def test_find_top_k_neighbours(self):
similarityDict = {
1: {
2: 0.1,
3: 0.2,
4: 0.5
},
2: {
1: 0.1,
2: 0.6,
3: 0.3
},
3: {
1: 0.2,
2: 0.3,
4: 0.1
},
4: {
1: 0.5,
2: 0.6,
3: 0.1
}
}
userRecom = UserOrientedRecommendation(2, similarityDict)
userRecom.findTopKNeighbours()
assert_equals(
userRecom.getSimilarityDict(), {
1: [(4, 0.5), (3, 0.2)],
2: [(2, 0.6), (3, 0.3)],
3: [(2, 0.3), (1, 0.2)],
4: [(2, 0.6), (1, 0.5)]
})
def test_find_top_k_neighbours_for_user(self):
similarityDict = {1 : { 2 : 0.1, 3 : 0.2, 4 : 0.3, 5 : 0.4},
2 : { 1: 0.1 }}
userRecom = UserOrientedRecommendation(3, similarityDict)
assert_equals(userRecom.findTopKNeighboursForUser(similarityDict[1]),[(5, 0.4), (4, 0.3), (3, 0.2)])
def test_find_top_k_neighbours_for_user(self):
similarityDict = {1: {2: 0.1, 3: 0.2, 4: 0.3, 5: 0.4}, 2: {1: 0.1}}
userRecom = UserOrientedRecommendation(3, similarityDict)
assert_equals(userRecom.findTopKNeighboursForUser(similarityDict[1]),
[(5, 0.4), (4, 0.3), (3, 0.2)])
def test_find_top_k_neighbours(self):
similarityDict = {1 : { 2 : 0.1, 3 : 0.2, 4 : 0.5},
2 : { 1 : 0.1, 2 : 0.6, 3 : 0.3},
3 : { 1 : 0.2, 2 : 0.3, 4 : 0.1},
4 : { 1 : 0.5, 2 : 0.6, 3 : 0.1}}
userRecom = UserOrientedRecommendation(2, similarityDict)
userRecom.findTopKNeighbours()
assert_equals(userRecom.getSimilarityDict(), {1: [(4, 0.5), (3, 0.2)], 2: [(2, 0.6), (3, 0.3)], 3: [(2, 0.3), (1, 0.2)], 4: [(2, 0.6), (1, 0.5)]})
