/*
    * Licensed to the Apache Software Foundation (ASF) under one or more
    * contributor license agreements.  See the NOTICE file distributed with
    * this work for additional information regarding copyright ownership.
    * The ASF licenses this file to You under the Apache License, Version 2.0
    * (the "License"); you may not use this file except in compliance with
    * the License.  You may obtain a copy of the License at
    *
    *      http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  package org.apache.commons.math4.transform;
  
  import java.util.Arrays;
  import java.util.function.DoubleUnaryOperator;
  
  import org.apache.commons.numbers.core.ArithmeticUtils;
  import org.apache.commons.numbers.complex.Complex;
  
  /**
   * Implements the Fast Fourier Transform for transformation of one-dimensional
   * real or complex data sets. For reference, see <em>Applied Numerical Linear
   * Algebra</em>, ISBN 0898713897, chapter 6.
   * <p>
   * There are several variants of the discrete Fourier transform, with various
   * normalization conventions, which are specified by the parameter
   * {@link Norm}.
   * <p>
   * 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,
   * <i>On computing the discrete Fourier transform</i>, Mathematics of
   * Computation, 32 (1978), 175 - 199.
   */
  public class FastFourierTransform implements ComplexTransform {
      /** Number of array slots: 1 for "real" parts 1 for "imaginary" parts. */
      private static final int NUM_PARTS = 2;
      /**
       * {@code W_SUB_N_R[i]} is the real part of
       * {@code exp(- 2 * i * pi / n)}:
       * {@code W_SUB_N_R[i] = cos(2 * pi/ n)}, where {@code n = 2^i}.
       */
      private static final double[] W_SUB_N_R = {
          0x1.0p0, -0x1.0p0, 0x1.1a62633145c07p-54, 0x1.6a09e667f3bcdp-1,
          0x1.d906bcf328d46p-1, 0x1.f6297cff75cbp-1, 0x1.fd88da3d12526p-1, 0x1.ff621e3796d7ep-1,
          0x1.ffd886084cd0dp-1, 0x1.fff62169b92dbp-1, 0x1.fffd8858e8a92p-1, 0x1.ffff621621d02p-1,
          0x1.ffffd88586ee6p-1, 0x1.fffff62161a34p-1, 0x1.fffffd8858675p-1, 0x1.ffffff621619cp-1,
          0x1.ffffffd885867p-1, 0x1.fffffff62161ap-1, 0x1.fffffffd88586p-1, 0x1.ffffffff62162p-1,
          0x1.ffffffffd8858p-1, 0x1.fffffffff6216p-1, 0x1.fffffffffd886p-1, 0x1.ffffffffff621p-1,
          0x1.ffffffffffd88p-1, 0x1.fffffffffff62p-1, 0x1.fffffffffffd9p-1, 0x1.ffffffffffff6p-1,
          0x1.ffffffffffffep-1, 0x1.fffffffffffffp-1, 0x1.0p0, 0x1.0p0,
          0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0,
          0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0,
          0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0,
          0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0,
          0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0,
          0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0,
          0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0,
          0x1.0p0, 0x1.0p0, 0x1.0p0 };
  
      /**
       * {@code W_SUB_N_I[i]} is the imaginary part of
       * {@code exp(- 2 * i * pi / n)}:
       * {@code W_SUB_N_I[i] = -sin(2 * pi/ n)}, where {@code n = 2^i}.
       */
      private static final double[] W_SUB_N_I = {
          0x1.1a62633145c07p-52, -0x1.1a62633145c07p-53, -0x1.0p0, -0x1.6a09e667f3bccp-1,
          -0x1.87de2a6aea963p-2, -0x1.8f8b83c69a60ap-3, -0x1.917a6bc29b42cp-4, -0x1.91f65f10dd814p-5,
          -0x1.92155f7a3667ep-6, -0x1.921d1fcdec784p-7, -0x1.921f0fe670071p-8, -0x1.921f8becca4bap-9,
          -0x1.921faaee6472dp-10, -0x1.921fb2aecb36p-11, -0x1.921fb49ee4ea6p-12, -0x1.921fb51aeb57bp-13,
          -0x1.921fb539ecf31p-14, -0x1.921fb541ad59ep-15, -0x1.921fb5439d73ap-16, -0x1.921fb544197ap-17,
          -0x1.921fb544387bap-18, -0x1.921fb544403c1p-19, -0x1.921fb544422c2p-20, -0x1.921fb54442a83p-21,
          -0x1.921fb54442c73p-22, -0x1.921fb54442cefp-23, -0x1.921fb54442d0ep-24, -0x1.921fb54442d15p-25,
          -0x1.921fb54442d17p-26, -0x1.921fb54442d18p-27, -0x1.921fb54442d18p-28, -0x1.921fb54442d18p-29,
          -0x1.921fb54442d18p-30, -0x1.921fb54442d18p-31, -0x1.921fb54442d18p-32, -0x1.921fb54442d18p-33,
          -0x1.921fb54442d18p-34, -0x1.921fb54442d18p-35, -0x1.921fb54442d18p-36, -0x1.921fb54442d18p-37,
          -0x1.921fb54442d18p-38, -0x1.921fb54442d18p-39, -0x1.921fb54442d18p-40, -0x1.921fb54442d18p-41,
          -0x1.921fb54442d18p-42, -0x1.921fb54442d18p-43, -0x1.921fb54442d18p-44, -0x1.921fb54442d18p-45,
          -0x1.921fb54442d18p-46, -0x1.921fb54442d18p-47, -0x1.921fb54442d18p-48, -0x1.921fb54442d18p-49,
          -0x1.921fb54442d18p-50, -0x1.921fb54442d18p-51, -0x1.921fb54442d18p-52, -0x1.921fb54442d18p-53,
          -0x1.921fb54442d18p-54, -0x1.921fb54442d18p-55, -0x1.921fb54442d18p-56, -0x1.921fb54442d18p-57,
          -0x1.921fb54442d18p-58, -0x1.921fb54442d18p-59, -0x1.921fb54442d18p-60 };
  
      /** Type of DFT. */
      private final Norm normalization;
      /** Inverse or forward. */
      private final boolean inverse;
  
      /**
       * @param normalization Normalization to be applied to the
       * transformed data.
       * @param inverse Whether to perform the inverse transform.
      */
     public FastFourierTransform(final Norm normalization,
                                 final boolean inverse) {
         this.normalization = normalization;
         this.inverse = inverse;
     }
 
     /**
      * @param normalization Normalization to be applied to the
      * transformed data.
      */
     public FastFourierTransform(final Norm normalization) {
         this(normalization, false);
     }
 
     /**
      * Computes the standard transform of the data.
      * Computation is done in place.
      * Assumed layout of the input data:
      * <ul>
      *   <li>{@code dataRI[0][i]}: Real part of the {@code i}-th data point,</li>
      *   <li>{@code dataRI[1][i]}: Imaginary part of the {@code i}-th data point.</li>
      * </ul>
      *
      * @param dataRI Two-dimensional array of real and imaginary parts of the data.
      * @throws IllegalArgumentException if the number of data points is not
      * a power of two, if the number of rows of the specified array is not two,
      * or the array is not rectangular.
      */
     public void transformInPlace(final double[][] dataRI) {
         if (dataRI.length != NUM_PARTS) {
             throw new TransformException(TransformException.SIZE_MISMATCH,
                                          dataRI.length, NUM_PARTS);
         }
         final double[] dataR = dataRI[0];
         final double[] dataI = dataRI[1];
         if (dataR.length != dataI.length) {
             throw new TransformException(TransformException.SIZE_MISMATCH,
                                          dataI.length, dataR.length);
         }
         final int n = dataR.length;
         if (!ArithmeticUtils.isPowerOfTwo(n)) {
             throw new TransformException(TransformException.NOT_POWER_OF_TWO,
                                          Integer.valueOf(n));
         }
 
         if (n == 1) {
             return;
         } else if (n == 2) {
             final double srcR0 = dataR[0];
             final double srcI0 = dataI[0];
             final double srcR1 = dataR[1];
             final double srcI1 = dataI[1];
 
             // X_0 = x_0 + x_1
             dataR[0] = srcR0 + srcR1;
             dataI[0] = srcI0 + srcI1;
             // X_1 = x_0 - x_1
             dataR[1] = srcR0 - srcR1;
             dataI[1] = srcI0 - srcI1;
 
             normalizeTransformedData(dataRI);
             return;
         }
 
         bitReversalShuffle2(dataR, dataI);
 
         // Do 4-term DFT.
         if (inverse) {
             for (int i0 = 0; i0 < n; i0 += 4) {
                 final int i1 = i0 + 1;
                 final int i2 = i0 + 2;
                 final int i3 = i0 + 3;
 
                 final double srcR0 = dataR[i0];
                 final double srcI0 = dataI[i0];
                 final double srcR1 = dataR[i2];
                 final double srcI1 = dataI[i2];
                 final double srcR2 = dataR[i1];
                 final double srcI2 = dataI[i1];
                 final double srcR3 = dataR[i3];
                 final double srcI3 = dataI[i3];
 
                 // 4-term DFT
                 // X_0 = x_0 + x_1 + x_2 + x_3
                 dataR[i0] = srcR0 + srcR1 + srcR2 + srcR3;
                 dataI[i0] = srcI0 + srcI1 + srcI2 + srcI3;
                 // X_1 = x_0 - x_2 + j * (x_3 - x_1)
                 dataR[i1] = srcR0 - srcR2 + (srcI3 - srcI1);
                 dataI[i1] = srcI0 - srcI2 + (srcR1 - srcR3);
                 // X_2 = x_0 - x_1 + x_2 - x_3
                 dataR[i2] = srcR0 - srcR1 + srcR2 - srcR3;
                 dataI[i2] = srcI0 - srcI1 + srcI2 - srcI3;
                 // X_3 = x_0 - x_2 + j * (x_1 - x_3)
                 dataR[i3] = srcR0 - srcR2 + (srcI1 - srcI3);
                 dataI[i3] = srcI0 - srcI2 + (srcR3 - srcR1);
             }
         } else {
             for (int i0 = 0; i0 < n; i0 += 4) {
                 final int i1 = i0 + 1;
                 final int i2 = i0 + 2;
                 final int i3 = i0 + 3;
 
                 final double srcR0 = dataR[i0];
                 final double srcI0 = dataI[i0];
                 final double srcR1 = dataR[i2];
                 final double srcI1 = dataI[i2];
                 final double srcR2 = dataR[i1];
                 final double srcI2 = dataI[i1];
                 final double srcR3 = dataR[i3];
                 final double srcI3 = dataI[i3];
 
                 // 4-term DFT
                 // X_0 = x_0 + x_1 + x_2 + x_3
                 dataR[i0] = srcR0 + srcR1 + srcR2 + srcR3;
                 dataI[i0] = srcI0 + srcI1 + srcI2 + srcI3;
                 // X_1 = x_0 - x_2 + j * (x_3 - x_1)
                 dataR[i1] = srcR0 - srcR2 + (srcI1 - srcI3);
                 dataI[i1] = srcI0 - srcI2 + (srcR3 - srcR1);
                 // X_2 = x_0 - x_1 + x_2 - x_3
                 dataR[i2] = srcR0 - srcR1 + srcR2 - srcR3;
                 dataI[i2] = srcI0 - srcI1 + srcI2 - srcI3;
                 // X_3 = x_0 - x_2 + j * (x_1 - x_3)
                 dataR[i3] = srcR0 - srcR2 + (srcI3 - srcI1);
                 dataI[i3] = srcI0 - srcI2 + (srcR1 - srcR3);
             }
         }
 
         int lastN0 = 4;
         int lastLogN0 = 2;
         while (lastN0 < n) {
             final int n0 = lastN0 << 1;
             final int logN0 = lastLogN0 + 1;
             final double wSubN0R = W_SUB_N_R[logN0];
             double wSubN0I = W_SUB_N_I[logN0];
             if (inverse) {
                 wSubN0I = -wSubN0I;
             }
 
             // Combine even/odd transforms of size lastN0 into a transform of size N0 (lastN0 * 2).
             for (int destEvenStartIndex = 0; destEvenStartIndex < n; destEvenStartIndex += n0) {
                 final int destOddStartIndex = destEvenStartIndex + lastN0;
 
                 double wSubN0ToRR = 1;
                 double wSubN0ToRI = 0;
 
                 for (int r = 0; r < lastN0; r++) {
                     final int destEvenStartIndexPlusR = destEvenStartIndex + r;
                     final int destOddStartIndexPlusR = destOddStartIndex + r;
 
                     final double grR = dataR[destEvenStartIndexPlusR];
                     final double grI = dataI[destEvenStartIndexPlusR];
                     final double hrR = dataR[destOddStartIndexPlusR];
                     final double hrI = dataI[destOddStartIndexPlusR];
 
                     final double a = wSubN0ToRR * hrR - wSubN0ToRI * hrI;
                     final double b = wSubN0ToRR * hrI + wSubN0ToRI * hrR;
                     // dest[destEvenStartIndex + r] = Gr + WsubN0ToR * Hr
                     dataR[destEvenStartIndexPlusR] = grR + a;
                     dataI[destEvenStartIndexPlusR] = grI + b;
                     // dest[destOddStartIndex + r] = Gr - WsubN0ToR * Hr
                     dataR[destOddStartIndexPlusR] = grR - a;
                     dataI[destOddStartIndexPlusR] = grI - b;
 
                     // WsubN0ToR *= WsubN0R
                     final double nextWsubN0ToRR = wSubN0ToRR * wSubN0R - wSubN0ToRI * wSubN0I;
                     final double nextWsubN0ToRI = wSubN0ToRR * wSubN0I + wSubN0ToRI * wSubN0R;
                     wSubN0ToRR = nextWsubN0ToRR;
                     wSubN0ToRI = nextWsubN0ToRI;
                 }
             }
 
             lastN0 = n0;
             lastLogN0 = logN0;
         }
 
         normalizeTransformedData(dataRI);
     }
 
     /**
      * {@inheritDoc}
      *
      * @throws IllegalArgumentException if the length of the data array is not a power of two.
      */
     @Override
     public Complex[] apply(final double[] f) {
         final double[][] dataRI = {
             Arrays.copyOf(f, f.length),
             new double[f.length]
         };
         transformInPlace(dataRI);
         return TransformUtils.createComplex(dataRI);
     }
 
     /**
      * {@inheritDoc}
      *
      * @throws IllegalArgumentException if the number of sample points
      * {@code n} is not a power of two, if the lower bound is greater than,
      * or equal to the upper bound, if the number of sample points {@code n}
      * is negative
      */
     @Override
     public Complex[] apply(final DoubleUnaryOperator f,
                            final double min,
                            final double max,
                            final int n) {
         return apply(TransformUtils.sample(f, min, max, n));
     }
 
     /**
      * {@inheritDoc}
      *
      * @throws IllegalArgumentException if the length of the data array is
      * not a power of two.
      */
     @Override
     public Complex[] apply(final Complex[] f) {
         final double[][] dataRI = TransformUtils.createRealImaginary(f);
         transformInPlace(dataRI);
         return TransformUtils.createComplex(dataRI);
     }
 
     /**
      * Applies normalization to the transformed data.
      *
      * @param dataRI Unscaled transformed data.
      */
     private void normalizeTransformedData(final double[][] dataRI) {
         final double[] dataR = dataRI[0];
         final double[] dataI = dataRI[1];
         final int n = dataR.length;
 
         switch (normalization) {
         case STD:
             if (inverse) {
                 final double scaleFactor = 1d / n;
                 for (int i = 0; i < n; i++) {
                     dataR[i] *= scaleFactor;
                     dataI[i] *= scaleFactor;
                 }
             }
 
             break;
 
         case UNIT:
             final double scaleFactor = 1d / Math.sqrt(n);
             for (int i = 0; i < n; i++) {
                 dataR[i] *= scaleFactor;
                 dataI[i] *= scaleFactor;
             }
 
             break;
 
         default:
             throw new IllegalStateException(); // Should never happen.
         }
     }
 
     /**
      * Performs identical index bit reversal shuffles on two arrays of
      * identical size.
      * Each element in the array is swapped with another element based
      * on the bit-reversal of the index.
      * For example, in an array with length 16, item at binary index 0011
      * (decimal 3) would be swapped with the item at binary index 1100
      * (decimal 12).
      *
      * @param a Array to be shuffled.
      * @param b Array to be shuffled.
      */
     private static void bitReversalShuffle2(double[] a,
                                             double[] b) {
         final int n = a.length;
         final int halfOfN = n >> 1;
 
         int j = 0;
         for (int i = 0; i < n; i++) {
             if (i < j) {
                 // swap indices i & j
                 double temp = a[i];
                 a[i] = a[j];
                 a[j] = temp;
 
                 temp = b[i];
                 b[i] = b[j];
                 b[j] = temp;
             }
 
             int k = halfOfN;
             while (k <= j && k > 0) {
                 j -= k;
                 k >>= 1;
             }
             j += k;
         }
     }
 
     /**
      * Normalization types.
      */
     public enum Norm {
         /**
          * Should be passed to the constructor of {@link FastFourierTransform}
          * to use the <em>standard</em> normalization convention. This normalization
          * convention is defined as follows
          * <ul>
          * <li>forward transform: \( y_n = \sum_{k = 0}^{N - 1} x_k e^{-2 \pi i n k / N} \),</li>
          * <li>inverse transform: \( x_k = \frac{1}{N} \sum_{n = 0}^{N - 1} y_n e^{2 \pi i n k / N} \),</li>
          * </ul>
          * where \( N \) is the size of the data sample.
          */
         STD,
 
         /**
          * Should be passed to the constructor of {@link FastFourierTransform}
          * to use the <em>unitary</em> normalization convention. This normalization
          * convention is defined as follows
          * <ul>
          * <li>forward transform: \( y_n = \frac{1}{\sqrt{N}} \sum_{k = 0}^{N - 1} x_k e^{-2 \pi i n k / N} \),</li>
          * <li>inverse transform: \( x_k = \frac{1}{\sqrt{N}} \sum_{n = 0}^{N - 1} y_n e^{2 \pi i n k / N} \),</li>
          * </ul>
          * where \( N \) is the size of the data sample.
          */
         UNIT;
     }
 }