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/*
* Copyright (c) 2013 The WebRTC project authors. All Rights Reserved.
*
* Use of this source code is governed by a BSD-style license
* that can be found in the LICENSE file in the root of the source
* tree. An additional intellectual property rights grant can be found
* in the file PATENTS. All contributing project authors may
* be found in the AUTHORS file in the root of the source tree.
*/
#include "webrtc/modules/audio_processing/transient/moving_moments.h"
#include <memory>
#include "testing/gtest/include/gtest/gtest.h"
namespace webrtc {
static const float kTolerance = 0.0001f;
class MovingMomentsTest : public ::testing::Test {
protected:
static const size_t kMovingMomentsBufferLength = 5;
static const size_t kMaxOutputLength = 20; // Valid for this tests only.
virtual void SetUp();
// Calls CalculateMoments and verifies that it produces the expected
// outputs.
void CalculateMomentsAndVerify(const float* input, size_t input_length,
const float* expected_mean,
const float* expected_mean_squares);
std::unique_ptr<MovingMoments> moving_moments_;
float output_mean_[kMaxOutputLength];
float output_mean_squares_[kMaxOutputLength];
};
const size_t MovingMomentsTest::kMaxOutputLength;
void MovingMomentsTest::SetUp() {
moving_moments_.reset(new MovingMoments(kMovingMomentsBufferLength));
}
void MovingMomentsTest::CalculateMomentsAndVerify(
const float* input, size_t input_length,
const float* expected_mean,
const float* expected_mean_squares) {
ASSERT_LE(input_length, kMaxOutputLength);
moving_moments_->CalculateMoments(input,
input_length,
output_mean_,
output_mean_squares_);
for (size_t i = 1; i < input_length; ++i) {
EXPECT_NEAR(expected_mean[i], output_mean_[i], kTolerance);
EXPECT_NEAR(expected_mean_squares[i], output_mean_squares_[i], kTolerance);
}
}
TEST_F(MovingMomentsTest, CorrectMomentsOfAnAllZerosBuffer) {
const float kInput[] = {0.f, 0.f, 0.f, 0.f, 0.f};
const size_t kInputLength = sizeof(kInput) / sizeof(kInput[0]);
const float expected_mean[kInputLength] = {0.f, 0.f, 0.f, 0.f, 0.f};
const float expected_mean_squares[kInputLength] = {0.f, 0.f, 0.f, 0.f, 0.f};
CalculateMomentsAndVerify(kInput, kInputLength, expected_mean,
expected_mean_squares);
}
TEST_F(MovingMomentsTest, CorrectMomentsOfAConstantBuffer) {
const float kInput[] = {5.f, 5.f, 5.f, 5.f, 5.f, 5.f, 5.f, 5.f, 5.f, 5.f};
const size_t kInputLength = sizeof(kInput) / sizeof(kInput[0]);
const float expected_mean[kInputLength] =
{1.f, 2.f, 3.f, 4.f, 5.f, 5.f, 5.f, 5.f, 5.f, 5.f};
const float expected_mean_squares[kInputLength] =
{5.f, 10.f, 15.f, 20.f, 25.f, 25.f, 25.f, 25.f, 25.f, 25.f};
CalculateMomentsAndVerify(kInput, kInputLength, expected_mean,
expected_mean_squares);
}
TEST_F(MovingMomentsTest, CorrectMomentsOfAnIncreasingBuffer) {
const float kInput[] = {1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f};
const size_t kInputLength = sizeof(kInput) / sizeof(kInput[0]);
const float expected_mean[kInputLength] =
{0.2f, 0.6f, 1.2f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f};
const float expected_mean_squares[kInputLength] =
{0.2f, 1.f, 2.8f, 6.f, 11.f, 18.f, 27.f, 38.f, 51.f};
CalculateMomentsAndVerify(kInput, kInputLength, expected_mean,
expected_mean_squares);
}
TEST_F(MovingMomentsTest, CorrectMomentsOfADecreasingBuffer) {
const float kInput[] =
{-1.f, -2.f, -3.f, -4.f, -5.f, -6.f, -7.f, -8.f, -9.f};
const size_t kInputLength = sizeof(kInput) / sizeof(kInput[0]);
const float expected_mean[kInputLength] =
{-0.2f, -0.6f, -1.2f, -2.f, -3.f, -4.f, -5.f, -6.f, -7.f};
const float expected_mean_squares[kInputLength] =
{0.2f, 1.f, 2.8f, 6.f, 11.f, 18.f, 27.f, 38.f, 51.f};
CalculateMomentsAndVerify(kInput, kInputLength, expected_mean,
expected_mean_squares);
}
TEST_F(MovingMomentsTest, CorrectMomentsOfAZeroMeanSequence) {
const size_t kMovingMomentsBufferLength = 4;
moving_moments_.reset(new MovingMoments(kMovingMomentsBufferLength));
const float kInput[] =
{1.f, -1.f, 1.f, -1.f, 1.f, -1.f, 1.f, -1.f, 1.f, -1.f};
const size_t kInputLength = sizeof(kInput) / sizeof(kInput[0]);
const float expected_mean[kInputLength] =
{0.25f, 0.f, 0.25f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f};
const float expected_mean_squares[kInputLength] =
{0.25f, 0.5f, 0.75f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f};
CalculateMomentsAndVerify(kInput, kInputLength, expected_mean,
expected_mean_squares);
}
TEST_F(MovingMomentsTest, CorrectMomentsOfAnArbitraryBuffer) {
const float kInput[] =
{0.2f, 0.3f, 0.5f, 0.7f, 0.11f, 0.13f, 0.17f, 0.19f, 0.23f};
const size_t kInputLength = sizeof(kInput) / sizeof(kInput[0]);
const float expected_mean[kInputLength] =
{0.04f, 0.1f, 0.2f, 0.34f, 0.362f, 0.348f, 0.322f, 0.26f, 0.166f};
const float expected_mean_squares[kInputLength] =
{0.008f, 0.026f, 0.076f, 0.174f, 0.1764f, 0.1718f, 0.1596f, 0.1168f,
0.0294f};
CalculateMomentsAndVerify(kInput, kInputLength, expected_mean,
expected_mean_squares);
}
TEST_F(MovingMomentsTest, MutipleCalculateMomentsCalls) {
const float kInputFirstCall[] =
{0.2f, 0.3f, 0.5f, 0.7f, 0.11f, 0.13f, 0.17f, 0.19f, 0.23f};
const size_t kInputFirstCallLength = sizeof(kInputFirstCall) /
sizeof(kInputFirstCall[0]);
const float kInputSecondCall[] = {0.29f, 0.31f};
const size_t kInputSecondCallLength = sizeof(kInputSecondCall) /
sizeof(kInputSecondCall[0]);
const float kInputThirdCall[] = {0.37f, 0.41f, 0.43f, 0.47f};
const size_t kInputThirdCallLength = sizeof(kInputThirdCall) /
sizeof(kInputThirdCall[0]);
const float expected_mean_first_call[kInputFirstCallLength] =
{0.04f, 0.1f, 0.2f, 0.34f, 0.362f, 0.348f, 0.322f, 0.26f, 0.166f};
const float expected_mean_squares_first_call[kInputFirstCallLength] =
{0.008f, 0.026f, 0.076f, 0.174f, 0.1764f, 0.1718f, 0.1596f, 0.1168f,
0.0294f};
const float expected_mean_second_call[kInputSecondCallLength] =
{0.202f, 0.238f};
const float expected_mean_squares_second_call[kInputSecondCallLength] =
{0.0438f, 0.0596f};
const float expected_mean_third_call[kInputThirdCallLength] =
{0.278f, 0.322f, 0.362f, 0.398f};
const float expected_mean_squares_third_call[kInputThirdCallLength] =
{0.0812f, 0.1076f, 0.134f, 0.1614f};
CalculateMomentsAndVerify(kInputFirstCall, kInputFirstCallLength,
expected_mean_first_call, expected_mean_squares_first_call);
CalculateMomentsAndVerify(kInputSecondCall, kInputSecondCallLength,
expected_mean_second_call, expected_mean_squares_second_call);
CalculateMomentsAndVerify(kInputThirdCall, kInputThirdCallLength,
expected_mean_third_call, expected_mean_squares_third_call);
}
TEST_F(MovingMomentsTest,
VerifySampleBasedVsBlockBasedCalculation) {
const float kInput[] =
{0.2f, 0.3f, 0.5f, 0.7f, 0.11f, 0.13f, 0.17f, 0.19f, 0.23f};
const size_t kInputLength = sizeof(kInput) / sizeof(kInput[0]);
float output_mean_block_based[kInputLength];
float output_mean_squares_block_based[kInputLength];
float output_mean_sample_based;
float output_mean_squares_sample_based;
moving_moments_->CalculateMoments(
kInput, kInputLength, output_mean_block_based,
output_mean_squares_block_based);
moving_moments_.reset(new MovingMoments(kMovingMomentsBufferLength));
for (size_t i = 0; i < kInputLength; ++i) {
moving_moments_->CalculateMoments(
&kInput[i], 1, &output_mean_sample_based,
&output_mean_squares_sample_based);
EXPECT_FLOAT_EQ(output_mean_block_based[i], output_mean_sample_based);
EXPECT_FLOAT_EQ(output_mean_squares_block_based[i],
output_mean_squares_sample_based);
}
}
} // namespace webrtc