def test_simulating_data_sets():
with within_directory(__example_dir):
ogip = OGIPLike('test_ogip', observation='test.pha{1}')
with pytest.raises(AssertionError):
_ = ogip.simulated_parameters
n_data_points = 128
ogip.set_active_measurements("all")
assert ogip._n_synthetic_datasets == 0
ab = AnalysisBuilder(ogip)
_ = ab.get_jl('normal')
new_ogip = ogip.get_simulated_dataset('sim')
assert new_ogip.name == 'sim'
assert ogip._n_synthetic_datasets == 1
assert new_ogip.n_data_points == n_data_points
assert new_ogip.n_data_points == sum(new_ogip._mask)
assert sum(new_ogip._mask) == new_ogip.n_data_points
assert new_ogip.tstart == 0.
assert 'cons_sim' in new_ogip.nuisance_parameters
assert new_ogip.nuisance_parameters['cons_sim'].fix == True
assert new_ogip.nuisance_parameters['cons_sim'].free == False
pha_info = new_ogip.get_pha_files()
assert 'pha' in pha_info
assert 'bak' in pha_info
assert 'rsp' in pha_info
del ogip
del new_ogip
ogip = OGIPLike('test_ogip', observation='test.pha{1}')
ab = AnalysisBuilder(ogip)
_ = ab.get_jl('normal')
# Now check that generationing a lot of data sets works
sim_data_sets = [
ogip.get_simulated_dataset('sim%d' % i) for i in range(100)
]
assert len(sim_data_sets) == ogip._n_synthetic_datasets
for i, ds in enumerate(sim_data_sets):
assert ds.name == "sim%d" % i
assert sum(ds._mask) == sum(ogip._mask)
assert ds._rebinner is None
def _get_dataset():
datadir = os.path.join(get_test_datasets_directory(), "bn090217206")
obsSpectrum = os.path.join(datadir, "bn090217206_n6_srcspectra.pha{1}")
bakSpectrum = os.path.join(datadir, "bn090217206_n6_bkgspectra.bak{1}")
rspFile = os.path.join(datadir, "bn090217206_n6_weightedrsp.rsp{1}")
NaI6 = OGIPLike("NaI6", obsSpectrum, bakSpectrum, rspFile)
NaI6.set_active_measurements("10.0-30.0", "40.0-950.0")
return NaI6
def get_dataset():
datadir = os.path.join(get_test_datasets_directory(), "bn090217206")
obsSpectrum = os.path.join(datadir, "bn090217206_n6_srcspectra.pha{1}")
bakSpectrum = os.path.join(datadir, "bn090217206_n6_bkgspectra.bak{1}")
rspFile = os.path.join(datadir, "bn090217206_n6_weightedrsp.rsp{1}")
NaI6 = OGIPLike("NaI6", obsSpectrum, bakSpectrum, rspFile)
NaI6.set_active_measurements("10.0-30.0", "40.0-950.0")
return NaI6
def get_dataset():
data_dir = Path(get_test_datasets_directory(), "bn090217206")
obs_spectrum = Path(data_dir, "bn090217206_n6_srcspectra.pha{1}")
bak_spectrum = Path(data_dir, "bn090217206_n6_bkgspectra.bak{1}")
rsp_file = Path(data_dir, "bn090217206_n6_weightedrsp.rsp{1}")
NaI6 = OGIPLike("NaI6", str(obs_spectrum), str(bak_spectrum),
str(rsp_file))
NaI6.set_active_measurements("10.0-30.0", "40.0-950.0")
return NaI6
def get_dataset_det(det):
data_dir = Path(get_test_datasets_directory(), "bn090217206")
obs_spectrum = Path(data_dir, f"bn090217206_{det}_srcspectra.pha{{1}}")
bak_spectrum = Path(data_dir, f"bn090217206_{det}_bkgspectra.bak{{1}}")
rsp_file = Path(data_dir, f"bn090217206_{det}_weightedrsp.rsp{{1}}")
p = OGIPLike(det, str(obs_spectrum), str(bak_spectrum), str(rsp_file))
if det[0] == "b":
p.set_active_measurements("250-25000")
else:
p.set_active_measurements("10.0-30.0", "40.0-950.0")
return p
def test_likelihood_ratio_test():
with within_directory(__example_dir):
ogip = OGIPLike('test_ogip', observation='test.pha{1}')
ogip.set_active_measurements("all")
ab = AnalysisBuilder(ogip)
jl1 = ab.get_jl('normal')
res1, _ = jl1.fit(compute_covariance=True)
jl2 = ab.get_jl('cpl')
res2, _ = jl2.fit(compute_covariance=True)
lrt = LikelihoodRatioTest(jl1, jl2)
null_hyp_prob, TS, data_frame, like_data_frame = lrt.by_mc(
n_iterations=50, continue_on_failure=True)
def test_ogip_rebinner():
with within_directory(__example_dir):
ogip = OGIPLike("test_ogip", observation="test.pha{1}")
n_data_points = 128
ogip.set_active_measurements("all")
assert ogip.n_data_points == n_data_points
ogip.rebin_on_background(min_number_of_counts=100)
assert ogip.n_data_points < 128
with pytest.raises(AssertionError):
ogip.set_active_measurements("all")
ogip.remove_rebinning()
assert ogip._rebinner is None
assert ogip.n_data_points == n_data_points
ogip.view_count_spectrum()
def test_swift_gbm():
with within_directory(__example_dir):
gbm_dir = "gbm"
bat_dir = "bat"
bat = OGIPLike(
"BAT",
observation=os.path.join(bat_dir, "gbm_bat_joint_BAT.pha"),
response=os.path.join(bat_dir, "gbm_bat_joint_BAT.rsp"),
)
bat.set_active_measurements("15-150")
bat.view_count_spectrum()
nai6 = OGIPLike(
"n6",
os.path.join(gbm_dir, "gbm_bat_joint_NAI_06.pha"),
os.path.join(gbm_dir, "gbm_bat_joint_NAI_06.bak"),
os.path.join(gbm_dir, "gbm_bat_joint_NAI_06.rsp"),
spectrum_number=1,
)
nai6.set_active_measurements("8-900")
nai6.view_count_spectrum()
bgo0 = OGIPLike(
"b0",
os.path.join(gbm_dir, "gbm_bat_joint_BGO_00.pha"),
os.path.join(gbm_dir, "gbm_bat_joint_BGO_00.bak"),
os.path.join(gbm_dir, "gbm_bat_joint_BGO_00.rsp"),
spectrum_number=1,
)
bgo0.set_active_measurements("250-10000")
bgo0.view_count_spectrum()
bat.use_effective_area_correction(0.2, 1.5)
bat.fix_effective_area_correction(0.6)
bat.use_effective_area_correction(0.2, 1.5)
band = Band()
model = Model(PointSource("joint_fit", 0, 0, spectral_shape=band))
band.K = 0.04
band.xp = 300.0
data_list = DataList(bat, nai6, bgo0)
jl = JointLikelihood(model, data_list)
_ = jl.fit()
_ = display_spectrum_model_counts(jl, step=False)
def test_swift_gbm():
with within_directory(__example_dir):
gbm_dir = "gbm"
bat_dir = "bat"
bat = OGIPLike('BAT',
observation=os.path.join(bat_dir,
'gbm_bat_joint_BAT.pha'),
response=os.path.join(bat_dir, 'gbm_bat_joint_BAT.rsp'))
bat.set_active_measurements('15-150')
bat.view_count_spectrum()
nai6 = OGIPLike('n6',
os.path.join(gbm_dir, 'gbm_bat_joint_NAI_06.pha'),
os.path.join(gbm_dir, 'gbm_bat_joint_NAI_06.bak'),
os.path.join(gbm_dir, 'gbm_bat_joint_NAI_06.rsp'),
spectrum_number=1)
nai6.set_active_measurements('8-900')
nai6.view_count_spectrum()
bgo0 = OGIPLike('b0',
os.path.join(gbm_dir, 'gbm_bat_joint_BGO_00.pha'),
os.path.join(gbm_dir, 'gbm_bat_joint_BGO_00.bak'),
os.path.join(gbm_dir, 'gbm_bat_joint_BGO_00.rsp'),
spectrum_number=1)
bgo0.set_active_measurements('250-10000')
bgo0.view_count_spectrum()
bat.use_effective_area_correction(.2, 1.5)
bat.fix_effective_area_correction(.6)
bat.use_effective_area_correction(.2, 1.5)
band = Band()
model = Model(PointSource('joint_fit', 0, 0, spectral_shape=band))
band.K = .04
band.xp = 300.
data_list = DataList(bat, nai6, bgo0)
jl = JointLikelihood(model, data_list)
_ = jl.fit()
_ = display_spectrum_model_counts(jl, step=False)
def test_ogip_energy_selection():
with within_directory(__example_dir):
ogip = OGIPLike("test_ogip", observation="test.pha{1}")
assert sum(ogip._mask) == sum(ogip.quality.good)
# Test that selecting a subset reduces the number of data points
ogip.set_active_measurements("10-30")
assert sum(ogip._mask) == ogip.n_data_points
assert sum(ogip._mask) < 128
# Test selecting all channels
ogip.set_active_measurements("all")
assert sum(ogip._mask) == ogip.n_data_points
assert sum(ogip._mask) == 128
# Test channel setting
ogip.set_active_measurements(exclude=["c0-c1"])
assert sum(ogip._mask) == ogip.n_data_points
assert sum(ogip._mask) == 126
# Test mixed ene/chan setting
ogip.set_active_measurements(exclude=["0-c1"], verbose=True)
assert sum(ogip._mask) == ogip.n_data_points
assert sum(ogip._mask) == 126
# Test that energies cannot be input backwards
with pytest.raises(AssertionError):
ogip.set_active_measurements("50-30")
with pytest.raises(AssertionError):
ogip.set_active_measurements("c20-c10")
with pytest.raises(AssertionError):
ogip.set_active_measurements("c100-0")
with pytest.raises(AssertionError):
ogip.set_active_measurements("c1-c200")
with pytest.raises(AssertionError):
ogip.set_active_measurements("10-c200")
ogip.set_active_measurements("reset")
assert sum(ogip._mask) == sum(ogip.quality.good)
def test_pha_files_in_generic_ogip_constructor_spec_number_in_arguments():
with within_directory(__example_dir):
ogip = OGIPLike("test_ogip", observation="test.pha", spectrum_number=1)
ogip.set_active_measurements("all")
pha_info = ogip.get_pha_files()
for key in ["pha", "bak"]:
assert isinstance(pha_info[key], PHASpectrum)
assert pha_info["pha"].background_file == "test_bak.pha{1}"
assert pha_info["pha"].ancillary_file is None
assert pha_info["pha"].instrument == "GBM_NAI_03"
assert pha_info["pha"].mission == "GLAST"
assert pha_info["pha"].is_poisson == True
assert pha_info["pha"].n_channels == ogip.n_data_points
assert pha_info["pha"].n_channels == len(pha_info["pha"].rates)
# Test that Poisson rates cannot call rate error
assert pha_info["pha"].rate_errors is None
assert (
sum(pha_info["pha"].sys_errors == np.zeros_like(pha_info["pha"].rates))
== pha_info["bak"].n_channels
)
assert (
pha_info["pha"].response_file.split("/")[-1]
== "glg_cspec_n3_bn080916009_v07.rsp"
)
assert pha_info["pha"].scale_factor == 1.0
assert pha_info["bak"].background_file is None
# Test that we cannot get a bak file
#
# with pytest.raises(KeyError):
#
# _ = pha_info['bak'].background_file
#
# Test that we cannot get a anc file
# with pytest.raises(KeyError):
#
# _ = pha_info['bak'].ancillary_file
assert pha_info["bak"].response_file is None
assert pha_info["bak"].ancillary_file is None
# # Test that we cannot get a RSP file
# with pytest.raises(AttributeError):
# _ = pha_info['bak'].response_file
assert pha_info["bak"].instrument == "GBM_NAI_03"
assert pha_info["bak"].mission == "GLAST"
assert pha_info["bak"].is_poisson == False
assert pha_info["bak"].n_channels == ogip.n_data_points
assert pha_info["bak"].n_channels == len(pha_info["pha"].rates)
assert len(pha_info["bak"].rate_errors) == pha_info["bak"].n_channels
assert (
sum(pha_info["bak"].sys_errors == np.zeros_like(pha_info["pha"].rates))
== pha_info["bak"].n_channels
)
assert pha_info["bak"].scale_factor == 1.0
assert isinstance(pha_info["rsp"], OGIPResponse)
def test_pha_files_in_generic_ogip_constructor_spec_number_in_file_name():
with within_directory(__example_dir):
ogip = OGIPLike('test_ogip', observation='test.pha{1}')
ogip.set_active_measurements('all')
pha_info = ogip.get_pha_files()
for key in ['pha', 'bak']:
assert isinstance(pha_info[key], PHASpectrum)
assert pha_info['pha'].background_file == 'test_bak.pha{1}'
assert pha_info['pha'].ancillary_file is None
assert pha_info['pha'].instrument == 'GBM_NAI_03'
assert pha_info['pha'].mission == 'GLAST'
assert pha_info['pha'].is_poisson == True
assert pha_info['pha'].n_channels == ogip.n_data_points
assert pha_info['pha'].n_channels == len(pha_info['pha'].rates)
# Test that Poisson rates cannot call rate error
assert pha_info['pha'].rate_errors is None
assert sum(pha_info['pha'].sys_errors == np.zeros_like(
pha_info['pha'].rates)) == pha_info['bak'].n_channels
assert pha_info['pha'].response_file.split(
'/')[-1] == 'glg_cspec_n3_bn080916009_v07.rsp'
assert pha_info['pha'].scale_factor == 1.0
assert pha_info['bak'].background_file is None
# Test that we cannot get a bak file
#
#
# with pytest.raises(KeyError):
#
# _ = pha_info['bak'].background_file
# Test that we cannot get a anc file
# with pytest.raises(KeyError):
#
# _ = pha_info['bak'].ancillary_file
# Test that we cannot get a RSP file
assert pha_info['bak'].response_file is None
assert pha_info['bak'].ancillary_file is None
# with pytest.raises(AttributeError):
# _ = pha_info['bak'].response_file
assert pha_info['bak'].instrument == 'GBM_NAI_03'
assert pha_info['bak'].mission == 'GLAST'
assert pha_info['bak'].is_poisson == False
assert pha_info['bak'].n_channels == ogip.n_data_points
assert pha_info['bak'].n_channels == len(pha_info['pha'].rates)
assert len(pha_info['bak'].rate_errors) == pha_info['bak'].n_channels
assert sum(pha_info['bak'].sys_errors == np.zeros_like(
pha_info['pha'].rates)) == pha_info['bak'].n_channels
assert pha_info['bak'].scale_factor == 1.0
assert isinstance(pha_info['rsp'], OGIPResponse)