Hacktoberfest 2026: the issues maintainers tagged for October, open and beginner-friendly. Browse Hacktoberfest issues

GeneInterpolate not accepting border_predictions

Open
  • Is something wrong?
#71 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
3/5
Estimated time
1-2 days
Newbie friendliness
35/100
Issue type
Bug
Clarity
Mostly clear
Activity status
Stale
Tech stack
python
Domain
backend

Research direction

Start with pipeline/full_pipeline.py around lines 240-253 and pipeline/interpolate_gene.py at line 186, then inspect which atlas-interpolator version is available inside the Singularity environment. Confirm the dependency and constructor mismatch, and consider the issue done when full_pipeline.py runs without the unexpected border_predictions argument error.

Written by the indexing model from the issue text.

Description

I am getting this traceback when running full_pipeline.py

Traceback (most recent call last):
  File "/gpfs/bbp.cscs.ch/project/proj148/atlas/Deep-Atlas/pipeline/full_pipeline.py", line 253, in <module>
    sys.exit(main(**kwargs))
  File "/gpfs/bbp.cscs.ch/project/proj148/atlas/Deep-Atlas/pipeline/full_pipeline.py", line 240, in main
    output_dir=interpolation_results_dir,
  File "/gpfs/bbp.cscs.ch/project/proj148/atlas/Deep-Atlas/pipeline/interpolate_gene.py", line 186, in main
    gene_dataset, interpolator_model, border_predictions=False
TypeError: __init__() got an unexpected keyword argument 'border_predictions'

I have the latest version of atlas-interpolator installed, but I guess it's using a version it installed inside the singularity environment? (I have no Idea how this works). If so, then the issue must be that that is out of date.

Dominant language
Python
Stars
4
Forks
2
No merged PRs in 30d

Getting set up

This project ships no dev container, Dockerfile or contributing guide, so setting up is up to you: start from its README, and see our first-contribution guide for the general steps.

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from BlueBrain/Deep-Atlas

All issues in BlueBrain/Deep-Atlas

Similar issues

More Python issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.