[BUG] reject non-positive sigma/scale in Normal and Laplace #959

[shubhumre777]

Reference Issues/PRs

Fixes #959

What does this implement/fix? Explain your changes.

This PR adds input parameter validation to the constructors (__init__) of both the Normal and Laplace distributions to enforce strictly positive scale parameters (sigma for Normal and scale for Laplace).

Previously, passing non-positive values allowed mathematically invalid negative values to propagate to the _pdf calculation. The input validation uses a robust vectorized numpy check np.any(np.asarray(...) <= 0) to seamlessly handle both scalar values and multi-dimensional array structures without crashing.

Does your contribution introduce a new dependency? If yes, which one?

No.

What should a reviewer concentrate their feedback on?

The vector/array validation logic implementation using np.any(np.asarray(...) <= 0) inside the constructors.

Did you add any tests for the change?

Yes, added a new automated unit test file:
skpro/distributions/tests/test_parameter_validation.py which verifies that both distributions throw a descriptive ValueError on negative and zero boundary values.

Any other comments?

This is my first contribution to skpro , Excited to hear feedback.

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