code: def test_onenormest_table_5_t_1(self):
      # "note that there is no randomness and hence only one estimate for t=1"
      t = 1
      n = 100
      itmax = 5
      alpha = 1 - 1e-6
      A = -scipy.linalg.inv(np.identity(n) + alpha * np.eye(n, k=1))
      first_col = np.array([1] + [0] * (n - 1))
      first_row = np.array([(-alpha) ** i for i in range(n)])
      B = -scipy.linalg.toeplitz(first_col, first_row)
      assert_allclose(A, B)
      est, v, w, nmults, nresamples = _onenormest_core(B, B.T, t, itmax)
      exact_value = scipy.linalg.norm(B, 1)
      underest_ratio = est / exact_value
      assert_allclose(underest_ratio, 0.05, rtol=1e-4)
      assert_equal(nmults, 11)
      assert_equal(nresamples, 0)
      # check the non-underscored version of onenormest
      est_plain = scipy.sparse.linalg.onenormest(B, t=t, itmax=itmax)
      assert_allclose(est, est_plain)
  
imports: import numpy
  from numpy.testing import assert_allclose, assert_equal, assert_
  import pytest
  import scipy.linalg
  import scipy.sparse.linalg
  from scipy.sparse.linalg._onenormest import _onenormest_core, _algorithm_2_2
label_desc: Use image node_id 3 for calling the TestOnenormest obj's underlying member method code with example usage: obj.test_onenormest_table_5_t_1() without return types