Uses of Class
org.apache.commons.math3.exception.NumberIsTooLargeException

Packages that use NumberIsTooLargeException
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.solvers Root finding algorithms, for univariate real functions. 
org.apache.commons.math3.distribution Implementations of common discrete and continuous distributions. 
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.random Random number and random data generators. 
org.apache.commons.math3.special Implementations of special functions such as Beta and Gamma. 
org.apache.commons.math3.stat.inference Classes providing hypothesis testing and confidence interval construction. 
org.apache.commons.math3.util Convenience routines and common data structures used throughout the commons-math library. 
 

Uses of NumberIsTooLargeException in org.apache.commons.math3.analysis.differentiation
 

Methods in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooLargeException
 double DerivativeStructure.getPartialDerivative(int... orders)
          Get a partial derivative.
 int DSCompiler.getPartialDerivativeIndex(int... orders)
          Get the index of a partial derivative in the array.
 

Constructors in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooLargeException
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 NumberIsTooLargeException
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 NumberIsTooLargeException
protected  double MullerSolver.doSolve()
          Method for implementing actual optimization algorithms in derived classes.
protected  double BracketingNthOrderBrentSolver.doSolve()
          Method for implementing actual optimization algorithms in derived classes.
protected  double BrentSolver.doSolve()
          Method for implementing actual optimization algorithms in derived classes.
protected  double MullerSolver2.doSolve()
          Method for implementing actual optimization algorithms in derived classes.
 double LaguerreSolver.doSolve()
          Method for implementing actual optimization algorithms in derived classes.
 double BracketingNthOrderBrentSolver.solve(int maxEval, UnivariateFunction f, double min, double max, AllowedSolution allowedSolution)
          Solve for a zero in the given interval.
 double BracketingNthOrderBrentSolver.solve(int maxEval, UnivariateFunction f, double min, double max, double startValue, AllowedSolution allowedSolution)
          Solve for a zero in the given interval, start at startValue.
protected  void BaseAbstractUnivariateSolver.verifyInterval(double lower, double upper)
          Check that the endpoints specify an interval.
static void UnivariateSolverUtils.verifyInterval(double lower, double upper)
          Check that the endpoints specify an interval.
protected  void BaseAbstractUnivariateSolver.verifySequence(double lower, double initial, double upper)
          Check that lower < initial < upper.
static void UnivariateSolverUtils.verifySequence(double lower, double initial, double upper)
          Check that lower < initial < upper.
 

Uses of NumberIsTooLargeException in org.apache.commons.math3.distribution
 

Methods in org.apache.commons.math3.distribution that throw NumberIsTooLargeException
 double LogNormalDistribution.cumulativeProbability(double x0, double x1)
          Deprecated. See RealDistribution.cumulativeProbability(double,double)
 double RealDistribution.cumulativeProbability(double x0, double x1)
          Deprecated. As of 3.1. In 4.0, this method will be renamed probability(double x0, double x1).
 double AbstractRealDistribution.cumulativeProbability(double x0, double x1)
          Deprecated. As of 3.1 (to be removed in 4.0). Please use AbstractRealDistribution.probability(double,double) instead.
 double NormalDistribution.cumulativeProbability(double x0, double x1)
          Deprecated. See RealDistribution.cumulativeProbability(double,double)
 double AbstractIntegerDistribution.cumulativeProbability(int x0, int x1)
          For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
 double IntegerDistribution.cumulativeProbability(int x0, int x1)
          For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
 double LogNormalDistribution.probability(double x0, double x1)
          For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
 double NormalDistribution.probability(double x0, double x1)
          For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
 

Constructors in org.apache.commons.math3.distribution that throw NumberIsTooLargeException
HypergeometricDistribution(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)
          Create a uniform distribution.
UniformRealDistribution(RandomGenerator rng, double lower, double upper, double inverseCumAccuracy)
          Creates a uniform distribution.
 

Uses of NumberIsTooLargeException in org.apache.commons.math3.genetics
 

Methods in org.apache.commons.math3.genetics that throw NumberIsTooLargeException
 void ListPopulation.addChromosome(Chromosome chromosome)
          Add the given chromosome to the population.
 void Population.addChromosome(Chromosome chromosome)
          Add the given chromosome to the population.
 void ListPopulation.addChromosomes(Collection<Chromosome> chromosomeColl)
          Add a Collection of chromosomes to this Population.
 void ListPopulation.setChromosomes(List<Chromosome> chromosomes)
          Deprecated. use ListPopulation.addChromosomes(Collection) instead
 

Constructors in org.apache.commons.math3.genetics that throw NumberIsTooLargeException
ElitisticListPopulation(List<Chromosome> chromosomes, int populationLimit, double elitismRate)
          Creates a new ElitisticListPopulation instance.
ListPopulation(List<Chromosome> chromosomes, int populationLimit)
          Creates a new ListPopulation instance.
 

Uses of NumberIsTooLargeException in org.apache.commons.math3.linear
 

Methods in org.apache.commons.math3.linear that throw NumberIsTooLargeException
 OpenMapRealMatrix OpenMapRealMatrix.createMatrix(int rowDimension, int columnDimension)
          Deprecated. Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
 OpenMapRealMatrix OpenMapRealMatrix.multiply(OpenMapRealMatrix m)
          Deprecated. Postmultiply this matrix by m.
 RealMatrix OpenMapRealMatrix.multiply(RealMatrix m)
          Deprecated. Returns the result of postmultiplying this by m.
 

Constructors in org.apache.commons.math3.linear that throw NumberIsTooLargeException
ArrayFieldVector(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)
          Deprecated. 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 NumberIsTooLargeException
 int RandomDataGenerator.nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize)
          Generates a random value from the Hypergeometric Distribution.
 int RandomDataImpl.nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize)
          Deprecated. Generates a random value from the Hypergeometric Distribution.
 int RandomDataGenerator.nextInt(int lower, int upper)
          Generates a uniformly distributed random integer between lower and upper (endpoints included).
 int RandomData.nextInt(int lower, int upper)
          Deprecated. Generates a uniformly distributed random integer between lower and upper (endpoints included).
 int RandomDataImpl.nextInt(int lower, int upper)
          Deprecated. Generates a uniformly distributed random integer between lower and upper (endpoints included).
 long RandomDataGenerator.nextLong(long lower, long upper)
          Generates a uniformly distributed random long integer between lower and upper (endpoints included).
 long RandomData.nextLong(long lower, long upper)
          Deprecated. Generates a uniformly distributed random long integer between lower and upper (endpoints included).
 long RandomDataImpl.nextLong(long lower, long upper)
          Deprecated. Generates a uniformly distributed random long integer between lower and upper (endpoints included).
 int[] RandomDataGenerator.nextPermutation(int n, int k)
          Generates an integer array of length k whose entries are selected randomly, without repetition, from the integers 0, ..., n - 1 (inclusive).
 int[] RandomData.nextPermutation(int n, int k)
          Deprecated. Generates an integer array of length k whose entries are selected randomly, without repetition, from the integers 0, ..., n - 1 (inclusive).
 int[] RandomDataImpl.nextPermutation(int n, int k)
          Deprecated. Generates an integer array of length k whose entries are selected randomly, without repetition, from the integers 0, ..., n - 1 (inclusive).
 Object[] RandomDataGenerator.nextSample(Collection<?> c, int k)
          Returns an array of k objects selected randomly from the Collection c.
 Object[] RandomData.nextSample(Collection<?> c, int k)
          Deprecated. Returns an array of k objects selected randomly from the Collection c.
 Object[] RandomDataImpl.nextSample(Collection<?> c, int k)
          Deprecated. Returns an array of k objects selected randomly from the Collection c.
 int RandomDataGenerator.nextSecureInt(int lower, int upper)
          Generates a uniformly distributed random integer between lower and upper (endpoints included) from a secure random sequence.
 int RandomData.nextSecureInt(int lower, int upper)
          Deprecated. Generates a uniformly distributed random integer between lower and upper (endpoints included) from a secure random sequence.
 int RandomDataImpl.nextSecureInt(int lower, int upper)
          Deprecated. Generates a uniformly distributed random integer between lower and upper (endpoints included) from a secure random sequence.
 long RandomDataGenerator.nextSecureLong(long lower, long upper)
          Generates a uniformly distributed random long integer between lower and upper (endpoints included) from a secure random sequence.
 long RandomData.nextSecureLong(long lower, long upper)
          Deprecated. Generates a uniformly distributed random long integer between lower and upper (endpoints included) from a secure random sequence.
 long RandomDataImpl.nextSecureLong(long lower, long upper)
          Deprecated. Generates a uniformly distributed random long integer between lower and upper (endpoints included) from a secure random sequence.
 double RandomDataGenerator.nextUniform(double lower, double upper)
          Generates a uniformly distributed random value from the open interval (lower, upper) (i.e., endpoints excluded).
 double RandomData.nextUniform(double lower, double upper)
          Deprecated. Generates a uniformly distributed random value from the open interval (lower, upper) (i.e., endpoints excluded).
 double RandomDataImpl.nextUniform(double lower, double upper)
          Deprecated. Generates a uniformly distributed random value from the open interval (lower, upper) (i.e., endpoints excluded).
 double RandomDataGenerator.nextUniform(double lower, double upper, boolean lowerInclusive)
          Generates a uniformly distributed random value from the interval (lower, upper) or the interval [lower, upper).
 double RandomData.nextUniform(double lower, double upper, boolean lowerInclusive)
          Deprecated. Generates a uniformly distributed random value from the interval (lower, upper) or the interval [lower, upper).
 double RandomDataImpl.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 NumberIsTooLargeException
static double Gamma.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 NumberIsTooLargeException
 double WilcoxonSignedRankTest.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.util
 

Methods in org.apache.commons.math3.util that throw NumberIsTooLargeException
static long ArithmeticUtils.binomialCoefficient(int n, int k)
          Returns an exact representation of the Binomial Coefficient, "n choose k", the number of k-element subsets that can be selected from an n-element set.
static double ArithmeticUtils.binomialCoefficientDouble(int n, int k)
          Returns a double representation of the Binomial Coefficient, "n choose k", the number of k-element subsets that can be selected from an n-element set.
static double ArithmeticUtils.binomialCoefficientLog(int n, int k)
          Returns the natural log of the Binomial Coefficient, "n choose k", the number of k-element subsets that can be selected from an n-element set.
static long ArithmeticUtils.stirlingS2(int n, int k)
          Returns the Stirling number of the second kind, "S(n,k)", the number of ways of partitioning an n-element set into k non-empty subsets.
 



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