def test_simple(tempfiles):
n = 2
files = tempfiles[:n]
for i in range(n):
data = np.full((100, 100), 5, dtype=float)
fits.writeto(files[i], data)
flat, fhead = combine_flat(files, "common", "", extension=0)
assert isinstance(flat, np.ndarray)
assert flat.shape[0] == 100
assert flat.shape[1] == 100
assert np.all(flat == 5 * n)
n = 6
files = tempfiles[:n]
for i in range(n):
data = np.full((200, 100), 5, dtype=float)
fits.writeto(files[i], data, overwrite=True)
flat, fhead = combine_flat(files, "common", "", extension=0, window=50)
assert isinstance(flat, np.ndarray)
assert flat.shape[0] == 200
assert flat.shape[1] == 100
assert np.all(flat == 5 * n)
def test_flat(instrument, mode, files, mask):
if len(files["flat"]) == 0:
pytest.skip(f"No flat files for instrument {instrument}")
flat, fhead = combine_flat(files["flat"],
instrument,
mode,
window=50,
mask=mask)
assert isinstance(flat, np.ma.masked_array)
assert isinstance(fhead, fits.Header)
assert flat.ndim == 2
assert flat.shape[0] > 1
assert flat.shape[1] > 1
def flat(instrument, mode, files, extension, mask, bias, output_dir):
"""Load or if necessary create the flat field calibration data
Parameters
----------
instrument : str
instrument name
mode : str
observing mode
files : dict(str:str)
calibration file names
extension : int
fits data extension
mask : array(bool)
Bad pixel mask
bias : array(float)
bias calibration data
output_dir : str
output directory
Returns
-------
flat : array(float)
flat field calibration data
fhead : fits.header
flat information
"""
flatfile = os.path.join(output_dir, "test_flat.fits")
try:
flat = fits.open(flatfile)
fhead, flat = flat[0].header, flat[0].data
flat = np.ma.masked_array(flat, mask=mask)
except FileNotFoundError:
bias, _ = bias
flat, fhead = combine_flat(
files["flat"],
instrument,
mode,
extension=extension,
bias=bias,
window=50,
mask=mask,
)
fits.writeto(flatfile, data=flat.data, header=fhead, overwrite=True)
return flat, fhead
def test_flat(instrument, mode, files, extension, mask):
flat, fhead = combine_flat(
files["flat"],
instrument,
mode,
extension=extension,
bias=0,
window=50,
mask=mask,
)
assert isinstance(flat, np.ma.masked_array)
assert isinstance(fhead, fits.Header)
assert flat.ndim == fhead["NAXIS"]
assert flat.shape[0] == fhead["NAXIS1"] - 100 # remove window from both sides
assert flat.shape[1] == fhead["NAXIS2"]
base_dir=base_dir,
input_dir=input_dir,
output_dir=output_dir,
configuration=config,
# order_range=(0, 25),
)
files = data[0]["files"]
mask = data[0]["mask"]
bias, bhead = data[0]["bias"]
orders, column_range = data[0]["orders"]
wave, coef, linelist = data[0]["wavecal"]
xwd = config["wavecal"]["extraction_width"]
nrow, ncol = bias.shape
nord = len(orders)
xwd, column_range, orders = fix_parameters(xwd, column_range, orders, nrow,
ncol, nord)
orig, _ = combine_flat(
files["wavecal_master"],
instrument,
mode,
extension,
mask=mask,
bias=bias,
bhead=bhead,
)
ref = make_reference_spectrum(linelist, nrow, ncol, nord)
plot_comparison(orig, orders, ref, None, xwd, column_range)