Base Module
===========

Abstract base class and data utilities shared by every MaldiDeepKit
classifier. Users implementing a new architecture only need to inherit
from :class:`~maldideepkit.BaseSpectralClassifier` and override
``_build_model()``.

BaseSpectralClassifier
----------------------

.. autoclass:: maldideepkit.BaseSpectralClassifier
   :members:
   :inherited-members:
   :undoc-members:
   :show-inheritance:

SpectralDataset
---------------

.. autoclass:: maldideepkit.SpectralDataset
   :members:
   :undoc-members:
   :show-inheritance:

``SpectralDataset`` accepts NumPy arrays, pandas DataFrames, and any
object with a DataFrame-like ``.X`` attribute (e.g.
:class:`maldiamrkit.MaldiSet`):

.. code-block:: python

    import numpy as np
    import pandas as pd
    from maldideepkit import SpectralDataset

    ds_array = SpectralDataset(np.zeros((10, 6000)))
    ds_frame = SpectralDataset(pd.DataFrame(np.zeros((10, 6000))))

make_loaders
------------

.. autofunction:: maldideepkit.make_loaders

Loader Example
~~~~~~~~~~~~~~

.. code-block:: python

    import numpy as np
    from maldideepkit import make_loaders

    X = np.random.default_rng(0).standard_normal((200, 6000)).astype("float32")
    y = np.random.default_rng(0).integers(0, 2, size=200)

    train, val, stats = make_loaders(
        X, y, batch_size=32, val_size=0.1, standardize=True, random_state=0,
    )