use of dr.evolution.coalescent.PiecewiseLinearPopulation in project beast-mcmc by beast-dev.
the class VariableCoalescentSimulator method main.
public static void main(String[] arg) throws IOException {
long startTime = System.currentTimeMillis();
Options options = new Options(arg, 0, 7);
options.getSet().addOption("g", Options.Separator.EQUALS, Options.Multiplicity.ZERO_OR_ONE);
options.getSet().addOption("n", Options.Separator.EQUALS, Options.Multiplicity.ZERO_OR_ONE);
options.getSet().addOption("p", Options.Separator.EQUALS, Options.Multiplicity.ZERO_OR_ONE);
options.getSet().addOption("se", Options.Separator.EQUALS, Options.Multiplicity.ZERO_OR_ONE);
options.getSet().addOption("ss", Options.Separator.EQUALS, Options.Multiplicity.ZERO_OR_ONE);
options.getSet().addOption("reps", Options.Separator.EQUALS, Options.Multiplicity.ZERO_OR_ONE);
options.getSet().addOption("f", Options.Multiplicity.ZERO_OR_ONE);
if (!options.check()) {
System.out.println(options.getCheckErrors());
System.out.println();
printUsage();
System.exit(1);
}
double generationTime = 1.0;
double popSizeScale = 1.0;
int n = 50;
double ss = -1;
double se = -1;
int reps = 1;
boolean timeForward = options.getSet().isSet("f");
if (options.getSet().isSet("g")) {
String g = options.getSet().getOption("g").getResultValue(0);
generationTime = Double.parseDouble(g);
System.out.println("generation time = " + g);
}
if (options.getSet().isSet("n")) {
String sampleSize = options.getSet().getOption("n").getResultValue(0);
n = Integer.parseInt(sampleSize);
System.out.println("sample size = " + n);
}
if (options.getSet().isSet("p")) {
String p = options.getSet().getOption("p").getResultValue(0);
popSizeScale = Double.parseDouble(p);
System.out.println("population size scale factor = " + p);
}
if (options.getSet().isSet("ss")) {
String sampleStart = options.getSet().getOption("ss").getResultValue(0);
ss = Double.parseDouble(sampleStart);
System.out.println("sample start time = " + ss);
}
if (options.getSet().isSet("se")) {
String sampleEnd = options.getSet().getOption("se").getResultValue(0);
se = Double.parseDouble(sampleEnd);
System.out.println("sample end time = " + se);
}
if (options.getSet().isSet("reps")) {
String replicates = options.getSet().getOption("reps").getResultValue(0);
reps = Integer.parseInt(replicates);
System.out.println("replicates = " + reps);
}
String filename = options.getSet().getData().get(0);
String outfile = options.getSet().getData().get(1);
// READ DEMOGRAPHIC FUNCTION
BufferedReader reader = new BufferedReader(new FileReader(filename));
List<Double> times = new ArrayList<Double>();
String line = reader.readLine();
String[] tokens = line.trim().split("[\t ]+");
if (tokens.length < 2)
throw new RuntimeException();
ArrayList<ArrayList> popSizes = new ArrayList<ArrayList>();
while (line != null) {
double time = Double.parseDouble(tokens[0]) / generationTime;
times.add(time);
for (int i = 1; i < tokens.length; i++) {
popSizes.add(new ArrayList<Double>());
popSizes.get(i - 1).add(Double.parseDouble(tokens[i]));
}
line = reader.readLine();
if (line != null) {
tokens = line.trim().split("[\t ]+");
if (tokens.length != popSizes.size() + 1)
throw new RuntimeException();
}
}
reader.close();
// GENERATE SAMPLE
double lastTime = times.get(times.size() - 1);
if (ss == -1) {
ss = timeForward ? lastTime : times.get(0);
}
if (se == -1) {
se = timeForward ? lastTime : times.get(0);
}
double dt = (se - ss) / ((double) n - 1.0);
double time = ss;
Taxa taxa = new Taxa();
for (int i = 0; i < n; i++) {
double sampleTime;
if (timeForward) {
sampleTime = (lastTime - time) / generationTime;
} else
sampleTime = time / generationTime;
Taxon taxon = new Taxon(i + "");
taxon.setAttribute(dr.evolution.util.Date.DATE, new Date(sampleTime, Units.Type.GENERATIONS, true));
taxa.addTaxon(taxon);
time += dt;
}
double minTheta = Double.MAX_VALUE;
double maxTheta = 0.0;
PrintWriter out = new PrintWriter(new FileWriter(outfile));
int popHistory = 0;
PiecewiseLinearPopulation[] demography = new PiecewiseLinearPopulation[popSizes.size()];
for (List<Double> popSize : popSizes) {
double[] thetas = new double[popSize.size()];
double[] intervals = new double[times.size() - 1];
for (int i = intervals.length; i >= 0; i--) {
int j = timeForward ? intervals.length - i : i - 1;
int k = timeForward ? i : intervals.length - i + 1;
if (i != 0)
intervals[j] = times.get(k) - times.get(k - 1);
double theta = popSize.get(k) * popSizeScale;
thetas[j] = theta;
if (theta < minTheta) {
minTheta = theta;
}
if (theta > maxTheta) {
maxTheta = theta;
}
//System.out.println(t + "\t" + theta);
}
System.out.println("N" + popHistory + "(t) range = [" + minTheta + ", " + maxTheta + "]");
demography[popHistory] = new PiecewiseLinearPopulation(intervals, thetas, Units.Type.GENERATIONS);
popHistory += 1;
}
CoalescentSimulator simulator = new CoalescentSimulator();
for (int i = 0; i < reps; i++) {
out.println("#rep " + i);
for (int j = 0; j < demography.length; j++) {
Tree tree = simulator.simulateTree(taxa, demography[j]);
out.println(TreeUtils.newick(tree));
//System.err.println(Tree.Utils.newick(tree));
}
}
out.flush();
out.close();
long stopTime = System.currentTimeMillis();
System.out.println("Took " + (stopTime - startTime) / 1000.0 + " seconds");
}
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