code: def update_data():
      np.random.seed(12345)
      xs_orig = np.random.uniform(0, 1, size=(1000, 5))
      xs_fresh = np.random.uniform(0, 1, size=xs_orig.shape)
      xs_fresh_small = np.random.uniform(
          0, 1, size=(100, xs_orig.shape[1])
      )
      xs_for_complete_update = np.random.uniform(
          0, 1, size=xs_orig.shape
      )
      updates = [
          (xs_orig, None, None, None),
          (xs_orig, xs_fresh, None, None),
          (
              xs_orig,
              None,
              xs_for_complete_update,
              list(range(xs_orig.shape[0])),
          ),
          (xs_orig, None, -xs_orig[0:50:2], list(range(0, 50, 2))),
          (xs_orig, None, -xs_orig[0:500:2], list(range(0, 500, 2))),
          (
              xs_orig,
              xs_fresh,
              xs_for_complete_update,
              list(range(xs_orig.shape[0])),
          ),
          (
              xs_orig,
              xs_fresh_small,
              -xs_orig[0:50:2],
              list(range(0, 50, 2)),
          ),
          (
              xs_orig,
              xs_fresh,
              -xs_orig[0:500:2],
              list(range(0, 500, 2)),
          ),
      ]
      return updates
  
file_path: pynndescent/pynndescent/tests/conftest.py
imports: import os
  import pytest
  import numpy
  from scipy import sparse
label_desc: Use image node_id 12 for calling a global function with example usage: update_data() and returns: updates