class_docstr: Class for modeling a linear 1D localization problem.
  
  The state is made of a scalar position and scalar speed, thus a 2D vector.
  A sensor provides acceleration inputs, while another one provides sparse
  measurements of the position.
docstr: Model used to create the measurements.
  
  This model simply outputs the position part of the state, i.e. its
  first element.
  
  Parameters
  ----------
  state : array-like, shape=[dim]
      Vector representing the state.
  
  Returns
  -------
  observation : array-like, shape=[dim_obs]
      Expected observation of the state.
docstr_tok: ["Model","used","to","create","the","measurements",".","This","model","simply","outputs","the","position","part","of","the","state",",","i.e",".","its","first","element",".","Parameters","--","--","--","--","--","state",":","array-like",",","shape=","[","dim","]","Vector","representing","the","state",".","Returns","--","--","--","-","observation",":","array-like",",","shape=","[","dim_obs","]","Expected","observation","of","the","state","."]
code: def observation_model(state):
      """Model used to create the measurements.
  
      This model simply outputs the position part of the state, i.e. its
      first element.
  
      Parameters
      ----------
      state : array-like, shape=[dim]
          Vector representing the state.
  
      Returns
      -------
      observation : array-like, shape=[dim_obs]
          Expected observation of the state.
      """
      return state[:1]
  
imports: import geomstats.backend
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.matrices import Matrices
  from geomstats.geometry.special_euclidean import SpecialEuclidean
label_desc: Use image node_id 7 for calling the LocalizationLinear obj's underlying member method code with example usage: obj.observation_model(state) and returns: state