def testIteratorFunc2(self):
dataset = MendeleyGroupsDataset()
trainIterator = dataset.getTrainIteratorFunc()
testIterator = dataset.getTestIteratorFunc()
for trainX in trainIterator:
testX = testIterator.next()
print(trainX.shape, trainX.nnz, testX.nnz)
self.assertEquals(trainX.shape, testX.shape)
def testIteratorFunc3(self):
#Check to see if repeated calls generate new matrices
dataset = MendeleyGroupsDataset()
trainIterator = dataset.getTrainIteratorFunc()
X = next(trainIterator)
X.data += 1
trainIterator = dataset.getTrainIteratorFunc()
X2 = next(trainIterator)
nptst.assert_array_almost_equal(X.data, X2.data+1)
def testBipartiteToUni(self):
userInds = numpy.array([0, 1, 2, 0, 4])
itemInds = numpy.array([0, 0, 0, 1, 1])
dates = numpy.array([1, 2, 3, 4, 5])
dataset = MendeleyGroupsDataset()
user1Inds, user2Inds, newDates = dataset.bipartiteToUni(userInds, itemInds, dates)
X = scipy.sparse.csc_matrix((newDates, (user1Inds, user2Inds)))
nptst.assert_array_equal(X[0, :].nonzero()[1], numpy.array([1, 2, 4]))
nptst.assert_array_equal(X[1, :].nonzero()[1], numpy.array([0, 2]))
nptst.assert_array_equal(X[2, :].nonzero()[1], numpy.array([0, 1]))
nptst.assert_array_equal(X[3, :].nonzero()[1], numpy.array([]))
nptst.assert_array_equal(X[4, :].nonzero()[1], numpy.array([0]))
def testIteratorFunc(self):
iterStartTimeStamp = time.mktime(datetime(2009,01,25).timetuple())
dataset = MendeleyGroupsDataset(iterStartTimeStamp=iterStartTimeStamp)
#iterator = dataset.getTrainIteratorFunc()
trainIterator = dataset.getTrainIteratorFunc()
testIterator = dataset.getTestIteratorFunc()
trainX = trainIterator.next()
testX = testIterator.next()
self.assertEquals(trainX.shape, testX.shape)
self.assertEquals(trainX.nnz + testX.nnz, dataset.numRatings)
try:
trainIterator.next()
self.fail()
except StopIteration:
pass
