code: def plot_splits(X, y, groups, image_file_path=None, **cv_args):
      """Visualize splits by group."""
      cv = GroupTimeSeriesSplit(**cv_args)
      cv._n_groups = len(np.unique(groups))
      cv._calculate_split_params()
      n_splits = cv.n_splits
  
      plot_split_indices(
          cv,
          cv_args,
          X,
          y,
          groups,
          n_splits,
          image_file_path=image_file_path,
      )
  
file_path: mlxtend/mlxtend/evaluate/time_series.py
imports: from itertools import accumulate, chain, groupby, islice
  import matplotlib.pyplot
  import numpy
  from matplotlib.patches import Patch
  from matplotlib.ticker import MaxNLocator
  from sklearn.utils import indexable
label_desc: Use image node_id 3 for calling a global function with example usage: plot_splits(X, y, groups, image_file_path) without return types