Update main.yml

* chore(github action): update composite action version to configure buildx

* chore(github action): use tagged release for speckle automate action

.devcontainer/devcontainer.json

@@ -6,7 +6,7 @@
   "dockerFile": "../Dockerfile",
 
   // Use 'postCreateCommand' to run commands after the container is created.
-  // "postCreateCommand": "poetry install --no-root",
+  "postCreateCommand": "poetry install --no-root",
 
   // Configure tool-specific properties.
   "customizations": {

.dockerignore

@@ -4,8 +4,6 @@ dist/
 *.egg-info/
 .cache/
 *.log
-.ruff_cache/
-.venv/
 .env/
 .git/
 Dockerfile copy*

.github/dependabot.yml

@@ -0,0 +1,6 @@
+version: 2
+updates:
+  - package-ecosystem: "github-actions"
+    directory: "/"
+    schedule:
+      interval: "daily"

.github/workflows/main.yml

@@ -29,12 +29,12 @@ jobs:
         run: |
           python main.py generate_schema ${HOME}/${{ env.FUNCTION_SCHEMA_FILE_NAME }}
       - name: Speckle Automate Function - Build and Publish
-        uses: specklesystems/speckle-automate-github-composite-action@0.7.2
+        uses: specklesystems/speckle-automate-github-composite-action@0.7.4
         with:
           speckle_automate_url: ${{ env.SPECKLE_AUTOMATE_URL || 'https://automate.speckle.dev' }} 
           speckle_token: ${{ secrets.SPECKLE_FUNCTION_TOKEN }}
           speckle_function_id: ${{ secrets.SPECKLE_FUNCTION_ID }}
           speckle_function_input_schema_file_path: ${{ env.FUNCTION_SCHEMA_FILE_NAME }}
           speckle_function_command: 'python -u main.py run'
-          speckle_function_recommended_cpu_m: 2000
-          speckle_function_recommended_memory_mi: 100
+          speckle_function_recommended_cpu_m: 4000
+          speckle_function_recommended_memory_mi: 4000

.gitignore

@@ -311,3 +311,14 @@ pyrightconfig.json
 .ionide
 
 # End of https://www.toptal.com/developers/gitignore/api/visualstudiocode,python,pycharm
+Dockerfile copy
+Dockerfile copy 2
+.idea/git_toolbox_prj.xml
+.gitignore
+.idea/misc.xml
+.idea/inspectionProfiles/Project_Default.xml
+.gitignore
+.idea/vcs.xml
+.idea/speckle-automate-basic-clash-demo.iml
+.idea/modules.xml
+.idea/inspectionProfiles/profiles_settings.xml

Dockerfile

@@ -246,4 +246,6 @@ COPY . /home/speckle
 
 # Using poetry, we generate a list of requirements, save them to requirements.txt, and then use pip to install them
 RUN poetry export --format requirements.txt --output /home/speckle/requirements.txt --without-hashes && \
-    pip install --requirement /home/speckle/requirements.txt
+    pip install --requirement /home/speckle/requirements.txt
+
+RUN poetry install --no-root

Geometry/clash.py

@@ -0,0 +1,156 @@
+from concurrent.futures import ProcessPoolExecutor, as_completed
+from typing import List, Tuple, Any, Optional
+
+try:
+    import pymesh
+except ImportError:
+    from Geometry.mocks import mypymesh
+
+    pymesh = mypymesh
+
+from speckle_automate import AutomationContext
+
+from Geometry.element import Element
+from Geometry.mesh import cast
+
+
+def detect_clashes_old(
+        reference_elements: List[Element], latest_elements: List[Element], _tolerance: float
+) -> list[tuple[str, str, float]]:
+    """
+    Detect clashes between two sets of mesh elements using Pymesh.
+
+    Args:
+        reference_elements (List[Element]): Elements from the reference model.
+        latest_elements (List[Element]): Elements from the latest model.
+        _tolerance (float): Tolerance value for clash detection. TODO: how to implement this?
+
+    Returns:
+        List[Tuple[str, str]]: List of tuples indicating clashes, with each tuple
+                               containing the IDs of the clashing elements.
+    """
+    # TODO: Spatial partitioning to reduce number of comparisons
+    # TODO: Tolerance
+    # TODO: parallel processing
+
+    clashes = []
+    for ref_element in reference_elements:
+        for latest_element in latest_elements:
+            for ref_mesh in ref_element.meshes:
+                for latest_mesh in latest_element.meshes:
+                    # Convert Trimesh meshes to Pymesh if necessary
+                    ref_pymesh: pymesh.Mesh = cast(ref_mesh, pymesh.Mesh)
+                    latest_pymesh: pymesh.Mesh = cast(latest_mesh, pymesh.Mesh)
+
+                    if not ref_pymesh or not latest_pymesh:
+                        continue
+
+                    intersection = pymesh.boolean(
+                        latest_pymesh, ref_pymesh, operation="intersection"
+                    )
+
+                    if (
+                            intersection and intersection.volume > 0
+                    ):  # TODO: could tolerance relate to this?
+                        severity = intersection.volume / min(
+                            ref_pymesh.volume, latest_pymesh.volume
+                        )
+                        clashes.append((ref_element.id, latest_element.id, severity))
+                        break
+
+    return clashes
+
+
+def check_for_clash(
+        ref_element: Element, latest_element: Element
+) -> Optional[tuple[Any, Any, Any]]:
+    """
+    Check for a clash between two elements and calculate the severity of the clash.
+
+    Args:
+        ref_element (Element): An element from the reference model.
+        latest_element (Element): An element from the latest model.
+
+    Returns:
+        Tuple[str, str, float]: A tuple containing the IDs of the clashing elements and the severity, if a clash is found.
+    """
+
+    for ref_mesh in ref_element.meshes:
+        for latest_mesh in latest_element.meshes:
+            ref_pymesh = cast(ref_mesh, pymesh.Mesh)
+            latest_pymesh = cast(latest_mesh, pymesh.Mesh)
+
+            if not ref_pymesh or not latest_pymesh:
+                continue
+
+            intersection = pymesh.boolean(latest_pymesh, ref_pymesh, operation="intersection")
+
+            if intersection and intersection.volume > 0:
+                severity = intersection.volume / min(
+                    ref_pymesh.volume, latest_pymesh.volume
+                )
+                return ref_element.id, latest_element.id, severity
+    return None
+
+
+def detect_clashes(
+        reference_elements: List[Element], latest_elements: List[Element], _tolerance: float
+) -> List[Tuple[str, str, float]]:
+    """
+    Detect clashes between two sets of mesh elements using parallel processing.
+
+    Args:
+        reference_elements (List[Element]): Elements from the reference model.
+        latest_elements (List[Element]): Elements from the latest model.
+        _tolerance (float): Tolerance value for clash detection. TODO: how to implement this?
+
+    Returns:
+        List[Tuple[str, str, float]]: A list of tuples indicating clashes.
+    """
+    clashes = []
+    with ProcessPoolExecutor() as executor:
+        future_clash = {
+            executor.submit(check_for_clash, ref, latest): (ref, latest)
+            for ref in reference_elements
+            for latest in latest_elements
+        }
+        for future in as_completed(future_clash):
+            result = future.result()
+            if result:
+                clashes.append(result)
+
+    return clashes
+
+
+def detect_and_report_clashes(
+        reference_elements: list[Element],
+        latest_elements: list[Element],
+        tolerance: float,
+        automate_context: AutomationContext,
+) -> list[tuple[str, str, float]]:
+    print(f"{len(reference_elements[0].meshes)} reference meshes")
+    print(f"{len(latest_elements[0].meshes)} latest meshes")
+
+    clashes = detect_clashes(reference_elements, latest_elements, tolerance)
+
+    total_clashes = len(clashes)
+    padding_length = len(str(total_clashes))
+
+    for i, (ref_id, latest_id, severity) in enumerate(clashes, start=1):
+        clash_number = str(i).zfill(padding_length)
+        combined_message = f"Clash {clash_number}: between {ref_id} and {latest_id} with severity {severity:.2f}"
+        object_ids = [ref_id, latest_id]
+
+        # Assuming severity levels: Low (<0.25), Medium (0.25-0.75), High (>0.75) TODO: Determine severity levels
+        if severity > 0.75:
+            category = "High"
+        elif severity > 0.25:
+            category = "Medium"
+        else:
+            category = "Low"
+
+        automate_context.attach_error_to_objects(
+            category=category, object_ids=object_ids, message=combined_message
+        )
+
+    return clashes

Geometry/element.py

@@ -0,0 +1,64 @@
+from typing import Tuple, Optional, List
+
+import numpy as np
+import trimesh
+from specklepy.objects import Base
+from specklepy.objects.geometry import Mesh as SpeckleMesh
+from specklepy.objects.other import Transform
+
+from Geometry.helpers import combine_transform_matrices
+from Geometry.mesh import speckle_mesh_to_trimesh
+
+
+class Element:
+    def __init__(self, id, meshes):
+        """
+        Initialize an Element object with an ID and a list of meshes.
+
+        Args:
+        id (str): The ID of the Element.
+        meshes (List[Trimesh]): List of trimesh Mesh objects.
+        """
+        self.id = id
+        self.meshes = meshes
+
+
+def speckle_to_element(
+    base_id_transforms: Tuple[Base, str, Optional[List[Transform]]]
+) -> Element:
+    """
+    Convert a SpecklePy Base object, its identifier, and an optional list of transforms
+    to an Element object.
+
+    Args:
+        base_id_transforms (tuple): Contains a SpecklePy Base object, its identifier,
+            and an optional list of Transform objects.
+
+    Returns:
+        Element: The resulting Element object.
+    """
+    base, speckle_id, transforms = base_id_transforms
+
+    display_value = base.displayValue
+    if isinstance(display_value, SpeckleMesh):
+        display_value = [display_value]
+
+    element = Element(speckle_id, meshes=[])
+
+    # Combine all transforms into a single matrix
+    combined_transform = (
+        combine_transform_matrices(transforms) if transforms else np.identity(4)
+    )
+
+    if isinstance(display_value, list):
+        for mesh in display_value:
+            if mesh:
+                t_mesh = speckle_mesh_to_trimesh(mesh)
+                if not isinstance(t_mesh, trimesh.Trimesh):
+                    continue
+
+                # Apply the combined transformation matrix
+                t_mesh.apply_transform(combined_transform)
+                element.meshes.append(t_mesh)
+
+    return element

Geometry/helpers.py

@@ -0,0 +1,143 @@
+from typing import List
+
+import numpy as np
+from specklepy.objects.geometry import Vector
+from specklepy.objects.other import Transform as SpeckleTransform
+
+
+def calculate_polygon_normal(vertices: List[Vector]) -> Vector:
+    """
+    Calculate the normal vector for a polygon represented by a list of vertices.
+
+    Args:
+        vertices (List[Vector]): A list of vertices representing the polygon.
+
+    Returns:
+        Vector: The normal vector of the polygon.
+    """
+    normal = Vector.from_list([0.0, 0.0, 0.0])
+    num_vertices = len(vertices)
+    for i in range(num_vertices):
+        curr, nxt = vertices[i], vertices[(i + 1) % num_vertices]
+        # Cross product components are accumulated to find the normal.
+        normal.x += (curr.y - nxt.y) * (curr.z + nxt.z)
+        normal.y += (curr.z - nxt.z) * (curr.x + nxt.x)
+        normal.z += (curr.x - nxt.x) * (curr.y + nxt.y)
+
+    # Normalize the calculated normal vector.
+    length = np.sqrt(normal.x**2 + normal.y**2 + normal.z**2)
+    normal.x, normal.y, normal.z = (
+        normal.x / length,
+        normal.y / length,
+        normal.z / length,
+    )
+    return normal
+
+
+def is_point_within_triangle(pt: Vector, v1: Vector, v2: Vector, v3: Vector) -> bool:
+    """
+    Check if a point is inside a given triangle.
+
+    Args:
+        pt (Vector): The point to check.
+        v1, v2, v3 (Vector): The vertices of the triangle.
+
+    Returns:
+        bool: True if the point is inside the triangle, False otherwise.
+    """
+
+    def sign(p1, p2, p3):
+        return (p1.x - p3.x) * (p2.y - p3.y) - (p2.x - p3.x) * (p1.y - p3.y)
+
+    b1 = sign(pt, v1, v2) < 0.0
+    b2 = sign(pt, v2, v3) < 0.0
+    b3 = sign(pt, v3, v1) < 0.0
+
+    return (b1 == b2) and (b2 == b3)
+
+
+def triangulate_face(vertices: List[Vector]) -> List[List[int]]:
+    """
+    Triangulate a polygon defined by a list of vertices.
+
+    Args:
+        vertices (List[Vector]): The vertices of the polygon.
+
+    Returns:
+        List[List[int]]: A list of triangles, each represented as a list of vertex indices.
+    """
+    triangles = []
+    indices = list(range(len(vertices)))
+    normal = calculate_polygon_normal(vertices)
+
+    # The ear clipping algorithm is used for triangulation.
+    while len(indices) > 2:
+        for i in range(len(indices)):
+            prev, curr, nxt = (
+                indices[i - 1],
+                indices[i],
+                indices[(i + 1) % len(indices)],
+            )
+            if is_convex(vertices[prev], vertices[curr], vertices[nxt], normal):
+                triangles.append([prev, curr, nxt])
+                del indices[i]
+                break
+
+    return triangles
+
+
+def is_convex(a: Vector, b: Vector, c: Vector, normal: Vector) -> bool:
+    """
+    Check if a triangle formed by three vertices (a, b, c) is convex with respect to a given normal.
+
+    Args:
+        a (Vector): The first vertex of the triangle.
+        b (Vector): The second vertex of the triangle.
+        c (Vector): The third vertex of the triangle.
+        normal (Vector): The normal vector with respect to which convexity is checked.
+
+    Returns:
+        bool: True if the triangle is convex with respect to the normal, False otherwise.
+    """
+    ab = Vector.from_list([b.x - a.x, b.y - a.y, b.z - a.z])
+    bc = Vector.from_list([c.x - b.x, c.y - b.y, c.z - b.z])
+    cross = Vector.from_list(
+        [
+            ab.y * bc.z - ab.z * bc.y,
+            ab.z * bc.x - ab.x * bc.z,
+            ab.x * bc.y - ab.y * bc.x,
+        ]
+    )
+
+    # Dot product to compare with the face normal
+    return cross.x * normal.x + cross.y * normal.y + cross.z * normal.z > 0
+
+
+def combine_transform_matrices(transforms: List[SpeckleTransform]) -> np.ndarray:
+    """
+    Combine multiple transformation matrices into a single matrix.
+
+    Args:
+        transforms (List[SpeckleTransform]): A list of Speckle Transform objects.
+
+    Returns:
+        np.ndarray: A combined 4x4 transformation matrix.
+    """
+    combined_matrix = np.identity(4)
+    for transform in transforms:
+        matrix = convert_speckle_transform_to_matrix(transform)
+        combined_matrix = np.dot(combined_matrix, matrix)
+    return combined_matrix
+
+
+def convert_speckle_transform_to_matrix(transform: SpeckleTransform) -> np.ndarray:
+    """
+    Convert a Speckle Transform object to a 4x4 NumPy matrix.
+
+    Args:
+        transform (SpeckleTransform): The Speckle Transform object.
+
+    Returns:
+        np.ndarray: A 4x4 transformation matrix.
+    """
+    return np.array(transform.value).reshape(4, 4)

Geometry/mesh.py

@@ -1,107 +1,95 @@
-from typing import Tuple, Optional
+from typing import Union, Type
+
+try:
+    import pymesh
+except ImportError:
+    from Geometry.mocks import mypymesh
+
+    pymesh = mypymesh
+
+import trimesh
+
+from Geometry.helpers import triangulate_face
+
+
+def trimesh_to_pymesh(mesh: trimesh.Trimesh) -> pymesh.Mesh:
+    """
+    Convert a Trimesh object to a Pymesh object.
+    Args:
+        mesh (Trimesh): The Trimesh object to convert.
+    Returns:
+        pymesh.Mesh: The resulting Pymesh object.
+    """
+    return pymesh.form_mesh(mesh.vertices, mesh.faces)
+
+
+def pymesh_to_trimesh(mesh: pymesh.Mesh) -> trimesh.Trimesh:
+    """
+    Convert a Pymesh object to a Trimesh object.
+    Args:
+        mesh (pymesh.Mesh): The Pymesh object to convert.
+    Returns:
+        trimesh.Trimesh: The resulting Trimesh object.
+    """
+    return trimesh.Trimesh(vertices=mesh.vertices, faces=mesh.faces)
+
+
+def cast(
+        mesh: Union[trimesh.Trimesh, pymesh.Mesh], target_type: Type
+) -> Union[trimesh.Trimesh, pymesh.Mesh]:
+    """
+    Casts a mesh object to a specified type.
+
+    Args:
+        mesh (Union[trimesh.Trimesh, pymesh.Mesh]): The mesh object to cast.
+        target_type (Type): The type to cast the mesh to.
+
+    Returns:
+        Union[trimesh.Trimesh, pymesh.Mesh]: The cast mesh object.
+    """
+
+    if isinstance(mesh, trimesh.Trimesh) and target_type is pymesh.Mesh:
+        return trimesh_to_pymesh(mesh)
+    elif isinstance(mesh, pymesh.Mesh) and target_type is trimesh.Trimesh:
+        return pymesh_to_trimesh(mesh)
+    else:
+        raise TypeError("Unsupported mesh type or target type.")
+
 
 import numpy as np
 import trimesh
-from specklepy.objects import Base
-from specklepy.objects.geometry import Mesh as SpeckleMesh
-from specklepy.objects.other import Transform
-from trimesh import Trimesh
+from specklepy.objects.geometry import Mesh as SpeckleMesh, Vector
 
 
-class Element:
-    def __init__(self, id, meshes):
-        """
-        Initialize an Element object with an ID and a list of meshes.
+def speckle_mesh_to_trimesh(input_mesh: SpeckleMesh) -> trimesh.Trimesh:
+    vertices = np.array(input_mesh.vertices).reshape((-1, 3))
+    faces = []
 
-        Args:
-        id (str): The ID of the Element.
-        meshes (List[Trimesh]): List of trimesh Mesh objects.
-        """
-        self.id = id
-        self.meshes = meshes
+    i = 0
+    while i < len(input_mesh.faces):
+        face_vertex_count = input_mesh.faces[i]
+        i += 1  # Skip the vertex count
 
+        face_vertex_indices = input_mesh.faces[i: i + face_vertex_count]
 
-def speckle_transform_to_trimesh_matrix(transform: Transform) -> np.ndarray:
-    """
-    Convert the Speckle Transform matrix to a NumPy array format suitable for trimesh.
+        face_vertices = [
+            Vector.from_list(vertices[idx].tolist()) for idx in face_vertex_indices
+        ]
 
-    Returns:
-        np.ndarray: 4x4 transformation matrix in NumPy array format.
-    """
-    return np.array(transform.value).reshape(4, 4)
+        if face_vertex_count == 3:
+            faces.append(face_vertex_indices)
+        else:
+            triangulated = triangulate_face(face_vertices)
+            faces.extend(
+                [[face_vertex_indices[idx] for idx in tri] for tri in triangulated]
+            )
 
+        i += face_vertex_count
 
-def speckle_to_element(
-    base_with_transforms: Tuple[Base, str, Optional[Transform]]
-) -> Element:
-    """
-    Convert a SpecklePy Base object and its associated Transform to an Element object.
+    t_mesh = trimesh.Trimesh(vertices=vertices, faces=np.array(faces))
 
-    Args:
-        base_with_transforms (tuple): Contains a SpecklePy Base object and its
-            associated Transform object.
+    obbox = t_mesh.bounding_box_oriented
 
-    Returns:
-        Element: The resulting Element object.
-    """
+    obbox_mesh = obbox.to_mesh()
 
-    # Unpack the tuple to get the base, speckle ID, and transform.
-    base, speckle_id, transform = base_with_transforms
-
-    # To convert the Base object to a trimesh Mesh, use the displayValue property.
-    # This property provides the display mesh, expected to be an iterable of
-    # SpecklePy Mesh objects. However, legacy objects might be a single mesh.
-    display_value = base.displayValue
-    if isinstance(display_value, SpeckleMesh):
-        display_value = [display_value]
-
-    if isinstance(display_value, list):
-        # Initialize an Element with an empty list of meshes.
-        element = Element(speckle_id, meshes=[])
-
-        for mesh in display_value:
-            if mesh:
-                # Convert the SpecklePy Mesh to a trimesh Mesh.
-                t_mesh = speckle_to_trimesh(mesh)
-                if not isinstance(t_mesh, Trimesh):
-                    continue
-
-                # If there's a transform, apply it to the trimesh Mesh.
-                if transform is not None:
-                    trimesh_matrix = speckle_transform_to_trimesh_matrix(transform)
-                    t_mesh.apply_transform(trimesh_matrix)
-
-                # Append the trimesh Mesh to the Element's list of meshes.
-                element.meshes.append(t_mesh)
-
-        return element
-
-
-def speckle_to_trimesh(speckle_mesh: SpeckleMesh) -> Trimesh:
-    """
-    Convert a SpecklePy Mesh to a trimesh Mesh object.
-
-    Args:
-        speckle_mesh: The SpecklePy Mesh to convert.
-
-    Returns:
-        trimesh.Trimesh: The resulting trimesh Mesh object.
-    """
-
-    # Convert the list of vertices to a numpy array. Reshape it to
-    # (num_vertices, 3) to fit the trimesh format.
-    vertices_array = np.array(speckle_mesh.vertices).reshape((-1, 3))
-
-    # Faces are expected to be triangular. Reshape the faces list accordingly.
-
-    # Convert the faces list to a numpy array
-    faces_array_raw = np.array(speckle_mesh.faces)
-
-    # Remove the leading 3s by skipping every 4th value
-    faces_cleaned = np.delete(faces_array_raw, np.arange(0, faces_array_raw.size, 4))
-
-    # Reshape the array into (-1, 3) shape
-    faces_array = faces_cleaned.reshape((-1, 3))
-
-    # Return a new trimesh object using the reshaped vertices and faces.
-    return trimesh.Trimesh(vertices=vertices_array, faces=faces_array)
+    return obbox_mesh

Geometry/mocks.py

@@ -0,0 +1,17 @@
+class mypymesh:
+    class Mesh:
+        def __init__(self, vertices, faces):
+            self.vertices = vertices
+            self.faces = faces
+
+        @property
+        def volume(self):
+            return 0
+
+    @staticmethod
+    def boolean(mesh_a, mesh_b, operation):
+        return mypymesh.Mesh([], [])
+
+    @staticmethod
+    def form_mesh(vertices, faces):
+        return mypymesh.Mesh(vertices, faces)

Geometry/p.py

@@ -1,16 +0,0 @@
-import pymesh
-
-vertices = [
-    [0, 0, 0],
-    [1, 0, 0],
-    [1, 1, 0],
-    [0, 1, 0]
-
-]
-
-faces = [
-    [0, 1, 2],
-    [0, 2, 3]
-]
-
-mesh = pymesh.form_mesh(vertices, faces)

README.md

@@ -28,6 +28,27 @@ This demo showcases the ability to incorporate complex third-party libraries for
 ## Note
 This function is designed for educational purposes and is not equipped for real-world AEC projects.
 
+---
+## Potential Expansions for the Basic Clash Analysis Demo
+
+This demo serves as a starting point and can be expanded in several ways to enhance its capabilities and usability within Speckle Automate. Below are some ideas for future development:
+
+### Importing Rule Sets from External Sources
+- **Dynamic Rule Set Integration:** Enable the function to import clash detection rules from external files or databases, allowing for greater flexibility and customization of clash criteria.
+- **API-Based Rule Configuration:** Develop an API endpoint where users can update or modify rule sets dynamically, making the function adaptable to varying project requirements.
+
+### Enhancing User Interaction with External UIs
+- **Customizable User Interface:** Implement a user-friendly interface that allows users to interact with the function directly, configure settings, and view clash reports more intuitively.
+- **Integration with AEC Tools:** Design interfaces or plugins for popular AEC software tools, enabling users to access and use the clash detection function directly from their preferred design environment.
+
+### Advanced Analysis Features
+- **Complex Geometric Analysis:** Expand the function to perform more sophisticated geometric analyses, potentially using advanced algorithms or machine learning models to identify complex clashes.
+- **Historical Data Analysis:** Incorporate features to analyze the evolution of clashes over time, providing insights into recurring issues or patterns in the project lifecycle.
+
+### Collaborative Feedback Loops
+- **Real-Time Collaboration Tools:** Integrate real-time communication tools within the function, allowing team members to discuss and resolve clashes directly within the Speckle environment.
+- **Automated Notification System:** Enhance the notification system to provide more detailed alerts, including clash severity levels and suggested resolutions.
+
 ---
 
 **Reminder:** This repository is a conceptual demonstration for automated clash detection and the use of third-party libraries in Speckle Automate.

Rules/checks.py

@@ -30,12 +30,12 @@ class ElementCheckRules:
         """Rule: Check if a parameter is displayable."""
         return (
             lambda parameter: parameter.displayValue
-            and parameter.displayValue is not None
+                              and parameter.displayValue is not None
         )
 
     @staticmethod
     def speckle_type_rule(
-        desired_type: Union[str, List[str]]
+            desired_type: Union[str, List[str]]
     ) -> Callable[[Base], bool]:
         """Rule: Check if a parameter's speckle_type matches the desired type."""
 
@@ -43,9 +43,7 @@ class ElementCheckRules:
         if isinstance(desired_type, str):
             desired_type = [desired_type]
 
-        print(desired_type)
-
         return (
             lambda speckle_object: getattr(speckle_object, "speckle_type", None)
-            in desired_type
+                                   in desired_type
         )

Utilities/flatten.py

@@ -1,5 +1,5 @@
 """Helper module for a simple speckle object tree flattening."""
-from typing import Tuple, Optional
+from typing import Tuple, Optional, List
 
 from specklepy.objects import Base
 from specklepy.objects.other import Instance, Transform

main.py

@@ -2,7 +2,7 @@
 
 use the automation_context module to wrap your function in an Automate context helper
 """
-from typing import List, Optional, Tuple
+from typing import Optional
 
 from pydantic import Field
 from speckle_automate import (
@@ -16,11 +16,11 @@ from specklepy.objects import Base
 from specklepy.objects.other import Transform
 from specklepy.objects.units import Units
 from specklepy.transports.server import ServerTransport
-from trimesh import Trimesh
 
-from Geometry.mesh import speckle_to_element, Element
+from Geometry.clash import detect_and_report_clashes
+from Geometry.element import speckle_to_element
 from Rules.checks import ElementCheckRules
-from flatten import extract_base_and_transform
+from Utilities.flatten import extract_base_and_transform
 
 
 class FunctionInputs(AutomateBase):
@@ -31,28 +31,31 @@ class FunctionInputs(AutomateBase):
     https://docs.pydantic.dev/latest/usage/models/
     """
 
-    tolerance: float = Field(
-        default=25.0,
-        title="Tolerance",
-        description="Specify the tolerance value for the analysis. \
-            Negative values relaxes the test, positive values make it more strict.",
-    )
-    tolerance_unit: str = Field(  # Using the SpecklePy Units enum here
-        default=Units.mm,
-        json_schema_extra={"examples": ["mm", "cm", "m"]},
-        title="Tolerance Unit",
-        description="Unit of the tolerance value.",
-    )
     static_model_name: str = Field(
         ...,
         title="Static Model Name",
         description="Name of the static structural model.",
     )
+    tolerance: float = Field(
+        default=25.0,
+        title="Tolerance",
+        description="Specify the tolerance value for the analysis. \
+        Negative values relaxes the test, positive values make it more strict.",
+        json_schema_extra={
+            "readOnly": True,
+        }
+    )
+    tolerance_unit: str = Field(  # Using the SpecklePy Units enum here
+        default=Units.mm,
+        json_schema_extra={"examples": ["mm", "cm", "m"], "readOnly": True},
+        title="Tolerance Unit",
+        description="Unit of the tolerance value.",
+    )
 
 
 def automate_function(
-    automate_context: AutomationContext,
-    function_inputs: FunctionInputs,
+        automate_context: AutomationContext,
+        function_inputs: FunctionInputs,
 ) -> None:
     """This is an example Speckle Automate function.
 
@@ -67,9 +70,10 @@ def automate_function(
     changed_model_version = automate_context.receive_version()
 
     try:
-        reference_model_version = get_reference_model(
+        reference_model_version, reference_model_id, reference_model_version_id = get_reference_model(
             automate_context, function_inputs.static_model_name
         )
+        print(f"Reference model id: {reference_model_id}, version id: {reference_model_version_id}")
 
     except Exception as ex:
         automate_context.mark_run_failed(status_message=str(ex))
@@ -112,6 +116,7 @@ def automate_function(
         for base_obj, id, transform in reference_objects
         if visible_beams_rule(base_obj)
     ]
+
     latest_displayable_objects = [
         (base_obj, id, transform)
         for base_obj, id, transform in latest_objects
@@ -125,84 +130,53 @@ def automate_function(
         speckle_to_element(obj) for obj in latest_displayable_objects
     ]
 
-    # using trimesh library process all these meshes in the form of A vs B
-    # and get the clashes
+    tolerance = function_inputs.tolerance
 
-    clashes = detect_clashes(
-        reference_mesh_elements, latest_mesh_elements, function_inputs.tolerance
+    clashes = detect_and_report_clashes(
+        reference_mesh_elements, latest_mesh_elements, tolerance, automate_context
     )
 
-    print(len(clashes))
+    percentage_reference_objects_clashing = (
+            len(set([ref_id for ref_id, latest_id, severity in clashes]))
+            / len(reference_mesh_elements)
+            * 100
+    )
+    percentage_latest_objects_clashing = (
+            len(set([latest_id for ref_id, latest_id, severity in clashes]))
+            / len(latest_mesh_elements)
+            * 100
+    )
 
-    automate_context.mark_run_success(status_message="Clash detection completed.")
+    # all clashes count
+    all_objects_count = len(reference_mesh_elements) + len(latest_mesh_elements)
+    all_clashes_count = len(clashes)
 
+    print(f"Clash detection report: {all_clashes_count} clashes found between {all_objects_count} objects.")
 
+    print(f"Reference objects: {len([x for x in reference_objects])}.")
+    print(f"Latest objects: {len([x for x in latest_objects])}.")
 
-def detect_clashes(
-    elements_a: List[Element], elements_b: List[Element], length_tolerance: float
-) -> List[Tuple[Element, Element]]:
-    """
-    Detects clashes between two sets of elements with a specified tolerance.
+    clash_report_message = (
+        f"Clash detection report: {all_clashes_count} clashes found "
+        f"between {all_objects_count} objects. "
+        f"Percentage of reference objects clashing: "
+        f"{percentage_reference_objects_clashing}%. "
+        f"Percentage of latest objects clashing: "
+        f"{percentage_latest_objects_clashing}%."
+    )
 
-    This function checks each combination of elements from `elements_a` and `elements_b`
-    to see if any of their respective meshes intersect within the specified tolerance.
-    If a clash is detected between any mesh from an element in `elements_a` and any mesh
-    from an element in `elements_b`, the pair of elements is added to the results.
+    reference_view = [f"{reference_model_id}@{reference_model_version_id}"]
 
-    Args:
-    - elements_a (List[Element]): A list of `Element` objects to be checked for clashes.
-    - elements_b (List[Element]): A second list of `Element` objects to be checked for clashes against `elements_a`.
-    - length_tolerance (float): The distance to offset mesh vertices for intersection check.
+    automate_context.set_context_view(reference_view)
 
-    Returns:
-    - List[Tuple[Element, Element]]: A list of tuples where each tuple contains a pair of `Element` objects that clash.
-    """
-
-    # Use list comprehension to get pairs of elements that have clashing meshes
-    clashes = [
-        (element_a, element_b)
-        for element_a in elements_a
-        for element_b in elements_b
-        if any(
-            check_intersection_with_tolerance(mesh_a, mesh_b, length_tolerance)
-            for mesh_a in element_a.meshes
-            for mesh_b in element_b.meshes
-        )
-    ]
-
-    return clashes
-
-
-def check_intersection_with_tolerance(
-    mesh_a: Trimesh, mesh_b: Trimesh, tolerance: float
-) -> bool:
-    """
-    Checks for intersections between two meshes within a specified tolerance.
-
-    Args:
-    - mesh_a: The first mesh to check.
-    - mesh_b: The second mesh to check.
-    - tolerance (float): The distance to offset mesh vertices for intersection check.
-                         Positive values expand the mesh, negative values contract it.
-
-    Returns:
-    - bool: True if the meshes intersect within the specified tolerance, otherwise False.
-    """
-    half_tolerance = tolerance / 2.0  # TODO: how to shrink bloat mesh?
-    offset_mesh_a: Trimesh = mesh_a  # mesh_a.offset_mesh(half_tolerance)
-    offset_mesh_b: Trimesh = mesh_b  # mesh_b.offset_mesh(half_tolerance)
-
-    # return offset_mesh_a.intersection(offset_mesh_b).volume > 0 TODO: Install Blender as the engine
-
-    # return a random boolean for testing - significantly favouring false
-    import random
-
-    return random.random() < 0.05
+    automate_context.mark_run_success(
+        status_message="Clash detection completed. " + clash_report_message
+    )
 
 
 def get_reference_model(
-    automate_context: AutomationContext, static_model_name: str
-) -> Base:
+        automate_context: AutomationContext, static_model_name: str
+) -> tuple[Base, Optional[str], Optional[str]]:
     # the static reference model will be retrieved from the project using model name stored in the inputs
     speckle_client = automate_context.speckle_client
     project_id = automate_context.automation_run_data.project_id
@@ -236,7 +210,7 @@ def get_reference_model(
         remote_transport,
     )  # receive the static model
 
-    return latest_reference_model_version
+    return latest_reference_model_version, model.id, reference_model_commits[0].id
 
 
 # make sure to call the function with the executor

poetry.lock

@@ -540,6 +540,51 @@ files = [
     {file = "mypy_extensions-1.0.0.tar.gz", hash = "sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782"},
 ]
 
+[[package]]
+name = "numpy"
+version = "1.26.2"
+description = "Fundamental package for array computing in Python"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "numpy-1.26.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:3703fc9258a4a122d17043e57b35e5ef1c5a5837c3db8be396c82e04c1cf9b0f"},
+    {file = "numpy-1.26.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:cc392fdcbd21d4be6ae1bb4475a03ce3b025cd49a9be5345d76d7585aea69440"},
+    {file = "numpy-1.26.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:36340109af8da8805d8851ef1d74761b3b88e81a9bd80b290bbfed61bd2b4f75"},
+    {file = "numpy-1.26.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bcc008217145b3d77abd3e4d5ef586e3bdfba8fe17940769f8aa09b99e856c00"},
+    {file = "numpy-1.26.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:3ced40d4e9e18242f70dd02d739e44698df3dcb010d31f495ff00a31ef6014fe"},
+    {file = "numpy-1.26.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:b272d4cecc32c9e19911891446b72e986157e6a1809b7b56518b4f3755267523"},
+    {file = "numpy-1.26.2-cp310-cp310-win32.whl", hash = "sha256:22f8fc02fdbc829e7a8c578dd8d2e15a9074b630d4da29cda483337e300e3ee9"},
+    {file = "numpy-1.26.2-cp310-cp310-win_amd64.whl", hash = "sha256:26c9d33f8e8b846d5a65dd068c14e04018d05533b348d9eaeef6c1bd787f9919"},
+    {file = "numpy-1.26.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b96e7b9c624ef3ae2ae0e04fa9b460f6b9f17ad8b4bec6d7756510f1f6c0c841"},
+    {file = "numpy-1.26.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:aa18428111fb9a591d7a9cc1b48150097ba6a7e8299fb56bdf574df650e7d1f1"},
+    {file = "numpy-1.26.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:06fa1ed84aa60ea6ef9f91ba57b5ed963c3729534e6e54055fc151fad0423f0a"},
+    {file = "numpy-1.26.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:96ca5482c3dbdd051bcd1fce8034603d6ebfc125a7bd59f55b40d8f5d246832b"},
+    {file = "numpy-1.26.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:854ab91a2906ef29dc3925a064fcd365c7b4da743f84b123002f6139bcb3f8a7"},
+    {file = "numpy-1.26.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:f43740ab089277d403aa07567be138fc2a89d4d9892d113b76153e0e412409f8"},
+    {file = "numpy-1.26.2-cp311-cp311-win32.whl", hash = "sha256:a2bbc29fcb1771cd7b7425f98b05307776a6baf43035d3b80c4b0f29e9545186"},
+    {file = "numpy-1.26.2-cp311-cp311-win_amd64.whl", hash = "sha256:2b3fca8a5b00184828d12b073af4d0fc5fdd94b1632c2477526f6bd7842d700d"},
+    {file = "numpy-1.26.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:a4cd6ed4a339c21f1d1b0fdf13426cb3b284555c27ac2f156dfdaaa7e16bfab0"},
+    {file = "numpy-1.26.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5d5244aabd6ed7f312268b9247be47343a654ebea52a60f002dc70c769048e75"},
+    {file = "numpy-1.26.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6a3cdb4d9c70e6b8c0814239ead47da00934666f668426fc6e94cce869e13fd7"},
+    {file = "numpy-1.26.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aa317b2325f7aa0a9471663e6093c210cb2ae9c0ad824732b307d2c51983d5b6"},
+    {file = "numpy-1.26.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:174a8880739c16c925799c018f3f55b8130c1f7c8e75ab0a6fa9d41cab092fd6"},
+    {file = "numpy-1.26.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f79b231bf5c16b1f39c7f4875e1ded36abee1591e98742b05d8a0fb55d8a3eec"},
+    {file = "numpy-1.26.2-cp312-cp312-win32.whl", hash = "sha256:4a06263321dfd3598cacb252f51e521a8cb4b6df471bb12a7ee5cbab20ea9167"},
+    {file = "numpy-1.26.2-cp312-cp312-win_amd64.whl", hash = "sha256:b04f5dc6b3efdaab541f7857351aac359e6ae3c126e2edb376929bd3b7f92d7e"},
+    {file = "numpy-1.26.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:4eb8df4bf8d3d90d091e0146f6c28492b0be84da3e409ebef54349f71ed271ef"},
+    {file = "numpy-1.26.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1a13860fdcd95de7cf58bd6f8bc5a5ef81c0b0625eb2c9a783948847abbef2c2"},
+    {file = "numpy-1.26.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:64308ebc366a8ed63fd0bf426b6a9468060962f1a4339ab1074c228fa6ade8e3"},
+    {file = "numpy-1.26.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:baf8aab04a2c0e859da118f0b38617e5ee65d75b83795055fb66c0d5e9e9b818"},
+    {file = "numpy-1.26.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:d73a3abcac238250091b11caef9ad12413dab01669511779bc9b29261dd50210"},
+    {file = "numpy-1.26.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:b361d369fc7e5e1714cf827b731ca32bff8d411212fccd29ad98ad622449cc36"},
+    {file = "numpy-1.26.2-cp39-cp39-win32.whl", hash = "sha256:bd3f0091e845164a20bd5a326860c840fe2af79fa12e0469a12768a3ec578d80"},
+    {file = "numpy-1.26.2-cp39-cp39-win_amd64.whl", hash = "sha256:2beef57fb031dcc0dc8fa4fe297a742027b954949cabb52a2a376c144e5e6060"},
+    {file = "numpy-1.26.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:1cc3d5029a30fb5f06704ad6b23b35e11309491c999838c31f124fee32107c79"},
+    {file = "numpy-1.26.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:94cc3c222bb9fb5a12e334d0479b97bb2df446fbe622b470928f5284ffca3f8d"},
+    {file = "numpy-1.26.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:fe6b44fb8fcdf7eda4ef4461b97b3f63c466b27ab151bec2366db8b197387841"},
+    {file = "numpy-1.26.2.tar.gz", hash = "sha256:f65738447676ab5777f11e6bbbdb8ce11b785e105f690bc45966574816b6d3ea"},
+]
+
 [[package]]
 name = "packaging"
 version = "23.2"
@@ -751,6 +796,20 @@ tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
 [package.extras]
 testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
+[[package]]
+name = "python-dotenv"
+version = "1.0.0"
+description = "Read key-value pairs from a .env file and set them as environment variables"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "python-dotenv-1.0.0.tar.gz", hash = "sha256:a8df96034aae6d2d50a4ebe8216326c61c3eb64836776504fcca410e5937a3ba"},
+    {file = "python_dotenv-1.0.0-py3-none-any.whl", hash = "sha256:f5971a9226b701070a4bf2c38c89e5a3f0d64de8debda981d1db98583009122a"},
+]
+
+[package.extras]
+cli = ["click (>=5.0)"]
+
 [[package]]
 name = "requests"
 version = "2.31.0"
@@ -865,6 +924,26 @@ files = [
     {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
 ]
 
+[[package]]
+name = "trimesh"
+version = "4.0.4"
+description = "Import, export, process, analyze and view triangular meshes."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "trimesh-4.0.4-py3-none-any.whl", hash = "sha256:a7149aac5609df7e1da3bf6f40c1ced5b44c2084eec3b14ef982c926045ba7e9"},
+    {file = "trimesh-4.0.4.tar.gz", hash = "sha256:dd7a67706e8848a414fa1a89a6f724f36b3405882f6293469f7cdc756901e4fb"},
+]
+
+[package.dependencies]
+numpy = "*"
+
+[package.extras]
+all = ["trimesh[easy,recommend,test]"]
+easy = ["chardet", "colorlog", "embreex", "jsonschema", "lxml", "mapbox-earcut", "networkx", "pillow", "pycollada", "requests", "rtree", "scipy", "setuptools", "shapely", "svg.path", "xxhash"]
+recommend = ["glooey", "manifold3d", "meshio", "psutil", "pyglet (<2)", "python-fcl", "scikit-image", "sympy", "vhacdx", "xatlas"]
+test = ["black", "coveralls", "ezdxf", "matplotlib", "mypy", "pyinstrument", "pymeshlab", "pytest", "pytest-cov", "ruff"]
+
 [[package]]
 name = "typing-extensions"
 version = "4.8.0"
@@ -1209,4 +1288,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "4fdcfbc4093906ea3530e143e5a06e9f323fda77d7685503cd2e545528063c2a"
+content-hash = "e4e56818583a9f0fad2adbfbc4dcb2ebaa1fc8f917004477f0e1574237b7850a"

pyproject.toml

@@ -8,12 +8,14 @@ readme = "README.md"
 [tool.poetry.dependencies]
 python = "^3.10"
 specklepy = "2.17.11"
+trimesh = "^4.0.4"
+pytest = "^7.4.2"
+python-dotenv = "^1.0.0"
 
 [tool.poetry.group.dev.dependencies]
 black = "^23.3.0"
 mypy = "^1.3.0"
 ruff = "^0.0.271"
-pytest = "^7.4.2"
 
 [build-system]
 requires = ["poetry-core"]
@@ -21,11 +23,11 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.ruff]
 select = [
-  "E",   # pycodestyle
-  "F",   # pyflakes
-  "UP",  # pyupgrade
-  "D",   # pydocstyle
-  "I",   # isort
+    "E", # pycodestyle
+    "F", # pyflakes
+    "UP", # pyupgrade
+    "D", # pydocstyle
+    "I", # isort
 ]
 
 [tool.ruff.pydocstyle]

requirements.txt

@@ -206,6 +206,32 @@ multidict==6.0.4 ; python_version >= "3.10" and python_version < "4.0" \
     --hash=sha256:f70b98cd94886b49d91170ef23ec5c0e8ebb6f242d734ed7ed677b24d50c82cf \
     --hash=sha256:fc35cb4676846ef752816d5be2193a1e8367b4c1397b74a565a9d0389c433a1d \
     --hash=sha256:ff959bee35038c4624250473988b24f846cbeb2c6639de3602c073f10410ceba
+numpy==1.25.2 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:0d60fbae8e0019865fc4784745814cff1c421df5afee233db6d88ab4f14655a2 \
+    --hash=sha256:1a1329e26f46230bf77b02cc19e900db9b52f398d6722ca853349a782d4cff55 \
+    --hash=sha256:1b9735c27cea5d995496f46a8b1cd7b408b3f34b6d50459d9ac8fe3a20cc17bf \
+    --hash=sha256:2792d23d62ec51e50ce4d4b7d73de8f67a2fd3ea710dcbc8563a51a03fb07b01 \
+    --hash=sha256:3e0746410e73384e70d286f93abf2520035250aad8c5714240b0492a7302fdca \
+    --hash=sha256:4c3abc71e8b6edba80a01a52e66d83c5d14433cbcd26a40c329ec7ed09f37901 \
+    --hash=sha256:5883c06bb92f2e6c8181df7b39971a5fb436288db58b5a1c3967702d4278691d \
+    --hash=sha256:5c97325a0ba6f9d041feb9390924614b60b99209a71a69c876f71052521d42a4 \
+    --hash=sha256:60e7f0f7f6d0eee8364b9a6304c2845b9c491ac706048c7e8cf47b83123b8dbf \
+    --hash=sha256:76b4115d42a7dfc5d485d358728cdd8719be33cc5ec6ec08632a5d6fca2ed380 \
+    --hash=sha256:7dc869c0c75988e1c693d0e2d5b26034644399dd929bc049db55395b1379e044 \
+    --hash=sha256:834b386f2b8210dca38c71a6e0f4fd6922f7d3fcff935dbe3a570945acb1b545 \
+    --hash=sha256:8b77775f4b7df768967a7c8b3567e309f617dd5e99aeb886fa14dc1a0791141f \
+    --hash=sha256:90319e4f002795ccfc9050110bbbaa16c944b1c37c0baeea43c5fb881693ae1f \
+    --hash=sha256:b79e513d7aac42ae918db3ad1341a015488530d0bb2a6abcbdd10a3a829ccfd3 \
+    --hash=sha256:bb33d5a1cf360304754913a350edda36d5b8c5331a8237268c48f91253c3a364 \
+    --hash=sha256:bec1e7213c7cb00d67093247f8c4db156fd03075f49876957dca4711306d39c9 \
+    --hash=sha256:c5462d19336db4560041517dbb7759c21d181a67cb01b36ca109b2ae37d32418 \
+    --hash=sha256:c5652ea24d33585ea39eb6a6a15dac87a1206a692719ff45d53c5282e66d4a8f \
+    --hash=sha256:d7806500e4f5bdd04095e849265e55de20d8cc4b661b038957354327f6d9b295 \
+    --hash=sha256:db3ccc4e37a6873045580d413fe79b68e47a681af8db2e046f1dacfa11f86eb3 \
+    --hash=sha256:dfe4a913e29b418d096e696ddd422d8a5d13ffba4ea91f9f60440a3b759b0187 \
+    --hash=sha256:eb942bfb6f84df5ce05dbf4b46673ffed0d3da59f13635ea9b926af3deb76926 \
+    --hash=sha256:f08f2e037bba04e707eebf4bc934f1972a315c883a9e0ebfa8a7756eabf9e357 \
+    --hash=sha256:fd608e19c8d7c55021dffd43bfe5492fab8cc105cc8986f813f8c3c048b38760
 pydantic-core==2.10.1 ; python_version >= "3.10" and python_version < "4.0" \
     --hash=sha256:042462d8d6ba707fd3ce9649e7bf268633a41018d6a998fb5fbacb7e928a183e \
     --hash=sha256:0523aeb76e03f753b58be33b26540880bac5aa54422e4462404c432230543f33 \
@@ -330,6 +356,9 @@ specklepy==2.17.11 ; python_version >= "3.10" and python_version < "4.0" \
     --hash=sha256:e915ec4c3862a517f417f0b764e252a6582e7ace3696938a8e5043891308a5ab
 stringcase==1.2.0 ; python_version >= "3.10" and python_version < "4.0" \
     --hash=sha256:48a06980661908efe8d9d34eab2b6c13aefa2163b3ced26972902e3bdfd87008
+trimesh==4.0.4 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:a7149aac5609df7e1da3bf6f40c1ced5b44c2084eec3b14ef982c926045ba7e9 \
+    --hash=sha256:dd7a67706e8848a414fa1a89a6f724f36b3405882f6293469f7cdc756901e4fb
 typing-extensions==4.8.0 ; python_version >= "3.10" and python_version < "4.0" \
     --hash=sha256:8f92fc8806f9a6b641eaa5318da32b44d401efaac0f6678c9bc448ba3605faa0 \
     --hash=sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef
@@ -614,3 +643,51 @@ yarl==1.9.2 ; python_version >= "3.10" and python_version < "4.0" \
     --hash=sha256:f3b078dbe227f79be488ffcfc7a9edb3409d018e0952cf13f15fd6512847f3f7 \
     --hash=sha256:f4e2d08f07a3d7d3e12549052eb5ad3eab1c349c53ac51c209a0e5991bbada78 \
     --hash=sha256:f7a3d8146575e08c29ed1cd287068e6d02f1c7bdff8970db96683b9591b86ee7
+
+yarl~=1.9.2
+gql~=3.4.1
+backoff~=2.2.1
+multidict~=6.0.4
+requests~=2.31.0
+websockets~=10.4
+pytest~=7.4.2
+h11~=0.14.0
+pip~=23.3.1
+attrs~=23.1.0
+wheel~=0.40.0
+mypy~=1.6.1
+idna~=3.4
+sniffio~=1.3.0
+black~=23.10.0
+platformdirs~=3.11.0
+packaging~=23.2
+pathspec~=0.11.2
+click~=8.1.5
+httpcore~=1.0.2
+certifi~=2023.7.22
+setuptools~=65.5.0
+numpy~=1.25.2
+pluggy~=1.3.0
+Deprecated~=1.2.14
+iniconfig~=2.0.0
+trimesh~=4.0.4
+anyio~=4.0.0
+pydantic~=2.4.2
+urllib3~=1.26.18
+specklepy~=2.17.11
+stringcase~=1.2.0
+ujson~=5.8.0
+wrapt~=1.16.0
+httpx~=0.25.1
+Pillow~=10.1.0
+docutils~=0.20.1
+sphinx~=7.0.1
+Jinja2~=3.1.2
+filelock~=3.12.2
+Pygments~=2.15.1
+pytz~=2023.3.post1
+networkx~=3.1
+scipy~=1.11.1
+psutil~=5.9.5
+python-dotenv~=1.0.0
+pymesh~=1.0.2

tests/test_main.py

@@ -23,12 +23,12 @@ def crypto_random_string(length: int) -> str:
 
 
 def register_new_automation(
-    project_id: str,
-    model_id: str,
-    speckle_client: SpeckleClient,
-    automation_id: str,
-    automation_name: str,
-    automation_revision_id: str,
+        project_id: str,
+        model_id: str,
+        speckle_client: SpeckleClient,
+        automation_id: str,
+        automation_name: str,
+        automation_revision_id: str,
 ):
     """Register a new automation in the speckle server."""
     query = gql(
@@ -103,7 +103,7 @@ def fake_automation_run_data(request, test_client: SpeckleClient) -> AutomationR
     function_name = "Clash Test"
 
     automation_id = crypto_random_string(10)
-    automation_name = "Local Test Automation"
+    automation_name = "Long running clash test"
     automation_revision_id = crypto_random_string(10)
 
     register_new_automation(
@@ -119,7 +119,7 @@ def fake_automation_run_data(request, test_client: SpeckleClient) -> AutomationR
         project_id=project_id,
         model_id=model_id,
         branch_name="main",
-        version_id="2b16327448",
+        version_id="861bbab860",
         speckle_server_url=server_url,
         # These ids would be available with a valid registered Automation definition.
         automation_id=automation_id,
@@ -142,7 +142,7 @@ def test_function_run(fake_automation_run_data: AutomationRunData, speckle_token
         context,
         automate_function,
         FunctionInputs(
-            tolerance=0.1, tolerance_unit="mm", static_model_name="structural"
+            tolerance=0.1, tolerance_unit="mm", static_model_name="structures from revit"
         ),
     )
 
@@ -156,26 +156,26 @@ def context(fake_automation_run_data: AutomationRunData, speckle_token: str):
 
 def test_non_existent_model(context, test_client: SpeckleClient):
     with pytest.raises(
-        Exception, match="The static model named does not exist, skipping the function."
+            Exception, match="The static model named does not exist, skipping the function."
     ):
         get_reference_model(context, "Fake Name")
 
 
 def test_model_with_no_versions(context, test_client: SpeckleClient):
     with pytest.raises(
-        Exception, match="The static model has no versions, skipping the function."
+            Exception, match="The static model has no versions, skipping the function."
     ):
         get_reference_model(context, "blank")
 
 
 def test_same_as_changed_model(context, test_client: SpeckleClient):
     with pytest.raises(
-        Exception,
-        match="The static model is the same as the changed model, skipping the function.",
+            Exception,
+            match="The static model is the same as the changed model, skipping the function.",
     ):
-        get_reference_model(context, "hvac")
+        get_reference_model(context, "clash simple")
 
 
 def test_valid_reference_model(context, test_client: SpeckleClient):
-    reference_model = get_reference_model(context, "structural")
+    reference_model = get_reference_model(context, "simple beams")
     assert reference_model is not None