code: def interp_sort(t, x):
      """
      sorts time series x by timestamp t, removing duplicates in the first entry
  
      this is required to user the scipy interp1d methods which returns nan when there are duplicate
      values for t_min
  
      this can be removed once the scipy issue is fixed
  
      Parameters
      ----------
      t : array-like, shape [n]
          timestamps
      x : array-like, shape [n, ]
          data
  
      Returns
      -------
      t : array-like, shape [n]
          timestamps
      x : array-like, shape [n, ]
          data
      """
      if len(t) != len(x):
          raise ValueError(
              "Interpolation time and value errors not equal"
          )
  
      ind = np.argsort(t)
      t = t[ind]
      x = x[ind]
  
      t, ind = np.unique(t, return_index=True)
  
      if len(t) < len(x):
          warnings.warn(
              "Interpolation time has duplicate time indices",
              UserWarning,
          )
          x = x[ind]
  
      return t, x
  
file_path: seglearn/seglearn/util.py
imports: from pandas import DataFrame
  import numpy
  import warnings
  from seglearn.base import TS_Data
label_desc: Use image node_id 5 for calling a global function with example usage: interp_sort(t, x) and returns: t,  x