def test_psf():
get_psf(
mirror_diameter=8.36,
effective_area=32.4,
filt_wavelength=7528.51,
fwhm=0.748,
atmospheric_model="Moffat",
)
get_psf(
mirror_diameter=8.36,
effective_area=32.4,
filt_wavelength=7528.51,
fwhm=0.748,
atmospheric_model=None,
)
with pytest.raises(NotImplementedError) as excinfo:
get_psf(
mirror_diameter=8.36,
effective_area=32.4,
filt_wavelength=7528.51,
fwhm=0.748,
atmospheric_model="Layered",
)
assert "atmospheric model request" in str(excinfo.value)
with pytest.raises(RuntimeError) as excinfo:
get_psf(mirror_diameter=1,
effective_area=4,
filt_wavelength=7528.51,
fwhm=0.748)
assert "Incompatible effective-area and mirror-diameter values." in str(
excinfo.value)
with pytest.raises(RuntimeError) as excinfo:
get_psf(
mirror_diameter=0,
effective_area=0,
filt_wavelength=7528.51,
fwhm=0.748,
atmospheric_model=None,
)
assert "Neither the atmospheric nor the optical PSF components are defined." in str(
excinfo.value)
get_psf(mirror_diameter=0,
effective_area=0,
filt_wavelength=7528.51,
fwhm=0.748)
get_psf_from_file("tests/example_psf", get_surveys("Rubin"))
get_psf_from_file("tests/multi_psf", get_surveys("Rubin"))
def test_sampling_too_much_objects():
# FAILING
CATALOG_PATH = "data/sample_input_catalog.fits"
class TestSamplingFunction(SamplingFunction):
def __call__(self, table, **kwargs):
return table[:self.max_number + 1]
@property
def compatible_catalogs(self):
return "CatsimCatalog", "CosmosCatalog"
with pytest.raises(ValueError) as excinfo:
stamp_size = 24.0
batch_size = 8
cpus = 1
add_noise = "all"
catalog = CatsimCatalog.from_file(CATALOG_PATH)
sampling_function = TestSamplingFunction(max_number=5)
draw_generator = CatsimGenerator(
catalog,
sampling_function,
get_surveys("Rubin"),
stamp_size=stamp_size,
batch_size=batch_size,
cpus=cpus,
add_noise=add_noise,
)
draw_output = next(draw_generator) # noqa: F841
assert "Number of objects per blend must be less than max_number" in str(
excinfo.value)
def test_sampling_incompatible_catalog():
class TestSamplingFunction(SamplingFunction):
def __call__(self, table, **kwargs):
pass
@property
def compatible_catalogs(self):
return "CosmosCatalog"
with pytest.raises(AttributeError) as excinfo:
stamp_size = 24.0
batch_size = 8
cpus = 1
add_noise = "all"
catalog = CatsimCatalog.from_file(CATALOG_PATH)
sampling_function = TestSamplingFunction(max_number=5)
draw_generator = CatsimGenerator(
catalog,
sampling_function,
get_surveys("Rubin"),
stamp_size=stamp_size,
batch_size=batch_size,
cpus=cpus,
add_noise=add_noise,
)
draw_output = next(draw_generator) # noqa: F841
assert "Your catalog and sampling functions are not compatible with each other." in str(
excinfo.value)
def get_meas_results(meas_function, cpus=1, measure_kwargs=None):
"""Returns draw generator with group sampling function"""
catalog_name = data_dir / "sample_input_catalog.fits"
stamp_size = 24
survey = get_surveys("Rubin")
shifts = [[-0.3, 1.2]]
indexes = [[1]]
catalog = CatsimCatalog.from_file(catalog_name)
draw_blend_generator = CatsimGenerator(
catalog,
DefaultSampling(seed=TEST_SEED),
[survey],
shifts=shifts,
indexes=indexes,
stamp_size=stamp_size,
batch_size=1,
seed=TEST_SEED,
)
meas_generator = MeasureGenerator(meas_function,
draw_blend_generator,
cpus=cpus,
measure_kwargs=measure_kwargs)
blend_results, results = next(meas_generator)
wcs = blend_results["wcs"]
x, y = wcs.world_to_pixel_values(shifts[0][0] / 3600, shifts[0][1] / 3600)
target = np.array([x.item(), y.item()])
return target, results
def test_multiresolution(mock_show):
catalog_name = data_dir / "sample_input_catalog.fits"
stamp_size = 24.0
batch_size = 8
cpus = 1
add_noise = "all"
surveys = get_surveys(["Rubin", "HSC"])
catalog = CatsimCatalog.from_file(catalog_name)
sampling_function = DefaultSampling(stamp_size=stamp_size)
draw_blend_generator = CatsimGenerator(
catalog,
sampling_function,
surveys,
stamp_size=stamp_size,
batch_size=batch_size,
cpus=cpus,
add_noise=add_noise,
)
meas_generator = MeasureGenerator(sep_measure,
draw_blend_generator,
cpus=cpus)
metrics_generator = MetricsGenerator(
meas_generator,
target_meas={"ellipticity": meas_ksb_ellipticity},
meas_band_num=(2, 1))
blend_results, measure_results, metrics_results = next(metrics_generator)
assert "Rubin" in blend_results["blend_list"].keys(
), "Both surveys get well defined outputs"
assert "HSC" in blend_results["blend_list"].keys(
), "Both surveys get well defined outputs"
assert blend_results["blend_images"]["Rubin"][0].shape[-1] == int(
24.0 / 0.2), "Rubin survey should have a pixel scale of 0.2"
assert blend_results["blend_images"]["HSC"][0].shape[-1] == int(
24.0 / 0.167), "HSC survey should have a pixel scale of 0.167"
assert ("Rubin" in measure_results["catalog"]["sep_measure"].keys()
), "Both surveys get well defined outputs"
assert ("HSC" in measure_results["catalog"]["sep_measure"].keys()
), "Both surveys get well defined outputs"
assert ("Rubin" in metrics_results["galaxy_summary"]["sep_measure"].keys()
), "Both surveys get well defined outputs"
assert ("HSC" in metrics_results["galaxy_summary"]["sep_measure"].keys()
), "Both surveys get well defined outputs"
plot_metrics_summary(
metrics_results,
target_meas_keys=["ellipticity0"],
target_meas_limits=[[-1, 1]],
interactive=False,
)
plot_metrics_summary(
metrics_results,
target_meas_keys=["ellipticity0"],
target_meas_limits=[[-1, 1]],
interactive=True,
)
def test_incompatible_catalogs():
stamp_size = 24.0
batch_size = 8
cpus = 1
add_noise = True
catalog = CatsimCatalog.from_file(CATALOG_PATH)
sampling_function = DefaultSampling(stamp_size=stamp_size)
with pytest.raises(ValueError):
# Wrong generator
draw_generator = CosmosGenerator( # noqa: F841
catalog,
sampling_function,
get_surveys("Rubin"),
stamp_size=stamp_size,
batch_size=batch_size,
cpus=cpus,
add_noise=add_noise,
)
with pytest.raises(ValueError):
# Missing filter
draw_generator = CatsimGenerator( # noqa: F841
catalog,
sampling_function,
get_surveys("HST"),
stamp_size=stamp_size,
batch_size=batch_size,
cpus=cpus,
add_noise=add_noise,
)
catalog = CosmosCatalog.from_file(COSMOS_CATALOG_PATHS,
exclusion_level="none")
with pytest.raises(ValueError):
draw_generator = CatsimGenerator( # noqa: F841
catalog,
sampling_function,
get_surveys("Rubin"),
stamp_size=stamp_size,
batch_size=batch_size,
cpus=cpus,
add_noise=add_noise,
)
def test_source_not_visible():
filt = Filter(
name="u",
psf=get_psf(
mirror_diameter=8.36,
effective_area=32.4,
filt_wavelength=3592.13,
fwhm=0.859,
),
sky_brightness=22.9,
exp_time=1680,
zeropoint=9.16,
extinction=0.451,
)
catalog = CatsimCatalog.from_file(CATALOG_PATH)
with pytest.raises(SourceNotVisible):
gal = get_catsim_galaxy( # noqa: F841
catalog.table[0], filt, get_surveys("Rubin"), True, True, True)
def get_group_sampling_draw_generator(batch_size=3):
"""Returns draw generator with group sampling function"""
wld_catalog_name = data_dir / "sample_group_catalog.fits"
catalog_name = data_dir / "sample_group_input_catalog.fits"
max_number = 10
stamp_size = 24
survey = get_surveys("Rubin")
pixel_scale = 0.2
shift = [0.8, -0.7]
catalog = CatsimCatalog.from_file(catalog_name)
sampling_function = GroupSamplingNumbered(
max_number, wld_catalog_name, stamp_size, pixel_scale, shift=shift, seed=TEST_SEED
)
draw_blend_generator = CatsimGenerator(
catalog, sampling_function, [survey], batch_size=batch_size, seed=TEST_SEED
)
return draw_blend_generator
def get_draw_generator(
batch_size=8,
cpus=1,
add_noise="all",
fixed_parameters=False,
sampling_function=None,
):
"""Returns a btk.draw_blends generator for default parameters"""
catalog_name = "data/sample_input_catalog.fits"
stamp_size = 24.0
if fixed_parameters:
shifts = [
[[-0.3, 1.2], [-1.6, -1.7]],
[[-1.1, -2.1], [1.4, 1.8]],
[[-1.8, -0.8], [-0.6, 2.2]],
[[-2.0, -0.7], [-2.2, 1.9]],
[[1.1, -1.5], [0.1, -2.3]],
[[-2.3, 1.9], [0.4, -1.9]],
[[2.0, -2.0], [2.0, 0.1]],
[[0.2, 2.4], [-1.8, -2.0]],
]
indexes = [[4, 5], [9, 1], [9, 2], [0, 2], [3, 8], [0, 7], [10, 2],
[0, 10]]
else:
shifts = None
indexes = None
catalog = btk.catalog.CatsimCatalog.from_file(catalog_name)
if sampling_function is None:
sampling_function = btk.sampling_functions.DefaultSampling(
stamp_size=stamp_size, seed=TEST_SEED)
draw_generator = btk.draw_blends.CatsimGenerator(
catalog,
sampling_function,
get_surveys("Rubin"),
batch_size=batch_size,
stamp_size=stamp_size,
shifts=shifts,
indexes=indexes,
cpus=cpus,
add_noise=add_noise,
verbose=True,
seed=TEST_SEED,
)
return draw_generator
def test_cosmos_ext_galaxies():
stamp_size = 24.0
batch_size = 2
catalog = CosmosCatalog.from_file(COSMOS_EXT_CATALOG_PATHS, exclusion_level="none")
sampling_function = DefaultSampling(stamp_size=stamp_size)
HST = get_surveys("HST")
draw_generator = CosmosGenerator(
catalog,
sampling_function,
HST,
batch_size=batch_size,
stamp_size=stamp_size,
cpus=1,
add_noise="all",
verbose=True,
)
_ = next(draw_generator)
def test_cosmos_galaxies_parametric():
stamp_size = 24.0
batch_size = 2
catalog = CosmosCatalog.from_file(COSMOS_CATALOG_PATHS)
sampling_function = DefaultSampling(stamp_size=stamp_size)
HST = get_surveys("HST")
draw_generator = CosmosGenerator(
catalog,
sampling_function,
HST,
batch_size=batch_size,
stamp_size=stamp_size,
cpus=1,
add_noise="all",
verbose=True,
gal_type="parametric",
)
_ = next(draw_generator)
def get_metrics_generator(
meas_function,
cpus=1,
measure_kwargs=None,
):
"""Returns draw generator with group sampling function"""
catalog_name = "data/sample_input_catalog.fits"
stamp_size = 24
survey = get_surveys("Rubin")
shifts = [
[[-0.3, 1.2], [-1.6, -1.7]],
[[-1.1, -2.1], [1.4, 1.8]],
[[-1.8, -0.8], [-0.6, 2.2]],
[[-2.0, -0.7], [-2.2, 1.9]],
[[1.1, -1.5], [0.1, -2.3]],
[[-2.3, 1.9], [0.4, -1.9]],
[[2.0, -2.0], [2.0, 0.1]],
[[0.2, 2.4], [-1.8, -2.0]],
]
indexes = [[4, 5], [9, 1], [9, 2], [0, 2], [3, 8], [0, 7], [10, 2],
[0, 10]]
catalog = CatsimCatalog.from_file(catalog_name)
draw_blend_generator = CatsimGenerator(
catalog,
DefaultSampling(seed=TEST_SEED),
[survey],
shifts=shifts,
indexes=indexes,
stamp_size=stamp_size,
seed=TEST_SEED,
)
meas_generator = MeasureGenerator(meas_function,
draw_blend_generator,
cpus=cpus,
measure_kwargs=measure_kwargs)
metrics_generator = MetricsGenerator(
meas_generator,
target_meas={"ellipticity": meas_ksb_ellipticity},
)
return metrics_generator