def test_lris_red_multi():
file_list = glob.glob(
os.path.join(os.environ['PYPEIT_DEV'], 'RAW_DATA', 'keck_lris_red',
'multi*', '*.fits*'))
cfg_lines = ['[rdx]', 'spectrograph = keck_lris_red']
ps = PypeItSetup(file_list, cfg_lines=cfg_lines)
ps.build_fitstbl()
ps.get_frame_types(flag_unknown=True)
cfgs = ps.fitstbl.unique_configurations(ignore_frames=['bias', 'dark'])
ps.fitstbl.set_configurations(cfgs, ignore_frames=['bias', 'dark'])
ps.fitstbl.set_calibration_groups(global_frames=['bias', 'dark'])
def test_lris_red_multi_400():
file_list = glob.glob(
os.path.join(os.environ['PYPEIT_DEV'], 'RAW_DATA', 'keck_lris_red',
'multi_400_8500_d560', '*.fits.gz'))
cfg_lines = ['[rdx]', 'spectrograph = keck_lris_red']
ps = PypeItSetup(file_list, cfg_lines=cfg_lines)
ps.build_fitstbl()
ps.get_frame_types(flag_unknown=True)
cfgs = ps.fitstbl.unique_configurations()
ps.fitstbl.set_configurations(cfgs)
ps.fitstbl.set_calibration_groups() #global_frames=['bias', 'dark'])
# Test
assert np.all(ps.fitstbl['setup'] == 'A')
def test_lris_red_multi_calib():
file_list = glob.glob(
os.path.join(os.environ['PYPEIT_DEV'], 'RAW_DATA', 'keck_lris_red',
'multi_400_8500_d560', '*.fits.gz'))
cfg_lines = ['[rdx]', 'spectrograph = keck_lris_red']
ps = PypeItSetup(file_list, cfg_lines=cfg_lines)
ps.build_fitstbl()
ps.get_frame_types(flag_unknown=True)
cfgs = ps.fitstbl.unique_configurations()
ps.fitstbl.set_configurations(cfgs)
ps.fitstbl.set_calibration_groups() #global_frames=['bias', 'dark'])
cfile = data_path('test.calib')
ps.fitstbl.write_calib(cfile)
with open(cfile, 'r') as f:
calib = yaml.load(f, Loader=yaml.FullLoader)
assert np.array_equal(list(calib['A'].keys()), ['--', 1]), \
'Calibrations dictionary read incorrectly.'
os.remove(cfile)
def main(args: argparse.Namespace):
t = time.perf_counter()
# need an arc frame and a flat frame
root = args.fname.rstrip('0123456789.fits')
paths = glob.glob(f'{root}*.fits')
spectrograph = 'p200_dbsp_red' if 'red' in os.path.basename(
args.fname) else 'p200_dbsp_blue'
arm = spectrograph.split('_')[-1]
CFG_LINES = get_cfg_lines(spectrograph)
flatimg = ""
arcimg = ""
sciimg = args.fname
calib_only = not os.path.isfile(sciimg)
if calib_only:
for path in paths:
with fits.open(path) as hdul:
if not flatimg:
if hdul[0].header['OBJECT'] == 'flat' or hdul[0].header[
'IMGTYPE'] == 'flat':
flatimg = path
if not arcimg:
if hdul[0].header['OBJECT'] == 'arcs' or hdul[0].header[
'IMGTYPE'] == 'cal':
arcimg = path
if flatimg and arcimg:
break
if not (flatimg and arcimg):
raise Exception(
f"Could not find a flat and an arc frame in the same directory as {root}!"
)
files = [arcimg, flatimg]
else:
files = [sciimg]
ps = PypeItSetup(files,
path="./",
spectrograph_name=spectrograph,
cfg_lines=CFG_LINES)
ps.build_fitstbl()
bm = framematch.FrameTypeBitMask()
file_bits = np.zeros(len(files), dtype=bm.minimum_dtype())
if calib_only:
file_bits[0] = bm.turn_on(file_bits[0], ['arc', 'tilt'])
file_bits[1] = bm.turn_on(file_bits[1],
['pixelflat', 'trace', 'illumflat'])
else:
file_bits[0] = bm.turn_on(file_bits[0], 'science')
asrt = np.array([
ps.fitstbl['filename'].data.tolist().index(os.path.basename(fname))
for fname in files
])
ps.fitstbl.set_frame_types(file_bits[asrt])
ps.fitstbl.set_combination_groups()
ps.fitstbl['setup'] = 'A'
ofiles = ps.fitstbl.write_pypeit(configs='A', cfg_lines=CFG_LINES)
pypeIt = pypeit.PypeIt(ofiles[0],
verbosity=0,
reuse_masters=True,
overwrite=True,
logname='dbsp_ql.log',
show=False,
calib_only=calib_only)
if calib_only:
pypeIt.calib_all()
else:
pypeIt.reduce_all()
pypeIt.build_qa()
output_spec2ds = list(filter(lambda f: os.path.isfile(os.path.join('Science', f)), [
pypeIt.spec_output_file(i, True) \
for i in range(len(pypeIt.fitstbl.table)) \
if pypeIt.fitstbl.table[i]['frametype'] in ['science']
]))
output_spec1ds = list(filter(lambda f: os.path.isfile(os.path.join('Science', f)), [
pypeIt.spec_output_file(i) \
for i in range(len(pypeIt.fitstbl.table)) \
if pypeIt.fitstbl.table[i]['frametype'] in ['science']
]))
if output_spec1ds and not calib_only:
sensfiles = [
resource_filename("dbsp_drp", f"data/sens_{arm}_archived.fits")
]
FxCalib = fluxcalibrate.FluxCalibrate.get_instance(
output_spec1ds, sensfiles, par=ps.par['fluxcalib'])
print(f"Time elapsed: {time.perf_counter() - t}s.")
if not calib_only and not args.no_show:
p1 = Process(target=show_spec2d_helper, args=(output_spec2ds[0], ))
p1.start()
if output_spec1ds:
with fits.open(output_spec1ds[0]) as hdul:
specs = len(hdul) - 2
parr = [None] * specs
for i in range(specs):
parr[i] = Process(target=show_spec1d_helper,
args=(str(i), output_spec1ds[0]))
parr[i].start()
