code: def ucr_dataset_info(dataset=None):
      """Information about the UCR datasets.
  
      Parameters
      ----------
      dataset : str, list of str or None (default = None)
          The data sets for which the information will be returned.
          If None, the information for all the datasets is returned.
  
      Returns
      -------
      dictionary : dict
          Dictionary with the information for each dataset.
  
      References
      ----------
      .. [1] `List of datasets on the UEA & UCR archive
             <http://www.timeseriesclassification.com/dataset.php>`_
  
      Examples
      --------
      >>> from pyts.datasets import ucr_dataset_info
      >>> ucr_dataset_info('Adiac')['n_classes']
      37
  
      """
      module_path = os.path.dirname(__file__)
      finfo = os.path.join(module_path, "info", "ucr.pickle")
      dictionary = pickle.load(open(finfo, "rb"))
      datasets = list(dictionary.keys())
  
      if dataset is None:
          return dictionary
      elif isinstance(dataset, str):
          if dataset not in datasets:
              raise ValueError(
                  "{0} is not a valid name. The list of available names "
                  "can be obtained by calling the "
                  "'pyts.datasets.ucr_dataset_list' function.".format(
                      dataset
                  )
              )
          else:
              return dictionary[dataset]
      elif isinstance(dataset, (list, tuple, np.ndarray)):
          dataset = np.asarray(dataset)
          invalid_datasets = np.setdiff1d(dataset, datasets)
          if invalid_datasets.size > 0:
              raise ValueError(
                  "The following names are not valid: {0}. The list of "
                  "available names can be obtained by calling the "
                  "'pyts.datasets.ucr_dataset_list' function.".format(
                      invalid_datasets
                  )
              )
          else:
              info = {}
              for data in dataset:
                  info[data] = dictionary[data]
              return info
  
file_path: pyts/pyts/datasets/ucr.py
imports: import numpy
  import os
  import pickle
  from scipy.io.arff import loadarff
  from sklearn.utils import Bunch
  from urllib.request import urlretrieve
  import zipfile
label_desc: Use image node_id 4 for calling a global function with example usage: ucr_dataset_info(dataset) and returns: dictionary, dictionary, info