def test_TrackExceptions():
"""
"""
image = hybridtrack.test_input()
try:
Track(image)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
try:
Track(image, is_modeled=True, is_measured=True)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
try:
Track(image, is_modeled=False, is_measured=False)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
def test_TrackExceptions():
"""
"""
image = hybridtrack.test_input()
try:
Track(image)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
try:
Track(image, is_modeled=True, is_measured=True)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
try:
Track(image, is_modeled=False, is_measured=False)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
def test_Track():
"""
"""
def test_Track_read(track):
# test Track data format
from etrack.io import trackio
import os
filebase = ''.join(
chr(i) for i in np.random.randint(97, 122, size=(8,)))
filename = '.'.join([filebase, 'h5'])
with h5py.File(filename, 'a') as h5file:
trackio.write_object_to_hdf5(
track, h5file, 'track')
with h5py.File(filename, 'r') as h5file:
track2 = trackio.read_object_from_hdf5(
h5file['track'])
assert track2['is_modeled'] == track.is_modeled
assert track2['pixel_size_um'] == track.pixel_size_um
assert track2['noise_ev'] == track.noise_ev
assert track2['label'] == track.label
assert track2['energy_kev'] == track.energy_kev
assert np.all(track2['image'] == track.image)
assert track2['algorithms']['python HT v1.5']['alpha_deg'] == 120.5
assert track2['algorithms']['python HT v1.5']['beta_deg'] == 43.5
test_Track_from_pydict(track, track2)
test_Track_from_hdf5()
os.remove(filename)
def test_Track_from_pydict(track, track2):
"""
track is the original generated Track object
track2 is the pydict from file
Returns the track object constructed from pydict.
"""
track3 = Track.from_pydict(track2)
assert track3.is_modeled == track.is_modeled
assert track3.pixel_size_um == track.pixel_size_um
assert track3.noise_ev == track.noise_ev
assert track3.label == track.label
assert track3.energy_kev == track.energy_kev
assert np.all(track3.image == track.image)
assert track3.algorithms['python HT v1.5'].alpha_deg == 120.5
assert track3.algorithms['python HT v1.5'].beta_deg == 43.5
return track3
def test_Track_from_hdf5():
"""
as previously, but test the Track.from_hdf5() constructor.
"""
# TODO
print('test_Track_from_hdf5 not implemented yet!')
pass
def test_TrackExceptions():
"""
"""
image = hybridtrack.test_input()
try:
Track(image)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
try:
Track(image, is_modeled=True, is_measured=True)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
try:
Track(image, is_modeled=False, is_measured=False)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
# test_Track() main
image = hybridtrack.test_input()
track = Track(image, is_modeled=True, pixel_size_um=10.5, noise_ev=0.0,
label='MultiAngle', energy_kev=np.sum(image))
options, info = hybridtrack.reconstruct(track)
track.add_algorithm('python HT v1.5', 120.5, 43.5, info=info)
test_Track_read(track)
test_TrackExceptions()
def test_Track():
"""
"""
def test_Track_read(track):
# test Track data format
from etrack.io import trackio
import os
filebase = ''.join(
chr(i) for i in np.random.randint(97, 122, size=(8, )))
filename = '.'.join([filebase, 'h5'])
with h5py.File(filename, 'a') as h5file:
trackio.write_object_to_hdf5(track, h5file, 'track')
with h5py.File(filename, 'r') as h5file:
track2 = trackio.read_object_from_hdf5(h5file['track'])
assert track2['is_modeled'] == track.is_modeled
assert track2['pixel_size_um'] == track.pixel_size_um
assert track2['noise_ev'] == track.noise_ev
assert track2['label'] == track.label
assert track2['energy_kev'] == track.energy_kev
assert np.all(track2['image'] == track.image)
assert track2['algorithms']['python HT v1.5']['alpha_deg'] == 120.5
assert track2['algorithms']['python HT v1.5']['beta_deg'] == 43.5
test_Track_from_pydict(track, track2)
test_Track_from_hdf5()
os.remove(filename)
def test_Track_from_pydict(track, track2):
"""
track is the original generated Track object
track2 is the pydict from file
Returns the track object constructed from pydict.
"""
track3 = Track.from_pydict(track2)
assert track3.is_modeled == track.is_modeled
assert track3.pixel_size_um == track.pixel_size_um
assert track3.noise_ev == track.noise_ev
assert track3.label == track.label
assert track3.energy_kev == track.energy_kev
assert np.all(track3.image == track.image)
assert track3.algorithms['python HT v1.5'].alpha_deg == 120.5
assert track3.algorithms['python HT v1.5'].beta_deg == 43.5
return track3
def test_Track_from_hdf5():
"""
as previously, but test the Track.from_hdf5() constructor.
"""
# TODO
print('test_Track_from_hdf5 not implemented yet!')
pass
def test_TrackExceptions():
"""
"""
image = hybridtrack.test_input()
try:
Track(image)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
try:
Track(image, is_modeled=True, is_measured=True)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
try:
Track(image, is_modeled=False, is_measured=False)
raise RuntimeError('Failed to raise error on Track instantiation')
except InputError:
pass
# test_Track() main
image = hybridtrack.test_input()
track = Track(image,
is_modeled=True,
pixel_size_um=10.5,
noise_ev=0.0,
label='MultiAngle',
energy_kev=np.sum(image))
options, info = hybridtrack.reconstruct(track)
track.add_algorithm('python HT v1.5', 120.5, 43.5, info=info)
test_Track_read(track)
test_TrackExceptions()