Uses of Class
org.apache.commons.math3.exception.DimensionMismatchException
-
Packages that use DimensionMismatchException Package Description org.apache.commons.math3 Common classes used throughout the commons-math library.org.apache.commons.math3.analysis.differentiation This package holds the main interfaces and basic building block classes dealing with differentiation.org.apache.commons.math3.analysis.function Thefunction
package contains function objects that wrap the methods contained inMath
, as well as common mathematical functions such as the gaussian and sinc functions.org.apache.commons.math3.analysis.integration.gauss Gauss family of quadrature schemes.org.apache.commons.math3.analysis.interpolation Univariate real functions interpolation algorithms.org.apache.commons.math3.analysis.polynomials Univariate real polynomials implementations, seen as differentiable univariate real functions.org.apache.commons.math3.complex Complex number type and implementations of complex transcendental functions.org.apache.commons.math3.dfp Decimal floating point library for Javaorg.apache.commons.math3.distribution Implementations of common discrete and continuous distributions.org.apache.commons.math3.distribution.fitting Fitting of parameters against distributions.org.apache.commons.math3.filter Implementations of common discrete-time linear filters.org.apache.commons.math3.genetics This package provides Genetic Algorithms components and implementations.org.apache.commons.math3.geometry.euclidean.threed This package provides basic 3D geometry components.org.apache.commons.math3.geometry.euclidean.twod This package provides basic 2D geometry components.org.apache.commons.math3.linear Linear algebra support.org.apache.commons.math3.ml.distance Common distance measures.org.apache.commons.math3.ode This package provides classes to solve Ordinary Differential Equations problems.org.apache.commons.math3.ode.nonstiff This package provides classes to solve non-stiff Ordinary Differential Equations problems.org.apache.commons.math3.optim.nonlinear.scalar.noderiv This package provides optimization algorithms that do not require derivatives.org.apache.commons.math3.optim.nonlinear.vector Algorithms for optimizing a vector function.org.apache.commons.math3.optimization.direct This package provides optimization algorithms that don't require derivatives.org.apache.commons.math3.random Random number and random data generators.org.apache.commons.math3.stat Data storage, manipulation and summary routines.org.apache.commons.math3.stat.correlation Correlations/Covariance computations.org.apache.commons.math3.stat.descriptive Generic univariate summary statistic objects.org.apache.commons.math3.stat.descriptive.moment Summary statistics based on moments.org.apache.commons.math3.stat.inference Classes providing hypothesis testing.org.apache.commons.math3.transform Implementations of transform methods, including Fast Fourier transforms.org.apache.commons.math3.util Convenience routines and common data structures used throughout the commons-math library. -
-
Uses of DimensionMismatchException in org.apache.commons.math3
Methods in org.apache.commons.math3 that throw DimensionMismatchException Modifier and Type Method Description T
RealFieldElement. atan2(T x)
Two arguments arc tangent operation.T
RealFieldElement. hypot(T y)
Returns the hypotenuse of a triangle with sidesthis
andy
- sqrt(this2 +y2) avoiding intermediate overflow or underflow.T
RealFieldElement. linearCombination(double[] a, T[] b)
Compute a linear combination.T
RealFieldElement. linearCombination(T[] a, T[] b)
Compute a linear combination.T
RealFieldElement. pow(T e)
Power operation.T
RealFieldElement. remainder(T a)
IEEE remainder operator. -
Uses of DimensionMismatchException in org.apache.commons.math3.analysis.differentiation
Methods in org.apache.commons.math3.analysis.differentiation that throw DimensionMismatchException Modifier and Type Method Description DerivativeStructure
DerivativeStructure. add(DerivativeStructure a)
Compute this + a.DerivativeStructure
DerivativeStructure. atan2(DerivativeStructure x)
Two arguments arc tangent operation.static DerivativeStructure
DerivativeStructure. atan2(DerivativeStructure y, DerivativeStructure x)
Two arguments arc tangent operation.void
DSCompiler. checkCompatibility(DSCompiler compiler)
Check rules set compatibility.DerivativeStructure
DerivativeStructure. compose(double... f)
Compute composition of the instance by a univariate function.DerivativeStructure
DerivativeStructure. divide(DerivativeStructure a)
Compute this ÷ a.double
DerivativeStructure. getPartialDerivative(int... orders)
Get a partial derivative.int
DSCompiler. getPartialDerivativeIndex(int... orders)
Get the index of a partial derivative in the array.DerivativeStructure
DerivativeStructure. hypot(DerivativeStructure y)
Returns the hypotenuse of a triangle with 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.DerivativeStructure
DerivativeStructure. linearCombination(double[] a, DerivativeStructure[] b)
Compute a linear combination.DerivativeStructure
DerivativeStructure. linearCombination(double a1, DerivativeStructure b1, double a2, DerivativeStructure b2)
Compute a linear combination.DerivativeStructure
DerivativeStructure. linearCombination(double a1, DerivativeStructure b1, double a2, DerivativeStructure b2, double a3, DerivativeStructure b3)
Compute a linear combination.DerivativeStructure
DerivativeStructure. linearCombination(double a1, DerivativeStructure b1, double a2, DerivativeStructure b2, double a3, DerivativeStructure b3, double a4, DerivativeStructure b4)
Compute a linear combination.DerivativeStructure
DerivativeStructure. linearCombination(DerivativeStructure[] a, DerivativeStructure[] b)
Compute a linear combination.DerivativeStructure
DerivativeStructure. linearCombination(DerivativeStructure a1, DerivativeStructure b1, DerivativeStructure a2, DerivativeStructure b2)
Compute a linear combination.DerivativeStructure
DerivativeStructure. linearCombination(DerivativeStructure a1, DerivativeStructure b1, DerivativeStructure a2, DerivativeStructure b2, DerivativeStructure a3, DerivativeStructure b3)
Compute a linear combination.DerivativeStructure
DerivativeStructure. linearCombination(DerivativeStructure a1, DerivativeStructure b1, DerivativeStructure a2, DerivativeStructure b2, DerivativeStructure a3, DerivativeStructure b3, DerivativeStructure a4, DerivativeStructure b4)
Compute a linear combination.SparseGradient
SparseGradient. linearCombination(SparseGradient[] a, SparseGradient[] b)
Compute a linear combination.DerivativeStructure
DerivativeStructure. multiply(DerivativeStructure a)
Compute this × a.DerivativeStructure
DerivativeStructure. pow(DerivativeStructure e)
Power operation.DerivativeStructure
DerivativeStructure. remainder(DerivativeStructure a)
IEEE remainder operator.DerivativeStructure
DerivativeStructure. subtract(DerivativeStructure a)
Compute this - a.DerivativeStructure
UnivariateDifferentiableFunction. value(DerivativeStructure t)
Simple mathematical function.Constructors in org.apache.commons.math3.analysis.differentiation that throw DimensionMismatchException Constructor Description DerivativeStructure(double a1, DerivativeStructure ds1, double a2, DerivativeStructure ds2)
Linear combination constructor.DerivativeStructure(double a1, DerivativeStructure ds1, double a2, DerivativeStructure ds2, double a3, DerivativeStructure ds3)
Linear combination constructor.DerivativeStructure(double a1, DerivativeStructure ds1, double a2, DerivativeStructure ds2, double a3, DerivativeStructure ds3, double a4, DerivativeStructure ds4)
Linear combination constructor.DerivativeStructure(int parameters, int order, double... derivatives)
Build an instance from all its derivatives. -
Uses of DimensionMismatchException in org.apache.commons.math3.analysis.function
Methods in org.apache.commons.math3.analysis.function that throw DimensionMismatchException Modifier and Type Method Description double[]
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
.DerivativeStructure
Gaussian. value(DerivativeStructure t)
Simple mathematical function.double
HarmonicOscillator.Parametric. value(double x, double... param)
Computes the value of the harmonic oscillator atx
.DerivativeStructure
HarmonicOscillator. value(DerivativeStructure t)
Simple mathematical 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
Sigmoid.Parametric. value(double x, double... param)
Computes the value of the sigmoid atx
.DerivativeStructure
Sigmoid. value(DerivativeStructure t)
Simple mathematical function.DerivativeStructure
Sinc. value(DerivativeStructure t)
Simple mathematical function.Constructors in org.apache.commons.math3.analysis.function that throw DimensionMismatchException Constructor Description StepFunction(double[] x, double[] y)
Builds a step function from a list of arguments and the corresponding values. -
Uses of DimensionMismatchException in org.apache.commons.math3.analysis.integration.gauss
Methods in org.apache.commons.math3.analysis.integration.gauss that throw DimensionMismatchException Modifier and Type Method Description protected void
BaseRuleFactory. addRule(Pair<T[],T[]> rule)
Stores a rule.protected abstract Pair<T[],T[]>
BaseRuleFactory. 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<BigDecimal[],BigDecimal[]>
LegendreHighPrecisionRuleFactory. 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[]>
BaseRuleFactory. getRule(int numberOfPoints)
Gets a copy of the quadrature rule with the given number of integration points.protected Pair<T[],T[]>
BaseRuleFactory. getRuleInternal(int numberOfPoints)
Gets a rule.Constructors in org.apache.commons.math3.analysis.integration.gauss that throw DimensionMismatchException Constructor Description GaussIntegrator(double[] points, double[] weights)
Creates an integrator from the givenpoints
andweights
.SymmetricGaussIntegrator(double[] points, double[] weights)
Creates an integrator from the givenpoints
andweights
. -
Uses of DimensionMismatchException in org.apache.commons.math3.analysis.interpolation
Methods in org.apache.commons.math3.analysis.interpolation that throw DimensionMismatchException Modifier and Type Method Description void
FieldHermiteInterpolator. addSamplePoint(T x, T[]... value)
Add a sample point.protected static double[]
DividedDifferenceInterpolator. computeDividedDifference(double[] x, double[] y)
Return a copy of the divided difference array.PolynomialSplineFunction
AkimaSplineInterpolator. interpolate(double[] xvals, double[] yvals)
Computes an interpolating function for the data set.BicubicInterpolatingFunction
BicubicInterpolator. interpolate(double[] xval, double[] yval, double[][] fval)
Compute an interpolating function for the dataset.BicubicSplineInterpolatingFunction
BicubicSplineInterpolator. interpolate(double[] xval, double[] yval, double[][] fval)
Deprecated.Compute an interpolating function for the dataset.BivariateFunction
BivariateGridInterpolator. interpolate(double[] xval, double[] yval, double[][] fval)
Compute an interpolating function for the dataset.PolynomialFunctionNewtonForm
DividedDifferenceInterpolator. interpolate(double[] x, double[] y)
Compute an interpolating function for the dataset.PolynomialSplineFunction
LinearInterpolator. interpolate(double[] x, double[] y)
Computes a linear interpolating function for the data set.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.MultivariateFunction
MicrosphereInterpolator. interpolate(double[][] xval, double[] yval)
Deprecated.Computes an interpolating function for the data set.MultivariateFunction
MicrosphereProjectionInterpolator. interpolate(double[][] xval, double[] yval)
Computes an interpolating function for the data set.MultivariateFunction
MultivariateInterpolator. interpolate(double[][] xval, double[] yval)
Computes an interpolating function for the data set.PolynomialFunctionLagrangeForm
NevilleInterpolator. interpolate(double[] x, double[] y)
Computes an interpolating function for the data set.PiecewiseBicubicSplineInterpolatingFunction
PiecewiseBicubicSplineInterpolator. interpolate(double[] xval, double[] yval, double[][] fval)
Compute an interpolating function for the dataset.BicubicSplineInterpolatingFunction
SmoothingPolynomialBicubicSplineInterpolator. interpolate(double[] xval, double[] yval, double[][] fval)
Deprecated.Compute an interpolating function for the dataset.PolynomialSplineFunction
SplineInterpolator. interpolate(double[] x, double[] y)
Computes an interpolating function for the data set.TricubicInterpolatingFunction
TricubicInterpolator. interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)
Compute an interpolating function for the dataset.TricubicSplineInterpolatingFunction
TricubicSplineInterpolator. interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)
Deprecated.Compute an interpolating function for the dataset.TrivariateFunction
TrivariateGridInterpolator. interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)
Compute an interpolating function for the dataset.UnivariateFunction
UnivariateInterpolator. interpolate(double[] xval, double[] yval)
Compute an interpolating function for the dataset.double[]
LoessInterpolator. smooth(double[] xval, double[] yval)
Compute a loess fit on the data at the original abscissae.double[]
LoessInterpolator. smooth(double[] xval, double[] yval, double[] weights)
Compute a weighted loess fit on the data at the original abscissae.double
MicrosphereInterpolatingFunction. value(double[] point)
Deprecated.Constructors in org.apache.commons.math3.analysis.interpolation that throw DimensionMismatchException Constructor Description BicubicInterpolatingFunction(double[] x, double[] y, double[][] f, double[][] dFdX, double[][] dFdY, double[][] d2FdXdY)
BicubicSplineInterpolatingFunction(double[] x, double[] y, double[][] f, double[][] dFdX, double[][] dFdY, double[][] d2FdXdY)
Deprecated.BicubicSplineInterpolatingFunction(double[] x, double[] y, double[][] f, double[][] dFdX, double[][] dFdY, double[][] d2FdXdY, boolean initializeDerivatives)
Deprecated.MicrosphereInterpolatingFunction(double[][] xval, double[] yval, int brightnessExponent, int microsphereElements, UnitSphereRandomVectorGenerator rand)
Deprecated.PiecewiseBicubicSplineInterpolatingFunction(double[] x, double[] y, double[][] f)
TricubicInterpolatingFunction(double[] x, double[] y, double[] z, double[][][] f, double[][][] dFdX, double[][][] dFdY, double[][][] dFdZ, double[][][] d2FdXdY, double[][][] d2FdXdZ, double[][][] d2FdYdZ, double[][][] d3FdXdYdZ)
TricubicSplineInterpolatingFunction(double[] x, double[] y, double[] z, double[][][] f, double[][][] dFdX, double[][][] dFdY, double[][][] dFdZ, double[][][] d2FdXdY, double[][][] d2FdXdZ, double[][][] d2FdYdZ, double[][][] d3FdXdYdZ)
Deprecated. -
Uses of DimensionMismatchException in org.apache.commons.math3.analysis.polynomials
Methods in org.apache.commons.math3.analysis.polynomials that throw DimensionMismatchException Modifier and Type Method Description 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.protected static void
PolynomialFunctionNewtonForm. verifyInputArray(double[] a, double[] c)
Verifies that the input arrays are valid.static boolean
PolynomialFunctionLagrangeForm. verifyInterpolationArray(double[] x, double[] y, boolean abort)
Check that the interpolation arrays are valid.Constructors in org.apache.commons.math3.analysis.polynomials that throw DimensionMismatchException Constructor Description 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 DimensionMismatchException in org.apache.commons.math3.complex
Constructors in org.apache.commons.math3.complex that throw DimensionMismatchException Constructor Description Quaternion(double scalar, double[] v)
Builds a quaternion from scalar and vector parts. -
Uses of DimensionMismatchException in org.apache.commons.math3.dfp
Methods in org.apache.commons.math3.dfp that throw DimensionMismatchException Modifier and Type Method Description Dfp
Dfp. atan2(Dfp x)
Two arguments arc tangent operation.Dfp
Dfp. linearCombination(double[] a, Dfp[] b)
Compute a linear combination.Dfp
Dfp. linearCombination(Dfp[] a, Dfp[] b)
Compute a linear combination. -
Uses of DimensionMismatchException in org.apache.commons.math3.distribution
Methods in org.apache.commons.math3.distribution that throw DimensionMismatchException Modifier and Type Method Description double
MultivariateNormalDistribution. density(double[] vals)
Returns the probability density function (PDF) of this distribution evaluated at the specified pointx
.Constructors in org.apache.commons.math3.distribution that throw DimensionMismatchException Constructor Description EnumeratedIntegerDistribution(int[] singletons, double[] probabilities)
Create a discrete distribution using the given probability mass function definition.EnumeratedIntegerDistribution(RandomGenerator rng, int[] singletons, double[] probabilities)
Create a discrete distribution using the given random number generator and probability mass function definition.EnumeratedRealDistribution(double[] singletons, double[] probabilities)
Create a discrete real-valued distribution using the given probability mass function enumeration.EnumeratedRealDistribution(RandomGenerator rng, double[] singletons, double[] probabilities)
Create a discrete real-valued distribution using the given random number generator and probability mass function enumeration.MixtureMultivariateNormalDistribution(RandomGenerator rng, List<Pair<Double,MultivariateNormalDistribution>> components)
Creates a mixture model from a list of distributions and their associated weights.MultivariateNormalDistribution(double[] means, double[][] covariances)
Creates a multivariate normal distribution with the given mean vector and covariance matrix.MultivariateNormalDistribution(RandomGenerator rng, double[] means, double[][] covariances)
Creates a multivariate normal distribution with the given mean vector and covariance matrix. -
Uses of DimensionMismatchException in org.apache.commons.math3.distribution.fitting
Methods in org.apache.commons.math3.distribution.fitting that throw DimensionMismatchException Modifier and Type Method Description static MixtureMultivariateNormalDistribution
MultivariateNormalMixtureExpectationMaximization. estimate(double[][] data, int numComponents)
Helper method to create a multivariate normal mixture model which can be used to initializeMultivariateNormalMixtureExpectationMaximization.fit(MixtureMultivariateNormalDistribution)
.void
MultivariateNormalMixtureExpectationMaximization. fit(MixtureMultivariateNormalDistribution initialMixture, int maxIterations, double threshold)
Fit a mixture model to the data supplied to the constructor.Constructors in org.apache.commons.math3.distribution.fitting that throw DimensionMismatchException Constructor Description MultivariateNormalMixtureExpectationMaximization(double[][] data)
Creates an object to fit a multivariate normal mixture model to data. -
Uses of DimensionMismatchException in org.apache.commons.math3.filter
Methods in org.apache.commons.math3.filter that throw DimensionMismatchException Modifier and Type Method Description void
KalmanFilter. correct(double[] z)
Correct the current state estimate with an actual measurement.void
KalmanFilter. correct(RealVector z)
Correct the current state estimate with an actual measurement.void
KalmanFilter. predict(double[] u)
Predict the internal state estimation one time step ahead.void
KalmanFilter. predict(RealVector u)
Predict the internal state estimation one time step ahead.Constructors in org.apache.commons.math3.filter that throw DimensionMismatchException Constructor Description DefaultMeasurementModel(double[][] measMatrix, double[][] measNoise)
Create a newMeasurementModel
, taking double arrays as input parameters for the respective measurement matrix and noise.DefaultProcessModel(double[][] stateTransition, double[][] control, double[][] processNoise)
Create a newProcessModel
, taking double arrays as input parameters.DefaultProcessModel(double[][] stateTransition, double[][] control, double[][] processNoise, double[] initialStateEstimate, double[][] initialErrorCovariance)
Create a newProcessModel
, taking double arrays as input parameters.KalmanFilter(ProcessModel process, MeasurementModel measurement)
Creates a new Kalman filter with the given process and measurement models. -
Uses of DimensionMismatchException in org.apache.commons.math3.genetics
Methods in org.apache.commons.math3.genetics that throw DimensionMismatchException Modifier and Type Method Description ChromosomePair
CycleCrossover. crossover(Chromosome first, Chromosome second)
Perform a crossover operation on the given chromosomes.ChromosomePair
NPointCrossover. crossover(Chromosome first, Chromosome second)
Performs a N-point crossover.ChromosomePair
OnePointCrossover. crossover(Chromosome first, Chromosome second)
Performs one point crossover.ChromosomePair
OrderedCrossover. crossover(Chromosome first, Chromosome second)
Perform a crossover operation on the given chromosomes.ChromosomePair
UniformCrossover. crossover(Chromosome first, Chromosome second)
Perform a crossover operation on the given chromosomes.static <S> List<Double>
RandomKey. inducedPermutation(List<S> originalData, List<S> permutedData)
Generates a representation of a permutation corresponding to a permutation which yieldspermutedData
when applied tooriginalData
.protected ChromosomePair
CycleCrossover. mate(AbstractListChromosome<T> first, AbstractListChromosome<T> second)
Helper forCycleCrossover.crossover(Chromosome, Chromosome)
.protected ChromosomePair
OrderedCrossover. mate(AbstractListChromosome<T> first, AbstractListChromosome<T> second)
-
Uses of DimensionMismatchException in org.apache.commons.math3.geometry.euclidean.threed
Constructors in org.apache.commons.math3.geometry.euclidean.threed that throw DimensionMismatchException Constructor Description FieldVector3D(T[] v)
Simple constructor.Vector3D(double[] v)
Simple constructor. -
Uses of DimensionMismatchException in org.apache.commons.math3.geometry.euclidean.twod
Constructors in org.apache.commons.math3.geometry.euclidean.twod that throw DimensionMismatchException Constructor Description Vector2D(double[] v)
Simple constructor. -
Uses of DimensionMismatchException in org.apache.commons.math3.linear
Subclasses of DimensionMismatchException in org.apache.commons.math3.linear Modifier and Type Class Description class
NonSquareMatrixException
Exception to be thrown when a square matrix is expected.class
NonSquareOperatorException
Exception to be thrown when a square linear operator is expected.Methods in org.apache.commons.math3.linear that throw DimensionMismatchException Modifier and Type Method Description ArrayFieldVector<T>
ArrayFieldVector. add(ArrayFieldVector<T> v)
Compute the sum ofthis
andv
.FieldVector<T>
ArrayFieldVector. add(FieldVector<T> v)
Compute the sum ofthis
andv
.ArrayRealVector
ArrayRealVector. add(RealVector v)
Compute the sum of this vector andv
.FieldVector<T>
FieldVector. add(FieldVector<T> v)
Compute the sum ofthis
andv
.OpenMapRealVector
OpenMapRealVector. add(OpenMapRealVector v)
Optimized method to add two OpenMapRealVectors.RealVector
OpenMapRealVector. add(RealVector v)
Compute the sum of this vector andv
.RealVector
RealVector. add(RealVector v)
Compute the sum of this vector andv
.FieldVector<T>
SparseFieldVector. add(FieldVector<T> v)
Compute the sum ofthis
andv
.FieldVector<T>
SparseFieldVector. add(SparseFieldVector<T> v)
Optimized method to add sparse vectors.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
ArrayFieldVector. checkVectorDimensions(int n)
Check if instance dimension is equal to some expected value.protected void
ArrayFieldVector. checkVectorDimensions(FieldVector<T> v)
Check if instance and specified vectors have the same dimension.protected void
ArrayRealVector. checkVectorDimensions(int n)
Check if instance dimension is equal to some expected value.protected void
ArrayRealVector. checkVectorDimensions(RealVector v)
Check if instance and specified vectors have the same dimension.protected void
RealVector. checkVectorDimensions(int n)
Check if instance dimension is equal to some expected value.protected void
RealVector. checkVectorDimensions(RealVector v)
Check if instance and specified vectors have the same dimension.protected void
SparseFieldVector. checkVectorDimensions(int n)
Check if instance dimension is equal to some expected value.ArrayRealVector
ArrayRealVector. combine(double a, double b, RealVector y)
Returns a new vector representinga * this + b * y
, the linear combination ofthis
andy
.RealVector
RealVector. combine(double a, double b, RealVector y)
Returns a new vector representinga * this + b * y
, the linear combination ofthis
andy
.ArrayRealVector
ArrayRealVector. combineToSelf(double a, double b, RealVector y)
Updatesthis
with the linear combination ofthis
andy
.RealVector
RealVector. combineToSelf(double a, double b, RealVector y)
Updatesthis
with the linear combination ofthis
andy
.double
RealVector. cosine(RealVector v)
Computes the cosine of the angle between this vector and the argument.static <T extends FieldElement<T>>
FieldMatrix<T>MatrixUtils. createFieldMatrix(T[][] data)
Returns aFieldMatrix
whose entries are the the values in the the input array.RealMatrix
DiagonalMatrix. createMatrix(int rowDimension, int columnDimension)
Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.static RealMatrix
MatrixUtils. createRealMatrix(double[][] data)
Returns aRealMatrix
whose entries are the the values in the the input array.T
ArrayFieldVector. dotProduct(ArrayFieldVector<T> v)
Compute the dot product.T
ArrayFieldVector. dotProduct(FieldVector<T> v)
Compute the dot product.double
ArrayRealVector. dotProduct(RealVector v)
Compute the dot product of this vector withv
.T
FieldVector. dotProduct(FieldVector<T> v)
Compute the dot product.double
OpenMapRealVector. dotProduct(OpenMapRealVector v)
Deprecated.as of 3.1 (to be removed in 4.0).double
RealVector. dotProduct(RealVector v)
Compute the dot product of this vector withv
.T
SparseFieldVector. dotProduct(FieldVector<T> v)
Compute the dot product.ArrayFieldVector<T>
ArrayFieldVector. ebeDivide(ArrayFieldVector<T> v)
Element-by-element division.FieldVector<T>
ArrayFieldVector. ebeDivide(FieldVector<T> v)
Element-by-element division.ArrayRealVector
ArrayRealVector. ebeDivide(RealVector v)
Element-by-element division.FieldVector<T>
FieldVector. ebeDivide(FieldVector<T> v)
Element-by-element division.OpenMapRealVector
OpenMapRealVector. ebeDivide(RealVector v)
Element-by-element division.abstract RealVector
RealVector. ebeDivide(RealVector v)
Element-by-element division.FieldVector<T>
SparseFieldVector. ebeDivide(FieldVector<T> v)
Element-by-element division.ArrayFieldVector<T>
ArrayFieldVector. ebeMultiply(ArrayFieldVector<T> v)
Element-by-element multiplication.FieldVector<T>
ArrayFieldVector. ebeMultiply(FieldVector<T> v)
Element-by-element multiplication.ArrayRealVector
ArrayRealVector. ebeMultiply(RealVector v)
Element-by-element multiplication.FieldVector<T>
FieldVector. ebeMultiply(FieldVector<T> v)
Element-by-element multiplication.OpenMapRealVector
OpenMapRealVector. ebeMultiply(RealVector v)
Element-by-element multiplication.abstract RealVector
RealVector. ebeMultiply(RealVector v)
Element-by-element multiplication.FieldVector<T>
SparseFieldVector. ebeMultiply(FieldVector<T> v)
Element-by-element multiplication.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.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.FieldMatrix<T>
AbstractFieldMatrix. multiply(FieldMatrix<T> m)
Postmultiply this matrix bym
.RealMatrix
AbstractRealMatrix. multiply(RealMatrix m)
Returns the result of postmultiplyingthis
bym
.Array2DRowFieldMatrix<T>
Array2DRowFieldMatrix. multiply(Array2DRowFieldMatrix<T> m)
Postmultiplying this matrix bym
.Array2DRowRealMatrix
Array2DRowRealMatrix. multiply(Array2DRowRealMatrix m)
Returns the result of postmultiplyingthis
bym
.BlockFieldMatrix<T>
BlockFieldMatrix. multiply(BlockFieldMatrix<T> m)
Returns the result of postmultiplyingthis
bym
.FieldMatrix<T>
BlockFieldMatrix. multiply(FieldMatrix<T> m)
Postmultiply this matrix bym
.BlockRealMatrix
BlockRealMatrix. multiply(BlockRealMatrix m)
Returns the result of postmultiplying this bym
.BlockRealMatrix
BlockRealMatrix. multiply(RealMatrix m)
Returns the result of postmultiplyingthis
bym
.DiagonalMatrix
DiagonalMatrix. multiply(DiagonalMatrix m)
Returns the result of postmultiplyingthis
bym
.RealMatrix
DiagonalMatrix. multiply(RealMatrix m)
Returns the result of postmultiplyingthis
bym
.FieldMatrix<T>
FieldMatrix. multiply(FieldMatrix<T> m)
Postmultiply this matrix bym
.OpenMapRealMatrix
OpenMapRealMatrix. multiply(OpenMapRealMatrix m)
Postmultiply this matrix bym
.RealMatrix
OpenMapRealMatrix. multiply(RealMatrix m)
Returns the result of postmultiplyingthis
bym
.RealMatrix
RealMatrix. multiply(RealMatrix m)
Returns the result of postmultiplyingthis
bym
.FieldVector<T>
AbstractFieldMatrix. operate(FieldVector<T> v)
Returns the result of multiplying this by the vectorv
.T[]
AbstractFieldMatrix. operate(T[] v)
Returns the result of multiplying this by the vectorv
.double[]
AbstractRealMatrix. operate(double[] v)
Returns the result of multiplying this by the vectorv
.RealVector
AbstractRealMatrix. operate(RealVector v)
Returns the result of multiplyingthis
by the vectorx
.T[]
Array2DRowFieldMatrix. operate(T[] v)
Returns the result of multiplying this by the vectorv
.double[]
Array2DRowRealMatrix. operate(double[] v)
Returns the result of multiplying this by the vectorv
.T[]
BlockFieldMatrix. operate(T[] v)
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
.FieldVector<T>
FieldMatrix. operate(FieldVector<T> v)
Returns the result of multiplying this by the vectorv
.T[]
FieldMatrix. operate(T[] v)
Returns the result of multiplying this by the vectorv
.abstract RealVector
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
.RealVector
RealMatrix. operate(RealVector v)
Returns the result of multiplying this by the vectorv
.RealVector
RealLinearOperator. operateTranspose(RealVector x)
Returns the result of multiplying the transpose ofthis
operator by the vectorx
(optional operation).FieldMatrix<T>
AbstractFieldMatrix. preMultiply(FieldMatrix<T> m)
Premultiply this matrix bym
.FieldVector<T>
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
.RealMatrix
AbstractRealMatrix. preMultiply(RealMatrix m)
Returns the result of premultiplyingthis
bym
.RealVector
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
.RealVector
DiagonalMatrix. preMultiply(RealVector v)
Returns the (row) vector result of premultiplying this by the vectorv
.FieldMatrix<T>
FieldMatrix. preMultiply(FieldMatrix<T> m)
Premultiply this matrix bym
.FieldVector<T>
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
RealMatrix. preMultiply(RealMatrix m)
Returns the result of premultiplyingthis
bym
.RealVector
RealMatrix. preMultiply(RealVector v)
Returns the (row) vector result of premultiplying this by the vectorv
.ArrayFieldVector<T>
ArrayFieldVector. projection(ArrayFieldVector<T> v)
Find the orthogonal projection of this vector onto another vector.FieldVector<T>
ArrayFieldVector. projection(FieldVector<T> v)
Find the orthogonal projection of this vector onto another vector.FieldVector<T>
FieldVector. projection(FieldVector<T> v)
Find the orthogonal projection of this vector onto another vector.RealVector
RealVector. projection(RealVector v)
Find the orthogonal projection of this vector onto another vector.FieldVector<T>
SparseFieldVector. projection(FieldVector<T> v)
Find the orthogonal projection of this vector onto another vector.void
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.RealVector
IterativeLinearSolver. solve(RealLinearOperator a, RealVector b)
Returns an estimate of the solution to the linear system A · x = b.RealVector
IterativeLinearSolver. solve(RealLinearOperator a, RealVector b, RealVector x0)
Returns an estimate of the solution to the linear system A · x = b.RealVector
PreconditionedIterativeLinearSolver. solve(RealLinearOperator a, RealLinearOperator m, RealVector b)
Returns an estimate of the solution to the linear system A · x = b.RealVector
PreconditionedIterativeLinearSolver. solve(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)
Returns an estimate of the solution to the linear system A · x = b.RealVector
PreconditionedIterativeLinearSolver. solve(RealLinearOperator a, RealVector b)
Returns an estimate of the solution to the linear system A · x = b.RealVector
PreconditionedIterativeLinearSolver. solve(RealLinearOperator a, RealVector b, RealVector x0)
Returns an estimate of the solution to the linear system A · x = b.RealVector
SymmLQ. solve(RealLinearOperator a, RealLinearOperator m, RealVector b)
Returns an estimate of the solution to the linear system A · x = b.RealVector
SymmLQ. solve(RealLinearOperator a, RealLinearOperator m, RealVector b, boolean goodb, double shift)
Returns an estimate of the solution to the linear system (A - shift · I) · x = b.RealVector
SymmLQ. solve(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x)
Returns an estimate of the solution to the linear system A · x = b.RealVector
SymmLQ. solve(RealLinearOperator a, RealVector b)
Returns an estimate of the solution to the linear system A · x = b.RealVector
SymmLQ. solve(RealLinearOperator a, RealVector b, boolean goodb, double shift)
Returns the solution to the system (A - shift · I) · x = b.RealVector
SymmLQ. solve(RealLinearOperator a, RealVector b, RealVector x)
Returns an estimate of the solution to the linear system A · x = b.RealVector
ConjugateGradient. solveInPlace(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)
Returns an estimate of the solution to the linear system A · x = b.abstract RealVector
IterativeLinearSolver. solveInPlace(RealLinearOperator a, RealVector b, RealVector x0)
Returns an estimate of the solution to the linear system A · x = b.abstract RealVector
PreconditionedIterativeLinearSolver. solveInPlace(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)
Returns an estimate of the solution to the linear system A · x = b.RealVector
PreconditionedIterativeLinearSolver. solveInPlace(RealLinearOperator a, RealVector b, RealVector x0)
Returns an estimate of the solution to the linear system A · x = b.RealVector
SymmLQ. solveInPlace(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x)
Returns an estimate of the solution to the linear system A · x = b.RealVector
SymmLQ. solveInPlace(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x, boolean goodb, double shift)
Returns an estimate of the solution to the linear system (A - shift · I) · x = b.RealVector
SymmLQ. solveInPlace(RealLinearOperator a, RealVector b, RealVector x)
Returns an estimate of the solution to the linear system A · x = b.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
.ArrayFieldVector<T>
ArrayFieldVector. subtract(ArrayFieldVector<T> v)
Computethis
minusv
.FieldVector<T>
ArrayFieldVector. subtract(FieldVector<T> v)
Computethis
minusv
.ArrayRealVector
ArrayRealVector. subtract(RealVector v)
Subtractv
from this vector.FieldVector<T>
FieldVector. subtract(FieldVector<T> v)
Computethis
minusv
.OpenMapRealVector
OpenMapRealVector. subtract(OpenMapRealVector v)
Optimized method to subtract OpenMapRealVectors.RealVector
OpenMapRealVector. subtract(RealVector v)
Subtractv
from this vector.RealVector
RealVector. subtract(RealVector v)
Subtractv
from this vector.FieldVector<T>
SparseFieldVector. subtract(FieldVector<T> v)
Computethis
minusv
.SparseFieldVector<T>
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.Constructors in org.apache.commons.math3.linear that throw DimensionMismatchException Constructor Description 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[][] 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.BlockFieldMatrix(int rows, int columns, T[][] blockData, boolean copyArray)
Create a new dense matrix copying entries from block layout data.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, double[][] blockData, boolean copyArray)
Create a new dense matrix copying entries from block layout data. -
Uses of DimensionMismatchException in org.apache.commons.math3.ml.distance
Methods in org.apache.commons.math3.ml.distance that throw DimensionMismatchException Modifier and Type Method Description double
CanberraDistance. compute(double[] a, double[] b)
Compute the distance between two n-dimensional vectors.double
ChebyshevDistance. compute(double[] a, double[] b)
Compute the distance between two n-dimensional vectors.double
DistanceMeasure. compute(double[] a, double[] b)
Compute the distance between two n-dimensional vectors.double
EarthMoversDistance. compute(double[] a, double[] b)
Compute the distance between two n-dimensional vectors.double
EuclideanDistance. compute(double[] a, double[] b)
Compute the distance between two n-dimensional vectors.double
ManhattanDistance. compute(double[] a, double[] b)
Compute the distance between two n-dimensional vectors. -
Uses of DimensionMismatchException in org.apache.commons.math3.ode
Methods in org.apache.commons.math3.ode that throw DimensionMismatchException Modifier and Type Method Description protected FieldODEStateAndDerivative<T>
AbstractFieldIntegrator. acceptStep(AbstractFieldStepInterpolator<T> interpolator, T tEnd)
Accept a step, triggering events and step handlers.protected double
AbstractIntegrator. acceptStep(AbstractStepInterpolator interpolator, double[] y, double[] yDot, double tEnd)
Accept a step, triggering events and step handlers.T[]
AbstractFieldIntegrator. computeDerivatives(T t, T[] y)
Compute the derivatives and check the number of evaluations.void
AbstractIntegrator. computeDerivatives(double t, double[] y, double[] yDot)
Compute the derivatives and check the number of evaluations.void
ExpandableStatefulODE. computeDerivatives(double t, double[] y, double[] yDot)
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[]
FieldSecondaryEquations. computeDerivatives(T t, T[] primary, T[] primaryDot, T[] secondary)
Compute the derivatives related to the secondary state parameters.void
FirstOrderDifferentialEquations. computeDerivatives(double t, double[] y, double[] yDot)
Get the current time derivative of the state vector.void
SecondaryEquations. computeDerivatives(double t, double[] primary, double[] primaryDot, double[] secondary, double[] secondaryDot)
Compute the derivatives related to the secondary state parameters.void
MainStateJacobianProvider. computeMainStateJacobian(double t, double[] y, double[] yDot, double[][] dFdY)
Compute the jacobian matrix of ODE with respect to main state.void
ParameterJacobianProvider. computeParameterJacobian(double t, double[] y, double[] yDot, String paramName, double[] dFdP)
Compute the Jacobian matrix of ODE with respect to one parameter.void
EquationsMapper. extractEquationData(double[] complete, double[] equationData)
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[]
ExpandableStatefulODE. getCompleteState()
Get the complete current state.void
EquationsMapper. insertEquationData(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.abstract void
AbstractIntegrator. integrate(ExpandableStatefulODE equations, double t)
Integrate a set of differential equations up to the given time.double
AbstractIntegrator. integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y)
Integrate the differential equations up to the given time.double
FirstOrderIntegrator. integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y)
Integrate the differential equations up to the given time.FieldODEStateAndDerivative<T>
FieldEquationsMapper. mapStateAndDerivative(T t, T[] y, T[] yDot)
Map flat arrays to a state and derivative.void
JacobianMatrices. registerVariationalEquations(ExpandableStatefulODE expandable)
Register the variational equations for the Jacobians matrices to the expandable set.protected void
AbstractFieldIntegrator. sanityChecks(FieldODEState<T> eqn, T t)
Check the integration span.protected void
AbstractIntegrator. sanityChecks(ExpandableStatefulODE equations, double t)
Check the integration span.void
ExpandableStatefulODE. setCompleteState(double[] completeState)
Set the complete current state.void
JacobianMatrices. setInitialMainStateJacobian(double[][] dYdY0)
Set the initial value of the Jacobian matrix with respect to state.void
JacobianMatrices. setInitialParameterJacobian(String pName, double[] dYdP)
Set the initial value of a column of the Jacobian matrix with respect to one parameter.void
ExpandableStatefulODE. setPrimaryState(double[] primaryState)
Set primary part of the current state.void
ExpandableStatefulODE. setSecondaryState(int index, double[] secondaryState)
Set secondary part of the current state.protected void
MultistepFieldIntegrator. start(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T t)
Start the integration.protected void
MultistepIntegrator. start(double t0, double[] y0, double t)
Start the integration.Constructors in org.apache.commons.math3.ode that throw DimensionMismatchException Constructor Description JacobianMatrices(FirstOrderDifferentialEquations fode, double[] hY, String... parameters)
Simple constructor for a secondary equations set computing Jacobian matrices. -
Uses of DimensionMismatchException in org.apache.commons.math3.ode.nonstiff
Methods in org.apache.commons.math3.ode.nonstiff that throw DimensionMismatchException Modifier and Type Method Description T
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, double t0, double[] y0, double[] yDot0, double[] y1, double[] yDot1)
Initialize the integration step.FieldODEStateAndDerivative<T>
AdamsBashforthFieldIntegrator. integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)
Integrate the differential equations up to the given time.void
AdamsBashforthIntegrator. integrate(ExpandableStatefulODE equations, double t)
Integrate a set of differential equations up to the given time.abstract FieldODEStateAndDerivative<T>
AdamsFieldIntegrator. integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)
Integrate the differential equations up to the given time.abstract void
AdamsIntegrator. integrate(ExpandableStatefulODE equations, double t)
Integrate a set of differential equations up to the given time.FieldODEStateAndDerivative<T>
AdamsMoultonFieldIntegrator. integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)
Integrate the differential equations up to the given time.void
AdamsMoultonIntegrator. integrate(ExpandableStatefulODE equations, double t)
Integrate a set of differential equations up to the given time.abstract void
AdaptiveStepsizeIntegrator. integrate(ExpandableStatefulODE equations, double t)
Integrate a set of differential equations up to the given time.FieldODEStateAndDerivative<T>
EmbeddedRungeKuttaFieldIntegrator. integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)
Integrate the differential equations up to the given time.void
EmbeddedRungeKuttaIntegrator. integrate(ExpandableStatefulODE equations, double t)
Integrate a set of differential equations up to the given time.void
GraggBulirschStoerIntegrator. integrate(ExpandableStatefulODE equations, double t)
Integrate a set of differential equations up to the given time.FieldODEStateAndDerivative<T>
RungeKuttaFieldIntegrator. integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)
Integrate the differential equations up to the given time.void
RungeKuttaIntegrator. integrate(ExpandableStatefulODE equations, double t)
Integrate a set of differential equations up to the given time.protected void
AdaptiveStepsizeFieldIntegrator. sanityChecks(FieldODEState<T> eqn, T t)
Check the integration span.protected void
AdaptiveStepsizeIntegrator. sanityChecks(ExpandableStatefulODE equations, double t)
Check the integration span. -
Uses of DimensionMismatchException in org.apache.commons.math3.optim.nonlinear.scalar.noderiv
Methods in org.apache.commons.math3.optim.nonlinear.scalar.noderiv that throw DimensionMismatchException Modifier and Type Method Description PointValuePair
CMAESOptimizer. optimize(OptimizationData... optData)
Stores data and performs the optimization. -
Uses of DimensionMismatchException in org.apache.commons.math3.optim.nonlinear.vector
Methods in org.apache.commons.math3.optim.nonlinear.vector that throw DimensionMismatchException Modifier and Type Method Description PointVectorValuePair
JacobianMultivariateVectorOptimizer. optimize(OptimizationData... optData)
Deprecated.Stores data and performs the optimization.PointVectorValuePair
MultivariateVectorOptimizer. optimize(OptimizationData... optData)
Deprecated.Stores data and performs the optimization. -
Uses of DimensionMismatchException in org.apache.commons.math3.optimization.direct
Methods in org.apache.commons.math3.optimization.direct that throw DimensionMismatchException Modifier and Type Method Description protected PointVectorValuePair
BaseAbstractMultivariateVectorOptimizer. optimize(int maxEval, FUNC f, OptimizationData... optData)
Deprecated.Optimize an objective function.protected PointVectorValuePair
BaseAbstractMultivariateVectorOptimizer. optimizeInternal(int maxEval, FUNC f, OptimizationData... optData)
Deprecated.Optimize an objective function. -
Uses of DimensionMismatchException in org.apache.commons.math3.random
Constructors in org.apache.commons.math3.random that throw DimensionMismatchException Constructor Description HaltonSequenceGenerator(int dimension, int[] bases, int[] weights)
Construct a new Halton sequence generator with the given base numbers and weights for each dimension. -
Uses of DimensionMismatchException in org.apache.commons.math3.stat
Methods in org.apache.commons.math3.stat that throw DimensionMismatchException Modifier and Type Method Description 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. 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. 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 DimensionMismatchException in org.apache.commons.math3.stat.correlation
Methods in org.apache.commons.math3.stat.correlation that throw DimensionMismatchException Modifier and Type Method Description void
StorelessCovariance. append(StorelessCovariance sc)
Appendssc
to this, effectively aggregating the computations insc
with this.double
KendallsCorrelation. correlation(double[] xArray, double[] yArray)
Computes the Kendall's Tau rank correlation coefficient between the two arrays.void
StorelessCovariance. increment(double[] data)
Increment the covariance matrix with one row of data. -
Uses of DimensionMismatchException in org.apache.commons.math3.stat.descriptive
Methods in org.apache.commons.math3.stat.descriptive that throw DimensionMismatchException Modifier and Type Method Description void
MultivariateSummaryStatistics. addValue(double[] value)
Add an n-tuple to the datavoid
SynchronizedMultivariateSummaryStatistics. addValue(double[] value)
Add an n-tuple to the datavoid
MultivariateSummaryStatistics. setGeoMeanImpl(StorelessUnivariateStatistic[] geoMeanImpl)
Sets the implementation for the geometric mean.void
SynchronizedMultivariateSummaryStatistics. setGeoMeanImpl(StorelessUnivariateStatistic[] geoMeanImpl)
Sets the implementation for the geometric mean.void
MultivariateSummaryStatistics. setMaxImpl(StorelessUnivariateStatistic[] maxImpl)
Sets the implementation for the maximum.void
SynchronizedMultivariateSummaryStatistics. setMaxImpl(StorelessUnivariateStatistic[] maxImpl)
Sets the implementation for the maximum.void
MultivariateSummaryStatistics. setMeanImpl(StorelessUnivariateStatistic[] meanImpl)
Sets the implementation for the mean.void
SynchronizedMultivariateSummaryStatistics. setMeanImpl(StorelessUnivariateStatistic[] meanImpl)
Sets the implementation for the mean.void
MultivariateSummaryStatistics. setMinImpl(StorelessUnivariateStatistic[] minImpl)
Sets the implementation for the minimum.void
SynchronizedMultivariateSummaryStatistics. setMinImpl(StorelessUnivariateStatistic[] minImpl)
Sets the implementation for the minimum.void
MultivariateSummaryStatistics. setSumImpl(StorelessUnivariateStatistic[] sumImpl)
Sets the implementation for the Sum.void
SynchronizedMultivariateSummaryStatistics. setSumImpl(StorelessUnivariateStatistic[] sumImpl)
Sets the implementation for the Sum.void
MultivariateSummaryStatistics. setSumLogImpl(StorelessUnivariateStatistic[] sumLogImpl)
Sets the implementation for the sum of logs.void
SynchronizedMultivariateSummaryStatistics. setSumLogImpl(StorelessUnivariateStatistic[] sumLogImpl)
Sets the implementation for the sum of logs.void
MultivariateSummaryStatistics. setSumsqImpl(StorelessUnivariateStatistic[] sumsqImpl)
Sets the implementation for the sum of squares.void
SynchronizedMultivariateSummaryStatistics. setSumsqImpl(StorelessUnivariateStatistic[] sumsqImpl)
Sets the implementation for the sum of squares. -
Uses of DimensionMismatchException in org.apache.commons.math3.stat.descriptive.moment
Methods in org.apache.commons.math3.stat.descriptive.moment that throw DimensionMismatchException Modifier and Type Method Description void
VectorialCovariance. increment(double[] v)
Add a new vector to the sample.void
VectorialMean. increment(double[] v)
Add a new vector to the sample. -
Uses of DimensionMismatchException in org.apache.commons.math3.stat.inference
Methods in org.apache.commons.math3.stat.inference that throw DimensionMismatchException Modifier and Type Method Description double
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<SummaryStatistics> categoryData, boolean allowOneElementData)
Computes the ANOVA P-value for a collection ofSummaryStatistics
.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
TestUtils. chiSquare(double[] expected, long[] observed)
static double
TestUtils. chiSquare(long[][] counts)
double
ChiSquareTest. chiSquareDataSetsComparison(long[] observed1, long[] observed2)
Computes a Chi-Square two sample test statistic comparing bin frequency counts inobserved1
andobserved2
.static double
TestUtils. chiSquareDataSetsComparison(long[] observed1, long[] observed2)
double
ChiSquareTest. chiSquareTest(double[] expected, long[] observed)
Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing 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
TestUtils. chiSquareTest(double[] expected, long[] observed)
static boolean
TestUtils. chiSquareTest(double[] expected, long[] observed, double alpha)
static double
TestUtils. chiSquareTest(long[][] counts)
static boolean
TestUtils. chiSquareTest(long[][] counts, double alpha)
double
ChiSquareTest. chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)
Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts 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
TestUtils. chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)
static boolean
TestUtils. chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
double
GTest. g(double[] expected, long[] observed)
static double
TestUtils. 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
TestUtils. gDataSetsComparison(long[] observed1, long[] observed2)
double
GTest. gTest(double[] expected, long[] observed)
Returns the observed significance level, or p-value, associated with a G-Test for goodness of fit comparing 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
TestUtils. gTest(double[] expected, long[] observed)
static boolean
TestUtils. gTest(double[] expected, long[] observed, double alpha)
double
GTest. gTestDataSetsComparison(long[] observed1, long[] observed2)
Returns the observed significance level, or p-value, associated with a G-Value (Log-Likelihood Ratio) for two sample test comparing bin frequency counts 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
TestUtils. gTestDataSetsComparison(long[] observed1, long[] observed2)
static boolean
TestUtils. gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
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
TestUtils. gTestIntrinsic(double[] expected, long[] observed)
static double
TestUtils. oneWayAnovaFValue(Collection<double[]> categoryData)
static double
TestUtils. oneWayAnovaPValue(Collection<double[]> categoryData)
static boolean
TestUtils. oneWayAnovaTest(Collection<double[]> categoryData, double alpha)
static double
TestUtils. pairedT(double[] sample1, double[] sample2)
double
TTest. pairedT(double[] sample1, double[] sample2)
Computes a paired, 2-sample t-statistic based on the data in the input arrays.static double
TestUtils. pairedTTest(double[] sample1, double[] sample2)
static boolean
TestUtils. pairedTTest(double[] sample1, double[] sample2, double alpha)
double
TTest. pairedTTest(double[] sample1, double[] sample2)
Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays.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
TestUtils. rootLogLikelihoodRatio(long k11, long k12, long k21, long k22)
double
WilcoxonSignedRankTest. wilcoxonSignedRank(double[] x, double[] y)
Computes the Wilcoxon signed ranked statistic comparing mean 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 DimensionMismatchException in org.apache.commons.math3.transform
Methods in org.apache.commons.math3.transform that throw DimensionMismatchException Modifier and Type Method Description static Complex[]
TransformUtils. createComplexArray(double[][] dataRI)
Builds a new array ofComplex
from the specified two dimensional array of real and imaginary parts. -
Uses of DimensionMismatchException in org.apache.commons.math3.util
Methods in org.apache.commons.math3.util that throw DimensionMismatchException Modifier and Type Method Description static void
MathArrays. checkRectangular(long[][] in)
Throws DimensionMismatchException if the input array is not rectangular.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.int
MultidimensionalCounter. getCount(int... c)
Convert to unidimensional counter.Decimal64
Decimal64. linearCombination(double[] a, Decimal64[] b)
Compute a linear combination.Decimal64
Decimal64. linearCombination(Decimal64[] a, Decimal64[] b)
Compute a linear combination.static double
MathArrays. linearCombination(double[] a, double[] b)
Compute a linear combination accurately.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.
-