def concatenate(self, listOfPartitions):
testObject = listOfPartitions[0]
# First see if we have a known array type
if is_array(testObject):
return numpy.concatenate(listOfPartitions)
# Next try for Python sequence types
if isinstance(testObject, (list, tuple)):
return utils_flatten(listOfPartitions)
# If we have scalars, just return listOfPartitions
return listOfPartitions
def concatenate(self, listOfPartitions):
testObject = listOfPartitions[0]
# First see if we have a known array type
if is_array(testObject):
return numpy.concatenate(listOfPartitions)
# Next try for Python sequence types
if isinstance(testObject, (list, tuple)):
return utils_flatten(listOfPartitions)
# If we have scalars, just return listOfPartitions
return listOfPartitions
def concatenate(self, listOfPartitions):
testObject = listOfPartitions[0]
# First see if we have a known array type
for m in arrayModules:
#print m
if isinstance(testObject, m['type']):
return m['module'].concatenate(listOfPartitions)
# Next try for Python sequence types
if isinstance(testObject, (types.ListType, types.TupleType)):
return utils_flatten(listOfPartitions)
# If we have scalars, just return listOfPartitions
return listOfPartitions
def concatenate(self, listOfPartitions):
testObject = listOfPartitions[0]
# First see if we have a known array type
for m in arrayModules:
#print m
if isinstance(testObject, m['type']):
return m['module'].concatenate(listOfPartitions)
# Next try for Python sequence types
if isinstance(testObject, (types.ListType, types.TupleType)):
return utils_flatten(listOfPartitions)
# If we have scalars, just return listOfPartitions
return listOfPartitions
