Merge branch 'main' into ibatzian/feature/sc-14359/download-mer-plot-…

…data-sdk

CHANGELOG.rst

@@ -1,6 +1,22 @@
 Changelog
 ---------
 
+0.2.3 (2024-08-21)
+******************
+
+New:
+
+- Added :py:class:`PostProcessInput<ansys.simai.core.data.model_configuration.PostProcessInput>` class to define post processing input fields.
+- Added support for NaN and Inf for Global Coefficients and Post Processings.
+
+Fixes:
+
+- Removed compute argument from :py:meth:`TrainingData.upload_folder()<ansys.simai.core.data.training_data.TrainingData.upload_folder>`
+- Fixed Model Configuration to raise a ProcessingError when volume field is missing from a sample specifying volume output.
+- Removed wakepy error mode success (deprecated) during optimization.
+- Renamed TrainingData method compute() to :py:meth:`TrainingData.extract_data()<ansys.simai.core.data.training_data.TrainingData.extract_data>`.
+- Updated documentation of :py:meth:`GeometryDirectory.upload()<ansys.simai.core.data.geometries.GeometryDirectory.upload>`: the ``workspace_id`` argument was moved to ``workspace`` but never updated.
+
 0.2.2 (2024-07-17)
 ******************
 

doc/source/api_reference/model_configuration.rst

@@ -49,3 +49,8 @@ ModelConfiguration
 .. autoclass:: ModelConfiguration()
     :members:
 
+PostProcessInput
+-----------------
+
+.. autoclass:: PostProcessInput()
+    :members:

doc/source/user_guide.rst

@@ -7,6 +7,6 @@ User guide
    user_guide/configuration
    user_guide/config_file
    user_guide/proxy
-   user_guide/training
+   user_guide/building_a_model
    user_guide/data_exploration
    user_guide/best_practices

doc/source/user_guide/building_a_model.rst

@@ -0,0 +1,103 @@
+Building a model
+================
+
+.. _building_a_model:
+
+.. note::
+
+   Building a model with PySimAI is still experimental and subject to API changes.
+
+   Rebuilding a model using the last configuration of a project is supported for models created
+   after v0.1.5 (April 15, 2024).
+
+SimAI allows you to build AI models using past simulation data. This first step to building such models is to upload
+your simulation data into a global pool of :class:`training data<ansys.simai.core.data.training_data.TrainingData>` instances.
+Then, you assign the imported data to different :class:`Project<ansys.simai.core.data.projects.Project>` instances,
+which you will eventually configure in order to build your AI model.
+
+Create a project and upload data
+--------------------------------
+
+#. Create a :class:`~ansys.simai.core.client.SimAIClient` instance::
+
+     import ansys.simai.core
+
+     simai = ansys.simai.core.SimAIClient()
+
+   You are prompted for your credentials.
+
+   If desired, you can create an instance using a configuration file. For more
+   information, see :ref:`configuration`.
+
+#. Create a
+   :class:`TrainingData<ansys.simai.core.data.training_data.TrainingData>` instance
+   and upload your simulation data into it::
+
+     td = simai.training_data.create("my-first-data")
+     td.upload_folder("/path/to/folder/where/files/are/stored")
+
+#. Create a project::
+
+     project = simai.projects.create("my-first-project")
+
+#. Associate the created training data with the created project::
+
+     td.add_to_project(project)
+
+Your project is created and your simulation data is associated with it. You can now configure and build your AI model.
+
+Configure and build the model
+-----------------------------
+
+#.   Import the modules related to model building::
+
+          from ansys.simai.core.data.model_configuration import (
+               DomainOfAnalysis,
+               ModelConfiguration,
+               ModelInput,
+               ModelOutput,
+          )
+
+#.   Set the inputs (:class:`ModelInput<ansys.simai.core.data.model_configuration.ModelInput>`) and outputs (:class:`ModelOutput<ansys.simai.core.data.model_configuration.ModelOutput>`) of the model::
+
+          model_input = ModelInput(surface=["wallShearStress"], boundary_conditions=["Vx"])
+
+          model_output = ModelOutput(surface=["alpha.water"], volume=["p", "p_rgh"])
+
+#.   Set the Global Coefficients::
+
+          global_coefficients = [('min("alpha.water")', "minalpha")]
+
+#.   Set the Domain of Analysis of the model using the :class:`DomainOfAnalysis<ansys.simai.core.data.model_configuration.DomainOfAnalysis>` instance::
+
+          doa = DomainOfAnalysis(
+               length=("relative_to_min", 15.321, 183.847),
+               width=("relative_to_min", 1.034, 12.414),
+               height=("relative_to_min", 2.046, 24.555),
+          )
+
+
+#.   Configure the model using the :class:`ModelConfiguration<ansys.simai.core.data.model_configuration.ModelConfiguration>` instance::
+
+          mdl_conf = ModelConfiguration(
+               project=project,                             # project of the model configuration
+               build_preset="debug",                        # duration of the build
+               continuous=False,                            # continuous training or not
+               input=model_input,                           # model input
+               output=model_output,                         # model output
+               global_coefficients=global_coefficients,     # Global Coefficients
+               domain_of_analysis=doa                       # Domain of Analysis
+          )
+
+#.   Verify if the project meets the requirements for training and launch a build::
+
+          if project.is_trainable():
+               new_model = simai.models.build(mdl_conf)
+
+Your AI model is configured and building.
+
+Learn more
+----------
+
+For more information on the actions available to you, see :ref:`training_data`,
+:ref:`training_data_parts`, :ref:`projects`, :ref:`model_configuration`, and :ref:`models`

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "flit_core.buildapi"
 
 [project]
 name = "ansys-simai-core"
-version = "0.2.2"
+version = "0.2.3"
 description = "A python wrapper for Ansys SimAI"
 authors = [
     {name = "ANSYS, Inc.", email = "[email protected]"},

src/ansys/simai/core/data/geometries.py

@@ -491,7 +491,7 @@ def upload(  # noqa: D417
                 For more information, see the :class:`~ansys.simai.core.data.types.NamedFile` class.
             metadata: Optional metadata to add to the geometry's simple key-value store.
                 Lists and nested objects are not supported.
-            workspace_id: ID or :class:`model <.workspaces.Workspace>` of the workspace to
+            workspace: ID or :class:`model <.workspaces.Workspace>` of the workspace to
                 upload the geometry to. This parameter is only necessary if no workspace
                 is set for the client.
             monitor_callback: Optional callback for monitoring the progress of the download.
@@ -501,15 +501,16 @@ def upload(  # noqa: D417
         Returns:
             Created :py:class:`Geometry` object.
         """
-        workspace_id = get_id_from_identifiable(workspace, default=self._client._current_workspace)
-        workspace = self._client.workspaces.get(workspace_id)
+        workspace = get_object_from_identifiable(
+            workspace, self._client.workspaces, default=self._client._current_workspace
+        )
         with unpack_named_file(file) as (readable_file, name, extension):
             if extension not in workspace.model_manifest.geometry["accepted_file_formats"]:
                 raise InvalidArguments(
                     f"Got a file with {extension} extension but expected one of : {workspace.model_manifest.geometry['accepted_file_formats']}"
                 )
             (geometry_fields, upload_id) = self._client._api.create_geometry(
-                workspace_id, name, extension, metadata
+                workspace.id, name, extension, metadata
             )
             geometry = self._model_from(geometry_fields, is_upload_complete=False)
             parts = self._client._api.upload_parts(

src/ansys/simai/core/data/global_coefficients_requests.py

@@ -30,6 +30,7 @@
     ComputableDataModel,
     Directory,
 )
+from ansys.simai.core.utils.numerical import cast_values_to_float
 
 if TYPE_CHECKING:
     import ansys.simai.core.client
@@ -179,7 +180,7 @@ def _handle_job_sse_event(self, data):
             self._set_is_pending()
         elif state == "successful":
             logger.debug(f"{self._classname} id {self.id} set status successful")
-            self._result = data.get("result").get("value")
+            self._result = cast_values_to_float(data.get("result", {}).get("value"))
             self._set_is_over()
         elif state in ERROR_STATES:
             error_message = f"Computation of global coefficient {target.get('formula')} failed with {data.get('reason', 'UNKNOWN ERROR')}"

src/ansys/simai/core/data/model_configuration.py

@@ -189,6 +189,17 @@ class ModelOutput:
     volume: list[str] = None
 
 
+@dataclass
+class PostProcessInput:
+    """Designates the variables to use as post-processing input.
+
+    Args:
+        surface: the post-processing input surface variables.
+    """
+
+    surface: list[str] = None
+
+
 @dataclass
 class ModelConfiguration:
     """Configures the build of a model.
@@ -209,6 +220,7 @@ class ModelConfiguration:
         output: the outputs of the model.
         global_coefficients: the Global Coefficients of the model.
         domain_of_analysis: The Domain of Analysis of the model configuration.
+        pp_input: The post-processing input (e.g. a surface variable).
 
     Example:
         Define a new configuration and launch a build.
@@ -222,6 +234,7 @@ class ModelConfiguration:
                 ModelConfiguration,
                 ModelInput,
                 ModelOutput,
+                PostProcessInput,
             )
 
             simai = asc.from_config()
@@ -237,6 +250,9 @@ class ModelConfiguration:
                 surface=["Pressure", "WallShearStress_0"], volume=["Velocity_0", "Pressure"]
             )
 
+            # Define the surface post-processing input
+            pp_input = PostProcessInput(surface=["Temperature_1"])
+
             # Define the model coefficients
             global_coefficients = [("max(Pressure)", "maxpress")]
 
@@ -256,6 +272,7 @@ class ModelConfiguration:
                 output=model_output,
                 global_coefficients=global_coefficients,
                 domain_of_analysis=doa,
+                pp_input=pp_input,
             )
 
             # Launch a mode build with the new configuration
@@ -273,6 +290,7 @@ class ModelConfiguration:
     input: ModelInput = field(default_factory=lambda: ModelInput())
     output: ModelOutput = field(default_factory=lambda: ModelOutput())
     domain_of_analysis: DomainOfAnalysis = field(default_factory=lambda: DomainOfAnalysis())
+    pp_input: PostProcessInput = field(default_factory=lambda: PostProcessInput())
 
     def __set_gc(self, gcs: list[GlobalCoefficientDefinition]):
         verified_gcs = []
@@ -307,23 +325,23 @@ def __init__(
         input: Optional[ModelInput] = None,
         output: Optional[ModelOutput] = None,
         domain_of_analysis: Optional[DomainOfAnalysis] = None,
-        surface_pp_input: Optional[list] = None,
+        pp_input: Optional[PostProcessInput] = None,
     ):
         """Sets the properties of a build configuration."""
-        if surface_pp_input is None:
-            surface_pp_input = []
         self.project = project
         self.input = ModelInput()
         if input is not None:
             self.input = input
         self.output = ModelOutput()
         if output is not None:
             self.output = output
+        self.pp_input = PostProcessInput()
+        if pp_input is not None:
+            self.pp_input = pp_input
         if boundary_conditions is not None and self.input.boundary_conditions is None:
             self.input.boundary_conditions = list(boundary_conditions.keys())
         self.build_preset = build_preset
         self.continuous = continuous
-        self.surface_pp_input = surface_pp_input
         if fields is not None:
             if fields.get("surface_input"):
                 self.input.surface = [fd.get("name") for fd in fields["surface_input"]]
@@ -334,7 +352,8 @@ def __init__(
             if fields.get("volume"):
                 self.output.volume = [fd.get("name") for fd in fields["volume"]]
 
-            self.surface_pp_input = fields.get("surface_pp_input", [])
+            if fields.get("surface_pp_input"):
+                self.pp_input.surface = [fd.get("name") for fd in fields["surface_pp_input"]]
 
         self.domain_of_analysis = domain_of_analysis
         if simulation_volume is not None:
@@ -365,7 +384,7 @@ def _set_doa_axis(self, fld: DomainAxisDefinition, param: str) -> dict[str, Any]
         return {"length": fld.length, "type": fld.position, "value": fld.value}
 
     def _to_payload(self):
-        """Constracts the payload for a build request."""
+        """Constructs the payload for a build request."""
 
         bcs = {}
         if self.input.boundary_conditions is not None:
@@ -390,22 +409,28 @@ def _to_payload(self):
             ]
 
         volume_fld = []
-        if self.output.volume is not None:
+        if self.output.volume:
+            if not sample_metadata.get("volume"):
+                raise ProcessingError(
+                    "No volume file was found in the reference sample. A volume file is required to use volume variables."
+                ) from None
             volume_fld = [
                 fd
-                for fd in sample_metadata.get("volume").get("fields")
+                for fd in sample_metadata["volume"].get("fields")
                 if fd.get("name") in self.output.volume
             ]
 
         gcs = []
         if self.global_coefficients is not None:
             gcs = [asdict(gc) for gc in self.global_coefficients]
 
+        surface_pp_input_fld = self.pp_input.surface or []
+
         flds = {
             "surface": surface_fld,
             "surface_input": surface_input_fld,
             "volume": volume_fld,
-            "surface_pp_input": self.surface_pp_input if self.surface_pp_input else [],
+            "surface_pp_input": surface_pp_input_fld,
         }
 
         simulation_volume = {