def test_get_centre_slice(self): #returns the 2D version AG = AcquisitionGeometry.create_Cone3D(source_position=[0, -500, 0], detector_position=[0, 1000, 0]) AG2 = AcquisitionGeometry.create_Cone2D(source_position=[0, -500], detector_position=[0, 1000]) cs = AG.config.system.get_centre_slice() self.assertEqual(cs, AG2.config.system) #returns the 2D version AG = AcquisitionGeometry.create_Cone3D( source_position=[0, -500, 0], detector_position=[0, 1000, 0], rotation_axis_direction=[-1, 0, 1], detector_direction_x=[1, 0, 1], detector_direction_y=[-1, 0, 1]) AG2 = AcquisitionGeometry.create_Cone2D(source_position=[0, -500], detector_position=[0, 1000]) cs = AG.config.system.get_centre_slice() self.assertEqual(cs, AG2.config.system) #raise error if cannot extract a cnetre slice AG = AcquisitionGeometry.create_Cone3D( source_position=[0, -500, 0], detector_position=[0, 1000, 0], rotation_axis_direction=[1, 0, 1]) with self.assertRaises(ValueError): cs = AG.config.system.get_centre_slice() AG = AcquisitionGeometry.create_Cone3D(source_position=[0, -500, 0], detector_position=[0, 1000, 0], detector_direction_x=[1, 0, 1], detector_direction_y=[-1, 0, 1]) with self.assertRaises(ValueError): cs = AG.config.system.get_centre_slice()
def test_calculate_magnification(self): AG = AcquisitionGeometry.create_Cone2D(source_position=[0,-500], detector_position=[0.,1000.]) out = AG.config.system.calculate_magnification() self.assertEqual(out, [500, 1000, 3]) AG = AcquisitionGeometry.create_Cone2D(source_position=[0,-500], detector_position=[0.,1000.], rotation_axis_position=[0.,250.]) out = AG.config.system.calculate_magnification() self.assertEqual(out, [750, 750, 2]) AG = AcquisitionGeometry.create_Cone2D(source_position=[0,-500], detector_position=[0.,1000.], rotation_axis_position=[5.,0.]) out = AG.config.system.calculate_magnification() source_to_object = numpy.sqrt(5.0**2 + 500.0**2) theta = math.atan2(5.0,500.0) source_to_detector = 1500.0/math.cos(theta) self.assertEqual(out, [source_to_object, source_to_detector - source_to_object, source_to_detector/source_to_object]) AG = AcquisitionGeometry.create_Cone2D(source_position=[0,-500], detector_position=[0.,1000.], rotation_axis_position=[5.,0.],detector_direction_x=[math.sqrt(5),math.sqrt(5)]) out = AG.config.system.calculate_magnification() source_to_object = numpy.sqrt(5.0**2 + 500.0**2) ab = (AG.config.system.rotation_axis.position - AG.config.system.source.position).astype(numpy.float64)/source_to_object #source_position + d * ab = detector_position + t * detector_direction_x #x: d * ab[0] = t * detector_direction_x[0] #y: -500 + d * ab[1] = 1000 + t * detector_direction_x[1] # t = (d * ab[0]) / math.sqrt(5) # d = 1500 / (ab[1] - ab[0]) source_to_detector = 1500 / (ab[1] - ab[0]) self.assertEqual(out, [source_to_object, source_to_detector - source_to_object, source_to_detector/source_to_object])
def test_cone2D(self): ag = AcquisitionGeometry.create_Cone2D(source_position=[0,-2], detector_position=[0,1])\ .set_angles(self.angles_rad, angle_unit='radian')\ .set_labels(['angle','horizontal'])\ .set_panel(self.num_pixels_x, self.pixel_size_x) ig = ag.get_ImageGeometry() ig.voxel_num_y = 50 ig.voxel_size_y /= 2 angles_rad = np.array([-np.pi / 2, -np.pi, -3 * np.pi / 2]) #2D cone tg_geometry, tg_angles = CIL2TIGREGeometry.getTIGREGeometry(ig, ag) np.testing.assert_allclose( tg_geometry.DSD, ag.dist_center_detector + ag.dist_source_center) np.testing.assert_allclose(tg_geometry.DSO, ag.dist_source_center) np.testing.assert_allclose(tg_angles, angles_rad) np.testing.assert_allclose(tg_geometry.dDetector, ag.config.panel.pixel_size[::-1]) np.testing.assert_allclose(tg_geometry.nDetector, ag.config.panel.num_pixels[::-1]) np.testing.assert_allclose( tg_geometry.sDetector, tg_geometry.dDetector * tg_geometry.nDetector) np.testing.assert_allclose(tg_geometry.rotDetector, 0) np.testing.assert_allclose(tg_geometry.offDetector, 0) np.testing.assert_allclose(tg_geometry.offOrigin, 0) mag = ag.magnification np.testing.assert_allclose(tg_geometry.nVoxel, [1, 50, 128]) np.testing.assert_allclose(tg_geometry.dVoxel, [0.1 / mag, 0.05 / mag, 0.1 / mag])
def setUp(self): #%% Setup Geometry voxel_num_xy = 255 voxel_num_z = 15 mag = 2 src_to_obj = 50 src_to_det = src_to_obj * mag pix_size = 0.2 det_pix_x = voxel_num_xy det_pix_y = voxel_num_z num_projections = 1000 angles = np.linspace(0, 360, num=num_projections, endpoint=False) self.ag = AcquisitionGeometry.create_Cone2D([0,-src_to_obj],[0,src_to_det-src_to_obj])\ .set_angles(angles)\ .set_panel(det_pix_x, pix_size)\ .set_labels(['angle','horizontal']) self.ig = self.ag.get_ImageGeometry() self.ag3D = AcquisitionGeometry.create_Cone3D([0,-src_to_obj,0],[0,src_to_det-src_to_obj,0])\ .set_angles(angles)\ .set_panel((det_pix_x,det_pix_y), (pix_size,pix_size))\ .set_labels(['angle','vertical','horizontal']) self.ig3D = self.ag3D.get_ImageGeometry() self.ad3D = self.ag3D.allocate('random') self.ig3D = self.ag3D.get_ImageGeometry()
def test_get_ImageGeometry(self): AG = AcquisitionGeometry.create_Parallel2D()\ .set_panel(num_pixels=[512,1],pixel_size=[0.1,0.1]) IG = AG.get_ImageGeometry() IG_gold = ImageGeometry(512,512,0,0.1,0.1,1,0,0,0,1) self.assertEqual(IG, IG_gold) AG = AcquisitionGeometry.create_Parallel3D()\ .set_panel(num_pixels=[512,3],pixel_size=[0.1,0.2]) IG = AG.get_ImageGeometry() IG_gold = ImageGeometry(512,512,3,0.1,0.1,0.2,0,0,0,1) self.assertEqual(IG, IG_gold) AG = AcquisitionGeometry.create_Cone2D(source_position=[0,-500], detector_position=[0.,500.])\ .set_panel(num_pixels=[512,1],pixel_size=[0.1,0.2]) IG = AG.get_ImageGeometry() IG_gold = ImageGeometry(512,512,0,0.05,0.05,1,0,0,0,1) self.assertEqual(IG, IG_gold) AG = AcquisitionGeometry.create_Cone3D(source_position=[0,-500,0], detector_position=[0.,500.,0])\ .set_panel(num_pixels=[512,3],pixel_size=[0.1,0.2]) IG = AG.get_ImageGeometry() IG_gold = ImageGeometry(512,512,3,0.05,0.05,0.1,0,0,0,1) self.assertEqual(IG, IG_gold) AG = AcquisitionGeometry.create_Cone3D(source_position=[0,-500,0], detector_position=[0.,500.,0])\ .set_panel(num_pixels=[512,3],pixel_size=[0.1,0.2]) IG = AG.get_ImageGeometry(resolution=0.5) IG_gold = ImageGeometry(256,256,2,0.025,0.025,0.05,0,0,0,1) self.assertEqual(IG, IG_gold)
def __init__(self, volume_geometry, sinogram_geometry): super(FBP_Flexible, self).__init__(volume_geometry=volume_geometry, sinogram_geometry=sinogram_geometry) #convert parallel geomerty to cone with large source to object sino_geom_cone = sinogram_geometry.copy() sino_geom_cone.config.system.update_reference_frame() #reverse ray direction unit-vector direction and extend to inf cone_source = -sino_geom_cone.config.system.ray.direction * sino_geom_cone.config.panel.pixel_size[ 1] * sino_geom_cone.config.panel.num_pixels[1] * 1e6 detector_position = sino_geom_cone.config.system.detector.position detector_direction_x = sino_geom_cone.config.system.detector.direction_x if sinogram_geometry.dimension == '2D': tmp = AcquisitionGeometry.create_Cone2D(cone_source, detector_position, detector_direction_x) else: detector_direction_y = sino_geom_cone.config.system.detector.direction_y tmp = AcquisitionGeometry.create_Cone3D(cone_source, detector_position, detector_direction_x, detector_direction_y) sino_geom_cone.config.system = tmp.config.system.copy() self.vol_geom_astra, self.proj_geom_astra = convert_geometry_to_astra_vec( volume_geometry, sino_geom_cone)
def test_get_centre_slice(self): AG = AcquisitionGeometry.create_Cone2D(source_position=[0, -500], detector_position=[0., 1000.]) AG2 = AG.copy() AG2.config.system.get_centre_slice() self.assertEqual(AG.config.system, AG2.config.system)
def test_align_reference_frame_tigre(self): ag = AcquisitionGeometry.create_Cone2D(source_position=[0, 50], detector_position=[0., -100.], rotation_axis_position=[5., 2]) ag.set_panel(100) ag_align = ag.copy() ag_align.config.system.align_reference_frame('tigre') numpy.testing.assert_allclose(ag_align.config.system.source.position, [0, -ag.dist_source_center], atol=1E-6) numpy.testing.assert_allclose( ag_align.config.system.rotation_axis.position, [0, 0], rtol=1E-6) cos_theta = abs( ag.config.system.source.position[1] - ag.config.system.rotation_axis.position[1]) / ag.dist_source_center sin_theta = math.sin(math.acos(cos_theta)) vec = ag.config.system.detector.position - ag.config.system.source.position tmp = abs(vec[1]) * cos_theta det_y = tmp - ag.dist_source_center det_x = numpy.sqrt(vec[1]**2 - tmp**2) numpy.testing.assert_allclose(ag_align.config.system.detector.position, [det_x, det_y], rtol=1E-6) dir_x = -ag.config.system.detector.direction_x[0] * cos_theta dir_y = ag.config.system.detector.direction_x[0] * sin_theta numpy.testing.assert_allclose( ag_align.config.system.detector.direction_x, [dir_x, dir_y], rtol=1E-6)
def has_gpu_tigre(): if not has_tigre: return False has_gpu = True if has_nvidia_smi(): from cil.plugins.tigre import ProjectionOperator from tigre.utilities.errors import TigreCudaCallError N = 3 angles = np.linspace(0, np.pi, 2, dtype='float32') ag = AcquisitionGeometry.create_Cone2D([0,-100],[0,200])\ .set_angles(angles, angle_unit='radian')\ .set_panel(N, 0.1)\ .set_labels(['angle', 'horizontal']) ig = ag.get_ImageGeometry() data = ig.allocate(1) Op = ProjectionOperator(ig, ag) try: Op.direct(data) has_gpu = True except TigreCudaCallError: has_gpu = False else: has_gpu = False print("has_gpu_tigre\t{}".format(has_gpu)) return has_gpu
def setUp(self): #%% Setup Geometry voxel_num_xy = 255 voxel_num_z = 15 cs_ind = (voxel_num_z - 1) // 2 mag = 2 src_to_obj = 50 src_to_det = src_to_obj * mag pix_size = 0.2 det_pix_x = voxel_num_xy det_pix_y = voxel_num_z num_projections = 1000 angles = np.linspace(0, 360, num=num_projections, endpoint=False) self.ag = AcquisitionGeometry.create_Cone2D([0,-src_to_obj],[0,src_to_det-src_to_obj])\ .set_angles(angles)\ .set_panel(det_pix_x, pix_size)\ .set_labels(['angle','horizontal']) self.ig = self.ag.get_ImageGeometry() self.ag3D = AcquisitionGeometry.create_Cone3D([0,-src_to_obj,0],[0,src_to_det-src_to_obj,0])\ .set_angles(angles)\ .set_panel((det_pix_x,det_pix_y), (pix_size,pix_size))\ .set_labels(['angle','vertical','horizontal']) self.ig3D = self.ag3D.get_ImageGeometry() #%% Create phantom kernel_size = voxel_num_xy kernel_radius = (kernel_size - 1) // 2 y, x = np.ogrid[-kernel_radius:kernel_radius + 1, -kernel_radius:kernel_radius + 1] circle1 = [5, 0, 0] #r,x,y dist1 = ((x - circle1[1])**2 + (y - circle1[2])**2)**0.5 circle2 = [5, 80, 0] #r,x,y dist2 = ((x - circle2[1])**2 + (y - circle2[2])**2)**0.5 circle3 = [25, 0, 80] #r,x,y dist3 = ((x - circle3[1])**2 + (y - circle3[2])**2)**0.5 mask1 = (dist1 - circle1[0]).clip(0, 1) mask2 = (dist2 - circle2[0]).clip(0, 1) mask3 = (dist3 - circle3[0]).clip(0, 1) phantom = 1 - np.logical_and(np.logical_and(mask1, mask2), mask3) self.golden_data = self.ig3D.allocate(0) for i in range(4): self.golden_data.fill(array=phantom, vertical=7 + i) self.golden_data_cs = self.golden_data.get_slice(vertical=cs_ind, force=True) self.Op = ProjectionOperator(self.ig3D, self.ag3D) self.fp = self.Op.direct(self.golden_data)
def test_update_reference_frame(self): AG = AcquisitionGeometry.create_Cone2D(source_position=[0,-500], detector_position=[0.,1000.], rotation_axis_position=[5.,2.]) AG.config.system.update_reference_frame() numpy.testing.assert_allclose(AG.config.system.source.position, [-5,-502], rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.detector.position, [-5,998], rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.detector.direction_x, [1,0], rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.rotation_axis.position, [0,0], rtol=1E-6)
def test_system_description(self): AG = AcquisitionGeometry.create_Cone2D(source_position=[0, -50], detector_position=[0, 100]) self.assertTrue(AG.system_description == 'simple') AG = AcquisitionGeometry.create_Cone2D(source_position=[5, -50], detector_position=[5, 100], rotation_axis_position=[5, 0]) self.assertTrue(AG.system_description == 'simple') AG = AcquisitionGeometry.create_Cone2D(source_position=[5, -50], detector_position=[0, 100]) self.assertTrue(AG.system_description == 'advanced') AG = AcquisitionGeometry.create_Cone2D(source_position=[0, -50], detector_position=[0, 100], rotation_axis_position=[5, 0]) self.assertTrue(AG.system_description == 'offset')
def test_create_Cone2D(self): #default source_position = [0.1, -500.0] detector_position = [-1.3, 1000.0] AG = AcquisitionGeometry.create_Cone2D(source_position, detector_position) numpy.testing.assert_allclose(AG.config.system.source.position, source_position, rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.detector.position, detector_position, rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.detector.direction_x, [1, 0], rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.rotation_axis.position, [0, 0], rtol=1E-6) #values detector_direction_x = [1, 0.2] rotation_axis_position = [0.1, 2] AG = AcquisitionGeometry.create_Cone2D(source_position, detector_position, detector_direction_x, rotation_axis_position) detector_direction_x = numpy.asarray(detector_direction_x) detector_direction_x /= numpy.sqrt((detector_direction_x**2).sum()) numpy.testing.assert_allclose(AG.config.system.source.position, source_position, rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.detector.position, detector_position, rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.detector.direction_x, detector_direction_x, rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.rotation_axis.position, rotation_axis_position, rtol=1E-6)
def setUp(self): N = 128 angles = np.linspace(0, 360, 50, True, dtype=np.float32) offset = 0.4 ag = AcquisitionGeometry.create_Cone2D((offset, -100), (offset, 100)) ag.set_panel(N) ag.set_angles(angles, angle_unit=AcquisitionGeometry.DEGREE) ig = ag.get_ImageGeometry() self.ag = ag self.ig = ig self.N = N
def setUp(self): self.acq_data = dataexample.SIMULATED_CONE_BEAM_DATA.get().get_slice( vertical='centre') self.img_data = dataexample.SIMULATED_SPHERE_VOLUME.get().get_slice( vertical='centre') self.acq_data = np.log(self.acq_data) self.acq_data *= -1.0 self.ig = self.img_data.geometry self.ag = self.acq_data.geometry self.ag_small = AcquisitionGeometry.create_Cone2D([0, -1000], [0, 0]) self.ag_small.set_panel((16)) self.ag_small.set_angles([0])
def setUp(self): # Define image geometry. pixels_x = 128 pixels_y = 3 angles_deg = np.asarray([0, 90.0, 180.0], dtype='float32') angles_rad = angles_deg * np.pi / 180.0 ag = AcquisitionGeometry.create_Parallel2D()\ .set_angles(angles_rad, angle_unit='radian')\ .set_labels(['angle','horizontal'])\ .set_panel(pixels_x, 0.1) ig = ag.get_ImageGeometry() ag_deg = AcquisitionGeometry.create_Parallel2D()\ .set_angles(angles_deg, angle_unit='degree')\ .set_labels(['angle','horizontal'])\ .set_panel(pixels_x, 0.1) ag_cone = AcquisitionGeometry.create_Cone2D([0,-2], [0,1])\ .set_angles(angles_rad, angle_unit='radian')\ .set_labels(['angle','horizontal'])\ .set_panel(pixels_x, 0.1) ag3 = AcquisitionGeometry.create_Parallel3D()\ .set_angles(angles_rad, angle_unit='radian')\ .set_labels(['vertical', 'angle','horizontal'])\ .set_panel((pixels_x,pixels_y), (0.1,0.1)) ig3 = ag3.get_ImageGeometry() ag3_cone = AcquisitionGeometry.create_Cone3D([0,-2,0], [0,1,0])\ .set_angles(angles_rad, angle_unit='radian')\ .set_labels(['vertical', 'angle','horizontal'])\ .set_panel((pixels_x,pixels_y), (0.1,0.1)) self.ig = ig self.ig3 = ig3 self.ag = ag self.ag_deg = ag_deg self.ag_cone = ag_cone self.ag3 = ag3 self.ag3_cone = ag3_cone
def setUp(self): N = 3 angles = np.linspace(0, np.pi, 2, dtype='float32') self.ag = AcquisitionGeometry.create_Cone2D([0,-100],[0,200])\ .set_angles(angles, angle_unit='radian')\ .set_panel(N, 0.1)\ .set_labels(['angle', 'horizontal']) self.ig = self.ag.get_ImageGeometry() self.Op = ProjectionOperator(self.ig, self.ag) self.ag3D = AcquisitionGeometry.create_Cone3D([0,-100,0],[0,200,0])\ .set_angles(angles, angle_unit='radian')\ .set_panel((N,N), (0.1,0.1))\ .set_labels(['angle', 'vertical', 'horizontal']) self.ig3D = self.ag3D.get_ImageGeometry() self.Op3D = ProjectionOperator(self.ig3D, self.ag3D)
def test_align_reference_frame_cil(self): AG = AcquisitionGeometry.create_Cone2D(source_position=[0, 50], detector_position=[0., -100.], rotation_axis_position=[5., 2.]) AG.set_panel(100) AG.config.system.align_reference_frame('cil') numpy.testing.assert_allclose(AG.config.system.source.position, [5, -48], rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.detector.position, [5, 102], rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.detector.direction_x, [-1, 0], rtol=1E-6) numpy.testing.assert_allclose(AG.config.system.rotation_axis.position, [0, 0], rtol=1E-6)
def test_cone2D(self): ag = AcquisitionGeometry.create_Cone2D(source_position=[0,-6], detector_position=[0,16])\ .set_angles(self.angles_rad, angle_unit='radian')\ .set_labels(['angle','horizontal'])\ .set_panel(self.num_pixels_x, self.pixel_size_x) #2D cone tg_geometry, tg_angles = CIL2TIGREGeometry.getTIGREGeometry( self.ig, ag) for i, ang in enumerate(tg_angles): ang2 = -(self.angles_rad[i] + np.pi / 2) self.compare_angles(ang, ang2, 1e-6) self.assertTrue(tg_geometry.mode == 'cone') np.testing.assert_allclose( tg_geometry.DSD, ag.dist_center_detector + ag.dist_source_center) np.testing.assert_allclose(tg_geometry.DSO, ag.dist_source_center) np.testing.assert_allclose(tg_geometry.dDetector, ag.config.panel.pixel_size[::-1]) np.testing.assert_allclose(tg_geometry.nDetector, ag.config.panel.num_pixels[::-1]) np.testing.assert_allclose( tg_geometry.sDetector, tg_geometry.dDetector * tg_geometry.nDetector) np.testing.assert_allclose(tg_geometry.rotDetector, 0) np.testing.assert_allclose(tg_geometry.offDetector, 0) np.testing.assert_allclose(tg_geometry.offOrigin, 0) np.testing.assert_allclose( tg_geometry.nVoxel, [1, self.ig.voxel_num_y, self.ig.voxel_num_x]) np.testing.assert_allclose(tg_geometry.dVoxel, [ ag.config.panel.pixel_size[1] / ag.magnification, self.ig.voxel_size_y, self.ig.voxel_size_x ])
def get_geometry(self): ''' Parse NEXUS file and returns either ImageData or Acquisition Data depending on file content ''' with h5py.File(self.file_name, 'r') as dfile: if np.string_(dfile.attrs['creator']) != np.string_( 'NEXUSDataWriter.py'): raise Exception( 'We can parse only files created by NEXUSDataWriter.py') ds_data = dfile['entry1/tomo_entry/data/data'] if ds_data.attrs['data_type'] == 'ImageData': self._geometry = ImageGeometry( voxel_num_x=int(ds_data.attrs['voxel_num_x']), voxel_num_y=int(ds_data.attrs['voxel_num_y']), voxel_num_z=int(ds_data.attrs['voxel_num_z']), voxel_size_x=ds_data.attrs['voxel_size_x'], voxel_size_y=ds_data.attrs['voxel_size_y'], voxel_size_z=ds_data.attrs['voxel_size_z'], center_x=ds_data.attrs['center_x'], center_y=ds_data.attrs['center_y'], center_z=ds_data.attrs['center_z'], channels=ds_data.attrs['channels']) if ds_data.attrs.__contains__('channel_spacing') == True: self._geometry.channel_spacing = ds_data.attrs[ 'channel_spacing'] # read the dimension_labels from dim{} dimension_labels = self.read_dimension_labels(ds_data.attrs) else: # AcquisitionData if ds_data.attrs.__contains__('dist_source_center') or dfile[ 'entry1/tomo_entry'].__contains__( 'config/source/position'): geom_type = 'cone' else: geom_type = 'parallel' if ds_data.attrs.__contains__('num_pixels_v'): num_pixels_v = ds_data.attrs.get('num_pixels_v') elif ds_data.attrs.__contains__('pixel_num_v'): num_pixels_v = ds_data.attrs.get('pixel_num_v') else: num_pixels_v = 1 if num_pixels_v > 1: dim = 3 else: dim = 2 if self.is_old_file_version(): num_pixels_h = ds_data.attrs.get('pixel_num_h', 1) num_channels = ds_data.attrs['channels'] ds_angles = dfile['entry1/tomo_entry/data/rotation_angle'] if geom_type == 'cone' and dim == 3: self._geometry = AcquisitionGeometry.create_Cone3D( source_position=[ 0, -ds_data.attrs['dist_source_center'], 0 ], detector_position=[ 0, ds_data.attrs['dist_center_detector'], 0 ]) elif geom_type == 'cone' and dim == 2: self._geometry = AcquisitionGeometry.create_Cone2D( source_position=[ 0, -ds_data.attrs['dist_source_center'] ], detector_position=[ 0, ds_data.attrs['dist_center_detector'] ]) elif geom_type == 'parallel' and dim == 3: self._geometry = AcquisitionGeometry.create_Parallel3D( ) elif geom_type == 'parallel' and dim == 2: self._geometry = AcquisitionGeometry.create_Parallel2D( ) else: num_pixels_h = ds_data.attrs.get('num_pixels_h', 1) num_channels = ds_data.attrs['num_channels'] ds_angles = dfile['entry1/tomo_entry/config/angles'] rotation_axis_position = list(dfile[ 'entry1/tomo_entry/config/rotation_axis/position']) detector_position = list( dfile['entry1/tomo_entry/config/detector/position']) ds_detector = dfile['entry1/tomo_entry/config/detector'] if ds_detector.__contains__('direction_x'): detector_direction_x = list(dfile[ 'entry1/tomo_entry/config/detector/direction_x']) else: detector_direction_x = list(dfile[ 'entry1/tomo_entry/config/detector/direction_row']) if ds_detector.__contains__('direction_y'): detector_direction_y = list(dfile[ 'entry1/tomo_entry/config/detector/direction_y']) elif ds_detector.__contains__('direction_col'): detector_direction_y = list(dfile[ 'entry1/tomo_entry/config/detector/direction_col']) ds_rotate = dfile['entry1/tomo_entry/config/rotation_axis'] if ds_rotate.__contains__('direction'): rotation_axis_direction = list(dfile[ 'entry1/tomo_entry/config/rotation_axis/direction'] ) if geom_type == 'cone': source_position = list( dfile['entry1/tomo_entry/config/source/position']) if dim == 2: self._geometry = AcquisitionGeometry.create_Cone2D( source_position, detector_position, detector_direction_x, rotation_axis_position) else: self._geometry = AcquisitionGeometry.create_Cone3D(source_position,\ detector_position, detector_direction_x, detector_direction_y,\ rotation_axis_position, rotation_axis_direction) else: ray_direction = list( dfile['entry1/tomo_entry/config/ray/direction']) if dim == 2: self._geometry = AcquisitionGeometry.create_Parallel2D( ray_direction, detector_position, detector_direction_x, rotation_axis_position) else: self._geometry = AcquisitionGeometry.create_Parallel3D(ray_direction,\ detector_position, detector_direction_x, detector_direction_y,\ rotation_axis_position, rotation_axis_direction) # for all Aquisition data #set angles angles = list(ds_angles) angle_unit = ds_angles.attrs.get('angle_unit', 'degree') initial_angle = ds_angles.attrs.get('initial_angle', 0) self._geometry.set_angles(angles, initial_angle=initial_angle, angle_unit=angle_unit) #set panel pixel_size_v = ds_data.attrs.get('pixel_size_v', ds_data.attrs['pixel_size_h']) origin = ds_data.attrs.get('panel_origin', 'bottom-left') self._geometry.set_panel((num_pixels_h, num_pixels_v),\ pixel_size=(ds_data.attrs['pixel_size_h'], pixel_size_v),\ origin=origin) # set channels self._geometry.set_channels(num_channels) dimension_labels = [] dimension_labels = self.read_dimension_labels(ds_data.attrs) #set labels self._geometry.set_labels(dimension_labels) return self._geometry
def test_Slicer(self): #test parallel 2D case ray_direction = [0.1, 3.0] detector_position = [-1.3, 1000.0] detector_direction_row = [1.0, 0.2] rotation_axis_position = [0.1, 2.0] AG = AcquisitionGeometry.create_Parallel2D(ray_direction=ray_direction, detector_position=detector_position, detector_direction_x=detector_direction_row, rotation_axis_position=rotation_axis_position) angles = numpy.linspace(0, 360, 10, dtype=numpy.float32) AG.set_channels(num_channels=10) AG.set_angles(angles, initial_angle=10, angle_unit='radian') AG.set_panel(100, pixel_size=0.1) data = AG.allocate('random') s = Slicer(roi={'channel': (1, -2, 3), 'angle': (2, 9, 2), 'horizontal': (10, -11, 7)}) s.set_input(data) data_sliced = s.process() AG_sliced = AG.clone() AG_sliced.set_channels(num_channels=numpy.arange(1, 10-2, 3).shape[0]) AG_sliced.set_panel([numpy.arange(10, 100-11, 7).shape[0], 1], pixel_size=0.1) AG_sliced.set_angles(angles[2:9:2], initial_angle=10, angle_unit='radian') self.assertTrue(data_sliced.geometry == AG_sliced) numpy.testing.assert_allclose(data_sliced.as_array(), numpy.squeeze(data.as_array()[1:-2:3, 2:9:2, 10:-11:7]), rtol=1E-6) #%% #test parallel 3D case ray_direction = [0.1, 3.0, 0.4] detector_position = [-1.3, 1000.0, 2] detector_direction_row = [1.0, 0.2, 0.0] detector_direction_col = [0.0 ,0.0, 1.0] rotation_axis_position = [0.1, 2.0, 0.5] rotation_axis_direction = [0.1, 2.0, 0.5] AG = AcquisitionGeometry.create_Parallel3D(ray_direction=ray_direction, detector_position=detector_position, detector_direction_x=detector_direction_row, detector_direction_y=detector_direction_col, rotation_axis_position=rotation_axis_position, rotation_axis_direction=rotation_axis_direction) angles = numpy.linspace(0, 360, 10, dtype=numpy.float32) AG.set_channels(num_channels=10) AG.set_angles(angles, initial_angle=10, angle_unit='radian') AG.set_panel((100, 50), pixel_size=(0.1, 0.2)) AG.dimension_labels = ['vertical',\ 'horizontal',\ 'angle',\ 'channel'] data = AG.allocate('random') s = Slicer(roi={'channel': (None, 1), 'angle': -1, 'horizontal': (10, None, 2), 'vertical': (10, 12, 1)}) s.set_input(data) data_sliced = s.process() dimension_labels_sliced = list(data.geometry.dimension_labels) dimension_labels_sliced.remove('channel') dimension_labels_sliced.remove('vertical') AG_sliced = AG.clone() AG_sliced.dimension_labels = dimension_labels_sliced AG_sliced.set_channels(num_channels=1) AG_sliced.set_panel([numpy.arange(10, 100, 2).shape[0], numpy.arange(10, 12, 1).shape[0]], pixel_size=(0.1, 0.2)) self.assertTrue(data_sliced.geometry == AG_sliced) numpy.testing.assert_allclose(data_sliced.as_array(), numpy.squeeze(data.as_array()[10:12:1, 10::2, :, :1]), rtol=1E-6) #%% #test cone 2D case source_position = [0.1, 3.0] detector_position = [-1.3, 1000.0] detector_direction_row = [1.0, 0.2] rotation_axis_position = [0.1, 2.0] AG = AcquisitionGeometry.create_Cone2D(source_position=source_position, detector_position=detector_position, detector_direction_x=detector_direction_row, rotation_axis_position=rotation_axis_position) angles = numpy.linspace(0, 360, 10, dtype=numpy.float32) AG.set_channels(num_channels=10) AG.set_angles(angles, initial_angle=10, angle_unit='degree') AG.set_panel(100, pixel_size=0.1) data = AG.allocate('random') s = Slicer(roi={'channel': (1, None, 4), 'angle': (2, 9, 2), 'horizontal': (10, -10, 5)}) s.set_input(data) data_sliced = s.process() AG_sliced = AG.clone() AG_sliced.set_channels(num_channels=numpy.arange(1,10,4).shape[0]) AG_sliced.set_angles(AG.config.angles.angle_data[2:9:2], angle_unit='degree', initial_angle=10) AG_sliced.set_panel(numpy.arange(10,90,5).shape[0], pixel_size=0.1) self.assertTrue(data_sliced.geometry == AG_sliced) numpy.testing.assert_allclose(data_sliced.as_array(), numpy.squeeze(data.as_array()[1::4, 2:9:2, 10:-10:5]), rtol=1E-6) #%% #test cone 3D case source_position = [0.1, 3.0, 0.4] detector_position = [-1.3, 1000.0, 2] rotation_axis_position = [0.1, 2.0, 0.5] AG = AcquisitionGeometry.create_Cone3D(source_position=source_position, detector_position=detector_position, rotation_axis_position=rotation_axis_position) angles = numpy.linspace(0, 360, 10, dtype=numpy.float32) AG.set_channels(num_channels=10) AG.set_angles(angles, initial_angle=10, angle_unit='radian') AG.set_panel((100, 50), pixel_size=(0.1, 0.2)) AG.dimension_labels = ['vertical',\ 'horizontal',\ 'angle',\ 'channel'] data = AG.allocate('random') s = Slicer(roi={'channel': (None, 1), 'angle': -1, 'horizontal': (10, None, 2), 'vertical': (10, -10, 2)}) s.set_input(data) data_sliced = s.process() dimension_labels_sliced = list(data.geometry.dimension_labels) dimension_labels_sliced.remove('channel') AG_sliced = AG.clone() AG_sliced.dimension_labels = dimension_labels_sliced AG_sliced.set_channels(num_channels=1) AG_sliced.set_panel([numpy.arange(10, 100, 2).shape[0], numpy.arange(10, 50-10, 2).shape[0]], pixel_size=(0.1, 0.2)) self.assertTrue(data_sliced.geometry == AG_sliced) numpy.testing.assert_allclose(data_sliced.as_array(), numpy.squeeze(data.as_array()[10:-10:2, 10::2, :, :1]), rtol=1E-6) #%% test cone 3D - central slice s = Slicer(roi={'channel': (None, 1), 'angle': -1, 'horizontal': (10, None, 2), 'vertical': (25, 26)}) s.set_input(data) data_sliced = s.process() dimension_labels_sliced = list(data.geometry.dimension_labels) dimension_labels_sliced.remove('channel') dimension_labels_sliced.remove('vertical') AG_sliced = AG.subset(vertical='centre') AG_sliced = AG_sliced.subset(channel=1) AG_sliced.config.panel.num_pixels[0] = numpy.arange(10,100,2).shape[0] self.assertTrue(data_sliced.geometry == AG_sliced) numpy.testing.assert_allclose(data_sliced.as_array(), numpy.squeeze(data.as_array()[25:26, 10::2, :, :1]), rtol=1E-6) #%% test ImageData IG = ImageGeometry(voxel_num_x=20, voxel_num_y=30, voxel_num_z=12, voxel_size_x=0.1, voxel_size_y=0.2, voxel_size_z=0.3, channels=10, center_x=0.2, center_y=0.4, center_z=0.6, dimension_labels = ['vertical',\ 'channel',\ 'horizontal_y',\ 'horizontal_x']) data = IG.allocate('random') s = Slicer(roi={'channel': (None, None, 2), 'horizontal_x': -1, 'horizontal_y': (10, None, 2), 'vertical': (5, None, 3)}) s.set_input(data) data_sliced = s.process() IG_sliced = IG.copy() IG_sliced.voxel_num_y = numpy.arange(10, 30, 2).shape[0] IG_sliced.voxel_num_z = numpy.arange(5, 12, 3).shape[0] IG_sliced.channels = numpy.arange(0, 10, 2).shape[0] self.assertTrue(data_sliced.geometry == IG_sliced) numpy.testing.assert_allclose(data_sliced.as_array(), numpy.squeeze(data.as_array()[5:12:3, ::2, 10:30:2, :]), rtol=1E-6)
def set_up(self, file_name=None, roi={ 'angle': -1, 'horizontal': -1, 'vertical': -1 }, normalise=True, mode='bin', fliplr=False, **kwargs): self.file_name = file_name self.roi = roi self.normalise = normalise self.mode = mode self.fliplr = fliplr if 'normalize' in kwargs.keys(): self.normalise = kwargs.get('normalize', True) warnings.warn( "'normalize' has now been deprecated. Please use 'normalise' instead." ) if self.file_name == None: raise Exception('Path to xtek file is required.') # check if xtek file exists if not (os.path.isfile(self.file_name)): raise Exception('File\n {}\n does not exist.'.format( self.file_name)) # check labels for key in self.roi.keys(): if key not in ['angle', 'horizontal', 'vertical']: raise Exception( "Wrong label. One of ollowing is expected: angle, horizontal, vertical" ) roi = self.roi.copy() if 'angle' not in roi.keys(): roi['angle'] = -1 if 'horizontal' not in roi.keys(): roi['horizontal'] = -1 if 'vertical' not in roi.keys(): roi['vertical'] = -1 # parse xtek file with open(self.file_name, 'r') as f: content = f.readlines() content = [x.strip() for x in content] #initialise parameters detector_offset_h = 0 detector_offset_v = 0 object_offset_x = 0 object_roll_deg = 0 for line in content: # filename of TIFF files if line.startswith("Name"): self._experiment_name = line.split('=')[1] # number of projections elif line.startswith("Projections"): num_projections = int(line.split('=')[1]) # white level - used for normalization elif line.startswith("WhiteLevel"): self._white_level = float(line.split('=')[1]) # number of pixels along Y axis elif line.startswith("DetectorPixelsY"): pixel_num_v_0 = int(line.split('=')[1]) # number of pixels along X axis elif line.startswith("DetectorPixelsX"): pixel_num_h_0 = int(line.split('=')[1]) # pixel size along X axis elif line.startswith("DetectorPixelSizeX"): pixel_size_h_0 = float(line.split('=')[1]) # pixel size along Y axis elif line.startswith("DetectorPixelSizeY"): pixel_size_v_0 = float(line.split('=')[1]) # source to center of rotation distance elif line.startswith("SrcToObject"): source_to_origin = float(line.split('=')[1]) # source to detector distance elif line.startswith("SrcToDetector"): source_to_det = float(line.split('=')[1]) # initial angular position of a rotation stage elif line.startswith("InitialAngle"): initial_angle = float(line.split('=')[1]) # angular increment (in degrees) elif line.startswith("AngularStep"): angular_step = float(line.split('=')[1]) # detector offset x in units elif line.startswith("DetectorOffsetX"): detector_offset_h = float(line.split('=')[1]) # detector offset y in units elif line.startswith("DetectorOffsetY"): detector_offset_v = float(line.split('=')[1]) # object offset x in units elif line.startswith("ObjectOffsetX"): object_offset_x = float(line.split('=')[1]) # object roll in degrees elif line.startswith("ObjectRoll"): object_roll_deg = float(line.split('=')[1]) self._roi_par = [[0, num_projections, 1], [0, pixel_num_v_0, 1], [0, pixel_num_h_0, 1]] for key in roi.keys(): if key == 'angle': idx = 0 elif key == 'vertical': idx = 1 elif key == 'horizontal': idx = 2 if roi[key] != -1: for i in range(2): if roi[key][i] != None: if roi[key][i] >= 0: self._roi_par[idx][i] = roi[key][i] else: self._roi_par[idx][ i] = self._roi_par[idx][1] + roi[key][i] if len(roi[key]) > 2: if roi[key][2] != None: if roi[key][2] > 0: self._roi_par[idx][2] = roi[key][2] else: raise Exception("Negative step is not allowed") if self.mode == 'bin': # calculate number of pixels and pixel size pixel_num_v = (self._roi_par[1][1] - self._roi_par[1][0]) // self._roi_par[1][2] pixel_num_h = (self._roi_par[2][1] - self._roi_par[2][0]) // self._roi_par[2][2] pixel_size_v = pixel_size_v_0 * self._roi_par[1][2] pixel_size_h = pixel_size_h_0 * self._roi_par[2][2] else: # slice pixel_num_v = numpy.int( numpy.ceil((self._roi_par[1][1] - self._roi_par[1][0]) / self._roi_par[1][2])) pixel_num_h = numpy.int( numpy.ceil((self._roi_par[2][1] - self._roi_par[2][0]) / self._roi_par[2][2])) pixel_size_v = pixel_size_v_0 pixel_size_h = pixel_size_h_0 det_start_0 = -(pixel_num_h_0 / 2) det_start = det_start_0 + self._roi_par[2][0] det_end = det_start + pixel_num_h * self._roi_par[2][2] det_pos_h = (det_start + det_end) * 0.5 * pixel_size_h_0 + detector_offset_h det_start_0 = -(pixel_num_v_0 / 2) det_start = det_start_0 + self._roi_par[1][0] det_end = det_start + pixel_num_v * self._roi_par[1][2] det_pos_v = (det_start + det_end) * 0.5 * pixel_size_v_0 + detector_offset_v #angles from xtek.ct ignore *.ang and _ctdata.txt as not correct angles = numpy.asarray( [angular_step * proj for proj in range(num_projections)], dtype=numpy.float32) if self.mode == 'bin': n_elem = (self._roi_par[0][1] - self._roi_par[0][0]) // self._roi_par[0][2] shape = (n_elem, self._roi_par[0][2]) angles = angles[self._roi_par[0][0]:( self._roi_par[0][0] + n_elem * self._roi_par[0][2])].reshape(shape).mean(1) else: angles = angles[slice(self._roi_par[0][0], self._roi_par[0][1], self._roi_par[0][2])] #convert NikonGeometry to CIL geometry angles = -angles - initial_angle + 180 object_roll_deg * numpy.pi / 180. rotate_axis_x = numpy.tan(object_roll_deg * numpy.pi / 180.) if self.fliplr: origin = 'top-left' else: origin = 'top-right' if pixel_num_v == 1 and (self._roi_par[1][0] + self._roi_par[1][1] ) // 2 == pixel_num_v_0 // 2: self._ag = AcquisitionGeometry.create_Cone2D( source_position=[0, -source_to_origin], rotation_axis_position=[-object_offset_x, 0], detector_position=[ -det_pos_h, source_to_det - source_to_origin ]) self._ag.set_angles(angles, angle_unit='degree') self._ag.set_panel(pixel_num_h, pixel_size=pixel_size_h, origin=origin) self._ag.set_labels(labels=['angle', 'horizontal']) else: self._ag = AcquisitionGeometry.create_Cone3D( source_position=[0, -source_to_origin, 0], rotation_axis_position=[-object_offset_x, 0, 0], rotation_axis_direction=[rotate_axis_x, 0, 1], detector_position=[ -det_pos_h, source_to_det - source_to_origin, det_pos_v ]) self._ag.set_angles(angles, angle_unit='degree') self._ag.set_panel((pixel_num_h, pixel_num_v), pixel_size=(pixel_size_h, pixel_size_v), origin=origin) self._ag.set_labels(labels=['angle', 'vertical', 'horizontal'])
#%% Read in data # path = "/media/scratch/Data/SophiaBeads/SophiaBeads_512_averaged/SophiaBeads_512_averaged.xtekct" path = "/mnt/data/CCPi/Dataset/SophiaBeads_64_averaged/CentreSlice" # Create a 2D fan beam Geometry source_position=(0, -80.6392412185669) detector_position=(0, 1007.006 - source_position[1]) angles = np.asarray([- 5.71428571428571 * i for i in range(63)], dtype=np.float32) * np.pi / 180. panel = 2000 panel_pixel_size = 0.2 ag_cs = AcquisitionGeometry.create_Cone2D(source_position, detector_position)\ .set_angles(angles, angle_unit='radian')\ .set_panel(panel, pixel_size=panel_pixel_size, origin='top-right') #%% reader = TIFFStackReader() reader.set_up(file_name=os.path.join(path, 'Sinograms', 'SophiaBeads_64_averaged_0001.tif')) data = reader.read_as_AcquisitionData(ag_cs) white_level = 60000.0 data_raw = data.subset(dimensions=['angle','horizontal']) data_raw = data / white_level # negative log ldata = data_raw.log() ldata *= -1