.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/datasets/plot_variable_frequency_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_datasets_plot_variable_frequency_dataset.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_datasets_plot_variable_frequency_dataset.py:


Plot dataset source domain and shifted target domain
====================================================

This illustrates the :func:`~skada.datasets.make_variable_frequency_dataset`
dataset generator. Each method consists of generating source data
and shifted target data.

.. GENERATED FROM PYTHON SOURCE LINES 10-21

.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np

    from skada import source_target_split
    from skada.datasets import make_variable_frequency_dataset

    # Use same random seed for multiple calls to make_datasets to
    # ensure same distributions
    RANDOM_SEED = np.random.randint(2**10)








.. GENERATED FROM PYTHON SOURCE LINES 22-40

.. code-block:: Python


    X, y, sample_domain = make_variable_frequency_dataset(
        n_samples_source=1,
        n_samples_target=1,
        n_channels=3,
        n_frequencies=2,
        n_classes=2,
        delta_f=2,
        band_size=1,
        sigma_ch=1,
        noise=0.2,
        random_state=RANDOM_SEED,
    )

    X_source, X_target, y_source, y_target = source_target_split(
        X, y, sample_domain=sample_domain
    )








.. GENERATED FROM PYTHON SOURCE LINES 41-60

.. code-block:: Python


    fig, ax = plt.subplots(3, 2, sharex="all", sharey="all", figsize=(8, 4))
    plt.subplots_adjust(bottom=0.15)
    fig.suptitle("Signal visualisation")
    time = np.linspace(0, 1, 100)
    for i in range(3):
        ax[i, 0].plot(time, X_source[0, i, 1000:1100], alpha=0.7, label="source")
        ax[i, 0].set_ylabel(f"chan {i}")
        ax[i, 0].plot(time, X_target[0, i, 1000:1100], alpha=0.7, label="target")

        ax[i, 1].plot(time, X_source[1, i, 1000:1100], alpha=0.7)
        ax[i, 1].plot(time, X_target[1, i, 1000:1100], alpha=0.7)
    ax[0, 0].set_title("Class 1")
    ax[0, 1].set_title("Class 2")
    ax[2, 0].set_xlabel("Time (s)")
    ax[2, 1].set_xlabel("Time (s)")
    ax[0, 0].legend()
    plt.show()




.. image-sg:: /auto_examples/datasets/images/sphx_glr_plot_variable_frequency_dataset_001.png
   :alt: Signal visualisation, Class 1, Class 2
   :srcset: /auto_examples/datasets/images/sphx_glr_plot_variable_frequency_dataset_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 61-84

.. code-block:: Python


    fig, ax = plt.subplots(3, 2, sharex="all", sharey="all", figsize=(8, 4))
    plt.subplots_adjust(bottom=0.15)
    fig.suptitle("PSD shift")
    for i in range(3):
        ax[i, 0].psd(X_source[0, i], Fs=100, alpha=0.7, label="source")
        ax[i, 0].psd(X_target[0, i], Fs=100, alpha=0.7, label="target")

        ax[i, 1].psd(X_source[1, i], Fs=100, alpha=0.7)
        ax[i, 1].psd(X_target[1, i], Fs=100, alpha=0.7)
    ax[0, 0].legend()
    ax[0, 0].set_title("Class 1")
    ax[0, 1].set_title("Class 2")
    for i in range(3):
        ax[i, 0].set_ylabel(f"PSD chan {i}")
        ax[i, 1].set_ylabel("")
        ax[i, 0].set_xlabel("")
        ax[i, 1].set_xlabel("")
    ax[2, 0].set_xlabel("Frequency")
    ax[2, 1].set_xlabel("Frequency")
    plt.show()

    print(f"The data was generated from (random_state={RANDOM_SEED})")



.. image-sg:: /auto_examples/datasets/images/sphx_glr_plot_variable_frequency_dataset_002.png
   :alt: PSD shift, Class 1, Class 2
   :srcset: /auto_examples/datasets/images/sphx_glr_plot_variable_frequency_dataset_002.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    The data was generated from (random_state=19)





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

   **Total running time of the script:** (0 minutes 0.678 seconds)


.. _sphx_glr_download_auto_examples_datasets_plot_variable_frequency_dataset.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_variable_frequency_dataset.ipynb <plot_variable_frequency_dataset.ipynb>`

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

      :download:`Download Python source code: plot_variable_frequency_dataset.py <plot_variable_frequency_dataset.py>`

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

      :download:`Download zipped: plot_variable_frequency_dataset.zip <plot_variable_frequency_dataset.zip>`


.. only:: html

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

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_