updated texts

pybop/optimisers/_random_search.py

@@ -12,7 +12,7 @@ class RandomSearchImpl(PopulationBasedOptimiser):
     2. At each iteration, generate new random solutions within boundaries.
     3. Evaluate the quality/fitness of the solutions.
     4. Update the best solution found so far.
-    
+
     Parameters:
     - population_size (optional): Number of solutions to evaluate per iteration.
 
@@ -30,6 +30,7 @@ def __init__(self, x0, sigma0=0.05, boundaries=None, population_size=None):
 
         super().__init__(x0, sigma0, boundaries=boundaries)
 
+
         # Population size, defaulting to a suggested value
         self._population_size = population_size or self._suggested_population_size()
         self.step_size = self._sigma0
@@ -70,6 +71,7 @@ def tell(self, replies):
         if not self._ready_for_tell:
             raise RuntimeError("Optimiser not ready for tell()")
 
+
         self._iterations += 1
         self._ready_for_tell = False
 

pybop/optimisers/pints_optimisers.py

@@ -684,6 +684,7 @@ def __init__(
             **optimiser_kwargs,
         )
 
+
 class RandomSearch(BasePintsOptimiser):
     """
     Adapter for the Random Search optimiser in PyBOP.
@@ -736,7 +737,6 @@ def __init__(
         parallel: bool = False,
         **optimiser_kwargs,
     ):
-
         super().__init__(
             cost,
             RandomSearchImpl,