def load_stats():
stats = []
for pub in test_imgsets.keys():
for window in windows:
for region in regions:
for training_set_size in training_set_sizes:
for image_number in test_imgsets[pub]:
stat = load_stat(image_number, pub, window, training_set_size, region)
stats.append(stat)
stat["pub"] = pub
stat["window"] = window
stat["training_set_size"] = training_set_size
stat["image"] = image_number
stat["region"] = region
return stats
def handle_stats(args, channel, user_id):
year, heading = _coerce_year(args, "%s Stats")
stmts = Statement.query.filter(Statement.veracity.isnot(None))
stmts = _maybe_filter_stmts_for_year(stmts, year)
stmts = stmts.order_by(Statement.timestamp).all()
stats = []
getters = _STAT_GETTERS[:]
random.shuffle(getters)
for getter in [_get_count] + getters[:]:
stat = getter(stmts)
if isinstance(stat, (list, tuple)):
stats.extend(stat)
else:
stats.append(stat)
return '{}:{}'.format(heading, ''.join(f'\n- {s}' for s in stats))
def normalizeData(self, data):
# create an empty list
stats = list()
player_ids = data.keys()
for player_id in player_ids:
self.players.append(player_id)
player_data = data[player_id]
if type(player_data) == type({}):
player_data['id'] = self.game_id
player_data['player_id'] = player_id
player_data['year'] = self.year
stats.append(player_data)
return stats
def rank_players(self, pos, stat):
stats = []
playerlst = []
if pos !='DST':
for x in self.players:
if self.players[x]['Position'] == pos:
playerlst.append(x)
for x in playerlst:
stats.append( (x,self.players[x][stat]) )
if stat == 'Overall':
sortedstats = sorted(stats,key=lambda tup: tup[1])
else:
sortedstats = sorted(stats,key=lambda tup: tup[1],reverse=True)
rank = 1
for x in sortedstats:
self.players[x[0]][stat+'rank'] = rank
rank = rank + 1
def get_stat(db, stat, distortions):
stats = []
for d in distortions:
res = np.array(map(float, np.array(db.query("SELECT " + stat + " FROM stats WHERE image LIKE \"" + d + "_76%\"")).flatten()))
stats.append([res.mean(), np.sqrt(res.var()), d])
return np.array(stats)
