Uses of Class
org.apache.commons.math3.exception.NumberIsTooSmallException
Packages that use NumberIsTooSmallException
Package
Description
This package holds the main interfaces and basic building block classes
dealing with differentiation.
Numerical integration (quadrature) algorithms for univariate real functions.
Univariate real functions interpolation algorithms.
Univariate real polynomials implementations, seen as differentiable
univariate real functions.
Root finding algorithms, for univariate real functions.
Decimal floating point library for Java
Implementations of common discrete and continuous distributions.
Fitting of parameters against distributions.
Specialized exceptions for algorithms errors.
This package provides Genetic Algorithms components and implementations.
Linear algebra support.
Clustering algorithms.
This package provides classes to solve Ordinary Differential Equations problems.
This package provides classes to solve non-stiff Ordinary Differential Equations problems.
Implementations of special functions such as Beta and Gamma.
Data storage, manipulation and summary routines.
Correlations/Covariance computations.
Classes providing hypothesis testing.
Convenience routines and common data structures used throughout the commons-math library.
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Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.differentiation
Constructors in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooSmallExceptionModifierConstructorDescriptionFiniteDifferencesDifferentiator(int nbPoints, double stepSize) Build a differentiator with number of points and step size when independent variable is unbounded.FiniteDifferencesDifferentiator(int nbPoints, double stepSize, double tLower, double tUpper) Build a differentiator with number of points and step size when independent variable is bounded. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.integration
Constructors in org.apache.commons.math3.analysis.integration that throw NumberIsTooSmallExceptionModifierConstructorDescriptionprotectedBaseAbstractUnivariateIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount) Construct an integrator with given accuracies and iteration counts.protectedBaseAbstractUnivariateIntegrator(int minimalIterationCount, int maximalIterationCount) Construct an integrator with given iteration counts.IterativeLegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount) Builds an integrator with given accuracies and iterations counts.IterativeLegendreGaussIntegrator(int n, int minimalIterationCount, int maximalIterationCount) Builds an integrator with given iteration counts.LegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount) Deprecated.Build a Legendre-Gauss integrator with given accuracies and iterations counts.MidPointIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount) Build a midpoint integrator with given accuracies and iterations counts.MidPointIntegrator(int minimalIterationCount, int maximalIterationCount) Build a midpoint integrator with given iteration counts.RombergIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount) Build a Romberg integrator with given accuracies and iterations counts.RombergIntegrator(int minimalIterationCount, int maximalIterationCount) Build a Romberg integrator with given iteration counts.SimpsonIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount) Build a Simpson integrator with given accuracies and iterations counts.SimpsonIntegrator(int minimalIterationCount, int maximalIterationCount) Build a Simpson integrator with given iteration counts.TrapezoidIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount) Build a trapezoid integrator with given accuracies and iterations counts.TrapezoidIntegrator(int minimalIterationCount, int maximalIterationCount) Build a trapezoid integrator with given iteration counts. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.interpolation
Methods in org.apache.commons.math3.analysis.interpolation that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionprotected static double[]DividedDifferenceInterpolator.computeDividedDifference(double[] x, double[] y) Return a copy of the divided difference array.AkimaSplineInterpolator.interpolate(double[] xvals, double[] yvals) Computes an interpolating function for the data set.BicubicInterpolator.interpolate(double[] xval, double[] yval, double[][] fval) Compute an interpolating function for the dataset.BicubicSplineInterpolator.interpolate(double[] xval, double[] yval, double[][] fval) Deprecated.Compute an interpolating function for the dataset.BivariateGridInterpolator.interpolate(double[] xval, double[] yval, double[][] fval) Compute an interpolating function for the dataset.DividedDifferenceInterpolator.interpolate(double[] x, double[] y) Compute an interpolating function for the dataset.LinearInterpolator.interpolate(double[] x, double[] y) Computes a linear interpolating function for the data set.final PolynomialSplineFunctionLoessInterpolator.interpolate(double[] xval, double[] yval) Compute an interpolating function by performing a loess fit on the data at the original abscissae and then building a cubic spline with aSplineInterpolatoron the resulting fit.NevilleInterpolator.interpolate(double[] x, double[] y) Computes an interpolating function for the data set.SplineInterpolator.interpolate(double[] x, double[] y) Computes an interpolating function for the data set.TricubicInterpolator.interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval) Compute an interpolating function for the dataset.TricubicSplineInterpolator.interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval) Deprecated.Compute an interpolating function for the dataset.TrivariateGridInterpolator.interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval) Compute an interpolating function for the dataset.UnivariatePeriodicInterpolator.interpolate(double[] xval, double[] yval) Compute an interpolating function for the dataset.final double[]LoessInterpolator.smooth(double[] xval, double[] yval) Compute a loess fit on the data at the original abscissae.final double[]LoessInterpolator.smooth(double[] xval, double[] yval, double[] weights) Compute a weighted loess fit on the data at the original abscissae. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.polynomials
Methods in org.apache.commons.math3.analysis.polynomials that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionstatic doublePolynomialFunctionLagrangeForm.evaluate(double[] x, double[] y, double z) Evaluate the Lagrange polynomial using Neville's Algorithm.static booleanPolynomialFunctionLagrangeForm.verifyInterpolationArray(double[] x, double[] y, boolean abort) Check that the interpolation arrays are valid.Constructors in org.apache.commons.math3.analysis.polynomials that throw NumberIsTooSmallExceptionModifierConstructorDescriptionPolynomialFunctionLagrangeForm(double[] x, double[] y) Construct a Lagrange polynomial with the given abscissas and function values.PolynomialSplineFunction(double[] knots, PolynomialFunction[] polynomials) Construct a polynomial spline function with the given segment delimiters and interpolating polynomials. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.solvers
Constructors in org.apache.commons.math3.analysis.solvers that throw NumberIsTooSmallExceptionModifierConstructorDescriptionBracketingNthOrderBrentSolver(double relativeAccuracy, double absoluteAccuracy, double functionValueAccuracy, int maximalOrder) Construct a solver.BracketingNthOrderBrentSolver(double relativeAccuracy, double absoluteAccuracy, int maximalOrder) Construct a solver.BracketingNthOrderBrentSolver(double absoluteAccuracy, int maximalOrder) Construct a solver.FieldBracketingNthOrderBrentSolver(T relativeAccuracy, T absoluteAccuracy, T functionValueAccuracy, int maximalOrder) Construct a solver. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.dfp
Constructors in org.apache.commons.math3.dfp that throw NumberIsTooSmallExceptionModifierConstructorDescriptionBracketingNthOrderBrentSolverDFP(Dfp relativeAccuracy, Dfp absoluteAccuracy, Dfp functionValueAccuracy, int maximalOrder) Deprecated.Construct a solver. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.distribution
Constructors in org.apache.commons.math3.distribution that throw NumberIsTooSmallExceptionModifierConstructorDescriptionTriangularDistribution(double a, double c, double b) Creates a triangular real distribution using the given lower limit, upper limit, and mode.TriangularDistribution(RandomGenerator rng, double a, double c, double b) Creates a triangular distribution. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.distribution.fitting
Constructors in org.apache.commons.math3.distribution.fitting that throw NumberIsTooSmallExceptionModifierConstructorDescriptionMultivariateNormalMixtureExpectationMaximization(double[][] data) Creates an object to fit a multivariate normal mixture model to data. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.exception
Subclasses of NumberIsTooSmallException in org.apache.commons.math3.exceptionModifier and TypeClassDescriptionclassException to be thrown when the argument is negative.classException to be thrown when the argument is not greater than 0. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.genetics
Methods in org.apache.commons.math3.genetics that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionvoidListPopulation.setPopulationLimit(int populationLimit) Sets the maximal population size.Constructors in org.apache.commons.math3.genetics that throw NumberIsTooSmallExceptionModifierConstructorDescriptionFixedElapsedTime(long maxTime) Create a newFixedElapsedTimeinstance.FixedElapsedTime(long maxTime, TimeUnit unit) Create a newFixedElapsedTimeinstance.FixedGenerationCount(int maxGenerations) Create a new FixedGenerationCount instance. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.linear
Subclasses of NumberIsTooSmallException in org.apache.commons.math3.linearModifier and TypeClassDescriptionclassException to be thrown when a positive definite matrix is expected.Methods in org.apache.commons.math3.linear that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionprotected voidRealVector.checkIndices(int start, int end) Checks that the indices of a subvector are valid.protected voidAbstractFieldMatrix.checkSubMatrixIndex(int startRow, int endRow, int startColumn, int endColumn) Check if submatrix ranges indices are valid.static voidMatrixUtils.checkSubMatrixIndex(AnyMatrix m, int startRow, int endRow, int startColumn, int endColumn) Check if submatrix ranges indices are valid.voidAbstractFieldMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination) Copy a submatrix.voidAbstractRealMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination) Copy a submatrix.voidFieldMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination) Copy a submatrix.voidRealMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination) Copy a submatrix.AbstractFieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn) Get a submatrix.AbstractRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.BlockFieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn) Get a submatrix.BlockRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.FieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn) Get a submatrix.RealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.AbstractFieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in column order.AbstractFieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in column order.doubleAbstractRealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in column order.doubleAbstractRealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in column order.Array2DRowFieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in column order.Array2DRowFieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in column order.doubleArray2DRowRealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in column order.doubleArray2DRowRealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in column order.FieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in column order.FieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in column order.doubleRealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in column order.doubleRealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in column order.ArrayFieldVector.walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor, int start, int end) Visits (and possibly alters) some entries of this vector in default order (increasing index).ArrayFieldVector.walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end) Visits (but does not alter) some entries of this vector in default order (increasing index).doubleArrayRealVector.walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end) Visits (and possibly alters) some entries of this vector in default order (increasing index).doubleArrayRealVector.walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end) Visits (but does not alter) some entries of this vector in default order (increasing index).doubleRealVector.walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end) Visits (and possibly alters) some entries of this vector in default order (increasing index).doubleRealVector.walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end) Visits (but does not alter) some entries of this vector in default order (increasing index).SparseFieldVector.walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor, int start, int end) Visits (and possibly alters) some entries of this vector in default order (increasing index).SparseFieldVector.walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end) Visits (but does not alter) some entries of this vector in default order (increasing index).AbstractFieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries using the fastest possible order.AbstractFieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries using the fastest possible order.doubleAbstractRealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries using the fastest possible order.doubleAbstractRealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries using the fastest possible order.ArrayFieldVector.walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor, int start, int end) Visits (and possibly change) some entries of this vector in optimized order.ArrayFieldVector.walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end) Visits (but does not alter) some entries of this vector in optimized order.doubleArrayRealVector.walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end) Visits (and possibly change) some entries of this vector in optimized order.doubleArrayRealVector.walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end) Visits (but does not alter) some entries of this vector in optimized order.BlockFieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries using the fastest possible order.BlockFieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries using the fastest possible order.doubleBlockRealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries using the fastest possible order.doubleBlockRealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries using the fastest possible order.FieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries using the fastest possible order.FieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries using the fastest possible order.doubleRealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries using the fastest possible order.doubleRealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries using the fastest possible order.doubleRealVector.walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end) Visits (and possibly change) some entries of this vector in optimized order.doubleRealVector.walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end) Visits (but does not alter) some entries of this vector in optimized order.SparseFieldVector.walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor, int start, int end) Visits (and possibly change) some entries of this vector in optimized order.SparseFieldVector.walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end) Visits (but does not alter) some entries of this vector in optimized order.AbstractFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.AbstractFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in row order.doubleAbstractRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.doubleAbstractRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in row order.Array2DRowFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.Array2DRowFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in row order.doubleArray2DRowRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.doubleArray2DRowRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in row order.BlockFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.BlockFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in row order.doubleBlockRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.doubleBlockRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in row order.FieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.FieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in row order.doubleRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.doubleRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (but don't change) some matrix entries in row order. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.ml.clustering
Constructors in org.apache.commons.math3.ml.clustering that throw NumberIsTooSmallExceptionModifierConstructorDescriptionFuzzyKMeansClusterer(int k, double fuzziness) Creates a new instance of a FuzzyKMeansClusterer.FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure) Creates a new instance of a FuzzyKMeansClusterer.FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure, double epsilon, RandomGenerator random) Creates a new instance of a FuzzyKMeansClusterer. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.ode
Methods in org.apache.commons.math3.ode that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionabstract voidAbstractIntegrator.integrate(ExpandableStatefulODE equations, double t) Integrate a set of differential equations up to the given time.doubleAbstractIntegrator.integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y) Integrate the differential equations up to the given time.FirstOrderFieldIntegrator.integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.doubleFirstOrderIntegrator.integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y) Integrate the differential equations up to the given time.protected voidAbstractFieldIntegrator.sanityChecks(FieldODEState<T> eqn, T t) Check the integration span.protected voidAbstractIntegrator.sanityChecks(ExpandableStatefulODE equations, double t) Check the integration span.protected voidMultistepFieldIntegrator.start(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T t) Start the integration.protected voidMultistepIntegrator.start(double t0, double[] y0, double t) Start the integration.Constructors in org.apache.commons.math3.ode that throw NumberIsTooSmallExceptionModifierConstructorDescriptionprotectedMultistepFieldIntegrator(Field<T> field, String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance) Build a multistep integrator with the given stepsize bounds.protectedMultistepIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance) Build a multistep integrator with the given stepsize bounds. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.ode.nonstiff
Methods in org.apache.commons.math3.ode.nonstiff that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionprotected TAdaptiveStepsizeFieldIntegrator.filterStep(T h, boolean forward, boolean acceptSmall) Filter the integration step.protected doubleAdaptiveStepsizeIntegrator.filterStep(double h, boolean forward, boolean acceptSmall) Filter the integration step.AdamsBashforthFieldIntegrator.integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.voidAdamsBashforthIntegrator.integrate(ExpandableStatefulODE equations, double t) Integrate a set of differential equations up to the given time.abstract FieldODEStateAndDerivative<T> AdamsFieldIntegrator.integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.abstract voidAdamsIntegrator.integrate(ExpandableStatefulODE equations, double t) Integrate a set of differential equations up to the given time.AdamsMoultonFieldIntegrator.integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.voidAdamsMoultonIntegrator.integrate(ExpandableStatefulODE equations, double t) Integrate a set of differential equations up to the given time.abstract voidAdaptiveStepsizeIntegrator.integrate(ExpandableStatefulODE equations, double t) Integrate a set of differential equations up to the given time.EmbeddedRungeKuttaFieldIntegrator.integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.voidEmbeddedRungeKuttaIntegrator.integrate(ExpandableStatefulODE equations, double t) Integrate a set of differential equations up to the given time.voidGraggBulirschStoerIntegrator.integrate(ExpandableStatefulODE equations, double t) Integrate a set of differential equations up to the given time.RungeKuttaFieldIntegrator.integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.voidRungeKuttaIntegrator.integrate(ExpandableStatefulODE equations, double t) Integrate a set of differential equations up to the given time.protected voidAdaptiveStepsizeFieldIntegrator.sanityChecks(FieldODEState<T> eqn, T t) Check the integration span.protected voidAdaptiveStepsizeIntegrator.sanityChecks(ExpandableStatefulODE equations, double t) Check the integration span.Constructors in org.apache.commons.math3.ode.nonstiff that throw NumberIsTooSmallExceptionModifierConstructorDescriptionAdamsBashforthFieldIntegrator(Field<T> field, int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance) Build an Adams-Bashforth integrator with the given order and step control parameters.AdamsBashforthIntegrator(int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance) Build an Adams-Bashforth integrator with the given order and step control parameters.AdamsFieldIntegrator(Field<T> field, String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance) Build an Adams integrator with the given order and step control parameters.AdamsIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance) Build an Adams integrator with the given order and step control parameters.AdamsMoultonFieldIntegrator(Field<T> field, int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance) Build an Adams-Moulton integrator with the given order and error control parameters.AdamsMoultonIntegrator(int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance) Build an Adams-Moulton integrator with the given order and error control parameters. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.special
Methods in org.apache.commons.math3.special that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionstatic doubleGamma.logGamma1p(double x) Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.stat
Methods in org.apache.commons.math3.stat that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionstatic doubleStatUtils.varianceDifference(double[] sample1, double[] sample2, double meanDifference) Returns the variance of the (signed) differences between corresponding elements of the input arrays -- i.e., var(sample1[i] - sample2[i]). -
Uses of NumberIsTooSmallException in org.apache.commons.math3.stat.correlation
Methods in org.apache.commons.math3.stat.correlation that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptiondoubleStorelessCovariance.getCovariance(int xIndex, int yIndex) Get the covariance for an individual element of the covariance matrix.StorelessCovariance.getCovarianceMatrix()Returns the covariance matrixdouble[][]StorelessCovariance.getData()Return the covariance matrix as two-dimensional array. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.stat.inference
Methods in org.apache.commons.math3.stat.inference that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionstatic doubleTestUtils.homoscedasticT(double[] sample1, double[] sample2) static doubleTestUtils.homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) doubleTTest.homoscedasticT(double[] sample1, double[] sample2) Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.doubleTTest.homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Computes a 2-sample t statistic, comparing the means of the datasets described by twoStatisticalSummaryinstances, under the assumption of equal subpopulation variances.static doubleTestUtils.homoscedasticTTest(double[] sample1, double[] sample2) static booleanTestUtils.homoscedasticTTest(double[] sample1, double[] sample2, double alpha) static doubleTestUtils.homoscedasticTTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) doubleTTest.homoscedasticTTest(double[] sample1, double[] sample2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances.booleanTTest.homoscedasticTTest(double[] sample1, double[] sample2, double alpha) Performs a two-sided t-test evaluating the null hypothesis thatsample1andsample2are drawn from populations with the same mean, with significance levelalpha, assuming that the subpopulation variances are equal.doubleTTest.homoscedasticTTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.static doubleTestUtils.pairedT(double[] sample1, double[] sample2) doubleTTest.pairedT(double[] sample1, double[] sample2) Computes a paired, 2-sample t-statistic based on the data in the input arrays.static doubleTestUtils.pairedTTest(double[] sample1, double[] sample2) static booleanTestUtils.pairedTTest(double[] sample1, double[] sample2, double alpha) doubleTTest.pairedTTest(double[] sample1, double[] sample2) Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays.booleanTTest.pairedTTest(double[] sample1, double[] sample2, double alpha) Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences betweensample1andsample2is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance levelalpha.static doubleTestUtils.t(double[] sample1, double[] sample2) static doubleTestUtils.t(double mu, double[] observed) static doubleTestUtils.t(double mu, StatisticalSummary sampleStats) static doubleTestUtils.t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) doubleTTest.t(double[] sample1, double[] sample2) Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.doubleTTest.t(double mu, double[] observed) Computes a t statistic given observed values and a comparison constant.doubleTTest.t(double mu, StatisticalSummary sampleStats) doubleTTest.t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Computes a 2-sample t statistic , comparing the means of the datasets described by twoStatisticalSummaryinstances, without the assumption of equal subpopulation variances.static doubleTestUtils.tTest(double[] sample1, double[] sample2) static booleanTestUtils.tTest(double[] sample1, double[] sample2, double alpha) static doubleTestUtils.tTest(double mu, double[] sample) static booleanTestUtils.tTest(double mu, double[] sample, double alpha) static doubleTestUtils.tTest(double mu, StatisticalSummary sampleStats) static booleanTestUtils.tTest(double mu, StatisticalSummary sampleStats, double alpha) static doubleTestUtils.tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) static booleanTestUtils.tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha) doubleTTest.tTest(double[] sample1, double[] sample2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.booleanTTest.tTest(double[] sample1, double[] sample2, double alpha) Performs a two-sided t-test evaluating the null hypothesis thatsample1andsample2are drawn from populations with the same mean, with significance levelalpha.doubleTTest.tTest(double mu, double[] sample) Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constantmu.booleanTTest.tTest(double mu, double[] sample, double alpha) Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from whichsampleis drawn equalsmu.doubleTTest.tTest(double mu, StatisticalSummary sampleStats) Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described bysampleStatswith the constantmu.booleanTTest.tTest(double mu, StatisticalSummary sampleStats, double alpha) Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described bystatsis drawn equalsmu.doubleTTest.tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.booleanTTest.tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha) Performs a two-sided t-test evaluating the null hypothesis thatsampleStats1andsampleStats2describe datasets drawn from populations with the same mean, with significance levelalpha. -
Uses of NumberIsTooSmallException in org.apache.commons.math3.util
Methods in org.apache.commons.math3.util that throw NumberIsTooSmallExceptionModifier and TypeMethodDescriptionprotected voidResizableDoubleArray.checkContractExpand(double contraction, double expansion) Checks the expansion factor and the contraction criterion and raises an exception if the contraction criterion is smaller than the expansion criterion.