def _check_read(fname):
known_extensions = ['.tiff', '.tif', '.h5', '.hdf', '.npy']
if not isinstance(fname, basestring):
logger.error('file name must be a string')
else:
if writer.get_extension(fname) not in known_extensions:
logger.error('unknown file extension')
return os.path.abspath(fname)
def _check_read(fname):
known_extensions = ['.edf', '.tiff', '.tif', '.h5', '.hdf', '.npy']
if not isinstance(fname, six.string_types):
logger.error('File name must be a string')
else:
if writer.get_extension(fname) not in known_extensions:
logger.error('Unknown file extension')
return os.path.abspath(fname)
def read_hdf5_stack(h5group, dname, ind, digit=4, slc=None, out_ind=None):
"""
Read data from stacked datasets in a hdf5 file
Parameters
----------
fname : str
One of the dataset names in the dataset stack
ind : list of int
Indices of the datasets to be read
digit : int
Number of digits indexing the stacked datasets
slc : {sequence, int}
Range of values for slicing data.
((start_1, end_1, step_1), ... , (start_N, end_N, step_N))
defines slicing parameters for each axis of the data matrix
out_ind : list of int, optional
Outer level indices for files with two levels of indexing.
i.e. [name_000_000.tif, name_000_001.tif, ..., name_000_lmn.tif,
name_001_lmn.tif, ..., ..., name_fgh_lmn.tif]
"""
list_fname = _list_file_stack(dname, ind, digit)
if out_ind is not None:
list_fname_ = []
for name in list_fname:
fname = (writer.get_body(name).split('/')[-1] + '_' + digit * '0' +
writer.get_extension(name))
list_fname_.extend(_list_file_stack(fname, out_ind, digit))
list_fname = list_fname_
for m, image in enumerate(list_fname):
_arr = h5group[image]
_arr = _slice_array(_arr, slc)
if m == 0:
dx, dy, dz = _arr.shape
dx = len(list_fname)
arr = np.empty((dx, dy, dz), dtype=_arr.dtype)
arr[m] = _arr
return arr
def read_hdf5_stack(h5group, dname, ind, digit=4, slc=None, out_ind=None):
"""
Read data from stacked datasets in a hdf5 file
Parameters
----------
fname : str
One of the dataset names in the dataset stack
ind : list of int
Indices of the datasets to be read
digit : int
Number of digits indexing the stacked datasets
slc : {sequence, int}
Range of values for slicing data.
((start_1, end_1, step_1), ... , (start_N, end_N, step_N))
defines slicing parameters for each axis of the data matrix
out_ind : list of int, optional
Outer level indices for files with two levels of indexing.
i.e. [name_000_000.tif, name_000_001.tif, ..., name_000_lmn.tif,
name_001_lmn.tif, ..., ..., name_fgh_lmn.tif]
"""
list_fname = _list_file_stack(dname, ind, digit)
if out_ind is not None:
list_fname_ = []
for name in list_fname:
fname = (writer.get_body(name).split('/')[-1] + '_' + digit*'0' +
writer.get_extension(name))
list_fname_.extend(_list_file_stack(fname, out_ind, digit))
list_fname = list_fname_
for m, image in enumerate(list_fname):
_arr = h5group[image]
_arr = _slice_array(_arr, slc)
if m == 0:
dx, dy, dz = _arr.shape
dx = len(list_fname)
arr = np.empty((dx, dy, dz), dtype=_arr.dtype)
arr[m] = _arr
return arr
def _list_file_stack(fname, ind, digit):
"""
Return a stack of file names in a folder as a list.
Parameters
----------
fname : str
String defining the path or file name.
ind : list of int
Indices of the files to read.
digit : int
Number of digits in indexing stacked files.
"""
fname = os.path.abspath(fname)
body = writer.get_body(fname, digit)
ext = writer.get_extension(fname)
list_fname = []
for m in ind:
list_fname.append(str(body + '{0:0={1}d}'.format(m, digit) + ext))
return list_fname
def _list_file_stack(fname, ind, digit):
"""
Return a stack of file names in a folder as a list.
Parameters
----------
fname : str
String defining the path of file or file name.
ind : list of int
Indices of the files to read.
digit : int
Number of digits in indexing stacked files.
"""
body = writer.get_body(fname, digit)
ext = writer.get_extension(fname)
list_fname = []
for m in ind:
list_fname.append(str(body + '{0:0={1}d}'.format(m, digit) + ext))
return list_fname