From 8ec49d35513aedccc8a6cf86db083b845ceebfa2 Mon Sep 17 00:00:00 2001 From: Marcel Kronfeld Date: Mon, 4 Aug 2008 15:22:59 +0000 Subject: [PATCH] Moving inference.metabolic to probs repository. --- .../AbstractCurveFittingProblem.java | 303 -- .../AbstractValineCurveFittingProblem.java | 195 - .../AbstractValineSplineFittingProblem.java | 81 - .../inference/metabolic/CKMMiProblem.java | 85 - .../inference/metabolic/CKMMrProblem.java | 80 - .../inference/metabolic/GMAKiProblem.java | 69 - .../inference/metabolic/GMAKrProblem.java | 70 - .../inference/metabolic/GMMiProblem.java | 111 - .../inference/metabolic/GMMrProblem.java | 85 - .../inference/metabolic/TimeSeries.java | 243 -- .../metabolic/odes/AbstractValineSystem.java | 3755 ----------------- .../inference/metabolic/odes/CKMMiSystem.java | 156 - .../inference/metabolic/odes/CKMMrSystem.java | 117 - .../inference/metabolic/odes/GMAKiSystem.java | 69 - .../inference/metabolic/odes/GMAKrSystem.java | 116 - .../inference/metabolic/odes/GMMiSystem.java | 120 - .../inference/metabolic/odes/GMMrSystem.java | 87 - 17 files changed, 5742 deletions(-) delete mode 100644 src/eva2/server/go/problems/inference/metabolic/AbstractCurveFittingProblem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/AbstractValineCurveFittingProblem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/AbstractValineSplineFittingProblem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/CKMMiProblem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/CKMMrProblem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/GMAKiProblem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/GMAKrProblem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/GMMiProblem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/GMMrProblem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/TimeSeries.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/odes/AbstractValineSystem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/odes/CKMMiSystem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/odes/CKMMrSystem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/odes/GMAKiSystem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/odes/GMAKrSystem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/odes/GMMiSystem.java delete mode 100644 src/eva2/server/go/problems/inference/metabolic/odes/GMMrSystem.java diff --git a/src/eva2/server/go/problems/inference/metabolic/AbstractCurveFittingProblem.java b/src/eva2/server/go/problems/inference/metabolic/AbstractCurveFittingProblem.java deleted file mode 100644 index 4aea0551..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/AbstractCurveFittingProblem.java +++ /dev/null @@ -1,303 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import java.io.Serializable; -import java.util.LinkedList; - -import eva2.server.go.individuals.AbstractEAIndividual; -import eva2.server.go.individuals.ESIndividualDoubleData; -import eva2.server.go.individuals.InterfaceDataTypeDouble; -import eva2.server.go.problems.AbstractOptimizationProblem; -import eva2.server.go.problems.InterfaceHasInitRange; -import eva2.tools.Mathematics; -import eva2.tools.des.RKSolver; - -/** - * This class provides a collection of methods to compare two curves one against - * the other and to optimize the parameters of a model to be fitted as close as - * possible to given measurements. - * - * @author Andreas Dräger - * @date Sept. 18 2006 - */ -public abstract class AbstractCurveFittingProblem extends - AbstractOptimizationProblem implements InterfaceHasInitRange, - Serializable { - - protected AbstractEAIndividual best = null; - - protected LinkedList metabolites; - - protected TimeSeries timeSeries; - - protected double xOffSet, noise, yOffSet; - - protected int m_ProblemDimension; - - protected double t0, t1; - - protected RKSolver solver; - - protected boolean monteCarlo = false; - - protected double[][] initRange; - - public AbstractCurveFittingProblem() { - m_Template = new ESIndividualDoubleData(); - } - - public void setIndividualTemplate(AbstractEAIndividual indy) { - m_Template = indy; - } - - /** - * This method allows you to swich to an initialization that is completely - * by chance instead of a certain more sophisticated initialization - * procedure. - * - * @param mc - * If true, a Monte Carlo initialization will be performed. Else - * another possibly more sophisticated procedure will be started. - */ - public void setMonteCarloInitialization(boolean mc) { - this.monteCarlo = mc; - } - - /** - * @param individual - */ - public void evaluate(AbstractEAIndividual individual) { - double fitness[] = this - .doEvaluation(((InterfaceDataTypeDouble) individual) - .getDoubleData()); - individual.SetFitness(fitness); - if (this.best == null) { - this.best = (AbstractEAIndividual) individual.clone(); - } else if (this.best.getFitness(0) > individual.getFitness(0)) { - this.best = (AbstractEAIndividual) individual.clone(); - } - } - - /** - * @param x - * @return - */ - public double[] doEvaluation(double[] x) { - double freturn[] = new double[1], fitness = 0; - double[][] result = model(x); - - if (result == null) { - freturn[0] = Double.MAX_VALUE; - return freturn; - } - - freturn[0] = 0; - if (this.solver != null) - if (this.solver.isUnstable()) { - freturn[0] += 10000; - } - - // for all metabolites - for (int i = 0; (i < metabolites.size()) - && (freturn[0] < Double.MAX_VALUE); i++) - try { - /* - * Metabolites, which have not been considered in the - * measurements should also be able to be simulated. They - * shouldn't contribute to the overall fitness. - */ - if (!timeSeries.containsMetabolite(metabolites.get(i) - .toString()) - || (timeSeries.numberOfMeasurements(metabolites.get(i) - .toString()) == 0)) - continue; - - double[] times = this.timeSeries.getTimes(this.metabolites.get( - i).toString()), values = this.timeSeries - .getValues(this.metabolites.get(i).toString()), mvalue = new double[times.length]; - // model - // values - - // tests: - // boolean name = false; - // for all measured times for the current metabolite - for (int j = 0, min = 0, max = result.length - 1; j < times.length; j++) { - /* - * This happens, if the parameters are that bad that the - * model function doesn't even produce sensefull values. - */ - if (result[result.length - 1][0] < times[j]) { - mvalue[j] = Math.max(10000, 10000 * values[j]); - continue; - } - - if (times[j] != result[j][0]) { - /* - * Seek the right time value from the model with an - * approach in logarithmic time. The variables min and - * max have been defined as an additional start - * condition of the for loop. - */ - int t = Math.round((max + min) / 2), t_old = t; - do { - t_old = t; - if (result[t][0] < times[j]) { - if (t < max) - min = t + 1; - else - min = t; - } else if (result[t][0] > times[j]) { - if (t > min) - max = t - 1; - else - max = t; - } else - break; - t = Math.round((max + min) / 2); - } while (t != t_old); - /* - * Set min and max for the search of the next time - * (measured times are assumed to be ordered). - */ - min = t; - max = result.length - 1; - - /* - * The model value for the i-th metabolite at time j is - * given by result[t][i+1] because the first column of - * result is the time. - */ - mvalue[j] = result[t][i + 1]; - - /* - * These steps are necessary if the resulting model - * contains more than one value for one time step. In - * this case for the fitness the model value with the - * greatest distance to the measured value should be - * considered. - */ - int up = t, down = t; - while (up < result.length - 1) - if (result[up][0] == result[up + 1][0]) - up++; - else - break; - while (down > 0) - if (result[down][0] == result[down - 1][0]) - down--; - else - break; - if (up != down) - for (int k = down; k < up; k++) - if (Math.abs(result[k][i + 1] - values[j]) > Math - .abs(mvalue[j] - values[j])) - mvalue[j] = result[k][i + 1]; - - if ((result[t][0] > times[j]) && (t > 0)) { - if (result[t - 1][0] < times[j]) { - /* - * if (!name) { - * System.out.println(metabolites.get(i)+":"); - * name=true; } System.out.println( - * result[t-1][0]+" = result["+(t-1)+"][0] < - * times["+j+"] = "+times[j]+" & " - * +result[t][0]+" = result["+t+"][0] > - * times["+j+"] = "+times[j]);// - */ - mvalue[j] = Mathematics.linearInterpolation( - times[j], result[t - 1][0], - result[t][0], result[t - 1][i + 1], - mvalue[j]); - } // otherwise we don't want to interpolate with - // the value before - // down. - } else if ((result[t][0] < times[j]) - && (t < result.length - 1)) { - if (result[t + 1][0] > times[j]) { - mvalue[j] = Mathematics.linearInterpolation( - times[j], result[t][0], - result[t + 1][0], mvalue[j], - result[t + 1][i + 1]); - } /* - * we don't want to interpolate with the value - * after up. This would propably smooth the - * error function. - */ - } - /* - * We are lucky: the model already contains this time - * point. So we just need to use the given model value. - */ - } else { - mvalue[j] = result[j][i + 1]; - } - - /* - * This also happens with bad parameter values. Give a heavy - * weight to the current metabolite. - */ - if ((mvalue[j] == Double.NaN) || (mvalue[j] < 0)) - mvalue[j] = Math.max(10000, 10000 * values[j]); - } // end for all times - - // average distance over all times - /* - * fitness = Mathematics.dist(mvalue, values, 2)/times.length; - * freturn[0] += fitness;// - */ - - // fitness = Mathematics.dist(mvalue, values, 2); - fitness = Mathematics.relDist(mvalue, values, 10000); - System.out.println(metabolites.get(i) + "\t" + fitness); - - if (!Double.isNaN(fitness) && !Double.isInfinite(fitness)) { - freturn[0] += fitness; - } else - freturn[0] += 99999999999999999.; // TODO this should be - // managed - // differently? - - } catch (Exception exc) { - exc.printStackTrace(); - } - if (Double.isInfinite(freturn[0]) - || (freturn[0] > 99999999999999999999.)) - freturn[0] = 99999999999999999999.; - return freturn; - } - - /** - * This method returns the best individual of the complete optimization - * process, which is not neccessarily identical to the best individual of - * the final population. - * - * @return best The best Individual of the complete optimization process - */ - public AbstractEAIndividual getOverallBestIndividual() { - return this.best; - } - - /** - * Computes the differential equation describing the decrease or increase of - * the current metabolite in the metabolic network. - * - * @param x - * The current parameters of the differential equation describing - * the metabolic network. - * @return - */ - public abstract double[][] model(double[] x); - - - public int getProblemDimension() { - return m_ProblemDimension; - } - - public double[][] getInitRange() { - return initRange; - } - - public void SetInitRange(double[][] initRange) { - this.initRange = initRange; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/AbstractValineCurveFittingProblem.java b/src/eva2/server/go/problems/inference/metabolic/AbstractValineCurveFittingProblem.java deleted file mode 100644 index d7fc6209..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/AbstractValineCurveFittingProblem.java +++ /dev/null @@ -1,195 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import java.io.Serializable; -import java.util.LinkedList; - -import wsi.ra.math.RNG; -import eva2.server.go.individuals.AbstractEAIndividual; -import eva2.server.go.individuals.ESIndividualDoubleData; -import eva2.server.go.individuals.InterfaceDataTypeDouble; -import eva2.server.go.populations.Population; -import eva2.server.go.problems.inference.metabolic.odes.AbstractValineSystem; -import eva2.tools.des.RKSolver; - -/** - * Super class for many simulation problems of the valine and leucine reaction - * network in C. glutamicum. - * - * @since 2.0 - * @version - * @author Andreas Dräger (draeger) - * Copyright (c) ZBiT, University of Tübingen, Germany Compiler: - * JDK 1.6.0 - * @date Sep 6, 2007 - */ -public abstract class AbstractValineCurveFittingProblem extends - AbstractCurveFittingProblem implements Serializable { - - /** - * Start values for: DHIV, IPM, AcLac, Val, Leu, KIV, KIC in this order. - */ - protected final double[] y = { 0.132, 0.0227, 0.236, 29.4, 0.209, 13.1, - 0.0741 }; - - protected AbstractValineSystem system; - - /** - * Generated serial id. - */ - private static final long serialVersionUID = -194867821991525140L; - - public AbstractValineCurveFittingProblem( - AbstractValineCurveFittingProblem avcfp) { - if (avcfp.m_Template != null) - this.m_Template = (AbstractEAIndividual) ((AbstractEAIndividual) avcfp.m_Template) - .clone(); - this.system = avcfp.system; - this.m_ProblemDimension = this.system.getNumberOfParameters(); - } - - /** - * Default constructor for simulation of the valine data. - */ - public AbstractValineCurveFittingProblem(AbstractValineSystem system) { - this.solver = new RKSolver(.01); - this.system = system; - this.m_ProblemDimension = system.getNumberOfParameters(); - solver.setWithLinearCalc(false); - m_Template = new ESIndividualDoubleData(); - } - - /* - * (non-Javadoc) - * - * @see eva2.server.go.OptimizationProblems.AbstractOptimizationProblem#initProblem() - */ - public void initProblem() { - this.best = null; - this.metabolites = new LinkedList(); - - this.timeSeries = new TimeSeries(); - - // this.metabolites.add("PYR"); // 46 - // this.metabolites.add("AKG"); // 47 - // this.metabolites.add("ALA"); // 47 - // this.metabolites.add("NAD"); // 47 - this.metabolites.add("DHIV"); // 44 - // this.metabolites.add("nadp"); // 45 - // this.metabolites.add("Glut"); // 47 - this.metabolites.add("2IPM"); // 45 - this.metabolites.add("AcLac"); // 40 - this.metabolites.add("Val"); // 46 - this.metabolites.add("Leu"); // 47 - this.metabolites.add("KIV"); // 47 - this.metabolites.add("KIC"); // 47 - - this.t0 = -3.894; - this.t1 = 20.643; - - this.xOffSet = RNG.gaussianDouble(0.1); - this.yOffSet = RNG.gaussianDouble(0.1); - this.noise = RNG.gaussianDouble(0.1); - initRange = new double[m_ProblemDimension][2]; - for (int i = 0; i < initRange.length; i++) { - initRange[i][0] = 0; - initRange[i][1] = 2; - } - this.SetInitRange(initRange); - } - - public void initPopulation(Population population) { - int i; - AbstractEAIndividual tmpIndy; - - best = null; - population.clear(); - - ((InterfaceDataTypeDouble) m_Template) - .setDoubleDataLength(initRange.length); - - // set the range - double[][] range = getParameterRanges(); - ((InterfaceDataTypeDouble) m_Template).SetDoubleRange(range); - - // for (i = 0; i < population.getPopulationSize(); i++) { - Population tmpPop = new Population(); - if (population.getPopulationSize() < 250) - tmpPop.setPopulationSize(250); - else - tmpPop.setPopulationSize(population.getPopulationSize()); - for (i = 0; i < tmpPop.getPopulationSize(); i++) { - tmpIndy = (AbstractEAIndividual) ((AbstractEAIndividual) m_Template) - .clone(); - // tmpIndy.init(this); - - // ////// B E G I N N /////////////// - int j; - double params[] = new double[m_ProblemDimension]; - - for (j = 0; j < params.length; j++) { - if (monteCarlo) - params[j] = RNG.randomDouble(range[j][0], range[j][1]); - else - params[j] = RNG.gaussianDouble(1) + 1; - if (params[j] < range[j][0]) { - params[j] = range[j][0]; - } - if (params[j] > range[j][1]) { - params[j] = range[j][1]; - } - } - - tmpIndy.initByValue(params, this); - // ////////E N D E ///////////////// - - tmpPop.add(tmpIndy); - // population.add(tmpIndy); - - // /////// B E G I N N ////////////// - ((InterfaceDataTypeDouble) tmpIndy).SetDoublePhenotype(params); - tmpIndy.resetConstraintViolation(); - params = ((InterfaceDataTypeDouble) tmpIndy).getDoubleData(); - for (j = 0; j < params.length; j++) - if ((params[j] < ((InterfaceDataTypeDouble) m_Template) - .getDoubleRange()[j][0]) - || (params[j] > ((InterfaceDataTypeDouble) m_Template) - .getDoubleRange()[j][1])) - System.out.println("Verletzung!\t" + params[j]);// */ - if (tmpIndy.violatesConstraint()) - System.out.println("Constraint violation: " - + tmpIndy.getConstraintViolation()); - // ////// E N D E ///////////////// - } - tmpPop.init(); - - for (i = 0; i < population.getPopulationSize(); i++) - population.add(tmpPop.remove(tmpPop.getIndexOfBestIndividual())); - population.init(); - } - - /** - * This method returns a matrix whose number of lines equals the number of - * parameters and which has two columns. In each line of this matrix the - * lower and the upper bound for the corresponding parameter are defined. - * - * @return - */ - protected abstract double[][] getParameterRanges(); - - /* - * (non-Javadoc) - * - * @see simulation.AbstractCurveFittingProblem#model(double[]) - */ - public double[][] model(double[] x) { - try { - system.setParameters(x); - return solver.solveAtTimePointsIncludingTime(system, y, - this.timeSeries.getTimes()); - } catch (Exception e) { - e.printStackTrace(); - return null; - } - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/AbstractValineSplineFittingProblem.java b/src/eva2/server/go/problems/inference/metabolic/AbstractValineSplineFittingProblem.java deleted file mode 100644 index 391f3fed..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/AbstractValineSplineFittingProblem.java +++ /dev/null @@ -1,81 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import java.io.Serializable; - -import eva2.server.go.individuals.AbstractEAIndividual; -import eva2.server.go.individuals.InterfaceDataTypeDouble; -import eva2.server.go.problems.inference.metabolic.odes.AbstractValineSystem; - -// Created at 2007-01-23 - -/** - * @author Andreas Dräger - */ -public abstract class AbstractValineSplineFittingProblem extends - AbstractValineCurveFittingProblem implements Serializable { - - /** - * Default Serial Verison ID - */ - private static final long serialVersionUID = 1L; - - /** - * Constructor - * - * @param s - */ - public AbstractValineSplineFittingProblem(AbstractValineSystem s) { - super(s); - } - - public AbstractValineSplineFittingProblem(GMAKiProblem problem) { - super(problem); - } - - @Override - public void evaluate(AbstractEAIndividual individual) { - double fitness[] = new double[] { 0 }, result[][] = model(((InterfaceDataTypeDouble) individual) - .getDoubleData()); - - if (result == null) { - fitness[0] = Double.MAX_VALUE; - } else { - - if (solver != null) - if (solver.isUnstable()) { - fitness[0] += 10000; - } - - for (int i = 0; i < result.length; i++) { // for all times - double spline[] = new double[] { // get the spline values at - // the - // current time point. - system.getDHIV(result[i][0]), - system.getIPM(result[i][0]), - system.getAcLac(result[i][0]), - system.getVal(result[i][0]), - system.getLeu(result[i][0]), - system.getKIV(result[i][0]), - system.getKIC(result[i][0]) }; - for (int j = 1; j < result[i].length - && (fitness[0] < Double.MAX_VALUE); j++) - // for all metabolites - if (spline[j - 1] != 0) - fitness[0] += Math - .pow( - ((result[i][j] - spline[j - 1]) / spline[j - 1]), - 2); - else - fitness[0] += 10000; - } - } - - individual.SetFitness(fitness); - if (this.best == null) { - this.best = (AbstractEAIndividual) individual.clone(); - } else if (this.best.getFitness(0) > individual.getFitness(0)) { - this.best = (AbstractEAIndividual) individual.clone(); - } - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/CKMMiProblem.java b/src/eva2/server/go/problems/inference/metabolic/CKMMiProblem.java deleted file mode 100644 index 31690bef..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/CKMMiProblem.java +++ /dev/null @@ -1,85 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import eva2.server.go.problems.inference.metabolic.odes.CKMMiSystem; -import eva2.server.go.strategies.InterfaceOptimizer; - -/** - * Created at 2007-02-04 - * - * @author Andreas Dräger - */ -public class CKMMiProblem extends AbstractValineCurveFittingProblem { - - /** - * Generated serial id. - */ - private static final long serialVersionUID = 3459101339325025847L; - - public CKMMiProblem() { - super(new CKMMiSystem()); - } - - public CKMMiProblem(CKMMiProblem ckmmiProblem) { - super(ckmmiProblem); - } - - public String getName() { - return "CKMMiProblem"; - } - - protected double[][] getParameterRanges() { - int i; - double[][] range = new double[m_ProblemDimension][2]; - for (i = 0; i < 9; i++) { // double[] kcat = new double[9]; // -> - // p[0..9] - range[i][0] = 0; - range[i][1] = 2000; - } - for (i = 9; i < 12; i++) { // double[] ki = new double[3]; // -> - // p[9..11] - range[i][0] = 0; - range[i][1] = 2000; - } - for (i = 12; i < 28; i++) { // double[] km = new double[16]; // -> - // p[12..27] - range[i][0] = 1E-8; - range[i][1] = 2000; - } - for (i = 28; i < 31; i++) { // double[] vm = new double[3]; // -> - // p[28..30] - range[i][0] = 0; - range[i][1] = 2000; - } - for (i = 31; i < 34; i++) { // double[] kmm = new double[3]; // -> - // p[31..33] - range[i][0] = 1E-8; - range[i][1] = 2000; - } - for (i = 34; i < 37; i++) { // double[] kia = new double[3]; // -> - // p[34..36] - range[i][0] = 0; - range[i][1] = 1E+8; - } - for (i = 37; i < 40; i++) { // double[] kib = new double[3]; // -> - // p[37..39] - range[i][0] = 0; - range[i][1] = 1E+8; - } - range[40][0] = 1E-8; // double acCoA = 0; // -> p[40] - range[40][1] = 2000; - return range; - } - - @Override - public Object clone() { - return new CKMMiProblem(this); - } - - public String getStringRepresentationForProblem(InterfaceOptimizer opt) { - return "Parameter optimization problem for the valine and leucine biosynthesis" - + " in C. glutamicum, where 7 reactions are modeled using convenience kinetics" - + " and 3 reactions with Michaelis Menten kinetics. Only two reactions" - + " are considered reversible."; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/CKMMrProblem.java b/src/eva2/server/go/problems/inference/metabolic/CKMMrProblem.java deleted file mode 100644 index 6a0e0fd9..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/CKMMrProblem.java +++ /dev/null @@ -1,80 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import eva2.server.go.problems.InterfaceMultimodalProblem; -import eva2.server.go.problems.inference.metabolic.odes.CKMMrSystem; -import eva2.server.go.strategies.InterfaceOptimizer; - -/** - * This class is a problem of the valine/leucine biosynthesis in C. glutamicum - * and uses a combination of Michaelis-Menten and Convenience Kinetic, both - * reversible. - * - * @date 2007-02-05 - * @author Andreas Dräger - */ -public class CKMMrProblem extends AbstractValineCurveFittingProblem implements - InterfaceMultimodalProblem { - - /** - * - */ - private static final long serialVersionUID = -3120557413810402464L; - - public CKMMrProblem() { - super(new CKMMrSystem()); - } - - public CKMMrProblem(CKMMrProblem ckmmrprob) { - super(ckmmrprob); - } - - public String getName() { - return "CKMMrProblem"; - } - - /* - * (non-Javadoc) - * @see eva2.server.go.problems.inference.metabolic.AbstractValineCurveFittingProblem#getParameterRanges() - */ - public double[][] getParameterRanges() { - int i; - - // double[] kcat = null, // <- params[0..6] - // bcat = null, // <- params[7..13] - // km = null, // <- params[14..43] - // ki = null, // <- params[44..46] - // vm = null, // <- params[47..50] - // kia = null, // <- params[51..53] - // kib = null; // 50) && (i < 57)) - range[i][1] = 1E+8; - else - range[i][1] = 2000; - } - return range; - } - - @Override - public Object clone() { - return new CKMMrProblem(this); - } - - public String getStringRepresentationForProblem(InterfaceOptimizer opt) { - return "Parameter optimization problem for the valine and leucine biosynthesis" - + " in C. glutamicum, where 7 reactions are modeled using convenience kinetics" - + " and 3 reactions with Michaelis Menten kinetics. Only two reactions" - + " are considered irreversible."; - } -} diff --git a/src/eva2/server/go/problems/inference/metabolic/GMAKiProblem.java b/src/eva2/server/go/problems/inference/metabolic/GMAKiProblem.java deleted file mode 100644 index 771cd3cf..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/GMAKiProblem.java +++ /dev/null @@ -1,69 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import eva2.server.go.problems.inference.metabolic.odes.GMAKiSystem; -import eva2.server.go.strategies.InterfaceOptimizer; - -// Created at 2007-02-02 - -/** - * @author Andreas Dräger - */ -public class GMAKiProblem extends AbstractValineSplineFittingProblem { - - /** - * Generated serial version id. - */ - private static final long serialVersionUID = -3635573692736142863L; - - /** - * Default constructor for simulation of the valine data. - */ - public GMAKiProblem() { - super(new GMAKiSystem()); - m_ProblemDimension = system.getNumberOfParameters(); - } - - public GMAKiProblem(GMAKiProblem gmakiProblem) { - super(gmakiProblem); - this.m_ProblemDimension = system.getNumberOfParameters(); - } - - public String getName() { - return "GMAKiProblem"; - } - - /* - * (non-Javadoc) - * @see eva2.server.go.problems.inference.metabolic.AbstractValineCurveFittingProblem#getParameterRanges() - */ - protected double[][] getParameterRanges() { - int i; - // set the range - double[][] range = new double[this.m_ProblemDimension][2]; - for (i = 0; i < 12; i++) { - range[i][0] = 0; - range[i][1] = 2000; - } - for (i = 12; i < this.m_ProblemDimension; i++) { - range[i][0] = 0; - range[i][1] = 8; - } - return range; - } - - /* - * (non-Javadoc) - * - * @see eva2.server.go.problems.AbstractOptimizationProblem#clone() - */ - public Object clone() { - return new GMAKiProblem(this); - } - - public String getStringRepresentationForProblem(InterfaceOptimizer opt) { - return "Parameter optimization problem for the valine and leucine biosynthesis" - + " in C. glutamicum, where all reactions are modeled using generalized" - + " mass-action kinetics. Only two reactions are considered irreversible."; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/GMAKrProblem.java b/src/eva2/server/go/problems/inference/metabolic/GMAKrProblem.java deleted file mode 100644 index 1a79636e..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/GMAKrProblem.java +++ /dev/null @@ -1,70 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import eva2.server.go.problems.InterfaceMultimodalProblem; -import eva2.server.go.problems.inference.metabolic.odes.GMAKrSystem; -import eva2.server.go.strategies.InterfaceOptimizer; - -/** - * In this problem, the valine/leucine reaction network in C. glutamicum is - * simulated using a generalized mass-action approach. - * - * @since 2.0 - * @version - * @author Andreas Dräger (draeger) - * Copyright (c) ZBiT, University of Tübingen, Germany Compiler: - * JDK 1.6.0 - * @date Sep 6, 2007 - */ -public class GMAKrProblem extends AbstractValineCurveFittingProblem implements - InterfaceMultimodalProblem { - - /** - * Generated id. - */ - private static final long serialVersionUID = 3423204672190772267L; - - /** - * Default constructor for simulation of the valine data. - */ - public GMAKrProblem() { - super(new GMAKrSystem()); - } - - public GMAKrProblem(GMAKrProblem gmakrprob) { - super(gmakrprob); - } - - public String getName() { - return "GMAKrProblem"; - } - - /* - * (non-Javadoc) - * @see eva2.server.go.problems.inference.metabolic.AbstractValineCurveFittingProblem#getParameterRanges() - */ - protected double[][] getParameterRanges() { - int i; - double[][] range = new double[m_ProblemDimension][2]; - for (i = 0; i < 18; i++) { - range[i][0] = 0; - range[i][1] = 2000; - } - for (i = 18; i < m_ProblemDimension; i++) { - range[i][0] = 0; - range[i][1] = 2000; - } - return range; - } - - @Override - public Object clone() { - return new GMAKrProblem(this); - } - - public String getStringRepresentationForProblem(InterfaceOptimizer opt) { - return "Parameter optimization problem for the valine and leucine biosynthesis" - + " in C. glutamicum, where all reactions are modeled using generalized" - + " mass-action kinetics. Only two reactions are considered irreversible."; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/GMMiProblem.java b/src/eva2/server/go/problems/inference/metabolic/GMMiProblem.java deleted file mode 100644 index 4ee6fad6..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/GMMiProblem.java +++ /dev/null @@ -1,111 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import eva2.server.go.problems.inference.metabolic.odes.GMMiSystem; -import eva2.server.go.strategies.InterfaceOptimizer; - -// Created at 2007-01-18 - -/** - * @author Andreas Dräger - */ -public class GMMiProblem extends AbstractValineCurveFittingProblem { - - /** - * Generated serial id. - */ - private static final long serialVersionUID = -7344294007783094303L; - - public GMMiProblem() { - super(new GMMiSystem()); - } - - public GMMiProblem(GMMiProblem gmmiproblem) { - super(gmmiproblem); - this.m_ProblemDimension = system.getNumberOfParameters(); - } - - public String getName() { - return "GMMiProblem"; - } - - /* - * (non-Javadoc) - * - * @see eva2.server.go.problems.inference.metabolic.AbstractValineCurveFittingProblem#getParameterRanges() - */ - protected double[][] getParameterRanges() { - int i; - double[][] range = new double[m_ProblemDimension][2]; - - // BRENDA: k+1 k+2 k+4 k+5 k+7 k+8 k+9 l1 l2 Ki1 Ki2 Ki3 vm1 vm2 vm3 - // kia1 - // kia2 kia3 kib1 kib2 kib3 km1 km2 km3 - double[] min = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, - 0, 0, 0, 1E-8, 1E-8, 1E-8 }, max = { 2000, 2000, 2000, 2000, - 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, - 2000, 1E+8, 1E+8, 1E+8, 1E+8, 1E+8, 1E+8, 2000, 2000, 2000 }; - - /* - * for (i = 0; i < 7; i++) { // k, rate constants for forward reaction - * range[i][0] = 0.01; range[i][1] = 2000; } for (i = 7; i < 9; i++) { // - * l, rate constants for backward reaction range[i][0] = 0.01; - * range[i][1] = 2000; } for (i = 9; i < 12; i++) { // ki, Rate constant - * for inhibition of uncertain mechanism range[i][0] = 0.01; range[i][1] = - * 100; } for (i = 12; i < 15; i++) { // vm, Maximal reaction velocity - * range[i][0] = 0.1; range[i][1] = 2000; } for (i = 15; i < 18; i++) { // - * kia' == km/kia, Rate constant for inhibition of the enzyme - * range[i][0] = 0; range[i][1] = 100; } for (i = 18; i < 21; i++) { // - * kib' == 1/kib, Rate constant for inhibition of the enzyme substrate - * complex range[i][0] = 0; range[i][1] = 100; } for (i = 21; i < 24; - * i++) { // km, the Michaelis-Menten constant range[i][0] = 0.01; - * range[i][1] = 2000; } // AcCo, Constant specifying the concentration - * of Acetyl-CoA // This is not needed because p_4 already includes - * Acetyl-CoA implicitely. //range[24][0] = 0.01; //range[24][1] = 100; // - */ - for (i = 0; i < range.length; i++) { - range[i][0] = min[i]; - range[i][1] = max[i]; - } - - /* - * double initial[] = new double[] { 15.625991725476922, 2000.0, 0.0010, - * 0.0010, 0.0014167666438540366, 0.03914648793059087, - * 0.0012346931715111, 0.0010, 0.002922248833329009, 50.00050096623751, - * 25.00075000582071, 87.5001338911313, 0.0010, 0.0010, 0.0010, - * 99.99692409764904, 99.9470190144952, 100.0, 99.99999925494194, - * 99.99994374811648, 99.9999922933057, 2000.0, 1999.9999939464062, - * 2000.0, - * - * 30.76270291064184, 1000.0004988358473, 0.0010, 0.0010, - * 0.0017147897187887668, 0.04677587864891996, 0.0010852159729891494, - * 0.0010, 0.0025497199896605963, 96.87503280922212, 12.500875002910353, - * 93.75044398773962, 0.0010, 0.0010, 0.0010, 99.9999962747097, - * 99.98389044776184, 100.0, 99.90234374997726, 99.9999973224476, - * 99.99389646109051, 1999.9999701976926, 1999.9999664724041, 2000.0 - * - * - * //10.773224990548886, 505.8899553355387, 0.0010, 0.0010, 0.0010, - * 0.0010, 0.0010, 0.0010, 0.0010, 100.0, //100.0, 100.0, 0.0010, - * 0.0010, 0.0010, 100.0, 0.0, 100.0, 100.0, 100.0, 0.0, 2000.0, 2000.0, - * 2000.0, - * - * //0.016, 6.1, 0.001, 0.001, 0.001, 0.01, 0.005, 0.7, 0.011, 0.011, - * 0.012, 35.3, 0.4, 0.001, 0.001, 0.001, 5, 5, 0.001, 5, 5, 10.9, 5, 5 }; - * double choice = RandomNumberGenerator.randomDouble(0, 1);// - */ - return range; - } - - @Override - public Object clone() { - return new GMMiProblem(this); - } - - public String getStringRepresentationForProblem(InterfaceOptimizer opt) { - return "Parameter optimization problem for the valine and leucine biosynthesis" - + " in C. glutamicum, where 7 reactions are modeled using generalized" - + " mass-action kinetics and 3 reactions using Michaelis-Menten kinetics. " - + "Only two reactions are considered reversible."; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/GMMrProblem.java b/src/eva2/server/go/problems/inference/metabolic/GMMrProblem.java deleted file mode 100644 index 94a942d2..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/GMMrProblem.java +++ /dev/null @@ -1,85 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import eva2.server.go.problems.inference.metabolic.odes.GMMrSystem; -import eva2.server.go.strategies.InterfaceOptimizer; - -/** - * Created at 2007-02-04. - * - * @author Andreas Dräger - */ -public class GMMrProblem extends AbstractValineCurveFittingProblem { - - /** - * Generated serial version id. - */ - private static final long serialVersionUID = -3889975340670999788L; - - public GMMrProblem() { - super(new GMMrSystem()); - } - - public GMMrProblem(GMMrProblem gmmrproblem) { - super(gmmrproblem); - } - - public String getName() { - return "GMMrProblem"; - } - - /* - * (non-Javadoc) - * @see eva2.server.go.problems.inference.metabolic.AbstractValineCurveFittingProblem#getParameterRanges() - */ - protected double[][] getParameterRanges() { - int i; - /* - * a // <- params[0..6] 7 b // <- params[7..13] 7 vm // <- - * params[14..17] 4 km // <- params[18..21] 4 kia // <- params[22..24] 3 - * kib // <- params[25..27] 3 ki // <- params[28..30] 3 - */ - double[][] range = new double[m_ProblemDimension][2]; - double min[] = { 0.000000000, 0.000000000, 0.000000000, 0.000000000, - 0.000000000, 0.000000000, 0.000000000, 0.000000000, - 0.000000000, 0.000000000, 0.000000000, 0.000000000, - 0.000000000, 0.000000000, 0.000000000, 0.000000000, - 0.000000000, 0.000000000, 0.000000000, 0.000000000, - 0.407343614, 0.059890210, 0.008423761, 0.000000000, - 0.000000000, 0.000000000, 0.432428055, 0.000000000, - 0.000000000, 0.000000000, 0.000000000 }; - double max[] = { 16.012590, 10.398386, 14.983890, 9.367657, 16.011989, - 7.229141, 409.395094, 3.348859, 65.532900, 424.407762, - 426.881040, 2.753995, 6.234599, 8.552800, 2.216418, 16.623249, - 1031.701261, 9.238867, 9.110233, 6.765434, 8.693675, 6.798338, - 5.628473, 5.364593, 8.438638, 9.185120, 6.459422, 12.470121, - 426.124248, 335.241456, 638.222487 }; - for (i = 0; i < range.length; i++) { - // Reaktionen, bei denen CO2 entsteht, sind wahrscheinlich - // irreversibel. - // if (i < 18) //((i == 7) || (i == 12)) - range[i][0] = min[i]; // 0; - /* - * else range[i][0] = 1E-8;/ - */ - if ((21 < i) && (i < 28)) - range[i][1] = max[i]; // 1E+8; - else - range[i][1] = max[i]; // 2000; - } - return range; - } - - - @Override - public Object clone() { - return new GMMrProblem(this); - } - - public String getStringRepresentationForProblem(InterfaceOptimizer opt) { - return "Parameter optimization problem for the valine and leucine biosynthesis" - + " in C. glutamicum, where 7 reactions are modeled using generalized" - + " mass-action kinetics and 3 reactions using Michaelis-Menten kinetics. " - + "Only two reactions are considered irreversible."; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/TimeSeries.java b/src/eva2/server/go/problems/inference/metabolic/TimeSeries.java deleted file mode 100644 index 5986b0e8..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/TimeSeries.java +++ /dev/null @@ -1,243 +0,0 @@ -package eva2.server.go.problems.inference.metabolic; - -import java.io.Serializable; -import java.util.HashMap; -import java.util.Iterator; -import java.util.Map; -import java.util.StringTokenizer; - -/** - * This class is able to parse and store the contents of a time series data - * file. These files are supposed to be a matrix, whose columns are separated by - * spaces or tabs. Every row is supposed to contain a time value in the first - * column. Every other column contains the concentration of the appropriate - * metabolite. Because the concentrations of different metabolites are not - * measured at the same time, it is possible that some values equal -1 or "NaN". - * For a given metabolite this class provides methods to extract the appropriate - * times as well as the concentration values from this file. - * - * @since 2.0 - * @version - * @author Andreas Dräger (draeger) - * Copyright (c) ZBiT, University of Tübingen, Germany Compiler: - * JDK 1.6.0 - * @date Sep 6, 2007 - */ -public class TimeSeries implements Serializable { - - /** - * - */ - private static final long serialVersionUID = 5744947450930268722L; - -String dataFile[] = new String[] { - "\"Time\" \"PYR\" \"AKG\" \"ALA\" \"NAD\" \"DHIV\" \"nadp\" \"Glut\" \"2IPM\" \"AcLac\" \"Val\" \"Leu\" \"KIV\" \"KIC\"", - "-3.894 0.69956151035 4.640691888659999 0.8149815245099999 0.43831117728999996 0.12919945973 NaN 39.91322431689 0.01634219825 0.22846321864000002 25.300234279730002 0.31457001595 13.06542276153 0.12828553615000002", - "-3.429 0.6887305946 4.4648219135 0.9733354471500001 0.46283738647 0.09269418599 0.01751164422 34.689755620279996 0.016622587119999997 0.26529057205 27.855794163480002 0.21601742448 12.27325468611 0.08806661914", - "-2.964 0.648489239 5.16446833661 1.08501337472 0.510398731 0.09668719327 0.015292064690000001 35.94424701067 0.0218616059 0.24372308822 27.512009946459997 0.19358187491999998 11.83868901432 0.08060740248 ", - "-2.499 0.66263247645 5.46655875364 1.25007291486 0.54709779337 0.27832465706 0.02017254508 42.09304165779 0.02271131235 0.31096389668 31.734637769419997 0.26547698208000003 9.74938023117 0.09527994438000001 ", - "-2.037 0.78148116407 5.01023940504 1.1274704877 0.54374513457 0.10951589105 0.023434610419999998 38.623872567220005 0.02310058527 0.23193180999000002 28.68948017027 0.27338539200999995 9.8790791622 0.06856701949 ", - "-1.572 0.7976018096 4.50327160849 0.9657423536899999 0.58804343197 0.07731788865 0.021456078269999998 39.65098562534 0.02122962586 NaN 23.23780871601 0.21372010324 7.35589658416 0.04408823098 ", - "-1.107 0.62138120097 5.527992933249999 1.11320796018 0.55468774709 0.19127059402000002 0.02151432978 37.43103867786 0.021760915119999998 0.1961057295 28.06503640484 0.25571800238 7.77390798856 0.08440327591999999 ", - "-0.642 0.61440001723 5.6582676904 1.0934342424799999 0.57892866745 0.29234911798 0.02163427084 41.73288066597 0.02358943064 0.23458068462 31.36134966529 0.28291670151 8.77177024347 0.0732470093 ", - "0.363 0.70849102753 5.6485532671600005 1.07913785266 0.5494837929699999 0.22848890345 0.03264048454 40.837490521439996 0.02034557524 0.25195151103 27.336329975730003 0.1981060288 6.68584901645 0.07329936145 ", - "0.828 0.7284264133299999 5.24081938936 1.20656221781 0.56038053457 0.50828902006 0.02799224444 43.839863948079994 0.02365648322 0.33595864068 30.40658463215 0.25328480297 7.46481961657 0.06727204061 ", - "1.293 2.35072982926 12.865197464340001 2.91425720335 0.6174561459100001 0.51680611101 0.0180555805 45.00192868082 0.02789099302 0.27282017381999996 35.47319021015 0.34012252203000004 12.4841096615 0.12075887125 ", - "1.758 1.9467590874099998 9.85083850897 2.38135380833 0.47990344534 0.36137563687 0.02083824064 39.874833705 0.02603135155 0.24703878422 35.24799025209 0.25499939033 10.58660287792 0.12011356083 ", - "2.220 1.76234822871 12.57168005228 2.535743239 0.58312865514 0.17860360497 0.018047886200000002 48.82282962176 0.02531203769 NaN 31.84083292177 0.21013809416 8.79825645884 0.10474495756 ", - "2.685 1.92439252352 11.2260038878 2.8335955021 0.49220203429 0.16592713605 0.0278326992 39.75506759172 0.02115183034 0.24700121622 29.23941353308 0.22169631684000002 8.94277598226 0.09683684583 ", - "3.150 1.92008237217 10.682979534100001 2.63737602928 0.36735949621999997 0.1546055768 0.01515236183 39.012881840679995 NaN 0.46143297886 35.812552779769995 0.28387244697 14.20243053826 0.10933158105 ", - "4.620 1.81992606678 11.067551454270001 2.70934921435 0.40725580208999995 0.24849740356 0.027964720069999997 40.42309102465 0.0170493166 0.42824885292 37.17528380543 0.33573709864 15.33969385816 0.10861095009 ", - "5.085 1.45412618172 8.37506633272 2.5510691881399996 0.5402956812899999 0.29017599822 0.029667666019999997 52.86610489844 0.01551224716 0.37018809756000004 42.07773461152 0.32912302835999996 16.97282365372 0.1127063518 ", - "5.550 1.7963431670299999 10.9951402722 3.2730762781499996 0.49909124182 0.36584625016 0.031689318279999996 49.69757534082 0.030182574599999998 0.50230756817 44.18764066063 0.34318150693 14.45568137413 0.13087029789 ", - "6.015 1.79488675167 10.58210664143 2.82815659112 0.42028499769 0.33884287302 0.02904992542 47.618463449870006 0.02065291348 0.38243112459999995 41.68555649409 0.31270596242 14.18407754513 0.12297689406000001 ", - "6.477 1.71658915979 13.051632359080001 2.86429255047 0.69044126446 0.2906864281 0.02542790495 52.905505205989996 0.0363051233 0.46612294623 51.36020781111 0.52323119427 15.99708653385 0.13462198459000002 ", - "6.942 1.70200349375 11.29511994965 2.47410519106 0.61838724543 0.74141022319 0.02954918008 52.05561320903 0.03626130189 0.36020464648 47.08381733066 0.39496256108 15.29065040412 0.12714131781000002 ", - "7.407 1.4797133761099999 10.85092666902 2.73282139173 0.60893255673 0.91712444816 0.031866304570000004 54.69762263264 0.034354864900000004 0.50457338093 42.85485451463 0.35559022922000005 11.0783278302 0.11004224548000001 ", - "7.872 1.9687388421799998 12.632535436100001 3.38129932903 0.6733727859399999 1.19712426006 0.02287925851 69.03104100976 0.0346858365 0.6115046939 52.213982982809995 0.44352030561 14.17030298056 0.11817042216 ", - "8.877 1.66191235556 10.202950777509999 2.7018080554500004 0.65431385574 0.8630518573 0.03842550936 55.18740808596 0.03100906854 0.43636326995 44.94372991982 0.39590424030000004 11.87915174242 0.12055380252 ", - "9.342 1.79446423883 9.223736902639999 2.82086676673 0.46928184702 0.25036756575999997 0.0261580927 44.218411563610005 0.02307492312 0.37136132062 34.8715067452 0.23048150172999998 9.83227607934 0.08369892896 ", - "9.807 2.02936743557 10.926146897779999 3.40942786382 0.4943626997 0.41616779600000003 0.020775668350000002 57.63290012324 0.02453204368 0.59384364452 41.567799898539995 0.37314942280999996 11.524438278929999 0.10958751164 ", - "10.272 1.96339182674 11.26182399865 3.6725323889699997 0.51033452936 0.38195138421 0.02349833226 68.82889744295 0.02130776115 0.56596184217 43.85824526299 0.3563165939 10.882216090570001 0.11761378372 ", - "10.734 1.69522699956 9.28644900764 3.09521900994 0.46748976233 0.25486955073 0.024124165519999997 56.23949510944 0.01806823073 NaN 36.05982284756 0.25298007274 8.86586676025 0.07157556397999999 ", - "11.199 1.87021691917 9.68208305253 3.2919709268000004 0.5270903229299999 0.42322311943 0.0327964463 59.54087126072 0.022691202100000002 0.47737124454999996 41.842194656909996 0.28466758982 11.91006067162 0.09872917755999999 ", - "11.664 2.23471175262 12.19887299453 3.6051454388299997 0.54389398527 0.54313316601 0.01479252184 63.04737515095 0.02776861734 0.48410774037 46.409590689800005 0.44546516811 12.6862786223 0.10475246765999999 ", - "12.129 1.58626042008 9.99097297113 3.7513050785999997 0.42925918395999996 0.44080053731999996 0.013039703409999999 54.332315720649994 0.02735050961 0.31900140121 39.37877381533 0.32147277213000003 10.09758737431 0.08824555916 ", - "13.134 1.09179740401 6.491353226309999 2.26052958713 0.5481437170200001 NaN 0.01664214786 49.99620609066 0.02341309598 NaN 32.90242406736 0.29822072293 7.4630383928 0.0570285326 ", - "13.599 1.3879954566700001 9.38597812226 3.67292411291 0.41493699655 0.35712124297000003 0.01725904447 49.842043735 0.025759816390000002 0.40749356039 36.65749859265 0.31221753187 8.49907762956 0.08041935436999999 ", - "14.064 1.46398956252 9.514586394050001 3.8008622291900003 0.48941052945 0.43946239095 0.01718538349 54.47374486523 0.02895368422 0.48952197341 40.26813532416 0.40474806982 9.42390966864 0.07994405853 ", - "14.529 1.38755206855 8.484590611449999 3.2508142214399998 0.4940005127 0.48337445569 0.01893519951 47.84282639242 0.026125384369999997 0.4407703548 41.362606442570005 0.27053364357 11.06193869222 0.1028701703 ", - "14.991 0.88675119894 6.09938485345 2.0966046727900003 0.51403159937 0.25811120551 0.0228857864 44.11169057688 0.021193232819999998 NaN 31.027494313570003 0.22906790417 7.52510837768 0.053950203 ", - "15.456 1.8352414024800001 8.469270941569999 3.3301897663099997 0.4957035248 0.26361946777 0.025116875570000002 36.08517318062 0.025039514409999998 0.38916760052 38.21581762714 0.2746950311 11.731711424339998 0.12009641433 ", - "15.921 1.3283163392300001 8.17980680802 3.0409809543 0.38135485122 0.31612171511000003 0.01517163163 32.72595199009 0.02671292861 0.34622186149 42.07802536984 0.2542175654 12.23730313735 0.13746139785 ", - "16.386 1.0127505969 4.742491586150001 1.84597095725 0.34553761760999996 NaN NaN 23.37116254961 NaN NaN NaN 0.15254582637 6.9247716185999995 0.07113160166999999 ", - "17.391 1.3310395982 7.94156759798 2.53879431682 0.48983728463 0.28795700924 0.026527055879999997 26.57827416636 0.02478540202 0.32631108383999996 33.95632215865 0.23618178628 10.48083524196 0.12515650878 ", - "17.856 0.95469028533 6.2343780867100005 2.17715476263 0.38729195765999996 0.28723013923 0.02123345169 24.49108607053 0.02618426224 0.29861161455 32.8592195428 0.2472225415 10.106162722479999 0.10923677735 ", - "18.321 NaN 5.49182392648 1.46886777519 0.34474738841999997 0.40646871383 0.01547566737 20.63720807926 0.02820014831 0.24058040600000002 40.71516409524 0.24270642545999999 14.12503277772 0.12899961175000002 ", - "18.786 0.82619105906 5.95530539146 2.299362329 0.44373946309 0.41075036223 0.02555677606 38.20802369971 0.02900285112 0.32959703389 34.213028316030005 0.25023635697 9.12222153162 0.10197379988000001 ", - "19.248 1.25881942787 6.53214282703 2.7302141736600003 0.50467802709 0.41526312678 0.02242466065 36.837815626659996 0.02483324467 0.38040913803 33.23783851764 0.23737761148 9.48079376972 0.11263783924000001 ", - "19.713 1.18507811227 5.4310205666 2.1360162267800002 0.46222885974 NaN 0.03397622205 28.19338823663 0.02104977904 NaN 25.47234120703 0.14638363385 7.60817737184 0.08542327693999999 ", - "20.178 0.98680703323 6.8729957498 2.34703189167 0.36189835991 0.35197395012 0.0170510439 26.43911126279 0.03024185129 0.30588350463 36.72827117308 0.23660664184000002 13.6943897464 0.16017717532 ", - "20.643 0.97377667062 6.15710096877 2.10492373702 0.46580796436000005 0.38984610765 0.020551778160000003 28.19084298145 0.02817732147 0.31660453741 33.563565688000004 0.17354025424 11.137671980450001 0.11278907400999999"}; - - private int dataFileLineCnt = dataFile.length; - - private Map names; - - public static void main(String args[]) { - new TimeSeries(); - } - - /** - * This constructs a new instance of this class from the given file. All - * entries of the given file are stored in a String matrix. The - * names of the metabolites are stored in a hash for easy retrival. - * - * @param fileName - */ - public TimeSeries() { - try { - int i = 0, j = 0; - this.names = new HashMap(); - StringTokenizer st = new StringTokenizer(dataFile[0]); - - // Lesen zum ersten Mal und initialisieren Matrix. - for (j = 0; st.hasMoreElements(); st.nextElement(), j++); - - String data[][] = new String[dataFileLineCnt - 1][j]; - - // Jetzt in Matrix einlesen. - for (i = 0; i < dataFileLineCnt; i++) { - j = 0; - st = new StringTokenizer(dataFile[i]); - while (st.hasMoreElements()) - if (i > 0) - data[i - 1][j++] = st.nextElement().toString(); - else names.put(st.nextElement().toString().replaceAll("\"", ""), - new Integer(j++)); - } - - /* - * for (i=0; i iter = names.keySet().iterator(); - while (iter.hasNext()) - try { - double values[][]; - int tcol = 0, count = 0; - String name = iter.next().toString(); - - i = 0; - j = ((Integer) names.get(name)).intValue(); - for (i = 0; i < data.length; i++) - if (!data[i][j].equals("-1") && !data[i][j].equals("NaN")) count++; - values = new double[2][count]; -// /* -// * The times are supposed to be the first column. However, this -// * enables the times to be any column. -// */ -// try { -// tcol = ((Integer) this.names.get("Time")).intValue(); -// } catch (Exception exc) { -// }; - for (i = 0, count = 0; i < data.length; i++) - if (!data[i][j].equals("-1") && !data[i][j].equals("NaN")) { - values[0][count] = Double.parseDouble(data[i][tcol]); - values[1][count++] = Double.parseDouble(data[i][j]); - } - names.put(name, values); - } catch (Exception exc) { - exc.printStackTrace(); - } - data = null; - } catch (Exception exc) { - exc.printStackTrace(); - } - } - - /** - * With this method one retrives the time data of the given metabolite or - * throws an exception if the given metabolite does not exist. - * - * @param metabolite - * The name of the metabolite, whose time data are desired. - * @return The time data. - * @throws Exception - * @throws If - * there is no entry for the desired metabolite, an exeption - * is thrown. - */ - public double[] getTimes(String metabolite) throws Exception { - if (names == null) System.err.println("getTimes: names is null"); - if (!names.containsKey(metabolite)) - throw new Exception("No data measured for this metabolite"); - if (names.get(metabolite) == null) System.err.println("get(metabolite) is null"); - return ((double[][]) names.get(metabolite))[0]; - } - - /** - * This method returns all measured times. - * - * @return An array containing all measurement times. - * @throws Exception - * If there is no column called "Time" in the data matrix. - */ - public double[] getTimes() throws Exception { - return getTimes("Time"); - } - - /** - * This method returns the concentration values of the given metabolite or - * throws an exception if there is no measurement for the desired metabolite. - * - * @param metabolite - * The name of the desired metabolite. - * @return an array of concentration values. - * @throws Exception - * @throws If - * there is no entry for the desired metabolite, an exception - * is thrown. - */ - public double[] getValues(String metabolite) throws Exception { - if (!names.containsKey(metabolite)) - throw new Exception("No data measured for this metabolite"); - return ((double[][]) names.get(metabolite))[1]; - } - - - /** - * With this method it can be checked wheather measurements have been - * perforemd for the given metabolite. - * - * @param name - * The name of the metabolite - * @return true if an entry for this metabolite exists or - * false otherwise. - */ - public boolean containsMetabolite(String name) { - return names.keySet().contains(name); - } - - /** - * Returns the number of measurements taken for this specific metabolite or - * zero if there are no measurements. - * - * @param name - * The name of the metabolite - * @return The number of available measurement data for this metabolite - */ - public int numberOfMeasurements(String name) { - try { - return getTimes(name).length; - } catch (Exception exc) { - return 0; - } - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/odes/AbstractValineSystem.java b/src/eva2/server/go/problems/inference/metabolic/odes/AbstractValineSystem.java deleted file mode 100644 index 62817b65..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/odes/AbstractValineSystem.java +++ /dev/null @@ -1,3755 +0,0 @@ -package eva2.server.go.problems.inference.metabolic.odes; - -import eva2.tools.des.DESystem; - -/** - * This class contains the necessary splines for selected metabolites of the - * valine/leucin reaction network in C. glutamicum. - * - * @since 2.0 - * @version - * @author Andreas Dräger (draeger) - * Copyright (c) ZBiT, University of Tübingen, Germany Compiler: - * JDK 1.6.0 - * @date - * @date 2006-12-06 - */ -public abstract class AbstractValineSystem implements DESystem { - - /** - * The metabolite concenterations in mM at the reference state transformed - * in the intervall [0,1] according to table 3 from the valine paper. - */ - protected final double pyr = 0.0430; // .689 - - protected final double akg = 0.0763; // 5.12 - - protected final double ala = 0.0787; // 1.05 - - protected final double nad = 0.5301; // .528 - - protected final double nadp = 0.1757; // .0175 - - protected final double glut = 0.3732; // 38.7 - - protected double[] p; - - /* - * (non-Javadoc) - * - * @see eva2.server.go.OptimizationProblems.InferenceRegulatoryNetworks.Des.DESystem#getDESSystemOrder() - */ - public int getDESystemDimension() { - return 7; - } - - /** - * Allows to set the parameters in this system to the designated value. - * - * @param x - * the new parameters for this system. - */ - public void setParameters(double[] params) { - if (params.length == getNumberOfParameters()) - this.p = params; - else - throw new IllegalArgumentException("This system requires exactly " - + getNumberOfParameters() + " parameters but received " - + params.length + "."); - } - - /** - * This method tells the required number of parameters of this system. - * @return - */ - public abstract int getNumberOfParameters(); - - /** - * @param v - * @return - */ - public double[] linearCombinationOfVelocities(double[] v) { - return new double[] { v[1] - v[2], // DHIV - v[6] - v[7], // 2IPM - v[0] - v[1], // AcLac - v[3] + v[4] - v[5], // Val - v[8] - v[9], // Leu - v[2] - v[3] - v[4] - v[6], // KIV - v[7] - v[8] // KIC - }; - } - - public void linearCombinationOfVelocities(double[] v, double[] res) { - res[0] = v[1] - v[2]; // DHIV - res[1] = v[6] - v[7]; // 2IPM - res[2] = v[0] - v[1]; // AcLac - res[3] = v[3] + v[4] - v[5]; // Val - res[4] = v[8] - v[9]; // Leu - res[5] = v[2] - v[3] - v[4] - v[6]; // KIV - res[6] = v[7] - v[8]; // KIC - } - - /** - * Returns the approximation spline for akg or the default value 5.12 mM - * with S=26 and all weights equal to one. - * - * @param t - * @return - */ - public double getAKG(double t) { - double y = this.akg; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.00969646 + 0.0299456 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) + 0.0624106 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.0298962 + 0.0704298 * (t + 3.429) + 8.706283e-02 - * Math.pow(t + 3.429, 2) - 0.110594 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.0703517 + 0.0796589 * (t + 2.964) - 6.721530e-02 - * Math.pow(t + 2.964, 2) - 0.0462005 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.0882142 - 0.0128204 * (t + 2.499) - 1.316651e-01 - * Math.pow(t + 2.499, 2) + 0.11841 * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.0658646 - 0.0586573 * (t + 2.037) + 3.245109e-02 - * Math.pow(t + 2.037, 2) + 0.104831 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.0561459 + 0.0395234 * (t + 1.572) + 1.786901e-01 - * Math.pow(t + 1.572, 2) - 0.194164 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.0936394 + 0.0797561 * (t + 1.107) - 9.216813e-02 - * Math.pow(t + 1.107, 2) - 0.019546 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.108832 - 0.0186393 * (t + 0.642) - 1.194349e-01 - * Math.pow(t + 0.642, 2) + 0.154951 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.126754 + 0.21081 * (t - 0.363) + 3.477431e-01 - * Math.pow(t - 0.363, 2) + 0.219188 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.32201 + 0.676393 * (t - 0.828) + 6.535099e-01 - * Math.pow(t - 0.828, 2) - 1.12127 * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.665101 + 0.556819 * (t - 1.293) - 9.106580e-01 - * Math.pow(t - 1.293, 2) + 0.691096 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.7966 + 0.158204 * (t - 1.758) + 5.342020e-02 - * Math.pow(t - 1.758, 2) - 0.288946 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.852599 + 0.0225423 * (t - 2.22) - 3.470596e-01 - * Math.pow(t - 2.22, 2) + 0.240586 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.812228 - 0.144161 * (t - 2.685) - 1.144258e-02 - * Math.pow(t - 2.685, 2) + 0.0968603 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.752458 - 0.0919719 * (t - 3.15) + 1.236776e-01 - * Math.pow(t - 3.15, 2) - 0.0669395 * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.671879 - 0.162309 * (t - 4.62) - 1.715257e-01 - * Math.pow(t - 4.62, 2) + 0.494727 * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.609059 - 0.00091066 * (t - 5.085) + 5.186183e-01 - * Math.pow(t - 5.085, 2) - 0.394601 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.681099 + 0.225436 * (t - 5.55) - 3.185070e-02 - * Math.pow(t - 5.55, 2) + 0.0649101 * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.785567 + 0.237921 * (t - 6.015) + 5.869895e-02 - * Math.pow(t - 6.015, 2) - 0.358464 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.872666 + 0.0626224 * (t - 6.477) - 4.381325e-01 - * Math.pow(t - 6.477, 2) + 0.378394 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.845096 - 0.0993862 * (t - 6.942) + 8.972702e-02 - * Math.pow(t - 6.942, 2) + 0.0910474 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.827437 + 0.0431201 * (t - 7.407) + 2.167382e-01 - * Math.pow(t - 7.407, 2) - 0.39346 * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.854792 - 0.0105413 * (t - 7.872) - 3.321390e-01 - * Math.pow(t - 7.872, 2) + 0.164397 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.675605 - 0.180004 * (t - 8.877) + 1.635190e-01 - * Math.pow(t - 8.877, 2) + 0.121832 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.639509 + 0.0510979 * (t - 9.342) + 3.334752e-01 - * Math.pow(t - 9.342, 2) - 0.371766 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.697996 + 0.120074 * (t - 9.807) - 1.851385e-01 - * Math.pow(t - 9.807, 2) - 0.0565306 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.708115 - 0.0887743 * (t - 10.272) - 2.639986e-01 - * Math.pow(t - 10.272, 2) + 0.426366 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.652797 - 0.059693 * (t - 10.734) + 3.269452e-01 - * Math.pow(t - 10.734, 2) - 0.101866 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.685492 + 0.178288 * (t - 11.199) + 1.848428e-01 - * Math.pow(t - 11.199, 2) - 0.552669 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.752796 - 0.00831021 * (t - 11.664) - 5.861302e-01 - * Math.pow(t - 11.664, 2) + 0.303168 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.652677 - 0.356754 * (t - 12.129) - 1.632107e-01 - * Math.pow(t - 12.129, 2) + 0.250424 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.383492 + 0.0739952 * (t - 13.134) + 5.918165e-01 - * Math.pow(t - 13.134, 2) - 0.603056 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.485231 + 0.233197 * (t - 13.599) - 2.494464e-01 - * Math.pow(t - 13.599, 2) - 0.0945359 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.530226 - 0.060111 * (t - 14.064) - 3.813240e-01 - * Math.pow(t - 14.064, 2) + 0.240277 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.443981 - 0.258881 * (t - 14.529) - 4.613781e-02 - * Math.pow(t - 14.529, 2) + 0.380038 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.352007 - 0.0581613 * (t - 14.991) + 4.805954e-01 - * Math.pow(t - 14.991, 2) - 0.555397 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.373036 + 0.0285202 * (t - 15.456) - 2.941836e-01 - * Math.pow(t - 15.456, 2) - 0.0154123 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.321138 - 0.255068 * (t - 15.921) - 3.156838e-01 - * Math.pow(t - 15.921, 2) + 0.629819 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.197598 - 0.140106 * (t - 16.386) + 5.629136e-01 - * Math.pow(t - 16.386, 2) - 0.326519 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.293907 + 0.00197248 * (t - 17.391) - 4.215417e-01 - * Math.pow(t - 17.391, 2) + 0.315744 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.235422 - 0.185246 * (t - 17.856) + 1.892171e-02 - * Math.pow(t - 17.856, 2) + 0.145936 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.168047 - 0.0729833 * (t - 18.321) + 2.225031e-01 - * Math.pow(t - 18.321, 2) - 0.134407 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.168707 + 0.0467579 * (t - 18.786) + 3.500489e-02 - * Math.pow(t - 18.786, 2) - 0.106218 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.187306 + 0.0110874 * (t - 19.248) - 1.122138e-01 - * Math.pow(t - 19.248, 2) + 0.203081 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.188617 + 0.0384625 * (t - 19.713) + 1.710848e-01 - * Math.pow(t - 19.713, 2) - 0.237274 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.219639 + 0.0436577 * (t - 20.178) - 1.599124e-01 - * Math.pow(t - 20.178, 2) + 0.114633 - * Math.pow(t - 20.178, 3); - - return y * (13.0516 - 4.4648) + 4.4648; - } - - /** - * Computes the approximation spline for ala or returns the default value - * 1.05 if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=5.9718 (= 2*(max(y) - min(y)) - * - * @param t - * @return - */ - public double getAla(double t) { - double y = this.ala; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.0111417 + 0.0976193 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) - 0.0137179 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.0551554 + 0.0887208 * (t + 3.429) - 1.913651e-02 - * Math.pow(t + 3.429, 2) - 0.0163295 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.0906309 + 0.0603313 * (t + 2.964) - 4.191618e-02 - * Math.pow(t + 2.964, 2) - 0.0165692 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.107956 + 0.0106012 * (t + 2.499) - 6.503016e-02 - * Math.pow(t + 2.499, 2) + 0.0299227 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.101924 - 0.0303262 * (t + 2.037) - 2.355734e-02 - * Math.pow(t + 2.037, 2) + 0.033286 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.0860752 - 0.0306427 * (t + 1.572) + 2.287664e-02 - * Math.pow(t + 1.572, 2) - 0.0105259 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.0757145 - 0.0161953 * (t + 1.107) + 8.193019e-03 - * Math.pow(t + 1.107, 2) + 0.0192259 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.0718883 + 0.00389554 * (t + 0.642) + 3.501316e-02 - * Math.pow(t + 0.642, 2) + 0.045535 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.157389 + 0.212246 * (t - 0.363) + 1.723011e-01 - * Math.pow(t - 0.363, 2) - 0.0393216 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.289386 + 0.346979 * (t - 0.828) + 1.174474e-01 - * Math.pow(t - 0.828, 2) - 0.234153 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.452583 + 0.304317 * (t - 1.293) - 2.091957e-01 - * Math.pow(t - 1.293, 2) + 0.0742497 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.556323 + 0.157928 * (t - 1.758) - 1.056173e-01 - * Math.pow(t - 1.758, 2) + 0.0351834 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.610212 + 0.0828671 * (t - 2.22) - 5.685313e-02 - * Math.pow(t - 2.22, 2) - 0.0065701 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.635791 + 0.0257318 * (t - 2.685) - 6.601841e-02 - * Math.pow(t - 2.685, 2) + 0.0430014 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.637805 - 0.00777138 * (t - 3.15) - 6.031459e-03 - * Math.pow(t - 3.15, 2) + 0.0091822 * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.642515 + 0.0340216 * (t - 4.62) + 3.446205e-02 - * Math.pow(t - 4.62, 2) - 0.000758179 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.665711 + 0.0655795 * (t - 5.085) + 3.340439e-02 - * Math.pow(t - 5.085, 2) - 0.104524 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.692919 + 0.0288435 * (t - 5.55) - 1.124066e-01 - * Math.pow(t - 5.55, 2) + 0.0559302 * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.687649 - 0.0394141 * (t - 6.015) - 3.438390e-02 - * Math.pow(t - 6.015, 2) + 0.0394099 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.665987 - 0.0459494 * (t - 6.477) + 2.023820e-02 - * Math.pow(t - 6.477, 2) + 0.0644611 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.655478 + 0.0146864 * (t - 6.942) + 1.101615e-01 - * Math.pow(t - 6.942, 2) - 0.0584419 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.680251 + 0.0792268 * (t - 7.407) + 2.863499e-02 - * Math.pow(t - 7.407, 2) - 0.105164 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.712709 + 0.0376398 * (t - 7.872) - 1.180694e-01 - * Math.pow(t - 7.872, 2) + 0.075549 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.707972 + 0.0292394 * (t - 8.877) + 1.097108e-01 - * Math.pow(t - 8.877, 2) - 0.0180929 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.743471 + 0.119534 * (t - 9.342) + 8.447119e-02 - * Math.pow(t - 9.342, 2) - 0.106349 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.806627 + 0.129106 * (t - 9.807) - 6.388543e-02 - * Math.pow(t - 9.807, 2) - 0.0296704 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.849864 + 0.0504465 * (t - 10.272) - 1.052756e-01 - * Math.pow(t - 10.272, 2) + 0.102264 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.860785 + 0.0186546 * (t - 10.734) + 3.646185e-02 - * Math.pow(t - 10.734, 2) - 0.0173023 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.875603 + 0.0413405 * (t - 11.199) + 1.232517e-02 - * Math.pow(t - 11.199, 2) - 0.0739829 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.890053 + 0.00481211 * (t - 11.664) - 9.088094e-02 - * Math.pow(t - 11.664, 2) - 0.0193171 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.870698 - 0.0922377 * (t - 12.129) - 1.178283e-01 - * Math.pow(t - 12.129, 2) + 0.119448 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.780238 + 0.0328649 * (t - 13.134) + 2.423084e-01 - * Math.pow(t - 13.134, 2) - 0.245131 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.823267 + 0.0992016 * (t - 13.599) - 9.964895e-02 - * Math.pow(t - 13.599, 2) - 0.0802879 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.839777 - 0.0455527 * (t - 14.064) - 2.116505e-01 - * Math.pow(t - 14.064, 2) + 0.116983 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.784593 - 0.166504 * (t - 14.529) - 4.845904e-02 - * Math.pow(t - 14.529, 2) + 0.155386 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.712648 - 0.111781 * (t - 14.991) + 1.669064e-01 - * Math.pow(t - 14.991, 2) - 0.193567 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.677297 - 0.0821204 * (t - 15.456) - 1.031202e-01 - * Math.pow(t - 15.456, 2) + 0.00967204 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.617786 - 0.171748 * (t - 15.921) - 8.962768e-02 - * Math.pow(t - 15.921, 2) + 0.166928 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.535327 - 0.14682 * (t - 16.386) + 1.432362e-01 - * Math.pow(t - 16.386, 2) - 0.0670531 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.464381 - 0.0620913 * (t - 17.391) - 5.892878e-02 - * Math.pow(t - 17.391, 2) + 0.0720023 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.430006 - 0.0701889 * (t - 17.856) + 4.151449e-02 - * Math.pow(t - 17.856, 2) + 0.104259 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.416827 + 0.0360499 * (t - 18.321) + 1.869560e-01 - * Math.pow(t - 18.321, 2) - 0.13932 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.460007 + 0.119546 * (t - 18.786) - 7.395260e-03 - * Math.pow(t - 18.786, 2) - 0.0936091 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.504428 + 0.0527714 * (t - 19.248) - 1.371375e-01 - * Math.pow(t - 19.248, 2) + 0.0750712 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.506862 - 0.0260696 * (t - 19.713) - 3.241318e-02 - * Math.pow(t - 19.713, 2) - 0.00426263 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.487302 - 0.058979 * (t - 20.178) - 3.835956e-02 - * Math.pow(t - 20.178, 2) + 0.0274979 - * Math.pow(t - 20.178, 3); - - return y * (3.8009 - .8150) + .8150; - } - - /** - * Computes the spline equation for pyr with the parameter S=2.5 and all - * weights equal to one. For values of t smaller or greater than the - * considered time the default steady-state value of 0.689 mM will be - * returned. - * - * @param t - * @return y the concentration of pyr at the given time t. - */ - public double getPyr(double t) { - double y = this.pyr; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.0468378 - 0.0255021 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) + 0.00825634 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.0358095 - 0.0201464 * (t + 3.429) + 1.151759e-02 - * Math.pow(t + 3.429, 2) + 0.0344174 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.0323923 + 0.0128907 * (t + 2.964) + 5.952992e-02 - * Math.pow(t + 2.964, 2) - 0.0132711 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.0499239 + 0.0596449 * (t + 2.499) + 4.101675e-02 - * Math.pow(t + 2.499, 2) - 0.0960409 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.076764 + 0.0360463 * (t + 2.037) - 9.209594e-02 - * Math.pow(t + 2.037, 2) - 0.0232984 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.0712695 - 0.0647161 * (t + 1.572) - 1.245973e-01 - * Math.pow(t + 1.572, 2) + 0.10468 * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.0247605 - 0.112688 * (t + 1.107) + 2.143171e-02 - * Math.pow(t + 1.107, 2) + 0.0271642 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = -0.0202741 - 0.0751358 * (t + 0.642) + 5.932581e-02 - * Math.pow(t + 0.642, 2) + 0.10294 * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.0686263 + 0.356024 * (t - 0.363) + 3.696886e-01 - * Math.pow(t - 0.363, 2) + 0.0489817 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.319038 + 0.731607 * (t - 0.828) + 4.380181e-01 - * Math.pow(t - 0.828, 2) - 0.897988 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.663658 + 0.556462 * (t - 1.293) - 8.146750e-01 - * Math.pow(t - 1.293, 2) + 0.359103 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.782366 + 0.031755 * (t - 1.758) - 3.137269e-01 - * Math.pow(t - 1.758, 2) + 0.302952 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.759948 - 0.064139 * (t - 2.22) + 1.061641e-01 - * Math.pow(t - 2.22, 2) - 0.0663651 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.746406 - 0.00845576 * (t - 2.685) + 1.358482e-02 - * Math.pow(t - 2.685, 2) - 0.0362597 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.741766 - 0.0193426 * (t - 3.15) - 3.699747e-02 - * Math.pow(t - 3.15, 2) + 0.00191105 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.639454 - 0.115726 * (t - 4.62) - 2.856973e-02 - * Math.pow(t - 4.62, 2) + 0.206882 * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.600265 - 0.00809734 * (t - 5.085) + 2.600302e-01 - * Math.pow(t - 5.085, 2) - 0.229079 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.629692 + 0.0851332 * (t - 5.55) - 5.953446e-02 - * Math.pow(t - 5.55, 2) - 0.0383844 * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.652547 + 0.00486712 * (t - 6.015) - 1.130807e-01 - * Math.pow(t - 6.015, 2) + 0.0637543 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.636946 - 0.0587955 * (t - 6.477) - 2.471716e-02 - * Math.pow(t - 6.477, 2) + 0.0556625 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.609858 - 0.0456756 * (t - 6.942) + 5.293199e-02 - * Math.pow(t - 6.942, 2) + 0.117416 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.61187 + 0.0797159 * (t - 7.407) + 2.167272e-01 - * Math.pow(t - 7.407, 2) - 0.30684 * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.664948 + 0.0822328 * (t - 7.872) - 2.113145e-01 - * Math.pow(t - 7.872, 2) + 0.123173 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.659189 + 0.0307141 * (t - 8.877) + 1.600521e-01 - * Math.pow(t - 8.877, 2) - 0.0857489 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.699457 + 0.123939 * (t - 9.342) + 4.043249e-02 - * Math.pow(t - 9.342, 2) - 0.159848 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.74976 + 0.0578521 * (t - 9.807) - 1.825560e-01 - * Math.pow(t - 9.807, 2) + 0.0836857 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.745602 - 0.0576401 * (t - 10.272) - 6.581435e-02 - * Math.pow(t - 10.272, 2) + 0.200744 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.72472 + 0.0100902 * (t - 10.734) + 2.124167e-01 - * Math.pow(t - 10.734, 2) - 0.18139 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.757104 + 0.0899747 * (t - 11.199) - 4.062200e-02 - * Math.pow(t - 11.199, 2) - 0.307885 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.759203 - 0.147521 * (t - 11.664) - 4.701216e-01 - * Math.pow(t - 11.664, 2) + 0.34237 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.623377 - 0.362647 * (t - 12.129) + 7.484435e-03 - * Math.pow(t - 12.129, 2) + 0.104455 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.372505 - 0.0310977 * (t - 13.134) + 3.224157e-01 - * Math.pow(t - 13.134, 2) - 0.260175 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.4016 + 0.0999801 * (t - 13.599) - 4.052806e-02 - * Math.pow(t - 13.599, 2) - 0.0959657 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.429678 + 3.84408e-05 * (t - 14.064) - 1.744002e-01 - * Math.pow(t - 14.064, 2) + 0.126879 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.404744 - 0.0798503 * (t - 14.529) + 2.596388e-03 - * Math.pow(t - 14.529, 2) + 0.278383 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.395859 + 0.100806 * (t - 14.991) + 3.884357e-01 - * Math.pow(t - 14.991, 2) - 0.614904 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.464898 + 0.0631788 * (t - 15.456) - 4.693555e-01 - * Math.pow(t - 15.456, 2) + 0.275445 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.420484 - 0.194647 * (t - 15.921) - 8.510932e-02 - * Math.pow(t - 15.921, 2) + 0.240611 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.335763 - 0.117721 * (t - 16.386) + 2.505425e-01 - * Math.pow(t - 16.386, 2) - 0.156845 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.311298 - 0.0893822 * (t - 17.391) - 2.223447e-01 - * Math.pow(t - 17.391, 2) + 0.222271 - * Math.pow(t - 17.391, 3); - else if (t <= 18.786) - y = 0.244007 - 0.151981 * (t - 17.856) + 8.772290e-02 - * Math.pow(t - 17.856, 2) + 0.0427783 - * Math.pow(t - 17.856, 3); - else if (t <= 19.248) - y = 0.212945 + 0.12218 * (t - 18.786) + 2.070743e-01 - * Math.pow(t - 18.786, 2) - 0.297219 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.284281 + 0.123198 * (t - 19.248) - 2.048717e-01 - * Math.pow(t - 19.248, 2) + 0.0274136 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.300026 - 0.0495505 * (t - 19.713) - 1.666297e-01 - * Math.pow(t - 19.713, 2) + 0.134468 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.254476 - 0.11729 * (t - 20.178) + 2.095292e-02 - * Math.pow(t - 20.178, 2) - 0.01502 - * Math.pow(t - 20.178, 3); - - return y * (2.3507 - 0.6144) + 0.6144; // Rücktransformation. - } - - /** - * Computes the approximation spline for glut or returns the default value - * 38.7 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=798.4982 (= 16.5*(max(y) - min(y))). - * - * @param t - * @return - */ - public double getGlut(double t) { - double y = this.glut; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.346152 + 0.0125877 * (t + 3.894) + 0 * Math.pow(t + 3.894, 2) - + 0.00386753 * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.352394 + 0.0150965 * (t + 3.429) + 5.395202e-03 - * Math.pow(t + 3.429, 2) - 0.000730397 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.360507 + 0.0196402 * (t + 2.964) + 4.376298e-03 - * Math.pow(t + 2.964, 2) - 0.00400789 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.370183 + 0.0211104 * (t + 2.499) - 1.214705e-03 - * Math.pow(t + 2.499, 2) + 0.00141752 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.379816 + 0.0208957 * (t + 2.037) + 7.499822e-04 - * Math.pow(t + 2.037, 2) + 0.000813723 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.389777 + 0.022121 * (t + 1.572) + 1.885125e-03 - * Math.pow(t + 1.572, 2) + 0.00104503 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.400576 + 0.0245521 * (t + 1.107) + 3.342938e-03 - * Math.pow(t + 1.107, 2) - 0.00292541 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.412421 + 0.0257634 * (t + 0.642) - 7.380070e-04 - * Math.pow(t + 0.642, 2) - 0.00118342 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.436367 + 0.0206941 * (t - 0.363) - 4.306028e-03 - * Math.pow(t - 0.363, 2) - 0.00258859 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.444798 + 0.0150103 * (t - 0.828) - 7.917118e-03 - * Math.pow(t - 0.828, 2) - 1.90838e-05 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.450064 + 0.00763503 * (t - 1.293) - 7.943740e-03 - * Math.pow(t - 1.293, 2) + 0.00394034 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.452293 + 0.00280336 * (t - 1.758) - 2.446961e-03 - * Math.pow(t - 1.758, 2) - 0.000120479 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.453054 + 0.00046522 * (t - 2.22) - 2.613945e-03 - * Math.pow(t - 2.22, 2) + 0.00947111 - * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.453657 + 0.00417793 * (t - 2.685) + 1.059826e-02 - * Math.pow(t - 2.685, 2) + 0.00512564 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.458407 + 0.0173592 * (t - 3.15) + 1.774853e-02 - * Math.pow(t - 3.15, 2) - 0.000709047 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.520026 + 0.0649433 * (t - 4.62) + 1.462163e-02 - * Math.pow(t - 4.62, 2) - 0.00895174 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.552486 + 0.0727347 * (t - 5.085) + 2.133952e-03 - * Math.pow(t - 5.085, 2) - 0.0005377 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.586715 + 0.0743704 * (t - 5.55) + 1.383860e-03 - * Math.pow(t - 5.55, 2) + 0.000484168 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.621645 + 0.0759715 * (t - 6.015) + 2.059275e-03 - * Math.pow(t - 6.015, 2) - 0.00426907 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.656762 + 0.0751406 * (t - 6.477) - 3.857662e-03 - * Math.pow(t - 6.477, 2) - 0.00352595 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.690514 + 0.0692658 * (t - 6.942) - 8.776359e-03 - * Math.pow(t - 6.942, 2) - 0.00658733 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.720163 + 0.0568308 * (t - 7.407) - 1.796568e-02 - * Math.pow(t - 7.407, 2) - 0.00779921 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.74192 + 0.0350635 * (t - 7.872) - 2.884559e-02 - * Math.pow(t - 7.872, 2) + 0.0113354 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.759531 + 0.0114309 * (t - 8.877) + 5.330512e-03 - * Math.pow(t - 8.877, 2) + 0.00795504 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.766798 + 0.0215485 * (t - 9.342) + 1.642779e-02 - * Math.pow(t - 9.342, 2) - 0.0127692 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.779087 + 0.0285432 * (t - 9.807) - 1.385314e-03 - * Math.pow(t - 9.807, 2) - 0.0138529 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.790667 + 0.0182689 * (t - 10.272) - 2.071006e-02 - * Math.pow(t - 10.272, 2) + 0.00135784 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.794821 + 2.26621e-06 * (t - 10.734) - 1.882810e-02 - * Math.pow(t - 10.734, 2) - 0.0030271 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.790446 - 0.0194715 * (t - 11.199) - 2.305090e-02 - * Math.pow(t - 11.199, 2) - 0.00202981 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.776204 - 0.0422255 * (t - 11.664) - 2.588248e-02 - * Math.pow(t - 11.664, 2) + 0.00539561 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.751515 - 0.0627962 * (t - 12.129) - 1.835561e-02 - * Math.pow(t - 12.129, 2) + 0.00129954 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.671184 - 0.0957533 * (t - 13.134) - 1.443750e-02 - * Math.pow(t - 13.134, 2) - 0.00348381 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.623187 - 0.11144 * (t - 13.599) - 1.929741e-02 - * Math.pow(t - 13.599, 2) - 0.00494472 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.566697 - 0.132594 * (t - 14.064) - 2.619529e-02 - * Math.pow(t - 14.064, 2) + 0.00487863 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.499868 - 0.153791 * (t - 14.529) - 1.938961e-02 - * Math.pow(t - 14.529, 2) + 0.00949794 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.425614 - 0.165625 * (t - 14.991) - 6.225460e-03 - * Math.pow(t - 14.991, 2) + 0.0139063 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.348651 - 0.162394 * (t - 15.456) + 1.317376e-02 - * Math.pow(t - 15.456, 2) + 0.0117237 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.277164 - 0.142538 * (t - 15.921) + 2.952836e-02 - * Math.pow(t - 15.921, 2) + 0.00969481 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.218244 - 0.108788 * (t - 16.386) + 4.305262e-02 - * Math.pow(t - 16.386, 2) - 0.00229767 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.150064 - 0.029214 * (t - 17.391) + 3.612515e-02 - * Math.pow(t - 17.391, 2) - 0.0043217 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.143856 + 0.00157903 * (t - 17.856) + 3.009639e-02 - * Math.pow(t - 17.856, 2) - 0.00908315 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.150185 + 0.0236767 * (t - 18.321) + 1.742540e-02 - * Math.pow(t - 18.321, 2) - 0.0202182 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.16293 + 0.0267673 * (t - 18.786) - 1.077895e-02 - * Math.pow(t - 18.786, 2) - 0.00537863 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.172465 + 0.0133634 * (t - 19.248) - 1.823373e-02 - * Math.pow(t - 19.248, 2) + 0.0066547 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.175405 + 0.000722759 * (t - 19.713) - 8.950425e-03 - * Math.pow(t - 19.713, 2) + 0.00522627 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.174332 - 0.00421098 * (t - 20.178) - 1.659774e-03 - * Math.pow(t - 20.178, 2) + 0.0011898 - * Math.pow(t - 20.178, 3); - - return y * (69.0310 - 20.6372) + 20.6372; - } - - /** - * Computes the approximation spline for nadp or returns the default value - * 0.0175 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=0.0003 - * - * @param t - * @return - */ - public double getNADP(double t) { - double y = this.nadp; - - if ((-3.429 <= t) && (t <= -2.964)) - y = 0.152191 - 0.100851 * (t + 3.429) + 0 * Math.pow(t + 3.429, 2) - + 0.359178 * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.141409 + 0.132138 * (t + 2.964) + 5.010527e-01 - * Math.pow(t + 2.964, 2) - 0.430333 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.267926 + 0.318971 * (t + 2.499) - 9.926155e-02 - * Math.pow(t + 2.499, 2) - 0.234737 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.370956 + 0.0769439 * (t + 2.037) - 4.246067e-01 - * Math.pow(t + 2.037, 2) + 0.342541 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.349365 - 0.0957427 * (t + 1.572) + 5.323777e-02 - * Math.pow(t + 1.572, 2) + 0.0754021 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.323937 + 0.00267988 * (t + 1.107) + 1.584237e-01 - * Math.pow(t + 1.107, 2) + 0.223708 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.381931 + 0.295128 * (t + 0.642) + 4.704962e-01 - * Math.pow(t + 0.642, 2) - 0.426272 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.721049 - 0.0508122 * (t - 0.363) - 8.147149e-01 - * Math.pow(t - 0.363, 2) + 0.339015 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.555345 - 0.588587 * (t - 0.828) - 3.417892e-01 - * Math.pow(t - 0.828, 2) + 0.843539 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.292562 - 0.359268 * (t - 1.293) + 8.349473e-01 - * Math.pow(t - 1.293, 2) - 0.579768 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.247747 + 0.0411519 * (t - 1.758) + 2.617095e-02 - * Math.pow(t - 1.758, 2) + 0.311203 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.303033 + 0.264607 * (t - 2.22) + 4.574978e-01 - * Math.pow(t - 2.22, 2) - 1.27356 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.396948 - 0.136044 * (t - 2.685) - 1.319114e+00 - * Math.pow(t - 2.685, 2) + 1.5105 * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.200335 - 0.382996 * (t - 3.15) + 7.880343e-01 - * Math.pow(t - 3.15, 2) - 0.244541 * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.563404 + 0.348539 * (t - 4.62) - 2.903913e-01 - * Math.pow(t - 4.62, 2) + 0.122972 * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.675049 + 0.158244 * (t - 5.085) - 1.188447e-01 - * Math.pow(t - 5.085, 2) - 0.177319 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.705106 - 0.0673041 * (t - 5.55) - 3.662051e-01 - * Math.pow(t - 5.55, 2) + 0.265379 * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.62131 - 0.23573 * (t - 6.015) + 3.998480e-03 - * Math.pow(t - 6.015, 2) + 0.405744 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.553267 + 0.0277755 * (t - 6.477) + 5.663602e-01 - * Math.pow(t - 6.477, 2) - 0.572376 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.631094 + 0.183205 * (t - 6.942) - 2.321041e-01 - * Math.pow(t - 6.942, 2) - 0.283917 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.637551 - 0.216822 * (t - 7.407) - 6.281689e-01 - * Math.pow(t - 7.407, 2) + 1.27563 * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.529161 + 0.026452 * (t - 7.872) + 1.151340e+00 - * Math.pow(t - 7.872, 2) - 0.845774 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.860103 - 0.222113 * (t - 8.877) - 1.398668e+00 - * Math.pow(t - 8.877, 2) + 1.2507 * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.580145 - 0.711574 * (t - 9.342) + 3.460638e-01 - * Math.pow(t - 9.342, 2) + 0.300835 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.354338 - 0.194591 * (t - 9.807) + 7.657292e-01 - * Math.pow(t - 9.807, 2) - 0.442497 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.384933 + 0.230501 * (t - 10.272) + 1.484461e-01 - * Math.pow(t - 10.272, 2) - 0.0370582 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.519455 + 0.343936 * (t - 10.734) + 9.708344e-02 - * Math.pow(t - 10.734, 2) - 1.27811 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.57187 - 0.394852 * (t - 11.199) - 1.685874e+00 - * Math.pow(t - 11.199, 2) + 1.81482 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.206206 - 0.785485 * (t - 11.664) + 8.458034e-01 - * Math.pow(t - 11.664, 2) - 0.240625 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = -0.000354184 - 0.154975 * (t - 12.129) + 5.101319e-01 - * Math.pow(t - 12.129, 2) - 0.235317 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.120277 + 0.157362 * (t - 13.134) - 1.993487e-01 - * Math.pow(t - 13.134, 2) + 0.0888371 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.159278 + 0.0295938 * (t - 13.599) - 7.542095e-02 - * Math.pow(t - 13.599, 2) + 0.192695 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.176106 + 0.0844486 * (t - 14.064) + 1.933881e-01 - * Math.pow(t - 14.064, 2) + 0.000891114 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.257279 + 0.264878 * (t - 14.529) + 1.946312e-01 - * Math.pow(t - 14.529, 2) - 0.374409 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.384275 + 0.204971 * (t - 14.991) - 3.242994e-01 - * Math.pow(t - 14.991, 2) - 0.320716 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.377218 - 0.304668 * (t - 15.456) - 7.716985e-01 - * Math.pow(t - 15.456, 2) + 1.15579 - * Math.pow(t - 15.456, 3); - else if (t <= 17.391) - y = 0.184896 - 0.272614 * (t - 15.921) + 8.406312e-01 - * Math.pow(t - 15.921, 2) - 0.356506 - * Math.pow(t - 15.921, 3); - else if (t <= 17.856) - y = 0.468224 - 0.112279 * (t - 17.391) - 7.315592e-01 - * Math.pow(t - 17.391, 2) + 0.588669 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.317021 - 0.410774 * (t - 17.856) + 8.963419e-02 - * Math.pow(t - 17.856, 2) + 0.674812 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.213241 + 0.11032 * (t - 18.321) + 1.030997e+00 - * Math.pow(t - 18.321, 2) - 1.08278 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.378599 + 0.366776 * (t - 18.786) - 4.794776e-01 - * Math.pow(t - 18.786, 2) + 0.632722 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.508102 + 0.328891 * (t - 19.248) + 3.974756e-01 - * Math.pow(t - 19.248, 2) - 1.44145 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.60205 - 0.236491 * (t - 19.713) - 1.613351e+00 - * Math.pow(t - 19.713, 2) + 1.89565 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.333833 - 0.507245 * (t - 20.178) + 1.031084e+00 - * Math.pow(t - 20.178, 2) - 0.739129 - * Math.pow(t - 20.178, 3); - - return y * (0.0384 - 0.0130) + 0.0130; - } - - /** - * Computes the approximation spline for nad or returns the default value - * 0.528 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=0.0838 (= std(y)) - * - * @param t - * @return - */ - public double getNAD(double t) { - double y = this.nad; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.26415 + 0.195236 * (t + 3.894) + 0 * Math.pow(t + 3.894, 2) - + 0.0529289 * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.360257 + 0.22957 * (t + 3.429) + 7.383579e-02 - * Math.pow(t + 3.429, 2) - 0.09885 * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.473033 + 0.234116 * (t + 2.964) - 6.406001e-02 - * Math.pow(t + 2.964, 2) - 0.0487923 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.56314 + 0.142889 * (t + 2.499) - 1.321253e-01 - * Math.pow(t + 2.499, 2) + 0.131891 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.613959 + 0.105259 * (t + 2.037) + 5.067510e-02 - * Math.pow(t + 2.037, 2) - 0.179837 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.65578 + 0.0357315 * (t + 1.572) - 2.001977e-01 - * Math.pow(t + 1.572, 2) + 0.210804 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.650303 - 0.0137091 * (t + 1.107) + 9.387388e-02 - * Math.pow(t + 1.107, 2) - 0.139083 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.650242 - 0.0166259 * (t + 0.642) - 1.001466e-01 - * Math.pow(t + 0.642, 2) + 0.0820861 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.615706 + 0.0308066 * (t - 0.363) + 1.473431e-01 - * Math.pow(t - 0.363, 2) - 0.108785 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.650953 + 0.0972696 * (t - 0.828) - 4.411873e-03 - * Math.pow(t - 0.828, 2) - 0.329967 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.662053 - 0.120875 * (t - 1.293) - 4.647152e-01 - * Math.pow(t - 1.293, 2) + 0.701928 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.575938 - 0.0977365 * (t - 1.758) + 5.144744e-01 - * Math.pow(t - 1.758, 2) - 0.803084 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.561402 - 0.136602 * (t - 2.22) - 5.985996e-01 - * Math.pow(t - 2.22, 2) + 0.239797 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.39256 - 0.53775 * (t - 2.685) - 2.640832e-01 - * Math.pow(t - 2.685, 2) + 0.516334 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.13732 - 0.448414 * (t - 3.15) + 4.562028e-01 - * Math.pow(t - 3.15, 2) - 0.0687614 * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.245537 + 0.447062 * (t - 4.62) + 1.529651e-01 - * Math.pow(t - 4.62, 2) - 0.595339 * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.426638 + 0.203138 * (t - 5.085) - 6.775328e-01 - * Math.pow(t - 5.085, 2) + 0.535904 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.42848 - 0.0793393 * (t - 5.55) + 7.005394e-02 - * Math.pow(t - 5.55, 2) + 0.682327 * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.475339 + 0.428419 * (t - 6.015) + 1.021900e+00 - * Math.pow(t - 6.015, 2) - 1.40739 * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.752603 + 0.471457 * (t - 6.477) - 9.287462e-01 - * Math.pow(t - 6.477, 2) + 0.605586 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.8319 + 0.000551332 * (t - 6.942) - 8.395334e-02 - * Math.pow(t - 6.942, 2) + 0.277409 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.841896 + 0.102423 * (t - 7.407) + 3.030328e-01 - * Math.pow(t - 7.407, 2) - 0.354633 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.919389 + 0.154202 * (t - 7.872) - 1.916809e-01 - * Math.pow(t - 7.872, 2) - 0.100478 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.778767 - 0.535532 * (t - 8.877) - 4.946216e-01 - * Math.pow(t - 8.877, 2) + 0.849276 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.508185 - 0.444626 * (t - 9.342) + 6.901186e-01 - * Math.pow(t - 9.342, 2) - 0.35446 * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.415016 - 0.0327449 * (t - 9.807) + 1.956475e-01 - * Math.pow(t - 9.807, 2) - 0.209782 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.421001 + 0.0131269 * (t - 10.272) - 9.699846e-02 - * Math.pow(t - 10.272, 2) + 0.262128 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.432211 + 0.0913491 * (t - 10.734) + 2.663105e-01 - * Math.pow(t - 10.734, 2) - 0.365611 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.495511 + 0.101855 * (t - 11.199) - 2.437172e-01 - * Math.pow(t - 11.199, 2) - 0.105576 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.47956 - 0.193287 * (t - 11.664) - 3.909959e-01 - * Math.pow(t - 11.664, 2) + 0.67975 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.373484 - 0.115976 * (t - 12.129) + 5.572554e-01 - * Math.pow(t - 12.129, 2) - 0.36999 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.444203 - 0.116991 * (t - 13.134) - 5.582651e-01 - * Math.pow(t - 13.134, 2) + 0.803056 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.349834 - 0.115255 * (t - 13.599) + 5.619983e-01 - * Math.pow(t - 13.599, 2) - 0.391353 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.37841 + 0.153543 * (t - 14.064) + 1.606073e-02 - * Math.pow(t - 14.064, 2) - 0.0653872 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.446706 + 0.126064 * (t - 14.529) - 7.515447e-02 - * Math.pow(t - 14.529, 2) - 0.187084 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.470458 - 0.0631743 * (t - 14.991) - 3.344527e-01 - * Math.pow(t - 14.991, 2) - 0.0305672 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.365691 - 0.394043 * (t - 15.456) - 3.770939e-01 - * Math.pow(t - 15.456, 2) + 0.547005 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.155923 - 0.389912 * (t - 15.921) + 3.859784e-01 - * Math.pow(t - 15.921, 2) + 0.139954 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.0721433 + 0.0598327 * (t - 16.386) + 5.812147e-01 - * Math.pow(t - 16.386, 2) - 0.428449 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.284409 - 0.0701584 * (t - 17.391) - 7.105590e-01 - * Math.pow(t - 17.391, 2) + 0.672417 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.165752 - 0.294798 * (t - 17.856) + 2.274630e-01 - * Math.pow(t - 17.856, 2) + 0.325128 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.110544 + 0.127645 * (t - 18.321) + 6.810168e-01 - * Math.pow(t - 18.321, 2) - 0.574329 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.259406 + 0.388438 * (t - 18.786) - 1.201718e-01 - * Math.pow(t - 18.786, 2) - 0.355037 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.378204 + 0.050058 * (t - 19.248) - 6.122524e-01 - * Math.pow(t - 19.248, 2) + 0.331958 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.302473 - 0.304004 * (t - 19.713) - 1.491710e-01 - * Math.pow(t - 19.713, 2) + 0.636016 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.192805 - 0.0301656 * (t - 20.178) + 7.380708e-01 - * Math.pow(t - 20.178, 2) - 0.529083 - * Math.pow(t - 20.178, 3); - - return y * (0.6904 - 0.3447) + 0.3447; - } - - /* - * Alternative Splines. - * ------------------------------------------------------------------------------ - */ - - /** - * Computes the approximation spline for nad or returns the default value - * 5.12 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1. - * - * @param t - * @return - */ - public double getAKG_2(double t) { - double y = this.akg; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.0103873 + 0.0245023 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) + 0.000889259 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.0218703 + 0.0250792 * (t + 3.429) + 1.240516e-003 - * Math.pow(t + 3.429, 2) - 0.00103745 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.0336961 + 0.0255599 * (t + 2.964) - 2.067336e-004 - * Math.pow(t + 2.964, 2) + 0.0031721 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.0458557 + 0.0274253 * (t + 2.499) + 4.218348e-003 - * Math.pow(t + 2.499, 2) + 0.00940976 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.0603544 + 0.0373484 * (t + 2.037) + 1.726027e-002 - * Math.pow(t + 2.037, 2) + 0.00968846 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.0824277 + 0.0596851 * (t + 1.572) + 3.077568e-002 - * Math.pow(t + 1.572, 2) + 0.0028213 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.117119 + 0.0901366 * (t + 1.107) + 3.471139e-002 - * Math.pow(t + 1.107, 2) + 0.00341112 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.166881 + 0.124631 * (t + 0.642) + 3.946990e-002 - * Math.pow(t + 0.642, 2) + 0.00095361 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.332969 + 0.206855 * (t - 0.363) + 4.234504e-002 - * Math.pow(t - 0.363, 2) - 0.0162354 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.43668 + 0.235704 * (t - 0.828) + 1.969664e-002 - * Math.pow(t - 0.828, 2) - 0.0467443 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.545842 + 0.2237 * (t - 1.293) - 4.551161e-002 - * Math.pow(t - 1.293, 2) - 0.00864697 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.639152 + 0.175765 * (t - 1.758) - 5.757413e-002 - * Math.pow(t - 1.758, 2) - 0.00969614 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.707111 + 0.116358 * (t - 2.22) - 7.101299e-002 - * Math.pow(t - 2.22, 2) + 0.0111824 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.746987 + 0.0575699 * (t - 2.685) - 5.541349e-002 - * Math.pow(t - 2.685, 2) + 0.014742 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.763257 + 0.0155981 * (t - 3.15) - 3.484845e-002 - * Math.pow(t - 3.15, 2) + 0.0112969 * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.746768 - 0.0136219 * (t - 4.62) + 1.497086e-002 - * Math.pow(t - 4.62, 2) + 0.0132501 * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.745003 + 0.00889596 * (t - 5.085) + 3.345475e-002 - * Math.pow(t - 5.085, 2) - 0.012265 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.75514 + 0.0320529 * (t - 5.55) + 1.634507e-002 - * Math.pow(t - 5.55, 2) - 0.0117923 * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.772393 + 0.0396044 * (t - 6.015) - 1.051669e-004 - * Math.pow(t - 6.015, 2) - 0.0170771 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.788984 + 0.0285723 * (t - 6.477) - 2.377399e-002 - * Math.pow(t - 6.477, 2) + 0.00151285 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.797281 + 0.0074438 * (t - 6.942) - 2.166356e-002 - * Math.pow(t - 6.942, 2) + 0.00135068 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.796194 - 0.0118272 * (t - 7.407) - 1.977937e-002 - * Math.pow(t - 7.407, 2) - 0.00327297 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.786089 - 0.0323451 * (t - 7.872) - 2.434516e-002 - * Math.pow(t - 7.872, 2) + 0.0112722 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.740435 - 0.0471232 * (t - 8.877) + 9.640591e-003 - * Math.pow(t - 8.877, 2) + 0.00491285 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.721101 - 0.0349706 * (t - 9.342) + 1.649402e-002 - * Math.pow(t - 9.342, 2) - 0.0097896 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.707422 - 0.0259814 * (t - 9.807) + 2.837523e-003 - * Math.pow(t - 9.807, 2) - 0.00582093 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.695369 - 0.0271184 * (t - 10.272) - 5.282677e-003 - * Math.pow(t - 10.272, 2) + 0.00265349 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.681974 - 0.0303005 * (t - 10.734) - 1.604944e-003 - * Math.pow(t - 10.734, 2) - 0.0079586 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.666737 - 0.0369556 * (t - 11.199) - 1.270719e-002 - * Math.pow(t - 11.199, 2) - 0.0131693 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.645481 - 0.0573159 * (t - 11.664) - 3.107839e-002 - * Math.pow(t - 11.664, 2) + 0.0093138 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.613046 - 0.0801772 * (t - 12.129) - 1.808564e-002 - * Math.pow(t - 12.129, 2) + 0.0120022 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.526384 - 0.0801617 * (t - 13.134) + 1.810107e-002 - * Math.pow(t - 13.134, 2) - 0.0135793 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.491658 - 0.0721363 * (t - 13.599) - 8.420971e-004 - * Math.pow(t - 13.599, 2) - 0.00640392 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.457288 - 0.0770735 * (t - 14.064) - 9.775570e-003 - * Math.pow(t - 14.064, 2) + 0.00511879 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.41985 - 0.0828443 * (t - 14.529) - 2.634851e-003 - * Math.pow(t - 14.529, 2) + 0.00937238 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.381938 - 0.0792775 * (t - 14.991) + 1.035527e-002 - * Math.pow(t - 14.991, 2) - 0.0075053 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.346558 - 0.0745156 * (t - 15.456) - 1.146279e-004 - * Math.pow(t - 15.456, 2) + 0.00304791 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.31219 - 0.0726451 * (t - 15.921) + 4.137208e-003 - * Math.pow(t - 15.921, 2) + 0.0136591 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.280678 - 0.0599372 * (t - 16.386) + 2.319161e-002 - * Math.pow(t - 16.386, 2) - 0.00821908 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.235522 - 0.0382265 * (t - 17.391) - 1.588930e-003 - * Math.pow(t - 17.391, 2) + 0.00670205 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.218077 - 0.0353567 * (t - 17.856) + 7.760434e-003 - * Math.pow(t - 17.856, 2) + 0.00564499 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.203882 - 0.0244778 * (t - 18.321) + 1.563519e-002 - * Math.pow(t - 18.321, 2) - 0.00177981 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.195702 - 0.0110916 * (t - 18.786) + 1.315236e-002 - * Math.pow(t - 18.786, 2) - 0.00372881 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.193017 - 0.00132647 * (t - 19.248) + 7.984227e-003 - * Math.pow(t - 19.248, 2) + 0.00047682 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.194174 + 0.00640816 * (t - 19.713) + 8.649391e-003 - * Math.pow(t - 19.713, 2) - 0.00671658 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.198349 + 0.0100952 * (t - 20.178) - 7.202434e-004 - * Math.pow(t - 20.178, 2) + 0.000516303 - * Math.pow(t - 20.178, 3); - - return (13.05163236 - 4.464821914) * y + 4.464821914; - } - - /** - * Computes the approximation spline for nad or returns the default value - * 1.05 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1. - * - * @param t - * @return - */ - public double getAla_2(double t) { - double y = this.ala; - - if ((-3.894 <= t) && (t <= -3.429)) - y = -0.0257788 + 0.0757032 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) + 8.46192e-005 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.00943169 + 0.0757581 * (t + 3.429) + 1.180437e-004 - * Math.pow(t + 3.429, 2) + 0.000227745 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.0447076 + 0.0760156 * (t + 2.964) + 4.357480e-004 - * Math.pow(t + 2.964, 2) + 0.00037785 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.0801871 + 0.0766659 * (t + 2.499) + 9.628484e-004 - * Math.pow(t + 2.499, 2) + 0.00059295 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.115871 + 0.0779353 * (t + 2.037) + 1.784677e-003 - * Math.pow(t + 2.037, 2) + 0.000556136 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.152552 + 0.0799558 * (t + 1.572) + 2.560487e-003 - * Math.pow(t + 1.572, 2) + 0.000221119 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.190308 + 0.0824805 * (t + 1.107) + 2.868948e-003 - * Math.pow(t + 1.107, 2) - 7.57144e-005 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.229274 + 0.0850995 * (t + 0.642) + 2.763327e-003 - * Math.pow(t + 0.642, 2) - 0.000522193 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.31706 + 0.0890715 * (t - 0.363) + 1.188915e-003 - * Math.pow(t - 0.363, 2) - 0.00127255 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.358607 + 0.0893517 * (t - 0.828) - 5.862872e-004 - * Math.pow(t - 0.828, 2) - 0.0020192 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.399826 + 0.0874966 * (t - 1.293) - 3.403066e-003 - * Math.pow(t - 1.293, 2) - 0.0010238 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.439673 + 0.0836677 * (t - 1.758) - 4.831271e-003 - * Math.pow(t - 1.758, 2) - 0.000745052 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.477223 + 0.0787265 * (t - 2.22) - 5.863913e-003 - * Math.pow(t - 2.22, 2) - 0.000419832 - * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.512521 + 0.0730007 * (t - 2.685) - 6.449578e-003 - * Math.pow(t - 2.685, 2) + 0.000116966 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.545083 + 0.0670785 * (t - 3.15) - 6.286411e-003 - * Math.pow(t - 3.15, 2) + 0.000331164 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.631156 + 0.0507433 * (t - 4.62) - 4.825979e-003 - * Math.pow(t - 4.62, 2) + 0.000341949 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.653743 + 0.0464769 * (t - 5.085) - 4.348961e-003 - * Math.pow(t - 5.085, 2) + 0.00010459 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.674425 + 0.0425003 * (t - 5.55) - 4.203058e-003 - * Math.pow(t - 5.55, 2) + 0.000593076 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.693338 + 0.0389761 * (t - 6.015) - 3.375717e-003 - * Math.pow(t - 6.015, 2) + 0.000530359 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.710677 + 0.0361966 * (t - 6.477) - 2.640640e-003 - * Math.pow(t - 6.477, 2) + 0.000450453 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.726982 + 0.034033 * (t - 6.942) - 2.012259e-003 - * Math.pow(t - 6.942, 2) - 0.000111927 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.742361 + 0.032089 * (t - 7.407) - 2.168397e-003 - * Math.pow(t - 7.407, 2) - 0.00044037 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.75677 + 0.0297867 * (t - 7.872) - 2.782713e-003 - * Math.pow(t - 7.872, 2) - 0.000103208 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.78379 + 0.0238807 * (t - 8.877) - 3.093887e-003 - * Math.pow(t - 8.877, 2) - 0.000601735 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.794165 + 0.0206131 * (t - 9.342) - 3.933308e-003 - * Math.pow(t - 9.342, 2) - 0.00100343 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.802799 + 0.0163042 * (t - 9.807) - 5.333096e-003 - * Math.pow(t - 9.807, 2) - 0.000786438 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.809148 + 0.0108343 * (t - 10.272) - 6.430177e-003 - * Math.pow(t - 10.272, 2) - 0.000301043 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.812751 + 0.00470002 * (t - 10.734) - 6.847422e-003 - * Math.pow(t - 10.734, 2) - 0.000462141 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.81341 - 0.00196787 * (t - 11.199) - 7.492109e-003 - * Math.pow(t - 11.199, 2) - 0.000409103 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.810833 - 0.0092009 * (t - 11.664) - 8.062808e-003 - * Math.pow(t - 11.664, 2) - 3.32225e-006 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.804811 - 0.0167015 * (t - 12.129) - 8.067443e-003 - * Math.pow(t - 12.129, 2) + 0.000582906 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.78047 - 0.0311508 * (t - 13.134) - 6.309980e-003 - * Math.pow(t - 13.134, 2) - 0.000389839 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.764581 - 0.0372719 * (t - 13.599) - 6.853806e-003 - * Math.pow(t - 13.599, 2) + 0.000242278 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.745792 - 0.0434888 * (t - 14.064) - 6.515828e-003 - * Math.pow(t - 14.064, 2) + 0.00107672 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.724269 - 0.0488501 * (t - 14.529) - 5.013806e-003 - * Math.pow(t - 14.529, 2) + 0.00137712 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.700766 - 0.052601 * (t - 14.991) - 3.105123e-003 - * Math.pow(t - 14.991, 2) + 0.000485789 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.675684 - 0.0551737 * (t - 15.456) - 2.427447e-003 - * Math.pow(t - 15.456, 2) + 0.00103293 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.649607 - 0.0567612 * (t - 15.921) - 9.865110e-004 - * Math.pow(t - 15.921, 2) + 0.00134773 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.623135 - 0.0568044 * (t - 16.386) + 8.935673e-004 - * Math.pow(t - 16.386, 2) + 0.00043569 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.567392 - 0.0536882 * (t - 17.391) + 2.207173e-003 - * Math.pow(t - 17.391, 2) + 0.000468284 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.542951 - 0.0513317 * (t - 17.856) + 2.860429e-003 - * Math.pow(t - 17.856, 2) + 0.000183539 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.519719 - 0.0485525 * (t - 18.321) + 3.116466e-003 - * Math.pow(t - 18.321, 2) - 0.000803598 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.497735 - 0.0461754 * (t - 18.786) + 1.995447e-003 - * Math.pow(t - 18.786, 2) - 0.000805573 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.476748 - 0.0448475 * (t - 19.248) + 8.789230e-004 - * Math.pow(t - 19.248, 2) - 0.000265004 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.456058 - 0.044202 * (t - 19.713) + 5.092420e-004 - * Math.pow(t - 19.713, 2) - 0.000309747 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.435583 - 0.0439293 * (t - 20.178) + 7.714514e-005 - * Math.pow(t - 20.178, 2) - 5.53012e-005 - * Math.pow(t - 20.178, 3); - - return (3.800862229 - 0.814981525) * y + 0.814981525; - } - - /** - * Computes the spline equation for pyr with the parameter S=1 and all - * weights equal to one. For values of t smaller or greater than the - * considered time the default steady-state value of 0.689 mM will be - * returned. - * - * @param t - * @return y the concentration of pyr at the given time t. - */ - public double getPyr_2(double t) { - double y = this.pyr; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.00709166 + 0.0109621 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) + 0.00196669 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.0123868 + 0.0122378 * (t + 3.429) + 2.743530e-003 - * Math.pow(t + 3.429, 2) + 0.00339276 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.0190117 + 0.0169901 * (t + 2.964) + 7.476430e-003 - * Math.pow(t + 2.964, 2) + 0.00342188 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.0288727 + 0.0261629 * (t + 2.499) + 1.224995e-002 - * Math.pow(t + 2.499, 2) + 0.00337058 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.043907 + 0.0396401 * (t + 2.037) + 1.692158e-002 - * Math.pow(t + 2.037, 2) + 0.00582311 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.066584 + 0.0591545 * (t + 1.572) + 2.504482e-002 - * Math.pow(t + 1.572, 2) + 0.00764784 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.100275 + 0.0874071 * (t + 1.107) + 3.571356e-002 - * Math.pow(t + 1.107, 2) + 0.00313583 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.148957 + 0.122655 * (t + 0.642) + 4.008804e-002 - * Math.pow(t + 0.642, 2) - 0.00384667 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.30881 + 0.191576 * (t - 0.363) + 2.849033e-002 - * Math.pow(t - 0.363, 2) - 0.0157823 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.402467 + 0.207835 * (t - 0.828) + 6.474088e-003 - * Math.pow(t - 0.828, 2) - 0.0315699 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.497336 + 0.193377 * (t - 1.293) - 3.756588e-002 - * Math.pow(t - 1.293, 2) - 0.00800701 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.578328 + 0.153247 * (t - 1.758) - 4.873566e-002 - * Math.pow(t - 1.758, 2) + 0.000853208 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.63881 + 0.108761 * (t - 2.22) - 4.755311e-002 - * Math.pow(t - 2.22, 2) + 0.00189972 - * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.679293 + 0.0657692 * (t - 2.685) - 4.490300e-002 - * Math.pow(t - 2.685, 2) + 0.00542329 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.700711 + 0.0275273 * (t - 3.15) - 3.733752e-002 - * Math.pow(t - 3.15, 2) + 0.00782647 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.685355 - 0.0315083 * (t - 4.62) - 2.822794e-003 - * Math.pow(t - 4.62, 2) + 0.00824557 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.670922 - 0.0287848 * (t - 5.085) + 8.679771e-003 - * Math.pow(t - 5.085, 2) - 0.00053434 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.65936 - 0.0210592 * (t - 5.55) + 7.934367e-003 - * Math.pow(t - 5.55, 2) + 0.000466607 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.65133 - 0.0133776 * (t - 6.015) + 8.585283e-003 - * Math.pow(t - 6.015, 2) + 0.00180465 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.64716 - 0.00428923 * (t - 6.477) + 1.108653e-002 - * Math.pow(t - 6.477, 2) + 0.00122435 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.647686 + 0.00681544 * (t - 6.942) + 1.279450e-002 - * Math.pow(t - 6.942, 2) + 0.000225641 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.653645 + 0.0188607 * (t - 7.407) + 1.310927e-002 - * Math.pow(t - 7.407, 2) - 0.00705357 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.66454 + 0.0264768 * (t - 7.872) + 3.269535e-003 - * Math.pow(t - 7.872, 2) - 0.00164124 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.692786 + 0.0280755 * (t - 8.877) - 1.678801e-003 - * Math.pow(t - 8.877, 2) - 0.00583638 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.704891 + 0.0227283 * (t - 9.342) - 9.820550e-003 - * Math.pow(t - 9.342, 2) - 0.00702045 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.71263 + 0.00904123 * (t - 9.807) - 1.961407e-002 - * Math.pow(t - 9.807, 2) - 0.00222559 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.71237 - 0.0106435 * (t - 10.272) - 2.271877e-002 - * Math.pow(t - 10.272, 2) + 0.000800336 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.702682 - 0.0311232 * (t - 10.734) - 2.160950e-002 - * Math.pow(t - 10.734, 2) - 0.00295931 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.68324 - 0.0531397 * (t - 11.199) - 2.573774e-002 - * Math.pow(t - 11.199, 2) - 0.00108335 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.652856 - 0.0777785 * (t - 11.664) - 2.724901e-002 - * Math.pow(t - 11.664, 2) + 0.0120572 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.612009 - 0.0952989 * (t - 12.129) - 1.042920e-002 - * Math.pow(t - 12.129, 2) + 0.00960616 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.515451 - 0.0871542 * (t - 13.134) + 1.853336e-002 - * Math.pow(t - 13.134, 2) - 0.00166772 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.478764 - 0.071 * (t - 13.599) + 1.620689e-002 - * Math.pow(t - 13.599, 2) - 0.00322537 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.448929 - 0.0580198 * (t - 14.064) + 1.170750e-002 - * Math.pow(t - 14.064, 2) - 0.00133285 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.424347 - 0.0479964 * (t - 14.529) + 9.848170e-003 - * Math.pow(t - 14.529, 2) - 0.000351634 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.40424 - 0.0391218 * (t - 14.991) + 9.360805e-003 - * Math.pow(t - 14.991, 2) - 0.0119481 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.386871 - 0.0381667 * (t - 15.456) - 7.306757e-003 - * Math.pow(t - 15.456, 2) + 0.00287619 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.367833 - 0.0430963 * (t - 15.921) - 3.294470e-003 - * Math.pow(t - 15.921, 2) + 0.00490737 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.347574 - 0.0429768 * (t - 16.386) + 3.551307e-003 - * Math.pow(t - 16.386, 2) - 0.000631183 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.307329 - 0.0377513 * (t - 17.391) + 1.648289e-003 - * Math.pow(t - 17.391, 2) + 0.0043097 - * Math.pow(t - 17.391, 3); - else if (t <= 18.786) - y = 0.290564 - 0.0334227 * (t - 17.856) + 7.660326e-003 - * Math.pow(t - 17.856, 2) - 0.000123905 - * Math.pow(t - 17.856, 3); - else if (t <= 19.248) - y = 0.266007 - 0.019496 * (t - 18.786) + 7.314632e-003 - * Math.pow(t - 18.786, 2) - 0.00687547 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.257883 - 0.0171399 * (t - 19.248) - 2.214775e-003 - * Math.pow(t - 19.248, 2) - 0.0015665 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.249277 - 0.0202158 * (t - 19.713) - 4.400043e-003 - * Math.pow(t - 19.713, 2) + 0.0021551 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.239141 - 0.0229099 * (t - 20.178) - 1.393672e-003 - * Math.pow(t - 20.178, 2) + 0.000999048 - * Math.pow(t - 20.178, 3); - - return (2.350729829 - 0.614400017) * y + 0.614400017; - } - - /** - * Computes the approximation spline for glut or returns the default value - * 38.7 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1. - * - * @param t - * @return - */ - public double getGlut_2(double t) { - double y = this.glut; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.345758 + 0.0308006 * (t + 3.894) + 0 * Math.pow(t + 3.894, 2) - + 1.46278e-005 * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.360082 + 0.03081 * (t + 3.429) + 2.040578e-005 - * Math.pow(t + 3.429, 2) - 4.77212e-006 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.374413 + 0.0308259 * (t + 2.964) + 1.374867e-005 - * Math.pow(t + 2.964, 2) - 2.09457e-005 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.388748 + 0.0308251 * (t + 2.499) - 1.547064e-005 - * Math.pow(t + 2.499, 2) - 5.74626e-006 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.402985 + 0.0308071 * (t + 2.037) - 2.343495e-005 - * Math.pow(t + 2.037, 2) - 1.44612e-005 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.417304 + 0.030776 * (t + 1.572) - 4.360827e-005 - * Math.pow(t + 1.572, 2) - 2.12542e-005 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.431603 + 0.0307216 * (t + 1.107) - 7.325784e-005 - * Math.pow(t + 1.107, 2) - 4.47943e-005 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.445868 + 0.0306244 * (t + 0.642) - 1.357459e-004 - * Math.pow(t + 0.642, 2) - 4.75641e-005 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.47646 + 0.0302075 * (t - 0.363) - 2.791515e-004 - * Math.pow(t - 0.363, 2) - 6.39979e-005 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.49044 + 0.0299063 * (t - 0.828) - 3.684286e-004 - * Math.pow(t - 0.828, 2) - 6.70553e-005 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.50426 + 0.0295202 * (t - 1.293) - 4.619707e-004 - * Math.pow(t - 1.293, 2) - 6.72759e-005 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.51788 + 0.0290469 * (t - 1.758) - 5.558206e-004 - * Math.pow(t - 1.758, 2) - 0.000100774 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.531172 + 0.0284688 * (t - 2.22) - 6.954937e-004 - * Math.pow(t - 2.22, 2) - 8.65101e-005 - * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.54425 + 0.0277659 * (t - 2.685) - 8.161753e-004 - * Math.pow(t - 2.685, 2) - 0.000128037 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.556972 + 0.0269238 * (t - 3.15) - 9.947864e-004 - * Math.pow(t - 3.15, 2) - 0.000177372 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.593837 + 0.0228493 * (t - 4.62) - 1.776998e-003 - * Math.pow(t - 4.62, 2) - 0.000228858 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.604055 + 0.0210482 * (t - 5.085) - 2.096254e-003 - * Math.pow(t - 5.085, 2) - 0.000211625 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.613368 + 0.0189614 * (t - 5.55) - 2.391471e-003 - * Math.pow(t - 5.55, 2) - 0.000215207 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.621646 + 0.0165978 * (t - 6.015) - 2.691685e-003 - * Math.pow(t - 6.015, 2) - 0.000233051 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.628717 + 0.0139614 * (t - 6.477) - 3.014694e-003 - * Math.pow(t - 6.477, 2) - 0.000222455 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.634535 + 0.0110134 * (t - 6.942) - 3.325019e-003 - * Math.pow(t - 6.942, 2) - 0.000218367 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.638915 + 0.00777953 * (t - 7.407) - 3.629641e-003 - * Math.pow(t - 7.407, 2) - 0.000200303 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.641727 + 0.00427403 * (t - 7.872) - 3.909065e-003 - * Math.pow(t - 7.872, 2) - 0.000100588 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.641972 - 0.00388798 * (t - 8.877) - 4.212339e-003 - * Math.pow(t - 8.877, 2) - 8.05589e-005 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.639246 - 0.00785771 * (t - 9.342) - 4.324718e-003 - * Math.pow(t - 9.342, 2) - 0.000122855 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.634644 - 0.0119594 * (t - 9.807) - 4.496101e-003 - * Math.pow(t - 9.807, 2) - 8.67214e-005 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.628102 - 0.016197 * (t - 10.272) - 4.617077e-003 - * Math.pow(t - 10.272, 2) + 1.56232e-005 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.619635 - 0.0204532 * (t - 10.734) - 4.595424e-003 - * Math.pow(t - 10.734, 2) + 4.79204e-005 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.609136 - 0.0246959 * (t - 11.199) - 4.528575e-003 - * Math.pow(t - 11.199, 2) + 0.000102127 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.596683 - 0.0288412 * (t - 11.664) - 4.386108e-003 - * Math.pow(t - 11.664, 2) + 0.000179965 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.582342 - 0.0328035 * (t - 12.129) - 4.135056e-003 - * Math.pow(t - 12.129, 2) + 0.000211674 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.545413 - 0.0404736 * (t - 13.134) - 3.496860e-003 - * Math.pow(t - 13.134, 2) + 0.000228722 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.525859 - 0.0435773 * (t - 13.599) - 3.177793e-003 - * Math.pow(t - 13.599, 2) + 0.000250327 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.504934 - 0.0463703 * (t - 14.064) - 2.828587e-003 - * Math.pow(t - 14.064, 2) + 0.000304393 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.482791 - 0.0488034 * (t - 14.529) - 2.403960e-003 - * Math.pow(t - 14.529, 2) + 0.000326486 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.459763 - 0.0508156 * (t - 14.991) - 1.951450e-003 - * Math.pow(t - 14.991, 2) + 0.00033353 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.435745 - 0.0524141 * (t - 15.456) - 1.486176e-003 - * Math.pow(t - 15.456, 2) + 0.000301097 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.411081 - 0.0536009 * (t - 15.921) - 1.066146e-003 - * Math.pow(t - 15.921, 2) + 0.000256208 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.385952 - 0.0544263 * (t - 16.386) - 7.087358e-004 - * Math.pow(t - 16.386, 2) + 0.000164513 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.330705 - 0.0553523 * (t - 17.391) - 2.127293e-004 - * Math.pow(t - 17.391, 2) + 0.000106639 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.304931 - 0.055481 * (t - 17.856) - 6.396824e-005 - * Math.pow(t - 17.856, 2) + 4.39342e-005 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.279123 - 0.055512 * (t - 18.321) - 2.679996e-006 - * Math.pow(t - 18.321, 2) - 3.37517e-005 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.253306 - 0.0555364 * (t - 18.786) - 4.976359e-005 - * Math.pow(t - 18.786, 2) - 3.19922e-006 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.227637 - 0.0555844 * (t - 19.248) - 5.419771e-005 - * Math.pow(t - 19.248, 2) + 2.66171e-005 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.201781 - 0.0556175 * (t - 19.713) - 1.706686e-005 - * Math.pow(t - 19.713, 2) + 1.3914e-005 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.175917 - 0.0556244 * (t - 20.178) + 2.343138e-006 - * Math.pow(t - 20.178, 2) - 1.67967e-006 - * Math.pow(t - 20.178, 3); - - return (69.03104101 - 20.63720808) * y + 20.63720808; - } - - /** - * Computes the approximation spline for nadp or returns the default value - * 0.0175 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1 - * - * @param t - * @return - */ - public double getNADP_2(double t) { - double y = this.nadp; - - if ((-3.429 <= t) && (t <= -2.964)) - y = 0.13595 + 0.0971795 * (t + 3.429) + 0 * Math.pow(t + 3.429, 2) - + 0.05691 * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.186861 + 0.134096 * (t + 2.964) + 7.938952e-002 - * Math.pow(t + 2.964, 2) - 0.0819871 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.258138 + 0.154745 * (t + 2.499) - 3.498256e-002 - * Math.pow(t + 2.499, 2) - 0.0496607 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.317266 + 0.0906217 * (t + 2.037) - 1.038122e-001 - * Math.pow(t + 2.037, 2) + 0.0808513 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.345087 + 0.0465225 * (t + 1.572) + 8.975385e-003 - * Math.pow(t + 1.572, 2) + 0.0616748 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.374862 + 0.0948765 * (t + 1.107) + 9.501172e-002 - * Math.pow(t + 1.107, 2) + 0.00360399 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.439886 + 0.185575 * (t + 0.642) + 1.000393e-001 - * Math.pow(t + 0.642, 2) - 0.139812 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.585512 - 0.0369863 * (t - 0.363) - 3.214935e-001 - * Math.pow(t - 0.363, 2) + 0.1243 * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.511296 - 0.255345 * (t - 0.828) - 1.480948e-001 - * Math.pow(t - 0.828, 2) + 0.234296 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.384096 - 0.241091 * (t - 1.293) + 1.787485e-001 - * Math.pow(t - 1.293, 2) - 0.0296831 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.307654 - 0.0941094 * (t - 1.758) + 1.373406e-001 - * Math.pow(t - 1.758, 2) - 0.0303251 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.2905 + 0.0133752 * (t - 2.22) + 9.531002e-002 - * Math.pow(t - 2.22, 2) - 0.162261 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.301013 - 0.00324113 * (t - 2.685) - 1.310440e-001 - * Math.pow(t - 2.685, 2) + 0.236466 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.294947 + 0.0282775 * (t - 3.15) + 1.988259e-001 - * Math.pow(t - 3.15, 2) - 0.0632008 * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.565399 + 0.203114 * (t - 4.62) - 7.988958e-002 - * Math.pow(t - 4.62, 2) - 0.0313141 * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.639424 + 0.108504 * (t - 5.085) - 1.235727e-001 - * Math.pow(t - 5.085, 2) - 0.00925389 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.662228 - 0.0124214 * (t - 5.55) - 1.364819e-001 - * Math.pow(t - 5.55, 2) + 0.0932451 * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.636317 - 0.0788638 * (t - 6.015) - 6.404951e-003 - * Math.pow(t - 6.015, 2) + 0.0852613 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.606922 - 0.0301864 * (t - 6.477) + 1.117673e-001 - * Math.pow(t - 6.477, 2) - 0.083061 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.608701 + 0.0198776 * (t - 6.942) - 4.102769e-003 - * Math.pow(t - 6.942, 2) - 0.0241232 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.614632 + 0.000413894 * (t - 7.407) - 3.775461e-002 - * Math.pow(t - 7.407, 2) + 0.15561 * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.622307 + 0.0662424 * (t - 7.872) + 1.793212e-001 - * Math.pow(t - 7.872, 2) - 0.176584 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.690753 - 0.108384 * (t - 8.877) - 3.530788e-001 - * Math.pow(t - 8.877, 2) + 0.261112 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.590264 - 0.26737 * (t - 9.342) + 1.117277e-002 - * Math.pow(t - 9.342, 2) + 0.157079 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.484146 - 0.155086 * (t - 9.807) + 2.302982e-001 - * Math.pow(t - 9.807, 2) - 0.0968507 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.452089 - 0.00373366 * (t - 10.272) + 9.519140e-002 - * Math.pow(t - 10.272, 2) - 0.153609 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.455535 - 0.0141377 * (t - 10.734) - 1.177110e-001 - * Math.pow(t - 10.734, 2) - 0.180352 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.405375 - 0.240598 * (t - 11.199) - 3.693013e-001 - * Math.pow(t - 11.199, 2) + 0.347415 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.248575 - 0.358689 * (t - 11.664) + 1.153421e-001 - * Math.pow(t - 11.664, 2) + 0.0933175 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.116107 - 0.190889 * (t - 12.129) + 2.455201e-001 - * Math.pow(t - 12.129, 2) - 0.071016 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.100159 + 0.087423 * (t - 13.134) + 3.140679e-002 - * Math.pow(t - 13.134, 2) - 0.0119264 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.146403 + 0.108895 * (t - 13.599) + 1.476952e-002 - * Math.pow(t - 13.599, 2) + 0.0161065 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.201852 + 0.133079 * (t - 14.064) + 3.723807e-002 - * Math.pow(t - 14.064, 2) - 0.0384482 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.267919 + 0.14277 * (t - 14.529) - 1.639710e-002 - * Math.pow(t - 14.529, 2) - 0.0889529 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.321607 + 0.0706593 * (t - 14.991) - 1.396858e-001 - * Math.pow(t - 14.991, 2) + 0.00481567 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.324744 - 0.0561247 * (t - 15.456) - 1.329680e-001 - * Math.pow(t - 15.456, 2) + 0.218536 - * Math.pow(t - 15.456, 3); - else if (t <= 17.391) - y = 0.291868 - 0.0380259 * (t - 15.921) + 1.718902e-001 - * Math.pow(t - 15.921, 2) - 0.0756988 - * Math.pow(t - 15.921, 3); - else if (t <= 17.856) - y = 0.366948 - 0.0234014 * (t - 17.391) - 1.619415e-001 - * Math.pow(t - 17.391, 2) + 0.156911 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.336828 - 0.0722227 * (t - 17.856) + 5.694952e-002 - * Math.pow(t - 17.856, 2) + 0.137013 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.329334 + 0.0696174 * (t - 18.321) + 2.480828e-001 - * Math.pow(t - 18.321, 2) - 0.193298 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.395912 + 0.174947 * (t - 18.786) - 2.156847e-002 - * Math.pow(t - 18.786, 2) - 0.0557802 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.466634 + 0.119299 * (t - 19.248) - 9.887981e-002 - * Math.pow(t - 19.248, 2) - 0.192986 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.481324 - 0.097844 * (t - 19.713) - 3.680952e-001 - * Math.pow(t - 19.713, 2) + 0.293063 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.385701 - 0.25007 * (t - 20.178) + 4.072711e-002 - * Math.pow(t - 20.178, 2) - 0.0291951 - * Math.pow(t - 20.178, 3); - - return (0.038425509 - 0.013039703) * y + 0.013039703; - } - - /** - * Computes the approximation spline for nad or returns the default value - * 0.528 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1 - * - * @param t - * @return - */ - public double getNAD_2(double t) { - double y = this.nad; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.285913 + 0.197505 * (t + 3.894) + 0 * Math.pow(t + 3.894, 2) - - 0.00471653 * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.377278 + 0.194445 * (t + 3.429) - 6.579559e-003 - * Math.pow(t + 3.429, 2) - 0.0157447 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.464689 + 0.178113 * (t + 2.964) - 2.854341e-002 - * Math.pow(t + 2.964, 2) - 0.0112637 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.540208 + 0.144261 * (t + 2.499) - 4.425629e-002 - * Math.pow(t + 2.499, 2) + 0.00268962 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.597675 + 0.105091 * (t + 2.037) - 4.052848e-002 - * Math.pow(t + 2.037, 2) - 0.00411981 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.637365 + 0.0647267 * (t + 1.572) - 4.627561e-002 - * Math.pow(t + 1.572, 2) + 0.0164141 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.659107 + 0.0323377 * (t + 1.107) - 2.337800e-002 - * Math.pow(t + 1.107, 2) + 0.000399521 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.66913 + 0.0108554 * (t + 0.642) - 2.282067e-002 - * Math.pow(t + 0.642, 2) + 0.00296352 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.659998 - 0.0260345 * (t - 0.363) - 1.388565e-002 - * Math.pow(t - 0.363, 2) - 0.0179798 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.643082 - 0.0506112 * (t - 0.828) - 3.896752e-002 - * Math.pow(t - 0.828, 2) - 0.0239499 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.608714 - 0.102387 * (t - 1.293) - 7.237756e-002 - * Math.pow(t - 1.293, 2) + 0.0317423 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.548646 - 0.149107 * (t - 1.758) - 2.809708e-002 - * Math.pow(t - 1.758, 2) - 0.0169992 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.472084 - 0.185954 * (t - 2.22) - 5.165802e-002 - * Math.pow(t - 2.22, 2) + 0.0502322 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.379497 - 0.201412 * (t - 2.685) + 1.841597e-002 - * Math.pow(t - 2.685, 2) + 0.0647767 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.296335 - 0.142266 * (t - 3.15) + 1.087795e-001 - * Math.pow(t - 3.15, 2) - 0.00660796 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.301275 + 0.134708 * (t - 4.62) + 7.963841e-002 - * Math.pow(t - 4.62, 2) - 0.0438438 * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.376726 + 0.180332 * (t - 5.085) + 1.847627e-002 - * Math.pow(t - 5.085, 2) + 0.0145632 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.46604 + 0.206962 * (t - 5.55) + 3.879198e-002 - * Math.pow(t - 5.55, 2) + 0.00851535 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.571521 + 0.248562 * (t - 6.015) + 5.067090e-002 - * Math.pow(t - 6.015, 2) - 0.10061 * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.687251 + 0.230958 * (t - 6.477) - 8.877391e-002 - * Math.pow(t - 6.477, 2) - 0.00393058 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.775056 + 0.145849 * (t - 6.942) - 9.425707e-002 - * Math.pow(t - 6.942, 2) + 0.00117341 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.822613 + 0.0589508 * (t - 7.407) - 9.262016e-002 - * Math.pow(t - 7.407, 2) - 0.0168782 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.828301 - 0.0381344 * (t - 7.872) - 1.161653e-001 - * Math.pow(t - 7.872, 2) + 0.0209354 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.693897 - 0.208191 * (t - 8.877) - 5.304513e-002 - * Math.pow(t - 8.877, 2) + 0.0832539 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.59399 - 0.203518 * (t - 9.342) + 6.309407e-002 - * Math.pow(t - 9.342, 2) + 0.0109974 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.514102 - 0.137707 * (t - 9.807) + 7.843539e-002 - * Math.pow(t - 9.807, 2) - 0.014136 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.465606 - 0.0739317 * (t - 10.272) + 5.871560e-002 - * Math.pow(t - 10.272, 2) - 0.00999596 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.442997 - 0.0260793 * (t - 10.734) + 4.486120e-002 - * Math.pow(t - 10.734, 2) - 0.0371792 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.436832 - 0.00847559 * (t - 11.199) - 7.003852e-003 - * Math.pow(t - 11.199, 2) - 0.00916083 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.430455 - 0.0209316 * (t - 11.664) - 1.978321e-002 - * Math.pow(t - 11.664, 2) + 0.0358549 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.420049 - 0.0160718 * (t - 12.129) + 3.023440e-002 - * Math.pow(t - 12.129, 2) - 0.0184213 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.415736 - 0.0111184 * (t - 13.134) - 2.530570e-002 - * Math.pow(t - 13.134, 2) + 0.0349448 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.408608 - 0.0119849 * (t - 13.599) + 2.344233e-002 - * Math.pow(t - 13.599, 2) - 0.0286015 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.405228 - 0.00873664 * (t - 14.064) - 1.645683e-002 - * Math.pow(t - 14.064, 2) - 0.0245074 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.395143 - 0.0399389 * (t - 14.529) - 5.064472e-002 - * Math.pow(t - 14.529, 2) - 0.0131914 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.36458 - 0.0951814 * (t - 14.991) - 6.892794e-002 - * Math.pow(t - 14.991, 2) + 0.0254845 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.307979 - 0.142753 * (t - 15.456) - 3.337702e-002 - * Math.pow(t - 15.456, 2) + 0.065268 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.240944 - 0.131456 * (t - 15.921) + 5.767177e-002 - * Math.pow(t - 15.921, 2) + 0.0235208 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.194652 - 0.0625641 * (t - 16.386) + 9.048331e-002 - * Math.pow(t - 16.386, 2) - 0.0359447 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.186679 + 0.0103924 * (t - 17.391) - 1.788984e-002 - * Math.pow(t - 17.391, 2) + 0.03609 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.191272 + 0.0171655 * (t - 17.856) + 3.245578e-002 - * Math.pow(t - 17.856, 2) + 0.015007 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.207781 + 0.0570841 * (t - 18.321) + 5.339052e-002 - * Math.pow(t - 18.321, 2) - 0.0492235 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.24092 + 0.0748072 * (t - 18.786) - 1.527625e-002 - * Math.pow(t - 18.786, 2) - 0.0351776 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.268752 + 0.0381666 * (t - 19.248) - 6.403238e-002 - * Math.pow(t - 19.248, 2) + 0.0247573 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.275143 - 0.00532401 * (t - 19.713) - 2.949588e-002 - * Math.pow(t - 19.713, 2) + 0.0447577 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.27079 - 0.00372197 * (t - 20.178) + 3.294111e-002 - * Math.pow(t - 20.178, 2) - 0.0236137 - * Math.pow(t - 20.178, 3); - - return (0.690441264 - 0.344747388) * y + 0.344747388; - } - - /* - * Splines of the data which should be fit normally. - */ - - /** - * Computes the approximation spline for Leu or returns the default value - * 0.209 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1 - * - * @param t - * @return - */ - public double getLeu(double t) { - double y = 0.209 / (0.523231194 - 0.146383634) - 1 - / (0.523231194 - 0.146383634) * 0.146383634; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.254575 + 0.00234099 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) + 0.00081644 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.255745 + 0.0028706 * (t + 3.429) + 1.138934e-003 - * Math.pow(t + 3.429, 2) + 0.000514239 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.257378 + 0.00426338 * (t + 2.964) + 1.856298e-003 - * Math.pow(t + 2.964, 2) - 4.84395e-005 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.259757 + 0.00595832 * (t + 2.499) + 1.788725e-003 - * Math.pow(t + 2.499, 2) + 0.000191175 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.26291 + 0.00773351 * (t + 2.037) + 2.053693e-003 - * Math.pow(t + 2.037, 2) + 0.000506726 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.267001 + 0.00997215 * (t + 1.572) + 2.760576e-003 - * Math.pow(t + 1.572, 2) + 0.000130631 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.272249 + 0.0126242 * (t + 1.107) + 2.942806e-003 - * Math.pow(t + 1.107, 2) + 0.000206773 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.278776 + 0.0154952 * (t + 0.642) + 3.231255e-003 - * Math.pow(t + 0.642, 2) + 0.000562468 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.298183 + 0.0236943 * (t - 0.363) + 4.927094e-003 - * Math.pow(t - 0.363, 2) - 0.000122853 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.310254 + 0.0281968 * (t - 0.828) + 4.755714e-003 - * Math.pow(t - 0.828, 2) - 0.00023605 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.32437 + 0.0324665 * (t - 1.293) + 4.426424e-003 - * Math.pow(t - 1.293, 2) + 0.000571918 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.340482 + 0.0369541 * (t - 1.758) + 5.224250e-003 - * Math.pow(t - 1.758, 2) + 0.000349374 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.358704 + 0.042005 * (t - 2.22) + 5.708482e-003 - * Math.pow(t - 2.22, 2) - 0.000457706 - * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.379425 + 0.047017 * (t - 2.685) + 5.069983e-003 - * Math.pow(t - 2.685, 2) - 0.00122241 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.402261 + 0.0509391 * (t - 3.15) + 3.364716e-003 - * Math.pow(t - 3.15, 2) - 0.00138177 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.480023 + 0.0518738 * (t - 4.62) - 2.728891e-003 - * Math.pow(t - 4.62, 2) - 0.00128619 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.503425 + 0.0485016 * (t - 5.085) - 4.523131e-003 - * Math.pow(t - 5.085, 2) - 0.00136501 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.524863 + 0.0434096 * (t - 5.55) - 6.427323e-003 - * Math.pow(t - 5.55, 2) - 0.00137626 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.54352 + 0.0365395 * (t - 6.015) - 8.347206e-003 - * Math.pow(t - 6.015, 2) - 0.00181134 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.558441 + 0.0276668 * (t - 6.477) - 1.085772e-002 - * Math.pow(t - 6.477, 2) + 6.90083e-005 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.568965 + 0.0176139 * (t - 6.942) - 1.076145e-002 - * Math.pow(t - 6.942, 2) + 0.000455085 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.574875 + 0.00790092 * (t - 7.407) - 1.012661e-002 - * Math.pow(t - 7.407, 2) + 0.000371085 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.576396 - 0.00127611 * (t - 7.872) - 9.608945e-003 - * Math.pow(t - 7.872, 2) + 0.00127423 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.566702 - 0.0167291 * (t - 8.877) - 5.767152e-003 - * Math.pow(t - 8.877, 2) + 0.00168058 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.557845 - 0.0210024 * (t - 9.342) - 3.422739e-003 - * Math.pow(t - 9.342, 2) + 0.000255359 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.547364 - 0.0240199 * (t - 9.807) - 3.066513e-003 - * Math.pow(t - 9.807, 2) + 0.000486931 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.535581 - 0.0265559 * (t - 10.272) - 2.387245e-003 - * Math.pow(t - 10.272, 2) + 0.000578468 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.52286 - 0.0283913 * (t - 10.734) - 1.585488e-003 - * Math.pow(t - 10.734, 2) - 0.000443537 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.50927 - 0.0301535 * (t - 11.199) - 2.204222e-003 - * Math.pow(t - 11.199, 2) - 0.0010496 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.494667 - 0.0328843 * (t - 11.664) - 3.668415e-003 - * Math.pow(t - 11.664, 2) + 0.000223556 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.478605 - 0.0361509 * (t - 12.129) - 3.356554e-003 - * Math.pow(t - 12.129, 2) + 0.000163983 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.43905 - 0.0424007 * (t - 13.134) - 2.862147e-003 - * Math.pow(t - 13.134, 2) + 1.01014e-005 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.418715 - 0.0450559 * (t - 13.599) - 2.848055e-003 - * Math.pow(t - 13.599, 2) + 0.000100977 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.397159 - 0.0476391 * (t - 14.064) - 2.707192e-003 - * Math.pow(t - 14.064, 2) + 0.00132926 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.374555 - 0.0492946 * (t - 14.529) - 8.528782e-004 - * Math.pow(t - 14.529, 2) + 0.00113715 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.351711 - 0.0493545 * (t - 14.991) + 7.232178e-004 - * Math.pow(t - 14.991, 2) + 0.000573763 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.328975 - 0.0483097 * (t - 15.456) + 1.523618e-003 - * Math.pow(t - 15.456, 2) + 0.000622783 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.306903 - 0.0464887 * (t - 15.921) + 2.392399e-003 - * Math.pow(t - 15.921, 2) + 0.000534396 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.285857 - 0.0439171 * (t - 16.386) + 3.137882e-003 - * Math.pow(t - 16.386, 2) - 0.00061327 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.244267 - 0.0394683 * (t - 17.391) + 1.288872e-003 - * Math.pow(t - 17.391, 2) - 0.000638732 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.226129 - 0.0386839 * (t - 17.856) + 3.978406e-004 - * Math.pow(t - 17.856, 2) - 0.000462192 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.20818 - 0.0386138 * (t - 18.321) - 2.469173e-004 - * Math.pow(t - 18.321, 2) - 0.000260252 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.190145 - 0.0390122 * (t - 18.786) - 6.099692e-004 - * Math.pow(t - 18.786, 2) + 0.000103577 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.172002 - 0.0395095 * (t - 19.248) - 4.664113e-004 - * Math.pow(t - 19.248, 2) + 0.000399364 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.153569 - 0.0396842 * (t - 19.713) + 9.070190e-005 - * Math.pow(t - 19.713, 2) - 0.000254598 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.13511 - 0.039765 * (t - 20.178) - 2.644617e-004 - * Math.pow(t - 20.178, 2) + 0.000189578 - * Math.pow(t - 20.178, 3); - - return (0.523231194 - 0.146383634) * y + 0.146383634; - } - - /** - * Computes the approximation spline for AcLac or returns the default value - * 0.236 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1 - * - * @param t - * @return - */ - public double getAcLac(double t) { - double y = 0.236 / (0.611504694 - 0.19610573) - 0.19610573 - / (0.611504694 - 0.19610573); - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.0509318 + 0.0425125 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) + 3.31769e-005 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.0707035 + 0.0425341 * (t + 3.429) + 4.628182e-005 - * Math.pow(t + 3.429, 2) + 0.000151112 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.090507 + 0.0426751 * (t + 2.964) + 2.570833e-004 - * Math.pow(t + 2.964, 2) + 0.000180795 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.110425 + 0.0430315 * (t + 2.499) + 5.092922e-004 - * Math.pow(t + 2.499, 2) + 0.000385144 - * Math.pow(t + 2.499, 3); - else if (t <= -1.107) - y = 0.130452 + 0.0437487 * (t + 2.037) + 1.043102e-003 - * Math.pow(t + 2.037, 2) + 0.000330749 - * Math.pow(t + 2.037, 3); - else if (t <= -0.642) - y = 0.172306 + 0.0465471 * (t + 1.107) + 1.965893e-003 - * Math.pow(t + 1.107, 2) + 0.000118734 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.194388 + 0.0484524 * (t + 0.642) + 2.131527e-003 - * Math.pow(t + 0.642, 2) - 6.48454e-006 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.245229 + 0.0527171 * (t - 0.363) + 2.111976e-003 - * Math.pow(t - 0.363, 2) - 0.000142806 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.270185 + 0.0545886 * (t - 0.828) + 1.912761e-003 - * Math.pow(t - 0.828, 2) - 6.09975e-005 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.295976 + 0.0563279 * (t - 1.293) + 1.827670e-003 - * Math.pow(t - 1.293, 2) - 0.000197946 - * Math.pow(t - 1.293, 3); - else if (t <= 2.685) - y = 0.322543 + 0.0578992 * (t - 1.758) + 1.551535e-003 - * Math.pow(t - 1.758, 2) - 0.000443952 - * Math.pow(t - 1.758, 3); - else if (t <= 3.15) - y = 0.377196 + 0.0596313 * (t - 2.685) + 3.169039e-004 - * Math.pow(t - 2.685, 2) - 0.000757317 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.404917 + 0.0594347 * (t - 3.15) - 7.395529e-004 - * Math.pow(t - 3.15, 2) - 0.000469621 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.489196 + 0.054216 * (t - 4.62) - 2.810583e-003 - * Math.pow(t - 4.62, 2) - 0.000383922 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.51376 + 0.0513531 * (t - 5.085) - 3.346154e-003 - * Math.pow(t - 5.085, 2) - 0.000500431 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.536865 + 0.0479166 * (t - 5.55) - 4.044255e-003 - * Math.pow(t - 5.55, 2) - 0.000254017 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.558246 + 0.0439907 * (t - 6.015) - 4.398609e-003 - * Math.pow(t - 6.015, 2) - 0.000388999 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.577593 + 0.0396773 * (t - 6.477) - 4.937762e-003 - * Math.pow(t - 6.477, 2) - 0.000299882 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.594945 + 0.0348906 * (t - 6.942) - 5.356098e-003 - * Math.pow(t - 6.942, 2) - 0.000545857 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.609956 + 0.0295554 * (t - 7.407) - 6.117569e-003 - * Math.pow(t - 7.407, 2) - 0.000382667 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.622338 + 0.0236178 * (t - 7.872) - 6.651389e-003 - * Math.pow(t - 7.872, 2) + 8.20287e-005 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.639439 + 0.0104971 * (t - 8.877) - 6.404073e-003 - * Math.pow(t - 8.877, 2) + 6.89544e-006 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.642936 + 0.00454574 * (t - 9.342) - 6.394454e-003 - * Math.pow(t - 9.342, 2) - 0.000265083 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.643641 - 0.00157305 * (t - 9.807) - 6.764245e-003 - * Math.pow(t - 9.807, 2) + 0.000121087 - * Math.pow(t - 9.807, 3); - else if (t <= 11.199) - y = 0.641459 - 0.00778526 * (t - 10.272) - 6.595329e-003 - * Math.pow(t - 10.272, 2) + 0.000427353 - * Math.pow(t - 10.272, 3); - else if (t <= 11.664) - y = 0.628915 - 0.0189113 * (t - 11.199) - 5.406861e-003 - * Math.pow(t - 11.199, 2) + 0.000486639 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.619001 - 0.023624 * (t - 11.664) - 4.727999e-003 - * Math.pow(t - 11.664, 2) + 0.000578078 - * Math.pow(t - 11.664, 3); - else if (t <= 13.599) - y = 0.607052 - 0.027646 * (t - 12.129) - 3.921580e-003 - * Math.pow(t - 12.129, 2) + 0.000195159 - * Math.pow(t - 12.129, 3); - else if (t <= 14.064) - y = 0.558558 - 0.0379103 * (t - 13.599) - 3.060930e-003 - * Math.pow(t - 13.599, 2) + 0.000134031 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.540281 - 0.0406701 * (t - 14.064) - 2.873957e-003 - * Math.pow(t - 14.064, 2) + 0.000338369 - * Math.pow(t - 14.064, 3); - else if (t <= 15.456) - y = 0.520782 - 0.0431233 * (t - 14.529) - 2.401931e-003 - * Math.pow(t - 14.529, 2) + 0.000422293 - * Math.pow(t - 14.529, 3); - else if (t <= 15.921) - y = 0.479079 - 0.0464879 * (t - 15.456) - 1.227535e-003 - * Math.pow(t - 15.456, 2) + 0.000404677 - * Math.pow(t - 15.456, 3); - else if (t <= 17.391) - y = 0.457237 - 0.047367 * (t - 15.921) - 6.630106e-004 - * Math.pow(t - 15.921, 2) + 0.000286727 - * Math.pow(t - 15.921, 3); - else if (t <= 17.856) - y = 0.387086 - 0.0474575 * (t - 17.391) + 6.014537e-004 - * Math.pow(t - 17.391, 2) + 0.000196116 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.365168 - 0.0467709 * (t - 17.856) + 8.750362e-004 - * Math.pow(t - 17.856, 2) + 5.04267e-005 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.343614 - 0.0459244 * (t - 18.321) + 9.453814e-004 - * Math.pow(t - 18.321, 2) - 0.000240636 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.322439 - 0.0452013 * (t - 18.786) + 6.096940e-004 - * Math.pow(t - 18.786, 2) - 0.000241968 - * Math.pow(t - 18.786, 3); - else if (t <= 20.178) - y = 0.301663 - 0.0447929 * (t - 19.248) + 2.743264e-004 - * Math.pow(t - 19.248, 2) - 6.72243e-005 - * Math.pow(t - 19.248, 3); - else if (t <= 20.643) - y = 0.260188 - 0.044457 * (t - 20.178) + 8.677062e-005 - * Math.pow(t - 20.178, 2) - 6.22012e-005 - * Math.pow(t - 20.178, 3); - - return (0.611504694 - 0.19610573) * y + 0.19610573; - } - - /** - * Computes the approximation spline for KIC or returns the default value - * 0.0741 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1 - * - * @param t - * @return - */ - public double getKIC(double t) { - double y = 0.0741 / (0.160177175 - 0.044088231) - 0.044088231 - / (0.160177175 - 0.044088231); - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.59717 - 0.253511 * (t + 3.894) + 0 * Math.pow(t + 3.894, 2) - + 0.030027 * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.482307 - 0.234033 * (t + 3.429) + 4.188770e-002 - * Math.pow(t + 3.429, 2) + 0.00577486 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.38312 - 0.191331 * (t + 2.964) + 4.994363e-002 - * Math.pow(t + 2.964, 2) - 0.0102897 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.303915 - 0.151558 * (t + 2.499) + 3.558955e-002 - * Math.pow(t + 2.499, 2) + 0.0218333 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.243645 - 0.104693 * (t + 2.037) + 6.585046e-002 - * Math.pow(t + 2.037, 2) + 0.0141498 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.210624 - 0.0342735 * (t + 1.572) + 8.558938e-002 - * Math.pow(t + 1.572, 2) - 0.0352163 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.209652 + 0.0224808 * (t + 1.107) + 3.646268e-002 - * Math.pow(t + 1.107, 2) - 0.00295964 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.227692 + 0.0544712 * (t + 0.642) + 3.233398e-002 - * Math.pow(t + 0.642, 2) + 0.00254454 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.317677 + 0.127173 * (t - 0.363) + 4.000576e-002 - * Math.pow(t - 0.363, 2) - 0.0129362 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.384162 + 0.155987 * (t - 0.828) + 2.195974e-002 - * Math.pow(t - 0.828, 2) - 0.0561687 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.455796 + 0.139974 * (t - 1.293) - 5.639562e-002 - * Math.pow(t - 1.293, 2) - 0.00820249 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.507865 + 0.0822052 * (t - 1.758) - 6.783810e-002 - * Math.pow(t - 1.758, 2) + 0.0262569 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.533954 + 0.036336 * (t - 2.22) - 3.144602e-002 - * Math.pow(t - 2.22, 2) + 0.0235729 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.546421 + 0.0223823 * (t - 2.685) + 1.438178e-003 - * Math.pow(t - 2.685, 2) + 0.00200063 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.557341 + 0.0250176 * (t - 3.15) + 4.229058e-003 - * Math.pow(t - 3.15, 2) + 0.00309548 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.613088 + 0.0575181 * (t - 4.62) + 1.788011e-002 - * Math.pow(t - 4.62, 2) - 0.0103307 * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.642661 + 0.0674453 * (t - 5.085) + 3.468802e-003 - * Math.pow(t - 5.085, 2) - 0.0224198 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.672519 + 0.0561282 * (t - 5.55) - 2.780675e-002 - * Math.pow(t - 5.55, 2) - 0.00483441 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.69212 + 0.0271319 * (t - 6.015) - 3.455076e-002 - * Math.pow(t - 6.015, 2) - 0.00777974 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.696513 - 0.0097746 * (t - 6.477) - 4.533348e-002 - * Math.pow(t - 6.477, 2) + 0.0117564 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.683348 - 0.0443086 * (t - 6.942) - 2.893330e-002 - * Math.pow(t - 6.942, 2) + 0.019275 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.658426 - 0.0587134 * (t - 7.407) - 2.044715e-003 - * Math.pow(t - 7.407, 2) - 0.00188787 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.630492 - 0.0618396 * (t - 7.872) - 4.678294e-003 - * Math.pow(t - 7.872, 2) - 9.30383e-005 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.563524 - 0.0715249 * (t - 8.877) - 4.958805e-003 - * Math.pow(t - 8.877, 2) + 0.0222099 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.531426 - 0.0617296 * (t - 9.342) + 2.602397e-002 - * Math.pow(t - 9.342, 2) - 0.022373 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.506099 - 0.0520401 * (t - 9.807) - 5.186390e-003 - * Math.pow(t - 9.807, 2) - 0.00875147 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.479899 - 0.0625403 * (t - 10.272) - 1.739469e-002 - * Math.pow(t - 10.272, 2) + 0.0272157 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.449976 - 0.061186 * (t - 10.734) + 2.032624e-002 - * Math.pow(t - 10.734, 2) - 0.0227538 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.423632 - 0.0570424 * (t - 11.199) - 1.141533e-002 - * Math.pow(t - 11.199, 2) - 0.0117263 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.39346 - 0.0752652 * (t - 11.664) - 2.777356e-002 - * Math.pow(t - 11.664, 2) + 0.0185337 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.35432 - 0.0890723 * (t - 12.129) - 1.918985e-003 - * Math.pow(t - 12.129, 2) + 0.0246405 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.287876 - 0.0182668 * (t - 13.134) + 7.237216e-002 - * Math.pow(t - 13.134, 2) - 0.0167059 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.293351 + 0.0382026 * (t - 13.599) + 4.906743e-002 - * Math.pow(t - 13.599, 2) - 0.0121101 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.320507 + 0.0759798 * (t - 14.064) + 3.217383e-002 - * Math.pow(t - 14.064, 2) - 0.0148388 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.361303 + 0.0962759 * (t - 14.529) + 1.147372e-002 - * Math.pow(t - 14.529, 2) + 0.0191581 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.41012 + 0.119145 * (t - 14.991) + 3.802679e-002 - * Math.pow(t - 14.991, 2) - 0.0570551 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.468009 + 0.1175 * (t - 15.456) - 4.156503e-002 - * Math.pow(t - 15.456, 2) - 0.0132887 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.512323 + 0.0702243 * (t - 15.921) - 6.010273e-002 - * Math.pow(t - 15.921, 2) + 0.0551508 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.537526 + 0.0501038 * (t - 16.386) + 1.683269e-002 - * Math.pow(t - 16.386, 2) - 0.016235 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.588402 + 0.0347443 * (t - 17.391) - 3.211571e-002 - * Math.pow(t - 17.391, 2) + 0.00952971 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.598572 + 0.0110584 * (t - 17.856) - 1.882176e-002 - * Math.pow(t - 17.856, 2) + 0.000769216 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.599722 - 0.00594685 * (t - 18.321) - 1.774871e-002 - * Math.pow(t - 18.321, 2) + 0.0316399 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.5963 - 0.00192916 * (t - 18.786) + 2.638891e-002 - * Math.pow(t - 18.786, 2) + 0.00874813 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.601904 + 0.0280559 * (t - 19.248) + 3.851381e-002 - * Math.pow(t - 19.248, 2) + 0.00607335 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.623889 + 0.0678134 * (t - 19.713) + 4.698613e-002 - * Math.pow(t - 19.713, 2) - 0.0566996 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.659881 + 0.0747309 * (t - 20.178) - 3.210978e-002 - * Math.pow(t - 20.178, 2) + 0.0230178 - * Math.pow(t - 20.178, 3); - - return (0.160177175 - 0.044088231) * y + 0.044088231; - } - - /** - * Computes the approximation spline for 2IPM or returns the default value - * 0.0227 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1 - * - * @param t - * @return - */ - public double getIPM(double t) { - double y = 0.0227 / (0.036305123 - 0.015512247) - 0.015512247 - / (0.036305123 - 0.015512247); - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.0802829 + 0.147166 * (t + 3.894) + 0 * Math.pow(t + 3.894, 2) - - 0.00476735 * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.148236 + 0.144073 * (t + 3.429) - 6.650452e-003 - * Math.pow(t + 3.429, 2) - 0.0159672 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.212186 + 0.127531 * (t + 2.964) - 2.892476e-002 - * Math.pow(t + 2.964, 2) - 0.00496333 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.264735 + 0.0974111 * (t + 2.499) - 3.584861e-002 - * Math.pow(t + 2.499, 2) + 0.00466081 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.302547 + 0.0672715 * (t + 2.037) - 2.938873e-002 - * Math.pow(t + 2.037, 2) + 0.0120304 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.328683 + 0.0477438 * (t + 1.572) - 1.260631e-002 - * Math.pow(t + 1.572, 2) + 0.00568681 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.34873 + 0.0397088 * (t + 1.107) - 4.673207e-003 - * Math.pow(t + 1.107, 2) - 6.69227e-006 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.366183 + 0.0353584 * (t + 0.642) - 4.682543e-003 - * Math.pow(t + 0.642, 2) + 0.00262408 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.399652 + 0.0338976 * (t - 0.363) + 3.229045e-003 - * Math.pow(t - 0.363, 2) - 0.0171221 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.414391 + 0.0257939 * (t - 0.828) - 2.065624e-002 - * Math.pow(t - 0.828, 2) - 0.0198038 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.419928 - 0.00626258 * (t - 1.293) - 4.828252e-002 - * Math.pow(t - 1.293, 2) + 0.000911555 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.406668 - 0.050574 * (t - 1.758) - 4.701090e-002 - * Math.pow(t - 1.758, 2) + 0.0126306 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.374514 - 0.0859243 * (t - 2.22) - 2.950484e-002 - * Math.pow(t - 2.22, 2) + 0.0240615 * Math.pow(t - 2.22, 3); - else if (t <= 4.62) - y = 0.330599 - 0.0977557 * (t - 2.685) + 4.060973e-003 - * Math.pow(t - 2.685, 2) + 0.0170498 - * Math.pow(t - 2.685, 3); - else if (t <= 5.085) - y = 0.280174 + 0.109475 * (t - 4.62) + 1.030351e-001 - * Math.pow(t - 4.62, 2) - 0.00730802 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.352624 + 0.200557 * (t - 5.085) + 9.284036e-002 - * Math.pow(t - 5.085, 2) - 0.0489522 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.461035 + 0.255145 * (t - 5.55) + 2.455205e-002 - * Math.pow(t - 5.55, 2) - 0.020076 * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.582968 + 0.264955 * (t - 6.015) - 3.453901e-003 - * Math.pow(t - 6.015, 2) - 0.0597257 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.69875 + 0.22352 * (t - 6.477) - 8.623371e-002 - * Math.pow(t - 6.477, 2) - 0.0241487 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.781613 + 0.127658 * (t - 6.942) - 1.199211e-001 - * Math.pow(t - 6.942, 2) + 0.00139353 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.815184 + 0.017035 * (t - 7.407) - 1.179771e-001 - * Math.pow(t - 7.407, 2) + 0.012143 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.798817 - 0.0848069 * (t - 7.872) - 1.010377e-001 - * Math.pow(t - 7.872, 2) + 0.0267053 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.638643 - 0.206974 * (t - 8.877) - 2.052130e-002 - * Math.pow(t - 8.877, 2) + 0.0393006 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.541914 - 0.200565 * (t - 9.342) + 3.430310e-002 - * Math.pow(t - 9.342, 2) + 0.0182556 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.457904 - 0.156821 * (t - 9.807) + 5.976968e-002 - * Math.pow(t - 9.807, 2) + 0.0154081 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.399455 - 0.0912406 * (t - 10.272) + 8.126393e-002 - * Math.pow(t - 10.272, 2) + 0.00115016 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.374761 - 0.0154163 * (t - 10.734) + 8.285805e-002 - * Math.pow(t - 10.734, 2) - 0.0285911 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.382634 + 0.0430954 * (t - 11.199) + 4.297352e-002 - * Math.pow(t - 11.199, 2) - 0.0330048 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.408646 + 0.0616514 * (t - 11.664) - 3.068147e-003 - * Math.pow(t - 11.664, 2) - 0.0116522 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.435479 + 0.0512395 * (t - 12.129) - 1.932292e-002 - * Math.pow(t - 12.129, 2) + 0.00415678 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.471678 + 0.0249958 * (t - 13.134) - 6.790222e-003 - * Math.pow(t - 13.134, 2) - 0.00667273 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.481162 + 0.0143525 * (t - 13.599) - 1.609868e-002 - * Math.pow(t - 13.599, 2) - 0.00529352 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.483823 - 0.00405304 * (t - 14.064) - 2.348313e-002 - * Math.pow(t - 14.064, 2) + 0.0139118 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.478259 - 0.0168681 * (t - 14.529) - 4.076173e-003 - * Math.pow(t - 14.529, 2) + 0.0177102 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.471342 - 0.00929412 * (t - 14.991) + 2.047010e-002 - * Math.pow(t - 14.991, 2) - 0.00568797 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.470875 + 0.00605343 * (t - 15.456) + 1.253539e-002 - * Math.pow(t - 15.456, 2) - 0.00718501 - * Math.pow(t - 15.456, 3); - else if (t <= 17.391) - y = 0.475678 + 0.0130506 * (t - 15.921) + 2.512302e-003 - * Math.pow(t - 15.921, 2) + 0.000255298 - * Math.pow(t - 15.921, 3); - else if (t <= 17.856) - y = 0.501102 + 0.0220918 * (t - 17.391) + 3.638165e-003 - * Math.pow(t - 17.391, 2) - 0.00625479 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.511532 + 0.021418 * (t - 17.856) - 5.087271e-003 - * Math.pow(t - 17.856, 2) - 0.00605154 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.519783 + 0.0127613 * (t - 18.321) - 1.352917e-002 - * Math.pow(t - 18.321, 2) + 0.004627 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.523257 + 0.0031806 * (t - 18.786) - 7.074514e-003 - * Math.pow(t - 18.786, 2) + 0.0194544 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.525135 + 0.00910103 * (t - 19.248) + 1.988931e-002 - * Math.pow(t - 19.248, 2) + 0.0103778 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.534711 + 0.0343299 * (t - 19.713) + 3.436634e-002 - * Math.pow(t - 19.713, 2) - 0.0213188 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.555962 + 0.0524616 * (t - 20.178) + 4.626590e-003 - * Math.pow(t - 20.178, 2) - 0.00331655 - * Math.pow(t - 20.178, 3); - - return (0.036305123 - 0.015512247) * y + 0.015512247; - } - - /** - * Computes the approximation spline for Val or returns the default value - * 29.4 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1 - * - * @param t - * @return - */ - public double getVal(double t) { - double y = 29.4 / (52.21398298 - 23.23780872) - 23.23780872 - / (52.21398298 - 23.23780872); - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.0870064 + 0.0543556 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) - 8.90776e-006 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.112281 + 0.0543499 * (t + 3.429) - 1.242632e-005 - * Math.pow(t + 3.429, 2) + 1.75913e-005 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.137553 + 0.0543497 * (t + 2.964) + 1.211360e-005 - * Math.pow(t + 2.964, 2) + 2.31931e-005 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.16283 + 0.054376 * (t + 2.499) + 4.446802e-005 - * Math.pow(t + 2.499, 2) + 9.65747e-005 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.187971 + 0.054479 * (t + 2.037) + 1.783206e-004 - * Math.pow(t + 2.037, 2) + 9.66717e-005 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.213352 + 0.0547075 * (t + 1.572) + 3.131776e-004 - * Math.pow(t + 1.572, 2) - 2.3386e-005 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.238856 + 0.0549836 * (t + 1.107) + 2.805541e-004 - * Math.pow(t + 1.107, 2) - 6.40501e-005 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.264478 + 0.055203 * (t + 0.642) + 1.912042e-004 - * Math.pow(t + 0.642, 2) - 5.51172e-005 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.320094 + 0.0554203 * (t - 0.363) + 2.502589e-005 - * Math.pow(t - 0.363, 2) - 0.000155647 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.345854 + 0.0553426 * (t - 0.828) - 1.921018e-004 - * Math.pow(t - 0.828, 2) - 0.000211048 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.371526 + 0.055027 * (t - 1.293) - 4.865138e-004 - * Math.pow(t - 1.293, 2) - 0.000182501 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.39699 + 0.0544562 * (t - 1.758) - 7.411022e-004 - * Math.pow(t - 1.758, 2) - 0.000172656 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.421973 + 0.0536608 * (t - 2.22) - 9.804033e-004 - * Math.pow(t - 2.22, 2) - 0.000243037 - * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.446689 + 0.0525914 * (t - 2.685) - 1.319440e-003 - * Math.pow(t - 2.685, 2) - 0.000377847 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.470821 + 0.0511192 * (t - 3.15) - 1.846537e-003 - * Math.pow(t - 3.15, 2) - 0.000398585 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.54071 + 0.0431065 * (t - 4.62) - 3.604295e-003 - * Math.pow(t - 4.62, 2) - 0.000432186 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.559932 + 0.0394742 * (t - 5.085) - 4.207195e-003 - * Math.pow(t - 5.085, 2) - 0.000381397 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.577339 + 0.0353141 * (t - 5.55) - 4.739244e-003 - * Math.pow(t - 5.55, 2) - 0.00029943 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.592705 + 0.0307123 * (t - 6.015) - 5.156948e-003 - * Math.pow(t - 6.015, 2) - 0.0002747 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.605767 + 0.0257714 * (t - 6.477) - 5.537682e-003 - * Math.pow(t - 6.477, 2) - 6.94366e-005 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.616546 + 0.0205763 * (t - 6.942) - 5.634546e-003 - * Math.pow(t - 6.942, 2) + 4.67127e-005 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.6249 + 0.0153665 * (t - 7.407) - 5.569382e-003 - * Math.pow(t - 7.407, 2) + 7.60338e-005 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.630849 + 0.0102363 * (t - 7.872) - 5.463315e-003 - * Math.pow(t - 7.872, 2) + 0.000283763 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.635907 + 0.000114872 * (t - 8.877) - 4.607770e-003 - * Math.pow(t - 8.877, 2) + 0.000347457 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.634999 - 0.00394497 * (t - 9.342) - 4.123067e-003 - * Math.pow(t - 9.342, 2) + 0.000216058 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.632294 - 0.00763927 * (t - 9.807) - 3.821667e-003 - * Math.pow(t - 9.807, 2) + 0.000216223 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.627938 - 0.0110532 * (t - 10.272) - 3.520036e-003 - * Math.pow(t - 10.272, 2) + 0.000263321 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.622106 - 0.0141371 * (t - 10.734) - 3.155073e-003 - * Math.pow(t - 10.734, 2) + 0.000162254 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.614866 - 0.016966 * (t - 11.199) - 2.928729e-003 - * Math.pow(t - 11.199, 2) + 0.000177556 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.606361 - 0.0195746 * (t - 11.664) - 2.681039e-003 - * Math.pow(t - 11.664, 2) + 0.000286342 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.596708 - 0.0218822 * (t - 12.129) - 2.281591e-003 - * Math.pow(t - 12.129, 2) + 0.000264022 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.57268 - 0.0256682 * (t - 13.134) - 1.485566e-003 - * Math.pow(t - 13.134, 2) + 0.00012945 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.560436 - 0.0269658 * (t - 13.599) - 1.304983e-003 - * Math.pow(t - 13.599, 2) + 7.46932e-005 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.547623 - 0.028131 * (t - 14.064) - 1.200785e-003 - * Math.pow(t - 14.064, 2) + 9.72656e-005 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.534292 - 0.0291846 * (t - 14.529) - 1.065100e-003 - * Math.pow(t - 14.529, 2) + 0.000148594 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.520596 - 0.0300736 * (t - 14.991) - 8.591482e-004 - * Math.pow(t - 14.991, 2) + 6.92071e-006 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.506427 - 0.0308681 * (t - 15.456) - 8.494938e-004 - * Math.pow(t - 15.456, 2) + 1.28187e-005 - * Math.pow(t - 15.456, 3); - else if (t <= 17.391) - y = 0.49189 - 0.0316498 * (t - 15.921) - 8.316116e-004 - * Math.pow(t - 15.921, 2) + 0.000101901 - * Math.pow(t - 15.921, 3); - else if (t <= 17.856) - y = 0.443892 - 0.0334342 * (t - 17.391) - 3.822275e-004 - * Math.pow(t - 17.391, 2) + 6.02688e-005 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.428268 - 0.0337506 * (t - 17.856) - 2.981526e-004 - * Math.pow(t - 17.856, 2) + 6.12216e-006 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.41251 - 0.0340239 * (t - 18.321) - 2.896122e-004 - * Math.pow(t - 18.321, 2) + 0.000113406 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.396638 - 0.0342197 * (t - 18.786) - 1.314102e-004 - * Math.pow(t - 18.786, 2) + 0.00010335 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.380811 - 0.0342749 * (t - 19.248) + 1.183285e-005 - * Math.pow(t - 19.248, 2) + 8.32616e-005 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.364884 - 0.0342099 * (t - 19.713) + 1.279827e-004 - * Math.pow(t - 19.713, 2) - 7.86715e-005 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.348996 - 0.0341419 * (t - 20.178) + 1.823597e-005 - * Math.pow(t - 20.178, 2) - 1.30724e-005 - * Math.pow(t - 20.178, 3); - - return (52.21398298 - 23.23780872) * y + 23.23780872; - } - - /** - * Computes the approximation spline for DHIV or returns the default value - * 0.132 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1 - * - * @param t - * @return - */ - public double getDHIV(double t) { - double y = 0.132 / (1.19712426 - 0.077317889) - 0.077317889 - / (1.19712426 - 0.077317889); - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.0260752 + 0.0333816 * (t + 3.894) + 0 - * Math.pow(t + 3.894, 2) + 0.000123214 - * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.0416101 + 0.0334615 * (t + 3.429) + 1.718840e-004 - * Math.pow(t + 3.429, 2) - 4.6372e-005 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.0572022 + 0.0335913 * (t + 2.964) + 1.071950e-004 - * Math.pow(t + 2.964, 2) - 0.000289114 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.0728163 + 0.0335035 * (t + 2.499) - 2.961193e-004 - * Math.pow(t + 2.499, 2) + 0.000359848 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.0882672 + 0.0334603 * (t + 2.037) + 2.026304e-004 - * Math.pow(t + 2.037, 2) - 2.17354e-006 - * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.10387 + 0.0336473 * (t + 1.572) + 1.995983e-004 - * Math.pow(t + 1.572, 2) - 0.00063401 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.119495 + 0.0334217 * (t + 1.107) - 6.848463e-004 - * Math.pow(t + 1.107, 2) - 0.000741887 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.134814 + 0.0323035 * (t + 0.642) - 1.719778e-003 - * Math.pow(t + 0.642, 2) - 0.000393869 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.165142 + 0.0276533 * (t - 0.363) - 2.907293e-003 - * Math.pow(t - 0.363, 2) - 0.000577236 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.177314 + 0.0245751 * (t - 0.828) - 3.712538e-003 - * Math.pow(t - 0.828, 2) + 0.000685274 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.188008 + 0.021567 * (t - 1.293) - 2.756581e-003 - * Math.pow(t - 1.293, 2) + 0.001929 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.197634 + 0.0202546 * (t - 1.758) - 6.562414e-005 - * Math.pow(t - 1.758, 2) + 0.00226985 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.207202 + 0.0216475 * (t - 2.22) + 3.080384e-003 - * Math.pow(t - 2.22, 2) + 0.00155965 - * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.21809 + 0.0255239 * (t - 2.685) + 5.256091e-003 - * Math.pow(t - 2.685, 2) + 0.000714349 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.231167 + 0.0308755 * (t - 3.15) + 6.252608e-003 - * Math.pow(t - 3.15, 2) - 0.000271997 - * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.289202 + 0.0474948 * (t - 4.62) + 5.053102e-003 - * Math.pow(t - 4.62, 2) - 0.00110133 - * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.312269 + 0.0514798 * (t - 5.085) + 3.516751e-003 - * Math.pow(t - 5.085, 2) - 0.00184457 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.336782 + 0.0535539 * (t - 5.55) + 9.435794e-004 - * Math.pow(t - 5.55, 2) - 0.00232587 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.361654 + 0.0529227 * (t - 6.015) - 2.301005e-003 - * Math.pow(t - 6.015, 2) - 0.00310515 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.385307 + 0.0488082 * (t - 6.477) - 6.604749e-003 - * Math.pow(t - 6.477, 2) - 0.00428991 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.406144 + 0.039883 * (t - 6.942) - 1.258918e-002 - * Math.pow(t - 6.942, 2) - 0.00315302 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.42165 + 0.0261298 * (t - 7.407) - 1.698764e-002 - * Math.pow(t - 7.407, 2) - 0.00115594 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.430011 + 0.0095815 * (t - 7.872) - 1.860017e-002 - * Math.pow(t - 7.872, 2) + 0.00231129 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.4232 - 0.0208015 * (t - 8.877) - 1.163163e-002 - * Math.pow(t - 8.877, 2) + 0.00400521 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.411415 - 0.0290208 * (t - 9.342) - 6.044358e-003 - * Math.pow(t - 9.342, 2) + 0.00244262 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.396859 - 0.0330576 * (t - 9.807) - 2.636904e-003 - * Math.pow(t - 9.807, 2) + 0.00186923 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.381105 - 0.0342974 * (t - 10.272) - 2.933415e-005 - * Math.pow(t - 10.272, 2) + 0.00120579 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.365372 - 0.0335524 * (t - 10.734) + 1.641895e-003 - * Math.pow(t - 10.734, 2) - 5.22663e-005 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.35012 - 0.0320593 * (t - 11.199) + 1.568984e-003 - * Math.pow(t - 11.199, 2) - 0.000303024 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.335521 - 0.0307967 * (t - 11.664) + 1.146266e-003 - * Math.pow(t - 11.664, 2) + 0.000186394 - * Math.pow(t - 11.664, 3); - else if (t <= 13.599) - y = 0.321468 - 0.0296098 * (t - 12.129) + 1.406286e-003 - * Math.pow(t - 12.129, 2) + 0.000205413 - * Math.pow(t - 12.129, 3); - else if (t <= 14.064) - y = 0.281632 - 0.0241437 * (t - 13.599) + 2.312159e-003 - * Math.pow(t - 13.599, 2) + 1.21887e-005 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.270907 - 0.0219855 * (t - 14.064) + 2.329162e-003 - * Math.pow(t - 14.064, 2) + 0.000331498 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.261221 - 0.0196043 * (t - 14.529) + 2.791602e-003 - * Math.pow(t - 14.529, 2) + 0.000948267 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.252853 - 0.0164177 * (t - 14.991) + 4.105900e-003 - * Math.pow(t - 14.991, 2) + 0.00039227 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.246146 - 0.0123447 * (t - 15.456) + 4.653117e-003 - * Math.pow(t - 15.456, 2) - 9.30071e-005 - * Math.pow(t - 15.456, 3); - else if (t <= 17.391) - y = 0.241402 - 0.00807765 * (t - 15.921) + 4.523372e-003 - * Math.pow(t - 15.921, 2) - 0.000264229 - * Math.pow(t - 15.921, 3); - else if (t <= 17.856) - y = 0.238463 + 0.00350815 * (t - 17.391) + 3.358124e-003 - * Math.pow(t - 17.391, 2) - 0.000570568 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.240763 + 0.00626109 * (t - 17.856) + 2.562182e-003 - * Math.pow(t - 17.856, 2) - 0.000894847 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.244139 + 0.00806346 * (t - 18.321) + 1.313871e-003 - * Math.pow(t - 18.321, 2) - 0.000591935 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.248113 + 0.00890138 * (t - 18.786) + 4.881216e-004 - * Math.pow(t - 18.786, 2) - 0.000289939 - * Math.pow(t - 18.786, 3); - else if (t <= 20.178) - y = 0.252301 + 0.00916675 * (t - 19.248) + 8.626680e-005 - * Math.pow(t - 19.248, 2) + 1.10962e-005 - * Math.pow(t - 19.248, 3); - else if (t <= 20.643) - y = 0.26091 + 0.009356 * (t - 20.178) + 1.172251e-004 - * Math.pow(t - 20.178, 2) - 8.40323e-005 - * Math.pow(t - 20.178, 3); - - return (1.19712426 - 0.077317889) * y + 0.077317889; - } - - /** - * Computes the approximation spline for KIV or returns the default value - * 13.1 mM if t is not in the measured time intervall. Parameter for the - * spline: weights all equal to one, S=1 - * - * @param t - * @return - */ - public double getKIV(double t) { - double y = 13.1 / (16.97282365372 - 6.68584901645) - 6.68584901645 - / (16.97282365372 - 6.68584901645); - ; - - if ((-3.894 <= t) && (t <= -3.429)) - y = 0.632703 - 0.200248 * (t + 3.894) + 0 * Math.pow(t + 3.894, 2) - - 0.00683388 * Math.pow(t + 3.894, 3); - else if (t <= -2.964) - y = 0.5389 - 0.204681 * (t + 3.429) - 9.533265e-03 - * Math.pow(t + 3.429, 2) - 0.00451643 - * Math.pow(t + 3.429, 3); - else if (t <= -2.499) - y = 0.441208 - 0.216476 * (t + 2.964) - 1.583368e-02 - * Math.pow(t + 2.964, 2) + 0.0280129 - * Math.pow(t + 2.964, 3); - else if (t <= -2.037) - y = 0.33994 - 0.21303 * (t + 2.499) + 2.324431e-02 - * Math.pow(t + 2.499, 2) + 0.00505588 - * Math.pow(t + 2.499, 3); - else if (t <= -1.572) - y = 0.24698 - 0.188315 * (t + 2.037) + 3.025176e-02 - * Math.pow(t + 2.037, 2) + 0.03962 * Math.pow(t + 2.037, 3); - else if (t <= -1.107) - y = 0.169938 - 0.134481 * (t + 1.572) + 8.552163e-02 - * Math.pow(t + 1.572, 2) - 0.0174838 - * Math.pow(t + 1.572, 3); - else if (t <= -0.642) - y = 0.124138 - 0.0662868 * (t + 1.107) + 6.113172e-02 - * Math.pow(t + 1.107, 2) - 0.0274919 - * Math.pow(t + 1.107, 3); - else if (t <= 0.363) - y = 0.103769 - 0.0272676 * (t + 0.642) + 2.278052e-02 - * Math.pow(t + 0.642, 2) + 0.0264526 - * Math.pow(t + 0.642, 3); - else if (t <= 0.828) - y = 0.126225 + 0.0986746 * (t - 0.363) + 1.025350e-01 - * Math.pow(t - 0.363, 2) - 0.0423241 - * Math.pow(t - 0.363, 3); - else if (t <= 1.293) - y = 0.190024 + 0.166578 * (t - 0.828) + 4.349295e-02 - * Math.pow(t - 0.828, 2) - 0.104603 - * Math.pow(t - 0.828, 3); - else if (t <= 1.758) - y = 0.26637 + 0.139173 * (t - 1.293) - 1.024283e-01 - * Math.pow(t - 1.293, 2) + 0.0573769 - * Math.pow(t - 1.293, 3); - else if (t <= 2.22) - y = 0.314706 + 0.0811332 * (t - 1.758) - 2.238759e-02 - * Math.pow(t - 1.758, 2) + 0.092514 - * Math.pow(t - 1.758, 3); - else if (t <= 2.685) - y = 0.356534 + 0.119687 * (t - 2.22) + 1.058368e-01 - * Math.pow(t - 2.22, 2) + 0.0101367 * Math.pow(t - 2.22, 3); - else if (t <= 3.15) - y = 0.436093 + 0.22469 * (t - 2.685) + 1.199775e-01 - * Math.pow(t - 2.685, 2) - 0.107935 - * Math.pow(t - 2.685, 3); - else if (t <= 4.62) - y = 0.555663 + 0.266255 * (t - 3.15) - 3.059157e-02 - * Math.pow(t - 3.15, 2) - 0.0125683 * Math.pow(t - 3.15, 3); - else if (t <= 5.085) - y = 0.84103 + 0.0948394 * (t - 4.62) - 8.601761e-02 - * Math.pow(t - 4.62, 2) - 0.012452 * Math.pow(t - 4.62, 3); - else if (t <= 5.55) - y = 0.865279 + 0.00676576 * (t - 5.085) - 1.033881e-01 - * Math.pow(t - 5.085, 2) + 0.0609538 - * Math.pow(t - 5.085, 3); - else if (t <= 6.015) - y = 0.852198 - 0.049846 * (t - 5.55) - 1.835756e-02 - * Math.pow(t - 5.55, 2) + 0.00816093 - * Math.pow(t - 5.55, 3); - else if (t <= 6.477) - y = 0.825871 - 0.0616247 * (t - 6.015) - 6.973056e-03 - * Math.pow(t - 6.015, 2) - 0.0446731 - * Math.pow(t - 6.015, 3); - else if (t <= 6.942) - y = 0.791507 - 0.0966734 * (t - 6.477) - 6.888994e-02 - * Math.pow(t - 6.477, 2) + 0.0172469 - * Math.pow(t - 6.477, 3); - else if (t <= 7.407) - y = 0.733392 - 0.149553 * (t - 6.942) - 4.483048e-02 - * Math.pow(t - 6.942, 2) + 0.0734141 - * Math.pow(t - 6.942, 3); - else if (t <= 7.872) - y = 0.661538 - 0.143624 * (t - 7.407) + 5.758222e-02 - * Math.pow(t - 7.407, 2) - 0.054382 - * Math.pow(t - 7.407, 3); - else if (t <= 8.877) - y = 0.601735 - 0.125349 * (t - 7.872) - 1.828061e-02 - * Math.pow(t - 7.872, 2) + 0.0141796 - * Math.pow(t - 7.872, 3); - else if (t <= 9.342) - y = 0.47169 - 0.119127 * (t - 8.877) + 2.447087e-02 - * Math.pow(t - 8.877, 2) + 0.0322437 - * Math.pow(t - 8.877, 3); - else if (t <= 9.807) - y = 0.424829 - 0.0754538 * (t - 9.342) + 6.945085e-02 - * Math.pow(t - 9.342, 2) - 0.0325761 - * Math.pow(t - 9.342, 3); - else if (t <= 10.272) - y = 0.401484 - 0.0319958 * (t - 9.807) + 2.400726e-02 - * Math.pow(t - 9.807, 2) + 0.00495286 - * Math.pow(t - 9.807, 3); - else if (t <= 10.734) - y = 0.392295 - 0.00645621 * (t - 10.272) + 3.091651e-02 - * Math.pow(t - 10.272, 2) + 0.013472 - * Math.pow(t - 10.272, 3); - else if (t <= 11.199) - y = 0.39724 + 0.0307372 * (t - 10.734) + 4.958866e-02 - * Math.pow(t - 10.734, 2) - 0.0875034 - * Math.pow(t - 10.734, 3); - else if (t <= 11.664) - y = 0.413457 + 0.0200934 * (t - 11.199) - 7.247858e-02 - * Math.pow(t - 11.199, 2) - 0.0360727 - * Math.pow(t - 11.199, 3); - else if (t <= 12.129) - y = 0.403502 - 0.0707112 * (t - 11.664) - 1.228001e-01 - * Math.pow(t - 11.664, 2) + 0.0618963 - * Math.pow(t - 11.664, 3); - else if (t <= 13.134) - y = 0.350292 - 0.144765 * (t - 12.129) - 3.645476e-02 - * Math.pow(t - 12.129, 2) + 0.0517422 - * Math.pow(t - 12.129, 3); - else if (t <= 13.599) - y = 0.220505 - 0.061256 * (t - 13.134) + 1.195480e-01 - * Math.pow(t - 13.134, 2) - 0.0272394 - * Math.pow(t - 13.134, 3); - else if (t <= 14.064) - y = 0.215132 + 0.0322542 * (t - 13.599) + 8.154909e-02 - * Math.pow(t - 13.599, 2) - 0.0484171 - * Math.pow(t - 13.599, 3); - else if (t <= 14.529) - y = 0.242895 + 0.0766879 * (t - 14.064) + 1.400728e-02 - * Math.pow(t - 14.064, 2) - 0.0357363 - * Math.pow(t - 14.064, 3); - else if (t <= 14.991) - y = 0.27799 + 0.0665334 * (t - 14.529) - 3.584491e-02 - * Math.pow(t - 14.529, 2) + 0.0445836 - * Math.pow(t - 14.529, 3); - else if (t <= 15.456) - y = 0.305474 + 0.061961 * (t - 14.991) + 2.594790e-02 - * Math.pow(t - 14.991, 2) - 0.0774076 - * Math.pow(t - 14.991, 3); - else if (t <= 15.921) - y = 0.332114 + 0.0358802 * (t - 15.456) - 8.203569e-02 - * Math.pow(t - 15.456, 2) + 0.00889788 - * Math.pow(t - 15.456, 3); - else if (t <= 16.386) - y = 0.331955 - 0.0346412 * (t - 15.921) - 6.962314e-02 - * Math.pow(t - 15.921, 2) + 0.12207 - * Math.pow(t - 15.921, 3); - else if (t <= 17.391) - y = 0.313066 - 0.020207 * (t - 16.386) + 1.006644e-01 - * Math.pow(t - 16.386, 2) - 0.0358557 - * Math.pow(t - 16.386, 3); - else if (t <= 17.856) - y = 0.358035 + 0.0734829 * (t - 17.391) - 7.440562e-03 - * Math.pow(t - 17.391, 2) - 0.0299292 - * Math.pow(t - 17.391, 3); - else if (t <= 18.321) - y = 0.387586 + 0.0471488 * (t - 17.856) - 4.919179e-02 - * Math.pow(t - 17.856, 2) - 0.0599498 - * Math.pow(t - 17.856, 3); - else if (t <= 18.786) - y = 0.392846 - 0.0374874 * (t - 18.321) - 1.328217e-01 - * Math.pow(t - 18.321, 2) + 0.120032 - * Math.pow(t - 18.321, 3); - else if (t <= 19.248) - y = 0.358764 - 0.0831502 * (t - 18.786) + 3.462234e-02 - * Math.pow(t - 18.786, 2) + 0.053599 - * Math.pow(t - 18.786, 3); - else if (t <= 19.713) - y = 0.333024 - 0.016838 * (t - 19.248) + 1.089105e-01 - * Math.pow(t - 19.248, 2) + 0.0201839 - * Math.pow(t - 19.248, 3); - else if (t <= 20.178) - y = 0.350773 + 0.0975416 * (t - 19.713) + 1.370670e-01 - * Math.pow(t - 19.713, 2) - 0.122089 - * Math.pow(t - 19.713, 3); - else if (t <= 20.643) - y = 0.413492 + 0.145818 * (t - 20.178) - 3.324745e-02 - * Math.pow(t - 20.178, 2) + 0.0238333 - * Math.pow(t - 20.178, 3); - - return (16.97282365372 - 6.68584901645) * y + 6.68584901645; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/odes/CKMMiSystem.java b/src/eva2/server/go/problems/inference/metabolic/odes/CKMMiSystem.java deleted file mode 100644 index cb5dd66e..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/odes/CKMMiSystem.java +++ /dev/null @@ -1,156 +0,0 @@ -/** - * - */ -package eva2.server.go.problems.inference.metabolic.odes; - -/** - * Created at 2007-02-03 - * - * This class describes the valine/leucine biosynthesis in Corynebacterium - * glutamicum acording to the convenience kinetics as proposed by - * Liebermeister and Klipp. Three reaction velocities follow the traditional - * Michaelis Menten scheme the others are given in the convenience kinetics. All - * reactions are considered to be ehter reversible or irreversible according to - * what is written in the KEGG database. - * - * @author Andreas Dräger - * - */ -public class CKMMiSystem extends AbstractValineSystem { - - /** - * Generated serial id. - */ - private static final long serialVersionUID = 8595111459805099502L; - - - /** - * - */ - public CKMMiSystem() { - this.p = null; - } - - /** - * @param params - * The parameters of this system. - */ - public CKMMiSystem(double[] params) { - this.p = params; - } - - /* - * (non-Javadoc) - * - * @see javaeva.server.oa.go.OptimizationProblems.InferenceRegulatoryNetworks.Des.DESystem#getValue(double, - * double[]) - */ - public double[] getValue(double t, double[] Y) { - // double[] kcat = new double[9]; // -> p[0..9] - // double[] ki = new double[3]; // -> p[9..11] - // double[] km = new double[16]; // -> p[12..27] - // double[] vm = new double[3]; // -> p[28..30] - // double[] kmm = new double[3]; // -> p[31..33] - // double[] kia = new double[3]; // -> p[34..36] - // double[] kib = new double[3]; // -> p[37..39] - // double acCoA = 0; // -> p[40] - - double pyr = getPyr_2(t), nadp = getNADP_2(t), nadph = 0.04 - nadp, glut = getGlut_2(t), ala = getAla_2(t); - /* - * Y[0] DHIV Y[1] IPM Y[2] AcLac Y[3] Val Y[4] Leu Y[5] KIV Y[6] KIC - */ - - return linearCombinationOfVelocities(new double[] { - /* Korrigiert: */ - // v_1: AHAS: convenience (ge�ndert) - (p[0] * p[9] * Math.pow(pyr / p[12], 2)) - / ((1 + pyr / p[12] + Math.pow(pyr / p[12], 2)) * (p[9] + Y[3])), - - // v_2: AHAIR: convenience (ge�ndert) - (p[1] * Y[2] / p[13] * nadph / p[14] * p[10] - p[2] * Y[0] - / p[15] * nadp / p[16] * p[10]) - / ((1 + Y[2] / p[13] + nadph / p[14] + (Y[2] * nadph) - / (p[13] * p[14]) + Y[0] / p[15] + nadp / p[16] + (Y[0] * nadp) - / (p[15] * p[16])) * (p[10] + Y[3])), - - // v_3: DHAD: reversible Michaelis Menten with two inhibitions - // (ge�ndert) - (p[28] * Y[0]) - / (p[31] + Y[0] + Y[3] * (p[31] * p[34] + p[37] * Y[0])), - - // v_4: BCAAT_ValB: convenience (ge�ndert) - (p[3] * Y[5] / p[17] * glut / p[18]) - / (1 + Y[5] / p[17] + glut / p[18] + (Y[5] * glut) - / (p[17] * p[18])), - - // v_5: BCAAT_ValC: convenience (ge�ndert) - (p[4] * Y[5] / p[19] * ala / p[20]) - / (1 + Y[5] / p[19] + ala / p[20] + (Y[5] * ala) - / (p[19] * p[20])), - - // v_6: Trans_Val: irreversible Michaelis Menten with two - // inhibitions - (p[29] * Y[3]) - / (p[32] + Y[3] + p[32] * p[35] * Y[4] + p[38] * Y[3] - * Y[4]), - - // v_7: IPMS: convenience (AcCoA/K_m = p40) (ge�ndert) - (p[5] * Y[5] / p[21] * p[40] * p[11]) - / ((1 + Y[5] / p[21] + p[40] + p[40] * Y[5] / p[21]) * (p[11] + Y[4])), - - // v_8: IPMDH: convenience (ge�ndert) - (p[6] * Y[1] / p[22] * nad / p[23]) - / (1 + Y[1] / p[22] + nad / p[23] + (Y[1] * nad) - / (p[22] * p[23])), - - // v_9: BCAAT_LeuB: convenience (ge�ndert) - (p[7] * Y[6] / p[24] * glut / p[25] - p[8] * Y[4] / p[26] * akg - / p[27]) - / (1 + Y[6] / p[24] + glut / p[25] + (Y[6] * glut) - / (p[24] * p[25]) + Y[4] / p[26] + akg / p[27] + (Y[4] * akg) - / (p[26] * p[27])), - - // v_10: Trans_Leu: irreversible Michaelis Menten with two - // inhibitions - (p[30] * Y[4]) - / (p[33] + Y[4] + p[33] * p[36] * Y[3] + p[39] * Y[3] - * Y[4]) - - /* - * zuvor: // AHAS: convenience (p[0] * pyr)/(p[9] * (1 + pyr/p[12] + - * Math.pow(pyr/p[12], 2)) + Y[3] * (1 + pyr/p[12] + Math.pow(pyr/p[12], - * 2))), // AHAIR: convenience (p[1] * Y[2] * nadph - p[2] * Y[0] * - * nadp)/((1 + Y[2]/p[13] + nadph/p[14] + (Y[2]*nadph)/(p[13]*p[14]) + - * Y[0]/p[15] + nadp/p[16] + (Y[0] * nadp)/(p[15] * p[16])) * p[10] * - * Y[3]), // DHAD: reversible Michaelis Menten with two inhibitions - * (p[28]* Y[0])/(p[31] + Y[0] + Y[3] * (p[28] * p[34] + p[37] * Y[0])), // - * BCAAT_ValB: convenience (p[3] * Y[5] * glut)/(1 + Y[5]/p[17] + - * glut/p[18] + (Y[5] * glut)/(p[17] * p[18])), // BCAAT_ValC: - * convenience (p[4] * Y[5] * ala)/(1 + Y[5]/p[19] + ala/p[20] + (Y[5] * - * ala)/(p[19] * p[20])), // Trans_Val: irreversible Michaelis Menten - * with two inhibitions (p[29] * Y[3])/(p[32] + Y[3] + p[32] * p[35] * - * Y[4] + p[38] * Y[3] * Y[4]), // IPMS: convenience (p[5] * Y[5])/((1 + - * Y[5]/p[21] + p[40] + (p[40] * Y[5])/p[21]) * (p[11] + Y[4])), // - * IPMDH: convenience (p[6] * Y[1] * nad)/(1 + Y[1]/p[22] + nad/p[23] + - * (Y[1] * nad)/(p[22] * p[23])), // BCAAT_LeuB: convenience (p[7] * - * Y[6] * glut - p[8] * Y[4] * akg)/(1 + Y[6]/p[24] + glut/p[25] + (Y[6] * - * glut)/(p[24] * p[25]) + Y[4]/p[26] + akg/p[27] + (Y[4] * akg)/(p[26] * - * p[27])), // Trans_Leu: irreversible Michaelis Menten with two - * inhibitions (p[30] * Y[4])/(p[33] + Y[4] + p[33] * p[36] * Y[3] + - * p[39] * Y[3] * Y[4]) - */ - }); - } - - - public void getValue(double t, double[] Y, double[] resultVector) { - double tmp[] = getValue(t, Y); - System.arraycopy(tmp, 0, resultVector, 0, tmp.length); - } - - @Override - public int getNumberOfParameters() { - return 41; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/odes/CKMMrSystem.java b/src/eva2/server/go/problems/inference/metabolic/odes/CKMMrSystem.java deleted file mode 100644 index ed52c8a2..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/odes/CKMMrSystem.java +++ /dev/null @@ -1,117 +0,0 @@ -package eva2.server.go.problems.inference.metabolic.odes; - -/** - * This class describes the valine/leucine biosynthesis in Corynebacterium - * glutamicum acording to the convenience kinetics as proposed by - * Liebermeister and Klipp. Three reaction velocities follow the traditional - * Michaelis Menten scheme the others are given in the convenience kinetics. - * However, in this class all reactions are assumed to be reversible. - * - * @since 2.0 - * @version - * @author Andreas Dräger (draeger) - * Copyright (c) ZBiT, University of Tübingen, Germany Compiler: - * JDK 1.6.0 - * @date 2007-02-05 - */ -public class CKMMrSystem extends AbstractValineSystem { - - /** - * Generated serial id. - */ - private static final long serialVersionUID = 726678613269764327L; - transient protected double velocities[] = null; - - /** - * @param x - */ - public CKMMrSystem(double[] x) { - this.p = x; - } - - public CKMMrSystem() { - super(); - } - - /* - * (non-Javadoc) - * - * @see eva2.server.go.OptimizationProblems.InferenceRegulatoryNetworks.Des.DESystem#getValue(double, - * double[]) - */ - public double[] getValue(double t, double[] Y) { - - double[] res = new double[7]; - getValue(t, Y, res); - return res; - - } - - public void getValue(double t, double[] Y, double[] res) { - double pyr = getPyr_2(t), nadp = getNADP_2(t), nadph = 0.04 - nadp, glut = getGlut_2(t), akg = getAKG_2(t), ala = getAla_2(t), nad = getNAD_2(t), nadh = 0.8 - nad; - - if (velocities == null) - velocities = new double[10]; - - // v_1 - velocities[0] = ((p[0] * p[44] * Math.pow(pyr, 2)) / Math.pow(p[14], 2) - (p[7] - * p[44] * Y[2]) - / p[15]) - / ((1 + pyr / p[14] + Math.pow(pyr / p[14], 2) + Y[2] / p[15]) * (p[44] + Y[3])); - // v_2 - velocities[1] = ((p[1] * p[45] * Y[2] * nadph) / (p[16] * p[17]) - (p[8] - * p[45] * Y[0] * nadp) - / (p[18] * p[19])) - / ((1 + Y[2] / p[16] + nadph / p[17] + (Y[2] * nadph) - / (p[16] * p[17]) + Y[0] / p[18] + nadp / p[19] + (Y[0] * nadp) - / (p[18] * p[19])) * (p[45] + Y[3])); - // v_3 - velocities[2] = ((p[47] * Y[0]) / p[20] - (p[48] * Y[5]) / p[21]) - / (1 + p[51] * Y[3] + (Y[0] / p[20] + Y[5] / p[21]) - * (1 + p[54] * Y[3])); - // v_4 - velocities[3] = ((p[2] * Y[5] * glut) / (p[22] * p[23]) - (p[9] * Y[3] * akg) - / (p[24] * p[25])) - / (1 + Y[5] / p[22] + glut / p[23] + (Y[5] * glut) - / (p[22] * p[23]) + Y[3] / p[24] + akg / p[25] + (Y[3] * akg) - / (p[24] * p[25])); - // v_5 - velocities[4] = ((p[3] * Y[5] * ala) / (p[26] * p[27]) - (p[10] * Y[3] * pyr) - / (p[28] * p[29])) - / (1 + Y[5] / p[26] + ala / p[27] + (Y[5] * ala) - / (p[26] * p[27]) + Y[3] / p[28] + pyr / p[29] + (Y[3] * pyr) - / (p[28] * p[29])); - // v_6 - velocities[5] = (p[49] * Y[3]) - / (p[30] + p[30] * p[52] * Y[4] + Y[3] + p[55] * Y[3] * Y[4]); - // v_7 - velocities[6] = ((p[4] * p[46] * Y[5] * p[57]) / (p[31] * p[32]) - (p[11] - * p[46] * Y[1] * p[58]) - / (p[33] * p[34])) - / ((1 + Y[5] / p[31] + p[57] / p[32] + (Y[5] * p[57]) - / (p[31] * p[32]) + Y[1] / p[33] + p[58] / p[34] + (Y[1] * p[58]) - / (p[33] * p[34])) * (p[46] + Y[4])); - // v_8 - velocities[7] = ((p[5] * Y[1] * nad) / (p[35] * p[36]) - (p[12] * Y[6] * nadh) - / (p[37] * p[38])) - / (1 + Y[1] / p[35] + nad / p[36] + (Y[1] * nad) - / (p[35] * p[36]) + Y[6] / p[37] + nadh / p[38] + (Y[6] * nadh) - / (p[37] * p[38])); - // v_9 - velocities[8] = ((p[6] * Y[6] * glut) / (p[39] * p[40]) - (p[13] * Y[4] * akg) - / (p[41] * p[42])) - / (1 + Y[6] / p[39] + glut / p[40] + (Y[6] * glut) - / (p[39] * p[40]) + Y[4] / p[41] + akg / p[42] + (Y[4] * akg) - / (p[41] * p[42])); - // v_10 - velocities[9] = (p[50] * Y[4]) - / (p[43] + p[43] * p[53] * Y[3] + Y[4] + p[56] * Y[3] * Y[4]); - - linearCombinationOfVelocities(velocities, res); - } - - @Override - public int getNumberOfParameters() { - return 59; - } -} diff --git a/src/eva2/server/go/problems/inference/metabolic/odes/GMAKiSystem.java b/src/eva2/server/go/problems/inference/metabolic/odes/GMAKiSystem.java deleted file mode 100644 index 308a8e41..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/odes/GMAKiSystem.java +++ /dev/null @@ -1,69 +0,0 @@ -/** - * - */ -package eva2.server.go.problems.inference.metabolic.odes; - -// Created ad 2007-01-13 - -/** - * In this class the valine/leucine biosynthesis in Corynebacterium glutamicum - * is modeled to be in many reactions irreversible according to what is written - * in the KEGG database. Inhibition is modeled as negative exponential function. - * - * @author Andreas Dräger - * - */ -public class GMAKiSystem extends AbstractValineSystem { - - /** - * Generated serial id. - */ - private static final long serialVersionUID = -5893476466596099997L; - - /** - * - * @param params - */ - public GMAKiSystem(double params[]) { - this.p = params; - } - - public GMAKiSystem() { - this.p = null; - } - - /* - * (non-Javadoc) - * - * @see javaeva.server.oa.go.OptimizationProblems.InferenceRegulatoryNetworks.Des.DESystem#getValue(double, - * double[]) - */ - public double[] getValue(double t, double[] Y) { - return linearCombinationOfVelocities(new double[] { - p[0] * Math.pow(getPyr_2(t), 2) - * Math.exp((-p[12]) * Y[3]), - (p[1] * Y[2] * (0.04 - getNADP_2(t)) - p[10] * Y[0] - * getNADP_2(t)) - * Math.exp((-p[13]) * Y[3]), - p[2] * Y[0] * Math.exp((-p[14]) * Y[3]), - p[3] * getGlut_2(t) * Y[5], - p[4] * getAla_2(t) * Y[5], - p[5] * Y[3] * Math.exp((-p[15]) * Y[4]), - p[6] * Y[5] * Math.exp((-p[16]) * Y[4]), - p[7] * getNAD_2(t) * Y[1], - p[8] * getGlut_2(t) * Y[6] - p[11] * getAKG_2(t) - * Y[4], - p[9] * Y[4] * Math.exp((-p[17]) * Y[3]) }); - } - - public void getValue(double t, double[] Y, double[] resultVector) { - double tmp[] = getValue(t, Y); - System.arraycopy(tmp, 0, resultVector, 0, tmp.length); - } - - @Override - public int getNumberOfParameters() { - return 18; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/odes/GMAKrSystem.java b/src/eva2/server/go/problems/inference/metabolic/odes/GMAKrSystem.java deleted file mode 100644 index 0344b70e..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/odes/GMAKrSystem.java +++ /dev/null @@ -1,116 +0,0 @@ -package eva2.server.go.problems.inference.metabolic.odes; - -/** - * This class describes the valine/leucine biosynthesis in Corynebacterium - * glutamicum. All 10 reactions are assumed to be reversible and modeled - * following the generalized mass action kinetic, where inhibition is modeled - * using the function 1/(1 + ki*[Inhibitor]). - * - * @date 2007-02-04 - * @author Andreas Dräger - */ -public class GMAKrSystem extends AbstractValineSystem { - - /** - * Generated serial id. - */ - private static final long serialVersionUID = -5668558229555497614L; - transient double[] veloc = null; - - public GMAKrSystem() { - super(); - } - - /** - * @param params - */ - public GMAKrSystem(double params[]) { - super(); - this.p = params; - } - - - /* - * (non-Javadoc) - * - * @see eva2.server.go.OptimizationProblems.InferenceRegulatoryNetworks.Des.DESystem#getValue(double, - * double[]) - */ - public double[] getValue(double t, double[] Y) { - // a <- params[0..9] - // b <- params[10..17] - // g <- params[18..23] - double[] res = new double[7]; - getValue(t, Y, res); - return res; - // return linearCombinationOfVelocities(new double[] { - // (params[0] * Math.pow(getPyr_2(t), 2) - params[10] * Y[2])/ (1 + - // params[18] * Y[3]), // Math.exp((-params[18]) * Y[3]), - // (params[1] * Y[2] * (.04 - getNADP_2(t)) - params[11] * Y[0] * - // getNADP_2(t)) / (1 + params[19] * Y[3]), // * Math.exp((-params[19]) - // * - // Y[3]), - // (params[2] * Y[0] - params[12] * Y[5]) / (1 + params[20] * Y[3]), // - // * - // // Math.exp((-params[20]) - // // * - // // Y[3]), - // params[3] * getGlut_2(t) * Y[5] - params[13] * getAKG_2(t) * Y[3], - // params[4] * getAla_2(t) * Y[5] - params[14] * getPyr_2(t) * Y[3], - // (params[5] * Y[3]) / (1 + params[21] * Y[4]), // * - // // Math.exp((-params[21]) - // // * Y[4]), - // (params[6] * Y[5] - params[15] * Y[1]) / (1 + params[22] * Y[4]), // - // * - // // Math.exp((-params[22]) - // // * - // // Y[4]), - // params[7] * getNAD_2(t) * Y[1] - params[16] * Y[6] * (.8 - - // getNAD_2(t)), - // params[8] * getGlut_2(t) * Y[6] - params[17] * getAKG_2(t) * Y[4], - // (params[9] * Y[4]) / (1 + params[23] * Y[3]) // * - // // Math.exp((-params[23]) - // // * Y[3]) - // }); - } - - public void getValue(double t, double[] Y, double[] res) { - if (veloc == null) - veloc = new double[10]; - - veloc[0] = (p[0] * Math.pow(getPyr_2(t), 2) - p[10] * Y[2]) - / (1 + p[18] * Y[3]); // Math.exp((-params[18]) * Y[3]), - veloc[1] = (p[1] * Y[2] * (.04 - getNADP_2(t)) - p[11] * Y[0] - * getNADP_2(t)) - / (1 + p[19] * Y[3]); // * Math.exp((-params[19]) * Y[3]), - veloc[2] = (p[2] * Y[0] - p[12] * Y[5]) - / (1 + p[20] * Y[3]); // * - // Math.exp((-params[20]) - // * - // Y[3]), - veloc[3] = p[3] * getGlut_2(t) * Y[5] - p[13] * getAKG_2(t) - * Y[3]; - veloc[4] = p[4] * getAla_2(t) * Y[5] - p[14] * getPyr_2(t) - * Y[3]; - veloc[5] = (p[5] * Y[3]) / (1 + p[21] * Y[4]); // * - // Math.exp((-params[21]) - // * Y[4]), - veloc[6] = (p[6] * Y[5] - p[15] * Y[1]) - / (1 + p[22] * Y[4]); // * - // Math.exp((-params[22]) - // * - // Y[4]), - veloc[7] = p[7] * getNAD_2(t) * Y[1] - p[16] * Y[6] - * (.8 - getNAD_2(t)); - veloc[8] = p[8] * getGlut_2(t) * Y[6] - p[17] * getAKG_2(t) - * Y[4]; - veloc[9] = (p[9] * Y[4]) / (1 + p[23] * Y[3]); // * - linearCombinationOfVelocities(veloc, res); - } - - @Override - public int getNumberOfParameters() { - return 24; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/odes/GMMiSystem.java b/src/eva2/server/go/problems/inference/metabolic/odes/GMMiSystem.java deleted file mode 100644 index 77c8c87d..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/odes/GMMiSystem.java +++ /dev/null @@ -1,120 +0,0 @@ -package eva2.server.go.problems.inference.metabolic.odes; - -// Created at 2007-01-18 - -/** - * This class implements a system of ordinary differential equations describing - * the valine and leucin biosynthesis in Corynebacterium gluthamicum. - * - * @author Andreas Dräger - */ -public class GMMiSystem extends AbstractValineSystem { - - /** - * Generated version id. - */ - private static final long serialVersionUID = 6119930633376953563L; - - - /** - *

- * A vector of parameters it needed to initialize this class. The parameters - * are given as: - *

- *
    - *
  • params[0-6] = k, Rate constant for the forward reaction
    • - *
  • params[7-8] = l, Rate constant for the backward reaction
    • - *
  • params[9-11] = ki, Rate constant for inhibition of uncertain - * mechanism
    • - *
  • params[12-14] = vm, Maximal reaction velocity
    • - *
  • params[15-17] = kia, Rate constant for inhibition of the enzyme
    • - *
  • params[18-20] = kib, Rate constant for inhibition of the enzyme - * substrate complex
    • - *
  • params[21-23] = km, the Michaelis-Menten constant
    • - *
- * - * @param params - */ - public GMMiSystem(double[] params) { - if (params != null) - if (params.length != 24) - throw new Error( - "This ODE system needs exactly 24 parameters. Given are " - + params.length); - this.p = params; - } - - /** - * - * - */ - public GMMiSystem() { - this.p = null; - } - - - /* - * (non-Javadoc) - * - * @see javaeva.server.oa.go.OptimizationProblems.InferenceRegulatoryNetworks.Des.DESystem#getValue(double, - * double[]) - */ - public double[] getValue(double t, double[] Y) { - double[] v = new double[] { - // v_1 - (p[0] * Math.pow(getPyr_2(t), 2)) / (1 + p[9] * Y[3]), - // v_2 - (p[1] * Y[2] * (0.04 - getNADP_2(t)) - p[7] * Y[0] - * getNADP_2(t)) - / (1 + p[10] * Y[3]), - // v_3 - // ((p[12] * Y[0])/p[21])/(1 + p[15] * Y[3] + (Y[0] + p[18] * - // Y[3] * - // Y[0])/p[21]), - (p[12] * Y[0]) - / (p[21] + Y[0] + p[21] * p[15] * Y[3] + p[18] * Y[0] - * Y[3]), - // v_4 - p[2] * Y[5] * getGlut_2(t), - // v_5 - p[3] * Y[5] * getAla_2(t), - // v_6 - // (p[13]/p[22] * Y[3])/(1 + p[16] * Y[4] + (Y[3] + p[19] * Y[4] - // * - // Y[3])/p[22]), - (p[13] * Y[3]) - / (p[22] + Y[3] + p[22] * p[16] * Y[4] + p[19] * Y[3] - * Y[4]), - // v_7 - (p[4] * Y[5]) / (1 + p[11] * Y[4]), - // v_8 - p[5] * Y[1] * getNAD_2(t), - // v_9 - p[6] * Y[6] * getGlut_2(t) - p[8] * Y[4] * getAKG_2(t), - // v_10 - // ((p[14] * Y[4])/p[23])/(1 + p[17] * Y[3] + (Y[4] + p[20] * - // Y[3] * - // Y[4])/p[23]) - (p[14] * Y[4]) - / (p[23] + Y[4] + p[17] * p[23] * Y[3] + p[20] * Y[3] - * Y[4]) }; - - /* - * if ((Double.isNaN(v[0]) || Double.isInfinite(v[0])) && (t < -1.784)) { - * System.out.println(t+". Nenner: "+(1 + p[9] * Y[3])+"\tY[3] = - * "+Y[3]+"\tparam9 = "+p[9]); }// - */ - return linearCombinationOfVelocities(v); - } - - public void getValue(double t, double[] Y, double[] resultVector) { - double tmp[] = getValue(t, Y); - System.arraycopy(tmp, 0, resultVector, 0, tmp.length); - } - - @Override - public int getNumberOfParameters() { - return 24; - } - -} diff --git a/src/eva2/server/go/problems/inference/metabolic/odes/GMMrSystem.java b/src/eva2/server/go/problems/inference/metabolic/odes/GMMrSystem.java deleted file mode 100644 index bf01712e..00000000 --- a/src/eva2/server/go/problems/inference/metabolic/odes/GMMrSystem.java +++ /dev/null @@ -1,87 +0,0 @@ -package eva2.server.go.problems.inference.metabolic.odes; - -/** - * This class describes the valine/leucine biosynthesis in Corynebacterium - * gluthamicum where three reactions are modeled using traditional reversible - * Michaelis Menten kinetics and the remaining reactions are modeled using - * reversible generalized mass action kinetics, where inhibition is modeled - * using 1/(1 + ki*[Inhibitor]). Created at 2007-02-04. - * - * @author Andreas Dräger - */ -public class GMMrSystem extends AbstractValineSystem { - - /** - * Generated serial id. - */ - private static final long serialVersionUID = 7461506193192163451L; - - /** - * - */ - public GMMrSystem() { - } - - /** - * @param params - */ - public GMMrSystem(double[] params) { - this.p = params; - } - - /* - * (non-Javadoc) - * - * @see eva2.server.go.OptimizationProblems.InferenceRegulatoryNetworks.Des.DESystem#getValue(double, - * double[]) - */ - public double[] getValue(double t, double[] Y) { - /* - * double[] a = null, // <- params[0..6] 7 b = null, // <- params[7..13] - * 7 vm = null, // <- params[14..17] 4 km = null, // <- params[18..21] 4 - * kia = null, // <- params[22..24] 3 kib = null, // <- params[25..27] 3 - * ki = null; // <- params[28..30] 3 // - */ - - return linearCombinationOfVelocities(new double[] { - // v_1 - (p[0] * Math.pow(getPyr_2(t), 2) - p[7] * Y[2]) - / (1 + p[28] * Y[3]), - // v_2 - (p[1] * Y[2] * (.04 - getNADP_2(t)) - p[8] * Y[0] - * getNADP_2(t)) - / (1 + p[29] * Y[3]), - // v_3 - ((p[14] * Y[0]) / p[18] - (p[15] * Y[5]) / p[19]) - / (1 + p[22] * Y[3] + (Y[0] / p[18] + Y[5] / p[19]) - * (1 + p[25] * Y[3])), - // v_4 - p[2] * Y[5] * getGlut_2(t) - p[9] * Y[3] * getAKG_2(t), - // v_5 - p[3] * Y[5] * getAla_2(t) - p[10] * Y[3] * getPyr_2(t), - // v_6 - (p[16] * Y[3]) - / (p[20] + p[20] * p[23] * Y[4] + Y[3] + p[26] * Y[4] - * Y[3]), - // v_7 - (p[4] * Y[5] - p[11] * Y[1]) / (1 + p[30] * Y[4]), - // v_8 - p[5] * Y[1] * getNAD_2(t) - p[12] * Y[6] * (.8 - getNAD_2(t)), - // v_9 - p[6] * Y[6] * getGlut_2(t) - p[13] * Y[4] * getAKG_2(t), - // v_10 - (p[17] * Y[4]) - / (p[21] + p[21] * p[24] * Y[3] + Y[4] + p[27] * Y[3] - * Y[4]) }); - } - - public void getValue(double t, double[] Y, double[] resultVector) { - resultVector = getValue(t, Y); - } - - @Override - public int getNumberOfParameters() { - return 31; - } - -} \ No newline at end of file