content: import unittest
  from conformal_predictors.nc_measures.SVM import SVCDistanceNCMeasure
  from sklearn.svm import SVC
  from numpy import array
  
  
  class SVMTest(unittest.TestCase):
  
      def setUp(self):
          pass
  
      def tearDown(self):
          pass
  
      def test_1(self):
          x = array([[1, 1], [2, 2]])
          y = array([0, 1])
          measure = SVCDistanceNCMeasure()
          clf = SVC(decision_function_shape='ovr')
          clf.fit(x, y)
          measures = measure.evaluate(clf, x)
          self.assertAlmostEqual(measures[0, 0], -.63212056)
          self.assertAlmostEqual(measures[0, 1], .63212056)
          self.assertAlmostEqual(measures[1, 0], .63212056)
          self.assertAlmostEqual(measures[1, 1], -.63212056)
  
      def tests_2(self):
          x = array([[1, 1], [2, 2], [3, 3]])
          y = array([0, 1, 2])
          measure = SVCDistanceNCMeasure()
          clf = SVC(decision_function_shape='ovr')
          clf.fit(x, y)
          measures = measure.evaluate(clf, x)
          self.assertAlmostEqual(measures[0, 0], -1.5)
          self.assertAlmostEqual(measures[0, 1], 1.08754365)
          self.assertAlmostEqual(measures[0, 2], .41245635)
          self.assertAlmostEqual(measures[1, 0], 1.19584788)
          self.assertAlmostEqual(measures[1, 1], -1.60830423)
          self.assertAlmostEqual(measures[1, 2], .19584788)
          self.assertAlmostEqual(measures[2, 0], .41245635)
          self.assertAlmostEqual(measures[2, 1], 1.08754365)
          self.assertAlmostEqual(measures[2, 2], -1.5)
  