Python DataProvider.get_block_id方法代码示例

# 需要导入模块: from grid_control.datasets import DataProvider [as 别名]
# 或者: from grid_control.datasets.DataProvider import get_block_id [as 别名]
	def _check_lumi_filter(self, block, idx_runs, idx_lumi):
		lumi_filter = self._lumi_filter.lookup(block[DataProvider.Nickname], is_selector=False)
		if not lumi_filter:
			return
		if (self._lumi_strict == LumiMode.strict) and ((idx_runs is None) or (idx_lumi is None)):
			raise DatasetError('Strict lumi filter active but ' +
				'dataset %s does not provide lumi information!' % DataProvider.get_block_id(block))
		elif (self._lumi_strict == LumiMode.weak) and (idx_runs is None):
			raise DatasetError('Weak lumi filter active but ' +
				'dataset %s does not provide run information!' % DataProvider.get_block_id(block))

# 需要导入模块: from grid_control.datasets import DataProvider [as 别名]
# 或者: from grid_control.datasets.DataProvider import get_block_id [as 别名]
def create_dbs3_proto_blocks(opts, dataset_blocks):
	for dataset in dataset_blocks:
		missing_info_blocks = []
		dataset_types = set()
		for block in dataset_blocks[dataset]:
			block_dump = {'dataset_conf_list': [], 'files': [], 'file_conf_list': [], 'file_parent_list': []}
			(block_size, block_dataset_types) = create_dbs3_json_files(opts, block, block_dump)
			if len(block_dataset_types) > 1:
				raise Exception('Data and MC files are mixed in block %s' % DataProvider.get_block_id(block))
			elif len(block_dataset_types) == 1:
				yield (block, block_dump, block_size, block_dataset_types.pop())
			else:
				missing_info_blocks.append((block, block_dump, block_size))
			# collect dataset types in this dataset for blocks with missing type information
			dataset_types.update(block_dataset_types)

		if missing_info_blocks:
			if len(dataset_types) > 1:
				raise Exception('Data and MC files are mixed in dataset %s! ' +
					'Unable to determine dataset type for blocks without type info')
			elif len(dataset_types) == 0:
				if not opts.datatype:
					raise Exception('Please supply dataset type via --datatype!')
				dataset_type = opts.datatype
			else:
				dataset_type = dataset_types.pop()
			for (block, block_dump, block_size) in missing_info_blocks:
				yield (block, block_dump, block_size, dataset_type)

# 需要导入模块: from grid_control.datasets import DataProvider [as 别名]
# 或者: from grid_control.datasets.DataProvider import get_block_id [as 别名]
def create_dbs3_json_blocks(opts, dataset_blocks):
	dbs3_proto_block_iter = create_dbs3_proto_blocks(opts, dataset_blocks)
	for (block, block_dump, block_size, dataset_type) in dbs3_proto_block_iter:
		dataset = block[DataProvider.Dataset]
		try:
			primary_dataset, processed_dataset, data_tier = dataset[1:].split('/')
		except Exception:
			raise DatasetError('Dataset name %s is not a valid DBS name!' % dataset)

		# add primary dataset information
		block_dump['primds'] = {'primary_ds_type': dataset_type, 'primary_ds_name': primary_dataset}

		# add dataset information
		block_dump['dataset'] = {
			'dataset': dataset, 'processed_ds_name': processed_dataset, 'data_tier_name': data_tier,
			'physics_group_name': None, 'dataset_access_type': 'VALID',
			'xtcrosssection': None,  # TODO: Add to metadata from FrameWorkJobReport, if possible!
		}

		# add block information
		site_db = SiteDB()
		try:
			origin_site_name = site_db.se_to_cms_name(block[DataProvider.Locations][0])[0]
		except IndexError:
			clear_current_exception()
			origin_site_name = 'UNKNOWN'

		block_dump['block'] = {'block_name': DataProvider.get_block_id(block), 'block_size': block_size,
			'file_count': len(block[DataProvider.FileList]), 'origin_site_name': origin_site_name}
		if opts.do_close_blocks:
			block_dump['block']['open_for_writing'] = 0
		else:
			block_dump['block']['open_for_writing'] = 1

		# add acquisition_era, CRAB is important because of checks within DBS 3
		block_dump['acquisition_era'] = {'acquisition_era_name': 'CRAB', 'start_date': 0}
		# add processing_era
		block_dump['processing_era'] = {'processing_version': 1, 'description': 'grid-control'}

		yield validate_dbs3_json('blockBulk', block_dump)

# 需要导入模块: from grid_control.datasets import DataProvider [as 别名]
# 或者: from grid_control.datasets.DataProvider import get_block_id [as 别名]
	def _get_fi_class(self, fi, block):
		run_range = self._run_range.lookup(DataProvider.get_block_id(block))
		metadata_idx = block[DataProvider.Metadata].index('Runs')
		return tuple(imap(lambda r: int(r / run_range), fi[DataProvider.Metadata][metadata_idx]))