e-7*1e4*1e4
data = np.stack((data_wavel, data_flux), axis=1)
index_sort = np.argsort(data[:, 0])
data = data[index_sort, :]
if np.all(np.diff(data[:, 0]) < 0):
raise ValueError('The wavelengths are not all sorted by increasing value.')
teff.append(teff_val)
logg.append(logg_val)
try:
flux.append(spectres.spectres(wavelength,
data[:, 0],
data[:, 1],
fill=0.,
verbose=False))
except (ValueError, IndexError):
flux.append(np.zeros(wavelength.shape[0]))
warnings.warn(f'The wavelength range ({wavelength[0]:.2f}-{wavelength[-1]:.2f}'
f' um) should fall within the range of the original '
f'wavelength sampling ({data[0, 0]:.2f}-{data[-1, 0]:.2f} '
f'um). Storing zeros for the flux of Teff={teff_val} '
f'and log(g)={logg_val}, which will be corrected by the '
f'\'write_data\' function afterwards.')
data_sorted = data_util.sort_data(np.asarray(teff),
np.asarray(logg),
None,
None,
None,
wavelength,
np.asarray(flux))
data_util.write_data('ames-dusty', ['teff', 'logg'], database, data_sorted)
print_message = 'Adding AMES-Dusty model spectra... [DONE]'
print(f'\r{print_message:<75}')