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README.md

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 ---
+license: cc-by-sa-4.0
+size_categories:
+- n<1K
+task_categories:
+- graph-ml
+pretty_name: 2D external aero CFD RANS datasets, under geometrical variations
+tags:
+- physics learning
+- geometry learning
+configs:
+- config_name: default
+  data_files:
+  - split: all_samples
+    path: data/all_samples-*
 dataset_info:
+  description:
+    legal:
+      owner: Safran
+      license: CC-by-SA 4.0
+    data_production:
+      type: simulation
+      physics: 2D stationary RANS
+      simulator: elsA
+    split:
+      train:
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+      test:
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+    task: regression
+    in_scalars_names: []
+    out_scalars_names: []
+    in_timeseries_names: []
+    out_timeseries_names: []
+    in_fields_names: []
+    out_fields_names:
+    - Mach
+    - Pressure
+    - Velocity-x
+    - Velocity-y
+    in_meshes_names:
+    - /Base_2_2/Zone
+    out_meshes_names: []
   features:
   - name: sample
     dtype: binary
@@ -9,9 +448,67 @@ dataset_info:
     num_examples: 400
   download_size: 813895818
   dataset_size: 1290091704
-configs:
-- config_name: default
-  data_files:
-  - split: all_samples
-    path: data/all_samples-*
 ---
+
+# Dataset Card
+![image/png](https://i.ibb.co/fd5njm16/2-D-profile.png)
+
+This dataset contains a single huggingface split, named 'all_samples'.
+
+The samples contains a single huggingface feature, named called "sample".
+
+Samples are instances of [plaid.containers.sample.Sample](https://plaid-lib.readthedocs.io/en/latest/autoapi/plaid/containers/sample/index.html#plaid.containers.sample.Sample).
+Mesh objects included in samples follow the [CGNS](https://cgns.github.io/) standard, and can be converted in
+[Muscat.Containers.Mesh.Mesh](https://muscat.readthedocs.io/en/latest/_source/Muscat.Containers.Mesh.html#Muscat.Containers.Mesh.Mesh).
+
+
+Example of commands:
+```python
+import pickle
+from datasets import load_dataset
+from plaid.containers.sample import Sample
+
+# Load the dataset
+dataset = load_dataset("chanel/dataset", split="all_samples")
+
+# Get the first sample of the first split
+split_names = list(dataset.description["split"].keys())
+ids_split_0 = dataset.description["split"][split_names[0]]
+sample_0_split_0 = dataset[ids_split_0[0]]["sample"]
+plaid_sample = Sample.model_validate(pickle.loads(sample_0_split_0))
+print("type(plaid_sample) =", type(plaid_sample))
+
+print("plaid_sample =", plaid_sample)
+
+# Get a field from the sample
+field_names = plaid_sample.get_field_names()
+field = plaid_sample.get_field(field_names[0])
+print("field_names[0] =", field_names[0])
+
+print("field.shape =", field.shape)
+
+# Get the mesh and convert it to Muscat
+from Muscat.Bridges import CGNSBridge
+CGNS_tree = plaid_sample.get_mesh()
+mesh = CGNSBridge.CGNSToMesh(CGNS_tree)
+print(mesh)
+```
+
+## Dataset Details
+
+### Dataset Description
+
+
+This dataset contains 2D external aero CFD RANS solutions, under geometrical variations (correspond to "large" in the Zenodo repository).
+
+The variablity in the samples is the geometry (mesh). Outputs of interest are 4 fields. Each sample have been computed on large refined meshes, which have been cut close to the profil, and adapted (remeshed) using an anisotropic metric based on the output fields of interest.
+
+Dataset created using the [PLAID](https://plaid-lib.readthedocs.io/) library and datamodel, version 0.1.
+    
+- **Language:** [PLAID](https://plaid-lib.readthedocs.io/)
+- **License:** cc-by-sa-4.0
+- **Owner:** Safran
+
+### Dataset Sources
+
+- **Repository:** [Zenodo](https://zenodo.org/records/14840426)