bool CAR_DKW_o::SetParameters_InitializeABOmega()
{
if (!CAR_DKW::SetParameters_InitializeABOmega())
return false;
TDenseMatrix lambda1 = SIGMA_inverse * SIGMAlambda1;
TDenseVector KAPPAtheta = KAPPA * theta;
TDenseVector theta_Q;
aI_Q.Zeros(dataP->MATgrid_options.Dimension());
bI_Q.Zeros(dataP->MATgrid_options.Dimension(), Nfac);
for (int i=0; i<dataP->MATgrid_options.Dimension(); i++)
{
double MAT = dataP->MATgrid_options(i);
TDenseVector temp_ay;
TDenseMatrix temp_by;
if (!YieldFacLoad(temp_ay, temp_by, KAPPA_rn, Inv_KAPPA_rn, Inv_Kron_KAPPA_rn, SIGMA, KAPPAtheta, rho0, rho1, lambda0,TDenseVector(1,MAT)))
return false;
TDenseVector temp_by_vector = temp_by.RowVector(0); // -MAT * temp_by.RowVector(0);
theta_Q = Multiply(Inv_KAPPA_rn, KAPPAtheta-SIGMA*lambda0+MultiplyTranspose(SIGMA,SIGMA)*temp_by_vector);
double rho0_Q = rho0_pi - InnerProduct(lambda0, sigq)+InnerProduct(sigq, TransposeMultiply(SIGMA,temp_by_vector));
TDenseVector rho1_Q = rho1_pi - TransposeMultiply(lambda1, sigq);
double temp_aI_Q;
TDenseVector temp_bI_Q;
InfExpFacLoad(temp_aI_Q, temp_bI_Q, KAPPA_rn, Inv_KAPPA_rn, Inv_Kron_KAPPA_rn, SIGMA, theta_Q, sigq, sigqx, rho0_Q, rho1_Q, MAT);
aI_Q(i) = temp_aI_Q;
bI_Q.InsertRowMatrix(i, 0, temp_bI_Q);
}
return true;
}
void CompMod(zz_pX& x, const zz_pX& g, const zz_pXArgument& A,
const zz_pXModulus& F)
{
if (deg(g) <= 0) {
x = g;
return;
}
zz_pX s, t;
vec_zz_p scratch(INIT_SIZE, F.n);
long m = A.H.length() - 1;
long l = ((g.rep.length()+m-1)/m) - 1;
zz_pXMultiplier M;
build(M, A.H[m], F);
InnerProduct(t, g.rep, l*m, l*m + m - 1, A.H, F.n, scratch);
for (long i = l-1; i >= 0; i--) {
InnerProduct(s, g.rep, i*m, i*m + m - 1, A.H, F.n, scratch);
MulMod(t, t, M, F);
add(t, t, s);
}
x = t;
}
void PlainUpdateMap(vec_zz_p& xx, const vec_zz_p& a,
const zz_pX& b, const zz_pX& f)
{
long n = deg(f);
long i, m;
if (IsZero(b)) {
xx.SetLength(0);
return;
}
m = n-1 - deg(b);
vec_zz_p x(INIT_SIZE, n);
for (i = 0; i <= m; i++)
InnerProduct(x[i], a, b.rep, i);
if (deg(b) != 0) {
zz_pX c(INIT_SIZE, n);
LeftShift(c, b, m);
for (i = m+1; i < n; i++) {
MulByXMod(c, c, f);
InnerProduct(x[i], a, c.rep);
}
}
xx = x;
}
void CompMod(ZZ_pX& x, const ZZ_pX& g, const ZZ_pXArgument& A,
const ZZ_pXModulus& F)
{
if (deg(g) <= 0) {
x = g;
return;
}
ZZ_pX s, t;
ZZVec scratch(F.n, ZZ_p::ExtendedModulusSize());
long m = A.H.length() - 1;
long l = ((g.rep.length()+m-1)/m) - 1;
ZZ_pXMultiplier M;
build(M, A.H[m], F);
InnerProduct(t, g.rep, l*m, l*m + m - 1, A.H, F.n, scratch);
for (long i = l-1; i >= 0; i--) {
InnerProduct(s, g.rep, i*m, i*m + m - 1, A.H, F.n, scratch);
MulMod(t, t, M, F);
add(t, t, s);
}
x = t;
}
double DoubleDeriv1 (edge *TheEdge, position *ThePosition, line *TheLine,
int index_x, int index_y)
{
int index;
double dv[3], v[3], newv[3], hat[3], temp1;
if (!TheEdge || !ThePosition || !TheLine) return (0.0);
if (index_y < index_x) {
index = index_x; index_x = index_y; index_y = index;
}
ComputeV (v, *TheLine);
RotateQuaternion (newv, ThePosition->q, v);
temp1 = InnerProduct (newv, TheEdge->m);
if ((index_x == THETA) && (index_y == THETA) ||
(index_x == OMEGA) && (index_y == OMEGA))
return (-2.0 * sqr(temp1));
if ((index_x == THETA) && (index_y == OMEGA))
return (0.0);
if (((index_x == THETA) || (index_x == OMEGA)) &&
((index_y == ALPHA) || (index_y == BETA) || (index_y == GAMMA))) {
if (index_x == THETA) {
hat[0] = 0.0; hat[1] = -1.0; hat[2] = 0.0;
} else {
hat[0] = 1.0; hat[1] = 0.0; hat[2] = 0.0;
}
RotateQuaternion (v, TheLine->q, hat);
RotateQuaternion (newv, ThePosition->q, v);
DerivR (dv, newv, IndexToAxis (index_y));
return (2.0 * temp1 * InnerProduct (dv, TheEdge->m));
}
if ( ((index_x == ALPHA) || (index_x == BETA) || (index_x == GAMMA)) &&
((index_y == ALPHA) || (index_y == BETA) || (index_y == GAMMA)) ) {
ComputeV (v, *TheLine);
RotateQuaternion (newv, ThePosition->q, v);
DoubleDerivR (dv, newv, IndexToAxis (index_x), IndexToAxis (index_y));
return (2.0 * temp1 * InnerProduct (dv, TheEdge->m));
}
pexit ("Bad Parameters to DoubleDeriv1");
return 0.0;
}
static
void ComputeGS(mat_ZZ& B, xdouble **B1, xdouble **mu, xdouble *b,
xdouble *c, long k, xdouble bound, long st, xdouble *buf)
{
long n = B.NumCols();
long i, j;
xdouble s, t1, y, t;
ZZ T1;
xdouble *mu_k = mu[k];
if (st < k) {
for (i = 1; i < st; i++)
buf[i] = mu_k[i]*c[i];
}
for (j = st; j <= k-1; j++) {
if (b[k]*b[j] < NTL_FDOUBLE_PRECISION*NTL_FDOUBLE_PRECISION) {
double z = 0;
xdouble *B1_k = B1[k];
xdouble *B1_j = B1[j];
for (i = 1; i <= n; i++)
z += B1_k[i].x * B1_j[i].x;
s = z;
}
else {
s = InnerProduct(B1[k], B1[j], n);
if (s*s <= b[k]*b[j]/bound) {
InnerProduct(T1, B(k), B(j));
conv(s, T1);
}
}
xdouble *mu_j = mu[j];
t1 = 0;
for (i = 1; i <= j-1; i++)
MulAdd(t1, t1, mu_j[i], buf[i]);
mu_k[j] = (buf[j] = (s - t1))/c[j];
}
s = 0;
for (j = 1; j <= k-1; j++)
MulAdd(s, s, mu_k[j], buf[j]);
c[k] = b[k] - s;
}
double Deriv1 (edge *TheEdge, position *ThePosition, line *TheLine,
int index)
{
double v[3], newv[3], dv[3], hat[3];
if (!TheEdge || !ThePosition || !TheLine) return (0.0);
switch (index) {
case THETA :
hat[0] = 0.0; hat[1] = -1.0; hat[2] = 0.0;
RotateQuaternion (dv, TheLine->q, hat);
RotateQuaternion (newv, ThePosition->q, dv);
return (InnerProduct (newv, TheEdge->m));
break;
case OMEGA :
hat[0] = 1.0; hat[1] = 0.0; hat[2] = 0.0;
RotateQuaternion (dv, TheLine->q, hat);
RotateQuaternion (newv, ThePosition->q, dv);
return (InnerProduct (newv, TheEdge->m));
break;
case ALPHA :
ComputeV (v, *TheLine);
RotateQuaternion (newv, ThePosition->q, v);
DerivR (dv, newv, 'x');
return (InnerProduct (dv, TheEdge->m));
break;
case BETA :
ComputeV (v, *TheLine);
RotateQuaternion (newv, ThePosition->q, v);
DerivR (dv, newv, 'y');
return (InnerProduct (dv, TheEdge->m));
break;
case GAMMA :
ComputeV (v, *TheLine);
RotateQuaternion (newv, ThePosition->q, v);
DerivR (dv, newv, 'z');
return (InnerProduct (dv, TheEdge->m));
break;
default :
pexit ("Bad parameters to Deriv1");
break;
}
return 0.0;
}
double SBVAR::LogLikelihood(void)
{
double log_likelihood=log_likelihood_constant + lambda_T*LogAbsDeterminant(A0);
TDenseVector a0(n_vars), aplus(n_predetermined);
for (int i=n_vars-1; i >= 0; i--)
{
a0.RowVector(A0,i);
aplus.RowVector(Aplus,i);
log_likelihood+=-0.5*(InnerProduct(a0,a0,YY) - 2.0*InnerProduct(aplus,a0,XY) + InnerProduct(aplus,aplus,XX));
}
return log_likelihood;
}
/*
Computes the log of the integral of the tempered posterior.
Integrate( (p(Y|Theta)*p(Theta))^(1/K) dTheta )
*/
double SBVAR_symmetric_linear::LogPosteriorIntegral(TDenseVector p, int ndraws, int thin, int burn_in)
{
if (ndraws <= 0) throw dw_exception("PosteriorIntegral(): number of draws must be postive");
if (thin <= 0) throw dw_exception("PosteriorIntegral(): thinning factor must be positive");
if (p.dim != NumberParameters()) throw dw_exception("PosteriorIntegral(): Incorrect number of parameters");
if (!simulation_info_set) SetSimulationInfo();
SetParameters(p.vector);
double integral=log_likelihood_constant + log_prior_constant;
for (int i=0; i < n_vars; i++)
integral+=0.5*dim_g[i]*1.837877066409345 + LogAbsDeterminant(Simulate_SqrtH[i]); // 1.837877066409345 = log(2*pi)
integral+=lambda_T*LogAbsDeterminant(A0);
for (int i=0; i < n_vars; i++)
{
TDenseVector x=InverseMultiply(Simulate_SqrtS[i],p.SubVector(begin_b[i],begin_b[i]+dim_b[i]-1));
integral+=-0.5*lambda_T*InnerProduct(x,x);
}
for (int i=0; i < n_vars; i++)
integral-=LogConditionalA0_gibbs(p,i,ndraws,thin,burn_in);
return integral;
}
double SBVAR_symmetric::LogPrior(void)
{
if (flat_prior) return 0.0;
double log_prior=log_prior_constant;
TDenseVector a0(n_vars), aplus(n_predetermined);
for (int i=n_vars-1; i >= 0; i--)
{
a0.RowVector(A0,i);
aplus.RowVector(Aplus,i);
log_prior+=-0.5*(InnerProduct(a0,a0,prior_YY) - 2.0*InnerProduct(aplus,a0,prior_XY) + InnerProduct(aplus,aplus,prior_XX));
}
return log_prior;
}
wrapper(size_t n, params prm = params(),
const backend_params &bprm = backend_params(),
const InnerProduct &inner_product = InnerProduct()
)
: s(prm.get("type", runtime::solver::bicgstab)), handle(0)
{
if (!prm.erase("type")) AMGCL_PARAM_MISSING("type");
switch(s) {
#define AMGCL_RUNTIME_SOLVER(type) \
case type: \
handle = static_cast<void*>(new amgcl::solver::type<Backend, InnerProduct>(n, prm, bprm, inner_product)); \
break
AMGCL_RUNTIME_SOLVER(cg);
AMGCL_RUNTIME_SOLVER(bicgstab);
AMGCL_RUNTIME_SOLVER(bicgstabl);
AMGCL_RUNTIME_SOLVER(gmres);
AMGCL_RUNTIME_SOLVER(lgmres);
AMGCL_RUNTIME_SOLVER(fgmres);
AMGCL_RUNTIME_SOLVER(idrs);
#undef AMGCL_RUNTIME_SOLVER
default:
throw std::invalid_argument("Unsupported solver type");
}
}
double GillespiePetzold_Stepsize(Vector& x ,
Vector& a ,
double & a0 ,
const Matrix& nu ,
double tau,
double eps,
PropensityJacobianFunc jacobian)
{
static Matrix f(x.Size(), x.Size());
static Vector mu = a;
static Vector sigma = a;
static double r1, r2;
static double tau1, tau2;
f = jacobian(x)*nu;
mu = f*a;
sigma = InnerProduct(f, f)*a;
r1 = mu.Norm(); //Max norm
r2 = sigma.Norm(); // Max norm
tau1 = eps * a0;
tau2 = tau1 * tau1;
if (r1 > 0)
tau1 = tau1/r1;
else
tau1 = 100.;
if (r2 > 0)
tau2 = tau2/r2;
else
tau2 = 100.;
if (tau1 > tau2)
return tau2;
else
return tau1;
}
NTL_START_IMPL
static
long CharPolyBound(const mat_ZZ& a)
// This bound is computed via interpolation
// through complex roots of unity.
{
long n = a.NumRows();
long i;
ZZ res, t1, t2;
set(res);
for (i = 0; i < n; i++) {
InnerProduct(t1, a[i], a[i]);
abs(t2, a[i][i]);
mul(t2, t2, 2);
add(t2, t2, 1);
add(t1, t1, t2);
if (t1 > 1) {
SqrRoot(t1, t1);
add(t1, t1, 1);
}
mul(res, res, t1);
}
return NumBits(res);
}
TInt DoCP0Test(TAny* aPtr)
{
TUint seed[2];
seed[0]=(TUint)aPtr;
seed[1]=0;
TInt16 vec1[128];
TInt16 vec2[128];
TInt run;
for (run=0; run<100000; ++run)
{
TInt n=(Random(seed)&63)+64; // vector length
TInt i;
for (i=0; i<n; ++i)
{
vec1[i]=(TInt16)(Random(seed)&0xffff);
vec2[i]=(TInt16)(Random(seed)&0xffff);
TInt64 result, result2;
InnerProduct(result,vec1,vec2,n);
InnerProduct2(result2,vec1,vec2,n);
if (result != result2)
{
User::Panic(_L("ERROR"),run);
}
}
}
return 0;
}
double ScalarFiniteElement<D> ::
Evaluate (const IntegrationPoint & ip, FlatVector<double> x) const
{
VectorMem<20, double> shape(ndof);
CalcShape (ip, shape);
return InnerProduct (shape, x);
}
void ProjectPowers(vec_zz_p& x, const vec_zz_p& a, long k,
const zz_pXArgument& H, const zz_pXModulus& F)
{
long n = F.n;
if (a.length() > n || k < 0 || NTL_OVERFLOW(k, 1, 0))
Error("ProjectPowers: bad args");
long m = H.H.length()-1;
long l = (k+m-1)/m - 1;
zz_pXMultiplier M;
build(M, H.H[m], F);
vec_zz_p s(INIT_SIZE, n);
s = a;
StripZeroes(s);
x.SetLength(k);
for (long i = 0; i <= l; i++) {
long m1 = min(m, k-i*m);
zz_p* w = &x[i*m];
for (long j = 0; j < m1; j++)
InnerProduct(w[j], H.H[j].rep, s);
if (i < l)
UpdateMap(s, s, M, F);
}
}
//--------------------------------------------------------------------------------
//
// CalculateHardening
// Current used for testing the other parts of the code.
//
//
// This is almost a direct translation from Ricardo's "HARDEN" routine from fft3.for
//
//--------------------------------------------------------------------------------
vector<Float> CalculateHardening( Float & AccumulatedShear,
const Float & TimeStep,
const EigenRep & StressState,
const vector<EigenRep> & SchmidtTensors,
const vector<Float> & CRSS,
const vector<Float> & GammaDotBase, // reference shear rate
const vector<int> & RateSensitivity,
const vector< vector< Float > > & HardeningMatrix,
const vector<Float> & Tau0,
const vector<Float> & Tau1,
const vector<Float> & Theta0,
const vector<Float> & Theta1 )
{
vector<Float> UpdatedCRSS = CRSS;
Float LocalShearAccumulation = 0;
std::vector<Float> GammaDot( SchmidtTensors.size(), 0 );
for( int i = 0; i < SchmidtTensors.size(); i ++ )
{
Float RSS = InnerProduct( SchmidtTensors[i], StressState) / CRSS[i];
if( RateSensitivity[i] > 0 )
GammaDot[i] = GammaDotBase[i] * std::pow( std::fabs( RSS ), static_cast<int>( RateSensitivity[i] ) );
else
GammaDot[i] = GammaDotBase[i];
LocalShearAccumulation += std::fabs( GammaDot[i] ) * TimeStep;
}
for( int i = 0; i < SchmidtTensors.size(); i ++ )
{
Float DTau = 0;
for( int j = 0; j < SchmidtTensors.size(); j ++ )
DTau += HardeningMatrix[i][j] * std::fabs( GammaDot[j] ) * TimeStep;
Float Tiny = 1e-4 * Tau0[i];
Float VoceFactor = 0;
if( std::fabs( Theta0[i] ) > Tiny )
{
VoceFactor = Theta1[i] * LocalShearAccumulation;
if( std::fabs( Tau1[i]) > Tiny )
{
Float fRatio = std::fabs( Theta0[i] / Tau1[i] );
Float ExpIni = exp( -AccumulatedShear * fRatio );
Float ExpDel = exp( -LocalShearAccumulation * fRatio );
VoceFactor = VoceFactor - (fRatio * Tau1[i] * Theta1[i])/ fRatio * ExpIni
* ( ExpDel - static_cast<Float>(1) ) - Theta1[i]/fRatio * ExpIni
* ( ExpDel * ( ( AccumulatedShear + LocalShearAccumulation)
* fRatio + static_cast<Float>(1) )
- ( AccumulatedShear * fRatio + static_cast<Float>(1) ) );
}
}
UpdatedCRSS[i] += DTau * VoceFactor / LocalShearAccumulation;
}
AccumulatedShear += LocalShearAccumulation;
return UpdatedCRSS;
}
complex stb_InnerProduct(stabiliser *phi1, stabiliser *phi2)
{
affine_sp a = afp_Copy(phi1->a); //This won't work. I need to define a copy method
stabiliser stab;
stab.a = &a;
stab.q = phi1->q;
affine_sp *a1 = phi1->a, *a2 = phi2->a;
quadratic_fm *q1 = phi1->q, *q2 = phi2->q;
for (int i = a2->k +1; i < a2->n; i++){
alpha = InnerProduct(a2->h, a2->GBar[i])
res = shrink(&stab, a2->HBar[i], alpha);
if (res == EMPTY){
return (complex) 0;
}
}
short *y = (short *)calloc(a2->k, sizeof(short));
short *scratch_space = (short *)calloc(a2->n, sizeof(short));
short res = 0;
AddVectors(a2->n, scratch_space, a1->h);
AddVectors(a2->n, scratch_space, a2->h);
short **R = (short **)calloc(a2->n, sizeof(short*));
for (int i=0; i<a2->n; i++){R[i] = (short *)calloc(a2->n, sizeof(short));}
for (int i = 0; i < a2->k; i++){
y[i] = InnerProduct(scratch_space, a2->Gbar[i]);
for (int j = 0; j < a.k; j++){
R[j][i] = InnerProduct(a.G[j], a2.GBar[i]);
}
}
qfm_BasisChange(q2, R);
qfm_ShiftChange(q2, y);
for (int i = 0; i<a2->n; i++){a2->h[i] = a1->h[i];}
//Cleanup
for(int i = 0; i<q2->k; i++){free(R[i]);}
free(scratch_space);
free (R);
free(y);
//Find the final quadratic form q
q.Q = Modulo(q1->Q - q2->Q, 8);
for (int i = 0; i < q.K; i++){
q.D[i] = Modulo(q1->D[i]-q2->D[i], 8);
for (int j = 0; j<q.k; j++){
q.J[i][j] = Modulo(q1->J[i][j] - q2->J[i][j], 8);
}
}
return pow(2, -1*(a1->k - a2->k)/2)*ExponentialSum(q);
}
static
void IncrementalGS(mat_ZZ& B, vec_long& P, vec_ZZ& D, vec_vec_ZZ& lam,
long& s, long k)
{
long n = B.NumCols();
long m = B.NumRows();
static ZZ u, t1, t2;
long i, j;
for (j = 1; j <= k-1; j++) {
long posj = P(j);
if (posj == 0) continue;
InnerProduct(u, B(k), B(j));
for (i = 1; i <= posj-1; i++) {
mul(t1, D[i], u);
mul(t2, lam(k)(i), lam(j)(i));
sub(t1, t1, t2);
div(t1, t1, D[i-1]);
u = t1;
}
lam(k)(posj) = u;
}
InnerProduct(u, B(k), B(k));
for (i = 1; i <= s; i++) {
mul(t1, D[i], u);
mul(t2, lam(k)(i), lam(k)(i));
sub(t1, t1, t2);
div(t1, t1, D[i-1]);
u = t1;
}
if (u == 0) {
P(k) = 0;
}
else {
s++;
P(k) = s;
D[s] = u;
}
}
long Convolution(CircultBuffer *rb,int const *Hn,int ADC_Value){ //Input ADCoutput,Output FIR coef
long Sum=0;
rb->NewValue=ADC_Value;
rb->Coef[rb->Front] = ADC_Value;
rb->Front++;
rb->Front &=(rb->len-1); //modular operation
Sum=InnerProduct((int*)Hn,rb->Coef,rb->len,rb->Front);
return Sum;
}
double CMercerKernel<vec3>::Evaluate(vec3* x, vec3* y) {
double result = 0;
for(size_t i=0; i<m_n; i++)
result += InnerProduct(x[i],y[i]);
return result;
}
double CMercerKernel<vec3f>::Evaluate(vec3f* x, vec3f* y) {
float result = 0;
for(size_t i=0; i<m_n; i++)
result += InnerProduct(x[i],y[i]);
return static_cast<double>(result);
}
double Error1 (edge *TheEdge, position *ThePosition, line *TheLine)
{
double v[3], newv[3], temp;
if (!TheEdge || !ThePosition || !TheLine) return (0.0);
ComputeV (v, *TheLine);
RotateQuaternion (newv, ThePosition->q, v);
temp = InnerProduct (newv, TheEdge->m);
return (sqr(temp) / (TheEdge->m_error));
}
static
void BKZStatus(double tt, double enum_time, unsigned long NumIterations,
unsigned long NumTrivial, unsigned long NumNonTrivial,
unsigned long NumNoOps, long m,
const mat_ZZ& B)
{
cerr << "---- BKZ_XD status ----\n";
cerr << "elapsed time: ";
PrintTime(cerr, tt-StartTime);
cerr << ", enum time: ";
PrintTime(cerr, enum_time);
cerr << ", iter: " << NumIterations << "\n";
cerr << "triv: " << NumTrivial;
cerr << ", nontriv: " << NumNonTrivial;
cerr << ", no ops: " << NumNoOps;
cerr << ", rank: " << m;
cerr << ", swaps: " << NumSwaps << "\n";
ZZ t1;
long i;
double prodlen = 0;
for (i = 1; i <= m; i++) {
InnerProduct(t1, B(i), B(i));
if (!IsZero(t1))
prodlen += log(t1);
}
cerr << "log of prod of lengths: " << prodlen/(2.0*log(2.0)) << "\n";
if (LLLDumpFile) {
cerr << "dumping to " << LLLDumpFile << "...";
ofstream f;
OpenWrite(f, LLLDumpFile);
f << "[";
for (i = 1; i <= m; i++) {
f << B(i) << "\n";
}
f << "]\n";
f.close();
cerr << "\n";
}
LastTime = tt;
}
void TraceMod(zz_p& x, const zz_pX& a, const zz_pXModulus& F)
{
long n = F.n;
if (deg(a) >= n)
Error("trace: bad args");
if (F.tracevec.length() == 0)
ComputeTraceVec(F);
InnerProduct(x, a.rep, F.tracevec);
}
uint64_t CGMethod(double *A, double *x, double *b, uint64_t dim, double eps, uint64_t max)
{
max = (max?max:dim);
double *r = new double[dim];
double *p = new double[dim];
double *Ap = new double[dim];
mul(A, x, Ap, dim);
for(uint64_t i = 0; i < dim; ++i)
r[i] = p[i] = b[i] - Ap[i];
for(uint64_t k = 0; k < max; ++k)
{
mul(A, p, Ap, dim);
double alpha = InnerProduct(r, 0, p, dim)/InnerProduct(p, 0, Ap, dim);
double beta = 1./InnerProduct(r, 0, r, dim);
for(uint64_t i = 0; i < dim; ++i)
x[i] += alpha*p[i], r[i] -= alpha*Ap[i];
double gamma = InnerProduct(r, 0, r, dim);
if(gamma < eps)
{
delete [] r;
delete [] p;
delete [] Ap;
return k + 1;
}
beta *= gamma;
for(uint64_t i = 0; i < dim; ++i)
p[i] = r[i] + beta*p[i];
}
delete [] r;
delete [] p;
delete [] Ap;
return max;
}
/*!
* \example SerialExample/ex1.cpp
*
* A simple example of MINRES() usage without preconditioner.
*/
int main()
{
//(1) Define the size of the problem we want to solve
int size(1000);
//(2) Define the linear operator "op" we want to solve.
SimpleOperator op(size);
//(3) Generate a random linear system
op.Randomize(0);
//(3) Define the exact solution (at random)
SimpleVector sol(size);
sol.Randomize( 1 );
//(4) Define the "rhs" as "rhs = op*sol"
SimpleVector rhs(size);
op.Apply(sol, rhs);
double rhsNorm( sqrt(InnerProduct(rhs,rhs)) );
std::cout << "|| rhs || = " << rhsNorm << "\n";
//(5) We don't use any preconditioner. Let prec be a null pointer.
Preconditioner * prec = NULL;
//(6) Use an identically zero initial guess
SimpleVector x(size);
x = 0;
//(7) Set the minres parameters
double shift(0);
int max_iter(10000);
double tol(1e-6);
bool show(false);
//(8) Solve the problem with minres
MINRES(op, x, rhs, prec, shift, max_iter, tol, show);
//(9) Compute the error || x_ex - x_minres ||_2
subtract(x, sol, x);
double err2 = InnerProduct(x,x);
std::cout<< "|| x_ex - x_n || = " << sqrt(err2) << "\n";
std::ofstream fid("ex3.m");
op.Print(fid);
fid<< "rhs = [";
for(int i(0); i<size-1; ++i)
fid<<rhs[i] <<"; ";
fid<<rhs[size-1] <<"]; \n";
fid<<"[ x, istop, itn, rnorm, Arnorm, Anorm, Acond, ynorm ] = minres(Op, rhs, [], 0, true, false, 100, 1e-6);\n";
return 0;
}
double Gradient1 (edge *TheEdge, position *ThePosition, line *TheLine,
int index)
{
double v[3], newv[3], temp1, temp2;
if (!TheEdge || !ThePosition || !TheLine) return (0.0);
ComputeV (v, *TheLine);
RotateQuaternion (newv, ThePosition->q, v);
temp1 = InnerProduct (newv, TheEdge->m);
temp2 = Deriv1 (TheEdge, ThePosition, TheLine, index);
return ( (2.0*temp1*temp2) / (TheEdge->m_error) );
}
bool Sphere::Intersection(const ray& r, intersection_data& intersect)
{
Vector3 result;
Vector3 L;
float Tca, Thc, d, T;
L = center - r.origin;
Tca = InnerProduct(L, r.direction);
if (Tca < 0) return false;
d = InnerProduct(L, L) + Tca * Tca;
if (d > radius * radius) return false;
Thc = sqrt(radius * radius - d);
/* assuming T won't be negative, which should never happen in cases that matter (either we're inside the sphere and so we have bigger problems, or it's behind us)*/
T = std::min(Tca - Thc, Tca + Thc);
intersect.point = (Vector3)r.direction * T;
intersect.col = this->mtl_diffuse; //change to something more complex next submission
intersect.normal = intersect.point - this->center;
intersect.T = T;
return true;
}
static
void hadamard(ZZ& num_bound, ZZ& den_bound,
const mat_ZZ& A, const vec_ZZ& b)
{
long n = A.NumRows();
if (n == 0) Error("internal error: hadamard with n = 0");
ZZ b_len, min_A_len, prod, t1;
InnerProduct(min_A_len, A[0], A[0]);
prod = min_A_len;
long i;
for (i = 1; i < n; i++) {
InnerProduct(t1, A[i], A[i]);
if (t1 < min_A_len)
min_A_len = t1;
mul(prod, prod, t1);
}
if (min_A_len == 0) {
num_bound = 0;
den_bound = 0;
return;
}
InnerProduct(b_len, b, b);
div(t1, prod, min_A_len);
mul(t1, t1, b_len);
SqrRoot(num_bound, t1);
SqrRoot(den_bound, prod);
}