def test__interferometer_generator_from_aggregator(
visibilities_7,
visibilities_noise_map_7,
uv_wavelengths_7x2,
mask_2d_7x7,
samples,
model,
):
path_prefix = "aggregator_interferometer"
database_file = path.join(conf.instance.output_path,
"interferometer.sqlite")
result_path = path.join(conf.instance.output_path, path_prefix)
clean(database_file=database_file, result_path=result_path)
interferometer_7 = ag.Interferometer(
visibilities=visibilities_7,
noise_map=visibilities_noise_map_7,
uv_wavelengths=uv_wavelengths_7x2,
real_space_mask=mask_2d_7x7,
settings=ag.SettingsInterferometer(
grid_class=ag.Grid2DIterate,
grid_inversion_class=ag.Grid2DIterate,
fractional_accuracy=0.5,
sub_steps=[2],
transformer_class=ag.TransformerDFT,
),
)
search = mock.MockSearch(samples=samples)
search.paths = af.DirectoryPaths(path_prefix=path_prefix)
analysis = ag.AnalysisInterferometer(dataset=interferometer_7)
search.fit(model=model, analysis=analysis)
agg = af.Aggregator.from_database(filename=database_file)
agg.add_directory(directory=result_path)
interferometer_agg = ag.agg.InterferometerAgg(aggregator=agg)
interferometer_gen = interferometer_agg.interferometer_gen()
for interferometer in interferometer_gen:
assert (interferometer.visibilities == interferometer_7.visibilities
).all()
assert (interferometer.real_space_mask == mask_2d_7x7).all()
assert isinstance(interferometer.grid, ag.Grid2DIterate)
assert isinstance(interferometer.grid_inversion, ag.Grid2DIterate)
assert interferometer.grid.sub_steps == [2]
assert interferometer.grid.fractional_accuracy == 0.5
assert isinstance(interferometer.transformer, ag.TransformerDFT)
clean(database_file=database_file, result_path=result_path)
def test__1x2_image__1x2_visibilities__simple_fourier_transform(self):
# The image plane image generated by the galaxy is [1.0, 1.0]
# Thus the chi squared is 4.0**2.0 + 3.0**2.0 = 25.0
real_space_mask = ag.Mask2D.manual(
mask=[
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
],
pixel_scales=1.0,
)
interferometer = ag.Interferometer(
visibilities=ag.Visibilities.full(fill_value=5.0, shape_slim=(1,)),
noise_map=ag.Visibilities.ones(shape_slim=(1,)),
uv_wavelengths=np.array([[0.0, 0.0]]),
real_space_mask=real_space_mask,
settings=ag.SettingsInterferometer(
grid_class=ag.Grid2D, sub_size=1, transformer_class=ag.TransformerDFT
),
)
interferometer.visibilities[0] = 5.0 + 4.0j
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2))
plane = ag.Plane(galaxies=[g0])
fit = ag.FitInterferometer(interferometer=interferometer, plane=plane)
assert (fit.visibilities.slim == np.array([5.0 + 4.0j])).all()
assert (fit.noise_map.slim == np.array([1.0 + 1.0j])).all()
assert (fit.model_visibilities.slim == np.array([2.0 + 0.0j])).all()
assert (fit.residual_map.slim == np.array([3.0 + 4.0j])).all()
assert (fit.normalized_residual_map.slim == np.array([3.0 + 4.0j])).all()
assert (fit.chi_squared_map.slim == np.array([9.0 + 16.0j])).all()
assert fit.chi_squared == 25.0
assert fit.noise_normalization == pytest.approx(
2.0 * np.log(2 * np.pi * 1.0 ** 2.0), 1.0e-4
)
assert fit.log_likelihood == pytest.approx(
-0.5 * (25.0 + 2.0 * np.log(2 * np.pi * 1.0 ** 2.0)), 1.0e-4
)
def interferometer_via_database_from(
fit: Fit,
real_space_mask: Optional[ag.Mask2D] = None,
settings_interferometer: Optional[ag.SettingsInterferometer] = None,
):
"""
Returns a `Interferometer` object from an aggregator's `SearchOutput` class, which we call an 'agg_obj' to
describe that it acts as the aggregator object for one result in the `Aggregator`. This uses the aggregator's
generator outputs such that the function can use the `Aggregator`'s map function to to create a
`Interferometer` generator.
The `Interferometer` is created following the same method as the PyAutoGalaxy `Search` classes, including
using the `SettingsInterferometer` instance output by the Search to load inputs of the `Interferometer`
(e.g. psf_shape_2d).
Parameters
----------
fit : af.SearchOutput
A PyAutoFit aggregator's SearchOutput object containing the generators of the results of PyAutoGalaxy
model-fits.
"""
data = fit.value(name="data")
noise_map = fit.value(name="noise_map")
uv_wavelengths = fit.value(name="uv_wavelengths")
real_space_mask = real_space_mask or fit.value(name="real_space_mask")
settings_interferometer = settings_interferometer or fit.value(
name="settings_dataset"
)
interferometer = ag.Interferometer(
visibilities=data,
noise_map=noise_map,
uv_wavelengths=uv_wavelengths,
real_space_mask=real_space_mask,
)
interferometer = interferometer.apply_settings(settings=settings_interferometer)
return interferometer
def test__hyper_background_changes_background_sky__reflected_in_likelihood(self,):
uv_wavelengths = np.array([[1.0, 0.0], [1.0, 1.0], [2.0, 2.0]])
real_space_mask = ag.Mask2D.manual(
mask=[
[True, True, True, True, True],
[True, False, False, False, True],
[True, True, True, True, True],
],
pixel_scales=1.0,
)
interferometer = ag.Interferometer(
visibilities=ag.Visibilities.full(fill_value=5.0, shape_slim=(3,)),
noise_map=ag.Visibilities.full(fill_value=2.0, shape_slim=(3,)),
uv_wavelengths=uv_wavelengths,
real_space_mask=real_space_mask,
settings=ag.SettingsInterferometer(grid_class=ag.Grid2D, sub_size=1),
)
# Setup as a ray trace instance, using a light profile for the galaxy
g0 = ag.Galaxy(redshift=0.5, light_profile=MockLightProfile(value=1.0, size=2))
plane = ag.Plane(galaxies=[g0])
hyper_background_noise = ag.hyper_data.HyperBackgroundNoise(noise_scale=1.0)
fit = ag.FitInterferometer(
interferometer=interferometer,
plane=plane,
hyper_background_noise=hyper_background_noise,
)
assert (
fit.visibilities.slim == np.array([5.0 + 5.0j, 5.0 + 5.0j, 5.0 + 5.0j])
).all()
assert (
fit.noise_map.slim == np.array([3.0 + 3.0j, 3.0 + 3.0j, 3.0 + 3.0j])
).all()