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_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_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