Fix ClipIntensityPercentiles metadata accumulation

[engmohamedsalah]

Description

ClipIntensityPercentiles stored returned clipping values on the transform instance. Reusing the same transform therefore accumulated values from earlier calls and also mutated the metadata of earlier outputs.

This change keeps the clipping-value accumulator local to each __call__. Each result now receives only its own clipping values, and later calls cannot change metadata already returned to a caller.

Regression tests cover repeated channel-wise and non-channel-wise calls.

Types of changes

• Non-breaking change (fix or new feature that would not break existing functionality).
• Breaking change (fix or new feature that would cause existing functionality to change).
• New tests added to cover the changes.
• Integration tests passed locally by running ./runtests.sh -f -u --net --coverage.
• Quick tests passed locally by running ./runtests.sh --quick --unittests --disttests.
• In-line docstrings updated.
• Documentation updated, tested make html command in the docs/ folder.

Testing

• python -m unittest tests.transforms.test_clip_intensity_percentiles tests.transforms.test_clip_intensity_percentilesd — 96 tests passed
• python -m ruff check monai/transforms/intensity/array.py tests/transforms/test_clip_intensity_percentiles.py
• python -m black --check monai/transforms/intensity/array.py tests/transforms/test_clip_intensity_percentiles.py

[coderabbitai]

📝 Walkthrough

Walkthrough

ClipIntensityPercentiles now collects clipping percentile pairs in a local list for each invocation, passes that list through both clipping paths, and stores it in image metadata when enabled. New tests cover repeated channel-wise and non-channel-wise calls to ensure metadata does not leak between invocations.

Estimated code review effort: 2 (Simple) | ~10 minutes

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title is concise and accurately names the main fix to ClipIntensityPercentiles metadata handling.
Description check	✅ Passed	The description covers the change, impact, change type, and testing, matching the template well.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

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[coderabbitai]

Actionable comments posted: 1

🤖 Prompt for all review comments with AI agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@monai/transforms/intensity/array.py`:
- Around line 1177-1178: Update the clipping_values assignment in the transform
logic to verify that img has a meta attribute before accessing it, while
preserving the existing clipping_values non-None condition and metadata
assignment when available.

🪄 Autofix (Beta)

Fix all unresolved CodeRabbit comments on this PR:

• Push a commit to this branch (recommended)
• Create a new PR with the fixes

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ℹ️ Review info

⚙️ Run configuration

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Pro

Run ID: 172b6c36-87cd-48a5-82ae-6a2627769c24

📥 Commits

Reviewing files that changed from the base of the PR and between 5da2472 and 7904d66.

📒 Files selected for processing (2)

• monai/transforms/intensity/array.py
• tests/transforms/test_clip_intensity_percentiles.py

[coderabbitai]

🩺 Stability & Availability | 🟡 Minor | ⚡ Quick win

Guard against missing meta attribute.

If metadata tracking is disabled globally (get_track_meta() == False), img will not be a MetaTensor and accessing img.meta raises an AttributeError. Check for existence before assignment.

🛡️ Proposed fix

-        if clipping_values is not None:
+        if clipping_values is not None and hasattr(img, "meta"):
             img.meta["clipping_values"] = clipping_values  # type: ignore

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change

	if clipping_values is not None:
	img.meta["clipping_values"] = clipping_values # type: ignore
	if clipping_values is not None and hasattr(img, "meta"):
	img.meta["clipping_values"] = clipping_values # type: ignore

🤖 Prompt for AI Agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@monai/transforms/intensity/array.py` around lines 1177 - 1178, Update the
clipping_values assignment in the transform logic to verify that img has a meta
attribute before accessing it, while preserving the existing clipping_values
non-None condition and metadata assignment when available.