code: def test_steps():
      # test for gauss_initialize_position
      distribution = ElectronSampler(
          np.array([[1, 1, 3], [3, 2, 3]]), f, batch_no=2, steps=1000
      )
      distribution.gauss_initialize_position(np.array([[1], [2]]))
      assert (
          (
              distribution.x
              - np.array(
                  [
                      [[[1, 1, 3]], [[3, 2, 3]], [[3, 2, 3]]],
                      [[[1, 1, 3]], [[3, 2, 3]], [[3, 2, 3]]],
                  ]
              )
          )
          != 0
      ).any()
  
      # testing symmetric simultaneous_move
      x1 = distribution.x
      distribution.move()
      assert ((distribution.x - x1) != 0).all()
  
      # testing asymmetric simultaneous_move
      distribution = ElectronSampler(
          np.array([[1, 1, 3], [3, 2, 3]]),
          f,
          batch_no=2,
          steps=1000,
          symmetric=False,
      )
      distribution.gauss_initialize_position(np.array([[1], [2]]))
      x1 = distribution.x
      distribution.move(asymmetric_func=distribution.harmonic_mean)
      assert ((distribution.x - x1) != 0).all()
      assert np.shape(distribution.sampled_electrons) == (2000, 3, 1, 3)
  
      # testing symmetric single_move
      distribution = ElectronSampler(
          np.array([[1, 1, 3], [3, 2, 3]]),
          f,
          batch_no=2,
          steps=1000,
          simultaneous=False,
      )
      distribution.gauss_initialize_position(np.array([[1], [2]]))
      x1 = distribution.x
      distribution.move(index=1)
      assert ((distribution.x[:, 1, :, :] - x1[:, 1, :, :]) != 0).all()
      assert ((distribution.x[:, 2, :, :] - x1[:, 2, :, :]) == 0).all()
      assert np.shape(distribution.sampled_electrons) == (2000, 3, 1, 3)
  
      # testing asymmetric single_move
      distribution = ElectronSampler(
          np.array([[1, 1, 3], [3, 2, 3]]),
          f,
          batch_no=2,
          steps=1000,
          simultaneous=False,
          symmetric=False,
      )
      distribution.gauss_initialize_position(np.array([[1], [2]]))
      x1 = distribution.x
      distribution.move(
          asymmetric_func=distribution.harmonic_mean, index=1
      )
      assert ((distribution.x[:, 1, :, :] - x1[:, 1, :, :]) != 0).all()
      assert ((distribution.x[:, 2, :, :] - x1[:, 2, :, :]) == 0).all()
      assert np.shape(distribution.sampled_electrons) == (2000, 3, 1, 3)
  
imports: import numpy
  from deepchem.utils.electron_sampler import ElectronSampler
label_desc: Use image node_id 4 for calling a global function with example usage: test_steps() without return types