/**
* Returns an EvolutionState object read from a checkpoint file whose filename is
* <i>checkpoint</i>
*
* @exception java.lang.ClassNotFoundException thrown when the checkpoint file contains a class
* reference which doesn't exist in your class hierarchy.
*/
public static EvolutionState restoreFromCheckpoint(String checkpoint)
throws IOException, ClassNotFoundException, OptionalDataException
/* must throw something if error -- NEVER return null */
{
// load from the file
ObjectInputStream s =
new ObjectInputStream(
new GZIPInputStream(new BufferedInputStream(new FileInputStream(checkpoint))));
EvolutionState e = (EvolutionState) s.readObject();
s.close();
// restart from the checkpoint
e.resetFromCheckpoint();
return e;
}
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);
}