savepoint after refactor

probppl.go

@@ -8,15 +8,19 @@ import (
 )
 
 type src = *rand.Rand
-type IntProbability {
+type IntProbability struct {
 	N int64
-  p float64
+	p float64
+}
+type IntProbabilities = []IntProbability
+type IntProbabilitiesWeights struct {
+	IntProb IntProbabilities
+	w       int64
 }
 
-type pplKnownDistrib = map[int64]float64
+func generatePeopleKnownDistribution(r src) IntProbabilities {
 
-func generatePeopleKnownDistribution(r src) map[int64]float64 {
-	mapping := make(map[int64]float64)
+	var probabilities IntProbabilities
 	sum := 0.0
 
 	// Consider zero case separately
@@ -31,15 +35,15 @@ func generatePeopleKnownDistribution(r src) map[int64]float64 {
 	for i := 1; i < 8; i++ {
 		num = num * base
 		p := r.Float64()
-		mapping[int64(num)] = p
+		probabilities = append(probabilities, IntProbability{N: int64(num), p: p})
 		sum += p
 	}
 
-	for key, value := range mapping {
-		mapping[key] = value / sum
+	for i := range probabilities {
+		probabilities[i].p = probabilities[i].p / sum
 	}
 
-	return mapping
+	return probabilities
 }
 
 func chooseWrapper(n int64, k int64) int64 {
@@ -80,13 +84,13 @@ func getMatchesDrawGivenNPeopleKnown(n int64, r src) int64 {
 	≥3: 9.5% | 14
 */
 
-func drawFromDistributionWithReplacement(d pplKnownDistrib, r src) int64 {
+func drawFromDistributionWithReplacement(d IntProbabilities, r src) int64 {
 	pp := r.Float64()
 	sum := 0.0
-	for i, p := range d {
-		sum += p
+	for i := range d {
+		sum += d[i].p
 		if pp <= sum {
-			return int64(i) // this introduces some non-determinism, as order of maps in go isn't guaranteed
+			return int64(d[i].N) // this introduces some non-determinism, as order of maps in go isn't guaranteed
 		}
 
 	}
@@ -100,7 +104,7 @@ func aboutEq(a int64, b int64) bool {
 	return ((-h) <= (a - b)) && ((a - b) <= h)
 }
 
-func draw148PplFromDistributionAndCheck(d pplKnownDistrib, r src, show bool) int64 {
+func draw148PplFromDistributionAndCheck(d IntProbabilities, r src, show bool) int64 {
 
 	count := make(map[int64]int64)
 	count[0] = 0
@@ -123,7 +127,7 @@ func draw148PplFromDistributionAndCheck(d pplKnownDistrib, r src, show bool) int
 	}
 }
 
-func getUnnormalizedBayesianUpdateForDistribution(d pplKnownDistrib, r src) int64 {
+func getUnnormalizedBayesianUpdateForDistribution(d IntProbabilities, r src) int64 {
 	var sum int64 = 0
 	n := 1000
 	for i := 0; i < n; i++ {
@@ -141,9 +145,10 @@ func main() {
 
 	var r = rand.New(rand.NewPCG(uint64(1), uint64(2)))
 
+	var distribs []IntProbabilitiesWeights
+
 	sum := int64(0)
-	distribs := [](int64, pplKnownDistrib){}
-	for i := 0; i < 1000; i++ {
+	for i := 0; i < 100; i++ {
 
 		people_known_distribution := generatePeopleKnownDistribution(r)
 		// fmt.Println(people_known_distribution)
@@ -152,7 +157,7 @@ func main() {
 		if result > 0 {
 			fmt.Println(people_known_distribution)
 			fmt.Println(result)
-			distribs.append()
+			distribs = append(distribs, IntProbabilitiesWeights{IntProb: people_known_distribution, w: result})
 		}
 		sum += result
 		// fmt.Println(result)