136 lines
3.0 KiB
Plaintext
136 lines
3.0 KiB
Plaintext
package ope
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import (
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"encoding/binary"
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"math"
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"math/big"
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"xdx.jelly/xgcl/grand"
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)
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// uniformRand returns a random number in [0, 1]
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func uniformRand() float64 {
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b := make([]byte, 4)
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_, _ = grand.GenerateRandom(b)
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return float64(binary.LittleEndian.Uint32(b)) / float64(uint64(1)<<32-1)
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}
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func minBig(a, b *big.Int) *big.Int {
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if a.Cmp(b) < 0 {
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return a
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}
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return b
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}
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func maxBig(a, b *big.Int) *big.Int {
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if a.Cmp(b) < 0 {
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return b
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}
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return a
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}
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func floatFromBig(a *big.Int) float64 {
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r, _ := a.Float64()
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return r
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}
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// hypergeometric10 returns a sample in hypergeometric distribution.
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// Pr[X=x] = choose(y, x) * choose(N-y, M-x) / choose(N, M)
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func hypergeometricSmall(M *big.Int, N *big.Int, y *big.Int) *big.Int {
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d1 := new(big.Int).Sub(N, y)
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nm := new(big.Int).Sub(N, M)
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d2 := minBig(M, nm)
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Y := new(big.Int).Set(d2)
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K := y.Int64()
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for Y.Sign() > 0 && K != 0 {
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U := uniformRand()
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Y.Sub(Y, big.NewInt(int64(U+floatFromBig(Y)/(floatFromBig(d1)+float64(K)))))
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K--
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}
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Z := new(big.Int).Sub(d2, Y)
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if nm.Cmp(M) < 0 {
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Z.Sub(y, Z)
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}
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return Z
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}
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func loggam(x int64) float64 {
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return math.Log(math.Gamma(float64(x)))
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}
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func hypergeometric(M *big.Int, N *big.Int, y *big.Int) *big.Int {
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if y.BitLen() < 4 {
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return hypergeometricSmall(M, N, y)
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}
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return hypergeometricBig(M, N, y)
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}
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func hypergeometricBig(M *big.Int, N *big.Int, y *big.Int) *big.Int {
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D1 := 1.7155277699214135
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D2 := 0.8989161620588988
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// # long mingoodbad, maxgoodbad, popsize, m, d9;
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// # double d4, d5, d6, d7, d8, d10, d11;
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// # long Z;
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// # double T, W, X, Y;
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good := M
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bad := new(big.Int).Sub(N, M)
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sample := y
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mingoodbad := minBig(good, bad)
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popsize := N
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maxgoodbad := maxBig(good, bad)
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m := minBig(sample, new(big.Int).Sub(popsize, sample))
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d4 := floatFromBig(mingoodbad) / floatFromBig(popsize)
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d5 := 1.0 - d4
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d6 := floatFromBig(m)*d4 + 0.5
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d7 := math.Sqrt(floatFromBig(new(big.Int).Sub(popsize, m))*floatFromBig(sample)*d4*d5/floatFromBig(new(big.Int).Sub(popsize, one)) + 0.5)
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d8 := D1*d7 + D2
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d9 := floatFromBig(new(big.Int).Add(m, one).Mul(new(big.Int).Add(mingoodbad, one))) / (popsize + 2)
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d10 := loggam(d9+1) + loggam(mingoodbad-d9+1) + loggam(m-d9+1) + loggam(maxgoodbad-m+d9+1)
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d11 := min(float64(min(m, mingoodbad)+1), math.Floor(d6+16*d7))
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// # 16 for 16-decimal-digit precision in D1 and D2
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var Z int64
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for {
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X := uniformRand()
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Y := uniformRand()
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W := d6 + d8*(Y-0.5)/X
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// # fast rejection:
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if W < 0.0 || W >= d11 {
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continue
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}
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Z = int64(math.Floor(W))
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T := d10 - (loggam(Z+1) + loggam(mingoodbad-Z+1) + loggam(m-Z+1) + loggam(maxgoodbad-m+Z+1))
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// # fast acceptance:
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if (X*(4.0-X) - 3.0) <= T {
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break
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}
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// # fast rejection:
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if X*(X-T) >= 1 {
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continue
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}
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// # acceptance:
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if 2.0*math.Log(X) <= T {
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break
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}
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}
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// # this is a correction to HRUA* by Ivan Frohne in rv.py
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if good > bad {
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Z = m - Z
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}
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// # another fix from rv.py to allow sample to exceed popsize/2
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if m < sample {
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Z = good - Z
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}
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return Z
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}
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