package hex.example;

import hex.ModelBuilder;
import hex.ModelCategory;
import hex.example.ExampleModel.ExampleOutput;
import hex.example.ExampleModel.ExampleParameters;
import water.Job;
import water.MRTask;
import water.fvec.Chunk;
import water.util.Log;

import java.util.Arrays;

/**
 * Example model builder... building a trivial ExampleModel
 */
public class Example extends ModelBuilder<ExampleModel, ExampleParameters, ExampleOutput> {

    @Override
    public ModelCategory[] can_build() {
        return new ModelCategory[]{ModelCategory.Unknown,};
    }

    @Override
    public BuilderVisibility builderVisibility() {
        return BuilderVisibility.Experimental;
    }

    @Override
    public boolean isSupervised() {
        return false;
    }

    // for ModelBuilder registration
    public Example(boolean startup_once) {
        super(new ExampleParameters(), startup_once);
    }

    public Example(ExampleModel.ExampleParameters parms) {
        super(parms);
        init(false);
    }

    @Override
    protected ExampleDriver trainModelImpl() {
        return new ExampleDriver();
    }

    /**
     * Initialize the ModelBuilder, validating all arguments and preparing the
     * training frame.  This call is expected to be overridden in the subclasses
     * and each subclass will start with "super.init();".  This call is made
     * by the front-end whenever the GUI is clicked, and needs to be fast;
     * heavy-weight prep needs to wait for the trainModel() call.
     * 
     * Validate the max_iterations.
     */
    @Override
    public void init(boolean expensive) {
        super.init(expensive);
        if (_parms._max_iterations < 1 || _parms._max_iterations > 9999999)
            error("max_iterations", "must be between 1 and 10 million");
    }

    // ----------------------
    private class ExampleDriver extends Driver {
        @Override
        public void computeImpl() {
            ExampleModel model = null;
            try {
                init(true);

                // The model to be built
                model = new ExampleModel(_job._result, _parms, new ExampleModel.ExampleOutput(Example.this));
                model.delete_and_lock(_job);

                // ---
                // Run the main Example Loop
                // Stop after enough iterations
                for (; model._output._iterations < _parms._max_iterations; model._output._iterations++) {
                    if (stop_requested() && !timeout())
                        throw new Job.JobCancelledException(); // Stopped/cancelled

                    double[] maxs = new Max().doAll(_parms.train())._maxs;
                    Log.info("Max per-column: " + Arrays.toString(maxs));

                    // Fill in the model
                    model._output._maxs = maxs;
                    model.update(_job);   // Update model in K/V store
                    _job.update(1);       // One unit of work

                    StringBuilder sb = new StringBuilder();
                    sb.append("Example: iter: ").append(model._output._iterations);
                    Log.info(sb);
                }
            } finally {
                if (model != null) model.unlock(_job);
            }
        }
    }


    // -------------------------------------------------------------------------
    // Find max per-column
    private static class Max extends MRTask<Max> {
        // IN

        // OUT
        double[] _maxs;

        @Override
        public void map(Chunk[] cs) {
            _maxs = new double[cs.length];
            Arrays.fill(_maxs, -Double.MAX_VALUE);
            for (int col = 0; col < cs.length; col++)
                for (int row = 0; row < cs[col]._len; row++)
                    _maxs[col] = Math.max(_maxs[col], cs[col].atd(row));
        }

        @Override
        public void reduce(Max that) {
            for (int col = 0; col < _maxs.length; col++)
                _maxs[col] = Math.max(_maxs[col], that._maxs[col]);
        }
    }
}

@@ -2099,20 +2099,14 @@
 del(
-_job._result
+dest()
 , _p

Fix Example to use proper Model key (_job._result won't work in CV)