pypet/storageservice.py
def _prm_write_into_array(self, key, data, group, fullname, **kwargs):
        """Stores data as array.

        :param key:

            Name of data item to store

        :param data:

            Data to store

        :param group:

            Group node where to store data in hdf5 file

        :param fullname:

            Full name of the `data_to_store`s original container, only needed for throwing errors.

        :param recall:

            If container type and data type for perfect recall should be stored

        """

        try:
            if key in group:
                raise ValueError(
                    'Array `%s` already exists in `%s`. Appending is not supported (yet).')

            try:

                array = self._hdf5file.create_array(where=group,
                                              name=key, obj=data, **kwargs)
            except (TypeError, ValueError) as exc:
                try:
                    if type(data) is dict and len(data) == 0:
                        # We cannot store an empty dictionary,
                        # but we can use an empty tuple as a dummy.
                        conv_data = ()
                    elif isinstance(data, str):
                        conv_data = data.encode(self._encoding)
                    elif isinstance(data, int):
                        conv_data = np.int64(data)
                    else:
                        conv_data = []
                        for string in data:
                            conv_data.append(string.encode(self._encoding))
                    array = self._hdf5file.create_array(where=group,
                                                  name=key, obj=conv_data, **kwargs)
                except Exception:
                    # Re-raise original error
                    raise exc

            if data is not None:
                # Remember the types of the original data to recall them on loading
                self._all_set_attributes_to_recall_natives(data, array,
                                                           HDF5StorageService.DATA_PREFIX)
            setattr(array._v_attrs, HDF5StorageService.STORAGE_TYPE,
                    HDF5StorageService.ARRAY)
            self._hdf5file.flush()
        except:
            self._logger.error('Failed storing array `%s` of `%s`.' % (key, fullname))
            raise
def _prm_write_into_array(self, key, data, group, fullname, **kwargs):
        try:
            if key in group:
                raise ValueError(
                    'Array `%s` already exists in `%s`. Appending is not supported (yet).')

            try:

                array = self._hdf5file.create_array(where=group,
                                              name=key, obj=data, **kwargs)
            except (TypeError, ValueError) as exc:
                try:
                    if type(data) is dict and len(data) == 0:
                        # We cannot store an empty dictionary,
                        # but we can use an empty tuple as a dummy.
                        conv_data = ()
                    elif isinstance(data, str):
                        conv_data = data.encode(self._encoding)
                    elif isinstance(data, int):
                        conv_data = np.int64(data)
                    else:
                        conv_data = []
                        for string in data:
                            conv_data.append(string.encode(self._encoding))
                    array = self._hdf5file.create_array(where=group,
                                                  name=key, obj=conv_data, **kwargs)
                except Exception:
                    # Re-raise original error
                    raise exc

            if data is not None:
                # Remember the types of the original data to recall them on loading
                self._all_set_attributes_to_recall_natives(data, array,
                                                           HDF5StorageService.DATA_PREFIX)
            setattr(array._v_attrs, HDF5StorageService.STORAGE_TYPE,
                    HDF5StorageService.ARRAY)
            self._hdf5file.flush()
        except:
            self._logger.error('Failed storing array `%s` of `%s`.' % (key, fullname))
            raise
def _prm_write_into_array ( self , key , data , group , fullname , * * kwargs ) : try : if key in group : raise ValueError ( 'Array `%s` already exists in `%s`. Appending is not supported (yet).' ) try : array = self . _hdf5file . create_array ( where = group , name = key , obj = data , * * kwargs ) except ( TypeError , ValueError ) as exc : try : if type ( data ) is dict and len ( data ) == 0 : # We cannot store an empty dictionary, # but we can use an empty tuple as a dummy. conv_data = ( ) elif isinstance ( data , str ) : conv_data = data . encode ( self . _encoding ) elif isinstance ( data , int ) : conv_data = np . int64 ( data ) else : conv_data = [ ] for string in data : conv_data . append ( string . encode ( self . _encoding ) ) array = self . _hdf5file . create_array ( where = group , name = key , obj = conv_data , * * kwargs ) except Exception : # Re-raise original error raise exc if data is not None : # Remember the types of the original data to recall them on loading self . _all_set_attributes_to_recall_natives ( data , array , HDF5StorageService . DATA_PREFIX ) setattr ( array . _v_attrs , HDF5StorageService . STORAGE_TYPE , HDF5StorageService . ARRAY ) self . _hdf5file . flush ( ) except : self . _logger . error ( 'Failed storing array `%s` of `%s`.' % ( key , fullname ) ) raise
Stores data as array.

        :param key:

            Name of data item to store

        :param data:

            Data to store

        :param group:

            Group node where to store data in hdf5 file

        :param fullname:

            Full name of the `data_to_store`s original container, only needed for throwing errors.

        :param recall:

            If container type and data type for perfect recall should be stored
Stores data as array .