Пример #1
0
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
Пример #2
0
 def test_list_file_stack_long_path(self):
     file_stack = reader._list_file_stack("someFile/otherFile/image_0.xrm",
                                          [1, 2])
     self.assertEqual(file_stack, [
         "someFile/otherFile/image_1.xrm", "someFile/otherFile/image_2.xrm"
     ])
Пример #3
0
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
Пример #4
0
 def test_list_file_stack_underscore_split_digits(self):
     file_stack = reader._list_file_stack("path/image_00000_00000.xrm",
                                          [1, 2])
     self.assertEqual(
         file_stack,
         ["path/image_00000_00001.xrm", "path/image_00000_00002.xrm"])
Пример #5
0
 def test_list_file_stack_one_digit(self):
     file_stack = reader._list_file_stack("path/image_0.xrm", [1, 2])
     self.assertEqual(file_stack, ["path/image_1.xrm", "path/image_2.xrm"])
Пример #6
0
 def test_list_file_stack_long_path(self):
     file_stack = reader._list_file_stack(
         "someFile/otherFile/image_0.xrm", [1, 2])
     self.assertEqual(
         file_stack,
         ["someFile/otherFile/image_1.xrm", "someFile/otherFile/image_2.xrm"])
Пример #7
0
 def test_list_file_stack_underscore_split_digits(self):
     file_stack = reader._list_file_stack(
         "path/image_00000_00000.xrm", [1, 2])
     self.assertEqual(
         file_stack,
         ["path/image_00000_00001.xrm", "path/image_00000_00002.xrm"])
Пример #8
0
 def test_list_file_stack_one_digit(self):
     file_stack = reader._list_file_stack("path/image_0.xrm", [1, 2])
     self.assertEqual(
         file_stack, ["path/image_1.xrm", "path/image_2.xrm"])