class_docstr: Common features in univariate interpolation
  
  Deal with input data type and interpolation axis rolling. The
  actual interpolator can assume the y-data is of shape (n, r) where
  `n` is the number of x-points, and `r` the number of variables,
  and use self.dtype as the y-data type.
  
  Attributes
  ----------
  _y_axis
      Axis along which the interpolation goes in the original array
  _y_extra_shape
      Additional trailing shape of the input arrays, excluding
      the interpolation axis.
  dtype
      Dtype of the y-data arrays. Can be set via _set_dtype, which
      forces it to be float or complex.
  
  Methods
  -------
  __call__
  _prepare_x
  _finish_y
  _reshape_yi
  _set_yi
  _set_dtype
  _evaluate
docstr: Actually evaluate the value of the interpolator.
docstr_tok: ["Actually","evaluate","the","value","of","the","interpolator","."]
code: def _evaluate(self, x):
      """
      Actually evaluate the value of the interpolator.
      """
      raise NotImplementedError()
  
imports: import numpy
  from scipy.special import factorial
  from scipy._lib._util import _asarray_validated, float_factorial
label_desc: Use image node_id 3 for calling the _Interpolator1D obj's underlying member method code with example usage: obj._evaluate(x) without return types