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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_howto_howto_examples_plot_afq_callosal.py>`
        to download the full example code

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

.. _sphx_glr_howto_howto_examples_plot_afq_callosal.py:


==========================
Callosal bundles using AFQ API
==========================
An example using the AFQ API to find callosal bundles using the templates from:
http://hdl.handle.net/1773/34926

.. GENERATED FROM PYTHON SOURCE LINES 8-19

.. code-block:: Python

    import os.path as op
    import matplotlib.pyplot as plt
    import nibabel as nib

    import plotly

    from AFQ.api.group import GroupAFQ
    import AFQ.api.bundle_dict as abd
    from AFQ.definitions.image import RoiImage
    import AFQ.data.fetch as afd








.. GENERATED FROM PYTHON SOURCE LINES 20-25

Get some example data
---------------------

Retrieves `Stanford HARDI dataset <https://purl.stanford.edu/ng782rw8378>`_.


.. GENERATED FROM PYTHON SOURCE LINES 25-28

.. code-block:: Python


    afd.organize_stanford_data(clear_previous_afq="track")





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

 .. code-block:: none


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.. GENERATED FROM PYTHON SOURCE LINES 29-36

Set tractography parameters (optional)
---------------------
We make this tracking_params which we will pass to the GroupAFQ object
which specifies that we want 100,000 seeds randomly distributed
in the ROIs of every bundle.

We only do this to make this example faster and consume less space.

.. GENERATED FROM PYTHON SOURCE LINES 36-42

.. code-block:: Python


    tracking_params = dict(seed_mask=RoiImage(),
                           n_seeds=10000,
                           random_seeds=True,
                           rng_seed=42)








.. GENERATED FROM PYTHON SOURCE LINES 43-53

Set segmentation parameters (optional)
---------------------
We make this segmentation_params which we will pass to the GroupAFQ object
which specifies that we want to clip the extracted tract profiles
to only be between the two ROIs.

We do this because tract profiles become less reliable as the bundles
approach the gray matter-white matter boundary. On some of the non-callosal
bundles, ROIs are not in a good position to clip edges. In these cases,
one can remove the first and last nodes in a tract profile.

.. GENERATED FROM PYTHON SOURCE LINES 53-56

.. code-block:: Python


    segmentation_params = {"clip_edges": True}








.. GENERATED FROM PYTHON SOURCE LINES 57-66

Initialize a GroupAFQ object:
-------------------------

We specify bundle_info as the callosal bundles only
(`abd.callosal_bd`). If we want to segment both the callosum
and the other bundles, we would pass
`abd.callosal_bd() + abd.default18_bd()`
instead. This would tell the GroupAFQ object to use bundles from both
the standard and callosal templates.

.. GENERATED FROM PYTHON SOURCE LINES 66-80

.. code-block:: Python


    myafq = GroupAFQ(
        bids_path=op.join(afd.afq_home, 'stanford_hardi'),
        preproc_pipeline='vistasoft',
        bundle_info=abd.callosal_bd(),
        tracking_params=tracking_params,
        segmentation_params=segmentation_params,
        viz_backend_spec='plotly_no_gif')

    # Calling export all produces all of the outputs of processing, including
    # tractography, scalar maps, tract profiles and visualizations:
    myafq.export_all()






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

 .. code-block:: none


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    Optimizing level 2 [max iter: 10000]
    Optimizing level 1 [max iter: 1000]
    Optimizing level 0 [max iter: 100]
    Optimizing level 2 [max iter: 10000]
    Optimizing level 1 [max iter: 1000]
    Optimizing level 0 [max iter: 100]
    Optimizing level 2 [max iter: 10000]
    Optimizing level 1 [max iter: 1000]
    Optimizing level 0 [max iter: 100]

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.. GENERATED FROM PYTHON SOURCE LINES 81-87

Create Group Density Maps:
-------------------------

pyAFQ can make density maps of streamline counts per subject/session
by calling `myafq.export("density_map")`. When using `GroupAFQ`, you can also
combine these into one file by calling `myafq.export_group_density()`.

.. GENERATED FROM PYTHON SOURCE LINES 87-96

.. code-block:: Python

    group_density = myafq.export_group_density()
    group_density = nib.load(group_density).get_fdata()
    fig, ax = plt.subplots(1)
    ax.matshow(
        group_density[:, :, group_density.shape[-1] // 2, 0],
        cmap='viridis')
    ax.axis("off")





.. image-sg:: /howto/howto_examples/images/sphx_glr_plot_afq_callosal_001.png
   :alt: plot afq callosal
   :srcset: /howto/howto_examples/images/sphx_glr_plot_afq_callosal_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


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    (-0.5, 105.5, 80.5, -0.5)



.. GENERATED FROM PYTHON SOURCE LINES 97-102

Visualizing bundles and tract profiles:
---------------------------------------
This would run the script and visualize the bundles using the plotly
interactive visualization, which should automatically open in a
new browser window.

.. GENERATED FROM PYTHON SOURCE LINES 102-104

.. code-block:: Python

    bundle_html = myafq.export("all_bundles_figure")
    plotly.io.show(bundle_html["01"][0])



.. raw:: html
    :file: images/sphx_glr_plot_afq_callosal_002.html






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

   **Total running time of the script:** (15 minutes 48.166 seconds)

**Estimated memory usage:**  2272 MB


.. _sphx_glr_download_howto_howto_examples_plot_afq_callosal.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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