diff --git a/api/solarperformanceinsight_api/compute.py b/api/solarperformanceinsight_api/compute.py
index 204b2421..88224325 100644
--- a/api/solarperformanceinsight_api/compute.py
+++ b/api/solarperformanceinsight_api/compute.py
@@ -648,7 +648,7 @@ def _calculate_weather_adjusted_predicted_performance(
         # could make more sense to use weighted mean with weights set
         # by array power percentage
         # another alternative, calculate average POArat and TempFactor separately
-        poa_rat = [_zero_div(pa, pr) for pa, pr in zip(poa_actual, poa_ref)]
+        poa_rat = list(map(_zero_div, poa_actual, poa_ref))
         tempfactor = list(map(_temp_factor, gammas, t_ref, t_actual))
         poa_rat_x_temp_factor = adjust(  # modelchain outputs are all shifted
             sum([p * t for p, t in zip(poa_rat, tempfactor)]) / num_arrays
@@ -739,9 +739,9 @@ def compare_monthly_predicted_and_actual(
             "PVsyst specified arrays."
         )
 
-    avg_gamma = mean(
+    avg_gamma: float = mean(
         [
-            mean([arr.module_parameters._gamma for arr in inv.arrays])
+            mean([arr.module_parameters._gamma for arr in inv.arrays])  # type: ignore
             for inv in inverters
         ]
     )
diff --git a/api/solarperformanceinsight_api/models.py b/api/solarperformanceinsight_api/models.py
index 84366f94..0ca55565 100644
--- a/api/solarperformanceinsight_api/models.py
+++ b/api/solarperformanceinsight_api/models.py
@@ -1013,17 +1013,11 @@ class CalculateWeatherAdjustedPRJobParameters(CompareMixin, JobParametersBase):
     _performance_types = PrivateAttr((JobDataTypeEnum.actual_performance,))
 
 
-def _get_model_chain_method(
-    irradiance_type: Optional[IrradianceTypeEnum],
-) -> Union[str, None]:
-    if irradiance_type == IrradianceTypeEnum.effective:
-        return "run_model_from_effective_irradiance"
-    elif irradiance_type == IrradianceTypeEnum.poa:
-        return "run_model_from_poa"
-    elif irradiance_type == IrradianceTypeEnum.standard:
-        return "run_model"
-    else:
-        return None
+MODEL_CHAIN_METHOD_MAP = {
+    IrradianceTypeEnum.effective: "run_model_from_effective_irradiance",
+    IrradianceTypeEnum.poa: "run_model_from_poa",
+    IrradianceTypeEnum.standard: "run_model",
+}
 
 
 class ActualDataParams(CompareMixin):
@@ -1035,7 +1029,7 @@ class ActualDataParams(CompareMixin):
 
     def __init__(self, **data):
         super().__init__(**data)
-        self._model_chain_method = _get_model_chain_method(self.irradiance_type)
+        self._model_chain_method = MODEL_CHAIN_METHOD_MAP[self.irradiance_type]
 
 
 class PredictedDataEnum(str, Enum):
@@ -1063,7 +1057,7 @@ def __init__(self, **data):
             )
         else:
             self._performance_types = ()
-        self._model_chain_method = _get_model_chain_method(self.irradiance_type)
+        self._model_chain_method = MODEL_CHAIN_METHOD_MAP[self.irradiance_type]
 
     @root_validator
     def check_performance_granularity(cls, values):
@@ -1185,7 +1179,7 @@ def __init__(self, **data):
         self._data_items = self.parameters._construct_data_items(self.system_definition)
         # determine what columns to expect in uploads
         irradiance_type = getattr(self.parameters, "irradiance_type", None)
-        self._model_chain_method = _get_model_chain_method(irradiance_type)
+        self._model_chain_method = MODEL_CHAIN_METHOD_MAP.get(irradiance_type, None)
 
 
 class JobStatusEnum(str, Enum):