def testGreedyMC2(self):
list1 = [2, 1, 3, 4, 5, 0]
list2 = [3, 2, 5, 0, 4, 1]
list3 = [3, 4, 2, 5, 1, 0]
list4 = [3, 4, 5, 0, 1, 2]
lists = [list1, list2, list3, list4]
itemList = [0, 1, 2, 3, 4, 5]
topQList = [3, 4, 5]
n = 3
outputInds = RankAggregator.greedyMC2(lists, itemList, topQList, n)
self.assertEquals(outputInds, [3])
list1 = [2, 1, 3, 4, 5, 0]
list2 = [3, 2, 5, 4, 0, 1]
list3 = [4, 3, 2, 5, 1, 0]
list4 = [3, 4, 0, 5, 1, 2]
lists = [list1, list2, list3, list4]
outputInds = RankAggregator.greedyMC2(lists, itemList, topQList, n)
newLists = []
for ind in outputInds:
newLists.append(lists[ind])
outputList, scores = RankAggregator.MC2(newLists, itemList)
self.assertEquals(outputList[0:3], [3, 4, 5])
def testBorda(self):
list1 = [5, 4, 3, 2, 1, 0]
list2 = [5, 4, 3, 2, 1, 0]
outList = RankAggregator.borda(list1, list2)
nptst.assert_array_equal(outList, numpy.array([5,4,3,2,1,0]))
list2 = [4, 3, 2, 5, 1, 0]
outList = RankAggregator.borda(list1, list2)
nptst.assert_array_equal(outList, numpy.array([4,5,3,2,1,0]))
def testSpearmanFootrule(self):
list1 = [5, 4, 3, 2, 1, 0]
list2 = [5, 4, 3, 2, 1, 0]
dist = RankAggregator.spearmanFootrule(list1, list2)
self.assertEquals(dist, 0)
list2 = [5, 4, 3, 2, 0, 1]
dist = RankAggregator.spearmanFootrule(list1, list2)
self.assertEquals(dist, 1.0/9)
list2 = [0, 1, 2, 3, 4, 5]
dist = RankAggregator.spearmanFootrule(list1, list2)
self.assertEquals(dist, 1.0)
def testSupervisedMC22(self):
list1 = [2, 1, 3, 4, 5, 0]
list2 = [3, 2, 5, 0, 4, 1]
list3 = [3, 4, 2, 5, 1, 0]
list4 = [5, 0, 3, 4, 1, 2]
lists = [list1, list2, list3, list4]
itemList = [0, 1, 2, 3, 4, 5]
topQList = [5, 4, 3, 2, 1, 0]
outputList, scores = RankAggregator.supervisedMC22(lists, itemList, topQList)
