From 7a47d3c0d923512d77c89ccdefe1764d912c00e6 Mon Sep 17 00:00:00 2001
From: Janos Gabler <janos.gabler@gmail.com>
Date: Sun, 17 Aug 2025 16:51:38 +0200
Subject: [PATCH] Add nlopt bobyqa.

---
 examples/example.ipynb     |  1 +
 src/optimini/algorithms.py | 40 ++++++++++++++++++++++++++++++++++++++
 2 files changed, 41 insertions(+)

diff --git a/examples/example.ipynb b/examples/example.ipynb
index 9563240..6671451 100644
--- a/examples/example.ipynb
+++ b/examples/example.ipynb
@@ -27,6 +27,7 @@
     "results = {\n",
     "    \"L-BFGS-B\": minimize(my_fun, params, method=\"L-BFGS-B\"),\n",
     "    \"Nelder-Mead\": minimize(my_fun, params, method=\"Nelder-Mead\"),\n",
+    "    \"bobyqa\": minimize(my_fun, params, method=\"bobyqa\"),\n",
     "}\n",
     "history_plot(results)"
    ]
diff --git a/src/optimini/algorithms.py b/src/optimini/algorithms.py
index e962a1d..fd0c954 100644
--- a/src/optimini/algorithms.py
+++ b/src/optimini/algorithms.py
@@ -1,5 +1,6 @@
 from dataclasses import dataclass
 
+import nlopt
 import numpy as np
 from numpy.typing import NDArray
 from scipy.optimize import Bounds as ScipyBounds
@@ -104,8 +105,47 @@ def _get_scipy_bounds(lower_bounds, upper_bounds):
     return ScipyBounds(lower_bounds, upper_bounds)
 
 
+@mark.minimizer(
+    name="nlopt_bobyqa",
+    supports_bounds=True,
+    needs_bounds=False,
+)
+@dataclass(frozen=True)
+class NloptBobyqa(Algorithm):
+    stopping_maxfun: int = 100
+    convergence_ftol_rel: float = 1e-4
+    # more options here ...
+
+    def _solve_internal_problem(
+        self, problem: InternalProblem, x0: NDArray[np.float64]
+    ) -> InternalResult:
+        def func(x, grad):
+            if grad.size > 0:
+                fun, jac = problem.fun_and_jac(x)
+                grad[:] = jac
+            else:
+                fun = problem.fun(x)
+            return fun
+
+        opt = nlopt.opt(nlopt.LN_BOBYQA, x0.shape[0])
+        opt.set_min_objective(func)
+        if self.convergence_ftol_rel is not None:
+            opt.set_ftol_rel(self.convergence_ftol_rel)
+        if self.stopping_maxfun is not None:
+            opt.set_maxeval(self.stopping_maxfun)
+        if problem.lower_bounds is not None:
+            opt.set_lower_bounds(problem.lower_bounds)
+        if problem.upper_bounds is not None:
+            opt.set_upper_bounds(problem.upper_bounds)
+
+        solution_x = opt.optimize(x0)
+
+        return InternalResult(solution_x, opt.last_optimum_value())
+
+
 OPTIMIZER_REGISTRY = {
     "L-BFGS-B": SciPyLBFGSB,
     "CG": SciPyCG,
     "Nelder-Mead": SciPyNelderMead,
+    "bobyqa": NloptBobyqa,
 }