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