/*$$ * packages uchicago.src.* * Copyright (c) 1999, Trustees of the University of Chicago * All rights reserved. * * Redistribution and use in source and binary forms, with * or without modification, are permitted provided that the following * conditions are met: * *	 Redistributions of source code must retain the above copyright notice, *	 this list of conditions and the following disclaimer. * *	 Redistributions in binary form must reproduce the above copyright notice, *	 this list of conditions and the following disclaimer in the documentation *	 and/or other materials provided with the distribution. * *	 Neither the name of the University of Chicago nor the names of its *   contributors may be used to endorse or promote products derived from *   this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A * PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE TRUSTEES OR * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, * EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * * Nick Collier * nick@src.uchicago.edu * * packages cern.jet.random.* * Copyright (c) 1999 CERN - European Laboratory for Particle * Physics. Permission to use, copy, modify, distribute and sell this * software and its documentation for any purpose is hereby granted without * fee, provided that the above copyright notice appear in all copies * and that both that copyright notice and this permission notice appear in * supporting documentation. CERN makes no representations about the * suitability of this software for any purpose. It is provided "as is" * without expressed or implied warranty. * * Wolfgang Hoschek * wolfgang.hoschek@cern.ch *$$*/package tom.edu.csustan.astarte;import java.util.Vector;import java.util.ArrayList;import java.util.Arrays;import java.util.Random;import java.util.ListIterator;import java.awt.Color;import java.util.Collections;import java.lang.Math;import uchicago.src.reflector.ListPropertyDescriptor;import uchicago.src.sim.space.*;import uchicago.src.sim.engine.*;import uchicago.src.sim.gui.*;import uchicago.src.sim.util.SimUtilities;import uchicago.src.sim.analysis.*;import cern.jet.random.Uniform;import cern.jet.random.Normal;import uchicago.src.reflector.BooleanPropertyDescriptor;// Simulation models should extend SimModelImpl which does some basic setup// and allows a controller easy access to a simulations initial parameters.public class WealthModel extends SimModelImpl {  // Every model must have a schedule  private Schedule schedule;  // A list of all the agents. Convenient for any method that  // iterates through a list of agents. A least one list like this is common  // to most simulations. See below for examples of its use.//  private ArrayList agentList = new ArrayList();  public static ArrayList agentList = new ArrayList();  // A list of WealthAgents who have been "birthed" and should be introduced  // to the simulation in the next turn  private Vector birthList = new Vector();  // The Wealth Space - the agent's environment consisting of variable  // amounts of wealth arranged on a grid  private WealthSpace space;  // The 2 dimensional torusr on which the agents act.  private static Object2DTorus agentGrid;  // A queue that tracks dead agents.  private Vector reaperQueue = new Vector();  // A DataRecorder or ObjectDataRecorder allows data generated by  // a simulation to be written to a file  // Note to self:  lines beginning //** should be uncommented to record data  private DataRecorder recorder;  // default and modifiable parameters of the model    private String behaviour = "Both";          // Behaviour of agents  public static boolean Exchange = false;    // Do exchange model  public static boolean Both = false;          // Combine exchange and investment economies  public static boolean DeathTax = false;     // Implement "death tax"  public static int MaxAge = 1200;            // Age for "death tax" (if turned on)  private int MaxInitialWealth = 110;         // Maximum initial wealth for agents  private int MinInitialWealth = 90;          // Minimum initial wealth for agents  public static double MinWealth = 1.0;       // Minimum wealth  public static boolean Moving = false;       // Do agents move (for exchange or "synch" models)  private static int NumAgents = 1500;		  // Total number of agents (must be <= 2500)  private static int NumLogLogBins = 30;	  // Number of bins for log:log plot  private static int NumPlainBins = 100;	  // Number of bins for plain plot  private static double PlainPlotXMax = 300.0;// Maximum X (wealth) plotted in plain plot (-1 = any)  private static double PlainPlotYMax = -1.0; // Maximum Y (P_i) plotted in plain plot (-1 = any)  private static boolean PlotLogLog = true;   // Whether to display log:log plot  private static boolean PlotPlain = true;    // Whether to display plain plot  public static boolean ROI = false;          // Whether to do investment economy (only)  public static double ROIMean = 0.00;           // Mean return on investment  public static double ROIStdDev = 0.05;          // Standard deviation of normal dist. of return  public static boolean RandomWalk = false;   // Whether to do individual random walk  public static boolean Smarter = false;	  // Are some agents smarter?  public static int SmarterNum = 50;          // 1 in SmarterNum is smarter.  public static boolean Sync = false;         // Whether to run the sync model instead  public static double SyncLatency = 3.0;     // Latency in sync mode after "flash"  public static int SyncMax = 150;            // Max value in sync model  public static boolean SyncRegion = true;   // Do agents affect only nearbys or everybody (in sync)  public static int TaxPCT = 10;              // Tax rate for death tax  private static boolean ViewAvg = true;      // Whether to show average wealth of all agents  private static boolean ViewStDAvg = true;   // Whether to show moving average of Std. Dev. of wealth of all agents  private static boolean ViewStDev = true;    // Whether to show standard deviation of wealth of all agents  private static boolean ViewStats = true;    // Whether to show average wealth of all agents  private static boolean WriteStats = false;  // Whether to write stats out to a file on pause or stop  private static boolean ViewPowerLawExp = true;  // Whether to show power law exponent  private static int RichMinPct = 90;		  // Rich above what per cent . . .  private static boolean ViewEntropy = true;  // Whether to show entropy  private static int entropyBin = 5;          // size of bins for calculating entropy    private boolean replace = true;  private static int MAvgRange = 1000;  private static double[] StDAvg = new double[MAvgRange];  private static int stepModMAvgRange = 0;  private static boolean testing = false;    private static int step = 0;  // The surface on which the agents and their environment are displayed  private DisplaySurface dsurf;  // A graph that plots sequence  private OpenSequenceGraph statsGraph;    // A graph for the "power law" exponent;  private OpenSequenceGraph powerlawGraph;    // A graph for the entropy;  private OpenSequenceGraph entropyGraph;  // A histogram for wealth  private OpenHistogram bar;    // A graph for log-log plot  private Plot logLogPlot;    // A graph for plain plot  private Plot plainPlot;    // A histogram for ages//  private OpenHistogram barAge;  // These inner classes are used by all the data collection methods - i.e.  // DataRecorder, SequenceGraph and the Histogram.  // All simulations should have a no argument constructor - this is empty and  // thus not strictly necessary  public WealthModel() {	  	  String[] props1 = new String[] {"Both", "Exchange", "ROI", "RandomWalk", "Sync"};	  ListPropertyDescriptor pd1 = new ListPropertyDescriptor("Behaviour", props1);	  descriptors.put("Behaviour", pd1);	  	  Controller.ALPHA_ORDER = false;  }  // The typical way to code a simulation is to divide up the creation of the  // simulation into three methods - buildModel(), buildDisplay(),  // buildSchedule(). This division is not strictly necessary, but it does  // make the creation conceptually clearer.  // The buildModel() method is responsible for creating those parts of the  // simulation that represent what is being modeled. Consequently, the agents  // and their environment are typically created here together with any  // optional data collection objects. Of course, this method may call other  // methods to help build the model.  private void buildModel() {    // creates the wealth space using the values in wealthspace.pgm as    // the amount of wealth (see WealthSpace.java for more).    //    space = new WealthSpace("/WealthModel/wealthspace.pgm");    space = new WealthSpace("/wealthspace.pgm");    agentGrid = new Object2DTorus(space.getXSize(), space.getYSize());        // createNormal(ROIMean, ROIStdDev);    for (int i = 0; i < NumAgents; i++) {      addNewAgent();    }    // create a new DataRecorder and write the data to ./wealth_data.txt    	if (WriteStats) {      recorder = new DataRecorder("./wealth_data.txt", this);	}    // first we make an inner class that implements the DataSource interface    //    class AgentCountClass implements DataSource {//      public Object execute() {//        int i = agentList.size();//        return new Integer(i);//      }//    };    class AgentWealthClass implements DataSource {      public Object execute() {        String s = " ";        for (int i = 0; i < agentList.size(); i++) {            WealthAgent agent = (WealthAgent)agentList.get(i);            if (i < agentList.size() - 1)              s = s + agent.getWealth() + ",";            else              s = s + agent.getWealth();        }        return s;      }    };//    recorder.addObjectDataSource("AgentCount", new AgentCountClass());	if (WriteStats) {      recorder.addObjectDataSource("AgentWealth", new AgentWealthClass());	}    // we could also have done the above with an anonymous inner class    // recorder.addObjectDataSource("Agent Count", new DataSource() {    //  public Object execute() {    //    return new Integer(agentList.size());    //  }    // });  }  // buildDisplay() builds those parts of the simulation that have to do with  // displaying the simulation to a user.  private void buildDisplay() {    // Create a display to display the agentGrid on the screen.    // This will display any Drawable contained within the Object2DTorus.    // In a non-batch simulation the agents in a simulation will typically    // implement the Drawable interface.    Object2DDisplay agentDisplay = new Object2DDisplay(agentGrid);    // Rather than have the agentDisplay iterating over each object in the    // Object2DTorus, give the display a list of Drawables to display.    agentDisplay.setObjectList(agentList);    // Maps 4 shades of yellow to integers 1 - 4, and white to 0.    ColorMap map = new ColorMap();    map.mapColor(4, new Color(255, 255, 0));    map.mapColor(3, new Color(255, 255, 255 / 3));    map.mapColor(2, new Color(255, 255, 255 / 2));    map.mapColor(1, new Color(255, 255, (int)(255 / 1.2)));    map.mapColor(0, Color.white);    // WealthSpace.getCurrentWealth returns an Object2DTorus containing an    // Integer of value (0 - 4) at each x, y coordinate. Using the map created    // above this Value2DDisplay will display will display each of these    // Integers as a shade of yellow (or white, if the Integer == 0).    Value2DDisplay wealthDisplay = new Value2DDisplay(space.getCurrentWealth(),                                                map);    // DisplaySurface does the actual drawing of the various displays on the    // user's screen. Displays are displayed in the order they are added.    // Our dsurf object is created in the setup() method    dsurf.addDisplayableProbeable(wealthDisplay, "Wealth Space");    dsurf.addDisplayableProbeable(agentDisplay, "Agents");    // Histograms get their data from histogramItems. This creates an item    // called wealth that gets its data by calling getWealth on each agent    // in the agent list.    bar.createHistogramItem("Wealth", agentList, new BinDataSource() {      public double getBinValue(Object o) {        WealthAgent agent = (WealthAgent)o;        return agent.getWealth();      }    },7 ,0);    bar.setYRange(0, 1.0);		if (ViewPowerLawExp) {		powerlawGraph = new OpenSequenceGraph("Power Law Exponent", this);		powerlawGraph.setXRange(0,200);		powerlawGraph.setYRange(1.5,4.0);		powerlawGraph.setAxisTitles("time", "exponent - alpha");		powerlawGraph.addSequence("alpha", new Sequence() {			public double getSValue() {				int nMin, n;				double xMin, alpha = 0.0;								double[] agentWealths = new double[agentList.size()];								for (int i = 0; i < agentList.size(); i++) {					WealthAgent a = (WealthAgent) agentList.get(i);					agentWealths[i] = a.getWealth();				}								java.util.Arrays.sort(agentWealths);								nMin = (int) Math.round(agentList.size() * RichMinPct / 100.0);				n = agentList.size() - nMin + 1;				xMin = agentWealths[nMin];								for (int i = nMin; i < agentList.size(); i++) {					alpha = alpha + Math.log(agentWealths[i] / xMin);				}								alpha = 1 + n * (1 / alpha);								return alpha;			}        });	}	if (ViewEntropy) {		entropyGraph = new OpenSequenceGraph("Entropy", this);		entropyGraph.setXRange(0,200);		entropyGraph.setYRange(1.5,4.0);		entropyGraph.setAxisTitles("time", "entropy");		entropyGraph.addSequence("entropy", new Sequence() {			public double getSValue() {				int nBins;				double wealthMax = 0.0, entropy = 0.0;												for (int i = 0; i < agentList.size(); i++) {					WealthAgent a = (WealthAgent) agentList.get(i);					if ( a.getWealth() > wealthMax )						wealthMax = a.getWealth();				}								nBins = (int) Math.floor(wealthMax/entropyBin) + 1;								int[] agentCounts = new int[nBins];								for (int i = 0; i < nBins; i++)					agentCounts[i] = 0;								for (int i = 0; i < agentList.size(); i++) {					WealthAgent a = (WealthAgent) agentList.get(i);					agentCounts[(int) Math.floor(a.getWealth()/entropyBin)]++;				}								for (int i = 0; i < nBins; i++)					if ( agentCounts[i] > 0 )						entropy = entropy + ((double) agentCounts[i] / agentList.size())							* Math.log((double) agentList.size() / agentCounts[i]);								return entropy;			}        });		if (testing) {			entropyGraph.addSequence("max wealth", new Sequence() {				public double getSValue() {					double wealthMax = 0.0;															for (int i = 0; i < agentList.size(); i++) {						WealthAgent a = (WealthAgent) agentList.get(i);						if ( a.getWealth() > wealthMax )							wealthMax = a.getWealth();					}										return wealthMax;				}			});		}	}		if (ViewStats || ViewAvg || ViewStDev || ViewStDAvg ) {	  statsGraph = new OpenSequenceGraph("Agent Stats.", this);      statsGraph.setXRange(0, 200);      statsGraph.setYRange(0, 200);      statsGraph.setAxisTitles("time", "agent attributes");	  	  	  if (ViewAvg) {        statsGraph.addSequence("Avg. Wealth", new Sequence() {          public double getSValue() {            double totalWealth = 0;            for (int i = 0; i < agentList.size(); i++) {              WealthAgent a = (WealthAgent)agentList.get(i);              totalWealth += a.getWealth();            }              return totalWealth / agentList.size();          }        });	  }	  	  if (ViewStDev) {	    statsGraph.addSequence("Std. Dev. - Wealth", new Sequence() {	  	  public double getSValue() {			  double totalWealth = 0.0;			  double avgWealth = 0.0;			  double calcSD = 0.0;			  			  for (int i = 0; i < agentList.size(); i++) {				  WealthAgent a = (WealthAgent)agentList.get(i);				  totalWealth += a.getWealth();			  }			  			  avgWealth = totalWealth / agentList.size();			  			  for (int i = 0; i < agentList.size(); i++) {				  WealthAgent a = (WealthAgent)agentList.get(i);				  calcSD += (a.getWealth() - avgWealth) * (a.getWealth() - avgWealth);			  }			  			  calcSD = calcSD / agentList.size();			  			  calcSD = Math.sqrt(calcSD);			  			  return calcSD;		  }        });	  }	  	  if (ViewStDAvg) {		  statsGraph.addSequence("Std. Dev. - Mvg. Avg.", new Sequence() {			  public double getSValue() {				  double totalWealth = 0.0;				  double avgWealth = 0.0;				  double calcSD = 0.0;				  				  for (int i = 0; i < agentList.size(); i++) {					  WealthAgent a = (WealthAgent)agentList.get(i);					  totalWealth += a.getWealth();				  }				  				  avgWealth = totalWealth / agentList.size();				  				  for (int i = 0; i < agentList.size(); i++) {					  WealthAgent a = (WealthAgent)agentList.get(i);					  calcSD += (a.getWealth() - avgWealth) * (a.getWealth() - avgWealth);				  }				  				  calcSD = calcSD / agentList.size();				  				  calcSD = Math.sqrt(calcSD);				  				  stepModMAvgRange = (stepModMAvgRange + 1) % MAvgRange;