initialGuessSlope = NumericalDifferentiator.DoubleJacobian.differentiate( this.getInitialGuess(), this.data );
initialGuessSlope = NumericalDifferentiator.DoubleJacobian.differentiate( this.getInitialGuess(), this.data );
initialGuessSlope = NumericalDifferentiator.DoubleJacobian.differentiate( this.getInitialGuess(), this.data );
@Override @SuppressWarnings("unchecked") protected boolean initializeAlgorithm() { double x = this.getInitialGuess(); double fx = this.data.evaluate( x ); if( this.data instanceof DifferentiableEvaluator ) { this.dfdx = (DifferentiableEvaluator<Double,Double,Double>) this.data; } else { this.dfdx = new NumericalDifferentiator.DoubleJacobian( this.data, this.getTolerance() ); } this.stepMultiplier = 1.0; this.result = new DefaultInputOutputPair<Double, Double>( x, fx ); return true; }
@Override @SuppressWarnings("unchecked") protected boolean initializeAlgorithm() { double x = this.getInitialGuess(); double fx = this.data.evaluate( x ); if( this.data instanceof DifferentiableEvaluator ) { this.dfdx = (DifferentiableEvaluator<Double,Double,Double>) this.data; } else { this.dfdx = new NumericalDifferentiator.DoubleJacobian( this.data, this.getTolerance() ); } this.stepMultiplier = 1.0; this.result = new DefaultInputOutputPair<Double, Double>( x, fx ); return true; }
@Override @SuppressWarnings("unchecked") protected boolean initializeAlgorithm() { double x = this.getInitialGuess(); double fx = this.data.evaluate( x ); if( this.data instanceof DifferentiableEvaluator ) { this.dfdx = (DifferentiableEvaluator<Double,Double,Double>) this.data; } else { this.dfdx = new NumericalDifferentiator.DoubleJacobian( this.data, this.getTolerance() ); } this.stepMultiplier = 1.0; this.result = new DefaultInputOutputPair<Double, Double>( x, fx ); return true; }
/** * Static access to the numerical differentiation procedure. * @param input * Input about which to approximate the derivative. * @param f * Function of which to approximate the derivative. * @return * Approximated Jacobian, of the same dimension as input */ public static Double differentiate( double input, Evaluator<? super Double,Double> f ) { return DoubleJacobian.differentiate( input, f, DEFAULT_DELTA ); }
/** * Static access to the numerical differentiation procedure. * @param input * Input about which to approximate the derivative. * @param f * Function of which to approximate the derivative. * @return * Approximated Jacobian, of the same dimension as input */ public static Double differentiate( double input, Evaluator<? super Double,Double> f ) { return DoubleJacobian.differentiate( input, f, DEFAULT_DELTA ); }
/** * Static access to the numerical differentiation procedure. * @param input * Input about which to approximate the derivative. * @param f * Function of which to approximate the derivative. * @return * Approximated Jacobian, of the same dimension as input */ public static Double differentiate( double input, Evaluator<? super Double,Double> f ) { return DoubleJacobian.differentiate( input, f, DEFAULT_DELTA ); }
public Double differentiate( Double input ) { return DoubleJacobian.differentiate( input, this.getInternalFunction(), this.getDelta() ); }
public Double differentiate( Double input ) { return DoubleJacobian.differentiate( input, this.getInternalFunction(), this.getDelta() ); }
public Double differentiate( Double input ) { return DoubleJacobian.differentiate( input, this.getInternalFunction(), this.getDelta() ); }