class_docstr: Interface for Gaussian measurement for which Jacobians can be efficiently
  calculated, usu. analytically or by automatic differentiation.
class_docstr_tok: ["Interface","for","Gaussian","measurement","for","which","Jacobians","can","be","efficiently","calculated",",","usu",".","analytically","or","by","automatic","differentiation","."]
docstr: Compute and return Jacobian (H) of measurement map (h) at target PV
  state ``x`` .
  
  :param x: PV state. Use default argument ``None`` when 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. Use default argument ``None`` when the Jacobian is not
            state-dependent.
      :return: Read-only Jacobian (H) of measurement map (h).
      """
      raise NotImplementedError
  
imports: from abc import ABCMeta, abstractmethod
  import torch
  from pyro.distributions.util import eye_like
label_desc: Use image node_id 1 for calling the DifferentiableMeasurement obj's underlying member method code with example usage: obj.jacobian(x) without return types