Remove usage of _result_properties dictionary (#918)

Author: FedericoNegri

src/ansys/dpf/post/harmonic_mechanical_simulation.py

@@ -81,9 +81,10 @@ def _get_result_workflow(
         averaging_config: AveragingConfig = AveragingConfig(),
         rescoping: Optional[_Rescoping] = None,
         shell_layer: Optional[shell_layers] = None,
-    ) -> (dpf.Workflow, Union[str, list[str], None], str):
+    ) -> Tuple[dpf.Workflow, Union[str, list[str], None], str]:
         """Generate (without evaluating) the Workflow to extract results."""
         result_workflow_inputs = _create_result_workflow_inputs(
+            available_results=self.results,
             base_name=base_name,
             category=category,
             components=components,

src/ansys/dpf/post/modal_mechanical_simulation.py

@@ -26,7 +26,7 @@
 -------------------------
 
 """
-from typing import List, Optional, Union
+from typing import List, Optional, Tuple, Union
 
 from ansys.dpf.core import shell_layers
 
@@ -70,9 +70,10 @@ def _get_result_workflow(
         averaging_config: AveragingConfig = AveragingConfig(),
         rescoping: Optional[_Rescoping] = None,
         shell_layer: Optional[shell_layers] = None,
-    ) -> (dpf.Workflow, Union[str, list[str], None], str):
+    ) -> Tuple[dpf.Workflow, Union[str, list[str], None], str]:
         """Generate (without evaluating) the Workflow to extract results."""
         result_workflow_inputs = _create_result_workflow_inputs(
+            available_results=self.results,
             base_name=base_name,
             category=category,
             components=components,

src/ansys/dpf/post/result_workflows/_build_workflow.py

@@ -24,7 +24,7 @@
 from typing import Callable, List, Optional, Union
 
 from ansys.dpf.core import Operator, Workflow, shell_layers
-from ansys.dpf.core.available_result import _result_properties
+from ansys.dpf.core.available_result import AvailableResult
 from ansys.dpf.core.common import locations
 
 from ansys.dpf.post.result_workflows._component_helper import (
@@ -45,6 +45,7 @@
 from ansys.dpf.post.result_workflows._utils import (
     AveragingConfig,
     _CreateOperatorCallable,
+    _get_native_location,
     _Rescoping,
 )
 from ansys.dpf.post.selection import Selection, _WfNames
@@ -120,6 +121,7 @@ class _CreateWorkflowInputs:
 
 
 def _requires_manual_averaging(
+    available_results: list[AvailableResult],
     base_name: str,
     location: str,
     category: ResultCategory,
@@ -128,8 +130,7 @@ def _requires_manual_averaging(
     create_operator_callable: Callable[[str], Operator],
     average_per_body: bool,
 ):
-    res = _result_properties[base_name] if base_name in _result_properties else None
-    native_location = res["location"] if res is not None else None
+    native_location = _get_native_location(available_results, base_name)
 
     if average_per_body and (
         native_location == locations.elemental
@@ -138,7 +139,7 @@ def _requires_manual_averaging(
         return True
     if category == ResultCategory.equivalent and base_name[0] == "E":  # strain eqv
         return True
-    if res is not None:
+    if native_location is not None:
         is_model_cyclic = create_operator_callable("is_cyclic").eval()
         is_model_cyclic = is_model_cyclic in ["single_stage", "multi_stage"]
         if has_external_layer and is_model_cyclic and location != native_location:
@@ -265,6 +266,7 @@ def _create_result_workflows(
 
 
 def _create_result_workflow_inputs(
+    available_results: list[AvailableResult],
     base_name: str,
     category: ResultCategory,
     components: Union[str, List[str], int, List[int], None],
@@ -284,6 +286,7 @@ def _create_result_workflow_inputs(
     )
 
     force_elemental_nodal = _requires_manual_averaging(
+        available_results=available_results,
         base_name=base_name,
         location=location,
         category=category,

src/ansys/dpf/post/result_workflows/_utils.py

@@ -24,6 +24,7 @@
 from typing import Optional, Protocol
 
 from ansys.dpf.core import Operator, Workflow
+from ansys.dpf.core.available_result import AvailableResult
 
 from ansys.dpf.post.selection import _WfNames
 
@@ -122,3 +123,28 @@ def _append_workflow(new_wf: Optional[Workflow], last_wf: Workflow):
         output_input_names={_WfNames.output_data: _WfNames.input_data},
     )
     return new_wf
+
+
+def _get_native_location(
+    available_results: list[AvailableResult], base_name: str
+) -> str:
+    """Get the native location of a result from its base name."""
+    res = next((r for r in available_results if r.operator_name == base_name), None)
+
+    # special case for beam results, which are extracted from SMISC
+    if res is None and base_name in [
+        "B_N",
+        "B_M1",
+        "B_M2",
+        "B_MT",
+        "B_SN",
+        "B_EL",
+        "B_T1",
+        "B_T2",
+    ]:
+        res = next((r for r in available_results if r.operator_name == "SMISC"), None)
+
+    if res is not None:
+        return res.native_location
+
+    raise ValueError(f"Result with base name '{base_name}' not found.")

src/ansys/dpf/post/simulation.py

@@ -53,7 +53,7 @@
 from ansys.dpf.post.meshes import Meshes
 from ansys.dpf.post.result_workflows._build_workflow import _requires_manual_averaging
 from ansys.dpf.post.result_workflows._component_helper import ResultCategory
-from ansys.dpf.post.result_workflows._utils import _Rescoping
+from ansys.dpf.post.result_workflows._utils import _get_native_location, _Rescoping
 from ansys.dpf.post.selection import Selection
 
 
@@ -636,6 +636,7 @@ def _build_selection(
             has_skin = len(skin) > 0
 
         requires_manual_averaging = _requires_manual_averaging(
+            available_results=self.results,
             base_name=base_name,
             location=location,
             category=category,
@@ -658,13 +659,7 @@ def _build_selection(
         if requires_manual_averaging and location != locations.elemental_nodal:
             location = locations.elemental_nodal
 
-        available_results = self._model.metadata.result_info.available_results
-        result_info = next(
-            (r for r in available_results if r.operator_name == base_name), None
-        )
-        result_native_location = None
-        if result_info is not None:
-            result_native_location = result_info.native_location
+        result_native_location = _get_native_location(self.results, base_name)
 
         # Create the SpatialSelection
 

src/ansys/dpf/post/static_mechanical_simulation.py

@@ -66,9 +66,10 @@ def _get_result_workflow(
         averaging_config: AveragingConfig = AveragingConfig(),
         rescoping: Optional[_Rescoping] = None,
         shell_layer: Optional[shell_layers] = None,
-    ) -> (core.Workflow, Union[str, list[str], None], str):
+    ) -> Tuple[core.Workflow, Union[str, list[str], None], str]:
         """Generate (without evaluating) the Workflow to extract results."""
         result_workflow_inputs = _create_result_workflow_inputs(
+            available_results=self.results,
             base_name=base_name,
             category=category,
             components=components,

src/ansys/dpf/post/transient_mechanical_simulation.py

@@ -68,9 +68,10 @@ def _get_result_workflow(
         averaging_config: AveragingConfig = AveragingConfig(),
         rescoping: Optional[_Rescoping] = None,
         shell_layer: Optional[shell_layers] = None,
-    ) -> (dpf.Workflow, Union[str, list[str], None], str):
+    ) -> Tuple[dpf.Workflow, Union[str, list[str], None], str]:
         """Generate (without evaluating) the Workflow to extract results."""
         result_workflow_inputs = _create_result_workflow_inputs(
+            available_results=self.results,
             base_name=base_name,
             category=category,
             components=components,

tests/test_simulation.py

@@ -2203,36 +2203,10 @@ def test_kinetic_energy(self, transient_simulation):
         assert np.allclose(field.data, field_ref.data)
 
     def test_structural_temperature(self, transient_simulation):
-        result = transient_simulation.structural_temperature(set_ids=[2])
-        assert len(result._fc) == 1
-        assert result._fc.get_time_scoping().ids == [2]
-        field = result._fc[0]
-        op = transient_simulation._model.operator("BFE")
-        field_ref = op.eval()[0]
-        assert field.component_count == 1
-        assert np.allclose(field.data, field_ref.data)
-
-    def test_structural_temperature_nodal(self, transient_simulation):
-        result = transient_simulation.structural_temperature_nodal(set_ids=[2])
-        assert len(result._fc) == 1
-        assert result._fc.get_time_scoping().ids == [2]
-        field = result._fc[0]
-        op = transient_simulation._model.operator("BFE")
-        op.connect(9, post.locations.nodal)
-        field_ref = op.eval()[0]
-        assert field.component_count == 1
-        assert np.allclose(field.data, field_ref.data)
-
-    def test_structural_temperature_elemental(self, transient_simulation):
-        result = transient_simulation.structural_temperature_elemental(set_ids=[2])
-        assert len(result._fc) == 1
-        assert result._fc.get_time_scoping().ids == [2]
-        field = result._fc[0]
-        op = transient_simulation._model.operator("BFE")
-        op.connect(9, post.locations.elemental)
-        field_ref = op.eval()[0]
-        assert field.component_count == 1
-        assert np.allclose(field.data, field_ref.data)
+        # the model does not contain structural temperature results
+        with pytest.raises(ValueError) as excinfo:
+            _ = transient_simulation.structural_temperature(set_ids=[1])
+        assert "not found" in str(excinfo.value)
 
     # @pytest.mark.skipif(
     #     not SERVERS_VERSION_GREATER_THAN_OR_EQUAL_TO_5_0,