#include "solvespace.h" const double System::RANK_MAG_TOLERANCE = 1e-4; const double System::CONVERGE_TOLERANCE = 1e-10; void System::WriteJacobian(int tag) { int a, i, j; j = 0; for(a = 0; a < param.n; a++) { Param *p = &(param.elem[a]); if(p->tag != tag) continue; mat.param[j] = p->h; j++; } mat.n = j; i = 0; for(a = 0; a < eq.n; a++) { Equation *e = &(eq.elem[a]); if(e->tag != tag) continue; mat.eq[i] = e->h; Expr *f = e->e->DeepCopyWithParamsAsPointers(¶m, &(SS.param)); f = f->FoldConstants(); // Hash table (61 bits) to accelerate generation of zero partials. QWORD scoreboard = f->ParamsUsed(); for(j = 0; j < mat.n; j++) { Expr *pd; if(scoreboard & ((QWORD)1 << (mat.param[j].v % 61)) && f->DependsOn(mat.param[j])) { pd = f->PartialWrt(mat.param[j]); pd = pd->FoldConstants(); pd = pd->DeepCopyWithParamsAsPointers(¶m, &(SS.param)); } else { pd = Expr::From(0.0); } mat.A.sym[i][j] = pd; } mat.B.sym[i] = f; i++; } mat.m = i; } void System::EvalJacobian(void) { int i, j; for(i = 0; i < mat.m; i++) { for(j = 0; j < mat.n; j++) { mat.A.num[i][j] = (mat.A.sym[i][j])->Eval(); } } } bool System::IsDragged(hParam p) { if(SS.GW.pending.point.v) { // The pending point could be one in a group that has not yet // been processed, in which case the lookup will fail; but // that's not an error. Entity *pt = SS.entity.FindByIdNoOops(SS.GW.pending.point); if(pt) { switch(pt->type) { case Entity::POINT_N_TRANS: case Entity::POINT_IN_3D: if(p.v == (pt->param[0]).v) return true; if(p.v == (pt->param[1]).v) return true; if(p.v == (pt->param[2]).v) return true; break; case Entity::POINT_IN_2D: if(p.v == (pt->param[0]).v) return true; if(p.v == (pt->param[1]).v) return true; break; } } } if(SS.GW.pending.circle.v) { Entity *circ = SS.entity.FindByIdNoOops(SS.GW.pending.circle); if(circ) { Entity *dist = SS.GetEntity(circ->distance); switch(dist->type) { case Entity::DISTANCE: if(p.v == (dist->param[0].v)) return true; break; } } } if(SS.GW.pending.normal.v) { Entity *norm = SS.entity.FindByIdNoOops(SS.GW.pending.normal); if(norm) { switch(norm->type) { case Entity::NORMAL_IN_3D: if(p.v == (norm->param[0].v)) return true; if(p.v == (norm->param[1].v)) return true; if(p.v == (norm->param[2].v)) return true; if(p.v == (norm->param[3].v)) return true; break; // other types are locked, so not draggable } } } return false; } void System::SolveBySubstitution(void) { int i; for(i = 0; i < eq.n; i++) { Equation *teq = &(eq.elem[i]); Expr *tex = teq->e; if(tex->op == Expr::MINUS && tex->a->op == Expr::PARAM && tex->b->op == Expr::PARAM) { hParam a = (tex->a)->x.parh; hParam b = (tex->b)->x.parh; if(!(param.FindByIdNoOops(a) && param.FindByIdNoOops(b))) { // Don't substitute unless they're both solver params; // otherwise it's an equation that can be solved immediately, // or an error to flag later. continue; } if(IsDragged(a)) { // A is being dragged, so A should stay, and B should go hParam t = a; a = b; b = t; } int j; for(j = 0; j < eq.n; j++) { Equation *req = &(eq.elem[j]); (req->e)->Substitute(a, b); // A becomes B, B unchanged } for(j = 0; j < param.n; j++) { Param *rp = &(param.elem[j]); if(rp->substd.v == a.v) { rp->substd = b; } } Param *ptr = param.FindById(a); ptr->tag = VAR_SUBSTITUTED; ptr->substd = b; teq->tag = EQ_SUBSTITUTED; } } } //----------------------------------------------------------------------------- // Calculate the rank of the Jacobian matrix, by Gram-Schimdt orthogonalization // in place. A row (~equation) is considered to be all zeros if its magnitude // is less than the tolerance RANK_MAG_TOLERANCE. //----------------------------------------------------------------------------- int System::CalculateRank(void) { // Actually work with magnitudes squared, not the magnitudes double rowMag[MAX_UNKNOWNS]; ZERO(&rowMag); double tol = RANK_MAG_TOLERANCE*RANK_MAG_TOLERANCE; int i, iprev, j; int rank = 0; for(i = 0; i < mat.m; i++) { // Subtract off this row's component in the direction of any // previous rows for(iprev = 0; iprev < i; iprev++) { if(rowMag[iprev] <= tol) continue; // ignore zero rows double dot = 0; for(j = 0; j < mat.n; j++) { dot += (mat.A.num[iprev][j]) * (mat.A.num[i][j]); } for(j = 0; j < mat.n; j++) { mat.A.num[i][j] -= (dot/rowMag[iprev])*mat.A.num[iprev][j]; } } // Our row is now normal to all previous rows; calculate the // magnitude of what's left double mag = 0; for(j = 0; j < mat.n; j++) { mag += (mat.A.num[i][j]) * (mat.A.num[i][j]); } if(mag > tol) { rank++; } rowMag[i] = mag; } return rank; } bool System::SolveLinearSystem(double X[], double A[][MAX_UNKNOWNS], double B[], int n) { // Gaussian elimination, with partial pivoting. It's an error if the // matrix is singular, because that means two constraints are // equivalent. int i, j, ip, jp, imax; double max, temp; for(i = 0; i < n; i++) { // We are trying eliminate the term in column i, for rows i+1 and // greater. First, find a pivot (between rows i and N-1). max = 0; for(ip = i; ip < n; ip++) { if(fabs(A[ip][i]) > max) { imax = ip; max = fabs(A[ip][i]); } } // Don't give up on a singular matrix unless it's really bad; the // assumption code is responsible for identifying that condition, // so we're not responsible for reporting that error. if(fabs(max) < 1e-20) return false; // Swap row imax with row i for(jp = 0; jp < n; jp++) { SWAP(double, A[i][jp], A[imax][jp]); } SWAP(double, B[i], B[imax]); // For rows i+1 and greater, eliminate the term in column i. for(ip = i+1; ip < n; ip++) { temp = A[ip][i]/A[i][i]; for(jp = i; jp < n; jp++) { A[ip][jp] -= temp*(A[i][jp]); } B[ip] -= temp*B[i]; } } // We've put the matrix in upper triangular form, so at this point we // can solve by back-substitution. for(i = n - 1; i >= 0; i--) { if(fabs(A[i][i]) < 1e-20) return false; temp = B[i]; for(j = n - 1; j > i; j--) { temp -= X[j]*A[i][j]; } X[i] = temp / A[i][i]; } return true; } bool System::SolveLeastSquares(void) { int r, c, i; // Scale the columns; this scale weights the parameters for the least // squares solve, so that we can encourage the solver to make bigger // changes in some parameters, and smaller in others. for(c = 0; c < mat.n; c++) { if(IsDragged(mat.param[c])) { // It's least squares, so this parameter doesn't need to be all // that big to get a large effect. mat.scale[c] = 1/20.0; } else { mat.scale[c] = 1; } for(r = 0; r < mat.m; r++) { mat.A.num[r][c] *= mat.scale[c]; } } // Write A*A' for(r = 0; r < mat.m; r++) { for(c = 0; c < mat.m; c++) { // yes, AAt is square double sum = 0; for(i = 0; i < mat.n; i++) { sum += mat.A.num[r][i]*mat.A.num[c][i]; } mat.AAt[r][c] = sum; } } if(!SolveLinearSystem(mat.Z, mat.AAt, mat.B.num, mat.m)) return false; // And multiply that by A' to get our solution. for(c = 0; c < mat.n; c++) { double sum = 0; for(i = 0; i < mat.m; i++) { sum += mat.A.num[i][c]*mat.Z[i]; } mat.X[c] = sum * mat.scale[c]; } return true; } bool System::NewtonSolve(int tag) { if(mat.m > mat.n) return false; int iter = 0; bool converged = false; int i; // Evaluate the functions at our operating point. for(i = 0; i < mat.m; i++) { mat.B.num[i] = (mat.B.sym[i])->Eval(); } do { // And evaluate the Jacobian at our initial operating point. EvalJacobian(); if(!SolveLeastSquares()) break; // Take the Newton step; // J(x_n) (x_{n+1} - x_n) = 0 - F(x_n) for(i = 0; i < mat.n; i++) { Param *p = param.FindById(mat.param[i]); p->val -= mat.X[i]; if(isnan(p->val)) { // Very bad, and clearly not convergent return false; } } // Re-evalute the functions, since the params have just changed. for(i = 0; i < mat.m; i++) { mat.B.num[i] = (mat.B.sym[i])->Eval(); } // Check for convergence converged = true; for(i = 0; i < mat.m; i++) { if(isnan(mat.B.num[i])) { return false; } if(fabs(mat.B.num[i]) > CONVERGE_TOLERANCE) { converged = false; break; } } } while(iter++ < 50 && !converged); return converged; } void System::WriteEquationsExceptFor(hConstraint hc, hGroup hg) { int i; // Generate all the equations from constraints in this group for(i = 0; i < SS.constraint.n; i++) { Constraint *c = &(SS.constraint.elem[i]); if(c->group.v != hg.v) continue; if(c->h.v == hc.v) continue; c->Generate(&eq); } // And the equations from entities for(i = 0; i < SS.entity.n; i++) { Entity *e = &(SS.entity.elem[i]); if(e->group.v != hg.v) continue; e->GenerateEquations(&eq); } // And from the groups themselves (SS.GetGroup(hg))->GenerateEquations(&eq); } void System::FindWhichToRemoveToFixJacobian(Group *g) { int a, i; (g->solved.remove).Clear(); for(a = 0; a < 2; a++) { for(i = 0; i < SS.constraint.n; i++) { Constraint *c = &(SS.constraint.elem[i]); if(c->group.v != g->h.v) continue; if((c->type == Constraint::POINTS_COINCIDENT && a == 0) || (c->type != Constraint::POINTS_COINCIDENT && a == 1)) { // Do the constraints in two passes: first everything but // the point-coincident constraints, then only those // constraints (so they appear last in the list). continue; } param.ClearTags(); eq.Clear(); WriteEquationsExceptFor(c->h, g->h); eq.ClearTags(); // It's a major speedup to solve the easy ones by substitution here, // and that doesn't break anything. SolveBySubstitution(); WriteJacobian(0); EvalJacobian(); int rank = CalculateRank(); if(rank == mat.m) { // We fixed it by removing this constraint (g->solved.remove).Add(&(c->h)); } } } } void System::Solve(Group *g, bool andFindFree) { g->solved.remove.Clear(); WriteEquationsExceptFor(Constraint::NO_CONSTRAINT, g->h); int i, j = 0; /* dbp("%d equations", eq.n); for(i = 0; i < eq.n; i++) { dbp(" %.3f = %s = 0", eq.elem[i].e->Eval(), eq.elem[i].e->Print()); } dbp("%d parameters", param.n); for(i = 0; i < param.n; i++) { dbp(" param %08x at %.3f", param.elem[i].h.v, param.elem[i].val); } */ // All params and equations are assigned to group zero. param.ClearTags(); eq.ClearTags(); SolveBySubstitution(); // Before solving the big system, see if we can find any equations that // are soluble alone. This can be a huge speedup. We don't know whether // the system is consistent yet, but if it isn't then we'll catch that // later. int alone = 1; for(i = 0; i < eq.n; i++) { Equation *e = &(eq.elem[i]); if(e->tag != 0) continue; hParam hp = e->e->ReferencedParams(¶m); if(hp.v == Expr::NO_PARAMS.v) continue; if(hp.v == Expr::MULTIPLE_PARAMS.v) continue; Param *p = param.FindById(hp); if(p->tag != 0) continue; // let rank test catch inconsistency e->tag = alone; p->tag = alone; WriteJacobian(alone); if(!NewtonSolve(alone)) { // Failed to converge, bail out early goto didnt_converge; } alone++; } // Now write the Jacobian for what's left, and do a rank test; that // tells us if the system is inconsistently constrained. WriteJacobian(0); EvalJacobian(); int rank = CalculateRank(); if(rank != mat.m) { FindWhichToRemoveToFixJacobian(g); g->solved.how = Group::SINGULAR_JACOBIAN; g->solved.dof = 0; TextWindow::ReportHowGroupSolved(g->h); return; } // This is not the full Jacobian, but any substitutions or single-eq // solves removed one equation and one unknown, therefore no effect // on the number of DOF. g->solved.dof = mat.n - mat.m; // And do the leftovers as one big system if(!NewtonSolve(0)) { goto didnt_converge; } // If requested, find all the free (unbound) variables. This might be // more than the number of degrees of freedom. Don't always do this, // because the display would get annoying and it's slow. for(i = 0; i < param.n; i++) { Param *p = &(param.elem[i]); p->free = false; if(andFindFree) { if(p->tag == 0) { p->tag = VAR_DOF_TEST; WriteJacobian(0); EvalJacobian(); rank = CalculateRank(); if(rank == mat.m) { p->free = true; } p->tag = 0; } } } // System solved correctly, so write the new values back in to the // main parameter table. for(i = 0; i < param.n; i++) { Param *p = &(param.elem[i]); double val; if(p->tag == VAR_SUBSTITUTED) { val = param.FindById(p->substd)->val; } else { val = p->val; } Param *pp = SS.GetParam(p->h); pp->val = val; pp->known = true; pp->free = p->free; } if(g->solved.how != Group::SOLVED_OKAY) { g->solved.how = Group::SOLVED_OKAY; TextWindow::ReportHowGroupSolved(g->h); } return; didnt_converge: g->solved.how = Group::DIDNT_CONVERGE; (g->solved.remove).Clear(); SS.constraint.ClearTags(); for(i = 0; i < eq.n; i++) { if(fabs(mat.B.num[i]) > CONVERGE_TOLERANCE || isnan(mat.B.num[i])) { // This constraint is unsatisfied. if(!mat.eq[i].isFromConstraint()) continue; hConstraint hc = mat.eq[i].constraint(); Constraint *c = SS.constraint.FindByIdNoOops(hc); if(!c) continue; // Don't double-show constraints that generated multiple // unsatisfied equations if(!c->tag) { (g->solved.remove).Add(&(c->h)); c->tag = 1; } } } TextWindow::ReportHowGroupSolved(g->h); }