refactor: clean-up sa cooling attrs, update hypers in integration test

pybop/optimisers/_simulated_annealing.py

@@ -68,7 +68,7 @@ def ask(self):
         to evaluate from the optimiser.
         """
         # Update temperature
-        self._temp = self._initial_temp * (self._temp_decay**self._iterations)
+        self._temp *= self._temp_decay
 
         # Generate new point with random perturbation
         step = np.random.normal(0, self._sigma0, size=len(self._current))
@@ -105,7 +105,7 @@ def tell(self, reply):
         if fx < self._current_f:
             accept = True
         else:
-            p = np.exp(-(fx - self._current_f) / self._temp)
+            p = np.exp(-(fx - self._current_f) / (np.finfo(float).eps + self._temp))
             accept = np.random.random() < p
 
         if accept:
@@ -168,7 +168,9 @@ def cooling_rate(self, alpha):
         """
         Sets the cooling rate for the temperature schedule.
         """
-        if not isinstance(alpha, (int, float)) or not 0 < alpha < 1:
+        if not isinstance(alpha, (int, float)):
+            raise TypeError("Cooling rate must be a number")
+        if not 0 < alpha < 1:
             raise ValueError("Cooling rate must be between 0 and 1")
         self._temp_decay = float(alpha)
 

tests/integration/test_spm_parameterisations.py

@@ -124,7 +124,7 @@ def optim(self, optimiser, model, parameters, cost, init_soc):
             "cost": cost,
             "max_iterations": 450,
             "absolute_tolerance": 1e-6,
-            "max_unchanged_iterations": 450
+            "max_unchanged_iterations": 400  # 500
             if optimiser is pybop.SimulatedAnnealing
             else 55,
             "sigma0": [0.05, 0.05, 1e-3]
@@ -147,9 +147,10 @@ def optim(self, optimiser, model, parameters, cost, init_soc):
         optim = optimiser(**common_args)
 
         if isinstance(optim, pybop.SimulatedAnnealing):
-            optim.optimiser.sigma0 = [0.125, 0.125]
+            optim.optimiser.sigma0 = [0.1, 0.1]
+            optim.optimiser.cooling_rate = 0.8  # Cool quickly
             if isinstance(cost, pybop.GaussianLogLikelihood):
-                optim.optimiser.sigma0.extend([1e-3])
+                optim.optimiser.sigma0.extend([3e-3])
 
         return optim