added seed parameter

Author: r3kste

docs/source/algorithms.md

@@ -4017,9 +4017,13 @@ these optimizers, you need to have
     toward the best solutions.
 
     - **transform** (str): The transform to use to map from PSO optimization space to
-      R-space.
+      R-space. Available options are:
+      - "arctan" (default)
+      - "identity"
+      - "gaussian"
     - **population_size** (int): Population size of the particle swarm.
     - **n_cores** (int): Number of cores to use.
+    - **seed** (int): Seed used by the internal random number generator.
     - **stopping.maxfun** (int): Maximum number of function evaluations.
     - **inertia** (float): Inertia weight. Denoted by :math:`\omega`.
       Default is 0.7213475204444817. To prevent divergence, the value must be smaller

docs/source/refs.bib

@@ -906,19 +906,6 @@ @article{JAMES1975343
 author = {F. James and M. Roos}
 }
 
-@article{JAMES1975343,
-title = {Minuit - a system for function minimization and analysis of the parameter errors and correlations},
-journal = {Computer Physics Communications},
-volume = {10},
-number = {6},
-pages = {343-367},
-year = {1975},
-issn = {0010-4655},
-doi = {https://doi.org/10.1016/0010-4655(75)90039-9},
-url = {https://www.sciencedirect.com/science/article/pii/0010465575900399},
-author = {F. James and M. Roos}
-}
-
 @InProceedings{Kennedy1995,
   author={Kennedy, J. and Eberhart, R.},
   booktitle={Proceedings of ICNN'95 - International Conference on Neural Networks}, 

src/optimagic/optimizers/nevergrad_optimizers.py

@@ -39,6 +39,7 @@ class NevergradPSO(Algorithm):
     transform: Literal["arctan", "gaussian", "identity"] = "arctan"
     population_size: int | None = None
     n_cores: int = 1
+    seed: int | None = None
     stopping_maxfun: PositiveInt = STOPPING_MAXFUN_GLOBAL
     inertia: float = 0.5 / math.log(2.0)
     cognitive: float = 0.5 + math.log(2.0)
@@ -64,6 +65,9 @@ def _solve_internal_problem(
             )
         )
 
+        if self.seed is not None:
+            instrum.random_state.seed(self.seed)
+
         optimizer = ng.optimizers.ConfPSO(
             transform=self.transform,
             popsize=self.population_size,