Startpoints as dict

petab/problem.py

@@ -767,13 +767,32 @@ def create_parameter_df(self, *args, **kwargs):
             *args, **kwargs)
 
     def sample_parameter_startpoints(self, n_starts: int = 100):
-        """Create starting points for optimization
+        """Create 2D array with starting points for optimization
 
         See :py:func:`petab.sample_parameter_startpoints`.
         """
         return sampling.sample_parameter_startpoints(
             self.parameter_df, n_starts=n_starts)
 
+    def sample_parameter_startpoints_dict(
+            self,
+            n_starts: int = 100
+    ) -> List[Dict[str, float]]:
+        """Create dictionaries with starting points for optimization
+
+        See also :py:func:`petab.sample_parameter_startpoints`.
+
+        Returns:
+            A list of dictionaries with parameter IDs mapping to samples
+            parameter values.
+        """
+        return [
+            dict(zip(self.x_free_ids, parameter_values))
+            for parameter_values in self.sample_parameter_startpoints(
+                n_starts=n_starts
+            )
+        ]
+
     def unscale_parameters(
         self,
         x_dict: Dict[str, float],

tests/test_petab.py

@@ -202,6 +202,15 @@ def test_startpoint_sampling(fujita_model_scaling):
         assert -3 <= sp[1] <= 3
 
 
+def test_startpoint_sampling_dict(fujita_model_scaling):
+    n_starts = 10
+    startpoints = fujita_model_scaling.sample_parameter_startpoints_dict(
+        n_starts)
+    assert len(startpoints) == n_starts
+    for startpoint in startpoints:
+        assert set(startpoint.keys()) == set(fujita_model_scaling.x_free_ids)
+
+
 def test_create_parameter_df(
         condition_df_2_conditions):  # pylint: disable=W0621
     """Test petab.create_parameter_df."""