def test_asmooth_map_dataset_on_off():
kernel = Tophat2DKernel
scales = ASmoothMapEstimator.get_scales(3, factor=2,
kernel=kernel) * 0.1 * u.deg
asmooth = ASmoothMapEstimator(kernel=kernel,
scales=scales,
method="lima",
threshold=2.5)
counts = WcsNDMap.create(npix=(50, 50), binsz=0.02, unit="")
counts += 2
counts_off = WcsNDMap.create(npix=(50, 50), binsz=0.02, unit="")
counts_off += 3
acceptance = WcsNDMap.create(npix=(50, 50), binsz=0.02, unit="")
acceptance += 1
acceptance_off = WcsNDMap.create(npix=(50, 50), binsz=0.02, unit="")
acceptance_off += 3
dataset = MapDatasetOnOff(
counts=counts,
counts_off=counts_off,
acceptance=acceptance,
acceptance_off=acceptance_off,
)
smoothed = asmooth.run(dataset)
assert_allclose(smoothed["counts"].data[25, 25], 2)
assert_allclose(smoothed["background"].data[25, 25], 1)
assert_allclose(smoothed["significance"].data[25, 25], 4.391334)
def test_asmooth_dataset(input_dataset):
kernel = Tophat2DKernel
scales = ASmoothMapEstimator.get_scales(3, factor=2,
kernel=kernel) * 0.1 * u.deg
asmooth = ASmoothMapEstimator(scales=scales,
kernel=kernel,
method="lima",
threshold=2.5)
smoothed = asmooth.run(input_dataset)
assert smoothed["flux"].data.shape == (1, 40, 50)
assert smoothed["flux"].unit == u.Unit("cm-2s-1")
assert smoothed["counts"].unit == u.Unit("")
assert smoothed["background"].unit == u.Unit("")
assert smoothed["scale"].unit == u.Unit("deg")
desired = {
"counts": 369.479167,
"background": 0.184005,
"scale": 0.056419,
"sqrt_ts": 72.971513,
"flux": 1.237119e-09,
}
for name in smoothed:
actual = smoothed[name].data[0, 20, 25]
assert_allclose(actual, desired[name], rtol=1e-2)
def run_asmooth(dataset):
scales = u.Quantity(np.arange(0.05, 1, 0.05), unit="deg")
smooth = ASmoothMapEstimator(threshold=3,
scales=scales,
energy_edges=[10, 300] * u.GeV)
images = smooth.run(dataset)
return images
def test_asmooth_map_dataset_on_off():
kernel = Tophat2DKernel
scales = ASmoothMapEstimator.get_scales(3, factor=2,
kernel=kernel) * 0.1 * u.deg
asmooth = ASmoothMapEstimator(kernel=kernel,
scales=scales,
method="lima",
threshold=2.5)
axis = MapAxis.from_energy_bounds("1 TeV", "10 TeV", nbin=1)
counts = WcsNDMap.create(npix=(50, 50), binsz=0.02, unit="", axes=[axis])
counts += 2
counts_off = WcsNDMap.create(npix=(50, 50),
binsz=0.02,
unit="",
axes=[axis])
counts_off += 3
acceptance = WcsNDMap.create(npix=(50, 50),
binsz=0.02,
unit="",
axes=[axis])
acceptance += 1
acceptance_off = WcsNDMap.create(npix=(50, 50),
binsz=0.02,
unit="",
axes=[axis])
acceptance_off += 3
dataset = MapDatasetOnOff(
counts=counts,
counts_off=counts_off,
acceptance=acceptance,
acceptance_off=acceptance_off,
)
smoothed = asmooth.run(dataset)
assert_allclose(smoothed["counts"].data[25, 25], 2)
assert_allclose(smoothed["background"].data[25, 25], 1.25)
assert_allclose(smoothed["significance"].data[25, 25],
3.079799117645,
rtol=1e-2)
def test_asmooth(input_dataset_simple):
kernel = Tophat2DKernel
scales = ASmoothMapEstimator.get_scales(3, factor=2,
kernel=kernel) * 0.1 * u.deg
asmooth = ASmoothMapEstimator(scales=scales,
kernel=kernel,
method="lima",
threshold=2.5)
smoothed = asmooth.estimate_maps(input_dataset_simple)
desired = {
"counts": 6.454327,
"background": 1.0,
"scale": 0.056419,
"sqrt_ts": 18.125747,
}
for name in smoothed:
actual = smoothed[name].data[0, 100, 100]
assert_allclose(actual, desired[name], rtol=1e-5)
def test_asmooth_dataset(input_dataset):
kernel = Tophat2DKernel
scales = ASmoothMapEstimator.get_scales(3, factor=2,
kernel=kernel) * 0.1 * u.deg
asmooth = ASmoothMapEstimator(scales=scales,
kernel=kernel,
method="lima",
threshold=2.5)
# First check that is fails if don't use to_image()
with pytest.raises(ValueError):
asmooth.run(input_dataset)
smoothed = asmooth.run(input_dataset.to_image())
assert smoothed["flux"].data.shape == (40, 50)
assert smoothed["flux"].unit == u.Unit("cm-2s-1")
assert smoothed["counts"].unit == u.Unit("")
assert smoothed["background"].unit == u.Unit("")
assert smoothed["scale"].unit == u.Unit("deg")
desired = {
"counts": 369.479167,
"background": 0.13461,
"scale": 0.056419,
"significance": 74.677406,
"flux": 1.237284e-09,
}
for name in smoothed:
actual = smoothed[name].data[20, 25]
assert_allclose(actual, desired[name], rtol=1e-5)