def findCentroids(nrOfClusters, data):
# TODO write algorithm setting initial location of centroids
print "-->IN findCentroids"
centroidsList = Dataset([0 for i in range(0, nrOFCluster)])
jump = (int((data.getSize()+1)/nrOfClusters) )
for i in range(0,nrOfClusters):
centroidsList.getListOfVectors()[i]= data.getListOfVectors()[jump * i]
print "\tOUT Found centroids= ", centroidsList.getListOfVectors(), "\n"
return centroidsList
def calculateNewCentroids(nrOfClusters, data, assignment, centroids):
print "-->IN calculateNewCentroids"
print "\tcentroids= ", centroids.getListOfVectors()
# create DataSet object for centroids
newCentroidsDataset = Dataset([Vector() for i in range(0, nrOfClusters)])
# init with Zeros all Vectors
for t in range(0, newCentroidsDataset.getListOfVectors().__len__()):
for q in range(0, data.getListOfVectors()[0].__len__()):
newCentroidsDataset.getListOfVectors()[t].append(0)
# arithmetic mean
for i in range(0, data.getListOfVectors().__len__()):
for x in range(0, data.getListOfVectors()[0].__len__()):
newCentroidsDataset.getListOfVectors()[assignment[i]][x] += data.getListOfVectors()[i][x]
for q in range(0, nrOfClusters):
for x in range(0, data.getListOfVectors()[0].__len__()):
if assignment.count(q) != 0:
newCentroidsDataset.getListOfVectors()[q][x] = newCentroidsDataset.getListOfVectors()[q][x] / assignment.count(q)
else:
newCentroidsDataset.getListOfVectors()[q][x] = 0
print "\t\nOUT list of new centroids= ", newCentroidsDataset.getListOfVectors(), "\n"
return newCentroidsDataset
def findCentroids(nrOfClusters, data):
# TODO write algo finding location of centroids
print "-->IN findCentroids"
print "\tnrOfClusters= ", nrOfClusters, "\n\tdata= ", data.getListOfVectors()
centroidsList = Dataset([Vector() for i in range(0, nrOFCluster)])
# print "\tcentroidsList= " , centroidsList.getListOfVectors()
jump = (int((data.getSize()+1)/nrOfClusters) )
# print "\tjump between indexes= ", jump
for i in range(0,nrOfClusters):
# print "\t\tposition=", i, " Vector= ",data.getListOfVectors()[jump * i]
centroidsList.getListOfVectors()[i]= data.getListOfVectors()[jump * i]
print "\tOUT Founded centroids= ", centroidsList.getListOfVectors(), "\n"
return centroidsList
def reconcile(data, centroids, nrOFCluster, assignment, Dlist, whichCluster):
print "-->IN reconcile"
newData = Dataset([])
newAssignment = []
newCentroids = Dataset([])
newDList= [[],[]]
for x in range(0, data.getListOfVectors().__len__()):
if assignment[x] == whichCluster:
newData.getListOfVectors().append(data.getListOfVectors()[x])
newAssignment.append(assignment[x])
if newCentroids.getListOfVectors().__len__() == 0:
newlist = [field for field in assignment]
newlist.sort()
counterTmp = [newlist[0]]
for w in range(0, newlist.__len__()-1):
if newlist == whichCluster:
break
if newlist[w] != newlist[w+1]:
counterTmp.append(newlist[w+1])
position = counterTmp.index(whichCluster)
print newDList
print Dlist
print assignment[x]
newCentroids.getListOfVectors().append(centroids.getListOfVectors()[position])
newDList[0].append(Dlist[0][position])
newDList[1].append(Dlist[1][position])
print "\t ", x
# newNrOFCluster = nrOFCluster - 1
print "\nRECONCILIE:"
print "## Data= ", newData.getListOfVectors()
print "## Centroids= " , newCentroids.getListOfVectors()
# print "## nrOFCluster" , newNrOFCluster
print "## assignment=", newAssignment
print "## Dlist=", newDList
print "## Q= ", q
print "which cluster=", whichCluster
print "\n"
return [newData, newCentroids, newAssignment, newDList]
def calculateNewCentroids(nrOfClusters, data, assignment, centroids):
print "-->IN calculateNewCentroids"
print "\tnrOfClusters= ", nrOfClusters, "\n\tdata= ", data.getListOfVectors(), "\n\tassignment=", assignment, "\n\tcentroids= ", centroids.getListOfVectors()
# create DataSet object for centroids
newCentroidsDataset = Dataset([Vector() for i in range(0, nrOfClusters)])
# init with Zeros all Vectors
for t in range(0, newCentroidsDataset.getListOfVectors().__len__()):
for q in range(0, data.getListOfVectors()[0].__len__()):
newCentroidsDataset.getListOfVectors()[t].append(0)
# arithmetic mean
for i in range(0, data.getListOfVectors().__len__()):
for x in range(0, data.getListOfVectors()[0].__len__()):
# print "list of new centroids= ", listOfNewCentroids
newCentroidsDataset.getListOfVectors()[assignment[i]][x] += data.getListOfVectors()[i][x]
# print "list of new centroids after loop= ", listOfNewCentroids
for q in range(0, nrOfClusters):
for x in range(0, data.getListOfVectors()[0].__len__()):
newCentroidsDataset.getListOfVectors()[q][x] = newCentroidsDataset.getListOfVectors()[q][x] / data.getListOfVectors()[0].__len__()
print "\tOUT list of new centroids= ", newCentroidsDataset.getListOfVectors(), "\n"
return newCentroidsDataset
def kMeans(data, nrOFCluster, nrOfGivenIterations):
centroids = findCentroids(nrOFCluster, data)
listD = [[0 for i in range(0, nrOFCluster)], [0 for i in range(0, nrOFCluster)]]
loopCounter = 0
givenError = 0.5
while loopCounter < nrOfGivenIterations:
assignment = assignToCluster(nrOFCluster, data, centroids)
# seeking for empty centroids
empty = []
for e in range(0, nrOFCluster):
if assignment.count(e) == 0:
empty.append(e)
# print "empty ", empty, "\n\n"
#collecting empty centroids
emptyCentroid = Dataset([])
emptyListD = [[], []]
for q in range(0, empty.__len__()):
emptyCentroid.getListOfVectors().append(centroids.getListOfVectors()[empty[q]])
emptyListD[0].append(listD[0][empty[q]])
emptyListD[1].append(listD[1][empty[q]])
#calculation
D = meanQuantizationError(nrOFCluster, data, assignment, centroids)
centroids = calculateNewCentroids(nrOFCluster, data, assignment, centroids)
numberOfExistingCluster = []
if (loopCounter == 0):
listD[0] = D
else:
if loopCounter == 1:
listD[1] = D
else:
listD[0] = listD[1]
listD[1] = D
# check if all cluster have at least one Vector assigned
# otherwise del from cluster, decrement nrOFCluster
centroidsTmp = Dataset([])
listDTmp= [[],[]]
for z in range(0, centroids.getListOfVectors().__len__()):
ctr = 0
for q in range(0, centroids.getListOfVectors()[0].__len__()):
if centroids.getListOfVectors()[z][q] != 0:
ctr += 1
if ctr == 0:
centroidsTmp.getListOfVectors().append(centroids.getListOfVectors()[z])
listDTmp[0].append(listD[0][z])
listDTmp[1].append(listD[1][z])
else:
numberOfExistingCluster.append(z)
#remove empty data from processing
for q in range(0,centroidsTmp.getListOfVectors().__len__()):
centroids.getListOfVectors().remove(centroidsTmp.getListOfVectors()[q])
listD[0].remove(listDTmp[0][q])
listD[1].remove(listDTmp[1][q])
nrOFCluster -= 1
#check if given error tha calculated
QoS = 0
for q in range(0, numberOfExistingCluster.__len__()):
if countDiff(listD[0][q], listD[1][q]) < givenError:
QoS += 1
if QoS == centroids.getListOfVectors().__len__():
print "\n!!!!!!!!!!KONIEC!!!!!!!!!!"
break
#restore empty centroids
centroids.getListOfVectors().extend(emptyCentroid.getListOfVectors())
nrOFCluster += emptyCentroid.getListOfVectors().__len__()
listD[1].extend(emptyListD[0])
listD[0].extend(emptyListD[1])
print "@@ centr= " , centroids.getListOfVectors()
print "\n*******END OF LOOP " ,loopCounter, "\n"
loopCounter += 1
for i in range(len(assignment)):
print assignment[i], getAllFiles('../input')[i]
if QoS == centroids.getListOfVectors().__len__():
print "\n!!!!!!!!!!KONIEC!!!!!!!!!!"
break
#restore empty centroids
centroids.getListOfVectors().extend(emptyCentroid.getListOfVectors())
nrOFCluster += emptyCentroid.getListOfVectors().__len__()
listD[1].extend(emptyListD[0])
listD[0].extend(emptyListD[1])
print "@@ centr= " , centroids.getListOfVectors()
print "\n*******END OF LOOP " ,loopCounter, "\n"
loopCounter += 1
for i in range(len(assignment)):
print assignment[i], getAllFiles('../input')[i]
nrOFCluster = 3
nrOfGivenIterations = 3
data = Dataset(prepareInput('../input', 10, '/home/kchrusci/Workspace/repo/k-means/projektpython/ForbiddenWords.txt'))
print "data = ", data.getListOfVectors()
kMeans(data,nrOFCluster,nrOfGivenIterations)
print(getAllFiles('/home/koper/PycharmProjects/First/Samples'))
def kMeans(data, nrOFCluster, nrOfGivenIterations):
centroids = findCentroids(nrOFCluster, data)
listD = [[0 for i in range(0, nrOFCluster)], [0 for i in range(0, nrOFCluster)]]
loopCounter = 0
givenError = 0.5
while loopCounter < nrOfGivenIterations:
assignment = assignToCluster(nrOFCluster, data, centroids)
D = meanQuantizationError(nrOFCluster, data, assignment, centroids)
centroids = calculateNewCentroids(nrOFCluster, data, assignment, centroids)
numberOfExistingCluster = []
if (loopCounter == 0):
listD[0] = D
print "@ListD in loop 0= " , listD
else:
if loopCounter == 1:
listD[1] = D
else:
listD[0] = listD[1]
listD[1] = D
print "@nrOFCluster before loop=", nrOFCluster, "listD= ", listD
# check if all cluster have at least one Vector assigned
# otherwise del from cluster, decrement nrOFCluster
centroidsTmp = Dataset([])
listDTmp= [[],[]]
for z in range(0, centroids.getListOfVectors().__len__()):
ctr = 0
for q in range(0, centroids.getListOfVectors()[0].__len__()):
if centroids.getListOfVectors()[z][q] != 0:
ctr += 1
if ctr == 0:
centroidsTmp.getListOfVectors().append(centroids.getListOfVectors()[z])
listDTmp[0].append(listD[0][z])
listDTmp[1].append(listD[1][z])
else:
numberOfExistingCluster.append(z)
# print z
# print assignment[z]
print "listDTmp=" , listDTmp
print "centroidsTmp= ", centroidsTmp.getListOfVectors()
print "~\n\n\nnumberOfExistingCluster= " ,numberOfExistingCluster
for q in range(0,centroidsTmp.getListOfVectors().__len__()):
centroids.getListOfVectors().remove(centroidsTmp.getListOfVectors()[q])
listD[0].remove(listDTmp[0][q])
listD[1].remove(listDTmp[1][q])
nrOFCluster -= 1
print "\n\nExtracted valid data "
print "#Data= ", data.getListOfVectors()
print "#centroids= ", centroids.getListOfVectors()
print "#nrOFCluster" , nrOFCluster
print "#assignment=", assignment
print "#listD= ", listD
print "\n\n"
newData = Dataset([])
newAssignment = []
newCentroids = Dataset([])
newNrOfCluster = -1
newDlist = [[],[]]
datVecList = newData.getListOfVectors()
centVecList = newCentroids.getListOfVectors()
nrOFClustertemp = nrOFCluster
for q in range(0, numberOfExistingCluster.__len__()):
print "@@ ListD in loop= " , listD
print "@@ Data= ", data.getListOfVectors()
print "@@ centr= " , centroids.getListOfVectors()
print "@@ nrOFCluster" , nrOFCluster
print "@@ assignment=", assignment
print "@@ Q in RECONCILIATION LOOP= ", q
print "\n"
if countDiff(listD[0][q], listD[1][q]) < givenError:
# print "nrOFCluster= " , nrOFCluster
datatemp, centroidstemp, assignmenttemp, listDtemp = reconcile(data,centroids,nrOFCluster, assignment, listD, numberOfExistingCluster[q])
datVecList += datatemp.getListOfVectors()
centVecList += centroidstemp.getListOfVectors()
nrOFClustertemp -= 1
newAssignment += assignmenttemp
newDlist[0] += listDtemp[0]
newDlist[1] += listDtemp[1]
print " #########x" , datVecList
print " #########x" , centVecList
print " #########x" , newNrOfCluster
print " #########x" , newAssignment
print " #########x" , newDlist
# print "\nData after reconc:"
# print "newData=", newData.getListOfVectors()
# print "newCentroids", newCentroids.getListOfVectors()
# print "nrOFCluster" , nrOFClustertemp
# print "newAssignment" ,newAssignment
# print "\n"
for k in range(0, newData.getListOfVectors().__len__()):
data.getListOfVectors().remove(newData.getListOfVectors()[k])
assignment.remove(newAssignment[k])
print "\nData after DELETION="
print "newData=", data.getListOfVectors()
print "assignment " , assignment
for q in range(0,newCentroids.getListOfVectors().__len__()):
centroids.getListOfVectors().remove(newCentroids.getListOfVectors()[q])
listD[0].remove(newDlist[0][q])
listD[1].remove(newDlist[1][q])
print "newCentroids", centroids.getListOfVectors()
print "Dlist ", listD
# centroids = newCentroids
# listD = newDlist
nrOFCluster = nrOFClustertemp
# data = newData
# assignment = newAssignment
print "*******Loop counter= " ,loopCounter
loopCounter += 1
if (data.getListOfVectors().__len__() == 0 ):
break
