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Differentiable geometry representations for shape parameterization and optimization.

Project description

Differentiable geometry representations for shape parameterization and optimization.

Project Plan

Stage 1: Initial Setup

  • Add Github Actions workflow for Github Pages.
  • Create first cut User Docs using Jupyter Books and MyST markdown.
    • What is this package for?
    • Add .gitignore for MyST markdown.
  • Launch Github Discussions for the project.
    • Create introductory dicussion post.
  • Add MIT License.
  • Update pyproject.toml.
    • Maintainers, license, license-file, keywords, classifiers, project urls.
  • Add Github Actions workflow for Github Release and PyPI publishing.
  • Add CHANGELOG.md to maintain release details.
  • Create first tag and push it to initiate first release and publish.

Stage 2: Implement Geometry Representations

  • Install necessary dependencies
    • numpy, matplotlib and pytorch.
  • Implement loss functions.
    • Start with Chamfer loss.
  • Hicks-Henne bump functions.
    • Implement the Hicks-Henne class.
    • Add visualization method.
    • Add type hints and docstrings.
    • Add test script.
    • Add documentation.
    • Merge with main branch.
    • Create a tag and push it to create a release.
  • CST parameterization.
    • Implement the CST class.
    • Add visualization method.
    • Add type hints and docstrings.
    • Add test script.
    • Add documentation.
    • Merge with main branch.
    • Create a tag and push it to create a release.
  • NICE normalizing flow parameterization.
    • Implement the NICE class.
    • Add visualization method.
    • Add type hints and docstrings.
    • Add test script.
    • Add documentation.
    • Merge with main branch.
    • Create a tag and push it to create a release.
  • RealNVP normalizing flow parameterization.
    • Implement the RealNVP class.
    • Add visualization method.
    • Add type hints and docstrings.
    • Add test script.
    • Add documentation.
    • Merge with main branch.
    • Create a tag and push it to create a release.
  • NIGnet parameterization.
    • Implement the NIGnet class.
    • Add visualization method.
    • Add type hints and docstrings.
    • Add test script.
    • Add documentation.
    • Merge with main branch.
    • Create a tag and push it to create a release.
  • NeuralODE parameterization.
    • Implement the NeuralODE class.
    • Add visualization method.
    • Add type hints and docstrings.
    • Add test script.
    • Add documentation.
    • Merge with main branch.
    • Create a tag and push it to create a release.

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