typing

pyciemss/integration_utils/intervention_builder.py

@@ -130,7 +130,9 @@ def intervention_generator(
     ) -> Dict[float, Dict[str, Intervention]]:
         x = torch.atleast_1d(x)
         assert x.size()[0] == total_length
-        interventions: List[Dict[float, Dict[str, Intervention]]] = [None] * len(intervention_funcs)
+        interventions: List[Dict[float, Dict[str, Intervention]]] = [None] * len(
+            intervention_funcs
+        )
         i = 0
         for j, (input_length, intervention_func) in enumerate(
             zip(intervention_func_lengths, intervention_funcs)

pyciemss/ouu/ouu.py

@@ -1,7 +1,7 @@
 import contextlib
 import warnings
 from copy import deepcopy
-from typing import Any, Callable, Dict, List, Tuple, Union
+from typing import Any, Callable, Dict, List, Tuple
 
 import numpy as np
 import pyro

tests/fixtures.py

@@ -7,6 +7,7 @@
 import torch
 
 from pyciemss.integration_utils.intervention_builder import (
+    intervention_func_combinator,
     param_value_objective,
     start_time_objective,
     start_time_param_value_objective,
@@ -142,10 +143,10 @@ def __init__(
 optkwargs_SEIRHD_paramtimeComb_maxQoI = {
     "qoi": lambda x: obs_max_qoi(x, ["I_state"]),
     "risk_bound": 3e5,
-    "static_parameter_interventions": lambda x: [
-        static_parameter_interventions1(torch.atleast_1d(x[0])),
-        static_parameter_interventions2(torch.atleast_1d(x[1])),
-    ],
+    "static_parameter_interventions": intervention_func_combinator(
+        [static_parameter_interventions1, static_parameter_interventions2],
+        [1, 1],
+    ),
     "objfun": lambda x: np.abs(0.35 - x[0]) - x[1],
     "initial_guess_interventions": [0.35, 5.0],
     "bounds_interventions": [[0.1, 1.0], [0.5, 90.0]],