def run():
dataset = NetflixDataset(maxIter=30)
trainIterator = dataset.getTrainIteratorFunc()
for trainX in trainIterator:
print(trainX.shape)
def testIteratorFunc2(self):
dataset = NetflixDataset()
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 profileSvd3(self):
dataset = NetflixDataset()
iterator = dataset.getTrainIteratorFunc()
X = iterator.next()
#L = LinOperatorUtils.parallelSparseOp(X)
L = GeneralLinearOperator.asLinearOperator(X)
k = 50
U, s, V = RandomisedSVD.svd(L, k)
print(s)
print("All done")
def profileSvd3(self):
dataset = NetflixDataset()
iterator = dataset.getTrainIteratorFunc()
X = iterator.next()
#L = LinOperatorUtils.parallelSparseOp(X)
L = GeneralLinearOperator.asLinearOperator(X)
k = 50
U, s, V = RandomisedSVD.svd(L, k)
print(s)
print("All done")
def testIteratorFunc(self):
iterStartTimeStamp = time.mktime(datetime(2005,12,31).timetuple())
dataset = NetflixDataset(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
