def generateRandomCentroid(self,pointName):
avgDist= self.hiRanges[self.TOTAL_DIST] - self.loRanges[self.TOTAL_DIST]
if avgDist != 0:
avgDist = random.randrange(int(self.loRanges[self.TOTAL_DIST]),int(self.hiRanges[self.TOTAL_DIST]))
avgHR = self.hiRanges[self.AVG_HR] - self.loRanges[self.AVG_HR]
if avgHR != 0:
avgHR = random.randrange(int(self.loRanges[self.AVG_HR]),int(self.hiRanges[self.AVG_HR]))
avgGained = self.hiRanges[self.NET_GAINED] - self.loRanges[self.NET_GAINED]
if avgGained != 0:
avgGained = random.randrange(int(self.loRanges[self.NET_GAINED]),int(self.hiRanges[self.NET_GAINED]))
avgLost = self.hiRanges[self.NET_LOST] - self.loRanges[self.NET_LOST]
if avgLost != 0:
avgLost = random.randrange(int(self.loRanges[self.NET_LOST]),int(self.hiRanges[self.NET_LOST]))
avgTime = self.hiRanges[self.TIME] - self.loRanges[self.TIME]
if avgTime != 0:
avgTime = random.randrange(int(self.loRanges[self.TIME]),int(self.hiRanges[self.TIME]))
return GarminLap.asLap(pointName,
random.randrange(int(self.loRanges[self.TIME]),int(self.hiRanges[self.TIME])),
random.randrange(int(self.loRanges[self.TOTAL_DIST]),int(self.hiRanges[self.TOTAL_DIST])),
random.randrange(int(self.loRanges[self.AVG_HR]),int(self.hiRanges[self.AVG_HR])),
random.randrange(int(self.loRanges[self.NET_GAINED]),int(self.hiRanges[self.NET_GAINED])),
random.randrange(int(self.loRanges[self.NET_LOST]),int(self.hiRanges[self.NET_LOST]))
)
def createMeanCentroid(self, clusterName, centroids):
summaryTotalTime = 0.0
summaryTotalDistance = 0.0
summaryAvgHR = 0.0
summaryNetGained = 0.0
summaryNetLost = 0.0
for data in centroids:
summaryTotalTime += data.totalTime
summaryTotalDistance += data.totalDistance
summaryAvgHR += data.avgHR
summaryNetGained += data.netGained
summaryNetLost += data.netLost
divisor = len(centroids)
avgTime = summaryTotalTime / divisor
avgDist = summaryTotalDistance / divisor
avgHR = summaryAvgHR / divisor
avgNetGained = summaryNetGained / divisor
avgNetLost = summaryNetLost / divisor
return GarminLap.asLap(clusterName, avgTime, avgDist, avgHR,
avgNetGained, avgNetLost)
def createMeanCentroid(self,clusterName,centroids):
summaryTotalTime = 0.0
summaryTotalDistance = 0.0
summaryAvgHR = 0.0
summaryNetGained = 0.0
summaryNetLost = 0.0
for data in centroids:
summaryTotalTime += data.totalTime
summaryTotalDistance += data.totalDistance
summaryAvgHR += data.avgHR
summaryNetGained += data.netGained
summaryNetLost += data.netLost
divisor = len(centroids)
avgTime = summaryTotalTime/divisor
avgDist = summaryTotalDistance/divisor
avgHR = summaryAvgHR/divisor
avgNetGained = summaryNetGained/divisor
avgNetLost = summaryNetLost/divisor
return GarminLap.asLap(clusterName,avgTime,avgDist,avgHR, avgNetGained,avgNetLost)
def testNewGarminLapFromAsGarminLap(self):
lap1 = GarminLap.asLap(1, 589, 300, 140, 100, 200)
self.assertFalse(None == lap1)
self.assertEquals(1, lap1.lap)
self.assertEquals(589, lap1.totalTime)
self.assertEquals(ClusterData.metersToFeet(300), lap1.totalDistance)
self.assertEquals(ClusterData.metersToFeet(100), lap1.netGained)
self.assertEquals(ClusterData.metersToFeet(200), lap1.netLost)
def testNewGarminLapFromAsGarminLap(self):
lap1 = GarminLap.asLap(1,589,300,140, 100,200)
self.assertFalse(None == lap1)
self.assertEquals(1,lap1.lap)
self.assertEquals(589,lap1.totalTime)
self.assertEquals(ClusterData.metersToFeet(300),lap1.totalDistance)
self.assertEquals(ClusterData.metersToFeet(100),lap1.netGained)
self.assertEquals(ClusterData.metersToFeet(200),lap1.netLost)
def testInErrorRange(self):
parser = MileSplitParser()
parser.loadData('../resources/test.csv')
gdf = GarminDataFilter(parser)
self.assertNotEqual(None,gdf)
lap1 = GarminLap.asLap(1,600,100,120,12,30)
lap2 = GarminLap.asLap(2,400,300,150,123,300)
self.assertFalse(gdf.inErrorRange(lap1, lap2))
lap1 = GarminLap.asLap(1,600,100,120,12,30)
lap2 = GarminLap.asLap(2,600,100,120,12,30)
self.assertTrue(gdf.inErrorRange(lap1, lap2))
def testNewLapFromTokens(self):
string = '1,1,,2011-01-05T15:00:46Z,576.5800000,1609.3439941,3.3762498,179,113,132,Active,,Distance,"",'
tokens = string.split(',')
lap = GarminLap(tokens)
self.assertFalse(None == lap)
self.assertEquals('2011-01-05T15:00:46Z', lap.lap)
self.assertEquals(1, lap.id)
self.assertEquals(1, lap.activityId)
self.assertEquals(ClusterData.metersToFeet(1609.3439941),
lap.totalDistance)
self.assertEquals(576.58, lap.totalTime)
def generateRandomCentroid(self, pointName):
avgDist = self.hiRanges[self.TOTAL_DIST] - self.loRanges[
self.TOTAL_DIST]
if avgDist != 0:
avgDist = random.randrange(int(self.loRanges[self.TOTAL_DIST]),
int(self.hiRanges[self.TOTAL_DIST]))
avgHR = self.hiRanges[self.AVG_HR] - self.loRanges[self.AVG_HR]
if avgHR != 0:
avgHR = random.randrange(int(self.loRanges[self.AVG_HR]),
int(self.hiRanges[self.AVG_HR]))
avgGained = self.hiRanges[self.NET_GAINED] - self.loRanges[
self.NET_GAINED]
if avgGained != 0:
avgGained = random.randrange(int(self.loRanges[self.NET_GAINED]),
int(self.hiRanges[self.NET_GAINED]))
avgLost = self.hiRanges[self.NET_LOST] - self.loRanges[self.NET_LOST]
if avgLost != 0:
avgLost = random.randrange(int(self.loRanges[self.NET_LOST]),
int(self.hiRanges[self.NET_LOST]))
avgTime = self.hiRanges[self.TIME] - self.loRanges[self.TIME]
if avgTime != 0:
avgTime = random.randrange(int(self.loRanges[self.TIME]),
int(self.hiRanges[self.TIME]))
return GarminLap.asLap(
pointName,
random.randrange(int(self.loRanges[self.TIME]),
int(self.hiRanges[self.TIME])),
random.randrange(int(self.loRanges[self.TOTAL_DIST]),
int(self.hiRanges[self.TOTAL_DIST])),
random.randrange(int(self.loRanges[self.AVG_HR]),
int(self.hiRanges[self.AVG_HR])),
random.randrange(int(self.loRanges[self.NET_GAINED]),
int(self.hiRanges[self.NET_GAINED])),
random.randrange(int(self.loRanges[self.NET_LOST]),
int(self.hiRanges[self.NET_LOST])))