def test__likelihood__is_sum_of_separations_divided_by_noise(self):
positions = al.GridCoordinates([
[(0.0, 0.0), (0.0, 1.0), (0.0, 0.5)],
[(0.0, 0.0), (0.0, 0.0), (3.0, 3.0)],
[(0.0, 0.0), (1.0, 1.0), (3.0, 3.0)],
])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.chi_squared_map[0] == 1.0
assert fit.chi_squared_map[1] == pytest.approx(18.0, 1e-4)
assert fit.chi_squared_map[2] == pytest.approx(18.0, 1e-4)
assert fit.figure_of_merit == pytest.approx(-0.5 * (1.0 + 18 + 18),
1e-4)
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=2.0)
assert fit.chi_squared_map[0] == (1.0 / 2.0)**2.0
assert fit.chi_squared_map[1] == pytest.approx(
(np.sqrt(18.0) / 2.0)**2.0, 1e-4)
assert fit.chi_squared_map[2] == pytest.approx(
(np.sqrt(18.0) / 2.0)**2.0, 1e-4)
assert fit.figure_of_merit == pytest.approx(
-0.5 * ((1.0 / 2.0)**2.0 + (np.sqrt(18.0) / 2.0)**2.0 +
(np.sqrt(18.0) / 2.0)**2.0),
1e-4,
)
def test_multiple_positions__mock_position_tracer__maximum_separation_is_correct(
self,
):
positions = al.GridIrregularGrouped([[(0.0, 0.0), (0.0, 1.0), (0.0, 0.5)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(
positions=positions, tracer=tracer, noise_value=1.0
)
assert fit.maximum_separations[0] == 1.0
positions = al.GridIrregularGrouped([[(0.0, 0.0), (0.0, 0.0), (3.0, 3.0)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(
positions=positions, tracer=tracer, noise_value=1.0
)
assert fit.maximum_separations[0] == np.sqrt(18)
al.GridIrregularGrouped([[(0.0, 0.0), (1.0, 1.0), (3.0, 3.0)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(
positions=positions, tracer=tracer, noise_value=1.0
)
assert fit.maximum_separations[0] == np.sqrt(18)
positions = al.GridIrregularGrouped(
[
[
(-2.0, -4.0),
(1.0, 3.0),
(0.1, 0.1),
(-0.1, -0.1),
(0.3, 0.4),
(-0.6, 0.5),
]
]
)
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(
positions=positions, tracer=tracer, noise_value=1.0
)
assert fit.maximum_separations[0] == np.sqrt(np.square(3.0) + np.square(7.0))
positions = al.GridIrregularGrouped([[(8.0, 4.0), (8.0, 4.0), (-9.0, -4.0)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(
positions=positions, tracer=tracer, noise_value=1.0
)
assert fit.maximum_separations[0] == np.sqrt(np.square(17.0) + np.square(8.0))
def test__threshold__if_not_met_returns_ray_tracing_exception(self):
positions = al.GridCoordinates([[(0.0, 0.0), (0.0, 1.0)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.maximum_separation_within_threshold(threshold=100.0)
assert not fit.maximum_separation_within_threshold(threshold=0.1)
def test__above_with_real_tracer(self):
tracer = al.Tracer.from_galaxies(galaxies=[
al.Galaxy(redshift=0.5,
mass=al.mp.SphericalIsothermal(einstein_radius=1.0)),
al.Galaxy(redshift=1.0),
])
positions = al.GridCoordinates([[(1.0, 0.0), (-1.0, 0.0)]])
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.maximum_separation_within_threshold(threshold=0.01)
positions = al.GridCoordinates([[(1.2, 0.0), (-1.0, 0.0)]])
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.maximum_separation_within_threshold(threshold=0.3)
assert not fit.maximum_separation_within_threshold(threshold=0.15)
def test__x1_positions__mock_position_tracer__maximum_separation_is_correct(
self):
positions = al.GridCoordinates(coordinates=[[(0.0, 0.0), (0.0, 1.0)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.maximum_separations[0] == 1.0
positions = al.GridCoordinates([[(0.0, 0.0), (1.0, 1.0)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.maximum_separations[0] == np.sqrt(2)
positions = al.GridCoordinates([[(0.0, 0.0), (1.0, 3.0)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.maximum_separations[0] == np.sqrt(
np.square(1.0) + np.square(3.0))
positions = al.GridCoordinates([[(-2.0, -4.0), (1.0, 3.0)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.maximum_separations[0] == np.sqrt(
np.square(3.0) + np.square(7.0))
positions = al.GridCoordinates([[(8.0, 4.0), (-9.0, -4.0)]])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.maximum_separations[0] == np.sqrt(
np.square(17.0) + np.square(8.0))
def test_multiple_sets_of_positions__multiple_sets_of_max_distances(self):
positions = al.GridCoordinates([
[(0.0, 0.0), (0.0, 1.0), (0.0, 0.5)],
[(0.0, 0.0), (0.0, 0.0), (3.0, 3.0)],
[(0.0, 0.0), (1.0, 1.0), (3.0, 3.0)],
])
tracer = MockTracerPositions(positions=positions)
fit = al.FitPositionsSourcePlaneMaxSeparation(positions=positions,
tracer=tracer,
noise_value=1.0)
assert fit.maximum_separations[0] == 1.0
assert fit.maximum_separations[1] == np.sqrt(18)
assert fit.maximum_separations[2] == np.sqrt(18)