/**
* @return
* @throws BadParameterException
*/
Output initializeOutput() throws BadParameterException {
// 1. create the output
// boolean store = parameters.getBoolean(new Parameter(Evolve.P_STORE),null,false);
int verbosity = parameters.getInt(new Parameter(Evolve.P_VERBOSITY), null, 0);
if (verbosity < 0)
Output.initialError(
"Verbosity should be an integer >= 0.\n", new Parameter(Evolve.P_VERBOSITY));
Output output = new Output(true, verbosity);
// output.setFlush(
// parameters.getBoolean(new Parameter(Evolve.P_FLUSH),null,false));
// stdout is always log #0. stderr is always log #1.
// stderr accepts announcements, and both are fully verbose
// by default.
output.addLog(ec.util.Log.D_STDOUT, Output.V_VERBOSE, false);
output.addLog(ec.util.Log.D_STDERR, Output.V_VERBOSE, true);
output.systemMessage(Version.message());
return output;
}
public static void main(ParameterDatabase parameters) {
EvolutionState state;
// ParameterDatabase parameters;
ParameterDatabase original = (ParameterDatabase) deepClone(parameters);
int currentJob = 0; // the next job number (0 by default)
// parameters = loadParameterDatabase(args);
if (currentJob == 0) // no current job number yet
currentJob = parameters.getIntWithDefault(new Parameter("current-job"), null, 0);
if (currentJob < 0)
Output.initialError(
"The 'current-job' parameter must be >= 0 (or not exist, which defaults to 0)");
int numJobs = parameters.getIntWithDefault(new Parameter("jobs"), null, 1);
if (numJobs < 1)
Output.initialError("The 'jobs' parameter must be >= 1 (or not exist, which defaults to 1)");
// Now we know how many jobs remain. Let's loop for that many jobs. Each time we'll
// load the parameter database scratch (except the first time where we reuse the one we
// just loaded a second ago). The reason we reload from scratch each time is that the
// experimenter is free to scribble all over the parameter database and it'd be nice to
// have everything fresh and clean. It doesn't take long to load the database anyway,
// it's usually small.
for (int job = currentJob; job < numJobs; job++) {
// We used to have a try/catch here to catch errors thrown by this job and continue to the
// next.
// But the most common error is an OutOfMemoryException, and printing its stack trace would
// just create another OutOfMemoryException! Which dies anyway and has a worthless stack
// trace as a result.
// try
{
// load the parameter database (reusing the very first if it exists)
if (parameters == null) parameters = (ParameterDatabase) deepClone(original);
// parameters = loadParameterDatabase(args);
// Initialize the EvolutionState, then set its job variables
state = initialize(parameters, job); // pass in job# as the seed increment
state.output.systemMessage("Job: " + job);
state.job = new Object[1]; // make the job argument storage
state.job[0] = Integer.valueOf(job); // stick the current job in our job storage
// state.runtimeArguments = args; // stick the runtime
// arguments in our storage
if (numJobs > 1) // only if iterating (so we can be backwards-compatible),
{
String jobFilePrefix = "job." + job + ".";
state.output.setFilePrefix(jobFilePrefix); // add a prefix for checkpoint/output files
state.checkpointPrefix =
jobFilePrefix + state.checkpointPrefix; // also set up checkpoint prefix
}
// Here you can set up the EvolutionState's parameters further before it's setup(...).
// This includes replacing the random number generators, changing values in
// state.parameters,
// changing instance variables (except for job and runtimeArguments, please), etc.
// now we let it go
state.run(EvolutionState.C_STARTED_FRESH);
cleanup(state); // flush and close various streams, print out parameters if necessary
parameters = null; // so we load a fresh database next time around
}
}
System.exit(0);
}