def test_contrast_curve_fpf(self) -> None:
with h5py.File(self.test_dir+'PynPoint_database.hdf5', 'a') as hdf_file:
hdf_file['config'].attrs['CPU'] = 1
module = ContrastCurveModule(name_in='contrast_fpf',
image_in_tag='read',
psf_in_tag='read',
contrast_out_tag='limits_fpf',
separation=(0.2, 0.3, 0.2),
angle=(0., 360., 180.),
threshold=('fpf', 1e-6),
psf_scaling=1.,
aperture=0.05,
pca_number=2,
cent_size=None,
edge_size=1.,
extra_rot=0.)
self.pipeline.add_module(module)
self.pipeline.run_module('contrast_fpf')
data = self.pipeline.get_data('limits_fpf')
assert data[0, 0] == pytest.approx(0.2, rel=self.limit, abs=0.)
assert data[0, 1] == pytest.approx(1.797063014325614, rel=self.limit, abs=0.)
assert data[0, 2] == pytest.approx(0.0006250749411564145, rel=self.limit, abs=0.)
assert data[0, 3] == pytest.approx(1e-06, rel=self.limit, abs=0.)
assert data.shape == (1, 4)
def test_contrast_curve(self) -> None:
proc = ['single', 'multi']
for item in proc:
if item == 'multi':
with h5py.File(self.test_dir+'PynPoint_database.hdf5', 'a') as hdf_file:
hdf_file['config'].attrs['CPU'] = 4
module = ContrastCurveModule(name_in='contrast_'+item,
image_in_tag='read',
psf_in_tag='read',
contrast_out_tag='limits_'+item,
separation=(0.2, 0.3, 0.2),
angle=(0., 360., 180.),
threshold=('sigma', 5.),
psf_scaling=1.,
aperture=0.05,
pca_number=2,
cent_size=None,
edge_size=1.,
extra_rot=0.)
self.pipeline.add_module(module)
self.pipeline.run_module('contrast_'+item)
data = self.pipeline.get_data('limits_'+item)
assert data[0, 0] == pytest.approx(0.2, rel=self.limit, abs=0.)
assert data[0, 1] == pytest.approx(2.5223717329932676, rel=self.limit, abs=0.)
assert data[0, 2] == pytest.approx(0.0006250749411563979, rel=self.limit, abs=0.)
assert data[0, 3] == pytest.approx(0.00026866680137822624, rel=self.limit, abs=0.)
assert data.shape == (1, 4)
def test_contrast_curve_fpf(self):
with h5py.File(self.test_dir+'PynPoint_database.hdf5', 'a') as hdf_file:
hdf_file['config'].attrs['CPU'] = 1
module = ContrastCurveModule(name_in='contrast_fpf',
image_in_tag='read',
psf_in_tag='read',
contrast_out_tag='limits_fpf',
separation=(0.5, 0.6, 0.1),
angle=(0., 360., 180.),
threshold=('fpf', 1e-6),
psf_scaling=1.,
aperture=0.1,
pca_number=15,
cent_size=None,
edge_size=None,
extra_rot=0.)
self.pipeline.add_module(module)
self.pipeline.run_module('contrast_fpf')
data = self.pipeline.get_data('limits_fpf')
assert np.allclose(data[0, 0], 5.00000000e-01, rtol=limit, atol=0.)
assert np.allclose(data[0, 1], 0.6820548720545829, rtol=limit, atol=0.)
assert np.allclose(data[0, 2], 0.2594381985736874, rtol=limit, atol=0.)
assert np.allclose(data[0, 3], 1e-6, rtol=limit, atol=0.)
assert data.shape == (1, 4)
def test_contrast_curve(self):
proc = ['single', 'multi']
for item in proc:
if item == 'multi':
with h5py.File(self.test_dir+'PynPoint_database.hdf5', 'a') as hdf_file:
hdf_file['config'].attrs['CPU'] = 4
module = ContrastCurveModule(name_in='contrast_'+item,
image_in_tag='read',
psf_in_tag='read',
contrast_out_tag='limits_'+item,
separation=(0.5, 0.6, 0.1),
angle=(0., 360., 180.),
threshold=('sigma', 5.),
psf_scaling=1.,
aperture=0.1,
pca_number=15,
cent_size=None,
edge_size=None,
extra_rot=0.)
self.pipeline.add_module(module)
self.pipeline.run_module('contrast_'+item)
data = self.pipeline.get_data('limits_'+item)
assert np.allclose(data[0, 0], 5.00000000e-01, rtol=limit, atol=0.)
assert np.allclose(data[0, 1], 1.2034060712266164, rtol=limit, atol=0.)
assert np.allclose(data[0, 2], 0.2594381985736874, rtol=limit, atol=0.)
assert np.allclose(data[0, 3], 0.00012147700290954244, rtol=limit, atol=0.)
assert data.shape == (1, 4)
def test_contrast_curve(self):
proc = ["single", "multi"]
for item in proc:
if item == "multi":
database = h5py.File(self.test_dir + 'PynPoint_database.hdf5',
'a')
database['config'].attrs['CPU'] = 4
contrast = ContrastCurveModule(name_in="contrast_" + item,
image_in_tag="read",
psf_in_tag="read",
contrast_out_tag="limits_" + item,
separation=(0.5, 0.6, 0.1),
angle=(0., 360., 180.),
magnitude=(7.5, 1.),
threshold=("sigma", 5.),
accuracy=1e-1,
psf_scaling=1.,
aperture=0.1,
ignore=True,
pca_number=15,
norm=False,
cent_size=None,
edge_size=None,
extra_rot=0.)
self.pipeline.add_module(contrast)
self.pipeline.run_module("contrast_" + item)
data = self.pipeline.get_data("limits_" + item)
assert np.allclose(data[0, 0], 5.00000000e-01, rtol=limit, atol=0.)
assert np.allclose(data[0, 1],
6.647211555936695,
rtol=limit,
atol=0.)
assert np.allclose(data[0, 2],
0.07837070875760642,
rtol=limit,
atol=0.)
assert np.allclose(data[0, 3],
0.0002012649090622487,
rtol=limit,
atol=0.)
assert data.shape == (1, 4)
def test_contrast_curve(self):
proc = ["single", "multi"]
for item in proc:
if item == "multi":
database = h5py.File(self.test_dir + 'PynPoint_database.hdf5',
'a')
database['config'].attrs['CPU'] = 4
contrast = ContrastCurveModule(name_in="contrast_" + item,
image_in_tag="read",
psf_in_tag="read",
contrast_out_tag="limits_" + item,
separation=(0.5, 0.6, 0.1),
angle=(0., 360., 180.),
threshold=("sigma", 5.),
psf_scaling=1.,
aperture=0.1,
pca_number=15,
cent_size=None,
edge_size=None,
extra_rot=0.)
self.pipeline.add_module(contrast)
self.pipeline.run_module("contrast_" + item)
data = self.pipeline.get_data("limits_" + item)
assert np.allclose(data[0, 0], 5.00000000e-01, rtol=limit, atol=0.)
assert np.allclose(data[0, 1],
2.3624384190310397,
rtol=limit,
atol=0.)
assert np.allclose(data[0, 2],
0.05234065236317515,
rtol=limit,
atol=0.)
assert np.allclose(data[0, 3],
0.00012147700290954244,
rtol=limit,
atol=0.)
assert data.shape == (1, 4)