def test_to_image_mask_safe():
axis = MapAxis.from_energy_bounds("0.1 TeV", "10 TeV", nbin=2)
geom = WcsGeom.create(
skydir=(0, 0), binsz=0.5, width=(1, 1), frame="icrs", axes=[axis]
)
dataset = MapDataset.create(geom)
# Check map_safe handling
data = np.array([[[False, True], [True, True]], [[False, False], [True, True]]])
dataset.mask_safe = WcsNDMap.from_geom(geom=geom, data=data)
dataset_im = dataset.to_image()
assert dataset_im.mask_safe.data.dtype == bool
desired = np.array([[False, True], [True, True]])
assert (dataset_im.mask_safe.data == desired).all()
# Check that missing entries in the dataset do not break
dataset_copy = dataset.copy()
dataset_copy.exposure = None
dataset_im = dataset_copy.to_image()
assert dataset_im.exposure is None
dataset_copy = dataset.copy()
dataset_copy.counts = None
dataset_im = dataset_copy.to_image()
assert dataset_im.counts is None
def test_wcsndmap_pad_cval():
geom = WcsGeom.create(npix=(5, 5))
m = WcsNDMap.from_geom(geom)
cval = 1.1
m_padded = m.pad(1, mode="constant", cval=cval)
assert_allclose(m_padded.data[0, 0], cval)
def exclusion_mask(geom):
"""Example mask for testing."""
pos = SkyCoord(83.633, 22.014, unit="deg", frame="icrs")
region = CircleSkyRegion(pos, Angle(0.15, "deg"))
exclusion = WcsNDMap.from_geom(geom)
exclusion.data = geom.region_mask([region], inside=False)
return exclusion
def test_exclusion_region(tmp_path):
config = get_example_config("1d")
analysis = Analysis(config)
exclusion_region = CircleSkyRegion(center=SkyCoord("85d 23d"),
radius=1 * u.deg)
exclusion_mask = Map.create(npix=(150, 150),
binsz=0.05,
skydir=SkyCoord("83d 22d"))
mask = exclusion_mask.geom.region_mask([exclusion_region], inside=False)
exclusion_mask.data = mask.astype(int)
filename = tmp_path / "exclusion.fits"
exclusion_mask.write(filename)
config.datasets.background.method = "reflected"
config.datasets.background.exclusion = filename
analysis.get_observations()
analysis.get_datasets()
assert len(analysis.datasets) == 2
config = get_example_config("3d")
analysis = Analysis(config)
analysis.get_observations()
analysis.get_datasets()
geom = analysis.datasets[0]._geom
exclusion = WcsNDMap.from_geom(geom)
exclusion.data = geom.region_mask([exclusion_region],
inside=False).astype(int)
filename = tmp_path / "exclusion3d.fits"
exclusion.write(filename)
config.datasets.background.exclusion = filename
analysis.get_datasets()
assert len(analysis.datasets) == 1
def _exclusion_mask_ref(reference_geom, exclusion_mask):
"""Exclusion mask reprojected"""
if exclusion_mask:
mask = exclusion_mask.interp_to_geom(reference_geom,
fill_value=True)
else:
mask = WcsNDMap.from_geom(geom=reference_geom, data=True)
return mask
def exclusion_mask_ref(self):
"""Exclusion mask reprojected"""
if self.exclusion_mask:
mask = self.exclusion_mask.interp_to_geom(self.geom_ref,
fill_value=True)
else:
mask = WcsNDMap.from_geom(geom=self.geom_ref, data=True)
return mask
def test_to_image(geom):
counts = Map.read(
"$GAMMAPY_DATA/fermi-3fhl-gc/fermi-3fhl-gc-counts-cube.fits.gz")
background = Map.read(
"$GAMMAPY_DATA/fermi-3fhl-gc/fermi-3fhl-gc-background-cube.fits.gz")
background = BackgroundModel(background, datasets_names=["fermi"])
exposure = Map.read(
"$GAMMAPY_DATA/fermi-3fhl-gc/fermi-3fhl-gc-exposure-cube.fits.gz")
exposure = exposure.sum_over_axes(keepdims=True)
dataset = MapDataset(counts=counts,
models=[background],
exposure=exposure,
name="fermi")
dataset_im = dataset.to_image()
assert dataset_im.mask_safe is None
assert dataset_im.counts.data.sum() == dataset.counts.data.sum()
assert_allclose(dataset_im.background_model.map.data.sum(),
28548.625,
rtol=1e-5)
ebounds = np.logspace(-1.0, 1.0, 3)
axis = MapAxis.from_edges(ebounds, name="energy", unit=u.TeV, interp="log")
geom = WcsGeom.create(skydir=(0, 0),
binsz=0.5,
width=(1, 1),
frame="icrs",
axes=[axis])
dataset = MapDataset.create(geom)
# Check map_safe handling
data = np.array([[[False, True], [True, True]],
[[False, False], [True, True]]])
dataset.mask_safe = WcsNDMap.from_geom(geom=geom, data=data)
dataset_im = dataset.to_image()
assert dataset_im.mask_safe.data.dtype == bool
desired = np.array([[False, True], [True, True]])
assert (dataset_im.mask_safe.data == desired).all()
# Check that missing entries in the dataset do not break
dataset_copy = dataset.copy()
dataset_copy.exposure = None
dataset_copy._background_model = None
dataset_im = dataset_copy.to_image()
assert dataset_im.exposure is None
assert dataset_im.background_model == None
dataset_copy = dataset.copy()
dataset_copy.counts = None
dataset_im = dataset_copy.to_image()
assert dataset_im.counts is None
def test_to_image(geom):
ebounds = np.logspace(-1.0, 1.0, 3)
axis = MapAxis.from_edges(ebounds, name="energy", unit=u.TeV, interp="log")
geom = WcsGeom.create(
skydir=(0, 0), binsz=0.5, width=(1, 1), coordsys="CEL", axes=[axis]
)
dataset = MapDataset.create(geom)
# Check map_safe handling
data = np.array([[[False, True], [True, True]], [[False, False], [True, True]]])
dataset.mask_safe = WcsNDMap.from_geom(geom=geom, data=data)
dataset_im = dataset.to_image()
assert dataset_im.mask_safe.data.dtype == bool
desired = np.array([[False, True], [True, True]])
assert (dataset_im.mask_safe.data == desired).all()
def to_cube(image):
# introduce a fake enery axis for now
axis = MapAxis.from_edges([1, 10] * u.TeV, name="energy")
geom = image.geom.to_cube([axis])
return WcsNDMap.from_geom(geom=geom, data=image.data)
