def test_extract(
pars,
results,
observations_hess_dl3,
spectrum_dataset_crab_fine,
reflected_regions_bkg_maker,
):
"""Test quantitative output for various configs"""
safe_mask_maker = SafeMaskMaker()
maker = SpectrumDatasetMaker(
containment_correction=pars["containment_correction"])
obs = observations_hess_dl3[0]
dataset = maker.run(spectrum_dataset_crab_fine, obs)
dataset = reflected_regions_bkg_maker.run(dataset, obs)
dataset = safe_mask_maker.run(dataset, obs)
aeff_actual = dataset.aeff.data.evaluate(energy=5 * u.TeV)
edisp_actual = dataset.edisp.data.evaluate(e_true=5 * u.TeV,
e_reco=5.2 * u.TeV)
assert_quantity_allclose(aeff_actual, results["aeff"], rtol=1e-3)
assert_quantity_allclose(edisp_actual, results["edisp"], rtol=1e-3)
# TODO: Introduce assert_stats_allclose
info = dataset.info_dict()
assert info["n_on"] == results["n_on"]
assert_allclose(info["significance"], results["sigma"], atol=1e-2)
gti_obs = obs.gti.table
gti_dataset = dataset.gti.table
assert_allclose(gti_dataset["START"], gti_obs["START"])
assert_allclose(gti_dataset["STOP"], gti_obs["STOP"])
def _spectrum_extraction(self):
"""Run all steps for the spectrum extraction."""
log.info("Reducing spectrum datasets.")
datasets_settings = self.config.datasets
on_lon = datasets_settings.on_region.lon
on_lat = datasets_settings.on_region.lat
on_center = SkyCoord(on_lon,
on_lat,
frame=datasets_settings.on_region.frame)
on_region = CircleSkyRegion(on_center,
datasets_settings.on_region.radius)
maker_config = {}
if datasets_settings.containment_correction:
maker_config[
"containment_correction"] = datasets_settings.containment_correction
e_reco = self._make_energy_axis(
datasets_settings.geom.axes.energy).edges
maker_config["selection"] = ["counts", "aeff", "edisp"]
dataset_maker = SpectrumDatasetMaker(**maker_config)
bkg_maker_config = {}
if datasets_settings.background.exclusion:
exclusion_region = Map.read(datasets_settings.background.exclusion)
bkg_maker_config["exclusion_mask"] = exclusion_region
bkg_maker = ReflectedRegionsBackgroundMaker(**bkg_maker_config)
safe_mask_selection = self.config.datasets.safe_mask.methods
safe_mask_settings = self.config.datasets.safe_mask.settings
safe_mask_maker = SafeMaskMaker(methods=safe_mask_selection,
**safe_mask_settings)
e_true = self._make_energy_axis(
datasets_settings.geom.axes.energy_true).edges
reference = SpectrumDataset.create(e_reco=e_reco,
e_true=e_true,
region=on_region)
datasets = []
for obs in self.observations:
log.info(f"Processing observation {obs.obs_id}")
dataset = dataset_maker.run(reference.copy(), obs)
dataset = bkg_maker.run(dataset, obs)
if dataset.counts_off is None:
log.info(
f"No OFF region found for observation {obs.obs_id}. Discarding."
)
continue
dataset = safe_mask_maker.run(dataset, obs)
log.debug(dataset)
datasets.append(dataset)
self.datasets = Datasets(datasets)
if self.config.datasets.stack:
stacked = self.datasets.stack_reduce(name="stacked")
self.datasets = Datasets([stacked])
def test_safe_mask_maker_dc1(spectrum_dataset_gc, observations_cta_dc1):
safe_mask_maker = SafeMaskMaker(methods=["edisp-bias", "aeff-max"])
obs = observations_cta_dc1[0]
maker = SpectrumDatasetMaker()
dataset = maker.run(spectrum_dataset_gc, obs)
dataset = safe_mask_maker.run(dataset, obs)
assert_allclose(dataset.energy_range[0].value, 3.162278, rtol=1e-3)
assert dataset.energy_range[0].unit == "TeV"
def _spectrum_extraction(self):
"""Run all steps for the spectrum extraction."""
region = self.settings["datasets"]["geom"]["region"]
log.info("Reducing spectrum datasets.")
on_lon = Angle(region["center"][0])
on_lat = Angle(region["center"][1])
on_center = SkyCoord(on_lon, on_lat, frame=region["frame"])
on_region = CircleSkyRegion(on_center, Angle(region["radius"]))
maker_config = {}
if "containment_correction" in self.settings["datasets"]:
maker_config["containment_correction"] = self.settings["datasets"][
"containment_correction"
]
params = self.settings["datasets"]["geom"]["axes"][0]
e_reco = MapAxis.from_bounds(**params).edges
maker_config["e_reco"] = e_reco
# TODO: remove hard-coded e_true and make it configurable
maker_config["e_true"] = np.logspace(-2, 2.5, 109) * u.TeV
maker_config["region"] = on_region
dataset_maker = SpectrumDatasetMaker(**maker_config)
bkg_maker_config = {}
background = self.settings["datasets"]["background"]
if "exclusion_mask" in background:
map_hdu = {}
filename = background["exclusion_mask"]["filename"]
if "hdu" in background["exclusion_mask"]:
map_hdu = {"hdu": background["exclusion_mask"]["hdu"]}
exclusion_region = Map.read(filename, **map_hdu)
bkg_maker_config["exclusion_mask"] = exclusion_region
if background["background_estimator"] == "reflected":
reflected_bkg_maker = ReflectedRegionsBackgroundMaker(**bkg_maker_config)
else:
# TODO: raise error?
log.info("Background estimation only for reflected regions method.")
safe_mask_maker = SafeMaskMaker(methods=["aeff-default", "aeff-max"])
datasets = []
for obs in self.observations:
log.info(f"Processing observation {obs.obs_id}")
selection = ["counts", "aeff", "edisp"]
dataset = dataset_maker.run(obs, selection=selection)
dataset = reflected_bkg_maker.run(dataset, obs)
dataset = safe_mask_maker.run(dataset, obs)
log.debug(dataset)
datasets.append(dataset)
self.datasets = Datasets(datasets)
if self.settings["datasets"]["stack-datasets"]:
stacked = self.datasets.stack_reduce()
stacked.name = "stacked"
self.datasets = Datasets([stacked])
def data_prep():
data_store = DataStore.from_dir("$GAMMAPY_DATA/hess-dl3-dr1/")
OBS_ID = 23523
obs_ids = OBS_ID * np.ones(N_OBS)
observations = data_store.get_observations(obs_ids)
target_position = SkyCoord(ra=83.63, dec=22.01, unit="deg", frame="icrs")
on_region_radius = Angle("0.11 deg")
on_region = CircleSkyRegion(center=target_position, radius=on_region_radius)
exclusion_region = CircleSkyRegion(
center=SkyCoord(183.604, -8.708, unit="deg", frame="galactic"),
radius=0.5 * u.deg,
)
skydir = target_position.galactic
exclusion_mask = Map.create(
npix=(150, 150), binsz=0.05, skydir=skydir, proj="TAN", coordsys="GAL"
)
mask = exclusion_mask.geom.region_mask([exclusion_region], inside=False)
exclusion_mask.data = mask
e_reco = MapAxis.from_bounds(0.1, 40, nbin=40, interp="log", unit="TeV").edges
e_true = MapAxis.from_bounds(0.05, 100, nbin=200, interp="log", unit="TeV").edges
dataset_maker = SpectrumDatasetMaker(
region=on_region, e_reco=e_reco, e_true=e_true, containment_correction=True
)
bkg_maker = ReflectedRegionsBackgroundMaker(exclusion_mask=exclusion_mask)
safe_mask_masker = SafeMaskMaker(methods=["aeff-max"], aeff_percent=10)
spectral_model = PowerLawSpectralModel(
index=2, amplitude=2e-11 * u.Unit("cm-2 s-1 TeV-1"), reference=1 * u.TeV
)
spatial_model = PointSpatialModel(
lon_0=target_position.ra, lat_0=target_position.dec, frame="icrs"
)
spatial_model.lon_0.frozen = True
spatial_model.lat_0.frozen = True
sky_model = SkyModel(
spatial_model=spatial_model, spectral_model=spectral_model, name=""
)
# Data preparation
datasets = []
for ind, observation in enumerate(observations):
dataset = dataset_maker.run(observation, selection=["counts", "aeff", "edisp"])
dataset_on_off = bkg_maker.run(dataset, observation)
dataset_on_off = safe_mask_masker.run(dataset_on_off, observation)
dataset_on_off.name = f"dataset{ind}"
dataset_on_off.models = sky_model
datasets.append(dataset_on_off)
return Datasets(datasets)
def data_prep():
data_store = DataStore.from_dir("$GAMMAPY_DATA/hess-dl3-dr1/")
OBS_ID = 23523
obs_ids = OBS_ID * np.ones(N_OBS)
observations = data_store.get_observations(obs_ids)
target_position = SkyCoord(ra=83.63308, dec=22.01450, unit="deg")
e_reco = MapAxis.from_bounds(0.1, 40, nbin=40, interp="log",
unit="TeV").edges
e_true = MapAxis.from_bounds(0.05, 100, nbin=200, interp="log",
unit="TeV").edges
on_region_radius = Angle("0.11 deg")
on_region = CircleSkyRegion(center=target_position,
radius=on_region_radius)
dataset_maker = SpectrumDatasetMaker(containment_correction=True,
selection=["counts", "aeff", "edisp"])
empty = SpectrumDatasetOnOff.create(region=on_region,
e_reco=e_reco,
e_true=e_true)
bkg_maker = ReflectedRegionsBackgroundMaker()
safe_mask_masker = SafeMaskMaker(methods=["aeff-max"], aeff_percent=10)
spectral_model = PowerLawSpectralModel(index=2.6,
amplitude=2.0e-11 *
u.Unit("1 / (cm2 s TeV)"),
reference=1 * u.TeV)
spectral_model.index.frozen = False
model = spectral_model.copy()
model.name = "crab"
datasets_1d = []
for observation in observations:
dataset = dataset_maker.run(dataset=empty.copy(),
observation=observation)
dataset_on_off = bkg_maker.run(dataset, observation)
dataset_on_off = safe_mask_masker.run(dataset_on_off, observation)
datasets_1d.append(dataset_on_off)
for dataset in datasets_1d:
model = spectral_model.copy()
model.name = "crab"
dataset.model = model
return datasets_1d
def test_compute_energy_threshold(self, spectrum_dataset_crab_fine,
observations_hess_dl3):
maker = SpectrumDatasetMaker(containment_correction=True)
safe_mask_maker = SafeMaskMaker(methods=["aeff-max"], aeff_percent=10)
obs = observations_hess_dl3[0]
dataset = maker.run(spectrum_dataset_crab_fine, obs)
dataset = safe_mask_maker.run(dataset, obs)
actual = dataset.energy_range[0]
assert_quantity_allclose(actual, 0.8799225 * u.TeV, rtol=1e-3)
def data(self) -> SpectrumDataset:
"""Actual event data in form of a SpectrumDataset.
"""
dataset_empty = SpectrumDataset.create(e_reco=self.energy_axis,
e_true=self.energy_axis,
region=self.on_region)
maker = SpectrumDatasetMaker(containment_correction=False,
selection=["background", "aeff", "edisp"])
dataset = maker.run(dataset_empty, self.obs)
dataset.models = self.true_model
dataset.fake()
return dataset
def data_prep():
data_store = DataStore.from_dir("$GAMMAPY_DATA/hess-dl3-dr1/")
OBS_ID = 23523
obs_ids = OBS_ID * np.ones(N_OBS)
observations = data_store.get_observations(obs_ids)
target_position = SkyCoord(ra=83.63, dec=22.01, unit="deg", frame="icrs")
on_region_radius = Angle("0.11 deg")
on_region = CircleSkyRegion(center=target_position,
radius=on_region_radius)
exclusion_region = CircleSkyRegion(
center=SkyCoord(183.604, -8.708, unit="deg", frame="galactic"),
radius=0.5 * u.deg,
)
skydir = target_position.galactic
exclusion_mask = Map.create(npix=(150, 150),
binsz=0.05,
skydir=skydir,
proj="TAN",
coordsys="GAL")
mask = exclusion_mask.geom.region_mask([exclusion_region], inside=False)
exclusion_mask.data = mask
e_reco = MapAxis.from_bounds(0.1, 40, nbin=40, interp="log",
unit="TeV").edges
e_true = MapAxis.from_bounds(0.05, 100, nbin=200, interp="log",
unit="TeV").edges
stacked = SpectrumDatasetOnOff.create(e_reco=e_reco, e_true=e_true)
stacked.name = "stacked"
dataset_maker = SpectrumDatasetMaker(region=on_region,
e_reco=e_reco,
e_true=e_true,
containment_correction=False)
bkg_maker = ReflectedRegionsBackgroundMaker(exclusion_mask=exclusion_mask)
safe_mask_masker = SafeMaskMaker(methods=["aeff-max"], aeff_percent=10)
for observation in observations:
dataset = dataset_maker.run(observation,
selection=["counts", "aeff", "edisp"])
dataset_on_off = bkg_maker.run(dataset, observation)
dataset_on_off = safe_mask_masker.run(dataset_on_off, observation)
stacked.stack(dataset_on_off)
return stacked
def test_spectrum_dataset_maker_hess_dl3(spectrum_dataset_crab,
observations_hess_dl3):
datasets = []
maker = SpectrumDatasetMaker()
for obs in observations_hess_dl3:
dataset = maker.run(spectrum_dataset_crab, obs)
datasets.append(dataset)
assert_allclose(datasets[0].counts.data.sum(), 100)
assert_allclose(datasets[1].counts.data.sum(), 92)
assert_allclose(datasets[0].livetime.value, 1581.736758)
assert_allclose(datasets[1].livetime.value, 1572.686724)
assert_allclose(datasets[0].background.data.sum(), 7.74732, rtol=1e-5)
assert_allclose(datasets[1].background.data.sum(), 6.118879, rtol=1e-5)
def test_spectrum_dataset_maker_hess_cta(spectrum_dataset_gc,
observations_cta_dc1):
maker = SpectrumDatasetMaker()
datasets = []
for obs in observations_cta_dc1:
dataset = maker.run(spectrum_dataset_gc, obs)
datasets.append(dataset)
assert_allclose(datasets[0].counts.data.sum(), 53)
assert_allclose(datasets[1].counts.data.sum(), 47)
assert_allclose(datasets[0].livetime.value, 1764.000034)
assert_allclose(datasets[1].livetime.value, 1764.000034)
assert_allclose(datasets[0].background.data.sum(), 2.238345, rtol=1e-5)
assert_allclose(datasets[1].background.data.sum(), 2.164593, rtol=1e-5)
def test_safe_mask_maker_dl3(spectrum_dataset_crab, observations_hess_dl3):
safe_mask_maker = SafeMaskMaker()
maker = SpectrumDatasetMaker()
obs = observations_hess_dl3[0]
dataset = maker.run(spectrum_dataset_crab, obs)
dataset = safe_mask_maker.run(dataset, obs)
assert_allclose(dataset.energy_range[0].value, 1)
assert dataset.energy_range[0].unit == "TeV"
mask_safe = safe_mask_maker.make_mask_energy_aeff_max(dataset)
assert mask_safe.sum() == 4
mask_safe = safe_mask_maker.make_mask_energy_edisp_bias(dataset)
assert mask_safe.sum() == 3
mask_safe = safe_mask_maker.make_mask_energy_bkg_peak(dataset)
assert mask_safe.sum() == 3
def test_run(observations, phase_bkg_maker):
maker = SpectrumDatasetMaker()
e_reco = np.logspace(0, 2, 5) * u.TeV
e_true = np.logspace(-0.5, 2, 11) * u.TeV
pos = SkyCoord("08h35m20.65525s", "-45d10m35.1545s", frame="icrs")
radius = Angle(0.2, "deg")
region = SphericalCircleSkyRegion(pos, radius)
dataset_empty = SpectrumDataset.create(e_reco, e_true, region=region)
obs = observations["111630"]
dataset = maker.run(dataset_empty, obs)
dataset_on_off = phase_bkg_maker.run(dataset, obs)
assert_allclose(dataset_on_off.acceptance, 0.1)
assert_allclose(dataset_on_off.acceptance_off, 0.3)
assert_allclose(dataset_on_off.counts.data.sum(), 28)
assert_allclose(dataset_on_off.counts_off.data.sum(), 57)
def run_analysis_1d(target_dict):
"""Run spectral analysis for the selected target"""
tag = target_dict["tag"]
name = target_dict["name"]
log.info(f"running 1d analysis, {tag}")
path_res = Path(tag + "/results/")
ra = target_dict["ra"]
dec = target_dict["dec"]
on_size = target_dict["on_size"]
e_decorr = target_dict["e_decorr"]
target_pos = SkyCoord(ra, dec, unit="deg", frame="icrs")
on_radius = Angle(on_size * u.deg)
containment_corr = True
# Observations selection
data_store = DataStore.from_dir("$GAMMAPY_DATA/hess-dl3-dr1/")
mask = data_store.obs_table["TARGET_NAME"] == name
obs_table = data_store.obs_table[mask]
observations = data_store.get_observations(obs_table["OBS_ID"])
if DEBUG is True:
observations = [observations[0]]
# Reflected regions background estimation
on_region = CircleSkyRegion(center=target_pos, radius=on_radius)
dataset_maker = SpectrumDatasetMaker(
region=on_region,
e_reco=E_RECO,
e_true=E_RECO,
containment_correction=containment_corr,
)
bkg_maker = ReflectedRegionsBackgroundMaker()
safe_mask_masker = SafeMaskMaker(methods=["edisp-bias"], bias_percent=10)
datasets = []
for observation in observations:
dataset = dataset_maker.run(observation, selection=["counts", "aeff", "edisp"])
dataset_on_off = bkg_maker.run(dataset, observation)
dataset_on_off = safe_mask_masker.run(dataset_on_off, observation)
datasets.append(dataset_on_off)
# Fit spectrum
model = PowerLawSpectralModel(
index=2, amplitude=2e-11 * u.Unit("cm-2 s-1 TeV-1"), reference=e_decorr * u.TeV
)
for dataset in datasets:
dataset.model = model
fit_joint = Fit(datasets)
result_joint = fit_joint.run()
parameters = model.parameters
parameters.covariance = result_joint.parameters.covariance
write_fit_summary(parameters, str(path_res / "results-summary-fit-1d.yaml"))
# Flux points
fpe = FluxPointsEstimator(datasets=datasets, e_edges=FLUXP_EDGES)
flux_points = fpe.run()
flux_points.table["is_ul"] = flux_points.table["ts"] < 4
keys = ["e_ref", "e_min", "e_max", "dnde", "dnde_errp", "dnde_errn", "is_ul"]
flux_points.table_formatted[keys].write(
path_res / "flux-points-1d.ecsv", format="ascii.ecsv"
)
dataset_empty = SpectrumDataset.create(
e_reco=e_reco, e_true=e_true, region=on_region
)
dataset_maker = SpectrumDatasetMaker()
phase_bkg_maker = PhaseBackgroundMaker(
on_phase=on_phase_range, off_phase=off_phase_range
)
safe_mask_maker = SafeMaskMaker(
methods=["aeff-default", "edisp-bias"], bias_percent=20
)
datasets = []
for obs in obs_list_vela:
dataset = dataset_maker.run(dataset_empty, obs)
dataset_on_off = phase_bkg_maker.run(dataset, obs)
dataset_on_off = safe_mask_maker.run(dataset_on_off, obs)
datasets.append(dataset_on_off)
# Now let's a look at the datasets we just created:
# In[ ]:
datasets[0].peek()
# Now we'll fit a model to the spectrum with the `Fit` class. First we load a power law model with an initial value for the index and the amplitude and then wo do a likelihood fit. The fit results are printed below.
crab_position = SkyCoord(83.63, 22.01, unit="deg", frame="icrs")
# The ON region center is defined in the icrs frame. The angle is defined w.r.t. to its axis.
rectangle = RectangleSkyRegion(
center=crab_position, width=0.5 * u.deg, height=0.4 * u.deg, angle=0 * u.deg
)
bkg_maker = ReflectedRegionsBackgroundMaker(min_distance=0.1 * u.rad)
dataset_maker = SpectrumDatasetMaker(
region=rectangle, e_reco=np.logspace(-1, 2, 30) * u.TeV
)
datasets = []
for obs in observations:
dataset = dataset_maker.run(obs, selection=["counts"])
dataset_on_off = bkg_maker.run(observation=obs, dataset=dataset)
datasets.append(dataset_on_off)
m = Map.create(skydir=crab_position, width=(8, 8), proj="TAN")
_, ax, _ = m.plot(vmin=-1, vmax=0)
rectangle.to_pixel(ax.wcs).plot(ax=ax, color="black")
plot_spectrum_datasets_off_regions(datasets=datasets, ax=ax)
plt.show()
