def test_clean(global_datadir):
fits_file = global_datadir / "test.fits"
clean_param = {
"isz": 79,
"r1": 35,
"dr": 2,
"apod": True,
"window": 65,
"f_kernel": 3,
"add_bad": [[39, 39]],
}
cube_clean = amical.select_clean_data(fits_file, clip=True, **clean_param)
amical.show_clean_params(fits_file, **clean_param)
amical.show_clean_params(fits_file, **clean_param, remove_bad=False)
im1 = amical.data_processing._apply_patch_ghost(
cube_clean, 40, 40, radius=20, dx=3, dy=3, method="zero"
)
im2 = amical.data_processing._apply_patch_ghost(
cube_clean, 40, 40, radius=20, dx=3, dy=3, method="bg"
)
assert type(cube_clean) == np.ndarray
assert im1.shape == cube_clean.shape
assert im2.shape == cube_clean.shape
file_c = os.path.join(datadir, 'HD142695_IRD_SCIENCE_DBI_LEFT_CUBE.fits')
# ----------------------------------
# Cleaning step
# ----------------------------------
clean_param = {'isz': 149,
'r1': 70,
'dr': 2,
'apod': True,
'window': 65,
'f_kernel': 3
}
amical.check_data_params(file_t, **clean_param)
cube_t = amical.select_clean_data(file_t, clip=True,
**clean_param, display=True)
cube_c = amical.select_clean_data(file_c, clip=True,
**clean_param, display=True)
# AMI parameters (refer to the docstrings of `extract_bs` for details)
params_ami = {"peakmethod": 'fft',
"bs_multi_tri": False,
"maskname": "g7",
"fw_splodge": 0.7,
"filtname": 'K1'
}
# # Extract raw complex observables for the target and the calibrator:
# # It's the core of the pipeline (amical/mf_pipeline/bispect.py)
def perform_clean(args):
"""Clean the data with AMICAL."""
cprint("---- AMICAL clean process ----", "cyan")
clean_param = {
"isz": args.isz,
"r1": args.r1,
"dr": args.dr,
"apod": args.apod,
"window": args.window,
"f_kernel": args.kernel,
}
if not os.path.exists(args.datadir):
print(
"%s directory not found, check --datadir. AMICAL look for data only in this specified directory."
% args.datadir)
return 1
l_file = sorted(glob("%s/*.fits" % args.datadir))
if len(l_file) == 0:
print("No fits files found in %s, check --datadir." % args.datadir)
return 1
if not args.all:
filename, hdr = _select_data_file(args, process="clean")
if args.check:
amical.show_clean_params(filename, **clean_param)
plt.show(block=True)
return 0
if not os.path.exists(args.outdir):
os.mkdir(args.outdir)
clean_param["clip"] = args.clip
clean_param["sky"] = args.sky
if args.all:
# Clean all files in --datadir
for f in tqdm(l_file, ncols=100, desc="# files"):
hdr = fits.open(f)[0].header
hdr["HIERARCH AMICAL step"] = "CLEANED"
cube = amical.select_clean_data(f, **clean_param, display=True)
f_clean = os.path.join(args.outdir, Path(f).stem + "_cleaned.fits")
fits.writeto(f_clean, cube, header=hdr, overwrite=True)
else:
# Or clean just the specified file (in --datadir)
hdr["HIERARCH AMICAL step"] = "CLEANED"
now = datetime.now()
dt_string = now.strftime("%d/%m/%Y %H:%M:%S")
hdr["HIERARCH AMICAL time"] = dt_string
for k in clean_param:
hdr["HIERARCH AMICAL params %s" % k] = clean_param[k]
cube = amical.select_clean_data(filename, **clean_param, display=True)
if args.plot:
plt.show()
f_clean = os.path.join(args.outdir,
Path(filename).stem + "_cleaned.fits")
fits.writeto(f_clean, cube, header=hdr, overwrite=True)
return 0