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Fix bucket_prob: bounded ranges now use proper Gaussian CDF (was returning 0 for all finite ranges)

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John Doe
2026-04-18 17:23:15 +08:00
parent 030c25224c
commit 1698f09ad0
1 changed files with 8 additions and 1 deletions
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bot_v3.py
+8 -1
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@@ -81,11 +81,18 @@ def norm_cdf(x):
return 0.5 * (1.0 + math.erf(x / math.sqrt(2.0)))
def bucket_prob(forecast, t_low, t_high, sigma=2.0):
"""
Gaussian probability that forecast falls in [t_low, t_high].
Uses error function (math.erf) — no scipy needed.
"""
if t_low == -999:
return norm_cdf((t_high - float(forecast)) / sigma)
if t_high == 999:
return 1.0 - norm_cdf((t_low - float(forecast)) / sigma)
return 1.0 if in_bucket(forecast, t_low, t_high) else 0.0
# Bounded range: P(t_low <= X <= t_high) = CDF(t_high) - CDF(t_low)
z_low = (t_low - float(forecast)) / sigma
z_high = (t_high - float(forecast)) / sigma
return norm_cdf(z_high) - norm_cdf(z_low)
def calc_ev(p, price):
if price <= 0 or price >= 1: return 0.0