sbi script

SBI-16-2D.py

@@ -155,58 +155,4 @@ class SBI_16_2D(datasets.GeneratorBasedBuilder):
                 # Process image data from HDU index 4
                 image_data_4 = hdul[4].data[:, :].tolist()
                 task_instance_key_4 = f"{self.config.name}-{split}-{idx}-HDU4"
-                yield task_instance_key_4, {**{"image": image_data_4}, **item}
-
-
-
-def make_split_jsonl_files(
-    config_type="tiny", data_dir="./data", outdir="./splits", seed=42
-):
-    """
-    Create jsonl files for the SBI-16-2D dataset.
-
-    config_type: str, default="tiny"
-        The type of split to create. Options are "tiny" and "full".
-    data_dir: str, default="./data"
-        The directory where the FITS files are located.
-    outdir: str, default="./splits"
-        The directory where the jsonl files will be created.
-    seed: int, default=42
-        The seed for the random split.
-    """
-    random.seed(seed)
-    os.makedirs(outdir, exist_ok=True)
-
-    fits_files = glob(os.path.join(data_dir, "*.fits"))
-    random.shuffle(fits_files)
-    if config_type == "tiny":
-        train_files = fits_files[:2]
-        test_files = fits_files[2:3]
-    elif config_type == "full":
-        split_idx = int(0.8 * len(fits_files))
-        train_files = fits_files[:split_idx]
-        test_files = fits_files[split_idx:]
-    else:
-        raise ValueError("Unsupported config_type. Use 'tiny' or 'full'.")
-
-    def create_jsonl(files, split_name):
-        output_file = os.path.join(outdir, f"{config_type}_{split_name}.jsonl")
-        with open(output_file, "w") as out_f:
-            for file in files:
-                print(file, flush=True, end="...")
-                with fits.open(file, memmap=False) as hdul:
-                    image_id = os.path.basename(file).split(".fits")[0]
-                    ra = hdul["SCI"].header.get("CRVAL1", 0)
-                    dec = hdul["SCI"].header.get("CRVAL2", 0)
-                    pixscale = hdul["SCI"].header.get("CD1_2", 0.396)
-                    item = {
-                        "image_id": image_id,
-                        "image": file,
-                        "ra": ra,
-                        "dec": dec,
-                        "pixscale": pixscale,
-                    }
-                    out_f.write(json.dumps(item) + "\n")
-
-    create_jsonl(train_files, "train")
-    create_jsonl(test_files, "test")
+                yield task_instance_key_4, {**{"image": image_data_4}, **item}