Merge working development into master

2 files changed, 111 insertions, 0 deletions

diff --git a/print.go b/print.go
new file mode 100644
index 0000000..2a39c71
--- /dev/null
+++ b/print.go
@@ -0,0 +1,21 @@
+package stats
+
+import (
+	"fmt"
+)
+
+// Prints each calculated statistic on a line with one tab preceding it
+func (s *Stats) PrettyStats() string {
+	return fmt.Sprintf(`
+	Mean: %.2f
+	Variance: %.2f
+	Standard Deviation: %.2f
+	Skewness: %.2f
+	Kurtosis: %.2f
+`, s.Mean(), s.Variance(), s.StandardDeviation(), s.Skewness(), s.Kurtosis())
+}
+
+// Returns a string containing all of the data within the struct
+func (s *Stats) Internals() string {
+	return fmt.Sprintf("%#v", s)
+}
diff --git a/stats.go b/stats.go
new file mode 100644
index 0000000..ffe94eb
--- /dev/null
+++ b/stats.go
@@ -0,0 +1,90 @@
+// Provides some basic statisitcs functionality. Specifically tailored around
+// dealing with large streams of data
+// It's a Go implimentation of this:
+//
+// https://www.johndcook.com/blog/skewness_kurtosis/
+//
+// Example program:
+//	package main
+//
+//	import (
+//		"git.riedstra.us/go/stats"
+//
+//		"fmt"
+//	)
+//
+//	func main() {
+//		myFakeStreamOfData := []float64{01, 04, 60, 55, 80, 06, 75, 51, 63, 10}
+//		myStats := &stats.Stats{}
+//		for _, entry := range myFakeStreamOfData {
+//			myStats.Push(entry)
+//		}
+//		fmt.Println(myStats.PrettyStats())
+//	}
+// Example output:
+//
+//		Mean: 40.50
+//		Variance: 996.72
+//		Standard Deviation: 31.57
+//		Skewness: -0.20
+//		Kurtosis: -1.66
+//
+//
+package stats
+
+import (
+	"math"
+)
+
+// Structure used to hold the information about the dataset.
+// several methods are exposed in order to make your life easy
+type Stats struct {
+	n, m1, m2, m3, m4 float64
+}
+
+// Zeros out the  struct for re-use
+func (s *Stats) Clear() {
+	s.n = 0
+	s.m1, s.m2, s.m3, s.m4 = 0, 0, 0, 0
+}
+
+// This function is used to push numbers onto the struct and calculate on the
+// fly the necessary information to output relevant statistics
+func (s *Stats) Push(x float64) {
+	var delta, delta_n, delta_n2, term1, n1 float64
+
+	n1 = s.n
+	s.n++
+	delta = x - s.m1
+	delta_n = delta / s.n
+	delta_n2 = delta_n * delta_n
+	term1 = delta * delta_n * n1
+	s.m1 += delta_n
+	s.m4 += term1*delta_n2*(s.n*s.n-3*s.n+3) + 6*delta_n2*s.m2 - 4*delta_n*s.m3
+	s.m3 += term1*delta_n*(s.n-2) - 3*delta_n*s.m2
+	s.m2 += term1
+}
+
+func (s *Stats) NumValues() float64 {
+	return s.n
+}
+
+func (s *Stats) Mean() float64 {
+	return s.m1
+}
+
+func (s *Stats) Variance() float64 {
+	return s.m2 / (s.n - 1)
+}
+
+func (s *Stats) StandardDeviation() float64 {
+	return math.Sqrt(s.Variance())
+}
+
+func (s *Stats) Skewness() float64 {
+	return math.Sqrt(s.n) * s.m3 / math.Pow(s.m2, 1.5)
+}
+
+func (s *Stats) Kurtosis() float64 {
+	return s.n*s.m4/(s.m2*s.m2) - 3
+}