Uses of Class
org.hipparchus.exception.MathIllegalArgumentException

Packages that use MathIllegalArgumentException

Package	Description
org.hipparchus	Common classes used throughout the Hipparchus library.
org.hipparchus.analysis	Parent package for common numerical analysis procedures, including root finding, function interpolation and integration.
org.hipparchus.analysis.differentiation	This package holds the main interfaces and basic building block classes dealing with differentiation.
org.hipparchus.analysis.function	The function package contains function objects that wrap the methods contained in Math, as well as common mathematical functions such as the gaussian and sinc functions.
org.hipparchus.analysis.integration	Numerical integration (quadrature) algorithms for univariate real functions.
org.hipparchus.analysis.integration.gauss	Gauss family of quadrature schemes.
org.hipparchus.analysis.interpolation	Univariate real functions interpolation algorithms.
org.hipparchus.analysis.polynomials	Univariate real polynomials implementations, seen as differentiable univariate real functions.
org.hipparchus.analysis.solvers	Root finding algorithms, for univariate real functions.
org.hipparchus.clustering	Clustering algorithms.
org.hipparchus.clustering.distance	Common distance measures.
org.hipparchus.complex	Complex number type and implementations of complex transcendental functions.
org.hipparchus.dfp	Decimal floating point library for Java
org.hipparchus.distribution	Interfaces and implementations of common discrete and continuous distributions.
org.hipparchus.distribution.continuous	Implementations of common continuous distributions.
org.hipparchus.distribution.discrete	Implementations of common discrete distributions.
org.hipparchus.distribution.multivariate	Implementations of multivariate distributions.
org.hipparchus.filtering.kalman	Kalman filter.
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.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.migration.exception	This package provides migration classes from Apache Commons Math to Hipparchus.
org.hipparchus.migration.genetics	This package provides migration classes from Apache Commons Math to Hipparchus.
org.hipparchus.migration.geometry.euclidean.threed	This package provides migration classes from Apache Commons Math to Hipparchus.
org.hipparchus.migration.linear	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.stat.regression	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.optim.nonlinear.scalar	Algorithms for optimizing a scalar function.
org.hipparchus.optim.nonlinear.scalar.noderiv	This package provides optimization algorithms that do not require derivatives.
org.hipparchus.random	Random number and random data generators.
org.hipparchus.special	Implementations of special functions such as Beta and Gamma.
org.hipparchus.stat	Data storage, manipulation and summary routines.
org.hipparchus.stat.correlation	Correlations/Covariance computations.
org.hipparchus.stat.descriptive	Generic univariate and multivariate summary statistic objects.
org.hipparchus.stat.descriptive.moment	Summary statistics based on moments.
org.hipparchus.stat.descriptive.rank	Summary statistics based on ranks.
org.hipparchus.stat.descriptive.summary	Other summary statistics.
org.hipparchus.stat.descriptive.vector	Multivariate statistics.
org.hipparchus.stat.fitting	Statistical methods for fitting distributions.
org.hipparchus.stat.inference	Classes providing hypothesis testing.
org.hipparchus.stat.interval	Utilities to calculate binomial proportion confidence intervals.
org.hipparchus.stat.regression	Statistical routines involving multivariate data.
org.hipparchus.transform	Implementations of transform methods, including Fast Fourier transforms.
org.hipparchus.util	Convenience routines and common data structures used throughout the Hipparchus library.

Uses of MathIllegalArgumentException in org.hipparchus

Methods in org.hipparchus that throw MathIllegalArgumentException

Modifier and Type	Method	Description
T	CalculusFieldElement.atan2(T x)	Two arguments arc tangent operation.
T	CalculusFieldElement.hypot(T y)	Returns the hypotenuse of a triangle with sides this and y - sqrt(this2 +y2) avoiding intermediate overflow or underflow.
default T	CalculusFieldElement.linearCombination(double[] a, T[] b)	Compute a linear combination.
T	CalculusFieldElement.linearCombination(T[] a, T[] b)	Compute a linear combination.
T	CalculusFieldElement.pow(T e)	Power operation.

Uses of MathIllegalArgumentException in org.hipparchus.analysis

Methods in org.hipparchus.analysis that throw MathIllegalArgumentException

Modifier and Type	Method	Description
static double[]	FunctionUtils.sample(UnivariateFunction f, double min, double max, int n)	Samples the specified univariate real function on the specified interval.

Uses of MathIllegalArgumentException in org.hipparchus.analysis.differentiation

Methods in org.hipparchus.analysis.differentiation that throw MathIllegalArgumentException

Modifier and Type	Method	Description
DerivativeStructure	DerivativeStructure.add(DerivativeStructure a)	Compute this + a.
FieldDerivativeStructure<T>	FieldDerivativeStructure.add(FieldDerivativeStructure<T> a)	Compute this + a.
DerivativeStructure	DerivativeStructure.atan2(DerivativeStructure x)	Two arguments arc tangent operation.
static DerivativeStructure	DerivativeStructure.atan2(DerivativeStructure y, DerivativeStructure x)	Two arguments arc tangent operation.
FieldDerivativeStructure<T>	FieldDerivativeStructure.atan2(FieldDerivativeStructure<T> x)	Two arguments arc tangent operation.
static <T extends CalculusFieldElement<T>> FieldDerivativeStructure<T>	FieldDerivativeStructure.atan2(FieldDerivativeStructure<T> y, FieldDerivativeStructure<T> x)	Two arguments arc tangent operation.
final DerivativeStructure	DSFactory.build(double... derivatives)	Build a DerivativeStructure from all its derivatives.
FieldDerivativeStructure<T>	FDSFactory.build(double... derivatives)	Build a FieldDerivativeStructure from all its derivatives.
final FieldDerivativeStructure<T>	FDSFactory.build(T... derivatives)	Build a FieldDerivativeStructure from all its derivatives.
void	DSCompiler.checkCompatibility(DSCompiler compiler)	Check rules set compatibility.
T	Derivative.compose(double... f)	Compute composition of the instance by a univariate function.
DerivativeStructure	DerivativeStructure.compose(double... f)	Compute composition of the instance by a univariate function.
FieldDerivativeStructure<T>	FieldDerivativeStructure.compose(double... f)	Compute composition of the instance by a univariate function.
final FieldDerivativeStructure<T>	FieldDerivativeStructure.compose(T... f)	Compute composition of the instance by a univariate function.
DerivativeStructure	DerivativeStructure.divide(DerivativeStructure a)	Compute this ÷ a.
FieldDerivativeStructure<T>	FieldDerivativeStructure.divide(FieldDerivativeStructure<T> a)	Compute this ÷ a.
static DSCompiler	DSCompiler.getCompiler(int parameters, int order)	Get the compiler for number of free parameters and order.
abstract S	FieldUnivariateDerivative.getDerivative(int n)	Get a derivative from the univariate derivative.
abstract double	UnivariateDerivative.getDerivative(int n)	Get a derivative from the univariate derivative.
double	Derivative.getPartialDerivative(int... orders)	Get a partial derivative.
double	DerivativeStructure.getPartialDerivative(int... orders)	Get a partial derivative.
S	FieldDerivative.getPartialDerivative(int... orders)	Get a partial derivative.
T	FieldDerivativeStructure.getPartialDerivative(int... orders)	Get a partial derivative.
T	FieldGradient.getPartialDerivative(int n)	Get the partial derivative with respect to one parameter.
T	FieldGradient.getPartialDerivative(int... orders)	Get a partial derivative.
S	FieldUnivariateDerivative.getPartialDerivative(int... orders)	Get a partial derivative.
double	Gradient.getPartialDerivative(int n)	Get the partial derivative with respect to one parameter.
double	Gradient.getPartialDerivative(int... orders)	Get a partial derivative.
double	SparseGradient.getPartialDerivative(int... orders)	Get a partial derivative.
double	UnivariateDerivative.getPartialDerivative(int... orders)	Get a partial derivative.
int	DSCompiler.getPartialDerivativeIndex(int... orders)	Get the index of a partial derivative in the array.
DerivativeStructure	DerivativeStructure.hypot(DerivativeStructure y)	Returns the hypotenuse of a triangle with sides this and y - sqrt(this2 +y2) avoiding intermediate overflow or underflow.
static DerivativeStructure	DerivativeStructure.hypot(DerivativeStructure x, DerivativeStructure y)	Returns the hypotenuse of a triangle with sides x and y - sqrt(x2 +y2) avoiding intermediate overflow or underflow.
FieldDerivativeStructure<T>	FieldDerivativeStructure.hypot(FieldDerivativeStructure<T> y)	Returns the hypotenuse of a triangle with sides this and y - sqrt(this2 +y2) avoiding intermediate overflow or underflow.
static <T extends CalculusFieldElement<T>> FieldDerivativeStructure<T>	FieldDerivativeStructure.hypot(FieldDerivativeStructure<T> x, FieldDerivativeStructure<T> y)	Returns the hypotenuse of a triangle with sides x and y - sqrt(x2 +y2) avoiding intermediate overflow or underflow.
DerivativeStructure	DerivativeStructure.linearCombination(double[] a, DerivativeStructure[] b)	Compute a linear combination.
DerivativeStructure	DerivativeStructure.linearCombination(double a1, DerivativeStructure b1, double a2, DerivativeStructure b2)	Compute a linear combination.
DerivativeStructure	DerivativeStructure.linearCombination(double a1, DerivativeStructure b1, double a2, DerivativeStructure b2, double a3, DerivativeStructure b3)	Compute a linear combination.
DerivativeStructure	DerivativeStructure.linearCombination(double a1, DerivativeStructure b1, double a2, DerivativeStructure b2, double a3, DerivativeStructure b3, double a4, DerivativeStructure b4)	Compute a linear combination.
DerivativeStructure	DerivativeStructure.linearCombination(DerivativeStructure[] a, DerivativeStructure[] b)	Compute a linear combination.
DerivativeStructure	DerivativeStructure.linearCombination(DerivativeStructure a1, DerivativeStructure b1, DerivativeStructure a2, DerivativeStructure b2)	Compute a linear combination.
DerivativeStructure	DerivativeStructure.linearCombination(DerivativeStructure a1, DerivativeStructure b1, DerivativeStructure a2, DerivativeStructure b2, DerivativeStructure a3, DerivativeStructure b3)	Compute a linear combination.
DerivativeStructure	DerivativeStructure.linearCombination(DerivativeStructure a1, DerivativeStructure b1, DerivativeStructure a2, DerivativeStructure b2, DerivativeStructure a3, DerivativeStructure b3, DerivativeStructure a4, DerivativeStructure b4)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(double[] a, FieldDerivativeStructure<T>[] b)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(double a1, FieldDerivativeStructure<T> b1, double a2, FieldDerivativeStructure<T> b2)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(double a1, FieldDerivativeStructure<T> b1, double a2, FieldDerivativeStructure<T> b2, double a3, FieldDerivativeStructure<T> b3)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(double a1, FieldDerivativeStructure<T> b1, double a2, FieldDerivativeStructure<T> b2, double a3, FieldDerivativeStructure<T> b3, double a4, FieldDerivativeStructure<T> b4)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(FieldDerivativeStructure<T>[] a, FieldDerivativeStructure<T>[] b)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(FieldDerivativeStructure<T> a1, FieldDerivativeStructure<T> b1, FieldDerivativeStructure<T> a2, FieldDerivativeStructure<T> b2)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(FieldDerivativeStructure<T> a1, FieldDerivativeStructure<T> b1, FieldDerivativeStructure<T> a2, FieldDerivativeStructure<T> b2, FieldDerivativeStructure<T> a3, FieldDerivativeStructure<T> b3)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(FieldDerivativeStructure<T> a1, FieldDerivativeStructure<T> b1, FieldDerivativeStructure<T> a2, FieldDerivativeStructure<T> b2, FieldDerivativeStructure<T> a3, FieldDerivativeStructure<T> b3, FieldDerivativeStructure<T> a4, FieldDerivativeStructure<T> b4)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(T[] a, FieldDerivativeStructure<T>[] b)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(T a1, FieldDerivativeStructure<T> b1, T a2, FieldDerivativeStructure<T> b2)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(T a1, FieldDerivativeStructure<T> b1, T a2, FieldDerivativeStructure<T> b2, T a3, FieldDerivativeStructure<T> b3)	Compute a linear combination.
FieldDerivativeStructure<T>	FieldDerivativeStructure.linearCombination(T a1, FieldDerivativeStructure<T> b1, T a2, FieldDerivativeStructure<T> b2, T a3, FieldDerivativeStructure<T> b3, T a4, FieldDerivativeStructure<T> b4)	Compute a linear combination.
SparseGradient	SparseGradient.linearCombination(SparseGradient[] a, SparseGradient[] b)	Compute a linear combination.
DerivativeStructure	DerivativeStructure.multiply(DerivativeStructure a)	Compute this × a.
FieldDerivativeStructure<T>	FieldDerivativeStructure.multiply(FieldDerivativeStructure<T> a)	Compute this × a.
DerivativeStructure	DerivativeStructure.pow(DerivativeStructure e)	Power operation.
FieldDerivativeStructure<T>	FieldDerivativeStructure.pow(FieldDerivativeStructure<T> e)	Power operation.
DerivativeStructure	DerivativeStructure.remainder(DerivativeStructure a)	IEEE remainder operator.
FieldDerivativeStructure<T>	FieldDerivativeStructure.remainder(FieldDerivativeStructure<T> a)	IEEE remainder operator.
DerivativeStructure	DerivativeStructure.subtract(DerivativeStructure a)	Compute this - a.
FieldDerivativeStructure<T>	FieldDerivativeStructure.subtract(FieldDerivativeStructure<T> a)	Compute this - a.
DerivativeStructure	MultivariateDifferentiableFunction.value(DerivativeStructure[] point)	Compute the value for the function at the given point.
DerivativeStructure[]	MultivariateDifferentiableVectorFunction.value(DerivativeStructure[] point)	Compute the value for the function at the given point.
<T extends Derivative<T>> T	UnivariateDifferentiableFunction.value(T x)	Compute the value for the function.
<T extends Derivative<T>> T[][]	UnivariateDifferentiableMatrixFunction.value(T x)	Compute the value for the function.
<T extends Derivative<T>> T[]	UnivariateDifferentiableVectorFunction.value(T x)	Compute the value for the function.
DerivativeStructure	DSFactory.variable(int index, double value)	Build a DerivativeStructure representing a variable.
FieldDerivativeStructure<T>	FDSFactory.variable(int index, double value)	Build a FieldDerivativeStructure representing a variable.
FieldDerivativeStructure<T>	FDSFactory.variable(int index, T value)	Build a FieldDerivativeStructure representing a variable.

Constructors in org.hipparchus.analysis.differentiation that throw MathIllegalArgumentException

Modifier	Constructor	Description
	FieldGradient(FieldDerivativeStructure<T> ds)	Build an instance from a DerivativeStructure.
	FieldUnivariateDerivative1(FieldDerivativeStructure<T> ds)	Build an instance from a DerivativeStructure.
	FieldUnivariateDerivative2(FieldDerivativeStructure<T> ds)	Build an instance from a DerivativeStructure.
	FiniteDifferencesDifferentiator(int nbPoints, double stepSize)	Build a differentiator with number of points and step size when independent variable is unbounded.
	FiniteDifferencesDifferentiator(int nbPoints, double stepSize, double tLower, double tUpper)	Build a differentiator with number of points and step size when independent variable is bounded.
	Gradient(DerivativeStructure ds)	Build an instance from a DerivativeStructure.
	UnivariateDerivative1(DerivativeStructure ds)	Build an instance from a DerivativeStructure.
	UnivariateDerivative2(DerivativeStructure ds)	Build an instance from a DerivativeStructure.

Uses of MathIllegalArgumentException in org.hipparchus.analysis.function

Methods in org.hipparchus.analysis.function that throw MathIllegalArgumentException

Modifier and Type	Method	Description
double[]	Gaussian.Parametric.gradient(double x, double... param)	Computes the value of the gradient at x.
double[]	HarmonicOscillator.Parametric.gradient(double x, double... param)	Computes the value of the gradient at x.
double[]	Logistic.Parametric.gradient(double x, double... param)	Computes the value of the gradient at x.
double[]	Logit.Parametric.gradient(double x, double... param)	Computes the value of the gradient at x.
double[]	Sigmoid.Parametric.gradient(double x, double... param)	Computes the value of the gradient at x.
double	Gaussian.Parametric.value(double x, double... param)	Computes the value of the Gaussian at x.
<T extends Derivative<T>> T	Gaussian.value(T t)	Compute the value for the function.
double	HarmonicOscillator.Parametric.value(double x, double... param)	Computes the value of the harmonic oscillator at x.
<T extends Derivative<T>> T	HarmonicOscillator.value(T t)	Compute the value for the function.
double	Logistic.Parametric.value(double x, double... param)	Computes the value of the sigmoid at x.
double	Logit.Parametric.value(double x, double... param)	Computes the value of the logit at x.
double	Logit.value(double x)	Compute the value of the function.
<T extends Derivative<T>> T	Logit.value(T t)	Compute the value for the function.
double	Sigmoid.Parametric.value(double x, double... param)	Computes the value of the sigmoid at x.
<T extends Derivative<T>> T	Sigmoid.value(T t)	Compute the value for the function.
<T extends Derivative<T>> T	Sinc.value(T t)	Compute the value for the function.

Constructors in org.hipparchus.analysis.function that throw MathIllegalArgumentException

Modifier	Constructor	Description
	Gaussian(double mean, double sigma)	Normalized gaussian with given mean and standard deviation.
	Gaussian(double norm, double mean, double sigma)	Gaussian with given normalization factor, mean and standard deviation.
	Logistic(double k, double m, double b, double q, double a, double n)	Simple constructor.
	StepFunction(double[] x, double[] y)	Builds a step function from a list of arguments and the corresponding values.

Uses of MathIllegalArgumentException in org.hipparchus.analysis.integration

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

Modifier and Type	Method	Description
protected T	FieldMidPointIntegrator.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	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.
protected void	BaseAbstractFieldUnivariateIntegrator.setup(int maxEval, CalculusFieldUnivariateFunction<T> f, T lower, T upper)	Prepare for computation.
protected void	BaseAbstractUnivariateIntegrator.setup(int maxEval, UnivariateFunction f, double lower, double upper)	Prepare for computation.

Constructors in org.hipparchus.analysis.integration that throw MathIllegalArgumentException

Modifier	Constructor	Description
protected	BaseAbstractFieldUnivariateIntegrator(Field<T> field, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Construct an integrator with given accuracies and iteration counts.
protected	BaseAbstractFieldUnivariateIntegrator(Field<T> field, int minimalIterationCount, int maximalIterationCount)	Construct an integrator with given iteration counts.
protected	BaseAbstractUnivariateIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Construct an integrator with given accuracies and iteration counts.
protected	BaseAbstractUnivariateIntegrator(int minimalIterationCount, int maximalIterationCount)	Construct an integrator with given iteration counts.
	FieldMidPointIntegrator(Field<T> field, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Build a midpoint integrator with given accuracies and iterations counts.
	FieldMidPointIntegrator(Field<T> field, int minimalIterationCount, int maximalIterationCount)	Build a midpoint integrator with given iteration counts.
	FieldRombergIntegrator(Field<T> field, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Build a Romberg integrator with given accuracies and iterations counts.
	FieldRombergIntegrator(Field<T> field, int minimalIterationCount, int maximalIterationCount)	Build a Romberg integrator with given iteration counts.
	FieldSimpsonIntegrator(Field<T> field, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Build a Simpson integrator with given accuracies and iterations counts.
	FieldSimpsonIntegrator(Field<T> field, int minimalIterationCount, int maximalIterationCount)	Build a Simpson integrator with given iteration counts.
	FieldTrapezoidIntegrator(Field<T> field, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Build a trapezoid integrator with given accuracies and iterations counts.
	FieldTrapezoidIntegrator(Field<T> field, int minimalIterationCount, int maximalIterationCount)	Build a trapezoid integrator with given iteration counts.
	IterativeLegendreFieldGaussIntegrator(Field<T> field, int n, double relativeAccuracy, double absoluteAccuracy)	Builds an integrator with given accuracies.
	IterativeLegendreFieldGaussIntegrator(Field<T> field, int n, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Builds an integrator with given accuracies and iterations counts.
	IterativeLegendreFieldGaussIntegrator(Field<T> field, int n, int minimalIterationCount, int maximalIterationCount)	Builds an integrator with given iteration counts.
	IterativeLegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy)	Builds an integrator with given accuracies.
	IterativeLegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Builds an integrator with given accuracies and iterations counts.
	IterativeLegendreGaussIntegrator(int n, int minimalIterationCount, int maximalIterationCount)	Builds an integrator with given iteration counts.
	MidPointIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Build a midpoint integrator with given accuracies and iterations counts.
	MidPointIntegrator(int minimalIterationCount, int maximalIterationCount)	Build a midpoint integrator with given iteration counts.
	RombergIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Build a Romberg integrator with given accuracies and iterations counts.
	RombergIntegrator(int minimalIterationCount, int maximalIterationCount)	Build a Romberg integrator with given iteration counts.
	SimpsonIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Build a Simpson integrator with given accuracies and iterations counts.
	SimpsonIntegrator(int minimalIterationCount, int maximalIterationCount)	Build a Simpson integrator with given iteration counts.
	TrapezoidIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)	Build a trapezoid integrator with given accuracies and iterations counts.
	TrapezoidIntegrator(int minimalIterationCount, int maximalIterationCount)	Build a trapezoid integrator with given iteration counts.

Uses of MathIllegalArgumentException in org.hipparchus.analysis.integration.gauss

Methods in org.hipparchus.analysis.integration.gauss that throw MathIllegalArgumentException

Modifier and Type	Method	Description
protected abstract Pair<double[],double[]>	AbstractRuleFactory.computeRule(int numberOfPoints)	Computes the rule for the given order.
protected Pair<double[],double[]>	ConvertingRuleFactory.computeRule(int numberOfPoints)	Computes the rule for the given order.
protected abstract Pair<T[],T[]>	FieldAbstractRuleFactory.computeRule(int numberOfPoints)	Computes the rule for the given order.
protected Pair<T[],T[]>	FieldHermiteRuleFactory.computeRule(int numberOfPoints)	Computes the rule for the given order.
Pair<T[],T[]>	FieldLaguerreRuleFactory.computeRule(int numberOfPoints)	Computes the rule for the given order.
Pair<T[],T[]>	FieldLegendreRuleFactory.computeRule(int numberOfPoints)	Computes the rule for the given order.
protected Pair<double[],double[]>	HermiteRuleFactory.computeRule(int numberOfPoints)	Computes the rule for the given order.
protected Pair<double[],double[]>	LegendreRuleFactory.computeRule(int numberOfPoints)	Computes the rule for the given order.
Pair<double[],double[]>	AbstractRuleFactory.getRule(int numberOfPoints)	Gets a copy of the quadrature rule with the given number of integration points.
Pair<T[],T[]>	FieldAbstractRuleFactory.getRule(int numberOfPoints)	Gets a copy of the quadrature rule with the given number of integration points.
Pair<T[],T[]>	FieldRuleFactory.getRule(int numberOfPoints)	Gets a copy of the quadrature rule with the given number of integration points.
Pair<double[],double[]>	RuleFactory.getRule(int numberOfPoints)	Gets a copy of the quadrature rule with the given number of integration points.
FieldGaussIntegrator<T>	FieldGaussIntegratorFactory.legendre(int numberOfPoints, T lowerBound, T upperBound)	Creates a Gauss-Legendre integrator of the given order.
GaussIntegrator	GaussIntegratorFactory.legendre(int numberOfPoints, double lowerBound, double upperBound)	Creates a Gauss-Legendre integrator of the given order.
GaussIntegrator	GaussIntegratorFactory.legendreHighPrecision(int numberOfPoints)	Creates a Gauss-Legendre integrator of the given order.
GaussIntegrator	GaussIntegratorFactory.legendreHighPrecision(int numberOfPoints, double lowerBound, double upperBound)	Creates an integrator of the given order, and whose call to the integrate method will perform an integration on the given interval.

Constructors in org.hipparchus.analysis.integration.gauss that throw MathIllegalArgumentException

Modifier	Constructor	Description
	FieldGaussIntegrator(Pair<T[],T[]> pointsAndWeights)	Creates an integrator from the given pair of points (first element of the pair) and weights (second element of the pair.
	FieldGaussIntegrator(T[] points, T[] weights)	Creates an integrator from the given points and weights.
	GaussIntegrator(double[] points, double[] weights)	Creates an integrator from the given points and weights.
	GaussIntegrator(Pair<double[],double[]> pointsAndWeights)	Creates an integrator from the given pair of points (first element of the pair) and weights (second element of the pair.
	SymmetricFieldGaussIntegrator(Pair<T[],T[]> pointsAndWeights)	Creates an integrator from the given pair of points (first element of the pair) and weights (second element of the pair.
	SymmetricFieldGaussIntegrator(T[] points, T[] weights)	Creates an integrator from the given points and weights.
	SymmetricGaussIntegrator(double[] points, double[] weights)	Creates an integrator from the given points and weights.
	SymmetricGaussIntegrator(Pair<double[],double[]> pointsAndWeights)	Creates an integrator from the given pair of points (first element of the pair) and weights (second element of the pair.

Uses of MathIllegalArgumentException in org.hipparchus.analysis.interpolation

Methods in org.hipparchus.analysis.interpolation that throw MathIllegalArgumentException

Modifier and Type	Method	Description
final void	FieldHermiteInterpolator.addSamplePoint(T x, T[]... value)	Add a sample point.
void	HermiteInterpolator.addSamplePoint(double x, double[]... value)	Add a sample point.
protected static double[]	DividedDifferenceInterpolator.computeDividedDifference(double[] x, double[] y)	Return a copy of the divided difference array.
T[][]	FieldHermiteInterpolator.derivatives(T x, int order)	Interpolate value and first derivatives at a specified abscissa.
double[][]	HermiteInterpolator.derivatives(double x, int order)	Interpolate value and first derivatives at a specified abscissa.
PolynomialFunction[]	HermiteInterpolator.getPolynomials()	Compute the interpolation polynomials.
PolynomialSplineFunction	AkimaSplineInterpolator.interpolate(double[] xvals, double[] yvals)	Computes an interpolating function for the data set.
<T extends CalculusFieldElement<T>> FieldPolynomialSplineFunction<T>	AkimaSplineInterpolator.interpolate(T[] xvals, T[] yvals)	Computes an interpolating function for the data set.
BicubicInterpolatingFunction	BicubicInterpolator.interpolate(double[] xval, double[] yval, double[][] fval)	Compute an interpolating function for the dataset.
BilinearInterpolatingFunction	BilinearInterpolator.interpolate(double[] xval, double[] yval, double[][] fval)	Compute an interpolating function for the dataset.
BivariateFunction	BivariateGridInterpolator.interpolate(double[] xval, double[] yval, double[][] fval)	Compute an interpolating function for the dataset.
PolynomialFunctionNewtonForm	DividedDifferenceInterpolator.interpolate(double[] x, double[] y)	Compute an interpolating function for the dataset.
<T extends CalculusFieldElement<T>> CalculusFieldUnivariateFunction<T>	FieldUnivariateInterpolator.interpolate(T[] xval, T[] yval)	Compute an interpolating function for the dataset.
PolynomialSplineFunction	LinearInterpolator.interpolate(double[] x, double[] y)	Computes a linear interpolating function for the data set.
<T extends CalculusFieldElement<T>> FieldPolynomialSplineFunction<T>	LinearInterpolator.interpolate(T[] x, T[] y)	Computes a linear interpolating function for the data set.
final PolynomialSplineFunction	LoessInterpolator.interpolate(double[] xval, double[] yval)	Compute an interpolating function by performing a loess fit on the data at the original abscissae and then building a cubic spline with a SplineInterpolator on the resulting fit.
MultivariateFunction	MicrosphereProjectionInterpolator.interpolate(double[][] xval, double[] yval)	Computes an interpolating function for the data set.
MultivariateFunction	MultivariateInterpolator.interpolate(double[][] xval, double[] yval)	Computes an interpolating function for the data set.
PolynomialFunctionLagrangeForm	NevilleInterpolator.interpolate(double[] x, double[] y)	Computes an interpolating function for the data set.
PiecewiseBicubicSplineInterpolatingFunction	PiecewiseBicubicSplineInterpolator.interpolate(double[] xval, double[] yval, double[][] fval)	Compute an interpolating function for the dataset.
PolynomialSplineFunction	SplineInterpolator.interpolate(double[] x, double[] y)	Computes an interpolating function for the data set.
<T extends CalculusFieldElement<T>> FieldPolynomialSplineFunction<T>	SplineInterpolator.interpolate(T[] x, T[] y)	Computes an interpolating function for the data set.
TricubicInterpolatingFunction	TricubicInterpolator.interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)	Compute an interpolating function for the dataset.
TrivariateFunction	TrivariateGridInterpolator.interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)	Compute an interpolating function for the dataset.
UnivariateFunction	UnivariateInterpolator.interpolate(double[] xval, double[] yval)	Compute an interpolating function for the dataset.
UnivariateFunction	UnivariatePeriodicInterpolator.interpolate(double[] xval, double[] yval)	Compute an interpolating function for the dataset.
final double[]	LoessInterpolator.smooth(double[] xval, double[] yval)	Compute a loess fit on the data at the original abscissae.
final double[]	LoessInterpolator.smooth(double[] xval, double[] yval, double[] weights)	Compute a weighted loess fit on the data at the original abscissae.
double	BicubicInterpolatingFunction.value(double x, double y)	Compute the value for the function.
T[]	FieldHermiteInterpolator.value(T x)	Interpolate value at a specified abscissa.
double[]	HermiteInterpolator.value(double x)	Interpolate value at a specified abscissa.
<T extends Derivative<T>> T[]	HermiteInterpolator.value(T x)	Compute the value for the function.
double	PiecewiseBicubicSplineInterpolatingFunction.value(double x, double y)	Compute the value for the function.
<T extends CalculusFieldElement<T>> T	PiecewiseBicubicSplineInterpolatingFunction.value(T x, T y)	Compute the value for the function.
double	TricubicInterpolatingFunction.value(double x, double y, double z)	Compute the value for the function.

Constructors in org.hipparchus.analysis.interpolation that throw MathIllegalArgumentException

Modifier	Constructor	Description
	BicubicInterpolatingFunction(double[] x, double[] y, double[][] f, double[][] dFdX, double[][] dFdY, double[][] d2FdXdY)	Simple constructor.
	BilinearInterpolatingFunction(double[] xVal, double[] yVal, double[][] fVal)	Simple constructor.
	GridAxis(double[] grid, int n)	Simple constructor.
	LoessInterpolator(double bandwidth, int robustnessIters, double accuracy)	Construct a new LoessInterpolator with given bandwidth, number of robustness iterations and accuracy.
	MicrosphereProjectionInterpolator(InterpolatingMicrosphere microsphere, double exponent, boolean sharedSphere, double noInterpolationTolerance)	Create a microsphere interpolator.
	PiecewiseBicubicSplineInterpolatingFunction(double[] x, double[] y, double[][] f)	Simple constructor.
	TricubicInterpolatingFunction(double[] x, double[] y, double[] z, double[][][] f, double[][][] dFdX, double[][][] dFdY, double[][][] dFdZ, double[][][] d2FdXdY, double[][][] d2FdXdZ, double[][][] d2FdYdZ, double[][][] d3FdXdYdZ)	Simple constructor.

Uses of MathIllegalArgumentException in org.hipparchus.analysis.polynomials

Methods in org.hipparchus.analysis.polynomials that throw MathIllegalArgumentException

Modifier and Type	Method	Description
static void	SmoothStepFactory.checkBetweenZeroAndOneIncluded(double input)	Check that input is between [0:1].
protected static <T extends CalculusFieldElement<T>> T[]	FieldPolynomialFunction.differentiate(T[] coefficients)	Returns the coefficients of the derivative of the polynomial with the given coefficients.
protected static double[]	PolynomialFunction.differentiate(double[] coefficients)	Returns the coefficients of the derivative of the polynomial with the given coefficients.
protected static <T extends CalculusFieldElement<T>> T	FieldPolynomialFunction.evaluate(T[] coefficients, T argument)	Uses Horner's Method to evaluate the polynomial with the given coefficients at the argument.
protected static double	PolynomialFunction.evaluate(double[] coefficients, double argument)	Uses Horner's Method to evaluate the polynomial with the given coefficients at the argument.
static double	PolynomialFunctionLagrangeForm.evaluate(double[] x, double[] y, double z)	Evaluate the Lagrange polynomial using Neville's Algorithm.
static double	PolynomialFunctionNewtonForm.evaluate(double[] a, double[] c, double z)	Evaluate the Newton polynomial using nested multiplication.
double	PolynomialFunction.Parametric.value(double x, double... parameters)	Compute the value of the function.
<T extends Derivative<T>> T	PolynomialFunction.value(T t)	Compute the value for the function.
<T extends CalculusFieldElement<T>> T	PolynomialFunction.value(T t)	Compute the value of the function.
T	SmoothStepFactory.FieldSmoothStepFunction.value(double leftEdge, double rightEdge, T x)	Compute the value of the smoothstep function for the given edges and argument.
double	SmoothStepFactory.QuadraticSmoothStepFunction.value(double leftEdge, double rightEdge, double x)	Compute the value of the smoothstep function for the given edges and argument.
double	SmoothStepFactory.SmoothStepFunction.value(double leftEdge, double rightEdge, double x)	Compute the value of the smoothstep function for the given edges and argument.
protected static void	PolynomialFunctionNewtonForm.verifyInputArray(double[] a, double[] c)	Verifies that the input arrays are valid.
static boolean	PolynomialFunctionLagrangeForm.verifyInterpolationArray(double[] x, double[] y, boolean abort)	Check that the interpolation arrays are valid.

Constructors in org.hipparchus.analysis.polynomials that throw MathIllegalArgumentException

Modifier	Constructor	Description
	FieldPolynomialFunction(T[] c)	Construct a polynomial with the given coefficients.
	FieldPolynomialSplineFunction(T[] knots, FieldPolynomialFunction<T>[] polynomials)	Construct a polynomial spline function with the given segment delimiters and interpolating polynomials.
	PolynomialFunction(double... c)	Construct a polynomial with the given coefficients.
	PolynomialFunctionLagrangeForm(double[] x, double[] y)	Construct a Lagrange polynomial with the given abscissas and function values.
	PolynomialFunctionNewtonForm(double[] a, double[] c)	Construct a Newton polynomial with the given a[] and c[].
	PolynomialSplineFunction(double[] knots, PolynomialFunction[] polynomials)	Construct a polynomial spline function with the given segment delimiters and interpolating polynomials.

Uses of MathIllegalArgumentException in org.hipparchus.analysis.solvers

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

Modifier and Type	Method	Description
static <T extends CalculusFieldElement<T>> T[]	UnivariateSolverUtils.bracket(CalculusFieldUnivariateFunction<T> function, T initial, T lowerBound, T upperBound)	This method simply calls bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations) with q and r set to 1.0 and maximumIterations set to Integer.MAX_VALUE.
static <T extends CalculusFieldElement<T>> T[]	UnivariateSolverUtils.bracket(CalculusFieldUnivariateFunction<T> function, T initial, T lowerBound, T upperBound, int maximumIterations)	This method simply calls bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations) with q and r set to 1.0.
static <T extends CalculusFieldElement<T>> T[]	UnivariateSolverUtils.bracket(CalculusFieldUnivariateFunction<T> function, T initial, T lowerBound, T upperBound, T q, T r, int maximumIterations)	This method attempts to find two values a and b satisfying lowerBound <= a < initial < b <= upperBound f(a) * f(b) <= 0 If f is continuous on [a,b], this means that a and b bracket a root of f.
static double[]	UnivariateSolverUtils.bracket(UnivariateFunction function, double initial, double lowerBound, double upperBound)	This method simply calls bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations) with q and r set to 1.0 and maximumIterations set to Integer.MAX_VALUE.
static double[]	UnivariateSolverUtils.bracket(UnivariateFunction function, double initial, double lowerBound, double upperBound, double q, double r, int maximumIterations)	This method attempts to find two values a and b satisfying lowerBound <= a < initial < b <= upperBound f(a) * f(b) <= 0 If f is continuous on [a,b], this means that a and b bracket a root of f.
static double[]	UnivariateSolverUtils.bracket(UnivariateFunction function, double initial, double lowerBound, double upperBound, int maximumIterations)	This method simply calls bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations) with q and r set to 1.0.
protected abstract double	BaseAbstractUnivariateSolver.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	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.
static double	UnivariateSolverUtils.forceSide(int maxEval, UnivariateFunction f, BracketedUnivariateSolver<UnivariateFunction> bracketing, double baseRoot, double min, double max, AllowedSolution allowedSolution)	Force a root found by a non-bracketing solver to lie on a specified side, as if the solver were a bracketing 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.
T	FieldBracketingNthOrderBrentSolver.solve(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max, AllowedSolution allowedSolution)	Solve for a zero in the given interval.
T	FieldBracketingNthOrderBrentSolver.solve(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max, T startValue, AllowedSolution allowedSolution)	Solve for a zero in the given interval, start at startValue.
static double	UnivariateSolverUtils.solve(UnivariateFunction function, double x0, double x1)	Convenience method to find a zero of a univariate real function.
static double	UnivariateSolverUtils.solve(UnivariateFunction function, double x0, double x1, double absoluteAccuracy)	Convenience method to find a zero of a univariate real function.
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.
protected void	BaseAbstractUnivariateSolver.verifyBracketing(double lower, double upper)	Check that the endpoints specify an interval and the function takes opposite signs at the endpoints.
static void	UnivariateSolverUtils.verifyBracketing(UnivariateFunction function, double lower, double upper)	Check that the endpoints specify an interval and the end points bracket a root.
protected void	BaseAbstractUnivariateSolver.verifyInterval(double lower, double upper)	Check that the endpoints specify an interval.
static void	UnivariateSolverUtils.verifyInterval(double lower, double upper)	Check that the endpoints specify an interval.
protected void	BaseAbstractUnivariateSolver.verifySequence(double lower, double initial, double upper)	Check that lower < initial < upper.
static void	UnivariateSolverUtils.verifySequence(double lower, double initial, double upper)	Check that lower < initial < upper.

Constructors in org.hipparchus.analysis.solvers that throw MathIllegalArgumentException

Modifier	Constructor	Description
	BracketingNthOrderBrentSolver(double relativeAccuracy, double absoluteAccuracy, double functionValueAccuracy, int maximalOrder)	Construct a solver.
	BracketingNthOrderBrentSolver(double relativeAccuracy, double absoluteAccuracy, int maximalOrder)	Construct a solver.
	BracketingNthOrderBrentSolver(double absoluteAccuracy, int maximalOrder)	Construct a solver.
	FieldBracketingNthOrderBrentSolver(T relativeAccuracy, T absoluteAccuracy, T functionValueAccuracy, int maximalOrder)	Construct a solver.

Uses of MathIllegalArgumentException in org.hipparchus.clustering

Methods in org.hipparchus.clustering that throw MathIllegalArgumentException

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>>	FuzzyKMeansClusterer.cluster(Collection<T> dataPoints)	Performs Fuzzy K-Means cluster analysis.
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.

Constructors in org.hipparchus.clustering that throw MathIllegalArgumentException

Modifier	Constructor	Description
	DBSCANClusterer(double eps, int minPts)	Creates a new instance of a DBSCANClusterer.
	DBSCANClusterer(double eps, int minPts, DistanceMeasure measure)	Creates a new instance of a DBSCANClusterer.
	FuzzyKMeansClusterer(int k, double fuzziness)	Creates a new instance of a FuzzyKMeansClusterer.
	FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure)	Creates a new instance of a FuzzyKMeansClusterer.
	FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure, double epsilon, RandomGenerator random)	Creates a new instance of a FuzzyKMeansClusterer.

Uses of MathIllegalArgumentException in org.hipparchus.clustering.distance

Methods in org.hipparchus.clustering.distance that throw MathIllegalArgumentException

Modifier and Type	Method	Description
double	CanberraDistance.compute(double[] a, double[] b)	Compute the distance between two n-dimensional vectors.
double	ChebyshevDistance.compute(double[] a, double[] b)	Compute the distance between two n-dimensional vectors.
double	DistanceMeasure.compute(double[] a, double[] b)	Compute the distance between two n-dimensional vectors.
double	EarthMoversDistance.compute(double[] a, double[] b)	Compute the distance between two n-dimensional vectors.
double	EuclideanDistance.compute(double[] a, double[] b)	Compute the distance between two n-dimensional vectors.
double	ManhattanDistance.compute(double[] a, double[] b)	Compute the distance between two n-dimensional vectors.

Uses of MathIllegalArgumentException in org.hipparchus.complex

Methods in org.hipparchus.complex that throw MathIllegalArgumentException

Modifier and Type	Method	Description
void	RootsOfUnity.computeRoots(int n)	Computes the n-th roots of unity.
StringBuffer	ComplexFormat.format(Object obj, StringBuffer toAppendTo, FieldPosition pos)	Formats a object to produce a string.
static ComplexFormat	ComplexFormat.getComplexFormat(String imaginaryCharacter, Locale locale)	Returns the default complex format for the given locale.
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.
Complex	Complex.linearCombination(double[] a, Complex[] b)	Compute a linear combination.
Complex	Complex.linearCombination(Complex[] a, Complex[] b)	Compute a linear combination.
FieldComplex<T>	FieldComplex.linearCombination(double[] a, FieldComplex<T>[] b)	Compute a linear combination.
FieldComplex<T>	FieldComplex.linearCombination(FieldComplex<T>[] a, FieldComplex<T>[] b)	Compute a linear combination.
List<Complex>	Complex.nthRoot(int n)	Computes the n-th roots of this complex number.
List<FieldComplex<T>>	FieldComplex.nthRoot(int n)	Computes the n-th roots of this complex number.
static Complex	ComplexUtils.polar2Complex(double r, double theta)	Creates a complex number from the given polar representation.
static <T extends CalculusFieldElement<T>> FieldComplex<T>	ComplexUtils.polar2Complex(T r, T theta)	Creates a complex number from the given polar representation.

Constructors in org.hipparchus.complex that throw MathIllegalArgumentException

Modifier	Constructor	Description
	ComplexFormat(String imaginaryCharacter)	Create an instance with a custom imaginary character, and the default number format for both real and imaginary parts.
	ComplexFormat(String imaginaryCharacter, NumberFormat format)	Create an instance with a custom imaginary character, and a custom number format for both real and imaginary parts.
	ComplexFormat(String imaginaryCharacter, NumberFormat realFormat, NumberFormat imaginaryFormat)	Create an instance with a custom imaginary character, a custom number format for the real part, and a custom number format for the imaginary part.
	Quaternion(double scalar, double[] v)	Builds a quaternion from scalar and vector parts.

Uses of MathIllegalArgumentException in org.hipparchus.dfp

Methods in org.hipparchus.dfp that throw MathIllegalArgumentException

Modifier and Type	Method	Description
Dfp	Dfp.atan2(Dfp x)	Two arguments arc tangent operation.
Dfp	Dfp.linearCombination(double[] a, Dfp[] b)	Compute a linear combination.
Dfp	Dfp.linearCombination(Dfp[] a, Dfp[] b)	Compute a linear combination.

Uses of MathIllegalArgumentException in org.hipparchus.distribution

Methods in org.hipparchus.distribution that throw MathIllegalArgumentException

Modifier and Type	Method	Description
int	IntegerDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	RealDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	IntegerDistribution.probability(int x0, int x1)	For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
double	RealDistribution.probability(double x0, double x1)	For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
double[][]	MultivariateRealDistribution.sample(int sampleSize)	Generates a list of a random value vectors from the distribution.

Constructors in org.hipparchus.distribution that throw MathIllegalArgumentException

Modifier	Constructor	Description
	EnumeratedDistribution(List<Pair<T,Double>> pmf)	Create an enumerated distribution using the given probability mass function enumeration.

Uses of MathIllegalArgumentException in org.hipparchus.distribution.continuous

Methods in org.hipparchus.distribution.continuous that throw MathIllegalArgumentException

Modifier and Type	Method	Description
double	AbstractRealDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	CauchyDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	ConstantRealDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	EnumeratedRealDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	ExponentialDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	GumbelDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	LaplaceDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	LevyDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	LogisticDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	NormalDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	TriangularDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	UniformRealDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	AbstractRealDistribution.probability(double x0, double x1)	For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
double	LogNormalDistribution.probability(double x0, double x1)	For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
double	NormalDistribution.probability(double x0, double x1)	For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).

Constructors in org.hipparchus.distribution.continuous that throw MathIllegalArgumentException

Modifier	Constructor	Description
	CauchyDistribution(double median, double scale)	Creates a Cauchy distribution.
	EnumeratedRealDistribution(double[] singletons, double[] probabilities)	Create a discrete real-valued distribution using the given probability mass function enumeration.
	ExponentialDistribution(double mean)	Create an exponential distribution with the given mean.
	FDistribution(double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom)	Creates an F distribution using the given degrees of freedom.
	FDistribution(double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom, double inverseCumAccuracy)	Creates an F distribution.
	GammaDistribution(double shape, double scale)	Creates a new gamma distribution with specified values of the shape and scale parameters.
	GammaDistribution(double shape, double scale, double inverseCumAccuracy)	Creates a Gamma distribution.
	GumbelDistribution(double mu, double beta)	Build a new instance.
	LaplaceDistribution(double mu, double beta)	Build a new instance.
	LogisticDistribution(double mu, double s)	Build a new instance.
	LogNormalDistribution(double location, double shape)	Create a log-normal distribution using the specified location and shape.
	LogNormalDistribution(double location, double shape, double inverseCumAccuracy)	Creates a log-normal distribution.
	NakagamiDistribution(double mu, double omega)	Build a new instance.
	NakagamiDistribution(double mu, double omega, double inverseAbsoluteAccuracy)	Build a new instance.
	NormalDistribution(double mean, double sd)	Create a normal distribution using the given mean, standard deviation.
	ParetoDistribution(double scale, double shape)	Create a Pareto distribution using the specified scale and shape.
	ParetoDistribution(double scale, double shape, double inverseCumAccuracy)	Creates a Pareto distribution.
	TDistribution(double degreesOfFreedom)	Create a t distribution using the given degrees of freedom.
	TDistribution(double degreesOfFreedom, double inverseCumAccuracy)	Create a t distribution using the given degrees of freedom and the specified inverse cumulative probability absolute accuracy.
	TriangularDistribution(double a, double c, double b)	Creates a triangular real distribution using the given lower limit, upper limit, and mode.
	UniformRealDistribution(double lower, double upper)	Create a uniform real distribution using the given lower and upper bounds.
	WeibullDistribution(double alpha, double beta)	Create a Weibull distribution with the given shape and scale.

Uses of MathIllegalArgumentException in org.hipparchus.distribution.discrete

Methods in org.hipparchus.distribution.discrete that throw MathIllegalArgumentException

Modifier and Type	Method	Description
int	AbstractIntegerDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
int	GeometricDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
double	AbstractIntegerDistribution.probability(int x0, int x1)	For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).

Constructors in org.hipparchus.distribution.discrete that throw MathIllegalArgumentException

Modifier	Constructor	Description
	BinomialDistribution(int trials, double p)	Create a binomial distribution with the given number of trials and probability of success.
	EnumeratedIntegerDistribution(int[] singletons, double[] probabilities)	Create a discrete distribution using the given probability mass function definition.
	GeometricDistribution(double p)	Create a geometric distribution with the given probability of success.
	HypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize)	Construct a new hypergeometric distribution with the specified population size, number of successes in the population, and sample size.
	PascalDistribution(int r, double p)	Create a Pascal distribution with the given number of successes and probability of success.
	PoissonDistribution(double p)	Creates a new Poisson distribution with specified mean.
	PoissonDistribution(double p, double epsilon)	Creates a new Poisson distribution with the specified mean and convergence criterion.
	PoissonDistribution(double p, double epsilon, int maxIterations)	Creates a new Poisson distribution with specified mean, convergence criterion and maximum number of iterations.
	UniformIntegerDistribution(int lower, int upper)	Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).
	ZipfDistribution(int numberOfElements, double exponent)	Create a new Zipf distribution with the given number of elements and exponent.

Uses of MathIllegalArgumentException in org.hipparchus.distribution.multivariate

Methods in org.hipparchus.distribution.multivariate that throw MathIllegalArgumentException

Modifier and Type	Method	Description
double	MultivariateNormalDistribution.density(double[] vals)	Returns the probability density function (PDF) of this distribution evaluated at the specified point x.

Constructors in org.hipparchus.distribution.multivariate that throw MathIllegalArgumentException

Modifier	Constructor	Description
	MixtureMultivariateNormalDistribution(RandomGenerator rng, List<Pair<Double,MultivariateNormalDistribution>> components)	Creates a mixture model from a list of distributions and their associated weights.
	MultivariateNormalDistribution(double[] means, double[][] covariances)	Creates a multivariate normal distribution with the given mean vector and covariance matrix. The number of dimensions is equal to the length of the mean vector and to the number of rows and columns of the covariance matrix.
	MultivariateNormalDistribution(double[] means, double[][] covariances, double singularMatrixCheckTolerance)	Creates a multivariate normal distribution with the given mean vector and covariance matrix. The number of dimensions is equal to the length of the mean vector and to the number of rows and columns of the covariance matrix.
	MultivariateNormalDistribution(RandomGenerator rng, double[] means, double[][] covariances, double singularMatrixCheckTolerance)	Creates a multivariate normal distribution with the given mean vector and covariance matrix.

Uses of MathIllegalArgumentException in org.hipparchus.filtering.kalman

Methods in org.hipparchus.filtering.kalman that throw MathIllegalArgumentException

Modifier and Type	Method	Description
protected void	AbstractKalmanFilter.correct(T measurement, RealMatrix stm, RealVector innovation, RealMatrix h, RealMatrix s)	Perform correction step.

Uses of MathIllegalArgumentException in org.hipparchus.fraction

Methods in org.hipparchus.fraction that throw MathIllegalArgumentException

Modifier and Type	Method	Description
StringBuffer	FractionFormat.format(Object obj, StringBuffer toAppendTo, FieldPosition pos)	Formats an object and appends the result to a StringBuffer.

Constructors in org.hipparchus.fraction that throw MathIllegalArgumentException

Modifier	Constructor	Description
	BigFraction(double value)	Create a fraction given the double value.

Uses of MathIllegalArgumentException in org.hipparchus.geometry

Methods in org.hipparchus.geometry that throw MathIllegalArgumentException

Modifier and Type	Method	Description
default V	Vector.blendArithmeticallyWith(Vector<S,V> other, double blendingValue)	Blend arithmetically this instance with another one.

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

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

Modifier and Type	Method	Description
FieldVector3D<T>	FieldVector3D.blendArithmeticallyWith(FieldVector3D<T> other, T blendingValue)	Blend arithmetically this instance with another one.
void	FieldLine.reset(FieldVector3D<T> p1, FieldVector3D<T> p2)	Reset the instance as if built from two points.
void	Line.reset(Vector3D p1, Vector3D p2)	Reset the instance as if built from two points.

Constructors in org.hipparchus.geometry.euclidean.threed that throw MathIllegalArgumentException

Modifier	Constructor	Description
	FieldLine(FieldVector3D<T> p1, FieldVector3D<T> p2, double tolerance)	Build a line from two points.
	FieldRotation(FieldVector3D<T> axis, T angle, RotationConvention convention)	Build a rotation from an axis and an angle.
	FieldRotation(T[][] m, double threshold)	Build a rotation from a 3X3 matrix.
	FieldVector3D(T[] v)	Simple constructor.
	Line(Vector3D p1, Vector3D p2, double tolerance)	Build a line from two points.
	Rotation(double[][] m, double threshold)	Build a rotation from a 3X3 matrix.
	Rotation(Vector3D axis, double angle, RotationConvention convention)	Build a rotation from an axis and an angle.
	SubLine(Segment segment)	Create a sub-line from a segment.
	SubLine(Vector3D start, Vector3D end, double tolerance)	Create a sub-line from two endpoints.
	Vector3D(double[] v)	Simple constructor.

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

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

Modifier and Type	Method	Description
static Transform<Euclidean2D,Euclidean1D>	Line.getTransform(double cXX, double cYX, double cXY, double cYY, double cX1, double cY1)	Get a Transform embedding an affine transform.

Constructors in org.hipparchus.geometry.euclidean.twod that throw MathIllegalArgumentException

Modifier	Constructor	Description
	FieldVector2D(T[] v)	Simple constructor.
	Vector2D(double[] v)	Simple constructor.

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

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

Modifier and Type	Method	Description
Region<Euclidean2D>	ConvexHull2D.createRegion()	Returns a new region that is enclosed by the convex hull.

Constructors in org.hipparchus.geometry.euclidean.twod.hull that throw MathIllegalArgumentException

Modifier	Constructor	Description
	ConvexHull2D(Vector2D[] vertices, double tolerance)	Simple constructor.

Uses of MathIllegalArgumentException in org.hipparchus.geometry.hull

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

Modifier and Type	Method	Description
Region<S>	ConvexHull.createRegion()	Returns a new region that is enclosed by the convex hull.

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

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

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

Methods in org.hipparchus.geometry.spherical.oned that throw MathIllegalArgumentException

Modifier and Type	Method	Description
static void	Sphere1D.checkTolerance(double tolerance)	Check tolerance against Sphere1D.SMALLEST_TOLERANCE.

Constructors in org.hipparchus.geometry.spherical.oned that throw MathIllegalArgumentException

Modifier	Constructor	Description
	Arc(double lower, double upper, double tolerance)	Simple constructor.
	ArcsSet(double tolerance)	Build an arcs set representing the whole circle.
	ArcsSet(double lower, double upper, double tolerance)	Build an arcs set corresponding to a single arc.
	ArcsSet(Collection<SubHyperplane<Sphere1D>> boundary, double tolerance)	Build an arcs set from a Boundary REPresentation (B-rep).
	ArcsSet(BSPTree<Sphere1D> tree, double tolerance)	Build an arcs set from an inside/outside BSP tree.
	LimitAngle(S1Point location, boolean direct, double tolerance)	Simple constructor.

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

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

Modifier and Type	Method	Description
static void	Sphere2D.checkTolerance(double tolerance)	Check tolerance against Sphere2D.SMALLEST_TOLERANCE.

Constructors in org.hipparchus.geometry.spherical.twod that throw MathIllegalArgumentException

Modifier	Constructor	Description
	Circle(Vector3D pole, double tolerance)	Build a great circle from its pole.
	Circle(S2Point first, S2Point second, double tolerance)	Build a great circle from two non-aligned points.
	S2Point(double theta, double phi)	Simple constructor.
	SphericalPolygonsSet(double tolerance)	Build a polygons set representing the whole real 2-sphere.
	SphericalPolygonsSet(double hyperplaneThickness, S2Point... vertices)	Build a polygon from a simple list of vertices.
	SphericalPolygonsSet(Collection<SubHyperplane<Sphere2D>> boundary, double tolerance)	Build a polygons set from a Boundary REPresentation (B-rep).
	SphericalPolygonsSet(Vector3D pole, double tolerance)	Build a polygons set representing a hemisphere.
	SphericalPolygonsSet(Vector3D center, Vector3D meridian, double outsideRadius, int n, double tolerance)	Build a polygons set representing a regular polygon.
	SphericalPolygonsSet(BSPTree<Sphere2D> tree, double tolerance)	Build a polygons set from a BSP tree.

Uses of MathIllegalArgumentException in org.hipparchus.linear

Methods in org.hipparchus.linear that throw MathIllegalArgumentException

Modifier and Type	Method	Description
FieldMatrix<T>	AbstractFieldMatrix.add(FieldMatrix<T> m)	Compute the sum of this and m.
RealMatrix	AbstractRealMatrix.add(RealMatrix m)	Returns the sum of this and m.
Array2DRowFieldMatrix<T>	Array2DRowFieldMatrix.add(Array2DRowFieldMatrix<T> m)	Add m to this matrix.
Array2DRowRealMatrix	Array2DRowRealMatrix.add(Array2DRowRealMatrix m)	Compute the sum of this and m.
ArrayFieldVector<T>	ArrayFieldVector.add(ArrayFieldVector<T> v)	Compute the sum of this and v.
FieldVector<T>	ArrayFieldVector.add(FieldVector<T> v)	Compute the sum of this and v.
ArrayRealVector	ArrayRealVector.add(RealVector v)	Compute the sum of this vector and v.
BlockFieldMatrix<T>	BlockFieldMatrix.add(BlockFieldMatrix<T> m)	Compute the sum of this and m.
FieldMatrix<T>	BlockFieldMatrix.add(FieldMatrix<T> m)	Compute the sum of this and m.
BlockRealMatrix	BlockRealMatrix.add(BlockRealMatrix m)	Compute the sum of this matrix and m.
BlockRealMatrix	BlockRealMatrix.add(RealMatrix m)	Returns the sum of this and m.
DiagonalMatrix	DiagonalMatrix.add(DiagonalMatrix m)	Compute the sum of this and m.
FieldMatrix<T>	FieldMatrix.add(FieldMatrix<T> m)	Compute the sum of this and m.
FieldVector<T>	FieldVector.add(FieldVector<T> v)	Compute the sum of this and v.
OpenMapRealMatrix	OpenMapRealMatrix.add(OpenMapRealMatrix m)	Compute the sum of this matrix and m.
OpenMapRealVector	OpenMapRealVector.add(OpenMapRealVector v)	Optimized method to add two OpenMapRealVectors.
RealVector	OpenMapRealVector.add(RealVector v)	Compute the sum of this vector and v.
RealMatrix	RealMatrix.add(RealMatrix m)	Returns the sum of this and m.
RealVector	RealVector.add(RealVector v)	Compute the sum of this vector and v.
FieldVector<T>	SparseFieldVector.add(FieldVector<T> v)	Compute the sum of this and v.
FieldVector<T>	SparseFieldVector.add(SparseFieldVector<T> v)	Optimized method to add sparse vectors.
abstract void	AbstractFieldMatrix.addToEntry(int row, int column, T increment)	Change an entry in the specified row and column.
void	AbstractRealMatrix.addToEntry(int row, int column, double increment)	Adds (in place) the specified value to the specified entry of this matrix.
void	Array2DRowFieldMatrix.addToEntry(int row, int column, T increment)	Change an entry in the specified row and column.
void	Array2DRowRealMatrix.addToEntry(int row, int column, double increment)	Adds (in place) the specified value to the specified entry of this matrix.
void	ArrayRealVector.addToEntry(int index, double increment)	Change an entry at the specified index.
void	BlockFieldMatrix.addToEntry(int row, int column, T increment)	Change an entry in the specified row and column.
void	BlockRealMatrix.addToEntry(int row, int column, double increment)	Adds (in place) the specified value to the specified entry of this matrix.
void	DiagonalMatrix.addToEntry(int row, int column, double increment)	Adds (in place) the specified value to the specified entry of this matrix.
void	FieldMatrix.addToEntry(int row, int column, T increment)	Change an entry in the specified row and column.
void	OpenMapRealMatrix.addToEntry(int row, int column, double increment)	Adds (in place) the specified value to the specified entry of this matrix.
void	RealMatrix.addToEntry(int row, int column, double increment)	Adds (in place) the specified value to the specified entry of this matrix.
void	RealVector.addToEntry(int index, double increment)	Change an entry at the specified index.
protected void	AbstractFieldMatrix.checkAdditionCompatible(FieldMatrix<T> m)	Check if a matrix is addition compatible with the instance.
static void	MatrixUtils.checkAdditionCompatible(AnyMatrix left, AnyMatrix right)	Check if matrices are addition compatible.
protected void	AbstractFieldMatrix.checkColumnIndex(int column)	Check if a column index is valid.
static void	MatrixUtils.checkColumnIndex(AnyMatrix m, int column)	Check if a column index is valid.
protected void	RealVector.checkIndex(int index)	Check if an index is valid.
protected void	RealVector.checkIndices(int start, int end)	Checks that the indices of a subvector are valid.
static void	MatrixUtils.checkMatrixIndex(AnyMatrix m, int row, int column)	Check if matrix indices are valid.
protected void	AbstractFieldMatrix.checkMultiplicationCompatible(FieldMatrix<T> m)	Check if a matrix is multiplication compatible with the instance.
static void	MatrixUtils.checkMultiplicationCompatible(AnyMatrix left, AnyMatrix right)	Check if matrices are multiplication compatible
protected static void	IterativeLinearSolver.checkParameters(RealLinearOperator a, RealVector b, RealVector x0)	Performs all dimension checks on the parameters of solve and solveInPlace, and throws an exception if one of the checks fails.
protected static void	PreconditionedIterativeLinearSolver.checkParameters(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)	Performs all dimension checks on the parameters of solve and solveInPlace, and throws an exception if one of the checks fails.
protected void	AbstractFieldMatrix.checkRowIndex(int row)	Check if a row index is valid.
static void	MatrixUtils.checkRowIndex(AnyMatrix m, int row)	Check if a row index is valid.
static void	MatrixUtils.checkSameColumnDimension(AnyMatrix left, AnyMatrix right)	Check if matrices have the same number of columns.
static void	MatrixUtils.checkSameRowDimension(AnyMatrix left, AnyMatrix right)	Check if matrices have the same number of rows.
protected void	AbstractFieldMatrix.checkSubMatrixIndex(int[] selectedRows, int[] selectedColumns)	Check if submatrix ranges indices are valid.
protected void	AbstractFieldMatrix.checkSubMatrixIndex(int startRow, int endRow, int startColumn, int endColumn)	Check if submatrix ranges indices are valid.
static void	MatrixUtils.checkSubMatrixIndex(AnyMatrix m, int[] selectedRows, int[] selectedColumns)	Check if submatrix ranges indices are valid.
static void	MatrixUtils.checkSubMatrixIndex(AnyMatrix m, int startRow, int endRow, int startColumn, int endColumn)	Check if submatrix ranges indices are valid.
protected void	AbstractFieldMatrix.checkSubtractionCompatible(FieldMatrix<T> m)	Check if a matrix is subtraction compatible with the instance.
static void	MatrixUtils.checkSubtractionCompatible(AnyMatrix left, AnyMatrix right)	Check if matrices are subtraction compatible
protected void	ArrayFieldVector.checkVectorDimensions(int n)	Check if instance dimension is equal to some expected value.
protected void	ArrayFieldVector.checkVectorDimensions(FieldVector<T> v)	Check if instance and specified vectors have the same dimension.
protected void	ArrayRealVector.checkVectorDimensions(int n)	Check if instance dimension is equal to some expected value.
protected void	ArrayRealVector.checkVectorDimensions(RealVector v)	Check if instance and specified vectors have the same dimension.
protected void	RealVector.checkVectorDimensions(int n)	Check if instance dimension is equal to some expected value.
protected void	RealVector.checkVectorDimensions(RealVector v)	Check if instance and specified vectors have the same dimension.
protected void	SparseFieldVector.checkVectorDimensions(int n)	Check if instance dimension is equal to some expected value.
ArrayRealVector	ArrayRealVector.combine(double a, double b, RealVector y)	Returns a new vector representing a * this + b * y, the linear combination of this and y.
RealVector	RealVector.combine(double a, double b, RealVector y)	Returns a new vector representing a * this + b * y, the linear combination of this and y.
ArrayRealVector	ArrayRealVector.combineToSelf(double a, double b, RealVector y)	Updates this with the linear combination of this and y.
RealVector	RealVector.combineToSelf(double a, double b, RealVector y)	Updates this with the linear combination of this and y.
void	AbstractFieldMatrix.copySubMatrix(int[] selectedRows, int[] selectedColumns, T[][] destination)	Copy a submatrix.
void	AbstractFieldMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination)	Copy a submatrix.
void	AbstractRealMatrix.copySubMatrix(int[] selectedRows, int[] selectedColumns, double[][] destination)	Copy a submatrix.
void	AbstractRealMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination)	Copy a submatrix.
void	FieldMatrix.copySubMatrix(int[] selectedRows, int[] selectedColumns, T[][] destination)	Copy a submatrix.
void	FieldMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination)	Copy a submatrix.
void	RealMatrix.copySubMatrix(int[] selectedRows, int[] selectedColumns, double[][] destination)	Copy a submatrix.
void	RealMatrix.copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination)	Copy a submatrix.
double	RealVector.cosine(RealVector v)	Computes the cosine of the angle between this vector and the argument.
static JacobiPreconditioner	JacobiPreconditioner.create(RealLinearOperator a)	Creates a new instance of this class.
static <T extends FieldElement<T>> FieldMatrix<T>	MatrixUtils.createColumnFieldMatrix(T[] columnData)	Creates a column FieldMatrix using the data from the input array.
static RealMatrix	MatrixUtils.createColumnRealMatrix(double[] columnData)	Creates a column RealMatrix using the data from the input array.
static <T extends FieldElement<T>> FieldMatrix<T>	MatrixUtils.createFieldMatrix(T[][] data)	Returns a FieldMatrix whose entries are the the values in the the input array.
static <T extends FieldElement<T>> FieldVector<T>	MatrixUtils.createFieldVector(T[] data)	Creates a FieldVector using the data from the input array.
abstract FieldMatrix<T>	AbstractFieldMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new FieldMatrix of the same type as the instance with the supplied row and column dimensions.
abstract RealMatrix	AbstractRealMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
FieldMatrix<T>	Array2DRowFieldMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new FieldMatrix of the same type as the instance with the supplied row and column dimensions.
RealMatrix	Array2DRowRealMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
FieldMatrix<T>	BlockFieldMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new FieldMatrix of the same type as the instance with the supplied row and column dimensions.
BlockRealMatrix	BlockRealMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
RealMatrix	DiagonalMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
FieldMatrix<T>	FieldMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new FieldMatrix of the same type as the instance with the supplied row and column dimensions.
OpenMapRealMatrix	OpenMapRealMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
RealMatrix	RealMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
static RealMatrix	MatrixUtils.createRealMatrix(double[][] data)	Returns a RealMatrix whose entries are the the values in the the input array.
static RealVector	MatrixUtils.createRealVector(double[] data)	Creates a RealVector using the data from the input array.
static <T extends FieldElement<T>> FieldMatrix<T>	MatrixUtils.createRowFieldMatrix(T[] rowData)	Create a row FieldMatrix using the data from the input array.
static RealMatrix	MatrixUtils.createRowRealMatrix(double[] rowData)	Create a row RealMatrix using the data from the input array.
FieldDecompositionSolver<T>	FieldMatrixDecomposer.decompose(FieldMatrix<T> a)	Get a solver for finding the A × X = B solution in least square sense.
DecompositionSolver	MatrixDecomposer.decompose(RealMatrix a)	Get a solver for finding the A × X = B solution in least square sense.
T	ArrayFieldVector.dotProduct(ArrayFieldVector<T> v)	Compute the dot product.
T	ArrayFieldVector.dotProduct(FieldVector<T> v)	Compute the dot product.
double	ArrayRealVector.dotProduct(RealVector v)	Compute the dot product of this vector with v.
T	FieldVector.dotProduct(FieldVector<T> v)	Compute the dot product.
double	RealVector.dotProduct(RealVector v)	Compute the dot product of this vector with v.
T	SparseFieldVector.dotProduct(FieldVector<T> v)	Compute the dot product.
ArrayFieldVector<T>	ArrayFieldVector.ebeDivide(ArrayFieldVector<T> v)	Element-by-element division.
FieldVector<T>	ArrayFieldVector.ebeDivide(FieldVector<T> v)	Element-by-element division.
ArrayRealVector	ArrayRealVector.ebeDivide(RealVector v)	Element-by-element division.
FieldVector<T>	FieldVector.ebeDivide(FieldVector<T> v)	Element-by-element division.
OpenMapRealVector	OpenMapRealVector.ebeDivide(RealVector v)	Element-by-element division.
abstract RealVector	RealVector.ebeDivide(RealVector v)	Element-by-element division.
FieldVector<T>	SparseFieldVector.ebeDivide(FieldVector<T> v)	Element-by-element division.
ArrayFieldVector<T>	ArrayFieldVector.ebeMultiply(ArrayFieldVector<T> v)	Element-by-element multiplication.
FieldVector<T>	ArrayFieldVector.ebeMultiply(FieldVector<T> v)	Element-by-element multiplication.
ArrayRealVector	ArrayRealVector.ebeMultiply(RealVector v)	Element-by-element multiplication.
FieldVector<T>	FieldVector.ebeMultiply(FieldVector<T> v)	Element-by-element multiplication.
OpenMapRealVector	OpenMapRealVector.ebeMultiply(RealVector v)	Element-by-element multiplication.
abstract RealVector	RealVector.ebeMultiply(RealVector v)	Element-by-element multiplication.
FieldVector<T>	SparseFieldVector.ebeMultiply(FieldVector<T> v)	Element-by-element multiplication.
protected static <T extends FieldElement<T>> Field<T>	AbstractFieldMatrix.extractField(T[] d)	Get the elements type from an array.
protected static <T extends FieldElement<T>> Field<T>	AbstractFieldMatrix.extractField(T[][] d)	Get the elements type from an array.
T[]	AbstractFieldMatrix.getColumn(int column)	Get the entries in column number col as an array.
double[]	AbstractRealMatrix.getColumn(int column)	Get the entries at the given column index as an array.
T[]	BlockFieldMatrix.getColumn(int column)	Get the entries in column number col as an array.
double[]	BlockRealMatrix.getColumn(int column)	Get the entries at the given column index as an array.
T[]	FieldMatrix.getColumn(int column)	Get the entries in column number col as an array.
double[]	RealMatrix.getColumn(int column)	Get the entries at the given column index as an array.
FieldMatrix<T>	AbstractFieldMatrix.getColumnMatrix(int column)	Get the entries in column number column as a column matrix.
RealMatrix	AbstractRealMatrix.getColumnMatrix(int column)	Get the entries at the given column index as a column matrix.
FieldMatrix<T>	BlockFieldMatrix.getColumnMatrix(int column)	Get the entries in column number column as a column matrix.
BlockRealMatrix	BlockRealMatrix.getColumnMatrix(int column)	Get the entries at the given column index as a column matrix.
FieldMatrix<T>	FieldMatrix.getColumnMatrix(int column)	Get the entries in column number column as a column matrix.
RealMatrix	RealMatrix.getColumnMatrix(int column)	Get the entries at the given column index as a column matrix.
FieldVector<T>	AbstractFieldMatrix.getColumnVector(int column)	Returns the entries in column number column as a vector.
RealVector	AbstractRealMatrix.getColumnVector(int column)	Get the entries at the given column index as a vector.
FieldVector<T>	BlockFieldMatrix.getColumnVector(int column)	Returns the entries in column number column as a vector.
RealVector	BlockRealMatrix.getColumnVector(int column)	Get the entries at the given column index as a vector.
FieldVector<T>	FieldMatrix.getColumnVector(int column)	Returns the entries in column number column as a vector.
RealVector	RealMatrix.getColumnVector(int column)	Get the entries at the given column index as a vector.
double	ArrayRealVector.getDistance(RealVector v)	Distance between two vectors.
double	OpenMapRealVector.getDistance(OpenMapRealVector v)	Optimized method to compute distance.
double	OpenMapRealVector.getDistance(RealVector v)	Distance between two vectors.
double	RealVector.getDistance(RealVector v)	Distance between two vectors.
abstract T	AbstractFieldMatrix.getEntry(int row, int column)	Returns the entry in the specified row and column.
abstract double	AbstractRealMatrix.getEntry(int row, int column)	Get the entry in the specified row and column.
T	Array2DRowFieldMatrix.getEntry(int row, int column)	Returns the entry in the specified row and column.
double	Array2DRowRealMatrix.getEntry(int row, int column)	Get the entry in the specified row and column.
double	ArrayRealVector.getEntry(int index)	Return the entry at the specified index.
T	BlockFieldMatrix.getEntry(int row, int column)	Returns the entry in the specified row and column.
double	BlockRealMatrix.getEntry(int row, int column)	Get the entry in the specified row and column.
double	DiagonalMatrix.getEntry(int row, int column)	Get the entry in the specified row and column.
T	FieldMatrix.getEntry(int row, int column)	Returns the entry in the specified row and column.
T	FieldVector.getEntry(int index)	Returns the entry in the specified index.
double	OpenMapRealMatrix.getEntry(int row, int column)	Get the entry in the specified row and column.
double	OpenMapRealVector.getEntry(int index)	Return the entry at the specified index.
double	RealMatrix.getEntry(int row, int column)	Get the entry in the specified row and column.
abstract double	RealVector.getEntry(int index)	Return the entry at the specified index.
T	SparseFieldVector.getEntry(int index)	Returns the entry in the specified index.
RealMatrix	DecompositionSolver.getInverse()	Get the pseudo-inverse of the decomposed matrix.
double	ArrayRealVector.getL1Distance(RealVector v)	Distance between two vectors.
double	OpenMapRealVector.getL1Distance(OpenMapRealVector v)	Distance between two vectors.
double	OpenMapRealVector.getL1Distance(RealVector v)	Distance between two vectors.
double	RealVector.getL1Distance(RealVector v)	Distance between two vectors.
double	ArrayRealVector.getLInfDistance(RealVector v)	Distance between two vectors.
double	OpenMapRealVector.getLInfDistance(RealVector v)	Distance between two vectors.
double	RealVector.getLInfDistance(RealVector v)	Distance between two vectors.
T[]	AbstractFieldMatrix.getRow(int row)	Get the entries in row number row as an array.
double[]	AbstractRealMatrix.getRow(int row)	Get the entries at the given row index.
T[]	Array2DRowFieldMatrix.getRow(int row)	Get the entries in row number row as an array.
double[]	Array2DRowRealMatrix.getRow(int row)	Get the entries at the given row index.
T[]	BlockFieldMatrix.getRow(int row)	Get the entries in row number row as an array.
double[]	BlockRealMatrix.getRow(int row)	Get the entries at the given row index.
T[]	FieldMatrix.getRow(int row)	Get the entries in row number row as an array.
double[]	RealMatrix.getRow(int row)	Get the entries at the given row index.
FieldMatrix<T>	AbstractFieldMatrix.getRowMatrix(int row)	Get the entries in row number row as a row matrix.
RealMatrix	AbstractRealMatrix.getRowMatrix(int row)	Get the entries at the given row index as a row matrix.
FieldMatrix<T>	BlockFieldMatrix.getRowMatrix(int row)	Get the entries in row number row as a row matrix.
BlockRealMatrix	BlockRealMatrix.getRowMatrix(int row)	Get the entries at the given row index as a row matrix.
FieldMatrix<T>	FieldMatrix.getRowMatrix(int row)	Get the entries in row number row as a row matrix.
RealMatrix	RealMatrix.getRowMatrix(int row)	Get the entries at the given row index as a row matrix.
FieldVector<T>	AbstractFieldMatrix.getRowVector(int row)	Get the entries in row number row as a vector.
RealVector	AbstractRealMatrix.getRowVector(int row)	Returns the entries in row number row as a vector.
FieldVector<T>	BlockFieldMatrix.getRowVector(int row)	Get the entries in row number row as a vector.
RealVector	BlockRealMatrix.getRowVector(int row)	Returns the entries in row number row as a vector.
FieldVector<T>	FieldMatrix.getRowVector(int row)	Get the entries in row number row as a vector.
RealVector	RealMatrix.getRowVector(int row)	Returns the entries in row number row as a vector.
FieldMatrix<T>	AbstractFieldMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Get a submatrix.
FieldMatrix<T>	AbstractFieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Get a submatrix.
RealMatrix	AbstractRealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Gets a submatrix.
RealMatrix	AbstractRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Gets a submatrix.
FieldMatrix<T>	Array2DRowFieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Get a submatrix.
RealMatrix	Array2DRowRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Gets a submatrix.
FieldMatrix<T>	BlockFieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Get a submatrix.
BlockRealMatrix	BlockRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Gets a submatrix.
FieldMatrix<T>	FieldMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Get a submatrix.
FieldMatrix<T>	FieldMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Get a submatrix.
RealMatrix	RealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Gets a submatrix.
RealMatrix	RealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Gets a submatrix.
FieldVector<T>	ArrayFieldVector.getSubVector(int index, int n)	Get a subvector from consecutive elements.
RealVector	ArrayRealVector.getSubVector(int index, int n)	Get a subvector from consecutive elements.
FieldVector<T>	FieldVector.getSubVector(int index, int n)	Get a subvector from consecutive elements.
OpenMapRealVector	OpenMapRealVector.getSubVector(int index, int n)	Get a subvector from consecutive elements.
abstract RealVector	RealVector.getSubVector(int index, int n)	Get a subvector from consecutive elements.
FieldVector<T>	SparseFieldVector.getSubVector(int index, int n)	Get a subvector from consecutive elements.
T	AbstractFieldMatrix.getTrace()	Returns the trace of the matrix (the sum of the elements on the main diagonal).
double	AbstractRealMatrix.getTrace()	Returns the trace of the matrix (the sum of the elements on the main diagonal).
T	FieldMatrix.getTrace()	Returns the trace of the matrix (the sum of the elements on the main diagonal).
double	RealMatrix.getTrace()	Returns the trace of the matrix (the sum of the elements on the main diagonal).
DiagonalMatrix	DiagonalMatrix.inverse()	Computes the inverse of this diagonal matrix.
DiagonalMatrix	DiagonalMatrix.inverse(double threshold)	Computes the inverse of this diagonal matrix.
static RealMatrix	MatrixUtils.inverse(RealMatrix matrix)	Computes the inverse of the given matrix.
static RealMatrix	MatrixUtils.inverse(RealMatrix matrix, double threshold)	Computes the inverse of the given matrix.
FieldMatrix<T>	AbstractFieldMatrix.multiply(FieldMatrix<T> m)	Postmultiply this matrix by m.
RealMatrix	AbstractRealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
Array2DRowFieldMatrix<T>	Array2DRowFieldMatrix.multiply(Array2DRowFieldMatrix<T> m)	Postmultiplying this matrix by m.
Array2DRowRealMatrix	Array2DRowRealMatrix.multiply(Array2DRowRealMatrix m)	Returns the result of postmultiplying this by m.
BlockFieldMatrix<T>	BlockFieldMatrix.multiply(BlockFieldMatrix<T> m)	Returns the result of postmultiplying this by m.
FieldMatrix<T>	BlockFieldMatrix.multiply(FieldMatrix<T> m)	Postmultiply this matrix by m.
BlockRealMatrix	BlockRealMatrix.multiply(BlockRealMatrix m)	Returns the result of postmultiplying this by m.
BlockRealMatrix	BlockRealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
DiagonalMatrix	DiagonalMatrix.multiply(DiagonalMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	DiagonalMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
FieldMatrix<T>	FieldMatrix.multiply(FieldMatrix<T> m)	Postmultiply this matrix by m.
OpenMapRealMatrix	OpenMapRealMatrix.multiply(OpenMapRealMatrix m)	Postmultiply this matrix by m.
RealMatrix	OpenMapRealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	RealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
abstract void	AbstractFieldMatrix.multiplyEntry(int row, int column, T factor)	Change an entry in the specified row and column.
void	AbstractRealMatrix.multiplyEntry(int row, int column, double factor)	Multiplies (in place) the specified entry of this matrix by the specified value.
void	Array2DRowFieldMatrix.multiplyEntry(int row, int column, T factor)	Change an entry in the specified row and column.
void	Array2DRowRealMatrix.multiplyEntry(int row, int column, double factor)	Multiplies (in place) the specified entry of this matrix by the specified value.
void	BlockFieldMatrix.multiplyEntry(int row, int column, T factor)	Change an entry in the specified row and column.
void	BlockRealMatrix.multiplyEntry(int row, int column, double factor)	Multiplies (in place) the specified entry of this matrix by the specified value.
void	DiagonalMatrix.multiplyEntry(int row, int column, double factor)	Multiplies (in place) the specified entry of this matrix by the specified value.
void	FieldMatrix.multiplyEntry(int row, int column, T factor)	Change an entry in the specified row and column.
void	OpenMapRealMatrix.multiplyEntry(int row, int column, double factor)	Multiplies (in place) the specified entry of this matrix by the specified value.
void	RealMatrix.multiplyEntry(int row, int column, double factor)	Multiplies (in place) the specified entry of this matrix by the specified value.
FieldMatrix<T>	Array2DRowFieldMatrix.multiplyTransposed(Array2DRowFieldMatrix<T> m)	Returns the result of postmultiplying this by m^T.
RealMatrix	Array2DRowRealMatrix.multiplyTransposed(Array2DRowRealMatrix m)	Returns the result of postmultiplying this by m^T.
BlockFieldMatrix<T>	BlockFieldMatrix.multiplyTransposed(BlockFieldMatrix<T> m)	Returns the result of postmultiplying this by m^T.
BlockFieldMatrix<T>	BlockFieldMatrix.multiplyTransposed(FieldMatrix<T> m)	Returns the result of postmultiplying this by m^T.
BlockRealMatrix	BlockRealMatrix.multiplyTransposed(BlockRealMatrix m)	Returns the result of postmultiplying this by m^T.
BlockRealMatrix	BlockRealMatrix.multiplyTransposed(RealMatrix m)	Returns the result of postmultiplying this by m^T.
DiagonalMatrix	DiagonalMatrix.multiplyTransposed(DiagonalMatrix m)	Returns the result of postmultiplying this by m^T.
RealMatrix	DiagonalMatrix.multiplyTransposed(RealMatrix m)	Returns the result of postmultiplying this by m^T.
default FieldMatrix<T>	FieldMatrix.multiplyTransposed(FieldMatrix<T> m)	Returns the result of postmultiplying this by m^T.
RealMatrix	OpenMapRealMatrix.multiplyTransposed(RealMatrix m)	Returns the result of postmultiplying this by m^T.
default RealMatrix	RealMatrix.multiplyTransposed(RealMatrix m)	Returns the result of postmultiplying this by m^T.
FieldMatrix<T>	SparseFieldMatrix.multiplyTransposed(FieldMatrix<T> m)	Returns the result of postmultiplying this by m^T.
FieldVector<T>	AbstractFieldMatrix.operate(FieldVector<T> v)	Returns the result of multiplying this by the vector v.
T[]	AbstractFieldMatrix.operate(T[] v)	Returns the result of multiplying this by the vector v.
double[]	AbstractRealMatrix.operate(double[] v)	Returns the result of multiplying this by the vector v.
RealVector	AbstractRealMatrix.operate(RealVector v)	Returns the result of multiplying this by the vector v.
T[]	Array2DRowFieldMatrix.operate(T[] v)	Returns the result of multiplying this by the vector v.
double[]	Array2DRowRealMatrix.operate(double[] v)	Returns the result of multiplying this by the vector v.
T[]	BlockFieldMatrix.operate(T[] v)	Returns the result of multiplying this by the vector v.
double[]	BlockRealMatrix.operate(double[] v)	Returns the result of multiplying this by the vector v.
double[]	DiagonalMatrix.operate(double[] v)	Returns the result of multiplying this by the vector v.
FieldVector<T>	FieldMatrix.operate(FieldVector<T> v)	Returns the result of multiplying this by the vector v.
T[]	FieldMatrix.operate(T[] v)	Returns the result of multiplying this by the vector v.
RealVector	RealLinearOperator.operate(RealVector x)	Returns the result of multiplying this by the vector x.
double[]	RealMatrix.operate(double[] v)	Returns the result of multiplying this by the vector v.
RealVector	RealMatrix.operate(RealVector v)	Returns the result of multiplying this by the vector v.
default RealVector	RealLinearOperator.operateTranspose(RealVector x)	Returns the result of multiplying the transpose of this operator by the vector x (optional operation).
FieldMatrix<T>	AbstractFieldMatrix.power(int p)	Returns the result multiplying this with itself p times.
RealMatrix	AbstractRealMatrix.power(int p)	Returns the result of multiplying this with itself p times.
FieldMatrix<T>	FieldMatrix.power(int p)	Returns the result multiplying this with itself p times.
RealMatrix	RealMatrix.power(int p)	Returns the result of multiplying this with itself p times.
FieldMatrix<T>	AbstractFieldMatrix.preMultiply(FieldMatrix<T> m)	Premultiply this matrix by m.
FieldVector<T>	AbstractFieldMatrix.preMultiply(FieldVector<T> v)	Returns the (row) vector result of premultiplying this by the vector v.
T[]	AbstractFieldMatrix.preMultiply(T[] v)	Returns the (row) vector result of premultiplying this by the vector v.
double[]	AbstractRealMatrix.preMultiply(double[] v)	Returns the (row) vector result of premultiplying this by the vector v.
RealMatrix	AbstractRealMatrix.preMultiply(RealMatrix m)	Returns the result of premultiplying this by m.
RealVector	AbstractRealMatrix.preMultiply(RealVector v)	Returns the (row) vector result of premultiplying this by the vector v.
T[]	Array2DRowFieldMatrix.preMultiply(T[] v)	Returns the (row) vector result of premultiplying this by the vector v.
double[]	Array2DRowRealMatrix.preMultiply(double[] v)	Returns the (row) vector result of premultiplying this by the vector v.
T[]	BlockFieldMatrix.preMultiply(T[] v)	Returns the (row) vector result of premultiplying this by the vector v.
double[]	BlockRealMatrix.preMultiply(double[] v)	Returns the (row) vector result of premultiplying this by the vector v.
double[]	DiagonalMatrix.preMultiply(double[] v)	Returns the (row) vector result of premultiplying this by the vector v.
RealVector	DiagonalMatrix.preMultiply(RealVector v)	Returns the (row) vector result of premultiplying this by the vector v.
FieldMatrix<T>	FieldMatrix.preMultiply(FieldMatrix<T> m)	Premultiply this matrix by m.
FieldVector<T>	FieldMatrix.preMultiply(FieldVector<T> v)	Returns the (row) vector result of premultiplying this by the vector v.
T[]	FieldMatrix.preMultiply(T[] v)	Returns the (row) vector result of premultiplying this by the vector v.
double[]	RealMatrix.preMultiply(double[] v)	Returns the (row) vector result of premultiplying this by the vector v.
RealMatrix	RealMatrix.preMultiply(RealMatrix m)	Returns the result of premultiplying this by m.
RealVector	RealMatrix.preMultiply(RealVector v)	Returns the (row) vector result of premultiplying this by the vector v.
ArrayFieldVector<T>	ArrayFieldVector.projection(ArrayFieldVector<T> v)	Find the orthogonal projection of this vector onto another vector.
FieldVector<T>	ArrayFieldVector.projection(FieldVector<T> v)	Find the orthogonal projection of this vector onto another vector.
FieldVector<T>	FieldVector.projection(FieldVector<T> v)	Find the orthogonal projection of this vector onto another vector.
RealVector	RealVector.projection(RealVector v)	Find the orthogonal projection of this vector onto another vector.
FieldVector<T>	SparseFieldVector.projection(FieldVector<T> v)	Find the orthogonal projection of this vector onto another vector.
void	ArrayFieldVector.set(int index, ArrayFieldVector<T> v)	Set a set of consecutive elements.
void	AbstractFieldMatrix.setColumn(int column, T[] array)	Set the entries in column number column as a column matrix.
void	AbstractRealMatrix.setColumn(int column, double[] array)	Sets the specified column of this matrix to the entries of the specified array.
void	BlockFieldMatrix.setColumn(int column, T[] array)	Set the entries in column number column as a column matrix.
void	BlockRealMatrix.setColumn(int column, double[] array)	Sets the specified column of this matrix to the entries of the specified array.
void	FieldMatrix.setColumn(int column, T[] array)	Set the entries in column number column as a column matrix.
void	RealMatrix.setColumn(int column, double[] array)	Sets the specified column of this matrix to the entries of the specified array.
void	AbstractFieldMatrix.setColumnMatrix(int column, FieldMatrix<T> matrix)	Set the entries in column number column as a column matrix.
void	AbstractRealMatrix.setColumnMatrix(int column, RealMatrix matrix)	Sets the specified column of this matrix to the entries of the specified column matrix.
void	BlockFieldMatrix.setColumnMatrix(int column, FieldMatrix<T> matrix)	Set the entries in column number column as a column matrix.
void	BlockRealMatrix.setColumnMatrix(int column, RealMatrix matrix)	Sets the specified column of this matrix to the entries of the specified column matrix.
void	FieldMatrix.setColumnMatrix(int column, FieldMatrix<T> matrix)	Set the entries in column number column as a column matrix.
void	RealMatrix.setColumnMatrix(int column, RealMatrix matrix)	Sets the specified column of this matrix to the entries of the specified column matrix.
void	AbstractFieldMatrix.setColumnVector(int column, FieldVector<T> vector)	Set the entries in column number column as a vector.
void	AbstractRealMatrix.setColumnVector(int column, RealVector vector)	Sets the specified column of this matrix to the entries of the specified vector.
void	BlockFieldMatrix.setColumnVector(int column, FieldVector<T> vector)	Set the entries in column number column as a vector.
void	BlockRealMatrix.setColumnVector(int column, RealVector vector)	Sets the specified column of this matrix to the entries of the specified vector.
void	FieldMatrix.setColumnVector(int column, FieldVector<T> vector)	Set the entries in column number column as a vector.
void	RealMatrix.setColumnVector(int column, RealVector vector)	Sets the specified column of this matrix to the entries of the specified vector.
abstract void	AbstractFieldMatrix.setEntry(int row, int column, T value)	Set the entry in the specified row and column.
abstract void	AbstractRealMatrix.setEntry(int row, int column, double value)	Set the entry in the specified row and column.
void	Array2DRowFieldMatrix.setEntry(int row, int column, T value)	Set the entry in the specified row and column.
void	Array2DRowRealMatrix.setEntry(int row, int column, double value)	Set the entry in the specified row and column.
void	ArrayRealVector.setEntry(int index, double value)	Set a single element.
void	BlockFieldMatrix.setEntry(int row, int column, T value)	Set the entry in the specified row and column.
void	BlockRealMatrix.setEntry(int row, int column, double value)	Set the entry in the specified row and column.
void	DiagonalMatrix.setEntry(int row, int column, double value)	Set the entry in the specified row and column.
void	FieldMatrix.setEntry(int row, int column, T value)	Set the entry in the specified row and column.
void	FieldVector.setEntry(int index, T value)	Set a single element.
void	OpenMapRealMatrix.setEntry(int row, int column, double value)	Set the entry in the specified row and column.
void	OpenMapRealVector.setEntry(int index, double value)	Set a single element.
void	RealMatrix.setEntry(int row, int column, double value)	Set the entry in the specified row and column.
abstract void	RealVector.setEntry(int index, double value)	Set a single element.
void	SparseFieldVector.setEntry(int index, T value)	Set a single element.
void	AbstractFieldMatrix.setRow(int row, T[] array)	Set the entries in row number row as a row matrix.
void	AbstractRealMatrix.setRow(int row, double[] array)	Sets the specified row of this matrix to the entries of the specified array.
void	Array2DRowFieldMatrix.setRow(int row, T[] array)	Set the entries in row number row as a row matrix.
void	Array2DRowRealMatrix.setRow(int row, double[] array)	Sets the specified row of this matrix to the entries of the specified array.
void	BlockFieldMatrix.setRow(int row, T[] array)	Set the entries in row number row as a row matrix.
void	BlockRealMatrix.setRow(int row, double[] array)	Sets the specified row of this matrix to the entries of the specified array.
void	FieldMatrix.setRow(int row, T[] array)	Set the entries in row number row as a row matrix.
void	RealMatrix.setRow(int row, double[] array)	Sets the specified row of this matrix to the entries of the specified array.
void	AbstractFieldMatrix.setRowMatrix(int row, FieldMatrix<T> matrix)	Set the entries in row number row as a row matrix.
void	AbstractRealMatrix.setRowMatrix(int row, RealMatrix matrix)	Sets the specified row of this matrix to the entries of the specified row matrix.
void	BlockFieldMatrix.setRowMatrix(int row, BlockFieldMatrix<T> matrix)	Sets the entries in row number row as a row matrix.
void	BlockFieldMatrix.setRowMatrix(int row, FieldMatrix<T> matrix)	Set the entries in row number row as a row matrix.
void	BlockRealMatrix.setRowMatrix(int row, BlockRealMatrix matrix)	Sets the entries in row number row as a row matrix.
void	BlockRealMatrix.setRowMatrix(int row, RealMatrix matrix)	Sets the specified row of this matrix to the entries of the specified row matrix.
void	FieldMatrix.setRowMatrix(int row, FieldMatrix<T> matrix)	Set the entries in row number row as a row matrix.
void	RealMatrix.setRowMatrix(int row, RealMatrix matrix)	Sets the specified row of this matrix to the entries of the specified row matrix.
void	AbstractFieldMatrix.setRowVector(int row, FieldVector<T> vector)	Set the entries in row number row as a vector.
void	AbstractRealMatrix.setRowVector(int row, RealVector vector)	Sets the specified row of this matrix to the entries of the specified vector.
void	BlockFieldMatrix.setRowVector(int row, FieldVector<T> vector)	Set the entries in row number row as a vector.
void	BlockRealMatrix.setRowVector(int row, RealVector vector)	Sets the specified row of this matrix to the entries of the specified vector.
void	FieldMatrix.setRowVector(int row, FieldVector<T> vector)	Set the entries in row number row as a vector.
void	RealMatrix.setRowVector(int row, RealVector vector)	Sets the specified row of this matrix to the entries of the specified vector.
void	AbstractFieldMatrix.setSubMatrix(T[][] subMatrix, int row, int column)	Replace the submatrix starting at (row, column) using data in the input subMatrix array.
void	AbstractRealMatrix.setSubMatrix(double[][] subMatrix, int row, int column)	Replace the submatrix starting at row, column using data in the input subMatrix array.
void	Array2DRowFieldMatrix.setSubMatrix(T[][] subMatrix, int row, int column)	Replace the submatrix starting at (row, column) using data in the input subMatrix array.
void	Array2DRowRealMatrix.setSubMatrix(double[][] subMatrix, int row, int column)	Replace the submatrix starting at row, column using data in the input subMatrix array.
void	BlockFieldMatrix.setSubMatrix(T[][] subMatrix, int row, int column)	Replace the submatrix starting at (row, column) using data in the input subMatrix array.
void	BlockRealMatrix.setSubMatrix(double[][] subMatrix, int row, int column)	Replace the submatrix starting at row, column using data in the input subMatrix array.
void	FieldMatrix.setSubMatrix(T[][] subMatrix, int row, int column)	Replace the submatrix starting at (row, column) using data in the input subMatrix array.
void	RealMatrix.setSubMatrix(double[][] subMatrix, int row, int column)	Replace the submatrix starting at row, column using data in the input subMatrix array.
void	ArrayFieldVector.setSubVector(int index, FieldVector<T> v)	Set a set of consecutive elements.
void	ArrayRealVector.setSubVector(int index, double[] v)	Set a set of consecutive elements.
void	ArrayRealVector.setSubVector(int index, RealVector v)	Set a sequence of consecutive elements.
void	FieldVector.setSubVector(int index, FieldVector<T> v)	Set a set of consecutive elements.
void	OpenMapRealVector.setSubVector(int index, RealVector v)	Set a sequence of consecutive elements.
abstract void	RealVector.setSubVector(int index, RealVector v)	Set a sequence of consecutive elements.
void	SparseFieldVector.setSubVector(int index, FieldVector<T> v)	Set a set of consecutive elements.
RealMatrix	DecompositionSolver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealVector	DecompositionSolver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
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)	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, 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)	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	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)	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.
RealVector	SymmLQ.solveInPlace(RealLinearOperator a, RealVector b, RealVector x)	Returns an estimate of the solution to the linear system A · x = b.
static void	MatrixUtils.solveLowerTriangularSystem(RealMatrix rm, RealVector b)	Solve a system of composed of a Lower Triangular Matrix RealMatrix.
static void	MatrixUtils.solveUpperTriangularSystem(RealMatrix rm, RealVector b)	Solver a system composed of an Upper Triangular Matrix RealMatrix.
FieldMatrix<T>	AbstractFieldMatrix.subtract(FieldMatrix<T> m)	Subtract m from this matrix.
RealMatrix	AbstractRealMatrix.subtract(RealMatrix m)	Returns this minus m.
Array2DRowFieldMatrix<T>	Array2DRowFieldMatrix.subtract(Array2DRowFieldMatrix<T> m)	Subtract m from this matrix.
Array2DRowRealMatrix	Array2DRowRealMatrix.subtract(Array2DRowRealMatrix m)	Returns this minus m.
ArrayFieldVector<T>	ArrayFieldVector.subtract(ArrayFieldVector<T> v)	Compute this minus v.
FieldVector<T>	ArrayFieldVector.subtract(FieldVector<T> v)	Compute this minus v.
ArrayRealVector	ArrayRealVector.subtract(RealVector v)	Subtract v from this vector.
BlockFieldMatrix<T>	BlockFieldMatrix.subtract(BlockFieldMatrix<T> m)	Compute this - m.
FieldMatrix<T>	BlockFieldMatrix.subtract(FieldMatrix<T> m)	Subtract m from this matrix.
BlockRealMatrix	BlockRealMatrix.subtract(BlockRealMatrix m)	Subtract m from this matrix.
BlockRealMatrix	BlockRealMatrix.subtract(RealMatrix m)	Returns this minus m.
DiagonalMatrix	DiagonalMatrix.subtract(DiagonalMatrix m)	Returns this minus m.
FieldMatrix<T>	FieldMatrix.subtract(FieldMatrix<T> m)	Subtract m from this matrix.
FieldVector<T>	FieldVector.subtract(FieldVector<T> v)	Compute this minus v.
OpenMapRealMatrix	OpenMapRealMatrix.subtract(OpenMapRealMatrix m)	Subtract m from this matrix.
OpenMapRealMatrix	OpenMapRealMatrix.subtract(RealMatrix m)	Returns this minus m.
OpenMapRealVector	OpenMapRealVector.subtract(OpenMapRealVector v)	Optimized method to subtract OpenMapRealVectors.
RealVector	OpenMapRealVector.subtract(RealVector v)	Subtract v from this vector.
RealMatrix	RealMatrix.subtract(RealMatrix m)	Returns this minus m.
RealVector	RealVector.subtract(RealVector v)	Subtract v from this vector.
FieldVector<T>	SparseFieldVector.subtract(FieldVector<T> v)	Compute this minus v.
SparseFieldVector<T>	SparseFieldVector.subtract(SparseFieldVector<T> v)	Optimized method to compute this minus v.
static <T extends FieldElement<T>> T[][]	BlockFieldMatrix.toBlocksLayout(T[][] rawData)	Convert a data array from raw layout to blocks layout.
static double[][]	BlockRealMatrix.toBlocksLayout(double[][] rawData)	Convert a data array from raw layout to blocks layout.
FieldMatrix<T>	Array2DRowFieldMatrix.transposeMultiply(Array2DRowFieldMatrix<T> m)	Returns the result of postmultiplying this^T by m.
RealMatrix	Array2DRowRealMatrix.transposeMultiply(Array2DRowRealMatrix m)	Returns the result of postmultiplying this^T by m.
BlockFieldMatrix<T>	BlockFieldMatrix.transposeMultiply(BlockFieldMatrix<T> m)	Returns the result of postmultiplying this^T by m.
BlockFieldMatrix<T>	BlockFieldMatrix.transposeMultiply(FieldMatrix<T> m)	Returns the result of postmultiplying this^T by m.
BlockRealMatrix	BlockRealMatrix.transposeMultiply(BlockRealMatrix m)	Returns the result of postmultiplying this^T by m.
BlockRealMatrix	BlockRealMatrix.transposeMultiply(RealMatrix m)	Returns the result of postmultiplying this^T by m.
DiagonalMatrix	DiagonalMatrix.transposeMultiply(DiagonalMatrix m)	Returns the result of postmultiplying this^T by m.
default FieldMatrix<T>	FieldMatrix.transposeMultiply(FieldMatrix<T> m)	Returns the result of postmultiplying this^T by m.
RealMatrix	OpenMapRealMatrix.transposeMultiply(RealMatrix m)	Returns the result of postmultiplying this^T by m.
default RealMatrix	RealMatrix.transposeMultiply(RealMatrix m)	Returns the result of postmultiplying this^T by m.
FieldMatrix<T>	SparseFieldMatrix.transposeMultiply(FieldMatrix<T> m)	Returns the result of postmultiplying this^T by m.
T	AbstractFieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in column order.
T	AbstractFieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in column order.
double	AbstractRealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in column order.
double	AbstractRealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in column order.
T	Array2DRowFieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in column order.
T	Array2DRowFieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in column order.
double	Array2DRowRealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in column order.
double	Array2DRowRealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in column order.
T	FieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in column order.
T	FieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in column order.
double	RealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in column order.
double	RealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in column order.
T	ArrayFieldVector.walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)	Visits (and possibly alters) some entries of this vector in default order (increasing index).
T	ArrayFieldVector.walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)	Visits (but does not alter) some entries of this vector in default order (increasing index).
double	ArrayRealVector.walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end)	Visits (and possibly alters) some entries of this vector in default order (increasing index).
double	ArrayRealVector.walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end)	Visits (but does not alter) some entries of this vector in default order (increasing index).
double	RealVector.walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end)	Visits (and possibly alters) some entries of this vector in default order (increasing index).
double	RealVector.walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end)	Visits (but does not alter) some entries of this vector in default order (increasing index).
T	SparseFieldVector.walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)	Visits (and possibly alters) some entries of this vector in default order (increasing index).
T	SparseFieldVector.walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)	Visits (but does not alter) some entries of this vector in default order (increasing index).
T	AbstractFieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries using the fastest possible order.
T	AbstractFieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries using the fastest possible order.
double	AbstractRealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries using the fastest possible order.
double	AbstractRealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries using the fastest possible order.
T	ArrayFieldVector.walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)	Visits (and possibly change) some entries of this vector in optimized order.
T	ArrayFieldVector.walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)	Visits (but does not alter) some entries of this vector in optimized order.
double	ArrayRealVector.walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end)	Visits (and possibly change) some entries of this vector in optimized order.
double	ArrayRealVector.walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end)	Visits (but does not alter) some entries of this vector in optimized order.
T	BlockFieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries using the fastest possible order.
T	BlockFieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries using the fastest possible order.
double	BlockRealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries using the fastest possible order.
double	BlockRealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries using the fastest possible order.
T	FieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries using the fastest possible order.
T	FieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries using the fastest possible order.
double	RealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries using the fastest possible order.
double	RealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries using the fastest possible order.
double	RealVector.walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end)	Visits (and possibly change) some entries of this vector in optimized order.
double	RealVector.walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end)	Visits (but does not alter) some entries of this vector in optimized order.
T	SparseFieldVector.walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)	Visits (and possibly change) some entries of this vector in optimized order.
T	SparseFieldVector.walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)	Visits (but does not alter) some entries of this vector in optimized order.
T	AbstractFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in row order.
T	AbstractFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in row order.
double	AbstractRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in row order.
double	AbstractRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in row order.
T	Array2DRowFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in row order.
T	Array2DRowFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in row order.
double	Array2DRowRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in row order.
double	Array2DRowRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in row order.
T	BlockFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in row order.
T	BlockFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in row order.
double	BlockRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in row order.
double	BlockRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in row order.
T	FieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in row order.
T	FieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in row order.
double	RealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (and possibly change) some matrix entries in row order.
double	RealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)	Visit (but don't change) some matrix entries in row order.

Constructors in org.hipparchus.linear that throw MathIllegalArgumentException

Modifier	Constructor	Description
protected	AbstractFieldMatrix(Field<T> field, int rowDimension, int columnDimension)	Create a new FieldMatrix with the supplied row and column dimensions.
protected	AbstractRealMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix with the supplied row and column dimensions.
	Array2DRowFieldMatrix(Field<T> field, int rowDimension, int columnDimension)	Create a new FieldMatrix<T> with the supplied row and column dimensions.
	Array2DRowFieldMatrix(Field<T> field, T[][] d)	Create a new FieldMatrix<T> using the input array as the underlying data array.
	Array2DRowFieldMatrix(Field<T> field, T[][] d, boolean copyArray)	Create a new FieldMatrix<T> using the input array as the underlying data array.
	Array2DRowFieldMatrix(T[] v)	Create a new (column) FieldMatrix<T> using v as the data for the unique column of the created matrix.
	Array2DRowFieldMatrix(T[][] d)	Create a new FieldMatrix<T> using the input array as the underlying data array.
	Array2DRowFieldMatrix(T[][] d, boolean copyArray)	Create a new FieldMatrix<T> using the input array as the underlying data array.
	Array2DRowRealMatrix(double[][] d)	Create a new RealMatrix using the input array as the underlying data array.
	Array2DRowRealMatrix(double[][] d, boolean copyArray)	Create a new RealMatrix using the input array as the underlying data array.
	Array2DRowRealMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix with the supplied row and column dimensions.
	ArrayFieldVector(Field<T> field, T[] d, int pos, int size)	Construct a vector from part of a array.
	ArrayFieldVector(Field<T> field, T[] v1, T[] v2)	Construct a vector by appending one vector to another vector.
	ArrayFieldVector(T[] d)	Construct a vector from an array, copying the input array.
	ArrayFieldVector(T[] d, boolean copyArray)	Create a new ArrayFieldVector using the input array as the underlying data array.
	ArrayFieldVector(T[] d, int pos, int size)	Construct a vector from part of a array.
	ArrayFieldVector(T[] v1, T[] v2)	Construct a vector by appending one vector to another vector.
	ArrayRealVector(double[] d, int pos, int size)	Construct a vector from part of a array.
	ArrayRealVector(Double[] d, int pos, int size)	Construct a vector from part of an array.
	BlockFieldMatrix(int rows, int columns, T[][] blockData, boolean copyArray)	Create a new dense matrix copying entries from block layout data.
	BlockFieldMatrix(Field<T> field, int rows, int columns)	Create a new matrix with the supplied row and column dimensions.
	BlockFieldMatrix(T[][] rawData)	Create a new dense matrix copying entries from raw layout data.
	BlockRealMatrix(double[][] rawData)	Create a new dense matrix copying entries from raw layout data.
	BlockRealMatrix(int rows, int columns)	Create a new matrix with the supplied row and column dimensions.
	BlockRealMatrix(int rows, int columns, double[][] blockData, boolean copyArray)	Create a new dense matrix copying entries from block layout data.
	DiagonalMatrix(int dimension)	Creates a matrix with the supplied dimension.
	OpenMapRealMatrix(int rowDimension, int columnDimension)	Build a sparse matrix with the supplied row and column dimensions.
	RectangularCholeskyDecomposition(RealMatrix matrix)	Decompose a symmetric positive semidefinite matrix.
	RectangularCholeskyDecomposition(RealMatrix matrix, double small)	Decompose a symmetric positive semidefinite matrix.

Uses of MathIllegalArgumentException in org.hipparchus.migration.exception

Subclasses of MathIllegalArgumentException in org.hipparchus.migration.exception

Modifier and Type	Class	Description
class	DimensionMismatchException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	InsufficientDataException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	MathIllegalNumberException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	MultiDimensionMismatchException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NoBracketingException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NoDataException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NonMonotonicSequenceException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NotANumberException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NotFiniteNumberException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NotPositiveException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NotStrictlyPositiveException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NumberIsTooLargeException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NumberIsTooSmallException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	OutOfRangeException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	ZeroException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException

Uses of MathIllegalArgumentException in org.hipparchus.migration.genetics

Subclasses of MathIllegalArgumentException in org.hipparchus.migration.genetics

Modifier and Type	Class	Description
class	InvalidRepresentationException	Deprecated. as of 1.0, this exception is replaced by MathIllegalStateException

Uses of MathIllegalArgumentException in org.hipparchus.migration.geometry.euclidean.threed

Subclasses of MathIllegalArgumentException in org.hipparchus.migration.geometry.euclidean.threed

Modifier and Type	Class	Description
class	NotARotationMatrixException	Deprecated. as of 1.0, this exception is replaced by MathIllegalStateException

Uses of MathIllegalArgumentException in org.hipparchus.migration.linear

Subclasses of MathIllegalArgumentException in org.hipparchus.migration.linear

Modifier and Type	Class	Description
class	IllConditionedOperatorException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	MatrixDimensionMismatchException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NonPositiveDefiniteMatrixException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NonPositiveDefiniteOperatorException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NonSelfAdjointOperatorException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NonSquareMatrixException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NonSquareOperatorException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	NonSymmetricMatrixException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException
class	SingularMatrixException	Deprecated. as of 1.0, this exception is replaced by MathIllegalStateException
class	SingularOperatorException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException

Uses of MathIllegalArgumentException in org.hipparchus.migration.ode

Subclasses of MathIllegalArgumentException in org.hipparchus.migration.ode

Modifier and Type	Class	Description
static class	JacobianMatrices.MismatchedEquations	Deprecated. Special exception for equations mismatch.
class	UnknownParameterException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException

Methods in org.hipparchus.migration.ode that throw MathIllegalArgumentException

Modifier and Type	Method	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.
void	JacobianMatrices.registerVariationalEquations(ExpandableODE expandable)	Deprecated. Register the variational equations for the Jacobians matrices to the expandable set.
void	JacobianMatrices.setInitialMainStateJacobian(double[][] dYdY0)	Deprecated. Set the initial value of the Jacobian matrix with respect to state.
void	JacobianMatrices.setInitialParameterJacobian(String pName, double[] dYdP)	Deprecated. Set the initial value of a column of the Jacobian matrix with respect to one parameter.
void	JacobianMatrices.setParameterStep(String parameter, double hP)	Deprecated. Set the step associated to a parameter in order to compute by finite difference the Jacobian matrix.

Constructors in org.hipparchus.migration.ode that throw MathIllegalArgumentException

Modifier	Constructor	Description
	JacobianMatrices(OrdinaryDifferentialEquation fode, double[] hY, String... parameters)	Deprecated. Simple constructor for a secondary equations set computing Jacobian matrices.

Uses of MathIllegalArgumentException in org.hipparchus.migration.stat.regression

Subclasses of MathIllegalArgumentException in org.hipparchus.migration.stat.regression

Modifier and Type	Class	Description
class	ModelSpecificationException	Deprecated. as of 1.0, this exception is replaced by MathIllegalArgumentException

Uses of MathIllegalArgumentException in org.hipparchus.ode

Subclasses of MathIllegalArgumentException in org.hipparchus.ode

Modifier and Type	Class	Description
static class	VariationalEquation.MismatchedEquations	Special exception for equations mismatch.

Methods in org.hipparchus.ode that throw MathIllegalArgumentException

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.
void	AbstractParameterizable.complainIfNotSupported(String name)	Check if a parameter is supported and throw an IllegalArgumentException if not.
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.
default double[]	ODEJacobiansProvider.computeParameterJacobian(double t, double[] y, double[] yDot, String paramName)	Compute the Jacobian matrix of ODE with respect to one parameter.
double[]	EquationsMapper.extractEquationData(int index, double[] complete)	Extract equation data from a complete state or derivative array.
T[]	FieldEquationsMapper.extractEquationData(int index, T[] complete)	Extract equation data from a complete state or derivative array.
double	ParametersController.getParameter(String name)	Get parameter value from its name.
void	EquationsMapper.insertEquationData(int index, double[] equationData, double[] complete)	Insert equation data into a complete state or derivative array.
void	FieldEquationsMapper.insertEquationData(int index, T[] equationData, T[] complete)	Insert equation data into a complete state or derivative array.
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.
ODEStateAndDerivative	EquationsMapper.mapStateAndDerivative(double t, double[] y, double[] yDot)	Map flat arrays to a state and derivative.
FieldODEStateAndDerivative<T>	FieldEquationsMapper.mapStateAndDerivative(T t, T[] y, T[] yDot)	Map flat arrays to a state and derivative.
protected void	AbstractFieldIntegrator.sanityChecks(FieldODEState<T> initialState, T t)	Check the integration span.
protected void	AbstractIntegrator.sanityChecks(ODEState initialState, double t)	Check the integration span.
void	VariationalEquation.setInitialMainStateJacobian(double[][] dYdY0)	Set the initial value of the Jacobian matrix with respect to state.
void	VariationalEquation.setInitialParameterJacobian(String pName, double[] dYdP)	Set the initial value of a column of the Jacobian matrix with respect to one parameter.
void	ParametersController.setParameter(String name, double value)	Set the value for a given parameter.
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.

Constructors in org.hipparchus.ode that throw MathIllegalArgumentException

Modifier	Constructor	Description
protected	MultistepFieldIntegrator(Field<T> field, String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)	Build a multistep integrator with the given stepsize bounds.
protected	MultistepIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)	Build a multistep integrator with the given stepsize bounds.

Uses of MathIllegalArgumentException in org.hipparchus.ode.events

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

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.

Uses of MathIllegalArgumentException in org.hipparchus.ode.nonstiff

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

Modifier and Type	Method	Description
double	StepsizeHelper.filterStep(double h, boolean forward, boolean acceptSmall)	Filter the integration step.
<T extends CalculusFieldElement<T>> T	StepsizeHelper.filterStep(T h, boolean forward, boolean acceptSmall)	Filter the integration step.
double	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.
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.
ODEStateAndDerivative	GraggBulirschStoerIntegrator.integrate(ExpandableODE equations, ODEState initialState, double 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.
ODEStateAndDerivative	RungeKuttaIntegrator.integrate(ExpandableODE equations, ODEState initialState, double finalTime)	Integrate the differential equations up to the given time.
protected void	AdaptiveStepsizeFieldIntegrator.sanityChecks(FieldODEState<T> initialState, T t)	Check the integration span.
protected void	AdaptiveStepsizeIntegrator.sanityChecks(ODEState initialState, double t)	Check the integration span.
protected void	StepsizeHelper.setMainSetDimension(int mainSetDimension)	Set main set dimension.

Constructors in org.hipparchus.ode.nonstiff that throw MathIllegalArgumentException

Modifier	Constructor	Description
	AdamsBashforthFieldIntegrator(Field<T> field, int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)	Build an Adams-Bashforth integrator with the given order and step control parameters.
	AdamsBashforthIntegrator(int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)	Build an Adams-Bashforth integrator with the given order and step control parameters.
	AdamsFieldIntegrator(Field<T> field, String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)	Build an Adams integrator with the given order and step control parameters.
	AdamsIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)	Build an Adams integrator with the given order and step control parameters.
	AdamsMoultonFieldIntegrator(Field<T> field, int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)	Build an Adams-Moulton integrator with the given order and error control parameters.
	AdamsMoultonIntegrator(int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)	Build an Adams-Moulton integrator with the given order and error control parameters.

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

Constructors in org.hipparchus.optim.nonlinear.scalar that throw MathIllegalArgumentException

Modifier	Constructor	Description
	MultiStartMultivariateOptimizer(MultivariateOptimizer optimizer, int starts, RandomVectorGenerator generator)	Create a multi-start optimizer from a single-start optimizer.

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

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

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

Constructors in org.hipparchus.optim.nonlinear.scalar.noderiv that throw MathIllegalArgumentException

Modifier	Constructor	Description
	PopulationSize(int size)	Simple constructor.
	Sigma(double[] s)	Simple constructor.

Uses of MathIllegalArgumentException in org.hipparchus.random

Methods in org.hipparchus.random that throw MathIllegalArgumentException

Modifier and Type	Method	Description
String	RandomDataGenerator.nextHexString(int len)	Generates a random string of hex characters of length len.
long	RandomDataGenerator.nextLong(long lower, long upper)	Returns a uniformly distributed random long integer between lower and upper (inclusive).
int[]	RandomDataGenerator.nextPermutation(int n, int k)	Generates an integer array of length k whose entries are selected randomly, without repetition, from the integers 0, ..., n - 1 (inclusive).
double[]	RandomDataGenerator.nextSample(double[] a, int k)	Returns an array of k double values selected randomly from the double array a.
Object[]	RandomDataGenerator.nextSample(Collection<?> c, int k)	Returns an array of k objects selected randomly from the Collection c.
double[]	HaltonSequenceGenerator.skipTo(int index)	Skip to the i-th point in the Halton sequence.
double[]	SobolSequenceGenerator.skipTo(int index)	Skip to the i-th point in the Sobol sequence.

Constructors in org.hipparchus.random that throw MathIllegalArgumentException

Modifier	Constructor	Description
	HaltonSequenceGenerator(int dimension)	Construct a new Halton sequence generator for the given space dimension.
	HaltonSequenceGenerator(int dimension, int[] bases, int[] weights)	Construct a new Halton sequence generator with the given base numbers and weights for each dimension.
	SobolSequenceGenerator(int dimension)	Construct a new Sobol sequence generator for the given space dimension.
	SobolSequenceGenerator(int dimension, InputStream is)	Construct a new Sobol sequence generator for the given space dimension with direction vectors loaded from the given stream.
	StableRandomGenerator(RandomGenerator generator, double alpha, double beta)	Create a new generator.

Uses of MathIllegalArgumentException in org.hipparchus.special

Methods in org.hipparchus.special that throw MathIllegalArgumentException

Modifier and Type	Method	Description
static double	Gamma.logGamma1p(double x)	Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5.
static <T extends CalculusFieldElement<T>> T	Gamma.logGamma1p(T x)	Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5.
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 MathIllegalArgumentException in org.hipparchus.stat

Methods in org.hipparchus.stat that throw MathIllegalArgumentException

Modifier and Type	Method	Description
static double	StatUtils.geometricMean(double... values)	Returns the geometric mean of the entries in the input array, or Double.NaN if the array is empty.
static double	StatUtils.geometricMean(double[] values, int begin, int length)	Returns the geometric mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double	StatUtils.max(double... values)	Returns the maximum of the entries in the input array, or Double.NaN if the array is empty.
static double	StatUtils.max(double[] values, int begin, int length)	Returns the maximum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double	StatUtils.mean(double... values)	Returns the arithmetic mean of the entries in the input array, or Double.NaN if the array is empty.
static double	StatUtils.mean(double[] values, int begin, int length)	Returns the arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double	StatUtils.meanDifference(double[] sample1, double[] sample2)	Returns the mean of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]) / sample1.length.
static double	StatUtils.min(double... values)	Returns the minimum of the entries in the input array, or Double.NaN if the array is empty.
static double	StatUtils.min(double[] values, int begin, int length)	Returns the minimum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double[]	StatUtils.mode(double... sample)	Returns the sample mode(s).
static double	StatUtils.percentile(double[] values, double p)	Returns an estimate of the pth percentile of the values in the values array.
static double	StatUtils.percentile(double[] values, int begin, int length, double p)	Returns an estimate of the pth percentile of the values in the values array, starting with the element in (0-based) position begin in the array and including length values.
static double	StatUtils.populationVariance(double... values)	Returns the population variance of the entries in the input array, or Double.NaN if the array is empty.
static double	StatUtils.populationVariance(double[] values, double mean)	Returns the population variance of the entries in the input array, using the precomputed mean value.
static double	StatUtils.populationVariance(double[] values, double mean, int begin, int length)	Returns the population variance of the entries in the specified portion of the input array, using the precomputed mean value.
static double	StatUtils.populationVariance(double[] values, int begin, int length)	Returns the population variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double	StatUtils.product(double... values)	Returns the product of the entries in the input array, or Double.NaN if the array is empty.
static double	StatUtils.product(double[] values, int begin, int length)	Returns the product of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double	StatUtils.sum(double... values)	Returns the sum of the values in the input array, or Double.NaN if the array is empty.
static double	StatUtils.sum(double[] values, int begin, int length)	Returns the sum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double	StatUtils.sumDifference(double[] sample1, double[] sample2)	Returns the sum of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]).
static double	StatUtils.sumLog(double... values)	Returns the sum of the natural logs of the entries in the input array, or Double.NaN if the array is empty.
static double	StatUtils.sumLog(double[] values, int begin, int length)	Returns the sum of the natural logs of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double	StatUtils.sumSq(double... values)	Returns the sum of the squares of the entries in the input array, or Double.NaN if the array is empty.
static double	StatUtils.sumSq(double[] values, int begin, int length)	Returns the sum of the squares of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double	StatUtils.variance(double... values)	Returns the variance of the entries in the input array, or Double.NaN if the array is empty.
static double	StatUtils.variance(double[] values, double mean)	Returns the variance of the entries in the input array, using the precomputed mean value.
static double	StatUtils.variance(double[] values, double mean, int begin, int length)	Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
static double	StatUtils.variance(double[] values, int begin, int length)	Returns the variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
static double	StatUtils.varianceDifference(double[] sample1, double[] sample2, double meanDifference)	Returns the variance of the (signed) differences between corresponding elements of the input arrays -- i.e., var(sample1[i] - sample2[i]).

Uses of MathIllegalArgumentException in org.hipparchus.stat.correlation

Methods in org.hipparchus.stat.correlation that throw MathIllegalArgumentException

Modifier and Type	Method	Description
void	StorelessCovariance.append(StorelessCovariance sc)	Appends sc to this, effectively aggregating the computations in sc with this.
protected RealMatrix	Covariance.computeCovarianceMatrix(double[][] data)	Create a covariance matrix from a rectangular array whose columns represent covariates.
protected RealMatrix	Covariance.computeCovarianceMatrix(double[][] data, boolean biasCorrected)	Compute a covariance matrix from a rectangular array whose columns represent covariates.
protected RealMatrix	Covariance.computeCovarianceMatrix(RealMatrix matrix)	Create a covariance matrix from a matrix whose columns represent covariates.
protected RealMatrix	Covariance.computeCovarianceMatrix(RealMatrix matrix, boolean biasCorrected)	Compute a covariance matrix from a matrix whose columns represent covariates.
double	KendallsCorrelation.correlation(double[] xArray, double[] yArray)	Computes the Kendall's Tau rank correlation coefficient between the two arrays.
double	Covariance.covariance(double[] xArray, double[] yArray)	Computes the covariance between the two arrays, using the bias-corrected formula.
double	Covariance.covariance(double[] xArray, double[] yArray, boolean biasCorrected)	Computes the covariance between the two arrays.
double	StorelessCovariance.getCovariance(int xIndex, int yIndex)	Get the covariance for an individual element of the covariance matrix.
RealMatrix	StorelessCovariance.getCovarianceMatrix()	Returns the covariance matrix
double[][]	StorelessCovariance.getData()	Return the covariance matrix as two-dimensional array.
void	StorelessCovariance.increment(double[] data)	Increment the covariance matrix with one row of data.

Constructors in org.hipparchus.stat.correlation that throw MathIllegalArgumentException

Modifier	Constructor	Description
	Covariance(double[][] data)	Create a Covariance matrix from a rectangular array whose columns represent covariates.
	Covariance(double[][] data, boolean biasCorrected)	Create a Covariance matrix from a rectangular array whose columns represent covariates.
	Covariance(RealMatrix matrix)	Create a covariance matrix from a matrix whose columns represent covariates.
	Covariance(RealMatrix matrix, boolean biasCorrected)	Create a covariance matrix from a matrix whose columns represent covariates.
	SpearmansCorrelation(RealMatrix dataMatrix, RankingAlgorithm rankingAlgorithm)	Create a SpearmansCorrelation with the given input data matrix and ranking algorithm.
	SpearmansCorrelation(RankingAlgorithm rankingAlgorithm)	Create a SpearmansCorrelation with the given ranking algorithm.

Uses of MathIllegalArgumentException in org.hipparchus.stat.descriptive

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

Modifier and Type	Method	Description
void	MultivariateSummaryStatistics.addValue(double[] value)	Add an n-tuple to the data
double	AbstractUnivariateStatistic.evaluate()	Returns the result of evaluating the statistic over the stored data.
abstract double	AbstractUnivariateStatistic.evaluate(double[] values, int begin, int length)	Returns the result of evaluating the statistic over the specified entries in the input array.
default double	StorelessUnivariateStatistic.evaluate(double[] values, int begin, int length)	Returns the result of evaluating the statistic over the specified entries in the input array.
default double	UnivariateStatistic.evaluate(double[] values)	Returns the result of evaluating the statistic over the input array.
double	UnivariateStatistic.evaluate(double[] values, int begin, int length)	Returns the result of evaluating the statistic over the specified entries in the input array.
default double	WeightedEvaluation.evaluate(double[] values, double[] weights)	Returns the result of evaluating the statistic over the input array, using the supplied weights.
double	WeightedEvaluation.evaluate(double[] values, double[] weights, int begin, int length)	Returns the result of evaluating the statistic over the specified entries in the input array, using corresponding entries in the supplied weights array.
double	DescriptiveStatistics.getPercentile(double p)	Returns an estimate for the pth percentile of the stored values.
default void	StorelessUnivariateStatistic.incrementAll(double[] values)	Updates the internal state of the statistic to reflect addition of all values in the values array.
default void	StorelessUnivariateStatistic.incrementAll(double[] values, int start, int length)	Updates the internal state of the statistic to reflect addition of the values in the designated portion of the values array.
void	AbstractUnivariateStatistic.setData(double[] values, int begin, int length)	Set the data array.
void	DescriptiveStatistics.setWindowSize(int windowSize)	WindowSize controls the number of values that contribute to the reported statistics.

Constructors in org.hipparchus.stat.descriptive that throw MathIllegalArgumentException

Modifier	Constructor	Description
	DescriptiveStatistics(int size)	Construct a DescriptiveStatistics instance with the specified window.

Uses of MathIllegalArgumentException in org.hipparchus.stat.descriptive.moment

Methods in org.hipparchus.stat.descriptive.moment that throw MathIllegalArgumentException

Modifier and Type	Method	Description
double	GeometricMean.evaluate(double[] values, int begin, int length)	Returns the geometric mean of the entries in the specified portion of the input array.
double	Kurtosis.evaluate(double[] values, int begin, int length)	Returns the kurtosis of the entries in the specified portion of the input array.
double	Mean.evaluate(double[] values, double[] weights, int begin, int length)	Returns the weighted arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
double	Mean.evaluate(double[] values, int begin, int length)	Returns the arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
double	SemiVariance.evaluate(double[] values, double cutoff)	Returns the SemiVariance of the designated values against the cutoff, using instance properties variancDirection and biasCorrection.
double	SemiVariance.evaluate(double[] values, double cutoff, SemiVariance.Direction direction)	Returns the SemiVariance of the designated values against the cutoff in the given direction, using the current value of the biasCorrection instance property.
double	SemiVariance.evaluate(double[] values, double cutoff, SemiVariance.Direction direction, boolean corrected, int start, int length)	Returns the SemiVariance of the designated values against the cutoff in the given direction with the provided bias correction.
double	SemiVariance.evaluate(double[] values, int start, int length)	Returns the SemiVariance of the designated values against the mean, using instance properties varianceDirection and biasCorrection.
double	SemiVariance.evaluate(double[] values, SemiVariance.Direction direction)	This method calculates SemiVariance for the entire array against the mean, using the current value of the biasCorrection instance property.
double	Skewness.evaluate(double[] values, int begin, int length)	Returns the Skewness of the entries in the specified portion of the input array.
double	StandardDeviation.evaluate(double[] values, double mean)	Returns the Standard Deviation of the entries in the input array, using the precomputed mean value.
double	StandardDeviation.evaluate(double[] values, double mean, int begin, int length)	Returns the Standard Deviation of the entries in the specified portion of the input array, using the precomputed mean value.
double	StandardDeviation.evaluate(double[] values, int begin, int length)	Returns the Standard Deviation of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
double	Variance.evaluate(double[] values, double mean)	Returns the variance of the entries in the input array, using the precomputed mean value.
double	Variance.evaluate(double[] values, double[] weights, double mean)	Returns the weighted variance of the values in the input array, using the precomputed weighted mean value.
double	Variance.evaluate(double[] values, double[] weights, double mean, int begin, int length)	Returns the weighted variance of the entries in the specified portion of the input array, using the precomputed weighted mean value.
double	Variance.evaluate(double[] values, double[] weights, int begin, int length)	Returns the weighted variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
double	Variance.evaluate(double[] values, double mean, int begin, int length)	Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
double	Variance.evaluate(double[] values, int begin, int length)	Returns the variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.

Uses of MathIllegalArgumentException in org.hipparchus.stat.descriptive.rank

Methods in org.hipparchus.stat.descriptive.rank that throw MathIllegalArgumentException

Modifier and Type	Method	Description
double	Max.evaluate(double[] values, int begin, int length)	Returns the maximum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
double	Median.evaluate(double[] values, int begin, int length)	Returns the result of evaluating the statistic over the specified entries in the input array.
double	Min.evaluate(double[] values, int begin, int length)	Returns the minimum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
double	Percentile.evaluate(double p)	Returns the result of evaluating the statistic over the stored data.
double	Percentile.evaluate(double[] values, double p)	Returns an estimate of the pth percentile of the values in the values array.
double	Percentile.evaluate(double[] values, int start, int length)	Returns an estimate of the quantileth percentile of the designated values in the values array.
double	Percentile.evaluate(double[] values, int begin, int length, double p)	Returns an estimate of the pth percentile of the values in the values array, starting with the element in (0-based) position begin in the array and including length values.
double	RandomPercentile.evaluate(double percentile, double[] values, int begin, int length)	Returns an estimate of the given percentile, computed using the designated array segment as input data.
void	Percentile.setData(double[] values, int begin, int length)	Set the data array.
void	Percentile.setQuantile(double p)	Sets the value of the quantile field (determines what percentile is computed when evaluate() is called with no quantile argument).

Constructors in org.hipparchus.stat.descriptive.rank that throw MathIllegalArgumentException

Modifier	Constructor	Description
	Percentile(double quantile)	Constructs a Percentile with the specific quantile value and the following default method type: Percentile.EstimationType.LEGACY default NaN strategy: NaNStrategy.REMOVED a Kth Selector : KthSelector
protected	Percentile(double quantile, Percentile.EstimationType estimationType, NaNStrategy nanStrategy, KthSelector kthSelector)	Constructs a Percentile with the specific quantile value, Percentile.EstimationType, NaNStrategy and KthSelector.

Uses of MathIllegalArgumentException in org.hipparchus.stat.descriptive.summary

Methods in org.hipparchus.stat.descriptive.summary that throw MathIllegalArgumentException

Modifier and Type	Method	Description
double	Product.evaluate(double[] values, double[] weights, int begin, int length)	Returns the weighted product of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
double	Product.evaluate(double[] values, int begin, int length)	Returns the product of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
double	Sum.evaluate(double[] values, double[] weights, int begin, int length)	The weighted sum of the entries in the specified portion of the input array, or 0 if the designated subarray is empty.
double	Sum.evaluate(double[] values, int begin, int length)	The sum of the entries in the specified portion of the input array, or 0 if the designated subarray is empty.
double	SumOfLogs.evaluate(double[] values, int begin, int length)	Returns the sum of the natural logs of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
double	SumOfSquares.evaluate(double[] values, int begin, int length)	Returns the sum of the squares of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.

Uses of MathIllegalArgumentException in org.hipparchus.stat.descriptive.vector

Methods in org.hipparchus.stat.descriptive.vector that throw MathIllegalArgumentException

Modifier and Type	Method	Description
void	VectorialCovariance.increment(double[] v)	Add a new vector to the sample.

Uses of MathIllegalArgumentException in org.hipparchus.stat.fitting

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

Modifier and Type	Method	Description
static MixtureMultivariateNormalDistribution	MultivariateNormalMixtureExpectationMaximization.estimate(double[][] data, int numComponents)	Helper method to create a multivariate normal mixture model which can be used to initialize MultivariateNormalMixtureExpectationMaximization.fit(MixtureMultivariateNormalDistribution).
void	MultivariateNormalMixtureExpectationMaximization.fit(MixtureMultivariateNormalDistribution initialMixture)	Fit a mixture model to the data supplied to the constructor.
void	MultivariateNormalMixtureExpectationMaximization.fit(MixtureMultivariateNormalDistribution initialMixture, int maxIterations, double threshold)	Fit a mixture model to the data supplied to the constructor.
double	EmpiricalDistribution.inverseCumulativeProbability(double p)	Computes the quantile function of this distribution.
void	EmpiricalDistribution.load(URL url)	Computes the empirical distribution using data read from a URL.

Constructors in org.hipparchus.stat.fitting that throw MathIllegalArgumentException

Modifier	Constructor	Description
	MultivariateNormalMixtureExpectationMaximization(double[][] data)	Creates an object to fit a multivariate normal mixture model to data.

Uses of MathIllegalArgumentException in org.hipparchus.stat.inference

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

Modifier and Type	Method	Description
double	OneWayAnova.anovaFValue(Collection<double[]> categoryData)	Computes the ANOVA F-value for a collection of double[] arrays.
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.chiSquare(double[] expected, long[] observed)	Computes the Chi-Square statistic comparing observed and expected frequency counts.
double	ChiSquareTest.chiSquare(long[][] counts)	Computes the Chi-Square statistic associated with a chi-square test of independence based on the input counts array, viewed as a two-way table.
static double	InferenceTestUtils.chiSquare(double[] expected, long[] observed)	Computes the Chi-Square statistic comparing observed and expected frequency counts.
static double	InferenceTestUtils.chiSquare(long[][] counts)	Computes the Chi-Square statistic associated with a chi-square test of independence based on the input counts array, viewed as a two-way table.
double	ChiSquareTest.chiSquareDataSetsComparison(long[] observed1, long[] observed2)	Computes a Chi-Square two sample test statistic comparing bin frequency counts in observed1 and observed2.
static double	InferenceTestUtils.chiSquareDataSetsComparison(long[] observed1, long[] observed2)	Computes a Chi-Square two sample test statistic comparing bin frequency counts in observed1 and observed2.
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.g(double[] expected, long[] observed)	Computes the G statistic for Goodness of Fit comparing observed and expected frequency counts.
static double	InferenceTestUtils.g(double[] expected, long[] observed)	Computes the G statistic for Goodness of Fit comparing observed and expected frequency counts.
double	GTest.gDataSetsComparison(long[] observed1, long[] observed2)	Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts in observed1 and observed2.
static double	InferenceTestUtils.gDataSetsComparison(long[] observed1, long[] observed2)	Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts in observed1 and observed2.
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.
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.homoscedasticT(double[] sample1, double[] sample2)	Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.
static double	InferenceTestUtils.homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)	Computes a 2-sample t statistic, comparing the means of the datasets described by two StatisticalSummary instances, under the assumption of equal subpopulation variances.
double	TTest.homoscedasticT(double[] sample1, double[] sample2)	Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.
double	TTest.homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)	Computes a 2-sample t statistic, comparing the means of the datasets described by two StatisticalSummary instances, under the assumption of equal subpopulation variances.
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.kolmogorovSmirnovStatistic(double[] x, double[] y)	Computes the two-sample Kolmogorov-Smirnov test statistic, \(D_{n,m}=\sup_x |F_n(x)-F_m(x)|\) where \(n\) is the length of x, \(m\) is the length of y, \(F_n\) is the empirical distribution that puts mass \(1/n\) at each of the values in x and \(F_m\) is the empirical distribution of the y values.
static double	InferenceTestUtils.kolmogorovSmirnovStatistic(RealDistribution dist, double[] data)	Computes the one-sample Kolmogorov-Smirnov test statistic, \(D_n=\sup_x |F_n(x)-F(x)|\) where \(F\) is the distribution (cdf) function associated with distribution, \(n\) is the length of data and \(F_n\) is the empirical distribution that puts mass \(1/n\) at each of the values in data.
static double	InferenceTestUtils.kolmogorovSmirnovTest(double[] x, double[] y)	Computes the p-value, or observed significance level, of a two-sample Kolmogorov-Smirnov test evaluating the null hypothesis that x and y are samples drawn from the same probability distribution.
static double	InferenceTestUtils.kolmogorovSmirnovTest(double[] x, double[] y, boolean strict)	Computes the p-value, or observed significance level, of a two-sample Kolmogorov-Smirnov test evaluating the null hypothesis that x and y are samples drawn from the same probability distribution.
static double	InferenceTestUtils.kolmogorovSmirnovTest(RealDistribution dist, double[] data)	Computes the p-value, or observed significance level, of a one-sample Kolmogorov-Smirnov test evaluating the null hypothesis that data conforms to distribution.
static double	InferenceTestUtils.kolmogorovSmirnovTest(RealDistribution dist, double[] data, boolean strict)	Computes the p-value, or observed significance level, of a one-sample Kolmogorov-Smirnov test evaluating the null hypothesis that data conforms to distribution.
static boolean	InferenceTestUtils.kolmogorovSmirnovTest(RealDistribution dist, double[] data, double alpha)	Performs a Kolmogorov-Smirnov test evaluating the null hypothesis that data conforms to distribution.
double	MannWhitneyUTest.mannWhitneyU(double[] x, double[] y)	Computes the Mann-Whitney U statistic comparing means for two independent samples possibly of different lengths.
double	MannWhitneyUTest.mannWhitneyUTest(double[] x, double[] y)	Returns the asymptotic observed significance level, or p-value, associated with a Mann-Whitney U Test comparing means for two independent samples.
double	MannWhitneyUTest.mannWhitneyUTest(double[] x, double[] y, boolean exact)	Returns the asymptotic observed significance level, or p-value, associated with a Mann-Whitney U Test comparing means for two independent samples.
static double	InferenceTestUtils.oneWayAnovaFValue(Collection<double[]> categoryData)	Computes the ANOVA F-value for a collection of double[] arrays.
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.pairedT(double[] sample1, double[] sample2)	Computes a paired, 2-sample t-statistic based on the data in the input arrays.
double	TTest.pairedT(double[] sample1, double[] sample2)	Computes a paired, 2-sample t-statistic based on the data in the input arrays.
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.rootLogLikelihoodRatio(long k11, long k12, long k21, long k22)	Calculates the root log-likelihood ratio for 2 state Datasets.
static double	InferenceTestUtils.t(double[] sample1, double[] sample2)	Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.
static double	InferenceTestUtils.t(double mu, double[] observed)	Computes a t statistic given observed values and a comparison constant.
static double	InferenceTestUtils.t(double mu, StatisticalSummary sampleStats)	Computes a t statistic to use in comparing the mean of the dataset described by sampleStats to mu.
static double	InferenceTestUtils.t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)	Computes a 2-sample t statistic, comparing the means of the datasets described by two StatisticalSummary instances, without the assumption of equal subpopulation variances.
double	TTest.t(double[] sample1, double[] sample2)	Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.
double	TTest.t(double mu, double[] observed)	Computes a t statistic given observed values and a comparison constant.
double	TTest.t(double mu, StatisticalSummary sampleStats)	Computes a t statistic to use in comparing the mean of the dataset described by sampleStats to mu.
double	TTest.t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)	Computes a 2-sample t statistic, comparing the means of the datasets described by two StatisticalSummary instances, without the assumption of equal subpopulation variances.
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.wilcoxonSignedRank(double[] x, double[] y)	Computes the Wilcoxon signed ranked statistic comparing means for two related samples or repeated measurements on a single sample.
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 MathIllegalArgumentException in org.hipparchus.stat.interval

Methods in org.hipparchus.stat.interval that throw MathIllegalArgumentException

Modifier and Type	Method	Description
static ConfidenceInterval	BinomialProportion.getAgrestiCoullInterval(int numberOfTrials, double probabilityOfSuccess, double confidenceLevel)	Create an Agresti-Coull binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, probability of success and confidence level.
static ConfidenceInterval	BinomialProportion.getClopperPearsonInterval(int numberOfTrials, double probabilityOfSuccess, double confidenceLevel)	Create a Clopper-Pearson binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, probability of success and confidence level.
static ConfidenceInterval	BinomialProportion.getNormalApproximationInterval(int numberOfTrials, double probabilityOfSuccess, double confidenceLevel)	Create a binomial confidence interval using normal approximation for the true probability of success of an unknown binomial distribution with the given observed number of trials, probability of success and confidence level.
static ConfidenceInterval	BinomialProportion.getWilsonScoreInterval(int numberOfTrials, double probabilityOfSuccess, double confidenceLevel)	Create an Wilson score binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, probability of success and confidence level.

Uses of MathIllegalArgumentException in org.hipparchus.stat.regression

Methods in org.hipparchus.stat.regression that throw MathIllegalArgumentException

Modifier and Type	Method	Description
void	SimpleRegression.addData(double[][] data)	Adds the observations represented by the elements in data.
void	MillerUpdatingRegression.addObservation(double[] x, double y)	Adds an observation to the regression model.
void	SimpleRegression.addObservation(double[] x, double y)	Adds one observation to the regression model.
void	UpdatingMultipleLinearRegression.addObservation(double[] x, double y)	Adds one observation to the regression model.
void	MillerUpdatingRegression.addObservations(double[][] x, double[] y)	Adds multiple observations to the model.
void	SimpleRegression.addObservations(double[][] x, double[] y)	Adds a series of observations to the regression model.
void	UpdatingMultipleLinearRegression.addObservations(double[][] x, double[] y)	Adds a series of observations to the regression model.
double	RegressionResults.getCovarianceOfParameters(int i, int j)	Returns the covariance between regression parameters i and j.
double	RegressionResults.getParameterEstimate(int index)	Returns the parameter estimate for the regressor at the given index.
double	SimpleRegression.getSlopeConfidenceInterval()	Returns the half-width of a 95% confidence interval for the slope estimate.
double	SimpleRegression.getSlopeConfidenceInterval(double alpha)	Returns the half-width of a (100-100*alpha)% confidence interval for the slope estimate.
double	RegressionResults.getStdErrorOfEstimate(int index)	Returns the standard error of the parameter estimate at index, usually denoted s(bindex).
void	OLSMultipleLinearRegression.newSampleData(double[] y, double[][] x)	Loads model x and y sample data, overriding any previous sample.
RegressionResults	MillerUpdatingRegression.regress()	Conducts a regression on the data in the model, using all regressors.
RegressionResults	MillerUpdatingRegression.regress(int numberOfRegressors)	Conducts a regression on the data in the model, using a subset of regressors.
RegressionResults	MillerUpdatingRegression.regress(int[] variablesToInclude)	Conducts a regression on the data in the model, using regressors in array Calling this method will change the internal order of the regressors and care is required in interpreting the hatmatrix.
RegressionResults	SimpleRegression.regress()	Performs a regression on data present in buffers and outputs a RegressionResults object.
RegressionResults	SimpleRegression.regress(int[] variablesToInclude)	Performs a regression on data present in buffers including only regressors indexed in variablesToInclude and outputs a RegressionResults object
RegressionResults	UpdatingMultipleLinearRegression.regress()	Performs a regression on data present in buffers and outputs a RegressionResults object
RegressionResults	UpdatingMultipleLinearRegression.regress(int[] variablesToInclude)	Performs a regression on data present in buffers including only regressors indexed in variablesToInclude and outputs a RegressionResults object
protected void	AbstractMultipleLinearRegression.validateSampleData(double[][] x, double[] y)	Validates sample data.

Constructors in org.hipparchus.stat.regression that throw MathIllegalArgumentException

Modifier	Constructor	Description
	MillerUpdatingRegression(int numberOfVariables, boolean includeConstant)	Primary constructor for the MillerUpdatingRegression.
	MillerUpdatingRegression(int numberOfVariables, boolean includeConstant, double errorTolerance)	This is the augmented constructor for the MillerUpdatingRegression class.

Uses of MathIllegalArgumentException in org.hipparchus.transform

Methods in org.hipparchus.transform that throw MathIllegalArgumentException

Modifier and Type	Method	Description
static Complex[]	TransformUtils.createComplexArray(double[][] dataRI)	Builds a new array of Complex from the specified two dimensional array of real and imaginary parts.
static int	TransformUtils.exactLog2(int n)	Returns the base-2 logarithm of the specified int.
protected double[]	FastCosineTransformer.fct(double[] f)	Perform the FCT algorithm (including inverse).
protected double[]	FastHadamardTransformer.fht(double[] x)	The FHT (Fast Hadamard Transformation) which uses only subtraction and addition.
protected int[]	FastHadamardTransformer.fht(int[] x)	Returns the forward transform of the specified integer data set.
protected double[]	FastSineTransformer.fst(double[] f)	Perform the FST algorithm (including inverse).
double[]	FastCosineTransformer.transform(double[] f, TransformType type)	Returns the (forward, inverse) transform of the specified real data set.
double[]	FastCosineTransformer.transform(UnivariateFunction f, double min, double max, int n, TransformType type)	Returns the (forward, inverse) transform of the specified real function, sampled on the specified interval.
double[]	RealTransformer.transform(double[] f, TransformType type)	Returns the (forward, inverse) transform of the specified real data set.
double[]	RealTransformer.transform(UnivariateFunction f, double min, double max, int n, TransformType type)	Returns the (forward, inverse) transform of the specified real function, sampled on the specified interval.

Uses of MathIllegalArgumentException in org.hipparchus.util

Methods in org.hipparchus.util that throw MathIllegalArgumentException

Modifier and Type	Method	Description
static long	CombinatoricsUtils.binomialCoefficient(int n, int k)	Returns an exact representation of the Binomial Coefficient, "n choose k", the number of k-element subsets that can be selected from an n-element set.
static double	CombinatoricsUtils.binomialCoefficientDouble(int n, int k)	Returns a double representation of the Binomial Coefficient, "n choose k", the number of k-element subsets that can be selected from an n-element set.
static double	CombinatoricsUtils.binomialCoefficientLog(int n, int k)	Returns the natural log of the Binomial Coefficient, "n choose k", the number of k-element subsets that can be selected from an n-element set.
B	Blendable.blendArithmeticallyWith(B other, double blendingValue)	Blend arithmetically this instance with another one.
B	FieldBlendable.blendArithmeticallyWith(B other, T blendingValue)	Blend arithmetically this instance with another one.
static void	CombinatoricsUtils.checkBinomial(int n, int k)	Check binomial preconditions.
protected void	ResizableDoubleArray.checkContractExpand(double contraction, double expansion)	Checks the expansion factor and the contraction criterion and raises an exception if the contraction criterion is smaller than the expansion criterion.
static void	MathUtils.checkFinite(double x)	Check that the argument is a real number.
static void	MathUtils.checkFinite(double[] val)	Check that all the elements are real numbers.
static void	MathArrays.checkNonNegative(long[] in)	Check that all entries of the input array are >= 0.
static void	MathArrays.checkNonNegative(long[][] in)	Check all entries of the input array are >= 0.
static void	MathArrays.checkNotNaN(double[] in)	Check that no entry of the input array is NaN.
static void	MathArrays.checkOrder(double[] val)	Check that the given array is sorted in strictly increasing order.
static void	MathArrays.checkOrder(double[] val, MathArrays.OrderDirection dir, boolean strict)	Check that the given array is sorted.
static boolean	MathArrays.checkOrder(double[] val, MathArrays.OrderDirection dir, boolean strict, boolean abort)	Check that the given array is sorted.
static <T extends CalculusFieldElement<T>> void	MathArrays.checkOrder(T[] val)	Check that the given array is sorted in strictly increasing order.
static <T extends CalculusFieldElement<T>> void	MathArrays.checkOrder(T[] val, MathArrays.OrderDirection dir, boolean strict)	Check that the given array is sorted.
static <T extends CalculusFieldElement<T>> boolean	MathArrays.checkOrder(T[] val, MathArrays.OrderDirection dir, boolean strict, boolean abort)	Check that the given array is sorted.
static void	MathArrays.checkPositive(double[] in)	Check that all entries of the input array are strictly positive.
static void	MathArrays.checkRectangular(long[][] in)	Throws MathIllegalArgumentException if the input array is not rectangular.
static double[]	MathArrays.convolve(double[] x, double[] h)	Calculates the convolution between two sequences.
void	ResizableDoubleArray.discardFrontElements(int i)	Discards the i initial elements of the array.
void	ResizableDoubleArray.discardMostRecentElements(int i)	Discards the i last elements of the array.
static double	MathArrays.distance(double[] p1, double[] p2)	Calculates the L2 (Euclidean) distance between two points.
static double	MathArrays.distance(int[] p1, int[] p2)	Calculates the L2 (Euclidean) distance between two points.
static double	MathArrays.distance1(double[] p1, double[] p2)	Calculates the L1 (sum of abs) distance between two points.
static int	MathArrays.distance1(int[] p1, int[] p2)	Calculates the L1 (sum of abs) distance between two points.
static double	MathArrays.distanceInf(double[] p1, double[] p2)	Calculates the L∞ (max of abs) distance between two points.
static int	MathArrays.distanceInf(int[] p1, int[] p2)	Calculates the L∞ (max of abs) distance between two points.
static double[]	MathArrays.ebeAdd(double[] a, double[] b)	Creates an array whose contents will be the element-by-element addition of the arguments.
static double[]	MathArrays.ebeDivide(double[] a, double[] b)	Creates an array whose contents will be the element-by-element division of the first argument by the second.
static double[]	MathArrays.ebeMultiply(double[] a, double[] b)	Creates an array whose contents will be the element-by-element multiplication of the arguments.
static double[]	MathArrays.ebeSubtract(double[] a, double[] b)	Creates an array whose contents will be the element-by-element subtraction of the second argument from the first.
static long	CombinatoricsUtils.factorial(int n)	Returns n!.
static double	CombinatoricsUtils.factorialDouble(int n)	Compute n!, the factorial of n (the product of the numbers 1 to n), as a double.
static double	CombinatoricsUtils.factorialLog(int n)	Compute the natural logarithm of the factorial of n.
int	MultidimensionalCounter.getCount(int... c)	Convert to unidimensional counter.
int[]	MultidimensionalCounter.getCounts(int index)	Convert to multidimensional counter.
Binary64	Binary64.linearCombination(double[] a, Binary64[] b)	Compute a linear combination.
Binary64	Binary64.linearCombination(Binary64[] a, Binary64[] b)	Compute a linear combination.
FieldTuple<T>	FieldTuple.linearCombination(double[] a, FieldTuple<T>[] b)	Compute a linear combination.
FieldTuple<T>	FieldTuple.linearCombination(FieldTuple<T>[] a, FieldTuple<T>[] b)	Compute a linear combination.
static double	MathArrays.linearCombination(double[] a, double[] b)	Compute a linear combination accurately.
Tuple	Tuple.linearCombination(double[] a, Tuple[] b)	Compute a linear combination.
Tuple	Tuple.linearCombination(Tuple[] a, Tuple[] b)	Compute a linear combination.
static double[]	MathArrays.normalizeArray(double[] values, double normalizedSum)	Normalizes an array to make it sum to a specified value.
abstract int	PivotingStrategy.pivotIndex(double[] work, int begin, int end)	Find pivot index of the array so that partition and Kth element selection can be made
static int	ArithmeticUtils.pow(int k, int e)	Raise an int to an int power.
static long	ArithmeticUtils.pow(long k, int e)	Raise a long to an int power.
static BigInteger	ArithmeticUtils.pow(BigInteger k, int e)	Raise a BigInteger to an int power.
static BigInteger	ArithmeticUtils.pow(BigInteger k, long e)	Raise a BigInteger to a long power.
static BigInteger	ArithmeticUtils.pow(BigInteger k, BigInteger e)	Raise a BigInteger to a BigInteger power.
static float	Precision.round(float x, int scale, RoundingMode roundingMethod)	Rounds the given value to the specified number of decimal places.
void	ResizableDoubleArray.setNumElements(int i)	This function allows you to control the number of elements contained in this array, and can be used to "throw out" the last n values in an array.
static void	MathArrays.sortInPlace(double[] x, double[]... yList)	Sort an array in ascending order in place and perform the same reordering of entries on other arrays.
static void	MathArrays.sortInPlace(double[] x, MathArrays.OrderDirection dir, double[]... yList)	Sort an array in place and perform the same reordering of entries on other arrays.
static long	CombinatoricsUtils.stirlingS2(int n, int k)	Returns the Stirling number of the second kind, "S(n,k)", the number of ways of partitioning an n-element set into k non-empty subsets.
static boolean	MathArrays.verifyValues(double[] values, double[] weights, int begin, int length)	This method is used to verify that the begin and length parameters designate a subarray of positive length and the weights are all non-negative, non-NaN, finite, and not all zero.
static boolean	MathArrays.verifyValues(double[] values, double[] weights, int begin, int length, boolean allowEmpty)	This method is used to verify that the begin and length parameters designate a subarray of positive length and the weights are all non-negative, non-NaN, finite, and not all zero.
static boolean	MathArrays.verifyValues(double[] values, int begin, int length)	This method is used to verify that the input parameters designate a subarray of positive length.
static boolean	MathArrays.verifyValues(double[] values, int begin, int length, boolean allowEmpty)	This method is used to verify that the input parameters designate a subarray of positive length.

Constructors in org.hipparchus.util that throw MathIllegalArgumentException

Modifier	Constructor	Description
	MultidimensionalCounter(int... size)	Create a counter.
	ResizableDoubleArray(int initialCapacity)	Creates an instance with the specified initial capacity.
	ResizableDoubleArray(int initialCapacity, double expansionFactor)	Creates an instance with the specified initial capacity and expansion factor.
	ResizableDoubleArray(int initialCapacity, double expansionFactor, double contractionCriterion)	Creates an instance with the specified initial capacity, expansion factor, and contraction criteria.
	ResizableDoubleArray(int initialCapacity, double expansionFactor, double contractionCriterion, ResizableDoubleArray.ExpansionMode expansionMode, double... data)	Creates an instance with the specified properties.