/*
 * Copyright (c) 2018, Alliance for Open Media. All rights reserved
 *
 * This source code is subject to the terms of the BSD 2 Clause License and
 * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
 * was not distributed with this source code in the LICENSE file, you can
 * obtain it at https://www.aomedia.org/license/software-license. If the Alliance for Open
 * Media Patent License 1.0 was not distributed with this source code in the
 * PATENTS file, you can obtain it at https://www.aomedia.org/license/patent-license.
 */

#include "EbDefinitions.h"
#include "fft_common.h"

static INLINE void simple_transpose(const float *A, float *b, int32_t n) {
    for (int32_t y = 0; y < n; y++) {
        for (int32_t x = 0; x < n; x++) b[y * n + x] = A[x * n + y];
    }
}

// The 1d transform is real to complex and packs the complex results in
// a way to take advantage of conjugate symmetry (e.g., the n/2 + 1 real
// components, followed by the n/2 - 1 imaginary components). After the
// transform is done on the rows, the first n/2 + 1 columns are real, and
// the remaining are the imaginary components. After the transform on the
// columns, the region of [0, n/2]x[0, n/2] contains the real part of
// fft of the real columns. The real part of the 2d fft also includes the
// imaginary part of transformed imaginary columns. This function assembles
// the correct outputs while putting the real and imaginary components
// next to each other.
static INLINE void unpack_2d_output(const float *col_fft, float *output, int32_t n) {
    for (int32_t y = 0; y <= n / 2; ++y) {
        const int32_t y2      = y + n / 2;
        const int32_t y_extra = y2 > n / 2 && y2 < n;

        for (int32_t x = 0; x <= n / 2; ++x) {
            const int32_t x2        = x + n / 2;
            const int32_t x_extra   = x2 > n / 2 && x2 < n;
            output[2 * (y * n + x)] = col_fft[y * n + x] -
                (x_extra && y_extra ? col_fft[y2 * n + x2] : 0);
            output[2 * (y * n + x) + 1] = (y_extra ? col_fft[y2 * n + x] : 0) +
                (x_extra ? col_fft[y * n + x2] : 0);
            if (y_extra) {
                output[2 * ((n - y) * n + x)] = col_fft[y * n + x] +
                    (x_extra && y_extra ? col_fft[y2 * n + x2] : 0);
                output[2 * ((n - y) * n + x) + 1] = -col_fft[y2 * n + x] +
                    (x_extra ? col_fft[y * n + x2] : 0);
            }
        }
    }
}

void svt_aom_fft_2d_gen(const float *input, float *temp, float *output, int32_t n,
                        AomFft1dFunc tform, AomFftTransposeFunc transpose, AomFftUnpackFunc unpack,
                        int32_t vec_size) {
    for (int32_t x = 0; x < n; x += vec_size) tform(input + x, output + x, n);
    transpose(output, temp, n);

    for (int32_t x = 0; x < n; x += vec_size) tform(temp + x, output + x, n);
    transpose(output, temp, n);

    unpack(temp, output, n);
}

static INLINE void  store_float(float *output, float input) { *output = input; }
static INLINE float add_float(float a, float b) { return a + b; }
static INLINE float sub_float(float a, float b) { return a - b; }
static INLINE float mul_float(float a, float b) { return a * b; }

GEN_FFT_2(void, float, float, float, *, store_float);
GEN_FFT_4(void, float, float, float, *, store_float, (float), add_float, sub_float);
GEN_FFT_8(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float);
GEN_FFT_16(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float);
GEN_FFT_32(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float);

void svt_aom_fft2x2_float_c(const float *input, float *temp, float *output) {
    svt_aom_fft_2d_gen(
        input, temp, output, 2, svt_aom_fft1d_2_float, simple_transpose, unpack_2d_output, 1);
}

void svt_aom_fft4x4_float_c(const float *input, float *temp, float *output) {
    svt_aom_fft_2d_gen(
        input, temp, output, 4, svt_aom_fft1d_4_float, simple_transpose, unpack_2d_output, 1);
}

void svt_aom_fft8x8_float_c(const float *input, float *temp, float *output) {
    svt_aom_fft_2d_gen(
        input, temp, output, 8, svt_aom_fft1d_8_float, simple_transpose, unpack_2d_output, 1);
}

void svt_aom_fft16x16_float_c(const float *input, float *temp, float *output) {
    svt_aom_fft_2d_gen(
        input, temp, output, 16, svt_aom_fft1d_16_float, simple_transpose, unpack_2d_output, 1);
}

void svt_aom_fft32x32_float_c(const float *input, float *temp, float *output) {
    svt_aom_fft_2d_gen(
        input, temp, output, 32, svt_aom_fft1d_32_float, simple_transpose, unpack_2d_output, 1);
}

void svt_aom_ifft_2d_gen(const float *input, float *temp, float *output, int32_t n,
                         AomFft1dFunc fft_single, AomFft1dFunc fft_multi, AomFft1dFunc ifft_multi,
                         AomFftTransposeFunc transpose, int32_t vec_size) {
    // Column 0 and n/2 have conjugate symmetry, so we can directly do the ifft
    // and get real outputs.
    for (int32_t y = 0; y <= n / 2; ++y) {
        output[y * n]     = input[2 * y * n];
        output[y * n + 1] = input[2 * (y * n + n / 2)];
    }
    for (int32_t y = n / 2 + 1; y < n; ++y) {
        output[y * n]     = input[2 * (y - n / 2) * n + 1];
        output[y * n + 1] = input[2 * ((y - n / 2) * n + n / 2) + 1];
    }

    for (int32_t i = 0; i < 2; i += vec_size) ifft_multi(output + i, temp + i, n);
    // For the other columns, since we don't have a full ifft for complex inputs
    // we have to split them into the real and imaginary counterparts.
    // Pack the real component, then the imaginary components.
    for (int32_t y = 0; y < n; ++y) {
        for (int32_t x = 1; x < n / 2; ++x) output[y * n + (x + 1)] = input[2 * (y * n + x)];
        for (int32_t x = 1; x < n / 2; ++x)
            output[y * n + (x + n / 2)] = input[2 * (y * n + x) + 1];
    }
    for (int32_t y = 2; y < vec_size; y++) fft_single(output + y, temp + y, n);
    // This is the part that can be sped up with SIMD
    for (int32_t y = AOMMAX(2, vec_size); y < n; y += vec_size) fft_multi(output + y, temp + y, n);
    // Put the 0 and n/2 th results in the correct place.
    for (int32_t x = 0; x < n; ++x) {
        output[x]               = temp[x * n];
        output[(n / 2) * n + x] = temp[x * n + 1];
    }
    // This rearranges and transposes.
    for (int32_t y = 1; y < n / 2; ++y) {
        // Fill in the real columns
        for (int32_t x = 0; x <= n / 2; ++x) {
            output[x + y * n] = temp[(y + 1) + x * n] +
                ((x > 0 && x < n / 2) ? temp[(y + n / 2) + (x + n / 2) * n] : 0);
        }
        for (int32_t x = n / 2 + 1; x < n; ++x) {
            output[x + y * n] = temp[(y + 1) + (n - x) * n] -
                temp[(y + n / 2) + ((n - x) + n / 2) * n];
        }
        // Fill in the imag columns
        for (int32_t x = 0; x <= n / 2; ++x) {
            output[x + (y + n / 2) * n] = temp[(y + n / 2) + x * n] -
                ((x > 0 && x < n / 2) ? temp[(y + 1) + (x + n / 2) * n] : 0);
        }
        for (int32_t x = n / 2 + 1; x < n; ++x) {
            output[x + (y + n / 2) * n] = temp[(y + 1) + ((n - x) + n / 2) * n] +
                temp[(y + n / 2) + (n - x) * n];
        }
    }
    for (int32_t y = 0; y < n; y += vec_size) ifft_multi(output + y, temp + y, n);
    transpose(temp, output, n);
}

GEN_IFFT_2(void, float, float, float, *, store_float);
GEN_IFFT_4(void, float, float, float, *, store_float, (float), add_float, sub_float);
GEN_IFFT_8(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float);
GEN_IFFT_16(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float);
GEN_IFFT_32(void, float, float, float, *, store_float, (float), add_float, sub_float, mul_float);

void svt_aom_ifft2x2_float_c(const float *input, float *temp, float *output) {
    svt_aom_ifft_2d_gen(input,
                        temp,
                        output,
                        2,
                        svt_aom_fft1d_2_float,
                        svt_aom_fft1d_2_float,
                        svt_aom_ifft1d_2_float,
                        simple_transpose,
                        1);
}

void svt_aom_ifft4x4_float_c(const float *input, float *temp, float *output) {
    svt_aom_ifft_2d_gen(input,
                        temp,
                        output,
                        4,
                        svt_aom_fft1d_4_float,
                        svt_aom_fft1d_4_float,
                        svt_aom_ifft1d_4_float,
                        simple_transpose,
                        1);
}

void svt_aom_ifft8x8_float_c(const float *input, float *temp, float *output) {
    svt_aom_ifft_2d_gen(input,
                        temp,
                        output,
                        8,
                        svt_aom_fft1d_8_float,
                        svt_aom_fft1d_8_float,
                        svt_aom_ifft1d_8_float,
                        simple_transpose,
                        1);
}

void svt_aom_ifft16x16_float_c(const float *input, float *temp, float *output) {
    svt_aom_ifft_2d_gen(input,
                        temp,
                        output,
                        16,
                        svt_aom_fft1d_16_float,
                        svt_aom_fft1d_16_float,
                        svt_aom_ifft1d_16_float,
                        simple_transpose,
                        1);
}

void svt_aom_ifft32x32_float_c(const float *input, float *temp, float *output) {
    svt_aom_ifft_2d_gen(input,
                        temp,
                        output,
                        32,
                        svt_aom_fft1d_32_float,
                        svt_aom_fft1d_32_float,
                        svt_aom_ifft1d_32_float,
                        simple_transpose,
                        1);
}
