Fix params

[ternaus]

Summary by Sourcery

Refactor the codebase to improve readability and maintainability by reordering transformations, breaking down long lines, and updating import statements. Fix validation logic for normalization parameters. Enhance test coverage by adding new test cases for auto_contrast and updating existing tests. Update pre-commit configuration to use the latest tool versions.

Bug Fixes:

• Fix the validation logic for normalization parameters to ensure correct error handling when parameters are missing.

Enhancements:

• Reorder and update the list of transformations in the transforms module to include new transformations and remove deprecated ones.
• Refactor the code to improve readability by breaking down long lines and adding line breaks for better formatting.

Tests:

• Add new test cases to verify the functionality of the auto_contrast function, ensuring it handles various image types correctly.
• Update existing tests to improve coverage and ensure compatibility with the refactored code.

Chores:

• Update the pre-commit configuration to use the latest versions of tools like Ruff and markdownlint.
• Reorganize import statements across multiple modules to follow a consistent order.

[sourcery-ai]

Reviewer's Guide by Sourcery

The changes focus on improving code organization and readability through parameter validation refinement, function signature formatting, and alphabetical sorting of imports and exports. The main implementation changes include fixing parameter validation logic in transforms, updating pre-commit hooks, and reorganizing transformation lists.

Class diagram for updated parameter validation

classDiagram
    class ImageCompression {
        +tuple[int, int] quality_range
        +validate_ranges() Self
        +apply(np.ndarray img, int quality, Literal[".jpg", ".webp"] image_type, **params: Any) np.ndarray
    }
    class RandomSnow {
        +tuple[float, float] snow_point_range
        +validate_ranges() Self
        +apply(np.ndarray img, float snow_point, float brightness_coeff, np.ndarray snow_texture, np.ndarray sparkle_mask) np.ndarray
    }
    class Posterize {
        +int | tuple[int, int] | list[tuple[int, int]] num_bits
        +validate_num_bits(Any num_bits) tuple[int, int] | list[tuple[int, int]]
        +apply(np.ndarray img, int num_bits, **params: Any) np.ndarray
    }

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Class diagram for updated noise parameters

classDiagram
    class AdditiveNoise {
        +Literal["uniform", "gaussian", "laplace", "beta"] noise_type
        +Literal["constant", "per_pixel", "shared"] spatial_mode
        +dict[str, Any] | None noise_params
        +apply(np.ndarray img, np.ndarray noise_map, **params: Any) np.ndarray
    }
    class UniformParams {
        +list[Sequence[float]] ranges
        +validate_ranges(list[Sequence[float]] v) list[tuple[float, float]]
    }
    class GaussianParams {
        +Sequence[float] mean_range
        +Sequence[float] std_range
    }
    class LaplaceParams {
        +Sequence[float] mean_range
        +Sequence[float] scale_range
    }
    class BetaParams {
        +Sequence[float] alpha_range
        +Sequence[float] beta_range
        +Sequence[float] scale_range
    }

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File-Level Changes

Change	Details	Files
Refactor function signatures for better readability	Split long function signatures into multiple lines Add consistent indentation for multi-line parameters Improve parameter alignment in complex function definitions	albumentations/augmentations/transforms.py albumentations/augmentations/functional.py
Fix parameter validation logic	Fix condition in normalization validation to properly check max_pixel_value Improve error messages for parameter validation Update validation logic for snow_point_range and fog_coef_range Fix validation for quality_range in ImageCompression	albumentations/augmentations/transforms.py
Reorganize transformation lists and imports	Sort transformation lists alphabetically for better organization Reorder import statements alphabetically Update all lists to be alphabetically sorted	albumentations/augmentations/transforms.py albumentations/augmentations/functional.py albumentations/augmentations/geometric/transforms.py albumentations/core/composition.py
Update build configuration and dependencies	Update ruff pre-commit hook to v0.8.1 Update markdownlint-cli to v0.43.0 Modify ruff linting rules in pyproject.toml	.pre-commit-config.yaml pyproject.toml

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[sourcery-ai]

Hey @ternaus - I've reviewed your changes - here's some feedback:

Overall Comments:

• This PR contains breaking changes: 1) Removed Poisson noise option from noise transforms 2) Modified Posterize transform to no longer accept 0 bits. Please document these changes in the changelog.

Here's what I looked at during the review

• 🟡 General issues: 1 issue found
• 🟢 Security: all looks good
• 🟡 Testing: 2 issues found
• 🟢 Complexity: all looks good
• 🟢 Documentation: all looks good

---

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[codecov]

Codecov Report

Attention: Patch coverage is 85.47718% with 35 lines in your changes missing coverage. Please review.

Project coverage is 89.80%. Comparing base (b1a79c2) to head (9291e0d).
Report is 298 commits behind head on main.

Files with missing lines	Patch %	Lines
albumentations/augmentations/transforms.py	86.25%	22 Missing ⚠️
albumentations/augmentations/functional.py	82.66%	13 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff            @@
##           main    #2173       +/-   ##
=========================================
+ Coverage      0   89.80%   +89.80%     
=========================================
  Files         0       47       +47     
  Lines         0     8478     +8478     
=========================================
+ Hits          0     7614     +7614     
- Misses        0      864      +864     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

[sourcery-ai]

Hey @ternaus - I've reviewed your changes and they look great!

Here's what I looked at during the review

• 🟡 General issues: 1 issue found
• 🟢 Security: all looks good
• 🟡 Testing: 3 issues found
• 🟢 Complexity: all looks good
• 🟢 Documentation: all looks good

---

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_{Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.}