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Packages that use NullArgumentException | |
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org.apache.commons.math3 | Common classes used throughout the commons-math library. |
org.apache.commons.math3.analysis.function |
The function package contains function objects that wrap the
methods contained in Math , as well as common
mathematical functions such as the gaussian and sinc functions. |
org.apache.commons.math3.analysis.integration | Numerical integration (quadrature) algorithms for univariate real functions. |
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.analysis.solvers | Root finding algorithms, for 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 Java |
org.apache.commons.math3.filter | Implementations of common discrete-time linear filters. |
org.apache.commons.math3.fraction | Fraction number type and fraction number formatting. |
org.apache.commons.math3.genetics | This package provides Genetic Algorithms components and implementations. |
org.apache.commons.math3.linear | Linear algebra support. |
org.apache.commons.math3.optim.nonlinear.scalar | Algorithms for optimizing a scalar function. |
org.apache.commons.math3.optim.nonlinear.vector | Algorithms for optimizing a vector function. |
org.apache.commons.math3.random | Random number and random data generators. |
org.apache.commons.math3.stat.clustering | Clustering algorithms |
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.descriptive.rank | Summary statistics based on ranks. |
org.apache.commons.math3.stat.descriptive.summary | Other summary statistics. |
org.apache.commons.math3.stat.inference | Classes providing hypothesis testing and confidence interval construction. |
org.apache.commons.math3.util | Convenience routines and common data structures used throughout the commons-math library. |
Uses of NullArgumentException in org.apache.commons.math3 |
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Methods in org.apache.commons.math3 that throw NullArgumentException | |
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T |
FieldElement.add(T a)
Compute this + a. |
T |
FieldElement.divide(T a)
Compute this ÷ a. |
T |
FieldElement.multiply(T a)
Compute this × a. |
T |
FieldElement.subtract(T a)
Compute this - a. |
Uses of NullArgumentException in org.apache.commons.math3.analysis.function |
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Methods in org.apache.commons.math3.analysis.function that throw NullArgumentException | |
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double[] |
HarmonicOscillator.Parametric.gradient(double x,
double... param)
Computes the value of the gradient at x . |
double[] |
Logit.Parametric.gradient(double x,
double... param)
Computes the value of the gradient at x . |
double[] |
Sigmoid.Parametric.gradient(double x,
double... param)
Computes the value of the gradient at x . |
double[] |
Logistic.Parametric.gradient(double x,
double... param)
Computes the value of the gradient at x . |
double[] |
Gaussian.Parametric.gradient(double x,
double... param)
Computes the value of the gradient at x . |
double |
HarmonicOscillator.Parametric.value(double x,
double... param)
Computes the value of the harmonic oscillator at x . |
double |
Logit.Parametric.value(double x,
double... param)
Computes the value of the logit at x . |
double |
Sigmoid.Parametric.value(double x,
double... param)
Computes the value of the sigmoid at x . |
double |
Logistic.Parametric.value(double x,
double... param)
Computes the value of the sigmoid at x . |
double |
Gaussian.Parametric.value(double x,
double... param)
Computes the value of the Gaussian at x . |
Constructors in org.apache.commons.math3.analysis.function that throw NullArgumentException | |
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StepFunction(double[] x,
double[] y)
Builds a step function from a list of arguments and the corresponding values. |
Uses of NullArgumentException in org.apache.commons.math3.analysis.integration |
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Methods in org.apache.commons.math3.analysis.integration that throw NullArgumentException | |
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double |
BaseAbstractUnivariateIntegrator.integrate(int maxEval,
UnivariateFunction f,
double lower,
double upper)
Integrate the function in the given interval. |
double |
UnivariateIntegrator.integrate(int maxEval,
UnivariateFunction f,
double min,
double max)
Integrate the function in the given interval. |
protected void |
BaseAbstractUnivariateIntegrator.setup(int maxEval,
UnivariateFunction f,
double lower,
double upper)
Prepare for computation. |
Uses of NullArgumentException in org.apache.commons.math3.analysis.interpolation |
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Methods in org.apache.commons.math3.analysis.interpolation that throw NullArgumentException | |
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MultivariateFunction |
MicrosphereInterpolator.interpolate(double[][] xval,
double[] yval)
Computes an interpolating function for the data set. |
Constructors in org.apache.commons.math3.analysis.interpolation that throw NullArgumentException | |
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MicrosphereInterpolatingFunction(double[][] xval,
double[] yval,
int brightnessExponent,
int microsphereElements,
UnitSphereRandomVectorGenerator rand)
|
Uses of NullArgumentException in org.apache.commons.math3.analysis.polynomials |
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Methods in org.apache.commons.math3.analysis.polynomials that throw NullArgumentException | |
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protected static double[] |
PolynomialFunction.differentiate(double[] coefficients)
Returns the coefficients of the derivative of the polynomial with the given coefficients. |
protected static double |
PolynomialFunction.evaluate(double[] coefficients,
double argument)
Uses Horner's Method to evaluate the polynomial with the given coefficients at the argument. |
DerivativeStructure |
PolynomialFunction.value(DerivativeStructure t)
Simple mathematical function. |
Constructors in org.apache.commons.math3.analysis.polynomials that throw NullArgumentException | |
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PolynomialFunction(double[] c)
Construct a polynomial with the given coefficients. |
Uses of NullArgumentException in org.apache.commons.math3.analysis.solvers |
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Methods in org.apache.commons.math3.analysis.solvers that throw NullArgumentException | |
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static double[] |
UnivariateSolverUtils.bracket(UnivariateFunction function,
double initial,
double lowerBound,
double upperBound)
This method attempts to find two values a and b satisfying lowerBound <= a < initial < b <= upperBound
f(a) * f(b) < 0
If f is continuous on [a,b], this means that a
and b bracket a root of f. |
static double[] |
UnivariateSolverUtils.bracket(UnivariateFunction function,
double initial,
double lowerBound,
double upperBound,
int maximumIterations)
This method attempts to find two values a and b satisfying lowerBound <= a < initial < b <= upperBound
f(a) * f(b) <= 0
If f is continuous on [a,b], this means that a
and b bracket a root of f. |
static boolean |
UnivariateSolverUtils.isBracketing(UnivariateFunction function,
double lower,
double upper)
Check whether the interval bounds bracket a root. |
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.solveComplex(double[] coefficients,
double initial)
Find a complex root for the polynomial with the given coefficients, starting from the given initial value. |
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. |
Uses of NullArgumentException in org.apache.commons.math3.complex |
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Methods in org.apache.commons.math3.complex that throw NullArgumentException | |
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Complex |
Complex.add(Complex addend)
Returns a Complex whose value is
(this + addend) . |
Complex |
Complex.divide(Complex divisor)
Returns a Complex whose value is
(this / divisor) . |
static ComplexFormat |
ComplexFormat.getInstance(String imaginaryCharacter,
Locale locale)
Returns the default complex format for the given locale. |
Complex |
Complex.multiply(Complex factor)
Returns a Complex whose value is this * factor . |
Complex |
Complex.pow(Complex x)
Returns of value of this complex number raised to the power of x . |
Complex |
Complex.subtract(Complex subtrahend)
Returns a Complex whose value is
(this - subtrahend) . |
Constructors in org.apache.commons.math3.complex that throw NullArgumentException | |
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ComplexFormat(NumberFormat format)
Create an instance with a custom number format for both real and imaginary parts. |
|
ComplexFormat(NumberFormat realFormat,
NumberFormat imaginaryFormat)
Create an instance with a custom number format for the real part and a custom number format for the imaginary part. |
|
ComplexFormat(String imaginaryCharacter)
Create an instance with a custom imaginary character, and the default number format for both real and imaginary parts. |
|
ComplexFormat(String imaginaryCharacter,
NumberFormat format)
Create an instance with a custom imaginary character, and a custom number format for both real and imaginary parts. |
|
ComplexFormat(String imaginaryCharacter,
NumberFormat realFormat,
NumberFormat imaginaryFormat)
Create an instance with a custom imaginary character, a custom number format for the real part, and a custom number format for the imaginary part. |
Uses of NullArgumentException in org.apache.commons.math3.dfp |
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Methods in org.apache.commons.math3.dfp that throw NullArgumentException | |
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Dfp |
BracketingNthOrderBrentSolverDFP.solve(int maxEval,
UnivariateDfpFunction f,
Dfp min,
Dfp max,
AllowedSolution allowedSolution)
Solve for a zero in the given interval. |
Dfp |
BracketingNthOrderBrentSolverDFP.solve(int maxEval,
UnivariateDfpFunction f,
Dfp min,
Dfp max,
Dfp startValue,
AllowedSolution allowedSolution)
Solve for a zero in the given interval, start at startValue . |
Uses of NullArgumentException in org.apache.commons.math3.filter |
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Methods in org.apache.commons.math3.filter that throw NullArgumentException | |
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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. |
Constructors in org.apache.commons.math3.filter that throw NullArgumentException | |
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DefaultMeasurementModel(double[][] measMatrix,
double[][] measNoise)
Create a new MeasurementModel , taking double arrays as input parameters for the
respective measurement matrix and noise. |
|
DefaultProcessModel(double[][] stateTransition,
double[][] control,
double[][] processNoise)
Create a new ProcessModel , taking double arrays as input parameters. |
|
DefaultProcessModel(double[][] stateTransition,
double[][] control,
double[][] processNoise,
double[] initialStateEstimate,
double[][] initialErrorCovariance)
Create a new ProcessModel , 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 NullArgumentException in org.apache.commons.math3.fraction |
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Methods in org.apache.commons.math3.fraction that throw NullArgumentException | |
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BigFraction |
BigFraction.add(BigInteger bg)
Adds the value of this fraction to the passed BigInteger ,
returning the result in reduced form. |
Uses of NullArgumentException in org.apache.commons.math3.genetics |
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Methods in org.apache.commons.math3.genetics that throw NullArgumentException | |
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void |
ListPopulation.setChromosomes(List<Chromosome> chromosomes)
Deprecated. use ListPopulation.addChromosomes(Collection) instead |
Constructors in org.apache.commons.math3.genetics that throw NullArgumentException | |
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ElitisticListPopulation(List<Chromosome> chromosomes,
int populationLimit,
double elitismRate)
Creates a new ElitisticListPopulation instance. |
|
ListPopulation(List<Chromosome> chromosomes,
int populationLimit)
Creates a new ListPopulation instance. |
Uses of NullArgumentException in org.apache.commons.math3.linear |
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Methods in org.apache.commons.math3.linear that throw NullArgumentException | ||
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protected static void |
PreconditionedIterativeLinearSolver.checkParameters(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x0)
Performs all dimension checks on the parameters of solve
and
solveInPlace ,
and throws an exception if one of the checks fails. |
|
protected static void |
IterativeLinearSolver.checkParameters(RealLinearOperator a,
RealVector b,
RealVector x0)
Performs all dimension checks on the parameters of solve and
solveInPlace ,
and throws an exception if one of the checks fails. |
|
static void |
MatrixUtils.checkSubMatrixIndex(AnyMatrix m,
int[] selectedRows,
int[] selectedColumns)
Check if submatrix ranges indices are valid. |
|
protected void |
AbstractFieldMatrix.checkSubMatrixIndex(int[] selectedRows,
int[] selectedColumns)
Check if submatrix ranges indices are valid. |
|
void |
AbstractRealMatrix.copySubMatrix(int[] selectedRows,
int[] selectedColumns,
double[][] destination)
Copy a submatrix. |
|
void |
RealMatrix.copySubMatrix(int[] selectedRows,
int[] selectedColumns,
double[][] destination)
Copy a submatrix. |
|
void |
FieldMatrix.copySubMatrix(int[] selectedRows,
int[] selectedColumns,
T[][] destination)
Copy a submatrix. |
|
void |
AbstractFieldMatrix.copySubMatrix(int[] selectedRows,
int[] selectedColumns,
T[][] destination)
Copy a submatrix. |
|
static
|
MatrixUtils.createColumnFieldMatrix(T[] columnData)
Creates a column FieldMatrix using the data from the input
array. |
|
static RealMatrix |
MatrixUtils.createColumnRealMatrix(double[] columnData)
Creates a column RealMatrix using the data from the input
array. |
|
static
|
MatrixUtils.createFieldMatrix(T[][] data)
Returns a FieldMatrix whose entries are the the values in the
the input array. |
|
static
|
MatrixUtils.createFieldVector(T[] data)
Creates a FieldVector using the data from the input array. |
|
static RealMatrix |
MatrixUtils.createRealMatrix(double[][] data)
Returns a RealMatrix whose entries are the the values in the
the input array. |
|
static RealVector |
MatrixUtils.createRealVector(double[] data)
Creates a RealVector using the data from the input array. |
|
static
|
MatrixUtils.createRowFieldMatrix(T[] rowData)
Create a row FieldMatrix using the data from the input
array. |
|
static RealMatrix |
MatrixUtils.createRowRealMatrix(double[] rowData)
Create a row RealMatrix using the data from the input
array. |
|
protected static
|
AbstractFieldMatrix.extractField(T[][] d)
Get the elements type from an array. |
|
RealMatrix |
AbstractRealMatrix.getSubMatrix(int[] selectedRows,
int[] selectedColumns)
Gets a submatrix. |
|
RealMatrix |
RealMatrix.getSubMatrix(int[] selectedRows,
int[] selectedColumns)
Gets a submatrix. |
|
FieldMatrix<T> |
FieldMatrix.getSubMatrix(int[] selectedRows,
int[] selectedColumns)
Get a submatrix. |
|
FieldMatrix<T> |
AbstractFieldMatrix.getSubMatrix(int[] selectedRows,
int[] selectedColumns)
Get a submatrix. |
|
FieldVector<T> |
ArrayFieldVector.mapAdd(T d)
Map an addition operation to each entry. |
|
FieldVector<T> |
SparseFieldVector.mapAdd(T d)
Deprecated. Map an addition operation to each entry. |
|
FieldVector<T> |
FieldVector.mapAdd(T d)
Map an addition operation to each entry. |
|
FieldVector<T> |
ArrayFieldVector.mapAddToSelf(T d)
Map an addition operation to each entry. |
|
FieldVector<T> |
SparseFieldVector.mapAddToSelf(T d)
Deprecated. Map an addition operation to each entry. |
|
FieldVector<T> |
FieldVector.mapAddToSelf(T d)
Map an addition operation to each entry. |
|
FieldVector<T> |
ArrayFieldVector.mapDivide(T d)
Map a division operation to each entry. |
|
FieldVector<T> |
SparseFieldVector.mapDivide(T d)
Deprecated. Map a division operation to each entry. |
|
FieldVector<T> |
FieldVector.mapDivide(T d)
Map a division operation to each entry. |
|
FieldVector<T> |
ArrayFieldVector.mapDivideToSelf(T d)
Map a division operation to each entry. |
|
FieldVector<T> |
SparseFieldVector.mapDivideToSelf(T d)
Deprecated. Map a division operation to each entry. |
|
FieldVector<T> |
FieldVector.mapDivideToSelf(T d)
Map a division operation to each entry. |
|
FieldVector<T> |
ArrayFieldVector.mapMultiply(T d)
Map a multiplication operation to each entry. |
|
FieldVector<T> |
SparseFieldVector.mapMultiply(T d)
Deprecated. Map a multiplication operation to each entry. |
|
FieldVector<T> |
FieldVector.mapMultiply(T d)
Map a multiplication operation to each entry. |
|
FieldVector<T> |
ArrayFieldVector.mapMultiplyToSelf(T d)
Map a multiplication operation to each entry. |
|
FieldVector<T> |
SparseFieldVector.mapMultiplyToSelf(T d)
Deprecated. Map a multiplication operation to each entry. |
|
FieldVector<T> |
FieldVector.mapMultiplyToSelf(T d)
Map a multiplication operation to each entry. |
|
FieldVector<T> |
ArrayFieldVector.mapSubtract(T d)
Map a subtraction operation to each entry. |
|
FieldVector<T> |
SparseFieldVector.mapSubtract(T d)
Deprecated. Map a subtraction operation to each entry. |
|
FieldVector<T> |
FieldVector.mapSubtract(T d)
Map a subtraction operation to each entry. |
|
FieldVector<T> |
ArrayFieldVector.mapSubtractToSelf(T d)
Map a subtraction operation to each entry. |
|
FieldVector<T> |
SparseFieldVector.mapSubtractToSelf(T d)
Deprecated. Map a subtraction operation to each entry. |
|
FieldVector<T> |
FieldVector.mapSubtractToSelf(T d)
Map a subtraction operation to each entry. |
|
void |
Array2DRowRealMatrix.setSubMatrix(double[][] subMatrix,
int row,
int column)
Replace the submatrix starting at row, column using data in the
input subMatrix array. |
|
void |
AbstractRealMatrix.setSubMatrix(double[][] subMatrix,
int row,
int column)
Replace the submatrix starting at row, column using data in the
input subMatrix array. |
|
void |
RealMatrix.setSubMatrix(double[][] subMatrix,
int row,
int column)
Replace the submatrix starting at row, column using data in the
input subMatrix array. |
|
void |
BlockRealMatrix.setSubMatrix(double[][] subMatrix,
int row,
int column)
Replace the submatrix starting at row, column using data in the
input subMatrix array. |
|
void |
FieldMatrix.setSubMatrix(T[][] subMatrix,
int row,
int column)
Replace the submatrix starting at (row, column) using data in the
input subMatrix array. |
|
void |
Array2DRowFieldMatrix.setSubMatrix(T[][] subMatrix,
int row,
int column)
Replace the submatrix starting at (row, column) using data in the
input subMatrix array. |
|
void |
AbstractFieldMatrix.setSubMatrix(T[][] subMatrix,
int row,
int column)
Replace the submatrix starting at (row, column) using data in the
input subMatrix array. |
|
void |
BlockFieldMatrix.setSubMatrix(T[][] subMatrix,
int row,
int column)
Replace the submatrix starting at (row, column) using data in the
input subMatrix array. |
|
RealVector |
PreconditionedIterativeLinearSolver.solve(RealLinearOperator a,
RealLinearOperator m,
RealVector b)
Returns an estimate of the solution to the linear system A · x = b. |
|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealLinearOperator m,
RealVector b)
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 |
PreconditionedIterativeLinearSolver.solve(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x0)
Returns an estimate of the solution to the linear system A · x = b. |
|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x)
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 |
IterativeLinearSolver.solve(RealLinearOperator a,
RealVector b)
Returns an estimate of the solution to the linear system A · x = b. |
|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealVector b)
Returns an estimate of the solution to the linear system A · x = b. |
|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealVector b,
boolean goodb,
double shift)
Returns the solution to the system (A - shift · I) · x = b. |
|
RealVector |
PreconditionedIterativeLinearSolver.solve(RealLinearOperator a,
RealVector b,
RealVector x0)
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 |
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 |
PreconditionedIterativeLinearSolver.solveInPlace(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x0)
Returns an estimate of the solution to the linear system A · x = b. |
|
RealVector |
SymmLQ.solveInPlace(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x)
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 |
PreconditionedIterativeLinearSolver.solveInPlace(RealLinearOperator a,
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. |
|
RealVector |
SymmLQ.solveInPlace(RealLinearOperator a,
RealVector b,
RealVector x)
Returns an estimate of the solution to the linear system A · x = b. |
Constructors in org.apache.commons.math3.linear that throw NullArgumentException | |
---|---|
Array2DRowFieldMatrix(Field<T> field,
T[][] d)
Create a new FieldMatrix<T> using the input array as the underlying
data array. |
|
Array2DRowFieldMatrix(Field<T> field,
T[][] d,
boolean copyArray)
Create a new FieldMatrix<T> using the input array as the underlying
data array. |
|
Array2DRowFieldMatrix(T[][] d)
Create a new FieldMatrix<T> using the input array as the underlying
data array. |
|
Array2DRowFieldMatrix(T[][] d,
boolean copyArray)
Create a new FieldMatrix<T> using the input array as the underlying
data array. |
|
Array2DRowRealMatrix(double[][] d)
Create a new RealMatrix using the input array as the underlying
data array. |
|
Array2DRowRealMatrix(double[][] d,
boolean copyArray)
Create a new RealMatrix using the input array as the underlying data array. |
|
ArrayFieldVector(ArrayFieldVector<T> v)
Construct a vector from another vector, using a deep copy. |
|
ArrayFieldVector(ArrayFieldVector<T> v1,
ArrayFieldVector<T> v2)
Construct a vector by appending one vector to another vector. |
|
ArrayFieldVector(ArrayFieldVector<T> v,
boolean deep)
Construct a vector from another vector. |
|
ArrayFieldVector(ArrayFieldVector<T> v1,
T[] v2)
Construct a vector by appending one vector to another vector. |
|
ArrayFieldVector(Field<T> field,
T[] d)
Construct a vector from an array, copying the input array. |
|
ArrayFieldVector(Field<T> field,
T[] d,
boolean copyArray)
Create a new ArrayFieldVector using the input array as the underlying data array. |
|
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(FieldVector<T> v)
Construct a vector from another vector, using a deep copy. |
|
ArrayFieldVector(T[] d)
Construct a vector from an array, copying the input array. |
|
ArrayFieldVector(T[] v1,
ArrayFieldVector<T> v2)
Construct a vector by appending one vector to another vector. |
|
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(ArrayRealVector v)
Construct a vector from another vector, using a deep copy. |
|
ArrayRealVector(double[] d,
boolean copyArray)
Create a new ArrayRealVector using the input array as the underlying data array. |
|
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. |
|
ArrayRealVector(RealVector v)
Construct a vector from another vector, using a deep copy. |
|
ConjugateGradient(IterationManager manager,
double delta,
boolean check)
Creates a new instance of this class, with default stopping criterion and custom iteration manager. |
|
IterativeLinearSolver(IterationManager manager)
Creates a new instance of this class, with custom iteration manager. |
|
PreconditionedIterativeLinearSolver(IterationManager manager)
Creates a new instance of this class, with custom iteration manager. |
Uses of NullArgumentException in org.apache.commons.math3.optim.nonlinear.scalar |
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Constructors in org.apache.commons.math3.optim.nonlinear.scalar that throw NullArgumentException | |
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MultiStartMultivariateOptimizer(MultivariateOptimizer optimizer,
int starts,
RandomVectorGenerator generator)
Create a multi-start optimizer from a single-start optimizer. |
Uses of NullArgumentException in org.apache.commons.math3.optim.nonlinear.vector |
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Constructors in org.apache.commons.math3.optim.nonlinear.vector that throw NullArgumentException | |
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MultiStartMultivariateVectorOptimizer(MultivariateVectorOptimizer optimizer,
int starts,
RandomVectorGenerator generator)
Create a multi-start optimizer from a single-start optimizer. |
Uses of NullArgumentException in org.apache.commons.math3.random |
---|
Methods in org.apache.commons.math3.random that throw NullArgumentException | |
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void |
ValueServer.computeDistribution()
Computes the empirical distribution using values from the file in valuesFileURL , using the default number of bins. |
void |
ValueServer.computeDistribution(int binCount)
Computes the empirical distribution using values from the file in valuesFileURL and binCount bins. |
void |
EmpiricalDistribution.load(double[] in)
Computes the empirical distribution from the provided array of numbers. |
void |
EmpiricalDistribution.load(File file)
Computes the empirical distribution from the input file. |
void |
EmpiricalDistribution.load(URL url)
Computes the empirical distribution using data read from a URL. |
Constructors in org.apache.commons.math3.random that throw NullArgumentException | |
---|---|
StableRandomGenerator(RandomGenerator generator,
double alpha,
double beta)
Create a new generator. |
Uses of NullArgumentException in org.apache.commons.math3.stat.clustering |
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Methods in org.apache.commons.math3.stat.clustering that throw NullArgumentException | |
---|---|
List<Cluster<T>> |
DBSCANClusterer.cluster(Collection<T> points)
Performs DBSCAN cluster analysis. |
Uses of NullArgumentException in org.apache.commons.math3.stat.descriptive |
---|
Methods in org.apache.commons.math3.stat.descriptive that throw NullArgumentException | |
---|---|
static void |
DescriptiveStatistics.copy(DescriptiveStatistics source,
DescriptiveStatistics dest)
Copies source to dest. |
static void |
SummaryStatistics.copy(SummaryStatistics source,
SummaryStatistics dest)
Copies source to dest. |
static void |
SynchronizedDescriptiveStatistics.copy(SynchronizedDescriptiveStatistics source,
SynchronizedDescriptiveStatistics dest)
Copies source to dest. |
static void |
SynchronizedSummaryStatistics.copy(SynchronizedSummaryStatistics source,
SynchronizedSummaryStatistics dest)
Copies source to dest. |
Constructors in org.apache.commons.math3.stat.descriptive that throw NullArgumentException | |
---|---|
AggregateSummaryStatistics(SummaryStatistics prototypeStatistics)
Initializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics. |
|
DescriptiveStatistics(DescriptiveStatistics original)
Copy constructor. |
|
SummaryStatistics(SummaryStatistics original)
A copy constructor. |
|
SynchronizedDescriptiveStatistics(SynchronizedDescriptiveStatistics original)
A copy constructor. |
|
SynchronizedSummaryStatistics(SynchronizedSummaryStatistics original)
A copy constructor. |
Uses of NullArgumentException in org.apache.commons.math3.stat.descriptive.moment |
---|
Methods in org.apache.commons.math3.stat.descriptive.moment that throw NullArgumentException | |
---|---|
static void |
GeometricMean.copy(GeometricMean source,
GeometricMean dest)
Copies source to dest. |
static void |
Kurtosis.copy(Kurtosis source,
Kurtosis dest)
Copies source to dest. |
static void |
Mean.copy(Mean source,
Mean dest)
Copies source to dest. |
static void |
SecondMoment.copy(SecondMoment source,
SecondMoment dest)
Copies source to dest. |
static void |
SemiVariance.copy(SemiVariance source,
SemiVariance dest)
Copies source to dest. |
static void |
Skewness.copy(Skewness source,
Skewness dest)
Copies source to dest. |
static void |
StandardDeviation.copy(StandardDeviation source,
StandardDeviation dest)
Copies source to dest. |
static void |
Variance.copy(Variance source,
Variance dest)
Copies source to dest. |
Constructors in org.apache.commons.math3.stat.descriptive.moment that throw NullArgumentException | |
---|---|
GeometricMean(GeometricMean original)
Copy constructor, creates a new GeometricMean identical
to the original |
|
Kurtosis(Kurtosis original)
Copy constructor, creates a new Kurtosis identical
to the original |
|
Mean(Mean original)
Copy constructor, creates a new Mean identical
to the original |
|
SecondMoment(SecondMoment original)
Copy constructor, creates a new SecondMoment identical
to the original |
|
SemiVariance(SemiVariance original)
Copy constructor, creates a new SemiVariance identical
to the original |
|
Skewness(Skewness original)
Copy constructor, creates a new Skewness identical
to the original |
|
StandardDeviation(StandardDeviation original)
Copy constructor, creates a new StandardDeviation identical
to the original |
|
Variance(Variance original)
Copy constructor, creates a new Variance identical
to the original |
Uses of NullArgumentException in org.apache.commons.math3.stat.descriptive.rank |
---|
Methods in org.apache.commons.math3.stat.descriptive.rank that throw NullArgumentException | |
---|---|
static void |
Max.copy(Max source,
Max dest)
Copies source to dest. |
static void |
Min.copy(Min source,
Min dest)
Copies source to dest. |
static void |
Percentile.copy(Percentile source,
Percentile dest)
Copies source to dest. |
Constructors in org.apache.commons.math3.stat.descriptive.rank that throw NullArgumentException | |
---|---|
Max(Max original)
Copy constructor, creates a new Max identical
to the original |
|
Median(Median original)
Copy constructor, creates a new Median identical
to the original |
|
Min(Min original)
Copy constructor, creates a new Min identical
to the original |
|
Percentile(Percentile original)
Copy constructor, creates a new Percentile identical
to the original |
Uses of NullArgumentException in org.apache.commons.math3.stat.descriptive.summary |
---|
Methods in org.apache.commons.math3.stat.descriptive.summary that throw NullArgumentException | |
---|---|
static void |
Product.copy(Product source,
Product dest)
Copies source to dest. |
static void |
SumOfLogs.copy(SumOfLogs source,
SumOfLogs dest)
Copies source to dest. |
static void |
SumOfSquares.copy(SumOfSquares source,
SumOfSquares dest)
Copies source to dest. |
static void |
Sum.copy(Sum source,
Sum dest)
Copies source to dest. |
Constructors in org.apache.commons.math3.stat.descriptive.summary that throw NullArgumentException | |
---|---|
Product(Product original)
Copy constructor, creates a new Product identical
to the original |
|
Sum(Sum original)
Copy constructor, creates a new Sum identical
to the original |
|
SumOfLogs(SumOfLogs original)
Copy constructor, creates a new SumOfLogs identical
to the original |
|
SumOfSquares(SumOfSquares original)
Copy constructor, creates a new SumOfSquares identical
to the original |
Uses of NullArgumentException in org.apache.commons.math3.stat.inference |
---|
Methods in org.apache.commons.math3.stat.inference that throw NullArgumentException | |
---|---|
double |
OneWayAnova.anovaFValue(Collection<double[]> categoryData)
Computes the ANOVA F-value for a collection of double[]
arrays. |
double |
OneWayAnova.anovaPValue(Collection<double[]> categoryData)
Computes the ANOVA P-value for a collection of double[]
arrays. |
boolean |
OneWayAnova.anovaTest(Collection<double[]> categoryData,
double alpha)
Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories. |
static double |
TestUtils.chiSquare(long[][] counts)
|
double |
ChiSquareTest.chiSquare(long[][] counts)
Computes the Chi-Square statistic associated with a chi-square test of independence based on the input counts
array, viewed as a two-way table. |
static double |
TestUtils.chiSquareTest(long[][] counts)
|
double |
ChiSquareTest.chiSquareTest(long[][] counts)
Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input counts
array, viewed as a two-way table. |
static boolean |
TestUtils.chiSquareTest(long[][] counts,
double alpha)
|
boolean |
ChiSquareTest.chiSquareTest(long[][] counts,
double alpha)
Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level alpha . |
static double |
TestUtils.homoscedasticT(double[] sample1,
double[] sample2)
|
double |
TTest.homoscedasticT(double[] sample1,
double[] sample2)
Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances. |
static double |
TestUtils.homoscedasticT(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
|
double |
TTest.homoscedasticT(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Computes a 2-sample t statistic, comparing the means of the datasets described by two StatisticalSummary instances, under the
assumption of equal subpopulation variances. |
static double |
TestUtils.homoscedasticTTest(double[] sample1,
double[] sample2)
|
double |
TTest.homoscedasticTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances. |
static boolean |
TestUtils.homoscedasticTTest(double[] sample1,
double[] sample2,
double alpha)
|
boolean |
TTest.homoscedasticTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha , assuming that the
subpopulation variances are equal. |
static double |
TestUtils.homoscedasticTTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
|
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. |
double |
MannWhitneyUTest.mannWhitneyU(double[] x,
double[] y)
Computes the Mann-Whitney U statistic comparing mean for two independent samples possibly of different length. |
double |
MannWhitneyUTest.mannWhitneyUTest(double[] x,
double[] y)
Returns the asymptotic observed significance level, or p-value, associated with a Mann-Whitney U statistic comparing mean for two independent samples. |
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)
|
double |
TTest.pairedTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays. |
static boolean |
TestUtils.pairedTTest(double[] sample1,
double[] sample2,
double alpha)
|
boolean |
TTest.pairedTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between sample1 and
sample2 is 0 in favor of the two-sided alternative that the
mean paired difference is not equal to 0, with significance level
alpha . |
static double |
TestUtils.t(double[] sample1,
double[] sample2)
|
double |
TTest.t(double[] sample1,
double[] sample2)
Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances. |
static double |
TestUtils.t(double mu,
double[] observed)
|
double |
TTest.t(double mu,
double[] observed)
Computes a t statistic given observed values and a comparison constant. |
static double |
TestUtils.t(double mu,
StatisticalSummary sampleStats)
|
double |
TTest.t(double mu,
StatisticalSummary sampleStats)
Computes a t statistic to use in comparing the mean of the dataset described by sampleStats to mu . |
static double |
TestUtils.t(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
|
double |
TTest.t(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Computes a 2-sample t statistic , comparing the means of the datasets described by two StatisticalSummary instances, without the
assumption of equal subpopulation variances. |
static double |
TestUtils.tTest(double[] sample1,
double[] sample2)
|
double |
TTest.tTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays. |
static boolean |
TestUtils.tTest(double[] sample1,
double[] sample2,
double alpha)
|
boolean |
TTest.tTest(double[] sample1,
double[] sample2,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha . |
static double |
TestUtils.tTest(double mu,
double[] sample)
|
double |
TTest.tTest(double mu,
double[] sample)
Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant mu . |
static boolean |
TestUtils.tTest(double mu,
double[] sample,
double alpha)
|
boolean |
TTest.tTest(double mu,
double[] sample,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which sample is drawn equals mu . |
static double |
TestUtils.tTest(double mu,
StatisticalSummary sampleStats)
|
double |
TTest.tTest(double mu,
StatisticalSummary sampleStats)
Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by sampleStats
with the constant mu . |
static boolean |
TestUtils.tTest(double mu,
StatisticalSummary sampleStats,
double alpha)
|
boolean |
TTest.tTest(double mu,
StatisticalSummary sampleStats,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by stats is
drawn equals mu . |
static double |
TestUtils.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
|
double |
TTest.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances. |
static boolean |
TestUtils.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2,
double alpha)
|
boolean |
TTest.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that sampleStats1 and sampleStats2 describe
datasets drawn from populations with the same mean, with significance
level alpha . |
double |
WilcoxonSignedRankTest.wilcoxonSignedRank(double[] x,
double[] y)
Computes the Wilcoxon signed ranked statistic comparing 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 NullArgumentException in org.apache.commons.math3.util |
---|
Methods in org.apache.commons.math3.util that throw NullArgumentException | |
---|---|
static void |
MathUtils.checkNotNull(Object o)
Checks that an object is not null. |
static void |
MathUtils.checkNotNull(Object o,
Localizable pattern,
Object... args)
Checks that an object is not null. |
static void |
MathArrays.checkRectangular(long[][] in)
Throws DimensionMismatchException if the input array is not rectangular. |
static void |
ResizableDoubleArray.copy(ResizableDoubleArray source,
ResizableDoubleArray dest)
Copies source to dest, copying the underlying data, so dest is a new, independent copy of source. |
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. |
double |
DefaultTransformer.transform(Object o)
|
Constructors in org.apache.commons.math3.util that throw NullArgumentException | |
---|---|
ResizableDoubleArray(ResizableDoubleArray original)
Copy constructor. |
|
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