def idd_estrank(eps, A):
A = np.asfortranarray(A)<EOL>m, n = A.shape<EOL>n2, w = idd_frmi(m)<EOL>ra = np.empty(n*n2 + (n + <NUM_LIT:1>)*(n2 + <NUM_LIT:1>), order='<STR_LIT:F>')<EOL>k, ra = _id.idd_estrank(eps, A, w, ra)<EOL>return k<EOL>
Estimate rank of a real matrix to a specified relative precision using
random sampling.

The output rank is typically about 8 higher than the actual rank.

:param eps:
    Relative precision.
:type eps: float
:param A:
    Matrix.
:type A: :class:`numpy.ndarray`

:return:
    Rank estimate.
:rtype: int