elif inv.hasParameter("run_startup"):
startup_contract = Contract.getNonCoreContract("startup")
startup_contract.callFunction("on_start_up", [Monad.getContext()])
elif inv.hasParameter("cancel_backend"):
backend_pid = inv.getLong("backend_pid")
con = Hiber.session().connection()
stmt = con.createStatement()
stmt.execute("select pg_terminate_backend(" + str(backend_pid) + ")")
stmt.close()
Hiber.commit()
source.appendChild(MonadMessage("Cancelled backend.").toXml(doc))
df = DecimalFormat("###,###,###,###,##0")
runtime = Runtime.getRuntime()
source.setAttribute("free-memory", df.format(runtime.freeMemory()))
source.setAttribute("max-memory", df.format(runtime.maxMemory()))
source.setAttribute("total-memory", df.format(runtime.totalMemory()))
source.setAttribute("available-processors", str(runtime.availableProcessors()))
source.setAttribute("system-load-average", str(ManagementFactory.getOperatingSystemMXBean().getSystemLoadAverage()))
mon = JavaSysMon()
source.setAttribute("cpu-frequency-in-hz", df.format(mon.cpuFrequencyInHz()))
source.setAttribute("current-pid", df.format(mon.currentPid()))
source.setAttribute("num-cpus", df.format(mon.numCpus()))
source.setAttribute("os-name", mon.osName())
source.setAttribute("uptime-in-seconds", df.format(mon.uptimeInSeconds()))
cpu = mon.cpuTimes()
source.setAttribute("idle-millis", df.format(cpu.getIdleMillis()))
source.setAttribute("system-millis", df.format(cpu.getSystemMillis()))
def trainClassifier(classifier, matchingExamples, mismatchingExamples):
ti = createTrainingInstances(matchingExamples, mismatchingExamples)
classifier.buildClassifier(ti)
df = DecimalFormat("0.0000")
return df.format(classifier.measureOutOfBagError()) #print
