SacessOptimizer: collect worker stats (#1381)

So far, most stats from different SacessOptimizer workers have only been available from the logs.
Now they are also available via `SacessOptimizer.worker_results`.
Additionally, the total number of objective evaluations across all workers ís logged.

pypesto/optimize/ess/sacess.py

@@ -6,6 +6,7 @@
 import multiprocessing
 import os
 import time
+from dataclasses import dataclass
 from math import ceil, sqrt
 from multiprocessing import get_context
 from multiprocessing.managers import SyncManager
@@ -128,6 +129,7 @@ def __init__(
         self.exit_flag = ESSExitFlag.DID_NOT_RUN
         self.ess_loglevel = ess_loglevel
         self.sacess_loglevel = sacess_loglevel
+        self.worker_results: list[SacessWorkerResult] = []
         logger.setLevel(self.sacess_loglevel)
 
         self._tmpdir = tmpdir
@@ -249,21 +251,29 @@ def minimize(
 
             # wait for finish
             # collect results
-            histories = [
+            self.worker_results = [
                 sacess_manager._result_queue.get()
                 for _ in range(self.num_workers)
             ]
-            self.histories = histories
             for p in worker_processes:
                 p.join()
 
         logging_thread.stop()
+
+        self.histories = [
+            worker_result.history for worker_result in self.worker_results
+        ]
+
         result = self._create_result(problem)
 
         walltime = time.time() - start_time
+        n_eval_total = sum(
+            worker_result.n_eval for worker_result in self.worker_results
+        )
         logger.info(
-            f"{self.__class__.__name__} stopped after {walltime:3g}s with global best "
-            f"{result.optimize_result[0].fval}."
+            f"{self.__class__.__name__} stopped after {walltime:3g}s "
+            f"and {n_eval_total} objective evaluations "
+            f"with global best {result.optimize_result[0].fval}."
         )
 
         return result
@@ -587,7 +597,15 @@ def run(
             )
 
         ess.history.finalize(exitflag=ess.exit_flag.name)
-        self._manager._result_queue.put(ess.history)
+        worker_result = SacessWorkerResult(
+            x=ess.x_best,
+            fx=ess.fx_best,
+            history=ess.history,
+            n_eval=ess.evaluator.n_eval,
+            n_iter=ess.n_iter,
+            exit_flag=ess.exit_flag,
+        )
+        self._manager._result_queue.put(worker_result)
         ess._report_final()
 
     def _setup_ess(self, startpoint_method: StartpointMethod) -> ESSOptimizer:
@@ -1025,3 +1043,35 @@ def __call__(
 
     def __repr__(self):
         return f"{self.__class__.__name__}(fides_options={self._fides_options}, fides_kwargs={self._fides_kwargs})"
+
+
+@dataclass
+class SacessWorkerResult:
+    """Container for :class:`SacessWorker` results.
+
+    Contains various information about the optimization process of a single
+    :class:`SacessWorker` instance that is to be sent to
+    :class:`SacessOptimizer`.
+
+    Attributes
+    ----------
+    x:
+        Best parameters found.
+    fx:
+        Objective value corresponding to ``x``.
+    n_eval:
+        Number of objective evaluations performed.
+    n_iter:
+        Number of scatter search iterations performed.
+    history:
+        History object containing information about the optimization process.
+    exit_flag:
+        Exit flag of the optimization process.
+    """
+
+    x: np.array
+    fx: float
+    n_eval: int
+    n_iter: int
+    history: "pypesto.history.memory.MemoryHistory"
+    exit_flag: ESSExitFlag