From 0fa8c75fc04504762adbceb615711f7f77d1c603 Mon Sep 17 00:00:00 2001 From: Thomas Dougherty Date: Mon, 24 Feb 2025 18:49:43 +0000 Subject: [PATCH] Updating stats metrics for weighting on tstat --- vali_objects/utils/metrics.py | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/vali_objects/utils/metrics.py b/vali_objects/utils/metrics.py index dacf42e9..c955e85a 100644 --- a/vali_objects/utils/metrics.py +++ b/vali_objects/utils/metrics.py @@ -242,7 +242,7 @@ def omega(log_returns: list[float], bypass_confidence: bool = False, weighting: return float(numerator / denominator) @staticmethod - def statistical_confidence(log_returns: list[float], bypass_confidence: bool = False, weighting: bool = False, **kwargs) -> float: + def statistical_confidence(log_returns: list[float], bypass_confidence: bool = False, **kwargs) -> float: """ Args: log_returns: list of daily log returns from the miner @@ -254,10 +254,6 @@ def statistical_confidence(log_returns: list[float], bypass_confidence: bool = F if not bypass_confidence or len(log_returns) < 2: return ValiConfig.STATISTICAL_CONFIDENCE_NOCONFIDENCE_VALUE - if weighting: - # Weighted distribution - log_returns = Metrics.weighted_log_returns(log_returns) - # Also now check for zero variance condition zero_variance_condition = bool(np.isclose(np.var(log_returns), 0)) if zero_variance_condition: