Beispiel #1
0
        /// <summary>
        /// Compute a 1D fast Fourier transform of a dataset of complex numbers.
        /// </summary>
        /// <param name="data"></param>
        /// <param name="length"></param>
        /// <param name="direction"></param>
        public static void FFT_Quick(Complex[] data, int length, FourierDirection direction)
        {
            /*if( data == null ) {
             *  throw new ArgumentNullException( "data" );
             * }
             * if( data.Length < length ) {
             *  throw new ArgumentOutOfRangeException( "length", length, "must be at least as large as 'data.Length' parameter" );
             * }
             * if( Fourier.IsPowerOf2( length ) == false ) {
             *  throw new ArgumentOutOfRangeException( "length", length, "must be a power of 2" );
             * }
             *
             * Fourier.SyncLookupTableLength( length );   */

            int ln = Fourier.Log2(length);

            // reorder array
            Fourier.ReorderArray(data);

            // successive doubling
            int N         = 1;
            int signIndex = (direction == FourierDirection.Forward) ? 0 : 1;

            for (int level = 1; level <= ln; level++)
            {
                int M = N;
                N <<= 1;

                double[] uRLookup = _uRLookup[level, signIndex];
                double[] uILookup = _uILookup[level, signIndex];

                for (int j = 0; j < M; j++)
                {
                    double uR = uRLookup[j];
                    double uI = uILookup[j];

                    for (int even = j; even < length; even += N)
                    {
                        int odd = even + M;

                        double r = data[odd].Re;
                        double i = data[odd].Im;

                        double odduR = r * uR - i * uI;
                        double odduI = r * uI + i * uR;

                        r = data[even].Re;
                        i = data[even].Im;

                        data[even].Re = r + odduR;
                        data[even].Im = i + odduI;

                        data[odd].Re = r - odduR;
                        data[odd].Im = i - odduI;
                    }
                }
            }
        }
Beispiel #2
0
        /// <summary>
        /// Compute a 1D fast Fourier transform of a dataset of complex numbers (as pairs of float's).
        /// </summary>
        /// <param name="data"></param>
        /// <param name="length"></param>
        /// <param name="direction"></param>
        public static void FFT_Quick(float[] data, int length, FourierDirection direction)
        {
            /*Debug.Assert( data != null );
             * Debug.Assert( data.Length >= length*2 );
             * Debug.Assert( Fourier.IsPowerOf2( length ) == true );
             *
             * Fourier.SyncLookupTableLength( length );*/

            int ln = Fourier.Log2(length);

            // reorder array
            Fourier.ReorderArray(data);

            // successive doubling
            int N         = 1;
            int signIndex = (direction == FourierDirection.Forward) ? 0 : 1;

            for (int level = 1; level <= ln; level++)
            {
                int M = N;
                N <<= 1;

                float[] uRLookup = _uRLookupF[level, signIndex];
                float[] uILookup = _uILookupF[level, signIndex];

                for (int j = 0; j < M; j++)
                {
                    float uR = uRLookup[j];
                    float uI = uILookup[j];

                    for (int evenT = j; evenT < length; evenT += N)
                    {
                        int even = evenT << 1;
                        int odd  = (evenT + M) << 1;

                        float r = data[odd];
                        float i = data[odd + 1];

                        float odduR = r * uR - i * uI;
                        float odduI = r * uI + i * uR;

                        r = data[even];
                        i = data[even + 1];

                        data[even]     = r + odduR;
                        data[even + 1] = i + odduI;

                        data[odd]     = r - odduR;
                        data[odd + 1] = i - odduI;
                    }
                }
            }
        }