add MutCorrelate func, get mutual correlation

p2/run.go

@@ -21,14 +21,14 @@ func run() error {
 
 		defer f.Close()
 
-		u := 0
-		y := 1
-
 		data, err := readData(f)
 		if err != nil {
 			return err
 		}
 
+		u := 0
+		y := 1
+
 		meanU := stats.Mean(data[u])
 		meanY := stats.Mean(data[y])
 		varianceU := stats.Variance(data[u])
@@ -38,6 +38,11 @@ func run() error {
 		autocorrelationU := stats.Autocorrelate(data[u], maxShift)
 		autocorrelationY := stats.Autocorrelate(data[y], maxShift)
 
+		mutCorrelationUY, err := stats.MutCorrelate(data[u], data[y], maxShift)
+		if err != nil {
+			return err
+		}
+
 		log.Printf("len(data): %d", len(data[u]))
 
 		log.Printf("means - u: %v, y: %v", meanU, meanY)
@@ -47,6 +52,7 @@ func run() error {
 		log.Printf("len(autocorrelationU): %d", len(autocorrelationU))
 		log.Printf("autocorrelationU: %v", autocorrelationU)
 		log.Printf("autocorrelationY: %v", autocorrelationY)
+		log.Printf("mutual correlation U,Y: %v", mutCorrelationUY)
 	}
 
 	return nil

p2/stats/stats.go

@@ -1,6 +1,7 @@
 package stats
 
 import (
+	"errors"
 	"math"
 
 	"gonum.org/v1/gonum/stat"
@@ -61,3 +62,30 @@ func AutocorrelateMP(f []float64, maxShift float64) []float64 {
 
 	return v
 }
+
+func MutCorrelate(f1, f2 []float64, maxShift float64) ([]float64, error) {
+	fLen := len(f1)
+	if fLen != len(f2) {
+		return []float64{}, errors.New("arrays passed are of different lengths")
+	}
+
+	m := float64(fLen) * maxShift
+	v := make([]float64, 0, int(m)*4)
+	currentShift := 0
+
+	for m >= float64(currentShift) {
+		var r float64
+
+		for i := 0; i < fLen-currentShift; i++ {
+			r += f1[i] * f2[i+currentShift]
+		}
+
+		r *= 1 / float64(fLen-currentShift)
+
+		v = append(v, r)
+
+		currentShift++
+	}
+
+	return v, nil
+}