def read_diamond_l12(fname, ind_tomo, proj=None):
"""
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.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
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 = list(range(0, 1))
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
tomo = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo)
flat = dxreader.read_tiff_stack(flat_name, ind=ind_flat)
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 = list(range(0, 1))
tomo = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo, digit=6)
flat = dxreader.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 = list(range(0, 1))
tomo = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo, digit=6)
flat = dxreader.read_tiff_stack(flat_name, ind=ind_flat, digit=6)
return tomo, flat
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 = dxreader.read_tiff_stack(tomo_name,
ind=ind_tomo,
digit=4,
slc=(sino, proj))
flat = dxreader.read_tiff_stack(flat_name,
ind=ind_flat,
digit=4,
slc=(sino, None))
dark = dxreader.read_tiff_stack(dark_name,
ind=ind_dark,
digit=4,
slc=(sino, None))
return tomo, flat, dark
def read_diamond_l12(fname, ind_tomo, proj=None):
"""
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.
proj : {sequence, int}, optional
Specify projections to read. (start, end, step)
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 = list(range(0, 1))
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
tomo = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo)
flat = dxreader.read_tiff_stack(flat_name, ind=ind_flat)
return tomo, flat
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 = dxreader.read_tiff_stack(tomo_name,
ind=ind_tomo,
digit=4,
slc=(sino, proj))
flat = dxreader.read_tiff_stack(flat_name,
ind=ind_flat,
digit=1,
slc=(sino, None))
dark = dxreader.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 = dxreader.read_tiff_stack(tomo_name,
ind=ind_tomo,
digit=5,
slc=(sino, proj))
flat = dxreader.read_tiff_stack(flat_name,
ind=ind_flat,
digit=5,
slc=(sino, None))
dark = dxreader.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')
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
tomo = dxreader.read_tiff_stack(
tomo_name, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(
flat_name, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff_stack(
dark_name, ind=ind_dark, slc=(sino, None))
return tomo, flat, dark
def read_aus_microct(fname,
ind_tomo,
ind_flat,
ind_dark,
proj=None,
sino=None):
"""
Read Australian Synchrotron micro-CT 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, 'SAMPLE_T_0000.tif')
flat_name = os.path.join(fname, 'BG__BEFORE_00.tif')
dark_name = os.path.join(fname, 'DF__BEFORE_00.tif')
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
tomo = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(flat_name, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff_stack(dark_name, ind=ind_dark, slc=(sino, None))
return tomo, flat, dark
def read_aus_microct(fname, ind_tomo, ind_flat, ind_dark, proj=None, sino=None):
"""
Read Australian Synchrotron micro-CT 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, 'SAMPLE_T_0000.tif')
flat_name = os.path.join(fname, 'BG__BEFORE_00.tif')
dark_name = os.path.join(fname, 'DF__BEFORE_00.tif')
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
tomo = dxreader.read_tiff_stack(
tomo_name, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(
flat_name, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff_stack(
dark_name, ind=ind_dark, slc=(sino, None))
return tomo, flat, dark
def read_anka_topotomo(
fname, ind_tomo, ind_flat, ind_dark, proj=None, sino=None):
"""
Read ANKA TOPO-TOMO standard data format.
Parameters
----------
fname : str
Path to data folder name without indices and extension.
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, 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')
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
tomo = dxreader.read_tiff_stack(
tomo_name, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(
flat_name, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff_stack(
dark_name, ind=ind_dark, slc=(sino, None))
return tomo, flat, dark
def read_aps_5bm(fname, sino=None):
"""
Read APS 5-BM standard data format.
Parameters
----------
fname : str
Path to data folder.
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, 'sdat0000.xmt')
flat_name = os.path.join(fname, 'snor0000.xmt')
dark_name = os.path.join(fname, 'sdarkfile.xmt')
ntomo = len(fnmatch.filter(os.listdir(fname), 'sdat*'))
ind_tomo = range(0, ntomo)
nflat = len(fnmatch.filter(os.listdir(fname), 'snor*'))
ind_flat = range(0, nflat)
tomo = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(flat_name, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff(dark_name, slc=(sino, None))
# array bite swapping
for index in ind_tomo:
tomo[index] = tomo[index].byteswap()
for index in ind_flat:
flat[index] = flat[index].byteswap()
dark = dark.byteswap()
return tomo, flat, dark
def read_aps_5bm(fname, sino=None):
"""
Read APS 5-BM standard data format.
Parameters
----------
fname : str
Path to data folder.
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, 'sdat0000.xmt')
flat_name = os.path.join(fname, 'snor0000.xmt')
dark_name = os.path.join(fname, 'sdarkfile.xmt')
ntomo = len(fnmatch.filter(os.listdir(fname), 'sdat*'))
ind_tomo = range(0, ntomo)
nflat = len(fnmatch.filter(os.listdir(fname), 'snor*'))
ind_flat = range(0, nflat)
tomo = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(flat_name, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff(dark_name, slc=(sino, None))
# array bite swapping
for index in ind_tomo:
tomo[index] = tomo[index].byteswap()
for index in ind_flat:
flat[index] = flat[index].byteswap()
dark = dark.byteswap()
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 = dxreader.read_tiff_stack(
tomo_name, ind=ind_tomo, digit=4, slc=(sino, proj))
flat = dxreader.read_tiff_stack(
flat_name, ind=ind_flat, digit=1, slc=(sino, None))
dark = dxreader.read_tiff_stack(
dark_name, ind=ind_dark, digit=1, slc=(sino, None))
return tomo, flat, dark
def read_aus_microct(fname, ind_tomo, ind_flat, ind_dark):
"""
Read Australian Synchrotron micro-CT 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 = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
flat = dxreader.read_tiff_stack(flat_name, ind=ind_flat, digit=2)
dark = dxreader.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-CT 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 = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4)
flat = dxreader.read_tiff_stack(flat_name, ind=ind_flat, digit=2)
dark = dxreader.read_tiff_stack(dark_name, ind=ind_dark, digit=2)
return tomo, flat, dark
def find_roi(opt):
"""
Use bright field to determine ROI (crop region)
:param opt:
output of tomo_par_init
:return roi:
roi = (x, y, w, h)
"""
import dxchange.reader as dxread
ind_to_read = [opt['ind_w1'][0][0]]
roi = opt['roi']
rot_angle = opt['rot_angle']
medfilter_size = None
fname = opt['input_template']
imgw = dxread.read_tiff_stack(fname,
ind=ind_to_read,
digit=None,
slc=None,
angle=rot_angle,
mblur=medfilter_size)
imgn = cv2.normalize(imgw[0, :, :],
None,
alpha=0,
beta=255,
norm_type=cv2.NORM_MINMAX,
dtype=cv2.CV_8U)
[ch, cw] = imgn.shape
if roi[2] < cw or roi[3] < ch or roi[0] != 0 or roi[1] != 0:
cv2.rectangle(imgn, (roi[0], roi[1]),
(roi[0] + roi[2], roi[1] + roi[3]), 255, 2, cv2.LINE_AA)
cv2.putText(imgn, 'current ROI(x,y,w,h): ' + ','.join(map(str, roi)),
(roi[0], roi[1] - 5), cv2.FONT_HERSHEY_SIMPLEX, 1, 255, 2,
cv2.LINE_AA)
cv2.namedWindow('Select ROI', cv2.WINDOW_NORMAL)
(x, y, w, h) = cv2.selectROI('Select ROI', imgn, True)
if x + y + w + h == 0:
print('ROI remains the same!!')
return roi
else:
print('New ROI is ', x, y, w, h)
return x, y, w, h
def merge_tiffs(fname,output,ind):
print('Reading data')
data = dxreader.read_tiff_stack(fname, ind)
print('Saving merged data to {}'.format(output))
dxwriter.write_tiff(data,fname=output)
def read_als_832(fname, ind_tomo=None, normalized=False, proj=None, sino=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.
normalized : boolean, optional
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.
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)
if not normalized:
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 = list(range(0, nproj))
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
if not normalized:
ind_flat = list(range(0, nflat))
if inter_bright > 0:
ind_flat = list(range(0, nproj, inter_bright))
flat_name = fname + 'bak_0000_0000.tif'
ind_dark = list(range(0, ndark))
# Read image data from tiff stack.
tomo = dxreader.read_tiff_stack(tomo_name,
ind=ind_tomo,
digit=4,
slc=(sino, None))
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 = dxreader._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 = dxreader.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 = dxreader._slice_array(flat, (None, sino))
else:
flat = dxreader.read_tiff_stack(flat_name,
ind=ind_flat,
digit=4,
slc=(sino, None))
# 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 = dxreader._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 = dxreader.read_tiff(image)
if m == 0:
dx = len(ind_dark)
dy, dz = _arr.shape
dark = np.zeros((dx, dy, dz))
dark[m] = _arr
dark = dxreader._slice_array(dark, (None, sino))
else:
flat = np.ones(1)
dark = np.zeros(1)
return tomo, flat, dark
def read_aps_1id(fname, ind_tomo=None, proj=None, sino=None, layer=0):
"""
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)
layer: int, optional
Specify the layer to reconstruct
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 = fname + 'TomoStillScan.dat'
# parse the log/metadata file
_metadf = dxreader.read_aps_1id_metafile(log_file)
# meta data for layer to reconstruct
try:
_layerdf = _metadf[_metadf['layerID'] == layer]
except:
print("Valid layers for reconstruction are: {}".format(
_metadf['layerID'].unique()))
# -- queery image data meta for given layer
# still/projection images
prj_start = _layerdf.loc[_layerdf['type'] == 'still', 'nSeq'].values[0]
nprj = _layerdf.loc[_layerdf['type'] == 'still', 'nSeq'].shape[0]
# dark field images
dark_start = _layerdf.loc[_layerdf['type'] == 'post_dark',
'nSeq'].values[0]
ndark = _layerdf.loc[_layerdf['type'] == 'post_dark', 'nSeq'].shape[0]
# white/flat field images (only use pre_white)
# NOTE: The beam condition might change overtime, therefore flat field
# images are taken both before and after the experiment.
# The implementation here assumes the beam is stable throughout the
# experiment
flat_start = _layerdf.loc[_layerdf['type'] == 'pre_white',
'nSeq'].values[0]
nflat = _layerdf.loc[_layerdf['type'] == 'pre_white', 'nSeq'].shape[0]
if ind_tomo is None:
ind_tomo = list(range(prj_start, prj_start + nprj))
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
ind_flat = list(range(flat_start, flat_start + nflat))
ind_dark = list(range(dark_start, dark_start + ndark))
tomo = dxreader.read_tiff_stack(_fname, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(_fname, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff_stack(_fname, ind=ind_dark, 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 = list(range(proj_start, proj_end))
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
ind_flat = list(range(flat_start, flat_end))
ind_dark = list(range(dark_start, dark_end))
tomo = dxreader.read_tiff_stack(_fname, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(_fname, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff_stack(_fname, ind=ind_dark, 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 = list(range(proj_start, proj_end))
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
ind_flat = list(range(flat_start, flat_end))
ind_dark = list(range(dark_start, dark_end))
tomo = dxreader.read_tiff_stack(
_fname, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(
_fname, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff_stack(
_fname, ind=ind_dark, slc=(sino, None))
return tomo, flat, dark
def read_als_832(fname, ind_tomo=None, normalized=False, proj=None, sino=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.
normalized : boolean, optional
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.
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)
if not normalized:
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 = list(range(0, nproj))
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
if not normalized:
ind_flat = list(range(0, nflat))
if inter_bright > 0:
ind_flat = list(range(0, nproj, inter_bright))
flat_name = fname + 'bak_0000_0000.tif'
ind_dark = list(range(0, ndark))
# Read image data from tiff stack.
tomo = dxreader.read_tiff_stack(tomo_name, ind=ind_tomo, digit=4,
slc=(sino, None))
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 = dxreader._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 = dxreader.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 = dxreader._slice_array(flat, (None, sino))
else:
flat = dxreader.read_tiff_stack(flat_name, ind=ind_flat, digit=4,
slc=(sino, None))
# 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 = dxreader._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 = dxreader.read_tiff(image)
if m == 0:
dx = len(ind_dark)
dy, dz = _arr.shape
dark = np.zeros((dx, dy, dz))
dark[m] = _arr
dark = dxreader._slice_array(dark, (None, sino))
else:
flat = np.ones(1)
dark = np.zeros(1)
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 = fname + '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 = list(range(prj_start, prj_start + nprj))
if proj is not None:
ind_tomo = ind_tomo[slice(*proj)]
ind_flat = list(range(flat_start, flat_start + nflat))
ind_dark = list(range(dark_start, dark_start + ndark))
tomo = dxreader.read_tiff_stack(
_fname, ind=ind_tomo, slc=(sino, None))
flat = dxreader.read_tiff_stack(
_fname, ind=ind_flat, slc=(sino, None))
dark = dxreader.read_tiff_stack(
_fname, ind=ind_dark, slc=(sino, None))
return tomo, flat, dark
if nstitch > 4:
print('Do not support stitch > 4!!')
elif nstitch == 3:
# generate index of files
ind_wf1 = opt['ind_w1'][2]
ind_pj1 = opt['ind_pj'][0]
ind_pj2 = opt['ind_pj'][1]
ind_pj3 = opt['ind_pj'][2]
ind_dk1 = opt['ind_dk'][0]
tic = time.time()
print("Start reading files....")
wf1 = dxreader.read_tiff_stack(fname,
ind=ind_wf1,
digit=None,
slc=(crop_y, crop_x),
angle=rot_angle,
mblur=medfilter_size)
#wf2 = dxreader.read_tiff_stack(fname, ind=ind_wf2, digit=None, slc=(crop_y, crop_x), angle=rot_angle, mblur=medfilter_size)
pj1 = dxreader.read_tiff_stack(fname,
ind=ind_pj1,
digit=None,
slc=(crop_y, crop_x),
angle=rot_angle,
mblur=medfilter_size)
pj2 = dxreader.read_tiff_stack(fname,
ind=ind_pj2,
digit=None,
slc=(crop_y, crop_x),
angle=rot_angle,
mblur=medfilter_size)
