def testIteratorFunc2(self):
dataset = MovieLensDataset()
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
iterStartTimeStamp = time.mktime(datetime(2005,1,1).timetuple())
dataset = MovieLensDataset(iterStartTimeStamp=iterStartTimeStamp)
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 testIteratorFunc(self):
iterStartTimeStamp = time.mktime(datetime(2009,01,25).timetuple())
dataset = MovieLensDataset(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
