Update elastic

[ternaus]

Fixes: #2046

Summary by Sourcery

Add support for configurable noise distribution in the ElasticTransform class, allowing users to select between Gaussian and uniform distributions for displacement fields. Refactor related functions for improved clarity and update the pre-commit configuration to the latest Ruff version.

New Features:

• Introduce a new parameter 'noise_distribution' to the ElasticTransform class, allowing users to choose between 'gaussian' and 'uniform' noise distributions for generating displacement fields.

Enhancements:

• Refactor the generate_displacement_fields function to support different noise distributions and improve code readability.

Build:

• Update the pre-commit configuration to use Ruff version v0.7.2.

[sourcery-ai]

Reviewer's Guide by Sourcery

This PR enhances the elastic transform functionality by adding support for different noise distributions (Gaussian and uniform) in displacement field generation. The implementation refactors the displacement field generation code into a separate function and adds a new parameter to control the noise distribution type.

Updated class diagram for ElasticTransform

classDiagram
    class ElasticTransform {
        +float alpha
        +float sigma
        +bool approximate
        +bool same_dxdy
        +Literal["gaussian", "uniform"] noise_distribution
        +int mask_interpolation
        +float p
        +get_params_dependent_on_data(params: dict[str, Any], data: dict[str, Any]) dict[str, Any]
        +get_transform_init_args_names() tuple[str, ...]
    }
    note for ElasticTransform "Added noise_distribution attribute and updated methods to use it."

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Updated class diagram for generate_displacement_fields function

classDiagram
    class generate_displacement_fields {
        +np.ndarray image_shape
        +float alpha
        +float sigma
        +bool same_dxdy
        +tuple[int, int] kernel_size
        +np.random.Generator random_generator
        +Literal["gaussian", "uniform"] noise_distribution
        +generate_noise_field() np.ndarray
    }
    note for generate_displacement_fields "Refactored to include noise_distribution and generate_noise_field function."

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File-Level Changes

Change	Details	Files
Added support for different noise distributions in elastic transform	Added new 'noise_distribution' parameter to control the type of noise (gaussian or uniform) Refactored displacement field generation into a separate helper function Added documentation for the new noise_distribution parameter Updated function signatures and initialization arguments to include the new parameter	albumentations/augmentations/geometric/functional.py albumentations/augmentations/geometric/transforms.py
Updated development tooling	Bumped ruff-pre-commit from v0.7.1 to v0.7.2	.pre-commit-config.yaml

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[sourcery-ai]

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

Overall Comments:

• Consider expanding the PR description to explain the motivation for adding the new noise distribution option and its expected benefits. This helps reviewers and future maintainers understand the context better.

Here's what I looked at during the review

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

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[codecov]

Codecov Report

Attention: Patch coverage is 76.92308% with 3 lines in your changes missing coverage. Please review.

Project coverage is 90.31%. Comparing base (b1a79c2) to head (55c7668).
Report is 246 commits behind head on main.

Files with missing lines	Patch %	Lines
...bumentations/augmentations/geometric/functional.py	70.00%	3 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff            @@
##           main    #2047       +/-   ##
=========================================
+ Coverage      0   90.31%   +90.31%     
=========================================
  Files         0       46       +46     
  Lines         0     7597     +7597     
=========================================
+ Hits          0     6861     +6861     
- Misses        0      736      +736     

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