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JAva SImulatior for MAnufacturing and logistics - A framework for discrete event simulation and computer experiments with a main focus on modelling and analyzing logistic/manufacturing systems.
/*******************************************************************************
* Copyright (c) 2010-2013 Torsten Hildebrandt and jasima contributors
*
* This file is part of jasima, v1.0.
*
* jasima is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* jasima is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with jasima. If not, see
* - Raj Jain, Imrich Chlamtac: The P2 Algorithm for Dynamic Calculation of
* Quantiles and Histograms Without Storing Observations, ACM 28, 10 (1985)
*
- Kimmo Raatikainen: Simultaneous estimation of several percentiles,
* Simulations Councils (1987)
*
*
* @author Robin Kreis , 2012-09-07
* @version "$Id: QuantileEstimator.java 74 2013-01-08 17:31:49Z [email protected] $"
*/
public class QuantileEstimator extends SummaryStat implements
Iterable {
private static final long serialVersionUID = 1342062250846464757L;
/**
* Stores the
*/
protected double[] p2_q;
protected int[] p2_n;
protected double[] p2_n_increment;
/**
* Creates a QuantileEstimator and optimizes the marker positions to
* estimates the quantiles 0.1, 0.5 (the median) and 0.9 well.
*
* @param name
* the name of this {@link SummaryStat}
*/
public QuantileEstimator(String name) {
super(name);
p2_n_increment = new double[] { 0, 0.05, 0.1, 0.3, 0.5, 0.7, 0.9, 0.95,
1 };
initMarkers();
}
/**
* Creates a QuantileEstimator and optimizes the marker positions to
* estimates the given quantiles well.
*
* @see #setQuantileList(double...)
* @param name
* the name of this {@link SummaryStat}
* @param quantiles
* a list of quantiles to be estimated
*/
public QuantileEstimator(String name, double... quantiles) {
super(name);
setQuantileList(quantiles);
}
/**
* Sets a list of quantiles to be estimated. For n quantiles, 2n+3 markers
* will be created.
*/
public void setQuantileList(double... quantiles) {
Arrays.sort(quantiles);
p2_n_increment = new double[quantiles.length * 2 + 3];
// ~ is the mean of the neighbors, q is quantiles, we need:
// p2_n_increment = [0, ~, q[0], ~, q[1], ~, q[2], ~, 1]
// first, fill in all except for the mean
p2_n_increment[0] = 0.0;
for (int i = 0; i < quantiles.length; ++i) {
assert quantiles[i] > 0.0 && quantiles[i] < 1.0;
// first quantile at 2, one value inbetween:
p2_n_increment[i * 2 + 2] = quantiles[i];
}
p2_n_increment[p2_n_increment.length - 1] = 1.0;
// then, fill in the values inbetween
for (int i = 1; i < p2_n_increment.length - 1; i += 2) {
p2_n_increment[i] = (p2_n_increment[i - 1] + p2_n_increment[i + 1]) / 2;
}
initMarkers();
}
/**
* Returns a list of quantiles that are estimated well.
*
* The returned array will be equal to the one passed to
* {@link #QuantileEstimator(String, double...)} or
* {@link #setQuantileList(double...)}, if the markers haven't been modified
* afterwards.
*/
public double[] getQuantileList() {
double[] retVal = new double[(p2_n_increment.length - 3) / 2];
for (int i = 0; i < retVal.length; ++i) {
retVal[i] = p2_n_increment[i * 2 + 2];
}
return retVal;
}
/**
* Sets the number of cells of the histogram. Each cell will usually be
* plotted as a bar.
*/
public void setCellCount(int cells) {
assert cells >= 2;
p2_n_increment = new double[cells + 1];
for (int i = 0; i < p2_n_increment.length; ++i) {
p2_n_increment[i] = i / (p2_n_increment.length - 1.0);
}
initMarkers();
}
/**
* Returns the number of cells of the histogram. The returned value will be
* equal to the one passed to {@link #setCellCount(int)}, if the markers
* have't been modified afterwards.
*/
public int getCellCount() {
return p2_q.length - 1;
}
@Override
public void combine(SummaryStat other) {
throw new RuntimeException(
"QuantileEstimator.combine not implemented yet");
}
@Override
public void clear() {
if (numObs() > 0)
super.clear();
initMarkers();
}
/**
* Initializes all markers. This requires {@link #p2_n_increment} to be set.
* After this method completes, {@link #p2_n} and {@link #p2_q} will have
* the right dimensions and {@link #p2_n} will be initialized. This method
* should only be called when {@link #numObs()} would return 0. Otherwise,
* {@link #clear()} should be called.
*/
protected void initMarkers() {
assert numObs() == 0;
if (p2_n_increment != null) {
if (p2_n == null || p2_n.length != p2_n_increment.length) {
p2_n = new int[p2_n_increment.length];
}
if (p2_q == null || p2_q.length != p2_n_increment.length) {
p2_q = new double[p2_n_increment.length];
}
for (int i = 0; i < p2_n.length; ++i) {
// should this look at the desired marker pos?
p2_n[i] = i;
}
}
}
@Override
public void value(double v, double weight) {
super.value(v, weight);
int obsIdx = numObs() - 1; // first observation: 0
if (obsIdx < p2_q.length) {
// initialization
p2_q[obsIdx] = v;
if (obsIdx == p2_q.length - 1) {
// finish initialization
Arrays.sort(p2_q);
}
} else {
// usual case
int k = Arrays.binarySearch(p2_q, v);
if (k < 0) {
k = -(k + 1);
}
if (k == 0) {
p2_q[0] = v;
k = 1;
} else if (k == p2_q.length) {
k = p2_q.length - 1;
p2_q[k] = v;
}
for (int i = k; i < p2_n.length; ++i) {
++p2_n[i];
}
for (int i = 1; i < p2_q.length - 1; ++i) {
double n_ = p2_n_increment[i] * obsIdx;
double di = n_ - p2_n[i];
if ((di >= 1.0 && p2_n[i + 1] - p2_n[i] > 1)
|| ((di <= -1.0 && p2_n[i - 1] - p2_n[i] < -1))) {
int d = di < 0 ? -1 : 1;
double qi_ = quadPred(d, i);
if (qi_ < p2_q[i - 1] || qi_ > p2_q[i + 1]) {
qi_ = linPred(d, i);
}
p2_q[i] = qi_;
p2_n[i] += d;
}
}
}
}
protected double quadPred(int d, int i) {
double qi = p2_q[i];
double qip1 = p2_q[i + 1];
double qim1 = p2_q[i - 1];
int ni = p2_n[i];
int nip1 = p2_n[i + 1];
int nim1 = p2_n[i - 1];
double a = (ni - nim1 + d) * (qip1 - qi) / (nip1 - ni);
double b = (nip1 - ni - d) * (qi - qim1) / (ni - nim1);
return qi + (d * (a + b)) / (nip1 - nim1);
}
protected double linPred(int d, int i) {
double qi = p2_q[i];
double qipd = p2_q[i + d];
int ni = p2_n[i];
int nipd = p2_n[i + d];
return qi + d * (qipd - qi) / (nipd - ni);
}
/**
* Returns all markers and their positions. Used for testing.
*
* @return the current markers formatted as a string
*/
public String getMarkers() {
Formatter fmt = new Formatter(Locale.US);
fmt.format("%5d", numObs());
fmt.format(" |");
for (int i = 0; i < p2_n.length; ++i) {
fmt.format("%8.2f", 1 + (i * (numObs() - 1)) / (p2_n.length - 1.0));
}
fmt.format(" |");
for (int n : p2_n) {
fmt.format("%5d", n + 1);
}
fmt.format(" |");
for (double q : p2_q) {
fmt.format("%8.2f", q);
}
String retVal = fmt.toString();
fmt.close();
return retVal;
}
/**
* Can be used to receive a list of {@link Bar} instances to create a
* histogram.
*/
@Override
public Iterator iterator() {
return new Iterator() {
private int bar = 0;
private Bar retVal = new Bar();
private double div = 1.0 / numObs();
@Override
public boolean hasNext() {
return bar < p2_n.length - 1;
}
@Override
public Bar next() {
retVal.minX = p2_q[bar];
retVal.maxX = p2_q[bar + 1];
retVal.area = (p2_n[bar + 1] - p2_n[bar]) * div;
++bar;
return retVal;
}
@Override
public void remove() {
assert false;
}
};
}
/**
* Formats a histogram so that a bar graph can be plotted. Each line of the
* output will represent one bar and have three columns for the middle X
* position, height and width of the bar. The area of each bar is the ratio
* of all values within the X range of the bar.
*
* Gnuplot can directly plot a bar graph using the command
* plot filename with boxes.
*
* @param fmt
* the formatter to store the output
*/
public void formatForGnuplot(Formatter fmt) {
for (Bar b : this) {
fmt.format(Locale.US, "%6.4f %6.4f %6.4f%n", (b.minX + b.maxX) / 2,
b.height(), b.width());
}
}
/**
* Estimates a quantile. If there is no marker for the quantile p, linear
* interpolation between the two closest markers is performed. If p is NaN,
* NaN will be returned. If there haven't been enough observations or the
* markers are not initialized, NaN is returned. If p <= 0.0
* or p >= 1.0, the minimum or maximum will be returned.
*
* @param p
* any number
* @return a number that is estimated to be bigger than 100p percent of all
* numbers or Double.NaN, if no data is available
*/
public double quantile(double p) {
if (Double.isNaN(p) || p2_n == null || numObs() < p2_n.length)
return Double.NaN;
if (p <= 0.0)
return p2_q[0];
if (p >= 1.0)
return p2_q[p2_q.length - 1];
int idx = Arrays.binarySearch(p2_n_increment, p);
if (idx < 0) {
int left = -idx - 2;
int right = -idx - 1;
double pl = p2_n_increment[left];
double pr = p2_n_increment[right];
return (p2_q[left] * (pr - p) + p2_q[right] * (p - pl)) / (pr - pl);
}
return p2_q[idx];
}
@Override
public String toString() {
if (p2_q.length > 10) {
return String.format(
"[10%%<%f, median: %f, 90%%<%f; %d more markers]",
quantile(0.1), quantile(0.5), quantile(0.9),
p2_q.length - 3);
}
Formatter fmt = new Formatter();
fmt.format("[");
// extract quantiles
for (int i = 2; i < p2_n_increment.length - 2; i += 2) {
if (i != 2)
fmt.format("; ");
fmt.format("%.0f%%<%f", p2_n_increment[i] * 100, p2_q[i]);
}
String retVal = fmt.format("]").toString();
fmt.close();
return retVal;
}
/**
* Represents one bar of a histogram.
*/
public class Bar {
public double minX;
public double maxX;
/**
* The estimated ratio of observations within {@link #minX} and
* {@link #maxX}.
*/
public double area;
public final double height() {
return area / width();
}
public final double width() {
return maxX - minX;
}
}
}
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