.. _sphx_glr_auto_examples_plot_update_model.py:


=============================
Create a model from scratch, and then update it with new subject data
=============================

In this example, we will simulate a model and update the model with the new data.
First, we'll load in some example locations. Then, we will simulate
correlational structure (a toeplitz matrix) to impose on our simulated data.
We simulate 3 brain objects by sampling 10 locations from example_locs and
create a model from these brain objects. Then, we will simulate an additional
brain object and use the model.update method to update an existing model with
new data.





.. rst-class:: sphx-glr-horizontal


    *

      .. image:: /auto_examples/images/sphx_glr_plot_update_model_001.png
            :scale: 47

    *

      .. image:: /auto_examples/images/sphx_glr_plot_update_model_002.png
            :scale: 47





.. code-block:: python


    # Code source: Andrew Heusser & Lucy Owen
    # License: MIT

    # import libraries
    import matplotlib.pyplot as plt
    import supereeg as se


    # simulate 100 locations
    locs = se.simulate_locations(n_elecs=100)

    # simulate correlation matrix
    R = se.create_cov(cov='toeplitz', n_elecs=len(locs))

    # simulate brain objects for the model that subsample n_elecs for each synthetic patient
    model_bos = [se.simulate_model_bos(n_samples=1000, sample_rate=1000, locs=locs, sample_locs=10, cov='toeplitz')
                 for x in range(3)]

    # create the model object
    model = se.Model(data=model_bos, locs=locs, n_subs=3)
    model.plot_data()

    # brain object locations subsetted
    sub_locs = locs.sample(10).sort_values(['x', 'y', 'z'])

    # simulate a new brain object using the same covariance matrix
    bo = se.simulate_bo(n_samples=1000, sample_rate=1000, locs=sub_locs, cov='toeplitz')

    # update the model
    new_model = model.update(bo, inplace=False)

    # initialize subplots
    f, (ax1, ax2) = plt.subplots(1, 2)
    f.set_size_inches(14,6)

    # plot it and set the title
    model.plot_data(ax=ax1, show=False, yticklabels=False, xticklabels=False, cbar=True, vmin=0, vmax=1)
    ax1.set_title('Before updating model: 3 subjects total')

    # plot it and set the title
    new_model.plot_data(ax=ax2, show=False, yticklabels=False, xticklabels=False, cbar=True, vmin=0, vmax=1)
    ax2.set_title('After updating model: 4 subjects total')

    plt.tight_layout()
    plt.show()

**Total running time of the script:** ( 0 minutes  3.762 seconds)



.. only :: html

 .. container:: sphx-glr-footer


  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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