head 1.5; access; symbols pkgsrc-2026Q1:1.5.0.10 pkgsrc-2026Q1-base:1.5 pkgsrc-2025Q4:1.5.0.8 pkgsrc-2025Q4-base:1.5 pkgsrc-2025Q3:1.5.0.6 pkgsrc-2025Q3-base:1.5 pkgsrc-2025Q2:1.5.0.4 pkgsrc-2025Q2-base:1.5 pkgsrc-2025Q1:1.5.0.2 pkgsrc-2025Q1-base:1.5 pkgsrc-2024Q4:1.3.0.12 pkgsrc-2024Q4-base:1.3 pkgsrc-2024Q3:1.3.0.10 pkgsrc-2024Q3-base:1.3 pkgsrc-2024Q2:1.3.0.8 pkgsrc-2024Q2-base:1.3 pkgsrc-2024Q1:1.3.0.6 pkgsrc-2024Q1-base:1.3 pkgsrc-2023Q4:1.3.0.4 pkgsrc-2023Q4-base:1.3 pkgsrc-2023Q3:1.3.0.2 pkgsrc-2023Q3-base:1.3 pkgsrc-2023Q2:1.2.0.16 pkgsrc-2023Q2-base:1.2 pkgsrc-2023Q1:1.2.0.14 pkgsrc-2023Q1-base:1.2 pkgsrc-2022Q4:1.2.0.12 pkgsrc-2022Q4-base:1.2 pkgsrc-2022Q3:1.2.0.10 pkgsrc-2022Q3-base:1.2 pkgsrc-2022Q2:1.2.0.8 pkgsrc-2022Q2-base:1.2 pkgsrc-2022Q1:1.2.0.6 pkgsrc-2022Q1-base:1.2 pkgsrc-2021Q4:1.2.0.4 pkgsrc-2021Q4-base:1.2 pkgsrc-2021Q3:1.2.0.2 pkgsrc-2021Q3-base:1.2 pkgsrc-2021Q2:1.1.0.46 pkgsrc-2021Q2-base:1.1 pkgsrc-2021Q1:1.1.0.44 pkgsrc-2021Q1-base:1.1 pkgsrc-2020Q4:1.1.0.42 pkgsrc-2020Q4-base:1.1 pkgsrc-2020Q3:1.1.0.40 pkgsrc-2020Q3-base:1.1 pkgsrc-2020Q2:1.1.0.36 pkgsrc-2020Q2-base:1.1 pkgsrc-2020Q1:1.1.0.16 pkgsrc-2020Q1-base:1.1 pkgsrc-2019Q4:1.1.0.38 pkgsrc-2019Q4-base:1.1 pkgsrc-2019Q3:1.1.0.34 pkgsrc-2019Q3-base:1.1 pkgsrc-2019Q2:1.1.0.32 pkgsrc-2019Q2-base:1.1 pkgsrc-2019Q1:1.1.0.30 pkgsrc-2019Q1-base:1.1 pkgsrc-2018Q4:1.1.0.28 pkgsrc-2018Q4-base:1.1 pkgsrc-2018Q3:1.1.0.26 pkgsrc-2018Q3-base:1.1 pkgsrc-2018Q2:1.1.0.24 pkgsrc-2018Q2-base:1.1 pkgsrc-2018Q1:1.1.0.22 pkgsrc-2018Q1-base:1.1 pkgsrc-2017Q4:1.1.0.20 pkgsrc-2017Q4-base:1.1 pkgsrc-2017Q3:1.1.0.18 pkgsrc-2017Q3-base:1.1 pkgsrc-2017Q2:1.1.0.14 pkgsrc-2017Q2-base:1.1 pkgsrc-2017Q1:1.1.0.12 pkgsrc-2017Q1-base:1.1 pkgsrc-2016Q4:1.1.0.10 pkgsrc-2016Q4-base:1.1 pkgsrc-2016Q3:1.1.0.8 pkgsrc-2016Q3-base:1.1 pkgsrc-2016Q2:1.1.0.6 pkgsrc-2016Q2-base:1.1 pkgsrc-2016Q1:1.1.0.4 pkgsrc-2016Q1-base:1.1 pkgsrc-2015Q4:1.1.0.2 pkgsrc-2015Q4-base:1.1; locks; strict; comment @# @; 1.5 date 2025.02.06.08.47.14; author adam; state Exp; branches; next 1.4; commitid PA3ZkcQ2kmcE1oIF; 1.4 date 2024.12.27.17.22.12; author adam; state Exp; branches; next 1.3; commitid GrpkL6NhkYvUbaDF; 1.3 date 2023.08.11.08.31.20; author mef; state Exp; branches; next 1.2; commitid p2mAohExTzLmslAE; 1.2 date 2021.09.18.05.06.06; author mef; state Exp; branches; next 1.1; commitid OrwMPvzxErRZyo9D; 1.1 date 2015.11.28.07.33.38; author wen; state Exp; branches; next ; commitid Yiyzk7twDpSbyPKy; desc @@ 1.5 log @nlopt: updated to 2.10.0 NLopt 2.10 * New Java bindings * Allow disabling exceptions with `set_exceptions_enabled` * Configurable `tolg` tolerance parameter for Luksan gradient stopping condition * Restored `LD_LBFGS_NOCEDAL` enum value (dropped in 2.9) to ease backwards compatibility for wrappers in other languages (though this algorithm is currently unimplemented) @ text @@@comment $NetBSD: PLIST,v 1.4 2024/12/27 17:22:12 adam Exp $ include/nlopt.h include/nlopt.hpp lib/cmake/nlopt/NLoptConfig.cmake lib/cmake/nlopt/NLoptConfigVersion.cmake lib/cmake/nlopt/NLoptLibraryDepends-release.cmake lib/cmake/nlopt/NLoptLibraryDepends.cmake lib/libnlopt.so lib/libnlopt.so.1 lib/libnlopt.so.1.0.0 lib/pkgconfig/nlopt.pc man/man3/nlopt.3 man/man3/nlopt_minimize.3 man/man3/nlopt_minimize_constrained.3 @ 1.4 log @nlopt: updated to 2.9.1 NLopt 2.9.1 * Fixed PRAXIS box constraints NLopt 2.9 * New `NLOPT_LUKSAN` cmake option to build without Luksan LGPL code * Dropped unused LD_LBFGS_NOCEDAL enum value. * Python 3.13 support * Fixed COBYLA not returning the optimum * Fixed SLSQP returning infeasible optimum * Fixed STOGO not registering new optimum * Various minor bugfixes NLopt 2.8 * Support C++ functors for objective functions * CCSA/MMA an now use the `initial_step` parameter to bound their initial stepsize, and also expose a new internal parameter `rho_init` * Install `pkg-config` file on Windows * Allow having more equality constraints than there are variables * Bugfixes to `nlopt_algorithm_name` @ text @d1 1 a1 1 @@comment $NetBSD: PLIST,v 1.3 2023/08/11 08:31:20 mef Exp $ d9 2 a10 2 lib/libnlopt.so.0 lib/libnlopt.so.0.13.0 @ 1.3 log @(math/nlopt) Updated 2.6.2 to 2.7.1 NLopt 2.7.1 * Various minor bugfixes (#268, #409, #420) and build * improvements (support Octave 6.x, Guile 3.x, Cmake 3.2). NLopt 2.7.0 * New nlopt_set_param API for setting internal algorithm parameters ([#365]). * Avoid library-symbol conflicts ([#355], [#361]) @ text @d1 1 a1 2 @@comment $NetBSD: PLIST,v 1.2 2021/09/18 05:06:06 mef Exp $ include/nlopt.f d10 1 a10 1 lib/libnlopt.so.0.11.1 @ 1.2 log @(math/nlopt) Updated 2.4.2 to 2.6.2 # NLopt Release Notes ## NLopt 2.6.2 15 April 2020 * Fixed forced stop exception with dimension elimination ([#317]) * Fixed `get_initial_step` wrapping ([#319]) * Various build fixes ([#314], [#308], [#303], [#278]) ## NLopt 2.6.1 13 April 2019 * Fix `nlopt_version` result for 2.6.x and update soname. ## NLopt 2.6 12 April 2019 * New `nlopt_set_upper_bound` and `nlopt_set_lower_bound` functions in the low-level C API to set one bound at a time ([#257]). * There is no longer a separate `libnlopt_cxx` library: C++ algorithms (STOGO and AGS) are compiled and included by default ([#198]). * Various build fixes ([#197], [#216], [#245], [#250], [#230], [#261], etc.), other fixes ([#242], [#258]). ## NLopt 2.5 26 July 2018 * New AGS global solver ([#194]), thanks to Vladislav Sovrasov. * New `nlopt_get_numevals` function providing a built-in evaluation counter ([#160]). * New `nlopt_get_errmsg` function for more descriptive error messages. * Build system is converted to `cmake` ([#49]), thanks to Julien Schueller * Plugins updated for recent Octave and Guile versions. * Various other build fixes and minor bug fixes. @ text @d1 1 a1 1 @@comment $NetBSD$ d11 1 a11 1 lib/libnlopt.so.0.10.0 @ 1.1 log @Import nlopt-2.4.2 as math/nlopt. NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization outines available online as well as original implementations of various other algorithms. Its features include: - Callable from C, C++, Fortran, Matlab or GNU Octave, Python, GNU Guile, Julia, GNU R, Lua, and OCaml. - A common interface for many different algorithms -- try a different algorithm just by changing one parameter. - Support for large-scale optimization (some algorithms scalable to millions of parameters and thousands of constraints). - Both global and local optimization algorithms. - Algorithms using function values only (derivative-free) and also algorithms exploiting user-supplied gradients. - Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear inequality/equality constraints. Reviewed by: wiz@@ @ text @d5 7 a11 1 lib/libnlopt.la d14 2 @