Source code for species.data.spec_data.spec_kesseli2017
"""
Module for adding O5 through L3 SDSS stellar spectra from
Kesseli et al. (2017) to the database.
"""
import os
import shutil
import urllib.request
import h5py
import numpy as np
from astropy.io import fits
from typeguard import typechecked
from species.util.data_util import extract_tarfile
[docs]
@typechecked
def add_kesseli2017(input_path: str, database: h5py._hl.files.File) -> None:
"""
Function for adding the SDSS stellar spectra from
Kesseli et al. (2017) to the database.
Parameters
----------
input_path : str
Path of the data folder.
database : h5py._hl.files.File
The HDF5 database.
Returns
-------
NoneType
None
"""
data_url = "https://cdsarc.unistra.fr/viz-bin/nph-Cat/tar.gz?J/ApJS/230/16"
data_file = os.path.join(input_path, "J_ApJS_230_16.tar.gz")
data_folder = os.path.join(input_path, "kesseli+2017/")
if not os.path.isfile(data_file):
print(
"Downloading SDSS spectra from Kesseli et al. 2017 (145 MB)...",
end="",
flush=True,
)
urllib.request.urlretrieve(data_url, data_file)
print(" [DONE]")
if os.path.exists(data_folder):
shutil.rmtree(data_folder)
print(
"Unpacking SDSS spectra from Kesseli et al. 2017 (145 MB)...",
end="",
flush=True,
)
extract_tarfile(data_file, data_folder)
print(" [DONE]")
database.create_group("spectra/kesseli+2017")
fits_folder = os.path.join(data_folder, "fits")
print_message = ""
for _, _, files in os.walk(fits_folder):
for _, filename in enumerate(files):
with fits.open(os.path.join(fits_folder, filename)) as hdu_list:
data = hdu_list[1].data
wavelength = 1e-4 * 10.0 ** data["LogLam"] # (um)
flux = data["Flux"] # Normalized units
error = data["PropErr"] # Normalized units
name = filename[:-5].replace("_", " ")
file_split = filename.split("_")
file_split = file_split[0].split(".")
sptype = file_split[0]
spdata = np.column_stack([wavelength, flux, error])
empty_message = len(print_message) * " "
print(f"\r{empty_message}", end="")
print_message = f"Adding spectra... {name}"
print(f"\r{print_message}", end="")
dset = database.create_dataset(
f"spectra/kesseli+2017/{name}", data=spdata
)
dset.attrs["name"] = str(name).encode()
dset.attrs["sptype"] = str(sptype).encode()
empty_message = len(print_message) * " "
print(f"\r{empty_message}", end="")
print_message = "Adding spectra... [DONE]"
print(f"\r{print_message}")