diff --git a/probppl.go b/probppl.go
index 47e1d7b..ebe6844 100644
--- a/probppl.go
+++ b/probppl.go
@@ -23,19 +23,9 @@ func generatePeopleKnownDistribution(r src) IntProbabilities {
 	var probabilities IntProbabilities
 	sum := 0.0
 
-	// Consider zero case separately
-	/*p0 := r.Float64()
-	mapping[0.0] = p0
-	sum += p0
-	*/
-
-	// Consider successive exponents of 1.5
-	num := 16.0
-	base := 2.0
-	for i := 1; i < 8; i++ {
-		num = num * base
+	for i := 16; i <= 2048; i *= 2 {
 		p := r.Float64()
-		probabilities = append(probabilities, IntProbability{N: int64(num), p: p})
+		probabilities = append(probabilities, IntProbability{N: int64(i), p: p})
 		sum += p
 	}
 
@@ -147,21 +137,22 @@ func main() {
 
 	var distribs []IntProbabilitiesWeights
 
-	sum := int64(0)
+	sum_weights := int64(0)
 	for i := 0; i < 100; i++ {
 
 		people_known_distribution := generatePeopleKnownDistribution(r)
 		// fmt.Println(people_known_distribution)
 		result := getUnnormalizedBayesianUpdateForDistribution(people_known_distribution, r)
-		fmt.Println(i)
+		// fmt.Println(i)
 		if result > 0 {
 			fmt.Println(people_known_distribution)
 			fmt.Println(result)
 			distribs = append(distribs, IntProbabilitiesWeights{IntProb: people_known_distribution, w: result})
 		}
-		sum += result
+		sum_weights += result
 		// fmt.Println(result)
 	}
-	fmt.Println(sum)
+	// fmt.Println(distribs)
 
+	// Now calculate the posterior
 }