Uses of Class
org.hipparchus.exception.MathIllegalStateException

Packages that use MathIllegalStateException

Package	Description
org.hipparchus.analysis.integration	Numerical integration (quadrature) algorithms for univariate real functions.
org.hipparchus.analysis.solvers	Root finding algorithms, for univariate real functions.
org.hipparchus.clustering	Clustering algorithms.
org.hipparchus.complex	Complex number type and implementations of complex transcendental functions.
org.hipparchus.fraction	Fraction number type and fraction number formatting.
org.hipparchus.geometry	This package is the top level package for geometry.
org.hipparchus.geometry.euclidean.oned	This package provides basic 1D geometry components.
org.hipparchus.geometry.euclidean.threed	This package provides basic 3D geometry components.
org.hipparchus.geometry.euclidean.twod	This package provides basic 2D geometry components.
org.hipparchus.geometry.euclidean.twod.hull	This package provides algorithms to generate the convex hull for a set of points in an two-dimensional euclidean space.
org.hipparchus.geometry.hull	This package provides interfaces and classes related to the convex hull problem.
org.hipparchus.geometry.spherical.oned	This package provides basic geometry components on the 1-sphere.
org.hipparchus.geometry.spherical.twod	This package provides basic geometry components on the 2-sphere.
org.hipparchus.linear	Linear algebra support.
org.hipparchus.ode	This package provides classes to solve Ordinary Differential Equations problems.
org.hipparchus.ode.events	Events
org.hipparchus.ode.nonstiff	This package provides classes to solve non-stiff Ordinary Differential Equations problems.
org.hipparchus.ode.nonstiff.interpolators	This package provides classes implementing interpolators for dense outputs of ODE integrators.
org.hipparchus.ode.sampling	This package provides classes to handle sampling steps during Ordinary Differential Equations integration.
org.hipparchus.optim	Generally, optimizers are algorithms that will either minimize or maximize a scalar function, called the objective function.
org.hipparchus.optim.linear	Optimization algorithms for linear constrained problems.
org.hipparchus.optim.nonlinear.scalar	Algorithms for optimizing a scalar function.
org.hipparchus.optim.nonlinear.scalar.gradient	This package provides optimization algorithms that require derivatives.
org.hipparchus.optim.nonlinear.scalar.noderiv	This package provides optimization algorithms that do not require derivatives.
org.hipparchus.optim.nonlinear.vector.constrained	This package provides algorithms that minimize the residuals between observations and model values.
org.hipparchus.optim.univariate	One-dimensional optimization algorithms.
org.hipparchus.random	Random number and random data generators.
org.hipparchus.special	Implementations of special functions such as Beta and Gamma.
org.hipparchus.stat.descriptive	Generic univariate and multivariate summary statistic objects.
org.hipparchus.stat.fitting	Statistical methods for fitting distributions.
org.hipparchus.stat.inference	Classes providing hypothesis testing.
org.hipparchus.util	Convenience routines and common data structures used throughout the Hipparchus library.

Uses of MathIllegalStateException in org.hipparchus.analysis.integration

Methods in org.hipparchus.analysis.integration that throw MathIllegalStateException

Modifier and Type	Method	Description
protected T	BaseAbstractFieldUnivariateIntegrator.computeObjectiveValue(T point)	Compute the objective function value.
protected double	BaseAbstractUnivariateIntegrator.computeObjectiveValue(double point)	Compute the objective function value.
protected abstract T	BaseAbstractFieldUnivariateIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected abstract double	BaseAbstractUnivariateIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected T	FieldMidPointIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected T	FieldRombergIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected T	FieldSimpsonIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected T	FieldTrapezoidIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected T	IterativeLegendreFieldGaussIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected double	IterativeLegendreGaussIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected double	MidPointIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected double	RombergIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected double	SimpsonIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
protected double	TrapezoidIntegrator.doIntegrate()	Method for implementing actual integration algorithms in derived classes.
T	BaseAbstractFieldUnivariateIntegrator.integrate(int maxEval, CalculusFieldUnivariateFunction<T> f, T lower, T upper)	Integrate the function in the given interval.
double	BaseAbstractUnivariateIntegrator.integrate(int maxEval, UnivariateFunction f, double lower, double upper)	Integrate the function in the given interval.
T	FieldUnivariateIntegrator.integrate(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max)	Integrate the function in the given interval.
double	UnivariateIntegrator.integrate(int maxEval, UnivariateFunction f, double min, double max)	Integrate the function in the given interval.

Uses of MathIllegalStateException in org.hipparchus.analysis.solvers

Methods in org.hipparchus.analysis.solvers that throw MathIllegalStateException

Modifier and Type	Method	Description
protected double	BaseAbstractUnivariateSolver.computeObjectiveValue(double point)	Compute the objective function value.
protected DerivativeStructure	AbstractUnivariateDifferentiableSolver.computeObjectiveValueAndDerivative(double point)	Compute the objective function value.
protected abstract double	BaseAbstractUnivariateSolver.doSolve()	Method for implementing actual optimization algorithms in derived classes.
protected double	BaseSecantSolver.doSolve()	Method for implementing actual optimization algorithms in derived classes.
protected double	BisectionSolver.doSolve()	Method for implementing actual optimization algorithms in derived classes.
protected double	BrentSolver.doSolve()	Method for implementing actual optimization algorithms in derived classes.
double	LaguerreSolver.doSolve()	Method for implementing actual optimization algorithms in derived classes.
protected double	MullerSolver.doSolve()	Method for implementing actual optimization algorithms in derived classes.
protected double	MullerSolver2.doSolve()	Method for implementing actual optimization algorithms in derived classes.
protected double	NewtonRaphsonSolver.doSolve()	Method for implementing actual optimization algorithms in derived classes.
protected double	RiddersSolver.doSolve()	Method for implementing actual optimization algorithms in derived classes.
protected double	SecantSolver.doSolve()	Method for implementing actual optimization algorithms in derived classes.
protected BracketedUnivariateSolver.Interval	BaseSecantSolver.doSolveInterval()	Find a root and return the containing interval.
protected void	BaseAbstractUnivariateSolver.incrementEvaluationCount()	Increment the evaluation count by one.
double	BaseAbstractUnivariateSolver.solve(int maxEval, F f, double startValue)	Solve for a zero in the vicinity of startValue.
double	BaseAbstractUnivariateSolver.solve(int maxEval, F f, double min, double max, double startValue)	Solve for a zero in the given interval, start at startValue.
double	BaseUnivariateSolver.solve(int maxEval, F f, double min, double max)	Solve for a zero root in the given interval.
double	BaseUnivariateSolver.solve(int maxEval, F f, double min, double max, double startValue)	Solve for a zero in the given interval, start at startValue.
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.
double	BracketingNthOrderBrentSolver.solve(int maxEval, UnivariateFunction f, double min, double max, AllowedSolution allowedSolution)	Solve for a zero in the given interval.
double	NewtonRaphsonSolver.solve(int maxEval, UnivariateDifferentiableFunction f, double min, double max)	Find a zero near the midpoint of min and max.
Complex[]	LaguerreSolver.solveAllComplex(double[] coefficients, double initial)	Find all complex roots for the polynomial with the given coefficients, starting from the given initial value.
Complex[]	LaguerreSolver.solveAllComplex(double[] coefficients, int maxEval, double initial)	Find all complex roots for the polynomial with the given coefficients, starting from the given initial value.
Complex	LaguerreSolver.solveComplex(double[] coefficients, double initial)	Find a complex root for the polynomial with the given coefficients, starting from the given initial value.
BracketedUnivariateSolver.Interval	BaseSecantSolver.solveInterval(int maxEval, UnivariateFunction f, double min, double max, double startValue)	Solve for a zero in the given interval and return a tolerance interval surrounding the root.
default BracketedRealFieldUnivariateSolver.Interval<T>	BracketedRealFieldUnivariateSolver.solveInterval(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max)	Solve for a zero in the given interval and return a tolerance interval surrounding the root.
BracketedRealFieldUnivariateSolver.Interval<T>	BracketedRealFieldUnivariateSolver.solveInterval(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max, T startValue)	Solve for a zero in the given interval and return a tolerance interval surrounding the root.
default BracketedUnivariateSolver.Interval	BracketedUnivariateSolver.solveInterval(int maxEval, F f, double min, double max)	Solve for a zero in the given interval and return a tolerance interval surrounding the root.
BracketedUnivariateSolver.Interval	BracketedUnivariateSolver.solveInterval(int maxEval, F f, double min, double max, double startValue)	Solve for a zero in the given interval and return a tolerance interval surrounding the root.
BracketedUnivariateSolver.Interval	BracketingNthOrderBrentSolver.solveInterval(int maxEval, UnivariateFunction f, double min, double max, double startValue)	Solve for a zero in the given interval and return a tolerance interval surrounding the root.
BracketedRealFieldUnivariateSolver.Interval<T>	FieldBracketingNthOrderBrentSolver.solveInterval(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max, T startValue)	Solve for a zero in the given interval and return a tolerance interval surrounding the root.

Uses of MathIllegalStateException in org.hipparchus.clustering

Methods in org.hipparchus.clustering that throw MathIllegalStateException

Modifier and Type	Method	Description
abstract List<? extends Cluster<T>>	Clusterer.cluster(Collection<T> points)	Perform a cluster analysis on the given set of Clusterable instances.
List<CentroidCluster<T>>	KMeansPlusPlusClusterer.cluster(Collection<T> points)	Runs the K-means++ clustering algorithm.
List<CentroidCluster<T>>	MultiKMeansPlusPlusClusterer.cluster(Collection<T> points)	Runs the K-means++ clustering algorithm.

Uses of MathIllegalStateException in org.hipparchus.complex

Methods in org.hipparchus.complex that throw MathIllegalStateException

Modifier and Type	Method	Description
double	RootsOfUnity.getImaginary(int k)	Get the imaginary part of the k-th n-th root of unity.
double	RootsOfUnity.getReal(int k)	Get the real part of the k-th n-th root of unity.
boolean	RootsOfUnity.isCounterClockWise()	Returns true if RootsOfUnity.computeRoots(int) was called with a positive value of its argument n.
Complex	ComplexFormat.parse(String source)	Parses a string to produce a Complex object.

Uses of MathIllegalStateException in org.hipparchus.fraction

Methods in org.hipparchus.fraction that throw MathIllegalStateException

Modifier and Type	Method	Description
StringBuffer	FractionFormat.format(Object obj, StringBuffer toAppendTo, FieldPosition pos)	Formats an object and appends the result to a StringBuffer.
BigFraction	BigFractionFormat.parse(String source)	Parses a string to produce a BigFraction object.
Fraction	FractionFormat.parse(String source)	Parses a string to produce a Fraction object.

Constructors in org.hipparchus.fraction that throw MathIllegalStateException

Constructor	Description
BigFraction(double value, double epsilon, int maxIterations)	Create a fraction given the double value and maximum error allowed.
BigFraction(double value, long maxDenominator)	Create a fraction given the double value and maximum denominator.
Fraction(double value)	Create a fraction given the double value.
Fraction(double value, double epsilon, int maxIterations)	Create a fraction given the double value and maximum error allowed.
Fraction(double value, int maxDenominator)	Create a fraction given the double value and maximum denominator.

Uses of MathIllegalStateException in org.hipparchus.geometry

Methods in org.hipparchus.geometry that throw MathIllegalStateException

Modifier and Type	Method	Description
abstract Vector<S,V>	VectorFormat.parse(String source)	Parses a string to produce a Vector object.

Uses of MathIllegalStateException in org.hipparchus.geometry.euclidean.oned

Methods in org.hipparchus.geometry.euclidean.oned that throw MathIllegalStateException

Modifier and Type	Method	Description
Vector1D	Vector1DFormat.parse(String source)	Parses a string to produce a Vector object.

Uses of MathIllegalStateException in org.hipparchus.geometry.euclidean.threed

Methods in org.hipparchus.geometry.euclidean.threed that throw MathIllegalStateException

Modifier and Type	Method	Description
Vector3D	Vector3DFormat.parse(String source)	Parses a string to produce a Vector3D object.

Uses of MathIllegalStateException in org.hipparchus.geometry.euclidean.twod

Methods in org.hipparchus.geometry.euclidean.twod that throw MathIllegalStateException

Modifier and Type	Method	Description
Vector2D	Vector2DFormat.parse(String source)	Parses a string to produce a Vector object.

Uses of MathIllegalStateException in org.hipparchus.geometry.euclidean.twod.hull

Methods in org.hipparchus.geometry.euclidean.twod.hull that throw MathIllegalStateException

Modifier and Type	Method	Description
ConvexHull2D	ConvexHullGenerator2D.generate(Collection<Vector2D> points)	Builds the convex hull from the set of input points.

Uses of MathIllegalStateException in org.hipparchus.geometry.hull

Methods in org.hipparchus.geometry.hull that throw MathIllegalStateException

Modifier and Type	Method	Description
ConvexHull<S,P,H,I>	ConvexHullGenerator.generate(Collection<P> points)	Builds the convex hull from the set of input points.

Uses of MathIllegalStateException in org.hipparchus.geometry.spherical.oned

Subclasses of MathIllegalStateException in org.hipparchus.geometry.spherical.oned

Modifier and Type	Class	Description
static class	ArcsSet.InconsistentStateAt2PiWrapping	Specialized exception for inconsistent BSP tree state inconsistency.

Uses of MathIllegalStateException in org.hipparchus.geometry.spherical.twod

Methods in org.hipparchus.geometry.spherical.twod that throw MathIllegalStateException

Modifier and Type	Method	Description
protected void	SphericalPolygonsSet.computeGeometricalProperties()	Compute some geometrical properties.
List<Vertex>	SphericalPolygonsSet.getBoundaryLoops()	Get the boundary loops of the polygon.

Uses of MathIllegalStateException in org.hipparchus.linear

Methods in org.hipparchus.linear that throw MathIllegalStateException

Modifier and Type	Method	Description
RealVector	IterativeLinearSolver.solve(RealLinearOperator a, RealVector b)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	IterativeLinearSolver.solve(RealLinearOperator a, RealVector b, RealVector x0)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	PreconditionedIterativeLinearSolver.solve(RealLinearOperator a, RealLinearOperator m, RealVector b)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	PreconditionedIterativeLinearSolver.solve(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	PreconditionedIterativeLinearSolver.solve(RealLinearOperator a, RealVector b)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	PreconditionedIterativeLinearSolver.solve(RealLinearOperator a, RealVector b, RealVector x0)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	SymmLQ.solve(RealLinearOperator a, RealLinearOperator m, RealVector b)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	SymmLQ.solve(RealLinearOperator a, RealLinearOperator m, RealVector b, boolean goodb, double shift)	Returns an estimate of the solution to the linear system (A - shift · I) · x = b.
RealVector	SymmLQ.solve(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	SymmLQ.solve(RealLinearOperator a, RealVector b)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	SymmLQ.solve(RealLinearOperator a, RealVector b, boolean goodb, double shift)	Returns the solution to the system (A - shift · I) · x = b.
RealVector	SymmLQ.solve(RealLinearOperator a, RealVector b, RealVector x)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	ConjugateGradient.solveInPlace(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)	Returns an estimate of the solution to the linear system A · x = b.
abstract RealVector	IterativeLinearSolver.solveInPlace(RealLinearOperator a, RealVector b, RealVector x0)	Returns an estimate of the solution to the linear system A · x = b.
abstract RealVector	PreconditionedIterativeLinearSolver.solveInPlace(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	PreconditionedIterativeLinearSolver.solveInPlace(RealLinearOperator a, RealVector b, RealVector x0)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	SymmLQ.solveInPlace(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x)	Returns an estimate of the solution to the linear system A · x = b.
RealVector	SymmLQ.solveInPlace(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x, boolean goodb, double shift)	Returns an estimate of the solution to the linear system (A - shift · I) · x = b.
RealVector	SymmLQ.solveInPlace(RealLinearOperator a, RealVector b, RealVector x)	Returns an estimate of the solution to the linear system A · x = b.

Uses of MathIllegalStateException in org.hipparchus.ode

Methods in org.hipparchus.ode that throw MathIllegalStateException

Modifier and Type	Method	Description
protected FieldODEStateAndDerivative<T>	AbstractFieldIntegrator.acceptStep(AbstractFieldODEStateInterpolator<T> interpolator, T tEnd)	Accept a step, triggering events and step handlers.
protected ODEStateAndDerivative	AbstractIntegrator.acceptStep(AbstractODEStateInterpolator interpolator, double tEnd)	Accept a step, triggering events and step handlers.
void	DenseOutputModel.append(DenseOutputModel model)	Append another model at the end of the instance.
void	FieldDenseOutputModel.append(FieldDenseOutputModel<T> model)	Append another model at the end of the instance.
T[]	AbstractFieldIntegrator.computeDerivatives(T t, T[] y)	Compute the derivatives and check the number of evaluations.
double[]	AbstractIntegrator.computeDerivatives(double t, double[] y)	Compute the derivatives and check the number of evaluations.
Complex[]	ComplexSecondaryODE.computeDerivatives(double t, Complex[] primary, Complex[] primaryDot, Complex[] secondary)	Compute the derivatives related to the secondary state parameters.
double[]	ExpandableODE.computeDerivatives(double t, double[] y)	Get the current time derivative of the complete state vector.
T[]	FieldExpandableODE.computeDerivatives(T t, T[] y)	Get the current time derivative of the complete state vector.
T[]	FieldSecondaryODE.computeDerivatives(T t, T[] primary, T[] primaryDot, T[] secondary)	Compute the derivatives related to the secondary state parameters.
double[]	SecondaryODE.computeDerivatives(double t, double[] primary, double[] primaryDot, double[] secondary)	Compute the derivatives related to the secondary state parameters.
double[][]	ODEJacobiansProvider.computeMainStateJacobian(double t, double[] y, double[] yDot)	Compute the Jacobian matrix of ODE with respect to state.
double[]	NamedParameterJacobianProvider.computeParameterJacobian(double t, double[] y, double[] yDot, String paramName)	Compute the Jacobian matrix of ODE with respect to one parameter.
FieldODEStateAndDerivative<T>	FieldODEIntegrator.integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)	Integrate the differential equations up to the given time.
ODEStateAndDerivative	ODEIntegrator.integrate(ExpandableODE equations, ODEState initialState, double finalTime)	Integrate the differential equations up to the given time.
default ODEStateAndDerivative	ODEIntegrator.integrate(OrdinaryDifferentialEquation equations, ODEState initialState, double finalTime)	Integrate the differential equations up to the given time.
protected void	MultistepFieldIntegrator.start(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T t)	Start the integration.
protected void	MultistepIntegrator.start(ExpandableODE equations, ODEState initialState, double finalTime)	Start the integration.

Uses of MathIllegalStateException in org.hipparchus.ode.events

Methods in org.hipparchus.ode.events that throw MathIllegalStateException

Modifier and Type	Method	Description
boolean	DetectorBasedEventState.evaluateStep(ODEStateInterpolator interpolator)	Evaluate the impact of the proposed step on the handler.
boolean	EventState.evaluateStep(ODEStateInterpolator interpolator)	Evaluate the impact of the proposed step on the handler.
boolean	FieldDetectorBasedEventState.evaluateStep(FieldODEStateInterpolator<T> interpolator)	Evaluate the impact of the proposed step on the event handler.
boolean	FieldEventState.evaluateStep(FieldODEStateInterpolator<T> interpolator)	Evaluate the impact of the proposed step on the event handler.
void	DetectorBasedEventState.reinitializeBegin(ODEStateInterpolator interpolator)	Reinitialize the beginning of the step.
void	FieldDetectorBasedEventState.reinitializeBegin(FieldODEStateInterpolator<T> interpolator)	Reinitialize the beginning of the step.

Uses of MathIllegalStateException in org.hipparchus.ode.nonstiff

Methods in org.hipparchus.ode.nonstiff that throw MathIllegalStateException

Modifier and Type	Method	Description
double	AdaptiveStepsizeFieldIntegrator.initializeStep(boolean forward, int order, T[] scale, FieldODEStateAndDerivative<T> state0)	Initialize the integration step.
double	AdaptiveStepsizeIntegrator.initializeStep(boolean forward, int order, double[] scale, ODEStateAndDerivative state0)	Initialize the integration step.
FieldODEStateAndDerivative<T>	AdamsFieldIntegrator.integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)	Integrate the differential equations up to the given time.
ODEStateAndDerivative	AdamsIntegrator.integrate(ExpandableODE equations, ODEState initialState, double finalTime)	Integrate the 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.
ODEStateAndDerivative	EmbeddedRungeKuttaIntegrator.integrate(ExpandableODE equations, ODEState initialState, double finalTime)	Integrate the differential equations up to the given time.
FieldODEStateAndDerivative<T>	FixedStepRungeKuttaFieldIntegrator.integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)	Integrate the differential equations up to the given time.
ODEStateAndDerivative	FixedStepRungeKuttaIntegrator.integrate(ExpandableODE equations, ODEState initialState, double finalTime)	Integrate the differential equations up to the given time.
ODEStateAndDerivative	GraggBulirschStoerIntegrator.integrate(ExpandableODE equations, ODEState initialState, double finalTime)	Integrate the differential equations up to the given time.

Uses of MathIllegalStateException in org.hipparchus.ode.nonstiff.interpolators

Methods in org.hipparchus.ode.nonstiff.interpolators that throw MathIllegalStateException

Modifier and Type	Method	Description
protected FieldODEStateAndDerivative<T>	DormandPrince853FieldStateInterpolator.computeInterpolatedStateAndDerivatives(FieldEquationsMapper<T> mapper, T time, T theta, T thetaH, T oneMinusThetaH)	Compute the state and derivatives at the interpolated time.

Uses of MathIllegalStateException in org.hipparchus.ode.sampling

Methods in org.hipparchus.ode.sampling that throw MathIllegalStateException

Modifier and Type	Method	Description
protected abstract FieldODEStateAndDerivative<T>	AbstractFieldODEStateInterpolator.computeInterpolatedStateAndDerivatives(FieldEquationsMapper<T> equationsMapper, T time, T theta, T thetaH, T oneMinusThetaH)	Compute the state and derivatives at the interpolated time.
protected abstract ODEStateAndDerivative	AbstractODEStateInterpolator.computeInterpolatedStateAndDerivatives(EquationsMapper equationsMapper, double time, double theta, double thetaH, double oneMinusThetaH)	Compute the state and derivatives at the interpolated time.

Uses of MathIllegalStateException in org.hipparchus.optim

Methods in org.hipparchus.optim that throw MathIllegalStateException

Modifier and Type	Method	Description
protected void	BaseOptimizer.incrementEvaluationCount()	Increment the evaluation count.
protected void	BaseOptimizer.incrementIterationCount()	Increment the iteration count.
P	BaseOptimizer.optimize()	Performs the optimization.
P	BaseOptimizer.optimize(OptimizationData... optData)	Stores data and performs the optimization.

Uses of MathIllegalStateException in org.hipparchus.optim.linear

Methods in org.hipparchus.optim.linear that throw MathIllegalStateException

Modifier and Type	Method	Description
protected void	SimplexSolver.doIteration(org.hipparchus.optim.linear.SimplexTableau tableau)	Runs one iteration of the Simplex method on the given model.
PointValuePair	SimplexSolver.doOptimize()	Performs the bulk of the optimization algorithm.
PointValuePair	LinearOptimizer.optimize(OptimizationData... optData)	Stores data and performs the optimization.
PointValuePair	SimplexSolver.optimize(OptimizationData... optData)	Stores data and performs the optimization.
protected void	SimplexSolver.solvePhase1(org.hipparchus.optim.linear.SimplexTableau tableau)	Solves Phase 1 of the Simplex method.

Uses of MathIllegalStateException in org.hipparchus.optim.nonlinear.scalar

Methods in org.hipparchus.optim.nonlinear.scalar that throw MathIllegalStateException

Modifier and Type	Method	Description
PointValuePair	GradientMultivariateOptimizer.optimize(OptimizationData... optData)	Stores data and performs the optimization.
PointValuePair	MultivariateOptimizer.optimize(OptimizationData... optData)	Stores data and performs the optimization.

Uses of MathIllegalStateException in org.hipparchus.optim.nonlinear.scalar.gradient

Methods in org.hipparchus.optim.nonlinear.scalar.gradient that throw MathIllegalStateException

Modifier and Type	Method	Description
PointValuePair	NonLinearConjugateGradientOptimizer.optimize(OptimizationData... optData)	Stores data and performs the optimization.

Uses of MathIllegalStateException in org.hipparchus.optim.nonlinear.scalar.noderiv

Methods in org.hipparchus.optim.nonlinear.scalar.noderiv that throw MathIllegalStateException

Modifier and Type	Method	Description
PointValuePair	CMAESOptimizer.optimize(OptimizationData... optData)	Stores data and performs the optimization.

Uses of MathIllegalStateException in org.hipparchus.optim.nonlinear.vector.constrained

Methods in org.hipparchus.optim.nonlinear.vector.constrained that throw MathIllegalStateException

Modifier and Type	Method	Description
LagrangeSolution	ConstraintOptimizer.optimize(OptimizationData... optData)	Stores data and performs the optimization.

Uses of MathIllegalStateException in org.hipparchus.optim.univariate

Methods in org.hipparchus.optim.univariate that throw MathIllegalStateException

Modifier and Type	Method	Description
UnivariatePointValuePair	UnivariateOptimizer.optimize(OptimizationData... optData)	Stores data and performs the optimization.

Uses of MathIllegalStateException in org.hipparchus.random

Constructors in org.hipparchus.random that throw MathIllegalStateException

Constructor	Description
SobolSequenceGenerator(int dimension, InputStream is)	Construct a new Sobol sequence generator for the given space dimension with direction vectors loaded from the given stream.

Uses of MathIllegalStateException in org.hipparchus.special

Methods in org.hipparchus.special that throw MathIllegalStateException

Modifier and Type	Method	Description
double	BesselJ.value(double x)	Returns the value of the constructed Bessel function of the first kind, for the passed argument.
static double	BesselJ.value(double order, double x)	Returns the first Bessel function, \(J_{order}(x)\).

Uses of MathIllegalStateException in org.hipparchus.stat.descriptive

Methods in org.hipparchus.stat.descriptive that throw MathIllegalStateException

Modifier and Type	Method	Description
void	DescriptiveStatistics.removeMostRecentValue()	Removes the most recent value from the dataset.
double	DescriptiveStatistics.replaceMostRecentValue(double v)	Replaces the most recently stored value with the given value.

Uses of MathIllegalStateException in org.hipparchus.stat.fitting

Methods in org.hipparchus.stat.fitting that throw MathIllegalStateException

Modifier and Type	Method	Description
double	EmpiricalDistribution.getNextValue()	Generates a random value from this distribution.

Uses of MathIllegalStateException in org.hipparchus.stat.inference

Methods in org.hipparchus.stat.inference that throw MathIllegalStateException

Modifier and Type	Method	Description
double	OneWayAnova.anovaPValue(Collection<double[]> categoryData)	Computes the ANOVA P-value for a collection of double[] arrays.
double	OneWayAnova.anovaPValue(Collection<StreamingStatistics> categoryData, boolean allowOneElementData)	Computes the ANOVA P-value for a collection of StreamingStatistics.
boolean	OneWayAnova.anovaTest(Collection<double[]> categoryData, double alpha)	Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.
double	ChiSquareTest.chiSquareTest(double[] expected, long[] observed)	Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the observed frequency counts to those in the expected array.
boolean	ChiSquareTest.chiSquareTest(double[] expected, long[] observed, double alpha)	Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha.
double	ChiSquareTest.chiSquareTest(long[][] counts)	Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input counts array, viewed as a two-way table.
boolean	ChiSquareTest.chiSquareTest(long[][] counts, double alpha)	Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level alpha.
static double	InferenceTestUtils.chiSquareTest(double[] expected, long[] observed)	Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the observed frequency counts to those in the expected array.
static boolean	InferenceTestUtils.chiSquareTest(double[] expected, long[] observed, double alpha)	Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha.
static double	InferenceTestUtils.chiSquareTest(long[][] counts)	Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input counts array, viewed as a two-way table.
static boolean	InferenceTestUtils.chiSquareTest(long[][] counts, double alpha)	Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level alpha.
double	ChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)	Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts in observed1 and observed2.
boolean	ChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)	Performs a Chi-Square two sample test comparing two binned data sets.
static double	InferenceTestUtils.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)	Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts in observed1 and observed2.
static boolean	InferenceTestUtils.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)	Performs a Chi-Square two sample test comparing two binned data sets.
double	GTest.gTest(double[] expected, long[] observed)	Returns the observed significance level, or p-value, associated with a G-Test for goodness of fit comparing the observed frequency counts to those in the expected array.
boolean	GTest.gTest(double[] expected, long[] observed, double alpha)	Performs a G-Test (Log-Likelihood Ratio Test) for goodness of fit evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha.
static double	InferenceTestUtils.gTest(double[] expected, long[] observed)	Returns the observed significance level, or p-value, associated with a G-Test for goodness of fit comparing the observed frequency counts to those in the expected array.
static boolean	InferenceTestUtils.gTest(double[] expected, long[] observed, double alpha)	Performs a G-Test (Log-Likelihood Ratio Test) for goodness of fit evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha.
double	GTest.gTestDataSetsComparison(long[] observed1, long[] observed2)	Returns the observed significance level, or p-value, associated with a G-Value (Log-Likelihood Ratio) for two sample test comparing bin frequency counts in observed1 and observed2.
boolean	GTest.gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)	Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets.
static double	InferenceTestUtils.gTestDataSetsComparison(long[] observed1, long[] observed2)	Returns the observed significance level, or p-value, associated with a G-Value (Log-Likelihood Ratio) for two sample test comparing bin frequency counts in observed1 and observed2.
static boolean	InferenceTestUtils.gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)	Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets.
double	GTest.gTestIntrinsic(double[] expected, long[] observed)	Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described in p64-69 of McDonald, J.H. 2009.
static double	InferenceTestUtils.gTestIntrinsic(double[] expected, long[] observed)	Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described in p64-69 of McDonald, J.H. 2009.
static double	InferenceTestUtils.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.
static boolean	InferenceTestUtils.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.
static double	InferenceTestUtils.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.
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.
protected double	TTest.homoscedasticTTest(double m1, double m2, double v1, double v2, double n1, double n2)	Computes p-value for 2-sided, 2-sample t-test, under the assumption of equal subpopulation variances.
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	InferenceTestUtils.oneWayAnovaPValue(Collection<double[]> categoryData)	Computes the ANOVA P-value for a collection of double[] arrays.
static boolean	InferenceTestUtils.oneWayAnovaTest(Collection<double[]> categoryData, double alpha)	Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.
static double	InferenceTestUtils.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.
static boolean	InferenceTestUtils.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.
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	InferenceTestUtils.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.
static boolean	InferenceTestUtils.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.
static double	InferenceTestUtils.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.
static boolean	InferenceTestUtils.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.
static double	InferenceTestUtils.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.
static boolean	InferenceTestUtils.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.
static double	InferenceTestUtils.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.
static boolean	InferenceTestUtils.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.
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.
protected double	TTest.tTest(double m, double mu, double v, double n)	Computes p-value for 2-sided, 1-sample t-test.
protected double	TTest.tTest(double m1, double m2, double v1, double v2, double n1, double n2)	Computes p-value for 2-sided, 2-sample t-test.
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.
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 MathIllegalStateException in org.hipparchus.util

Methods in org.hipparchus.util that throw MathIllegalStateException

Modifier and Type	Method	Description
double	ContinuedFraction.evaluate(double x)	Evaluates the continued fraction at the value x.
double	ContinuedFraction.evaluate(double x, double epsilon)	Evaluates the continued fraction at the value x.
double	ContinuedFraction.evaluate(double x, double epsilon, int maxIterations)	Evaluates the continued fraction at the value x.
double	ContinuedFraction.evaluate(double x, int maxIterations)	Evaluates the continued fraction at the value x.
<T extends CalculusFieldElement<T>> T	FieldContinuedFraction.evaluate(T x)	Evaluates the continued fraction at the value x.
<T extends CalculusFieldElement<T>> T	FieldContinuedFraction.evaluate(T x, double epsilon)	Evaluates the continued fraction at the value x.
<T extends CalculusFieldElement<T>> T	FieldContinuedFraction.evaluate(T x, double epsilon, int maxIterations)	Evaluates the continued fraction at the value x.
<T extends CalculusFieldElement<T>> T	FieldContinuedFraction.evaluate(T x, int maxIterations)	Evaluates the continued fraction at the value x.
void	IterationManager.incrementIterationCount()	Increments the iteration count by one, and throws an exception if the maximum number of iterations is reached.
double	ResizableDoubleArray.substituteMostRecentElement(double value)	Substitutes value for the most recently added value.
void	Incrementor.MaxCountExceededCallback.trigger(int maximalCount)	Function called when the maximal count has been reached.