def test_probability_calc_one_column(self):
matrix = pd.read_csv('test_files/test_probability_calc.csv', dtype=np.str)
samples = SampleSet(matrix)
a_prob = samples.probability(['a'])
self.assertEqual(float(a_prob.query('a=="catA"').joint_prob), 0.3)
self.assertEqual(float(a_prob.query('a=="catB"').joint_prob), 0.25)
self.assertEqual(float(a_prob.query('a=="catC"').joint_prob), 0.45)
def test_probability_calc_shuffled_columns(self):
matrix = pd.read_csv(
'test_files/test_probability_calc_shuffled_columns.csv',
dtype=np.str)
samples = SampleSet(matrix)
a_prob = samples.probability(['b', 'a'])
self.assertEqual(
float(a_prob.query('b=="1" and a=="catA"').joint_prob), 0.2)
self.assertEqual(
float(a_prob.query('b=="2" and a=="catA"').joint_prob), 0.1)
