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xrtm-eval v0.3.2

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The Judge for XRTM.

xrtm-eval is the scoring engine for probabilistic forecasts. It measures calibration, accuracy, and resolution using strict scoring rules.

Installation

pip install xrtm-eval

Scoring Metrics

Metric Class Description
Brier Score BrierScoreEvaluator Mean squared error (p - o)^2. Murphy decomposition into reliability/resolution/uncertainty.
ECE ExpectedCalibrationErrorEvaluator Expected Calibration Error via reliability binning.
Log Score LogScoreEvaluator Negative log-likelihood with epsilon clamping.
Dashboard summarize_binary_forecasts() Aggregate Brier, ECE, LogScore + calibration curve in one call.

Usage

from xrtm.eval import BrierScoreEvaluator, summarize_binary_forecasts

# Single forecast


evaluator = BrierScoreEvaluator()
score = evaluator.score(probability=0.7, ground_truth="yes")

# Batch evaluation
predictions = [(0.7, "yes"), (0.3, "no"), (0.9, "yes")]
summary = summarize_binary_forecasts(predictions)
print(f"Brier: {summary['brier_score']:.4f}")
print(f"ECE:   {summary['ece']:.4f}")

License

Apache 2.0

Metadata

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