Enable reading scalar attributes stored as shape-(1,) arrays. - #81
Merged
Merged
Conversation
This was probably never intended as PyASDF's own writer would use a scalar attribute in the first place. However, external writers might use H5LTset_attribute_*(..., size=1) which creates a size-1 array instead of an H5S_SCALAR. This still works fine with numpy <2.4.0, but from 2.4.0 onwards, it raises a type error rather than silently squeezing to a float: TypeError: only 0-dimensional arrays can be converted to Python scalars.
Member
|
Thank you! |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This was probably never intended as PyASDF's own writer would use a scalar attribute in the first place. However, external writers might use
H5LTset_attribute_*(..., size=1)which creates a size-1 array instead of anH5S_SCALAR.This PR converts attributes stored as size-1 arrays to scalar attributes. Without squeezing the arrays to scalars, numpy >=2.4.0 raises a type error like this: