Update BubbleML_2.py

BubbleML_2.py

@@ -11,7 +11,6 @@ from datasets import (
     GeneratorBasedBuilder,
     DatasetInfo,
     Features,
-    Array3D,
     Sequence,
     Value,
     Split,
@@ -20,115 +19,142 @@ from datasets import (
 
 _CITATION = ""  # optional
 _DESCRIPTION = """
-BubbleML: high-fidelity single-bubble boiling simulations (FC72 & R515B).
-Pre-defined train/test splits across two directories.
+BubbleML: high-fidelity boiling simulations for 3 Liquids- (FC72 & R515B & LN2)
+and Flow Boiling Regimes.
+Pre-defined train/test splits across all benchmarks.
 """
 
 class BubbleMLConfig(BuilderConfig):
     """BuilderConfig for BubbleML_2."""
     def __init__(
         self,
-        subset_dirs,
-        train_files_dict,
-        test_files_dict,
+        *,
+        name: str,
+        description: str,
+        data_files: dict,
+        data_dir: str = "",
         version: Version = Version("1.0.0"),
         **kwargs,
     ):
-        super().__init__(name=kwargs.pop("name"), version=version, description=kwargs.pop("description"), **kwargs)
-        self.subset_dirs = subset_dirs
-        self.train_files_dict = train_files_dict
-        self.test_files_dict = test_files_dict
+        super().__init__(name=name, version=version, description=description, **kwargs)
+        self.data_files = data_files
+        self.data_dir = data_dir
 
 class BubbleMLDataset(GeneratorBasedBuilder):
     """BubbleML_2: combined single-bubble dataset."""
-    
     BUILDER_CONFIG_CLASS = BubbleMLConfig
+    DEFAULT_CONFIG_NAME = "single-bubble"
     BUILDER_CONFIGS = [
         BubbleMLConfig(
             name="single-bubble",
             description="Single-bubble (FC72 & R515B) train/test split",
-            subset_dirs=[
-                "SingleBubble-Saturated-FC72-2D",
-                "SingleBubble-Saturated-R515B-2D",
-            ],
-            train_files_dict={
-                "SingleBubble-Saturated-FC72-2D": [
-                    "Twall_90.hdf5","Twall_91.hdf5","Twall_92.hdf5","Twall_94.hdf5",
-                    "Twall_96.hdf5","Twall_98.hdf5","Twall_99.hdf5","Twall_100.hdf5",
+            data_dir="",  # repo root when loading remotely; overridden by --data_dir in CLI
+            data_files={
+                "train": [
+                    # FC72 train
+                    "SingleBubble-Saturated-FC72-2D/Twall_90.hdf5",
+                    "SingleBubble-Saturated-FC72-2D/Twall_91.hdf5",
+                    "SingleBubble-Saturated-FC72-2D/Twall_92.hdf5",
+                    "SingleBubble-Saturated-FC72-2D/Twall_94.hdf5",
+                    "SingleBubble-Saturated-FC72-2D/Twall_96.hdf5",
+                    "SingleBubble-Saturated-FC72-2D/Twall_98.hdf5",
+                    "SingleBubble-Saturated-FC72-2D/Twall_99.hdf5",
+                    "SingleBubble-Saturated-FC72-2D/Twall_100.hdf5",
+                    # R515B train
+                    "SingleBubble-Saturated-R515B-2D/Twall_13.hdf5",
+                    "SingleBubble-Saturated-R515B-2D/Twall_14.hdf5",
+                    "SingleBubble-Saturated-R515B-2D/Twall_15.hdf5",
+                    "SingleBubble-Saturated-R515B-2D/Twall_17.hdf5",
+                    "SingleBubble-Saturated-R515B-2D/Twall_19.hdf5",
+                    "SingleBubble-Saturated-R515B-2D/Twall_21.hdf5",
+                    "SingleBubble-Saturated-R515B-2D/Twall_22.hdf5",
+                    "SingleBubble-Saturated-R515B-2D/Twall_23.hdf5",
                 ],
-                "SingleBubble-Saturated-R515B-2D": [
-                    "Twall_13.hdf5","Twall_14.hdf5","Twall_15.hdf5","Twall_17.hdf5",
-                    "Twall_19.hdf5","Twall_21.hdf5","Twall_22.hdf5","Twall_23.hdf5",
+                "test": [
+                    # FC72 test
+                    "SingleBubble-Saturated-FC72-2D/Twall_87.hdf5",
+                    "SingleBubble-Saturated-FC72-2D/Twall_95.hdf5",
+                    "SingleBubble-Saturated-FC72-2D/Twall_103.hdf5",
+                    # R515B test
+                    "SingleBubble-Saturated-R515B-2D/Twall_10.hdf5",
+                    "SingleBubble-Saturated-R515B-2D/Twall_18.hdf5",
+                    "SingleBubble-Saturated-R515B-2D/Twall_26.hdf5",
                 ],
             },
-            test_files_dict={
-                "SingleBubble-Saturated-FC72-2D": ["Twall_87.hdf5","Twall_95.hdf5","Twall_103.hdf5"],
-                "SingleBubble-Saturated-R515B-2D": ["Twall_10.hdf5","Twall_18.hdf5","Twall_26.hdf5"],
-            },
         ),
     ]
-    DEFAULT_CONFIG_NAME = "single-bubble"
 
     def _info(self) -> DatasetInfo:
+        # Nested Sequence to represent 4D arrays (time, channel, H, W) of floats
+        features = Features({
+            "input": Sequence(Sequence(Sequence(Sequence(Value("float32"))))),
+            "output": Sequence(Sequence(Sequence(Sequence(Value("float32"))))),
+            "fluid_params": Sequence(Value("float32")),
+            "filename": Value("string"),
+        })
         return DatasetInfo(
             description=_DESCRIPTION,
-            features=Features({
-                "input": Array3D(shape=(5, 4, None, None), dtype="float32"),
-                "output": Array3D(shape=(5, 4, None, None), dtype="float32"),
-                "fluid_params": Sequence(Value("float32")),
-                "filename": Value("string"),
-            }),
+            features=features,
             supervised_keys=None,
             homepage="https://huggingface.co/datasets/hpcforge/BubbleML_2",
             citation=_CITATION,
         )
 
     def _split_generators(self, dl_manager: datasets.DownloadManager):
-        # data already lives in the repo
-        base_dir = os.path.dirname(os.path.abspath(__file__))
-
-        cfg = self.config
-
-        def resolve(files_dict):
-            paths = []
-            for subdir, flist in files_dict.items():
-                subdir_path = os.path.join(base_dir, subdir)
-                for fname in flist:
-                    full = os.path.join(subdir_path, fname)
-                    if not os.path.isfile(full):
-                        raise FileNotFoundError(f"Could not find {full}")
-                    paths.append(full)
-            return paths
+        base_dir = (
+            self.config.data_dir
+            if self.config.data_dir
+            else os.path.dirname(os.path.abspath(__file__))
+        )
 
-        train_files = resolve(cfg.train_files_dict)
-        test_files  = resolve(cfg.test_files_dict)
+        def resolve(split_name: str):
+            out = []
+            for rel in self.config.data_files[split_name]:
+                full = os.path.join(base_dir, rel)
+                if not os.path.isfile(full):
+                    raise FileNotFoundError(f"Expected data file at {full}, but not found.")
+                out.append(full)
+            return out
 
         return [
-            datasets.SplitGenerator(name=Split.TRAIN, gen_kwargs={"files": train_files}),
-            datasets.SplitGenerator(name=Split.TEST,  gen_kwargs={"files": test_files}),
+            datasets.SplitGenerator(
+                name=Split.TRAIN, gen_kwargs={"files": resolve("train")}
+            ),
+            datasets.SplitGenerator(
+                name=Split.TEST, gen_kwargs={"files": resolve("test")}
+            ),
         ]
 
     def _generate_examples(self, files):
+        """Yield examples as dicts with input, output, fluid_params, filename."""
         for idx, path in enumerate(files):
+            # Load HDF5 arrays
             with h5py.File(path, "r") as h5f:
-                inp = np.stack([h5f[k][:5] for k in ["dfun","temperature","velx","vely"]])
-                out = np.stack([h5f[k][5:10] for k in ["dfun","temperature","velx","vely"]])
-            # metadata
+                inp = np.stack([h5f[k][:5] for k in ["dfun", "temperature", "velx", "vely"]])
+                out = np.stack([h5f[k][5:10] for k in ["dfun", "temperature", "velx", "vely"]])
+
+            # Load metadata JSON
             meta_path = path.replace(".hdf5", ".json")
-            if os.path.exists(meta_path):
-                with open(meta_path) as jf:
+            if os.path.isfile(meta_path):
+                with open(meta_path, "r") as jf:
                     p = json.load(jf)
                 fluid_params = [
-                    p["inv_reynolds"], p["cpgas"], p["mugas"], p["rhogas"],
-                    p["thcogas"], p["stefan"], p["prandtl"],
-                    p["heater"]["nucWaitTime"], p["heater"]["wallTemp"]
+                    p["inv_reynolds"],
+                    p["cpgas"],
+                    p["mugas"],
+                    p["rhogas"],
+                    p["thcogas"],
+                    p.get("stefan", 0.0),
+                    p["prandtl"],
+                    p["heater"]["nucWaitTime"],
+                    p["heater"].get("wallTemp", 0.0),
                 ]
             else:
                 fluid_params = []
 
             yield idx, {
-                "input": inp.astype(np.float32),
-                "output": out.astype(np.float32),
+                "input": inp.astype(np.float32).tolist(),
+                "output": out.astype(np.float32).tolist(),
                 "fluid_params": fluid_params,
                 "filename": os.path.basename(path),
             }