/PNCG_IPC

The source code of our paper PNCG.

Primary LanguagePython

This repository hosts the official implementation of the paper Preconditioned Nonlinear Conjugate Gradient Method for Real-time Interior-point Hyperelasticity.

Run demo

Requirements： pip install -r requirements.txt

Run：

cd PNCG_IPC/demo
python cubic_demos

Project Structure

The repository is organized as follows:

  • algorithm/: Contains core algorithms, infrastructure, and functions critical to our method. The workflow starts with base_deformer, progresses through collision_detection_v2, and finally integrates within pncg_base_ipc.

  • demo/: A collection of demonstrations showcasing the capabilities and performance of our method.

  • util/model_loading: Contains code for loading models necessary for our demonstrations and tests.

  • math_utils/: Hosts essential utility functions for elastic deformations, primarily within elastic_util.py and matrix_util.py.

  • model/: Stores model files utilized in the demonstrations and testing phases.

Note

  • The newest version of Numpy may cause Core Dumped, I don't figure out why it happens. It seems to due to the version difference of meshtaichi package and Numpy. Older version such as numpy1.26, is fine.
  • When using MeshTaichi to load a model, the xxxx.face file is necessary, while the face information is not required. So some .face files contain just one face. Or You can just delete following code in __init__.py in meshtaichi_patcher
        ans["face"] = read_tetgen(f'{base_name}.face')[0].reshape(-1, 3)
  • Please run in linux system, the performance of our code in windows is worse than linux.
  • Feel free to contact me at shenxing03@corp.netease.com / shenxingsx@zju.edu.cn or create a Github issue if you have questions regarding setting up the repository, running examples or adding new examples.
  • A introduction of our paper can be found at others/Paper介绍.pdf.

Citation

Please consider citing our paper if your find our research or this codebase helpful:

@inproceedings{10.1145/3641519.3657490,
author = {Shen, Xing and Cai, Runyuan and Bi, Mengxiao and Lv, Tangjie},
title = {Preconditioned Nonlinear Conjugate Gradient Method for Real-time Interior-point Hyperelasticity},
year = {2024},
isbn = {9798400705250},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3641519.3657490},
doi = {10.1145/3641519.3657490},
booktitle = {ACM SIGGRAPH 2024 Conference Papers},
articleno = {96},
numpages = {11},
keywords = {GPU, Nonlinear conjugate gradient method, Physics-based simulation},
location = {Denver, CO, USA},
series = {SIGGRAPH '24}
}