code: def poly_extrapolate(x, y, order):
      r"""Extrapolator to :math:`f(0)` for polynomial fit.
  
      The polynomial is defined as ``f(x) = p[0] * x**deg + p[1] * x**(deg-1) + ... + p[deg]`` such that ``deg = order + 1``.
      This function is compatible with all interfaces supported by pennylane.
  
      Args:
          x (Array): Data in x
          y (Array): Data in y = f(x)
          order (int): Order of the polynomial fit
  
      Returns:
          float: Extrapolated value at f(0).
  
      .. seealso:: :func:`~.pennylane.transforms.richardson_extrapolate`, :func:`~.pennylane.transforms.mitigate_with_zne`
  
      **Example:**
  
      >>> x = np.linspace(1, 10, 5)
      >>> y = x**2 + x + 1 + 0.3 * np.random.rand(len(x))
      >>> qml.transforms.poly_extrapolate(x, y, 2)
      tensor(1.01717601, requires_grad=True)
  
      """
      coeff = _polyfit(x, y, order)
      return coeff[-1]
  
file_path: pennylane/pennylane/transforms/mitigate.py
imports: from copy import copy
  from typing import Any, Dict, Optional, Sequence, Callable
  from pennylane import apply, adjoint
  from pennylane.math import mean, shape, round
  from pennylane.queuing import AnnotatedQueue
  from pennylane.tape import QuantumTape, QuantumScript
  from pennylane.transforms import transform
  import pennylane
label_desc: Use image node_id 5 for calling a global function with example usage: poly_extrapolate(x, y, order) and returns: coeff