Uses of Class
org.hipparchus.exception.MathIllegalStateException
Package
Description
Numerical integration (quadrature) algorithms for univariate real functions.
Root finding algorithms, for univariate real functions.
Clustering algorithms.
Complex number type and implementations of complex transcendental
functions.
Fraction number type and fraction number formatting.
This package is the top level package for geometry.
This package provides basic 1D geometry components.
This package provides basic 3D geometry components.
This package provides basic 2D geometry components.
This package provides algorithms to generate the convex hull
for a set of points in an two-dimensional euclidean space.
This package provides interfaces and classes related to the convex hull problem.
This package provides basic geometry components on the 2-sphere.
Linear algebra support.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides classes to solve Ordinary Differential Equations problems.
Events
This package provides classes to solve non-stiff Ordinary Differential Equations problems.
This package provides classes to handle sampling steps during
Ordinary Differential Equations integration.
Generally, optimizers are algorithms that will either
minimize
or
maximize
a scalar function, called the
objective
function
.Optimization algorithms for linear constrained problems.
Algorithms for optimizing a scalar function.
This package provides optimization algorithms that require derivatives.
This package provides optimization algorithms that do not require derivatives.
This package provides algorithms that minimize the residuals
between observations and model values.
One-dimensional optimization algorithms.
Random number and random data generators.
Implementations of special functions such as Beta and Gamma.
Generic univariate and multivariate summary statistic objects.
Statistical methods for fitting distributions.
Classes providing hypothesis testing.
Convenience routines and common data structures used throughout the Hipparchus library.
-
Uses of MathIllegalStateException in org.hipparchus.analysis.integration
Modifier and TypeMethodDescriptionprotected 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.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.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
Modifier and TypeMethodDescriptionprotected 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 final 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 final double
SecantSolver.doSolve()
Method for implementing actual optimization algorithms in derived classes.protected final BracketedUnivariateSolver.Interval
BaseSecantSolver.doSolveInterval()
Find a root and return the containing interval.protected void
BaseAbstractUnivariateSolver.incrementEvaluationCount()
Increment the evaluation count by one.double
Solve for a zero in the vicinity ofstartValue
.double
Solve for a zero in the given interval, start atstartValue
.double
Solve for a zero root in the given interval.double
Solve for a zero in the given interval, start atstartValue
.double
BracketingNthOrderBrentSolver.solve
(int maxEval, UnivariateFunction f, double min, double max, double startValue, AllowedSolution allowedSolution) Solve for a zero in the given interval, start atstartValue
.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 ofmin
andmax
.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.LaguerreSolver.solveComplex
(double[] coefficients, double initial) Find a complex root for the polynomial with the given coefficients, starting from the given initial value.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.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.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.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.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.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.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
Modifier and TypeMethodDescriptionClusterer.cluster
(Collection<T> points) Perform a cluster analysis on the given set ofClusterable
instances.KMeansPlusPlusClusterer.cluster
(Collection<T> points) Runs the K-means++ clustering algorithm.MultiKMeansPlusPlusClusterer.cluster
(Collection<T> points) Runs the K-means++ clustering algorithm. -
Uses of MathIllegalStateException in org.hipparchus.complex
Modifier and TypeMethodDescriptiondouble
RootsOfUnity.getImaginary
(int k) Get the imaginary part of thek
-thn
-th root of unity.double
RootsOfUnity.getReal
(int k) Get the real part of thek
-thn
-th root of unity.boolean
RootsOfUnity.isCounterClockWise()
Parses a string to produce aComplex
object. -
Uses of MathIllegalStateException in org.hipparchus.fraction
Modifier and TypeMethodDescriptionFractionFormat.format
(Object obj, StringBuffer toAppendTo, FieldPosition pos) Formats an object and appends the result to a StringBuffer.Parses a string to produce aBigFraction
object.Parses a string to produce aFraction
object.ModifierConstructorDescriptionBigFraction
(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
-
Uses of MathIllegalStateException in org.hipparchus.geometry.euclidean.oned
-
Uses of MathIllegalStateException in org.hipparchus.geometry.euclidean.threed
-
Uses of MathIllegalStateException in org.hipparchus.geometry.euclidean.twod
-
Uses of MathIllegalStateException in org.hipparchus.geometry.euclidean.twod.hull
Modifier and TypeMethodDescriptionConvexHullGenerator2D.generate
(Collection<Vector2D> points) Builds the convex hull from the set of input points. -
Uses of MathIllegalStateException in org.hipparchus.geometry.hull
Modifier and TypeMethodDescriptionConvexHull<S,
P> ConvexHullGenerator.generate
(Collection<P> points) Builds the convex hull from the set of input points. -
Uses of MathIllegalStateException in org.hipparchus.geometry.spherical.twod
Modifier and TypeMethodDescriptionprotected void
SphericalPolygonsSet.computeGeometricalProperties()
Compute some geometrical properties.SphericalPolygonsSet.getBoundaryLoops()
Get the boundary loops of the polygon. -
Uses of MathIllegalStateException in org.hipparchus.linear
Modifier and TypeMethodDescriptionIterativeLinearSolver.solve
(RealLinearOperator a, RealVector b) Returns an estimate of the solution to the linear system A · x = b.IterativeLinearSolver.solve
(RealLinearOperator a, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.PreconditionedIterativeLinearSolver.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b) Returns an estimate of the solution to the linear system A · x = b.PreconditionedIterativeLinearSolver.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.PreconditionedIterativeLinearSolver.solve
(RealLinearOperator a, RealVector b) Returns an estimate of the solution to the linear system A · x = b.PreconditionedIterativeLinearSolver.solve
(RealLinearOperator a, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b) Returns an estimate of the solution to the linear system A · x = b.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.SymmLQ.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealVector b) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealVector b, boolean goodb, double shift) Returns the solution to the system (A - shift · I) · x = b.SymmLQ.solve
(RealLinearOperator a, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.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.PreconditionedIterativeLinearSolver.solveInPlace
(RealLinearOperator a, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solveInPlace
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.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.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.migration.exception
Modifier and TypeClassDescriptionclass
Deprecated.class
Deprecated.as of 1.0, this exception is replaced byMathIllegalStateException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalStateException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalStateException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
-
Uses of MathIllegalStateException in org.hipparchus.migration.geometry.euclidean
Modifier and TypeClassDescriptionclass
Deprecated.as of 1.0, this exception is replaced byMathIllegalStateException
-
Uses of MathIllegalStateException in org.hipparchus.migration.ode
Modifier and TypeMethodDescriptionvoid
FirstOrderDifferentialEquations.computeDerivatives
(double t, double[] y, double[] yDot) Deprecated.Get the current time derivative of the state vector.default double[]
SecondaryEquations.computeDerivatives
(double t, double[] primary, double[] primaryDot, double[] secondary) Deprecated.Compute the derivatives related to the secondary state parameters.void
SecondaryEquations.computeDerivatives
(double t, double[] primary, double[] primaryDot, double[] secondary, double[] secondaryDot) Deprecated.Compute the derivatives related to the secondary state parameters.double[][]
MainStateJacobianProvider.computeMainStateJacobian
(double t, double[] y, double[] yDot) Deprecated.Compute the jacobian matrix of ODE with respect to main state.default double[]
ParameterJacobianProvider.computeParameterJacobian
(double t, double[] y, double[] yDot, String paramName) Deprecated.Compute the Jacobian matrix of ODE with respect to one parameter.void
ParameterJacobianProvider.computeParameterJacobian
(double t, double[] y, double[] yDot, String paramName, double[] dFdP) Deprecated.Compute the Jacobian matrix of ODE with respect to one parameter.double[]
ContinuousOutputModel.getInterpolatedDerivatives()
Deprecated.Get the derivatives of the state vector of the interpolated point.double[]
ContinuousOutputModel.getInterpolatedSecondaryDerivatives
(int secondaryStateIndex) Deprecated.Get the interpolated secondary derivatives corresponding to the secondary equations.double[]
ContinuousOutputModel.getInterpolatedSecondaryState
(int secondaryStateIndex) Deprecated.Get the interpolated secondary state corresponding to the secondary equations.double[]
ContinuousOutputModel.getInterpolatedState()
Deprecated.Get the state vector of the interpolated point. -
Uses of MathIllegalStateException in org.hipparchus.migration.ode.sampling
Modifier and TypeMethodDescriptionStepInterpolator.copy()
Deprecated.Copy the instance.double[]
StepInterpolator.getInterpolatedDerivatives()
Deprecated.as of 1.0, replaced withODEStateInterpolator.getInterpolatedState(double)
.ODEStateAndDerivative.getPrimaryDerivative()
double[]
StepInterpolator.getInterpolatedSecondaryDerivatives
(int index) Deprecated.as of 1.0, replaced withODEStateInterpolator.getInterpolatedState(double)
.ODEStateAndDerivative.getSecondaryDerivative(int)
double[]
StepInterpolator.getInterpolatedSecondaryState
(int index) Deprecated.as of 1.0, replaced withODEStateInterpolator.getInterpolatedState(double)
.ODEState.getSecondaryState(int)
double[]
StepInterpolator.getInterpolatedState()
Deprecated.as of 1.0, replaced withODEStateInterpolator.getInterpolatedState(double)
.ODEState.getPrimaryState()
void
StepHandler.handleStep
(org.hipparchus.migration.ode.sampling.MigrationStepInterpolator interpolator, boolean isLast) Deprecated.Handle the last accepted stepdefault void
StepHandler.handleStep
(ODEStateInterpolator interpolator) Deprecated.Handle the last accepted step. -
Uses of MathIllegalStateException in org.hipparchus.migration.optim.linear
Modifier and TypeClassDescriptionclass
Deprecated.as of 1.0, this exception is replaced byMathIllegalStateException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalStateException
-
Uses of MathIllegalStateException in org.hipparchus.ode
Modifier and TypeMethodDescriptionprotected 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.FieldODEIntegrator.integrate
(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.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
Modifier and TypeMethodDescriptionboolean
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
Modifier and TypeMethodDescriptiondouble
AdaptiveStepsizeFieldIntegrator.initializeStep
(boolean forward, int order, T[] scale, FieldODEStateAndDerivative<T> state0, FieldEquationsMapper<T> mapper) Initialize the integration step.double
AdaptiveStepsizeIntegrator.initializeStep
(boolean forward, int order, double[] scale, ODEStateAndDerivative state0) Initialize the integration step.AdamsFieldIntegrator.integrate
(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.AdamsIntegrator.integrate
(ExpandableODE equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time.EmbeddedRungeKuttaFieldIntegrator.integrate
(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.EmbeddedRungeKuttaIntegrator.integrate
(ExpandableODE equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time.GraggBulirschStoerIntegrator.integrate
(ExpandableODE equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time.RungeKuttaFieldIntegrator.integrate
(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.RungeKuttaIntegrator.integrate
(ExpandableODE equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time. -
Uses of MathIllegalStateException in org.hipparchus.ode.sampling
Modifier and TypeMethodDescriptionprotected 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
Modifier and TypeMethodDescriptionprotected void
BaseOptimizer.incrementEvaluationCount()
Increment the evaluation count.protected void
BaseOptimizer.incrementIterationCount()
Increment the iteration count.BaseOptimizer.optimize()
Performs the optimization.BaseOptimizer.optimize
(OptimizationData... optData) Stores data and performs the optimization. -
Uses of MathIllegalStateException in org.hipparchus.optim.linear
Modifier and TypeMethodDescriptionprotected void
SimplexSolver.doIteration
(org.hipparchus.optim.linear.SimplexTableau tableau) Runs one iteration of the Simplex method on the given model.SimplexSolver.doOptimize()
Performs the bulk of the optimization algorithm.LinearOptimizer.optimize
(OptimizationData... optData) Stores data and performs the optimization.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
Modifier and TypeMethodDescriptionGradientMultivariateOptimizer.optimize
(OptimizationData... optData) Stores data and performs the optimization.MultivariateOptimizer.optimize
(OptimizationData... optData) Stores data and performs the optimization. -
Uses of MathIllegalStateException in org.hipparchus.optim.nonlinear.scalar.gradient
Modifier and TypeMethodDescriptionNonLinearConjugateGradientOptimizer.optimize
(OptimizationData... optData) Stores data and performs the optimization. -
Uses of MathIllegalStateException in org.hipparchus.optim.nonlinear.scalar.noderiv
Modifier and TypeMethodDescriptionCMAESOptimizer.optimize
(OptimizationData... optData) Stores data and performs the optimization. -
Uses of MathIllegalStateException in org.hipparchus.optim.nonlinear.vector.constrained
Modifier and TypeMethodDescriptionConstraintOptimizer.optimize
(OptimizationData... optData) Stores data and performs the optimization. -
Uses of MathIllegalStateException in org.hipparchus.optim.univariate
Modifier and TypeMethodDescriptionUnivariateOptimizer.optimize
(OptimizationData... optData) Stores data and performs the optimization. -
Uses of MathIllegalStateException in org.hipparchus.random
ModifierConstructorDescriptionSobolSequenceGenerator
(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
-
Uses of MathIllegalStateException in org.hipparchus.stat.descriptive
Modifier and TypeMethodDescriptionvoid
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
Modifier and TypeMethodDescriptiondouble
EmpiricalDistribution.getNextValue()
Generates a random value from this distribution. -
Uses of MathIllegalStateException in org.hipparchus.stat.inference
Modifier and TypeMethodDescriptiondouble
OneWayAnova.anovaPValue
(Collection<double[]> categoryData) Computes the ANOVA P-value for a collection ofdouble[]
arrays.double
OneWayAnova.anovaPValue
(Collection<StreamingStatistics> categoryData, boolean allowOneElementData) Computes the ANOVA P-value for a collection ofStreamingStatistics
.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 theobserved
frequency counts to those in theexpected
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 levelalpha
.double
ChiSquareTest.chiSquareTest
(long[][] counts) Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the inputcounts
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 levelalpha
.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 theobserved
frequency counts to those in theexpected
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 levelalpha
.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 inputcounts
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 levelalpha
.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 inobserved1
andobserved2
.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 inobserved1
andobserved2
.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 theobserved
frequency counts to those in theexpected
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 levelalpha
.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 theobserved
frequency counts to those in theexpected
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 levelalpha
.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 inobserved1
andobserved2
.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 inobserved1
andobserved2
.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.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.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 thatsample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
, 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 thatsample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
, 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 ofdouble[]
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 betweensample1
andsample2
is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance levelalpha
.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 betweensample1
andsample2
is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance levelalpha
.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 thatsample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
.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 constantmu
.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 whichsample
is drawn equalsmu
.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 bysampleStats
with the constantmu
.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 bystats
is drawn equalsmu
.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 thatsampleStats1
andsampleStats2
describe datasets drawn from populations with the same mean, with significance levelalpha
.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 thatsample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
.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 constantmu
.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 whichsample
is drawn equalsmu
.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 bysampleStats
with the constantmu
.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 bystats
is drawn equalsmu
.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 thatsampleStats1
andsampleStats2
describe datasets drawn from populations with the same mean, with significance levelalpha
.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
Modifier and TypeMethodDescriptiondouble
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>>
TFieldContinuedFraction.evaluate
(T x) Evaluates the continued fraction at the value x.<T extends CalculusFieldElement<T>>
TFieldContinuedFraction.evaluate
(T x, double epsilon) Evaluates the continued fraction at the value x.<T extends CalculusFieldElement<T>>
TFieldContinuedFraction.evaluate
(T x, double epsilon, int maxIterations) Evaluates the continued fraction at the value x.<T extends CalculusFieldElement<T>>
TFieldContinuedFraction.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) Substitutesvalue
for the most recently added value.void
Incrementor.MaxCountExceededCallback.trigger
(int maximalCount) Function called when the maximal count has been reached.
MathIllegalStateException