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jiri committed 2026-10-30 21:56:04 +01:00
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commit 176562f088
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davidson.h
+1 -1
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@@ -42,7 +42,7 @@ namespace LA {
//@@@implement start from larger Krylov space than a single vector - useful for multiroot solutions
//Davidson algorithm: J. Comp. Phys. 17:817 (1975)
//Davidson algorithm: J. Comput. Phys. 17, 87 (1975)
template <typename T, typename Matrix>
diis.h
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@@ -57,7 +57,7 @@ public:
~DIIS();
DIIS(const DIIS &) = delete; //owns raw storage, not copyable
DIIS & operator=(const DIIS &) = delete;
typename LA_traits<U>::normtype extrapolate(T &vec, U &errvec, bool verbose=false, const Un diiseps=0, bool errvecout=false); //vec is input/output, errvec optionally too; returns square residual norm
typename LA_traits<U>::normtype extrapolate(T &vec, U &errvec, bool verbose=false, const Un diiseps=0, bool errvecout=false); //vec is input/output, errvec optionally too; returns the norm of the input errvec (1 in the first call)
};
template<typename T, typename U>
mat.cc
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@@ -1402,7 +1402,7 @@ const NRSMat<T> NRMat<T>::timestransposed() const {
/***************************************************************************//**
* fill given real matrix with random numbers
* @param[in] x generate random numbers from the interval [0, x]
* @param[in] x generate random numbers from the interval [-x, x)
******************************************************************************/
template<>
void NRMat<double>::randomize(const double &x) {
@@ -1432,7 +1432,7 @@ void NRMat<double>::randomize(const double &x) {
/***************************************************************************//**
* fill given complex matrix with random numbers
* real/imaginary components are generated independently
* @param[in] x generate random numbers from the interval [0, x]
* @param[in] x generate random numbers from the interval [-x, x)
******************************************************************************/
template<>
void NRMat<std::complex<double> >::randomize(const double &x) {
mat.h
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@@ -207,9 +207,9 @@ public:
//! unary minus
const NRMat operator-() const;
//! add scalar value to all matrix elements and return the result by value
//! add scalar value to the diagonal elements and return the result by value
inline const NRMat operator+(const T &a) const;
//! subtract scalar value from all matrix elements and return the result by value
//! subtract scalar value from the diagonal elements and return the result by value
inline const NRMat operator-(const T &a) const;
//! multiply all matrix elements by a scalar value and return the result by value
inline const NRMat operator*(const T &a) const;
optimize.cc
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@@ -1,6 +1,7 @@
/*
LA: linear algebra C++ interface library
Copyright (C) 2026 Jiri Pittner <jiri.pittner@jh-inst.cas.cz> or <jiri@pittnerovi.com>
This code has been prepared with the assistance of an AI (Claude Opus 5.5, Anthropic).
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -2074,6 +2075,9 @@ template class QNG_Optimizer<T>; \
template class Adam_Optimizer<T>; \
template class SPSA_Optimizer<T>; \
template T linemin_brent(optevaluator<T> &e, NRVec<T> &x, T &f, const NRVec<T> &u, const T t1, const T tol, const T abstol, const int maxiter, const int verbose); \
template optresult<T> linesearch_minimize(const char *name, linesearch_direction<T> &dir, const OptProblem<T> *o, NRVec<T> &x, const linesearch_hyperparameters<T> &hp, hyperparameters<T> *achieved); \
template optresult<T> firstorder_minimize(const char *name, firstorder_step<T> &stepper, const OptProblem<T> *o, NRVec<T> &x, const firstorder_hyperparameters<T> &hp, hyperparameters<T> *achieved, gradient_estimator<T> *est); \
template optresult<T> trustregion_minimize(const char *name, trustregion_step<T> &stepper, const OptProblem<T> *o, NRVec<T> &x, const trustregion_hyperparameters<T> &hp, hyperparameters<T> *achieved); \
INSTANTIZE(double)
optimize.h
+1
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@@ -1,6 +1,7 @@
/*
LA: linear algebra C++ interface library
Copyright (C) 2021 Jiri Pittner <jiri.pittner@jh-inst.cas.cz> or <jiri@pittnerovi.com>
This code has been prepared with the assistance of an AI (Claude Opus 5.5, Anthropic).
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by