loki2.preprocess
================

.. py:module:: loki2.preprocess

.. autoapi-nested-parse::

   Preprocessing utilities for Loki2.

   This module provides utilities for loading and preprocessing Loki2 outputs,
   including .pt embeddings and JSON metadata files.





Module Contents
---------------

.. py:function:: setup_dummy_modules() -> None

   Sets up dummy modules for 'loki2' and its submodules.

   This is required to simulate the module structure that the torch model
   expects when unpickling objects that reference e.g. 'loki2.data.dataclass.cell_graph'.


.. py:function:: load_and_print_tensor(file_path: str) -> Any

   Load a PyTorch object from a given file path.

   :param file_path: Path to the .pt file.

   :returns: The loaded Python object (typically a tensor or model state).
   :rtype: Any


.. py:function:: load_sample(base: str, sample_name: str) -> Tuple[numpy.ndarray, numpy.ndarray, List[Dict[str, Any]]]

   Load a single sample's embeddings, positions, and JSON cell metadata.

   Expects:
       - {sample_name}_cells.pt  (with attributes `.x` and `.positions`)
       - {sample_name}_cells.json (list or dict describing cells)

   :param base: Root directory containing the .pt and .json files.
   :param sample_name: Sample identifier (without suffix).

   :returns:     - emb: Embeddings array of shape (N, D) from data.x
                 - pos: Positions array from data.positions
                 - cells: List of per-cell dictionaries
   :rtype: Tuple[np.ndarray, np.ndarray, List[Dict[str, Any]]]

   :raises TypeError: If JSON structure is not recognized.