// // Math.NET Numerics, part of the Math.NET Project // https://numerics.mathdotnet.com // // Copyright (c) 2009-2018 Math.NET // // Permission is hereby granted, free of charge, to any person // obtaining a copy of this software and associated documentation // files (the "Software"), to deal in the Software without // restriction, including without limitation the rights to use, // copy, modify, merge, publish, distribute, sublicense, and/or sell // copies of the Software, and to permit persons to whom the // Software is furnished to do so, subject to the following // conditions: // // The above copyright notice and this permission notice shall be // included in all copies or substantial portions of the Software. // // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND // NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT // HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, // WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR // OTHER DEALINGS IN THE SOFTWARE. // using System; using IStation.Numerics.Threading; using Complex = System.Numerics.Complex; namespace IStation.Numerics.Providers.FourierTransform.Managed { internal partial class ManagedFourierTransformProvider { /// /// Sequences with length greater than Math.Sqrt(Int32.MaxValue) + 1 /// will cause k*k in the Bluestein sequence to overflow (GH-286). /// const int BluesteinSequenceLengthThreshold = 46341; /// /// Generate the bluestein sequence for the provided problem size. /// /// Number of samples. /// Bluestein sequence exp(I*Pi*k^2/N) private static Complex32[] BluesteinSequence32(int n) { double s = Constants.Pi / n; var sequence = new Complex32[n]; // TODO: benchmark whether the second variation is significantly // faster than the former one. If not just use the former one always. if (n > BluesteinSequenceLengthThreshold) { for (int k = 0; k < sequence.Length; k++) { double t = (s * k) * k; sequence[k] = new Complex32((float)Math.Cos(t), (float)Math.Sin(t)); } } else { for (int k = 0; k < sequence.Length; k++) { double t = s * (k * k); sequence[k] = new Complex32((float)Math.Cos(t), (float)Math.Sin(t)); } } return sequence; } /// /// Generate the bluestein sequence for the provided problem size. /// /// Number of samples. /// Bluestein sequence exp(I*Pi*k^2/N) private static Complex[] BluesteinSequence(int n) { double s = Constants.Pi / n; var sequence = new Complex[n]; // TODO: benchmark whether the second variation is significantly // faster than the former one. If not just use the former one always. if (n > BluesteinSequenceLengthThreshold) { for (int k = 0; k < sequence.Length; k++) { double t = (s * k) * k; sequence[k] = new Complex(Math.Cos(t), Math.Sin(t)); } } else { for (int k = 0; k < sequence.Length; k++) { double t = s * (k * k); sequence[k] = new Complex(Math.Cos(t), Math.Sin(t)); } } return sequence; } /// /// Convolution with the bluestein sequence (Parallel Version). /// /// Sample Vector. private static void BluesteinConvolutionParallel(Complex32[] samples) { int n = samples.Length; Complex32[] sequence = BluesteinSequence32(n); // Padding to power of two >= 2N–1 so we can apply Radix-2 FFT. int m = ((n << 1) - 1).CeilingToPowerOfTwo(); var b = new Complex32[m]; var a = new Complex32[m]; CommonParallel.Invoke( () => { // Build and transform padded sequence b_k = exp(I*Pi*k^2/N) for (int i = 0; i < n; i++) { b[i] = sequence[i]; } for (int i = m - n + 1; i < b.Length; i++) { b[i] = sequence[m - i]; } Radix2Forward(b); }, () => { // Build and transform padded sequence a_k = x_k * exp(-I*Pi*k^2/N) for (int i = 0; i < samples.Length; i++) { a[i] = sequence[i].Conjugate() * samples[i]; } Radix2Forward(a); }); for (int i = 0; i < a.Length; i++) { a[i] *= b[i]; } Radix2InverseParallel(a); var nbinv = 1.0f / m; for (int i = 0; i < samples.Length; i++) { samples[i] = nbinv * sequence[i].Conjugate() * a[i]; } } /// /// Convolution with the bluestein sequence (Parallel Version). /// /// Sample Vector. private static void BluesteinConvolutionParallel(Complex[] samples) { int n = samples.Length; Complex[] sequence = BluesteinSequence(n); // Padding to power of two >= 2N–1 so we can apply Radix-2 FFT. int m = ((n << 1) - 1).CeilingToPowerOfTwo(); var b = new Complex[m]; var a = new Complex[m]; CommonParallel.Invoke( () => { // Build and transform padded sequence b_k = exp(I*Pi*k^2/N) for (int i = 0; i < n; i++) { b[i] = sequence[i]; } for (int i = m - n + 1; i < b.Length; i++) { b[i] = sequence[m - i]; } Radix2Forward(b); }, () => { // Build and transform padded sequence a_k = x_k * exp(-I*Pi*k^2/N) for (int i = 0; i < samples.Length; i++) { a[i] = sequence[i].Conjugate() * samples[i]; } Radix2Forward(a); }); for (int i = 0; i < a.Length; i++) { a[i] *= b[i]; } Radix2InverseParallel(a); var nbinv = 1.0 / m; for (int i = 0; i < samples.Length; i++) { samples[i] = nbinv * sequence[i].Conjugate() * a[i]; } } /// /// Swap the real and imaginary parts of each sample. /// /// Sample Vector. private static void SwapRealImaginary(Complex32[] samples) { for (int i = 0; i < samples.Length; i++) { samples[i] = new Complex32(samples[i].Imaginary, samples[i].Real); } } /// /// Swap the real and imaginary parts of each sample. /// /// Sample Vector. private static void SwapRealImaginary(Complex[] samples) { for (int i = 0; i < samples.Length; i++) { samples[i] = new Complex(samples[i].Imaginary, samples[i].Real); } } /// /// Bluestein generic FFT for arbitrary sized sample vectors. /// private static void BluesteinForward(Complex[] samples) { BluesteinConvolutionParallel(samples); } /// /// Bluestein generic FFT for arbitrary sized sample vectors. /// private static void BluesteinInverse(Complex[] spectrum) { SwapRealImaginary(spectrum); BluesteinConvolutionParallel(spectrum); SwapRealImaginary(spectrum); } /// /// Bluestein generic FFT for arbitrary sized sample vectors. /// private static void BluesteinForward(Complex32[] samples) { BluesteinConvolutionParallel(samples); } /// /// Bluestein generic FFT for arbitrary sized sample vectors. /// private static void BluesteinInverse(Complex32[] spectrum) { SwapRealImaginary(spectrum); BluesteinConvolutionParallel(spectrum); SwapRealImaginary(spectrum); } } }