Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

ENH: Restore CIFTI-2 generation #3129

Merged
merged 6 commits into from
Nov 13, 2023

Conversation

effigies
Copy link
Member

@effigies effigies commented Nov 8, 2023

Builds on #3126.

This one splits out the selection of the MNI template for the CIFTI-2 generation from the rest of the resampling to volumetric templates. If someone requests MNI152NLin6Asym and CIFTI, then we will resample twice in the working directory, but given that resampling is significantly faster now and does not scale files per-time point, I'm okay with that. I think it's a pretty rare case, and I suspect we'll want to resample a smaller ROI than the full brain at some point, so a separate pathway for that seems okay.

@effigies effigies added the next label Nov 8, 2023
@effigies effigies force-pushed the enh/restore-cifti-take-2 branch 3 times, most recently from 7baefba to 0d1be7a Compare November 8, 2023 20:58
Copy link

codecov bot commented Nov 8, 2023

Codecov Report

Attention: 30 lines in your changes are missing coverage. Please review.

Comparison is base (c79464e) 48.20% compared to head (21b79e7) 48.22%.
Report is 1 commits behind head on next.

Additional details and impacted files
@@            Coverage Diff             @@
##             next    #3129      +/-   ##
==========================================
+ Coverage   48.20%   48.22%   +0.01%     
==========================================
  Files          53       53              
  Lines        4134     4131       -3     
==========================================
- Hits         1993     1992       -1     
+ Misses       2141     2139       -2     
Files Coverage Δ
fmriprep/workflows/bold/outputs.py 24.85% <ø> (+0.42%) ⬆️
fmriprep/interfaces/gifti.py 50.00% <0.00%> (-1.73%) ⬇️
fmriprep/workflows/bold/resampling.py 11.57% <0.00%> (+0.22%) ⬆️
fmriprep/workflows/bold/base.py 27.10% <7.69%> (-0.40%) ⬇️
fmriprep/workflows/base.py 15.18% <0.00%> (-0.84%) ⬇️

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

@effigies effigies mentioned this pull request Nov 9, 2023
@effigies
Copy link
Member Author

This is ready for review. Will move onto carpetplots building on this.

@effigies effigies force-pushed the enh/restore-cifti-take-2 branch from 19e9022 to da91be4 Compare November 13, 2023 16:39
@effigies effigies force-pushed the enh/restore-cifti-take-2 branch from da91be4 to 21b79e7 Compare November 13, 2023 19:23
@effigies
Copy link
Member Author

Tests passing. @mgxd do you have time to review?

Copy link
Collaborator

@mgxd mgxd left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

just a question

suffix='bold',
compress=False,
TaskName=all_metadata[0].get('TaskName'),
**prepare_timing_parameters(all_metadata[0]),
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

not necessarily related to this PR, but is this the only time we are outputing this metadata? seems like something we should only calculate once and then distribute to any bold outputs

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

No, we also calculate it in the volumetric workflow:

def init_ds_volumes_wf(
*,
bids_root: str,
output_dir: str,
multiecho: bool,
metadata: ty.List[dict],
name="ds_volumes_wf",
) -> pe.Workflow:
timing_parameters = prepare_timing_parameters(metadata)
workflow = pe.Workflow(name=name)
inputnode = pe.Node(
niu.IdentityInterface(
fields=[
'source_files',
'ref_file',
'bold', # Resampled into target space
'bold_mask', # boldref space
'bold_ref', # boldref space
't2star', # boldref space
# Anatomical
'boldref2anat_xfm',
# Template
'anat2std_xfm',
# Entities
'space',
'cohort',
'resolution',
]
),
name='inputnode',
)
raw_sources = pe.Node(niu.Function(function=_bids_relative), name='raw_sources')
raw_sources.inputs.bids_root = bids_root
boldref2target = pe.Node(niu.Merge(2), name='boldref2target')
# BOLD is pre-resampled
ds_bold = pe.Node(
DerivativesDataSink(
base_directory=output_dir,
desc='preproc',
compress=True,
SkullStripped=multiecho,
TaskName=metadata.get('TaskName'),
dismiss_entities=("echo",),
**timing_parameters,
),
name='ds_bold',
run_without_submitting=True,
mem_gb=DEFAULT_MEMORY_MIN_GB,
)

So it gets recalculated several times. We could refactor the function to have a cacheable core (can't @lru_cache with a dictionary argument), but I'm not sure saving <1s (estimate, not measured) at workflow build is really worth it.

@effigies effigies merged commit e2c3de1 into nipreps:next Nov 13, 2023
10 of 11 checks passed
@effigies effigies deleted the enh/restore-cifti-take-2 branch November 13, 2023 21:20
effigies added a commit that referenced this pull request Jan 10, 2024
23.2.0 (January 10, 2024)

New feature release in the 23.2.x series.

This release wraps up a significant refactor of fMRIPrep. The main new features
can be used with the ``--level`` and ``--derivatives`` flags.

The ``--level`` flag can take the arguments ``minimal``, ``resampling`` or
``full``. The default is ``full``, which should produce nearly the same results
as previous versions. ``minimal`` will produce only the minimum necessary to
deterministically generate the remaining derivatives. ``resampling`` will produce
some additional derivatives, intended to simplify resampling with other tools.

The ``--derivatives`` flag takes arguments of the form ``name=/path/to/dir``,
for example ``--derivatives anat=$SMRIPREP_DIR``.  If provided, fMRIPrep will
read the specified directories for pre-computed derivatives. If a derivative is
found, it will be used instead of computing it from scratch. If a derivative is
not found, fMRIPrep will compute it and proceed as usual.

Taken together, these features can allow a dataset provider to run a minimal
fMRIPrep run, targeting many output spaces, while a user can then run a
``--derivatives`` run to generate additional derivatives in only the output
spaces they need. Another use case is to provide an precomputed derivative
to override the default fMRIPrep behavior, enabling easier workarounds for
bugs or experimentation with alternatives.

Additionally, this release includes a number of bug fixes and improvements.
This release adds support for MSM-Sulc, improving the alignment of subject
surfaces to the fsLR template. This process is enabled by default, but may
be disabled with the ``--no-msm`` flag.

This release resolves a number of issues with fieldmaps inducing distortions
during correction. Phase difference and direct fieldmaps are now masked correctly,
preventing the overestimation of distortions outside the brain. Additionally,
we now implement Jacobian weighting during unwarping, which corrects for compression
and expansion effects on signal intensity. To disable Jacobian weighting, use
``--ignore fmap-jacobian``.

Finally, a new resampling method has been added, to better account for
susceptibility distortion and motion in a single shot resampling to a volumetric
target space. We anticipate extending this to surface targets in the future.

* FIX: Restore --ignore sbref functionality (#3180)
* FIX: Retrieve atlas ROIs at requested density (#3179)
* FIX: Keep minctracc executable in FreeSurfer installation (#3175)
* FIX: Exclude echo entity from optimally combined derivatives (#3166)
* FIX: Disable boldref-space outputs unless requested (#3159)
* FIX: Tag memory estimates in resamplers (#3150)
* FIX: Final revisions for next branch (#3134)
* FIX: Minor fixes to work with MSMSulc-enabled smriprep-next (#3098)
* FIX: Connect EPI-to-fieldmap transform (#3099)
* FIX: Use Py2-compatible version file template for fmriprep-docker (#3101)
* FIX: Update connections to unwarp_wf, convert ITK transforms to text (#3077)
* ENH: Allow --ignore fmap-jacobian to disable Jacobian determinant modulation during fieldmap correction (#3186)
* ENH: Exclude non-steady-state volumes from confound correlation plot (#3171)
* ENH: Pass FLAIR images to anatomical workflow builder to include in boilerplate (#3146)
* ENH: Restore carpetplot and other final adjustments (#3131)
* ENH: Restore CIFTI-2 generation (#3129)
* ENH: Restore resampling to surface GIFTIs (#3126)
* ENH: Restore confound generation (#3120)
* ENH: Restore resampling BOLD to volumetric templates (#3121)
* ENH: Restore resampling to T1w target (#3116)
* ENH: Add MSMSulc (#3085)
* ENH: Add reporting workflow for BOLD fit (#3082)
* ENH: Generate anatomical derivatives useful for resampling (#3081)
* RF: Load reportlets interfaces from nireports rather than niworkflows (#3176, #3184)
* RF: Separate goodvoxels mask creation from fsLR resampling (#3170)
* RF: Write out anatomical template derivatives (#3136)
* RF: Update primary bold workflow to incorporate single shot resampling (#3114)
* RF: Update derivative cache spec, calculate per-BOLD, reuse boldref2fmap (#3078)
* RF: Split fMRIPrep into fit and derivatives workflows (#2913)
* RPT: Rename CSF/WM confounds in fMRIPlot (#3172)
* TST: Add smoke tests for full workflow and most branching flags (#3155)
* TST: Add smoke-tests for bold_fit_wf (#3152)
* DOC: Fix documentation and description for init_bold_grayords_wf (#3051)
* DOC: Minor updates in outputs.rst (#3148)
* STY: Apply a couple refurb suggestions (#3151)
* STY: Fix flake8 warnings (#3044)
* STY: Apply pyupgrade suggestions (#3043)
* MNT: Restore mritotal subcommands to Dockerfile (#3149)
* MNT: Update smriprep to 0.13.1 (#3153)
* MNT: optimise size of PNG files (#3145)
* MNT: update vendored docs script ``github_link.py`` (#3144)
* MNT: Update tedana pin, test on Python 3.12 (#3141)
* MNT: Bump environment (#3132)
* MNT: Bump version requirements (#3107)
* MNT: http:// → https:// (#3097)
* MNT: Remove mritotal and dependencies from FreeSurfer ignore file (#3090)
* MNT: Update environment (#3073)
* MNT: Depend on newer sphinx (#3067)
* MNT: Install ANTs from conda-forge (#3061)
* MNT: Drop Python 3.8 and numpy 1.21 support (NEP29) (#3052)
* MNT: update update_zenodo.py script (#3042)
* MNT: Fix welcome message formatting and instructions (#3039)
* MNT: Python 3.11 should be supported (#3038)
* CI: Bump actions/setup-python from 4 to 5 (#3181)
* CI: Stop testing legacy layout (#3079)
* CI: Improve tag detection for docker builds (#3066)
* CI: Clean up pre-release builds (#3040)
NingAnMe added a commit to NingAnMe/fmriprep that referenced this pull request Jan 11, 2024
23.2.0 (January 10, 2024)

New feature release in the 23.2.x series.

This release wraps up a significant refactor of fMRIPrep. The main new features
can be used with the ``--level`` and ``--derivatives`` flags.

The ``--level`` flag can take the arguments ``minimal``, ``resampling`` or
``full``. The default is ``full``, which should produce nearly the same results
as previous versions. ``minimal`` will produce only the minimum necessary to
deterministically generate the remaining derivatives. ``resampling`` will produce
some additional derivatives, intended to simplify resampling with other tools.

The ``--derivatives`` flag takes arguments of the form ``name=/path/to/dir``,
for example ``--derivatives anat=$SMRIPREP_DIR``.  If provided, fMRIPrep will
read the specified directories for pre-computed derivatives. If a derivative is
found, it will be used instead of computing it from scratch. If a derivative is
not found, fMRIPrep will compute it and proceed as usual.

Taken together, these features can allow a dataset provider to run a minimal
fMRIPrep run, targeting many output spaces, while a user can then run a
``--derivatives`` run to generate additional derivatives in only the output
spaces they need. Another use case is to provide an precomputed derivative
to override the default fMRIPrep behavior, enabling easier workarounds for
bugs or experimentation with alternatives.

Additionally, this release includes a number of bug fixes and improvements.
This release adds support for MSM-Sulc, improving the alignment of subject
surfaces to the fsLR template. This process is enabled by default, but may
be disabled with the ``--no-msm`` flag.

This release resolves a number of issues with fieldmaps inducing distortions
during correction. Phase difference and direct fieldmaps are now masked correctly,
preventing the overestimation of distortions outside the brain. Additionally,
we now implement Jacobian weighting during unwarping, which corrects for compression
and expansion effects on signal intensity. To disable Jacobian weighting, use
``--ignore fmap-jacobian``.

Finally, a new resampling method has been added, to better account for
susceptibility distortion and motion in a single shot resampling to a volumetric
target space. We anticipate extending this to surface targets in the future.

* FIX: Restore --ignore sbref functionality (nipreps#3180)
* FIX: Retrieve atlas ROIs at requested density (nipreps#3179)
* FIX: Keep minctracc executable in FreeSurfer installation (nipreps#3175)
* FIX: Exclude echo entity from optimally combined derivatives (nipreps#3166)
* FIX: Disable boldref-space outputs unless requested (nipreps#3159)
* FIX: Tag memory estimates in resamplers (nipreps#3150)
* FIX: Final revisions for next branch (nipreps#3134)
* FIX: Minor fixes to work with MSMSulc-enabled smriprep-next (nipreps#3098)
* FIX: Connect EPI-to-fieldmap transform (nipreps#3099)
* FIX: Use Py2-compatible version file template for fmriprep-docker (nipreps#3101)
* FIX: Update connections to unwarp_wf, convert ITK transforms to text (nipreps#3077)
* ENH: Allow --ignore fmap-jacobian to disable Jacobian determinant modulation during fieldmap correction (nipreps#3186)
* ENH: Exclude non-steady-state volumes from confound correlation plot (nipreps#3171)
* ENH: Pass FLAIR images to anatomical workflow builder to include in boilerplate (nipreps#3146)
* ENH: Restore carpetplot and other final adjustments (nipreps#3131)
* ENH: Restore CIFTI-2 generation (nipreps#3129)
* ENH: Restore resampling to surface GIFTIs (nipreps#3126)
* ENH: Restore confound generation (nipreps#3120)
* ENH: Restore resampling BOLD to volumetric templates (nipreps#3121)
* ENH: Restore resampling to T1w target (nipreps#3116)
* ENH: Add MSMSulc (nipreps#3085)
* ENH: Add reporting workflow for BOLD fit (nipreps#3082)
* ENH: Generate anatomical derivatives useful for resampling (nipreps#3081)
* RF: Load reportlets interfaces from nireports rather than niworkflows (nipreps#3176, nipreps#3184)
* RF: Separate goodvoxels mask creation from fsLR resampling (nipreps#3170)
* RF: Write out anatomical template derivatives (nipreps#3136)
* RF: Update primary bold workflow to incorporate single shot resampling (nipreps#3114)
* RF: Update derivative cache spec, calculate per-BOLD, reuse boldref2fmap (nipreps#3078)
* RF: Split fMRIPrep into fit and derivatives workflows (nipreps#2913)
* RPT: Rename CSF/WM confounds in fMRIPlot (nipreps#3172)
* TST: Add smoke tests for full workflow and most branching flags (nipreps#3155)
* TST: Add smoke-tests for bold_fit_wf (nipreps#3152)
* DOC: Fix documentation and description for init_bold_grayords_wf (nipreps#3051)
* DOC: Minor updates in outputs.rst (nipreps#3148)
* STY: Apply a couple refurb suggestions (nipreps#3151)
* STY: Fix flake8 warnings (nipreps#3044)
* STY: Apply pyupgrade suggestions (nipreps#3043)
* MNT: Restore mritotal subcommands to Dockerfile (nipreps#3149)
* MNT: Update smriprep to 0.13.1 (nipreps#3153)
* MNT: optimise size of PNG files (nipreps#3145)
* MNT: update vendored docs script ``github_link.py`` (nipreps#3144)
* MNT: Update tedana pin, test on Python 3.12 (nipreps#3141)
* MNT: Bump environment (nipreps#3132)
* MNT: Bump version requirements (nipreps#3107)
* MNT: http:// → https:// (nipreps#3097)
* MNT: Remove mritotal and dependencies from FreeSurfer ignore file (nipreps#3090)
* MNT: Update environment (nipreps#3073)
* MNT: Depend on newer sphinx (nipreps#3067)
* MNT: Install ANTs from conda-forge (nipreps#3061)
* MNT: Drop Python 3.8 and numpy 1.21 support (NEP29) (nipreps#3052)
* MNT: update update_zenodo.py script (nipreps#3042)
* MNT: Fix welcome message formatting and instructions (nipreps#3039)
* MNT: Python 3.11 should be supported (nipreps#3038)
* CI: Bump actions/setup-python from 4 to 5 (nipreps#3181)
* CI: Stop testing legacy layout (nipreps#3079)
* CI: Improve tag detection for docker builds (nipreps#3066)
* CI: Clean up pre-release builds (nipreps#3040)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants