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Test collection on real data.
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.github/workflows/build-test-publish.yml

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@@ -184,6 +184,11 @@ jobs:
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datalad update -r --merge -d hcph-pilot_fieldmaps/
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datalad get -r -J 2 -d hcph-pilot_fieldmaps/ hcph-pilot_fieldmaps/*
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# ds005250
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datalad install -r https://gin.g-node.org/tsalo/ds005250-sdcflows.git
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datalad update -r --merge -d ds005250-sdcflows/
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datalad get -r -J 2 -d ds005250-sdcflows/ ds005250-sdcflows/sub-04/ses-2/
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- name: Set FreeSurfer variables
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run: |
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echo "FREESURFER_HOME=$HOME/.cache/freesurfer" >> $GITHUB_ENV

sdcflows/utils/wrangler.py

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@@ -321,6 +321,15 @@ def find_estimators(
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FieldmapEstimation(sources=<2 files>, method=<EstimatorType.ANAT: 5>,
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bids_id='auto_...')]
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>>> find_estimators(
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... layout=layouts['ds005250-sdcflows'],
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... subject='04',
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... fmapless=False,
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... force_fmapless=False,
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... bids_filters={'session': '2'},
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... ) # doctest: +ELLIPSIS
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[FieldmapEstimation(sources=<10 files>, method=<EstimatorType.MEDIC: 6>,
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bids_id='auto_...')]
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"""
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from .misc import create_logger
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from bids.layout import Query

sdcflows/workflows/fit/medic.py

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@@ -70,11 +70,17 @@ def init_medic_wf(name="medic_wf"):
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-----
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This workflow performs minimal preparation before running the MEDIC algorithm,
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as implemented in ``vandandrew/warpkit``.
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Any downstream processing piplines that use this workflow should include
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the following references in their boilerplate BibTeX file:
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- medic: https://doi.org/10.1101/2023.11.28.568744
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"""
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workflow = Workflow(name=name)
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workflow.__desc__ = """\
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A dynamic fieldmap was estimated from multi-echo EPI data using the MEDIC algorithm (@medic).
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Volume-wise *B<sub>0</sub>* nonuniformity maps (or *fieldmaps*) were estimated from
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complex-valued, multi-echo EPI data using the MEDIC algorithm (@medic).
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"""
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inputnode = pe.Node(niu.IdentityInterface(fields=INPUT_FIELDS), name="inputnode")

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