| | --- |
| | pretty_name: CoolData - A 3d Industrial-Grade Flow Field Dataset for Electronics Cooling |
| | size_categories: |
| | - 10K<n<100K |
| | license: cc-by-nc-4.0 |
| | --- |
| | # Cooldata - A Large-Scale Electronics Cooling 3D Flow Field Dataset |
| |
|
| | Cooldata is a large-scale electronics cooling dataset, containing over 60k stationary 3D flow fields for a diverse set of geometries, simulated with the commercial solver Simcenter STAR-CCM+. This library can be used to acccess the dataset and streamline its application in machine learning tasks. |
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| |  |
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| | Find the documentation at [cooldata.readthedocs.io](https://cooldata.readthedocs.io/). |
| |
|
| | ## Features |
| |
|
| | - **Data Storage:** Organized in folders containing `.cgns` files for compatibility with computational fluid dynamics tools. |
| | - **PyVista Integration:** Access to dataset samples as PyVista objects for easy 3D visualization and manipulation. |
| | - **Graph Neural Network Support:** |
| | - **DGL Support:** |
| | - Surface and volume data in mesh format. |
| | - 3D visualization of samples and predictions. |
| | - L2 loss computation and aggregate force evaluation for model training. |
| | - **PyG Support:** Implementing functionalities similar to DGL. |
| | - **Hugging Face Integration:** Direct dataset loading from [Hugging Face](https://huggingface.co/). |
| | - **Voxelized Flow Field Support:** Facilitates image processing-based ML approaches. |
| | - **Comprehensive Metadata Accessibility:** All metadata is accessible through the library. |
| |
|
| | ## Installation |
| |
|
| | Run |
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|
| | ```bash |
| | pip install cooldata |
| | ``` |
| |
|
| | If you want to use the DGL support, you also need to install the [DGL](https://www.dgl.ai/) library, as documented [here](https://www.dgl.ai/pages/start.html). |
