package binarize

import (
	"image"
	"math"
)

func mean(i []int) float64 {
	sum := 0
	for _, n := range i {
		sum += n
	}
	return float64(sum) / float64(len(i))
}

func stddev(i []int) float64 {
	m := mean(i)

	var sum float64
	for _, n := range i {
		sum += (float64(n) - m) * (float64(n) - m)
	}
	variance := sum / float64(len(i) - 1)
	return math.Sqrt(variance)
}

func meanstddev(i []int) (float64, float64) {
	m := mean(i)

	var sum float64
	for _, n := range i {
		sum += (float64(n) - m) * (float64(n) - m)
	}
	variance := float64(sum) / float64(len(i) - 1)
	return m, math.Sqrt(variance)
}

// gets the pixel values surrounding a point in the image
func surrounding(img *image.Gray, x int, y int, size int) []int {
	b := img.Bounds()
	step := size / 2

	miny := y - step
	if miny < b.Min.Y {
		miny = b.Min.Y
	}
	minx := x - step
	if minx < b.Min.X {
		minx = b.Min.X
	}
	maxy := y + step
	if maxy > b.Max.Y {
		maxy = b.Max.Y
	}
	maxx := x + step
	if maxx > b.Max.X {
		maxx = b.Max.X
	}

	var s []int
	for yi := miny; yi <= maxy; yi++ {
		for xi := minx; xi <= maxx; xi++ {
			s = append(s, int(img.GrayAt(xi, yi).Y))
		}
	}
	return s
}