# Uses of Class
org.apache.commons.math3.exception.NumberIsTooSmallException

Packages that use NumberIsTooSmallException
Package
Description
org.apache.commons.math3.analysis.differentiation
This package holds the main interfaces and basic building block classes dealing with differentiation.
org.apache.commons.math3.analysis.integration
Numerical integration (quadrature) algorithms for univariate real functions.
org.apache.commons.math3.analysis.interpolation
Univariate real functions interpolation algorithms.
org.apache.commons.math3.analysis.polynomials
Univariate real polynomials implementations, seen as differentiable univariate real functions.
org.apache.commons.math3.analysis.solvers
Root finding algorithms, for univariate real functions.
org.apache.commons.math3.dfp
Decimal floating point library for Java
org.apache.commons.math3.distribution
Implementations of common discrete and continuous distributions.
org.apache.commons.math3.distribution.fitting
Fitting of parameters against distributions.
org.apache.commons.math3.exception
Specialized exceptions for algorithms errors.
org.apache.commons.math3.genetics
This package provides Genetic Algorithms components and implementations.
org.apache.commons.math3.linear
Linear algebra support.
org.apache.commons.math3.ml.clustering
Clustering algorithms.
org.apache.commons.math3.ode
This package provides classes to solve Ordinary Differential Equations problems.
org.apache.commons.math3.ode.nonstiff
This package provides classes to solve non-stiff Ordinary Differential Equations problems.
org.apache.commons.math3.special
Implementations of special functions such as Beta and Gamma.
org.apache.commons.math3.stat
Data storage, manipulation and summary routines.
org.apache.commons.math3.stat.correlation
Correlations/Covariance computations.
org.apache.commons.math3.stat.inference
Classes providing hypothesis testing.
org.apache.commons.math3.util
Convenience routines and common data structures used throughout the commons-math library.

## Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.differentiation

Constructors in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooSmallException
Modifier
Constructor
Description
``
`FiniteDifferencesDifferentiator(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 NumberIsTooSmallException
Modifier
Constructor
Description
`protected`
`BaseAbstractUnivariateIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)`
Construct an integrator with given accuracies and iteration counts.
`protected`
`BaseAbstractUnivariateIntegrator(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 NumberIsTooSmallException
Modifier and Type
Method
Description
`protected static double[]`
DividedDifferenceInterpolator.`computeDividedDifference(double[] x, double[] y)`
Return a copy of the divided difference array.
`PolynomialSplineFunction`
AkimaSplineInterpolator.`interpolate(double[] xvals, double[] yvals)`
Computes an interpolating function for the data set.
`BicubicInterpolatingFunction`
BicubicInterpolator.`interpolate(double[] xval, double[] yval, double[][] fval)`
Compute an interpolating function for the dataset.
`BicubicSplineInterpolatingFunction`
BicubicSplineInterpolator.`interpolate(double[] xval, double[] yval, double[][] fval)`
Deprecated.
Compute an interpolating function for the dataset.
`BivariateFunction`
BivariateGridInterpolator.`interpolate(double[] xval, double[] yval, double[][] fval)`
Compute an interpolating function for the dataset.
`PolynomialFunctionNewtonForm`
DividedDifferenceInterpolator.`interpolate(double[] x, double[] y)`
Compute an interpolating function for the dataset.
`PolynomialSplineFunction`
LinearInterpolator.`interpolate(double[] x, double[] y)`
Computes a linear interpolating function for the data set.
`final PolynomialSplineFunction`
LoessInterpolator.`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 a `SplineInterpolator` on the resulting fit.
`PolynomialFunctionLagrangeForm`
NevilleInterpolator.`interpolate(double[] x, double[] y)`
Computes an interpolating function for the data set.
`PolynomialSplineFunction`
SplineInterpolator.`interpolate(double[] x, double[] y)`
Computes an interpolating function for the data set.
`TricubicInterpolatingFunction`
TricubicInterpolator.`interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)`
Compute an interpolating function for the dataset.
`TricubicSplineInterpolatingFunction`
TricubicSplineInterpolator.`interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)`
Deprecated.
Compute an interpolating function for the dataset.
`TrivariateFunction`
TrivariateGridInterpolator.`interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)`
Compute an interpolating function for the dataset.
`UnivariateFunction`
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 NumberIsTooSmallException
Modifier and Type
Method
Description
`static double`
PolynomialFunctionLagrangeForm.`evaluate(double[] x, double[] y, double z)`
Evaluate the Lagrange polynomial using Neville's Algorithm.
`static boolean`
PolynomialFunctionLagrangeForm.`verifyInterpolationArray(double[] x, double[] y, boolean abort)`
Check that the interpolation arrays are valid.
Constructors in org.apache.commons.math3.analysis.polynomials that throw NumberIsTooSmallException
Modifier
Constructor
Description
``
`PolynomialFunctionLagrangeForm(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 NumberIsTooSmallException
Modifier
Constructor
Description
``
`BracketingNthOrderBrentSolver(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 NumberIsTooSmallException
Modifier
Constructor
Description
``
`BracketingNthOrderBrentSolverDFP(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 NumberIsTooSmallException
Modifier
Constructor
Description
``
`TriangularDistribution(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 NumberIsTooSmallException
Modifier
Constructor
Description
``
`MultivariateNormalMixtureExpectationMaximization(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.exception
Modifier and Type
Class
Description
`class`
`NotPositiveException`
Exception to be thrown when the argument is negative.
`class`
`NotStrictlyPositiveException`
Exception 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 NumberIsTooSmallException
Modifier and Type
Method
Description
`void`
ListPopulation.`setPopulationLimit(int populationLimit)`
Sets the maximal population size.
Constructors in org.apache.commons.math3.genetics that throw NumberIsTooSmallException
Modifier
Constructor
Description
``
`FixedElapsedTime(long maxTime)`
Create a new `FixedElapsedTime` instance.
``
`FixedElapsedTime(long maxTime, TimeUnit unit)`
Create a new `FixedElapsedTime` instance.
``
`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.linear
Modifier and Type
Class
Description
`class`
`NonPositiveDefiniteMatrixException`
Exception to be thrown when a positive definite matrix is expected.
Methods in org.apache.commons.math3.linear that throw NumberIsTooSmallException
Modifier and Type
Method
Description
`protected void`
RealVector.`checkIndices(int start, int end)`
Checks that the indices of a subvector are valid.
`protected void`
AbstractFieldMatrix.`checkSubMatrixIndex(int startRow, int endRow, int startColumn, int endColumn)`
Check if submatrix ranges indices are valid.
`static void`
MatrixUtils.`checkSubMatrixIndex(AnyMatrix m, int startRow, int endRow, int startColumn, int endColumn)`
Check if submatrix ranges indices are valid.
`void`
AbstractFieldMatrix.`copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination)`
Copy a submatrix.
`void`
AbstractRealMatrix.`copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination)`
Copy a submatrix.
`void`
FieldMatrix.`copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination)`
Copy a submatrix.
`void`
RealMatrix.`copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination)`
Copy a submatrix.
`FieldMatrix<T>`
AbstractFieldMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)`
Get a submatrix.
`RealMatrix`
AbstractRealMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)`
Gets a submatrix.
`FieldMatrix<T>`
BlockFieldMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)`
Get a submatrix.
`BlockRealMatrix`
BlockRealMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)`
Gets a submatrix.
`FieldMatrix<T>`
FieldMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)`
Get a submatrix.
`RealMatrix`
RealMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)`
Gets a submatrix.
`T`
AbstractFieldMatrix.`walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in column order.
`T`
AbstractFieldMatrix.`walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in column order.
`double`
AbstractRealMatrix.`walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in column order.
`double`
AbstractRealMatrix.`walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in column order.
`T`
Array2DRowFieldMatrix.`walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in column order.
`T`
Array2DRowFieldMatrix.`walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in column order.
`double`
Array2DRowRealMatrix.`walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in column order.
`double`
Array2DRowRealMatrix.`walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in column order.
`T`
FieldMatrix.`walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in column order.
`T`
FieldMatrix.`walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in column order.
`double`
RealMatrix.`walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in column order.
`double`
RealMatrix.`walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in column order.
`T`
ArrayFieldVector.`walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)`
Visits (and possibly alters) some entries of this vector in default order (increasing index).
`T`
ArrayFieldVector.`walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)`
Visits (but does not alter) some entries of this vector in default order (increasing index).
`double`
ArrayRealVector.`walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end)`
Visits (and possibly alters) some entries of this vector in default order (increasing index).
`double`
ArrayRealVector.`walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end)`
Visits (but does not alter) some entries of this vector in default order (increasing index).
`double`
RealVector.`walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end)`
Visits (and possibly alters) some entries of this vector in default order (increasing index).
`double`
RealVector.`walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end)`
Visits (but does not alter) some entries of this vector in default order (increasing index).
`T`
SparseFieldVector.`walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)`
Visits (and possibly alters) some entries of this vector in default order (increasing index).
`T`
SparseFieldVector.`walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)`
Visits (but does not alter) some entries of this vector in default order (increasing index).
`T`
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.
`T`
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.
`double`
AbstractRealMatrix.`walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries using the fastest possible order.
`double`
AbstractRealMatrix.`walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries using the fastest possible order.
`T`
ArrayFieldVector.`walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)`
Visits (and possibly change) some entries of this vector in optimized order.
`T`
ArrayFieldVector.`walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)`
Visits (but does not alter) some entries of this vector in optimized order.
`double`
ArrayRealVector.`walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end)`
Visits (and possibly change) some entries of this vector in optimized order.
`double`
ArrayRealVector.`walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end)`
Visits (but does not alter) some entries of this vector in optimized order.
`T`
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.
`T`
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.
`double`
BlockRealMatrix.`walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries using the fastest possible order.
`double`
BlockRealMatrix.`walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries using the fastest possible order.
`T`
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.
`T`
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.
`double`
RealMatrix.`walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries using the fastest possible order.
`double`
RealMatrix.`walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries using the fastest possible order.
`double`
RealVector.`walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end)`
Visits (and possibly change) some entries of this vector in optimized order.
`double`
RealVector.`walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end)`
Visits (but does not alter) some entries of this vector in optimized order.
`T`
SparseFieldVector.`walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)`
Visits (and possibly change) some entries of this vector in optimized order.
`T`
SparseFieldVector.`walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)`
Visits (but does not alter) some entries of this vector in optimized order.
`T`
AbstractFieldMatrix.`walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in row order.
`T`
AbstractFieldMatrix.`walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in row order.
`double`
AbstractRealMatrix.`walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in row order.
`double`
AbstractRealMatrix.`walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in row order.
`T`
Array2DRowFieldMatrix.`walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in row order.
`T`
Array2DRowFieldMatrix.`walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in row order.
`double`
Array2DRowRealMatrix.`walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in row order.
`double`
Array2DRowRealMatrix.`walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in row order.
`T`
BlockFieldMatrix.`walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in row order.
`T`
BlockFieldMatrix.`walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in row order.
`double`
BlockRealMatrix.`walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in row order.
`double`
BlockRealMatrix.`walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in row order.
`T`
FieldMatrix.`walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in row order.
`T`
FieldMatrix.`walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (but don't change) some matrix entries in row order.
`double`
RealMatrix.`walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)`
Visit (and possibly change) some matrix entries in row order.
`double`
RealMatrix.`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 NumberIsTooSmallException
Modifier
Constructor
Description
``
`FuzzyKMeansClusterer(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 NumberIsTooSmallException
Modifier and Type
Method
Description
`abstract void`
AbstractIntegrator.`integrate(ExpandableStatefulODE equations, double t)`
Integrate a set of differential equations up to the given time.
`double`
AbstractIntegrator.`integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y)`
Integrate the differential equations up to the given time.
`FieldODEStateAndDerivative<T>`
FirstOrderFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)`
Integrate the differential equations up to the given time.
`double`
FirstOrderIntegrator.`integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y)`
Integrate the differential equations up to the given time.
`protected void`
AbstractFieldIntegrator.`sanityChecks(FieldODEState<T> eqn, T t)`
Check the integration span.
`protected void`
AbstractIntegrator.`sanityChecks(ExpandableStatefulODE equations, double t)`
Check the integration span.
`protected void`
MultistepFieldIntegrator.`start(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T t)`
Start the integration.
`protected void`
MultistepIntegrator.`start(double t0, double[] y0, double t)`
Start the integration.
Constructors in org.apache.commons.math3.ode that throw NumberIsTooSmallException
Modifier
Constructor
Description
`protected`
`MultistepFieldIntegrator(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.
`protected`
`MultistepIntegrator(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 NumberIsTooSmallException
Modifier and Type
Method
Description
`protected T`
AdaptiveStepsizeFieldIntegrator.`filterStep(T h, boolean forward, boolean acceptSmall)`
Filter the integration step.
`protected double`
AdaptiveStepsizeIntegrator.`filterStep(double h, boolean forward, boolean acceptSmall)`
Filter the integration step.
`FieldODEStateAndDerivative<T>`
AdamsBashforthFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)`
Integrate the differential equations up to the given time.
`void`
AdamsBashforthIntegrator.`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 void`
AdamsIntegrator.`integrate(ExpandableStatefulODE equations, double t)`
Integrate a set of differential equations up to the given time.
`FieldODEStateAndDerivative<T>`
AdamsMoultonFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)`
Integrate the differential equations up to the given time.
`void`
AdamsMoultonIntegrator.`integrate(ExpandableStatefulODE equations, double t)`
Integrate a set of differential equations up to the given time.
`abstract void`
AdaptiveStepsizeIntegrator.`integrate(ExpandableStatefulODE equations, double t)`
Integrate a set of differential equations up to the given time.
`FieldODEStateAndDerivative<T>`
EmbeddedRungeKuttaFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)`
Integrate the differential equations up to the given time.
`void`
EmbeddedRungeKuttaIntegrator.`integrate(ExpandableStatefulODE equations, double t)`
Integrate a set of differential equations up to the given time.
`void`
GraggBulirschStoerIntegrator.`integrate(ExpandableStatefulODE equations, double t)`
Integrate a set of differential equations up to the given time.
`FieldODEStateAndDerivative<T>`
RungeKuttaFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)`
Integrate the differential equations up to the given time.
`void`
RungeKuttaIntegrator.`integrate(ExpandableStatefulODE equations, double t)`
Integrate a set of differential equations up to the given time.
`protected void`
AdaptiveStepsizeFieldIntegrator.`sanityChecks(FieldODEState<T> eqn, T t)`
Check the integration span.
`protected void`
AdaptiveStepsizeIntegrator.`sanityChecks(ExpandableStatefulODE equations, double t)`
Check the integration span.
Constructors in org.apache.commons.math3.ode.nonstiff that throw NumberIsTooSmallException
Modifier
Constructor
Description
``
`AdamsBashforthFieldIntegrator(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 NumberIsTooSmallException
Modifier and Type
Method
Description
`static double`
Gamma.`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 NumberIsTooSmallException
Modifier and Type
Method
Description
`static double`
StatUtils.`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 NumberIsTooSmallException
Modifier and Type
Method
Description
`double`
StorelessCovariance.`getCovariance(int xIndex, int yIndex)`
Get the covariance for an individual element of the covariance matrix.
`RealMatrix`
StorelessCovariance.`getCovarianceMatrix()`
Returns the covariance matrix
`double[][]`
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 NumberIsTooSmallException
Modifier and Type
Method
Description
`static double`
TestUtils.`homoscedasticT(double[] sample1, double[] sample2)`
`static double`
TestUtils.`homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
`double`
TTest.`homoscedasticT(double[] sample1, double[] sample2)`
Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.
`double`
TTest.`homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, under the assumption of equal subpopulation variances.
`static double`
TestUtils.`homoscedasticTTest(double[] sample1, double[] sample2)`
`static boolean`
TestUtils.`homoscedasticTTest(double[] sample1, double[] sample2, double alpha)`
`static double`
TestUtils.`homoscedasticTTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
`double`
TTest.`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.
`boolean`
TTest.`homoscedasticTTest(double[] sample1, double[] sample2, double alpha)`
Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`, assuming that the subpopulation variances are equal.
`double`
TTest.`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 double`
TestUtils.`pairedT(double[] sample1, double[] sample2)`
`double`
TTest.`pairedT(double[] sample1, double[] sample2)`
Computes a paired, 2-sample t-statistic based on the data in the input arrays.
`static double`
TestUtils.`pairedTTest(double[] sample1, double[] sample2)`
`static boolean`
TestUtils.`pairedTTest(double[] sample1, double[] sample2, double alpha)`
`double`
TTest.`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.
`boolean`
TTest.`pairedTTest(double[] sample1, double[] sample2, double alpha)`
Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between `sample1` and `sample2` is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level `alpha`.
`static double`
TestUtils.`t(double[] sample1, double[] sample2)`
`static double`
TestUtils.`t(double mu, double[] observed)`
`static double`
TestUtils.`t(double mu, StatisticalSummary sampleStats)`
`static double`
TestUtils.`t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
`double`
TTest.`t(double[] sample1, double[] sample2)`
Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.
`double`
TTest.`t(double mu, double[] observed)`
Computes a t statistic given observed values and a comparison constant.
`double`
TTest.`t(double mu, StatisticalSummary sampleStats)`
Computes a t statistic to use in comparing the mean of the dataset described by `sampleStats` to `mu`.
`double`
TTest.`t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
Computes a 2-sample t statistic , comparing the means of the datasets described by two `StatisticalSummary` instances, without the assumption of equal subpopulation variances.
`static double`
TestUtils.`tTest(double[] sample1, double[] sample2)`
`static boolean`
TestUtils.`tTest(double[] sample1, double[] sample2, double alpha)`
`static double`
TestUtils.`tTest(double mu, double[] sample)`
`static boolean`
TestUtils.`tTest(double mu, double[] sample, double alpha)`
`static double`
TestUtils.`tTest(double mu, StatisticalSummary sampleStats)`
`static boolean`
TestUtils.`tTest(double mu, StatisticalSummary sampleStats, double alpha)`
`static double`
TestUtils.`tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`
`static boolean`
TestUtils.`tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha)`
`double`
TTest.`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.
`boolean`
TTest.`tTest(double[] sample1, double[] sample2, double alpha)`
Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`.
`double`
TTest.`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 constant `mu`.
`boolean`
TTest.`tTest(double mu, double[] sample, double alpha)`
Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which `sample` is drawn equals `mu`.
`double`
TTest.`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 by `sampleStats` with the constant `mu`.
`boolean`
TTest.`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 by `stats` is drawn equals `mu`.
`double`
TTest.`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.
`boolean`
TTest.`tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha)`
Performs a two-sided t-test evaluating the null hypothesis that `sampleStats1` and `sampleStats2` describe datasets drawn from populations with the same mean, with significance level `alpha`.

## Uses of NumberIsTooSmallException in org.apache.commons.math3.util

Methods in org.apache.commons.math3.util that throw NumberIsTooSmallException
Modifier and Type
Method
Description
`protected void`
ResizableDoubleArray.`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.