def read_hdf5(fname, dataset, slc=None, dtype=None, shared=False):
"""
Read data from hdf5 file from a specific group.
Parameters
----------
fname : str
String defining the path of file or file name.
dataset : str
Path to the dataset inside hdf5 file where data is located.
slc : sequence of tuples, optional
Range of values for slicing data in each axis.
((start_1, end_1, step_1), ... , (start_N, end_N, step_N))
defines slicing parameters for each axis of the data matrix.
dtype : numpy datatype (optional)
Convert data to this datatype on read if specified.
shared : bool (optional)
If True, read data into shared memory location. Defaults to True.
Returns
-------
ndarray
Data.
"""
try:
fname = _check_read(fname)
with h5py.File(fname, "r") as f:
try:
data = f[dataset]
except KeyError:
# NOTE: I think it would be better to raise an exception here.
logger.error('Unrecognized hdf5 dataset: "%s"' %
(str(dataset)))
return None
shape = _shape_after_slice(data.shape, slc)
if dtype is None:
dtype = data.dtype
if shared:
arr = empty_shared_array(shape, dtype)
else:
arr = np.empty(shape, dtype)
data.read_direct(arr, _make_slice_object_a_tuple(slc))
except KeyError:
return None
_log_imported_data(fname, arr)
return arr
def read_hdf5(fname, dataset, slc=None, dtype=None, shared=False):
"""
Read data from hdf5 file from a specific group.
Parameters
----------
fname : str
String defining the path of file or file name.
dataset : str
Path to the dataset inside hdf5 file where data is located.
slc : sequence of tuples, optional
Range of values for slicing data in each axis.
((start_1, end_1, step_1), ... , (start_N, end_N, step_N))
defines slicing parameters for each axis of the data matrix.
dtype : numpy datatype (optional)
Convert data to this datatype on read if specified.
shared : bool (optional)
If True, read data into shared memory location. Defaults to True.
Returns
-------
ndarray
Data.
"""
try:
fname = _check_read(fname)
with h5py.File(fname, "r") as f:
try:
data = f[dataset]
except KeyError:
# NOTE: I think it would be better to raise an exception here.
logger.error('Unrecognized hdf5 dataset: "%s"' %
(str(dataset)))
return None
shape = _shape_after_slice(data.shape, slc)
if dtype is None:
dtype = data.dtype
if shared:
arr = empty_shared_array(shape, dtype)
else:
arr = np.empty(shape, dtype)
data.read_direct(arr, _make_slice_object_a_tuple(slc))
except KeyError:
return None
_log_imported_data(fname, arr)
return arr
