Refactor ifp_egm: use JAX throughout and improve code organization

- Convert Gini coefficient and top share calculations from NumPy to JAX
- Embed utility functions (u_prime, u_prime_inv) and income function (y)
  inside K_numpy and K operators to simplify function signatures
- Introduce z_prime variable for better readability in nested loops
- Fix y_bar(k) to correctly implement mathematical definition of expected
  labor income conditional on current state
- Use vmap for vectorization in y_bar computation
- Remove redundant y_mean vector in favor of direct y_bar(k) calls

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Co-Authored-By: Claude <noreply@anthropic.com>

Author: jstac