//---------------------------------------------------------
void xyztorst
(
const DVec& X, // [in]
const DVec& Y, // [in]
const DVec& Z, // [in]
DVec& r, // [out]
DVec& s, // [out]
DVec& t // [out]
)
//---------------------------------------------------------
{
// function [r,s,t] = xyztorst(x, y, z)
// Purpose : Transfer from (x,y,z) in equilateral tetrahedron
// to (r,s,t) coordinates in standard tetrahedron
double sqrt3=sqrt(3.0), sqrt6=sqrt(6.0); int Nc=X.size();
DVec v1(3),v2(3),v3(3),v4(3);
DMat tmat1(3,Nc), A(3,3), rhs;
v1(1)=(-1.0); v1(2)=(-1.0/sqrt3); v1(3)=(-1.0/sqrt6);
v2(1)=( 1.0); v2(2)=(-1.0/sqrt3); v2(3)=(-1.0/sqrt6);
v3(1)=( 0.0); v3(2)=( 2.0/sqrt3); v3(3)=(-1.0/sqrt6);
v4(1)=( 0.0); v4(2)=( 0.0 ); v4(3)=( 3.0/sqrt6);
// back out right tet nodes
tmat1.set_row(1,X); tmat1.set_row(2,Y); tmat1.set_row(3,Z);
rhs = tmat1 - 0.5*outer(v2+v3+v4-v1, ones(Nc));
A.set_col(1,0.5*(v2-v1)); A.set_col(2,0.5*(v3-v1)); A.set_col(3,0.5*(v4-v1));
DMat RST = A|rhs;
r=RST.get_row(1); s=RST.get_row(2); t=RST.get_row(3);
}
// DGESV uses the LU factorization to compute solution
// to a real system of linear equations, A * X = B,
// where A is square (N,N) and X, B are (N,NRHS).
//
// If the system is over or under-determined,
// (i.e. A is not square), then pass the problem
// to the Least-squares solver (DGELSS) below.
//---------------------------------------------------------
void umSOLVE(const DMat& mat, const DMat& B, DMat& X)
//---------------------------------------------------------
{
if (!mat.ok()) {umWARNING("umSOLVE()", "system is empty"); return;}
if (!mat.is_square()) {
umSOLVE_LS(mat, B, X); // return a least-squares solution.
return;
}
DMat A(mat); // work with copy of input
X = B; // initialize result with RHS
int rows=A.num_rows(), LDA=A.num_rows(), cols=A.num_cols();
int LDB=B.num_rows(), NRHS=B.num_cols(), info=0;
if (rows<1) {umWARNING("umSOLVE()", "system is empty"); return;}
IVec ipiv(rows);
// Solve the system.
GESV(rows, NRHS, A.data(), LDA, ipiv.data(), X.data(), LDB, info);
if (info < 0) {
X = 0.0;
umERROR("umSOLVE(A,B, X)",
"Error in input argument (%d)\nNo solution computed.", -info);
} else if (info > 0) {
X = 0.0;
umERROR("umSOLVE(A,B, X)",
"\nINFO = %d. U(%d,%d) was exactly zero."
"\nThe factorization has been completed, but the factor U is "
"\nexactly singular, so the solution could not be computed.",
info, info, info);
}
}
// DPOSV uses Cholesky factorization A=U^T*U, A=L*L^T
// to compute the solution to a real system of linear
// equations A*X=B, where A is a square, (N,N) symmetric
// positive definite matrix and X and B are (N,NRHS).
//
// If the system is over or under-determined,
// (i.e. A is not square), then pass the problem
// to the Least-squares solver (DGELSS) below.
//---------------------------------------------------------
void umSOLVE_CH(const DMat& mat, const DMat& B, DMat& X)
//---------------------------------------------------------
{
if (!mat.ok()) {umWARNING("umSOLVE_CH()", "system is empty"); return;}
if (!mat.is_square()) {
umSOLVE_LS(mat, B, X); // return a least-squares solution.
return;
}
DMat A(mat); // Work with a copy of input array.
X = B; // initialize solution with rhs
int rows=A.num_rows(), LDA=A.num_rows(), cols=A.num_cols();
int LDB=X.num_rows(), NRHS=X.num_cols(), info=0;
assert(LDB >= rows); // enough space for solutions?
// Solve the system.
POSV('U', rows, NRHS, A.data(), LDA, X.data(), LDB, info);
if (info < 0) {
X = 0.0;
umERROR("umSOLVE_CH(A,B, X)",
"Error in input argument (%d)\nNo solution computed.", -info);
} else if (info > 0) {
X = 0.0;
umERROR("umSOLVE_CH(A,B, X)",
"\nINFO = %d. The leading minor of order %d of A"
"\nis not positive definite, so the factorization"
"\ncould not be completed. No solution computed.",
info, info);
}
}
//---------------------------------------------------------
DMat& chol(DMat& A, bool in_place)
//---------------------------------------------------------
{
// Given symmetric positive-definite matrix A,
// return its Cholesky-factorization for use
// later in solving (multiple) linear systems.
int M=A.num_rows(), LDA=A.num_rows(), info=0;
char uplo = 'U';
if (in_place)
{
// factorize arg
POTRF (uplo, M, A.data(), LDA, info);
if (info) { umERROR("chol(A)", "dpotrf reports: info = %d", info); }
A.zero_below_diag();
A.set_factmode(FACT_CHOL); // indicate factored state
return A;
}
else
{
// factorize copy of arg
DMat* tmp = new DMat(A, OBJ_temp, "chol(A)");
POTRF (uplo, M, tmp->data(), LDA, info);
if (info) { umERROR("chol(A)", "dpotrf reports: info = %d", info); }
tmp->zero_below_diag();
tmp->set_factmode(FACT_CHOL); // indicate factored state
#if (0)
// compare with Matlab
tmp->print(g_MSGFile, "chol", "lf", 4, 8);
#endif
return (*tmp);
}
}
// compute eigensystem of a real symmetric matrix
//---------------------------------------------------------
void eig_sym(const DMat& A, DVec& ev, DMat& Q, bool bDoEVecs)
//---------------------------------------------------------
{
if (!A.is_square()) { umERROR("eig_sym(A)", "matrix is not square."); }
int N = A.num_rows();
int LDA=N, LDVL=N, LDVR=N, ldwork=10*N, info=0;
DVec work(ldwork, 0.0, OBJ_temp, "work_TMP");
Q = A; // Calculate eigenvectors in Q (optional)
ev.resize(N); // Calculate eigenvalues in ev
char jobV = bDoEVecs ? 'V' : 'N';
SYEV (jobV,'U', N, Q.data(), LDA, ev.data(), work.data(), ldwork, info);
if (info < 0) {
umERROR("eig_sym(A, Re,Im)", "Error in input argument (%d)\nNo solution computed.", -info);
} else if (info > 0) {
umLOG(1, "eig_sym(A, W): ...\n"
"\nthe algorithm failed to converge;"
"\n%d off-diagonal elements of an intermediate"
"\ntridiagonal form did not converge to zero.\n", info);
}
}
//---------------------------------------------------------
DMat& lu(DMat& A, bool in_place)
//---------------------------------------------------------
{
// Given square matrix A, return its lu-factorization
// for use later in solving (multiple) linear systems.
if (!A.is_square()) { umERROR("lu(A)", "matrix is not square."); }
int rows=A.num_rows(); int N=rows, LDA=rows, info=0;
int* ipiv = umIVector(rows);
if (in_place)
{
// factorize arg
GETRF(N, N, A.data(), LDA, ipiv, info);
if (info) { umERROR("lu(A)", "dgetrf reports: info = %d", info); }
A.set_pivots(ipiv); // store pivots
A.set_factmode(FACT_LUP); // indicate factored state
return A;
}
else
{
// factorize copy of arg
DMat* tmp = new DMat(A, OBJ_temp, "lu(A)");
GETRF(N, N, tmp->data(), LDA, ipiv, info);
if (info) { umERROR("lu(A)", "dgetrf reports: info = %d", info); }
tmp->set_pivots(ipiv); // store pivots
tmp->set_factmode(FACT_LUP); // indicate factored state
return (*tmp);
}
}
//---------------------------------------------------------
DMat& qr(DMat& A, bool in_place)
//---------------------------------------------------------
{
// Form orthogonal QR factorization of A(m,n).
// The result Q is represented as a product of
// min(m, n) elementary reflectors.
int M=A.num_rows(), N=A.num_cols(), LDA=A.num_rows();
int min_mn = A.min_mn(), info=0; DVec tau(min_mn);
if (in_place)
{
// factorize arg
GEQRF(M, N, A.data(), LDA, tau.data(), info);
if (info) { umERROR("qr(A)", "dgeqrf reports: info = %d", info); }
//A.set_qrtau(tau); // H(i) = I - tau * v * v'
A.set_factmode(FACT_QR); // indicate factored state
return A;
}
else
{
// factorize copy of arg
DMat* tmp = new DMat(A, OBJ_temp, "qr(A)");
GEQRF (M, N, tmp->data(), LDA, tau.data(), info);
if (info) { umERROR("qr(A)", "dgeqrf reports: info = %d", info); }
//tmp->set_qrtau(tau); // H(i) = I - tau * v * v'
tmp->set_factmode(FACT_QR); // indicate factored state
return (*tmp);
}
}
// DPOSV uses Cholesky factorization A=U^T*U, A=L*L^T
// to compute the solution to a real system of linear
// equations A*X=B, where A is a square, (N,N) symmetric
// positive definite matrix and X and B are (N,NRHS).
//---------------------------------------------------------
void umSOLVE_CH(const DMat& mat, const DVec& b, DVec& x)
//---------------------------------------------------------
{
// check args
assert(mat.is_square()); // symmetric
assert(b.size() >= mat.num_rows()); // is b consistent?
assert(b.size() <= x.size()); // can x store solution?
DMat A(mat); // work with copy of input
x = b; // allocate solution vector
int rows=A.num_rows(), LDA=A.num_rows(), cols=A.num_cols();
int LDB=b.size(), NRHS=1, info=0;
if (rows<1) {umWARNING("umSOLVE_CH()", "system is empty"); return;}
// Solve the system.
POSV('U', rows, NRHS, A.data(), LDA, x.data(), LDB, info);
if (info < 0) {
x = 0.0;
umERROR("umSOLVE_CH(A,b, x)",
"Error in input argument (%d)\nNo solution computed.", -info);
} else if (info > 0) {
x = 0.0;
umERROR("umSOLVE_CH(A,b, x)",
"\nINFO = %d. The leading minor of order %d of A"
"\nis not positive definite, so the factorization"
"\ncould not be completed. No solution computed.",
info, info);
}
}
void scalarMultInPlace(DMat<RT>& A, const typename RT::ElementType &f)
{
for (size_t i=0; i<A.numRows()*A.numColumns(); i++)
{
A.ring().mult(A.array()[i], f, A.array()[i]);
}
}
bool isZero(const DMat<RT>& A)
{
size_t len = A.numRows() * A.numColumns();
if (len == 0) return true;
for (auto t = A.array() + len - 1; t >= A.array(); t--)
if (!A.ring().is_zero(*t)) return false;
return true;
}
void negateInPlace(DMat<RT>& A)
// A = -A
{
size_t len = A.numRows() * A.numColumns();
for (size_t i=0; i<len; i++)
{
A.ring().negate(A.array()[i], A.array()[i]);
}
}
//---------------------------------------------------------
void Euler3D::CouetteBC3D
(
const DVec& xi,
const DVec& yi,
const DVec& zi,
const DVec& nxi,
const DVec& nyi,
const DVec& nzi,
const IVec& tmapI,
const IVec& tmapO,
const IVec& tmapW,
const IVec& tmapC,
double ti,
DMat& Qio
)
//---------------------------------------------------------
{
//#######################################################
// FIXME: what about top and bottom of 3D annulus?
//#######################################################
// gmapB = concat(mapI,mapO,mapW, ...);
// Check for no boundary faces
if (gmapB.size() < 1) {
return;
}
// function [Q] = CouetteBC3D(xin, yin, nxin, nyin, mapI, mapO, mapW, mapC, Q, time);
// Purpose: evaluate solution for Couette flow
// Couette flow (mach .2 at inner cylinder)
// gamma = 1.4;
int Nr = Qio.num_rows();
DVec rho,rhou,rhov,rhow,Ener;
// wrap current state data (columns of Qio)
rho.borrow (Nr, Qio.pCol(1));
rhou.borrow(Nr, Qio.pCol(2));
rhov.borrow(Nr, Qio.pCol(3));
rhow.borrow(Nr, Qio.pCol(4));
Ener.borrow(Nr, Qio.pCol(5));
// update boundary nodes of Qio with boundary data
// pre-calculated in function precalc_bdry_data()
rho (gmapB) = rhoB;
rhou(gmapB) = rhouB;
rhov(gmapB) = rhovB;
rhow(gmapB) = rhowB;
Ener(gmapB) = EnerB;
}
//---------------------------------------------------------
void CurvedINS2D::Report(bool bForce)
//---------------------------------------------------------
{
static DMat vort;
bool normal_report=true;
if (eVolkerCylinder == sim_type) {normal_report=false;}
#if (1)
normal_report=true;
#endif
// print report header on first step
if (1 == tstep) {
if (normal_report) {
umLOG(1, "\n step time min(Ux) max(Ux) min(Vort) max(Vort)\n"
"--------------------------------------------------------------------\n");
} else {
umLOG(1, "\n step time Cd/ra Cl/ra dP \n"
"---------------------------------------------------\n");
}
}
if (normal_report) {
if (!umMOD(tstep,Nreport)||(1==tstep)||(tstep==Nsteps)||bForce) {
Curl2D(Ux, Uy, vort);
umLOG(1, "%7d %6.3lf %10.5lf %10.5lf %10.2lf %10.2lf\n",
tstep, time, Ux.min_val(), Ux.max_val(), vort.min_val(), vort.max_val());
}
} else {
// VolkerCylinder: compute coefficients of drag and lift,
// as well as the pressure drop at the two sample points.
INSLiftDrag2D(0.05);
}
if (!umMOD(tstep,Nrender)||(1==tstep)||(tstep==Nsteps)||bForce)
{
// (this->*ExactSolution)(x, y, time, nu, exUx, exUy, exPR);
Curl2D(Ux, Uy, vort);
// load render data
Q_plot.set_col(1, Ux); // -exUx);
Q_plot.set_col(2, Uy); // -exUy);
Q_plot.set_col(3, PR); // -exPR);
Q_plot.set_col(4, vort);
OutputVTK(Q_plot, NvtkInterp);
}
}
inline void norm2(const DMat<RT>& M, size_t n, typename RT::RealElementType& result)
{
const auto& C = M.ring();
const auto& R = C.real_ring();
typename RT::RealElementType c;
R.init(c);
R.set_zero(result);
for(size_t i=0; i<n; i++) {
C.abs_squared(c,M.entry(0,i));
R.add(result,result,c);
}
R.clear(c);
}
void set(DMat<RT>& A, MatrixWindow wA, const DMat<RT>& B, MatrixWindow wB)
{
M2_ASSERT(wA.sameSize(wB));
long rA = wA.begin_row;
long rB = wB.begin_row;
for ( ; rA < wA.end_row; ++rA, ++rB)
{
long cA = wA.begin_column;
long cB = wB.begin_column;
for ( ; cA < wA.end_column; ++cA, ++cB)
A.ring().set(A.entry(rA,cA), B.entry(rB,cB));
}
}
void scalarMultInPlace(DMat<RT>& A, MatrixWindow wA, const typename RT::ElementType& c)
{
M2_ASSERT(wA.sameSize(wB));
long rA = wA.begin_row;
for ( ; rA < wA.end_row; ++rA)
{
long cA = wA.begin_column;
for ( ; cA < wA.end_column; ++cA)
{
auto& a = A.entry(rA,cA);
A.ring().mult(a, a, c);
}
}
}
void scalarMult(DMat<RT>& A, MatrixWindow wA, const typename RT::ElementType& c, const DMat<RT>& B, MatrixWindow wB)
{
M2_ASSERT(wA.sameSize(wB));
long rA = wA.begin_row;
long rB = wB.begin_row;
for ( ; rA < wA.end_row; ++rA, ++rB)
{
long cA = wA.begin_column;
long cB = wB.begin_column;
for ( ; cA < wA.end_column; ++cA, ++cB)
{
A.ring().mult(A.entry(rA,cA), c, B.entry(rB,cB));
}
}
}
void addTo(DMat<RT>& A, MatrixWindow wA, const DMat<RT>& B, MatrixWindow wB)
{
assert(wA.sameSize(wB));
long rA = wA.begin_row;
long rB = wB.begin_row;
for (; rA < wA.end_row; ++rA, ++rB)
{
long cA = wA.begin_column;
long cB = wB.begin_column;
for (; cA < wA.end_column; ++cA, ++cB)
{
auto& a = A.entry(rA, cA);
A.ring().add(a, a, B.entry(rB, cB));
}
}
}
//---------------------------------------------------------
void CurvedCNS2D::BoxFlowIC2D
(
const DVec& xi, // [in]
const DVec& yi, // [in]
double ti, // [in]
DMat& Qo // [out]
)
//---------------------------------------------------------
{
// function Q = BoxFlowIC2D(x, y, time)
//
// Purpose: compute plane flow configuration
//-------------------------------------
// adjust parameters
//-------------------------------------
this->gamma = 1.4;
this->gm1 = 0.4; // (gamma-1)
//-------------------------------------
// use wrappers to update Qo in-place
//-------------------------------------
DVec rho,rhou,rhov,Ener; int Nr=Np*K;
rho.borrow (Nr, Qo.pCol(1));
rhou.borrow(Nr, Qo.pCol(2));
rhov.borrow(Nr, Qo.pCol(3));
Ener.borrow(Nr, Qo.pCol(4));
if (1)
{
this->pref = 12.0;
rho = 1.0;
rhou = -sin(2.0*pi*y);
rhov = sin(4.0*pi*x);
Ener = pref/gm1 + 0.5*(sqr(rhou) + sqr(rhov)).dd(rho);
}
else
{
this->pref = 12.0;
rho = 1.0;
rhou = 0.0;
rhov = 0.0;
Ener = pref/gm1 + 0.5 * rho.dm(exp(-4.0*(sqr(cos(pi*x))+sqr(cos(pi*y)))));
}
}
void transpose(const DMat<RT>& A, DMat<RT>& result)
{
assert(&A != &result); // these cannot be aliased!
assert(result.numRows() == A.numColumns());
assert(result.numColumns() == A.numRows());
for (size_t c = 0; c < A.numColumns(); ++c)
{
auto i = A.columnBegin(c);
auto j = result.rowBegin(c);
auto end = A.columnEnd(c);
for (; i != end; ++i, ++j) A.ring().set(*j, *i);
}
}
engine_RawArrayIntPairOrNull rawLQUPFactorizationInPlace(MutableMatrix *A, M2_bool transpose)
{
#ifdef HAVE_FFLAS_FFPACK
// Suppose A is m x n
// then we get A = LQUP = LSP, see e.g. http://www.ens-lyon.fr/LIP/Pub/Rapports/RR/RR2006/RR2006-28.pdf
// P and Q are permutation info using LAPACK's convention:, see
// http://www.netlib.org/lapack/explore-html/d0/d39/_v_a_r_i_a_n_t_s_2lu_2_r_e_c_2dgetrf_8f.html
// P is n element permutation on column: size(P)=min(m,n);
// for 1 <= i <= min(m,n), col i of the matrix was interchanged with col P(i).
// Qt is m element permutation on rows (inverse permutation)
// for 1 <= i <= min(m,n), col i of the matrix was interchanged with col P(i).
A->transpose();
DMat<M2::ARingZZpFFPACK> *mat = A->coerce< DMat<M2::ARingZZpFFPACK> >();
if (mat == 0)
{
throw exc::engine_error("LUDivine not defined for this ring");
// ERROR("LUDivine not defined for this ring");
// return 0;
}
size_t nelems = mat->numColumns();
if (mat->numRows() < mat->numColumns()) nelems = mat->numRows();
std::vector<size_t> P(nelems, -1);
std::vector<size_t> Qt(nelems, -1);
// ignore return value (rank) of:
LUdivine(mat->ring().field(),
FFLAS::FflasNonUnit,
(transpose ? FFLAS::FflasTrans : FFLAS::FflasNoTrans),
mat->numRows(),
mat->numColumns(),
mat->array(),
mat->numColumns(),
&P[0],
&Qt[0]);
engine_RawArrayIntPairOrNull result = new engine_RawArrayIntPair_struct;
result->a = stdvector_to_M2_arrayint(Qt);
result->b = stdvector_to_M2_arrayint(P);
return result;
#endif
return 0;
}
//---------------------------------------------------------
DMat& NDG2D::CurvedDGJump2D
(
const DMat& gU, // [in]
const IVec& gmapD, // [in]
const DVec& bcU // [in]
)
//---------------------------------------------------------
{
// function [jumpU] = CurvedDGJump2D(gU, gmapD, bcU)
// purpose: compute discontinuous Galerkin jump applied
// to a field given at cubature and Gauss nodes
DMat mmCHOL; DVec gUM,gUP,fx;
DMat *tmp = new DMat("jumpU", OBJ_temp);
DMat &jumpU(*tmp);
// shorthand references
Cub2D& cub = this->m_cub; Gauss2D& gauss = this->m_gauss;
// surface traces at Gauss nodes
gUM = gU(gauss.mapM);
gUP = gU(gauss.mapP);
if (gmapD.size()>0) { gUP(gmapD) = bcU(gmapD); }
// compute jump term and lift to triangle interiors
fx = gUM - gUP;
jumpU = -gauss.interpT*(gauss.W.dm(fx));
// multiply straight sided triangles by inverse mass matrix
jumpU(All,straight) = VVT * dd(jumpU(All,straight), J(All,straight));
// multiply by custom inverse mass matrix for each curvilinear triangle
int Ncurved = curved.size(), k=0;
for (int m=1; m<=Ncurved; ++m) {
k = curved(m);
mmCHOL.borrow(Np,Np, cub.mmCHOL.pCol(k));
mmCHOL.set_factmode(FACT_CHOL); // indicate factored state
jumpU(All,k) = chol_solve(mmCHOL, jumpU(All,k));
}
// these parameters may be OBJ_temp (allocated on the fly)
if (OBJ_temp == gU.get_mode()) { delete (&gU); }
if (OBJ_temp == bcU.get_mode()) { delete (&bcU); }
return jumpU;
}
//---------------------------------------------------------
void eig(const DMat& A, DVec& Re, DMat& VL, DMat& VR, bool bL, bool bR)
//---------------------------------------------------------
{
// Compute eigensystem of a real general matrix
// Currently NOT returning imaginary components
static DMat B;
if (!A.is_square()) { umERROR("eig(A)", "matrix is not square."); }
int N = A.num_rows();
int LDA=N, LDVL=N, LDVR=N, ldwork=10*N, info=0;
Re.resize(N); // store REAL components of eigenvalues in Re
VL.resize(N,N); // storage for LEFT eigenvectors
VR.resize(N,N); // storage for RIGHT eigenvectors
DVec Im(N); // NOT returning imaginary components
DVec work(ldwork, 0.0);
// Work on a copy of A
B = A;
char jobL = bL ? 'V' : 'N'; // calc LEFT eigenvectors?
char jobR = bR ? 'V' : 'N'; // calc RIGHT eigenvectors?
GEEV (jobL,jobR, N, B.data(), LDA, Re.data(), Im.data(),
VL.data(), LDVL, VR.data(), LDVR, work.data(), ldwork, info);
if (info < 0) {
umERROR("eig(A, Re,Im)", "Error in input argument (%d)\nNo solution computed.", -info);
} else if (info > 0) {
umLOG(1, "eig(A, Re,Im): ...\n"
"\nThe QR algorithm failed to compute all the"
"\neigenvalues, and no eigenvectors have been"
"\ncomputed; elements %d+1:N of WR and WI contain"
"\neigenvalues which have converged.\n", info);
}
#if (0)
// Return (Re,Imag) parts of eigenvalues as columns of Ev
Ev.resize(N,2);
Ev.set_col(1, Re);
Ev.set_col(2, Im);
#endif
#ifdef _DEBUG
//#####################################################
// Check for imaginary components in eigenvalues
//#####################################################
double im_max = Im.max_val_abs();
if (im_max > 1e-6) {
umERROR("eig(A)", "imaginary components in eigenvalues.");
}
//#####################################################
#endif
}
//---------------------------------------------------------
bool lu_solve(DMat& LU, const DMat& B, DMat& X)
//---------------------------------------------------------
{
// Solve a set of linear systems using lu-factored square matrix.
try {
LU.solve_LU(B, X, false, false);
} catch(...) { return false; }
return true;
}
// tex "table" output
//---------------------------------------------------------
void textable
(
string& capt,
FILE* fid,
string* titles,
DMat& entries,
string* form
)
//---------------------------------------------------------
{
int Nrows=entries.num_rows(), Ncols=entries.num_cols(), n=0,m=0;
fprintf(fid, "\\begin{table} \n");
fprintf(fid, "\\caption{%s} \n", capt.c_str());
fprintf(fid, "\\begin{center} \n");
fprintf(fid, "\\begin{tabular}{|");
for (n=1; n<=Ncols; ++n) {
fprintf(fid, "c|");
if (2==n) {
fprintf(fid, "|");
}
}
fprintf(fid, "} \\hline \n ");
for (n=1; n<=(Ncols-1); ++n) {
fprintf(fid, "%s & ", titles[n].c_str());
}
fprintf(fid, " %s \\\\ \\hline \n ", titles[Ncols].c_str());
for (m=1; m<=Nrows; ++m) {
for (n=1; n<=(Ncols-1); ++n) {
fprintf(fid, form[n].c_str(), entries(m,n)); fprintf(fid, " & ");
}
if (m<Nrows) {
fprintf(fid, form[Ncols].c_str(), entries(m,Ncols)); fprintf(fid, " \\\\ \n ");
} else {
fprintf(fid, form[Ncols].c_str(), entries(m,Ncols)); fprintf(fid, " \\\\ \\hline \n ");
}
}
fprintf(fid, "\\end{tabular} \n");
fprintf(fid, "\\end{center} \n");
fprintf(fid, "\\end{table} \n");
}
//---------------------------------------------------------
void CurvedINS2D::BackdropIC2D
(
const DVec& xi,
const DVec& yi,
double ti, // [in]
double nu, // [in]
DMat& Uxo, // [out]
DMat& Uyo, // [out]
DMat& PRo // [out]
)
//---------------------------------------------------------
{
// function [Ux, Uy, PR] = BackdropIC2D(x, y, time, nu)
// Purpose: evaluate solution for "Backdrop" configuration
Uxo.fill(0.0);
Uyo.fill(0.0);
PRo.fill(0.0);
}
inline void lowdegreesweep(DMat& m, size_t i, DynamicVector<NodeEliminationStatus>& status) {
bool hasLowDegreeNeighbour = false;
/* Cerco vicini low-degree*/
for (size_t j = 0; j < m.rows(); ++j) {
if (j != i && status[j] == LOW_DEGREE) {
hasLowDegreeNeighbour = true;
status[i] = NOT_ELIMINATED;
break;
}
}
/* Se non aveva un vicino low_degree allora è lui il nodo low_degree!*/
if (!hasLowDegreeNeighbour) {
status[i] = LOW_DEGREE;
for (size_t j = 0; j < m.rows(); ++j) {
if (j != i)
status[j] = NOT_ELIMINATED;
}
}
}
inline M2_arrayintOrNull rankProfile(const DMat<RT>& A,
bool row_profile)
{
std::vector<size_t> profile;
if (row_profile)
{
// First transpose A
DMat<RT> B(A.ring(), A.numColumns(), A.numRows());
MatrixOps::transpose(A,B);
DMatLinAlg<RT> LUdecomp(B);
LUdecomp.columnRankProfile(profile);
return stdvector_to_M2_arrayint(profile);
}
else
{
DMatLinAlg<RT> LUdecomp(A);
LUdecomp.columnRankProfile(profile);
return stdvector_to_M2_arrayint(profile);
}
}
//---------------------------------------------------------
void EulerShock2D::Report(bool bForce)
//---------------------------------------------------------
{
CurvedEuler2D::Report(bForce);
if (tstep>=1 && tstep <= resid.size())
{
// calculate residual
// resid(tstep) = sqrt(sum(sum(sum((Q-oldQ).^2)))/(4*K*Np));
// resid(tstep) = sqrt(sum(sum(sum((Q-oldQ).^2)))/(4*K*Np))/dt;
DMat Qresid = sqr(Q-oldQ); double d4KNp = double(4*K*Np);
resid(tstep) = sqrt(Qresid.sum()/d4KNp);
if (eScramInlet == sim_type) {
// scale residual
resid(tstep) /= dt;
}
}
}
inline void eliminationOperators(DMat& A, DynamicVector<size_t>& Cset, size_t fnode,
DynamicVector<double>& q, SpMat& P, size_t& P_col, size_t P_row) {
double scalingFactor = 1.0;
P.reserve(P_row, A.nonZeros(fnode) - 1);
DynamicVector<size_t>::Iterator ccol = Cset.begin();
for (size_t frow = 0; frow < A.rows(); ++frow) {
if (frow == fnode) { //Elemento sulla diagonale
q[P_row] = (1.0 / A(frow, fnode));
scalingFactor = -(q[P_row]);
} else if (ccol != Cset.end()) {
break; //Non ha senso andare avanti se abbiamo finito i ccol
} else if (frow == (*ccol)) {
P.append(P_row, P_col, A(frow, fnode));
P_col++;
ccol++;
}
}
P.finalize(P_row);
for (SpMat::Iterator it = P.begin(P_row); it != P.end(P_row); it++)
it->value() *= -scalingFactor;
}