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import os
import tarfile
import numpy as np
from . import get_data_home
from .tools import download_with_progress_bar
DATA_URL = ("https://github.com/astroML/astroML-data/raw/master/datasets/"
"RRLyr_ugriz_templates.tar.gz")
def fetch_rrlyrae_templates(data_home=None, download_if_missing=True):
"""Loader for RR-Lyrae template data
These are the light-curve templates from Sesar et al 2010, ApJ 708:717
Parameters
----------
data_home : optional, default=None
Specify another download and cache folder for the datasets. By default
all scikit learn data is stored in '~/astroML_data' subfolders.
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 : numpy record array
record array containing the templates
"""
data_home = get_data_home(data_home)
data_file = os.path.join(data_home, os.path.basename(DATA_URL))
if not os.path.exists(data_file):
if not download_if_missing:
raise IOError('data not present on disk. '
'set download_if_missing=True to download')
databuffer = download_with_progress_bar(DATA_URL)
open(data_file, 'wb').write(databuffer)
data = tarfile.open(data_file)
return dict([(name.strip('.dat'),
np.loadtxt(data.extractfile(name)))
for name in data.getnames()])
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