def usage_feature(d: int) -> Iterator[Tuple[str, List[float]]]:
"""Computes usage difference between day d and each of the previous 6 days (features 14-19).
Usage is defined as the ratio between the number of times it appears in every deck and the total of cards
that appears in every deck.
Simple stats: only about 1000 different cards are played in tournaments
"""
card_id_to_usages = defaultdict(list)
# Gets all cards that have been played for two weeks.
all_cards = set(
Tournament.get_played_cards(date.today() - timedelta(days=d),
date.today() - timedelta(days=d + 13)))
for i in range(7):
played_cards = Tournament.get_played_cards(
date.today() - timedelta(days=d + i),
date.today() - timedelta(days=d + i + 6))
total = sum(played_cards.values())
for card_name in all_cards:
usage = played_cards.get(card_name, 0) / total
for card in Card.objects.filter(name=card_name):
card_id_to_usages[card.id].append(usage)
for card_id, usages in card_id_to_usages.items():
if len(usages) > 1:
yield card_id, [usages[0] - usage for usage in usages[1:]]
else:
yield card_id, usages
def compute_statistics() -> None:
"""Compute all the statistics for every relevant cards.
This step needs to be done after all steps have finished.
"""
logger.info('Computing cards statistics')
class Classifier:
# TODO: implement me :'(
@staticmethod
def predict(_):
return 0
for card in Card.objects.filter(is_relevant=True):
logger.debug('Predicting price for card {}...'.format(card))
features = Features.objects.get(card=card, date=date.today())
predicted_price = Classifier.predict(features.features)
logger.debug('Computing price ratio for card {}...'.format(card))
current_prices = Price.objects.filter(card=card, date=date.today())
price_ratio = predicted_price / current_prices.mean_price
logger.debug('Computing playing ratio for card {}...'.format(card))
played_cards = Tournament.get_played_cards(
date.today(),
date.today() - timedelta(days=Statistics.PLAYING_WINDOW))
playing_ratio = played_cards[card.name.name] / sum(
played_cards.values())
statistics, created = Statistics.objects.get_or_create(
card=card,
date=date.today(),
defaults={
'predicted_price': predicted_price,
'price_ratio': price_ratio,
'playing_ratio': playing_ratio
})
if created:
logger.debug('Created statistics {}'.format(statistics))
