def test_only_one_file(instrument, mode, files, extension):
files = [files["bias"][0]]
bias, bhead = combine_bias(files, instrument, mode, extension=extension, window=50)
assert isinstance(bias, np.ma.masked_array)
assert isinstance(bhead, fits.Header)
assert bias.ndim == bhead["NAXIS"]
assert bias.shape[0] == bhead["NAXIS1"] - 100 # remove window from both sides
assert bias.shape[1] == bhead["NAXIS2"]
def test_only_one_file(instrument, mode, files, mask):
if len(files["bias"]) == 0:
pytest.skip(f"No bias files for instrument {instrument}")
files = [files["bias"][0]]
bias, bhead = combine_bias(files, instrument, mode, window=50, mask=mask)
assert isinstance(bias, np.ma.masked_array)
assert isinstance(bhead, fits.Header)
assert bias.ndim == 2
assert bias.shape[0] == mask.shape[0]
assert bias.shape[1] == mask.shape[1]
def test_simple_input(tempfiles):
n = 2
files = tempfiles[:n]
for i in range(n):
data = np.full((100, 100), i, dtype=float)
fits.writeto(files[i], data)
bias, bhead = combine_bias(files, "common", "", extension=0)
assert isinstance(bias, np.ndarray)
assert bias.shape[0] == 100
assert bias.shape[1] == 100
assert np.all(bias == sum(range(n)) / n)
def bias(instrument, mode, files, extension, mask, output_dir):
"""Load or if necessary create the bias calibration
Parameters
----------
instrument : str
instrument name
mode : str
observing mode
files : dict(str:str)
calibration files
extension : int
fits extension
mask : array(bool)
Bad pixel mask
output_dir : str
directory conatining the bias data
Returns
-------
bias : array(float)
bias calibration data
bhead : fits.header
bias information
"""
biasfile = os.path.join(output_dir, "test_bias.fits")
try:
bias = fits.open(biasfile)
bhead, bias = bias[0].header, bias[0].data
bias = np.ma.masked_array(bias, mask=mask)
except FileNotFoundError:
bias, bhead = combine_bias(files["bias"],
instrument,
mode,
extension=extension,
window=50,
mask=mask)
fits.writeto(biasfile, data=bias.data, header=bhead, overwrite=True)
return bias, bhead
def test_wrong_data_type():
with pytest.raises(TypeError):
combine_bias(None, None, "")
with pytest.raises(ValueError):
combine_bias([None], None, "")
def test_no_data_files():
with pytest.raises(FileNotFoundError):
combine_bias([], "", "")
