commit files to HF hub

metadata.json

@@ -1,6 +1,7 @@
 {
     "1": {
         "streamlines_mesh.ply": "data/1/streamlines_mesh.ply",
+        "input.json": "data/1/input.json",
         "coeff.json": "data/1/coeff.json",
         "openfoam_mesh.obj": "data/1/openfoam_mesh.obj",
         "pressure_field_mesh.vtk": "data/1/pressure_field_mesh.vtk",
@@ -8,6 +9,7 @@
     },
     "2": {
         "streamlines_mesh.ply": "data/2/streamlines_mesh.ply",
+        "input.json": "data/2/input.json",
         "coeff.json": "data/2/coeff.json",
         "openfoam_mesh.obj": "data/2/openfoam_mesh.obj",
         "pressure_field_mesh.vtk": "data/2/pressure_field_mesh.vtk",

windtunnel_dataset.py → windtunnel.py

@@ -2,6 +2,7 @@ import json
 import os
 import datasets
 
+
 class WindtunnelDataset(datasets.GeneratorBasedBuilder):
     """Dataset for loading simulation data with JSON and mesh files"""
 
@@ -10,7 +11,7 @@ class WindtunnelDataset(datasets.GeneratorBasedBuilder):
             features=datasets.Features(
                 {
                     "coeff": datasets.Value("dict"),  # JSON file as a dictionary
-                    # 'input': datasets.Value('dict'),                # JSON file as a dictionary
+                    "input": datasets.Value("dict"),  # JSON file as a dictionary
                     "input_mesh": datasets.Value("binary"),  # OBJ mesh file as binary
                     "openfoam_mesh": datasets.Value(
                         "binary"
@@ -25,17 +26,26 @@ class WindtunnelDataset(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """Define the splits for the dataset."""
-        metadata_path = os.path.join(self.config.data_dir, 'metadata.json')
-        with open(metadata_path, 'r') as f:
+        metadata_path = os.path.join(self.config.data_dir, "metadata.json")
+        with open(metadata_path, "r") as f:
             metadata = json.load(f)
 
         # Split the dataset into train, validation, and test
         train_ids, val_ids, test_ids = self._train_val_test_split(metadata)
 
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'metadata': {id: metadata[id] for id in train_ids}}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={'metadata': {id: metadata[id] for id in val_ids}}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={'metadata': {id: metadata[id] for id in test_ids}}),
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"metadata": {id: metadata[id] for id in train_ids}},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"metadata": {id: metadata[id] for id in val_ids}},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"metadata": {id: metadata[id] for id in test_ids}},
+            ),
         ]
 
     def _generate_examples(self, metadata):
@@ -45,7 +55,7 @@ class WindtunnelDataset(datasets.GeneratorBasedBuilder):
                 sim_id,
                 {
                     "coeff": self._load_json(files["coeff"]),
-                    # 'input': self._load_json(files['input']),
+                    "input": self._load_json(files["input"]),
                     "input_mesh": self._load_binary(
                         os.path.join(self.config.data_dir, sim_id, "input_mesh.obj")
                     ),
@@ -67,18 +77,18 @@ class WindtunnelDataset(datasets.GeneratorBasedBuilder):
 
     def _load_json(self, file_path):
         """Load a JSON file and return it as a dictionary."""
-        with open(file_path, 'r') as f:
+        with open(file_path, "r") as f:
             return json.load(f)
 
     def _load_binary(self, file_path):
         """Load a binary file and return its contents."""
-        with open(file_path, 'rb') as f:
+        with open(file_path, "rb") as f:
             return f.read()
 
     def _train_val_test_split(self, metadata):
         """Implement logic for splitting metadata into train, validation, and test sets."""
         keys = list(metadata.keys())
-        train_ids = keys[:int(0.7 * len(keys))]
-        val_ids = keys[int(0.7 * len(keys)):int(0.85 * len(keys))]
-        test_ids = keys[int(0.85 * len(keys)):]
+        train_ids = keys[: int(0.7 * len(keys))]
+        val_ids = keys[int(0.7 * len(keys)) : int(0.85 * len(keys))]
+        test_ids = keys[int(0.85 * len(keys)) :]
         return train_ids, val_ids, test_ids