code: def print_table(accuracies, times):
      """Utility function to pretty print the obtained accuracies"""
      header_str = "|"
      header_str += "{:^20}|".format("dataset")
      columns = ["sax error", "sax time", "eucl error", "eucl time"]
      for col in columns:
          header_str += "{:^12}|".format(col)
      print(header_str)
      print("-" * (len(columns) * 13 + 22))
  
      for dataset in accuracies:
          acc_sax, acc_euclidean = accuracies[dataset]
          time_sax, time_euclidean = times[dataset]
          sax_error = numpy.around(1 - acc_sax, 5)
          eucl_error = numpy.around(1 - acc_euclidean, 5)
          time_sax = numpy.around(time_sax, 5)
          time_euclidean = numpy.around(time_euclidean, 5)
          s = "|"
          s += "{:>20}|".format(dataset)
          s += "{:>12}|".format(sax_error)
          s += "{:>12}|".format(time_sax)
          s += "{:>12}|".format(eucl_error)
          s += "{:>12}|".format(time_euclidean)
          print(s.strip())
  
      print("-" * (len(columns) * 13 + 22))
  
file_path: tslearn/docs/examples/neighbors/plot_sax_mindist_knn.py
imports: import warnings
  import time
  import numpy
  import matplotlib.pyplot
  from scipy.stats import norm
  from tslearn.datasets import UCR_UEA_datasets
  from tslearn.preprocessing import TimeSeriesScalerMeanVariance
  from tslearn.neighbors import KNeighborsTimeSeriesClassifier
  from sklearn.base import clone
  from sklearn.metrics import pairwise_distances, accuracy_score
  from sklearn.neighbors import KNeighborsClassifier
label_desc: Use image node_id 1 for calling a global function with example usage: print_table(accuracies, times) without return types