Example usage for org.apache.commons.math3.distribution GeometricDistribution sample

Introduction

In this page you can find the example usage for org.apache.commons.math3.distribution GeometricDistribution sample.

Prototype

public int sample() 

Source Link

Document

The default implementation uses the <a href="http://en.wikipedia.org/wiki/Inverse_transform_sampling"> inversion method</a>.

Usage

From source file:edu.oregonstate.eecs.mcplan.domains.inventory.InventoryProblem.java

/**
 * Demand follows a bounded random walk with uniform increments of bounded
 * size. Delivery probability is fairly high, and warehouse costs are
 * small in proportion to prices.//from w w  w  .  j a  v a 2s . c om
 * @return
 */
public static InventoryProblem Geometric() {
    final int Nproducts = 2;
    final int max_inventory = 30;
    final double warehouse_cost = 1;
    final int min_order = 2;
    final int max_order = 5;
    final int cost[] = { 1, 2 };
    final double delivery_probability = 0.7;
    final int max_demand = 20;
    final int[] price = new int[] { 9, 15 };

    final InventoryProblem problem = new InventoryProblem(Nproducts, price, max_inventory, warehouse_cost,
            min_order, max_order, cost, delivery_probability, max_demand) {
        @Override
        public int[] sampleNextDemand(final InventoryState s) {
            final GeometricDistribution f = new GeometricDistribution(s.rng, 0.4);
            final int[] dprime = new int[s.problem.Nproducts];
            for (int i = 0; i < s.problem.Nproducts; ++i) {
                dprime[i] = Math.min(f.sample(), max_demand);
            }
            return dprime;
        }
    };
    return problem;
}

---

From source file:edu.oregonstate.eecs.mcplan.domains.inventory.InventoryProblem.java

/**
 * Almost the same as 'Geometric', but with a small warehouse capacity and
 * higher delivery probability./*w ww. j  a  v a 2 s.c o  m*/
 * We hope that this will make lookahead more useful.
 * @return
 */
public static InventoryProblem Geometric2() {
    final int Nproducts = 2;
    final int max_inventory = 4;
    final double warehouse_cost = 1;
    final int min_order = 2;
    final int max_order = 5;
    final int cost[] = { 1, 2 };
    final double delivery_probability = 0.8;
    final int max_demand = 20;
    final double demand_p = 0.4;
    final int[] price = new int[] { 9, 15 };

    final InventoryProblem problem = new InventoryProblem(Nproducts, price, max_inventory, warehouse_cost,
            min_order, max_order, cost, delivery_probability, max_demand) {
        @Override
        public int[] sampleNextDemand(final InventoryState s) {
            final GeometricDistribution f = new GeometricDistribution(s.rng, demand_p);
            final int[] dprime = new int[s.problem.Nproducts];
            for (int i = 0; i < s.problem.Nproducts; ++i) {
                dprime[i] = Math.min(f.sample(), max_demand);
            }
            return dprime;
        }
    };
    return problem;
}

---