Examples of org.apache.commons.math3.transform.FastFourierTransformer

Package org.apache.commons.math3.transform

Examples of org.apache.commons.math3.transform.FastFourierTransformer

org.apache.commons.math3.fraction.BigFraction
Implements the Fast Fourier Transform for transformation of one-dimensional real or complex data sets. For reference, see Applied Numerical Linear Algebra, ISBN 0898713897, chapter 6.
There are several variants of the discrete Fourier transform, with various normalization conventions, which are specified by the parameter {@link DftNormalization}.
The current implementation of the discrete Fourier transform as a fast Fourier transform requires the length of the data set to be a power of 2. This greatly simplifies and speeds up the code. Users can pad the data with zeros to meet this requirement. There are other flavors of FFT, for reference, see S. Winograd, On computing the discrete Fourier transform, Mathematics of Computation, 32 (1978), 175 - 199. @see DftNormalization @since 1.2

    @Override
    public double inverseCumulativeProbability(double p) throws OutOfRangeException {
        double ret;


        if (p < 0.0 || p > 1.0) {
            throw new OutOfRangeException(p, 0.0, 1.0);
        } else if (p == 1.0) {
            ret = Double.POSITIVE_INFINITY;
        } else {
            ret = -mean * FastMath.log(1.0 - p);
        }

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        if (lo >= hi) {
            throw new NumberIsTooLargeException(lo, hi, false);
        }
        if (init < lo ||
            init > hi) {
            throw new OutOfRangeException(init, lo, hi);
        }


        lower = lo;
        upper = hi;
        start = init;

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    @Override
    public double inverseCumulativeProbability(double p)
        throws OutOfRangeException {
        if (p < 0 || p > 1) {
            throw new OutOfRangeException(p, 0, 1);
        }
        if (p == 0) {
            return a;
        }
        if (p == 1) {

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        /**
         * {@inheritDoc}
         * @throws TooManyEvaluationsException.
         */
        public void trigger(int max) {
            throw new TooManyEvaluationsException(max);
        }

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    protected void incrementEvaluationCount()
        throws TooManyEvaluationsException {
        try {
            evaluations.incrementCount();
        } catch (MaxCountExceededException e) {
            throw new TooManyEvaluationsException(e.getMax());
        }
    }

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        /**
         * {@inheritDoc}
         * @throws TooManyIterationsException.
         */
        public void trigger(int max) {
            throw new TooManyIterationsException(max);
        }

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                                              double threshold) {
        super(wrong, threshold, false);
        this.index = index;
        this.threshold = threshold;


        final ExceptionContext context = getContext();
        context.addMessage(LocalizedFormats.NOT_POSITIVE_DEFINITE_MATRIX);
        context.addMessage(LocalizedFormats.ARRAY_ELEMENT, wrong, index);
    }

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            final double t = x.dotProduct(z);
            final double epsa = (s + MACH_PREC) * CBRT_MACH_PREC;
            if (FastMath.abs(s - t) > epsa) {
                final NonSelfAdjointOperatorException e;
                e = new NonSelfAdjointOperatorException();
                final ExceptionContext context = e.getContext();
                context.setValue(SymmLQ.OPERATOR, l);
                context.setValue(SymmLQ.VECTOR1, x);
                context.setValue(SymmLQ.VECTOR2, y);
                context.setValue(SymmLQ.THRESHOLD, Double.valueOf(epsa));
                throw e;
            }
        }

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         */
        private static void throwNPDLOException(final RealLinearOperator l,
            final RealVector v) throws NonPositiveDefiniteOperatorException {
            final NonPositiveDefiniteOperatorException e;
            e = new NonPositiveDefiniteOperatorException();
            final ExceptionContext context = e.getContext();
            context.setValue(OPERATOR, l);
            context.setValue(VECTOR, v);
            throw e;
        }

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            // build the P matrix elements from Taylor series formulas
            final BigFraction[] pI = pData[i];
            final int factor = -(i + 1);
            int aj = factor;
            for (int j = 0; j < pI.length; ++j) {
                pI[j] = new BigFraction(aj * (j + 2));
                aj *= factor;
            }
        }


        return new Array2DRowFieldMatrix<BigFraction>(pData, false);

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org.apache.commons.math3.analysis.differentiation.DerivativeStructure

org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction

org.apache.commons.math3.analysis.function.HarmonicOscillator

org.apache.commons.math3.analysis.function.Sin

org.apache.commons.math3.analysis.function.Sinc

org.apache.commons.math3.analysis.MultivariateFunction

org.apache.commons.math3.analysis.QuinticFunction

org.apache.commons.math3.analysis.solvers.BrentSolver

org.apache.commons.math3.analysis.UnivariateFunction

org.apache.commons.math3.complex.Complex

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