.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_06_manipulating_images_plot_resample_to_template.py>`     to download the full example code or to run this example in your browser via Binder
    .. rst-class:: sphx-glr-example-title

    .. _sphx_glr_auto_examples_06_manipulating_images_plot_resample_to_template.py:


Resample an image to a template
===============================

The goal of this example is to illustrate the use of the function
:func:`nilearn.image.resample_to_img` to resample an image to a template.
We use the MNI152 template as the reference for resampling a t-map image.
Function :func:`nilearn.image.resample_img` could also be used to achieve this.

First we load the required datasets using the nilearn datasets module.


.. code-block:: default

    from nilearn.datasets import fetch_neurovault_motor_task
    from nilearn.datasets import load_mni152_template

    template = load_mni152_template()

    motor_images = fetch_neurovault_motor_task()
    stat_img = motor_images.images[0]








Now, the localizer t-map image can be resampled to the MNI template image.


.. code-block:: default

    from nilearn.image import resample_to_img

    resampled_stat_img = resample_to_img(stat_img, template)








Let's check the shape and affine have been correctly updated.


.. code-block:: default


    # First load the original t-map in memory:
    from nilearn.image import load_img
    tmap_img = load_img(stat_img)

    original_shape = tmap_img.shape
    original_affine = tmap_img.affine

    resampled_shape = resampled_stat_img.shape
    resampled_affine = resampled_stat_img.affine

    template_img = load_img(template)
    template_shape = template_img.shape
    template_affine = template_img.affine
    print("""Shape comparison:
    - Original t-map image shape : {0}
    - Resampled t-map image shape: {1}
    - Template image shape       : {2}
    """.format(original_shape, resampled_shape, template_shape))

    print("""Affine comparison:
    - Original t-map image affine :\n {0}
    - Resampled t-map image affine:\n {1}
    - Template image affine       :\n {2}
    """.format(original_affine, resampled_affine, template_affine))





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

 Out:

 .. code-block:: none

    Shape comparison:
    - Original t-map image shape : (53, 63, 46)
    - Resampled t-map image shape: (91, 109, 91)
    - Template image shape       : (91, 109, 91)

    Affine comparison:
    - Original t-map image affine :
     [[  -3.    0.    0.   78.]
     [   0.    3.    0. -112.]
     [   0.    0.    3.  -50.]
     [   0.    0.    0.    1.]]
    - Resampled t-map image affine:
     [[  -2.    0.    0.   90.]
     [   0.    2.    0. -126.]
     [   0.    0.    2.  -72.]
     [   0.    0.    0.    1.]]
    - Template image affine       :
     [[  -2.    0.    0.   90.]
     [   0.    2.    0. -126.]
     [   0.    0.    2.  -72.]
     [   0.    0.    0.    1.]]





Finally, result images are displayed using nilearn plotting module.


.. code-block:: default

    from nilearn import plotting

    plotting.plot_stat_map(stat_img,
                           bg_img=template,
                           cut_coords=(36, -27, 66),
                           threshold=3,
                           title="t-map in original resolution")
    plotting.plot_stat_map(resampled_stat_img,
                           bg_img=template,
                           cut_coords=(36, -27, 66),
                           threshold=3,
                           title="Resampled t-map")
    plotting.show()



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


    *

      .. image:: /auto_examples/06_manipulating_images/images/sphx_glr_plot_resample_to_template_001.png
          :alt: plot resample to template
          :class: sphx-glr-multi-img

    *

      .. image:: /auto_examples/06_manipulating_images/images/sphx_glr_plot_resample_to_template_002.png
          :alt: plot resample to template
          :class: sphx-glr-multi-img






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

   **Total running time of the script:** ( 0 minutes  2.411 seconds)


.. _sphx_glr_download_auto_examples_06_manipulating_images_plot_resample_to_template.py:


.. only :: html

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


  .. container:: binder-badge

    .. image:: https://mybinder.org/badge_logo.svg
      :target: https://mybinder.org/v2/gh/nilearn/nilearn.github.io/master?filepath=examples/auto_examples/06_manipulating_images/plot_resample_to_template.ipynb
      :width: 150 px


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

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



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

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


.. only:: html

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

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