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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_surface_analyses_plot_interpolate_data.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_surface_analyses_plot_interpolate_data.py:


===================
Interpolate Data
===================

In this example we show how to interpolate data from a sparse collection of points
to all the points in the cortical surface.

The method used here is biharmonic interpolation, which finds the solution with
the minimum squared Laplacian (fourth derivative) that still passes through all
the selected points. This is similar to thin plate splines.

.. GENERATED FROM PYTHON SOURCE LINES 14-62



.. image-sg:: /auto_examples/surface_analyses/images/sphx_glr_plot_interpolate_data_001.png
   :alt: plot interpolate data
   :srcset: /auto_examples/surface_analyses/images/sphx_glr_plot_interpolate_data_001.png
   :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    /opt/hostedtoolcache/Python/3.9.12/x64/lib/python3.9/site-packages/scipy/sparse/linalg/_dsolve/linsolve.py:322: SparseEfficiencyWarning: splu requires CSC matrix format
      warn('splu requires CSC matrix format', SparseEfficiencyWarning)






|

.. code-block:: default


    import cortex
    from cortex.polyutils import Surface
    import numpy as np
    np.random.seed(1234)
    from matplotlib import pyplot as plt

    subject = "S1"

    # First we need to import the surfaces for this subject
    lsurf, rsurf = [Surface(*d) for d in cortex.db.get_surf(subject, "fiducial")]

    # Let's choose a few points and generate data for them
    selected_pts = np.arange(len(lsurf.pts), step=5000)
    num_selected_pts = len(selected_pts)
    sparse_data = np.random.randn(num_selected_pts)

    # Then interpolate
    interp_data = lsurf.interp(selected_pts, sparse_data)

    # Plot the result
    # interp_data is only for the left hemisphere, but the Vertex constructor
    # infers that and fills the right hemisphere with zeros
    interp_vertex = cortex.Vertex(interp_data[:,0], subject, 
                                  vmin=-2, vmax=2, cmap='RdBu_r')
    cortex.quickshow(interp_vertex, with_labels=False, with_rois=False)


    # plot the locations of the points we selected originally

    # nudge=True puts both left and right hemispheres in the same space, moving them
    # so that they don't overlap. These are the coordinates used in quickflat
    (lflatpts, lpolys), (rflatpts, rpolys) = cortex.db.get_surf(subject, "flat", 
                                                                nudge=True)

    ax = plt.gca()
    # zorder is set to 10 to make sure points go on top of other quickflat layers
    ax.scatter(lflatpts[selected_pts,0], lflatpts[selected_pts,1], s=50, 
               c=sparse_data, vmin=-2, vmax=2, cmap=plt.cm.RdBu_r, zorder=10)


    # the interpolate function can also handle multiple dimensions at the same time
    # (this takes a while to run for no plotting, and thus is commented out)
    #sparse_data_2d = np.random.randn(10, num_selected_pts)
    #interp_data_2d = lsurf.interp(selected_pts, sparse_data_2d)

    # > interp_data_2d.shape
    # (152893, 10)
    plt.show()

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

   **Total running time of the script:** ( 0 minutes  15.640 seconds)


.. _sphx_glr_download_auto_examples_surface_analyses_plot_interpolate_data.py:


.. only :: html

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



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

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



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

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


.. only:: html

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

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