class_docstr: Time series interpolator/re-sampler.
  
  Transformer that rescales series for another number of points.
  For each cell in dataframe transformer fits scipy linear interp1d
  and samples user defined number of points. Points are generated
  by numpy.linspace.
  
  After transformation each cell will be a pd.Series of given length.
  Indices of the pd.Series will be changed to integer indices.
  
  Parameters
  ----------
  length : integer, the length of time series to resize to.
docstr: Initialize estimator.
  
  Parameters
  ----------
  length : integer, the length of time series to resize to.
code: def __init__(self, length):
      """Initialize estimator.
  
      Parameters
      ----------
      length : integer, the length of time series to resize to.
      """
      if length <= 0 or (not isinstance(length, int)):
          raise ValueError("resizing length must be integer and > 0")
  
      self.length = length
      super().__init__()
  
file_path: sktime/sktime/transformations/panel/interpolate.py
imports: import numpy
  import pandas
  from sktime.transformations.base import BaseTransformer
  from sktime.utils.pandas import df_map
label_desc: Use image node_id 1 to create a new TSInterpolator object from inherited base classes: BaseTransformer with example: obj = TSInterpolator(length)