def fitstbl():
if os.getenv('PYPEIT_DEV') is None:
fitstbl = dummy_fitstbl(directory=data_path(''))
fitstbl['filename'][1] = 'b1.fits.gz'
fitstbl['filename'][5] = 'b27.fits.gz'
return fitstbl
fitstbl = dummy_fitstbl(directory=os.path.join(os.getenv(
'PYPEIT_DEV'), 'RAW_DATA', 'shane_kast_blue', '600_4310_d55'))
fitstbl['filename'][1] = 'b1.fits.gz'
for ii in range(2, 5):
fitstbl['filename'][ii] = 'b{0}.fits.gz'.format(ii)
fitstbl['filename'][5] = 'b27.fits.gz'
return fitstbl
def test_gen_sensfunc():
kastb = load_spectrograph('shane_kast_blue')
# Load a random spectrum for the sensitivity function
sfile = data_path('spec1d_r153-J0025-0312_KASTr_2015Jan23T025323.850.fits')
specobjs = load.load_specobjs(sfile)
# telescope = telescopes.ShaneTelescopePar()
fitstbl = dummy_fitstbl()
RA = '05:06:36.6'
DEC = '52:52:01.0'
# Get the sensitivity function
sens_dict = flux.generate_sensfunc(specobjs[0][0].boxcar['WAVE'],
specobjs[0][0].boxcar['COUNTS'],
specobjs[0][0].boxcar['COUNTS_IVAR'],
fitstbl['airmass'][4],
fitstbl['exptime'][4],
kastb.telescope['longitude'],
kastb.telescope['latitude'],
ra=RA,
dec=DEC)
# Test
assert isinstance(sens_dict, dict)
assert isinstance(sens_dict['wave_min'], units.Quantity)
def test_geocorrect():
"""
"""
fitstbl = dummy_fitstbl()
# Specobj (wrap in a list to mimic a slit)
scidx = 5
obstime = Time(fitstbl['mjd'][scidx],
format='mjd') #'%Y-%m-%dT%H:%M:%S.%f')
radec = ltu.radec_to_coord((fitstbl["ra"][scidx], fitstbl["dec"][scidx]))
helio, hel_corr = wave.geomotion_correct(radec, obstime, lon, lat, alt,
'heliocentric')
assert np.isclose(helio, -9.17461338,
rtol=1e-5) # Checked against x_keckhelio
#assert np.isclose(helio, -9.3344957, rtol=1e-5) # Original
assert np.isclose(1 - hel_corr, 3.060273748e-05, rtol=1e-5)
# Now apply to a specobj
npix = 1000
sobj = specobj.SpecObj('MultiSlit', 'DET01', SLITID=0)
sobj.BOX_WAVE = np.linspace(4000., 6000., npix)
sobj.BOX_COUNTS = 50. * (sobj.BOX_WAVE / 5000.)**-1.
sobj.BOX_COUNTS_IVAR = 1. / sobj.BOX_COUNTS.copy()
sobj.apply_helio(hel_corr, 'heliocentric')
assert np.isclose(sobj.BOX_WAVE[0], 3999.877589008, rtol=1e-8)
def fitstbl():
if os.getenv('PYPEIT_DEV') is None:
fitstbl = dummy_fitstbl(directory=data_path(''))
fitstbl['framebit'][0] = fitstbl.type_bitmask.turn_off(fitstbl['framebit'][0], flag='bias')
fitstbl['filename'][1] = 'b1.fits.gz'
fitstbl['filename'][5] = 'b27.fits.gz'
return fitstbl
fitstbl = dummy_fitstbl(directory=os.path.join(os.getenv('PYPEIT_DEV'), 'RAW_DATA',
'shane_kast_blue', '600_4310_d55'))
# Set the Bias to known
fitstbl['framebit'][0] = fitstbl.type_bitmask.turn_off(fitstbl['framebit'][0], flag='bias')
fitstbl['filename'][1] = 'b1.fits.gz'
for ii in range(2,5):
fitstbl['filename'][ii] = 'b{0}.fits.gz'.format(ii)
fitstbl['filename'][5] = 'b27.fits.gz'
return fitstbl
def test_save1d_fits():
""" save1d to FITS and HDF5
"""
# Init
fitstbl = dummy_fitstbl(spectro_name='shane_kast_blue', directory=data_path(''))
sobj = mk_specobj()
specObjs = specobjs.SpecObjs([sobj])
spectrograph = util.load_spectrograph('shane_kast_blue')
# Write to FITS
basename = 'test'
outfile = data_path('') + 'spec1d_{:s}.fits'.format(basename)
save.save_1d_spectra_fits(specObjs, fitstbl[5], spectrograph, outfile)
def test_save2d_fits():
#settings.dummy_settings()
#fitsdict = arutils.dummy_fitsdict(nfile=1, spectrograph='none', directory=data_path(''))
fitstbl = dummy_fitstbl(directory=data_path(''))
# Kludge
fitstbl.table.remove_column('filename')
fitstbl['filename'] = 'b1.fits.gz'
# Settings
#settings.argflag['run']['directory']['science'] = data_path('')
spectrograph = util.load_spectrograph('shane_kast_blue')
# Fill with dummy images
dum = np.ones((100, 100))
sci_dict = {}
sci_dict[0] = {}
sci_dict[0]['sciframe'] = dum
sci_dict[0]['finalvar'] = dum * 2
sci_dict[0]['finalsky'] = dum + 0.1
sci_dict['meta'] = {}
sci_dict['meta']['vel_corr'] = 0.
sci_dict['meta']['ir_redux'] = False
basename = 'test'
scidx = 5
path = fitstbl['directory'][scidx]
ifile = fitstbl['filename'][scidx]
rawfile = os.path.join(path, ifile)
master_dir = data_path('MF') + '_' + 'shane_kast_blue'
outfile = data_path('') + 'spec2d_{:s}.fits'.format(basename)
# Create a dummy master_key_dict
master_key_dict = dict(frame='',
bpm='bpmkey',
bias='',
arc='',
trace='',
flat='')
raw_hdr = fits.open(rawfile)[0].header
save.save_2d_images(sci_dict, raw_hdr, spectrograph, master_key_dict,
master_dir, outfile)
# Read and test
head0 = fits.getheader(data_path('spec2d_test.fits'))
assert head0['PYPMFDIR'] == master_dir
assert head0[
'BPMMKEY'] == 'bpm' # See save_2d_images; removes last 3 characters
assert 'PYPEIT' in head0['PIPELINE']
def fitstbl():
return dummy_fitstbl()
