text: import numpy as np
  
  from emukit.bayesian_optimization import epmgp
  
  
  def test_joint_min():
  
      # Uniform distribution
      n_points = 5
      m = np.ones([n_points])
      v = np.eye(n_points)
  
      pmin = epmgp.joint_min(m, v)
      pmin = np.exp(pmin)
  
      uprob = 1.0 / n_points
  
      assert pmin.shape[0] == n_points
      assert np.any(pmin < (uprob + 0.03)) and np.any(pmin > uprob - 0.01)
  
      # Dirac delta
      m = np.ones([n_points]) * 1000
      m[0] = 1
      v = np.eye(n_points)
  
      pmin = epmgp.joint_min(m, v)
      pmin = np.exp(pmin)
      assert pmin[0] == 1.0
      assert np.any(pmin[:1] > 1e-10)
  