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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def dea3(v0, v1, v2, symmetric=False):
 """ Extrapolate a slowly convergent sequence Parameters v0, v1, v2 : array-like 3 values of a convergent sequence to extrapolate Returns ------- result : array-like extrapolated value abserr : array-like absolute error estimate Notes ----- DEA3 attempts to extrapolate nonlinearly to a better estimate of the sequence's limiting value, thus improving the rate of convergence. The routine is based on the epsilon algorithm of P. Wynn, see [1]_. Examples -------- # integrate sin(x) from 0 to pi/2 True True True See also -------- dea References .. [1] C. Brezinski and M. Redivo Zaglia (1991) "Extrapolation Methods. Theory and Practice", North-Holland. .. [2] C. Brezinski (1977) "Acceleration de la convergence en analyse numerique", "Lecture Notes in Math.", vol. 584, Springer-Verlag, New York, 1977. .. [3] E. J. Weniger (1989) "Nonlinear sequence transformations for the acceleration of convergence and the summation of divergent series" Computer Physics Reports Vol. 10, 189 - 371 http://arxiv.org/abs/math/0306302v1 """

    e0, e1, e2 = np.atleast_1d(v0, v1, v2)
    with warnings.catch_warnings():
        warnings.simplefilter("ignore")  # ignore division by zero and overflow
        delta2, delta1 = e2 - e1, e1 - e0
        err2, err1 = np.abs(delta2), np.abs(delta1)
        tol2, tol1 = max_abs(e2, e1) * _EPS, max_abs(e1, e0) * _EPS
        delta1[err1 < _TINY] = _TINY
        delta2[err2 < _TINY] = _TINY  # avoid division by zero and overflow
        ss = 1.0 / delta2 - 1.0 / delta1 + _TINY
        smalle2 = abs(ss * e1) <= 1.0e-3
        converged = (err1 <= tol1) & (err2 <= tol2) | smalle2
        result = np.where(converged, e2 * 1.0, e1 + 1.0 / ss)
    abserr = err1 + err2 + np.where(converged, tol2 * 10, np.abs(result - e2))
    if symmetric and len(result) > 1:
        return result[:-1], abserr[1:]
    return result, abserr