def __init__(self, dim_x, dim_z, dim_u=0):

        assert dim_x > 0
        assert dim_z > 0
        assert dim_u >= 0

        self.dim_x = dim_x
        self.dim_z = dim_z
        self.dim_u = dim_u

        self._x = zeros((dim_x,1)) # state
        self._P = eye(dim_x)      # uncertainty covariance
        self._P1_2 = eye(dim_x)      # sqrt uncertainty covariance
        self._Q = eye(dim_x)      # sqrt process uncertainty
        self._Q1_2 = eye(dim_x)      # sqrt process uncertainty
        self._B = 0                # control transition matrix
        self._F = 0                # state transition matrix
        self._H = 0                # Measurement function
        self._R1_2 = eye(dim_z)      # sqrt state uncertainty

        # Residual is computed during the innovation (update) step. We
        # save it so that in case you want to inspect it for various
        # purposes
        self._y = zeros((dim_z, 1))

        # identity matrix.
        self._I = np.eye(dim_x)

        self._M = np.zeros((dim_z + dim_x, dim_z + dim_x))
Returns a list of identifiers that can be used to get key/value information
dataset/ETHPy150Open rlabbe/filterpy/filterpy/kalman/square_root.py/SquareRootKalmanFilter.__init__--crossover with--dataset/ETHPy150Open scottrice/Ice/ice/persistence/backing_store.py/BackingStore.identifiers