Same as compute(matter, dir) but with an explicit mobile atom list (intersected with free flags).
Eigenvector rows outside the list are 0.
51 {
54 lowestEv.resize(matter->numberOfAtoms(), 3);
56
58 const int size = 3 * static_cast<int>(mobile.size());
59 if (size == 0) {
61 return;
62 }
63
64 const long maxIters = std::max(1L,
params.lanczos_options().max_iterations);
65 MatrixXd T(size, maxIters), Q(size, maxIters);
66 T.setZero();
68
69 double alpha, beta = r.norm();
72 return;
73 }
74 double ew = 0, ewOld = 0, ewAbsRelErr;
75 const double dr =
params.main_options().finiteDifference;
77
78
81 VectorXd evEst, evT, evOldEst;
82
83 auto tmpMatter = std::make_unique<Matter>(*matter);
84 const long forceCallsStart = tmpMatter->getForceCalls();
85 const AtomMatrix pos0 = matter->getPositions();
86 const VectorXd force0 =
mobileForces(tmpMatter.get(), mobile);
87
88 auto applyH = [&](const VectorXd &v) -> VectorXd {
89 auto at = [&](double scale) -> VectorXd {
92 pos);
93 tmpMatter->setPositions(pos);
95 };
97 };
98
99 for (int i = 0; i < size; i++) {
101 Q.col(i) = r / beta;
102
103 u = applyH(Q.col(i));
104
105 if (i == 0) {
106 r = u;
107 } else {
108 r = u - beta * Q.col(i - 1);
109 }
110 alpha = Q.col(i).dot(r);
111 r = r - alpha * Q.col(i);
112
113 T(i, i) = alpha;
114 if (i > 0) {
115 T(i - 1, i) = beta;
116 T(i, i - 1) = beta;
117 }
118
119 beta = r.norm();
120
121
122 const bool krylovClosed = beta <= 1e-10 * std::fabs(alpha);
123
124 if (i >= 1) {
125 Eigen::SelfAdjointEigenSolver<MatrixXd> es(T.block(0, 0, i + 1, i + 1));
126 ew = es.eigenvalues()(0);
127 evT = es.eigenvectors().col(0);
129 std::fabs(ewOld), 1.0);
130 ewOld = ew;
131
132 evEst = Q.block(0, 0, size, i + 1) * evT;
133 eonc::safemath::safe_normalize_inplace(evEst);
137 evOldEst = evEst;
139 "[ILanczos] {:9s} {:9s} {:10s} {:14s} {:9.4f} "
140 "{:10.6f} {:7.3f} {:5} n_mobile={}",
141 "----", "----", "----", "----", ew, ewAbsRelErr,
143 if (krylovClosed) {
144 QUILL_LOG_ERROR(
log,
"[ILanczos] ERROR: linear dependence");
145 break;
146 }
147 if (ewAbsRelErr <
params.lanczos_options().tolerance) {
148 QUILL_LOG_INFO(
log,
"[ILanczos] Tolerance reached: {}",
149 params.lanczos_options().tolerance);
150 break;
151 }
152 } else {
153 ew = alpha;
154 ewOld = ew;
155 evEst = Q.col(0);
156 evOldEst = Q.col(0);
157 if (krylovClosed) {
158 QUILL_LOG_ERROR(
log,
"[ILanczos] ERROR: linear dependence");
159 break;
160 }
163 double Cnew = u.dot(Q.col(i));
165 std::fabs(Cprev), 1.0);
166 if (ewAbsRelErr <=
params.lanczos_options().tolerance) {
169 QUILL_LOG_INFO(
log,
"[ILanczos] Tolerance reached: {}",
170 params.lanczos_options().tolerance);
171 break;
172 }
173 }
174 }
175
176 if (i >=
params.lanczos_options().max_iterations - 1) {
177 QUILL_LOG_ERROR(
log,
"[ILanczos] Max iterations");
178 break;
179 }
180 }
181
184
186 if (evEst.size() == size) {
188 }
189}
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic, eOnStorageOrder > MatrixXd
Eigen::Matrix< double, Eigen::Dynamic, 3, eOnStorageOrder > AtomMatrix
constexpr double safe_div(double num, double denom, double fallback=0.0)
double safe_acos(double x)
FdScheme
Real finite-difference scheme for the assembled Hessian and for Lanczos/Davidson Hessian-vector produ...
VectorXd fdHessianVector(FdScheme scheme, double dr, const VectorXd &force0, Eval &&eval)
Energy Hessian-vector product -dF.
void unpackMobileRows(const VectorXd &packed, const VectorXi &mobile, AtomMatrix &full)
Write a 3*n_mobile vector into full AtomMatrix rows (other rows unchanged).
FdScheme parseFdScheme(std::string_view scheme)
VectorXd packMobileRows(const AtomMatrix &full, const VectorXi &mobile)
Pack full (n_atoms,3) rows of mobile atoms into a 3*n_mobile vector.
VectorXd mobileForces(Matter *matter, const VectorXi &mobile)
Force components on mobile atoms after Matter has a valid force cache (calls getForces under the hood...