def getEventDocs(cls, path, descriptor_uid):
for proj_index in range(cls.num_projections(path)):
yield embedded_local_event_doc(descriptor_uid,
'projection',
cls, (path, ),
resource_kwargs=dict(
arr='data', slc=proj_index))
for sino_index in range(cls.num_sinograms(path)):
yield embedded_local_event_doc(descriptor_uid,
'sinogram',
cls, (path, ),
resource_kwargs=dict(
arr='sino', slc=sino_index))
for flat_index in range(cls.num_flats(path)):
yield embedded_local_event_doc(descriptor_uid,
'flat',
cls, (path, ),
resource_kwargs=dict(
arr='data_white',
slc=flat_index))
for dark_index in range(cls.num_darks(path)):
yield embedded_local_event_doc(
descriptor_uid,
'dark',
cls, (path, ),
resource_kwargs=dict(arr='data_dark', slc=dark_index))
def getEventDocs(cls, path, descriptor_uid):
with h5py.File(path, 'r') as h5:
angles = np.deg2rad(h5['angle'])
for proj_index in range(cls.num_projections(path)):
yield embedded_local_event_doc(
descriptor_uid,
'projection',
cls, (path, ),
resource_kwargs=dict(arr='img_tomo', slc=proj_index),
metadata={'angle': angles[proj_index]})
for sino_index in range(cls.num_sinograms(path)):
yield embedded_local_event_doc(descriptor_uid,
'sinogram',
cls, (path, ),
resource_kwargs=dict(
arr='sino', slc=sino_index))
for flat_index in range(cls.num_flats(path)):
yield embedded_local_event_doc(descriptor_uid,
'flat',
cls, (path, ),
resource_kwargs=dict(
arr='img_bkg', slc=flat_index))
for dark_index in range(cls.num_darks(path)):
yield embedded_local_event_doc(descriptor_uid,
'dark',
cls, (path, ),
resource_kwargs=dict(
arr='img_dark', slc=dark_index))
def getVolumeEvents(cls, path, descriptor_uid):
with h5py.File(path, 'r') as f:
root_name = list(f.keys())[0] + '/'
n = f[root_name + 'data/image/image_cube'].shape[2]
wavenumbers = f[root_name + 'data/wavenumbers'][:]
ind_rc_map = f[root_name + 'data/image/ind_rc_map'][:, :]
ind2rc = {x[0]: tuple(x[1:]) for x in ind_rc_map}
rc2ind = {tuple(x[1:]): x[0] for x in ind_rc_map}
imgMask = f[root_name + 'data/image/image_mask'][:, :]
imgShape = (imgMask.shape[0], imgMask.shape[1])
for i in range(n):
yield embedded_local_event_doc(descriptor_uid, 'volume', cls, (path,), resource_kwargs={'E': i},
metadata = {'path': path, 'wavenumbers': wavenumbers, 'rc_index': rc2ind, 'index_rc': ind2rc, 'imgShape': imgShape})
def getSpectraEvents(cls, path, descriptor_uid):
# get a h5 object
# find the spectra data
# get spectra index
# iterate over rows
with h5py.File(path, 'r') as f:
root_name = list(f.keys())[0] + '/'
# get number of rows
n = f[root_name + 'data/spectra'].shape[0]
wavenumbers = f[root_name + 'data/wavenumbers'][:]
ind_rc_map = f[root_name + 'data/image/ind_rc_map'][:,:]
ind2rc = {x[0]: tuple(x[1:]) for x in ind_rc_map}
rc2ind = {tuple(x[1:]): x[0] for x in ind_rc_map}
mask = f[root_name + 'data/image/image_mask'][:, :]
imgShape = (mask.shape[0], mask.shape[1])
for i in range(n):
yield embedded_local_event_doc(descriptor_uid, 'spectra', cls, (path,), resource_kwargs={'i': i},
metadata={'wavenumbers':wavenumbers, 'rc_index': rc2ind, 'index_rc': ind2rc, 'imgShape':imgShape})
def getImageEvents(cls, path, descriptor_uid):
# get a h5 object
# find the imagecube
# get imagecube shape
# iterate over E dimension
with h5py.File(path, 'r') as f:
root_name = list(f.keys())[0] + '/'
# get number of frames
n = f[root_name + 'data/image/image_cube'].shape[2]
wavenumbers = f[root_name + 'data/wavenumbers'][:]
ind_rc_map = f[root_name + 'data/image/ind_rc_map'][:, :]
ind2rc = {x[0]: tuple(x[1:]) for x in ind_rc_map}
rc2ind = {tuple(x[1:]): x[0] for x in ind_rc_map}
imgMask = f[root_name + 'data/image/image_mask'][:, :]
imgShape = (imgMask.shape[0], imgMask.shape[1])
for i in range(n):
yield embedded_local_event_doc(descriptor_uid, 'image', cls, (path,), resource_kwargs={'E': i},
metadata={'wavenumbers': wavenumbers, 'rc_index': rc2ind, 'index_rc': ind2rc, 'imgShape': imgShape})