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
