Remove many unused files from //skia/ext

skia/ext/recursive_gaussian_convolution.cc

-// Copyright (c) 2013 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-#include <algorithm>
-#include <cmath>
-#include <vector>
-
-#include "base/logging.h"
-#include "skia/ext/recursive_gaussian_convolution.h"
-
-namespace skia {
-
-namespace {
-
-// Takes the value produced by accumulating element-wise product of image with
-// a kernel and brings it back into range.
-// All of the filter scaling factors are in fixed point with kShiftBits bits of
-// fractional part.
-template<bool take_absolute>
-inline unsigned char FloatTo8(float f) {
-  int a = static_cast<int>(f + 0.5f);
-  if (take_absolute)
-    a = std::abs(a);
-  else if (a < 0)
-    return 0;
-  if (a < 256)
-    return a;
-  return 255;
-}
-
-template<RecursiveFilter::Order order>
-inline float ForwardFilter(float in_n_1,
-                           float in_n,
-                           float in_n1,
-                           const std::vector<float>& w,
-                           int n,
-                           const float* b) {
-  switch (order) {
-    case RecursiveFilter::FUNCTION:
-      return b[0] * in_n + b[1] * w[n-1] + b[2] * w[n-2] + b[3] * w[n-3];
-    case RecursiveFilter::FIRST_DERIVATIVE:
-      return b[0] * 0.5f * (in_n1 - in_n_1) +
-          b[1] * w[n-1] + b[2] * w[n-2] + b[3] * w[n-3];
-    case RecursiveFilter::SECOND_DERIVATIVE:
-      return b[0] * (in_n - in_n_1)  +
-          b[1] * w[n-1] + b[2] * w[n-2] + b[3] * w[n-3];
-  }
-
-  NOTREACHED();
-  return 0.0f;
-}
-
-template<RecursiveFilter::Order order>
-inline float BackwardFilter(const std::vector<float>& out,
-                            int n,
-                            float w_n,
-                            float w_n1,
-                            const float* b) {
-  switch (order) {
-    case RecursiveFilter::FUNCTION:
-    case RecursiveFilter::FIRST_DERIVATIVE:
-      return b[0] * w_n +
-          b[1] * out[n + 1] + b[2] * out[n + 2] + b[3] * out[n + 3];
-    case RecursiveFilter::SECOND_DERIVATIVE:
-      return b[0] * (w_n1 - w_n)  +
-          b[1] * out[n + 1] + b[2] * out[n + 2] + b[3] * out[n + 3];
-  }
-  NOTREACHED();
-  return 0.0f;
-}
-
-template<RecursiveFilter::Order order, bool absolute_values>
-unsigned char SingleChannelRecursiveFilter(
-    const unsigned char* const source_data,
-    int source_pixel_stride,
-    int source_row_stride,
-    int row_width,
-    int row_count,
-    unsigned char* const output,
-    int output_pixel_stride,
-    int output_row_stride,
-    const float* b) {
-  const int intermediate_buffer_size = row_width + 6;
-  std::vector<float> w(intermediate_buffer_size);
-  const unsigned char* in = source_data;
-  unsigned char* out = output;
-  unsigned char max_output = 0;
-  for (int r = 0; r < row_count;
-       ++r, in += source_row_stride, out += output_row_stride) {
-    // Compute forward filter.
-    // First initialize start of the w (temporary) vector.
-    if (order == RecursiveFilter::FUNCTION)
-      w[0] = w[1] = w[2] = in[0];
-    else
-      w[0] = w[1] = w[2] = 0.0f;
-    // Note that special-casing of w[3] is needed because of derivatives.
-    w[3] = ForwardFilter<order>(
-        in[0], in[0], in[source_pixel_stride], w, 3, b);
-    int n = 4;
-    int c = 1;
-    int byte_index = source_pixel_stride;
-    for (; c < row_width - 1; ++c, ++n, byte_index += source_pixel_stride) {
-      w[n] = ForwardFilter<order>(in[byte_index - source_pixel_stride],
-                                  in[byte_index],
-                                  in[byte_index + source_pixel_stride],
-                                  w, n, b);
-    }
-
-    // The value of w corresponding to the last image pixel needs to be computed
-    // separately, again because of derivatives.
-    w[n] = ForwardFilter<order>(in[byte_index - source_pixel_stride],
-                                in[byte_index],
-                                in[byte_index],
-                                w, n, b);
-    // Now three trailing bytes set to the same value as current w[n].
-    w[n + 1] = w[n];
-    w[n + 2] = w[n];
-    w[n + 3] = w[n];
-
-    // Now apply the back filter.
-    float w_n1 = w[n + 1];
-    int output_index = (row_width - 1) * output_pixel_stride;
-    for (; c >= 0; output_index -= output_pixel_stride, --c, --n) {
-      float w_n = BackwardFilter<order>(w, n, w[n], w_n1, b);
-      w_n1 = w[n];
-      w[n] = w_n;
-      out[output_index] = FloatTo8<absolute_values>(w_n);
-      max_output = std::max(max_output, out[output_index]);
-    }
-  }
-  return max_output;
-}
-
-unsigned char SingleChannelRecursiveFilter(
-    const unsigned char* const source_data,
-    int source_pixel_stride,
-    int source_row_stride,
-    int row_width,
-    int row_count,
-    unsigned char* const output,
-    int output_pixel_stride,
-    int output_row_stride,
-    const float* b,
-    RecursiveFilter::Order order,
-    bool absolute_values) {
-  if (absolute_values) {
-   switch (order) {
-     case RecursiveFilter::FUNCTION:
-       return SingleChannelRecursiveFilter<RecursiveFilter::FUNCTION, true>(
-           source_data, source_pixel_stride, source_row_stride,
-           row_width, row_count,
-           output, output_pixel_stride, output_row_stride, b);
-     case RecursiveFilter::FIRST_DERIVATIVE:
-       return SingleChannelRecursiveFilter<
-         RecursiveFilter::FIRST_DERIVATIVE, true>(
-             source_data, source_pixel_stride, source_row_stride,
-             row_width, row_count,
-             output, output_pixel_stride, output_row_stride, b);
-     case RecursiveFilter::SECOND_DERIVATIVE:
-       return SingleChannelRecursiveFilter<
-         RecursiveFilter::SECOND_DERIVATIVE, true>(
-             source_data, source_pixel_stride, source_row_stride,
-             row_width, row_count,
-             output, output_pixel_stride, output_row_stride, b);
-   }
-  } else {
-    switch (order) {
-     case RecursiveFilter::FUNCTION:
-       return SingleChannelRecursiveFilter<RecursiveFilter::FUNCTION, false>(
-           source_data, source_pixel_stride, source_row_stride,
-           row_width, row_count,
-           output, output_pixel_stride, output_row_stride, b);
-     case RecursiveFilter::FIRST_DERIVATIVE:
-       return SingleChannelRecursiveFilter<
-         RecursiveFilter::FIRST_DERIVATIVE, false>(
-             source_data, source_pixel_stride, source_row_stride,
-             row_width, row_count,
-             output, output_pixel_stride, output_row_stride, b);
-     case RecursiveFilter::SECOND_DERIVATIVE:
-       return SingleChannelRecursiveFilter<
-         RecursiveFilter::SECOND_DERIVATIVE, false>(
-             source_data, source_pixel_stride, source_row_stride,
-             row_width, row_count,
-             output, output_pixel_stride, output_row_stride, b);
-   }
-  }
-
-  NOTREACHED();
-  return 0;
-}
-
-}
-
-float RecursiveFilter::qFromSigma(float sigma) {
-  DCHECK_GE(sigma, 0.5f);
-  if (sigma <= 2.5f)
-    return 3.97156f - 4.14554f * std::sqrt(1.0f - 0.26891f * sigma);
-  return 0.98711f * sigma - 0.96330f;
-}
-
-void RecursiveFilter::computeCoefficients(float q, float b[4]) {
-  b[0] = 1.57825f + 2.44413f * q + 1.4281f * q * q + 0.422205f * q * q * q;
-  b[1] = 2.4413f * q + 2.85619f * q * q + 1.26661f * q * q * q;
-  b[2] = - 1.4281f * q * q - 1.26661f * q * q * q;
-  b[3] = 0.422205f * q * q * q;
-
-  // The above is exactly like in the paper. To cut down on computations,
-  // we can fix up these numbers a bit now.
-  float b_norm = 1.0f - (b[1] + b[2] + b[3]) / b[0];
-  b[1] /= b[0];
-  b[2] /= b[0];
-  b[3] /= b[0];
-  b[0] = b_norm;
-}
-
-RecursiveFilter::RecursiveFilter(float sigma, Order order)
-    : order_(order), q_(qFromSigma(sigma)) {
-  computeCoefficients(q_, b_);
-}
-
-unsigned char SingleChannelRecursiveGaussianX(const unsigned char* source_data,
-                                              int source_byte_row_stride,
-                                              int input_channel_index,
-                                              int input_channel_count,
-                                              const RecursiveFilter& filter,
-                                              const SkISize& image_size,
-                                              unsigned char* output,
-                                              int output_byte_row_stride,
-                                              int output_channel_index,
-                                              int output_channel_count,
-                                              bool absolute_values) {
-  return SingleChannelRecursiveFilter(source_data + input_channel_index,
-                                      input_channel_count,
-                                      source_byte_row_stride,
-                                      image_size.width(),
-                                      image_size.height(),
-                                      output + output_channel_index,
-                                      output_channel_count,
-                                      output_byte_row_stride,
-                                      filter.b(),
-                                      filter.order(),
-                                      absolute_values);
-}
-
-unsigned char  SingleChannelRecursiveGaussianY(const unsigned char* source_data,
-                                               int source_byte_row_stride,
-                                               int input_channel_index,
-                                               int input_channel_count,
-                                               const RecursiveFilter& filter,
-                                               const SkISize& image_size,
-                                               unsigned char* output,
-                                               int output_byte_row_stride,
-                                               int output_channel_index,
-                                               int output_channel_count,
-                                               bool absolute_values) {
-  return SingleChannelRecursiveFilter(source_data + input_channel_index,
-                                      source_byte_row_stride,
-                                      input_channel_count,
-                                      image_size.height(),
-                                      image_size.width(),
-                                      output + output_channel_index,
-                                      output_byte_row_stride,
-                                      output_channel_count,
-                                      filter.b(),
-                                      filter.order(),
-                                      absolute_values);
-}
-
-}  // namespace skia