def scoreZValue(self, syncNumber, get):
"""Score one event with a zValue testStatistic (non-Gaussian)."""
value = get(self.field)
if value is INVALID or value is MISSING:
return INVALID
probability = self.baseline.cdf(value)
if probability <= 1e-16:
zValue = -10.
elif probability >= 1. - 1e-16:
zValue = 10.
else:
zValue = math.sqrt(2.) * erfinv(2. * probability - 1.)
pValue = 1. - 2. * abs(probability - 0.5)
return {SCORE_predictedValue: zValue, SCORE_pValue: pValue}
def scoreZValue(self, syncNumber, get):
"""Score one event with a zValue testStatistic (non-Gaussian)."""
value = get(self.field)
if value is INVALID or value is MISSING:
return INVALID
probability = self.baseline.cdf(value)
if probability <= 1e-16:
zValue = -10.0
elif probability >= 1.0 - 1e-16:
zValue = 10.0
else:
zValue = math.sqrt(2.0) * erfinv(2.0 * probability - 1.0)
pValue = 1.0 - 2.0 * abs(probability - 0.5)
return {SCORE_predictedValue: zValue, SCORE_pValue: pValue}
def scoreZValue(self, syncNumber, get):
"""Score one event with a zValue testStatistic (non-Gaussian)."""
self.resetLoggerLevels()
value = get(self.field)
if value is INVALID or value is MISSING:
self.lastScore = INVALID
self.logger.debug("scoreZValue: returning INVALID score")
return self.lastScore
probability = self.baseline.cdf(value)
if probability <= 1e-16:
zValue = -10.
elif probability >= 1. - 1e-16:
zValue = 10.
else:
zValue = math.sqrt(2.)*erfinv(2.*probability - 1.)
pValue = 1. - 2.*abs(probability - 0.5)
self.lastScore = {SCORE_predictedValue: zValue, SCORE_pValue: pValue}
return self.lastScore
def scoreZValue(self, syncNumber, get):
"""Score one event with a zValue testStatistic (non-Gaussian)."""
self.resetLoggerLevels()
value = get(self.field)
if value is INVALID or value is MISSING:
self.lastScore = INVALID
self.logger.debug("scoreZValue: returning INVALID score")
return self.lastScore
probability = self.baseline.cdf(value)
if probability <= 1e-16:
zValue = -10.
elif probability >= 1. - 1e-16:
zValue = 10.
else:
zValue = math.sqrt(2.)*erfinv(2.*probability - 1.)
pValue = 1. - 2.*abs(probability - 0.5)
self.lastScore = {SCORE_predictedValue: zValue, SCORE_pValue: pValue}
return self.lastScore
