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_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 from_hdf5(cls, h5group, h5_to_pydict=None, pydict_to_pyobj=None):
"""
Initialize a Track instance from an HDF5 group.
"""
if h5_to_pydict is None:
h5_to_pydict = {}
if pydict_to_pyobj is None:
pydict_to_pyobj = {}
read_dict = trackio.read_object_from_hdf5(
h5group, h5_to_pydict=h5_to_pydict)
constructed_object = cls.from_pydict(
read_dict, pydict_to_pyobj=pydict_to_pyobj)
return constructed_object
def from_hdf5(cls, h5group, h5_to_pydict=None, pydict_to_pyobj=None):
"""
Initialize a MatlabAlgorithmInfo object from an HDF5 group.
"""
if h5_to_pydict is None:
h5_to_pydict = {}
if pydict_to_pyobj is None:
pydict_to_pyobj = {}
read_dict = trackio.read_object_from_hdf5(h5group,
h5_to_pydict=h5_to_pydict)
constructed_object = cls.from_pydict(read_dict,
pydict_to_pyobj=pydict_to_pyobj)
return constructed_object
def from_hdf5(cls, h5group, h5_to_pydict=None, pydict_to_pyobj=None,
reconstruct=False):
"""
Initialize a Classifier object from an HDF5 group.
"""
if h5_to_pydict is None:
h5_to_pydict = {}
if pydict_to_pyobj is None:
pydict_to_pyobj = {}
read_dict = trackio.read_object_from_hdf5(
h5group, h5_to_pydict=h5_to_pydict)
constructed_object = cls.from_pydict(
read_dict, pydict_to_pyobj=pydict_to_pyobj,
reconstruct=reconstruct)
return constructed_object
def from_hdf5(cls, h5group, h5_to_pydict=None, pydict_to_pyobj=None,
reconstruct=False):
"""
Initialize a Classifier object from an HDF5 group.
"""
if h5_to_pydict is None:
h5_to_pydict = {}
if pydict_to_pyobj is None:
pydict_to_pyobj = {}
read_dict = trackio.read_object_from_hdf5(
h5group, h5_to_pydict=h5_to_pydict)
constructed_object = cls.from_pydict(
read_dict, pydict_to_pyobj=pydict_to_pyobj,
reconstruct=reconstruct)
return constructed_object
