Fix NormalizeIntensity inverse for non-contiguous inputs

[mottopanikeiku]

Fixes #9182.

Description

The text below was written with AI assistance (Claude and GPT-6 Astra).

NormalizeIntensity(nonzero=True).inverse() builds a boolean mask that keeps the input's layout and then calls view(-1) on it, which raises for a transposed image even though the forward pass works. NormalizeIntensityd goes through the same code. I make that temporary mask contiguous before updating it through its flattened indices; the image itself is left as it is.

With the reproducer from #9182:

Case	Before	After
Array and dictionary, global	RuntimeError: view size is not compatible with input tensor's size and stride ...	round_trip= True
Array and dictionary, channel-wise	same RuntimeError	round_trip= True

The new tests in test_normalize_intensity.py and test_normalize_intensityd.py round-trip a transposed input in global and channel-wise mode, including zero voxels and non-zero values that normalize to zero. All four fail before the change. With it, test_normalize_intensity.py, test_normalize_intensityd.py, inverse/test_invertd.py, test_inverse_collation.py and compose/test_compose.py pass (228 tests). Black, isort and Ruff pass on the changed files.

Types of changes

• Non-breaking change (fix or new feature that would not break existing functionality).
• New tests added to cover the changes.

I used AI assistance (Claude and GPT-6 Astra) to find, fix and test this bug.

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📥 Commits

Reviewing files that changed from the base of the PR and between 4cb5df9 and 2e4d272.

📒 Files selected for processing: 2

• tests/transforms/test_normalize_intensity.py
• tests/transforms/test_normalize_intensityd.py

🚧 Files skipped from review as they are similar to previous changes: 2

• tests/transforms/test_normalize_intensity.py
• tests/transforms/test_normalize_intensityd.py

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📝 Walkthrough

NormalizeIntensity.inverse now makes the nonzero restoration mask contiguous before applying recorded flat indices. Regression tests cover array and dictionary transforms on transposed, non-contiguous inputs in global and channel-wise modes. They check restored values and cleared applied-operation history.

Priority: ➖ Normal

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

Severity of issue fixed: Medium

Merge Risk: ⚪ Minimal · up to 2e4d2

This change fixes inverse normalization for transposed, non-contiguous inputs and adds regression tests. No merge-blocking risk is identified.

Pre-merge checks: 4 · 1

Failed checks: 1 warning

Check name	Status	Explanation	Resolution
Docstring Coverage		Docstring coverage is 50.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 8 functions across 3 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

Passed checks: 4 passed

Check name	Status	Explanation
Title check		The title clearly and concisely describes the main fix for non-contiguous inputs.
Description check		The description explains the bug, implementation, affected APIs, tests, validation results, issue reference, and change type. It omits several unchecked template items, but the required information is…
Linked Issues check		Issue #9182 requires inverse normalization to restore transposed, non-contiguous inputs with nonzero=True in global and channel-wise modes. The PR makes the temporary restoration mask contiguous. Th…
Out of Scope Changes check		The reported changes contain one restoration-mask fix and focused regression tests for the affected transforms. These changes directly support issue #9182. No unrelated change is shown.

Full details: Description check

Explanation

The description explains the bug, implementation, affected APIs, tests, validation results, issue reference, and change type. It omits several unchecked template items, but the required information is mostly complete.

Full details: Linked Issues check

Explanation

Issue #9182 requires inverse normalization to restore transposed, non-contiguous inputs with nonzero=True in global and channel-wise modes. The PR makes the temporary restoration mask contiguous. The added tests cover NormalizeIntensity and NormalizeIntensityd and verify round trips for both modes.

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Actionable comments posted: 2

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• 🪄 Fix comments: Fix CodeRabbit comments on this PR

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Inline comments:
Review comments at @tests/transforms/test_normalize_intensity.py:
- Around line 180-181: Update the test_inverse_nonzero_noncontiguous docstring
to add an Args section documenting channel_wise as controlling whether each
channel is normalized independently; do not add a Returns section.

Review comments at @tests/transforms/test_normalize_intensityd.py:
- Around line 102-103: Update the docstring of
test_inverse_nonzero_noncontiguous to document the channel_wise argument in an
Args section; do not add a Returns section.

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📥 Commits

Reviewing files that changed from the base of the PR and between 6aa4abf and 4cb5df9.

📒 Files selected for processing: 3

• monai/transforms/intensity/array.py
• tests/transforms/test_normalize_intensity.py
• tests/transforms/test_normalize_intensityd.py

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