Uses of Class
com.irurueta.numerical.EvaluationException

Packages that use EvaluationException

Package	Description
com.irurueta.numerical	This library contains packages for:
com.irurueta.numerical.fitting
com.irurueta.numerical.integration
com.irurueta.numerical.optimization

Uses of EvaluationException in com.irurueta.numerical

Methods in com.irurueta.numerical that throw EvaluationException

Modifier and Type	Method	Description
double	DerivativeEstimator.derivative(double x)	Computes the function derivative at provided point x.
double	SavitzkyGolayDerivativeEstimator.derivative(double x)	Computes the function derivative at provided point x.
double	SymmetricDerivativeEstimator.derivative(double x)	Computes the function derivative at provided point x.
double	DirectionalDerivativeEvaluator.differentiateAt(double x)	Computes derivative on current direction of a function at distance x from current point and using current listener and gradient listener.
double	MultiDimensionFunctionEvaluatorListener.evaluate(double[] point)	Evaluates a multi dimension function such as f([x1, x2, ..., xn]) at provided multidimensional point and returns the result as a scalar value.
void	MultiVariateFunctionEvaluatorListener.evaluate(double[] point, double[] result)	Evaluates a multi variate function such as f1(x1, x2, ...), f2(x1, x2, ...) at provided multidimensional point and returns the result as a vectorial value
double	SingleDimensionFunctionEvaluatorListener.evaluate(double point)	Evaluates a single dimension function such as f(x) at provided point and returns the result.
double	DirectionalEvaluator.evaluateAt(double x)	Evaluates a function using current listener at a distance x from current point using current direction
void	GradientFunctionEvaluatorListener.evaluateGradient(double[] params, double[] result)	Computes/retrieves a multidimensional function's gradient.
double[]	GradientEstimator.gradient(double[] point)	Returns the gradient of a multidimensional function at provided point.
void	GradientEstimator.gradient(double[] point, double[] result)	Sets estimated gradient in provided result array of a multidimensional function at provided point.
void	SavitzkyGolayGradientEstimator.gradient(double[] point, double[] result)	Sets estimated gradient in provided result array of a multidimensional function at provided point.
void	SymmetricGradientEstimator.gradient(double[] point, double[] result)	Sets estimated gradient in provided result array of a multidimensional function at provided point.
com.irurueta.algebra.Matrix	JacobianEstimator.jacobian(double[] point)	Returns the Jacobian of a multivariate function at provided point.
void	JacobianEstimator.jacobian(double[] point, com.irurueta.algebra.Matrix result)	Sets estimated jacobian in provided result matrix of a multivariate function at provided point.

Uses of EvaluationException in com.irurueta.numerical.fitting

Methods in com.irurueta.numerical.fitting that throw EvaluationException

Modifier and Type	Method	Description
private void	LevenbergMarquardtMultiDimensionFitter.adjustCovariance()	Adjusts covariance.
private void	LevenbergMarquardtMultiVariateFitter.adjustCovariance()	Adjusts covariance.
private void	LevenbergMarquardtSingleDimensionFitter.adjustCovariance()	Adjusts covariance.
double	LevenbergMarquardtMultiDimensionFunctionEvaluator.evaluate(int i, double[] point, double[] params, double[] derivatives)	Evaluates a non-linear multi dimension function at provided point using provided parameters and returns its evaluation and derivatives of the function respect the function parameters.
void	LevenbergMarquardtMultiVariateFunctionEvaluator.evaluate(int i, double[] point, double[] result, double[] params, com.irurueta.algebra.Matrix jacobian)	Evaluates a non-linear multi variate function at provided point using provided parameters and returns its evaluation and jacobian of the function respect the function parameters
double	LevenbergMarquardtSingleDimensionFunctionEvaluator.evaluate(int i, double point, double[] params, double[] derivatives)	Evaluates a non-linear single dimension function at provided point using provided parameters and returns its evaluation and derivatives of the function respect the function parameters
void	LinearFitterMultiDimensionFunctionEvaluator.evaluate(double[] point, double[] result)	Evaluates a linear multi dimension function at provided point and returns the evaluations of the basis functions at such point
void	LinearFitterSingleDimensionFunctionEvaluator.evaluate(double point, double[] result)	Evaluates a linear single dimension function at provided point and returns the evaluations of the basis functions at such point
private void	LevenbergMarquardtMultiDimensionFitter.mrqcof(double[] a, com.irurueta.algebra.Matrix alpha, double[] beta)	Used by fit to evaluate the linearized fitting matrix alpha, and vector beta to calculate chi square.
private void	LevenbergMarquardtMultiVariateFitter.mrqcof(double[] a, com.irurueta.algebra.Matrix alpha, double[] beta)	Used by fit to evaluate the linearized fitting matrix alpha, and vector beta to calculate chi square.
private void	LevenbergMarquardtSingleDimensionFitter.mrqcof(double[] a, com.irurueta.algebra.Matrix alpha, double[] beta)	Used by LevenbergMarquardtSingleDimensionFitter.fit() to evaluate the linearized fitting matrix alpha, and vector beta to calculate chi square.

Uses of EvaluationException in com.irurueta.numerical.integration

Methods in com.irurueta.numerical.integration that throw EvaluationException

Modifier and Type	Method	Description
void	DoubleExponentialMatrixSingleDimensionFunctionEvaluatorListener.evaluate(double x, double delta, com.irurueta.algebra.Matrix result)	Evaluates a single dimension function such as f(x) at provided point and returns the result.
double	DoubleExponentialSingleDimensionFunctionEvaluatorListener.evaluate(double x, double delta)	Evaluates a single dimension function such as f(x) at provided point and returns the result.
void	MatrixSingleDimensionFunctionEvaluatorListener.evaluate(double point, com.irurueta.algebra.Matrix result)	Evaluates a matrix function such as f(x1) at provided point and returns the result as a matrix.
protected void	ExponentialMidPointMatrixQuadrature.func(double x, com.irurueta.algebra.Matrix result)	Evaluates function at f(-log(x))/x.
protected double	ExponentialMidPointQuadrature.func(double x)	Evaluates function at f(-log(x))/x.
protected void	InfinityMidPointMatrixQuadrature.func(double x, com.irurueta.algebra.Matrix result)	Evaluates function at 1/x.
protected double	InfinityMidPointQuadrature.func(double x)	Evaluates function at 1/x.
protected void	LowerSquareRootMidPointMatrixQuadrature.func(double x, com.irurueta.algebra.Matrix result)	Evaluates function at 2*x*f(a0+x^2).
protected double	LowerSquareRootMidPointQuadrature.func(double x)	Evaluates function at 2*x*f(a0+x^2).
protected void	MidPointMatrixQuadrature.func(double x, com.irurueta.algebra.Matrix result)	Evaluates matrix function at x.
protected double	MidPointQuadrature.func(double x)	Evaluates function at x.
protected void	UpperSquareRootMidPointMatrixQuadrature.func(double x, com.irurueta.algebra.Matrix result)	Evaluates function at 2*x*f(a0+x^2).
protected double	UpperSquareRootMidPointQuadrature.func(double x)	Evaluates function at 2*x*f(a0+x^2).
void	DoubleExponentialRuleMatrixQuadrature.next(com.irurueta.algebra.Matrix result)	Returns the value of the integral at the nth stage of refinement.
double	DoubleExponentialRuleQuadrature.next()	Returns the value of the integral at the nth stage of refinement.
abstract void	MatrixQuadrature.next(com.irurueta.algebra.Matrix result)	Returns the value of the integral at the nth stage of refinement.
void	MidPointMatrixQuadrature.next(com.irurueta.algebra.Matrix result)	Returns the value of the integral at the nth stage of refinement.
double	MidPointQuadrature.next()	Returns the value of the integral at the nth stage of refinement.
abstract double	Quadrature.next()	Returns the value of the integral at the nth stage of refinement.
void	TrapezoidalMatrixQuadrature.next(com.irurueta.algebra.Matrix result)	Returns the value of the integral at the nth stage of refinement.
double	TrapezoidalQuadrature.next()	Returns the value of the integral at the nth stage of refinement.

Uses of EvaluationException in com.irurueta.numerical.optimization

Methods in com.irurueta.numerical.optimization that throw EvaluationException

Modifier and Type	Method	Description
private double	SimplexMultiOptimizer.amotry(com.irurueta.algebra.Matrix p, double[] y, double[] psum, int ihi, double fac, MultiDimensionFunctionEvaluatorListener listener)	Internal method to move simplex around.