code: def check_rbf1d_stability(function):
      # Check that the Rbf function with default epsilon is not subject
      # to overshoot. Regression for issue #4523.
      #
      # Generate some data (fixed random seed hence deterministic)
      np.random.seed(1234)
      x = np.linspace(0, 10, 50)
      z = x + 4.0 * np.random.randn(len(x))
  
      rbf = Rbf(x, z, function=function)
      xi = np.linspace(0, 10, 1000)
      yi = rbf(xi)
  
      # subtract the linear trend and make sure there no spikes
      assert_(np.abs(yi - xi).max() / np.abs(z - x).max() < 1.1)
  
imports: import numpy
  from numpy.testing import assert_, assert_array_almost_equal, assert_almost_equal
  from numpy import linspace, sin, cos, random, exp, allclose
  from scipy.interpolate._rbf import Rbf
label_desc: Use image node_id 13 for calling a global function with example usage: check_rbf1d_stability(function) without return types