code: def jitter(x, inplace=False, scale=0.01, random_state=None):
      """Add jitter with small standard deviation to avoid numerical problems
      when the points overlap exactly.
  
      Parameters
      ----------
      x: np.ndarray
      inplace: bool
      scale: float
      random_state: int or np.random.RandomState
  
      Returns
      -------
      np.ndarray
          A jittered version of ``x``.
  
      """
      if not inplace:
          x = np.array(x, copy=True)
  
      target_std = np.std(x[:, 0]) * scale
      random_state = check_random_state(random_state)
      x += random_state.normal(0, target_std, x.shape)
  
      return x
  
file_path: openTSNE/openTSNE/initialization.py
imports: import numpy
  import scipy.sparse
  from sklearn.decomposition import PCA
  from sklearn.utils import check_random_state
  from openTSNE import utils
label_desc: Use image node_id 2 for calling a global function with example usage: jitter(x, inplace, scale, random_state) and returns: x