Error in Pycurv Step

[Kathir-66]

When I run Pycurv it failed for couple of tomograms the error was the following

Error message

/u/kaezhila/conda-envs/morphometrics/lib/python3.7/site-packages/numpy/core/fromnumeric.py:3441: RuntimeWarning: Mean of empty slice. out=out, **kwargs) /u/kaezhila/conda-envs/morphometrics/lib/python3.7/site-packages/numpy/core/_methods.py:189: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) Traceback (most recent call last): File "run_pycurv.py", line 71, in <module> cores=config["cores"]) File "/viper/u1/kaezhila/surface_morphometrics/curvature.py", line 47, in run_pycurv basename, seg_file, folder, scale, radius_hit, methods=['VV'], min_component=min_component, runtimes=runtimes_file, cores=cores, remove_wrong_borders=remove_wrong_borders) File "/viper/u1/kaezhila/surface_morphometrics/curvature_calculation.py", line 323, in new_workflow cores=cores, runtimes=runtimes) File "/u/kaezhila/conda-envs/morphometrics/lib/python3.7/site-packages/pycurv/vector_voting.py", line 92, in normals_directions_and_curvature_estimation runtimes=runtimes, graph_file=graph_file) File "/u/kaezhila/conda-envs/morphometrics/lib/python3.7/site-packages/pycurv/vector_voting.py", line 315, in normals_estimation sg.graph.vp.avg_normals[v] = avg_normal / np.linalg.norm(avg_normal) File "/u/kaezhila/conda-envs/morphometrics/lib/python3.7/site-packages/graph_tool/__init__.py", line 847, in __setitem__ self._PropertyMap__map[k] = v AttributeError: 'numpy.float64' object has no attribute '__iter__'

I am attaching the config file for reference

Config file

`
data_dir: "/ptmp/kaezhila/morphometrics/inputs/"
work_dir: "/ptmp/kaezhila/morphometrics/results/"
segmentation_values: # The value used to represent each feature, and the name of the feature.
OMM: 1
IMM: 2
ER: 11
surface_generation:
angstroms: false # Default scaling adjusts so surfaces are nm-scaled, if set to true surfaces are not rescaled and remain angstrom-scaled.
ultrafine: false # If true, the surface is generated with a new high quality protocol. This makes calculation much slower but the surface is much better for sampling density.
mesh_sampling: 1 # Approximate mesh sampling rate, for ultrafine mode
simplify: true # Non-simplified surfaces can be VERY slow, but are better for sampling the coulomb potential.
max_triangles: 300000 # If simplifying and more than this number of triangles are generated, the surface is decimated to this number
extrapolation_distance: 1.5 # Distance in nm (or angstroms, if angstrom setting is True) to extrapolate the surface
octree_depth: 9 # Increase if the surface is too smooth, decrease if surface is too jagged - but has a HUGE effect.
point_weight: 0.7 # Larger numbers have stronger weight towards fitting segmented points, smaller numbers have stronger weight towards generating a smooth surface
neighbor_count: 400 # Number of neighbors used for normal estimation. Should not need to adjust this, but I am exposing it as a tuning variable. Values over 50 seem to all be equivalently good...
smoothing_iterations: 1 # Number of smoothing iterations to perform for estimating normals. You should usually leave this at 1.
curvature_measurements:
radius_hit: 9 # This corresponds to the radius of the smallest feature of interest, roughly, for neighborhood determination. 8-15 seems to be a good range for mitochondria
min_component: 30 # The minimum number of triangles for a component to be considered for curvature measurement.
exclude_borders: 1 # Values greater than zero exclude the border from the curvature calculation by n nm/angstroms.
distance_and_orientation_measurements:
mindist: 3 # Minimum distance between two points for them to be considered for distance measurement.
maxdist: 400 # Maximum distance between two points for them to be considered for distance measurement.
tolerance: 0.1 # Tolerance for determining if a triangle is contacted by a line.
verticality: true # Measure verticality (angle relative to growth plane).
intra: # Intra-surface distance/orientation (verticality) measurements
- IMM
- OMM
- ER
relative_orientation: true # Measure relative orientation (angle relative to nearest neighbor surface).
inter: # Intersurface distance/orientation measurements. Writes out symmetrically so you do not need to give symmetric options.
OMM:
- IMM
- ER
IMM:
- ER

cores: 20 # Number of cores to use for parallel processing.

`

I am attaching couple of the $.surface.vtp files it failed for

[bbarad]

Looking at your surfaces I am almost certain it is not a problem with your files, nor is it an issue with your config as best I can tell. Can you share a pip freeze and any other system information?

It seems like for some reason the normal vector is getting generated as a single float instead of as a triple (or vector), which is odd - we've never run into this one. @hemanthkapa is actively working on potential issues w/ pycurv with newer versions of python/numpy (as part of our GUI effort) so I wonder if you're running into something new with that.

[Kathir-66]

Hi, Yes here is the pip freeze output

Please let me know if you would need anymore information would be happy to provide!

A GUI is really cool! What can I expect from that ?

pip freeze

`
(/u/kaezhila/conda-envs/morphometrics) [kaezhila@viper03 ~]$ pip freeze
aiofiles==22.1.0
aiosqlite==0.19.0
anyio==3.7.1
argon2-cffi==23.1.0
argon2-cffi-bindings==21.2.0
arrow==1.2.3
attrs==24.2.0
Babel==2.14.0
backcall==0.2.0
beautifulsoup4==4.13.4
bleach==6.0.0
cached-property==1.5.2
certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1725278078093/work/certifi
cffi @ file:///home/conda/feedstock_root/build_artifacts/cffi_1625835301720/work
charset-normalizer==3.4.1
click==8.1.8
cloudpickle==2.2.1
comm==0.1.4
cycler @ file:///home/conda/feedstock_root/build_artifacts/cycler_1635519461629/work
debugpy==1.7.0
decorator==5.1.1
defusedxml==0.7.1
dill==0.3.7
doit==0.34.2
entrypoints==0.4
exceptiongroup==1.2.2
fastjsonschema==2.21.1
fqdn==1.5.1
future==1.0.0
idna==3.10
imageio==2.31.2
importlib-metadata==6.7.0
importlib-resources==5.12.0
iniconfig==2.0.0
ipykernel==6.16.2
ipython==7.34.0
ipython-genutils==0.2.0
ipywidgets==8.1.6
isoduration==20.11.0
jedi==0.19.2
Jinja2==3.1.6
joblib==1.3.2
json5==0.9.16
jsonpointer==3.0.0
jsonschema==4.17.3
jupyter==1.1.1
jupyter-console==6.6.3
jupyter-events==0.6.3
jupyter-server==1.24.0
jupyter-ydoc==0.2.5
jupyter_client==7.4.9
jupyter_core==4.12.0
jupyter_server_fileid==0.9.3
jupyter_server_ydoc==0.8.0
jupyterlab==3.6.8
jupyterlab-pygments==0.2.2
jupyterlab_server==2.24.0
jupyterlab_widgets==3.0.14
kiwisolver @ file:///home/conda/feedstock_root/build_artifacts/kiwisolver_1657953088445/work
MarkupSafe==2.1.5
matplotlib @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-suite_1610582853335/work
matplotlib-inline==0.1.6
mistune==3.0.2
mrcfile==1.5.4
multiprocess==0.70.15
nbclassic==1.2.0
nbclient==0.7.4
nbconvert==7.6.0
nbformat==5.8.0
nest-asyncio==1.6.0
networkx==2.6.3
nibabel==4.0.2
notebook==6.5.7
notebook_shim==0.2.4
numpy @ file:///home/conda/feedstock_root/build_artifacts/numpy_1649806299270/work
packaging==24.0
pandas==1.3.5
pandocfilters==1.5.1
parso==0.8.4
pathos==0.3.1
patsy==1.0.1
pexpect==4.9.0
pickleshare==0.7.5
Pillow @ file:///home/conda/feedstock_root/build_artifacts/pillow_1660385854171/work
pkgutil_resolve_name==1.3.10
pluggy==1.2.0
pox==0.3.3
ppft==1.7.6.7
prometheus-client==0.17.1
prompt_toolkit==3.0.48
psutil==7.0.0
ptyprocess==0.7.0
pycairo==1.21.0
pycparser @ file:///home/conda/feedstock_root/build_artifacts/pycparser_1636257122734/work
pycurv @ git+https://github.com/kalemaria/pycurv.git@49f97a545e582ccaa0f7eb8b2a7a84192b9345e6
Pygments==2.17.2
PyGObject==3.40.1
pyinotify==0.9.6
pymeshlab==2022.2.post3
pyparsing @ file:///home/conda/feedstock_root/build_artifacts/pyparsing_1724616129934/work
PyQt5==5.12.3
PyQt5_sip==4.19.18
PyQtChart==5.12
PyQtWebEngine==5.12.1
pyrsistent==0.19.3
pytest==7.4.4
python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1709299778482/work
python-json-logger==3.0.1
pyto @ git+https://github.com/bbarad/Pyto.git@6e9236c2fdf085ff7bec9ea6113a3da26643d66e
pytz @ file:///home/conda/feedstock_root/build_artifacts/pytz_1726055524169/work
PyWavelets==1.3.0
PyYAML==6.0.1
pyzmq==26.2.1
requests==2.31.0
rfc3339-validator==0.1.4
rfc3986-validator==0.1.1
scikit-image==0.19.3
scikit-learn==1.0.2
scipy==1.7.0
Send2Trash==1.8.3
six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
sniffio==1.3.1
soupsieve==2.4.1
statsmodels==0.13.5
terminado==0.17.1
threadpoolctl==3.1.0
tifffile==2021.11.2
tinycss2==1.2.1
tomli==2.0.1
tornado @ file:///home/conda/feedstock_root/build_artifacts/tornado_1656937818679/work
traitlets==5.9.0
typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1688315532570/work
uri-template==1.3.0
urllib3==2.0.7
vtk==9.3.1
wcwidth==0.2.13
webcolors==1.13
webencodings==0.5.1
websocket-client==1.6.1
widgetsnbextension==4.0.14
y-py==0.6.2
ypy-websocket==0.8.4
zipp==3.15.0
zstandard @ file:///home/conda/feedstock_root/build_artifacts/zstandard_1655887611100/work

`

[hemanthkapa]

@Kathir-66 We currently have a minimum viable product of the surface morphometrics GUI. It is still in development, but it will run the entire surface morphometrics pipeline and can do visualization-in-place so that you can quickly determine whether you are getting good quality results. I am attaching the link here. Please feel free to make an issue at GUI if you face any issues or have any feedback. I really appreciate your involvement. Thank you 😄

[Kathir-66]

Thank you for sharing! I’ll give the GUI a try and keep you updated on my side.

I also wanted to share an update regarding the Pycurv problem.

Previously, I ran the failed tomograms on a cluster. I had installed Morphometrics a couple of months ago, and while the process completed successfully for about 30 tomograms, I encountered errors on 5 tomograms (3 IMM and 2 OMM).

Yesterday, I reran these failed tomograms on my local workstation, and this time they ran successfully.

On my workstation, Morphometrics was installed last year, around the time the major Pycurv issue was resolved and the new version was released. So I suspect this might be due to some package version differences or other dependency changes.

I’ve shared the pip freeze output of Morphometrics from my workstation in case it helps.

Thanks again for looking into this and for maintaining the pipeline!

Pip freeze

`

`
(morphometrics_l) kaezhila@kraken /sbdata/EM/projects/kaezhila/surface_morphometrics $ > pip freeze
aiofiles==22.1.0
aiosqlite==0.19.0
anyio==3.7.1
argon2-cffi==23.1.0
argon2-cffi-bindings==21.2.0
arrow==1.2.3
attrs==24.2.0
Babel==2.14.0
backcall==0.2.0
beautifulsoup4==4.12.3
bleach==6.0.0
cached-property==1.5.2
certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1725278078093/work/certifi
cffi @ file:///home/conda/feedstock_root/build_artifacts/cffi_1625835301720/work
charset-normalizer==3.4.0
click==8.1.7
cloudpickle==2.2.1
comm==0.1.4
cycler @ file:///home/conda/feedstock_root/build_artifacts/cycler_1635519461629/work
debugpy==1.7.0
decorator==5.1.1
defusedxml==0.7.1
dill==0.3.7
doit==0.34.2
entrypoints==0.4
exceptiongroup==1.2.2
fastjsonschema==2.21.0
fqdn==1.5.1
future==1.0.0
idna==3.10
imageio==2.31.2
importlib-metadata==6.7.0
importlib-resources==5.12.0
iniconfig==2.0.0
ipykernel==6.16.2
ipython==7.34.0
ipython-genutils==0.2.0
ipywidgets==8.1.5
isoduration==20.11.0
jedi==0.19.2
Jinja2==3.1.4
joblib==1.3.2
json5==0.9.16
jsonpointer==3.0.0
jsonschema==4.17.3
jupyter==1.1.1
jupyter-console==6.6.3
jupyter-events==0.6.3
jupyter-server==1.24.0
jupyter-ydoc==0.2.5
jupyter_client==7.4.9
jupyter_core==4.12.0
jupyter_server_fileid==0.9.3
jupyter_server_ydoc==0.8.0
jupyterlab==3.6.8
jupyterlab-pygments==0.2.2
jupyterlab_server==2.24.0
jupyterlab_widgets==3.0.13
kiwisolver @ file:///home/conda/feedstock_root/build_artifacts/kiwisolver_1657953088445/work
MarkupSafe==2.1.5
matplotlib @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-suite_1610582853335/work
matplotlib-inline==0.1.6
mistune==3.0.2
mrcfile==1.5.3
multiprocess==0.70.15
nbclassic==1.1.0
nbclient==0.7.4
nbconvert==7.6.0
nbformat==5.8.0
nest-asyncio==1.6.0
networkx==2.6.3
nibabel==4.0.2
notebook==6.5.7
notebook_shim==0.2.4
numpy @ file:///home/conda/feedstock_root/build_artifacts/numpy_1649806299270/work
packaging==24.0
pandas==1.3.5
pandocfilters==1.5.1
parso==0.8.4
pathos==0.3.1
patsy==1.0.1
pexpect==4.9.0
pickleshare==0.7.5
Pillow @ file:///home/conda/feedstock_root/build_artifacts/pillow_1660385854171/work
pkgutil_resolve_name==1.3.10
platformdirs==4.0.0
plotly==5.18.0
pluggy==1.2.0
pooch==1.8.2
pox==0.3.3
ppft==1.7.6.7
prometheus-client==0.17.1
prompt_toolkit==3.0.48
psutil==6.1.0
ptyprocess==0.7.0
pycairo==1.21.0
pycparser @ file:///home/conda/feedstock_root/build_artifacts/pycparser_1636257122734/work
pycurv @ git+https://github.com/kalemaria/pycurv.git@6dd72f64455b3c8abfa0a152ab54894a27043080
Pygments==2.17.2
PyGObject==3.40.1
pyinotify==0.9.6
pymeshlab==2022.2.post3
pyparsing @ file:///home/conda/feedstock_root/build_artifacts/pyparsing_1724616129934/work
PyQt5==5.12.3
PyQt5_sip==4.19.18
PyQtChart==5.12
PyQtWebEngine==5.12.1
pyrsistent==0.19.3
pytest==7.4.4
python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1709299778482/work
python-json-logger==2.0.7
pyto @ git+https://github.com/bbarad/Pyto.git@6e9236c2fdf085ff7bec9ea6113a3da26643d66e
pytz @ file:///home/conda/feedstock_root/build_artifacts/pytz_1726055524169/work
pyvista==0.38.6
PyWavelets==1.3.0
PyYAML==6.0.1
pyzmq==26.2.0
requests==2.31.0
rfc3339-validator==0.1.4
rfc3986-validator==0.1.1
scikit-image==0.19.3
scikit-learn==1.0.2
scipy==1.7.0
scooby==0.7.3
Send2Trash==1.8.3
six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
sniffio==1.3.1
soupsieve==2.4.1
statsmodels==0.13.5
tenacity==8.2.3
terminado==0.17.1
threadpoolctl==3.1.0
tifffile==2021.11.2
tinycss2==1.2.1
tomli==2.0.1
tornado @ file:///home/conda/feedstock_root/build_artifacts/tornado_1656937818679/work
traitlets==5.9.0
typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1688315532570/work
uri-template==1.3.0
urllib3==2.0.7
vtk==9.3.1
wcwidth==0.2.13
webcolors==1.13
webencodings==0.5.1
websocket-client==1.6.1
widgetsnbextension==4.0.13
y-py==0.6.2
ypy-websocket==0.8.4
zipp==3.15.0
zstandard @ file:///home/conda/feedstock_root/build_artifacts/zstandard_1655887611100/work

`

`

[eunyoungjeong2]

@hemanthkapa Hello all, I'm running into the same issue as posted here. My "Config file" is exactly the same or simpler containing only one type of membrane. The input.vtp also looks fine on ParaView. I installed Morphometrics recently like a few weeks ago. It would be great if I could find out how to get around the error.

Log:
Input file specified - will run on this file only
Processing 582_clean.membrane.surface.vtp

Calculating curvatures for 582_clean.membrane
/home/ms/eujeong/miniforge3/envs/morphometrics_mssrv003/lib/python3.7/site-packages/numpy/core/fromnumeric.py:3441: RuntimeWarning: Mean of empty slice.
out=out, **kwargs)
/home/ms/eujeong/miniforge3/envs/morphometrics_mssrv003/lib/python3.7/site-packages/numpy/core/_methods.py:189: RuntimeWarning: invalid value encountered in double_scalars
ret = ret.dtype.type(ret / rcount)
Traceback (most recent call last):
File "/home/ms/eujeong/surface_morphometrics/run_pycurv.py", line 71, in
cores=config["cores"])
File "/home/ms/eujeong/surface_morphometrics/curvature.py", line 47, in run_pycurv
basename, seg_file, folder, scale, radius_hit, methods=['VV'], min_component=min_component, runtimes=runtimes_file, cores=cores, remove_wrong_borders=remove_wrong_borders)
File "/home/ms/eujeong/surface_morphometrics/curvature_calculation.py", line 323, in new_workflow
cores=cores, runtimes=runtimes)
File "/home/ms/eujeong/miniforge3/envs/morphometrics_mssrv003/lib/python3.7/site-packages/pycurv/vector_voting.py", line 92, in normals_directions_and_curvature_estimation
runtimes=runtimes, graph_file=graph_file)
File "/home/ms/eujeong/miniforge3/envs/morphometrics_mssrv003/lib/python3.7/site-packages/pycurv/vector_voting.py", line 315, in normals_estimation
sg.graph.vp.avg_normals[v] = avg_normal / np.linalg.norm(avg_normal)
File "/home/ms/eujeong/miniforge3/envs/morphometrics_mssrv003/lib/python3.7/site-packages/graph_tool/init.py", line 847, in setitem
self._PropertyMap__map[k] = v
AttributeError: 'numpy.float64' object has no attribute 'iter'

[ajiwatson]

I got a different error, but still an error in the PyCurv step, so thought it best to put on this thread. (I then also got a similar error). I am running on the example data just to get familiar with the pipeline. Specifically, TE1_ER.surface.vtp and TE1_OMM.surface.vtp

I temporarily got around it by going in and changing the purge=True to purge=False in curvature_calculation.py

lines 288-294 curvature_calculation.py
# Filter out possibly occurring small disconnected fragments if min_component > 0: print('\nFinding small connected components of the graph...') tg.find_small_connected_components( threshold=min_component, purge=False, verbose=True) #made change in this line print('The graph has {} vertices and {} edges'.format( tg.graph.num_vertices(), tg.graph.num_edges()))

In find_small_connected_components, I'm getting an error related to this line: self.graph.vp.small_component.t(lambda x: 1-x))

File "/hpc/group/bartesaghilab/ajw111/miniconda3/envs/surface_morphometrics/lib/python3.7/site-packages/pycurv/surface_graphs.py", line 1609, in find_vertices_near_border self.graph.set_vertex_filter(self.graph.vp.is_near_border.t(lambda x: 1-x)) AttributeError: 'VertexPropertyMap' object has no attribute 't'

Changing the setting let me get past that error. Funny enough, after changing it back to True again for the OMM, I am not longer getting the error, I am uncertain if it is just still skipping that purge step in pycurv or not, I would need to investigate further.

However, for both, I still run into the error others were having:

/hpc/group/bartesaghilab/ajw111/miniconda3/envs/surface_morphometrics/lib/python3.7/site-packages/numpy/core/fromnumeric.py:3441: RuntimeWarning: Mean of empty slice. out=out, **kwargs) /hpc/group/bartesaghilab/ajw111/miniconda3/envs/surface_morphometrics/lib/python3.7/site-packages/numpy/core/_methods.py:189: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) Traceback (most recent call last): File "run_pycurv.py", line 71, in <module> cores=config["cores"]) File "/nfs/bartesaghilab/ajw111/programs/surface_morphometrics/curvature.py", line 47, in run_pycurv basename, seg_file, folder, scale, radius_hit, methods=['VV'], min_component=min_component, runtimes=runtimes_file, cores=cores, remove_wrong_borders=remove_wrong_borders) File "/nfs/bartesaghilab/ajw111/programs/surface_morphometrics/curvature_calculation.py", line 324, in new_workflow cores=cores, runtimes=runtimes) File "/hpc/group/bartesaghilab/ajw111/miniconda3/envs/surface_morphometrics/lib/python3.7/site-packages/pycurv/vector_voting.py", line 92, in normals_directions_and_curvature_estimation runtimes=runtimes, graph_file=graph_file) File "/hpc/group/bartesaghilab/ajw111/miniconda3/envs/surface_morphometrics/lib/python3.7/site-packages/pycurv/vector_voting.py", line 315, in normals_estimation sg.graph.vp.avg_normals[v] = avg_normal / np.linalg.norm(avg_normal) File "/hpc/group/bartesaghilab/ajw111/miniconda3/envs/surface_morphometrics/lib/python3.7/site-packages/graph_tool/__init__.py", line 847, in __setitem__ self._PropertyMap__map[k] = v AttributeError: 'numpy.float64' object has no attribute '__iter__'

Was the consensus solution for this second error to use an older version of pycurv? I also saw that in an older version of pycurv, the function for the find_small_connected_components is different, as a different conda environement on my machine has an older version. Should I just try an older pycurv version for both issues? If so, any guess as to which version of pycurv should work?

[bbarad]

What version/git commit is known working? @hemanthkapa can you do a test of our current install without the GUI - I am worried the changes recently pushed to pycurv may have caused unforseen issues, and will need to be rolled back?

[bbarad]

Actually, I am somewhat convinced this is an issue with Graph-Tool changing its API - Could you share the pip freeze for your working vs broken environments? We currently aren't pinning graph-tool to a specific version, which is 100% my mistake but we should rectify this ASAP. Graph-tool seems to have changed some bits of its API in surprisingly breaking ways...

[ajiwatson]

Yes of course. A heads up that the 'working' environment has things not relevant to surface morphometrics or pycurv as well because I built it to work on turning some 20 year old C++ code into python to be able to use the .vtp files rather than legacy vtk files. Also I put 'working' in quotes as though I don't get that error after about half an hour, it has yet to finish, so I'm not 100% sure it works yet. Though I'll follow up later after I get some output.

For pycurv spefically the one in the 'working' is listed in the pip freeze as:
pycurv @ git+https://github.com/kalemaria/pycurv.git@49f97a545e582ccaa0f7eb8b2a7a84192b9345e6

working_env.txt

broken_env.txt

[bbarad]

Could you do a "conda list" for each and check graph-tool version? My personal machine is on 2.58, I wonder if there are problems with 2.97 - we just made some changes to improve compatibility with new graph-tool versions so I know stuff has been breaking due to graph-tool changes, I just want to pick a version and lock it in the conda env file.

[hemanthkapa]

hi @Kathir-66 @ajiwatson @eunyoungjeong2

Just wanted to confirm, I ran Pycurv on the example dataset, and didn’t encounter any errors on my end. To help troubleshoot, could you share which operating system you’re using? Also, have you tried running the pipeline in a Docker container or a fresh conda environment?

[ajiwatson]

@bbarad They have the same graph-tool version, not sure if something was wrong with my conda set up. TemplatePYP, old environment that works, (PyCurv finished successfully) has graph-tool 2.43
surface_morphometrics, the brand new environment with that error, has graph-tool 2.43 as well

@hemanthkapa I'm running this on a linux-based HPC, specifically on an intel node (Intel nodes with Intel Xeon Gold 6154 processors (34 cores @ 3.00 GHz), 768GB of RAM and 3.2TB NVMe PCIe 3.0 SSD drives)

I have not tried Docker, but in theory this was a fresh conda environment (the surface_morphometrics one) though Ben's version 2.58 and 2.97 vs my 2.43 for graph-tool have me wondering if something went haywire with the new conda environment set up)