.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_02_decoding_plot_haxby_stimuli.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_02_decoding_plot_haxby_stimuli.py:


Show stimuli of Haxby et al. dataset
===============================================================================

In this script we plot an overview of the stimuli used in "Distributed
and Overlapping Representations of Faces and Objects in Ventral Temporal
Cortex" (Science 2001)



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


    *

      .. image:: /auto_examples/02_decoding/images/sphx_glr_plot_haxby_stimuli_001.png
          :alt: bottles
          :class: sphx-glr-multi-img

    *

      .. image:: /auto_examples/02_decoding/images/sphx_glr_plot_haxby_stimuli_002.png
          :alt: chairs
          :class: sphx-glr-multi-img

    *

      .. image:: /auto_examples/02_decoding/images/sphx_glr_plot_haxby_stimuli_003.png
          :alt: scissors
          :class: sphx-glr-multi-img

    *

      .. image:: /auto_examples/02_decoding/images/sphx_glr_plot_haxby_stimuli_004.png
          :alt: cats
          :class: sphx-glr-multi-img

    *

      .. image:: /auto_examples/02_decoding/images/sphx_glr_plot_haxby_stimuli_005.png
          :alt: houses
          :class: sphx-glr-multi-img

    *

      .. image:: /auto_examples/02_decoding/images/sphx_glr_plot_haxby_stimuli_006.png
          :alt: shoes
          :class: sphx-glr-multi-img

    *

      .. image:: /auto_examples/02_decoding/images/sphx_glr_plot_haxby_stimuli_007.png
          :alt: faces
          :class: sphx-glr-multi-img






.. code-block:: default


    import matplotlib.pyplot as plt

    from nilearn import datasets
    from nilearn.plotting import show

    haxby_dataset = datasets.fetch_haxby(subjects=[], fetch_stimuli=True)
    stimulus_information = haxby_dataset.stimuli

    for stim_type in stimulus_information:
        # skip control images, there are too many
        if stim_type != 'controls':

            file_names = stimulus_information[stim_type]

            fig, axes = plt.subplots(6, 8)
            fig.suptitle(stim_type)

            for img_path, ax in zip(file_names, axes.ravel()):
                ax.imshow(plt.imread(img_path), cmap=plt.cm.gray)

            for ax in axes.ravel():
                ax.axis("off")

    show()


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

   **Total running time of the script:** ( 0 minutes  6.245 seconds)


.. _sphx_glr_download_auto_examples_02_decoding_plot_haxby_stimuli.py:


.. only :: html

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


  .. container:: binder-badge

    .. image:: images/binder_badge_logo.svg
      :target: https://mybinder.org/v2/gh/nilearn/nilearn.github.io/main?filepath=examples/auto_examples/02_decoding/plot_haxby_stimuli.ipynb
      :alt: Launch binder
      :width: 150 px


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

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



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

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


.. only:: html

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

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