Improve name of dataset

scripts/register_inventory.py

@@ -20,7 +20,7 @@
     resample_roi_image,
     show_image,
 )
-from hipct_reg.inventory import Dataset, load_datasets, save_datasets
+from hipct_reg.inventory import RegDataset, load_datasets, save_datasets
 from hipct_reg.registration import run_registration
 from hipct_reg.types import RegistrationInput
 
@@ -39,7 +39,7 @@
 DATASETS = {d.name: d for d in load_datasets()}
 
 
-def register(ds: Dataset) -> tuple[RegistrationInput, sitk.Similarity3DTransform]:
+def register(ds: RegDataset) -> tuple[RegistrationInput, sitk.Similarity3DTransform]:
     """
     Register a single dataset.
 
@@ -113,7 +113,7 @@ def plot_central_slice(
         ax.grid(color="k")
 
 
-def keep_dataset(d: Dataset) -> bool:
+def keep_dataset(d: RegDataset) -> bool:
     """
     Whether to keep a dataset for listing in the registration widget.
     """

scripts/update_inventory.py

@@ -77,7 +77,7 @@ def select_parent(
 
         if d.name not in datasets_reg_names:
             # Create new dataset
-            datasets_reg_names[d.name] = hipct_reg.inventory.Dataset(
+            datasets_reg_names[d.name] = hipct_reg.inventory.RegDataset(
                 name=d.name, parent_name=parent.name
             )
 

src/hipct_reg/inventory.py

@@ -9,7 +9,7 @@
 INVENTORY_FILE = Path(__file__).parent / "reg_inventory.csv"
 
 
-class Dataset(BaseModel):
+class RegDataset(BaseModel):
     """
     A dataset that can be, or has been registered.
     """
@@ -146,7 +146,7 @@ def neuroglancer_link(self) -> str:
         return link
 
 
-def save_datasets(datasets: list[Dataset]) -> None:
+def save_datasets(datasets: list[RegDataset]) -> None:
     """
     Save a list of datasets to the .csv inventory file.
     """
@@ -155,17 +155,17 @@ def save_datasets(datasets: list[Dataset]) -> None:
     df.to_csv(INVENTORY_FILE, index=False, lineterminator="\n")
 
 
-def load_datasets() -> list[Dataset]:
+def load_datasets() -> list[RegDataset]:
     """
     Load a list of datasets from the .csv inventory file.
     """
     df = pd.read_csv(INVENTORY_FILE, na_filter=False)
 
-    def parse_row(row: "pd.Series[Any]") -> Dataset:
+    def parse_row(row: "pd.Series[Any]") -> RegDataset:
         d = dict(row)
         for key in d:
             if d[key] == "":
                 d[key] = None
-        return Dataset(**d)
+        return RegDataset(**d)
 
     return [parse_row(row) for i, row in df.iterrows()]