def full(images: Images,
cors: List[ScalarCoR],
recon_params: ReconstructionParameters,
progress: Optional[Progress] = None) -> Images:
progress = Progress.ensure_instance(progress, num_steps=images.height)
output_shape = (images.num_sinograms, images.width, images.width)
output_images: Images = Images.create_empty_images(
output_shape, images.dtype, images.metadata)
output_images.record_operation('AstraRecon.full', 'Reconstruction',
**recon_params.to_dict())
# FIXME multiple GPU support - just starting up a Pool doesn't seem to work
# the GPUs can't initialise the memory properly. Not sure why
# num_gpus = AstraRecon._count_gpus()
# LOG.info(f"Running with {num_gpus} GPUs")
# partial = ptsm.create_partial(AstraRecon.single, ptsm.fwd_gpu_recon,
# num_gpus=num_gpus, cors=cors,
# proj_angles=proj_angles, recon_params=recon_params)
# ptsm.execute(images.sinograms, output_images.data, partial, num_gpus, progress=progress)
proj_angles = images.projection_angles()
for i in range(images.height):
output_images.data[i] = AstraRecon.single_sino(
images.sino(i), cors[i], proj_angles, recon_params)
progress.update(1, "Reconstructed slice")
return output_images
def test_adjust_cor(self):
images = generate_images()
m = CORInspectionDialogModel(
images, 5, ScalarCoR(20),
ReconstructionParameters('FBP_CUDA', 'ram-lak'), False)
m.centre_value = 5
m.step = 1
m.adjust(ImageType.CURRENT)
self.assertEqual(m.centre_value, 5)
self.assertEqual(m.step, 0.5)
m.adjust(ImageType.LESS)
self.assertEqual(m.centre_value, 4.5)
self.assertEqual(m.step, 0.5)
m.adjust(ImageType.CURRENT)
self.assertEqual(m.centre_value, 4.5)
self.assertEqual(m.step, 0.25)
m.adjust(ImageType.MORE)
self.assertEqual(m.centre_value, 4.75)
self.assertEqual(m.step, 0.25)
m.adjust(ImageType.CURRENT)
self.assertEqual(m.centre_value, 4.75)
self.assertEqual(m.step, 0.125)
def test_construct(self):
images = generate_images()
m = CORInspectionDialogModel(
images, 5, ScalarCoR(20),
ReconstructionParameters('FBP_CUDA', 'ram-lak'), False)
npt.assert_equal(m.sino, images.sino(5))
self.assertEqual(m.cor_extents, (0, 9))
self.assertEqual(m.proj_angles.value.shape, (10, ))
def test_current_cor(self):
images = generate_images()
m = CORInspectionDialogModel(images, 5, ScalarCoR(20), ReconstructionParameters('FBP_CUDA', 'ram-lak'))
m.centre_cor = 5
m.cor_step = 1
self.assertEqual(m.cor(ImageType.LESS), 4)
self.assertEqual(m.cor(ImageType.CURRENT), 5)
self.assertEqual(m.cor(ImageType.MORE), 6)
def test_divide_iters_step(self):
images = generate_images()
m = CORInspectionDialogModel(
images, 5, ScalarCoR(20),
ReconstructionParameters('FBP_CUDA', 'ram-lak'), True)
m.step = 11
m._divide_step()
self.assertEqual(m.step, 5)
def recon_params(self) -> ReconstructionParameters:
return ReconstructionParameters(
algorithm=self.algorithm_name,
filter_name=self.filter_name,
num_iter=self.num_iter,
cor=ScalarCoR(self.rotation_centre),
tilt=Degrees(self.tilt),
pixel_size=self.pixel_size,
max_projection_angle=self.max_proj_angle)
def setUp(self, model) -> None:
self.view = mock.MagicMock()
self.model = model.return_value
self.recon_params = ReconstructionParameters("", "", 0, ScalarCoR(2),
Degrees(2), 2, 2)
self.presenter = CORInspectionDialogPresenter(self.view,
th.generate_images(), 5,
ScalarCoR(2),
self.recon_params, False)
def test_iters_mode_init(self):
images = generate_images()
m = CORInspectionDialogModel(
images, 5, ScalarCoR(20),
ReconstructionParameters('FBP_CUDA', 'ram-lak'), True)
self.assertEqual(m.centre_value, INIT_ITERS_CENTRE_VALUE)
self.assertEqual(m.step, INIT_ITERS_STEP)
self.assertEqual(m._recon_preview, m._recon_iters_preview)
self.assertEqual(m._divide_step, m._divide_iters_step)
def test_cor_mode_init(self):
images = generate_images()
initial_cor = ScalarCoR(20)
m = CORInspectionDialogModel(
images, 5, initial_cor,
ReconstructionParameters('FBP_CUDA', 'ram-lak'), False)
self.assertEqual(m.centre_value, initial_cor.value)
self.assertEqual(m.step, images.width * 0.05)
self.assertEqual(m._recon_preview, m._recon_cor_preview)
self.assertEqual(m._divide_step, m._divide_cor_step)
def test_recon_iters_preview(self, replace_mock):
images = generate_images()
m = CORInspectionDialogModel(
images, 5, ScalarCoR(20),
ReconstructionParameters('FBP_CUDA', 'ram-lak'), True)
m.reconstructor = Mock()
m.recon_preview(ImageType.CURRENT)
replace_mock.assert_called_once_with(m.recon_params, num_iter=100)
m.reconstructor.single_sino.assert_called_once_with(
m.sino, m.initial_cor, m.proj_angles, replace_mock.return_value)
def test_do_preview_reconstruct_slice(self, mock_start_async_task_view):
recon_params = ReconstructionParameters("FBP", "ram-lak", 10)
self.view.recon_params.return_value = recon_params
self.presenter.model.preview_slice_idx = 0
self.presenter.model.last_cor = ScalarCoR(150)
self.presenter.model.data_model._cached_gradient = None
self.presenter.do_preview_reconstruct_slice()
self.view.update_sinogram.assert_called_once()
mock_start_async_task_view.assert_called_once()
self.view.recon_params.assert_called_once()
def test_apply_pixel_size(self):
images = generate_images()
initial_value = images.data[0][0, 0]
test_pixel_size = 100
recon_params = ReconstructionParameters("FBP",
"ram-lak",
test_pixel_size,
pixel_size=test_pixel_size)
images = self.model._apply_pixel_size(images, recon_params)
# converts the number we put for pixel size to microns
expected_value = initial_value / (test_pixel_size * 1e-4)
self.assertAlmostEqual(expected_value, images.data[0][0, 0], places=4)
self.assertEqual(test_pixel_size, images.metadata[const.PIXEL_SIZE])
self.assertEqual(1, len(images.metadata[const.OPERATION_HISTORY]))
def test_iterations(self):
images = generate_images()
m = CORInspectionDialogModel(
images, 5, ScalarCoR(20),
ReconstructionParameters('FBP_CUDA', 'ram-lak'), True)
m.adjust(ImageType.LESS)
self.assertEqual(m.centre_value, 50)
self.assertEqual(m.step, 50)
m.adjust(ImageType.CURRENT)
self.assertEqual(m.centre_value, 50)
self.assertEqual(m.step, 25)
m.adjust(ImageType.MORE)
self.assertEqual(m.centre_value, 75)
self.assertEqual(m.step, 25)
def test_run_preview_recon(self, mock_get_reconstructor_for):
mock_reconstructor = mock.Mock()
mock_reconstructor.single_sino = mock.Mock()
mock_get_reconstructor_for.return_value = mock_reconstructor
expected_idx = 5
expected_sino = self.model.images.sino(expected_idx)
expected_cor = ScalarCoR(15)
expected_recon_params = ReconstructionParameters("FBP_CUDA", "ram-lak")
self.model.run_preview_recon(expected_idx, expected_cor,
expected_recon_params)
mock_get_reconstructor_for.assert_called_once_with(
expected_recon_params.algorithm)
assert_called_once_with(mock_reconstructor.single_sino, expected_sino,
expected_cor,
self.model.images.projection_angles(),
expected_recon_params)
def test_set_slice_preview_index(self, mock_get_reconstructor_for):
mock_reconstructor = mock.Mock()
mock_reconstructor.single_sino = mock.Mock()
mock_reconstructor.single_sino.return_value = np.random.rand(128, 128)
mock_get_reconstructor_for.return_value = mock_reconstructor
recon_params = ReconstructionParameters("FBP", "ram-lak", 10)
self.view.recon_params.return_value = recon_params
self.presenter.set_preview_slice_idx(5)
self.assertEqual(self.presenter.model.preview_slice_idx, 5)
self.view.update_projection.assert_called_once()
self.view.update_sinogram.assert_called_once()
self.view.update_recon_preview.assert_called_once()
self.view.recon_params.assert_called_once()
mock_get_reconstructor_for.assert_called_once()
mock_reconstructor.single_sino.assert_called_once()
def full(images: Images,
cors: List[ScalarCoR],
recon_params: ReconstructionParameters,
progress: Optional[Progress] = None) -> Images:
progress = Progress.ensure_instance(progress, num_steps=images.height)
output_shape = (images.num_sinograms, images.width, images.width)
output_images: Images = Images.create_empty_images(
output_shape, images.dtype, images.metadata)
output_images.record_operation('AstraRecon.full', 'Reconstruction',
**recon_params.to_dict())
proj_angles = images.projection_angles(
recon_params.max_projection_angle)
for i in range(images.height):
output_images.data[i] = AstraRecon.single_sino(
images.sino(i), cors[i], proj_angles, recon_params)
progress.update(1, "Reconstructed slice")
return output_images
def test_do_reconstruct_slice(self, mock_get_reconstructor_for):
mock_reconstructor = mock.Mock()
mock_reconstructor.single_sino = mock.Mock()
mock_reconstructor.single_sino.return_value = np.random.rand(128, 128)
mock_get_reconstructor_for.return_value = mock_reconstructor
recon_params = ReconstructionParameters("FBP", "ram-lak", 10)
self.view.recon_params.return_value = recon_params
self.presenter.model.preview_slice_idx = 0
self.presenter.model.last_cor = ScalarCoR(150)
self.presenter.model.data_model._cached_gradient = None
self.presenter.do_preview_reconstruct_slice()
self.view.update_sinogram.assert_called_once()
self.view.update_recon_preview.assert_called_once()
self.view.recon_params.assert_called_once()
mock_get_reconstructor_for.assert_called_once()
mock_reconstructor.single_sino.assert_called_once()
def test_set_stack_uuid(self, mock_get_reconstructor_for):
# reset the model data
self.presenter.model.initial_select_data(None)
mock_reconstructor = mock.Mock()
mock_reconstructor.single_sino = mock.Mock()
mock_reconstructor.single_sino.return_value = np.random.rand(128, 128)
mock_get_reconstructor_for.return_value = mock_reconstructor
recon_params = ReconstructionParameters("FBP", "ram-lak", 10)
self.view.recon_params.return_value = recon_params
# first-time selecting this data after reset
self.presenter.set_stack_uuid(self.uuid)
self.view.get_stack_visualiser.assert_called_once_with(self.uuid)
self.view.update_projection.assert_called_once()
self.view.clear_cor_table.assert_called_once()
self.view.update_projection.assert_called_once()
self.view.update_sinogram.assert_called_once()
self.view.update_recon_preview.assert_called_once()
mock_get_reconstructor_for.assert_called_once()
mock_reconstructor.single_sino.assert_called_once()
self.view.recon_params.assert_called_once()
# calling again with the same stack shouldn't re-do everything
self.presenter.set_stack_uuid(self.uuid)
self.assertEqual(self.view.get_stack_visualiser.call_count, 2)
self.view.get_stack_visualiser.assert_has_calls([mock.call(self.uuid), mock.call(self.uuid)])
self.view.update_projection.assert_called_once()
self.view.clear_cor_table.assert_called_once()
self.view.update_projection.assert_called_once()
self.view.update_sinogram.assert_called_once()
self.view.update_recon_preview.assert_called_once()
mock_get_reconstructor_for.assert_called_once()
mock_reconstructor.single_sino.assert_called_once()
def recon_params(self) -> ReconstructionParameters:
return ReconstructionParameters(self.algorithm_name, self.filter_name,
self.num_iter,
ScalarCoR(self.rotation_centre),
Degrees(self.tilt))
def test_start_cor_step(self):
images = generate_images()
m = CORInspectionDialogModel(
images, 5, ScalarCoR(20),
ReconstructionParameters('FBP_CUDA', 'ram-lak'), False)
self.assertEqual(images.width * 0.05, m.step)
