Hi all,
I used newest version of fmriprep (1.4.1) on my dataset, but it finished with a bunch of errors. All errors are related to ica_aroma node or func_derivatives node (but only in MNI152NLin6Asym space that is also related to AROMA). Errors result in many missing files varying from subject to subject (although all bold_preproc files are created): some subjects are missing confounds files or json files related to preprocessed imaging files. Errors for specific subjects also vary from subject to subjects but most common ones are:
Memory error
Node Name: fmriprep_wf.single_subject_m33_wf.func_preproc_task_prlpun_wf.func_derivatives_wf.ds_bold_std
File: /out/fmriprep/sub-m33/log/20190819-144336_d25ee372-868d-4b3e-a1f8-6ce6c259f943/crash-20190821-193504-root-ds_bold_std.a1-788e4e76-fc7b-4d31-9112-9a2935ea1236.txt
Working Directory: /scratch/fmriprep_wf/single_subject_m33_wf/func_preproc_task_prlpun_wf/func_derivatives_wf/_key_MNI152NLin6Asym/ds_bold_std
Inputs:
base_directory: /out
check_hdr: True
compress: True
desc: preproc
extra_values:
in_file: ['/scratch/fmriprep_wf/single_subject_m33_wf/func_preproc_task_prlpun_wf/bold_std_trans_wf/_key_MNI152NLin6Asym/merge/vol0000_xform-00000_merged.nii.gz']
keep_dtype: True
meta_dict:
source_file: /data/sub-m33/func/sub-m33_task-prlpun_bold.nii.gz
space: MNI152NLin6Asym
Traceback (most recent call last):
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py", line 316, in _send_procs_to_workers
self.procs[jobid].run(updatehash=updatehash)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py", line 472, in run
result = self._run_interface(execute=True)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py", line 563, in _run_interface
return self._run_command(execute)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py", line 643, in _run_command
result = self._interface.run(cwd=outdir)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/interfaces/base/core.py", line 375, in run
runtime = self._run_interface(runtime)
File "/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/interfaces/bids.py", line 494, in _run_interface
nii.__class__(np.array(nii.dataobj), nii.affine, hdr).to_filename(
File "/usr/local/miniconda/lib/python3.7/site-packages/nibabel/arrayproxy.py", line 356, in __array__
return apply_read_scaling(raw_data, self._slope, self._inter)
File "/usr/local/miniconda/lib/python3.7/site-packages/nibabel/volumeutils.py", line 965, in apply_read_scaling
arr = arr * slope
MemoryError
Aroma error
Node Name: fmriprep_wf.single_subject_m14_wf.func_preproc_task_prlpun_wf.ica_aroma_wf.ica_aroma
File: /out/fmriprep/sub-m14/log/20190816-094855_b4ae6d79-b309-4e83-a722-a5801787ac44/crash-20190819-114145-root-ica_aroma-9e78cb96-0cac-4e01-a45c-0113c8045848.txt
Working Directory: /scratch/fmriprep_wf/single_subject_m14_wf/func_preproc_task_prlpun_wf/ica_aroma_wf/ica_aroma
Inputs:
TR: 2.0
args:
compress_report: auto
denoise_type: nonaggr
dim:
environ: {}
feat_dir:
fnirt_warp_file:
in_file: /scratch/fmriprep_wf/single_subject_m14_wf/func_preproc_task_prlpun_wf/ica_aroma_wf/smooth/vol0000_xform-00000_merged_smooth.nii.gz
mask: /scratch/fmriprep_wf/single_subject_m14_wf/func_preproc_task_prlpun_wf/bold_std_trans_wf/_key_MNI152NLin6Asym/mask_std_tfm/ref_bold_corrected_brain_mask_maths_trans.nii.gz
mat_file:
melodic_dir: /scratch/fmriprep_wf/single_subject_m14_wf/func_preproc_task_prlpun_wf/ica_aroma_wf/melodic
motion_parameters: /scratch/fmriprep_wf/single_subject_m14_wf/func_preproc_task_prlpun_wf/bold_hmc_wf/normalize_motion/motion_params.txt
out_dir: out
out_report: ica_aroma_reportlet.svg
report_mask: /scratch/fmriprep_wf/single_subject_m14_wf/func_preproc_task_prlpun_wf/bold_std_trans_wf/_key_MNI152NLin6Asym/mask_std_tfm/ref_bold_corrected_brain_mask_maths_trans.nii.gz
Traceback (most recent call last):
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/pipeline/plugins/multiproc.py", line 69, in run_node
result['result'] = node.run(updatehash=updatehash)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py", line 472, in run
result = self._run_interface(execute=True)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py", line 563, in _run_interface
return self._run_command(execute)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/pipeline/engine/nodes.py", line 643, in _run_command
result = self._interface.run(cwd=outdir)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/interfaces/base/core.py", line 376, in run
runtime = self._post_run_hook(runtime)
File "/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/interfaces/segmentation.py", line 171, in _post_run_hook
outputs = self.aggregate_outputs(runtime=runtime)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/interfaces/base/core.py", line 478, in aggregate_outputs
raise error
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/interfaces/base/core.py", line 471, in aggregate_outputs
setattr(outputs, key, val)
File "/usr/local/miniconda/lib/python3.7/site-packages/nipype/interfaces/base/traits_extension.py", line 112, in validate
self.info_text, value))
traits.trait_errors.TraitError: The trait 'nonaggr_denoised_file' of an ICA_AROMAOutputSpecRPT instance is an existing file name, but the path '/scratch/fmriprep_wf/single_subject_m14_wf/func_preproc_task_prlpun_wf/ica_aroma_wf/ica_aroma/out/denoised_func_data_nonaggr.nii.gz' does not exist.
It seems like AROMA error is correlated with missing confounds file. Interestingly all HTML reports have plots for correlation among nuissance regressors. I was running fmriprep on two lab PC’s for selected subjects and one PC had significantly less errors than the other (although type of error was identical).
Any ideas what is causing the problem? Now I am running fmriprep without --use-aroma flag to see if problem remain. I can also try running downgraded version of fmriprep to see if there is improvement.
Thanks in advance,
Kamil