def actions_in_continuous_rank_order(self):
# FIXME: multiplying query order nr by 1M is just a silly hack
return _memoize_attr(
self, '_actions_in_continuous_rank_order', lambda: sorted(
self.actions,
key=lambda action: action.query.order_number() * 1000000 + int(
getattr(action, 'rank', sys.maxsize))))
def gain_events(self, gain_levels):
possible_gain_actions = self.document_marked_relevant_actions()
return _memoize_attr(
self,
'_gain_events',
lambda: [self.create_gain_pair(action, gain_levels) for (idx, action) in possible_gain_actions if action.gain(gain_levels) > 0]
)
def actions_in_continuous_rank_order(self):
# FIXME: multiplying query order nr by 1M is just a silly hack
return _memoize_attr(self, '_actions_in_continuous_rank_order',
lambda: sorted(self.actions,
key=lambda action:
action.query.order_number() * 1000000 + int(getattr(
action, 'rank', sys.maxsize))))
def gain_events(self, gain_levels):
possible_gain_actions = self.document_marked_relevant_actions()
return _memoize_attr(
self, '_gain_events', lambda: [
self.create_gain_pair(action, gain_levels)
for (idx, action) in possible_gain_actions
if action.gain(gain_levels) > 0
])
def get_start_timestamp(self):
# No actions?
if len(self.actions) == 0:
return None
return _memoize_attr(
self,
'_start_timestamp',
lambda: self.actions[0].timestamp
)
def get_relevance_for_topic_id(self, topic_id):
rel = _memoize_attr(
self,
'_relevance_for_topic_id_' + str(topic_id),
lambda: self.relevances.get(str(topic_id))
)
if rel is None:
raise RuntimeError("ERROR: document ID %s, topic ID %s relevance cannot be determined!" % (self.record_id, topic_id))
return rel
def get_start_timestamp(self):
# No actions?
if len(self.actions) == 0:
return None
return _memoize_attr(self, '_start_timestamp',
lambda: self.actions[0].timestamp)
def queries_prior_to(self, test_query):
return _memoize_attr(
self,
'_queries_prior_to_' + str(test_query.record_id),
lambda: self._calculate_queries_prior_to(test_query)
)
def is_moderately_relevant(self):
return _memoize_attr(
self,
'_is_moderately_relevant',
lambda: self.relevance_level == 1
)
def is_highly_relevant(self):
return _memoize_attr(
self,
'_is_highly_relevant',
lambda: self.relevance_level == 2
)
def actions_by_type_before_rank(self, action_type, rank):
return _memoize_attr(
self,
'_actions_by_' + str(action_type) + '_type_before_rank_' + str(rank),
lambda: self._calculate_actions_by_type_before_rank(action_type, rank)
)
def actions_by_type_until(self, action_type, seconds):
return _memoize_attr(
self,
'_actions_by_' + str(action_type) + '_type_until_' + str(seconds),
lambda: self._calculate_actions_by_type_until(action_type, seconds)
)
def rank_of(self, document):
return _memoize_attr(
self,
'_rank_of_' + str(document.record_id),
lambda: self._calculate_rank_of(document)
)
def actions_by_type_until(self, action_type, seconds):
return _memoize_attr(
self,
'_actions_by_' + str(action_type) + '_type_until_' + str(seconds),
lambda: self._calculate_actions_by_type_until(
action_type, seconds))
def sorted_queries(self):
return _memoize_attr(
self,
'_sorted_queries',
lambda: sorted(self.queries.values(), key=lambda q: q.get_start_timestamp())
)
def last_rank_reached(self):
return _memoize_attr(
self,
'_last_rank_reached',
lambda: self._calculate_last_rank_reached()
)
def is_moderately_relevant(self):
return _memoize_attr(self, '_is_moderately_relevant',
lambda: self.relevance_level == 1)
def is_highly_relevant(self):
return _memoize_attr(self, '_is_highly_relevant',
lambda: self.relevance_level == 2)
def seconds_elapsed_at(self, timestamp):
return _memoize_attr(
self, '_seconds_elapsed_at_' + str(timestamp), lambda:
(timestamp - self.get_start_timestamp()).total_seconds())
def seconds_elapsed_at(self, timestamp):
return _memoize_attr(
self,
'_seconds_elapsed_at_' + str(timestamp),
lambda: (timestamp - self.get_start_timestamp()).total_seconds()
)
def actions_by_type_before_rank(self, action_type, rank):
return _memoize_attr(
self, '_actions_by_' + str(action_type) + '_type_before_rank_' +
str(rank), lambda: self._calculate_actions_by_type_before_rank(
action_type, rank))
def highly_relevant_results_up_to_rank(self, rank):
return _memoize_attr(
self,
'_highly_relevant_results_up_to_rank_' + str(rank),
lambda: list(filter(lambda result_document: result_document.is_highly_relevant_for_topic(self.query.topic), self.result_documents[:int(rank)]))
)
