def test_dissimilarity_fake(self):
""" Compare dissimalirity values computed by hands """
city = fake_city()
d = mb.dissimilarity(city)
d_answer = {1: {1:0.0, 2:0.5205882352941176, 3:0.411764705882353},
2: {1:0.5205882352941176, 2:0.0, 3:0.4411764705882353},
3: {1:0.411764705882353, 2:0.4411764705882353, 3:0.0}}
for c0 in d:
for c1 in d[c0]:
assert_equal(d[c0][c1], d_answer[c0][c1])
def test_dissimilarity_segregated_city(self):
""" 1 in the segregated city """
city = segregated_city()
d = mb.dissimilarity(city)
d_answer = {1:{1:0, 2:1, 3:1},
2:{1:1, 2:0, 3:1},
3:{1:1, 2:1, 3:0}}
for c0 in d:
for c1 in d[c0]:
assert_equal(d[c0][c1], d_answer[c0][c1])
def test_dissimilarity_uniform_city(self):
""" Null values in the uniform city """
city = uniform_city()
d = mb.dissimilarity(city)
d_answer = {1:{1:0, 2:0, 3:0},
2:{1:0, 2:0, 3:0},
3:{1:0, 2:0, 3:0}}
for c0 in d:
for c1 in d[c0]:
assert_equal(d[c0][c1], d_answer[c0][c1])
def test_dissimilarity_uniform_city(self):
""" Null values in the uniform city """
city = uniform_city()
d = mb.dissimilarity(city)
d_answer = {
1: {
1: 0,
2: 0,
3: 0
},
2: {
1: 0,
2: 0,
3: 0
},
3: {
1: 0,
2: 0,
3: 0
}
}
for c0 in d:
for c1 in d[c0]:
assert_equal(d[c0][c1], d_answer[c0][c1])
def test_dissimilarity_fake(self):
""" Compare dissimalirity values computed by hands """
city = fake_city()
d = mb.dissimilarity(city)
d_answer = {
1: {
1: 0.0,
2: 0.5205882352941176,
3: 0.411764705882353
},
2: {
1: 0.5205882352941176,
2: 0.0,
3: 0.4411764705882353
},
3: {
1: 0.411764705882353,
2: 0.4411764705882353,
3: 0.0
}
}
for c0 in d:
for c1 in d[c0]:
assert_equal(d[c0][c1], d_answer[c0][c1])
def test_dissimilarity_segregated_city(self):
""" 1 in the segregated city """
city = segregated_city()
d = mb.dissimilarity(city)
d_answer = {
1: {
1: 0,
2: 1,
3: 1
},
2: {
1: 1,
2: 0,
3: 1
},
3: {
1: 1,
2: 1,
3: 0
}
}
for c0 in d:
for c1 in d[c0]:
assert_equal(d[c0][c1], d_answer[c0][c1])