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