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* Add SQLite support, fix un-thread-safe DB caches, small performance fixes Signed-off-by: kim (grufwub) <grufwub@gmail.com> * add SQLite licenses to README Signed-off-by: kim (grufwub) <grufwub@gmail.com> * appease the linter, and fix my dumbass-ery Signed-off-by: kim (grufwub) <grufwub@gmail.com> * make requested changes Signed-off-by: kim (grufwub) <grufwub@gmail.com> * add back comment Signed-off-by: kim (grufwub) <grufwub@gmail.com>
371 lines
9.7 KiB
Go
371 lines
9.7 KiB
Go
// Package bigfft implements multiplication of big.Int using FFT.
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//
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// The implementation is based on the Schönhage-Strassen method
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// using integer FFT modulo 2^n+1.
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package bigfft
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import (
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"math/big"
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"unsafe"
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)
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const _W = int(unsafe.Sizeof(big.Word(0)) * 8)
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type nat []big.Word
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func (n nat) String() string {
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v := new(big.Int)
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v.SetBits(n)
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return v.String()
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}
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// fftThreshold is the size (in words) above which FFT is used over
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// Karatsuba from math/big.
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//
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// TestCalibrate seems to indicate a threshold of 60kbits on 32-bit
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// arches and 110kbits on 64-bit arches.
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var fftThreshold = 1800
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// Mul computes the product x*y and returns z.
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// It can be used instead of the Mul method of
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// *big.Int from math/big package.
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func Mul(x, y *big.Int) *big.Int {
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xwords := len(x.Bits())
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ywords := len(y.Bits())
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if xwords > fftThreshold && ywords > fftThreshold {
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return mulFFT(x, y)
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}
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return new(big.Int).Mul(x, y)
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}
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func mulFFT(x, y *big.Int) *big.Int {
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var xb, yb nat = x.Bits(), y.Bits()
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zb := fftmul(xb, yb)
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z := new(big.Int)
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z.SetBits(zb)
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if x.Sign()*y.Sign() < 0 {
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z.Neg(z)
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}
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return z
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}
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// A FFT size of K=1<<k is adequate when K is about 2*sqrt(N) where
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// N = x.Bitlen() + y.Bitlen().
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func fftmul(x, y nat) nat {
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k, m := fftSize(x, y)
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xp := polyFromNat(x, k, m)
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yp := polyFromNat(y, k, m)
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rp := xp.Mul(&yp)
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return rp.Int()
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}
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// fftSizeThreshold[i] is the maximal size (in bits) where we should use
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// fft size i.
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var fftSizeThreshold = [...]int64{0, 0, 0,
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4 << 10, 8 << 10, 16 << 10, // 5
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32 << 10, 64 << 10, 1 << 18, 1 << 20, 3 << 20, // 10
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8 << 20, 30 << 20, 100 << 20, 300 << 20, 600 << 20,
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}
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// returns the FFT length k, m the number of words per chunk
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// such that m << k is larger than the number of words
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// in x*y.
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func fftSize(x, y nat) (k uint, m int) {
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words := len(x) + len(y)
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bits := int64(words) * int64(_W)
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k = uint(len(fftSizeThreshold))
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for i := range fftSizeThreshold {
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if fftSizeThreshold[i] > bits {
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k = uint(i)
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break
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}
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}
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// The 1<<k chunks of m words must have N bits so that
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// 2^N-1 is larger than x*y. That is, m<<k > words
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m = words>>k + 1
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return
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}
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// valueSize returns the length (in words) to use for polynomial
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// coefficients, to compute a correct product of polynomials P*Q
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// where deg(P*Q) < K (== 1<<k) and where coefficients of P and Q are
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// less than b^m (== 1 << (m*_W)).
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// The chosen length (in bits) must be a multiple of 1 << (k-extra).
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func valueSize(k uint, m int, extra uint) int {
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// The coefficients of P*Q are less than b^(2m)*K
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// so we need W * valueSize >= 2*m*W+K
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n := 2*m*_W + int(k) // necessary bits
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K := 1 << (k - extra)
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if K < _W {
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K = _W
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}
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n = ((n / K) + 1) * K // round to a multiple of K
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return n / _W
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}
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// poly represents an integer via a polynomial in Z[x]/(x^K+1)
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// where K is the FFT length and b^m is the computation basis 1<<(m*_W).
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// If P = a[0] + a[1] x + ... a[n] x^(K-1), the associated natural number
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// is P(b^m).
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type poly struct {
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k uint // k is such that K = 1<<k.
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m int // the m such that P(b^m) is the original number.
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a []nat // a slice of at most K m-word coefficients.
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}
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// polyFromNat slices the number x into a polynomial
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// with 1<<k coefficients made of m words.
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func polyFromNat(x nat, k uint, m int) poly {
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p := poly{k: k, m: m}
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length := len(x)/m + 1
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p.a = make([]nat, length)
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for i := range p.a {
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if len(x) < m {
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p.a[i] = make(nat, m)
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copy(p.a[i], x)
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break
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}
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p.a[i] = x[:m]
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x = x[m:]
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}
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return p
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}
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// Int evaluates back a poly to its integer value.
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func (p *poly) Int() nat {
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length := len(p.a)*p.m + 1
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if na := len(p.a); na > 0 {
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length += len(p.a[na-1])
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}
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n := make(nat, length)
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m := p.m
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np := n
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for i := range p.a {
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l := len(p.a[i])
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c := addVV(np[:l], np[:l], p.a[i])
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if np[l] < ^big.Word(0) {
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np[l] += c
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} else {
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addVW(np[l:], np[l:], c)
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}
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np = np[m:]
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}
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n = trim(n)
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return n
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}
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func trim(n nat) nat {
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for i := range n {
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if n[len(n)-1-i] != 0 {
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return n[:len(n)-i]
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}
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}
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return nil
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}
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// Mul multiplies p and q modulo X^K-1, where K = 1<<p.k.
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// The product is done via a Fourier transform.
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func (p *poly) Mul(q *poly) poly {
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// extra=2 because:
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// * some power of 2 is a K-th root of unity when n is a multiple of K/2.
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// * 2 itself is a square (see fermat.ShiftHalf)
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n := valueSize(p.k, p.m, 2)
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pv, qv := p.Transform(n), q.Transform(n)
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rv := pv.Mul(&qv)
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r := rv.InvTransform()
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r.m = p.m
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return r
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}
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// A polValues represents the value of a poly at the powers of a
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// K-th root of unity θ=2^(l/2) in Z/(b^n+1)Z, where b^n = 2^(K/4*l).
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type polValues struct {
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k uint // k is such that K = 1<<k.
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n int // the length of coefficients, n*_W a multiple of K/4.
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values []fermat // a slice of K (n+1)-word values
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}
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// Transform evaluates p at θ^i for i = 0...K-1, where
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// θ is a K-th primitive root of unity in Z/(b^n+1)Z.
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func (p *poly) Transform(n int) polValues {
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k := p.k
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inputbits := make([]big.Word, (n+1)<<k)
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input := make([]fermat, 1<<k)
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// Now computed q(ω^i) for i = 0 ... K-1
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valbits := make([]big.Word, (n+1)<<k)
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values := make([]fermat, 1<<k)
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for i := range values {
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input[i] = inputbits[i*(n+1) : (i+1)*(n+1)]
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if i < len(p.a) {
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copy(input[i], p.a[i])
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}
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values[i] = fermat(valbits[i*(n+1) : (i+1)*(n+1)])
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}
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fourier(values, input, false, n, k)
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return polValues{k, n, values}
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}
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// InvTransform reconstructs p (modulo X^K - 1) from its
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// values at θ^i for i = 0..K-1.
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func (v *polValues) InvTransform() poly {
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k, n := v.k, v.n
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// Perform an inverse Fourier transform to recover p.
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pbits := make([]big.Word, (n+1)<<k)
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p := make([]fermat, 1<<k)
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for i := range p {
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p[i] = fermat(pbits[i*(n+1) : (i+1)*(n+1)])
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}
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fourier(p, v.values, true, n, k)
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// Divide by K, and untwist q to recover p.
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u := make(fermat, n+1)
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a := make([]nat, 1<<k)
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for i := range p {
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u.Shift(p[i], -int(k))
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copy(p[i], u)
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a[i] = nat(p[i])
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}
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return poly{k: k, m: 0, a: a}
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}
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// NTransform evaluates p at θω^i for i = 0...K-1, where
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// θ is a (2K)-th primitive root of unity in Z/(b^n+1)Z
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// and ω = θ².
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func (p *poly) NTransform(n int) polValues {
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k := p.k
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if len(p.a) >= 1<<k {
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panic("Transform: len(p.a) >= 1<<k")
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}
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// θ is represented as a shift.
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θshift := (n * _W) >> k
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// p(x) = a_0 + a_1 x + ... + a_{K-1} x^(K-1)
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// p(θx) = q(x) where
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// q(x) = a_0 + θa_1 x + ... + θ^(K-1) a_{K-1} x^(K-1)
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//
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// Twist p by θ to obtain q.
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tbits := make([]big.Word, (n+1)<<k)
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twisted := make([]fermat, 1<<k)
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src := make(fermat, n+1)
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for i := range twisted {
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twisted[i] = fermat(tbits[i*(n+1) : (i+1)*(n+1)])
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if i < len(p.a) {
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for i := range src {
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src[i] = 0
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}
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copy(src, p.a[i])
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twisted[i].Shift(src, θshift*i)
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}
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}
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// Now computed q(ω^i) for i = 0 ... K-1
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valbits := make([]big.Word, (n+1)<<k)
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values := make([]fermat, 1<<k)
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for i := range values {
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values[i] = fermat(valbits[i*(n+1) : (i+1)*(n+1)])
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}
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fourier(values, twisted, false, n, k)
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return polValues{k, n, values}
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}
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// InvTransform reconstructs a polynomial from its values at
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// roots of x^K+1. The m field of the returned polynomial
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// is unspecified.
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func (v *polValues) InvNTransform() poly {
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k := v.k
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n := v.n
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θshift := (n * _W) >> k
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// Perform an inverse Fourier transform to recover q.
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qbits := make([]big.Word, (n+1)<<k)
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q := make([]fermat, 1<<k)
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for i := range q {
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q[i] = fermat(qbits[i*(n+1) : (i+1)*(n+1)])
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}
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fourier(q, v.values, true, n, k)
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// Divide by K, and untwist q to recover p.
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u := make(fermat, n+1)
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a := make([]nat, 1<<k)
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for i := range q {
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u.Shift(q[i], -int(k)-i*θshift)
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copy(q[i], u)
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a[i] = nat(q[i])
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}
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return poly{k: k, m: 0, a: a}
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}
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// fourier performs an unnormalized Fourier transform
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// of src, a length 1<<k vector of numbers modulo b^n+1
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// where b = 1<<_W.
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func fourier(dst []fermat, src []fermat, backward bool, n int, k uint) {
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var rec func(dst, src []fermat, size uint)
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tmp := make(fermat, n+1) // pre-allocate temporary variables.
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tmp2 := make(fermat, n+1) // pre-allocate temporary variables.
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// The recursion function of the FFT.
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// The root of unity used in the transform is ω=1<<(ω2shift/2).
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// The source array may use shifted indices (i.e. the i-th
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// element is src[i << idxShift]).
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rec = func(dst, src []fermat, size uint) {
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idxShift := k - size
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ω2shift := (4 * n * _W) >> size
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if backward {
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ω2shift = -ω2shift
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}
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// Easy cases.
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if len(src[0]) != n+1 || len(dst[0]) != n+1 {
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panic("len(src[0]) != n+1 || len(dst[0]) != n+1")
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}
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switch size {
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case 0:
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copy(dst[0], src[0])
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return
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case 1:
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dst[0].Add(src[0], src[1<<idxShift]) // dst[0] = src[0] + src[1]
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dst[1].Sub(src[0], src[1<<idxShift]) // dst[1] = src[0] - src[1]
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return
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}
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// Let P(x) = src[0] + src[1<<idxShift] * x + ... + src[K-1 << idxShift] * x^(K-1)
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// The P(x) = Q1(x²) + x*Q2(x²)
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// where Q1's coefficients are src with indices shifted by 1
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// where Q2's coefficients are src[1<<idxShift:] with indices shifted by 1
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// Split destination vectors in halves.
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dst1 := dst[:1<<(size-1)]
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dst2 := dst[1<<(size-1):]
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// Transform Q1 and Q2 in the halves.
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rec(dst1, src, size-1)
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rec(dst2, src[1<<idxShift:], size-1)
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// Reconstruct P's transform from transforms of Q1 and Q2.
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// dst[i] is dst1[i] + ω^i * dst2[i]
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// dst[i + 1<<(k-1)] is dst1[i] + ω^(i+K/2) * dst2[i]
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//
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for i := range dst1 {
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tmp.ShiftHalf(dst2[i], i*ω2shift, tmp2) // ω^i * dst2[i]
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dst2[i].Sub(dst1[i], tmp)
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dst1[i].Add(dst1[i], tmp)
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}
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}
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rec(dst, src, k)
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}
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// Mul returns the pointwise product of p and q.
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func (p *polValues) Mul(q *polValues) (r polValues) {
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n := p.n
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r.k, r.n = p.k, p.n
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r.values = make([]fermat, len(p.values))
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bits := make([]big.Word, len(p.values)*(n+1))
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buf := make(fermat, 8*n)
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for i := range r.values {
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r.values[i] = bits[i*(n+1) : (i+1)*(n+1)]
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z := buf.Mul(p.values[i], q.values[i])
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copy(r.values[i], z)
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}
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return
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}
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