def test_save(filepath):
hdu = fits.open(filepath)
cube = hdu[0].data
hdu.close()
params_ami = {
"peakmethod": 'fft',
"bs_multi_tri": False,
"maskname": "g7",
"fw_splodge": 0.7,
}
bs = amical.extract_bs(cube,
filepath,
targetname='test',
**params_ami,
display=False)
cal = amical.calibrate(bs, bs)
assert isinstance(cal, munch.Munch)
dic, savefile = amical.save(cal, oifits_file='test.oifits', fake_obj=True)
v2 = dic['OI_VIS2']['VIS2DATA']
cp = dic['OI_T3']['T3PHI']
assert isinstance(dic, dict)
assert isinstance(savefile, str)
assert (isinstance(v2, np.ndarray))
assert (isinstance(cp, np.ndarray))
assert (len(v2) == 21)
assert (len(cp) == 35)
def example_cal_fft(global_datadir):
fits_file = global_datadir / "test.fits"
with fits.open(fits_file) as fh:
cube = fh[0].data
bs = amical.extract_bs(
cube,
fits_file,
targetname="test",
bs_multi_tri=False,
maskname="g7",
fw_splodge=0.7,
display=False,
peakmethod="fft",
)
return amical.calibrate(bs, bs)
def test_cal_phscorr(global_datadir):
fits_file = global_datadir / "test.fits"
with fits.open(fits_file) as fh:
cube = fh[0].data
bs = amical.extract_bs(
cube,
fits_file,
targetname="test",
bs_multi_tri=False,
maskname="g7",
fw_splodge=0.7,
display=False,
peakmethod="fft",
)
cal = amical.calibrate(bs, bs, apply_atmcorr=True)
assert isinstance(cal, munch.Munch)
def test_save(bss, tmpdir):
bs = bss["fft"]
cal = amical.calibrate(bs, bs)
assert isinstance(cal, munch.Munch)
dic, savefile = amical.save(cal, oifits_file='test.oifits',
datadir=tmpdir, fake_obj=True)
v2 = dic['OI_VIS2']['VIS2DATA']
cp = dic['OI_T3']['T3PHI']
assert isinstance(dic, dict)
assert isinstance(savefile, str)
assert(isinstance(v2, np.ndarray))
assert(isinstance(cp, np.ndarray))
assert(len(v2) == 21)
assert(len(cp) == 35)
def test_show(filepath):
hdu = fits.open(filepath)
cube = hdu[0].data
hdu.close()
params_ami = {
"peakmethod": 'fft',
"bs_multi_tri": False,
"maskname": "g7",
"fw_splodge": 0.7,
}
bs = amical.extract_bs(cube,
filepath,
targetname='test',
**params_ami,
display=False)
cal = amical.calibrate(bs, bs)
amical.show(cal)
def perform_calibrate(args):
"""Calibrate the data with AMICAL (save calibrated oifits files)"""
sciname, calname = _select_association_file(args)
bs_t = amical.load_bs_hdf5(sciname)
bs_c = []
for x in calname:
bs_c = amical.load_bs_hdf5(x)
display = len(bs_c) > 1
cal = amical.calibrate(
bs_t,
bs_c,
clip=args.clip,
normalize_err_indep=args.norm,
apply_atmcorr=args.atmcorr,
apply_phscorr=args.phscorr,
display=display,
)
# Position angle from North to East
pa = bs_t.infos.pa
cprint("\nPosition angle computed for the data: pa = %2.3f deg" % pa,
"cyan")
# Display and save the results as oifits
if args.plot:
amical.show(cal, true_flag_t3=False, cmax=180, pa=pa)
plt.show()
oifits_file = Path(bs_t.infos.filename).stem + "_calibrated.fits"
amical.save(cal, oifits_file=oifits_file, datadir=args.outdir)
return 0
"bs_multi_tri": False,
"maskname": "g7",
"fw_splodge": 0.7,
}
# Extract raw complex observables for the target and the calibrator:
# It's the core of the pipeline (amical/mf_pipeline/bispect.py)
bs_t = amical.extract_bs(cube_t,
file_t,
targetname="fakebinary",
**params_ami,
display=True)
bs_c = amical.extract_bs(cube_c,
file_c,
targetname="fakepsf",
**params_ami,
display=False)
# Calibrate the raw data to get calibrated V2 and CP.
# bs_c can be a single calibrator result or a list of calibrators.
# (see amical/calibration.py for details).
cal = amical.calibrate(bs_t, bs_c)
# Display and save the results as oifits
amical.show(cal)
dic = amical.save(cal,
oifits_file="example_fakebinary_NIRISS.oifits",
fake_obj=True)
plt.show(block=True)
def test_show(bss):
bs = bss["fft"]
cal = amical.calibrate(bs, bs)
amical.show(cal)
def test_calibration(bss):
bs = bss["fft"]
cal = amical.calibrate(bs, bs)
assert isinstance(cal, munch.Munch)