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SFBC_dataset_II

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  1. .gitattributes +1 -0
  2. README.md +22 -0
  3. dataset/test/generative - 2023-03-13_10-01-01.hdf5 +3 -0
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  18. dataset/test/generative - 2023-03-13_10-39-18.hdf5 +3 -0
  19. dataset/train/generative - 2023-03-22_14-22-55.hdf5 +3 -0
  20. dataset/train/generative - 2023-03-22_14-25-43.hdf5 +3 -0
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  46. dataset/train/generative - 2023-03-22_15-36-34.hdf5 +3 -0
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.gitattributes CHANGED
@@ -34,6 +34,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
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  # Audio files - uncompressed
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  *.pcm filter=lfs diff=lfs merge=lfs -text
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  *.sam filter=lfs diff=lfs merge=lfs -text
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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  # Audio files - uncompressed
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README.md CHANGED
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  ---
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  license: mit
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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  ---
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+
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+ # Symmetric basis convolutions for learning lagrangian fluid mechanics (Published at ICLR 2024) - Test Case I
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+
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+ This dataset contains the data for the first test case (1D compressible SPH) for the paper Symmetric basis convolutions for learning lagrangian fluid mechanics (Published at ICLR 2024).
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+
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+ You can find the full paper [here](https://arxiv.org/abs/2403.16680).
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+
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+ The source core repository is available [here](https://github.com/tum-pbs/SFBC/) and also contains information on the data generation
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+
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+ For the other test case datasets look here:
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+
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+ [Test Case I (compressible 1D)](https://huggingface.co/datasets/Wi-Re/SFBC_dataset_i)
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+
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+ [Test Case II (wcsph 2D)](https://huggingface.co/datasets/Wi-Re/SFBC_dataset_ii)
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+
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+ [Test Case III (isph 2D)](https://huggingface.co/datasets/Wi-Re/SFBC_dataset_iii)
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+
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+ [Test Case IV (3D)](https://huggingface.co/datasets/Wi-Re/SFBC_dataset_iv)
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+
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+ ## File Layout
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+
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+ The datasets are stored as hdf5 files with a single file per experiment. Within each file there is a set of configuration parameters and each frame of the simulation stored separately as a group. Each frame contains information for all fluid particles and all potentially relevant information. For the 2D test cases there is a pre-defined test/train split on a simulation level, wheras the 1D and 3D cases do not contain such a split.
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