def test_stack_and_subset(self):
self.pipeline.set_attribute("images", "PARANG", np.arange(1., 41., 1.), static=False)
stack = StackAndSubsetModule(name_in="stack",
image_in_tag="images",
image_out_tag="stack",
random=10,
stacking=2)
self.pipeline.add_module(stack)
self.pipeline.run_module("stack")
data = self.pipeline.get_data("stack")
assert np.allclose(data[0, 50, 50], 0.09816320034649725, rtol=limit, atol=0.)
assert np.allclose(np.mean(data), 9.983545774937238e-05, rtol=limit, atol=0.)
assert data.shape == (10, 100, 100)
data = self.pipeline.get_data("header_stack/INDEX")
index = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
assert np.allclose(data, index, rtol=limit, atol=0.)
assert data.shape == (10, )
data = self.pipeline.get_data("header_stack/PARANG")
parang = [1.5, 15.5, 19.5, 23.5, 25.5, 29.5, 31.5, 35.5, 37.5, 39.5]
assert np.allclose(data, parang, rtol=limit, atol=0.)
assert data.shape == (10, )
def test_stack_and_subset(self) -> None:
self.pipeline.set_attribute('images', 'PARANG', np.arange(10.), static=False)
module = StackAndSubsetModule(name_in='stack1',
image_in_tag='images',
image_out_tag='stack1',
random=4,
stacking=2,
combine='mean',
max_rotation=None)
self.pipeline.add_module(module)
self.pipeline.run_module('stack1')
data = self.pipeline.get_data('stack1')
assert np.mean(data) == pytest.approx(0.08758276283743936, rel=self.limit, abs=0.)
assert data.shape == (4, 11, 11)
data = self.pipeline.get_data('header_stack1/INDEX')
assert data == pytest.approx(np.arange(4), rel=self.limit, abs=0.)
assert data.shape == (4, )
data = self.pipeline.get_data('header_stack1/PARANG')
assert data == pytest.approx([0.5, 2.5, 6.5, 8.5], rel=self.limit, abs=0.)
assert data.shape == (4, )
def test_stack(self):
subset = StackAndSubsetModule(name_in="stacking_subset",
image_in_tag="im_arr_aligned",
image_out_tag="im_arr_stacked",
random=None,
stacking=4)
self.pipeline.add_module(subset)
self.pipeline.run_module("stacking_subset")
data = self.pipeline.get_data("im_arr_stacked")
assert np.allclose(data[0, 10, 10],
2.55745339731812e-05,
rtol=limit,
atol=0.)
assert data.shape == (20, 46, 46)
def test_stack_max_rotation(self) -> None:
angles = np.arange(1., 41., 1.)
angles[1:6] = 3.
angles[39] = 50.
self.pipeline.set_attribute('images', 'PARANG', angles, static=False)
module = StackAndSubsetModule(name_in='stack2',
image_in_tag='images',
image_out_tag='stack2',
random=None,
stacking=2,
combine='median',
max_rotation=1.)
self.pipeline.add_module(module)
with pytest.warns(UserWarning) as warning:
self.pipeline.run_module('stack2')
assert len(warning) == 1
assert warning[0].message.args[0] == 'Testing of util.module.stack_angles has been ' \
'limited, please use carefully.'
data = self.pipeline.get_data('stack2')
assert np.allclose(data[0, 50, 50],
0.09798413502193704,
rtol=limit,
atol=0.)
assert np.allclose(np.mean(data),
0.00010035876175210947,
rtol=limit,
atol=0.)
assert data.shape == (22, 100, 100)
data = self.pipeline.get_data('header_stack2/INDEX')
assert np.allclose(data, np.arange(22), rtol=limit, atol=0.)
assert data.shape == (22, )
data = self.pipeline.get_data('header_stack2/PARANG')
assert data.shape == (22, )
self.pipeline.set_attribute('images',
'PARANG',
np.arange(1., 41., 1.),
static=False)
def test_stack_max_rotation(self) -> None:
angles = np.arange(10.)
angles[1:6] = 3.
angles[9] = 50.
self.pipeline.set_attribute('images', 'PARANG', angles, static=False)
module = StackAndSubsetModule(name_in='stack2',
image_in_tag='images',
image_out_tag='stack2',
random=None,
stacking=2,
combine='median',
max_rotation=1.)
self.pipeline.add_module(module)
with pytest.warns(UserWarning) as warning:
self.pipeline.run_module('stack2')
assert len(warning) == 1
assert warning[0].message.args[0] == 'Testing of util.module.stack_angles has been ' \
'limited, please use carefully.'
data = self.pipeline.get_data('stack2')
assert np.mean(data) == pytest.approx(0.08580759396987508,
rel=self.limit,
abs=0.)
assert data.shape == (7, 11, 11)
data = self.pipeline.get_data('header_stack2/INDEX')
assert data == pytest.approx(np.arange(7), rel=self.limit, abs=0.)
assert data.shape == (7, )
data = self.pipeline.get_data('header_stack2/PARANG')
assert data.shape == (7, )
self.pipeline.set_attribute('images',
'PARANG',
np.arange(10.),
static=False)
def test_stack_and_subset(self) -> None:
self.pipeline.set_attribute('images',
'PARANG',
np.arange(1., 41., 1.),
static=False)
module = StackAndSubsetModule(name_in='stack1',
image_in_tag='images',
image_out_tag='stack1',
random=10,
stacking=2,
combine='mean',
max_rotation=None)
self.pipeline.add_module(module)
self.pipeline.run_module('stack1')
data = self.pipeline.get_data('stack1')
assert np.allclose(data[0, 50, 50],
0.09816320034649725,
rtol=limit,
atol=0.)
assert np.allclose(np.mean(data),
9.983545774937238e-05,
rtol=limit,
atol=0.)
assert data.shape == (10, 100, 100)
data = self.pipeline.get_data('header_stack1/INDEX')
assert np.allclose(data, np.arange(10), rtol=limit, atol=0.)
assert data.shape == (10, )
data = self.pipeline.get_data('header_stack1/PARANG')
parang = [1.5, 15.5, 19.5, 23.5, 25.5, 29.5, 31.5, 35.5, 37.5, 39.5]
assert np.allclose(data, parang, rtol=limit, atol=0.)
assert data.shape == (10, )