code: def _poor_convergence(z, r, f, bn, mvec):
      
      check_points = (-0.4 + 0.3j, 0.7 + 0.2j, 0.02 - 0.06j)
      diffs = []
      ftests = []
      for check_point in check_points:
          rtest = r * check_point
          ztest = z + rtest
          ftest = f(ztest)
          # Evaluate powerseries:
          comp = np.sum(bn * np.power(check_point, mvec))
          ftests.append(ftest)
          diffs.append(comp - ftest)
  
      max_abs_error = np.max(np.abs(diffs))
      max_f_value = np.max(np.abs(ftests))
      return max_abs_error > 1e-3 * max_f_value
docs: Test for poor convergence based on three function evaluations.
  
      This test evaluates the function at the three points and returns false if
      the relative error is greater than 1e-3.