Skip to content

Do not fail with zero-sized arrays in dataset_to_point_list #7856

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jul 17, 2025

Conversation

ricardoV94
Copy link
Member

@ricardoV94 ricardoV94 commented Jul 17, 2025

Numpy does not support reshape(-1, ...) when size is zero


📚 Documentation preview 📚: https://pymc--7856.org.readthedocs.build/en/7856/

@ricardoV94 ricardoV94 added bug trace-backend Traces and ArviZ stuff labels Jul 17, 2025
@ricardoV94 ricardoV94 changed the title Do not fail with zero-sized arrays in dataset_to_point_list Do not fail with zero-sized arrays in dataset_to_point_list Jul 17, 2025
Numpy does not support reshape(-1, ...) when size is zero
@ricardoV94 ricardoV94 requested a review from OriolAbril July 17, 2025 14:37
Copy link

codecov bot commented Jul 17, 2025

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 92.98%. Comparing base (8a436d8) to head (5ecc420).
Report is 1 commits behind head on main.

Additional details and impacted files

Impacted file tree graph

@@            Coverage Diff             @@
##             main    #7856      +/-   ##
==========================================
+ Coverage   89.25%   92.98%   +3.73%     
==========================================
  Files         108      108              
  Lines       18327    18328       +1     
==========================================
+ Hits        16358    17043     +685     
+ Misses       1969     1285     -684     
Files with missing lines Coverage Δ
pymc/backends/arviz.py 95.79% <100.00%> (+0.01%) ⬆️

... and 21 files with indirect coverage changes

🚀 New features to boost your workflow:
  • ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

num_sample_dims = len(sample_dims)
stacked_dims = {dim_name: ds[var_names[0]][dim_name] for dim_name in sample_dims}
transposed_dict = {vn: da.transpose(*sample_dims, ...) for vn, da in ds.items()}
stacked_size = np.prod(transposed_dict[var_names[0]].shape[:num_sample_dims], dtype=int)
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

should be the same as

stacked_size = np.prod([ds.sizes[dim] for dim in sample_dims], dtype=int)

feel free to choose whichever you prefer

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

ds may be a dict

@ricardoV94 ricardoV94 merged commit f34eb26 into pymc-devs:main Jul 17, 2025
40 of 42 checks passed
@ricardoV94 ricardoV94 deleted the zero_size_dataset branch July 17, 2025 15:07
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
bug trace-backend Traces and ArviZ stuff
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants