def testSerialization4(self):
# This test verifies that saveToFile() and loadFromFile with BINARY on Classifier are accessible from Python.
inputData = SDR( 1000 ).randomize( 0.02 )
categories = { 'A': 0, 'B': 1, 'C': 2, 'D': 3 }
c1 = Classifier()
c1.learn(inputData, categories['B'] )
file = "Classifier_test_save.BINARY"
c1.saveToFile(file)
c2 = Classifier()
c2.loadFromFile(file)
result2 = c2.infer( inputData )
self.assertTrue(numpy.argmax( result2 ) == categories['B'])
os.remove(file)
def testSerialization3(self):
# This test verifies that saveToFile() and loadFromFile() on Classifier are accessable from Python.
SDR1 = SDR(15); SDR1.sparse = [1, 5, 9]
SDR2 = SDR(15); SDR2.sparse = [0, 6, 9, 11]
SDR3 = SDR(15); SDR3.sparse = [6, 9]
SDR4 = SDR(15); SDR4.sparse = [1, 5, 9]
c1 = Classifier()
c1.learn(pattern=SDR1, classification=4)
c1.learn(pattern=SDR2, classification=5)
c1.learn(pattern=SDR3, classification=5)
c1.learn(pattern=SDR4, classification=4)
# The Predictor now has some data in it, try serialization.
file = "Classifier_test_save.XML"
c1.saveToFile(file, "XML")
c2 = Classifier()
c2.loadFromFile(file, "XML")
os.remove(file)
result1 = c1.infer(SDR1)
result2 = c2.infer(SDR1)
self.assertEqual(len(result1), len(result2))
for i in range(len(result1)):
self.assertAlmostEqual(result1[i], result2[i], places=5)
