// Get multiple layers of a Benes permutation network. Returns in out[i][j]
// the shift amount to move item j in the i'th layer. Also isID[i]=true if
// the i'th layer is the identity (i.e., contains only 0 shift amounts).
void ColPerm::getBenesShiftAmounts(Vec<Permut>& out, Vec<bool>& isID,
const Vec<long>& benesLvls) const
{
// Go over the columns one by one. For each column extract the columns
// permutation, prepare a Benes network for it, and then for every layer
// compute the shift amounts for this columns.
long n = getDim(dim); // the permutations are over [0,n-1]
// Allocate space
out.SetLength(benesLvls.length());
isID.SetLength(benesLvls.length());
for (long k=0; k<benesLvls.length(); k++) {
out[k].SetLength(getSize());
isID[k] = true;
}
Vec<long> col;
col.SetLength(n);
for (long slice_index = 0; slice_index < numSlices(dim); slice_index++) {
ConstCubeSlice<long> slice(*this, slice_index, dim);
for (long col_index = 0; col_index < slice.numCols(); col_index++) {
getHyperColumn(col, slice, col_index);
GeneralBenesNetwork net(col); // build a Benes network for this column
// Sanity checks: width of network == n,
// and sum of benesLvls entries == # of levels
assert(net.getSize()==n);
{long sum=0;
for (long k=0; k<benesLvls.length(); k++) sum+=benesLvls[k];
assert(net.getNumLevels()==sum);
}
// Compute the layers of the collapased network for this column
for (long lvl=0,k=0; k<benesLvls.length(); lvl += benesLvls[k], k++) {
// Returns in col the shift amounts for this layer in the network,
// restricted to this column. Also returns true if the returned
// permutation is the idendity, false otherwise.
bool id = collapseBenesLevels(col, net, lvl, benesLvls[k]);
isID[k] = isID[k] && id;
CubeSlice<long> oslice(out[k], getSig());
CubeSlice<long> osubslice(oslice, slice_index, dim);
setHyperColumn(col, osubslice, col_index);
} // next collapsed layer
} // next column
} // next slice
}
// powVec[d] = m_d = p_d^{e_d}
// computes multiEvalPoints[d] as a vector of length phi(m_d)
// containing base^{(m/m_d) j} for j in Z_{m_d}^*
void computeMultiEvalPoints(Vec< Vec<zz_p> >& multiEvalPoints,
const zz_p& base,
long m,
const Vec<long>& powVec,
const Vec<long>& phiVec)
{
long k = powVec.length();
multiEvalPoints.SetLength(k);
for (long d = 0; d < k; d++) {
long m_d = powVec[d];
long phi_d = phiVec[d];
long count = 0;
zz_p pow = conv<zz_p>(1);
zz_p mult = power(base, m/m_d);
multiEvalPoints[d].SetLength(phi_d);
for (long j = 0; j < m_d; j++) {
if (GCD(j, m_d) == 1) {
multiEvalPoints[d][count] = pow;
count++;
}
pow = pow * mult;
}
}
}
void IndexCalc::GenerateBase(long quant){
Vec<ZZ> numbersTable;
numbersTable.SetLength(quant);
for(long i = 2; i < quant; ++i)
numbersTable[i] = conv<ZZ>("0");
for (long i = 2; i*i < quant; ++i ) // przeszukuj liczby od 2 do sqrt(n), 0 i 1 nie s¹ liczbami pierwszymi
{
if (numbersTable[i] == conv<ZZ>("1")) // je¿eli dana liczba jest ju¿ wykreœlona
continue; // to przejdŸ do kolejnej
for (long j = 2*i ; j < quant; j += i){ // przejdŸ od liczby 2 * i do n przesuwaj¹c siê o i
numbersTable[j] = conv<ZZ>("1"); // i ka¿d¹ z nich usuwaj ze zbioru
}
}
cout << "Liczby pierwsze z przedzia³u od 2 do " << quant << ":" << endl;
long j = 0;
for (int i = 2; i < quant; i++) // przeszukaj liczby od 2 do n
if (numbersTable[i] == conv<ZZ>("0")){ // jeœli liczba nie zosta³a usuniêta ze zbioru
j++;
primeNumbers.SetLength(j);
primeNumbers[j-1] = i;
}
}
// Compute the cost for all (n choose 2) possible ways to collapse levels.
// For j in [0..nlev-i) tab[i][j] is the cost of collapsing levels i..i+j.
// I.e., how many different shift amounts would we need to implement for
// a permutation-network-layer constructed by collapsing these levels.
void buildBenesCostTable(long n, long k, bool good, Vec< Vec<long> >& tab)
{
long nlev = 2*k-1;
tab.SetLength(nlev);
for (long i = 0; i < nlev; i++) tab[i].SetLength(nlev-i);
Vec<bool> aux_vec;
aux_vec.SetLength(2*n-1);
bool *aux = &aux_vec[n-1];
for (long i = 0; i < 2*n-1; i++) aux_vec[i] = false;
for (long i = 0; i < nlev; i++) {
list<long> x;
x.push_front(0L);
for (long j = 0; j < nlev-i; j++) {
long shamt = GeneralBenesNetwork::shamt(n, k, i+j);
// The shift amount for this level
addOffset(x, shamt, n, aux);
if (good)
tab[i][j] = reducedCount(x, n, aux) - 1;
else
tab[i][j] = x.size() - 1;
// FIXME: Alternative Impl:
// Replace the 5 lines above by
// addOffset(x, shamt, n, aux, good);
// tab[i][j] = x.size() - 1;
// Also initialize aux to false in every iteration
}
}
}
void applyPermToVec(Vec<T>& out, const Vec<T>& in, const Permut& p1)
{
assert(&out != &in); // NOT an in-place procedure
out.SetLength(p1.length());
for (long i=0; i<p1.length(); i++)
out[i] = in.at(p1[i]);
}
void factorize(Vec< Pair<long, long> > &factors, long N)
{
factors.SetLength(0);
if (N < 2) return;
PrimeSeq s;
long n = N;
while (n > 1) {
if (ProbPrime(n)) {
append(factors, cons(n, 1L));
return;
}
long p = s.next();
if ((n % p) == 0) {
long e = 1;
n = n/p;
while ((n % p) == 0) {
n = n/p;
e++;
}
append(factors, cons(p, e));
}
}
}
// Returns a list of prime factors and their multiplicity,
// N = \prod_i factors[i].first^{factors[i].second}
void factorize(Vec< Pair<long, long> > &factors, long N)
{
factors.SetLength(0);
if (N < 2) return;
PrimeSeq s;
long n = N;
while (n > 1) {
if (ProbPrime(n)) { // n itself is a prime, add (n,1) to the list
append(factors, cons(n, 1L));
return;
}
long p = s.next();
if ((n % p) == 0) { // p divides n, find its multiplicity
long e = 1;
n = n/p;
while ((n % p) == 0) {
n = n/p;
e++;
}
append(factors, cons(p, e)); // add (p,e) to the list
}
}
}
void computePowVec(Vec<long>& powVec,
const Vec< Pair<long, long> >& factors)
{
long k = factors.length();
powVec.SetLength(k);
for (long i = 0; i < k; i++)
powVec[i] = computePow(factors[i]);
}
// factors[d] = (p_d, e_d)
// computes powVec[d] = p_d^{e_d}
void computePowVec(Vec<long>& powVec,
const Vec< Pair<long, long> >& factors)
{
long k = factors.length();
powVec.SetLength(k);
for (long d = 0; d < k; d++)
powVec[d] = computePow(factors[d]);
}
void FileList::AddFile(const char *name)
{
Vec<char> item;
item.SetLength(strlen(name)+1);
strcpy(item.elts(), name);
data.append(item);
}
// powVec[d] = p_d^{e_d}, m = \prod_d p_d^{e_d}
// computes divVec[d] = m/p_d^{e_d}
void computeDivVec(Vec<long>& divVec, long m,
const Vec<long>& powVec)
{
long k = powVec.length();
divVec.SetLength(k);
for (long d = 0; d < k; d++)
divVec[d] = m/powVec[d];
}
void computeDivVec(Vec<long>& divVec, long m,
const Vec<long>& powVec)
{
long k = powVec.length();
divVec.SetLength(k);
for (long i = 0; i < k; i++)
divVec[i] = m/powVec[i];
}
void FFTHelper::FFT(const zz_pX& f, Vec<zz_p>& v) const
{
tmp = f;
BluesteinFFT(tmp, m, root, powers, powers_aux, Rb, Rb_aux, Ra);
v.SetLength(phim);
for (long i = 0, j = 0; i < m; i++)
if (coprime[i]) v[j++] = coeff(tmp, i);
}
// powVec[d] = p_d^{e_d}
// cycVec[d] = Phi_{p_d^{e_d}}(X) mod p
void computeCycVec(Vec<zz_pX>& cycVec, const Vec<long>& powVec)
{
long k = powVec.length();
cycVec.SetLength(k);
for (long d = 0; d < k; d++) {
ZZX PhimX = Cyclotomic(powVec[d]);
cycVec[d] = conv<zz_pX>(PhimX);
}
}
void getHyperColumn(Vec<T>& v, const ConstCubeSlice<T>& s, long pos)
{
long m = s.getProd(1);
long n = s.getDim(0);
assert(pos >= 0 && pos < m);
v.SetLength(n);
for (long i = 0; i < n; i++)
v[i] = s[pos + i*m];
}
// Get the "crude" cube dimensions corresponding to a vector of trees,
// the ordered vector with one dimension per tree
void GeneratorTrees::getCubeDims(Vec<long>& dims) const
{
dims.SetLength(trees.length());
// copy dims from the trees
for (long i=0; i<trees.length(); i++) {
const OneGeneratorTree& T = trees[i];
dims[T.getAuxKey()] = T.DataOfNode(T.rootIdx()).size;
// getAuxKey() returns the generator number associated with this tree
}
}
// Compute one or more layers corresponding to one network of one leaf
void PermNetwork::setLayers4Leaf(long lyrIdx, const ColPerm& p,
const Vec<long>& benesLvls, long gIdx,
const SubDimension& leafData,
const Permut& map2cube)
{
#ifdef DEBUG_PRINTOUT
std::cerr << "Layer "<<lyrIdx<<", column-permutation="<< p << endl;
#endif
// Compute the shift amounts for all the layers in this network
Vec<bool> isID;
Vec<Permut> shifts;
if (benesLvls.length()==1) {// Special case for a "trivial" 1-layer network
shifts.SetLength(1);
isID.SetLength(1);
isID[0] = !p.getShiftAmounts(shifts[0]);
}
else // The general case of a multi-layer Benes network
p.getBenesShiftAmounts(shifts,isID,benesLvls);
// Copy the shift amounts to the right place in the bigger network,
// renaming the slots from a linear array to the hyper cube
for (long i=0; i<benesLvls.length(); i++) {
PermNetLayer& lyr = layers[lyrIdx+i];
lyr.genIdx = gIdx;
lyr.isID = isID[i];
lyr.e = leafData.e;
if (!lyr.isID) {
#ifdef DEBUG_PRINTOUT
std::cerr << "layer "<<lyrIdx+i<<": "<<shifts[i]<<endl;
#endif
if (leafData.good) // For good leaves, shift by -x is the same as size-x
for (long k=0; k<shifts[i].length(); k++)
if (shifts[i][k]<0) shifts[i][k] += leafData.size;
applyPermToVec(lyr.shifts, shifts[i], map2cube); // do the renaming
#ifdef DEBUG_PRINTOUT
std::cerr << " : "<<lyr.shifts<<endl;
#endif
}
// else std::cerr << "layer "<<lyrIdx+i<<"= identity\n";
}
}
static void
init_representatives(Vec<long>& representatives, long dim,
const Vec<long>& mvec, const PAlgebra& zMStar)
{
assert(dim >= 0 && dim < mvec.length());
// special case
if (dim >= LONG(zMStar.numOfGens())) {
representatives.SetLength(1);
representatives[0] = 1;
return;
}
long m = mvec[dim];
long D = zMStar.OrderOf(dim);
long g = InvMod(zMStar.ZmStarGen(dim) % m, m);
representatives.SetLength(D);
for (long i = 0; i < D; i++)
representatives[i] = PowerMod(g, i, m);
}
// Converts list<long> to Vec<long>
static long listToVec(Vec<long>& vec, LongNodePtr ptr)
{
long len = length(ptr);
vec.SetLength(len);
long i = 0;
for (LongNodePtr p = ptr; p != NULL; p = p->next) {
vec[i] = p->count;
i++;
}
return len;
}
// divVec[d] = m/p_d^{e_d}, powVec[d] = p^{e_d}
// computes invVec[d] = divVec[d]^{-1} mod powVec[d]
void computeInvVec(Vec<long>& invVec,
const Vec<long>& divVec, const Vec<long>& powVec)
{
long k = divVec.length();
invVec.SetLength(k);
for (long d = 0; d < k; d++) {
long t1 = divVec[d] % powVec[d];
long t2 = InvMod(t1, powVec[d]);
invVec[d] = t2;
}
}
void computeInvVec(Vec<long>& invVec,
const Vec<long>& divVec, const Vec<long>& powVec)
{
long k = divVec.length();
invVec.SetLength(k);
for (long i = 0; i < k; i++) {
long t1 = divVec[i] % powVec[i];
long t2 = InvMod(t1, powVec[i]);
invVec[i] = t2;
}
}
// computes linearEvalPoints[i] = base^i, i in Z_m^*
void computeLinearEvalPoints(Vec<zz_p>& linearEvalPoints,
const zz_p& base,
long m, long phim)
{
linearEvalPoints.SetLength(phim);
zz_p pow = conv<zz_p>(1);
for (long i = 0, j = 0; i < m; i++) {
if (GCD(i, m) == 1) linearEvalPoints[j++] = pow;
pow = pow * base;
}
}
static void
init_representatives(Vec<long>& representatives, long dim,
const Vec<long>& mvec, const PAlgebra& zMStar)
{
//OLD: assert(dim >= 0 && dim < mvec.length());
helib::assertInRange(dim, 0l, mvec.length(), "Invalid argument: dim must be between 0 and mvec.length()");
// special case
if (dim >= LONG(zMStar.numOfGens())) {
representatives.SetLength(1);
representatives[0] = 1;
return;
}
long m = mvec[dim];
long D = zMStar.OrderOf(dim);
long g = InvMod(zMStar.ZmStarGen(dim) % m, m);
representatives.SetLength(D);
for (long i = 0; i < D; i++)
representatives[i] = PowerMod(g, i, m);
}
NTL_CLIENT
// powVec[d] = p_d^{e_d}, m = \prod_d p_d^{e_d}
// computes divVec[d] = m/p_d^{e_d}
inline void computeDivVec(Vec<long>& divVec, long m,
const Vec<long>& powVec)
{
long k = powVec.length();
divVec.SetLength(k);
for (long d = 0; d < k; d++)
divVec[d] = m/powVec[d];
}
// m = m_1 ... m_k, m_d = p_d^{e_d}
// powVec[d] = m_d
// invVec[d] = (m/m_d)^{-1} mod m_d
// computes polyToCubeMap[i] and cubeToPolyMap[i]
// where polyToCubeMap[i] is the index of (i_1, ..., i_k)
// in the cube with CubeSignature longSig = (m_1, ..., m_k),
// and (i_1, ..., i_k) is the unique tuple satistifying
// i = i_1 (m/m_1) + ... + i_k (m/m_k) mod m
// and
// cubeToPolyMap is the inverse map.
void computePowerToCubeMap(Vec<long>& polyToCubeMap,
Vec<long>& cubeToPolyMap,
long m,
const Vec<long>& powVec,
const Vec<long>& invVec,
const CubeSignature& longSig)
{
long k = powVec.length();
polyToCubeMap.SetLength(m);
cubeToPolyMap.SetLength(m);
for (long i = 0; i < m; i++) {
long j = 0;
for (long d = 0; d < k; d++) {
long i_d = MulMod((i % powVec[d]), invVec[d], powVec[d]);
j += i_d * longSig.getProd(d+1);
}
polyToCubeMap[i] = j;
cubeToPolyMap[j] = i;
}
}
int main()
{
Vec<ZZ> v;
cin >> v;
long n = v.length();
v.SetLength(2*n);
long i;
for (i = 0 ; i < n; i++)
v[n+i] = v[n-1-i];
cout << v << "\n";
}
void vecRed(Vec<ZZ>& out, const Vec<ZZ>& in, long q, bool abs)
{
out.SetLength(in.length()); // allocate space if needed
for (long i=0; i<in.length(); i++) {
long c = in[i]%q;
if (abs) { if (c<0) c+=q; }
else if (q==2) { if (in[i]<0) c = -c; }
else {
if (c >= q/2) c -= q;
else if (c < -(q/2)) c += q;
}
out[i] = c;
}
}
// Computes the inverse of the shortToLongMap, computed above.
// "undefined" entries are initialzed to -1.
void computeLongToShortMap(Vec<long>& longToShortMap,
long m,
const Vec<long>& shortToLongMap)
{
long n = shortToLongMap.length();
longToShortMap.SetLength(m);
for (long i = 0; i < m; i++) longToShortMap[i] = -1;
for (long j = 0; j < n; j++) {
long i = shortToLongMap[j];
longToShortMap[i] = j;
}
}
// For each position in the data vector, compute how many slots it should be
// shifted inside its small permutation.
// Return value is zero if all the shift amounts are zero, nonzero otherwise.
long ColPerm::getShiftAmounts(Vec<long>& out) const
{
long sz = getSize();
out.SetLength(sz);
long nonZero = 0;
for (long k = 0; k < sz; k++) {
long i = getCoord(k, dim);
long pi_i = at(k);
if (i != pi_i) nonZero = 1;
out.at(addCoord(k, dim, pi_i-i)) = i - pi_i;
}
return nonZero;
}
// Get the "fine" cube dimensions corresponding to a vector of trees,
// the ordered vector with one dimension per leaf in any of the trees.
void GeneratorTrees::getCubeSubDims(Vec<long>& dims) const
{
// how many dimensions do we need
long nDims = 0;
for (long i=0; i<trees.length(); i++)
nDims += trees[i].getNleaves();
dims.SetLength(nDims); // set the size
// copy dims from the leaves in all the trees
long idx = 0;
for (long i=0; i<trees.length(); i++) {
const OneGeneratorTree& T = trees[i];
for (long leaf=T.firstLeaf(); leaf>=0; leaf=T.nextLeaf(leaf))
dims[idx++] = T[leaf].getData().size;
}
}
