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package io.virtdata.libbasics.shared.from_long.to_object;

import io.virtdata.annotations.Categories;
import io.virtdata.annotations.Category;
import io.virtdata.annotations.ThreadSafeMapper;
import io.virtdata.libbasics.core.stathelpers.AliasSamplerDoubleInt;
import io.virtdata.libbasics.core.stathelpers.EvProbD;
import io.virtdata.libbasics.shared.from_long.to_double.HashedDoubleRange;
import io.virtdata.util.VirtDataFunctions;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.function.LongFunction;

/**
 * Allows for easy branching over multiple functions with specific
 * weights.
 */
@Categories(Category.distributions)
@ThreadSafeMapper
public class WeightedFuncs implements LongFunction {

    private final LongFunction[] funcs;
    private final AliasSamplerDoubleInt functionSampler;
    private HashedDoubleRange unitSampler = new HashedDoubleRange(0.0d, 1.0d);

    public WeightedFuncs(Object... weightsAndFuncs) {
        List probabilites = new ArrayList<>();
        List> functions = new ArrayList<>();

        List probabilities = new ArrayList<>();

        if ((weightsAndFuncs.length % 2) != 0) {
            throw new RuntimeException("You must have weights and functions, pairwise." +
                    "This is not possible with " + Arrays.toString(weightsAndFuncs));
        }

        for (int i = 0; i < weightsAndFuncs.length; i += 2) {

            Object w = weightsAndFuncs[i];
            double weight = 1.0d;
            try {
                weight = (double) w;
            } catch (NumberFormatException nfe) {
                throw new RuntimeException("the 0th and ever even value must be a floating point weight.");
            }
            probabilites.add(new EvProbD(i >> 1, weight));

            Object f = weightsAndFuncs[i + 1];
            try {
                LongFunction func = VirtDataFunctions.adapt(
                        f, LongFunction.class, Object.class, true
                );
                functions.add(func);
            } catch (Exception e) {
                throw new RuntimeException("There was a problem resolving function " + f);
            }
        }
        this.funcs = functions.toArray(new LongFunction[0]);
        this.functionSampler = new AliasSamplerDoubleInt(probabilites);
    }

    @Override
    public Object apply(long value) {
        double univariate = unitSampler.applyAsDouble(value);
        int index = functionSampler.applyAsInt(univariate);
        LongFunction func = funcs[index];
        Object result = func.apply(value);
        return result;
    }
}
 















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