/*$$ * 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 WealthModel; 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 static boolean logEntropy = true; // scale entropy bins by logarithm . . . private static int numLogEntropyBins = 50; // number of log-entropy bins . . . 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, binStep = 0.0; if (logEntropy) { for (int i = 0; i < agentList.size(); i++) { WealthAgent a = (WealthAgent) agentList.get(i); if ( a.getWealth() > wealthMax ) wealthMax = a.getWealth(); } nBins = numLogEntropyBins; binStep = Math.log(wealthMax) / nBins; 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); if (a.getWealth() <= 1.0) agentCounts[0]++; else agentCounts[(int) Math.floor(Math.log(a.getWealth())/(binStep + 1.0))]++; } 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; } else { 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; StDAvg[stepModMAvgRange] = calcSD; calcSD = 0.0; for (int i = 0; i < MAvgRange; i++) calcSD = calcSD + StDAvg[i]; calcSD = calcSD / MAvgRange; return calcSD; } }); } if (DeathTax) { statsGraph.addSequence("Avg. Age", new Sequence() { public double getSValue() { double totalAge = 0; for (int i = 0; i < agentList.size(); i++) { WealthAgent a = (WealthAgent)agentList.get(i); totalAge += a.getAge(); } return totalAge / agentList.size(); } }); } } if (PlotLogLog) { logLogPlot = new Plot("Log(P_i) : Log(W_i) Plot"); } if (PlotPlain) { plainPlot = new Plot("Plain Plot"); if (PlainPlotXMax > 0.0) { plainPlot.setXRange(0.0, PlainPlotXMax); } if (PlainPlotYMax > 0.0) { plainPlot.setYRange(0.0, PlainPlotYMax); } plainPlot.addLegend(1, "> 250", java.awt.Color.magenta, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(2, "> 200", java.awt.Color.pink, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(3, "> 150", java.awt.Color.red, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(4, "> 125", java.awt.Color.orange, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(5, "> 100", java.awt.Color.yellow, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(6, "> 75", java.awt.Color.green, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(7, "> 50", java.awt.Color.cyan, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(8, "> 40", java.awt.Color.blue, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(9, "> 30", java.awt.Color.lightGray, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(10, "> 20", java.awt.Color.gray, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(11, "> 10", java.awt.Color.darkGray, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); plainPlot.addLegend(12, "<= 10", java.awt.Color.black, uchicago.src.sim.analysis.plot.OpenGraph.FILLED_CIRCLE); } // if (DeathTax) { // barAge.createHistogramItem("Age", agentList, new BinDataSource() { // public double getBinValue(Object o) { // WealthAgent agent = (WealthAgent)o; // return agent.getAge(); // } // },4 ,0); // // barAge.setYRange(0, 1.0); // } //bar.createHistogramItem("Wealth", agentList, "getWealth"); // This causes the display surface to update the display whenever the // simulation run is paused or ended. The DisplaySurface now listens // for SimEvents produced by the WealthModel if ( WealthModel.Both ) { setROI(false); } addSimEventListener(dsurf); } // buildSchedule builds the schedule that changes the simulations state. // Under this scheme, a simulation is a state machine where all transitions // between states are the result of actions initiated by a schedule. private void buildSchedule() { // this is a static schedule (no need to add or replace actions) so // we can create an inner class that extends from basic action. The // execute method of the inner class will execute all the methods that // we wish to schedule on the agents and the environment. // this inner class could also be done anonymously with the // same result, but doing it this way is clearer for those // with less experience with Java. // we could also move everything in the execute method of the WealthRunner // into a method of this WealthModel class, a step() method for example, // and then schedule that as follows: // // schedule.scheduleActionBeginning(0, this, "step"); class WealthRunner extends BasicAction { public void execute() { step = step + 1; // call the birthAgents methods on this model birthAgents(); // call the shuffleAgents method on this model shuffleAgents(); // call the step method on each WealthAgent in the agentList for (int i = 0; i < agentList.size(); i++) { WealthAgent agent = (WealthAgent)agentList.get(i); agent.step(); } space.updateWealth(); // should call update display after the things that it displays // have changed their state. Otherwise, displays won't be in // synch with what it displays at end or at pause. dsurf.updateDisplay(); bar.step(); if (ViewPowerLawExp && (step > 300) && ((step % 10) == 0) ) powerlawGraph.step(); if (ViewEntropy && ((step % 10) == 0) ) entropyGraph.step(); if (ViewStats || ViewAvg || ViewStDev || ViewStDAvg) statsGraph.step(); // if (DeathTax) // barAge.step(); // recorder.record(); reapAgents(); } }; // the schedule has been created in setup() schedule.scheduleActionBeginning(0, new WealthRunner()); // On a pause in the simulation run, call the writeToFile method // on the recorder object. (Writes the data collected by the recorder // to a file. // schedule.scheduleActionAtPause(recorder, "writeToFile"); if (WriteStats) { schedule.scheduleActionAtPause(recorder, "record"); schedule.scheduleActionAtPause(recorder, "writeToFile"); // When the simulation run ends, call the writeToFile method // on the recorder object. (Writes the data collected by the recorder // to a file. schedule.scheduleActionAtEnd(recorder, "record"); schedule.scheduleActionAtEnd(recorder, "writeToFile"); } class LogLogPlot extends BasicAction { public void execute() { int i, j; double logWealth; WealthAgent agent = (WealthAgent)agentList.get(0); double min = agent.wealth; double max = agent.wealth; for (i = 1; i < agentList.size(); i++) { agent = (WealthAgent)agentList.get(i); if (agent.wealth < min) min = agent.wealth; if (agent.wealth > max) max = agent.wealth; } double logMin = Math.log(min)/Math.log(10.0); double logMax = Math.log(max)/Math.log(10.0); double binStep = (logMax - logMin) / NumLogLogBins; double[] plotBins = new double[NumLogLogBins]; for (i = 0; i < NumLogLogBins; i++) plotBins[i] = 0.0; for (i = 0; i < agentList.size(); i++) { agent = (WealthAgent)agentList.get(i); logWealth = Math.log(agent.wealth)/Math.log(10.0); j = 0; while ( logWealth > (logMin + (j + 1) * binStep)) j++; if (j < NumLogLogBins) plotBins[j] += 1.0; else plotBins[NumLogLogBins -1] += 1; } logLogPlot.clear(1); logLogPlot.clear(2); double cum = 0.0; for (i = 0; i < NumLogLogBins; i++) if (plotBins[i] > 0.0) { logLogPlot.plotPoint(logMin + (i + 0.5) * binStep, Math.log(1 - cum)/Math.log(10.0), 1); logLogPlot.plotPoint(logMin + (i + 0.5) * binStep, Math.log(plotBins[i] / agentList.size())/Math.log(10.0), 2); cum += plotBins[i] / agentList.size(); } logLogPlot.fillPlot(); logLogPlot.updateGraph(); } }; if (PlotLogLog) { schedule.scheduleActionAtInterval(100, new LogLogPlot(), Schedule.LAST); }; class PlainPlot extends BasicAction { public void execute() { int i, j; double min = MinWealth; double max; WealthAgent agent = (WealthAgent)agentList.get(0); if (PlainPlotXMax > 0.0){ max = PlainPlotXMax; } else { max = agent.wealth; for (i = 1; i < agentList.size(); i++) { agent = (WealthAgent)agentList.get(i); if (agent.wealth > max) max = agent.wealth; } } double binStep = (max - min) / NumPlainBins; double[] plotBins = new double[NumPlainBins]; for (i = 0; i < NumPlainBins; i++) plotBins[i] = 0.0; for (i = 0; i < agentList.size(); i++) { agent = (WealthAgent)agentList.get(i); j = 0; while ( (agent.wealth > (min + (j + 1) * binStep)) && (j < NumPlainBins)) j++; if (j < NumPlainBins) plotBins[j] += 1.0; // else // plotBins[NumPlainBins -1] += 1; } for (i = 1; i <= 12; i++) plainPlot.clear(i); for (i = 0; i < NumPlainBins; i++) { plotBins[i] = plotBins[i] / agentList.size(); if (plotBins[i] > 0.0) { if (PlainPlotYMax > 0.0) { if ((plotBins[i]) <= PlainPlotYMax) { if (min + (i + 0.5) * binStep > 250) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 1); else if (min + (i + 0.5) * binStep > 200) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 2); else if (min + (i + 0.5) * binStep > 150) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 3); else if (min + (i + 0.5) * binStep > 125) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 4); else if (min + (i + 0.5) * binStep > 100) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 5); else if (min + (i + 0.5) * binStep > 75) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 6); else if (min + (i + 0.5) * binStep > 50) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 7); else if (min + (i + 0.5) * binStep > 40) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 8); else if (min + (i + 0.5) * binStep > 30) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 9); else if (min + (i + 0.5) * binStep > 20) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 10); else if (min + (i + 0.5) * binStep > 10) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 11); else plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 12); } } else { if (min + (i + 0.5) * binStep > 250) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 1); else if (min + (i + 0.5) * binStep > 200) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 2); else if (min + (i + 0.5) * binStep > 150) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 3); else if (min + (i + 0.5) * binStep > 125) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 4); else if (min + (i + 0.5) * binStep > 100) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 5); else if (min + (i + 0.5) * binStep > 75) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 6); else if (min + (i + 0.5) * binStep > 50) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 7); else if (min + (i + 0.5) * binStep > 40) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 8); else if (min + (i + 0.5) * binStep > 30) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 9); else if (min + (i + 0.5) * binStep > 20) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 10); else if (min + (i + 0.5) * binStep > 10) plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 11); else plainPlot.plotPoint(min + (i + 0.5) * binStep, (plotBins[i]), 12); } } } if ((PlainPlotXMax < 0.0) || (PlainPlotYMax < 0.0)) plainPlot.fillPlot(); plainPlot.updateGraph(); } }; if (PlotPlain) { schedule.scheduleActionAtInterval(100, new PlainPlot(), Schedule.LAST); }; } // Randomize the order of the object (the WealthAgents) in the agentList public void shuffleAgents() { SimUtilities.shuffle(agentList); } // Add a new agent. public void addNewAgent() { WealthAgent agent = new WealthAgent(space, this); int x, y; do { x = Uniform.staticNextIntFromTo(0, space.getXSize() - 1); y = Uniform.staticNextIntFromTo(0, space.getYSize() - 1); } while (agentGrid.getObjectAt(x, y) != null); agentGrid.putObjectAt(x, y, agent); agent.setXY(x, y); // Use the initial simulation parameters (maxMetabolism etc.) to construct //the agents if (Sync) agent.setWealth((double) (Uniform.staticNextIntFromTo(0, SyncMax))); else agent.setWealth((double) (Uniform.staticNextIntFromTo(MinInitialWealth, MaxInitialWealth))); if (DeathTax) { agent.setMaxAge(Uniform.staticNextIntFromTo(WealthModel.MaxAge / 2, WealthModel.MaxAge)); agent.setAge(Uniform.staticNextIntFromTo(0, agent.getMaxAge())); } else agent.setAge(0); if (Smarter) if (1 == Uniform.staticNextIntFromTo(1, SmarterNum)) agent.setSmart(Normal.staticNextDouble(0.01,0.005)); agentBirth(agent); } public void agentBirth(WealthAgent agent) { // if (this.getTickCount() == 0) { // agentList.add(agent); // } else { birthList.add(agent); // } } public void birthAgents() { agentList.addAll(birthList); birthList.clear(); } // When an agent "dies" it is added to the reaperQueue public void agentDeath(WealthAgent agent) { reaperQueue.add(agent); if (replace) { addNewAgent(); } } public static WealthAgent getAgentAt(int x, int y) { return (WealthAgent)agentGrid.getObjectAt(x, y); } public void reapAgents() { ListIterator li = reaperQueue.listIterator(); while (li.hasNext()) { WealthAgent agent = (WealthAgent)li.next(); agentList.remove(agent); agentGrid.putObjectAt(agent.getX(), agent.getY(), null); } reaperQueue.clear(); } public static void moveAgent(WealthAgent agent, int x, int y) { agentGrid.putObjectAt(agent.getX(), agent.getY(), null); agentGrid.putObjectAt(x, y, agent); agent.setXY(x, y); } // When a simulation is started through SimInit, some BaseController is // created to control the running of that model. This BaseController calls // getInitParam() on the model and receives a list of initial parameters // that can be displayed for modification to the user. In order to display // the value of these parameters the controller determines if the model // has implemented get and set methods for that parameter. If so, the // controller calls the get method and displays the result to the user. A // similar process occurs when a model's initial starting parameters // are written to a data file. // // What this means is that if a user wants to display some initial starting // parameter and have this parameter be modifiable, the name of the parameter // must be returned by the getInitParam() method and the model must contain // the appropriate get and set methods. For example, to do the above for // a parameter called NumAgents, "NumAgents" must be present in the array // return by getInitParam and the model must have a getNumAgents method and a // setNumAgents method. The parameter name must match the method names minus // the "get" and "set". So "numAgents" and getNumAgents won't work, but // "NumAgents" and getNumAgents will. // // The following methods are an example of this pattern. public int getNumAgents() { return NumAgents; } public void setNumAgents(int num) { NumAgents = num; } public int getMaxInitialWealth() { return MaxInitialWealth; } public void setMaxInitialWealth(int maxInitWealth) { MaxInitialWealth = maxInitWealth; } public int getMinInitialWealth() { return MinInitialWealth; } public void setMinInitialWealth(int minInitWealth) { MinInitialWealth = minInitWealth; } public boolean getROI() { return ROI; } public void setROI(boolean newROI) { ROI = newROI; } public boolean getBoth() { return Both; } public void setBoth(boolean newBoth) { Both = newBoth; } public double getMinWealth() { return MinWealth; } public void setMinWealth(double newMinWealth) { MinWealth = newMinWealth; } public boolean getRandomWalk() { return RandomWalk; } public void setRandomWalk(boolean newRandomWalk) { RandomWalk = newRandomWalk; } public boolean getSmarter() { return Smarter; } public void setSmarter(boolean newSmarter) { Smarter = newSmarter; } public int getSmarterNum() { return SmarterNum; } public void setSmarterNum(int newSmarterNum) { SmarterNum = newSmarterNum; } public boolean getDeathTax() { return DeathTax; } public void setDeathTax(boolean newDeathTax) { DeathTax = newDeathTax; } public boolean getMoving() { return Moving; } public void setMoving(boolean newMoving) { Moving = newMoving; } public boolean getSync() { return Sync; } public void setSync(boolean newSync) { Sync = newSync; } public boolean getSyncRegion() { return SyncRegion; } public void setSyncRegion(boolean newSyncRegion) { SyncRegion = newSyncRegion; } public double getSyncLatency() { return SyncLatency; } public void setSyncLatency(double newSyncLatency) { SyncLatency = newSyncLatency; } public int getSyncMax() { return SyncMax; } public void setSyncMax(int newSyncMax) { SyncMax = newSyncMax; } public int getNumLogLogBins() { return NumLogLogBins; } public void setNumLogLogBins(int newNumLogLogBins) { NumLogLogBins = newNumLogLogBins; } public int getNumPlainBins() { return NumPlainBins; } public void setNumPlainBins(int newNumPlainBins) { NumPlainBins = newNumPlainBins; } public double getPlainPlotXMax() { return PlainPlotXMax; } public void setPlainPlotXMax(double newPlainPlotXMax) { PlainPlotXMax = newPlainPlotXMax; } public double getPlainPlotYMax() { return PlainPlotYMax; } public void setPlainPlotYMax(double newPlainPlotYMax) { PlainPlotYMax = newPlainPlotYMax; } public boolean getPlotLogLog() { return PlotLogLog; } public void setPlotLogLog(boolean newPlotLogLog) { PlotLogLog = newPlotLogLog; } public boolean getPlotPlain() { return PlotPlain; } public void setPlotPlain(boolean newPlotPlain) { PlotPlain = newPlotPlain; } public boolean getViewStats() { return ViewStats; } public void setViewStats(boolean newViewStats) { ViewStats = newViewStats; } public boolean getViewAvg() { return ViewAvg; } public void setViewAvg(boolean newViewAvg) { ViewAvg = newViewAvg; } public boolean getViewStDev() { return ViewStDev; } public void setViewStDev(boolean newViewStDev) { ViewStDev = newViewStDev; } public boolean getViewStDAvg() { return ViewStDAvg; } public void setViewStDAvg(boolean newViewStDAvg) { ViewStDAvg = newViewStDAvg; } public boolean getWriteStats() { return WriteStats; } public void setWriteStats(boolean newWriteStats) { WriteStats = newWriteStats; } public int getMaxAge() { return MaxAge; } public void setMaxAge(int newMaxAge) { MaxAge = newMaxAge; } public int getTaxPCT() { return TaxPCT; } public void setTaxPCT(int newTaxPCT) { TaxPCT = newTaxPCT; } public double getROIMean() { return ROIMean; } public void setROIMean(double newROIMean) { ROIMean = newROIMean; } public double getROIStdDev() { return ROIStdDev; } public void setROIStdDev(double newROIStdDev) { ROIStdDev = newROIStdDev; } public boolean getViewPowerLawExp() { return ViewPowerLawExp; } public void setViewPowerLawExp(boolean newViewPowerLawExp) { ViewPowerLawExp = newViewPowerLawExp; } public int getRichMinPct() { return RichMinPct; } public void setRichMinPct(int newRichMinPct) { RichMinPct = newRichMinPct; } public boolean getViewEntropy() { return ViewEntropy; } public void setentropyBin(int newentropyBin) { entropyBin = newentropyBin; } public int getentropyBin() { return entropyBin; } public void setViewEntropy(boolean newViewEntropy) { ViewEntropy = newViewEntropy; } public String getBehaviour() { return behaviour; } public void setBehaviour(String behaviour) { this.behaviour = behaviour; } public String[] getInitParam() { String[] params = {"NumAgents", "Behaviour", "Moving", "DeathTax", "TaxPCT", "MaxAge", "MaxInitialWealth", "MinInitialWealth", "MinWealth", "NumLogLogBins", "NumPlainBins", "PlainPlotXMax", "PlainPlotYMax", "PlotLogLog", "PlotPlain", "ROIMean", "ROIStdDev", "Smarter", "SmarterNum", "SyncLatency", "SyncMax", "SyncRegion", "ViewAvg", "ViewStDAvg", "ViewStDev", "ViewStats", "ViewPowerLawExp", "RichMinPct", "ViewEntropy", "entropyBin", "WriteStats" }; return params; } // Every model must have begin() and setup() methods (required for implementing // the SimModel inteface). // begin() should intialize the model for the start of a run. Consequently, // the build* methods are called here, and any displays are displayed. build() // is called whenever the start button (or the step button if the run has // not yet started) is clicked. public void begin() { buildModel(); buildDisplay(); buildSchedule(); Exchange = false; Both = false; ROI = false; RandomWalk = false; Sync = false; step = 0; if (behaviour == "Exchange") { Exchange = true; setViewPowerLawExp(false); } if (behaviour == "Both") { Both = true; ROI = true; Exchange = true; } if (behaviour == "ROI") ROI = true; if (behaviour == "RandomWalk") { RandomWalk = true; setViewPowerLawExp(false); } if (behaviour == "Sync") { Sync = true; setPlotLogLog(false); setPlotPlain(false); setViewPowerLawExp(false); setViewAvg(false); setViewStDAvg(false); setViewStDev(false); setViewStats(false); setViewEntropy(false); } dsurf.display(); bar.display(); if (ViewPowerLawExp) powerlawGraph.display(); if (ViewEntropy) entropyGraph.display(); if (ViewStats || ViewAvg || ViewStDev || ViewStDAvg) statsGraph.display(); if (PlotLogLog) { logLogPlot.display(); logLogPlot.addLegend(1, "log(1-cumul.)", java.awt.Color.green); logLogPlot.addLegend(2, "log:log plot", java.awt.Color.blue); } if (PlotPlain) { plainPlot.display(); plainPlot.setConnected(false); } // if (DeathTax) // barAge.display(); } // setup() prepares the model for another run. Called whenver the setup button // is clicked. Setup should set any objects that are created over the course // of the run to null, and dispose of any DisplaySurfaces or graphs. While // not strictly necessary this should some prevent memory leaks and calling // System.gc() helps too. The initial parameters should be set to whatever // defaults the user wants to see initially. public void setup() { schedule = null; agentList = new ArrayList(); birthList = new Vector(); space = null; agentGrid = null; reaperQueue = new Vector(); Both = false; ROI = false; RandomWalk = false; Sync = false; if (behaviour == "Both") Both = true; if (behaviour == "ROI") ROI = true; if (behaviour == "RandomWalk") RandomWalk = true; if (behaviour == "Sync") Sync = true; if (dsurf != null) dsurf.dispose(); dsurf = null; if (powerlawGraph != null) powerlawGraph.dispose(); powerlawGraph = null; if (entropyGraph != null) entropyGraph.dispose(); entropyGraph = null; if (statsGraph != null) statsGraph.dispose(); statsGraph = null; if (ViewStDAvg) for (int i = 0; i < MAvgRange; i++) StDAvg[i] = 0.0; if (bar != null) bar.dispose(); bar = null; if (logLogPlot != null) logLogPlot.dispose(); logLogPlot = null; if (plainPlot != null) plainPlot.dispose(); plainPlot = null; // if (barAge != null) // barAge.dispose(); // barAge = null; System.gc(); // create a schedule with an interval of one. schedule = new Schedule(1); dsurf = new DisplaySurface(this, "Wealth Scape"); // By registering a DisplaySurface, you are allowing Repast to automate // some tasks on the displays surface, such as making movies or taking // snapshots. registerDisplaySurface("Wealth Scape", dsurf); // creates a dynamic histogram of the distribution of wealth over the // agents. bar = new OpenHistogram("Agent Wealth Distribution", 16, 0, this); this.registerMediaProducer("Hist", bar); // barAge = new OpenHistogram("Agent Age Distribution", 16, 0, this); // this.registerMediaProducer("Hist", barAge); // agent properties // numAgents = 1600; // maxInitialWealth = 100; // minInitialWealth = 100; } // a required method public Schedule getSchedule() { return schedule; } // a required method - displayed on the Controller toolbar. public String getName() { return "WealthScape"; } public static void main(String[] args) { SimInit init = new SimInit(); WealthModel model = new WealthModel(); init.loadModel(model, "", false); } }