Make it possible for reveal_type() to format types in the same way as error messages

Feature

Add an option to reveal_type() to format the type in the same way as error messages. Something like reveal_type(variable, format="short") or similar API.

Pitch

Example (based on a bug in numpy 2.2):

import numpy as np
from numpy.typing import NDArray

def multiply(image: NDArray[np.float64], factor: float) -> NDArray[np.float64]:
    reveal_type(image * factor)
    return image * factor

results in

test.py:7: note: Revealed type is "numpy.ndarray[builtins.tuple[builtins.int, ...], numpy.dtype[numpy.floating[Any]]]"
test.py:8: error: Incompatible return value type (got "ndarray[tuple[int, ...], dtype[floating[Any]]]", expected "ndarray[tuple[int, ...], dtype[float64]]")  [return-value]

The error is a numpy bug, and not the point of this request. My point is that the type formatting in reveal_type() is different than in the error message, which makes debugging harder. Compare

numpy.ndarray[builtins.tuple[builtins.int, ...], numpy.dtype[numpy.floating[Any]]]
ndarray[tuple[int, ...], dtype[floating[Any]]]

I would like to be able to get reveal_type() to display the type in the same way. Form a quick look, it seems that the error message uses format_type_distinctly() whereas reveal_type() uses the str representation. I assume the this is done intentionally and we don't want to change this by default (if that's not the case, could we just change it?). Therefore. I propose to make this configurable through an optional parameter.

Start by tracing how reveal_type() currently uses the string representation and compare it with format_type_distinctly(), which the issue identifies as the error-message formatter. Determine the optional API behavior and verify that the new format produces error-style type output while preserving the existing default behavior.