.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/01_tutorials/3_create_dataset.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_01_tutorials_3_create_dataset.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_01_tutorials_3_create_dataset.py:


Creating a dataset
===========================

This example shows how to create a multi-modal dataset for training.


.. GENERATED FROM PYTHON SOURCE LINES 11-17

Creating a Dataset with Multiple Modalities
--------------------------------------------
MyoVerse stores continuous data with named dimensions (xarray + zarr).
Any number of modalities can be stored - you decide what's input vs
target at training time, not storage time.


.. GENERATED FROM PYTHON SOURCE LINES 17-50

.. code-block:: Python

    from pathlib import Path

    from myoverse.datasets import DatasetCreator, Modality

    # Get the path to the data file
    # Find data directory relative to myoverse package (works in all contexts)
    import myoverse
    _pkg_dir = Path(myoverse.__file__).parent.parent
    DATA_DIR = _pkg_dir / "examples" / "data"
    if not DATA_DIR.exists():
        DATA_DIR = Path.cwd() / "examples" / "data"

    # Create dataset with multiple modalities
    creator = DatasetCreator(
        modalities={
            "emg": Modality(
                path=DATA_DIR / "emg.pkl",
                dims=("channel", "time"),
            ),
            "kinematics": Modality(
                path=DATA_DIR / "kinematics.pkl",
                dims=("joint", "xyz", "time"),
            ),
        },
        sampling_frequency=2044.0,
        tasks_to_use=["1", "2"],
        save_path=DATA_DIR / "dataset.zip",
        test_ratio=0.2,
        val_ratio=0.2,
        debug_level=1,
    )

    creator.create()




.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    ────────────────────────── STARTING DATASET CREATION ───────────────────────────

                                 Dataset Configuration                              
    ┏━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
    ┃ Parameter               ┃ Value                                              ┃
    ┡━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
    │ Modalities              │ emg, kinematics                                    │
    │ Sampling frequency (Hz) │ 2044.0                                             │
    │ Save path               │ /home/runner/work/MyoVerse/MyoVerse/examples/data… │
    │ Test ratio              │ 0.2                                                │
    │ Validation ratio        │ 0.2                                                │
    └─────────────────────────┴────────────────────────────────────────────────────┘

    Processing 2 tasks: 1, 2

    Dataset Structure
    ├── emg dims=('channel', 'time')
    │   ├── Task 1: (320, 20440)
    │   └── Task 2: (320, 20440)
    └── kinematics dims=('joint', 'xyz', 'time')
        ├── Task 1: (21, 3, 20440)
        └── Task 2: (21, 3, 20440)

    ─────────────────────────────── PROCESSING TASKS ───────────────────────────────

      Processing task 2 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
    ────────────────────────── DATASET CREATION COMPLETED ──────────────────────────

                    Dataset Summary                 
     Split       emg              kinematics        
     training    1: (320, 16352)  1: (21, 3, 16352) 
                 2: (320, 16352)  2: (21, 3, 16352) 
     validation  1: (320, 816)    1: (21, 3, 816)   
                 2: (320, 816)    2: (21, 3, 816)   
     testing     1: (320, 3272)   1: (21, 3, 3272)  
                 2: (320, 3272)   2: (21, 3, 3272)  

    Total size: 26.09 MB
    ─────────────────── Dataset Creation Successfully Completed! ───────────────────





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.754 seconds)

**Estimated memory usage:**  626 MB


.. _sphx_glr_download_auto_examples_01_tutorials_3_create_dataset.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: 3_create_dataset.ipynb <3_create_dataset.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: 3_create_dataset.py <3_create_dataset.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: 3_create_dataset.zip <3_create_dataset.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

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