Uses of Class
org.apache.commons.math3.exception.NumberIsTooLargeException
Packages that use NumberIsTooLargeException
Package
Description
Parent package for common numerical analysis procedures, including root finding,
function interpolation and integration.
This package holds the main interfaces and basic building block classes
dealing with differentiation.
Numerical integration (quadrature) algorithms for univariate real functions.
Root finding algorithms, for univariate real functions.
Implementations of common discrete and continuous distributions.
This package provides Genetic Algorithms components and implementations.
This package provides basic geometry components on the 1-sphere.
Linear algebra support.
Random number and random data generators.
Implementations of special functions such as Beta and Gamma.
Classes providing hypothesis testing.
Classes providing binomial proportion confidence interval construction.
Convenience routines and common data structures used throughout the commons-math library.
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Uses of NumberIsTooLargeException in org.apache.commons.math3.analysis
Methods in org.apache.commons.math3.analysis that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptionstatic double[]FunctionUtils.sample(UnivariateFunction f, double min, double max, int n) Samples the specified univariate real function on the specified interval. -
Uses of NumberIsTooLargeException in org.apache.commons.math3.analysis.differentiation
Methods in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptionstatic DSCompilerDSCompiler.getCompiler(int parameters, int order) Get the compiler for number of free parameters and order.doubleDerivativeStructure.getPartialDerivative(int... orders) Get a partial derivative.intDSCompiler.getPartialDerivativeIndex(int... orders) Get the index of a partial derivative in the array.Constructors in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooLargeExceptionModifierConstructorDescriptionDerivativeStructure(int parameters, int order) Build an instance with all values and derivatives set to 0.DerivativeStructure(int parameters, int order, double value) Build an instance representing a constant value.DerivativeStructure(int parameters, int order, double... derivatives) Build an instance from all its derivatives.DerivativeStructure(int parameters, int order, int index, double value) Build an instance representing a variable.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 NumberIsTooLargeException in org.apache.commons.math3.analysis.integration
Constructors in org.apache.commons.math3.analysis.integration that throw NumberIsTooLargeExceptionModifierConstructorDescriptionMidPointIntegrator(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 NumberIsTooLargeException in org.apache.commons.math3.analysis.solvers
Methods in org.apache.commons.math3.analysis.solvers that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptionprotected doubleBracketingNthOrderBrentSolver.doSolve()Method for implementing actual optimization algorithms in derived classes.protected doubleBrentSolver.doSolve()Method for implementing actual optimization algorithms in derived classes.doubleLaguerreSolver.doSolve()Method for implementing actual optimization algorithms in derived classes.protected doubleMullerSolver.doSolve()Method for implementing actual optimization algorithms in derived classes.protected doubleMullerSolver2.doSolve()Method for implementing actual optimization algorithms in derived classes.doubleBracketingNthOrderBrentSolver.solve(int maxEval, UnivariateFunction f, double min, double max, double startValue, AllowedSolution allowedSolution) Solve for a zero in the given interval, start atstartValue.doubleBracketingNthOrderBrentSolver.solve(int maxEval, UnivariateFunction f, double min, double max, AllowedSolution allowedSolution) Solve for a zero in the given interval.protected voidBaseAbstractUnivariateSolver.verifyInterval(double lower, double upper) Check that the endpoints specify an interval.static voidUnivariateSolverUtils.verifyInterval(double lower, double upper) Check that the endpoints specify an interval.protected voidBaseAbstractUnivariateSolver.verifySequence(double lower, double initial, double upper) Check thatlower < initial < upper.static voidUnivariateSolverUtils.verifySequence(double lower, double initial, double upper) Check thatlower < initial < upper. -
Uses of NumberIsTooLargeException in org.apache.commons.math3.distribution
Methods in org.apache.commons.math3.distribution that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptiondoubleAbstractIntegerDistribution.cumulativeProbability(int x0, int x1) For a random variableXwhose values are distributed according to this distribution, this method returnsP(x0 < X <= x1).doubleAbstractRealDistribution.cumulativeProbability(double x0, double x1) Deprecated.As of 3.1 (to be removed in 4.0).doubleIntegerDistribution.cumulativeProbability(int x0, int x1) For a random variableXwhose values are distributed according to this distribution, this method returnsP(x0 < X <= x1).doubleLogNormalDistribution.cumulativeProbability(double x0, double x1) Deprecated.doubleNormalDistribution.cumulativeProbability(double x0, double x1) Deprecated.doubleParetoDistribution.cumulativeProbability(double x0, double x1) Deprecated.doubleRealDistribution.cumulativeProbability(double x0, double x1) Deprecated.As of 3.1.doubleLogNormalDistribution.probability(double x0, double x1) For a random variableXwhose values are distributed according to this distribution, this method returnsP(x0 < X <= x1).doubleNormalDistribution.probability(double x0, double x1) For a random variableXwhose values are distributed according to this distribution, this method returnsP(x0 < X <= x1).Constructors in org.apache.commons.math3.distribution that throw NumberIsTooLargeExceptionModifierConstructorDescriptionHypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize) Construct a new hypergeometric distribution with the specified population size, number of successes in the population, and sample size.HypergeometricDistribution(RandomGenerator rng, int populationSize, int numberOfSuccesses, int sampleSize) Creates a new hypergeometric distribution.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.UniformIntegerDistribution(int lower, int upper) Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).UniformIntegerDistribution(RandomGenerator rng, int lower, int upper) Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).UniformRealDistribution(double lower, double upper) Create a uniform real distribution using the given lower and upper bounds.UniformRealDistribution(double lower, double upper, double inverseCumAccuracy) Deprecated.as of 3.2, inverse CDF is now calculated analytically, useUniformRealDistribution(double, double)instead.UniformRealDistribution(RandomGenerator rng, double lower, double upper) Creates a uniform distribution. -
Uses of NumberIsTooLargeException in org.apache.commons.math3.genetics
Methods in org.apache.commons.math3.genetics that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptionvoidListPopulation.addChromosome(Chromosome chromosome) Add the given chromosome to the population.voidPopulation.addChromosome(Chromosome chromosome) Add the given chromosome to the population.voidListPopulation.addChromosomes(Collection<Chromosome> chromosomeColl) Add aCollectionof chromosomes to thisPopulation.voidListPopulation.setChromosomes(List<Chromosome> chromosomes) Deprecated.useListPopulation.addChromosomes(Collection)insteadConstructors in org.apache.commons.math3.genetics that throw NumberIsTooLargeExceptionModifierConstructorDescriptionElitisticListPopulation(List<Chromosome> chromosomes, int populationLimit, double elitismRate) Creates a newElitisticListPopulationinstance.ListPopulation(List<Chromosome> chromosomes, int populationLimit) Creates a new ListPopulation instance. -
Uses of NumberIsTooLargeException in org.apache.commons.math3.geometry.spherical.oned
Constructors in org.apache.commons.math3.geometry.spherical.oned that throw NumberIsTooLargeException -
Uses of NumberIsTooLargeException in org.apache.commons.math3.linear
Methods in org.apache.commons.math3.linear that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptionvoidDiagonalMatrix.addToEntry(int row, int column, double increment) Adds (in place) the specified value to the specified entry ofthismatrix.OpenMapRealMatrix.createMatrix(int rowDimension, int columnDimension) Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.OpenMapRealMatrix.multiply(OpenMapRealMatrix m) Postmultiply this matrix bym.OpenMapRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.voidDiagonalMatrix.setEntry(int row, int column, double value) Set the entry in the specified row and column.Constructors in org.apache.commons.math3.linear that throw NumberIsTooLargeExceptionModifierConstructorDescriptionArrayFieldVector(Field<T> field, T[] d, int pos, int size) Construct a vector from part of a array.ArrayFieldVector(T[] d, int pos, int size) Construct a vector from part of a array.ArrayRealVector(double[] d, int pos, int size) Construct a vector from part of a array.ArrayRealVector(Double[] d, int pos, int size) Construct a vector from part of an array.OpenMapRealMatrix(int rowDimension, int columnDimension) Build a sparse matrix with the supplied row and column dimensions. -
Uses of NumberIsTooLargeException in org.apache.commons.math3.random
Methods in org.apache.commons.math3.random that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptionintRandomDataGenerator.nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize) Generates a random value from theHypergeometric Distribution.intRandomDataImpl.nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize) Deprecated.Generates a random value from theHypergeometric Distribution.intRandomData.nextInt(int lower, int upper) Deprecated.Generates a uniformly distributed random integer betweenlowerandupper(endpoints included).intRandomDataGenerator.nextInt(int lower, int upper) Generates a uniformly distributed random integer betweenlowerandupper(endpoints included).intRandomDataImpl.nextInt(int lower, int upper) Deprecated.Generates a uniformly distributed random integer betweenlowerandupper(endpoints included).longRandomData.nextLong(long lower, long upper) Deprecated.Generates a uniformly distributed random long integer betweenlowerandupper(endpoints included).longRandomDataGenerator.nextLong(long lower, long upper) Generates a uniformly distributed random long integer betweenlowerandupper(endpoints included).longRandomDataImpl.nextLong(long lower, long upper) Deprecated.Generates a uniformly distributed random long integer betweenlowerandupper(endpoints included).int[]RandomData.nextPermutation(int n, int k) Deprecated.Generates an integer array of lengthkwhose entries are selected randomly, without repetition, from the integers0, ..., n - 1(inclusive).int[]RandomDataGenerator.nextPermutation(int n, int k) Generates an integer array of lengthkwhose entries are selected randomly, without repetition, from the integers0, ..., n - 1(inclusive).int[]RandomDataImpl.nextPermutation(int n, int k) Deprecated.Generates an integer array of lengthkwhose entries are selected randomly, without repetition, from the integers0, ..., n - 1(inclusive).Object[]RandomData.nextSample(Collection<?> c, int k) Deprecated.Returns an array ofkobjects selected randomly from the Collectionc.Object[]RandomDataGenerator.nextSample(Collection<?> c, int k) Returns an array ofkobjects selected randomly from the Collectionc.Object[]RandomDataImpl.nextSample(Collection<?> c, int k) Deprecated.Returns an array ofkobjects selected randomly from the Collectionc.intRandomData.nextSecureInt(int lower, int upper) Deprecated.Generates a uniformly distributed random integer betweenlowerandupper(endpoints included) from a secure random sequence.intRandomDataGenerator.nextSecureInt(int lower, int upper) Generates a uniformly distributed random integer betweenlowerandupper(endpoints included) from a secure random sequence.intRandomDataImpl.nextSecureInt(int lower, int upper) Deprecated.Generates a uniformly distributed random integer betweenlowerandupper(endpoints included) from a secure random sequence.longRandomData.nextSecureLong(long lower, long upper) Deprecated.Generates a uniformly distributed random long integer betweenlowerandupper(endpoints included) from a secure random sequence.longRandomDataGenerator.nextSecureLong(long lower, long upper) Generates a uniformly distributed random long integer betweenlowerandupper(endpoints included) from a secure random sequence.longRandomDataImpl.nextSecureLong(long lower, long upper) Deprecated.Generates a uniformly distributed random long integer betweenlowerandupper(endpoints included) from a secure random sequence.doubleRandomData.nextUniform(double lower, double upper) Deprecated.Generates a uniformly distributed random value from the open interval(lower, upper)(i.e., endpoints excluded).doubleRandomData.nextUniform(double lower, double upper, boolean lowerInclusive) Deprecated.Generates a uniformly distributed random value from the interval(lower, upper)or the interval[lower, upper).doubleRandomDataGenerator.nextUniform(double lower, double upper) Generates a uniformly distributed random value from the open interval(lower, upper)(i.e., endpoints excluded).doubleRandomDataGenerator.nextUniform(double lower, double upper, boolean lowerInclusive) Generates a uniformly distributed random value from the interval(lower, upper)or the interval[lower, upper).doubleRandomDataImpl.nextUniform(double lower, double upper) Deprecated.Generates a uniformly distributed random value from the open interval(lower, upper)(i.e., endpoints excluded).doubleRandomDataImpl.nextUniform(double lower, double upper, boolean lowerInclusive) Deprecated.Generates a uniformly distributed random value from the interval(lower, upper)or the interval[lower, upper). -
Uses of NumberIsTooLargeException in org.apache.commons.math3.special
Methods in org.apache.commons.math3.special that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptionstatic doubleGamma.logGamma1p(double x) Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5. -
Uses of NumberIsTooLargeException in org.apache.commons.math3.stat.inference
Methods in org.apache.commons.math3.stat.inference that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptiondoubleWilcoxonSignedRankTest.wilcoxonSignedRankTest(double[] x, double[] y, boolean exactPValue) Returns the observed significance level, or p-value, associated with a Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample. -
Uses of NumberIsTooLargeException in org.apache.commons.math3.stat.interval
Methods in org.apache.commons.math3.stat.interval that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptionBinomialConfidenceInterval.createInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel) Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level. -
Uses of NumberIsTooLargeException in org.apache.commons.math3.util
Methods in org.apache.commons.math3.util that throw NumberIsTooLargeExceptionModifier and TypeMethodDescriptionstatic longArithmeticUtils.binomialCoefficient(int n, int k) Deprecated.static longCombinatoricsUtils.binomialCoefficient(int n, int k) Returns an exact representation of the Binomial Coefficient, "n choose k", the number ofk-element subsets that can be selected from ann-element set.static doubleArithmeticUtils.binomialCoefficientDouble(int n, int k) Deprecated.static doubleCombinatoricsUtils.binomialCoefficientDouble(int n, int k) Returns adoublerepresentation of the Binomial Coefficient, "n choose k", the number ofk-element subsets that can be selected from ann-element set.static doubleArithmeticUtils.binomialCoefficientLog(int n, int k) Deprecated.static doubleCombinatoricsUtils.binomialCoefficientLog(int n, int k) Returns the naturallogof the Binomial Coefficient, "n choose k", the number ofk-element subsets that can be selected from ann-element set.static voidCombinatoricsUtils.checkBinomial(int n, int k) Check binomial preconditions.static longArithmeticUtils.stirlingS2(int n, int k) Deprecated.static longCombinatoricsUtils.stirlingS2(int n, int k) Returns the Stirling number of the second kind, "S(n,k)", the number of ways of partitioning ann-element set intoknon-empty subsets.