def simulate_single(self,
pointing,
models=None,
empty=None,
random_state="random-seed"):
obs = Observation.create(pointing=pointing,
livetime=self.livetime,
irfs=self.get_irf())
maker = MapDatasetMaker(
selection=["exposure", "background", "psf", "edisp"])
maker_safe_mask = SafeMaskMaker(methods=["offset-max"],
offset_max=2.0 * u.deg)
dataset = maker.run(empty, obs)
dataset = maker_safe_mask.run(dataset, obs)
dataset.models = Models([models])
#fluctuate the background - gaussian fluctuations
bkg_factor = np.random.normal(self.mean_bkg, self.sigma_bkg)
while bkg_factor < 0.0:
bkg_factor = np.random.normal(self.mean_bkg, self.sigma_bkg)
dataset.background.data = bkg_factor * dataset.background.data
self.bkg_norms.append(bkg_factor)
#Poission fluctuate source + background
dataset.fake()
dataset.models = None #remove the model on the dataset
dataset.background.data /= bkg_factor # restore the old background
return dataset
def test_adaptive_ring_bkg_maker(pars, geom, observations, exclusion_mask):
adaptive_ring_bkg_maker = AdaptiveRingBackgroundMaker(
r_in="0.2 deg",
width="0.3 deg",
r_out_max="2 deg",
stepsize="0.2 deg",
exclusion_mask=exclusion_mask,
method=pars["method"],
)
safe_mask_maker = SafeMaskMaker(methods=["offset-max"], offset_max="2 deg")
map_dataset_maker = MapDatasetMaker(
selection=["counts", "background", "exposure"])
obs = observations[pars["obs_idx"]]
dataset = MapDataset.create(geom).cutout(obs.pointing_radec, width="4 deg")
dataset = map_dataset_maker.run(dataset, obs)
dataset = safe_mask_maker.run(dataset, obs)
dataset = dataset.to_image()
dataset_on_off = adaptive_ring_bkg_maker.run(dataset)
mask = dataset.mask_safe
assert_allclose(dataset_on_off.counts_off.data[mask].sum(),
pars["counts_off"])
assert_allclose(dataset_on_off.acceptance_off.data[mask].sum(),
pars["acceptance_off"])
assert_allclose(dataset_on_off.alpha.data[0][100][100], pars["alpha"])
assert_allclose(dataset_on_off.exposure.data[0][100][100],
pars["exposure"])
def test_safe_mask_maker_bkg_invalid(observations_hess_dl3):
obs = observations_hess_dl3[0]
axis = MapAxis.from_bounds(0.1,
10,
nbin=16,
unit="TeV",
name="energy",
interp="log")
axis_true = MapAxis.from_bounds(0.1,
50,
nbin=30,
unit="TeV",
name="energy_true",
interp="log")
geom = WcsGeom.create(npix=(9, 9), axes=[axis], skydir=obs.pointing_radec)
empty_dataset = MapDataset.create(geom=geom, energy_axis_true=axis_true)
dataset_maker = MapDatasetMaker()
safe_mask_maker_nonan = SafeMaskMaker([])
dataset = dataset_maker.run(empty_dataset, obs)
bkg = dataset.background.data
bkg[0, 0, 0] = np.nan
mask_nonan = safe_mask_maker_nonan.make_mask_bkg_invalid(dataset)
assert not mask_nonan[0, 0, 0]
assert_allclose(bkg[mask_nonan].max(), 20.656366)
dataset = safe_mask_maker_nonan.run(dataset, obs)
assert_allclose(dataset.mask_safe, mask_nonan)
def test_ring_bkg_maker(geom, observations, exclusion_mask):
ring_bkg_maker = RingBackgroundMaker(r_in="0.2 deg",
width="0.3 deg",
exclusion_mask=exclusion_mask)
safe_mask_maker = SafeMaskMaker(methods=["offset-max"], offset_max="2 deg")
map_dataset_maker = MapDatasetMaker(
selection=["counts", "background", "exposure"])
reference = MapDataset.create(geom)
datasets = []
for obs in observations:
cutout = reference.cutout(obs.pointing_radec, width="4 deg")
dataset = map_dataset_maker.run(cutout, obs)
dataset = safe_mask_maker.run(dataset, obs)
dataset = dataset.to_image()
dataset_on_off = ring_bkg_maker.run(dataset)
datasets.append(dataset_on_off)
mask = dataset.mask_safe
assert_allclose(datasets[0].counts_off.data[mask].sum(), 2511333)
assert_allclose(datasets[1].counts_off.data[mask].sum(), 2143577.0)
assert_allclose(datasets[0].acceptance_off.data[mask].sum(),
2961300,
rtol=1e-5)
assert_allclose(datasets[1].acceptance_off.data[mask].sum(),
2364657.2,
rtol=1e-5)
assert_allclose(datasets[0].alpha.data[0][100][100],
0.00063745599,
rtol=1e-5)
assert_allclose(datasets[0].exposure.data[0][100][100],
806254444.8480084,
rtol=1e-5)
def test_make_meta_table(observations):
maker_obs = MapDatasetMaker()
map_dataset_meta_table = maker_obs.make_meta_table(observation=observations[0])
assert_allclose(map_dataset_meta_table["RA_PNT"], 267.68121338)
assert_allclose(map_dataset_meta_table["DEC_PNT"], -29.6075)
assert_allclose(map_dataset_meta_table["OBS_ID"], 110380)
def simulate_map_dataset(random_state=0, name=None):
irfs = load_cta_irfs(
"$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
)
skydir = SkyCoord("0 deg", "0 deg", frame="galactic")
edges = np.logspace(-1, 2, 15) * u.TeV
energy_axis = MapAxis.from_edges(edges=edges, name="energy", interp="log")
geom = WcsGeom.create(
skydir=skydir, width=(4, 4), binsz=0.1, axes=[energy_axis], frame="galactic"
)
gauss = GaussianSpatialModel(
lon_0="0 deg", lat_0="0 deg", sigma="0.4 deg", frame="galactic"
)
pwl = PowerLawSpectralModel(amplitude="1e-11 cm-2 s-1 TeV-1")
skymodel = SkyModel(spatial_model=gauss, spectral_model=pwl, name="source")
obs = Observation.create(pointing=skydir, livetime=1 * u.h, irfs=irfs)
empty = MapDataset.create(geom, name=name)
maker = MapDatasetMaker(selection=["exposure", "background", "psf", "edisp"])
dataset = maker.run(empty, obs)
dataset.models.append(skymodel)
dataset.fake(random_state=random_state)
return dataset
def prepare_dataset_simple(filename_dataset):
"""Prepare dataset for a given skymodel."""
log.info(f"Reading {IRF_FILE}")
irfs = load_cta_irfs(IRF_FILE)
edisp_gauss = EnergyDispersion2D.from_gauss(
e_true=ENERGY_AXIS_TRUE.edges,
migra=MIGRA_AXIS.edges,
sigma=0.1,
bias=0,
offset=[0, 2, 4, 6, 8] * u.deg,
)
irfs["edisp"] = edisp_gauss
# irfs["aeff"].data.data = np.ones_like(irfs["aeff"].data.data) * 1e6
observation = Observation.create(
obs_id=1001, pointing=POINTING, livetime=LIVETIME, irfs=irfs
)
empty = MapDataset.create(
WCS_GEOM, energy_axis_true=ENERGY_AXIS_TRUE, migra_axis=MIGRA_AXIS
)
# maker = MapDatasetMaker(selection=["exposure", "edisp"])
# maker = MapDatasetMaker(selection=["exposure", "edisp", "background"])
maker = MapDatasetMaker(selection=["exposure", "edisp", "psf", "background"])
dataset = maker.run(empty, observation)
filename_dataset.parent.mkdir(exist_ok=True, parents=True)
log.info(f"Writing {filename_dataset}")
dataset.write(filename_dataset, overwrite=True)
def test_make_map_no_count(observations):
dataset = MapDataset.create(geom((0.1, 1, 10)))
maker_obs = MapDatasetMaker(selection=["exposure"])
map_dataset = maker_obs.run(dataset, observation=observations[0])
assert map_dataset.counts is not None
assert_allclose(map_dataset.counts.data, 0)
assert map_dataset.counts.geom == dataset.counts.geom
def data_prep():
data_store = DataStore.from_dir("$GAMMAPY_DATA/cta-1dc/index/gps/")
OBS_ID = 110380
obs_ids = OBS_ID * np.ones(N_OBS)
observations = data_store.get_observations(obs_ids)
energy_axis = MapAxis.from_bounds(0.1,
10,
nbin=10,
unit="TeV",
name="energy",
interp="log")
geom = WcsGeom.create(
skydir=(0, 0),
binsz=0.02,
width=(10, 8),
frame="galactic",
proj="CAR",
axes=[energy_axis],
)
energy_axis_true = MapAxis.from_bounds(0.05,
20,
nbin=30,
unit="TeV",
name="energy_true",
interp="log")
offset_max = 4 * u.deg
maker = MapDatasetMaker()
safe_mask_maker = SafeMaskMaker(methods=["offset-max"],
offset_max=offset_max)
stacked = MapDataset.create(geom=geom, energy_axis_true=energy_axis_true)
spatial_model = PointSpatialModel(lon_0="-0.05 deg",
lat_0="-0.05 deg",
frame="galactic")
spectral_model = ExpCutoffPowerLawSpectralModel(
index=2,
amplitude=3e-12 * u.Unit("cm-2 s-1 TeV-1"),
reference=1.0 * u.TeV,
lambda_=0.1 / u.TeV,
)
model = SkyModel(spatial_model=spatial_model,
spectral_model=spectral_model,
name="gc-source")
datasets = Datasets([])
for idx, obs in enumerate(observations):
cutout = stacked.cutout(obs.pointing_radec,
width=2 * offset_max,
name=f"dataset{idx}")
dataset = maker.run(cutout, obs)
dataset = safe_mask_maker.run(dataset, obs)
dataset.models = [model, FoVBackgroundModel(dataset_name=dataset.name)]
datasets.append(dataset)
return datasets
def test_safe_mask_maker(observations, caplog):
obs = observations[0]
axis = MapAxis.from_bounds(0.1,
10,
nbin=16,
unit="TeV",
name="energy",
interp="log")
axis_true = MapAxis.from_bounds(0.1,
50,
nbin=30,
unit="TeV",
name="energy_true",
interp="log")
geom = WcsGeom.create(npix=(11, 11),
axes=[axis],
skydir=obs.pointing_radec)
empty_dataset = MapDataset.create(geom=geom, energy_axis_true=axis_true)
dataset_maker = MapDatasetMaker()
safe_mask_maker = SafeMaskMaker(offset_max="3 deg",
bias_percent=0.02,
position=obs.pointing_radec)
fixed_offset = 1.5 * u.deg
safe_mask_maker_offset = SafeMaskMaker(offset_max="3 deg",
bias_percent=0.02,
fixed_offset=fixed_offset)
dataset = dataset_maker.run(empty_dataset, obs)
mask_offset = safe_mask_maker.make_mask_offset_max(dataset=dataset,
observation=obs)
assert_allclose(mask_offset.sum(), 109)
mask_energy_aeff_default = safe_mask_maker.make_mask_energy_aeff_default(
dataset=dataset, observation=obs)
assert_allclose(mask_energy_aeff_default.data.sum(), 1936)
mask_aeff_max = safe_mask_maker.make_mask_energy_aeff_max(dataset)
mask_aeff_max_offset = safe_mask_maker_offset.make_mask_energy_aeff_max(
dataset, obs)
assert_allclose(mask_aeff_max.data.sum(), 1210)
assert_allclose(mask_aeff_max_offset.data.sum(), 1210)
mask_edisp_bias = safe_mask_maker.make_mask_energy_edisp_bias(dataset)
mask_edisp_bias_offset = safe_mask_maker_offset.make_mask_energy_edisp_bias(
dataset, obs)
assert_allclose(mask_edisp_bias.data.sum(), 1815)
assert_allclose(mask_edisp_bias_offset.data.sum(), 121)
mask_bkg_peak = safe_mask_maker.make_mask_energy_bkg_peak(dataset)
assert_allclose(mask_bkg_peak.data.sum(), 1815)
assert caplog.records[-1].levelname == "WARNING"
assert caplog.records[
-1].message == "No default thresholds defined for obs 110380"
def obs_dataset(geom, observation):
safe_mask_maker = SafeMaskMaker(methods=["offset-max"], offset_max="2 deg")
map_dataset_maker = MapDatasetMaker(selection=["counts", "background", "exposure"])
reference = MapDataset.create(geom)
cutout = reference.cutout(
observation.pointing_radec, width="4 deg", name="test-fov"
)
dataset = map_dataset_maker.run(cutout, observation)
dataset = safe_mask_maker.run(dataset, observation)
return dataset
def test_make_mean_psf(data_store):
psf = data_store.obs(23523).psf
geom = RegionGeom.create(region="icrs;point(83.63, 22.01)",
axes=[psf.rad_axis, psf.energy_axis])
maker = MapDatasetMaker()
psf_map_1 = maker.make_psf(geom=geom, observation=data_store.obs(23523))
psf_map_2 = maker.make_psf(geom=geom, observation=data_store.obs(23526))
psf_map_1.stack(psf_map_2)
psf = psf_map_1.get_energy_dependent_table_psf()
assert not np.isnan(psf.psf_value.value).any()
assert_allclose(psf.psf_value.value[22, 22], 12206.167892)
def test_datasetsmaker_map_2steps(observations_cta, makers_map, tmp_path):
makers = DatasetsMaker(
[MapDatasetMaker()],
stack_datasets=False,
cutout_mode="partial",
cutout_width="5 deg",
n_jobs=None,
)
dataset = get_mapdataset(name="2steps")
datasets = makers.run(dataset, observations_cta)
makers_list = [
SafeMaskMaker(methods=["offset-max"], offset_max="2 deg"),
FoVBackgroundMaker(method="scale"),
]
makers = DatasetsMaker(
makers_list,
stack_datasets=True,
cutout_mode="partial",
cutout_width="5 deg",
n_jobs=None,
)
datasets = makers.run(dataset, observations_cta, datasets)
counts = datasets[0].counts
assert counts.unit == ""
assert_allclose(counts.data.sum(), 46716, rtol=1e-5)
exposure = datasets[0].exposure
assert exposure.unit == "m2 s"
assert_allclose(exposure.data.mean(), 1.350841e09, rtol=3e-3)
def prepare_dataset(filename_dataset):
"""Prepare dataset for a given skymodel."""
log.info(f"Reading {IRF_FILE}")
irfs = load_cta_irfs(IRF_FILE)
observation = Observation.create(
obs_id=1001, pointing=POINTING, livetime=LIVETIME, irfs=irfs
)
empty = MapDataset.create(
WCS_GEOM, energy_axis_true=ENERGY_AXIS_TRUE, migra_axis=MIGRA_AXIS
)
maker = MapDatasetMaker(selection=["exposure", "background", "psf", "edisp"])
dataset = maker.run(empty, observation)
filename_dataset.parent.mkdir(exist_ok=True, parents=True)
log.info(f"Writing {filename_dataset}")
dataset.write(filename_dataset, overwrite=True)
def data_prep():
data_store = DataStore.from_dir("$GAMMAPY_DATA/cta-1dc/index/gps/")
OBS_ID = 110380
obs_ids = OBS_ID * np.ones(N_OBS)
observations = data_store.get_observations(obs_ids)
energy_axis = MapAxis.from_bounds(0.1,
10,
nbin=10,
unit="TeV",
name="energy",
interp="log")
geom = WcsGeom.create(
skydir=(0, 0),
binsz=0.05,
width=(10, 8),
frame="galactic",
proj="CAR",
axes=[energy_axis],
)
stacked = MapDataset.create(geom, name="stacked_ds")
maker = MapDatasetMaker()
safe_mask_maker = SafeMaskMaker(methods=["offset-max"], offset_max="4 deg")
for obs in observations:
dataset = maker.run(stacked, obs)
dataset = safe_mask_maker.run(dataset, obs)
stacked.stack(dataset)
spatial_model = PointSpatialModel(lon_0="0.01 deg",
lat_0="0.01 deg",
frame="galactic")
spectral_model = ExpCutoffPowerLawSpectralModel(
index=2,
amplitude=3e-12 * u.Unit("cm-2 s-1 TeV-1"),
reference=1.0 * u.TeV,
lambda_=0.1 / u.TeV,
)
model = SkyModel(spatial_model=spatial_model,
spectral_model=spectral_model,
name="gc-source")
stacked.models.append(model)
return Datasets([stacked])
def test_safe_mask_maker(observations):
obs = observations[0]
axis = MapAxis.from_bounds(0.1,
10,
nbin=16,
unit="TeV",
name="energy",
interp="log")
axis_true = MapAxis.from_bounds(0.1,
50,
nbin=30,
unit="TeV",
name="energy_true",
interp="log")
geom = WcsGeom.create(npix=(11, 11),
axes=[axis],
skydir=obs.pointing_radec)
empty_dataset = MapDataset.create(geom=geom, energy_axis_true=axis_true)
dataset_maker = MapDatasetMaker()
safe_mask_maker = SafeMaskMaker(offset_max="3 deg",
bias_percent=0.02,
position=obs.pointing_radec)
dataset = dataset_maker.run(empty_dataset, obs)
mask_offset = safe_mask_maker.make_mask_offset_max(dataset=dataset,
observation=obs)
assert_allclose(mask_offset.sum(), 109)
mask_energy_aeff_default = safe_mask_maker.make_mask_energy_aeff_default(
dataset=dataset, observation=obs)
assert_allclose(mask_energy_aeff_default.data.sum(), 1936)
mask_aeff_max = safe_mask_maker.make_mask_energy_aeff_max(dataset)
assert_allclose(mask_aeff_max.data.sum(), 1210)
mask_edisp_bias = safe_mask_maker.make_mask_energy_edisp_bias(dataset)
assert_allclose(mask_edisp_bias.data.sum(), 1815)
mask_bkg_peak = safe_mask_maker.make_mask_energy_bkg_peak(dataset)
assert_allclose(mask_bkg_peak.data.sum(), 1815)
def test_map_maker(pars, observations):
stacked = MapDataset.create(
geom=pars["geom"],
energy_axis_true=pars["e_true"],
binsz_irf=pars["binsz_irf"],
migra_axis=pars["migra"],
)
maker = MapDatasetMaker(
background_oversampling=pars.get("background_oversampling"))
safe_mask_maker = SafeMaskMaker(methods=["offset-max"], offset_max="2 deg")
for obs in observations:
cutout = stacked.cutout(position=obs.pointing_radec, width="4 deg")
dataset = maker.run(cutout, obs)
dataset = safe_mask_maker.run(dataset, obs)
stacked.stack(dataset)
counts = stacked.counts
assert counts.unit == ""
assert_allclose(counts.data.sum(), pars["counts"], rtol=1e-5)
exposure = stacked.exposure
assert exposure.unit == "m2 s"
assert_allclose(exposure.data.mean(), pars["exposure"], rtol=3e-3)
background = stacked.npred_background()
assert background.unit == ""
assert_allclose(background.data.sum(), pars["background"], rtol=1e-4)
image_dataset = stacked.to_image()
counts = image_dataset.counts
assert counts.unit == ""
assert_allclose(counts.data.sum(), pars["counts"], rtol=1e-4)
exposure = image_dataset.exposure
assert exposure.unit == "m2 s"
assert_allclose(exposure.data.sum(), pars["exposure_image"], rtol=1e-3)
background = image_dataset.npred_background()
assert background.unit == ""
assert_allclose(background.data.sum(), pars["background"], rtol=1e-4)
def test_map_maker_obs_with_migra(observations):
# Test for different spatial geoms and etrue, ereco bins
migra = MapAxis.from_edges(np.linspace(0, 2.0, 50), unit="", name="migra")
geom_reco = geom(ebounds=[0.1, 1, 10])
e_true = MapAxis.from_edges(
[0.1, 0.5, 2.5, 10.0], name="energy_true", unit="TeV", interp="log"
)
reference = MapDataset.create(
geom=geom_reco, energy_axis_true=e_true, migra_axis=migra, binsz_irf=1.0
)
maker_obs = MapDatasetMaker()
map_dataset = maker_obs.run(reference, observations[0])
assert map_dataset.counts.geom == geom_reco
assert isinstance(map_dataset.edisp, EDispMap)
assert map_dataset.edisp.edisp_map.data.shape == (3, 49, 5, 10)
assert map_dataset.edisp.exposure_map.data.shape == (3, 1, 5, 10)
def create_datasets_3d(observations, target_position):
# Target geometry definition
e_reco = MapAxis.from_energy_bounds(0.23, 20, 12, "TeV")
e_true = MapAxis.from_energy_bounds(0.1, 40, 40, "TeV", name="energy_true")
geom = WcsGeom.create(skydir=target_position,
width=(2, 2),
binsz=0.02,
axes=[e_reco])
exclusion_region = CircleSkyRegion(target_position, 0.3 * u.deg)
exclusion_mask = geom.region_mask([exclusion_region], inside=False)
offset_max = 2.0 * u.deg
#data reduction makers
maker = MapDatasetMaker()
bkg_maker = FoVBackgroundMaker(method="scale",
exclusion_mask=exclusion_mask)
safe_mask_maker = SafeMaskMaker(methods=["aeff-max", "offset-max"],
aeff_percent=10,
offset_max=offset_max)
datasets = []
dataset_empty = MapDataset.create(geom=geom, energy_axis_true=e_true)
for obs in observations:
cutout = dataset_empty.cutout(obs.pointing_radec, width=2 * offset_max)
# A MapDataset is filled in this cutout geometry
dataset = maker.run(cutout, obs)
# The data quality cut is applied
dataset = safe_mask_maker.run(dataset, obs)
# fit background model
dataset = bkg_maker.run(dataset)
print(
f"Background norm obs {obs.obs_id}: {dataset.background_model.spectral_model.norm.value:.2f}"
)
datasets.append(dataset)
return datasets
def test_minimal_datastore():
""" "Check that a standard analysis runs on a minimal datastore"""
energy_axis = MapAxis.from_energy_bounds(1,
10,
nbin=3,
per_decade=False,
unit="TeV",
name="energy")
geom = WcsGeom.create(
skydir=(83.633, 22.014),
binsz=0.5,
width=(2, 2),
frame="icrs",
proj="CAR",
axes=[energy_axis],
)
data_store = DataStore.from_dir("$GAMMAPY_DATA/tests/minimal_datastore")
observations = data_store.get_observations()
maker = MapDatasetMaker()
offset_max = 2.3 * u.deg
maker_safe_mask = SafeMaskMaker(methods=["offset-max"],
offset_max=offset_max)
circle = CircleSkyRegion(center=SkyCoord("83.63 deg", "22.14 deg"),
radius=0.2 * u.deg)
exclusion_mask = ~geom.region_mask(regions=[circle])
maker_fov = FoVBackgroundMaker(method="fit", exclusion_mask=exclusion_mask)
stacked = MapDataset.create(geom=geom, name="crab-stacked")
for obs in observations:
dataset = maker.run(stacked, obs)
dataset = maker_safe_mask.run(dataset, obs)
dataset = maker_fov.run(dataset)
stacked.stack(dataset)
assert_allclose(stacked.exposure.data.sum(), 6.01909e10)
assert_allclose(stacked.counts.data.sum(), 1446)
assert_allclose(stacked.background.data.sum(), 1445.9841)
def test_map_dataset_maker_hpx(geom_config_hpx, observations):
reference = MapDataset.create(**geom_config_hpx, binsz_irf=5 * u.deg)
maker = MapDatasetMaker()
safe_mask_maker = SafeMaskMaker(offset_max="2.5 deg",
methods=["aeff-default", "offset-max"])
dataset = maker.run(reference, observation=observations[0])
dataset = safe_mask_maker.run(dataset,
observation=observations[0]).to_masked()
assert_allclose(dataset.counts.data.sum(), 4264)
assert_allclose(dataset.background.data.sum(), 2964.5369, rtol=1e-5)
assert_allclose(dataset.exposure.data[4, 1000], 5.987e09, rtol=1e-4)
coords = SkyCoord([0, 3], [0, 0], frame="galactic", unit="deg")
coords = {"skycoord": coords, "energy": 1 * u.TeV}
assert_allclose(dataset.mask_safe.get_by_coord(coords), [True, False])
kernel = dataset.edisp.get_edisp_kernel()
assert_allclose(kernel.data.sum(axis=1)[3], 1, rtol=0.01)
def test_map_maker_obs(observations):
# Test for different spatial geoms and etrue, ereco bins
geom_reco = geom(ebounds=[0.1, 1, 10])
e_true = MapAxis.from_edges(
[0.1, 0.5, 2.5, 10.0], name="energy_true", unit="TeV", interp="log"
)
reference = MapDataset.create(
geom=geom_reco, energy_axis_true=e_true, binsz_irf=1.0
)
maker_obs = MapDatasetMaker()
map_dataset = maker_obs.run(reference, observations[0])
assert map_dataset.counts.geom == geom_reco
assert map_dataset.background_model.map.geom == geom_reco
assert map_dataset.edisp.edisp_map.data.shape == (3, 48, 5, 10)
assert map_dataset.edisp.exposure_map.data.shape == (3, 1, 5, 10)
assert map_dataset.psf.psf_map.data.shape == (3, 66, 5, 10)
assert map_dataset.psf.exposure_map.data.shape == (3, 1, 5, 10)
assert_allclose(map_dataset.gti.time_delta, 1800.0 * u.s)
def test_make_psf(pars, data_store):
energy_axis = pars["energy"]
rad_axis = pars["rad"]
psf = data_store.obs(23523).psf
if energy_axis is None:
energy_axis = psf.energy_axis
if rad_axis is None:
rad_axis = psf.rad_axis
geom = RegionGeom(
region=PointSkyRegion(SkyCoord(83.63, 22.01, unit="deg")),
axes=[rad_axis, energy_axis]
)
maker = MapDatasetMaker()
psf_map = maker.make_psf(geom=geom, observation=data_store.obs(23523))
psf = psf_map.get_energy_dependent_table_psf()
assert psf.energy.unit == "GeV"
assert psf.energy.shape == pars["energy_shape"]
assert_allclose(psf.energy.value[15], pars["psf_energy"], rtol=1e-3)
assert psf.rad.unit == "rad"
assert psf.rad.shape == pars["rad_shape"]
assert_allclose(psf.rad.value[15], pars["psf_rad"], rtol=1e-3)
assert psf.exposure.unit == "cm2 s"
assert psf.exposure.shape == pars["energy_shape"]
assert_allclose(psf.exposure.value[15], pars["psf_exposure"], rtol=1e-3)
assert psf.psf_value.unit == "sr-1"
assert psf.psf_value.shape == pars["psf_value_shape"]
assert_allclose(psf.psf_value.value[15, 50], pars["psf_value"], rtol=1e-3)
def _create_dataset_maker(self):
"""Create the Dataset Maker."""
log.debug("Creating the target Dataset Maker.")
datasets_settings = self.config.datasets
if datasets_settings.type == "3d":
maker = MapDatasetMaker(selection=datasets_settings.map_selection)
elif datasets_settings.type == "1d":
maker_config = {}
if datasets_settings.containment_correction:
maker_config[
"containment_correction"] = datasets_settings.containment_correction
maker_config["selection"] = ["counts", "exposure", "edisp"]
maker = SpectrumDatasetMaker(**maker_config)
return maker
def simulate():
irfs = load_cta_irfs(
"$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits"
)
center = SkyCoord(0.0, 0.0, unit="deg", frame="galactic")
energy_reco = MapAxis.from_edges(np.logspace(-1.0, 1.0, 10),
unit="TeV",
name="energy",
interp="log")
pointing = SkyCoord(0.5, 0.5, unit="deg", frame="galactic")
geom = WcsGeom.create(
skydir=center,
binsz=0.02,
width=(4, 4),
frame="galactic",
axes=[energy_reco],
)
energy_true = MapAxis.from_edges(np.logspace(-1.5, 1.5, 30),
unit="TeV",
name="energy_true",
interp="log")
spectral_model = PowerLawSpectralModel(index=3,
amplitude="1e-11 cm-2 s-1 TeV-1",
reference="1 TeV")
temporal_model = ExpDecayTemporalModel(t0="6 h", t_ref=gti_t0.mjd * u.d)
spatial_model = GaussianSpatialModel(lon_0="0.2 deg",
lat_0="0.1 deg",
sigma="0.3 deg",
frame="galactic")
model_simu = SkyModel(
spectral_model=spectral_model,
spatial_model=spatial_model,
temporal_model=temporal_model,
name="model-simu",
)
lvtm = np.ones(N_OBS) * 1.0 * u.hr
tstart = 1.0 * u.hr
datasets = []
for i in range(N_OBS):
obs = Observation.create(
pointing=pointing,
livetime=lvtm[i],
tstart=tstart,
irfs=irfs,
reference_time=gti_t0,
)
empty = MapDataset.create(geom,
name=f"dataset_{i}",
energy_axis_true=energy_true)
maker = MapDatasetMaker(
selection=["exposure", "background", "psf", "edisp"])
maker_safe_mask = SafeMaskMaker(methods=["offset-max"],
offset_max=4.0 * u.deg)
dataset = maker.run(empty, obs)
dataset = maker_safe_mask.run(dataset, obs)
dataset.models = [
model_simu,
FoVBackgroundModel(dataset_name=dataset.name)
]
dataset.fake()
datasets.append(dataset)
tstart = tstart + 2.0 * u.hr
return datasets
def make_datasets_example():
# Define which data to use and print some information
energy_axis = MapAxis.from_edges(
np.logspace(-1.0, 1.0, 4), unit="TeV", name="energy", interp="log"
)
geom0 = WcsGeom.create(
skydir=(0, 0),
binsz=0.1,
width=(1, 1),
frame="galactic",
proj="CAR",
axes=[energy_axis],
)
geom1 = WcsGeom.create(
skydir=(1, 0),
binsz=0.1,
width=(1, 1),
frame="galactic",
proj="CAR",
axes=[energy_axis],
)
geoms = [geom0, geom1]
sources_coords = [(0, 0), (0.9, 0.1)]
names = ["gc", "g09"]
models = []
for idx, (lon, lat) in enumerate(sources_coords):
spatial_model = PointSpatialModel(
lon_0=lon * u.deg, lat_0=lat * u.deg, frame="galactic"
)
spectral_model = ExpCutoffPowerLawSpectralModel(
index=2 * u.Unit(""),
amplitude=3e-12 * u.Unit("cm-2 s-1 TeV-1"),
reference=1.0 * u.TeV,
lambda_=0.1 / u.TeV,
)
model_ecpl = SkyModel(
spatial_model=spatial_model, spectral_model=spectral_model, name=names[idx]
)
models.append(model_ecpl)
# test to link a spectral parameter
params0 = models[0].spectral_model.parameters
params1 = models[1].spectral_model.parameters
params0.link("reference", params1["reference"])
# update the sky model
models[0].parameters.link("reference", params1["reference"])
obs_ids = [110380, 111140, 111159]
data_store = DataStore.from_dir("$GAMMAPY_DATA/cta-1dc/index/gps/")
diffuse_model = SkyDiffuseCube.read(
"$GAMMAPY_DATA/fermi_3fhl/gll_iem_v06_cutout.fits"
)
datasets_list = []
for idx, geom in enumerate(geoms):
observations = data_store.get_observations(obs_ids)
stacked = MapDataset.create(geom=geom)
stacked.background_model.name = "background_irf_" + names[idx]
maker = MapDatasetMaker(offset_max=4.0 * u.deg)
for obs in observations:
dataset = maker.run(stacked, obs)
stacked.stack(dataset)
stacked.psf = stacked.psf.get_psf_kernel(
position=geom.center_skydir, geom=geom, max_radius="0.3 deg"
)
stacked.name = names[idx]
stacked.models = models[idx] + diffuse_model
datasets_list.append(stacked)
datasets = Datasets(datasets_list)
dataset0 = datasets[0]
print("dataset0")
print("counts sum : ", dataset0.counts.data.sum())
print("expo sum : ", dataset0.exposure.data.sum())
print("bkg0 sum : ", dataset0.background_model.evaluate().data.sum())
datasets.write("$GAMMAPY_DATA/tests/models", prefix="gc_example_", overwrite=True)
def make_datasets_example():
# Define which data to use and print some information
energy_axis = MapAxis.from_edges(np.logspace(-1.0, 1.0, 4),
unit="TeV",
name="energy",
interp="log")
geom0 = WcsGeom.create(
skydir=(0, 0),
binsz=0.1,
width=(2, 2),
frame="galactic",
proj="CAR",
axes=[energy_axis],
)
geom1 = WcsGeom.create(
skydir=(1, 0),
binsz=0.1,
width=(2, 2),
frame="galactic",
proj="CAR",
axes=[energy_axis],
)
geoms = [geom0, geom1]
sources_coords = [(0, 0), (0.9, 0.1)]
names = ["gc", "g09"]
models = Models()
for idx, (lon, lat) in enumerate(sources_coords):
spatial_model = PointSpatialModel(lon_0=lon * u.deg,
lat_0=lat * u.deg,
frame="galactic")
spectral_model = ExpCutoffPowerLawSpectralModel(
index=2 * u.Unit(""),
amplitude=3e-12 * u.Unit("cm-2 s-1 TeV-1"),
reference=1.0 * u.TeV,
lambda_=0.1 / u.TeV,
)
model_ecpl = SkyModel(spatial_model=spatial_model,
spectral_model=spectral_model,
name=names[idx])
models.append(model_ecpl)
models["gc"].spectral_model.reference = models[
"g09"].spectral_model.reference
obs_ids = [110380, 111140, 111159]
data_store = DataStore.from_dir("$GAMMAPY_DATA/cta-1dc/index/gps/")
diffuse_spatial = TemplateSpatialModel.read(
"$GAMMAPY_DATA/fermi-3fhl-gc/gll_iem_v06_gc.fits.gz")
diffuse_model = SkyModel(PowerLawSpectralModel(), diffuse_spatial)
maker = MapDatasetMaker()
datasets = Datasets()
observations = data_store.get_observations(obs_ids)
for idx, geom in enumerate(geoms):
stacked = MapDataset.create(geom=geom, name=names[idx])
for obs in observations:
dataset = maker.run(stacked, obs)
stacked.stack(dataset)
bkg = stacked.models.pop(0)
stacked.models = [models[idx], diffuse_model, bkg]
datasets.append(stacked)
datasets.write(
"$GAMMAPY_DATA/tests/models",
prefix="gc_example",
overwrite=True,
write_covariance=False,
)
def makers_map():
return [
MapDatasetMaker(),
SafeMaskMaker(methods=["offset-max"], offset_max="2 deg"),
FoVBackgroundMaker(method="scale"),
]
def test_interpolate_map_dataset():
energy = MapAxis.from_energy_bounds("1 TeV", "300 TeV", nbin=5, name="energy")
energy_true = MapAxis.from_nodes(np.logspace(-1, 3, 20), name="energy_true", interp="log", unit="TeV")
# make dummy map IRFs
geom_allsky = WcsGeom.create(npix=(5, 3), proj="CAR", binsz=60, axes=[energy], skydir=(0, 0))
geom_allsky_true = geom_allsky.drop('energy').to_cube([energy_true])
#background
value = 30
bkg_map = Map.from_geom(geom_allsky, unit="")
bkg_map.data = value*np.ones(bkg_map.data.shape)
#effective area - with a gradient that also depends on energy
aeff_map = Map.from_geom(geom_allsky_true, unit="cm2 s")
ra_arr = np.arange(aeff_map.data.shape[1])
dec_arr = np.arange(aeff_map.data.shape[2])
for i in np.arange(aeff_map.data.shape[0]):
aeff_map.data[i, :, :] = (i+1)*10*np.meshgrid(dec_arr, ra_arr)[0]+10*np.meshgrid(dec_arr, ra_arr)[1]+10
aeff_map.meta["TELESCOP"] = "HAWC"
#psf map
width = 0.2*u.deg
rad_axis = MapAxis.from_nodes(np.linspace(0, 2, 50), name="rad", unit="deg")
psfMap = PSFMap.from_gauss(energy_true, rad_axis, width)
#edispmap
edispmap = EDispKernelMap.from_gauss(energy, energy_true, sigma=0.1, bias=0.0, geom=geom_allsky)
#events and gti
nr_ev = 10
ev_t = Table()
gti_t = Table()
ev_t['EVENT_ID'] = np.arange(nr_ev)
ev_t['TIME'] = nr_ev*[Time('2011-01-01 00:00:00', scale='utc', format='iso')]
ev_t['RA'] = np.linspace(-1, 1, nr_ev)*u.deg
ev_t['DEC'] = np.linspace(-1, 1, nr_ev)*u.deg
ev_t['ENERGY'] = np.logspace(0, 2, nr_ev)*u.TeV
gti_t['START'] = [Time('2010-12-31 00:00:00', scale='utc', format='iso')]
gti_t['STOP'] = [Time('2011-01-02 00:00:00', scale='utc', format='iso')]
events = EventList(ev_t)
gti = GTI(gti_t)
#define observation
obs = Observation(
obs_id=0,
obs_info={},
gti=gti,
aeff=aeff_map,
edisp=edispmap,
psf=psfMap,
bkg=bkg_map,
events=events,
obs_filter=None,
)
#define analysis geometry
geom_target = WcsGeom.create(
skydir=(0, 0),
width=(10, 10),
binsz=0.1*u.deg,
axes=[energy]
)
maker = MapDatasetMaker(selection=["exposure", "counts", "background", "edisp", "psf"])
dataset = MapDataset.create(geom=geom_target, energy_axis_true=energy_true, name="test")
dataset = maker.run(dataset, obs)
# test counts
assert dataset.counts.data.sum() == nr_ev
#test background
coords_bg = {
'skycoord' : SkyCoord("0 deg", "0 deg"),
'energy' : energy.center[0]
}
assert_allclose(
dataset.background_model.evaluate().get_by_coord(coords_bg)[0],
value,
atol=1e-7)
#test effective area
coords_aeff = {
'skycoord' : SkyCoord("0 deg", "0 deg"),
'energy_true' : energy_true.center[0]
}
assert_allclose(
aeff_map.get_by_coord(coords_aeff)[0]/dataset.exposure.get_by_coord(coords_aeff)[0],
1,
atol=1e-3)
#test edispmap
pdfmatrix_preinterp = edispmap.get_edisp_kernel(SkyCoord("0 deg", "0 deg")).pdf_matrix
pdfmatrix_postinterp = dataset.edisp.get_edisp_kernel(SkyCoord("0 deg", "0 deg")).pdf_matrix
assert_allclose(pdfmatrix_preinterp, pdfmatrix_postinterp, atol=1e-7)
#test psfmap
geom_psf = geom_target.drop('energy').to_cube([energy_true])
psfkernel_preinterp = psfMap.get_psf_kernel(SkyCoord("0 deg", "0 deg"), geom_psf, max_radius=2*u.deg).data
psfkernel_postinterp = dataset.psf.get_psf_kernel(SkyCoord("0 deg", "0 deg"), geom_psf, max_radius=2*u.deg).data
assert_allclose(psfkernel_preinterp, psfkernel_postinterp, atol=1e-4)
def _map_making(self):
"""Make maps and datasets for 3d analysis."""
datasets_settings = self.config.datasets
log.info("Creating geometry.")
geom = self._create_geometry()
geom_settings = datasets_settings.geom
geom_irf = dict(energy_axis_true=None, binsz_irf=None)
if geom_settings.axes.energy_true.min is not None:
geom_irf["energy_axis_true"] = self._make_energy_axis(
geom_settings.axes.energy_true, name="energy_true")
geom_irf["binsz_irf"] = geom_settings.wcs.binsize_irf.to("deg").value
offset_max = geom_settings.selection.offset_max
log.info("Creating datasets.")
maker = MapDatasetMaker(selection=datasets_settings.map_selection)
safe_mask_selection = datasets_settings.safe_mask.methods
safe_mask_settings = datasets_settings.safe_mask.parameters
maker_safe_mask = SafeMaskMaker(methods=safe_mask_selection,
**safe_mask_settings)
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_config.update(datasets_settings.background.parameters)
bkg_method = datasets_settings.background.method
if bkg_method == "fov_background":
log.debug(
f"Creating FoVBackgroundMaker with arguments {bkg_maker_config}"
)
bkg_maker = FoVBackgroundMaker(**bkg_maker_config)
elif bkg_method == "ring":
bkg_maker = RingBackgroundMaker(**bkg_maker_config)
log.debug(
f"Creating RingBackgroundMaker with arguments {bkg_maker_config}"
)
if datasets_settings.geom.axes.energy.nbins > 1:
raise ValueError(
"You need to define a single-bin energy geometry for your dataset."
)
else:
bkg_maker = None
log.warning(
f"No background maker set for 3d analysis. Check configuration."
)
stacked = MapDataset.create(geom=geom, name="stacked", **geom_irf)
if datasets_settings.stack:
for obs in self.observations:
log.info(f"Processing observation {obs.obs_id}")
cutout = stacked.cutout(obs.pointing_radec,
width=2 * offset_max)
dataset = maker.run(cutout, obs)
dataset = maker_safe_mask.run(dataset, obs)
if bkg_maker is not None:
dataset = bkg_maker.run(dataset)
if bkg_method == "ring":
dataset = dataset.to_map_dataset()
log.debug(dataset)
stacked.stack(dataset)
datasets = [stacked]
else:
datasets = []
for obs in self.observations:
log.info(f"Processing observation {obs.obs_id}")
cutout = stacked.cutout(obs.pointing_radec,
width=2 * offset_max)
dataset = maker.run(cutout, obs)
dataset = maker_safe_mask.run(dataset, obs)
if bkg_maker is not None:
dataset = bkg_maker.run(dataset)
log.debug(dataset)
datasets.append(dataset)
self.datasets = Datasets(datasets)
