"""
Module for downloading filter data from the website
of the SVO Filter Profile Service.
"""
import os
import urllib.request
import warnings
from typing import Optional, Tuple
import h5py
import numpy as np
from astropy.io.votable import parse_single_table
from typeguard import typechecked
[docs]
@typechecked
def download_filter(
filter_id: str,
input_path: str,
) -> Tuple[Optional[np.ndarray], Optional[np.ndarray], Optional[str]]:
"""
Function for downloading filter profile data
from the SVO Filter Profile Service.
Parameters
----------
filter_id : str
Filter name as listed on the website of the `SVO
Filter Profile Service
<http://svo2.cab.inta-csic.es/svo/theory/fps/>`_.
input_path : str
Folder where the data is located.
Returns
-------
np.ndarray
Wavelength (um).
np.ndarray
Fractional transmission.
str
Detector type ('energy' or 'photon').
"""
if filter_id == "Magellan/VisAO.rp":
url = "https://xwcl.science/magao/visao/VisAO_rp_filter_curve.dat"
filter_path = os.path.join(input_path, "VisAO_rp_filter_curve.dat")
urllib.request.urlretrieve(url, filter_path)
wavelength, transmission, _, _ = np.loadtxt(filter_path, unpack=True)
det_type = "photon"
os.remove(filter_path)
elif filter_id == "Magellan/VisAO.ip":
url = "https://xwcl.science/magao/visao/VisAO_ip_filter_curve.dat"
filter_path = os.path.join(input_path, "VisAO_ip_filter_curve.dat")
urllib.request.urlretrieve(url, filter_path)
wavelength, transmission, _, _ = np.loadtxt(filter_path, unpack=True)
det_type = "photon"
os.remove(filter_path)
elif filter_id == "Magellan/VisAO.zp":
url = "https://xwcl.science/magao/visao/VisAO_zp_filter_curve.dat"
filter_path = os.path.join(input_path, "VisAO_zp_filter_curve.dat")
urllib.request.urlretrieve(url, filter_path)
wavelength, transmission, _, _ = np.loadtxt(filter_path, unpack=True)
det_type = "photon"
os.remove(filter_path)
elif filter_id == "Keck/NIRC2.NB_4.05":
# The filter profile of Br_alpha has been digitized from
# https://www2.keck.hawaii.edu/inst/nirc2/filters.html
url = "https://home.strw.leidenuniv.nl/~stolker/species/Keck_NIRC2.NB_4.05.dat"
filter_path = os.path.join(input_path, "Keck_NIRC2.NB_4.05.dat")
urllib.request.urlretrieve(url, filter_path)
wavelength, transmission = np.loadtxt(filter_path, unpack=True)
det_type = "photon"
os.remove(filter_path)
elif filter_id == "Keck/NIRC.Y":
# The filter profile of the Y band has been
# adopted from Hillenbrand et al. (2002)
url = "https://home.strw.leidenuniv.nl/~stolker/species/Keck_NIRC.Y.dat"
filter_path = os.path.join(input_path, "Keck_NIRC.Y.dat")
urllib.request.urlretrieve(url, filter_path)
wavelength, transmission = np.loadtxt(filter_path, unpack=True)
det_type = "photon"
os.remove(filter_path)
elif filter_id in ["LCO/VisAO.Ys", "Magellan/VisAO.Ys"]:
url = "https://xwcl.science/magao/visao/VisAO_Ys_filter_curve.dat"
filter_path = os.path.join(input_path, "VisAO_Ys_filter_curve.dat")
urllib.request.urlretrieve(url, filter_path)
wavelength, transmission, _, _ = np.loadtxt(filter_path, unpack=True)
# Remove wavelengths with zero transmission
wavelength = wavelength[:-7]
transmission = transmission[:-7]
det_type = "photon"
os.remove(filter_path)
elif filter_id == "ALMA/band6":
url = "https://home.strw.leidenuniv.nl/~stolker/species/alma_band6.dat"
filter_path = os.path.join(input_path, "alma_band6.dat")
urllib.request.urlretrieve(url, filter_path)
wavelength, transmission = np.loadtxt(filter_path, unpack=True)
det_type = "photon"
os.remove(filter_path)
elif filter_id == "ALMA/band7":
url = "https://home.strw.leidenuniv.nl/~stolker/species/alma_band7.dat"
filter_path = os.path.join(input_path, "alma_band7.dat")
urllib.request.urlretrieve(url, filter_path)
wavelength, transmission = np.loadtxt(filter_path, unpack=True)
det_type = "photon"
os.remove(filter_path)
else:
url = "http://svo2.cab.inta-csic.es/svo/theory/fps/fps.php?ID=" + filter_id
filter_path = os.path.join(input_path, "filter.xml")
urllib.request.urlretrieve(url, filter_path)
try:
table = parse_single_table(filter_path)
wavelength = table.array["Wavelength"]
transmission = table.array["Transmission"]
except IndexError:
wavelength = None
transmission = None
det_type = None
warnings.warn(
f"Filter '{filter_id}' is not available "
"on the SVO Filter Profile Service."
)
except:
os.remove(filter_path)
raise ValueError(
f"The filter data of '{filter_id}' could not "
"be downloaded. Perhaps the website of the "
"SVO Filter Profile Service (http://svo2.cab."
"inta-csic.es/svo/theory/fps/) is not available?"
)
if transmission is not None:
det_type = table.get_field_by_id("DetectorType").value
# For backward compatibility
if not isinstance(det_type, str):
det_type = det_type.decode("utf-8")
if int(det_type) == 0:
det_type = "energy"
elif int(det_type) == 1:
det_type = "photon"
else:
det_type = "photon"
warnings.warn(
f"Detector type, '{det_type}', not "
"recognized. Setting detector "
"type to photon-counting detector."
)
wavelength *= 1e-4 # (um)
os.remove(filter_path)
if wavelength is not None:
indices = []
for i in range(transmission.size):
if i == 0 and transmission[i] == 0.0 and transmission[i + 1] == 0.0:
indices.append(i)
elif (
i == transmission.size - 1
and transmission[i - 1] == 0.0
and transmission[i] == 0.0
):
indices.append(i)
elif (
transmission[i - 1] == 0.0
and transmission[i] == 0.0
and transmission[i + 1] == 0.0
):
indices.append(i)
wavelength = np.delete(wavelength, indices)
transmission = np.delete(transmission, indices)
if np.amin(transmission) < 0.0:
warnings.warn(
f"The minimum transmission value of {filter_id} is "
f"smaller than zero ({np.amin(transmission):.2e}). "
f"Wavelengths with negative transmission "
f"values will be removed."
)
indices = []
for i, item in enumerate(transmission):
if item > 0.0:
indices.append(i)
wavelength = wavelength[indices]
transmission = transmission[indices]
return wavelength, transmission, det_type
[docs]
@typechecked
def add_filter_profile(
input_path: str, database: h5py._hl.files.File, filter_name: str
) -> None:
"""
Function for downloading and adding a filter profile
to the HDF5 database.
Parameters
----------
input_path : str
Folder where the data is located.
database : h5py._hl.files.File
Database.
filter_name : str
Filter name from the SVO Filter Profile Service (e.g.,
'Paranal/NACO.Lp') or a user-defined name if a ``filename``
is specified.
Returns
-------
None
NoneType
"""
wavelength, transmission, detector_type = download_filter(filter_name, input_path)
if wavelength is not None and transmission is not None:
wavel_new = [wavelength[0]]
transm_new = [transmission[0]]
for i in range(wavelength.size - 1):
if wavelength[i + 1] > wavel_new[-1]:
# Required for the issue with the Keck/NIRC2.J filter on SVO
wavel_new.append(wavelength[i + 1])
transm_new.append(transmission[i + 1])
dset = database.create_dataset(
f"filters/{filter_name}", data=np.column_stack((wavel_new, transm_new))
)
dset.attrs["det_type"] = str(detector_type)
