class_docstr: A convenience class to access UCR/UEA time series datasets.
  
  When using one (or several) of these datasets in research projects, please
  cite [1]_.
  
  This class will attempt to recover from some known misnamed files, like the
  `StarLightCurves` dataset being provided in `StarlightCurves.zip` and
  alike.
  
  Parameters
  ----------
  use_cache : bool (default: True)
      Whether a cached version of the dataset should be used in
      :meth:`~load_dataset`, if one is found.
      Datasets are always cached upon loading, and this parameter only
      determines whether the cached version shall be refreshed upon loading.
  
  Notes
  -----
      Downloading dataset files can be time-consuming, it is recommended
      using `use_cache=True` (default) in order to only experience
      downloading time once per dataset and work on a cached version of the
      datasets afterward.
  
  See Also
  --------
  CachedDatasets : Provides pre-selected datasets for offline use.
  
  References
  ----------
  .. [1] A. Bagnall, J. Lines, W. Vickers and E. Keogh, The UEA & UCR Time
     Series Classification Repository, www.timeseriesclassification.com
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docstr: List datasets (both univariate and multivariate) available in the 
  UCR/UEA archive.
  
  Examples
  --------
  >>> l = UCR_UEA_datasets().list_datasets()
  >>> "PenDigits" in l
  True
  >>> "BeetleFly" in l
  True
  >>> "DatasetThatDoesNotExist" in l
  False
  
  Returns
  -------
  list of str:
      A list of names of all (univariate and multivariate) dataset namas.
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code: def list_datasets(self):
      """List datasets (both univariate and multivariate) available in the
      UCR/UEA archive.
  
      Examples
      --------
      >>> l = UCR_UEA_datasets().list_datasets()
      >>> "PenDigits" in l
      True
      >>> "BeetleFly" in l
      True
      >>> "DatasetThatDoesNotExist" in l
      False
  
      Returns
      -------
      list of str:
          A list of names of all (univariate and multivariate) dataset namas.
      """
      return (
          self.list_univariate_datasets()
          + self.list_multivariate_datasets()
      )
  
file_path: tslearn/tslearn/datasets/ucr_uea.py
imports: import os
  import warnings
  import csv
  import shutil
  from urllib.request import urlretrieve
  from tslearn.utils import _load_arff_uea, _load_txt_uea
  from .datasets import in_file_string_replace, extract_from_zip_url
label_desc: Use image node_id 5 for calling the UCR_UEA_datasets obj's underlying member method code with example usage: obj.list_datasets() and returns: unknown