.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_utils_plot_roi_voxel_mask.py>`     to download the full example code
    .. rst-class:: sphx-glr-example-title

    .. _sphx_glr_auto_examples_utils_plot_roi_voxel_mask.py:


==================
Get ROI Voxel Mask
==================

Get proportion of each voxel that exists within a named ROI (this 
constitutes a probability map for the ROI, with values ranging from
0-1). Plot this probablistic roi mask onto a flatmap. 

In order for this to work, the specified ROI must exist in the
overlays.svg file in the pycortex filestore for this subject.



.. image:: /auto_examples/utils/images/sphx_glr_plot_roi_voxel_mask_001.png
    :alt: plot roi voxel mask
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    Found 100.00% of EBA
    Cutting 0 overlapping voxels (should be < ~50)
    Generating a flatmap cache






|


.. code-block:: default


    import cortex
    import matplotlib.pyplot as plt

    subject = "S1"
    xfm = "fullhead"
    roi = "EBA"

    # Get the map of which voxels are inside of our ROI
    roi_masks = cortex.utils.get_roi_masks(subject, xfm, 
                                           roi_list=[roi],
                                           gm_sampler='cortical-conservative', # Select only voxels mostly within cortex
                                           split_lr=False, # No separate left/right ROIs
                                           threshold=None, # Leave roi mask values as probabilites / fractions
                                           return_dict=True
                                           )

    # Plot the mask for one ROI onto a flatmap
    roi_data = cortex.Volume(roi_masks[roi], subject, xfm, 
                             vmin=0, # This is a probability mask, so only
                             vmax=1, # so scale btw zero and one
                             cmap="inferno", # For pretty
                             )

    cortex.quickflat.make_figure(roi_data,
                                 thick=1, # select a single depth (btw white matter & pia)
                                 sampler='nearest', # no interpolation
                                 with_curvature=True,
                                 with_colorbar=True,
                                 )

    plt.show()

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

   **Total running time of the script:** ( 0 minutes  9.955 seconds)


.. _sphx_glr_download_auto_examples_utils_plot_roi_voxel_mask.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_roi_voxel_mask.py <plot_roi_voxel_mask.py>`



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

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


.. only:: html

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

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