示例#1
0
        /// <summary>
        /// Initializes a new instance of the Fourier transformer with the given sign and normalization conventions.
        /// </summary>
        /// <param name="size">The series length of the transformer, which must be positive.</param>
        /// <param name="signConvention">The sign convention of the transformer.</param>
        /// <param name="normalizationConvention">The normalization convention of the transformer.</param>
        public Fourier(int size, FourierSign signConvention, FourierNormalization normalizationConvention)
        {
            if (size < 1)
                throw new YAMPArgumentRangeException("size", 0);

            this.size = size;
            this.signConvention = signConvention;
            this.normalizationConvention = normalizationConvention;

            // pre-compute the Nth complex roots of unity
            this.roots = Helpers.ComputeRoots(size, +1);

            // decompose the size into prime factors
            this.factors = Factors(size);

            // store a plan for the transform based on the prime factorization
            plan = new List<Transformlet>();

            foreach (Factor factor in factors)
            {
                Transformlet t;
                switch (factor.Value)
                {
                    // use a radix-specialized transformlet when available
                    case 2:
                        t = new RadixTwoTransformlet(size, roots);
                        break;
                    case 3:
                        t = new RadixThreeTransformlet(size, roots);
                        break;
                    // eventually, we should make an optimized radix-4 transform
                    case 5:
                        t = new RadixFiveTransformlet(size, roots);
                        break;
                    case 7:
                        t = new RadixSevenTransformlet(size, roots);
                        break;
                    case 11:
                    case 13:
                        // the base transformlet is R^2, but when R is small, this can still be faster than the Bluestein algorithm
                        // timing measurements appear to indicate that this is the case for radix 11 and 13
                        // eventually, we should make optimized Winograd transformlets for these factors
                        t = new Transformlet(factor.Value, size, roots);
                        break;
                    default:
                        // for large factors with no available specialized transformlet, use the Bluestein algorithm
                        t = new BluesteinTransformlet(factor.Value, size, roots);
                        break;
                }

                t.Multiplicity = factor.Multiplicity;
                plan.Add(t);
            }
        }
示例#2
0
        /// <summary>
        /// Initializes a new instance of the Fourier transformer with the given sign and normalization conventions.
        /// </summary>
        /// <param name="size">The series length of the transformer, which must be positive.</param>
        /// <param name="signConvention">The sign convention of the transformer.</param>
        /// <param name="normalizationConvention">The normalization convention of the transformer.</param>
        public Fourier(int size, FourierSign signConvention, FourierNormalization normalizationConvention)
        {
            if (size < 1)
            {
                throw new YAMPArgumentRangeException("size", 0);
            }

            this.size                    = size;
            this.signConvention          = signConvention;
            this.normalizationConvention = normalizationConvention;

            // pre-compute the Nth complex roots of unity
            this.roots = Helpers.ComputeRoots(size, +1);

            // decompose the size into prime factors
            this.factors = Factors(size);

            // store a plan for the transform based on the prime factorization
            plan = new List <Transformlet>();

            foreach (Factor factor in factors)
            {
                Transformlet t;
                switch (factor.Value)
                {
                // use a radix-specialized transformlet when available
                case 2:
                    t = new RadixTwoTransformlet(size, roots);
                    break;

                case 3:
                    t = new RadixThreeTransformlet(size, roots);
                    break;

                // eventually, we should make an optimized radix-4 transform
                case 5:
                    t = new RadixFiveTransformlet(size, roots);
                    break;

                case 7:
                    t = new RadixSevenTransformlet(size, roots);
                    break;

                case 11:
                case 13:
                    // the base transformlet is R^2, but when R is small, this can still be faster than the Bluestein algorithm
                    // timing measurements appear to indicate that this is the case for radix 11 and 13
                    // eventually, we should make optimized Winograd transformlets for these factors
                    t = new Transformlet(factor.Value, size, roots);
                    break;

                default:
                    // for large factors with no available specialized transformlet, use the Bluestein algorithm
                    t = new BluesteinTransformlet(factor.Value, size, roots);
                    break;
                }

                t.Multiplicity = factor.Multiplicity;
                plan.Add(t);
            }
        }