Select: problem-specific minimize method for SaCeSS

pypesto/select/__init__.py

@@ -7,7 +7,7 @@
 """
 
 from . import postprocessors
-from .misc import model_to_pypesto_problem
+from .misc import SacessMinimizeMethod, model_to_pypesto_problem
 from .problem import Problem
 
 try:

pypesto/select/misc.py

@@ -11,6 +11,10 @@
 from petab_select.constants import PETAB_PROBLEM
 
 from ..objective import Objective
+from ..optimize.ess import (
+    SacessOptimizer,
+    get_default_ess_options,
+)
 from ..petab import PetabImporter
 from ..problem import Problem
 
@@ -163,3 +167,51 @@ def correct_x_guesses(
                 corrected_x_guess.append(corrected_value)
             corrected_x_guesses.append(corrected_x_guess)
     return corrected_x_guesses
+
+
+class SacessMinimizeMethod:
+    """Create a minimize method for SaCeSS that adapts to each problem.
+
+    When a pyPESTO SaCeSS optimizer is created, it takes the problem
+    dimension as input. Hence, an optimizer needs to be constructed for
+    each problem. Objects of this class act like a minimize method for model
+    selection, but a new problem-specific SaCeSS optimizer will be created
+    every time a model is minimized.
+
+    Class attributes correspond to pyPESTO's SaCeSS optimizer, and are
+    documented there.
+    """
+
+    def __init__(
+        self,
+        num_workers: int,
+        local_optimizer,
+        max_walltime_s: int,
+    ):
+        """Construct a minimize-like object."""
+        self.num_workers = num_workers
+        self.local_optimizer = local_optimizer
+        self.max_walltime_s = max_walltime_s
+
+    def __call__(self, problem: Problem, **minimize_options):
+        """Create then run a problem-specific sacess optimizer."""
+        # create optimizer
+        ess_init_args = get_default_ess_options(
+            num_workers=self.num_workers,
+            dim=problem.dim,
+        )
+        for x in ess_init_args:
+            x["local_optimizer"] = self.local_optimizer
+        ess = SacessOptimizer(
+            max_walltime_s=self.max_walltime_s,
+            sacess_loglevel=logging.DEBUG,
+            ess_loglevel=logging.WARNING,
+            ess_init_args=ess_init_args,
+        )
+
+        # optimize
+        result = ess.minimize(
+            problem=problem,
+            **minimize_options,
+        )
+        return result

pypesto/select/model_problem.py

@@ -142,15 +142,23 @@ def __init__(
     def minimize(self) -> Result:
         """Optimize the model.
 
-        Returns:
+        Returns
+        -------
             The optimization result.
         """
         return self.minimize_method(
             self.pypesto_problem,
             **self.minimize_options,
         )
 
-    def set_result_from_model(self, model):
+    def set_result_from_model(self, model) -> None:
+        """Set the calibration result from a previously-calibrated model.
+
+        Parameters
+        ----------
+        model:
+            The previously-calibrated model.
+        """
         self.model.criteria = model.criteria
         self.model.estimated_parameters = model.estimated_parameters
         if self.postprocessor is not None:
@@ -201,6 +209,12 @@ def create_fake_pypesto_result_from_fval(
     ----------
     fval:
         The objective function value.
+    evaluation_time:
+        CPU time taken to compute the objective function value.
+
+    Returns
+    -------
+    The dummy result.
     """
     result = Result()