class_docstr: Full-rank Gaussian position measurement in Euclidean space.
  
  :param mean: mean of measurement distribution.
  :param cov: covariance of measurement distribution.
  :param time: time of measurement.
class_docstr_tok: ["Full-rank","Gaussian","position","measurement","in","Euclidean","space",".",":","param","mean",":","mean","of","measurement","distribution",".",":","param","cov",":","covariance","of","measurement","distribution",".",":","param","time",":","time","of","measurement","."]
docstr: Compute and return Jacobian (H) of measurement map (h) at target PV
  state ``x`` .
  
  :param x: PV state. The default argument ``None`` may be used in this
        subclass since the Jacobian is not state-dependent.
  :return: Read-only Jacobian (H) of measurement map (h).
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code: def jacobian(self, x=None):
      """
      Compute and return Jacobian (H) of measurement map (h) at target PV
      state ``x`` .
  
      :param x: PV state. The default argument ``None`` may be used in this
            subclass since the Jacobian is not state-dependent.
      :return: Read-only Jacobian (H) of measurement map (h).
      """
      return self._jacobian
  
imports: from abc import ABCMeta, abstractmethod
  import torch
  from pyro.distributions.util import eye_like
label_desc: Use image node_id 3 for calling the PositionMeasurement obj's underlying member method code with example usage: obj.jacobian(x) and returns: self