fix mvp counting bug

probppl.go

@@ -20,7 +20,7 @@ func generatePeopleKnownDistribution(r src) map[int64]float64 {
 	// Consider successive exponents of 1.5
 	l := 1.0
 	m := 1.5
-	for i := 1; i < 22; i++ {
+	for i := 1; i < 20; i++ {
 		l = l * m
 		p := r.Float64()
 		mapping[int64(l)] = p
@@ -87,6 +87,11 @@ func drawFromDistributionWithReplacement(d pplKnownDistrib, r src) int64 {
 	panic("Probabilities should sum up to 1")
 }
 
+func aboutEq(a int64, b int64) bool {
+	h := int64(3)
+	return ((-h) <= (a - b)) && ((a - b) <= h)
+}
+
 func draw148PplFromDistributionAndCheck(d pplKnownDistrib, r src) int64 {
 
 	count := make(map[int64]int64)
@@ -99,35 +104,39 @@ func draw148PplFromDistributionAndCheck(d pplKnownDistrib, r src) int64 {
 		person_i_num_birthday_matches := getMatchesDrawGivenNPeopleKnown(person_i_ppl_known, r)
 		count[person_i_num_birthday_matches]++
 	}
-	if (count[0] == 69) && (count[1] == 46) && (count[2] == 19) && (count[3] == 14) {
+	// if (count[0] == 69) && (count[1] == 46) && (count[2] == 19) && (count[3] == 14) {
+	fmt.Println(count)
+	if aboutEq(count[0], 69) && aboutEq(count[1], 46) && aboutEq(count[2], 19) && aboutEq(count[3], 14) {
 		return 1
 	} else {
 		return 0
 	}
 }
 
-func getUnnormalizedBayesianUpdateForDistribution(d pplKnownDistrib, r src) float64 {
+func getUnnormalizedBayesianUpdateForDistribution(d pplKnownDistrib, r src) int64 {
 	var sum int64 = 0
-	n := 100_000
+	n := 1
 	for i := 0; i < n; i++ {
-		if i%1000 == 0 {
+		/* if i%1000 == 0 {
 			fmt.Println(i)
-		}
-		sum += draw148PplFromDistributionAndCheck(d, r)
+		} */
+		draw_result := draw148PplFromDistributionAndCheck(d, r)
+		// fmt.Println(draw_result)
+		sum += draw_result
 	}
-	return float64(sum) / float64(n)
+	return sum // float64(sum) / float64(n)
 }
 
 func main() {
-	fmt.Println("Hello world")
 
 	var r = rand.New(rand.NewPCG(uint64(1), uint64(2)))
-	people_known_distribution := generatePeopleKnownDistribution(r)
-	fmt.Println(people_known_distribution)
-	/* for i, p := range people_known_distribution {
-		fmt.Print64f("%d: %.4f\n", i, p)
-	} */
-	result := getUnnormalizedBayesianUpdateForDistribution(people_known_distribution, r)
-	fmt.Println(result)
+
+	for i := 0; i < 100; i++ {
+
+		people_known_distribution := generatePeopleKnownDistribution(r)
+		// fmt.Println(people_known_distribution)
+		result := getUnnormalizedBayesianUpdateForDistribution(people_known_distribution, r)
+		fmt.Println(result)
+	}
 
 }