class_docstr: Default Gaussian device for PennyLane.
  
  Args:
      wires (int, Iterable[Number, str]): Number of subsystems represented by the device,
          or iterable that contains unique labels for the subsystems as numbers (i.e., ``[-1, 0, 2]``)
          or strings (``['ancilla', 'q1', 'q2']``). Default 1 if not specified.
      shots (None, int): How many times the circuit should be evaluated (or sampled) to estimate
          the expectation values. If ``None``, the results are analytically computed and hence deterministic.
      hbar (float): (default 2) the value of :math:`\hbar` in the commutation
          relation :math:`[\x,\p]=i\hbar`
class_docstr_tok: ["Default","Gaussian","device","for","PennyLane",".","Args",":","wires","(","int",",","Iterable","[","Number",",","str","]",")",":","Number","of","subsystems","represented","by","the","device",",","or","iterable","that","contains","unique","labels","for","the","subsystems","as","numbers","(","i.e.",",","``","[","-1",",","0",",","2","]","``",")","or","strings","(","``","[","'ancilla","'",",","'q1","'",",","'q2","'","]","``",")",".","Default","1","if","not","specified",".","shots","(","None",",","int",")",":","How","many","times","the","circuit","should","be","evaluated","(","or","sampled",")","to","estimate","the","expectation","values",".","If","``","None","``",",","the","results","are","analytically","computed","and","hence","deterministic",".","hbar","(","float",")",":","(","default","2",")","the","value","of",":","math",":","`","\\hbar","`","in","the","commutation","relation",":","math",":","`","[","\\x",",","\\p","]","=i\\hbar","`"]
code: def observables(self):
      return set(self._observable_map.keys())
  
imports: import math
  import cmath
  import numpy
  from scipy.special import factorial
  import pennylane
  from pennylane.ops import Identity
  from pennylane import Device
  from .._version import __version__
label_desc: Use image node_id 12 for calling the DefaultGaussian obj's underlying member method code with example usage: obj.observables() and returns: set