# ["DUCT", "frodo2.algorithms.duct.DUCTsolver", "../agents/DUCT/DUCTagent.xml", problemFile],
#
# ["DSA", "frodo2.algorithms.localSearch.dsa.DSAsolver", "../agents/DSA/DSAagent.xml", problemFile],
#
# ["MaxSum", "frodo2.algorithms.maxsum.MaxSumSolver", "../agents/MaxSum/MaxSumAgent.xml", problemFile],
#
# ["MGM", "frodo2.algorithms.localSearch.mgm.MGMsolver", "../agents/MGM/MGMagent.xml", problemFile],
# ["MGM2", "frodo2.algorithms.localSearch.mgm.mgm2.MGM2solver", "../agents/MGM/MGM2agent.xml", problemFile],
[
"SynchBB", "frodo2.algorithms.synchbb.SynchBBsolver",
"../agents/SynchBB/SynchBBagent.xml", problemFile
],
]
timeout = 120 # in seconds
# The CSV file to which the statistics should be written
output = "outputMaxDisCSP.csv"
# Run the experiment
frodo2.run(java, javaParams, generator, genParams, nbrProblems, algos, timeout,
output)
# Tip: if some of the algorithms tend to time out most of the time on some problem files,
# you can run 2 experiments: one for all algorithms on the smaller problem sizes,
# and one with only the faster algorithms on the larger problem sizes
# Plot the graphs
frodo2.plot(
output, xCol=8,
yCol=11) # yCol = 11 is the NCCC count (the first column has index 0)
# ["MB-DPOP", "frodo2.algorithms.dpop.DPOPsolver", "../agents/DPOP/MB-DPOP/MB-DPOPagentJaCoP.xml", problemFile], # ["O-DPOP", "frodo2.algorithms.odpop.ODPOPsolver", "../agents/DPOP/O-DPOP/O-DPOPagentJaCoP.xml", problemFile], ["P-DPOP", "frodo2.algorithms.dpop.privacy.P_DPOPsolver", "../agents/DPOP/P-DPOP/P-DPOPagentJaCoP.xml", problemFile], ["P2-DPOP", "frodo2.algorithms.dpop.privacy.P2_DPOPsolver", "../agents/DPOP/P-DPOP/P2-DPOPagentJaCoP_DisCSP.xml", problemFile], # # ["DSA", "frodo2.algorithms.localSearch.dsa.DSAsolver", "../agents/DSA/DSAagentJaCoP.xml", problemFile], # # ["MaxSum", "frodo2.algorithms.maxsum.MaxSumSolver", "../agents/MaxSum/MaxSumAgentJaCoP.xml", problemFile], # # ["MGM", "frodo2.algorithms.localSearch.mgm.MGMsolver", "../agents/MGM/MGMagentJaCoP.xml", problemFile], # ["MGM2", "frodo2.algorithms.localSearch.mgm.mgm2.MGM2solver", "../agents/MGM/MGM2agentJaCoP.xml", problemFile], # ["MPC-DisCSP4", "frodo2.algorithms.mpc_discsp.MPC_DisWCSP4solver", "../agents/MPC/MPC-DisCSP4_JaCoP.xml", problemFileMPC], # ["SynchBB", "frodo2.algorithms.synchbb.SynchBBsolver", "../agents/SynchBB/SynchBBagentJaCoP.xml", problemFile], ] timeout = 600 # in seconds # The CSV file to which the statistics should be written output = "outputParty.csv" # Run the experiment frodo2.run(java, javaParams, generator, genParams, nbrProblems, algos, timeout, output) # Tip: if some of the algorithms tend to time out most of the time on some problem files, # you can run 2 experiments: one for all algorithms on the smaller problem sizes, # and one with only the faster algorithms on the larger problem sizes # Plot the graphs frodo2.plot(output, xCol = 6, yCol = 10) # the first column has index 0
# Run each experiment nbrProblems times
outputs = [] # the names of the CSV output files
for i in range(0, nbrProblems):
print("\n" + str(i + 1) + "/" + str(nbrProblems))
# Run each experiment
for exp in experiments:
print("\n" + exp[0]) # prints the algorithm
# The CSV file to which the statistics should be written
output = exp[0] + ".csv"
outputs += [output]
# Run the experiment
frodo2.run(java, javaParamsNew, generator, exp[1], 1, exp[2], timeout, output, saveProblems = False)
# Plot the results for each experiment
for j in range(0, len(experiments)):
exp = experiments[j]
# The CSV file to which the statistics should have been written
output = outputs[j]
# Plot curves with x = problem size and y = performance of each algorithm
# frodo2.plot(output, xCol = 9, yCol = 15, block = False) # 15 = message size
# frodo2.plot(output, xCol = 9, yCol = 13, block = (j == len(experiments)-1)) # 13 = runtime
# Scatter plot with one data point per instance, x = old algorithm and y = new algorithm
xAlgo = exp[2][0][0]
yAlgo = exp[2][1][0]
# Run each experiment nbrProblems times
outputs = [] # the names of the CSV output files
for i in range(0, nbrProblems):
print("\n" + str(i + 1) + "/" + str(nbrProblems))
# Run each experiment
for exp in experiments:
print("\n" + exp[0]) # prints the algorithm
# The CSV file to which the statistics should be written
output = exp[0] + ".csv"
outputs += [output]
# Run the experiment
frodo2.run(java, javaParamsNew, generator, exp[1], 1, exp[2], timeout,
output)
# Plot the results for each experiment
for j in range(0, len(experiments)):
exp = experiments[j]
# The CSV file to which the statistics should have been written
output = outputs[j]
# Plot curves with x = problem size and y = performance of each algorithm
# frodo2.plot(output, xCol = 6, yCol = 15, block = False) # 15 = message size
# frodo2.plot(output, xCol = 6, yCol = 13, block = (j == len(experiments)-1)) # 13 = runtime
# Scatter plot with one data point per instance, x = old algorithm and y = new algorithm
xAlgo = exp[2][0][0]
yAlgo = exp[2][1][0]
