blakeOutput = []
tracyOutput = []
# Data with feature selection
subSetData = []
subSetDataHeader = ['cpu', 'mem', 'project', 'ru_wallclock', 'io']
# List of symbolic columns
symCols = [2]
# Cluster count
clustCounts = [5, 6] #[3, 4, 5, 6, 7, 8]
data, head = util.readData(acctData, False)
for idx, item in enumerate(util.column(data, head.index('failed'))):
if int(item) == 0:
cpuIndex = head.index('cpu')
memIndex = head.index('mem')
projIndex = head.index('project')
clockIndex = head.index('ru_wallclock')
ioIndex = head.index('io')
subSetData.append([ \
str(data[idx][cpuIndex]), \
str(data[idx][memIndex]), \
str(data[idx][projIndex]), \
str(data[idx][clockIndex]), \
str(data[idx][ioIndex])])
newData, keyDict = util.convertSymbolic(subSetData, symCols, True)
