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')