I am using my university's high-performance computing cluster (HPC), and it currently has TractSeg version 2.3 and sklearn installed. However, when I try to run the TractSeg command with Python version 3.7.7, I've encountered an error as follows:
TractSeg -i ${tractseg_template}peaks.nii.gz Traceback (most recent call last): File "/usr/local/python/3.7.7/bin/TractSeg", line 417, in <module> main() File "/usr/local/python/3.7.7/bin/TractSeg", line 162, in main parser.add_argument('--version', action='version', version=require("TractSeg")[0].version) File "/usr/local/python/3.7.7/lib/python3.7/site-packages/pkg_resources/__init__.py", line 900, in require needed = self.resolve(parse_requirements(requirements)) File "/usr/local/python/3.7.7/lib/python3.7/site-packages/pkg_resources/__init__.py", line 786, in resolve raise DistributionNotFound(req, requirers) pkg_resources.DistributionNotFound: The 'sklearn' distribution was not found and is required by TractSeg
Any guidance and suggestions are greatly appreciated, thank you!
Hi TractSeg developers,
I am using my university's high-performance computing cluster (HPC), and it currently has TractSeg version 2.3 and sklearn installed. However, when I try to run the TractSeg command with Python version 3.7.7, I've encountered an error as follows:
TractSeg -i ${tractseg_template}peaks.nii.gz Traceback (most recent call last): File "/usr/local/python/3.7.7/bin/TractSeg", line 417, in <module> main() File "/usr/local/python/3.7.7/bin/TractSeg", line 162, in main parser.add_argument('--version', action='version', version=require("TractSeg")[0].version) File "/usr/local/python/3.7.7/lib/python3.7/site-packages/pkg_resources/__init__.py", line 900, in require needed = self.resolve(parse_requirements(requirements)) File "/usr/local/python/3.7.7/lib/python3.7/site-packages/pkg_resources/__init__.py", line 786, in resolve raise DistributionNotFound(req, requirers) pkg_resources.DistributionNotFound: The 'sklearn' distribution was not found and is required by TractSegAny guidance and suggestions are greatly appreciated, thank you!