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Apply transforms to raw data when MNI6 derivatives aren't available (#58)
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‎.github/ISSUE_TEMPLATE/bug_report.yml

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name: Bug Report
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description: File a report of a problem you encountered.
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labels: ["bug"]
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body:
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- type: markdown
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attributes:
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value: |
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# Thanks for taking the time to fill out this bug report!
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### The following information will help us in getting your issue resolved.
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- type: textarea
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id: what-happened
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attributes:
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label: What happened?
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description: A short description of what went wrong.
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validations:
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required: true
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- type: textarea
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id: command
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attributes:
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label: What command did you use?
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description: |
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If you're using `fmriprep-docker`, please include the `RUNNING: ...` line that is printed first.
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This helps us replicate the problem. This will be automatically formatted into code, so no need for backticks.
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render: shell
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validations:
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required: true
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- type: input
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id: version
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attributes:
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label: What version of fMRIPost-AROMA are you running?
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validations:
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required: true
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- type: dropdown
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id: environment
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attributes:
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label: How are you running fMRIPost-AROMA?
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options:
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- Docker
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- Singularity
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- Local installation ("bare-metal")
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- Other
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validations:
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required: true
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- type: dropdown
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id: bids-valid
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attributes:
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label: Is your data BIDS valid?
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description: |
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The BIDS validator can be found at: https://bids-standard.github.io/bids-validator/
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Errors should not be present, but warnings are acceptable.
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options:
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- "Yes"
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- "No"
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validations:
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required: true
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- type: dropdown
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id: reuse
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attributes:
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label: Are you reusing any previously computed results?
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description: |
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You can select multiple options.
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We recommend using a fresh working directory when upgrading to a new fMRIPost-AROMA minor series.
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multiple: true
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options:
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- FreeSurfer
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- Anatomical derivatives
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- Work directory
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- "No"
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validations:
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required: true
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- type: textarea
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id: logs
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attributes:
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label: Please copy and paste any relevant log output.
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description: |
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Can you find some traces of the error reported in the visual report (at the bottom) or in *crashfiles*?
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This will be automatically formatted into code, so no need for backticks.
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render: shell
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- type: textarea
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id: addinfo
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attributes:
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label: Additional information / screenshots
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description: |
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If you would like to include any further information, such as any visual reports, please include them below.
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Alternatively, you can privately share with us at <nipreps@gmail.com>.
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Reports do not contain data usable with personal identification or other research purposes.

‎.github/ISSUE_TEMPLATE/documentation.md

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---
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name: Documentation improvement
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about: Is the documentation of something missing, unclear, or lacking? This is the place.
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title: ''
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labels: 'documentation'
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assignees: ''
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---
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<!--
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For the Documentation request, please include the following:
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------------------------
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What would you like changed/added and why?
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Do you have any suggestions for the new documents?
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-->

‎.github/ISSUE_TEMPLATE/feature_request.yml

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name: Feature Request
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description: Suggest an idea for a new feature or a change to an existing one.
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labels: ["enhancement"]
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body:
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- type: markdown
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attributes:
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value: |
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## Thank you for your suggestion!
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We welcome any ideas about how to make *fMRIPost-AROMA* better for the community.
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Please keep in mind that features may not get implemented immediately.
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- type: textarea
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id: summary
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attributes:
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label: What would you like to see added in fMRIPost-AROMA?
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description: |
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What are you trying to achieve with fMRIPost-AROMA?
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Is this a more convenient way to do something that is already possible, or is a workaround currently unfeasible?
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Does this feature adhere to the [NiPreps driving principles](https://www.nipreps.org/community/CONTRIBUTING/#driving-principles)?
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validations:
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required: true
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- type: dropdown
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id: interest
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attributes:
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label: Do you have any interest in helping implement the feature?
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description: |
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We appreciate any help you can offer!
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For information on how to contribute, please refer to our [contributing guidelines](https://www.nipreps.org/community/CONTRIBUTING/).
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options:
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- "Yes"
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- Yes, but I would need guidance
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- "No"
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validations:
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required: true
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- type: textarea
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id: addinfo
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attributes:
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label: Additional information / screenshots
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description: Add any additional information or context about the feature request here.

‎pyproject.toml

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"fmriprep @ git+https://github.com/nipreps/fmriprep.git@master",
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"nipype >= 1.8.5",
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"nireports @ git+https://github.com/nipreps/nireports.git@main",
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"nitransforms == 23.0.1",
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"niworkflows @ git+https://github.com/nipreps/niworkflows.git@master",
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"pybids >= 0.15.6",
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"sdcflows @ git+https://github.com/nipreps/sdcflows.git@master",

‎src/fmripost_aroma/cli/parser.py

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@@ -318,8 +318,8 @@ def _bids_filter(value, parser):
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required=False,
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action='store',
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nargs='+',
321-
default=[],
322-
choices=['fieldmaps', 'slicetiming', 'jacobian'],
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default=['fieldmaps'],
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choices=['fieldmaps', 'slicetiming', 'fmap-jacobian'],
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help=(
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'Ignore selected aspects of the input dataset to disable corresponding '
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'parts of the resampling workflow (a space delimited list)'

‎src/fmripost_aroma/config.py

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@@ -546,10 +546,17 @@ class workflow(_Config):
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(positive = exact, negative = maximum)."""
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denoise_method = None
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"""Denoising strategy to be used."""
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ignore = None
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"""Ignore particular steps for *fMRIPost-AROMA*."""
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cifti_output = None
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"""Generate HCP Grayordinates, accepts either ``'91k'`` (default) or ``'170k'``."""
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dummy_scans = None
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"""Set a number of initial scans to be considered nonsteady states."""
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slice_time_ref = 0.5
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"""The time of the reference slice to correct BOLD values to, as a fraction
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acquisition time. 0 indicates the start, 0.5 the midpoint, and 1 the end
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of acquisition. The alias `start` corresponds to 0, and `middle` to 0.5.
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The default value is 0.5."""
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class loggers:

‎src/fmripost_aroma/data/io_spec.json

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"extension": [
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".tsv"
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]
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},
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"anat_dseg": {
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"datatype": "anat",
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"task": null,
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"run": null,
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"space": null,
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"res": null,
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"den": null,
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"desc": null,
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"suffix": "dseg",
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"extension": [
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".nii.gz",
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".nii"
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]
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}
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},
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"transforms": {

‎src/fmripost_aroma/data/reports-spec-func.yml

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reportlets:
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- bids: {datatype: figures, desc: summary, suffix: bold}
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- bids: {datatype: figures, desc: validation, suffix: bold}
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- bids: {datatype: figures, desc: aroma, suffix: bold}
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- bids: {datatype: figures, desc: metrics, suffix: bold}
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- bids: {datatype: figures, desc: coreg, suffix: bold}
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- bids: {datatype: figures, desc: normalization, suffix: bold}
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caption: This panel shows the alignment of the reference EPI (BOLD) image to the
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anatomical (T1-weighted) image.
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The reference EPI has been contrast enhanced and susceptibility-distortion
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corrected (if applicable) for improved anatomical fidelity.
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The anatomical image has been resampled into EPI space, as well as the
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anatomical white matter mask, which appears as a red contour.
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MNI152NLin6Asym template.
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The anatomical white matter mask has been warped to MNI152NLin6Asym space
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and appears as a red contour.
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static: false
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subtitle: Alignment of functional and anatomical MRI data (coregistration)
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subtitle: Alignment of functional and template MRI data (normalization)
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- bids: {datatype: figures, desc: aroma, suffix: bold}
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- bids: {datatype: figures, desc: metrics, suffix: bold}
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- bids: {datatype: figures, desc: preprocCarpetplot, suffix: bold}
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title: Preprocessed BOLD
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- bids: {datatype: figures, desc: nonaggrCarpetplot, suffix: bold}

‎src/fmripost_aroma/data/reports-spec.yml

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reportlets:
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- bids: {datatype: figures, desc: summary, suffix: bold}
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- bids: {datatype: figures, desc: validation, suffix: bold}
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- bids: {datatype: figures, desc: aroma, suffix: bold}
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- bids: {datatype: figures, desc: metrics, suffix: bold}
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- bids: {datatype: figures, desc: coreg, suffix: bold}
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- bids: {datatype: figures, desc: normalization, suffix: bold}
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caption: This panel shows the alignment of the reference EPI (BOLD) image to the
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anatomical (T1-weighted) image.
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The reference EPI has been contrast enhanced and susceptibility-distortion
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corrected (if applicable) for improved anatomical fidelity.
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The anatomical image has been resampled into EPI space, as well as the
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anatomical white matter mask, which appears as a red contour.
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MNI152NLin6Asym template.
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The anatomical white matter mask has been warped to MNI152NLin6Asym space
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and appears as a red contour.
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static: false
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subtitle: Alignment of functional and anatomical MRI data (coregistration)
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subtitle: Alignment of functional and template MRI data (normalization)
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- bids: {datatype: figures, desc: aroma, suffix: bold}
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- bids: {datatype: figures, desc: metrics, suffix: bold}
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- bids: {datatype: figures, desc: preprocCarpetplot, suffix: bold}
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title: Preprocessed BOLD
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- bids: {datatype: figures, desc: nonaggrCarpetplot, suffix: bold}

‎src/fmripost_aroma/interfaces/confounds.py

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# Regress the good components out of the bad time series to get "pure evil" regressors
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signal_mixing_arr = mixing_arr[signal_ics, :].T
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orthaggr_mixing_arr = aggr_mixing_arr.copy()
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aggr_mixing_arr_z = stats.zscore(aggr_mixing_arr, axis=0)
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signal_mixing_arr_z = stats.zscore(signal_mixing_arr, axis=0)
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betas = np.linalg.lstsq(signal_mixing_arr_z, aggr_mixing_arr_z, rcond=None)[0]

‎src/fmripost_aroma/interfaces/nilearn.py

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)
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mask_file = File(
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exists=True,
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mandatory=True,
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mandatory=False,
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desc='A binary brain mask.',
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)
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out_file = File(
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output_spec = _MeanImageOutputSpec
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def _run_interface(self, runtime):
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import nibabel as nb
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from nilearn.masking import apply_mask, unmask
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from nipype.interfaces.base import isdefined
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if isdefined(self.inputs.mask_file):
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data = apply_mask(self.inputs.bold_file, self.inputs.mask_file)
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mean_data = data.mean(axis=0)
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mean_img = unmask(mean_data, self.inputs.mask_file)
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else:
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in_img = nb.load(self.inputs.bold_file)
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mean_data = in_img.get_fdata().mean(axis=3)
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mean_img = nb.Nifti1Image(mean_data, in_img.affine, in_img.header)
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data = apply_mask(self.inputs.bold_file, self.inputs.mask_file)
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mean_data = data.mean(axis=0)
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mean_img = unmask(mean_data, self.inputs.mask_file)
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self._results['out_file'] = os.path.join(runtime.cwd, self.inputs.out_file)
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mean_img.to_filename(self._results['out_file'])
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‎src/fmripost_aroma/tests/test_base.py

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wf = init_ica_aroma_wf(
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bold_file='sub-01_task-rest_bold.nii.gz',
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metadata={'RepetitionTime': 2.0},
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mem_gb={'resampled': 1},
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)
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assert wf.name == 'aroma_task_rest_wf'
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‎src/fmripost_aroma/workflows/aroma.py

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*,
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bold_file: str,
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metadata: dict,
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mem_gb: dict,
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susan_fwhm: float = 6.0,
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):
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"""Build a workflow that runs `ICA-AROMA`_.
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output_type='NIFTI' if config.execution.low_mem else 'NIFTI_GZ',
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),
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name='smooth',
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mem_gb=mem_gb['resampled'],
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)
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workflow.connect([
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(rm_non_steady_state, smooth, [('bold_cut', 'in_file')]),
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dim=config.workflow.melodic_dim,
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),
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name='melodic',
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mem_gb=mem_gb['resampled'],
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)
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workflow.connect([
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(inputnode, melodic, [('bold_mask_std', 'mask')]),

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