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FormalPowerSeriesCoefficient

Trait FormalPowerSeriesCoefficient 

Source
pub trait FormalPowerSeriesCoefficient:
    Sized
    + Clone
    + Zero
    + PartialEq
    + One
    + From<usize>
    + From<isize>
    + Add<Output = Self>
    + Sub<Output = Self>
    + Mul<Output = Self>
    + Div<Output = Self>
    + for<'r> Add<&'r Self, Output = Self>
    + for<'r> Sub<&'r Self, Output = Self>
    + for<'r> Mul<&'r Self, Output = Self>
    + for<'r> Div<&'r Self, Output = Self>
    + AddAssign<Self>
    + SubAssign<Self>
    + MulAssign<Self>
    + DivAssign<Self>
    + for<'r> AddAssign<&'r Self>
    + for<'r> SubAssign<&'r Self>
    + for<'r> MulAssign<&'r Self>
    + for<'r> DivAssign<&'r Self>
    + Neg<Output = Self> {
    type Base: MIntConvert<usize> + MIntConvert<isize>;

    // Required methods
    fn pow(self, exp: usize) -> Self;
    fn memorized_fact(mf: &MemorizedFactorial<Self::Base>) -> &[Self];
    fn memorized_inv_fact(mf: &MemorizedFactorial<Self::Base>) -> &[Self];
    fn memorized_inv(mf: &MemorizedFactorial<Self::Base>, n: usize) -> Self;

    // Provided methods
    fn signed_pow(self, exp: isize) -> Self { ... }
    fn memorized_factorial(n: usize) -> MemorizedFactorial<Self::Base> { ... }
}

Required Associated Types§

Required Methods§

Source

fn pow(self, exp: usize) -> Self

Source

fn memorized_fact(mf: &MemorizedFactorial<Self::Base>) -> &[Self]

Source

fn memorized_inv_fact(mf: &MemorizedFactorial<Self::Base>) -> &[Self]

Source

fn memorized_inv(mf: &MemorizedFactorial<Self::Base>, n: usize) -> Self

Provided Methods§

Source

fn signed_pow(self, exp: isize) -> Self

Examples found in repository?
crates/competitive/src/math/formal_power_series/formal_power_series_impls.rs (line 516)
462    pub fn mul_of_pow_sparse(&self, q: &Self, exp_p: isize, exp_q: isize, deg: usize) -> Self {
463        if deg == 0 {
464            return Self::zero();
465        }
466        if exp_p == 0 && exp_q == 0 {
467            return Self::from_vec(
468                once(T::one())
469                    .chain(repeat_with(T::zero))
470                    .take(deg)
471                    .collect(),
472            );
473        }
474        if exp_p != 0 && self.iter().all(|x| x.is_zero()) {
475            assert!(exp_p > 0);
476            return Self::zeros(deg);
477        }
478        if exp_q != 0 && q.iter().all(|x| x.is_zero()) {
479            assert!(exp_q > 0);
480            return Self::zeros(deg);
481        }
482
483        let normalize = |f: &Self, exp: isize| {
484            if exp == 0 {
485                return (0usize, T::one(), Self::from_vec(vec![T::one()]));
486            }
487            let k = f.iter().position(|value| !value.is_zero()).unwrap();
488            assert!(
489                exp >= 0 || k == 0,
490                "Negative exponent with zero constant term"
491            );
492            let c = f[k].clone();
493            let f = (f.clone() >> k) / &c;
494            (k, c, f)
495        };
496        let (sp, cp, mut p) = normalize(self, exp_p);
497        let (sq, cq, mut q) = normalize(q, exp_q);
498
499        let shift = exp_p
500            .saturating_mul(sp as _)
501            .saturating_add(exp_q.saturating_mul(sq as _)) as usize;
502        if shift >= deg {
503            return Self::zeros(deg);
504        }
505        p.truncate(deg - shift);
506        q.truncate(deg - shift);
507
508        let mut f = Self::solve_sparse_differential2(
509            &p,
510            &q,
511            &p,
512            T::from(exp_p),
513            T::from(exp_q),
514            deg - shift,
515        );
516        f *= cp.signed_pow(exp_p) * cq.signed_pow(exp_q);
517        if shift > 0 {
518            f <<= shift;
519        }
520        f.prefix(deg)
521    }
Source

fn memorized_factorial(n: usize) -> MemorizedFactorial<Self::Base>

Examples found in repository?
crates/competitive/src/math/formal_power_series/formal_power_series_impls.rs (line 305)
293    pub fn exp(&self, deg: usize) -> Self {
294        debug_assert!(self[0].is_zero());
295        if self.data.iter().filter(|x| !x.is_zero()).count()
296            <= deg.next_power_of_two().trailing_zeros() as usize * 16
297        {
298            let diff = self.clone().diff();
299            let pos: Vec<_> = diff
300                .data
301                .iter()
302                .enumerate()
303                .filter_map(|(i, x)| if x.is_zero() { None } else { Some(i) })
304                .collect();
305            let mf = T::memorized_factorial(deg);
306            let mut f = Self::zeros(deg);
307            f[0] = T::one();
308            for i in 1..deg {
309                let mut tot = T::zero();
310                for &j in &pos {
311                    if j > i - 1 {
312                        break;
313                    }
314                    tot += f[i - 1 - j].clone() * &diff[j];
315                }
316                f[i] = tot * T::memorized_inv(&mf, i);
317            }
318            return f;
319        }
320        let mut f = Self::one();
321        let mut i = 1;
322        while i < deg {
323            let mut g = -f.log(i * 2);
324            g[0] += T::one();
325            for (g, x) in g.iter_mut().zip(self.iter().take(i * 2)) {
326                *g += x.clone();
327            }
328            f = (f * g).prefix(i * 2);
329            i *= 2;
330        }
331        f.prefix(deg)
332    }
333    pub fn log(&self, deg: usize) -> Self {
334        (self.inv(deg) * self.clone().diff()).integral().prefix(deg)
335    }
336    pub fn pow(&self, rhs: usize, deg: usize) -> Self {
337        if rhs == 0 {
338            return Self::from_vec(
339                once(T::one())
340                    .chain(repeat_with(T::zero))
341                    .take(deg)
342                    .collect(),
343            );
344        }
345        if let Some(k) = self.iter().position(|x| !x.is_zero()) {
346            if k >= deg.div_ceil(rhs) {
347                Self::zeros(deg)
348            } else {
349                let deg = deg - k * rhs;
350                let x0 = self[k].clone();
351                let mut f = (self >> k) / &x0;
352                if f.data.iter().filter(|x| !x.is_zero()).count()
353                    <= deg.next_power_of_two().trailing_zeros() as usize * 12
354                {
355                    f = f.pow_sparse1(T::from(rhs), deg);
356                } else {
357                    f = (f.log(deg) * &T::from(rhs)).exp(deg);
358                }
359                f *= x0.pow(rhs);
360                f <<= k * rhs;
361                f
362            }
363        } else {
364            Self::zeros(deg)
365        }
366    }
367    fn pow_sparse1(&self, rhs: T, deg: usize) -> Self {
368        debug_assert!(!self[0].is_zero());
369        let pos: Vec<_> = self
370            .data
371            .iter()
372            .enumerate()
373            .skip(1)
374            .filter_map(|(i, x)| if x.is_zero() { None } else { Some(i) })
375            .collect();
376        let mf = T::memorized_factorial(deg);
377        let mut f = Self::zeros(deg);
378        f[0] = T::one();
379        for i in 1..deg {
380            let mut tot = T::zero();
381            for &j in &pos {
382                if j > i {
383                    break;
384                }
385                tot += (T::from(j) * &rhs - T::from(i - j)) * &self[j] * &f[i - j];
386            }
387            f[i] = tot * T::memorized_inv(&mf, i);
388        }
389        f
390    }
391
392    fn sparse_fold(&self, sparse: impl IntoIterator<Item = (usize, T)>, deg: usize) -> T {
393        sparse
394            .into_iter()
395            .take_while(|&(i, _)| i <= deg)
396            .fold(T::zero(), |sum, (i, x)| sum + x * self.coeff(deg - i))
397    }
398
399    /// solve: $X(QF)'=\alpha P'(QF)+\beta P(Q'F)$ in $O(deg * max(nz(P), nz(Q), nz(X)))$
400    pub fn solve_sparse_differential2(
401        p: &Self,
402        q: &Self,
403        x: &Self,
404        alpha: T,
405        beta: T,
406        deg: usize,
407    ) -> Self {
408        if deg == 0 {
409            return Self::zero();
410        }
411        let collect_sparse = |p: &Self| -> Vec<(usize, T)> {
412            p.iter()
413                .enumerate()
414                .filter(|&(_, x)| !x.is_zero())
415                .map(|(i, x)| (i, x.clone()))
416                .collect()
417        };
418        assert!(q.coeff(0).is_one());
419        assert!(x.coeff(0).is_one());
420        let p = collect_sparse(p);
421        let q = collect_sparse(q);
422        let x = collect_sparse(x);
423        let diff = |p: &[(usize, T)]| -> Vec<(usize, T)> {
424            p.iter()
425                .filter(|&&(i, _)| i > 0)
426                .map(|&(i, ref x)| (i - 1, x.clone() * T::from(i)))
427                .collect()
428        };
429        let dp = diff(&p);
430        let dq = diff(&q);
431
432        let mf = T::memorized_factorial(deg);
433        let mut f = Self::zeros(deg);
434        let mut qf = Self::zeros(deg);
435        let mut dq_f = Self::zeros(deg);
436        let mut d_qf = Self::zeros(deg);
437        f[0] = T::one();
438        for i in 0..deg - 1 {
439            qf[i] = f.sparse_fold(q.iter().cloned(), i);
440            dq_f[i] = f.sparse_fold(dq.iter().cloned(), i);
441            let dp_qf_i = qf.sparse_fold(dp.iter().cloned(), i);
442            let p_dq_f_i = dq_f.sparse_fold(p.iter().cloned(), i);
443            let x_d_qf_i = d_qf.sparse_fold(
444                x.iter()
445                    .map(|&(i, ref x)| (i, x.clone() - T::from((i == 0) as usize))),
446                i,
447            );
448            d_qf[i] = alpha.clone() * dp_qf_i + beta.clone() * p_dq_f_i - x_d_qf_i;
449
450            let mut f_ip1 = d_qf[i].clone();
451            for &(j, ref q) in q.iter().take_while(|&&(j, _)| j <= i) {
452                if j > 0 {
453                    f_ip1 -= q.clone() * &f[i - (j - 1)] * T::from(i - (j - 1));
454                }
455            }
456            f[i + 1] = f_ip1 * T::memorized_inv(&mf, i + 1);
457        }
458        f
459    }
460
461    /// P^exp_p * Q^exp_q
462    pub fn mul_of_pow_sparse(&self, q: &Self, exp_p: isize, exp_q: isize, deg: usize) -> Self {
463        if deg == 0 {
464            return Self::zero();
465        }
466        if exp_p == 0 && exp_q == 0 {
467            return Self::from_vec(
468                once(T::one())
469                    .chain(repeat_with(T::zero))
470                    .take(deg)
471                    .collect(),
472            );
473        }
474        if exp_p != 0 && self.iter().all(|x| x.is_zero()) {
475            assert!(exp_p > 0);
476            return Self::zeros(deg);
477        }
478        if exp_q != 0 && q.iter().all(|x| x.is_zero()) {
479            assert!(exp_q > 0);
480            return Self::zeros(deg);
481        }
482
483        let normalize = |f: &Self, exp: isize| {
484            if exp == 0 {
485                return (0usize, T::one(), Self::from_vec(vec![T::one()]));
486            }
487            let k = f.iter().position(|value| !value.is_zero()).unwrap();
488            assert!(
489                exp >= 0 || k == 0,
490                "Negative exponent with zero constant term"
491            );
492            let c = f[k].clone();
493            let f = (f.clone() >> k) / &c;
494            (k, c, f)
495        };
496        let (sp, cp, mut p) = normalize(self, exp_p);
497        let (sq, cq, mut q) = normalize(q, exp_q);
498
499        let shift = exp_p
500            .saturating_mul(sp as _)
501            .saturating_add(exp_q.saturating_mul(sq as _)) as usize;
502        if shift >= deg {
503            return Self::zeros(deg);
504        }
505        p.truncate(deg - shift);
506        q.truncate(deg - shift);
507
508        let mut f = Self::solve_sparse_differential2(
509            &p,
510            &q,
511            &p,
512            T::from(exp_p),
513            T::from(exp_q),
514            deg - shift,
515        );
516        f *= cp.signed_pow(exp_p) * cq.signed_pow(exp_q);
517        if shift > 0 {
518            f <<= shift;
519        }
520        f.prefix(deg)
521    }
522
523    /// exp(P/Q)
524    pub fn exp_of_div_sparse(&self, q: &Self, deg: usize) -> Self {
525        if deg == 0 {
526            return Self::zero();
527        }
528        let shift_q = q
529            .iter()
530            .position(|value| !value.is_zero())
531            .expect("Zero denominator");
532        let shift_p = self.iter().position(|value| !value.is_zero()).unwrap_or(!0);
533        assert!(shift_p > shift_q);
534
535        let mut p = self >> shift_q;
536        let mut q = q >> shift_q;
537        assert!(!q.coeff(0).is_zero());
538
539        let c = q[0].clone();
540        p /= c.clone();
541        q /= c;
542
543        Self::solve_sparse_differential2(&p, &q, &q, T::one(), -T::one(), deg)
544    }
545}
546
547impl<T, C> FormalPowerSeries<T, C>
548where
549    T: FormalPowerSeriesCoefficientSqrt,
550    C: ConvolveSteps<T = Vec<T>>,
551{
552    pub fn sqrt(&self, deg: usize) -> Option<Self> {
553        if self[0].is_zero() {
554            if let Some(k) = self.iter().position(|x| !x.is_zero()) {
555                if k % 2 != 0 {
556                    return None;
557                } else if deg > k / 2 {
558                    return Some((self >> k).sqrt(deg - k / 2)? << (k / 2));
559                }
560            }
561        } else {
562            let s = self[0].sqrt_coefficient()?;
563            if self.data.iter().filter(|x| !x.is_zero()).count()
564                <= deg.next_power_of_two().trailing_zeros() as usize * 4
565            {
566                let t = self[0].clone();
567                let mut f = self / t;
568                f = f.pow_sparse1(T::one() / T::from(2usize), deg);
569                f *= s;
570                return Some(f);
571            }
572
573            let mut f = Self::from(s);
574            let inv2 = T::one() / (T::one() + T::one());
575            let mut i = 1;
576            while i < deg {
577                f = (&f + &(self.prefix_ref(i * 2) * f.inv(i * 2))).prefix(i * 2) * &inv2;
578                i *= 2;
579            }
580            f.truncate(deg);
581            return Some(f);
582        }
583        Some(Self::zeros(deg))
584    }
585}
586
587impl<T, C> FormalPowerSeries<T, C>
588where
589    T: FormalPowerSeriesCoefficient,
590    C: ConvolveSteps<T = Vec<T>>,
591{
592    pub fn count_subset_sum<F>(&self, deg: usize, mut inverse: F) -> Self
593    where
594        F: FnMut(usize) -> T,
595    {
596        let n = self.length();
597        let mut f = Self::zeros(n);
598        for i in 1..n {
599            if !self[i].is_zero() {
600                for (j, d) in (0..n).step_by(i).enumerate().skip(1) {
601                    if j & 1 != 0 {
602                        f[d] += self[i].clone() * &inverse(j);
603                    } else {
604                        f[d] -= self[i].clone() * &inverse(j);
605                    }
606                }
607            }
608        }
609        f.exp(deg)
610    }
611    pub fn count_multiset_sum<F>(&self, deg: usize, mut inverse: F) -> Self
612    where
613        F: FnMut(usize) -> T,
614    {
615        let n = self.length();
616        let mut f = Self::zeros(n);
617        for i in 1..n {
618            if !self[i].is_zero() {
619                for (j, d) in (0..n).step_by(i).enumerate().skip(1) {
620                    f[d] += self[i].clone() * &inverse(j);
621                }
622            }
623        }
624        f.exp(deg)
625    }
626    /// [x^n] P(x) / Q(x)
627    pub fn bostan_mori(mut self, mut rhs: Self, mut n: usize) -> T
628    where
629        C: NttReuse<T = Vec<T>>,
630    {
631        let mut res = T::zero();
632        rhs.trim_tail_zeros();
633        if self.length() >= rhs.length() {
634            let r = &self / &rhs;
635            if n < r.length() {
636                res = r[n].clone();
637            }
638            self -= r * &rhs;
639            self.trim_tail_zeros();
640        }
641        let k = rhs.length().next_power_of_two();
642        let mut p = C::transform(self.data, k * 2);
643        let mut q = C::transform(rhs.data, k * 2);
644        while n > 0 {
645            let t = C::even_mul_normal_neg(&q, &q);
646            p = if n.is_multiple_of(2) {
647                C::even_mul_normal_neg(&p, &q)
648            } else {
649                C::odd_mul_normal_neg(&p, &q)
650            };
651            q = t;
652            n /= 2;
653            if n != 0 {
654                if C::MULTIPLE {
655                    p = C::transform(C::inverse_transform(p, k), k * 2);
656                    q = C::transform(C::inverse_transform(q, k), k * 2);
657                } else {
658                    p = C::ntt_doubling(p);
659                    q = C::ntt_doubling(q);
660                }
661            }
662        }
663        let p = C::inverse_transform(p, k);
664        let q = C::inverse_transform(q, k);
665        res + p[0].clone() / q[0].clone()
666    }
667    /// return F(x) where [x^n] P(x) / Q(x) = [x^d-1] P(x) F(x)
668    pub fn bostan_mori_msb(self, n: usize) -> Self {
669        let d = self.length() - 1;
670        if n == 0 {
671            return (Self::one() << (d - 1)) / self[0].clone();
672        }
673        let q = self;
674        let mq = q.clone().parity_inversion();
675        let w = (q * &mq).even().bostan_mori_msb(n / 2);
676        let mut s = Self::zeros(w.length() * 2 - (n % 2));
677        for (i, x) in w.iter().enumerate() {
678            s[i * 2 + (1 - n % 2)] = x.clone();
679        }
680        let len = 2 * d + 1;
681        let ts = C::transform(s.prefix(len).data, len);
682        mq.reversed().middle_product(&ts, len).prefix(d + 1)
683    }
684    /// x^n mod self
685    pub fn pow_mod(self, n: usize) -> Self {
686        let d = self.length() - 1;
687        let q = self.reversed();
688        let u = q.clone().bostan_mori_msb(n);
689        let mut f = (u * q).prefix(d).reversed();
690        f.trim_tail_zeros();
691        f
692    }
693    fn middle_product(self, other: &C::F, deg: usize) -> Self {
694        let n = self.length();
695        let mut s = C::transform(self.reversed().data, deg);
696        C::multiply(&mut s, other);
697        Self::from_vec((C::inverse_transform(s, deg))[n - 1..].to_vec())
698    }
699    pub fn multipoint_evaluation(self, points: &[T]) -> Vec<T> {
700        let n = points.len();
701        if n <= 32 {
702            return points.iter().map(|p| self.eval(p.clone())).collect();
703        }
704        let mut subproduct_tree = Vec::with_capacity(n * 2);
705        subproduct_tree.resize_with(n, Zero::zero);
706        for x in points {
707            subproduct_tree.push(Self::from_vec(vec![-x.clone(), T::one()]));
708        }
709        for i in (1..n).rev() {
710            subproduct_tree[i] = &subproduct_tree[i * 2] * &subproduct_tree[i * 2 + 1];
711        }
712        let mut uptree_t = Vec::with_capacity(n * 2);
713        uptree_t.resize_with(1, Zero::zero);
714        subproduct_tree.reverse();
715        subproduct_tree.pop();
716        let m = self.length();
717        let v = subproduct_tree.pop().unwrap().reversed().resized(m);
718        let s = C::transform(self.data, m * 2);
719        uptree_t.push(v.inv(m).middle_product(&s, m * 2).resized(n).reversed());
720        for i in 1..n {
721            let subl = subproduct_tree.pop().unwrap();
722            let subr = subproduct_tree.pop().unwrap();
723            let (dl, dr) = (subl.length(), subr.length());
724            let len = dl.max(dr) + uptree_t[i].length();
725            let s = C::transform(uptree_t[i].data.to_vec(), len);
726            uptree_t.push(subr.middle_product(&s, len).prefix(dl));
727            uptree_t.push(subl.middle_product(&s, len).prefix(dr));
728        }
729        uptree_t[n..]
730            .iter()
731            .map(|u| u.data.first().cloned().unwrap_or_else(Zero::zero))
732            .collect()
733    }
734    pub fn product_all<I>(iter: I, deg: usize) -> Self
735    where
736        I: IntoIterator<Item = Self>,
737    {
738        let mut heap: BinaryHeap<_> = iter
739            .into_iter()
740            .map(|f| PartialIgnoredOrd(Reverse(f.length()), f))
741            .collect();
742        while let Some(PartialIgnoredOrd(_, x)) = heap.pop() {
743            if let Some(PartialIgnoredOrd(_, y)) = heap.pop() {
744                let z = (x * y).prefix(deg);
745                heap.push(PartialIgnoredOrd(Reverse(z.length()), z));
746            } else {
747                return x;
748            }
749        }
750        Self::one()
751    }
752    pub fn sum_all_rational<I>(iter: I, deg: usize) -> (Self, Self)
753    where
754        I: IntoIterator<Item = (Self, Self)>,
755    {
756        let mut heap: BinaryHeap<_> = iter
757            .into_iter()
758            .map(|(f, g)| PartialIgnoredOrd(Reverse(f.length().max(g.length())), (f, g)))
759            .collect();
760        while let Some(PartialIgnoredOrd(_, (xa, xb))) = heap.pop() {
761            if let Some(PartialIgnoredOrd(_, (ya, yb))) = heap.pop() {
762                let zb = (&xb * &yb).prefix(deg);
763                let za = (xa * yb + ya * xb).prefix(deg);
764                heap.push(PartialIgnoredOrd(
765                    Reverse(za.length().max(zb.length())),
766                    (za, zb),
767                ));
768            } else {
769                return (xa, xb);
770            }
771        }
772        (Self::zero(), Self::one())
773    }
774    pub fn kth_term_of_linearly_recurrence(self, a: Vec<T>, k: usize) -> T
775    where
776        C: NttReuse<T = Vec<T>>,
777    {
778        if let Some(x) = a.get(k) {
779            return x.clone();
780        }
781        let p = (Self::from_vec(a).prefix(self.length() - 1) * &self).prefix(self.length() - 1);
782        p.bostan_mori(self, k)
783    }
784    pub fn kth_term(a: Vec<T>, k: usize) -> T
785    where
786        C: NttReuse<T = Vec<T>>,
787    {
788        if let Some(x) = a.get(k) {
789            return x.clone();
790        }
791        Self::from_vec(berlekamp_massey(&a)).kth_term_of_linearly_recurrence(a, k)
792    }
793    /// sum_i a_i exp(b_i x)
794    pub fn linear_sum_of_exp<I, F>(iter: I, deg: usize, mut inv_fact: F) -> Self
795    where
796        I: IntoIterator<Item = (T, T)>,
797        F: FnMut(usize) -> T,
798    {
799        let (p, q) = Self::sum_all_rational(
800            iter.into_iter()
801                .map(|(a, b)| (Self::from_vec(vec![a]), Self::from_vec(vec![T::one(), -b]))),
802            deg,
803        );
804        let mut f = (p * q.inv(deg)).prefix(deg);
805        for i in 0..f.length() {
806            f[i] *= inv_fact(i);
807        }
808        f
809    }
810    /// sum_i (a_i x)^j
811    pub fn sum_of_powers<I>(iter: I, deg: usize) -> Self
812    where
813        I: IntoIterator<Item = T>,
814    {
815        let mut n = T::zero();
816        let prod = Self::product_all(
817            iter.into_iter().map(|a| {
818                n += T::one();
819                Self::from_vec(vec![T::one(), -a])
820            }),
821            deg,
822        );
823        (-prod.log(deg).diff() << 1) + Self::from_vec(vec![n])
824    }
825
826    pub fn power_projection(&self, w: &[T], m: usize) -> Self
827    where
828        C: NttReuse<T = Vec<T>>,
829    {
830        if w.is_empty() {
831            return Self::zeros(m);
832        }
833        if m <= 1 {
834            return Self::from_vec(vec![w[0].clone(); m]);
835        }
836
837        let n0 = w.len();
838        let mut n = n0.next_power_of_two();
839        let mut f = self.prefix_ref(n);
840        f.resize(n);
841
842        let base = n * 2;
843        let mut p_flat = vec![T::zero(); base];
844        for (i, wi) in w.iter().enumerate() {
845            p_flat[n - 1 - i] = wi.clone();
846        }
847        let mut q_flat = vec![T::zero(); base * 2];
848        q_flat[0] = T::one();
849        let q_offset = base;
850        for (i, fi) in f.iter().enumerate() {
851            q_flat[q_offset + i] = -fi.clone();
852        }
853        let mut py = 1usize;
854        let mut qy = 2usize;
855
856        let y_limit = m;
857        while n > 1 {
858            let base = n * 2;
859            let len_p = base * py;
860            let len_q = base * qy;
861            let len = (len_p + len_q - 1).max(len_q + len_q - 1);
862            let len_pot = len.max(1).next_power_of_two();
863            let half = len_pot / 2;
864
865            let p_fft = C::transform(p_flat, len);
866            let q_fft = C::transform(q_flat, len);
867            let pr_fft = C::odd_mul_normal_neg(&p_fft, &q_fft);
868            let qr_fft = C::even_mul_normal_neg(&q_fft, &q_fft);
869            let mut pr = C::inverse_transform(pr_fft, half);
870            let mut qr = C::inverse_transform(qr_fft, half);
871
872            let new_py = (py + qy - 1).min(y_limit);
873            let new_qy = (qy + qy - 1).min(y_limit);
874            let new_base = n;
875            let need_p = new_base * new_py;
876            if pr.len() < need_p {
877                pr.resize_with(need_p, T::zero);
878            } else if pr.len() > need_p {
879                pr.truncate(need_p);
880            }
881            let need_q = new_base * new_qy;
882            if qr.len() < need_q {
883                qr.resize_with(need_q, T::zero);
884            } else if qr.len() > need_q {
885                qr.truncate(need_q);
886            }
887
888            let n2 = n / 2;
889            if n2 < new_base {
890                for y in 0..new_py {
891                    let start = y * new_base + n2;
892                    let end = y * new_base + new_base;
893                    for v in pr[start..end].iter_mut() {
894                        *v = T::zero();
895                    }
896                }
897                for y in 0..new_qy {
898                    let start = y * new_base + n2;
899                    let end = y * new_base + new_base;
900                    for v in qr[start..end].iter_mut() {
901                        *v = T::zero();
902                    }
903                }
904            }
905
906            p_flat = pr;
907            q_flat = qr;
908            py = new_py;
909            qy = new_qy;
910            n = n2;
911        }
912
913        let base = 2;
914        let mut p_y = Vec::with_capacity(py);
915        for y in 0..py {
916            p_y.push(p_flat[base * y].clone());
917        }
918        let mut q_y = Vec::with_capacity(qy);
919        for y in 0..qy {
920            q_y.push(q_flat[base * y].clone());
921        }
922        (Self::from_vec(p_y) * Self::from_vec(q_y).inv(m)).prefix(m)
923    }
924
925    pub fn compositional_inverse(&self, deg: usize) -> Self
926    where
927        C: NttReuse<T = Vec<T>>,
928    {
929        if deg == 0 {
930            return Self::zero();
931        }
932        if deg == 1 {
933            return Self::from_vec(vec![T::zero()]);
934        }
935        debug_assert!(self[0].is_zero());
936        debug_assert!(!self[1].is_zero());
937
938        let mut f = self.prefix_ref(deg);
939        f.resize(deg);
940        let c = f[1].clone();
941        f /= c.clone();
942
943        let mut w = vec![T::zero(); deg];
944        w[deg - 1] = T::one();
945        let s = f.power_projection(&w, deg);
946
947        let n = deg - 1;
948        let n_t = T::from(n);
949        let mut h = vec![T::zero(); n];
950        for i in 1..=n {
951            h[n - i] = s[i].clone() * &n_t / T::from(i);
952        }
953
954        let h_fps = Self::from_vec(h);
955        let inv_n = T::one() / n_t;
956        let mut t = h_fps.log(n);
957        t *= -inv_n;
958        let g_over_x = t.exp(n);
959        let mut g = (g_over_x << 1).prefix(deg);
960
961        let inv_c = T::one() / c;
962        let mut pow = T::one();
963        for coef in g.iter_mut() {
964            *coef *= pow.clone();
965            pow *= inv_c.clone();
966        }
967        g
968    }
969    /// f(x) <- f(x + a)
970    pub fn taylor_shift(mut self, a: T) -> Self {
971        let f = T::memorized_factorial(self.length());
972        let n = self.length();
973        for i in 0..n {
974            self.data[i] *= T::memorized_fact(&f)[i].clone();
975        }
976        self.data.reverse();
977        let mut b = a.clone();
978        let mut g = Self::from_vec(T::memorized_inv_fact(&f)[..n].to_vec());
979        for i in 1..n {
980            g[i] *= b.clone();
981            b *= a.clone();
982        }
983        self *= g;
984        self.truncate(n);
985        self.data.reverse();
986        for i in 0..n {
987            self.data[i] *= T::memorized_inv_fact(&f)[i].clone();
988        }
989        self
990    }

Dyn Compatibility§

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementors§