| 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.twod | 
 
 This package provides basic geometry components on the 2-sphere. 
 | 
| org.hipparchus.linear | 
 Linear algebra support. 
 | 
| org.hipparchus.migration.exception | 
 
 This package provides migration classes from Apache Commons Math to Hipparchus. 
 | 
| org.hipparchus.migration.geometry.euclidean | 
 
 This package provides migration classes from Apache Commons Math to Hipparchus. 
 | 
| org.hipparchus.migration.ode | 
 
 This package provides migration classes from Apache Commons Math to Hipparchus. 
 | 
| org.hipparchus.migration.ode.sampling | 
 
 This package provides migration classes from Apache Commons Math to Hipparchus. 
 | 
| org.hipparchus.migration.optim.linear | 
 
 This package provides migration classes from Apache Commons Math to Hipparchus. 
 | 
| 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.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.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. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected double | 
BaseAbstractUnivariateIntegrator.computeObjectiveValue(double point)
Compute the objective function value. 
 | 
protected T | 
BaseAbstractFieldUnivariateIntegrator.computeObjectiveValue(T point)
Compute the objective function value. 
 | 
protected double | 
IterativeLegendreGaussIntegrator.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 | 
IterativeLegendreFieldGaussIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
 classes. 
 | 
protected abstract T | 
BaseAbstractFieldUnivariateIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
 classes. 
 | 
protected T | 
FieldTrapezoidIntegrator.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 | 
MidPointIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
 classes. 
 | 
protected double | 
SimpsonIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
 classes. 
 | 
protected T | 
FieldSimpsonIntegrator.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 double | 
TrapezoidIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
 classes. 
 | 
T | 
FieldUnivariateIntegrator.integrate(int maxEval,
         CalculusFieldUnivariateFunction<T> f,
         T min,
         T max)
Integrate the function in the given interval. 
 | 
T | 
BaseAbstractFieldUnivariateIntegrator.integrate(int maxEval,
         CalculusFieldUnivariateFunction<T> f,
         T lower,
         T upper)
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. 
 | 
double | 
BaseAbstractUnivariateIntegrator.integrate(int maxEval,
         UnivariateFunction f,
         double lower,
         double upper)
Integrate the function in the given interval. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected double | 
BaseAbstractUnivariateSolver.computeObjectiveValue(double point)
Compute the objective function value. 
 | 
protected DerivativeStructure | 
AbstractUnivariateDifferentiableSolver.computeObjectiveValueAndDerivative(double point)
Compute the objective function value. 
 | 
protected double | 
NewtonRaphsonSolver.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. 
 | 
protected double | 
MullerSolver.doSolve()
Method for implementing actual optimization algorithms in derived
 classes. 
 | 
protected double | 
BrentSolver.doSolve()
Method for implementing actual optimization algorithms in derived
 classes. 
 | 
protected abstract double | 
BaseAbstractUnivariateSolver.doSolve()
Method for implementing actual optimization algorithms in derived
 classes. 
 | 
protected double | 
SecantSolver.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 | 
RiddersSolver.doSolve()
Method for implementing actual optimization algorithms in derived
 classes. 
 | 
protected double | 
BisectionSolver.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 | 
BaseUnivariateSolver.solve(int maxEval,
     F f,
     double min,
     double max)
Solve for a zero root in the given interval. 
 | 
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,
     double startValue)
Solve for a zero in the given interval, start at  
startValue. | 
double | 
NewtonRaphsonSolver.solve(int maxEval,
     UnivariateDifferentiableFunction f,
     double min,
     double max)
Find a zero near the midpoint of  
min and max. | 
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. | 
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.solveComplex(double[] coefficients,
            double initial)
Find a complex root for the polynomial with the given coefficients,
 starting from the given initial value. 
 | 
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. 
 | 
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. 
 | 
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. 
 | 
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. 
 | 
| Modifier and Type | Method and 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>> | 
MultiKMeansPlusPlusClusterer.cluster(Collection<T> points)
Runs the K-means++ clustering algorithm. 
 | 
List<CentroidCluster<T>> | 
KMeansPlusPlusClusterer.cluster(Collection<T> points)
Runs the K-means++ clustering algorithm. 
 | 
| Modifier and Type | Method and 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()
 | 
Complex | 
ComplexFormat.parse(String source)
Parses a string to produce a  
Complex object. | 
| Modifier and Type | Method and 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. | 
| Constructor and 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. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
abstract Vector<S> | 
VectorFormat.parse(String source)
Parses a string to produce a  
Vector object. | 
| Modifier and Type | Method and Description | 
|---|---|
Vector1D | 
Vector1DFormat.parse(String source)
Parses a string to produce a  
Vector object. | 
| Modifier and Type | Method and Description | 
|---|---|
double[] | 
Rotation.getAngles(RotationOrder order,
         RotationConvention convention)
Get the Cardan or Euler angles corresponding to the instance. 
 | 
T[] | 
FieldRotation.getAngles(RotationOrder order,
         RotationConvention convention)
Get the Cardan or Euler angles corresponding to the instance. 
 | 
Vector3D | 
Vector3DFormat.parse(String source)
Parses a string to produce a  
Vector3D object. | 
| Modifier and Type | Method and Description | 
|---|---|
Vector2D | 
Vector2DFormat.parse(String source)
Parses a string to produce a  
Vector object. | 
| Modifier and Type | Method and Description | 
|---|---|
ConvexHull2D | 
ConvexHullGenerator2D.generate(Collection<Vector2D> points)
Builds the convex hull from the set of input points. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
ConvexHull<S,P> | 
ConvexHullGenerator.generate(Collection<P> points)
Builds the convex hull from the set of input points. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected void | 
SphericalPolygonsSet.computeGeometricalProperties()
Compute some geometrical properties. 
 | 
List<Vertex> | 
SphericalPolygonsSet.getBoundaryLoops()
Get the boundary loops of the polygon. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
RealVector | 
SymmLQ.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)
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 | 
PreconditionedIterativeLinearSolver.solve(RealLinearOperator a,
     RealLinearOperator m,
     RealVector b,
     RealVector x0)
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 | 
IterativeLinearSolver.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)
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 | 
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,
     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. 
 | 
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 | 
ConjugateGradient.solveInPlace(RealLinearOperator a,
            RealLinearOperator m,
            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,
            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. 
 | 
abstract RealVector | 
IterativeLinearSolver.solveInPlace(RealLinearOperator a,
            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. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
ConvergenceException
Deprecated. 
 
as of 1.0, this exception is replaced by  
MathIllegalStateException | 
class  | 
MathInternalError
Deprecated. 
 
as of 1.0, this exception is replaced by  
MathIllegalStateException | 
class  | 
MathParseException
Deprecated. 
 
as of 1.0, this exception is replaced by  
MathIllegalStateException | 
class  | 
MaxCountExceededException
Deprecated. 
 
as of 1.0, this exception is replaced by  
MathIllegalStateException | 
class  | 
TooManyEvaluationsException
Deprecated. 
 
as of 1.0, this exception is replaced by  
MathIllegalArgumentException | 
class  | 
TooManyIterationsException
Deprecated. 
 
as of 1.0, this exception is replaced by  
MathIllegalArgumentException | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
CardanEulerSingularityException
Deprecated. 
 
as of 1.0, this exception is replaced by  
MathIllegalStateException | 
| Modifier and Type | Method and Description | 
|---|---|
void | 
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. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
StepInterpolator | 
StepInterpolator.copy()
Deprecated.  
Copy the instance. 
 | 
double[] | 
StepInterpolator.getInterpolatedDerivatives()
Deprecated. 
 
as of 1.0, replaced with  
ODEStateInterpolator.getInterpolatedState(double).ODEStateAndDerivative.getPrimaryDerivative() | 
double[] | 
StepInterpolator.getInterpolatedSecondaryDerivatives(int index)
Deprecated. 
 
as of 1.0, replaced with  
ODEStateInterpolator.getInterpolatedState(double).ODEStateAndDerivative.getSecondaryDerivative(int) | 
double[] | 
StepInterpolator.getInterpolatedSecondaryState(int index)
Deprecated. 
 
as of 1.0, replaced with  
ODEStateInterpolator.getInterpolatedState(double).ODEState.getSecondaryState(int) | 
double[] | 
StepInterpolator.getInterpolatedState()
Deprecated. 
 
as of 1.0, replaced with  
ODEStateInterpolator.getInterpolatedState(double).ODEState.getPrimaryState() | 
void | 
StepHandler.handleStep(org.hipparchus.migration.ode.sampling.MigrationStepInterpolator interpolator,
          boolean isLast)
Deprecated.  
Handle the last accepted step 
 | 
default void | 
StepHandler.handleStep(ODEStateInterpolator interpolator)
Deprecated.  
Handle the last accepted step. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
NoFeasibleSolutionException
Deprecated. 
 
as of 1.0, this exception is replaced by  
MathIllegalStateException | 
class  | 
UnboundedSolutionException
Deprecated. 
 
as of 1.0, this exception is replaced by  
MathIllegalStateException | 
| Modifier and Type | Method and 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. 
 | 
Complex[] | 
ComplexSecondaryODE.computeDerivatives(double t,
                  Complex[] primary,
                  Complex[] primaryDot,
                  Complex[] secondary)
Compute the derivatives related to the secondary state parameters. 
 | 
double[] | 
AbstractIntegrator.computeDerivatives(double t,
                  double[] y)
Compute the derivatives and check the number of evaluations. 
 | 
double[] | 
ExpandableODE.computeDerivatives(double t,
                  double[] y)
Get the current time derivative of the complete state vector. 
 | 
double[] | 
SecondaryODE.computeDerivatives(double t,
                  double[] primary,
                  double[] primaryDot,
                  double[] secondary)
Compute the derivatives related to the secondary state parameters. 
 | 
T[] | 
AbstractFieldIntegrator.computeDerivatives(T t,
                  T[] y)
Compute the derivatives and check the number of evaluations. 
 | 
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[][] | 
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. 
 | 
ODEStateAndDerivative | 
ODEIntegrator.integrate(ExpandableODE equations,
         ODEState initialState,
         double finalTime)
Integrate the differential equations up to the given time. 
 | 
FieldODEStateAndDerivative<T> | 
FieldODEIntegrator.integrate(FieldExpandableODE<T> equations,
         FieldODEState<T> initialState,
         T 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 | 
MultistepIntegrator.start(ExpandableODE equations,
     ODEState initialState,
     double finalTime)
Start the integration. 
 | 
protected void | 
MultistepFieldIntegrator.start(FieldExpandableODE<T> equations,
     FieldODEState<T> initialState,
     T t)
Start the integration. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
boolean | 
FieldEventState.evaluateStep(FieldODEStateInterpolator<T> interpolator)
Evaluate the impact of the proposed step on the event handler. 
 | 
boolean | 
EventState.evaluateStep(ODEStateInterpolator interpolator)
Evaluate the impact of the proposed step on the event handler. 
 | 
void | 
FieldEventState.reinitializeBegin(FieldODEStateInterpolator<T> interpolator)
Reinitialize the beginning of the step. 
 | 
void | 
EventState.reinitializeBegin(ODEStateInterpolator interpolator)
Reinitialize the beginning of the step. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
double | 
AdaptiveStepsizeIntegrator.initializeStep(boolean forward,
              int order,
              double[] scale,
              ODEStateAndDerivative state0,
              EquationsMapper mapper)
Initialize the integration step. 
 | 
double | 
AdaptiveStepsizeFieldIntegrator.initializeStep(boolean forward,
              int order,
              T[] scale,
              FieldODEStateAndDerivative<T> state0,
              FieldEquationsMapper<T> mapper)
Initialize the integration step. 
 | 
ODEStateAndDerivative | 
EmbeddedRungeKuttaIntegrator.integrate(ExpandableODE equations,
         ODEState initialState,
         double 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. 
 | 
ODEStateAndDerivative | 
RungeKuttaIntegrator.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. 
 | 
FieldODEStateAndDerivative<T> | 
EmbeddedRungeKuttaFieldIntegrator.integrate(FieldExpandableODE<T> equations,
         FieldODEState<T> initialState,
         T finalTime)
Integrate the differential equations up to the given time. 
 | 
FieldODEStateAndDerivative<T> | 
AdamsFieldIntegrator.integrate(FieldExpandableODE<T> equations,
         FieldODEState<T> initialState,
         T finalTime)
Integrate the differential equations up to the given time. 
 | 
FieldODEStateAndDerivative<T> | 
RungeKuttaFieldIntegrator.integrate(FieldExpandableODE<T> equations,
         FieldODEState<T> initialState,
         T finalTime)
Integrate the differential equations up to the given time. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected abstract ODEStateAndDerivative | 
AbstractODEStateInterpolator.computeInterpolatedStateAndDerivatives(EquationsMapper equationsMapper,
                                      double time,
                                      double theta,
                                      double thetaH,
                                      double oneMinusThetaH)
Compute the state and derivatives at the interpolated time. 
 | 
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. 
 | 
| Modifier and Type | Method and 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. 
 | 
| Modifier and Type | Method and 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. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
PointValuePair | 
MultivariateOptimizer.optimize(OptimizationData... optData)
Stores data and performs the optimization. 
 | 
PointValuePair | 
GradientMultivariateOptimizer.optimize(OptimizationData... optData)
Stores data and performs the optimization. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
PointValuePair | 
NonLinearConjugateGradientOptimizer.optimize(OptimizationData... optData)
Stores data and performs the optimization. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
PointValuePair | 
CMAESOptimizer.optimize(OptimizationData... optData)
Stores data and performs the optimization. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
UnivariatePointValuePair | 
UnivariateOptimizer.optimize(OptimizationData... optData)
Stores data and performs the optimization. 
 | 
| Constructor and 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. 
 | 
| Modifier and Type | Method and 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, \(J_{order}(x)\). 
 | 
| Modifier and Type | Method and 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. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
double | 
EmpiricalDistribution.getNextValue()
Generates a random value from this distribution. 
 | 
| Modifier and Type | Method and 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. 
 | 
static double | 
InferenceTestUtils.chiSquareTest(double[] expected,
             long[] observed)  | 
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. | 
static boolean | 
InferenceTestUtils.chiSquareTest(double[] expected,
             long[] observed,
             double alpha)  | 
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. | 
static double | 
InferenceTestUtils.chiSquareTest(long[][] counts)  | 
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. | 
static boolean | 
InferenceTestUtils.chiSquareTest(long[][] counts,
             double alpha)  | 
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.chiSquareTestDataSetsComparison(long[] observed1,
                               long[] observed2)  | 
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. | 
static boolean | 
InferenceTestUtils.chiSquareTestDataSetsComparison(long[] observed1,
                               long[] observed2,
                               double alpha)  | 
boolean | 
ChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1,
                               long[] observed2,
                               double alpha)
Performs a Chi-Square two sample test comparing two binned data
 sets. 
 | 
static double | 
InferenceTestUtils.gTest(double[] expected,
     long[] observed)  | 
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. | 
static boolean | 
InferenceTestUtils.gTest(double[] expected,
     long[] observed,
     double alpha)  | 
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.gTestDataSetsComparison(long[] observed1,
                       long[] observed2)  | 
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. | 
static boolean | 
InferenceTestUtils.gTestDataSetsComparison(long[] observed1,
                       long[] observed2,
                       double alpha)  | 
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.gTestIntrinsic(double[] expected,
              long[] observed)  | 
double | 
GTest.gTestIntrinsic(double[] expected,
              long[] observed)
Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described
 in p64-69 of McDonald, J.H. 
 | 
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. 
 | 
static double | 
InferenceTestUtils.homoscedasticTTest(double[] sample1,
                  double[] sample2)  | 
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. | 
static boolean | 
InferenceTestUtils.homoscedasticTTest(double[] sample1,
                  double[] sample2,
                  double alpha)  | 
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.homoscedasticTTest(StatisticalSummary sampleStats1,
                  StatisticalSummary sampleStats2)  | 
static double | 
InferenceTestUtils.oneWayAnovaPValue(Collection<double[]> categoryData)  | 
static boolean | 
InferenceTestUtils.oneWayAnovaTest(Collection<double[]> categoryData,
               double alpha)  | 
double | 
TTest.pairedTTest(double[] sample1,
           double[] sample2)
Returns the observed significance level, or
  p-value, associated with a paired, two-sample, two-tailed t-test
 based on the data in the input arrays. 
 | 
static double | 
InferenceTestUtils.pairedTTest(double[] sample1,
           double[] sample2)  | 
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 boolean | 
InferenceTestUtils.pairedTTest(double[] sample1,
           double[] sample2,
           double alpha)  | 
double | 
TTest.tTest(double[] sample1,
     double[] sample2)
Returns the observed significance level, or
 p-value, associated with a two-sample, two-tailed t-test
 comparing the means of the input arrays. 
 | 
static double | 
InferenceTestUtils.tTest(double[] sample1,
     double[] sample2)  | 
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. | 
static boolean | 
InferenceTestUtils.tTest(double[] sample1,
     double[] sample2,
     double 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. | 
static double | 
InferenceTestUtils.tTest(double mu,
     double[] sample)  | 
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. | 
static boolean | 
InferenceTestUtils.tTest(double mu,
     double[] sample,
     double alpha)  | 
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. | 
static double | 
InferenceTestUtils.tTest(double mu,
     StatisticalSummary sampleStats)  | 
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. | 
static boolean | 
InferenceTestUtils.tTest(double mu,
     StatisticalSummary sampleStats,
     double alpha)  | 
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. 
 | 
static double | 
InferenceTestUtils.tTest(StatisticalSummary sampleStats1,
     StatisticalSummary sampleStats2)  | 
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. | 
static boolean | 
InferenceTestUtils.tTest(StatisticalSummary sampleStats1,
     StatisticalSummary sampleStats2,
     double 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. 
 | 
| Modifier and Type | Method and 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. 
 | 
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. 
 | 
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