def test_AcquisitionDataPadder(self):
reader = NexusReader(self.filename)
ad = reader.get_acquisition_data_whole()
print(ad.geometry)
cf = CenterOfRotationFinder()
cf.set_input(ad)
print("Center of rotation", cf.get_output())
self.assertAlmostEqual(86.25, cf.get_output())
adp = AcquisitionDataPadder(
acquisition_geometry=cf.get_input().geometry,
center_of_rotation=cf.get_output(),
pad_value=0)
adp.set_input(ad)
padded_data = adp.get_output()
print("Padded data shape", padded_data.shape)
print(" ", padded_data.dimension_labels)
idx = None
for k, v in padded_data.dimension_labels.items():
if v == AcquisitionGeometry.HORIZONTAL:
idx = k
padded_axis = padded_data.shape[idx]
self.assertEqual(padded_axis, math.ceil(cf.get_output() * 2))
numpy.save("pippo.npy", padded_data.as_array())
def testLoadProjectionCompareFull(self):
nr = NexusReader(self.filename)
projections_full = nr.load_projection()
projections_part = nr.load_projection(
(slice(None, None), slice(None, None), slice(None, None)))
numpy.testing.assert_array_equal(projections_part,
projections_full[:, :, :])
def test_get_acquisition_data_subset(self):
nr = NexusReader(self.filename)
key = nr.get_image_keys()
sl = nr.get_acquisition_data_subset(0, 10)
data = nr.get_acquisition_data().subset(['vertical', 'horizontal'])
self.assertTrue(sl.shape, (10, data.shape[1]))
def testLoadProjectionCompareRandom(self):
nr = NexusReader(self.filename)
projections_full = nr.load_projection()
projections_part = nr.load_projection(
(slice(1, 8), slice(5, 10), slice(8, 20)))
numpy.testing.assert_array_equal(projections_part,
projections_full[1:8, 5:10, 8:20])
def testLoadProjectionCompareMulti(self):
nr = NexusReader(self.filename)
projections_full = nr.load_projection()
projections_part = nr.load_projection(
(slice(0, 3), slice(0, 135), slice(0, 160)))
numpy.testing.assert_array_equal(projections_part,
projections_full[0:3, :, :])
def test_CenterOfRotation(self):
reader = NexusReader(self.filename)
data = reader.get_acquisition_data_whole()
ad = data.clone()
print(ad)
cf = CenterOfRotationFinder()
cf.set_input(ad)
print("Center of rotation", cf.get_output())
self.assertAlmostEqual(86.25, cf.get_output())
#def test_CenterOfRotation_transpose(self):
#reader = NexusReader(self.filename)
#data = reader.get_acquisition_data_whole()
ad = data.clone()
ad = ad.subset(['vertical', 'angle', 'horizontal'])
print(ad)
cf = CenterOfRotationFinder()
cf.set_input(ad)
print("Center of rotation", cf.get_output())
self.assertAlmostEqual(86.25, cf.get_output())
#def test_CenterOfRotation_singleslice(self):
#reader = NexusReader(self.filename)
#data = reader.get_acquisition_data_whole()
ad = data.clone()
ad = ad.subset(vertical=67)
print(ad)
cf = CenterOfRotationFinder()
cf.set_input(ad)
print("Center of rotation", cf.get_output())
self.assertAlmostEqual(86.25, cf.get_output())
#def test_CenterOfRotation_slice(self):
#reader = NexusReader(self.filename)
#data = reader.get_acquisition_data_whole()
ad = data.clone()
print(ad)
cf = CenterOfRotationFinder()
cf.set_input(ad)
cf.set_slice(80)
print("Center of rotation", cf.get_output())
self.assertAlmostEqual(86.25, cf.get_output())
cf.set_slice()
print("Center of rotation", cf.get_output())
self.assertAlmostEqual(86.25, cf.get_output())
cf.set_slice('centre')
print("Center of rotation", cf.get_output())
self.assertAlmostEqual(86.25, cf.get_output())
def testProjectionAngles(self):
nr = NexusReader(self.filename)
angles = nr.getProjectionAngles()
self.assertEqual(angles.shape, (91,), "Loaded projection number of angles are not correct")
def testLoadDarkCompareFull(self):
nr = NexusReader(self.filename)
darks_full = nr.loadDark()
darks_part = nr.loadDark((slice(None,None), slice(None,None), slice(None,None)))
numpy.testing.assert_array_equal(darks_part, darks_full[:,:,:])
def testLoadFlatCompareFull(self):
nr = NexusReader(self.filename)
flats_full = nr.loadFlat()
flats_part = nr.loadFlat((slice(None,None), slice(None,None), slice(None,None)))
numpy.testing.assert_array_equal(flats_part, flats_full[:,:,:])
def testLoadProjectionWithDimensions(self):
nr = NexusReader(self.filename)
projections = nr.loadProjection((slice(0,1), slice(0,135), slice(0,160)))
self.assertEqual(projections.shape, (1,135,160), "Loaded projection data dimensions are not correct")
def testGetProjectionDimensions(self):
nr = NexusReader(self.filename)
self.assertEqual(nr.getProjectionDimensions(), (91,135,160), "Projection dimensions are not correct")
def testGetDimensions(self):
nr = NexusReader(self.filename)
self.assertEqual(nr.getSinogramDimensions(), (135, 91, 160), "Sinogram dimensions are not correct")
def testAll(self):
if has_wget:
# def testGetDimensions(self):
nr = NexusReader(self.filename)
self.assertEqual(nr.get_sinogram_dimensions(), (135, 91, 160),
"Sinogram dimensions are not correct")
# def testGetProjectionDimensions(self):
nr = NexusReader(self.filename)
self.assertEqual(nr.get_projection_dimensions(), (91, 135, 160),
"Projection dimensions are not correct")
# def testLoadProjectionWithoutDimensions(self):
nr = NexusReader(self.filename)
projections = nr.load_projection()
self.assertEqual(
projections.shape, (91, 135, 160),
"Loaded projection data dimensions are not correct")
# def testLoadProjectionWithDimensions(self):
nr = NexusReader(self.filename)
projections = nr.load_projection(
(slice(0, 1), slice(0, 135), slice(0, 160)))
self.assertEqual(
projections.shape, (1, 135, 160),
"Loaded projection data dimensions are not correct")
# def testLoadProjectionCompareSingle(self):
nr = NexusReader(self.filename)
projections_full = nr.load_projection()
projections_part = nr.load_projection(
(slice(0, 1), slice(0, 135), slice(0, 160)))
numpy.testing.assert_array_equal(projections_part,
projections_full[0:1, :, :])
# def testLoadProjectionCompareMulti(self):
nr = NexusReader(self.filename)
projections_full = nr.load_projection()
projections_part = nr.load_projection(
(slice(0, 3), slice(0, 135), slice(0, 160)))
numpy.testing.assert_array_equal(projections_part,
projections_full[0:3, :, :])
# def testLoadProjectionCompareRandom(self):
nr = NexusReader(self.filename)
projections_full = nr.load_projection()
projections_part = nr.load_projection(
(slice(1, 8), slice(5, 10), slice(8, 20)))
numpy.testing.assert_array_equal(projections_part,
projections_full[1:8, 5:10, 8:20])
# def testLoadProjectionCompareFull(self):
nr = NexusReader(self.filename)
projections_full = nr.load_projection()
projections_part = nr.load_projection(
(slice(None, None), slice(None, None), slice(None, None)))
numpy.testing.assert_array_equal(projections_part,
projections_full[:, :, :])
# def testLoadFlatCompareFull(self):
nr = NexusReader(self.filename)
flats_full = nr.load_flat()
flats_part = nr.load_flat(
(slice(None, None), slice(None, None), slice(None, None)))
numpy.testing.assert_array_equal(flats_part, flats_full[:, :, :])
# def testLoadDarkCompareFull(self):
nr = NexusReader(self.filename)
darks_full = nr.load_dark()
darks_part = nr.load_dark(
(slice(None, None), slice(None, None), slice(None, None)))
numpy.testing.assert_array_equal(darks_part, darks_full[:, :, :])
# def testProjectionAngles(self):
nr = NexusReader(self.filename)
angles = nr.get_projection_angles()
self.assertEqual(
angles.shape, (91, ),
"Loaded projection number of angles are not correct")
# def test_get_acquisition_data_subset(self):
nr = NexusReader(self.filename)
key = nr.get_image_keys()
sl = nr.get_acquisition_data_subset(0, 10)
data = nr.get_acquisition_data()
print(data.geometry)
print(data.geometry.dimension_labels)
print(data.dimension_labels)
rdata = data.subset(channel=0)
#
self.assertTrue(sl.shape, (10, rdata.shape[1]))
try:
data.subset(['vertical', 'horizontal'])
self.assertTrue(False)
except ValueError as ve:
print("Exception catched", ve)
self.assertTrue(True)
else:
# skips all tests if module wget is not present
self.assertFalse(has_wget)
import os
# Define utility function to average over flat and dark images.
def avg_img(image):
shape = list(numpy.shape(image))
l = shape.pop(0)
avg = numpy.zeros(shape)
for i in range(l):
avg += image[i] / l
return avg
# Set up a reader object pointing to the Nexus data set. Revise path as needed.
reader = NexusReader(
os.path.join("..", "..", "..", "..", "CCPi-ReconstructionFramework",
"data", "24737_fd.nxs"))
# Read and print the dimensions of the raw projections
dims = reader.get_projection_dimensions()
print(dims)
# Load and average all flat and dark images in preparation for normalising data.
flat = avg_img(reader.load_flat())
dark = avg_img(reader.load_dark())
# Set up normaliser object for normalising data by flat and dark images.
norm = Normalizer(flat_field=flat, dark_field=dark)
# Load the raw projections and pass as input to the normaliser.
norm.set_input(reader.get_acquisition_data())
def testLoadProjectionWithoutDimensions(self):
nr = NexusReader(self.filename)
projections = nr.load_projection()
self.assertEqual(projections.shape, (91, 135, 160),
"Loaded projection data dimensions are not correct")
i = 0
while i < N:
stats , i = DataStatMoments.add_sample(data, i, self.axis, stats, offset=self.offset)
self.offset += N
labels = ['StatisticalMoments']
labels += [data.dimension_labels[i] \
for i in range(len(data.dimension_labels)) if i != ax]
y = DataContainer( stats[:4] , False,
dimension_labels=labels)
return y
directory = r'E:\Documents\Dataset\CCPi\Nexus_test'
data_path="entry1/instrument/pco1_hw_hdf_nochunking/data"
reader = NexusReader(os.path.join( os.path.abspath(directory) , '74331.nxs'))
print ("read flat")
read_flat = NexusReader(os.path.join( os.path.abspath(directory) , '74240.nxs'))
read_flat.data_path = data_path
flatsslice = read_flat.get_acquisition_data_whole()
avg = DataStatMoments('angle')
avg.set_input(flatsslice)
flats = avg.get_output()
ave = averager()
ave.stats(flatsslice.array[:,0,0])
print ("avg" , ave.avg, flats.array[0][0][0])
print ("var" , ave.var, flats.array[1][0][0])
