Add missing trimesh

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.

main.py

@@ -20,7 +20,7 @@ from trimesh import Trimesh
 
 from Geometry.mesh import speckle_to_element, Element
 from Rules.checks import ElementCheckRules
-from flatten import extract_base_and_transform
+from Utilities.flatten import extract_base_and_transform
 
 
 class FunctionInputs(AutomateBase):

poetry.lock

@@ -540,6 +540,40 @@ files = [
     {file = "mypy_extensions-1.0.0.tar.gz", hash = "sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782"},
 ]
 
+[[package]]
+name = "numpy"
+version = "1.25.2"
+description = "Fundamental package for array computing in Python"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "numpy-1.25.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:db3ccc4e37a6873045580d413fe79b68e47a681af8db2e046f1dacfa11f86eb3"},
+    {file = "numpy-1.25.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:90319e4f002795ccfc9050110bbbaa16c944b1c37c0baeea43c5fb881693ae1f"},
+    {file = "numpy-1.25.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dfe4a913e29b418d096e696ddd422d8a5d13ffba4ea91f9f60440a3b759b0187"},
+    {file = "numpy-1.25.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f08f2e037bba04e707eebf4bc934f1972a315c883a9e0ebfa8a7756eabf9e357"},
+    {file = "numpy-1.25.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:bec1e7213c7cb00d67093247f8c4db156fd03075f49876957dca4711306d39c9"},
+    {file = "numpy-1.25.2-cp310-cp310-win32.whl", hash = "sha256:7dc869c0c75988e1c693d0e2d5b26034644399dd929bc049db55395b1379e044"},
+    {file = "numpy-1.25.2-cp310-cp310-win_amd64.whl", hash = "sha256:834b386f2b8210dca38c71a6e0f4fd6922f7d3fcff935dbe3a570945acb1b545"},
+    {file = "numpy-1.25.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c5462d19336db4560041517dbb7759c21d181a67cb01b36ca109b2ae37d32418"},
+    {file = "numpy-1.25.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c5652ea24d33585ea39eb6a6a15dac87a1206a692719ff45d53c5282e66d4a8f"},
+    {file = "numpy-1.25.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0d60fbae8e0019865fc4784745814cff1c421df5afee233db6d88ab4f14655a2"},
+    {file = "numpy-1.25.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:60e7f0f7f6d0eee8364b9a6304c2845b9c491ac706048c7e8cf47b83123b8dbf"},
+    {file = "numpy-1.25.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:bb33d5a1cf360304754913a350edda36d5b8c5331a8237268c48f91253c3a364"},
+    {file = "numpy-1.25.2-cp311-cp311-win32.whl", hash = "sha256:5883c06bb92f2e6c8181df7b39971a5fb436288db58b5a1c3967702d4278691d"},
+    {file = "numpy-1.25.2-cp311-cp311-win_amd64.whl", hash = "sha256:5c97325a0ba6f9d041feb9390924614b60b99209a71a69c876f71052521d42a4"},
+    {file = "numpy-1.25.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:b79e513d7aac42ae918db3ad1341a015488530d0bb2a6abcbdd10a3a829ccfd3"},
+    {file = "numpy-1.25.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:eb942bfb6f84df5ce05dbf4b46673ffed0d3da59f13635ea9b926af3deb76926"},
+    {file = "numpy-1.25.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3e0746410e73384e70d286f93abf2520035250aad8c5714240b0492a7302fdca"},
+    {file = "numpy-1.25.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d7806500e4f5bdd04095e849265e55de20d8cc4b661b038957354327f6d9b295"},
+    {file = "numpy-1.25.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:8b77775f4b7df768967a7c8b3567e309f617dd5e99aeb886fa14dc1a0791141f"},
+    {file = "numpy-1.25.2-cp39-cp39-win32.whl", hash = "sha256:2792d23d62ec51e50ce4d4b7d73de8f67a2fd3ea710dcbc8563a51a03fb07b01"},
+    {file = "numpy-1.25.2-cp39-cp39-win_amd64.whl", hash = "sha256:76b4115d42a7dfc5d485d358728cdd8719be33cc5ec6ec08632a5d6fca2ed380"},
+    {file = "numpy-1.25.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:1a1329e26f46230bf77b02cc19e900db9b52f398d6722ca853349a782d4cff55"},
+    {file = "numpy-1.25.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c3abc71e8b6edba80a01a52e66d83c5d14433cbcd26a40c329ec7ed09f37901"},
+    {file = "numpy-1.25.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:1b9735c27cea5d995496f46a8b1cd7b408b3f34b6d50459d9ac8fe3a20cc17bf"},
+    {file = "numpy-1.25.2.tar.gz", hash = "sha256:fd608e19c8d7c55021dffd43bfe5492fab8cc105cc8986f813f8c3c048b38760"},
+]
+
 [[package]]
 name = "packaging"
 version = "23.2"
@@ -865,6 +899,26 @@ 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 +1263,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "4fdcfbc4093906ea3530e143e5a06e9f323fda77d7685503cd2e545528063c2a"
+content-hash = "3abedc1c21df21ba5ab28f1ea6dc49c8a84c768e0f8f155e5c619ca3fd023765"

pyproject.toml

@@ -8,6 +8,7 @@ readme = "README.md"
 [tool.poetry.dependencies]
 python = "^3.10"
 specklepy = "2.17.11"
+trimesh = "^4.0.4"
 
 [tool.poetry.group.dev.dependencies]
 black = "^23.3.0"

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