def apply_cfs(self, df):
y = df.Bugs.values
X = df.drop(labels=['Bugs'], axis=1)
X = X.values
selected_cols = CFS.cfs(X, y)
cols = df.columns[[selected_cols]].tolist()
cols.append('Bugs')
return df[cols], cols
def apply_cfs(df):
_cols = df.columns
y = df.Bugs.values
X = df.drop(labels=['Bugs'], axis=1)
X = X.values
selected_cols = CFS.cfs(X, y)
fss = []
cols = df.columns[[selected_cols]].tolist()
cols.append('Bugs')
for col in _cols:
if col in cols:
fss.append(1)
else:
fss.append(0)
return df[cols], cols, fss
def apply_cfs(self, df):
_cols = df.columns
y = df.Buggy.values
X = df.drop(labels=['Buggy'], axis=1)
X = X.values
selected_cols = CFS.cfs(X, y)
fss = []
imp_fss = []
cols = df.columns[[selected_cols]].tolist()
cols.append('Buggy')
for col in _cols:
_pos = cols.index(col) if col in cols else 0
if col in cols:
fss.append(1)
imp_fss.append(_pos)
else:
fss.append(0)
imp_fss.append(0)
return df[cols], cols, fss, imp_fss
def run_all_simulations(numCoresList, numProcessesList):
"""
sets up and runs all the simulations
:return:
"""
# open all statistics file, appending to the end of it
dirName = gWorkloadType + "_all"
fileName = gWorkloadType + "_all_statistics_table"
csvAllStatsTableFile = ScheduleUtilities.open_output_file(
dirName, fileName, "csv", "a")
# write the header for the all statistics file
temp = MachineFCFS.MachineFCFS()
temp.csv_all_statistics_table_write_header(csvAllStatsTableFile)
# the type of schedule algorithms
typeMachinesList = ["fcfs", "roundrobin", "spf", "srtf", "CFS", "FPPQ"]
numTypeMachines = len(typeMachinesList)
# 3 dimensional array
machineMatrix = [[[None for k in range(len(numProcessesList))]
for j in range(len(numCoresList))]
for i in range(len(typeMachinesList))]
# print(machineMatrix)
"""
for i in range(len(typeMachinesList)):
for j in range(len(numCoresList)):
for k in range(len(numProcessesList)):
print(machineMatrix[i][j][k])
"""
#
# create all the machines and add them to the matrix
#
for j in range(0, len(numCoresList)):
for k in range(0, len(numProcessesList)):
# add machines of each type to the matrix
# FCFS
machineMatrix[0][j][k] = MachineFCFS.MachineFCFS(numCoresList[j])
# Round Robin
machineMatrix[1][j][k] = MachineRoundRobin.MachineRoundRobin(
numCoresList[j])
# SPF
machineMatrix[2][j][
k] = MachineShortestProcessFirst.MachineShortestProcessFirst(
numCoresList[j])
# SRTF
machineMatrix[3][j][
k] = MachineShortestRemainingTimeFirst.MachineShortestRemainingTimeFirst(
numCoresList[j])
# CFS
machineMatrix[4][j][k] = PreemptiveMachine.PreemptiveMachine(
CFS.CFS(20, 16), numCoresList[j])
# FPPQ
machineMatrix[5][j][k] = FPPQMachine.FPPQMachine(numCoresList[j])
# print(machineMatrix)
#
# create process test cases
#
for j in range(0, len(numCoresList)):
for k in range(0, len(numProcessesList)):
if gWorkloadType == "lecture":
for i in range(0, len(typeMachinesList)):
ScheduleTests.create_lecture_example(
machineMatrix[i][j][k], 3)
if gWorkloadType == "balanced":
for i in range(0, len(typeMachinesList)):
ScheduleTests.create_balanced_statistical_test(
machineMatrix[i][j][k], numProcessesList[k])
if gWorkloadType == "cpu_heavy":
for i in range(0, len(typeMachinesList)):
ScheduleTests.create_cpu_heavy_statistical_test(
machineMatrix[i][j][k], numProcessesList[k])
if gWorkloadType == "io_heavy":
for i in range(0, len(typeMachinesList)):
ScheduleTests.create_io_heavy_statistical_test(
machineMatrix[i][j][k], numProcessesList[k])
if gWorkloadType == "cpu_only":
for i in range(0, len(typeMachinesList)):
ScheduleTests.create_cpu_only_statistical_test(
machineMatrix[i][j][k], numProcessesList[k])
#
# run all the simulations
#
for i in range(len(typeMachinesList)):
for j in range(len(numCoresList)):
for k in range(len(numProcessesList)):
simName = ""
simName += "Running simulation: "
simName += gWorkloadType + "_"
simName += typeMachinesList[i]
simName += " with # of cores = " + str(numCoresList[j])
simName += " and # of processes = " + str(numProcessesList[k])
print(simName)
algorithmName = gWorkloadType + "_" + typeMachinesList[i]
numCores = numCoresList[j]
numProcesses = numProcessesList[k]
# run the simulation
run_simulation(machineMatrix[i][j][k], algorithmName, numCores,
numProcesses)
# write out the all statistics file, append the final statistics to the all statistics table
machineMatrix[i][j][k].csv_all_statistics_table_write(
csvAllStatsTableFile, algorithmName, numCores,
numProcesses)
# close the all statistics file
csvAllStatsTableFile.close()