code: def _gp_index(
      x: np.ndarray,
      kernel: Kernel,
      max_chunk_size: int = 100,
  ) -> np.ndarray:
      """
      Sample a Gaussian process using input data.
      ``f(x) ~ GP(0, K)``
  
      If the number of samples is larger than ``max_chunk_size``, the sampling is
      split in sorted batches (first dimension) and sampled using a conditional
      multivariate normal.
  
      Args:
          x:
          kernel:
          max_chunk_size:
  
      Returns:
          A one-dimensional numpy array with a sample of f(x)
      """
      # if we dont have a parent, the input will have no columns
      if x.shape[1] == 0:
          return np.zeros(shape=(x.shape[0],))
  
      use_batches = x.shape[0] > max_chunk_size
  
      if not use_batches:
          y, _ = _unconditional_sample(x, kernel=kernel)
          return _scale_y(y)
  
      # if we need batches, we sort according to the first dimension
      ix_sort = np.argsort(x, axis=0)[:, 0].squeeze()
      reverse_ix = np.argsort(ix_sort).squeeze()
  
      # split into smaller pieces
      n_splits = (x.shape[0] // max_chunk_size) + 1
      x_splits = np.array_split(x[ix_sort, :], n_splits)
  
      outputs = []
      y, cov_mat = _unconditional_sample(x_splits[0], kernel=kernel)
      outputs.append(y)
      x_old = x_splits[0]
      for x_subset in x_splits[1:]:
          y, cov_mat = _conditional_sample(
              x_new=x_subset,
              x_old=x_old,
              f_old=outputs[-1],
              kernel=kernel,
              cov_mat_old=cov_mat,
          )
          outputs.append(y)
          x_old = x_subset
  
      y_all = _scale_y(np.concatenate(outputs))
      return y_all[reverse_ix]
  
imports: from typing import Dict, Hashable, List, Optional, Tuple, Union
  import networkx
  import numpy
  import pandas
  from sklearn.gaussian_process.kernels import RBF, Kernel
  from causalnex.structure import StructureModel
  from causalnex.structure.categorical_variable_mapper import VariableFeatureMapper, validate_schema
label_desc: Use image node_id 17 for calling a global function with example usage: _gp_index(x, kernel, max_chunk_size) and returns: y_all, np, _scale_y