setfunc/subset_convolution.hpp

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• Last update: 2023-09-23 23:33:32+09:00
• Include: #include "setfunc/subset_convolution.hpp"

Depends on

• setfunc/ranked_zeta.hpp

Required by

• linalg/hafnian.hpp
• setfunc/sps_exp.hpp
• setfunc/transposed_sps_composition.hpp

Verified with

• test/library_checker/convolution/subset_convolution.test.cpp
• test/library_checker/math/powproj_sps.test.cpp
• test/library_checker/math/sps_exp.test.cpp
• test/library_checker/matrix/hafnian_of_matrix.test.cpp
• test/yukicoder/2507.test.cpp
• test_atcoder/abc236h.test.cpp
• test_atcoder/abc253h.test.cpp
• test_atcoder/arc105.test.cpp

Code

#pragma once

#include "setfunc/ranked_zeta.hpp"


template <typename T, int LIM = 20>
vc<T> subset_convolution_square(const vc<T>& A) {
  auto RA = ranked_zeta<T, LIM>(A);
  int n = topbit(len(RA));
  FOR(s, len(RA)) {
    auto& f = RA[s];
    FOR_R(d, n + 1) {
      T x = 0;
      FOR(i, d + 1) x += f[i] * f[d - i];
      f[d] = x;
    }
  }
  return ranked_mobius<T, LIM>(RA);
}

template <typename T, int LIM = 20>
vc<T> subset_convolution(const vc<T>& A, const vc<T>& B) {
  if (A == B) return subset_convolution_square(A);
  auto RA = ranked_zeta<T, LIM>(A);
  auto RB = ranked_zeta<T, LIM>(B);
  int n = topbit(len(RA));
  FOR(s, len(RA)) {
    auto &f = RA[s], &g = RB[s];
    FOR_R(d, n + 1) {
      T x = 0;
      FOR(i, d + 1) x += f[i] * g[d - i];
      f[d] = x;
    }
  }
  return ranked_mobius<T, LIM>(RA);
}

#line 2 "setfunc/subset_convolution.hpp"

#line 2 "setfunc/ranked_zeta.hpp"

template <typename T, int LIM>
vc<array<T, LIM + 1>> ranked_zeta(const vc<T>& f) {
  int n = topbit(len(f));
  assert(n <= LIM);
  assert(len(f) == 1 << n);
  vc<array<T, LIM + 1>> Rf(1 << n);
  for (int s = 0; s < (1 << n); ++s) Rf[s][popcnt(s)] = f[s];
  for (int i = 0; i < n; ++i) {
    int w = 1 << i;
    for (int p = 0; p < (1 << n); p += 2 * w) {
      for (int s = p; s < p + w; ++s) {
        int t = s | 1 << i;
        for (int d = 0; d <= n; ++d) Rf[t][d] += Rf[s][d];
      }
    }
  }
  return Rf;
}

template <typename T, int LIM>
vc<T> ranked_mobius(vc<array<T, LIM + 1>>& Rf) {
  int n = topbit(len(Rf));
  assert(len(Rf) == 1 << n);
  for (int i = 0; i < n; ++i) {
    int w = 1 << i;
    for (int p = 0; p < (1 << n); p += 2 * w) {
      for (int s = p; s < p + w; ++s) {
        int t = s | 1 << i;
        for (int d = 0; d <= n; ++d) Rf[t][d] -= Rf[s][d];
      }
    }
  }
  vc<T> f(1 << n);
  for (int s = 0; s < (1 << n); ++s) f[s] = Rf[s][popcnt(s)];
  return f;
}
#line 4 "setfunc/subset_convolution.hpp"

template <typename T, int LIM = 20>
vc<T> subset_convolution_square(const vc<T>& A) {
  auto RA = ranked_zeta<T, LIM>(A);
  int n = topbit(len(RA));
  FOR(s, len(RA)) {
    auto& f = RA[s];
    FOR_R(d, n + 1) {
      T x = 0;
      FOR(i, d + 1) x += f[i] * f[d - i];
      f[d] = x;
    }
  }
  return ranked_mobius<T, LIM>(RA);
}

template <typename T, int LIM = 20>
vc<T> subset_convolution(const vc<T>& A, const vc<T>& B) {
  if (A == B) return subset_convolution_square(A);
  auto RA = ranked_zeta<T, LIM>(A);
  auto RB = ranked_zeta<T, LIM>(B);
  int n = topbit(len(RA));
  FOR(s, len(RA)) {
    auto &f = RA[s], &g = RB[s];
    FOR_R(d, n + 1) {
      T x = 0;
      FOR(i, d + 1) x += f[i] * g[d - i];
      f[d] = x;
    }
  }
  return ranked_mobius<T, LIM>(RA);
}

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