pypet/trajectory.py
def f_load_items(self, iterator, *args, **kwargs):
        """Loads parameters and results specified in `iterator`.

        You can directly list the Parameter objects or just their names.

        If names are given the `~pypet.naturalnaming.NNGroupNode.f_get` method is applied to find the
        parameters or results in the trajectory. Accordingly, the parameters and results
        you want to load must already exist in your trajectory (in RAM), probably they
        are just empty skeletons waiting desperately to handle data.
        If they do not exist in RAM yet, but have been stored to disk before,
        you can call :func:`~pypet.trajectory.Trajectory.f_load_skeleton` in order to
        bring your trajectory tree skeleton up to date. In case of a single run you can
        use the :func:`~pypet.naturalnaming.NNGroupNode.f_load_child` method to recursively
        load a subtree without any data.
        Then you can load the data of individual results or parameters one by one.

        If want to load the whole trajectory at once or ALL results and parameters that are
        still empty take a look at :func:`~pypet.trajectory.Trajectory.f_load`.
        As mentioned before, to load subtrees of your trajectory you might want to check out
        :func:`~pypet.naturalnaming.NNGroupNode.f_load_child`.

        To load a list of parameters or results with `f_load_items` you can pass
        the following arguments:

        :param iterator: A list with parameters or results to be loaded.

        :param only_empties:

            Optional keyword argument (boolean),
            if `True` only empty parameters or results are passed
            to the storage service to get loaded. Non-empty parameters or results found in
            `iterator` are simply ignored.

        :param args: Additional arguments directly passed to the storage service

        :param kwargs:

            Additional keyword arguments directly passed to the storage service
            (except the kwarg `only_empties`)

            If you use the standard hdf5 storage service, you can pass the following additional
            keyword arguments:

            :param load_only:

                If you load a result, you can partially load it and ignore the rest of data items.
                Just specify the name of the data you want to load. You can also provide a list,
                for example `load_only='spikes'`, `load_only=['spikes','membrane_potential']`.

                Be aware that you need to specify the names of parts as they were stored
                to HDF5. Depending on how your leaf construction works, this may differ
                from the names the data might have in your leaf in the trajectory container.

                A warning is issued if data specified in `load_only` cannot be found in the
                instances specified in `iterator`.

            :param load_except:

                Analogous to the above, but everything is loaded except names or parts
                specified in `load_except`.
                You cannot use `load_only` and `load_except` at the same time. If you do
                a ValueError is thrown.

                A warning is issued if names listed in `load_except` are not part of the
                items to load.

        """

        if not self._stored:
            raise TypeError(
                'Cannot load stuff from disk for a trajectory that has never been stored.')

        fetched_items = self._nn_interface._fetch_items(LOAD, iterator, args, kwargs)
        if fetched_items:
            self._storage_service.load(pypetconstants.LIST, fetched_items,
                                       trajectory_name=self.v_name)
        else:
            self._logger.warning('Your loading was not successful, could not find a single item '
                                 'to load.')
def f_load_items(self, iterator, *args, **kwargs):
        if not self._stored:
            raise TypeError(
                'Cannot load stuff from disk for a trajectory that has never been stored.')

        fetched_items = self._nn_interface._fetch_items(LOAD, iterator, args, kwargs)
        if fetched_items:
            self._storage_service.load(pypetconstants.LIST, fetched_items,
                                       trajectory_name=self.v_name)
        else:
            self._logger.warning('Your loading was not successful, could not find a single item '
                                 'to load.')
def f_load_items ( self , iterator , * args , * * kwargs ) : if not self . _stored : raise TypeError ( 'Cannot load stuff from disk for a trajectory that has never been stored.' ) fetched_items = self . _nn_interface . _fetch_items ( LOAD , iterator , args , kwargs ) if fetched_items : self . _storage_service . load ( pypetconstants . LIST , fetched_items , trajectory_name = self . v_name ) else : self . _logger . warning ( 'Your loading was not successful, could not find a single item ' 'to load.' )
Loads parameters and results specified in `iterator`.

        You can directly list the Parameter objects or just their names.

        If names are given the `~pypet.naturalnaming.NNGroupNode.f_get` method is applied to find the
        parameters or results in the trajectory. Accordingly, the parameters and results
        you want to load must already exist in your trajectory (in RAM), probably they
        are just empty skeletons waiting desperately to handle data.
        If they do not exist in RAM yet, but have been stored to disk before,
        you can call :func:`~pypet.trajectory.Trajectory.f_load_skeleton` in order to
        bring your trajectory tree skeleton up to date. In case of a single run you can
        use the :func:`~pypet.naturalnaming.NNGroupNode.f_load_child` method to recursively
        load a subtree without any data.
        Then you can load the data of individual results or parameters one by one.

        If want to load the whole trajectory at once or ALL results and parameters that are
        still empty take a look at :func:`~pypet.trajectory.Trajectory.f_load`.
        As mentioned before, to load subtrees of your trajectory you might want to check out
        :func:`~pypet.naturalnaming.NNGroupNode.f_load_child`.

        To load a list of parameters or results with `f_load_items` you can pass
        the following arguments:

        :param iterator: A list with parameters or results to be loaded.

        :param only_empties:

            Optional keyword argument (boolean),
            if `True` only empty parameters or results are passed
            to the storage service to get loaded. Non-empty parameters or results found in
            `iterator` are simply ignored.

        :param args: Additional arguments directly passed to the storage service

        :param kwargs:

            Additional keyword arguments directly passed to the storage service
            (except the kwarg `only_empties`)

            If you use the standard hdf5 storage service, you can pass the following additional
            keyword arguments:

            :param load_only:

                If you load a result, you can partially load it and ignore the rest of data items.
                Just specify the name of the data you want to load. You can also provide a list,
                for example `load_only='spikes'`, `load_only=['spikes','membrane_potential']`.

                Be aware that you need to specify the names of parts as they were stored
                to HDF5. Depending on how your leaf construction works, this may differ
                from the names the data might have in your leaf in the trajectory container.

                A warning is issued if data specified in `load_only` cannot be found in the
                instances specified in `iterator`.

            :param load_except:

                Analogous to the above, but everything is loaded except names or parts
                specified in `load_except`.
                You cannot use `load_only` and `load_except` at the same time. If you do
                a ValueError is thrown.

                A warning is issued if names listed in `load_except` are not part of the
                items to load.
Loads parameters and results specified in iterator .