NunoSempere/peopleprobs
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fix mvp counting bug

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This commit is contained in:
NunoSempere 2024-02-25 17:47:45 -03:00
parent c1c47966c2
commit 763add6b0e
1 changed files with 25 additions and 16 deletions
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41
probppl.go
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@ -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)
}
}