import os
import numpy as np
from urllib.request import urlopen
from astroML.datasets import get_data_home
# Info on vega spectrum: http://www.stsci.edu/hst/observatory/cdbs/calspec.html
VEGA_URL = ('https://github.com/astroML/astroML-data/raw/main/datasets/'
'1732526_nic_002.ascii')
FILTER_URL = 'http://classic.sdss.org/dr7/instruments/imager/filters/%s.dat'
[docs]def fetch_sdss_filter(fname, data_home=None, download_if_missing=True):
"""Loader for SDSS Filter profiles
Parameters
----------
fname : str
filter name: must be one of 'ugriz'
data_home : optional, default=None
Specify another download and cache folder for the datasets. By default
all data is stored in '~/astroML_data'.
download_if_missing : optional, default=True
If False, raise a IOError if the data is not locally available
instead of trying to download the data from the source site.
Returns
-------
data : ndarray
data is an array of shape (5, Nlam)
first row: wavelength in angstroms
second row: sensitivity to point source, airmass 1.3
third row: sensitivity to extended source, airmass 1.3
fourth row: sensitivity to extended source, airmass 0.0
fifth row: assumed atmospheric extinction, airmass 1.0
"""
if fname not in 'ugriz':
raise ValueError("Unrecognized filter name '%s'" % fname)
url = FILTER_URL % fname
data_home = get_data_home(data_home)
archive_file = os.path.join(data_home, '%s.dat' % fname)
if not os.path.exists(archive_file):
if not download_if_missing:
raise IOError('data not present on disk. '
'set download_if_missing=True to download')
print("downloading from %s" % url)
F = urlopen(url)
open(archive_file, 'wb').write(F.read())
F = open(archive_file)
return np.loadtxt(F, unpack=True)
[docs]def fetch_vega_spectrum(data_home=None, download_if_missing=True):
"""Loader for Vega reference spectrum
Parameters
----------
fname : str
filter name: must be one of 'ugriz'
data_home : optional, default=None
Specify another download and cache folder for the datasets. By default
all astroML data is stored in '~/astroML_data'.
download_if_missing : optional, default=True
If False, raise a IOError if the data is not locally available
instead of trying to download the data from the source site.
Returns
-------
data : ndarray
data[0] is the array of wavelength in angstroms
data[1] is the array of fluxes in Jy (F_nu, not F_lambda)
"""
data_home = get_data_home(data_home)
archive_name = os.path.join(data_home, VEGA_URL.split('/')[-1])
if not os.path.exists(archive_name):
if not download_if_missing:
raise IOError('data not present on disk. '
'set download_if_missing=True to download')
print("downnloading from %s" % VEGA_URL)
F = urlopen(VEGA_URL)
open(archive_name, 'wb').write(F.read())
F = open(archive_name, 'r')
return np.loadtxt(F, unpack=True)