I've run into this problem. It's one of many you'll get trying to get this data to work. xcp-d is good enough to know that 223 is sub-223
Starting
on this line of xcp-d you can see the BIDS format it's xcp-d is looking for. My issue was all the bold data was `task<tasktype><run-id>` instead of `task-<task-type>_run-<run-id>`. Once I changed those, it started to work. And now it's failing on trying to collect the brain registration data. I'm getting
```
2024-11-18 15:33:06,030 [ WARNING] WARNING: Cannot detect name collisions for function 'nifti_masker_extractor'
Traceback (most recent call last):
File "/usr/local/miniconda/bin/xcp_d", line 8, in <module>
sys.exit(main())
File "/usr/local/miniconda/lib/python3.10/site-packages/xcp_d/cli/run.py", line 27, in main
parse_args(args=sys.argv[1:])
File "/usr/local/miniconda/lib/python3.10/site-packages/xcp_d/cli/parser.py", line 799, in parse_args
convert_to_bids(
File "/usr/local/miniconda/lib/python3.10/site-packages/xcp_d/ingression/abcdbids.py", line 73, in convert_dcan2bids
convert_dcan_to_bids_single_subject(
File "/usr/local/miniconda/lib/python3.10/site-packages/xcp_d/ingression/abcdbids.py", line 298, in convert_dcan_to_bids_single_subject
collect_hcp_confounds(
File "/usr/local/miniconda/lib/python3.10/site-packages/xcp_d/ingression/utils.py", line 182, in collect_hcp_confounds
brainreg = pd.DataFrame(
File "/usr/local/miniconda/lib/python3.10/site-packages/pandas/core/frame.py", line 778, in __init__
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
File "/usr/local/miniconda/lib/python3.10/site-packages/pandas/core/internals/construction.py", line 503, in dict_to_mgr
return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
File "/usr/local/miniconda/lib/python3.10/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
index = _extract_index(arrays)
File "/usr/local/miniconda/lib/python3.10/site-packages/pandas/core/internals/construction.py", line 677, in _extract_index
raise ValueError("All arrays must be of the same length")
ValueError: All arrays must be of the same length
```
For some reason the masks or data are different lengths. It's immensely frustrating