Incorrect behavior/testing of real_if_close's "tol" argument

The docs say

    tol : float
        Tolerance in machine epsilons for the complex part of the elements
        in the array.

but

In [8]: np.real_if_close(.5j, 1)
Out[8]: array(0.0) # Oops.

Actually, the source of the issue is rather obvious in the source code:

    if tol > 1: # <--- Uh?
        from numpy.core import getlimits
        f = getlimits.finfo(a.dtype.type)
        tol = f.eps * tol

and the tests (test_type_check.py) actually cover a weird case:

        a = np.random.rand(10)
        b = real_if_close(a+1e-15j)
        assert_all(isrealobj(b))
        assert_array_equal(a, b)
        b = real_if_close(a+1e-7j)
        assert_all(iscomplexobj(b))
        b = real_if_close(a+1e-7j, tol=1e-6) # <--- Uh?
        assert_all(isrealobj(b))

I guess the writer of the test thought it was supplying a test in absolute value...

Start with the real_if_close implementation and the existing tests in test_type_check.py, then compare the tol documentation with the reported examples. Clarify the intended tolerance semantics, update the implementation or tests accordingly, and ensure the covered cases consistently verify the documented behavior.