/*

 * 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 www.aomedia.org/license/software. 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 www.aomedia.org/license/patent.

 */

#include <assert.h>

#include <immintrin.h>

#include "aom_dsp/x86/mem_sse2.h"

#include "aom_dsp/x86/synonyms_avx2.h"

#include "config/av1_rtcd.h"

#include "av1/encoder/rdopt.h"

// Process horizontal and vertical correlations in a 4x4 block of pixels.

// We actually use the 4x4 pixels to calculate correlations corresponding to

// the top-left 3x3 pixels, so this function must be called with 1x1 overlap,

// moving the window along/down by 3 pixels at a time.

static inline void horver_correlation_4x4(const int16_t *diff, int stride,

                                          __m256i *xy_sum_32,

                                          __m256i *xz_sum_32, __m256i *x_sum_32,

                                          __m256i *x2_sum_32) {

  // Pixels in this 4x4   [ a b c d ]

  // are referred to as:  [ e f g h ]

  //                      [ i j k l ]

  //                      [ m n o p ]

  const __m256i pixels = _mm256_set_epi64x(

      loadu_int64(&diff[0 * stride]), loadu_int64(&diff[1 * stride]),

      loadu_int64(&diff[2 * stride]), loadu_int64(&diff[3 * stride]));

  // pixels = [d c b a h g f e] [l k j i p o n m] as i16

  const __m256i slli = _mm256_slli_epi64(pixels, 16);

  // slli = [c b a 0 g f e 0] [k j i 0 o n m 0] as i16

  const __m256i madd_xy = _mm256_madd_epi16(pixels, slli);

  // madd_xy = [bc+cd ab fg+gh ef] [jk+kl ij no+op mn] as i32

  *xy_sum_32 = _mm256_add_epi32(*xy_sum_32, madd_xy);

  // Permute control [3 2] [1 0] => [2 1] [0 0], 0b10010000 = 0x90

  const __m256i perm = _mm256_permute4x64_epi64(slli, 0x90);

  // perm = [g f e 0 k j i 0] [o n m 0 o n m 0] as i16

  const __m256i madd_xz = _mm256_madd_epi16(slli, perm);

  // madd_xz = [cg+bf ae gk+fj ei] [ko+jn im oo+nn mm] as i32

  *xz_sum_32 = _mm256_add_epi32(*xz_sum_32, madd_xz);

  // Sum every element in slli (and then also their squares)

  const __m256i madd1_slli = _mm256_madd_epi16(slli, _mm256_set1_epi16(1));

  // madd1_slli = [c+b a g+f e] [k+j i o+n m] as i32

  *x_sum_32 = _mm256_add_epi32(*x_sum_32, madd1_slli);

  const __m256i madd_slli = _mm256_madd_epi16(slli, slli);

  // madd_slli = [cc+bb aa gg+ff ee] [kk+jj ii oo+nn mm] as i32

  *x2_sum_32 = _mm256_add_epi32(*x2_sum_32, madd_slli);

}

void av1_get_horver_correlation_full_avx2(const int16_t *diff, int stride,

                                          int width, int height, float *hcorr,

                                          float *vcorr) {

  // The following notation is used:

  // x - current pixel

  // y - right neighbour pixel

  // z - below neighbour pixel

  // w - down-right neighbour pixel

  int64_t xy_sum = 0, xz_sum = 0;

  int64_t x_sum = 0, x2_sum = 0;

  // Process horizontal and vertical correlations through the body in 4x4

  // blocks.  This excludes the final row and column and possibly one extra

  // column depending how 3 divides into width and height

  int32_t xy_xz_tmp[8] = { 0 }, x_x2_tmp[8] = { 0 };

  __m256i xy_sum_32 = _mm256_setzero_si256();

  __m256i xz_sum_32 = _mm256_setzero_si256();

  __m256i x_sum_32 = _mm256_setzero_si256();

  __m256i x2_sum_32 = _mm256_setzero_si256();

  for (int i = 0; i <= height - 4; i += 3) {

    for (int j = 0; j <= width - 4; j += 3) {

      horver_correlation_4x4(&diff[i * stride + j], stride, &xy_sum_32,

                             &xz_sum_32, &x_sum_32, &x2_sum_32);

    }

    const __m256i hadd_xy_xz = _mm256_hadd_epi32(xy_sum_32, xz_sum_32);

    // hadd_xy_xz = [ae+bf+cg ei+fj+gk ab+bc+cd ef+fg+gh]

    //              [im+jn+ko mm+nn+oo ij+jk+kl mn+no+op] as i32

    yy_storeu_256(xy_xz_tmp, hadd_xy_xz);

    xy_sum += (int64_t)xy_xz_tmp[5] + xy_xz_tmp[4] + xy_xz_tmp[1];

    xz_sum += (int64_t)xy_xz_tmp[7] + xy_xz_tmp[6] + xy_xz_tmp[3];

    const __m256i hadd_x_x2 = _mm256_hadd_epi32(x_sum_32, x2_sum_32);

    // hadd_x_x2 = [aa+bb+cc ee+ff+gg a+b+c e+f+g]

    //             [ii+jj+kk mm+nn+oo i+j+k m+n+o] as i32

    yy_storeu_256(x_x2_tmp, hadd_x_x2);

    x_sum += (int64_t)x_x2_tmp[5] + x_x2_tmp[4] + x_x2_tmp[1];

    x2_sum += (int64_t)x_x2_tmp[7] + x_x2_tmp[6] + x_x2_tmp[3];

    xy_sum_32 = _mm256_setzero_si256();

    xz_sum_32 = _mm256_setzero_si256();

    x_sum_32 = _mm256_setzero_si256();

    x2_sum_32 = _mm256_setzero_si256();

  }

  // x_sum now covers every pixel except the final 1-2 rows and 1-2 cols

  int64_t x_finalrow = 0, x_finalcol = 0, x2_finalrow = 0, x2_finalcol = 0;

  // Do we have 2 rows remaining or just the one?  Note that width and height

  // are powers of 2, so each modulo 3 must be 1 or 2.

  if (height % 3 == 1) {  // Just horiz corrs on the final row

    const int16_t x0 = diff[(height - 1) * stride];

    x_sum += x0;

    x_finalrow += x0;

    x2_sum += x0 * x0;

    x2_finalrow += x0 * x0;

    for (int j = 0; j < width - 1; ++j) {

      const int16_t x = diff[(height - 1) * stride + j];

      const int16_t y = diff[(height - 1) * stride + j + 1];

      xy_sum += x * y;

      x_sum += y;

      x2_sum += y * y;

      x_finalrow += y;

      x2_finalrow += y * y;

    }

  } else {  // Two rows remaining to do

    const int16_t x0 = diff[(height - 2) * stride];

    const int16_t z0 = diff[(height - 1) * stride];

    x_sum += x0 + z0;

    x2_sum += x0 * x0 + z0 * z0;

    x_finalrow += z0;

    x2_finalrow += z0 * z0;

    for (int j = 0; j < width - 1; ++j) {

      const int16_t x = diff[(height - 2) * stride + j];

      const int16_t y = diff[(height - 2) * stride + j + 1];

      const int16_t z = diff[(height - 1) * stride + j];

      const int16_t w = diff[(height - 1) * stride + j + 1];

      // Horizontal and vertical correlations for the penultimate row:

      xy_sum += x * y;

      xz_sum += x * z;

      // Now just horizontal correlations for the final row:

      xy_sum += z * w;

      x_sum += y + w;

      x2_sum += y * y + w * w;

      x_finalrow += w;

      x2_finalrow += w * w;

    }

  }

  // Do we have 2 columns remaining or just the one?

  if (width % 3 == 1) {  // Just vert corrs on the final col

    const int16_t x0 = diff[width - 1];

    x_sum += x0;

    x_finalcol += x0;

    x2_sum += x0 * x0;

    x2_finalcol += x0 * x0;

    for (int i = 0; i < height - 1; ++i) {

      const int16_t x = diff[i * stride + width - 1];

      const int16_t z = diff[(i + 1) * stride + width - 1];

      xz_sum += x * z;

      x_finalcol += z;

      x2_finalcol += z * z;

      // So the bottom-right elements don't get counted twice:

      if (i < height - (height % 3 == 1 ? 2 : 3)) {

        x_sum += z;

        x2_sum += z * z;

      }

    }

  } else {  // Two cols remaining

    const int16_t x0 = diff[width - 2];

    const int16_t y0 = diff[width - 1];

    x_sum += x0 + y0;

    x2_sum += x0 * x0 + y0 * y0;

    x_finalcol += y0;

    x2_finalcol += y0 * y0;

    for (int i = 0; i < height - 1; ++i) {

      const int16_t x = diff[i * stride + width - 2];

      const int16_t y = diff[i * stride + width - 1];

      const int16_t z = diff[(i + 1) * stride + width - 2];

      const int16_t w = diff[(i + 1) * stride + width - 1];

      // Horizontal and vertical correlations for the penultimate col:

      // Skip these on the last iteration of this loop if we also had two

      // rows remaining, otherwise the final horizontal and vertical correlation

      // get erroneously processed twice

      if (i < height - 2 || height % 3 == 1) {

        xy_sum += x * y;

        xz_sum += x * z;

      }

      x_finalcol += w;

      x2_finalcol += w * w;

      // So the bottom-right elements don't get counted twice:

      if (i < height - (height % 3 == 1 ? 2 : 3)) {

        x_sum += z + w;

        x2_sum += z * z + w * w;

      }

      // Now just vertical correlations for the final column:

      xz_sum += y * w;

    }

  }

  // Calculate the simple sums and squared-sums

  int64_t x_firstrow = 0, x_firstcol = 0;

  int64_t x2_firstrow = 0, x2_firstcol = 0;

  for (int j = 0; j < width; ++j) {

    x_firstrow += diff[j];

    x2_firstrow += diff[j] * diff[j];

  }

  for (int i = 0; i < height; ++i) {

    x_firstcol += diff[i * stride];

    x2_firstcol += diff[i * stride] * diff[i * stride];

  }

  int64_t xhor_sum = x_sum - x_finalcol;

  int64_t xver_sum = x_sum - x_finalrow;

  int64_t y_sum = x_sum - x_firstcol;

  int64_t z_sum = x_sum - x_firstrow;

  int64_t x2hor_sum = x2_sum - x2_finalcol;

  int64_t x2ver_sum = x2_sum - x2_finalrow;

  int64_t y2_sum = x2_sum - x2_firstcol;

  int64_t z2_sum = x2_sum - x2_firstrow;

  const float num_hor = (float)(height * (width - 1));

  const float num_ver = (float)((height - 1) * width);

  const float xhor_var_n = x2hor_sum - (xhor_sum * xhor_sum) / num_hor;

  const float xver_var_n = x2ver_sum - (xver_sum * xver_sum) / num_ver;

  const float y_var_n = y2_sum - (y_sum * y_sum) / num_hor;

  const float z_var_n = z2_sum - (z_sum * z_sum) / num_ver;

  const float xy_var_n = xy_sum - (xhor_sum * y_sum) / num_hor;

  const float xz_var_n = xz_sum - (xver_sum * z_sum) / num_ver;

  if (xhor_var_n > 0 && y_var_n > 0) {

    *hcorr = xy_var_n / sqrtf(xhor_var_n * y_var_n);

    *hcorr = *hcorr < 0 ? 0 : *hcorr;

  } else {

    *hcorr = 1.0;

  }

  if (xver_var_n > 0 && z_var_n > 0) {

    *vcorr = xz_var_n / sqrtf(xver_var_n * z_var_n);

    *vcorr = *vcorr < 0 ? 0 : *vcorr;

  } else {

    *vcorr = 1.0;

  }

}