[ENH] Improve type annotations with short_array_type and field defaults #14
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Added `repr=False` to `temp_interpolation_values` to prevent it from being displayed in object representations. This improves clarity and ensures sensitive or non-essential details are not exposed.
Introduced `numpy_array_short_validator` to ensure proper validation for `centers`, `resolution`, and `radius` attributes in the `CenteredGrid` class. This enhances data integrity and enforces stricter input checks.
Replaced raw tensor attributes with `Annotated` numpy arrays for better type validation and integrated a short numpy array validator. This improves code clarity and enforces input validation.
Replaced verbose `Annotated` type definitions with `short_array_type` for cleaner and more consistent code. Improved clarity and added error handling for deserialized implicit functions in `FiniteFaultData`.
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Improved Type Annotations and Serialization Support
[CLN] Hide temp_interpolation_values from repr output
Added
repr=Falsetotemp_interpolation_valuesto prevent it from being displayed in object representations, improving clarity when debugging or logging.[ENH] Introduce short_array_type for consistent type annotations
Created a reusable
short_array_typeusingAnnotated[np.ndarray, numpy_array_short_validator]to standardize array validation across the codebase.[ENH] Improve CenteredGrid field definitions
field(init=False)for cleaner dataclass definitionshort_array_typeand modern Python syntax[ENH] Enhance FiniteFaultData serialization support
short_array_typefor consistent validation[ENH] Update GeophysicsInput with proper type annotations
Replaced BackendTensor references with properly annotated numpy arrays using the validation system, improving type safety and serialization support.