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3 changes: 3 additions & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
@@ -1,9 +1,12 @@
* XX.X.X
- New features:
- LSQR algorithm added to the CIL algorithm class (#1975)
- Added `get_centre_slice` method to `ImageData`, `ImageGeometry`, and `AcquisitionGeometry`. (#2235)
- Allows passing vertical='centre' to `ImageGeometry.get_slice` (#2235)
- Bug fixes:
- `CentreOfRotationCorrector.image_sharpness` data is now correctly smoothed to reduce aliasing artefacts and improve robustness. (#2202)
- `PaganinProcessor` now correctly applies scaling with magnification for cone-beam geometry (#2225)
- Sets `center_x`, `center_y`, `center_z` appropriately for `ImageGeometry` returned by `get_slice` (#2235)

* 25.0.0
- New features:
Expand Down
6 changes: 6 additions & 0 deletions Wrappers/Python/cil/framework/acquisition_data.py
Original file line number Diff line number Diff line change
Expand Up @@ -230,6 +230,12 @@ def get_slice(self, *args, **kwargs):
kwargs['force'] = args[4]

return self._get_slice(**kwargs)

def get_centre_slice(self):
'''
Returns a new AcquisitionData of the centre slice in the vertical direction.
'''
return self.get_slice(vertical='centre')

def reorder(self, order):
'''
Expand Down
9 changes: 8 additions & 1 deletion Wrappers/Python/cil/framework/image_data.py
Original file line number Diff line number Diff line change
Expand Up @@ -127,7 +127,7 @@ def __eq__(self, other):

def get_slice(self,channel=None, vertical=None, horizontal_x=None, horizontal_y=None, force=False):
'''
Returns a new ImageData of a single slice of in the requested direction.
Returns a new ImageData of a single slice in the requested direction.
'''
try:
geometry_new = self.geometry.get_slice(channel=channel, vertical=vertical, horizontal_x=horizontal_x, horizontal_y=horizontal_y)
Expand Down Expand Up @@ -156,6 +156,13 @@ def get_slice(self,channel=None, vertical=None, horizontal_x=None, horizontal_y=
return out
else:
return ImageData(out.array, deep_copy=False, geometry=geometry_new)

def get_centre_slice(self):
'''
Returns a new ImageData of the centre slice in the vertical direction.
'''
return self.get_slice(vertical='centre')



def apply_circular_mask(self, radius=0.99, in_place=True):
Expand Down
48 changes: 43 additions & 5 deletions Wrappers/Python/cil/framework/image_geometry.py
Original file line number Diff line number Diff line change
Expand Up @@ -174,27 +174,65 @@ def __init__(self,

def get_slice(self,channel=None, vertical=None, horizontal_x=None, horizontal_y=None):
'''
Returns a new ImageGeometry of a single slice of in the requested direction.
Returns a new ImageGeometry of a single slice in the requested direction.

Parameters
----------
channel : int or 'centre', optional
The channel index to slice. Default is None (no slicing).
vertical : int or 'centre', optional
The vertical index to slice. Default is None (no slicing).
horizontal_x : int, optional
The horizontal x index to slice. Default is None (no slicing).
horizontal_y : int, optional
The horizontal y index to slice. Default is None (no slicing).
Returns
-------
geometry_new : ImageGeometry
A new ImageGeometry object representing the sliced geometry.

Note
----
Slicing on vertical with 'centre' will return the central slice in that dimension.
Slicing on channels returns a geometry with a single channel, however the channel label is not
typically stored in the geometry.
'''

geometry_new = self.copy()
if channel is not None:
geometry_new.channels = 1

try:
geometry_new.channel_labels = [self.channel_labels[channel]]
except:
geometry_new.channel_labels = None

if vertical is not None:
geometry_new.voxel_num_z = 0
geometry_new.voxel_num_z = 1
if vertical != 'centre':
if vertical == 0:
warnings.warn("Slicing vertical at index 0 results in a geometry \
offset along the vertical axis. If you do not require an offset ImageGeometry, set vertical='centre",
UserWarning)
voxel_offset = (self.voxel_num_z)/2 - (vertical+0.5)
geometry_new.center_z -= voxel_offset * geometry_new.voxel_size_z

if horizontal_y is not None:
geometry_new.voxel_num_y = 0
geometry_new.voxel_num_y = 1
voxel_offset = (self.voxel_num_y)/2 - (horizontal_y +0.5)
geometry_new.center_y -= voxel_offset * geometry_new.voxel_size_y

if horizontal_x is not None:
geometry_new.voxel_num_x = 0
geometry_new.voxel_num_x = 1
voxel_offset = (self.voxel_num_x)/2 - (horizontal_x+0.5)
geometry_new.center_x -= voxel_offset * geometry_new.voxel_size_x

return geometry_new

def get_centre_slice(self):
'''
Returns a new ImageGeometry of the centre slice in the vertical direction.
'''
return self.get_slice(vertical='centre')

def get_order_by_label(self, dimension_labels, default_dimension_labels):
order = []
Expand Down
13 changes: 10 additions & 3 deletions Wrappers/Python/test/test_DataContainer.py
Original file line number Diff line number Diff line change
Expand Up @@ -860,13 +860,20 @@ def test_ImageDataSubset(self):
ss1 = vol.get_slice(horizontal_x = 0)
self.assertListEqual(['channel', 'horizontal_y'], list(ss1.geometry.dimension_labels))

ss2 = vol.get_slice(channel=0)
self.assertListEqual([ImageDimension["HORIZONTAL_Y"], ImageDimension["HORIZONTAL_X"]], list(ss2.geometry.dimension_labels))

vg = ImageGeometry(3,4,5,channels=2)
self.assertListEqual([ImageDimension["CHANNEL"], ImageDimension["VERTICAL"],
ImageDimension["HORIZONTAL_Y"], ImageDimension["HORIZONTAL_X"]],
list(vg.dimension_labels))
ss2 = vg.allocate()
ss3 = vol.get_slice(channel=0)
self.assertListEqual([ImageDimension["HORIZONTAL_Y"], ImageDimension["HORIZONTAL_X"]], list(ss3.geometry.dimension_labels))
vol2 = vg.allocate()

ss3 = vol2.get_slice(vertical=0)
self.assertListEqual([ImageDimension["CHANNEL"], ImageDimension["HORIZONTAL_Y"], ImageDimension["HORIZONTAL_X"]],
list(ss3.geometry.dimension_labels))



def test_DataContainerSubset(self):
dc = DataContainer(np.ones((2,3,4,5)))
Expand Down
109 changes: 109 additions & 0 deletions Wrappers/Python/test/test_ImageGeometry.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,109 @@
# Copyright 2025 United Kingdom Research and Innovation
# Copyright 2025 The University of Manchester
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# Authors:
# CIL Developers, listed at: https://github.com/TomographicImaging/CIL/blob/master/NOTICE.txt

import unittest
from utils import initialise_tests
from cil.framework import ImageGeometry
from cil.framework.labels import ImageDimension

initialise_tests()


class TestImageGeometry(unittest.TestCase):
def setUp(self):
self.ig = ImageGeometry(2,3,4,channels=5)

# get_slice tests ---------------------------------------------------------------------------------------------------------------

def test_get_slice_vertical(self):
non_default_dimension_labels = [ImageDimension["HORIZONTAL_X"], ImageDimension["CHANNEL"], ImageDimension["HORIZONTAL_Y"],
ImageDimension["VERTICAL"]]
ig = self.ig.copy()
ig.set_labels(non_default_dimension_labels)
ig.voxel_size_z = 5.5
sub = ig.get_slice(vertical = 1)
self.assertTrue( sub.shape == (2,5,3))
self.assertEqual(sub.voxel_size_z,5.5)
self.assertEqual(sub.center_x,0)
self.assertEqual(sub.center_y,0)
self.assertEqual(sub.center_z,-0.5*sub.voxel_size_z)

def test_get_slice_vertical_centre(self):
non_default_dimension_labels = [ImageDimension["HORIZONTAL_X"], ImageDimension["CHANNEL"], ImageDimension["HORIZONTAL_Y"],
ImageDimension["VERTICAL"]]
self.ig.set_labels(non_default_dimension_labels)
sub = self.ig.get_slice(vertical = 'centre')
self.assertTrue( sub.shape == (2,5,3))
self.assertEqual(sub.center_x,0)
self.assertEqual(sub.center_y,0)
self.assertEqual(sub.center_z,0)


def test_get_slice_horizontal_x(self):
non_default_dimension_labels = [ImageDimension["HORIZONTAL_X"], ImageDimension["CHANNEL"], ImageDimension["HORIZONTAL_Y"],
ImageDimension["VERTICAL"]]
self.ig.set_labels(non_default_dimension_labels)
sub = self.ig.get_slice(horizontal_x = 1)
self.assertTrue(sub.shape == (5,3,4))
self.assertEqual(sub.center_x,0.5)
self.assertEqual(sub.center_y,0)
self.assertEqual(sub.center_z,0)


def test_get_slice_channel(self):
non_default_dimension_labels = [ImageDimension["HORIZONTAL_X"], ImageDimension["CHANNEL"], ImageDimension["HORIZONTAL_Y"],
ImageDimension["VERTICAL"]]
self.ig.set_labels(non_default_dimension_labels)
sub = self.ig.get_slice(channel = 1)
self.assertTrue(sub.shape == (2,3,4))
self.assertTrue(sub.channels == 1)

def test_get_slice_channel_centre(self):
non_default_dimension_labels = [ImageDimension["HORIZONTAL_X"], ImageDimension["CHANNEL"], ImageDimension["HORIZONTAL_Y"],
ImageDimension["VERTICAL"]]
self.ig.set_labels(non_default_dimension_labels)
sub = self.ig.get_slice(channel = 'centre')
self.assertTrue(sub.shape == (2,3,4))
self.assertTrue(sub.channels == 1)

def test_get_slice_horizontal_y(self):
non_default_dimension_labels = [ImageDimension["HORIZONTAL_X"], ImageDimension["HORIZONTAL_Y"]]
self.ig.set_labels(non_default_dimension_labels)
sub = self.ig.get_slice(horizontal_y = 0)
self.assertTrue( sub.shape == (2,))
self.assertEqual(sub.center_x,0)
self.assertEqual(sub.center_y,-1)
self.assertEqual(sub.center_z,0)

def test_get_slice_horizontal_x_and_horizontal_y(self):
sub = self.ig.get_slice(horizontal_x=0,horizontal_y=0)
self.assertTrue( sub.shape == (5,4))

# test get_centre_slice ---------------------------------------------------------------------------------------------------------------

def test_get_centre_slice(self):
sub = self.ig.get_centre_slice()
sub2 = self.ig.get_slice(vertical='centre')
self.assertTrue( sub == sub2)

# -------------------------------------------------------------------------------------------------------------------------------

def test_shape_change_with_new_labels(self):
new_dimension_labels = [ImageDimension["HORIZONTAL_Y"], ImageDimension["CHANNEL"], ImageDimension["VERTICAL"], ImageDimension["HORIZONTAL_X"]]
self.ig.set_labels(new_dimension_labels)
self.assertTrue( self.ig.shape == (3,5,4,2))
4 changes: 0 additions & 4 deletions Wrappers/Python/test/test_reconstructors.py
Original file line number Diff line number Diff line change
Expand Up @@ -80,7 +80,6 @@ def setUp(self):
.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', seed=3)
self.ig3D = self.ag3D.get_ImageGeometry()
Expand Down Expand Up @@ -164,7 +163,6 @@ def setUp(self):
.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', seed=4)
self.ig3D = self.ag3D.get_ImageGeometry()
Expand Down Expand Up @@ -351,7 +349,6 @@ def setUp(self):
.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', seed=5)
self.ig3D = self.ag3D.get_ImageGeometry()
Expand Down Expand Up @@ -454,7 +451,6 @@ def setUp(self):
.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', seed=3)
self.ig3D = self.ag3D.get_ImageGeometry()
Expand Down
15 changes: 13 additions & 2 deletions Wrappers/Python/test/test_subset.py
Original file line number Diff line number Diff line change
Expand Up @@ -161,7 +161,7 @@ def test_DataContainer(self):
self.assertEqual(data_new.shape,(5,))
numpy.testing.assert_array_equal(data_new.array, arr[1,1,3,:])

def test_ImageData(self):
def test_ImageData(self):
ig = ImageGeometry(voxel_num_x=5, voxel_num_y=4, voxel_num_z=3, channels=2, dimension_labels=['channel','vertical','horizontal_y','horizontal_x'])
data = ig.allocate(None)
data_new = data.get_slice(vertical=1)
Expand Down Expand Up @@ -299,6 +299,12 @@ def test_ImageDataSubset5a(self):
sub = data.get_slice(horizontal_y = 1)
self.assertTrue( sub.shape == (2,))

def test_ImageDataCentreSubset(self):
data = self.ig.allocate()
sub = data.get_centre_slice()
sub2 = data.get_slice(vertical='centre')
self.assertTrue( sub == sub2)

def test_ImageDataSubset1b(self):
non_default_dimension_labels = [ImageDimension["HORIZONTAL_X"], ImageDimension["CHANNEL"], ImageDimension["HORIZONTAL_Y"],
ImageDimension["VERTICAL"]]
Expand All @@ -313,7 +319,6 @@ def test_ImageDataSubset1c(self):
sub = data.get_slice(channel=0,horizontal_x=0,horizontal_y=0)
self.assertTrue( sub.shape == (4,))


def test_AcquisitionDataAllocate1a(self):
data = self.ag.allocate()
default_dimension_labels = [AcquisitionDimension["CHANNEL"] ,
Expand Down Expand Up @@ -429,3 +434,9 @@ def test_AcquisitionDataSubset1l(self):
sub = data.get_slice(projection = 0)
sub = sub.get_slice(channel = 0)
self.assertTrue(sub.shape == (2, 20))

def test_AcquisitionDataCentreSubset(self):
data = self.ag.allocate()
sub = data.get_centre_slice()
sub2 = data.get_slice(vertical='centre')
self.assertTrue( sub == sub2)
7 changes: 7 additions & 0 deletions Wrappers/Python/test/utils_projectors.py
Original file line number Diff line number Diff line change
Expand Up @@ -656,10 +656,17 @@ def test_FBP_roi(self):
np.testing.assert_allclose(reco.as_array(), self.gold_roi, atol=self.tolerance_fbp_roi)

if AcquisitionType.DIM3 & self.ag.dimension:
# Manually generated single slice Image Geometry
FBP = self.FBP(self.ig_single_slice, self.ag, **self.FBP_args)
reco = FBP(self.acq_data)
np.testing.assert_allclose(reco.as_array(), self.gold_roi_single_slice, atol=self.tolerance_fbp_roi)

# CIL generated single slice Image Geometry
central_slice_ig = self.ig.get_slice(vertical='centre')
FBP = self.FBP(central_slice_ig, self.ag, **self.FBP_args)
reco = FBP(self.acq_data)
np.testing.assert_allclose(reco.as_array(), self.img_data.get_slice(vertical='centre').as_array(),atol=self.tolerance_fbp)


def test_input_arguments(self):
# default image_geometry, named parameter acquisition_geometry
Expand Down
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