def test_arfmodelpha_call(ignore):
"""What happens calling an arf with a pha?
The ignore value indicates what channel to ignore (0 means
nothing is ignored). The aim is to check edge effects,
and as there are only a few channels, it was decided to
test all channels.
"""
# Note: the exposure is set in the PHA and ARF, but should not be
# used when evaluating the model; it's value has been
# set to a value that the test will fail it it is.
#
exposure = 200.1
estep = 0.01
egrid = np.arange(0.01, 0.06, estep)
svals = [1.1, 1.2, 1.3, 1.4]
specresp = np.asarray(svals)
adata = create_arf(egrid[:-1], egrid[1:], specresp, exposure=exposure)
constant = 2.3
mdl = Const1D('flat')
mdl.c0 = constant
channels = np.arange(1, 5, dtype=np.int16)
counts = np.asarray([10, 5, 12, 7], dtype=np.int16)
pha = DataPHA('test-pha',
channel=channels,
counts=counts,
exposure=exposure)
pha.set_arf(adata)
# force energy units (only needed if ignore is set)
pha.set_analysis('energy')
if ignore is not None:
de = estep * 0.9
e0 = egrid[ignore]
pha.notice(lo=e0, hi=e0 + de, ignore=True)
# The assert are intended to help people reading this
# code rather than being a useful check that the code
# is working.
mask = [True, True, True, True]
mask[ignore] = False
assert (pha.mask == mask).all()
wrapped = ARFModelPHA(adata, pha, mdl)
# The model is evaluated on the ARF grid, not whatever
# is sent in. It is also integrated across the bins,
# which is why there is a multiplication by the
# grid width (for this constant model).
#
# Note that the filter doesn't change the grid.
#
de = egrid[1:] - egrid[:-1]
expected = constant * np.asarray(svals) * de
out = wrapped([4, 5])
assert_allclose(out, expected)
def test_arf1d_pha_zero_energy_bin():
"What happens when the first bin starts at 0, with replacement"
ethresh = 1.0e-10
# Note: the two exposures are different to check which is
# used (the answer is neither, which seems surprising)
#
exposure1 = 0.1
egrid = np.asarray([0.0, 0.1, 0.2, 0.4, 0.5, 0.7, 0.8])
elo = egrid[:-1]
ehi = egrid[1:]
specresp = np.asarray([10.2, 9.8, 10.0, 12.0, 8.0, 10.0])
with warnings.catch_warnings(record=True) as ws:
warnings.simplefilter("always")
adata = create_arf(elo,
ehi,
specresp,
exposure=exposure1,
ethresh=ethresh)
validate_zero_replacement(ws, 'ARF', 'user-arf', ethresh)
arf = ARF1D(adata)
exposure2 = 2.4
channels = np.arange(1, 7, dtype=np.int16)
counts = np.ones(6, dtype=np.int16)
pha = DataPHA('test-pha',
channel=channels,
counts=counts,
exposure=exposure2)
pha.set_arf(adata)
pha.set_analysis('energy')
mdl = MyPowLaw1D()
tmdl = PowLaw1D()
wrapped = ARFModelPHA(arf, pha, mdl)
out = wrapped([0.1, 0.2])
elo[0] = ethresh
expected = specresp * tmdl(elo, ehi)
assert_allclose(out, expected)
assert not np.isnan(out[0])
def test_cstat_arfpha():
"""What does CSTAT calculate when there is an ARF+PHA instrument model.
The value here is technically wrong, in that the AREASCAL value
is not being included in the calculation, but is included as a
test to validate this use case.
See Also
--------
test_cstat_nophamodel, test_cstat_rmfpha, test_cstat_rsppha
"""
dset, mdl, expected = setup_likelihood(scale=True)
# Use the channel grid as the "energy axis".
#
arf = make_arf(energ_lo=dset.channel, energ_hi=dset.channel + 1)
mdl_ascal = ARFModelPHA(arf, dset, mdl)
stat = CStat()
sval_ascal = stat.calc_stat(dset, mdl_ascal)
assert_allclose(sval_ascal[0], expected)