def test_ManhattanMetricWith1Point(self):
point1 = DataPoint(value=[0.1, 0.2, 0.3])
resultExpected = 0
resultReceived = calculateManhattan([point1])
self.assertEqual(resultReceived, resultExpected)
def test_ManhattanMetricWith2Points(self):
point1 = DataPoint(value=[0.1, 0.2, 0.3])
point2 = DataPoint(value=[0.2, 0.3, 0.4])
resultExpected = 0.3
resultReceived = calculateManhattan([point1, point2])
self.assertEqual(resultReceived, resultExpected)
def test_ChebyshevMetricWith1Point(self):
point1 = DataPoint(value=[0.9, 0.8, 0.7])
resultExpected = 0
resultReceived = calculateChebyshev([point1])
self.assertEqual(resultReceived, resultExpected)
def test_ChebyshevMetricWith2Points(self):
point1 = DataPoint(value=[0.9, 0.8, 0.7])
point2 = DataPoint(value=[0.0, 0.1, 0.2])
resultExpected = 0.9
resultReceived = calculateChebyshev([point1, point2])
self.assertEqual(resultReceived, resultExpected)
def removeObservation(self, observation):
point = DataPoint(observation)
if observation in self._observations:
self._observations.remove(observation)
def assignOldCenter(self, center):
self.oldCenter = center
self._oldCenter = DataPoint(self.oldCenter)
def clearstaticOldCenter(self):
self.oldCenter = DataPoint("")
class Cluster:
oldCenter = DataPoint("")
def __init__(self, id, center):
self._id = id
self._center = center
self._oldCenter = center
self._observations = []
def __repr__(self):
return repr(self.value)
def __getitem__(self, item):
if isinstance(item, (int, slice)):
return self.__class__(self.value[item])
return [self.value[i] for i in item]
def appendObservation(self, observation):
point = DataPoint(observation)
if not point in self._observations:
self._observations.append(point)
def updateClusterCenterByMean(self):
dimension = 0
dimensionsAmount = len(self._center)
while dimension < dimensionsAmount:
sumOfDimension = 0
for observation in self._observations:
sumOfDimension += observation.getValue(dimension)
observationsAmount = self.getObservationsAmount()
mean = round(sumOfDimension / observationsAmount, 5)
self._center[dimension] = mean
dimension += 1
self.clearstaticOldCenter()
def clearstaticOldCenter(self):
self.oldCenter = DataPoint("")
def assignOldCenter(self, center):
self.oldCenter = center
self._oldCenter = DataPoint(self.oldCenter)
def checkIfClusterChanged(self):
if self._center == self._oldCenter:
return False
return True
def getCenter(self):
return self._center
def removeObservation(self, observation):
point = DataPoint(observation)
if observation in self._observations:
self._observations.remove(observation)
def getObservations(self):
return self._observations
def clearObservations(self):
self._observations.clear()
def getObservationsAmount(self):
return len(self._observations)
def appendObservation(self, observation):
point = DataPoint(observation)
if not point in self._observations:
self._observations.append(point)