[FEAT] MEDIC distortion correction via warpkit by vanandrew · Pull Request #541 · nipreps/sdcflows

vanandrew · 2026-04-26T04:31:17Z

Summary

Adds multi-echo dynamic distortion correction (MEDIC) to sdcflows, backed by warpkit. MEDIC estimates a per-volume B0 fieldmap directly from a multi-echo, mag+phase BOLD series, capturing breathing- and motion-driven field changes that a single static fieldmap can't.

Revives #435 / #438 with the simpler pure-Python warpkit (post vanandrew/warpkit#16, no Julia/C++ setup required). Closes #36.

What's new

Workflows

init_medic_wf (sdcflows/workflows/fit/medic.py) — multi-echo phase + magnitude → 4D Hz fieldmap (one volume per timepoint, on the EPI grid) + brain-extracted reference + brain mask. Two-stage warpkit call (UnwrapPhase → ComputeFieldmap) so the per-frame masks stay accessible. Single fmap output is 4D for MEDIC, leaving the 3D-vs-4D dispatch to the apply consumer.
init_dynamic_unwarp_wf (sdcflows/workflows/apply/dynamic.py) — per-volume apply path built on sdcflows.transform.apply_dynamic_unwarp, a per-frame extension of the same scipy/nitransforms-backed resampling that powers the static init_unwarp_wf. No warpkit needed at runtime. Includes Jacobian determinant intensity correction (jacobian=True default) sharing transform.fieldmap_jacobian with the static path.

Interfaces

sdcflows/interfaces/warpkit.py — thin LibraryBaseInterface wrappers around the two MEDIC stages SDCFlows actually drives: UnwrapPhase (ROMEO) and ComputeFieldmap. Lazy import — sdcflows imports warpkit only when these interfaces actually run.

Detection / dispatch

EstimatorType.MEDIC added. FieldmapEstimation.__attrs_post_init__ detects MEDIC inputs (part-{phase,mag} on bold/epi/sbref sources), enforces matched echo cardinality (≥2 phase, equal mag count), and rejects partial or mixed part sets. get_workflow instantiates init_medic_wf with EchoTime-sorted lists (BIDS doesn't guarantee echo entity == numeric order).
Wrangler seeds MEDIC detection from both part='phase' and part='mag' queries (some datasets carry IntendedFor only on one side); dedup walks the full sibling set, no reliance on pybids ordering.
force_medic opt-in on find_estimators — auto-discover MEDIC estimators from complex multi-echo BOLD even when neither IntendedFor nor B0FieldIdentifier is set. Pairing is unambiguous because the part-mag/part-phase echoes of the same run are MEDIC sources by construction. Intended for public datasets that ship the required echoes without the metadata the default discovery path needs.

Plumbing

init_fmap_preproc_wf skips fmap_coeff for MEDIC (the fieldmap is on the EPI grid by construction, no B-spline rep).
init_fmap_derivatives_wf uses MergeSeries(allow_4D=True) so MEDIC's 4D fmap passes through the same ds_fieldmap sink as the 3D static fmaps.

Packaging

New warpkit extra in pyproject.toml, explicitly excluded from [all] because warpkit ships under a non-commercial WUSTL license. Default pip install sdcflows stays Apache-clean.
tox.ini: the veryslow env pulls the warpkit extra so MEDIC end-to-end tests only run there.
CI: datalad-fetches sub-04/ses-2 of ds007637 and sub-a01 of ds006926 as MEDIC fixtures (cache key bumped to v3).

Validation

Three-layer multi-echo guard: wrangler seed query (echo=Query.REQUIRED), FieldmapEstimation cardinality check (len(phase_files) < 2), and _unpack_metadata runtime guard inside init_medic_wf.
Construction tests for both workflows run on every CI lane (no warpkit needed).
test_apply_dynamic_unwarp_matches_static pins apply_dynamic_unwarp to the same Hz→VSM + scipy.ndimage convention as the static _sdc_unwarp path — catches drift in sign / pe_info handling.
test_wrangler_filter / test_wrangler_URIs parametrized with a 3-session × 3-echo × {mag,phase} BIDS skeleton.
End-to-end runs on ds006926 (3-echo, 64×64×40, 205 frames) and ds007637 (5-echo, 110×110×72, 237 frames) confirm Jacobian factor sits at ~1.0 in the brain mask (std 0.087 / 0.118) with ~1–2% of voxels in compression/expansion regions and total signal change <2% — physically sensible.

Known compromises

Default wrangler MEDIC discovery still keys off IntendedFor / B0FieldIdentifier — same constraint as the existing single-PE EPI branch. Datasets missing both can opt into discovery via force_medic=True on find_estimators (see Detection / dispatch above).
The single fmap output is 4D for MEDIC. Downstream tools that expect 3D field maps need to either dispatch on dimensionality or block MEDIC-based estimators until they do.

Test plan

pytest sdcflows/utils/tests/test_wrangler.py — wrangler MEDIC detection paths (including force_medic)
pytest sdcflows/workflows/fit/tests/test_medic.py — init_medic_wf construction + _unpack_metadata guards
pytest sdcflows/workflows/apply/tests/test_dynamic.py — init_dynamic_unwarp_wf construction + jacobian flag + per-frame resampling vs. static path
pytest -m veryslow with pip install sdcflows[warpkit] and ds006926 / ds007637 fixtures present — full MEDIC fit + dynamic apply

codecov · 2026-04-26T15:44:34Z

Codecov Report

❌ Patch coverage is 85.65217% with 33 lines in your changes missing coverage. Please review.
✅ Project coverage is 84.21%. Comparing base (fcfe039) to head (aab352e).

Files with missing lines	Patch %	Lines
sdcflows/fieldmaps.py	56.25%	14 Missing ⚠️
sdcflows/workflows/apply/dynamic.py	74.07%	7 Missing ⚠️
sdcflows/transform.py	86.95%	3 Missing and 3 partials ⚠️
sdcflows/utils/wrangler.py	85.71%	3 Missing and 1 partial ⚠️
sdcflows/workflows/base.py	77.77%	1 Missing and 1 partial ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #541      +/-   ##
==========================================
+ Coverage   84.17%   84.21%   +0.04%     
==========================================
  Files          30       33       +3     
  Lines        2938     3104     +166     
  Branches      391      326      -65     
==========================================
+ Hits         2473     2614     +141     
- Misses        388      414      +26     
+ Partials       77       76       -1

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❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

Three additions targeting the codecov/patch failure on nipreps#541: * sdcflows/interfaces/tests/test_warpkit.py (new) — instantiates every warpkit-backed interface so its spec class body is hit at import (was 0% on codecov despite running locally; likely an xdist worker-merge artefact). Also covers ``_as_str_list``, the ``_pkg`` invariant, and the ``border_filt=(1, 5)`` traits default regression. * sdcflows/workflows/tests/test_outputs.py (new) — direct construction test for ``init_fmap_derivatives_wf``, exercising both the default and ``write_dynamic=True`` paths. The MEDIC dynamic sinks branch was only reached transitively from the ``test_fmap_wf`` slow test, hence 0% patch coverage on outputs.py. * sdcflows/workflows/fit/tests/test_medic.py — fill the remaining helper gaps: empty-metadata rejection, ``sloppy=True`` zooms_min, ``_first``, and ``_temporal_mean`` for both 3D and 4D inputs. The ``_run_interface`` method bodies in interfaces/warpkit.py remain uncovered in the fast/slow envs since they require warpkit to import; the existing ``veryslow`` MEDIC fixtures exercise them when the optional dependency is installed.

vanandrew · 2026-05-14T13:20:12Z

I have no idea why test (3.13, pre, fast) is failing on the cache step.

It looks like an out-of-space error on the runner (but the other jobs with the same steps succeeded, so very confused):

[test (3.13, pre, fast)](https://github.com/nipreps/sdcflows/actions/runs/25840682073/job/75990934202)
System.IO.IOException: No space left on device : '/home/runner/actions-runner/cached/2.334.0/_diag/Worker_20260514-125354-utc.log'
   at System.IO.RandomAccess.WriteAtOffset(SafeFileHandle handle, ReadOnlySpan`1 buffer, Int64 fileOffset)
   at System.IO.StreamWriter.Flush(Boolean flushStream, Boolean flushEncoder)
   at System.Diagnostics.TextWriterTraceListener.Flush()
   at GitHub.Runner.Common.HostTraceListener.WriteHeader(String source, TraceEventType eventType, Int32 id)
   at System.Diagnostics.TraceSource.TraceEvent(TraceEventType eventType, Int32 id, String message)
   at GitHub.Runner.Worker.Worker.RunAsync(String pipeIn, String pipeOut)
   at GitHub.Runner.Worker.Program.MainAsync(IHostContext context, String[] args)
System.IO.IOException: No space left on device : '/home/runner/actions-runner/cached/2.334.0/_diag/Worker_20260514-125354-utc.log'
   at System.IO.RandomAccess.WriteAtOffset(SafeFileHandle handle, ReadOnlySpan`1 buffer, Int64 fileOffset)
   at System.IO.StreamWriter.Flush(Boolean flushStream, Boolean flushEncoder)
   at System.Diagnostics.TextWriterTraceListener.Flush()
   at GitHub.Runner.Common.HostTraceListener.WriteHeader(String source, TraceEventType eventType, Int32 id)
   at System.Diagnostics.TraceSource.TraceEvent(TraceEventType eventType, Int32 id, String message)
   at GitHub.Runner.Common.Tracing.Error(Exception exception)
   at GitHub.Runner.Worker.Program.MainAsync(IHostContext context, String[] args)
Unhandled exception. System.IO.IOException: No space left on device : '/home/runner/actions-runner/cached/2.334.0/_diag/Worker_20260514-125354-utc.log'
   at System.IO.RandomAccess.WriteAtOffset(SafeFileHandle handle, ReadOnlySpan`1 buffer, Int64 fileOffset)
   at System.IO.StreamWriter.Flush(Boolean flushStream, Boolean flushEncoder)
   at System.Diagnostics.TextWriterTraceListener.Flush()
   at System.Diagnostics.TraceSource.Flush()
   at GitHub.Runner.Common.Tracing.Dispose(Boolean disposing)
   at GitHub.Runner.Common.Tracing.Dispose()
   at GitHub.Runner.Common.TraceManager.Dispose(Boolean disposing)
   at GitHub.Runner.Common.TraceManager.Dispose()
   at GitHub.Runner.Common.HostContext.Dispose(Boolean disposing)
   at GitHub.Runner.Common.HostContext.Dispose()
   at GitHub.Runner.Worker.Program.Main(String[] args)

tsalo · 2026-05-15T16:26:01Z

@vanandrew I think someone must have rerun that failing job and now it's passing.

tsalo

Thanks for this! I made a quick pass through the code.

vanandrew · 2026-05-16T02:59:06Z

Pushed four commits addressing your feedback (noise_frames, ctor inputs, nitransforms switch + interface cleanup, unified fmap output).

vanandrew · 2026-05-20T01:16:27Z

I can't tell if these test failures are something wrong with my dataset additions or if it's just another one-off error:

update(error): . (dataset) [Fetch failed: CommandError(CommandError: 'git -c diff.ignoreSubmodules=none -c core.quotepath=false fetch --verbose --progress --no-recurse-submodules --
prune origin' failed with exitcode 128 under /home/runner/sdcflows-tests/brain-extraction-tests [err: 'fatal: unable to access 'https://gin.g-node.org/nipreps-data/brain-extraction-
tests/': The requested URL returned error: 403'])] [CommandError: 'git -c diff.ignoreSubmodules=none -c core.quotepath=false fetch --verbose --progress --no-recurse-submodules --
prune origin' failed with exitcode 128 under /home/runner/sdcflows-tests/brain-extraction-tests [err: 'fatal: unable to access 'https://gin.g-node.org/nipreps-data/brain-extraction-
tests/': The requested URL returned error: 403']]
Error: Process completed with exit code 1.

vanandrew · 2026-05-25T17:58:19Z

Looks like the CI keeps failing because it's running out of space (I added two datasets for tests so that might have pushed it over the edge).

I pushed 6f5cfff2 adding a jlumbroso/free-disk-space@main step at the top of the test job:

- name: Free disk space
  uses: jlumbroso/free-disk-space@main
  with:
    tool-cache: false
    android: true
    dotnet: true
    haskell: true
    large-packages: false
    swap-storage: false

This gets rid of some unneeded development tools on the github runner to free room for data.

vanandrew · 2026-06-02T01:40:18Z

@tsalo Alright. I made changes based on our convo today:

find_estimators discovers a fieldmap estimator for every fieldmap declared in BIDS intent metadata: grouping inputs by B0FieldIdentifier (Step 1), or falling back to IntendedFor heuristics (Step 2) only when no B0FieldIdentifier exists. (no_medic suppresses MEDIC via either route). It adds a sort that always returns dynamic estimators (i.e. MEDIC) first.
Simplified fmap_ref and fmap_mask to be the first echo magntude and MEDIC fmap masks respectively. These likely won't be used by downstream consumers.
Removed force_medic and replaced with no_medic

Three additions targeting the codecov/patch failure on nipreps#541: * sdcflows/interfaces/tests/test_warpkit.py (new) — instantiates every warpkit-backed interface so its spec class body is hit at import (was 0% on codecov despite running locally; likely an xdist worker-merge artefact). Also covers ``_as_str_list``, the ``_pkg`` invariant, and the ``border_filt=(1, 5)`` traits default regression. * sdcflows/workflows/tests/test_outputs.py (new) — direct construction test for ``init_fmap_derivatives_wf``, exercising both the default and ``write_dynamic=True`` paths. The MEDIC dynamic sinks branch was only reached transitively from the ``test_fmap_wf`` slow test, hence 0% patch coverage on outputs.py. * sdcflows/workflows/fit/tests/test_medic.py — fill the remaining helper gaps: empty-metadata rejection, ``sloppy=True`` zooms_min, ``_first``, and ``_temporal_mean`` for both 3D and 4D inputs. The ``_run_interface`` method bodies in interfaces/warpkit.py remain uncovered in the fast/slow envs since they require warpkit to import; the existing ``veryslow`` MEDIC fixtures exercise them when the optional dependency is installed.

vanandrew · 2026-06-03T18:56:20Z

@tsalo I did a rebase to the latest main, hopefully to quash the 3.13 test error that happened in the last CI run: https://github.com/nipreps/sdcflows/actions/runs/26792754492/job/79155816998#step:22:320

Three additions targeting the codecov/patch failure on nipreps#541: * sdcflows/interfaces/tests/test_warpkit.py (new) — instantiates every warpkit-backed interface so its spec class body is hit at import (was 0% on codecov despite running locally; likely an xdist worker-merge artefact). Also covers ``_as_str_list``, the ``_pkg`` invariant, and the ``border_filt=(1, 5)`` traits default regression. * sdcflows/workflows/tests/test_outputs.py (new) — direct construction test for ``init_fmap_derivatives_wf``, exercising both the default and ``write_dynamic=True`` paths. The MEDIC dynamic sinks branch was only reached transitively from the ``test_fmap_wf`` slow test, hence 0% patch coverage on outputs.py. * sdcflows/workflows/fit/tests/test_medic.py — fill the remaining helper gaps: empty-metadata rejection, ``sloppy=True`` zooms_min, ``_first``, and ``_temporal_mean`` for both 3D and 4D inputs. The ``_run_interface`` method bodies in interfaces/warpkit.py remain uncovered in the fast/slow envs since they require warpkit to import; the existing ``veryslow`` MEDIC fixtures exercise them when the optional dependency is installed.

BIDS keeps trailing noise frames in separate noRF files, so SDCFlows shouldn't carry an interface input for them — let warpkit's default of zero apply.

Passing n_cpus and debug through the interface constructor keeps node construction in one place and removes the post-init mutation pattern.

…sforms The dynamic-fieldmap apply workflow was the only consumer of ``ApplyWarp``/``ConvertFieldmap`` in warpkit; rewrite it on top of ``sdcflows.transform.apply_dynamic_unwarp``, a per-frame extension of the existing scipy/nitransforms-backed resampling that powers the static path. With that internal consumer gone, the warpkit interface module shrinks to just the two stages SDCFlows actually runs (``UnwrapPhase``, ``ComputeFieldmap``); the unused ``MEDIC``, ``ApplyWarp``, ``ConvertWarp``, ``ConvertFieldmap`` and ``ComputeJacobian`` wrappers, along with the helpers that only served them, are removed.

``init_medic_wf`` previously emitted both a 3D static ``fmap`` (a B-spline-smoothed temporal mean of the dynamic field) and a separate 4D ``fmap_dynamic``, alongside parallel ``fmap_dynamic_ref`` and ``fmap_dynamic_mask`` plumbing in the base preproc workflow and a ``write_dynamic`` branch in the derivatives sinks. Per review, collapse all of that to a single ``fmap`` output whose dimensionality (3D for static estimators, 4D for MEDIC) tells consumers which apply path to use. The B-spline shim is gone (MEDIC's field is already on the EPI grid), the derivatives sink uses ``MergeSeries(allow_4D=True)`` to pass 3D and 4D fmaps through the same path, and the per-volume apply workflow renames its input from ``fmap_dynamic`` to ``fmap`` to match. Downstream tools that don't yet handle 4D field maps must block MEDIC-based estimators until they do.

The static init_magnitude_wf averaged across time before brain-extracting, which collapsed MEDIC's per-volume magnitude into one 3D ref/mask. The new init_dynamic_magnitude_wf splits the 4D first-echo magnitude, runs the IntensityClip/N4/BrainExtraction chain per frame, and re-concatenates so fmap_ref and fmap_mask are 4D and track the per-volume fieldmap.

…nt accepted kwargs Adds three regression tests around the MEDIC guard clauses in ``FieldmapEstimation.__attrs_post_init__`` (single-part input, single-echo pair, mismatched mag/phase counts), and documents the two ``init_medic_wf`` parameters (``use_metadata_estimates``, ``fallback_total_readout_time``) that are accepted via ``init_fmap_preproc_wf`` for parity but currently ignored.

…ation.is_dynamic Replaces the ``estimator.method == EstimatorType.MEDIC`` check in ``init_fmap_preproc_wf`` with a new ``FieldmapEstimation.is_dynamic`` property backed by a module-level ``_DYNAMIC_METHODS`` set in ``sdcflows.fieldmaps``. Future per-volume estimators (DOCMA, TOAST, ...) only need to be added to ``_DYNAMIC_METHODS`` — the shared workflow no longer carries per-method branching.

Adds ``test_wrangler_medic_trigger`` covering the three modes of MEDIC discovery against synthetic BIDS skeletons in a single parametrized test: 1. ``default-IntendedFor`` — sidecars carry ``IntendedFor`` and the default discovery path picks them up. 2. ``force_medic`` — sidecars carry no metadata; the explicit flag short-circuits the default ``IntendedFor`` gate. 3. ``baseline-no-trigger`` — no metadata, no override, no fmapless; MEDIC must refuse to fire so runs without expected metadata are not silently picked up. The existing ``test_wrangler_force_medic_without_intended_for`` covers cases 2 and 3 implicitly via ``medic_no_intended_for``; this new test pins all three side-by-side and was validated against a real ds006926/sub-a01 layout before being formalized here.

…s contributor

The bumped data-cache-v3 (now includes ds006926 + ds007637) tips the 3.10/min/fast lane over the 14 GB root-disk limit during cache restore. Free ~20 GB up front by purging the Android SDK, .NET, and Haskell tool-caches; keep the tool-cache, swap, and apt large-packages alone so later steps (apt-cache restore, conda, uv) aren't disturbed.

…arpkit masks The MEDIC workflow now exposes the first-echo magnitude series untouched as ``fmap_ref`` (the ``pick_mag1`` output) and routes warpkit's per-frame ``UnwrapPhase`` masks straight to ``fmap_mask``, instead of running a per-frame N4 + skull-strip pass to synthesize both. ``init_dynamic_magnitude_wf`` was only used by MEDIC, so it is removed from ``fit/fieldmap.py`` entirely. The expensive per-volume MapNode work (N4, intensity clip, brain extraction over every frame) is gone with it. Updates ``test_medic_construct`` to drop the removed ``magnitude_wf`` node.

…DIC-first ordering Make MEDIC discovery follow the BIDS fieldmap-intent model rather than file structure: * MEDIC is now discovered only from declared intent metadata -- a complex multi-echo BOLD is picked up via its ``B0FieldIdentifier`` (the self-referential pattern BIDS endorses for images that estimate their own B0 field, as in pepolar) through the existing Step 1 path, or via legacy ``IntendedFor`` in the dedicated MEDIC block. The structure-only auto-discovery (and the ``force_medic`` flag that enabled it) is removed: part-mag/part-phase alone no longer triggers MEDIC. * Add ``no_medic`` to disable MEDIC discovery via either route (kwarg + ``--no-medic`` CLI flag + ``config.workflow.no_medic``); it also skips a MEDIC-shaped ``B0FieldIdentifier`` group in Step 1. Return estimators in a deterministic order: ``estimators.sort(key=lambda e: (not e.is_dynamic, e.bids_id))``. Step 1 iterates a ``set`` of ``B0FieldIdentifier``s, so the prior order was hash-seed dependent. The sort also encodes one intentional, documented priority -- dynamic (MEDIC) estimators come first, so a consumer selecting the first applicable estimator per target prefers MEDIC over a coexisting static fieldmap. Fieldmap-less ANAT estimators are appended afterwards and stay last. Tests: cover the B0FieldIdentifier and IntendedFor MEDIC routes, a guard that structure alone does not fire MEDIC, and that MEDIC sorts ahead of a coexisting PEPOLAR estimator.

Address review: replace the fmt: off/on pair around workflow.connect with an inline # fmt:skip, and use pathlib.Path over os.path for the corrected output. Also normalize the warpkit module/test copyright headers to the unversioned NiPreps form.

Address review: collapse the unused use_metadata_estimates and fallback_total_readout_time parity args into **kwargs (dropping the now-dead del statement and their docstring entries), and inline the single-use _MEDIC_DESC string at the workflow.__desc__ assignment.

Address review: move the duplicated _MEDIC_TEST_VOLUMES, _truncate_to_volumes helper, and MEDIC_FIXTURES list out of the fit/apply test modules into shared conftest fixtures (medic_test_volumes, truncate_to_volumes, and a parametrized medic_fixture). Both end-to-end tests now consume the fixtures, removing the keep-in-sync duplication. Also normalize remaining copyright headers.

Move warpkit into the core dependencies (keeping the python_version >= '3.11' marker so 3.10 installs still resolve) rather than gating it behind an opt-in extra. Drop the [warpkit] optional-dependencies group and the now-redundant veryslow: warpkit tox extra. The non-commercial WUSTL license is documented in the init_medic_wf module docstring.

Address review: the helper recomputed fmap_hz * ro_time internally, duplicating the VSM already computed in _sdc_unwarp. Change the signature to accept the VSM and reuse it at the call site, keeping the 3D/4D-capable helper for downstream use.

nipype prunes a node's working directory to the files referenced by its string-valued outputs. _dynamic_unwarp returned a PosixPath, which the pruning did not recognize, so corrected.nii.gz was deleted before the downstream average node could read it. Return str() of the path.

Collapse the parallel dynamic apply stack into the static machinery: - unwarp_parallel accepts a 3D or 4D field; a 3D (shared) field is np.broadcast_to-viewed across frames so per-frame selection is a single branchless fmap_hz[..., volid]. The 3D case is the degenerate 4D case. - B0FieldTransform can be constructed from a pre-gridded field (mapped=) in addition to B-spline coeffs; apply() dispatches on provenance (coeffs -> fit(); pre-gridded -> use as-is), then both routes share one _resample_with_fieldmap helper (the formerly duplicated tail). Guard added for the empty (no coeffs, no mapped) case. - Drop _dynamic_unwarp_parallel and the apply_dynamic_unwarp wrapper; the MEDIC apply node constructs B0FieldTransform(mapped=...).apply(...) directly, mirroring how ApplyCoeffsField drives the static path with coeffs.

Address review feedback on the warpkit-backed interfaces: - Rename the `n_cpus` trait to `num_threads` (default 1, nohash) on both UnwrapPhase and ComputeFieldmap so nipype syncs it with the Node's `n_procs`; drop the explicit `n_cpus=omp_nthreads` in the MEDIC workflow. - Drop the `list(...)` casts (InputMultiObject already yields a list) and replace `isdefined(...) else None` with `... or None`. - Remove the ValueError->RuntimeError try/except; let errors propagate. - Add a `desc` to `svd_filt`.

Separate the two concepts the old docstring conflated: fmap_hz must be co-gridded with moving (same voxel lattice, so the per-voxel scaling and coordinate shift broadcast element-wise) AND valued in the undistorted (target) sense. The prior wording ("already on the moving grid") read as source/distorted space, which it is not.

warpkit 1.5.0 removes the ``wrap_limit`` argument from ``warpkit.api.unwrap_phase``, so forwarding it raised TypeError: unwrap_phase() got an unexpected keyword argument 'wrap_limit' inside the ``unwrap`` node, failing test_dynamic_unwarp_run on both fixtures. The flag only existed to disable a cascade of hardcoded field-magnitude thresholds, which warpkit replaced with an automatic 2-pi branch selector (vanandrew/warpkit#32). There is no successor input to thread through, so the trait is dropped rather than renamed. Nothing in SDCFlows ever set it.

vanandrew mentioned this pull request May 8, 2026

ENH: Add optional warpkit MEDIC support for multi-echo BOLD distortion correction nipreps/fmriprep#3645

Open

vanandrew force-pushed the feat/medic-warpkit branch from 57ccc47 to 21ab1c6 Compare May 10, 2026 03:21

vanandrew marked this pull request as ready for review May 10, 2026 04:49

vanandrew changed the title ~~[WIP] [FEAT] MEDIC distortion correction via warpkit~~ [FEAT] MEDIC distortion correction via warpkit May 11, 2026

vanandrew mentioned this pull request May 11, 2026

FIX: correctness fixes for MEDIC pipeline DVSneuro/fmriprep#1

Merged

vanandrew force-pushed the feat/medic-warpkit branch 6 times, most recently from bcaf4ad to 9ecfbae Compare May 13, 2026 03:10

tsalo requested changes May 15, 2026

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tsalo reviewed May 15, 2026

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Comment thread sdcflows/utils/wrangler.py

vanandrew requested a review from tsalo May 22, 2026 04:27

vanandrew force-pushed the feat/medic-warpkit branch from a4c4781 to b070878 Compare May 23, 2026 14:24

tsalo reviewed Jun 2, 2026

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Comment thread sdcflows/workflows/fit/medic.py Outdated

tsalo reviewed Jun 2, 2026

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Comment thread pyproject.toml Outdated

vanandrew force-pushed the feat/medic-warpkit branch from da9d07b to c55efd0 Compare June 2, 2026 20:36

vanandrew force-pushed the feat/medic-warpkit branch from c55efd0 to b0a6904 Compare June 2, 2026 20:37

vanandrew added 29 commits August 8, 2026 20:18

[FIX] warpkit: drop noise_frames trait

c752a9b

BIDS keeps trailing noise frames in separate noRF files, so SDCFlows shouldn't carry an interface input for them — let warpkit's default of zero apply.

[REF] medic: build UnwrapPhase/ComputeFieldmap nodes with ctor inputs

1c40300

Passing n_cpus and debug through the interface constructor keeps node construction in one place and removes the post-init mutation pattern.

[MAINT] zenodo: add Andrew Van (Washington University in St. Louis) a…

678107e

…s contributor

[CI] pin free-disk-space to v1.3.1

b132fd3

[MAINT] bump warpkit minimum to 1.2.2

e745e79

[FIX] medic: correct MEDIC citation key to van2026medic

7fd3b38

[MAINT] warpkit: bump minimum version to 1.4.0

fb9306d

bump warpkit version to 1.4.1

ea5d562

bump warpkit version to 1.5.0

6116f51

vanandrew force-pushed the feat/medic-warpkit branch from 71f7ba7 to aab352e Compare August 9, 2026 01:18

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Summary

What's new

Workflows

Interfaces

Detection / dispatch

Plumbing

Packaging

Validation

Known compromises

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vanandrew commented Apr 26, 2026 •

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codecov Bot commented Apr 26, 2026 •

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