| /* |
| * 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 <array> |
| #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/interpolated_gain_curve.h" |
| #include "modules/audio_processing/agc2/limiter.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); |
| const Limiter limiter; |
| |
| } // namespace |
| |
| TEST(AutomaticGainController2InterpolatedGainCurve, 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(AutomaticGainController2InterpolatedGainCurve, 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(AutomaticGainController2InterpolatedGainCurve, 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(AutomaticGainController2InterpolatedGainCurve, 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(AutomaticGainController2InterpolatedGainCurve, 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(AutomaticGainController2InterpolatedGainCurve, 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(AutomaticGainController2InterpolatedGainCurve, |
| 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(AutomaticGainController2InterpolatedGainCurve, |
| 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(AutomaticGainController2InterpolatedGainCurve, |
| 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(AutomaticGainController2InterpolatedGainCurve, 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 |