def test_hdftools():
dtypes = [numpy.int, numpy.int8, numpy.int16, numpy.int32, numpy.int64,
numpy.float, numpy.float32, numpy.float64]
d = {}
for dtype in dtypes:
name = numpy.dtype(dtype).name
d[name] = (numpy.random.rand(100, 100) * 10).astype(dtype)
fname = os.path.join(tmp_dir, 'hdf_test.hdf5')
hdftools.save_dict(d, filename=fname, group='data')
d2 = hdftools.load_dict(fname, 'data')
for k in d2.keys():
numpy.testing.assert_equal(d[k], d2[k])
def to_hdf5(self, path):
"""
Save model to a HDF5 file.
Requires ``h5py`` http://docs.h5py.org/
Parameters
----------
path : str
Full file path. File must not already exist.
Raises
------
FileExistsError
If a file with the same path already exists.
"""
if not HDF5_INSTALLED:
raise ImportError(h5py_msg)
d = self._to_dict(output='hdf5')
hdftools.save_dict(d, path, 'data')
