def METHOD_NAME(self):
    # Tests that ill conditioned covariance matrices are detected.
    from scipy.integrate import odeint
    #TODO: A quicker test-case for this would be great!
    def OnePopControlODE(y, t, p):
        a, b, c = p
        dydt = np.zeros(y.shape)
        k = (a - b) / c * (y[0] + y[1])
        dydt[0] = a * y[0] - b * y[0] - k * y[0]
        dydt[1] = k * y[0] - b * y[1]
        return dydt
    class Model(pints.ForwardModel):
        def simulate(self, parameters, times):
            y0 = [2000000, 0]
            solution = odeint(
                OnePopControlODE, y0, times, args=(parameters,))
            return np.sum(np.array(solution), axis=1)
        def n_parameters(self):
            return 3
    model = Model()
    times = [0, 0.5, 2, 4, 8, 24]
    values = [2e6, 3.9e6, 3.1e7, 3.7e8, 1.6e9, 1.6e9]
    problem = pints.SingleOutputProblem(model, times, values)
    score = pints.SumOfSquaresError(problem)
    x = [3.42, -0.21, 5e6]
    opt = pints.OptimisationController(score, x, method=method)
    with StreamCapture() as c:
        opt.run()
    self.assertTrue('Ill-conditioned covariance matrix' in c.text())