Add experimental AST-based optimizer and optimize_ast entrypoint; parametrize tests

[Erotemic]

Motivation

• Introduce an experimental AST-based optimizer that can be evaluated alongside the existing legacy optimizer without changing public behavior.
• Provide a separate entrypoint so both optimizers can coexist for comparison and iterative rule development.

Description

• Added a new experimental submodule delayed_image.experimental.astopt with driver, rule registry, traversal helpers, and canonical-signature helpers (optimizer.py, rules.py, transformer.py, signature.py, plus package __init__.py).
• Exposed new entrypoints: delayed_image.experimental.astopt.optimize() and optimize_trace(), and added DelayedOperation.optimize_ast() (and .pyi stub) which forwards to the experimental optimizer; the existing optimize() behavior is unchanged.
• Tests: added tests/conftest.py with fixtures to parametrize between the legacy and AST optimizer, added equivalence/idempotence tests in tests/test_ast_optimize_equivalence.py, and updated several existing tests to run against both optimizer callables.
• Documentation: added an Unreleased changelog entry describing the experimental optimizer and how to invoke it (CHANGELOG.md).

Testing

• Ran the full test suite via the project test driver (python run_tests.py, which runs pytest plus xdoctest); the run collected 184 items and produced a mixed result: 113 passed, 19 failed, 52 skipped, and 2 warnings.
• The new AST equivalence/idempotence tests (tests/test_ast_optimize_equivalence.py) passed in the test runs that exercised them, and the paramaterized tests exercised both optimize() and optimize_ast() paths.
• Remaining failures are mostly environment/backend related (examples: NotImplementedError from kwimage.warp_affine because the skimage backend is not available in this environment, and xdoctest failures caused by blocked external demo image downloads); these are pre-existing environment-sensitive failures rather than regressions in the new optimizer integration.

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Codex Task