coco_pipe.io.structures
=======================

.. py:module:: coco_pipe.io.structures

.. autoapi-nested-parse::

   Data Structures
   ===============

   Standardized containers for passing data between Datasets, Preprocessing, and main
   modules.

   This module provides the `~coco_pipe.io.DataContainer`, an N-dimensional tensor wrapper
   that manages metadata, coordinates, and labels alongside the raw data matrix. It serves
   as the common currency for the entire pipeline.

   .. rubric:: Examples

   >>> import numpy as np
   >>> from coco_pipe.io import DataContainer

   # 1. Creating a container for EEG Epochs (N_epochs, N_channels, N_time)
   >>> X = np.random.randn(10, 64, 500)
   >>> container = DataContainer(
   ...     X=X,
   ...     dims=("obs", "channel", "time"),
   ...     coords={
   ...         "channel": ["Fz", "Cz", "Pz"],  # ... etc
   ...         "time": np.linspace(0, 1.0, 500),
   ...     },
   ...     y=np.random.randint(0, 2, 10),
   ...     ids=[f"sub-01_trial-{i}" for i in range(10)],
   ... )

   # 2. Creating a container for simple Tabular Features (N_subjects, N_features)
   >>> X_tab = np.random.randn(20, 5)
   >>> container_tab = DataContainer(
   ...     X=X_tab,
   ...     dims=("obs", "feature"),
   ...     coords={"feature": ["age", "IQ", "response_time", "power_alpha", "power_beta"]},
   ... )



Attributes
----------

.. autoapisummary::

   coco_pipe.io.structures.logger


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

.. py:data:: logger