The exit status of the task that caused the workflow execution to fail was: 1
.
The full error message was:
Error executing process > 'postprocess (1)' Caused by: Process `postprocess (1)` terminated with an error exit status (1) Command executed: if false; then riken_flag="--includes_riken" else riken_flag="" fi cp /app/pipelines/gnps_ml_processing_workflow/GNPS_ML_Processing/bin/smiles_mapping_cache.json ./smiles_mapping_cache.json python3 /app/pipelines/gnps_ml_processing_workflow/GNPS_ML_Processing/bin/GNPS2_Postprocessor.py --includes_massbank --smiles_mapping_cache "smiles_mapping_cache.json" $riken_flag Command exit status: 1 Command output: 523.5 1 217.2 1 [M+H-C9H10O5]+ 1 Name: count, Length: 232, dtype: int64 Adduct Unknown 1466 [M+H-2H2O]+ 1050 [M+HCOO]- 1015 [M+CH3COO]-/[M-CH3]- 633 [M-H2O]+ 284 [M]- 239 M+FA- 66 Cat 63 -- 53 M+H+Na 48 [M+H-NH3]+ 31 M+3H 31 M+NH3 30 [(M+CH3COOH)-H]- 22 M-H+Na 21 Unk 18 M+H-CH3NH2 16 [M]+* 15 [M-CH3]- 14 [M-H-CO2-2HF]- 13 Name: count, dtype: int64 Warning: 6417 entries have Adducts that are not in the expected format, these will be removed. Adduct [M]1+ 6417 Name: count, dtype: int64 New Length: 916170 Warning: 231916 entries have Charge and Adduct Charge that are not equivalent, Adduct Charge will be prefered. Of the 231916 entires, 91367 have Charge of 0. Lost 0 entries due to Charge and Adduct Charge disagreement. Lost 0 entries due to Ion_Mode collision energy imputation. Lost 0 entries due to Compund_Name collision energy imputation. Imputing 2233 collision energies using the GNPS_Inst field. Lost 0 entries due to GNPS_Inst collision energy imputation. Imputing 350 positive ion modes using the Charge field. Imputing 614 negative ion modes using the Charge field. Correcting 1697 positive ion modes using the Charge field. Correcting 337 negative ion modes using the Charge field. Lost 0 entries due to Ion_Mode imputation. Lost 0 entries due to Manufacturer cleaning. Length of summary after basic cleaning: 916170 Done in 0:02:30.642183 seconds Cleaning up smiles strings Begining SMILES cleaning Loaded smiles_mapping_cache Begining SMILES tautomerization Command error: [16:42:33] Can't kekulize mol. Unkekulized atoms: 2 5 6 [16:42:33] Can't kekulize mol. Unkekulized atoms: 2 3 5 [16:42:33] Can't kekulize mol. Unkekulized atoms: 2 5 6 81%|████████ | 12704/15683 [00:46<00:02, 1075.28it/s] 83%|████████▎ | 12960/15683 [00:53<00:23, 115.22it/s] 83%|████████▎ | 13045/15683 [00:55<00:25, 104.73it/s] 84%|████████▎ | 13120/15683 [00:55<00:22, 116.41it/s] 84%|████████▍ | 13184/15683 [00:55<00:19, 129.01it/s] 85%|████████▍ | 13312/15683 [00:55<00:14, 167.82it/s][16:42:43] Can't kekulize mol. Unkekulized atoms: 3 10 86%|████████▌ | 13440/15683 [00:56<00:11, 196.42it/s] 87%|████████▋ | 13568/15683 [00:56<00:09, 221.52it/s] 87%|████████▋ | 13696/15683 [00:57<00:09, 216.53it/s] 87%|████████▋ | 13696/15683 [01:16<00:09, 216.53it/s][16:43:22] Tautomer enumeration stopped at 28718 tautomers: max transforms reached [16:43:47] Tautomer enumeration stopped at 38986 tautomers: max transforms reached [16:43:49] Tautomer enumeration stopped at 38986 tautomers: max transforms reached [16:43:55] Tautomer enumeration stopped at 35157 tautomers: max transforms reached [16:44:03] Can't kekulize mol. Unkekulized atoms: 2 25 [16:44:03] Can't kekulize mol. Unkekulized atoms: 2 25 88%|████████▊ | 13824/15683 [02:16<05:48, 5.33it/s] [16:44:07] Can't kekulize mol. Unkekulized atoms: 2 6 [16:44:25] Tautomer enumeration stopped at 21672 tautomers: max transforms reached [16:44:30] Tautomer enumeration stopped at 58034 tautomers: max transforms reached [16:44:33] Tautomer enumeration stopped at 14427 tautomers: max transforms reached [16:44:33] Can't kekulize mol. Unkekulized atoms: 2 30 Traceback (most recent call last): File "/app/pipelines/gnps_ml_processing_workflow/GNPS_ML_Processing/bin/GNPS2_Postprocessor.py", line 812, inmain() File "/app/pipelines/gnps_ml_processing_workflow/GNPS_ML_Processing/bin/GNPS2_Postprocessor.py", line 807, in main postprocess_files(csv_path, mgf_path, File "/app/pipelines/gnps_ml_processing_workflow/GNPS_ML_Processing/bin/GNPS2_Postprocessor.py", line 696, in postprocess_files summary = clean_smiles(summary, smiles_mapping_cache=smiles_mapping_cache) File "/app/pipelines/gnps_ml_processing_workflow/GNPS_ML_Processing/bin/GNPS2_Postprocessor.py", line 379, in clean_smiles cleaned_tautomers = Parallel(n_jobs=TAUTOMERIZATION_PARALLEL_WORKERS)(delayed(tautomerize_smiles)(x) for x in tqdm(unique_cleaned_smiles)) File "/app/pipelines/conda_envs/gnps2_ml_processing_env/lib/python3.8/site-packages/joblib/parallel.py", line 1952, in __call__ return output if self.return_generator else list(output) File "/app/pipelines/conda_envs/gnps2_ml_processing_env/lib/python3.8/site-packages/joblib/parallel.py", line 1595, in _get_outputs yield from self._retrieve() File "/app/pipelines/conda_envs/gnps2_ml_processing_env/lib/python3.8/site-packages/joblib/parallel.py", line 1699, in _retrieve self._raise_error_fast() File "/app/pipelines/conda_envs/gnps2_ml_processing_env/lib/python3.8/site-packages/joblib/parallel.py", line 1734, in _raise_error_fast error_job.get_result(self.timeout) File "/app/pipelines/conda_envs/gnps2_ml_processing_env/lib/python3.8/site-packages/joblib/parallel.py", line 736, in get_result return self._return_or_raise() File "/app/pipelines/conda_envs/gnps2_ml_processing_env/lib/python3.8/site-packages/joblib/parallel.py", line 754, in _return_or_raise raise self._result joblib.externals.loky.process_executor.TerminatedWorkerError: A worker process managed by the executor was unexpectedly terminated. This could be caused by a segmentation fault while calling the function or by an excessive memory usage causing the Operating System to kill the worker. The exit codes of the workers are {SIGKILL(-9)} Work dir: /app/work/35/0a0960396f6c4501e5946ed68c043e Tip: you can try to figure out what's wrong by changing to the process work dir and showing the script file named `.command.sh`
nextflow run /app/pipelines/gnps_ml_processing_workflow/GNPS_ML_Processing/nf_workflow.nf --GNPS_json_path /output/ALL_GNPS_NO_PROPOGATED.json --output_dir /output/cleaned_data/ --conda_path /app/pipelines/conda_envs/gnps2_ml_processing_env --matchms_conda_path /app/pipelines/conda_envs/matchms_env --api_cache /output/structure_classification/ -with-report /output/cleaned_data/ml_pipeline_report.html
6208b6b06139a8e3a15c4499c589c534
7a822b08-c220-44f4-b066-d5434b711ca2
These plots give an overview of the distribution of resource usage for each process.
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