def test_swmr_mode_consistency(self):
fname = self.mktemp()
fid = File(fname, 'w', libver='latest')
g = fid.create_group('foo')
assert fid.swmr_mode == g.file.swmr_mode == False
fid.swmr_mode = True
# This setter should affect both fid and group member file attribute
assert fid.swmr_mode == g.file.swmr_mode == True
fid.close()
def test_file_mode_generalizes(self):
fname = self.mktemp()
fid = File(fname, 'w', libver='latest')
g = fid.create_group('foo')
# fid and group member file attribute should have the same mode
assert fid.mode == g.file.mode == 'r+'
fid.swmr_mode = True
# fid and group member file attribute should still be 'r+'
# even though file intent has changed
assert fid.mode == g.file.mode == 'r+'
fid.close()
def write_data_to_file(datadict: DataDict,
f: h5py.File,
groupname: str = 'data',
append_mode: AppendMode = AppendMode.new,
swmr_mode: bool = True) -> None:
if groupname not in f:
raise RuntimeError('Group does not exist, initialize file first.')
grp = f[groupname]
# if we want to use swmr, we need to make sure that we're not
# creating any more objects (see hdf5 docs).
allexist = True
for k, v in datadict.data_items():
if k not in grp:
allexist = False
# add top-level meta data.
for k, v in datadict.meta_items(clean_keys=False):
set_attr(grp, k, v)
f.flush()
if allexist and swmr_mode and not f.swmr_mode:
f.swmr_mode = True
for k, v in datadict.data_items():
data = v['values']
shp = data.shape
nrows = shp[0]
# create new dataset, add axes and unit metadata
if k not in grp:
maxshp = tuple([None] + list(shp[1:]))
ds = grp.create_dataset(k, maxshape=maxshp, data=data)
# add meta data
add_cur_time_attr(ds)
if v.get('axes', []) != []:
set_attr(ds, 'axes', v['axes'])
if v.get('unit', "") != "":
set_attr(ds, 'unit', v['unit'])
for kk, vv in datadict.meta_items(k, clean_keys=False):
set_attr(ds, kk, vv)
ds.flush()
# if the dataset already exits, append data according to
# chosen append mode.
else:
ds = grp[k]
dslen = ds.shape[0]
if append_mode == AppendMode.new:
newshp = tuple([nrows] + list(shp[1:]))
ds.resize(newshp)
ds[dslen:] = data[dslen:]
elif append_mode == AppendMode.all:
newshp = tuple([dslen + nrows] + list(shp[1:]))
ds.resize(newshp)
ds[dslen:] = data[:]
ds.flush()
f.flush()