fft_iterative.cpp

#include "internal/fft_iterative.h"
 
#include <algorithm>
#include <cmath>
 
namespace fft {
using std::size_t;
 
// Check if an integer is a power of two.
bool is_power_of_two(size_t n) {
    return n && ((n & (n - 1)) == 0);
}
 
// Return the next power of two >= n.
size_t next_power_of_two(size_t n) {
    if (n == 0)
        return 1;
    --n;
    n |= n >> 1;
    n |= n >> 2;
    n |= n >> 4;
    n |= n >> 8;
    n |= n >> 16;
#if SIZE_MAX > UINT32_MAX
    n |= n >> 32;
#endif
    return ++n;
}
 
/*
 * In-place bit-reversal permutation.
 *
 * The DFT/FFT naturally orders outputs indexed by bit-reversed indices
 * during the divide-and-conquer recursion. For an iterative implementation,
 * we first reorder the input array by bit-reversed indices so subsequent
 * "butterfly" passes combine the correct elements.
 *
 * a: input vector of length N = 2^log_n
 */
void bit_reverse_permute(std::vector<cd>& a) {
    const size_t N = a.size();
    int log_n = 0; // Base 2
    while ((1u << log_n) < N)
        ++log_n; // Set log_n to the exponent of 2 such that N = 2^log_n
 
    // Reverse each element
    for (size_t i = 0; i < N; ++i) {
        // compute bit-reversed index of i with log_n bits
        size_t rev = 0;
        size_t x = i;
        // Reverse element i
        for (int b = 0; b < log_n; ++b) {
            rev = (rev << 1) | (x & 1);
            x >>= 1;
        }
        if (i < rev)
            std::swap(a[i], a[rev]); // Avoid swapping twice
    }
}
 
void pad_to_pow_two(std::vector<cd>& a, size_t& N) {
    if (is_power_of_two(N))
        return;
 
    size_t N2 = next_power_of_two(N);
    a.resize(N2, cd {0.0, 0.0});
    N = N2;
}
 
/*
 * Iterative in-place FFT.
 *
 * Engineering convention:
 *  - forward transform (inverse = false): uses exponent -j*2*pi*k*n/N
 *  - inverse transform (inverse = true): uses exponent +j*2*pi*k*n/N and
 *  divides final results by N (normalization).
 *
 * a: input buffer (modified in-place). After call it contains the transform.
 * inverse: false => forward FFT (negative exponent), true => inverse FFT.
 *
 * Complexity: O(N log N) arithmetic operations, N must be a power of two (or
 * will be padded if pad_to_pow2 is true).
 */
void iterative_fft(std::vector<cd>& a, bool inverse) {
    size_t N {a.size()};
 
    pad_to_pow_two(a, N);
 
    // 1) Bit-reversal permutation
    //      Reorder a for step 2
    bit_reverse_permute(a);
 
    // 2) Iterative Danielson-Lanczos (butterfly) stages.
    const double PI = std::acos(-1.0);
    const double sign =
        inverse ? +1.0 : -1.0; // -1 for forward (engineering convention), +1 for inverse
 
    // len is the current transform length (2, 4, 8, ..., N)
    // For a given len, we combine two sub-DFTs of size len/2 into one of size
    // len.
    for (size_t len = 2; len <= N; len <<= 1) {
        // primitive len-th root of unity for this stage:
        // w_len = exp(sign * j * 2*pi / len)
        const double angle = sign * 2.0 * PI / double(len);
        const cd wlen = std::polar(1.0, angle);
 
        // iterate over blocks of size len
        for (size_t i = 0; i < N; i += len) {
            cd w = cd {1.0, 0.0};         // w = wlen^0 initially
            const size_t half = len >> 1; // len/2 butterflies per block
            for (size_t j = 0; j < half; ++j) {
                // positions in array corresponding to the DFT indices:
                // u = X[i + j] (upper half), v = X[i + j + half] * w (lower half times
                // twiddle)
                cd u = a[i + j];
                cd v = a[i + j + half] * w;
                a[i + j] = u + v;        // combined even-frequency part
                a[i + j + half] = u - v; // combined odd-frequency part
                w *= wlen;               // advance twiddle: w = w * wlen
            }
        }
    }
 
    // 3) If inverse transform, normalize by 1/N to get the true inverse DFT.
    if (inverse) {
        for (size_t i = 0; i < N; ++i)
            a[i] /= static_cast<double>(N);
    }
}
 
/*
 * Convenience wrapper: take a const input vector and return the FFT result
 * as a new vector. This will optionally pad to power-of-two if requested.
 */
std::vector<cd> fft_copy(const std::vector<cd>& input, bool inverse) {
    std::vector<cd> a = input;
    iterative_fft(a, inverse);
    return a;
}
 
// Perform 2D FFT using your iterative FFT on rows and columns
void iterative_fft_2d(std::vector<cd>& data, size_t width, size_t height, bool inverse) {
    // Determine next power-of-two dimensions
    size_t W = fft::next_power_of_two(width);
    size_t H = fft::next_power_of_two(height);
 
    // Pad if necessary
    if (W != width || H != height) {
        std::vector<cd> padded(W * H, {0.0, 0.0});
        for (size_t y = 0; y < height; y++)
            for (size_t x = 0; x < width; x++)
                padded[y * W + x] = data[y * width + x];
        data = std::move(padded);
        width = W;
        height = H;
    }
 
    // Temporary buffers for row/column FFTs
    std::vector<cd> temp_row(width);
    std::vector<cd> temp_col(height);
 
    // FFT rows
    for (size_t y = 0; y < height; y++) {
        std::copy(data.begin() + y * width, data.begin() + (y + 1) * width, temp_row.begin());
        fft::iterative_fft(temp_row, inverse);
        std::copy(temp_row.begin(), temp_row.end(), data.begin() + y * width);
    }
 
    // FFT columns
    for (size_t x = 0; x < width; x++) {
        for (size_t y = 0; y < height; y++)
            temp_col[y] = data[y * width + x];
        fft::iterative_fft(temp_col, inverse);
        for (size_t y = 0; y < height; y++)
            data[y * width + x] = temp_col[y];
    }
}
 
/*
 * Convenience wrapper: take a const input vector and return the 2D FFT result
 * as a new vector. This will optionally pad to power-of-two if requested.
 */
std::vector<cd>
iterative_fft_2d_copy(const std::vector<cd>& input, size_t width, size_t height, bool inverse) {
    std::vector<cd> a = input;
    iterative_fft_2d(a, width, height, inverse);
    return a;
}
} // namespace fft