def dump_theta(self, file_name):
"""Add theta to the hdf5 file by using unique ids stored in the same hdf5 file
- read unique projection ids from the hdf5 file
- take angles by ids from the PSO
- dump angles into hdf5 file
"""
log.info('dump theta into the hdf5 file %s',file_name)
hdf_file = util.open_hdf5(file_name,'r+')
unique_ids = hdf_file['/defaults/NDArrayUniqueId'][:]
theta = self.epics_pvs['ThetaArray'].get(count=int(self.epics_pvs['NumAngles'].get()))
dset = hdf_file.create_dataset('/exchange/theta', (len(unique_ids),), dtype='float32')
dset[:] = theta[unique_ids]
log.info('theta to save: %s .. %s', theta[unique_ids[0]], theta[unique_ids[-1]])
log.info('total saved theta: %s', len(unique_ids))
def broadcast_flat(self):
"""Broadcast flat fields
- read flat fields from the file
- take average and bin flat fields according to StreamBinning parameter
- broadcast flat field with the pv variable
"""
log.info('broadcast flat fields')
dirname = os.path.dirname(self.epics_pvs['FPFullFileName'].get(as_string=True))
h5file = util.open_hdf5(dirname+'/flat_fields.h5','r')
data = h5file['exchange/data_white'][:]
data = numpy.mean(data.astype('float32'),0)
for k in range(self.epics_pvs['StreamBinning'].get() ):
data = 0.5*(data[:, ::2]+data[:, 1::2])
data = 0.5*(data[::2, :]+data[1::2, :])
self.pva_stream_flat['value'] = data.flatten()
self.pva_stream_flat['sizex'] = data.shape[1]
self.pva_stream_flat['sizey'] = data.shape[0]
def dump_theta(self):
"""Add theta to the hdf5 file by using unique ids stored in the same hdf5 file
- read unique projection ids from the hdf5 file
- take angles by ids from the PSO
- dump angles into hdf5 file
"""
file_name = self.epics_pvs['FPFullFileName'].get(as_string=True)
log.info('dump theta into the hdf5 file %s', file_name)
with util.open_hdf5(file_name, 'r+') as hdf_file:
unique_ids = hdf_file['/defaults/NDArrayUniqueId'][:]
if '/exchange/theta' in hdf_file:
del hdf_file['/exchange/theta']
dset = hdf_file.create_dataset('/exchange/theta',
(len(unique_ids), ),
dtype='float32')
dset[:] = self.theta[unique_ids]
log.info('saved theta: %s .. %s', self.theta[unique_ids[0]],
self.theta[unique_ids[-1]])
log.info('total saved theta: %s', len(unique_ids))
