class_docstr: Measures the expectation value of an operator using the classical shadow measurement process.
  
  Please refer to :func:`shadow_expval` for detailed documentation.
  
  Args:
      H (Operator, Sequence[Operator]): Operator or list of Operators to compute the expectation value over.
      seed (Union[int, None]): The seed used to generate the random measurements
      k (int): Number of equal parts to split the shadow's measurements to compute the median of means.
          ``k=1`` corresponds to simply taking the mean over all measurements.
      id (str): custom label given to a measurement instance, can be useful for some applications
          where the instance has to be identified
code: def samples_computational_basis(self):
      return False
  
imports: import copy
  from collections.abc import Iterable
  from typing import Optional, Union, Sequence
  from string import ascii_letters
  import numpy
  import pennylane
  from pennylane.operation import Operator
  from pennylane.wires import Wires
  from .measurements import MeasurementShapeError, MeasurementTransform, Shadow, ShadowExpval
label_desc: Use image node_id 6 for calling the ShadowExpvalMP obj's underlying member method code with example usage: obj.samples_computational_basis() and returns: False