def _load(self, load_dict):
for key in list(load_dict.keys()):<EOL><INDENT>if key in load_dict:<EOL><INDENT>if SparseResult.IDENTIFIER in key:<EOL><INDENT>new_key = key.split(SparseResult.IDENTIFIER)[<NUM_LIT:0>]<EOL>is_dia = load_dict.pop(new_key + SparseResult.IDENTIFIER + '<STR_LIT>')<EOL>name_list = SparseParameter._get_name_list(is_dia)<EOL>rename_list = ['<STR_LIT>' % (new_key, SparseResult.IDENTIFIER, name)<EOL>for name in name_list]<EOL>data_list = [load_dict.pop(name) for name in rename_list]<EOL>matrix = SparseParameter._reconstruct_matrix(data_list)<EOL>self._data[new_key] = matrix<EOL><DEDENT>else:<EOL><INDENT>self._data[key] = load_dict[key]<EOL><DEDENT><DEDENT><DEDENT>
Loads data from `load_dict`

        Reconstruction of sparse matrices similar to the :class:`~pypet.parameter.SparseParameter`.