When transforming DataTree elements, discard scales resulting in zero shape

[m-albert]

This PR implements a fix for #947.

Problem summary: spatialdata.transform transforms each of the scales of a multi-scale image and it can happen that (especially lower resolution) scales result in shape 0. One one hand it doesn't make sense to keep zero shape scales, on the other this leads to an error later on when the scale factors of the resulting image are extracted.

Fix proposed in this PR: scales resulting in zero shape are discarded, similarly to the postprocessing of bounding_box_query:

spatialdata/src/spatialdata/_core/query/_utils.py

Lines 116 to 126 in 7604a3d

	def _process_data_tree_query_result(query_result: DataTree) -> DataTree | None:
	d = {}
	for k, data_tree in query_result.items():
	v = data_tree.values()
	assert len(v) == 1
	xdata = v.__iter__().__next__()
	if 0 in xdata.shape:
	if k == "scale0":
	return None
	else:
	d[k] = xdata

In the case of 'scale0' resulting in zero shape, the PR proposes to raise an error.

Happy to work on any review points!

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 92.21%. Comparing base (2794fb0) to head (6903802).
⚠️ Report is 2 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##             main     #948   +/-   ##
=======================================
  Coverage   92.20%   92.21%           
=======================================
  Files          49       49           
  Lines        7572     7576    +4     
=======================================
+ Hits         6982     6986    +4     
  Misses        590      590           

Files with missing lines	Coverage Δ
src/spatialdata/_core/operations/transform.py	91.37% <100.00%> (+0.15%)	⬆️

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[Copilot]

Pull request overview

This PR addresses issue #947 by implementing logic to discard scales that result in zero shape when transforming multi-scale images, similar to the existing pattern in bounding_box_query. When scale0 (highest resolution) results in zero shape, an error is raised instead.

• Adds zero-shape detection and filtering logic in the DataTree transform function
• Raises a ValueError when scale0 (highest resolution) results in zero shape
• Adds a test to verify zero-shape scale handling

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 5 comments.

File	Description
src/spatialdata/_core/operations/transform.py	Adds logic to detect and skip scales with zero shape during transformation, with special error handling for scale0
tests/core/operations/test_transform.py	Adds test for zero-shape scale handling and imports Image2DModel

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[LucaMarconato]

Thanks for catching this and making a fix! I made only minor changes. Waiting until it's green and then merging.

[m-albert]

Thanks Luca!