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