static void apply(const EncryptedArrayDerived<type>& ea,
std::vector<zzX>& unpackSlotEncoding)
{
FHE_NTIMER_START(buildUnpackSlotEncoding);
RBak bak; bak.save(); ea.restoreContext(); // the NTL context for mod p^r
long nslots = ea.size(); // how many slots
long d = ea.getDegree(); // size of each slot
const Mat<R>& CBi=ea.getNormalBasisMatrixInverse();
// CBi contains a description of the normal-basis inverse transformation
std::vector<RX> LM(d);
for (long i = 0; i < d; i++) // prepare the linear polynomial
LM[i] = CBi[i][0];
std::vector<RX> C;
ea.buildLinPolyCoeffs(C, LM); // "build" the linear polynomial
unpackSlotEncoding.resize(d); // encode the coefficients
for (long j = 0; j < d; j++) {
std::vector<RX> v(nslots, C[j]);
ea.encode(unpackSlotEncoding[j], v);
}
}
static void apply(const EncryptedArrayDerived<type>& ea, Ctxt& ctxt,
const PlaintextBlockMatrixBaseInterface& mat)
{
assert(&ea == &mat.getEA().getDerived(type()));
assert(&ea.getContext() == &ctxt.getContext());
const PAlgebra& zMStar = ea.getContext().zMStar;
long p = zMStar.getP();
long m = zMStar.getM();
const RXModulus& F = ea.getTab().getPhimXMod();
RBak bak; bak.save(); ea.getTab().restoreContext();
const PlaintextBlockMatrixInterface<type>& mat1 =
dynamic_cast< const PlaintextBlockMatrixInterface<type>& >( mat );
ctxt.cleanUp(); // not sure, but this may be a good idea
long nslots = ea.size();
long d = ea.getDegree();
Vec< shared_ptr<Ctxt> > acc;
acc.SetLength(d);
for (long k = 0; k < d; k++)
acc[k] = shared_ptr<Ctxt>(new Ctxt(ZeroCtxtLike, ctxt));
mat_R entry;
entry.SetDims(d, d);
vector<RX> entry1;
entry1.resize(d);
vector< vector<RX> > diag;
diag.resize(nslots);
for (long j = 0; j < nslots; j++) diag[j].resize(d);
for (long i = 0; i < nslots; i++) { // process diagonal i
bool zDiag = true;
long nzLast = -1;
for (long j = 0; j < nslots; j++) {
bool zEntry = mat1.get(entry, mcMod(j-i, nslots), j);
assert(zEntry || (entry.NumRows() == d && entry.NumCols() == d));
// get(...) returns true if the entry is empty, false otherwise
if (!zEntry && IsZero(entry)) zEntry=true; // zero is an empty entry too
if (!zEntry) { // non-empty entry
zDiag = false; // mark diagonal as non-empty
// clear entries between last nonzero entry and this one
for (long jj = nzLast+1; jj < j; jj++) {
for (long k = 0; k < d; k++)
clear(diag[jj][k]);
}
nzLast = j;
// recode entry as a vector of polynomials
for (long k = 0; k < d; k++) conv(entry1[k], entry[k]);
// compute the lin poly coeffs
ea.buildLinPolyCoeffs(diag[j], entry1);
}
}
if (zDiag) continue; // zero diagonal, continue
// clear trailing zero entries
for (long jj = nzLast+1; jj < nslots; jj++) {
for (long k = 0; k < d; k++)
clear(diag[jj][k]);
}
// now diag[j] contains the lin poly coeffs
Ctxt shCtxt = ctxt;
ea.rotate(shCtxt, i);
shCtxt.cleanUp();
RX cpoly1, cpoly2;
ZZX cpoly;
// apply the linearlized polynomial
for (long k = 0; k < d; k++) {
// compute the constant
bool zConst = true;
vector<RX> cvec;
cvec.resize(nslots);
for (long j = 0; j < nslots; j++) {
cvec[j] = diag[j][k];
if (!IsZero(cvec[j])) zConst = false;
}
if (zConst) continue;
ea.encode(cpoly, cvec);
conv(cpoly1, cpoly);
// apply inverse automorphism to constant
plaintextAutomorph(cpoly2, cpoly1, PowerMod(p, mcMod(-k, d), m), zMStar, F);
conv(cpoly, cpoly2);
Ctxt shCtxt1 = shCtxt;
shCtxt1.multByConstant(cpoly);
*acc[k] += shCtxt1;
}
}
Ctxt res(ZeroCtxtLike, ctxt);
for (long k = 0; k < d; k++) {
acc[k]->frobeniusAutomorph(k);
res += *acc[k];
}
ctxt = res;
}