refactor: remove deprecated internal stats package

1 files changed, 0 insertions, 142 deletions

diff --git a/internal/stats/patterns.go b/internal/stats/patterns.go
deleted file mode 100644
index 06e906f..0000000
--- a/internal/stats/patterns.go
+++ /dev/null
@@ -1,142 +0,0 @@
-package stats
-
-import (
-	"math"
-	"time"
-)
-
-// PatternAnalysis represents the analysis of I/O patterns
-type PatternAnalysis struct {
-	// Burst detection
-	BurstCount     int
-	BurstDuration  time.Duration
-	BurstThreshold int64
-
-	// Periodicity detection
-	IsPeriodic     bool
-	PeriodDuration time.Duration
-
-	// Trend analysis
-	TrendSlope     float64
-	TrendDirection string // "increasing", "decreasing", "stable"
-}
-
-// AnalyzePatterns analyzes the I/O patterns from the statistics
-func (s *IOStats) AnalyzePatterns() *PatternAnalysis {
-	s.mu.RLock()
-	defer s.mu.RUnlock()
-
-	analysis := &PatternAnalysis{
-		BurstThreshold: 1000, // Configurable threshold
-	}
-
-	// Analyze bursts
-	analysis.analyzeBursts(s.bytesHistory, s.timestamps)
-
-	// Analyze periodicity
-	analysis.analyzePeriodicity(s.bytesHistory, s.timestamps)
-
-	// Analyze trends
-	analysis.analyzeTrend(s.bytesHistory, s.timestamps)
-
-	return analysis
-}
-
-func (a *PatternAnalysis) analyzeBursts(bytes []int64, timestamps []time.Time) {
-	if len(bytes) < 2 {
-		return
-	}
-
-	var currentBurstSize int64
-	var burstStart time.Time
-	inBurst := false
-
-	for i := 0; i < len(bytes); i++ {
-		if bytes[i] > a.BurstThreshold {
-			if !inBurst {
-				burstStart = timestamps[i]
-				inBurst = true
-			}
-			currentBurstSize += bytes[i]
-		} else if inBurst {
-			a.BurstCount++
-			a.BurstDuration += timestamps[i].Sub(burstStart)
-			inBurst = false
-			currentBurstSize = 0
-		}
-	}
-}
-
-func (a *PatternAnalysis) analyzePeriodicity(bytes []int64, timestamps []time.Time) {
-	if len(bytes) < 4 {
-		return
-	}
-
-	// Simple periodicity detection using autocorrelation
-	mean := 0.0
-	for _, b := range bytes {
-		mean += float64(b)
-	}
-	mean /= float64(len(bytes))
-
-	var maxCorrelation float64
-	var bestPeriod int
-
-	// Check for periods up to half the data length
-	for period := 1; period < len(bytes)/2; period++ {
-		correlation := 0.0
-		count := 0
-
-		for i := 0; i < len(bytes)-period; i++ {
-			correlation += (float64(bytes[i]) - mean) * (float64(bytes[i+period]) - mean)
-			count++
-		}
-
-		if count > 0 {
-			correlation /= float64(count)
-			if correlation > maxCorrelation {
-				maxCorrelation = correlation
-				bestPeriod = period
-			}
-		}
-	}
-
-	// If we found a strong correlation, consider it periodic
-	if maxCorrelation > 0.7 { // Threshold for periodicity
-		a.IsPeriodic = true
-		if bestPeriod > 0 && bestPeriod < len(timestamps)-1 {
-			a.PeriodDuration = timestamps[bestPeriod].Sub(timestamps[0])
-		}
-	}
-}
-
-func (a *PatternAnalysis) analyzeTrend(bytes []int64, timestamps []time.Time) {
-	if len(bytes) < 2 {
-		return
-	}
-
-	// Simple linear regression
-	var sumX, sumY, sumXY, sumX2 float64
-	n := float64(len(bytes))
-
-	for i := 0; i < len(bytes); i++ {
-		x := float64(timestamps[i].UnixNano())
-		y := float64(bytes[i])
-		sumX += x
-		sumY += y
-		sumXY += x * y
-		sumX2 += x * x
-	}
-
-	// Calculate slope
-	a.TrendSlope = (n*sumXY - sumX*sumY) / (n*sumX2 - sumX*sumX)
-
-	// Determine trend direction
-	if math.Abs(a.TrendSlope) < 0.1 {
-		a.TrendDirection = "stable"
-	} else if a.TrendSlope > 0 {
-		a.TrendDirection = "increasing"
-	} else {
-		a.TrendDirection = "decreasing"
-	}
-}