def test_allequal(self):
df = pd.DataFrame()
df["c1"] = [chr(0) for _ in range(100)]
df["c2"] = [1 for _ in range(100)]
df["c3"] = [0.7 for _ in range(100)]
r = entropy(0, df)[0]
self.assertEqual(r, 0.)
r = entropy(1, df)[0]
self.assertEqual(r, 0.)
r = entropy(2, df)[0]
self.assertEqual(r, 0.)
def test_allnull(self):
df = pd.DataFrame()
df["c1"] = [None for i in range(100)]
df["c2"] = [np.NaN for i in range(100)]
df["c3"] = [np.NaN / 0.7 for i in range(100)]
r = entropy(0, df)[0]
self.assertEqual(r, 0.)
r = entropy(1, df)[0]
self.assertEqual(r, 0.)
r = entropy(2, df)[0]
self.assertEqual(r, 0.)
def test_empty(self):
df = pd.DataFrame()
df["c1"] = []
df["c2"] = []
r1 = entropy(0, df)[0]
self.assertEqual(r1, 0.)
def test_halfhalf(self):
df = pd.DataFrame()
c1 = [chr(1) for _ in range(50)]
c2 = [2 for _ in range(50)]
c3 = [0.7 for _ in range(50)]
c1.extend(["zz" for _ in range(50)])
c2.extend([100 for _ in range(50)])
c3.extend([32. for _ in range(50)])
df["c1"] = c1
df["c2"] = c2
df["c3"] = c3
r = entropy(0, df)[0]
self.assertAlmostEqual(r, 1., delta=0.000001)
r = entropy(1, df)[0]
self.assertAlmostEqual(r, 1., delta=0.000001)
r = entropy(2, df)[0]
self.assertAlmostEqual(r, 1., delta=0.000001)
def test_halfnull_halfequal(self):
df = pd.DataFrame()
c1 = [chr(1) for _ in range(50)]
c2 = [2 for _ in range(50)]
c3 = [0.7 for _ in range(50)]
c1.extend([None for _ in range(50)])
c2.extend([np.NaN for _ in range(50)])
c3.extend([None for _ in range(50)])
df["c1"] = c1
df["c2"] = c2
df["c3"] = c3
r = entropy(0, df)[0]
self.assertAlmostEqual(r, 0., delta=0.000001)
r = entropy(1, df)[0]
self.assertAlmostEqual(r, 0., delta=0.000001)
r = entropy(2, df)[0]
self.assertAlmostEqual(r, 0., delta=0.000001)
def test_alldifferent(self):
df = pd.DataFrame()
c1 = [chr(i) for i in range(100)]
c2 = [i for i in range(100)]
c3 = [i / 0.7 for i in range(100)]
df["c1"] = c1
df["c2"] = c2
df["c3"] = c3
res = 6.6438561897747395
r = entropy(0, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
r = entropy(1, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
r = entropy(2, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
for i in range(10):
c1[i] = None
c2[i] = None
c3[i] = np.NaN
df["c1"] = c1
df["c2"] = c2
df["c3"] = c3
res = 6.491853096329675
r = entropy(0, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
r = entropy(1, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
r = entropy(2, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
def test_mixed(self):
df = pd.DataFrame()
c1 = [chr(i) for i in range(10)]
c2 = [i for i in range(1, 11)]
c3 = [i / 0.7 for i in range(1, 11)]
c1.extend(["swwewww" for _ in range(20)])
c2.extend([5000 for _ in range(20)])
c3.extend([231321.23131 for _ in range(20)])
df["c1"] = c1
df["c2"] = c2
df["c3"] = c3
res = 2.025605199016944
r = entropy(0, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
r = entropy(1, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
r = entropy(2, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
c1.extend([None for _ in range(5)])
c2.extend([np.NaN for _ in range(5)])
c3.extend([np.NaN for _ in range(5)])
df = pd.DataFrame()
df["c1"] = c1
df["c2"] = c2
df["c3"] = c3
res = 2.025605199016944
r = entropy(0, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
r = entropy(1, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)
r = entropy(2, df)[0]
self.assertAlmostEqual(r, res, delta=0.000001)