code: def load_gun_point_segmentation():
      """Load the GunPoint time series segmentation problem and returns X.
  
      We group TS of the UCR GunPoint dataset by class label and concatenate
      all TS to create segments with repeating temporal patterns and
      characteristics. The location at which different classes were
      concatenated are marked as change points.
  
      We resample the resulting TS to control the TS resolution.
      The window sizes for these datasets are hand-selected to capture
      temporal patterns but are approximate and limited to the values
      [10,20,50,100] to avoid over-fitting.
  
      Returns
      -------
      X : pd.Series
          Single time series for segmentation
      period_length : int
          The annotated period length by a human expert
      change_points : numpy array
          The change points annotated within the dataset
  
      Examples
      --------
      >>> from sktime.datasets import load_gun_point_segmentation
      >>> X, period_length, change_points = load_gun_point_segmentation()
      """
      dir = "segmentation"
      name = "GunPoint"
      fname = name + ".csv"
  
      period_length = int(10)
      change_points = np.int32([900])
  
      path = os.path.join(MODULE, DIRNAME, dir, fname)
      ts = pd.read_csv(path, index_col=0, header=None).squeeze(
          "columns"
      )
  
      return ts, period_length, change_points
  
imports: import os
  import zipfile
  from urllib.error import HTTPError, URLError
  from warnings import warn
  import numpy
  import pandas
  from sktime.datasets._data_io import _download_and_extract, _list_available_datasets, _load_dataset, _load_provided_dataset
  from sktime.datasets._readers_writers.tsf import load_tsf_to_dataframe
  from sktime.datasets.tsf_dataset_names import tsf_all, tsf_all_datasets
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 17 for calling a global function with example usage: load_gun_point_segmentation() and returns: ts,  period_length,  change_points