示例#1
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 def load_burst_configuration_from_folder(simulator_folder, project):
     bc_h5_filename = DirLoader(
         simulator_folder,
         None).find_file_for_has_traits_type(BurstConfiguration)
     burst_config = BurstConfiguration(project.id)
     with BurstConfigurationH5(
             os.path.join(simulator_folder, bc_h5_filename)) as bc_h5:
         bc_h5.load_into(burst_config)
     return burst_config
示例#2
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    def load_datatype_from_file(self,
                                current_file,
                                op_id,
                                datatype_group=None,
                                current_project_id=None):
        # type: (str, int, DataTypeGroup, int) -> HasTraitsIndex
        """
        Creates an instance of datatype from storage / H5 file 
        :returns: DatatypeIndex
        """
        self.logger.debug("Loading DataType from file: %s" % current_file)
        h5_class = H5File.h5_class_from_file(current_file)

        if h5_class is BurstConfigurationH5:
            if current_project_id is None:
                op_entity = dao.get_operationgroup_by_id(op_id)
                current_project_id = op_entity.fk_launched_in
            h5_file = BurstConfigurationH5(current_file)
            burst = BurstConfiguration(current_project_id)
            burst.fk_simulation = op_id
            h5_file.load_into(burst)
            result = burst
        else:
            datatype, generic_attributes = h5.load_with_links(current_file)
            index_class = h5.REGISTRY.get_index_for_datatype(
                datatype.__class__)
            datatype_index = index_class()
            datatype_index.fill_from_has_traits(datatype)
            datatype_index.fill_from_generic_attributes(generic_attributes)

            # Add all the required attributes
            if datatype_group:
                datatype_index.fk_datatype_group = datatype_group.id
                if len(datatype_group.subject) == 0:
                    datatype_group.subject = datatype_index.subject
                    dao.store_entity(datatype_group)
            datatype_index.fk_from_operation = op_id

            associated_file = h5.path_for_stored_index(datatype_index)
            if os.path.exists(associated_file):
                datatype_index.disk_size = FilesHelper.compute_size_on_disk(
                    associated_file)
            result = datatype_index

        return result
示例#3
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 def store_burst_configuration(self, burst_config, storage_path):
     bc_path = h5.path_for(storage_path, BurstConfigurationH5, burst_config.gid)
     with BurstConfigurationH5(bc_path) as bc_h5:
         bc_h5.store(burst_config)
示例#4
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 def store_burst_configuration(burst_config):
     project = dao.get_project_by_id(burst_config.fk_project)
     bc_path = h5.path_for(burst_config.fk_simulation, BurstConfigurationH5,
                           burst_config.gid, project.name)
     with BurstConfigurationH5(bc_path) as bc_h5:
         bc_h5.store(burst_config)
示例#5
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    def load_datatype_from_file(self,
                                current_file,
                                op_id,
                                datatype_group=None,
                                current_project_id=None):
        # type: (str, int, DataTypeGroup, int) -> HasTraitsIndex
        """
        Creates an instance of datatype from storage / H5 file
        :returns: DatatypeIndex
        """
        self.logger.debug("Loading DataType from file: %s" % current_file)
        h5_class = H5File.h5_class_from_file(current_file)

        if h5_class is BurstConfigurationH5:
            if current_project_id is None:
                op_entity = dao.get_operationgroup_by_id(op_id)
                current_project_id = op_entity.fk_launched_in
            h5_file = BurstConfigurationH5(current_file)
            burst = BurstConfiguration(current_project_id)
            burst.fk_simulation = op_id
            h5_file.load_into(burst)
            result = burst
        else:
            datatype, generic_attributes = h5.load_with_links(current_file)

            already_existing_datatype = h5.load_entity_by_gid(datatype.gid)
            if datatype_group is not None and already_existing_datatype is not None:
                raise DatatypeGroupImportException(
                    "The datatype group that you are trying to import"
                    " already exists!")
            index_class = h5.REGISTRY.get_index_for_datatype(
                datatype.__class__)
            datatype_index = index_class()
            datatype_index.fill_from_has_traits(datatype)
            datatype_index.fill_from_generic_attributes(generic_attributes)

            if datatype_group is not None and hasattr(datatype_index, 'fk_source_gid') and \
                    datatype_index.fk_source_gid is not None:
                ts = h5.load_entity_by_gid(datatype_index.fk_source_gid)

                if ts is None:
                    op = dao.get_operations_in_group(
                        datatype_group.fk_operation_group,
                        only_first_operation=True)
                    op.fk_operation_group = None
                    dao.store_entity(op)
                    dao.remove_entity(OperationGroup,
                                      datatype_group.fk_operation_group)
                    dao.remove_entity(DataTypeGroup, datatype_group.id)
                    raise DatatypeGroupImportException(
                        "Please import the time series group before importing the"
                        " datatype measure group!")

            # Add all the required attributes
            if datatype_group:
                datatype_index.fk_datatype_group = datatype_group.id
                if len(datatype_group.subject) == 0:
                    datatype_group.subject = datatype_index.subject
                    dao.store_entity(datatype_group)
            datatype_index.fk_from_operation = op_id

            associated_file = h5.path_for_stored_index(datatype_index)
            if os.path.exists(associated_file):
                datatype_index.disk_size = StorageInterface.compute_size_on_disk(
                    associated_file)
            result = datatype_index

        return result