Add docs

doc/source/api/index.rst

@@ -16,6 +16,7 @@ For in-depth documentation on the different failure criteria, refer to the ACP h
     data_sources
     failure_criteria
     layup_info
+    ply_wise_data
     result_definition
     sampling_point
     server_helpers

doc/source/api/ply_wise_data.rst

@@ -0,0 +1,12 @@
+Data sources
+------------
+
+.. module:: ansys.dpf.composites.ply_wise_data
+
+.. autosummary::
+    :toctree: _autosummary
+
+    ReductionStrategy
+    get_ply_wise_data
+
+

src/ansys/dpf/composites/__init__.py

@@ -14,6 +14,7 @@
     data_sources,
     failure_criteria,
     layup_info,
+    ply_wise_data,
     result_definition,
     sampling_point,
     select_indices,
@@ -27,6 +28,7 @@
     "data_sources",
     "failure_criteria",
     "layup_info",
+    "ply_wise_data",
     "result_definition",
     "sampling_point",
     "server_helpers",

src/ansys/dpf/composites/layup_info/_layup_info.py

@@ -219,8 +219,8 @@ def get_dpf_material_id_by_analyis_ply_map(
         DPF data source with rst file or streams_provider. The streams provider is
         available from :attr:`.CompositeModel.core_model` (under metadata.streams_provider).
 
-    Note
-    ----
+    Notes
+    -----
     Cache the output because the computation can be performance-critical.
     """
     warn(

src/ansys/dpf/composites/ply_wise_data.py

@@ -6,6 +6,8 @@
 from ansys.dpf.core import Field, MeshedRegion, Operator, operators
 from ansys.dpf.gate.common import locations
 
+__all__ = ("ReductionStrategy", "get_ply_wise_data")
+
 
 class ReductionStrategy(Enum):
     """The reduction strategy to get from spot values (BOT, MID, TOP) to a single value."""

tests/ply_wise_data_test.py

@@ -44,6 +44,15 @@ def get_reduced_value(all_spot_values: Sequence[float], reduction_strategy: Redu
 ]
 
 
+def get_all_spot_values_first_element_first_node(stress_field, component=0):
+    all_spot_values = []
+    entity_data = stress_field.get_entity_data_by_id(1)[:, component]
+    number_of_nodes = 4
+    for spot_index in range(3):
+        all_spot_values.append(entity_data[spot_index * number_of_nodes])
+    return all_spot_values
+
+
 def test_get_ply_wise_data(dpf_server):
     files = get_basic_shell_files()
 
@@ -53,14 +62,6 @@ def test_get_ply_wise_data(dpf_server):
     stress_result_op.inputs.bool_rotate_to_global(False)
     stress_field = stress_result_op.outputs.fields_container()[0]
 
-    def get_all_spot_values_first_element_first_node(stress_field, component=0):
-        all_spot_values = []
-        entity_data = stress_field.get_entity_data_by_id(1)[:, component]
-        number_of_nodes = 4
-        for spot_index in range(3):
-            all_spot_values.append(entity_data[spot_index * number_of_nodes])
-        return all_spot_values
-
     first_ply = "P1L1__woven_45"
 
     element_id = 1
@@ -82,6 +83,7 @@ def get_all_spot_values_first_element_first_node(stress_field, component=0):
 
             assert len(elemental_nodal_data.scoping.ids) == 4
             assert len(elemental_nodal_data.get_entity_data_by_id(element_id)) == 4
+            assert elemental_nodal_data.location == locations.elemental_nodal
 
             assert np.allclose(
                 elemental_nodal_data.get_entity_data_by_id(element_id)[first_node_index],
@@ -98,6 +100,7 @@ def get_all_spot_values_first_element_first_node(stress_field, component=0):
             )
             assert len(elemental_data.scoping.ids) == 4
             assert len(elemental_data.get_entity_data_by_id(element_id)) == 1
+            assert elemental_data.location == locations.elemental
 
             assert np.allclose(
                 elemental_data.get_entity_data_by_id(element_id)[first_node_index],
@@ -114,6 +117,7 @@ def get_all_spot_values_first_element_first_node(stress_field, component=0):
             )
             assert len(nodal_data.scoping.ids) == 9
             assert len(nodal_data.get_entity_data_by_id(element_id)) == 1
+            assert nodal_data.location == locations.nodal
 
             # Select node that only belongs to element 1
             # no averaging needed