def test_nmi(self):
"""
Test the normalized mututal information function
"""
x = array([[0.1,0.2,0.3,0.4],[1,1,1,0],[0.01,0.04,0.09,0.16],[0,0,0,1]])
y = array([[-0.1,-0.2,-0.3,-0.4],[1,1,0,0],[0.25,0.5,0.75,1.0],[0.015625,0.125,0.421875,1.0]])
dx = stats.discretize( x, iN = None, method = None, aiSkip = [1,3] )
dy = stats.discretize( y, iN = None, method = None, aiSkip = [1] )
p = itertools.product( range(len(x)), range(len(y)) )
expected_result={ 0: 1.0, 1: 0.345592029944, 2: 1.0, 3: 0.345592029944}
for (i,j) in p:
self.assertAlmostEqual(expected_result[i], distance.nmi(dx[i],dy[j]))
def test_ami(self):
"""
Test the adjusted mutual information function
"""
x = array([[0.1,0.2,0.3,0.4],[1,1,1,0],[0.01,0.04,0.09,0.16],[0,0,0,1]])
y = array([[-0.1,-0.2,-0.3,-0.4],[1,1,0,0],[0.25,0.5,0.75,1.0],[0.015625,0.125,0.421875,1.0]])
dx = stats.discretize( x, iN = None, method = None, aiSkip = [1,3] )
dy = stats.discretize( y, iN = None, method = None, aiSkip = [1] )
p = itertools.product( range(len(x)), range(len(y)) )
expected_result={ 0: 1.0, 1: 2.51758394487e-08, 2: 1.0, 3: -3.72523550982e-08}
for (i,j) in p:
self.assertAlmostEqual(expected_result[i], distance.ami(dx[i],dy[j]))
def test_discretize_nine_values(self):
"""
Test the discretize function on nine values which are mostly zero
"""
expected_result=[1, 0, 0, 0, 0, 0, 0, 0, 0]
result=stats.discretize([0.1, 0, 0, 0, 0, 0, 0, 0, 0])
self.assertEqual(expected_result,result)
def test_discretize_three_bins_ten_values(self):
"""
Test the discretize function on ten values with three bins
"""
expected_result=[0, 0, 0, 0, 1, 1, 1, 1, 1, 2]
result=stats.discretize([0, 0, 0, 0, 1, 2, 2, 2, 2, 3], 3)
self.assertEqual(expected_result,result)
def test_discretize_sixty_bins_six_values(self):
"""
Test the discretize function on six values with sixty bins
"""
expected_result=[3, 1, 5, 0, 2, 4]
result=stats.discretize([0.4, 0.2, 0.6, 0.1, 0.3, 0.5], 60)
self.assertEqual(expected_result,result)
def test_discretize_six_values(self):
"""
Test the discretize function on six values with default bins
"""
expected_result=[1, 0, 1, 0, 0, 1]
result=stats.discretize([0.4, 0.2, 0.6, 0.1, 0.3, 0.5])
self.assertEqual(expected_result,result)
def test_discretize_tenths(self):
"""
Test the discretize function on four values of tenths
"""
expected_result=[0, 0, 1, 1]
result=stats.discretize([0.1, 0.2, 0.3, 0.4])
self.assertEqual(expected_result,result)
def test_discretize_two_bins_four_values_one_int(self):
"""
Test the discretize function on four values (one int) with two bins
"""
expected_result=[1, 0, 0, 1]
result=stats.discretize([4, 0.2, 0.1, 0.3], 2)
self.assertEqual(expected_result,result)
def test_discretize_squares(self):
"""
Test the discretize function on four values of squares
"""
expected_result=[0, 0, 1, 1]
result=stats.discretize([0.01, 0.04, 0.09, 0.16])
self.assertEqual(expected_result,result)
def test_discretize_one_bin_three_values(self):
"""
Test the discretize function on three values with one bin
"""
expected_result=[0, 0, 0]
result=stats.discretize([0.2, 0.1, 0.3], 1)
self.assertEqual(expected_result,result)
def test_discretize_three_bins_three_values(self):
"""
Test the discretize function on three values with three bins
"""
expected_result=[1, 0, 2]
result=stats.discretize([0.2, 0.1, 0.3], 3)
self.assertEqual(expected_result,result)
def test_discretize_two_bins_two_values(self):
"""
Test the discretize function two values with two bins
"""
expected_result=[0,1]
result=stats.discretize([0, 1], 2)
self.assertEqual(expected_result,result)
def test_discretize_two_bins_two_values_reverse(self):
"""
Test the discretize function on two values (revered order) with two bins
"""
expected_result=[1,0]
result=stats.discretize([1, 0], 2)
self.assertEqual(expected_result,result)
def test_discretize_zero(self):
"""
Test the discretize function on an array containing a single zero
"""
expected_result=[0]
result=stats.discretize([0])
self.assertEqual(expected_result,result)
def test_discretize_one(self):
"""
Test the discretize function on an array of [0,1]
"""
expected_result=[0,0]
result=stats.discretize([0,1])
self.assertEqual(expected_result,result)
def test_discretize_eights(self):
"""
Test the discretize function on four values of eigths
"""
expected_result=[0, 0, 1, 1]
result=stats.discretize([0.015625, 0.125, 0.421875, 1])
self.assertEqual(expected_result,result)
def test_discretize_quarters(self):
"""
Test the discretize function on four values of quarters
"""
expected_result=[0, 0, 1, 1]
result=stats.discretize([0.25, 0.5, 0.75, 1.00])
self.assertEqual(expected_result,result)
def test_discretize_negatives(self):
"""
Test the discretize function on all negative values
"""
expected_result=[1, 1, 0, 0]
result=stats.discretize([-0.1, -0.2, -0.3, -0.4])
self.assertEqual(expected_result,result)
def test_discretize_two_bins_four_values_all_floats(self):
"""
Test the discretize function on four values (all floats) with two bins
"""
expected_result=[1, 0, 0, 1]
result=stats.discretize([0.4, 0.2, 0.1, 0.3], 2)
self.assertEqual(expected_result,result)
def test_discretize_array_skip_two(self):
"""
Test the discretize function with a numpy array and two skips
"""
expected_result=array([
[ 0., 0., 1., 1.],
[ 1., 1., 1., 0.],
[ 0., 0., 1., 1.],
[ 0., 0., 0., 1.]])
x = array([[0.1,0.2,0.3,0.4],[1,1,1,0],[0.01,0.04,0.09,0.16],[0,0,0,1]])
result=stats.discretize(x, aiSkip = [1,3])
self.assertEqual(expected_result.all(),result.all())
def test_discretize_array_skip_one(self):
"""
Test the discretize function with a numpy array and one skip
"""
expected_result=array([
[ 1., 1., 0., 0.],
[ 1., 1., 0., 0.],
[ 0., 0., 1., 1.],
[ 0., 0., 1., 1.]])
y = array([[-0.1,-0.2,-0.3,-0.4],[1,1,0,0],[0.25,0.5,0.75,1.0],
[0.015625,0.125,0.421875,1.0]])
result=stats.discretize(y, aiSkip = [1])
self.assertEqual(expected_result.all(),result.all())
def test_discretize_fifty_one_values(self):
"""
Test the discretize function on a large set of values
"""
expected_result=[3, 6, 6, 5, 5, 0, 2, 2, 3, 5,
2, 4, 4, 2, 3, 5, 0, 4, 0, 6,
0, 1, 6, 1, 5, 3, 0, 3, 2, 1,
3, 0, 6, 3, 2, 0, 6, 5, 1, 3,
6, 4, 1, 1, 4, 5, 0, 4, 2, 4, 1]
input_values=[0.992299, 1, 1, 0.999696, 0.999605, 0.663081, 0.978293,
0.987621, 0.997237, 0.999915, 0.984792, 0.998338, 0.999207, 0.98051,
0.997984, 0.999219, 0.579824, 0.998983, 0.720498, 1, 0.803619,
0.970992, 1, 0.952881, 0.999866, 0.997153, 0.014053, 0.998049,
0.977727, 0.971233, 0.995309, 0.0010376, 1, 0.989373, 0.989161,
0.91637, 1, 0.99977, 0.960816, 0.998025, 1, 0.998852, 0.960849,
0.957963, 0.998733, 0.999426, 0.876182, 0.998509, 0.988527,
0.998265, 0.943673]
result=stats.discretize(input_values)
self.assertEqual(expected_result,result)
