124 lines
4.1 KiB
Python
124 lines
4.1 KiB
Python
from math import sqrt
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# TRENDING_WINDOW is the number of blocks in ~6hr period (21600 seconds / 161 seconds per block)
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TRENDING_WINDOW = 134
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# TRENDING_DATA_POINTS says how many samples to use for the trending algorithm
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# i.e. only consider claims from the most recent (TRENDING_WINDOW * TRENDING_DATA_POINTS) blocks
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TRENDING_DATA_POINTS = 28
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CREATE_TREND_TABLE = """
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create table if not exists trend (
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claim_hash bytes not null,
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height integer not null,
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amount integer not null,
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primary key (claim_hash, height)
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) without rowid;
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"""
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class ZScore:
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__slots__ = 'count', 'total', 'power', 'last'
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def __init__(self):
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self.count = 0
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self.total = 0
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self.power = 0
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self.last = None
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def step(self, value):
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if self.last is not None:
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self.count += 1
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self.total += self.last
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self.power += self.last ** 2
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self.last = value
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@property
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def mean(self):
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return self.total / self.count
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@property
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def standard_deviation(self):
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value = (self.power / self.count) - self.mean ** 2
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return sqrt(value) if value > 0 else 0
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def finalize(self):
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if self.count == 0:
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return self.last
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return (self.last - self.mean) / (self.standard_deviation or 1)
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@classmethod
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def factory(cls):
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return cls(), cls.step, cls.finalize
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def install(connection):
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connection.createaggregatefunction("zscore", ZScore.factory, 1)
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connection.cursor().execute(CREATE_TREND_TABLE)
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def run(db, height, final_height, affected_claims):
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# don't start tracking until we're at the end of initial sync
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if height < (final_height - (TRENDING_WINDOW * TRENDING_DATA_POINTS)):
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return
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if height % TRENDING_WINDOW != 0:
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return
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db.execute(f"""
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DELETE FROM trend WHERE height < {height - (TRENDING_WINDOW * TRENDING_DATA_POINTS)}
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""")
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start = (height - TRENDING_WINDOW) + 1
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db.execute(f"""
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INSERT OR IGNORE INTO trend (claim_hash, height, amount)
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SELECT claim_hash, {start}, COALESCE(
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(SELECT SUM(amount) FROM support WHERE claim_hash=claim.claim_hash
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AND height >= {start}), 0
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) AS support_sum
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FROM claim WHERE support_sum > 0
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""")
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zscore = ZScore()
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for global_sum in db.execute("SELECT AVG(amount) AS avg_amount FROM trend GROUP BY height"):
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zscore.step(global_sum.avg_amount)
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global_mean, global_deviation = 0, 1
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if zscore.count > 0:
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global_mean = zscore.mean
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global_deviation = zscore.standard_deviation
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db.execute(f"""
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UPDATE claim SET
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trending_local = COALESCE((
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SELECT zscore(amount) FROM trend
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WHERE claim_hash=claim.claim_hash ORDER BY height DESC
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), 0),
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trending_global = COALESCE((
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SELECT (amount - {global_mean}) / {global_deviation} FROM trend
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WHERE claim_hash=claim.claim_hash AND height = {start}
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), 0),
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trending_group = 0,
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trending_mixed = 0
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""")
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# trending_group and trending_mixed determine how trending will show in query results
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# normally the SQL will be: "ORDER BY trending_group, trending_mixed"
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# changing the trending_group will have significant impact on trending results
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# changing the value used for trending_mixed will only impact trending within a trending_group
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db.execute(f"""
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UPDATE claim SET
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trending_group = CASE
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WHEN trending_local > 0 AND trending_global > 0 THEN 4
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WHEN trending_local <= 0 AND trending_global > 0 THEN 3
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WHEN trending_local > 0 AND trending_global <= 0 THEN 2
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WHEN trending_local <= 0 AND trending_global <= 0 THEN 1
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END,
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trending_mixed = CASE
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WHEN trending_local > 0 AND trending_global > 0 THEN trending_global
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WHEN trending_local <= 0 AND trending_global > 0 THEN trending_local
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WHEN trending_local > 0 AND trending_global <= 0 THEN trending_local
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WHEN trending_local <= 0 AND trending_global <= 0 THEN trending_global
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END
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WHERE trending_local <> 0 OR trending_global <> 0
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""")
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