class_docstr: H-Infinity filter. You are responsible for setting the
  various state variables to reasonable values; the defaults below will
  not give you a functional filter.
  
  Parameters
  ----------
  
  dim_x : int
      Number of state variables for the Kalman filter. For example, if
      you are tracking the position and velocity of an object in two
      dimensions, dim_x would be 4.
  
      This is used to set the default size of `P`, `Q`, and `u`
  
  dim_z : int
      Number of of measurement inputs. For example, if the sensor
      provides you with position in (x, y), `dim_z` would be 2.
  
  dim_u : int
      Number of control inputs for the Gu part of the prediction step.
  
  gamma : float
  
  .. warning::
      I do not believe this code is correct. DO NOT USE THIS.
      In particular, note that predict does not update the covariance
      matrix.
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code: def __init__(self, dim_x, dim_z, dim_u, gamma):
      warnings.warn(
          "This code is likely incorrect. DO NOT USE.",
          DeprecationWarning,
      )
  
      self.dim_x = dim_x
      self.dim_z = dim_z
      self.dim_u = dim_u
      self.gamma = gamma
  
      self.x = zeros((dim_x, 1))  # state
  
      self.B = 0  # control transition matrix
      self.F = eye(dim_x)  # state transition matrix
      self.H = zeros((dim_z, dim_x))  # Measurement function
      self.P = eye(dim_x)  # Uncertainty covariance.
      self.Q = eye(dim_x)
  
      self._V_inv = zeros((dim_z, dim_z))  # inverse measurement noise
      self._V = zeros((dim_z, dim_z))  #  measurement noise
      self.W = zeros((dim_x, dim_x))  # process uncertainty
  
      # gain and residual are computed during the innovation step. We
      # save them so that in case you want to inspect them for various
      # purposes
  
      self.K = 0  # H-infinity gain
      self.y = zeros((dim_z, 1))
      self.z = zeros((dim_z, 1))
  
      # identity matrix. Do not alter this.
      self._I = np.eye(dim_x)
  
file_path: filterpy/filterpy/hinfinity/hinfinity_filter.py
imports: from __future__ import absolute_import, division
  import copy
  import warnings
  import numpy
  from numpy import dot, zeros, eye
  import scipy.linalg
  from filterpy.common import pretty_str
label_desc: Use image node_id 1 to create a new HInfinityFilter object from inherited base classes: object with example: obj = HInfinityFilter(dim_x, dim_z, dim_u, gamma)