def test_weighted_random_choice(self, mock_random):
class _ItemWithWeight(object):
def __init__(self, value, weight):
self.value = value
self.weight = weight
items = [
_ItemWithWeight('abc', 0.1),
_ItemWithWeight('def', 0.3),
_ItemWithWeight('klm', 0.6),
]
mock_random.return_value = 0.05
observed = utils.weighted_random_choice(items)
self.assertEqual('abc', observed.value)
mock_random.return_value = 0.25
observed = utils.weighted_random_choice(items)
self.assertEqual('def', observed.value)
mock_random.return_value = 0.5
observed = utils.weighted_random_choice(items)
self.assertEqual('klm', observed.value)
def produce_task(world, actions):
available_action_items = {} # action -> (items)
for action in actions:
item_types = action.get_depends_on()
world_items = world.filter_items(item_types)
filtered_items = list(action.filter_items(world_items))
if not filtered_items:
continue
# LOG.debug('Available action: %s, item-types: %s, filtered_items: %s',
# action, item_types, filtered_items)
# check that filtered_items contain items of *all* item_types
filtered_item_types = set(i.item_type for i in filtered_items)
if item_types and filtered_item_types != item_types:
continue
available_action_items[action] = filtered_items
if available_action_items:
available_actions = list(available_action_items.keys())
chosen_action = utils.weighted_random_choice(available_actions)
available_items = available_action_items[chosen_action]
# pick one random item per type
items_per_type = collections.defaultdict(list)
for item in available_items:
items_per_type[item.item_type].append(item)
chosen_items = [random.choice(v) for v in items_per_type.values()]
chosen_action.reserve_items(chosen_items)
task = Task(id=utils.make_id(), action=chosen_action,
items=chosen_items)
LOG.info('Produced task: %s', task)
return task
else:
LOG.debug('No actions available')
return None