"""
Module for BT-NextGen atmospheric model spectra.
"""
import os
import tarfile
import warnings
import urllib.request
import spectres
import numpy as np
import pandas as pd
from species.util import data_util
[docs]def add_btnextgen(input_path,
database,
wavel_range,
teff_range,
spec_res):
"""
Function for adding the BT-NextGen 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, 'bt-nextgen/')
files = ['BT-NextGen_M-0.0_a+0.0_hot.tar',
'BT-NextGen_M+0.3_a+0.0_hot.tar',
'BT-NextGen_M+0.5_a+0.0_hot.tar']
urls = ['https://phoenix.ens-lyon.fr/Grids/BT-NextGen/SPECTRA/BT-NextGen_M-0.0_a+0.0_hot.tar',
'https://phoenix.ens-lyon.fr/Grids/BT-NextGen/SPECTRA/BT-NextGen_M+0.3_a+0.0_hot.tar',
'https://phoenix.ens-lyon.fr/Grids/BT-NextGen/SPECTRA/BT-NextGen_M+0.5_a+0.0_hot.tar']
labels = ['[Fe/H]=0.0 (5.9 GB)',
'[Fe/H]=0.3 (6.2 GB)',
'[Fe/H]=0.5 (6.4 GB)']
for i, item in enumerate(files):
data_file = os.path.join(input_path, item)
if not os.path.isfile(data_file):
print(f'Downloading BT-NextGen model spectra {labels[i]}...', end='', flush=True)
urllib.request.urlretrieve(urls[i], data_file)
print(' [DONE]')
print(f'Unpacking BT-NextGen model spectra {labels[i]}...', end='', flush=True)
tar = tarfile.open(data_file)
tar.extractall(data_folder)
tar.close()
print(' [DONE]')
teff = []
logg = []
feh = []
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.bz2'):
teff_val = float(filename[3:6])*100.
logg_val = float(filename[7:9])
feh_val = float(filename[11:14])
if teff_range is not None:
if teff_val < teff_range[0] or teff_val > teff_range[1]:
continue
print_message = f'Adding BT-NextGen model spectra... {filename}'
print(f'\r{print_message:<72}', end='')
dataf = pd.pandas.read_csv(data_folder+filename,
usecols=[0, 1],
names=['wavelength', 'flux'],
header=None,
dtype={'wavelength': str, 'flux': str},
delim_whitespace=True,
compression='bz2')
dataf['wavelength'] = dataf['wavelength'].str.replace('D', 'E')
dataf['flux'] = dataf['flux'].str.replace('D', 'E')
dataf = dataf.apply(pd.to_numeric)
data = dataf.values
# (Angstrom) -> (um)
data_wavel = data[:, 0]*1e-4
# See https://phoenix.ens-lyon.fr/Grids/FORMAT
data_flux = 10.**(data[:, 1]-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)
feh.append(feh_val)
flux.append(spectres.spectres(wavelength, data[:, 0], data[:, 1]))
try:
flux.append(spectres.spectres(wavelength, data[:, 0], data[:, 1]))
except ValueError:
flux.append(np.zeros(wavelength.shape[0]))
warnings.warn('The wavelength range should fall within the range of the '
'original wavelength sampling. Storing zeros instead.')
data_sorted = data_util.sort_data(np.asarray(teff),
np.asarray(logg),
np.asarray(feh),
None,
None,
wavelength,
np.asarray(flux))
data_util.write_data('bt-nextgen', ['teff', 'logg', 'feh'], database, data_sorted)
print_message = 'Adding BT-NextGen model spectra... [DONE]'
print(f'\r{print_message:<72}')