Merge branch 'main' into feat/upload_files_to_unique_folder

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 @@
+Ply wise data
+-------------
+
+.. module:: ansys.dpf.composites.ply_wise_data
+
+.. autosummary::
+    :toctree: _autosummary
+
+    ReductionStrategy
+    get_ply_wise_data
+
+

examples/006_filter_composite_data_example.py

@@ -4,9 +4,15 @@
 Filter result data by different criteria
 ----------------------------------------
 
-This example show how data filtering can be used for custom postprocessing of
+This example shows how data filtering can be used for custom postprocessing of
 layered composites. You can filter strains and stresses by material, layer, or
-analysis ply. The example filters data by layer, spot, and node, as well as material
+analysis ply. Filtering by analysis ply is implemented on the server side and
+exposed with the :func:`.get_ply_wise_data` function. In this case, the data is
+filtered (and reduced) on the server side and only the resulting field is returned
+to the client. This is the recommended way to filter data if possible.
+For more complex filtering, the data is transferred to the client side and filtered
+using numpy functionality.
+The examples show filtering data by layer, spot, and node, as well as material
 or analysis ply ID. To learn more about how layered result data is organized,
 see :ref:`select_indices`.
 """
@@ -24,17 +30,14 @@
 from ansys.dpf.composites.composite_model import CompositeModel
 from ansys.dpf.composites.constants import Spot, Sym3x3TensorComponent
 from ansys.dpf.composites.example_helper import get_continuous_fiber_example_files
-from ansys.dpf.composites.layup_info import (
-    AnalysisPlyInfoProvider,
-    get_all_analysis_ply_names,
-    get_dpf_material_id_by_analysis_ply_map,
-)
+from ansys.dpf.composites.layup_info import AnalysisPlyInfoProvider, get_all_analysis_ply_names
+from ansys.dpf.composites.ply_wise_data import ReductionStrategy, get_ply_wise_data
 from ansys.dpf.composites.select_indices import (
     get_selected_indices,
     get_selected_indices_by_analysis_ply,
     get_selected_indices_by_dpf_material_ids,
 )
-from ansys.dpf.composites.server_helpers import connect_to_or_start_server
+from ansys.dpf.composites.server_helpers import connect_to_or_start_server, version_equal_or_later
 
 # %%
 # Start a DPF server and copy the example files into the current working directory.
@@ -55,16 +58,52 @@
 stress_operator.inputs.bool_rotate_to_global(False)
 stress_field = stress_operator.get_output(pin=0, output_type=dpf.types.fields_container)[0]
 
+# %%
+# Filter data by analysis ply
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+# %%
+# List all available analysis plies.
+all_ply_names = get_all_analysis_ply_names(composite_model.get_mesh())
+all_ply_names
+
+# %%
+# The easiest way to filter data by analysis ply is to use the :func:`.get_ply_wise_data` function.
+# This function supports different reduction strategies such as computing the average,
+# maximum, or minimum over the spot locations.
+# It also supports selecting a specific spot (TOP, MID, BOT) directly.
+# This example selects the maximum value over all spots for each node and then requests
+# the elemental location, which implies averaging over all nodes in an element.
+# Using the :func:`.get_ply_wise_data` function has the advantage that all the averaging
+# and filtering is done on the server side.
+if version_equal_or_later(server, "8.0"):
+    elemental_max = get_ply_wise_data(
+        field=stress_field,
+        ply_name="P1L1__ud_patch ns1",
+        mesh=composite_model.get_mesh(),
+        component=Sym3x3TensorComponent.TENSOR11,
+        reduction_strategy=ReductionStrategy.MAX,
+        requested_location=dpf.locations.elemental,
+    )
+
+    composite_model.get_mesh().plot(elemental_max)
+
+
+# %%
+# Generic client-side filtering
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# This example shows how to filter data by layer, spot, and node using the generic filtering on
+# the client side.
+# This code plots stress values in the material direction for the first node and top spot.
+
 # %%
 # Get element information for all elements and show the first one as an example.
 element_ids = stress_field.scoping.ids
 element_infos = [composite_model.get_element_info(element_id) for element_id in element_ids]
 element_infos[0]
 
 # %%
-# Plot result data
-# ~~~~~~~~~~~~~~~~
-# For the top layer, plot stress values in the material direction for the first node and top spot.
+# Get filtered data
 component = Sym3x3TensorComponent.TENSOR11
 result_field = dpf.field.Field(location=dpf.locations.elemental, nature=dpf.natures.scalar)
 with result_field.as_local_field() as local_result_field:
@@ -82,23 +121,45 @@
 
 composite_model.get_mesh().plot(result_field)
 
+
 # %%
-# List analysis plies
-# ~~~~~~~~~~~~~~~~~~~
-# List all available analysis plies.
-all_ply_names = get_all_analysis_ply_names(composite_model.get_mesh())
-all_ply_names
+# Filter by material
+# ~~~~~~~~~~~~~~~~~~~~~
+# Loop over all elements and get the maximum stress in the material direction
+# for all plies that have a specific UD material.
+
+ud_material_id = composite_model.material_names["Epoxy Carbon UD (230 GPa) Prepreg"]
+component = Sym3x3TensorComponent.TENSOR11
+
+material_result_field = dpf.field.Field(location=dpf.locations.elemental, nature=dpf.natures.scalar)
+with material_result_field.as_local_field() as local_result_field:
+    element_ids = stress_field.scoping.ids
+
+    for element_id in element_ids:
+        element_info = composite_model.get_element_info(element_id)
+        assert element_info is not None
+        if ud_material_id in element_info.dpf_material_ids:
+            stress_data = stress_field.get_entity_data_by_id(element_id)
+            selected_indices = get_selected_indices_by_dpf_material_ids(
+                element_info, [ud_material_id]
+            )
+
+            value = np.max(stress_data[selected_indices][:, component])
+            local_result_field.append([value], element_id)
+
+composite_model.get_mesh().plot(material_result_field)
 
 # %%
-# Plot results
-# ~~~~~~~~~~~~
-# Loop all elements that contain a given ply and plot the maximum stress value
+# Filter by analysis ply on the client side
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# Loop over all elements that contain a given ply and plot the maximum stress value
 # in the material direction in this ply.
 component = Sym3x3TensorComponent.TENSOR11
 
 analysis_ply_info_provider = AnalysisPlyInfoProvider(
     mesh=composite_model.get_mesh(), name="P1L1__ud_patch ns1"
 )
+
 ply_result_field = dpf.field.Field(location=dpf.locations.elemental, nature=dpf.natures.scalar)
 with ply_result_field.as_local_field() as local_result_field:
     element_ids = analysis_ply_info_provider.property_field.scoping.ids
@@ -116,31 +177,3 @@
 
 
 composite_model.get_mesh().plot(ply_result_field)
-
-# %%
-# Loop all elements and get the maximum stress in the material direction
-# for all plies that have a material with DPF material ID.
-# Note: It is not possible to get a DPF material ID for a
-# given material name. It is only possible to get a DPF material
-# ID from an analysis ply.
-material_map = get_dpf_material_id_by_analysis_ply_map(
-    composite_model.get_mesh(), data_source_or_streams_provider=composite_model.data_sources.rst
-)
-ud_material_id = material_map["P1L1__ud_patch ns1"]
-component = Sym3x3TensorComponent.TENSOR11
-
-material_result_field = dpf.field.Field(location=dpf.locations.elemental, nature=dpf.natures.scalar)
-with material_result_field.as_local_field() as local_result_field:
-    element_ids = analysis_ply_info_provider.property_field.scoping.ids
-
-    for element_id in element_ids:
-        stress_data = stress_field.get_entity_data_by_id(element_id)
-        element_info = composite_model.get_element_info(element_id)
-        assert element_info is not None
-
-        selected_indices = get_selected_indices_by_dpf_material_ids(element_info, [ud_material_id])
-
-        value = np.max(stress_data[selected_indices][:, component])
-        local_result_field.append([value], element_id)
-
-composite_model.get_mesh().plot(material_result_field)

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

@@ -0,0 +1,87 @@
+"""Methods to get ply-wise data from a result field."""
+
+from enum import Enum, IntEnum
+from typing import Union
+
+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):
+    """Provides the reduction strategy for getting from spot values to a single value."""
+
+    MIN = "MIN"
+    MAX = "MAX"
+    AVG = "AVG"
+    BOT = "BOT"
+    MID = "MID"
+    TOP = "TOP"
+
+
+def get_ply_wise_data(
+    field: Field,
+    ply_name: str,
+    mesh: MeshedRegion,
+    reduction_strategy: ReductionStrategy = ReductionStrategy.AVG,
+    requested_location: str = locations.elemental_nodal,
+    component: Union[IntEnum, int] = 0,
+) -> Field:
+    """Get ply-wise data from a field.
+
+    Parameters
+    ----------
+    field:
+        Field to extract data from.
+    ply_name:
+        Name of the ply to extract data from.
+    mesh :
+        Meshed region enriched with composite information.
+        Use the ``CompositeModel.get_mesh()`` method to get the meshed region.
+    reduction_strategy :
+        Reduction strategy for getting from spot values (BOT, MID, TOP) to a single value
+        per corner node and layer. The default is ``AVG``.
+    requested_location :
+        Location of the output field. The default is ``"elemental_nodal"``. Options are
+        ``"elemental"``, ``"elemental_nodal"``, and ``"nodal"``.
+    component :
+        Component to extract data from. The default is ``0``.
+    """
+    component_int = component.value if isinstance(component, IntEnum) else component
+    component_selector = operators.logic.component_selector()
+
+    component_selector.inputs.field.connect(field)
+    component_selector.inputs.component_number.connect(component_int)
+    single_component_field = component_selector.outputs.field()
+
+    filter_ply_data_op = Operator("composite::filter_ply_data_operator")
+    filter_ply_data_op.inputs.field(single_component_field)
+    filter_ply_data_op.inputs.mesh(mesh)
+    filter_ply_data_op.inputs.ply_id(ply_name)
+    filter_ply_data_op.inputs.reduction_strategy(reduction_strategy.value)
+    elemental_nodal_data = filter_ply_data_op.outputs.field()
+
+    if requested_location == locations.elemental_nodal:
+        return elemental_nodal_data
+
+    if requested_location == locations.elemental:
+        elemental_nodal_to_elemental = operators.averaging.elemental_mean()
+        elemental_nodal_to_elemental.inputs.field.connect(elemental_nodal_data)
+        out_field = elemental_nodal_to_elemental.outputs.field()
+        out_field.location = locations.elemental
+        return out_field
+
+    if requested_location == locations.nodal:
+        elemental_nodal_to_nodal = operators.averaging.elemental_nodal_to_nodal()
+        elemental_nodal_to_nodal.inputs.mesh.connect(mesh)
+        elemental_nodal_to_nodal.inputs.field.connect(elemental_nodal_data)
+        out_field = elemental_nodal_to_nodal.outputs.field()
+        out_field.location = locations.nodal
+        return out_field
+
+    raise RuntimeError(
+        f"Invalid requested location {requested_location}. "
+        f"Valid locations are {locations.elemental_nodal}, "
+        f"{locations.elemental}, and {locations.nodal}."
+    )