4ed172063fc1ec493c91b327e4761192dbb227dd,pyemma/_base/serialization/jsonpickler_handlers.py,NumpyNPZHandler,flatten,#NumpyNPZHandler#Any#Any#,50

Before Change

    def flatten(self, obj, data):
        assert isinstance(obj, np.ndarray)
        buff = BytesIO()
        np.savez_compressed(buff, x=obj)
        buff.seek(0)
        flattened_bytes = util.b64encode(buff.read())
        data["npz_file_bytes"] = flattened_bytes

After Change

        return self.context.h5_file

    def flatten(self, obj, data):
        if obj.dtype == np.object_:
            raise NotImplementedError()
            res = [self.context.flatten(x) for x in obj]

            //raise Exception(str(obj))
            // TODO: how to deal with obj dtype? eg. return list
            //data.clear()

            data["py/object"] = "list"
        else:
            import uuid
            array_id = "{group}/{id}".format(group=self.file.name, id=uuid.uuid4())
            self.file.create_dataset(name=array_id, data=obj,
                                     chunks=True, compression="gzip", compression_opts=4, shuffle=True)
            data["array_ref"] = array_id
        return data

    def restore(self, obj):
        array_ref = obj["array_ref"]

Instances