+ dssource=ria+file:///data/project/QC_workflow/TMP/RIA_QCworkflow/inputstore#aae8905a-985f-46fb-91f5-35c772654ddd + pushgitremote=file:///data/project/QC_workflow/TMP/RIA_QCworkflow/aae/8905a-985f-46fb-91f5-35c772654ddd + subid=sub-cIVs032 + export 'DUCT_OUTPUT_PREFIX=logs/duct/sub-cIVs032_{datetime_filesafe}-{pid}_' + DUCT_OUTPUT_PREFIX='logs/duct/sub-cIVs032_{datetime_filesafe}-{pid}_' + datalad clone ria+file:///data/project/QC_workflow/TMP/RIA_QCworkflow/inputstore#aae8905a-985f-46fb-91f5-35c772654ddd ds [INFO] Attempting a clone into /var/lib/condor/execute/dir_3951239/ds [INFO] Attempting to clone from file:///data/project/QC_workflow/TMP/RIA_QCworkflow/inputstore/aae/8905a-985f-46fb-91f5-35c772654ddd to /var/lib/condor/execute/dir_3951239/ds [INFO] Completed clone attempts for Dataset(/var/lib/condor/execute/dir_3951239/ds) + cd ds + git remote add outputstore file:///data/project/QC_workflow/TMP/RIA_QCworkflow/aae/8905a-985f-46fb-91f5-35c772654ddd + git checkout -b job_sub-cIVs032_10066492 Switched to a new branch 'job_sub-cIVs032_10066492' + datalad get -n sourcedata/raw/ [INFO] Attempting a clone into /var/lib/condor/execute/dir_3951239/ds/sourcedata/raw [INFO] Attempting to clone from file:///data/project/QC_workflow/TMP/RIA_QCworkflow/inputstore/9e5/e9b46-fb3d-48cf-b766-89923247370d to /var/lib/condor/execute/dir_3951239/ds/sourcedata/raw [INFO] Attempting to clone from https://github.com/OpenNeuroDatasets/ds003416.git to /var/lib/condor/execute/dir_3951239/ds/sourcedata/raw [INFO] Start enumerating objects [INFO] Start counting objects [INFO] Start compressing objects [INFO] Start receiving objects [INFO] Start resolving deltas [INFO] Completed clone attempts for Dataset(/var/lib/condor/execute/dir_3951239/ds/sourcedata/raw) [INFO] Remote origin not usable by git-annex; setting annex-ignore [INFO] https://github.com/OpenNeuroDatasets/ds003416.git/config download failed: Not Found [INFO] access to 1 dataset sibling s3-PRIVATE not auto-enabled, enable with: | datalad siblings -d "/var/lib/condor/execute/dir_3951239/ds/sourcedata/raw" enable -s s3-PRIVATE + datalad containers-run -m 'Compute MRIQC for sub-cIVs032' -n bids-mriqc -i sourcedata/raw/sub-cIVs032 -i sourcedata/raw/dataset_description.json mriqc sourcedata/raw . participant --participant-label sub-cIVs032 --no-datalad-get --no-sub --verbose --nprocs 1 --mem 3000 --work-dir /tmp --float32 --verbose-reports [INFO] Making sure inputs are available (this may take some time) [INFO] Attempting a clone into /var/lib/condor/execute/dir_3951239/ds/code/containers [INFO] Attempting to clone from file:///data/project/QC_workflow/TMP/RIA_QCworkflow/inputstore/b02/e63c2-62c1-11e9-82b0-52540040489c to /var/lib/condor/execute/dir_3951239/ds/code/containers [INFO] Attempting to clone from https://github.com/ReproNim/containers.git to /var/lib/condor/execute/dir_3951239/ds/code/containers [INFO] Start enumerating objects [INFO] Start counting objects [INFO] Start compressing objects [INFO] Start receiving objects [INFO] Start resolving deltas [INFO] Completed clone attempts for Dataset(/var/lib/condor/execute/dir_3951239/ds/code/containers) [INFO] Remote origin not usable by git-annex; setting annex-ignore [INFO] https://github.com/ReproNim/containers.git/config download failed: Not Found [INFO] == Command start (output follows) ===== 2025-10-09T23:54:02+0200 [INFO ] con-duct: duct 0.16.0 is executing 'singularity exec -W /tmp/singtmp.a8FoNk -B /var/lib/condor/execute/dir_3951239/ds/code/containers/binds/zoneinfo/UTC:/etc/localtime -B /tmp/singtmp.a8FoNk/tmp:/tmp -B /tmp/singtmp.a8FoNk/var/tmp:/var/tmp -e -B /var/lib/condor/execute/dir_3951239/ds -H /var/lib/condor/execute/dir_3951239/ds/code/containers/binds/HOME --pwd /var/lib/condor/execute/dir_3951239/ds code/containers/images/bids/bids-mriqc--24.0.2.sing mriqc sourcedata/raw . participant --participant-label sub-cIVs032 --no-datalad-get --no-sub --verbose --nprocs 1 --mem 3000 --work-dir /tmp --float32 --verbose-reports'... 2025-10-09T23:54:02+0200 [INFO ] con-duct: Log files will be written to logs/duct/sub-cIVs032_2025.10.09T23.54.02-4041069_ Fontconfig error: No writable cache directories Fontconfig error: No writable cache directories Fontconfig error: No writable cache directories Fontconfig error: No writable cache directories Fontconfig error: No writable cache directories Fontconfig error: No writable cache directories Fontconfig error: No writable cache directories Fontconfig error: No writable cache directories Fontconfig error: No writable cache directories /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: divide by zero encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: invalid value encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: divide by zero encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: invalid value encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: divide by zero encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: invalid value encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: divide by zero encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: invalid value encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: divide by zero encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: invalid value encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: divide by zero encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: invalid value encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: divide by zero encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: invalid value encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: divide by zero encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/dipy/denoise/noise_estimate.py:240: RuntimeWarning: invalid value encountered in divide s = sum_m2 / (2 * K * sigma_init**2) /opt/conda/lib/python3.11/site-packages/mriqc/interfaces/anatomical.py:490: RuntimeWarning: divide by zero encountered in divide bg_data[bg_data > 0] = bg_data[bg_data > 0] / bg_spread /opt/conda/lib/python3.11/site-packages/mriqc/qc/anatomical.py:491: RuntimeWarning: divide by zero encountered in scalar divide data *= 100 / np.percentile(data, 99) /opt/conda/lib/python3.11/site-packages/mriqc/qc/anatomical.py:491: RuntimeWarning: invalid value encountered in multiply data *= 100 / np.percentile(data, 99) Traceback (most recent call last): File "/opt/conda/bin/mriqc", line 8, in sys.exit(main()) ^^^^^^ File "/opt/conda/lib/python3.11/site-packages/mriqc/cli/run.py", line 178, in main mriqc_wf.run(**_plugin) File "/opt/conda/lib/python3.11/site-packages/nipype/pipeline/engine/workflows.py", line 638, in run runner.run(execgraph, updatehash=updatehash, config=self.config) File "/opt/conda/lib/python3.11/site-packages/mriqc/engine/plugin.py", line 196, in run notrun.append(self._clean_queue(jobid, graph, result=result)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/mriqc/engine/plugin.py", line 259, in _clean_queue raise RuntimeError(''.join(result['traceback'])) RuntimeError: Traceback (most recent call last): File "/opt/conda/lib/python3.11/site-packages/mriqc/engine/plugin.py", line 64, in run_node result['result'] = node.run(updatehash=updatehash) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/nipype/pipeline/engine/nodes.py", line 527, in run result = self._run_interface(execute=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/nipype/pipeline/engine/nodes.py", line 645, in _run_interface return self._run_command(execute) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/nipype/pipeline/engine/nodes.py", line 771, in _run_command raise NodeExecutionError(msg) nipype.pipeline.engine.nodes.NodeExecutionError: Exception raised while executing Node ComputeQI2. Traceback: Traceback (most recent call last): File "/opt/conda/lib/python3.11/site-packages/nipype/interfaces/base/core.py", line 397, in run runtime = self._run_interface(runtime) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/mriqc/interfaces/anatomical.py", line 378, in _run_interface qi2, out_file = art_qi2(imdata, airdata) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/mriqc/qc/anatomical.py", line 497, in art_qi2 kde_skl = KernelDensity(kernel='gaussian', bandwidth=4.0).fit(modelx[:, np.newaxis]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/sklearn/base.py", line 1351, in wrapper return fit_method(estimator, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/sklearn/neighbors/_kde.py", line 226, in fit X = self._validate_data(X, order="C", dtype=np.float64) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/sklearn/base.py", line 633, in _validate_data out = check_array(X, input_name="X", **check_params) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/conda/lib/python3.11/site-packages/sklearn/utils/validation.py", line 1003, in check_array _assert_all_finite( File "/opt/conda/lib/python3.11/site-packages/sklearn/utils/validation.py", line 126, in _assert_all_finite _assert_all_finite_element_wise( File "/opt/conda/lib/python3.11/site-packages/sklearn/utils/validation.py", line 175, in _assert_all_finite_element_wise raise ValueError(msg_err) ValueError: Input X contains NaN. KernelDensity does not accept missing values encoded as NaN natively. For supervised learning, you might want to consider sklearn.ensemble.HistGradientBoostingClassifier and Regressor which accept missing values encoded as NaNs natively. Alternatively, it is possible to preprocess the data, for instance by using an imputer transformer in a pipeline or drop samples with missing values. See https://scikit-learn.org/stable/modules/impute.html You can find a list of all estimators that handle NaN values at the following page: https://scikit-learn.org/stable/modules/impute.html#estimators-that-handle-nan-values 2025-10-10T00:47:14+0200 [INFO ] con-duct: Summary: Exit Code: 1 Command: singularity exec -W /tmp/singtmp.a8FoNk -B /var/lib/condor/execute/dir_3951239/ds/code/containers/binds/zoneinfo/UTC:/etc/localtime -B /tmp/singtmp.a8FoNk/tmp:/tmp -B /tmp/singtmp.a8FoNk/var/tmp:/var/tmp -e -B /var/lib/condor/execute/dir_3951239/ds -H /var/lib/condor/execute/dir_3951239/ds/code/containers/binds/HOME --pwd /var/lib/condor/execute/dir_3951239/ds code/containers/images/bids/bids-mriqc--24.0.2.sing mriqc sourcedata/raw . participant --participant-label sub-cIVs032 --no-datalad-get --no-sub --verbose --nprocs 1 --mem 3000 --work-dir /tmp --float32 --verbose-reports Log files location: logs/duct/sub-cIVs032_2025.10.09T23.54.02-4041069_ Wall Clock Time: 3191.647 sec Memory Peak Usage (RSS): 13.5 GB Memory Average Usage (RSS): 1.8 GB Virtual Memory Peak Usage (VSZ): 19.1 GB Virtual Memory Average Usage (VSZ): 5.1 GB Memory Peak Percentage: 2.30% Memory Average Percentage: 0.15% CPU Peak Usage: 308.10% Average CPU Usage: 90.02% [INFO] == Command exit (modification check follows) =====