Uses of Class
org.hipparchus.exception.MathIllegalArgumentException
Package
Description
Common classes used throughout the Hipparchus library.
Parent package for common numerical analysis procedures, including root finding,
function interpolation and integration.
This package holds the main interfaces and basic building block classes
dealing with differentiation.
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.Numerical integration (quadrature) algorithms for univariate real functions.
Gauss family of quadrature schemes.
Univariate real functions interpolation algorithms.
Univariate real polynomials implementations, seen as differentiable
univariate real functions.
Root finding algorithms, for univariate real functions.
Clustering algorithms.
Common distance measures.
Complex number type and implementations of complex transcendental
functions.
Decimal floating point library for Java
Interfaces and implementations of common discrete and
continuous distributions.
Implementations of common continuous distributions.
Implementations of common discrete distributions.
Implementations of multivariate distributions.
Kalman filter.
Fraction number type and fraction number formatting.
This package is the top level package for geometry.
This package provides basic 3D geometry components.
This package provides basic 2D geometry components.
This package provides algorithms to generate the convex hull
for a set of points in an two-dimensional euclidean space.
This package provides interfaces and classes related to the convex hull problem.
This package provides basic geometry components on the 1-sphere.
This package provides basic geometry components on the 2-sphere.
Linear algebra support.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides classes to solve Ordinary Differential Equations problems.
Events
This package provides classes to solve non-stiff Ordinary Differential Equations problems.
Algorithms for optimizing a scalar function.
This package provides optimization algorithms that do not require derivatives.
Random number and random data generators.
Implementations of special functions such as Beta and Gamma.
Data storage, manipulation and summary routines.
Correlations/Covariance computations.
Generic univariate and multivariate summary statistic objects.
Summary statistics based on moments.
Summary statistics based on ranks.
Other summary statistics.
Multivariate statistics.
Statistical methods for fitting distributions.
Classes providing hypothesis testing.
Utilities to calculate binomial proportion confidence intervals.
Statistical routines involving multivariate data.
Implementations of transform methods, including Fast Fourier transforms.
Convenience routines and common data structures used throughout the Hipparchus library.
-
Uses of MathIllegalArgumentException in org.hipparchus
Modifier and TypeMethodDescriptionTwo arguments arc tangent operation.Returns the hypotenuse of a triangle with sidesthis
andy
- sqrt(this2 +y2) avoiding intermediate overflow or underflow.default T
CalculusFieldElement.linearCombination
(double[] a, T[] b) Compute a linear combination.CalculusFieldElement.linearCombination
(T[] a, T[] b) Compute a linear combination.Power operation. -
Uses of MathIllegalArgumentException in org.hipparchus.analysis
Modifier and TypeMethodDescriptionstatic 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
Modifier and TypeMethodDescriptionDerivativeStructure.add
(DerivativeStructure a) Compute this + a.FieldDerivativeStructure.add
(FieldDerivativeStructure<T> a) Compute this + a.DerivativeStructure.atan2
(DerivativeStructure x) Two arguments arc tangent operation.static DerivativeStructure
DerivativeStructure.atan2
(DerivativeStructure y, DerivativeStructure x) Two arguments arc tangent operation.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 aDerivativeStructure
from all its derivatives.FDSFactory.build
(double... derivatives) Build aFieldDerivativeStructure
from all its derivatives.final FieldDerivativeStructure<T>
Build aFieldDerivativeStructure
from all its derivatives.void
DSCompiler.checkCompatibility
(DSCompiler compiler) Check rules set compatibility.Derivative.compose
(double... f) Compute composition of the instance by a univariate function.DerivativeStructure.compose
(double... f) Compute composition of the instance by a univariate function.FieldDerivativeStructure.compose
(double... f) Compute composition of the instance by a univariate function.final FieldDerivativeStructure<T>
Compute composition of the instance by a univariate function.DerivativeStructure.divide
(DerivativeStructure a) Compute this ÷ a.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.FieldDerivative.getPartialDerivative
(int... orders) Get a partial derivative.FieldDerivativeStructure.getPartialDerivative
(int... orders) Get a partial derivative.FieldGradient.getPartialDerivative
(int n) Get the partial derivative with respect to one parameter.FieldGradient.getPartialDerivative
(int... orders) Get a partial derivative.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.hypot
(DerivativeStructure y) Returns the hypotenuse of a triangle with sidesthis
andy
- sqrt(this2 +y2) avoiding intermediate overflow or underflow.static DerivativeStructure
DerivativeStructure.hypot
(DerivativeStructure x, DerivativeStructure y) Returns the hypotenuse of a triangle with sidesx
andy
- sqrt(x2 +y2) avoiding intermediate overflow or underflow.FieldDerivativeStructure.hypot
(FieldDerivativeStructure<T> y) Returns the hypotenuse of a triangle with sidesthis
andy
- 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 sidesx
andy
- sqrt(x2 +y2) avoiding intermediate overflow or underflow.DerivativeStructure.linearCombination
(double[] a, DerivativeStructure[] b) Compute a linear combination.DerivativeStructure.linearCombination
(double a1, DerivativeStructure b1, double a2, DerivativeStructure b2) Compute a linear combination.DerivativeStructure.linearCombination
(double a1, DerivativeStructure b1, double a2, DerivativeStructure b2, double a3, DerivativeStructure b3) Compute a linear combination.DerivativeStructure.linearCombination
(double a1, DerivativeStructure b1, double a2, DerivativeStructure b2, double a3, DerivativeStructure b3, double a4, DerivativeStructure b4) Compute a linear combination.DerivativeStructure.linearCombination
(DerivativeStructure[] a, DerivativeStructure[] b) Compute a linear combination.DerivativeStructure.linearCombination
(DerivativeStructure a1, DerivativeStructure b1, DerivativeStructure a2, DerivativeStructure b2) Compute a linear combination.DerivativeStructure.linearCombination
(DerivativeStructure a1, DerivativeStructure b1, DerivativeStructure a2, DerivativeStructure b2, DerivativeStructure a3, DerivativeStructure b3) Compute a linear combination.DerivativeStructure.linearCombination
(DerivativeStructure a1, DerivativeStructure b1, DerivativeStructure a2, DerivativeStructure b2, DerivativeStructure a3, DerivativeStructure b3, DerivativeStructure a4, DerivativeStructure b4) Compute a linear combination.FieldDerivativeStructure.linearCombination
(double[] a, FieldDerivativeStructure<T>[] b) Compute a linear combination.FieldDerivativeStructure.linearCombination
(double a1, FieldDerivativeStructure<T> b1, double a2, FieldDerivativeStructure<T> b2) Compute a linear combination.FieldDerivativeStructure.linearCombination
(double a1, FieldDerivativeStructure<T> b1, double a2, FieldDerivativeStructure<T> b2, double a3, FieldDerivativeStructure<T> b3) Compute a linear combination.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.linearCombination
(FieldDerivativeStructure<T>[] a, FieldDerivativeStructure<T>[] b) Compute a linear combination.FieldDerivativeStructure.linearCombination
(FieldDerivativeStructure<T> a1, FieldDerivativeStructure<T> b1, FieldDerivativeStructure<T> a2, FieldDerivativeStructure<T> b2) Compute a linear combination.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.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.linearCombination
(T[] a, FieldDerivativeStructure<T>[] b) Compute a linear combination.FieldDerivativeStructure.linearCombination
(T a1, FieldDerivativeStructure<T> b1, T a2, FieldDerivativeStructure<T> b2) Compute a linear combination.FieldDerivativeStructure.linearCombination
(T a1, FieldDerivativeStructure<T> b1, T a2, FieldDerivativeStructure<T> b2, T a3, FieldDerivativeStructure<T> b3) Compute a linear combination.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.linearCombination
(SparseGradient[] a, SparseGradient[] b) Compute a linear combination.DerivativeStructure.multiply
(DerivativeStructure a) Compute this × a.FieldDerivativeStructure.multiply
(FieldDerivativeStructure<T> a) Compute this × a.DerivativeStructure.pow
(DerivativeStructure e) Power operation.FieldDerivativeStructure.pow
(FieldDerivativeStructure<T> e) Power operation.DerivativeStructure.remainder
(DerivativeStructure a) IEEE remainder operator.FieldDerivativeStructure.remainder
(FieldDerivativeStructure<T> a) IEEE remainder operator.DerivativeStructure.subtract
(DerivativeStructure a) Compute this - a.FieldDerivativeStructure.subtract
(FieldDerivativeStructure<T> a) Compute this - a.MultivariateDifferentiableFunction.value
(DerivativeStructure[] point) Compute the value for the function at the given point.MultivariateDifferentiableVectorFunction.value
(DerivativeStructure[] point) Compute the value for the function at the given point.<T extends Derivative<T>>
TUnivariateDifferentiableFunction.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.DSFactory.variable
(int index, double value) Build aDerivativeStructure
representing a variable.FDSFactory.variable
(int index, double value) Build aFieldDerivativeStructure
representing a variable.Build aFieldDerivativeStructure
representing a variable.ModifierConstructorDescriptionBuild an instance from aDerivativeStructure
.Build an instance from aDerivativeStructure
.Build an instance from aDerivativeStructure
.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.Build an instance from aDerivativeStructure
.Build an instance from aDerivativeStructure
.Build an instance from aDerivativeStructure
. -
Uses of MathIllegalArgumentException in org.hipparchus.analysis.function
Modifier and TypeMethodDescriptiondouble[]
Gaussian.Parametric.gradient
(double x, double... param) Computes the value of the gradient atx
.double[]
HarmonicOscillator.Parametric.gradient
(double x, double... param) Computes the value of the gradient atx
.double[]
Logistic.Parametric.gradient
(double x, double... param) Computes the value of the gradient atx
.double[]
Logit.Parametric.gradient
(double x, double... param) Computes the value of the gradient atx
.double[]
Sigmoid.Parametric.gradient
(double x, double... param) Computes the value of the gradient atx
.double
Gaussian.Parametric.value
(double x, double... param) Computes the value of the Gaussian atx
.<T extends Derivative<T>>
TGaussian.value
(T t) Compute the value for the function.double
HarmonicOscillator.Parametric.value
(double x, double... param) Computes the value of the harmonic oscillator atx
.<T extends Derivative<T>>
THarmonicOscillator.value
(T t) Compute the value for the function.double
Logistic.Parametric.value
(double x, double... param) Computes the value of the sigmoid atx
.double
Logit.Parametric.value
(double x, double... param) Computes the value of the logit atx
.double
Logit.value
(double x) Compute the value of the function.<T extends Derivative<T>>
TLogit.value
(T t) Compute the value for the function.double
Sigmoid.Parametric.value
(double x, double... param) Computes the value of the sigmoid atx
.<T extends Derivative<T>>
TSigmoid.value
(T t) Compute the value for the function.<T extends Derivative<T>>
TSinc.value
(T t) Compute the value for the function.ModifierConstructorDescriptionGaussian
(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
Modifier and TypeMethodDescriptionprotected 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.BaseAbstractFieldUnivariateIntegrator.integrate
(int maxEval, CalculusFieldUnivariateFunction<T> f, T lower, T upper) Integrate the function in the given interval.double
BaseAbstractUnivariateIntegrator.integrate
(int maxEval, UnivariateFunction f, double lower, double upper) Integrate the function in the given interval.FieldUnivariateIntegrator.integrate
(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max) Integrate the function in the given interval.double
UnivariateIntegrator.integrate
(int maxEval, UnivariateFunction f, double min, double max) Integrate the function in the given interval.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.ModifierConstructorDescriptionprotected
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
Modifier and TypeMethodDescriptionprotected 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.FieldAbstractRuleFactory.computeRule
(int numberOfPoints) Computes the rule for the given order.FieldHermiteRuleFactory.computeRule
(int numberOfPoints) Computes the rule for the given order.FieldLaguerreRuleFactory.computeRule
(int numberOfPoints) Computes the rule for the given order.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.FieldAbstractRuleFactory.getRule
(int numberOfPoints) Gets a copy of the quadrature rule with the given number of integration points.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.Creates a Gauss-Legendre integrator of the given order.GaussIntegratorFactory.legendre
(int numberOfPoints, double lowerBound, double upperBound) Creates a Gauss-Legendre integrator of the given order.GaussIntegratorFactory.legendreHighPrecision
(int numberOfPoints) Creates a Gauss-Legendre integrator of the given order.GaussIntegratorFactory.legendreHighPrecision
(int numberOfPoints, double lowerBound, double upperBound) Creates an integrator of the given order, and whose call to theintegrate
method will perform an integration on the given interval.ModifierConstructorDescriptionFieldGaussIntegrator
(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 givenpoints
andweights
.GaussIntegrator
(double[] points, double[] weights) Creates an integrator from the givenpoints
andweights
.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 givenpoints
andweights
.SymmetricGaussIntegrator
(double[] points, double[] weights) Creates an integrator from the givenpoints
andweights
.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
Modifier and TypeMethodDescriptionfinal 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.HermiteInterpolator.getPolynomials()
Compute the interpolation polynomials.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.BicubicInterpolator.interpolate
(double[] xval, double[] yval, double[][] fval) Compute an interpolating function for the dataset.BilinearInterpolator.interpolate
(double[] xval, double[] yval, double[][] fval) Compute an interpolating function for the dataset.BivariateGridInterpolator.interpolate
(double[] xval, double[] yval, double[][] fval) Compute an interpolating function for the dataset.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.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 aSplineInterpolator
on the resulting fit.MicrosphereProjectionInterpolator.interpolate
(double[][] xval, double[] yval) Computes an interpolating function for the data set.MultivariateInterpolator.interpolate
(double[][] xval, double[] yval) Computes an interpolating function for the data set.NevilleInterpolator.interpolate
(double[] x, double[] y) Computes an interpolating function for the data set.PiecewiseBicubicSplineInterpolator.interpolate
(double[] xval, double[] yval, double[][] fval) Compute an interpolating function for the dataset.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.TricubicInterpolator.interpolate
(double[] xval, double[] yval, double[] zval, double[][][] fval) Compute an interpolating function for the dataset.TrivariateGridInterpolator.interpolate
(double[] xval, double[] yval, double[] zval, double[][][] fval) Compute an interpolating function for the dataset.UnivariateInterpolator.interpolate
(double[] xval, double[] yval) Compute an interpolating function for the dataset.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[]
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>>
TPiecewiseBicubicSplineInterpolatingFunction.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.ModifierConstructorDescriptionBicubicInterpolatingFunction
(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 newLoessInterpolator
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
Modifier and TypeMethodDescriptionstatic 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>>
TFieldPolynomialFunction.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>>
TPolynomialFunction.value
(T t) Compute the value for the function.<T extends CalculusFieldElement<T>>
TPolynomialFunction.value
(T t) Compute the value of the function.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.ModifierConstructorDescriptionFieldPolynomialFunction
(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
Modifier and TypeMethodDescriptionstatic <T extends CalculusFieldElement<T>>
T[]UnivariateSolverUtils.bracket
(CalculusFieldUnivariateFunction<T> function, T initial, T lowerBound, T upperBound) This method simply callsbracket(function, initial, lowerBound, upperBound, q, r, maximumIterations)
withq
andr
set to 1.0 andmaximumIterations
set toInteger.MAX_VALUE
.static <T extends CalculusFieldElement<T>>
T[]UnivariateSolverUtils.bracket
(CalculusFieldUnivariateFunction<T> function, T initial, T lowerBound, T upperBound, int maximumIterations) This method simply callsbracket(function, initial, lowerBound, upperBound, q, r, maximumIterations)
withq
andr
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 satisfyinglowerBound <= a < initial < b <= upperBound
f(a) * f(b) <= 0
Iff
is continuous on[a,b]
, this means thata
andb
bracket a root off
.static double[]
UnivariateSolverUtils.bracket
(UnivariateFunction function, double initial, double lowerBound, double upperBound) This method simply callsbracket(function, initial, lowerBound, upperBound, q, r, maximumIterations)
withq
andr
set to 1.0 andmaximumIterations
set toInteger.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 satisfyinglowerBound <= a < initial < b <= upperBound
f(a) * f(b) <= 0
Iff
is continuous on[a,b]
, this means thata
andb
bracket a root off
.static double[]
UnivariateSolverUtils.bracket
(UnivariateFunction function, double initial, double lowerBound, double upperBound, int maximumIterations) This method simply callsbracket(function, initial, lowerBound, upperBound, q, r, maximumIterations)
withq
andr
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
Solve for a zero in the vicinity ofstartValue
.double
Solve for a zero in the given interval, start atstartValue
.double
Solve for a zero root in the given interval.double
Solve for a zero in the given interval, start atstartValue
.double
BracketingNthOrderBrentSolver.solve
(int maxEval, UnivariateFunction f, double min, double max, double startValue, AllowedSolution allowedSolution) Solve for a zero in the given interval, start atstartValue
.double
BracketingNthOrderBrentSolver.solve
(int maxEval, UnivariateFunction f, double min, double max, AllowedSolution allowedSolution) Solve for a zero in the given interval.FieldBracketingNthOrderBrentSolver.solve
(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max, AllowedSolution allowedSolution) Solve for a zero in the given interval.FieldBracketingNthOrderBrentSolver.solve
(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max, T startValue, AllowedSolution allowedSolution) Solve for a zero in the given interval, start atstartValue
.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.LaguerreSolver.solveComplex
(double[] coefficients, double initial) Find a complex root for the polynomial with the given coefficients, starting from the given initial value.BaseSecantSolver.solveInterval
(int maxEval, UnivariateFunction f, double min, double max, double startValue) Solve for a zero in the given interval and return a tolerance interval surrounding the root.BracketedRealFieldUnivariateSolver.solveInterval
(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max) Solve for a zero in the given interval and return a tolerance interval surrounding the root.BracketedRealFieldUnivariateSolver.solveInterval
(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max, T startValue) Solve for a zero in the given interval and return a tolerance interval surrounding the root.BracketedUnivariateSolver.solveInterval
(int maxEval, F f, double min, double max) Solve for a zero in the given interval and return a tolerance interval surrounding the root.BracketedUnivariateSolver.solveInterval
(int maxEval, F f, double min, double max, double startValue) Solve for a zero in the given interval and return a tolerance interval surrounding the root.BracketingNthOrderBrentSolver.solveInterval
(int maxEval, UnivariateFunction f, double min, double max, double startValue) Solve for a zero in the given interval and return a tolerance interval surrounding the root.FieldBracketingNthOrderBrentSolver.solveInterval
(int maxEval, CalculusFieldUnivariateFunction<T> f, T min, T max, T startValue) Solve for a zero in the given interval and return a tolerance interval surrounding the root.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 thatlower < initial < upper
.static void
UnivariateSolverUtils.verifySequence
(double lower, double initial, double upper) Check thatlower < initial < upper
.ModifierConstructorDescriptionBracketingNthOrderBrentSolver
(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
Modifier and TypeMethodDescriptionClusterer.cluster
(Collection<T> points) Perform a cluster analysis on the given set ofClusterable
instances.FuzzyKMeansClusterer.cluster
(Collection<T> dataPoints) Performs Fuzzy K-Means cluster analysis.KMeansPlusPlusClusterer.cluster
(Collection<T> points) Runs the K-means++ clustering algorithm.MultiKMeansPlusPlusClusterer.cluster
(Collection<T> points) Runs the K-means++ clustering algorithm.ModifierConstructorDescriptionDBSCANClusterer
(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
Modifier and TypeMethodDescriptiondouble
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
Modifier and TypeMethodDescriptionvoid
RootsOfUnity.computeRoots
(int n) Computes then
-th roots of unity.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 thek
-thn
-th root of unity.double
RootsOfUnity.getReal
(int k) Get the real part of thek
-thn
-th root of unity.Complex.linearCombination
(double[] a, Complex[] b) Compute a linear combination.Complex.linearCombination
(Complex[] a, Complex[] b) Compute a linear combination.FieldComplex.linearCombination
(double[] a, FieldComplex<T>[] b) Compute a linear combination.FieldComplex.linearCombination
(FieldComplex<T>[] a, FieldComplex<T>[] b) Compute a linear combination.Complex.nthRoot
(int n) Computes the n-th roots of this complex number.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.ModifierConstructorDescriptionComplexFormat
(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
Modifier and TypeMethodDescriptionTwo arguments arc tangent operation.Dfp.linearCombination
(double[] a, Dfp[] b) Compute a linear combination.Dfp.linearCombination
(Dfp[] a, Dfp[] b) Compute a linear combination. -
Uses of MathIllegalArgumentException in org.hipparchus.distribution
Modifier and TypeMethodDescriptionint
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 variableX
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
.double
RealDistribution.probability
(double x0, double x1) For a random variableX
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
.double[][]
MultivariateRealDistribution.sample
(int sampleSize) Generates a list of a random value vectors from the distribution.ModifierConstructorDescriptionEnumeratedDistribution
(List<Pair<T, Double>> pmf) Create an enumerated distribution using the given probability mass function enumeration. -
Uses of MathIllegalArgumentException in org.hipparchus.distribution.continuous
Modifier and TypeMethodDescriptiondouble
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 variableX
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
.double
LogNormalDistribution.probability
(double x0, double x1) For a random variableX
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
.double
NormalDistribution.probability
(double x0, double x1) For a random variableX
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
.ModifierConstructorDescriptionCauchyDistribution
(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
Modifier and TypeMethodDescriptionint
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 variableX
whose values are distributed according to this distribution, this method returnsP(x0 < X <= x1)
.ModifierConstructorDescriptionBinomialDistribution
(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
Modifier and TypeMethodDescriptiondouble
MultivariateNormalDistribution.density
(double[] vals) Returns the probability density function (PDF) of this distribution evaluated at the specified pointx
.ModifierConstructorDescriptionMixtureMultivariateNormalDistribution
(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
Modifier and TypeMethodDescriptionprotected void
AbstractKalmanFilter.correct
(T measurement, RealMatrix stm, RealVector innovation, RealMatrix h, RealMatrix s) Perform correction step. -
Uses of MathIllegalArgumentException in org.hipparchus.fraction
Modifier and TypeMethodDescriptionFractionFormat.format
(Object obj, StringBuffer toAppendTo, FieldPosition pos) Formats an object and appends the result to a StringBuffer.ModifierConstructorDescriptionBigFraction
(double value) Create a fraction given the double value. -
Uses of MathIllegalArgumentException in org.hipparchus.geometry
Modifier and TypeMethodDescriptiondefault 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
Modifier and TypeMethodDescriptionFieldVector3D.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
Reset the instance as if built from two points.ModifierConstructorDescriptionFieldLine
(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.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.Create a sub-line from a segment.Create a sub-line from two endpoints.Vector3D
(double[] v) Simple constructor. -
Uses of MathIllegalArgumentException in org.hipparchus.geometry.euclidean.twod
Modifier and TypeMethodDescriptionstatic Transform<Euclidean2D,
Euclidean1D> Line.getTransform
(double cXX, double cYX, double cXY, double cYY, double cX1, double cY1) Get aTransform
embedding an affine transform.ModifierConstructorDescriptionFieldVector2D
(T[] v) Simple constructor.Vector2D
(double[] v) Simple constructor. -
Uses of MathIllegalArgumentException in org.hipparchus.geometry.euclidean.twod.hull
Modifier and TypeMethodDescriptionConvexHull2D.createRegion()
Returns a new region that is enclosed by the convex hull.ModifierConstructorDescriptionConvexHull2D
(Vector2D[] vertices, double tolerance) Simple constructor. -
Uses of MathIllegalArgumentException in org.hipparchus.geometry.hull
Modifier and TypeMethodDescriptionConvexHull.createRegion()
Returns a new region that is enclosed by the convex hull. -
Uses of MathIllegalArgumentException in org.hipparchus.geometry.spherical.oned
Modifier and TypeClassDescriptionstatic class
Specialized exception for inconsistent BSP tree state inconsistency.Modifier and TypeMethodDescriptionstatic void
Sphere1D.checkTolerance
(double tolerance) Check tolerance againstSphere1D.SMALLEST_TOLERANCE
.ModifierConstructorDescriptionArc
(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).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
Modifier and TypeMethodDescriptionstatic void
Sphere2D.checkTolerance
(double tolerance) Check tolerance againstSphere2D.SMALLEST_TOLERANCE
.ModifierConstructorDescriptionBuild a great circle from its pole.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
Modifier and TypeMethodDescriptionAbstractFieldMatrix.add
(FieldMatrix<T> m) Compute the sum of this and m.AbstractRealMatrix.add
(RealMatrix m) Returns the sum ofthis
andm
.Array2DRowFieldMatrix.add
(Array2DRowFieldMatrix<T> m) Addm
to this matrix.Array2DRowRealMatrix.add
(Array2DRowRealMatrix m) Compute the sum ofthis
andm
.ArrayFieldVector.add
(ArrayFieldVector<T> v) Compute the sum ofthis
andv
.ArrayFieldVector.add
(FieldVector<T> v) Compute the sum ofthis
andv
.ArrayRealVector.add
(RealVector v) Compute the sum of this vector andv
.BlockFieldMatrix.add
(BlockFieldMatrix<T> m) Compute the sum ofthis
andm
.BlockFieldMatrix.add
(FieldMatrix<T> m) Compute the sum of this and m.BlockRealMatrix.add
(BlockRealMatrix m) Compute the sum of this matrix andm
.BlockRealMatrix.add
(RealMatrix m) Returns the sum ofthis
andm
.DiagonalMatrix.add
(DiagonalMatrix m) Compute the sum ofthis
andm
.FieldMatrix.add
(FieldMatrix<T> m) Compute the sum of this and m.FieldVector.add
(FieldVector<T> v) Compute the sum ofthis
andv
.OpenMapRealMatrix.add
(OpenMapRealMatrix m) Compute the sum of this matrix andm
.OpenMapRealVector.add
(OpenMapRealVector v) Optimized method to add two OpenMapRealVectors.OpenMapRealVector.add
(RealVector v) Compute the sum of this vector andv
.RealMatrix.add
(RealMatrix m) Returns the sum ofthis
andm
.RealVector.add
(RealVector v) Compute the sum of this vector andv
.SparseFieldVector.add
(FieldVector<T> v) Compute the sum ofthis
andv
.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 ofthis
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 ofthis
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 ofthis
matrix.void
DiagonalMatrix.addToEntry
(int row, int column, double increment) Adds (in place) the specified value to the specified entry ofthis
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 ofthis
matrix.void
RealMatrix.addToEntry
(int row, int column, double increment) Adds (in place) the specified value to the specified entry ofthis
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 compatibleprotected static void
IterativeLinearSolver.checkParameters
(RealLinearOperator a, RealVector b, RealVector x0) Performs all dimension checks on the parameters ofsolve
andsolveInPlace
, 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 ofsolve
andsolveInPlace
, 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 compatibleprotected 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.combine
(double a, double b, RealVector y) Returns a new vector representinga * this + b * y
, the linear combination ofthis
andy
.RealVector.combine
(double a, double b, RealVector y) Returns a new vector representinga * this + b * y
, the linear combination ofthis
andy
.ArrayRealVector.combineToSelf
(double a, double b, RealVector y) Updatesthis
with the linear combination ofthis
andy
.RealVector.combineToSelf
(double a, double b, RealVector y) Updatesthis
with the linear combination ofthis
andy
.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 columnFieldMatrix
using the data from the input array.static RealMatrix
MatrixUtils.createColumnRealMatrix
(double[] columnData) Creates a columnRealMatrix
using the data from the input array.static <T extends FieldElement<T>>
FieldMatrix<T>MatrixUtils.createFieldMatrix
(T[][] data) Returns aFieldMatrix
whose entries are the the values in the the input array.static <T extends FieldElement<T>>
FieldVector<T>MatrixUtils.createFieldVector
(T[] data) Creates aFieldVector
using the data from the input array.abstract FieldMatrix<T>
AbstractFieldMatrix.createMatrix
(int rowDimension, int columnDimension) Create a newFieldMatrix
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.Array2DRowFieldMatrix.createMatrix
(int rowDimension, int columnDimension) Create a newFieldMatrix
of the same type as the instance with the supplied row and column dimensions.Array2DRowRealMatrix.createMatrix
(int rowDimension, int columnDimension) Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.BlockFieldMatrix.createMatrix
(int rowDimension, int columnDimension) Create a newFieldMatrix
of the same type as the instance with the supplied row and column dimensions.BlockRealMatrix.createMatrix
(int rowDimension, int columnDimension) Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.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.createMatrix
(int rowDimension, int columnDimension) Create a newFieldMatrix
of the same type as the instance with the supplied row and column dimensions.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.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 aRealMatrix
whose entries are the the values in the the input array.static RealVector
MatrixUtils.createRealVector
(double[] data) Creates aRealVector
using the data from the input array.static <T extends FieldElement<T>>
FieldMatrix<T>MatrixUtils.createRowFieldMatrix
(T[] rowData) Create a rowFieldMatrix
using the data from the input array.static RealMatrix
MatrixUtils.createRowRealMatrix
(double[] rowData) Create a rowRealMatrix
using the data from the input array.FieldMatrixDecomposer.decompose
(FieldMatrix<T> a) Get a solver for finding the A × X = B solution in least square sense.MatrixDecomposer.decompose
(RealMatrix a) Get a solver for finding the A × X = B solution in least square sense.ArrayFieldVector.dotProduct
(ArrayFieldVector<T> v) Compute the dot product.ArrayFieldVector.dotProduct
(FieldVector<T> v) Compute the dot product.double
ArrayRealVector.dotProduct
(RealVector v) Compute the dot product of this vector withv
.FieldVector.dotProduct
(FieldVector<T> v) Compute the dot product.double
RealVector.dotProduct
(RealVector v) Compute the dot product of this vector withv
.SparseFieldVector.dotProduct
(FieldVector<T> v) Compute the dot product.ArrayFieldVector.ebeDivide
(ArrayFieldVector<T> v) Element-by-element division.ArrayFieldVector.ebeDivide
(FieldVector<T> v) Element-by-element division.ArrayRealVector.ebeDivide
(RealVector v) Element-by-element division.FieldVector.ebeDivide
(FieldVector<T> v) Element-by-element division.OpenMapRealVector.ebeDivide
(RealVector v) Element-by-element division.abstract RealVector
RealVector.ebeDivide
(RealVector v) Element-by-element division.SparseFieldVector.ebeDivide
(FieldVector<T> v) Element-by-element division.ArrayFieldVector.ebeMultiply
(ArrayFieldVector<T> v) Element-by-element multiplication.ArrayFieldVector.ebeMultiply
(FieldVector<T> v) Element-by-element multiplication.ArrayRealVector.ebeMultiply
(RealVector v) Element-by-element multiplication.FieldVector.ebeMultiply
(FieldVector<T> v) Element-by-element multiplication.OpenMapRealVector.ebeMultiply
(RealVector v) Element-by-element multiplication.abstract RealVector
RealVector.ebeMultiply
(RealVector v) Element-by-element multiplication.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 numbercol
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 numbercol
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 numbercol
as an array.double[]
RealMatrix.getColumn
(int column) Get the entries at the given column index as an array.AbstractFieldMatrix.getColumnMatrix
(int column) Get the entries in column numbercolumn
as a column matrix.AbstractRealMatrix.getColumnMatrix
(int column) Get the entries at the given column index as a column matrix.BlockFieldMatrix.getColumnMatrix
(int column) Get the entries in column numbercolumn
as a column matrix.BlockRealMatrix.getColumnMatrix
(int column) Get the entries at the given column index as a column matrix.FieldMatrix.getColumnMatrix
(int column) Get the entries in column numbercolumn
as a column matrix.RealMatrix.getColumnMatrix
(int column) Get the entries at the given column index as a column matrix.AbstractFieldMatrix.getColumnVector
(int column) Returns the entries in column numbercolumn
as a vector.AbstractRealMatrix.getColumnVector
(int column) Get the entries at the given column index as a vector.BlockFieldMatrix.getColumnVector
(int column) Returns the entries in column numbercolumn
as a vector.BlockRealMatrix.getColumnVector
(int column) Get the entries at the given column index as a vector.FieldMatrix.getColumnVector
(int column) Returns the entries in column numbercolumn
as a vector.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.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.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.FieldMatrix.getEntry
(int row, int column) Returns the entry in the specified row and column.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.SparseFieldVector.getEntry
(int index) Returns the entry in the specified index.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 numberrow
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 numberrow
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 numberrow
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 numberrow
as an array.double[]
RealMatrix.getRow
(int row) Get the entries at the given row index.AbstractFieldMatrix.getRowMatrix
(int row) Get the entries in row numberrow
as a row matrix.AbstractRealMatrix.getRowMatrix
(int row) Get the entries at the given row index as a row matrix.BlockFieldMatrix.getRowMatrix
(int row) Get the entries in row numberrow
as a row matrix.BlockRealMatrix.getRowMatrix
(int row) Get the entries at the given row index as a row matrix.FieldMatrix.getRowMatrix
(int row) Get the entries in row numberrow
as a row matrix.RealMatrix.getRowMatrix
(int row) Get the entries at the given row index as a row matrix.AbstractFieldMatrix.getRowVector
(int row) Get the entries in row numberrow
as a vector.AbstractRealMatrix.getRowVector
(int row) Returns the entries in row numberrow
as a vector.BlockFieldMatrix.getRowVector
(int row) Get the entries in row numberrow
as a vector.BlockRealMatrix.getRowVector
(int row) Returns the entries in row numberrow
as a vector.FieldMatrix.getRowVector
(int row) Get the entries in row numberrow
as a vector.RealMatrix.getRowVector
(int row) Returns the entries in row numberrow
as a vector.AbstractFieldMatrix.getSubMatrix
(int[] selectedRows, int[] selectedColumns) Get a submatrix.AbstractFieldMatrix.getSubMatrix
(int startRow, int endRow, int startColumn, int endColumn) Get a submatrix.AbstractRealMatrix.getSubMatrix
(int[] selectedRows, int[] selectedColumns) Gets a submatrix.AbstractRealMatrix.getSubMatrix
(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.Array2DRowFieldMatrix.getSubMatrix
(int startRow, int endRow, int startColumn, int endColumn) Get a submatrix.Array2DRowRealMatrix.getSubMatrix
(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.BlockFieldMatrix.getSubMatrix
(int startRow, int endRow, int startColumn, int endColumn) Get a submatrix.BlockRealMatrix.getSubMatrix
(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.FieldMatrix.getSubMatrix
(int[] selectedRows, int[] selectedColumns) Get a submatrix.FieldMatrix.getSubMatrix
(int startRow, int endRow, int startColumn, int endColumn) Get a submatrix.RealMatrix.getSubMatrix
(int[] selectedRows, int[] selectedColumns) Gets a submatrix.RealMatrix.getSubMatrix
(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.ArrayFieldVector.getSubVector
(int index, int n) Get a subvector from consecutive elements.ArrayRealVector.getSubVector
(int index, int n) Get a subvector from consecutive elements.FieldVector.getSubVector
(int index, int n) Get a subvector from consecutive elements.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.SparseFieldVector.getSubVector
(int index, int n) Get a subvector from consecutive elements.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).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.inverse()
Computes the inverse of this diagonal matrix.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.AbstractFieldMatrix.multiply
(FieldMatrix<T> m) Postmultiply this matrix bym
.AbstractRealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.Array2DRowFieldMatrix.multiply
(Array2DRowFieldMatrix<T> m) Postmultiplying this matrix bym
.Array2DRowRealMatrix.multiply
(Array2DRowRealMatrix m) Returns the result of postmultiplyingthis
bym
.BlockFieldMatrix.multiply
(BlockFieldMatrix<T> m) Returns the result of postmultiplyingthis
bym
.BlockFieldMatrix.multiply
(FieldMatrix<T> m) Postmultiply this matrix bym
.BlockRealMatrix.multiply
(BlockRealMatrix m) Returns the result of postmultiplying this bym
.BlockRealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.DiagonalMatrix.multiply
(DiagonalMatrix m) Returns the result of postmultiplyingthis
bym
.DiagonalMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.FieldMatrix.multiply
(FieldMatrix<T> m) Postmultiply this matrix bym
.OpenMapRealMatrix.multiply
(OpenMapRealMatrix m) Postmultiply this matrix bym
.OpenMapRealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.RealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.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 ofthis
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 ofthis
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 ofthis
matrix by the specified value.void
DiagonalMatrix.multiplyEntry
(int row, int column, double factor) Multiplies (in place) the specified entry ofthis
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 ofthis
matrix by the specified value.void
RealMatrix.multiplyEntry
(int row, int column, double factor) Multiplies (in place) the specified entry ofthis
matrix by the specified value.Array2DRowFieldMatrix.multiplyTransposed
(Array2DRowFieldMatrix<T> m) Returns the result of postmultiplyingthis
bym^T
.Array2DRowRealMatrix.multiplyTransposed
(Array2DRowRealMatrix m) Returns the result of postmultiplyingthis
bym^T
.BlockFieldMatrix.multiplyTransposed
(BlockFieldMatrix<T> m) Returns the result of postmultiplyingthis
bym^T
.BlockFieldMatrix.multiplyTransposed
(FieldMatrix<T> m) Returns the result of postmultiplyingthis
bym^T
.BlockRealMatrix.multiplyTransposed
(BlockRealMatrix m) Returns the result of postmultiplyingthis
bym^T
.BlockRealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.DiagonalMatrix.multiplyTransposed
(DiagonalMatrix m) Returns the result of postmultiplyingthis
bym^T
.DiagonalMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.default FieldMatrix<T>
FieldMatrix.multiplyTransposed
(FieldMatrix<T> m) Returns the result of postmultiplyingthis
bym^T
.OpenMapRealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.default RealMatrix
RealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.SparseFieldMatrix.multiplyTransposed
(FieldMatrix<T> m) Returns the result of postmultiplyingthis
bym^T
.AbstractFieldMatrix.operate
(FieldVector<T> v) Returns the result of multiplying this by the vectorv
.T[]
Returns the result of multiplying this by the vectorv
.double[]
AbstractRealMatrix.operate
(double[] v) Returns the result of multiplying this by the vectorv
.AbstractRealMatrix.operate
(RealVector v) Returns the result of multiplying this by the vectorv
.T[]
Returns the result of multiplying this by the vectorv
.double[]
Array2DRowRealMatrix.operate
(double[] v) Returns the result of multiplying this by the vectorv
.T[]
Returns the result of multiplying this by the vectorv
.double[]
BlockRealMatrix.operate
(double[] v) Returns the result of multiplying this by the vectorv
.double[]
DiagonalMatrix.operate
(double[] v) Returns the result of multiplying this by the vectorv
.FieldMatrix.operate
(FieldVector<T> v) Returns the result of multiplying this by the vectorv
.T[]
Returns the result of multiplying this by the vectorv
.RealLinearOperator.operate
(RealVector x) Returns the result of multiplyingthis
by the vectorx
.double[]
RealMatrix.operate
(double[] v) Returns the result of multiplying this by the vectorv
.RealMatrix.operate
(RealVector v) Returns the result of multiplying this by the vectorv
.default RealVector
RealLinearOperator.operateTranspose
(RealVector x) Returns the result of multiplying the transpose ofthis
operator by the vectorx
(optional operation).AbstractFieldMatrix.power
(int p) Returns the result multiplying this with itselfp
times.AbstractRealMatrix.power
(int p) Returns the result of multiplyingthis
with itselfp
times.FieldMatrix.power
(int p) Returns the result multiplying this with itselfp
times.RealMatrix.power
(int p) Returns the result of multiplyingthis
with itselfp
times.AbstractFieldMatrix.preMultiply
(FieldMatrix<T> m) Premultiply this matrix bym
.AbstractFieldMatrix.preMultiply
(FieldVector<T> v) Returns the (row) vector result of premultiplying this by the vectorv
.T[]
AbstractFieldMatrix.preMultiply
(T[] v) Returns the (row) vector result of premultiplying this by the vectorv
.double[]
AbstractRealMatrix.preMultiply
(double[] v) Returns the (row) vector result of premultiplying this by the vectorv
.AbstractRealMatrix.preMultiply
(RealMatrix m) Returns the result of premultiplyingthis
bym
.AbstractRealMatrix.preMultiply
(RealVector v) Returns the (row) vector result of premultiplying this by the vectorv
.T[]
Array2DRowFieldMatrix.preMultiply
(T[] v) Returns the (row) vector result of premultiplying this by the vectorv
.double[]
Array2DRowRealMatrix.preMultiply
(double[] v) Returns the (row) vector result of premultiplying this by the vectorv
.T[]
BlockFieldMatrix.preMultiply
(T[] v) Returns the (row) vector result of premultiplying this by the vectorv
.double[]
BlockRealMatrix.preMultiply
(double[] v) Returns the (row) vector result of premultiplying this by the vectorv
.double[]
DiagonalMatrix.preMultiply
(double[] v) Returns the (row) vector result of premultiplying this by the vectorv
.DiagonalMatrix.preMultiply
(RealVector v) Returns the (row) vector result of premultiplying this by the vectorv
.FieldMatrix.preMultiply
(FieldMatrix<T> m) Premultiply this matrix bym
.FieldMatrix.preMultiply
(FieldVector<T> v) Returns the (row) vector result of premultiplying this by the vectorv
.T[]
FieldMatrix.preMultiply
(T[] v) Returns the (row) vector result of premultiplying this by the vectorv
.double[]
RealMatrix.preMultiply
(double[] v) Returns the (row) vector result of premultiplying this by the vectorv
.RealMatrix.preMultiply
(RealMatrix m) Returns the result of premultiplyingthis
bym
.RealMatrix.preMultiply
(RealVector v) Returns the (row) vector result of premultiplying this by the vectorv
.ArrayFieldVector.projection
(ArrayFieldVector<T> v) Find the orthogonal projection of this vector onto another vector.ArrayFieldVector.projection
(FieldVector<T> v) Find the orthogonal projection of this vector onto another vector.FieldVector.projection
(FieldVector<T> v) Find the orthogonal projection of this vector onto another vector.RealVector.projection
(RealVector v) Find the orthogonal projection of this vector onto another vector.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
Set the entries in column numbercolumn
as a column matrix.void
AbstractRealMatrix.setColumn
(int column, double[] array) Sets the specifiedcolumn
ofthis
matrix to the entries of the specifiedarray
.void
Set the entries in column numbercolumn
as a column matrix.void
BlockRealMatrix.setColumn
(int column, double[] array) Sets the specifiedcolumn
ofthis
matrix to the entries of the specifiedarray
.void
Set the entries in column numbercolumn
as a column matrix.void
RealMatrix.setColumn
(int column, double[] array) Sets the specifiedcolumn
ofthis
matrix to the entries of the specifiedarray
.void
AbstractFieldMatrix.setColumnMatrix
(int column, FieldMatrix<T> matrix) Set the entries in column numbercolumn
as a column matrix.void
AbstractRealMatrix.setColumnMatrix
(int column, RealMatrix matrix) Sets the specifiedcolumn
ofthis
matrix to the entries of the specified columnmatrix
.void
BlockFieldMatrix.setColumnMatrix
(int column, FieldMatrix<T> matrix) Set the entries in column numbercolumn
as a column matrix.void
BlockRealMatrix.setColumnMatrix
(int column, RealMatrix matrix) Sets the specifiedcolumn
ofthis
matrix to the entries of the specified columnmatrix
.void
FieldMatrix.setColumnMatrix
(int column, FieldMatrix<T> matrix) Set the entries in column numbercolumn
as a column matrix.void
RealMatrix.setColumnMatrix
(int column, RealMatrix matrix) Sets the specifiedcolumn
ofthis
matrix to the entries of the specified columnmatrix
.void
AbstractFieldMatrix.setColumnVector
(int column, FieldVector<T> vector) Set the entries in column numbercolumn
as a vector.void
AbstractRealMatrix.setColumnVector
(int column, RealVector vector) Sets the specifiedcolumn
ofthis
matrix to the entries of the specifiedvector
.void
BlockFieldMatrix.setColumnVector
(int column, FieldVector<T> vector) Set the entries in column numbercolumn
as a vector.void
BlockRealMatrix.setColumnVector
(int column, RealVector vector) Sets the specifiedcolumn
ofthis
matrix to the entries of the specifiedvector
.void
FieldMatrix.setColumnVector
(int column, FieldVector<T> vector) Set the entries in column numbercolumn
as a vector.void
RealMatrix.setColumnVector
(int column, RealVector vector) Sets the specifiedcolumn
ofthis
matrix to the entries of the specifiedvector
.abstract void
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
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
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
Set the entry in the specified row and column.void
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
Set a single element.void
Set the entries in row numberrow
as a row matrix.void
AbstractRealMatrix.setRow
(int row, double[] array) Sets the specifiedrow
ofthis
matrix to the entries of the specifiedarray
.void
Set the entries in row numberrow
as a row matrix.void
Array2DRowRealMatrix.setRow
(int row, double[] array) Sets the specifiedrow
ofthis
matrix to the entries of the specifiedarray
.void
Set the entries in row numberrow
as a row matrix.void
BlockRealMatrix.setRow
(int row, double[] array) Sets the specifiedrow
ofthis
matrix to the entries of the specifiedarray
.void
Set the entries in row numberrow
as a row matrix.void
RealMatrix.setRow
(int row, double[] array) Sets the specifiedrow
ofthis
matrix to the entries of the specifiedarray
.void
AbstractFieldMatrix.setRowMatrix
(int row, FieldMatrix<T> matrix) Set the entries in row numberrow
as a row matrix.void
AbstractRealMatrix.setRowMatrix
(int row, RealMatrix matrix) Sets the specifiedrow
ofthis
matrix to the entries of the specified rowmatrix
.void
BlockFieldMatrix.setRowMatrix
(int row, BlockFieldMatrix<T> matrix) Sets the entries in row numberrow
as a row matrix.void
BlockFieldMatrix.setRowMatrix
(int row, FieldMatrix<T> matrix) Set the entries in row numberrow
as a row matrix.void
BlockRealMatrix.setRowMatrix
(int row, BlockRealMatrix matrix) Sets the entries in row numberrow
as a row matrix.void
BlockRealMatrix.setRowMatrix
(int row, RealMatrix matrix) Sets the specifiedrow
ofthis
matrix to the entries of the specified rowmatrix
.void
FieldMatrix.setRowMatrix
(int row, FieldMatrix<T> matrix) Set the entries in row numberrow
as a row matrix.void
RealMatrix.setRowMatrix
(int row, RealMatrix matrix) Sets the specifiedrow
ofthis
matrix to the entries of the specified rowmatrix
.void
AbstractFieldMatrix.setRowVector
(int row, FieldVector<T> vector) Set the entries in row numberrow
as a vector.void
AbstractRealMatrix.setRowVector
(int row, RealVector vector) Sets the specifiedrow
ofthis
matrix to the entries of the specifiedvector
.void
BlockFieldMatrix.setRowVector
(int row, FieldVector<T> vector) Set the entries in row numberrow
as a vector.void
BlockRealMatrix.setRowVector
(int row, RealVector vector) Sets the specifiedrow
ofthis
matrix to the entries of the specifiedvector
.void
FieldMatrix.setRowVector
(int row, FieldVector<T> vector) Set the entries in row numberrow
as a vector.void
RealMatrix.setRowVector
(int row, RealVector vector) Sets the specifiedrow
ofthis
matrix to the entries of the specifiedvector
.void
AbstractFieldMatrix.setSubMatrix
(T[][] subMatrix, int row, int column) Replace the submatrix starting at(row, column)
using data in the inputsubMatrix
array.void
AbstractRealMatrix.setSubMatrix
(double[][] subMatrix, int row, int column) Replace the submatrix starting atrow, column
using data in the inputsubMatrix
array.void
Array2DRowFieldMatrix.setSubMatrix
(T[][] subMatrix, int row, int column) Replace the submatrix starting at(row, column)
using data in the inputsubMatrix
array.void
Array2DRowRealMatrix.setSubMatrix
(double[][] subMatrix, int row, int column) Replace the submatrix starting atrow, column
using data in the inputsubMatrix
array.void
BlockFieldMatrix.setSubMatrix
(T[][] subMatrix, int row, int column) Replace the submatrix starting at(row, column)
using data in the inputsubMatrix
array.void
BlockRealMatrix.setSubMatrix
(double[][] subMatrix, int row, int column) Replace the submatrix starting atrow, column
using data in the inputsubMatrix
array.void
FieldMatrix.setSubMatrix
(T[][] subMatrix, int row, int column) Replace the submatrix starting at(row, column)
using data in the inputsubMatrix
array.void
RealMatrix.setSubMatrix
(double[][] subMatrix, int row, int column) Replace the submatrix starting atrow, column
using data in the inputsubMatrix
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.DecompositionSolver.solve
(RealMatrix b) Solve the linear equation A × X = B for matrices A.DecompositionSolver.solve
(RealVector b) Solve the linear equation A × X = B for matrices A.IterativeLinearSolver.solve
(RealLinearOperator a, RealVector b) Returns an estimate of the solution to the linear system A · x = b.IterativeLinearSolver.solve
(RealLinearOperator a, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.PreconditionedIterativeLinearSolver.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b) Returns an estimate of the solution to the linear system A · x = b.PreconditionedIterativeLinearSolver.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.PreconditionedIterativeLinearSolver.solve
(RealLinearOperator a, RealVector b) Returns an estimate of the solution to the linear system A · x = b.PreconditionedIterativeLinearSolver.solve
(RealLinearOperator a, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b, boolean goodb, double shift) Returns an estimate of the solution to the linear system (A - shift · I) · x = b.SymmLQ.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealVector b) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealVector b) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealVector b, boolean goodb, double shift) Returns the solution to the system (A - shift · I) · x = b.SymmLQ.solve
(RealLinearOperator a, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solve
(RealLinearOperator a, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.ConjugateGradient.solveInPlace
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.abstract RealVector
IterativeLinearSolver.solveInPlace
(RealLinearOperator a, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.abstract RealVector
PreconditionedIterativeLinearSolver.solveInPlace
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.PreconditionedIterativeLinearSolver.solveInPlace
(RealLinearOperator a, RealVector b, RealVector x0) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solveInPlace
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solveInPlace
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.SymmLQ.solveInPlace
(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x, boolean goodb, double shift) Returns an estimate of the solution to the linear system (A - shift · I) · x = b.SymmLQ.solveInPlace
(RealLinearOperator a, RealVector b, RealVector x) Returns an estimate of the solution to the linear system A · x = b.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 MatrixRealMatrix
.static void
MatrixUtils.solveUpperTriangularSystem
(RealMatrix rm, RealVector b) Solver a system composed of an Upper Triangular MatrixRealMatrix
.AbstractFieldMatrix.subtract
(FieldMatrix<T> m) Subtractm
from this matrix.AbstractRealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.Array2DRowFieldMatrix.subtract
(Array2DRowFieldMatrix<T> m) Subtractm
from this matrix.Array2DRowRealMatrix.subtract
(Array2DRowRealMatrix m) Returnsthis
minusm
.ArrayFieldVector.subtract
(ArrayFieldVector<T> v) Computethis
minusv
.ArrayFieldVector.subtract
(FieldVector<T> v) Computethis
minusv
.ArrayRealVector.subtract
(RealVector v) Subtractv
from this vector.BlockFieldMatrix.subtract
(BlockFieldMatrix<T> m) Computethis - m
.BlockFieldMatrix.subtract
(FieldMatrix<T> m) Subtractm
from this matrix.BlockRealMatrix.subtract
(BlockRealMatrix m) Subtractm
from this matrix.BlockRealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.DiagonalMatrix.subtract
(DiagonalMatrix m) Returnsthis
minusm
.FieldMatrix.subtract
(FieldMatrix<T> m) Subtractm
from this matrix.FieldVector.subtract
(FieldVector<T> v) Computethis
minusv
.OpenMapRealMatrix.subtract
(OpenMapRealMatrix m) Subtractm
from this matrix.OpenMapRealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.OpenMapRealVector.subtract
(OpenMapRealVector v) Optimized method to subtract OpenMapRealVectors.OpenMapRealVector.subtract
(RealVector v) Subtractv
from this vector.RealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.RealVector.subtract
(RealVector v) Subtractv
from this vector.SparseFieldVector.subtract
(FieldVector<T> v) Computethis
minusv
.SparseFieldVector.subtract
(SparseFieldVector<T> v) Optimized method to computethis
minusv
.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.Array2DRowFieldMatrix.transposeMultiply
(Array2DRowFieldMatrix<T> m) Returns the result of postmultiplyingthis^T
bym
.Array2DRowRealMatrix.transposeMultiply
(Array2DRowRealMatrix m) Returns the result of postmultiplyingthis^T
bym
.BlockFieldMatrix.transposeMultiply
(BlockFieldMatrix<T> m) Returns the result of postmultiplyingthis^T
bym
.BlockFieldMatrix.transposeMultiply
(FieldMatrix<T> m) Returns the result of postmultiplyingthis^T
bym
.BlockRealMatrix.transposeMultiply
(BlockRealMatrix m) Returns the result of postmultiplyingthis^T
bym
.BlockRealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.DiagonalMatrix.transposeMultiply
(DiagonalMatrix m) Returns the result of postmultiplyingthis^T
bym
.default FieldMatrix<T>
FieldMatrix.transposeMultiply
(FieldMatrix<T> m) Returns the result of postmultiplyingthis^T
bym
.OpenMapRealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.default RealMatrix
RealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.SparseFieldMatrix.transposeMultiply
(FieldMatrix<T> m) Returns the result of postmultiplyingthis^T
bym
.AbstractFieldMatrix.walkInColumnOrder
(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in column order.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.Array2DRowFieldMatrix.walkInColumnOrder
(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in column order.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.FieldMatrix.walkInColumnOrder
(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in column order.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.ArrayFieldVector.walkInDefaultOrder
(FieldVectorChangingVisitor<T> visitor, int start, int end) Visits (and possibly alters) some entries of this vector in default order (increasing index).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).SparseFieldVector.walkInDefaultOrder
(FieldVectorChangingVisitor<T> visitor, int start, int end) Visits (and possibly alters) some entries of this vector in default order (increasing index).SparseFieldVector.walkInDefaultOrder
(FieldVectorPreservingVisitor<T> visitor, int start, int end) Visits (but does not alter) some entries of this vector in default order (increasing index).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.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.ArrayFieldVector.walkInOptimizedOrder
(FieldVectorChangingVisitor<T> visitor, int start, int end) Visits (and possibly change) some entries of this vector in optimized order.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.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.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.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.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.SparseFieldVector.walkInOptimizedOrder
(FieldVectorChangingVisitor<T> visitor, int start, int end) Visits (and possibly change) some entries of this vector in optimized order.SparseFieldVector.walkInOptimizedOrder
(FieldVectorPreservingVisitor<T> visitor, int start, int end) Visits (but does not alter) some entries of this vector in optimized order.AbstractFieldMatrix.walkInRowOrder
(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.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.Array2DRowFieldMatrix.walkInRowOrder
(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.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.BlockFieldMatrix.walkInRowOrder
(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.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.FieldMatrix.walkInRowOrder
(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn) Visit (and possibly change) some matrix entries in row order.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.ModifierConstructorDescriptionprotected
AbstractFieldMatrix
(Field<T> field, int rowDimension, int columnDimension) Create a newFieldMatrix
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 newFieldMatrix<T>
with the supplied row and column dimensions.Array2DRowFieldMatrix
(Field<T> field, T[][] d) Create a newFieldMatrix<T>
using the input array as the underlying data array.Array2DRowFieldMatrix
(Field<T> field, T[][] d, boolean copyArray) Create a newFieldMatrix<T>
using the input array as the underlying data array.Array2DRowFieldMatrix
(T[] v) Create a new (column)FieldMatrix<T>
usingv
as the data for the unique column of the created matrix.Array2DRowFieldMatrix
(T[][] d) Create a newFieldMatrix<T>
using the input array as the underlying data array.Array2DRowFieldMatrix
(T[][] d, boolean copyArray) Create a newFieldMatrix<T>
using the input array as the underlying data array.Array2DRowRealMatrix
(double[][] d) Create a newRealMatrix
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.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
Modifier and TypeClassDescriptionclass
Deprecated.class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
-
Uses of MathIllegalArgumentException in org.hipparchus.migration.genetics
Modifier and TypeClassDescriptionclass
Deprecated.as of 1.0, this exception is replaced byMathIllegalStateException
-
Uses of MathIllegalArgumentException in org.hipparchus.migration.geometry.euclidean.threed
Modifier and TypeClassDescriptionclass
Deprecated.as of 1.0, this exception is replaced byMathIllegalStateException
-
Uses of MathIllegalArgumentException in org.hipparchus.migration.linear
Modifier and TypeClassDescriptionclass
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalStateException
class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
-
Uses of MathIllegalArgumentException in org.hipparchus.migration.ode
Modifier and TypeClassDescriptionstatic class
Deprecated.Special exception for equations mismatch.class
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
Modifier and TypeMethodDescriptionvoid
FirstOrderDifferentialEquations.computeDerivatives
(double t, double[] y, double[] yDot) Deprecated.Get the current time derivative of the state vector.default double[]
SecondaryEquations.computeDerivatives
(double t, double[] primary, double[] primaryDot, double[] secondary) Deprecated.Compute the derivatives related to the secondary state parameters.void
SecondaryEquations.computeDerivatives
(double t, double[] primary, double[] primaryDot, double[] secondary, double[] secondaryDot) Deprecated.Compute the derivatives related to the secondary state parameters.double[][]
MainStateJacobianProvider.computeMainStateJacobian
(double t, double[] y, double[] yDot) Deprecated.Compute the jacobian matrix of ODE with respect to main state.default double[]
ParameterJacobianProvider.computeParameterJacobian
(double t, double[] y, double[] yDot, String paramName) Deprecated.Compute the Jacobian matrix of ODE with respect to one parameter.void
ParameterJacobianProvider.computeParameterJacobian
(double t, double[] y, double[] yDot, String paramName, double[] dFdP) Deprecated.Compute the Jacobian matrix of ODE with respect to one parameter.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.ModifierConstructorDescriptionJacobianMatrices
(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
Modifier and TypeClassDescriptionclass
Deprecated.as of 1.0, this exception is replaced byMathIllegalArgumentException
-
Uses of MathIllegalArgumentException in org.hipparchus.ode
Modifier and TypeClassDescriptionstatic class
Special exception for equations mismatch.Modifier and TypeMethodDescriptionprotected FieldODEStateAndDerivative<T>
AbstractFieldIntegrator.acceptStep
(AbstractFieldODEStateInterpolator<T> interpolator, T tEnd) Accept a step, triggering events and step handlers.protected ODEStateAndDerivative
AbstractIntegrator.acceptStep
(AbstractODEStateInterpolator interpolator, double tEnd) Accept a step, triggering events and step handlers.void
DenseOutputModel.append
(DenseOutputModel model) Append another model at the end of the instance.void
FieldDenseOutputModel.append
(FieldDenseOutputModel<T> model) Append another model at the end of the instance.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.FieldODEIntegrator.integrate
(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.ODEIntegrator.integrate
(ExpandableODE equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time.default ODEStateAndDerivative
ODEIntegrator.integrate
(OrdinaryDifferentialEquation equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time.EquationsMapper.mapStateAndDerivative
(double t, double[] y, double[] yDot) Map flat arrays to a state and derivative.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.ModifierConstructorDescriptionprotected
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
Modifier and TypeMethodDescriptionboolean
DetectorBasedEventState.evaluateStep
(ODEStateInterpolator interpolator) Evaluate the impact of the proposed step on the handler.boolean
EventState.evaluateStep
(ODEStateInterpolator interpolator) Evaluate the impact of the proposed step on the handler.boolean
FieldDetectorBasedEventState.evaluateStep
(FieldODEStateInterpolator<T> interpolator) Evaluate the impact of the proposed step on the event handler.boolean
FieldEventState.evaluateStep
(FieldODEStateInterpolator<T> interpolator) Evaluate the impact of the proposed step on the event handler. -
Uses of MathIllegalArgumentException in org.hipparchus.ode.nonstiff
Modifier and TypeMethodDescriptiondouble
StepsizeHelper.filterStep
(double h, boolean forward, boolean acceptSmall) Filter the integration step.<T extends CalculusFieldElement<T>>
TStepsizeHelper.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.AdamsFieldIntegrator.integrate
(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.AdamsIntegrator.integrate
(ExpandableODE equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time.EmbeddedRungeKuttaFieldIntegrator.integrate
(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.EmbeddedRungeKuttaIntegrator.integrate
(ExpandableODE equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time.GraggBulirschStoerIntegrator.integrate
(ExpandableODE equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time.RungeKuttaFieldIntegrator.integrate
(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime) Integrate the differential equations up to the given time.RungeKuttaIntegrator.integrate
(ExpandableODE equations, ODEState initialState, double finalTime) Integrate the differential equations up to the given time.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.ModifierConstructorDescriptionAdamsBashforthFieldIntegrator
(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
ModifierConstructorDescriptionMultiStartMultivariateOptimizer
(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
Modifier and TypeMethodDescriptionCMAESOptimizer.optimize
(OptimizationData... optData) Stores data and performs the optimization.ModifierConstructorDescriptionPopulationSize
(int size) Simple constructor.Sigma
(double[] s) Simple constructor. -
Uses of MathIllegalArgumentException in org.hipparchus.random
Modifier and TypeMethodDescriptionRandomDataGenerator.nextHexString
(int len) Generates a random string of hex characters of lengthlen
.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 lengthk
whose entries are selected randomly, without repetition, from the integers0, ..., n - 1
(inclusive).double[]
RandomDataGenerator.nextSample
(double[] a, int k) Returns an array ofk
double values selected randomly from the double arraya
.Object[]
RandomDataGenerator.nextSample
(Collection<?> c, int k) Returns an array ofk
objects selected randomly from the Collectionc
.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.ModifierConstructorDescriptionHaltonSequenceGenerator
(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
Modifier and TypeMethodDescriptionstatic double
Gamma.logGamma1p
(double x) Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5.static <T extends CalculusFieldElement<T>>
TGamma.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
Modifier and TypeMethodDescriptionstatic double
StatUtils.geometricMean
(double... values) Returns the geometric mean of the entries in the input array, orDouble.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, orDouble.NaN
if the designated subarray is empty.static double
StatUtils.max
(double... values) Returns the maximum of the entries in the input array, orDouble.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, orDouble.NaN
if the designated subarray is empty.static double
StatUtils.mean
(double... values) Returns the arithmetic mean of the entries in the input array, orDouble.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, orDouble.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, orDouble.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, orDouble.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 thep
th percentile of the values in thevalues
array.static double
StatUtils.percentile
(double[] values, int begin, int length, double p) Returns an estimate of thep
th percentile of the values in thevalues
array, starting with the element in (0-based) positionbegin
in the array and includinglength
values.static double
StatUtils.populationVariance
(double... values) Returns the population variance of the entries in the input array, orDouble.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, orDouble.NaN
if the designated subarray is empty.static double
StatUtils.product
(double... values) Returns the product of the entries in the input array, orDouble.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, orDouble.NaN
if the designated subarray is empty.static double
StatUtils.sum
(double... values) Returns the sum of the values in the input array, orDouble.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, orDouble.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, orDouble.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, orDouble.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, orDouble.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, orDouble.NaN
if the designated subarray is empty.static double
StatUtils.variance
(double... values) Returns the variance of the entries in the input array, orDouble.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, orDouble.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
Modifier and TypeMethodDescriptionvoid
StorelessCovariance.append
(StorelessCovariance sc) Appendssc
to this, effectively aggregating the computations insc
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.StorelessCovariance.getCovarianceMatrix()
Returns the covariance matrixdouble[][]
StorelessCovariance.getData()
Return the covariance matrix as two-dimensional array.void
StorelessCovariance.increment
(double[] data) Increment the covariance matrix with one row of data.ModifierConstructorDescriptionCovariance
(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
Modifier and TypeMethodDescriptionvoid
MultivariateSummaryStatistics.addValue
(double[] value) Add an n-tuple to the datadouble
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.ModifierConstructorDescriptionDescriptiveStatistics
(int size) Construct a DescriptiveStatistics instance with the specified window. -
Uses of MathIllegalArgumentException in org.hipparchus.stat.descriptive.moment
Modifier and TypeMethodDescriptiondouble
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, orDouble.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, orDouble.NaN
if the designated subarray is empty.double
SemiVariance.evaluate
(double[] values, double cutoff) Returns theSemiVariance
of the designated values against the cutoff, using instance properties variancDirection and biasCorrection.double
SemiVariance.evaluate
(double[] values, double cutoff, SemiVariance.Direction direction) Returns theSemiVariance
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 theSemiVariance
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 theSemiVariance
of the designated values against the mean, using instance properties varianceDirection and biasCorrection.double
SemiVariance.evaluate
(double[] values, SemiVariance.Direction direction) This method calculatesSemiVariance
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, orDouble.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, orDouble.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, orDouble.NaN
if the designated subarray is empty. -
Uses of MathIllegalArgumentException in org.hipparchus.stat.descriptive.rank
Modifier and TypeMethodDescriptiondouble
Max.evaluate
(double[] values, int begin, int length) Returns the maximum of the entries in the specified portion of the input array, orDouble.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, orDouble.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 thep
th percentile of the values in thevalues
array.double
Percentile.evaluate
(double[] values, int start, int length) Returns an estimate of thequantile
th percentile of the designated values in thevalues
array.double
Percentile.evaluate
(double[] values, int begin, int length, double p) Returns an estimate of thep
th percentile of the values in thevalues
array, starting with the element in (0-based) positionbegin
in the array and includinglength
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).ModifierConstructorDescriptionPercentile
(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
andKthSelector
. -
Uses of MathIllegalArgumentException in org.hipparchus.stat.descriptive.summary
Modifier and TypeMethodDescriptiondouble
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, orDouble.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, orDouble.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, orDouble.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, orDouble.NaN
if the designated subarray is empty. -
Uses of MathIllegalArgumentException in org.hipparchus.stat.descriptive.vector
Modifier and TypeMethodDescriptionvoid
VectorialCovariance.increment
(double[] v) Add a new vector to the sample. -
Uses of MathIllegalArgumentException in org.hipparchus.stat.fitting
Modifier and TypeMethodDescriptionMultivariateNormalMixtureExpectationMaximization.estimate
(double[][] data, int numComponents) Helper method to create a multivariate normal mixture model which can be used to initializeMultivariateNormalMixtureExpectationMaximization.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
Computes the empirical distribution using data read from a URL.ModifierConstructorDescriptionMultivariateNormalMixtureExpectationMaximization
(double[][] data) Creates an object to fit a multivariate normal mixture model to data. -
Uses of MathIllegalArgumentException in org.hipparchus.stat.inference
Modifier and TypeMethodDescriptiondouble
OneWayAnova.anovaFValue
(Collection<double[]> categoryData) Computes the ANOVA F-value for a collection ofdouble[]
arrays.double
OneWayAnova.anovaPValue
(Collection<double[]> categoryData) Computes the ANOVA P-value for a collection ofdouble[]
arrays.double
OneWayAnova.anovaPValue
(Collection<StreamingStatistics> categoryData, boolean allowOneElementData) Computes the ANOVA P-value for a collection ofStreamingStatistics
.boolean
OneWayAnova.anovaTest
(Collection<double[]> categoryData, double alpha) Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.double
ChiSquareTest.chiSquare
(double[] expected, long[] observed) double
ChiSquareTest.chiSquare
(long[][] counts) Computes the Chi-Square statistic associated with a chi-square test of independence based on the inputcounts
array, viewed as a two-way table.static double
InferenceTestUtils.chiSquare
(double[] expected, long[] observed) static double
InferenceTestUtils.chiSquare
(long[][] counts) Computes the Chi-Square statistic associated with a chi-square test of independence based on the inputcounts
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 inobserved1
andobserved2
.static double
InferenceTestUtils.chiSquareDataSetsComparison
(long[] observed1, long[] observed2) Computes a Chi-Square two sample test statistic comparing bin frequency counts inobserved1
andobserved2
.double
ChiSquareTest.chiSquareTest
(double[] expected, long[] observed) Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing theobserved
frequency counts to those in theexpected
array.boolean
ChiSquareTest.chiSquareTest
(double[] expected, long[] observed, double alpha) Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance levelalpha
.double
ChiSquareTest.chiSquareTest
(long[][] counts) Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the inputcounts
array, viewed as a two-way table.boolean
ChiSquareTest.chiSquareTest
(long[][] counts, double alpha) Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance levelalpha
.static double
InferenceTestUtils.chiSquareTest
(double[] expected, long[] observed) Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing theobserved
frequency counts to those in theexpected
array.static boolean
InferenceTestUtils.chiSquareTest
(double[] expected, long[] observed, double alpha) Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance levelalpha
.static double
InferenceTestUtils.chiSquareTest
(long[][] counts) Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the inputcounts
array, viewed as a two-way table.static boolean
InferenceTestUtils.chiSquareTest
(long[][] counts, double alpha) Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance levelalpha
.double
ChiSquareTest.chiSquareTestDataSetsComparison
(long[] observed1, long[] observed2) Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts inobserved1
andobserved2
.boolean
ChiSquareTest.chiSquareTestDataSetsComparison
(long[] observed1, long[] observed2, double alpha) Performs a Chi-Square two sample test comparing two binned data sets.static double
InferenceTestUtils.chiSquareTestDataSetsComparison
(long[] observed1, long[] observed2) Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts inobserved1
andobserved2
.static boolean
InferenceTestUtils.chiSquareTestDataSetsComparison
(long[] observed1, long[] observed2, double alpha) Performs a Chi-Square two sample test comparing two binned data sets.double
GTest.g
(double[] expected, long[] observed) static double
InferenceTestUtils.g
(double[] expected, long[] observed) double
GTest.gDataSetsComparison
(long[] observed1, long[] observed2) Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts inobserved1
andobserved2
.static double
InferenceTestUtils.gDataSetsComparison
(long[] observed1, long[] observed2) Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts inobserved1
andobserved2
.double
GTest.gTest
(double[] expected, long[] observed) Returns the observed significance level, or p-value, associated with a G-Test for goodness of fit comparing theobserved
frequency counts to those in theexpected
array.boolean
GTest.gTest
(double[] expected, long[] observed, double alpha) Performs a G-Test (Log-Likelihood Ratio Test) for goodness of fit evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance levelalpha
.static double
InferenceTestUtils.gTest
(double[] expected, long[] observed) Returns the observed significance level, or p-value, associated with a G-Test for goodness of fit comparing theobserved
frequency counts to those in theexpected
array.static boolean
InferenceTestUtils.gTest
(double[] expected, long[] observed, double alpha) Performs a G-Test (Log-Likelihood Ratio Test) for goodness of fit evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance levelalpha
.double
GTest.gTestDataSetsComparison
(long[] observed1, long[] observed2) Returns the observed significance level, or p-value, associated with a G-Value (Log-Likelihood Ratio) for two sample test comparing bin frequency counts inobserved1
andobserved2
.boolean
GTest.gTestDataSetsComparison
(long[] observed1, long[] observed2, double alpha) Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets.static double
InferenceTestUtils.gTestDataSetsComparison
(long[] observed1, long[] observed2) Returns the observed significance level, or p-value, associated with a G-Value (Log-Likelihood Ratio) for two sample test comparing bin frequency counts inobserved1
andobserved2
.static boolean
InferenceTestUtils.gTestDataSetsComparison
(long[] observed1, long[] observed2, double alpha) Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets.double
GTest.gTestIntrinsic
(double[] expected, long[] observed) Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described in p64-69 of McDonald, J.H.static double
InferenceTestUtils.gTestIntrinsic
(double[] expected, long[] observed) Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described in p64-69 of McDonald, J.H.static double
InferenceTestUtils.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 twoStatisticalSummary
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 twoStatisticalSummary
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 thatsample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
, assuming that the subpopulation variances are equal.static double
InferenceTestUtils.homoscedasticTTest
(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.double
TTest.homoscedasticTTest
(double[] sample1, double[] sample2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances.boolean
TTest.homoscedasticTTest
(double[] sample1, double[] sample2, double alpha) Performs a two-sided t-test evaluating the null hypothesis thatsample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
, assuming that the subpopulation variances are equal.protected double
TTest.homoscedasticTTest
(double m1, double m2, double v1, double v2, double n1, double n2) Computes p-value for 2-sided, 2-sample t-test, under the assumption of equal subpopulation variances.double
TTest.homoscedasticTTest
(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.static double
InferenceTestUtils.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 ofx
, \(m\) is the length ofy
, \(F_n\) is the empirical distribution that puts mass \(1/n\) at each of the values inx
and \(F_m\) is the empirical distribution of they
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 withdistribution
, \(n\) is the length ofdata
and \(F_n\) is the empirical distribution that puts mass \(1/n\) at each of the values indata
.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 thatx
andy
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 thatx
andy
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 thatdata
conforms todistribution
.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 thatdata
conforms todistribution
.static boolean
InferenceTestUtils.kolmogorovSmirnovTest
(RealDistribution dist, double[] data, double alpha) Performs a Kolmogorov-Smirnov test evaluating the null hypothesis thatdata
conforms todistribution
.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 ofdouble[]
arrays.static double
InferenceTestUtils.oneWayAnovaPValue
(Collection<double[]> categoryData) Computes the ANOVA P-value for a collection ofdouble[]
arrays.static boolean
InferenceTestUtils.oneWayAnovaTest
(Collection<double[]> categoryData, double alpha) Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.static double
InferenceTestUtils.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 betweensample1
andsample2
is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance levelalpha
.double
TTest.pairedTTest
(double[] sample1, double[] sample2) Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays.boolean
TTest.pairedTTest
(double[] sample1, double[] sample2, double alpha) Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences betweensample1
andsample2
is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance levelalpha
.static double
InferenceTestUtils.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) static double
InferenceTestUtils.t
(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Computes a 2-sample t statistic, comparing the means of the datasets described by twoStatisticalSummary
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) double
TTest.t
(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Computes a 2-sample t statistic, comparing the means of the datasets described by twoStatisticalSummary
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 thatsample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
.static double
InferenceTestUtils.tTest
(double mu, double[] sample) Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constantmu
.static boolean
InferenceTestUtils.tTest
(double mu, double[] sample, double alpha) Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from whichsample
is drawn equalsmu
.static double
InferenceTestUtils.tTest
(double mu, StatisticalSummary sampleStats) Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described bysampleStats
with the constantmu
.static boolean
InferenceTestUtils.tTest
(double mu, StatisticalSummary sampleStats, double alpha) Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described bystats
is drawn equalsmu
.static double
InferenceTestUtils.tTest
(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.static boolean
InferenceTestUtils.tTest
(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha) Performs a two-sided t-test evaluating the null hypothesis thatsampleStats1
andsampleStats2
describe datasets drawn from populations with the same mean, with significance levelalpha
.double
TTest.tTest
(double[] sample1, double[] sample2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.boolean
TTest.tTest
(double[] sample1, double[] sample2, double alpha) Performs a two-sided t-test evaluating the null hypothesis thatsample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
.double
TTest.tTest
(double mu, double[] sample) Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constantmu
.boolean
TTest.tTest
(double mu, double[] sample, double alpha) Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from whichsample
is drawn equalsmu
.protected double
TTest.tTest
(double m, double mu, double v, double n) Computes p-value for 2-sided, 1-sample t-test.protected double
TTest.tTest
(double m1, double m2, double v1, double v2, double n1, double n2) Computes p-value for 2-sided, 2-sample t-test.double
TTest.tTest
(double mu, StatisticalSummary sampleStats) Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described bysampleStats
with the constantmu
.boolean
TTest.tTest
(double mu, StatisticalSummary sampleStats, double alpha) Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described bystats
is drawn equalsmu
.double
TTest.tTest
(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2) Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.boolean
TTest.tTest
(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha) Performs a two-sided t-test evaluating the null hypothesis thatsampleStats1
andsampleStats2
describe datasets drawn from populations with the same mean, with significance levelalpha
.double
WilcoxonSignedRankTest.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
Modifier and TypeMethodDescriptionstatic 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
Modifier and TypeMethodDescriptionvoid
SimpleRegression.addData
(double[][] data) Adds the observations represented by the elements indata
.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.MillerUpdatingRegression.regress()
Conducts a regression on the data in the model, using all regressors.MillerUpdatingRegression.regress
(int numberOfRegressors) Conducts a regression on the data in the model, using a subset of regressors.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.SimpleRegression.regress()
Performs a regression on data present in buffers and outputs a RegressionResults object.SimpleRegression.regress
(int[] variablesToInclude) Performs a regression on data present in buffers including only regressors indexed in variablesToInclude and outputs a RegressionResults objectUpdatingMultipleLinearRegression.regress()
Performs a regression on data present in buffers and outputs a RegressionResults objectUpdatingMultipleLinearRegression.regress
(int[] variablesToInclude) Performs a regression on data present in buffers including only regressors indexed in variablesToInclude and outputs a RegressionResults objectprotected void
AbstractMultipleLinearRegression.validateSampleData
(double[][] x, double[] y) Validates sample data.ModifierConstructorDescriptionMillerUpdatingRegression
(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
Modifier and TypeMethodDescriptionstatic Complex[]
TransformUtils.createComplexArray
(double[][] dataRI) Builds a new array ofComplex
from the specified two dimensional array of real and imaginary parts.static int
TransformUtils.exactLog2
(int n) Returns the base-2 logarithm of the specifiedint
.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
Modifier and TypeMethodDescriptionstatic long
CombinatoricsUtils.binomialCoefficient
(int n, int k) Returns an exact representation of the Binomial Coefficient, "n choose k
", the number ofk
-element subsets that can be selected from ann
-element set.static double
CombinatoricsUtils.binomialCoefficientDouble
(int n, int k) Returns adouble
representation of the Binomial Coefficient, "n choose k
", the number ofk
-element subsets that can be selected from ann
-element set.static double
CombinatoricsUtils.binomialCoefficientLog
(int n, int k) Returns the naturallog
of the Binomial Coefficient, "n choose k
", the number ofk
-element subsets that can be selected from ann
-element set.Blendable.blendArithmeticallyWith
(B other, double blendingValue) Blend arithmetically this instance with another one.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 isNaN
.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>>
voidMathArrays.checkOrder
(T[] val) Check that the given array is sorted in strictly increasing order.static <T extends CalculusFieldElement<T>>
voidMathArrays.checkOrder
(T[] val, MathArrays.OrderDirection dir, boolean strict) Check that the given array is sorted.static <T extends CalculusFieldElement<T>>
booleanMathArrays.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 thei
initial elements of the array.void
ResizableDoubleArray.discardMostRecentElements
(int i) Discards thei
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) static double
CombinatoricsUtils.factorialLog
(int n) Compute the natural logarithm of the factorial ofn
.int
MultidimensionalCounter.getCount
(int... c) Convert to unidimensional counter.int[]
MultidimensionalCounter.getCounts
(int index) Convert to multidimensional counter.Binary64.linearCombination
(double[] a, Binary64[] b) Compute a linear combination.Binary64.linearCombination
(Binary64[] a, Binary64[] b) Compute a linear combination.FieldTuple.linearCombination
(double[] a, FieldTuple<T>[] b) Compute a linear combination.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.linearCombination
(double[] a, Tuple[] b) Compute a linear combination.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 madestatic 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 ann
-element set intok
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.ModifierConstructorDescriptionMultidimensionalCounter
(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.
MathIllegalArgumentException