def test_model(self):
frame_shape = (10, 20, 30)
frame = scarlet.Frame(frame_shape, channels=np.arange(10))
shape = (5, 4, 6)
on_location = (1, 2, 3)
sed = np.zeros(shape[0])
sed[on_location[0]] = 1
morph = np.zeros(shape[1:])
morph[on_location[1:]] = 1
origin = (2, 3, 4)
box = scarlet.Box(shape, origin=origin)
spectrum = scarlet.TabulatedSpectrum(frame, sed, bbox=box[0])
morphology = scarlet.ImageMorphology(frame, morph, bbox=box[1:])
component = scarlet.FactorizedComponent(frame, spectrum, morphology)
model = component.get_model(frame=frame)
# everything zero except at one location?
test_loc = tuple(np.array(on_location) + np.array(origin))
mask = np.zeros(model.shape, dtype="bool")
mask[test_loc] = True
assert_array_equal(model[~mask], 0)
assert model[test_loc] == 1
# now with shift
shift_loc = (0, 1, 0)
shift = scarlet.Parameter(np.array(shift_loc[1:]),
step=0.1,
name="shift")
morphology = scarlet.ImageMorphology(frame,
morph,
bbox=box[1:],
shift=shift)
component = scarlet.FactorizedComponent(frame, spectrum, morphology)
model = component.get_model(frame=frame)
# everything zero except at one location?
test_loc = tuple(
np.array(on_location) + np.array(origin) + np.array(shift_loc))
mask = np.zeros(model.shape, dtype="bool")
mask[test_loc] = True
assert_almost_equal(model[~mask], 0)
assert_almost_equal(model[test_loc], 1)
def test_model(self):
frame_shape = (10, 20, 30)
frame = scarlet.Frame(frame_shape)
shape = (5, 4, 6)
on_location = (1, 2, 3)
sed = np.zeros(shape[0])
sed[on_location[0]] = 1
morph = np.zeros(shape[1:])
morph[on_location[1:]] = 1
sed = scarlet.Parameter(sed)
morph = scarlet.Parameter(morph)
origin = (2, 3, 4)
bbox = scarlet.Box(shape, origin=origin)
component = scarlet.FactorizedComponent(frame, sed, morph, bbox=bbox)
model = component.get_model()
# everything zero except at one location?
test_loc = tuple(np.array(on_location) + np.array(origin))
mask = np.zeros(model.shape, dtype='bool')
mask[test_loc] = True
assert_array_equal(model[~mask], 0)
assert model[test_loc] == 1
# now with shift
shift_loc = (0, 1, 0)
shift = scarlet.Parameter(np.array(shift_loc[1:]))
component = scarlet.FactorizedComponent(frame,
sed,
morph,
shift=shift,
bbox=bbox)
model = component.get_model()
# everything zero except at one location?
test_loc = tuple(
np.array(on_location) + np.array(origin) + np.array(shift_loc))
mask = np.zeros(model.shape, dtype='bool')
mask[test_loc] = True
assert_almost_equal(model[~mask], 0)
assert_almost_equal(model[test_loc], 1)
def test_model(self):
frame_shape = (10, 20, 30)
frame = scarlet.Frame(frame_shape, channels=np.arange(10))
shape = (5, 4, 6)
origin = (2, 3, 4)
box = scarlet.Box(shape, origin=origin)
on_location = (1, 2, 3)
sed = np.zeros(shape[0])
sed[on_location[0]] = 1
spectrum = scarlet.TabulatedSpectrum(frame, sed, bbox=box[0])
# construct functional morphology where the parameter sets
# the location of single pixel that is on
class OnePixelMorphology(scarlet.Morphology):
def __init__(self, model_frame, on_pixel, bbox=None):
self._bbox = bbox
self._on_pixel = scarlet.Parameter(on_pixel,
step=1,
name="on_pixel")
super().__init__(model_frame, self._on_pixel, bbox=bbox)
def get_model(self, *params):
on_pixel = self._on_pixel
for p in params:
if p._value.name == "on_pixel":
on_pixel = p
morph = np.zeros(self._bbox.shape)
morph[tuple(np.round(on_pixel).astype("int"))] = 1
return morph
morphology = OnePixelMorphology(frame,
np.array(on_location[1:],
dtype="float"),
bbox=box[1:])
component = scarlet.FactorizedComponent(frame, spectrum, morphology)
model = component.get_model(frame=frame)
# everything zero except at one location?
test_loc = tuple(np.array(on_location) + np.array(origin))
mask = np.zeros(model.shape, dtype="bool")
mask[test_loc] = True
assert_array_equal(model[~mask], 0)
assert model[test_loc] == 1
def test_model(self):
frame_shape = (10, 20, 30)
frame = scarlet.Frame(frame_shape)
shape = (5, 4, 6)
on_location = (1, 2, 3)
cube = np.zeros(shape)
cube[on_location] = 1
cube = scarlet.Parameter(cube)
origin1 = (2, 3, 4)
bbox1 = scarlet.Box(shape, origin=origin1)
component1 = scarlet.CubeComponent(frame, cube, bbox=bbox1)
sed = np.zeros(shape[0])
sed[on_location[0]] = 1
morph = np.zeros(shape[1:])
morph[on_location[1:]] = 1
sed = scarlet.Parameter(sed)
morph = scarlet.Parameter(morph)
origin2 = (5, 6, 7)
bbox2 = scarlet.Box(shape, origin=origin2)
component2 = scarlet.FactorizedComponent(frame, sed, morph, bbox=bbox2)
tree = scarlet.ComponentTree([component1, component2])
model = tree.get_model()
# everything zero except at one location?
test_locs = [
tuple(np.array(on_location) + np.array(origin1)),
tuple(np.array(on_location) + np.array(origin2))
]
mask = np.zeros(model.shape, dtype='bool')
for test_loc in test_locs:
mask[test_loc] = True
assert_array_equal(model[~mask], 0)
assert_array_equal(model[mask], 1)
def test_model(self):
frame_shape = (10, 20, 30)
frame = scarlet.Frame(frame_shape, channels=np.arange(10))
shape = (5, 4, 6)
origin = (2, 3, 4)
box = scarlet.Box(shape, origin=origin)
on_location1 = (1, 2, 3)
cube = np.zeros(shape)
cube[on_location1] = 1
cube = scarlet.Parameter(cube, name="cube")
component1 = scarlet.CubeComponent(frame, cube, bbox=box)
# make factorized component with a different origin
on_location2 = (1, 1, 1)
sed = np.zeros(shape[0])
sed[on_location2[0]] = 1
morph = np.zeros(shape[1:])
morph[on_location2[1:]] = 1
spectrum = scarlet.TabulatedSpectrum(frame, sed, bbox=box[0])
morphology = scarlet.ImageMorphology(frame, morph, bbox=box[1:])
component2 = scarlet.FactorizedComponent(frame, spectrum, morphology)
combined = scarlet.CombinedComponent([component1, component2])
model = combined.get_model(frame=frame)
# everything zero except at one location?
test_locs = [
tuple(np.array(on_location1) + np.array(origin)),
tuple(np.array(on_location2) + np.array(origin)),
]
mask = np.zeros(model.shape, dtype="bool")
for test_loc in test_locs:
mask[test_loc] = True
assert_array_equal(model[~mask], 0)
assert_array_equal(model[mask], 1)