def test_coadd1d_2():
"""
Test combining Echelle
"""
# NOTE: flux_value is False
parfile = 'coadd1d.par'
if os.path.isfile(parfile):
os.remove(parfile)
coadd_ofile = data_path('pisco_coadd.fits')
if os.path.isfile(coadd_ofile):
os.remove(coadd_ofile)
coadd_ifile = data_path('gemini_gnirs_32_sb_sxd.coadd1d')
scripts.coadd_1dspec.CoAdd1DSpec.main(
scripts.coadd_1dspec.CoAdd1DSpec.parse_args(
[coadd_ifile, '--test_spec_path',
data_path('')]))
hdu = io.fits_open(coadd_ofile)
assert hdu[1].header['EXT_MODE'] == 'OPT'
assert hdu[1].header['FLUXED'] is False
# Test that the output file is kosher and contains the right quantities
spec = onespec.OneSpec.from_file(coadd_ofile)
assert spec.wave.shape == spec.wave_grid_mid.shape
# Clean up
hdu.close()
os.remove(parfile)
os.remove(coadd_ofile)
def test_wmko_flux_std():
outfile = data_path('tmp_sens.fits')
if os.path.isfile(outfile):
os.remove(outfile)
# Do it
wmko_file = data_path('2017may28_d0528_0088.fits')
spectrograph = load_spectrograph('keck_deimos')
# Load + write
spec1dfile = data_path('tmp_spec1d.fits')
sobjs = keck_deimos.load_wmko_std_spectrum(wmko_file, outfile=spec1dfile)
# Sensfunc
# The following mirrors the main() call of sensfunc.py
par = spectrograph.default_pypeit_par()
par['sensfunc']['algorithm'] = "IR"
par['sensfunc']['multi_spec_det'] = [3, 7]
# Instantiate the relevant class for the requested algorithm
sensobj = sensfunc.SensFunc.get_instance(spec1dfile, outfile,
par['sensfunc'])
# Generate the sensfunc
sensobj.run()
# Write it out to a file
sensobj.to_file(outfile)
os.remove(spec1dfile)
os.remove(outfile)
def test_masterframe_methods():
master_key = 'A_1_DET01'
master_dir = data_path('')
# Filename
Aimg = buildimage.ArcImage(None)
Aimg.PYP_SPEC = 'shane_kast_blue'
filename = masterframe.construct_file_name(Aimg,
master_key,
master_dir=master_dir)
assert isinstance(filename, str)
assert filename == data_path(
f'Master{Aimg.master_type}_{master_key}.{Aimg.master_file_format}')
# Header
hdr = masterframe.build_master_header(Aimg, master_key, master_dir)
assert isinstance(hdr, fits.Header)
# Get those keys!
_master_key, _master_dir = masterframe.grab_key_mdir(hdr)
assert _master_key == master_key
_master_key2, _master_dir2 = masterframe.grab_key_mdir(filename,
from_filename=True)
assert _master_key2 == master_key
def test_coadd1d_2():
"""
Test combining Echelle
"""
# NOTE: flux_value is False
parfile = 'coadd1d.par'
if os.path.isfile(parfile):
os.remove(parfile)
coadd_ofile = data_path('pisco_coadd.fits')
if os.path.isfile(coadd_ofile):
os.remove(coadd_ofile)
coadd_ifile = data_path('gemini_gnirs_32_sb_sxd.coadd1d')
coadd_1dspec.main(
coadd_1dspec.parse_args(
[coadd_ifile, '--test_spec_path',
data_path('')]))
hdu = io.fits_open(coadd_ofile)
assert hdu[1].header['EXT_MODE'] == 'OPT'
assert hdu[1].header['FLUXED'] is False
# Clean up
hdu.close()
os.remove(parfile)
os.remove(coadd_ofile)
def test_from_sens_func(kast_blue_files):
sens_file = data_path('sensfunc.fits')
if os.path.isfile(sens_file):
os.remove(sens_file)
spectrograph = load_spectrograph('shane_kast_blue')
par = spectrograph.default_pypeit_par()
std_file, sci_file = kast_blue_files
# Build the sensitivity function
sensFunc = sensfunc.UVISSensFunc(std_file, sens_file)
sensFunc.run()
sensFunc.to_file(sens_file)
# Instantiate and run
outfile = data_path(os.path.basename(sci_file))
fluxCalibrate = fluxcalibrate.MultiSlitFC([sci_file], [sens_file],
par=par['fluxcalib'],
outfiles=[outfile])
# Test
sobjs = specobjs.SpecObjs.from_fitsfile(outfile)
assert 'OPT_FLAM' in sobjs[0].keys()
os.remove(sens_file)
os.remove(outfile)
def test_coadd1d_1(monkeypatch):
"""
Test basic coadd using shane_kast_blue
"""
dp = data_path('')
# Change to the parent directory of the data path, so we can test that
# coadding without a coadd output file specified places the output next
# to the spec1ds. Using monkeypatch means the current working directory
# will be restored after the test.
monkeypatch.chdir(Path(dp).parent)
# NOTE: flux_value is False
parfile = 'files/coadd1d.par'
if os.path.isfile(parfile):
os.remove(parfile)
coadd_ofile = data_path('coadd1d_J1217p3905_KASTb_20150520_20150520.fits')
if os.path.isfile(coadd_ofile):
os.remove(coadd_ofile)
coadd_ifile = data_path('shane_kast_blue.coadd1d')
scripts.coadd_1dspec.CoAdd1DSpec.main(
scripts.coadd_1dspec.CoAdd1DSpec.parse_args(
[coadd_ifile, "--par_outfile", parfile]))
hdu = io.fits_open(coadd_ofile)
assert hdu[1].header['EXT_MODE'] == 'OPT'
assert hdu[1].header['FLUXED'] is False
# Test that the output file is kosher and contains the right quantities
spec = onespec.OneSpec.from_file(coadd_ofile)
assert spec.wave.shape == spec.wave_grid_mid.shape
# Clean up
hdu.close()
os.remove(parfile)
os.remove(coadd_ofile)
def test_coadd1d_1():
"""
Test basic coadd using shane_kast_blue
"""
# NOTE: flux_value is False
parfile = 'coadd1d.par'
if os.path.isfile(parfile):
os.remove(parfile)
coadd_ofile = data_path('J1217p3905_coadd.fits')
if os.path.isfile(coadd_ofile):
os.remove(coadd_ofile)
coadd_ifile = data_path('shane_kast_blue.coadd1d')
coadd_1dspec.main(
coadd_1dspec.parse_args(
[coadd_ifile, '--test_spec_path',
data_path('')]))
hdu = io.fits_open(coadd_ofile)
assert hdu[1].header['EXT_MODE'] == 'OPT'
assert hdu[1].header['FLUXED'] is False
# Clean up
hdu.close()
os.remove(parfile)
os.remove(coadd_ofile)
def test_quicklook():
# The following needs the LRISb calibration files to be
# found in a CALIBS/ folder in the DEV Suite. You can get
# that folder here:
# https://drive.google.com/drive/folders/1NSg5Rmr8hD_1-fOchQc3WXjt59D6f9od?usp=sharing
calib_dir = os.path.join(os.environ['PYPEIT_DEV'], 'CALIBS')
if not os.path.isdir(calib_dir):
raise IOError("You need to get the CALIBS folder as described above!!")
# Define the output directories (HARDCODED!!)
cdir = os.getcwd()
os.chdir(data_path(''))
outdir = data_path('keck_lris_blue_A')
# Remove them if they already exist
if os.path.isdir(outdir):
shutil.rmtree(outdir)
# Raw path
droot = os.path.join(os.environ['PYPEIT_DEV'], 'RAW_DATA',
'keck_lris_blue', 'long_600_4000_d560')
ql_mos.main(
ql_mos.parse_args([
'keck_lris_blue', droot, 'b150910_2033.fits.gz',
'b150910_2051.fits.gz', 'b150910_2070.fits.gz', '--det=2',
'--user_pixflat={0}'.format(
os.path.join(
calib_dir,
'PYPEIT_LRISb_pixflat_B600_2x2_17sep2009.fits.gz'))
]))
# Cleanup
os.chdir(cdir)
shutil.rmtree(outdir)
def test_run_pypeit():
# Just get a few files
testrawdir = data_path('')
outdir = data_path('REDUX_OUT_TEST')
# For previously failed tests
if os.path.isdir(outdir):
shutil.rmtree(outdir)
# Run the setup
sargs = Setup.parse_args([
'-r', testrawdir + 'b', '-s', 'shane_kast_blue', '-c all', '-o',
'--output_path', outdir
])
Setup.main(sargs)
# Change to the configuration directory and set the pypeit file
configdir = os.path.join(outdir, 'shane_kast_blue_A')
pyp_file = os.path.join(configdir, 'shane_kast_blue_A.pypeit')
assert os.path.isfile(pyp_file), 'PypeIt file not written.'
# Try to run with -m and -o
pargs = RunPypeIt.parse_args([pyp_file, '-o', '-m', '-r', configdir])
RunPypeIt.main(pargs)
# TODO: Add some code that will try to open the QA HTML and check that it
# has the correct PNGs in it.
# #########################################################
# Test!!
# Files exist
spec1d_file = os.path.join(
configdir, 'Science',
'spec1d_b27-J1217p3905_KASTb_20150520T045733.560.fits')
assert os.path.isfile(spec1d_file), 'spec1d file missing'
# spec1d
specObjs = specobjs.SpecObjs.from_fitsfile(spec1d_file)
# Check RMS
assert specObjs[
0].WAVE_RMS < 0.02 # difference must be less than 0.02 pixels
# Flexure
assert abs(-0.03 - specObjs[0].FLEX_SHIFT_TOTAL
) < 0.1 # difference must be less than 0.1 pixels
# Helio
assert abs(specObjs[0].VEL_CORR - 0.9999261685542624) < 1.0E-10
# Now re-use those master files
pargs = RunPypeIt.parse_args([pyp_file, '-o', '-r', configdir])
RunPypeIt.main(pargs)
# Clean-up
shutil.rmtree(outdir)
def test_io():
detector = detector_container.DetectorContainer(**def_det)
detector.to_file(data_path('tmp_detector.fits'), overwrite=True)
_new_detector = detector.from_file(data_path('tmp_detector.fits'))
# Check a few attributes are equal
assert detector['dataext'] == _new_detector['dataext'], 'Bad read dataext'
assert np.array_equal(detector['gain'],
_new_detector['gain']), 'Bad read gain'
assert detector['binning'] == _new_detector['binning'], 'Bad read binning'
assert np.array_equal(detector['datasec'],
_new_detector['datasec']), 'Bad read datasec'
os.remove(data_path('tmp_detector.fits'))
def test_yamlify():
""" This tests the yamlify method and also the approach to
writing and reading the Setup block of PypeIt"""
obj = dict(a=1., b='acb', datasec='[2:23,:2048]', d=dict(c=3))
new_obj = utils.yamlify(obj)
# Write
tst_file = tstutils.data_path('tst.yaml')
with open(tst_file, 'w') as f:
setup_lines = io.dict_to_lines(new_obj, level=1)
f.write('\n'.join(setup_lines)+'\n')
# Read
with open(tst_file, 'r') as f:
lines = f.readlines()
# Strip white space
lines = [line.strip() for line in lines]
# Add back in \n
ystr = '\n'.join(lines)
sdict = yaml.safe_load(ystr)
# Clean up
os.remove(tst_file)
def test_all2dobj_update_image(init_dict):
allspec2D = spec2dobj.AllSpec2DObj()
allspec2D['meta']['bkg_redux'] = False
allspec2D['meta']['find_negative'] = False
for i in range(2):
d = load_spectrograph('keck_deimos').get_detector_par(i + 1)
allspec2D[d.name] = spec2dobj.Spec2DObj(detector=d, **init_dict)
# Write
ofile = tstutils.data_path('tst_allspec2d.fits')
if os.path.isfile(ofile):
os.remove(ofile)
allspec2D.write_to_fits(ofile)
_allspec2D = spec2dobj.AllSpec2DObj()
_allspec2D['meta']['bkg_redux'] = False
_allspec2D['meta']['find_negative'] = False
d = load_spectrograph('keck_deimos').get_detector_par(2)
detname = d.name
init_dict['sciimg'] = allspec2D[detname].sciimg.copy() * 2
_allspec2D[detname] = spec2dobj.Spec2DObj(detector=d, **init_dict)
_allspec2D.write_to_fits(ofile,
update_det=_allspec2D.detectors,
overwrite=True)
# Check
allspec2D_2 = spec2dobj.AllSpec2DObj.from_fits(ofile)
assert np.array_equal(allspec2D_2[detname].sciimg,
_allspec2D[detname].sciimg), 'Bad update'
assert np.array_equal(allspec2D_2[detname].sciimg,
allspec2D[detname].sciimg * 2), 'Bad update'
os.remove(ofile)
def test_all2dobj_write(init_dict):
# Build one
init_dict['detector'] = tstutils.get_kastb_detector()
spec2DObj = spec2dobj.Spec2DObj(**init_dict)
allspec2D = spec2dobj.AllSpec2DObj()
allspec2D['meta']['bkg_redux'] = False
allspec2D['meta']['find_negative'] = False
detname = spec2DObj.detname
allspec2D[detname] = spec2DObj
# Write
ofile = tstutils.data_path('tst_allspec2d.fits')
if os.path.isfile(ofile):
os.remove(ofile)
allspec2D.write_to_fits(ofile)
# Read
_allspec2D = spec2dobj.AllSpec2DObj.from_fits(ofile)
# Check
assert allspec2D.detectors == _allspec2D.detectors, 'Bad read: detector mismatch'
assert allspec2D['meta'] == _allspec2D['meta'], 'Bad read: meta mismatch'
# Try to update it
_allspec2D['meta']['bkg_redux'] = True
_allspec2D[detname].vel_corr = 2.
_allspec2D.write_to_fits(ofile, update_det='DET01')
__allspec2D = spec2dobj.AllSpec2DObj.from_fits(ofile)
assert __allspec2D['meta'] == _allspec2D['meta'], 'Bad read: meta mismatch'
assert __allspec2D['meta'] != allspec2D['meta'], 'Bad read: meta mismatch'
assert __allspec2D[detname].vel_corr == 2., 'Bad update'
os.remove(ofile)
def test_io():
file = os.path.join(os.environ['PYPEIT_DEV'], 'RAW_DATA', 'gemini_gmos',
'GN_HAM_R400_885', 'N20190205S0035.fits')
# Load the spectrograph
spec = load_spectrograph('gemini_gmos_north_ham')
msc = spec.get_mosaic_par((1, 2, 3), hdu=fits.open(file))
test_file = data_path('tmp_mosaic.fits')
msc.to_file(test_file, overwrite=True)
_msc = Mosaic.from_file(test_file)
# Check a few attributes are equal
assert np.array_equal(msc.tform, _msc.tform), 'Bad transform read'
assert _msc.shape == msc.shape, 'Bad shape read'
assert _msc.name == msc.name, 'Bad name setup'
assert len(_msc.detectors) == len(msc.detectors), 'Bad number of detectors'
assert _msc.detectors[0]['dataext'] == msc.detectors[0][
'dataext'], 'Bad read dataext'
assert np.array_equal(_msc.detectors[1]['gain'],
msc.detectors[1]['gain']), 'Bad read gain'
assert _msc.detectors[2]['binning'] == msc.detectors[2][
'binning'], 'Bad read binning'
assert np.array_equal(_msc.detectors[1]['datasec'], msc.detectors[1]['datasec']), \
'Bad read datasec'
os.remove(test_file)
def test_gen_sensfunc(kast_blue_files):
sens_file = data_path('sensfunc.fits')
if os.path.isfile(sens_file):
os.remove(sens_file)
# Get it started
spectrograph = load_spectrograph('shane_kast_blue')
par = spectrograph.default_pypeit_par()
std_file, sci_file = kast_blue_files
# Instantiate
sensFunc = sensfunc.UVISSensFunc(std_file, sens_file)
# Test the standard loaded
assert sensFunc.meta_spec['BINNING'] == '1,1'
assert sensFunc.meta_spec['TARGET'] == 'Feige 66'
# Generate the sensitivity function
sensFunc.run()
# Test
assert os.path.basename(sensFunc.std_cal) == 'feige66_002.fits'
# TODO: @jhennawi, please check this edit
assert 'SENS_ZEROPOINT' in sensFunc.sens.keys(), 'Bad column names'
# Write
sensFunc.to_file(sens_file)
os.remove(sens_file)
def test_read_combid():
# ------------------------------------------------------------------
# In case of failed tests
setup_dir = data_path('setup_files')
if os.path.isdir(setup_dir):
shutil.rmtree(setup_dir)
config_dir = data_path('shane_kast_blue_A')
if os.path.isdir(config_dir):
shutil.rmtree(config_dir)
# ------------------------------------------------------------------
# Generate the pypeit file with the comb_id
droot = data_path('b')
pargs = Setup.parse_args([
'-r', droot, '-s', 'shane_kast_blue', '-c=all', '-b',
'--extension=fits.gz', '--output_path={:s}'.format(data_path(''))
])
Setup.main(pargs)
shutil.rmtree(setup_dir)
pypeit_file = os.path.join(config_dir, 'shane_kast_blue_A.pypeit')
cfg_lines, data_files, frametype, usrdata, setups, _ = parse_pypeit_file(
pypeit_file)
# Get the spectrograph
spectrograph = None
for l in cfg_lines:
if 'spectrograph' in l:
spectrograph = load_spectrograph(l.split(' ')[-1])
break
assert spectrograph is not None, 'Did not appropriately read spectrograph'
# Set the metadata
pmd = PypeItMetaData(spectrograph,
spectrograph.default_pypeit_par(),
files=data_files,
usrdata=usrdata,
strict=False)
indx = pmd['filename'] == 'b27.fits.gz'
assert pmd['comb_id'][indx] == [1], 'Incorrect combination group ID'
assert pmd['comb_id'][np.where(~indx)
[0]][0] == -1, 'Incorrect combination group ID'
shutil.rmtree(config_dir)
def test_all2dobj_hdr(init_dict):
# Build one
init_dict['detector'] = tstutils.get_kastb_detector()
spec2DObj = spec2dobj.Spec2DObj(**init_dict)
allspec2D = spec2dobj.AllSpec2DObj()
allspec2D['meta']['bkg_redux'] = False
allspec2D['meta']['find_negative'] = False
allspec2D[spec2DObj.detname] = spec2DObj
#
kast_file = tstutils.data_path('b1.fits.gz')
header = fits.getheader(kast_file)
spectrograph = load_spectrograph('shane_kast_blue')
# Do it
hdr = allspec2D.build_primary_hdr(header,
spectrograph,
master_dir=tstutils.data_path(''))
# Test it
assert hdr['SKYSUB'] == 'MODEL'
def test_intrv_versions():
from pypeit.bspline.utilpy import intrv as intrv_py
from pypeit.bspline.utilc import intrv as intrv_c
d = np.load(data_path('intrv.npz'))
indx = intrv_py(d['nord'], d['breakpoints'], d['x'])
_indx = intrv_c(d['nord'], d['breakpoints'], d['x'])
assert np.allclose(indx, _indx), 'Differences in index'
def test_initialization():
""" Load input PypeIt file
"""
# Generate a PYPIT file
pypit_file = data_path('test.pypeit')
make_pypeit_file(pypit_file, 'shane_kast_blue', [data_path('b*fits.gz')], setup_mode=True)
# Perform the setup
setup = pypeitsetup.PypeItSetup.from_pypeit_file(pypit_file)
par, spectrograph, fitstbl = setup.run(sort_dir=data_path(''))
# Test
assert spectrograph.name == 'shane_kast_blue'
assert len(fitstbl) == 8
# Clean-up
os.remove(data_path('test.calib'))
os.remove(data_path('test.pypeit'))
def test_io():
"""
Test that bspline_profile (1) is successful and (2) produces the
same result for a set of data fit spectrally.
"""
# Files created using `rmtdict` branch (30 Jan 2020)
files = [
data_path('gemini_gnirs_32_{0}_spec_fit.npz'.format(slit))
for slit in [0, 1]
]
logrej = 0.5
spec_samp_fine = 1.2
for f in files:
d = np.load(f)
spec_bspl, spec_gpm_fit, spec_flat_fit, _, exit_status \
= fitting.bspline_profile(d['spec_coo_data'], d['spec_flat_data'], d['spec_ivar_data'],
np.ones_like(d['spec_coo_data']), ingpm=d['spec_gpm_data'],
nord=4, upper=logrej, lower=logrej,
kwargs_bspline={'bkspace': spec_samp_fine},
kwargs_reject={'groupbadpix': True, 'maxrej': 5}, quiet=True)
# Write
ofile = data_path('tst_bspline.fits')
if os.path.isfile(ofile):
os.remove(ofile)
spec_bspl.to_file(ofile)
# Read
_spec_bspl = bspline.bspline.from_file(ofile)
# Check that the data read in is the same
assert np.array_equal(_spec_bspl.breakpoints,
spec_bspl.breakpoints), 'Bad read'
# Evaluate the bsplines and check that the written and read in data
# provide the same result
tmp = spec_bspl.value(np.linspace(0., 1., 100))[0]
_tmp = _spec_bspl.value(np.linspace(0., 1., 100))[0]
assert np.array_equal(tmp, _tmp), 'Bad bspline evaluate'
# Test overwrite
_spec_bspl.to_file(ofile, overwrite=True)
# None
bspl = bspline.bspline(None)
bspl.to_file(ofile, overwrite=True)
os.remove(ofile)
def test_chk_calibs_not():
os.chdir(data_path(''))
droot = os.path.join(os.environ['PYPEIT_DEV'],
'RAW_DATA/not_alfosc/grism4')
droot += '/ALD'
pargs = chk_for_calibs.parse_args([droot, '-s', 'not_alfosc'])
answers, _ = chk_for_calibs.main(pargs)
assert answers['pass'][0], 'One or more failures!'
def test_load_specobjs():
spec_file = data_path(
'spec1d_r153-J0025-0312_KASTr_20150123T025323.850.fits')
sobjs = specobjs.SpecObjs.from_fitsfile(spec_file)
# Test
assert isinstance(sobjs, specobjs.SpecObjs)
assert len(sobjs[0].BOX_COUNTS) == 1200
assert isinstance(sobjs[0], specobj.SpecObj)
def test_spec2dobj_io(init_dict):
init_dict['detector'] = tstutils.get_kastb_detector()
spec2DObj = spec2dobj.Spec2DObj(**init_dict)
# Write
ofile = tstutils.data_path('tst_spec2d.fits')
if os.path.isfile(ofile):
os.remove(ofile)
spec2DObj.to_file(ofile)
# Read
_spec2DObj = spec2dobj.Spec2DObj.from_file(ofile, spec2DObj.detname)
os.remove(ofile)
def test_io():
sobj = specobj.SpecObj('MultiSlit', 'DET01', SLITID=0)
# Can we handle 1 array?
sobj['BOX_WAVE'] = np.arange(100).astype(float)
ofile = data_path('tmp.fits')
sobj.to_file(ofile, overwrite=True)
_sobj = specobj.SpecObj.from_file(ofile)
assert np.array_equal(sobj.BOX_WAVE, _sobj.BOX_WAVE)
# Cleanup
os.remove(ofile)
def test_model_versions():
from pypeit.bspline.utilpy import bspline_model as bspline_model_py
from pypeit.bspline.utilc import bspline_model as bspline_model_c
d = np.load(data_path('bspline_model.npz'))
mod = bspline_model_py(d['x'], d['action'], d['lower'], d['upper'],
d['coeff'], d['n'], d['nord'], d['npoly'])
_mod = bspline_model_c(d['x'], d['action'], d['lower'], d['upper'],
d['coeff'], d['n'], d['nord'], d['npoly'])
assert np.allclose(mod, _mod), 'Differences in index'
def test_rms():
"""Test on some real data."""
center = np.load(
data_path('example_trace_deimos_1200G_M_7750.npz'))['center']
pca = TracePCA(trace_cen=center, npca=2)
pca.build_interpolator(np.array([3, 1]),
function='legendre') #, debug=True)
pca_center = pca.predict(center[pca.reference_row, :])
rms = np.std(center - pca_center, axis=0)
assert np.sum(rms > 0.2) == 1, 'Change in the accuracy of the PCA.'
def test_io(sobj1, sobj2, sobj3, sobj4):
sobjs = specobjs.SpecObjs([sobj1, sobj2, sobj3, sobj4])
sobjs[0]['BOX_WAVE'] = np.arange(1000).astype(float)
sobjs[1]['BOX_WAVE'] = np.arange(1000).astype(float)
sobjs[2]['BOX_WAVE'] = np.arange(1000).astype(float)
#sobjs[0]['BOX_COUNTS'] = np.ones_like(sobjs[0].BOX_WAVE) # This tests single array
sobjs[1]['BOX_COUNTS'] = np.ones_like(sobjs[0].BOX_WAVE)
sobjs[2]['BOX_COUNTS'] = np.ones_like(sobjs[0].BOX_WAVE)
# Detector
sobjs[0]['DETECTOR'] = tstutils.get_kastb_detector()
tmp = tstutils.get_kastb_detector()
tmp['det'] = 2
sobjs[1]['DETECTOR'] = tmp
# Write
header = fits.PrimaryHDU().header
header['TST'] = 'TEST'
ofile = tstutils.data_path('tst_specobjs.fits')
if os.path.isfile(ofile):
os.remove(ofile)
sobjs.write_to_fits(header, ofile, overwrite=False)
# Read
hdul = io.fits_open(ofile)
assert len(hdul) == 7 # Primary + 4 Obj + 2 Detectors
assert hdul[0].header['NSPEC'] == 4
hdul.close()
#
_sobjs = specobjs.SpecObjs.from_fitsfile(ofile)
assert _sobjs.nobj == 4
assert np.array_equal(sobjs[0].BOX_WAVE, _sobjs[0].BOX_WAVE)
assert np.array_equal(sobjs[1].BOX_WAVE, _sobjs[1].BOX_WAVE)
_sobjs.write_to_fits(header, ofile, overwrite=True)
# Detector
assert _sobjs[0].DETECTOR is not None, '1st object started with Detector'
assert _sobjs[
1].DETECTOR is not None, '2nd object has DET=1 so should get decorated'
assert _sobjs[2].DETECTOR is None
# Now try updates!
sobjs1 = specobjs.SpecObjs([sobj1])
sobjs[0]['BOX_WAVE'] = np.arange(2000).astype(float)
sobjs1[0]['DETECTOR'] = tstutils.get_kastb_detector()
header1 = fits.PrimaryHDU().header
sobjs1.write_to_fits(header1, ofile, overwrite=True, update_det='DET01')
# Test
_sobjs1 = specobjs.SpecObjs.from_fitsfile(ofile)
assert _sobjs1.nobj == 3
assert _sobjs1[2].BOX_WAVE.size == 2000
os.remove(ofile)
def test_identify():
arc_file = os.path.join(os.getenv('PYPEIT_DEV'), 'Cooked',
'shane_kast_blue', 'MasterArc_A_1_DET01.fits')
slits_file = os.path.join(os.getenv('PYPEIT_DEV'), 'Cooked',
'shane_kast_blue',
'MasterSlits_A_1_DET01.fits.gz')
# Just list
pargs = scripts.identify.Identify.parse_args(
[arc_file, slits_file, '--test'])
arcfitter = scripts.identify.Identify.main(pargs)
# Load line list
arcfitter.load_IDs(fname=data_path('waveid_tests.ascii'))
assert arcfitter._detns.size == 31, 'Bad load'
# Fit
arcfitter._fitdict['polyorder'] = 3
arcfitter.fitsol_fit()
assert arcfitter._fitdict['fitc'].size == 4, 'Bad fit'
# Auto
arcfitter.auto_id()
assert np.sum(arcfitter._lineflg < 3) > 10, 'Bad auto ID'
arcfitter.fitsol_fit()
# Write
final_fit = arcfitter.get_results()
waveCalib = wavecalib.WaveCalib(
nslits=1,
wv_fits=np.atleast_1d(arcfitter._fitdict['WaveFit']),
arc_spectra=np.atleast_2d(arcfitter.specdata).T,
spat_ids=np.atleast_1d(int(arcfitter._spatid)),
PYP_SPEC='shane_kast_blue',
)
# If you touch the following line, you probably need to update the call in scripts/identify.py
wvarxiv_fn = arcfitter.store_solution(final_fit,
1,
rmstol=0.1,
force_save=True,
wvcalib=waveCalib)
# Test we can read it
tmp = wavecalib.WaveCalib.from_file('wvcalib.fits')
# Clean up -- If these fail then the store solution failed
os.remove('waveid.ascii')
os.remove(wvarxiv_fn)
os.remove('wvcalib.fits')
def test_cholesky_solve_versions():
# Import only when the test is performed
from pypeit.bspline.utilpy import cholesky_solve as cholesky_solve_py
from pypeit.bspline.utilc import cholesky_solve as cholesky_solve_c
# Read data
d = np.load(data_path('cholesky_solve_abb.npz'))
# Run python version
e, b = cholesky_solve_py(d['a'], d['bb'])
# Run C version
e, _b = cholesky_solve_c(d['a'], d['bb'])
# Check output arrays
assert np.allclose(b, _b), 'Differences in cholesky_solve'
def test_solution_array_versions():
# Import only when the test is performed
from pypeit.bspline.utilpy import solution_arrays as sol_py
from pypeit.bspline.utilc import solution_arrays as sol_c
d = np.load(data_path('solution_arrays.npz'))
a, b = sol_py(d['nn'], d['npoly'], d['nord'], d['ydata'], d['action'],
d['ivar'], d['upper'], d['lower'])
_a, _b = sol_c(d['nn'], d['npoly'], d['nord'], d['ydata'], d['action'],
d['ivar'], d['upper'], d['lower'])
assert np.allclose(a, _a), 'Differences in alpha'
assert np.allclose(b, _b), 'Differences in beta'