Initial Dataset commit

.gitattributes

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README.md

@@ -1,3 +1,25 @@
 ---
 license: mit
 ---
+
+# Symmetric basis convolutions for learning lagrangian fluid mechanics (Published at ICLR 2024) - Test Case I
+
+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). 
+
+You can find the full paper [here](https://arxiv.org/abs/2403.16680). 
+
+The source core repository is available [here](https://github.com/tum-pbs/SFBC/) and also contains information on the data generation
+
+For the other test case datasets look here:
+
+[Test Case I (compressible 1D)](https://huggingface.co/datasets/Wi-Re/SFBC_dataset_i)
+
+[Test Case II (wcsph 2D)](https://huggingface.co/datasets/Wi-Re/SFBC_dataset_ii)
+
+[Test Case III (isph 2D)](https://huggingface.co/datasets/Wi-Re/SFBC_dataset_iii)
+
+[Test Case IV (3D)](https://huggingface.co/datasets/Wi-Re/SFBC_dataset_iv)
+
+## File Layout
+
+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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