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merge latest lieonn.
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@bitsofcotton
bitsofcotton authored Jun 22, 2024
1 parent 490f5f0 commit 3a60fce
Showing 1 changed file with 108 additions and 131 deletions.
239 changes: 108 additions & 131 deletions lieonn.hh
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Original file line number Diff line number Diff line change
Expand Up @@ -63,8 +63,8 @@ using std::getline;
// Double int to new int class.
template <typename T, int bits> class DUInt {
public:
inline DUInt() { assert(0 < bits && ! (bits & 3)); }
inline DUInt(const int& src) {
inline DUInt(const int& src = 0) {
assert(0 < bits && ! (bits & 3));
const auto abssrc(src < 0 ? - src : src);
e[0] = T(abssrc);
e[1] ^= e[1];
Expand Down Expand Up @@ -1173,11 +1173,11 @@ template <typename T, typename W, int bits, typename U> static inline SimpleFloa
template <typename T> class Complex {
public:
inline Complex() { ; }
inline Complex(const Complex<T>& s) { *this = s; }
inline Complex(Complex<T>&& s) { *this = s; }
inline Complex(const T& real, const T& imag = T(int(0))) {
_real = real; _imag = imag;
}
inline Complex(const Complex<T>& s) { *this = s; }
inline Complex(Complex<T>&& s) { *this = s; }
inline Complex(T&& real) {
const static T zero(0);
_real = move(real);
Expand Down Expand Up @@ -2753,8 +2753,12 @@ template <typename T> static inline T revertProgramInvariant(const pair<T, T>& i

template <typename T> class idFeeder {
public:
inline idFeeder() { full = false; t = 0;}
inline idFeeder(const int& size) { res.resize(size); res.O(); full = false; t = 0; }
inline idFeeder(const int& size = 1) {
res.resize(size);
res.O();
full = false;
t = 0;
}
inline ~idFeeder() { ; }
inline const SimpleVector<T>& next(const T& in) {
if(t < res.size())
Expand Down Expand Up @@ -3124,8 +3128,7 @@ template <typename T> static inline vector<pair<vector<SimpleVector<T> >, vector

template <typename T> class P012L {
public:
inline P012L() { varlen = 0; }
inline P012L(const int& var, const int& step = 1) {
inline P012L(const int& var = 4, const int& step = 1) {
assert(1 < var && 0 < step);
varlen = var;
this->step = step;
Expand Down Expand Up @@ -3483,8 +3486,7 @@ public:
// cf. bitsofcotton/randtools .
template <typename T, bool nonlinear = true> class P01 {
public:
inline P01() { varlen = 0; }
inline P01(const int& var, const int& step = 1) {
inline P01(const int& var = 4, const int& step = 1) {
assert(0 < var && 0 < step);
this->varlen = var;
this->step = step;
Expand All @@ -3501,7 +3503,7 @@ public:
SimpleMatrix<T> invariants(3, nonlinear ? varlen + 2 : varlen);
invariants.O();
for(int i0 = 0; i0 < invariants.rows(); i0 ++) {
SimpleMatrix<T> toeplitz((in.size() - varlen - step + 2 - 1)
SimpleMatrix<T> toeplitz(in.size() - varlen - step + 2
- invariants.rows() + 1, invariants.cols());
for(int i = i0; i < toeplitz.rows() + i0; i ++) {
auto work(in.subVector(i, varlen));
Expand Down Expand Up @@ -3575,10 +3577,12 @@ public:
T M;
};

template <typename T, typename P> class Pprogression {
// N.B. this class feeds new states into predictor as a new dimension of
// linear sum.
template <typename T, typename P, bool lstart = true> class Pprogression {
public:
inline Pprogression() { ; }
inline Pprogression(const P& p, const int& loop0 = 1) {
inline Pprogression(const P& p, const int& loop0 = 1, const int& istat = 3) {
assert(loop0);
const auto loop(abs(loop0));
(this->p).resize(loop);
Expand All @@ -3598,6 +3602,7 @@ public:
for(int i = 0; i < loop; i ++)
bb.emplace_back(idFeeder<T>(addp ? i + 1 : 1));
t ^= t;
this->istat = istat;
}
inline ~Pprogression() { ; }
inline const T& progression(const SimpleVector<T>& h, const int& idx, const int& count) {
Expand All @@ -3615,11 +3620,16 @@ public:
const auto& hh(h.next(in));
auto M(zero);
if(! h.full) return M;
for(int i = 0; i < p.size(); i ++)
bb[i].next(p[i][t % p[i].size()].next(progression(hh, hh.size() - 1, i)));
for(int i = 0; i < p.size(); i ++) {
if(! lstart || (p.size() - 1 - i) * istat <= t)
bb[i].next(p[i][t % p[i].size()].next(
progression(hh, hh.size() - 1, i)));
}
if(! lstart || p.size() * istat <= t)
for(int i = 0; i < p.size(); i ++)
M += bb[i].res[0] + (i && addp ?
progression(hh, hh.size() - 2, i - 1) : zero);
t ++;
for(int i = 0; i < p.size(); i ++)
M += bb[i].res[0] + (i && addp ? progression(hh, hh.size() - 2, i - 1) : zero);
return addp ? M /= T(int(p.size())) : M;
}
vector<vector<P> > p;
Expand All @@ -3628,6 +3638,7 @@ public:
vector<vector<T> > eh;
vector<idFeeder<T> > bb;
int t;
int istat;
bool addp;
};

Expand Down Expand Up @@ -3742,9 +3753,8 @@ template <typename T> class Decompose {
public:
typedef SimpleVector<T> Vec;
typedef SimpleMatrix<T> Mat;
inline Decompose() { size = 0; }
inline Decompose(const int& size) {
assert(0 < size);
inline Decompose(const int& size = 0) {
assert(0 <= size);
this->size = size;
}
inline ~Decompose() { ; }
Expand Down Expand Up @@ -4212,7 +4222,7 @@ template <typename T> static inline T getImgPt(const T& y, const T& h) {
return yy % h;
}

template <typename T> pair<vector<SimpleVector<T> >, vector<SimpleVector<T> > > predv(const vector<SimpleVector<T> >& in) {
template <typename T> pair<SimpleVector<T>, SimpleVector<T> > predv(const vector<SimpleVector<T> >& in) {
// N.B. we need to initialize p0 vector.
SimpleVector<T> init(3);
for(int i = 0; i < init.size(); i ++)
Expand All @@ -4226,83 +4236,44 @@ template <typename T> pair<vector<SimpleVector<T> >, vector<SimpleVector<T> > >
for(int i = 0; i < in.size(); i ++) {
seconds[i] = makeProgramInvariant<T>(in[i], - T(int(1)), true).second;
}
// N.B. p210 works even when we're jammed condition, however, we suppose
// there's no jammer on us nor no noise nor no special stream condition.
const int p0(in.size() - (5 * 5 - 4 + 2) - 1);
vector<SimpleVector<T> > p;
p.resize(p0 + 1, SimpleVector<T>(in[0].size()).O());
auto q(p);
auto pfsz(p0);
// N.B. we need Pprogression<..., P01...> with maximum range.
const int p0(in.size() / (5 * 5 - 4 + 2));
SimpleVector<T> p;
SimpleVector<T> q;
p.resize(in[0].size());
q.resize(in[0].size());
p.O();
q.O();
#if defined(_OPENMP)
#pragma omp parallel for schedule(static, 1)
#endif
for(int j = 0; j < in[0].size(); j ++) {
cerr << j << " / " << in[0].size() << endl;
// N.B. our computer is infected, so out of the control could tell us
// predict and destroy by this way is correct ones.
// this is from arc4random implant test around p[012] results.
// so without p[0], q[0] as output average, we cannot get better
// from the tests.
// however, the arc4random implant can returns false positive for us.
// also we need to implant the input data itself into source code
// when not only pipe but also the file io is infected condition.
idFeeder<T> pf(in.size());
idFeeder<T> pb(in.size());
Pprogression<T, PBond<T, P01<T> > > pf(PBond<T, P01<T> >(P01<T>(4), 5 * 5 - 4 + 2), p0, 5 * 5 - 4 + 2);
Pprogression<T, PBond<T, P01<T> > > pb(PBond<T, P01<T> >(P01<T>(4), 5 * 5 - 4 + 2), p0, 5 * 5 - 4 + 2);
for(int i = 0; i < in.size(); i ++) {
pf.next(makeProgramInvariantPartial<T>(in[i][j], seconds[i], true));
pb.next(makeProgramInvariantPartial<T>(in[in.size() - i - 1][j], seconds[seconds.size() - i - 1], true));
}
for(int i = 0; i < p.size(); i ++) {
if(i) {
p[i][j] = P01<T>(4, i).next(pf.res);
q[i][j] = P01<T>(4, i).next(pb.res);
} else {
const auto& p0f(pf.res);
const auto& q0f(pb.res);
p[0][j] = q[0][j] = T(int(0));
for(int k = 1; k < p0f.size(); k ++) {
p[0][j] += p0f[k];
q[0][j] += q0f[k];
}
p[0][j] = - p[0][j];
q[0][j] = - q[0][j];
}
p[j] = pf.next(makeProgramInvariantPartial<T>(in[i][j], seconds[i], true));
q[j] = pb.next(makeProgramInvariantPartial<T>(in[in.size() - i - 1][j], seconds[seconds.size() - i - 1], true));
}
}
idFeeder<T> pf(in.size());
idFeeder<T> pb(in.size());
Pprogression<T, PBond<T, P01<T> > > pf(PBond<T, P01<T> >(P01<T>(4), 5 * 5 - 4 + 2), p0, 5 * 5 - 4 + 2);
Pprogression<T, PBond<T, P01<T> > > pb(PBond<T, P01<T> >(P01<T>(4), 5 * 5 - 4 + 2), p0, 5 * 5 - 4 + 2);
T rp;
T rq;
for(int i = 0; i < in.size(); i ++) {
pf.next(seconds[i]);
pb.next(seconds[seconds.size() - 1 - i]);
}
for(int i = 0; i < p.size(); i ++) {
T rp;
T rq;
if(i) {
rp = P01<T>(4, i).next(pf.res);
rq = P01<T>(4, i).next(pb.res);
} else {
const auto& p0f(pf.res);
const auto& q0f(pb.res);
rp = rq = T(int(0));
for(int k = 1; k < p0f.size(); k ++) {
rp += p0f[k];
rq += q0f[k];
}
rp = - rp;
rq = - rq;
}
for(int j = 0; j < p[i].size(); j ++) {
p[i][j] = p[i][j] == T(int(0)) || rp == T(int(0)) ? T(int(1)) / T(int(2))
: revertProgramInvariant<T>(make_pair(p[i][j], rp), true);
q[i][j] = q[i][j] == T(int(0)) || rp == T(int(0)) ? T(int(1)) / T(int(2))
: revertProgramInvariant<T>(make_pair(q[i][j], rq), true);
}
rp = pf.next(seconds[i]);
rq = pb.next(seconds[seconds.size() - 1 - i]);
}
for(int j = 0; j < p.size(); j ++) {
p[j] = p[j] == T(int(0)) || rp == T(int(0)) ? T(int(1)) / T(int(2))
: revertProgramInvariant<T>(make_pair(p[j], rp), true);
q[j] = q[j] == T(int(0)) || rp == T(int(0)) ? T(int(1)) / T(int(2))
: revertProgramInvariant<T>(make_pair(q[j], rq), true);
}
return make_pair(move(p), move(q));
}

template <typename T> pair<vector<vector<SimpleVector<T> > >, vector<vector<SimpleVector<T> > > > predVec(const vector<vector<SimpleVector<T> > >& in0) {
template <typename T> pair<vector<SimpleVector<T> >, vector<SimpleVector<T> > > predVec(const vector<vector<SimpleVector<T> > >& in0) {
assert(in0.size() && in0[0].size() && in0[0][0].size());
vector<SimpleVector<T> > in;
in.resize(in0.size());
Expand All @@ -4316,23 +4287,19 @@ template <typename T> pair<vector<vector<SimpleVector<T> > >, vector<vector<Simp
}
}
const auto p(predv<T>(in));
pair<vector<vector<SimpleVector<T> > >, vector<vector<SimpleVector<T> > > > res;
res.first.resize( p.first.size() );
res.second.resize(p.second.size());
for(int i = 0; i < p.first.size(); i ++) {
res.first[i].resize(in0[0].size());
res.second[i].resize(in0[0].size());
for(int j = 0; j < in0[0].size(); j ++) {
res.first[i][j] =
p.first[i].subVector(in0[0][0].size() * j, in0[0][0].size());
res.second[i][j] =
p.second[i].subVector(in0[0][0].size() * j, in0[0][0].size());
}
pair<vector<SimpleVector<T> >, vector<SimpleVector<T> > > res;
res.first.resize(in0[0].size());
res.second.resize(in0[0].size());
for(int j = 0; j < in0[0].size(); j ++) {
res.first[j] =
p.first.subVector(in0[0][0].size() * j, in0[0][0].size());
res.second[j] =
p.second.subVector(in0[0][0].size() * j, in0[0][0].size());
}
return res;
}

template <typename T> pair<vector<vector<SimpleMatrix<T> > >, vector<vector<SimpleMatrix<T> > > > predMat(const vector<vector<SimpleMatrix<T> > >& in0) {
template <typename T> pair<vector<SimpleMatrix<T> >, vector<SimpleMatrix<T> > > predMat(const vector<vector<SimpleMatrix<T> > >& in0) {
assert(in0.size() && in0[0].size() && in0[0][0].rows() && in0[0][0].cols());
vector<SimpleVector<T> > in;
in.resize(in0.size());
Expand All @@ -4348,31 +4315,27 @@ template <typename T> pair<vector<vector<SimpleMatrix<T> > >, vector<vector<Simp
}
}
const auto p(predv<T>(in));
pair<vector<vector<SimpleMatrix<T> > >, vector<vector<SimpleMatrix<T> > > > res;
res.first.resize( p.first.size() );
res.second.resize(p.second.size());
for(int i = 0; i < p.first.size(); i ++) {
res.first[i].resize(in0[i].size());
res.second[i].resize(in0[i].size());
for(int j = 0; j < res.first[i].size(); j ++) {
res.first[i][j].resize(in0[0][0].rows(), in0[0][0].cols());
res.second[i][j].resize(in0[0][0].rows(), in0[0][0].cols());
for(int k = 0; k < in0[0][0].rows(); k ++) {
res.first[i][j].row(k) =
p.first[i].subVector(
j * in0[0][0].rows() * in0[0][0].cols() + k * in0[0][0].cols(),
in0[0][0].cols());
res.second[i][j].row(k) =
p.second[i].subVector(
j * in0[0][0].rows() * in0[0][0].cols() + k * in0[0][0].cols(),
in0[0][0].cols());
}
pair<vector<SimpleMatrix<T> >, vector<SimpleMatrix<T> > > res;
res.first.resize(in0[0].size());
res.second.resize(in0[0].size());
for(int j = 0; j < res.first.size(); j ++) {
res.first[j].resize(in0[0][0].rows(), in0[0][0].cols());
res.second[j].resize(in0[0][0].rows(), in0[0][0].cols());
for(int k = 0; k < in0[0][0].rows(); k ++) {
res.first[j].row(k) =
p.first.subVector(
j * in0[0][0].rows() * in0[0][0].cols() + k * in0[0][0].cols(),
in0[0][0].cols());
res.second[j].row(k) =
p.second.subVector(
j * in0[0][0].rows() * in0[0][0].cols() + k * in0[0][0].cols(),
in0[0][0].cols());
}
}
return res;
}

template <typename T> pair<vector<SimpleSparseTensor<T> >, vector<SimpleSparseTensor<T> > > predSTen(const vector<SimpleSparseTensor<T> >& in0, const vector<int>& idx) {
template <typename T> pair<SimpleSparseTensor<T>, SimpleSparseTensor<T> > predSTen(const vector<SimpleSparseTensor<T> >& in0, const vector<int>& idx) {
assert(idx.size() && in0.size());
// N.B. we don't do input scaling.
// N.B. the data we target is especially string stream corpus.
Expand Down Expand Up @@ -4405,19 +4368,16 @@ template <typename T> pair<vector<SimpleSparseTensor<T> >, vector<SimpleSparseTe
}
auto p(predv<T>(in));
in.resize(0);
pair<vector<SimpleSparseTensor<T> >, vector<SimpleSparseTensor<T> > > res;
res.first.resize( p.first.size() );
res.second.resize(p.second.size());
for(int i = 0; i < p.first.size(); i ++)
for(int j = 0, cnt = 0; j < idx.size(); j ++)
for(int k = 0; k < idx.size(); k ++)
for(int m = 0; m < idx.size(); m ++) {
if(binary_search(absent.begin(), absent.end(),
make_pair(j, make_pair(k, m))))
continue;
res.first[i][idx[j]][idx[k]][idx[m]] = p.first[i][cnt] * T(int(2)) - T(int(1));
res.second[i][idx[j]][idx[k]][idx[m]] = p.second[i][cnt ++] * T(int(2)) - T(int(1));
}
pair<SimpleSparseTensor<T>, SimpleSparseTensor<T> > res;
for(int j = 0, cnt = 0; j < idx.size(); j ++)
for(int k = 0; k < idx.size(); k ++)
for(int m = 0; m < idx.size(); m ++) {
if(binary_search(absent.begin(), absent.end(),
make_pair(j, make_pair(k, m))))
continue;
res.first[idx[j]][idx[k]][idx[m]] = p.first[cnt] * T(int(2)) - T(int(1));
res.second[idx[j]][idx[k]][idx[m]] = p.second[cnt ++] * T(int(2)) - T(int(1));
}
return res;
}

Expand Down Expand Up @@ -4474,6 +4434,23 @@ template <typename T> static inline vector<SimpleMatrix<T> > xyz2rgb(const vecto
return rgb;
}

static const vector<int>& pnTinySingle(const int& upper = 1) {
static vector<int> pn;
if(! pn.size()) pn.push_back(2);
pn.reserve(upper);
for(int i = pn.size(); i < upper; i ++) {
for(int j = pn[pn.size() - 1] + 1; 0 <= j; j ++) {
for(int k = 0; k < pn.size(); k ++)
if(! (j % pn[k])) goto next_pn;
pn.push_back(j);
break;
next_pn:
;
}
}
return pn;
}

#define _SIMPLELIN_
#endif

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