periodEnd = "23:59:59"
compress = 1
splitLen = 10
numTopics = 8
#validDays = [0, 1, 2, 3, 4, 5, 6]
validDays = [0, 2, 4]
tdMatrix = []
minBehaviour = 2
if __name__ == "__main__":
#neighborclusters = ncluster.parse(neighborhoodLocation)
splits = bbdata.makeSplitsSequential(5184, "2008-03-09 00:00:00", \
splitLen = datetime.timedelta(minutes = splitLen),
skip = datetime.timedelta(minutes = 10))
"""
#Create all splits (documents) used for TD matrix
splits = bbdata.makeSplits(25, st, et, valid=validDays, \
splitLen = datetime.timedelta(minutes = splitLen),
sPeriod = "07:50:00", \
ePeriod = "08:00:00")
splits += bbdata.makeSplits(25, st, et, valid=validDays, \
splitLen = datetime.timedelta(minutes = splitLen),
sPeriod = "15:50:00", \
ePeriod = "16:00:00")
splits += bbdata.makeSplits(25, st, et, valid=validDays, \
dVector = []
times = []
lsaVector = []
splitLength = 8
skipLength = 1
numSplits = 50
i = 0
if __name__ == "__main__":
files = os.listdir(modelLocation)
neighborclusters = ncluster.parse(neighborhoodLocation)
#Make splits
splits = bbdata.makeSplitsSequential(numSplits, st, \
splitLen = datetime.timedelta(minutes = splitLength), \
skip = datetime.timedelta(minutes = skipLength))
#Iterate over splits.
for s in splits:
print i
i += 1
oldSplit = datetime.datetime.strptime(s[0], "%Y-%m-%d %H:%M:%S")
newSplit = datetime.datetime.strptime(s[1], "%Y-%m-%d %H:%M:%S")
tmpDoc = []
#Loop over all models
for f in files:
#It is a data file.
if f.split('.')[-1] == 'dat':
#Open it and grab the models and sensor list
periodEnd = "23:59:59"
compress = 1
splitLen = 10
numTopics = 8
#validDays = [0, 1, 2, 3, 4, 5, 6]
validDays = [0, 2, 4]
tdMatrix = []
minBehaviour = 2
if __name__ == "__main__":
#neighborclusters = ncluster.parse(neighborhoodLocation)
splits = bbdata.makeSplitsSequential(5184, "2008-03-09 00:00:00", \
splitLen = datetime.timedelta(minutes = splitLen),
skip = datetime.timedelta(minutes = 10))
"""
#Create all splits (documents) used for TD matrix
splits = bbdata.makeSplits(25, st, et, valid=validDays, \
splitLen = datetime.timedelta(minutes = splitLen),
sPeriod = "07:50:00", \
ePeriod = "08:00:00")
splits += bbdata.makeSplits(25, st, et, valid=validDays, \
splitLen = datetime.timedelta(minutes = splitLen),
sPeriod = "15:50:00", \
ePeriod = "16:00:00")
splits += bbdata.makeSplits(25, st, et, valid=validDays, \
splitLen = datetime.timedelta(minutes = splitLen),
dVector = []
times = []
lsaVector = []
splitLength = 8
skipLength = 1
numSplits = 50
i = 0
if __name__ == "__main__":
files = os.listdir(modelLocation)
neighborclusters = ncluster.parse(neighborhoodLocation)
#Make splits
splits = bbdata.makeSplitsSequential(numSplits, st, \
splitLen = datetime.timedelta(minutes = splitLength), \
skip = datetime.timedelta(minutes = skipLength))
#Iterate over splits.
for s in splits:
print i
i+=1
oldSplit = datetime.datetime.strptime(s[0], "%Y-%m-%d %H:%M:%S")
newSplit = datetime.datetime.strptime(s[1], "%Y-%m-%d %H:%M:%S")
tmpDoc = []
#Loop over all models
for f in files:
#It is a data file.
if f.split('.')[-1] == 'dat':
#Open it and grab the models and sensor list