docstr: ...Test if grad and log likelihood are correctly computed
          
docstr_tok: ["...","Test","if","grad","and","log","likelihood","are","correctly","computed"]
code: def test_hawkesgrad_hess_norm(self):
      """...Test if grad and log likelihood are correctly computed"""
      hessian_point = np.random.rand(self.model.n_coeffs)
      vector = np.random.rand(self.model.n_coeffs)
  
      hessian_norm = self.model.hessian_norm(hessian_point, vector)
  
      delta = 1e-7
      grad_point_minus = self.model.grad(hessian_point + delta * vector)
      grad_point_plus = self.model.grad(hessian_point - delta * vector)
      finite_diff_result = vector.dot(
          grad_point_minus - grad_point_plus
      )
      finite_diff_result /= 2 * delta
      self.assertAlmostEqual(finite_diff_result, hessian_norm)
  
      # print(self.model.hessian(hessian_point).shape, vector.shape)
      # print(self.model.hessian(hessian_point).dot(vector).shape)
      np.set_printoptions(precision=2)
  
      hessian_result = vector.T.dot(
          self.model.hessian(hessian_point).dot(vector)
      )
      self.assertAlmostEqual(hessian_result, hessian_norm)
  
file_path: tick/tick/hawkes/model/tests/model_hawkes_sumexpkern_loglik_test.py
imports: import unittest
  import numpy
  from scipy.optimize import check_grad
  from tick.hawkes.model import ModelHawkesSumExpKernLogLik
  from tick.hawkes.model.tests.model_hawkes_test_utils import hawkes_log_likelihood, hawkes_sumexp_kernel_intensities
label_desc: Use image node_id 7 for calling the Test obj's underlying member method code with example usage: obj.test_hawkesgrad_hess_norm() without return types