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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_run_ets_rss_marker.py:


Extracting root sum of squares from edge-wise timeseries.
=========================================================
This example uses a ``RSSETSMarker`` to compute root sum of squares
of the edge-wise timeseries using the Schaefer parcellation
(100 rois and 200 rois, 17 Yeo networks) for a 4D nifti BOLD file.

Authors: Leonard Sasse, Sami Hamdan, Nicolas Nieto, Synchon Mandal

License: BSD 3 clause

.. GENERATED FROM PYTHON SOURCE LINES 14-23

.. code-block:: Python


    import tempfile

    import junifer.testing.registry  # noqa: F401
    from junifer.api import collect, run
    from junifer.storage import SQLiteFeatureStorage
    from junifer.utils import configure_logging









.. GENERATED FROM PYTHON SOURCE LINES 24-25

Set the logging level to info to see extra information:

.. GENERATED FROM PYTHON SOURCE LINES 25-27

.. code-block:: Python

    configure_logging(level="INFO")





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

 .. code-block:: none

    2025-11-18 17:36:19 [info     ] ===== Lib Versions =====       [junifer]
    2025-11-18 17:36:19 [info     ] click: 8.1.8                   [junifer]
    2025-11-18 17:36:19 [info     ] numpy: 1.26.4                  [junifer]
    2025-11-18 17:36:19 [info     ] scipy: 1.15.0                  [junifer]
    2025-11-18 17:36:19 [info     ] datalad: 1.1.6                 [junifer]
    2025-11-18 17:36:19 [info     ] pandas: 2.1.4                  [junifer]
    2025-11-18 17:36:19 [info     ] nibabel: 5.3.2                 [junifer]
    2025-11-18 17:36:19 [info     ] nilearn: 0.10.4                [junifer]
    2025-11-18 17:36:19 [info     ] sqlalchemy: 2.0.44             [junifer]
    2025-11-18 17:36:19 [info     ] ruamel.yaml: 0.18.16           [junifer]
    2025-11-18 17:36:19 [info     ] tqdm: 4.66.6                   [junifer]
    2025-11-18 17:36:19 [info     ] templateflow: 24.2.2           [junifer]
    2025-11-18 17:36:19 [info     ] junifer_data: None             [junifer]
    2025-11-18 17:36:19 [info     ] junifer: 0.0.7.dev401          [junifer]
    2025-11-18 17:36:19 [info     ] ========================       [junifer]




.. GENERATED FROM PYTHON SOURCE LINES 28-29

Define the DataGrabber interface

.. GENERATED FROM PYTHON SOURCE LINES 29-33

.. code-block:: Python

    datagrabber = {
        "kind": "SPMAuditoryTestingDataGrabber",
    }








.. GENERATED FROM PYTHON SOURCE LINES 34-35

Define the markers interface

.. GENERATED FROM PYTHON SOURCE LINES 35-48

.. code-block:: Python

    markers = [
        {
            "name": "Schaefer100x17_RSSETS",
            "kind": "RSSETSMarker",
            "parcellation": ["Schaefer100x17"],
        },
        {
            "name": "Schaefer200x17_RSSETS",
            "kind": "RSSETSMarker",
            "parcellation": ["Schaefer200x17"],
        },
    ]








.. GENERATED FROM PYTHON SOURCE LINES 49-51

Create a temporary directory for junifer feature extraction:
At the end you can read the extracted data into a ``pandas.DataFrame``.

.. GENERATED FROM PYTHON SOURCE LINES 51-75

.. code-block:: Python

    with tempfile.TemporaryDirectory() as tmpdir:
        # Define the storage interface
        storage = {
            "kind": "SQLiteFeatureStorage",
            "uri": f"{tmpdir}/test.sqlite",
        }
        # Run the defined junifer feature extraction pipeline
        run(
            workdir=tmpdir,
            datagrabber=datagrabber,
            markers=markers,
            storage=storage,
            elements=["sub001"],  # we calculate for one subject only
        )
        # Collect extracted features data
        collect(storage=storage)
        # Create storage object to read in extracted features
        db = SQLiteFeatureStorage(uri=storage["uri"])

        # List all the features
        print(db.list_features())
        # Read extracted features
        df_rssets = db.read_df(feature_name="BOLD_Schaefer200x17_RSSETS_rss_ets")





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

 .. code-block:: none

    2025-11-18 17:36:19 [info     ] Registering RSSETSMarker in marker [junifer]
    2025-11-18 17:36:19 [info     ] Validating Marker Collection   [junifer]
    2025-11-18 17:36:19 [info     ] DataGrabber output type: ['BOLD', 'T1w'] [junifer]
    2025-11-18 17:36:19 [info     ] Validating Data Reader:        [junifer]
    2025-11-18 17:36:19 [info     ] Data Reader output type: ['BOLD', 'T1w'] [junifer]
    2025-11-18 17:36:19 [info     ] Validating Marker: Schaefer100x17_RSSETS [junifer]
    2025-11-18 17:36:19 [info     ] Marker output type: [<StorageType.Timeseries: 'timeseries'>] [junifer]
    2025-11-18 17:36:19 [info     ] Validating storage for Schaefer100x17_RSSETS [junifer]
    2025-11-18 17:36:19 [info     ] Validating Marker: Schaefer200x17_RSSETS [junifer]
    2025-11-18 17:36:19 [info     ] Marker output type: [<StorageType.Timeseries: 'timeseries'>] [junifer]
    2025-11-18 17:36:19 [info     ] Validating storage for Schaefer200x17_RSSETS [junifer]
    2025-11-18 17:36:19 [info     ] Getting element ('sub001',)    [junifer]

    Dataset created in /github/home/nilearn_data/spm_auditory

    Data absent, downloading...
    Downloading data from https://www.fil.ion.ucl.ac.uk/spm/download/data/MoAEpilot/MoAEpilot.zip ...

    Downloaded 1286144 of 34212021 bytes (3.8%,   26.8s remaining)
    Downloaded 6463488 of 34212021 bytes (18.9%,    8.9s remaining)
    Downloaded 11272192 of 34212021 bytes (32.9%,    6.3s remaining)
    Downloaded 16375808 of 34212021 bytes (47.9%,    4.5s remaining)
    Downloaded 21626880 of 34212021 bytes (63.2%,    3.0s remaining)
    Downloaded 26968064 of 34212021 bytes (78.8%,    1.7s remaining)
    Downloaded 32358400 of 34212021 bytes (94.6%,    0.4s remaining) ...done. (9 seconds, 0 min)
    Extracting data from /github/home/nilearn_data/spm_auditory/sub001/MoAEpilot.zip..... done.
    2025-11-18 17:36:30 [info     ] Fitting pipeline               [junifer]
    2025-11-18 17:36:30 [info     ] Reading BOLD from /tmp/tmpf7c8v3r_/sub001_bold.nii.gz [junifer]
    2025-11-18 17:36:30 [info     ] BOLD is of type NIFTI          [junifer]
    2025-11-18 17:36:30 [info     ] Reading T1w from /tmp/tmpf7c8v3r_/sub001_T1w.nii.gz [junifer]
    2025-11-18 17:36:30 [info     ] T1w is of type NIFTI           [junifer]
    2025-11-18 17:36:30 [info     ] Fitting marker Schaefer100x17_RSSETS [junifer]
    2025-11-18 17:36:30 [info     ] Computing DataType.BOLD        [junifer]
    2025-11-18 17:36:30 [info     ] Parcellation will be warped from MNI152NLin6Asym to MNI152Lin using highest resolution [junifer]
    2025-11-18 17:36:30 [info     ] Parcellation parameters:       [junifer]
    2025-11-18 17:36:30 [info     ]         resolution: None              [junifer]
    2025-11-18 17:36:30 [info     ]         n_rois: 100                   [junifer]
    2025-11-18 17:36:30 [info     ]         yeo_networks: 17              [junifer]
    2025-11-18 17:36:30 [info     ] Resolution set to None, using highest resolution. [junifer]
    2025-11-18 17:36:31 [info     ] Start annex operation          [datalad.annex] dlm_progress=annexprogress-139689173937296 dlm_progress_label=Total dlm_progress_noninteractive_level=5 dlm_progress_total=233863 dlm_progress_unit=' Bytes'
    2025-11-18 17:36:32 [info     ] Start annex action: {'command': 'get', 'file': 'parcellations/Schaefer2018/Yeo2011/Schaefer2018_100Parcels_17Networks_order_FSLMNI152_1mm.nii.gz', 'input': ['parcellations/Schaefer2018/Yeo2011/Schaefer2018_100Parcels_17Networks_order_FSLMNI152_1mm.nii.gz'], 'key': 'MD5E-s233863--52fdf9073096aa55b7196e41619442bb.nii.gz', 'note': 'from gin-src...'} [datalad.annex] dlm_progress=annexprogress-139689173937296-6360479011626891260 dlm_progress_label='Get parcella .. 2_1mm.nii.gz' dlm_progress_noninteractive_level=5 dlm_progress_total=233863.0 dlm_progress_unit=' Bytes'
    2025-11-18 17:36:32 [info     ] 35.03%                         [datalad.annex] dlm_progress=annexprogress-139689173937296-6360479011626891260 dlm_progress_noninteractive_level=5 dlm_progress_update=81920.0
    2025-11-18 17:36:33 [info     ] 63.05%                         [datalad.annex] dlm_progress=annexprogress-139689173937296-6360479011626891260 dlm_progress_noninteractive_level=5 dlm_progress_update=147456.0
    2025-11-18 17:36:33 [info     ] Finished annex action: None    [datalad.annex] dlm_progress=annexprogress-139689173937296-6360479011626891260 dlm_progress_noninteractive_level=5
    2025-11-18 17:36:33 [info     ] Finished annex get             [datalad.annex] dlm_progress=annexprogress-139689173937296 dlm_progress_noninteractive_level=5
    2025-11-18 17:36:33 [info     ] Loading parcellation: /github/home/junifer_data/v5/parcellations/Schaefer2018/Yeo2011/Schaefer2018_100Parcels_17Networks_order_FSLMNI152_1mm.nii.gz [junifer]
    2025-11-18 17:36:35 [info     ] Downloading template MNI152Lin (T1w in resolution 1) [junifer]
    2025-11-18 17:36:36 [info     ] antsApplyTransforms command to be executed:
    antsApplyTransforms -d 3 -e 3 -n 'GenericLabel[NearestNeighbor]' -i /tmp/tmpsmu00wqv/ants_parcellation_warper_Schaefer100x17_from_MNI152NLin6Asym_to_MNI152Lin_2011a2a2-c4a5-11f0-a26b-be2f509f929d55fq4q0p/prewarp_parcellation.nii.gz -r /tmp/tmpsmu00wqv/ants_parcellation_warper_Schaefer100x17_from_MNI152NLin6Asym_to_MNI152Lin_2011a2a2-c4a5-11f0-a26b-be2f509f929d55fq4q0p/MNI152Lin_T1w.nii.gz -t /github/home/junifer_data/v5/.git/annex/objects/JQ/Pp/SHA256E-s145422752--5091350b36f951d455dabd429ebe86c493c75a0217dca311ae355f1d62e080b0.h5/SHA256E-s145422752--5091350b36f951d455dabd429ebe86c493c75a0217dca311ae355f1d62e080b0.h5 -o /tmp/tmpsmu00wqv/ants_parcellation_warper_Schaefer100x17_from_MNI152NLin6Asym_to_MNI152Lin_2011a2a2-c4a5-11f0-a26b-be2f509f929d55fq4q0p/parcellation_warped.nii.gz [junifer]
    2025-11-18 17:36:42 [info     ] antsApplyTransforms command succeeded with the following output:
     [junifer]
    2025-11-18 17:36:45 [info     ] Storing in <SQLiteFeatureStorage @ /tmp/tmpee2ytr3a/test.sqlite (multiple output)> [junifer]
    2025-11-18 17:36:45 [info     ] Fitting marker Schaefer200x17_RSSETS [junifer]
    2025-11-18 17:36:45 [info     ] Computing DataType.BOLD        [junifer]
    2025-11-18 17:36:45 [info     ] Parcellation will be warped from MNI152NLin6Asym to MNI152Lin using highest resolution [junifer]
    2025-11-18 17:36:45 [info     ] Parcellation parameters:       [junifer]
    2025-11-18 17:36:45 [info     ]         resolution: None              [junifer]
    2025-11-18 17:36:45 [info     ]         n_rois: 200                   [junifer]
    2025-11-18 17:36:45 [info     ]         yeo_networks: 17              [junifer]
    2025-11-18 17:36:45 [info     ] Resolution set to None, using highest resolution. [junifer]
    2025-11-18 17:36:45 [info     ] Start annex operation          [datalad.annex] dlm_progress=annexprogress-139689188835696 dlm_progress_label=Total dlm_progress_noninteractive_level=5 dlm_progress_total=259405 dlm_progress_unit=' Bytes'
    2025-11-18 17:36:46 [info     ] Start annex action: {'command': 'get', 'file': 'parcellations/Schaefer2018/Yeo2011/Schaefer2018_200Parcels_17Networks_order_FSLMNI152_1mm.nii.gz', 'input': ['parcellations/Schaefer2018/Yeo2011/Schaefer2018_200Parcels_17Networks_order_FSLMNI152_1mm.nii.gz'], 'key': 'MD5E-s259405--74b10470e93053e255b8dad06d00c9c4.nii.gz', 'note': 'from gin-src...'} [datalad.annex] dlm_progress=annexprogress-139689188835696--117506222202749244 dlm_progress_label='Get parcella .. 2_1mm.nii.gz' dlm_progress_noninteractive_level=5 dlm_progress_total=259405.0 dlm_progress_unit=' Bytes'
    2025-11-18 17:36:46 [info     ] 12.63%                         [datalad.annex] dlm_progress=annexprogress-139689188835696--117506222202749244 dlm_progress_noninteractive_level=5 dlm_progress_update=32768.0
    2025-11-18 17:36:47 [info     ] 72.63%                         [datalad.annex] dlm_progress=annexprogress-139689188835696--117506222202749244 dlm_progress_noninteractive_level=5 dlm_progress_update=188416.0
    2025-11-18 17:36:47 [info     ] Finished annex action: None    [datalad.annex] dlm_progress=annexprogress-139689188835696--117506222202749244 dlm_progress_noninteractive_level=5
    2025-11-18 17:36:47 [info     ] Finished annex get             [datalad.annex] dlm_progress=annexprogress-139689188835696 dlm_progress_noninteractive_level=5
    2025-11-18 17:36:47 [info     ] Loading parcellation: /github/home/junifer_data/v5/parcellations/Schaefer2018/Yeo2011/Schaefer2018_200Parcels_17Networks_order_FSLMNI152_1mm.nii.gz [junifer]
    2025-11-18 17:36:49 [info     ] Downloading template MNI152Lin (T1w in resolution 1) [junifer]
    2025-11-18 17:36:50 [info     ] antsApplyTransforms command to be executed:
    antsApplyTransforms -d 3 -e 3 -n 'GenericLabel[NearestNeighbor]' -i /tmp/tmpsmu00wqv/ants_parcellation_warper_Schaefer200x17_from_MNI152NLin6Asym_to_MNI152Lin_288c7e5c-c4a5-11f0-a26b-be2f509f929dzn4hbpck/prewarp_parcellation.nii.gz -r /tmp/tmpsmu00wqv/ants_parcellation_warper_Schaefer200x17_from_MNI152NLin6Asym_to_MNI152Lin_288c7e5c-c4a5-11f0-a26b-be2f509f929dzn4hbpck/MNI152Lin_T1w.nii.gz -t /github/home/junifer_data/v5/.git/annex/objects/JQ/Pp/SHA256E-s145422752--5091350b36f951d455dabd429ebe86c493c75a0217dca311ae355f1d62e080b0.h5/SHA256E-s145422752--5091350b36f951d455dabd429ebe86c493c75a0217dca311ae355f1d62e080b0.h5 -o /tmp/tmpsmu00wqv/ants_parcellation_warper_Schaefer200x17_from_MNI152NLin6Asym_to_MNI152Lin_288c7e5c-c4a5-11f0-a26b-be2f509f929dzn4hbpck/parcellation_warped.nii.gz [junifer]
    2025-11-18 17:37:01 [info     ] antsApplyTransforms command succeeded with the following output:
     [junifer]
    2025-11-18 17:37:04 [info     ] Storing in <SQLiteFeatureStorage @ /tmp/tmpee2ytr3a/test.sqlite (multiple output)> [junifer]
    2025-11-18 17:37:04 [info     ] Marker collection fitting done [junifer]
    2025-11-18 17:37:04 [info     ] Collecting data using SQLiteFeatureStorage [junifer]
    2025-11-18 17:37:04 [info     ] Collecting data from /tmp/tmpee2ytr3a/*test.sqlite [junifer]

    file: 0it [00:00, ?it/s]

    feature:   0%|          | 0/2 [00:00<?, ?it/s]
    feature: 100%|██████████| 2/2 [00:00<00:00, 66.46it/s]

    file: 1it [00:00, 21.90it/s]
    2025-11-18 17:37:04 [info     ] Collect done                   [junifer]
    {'38b29577c909f6d3e33a149f319d5ccc': {'datagrabber': {'class': 'SPMAuditoryTestingDataGrabber', 'types': ['BOLD', 'T1w']}, 'dependencies': {'nilearn': '0.10.4'}, 'datareader': {'class': 'DefaultDataReader'}, 'type': 'BOLD', 'marker': {'agg_method': 'mean', 'agg_method_params': None, 'class': 'RSSETSMarker', 'masks': None, 'name': 'Schaefer100x17_RSSETS_rss_ets', 'on': ['BOLD'], 'parcellation': ['Schaefer100x17']}, '_element_keys': ['subject'], 'name': 'BOLD_Schaefer100x17_RSSETS_rss_ets'}, 'ed76fd21eaeade9503b38ec7767d4759': {'datagrabber': {'class': 'SPMAuditoryTestingDataGrabber', 'types': ['BOLD', 'T1w']}, 'dependencies': {'nilearn': '0.10.4'}, 'datareader': {'class': 'DefaultDataReader'}, 'type': 'BOLD', 'marker': {'agg_method': 'mean', 'agg_method_params': None, 'class': 'RSSETSMarker', 'masks': None, 'name': 'Schaefer200x17_RSSETS_rss_ets', 'on': ['BOLD'], 'parcellation': ['Schaefer200x17']}, '_element_keys': ['subject'], 'name': 'BOLD_Schaefer200x17_RSSETS_rss_ets'}}




.. GENERATED FROM PYTHON SOURCE LINES 76-77

Now we take a look at the dataframe

.. GENERATED FROM PYTHON SOURCE LINES 77-78

.. code-block:: Python

    df_rssets.head()





.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th></th>
          <th>root_sum_of_squares_ets</th>
        </tr>
        <tr>
          <th>subject</th>
          <th>timepoint</th>
          <th></th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th rowspan="5" valign="top">sub001</th>
          <th>0</th>
          <td>2502.888057</td>
        </tr>
        <tr>
          <th>1</th>
          <td>168.174038</td>
        </tr>
        <tr>
          <th>2</th>
          <td>102.849715</td>
        </tr>
        <tr>
          <th>3</th>
          <td>132.639660</td>
        </tr>
        <tr>
          <th>4</th>
          <td>109.615993</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />


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

   **Total running time of the script:** (0 minutes 44.750 seconds)


.. _sphx_glr_download_auto_examples_run_ets_rss_marker.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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