/*
 * JaamSim Discrete Event Simulation
 * Copyright (C) 2013 Ausenco Engineering Canada Inc.
 * Copyright (C) 2016 JaamSim Software Inc.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package com.jaamsim.ProbabilityDistributions;

import com.jaamsim.Samples.SampleConstant;
import com.jaamsim.input.IntegerInput;
import com.jaamsim.input.Keyword;
import com.jaamsim.input.ValueInput;
import com.jaamsim.rng.MRG1999a;
import com.jaamsim.units.Unit;
import com.jaamsim.units.UserSpecifiedUnit;

/**
 * Erlang Distribution.
 * Adapted from A.M. Law, "Simulation Modelling and Analysis, 4th Edition", page 449.
 */
public class ErlangDistribution extends Distribution {

	@Keyword(description = "The scale parameter for the Erlang distribution.",
	         exampleList = {"5.0"})
	private final ValueInput meanInput;

	@Keyword(description = "The shape parameter for the Erlang distribution.  An integer value >= 1.  " +
			"Shape = 1 gives the Exponential distribution.  " +
			"For Shape > 10 it is better to use the Gamma distribution.",
	         exampleList = {"2"})
	private final IntegerInput shapeInput;

	private final MRG1999a rng = new MRG1999a();

	{
		minValueInput.setDefaultValue(new SampleConstant(0.0d));

		meanInput = new ValueInput("Mean", "Key Inputs", 1.0d);
		meanInput.setUnitType(UserSpecifiedUnit.class);
		meanInput.setValidRange(0.0d, Double.POSITIVE_INFINITY);
		this.addInput(meanInput);

		shapeInput = new IntegerInput("Shape", "Key Inputs", 1);
		shapeInput.setValidRange( 1, Integer.MAX_VALUE);
		this.addInput(shapeInput);
	}

	public ErlangDistribution() {}

	@Override
	public void earlyInit() {
		super.earlyInit();
		rng.setSeedStream(getStreamNumber(), getSubstreamNumber());
	}

	@Override
	protected void setUnitType(Class<? extends Unit> specified) {
		super.setUnitType(specified);
		meanInput.setUnitType(specified);
	}

	@Override
	protected double getSample(double simTime) {

		// Calculate the product of k random values
		double u = 1.0;
		int k = shapeInput.getValue();
		for( int i=0; i<k; i++) {
			u *= rng.nextUniform();
		}

		// Inverse transform method
		return (- meanInput.getValue() / shapeInput.getValue() * Math.log( u ));
	}

	@Override
	protected double getMean(double simTime) {
		return meanInput.getValue();
	}

	@Override
	protected double getStandardDev(double simTime) {
		return meanInput.getValue() / Math.sqrt( shapeInput.getValue() );
	}
}

@@ -783,16 +783,56 @@
 nstant;%0A
+import com.jaamsim.Samples.SampleInput;%0A
 import c
@@ -900,45 +900,8 @@
 rd;%0A
-import com.jaamsim.input.ValueInput;%0A
 impo
@@ -1285,16 +1285,60 @@
 = %7B%225.0%22
+, %22InputValue1%22, %22'2 * %5BInputValue1%5D.Value'%22
 %7D)%0A%09priv
@@ -1347,20 +1347,21 @@
 e final 
-Valu
+Sampl
 eInput m
@@ -1794,20 +1794,21 @@
 t = new 
-Valu
+Sampl
 eInput(%22
@@ -1832,13 +1832,33 @@
 s%22, 
+new SampleConstant(
 1.0d)
+)
 ;%0A%09%09
@@ -1964,16 +1964,45 @@
 INITY);%0A
+%09%09meanInput.setEntity(this);%0A
 %09%09this.a
@@ -2720,17 +2720,21 @@
 d%0A%09%09
-return (-
+double mean =
  mea
@@ -2750,16 +2750,57 @@
 tValue()
+.getNextSample(simTime);%0A%09%09return (- mean
  / shape
@@ -2922,16 +2922,39 @@
 tValue()
+.getNextSample(simTime)
 ;%0A%09%7D%0A%0A%09@
@@ -3007,38 +3007,45 @@
 le simTime) %7B%0A%09%09
-return
+double mean =
  meanInput.getVa
@@ -3049,16 +3049,54 @@
 tValue()
+.getNextSample(simTime);%0A%09%09return mean
  / Math.
@@ -3129,10 +3129,11 @@
 ) );%0A%09%7D%0A
+%0A
 %7D%0A

convert ErlangDistribution keywords to SampleInput