package datascience

import "sort"

// MetricsDrift calculates the relative drift of a current measurement against
// a historical baseline computed at the given percentile.
//
// historical is a window of past measurements (e.g. duration_ms, bytes).
// percentile selects the baseline: 0.5 = median, 0.95 = p95.
// drift = (current - baseline) / baseline, e.g. 0.47 means +47% above baseline.
//
// Returns drift=0, baseline=0 when historical is empty or baseline is zero.
func MetricsDrift(historical []int64, current int64, percentile float64) (drift float64, baseline int64) {
	if len(historical) == 0 {
		return 0, 0
	}

	sorted := make([]int64, len(historical))
	copy(sorted, historical)
	sort.Slice(sorted, func(i, j int) bool { return sorted[i] < sorted[j] })

	baseline = Percentile(sorted, percentile)
	if baseline == 0 {
		return 0, 0
	}

	drift = float64(current-baseline) / float64(baseline)
	return drift, baseline
}
