docs: def encodeSplines(x, n_bases=10, spline_order=3, start=None, end=None, warn=True):
      """**Deprecated**. Function version of the transformer class `EncodeSplines`.
      Get B-spline base-function expansion
  
      # Details
          First, the knots for B-spline basis functions are placed
          equidistantly on the [start, end] range.
          (inferred from the data if None). Next, b_n(x) value is
          is computed for each x and each n (spline-index) with
          `scipy.interpolate.splev`.
  
      # Arguments
          x: a numpy array of positions with 2 dimensions
          n_bases int: Number of spline bases.
          spline_order: 2 for quadratic, 3 for qubic splines
          start, end: range of values. If None, they are inferred from the data
          as minimum and maximum value.
          warn: Show warnings.
  
      # Returns
          `np.ndarray` of shape `(x.shape[0], x.shape[1], n_bases)`
      """
  
      # TODO - make it general...
      if len(x.shape) == 1:
          x = x.reshape((-1, 1))
  
      if start is None:
          start = np.nanmin(x)
      else:
          if x.min() < start:
              if warn:
                  print("WARNING, x.min() < start for some elements. Truncating them to start: x[x < start] = start")
              x = _trunc(x, minval=start)
      if end is None:
          end = np.nanmax(x)
      else:
          if x.max() > end:
              if warn:
                  print("WARNING, x.max() > end for some elements. Truncating them to end: x[x > end] = end")
              x = _trunc(x, maxval=end)
      bs = BSpline(start, end,
                   n_bases=n_bases,
                   spline_order=spline_order
                   )
  
      # concatenate x to long
      assert len(x.shape) == 2
      n_rows = x.shape[0]
      n_cols = x.shape[1]
  
      x_long = x.reshape((-1,))
  
      x_feat = bs.predict(x_long, add_intercept=False)  # shape = (n_rows * n_cols, n_bases)
  
      x_final = x_feat.reshape((n_rows, n_cols, n_bases))
      return x_final