示例#1
0
        public static Complex[] padded_FFT(ref double[] @in)
        {
            Debug.Assert(@in.Length > 0);
            int n = @in.Length;

            int padded = n > 256 ? Util.NextLowPrimes(n) : n;

            Array.Resize <double>(ref @in, padded);

            // 4096 real numbers on input processed by FFTW dft_r2c_1d transform gives
            // 4096/2+1 = 2049 complex numbers at output
            // prepare the input arrays
            var fftwInput = new FFTW.DoubleArray(@in);

            int complexSize = (padded >> 1) + 1;             // this is the same as (padded / 2 + 1);
            var fftwOutput  = new FFTW.ComplexArray(complexSize);

            FFTW.ForwardTransform(fftwInput, fftwOutput);

            Array.Resize <double>(ref @in, n);

            // free up memory
            GC.Collect();

            return(FFTUtils.ComplexDoubleToComplex(fftwOutput.ComplexValues));
        }
		public static double[] padded_IFFT(ref Complex[] @in, bool doProperScaling=false)
		{
			Debug.Assert(@in.Length > 1);
			
			int originalLength = @in.Length;
			int n = (@in.Length - 1) * 2;
			
			int padded = n > 256 ? Util.NextLowPrimes(n) : n;

			Array.Resize<Complex>(ref @in, padded / 2 + 1);
			
			// prepare the input arrays
			var complexDouble = FFTUtils.ComplexToComplexDouble(@in);
			var fftwBackwardInput = new FFTW.ComplexArray(complexDouble);
			var fftwBackwardOutput = new FFTW.DoubleArray(padded);
			
			// this method needs that the backwards transform uses the output.length as it's N
			// i.e. FFTW.dft_c2r_1d(output.Length, input.Handle, output.Handle, Flags.Estimate);
			FFTW.BackwardTransform(fftwBackwardInput, fftwBackwardOutput);
			
			double[] @out = null;
			if (doProperScaling) {
				@out = fftwBackwardOutput.ValuesDivedByN;
			} else {
				// in the original method it wasn't scaled correctly (meaning ValuesDivedByN)
				@out = fftwBackwardOutput.Values;
			}
			
			Array.Resize<Complex>(ref @in, n / 2 + 1);
			
			// free up memory
			GC.Collect();

			return @out;
		}
示例#3
0
        private double[] MagnitudeSpectrum(float[] frame)
        {
            // prepare the input arrays
            FFTW.DoubleArray fftwInput = new FFTW.DoubleArray(MathUtils.FloatToDouble(frame));

            int complexSize = (frame.Length >> 1) + 1;

            FFTW.ComplexArray fftwOutput = new FFTW.ComplexArray(complexSize);

            FFTW.ForwardTransform(fftwInput, fftwOutput);
            double[] magSpectrum = fftwOutput.Abs;

            /*
             * double[] magSpectrum = new double[frame.Length];
             *
             * // calculate FFT for current frame
             * fft.ComputeFFT(frame);
             *
             * // System.err.println("FFT SUCCEED");
             * // calculate magnitude spectrum
             * for (int k = 0; k < frame.Length; k++)
             * {
             *      magSpectrum[k] = Math.Sqrt(fft.real[k] * fft.real[k] + fft.imag[k] * fft.imag[k]);
             * }
             */
            return(magSpectrum);
        }
		public static Complex[] padded_FFT(ref double[] @in)
		{
			Debug.Assert(@in.Length > 0);
			int n = @in.Length;
			
			int padded = n > 256 ? Util.NextLowPrimes(n) : n;
			Array.Resize<double>(ref @in, padded);

			// 4096 real numbers on input processed by FFTW dft_r2c_1d transform gives
			// 4096/2+1 = 2049 complex numbers at output
			// prepare the input arrays
			var fftwInput = new FFTW.DoubleArray(@in);
			
			int complexSize = (padded >> 1) + 1; // this is the same as (padded / 2 + 1);
			var fftwOutput = new FFTW.ComplexArray(complexSize);
			
			FFTW.ForwardTransform(fftwInput, fftwOutput);
			
			Array.Resize<double>(ref @in, n);
			
			// free up memory
			GC.Collect();
			
			return FFTUtils.ComplexDoubleToComplex(fftwOutput.ComplexValues);
		}
示例#5
0
        public static double[] padded_IFFT(ref Complex[] @in, bool doProperScaling = false)
        {
            Debug.Assert(@in.Length > 1);

            int originalLength = @in.Length;
            int n = (@in.Length - 1) * 2;

            int padded = n > 256 ? Util.NextLowPrimes(n) : n;

            Array.Resize <Complex>(ref @in, padded / 2 + 1);

            // prepare the input arrays
            var complexDouble      = FFTUtils.ComplexToComplexDouble(@in);
            var fftwBackwardInput  = new FFTW.ComplexArray(complexDouble);
            var fftwBackwardOutput = new FFTW.DoubleArray(padded);

            // this method needs that the backwards transform uses the output.length as it's N
            // i.e. FFTW.dft_c2r_1d(output.Length, input.Handle, output.Handle, Flags.Estimate);
            FFTW.BackwardTransform(fftwBackwardInput, fftwBackwardOutput);

            double[] @out = null;
            if (doProperScaling)
            {
                @out = fftwBackwardOutput.ValuesDivedByN;
            }
            else
            {
                // in the original method it wasn't scaled correctly (meaning ValuesDivedByN)
                @out = fftwBackwardOutput.Values;
            }

            Array.Resize <Complex>(ref @in, n / 2 + 1);

            // free up memory
            GC.Collect();

            return(@out);
        }