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)]})