.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "tutorials/tutorial_examples/plot_002_participant_afq_api.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_tutorials_tutorial_examples_plot_002_participant_afq_api.py>`
        to download the full example code.

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

.. _sphx_glr_tutorials_tutorial_examples_plot_002_participant_afq_api.py:


======================================
Getting started with pyAFQ - ParticipantAFQ
======================================

.. GENERATED FROM PYTHON SOURCE LINES 6-19

.. code-block:: Python


    import os
    import os.path as op

    import matplotlib.pyplot as plt
    import nibabel as nib
    import plotly
    import pandas as pd

    from AFQ.api.participant import ParticipantAFQ
    import AFQ.data.fetch as afd
    import AFQ.viz.altair as ava








.. GENERATED FROM PYTHON SOURCE LINES 20-41

Example data
------------
The following call dowloads a dataset that contains a single subject"s
high angular resolution diffusion imaging (HARDI) data, collected at the
Stanford Vista Lab

.. note::
  See https://purl.stanford.edu/ng782rw8378 for details on dataset.

The data are downloaded and organized locally into a BIDS compliant
anatomical data folder (``anat``) and a diffusion-weighted imaging data
(``dwi``) folder, which are both placed in the user's home directory under::

  ``~/AFQ_data/stanford_hardi/``

The data is also placed in a derivatives directory, signifying that it has
already undergone the required preprocessing necessary for pyAFQ to run.

The clear_previous_afq is used to remove any previous runs of the afq object
stored in the ``~/AFQ_data/stanford_hardi/`` BIDS directory. Set it to None if
you want to use the results of previous runs.

.. GENERATED FROM PYTHON SOURCE LINES 41-44

.. code-block:: Python


    afd.organize_stanford_data(clear_previous_afq = "track")








.. GENERATED FROM PYTHON SOURCE LINES 45-59

Defining data files
--------------------
If your data is not in BIDS format, you can still use pyAFQ. If you have BIDS
compliant dataset, you can use ``GroupAFQ`` instead (:doc:`plot_001_group_afq_api`). 
Otherwise, You will need to define the data files that you want to use. In 
this case, we will define the data files for the subject we downloaded above. 
The data files are located in the ``~/AFQ_data/stanford_hardi/derivatives/vistasoft``
directory, and are organized into a BIDS compliant directory structure. The 
data files are located in the ``dwi`` directories. The data files
are:  

- ``sub-01_dwi.nii.gz`` (the diffusion-weighted imaging data)
- ``sub-01_dwi.bval``   (the b-values)
- ``sub-01_dwi.bvec``   (the b-vectors)

.. GENERATED FROM PYTHON SOURCE LINES 59-74

.. code-block:: Python


    data_dir = op.join(afd.afq_home, "stanford_hardi", "derivatives", "vistasoft", 
                       "sub-01", "ses-01", "dwi")

    dwi_data_file = op.join(data_dir, "sub-01_ses-01_dwi.nii.gz")
    bval_file     = op.join(data_dir, "sub-01_ses-01_dwi.bval")
    bvec_file     = op.join(data_dir, "sub-01_ses-01_dwi.bvec")

    # You will also need to define the output directory where you want to store the
    # results. The output directory needs to exist before exporting ParticipantAFQ
    # results.

    output_dir = op.join(afd.afq_home, "stanford_hardi", "derivatives", "afq", "sub-01")
    os.makedirs(output_dir, exist_ok = True)








.. GENERATED FROM PYTHON SOURCE LINES 75-84

Set tractography parameters (optional)
---------------------------------------
We make create a `tracking_params` variable, which we will pass to the
ParticipantAFQ object which specifies that we want 25,000 seeds randomly
distributed in the white matter. We only do this to make this example
faster and consume less space. We also set ``num_chunks`` to `True`,
which will use ray to parallelize the tracking across all cores.
This can be removed to process in serial, or set to use a particular
distribution of work by setting `n_chunks` to an integer number.

.. GENERATED FROM PYTHON SOURCE LINES 84-91

.. code-block:: Python


    tracking_params = dict(n_seeds=25000,
                           random_seeds=True,
                           rng_seed=2022,
                           trx=True,
                           num_chunks=True)








.. GENERATED FROM PYTHON SOURCE LINES 92-108

Initialize a ParticipantAFQ object:
-------------------------

Creates a ParticipantAFQ object, that encapsulates tractometry. This object 
can be used to manage the entire :doc:`/explanations/tractometry_pipeline`, including:

- Tractography
- Registration
- Segmentation
- Cleaning
- Profiling
- Visualization

To initialize the object, we will pass in the diffusion data files and specify
the output directory where we want to store the results. We will also
pass in the tracking parameters we defined above. 

.. GENERATED FROM PYTHON SOURCE LINES 108-117

.. code-block:: Python


    myafq = ParticipantAFQ(
        dwi_data_file = dwi_data_file, 
        bval_file = bval_file,
        bvec_file = bvec_file,
        output_dir = output_dir,
        tracking_params = tracking_params,
    )








.. GENERATED FROM PYTHON SOURCE LINES 118-137

Calculating DTI FA (Diffusion Tensor Imaging Fractional Anisotropy)
------------------------------------------------------------------
The ParticipantAFQ object has a method called ``export``, which allows the user
to calculate various derived quantities from the data.

For example, FA can be computed using the DTI model, by explicitly
calling ``myafq.export("dti_fa")``. This triggers the computation of DTI
parameters, and stores the results in the AFQ derivatives directory. 
In addition, it calculates the FA from these parameters and stores it in a 
different file in the same directory.

.. note::

   The AFQ API computes quantities lazily. This means that DTI parameters
   are not computed until they are required. This means that the first
   line below is the one that requires time.

The result of the call to ``export`` is the filename of the corresponding FA 
files.

.. GENERATED FROM PYTHON SOURCE LINES 137-140

.. code-block:: Python


    FA_fname = myafq.export("dti_fa")








.. GENERATED FROM PYTHON SOURCE LINES 141-143

We will then use ``nibabel`` to load the deriviative file and retrieve the
data array.

.. GENERATED FROM PYTHON SOURCE LINES 143-147

.. code-block:: Python


    FA_img = nib.load(FA_fname)
    FA = FA_img.get_fdata()








.. GENERATED FROM PYTHON SOURCE LINES 148-159

Visualize the result with Matplotlib
-------------------------------------
At this point ``FA`` is an array, and we can use standard Python tools to
visualize it or perform additional computations with it.

In this case we are going to take an axial slice halfway through the
FA data array and plot using a sequential color map.

.. note::

   The data array is structured as a xyz coordinate system.

.. GENERATED FROM PYTHON SOURCE LINES 159-164

.. code-block:: Python


    fig, ax = plt.subplots(1)
    ax.matshow(FA[:, :, FA.shape[-1] // 2], cmap="viridis")
    ax.axis("off")




.. image-sg:: /tutorials/tutorial_examples/images/sphx_glr_plot_002_participant_afq_api_001.png
   :alt: plot 002 participant afq api
   :srcset: /tutorials/tutorial_examples/images/sphx_glr_plot_002_participant_afq_api_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    (np.float64(-0.5), np.float64(105.5), np.float64(80.5), np.float64(-0.5))



.. GENERATED FROM PYTHON SOURCE LINES 165-177

Recognizing the bundles and calculating tract profiles:
-----------------------------------------------------
Typically, users of pyAFQ are interested in calculating not only an overall
map of the FA, but also the major white matter pathways (or bundles) and
tract profiles of tissue properties along their length. To trigger the
pyAFQ pipeline that calculates the profiles, users can call the
``export("profiles")`` method:

.. note::
   Running the code below triggers the full pipeline of operations
   leading to the computation of the tract profiles. Therefore, it
   takes a little while to run (about 40 minutes, typically).

.. GENERATED FROM PYTHON SOURCE LINES 177-180

.. code-block:: Python


    myafq.export("profiles")





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

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    1178it [00:07, 161.20it/s]
    (TractActor pid=5332) 
    1213it [00:06, 165.07it/s]
    (TractActor pid=5325) 
    1422it [00:09, 216.40it/s]
    (TractActor pid=4912) 
    1196it [00:07, 166.37it/s]
    (TractActor pid=5332) 
    1233it [00:07, 173.96it/s]
    (TractActor pid=5325) 
    1445it [00:09, 207.36it/s]
    (TractActor pid=4912) 
    1213it [00:07, 165.09it/s]
    (TractActor pid=5332) 
    1252it [00:07, 176.90it/s]
    (TractActor pid=5325) 
    1469it [00:09, 215.28it/s]
    (TractActor pid=4912) 
    1233it [00:07, 173.68it/s]
    (TractActor pid=5332) 
    1274it [00:07, 188.98it/s]
    (TractActor pid=5325) 
    1492it [00:09, 216.00it/s]
    (TractActor pid=4912) 
    1251it [00:07, 175.43it/s]
    (TractActor pid=5332) 
    1294it [00:07, 190.41it/s]
    (TractActor pid=5325) 
    1514it [00:09, 200.84it/s]
    (TractActor pid=4912) 
    1274it [00:07, 190.52it/s]
    (TractActor pid=5325) 
    1538it [00:10, 207.09it/s]
    (TractActor pid=4912) 
    1294it [00:07, 191.20it/s]
    (TractActor pid=5332) 
    1314it [00:07, 143.72it/s]
    (TractActor pid=5325) 
    1559it [00:10, 200.15it/s]
    (TractActor pid=5332) 
    1331it [00:07, 144.56it/s]
    (TractActor pid=5325) 
    1583it [00:10, 209.20it/s]
    (TractActor pid=4912) 
    1314it [00:08, 143.12it/s]
    (TractActor pid=5332) 
    1349it [00:07, 153.11it/s]
    (TractActor pid=5325) 
    1608it [00:10, 219.46it/s]
    (TractActor pid=4912) 
    1331it [00:08, 143.19it/s]
    (TractActor pid=5332) 
    1367it [00:07, 158.11it/s]
    (TractActor pid=5325) 
    1635it [00:10, 229.41it/s]
    (TractActor pid=4912) 
    1349it [00:08, 151.76it/s]
    (TractActor pid=5332) 
    1386it [00:07, 166.59it/s]
    (TractActor pid=5325) 
    1659it [00:10, 230.84it/s]
    (TractActor pid=4912) 
    1367it [00:08, 156.93it/s]
    (TractActor pid=5332) 
    1404it [00:08, 165.98it/s]
    (TractActor pid=5325) 
    1683it [00:10, 229.12it/s]
    (TractActor pid=4912) 
    1387it [00:08, 167.37it/s]
    (TractActor pid=5332) 
    1422it [00:08, 168.46it/s]
    (TractActor pid=5325) 
    1706it [00:10, 222.33it/s]
    (TractActor pid=4912) 
    1405it [00:08, 166.06it/s]
    (TractActor pid=5332) 
    1440it [00:08, 160.38it/s]
    (TractActor pid=5325) 
    1729it [00:10, 223.21it/s]
    (TractActor pid=4912) 
    1423it [00:08, 167.16it/s]
    (TractActor pid=5332) 
    1458it [00:08, 163.10it/s]
    (TractActor pid=5325) 
    1752it [00:11, 222.81it/s]
    (TractActor pid=4912) 
    1441it [00:08, 158.47it/s]
    (TractActor pid=5332) 
    1477it [00:08, 169.84it/s]
    (TractActor pid=5325) 
    1778it [00:11, 231.79it/s]
    (TractActor pid=4912) 
    1459it [00:09, 164.08it/s]
    (TractActor pid=5332) 
    1495it [00:08, 162.67it/s]
    (TractActor pid=5325) 
    1802it [00:11, 230.52it/s]
    (TractActor pid=4912) 
    1478it [00:09, 169.02it/s]
    (TractActor pid=5332) 
    1512it [00:08, 148.95it/s]
    (TractActor pid=5325) 
    1826it [00:11, 228.60it/s]
    (TractActor pid=4912) 
    1496it [00:09, 162.93it/s]
    (TractActor pid=5332) 
    1530it [00:08, 156.08it/s]
    (TractActor pid=5325) 
    1849it [00:11, 224.76it/s]
    (TractActor pid=5325) 
    1873it [00:11, 227.33it/s]
    (TractActor pid=4912) 
    1513it [00:09, 149.41it/s]
    (TractActor pid=5332) 
    1546it [00:08, 151.20it/s]
    (TractActor pid=4912) 
    1531it [00:09, 155.97it/s]
    (TractActor pid=5332) 
    1564it [00:09, 157.31it/s]
    (TractActor pid=5325) 
    1896it [00:11, 174.05it/s]
    (TractActor pid=5332) 
    1582it [00:09, 163.34it/s]
    (TractActor pid=4912) 
    1547it [00:09, 150.94it/s]
    (TractActor pid=5332) 
    1599it [00:09, 163.82it/s]
    (TractActor pid=5325) 
    1920it [00:11, 189.49it/s]
    (TractActor pid=4912) 
    1564it [00:09, 155.78it/s]
    (TractActor pid=5325) 
    1942it [00:11, 196.87it/s]
    (TractActor pid=4912) 
    1582it [00:09, 162.49it/s]
    (TractActor pid=5332) 
    1622it [00:09, 176.00it/s]
    (TractActor pid=5325) 
    1968it [00:12, 209.98it/s]
    (TractActor pid=4912) 
    1599it [00:09, 163.09it/s]
    (TractActor pid=5332) 
    1643it [00:09, 181.53it/s]
    (TractActor pid=5325) 
    1990it [00:12, 207.28it/s]
    (TractActor pid=4912) 
    1622it [00:10, 175.19it/s]
    (TractActor pid=5332) 
    1662it [00:09, 179.82it/s]
    (TractActor pid=5325) 
    2012it [00:12, 210.77it/s]
    (TractActor pid=4912) 
    1643it [00:10, 180.86it/s]
    (TractActor pid=5332) 
    1681it [00:09, 175.93it/s]
    (TractActor pid=5325) 
    2036it [00:12, 216.67it/s]
    (TractActor pid=4912) 
    1662it [00:10, 178.98it/s]
    (TractActor pid=5332) 
    1699it [00:09, 170.82it/s]
    (TractActor pid=5325) 
    2059it [00:12, 212.90it/s]
    (TractActor pid=4912) 
    1680it [00:10, 178.02it/s]
    (TractActor pid=5332) 
    1717it [00:09, 169.08it/s]
    (TractActor pid=5325) 
    2083it [00:12, 220.35it/s]
    (TractActor pid=4912) 
    1698it [00:10, 168.47it/s]
    (TractActor pid=5332) 
    1735it [00:10, 170.50it/s]
    (TractActor pid=5325) 
    2107it [00:12, 225.79it/s]
    (TractActor pid=4912) 
    1715it [00:10, 167.95it/s]
    (TractActor pid=5332) 
    1753it [00:10, 171.81it/s]
    (TractActor pid=5325) 
    2132it [00:12, 231.95it/s]
    (TractActor pid=4912) 
    1732it [00:10, 167.29it/s]
    (TractActor pid=5332) 
    1774it [00:10, 181.48it/s]
    (TractActor pid=4912) 
    1750it [00:10, 170.25it/s]
    (TractActor pid=5332) 
    1793it [00:10, 174.80it/s]
    (TractActor pid=5325) 
    2156it [00:12, 215.18it/s]
    (TractActor pid=4912) 
    1770it [00:10, 177.71it/s]
    (TractActor pid=5332) 
    1812it [00:10, 177.82it/s]
    (TractActor pid=5325) 
    2178it [00:13, 208.46it/s]
    (TractActor pid=4912) 
    1789it [00:10, 177.71it/s]
    (TractActor pid=5332) 
    1830it [00:10, 176.58it/s]
    (TractActor pid=5325) 
    2200it [00:13, 206.42it/s]
    (TractActor pid=4912) 
    1808it [00:11, 180.90it/s]
    (TractActor pid=5332) 
    1848it [00:10, 172.35it/s]
    (TractActor pid=5325) 
    2223it [00:13, 211.61it/s]
    (TractActor pid=4912) 
    1827it [00:11, 176.86it/s]
    (TractActor pid=5332) 
    1867it [00:10, 174.32it/s]
    (TractActor pid=5325) 
    2245it [00:13, 189.42it/s]
    (TractActor pid=4912) 
    1845it [00:11, 173.62it/s]
    (TractActor pid=5332) 
    1885it [00:10, 170.43it/s]
    (TractActor pid=5325) 
    2271it [00:13, 205.95it/s]
    (TractActor pid=4912) 
    1863it [00:11, 175.36it/s]
    (TractActor pid=5325) 
    2293it [00:13, 205.98it/s]
    (TractActor pid=4912) 
    1881it [00:11, 174.70it/s]
    (TractActor pid=5332) 
    1903it [00:11, 128.24it/s]
    (TractActor pid=5325) 
    2320it [00:13, 220.86it/s]
    (TractActor pid=5332) 
    1921it [00:11, 138.45it/s]
    (TractActor pid=5325) 
    2343it [00:13, 212.45it/s]
    (TractActor pid=4912) 
    1899it [00:11, 132.62it/s]
    (TractActor pid=5332) 
    1941it [00:11, 152.08it/s]
    (TractActor pid=5325) 
    2367it [00:13, 217.91it/s]
    (TractActor pid=4912) 
    1918it [00:11, 145.33it/s]
    (TractActor pid=5332) 
    1960it [00:11, 161.26it/s]
    (TractActor pid=5325) 
    2390it [00:14, 215.40it/s]
    (TractActor pid=4912) 
    1934it [00:11, 148.65it/s]
    (TractActor pid=5332) 
    1978it [00:11, 166.10it/s]
    (TractActor pid=5325) 
    2414it [00:14, 220.11it/s]
    (TractActor pid=4912) 
    1953it [00:12, 158.06it/s]
    (TractActor pid=5332) 
    1996it [00:11, 156.40it/s]
    (TractActor pid=5325) 
    2438it [00:14, 225.06it/s]
    (TractActor pid=4912) 
    1971it [00:12, 163.91it/s]
    (TractActor pid=5332) 
    2016it [00:11, 166.88it/s]
    (TractActor pid=5325) 
    2461it [00:14, 221.79it/s]
    (TractActor pid=4912) 
    1989it [00:12, 162.22it/s]
    (TractActor pid=5332) 
    2034it [00:11, 168.56it/s]
    (TractActor pid=5325) 
    2486it [00:14, 228.85it/s]
    (TractActor pid=4912) 
    2006it [00:12, 162.80it/s]
    (TractActor pid=5332) 
    2052it [00:12, 169.05it/s]
    (TractActor pid=5325) 
    2510it [00:14, 231.27it/s]
    (TractActor pid=4912) 
    2024it [00:12, 166.88it/s]
    (TractActor pid=5332) 
    2070it [00:12, 167.50it/s]
    (TractActor pid=5325) 
    2537it [00:14, 238.95it/s]
    (TractActor pid=4912) 
    2041it [00:12, 167.34it/s]
    (TractActor pid=5332) 
    2088it [00:12, 169.41it/s]
    (TractActor pid=5325) 
    2561it [00:14, 234.64it/s]
    (TractActor pid=4912) 
    2058it [00:12, 164.01it/s]
    (TractActor pid=5332) 
    2107it [00:12, 175.12it/s]
    (TractActor pid=5325) 
    2587it [00:14, 237.76it/s]
    (TractActor pid=4912) 
    2077it [00:12, 170.94it/s]
    (TractActor pid=5332) 
    2125it [00:12, 175.66it/s]
    (TractActor pid=5325) 
    2611it [00:15, 222.37it/s]
    (TractActor pid=4912) 
    2095it [00:12, 168.32it/s]
    (TractActor pid=5332) 
    2143it [00:12, 174.72it/s]
    (TractActor pid=4912) 
    2115it [00:12, 177.16it/s]
    (TractActor pid=5325) 
    2634it [00:15, 171.87it/s]
    (TractActor pid=4912) 
    2134it [00:13, 178.96it/s]
    (TractActor pid=5332) 
    2161it [00:12, 161.46it/s]
    (TractActor pid=4912) 
    2152it [00:13, 164.27it/s]
    (TractActor pid=5332) 
    2182it [00:12, 172.88it/s]
    (TractActor pid=5325) 
    2653it [00:15, 165.04it/s]
    (TractActor pid=4912) 
    2169it [00:13, 158.28it/s]
    (TractActor pid=5332) 
    2200it [00:12, 163.00it/s]
    (TractActor pid=5325) 
    2675it [00:15, 176.58it/s]
    (TractActor pid=4912) 
    2186it [00:13, 151.47it/s]
    (TractActor pid=5332) 
    2220it [00:12, 169.56it/s]
    (TractActor pid=5325) 
    2701it [00:15, 196.84it/s]
    (TractActor pid=4912) 
    2203it [00:13, 156.21it/s]
    (TractActor pid=5332) 
    2238it [00:13, 146.43it/s]
    (TractActor pid=5325) 
    2726it [00:15, 207.70it/s]
    (TractActor pid=4912) 
    2222it [00:13, 164.61it/s]
    (TractActor pid=5332) 
    2255it [00:13, 150.95it/s]
    (TractActor pid=5325) 
    2750it [00:15, 214.05it/s]
    (TractActor pid=5332) 
    2273it [00:13, 158.15it/s]
    (TractActor pid=5325) 
    2774it [00:15, 220.63it/s]
    (TractActor pid=4912) 
    2239it [00:13, 143.68it/s]
    (TractActor pid=5332) 
    2290it [00:13, 159.63it/s]
    (TractActor pid=5325) 
    2797it [00:15, 216.33it/s]
    (TractActor pid=4912) 
    2256it [00:13, 144.93it/s]
    (TractActor pid=5332) 
    2315it [00:13, 183.59it/s]
    (TractActor pid=5325) 
    2820it [00:16, 197.98it/s]
    (TractActor pid=4912) 
    2275it [00:14, 155.54it/s]
    (TractActor pid=5332) 
    2334it [00:13, 176.59it/s]
    (TractActor pid=5325) 
    2845it [00:16, 210.23it/s]
    (TractActor pid=4912) 
    2291it [00:14, 154.73it/s]
    (TractActor pid=5332) 
    2354it [00:13, 180.73it/s]
    (TractActor pid=5325) 
    2867it [00:16, 208.02it/s]
    (TractActor pid=4912) 
    2312it [00:14, 167.69it/s]
    (TractActor pid=5325) 
    2893it [00:16, 218.64it/s]
    (TractActor pid=4912) 
    2330it [00:14, 165.23it/s]
    (TractActor pid=5332) 
    2373it [00:13, 168.41it/s]
    (TractActor pid=5325) 
    2919it [00:16, 229.90it/s]
    (TractActor pid=4912) 
    2348it [00:14, 168.62it/s]
    (TractActor pid=5332) 
    2391it [00:14, 170.12it/s]
    (TractActor pid=5325) 
    2943it [00:16, 230.05it/s]
    (TractActor pid=4912) 
    2366it [00:14, 166.15it/s]
    (TractActor pid=5332) 
    2409it [00:14, 169.84it/s]
    (TractActor pid=5325) 
    2967it [00:16, 231.51it/s]
    (TractActor pid=4912) 
    2383it [00:14, 159.83it/s]
    (TractActor pid=5332) 
    2431it [00:14, 183.30it/s]
    (TractActor pid=5325) 
    2991it [00:16, 223.88it/s]
    (TractActor pid=4912) 
    2403it [00:14, 170.98it/s]
    (TractActor pid=5332) 
    2450it [00:14, 172.86it/s]
    (TractActor pid=5325) 
    3014it [00:16, 214.72it/s]
    (TractActor pid=4912) 
    2421it [00:14, 172.28it/s]
    (TractActor pid=5332) 
    2468it [00:14, 174.09it/s]
    (TractActor pid=5325) 
    3038it [00:17, 221.67it/s]
    (TractActor pid=4912) 
    2439it [00:14, 173.83it/s]
    (TractActor pid=5332) 
    2487it [00:14, 174.34it/s]
    (TractActor pid=5325) 
    3061it [00:17, 221.92it/s]
    (TractActor pid=4912) 
    2457it [00:15, 169.77it/s]
    (TractActor pid=5332) 
    2507it [00:14, 180.67it/s]
    (TractActor pid=5325) 
    3085it [00:17, 224.61it/s]
    (TractActor pid=4912) 
    2477it [00:15, 175.52it/s]
    (TractActor pid=5332) 
    2528it [00:14, 187.51it/s]
    (TractActor pid=5325) 
    3112it [00:17, 235.90it/s]
    (TractActor pid=4912) 
    2495it [00:15, 172.35it/s]
    (TractActor pid=5332) 
    2547it [00:14, 185.03it/s]
    (TractActor pid=5325) 
    3137it [00:17, 238.27it/s]
    (TractActor pid=4912) 
    2515it [00:15, 179.00it/s]
    (TractActor pid=5332) 
    2566it [00:14, 178.93it/s]
    (TractActor pid=5325) 
    3164it [00:17, 246.63it/s]
    (TractActor pid=4912) 
    2536it [00:15, 186.82it/s]
    (TractActor pid=5332) 
    2586it [00:15, 184.68it/s]
    (TractActor pid=5325) 
    3189it [00:17, 242.06it/s]
    (TractActor pid=4912) 
    2557it [00:15, 181.49it/s]
    (TractActor pid=5332) 
    2605it [00:15, 164.14it/s]
    (TractActor pid=5325) 
    3214it [00:17, 238.19it/s]
    (TractActor pid=4912) 
    2576it [00:15, 183.29it/s]
    (TractActor pid=5332) 
    2626it [00:15, 173.71it/s]
    (TractActor pid=5325) 
    3238it [00:17, 233.84it/s]
    (TractActor pid=5325) 
    3262it [00:18, 232.85it/s]
    (TractActor pid=4912) 
    2595it [00:15, 170.91it/s]
    (TractActor pid=5325) 
    3286it [00:18, 216.96it/s]
    (TractActor pid=4912) 
    2613it [00:15, 168.34it/s]
    (TractActor pid=5332) 
    2644it [00:15, 127.84it/s]
    (TractActor pid=5325) 
    3309it [00:18, 219.00it/s]
    (TractActor pid=5332) 
    2659it [00:15, 126.12it/s]
    (TractActor pid=4912) 
    2630it [00:16, 126.55it/s]
    (TractActor pid=5332) 
    2678it [00:15, 140.07it/s]
    (TractActor pid=5325) 
    3332it [00:18, 210.12it/s]
    (TractActor pid=4912) 
    2645it [00:16, 128.99it/s]
    (TractActor pid=5332) 
    2699it [00:15, 156.42it/s]
    (TractActor pid=5325) 
    3357it [00:18, 219.06it/s]
    (TractActor pid=4912) 
    2660it [00:16, 129.86it/s]
    (TractActor pid=5332) 
    2719it [00:16, 163.91it/s]
    (TractActor pid=5325) 
    3380it [00:18, 218.06it/s]
    (TractActor pid=4912) 
    2679it [00:16, 144.04it/s]
    (TractActor pid=5332) 
    2737it [00:16, 167.81it/s]
    (TractActor pid=5325) 
    3402it [00:18, 211.66it/s]
    (TractActor pid=4912) 
    2700it [00:16, 159.01it/s]
    (TractActor pid=5332) 
    2755it [00:16, 168.27it/s]
    (TractActor pid=5325) 
    3425it [00:18, 214.77it/s]
    (TractActor pid=4912) 
    2719it [00:16, 165.53it/s]
    (TractActor pid=5332) 
    2775it [00:16, 173.74it/s]
    (TractActor pid=5325) 
    3454it [00:18, 231.41it/s]
    (TractActor pid=4912) 
    2737it [00:16, 169.03it/s]
    (TractActor pid=5332) 
    2793it [00:16, 175.21it/s]
    (TractActor pid=5325) 
    3478it [00:19, 230.76it/s]
    (TractActor pid=4912) 
    2755it [00:16, 168.88it/s]
    (TractActor pid=5332) 
    2811it [00:16, 157.59it/s]
    (TractActor pid=5325) 
    3502it [00:19, 219.65it/s]
    (TractActor pid=4912) 
    2775it [00:17, 174.44it/s]
    (TractActor pid=5332) 
    2831it [00:16, 167.59it/s]
    (TractActor pid=5325) 
    3526it [00:19, 224.54it/s]
    (TractActor pid=4912) 
    2793it [00:17, 175.63it/s]
    (TractActor pid=5332) 
    2851it [00:16, 174.73it/s]
    (TractActor pid=5325) 
    3549it [00:19, 221.25it/s]
    (TractActor pid=4912) 
    2811it [00:17, 157.31it/s]
    (TractActor pid=5332) 
    2869it [00:16, 168.35it/s]
    (TractActor pid=4912) 
    2831it [00:17, 167.36it/s]
    (TractActor pid=5332) 
    2891it [00:17, 178.31it/s]
    (TractActor pid=5325) 
    3572it [00:19, 151.22it/s]
    (TractActor pid=4912) 
    2851it [00:17, 174.48it/s]
    (TractActor pid=5332) 
    2911it [00:17, 183.43it/s]
    (TractActor pid=5325) 
    3594it [00:19, 164.59it/s]
    (TractActor pid=4912) 
    2869it [00:17, 168.87it/s]
    (TractActor pid=5332) 
    2930it [00:17, 178.73it/s]
    (TractActor pid=5325) 
    3620it [00:19, 186.12it/s]
    (TractActor pid=4912) 
    2891it [00:17, 178.57it/s]
    (TractActor pid=5332) 
    2949it [00:17, 181.59it/s]
    (TractActor pid=5325) 
    3645it [00:19, 200.84it/s]
    (TractActor pid=4912) 
    2911it [00:17, 183.62it/s]
    (TractActor pid=5332) 
    2968it [00:17, 179.11it/s]
    (TractActor pid=5325) 
    3669it [00:20, 207.36it/s]
    (TractActor pid=4912) 
    2930it [00:17, 178.55it/s]
    (TractActor pid=5332) 
    2986it [00:17, 172.84it/s]
    (TractActor pid=5325) 
    3692it [00:20, 206.84it/s]
    (TractActor pid=4912) 
    2949it [00:18, 181.20it/s]
    (TractActor pid=5325) 
    3714it [00:20, 208.87it/s]
    (TractActor pid=5332) 
    3004it [00:17, 166.14it/s]
    (TractActor pid=4912) 
    2968it [00:18, 178.62it/s]
    (TractActor pid=5325) 
    3737it [00:20, 213.60it/s]
    (TractActor pid=5332) 
    3021it [00:17, 163.82it/s]
    (TractActor pid=5325) 
    3759it [00:20, 209.05it/s]
    (TractActor pid=5332) 
    3040it [00:17, 171.08it/s]
    (TractActor pid=4912) 
    2986it [00:18, 172.31it/s]
    (TractActor pid=5325) 
    3784it [00:20, 218.70it/s]
    (TractActor pid=4912) 
    3004it [00:18, 165.52it/s]
    (TractActor pid=5332) 
    3058it [00:17, 168.05it/s]
    (TractActor pid=5325) 
    3807it [00:20, 214.89it/s]
    (TractActor pid=4912) 
    3021it [00:18, 163.23it/s]
    (TractActor pid=5332) 
    3077it [00:18, 173.87it/s]
    (TractActor pid=5325) 
    3831it [00:20, 221.21it/s]
    (TractActor pid=4912) 
    3040it [00:18, 170.42it/s]
    (TractActor pid=5332) 
    3098it [00:18, 179.54it/s]
    (TractActor pid=4912) 
    3058it [00:18, 167.77it/s]
    (TractActor pid=5332) 
    3117it [00:18, 182.08it/s]
    (TractActor pid=5325) 
    3854it [00:20, 214.29it/s]
    (TractActor pid=4912) 
    3077it [00:18, 173.03it/s]
    (TractActor pid=5332) 
    3136it [00:18, 181.66it/s]
    3155it [00:18, 183.58it/s]
    (TractActor pid=5325) 
    3876it [00:20, 214.64it/s]
    3900it [00:21, 220.93it/s]
    (TractActor pid=4912) 
    3098it [00:18, 178.93it/s]
    (TractActor pid=5332) 
    3175it [00:18, 186.31it/s]
    (TractActor pid=4912) 
    3117it [00:19, 181.91it/s]
    (TractActor pid=5332) 
    3194it [00:18, 184.54it/s]
    (TractActor pid=5325) 
    3926it [00:21, 226.85it/s]
    (TractActor pid=4912) 
    3136it [00:19, 182.22it/s]
    (TractActor pid=5325) 
    3949it [00:21, 223.60it/s]
    (TractActor pid=4912) 
    3155it [00:19, 183.97it/s]
    (TractActor pid=5332) 
    3213it [00:18, 180.68it/s]
    (TractActor pid=5325) 
    3973it [00:21, 223.41it/s]
    (TractActor pid=4912) 
    3175it [00:19, 186.58it/s]
    (TractActor pid=5332) 
    3232it [00:18, 178.95it/s]
    (TractActor pid=5325) 
    3996it [00:21, 223.88it/s]
    (TractActor pid=4912) 
    3194it [00:19, 184.40it/s]
    (TractActor pid=5332) 
    3250it [00:19, 177.39it/s]
    (TractActor pid=5325) 
    4020it [00:21, 224.61it/s]
    (TractActor pid=4912) 
    3213it [00:19, 180.44it/s]
    (TractActor pid=5332) 
    3268it [00:19, 175.34it/s]
    (TractActor pid=5325) 
    4043it [00:21, 210.94it/s]
    (TractActor pid=4912) 
    3232it [00:19, 178.83it/s]
    (TractActor pid=5332) 
    3286it [00:19, 167.41it/s]
    (TractActor pid=5325) 
    4067it [00:21, 217.01it/s]
    (TractActor pid=4912) 
    3250it [00:19, 177.37it/s]
    (TractActor pid=5332) 
    3305it [00:19, 172.14it/s]
    (TractActor pid=5325) 
    4089it [00:21, 214.66it/s]
    (TractActor pid=4912) 
    3268it [00:19, 175.43it/s]
    (TractActor pid=5332) 
    3323it [00:19, 165.77it/s]
    (TractActor pid=5325) 
    4112it [00:22, 217.53it/s]
    (TractActor pid=4912) 
    3286it [00:19, 167.23it/s]
    (TractActor pid=5332) 
    3340it [00:19, 163.51it/s]
    (TractActor pid=5325) 
    4134it [00:22, 209.53it/s]
    (TractActor pid=4912) 
    3305it [00:20, 171.55it/s]
    (TractActor pid=5332) 
    3359it [00:19, 168.77it/s]
    (TractActor pid=5325) 
    4156it [00:22, 201.71it/s]
    (TractActor pid=4912) 
    3323it [00:20, 165.13it/s]
    (TractActor pid=5332) 
    3377it [00:19, 168.36it/s]
    (TractActor pid=5325) 
    4177it [00:22, 202.36it/s]
    (TractActor pid=4912) 
    3340it [00:20, 163.07it/s]
    (TractActor pid=5332) 
    3394it [00:19, 161.33it/s]
    (TractActor pid=5325) 
    4201it [00:22, 210.75it/s]
    (TractActor pid=4912) 
    3359it [00:20, 168.33it/s]
    (TractActor pid=5332) 
    3413it [00:20, 166.43it/s]
    (TractActor pid=5325) 
    4223it [00:22, 209.66it/s]
    (TractActor pid=4912) 
    3377it [00:20, 167.97it/s]
    (TractActor pid=5332) 
    3430it [00:20, 166.64it/s]
    (TractActor pid=5325) 
    4245it [00:22, 204.47it/s]
    (TractActor pid=4912) 
    3394it [00:20, 160.94it/s]
    (TractActor pid=5332) 
    3452it [00:20, 177.91it/s]
    (TractActor pid=5325) 
    4266it [00:22, 200.72it/s]
    (TractActor pid=4912) 
    3413it [00:20, 165.64it/s]
    (TractActor pid=5332) 
    3470it [00:20, 176.28it/s]
    (TractActor pid=5325) 
    4290it [00:22, 209.06it/s]
    (TractActor pid=4912) 
    3430it [00:20, 165.79it/s]
    (TractActor pid=5332) 
    3489it [00:20, 175.56it/s]
    (TractActor pid=5325) 
    4311it [00:23, 208.78it/s]
    (TractActor pid=4912) 
    3452it [00:20, 177.14it/s]
    (TractActor pid=5332) 
    3507it [00:20, 164.33it/s]
    (TractActor pid=5325) 
    4338it [00:23, 225.28it/s]
    (TractActor pid=4912) 
    3470it [00:21, 175.89it/s]
    (TractActor pid=5332) 
    3526it [00:20, 170.44it/s]
    (TractActor pid=5325) 
    4363it [00:23, 232.40it/s]
    (TractActor pid=4912) 
    3489it [00:21, 175.64it/s]
    (TractActor pid=5332) 
    3544it [00:20, 170.59it/s]
    (TractActor pid=5325) 
    4387it [00:23, 220.01it/s]
    (TractActor pid=4912) 
    3507it [00:21, 164.69it/s]
    (TractActor pid=5325) 
    4413it [00:23, 229.39it/s]
    (TractActor pid=4912) 
    3527it [00:21, 172.32it/s]
    (TractActor pid=5325) 
    4437it [00:23, 220.41it/s]
    (TractActor pid=4912) 
    3545it [00:21, 173.41it/s]
    (TractActor pid=5332) 
    3562it [00:21, 113.88it/s]
    (TractActor pid=5325) 
    4462it [00:23, 228.57it/s]
    (TractActor pid=5332) 
    3580it [00:21, 126.71it/s]
    (TractActor pid=5325) 
    4490it [00:23, 242.01it/s]
    (TractActor pid=5332) 
    3596it [00:21, 134.01it/s]
    (TractActor pid=5325) 
    4518it [00:23, 251.32it/s]
    (TractActor pid=4912) 
    3563it [00:21, 117.97it/s]
    (TractActor pid=5332) 
    3618it [00:21, 154.14it/s]
    (TractActor pid=5325) 
    4544it [00:23, 248.37it/s]
    (TractActor pid=4912) 
    3580it [00:21, 129.11it/s]
    (TractActor pid=5332) 
    3638it [00:21, 164.63it/s]
    (TractActor pid=5325) 
    4570it [00:24, 250.33it/s]
    (TractActor pid=4912) 
    3596it [00:21, 135.27it/s]
    (TractActor pid=5332) 
    3659it [00:21, 174.72it/s]
    (TractActor pid=4912) 
    3617it [00:22, 153.06it/s]
    (TractActor pid=5332) 
    3678it [00:21, 165.32it/s]
    (TractActor pid=5325) 
    4596it [00:24, 228.51it/s]
    (TractActor pid=4912) 
    3638it [00:22, 164.97it/s]
    (TractActor pid=5332) 
    3696it [00:21, 167.02it/s]
    (TractActor pid=5325) 
    4621it [00:24, 225.70it/s]
    (TractActor pid=4912) 
    3659it [00:22, 175.03it/s]
    (TractActor pid=5332) 
    3714it [00:21, 163.08it/s]
    (TractActor pid=5325) 
    4644it [00:24, 218.22it/s]
    (TractActor pid=4912) 
    3678it [00:22, 165.65it/s]
    (TractActor pid=5332) 
    3732it [00:22, 165.94it/s]
    (TractActor pid=5325) 
    4669it [00:24, 225.83it/s]
    (TractActor pid=4912) 
    3696it [00:22, 167.13it/s]
    (TractActor pid=5332) 
    3749it [00:22, 161.50it/s]
    (TractActor pid=5325) 
    4693it [00:24, 228.63it/s]
    (TractActor pid=4912) 
    3714it [00:22, 162.84it/s]
    (TractActor pid=5332) 
    3768it [00:22, 168.19it/s]
    (TractActor pid=4912) 
    3731it [00:22, 164.29it/s]
    (TractActor pid=5332) 
    3786it [00:22, 168.22it/s]
    (TractActor pid=5325) 
    4717it [00:24, 161.89it/s]
    (TractActor pid=4912) 
    3748it [00:22, 161.41it/s]
    (TractActor pid=5332) 
    3803it [00:22, 164.74it/s]
    (TractActor pid=5325) 
    4740it [00:25, 176.72it/s]
    (TractActor pid=4912) 
    3766it [00:22, 165.18it/s]
    (TractActor pid=5332) 
    3821it [00:22, 166.96it/s]
    (TractActor pid=5325) 
    4761it [00:25, 178.46it/s]
    (TractActor pid=4912) 
    3784it [00:23, 168.34it/s]
    (TractActor pid=5325) 
    4785it [00:25, 193.16it/s]
    (TractActor pid=4912) 
    3801it [00:23, 168.39it/s]
    (TractActor pid=5332) 
    3841it [00:22, 169.57it/s]
    (TractActor pid=5325) 
    4810it [00:25, 204.28it/s]
    (TractActor pid=4912) 
    3818it [00:23, 166.25it/s]
    (TractActor pid=5332) 
    3858it [00:22, 164.09it/s]
    (TractActor pid=5325) 
    4832it [00:25, 207.03it/s]
    (TractActor pid=4912) 
    3838it [00:23, 175.15it/s]
    (TractActor pid=5332) 
    3875it [00:22, 163.91it/s]
    (TractActor pid=5325) 
    4856it [00:25, 214.52it/s]
    (TractActor pid=5332) 
    3892it [00:23, 165.44it/s]
    (TractActor pid=5325) 
    4879it [00:25, 214.05it/s]
    (TractActor pid=5332) 
    3911it [00:23, 171.74it/s]
    (TractActor pid=4912) 
    3856it [00:23, 162.98it/s]
    (TractActor pid=5332) 
    3930it [00:23, 177.01it/s]
    (TractActor pid=5325) 
    4902it [00:25, 214.42it/s]
    (TractActor pid=4912) 
    3873it [00:23, 161.44it/s]
    (TractActor pid=5332) 
    3948it [00:23, 174.64it/s]
    (TractActor pid=5325) 
    4925it [00:25, 217.11it/s]
    (TractActor pid=4912) 
    3890it [00:23, 162.87it/s]
    (TractActor pid=5332) 
    3966it [00:23, 172.43it/s]
    (TractActor pid=5325) 
    4948it [00:25, 219.90it/s]
    (TractActor pid=4912) 
    3909it [00:23, 170.14it/s]
    (TractActor pid=4912) 
    3928it [00:23, 175.45it/s]
    (TractActor pid=5332) 
    3984it [00:23, 173.66it/s]
    (TractActor pid=5325) 
    4971it [00:26, 211.58it/s]
    (TractActor pid=4912) 
    3946it [00:24, 174.91it/s]
    (TractActor pid=5325) 
    4995it [00:26, 216.69it/s]
    (TractActor pid=5332) 
    4002it [00:23, 169.21it/s]
    (TractActor pid=5325) 
    5020it [00:26, 218.28it/s]
    (TractActor pid=5332) 
    4020it [00:23, 170.48it/s]
    (TractActor pid=4912) 
    3964it [00:24, 169.39it/s]
    (TractActor pid=5325) 
    5042it [00:26, 207.56it/s]
    (TractActor pid=4912) 
    3983it [00:24, 173.68it/s]
    (TractActor pid=5332) 
    4038it [00:23, 159.20it/s]
    (TractActor pid=5325) 
    5066it [00:26, 213.75it/s]
    (TractActor pid=4912) 
    4001it [00:24, 169.75it/s]
    (TractActor pid=5332) 
    4058it [00:23, 168.01it/s]
    (TractActor pid=5325) 
    5088it [00:26, 211.59it/s]
    (TractActor pid=4912) 
    4020it [00:24, 170.63it/s]
    (TractActor pid=5332) 
    4075it [00:24, 162.60it/s]
    (TractActor pid=5325) 
    5111it [00:26, 215.30it/s]
    (TractActor pid=4912) 
    4038it [00:24, 159.15it/s]
    (TractActor pid=5332) 
    4092it [00:24, 164.32it/s]
    (TractActor pid=5325) 
    5138it [00:26, 229.82it/s]
    (TractActor pid=4912) 
    4058it [00:24, 167.73it/s]
    (TractActor pid=5332) 
    4110it [00:24, 166.21it/s]
    (TractActor pid=5325) 
    5162it [00:26, 229.21it/s]
    (TractActor pid=4912) 
    4075it [00:24, 162.47it/s]
    (TractActor pid=5332) 
    4127it [00:24, 158.02it/s]
    (TractActor pid=5325) 
    5186it [00:27, 229.78it/s]
    (TractActor pid=4912) 
    4092it [00:24, 164.39it/s]
    (TractActor pid=5332) 
    4144it [00:24, 159.56it/s]
    (TractActor pid=5325) 
    5213it [00:27, 241.23it/s]
    (TractActor pid=4912) 
    4110it [00:25, 166.43it/s]
    (TractActor pid=5332) 
    4161it [00:24, 157.19it/s]
    (TractActor pid=5325) 
    5238it [00:27, 237.76it/s]
    (TractActor pid=4912) 
    4127it [00:25, 158.12it/s]
    (TractActor pid=5332) 
    4177it [00:24, 151.61it/s]
    (TractActor pid=5325) 
    5262it [00:27, 232.65it/s]
    (TractActor pid=4912) 
    4144it [00:25, 159.67it/s]
    (TractActor pid=5332) 
    4196it [00:24, 160.75it/s]
    (TractActor pid=5325) 
    5288it [00:27, 237.39it/s]
    (TractActor pid=4912) 
    4161it [00:25, 157.13it/s]
    (TractActor pid=5332) 
    4215it [00:24, 167.16it/s]
    (TractActor pid=5325) 
    5312it [00:27, 233.63it/s]
    (TractActor pid=4912) 
    4177it [00:25, 151.76it/s]
    (TractActor pid=5332) 
    4232it [00:25, 162.63it/s]
    (TractActor pid=5325) 
    5336it [00:27, 234.80it/s]
    (TractActor pid=4912) 
    4196it [00:25, 160.71it/s]
    (TractActor pid=5332) 
    4249it [00:25, 152.17it/s]
    (TractActor pid=5325) 
    5364it [00:27, 241.19it/s]
    (TractActor pid=4912) 
    4215it [00:25, 166.80it/s]
    (TractActor pid=5332) 
    4265it [00:25, 149.94it/s]
    (TractActor pid=5325) 
    5389it [00:27, 239.42it/s]
    (TractActor pid=4912) 
    4232it [00:25, 162.18it/s]
    (TractActor pid=5332) 
    4283it [00:25, 157.34it/s]
    (TractActor pid=5332) 
    4301it [00:25, 162.69it/s]
    (TractActor pid=5325) 
    5413it [00:28, 222.07it/s]
    (TractActor pid=4912) 
    4249it [00:25, 151.79it/s]
    (TractActor pid=5332) 
    4318it [00:25, 162.51it/s]
    (TractActor pid=5325) 
    5436it [00:28, 223.88it/s]
    (TractActor pid=4912) 
    4265it [00:26, 149.60it/s]
    (TractActor pid=5332) 
    4339it [00:25, 175.69it/s]
    (TractActor pid=5325) 
    5461it [00:28, 229.55it/s]
    (TractActor pid=4912) 
    4283it [00:26, 156.99it/s]
    (TractActor pid=5332) 
    4359it [00:25, 182.22it/s]
    (TractActor pid=5325) 
    5487it [00:28, 235.87it/s]
    (TractActor pid=4912) 
    4301it [00:26, 162.51it/s]
    (TractActor pid=5325) 
    5512it [00:28, 239.83it/s]
    (TractActor pid=4912) 
    4318it [00:26, 162.36it/s]
    (TractActor pid=5332) 
    4378it [00:25, 170.56it/s]
    (TractActor pid=5325) 
    5537it [00:28, 233.82it/s]
    (TractActor pid=4912) 
    4339it [00:26, 175.66it/s]
    (TractActor pid=5332) 
    4399it [00:26, 178.38it/s]
    (TractActor pid=5325) 
    5561it [00:28, 228.05it/s]
    (TractActor pid=4912) 
    4359it [00:26, 181.89it/s]
    (TractActor pid=5332) 
    4418it [00:26, 173.92it/s]
    (TractActor pid=5325) 
    5590it [00:28, 242.90it/s]
    (TractActor pid=4912) 
    4378it [00:26, 170.16it/s]
    (TractActor pid=5332) 
    4436it [00:26, 167.78it/s]
    (TractActor pid=5325) 
    5615it [00:28, 244.65it/s]
    (TractActor pid=4912) 
    4399it [00:26, 177.78it/s]
    (TractActor pid=5332) 
    4456it [00:26, 175.82it/s]
    (TractActor pid=5325) 
    5640it [00:29, 216.26it/s]
    (TractActor pid=4912) 
    4417it [00:26, 172.74it/s]
    (TractActor pid=5332) 
    4477it [00:26, 182.97it/s]
    (TractActor pid=5325) 
    5663it [00:29, 216.27it/s]
    (TractActor pid=4912) 
    4435it [00:26, 167.14it/s]
    (TractActor pid=5332) 
    4499it [00:26, 192.76it/s]
    (TractActor pid=5325) 
    5687it [00:29, 222.62it/s]
    (TractActor pid=4912) 
    4455it [00:27, 174.30it/s]
    (TractActor pid=5332) 
    4519it [00:26, 194.70it/s]
    (TractActor pid=5325) 
    5713it [00:29, 232.23it/s]
    (TractActor pid=4912) 
    4476it [00:27, 183.41it/s]
    (TractActor pid=5332) 
    4539it [00:26, 187.79it/s]
    (TractActor pid=5325) 
    5737it [00:29, 231.73it/s]
    (TractActor pid=4912) 
    4497it [00:27, 190.06it/s]
    (TractActor pid=5332) 
    4559it [00:26, 190.34it/s]
    (TractActor pid=5325) 
    5761it [00:29, 230.53it/s]
    (TractActor pid=4912) 
    4518it [00:27, 194.11it/s]
    (TractActor pid=5332) 
    4579it [00:27, 188.01it/s]
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    Optimizing level 2 [max iter: 10000]
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    Optimizing level 0 [max iter: 100]

    '/home/runner/AFQ_data/stanford_hardi/derivatives/afq/sub-01/sub-01_ses-01_desc-profiles_tractography.csv'



.. GENERATED FROM PYTHON SOURCE LINES 181-199

Visualizing the bundles and calculating tract profiles:
-----------------------------------------------------
The pyAFQ API provides several ways to visualize bundles and profiles.

First, we will run a function that exports an html file that contains
an interactive visualization of the bundles that are segmented.

.. note::
   By default we resample a 100 points within a bundle, however to reduce
   processing time we will only resample 50 points.

Once it is done running, it should pop a browser window open and let you
interact with the bundles.

.. note::
   You can hide or show a bundle by clicking the legend, or select a
   single bundle by double clicking the legend. The interactive
   visualization will also all you to pan, zoom, and rotate.

.. GENERATED FROM PYTHON SOURCE LINES 199-203

.. code-block:: Python


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




.. raw:: html
    :file: images/sphx_glr_plot_002_participant_afq_api_002.html





.. GENERATED FROM PYTHON SOURCE LINES 204-209

We can also visualize the tract profiles in all of the bundles. These
plots show both FA (left) and MD (right) layed out anatomically.
To make this plot, it is required that you install with
``pip install pyAFQ[plot]`` so that you have the necessary dependencies.


.. GENERATED FROM PYTHON SOURCE LINES 209-212

.. code-block:: Python


    fig_files = myafq.export("tract_profile_plots")





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

 .. code-block:: none


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.. GENERATED FROM PYTHON SOURCE LINES 213-215

.. figure:: {{ fig_files[0] }}



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

   **Total running time of the script:** (10 minutes 50.558 seconds)

**Estimated memory usage:**  1671 MB


.. _sphx_glr_download_tutorials_tutorial_examples_plot_002_participant_afq_api.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_002_participant_afq_api.ipynb <plot_002_participant_afq_api.ipynb>`

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

      :download:`Download Python source code: plot_002_participant_afq_api.py <plot_002_participant_afq_api.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_002_participant_afq_api.zip <plot_002_participant_afq_api.zip>`


.. only:: html

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

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