def _preparePreScanSnapshot(self, env):
'''Extract pre-scan snapshot, filters elements of shape different
than scalar and split labels and values into chunks of 8 items.
:param: env (dict) scan environment
:return: labels, values (tuple<list,list>)
labels - list of chunks with 8 elements containing labels
values - list of chunks with 8 elements containing values
'''
# preScanSnapShot is a list o ColumnDesc objects
pre_scan_snapshot = env.get('preScanSnapShot',[])
labels = []; values = []
for column_desc in pre_scan_snapshot:
shape = column_desc.shape # shape is a tuple of dimensions
label = column_desc.label
dtype = column_desc.dtype
pre_scan_value = column_desc.pre_scan_value
# skip items with shape different than scalar
if len(shape) > 0:
self.info('Pre-scan snapshot of "%s" will not be stored.' + \
' Reason: value is non-scalar', label)
continue
if dtype not in self.supported_dtypes:
self.info('Pre-scan snapshot of "%s" will not be stored.' + \
' Reason: type %s not supported', label, dtype)
continue
labels.append(label)
values.append(pre_scan_value)
# split labels in chunks o 8 items
labels_chunks = list(chunks(labels, 8))
values_chunks = list(chunks(values, 8))
return labels_chunks, values_chunks
def _preparePreScanSnapshot(self, env):
'''Extract pre-scan snapshot, filters elements of shape different
than scalar and split labels and values into chunks of 8 items.
:param: env (dict) scan environment
:return: labels, values (tuple<list,list>)
labels - list of chunks with 8 elements containing labels
values - list of chunks with 8 elements containing values
'''
# preScanSnapShot is a list o ColumnDesc objects
pre_scan_snapshot = env.get('preScanSnapShot',[])
labels = []; values = []
for column_desc in pre_scan_snapshot:
shape = column_desc.shape # shape is a tuple of dimensions
label = column_desc.label
dtype = column_desc.dtype
pre_scan_value = column_desc.pre_scan_value
# skip items with shape different than scalar
if len(shape) > 0:
self.info('Pre-scan snapshot of "%s" will not be stored.' + \
' Reason: value is non-scalar', label)
continue
if dtype not in self.supported_dtypes:
self.info('Pre-scan snapshot of "%s" will not be stored.' + \
' Reason: type %s not supported', label, dtype)
continue
labels.append(label)
values.append(pre_scan_value)
# split labels in chunks o 8 items
labels_chunks = list(chunks(labels, 8))
values_chunks = list(chunks(values, 8))
return labels_chunks, values_chunks