code: def test_LinearVectorFunction_memoization():
      A = np.array([[-1, 2, 0], [0, 4, 2]])
      x0 = np.array([1, 2, -1])
      fun = LinearVectorFunction(A, x0, False)
  
      assert_array_equal(x0, fun.x)
      assert_array_equal(A.dot(x0), fun.f)
  
      x1 = np.array([-1, 3, 10])
      assert_array_equal(A, fun.jac(x1))
      assert_array_equal(x1, fun.x)
      assert_array_equal(A.dot(x0), fun.f)
      assert_array_equal(A.dot(x1), fun.fun(x1))
      assert_array_equal(A.dot(x1), fun.f)
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from numpy.testing import TestCase, assert_array_almost_equal, assert_array_equal, assert_
  from scipy.sparse import csr_matrix
  from scipy.sparse.linalg import LinearOperator
  from scipy.optimize._differentiable_functions import ScalarFunction, VectorFunction, LinearVectorFunction, IdentityVectorFunction
label_desc: Use image node_id 2 for calling a global function with example usage: test_LinearVectorFunction_memoization() without return types