def test_measures_with_empty_rel_and_ret(self):
sheet1 = EvaluationSheet(Scoresheet(), [], [])
sheet2 = EvaluationSheet(Scoresheet(), [], 10)
sheet3 = EvaluationSheet(Scoresheet(), [])
for sheet in (sheet1, sheet2, sheet3):
assert_raises(UndefinedError, sheet.precision)
assert_raises(UndefinedError, sheet.recall)
assert_raises(UndefinedError, sheet.f_score)
assert_raises(UndefinedError, sheet.fallout)
assert_raises(UndefinedError, sheet.miss)
assert_raises(UndefinedError, sheet.accuracy)
assert_raises(UndefinedError, sheet.generality)
def test_weighted(self):
known = {(0, 1): 1, (0, 2): 3, (1, 2): 1, (1, 3): 2, (2, 4): 1,
(0, 3): 2 / 3, (0, 4): 0.75, (1, 4): 0.5, (2, 3): 2 / 3,
(3, 4): 0.4}
known = Scoresheet(known)
graph_distance = GraphDistance(self.G).predict()
assert_dict_almost_equal(graph_distance, known)
def test_measures_with_empty_rel_and_ret(self):
sheet1 = EvaluationSheet(Scoresheet(), [], [])
sheet2 = EvaluationSheet(Scoresheet(), [], 10)
sheet3 = EvaluationSheet(Scoresheet(), [])
for sheet in (sheet1, sheet2, sheet3):
for method in [
"precision",
"recall",
"f_score",
"fallout",
"miss",
"accuracy",
"generality",
]:
with pytest.raises(UndefinedError):
getattr(sheet, method)()
def test_cosine(self):
known = {
(1, 5): 10 / sqrt(104),
(2, 3): 7 / sqrt(150),
(1, 4): 7 / sqrt(130),
(4, 5): 2 / sqrt(20),
}
found = nbr.Cosine(self.G).predict(weight="weight")
assert found == pytest.approx(Scoresheet(known))
def test_adamic_adar(self):
known = {
(1, 5): 10 / log(30),
(1, 4): 2 / log(5) + 5 / log(30),
(2, 3): 2 / log(5) + 5 / log(26),
(4, 5): 2 / log(30),
}
found = nbr.AdamicAdar(self.G).predict(weight="weight")
assert found == pytest.approx(Scoresheet(known))
def test_pearson(self):
known = {
(1, 5): 0.61237243,
(2, 3): 2 / 3,
(1, 4): 1,
(4, 5): 0.61237243
}
found = Pearson(self.G).predict()
assert_dict_almost_equal(found, Scoresheet(known))
def test_nmeasure(self):
known = {
(1, 5): sqrt(2 / 5),
(2, 3): sqrt(8 / 13),
(1, 4): 1,
(4, 5): sqrt(2 / 5)
}
found = NMeasure(self.G).predict()
assert_dict_almost_equal(found, Scoresheet(known))
def test_cosine(self):
known = {
(1, 5): 1 / sqrt(2),
(2, 3): 2 / sqrt(6),
(1, 4): 1,
(4, 5): 1 / sqrt(2)
}
found = Cosine(self.G).predict()
assert_dict_almost_equal(found, Scoresheet(known))
def test_resource_allocation(self):
known = {
(1, 5): 1 / 3,
(2, 3): 77 / 130,
(1, 4): 17 / 30,
(4, 5): 1 / 15
}
found = ResourceAllocation(self.G).predict(weight='weight')
assert_dict_almost_equal(found, Scoresheet(known))
def test_adamic_adar(self):
known = {
(1, 5): 1 / log(3),
(2, 3): 2 / log(2),
(1, 4): 1 / log(2) + 1 / log(3),
(4, 5): 1 / log(3)
}
found = AdamicAdar(self.G).predict()
assert_dict_almost_equal(found, Scoresheet(known))
def test_pearson(self):
known = {
(1, 5): 0.9798502,
(2, 3): 0.2965401,
(1, 4): 0.4383540,
(4, 5): 0.25
}
found = Pearson(self.G).predict(weight='weight')
assert_dict_almost_equal(found, Scoresheet(known))
def test_nmeasure(self):
known = {
(1, 5): sqrt(50 / 173),
(2, 3): sqrt(98 / 925),
(1, 4): sqrt(98 / 701),
(4, 5): sqrt(8 / 41)
}
found = NMeasure(self.G).predict(weight='weight')
assert_dict_almost_equal(found, Scoresheet(known))
def test_adamic_adar(self):
known = {
(1, 5): 1 / log(3),
(2, 3): 2 / log(2),
(1, 4): 1 / log(2) + 1 / log(3),
(4, 5): 1 / log(3),
}
found = nbr.AdamicAdar(self.G).predict()
assert found == pytest.approx(Scoresheet(known))
def test_nmeasure(self):
known = {
(1, 5): sqrt(50 / 173),
(2, 3): sqrt(98 / 925),
(1, 4): sqrt(98 / 701),
(4, 5): sqrt(8 / 41),
}
found = nbr.NMeasure(self.G).predict(weight="weight")
assert found == pytest.approx(Scoresheet(known))
def test_adamic_adar(self):
known = {
(1, 5): 10 / log(30),
(1, 4): 2 / log(5) + 5 / log(30),
(2, 3): 2 / log(5) + 5 / log(26),
(4, 5): 2 / log(30)
}
found = AdamicAdar(self.G).predict(weight='weight')
assert_dict_almost_equal(found, Scoresheet(known))
def test_pearson(self):
known = {
(1, 5): 0.61237243,
(2, 3): 2 / 3,
(1, 4): 1,
(4, 5): 0.61237243
}
found = nbr.Pearson(self.G).predict()
assert found == pytest.approx(Scoresheet(known))
def test_cosine(self):
known = {
(1, 5): 1 / sqrt(2),
(2, 3): 2 / sqrt(6),
(1, 4): 1,
(4, 5): 1 / sqrt(2),
}
found = nbr.Cosine(self.G).predict()
assert found == pytest.approx(Scoresheet(known))
def test_nmeasure(self):
known = {
(1, 5): sqrt(2 / 5),
(2, 3): sqrt(8 / 13),
(1, 4): 1,
(4, 5): sqrt(2 / 5),
}
found = nbr.NMeasure(self.G).predict()
assert found == pytest.approx(Scoresheet(known))
def test_resource_allocation(self):
known = {
(1, 5): 1 / 3,
(2, 3): 77 / 130,
(1, 4): 17 / 30,
(4, 5): 1 / 15
}
found = nbr.ResourceAllocation(self.G).predict(weight="weight")
assert found == pytest.approx(Scoresheet(known))
def test_pearson(self):
known = {
(1, 5): 0.9798502,
(2, 3): 0.2965401,
(1, 4): 0.4383540,
(4, 5): 0.25
}
found = nbr.Pearson(self.G).predict(weight="weight")
assert found == pytest.approx(Scoresheet(known))
def test_cosine(self):
known = {
(1, 5): 10 / sqrt(104),
(2, 3): 7 / sqrt(150),
(1, 4): 7 / sqrt(130),
(4, 5): 2 / sqrt(20)
}
found = Cosine(self.G).predict(weight='weight')
assert_dict_almost_equal(found, Scoresheet(known))
def test_weighted_alpha(self):
from math import sqrt
known = {(0, 1): 1, (0, 2): sqrt(3), (1, 2): 1, (1, 3): sqrt(2),
(2, 4): 1, (0, 3): 1 / (1 + 1 / sqrt(2)),
(0, 4): 1 / (1 + 1 / sqrt(3)), (1, 4): 0.5,
(2, 3): 1 / (1 + 1 / sqrt(2)), (3, 4): 1 / (2 + 1 / sqrt(2))}
known = Scoresheet(known)
graph_distance = GraphDistance(self.G).predict(alpha=0.5)
assert_dict_almost_equal(graph_distance, known)
def test_unweighted(self):
known = {(0, 1): 1, (0, 2): 1, (1, 2): 1, (1, 3): 1, (2, 4): 1,
(0, 3): 0.5, (0, 4): 0.5, (1, 4): 0.5, (2, 3): 0.5,
(3, 4): 1 / 3}
known = Scoresheet(known)
graph_distance = GraphDistance(self.G).predict(weight=None)
assert_dict_almost_equal(graph_distance, known)
graph_distance = GraphDistance(self.G).predict(alpha=0)
assert_dict_almost_equal(graph_distance, known)
def test_degree_product(self):
known = {
(1, 2): 130,
(1, 3): 780,
(1, 4): 130,
(1, 5): 104,
(2, 3): 150,
(2, 4): 25,
(2, 5): 20,
(3, 4): 150,
(3, 5): 120,
(4, 5): 20
}
found = DegreeProduct(self.G).predict(weight='weight')
assert_dict_almost_equal(found, Scoresheet(known))
def test_degree_product(self):
known = {
(1, 2): 4,
(1, 3): 6,
(1, 4): 4,
(1, 5): 2,
(2, 3): 6,
(2, 4): 4,
(2, 5): 2,
(3, 4): 6,
(3, 5): 3,
(4, 5): 2
}
found = DegreeProduct(self.G).predict()
assert_dict_almost_equal(found, Scoresheet(known))
def test_degree_product(self):
known = {
(1, 2): 4,
(1, 3): 6,
(1, 4): 4,
(1, 5): 2,
(2, 3): 6,
(2, 4): 4,
(2, 5): 2,
(3, 4): 6,
(3, 5): 3,
(4, 5): 2,
}
found = nbr.DegreeProduct(self.G).predict()
assert found == pytest.approx(Scoresheet(known))
def test_degree_product(self):
known = {
(1, 2): 130,
(1, 3): 780,
(1, 4): 130,
(1, 5): 104,
(2, 3): 150,
(2, 4): 25,
(2, 5): 20,
(3, 4): 150,
(3, 5): 120,
(4, 5): 20,
}
found = nbr.DegreeProduct(self.G).predict(weight="weight")
assert found == pytest.approx(Scoresheet(known))
def test_weighted(self):
known = {
(0, 1): 1,
(0, 2): 3,
(1, 2): 1,
(1, 3): 2,
(2, 4): 1,
(0, 3): 2 / 3,
(0, 4): 0.75,
(1, 4): 0.5,
(2, 3): 2 / 3,
(3, 4): 0.4,
}
known = Scoresheet(known)
graph_distance = GraphDistance(self.G).predict()
assert graph_distance == pytest.approx(known)
def test_unweighted(self):
known = {
(0, 1): 1,
(0, 2): 1,
(1, 2): 1,
(1, 3): 1,
(2, 4): 1,
(0, 3): 0.5,
(0, 4): 0.5,
(1, 4): 0.5,
(2, 3): 0.5,
(3, 4): 1 / 3,
}
known = Scoresheet(known)
graph_distance = GraphDistance(self.G).predict(weight=None)
assert graph_distance == pytest.approx(known)
graph_distance = GraphDistance(self.G).predict(alpha=0)
assert graph_distance == pytest.approx(known)
def test_resource_allocation(self):
known = {(1, 5): 1 / 3, (2, 3): 1, (1, 4): 5 / 6, (4, 5): 1 / 3}
found = nbr.ResourceAllocation(self.G).predict()
assert found == pytest.approx(Scoresheet(known))
