# Uses of Class
org.apache.commons.math3.exception.NoDataException

Packages that use NoDataException
Package
Description
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.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.filter
Implementations of common discrete-time linear filters.
org.apache.commons.math3.linear
Linear algebra support.
org.apache.commons.math3.stat
Data storage, manipulation and summary routines.
org.apache.commons.math3.stat.inference
Classes providing hypothesis testing.
org.apache.commons.math3.stat.regression
Statistical routines involving multivariate data.
org.apache.commons.math3.util
Convenience routines and common data structures used throughout the commons-math library.

## Uses of NoDataException in org.apache.commons.math3.analysis.function

Constructors in org.apache.commons.math3.analysis.function that throw NoDataException
Modifier
Constructor
Description
``
`StepFunction(double[] x, double[] y)`
Builds a step function from a list of arguments and the corresponding values.

## Uses of NoDataException in org.apache.commons.math3.analysis.interpolation

Methods in org.apache.commons.math3.analysis.interpolation that throw NoDataException
Modifier and Type
Method
Description
`T[][]`
FieldHermiteInterpolator.`derivatives(T x, int order)`
Interpolate value and first derivatives at a specified abscissa.
`PolynomialFunction[]`
HermiteInterpolator.`getPolynomials()`
Compute the interpolation polynomials.
`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.
`final PolynomialSplineFunction`
LoessInterpolator.`interpolate(double[] xval, double[] yval)`
Compute an interpolating function by performing a loess fit on the data at the original abscissae and then building a cubic spline with a `SplineInterpolator` on the resulting fit.
`MultivariateFunction`
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.
`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.
`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.
`final double[]`
LoessInterpolator.`smooth(double[] xval, double[] yval)`
Compute a loess fit on the data at the original abscissae.
`final double[]`
LoessInterpolator.`smooth(double[] xval, double[] yval, double[] weights)`
Compute a weighted loess fit on the data at the original abscissae.
`T[]`
FieldHermiteInterpolator.`value(T x)`
Interpolate value at a specified abscissa.
`double[]`
HermiteInterpolator.`value(double x)`
Interpolate value at a specified abscissa.
`DerivativeStructure[]`
HermiteInterpolator.`value(DerivativeStructure x)`
Interpolate value at a specified abscissa.
Constructors in org.apache.commons.math3.analysis.interpolation that throw NoDataException
Modifier
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 NoDataException in org.apache.commons.math3.analysis.polynomials

Methods in org.apache.commons.math3.analysis.polynomials that throw NoDataException
Modifier and Type
Method
Description
`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.
`static double`
PolynomialFunctionNewtonForm.`evaluate(double[] a, double[] c, double z)`
Evaluate the Newton polynomial using nested multiplication.
`double`
PolynomialFunction.Parametric.`value(double x, double... parameters)`
Compute the value of the function.
`DerivativeStructure`
PolynomialFunction.`value(DerivativeStructure t)`
Simple mathematical function.
`protected static void`
PolynomialFunctionNewtonForm.`verifyInputArray(double[] a, double[] c)`
Verifies that the input arrays are valid.
Constructors in org.apache.commons.math3.analysis.polynomials that throw NoDataException
Modifier
Constructor
Description
``
`PolynomialFunction(double[] c)`
Construct a polynomial with the given coefficients.
``
`PolynomialFunctionNewtonForm(double[] a, double[] c)`
Construct a Newton polynomial with the given a[] and c[].

## Uses of NoDataException in org.apache.commons.math3.analysis.solvers

Methods in org.apache.commons.math3.analysis.solvers that throw NoDataException
Modifier and Type
Method
Description
`Complex[]`
LaguerreSolver.`solveAllComplex(double[] coefficients, double initial)`
Find all complex roots for the polynomial with the given coefficients, starting from the given initial value.
`Complex[]`
LaguerreSolver.`solveAllComplex(double[] coefficients, double initial, int maxEval)`
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.
`Complex`
LaguerreSolver.`solveComplex(double[] coefficients, double initial, int maxEval)`
Find a complex root for the polynomial with the given coefficients, starting from the given initial value.

## Uses of NoDataException in org.apache.commons.math3.complex

Methods in org.apache.commons.math3.complex that throw NoDataException
Modifier and Type
Method
Description
`static ComplexFormat`
ComplexFormat.`getInstance(String imaginaryCharacter, Locale locale)`
Returns the default complex format for the given locale.
Constructors in org.apache.commons.math3.complex that throw NoDataException
Modifier
Constructor
Description
``
`ComplexFormat(String imaginaryCharacter)`
Create an instance with a custom imaginary character, and the default number format for both real and imaginary parts.
``
`ComplexFormat(String imaginaryCharacter, NumberFormat format)`
Create an instance with a custom imaginary character, and a custom number format for both real and imaginary parts.
``
`ComplexFormat(String imaginaryCharacter, NumberFormat realFormat, NumberFormat imaginaryFormat)`
Create an instance with a custom imaginary character, a custom number format for the real part, and a custom number format for the imaginary part.

## Uses of NoDataException in org.apache.commons.math3.filter

Constructors in org.apache.commons.math3.filter that throw NoDataException
Modifier
Constructor
Description
``
`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.

## Uses of NoDataException in org.apache.commons.math3.linear

Methods in org.apache.commons.math3.linear that throw NoDataException
Modifier and Type
Method
Description
`protected void`
AbstractFieldMatrix.`checkSubMatrixIndex(int[] selectedRows, int[] selectedColumns)`
Check if submatrix ranges indices are valid.
`static void`
MatrixUtils.`checkSubMatrixIndex(AnyMatrix m, int[] selectedRows, int[] selectedColumns)`
Check if submatrix ranges indices are valid.
`void`
AbstractFieldMatrix.`copySubMatrix(int[] selectedRows, int[] selectedColumns, T[][] destination)`
Copy a submatrix.
`void`
AbstractRealMatrix.`copySubMatrix(int[] selectedRows, int[] selectedColumns, double[][] destination)`
Copy a submatrix.
`void`
FieldMatrix.`copySubMatrix(int[] selectedRows, int[] selectedColumns, T[][] destination)`
Copy a submatrix.
`void`
RealMatrix.`copySubMatrix(int[] selectedRows, int[] selectedColumns, double[][] destination)`
Copy a submatrix.
`static <T extends FieldElement<T>>
FieldMatrix<T>`
MatrixUtils.`createColumnFieldMatrix(T[] columnData)`
Creates a column `FieldMatrix` using the data from the input array.
`static RealMatrix`
MatrixUtils.`createColumnRealMatrix(double[] columnData)`
Creates a column `RealMatrix` using the data from the input array.
`static <T extends FieldElement<T>>
FieldMatrix<T>`
MatrixUtils.`createFieldMatrix(T[][] data)`
Returns a `FieldMatrix` whose entries are the the values in the the input array.
`static <T extends FieldElement<T>>
FieldVector<T>`
MatrixUtils.`createFieldVector(T[] data)`
Creates a `FieldVector` using the data from the input array.
`static RealMatrix`
MatrixUtils.`createRealMatrix(double[][] data)`
Returns a `RealMatrix` whose entries are the the values in the the input array.
`static RealVector`
MatrixUtils.`createRealVector(double[] data)`
Creates a `RealVector` using the data from the input array.
`static <T extends FieldElement<T>>
FieldMatrix<T>`
MatrixUtils.`createRowFieldMatrix(T[] rowData)`
Create a row `FieldMatrix` using the data from the input array.
`static RealMatrix`
MatrixUtils.`createRowRealMatrix(double[] rowData)`
Create a row `RealMatrix` using the data from the input array.
`protected static <T extends FieldElement<T>>
Field<T>`
AbstractFieldMatrix.`extractField(T[] d)`
Get the elements type from an array.
`protected static <T extends FieldElement<T>>
Field<T>`
AbstractFieldMatrix.`extractField(T[][] d)`
Get the elements type from an array.
`FieldMatrix<T>`
AbstractFieldMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)`
Get a submatrix.
`RealMatrix`
AbstractRealMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)`
Gets a submatrix.
`FieldMatrix<T>`
FieldMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)`
Get a submatrix.
`RealMatrix`
RealMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)`
Gets a submatrix.
`void`
AbstractFieldMatrix.`setSubMatrix(T[][] subMatrix, int row, int column)`
Replace the submatrix starting at `(row, column)` using data in the input `subMatrix` array.
`void`
AbstractRealMatrix.`setSubMatrix(double[][] subMatrix, int row, int column)`
Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
`void`
Array2DRowFieldMatrix.`setSubMatrix(T[][] subMatrix, int row, int column)`
Replace the submatrix starting at `(row, column)` using data in the input `subMatrix` array.
`void`
Array2DRowRealMatrix.`setSubMatrix(double[][] subMatrix, int row, int column)`
Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
`void`
BlockFieldMatrix.`setSubMatrix(T[][] subMatrix, int row, int column)`
Replace the submatrix starting at `(row, column)` using data in the input `subMatrix` array.
`void`
BlockRealMatrix.`setSubMatrix(double[][] subMatrix, int row, int column)`
Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
`void`
FieldMatrix.`setSubMatrix(T[][] subMatrix, int row, int column)`
Replace the submatrix starting at `(row, column)` using data in the input `subMatrix` array.
`void`
RealMatrix.`setSubMatrix(double[][] subMatrix, int row, int column)`
Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
Constructors in org.apache.commons.math3.linear that throw NoDataException
Modifier
Constructor
Description
``
`Array2DRowFieldMatrix(Field<T> field, T[][] d)`
Create a new `FieldMatrix<T>` using the input array as the underlying data array.
``
`Array2DRowFieldMatrix(Field<T> field, T[][] d, boolean copyArray)`
Create a new `FieldMatrix<T>` using the input array as the underlying data array.
``
`Array2DRowFieldMatrix(T[] v)`
Create a new (column) `FieldMatrix<T>` using `v` as the data for the unique column of the created matrix.
``
`Array2DRowFieldMatrix(T[][] d)`
Create a new `FieldMatrix<T>` using the input array as the underlying data array.
``
`Array2DRowFieldMatrix(T[][] d, boolean copyArray)`
Create a new `FieldMatrix<T>` using the input array as the underlying data array.
``
`Array2DRowRealMatrix(double[][] d)`
Create a new `RealMatrix` using the input array as the underlying data array.
``
`Array2DRowRealMatrix(double[][] d, boolean copyArray)`
Create a new RealMatrix using the input array as the underlying data array.

## Uses of NoDataException in org.apache.commons.math3.stat

Methods in org.apache.commons.math3.stat that throw NoDataException
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]).

## Uses of NoDataException in org.apache.commons.math3.stat.inference

Methods in org.apache.commons.math3.stat.inference that throw NoDataException
Modifier and Type
Method
Description
`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.`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 between `sample1` and `sample2` is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level `alpha`.
`double`
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 NoDataException in org.apache.commons.math3.stat.regression

Methods in org.apache.commons.math3.stat.regression that throw NoDataException
Modifier and Type
Method
Description
`RegressionResults`
SimpleRegression.`regress()`
Performs a regression on data present in buffers and outputs a RegressionResults object.
`RegressionResults`
UpdatingMultipleLinearRegression.`regress()`
Performs a regression on data present in buffers and outputs a RegressionResults object

## Uses of NoDataException in org.apache.commons.math3.util

Methods in org.apache.commons.math3.util that throw NoDataException
Modifier and Type
Method
Description
`static double[]`
MathArrays.`convolve(double[] x, double[] h)`
Calculates the convolution between two sequences.