code: def test_default_dims():
      kf = KalmanFilter(dim_x=3, dim_z=1)
      kf.predict()
      kf.update(np.array([[1.0]]).T)
  
imports: from __future__ import absolute_import, division, print_function
  import numpy.random
  from numpy.random import randn
  import numpy
  import matplotlib.pyplot
  from pytest import approx
  from filterpy.kalman import KalmanFilter, update, predict, batch_filter
  from filterpy.common import Q_discrete_white_noise, kinematic_kf, Saver
  from filterpy.stats import mahalanobis
  from scipy.linalg import block_diag, norm
label_desc: Use image node_id 15 for calling a global function with example usage: test_default_dims() without return types