axiezai / pipetography Goto Github PK

Since atlas registration occurs without changing labels, the rounding step is now redundant.

Change default freesurfer recon-all to off, and use 5ttgen white matter mask for streamline generation option. But whole brain mask should apply as well.

Either as user input or a separate directory that's not part of the BIDS root.

List the pip installable libraries in settings.ini

Create substitutions for datasink so the output paths are in consistent with BIDS

Change hippocampal subfield inputs from 6.0 to 7.1 format, or disable completely.

doc string tests and sample pipeline testing?

Inside singularity we have

To run interactively or as a job execution, you will need a few flags:

-e -c flags for a clean environnment upon container start
-B to bind your data & code directories.
Example: singularity shell -e -c -B <BIDS_DIR>:<SINGULARITY_BIDS_DIR> {Path to singularity .sif}

we should make sure this works and add a new section outside install

This produces asymmetric segmentation resulting in asymmetric connectomes (hemispheres)

Insert the following to each notebook when recreating docs:

import warnings
warnings.filterwarnings('ignore')

This will clean up all the meaningless warning msgs in htmls.

Right now an activation of the tracts environment is required to run any code. This shouldn't be necessary in the container.

Possible improvements:

• Implement FSL reorient at beginning for anat/dwi
• Use FSL BET's output T1w image with -premasked option for 5ttgen

Change the base_dir default to a separate destination than datasink destination so the final outputs and intermediate files are separate.

self.workflow = Workflow(
            name=wf_name,
            base_dir=os.path.join(self.bids_dir, "derivatives"),
        )

interpolation defaults to Linear and is active even if args has an interpolation input, and interpolation is not hard coded to pre defined cases. So interpolation = genericLabel should work, test it out by printing out the cmdline first.

        if self.debug_mode:
            self.workflow.config["execution"] = {
                "use_relative_paths": "True",
                "hash_method": "content",
                "stop_on_first_crash": "True",
            }
        else:
           self.workflow.config["execution"] = {
                "use_relative_paths": "True",
                "hash_method": "content",
                "stop_on_first_crash": "True",
                "remove_node_directories": "True",
            }

Make this change for both pipeline and connectomes

I was using pipetography.connectome that crashed on the SIFT2 node. The followings are the error message.

SLURM log file:

```220124-01:02:20,949` nipype.workflow INFO:
[Node] Finished "LinearRegistration", elapsed time 2063.624523s.
220124-01:17:09,232 nipype.workflow INFO:
[Node] Finished "NonLinearRegistration", elapsed time 1052.248168s.
Traceback (most recent call last):
File "/test_BIDS_dwi2run/code/pipetography/postprocess_bids.py", line 21, in
main()
File "/test_BIDS_dwi2run/code/pipetography/postprocess_bids.py", line 18, in main
connectomes.run_pipeline(parallel=4)
File "/opt/pipetography/pipetography/connectomes.py", line 128, in run_pipeline
self.workflow.run('MultiProc', plugin_args = {'n_procs': parallel})
File "/opt/nipype/nipype/pipeline/engine/workflows.py", line 638, in run
runner.run(execgraph, updatehash=updatehash, config=self.config)
File "/opt/nipype/nipype/pipeline/plugins/base.py", line 166, in run
self._clean_queue(jobid, graph, result=result)
File "/opt/nipype/nipype/pipeline/plugins/base.py", line 244, in _clean_queue
raise RuntimeError("".join(result["traceback"]))
RuntimeError: Traceback (most recent call last):
File "/opt/nipype/nipype/pipeline/plugins/multiproc.py", line 67, in run_node
result["result"] = node.run(updatehash=updatehash)
File "/opt/nipype/nipype/pipeline/engine/nodes.py", line 524, in run
result = self._run_interface(execute=True)
File "/opt/nipype/nipype/pipeline/engine/nodes.py", line 642, in _run_interface
return self._run_command(execute)
File "/opt/nipype/nipype/pipeline/engine/nodes.py", line 751, in _run_command
f"Exception raised while executing Node {self.name}.\n\n{result.runtime.traceback}"
nipype.pipeline.engine.nodes.NodeExecutionError: Exception raised while executing Node SIFT2.

RuntimeError: subprocess exited with code 1.```

And the crash file message:

`Node inputs:
act =
args =
environ = {}
fd_scale_gm =
force =
in_file =
in_fod =
nthreads =
out_file = sift2.txt
proc_mask =
Traceback:
Traceback (most recent call last):
File "/opt/nipype/nipype/pipeline/plugins/multiproc.py", line 67, in run_node
result["result"] = node.run(updatehash=updatehash)
File "/opt/nipype/nipype/pipeline/engine/nodes.py", line 524, in run
result = self._run_interface(execute=True)
File "/opt/nipype/nipype/pipeline/engine/nodes.py", line 642, in _run_interface
return self._run_command(execute)
File "/opt/nipype/nipype/pipeline/engine/nodes.py", line 751, in _run_command
f"Exception raised while executing Node {self.name}.\n\n{result.runtime.traceback}"
nipype.pipeline.engine.nodes.NodeExecutionError: Exception raised while executing Node SIFT2.

RuntimeError: subprocess exited with code 1.`

Then I pasted the comman.txt in the SIFT2 working directory and ran the command script, the following error occurred:

Singularity> tcksift2 /test_BIDS_dwi2run/derivatives/streamlines/sub-UCSF002/ses-01/sub-UCSF002_ses-01_gmwmi2wm.tck /test_BIDS_dwi2run/code/pipetography/workingdir/connectomes/_session_id_01_subject_id_UCSF002/dwiFOD/wm.mif sift2.txt tcksift2: [100%] Creating homogeneous processing mask tcksift2: [100%] segmenting FODs tcksift2: [ERROR] invalid first line for key/value file "/test_BIDS_dwi2run/derivatives/streamlines/sub-UCSF002/ses-01/sub-UCSF002_ses-01_gmwmi2wm.tck" (expected "mrtrix tracks")

The file sub-UCSF002_ses-01_gmwmi2wm.tck exists, but somehow it showed this message.
Note that this same error occurred across different datasets.

missing filtering for full layout like in preprocessing

Something to replace nodes like ...

pipetography.preprocessing.anat
pipetography.preprocessing.dwi

Maybe...

Use docker because we need

• FSL
• ANTs
• mrtrix3

And these can't be pip/brew installed

Change neurodocker link for mrtrix3?

Install python and pip without conda for faster build time.

All commands should have adequate inputs now, but some are missing full functionality

Missing list.

If debug, save intermediate files, if not, delete.

Because whole-brain seeding may have advantages, and GMWMI generation may have disadvantages with data/image problems finding particular GM regions, make generating GMWMI=False by default. Whole-brain masks will be used for tractography seeding.

Update index.py/html with docker hub pull, singularity build, and job execution instructions.

Also update markdown formatting so the github page actually has consistent structure.