def read_aps_32id(fname, exchange_rank=0, proj=None, sino=None, dtype=None):
"""
Read APS 32-ID standard data format.
Parameters
----------
fname : str
Path to hdf5 file.
exchange_rank : int, optional
exchange_rank is added to "exchange" to point tomopy to the data
to reconstruct. if rank is not set then the data are raw from the
detector and are located under exchange = "exchange/...", to process
data that are the result of some intemedite processing step then
exchange_rank = 1, 2, ... will direct tomopy to process
"exchange1/...",
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
dtype : numpy datatype, optional
Convert data to this datatype on read if specified.
Returns
-------
ndarray
3D tomographic data.
ndarray
3D flat field data.
ndarray
3D dark field data.
ndarray
1D theta in radian.
"""
if exchange_rank > 0:
exchange_base = 'exchange{:d}'.format(int(exchange_rank))
else:
exchange_base = "exchange"
tomo_grp = '/'.join([exchange_base, 'data'])
flat_grp = '/'.join([exchange_base, 'data_white'])
dark_grp = '/'.join([exchange_base, 'data_dark'])
theta_grp = '/'.join([exchange_base, 'theta'])
tomo = dxreader.read_hdf5(fname, tomo_grp, slc=(proj, sino), dtype=dtype)
flat = dxreader.read_hdf5(fname, flat_grp, slc=(None, sino), dtype=dtype)
dark = dxreader.read_hdf5(fname, dark_grp, slc=(None, sino), dtype=dtype)
theta = dxreader.read_hdf5(fname, theta_grp, slc=None)
if (theta is None):
theta_size = dxreader.read_dx_dims(fname, 'data')[0]
theta = np.linspace(0., np.pi, theta_size)
else:
theta = theta * np.pi / 180.
return tomo, flat, dark, theta
def _read_theta_size(params):
if (str(params.file_format) in {'dx', 'aps2bm', 'aps7bm', 'aps32id'}):
theta_size = dxreader.read_dx_dims(params.file_name, 'data')[0]
else:
log.error(" *** %s is not a supported file format" % params.file_format)
exit()
return theta_size
def _read_theta_size(params):
if (str(params.file_type) in {'dx', 'aps2bm', 'aps7bm', 'aps32id'}):
theta_size = dxreader.read_dx_dims(params.file_name, 'data')[0]
# elif:
# # add here other reader of theta size for other formats
# log.info(" *** %s is a valid xxx file format" % params.file_name)
else:
log.error(" *** %s is not a supported file format" %
params.file_format)
exit()
return theta_size
def dump_hdf5_item_structure(g, file_name, offset=' '):
"""Prints the input file/group/dataset (g) name and begin iterations on its content"""
if isinstance(g, h5py.File):
print(g.file, 'File:', g.name)
elif isinstance(g, h5py.Dataset):
#print ('Dataset: ', g.name) #, g.dtype
if g.name == '/exchange/theta':
print('theta array', file_name, g.name,
dxreader.read_dx_dims(file_name, "theta"))
elif g.name == '/exchange/data':
print('data array', file_name, g.name,
dxreader.read_dx_dims(file_name, "data"))
elif g.name == '/exchange/data_white':
print('data white', file_name, g.name,
dxreader.read_dx_dims(file_name, "data_white"))
elif g.name == '/exchange/data_dark':
print('data dark', file_name, g.name,
dxreader.read_dx_dims(file_name, "data_dark"))
else:
# print (file_name, g.name, '=', read_hdf5(file_name, g.name))
read_hdf5(file_name, g.name)
elif isinstance(g, h5py.Group):
print('Group:', g.name)
else:
print('WARNING: UNKNOWN ITEM IN HDF5 FILE', g.name)
sys.exit("EXECUTION IS TERMINATED")
if isinstance(g, h5py.File) or isinstance(g, h5py.Group):
# for key,val in dict(g).iteritems() :
for key, val in dict(g).items():
subg = val
#print (offset, key )#," ", subg.name #, val, subg.len(), type(subg),
dump_hdf5_item_structure(subg, file_name, offset + ' ')
def read_tomo(sino, params):
if params.hdf_file_type == 'standard':
# Read APS 32-BM raw data.
log.info(" *** loading a stardard data set: %s" % params.hdf_file)
proj, flat, dark, theta = dxchange.read_aps_32id(params.hdf_file,
sino=sino)
elif params.hdf_file_type == 'flip_and_stich':
log.info(" *** loading a 360 deg flipped data set: %s" %
params.hdf_file)
proj360, flat360, dark360, theta360 = dxchange.read_aps_32id(
params.hdf_file, sino=sino)
proj, flat, dark = flip_and_stitch(variableDict, proj360, flat360,
dark360)
theta = theta360[:len(theta360) // 2] # take first half
else: # params.hdf_file_type == 'mosaic':
log.error(" *** loading a mosaic data set is not supported yet")
exit()
if params.reverse:
log.info(" *** correcting for 180-0 data collection")
step_size = (theta[1] - theta[0])
theta_size = dxreader.read_dx_dims(params.hdf_file, 'data')[0]
theta = np.linspace(np.pi, (0 + step_size), theta_size)
if params.blocked_views:
log.info(" *** correcting for blocked view data collection")
miss_angles = [params.missing_angles_start, params.missing_angle_end]
# Manage the missing angles:
proj = np.concatenate(
(proj[0:miss_angles[0], :, :], proj[miss_angles[1] + 1:-1, :, :]),
axis=0)
theta = np.concatenate(
(theta[0:miss_angles[0]], theta[miss_angles[1] + 1:-1]))
# new missing projection handling
# if params.blocked_views:
# log.warning(" *** new missing angle handling")
# miss_angles = [params.missing_angles_start, params.missing_angle_end]
# data = patch_projection(data, miss_angles)
proj, flat, dark = binning(proj, flat, dark, params)
rotation_axis = params.rotation_axis / np.power(2, float(params.binning))
log.info(" *** rotation center: %f" % rotation_axis)
return proj, flat, dark, theta, rotation_axis
def read_aps_32id(fname, exchange_rank=0, proj=None, sino=None, dtype=None):
"""
Read APS 32-ID standard data format.
Parameters
----------
fname : str
Path to hdf5 file.
exchange_rank : int, optional
exchange_rank is added to "exchange" to point tomopy to the data
to reconstruct. if rank is not set then the data are raw from the
detector and are located under exchange = "exchange/...", to process
data that are the result of some intemedite processing step then
exchange_rank = 1, 2, ... will direct tomopy to process
"exchange1/...",
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
dtype : numpy datatype, optional
Convert data to this datatype on read if specified.
Returns
-------
ndarray
3D tomographic data.
ndarray
3D flat field data.
ndarray
3D dark field data.
ndarray
1D theta in radian.
"""
if exchange_rank > 0:
exchange_base = 'exchange{:d}'.format(int(exchange_rank))
else:
exchange_base = "exchange"
tomo_grp = '/'.join([exchange_base, 'data'])
flat_grp = '/'.join([exchange_base, 'data_white'])
dark_grp = '/'.join([exchange_base, 'data_dark'])
theta_grp = '/'.join([exchange_base, 'theta'])
tomo = dxreader.read_hdf5(fname, tomo_grp, slc=(proj, sino), dtype=dtype)
flat = dxreader.read_hdf5(fname, flat_grp, slc=(None, sino), dtype=dtype)
dark = dxreader.read_hdf5(fname, dark_grp, slc=(None, sino), dtype=dtype)
theta = dxreader.read_hdf5(fname, theta_grp, slc=None)
if (theta is None):
theta_size = dxreader.read_dx_dims(fname, 'data')[0]
logger.warn('Generating "%s" [0-180] deg angles for missing "exchange/theta" dataset' % (str(theta_size)))
theta = np.linspace(0. , np.pi, theta_size)
else:
theta = theta * np.pi / 180.
return tomo, flat, dark, theta
