(self, call_shape: Sequence[int] | None, spatial_dims: int)
| 877 | return converted |
| 878 | |
| 879 | def _resolve_spatial_shape(self, call_shape: Sequence[int] | None, spatial_dims: int) -> tuple[int, ...]: |
| 880 | shape = call_shape if call_shape is not None else self.spatial_shape |
| 881 | if shape is None: |
| 882 | raise ValueError("Argument `spatial_shape` must be provided either at construction time or call time.") |
| 883 | shape_tuple = ensure_tuple(shape) |
| 884 | if len(shape_tuple) != spatial_dims: |
| 885 | if len(shape_tuple) == 1: |
| 886 | shape_tuple = shape_tuple * spatial_dims # type: ignore |
| 887 | else: |
| 888 | raise ValueError( |
| 889 | "Argument `spatial_shape` length must match the landmarks' spatial dims (or pass a single int to broadcast)." |
| 890 | ) |
| 891 | return tuple(int(s) for s in shape_tuple) |
| 892 | |
| 893 | def _resolve_sigma(self, spatial_dims: int) -> tuple[float, ...]: |
| 894 | if len(self._sigma) == spatial_dims: |
no test coverage detected