def read_petraIII_p05(fname,
ind_tomo,
ind_flat,
ind_dark,
proj=None,
sino=None):
"""
Read Petra-III P05 standard data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
ind_flat : list of int
Indices of the flat field files to read.
ind_dark : list of int
Indices of the dark field files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'scan_0002', 'ccd', 'pco01',
'ccd_0000.tif')
flat_name = os.path.join(fname, 'scan_0001', 'ccd', 'pco01',
'ccd_0000.tif')
dark_name = os.path.join(fname, 'scan_0000', 'ccd', 'pco01',
'ccd_0000.tif')
tomo = tio.read_tiff_stack(tomo_name,
ind=ind_tomo,
digit=4,
slc=(sino, proj))
flat = tio.read_tiff_stack(flat_name,
ind=ind_flat,
digit=4,
slc=(sino, None))
dark = tio.read_tiff_stack(dark_name,
ind=ind_dark,
digit=4,
slc=(sino, None))
return tomo, flat, dark
def read_diamond_l12(fname, ind_tomo):
"""
Read Diamond Light Source L12 (JEEP) standard data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'im_001000.tif')
flat_name = os.path.join(fname, 'flat_000000.tif')
ind_flat = range(0, 1)
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=6)
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=6)
return tomo, flat
def read_diamond_l12(fname, ind_tomo):
"""
Read Diamond Light Source L12 (JEEP) standard data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'im_001000.tif')
flat_name = os.path.join(fname, 'flat_000000.tif')
ind_flat = range(0, 1)
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=6)
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=6)
return tomo, flat
def read_elettra_syrmep(fname, ind_tomo):
"""
Read Elettra SYRMEP standard data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'tomo_0001.tif')
flat_name = os.path.join(fname, 'flat_0001.tif')
dark_name = os.path.join(fname, 'dark_0001.tif')
ind_flat = range(1, 11)
ind_dark = range(1, 11)
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=4)
dark = tio.read_tiff_stack(dark_name, ind=ind_dark, digit=4)
return tomo, flat, dark
def read_elettra_syrmep(fname,
ind_tomo,
ind_flat,
ind_dark,
proj=None,
sino=None):
"""
Read Elettra SYRMEP standard data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
ind_flat : list of int
Indices of the flat field files to read.
ind_dark : list of int
Indices of the dark field files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'tomo_0001.tif')
flat_name = os.path.join(fname, 'flat_1.tif')
dark_name = os.path.join(fname, 'dark_1.tif')
tomo = tio.read_tiff_stack(tomo_name,
ind=ind_tomo,
digit=4,
slc=(sino, proj))
flat = tio.read_tiff_stack(flat_name,
ind=ind_flat,
digit=1,
slc=(sino, None))
dark = tio.read_tiff_stack(dark_name,
ind=ind_dark,
digit=1,
slc=(sino, None))
return tomo, flat, dark
def read_anka_topotomo(fname,
ind_tomo,
ind_flat,
ind_dark,
proj=None,
sino=None):
"""
Read ANKA TOMO-TOMO standard data format.
Parameters
----------
fname : str
Path to data folder name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
ind_flat : list of int, optional
Indices of the flat field files to read.
ind_dark : list of int, optional
Indices of the dark field files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'radios', 'image_00000.tif')
flat_name = os.path.join(fname, 'flats', 'image_00000.tif')
dark_name = os.path.join(fname, 'darks', 'image_00000.tif')
tomo = tio.read_tiff_stack(tomo_name,
ind=ind_tomo,
digit=5,
slc=(sino, proj))
flat = tio.read_tiff_stack(flat_name,
ind=ind_flat,
digit=5,
slc=(sino, None))
dark = tio.read_tiff_stack(dark_name,
ind=ind_dark,
digit=5,
slc=(sino, None))
return tomo, flat, dark
def read_petraIII_p05(
fname, ind_tomo, ind_flat, ind_dark, proj=None, sino=None):
"""
Read Petra-III P05 standard data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
ind_flat : list of int
Indices of the flat field files to read.
ind_dark : list of int
Indices of the dark field files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(
fname, 'scan_0002', 'ccd', 'pco01', 'ccd_0000.tif')
flat_name = os.path.join(
fname, 'scan_0001', 'ccd', 'pco01', 'ccd_0000.tif')
dark_name = os.path.join(
fname, 'scan_0000', 'ccd', 'pco01', 'ccd_0000.tif')
tomo = tio.read_tiff_stack(
tomo_name, ind=ind_tomo, digit=4, slc=(sino, proj))
flat = tio.read_tiff_stack(
flat_name, ind=ind_flat, digit=4, slc=(sino, None))
dark = tio.read_tiff_stack(
dark_name, ind=ind_dark, digit=4, slc=(sino, None))
return tomo, flat, dark
def read_sls_tomcat(fname, ind_tomo=None):
"""
Read SLS TOMCAT standard data format.
Parameters
----------
fname : str
Path to file name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
# File definitions.
fname = os.path.abspath(fname)
_fname = fname + '0001.tif'
log_file = fname + '.log'
# Read metadata from ALS log file.
contents = open(log_file, 'r')
for line in contents:
ls = line.split()
if len(ls) > 1:
if ls[0] == 'Number' and ls[2] == 'projections':
nproj = int(ls[4])
elif ls[0] == 'Number' and ls[2] == 'flats':
nflat = int(ls[4])
elif ls[0] == 'Number' and ls[2] == 'darks':
ndark = int(ls[4])
contents.close()
if ind_tomo is None:
ind_tomo = range(ndark + nflat + 1, ndark + nflat + nproj)
ind_flat = range(ndark + 1, ndark + nflat)
ind_dark = range(1, ndark)
tomo = tio.read_tiff_stack(_fname, ind=ind_tomo, digit=4)
flat = tio.read_tiff_stack(_fname, ind=ind_flat, digit=4)
dark = tio.read_tiff_stack(_fname, ind=ind_dark, digit=4)
return tomo, flat, dark
def read_als_832(fname, ind_tomo=None):
"""
Read ALS 8.3.2 standard data format.
Parameters
----------
fname : str
Path to file name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
# File definitions.
fname = os.path.abspath(fname)
tomo_name = fname + '_0000_0000.tif'
flat_name = fname + 'bak_0000.tif'
dark_name = fname + 'drk_0000.tif'
log_file = fname + '.sct'
# Read metadata from ALS log file.
contents = open(log_file, 'r')
for line in contents:
if '-nangles' in line:
nproj = int(re.findall(r'\d+', line)[0])
if '-num_bright_field' in line:
nflat = int(re.findall(r'\d+', line)[0])
if '-num_dark_fields' in line:
ndark = int(re.findall(r'\d+', line)[0])
contents.close()
if ind_tomo is None:
ind_tomo = range(0, nproj)
ind_flat = range(0, nflat)
ind_dark = range(0, ndark)
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=4)
dark = tio.read_tiff_stack(dark_name, ind=ind_dark, digit=4)
return tomo, flat, dark
def read_elettra_syrmep(
fname, ind_tomo, ind_flat, ind_dark, proj=None, sino=None):
"""
Read Elettra SYRMEP standard data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
ind_flat : list of int
Indices of the flat field files to read.
ind_dark : list of int
Indices of the dark field files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'tomo_0001.tif')
flat_name = os.path.join(fname, 'flat_1.tif')
dark_name = os.path.join(fname, 'dark_1.tif')
tomo = tio.read_tiff_stack(
tomo_name, ind=ind_tomo, digit=4, slc=(sino, proj))
flat = tio.read_tiff_stack(
flat_name, ind=ind_flat, digit=1, slc=(sino, None))
dark = tio.read_tiff_stack(
dark_name, ind=ind_dark, digit=1, slc=(sino, None))
return tomo, flat, dark
def read_anka_topotomo(
fname, ind_tomo, ind_flat, ind_dark, proj=None, sino=None):
"""
Read ANKA TOMO-TOMO standard data format.
Parameters
----------
fname : str
Path to data folder name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
ind_flat : list of int, optional
Indices of the flat field files to read.
ind_dark : list of int, optional
Indices of the dark field files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'radios', 'image_00000.tif')
flat_name = os.path.join(fname, 'flats', 'image_00000.tif')
dark_name = os.path.join(fname, 'darks', 'image_00000.tif')
tomo = tio.read_tiff_stack(
tomo_name, ind=ind_tomo, digit=5, slc=(sino, proj))
flat = tio.read_tiff_stack(
flat_name, ind=ind_flat, digit=5, slc=(sino, None))
dark = tio.read_tiff_stack(
dark_name, ind=ind_dark, digit=5, slc=(sino, None))
return tomo, flat, dark
def read_petra3_p05(fname, ind_tomo, ind_flat, ind_dark):
"""
Read Petra-III P05 standard data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
ind_flat : list of int
Indices of the flat field files to read.
ind_dark : list of int
Indices of the dark field files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(
fname, 'scan_0002', 'ccd', 'pco01', 'ccd_0000.tif')
flat_name = os.path.join(
fname, 'scan_0001', 'ccd', 'pco01', 'ccd_0000.tif')
dark_name = os.path.join(
fname, 'scan_0003', 'ccd', 'pco01', 'ccd_0000.tif')
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=4)
dark = tio.read_tiff_stack(dark_name, ind=ind_dark, digit=4)
return tomo, flat, dark
def read_petra3_p05(fname, ind_tomo, ind_flat, ind_dark):
"""
Read Petra-III P05 standard data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
ind_flat : list of int
Indices of the flat field files to read.
ind_dark : list of int
Indices of the dark field files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'scan_0002', 'ccd', 'pco01',
'ccd_0000.tif')
flat_name = os.path.join(fname, 'scan_0001', 'ccd', 'pco01',
'ccd_0000.tif')
dark_name = os.path.join(fname, 'scan_0003', 'ccd', 'pco01',
'ccd_0000.tif')
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=4)
dark = tio.read_tiff_stack(dark_name, ind=ind_dark, digit=4)
return tomo, flat, dark
def read_aus_microct(fname, ind_tomo, ind_flat, ind_dark):
"""
Read Australian Synchrotron Micro Computed Tomography standard
data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
ind_flat : list of int
Indices of the flat field files to read.
ind_dark : list of int
Indices of the dark field files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'SAMPLE_T_0000.tif')
flat_name = os.path.join(fname, 'BG__BEFORE_00.tif')
dark_name = os.path.join(fname, 'DF__BEFORE_00.tif')
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=2)
dark = tio.read_tiff_stack(dark_name, ind=ind_dark, digit=2)
return tomo, flat, dark
def read_aus_microct(fname, ind_tomo, ind_flat, ind_dark):
"""
Read Australian Synchrotron Micro Computed Tomography standard
data format.
Parameters
----------
fname : str
Path to data folder.
ind_tomo : list of int
Indices of the projection files to read.
ind_flat : list of int
Indices of the flat field files to read.
ind_dark : list of int
Indices of the dark field files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'SAMPLE_T_0000.tif')
flat_name = os.path.join(fname, 'BG__BEFORE_00.tif')
dark_name = os.path.join(fname, 'DF__BEFORE_00.tif')
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=2)
dark = tio.read_tiff_stack(dark_name, ind=ind_dark, digit=2)
return tomo, flat, dark
def read_anka_tomotopo(fname, ind_tomo, ind_flat, ind_dark):
"""
Read ANKA TOMO-TOMO standard data format.
Parameters
----------
fname : str
Path to data folder name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
ind_flat : list of int, optional
Indices of the flat field files to read.
ind_dark : list of int, optional
Indices of the dark field files to read.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
fname = os.path.abspath(fname)
tomo_name = os.path.join(fname, 'radios', 'image_00000.tif')
flat_name = os.path.join(fname, 'flats', 'image_00000.tif')
dark_name = os.path.join(fname, 'darks', 'image_00000.tif')
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=5)
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=5)
dark = tio.read_tiff_stack(dark_name, ind=ind_dark, digit=5)
return tomo, flat, dark
def read_als_832(fname, ind_tomo=None, normalized=False):
"""
Read ALS 8.3.2 standard data format.
Parameters
----------
fname : str
Path to file name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
normalized : boolean
If False, darks and flats will not be read. This should
only be used for cases where tomo is already normalized.
8.3.2 has a plugin that normalization is preferred to be
done with prior to tomopy reconstruction.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
# File definitions.
fname = os.path.abspath(fname)
if not normalized:
fname = fname.split('output')[0] + fname.split('/')[
len(fname.split('/')) - 1]
tomo_name = fname + '_0000_0000.tif'
flat_name = fname + 'bak_0000.tif'
dark_name = fname + 'drk_0000.tif'
log_file = fname + '.sct'
else:
if "output" not in fname:
raise Exception(
'Please provide the normalized output directory as input')
tomo_name = fname + '_0.tif'
fname = fname.split('output')[0] + fname.split('/')[
len(fname.split('/')) - 1]
log_file = fname + '.sct'
# Read metadata from ALS log file.
contents = open(log_file, 'r')
for line in contents:
if '-nangles' in line:
nproj = int(re.findall(r'\d+', line)[0])
if '-num_bright_field' in line:
nflat = int(re.findall(r'\d+', line)[0])
if '-i0cycle' in line:
inter_bright = int(re.findall(r'\d+', line)[1])
if '-num_dark_fields' in line:
ndark = int(re.findall(r'\d+', line)[0])
contents.close()
if ind_tomo is None:
ind_tomo = range(0, nproj)
if not normalized:
ind_flat = range(0, nflat)
if inter_bright > 0:
ind_flat = range(0, nproj, inter_bright)
flat_name = fname + 'bak_0000_0000.tif'
ind_dark = range(0, ndark)
# Read image data from tiff stack.
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
if not normalized:
# Adheres to 8.3.2 flat/dark naming conventions:
# ----Flats----
# root_namebak_xxxx_yyyy
# For datasets that take flat at the start and end of its scan,
# xxxx is in incrementals of one, and yyyy is either 0000 or the
# last projection. For datasets that take flat while they scan
# (when the beam fluctuates during scans),
# xxxx is always 0000, and yyyy is in intervals given by log file.
if inter_bright == 0:
a = [0, nproj - 1]
list_flat = tio._list_file_stack(flat_name, ind_flat, digit=4)
for x in ind_flat:
body = os.path.splitext(list_flat[x])[0] + "_"
ext = os.path.splitext(list_flat[x])[1]
for y, z in enumerate(a):
y = body + '{0:0={1}d}'.format(z, 4) + ext
if z == 0:
list_flat[x] = y
else:
list_flat.append(y)
list_flat = sorted(list_flat)
for m, image in enumerate(list_flat):
_arr = tio.read_tiff(image)
if m == 0:
dx = len(ind_flat * 2)
dy, dz = _arr.shape
flat = np.zeros((dx, dy, dz))
flat[m] = _arr
flat = tio._slice_array(flat, None)
else:
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=4)
# Adheres to 8.3.2 flat/dark naming conventions:
# ----Darks----
# root_namedrk_xxxx_yyyy
# All datasets thus far that take darks at the start and end of
# its scan, so xxxx is in incrementals of one, and yyyy is either
# 0000 or the last projection.
list_dark = tio._list_file_stack(dark_name, ind_dark, digit=4)
for x in ind_dark:
body = os.path.splitext(list_dark[x])[0] + '_'
ext = os.path.splitext(list_dark[x])[1]
body = body + '{0:0={1}d}'.format(nproj - 1, 4) + ext
list_dark[x] = body
list_dark = sorted(list_dark)
for m, image in enumerate(list_dark):
_arr = tio.read_tiff(image)
if m == 0:
dx = len(ind_dark)
dy, dz = _arr.shape
dark = np.zeros((dx, dy, dz))
dark[m] = _arr
dark = tio._slice_array(dark, None)
else:
flat = np.ones(1)
dark = np.zeros(1)
return tomo, flat, dark
def read_sls_tomcat(fname, ind_tomo=None, proj=None, sino=None):
"""
Read SLS TOMCAT standard data format.
Parameters
----------
fname : str
Path to file name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
# File definitions.
fname = os.path.abspath(fname)
_fname = fname + '0001.tif'
log_file = fname + '.log'
# Read metadata from SLS log file.
contents = open(log_file, 'r')
for line in contents:
ls = line.split()
if len(ls) > 1:
if ls[0] == 'Number' and ls[2] == 'projections':
nproj = int(ls[4])
elif ls[0] == 'Number' and ls[2] == 'flats':
nflat = int(ls[4])
elif ls[0] == 'Number' and ls[2] == 'darks':
ndark = int(ls[4])
contents.close()
dark_start = 1
dark_end = ndark + 1
flat_start = dark_end
flat_end = flat_start + nflat
proj_start = flat_end
proj_end = proj_start + nproj
if ind_tomo is None:
ind_tomo = range(proj_start, proj_end)
ind_flat = range(flat_start, flat_end)
ind_dark = range(dark_start, dark_end)
tomo = tio.read_tiff_stack(_fname, ind=ind_tomo, digit=4, slc=(sino, proj))
flat = tio.read_tiff_stack(_fname, ind=ind_flat, digit=4, slc=(sino, None))
dark = tio.read_tiff_stack(_fname, ind=ind_dark, digit=4, slc=(sino, None))
return tomo, flat, dark
def read_aps_1id(fname, ind_tomo=None, proj=None, sino=None):
"""
Read APS 1-ID standard data format.
Parameters
----------
fname : str
Path to file name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
# File definitions.
fname = os.path.abspath(fname)
_fname = fname + '000001.tif'
log_file = os.path.dirname(fname) + os.path.sep + 'TomoStillScan.dat'
# Read APS 1-ID log file data
contents = open(log_file, 'r')
for line in contents:
ls = line.split()
if len(ls) > 1:
if ls[0] == "Tomography" and ls[1] == "scan":
prj_start = int(ls[6])
elif ls[0] == "Number" and ls[2] == "scan":
nprj = int(ls[4])
elif ls[0] == "Dark" and ls[1] == "field":
dark_start = int(ls[6])
elif ls[0] == "Number" and ls[2] == "dark":
ndark = int(ls[5])
elif ls[0] == "White" and ls[1] == "field":
flat_start = int(ls[6])
elif ls[0] == "Number" and ls[2] == "white":
nflat = int(ls[5])
contents.close()
if ind_tomo is None:
ind_tomo = range(prj_start, prj_start + nprj)
ind_flat = range(flat_start, flat_start + nflat)
ind_dark = range(dark_start, dark_start + ndark)
tomo = tio.read_tiff_stack(_fname, ind=ind_tomo, digit=6, slc=(sino, proj))
flat = tio.read_tiff_stack(_fname, ind=ind_flat, digit=6, slc=(sino, None))
dark = tio.read_tiff_stack(_fname, ind=ind_dark, digit=6, slc=(sino, None))
return tomo, flat, dark
def read_sls_tomcat(fname, ind_tomo=None, proj=None, sino=None):
"""
Read SLS TOMCAT standard data format.
Parameters
----------
fname : str
Path to file name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
# File definitions.
fname = os.path.abspath(fname)
_fname = fname + '0001.tif'
log_file = fname + '.log'
# Read metadata from SLS log file.
contents = open(log_file, 'r')
for line in contents:
ls = line.split()
if len(ls) > 1:
if ls[0] == 'Number' and ls[2] == 'projections':
nproj = int(ls[4])
elif ls[0] == 'Number' and ls[2] == 'flats':
nflat = int(ls[4])
elif ls[0] == 'Number' and ls[2] == 'darks':
ndark = int(ls[4])
contents.close()
dark_start = 1
dark_end = ndark + 1
flat_start = dark_end
flat_end = flat_start + nflat
proj_start = flat_end
proj_end = proj_start + nproj
if ind_tomo is None:
ind_tomo = range(proj_start, proj_end)
ind_flat = range(flat_start, flat_end)
ind_dark = range(dark_start, dark_end)
tomo = tio.read_tiff_stack(_fname, ind=ind_tomo, digit=4, slc=(sino, proj))
flat = tio.read_tiff_stack(_fname, ind=ind_flat, digit=4, slc=(sino, None))
dark = tio.read_tiff_stack(_fname, ind=ind_dark, digit=4, slc=(sino, None))
return tomo, flat, dark
def read_aps_1id(fname, ind_tomo=None, proj=None, sino=None):
"""
Read APS 1-ID standard data format.
Parameters
----------
fname : str
Path to file name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
sino : {sequence, int}, optional
Specify sinograms to read. (start, end, step)
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
# File definitions.
fname = os.path.abspath(fname)
_fname = fname + '000001.tif'
log_file = os.path.dirname(fname) + os.path.sep + 'TomoStillScan.dat'
# Read APS 1-ID log file data
contents = open(log_file, 'r')
for line in contents:
ls = line.split()
if len(ls) > 1:
if (ls[0] == "Tomography" and ls[1] == "scan"):
prj_start = int(ls[6])
elif (ls[0] == "Number" and ls[2] == "scan"):
nprj = int(ls[4])
elif (ls[0] == "Dark" and ls[1] == "field"):
dark_start = int(ls[6])
elif (ls[0] == "Number" and ls[2] == "dark"):
ndark = int(ls[5])
elif (ls[0] == "White" and ls[1] == "field"):
flat_start = int(ls[6])
elif (ls[0] == "Number" and ls[2] == "white"):
nflat = int(ls[5])
contents.close()
if ind_tomo is None:
ind_tomo = range(prj_start, prj_start + nprj)
ind_flat = range(flat_start, flat_start + nflat)
ind_dark = range(dark_start, dark_start + ndark)
tomo = tio.read_tiff_stack(_fname, ind=ind_tomo, digit=6, slc=(sino, proj))
flat = tio.read_tiff_stack(_fname, ind=ind_flat, digit=6, slc=(sino, None))
dark = tio.read_tiff_stack(_fname, ind=ind_dark, digit=6, slc=(sino, None))
return tomo, flat, dark
def read_als_832(fname, ind_tomo=None, normalized=False):
"""
Read ALS 8.3.2 standard data format.
Parameters
----------
fname : str
Path to file name without indices and extension.
ind_tomo : list of int, optional
Indices of the projection files to read.
normalized : boolean
If False, darks and flats will not be read. This should
only be used for cases where tomo is already normalized.
8.3.2 has a plugin that normalization is preferred to be
done with prior to tomopy reconstruction.
Returns
-------
ndarray
3D tomographic data.
ndarray
3d flat field data.
ndarray
3D dark field data.
"""
# File definitions.
fname = os.path.abspath(fname)
if not normalized:
fname = fname.split('output')[0]+fname.split('/')[len(fname.split('/'))-1]
tomo_name = fname + '_0000_0000.tif'
flat_name = fname + 'bak_0000.tif'
dark_name = fname + 'drk_0000.tif'
log_file = fname + '.sct'
else:
if "output" not in fname:
raise Exception('Please provide the normalized output directory as input')
tomo_name = fname + '_0.tif'
fname = fname.split('output')[0]+fname.split('/')[len(fname.split('/'))-1]
log_file = fname + '.sct'
# Read metadata from ALS log file.
contents = open(log_file, 'r')
for line in contents:
if '-nangles' in line:
nproj = int(re.findall(r'\d+', line)[0])
if '-num_bright_field' in line:
nflat = int(re.findall(r'\d+', line)[0])
if '-i0cycle' in line:
inter_bright = int(re.findall(r'\d+', line)[1])
if '-num_dark_fields' in line:
ndark = int(re.findall(r'\d+', line)[0])
contents.close()
if ind_tomo is None:
ind_tomo = range(0, nproj)
if not normalized:
ind_flat = range(0, nflat)
if inter_bright > 0:
ind_flat = range(0, nproj, inter_bright)
flat_name = fname + 'bak_0000_0000.tif'
ind_dark = range(0, ndark)
# Read image data from tiff stack.
tomo = tio.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
if not normalized:
""" Adheres to 8.3.2 flat/dark naming conventions:
----Flats----
root_namebak_xxxx_yyyy
For datasets that take flat at the start and end of its scan,
xxxx is in incrementals of one, and yyyy is either 0000 or the last projection.
For datasets that take flat while they scan (when the beam fluctuates during scans),
xxxx is always 0000, and yyyy is in intervals given by log file.
"""
if inter_bright == 0:
a = [0,nproj-1]
list_flat = tio._list_file_stack(flat_name, ind_flat, digit=4)
for x in ind_flat:
body = os.path.splitext(list_flat[x])[0] + "_"
ext = os.path.splitext(list_flat[x])[1]
for y,z in enumerate(a):
y = body + '{0:0={1}d}'.format(z, 4) + ext
if z == 0: list_flat[x] = y
else: list_flat.append(y)
list_flat = sorted(list_flat)
for m, image in enumerate(list_flat):
_arr = tio.read_tiff(image)
if m == 0:
dx = len(ind_flat*2)
dy, dz = _arr.shape
flat = np.zeros((dx, dy, dz))
flat[m] = _arr
flat = tio._slice_array(flat, None)
else:
flat = tio.read_tiff_stack(flat_name, ind=ind_flat, digit=4)
""" Adheres to 8.3.2 flat/dark naming conventions:
----Darks----
root_namedrk_xxxx_yyyy
All datasets thus far that take darks at the start and end of its scan, so
xxxx is in incrementals of one, and yyyy is either 0000 or the last projection.
"""
list_dark = tio._list_file_stack(dark_name, ind_dark, digit=4)
for x in ind_dark:
body = os.path.splitext(list_dark[x])[0] + '_'
ext = os.path.splitext(list_dark[x])[1]
body = body + '{0:0={1}d}'.format(nproj-1, 4) + ext
list_dark[x] = body
list_dark = sorted(list_dark)
for m, image in enumerate(list_dark):
_arr = tio.read_tiff(image)
if m == 0:
dx = len(ind_dark)
dy, dz = _arr.shape
dark = np.zeros((dx, dy, dz))
dark[m] = _arr
dark = tio._slice_array(dark, None)
else:
flat = np.ones(1)
dark = np.zeros(1)
return tomo, flat, dark
