package main

import (
	"fmt"
	"math"
	"math/rand"
	"time"
)

// "given"
func dice6() int {
	return rand.Intn(6) + 1
}

// function specified by task "Seven-sided dice from five-sided dice"
func dice16() (i int) {
	for {
		i = 6*dice6() - dice6()
		if i < 32 {
			break
		}
	}
	return (i / 2) + 1
}

// function specified by task "Verify distribution uniformity/Naive"
//
// Parameter "f" is expected to return a random integer in the range 1..n.
// (Values out of range will cause an unceremonious crash.)
// "Max" is returned as an "indication of distribution achieved."
// It is the maximum delta observed from the count representing a perfectly
// uniform distribution.
// Also returned is a boolean, true if "max" is less than threshold
// parameter "delta."
func distCheck(f func() int, n int,
	repeats int, delta float64) (max float64, flatEnough bool) {
	count := make([]int, n)
	for i := 0; i < repeats; i++ {
		count[f()-1]++
	}
	expected := float64(repeats) / float64(n)
	for _, c := range count {
		max = math.Max(max, math.Abs(float64(c)-expected))
	}
	fmt.Println(count)
	return max, max < delta
}

// Driver, produces output satisfying both tasks.
func main() {
	rand.Seed(time.Now().UnixNano())
	const calls = 1000000
	max, flatEnough := distCheck(dice16, 16, calls, 500)
	fmt.Println("Max delta:", max, "Flat enough:", flatEnough)
	max, flatEnough = distCheck(dice16, 16, calls, 500)
	fmt.Println("Max delta:", max, "Flat enough:", flatEnough)
}