test/test_HMMR_HMM.py

   1 import unittest
   2 import pytest
   3 from MACS3.Signal.HMMR_HMM import hmm_training, hmm_predict
   4 import numpy as np
   5
   6 # ------------------------------------
   7 # Main function
   8 # ------------------------------------
   9 ''' This unittest is to check the ouputs of the hmm_training() and hmm_predict() functions
  10 '''
  11
  12 # @pytest.mark.skip(reason="need to refine later")
  13 class Test_HMM_train(unittest.TestCase):
  14     def setUp( self ):
  15         self.train_data = np.loadtxt("test/large_training_data.txt", delimiter="\t", dtype="float", usecols=(2,3,4,5)).tolist()
  16         self.training_data_lengths = np.loadtxt('test/large_training_lengths.txt', dtype="int").tolist()
  17         self.expected_converged = True
  18         self.not_expected_covars = None
  19         self.not_expected_means = None
  20         self.not_expected_transmat = None
  21
  22     def test_predict( self ):
  23         model = hmm_training(training_data = self.train_data, training_data_lengths = self.training_data_lengths, n_states = 3, random_seed = 12345)
  24
  25         self.assertEqual( model.monitor_.converged, self.expected_converged )
  26         self.assertNotEqual( model.covars_.tolist(), self.not_expected_covars )
  27         self.assertNotEqual( model.means_.tolist(), self.not_expected_means )
  28         self.assertNotEqual( model.transmat_.tolist(), self.not_expected_transmat )
  29