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/*
* Copyright (c) 2018 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 "modules/audio_processing/agc2/interpolated_gain_curve.h"
#include <array>
#include <type_traits>
#include <vector>
#include "api/array_view.h"
#include "common_audio/include/audio_util.h"
#include "modules/audio_processing/agc2/agc2_common.h"
#include "modules/audio_processing/agc2/compute_interpolated_gain_curve.h"
#include "modules/audio_processing/agc2/limiter_db_gain_curve.h"
#include "modules/audio_processing/logging/apm_data_dumper.h"
#include "rtc_base/checks.h"
#include "rtc_base/gunit.h"
namespace webrtc {
namespace {
constexpr double kLevelEpsilon = 1e-2 * kMaxAbsFloatS16Value;
constexpr float kInterpolatedGainCurveTolerance = 1.f / 32768.f;
ApmDataDumper apm_data_dumper(0);
static_assert(std::is_trivially_destructible<LimiterDbGainCurve>::value, "");
const LimiterDbGainCurve limiter;
} // namespace
TEST(GainController2InterpolatedGainCurve, CreateUse) {
InterpolatedGainCurve igc(&apm_data_dumper, "");
const auto levels = test::LinSpace(
kLevelEpsilon, DbfsToFloatS16(limiter.max_input_level_db() + 1), 500);
for (const auto level : levels) {
EXPECT_GE(igc.LookUpGainToApply(level), 0.0f);
}
}
TEST(GainController2InterpolatedGainCurve, CheckValidOutput) {
InterpolatedGainCurve igc(&apm_data_dumper, "");
const auto levels = test::LinSpace(
kLevelEpsilon, limiter.max_input_level_linear() * 2.0, 500);
for (const auto level : levels) {
SCOPED_TRACE(std::to_string(level));
const float gain = igc.LookUpGainToApply(level);
EXPECT_LE(0.0f, gain);
EXPECT_LE(gain, 1.0f);
}
}
TEST(GainController2InterpolatedGainCurve, CheckMonotonicity) {
InterpolatedGainCurve igc(&apm_data_dumper, "");
const auto levels = test::LinSpace(
kLevelEpsilon, limiter.max_input_level_linear() + kLevelEpsilon + 0.5,
500);
float prev_gain = igc.LookUpGainToApply(0.0f);
for (const auto level : levels) {
const float gain = igc.LookUpGainToApply(level);
EXPECT_GE(prev_gain, gain);
prev_gain = gain;
}
}
TEST(GainController2InterpolatedGainCurve, CheckApproximation) {
InterpolatedGainCurve igc(&apm_data_dumper, "");
const auto levels = test::LinSpace(
kLevelEpsilon, limiter.max_input_level_linear() - kLevelEpsilon, 500);
for (const auto level : levels) {
SCOPED_TRACE(std::to_string(level));
EXPECT_LT(
std::fabs(limiter.GetGainLinear(level) - igc.LookUpGainToApply(level)),
kInterpolatedGainCurveTolerance);
}
}
TEST(GainController2InterpolatedGainCurve, CheckRegionBoundaries) {
InterpolatedGainCurve igc(&apm_data_dumper, "");
const std::vector<double> levels{
{kLevelEpsilon, limiter.knee_start_linear() + kLevelEpsilon,
limiter.limiter_start_linear() + kLevelEpsilon,
limiter.max_input_level_linear() + kLevelEpsilon}};
for (const auto level : levels) {
igc.LookUpGainToApply(level);
}
const auto stats = igc.get_stats();
EXPECT_EQ(1ul, stats.look_ups_identity_region);
EXPECT_EQ(1ul, stats.look_ups_knee_region);
EXPECT_EQ(1ul, stats.look_ups_limiter_region);
EXPECT_EQ(1ul, stats.look_ups_saturation_region);
}
TEST(GainController2InterpolatedGainCurve, CheckIdentityRegion) {
constexpr size_t kNumSteps = 10;
InterpolatedGainCurve igc(&apm_data_dumper, "");
const auto levels =
test::LinSpace(kLevelEpsilon, limiter.knee_start_linear(), kNumSteps);
for (const auto level : levels) {
SCOPED_TRACE(std::to_string(level));
EXPECT_EQ(1.0f, igc.LookUpGainToApply(level));
}
const auto stats = igc.get_stats();
EXPECT_EQ(kNumSteps - 1, stats.look_ups_identity_region);
EXPECT_EQ(1ul, stats.look_ups_knee_region);
EXPECT_EQ(0ul, stats.look_ups_limiter_region);
EXPECT_EQ(0ul, stats.look_ups_saturation_region);
}
TEST(GainController2InterpolatedGainCurve, CheckNoOverApproximationKnee) {
constexpr size_t kNumSteps = 10;
InterpolatedGainCurve igc(&apm_data_dumper, "");
const auto levels =
test::LinSpace(limiter.knee_start_linear() + kLevelEpsilon,
limiter.limiter_start_linear(), kNumSteps);
for (const auto level : levels) {
SCOPED_TRACE(std::to_string(level));
// Small tolerance added (needed because comparing a float with a double).
EXPECT_LE(igc.LookUpGainToApply(level),
limiter.GetGainLinear(level) + 1e-7);
}
const auto stats = igc.get_stats();
EXPECT_EQ(0ul, stats.look_ups_identity_region);
EXPECT_EQ(kNumSteps - 1, stats.look_ups_knee_region);
EXPECT_EQ(1ul, stats.look_ups_limiter_region);
EXPECT_EQ(0ul, stats.look_ups_saturation_region);
}
TEST(GainController2InterpolatedGainCurve, CheckNoOverApproximationBeyondKnee) {
constexpr size_t kNumSteps = 10;
InterpolatedGainCurve igc(&apm_data_dumper, "");
const auto levels = test::LinSpace(
limiter.limiter_start_linear() + kLevelEpsilon,
limiter.max_input_level_linear() - kLevelEpsilon, kNumSteps);
for (const auto level : levels) {
SCOPED_TRACE(std::to_string(level));
// Small tolerance added (needed because comparing a float with a double).
EXPECT_LE(igc.LookUpGainToApply(level),
limiter.GetGainLinear(level) + 1e-7);
}
const auto stats = igc.get_stats();
EXPECT_EQ(0ul, stats.look_ups_identity_region);
EXPECT_EQ(0ul, stats.look_ups_knee_region);
EXPECT_EQ(kNumSteps, stats.look_ups_limiter_region);
EXPECT_EQ(0ul, stats.look_ups_saturation_region);
}
TEST(GainController2InterpolatedGainCurve,
CheckNoOverApproximationWithSaturation) {
constexpr size_t kNumSteps = 3;
InterpolatedGainCurve igc(&apm_data_dumper, "");
const auto levels = test::LinSpace(
limiter.max_input_level_linear() + kLevelEpsilon,
limiter.max_input_level_linear() + kLevelEpsilon + 0.5, kNumSteps);
for (const auto level : levels) {
SCOPED_TRACE(std::to_string(level));
EXPECT_LE(igc.LookUpGainToApply(level), limiter.GetGainLinear(level));
}
const auto stats = igc.get_stats();
EXPECT_EQ(0ul, stats.look_ups_identity_region);
EXPECT_EQ(0ul, stats.look_ups_knee_region);
EXPECT_EQ(0ul, stats.look_ups_limiter_region);
EXPECT_EQ(kNumSteps, stats.look_ups_saturation_region);
}
TEST(GainController2InterpolatedGainCurve, CheckApproximationParams) {
test::InterpolatedParameters parameters =
test::ComputeInterpolatedGainCurveApproximationParams();
InterpolatedGainCurve igc(&apm_data_dumper, "");
for (size_t i = 0; i < kInterpolatedGainCurveTotalPoints; ++i) {
// The tolerance levels are chosen to account for deviations due
// to computing with single precision floating point numbers.
EXPECT_NEAR(igc.approximation_params_x_[i],
parameters.computed_approximation_params_x[i], 0.9f);
EXPECT_NEAR(igc.approximation_params_m_[i],
parameters.computed_approximation_params_m[i], 0.00001f);
EXPECT_NEAR(igc.approximation_params_q_[i],
parameters.computed_approximation_params_q[i], 0.001f);
}
}
} // namespace webrtc
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