Adding dep files and dependencies.

vendor/github.com/montanaflynn/stats/regression.go

@@ -0,0 +1,113 @@
+package stats
+
+import "math"
+
+// Series is a container for a series of data
+type Series []Coordinate
+
+// Coordinate holds the data in a series
+type Coordinate struct {
+	X, Y float64
+}
+
+// LinearRegression finds the least squares linear regression on data series
+func LinearRegression(s Series) (regressions Series, err error) {
+
+	if len(s) == 0 {
+		return nil, EmptyInput
+	}
+
+	// Placeholder for the math to be done
+	var sum [5]float64
+
+	// Loop over data keeping index in place
+	i := 0
+	for ; i < len(s); i++ {
+		sum[0] += s[i].X
+		sum[1] += s[i].Y
+		sum[2] += s[i].X * s[i].X
+		sum[3] += s[i].X * s[i].Y
+		sum[4] += s[i].Y * s[i].Y
+	}
+
+	// Find gradient and intercept
+	f := float64(i)
+	gradient := (f*sum[3] - sum[0]*sum[1]) / (f*sum[2] - sum[0]*sum[0])
+	intercept := (sum[1] / f) - (gradient * sum[0] / f)
+
+	// Create the new regression series
+	for j := 0; j < len(s); j++ {
+		regressions = append(regressions, Coordinate{
+			X: s[j].X,
+			Y: s[j].X*gradient + intercept,
+		})
+	}
+
+	return regressions, nil
+
+}
+
+// ExponentialRegression returns an exponential regression on data series
+func ExponentialRegression(s Series) (regressions Series, err error) {
+
+	if len(s) == 0 {
+		return nil, EmptyInput
+	}
+
+	var sum [6]float64
+
+	for i := 0; i < len(s); i++ {
+		sum[0] += s[i].X
+		sum[1] += s[i].Y
+		sum[2] += s[i].X * s[i].X * s[i].Y
+		sum[3] += s[i].Y * math.Log(s[i].Y)
+		sum[4] += s[i].X * s[i].Y * math.Log(s[i].Y)
+		sum[5] += s[i].X * s[i].Y
+	}
+
+	denominator := (sum[1]*sum[2] - sum[5]*sum[5])
+	a := math.Pow(math.E, (sum[2]*sum[3]-sum[5]*sum[4])/denominator)
+	b := (sum[1]*sum[4] - sum[5]*sum[3]) / denominator
+
+	for j := 0; j < len(s); j++ {
+		regressions = append(regressions, Coordinate{
+			X: s[j].X,
+			Y: a * math.Exp(b*s[j].X),
+		})
+	}
+
+	return regressions, nil
+
+}
+
+// LogarithmicRegression returns an logarithmic regression on data series
+func LogarithmicRegression(s Series) (regressions Series, err error) {
+
+	if len(s) == 0 {
+		return nil, EmptyInput
+	}
+
+	var sum [4]float64
+
+	i := 0
+	for ; i < len(s); i++ {
+		sum[0] += math.Log(s[i].X)
+		sum[1] += s[i].Y * math.Log(s[i].X)
+		sum[2] += s[i].Y
+		sum[3] += math.Pow(math.Log(s[i].X), 2)
+	}
+
+	f := float64(i)
+	a := (f*sum[1] - sum[2]*sum[0]) / (f*sum[3] - sum[0]*sum[0])
+	b := (sum[2] - a*sum[0]) / f
+
+	for j := 0; j < len(s); j++ {
+		regressions = append(regressions, Coordinate{
+			X: s[j].X,
+			Y: b + a*math.Log(s[j].X),
+		})
+	}
+
+	return regressions, nil
+
+}