code: def test_getitem_idx():
      # Create a GradientTable object with some test b-values and b-vectors
      bvals = np.array([0.0, 100.0, 200.0, 300.0, 400.0])
      # value should be in increasing order as b-value affects the diffusion
      # weighting of the image, and the amount of diffusion weighting increases
      # with increasing b-value.
      bvecs = np.array(
          [[0, 0, 1], [1, 0, 0], [0, 1, 0], [0, 0, 1], [1, 0, 0]]
      )
      # the b-vectors should be unit-length vectors
      gradients = bvals[:, None] * bvecs
  
      # Test a too large b0 threshold value
      b0_threshold = 100
      gtab = GradientTable(gradients, b0_threshold=b0_threshold)
  
      idx = 1
      with pytest.raises(ValueError) as excinfo:
          _ = gtab[idx]
          assert str(
              excinfo.value
          ) == b0_threshold_empty_gradient_message(
              bvals, [idx], b0_threshold
          )
  
      gtab = GradientTable(gradients)
  
      # Test with a single index
      gtab_slice1 = gtab[1]
      assert np.array_equal(gtab_slice1.bvals, np.array([100.0]))
      assert np.array_equal(
          gtab_slice1.bvecs, np.array([[1.0, 0.0, 0.0]])
      )
  
      # Test with a range of indices
      gtab = GradientTable(gradients)
      idx_start = 2
      idx_end = 5
      with warnings.catch_warnings():
          warnings.filterwarnings(
              "ignore",
              message=b0_threshold_update_slicing_message(idx_start),
              category=UserWarning,
          )
          gtab_slice2 = gtab[idx_start:idx_end]
          assert np.array_equal(
              gtab_slice2.bvals, np.array([200.0, 300.0, 400.0])
          )
          assert np.array_equal(
              gtab_slice2.bvecs,
              np.array(
                  [[0.0, 1.0, 0.0], [0.0, 0.0, 1.0], [1.0, 0.0, 0.0]]
              ),
          )
  
imports: import warnings
  import numpy
  import numpy.testing
  import pytest
  from dipy.data import get_fnames
  from dipy.core.gradients import b0_threshold_empty_gradient_message, b0_threshold_update_slicing_message, gradient_table, GradientTable, gradient_table_from_bvals_bvecs, gradient_table_from_qvals_bvecs, gradient_table_from_gradient_strength_bvecs, WATER_GYROMAGNETIC_RATIO, mask_non_weighted_bvals, orientation_to_string, reorient_bvecs, generate_bvecs, check_multi_b, round_bvals, get_bval_indices, unique_bvals_magnitude, unique_bvals_tolerance, unique_bvals, params_to_btens, btens_to_params, orientation_from_string, reorient_vectors
  from dipy.core.geometry import vec2vec_rotmat, vector_norm
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.utils.deprecator import ExpiredDeprecationError
  from dipy.testing import clear_and_catch_warnings
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 16 for calling a global function with example usage: test_getitem_idx() without return types