code: def test_dense_rank_deficient(self):
      A = np.array([[-0.307, -0.184]])
      b = np.array([0.773])
      lb = [-0.1, -0.1]
      ub = [0.1, 0.1]
      for lsq_solver in self.lsq_solvers:
          res = lsq_linear(
              A, b, (lb, ub), method=self.method, lsq_solver=lsq_solver
          )
          assert_allclose(res.x, [-0.1, -0.1])
          assert_allclose(
              res.unbounded_sol[0], lstsq(A, b, rcond=-1)[0]
          )
  
      A = np.array(
          [
              [0.334, 0.668],
              [-0.516, -1.032],
              [0.192, 0.384],
          ]
      )
      b = np.array([-1.436, 0.135, 0.909])
      lb = [0, -1]
      ub = [1, -0.5]
      for lsq_solver in self.lsq_solvers:
          res = lsq_linear(
              A, b, (lb, ub), method=self.method, lsq_solver=lsq_solver
          )
          assert_allclose(res.optimality, 0, atol=1e-11)
          assert_allclose(
              res.unbounded_sol[0], lstsq(A, b, rcond=-1)[0]
          )
  
imports: import pytest
  import numpy
  from numpy.linalg import lstsq
  from numpy.testing import assert_allclose, assert_equal, assert_
  from scipy.sparse import rand, coo_matrix
  from scipy.sparse.linalg import aslinearoperator
  from scipy.optimize import lsq_linear
  from scipy.optimize._minimize import Bounds
label_desc: Use image node_id 6 for calling the BaseMixin obj's underlying member method code with example usage: obj.test_dense_rank_deficient() without return types