class_docstr: NCP (Nearly-Constant Position) dynamic model. May be subclassed, e.g., with
  CWNV (Continuous White Noise Velocity) or DWNV (Discrete White Noise
  Velocity).
  
  :param dimension: native state dimension.
  :param sv2: variance of velocity. Usually chosen so that the standard
        deviation is roughly half of the max velocity one would ever expect
        to observe.
class_docstr_tok: ["NCP","(","Nearly-Constant","Position",")","dynamic","model",".","May","be","subclassed",",","e.g.",",","with","CWNV","(","Continuous","White","Noise","Velocity",")","or","DWNV","(","Discrete","White","Noise","Velocity",")",".",":","param","dimension",":","native","state","dimension",".",":","param","sv2",":","variance","of","velocity",".","Usually","chosen","so","that","the","standard","deviation","is","roughly","half","of","the","max","velocity","one","would","ever","expect","to","observe","."]
docstr: Compute and return cached native state transition Jacobian (F) over
  time interval ``dt``.
  
  :param dt: time interval to integrate over.
  :return: Read-only Jacobian (F) of integration map (f).
docstr_tok: ["Compute","and","return","cached","native","state","transition","Jacobian","(","F",")","over","time","interval","``","dt","``",".",":","param","dt",":","time","interval","to","integrate","over",".",":","return",":","Read-only","Jacobian","(","F",")","of","integration","map","(","f",")","."]
code: def jacobian(self, dt):
      """
      Compute and return cached native state transition Jacobian (F) over
      time interval ``dt``.
  
      :param dt: time interval to integrate over.
      :return: Read-only Jacobian (F) of integration map (f).
      """
      return self._F_cache
  
imports: from abc import ABCMeta, abstractmethod
  import torch
  from torch import nn
  from torch.nn import Parameter
  import pyro.distributions
  from pyro.distributions.util import eye_like
label_desc: Use image node_id 5 for calling the Ncp obj's underlying member method code with example usage: obj.jacobian(dt) and returns: self