def testPrecisionFromIndLists(self):
predList = [4, 2, 10]
testList = [4, 2]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList), 2.0/3)
testList = [4, 2, 10]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList), 1)
predList = [10, 2, 4]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList), 1)
testList = [1, 9, 11]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList), 0)
predList = [1, 2, 3, 4, 5]
testList = [1, 9, 11]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList), 1.0/5)
def testPrecisionFromIndLists(self):
predList = [4, 2, 10]
testList = [4, 2]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList),
2.0 / 3)
testList = [4, 2, 10]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList),
1)
predList = [10, 2, 4]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList),
1)
testList = [1, 9, 11]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList),
0)
predList = [1, 2, 3, 4, 5]
testList = [1, 9, 11]
self.assertEquals(Evaluator.precisionFromIndLists(testList, predList),
1.0 / 5)
outputLists = graphRanker.vertexRankings(graph, relevantAuthorsInds)
itemList = RankAggregator.generateItemList(outputLists)
methodNames = graphRanker.getNames()
if runLSI:
outputFilename = dataset.getOutputFieldDir(field) + "outputListsLSI.npz"
else:
outputFilename = dataset.getOutputFieldDir(field) + "outputListsLDA.npz"
Util.savePickle([outputLists, trainExpertMatchesInds, testExpertMatchesInds], outputFilename, debug=True)
numMethods = len(outputLists)
precisions = numpy.zeros((len(ns), numMethods))
averagePrecisions = numpy.zeros(numMethods)
for i, n in enumerate(ns):
for j in range(len(outputLists)):
precisions[i, j] = Evaluator.precisionFromIndLists(testExpertMatchesInds, outputLists[j][0:n])
for j in range(len(outputLists)):
averagePrecisions[j] = Evaluator.averagePrecisionFromLists(testExpertMatchesInds, outputLists[j][0:averagePrecisionN], averagePrecisionN)
precisions2 = numpy.c_[numpy.array(ns), precisions]
logging.debug(Latex.listToRow(methodNames))
logging.debug(Latex.array2DToRows(precisions2))
logging.debug(Latex.array1DToRow(averagePrecisions))
logging.debug("All done!")
