2019-05-19 21:57:39 +02:00
|
|
|
from math import sqrt
|
|
|
|
|
2019-10-11 16:51:36 +02:00
|
|
|
# TRENDING_WINDOW is the number of blocks in ~6hr period (21600 seconds / 161 seconds per block)
|
|
|
|
TRENDING_WINDOW = 134
|
|
|
|
|
|
|
|
# TRENDING_DATA_POINTS says how many samples to use for the trending algorithm
|
|
|
|
# i.e. only consider claims from the most recent (TRENDING_WINDOW * TRENDING_DATA_POINTS) blocks
|
2019-10-31 17:33:27 +01:00
|
|
|
TRENDING_DATA_POINTS = 28
|
2019-05-19 21:57:39 +02:00
|
|
|
|
|
|
|
CREATE_TREND_TABLE = """
|
|
|
|
create table if not exists trend (
|
|
|
|
claim_hash bytes not null,
|
|
|
|
height integer not null,
|
|
|
|
amount integer not null,
|
|
|
|
primary key (claim_hash, height)
|
|
|
|
) without rowid;
|
|
|
|
"""
|
|
|
|
|
|
|
|
|
|
|
|
class ZScore:
|
|
|
|
__slots__ = 'count', 'total', 'power', 'last'
|
|
|
|
|
|
|
|
def __init__(self):
|
|
|
|
self.count = 0
|
|
|
|
self.total = 0
|
|
|
|
self.power = 0
|
|
|
|
self.last = None
|
|
|
|
|
|
|
|
def step(self, value):
|
|
|
|
if self.last is not None:
|
|
|
|
self.count += 1
|
|
|
|
self.total += self.last
|
2019-10-11 16:51:36 +02:00
|
|
|
self.power += self.last ** 2
|
2019-05-19 21:57:39 +02:00
|
|
|
self.last = value
|
|
|
|
|
|
|
|
@property
|
|
|
|
def mean(self):
|
|
|
|
return self.total / self.count
|
|
|
|
|
|
|
|
@property
|
|
|
|
def standard_deviation(self):
|
2019-11-24 06:38:42 +01:00
|
|
|
value = (self.power / self.count) - self.mean ** 2
|
|
|
|
return sqrt(value) if value > 0 else 0
|
2019-05-19 21:57:39 +02:00
|
|
|
|
|
|
|
def finalize(self):
|
|
|
|
if self.count == 0:
|
|
|
|
return self.last
|
|
|
|
return (self.last - self.mean) / (self.standard_deviation or 1)
|
|
|
|
|
|
|
|
|
2020-01-28 21:53:57 +01:00
|
|
|
def install(connection):
|
2021-06-15 21:05:53 +02:00
|
|
|
connection.create_aggregate("zscore", 1, ZScore)
|
|
|
|
connection.executescript(CREATE_TREND_TABLE)
|
2019-05-19 21:57:39 +02:00
|
|
|
|
|
|
|
|
2020-01-28 21:53:57 +01:00
|
|
|
def run(db, height, final_height, affected_claims):
|
2019-05-20 02:22:25 +02:00
|
|
|
# don't start tracking until we're at the end of initial sync
|
2019-10-11 16:51:36 +02:00
|
|
|
if height < (final_height - (TRENDING_WINDOW * TRENDING_DATA_POINTS)):
|
2019-05-20 02:22:25 +02:00
|
|
|
return
|
|
|
|
|
2019-05-19 21:57:39 +02:00
|
|
|
if height % TRENDING_WINDOW != 0:
|
|
|
|
return
|
|
|
|
|
|
|
|
db.execute(f"""
|
2019-10-11 16:51:36 +02:00
|
|
|
DELETE FROM trend WHERE height < {height - (TRENDING_WINDOW * TRENDING_DATA_POINTS)}
|
2019-05-19 21:57:39 +02:00
|
|
|
""")
|
|
|
|
|
2019-10-11 16:51:36 +02:00
|
|
|
start = (height - TRENDING_WINDOW) + 1
|
2019-05-19 21:57:39 +02:00
|
|
|
db.execute(f"""
|
2019-06-28 22:02:54 +02:00
|
|
|
INSERT OR IGNORE INTO trend (claim_hash, height, amount)
|
2019-05-19 21:57:39 +02:00
|
|
|
SELECT claim_hash, {start}, COALESCE(
|
|
|
|
(SELECT SUM(amount) FROM support WHERE claim_hash=claim.claim_hash
|
|
|
|
AND height >= {start}), 0
|
|
|
|
) AS support_sum
|
|
|
|
FROM claim WHERE support_sum > 0
|
|
|
|
""")
|
|
|
|
|
|
|
|
zscore = ZScore()
|
2019-12-08 00:13:13 +01:00
|
|
|
for global_sum in db.execute("SELECT AVG(amount) AS avg_amount FROM trend GROUP BY height"):
|
|
|
|
zscore.step(global_sum.avg_amount)
|
2019-05-19 21:57:39 +02:00
|
|
|
global_mean, global_deviation = 0, 1
|
|
|
|
if zscore.count > 0:
|
|
|
|
global_mean = zscore.mean
|
|
|
|
global_deviation = zscore.standard_deviation
|
|
|
|
|
|
|
|
db.execute(f"""
|
|
|
|
UPDATE claim SET
|
|
|
|
trending_local = COALESCE((
|
|
|
|
SELECT zscore(amount) FROM trend
|
|
|
|
WHERE claim_hash=claim.claim_hash ORDER BY height DESC
|
|
|
|
), 0),
|
|
|
|
trending_global = COALESCE((
|
|
|
|
SELECT (amount - {global_mean}) / {global_deviation} FROM trend
|
|
|
|
WHERE claim_hash=claim.claim_hash AND height = {start}
|
|
|
|
), 0),
|
|
|
|
trending_group = 0,
|
|
|
|
trending_mixed = 0
|
|
|
|
""")
|
|
|
|
|
|
|
|
# trending_group and trending_mixed determine how trending will show in query results
|
|
|
|
# normally the SQL will be: "ORDER BY trending_group, trending_mixed"
|
|
|
|
# changing the trending_group will have significant impact on trending results
|
|
|
|
# changing the value used for trending_mixed will only impact trending within a trending_group
|
|
|
|
db.execute(f"""
|
|
|
|
UPDATE claim SET
|
|
|
|
trending_group = CASE
|
|
|
|
WHEN trending_local > 0 AND trending_global > 0 THEN 4
|
|
|
|
WHEN trending_local <= 0 AND trending_global > 0 THEN 3
|
|
|
|
WHEN trending_local > 0 AND trending_global <= 0 THEN 2
|
|
|
|
WHEN trending_local <= 0 AND trending_global <= 0 THEN 1
|
|
|
|
END,
|
|
|
|
trending_mixed = CASE
|
|
|
|
WHEN trending_local > 0 AND trending_global > 0 THEN trending_global
|
|
|
|
WHEN trending_local <= 0 AND trending_global > 0 THEN trending_local
|
|
|
|
WHEN trending_local > 0 AND trending_global <= 0 THEN trending_local
|
|
|
|
WHEN trending_local <= 0 AND trending_global <= 0 THEN trending_global
|
|
|
|
END
|
|
|
|
WHERE trending_local <> 0 OR trending_global <> 0
|
|
|
|
""")
|