Warning: 8GB of RAM is available within your Docker environment. Some parts of fMRIprep may fail to complete

[zddzxxsmile]

I run the ubuntu linux (virtual box) in win10 system (RAM=8G). When I input fmriprep-docker, Warning: “<8GB of RAM is available within your Docker environment. Some parts of fMRIprep may fail to complete. Continue anyway? [y/N]” I pressed y and I only preprocess a single structural T1 nii.gz, it took nearly 12 hours but failed finally. There is only one txt file in the path ~/output/fmriprep/sub-01/anat/. How long the preprocess generally takes? And the reason of my failure might due to the RAM or the memory is not enough?

[effigies]

How many cores do you have, and what speed? The longest steps are going to be:

1) FreeSurfer recon-all (you can disable this with --fs-no-reconall) 2) T1w-MNI normalization 3) Skull stripping

How quickly these run is going to be a function of processors more than RAM, though it's possible that RAM constraints could prevent some jobs from running simultaneously.

[zddzxxsmile]

My CPU is Intel Core i5-7500 3.4GHz with 4-cores. Thanks, I will try again.

[effigies]

Without FreeSurfer, I'd expect it to finish within 2 hours. I don't have a good estimate for FreeSurfer on 4 cores, but I'd guess on the order of 8-9 hours.

[zddzxxsmile]

-------- freesurfer-Linux-centos6_x86_64-stable-pub-v6.0.0-2beb96c -------- Setting up environment for FreeSurfer/FS-FAST (and FSL) FREESURFER_HOME /usr/local/freesurfer FSFAST_HOME /usr/local/freesurfer/fsfast FSF_OUTPUT_FORMAT nii.gz SUBJECTS_DIR /usr/local/freesurfer/subjects MNI_DIR /usr/local/freesurfer/mni zhoudongdong@zhoudongdong-VirtualBox:~$ sudo rm -rf ~/output [sudo] zhoudongdong 的密码： zhoudongdong@zhoudongdong-VirtualBox:~$ export FS_LICENSE=/usr/local/freesurfer/license.txt zhoudongdong@zhoudongdong-VirtualBox:~$ fmriprep-docker --anat-only --fs-no-reconall \

~/data ~/output participant \

--ignore fieldmaps

Warning: <8GB of RAM is available within your Docker environment. Some parts of fMRIPrep may fail to complete. Continue anyway? [y/N]RUNNING: docker run --rm -it -v /usr/local/freesurfer/license.txt:/opt/freesurfer/license.txt:ro -v /home/zhoudongdong/data:/data:ro -v /home/zhoudongdong/output:/out poldracklab/fmriprep:1.2.1 /data /out participant --anat-only --fs-no-reconall --ignore fieldmaps /usr/local/miniconda/lib/python3.6/site-packages/bids/grabbids/init.py:6: FutureWarning: grabbids has been renamed to layout in version 0.6.5, and will be removed in version 0.8 warnings.warn("grabbids has been renamed to layout in version 0.6.5, and will be removed in version 0.8", FutureWarning) /usr/local/miniconda/lib/python3.6/site-packages/bids/grabbids/init.py:6: FutureWarning: grabbids has been renamed to layout in version 0.6.5, and will be removed in version 0.8 warnings.warn("grabbids has been renamed to layout in version 0.6.5, and will be removed in version 0.8", FutureWarning) 181109-15:02:25,640 nipype.workflow IMPORTANT:

Running fMRIPREP version 1.2.1:
  * BIDS dataset path: /data.
  * Participant list: ['01'].
  * Run identifier: 20181109-150225_911f5960-2d5d-4f6b-92f2-b861461219d5.

181109-15:02:25,640 nipype.workflow WARNING: Option --debug is deprecated and has no effect /usr/local/miniconda/lib/python3.6/site-packages/bids/layout/bids_layout.py:116: UserWarning: 'dataset_description.json' file is missing from project root. You may want to set the root path to a valid BIDS project. warnings.warn("'dataset_description.json' file is missing from " 181109-15:02:27,612 nipype.workflow IMPORTANT: Works derived from this fMRIPrep execution should include the following boilerplate:

Results included in this manuscript come from preprocessing performed using fMRIPprep 1.2.1 (@fmriprep1; @fmriprep2; RRID:SCR_016216), which is based on Nipype 1.1.4 (@nipype1; @nipype2; RRID:SCR_002502).

Anatomical data preprocessing

: The T1-weighted (T1w) image was corrected for intensity non-uniformity (INU) using N4BiasFieldCorrection [@n4, ANTs 2.2.0], and used as T1w-reference throughout the workflow. The T1w-reference was then skull-stripped using antsBrainExtraction.sh (ANTs 2.2.0), using OASIS as target template. Spatial normalization to the ICBM 152 Nonlinear Asymmetrical template version 2009c [@mni, RRID:SCR_008796] was performed through nonlinear registration with antsRegistration [ANTs 2.2.0, RRID:SCR_004757, @ants], using brain-extracted versions of both T1w volume and template. Brain tissue segmentation of cerebrospinal fluid (CSF), white-matter (WM) and gray-matter (GM) was performed on the brain-extracted T1w using fast [FSL 5.0.9, RRID:SCR_002823, @fsl_fast].

Many internal operations of fMRIPrep use Nilearn 0.4.2 [@nilearn, RRID:SCR_001362], mostly within the functional processing workflow. For more details of the pipeline, see the section corresponding to workflows in fMRIPrep's documentation.

References

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