interpolated_gain_curve_unittest.cc (7431B)
1 /* 2 * Copyright (c) 2018 The WebRTC project authors. All Rights Reserved. 3 * 4 * Use of this source code is governed by a BSD-style license 5 * that can be found in the LICENSE file in the root of the source 6 * tree. An additional intellectual property rights grant can be found 7 * in the file PATENTS. All contributing project authors may 8 * be found in the AUTHORS file in the root of the source tree. 9 */ 10 11 #include "modules/audio_processing/agc2/interpolated_gain_curve.h" 12 13 #include <array> 14 #include <cmath> 15 #include <cstddef> 16 #include <string> 17 #include <type_traits> 18 #include <vector> 19 20 #include "common_audio/include/audio_util.h" 21 #include "modules/audio_processing/agc2/agc2_common.h" 22 #include "modules/audio_processing/agc2/agc2_testing_common.h" 23 #include "modules/audio_processing/agc2/compute_interpolated_gain_curve.h" 24 #include "modules/audio_processing/agc2/limiter_db_gain_curve.h" 25 #include "modules/audio_processing/logging/apm_data_dumper.h" 26 #include "test/gtest.h" 27 28 namespace webrtc { 29 namespace { 30 31 constexpr double kLevelEpsilon = 1e-2 * kMaxAbsFloatS16Value; 32 constexpr float kInterpolatedGainCurveTolerance = 1.f / 32768.f; 33 ApmDataDumper apm_data_dumper(0); 34 static_assert(std::is_trivially_destructible<LimiterDbGainCurve>::value, ""); 35 const LimiterDbGainCurve limiter; 36 37 } // namespace 38 39 TEST(GainController2InterpolatedGainCurve, CreateUse) { 40 InterpolatedGainCurve igc(&apm_data_dumper, ""); 41 42 const auto levels = test::LinSpace( 43 kLevelEpsilon, DbfsToFloatS16(limiter.max_input_level_db() + 1), 500); 44 for (const auto level : levels) { 45 EXPECT_GE(igc.LookUpGainToApply(level), 0.0f); 46 } 47 } 48 49 TEST(GainController2InterpolatedGainCurve, CheckValidOutput) { 50 InterpolatedGainCurve igc(&apm_data_dumper, ""); 51 52 const auto levels = test::LinSpace( 53 kLevelEpsilon, limiter.max_input_level_linear() * 2.0, 500); 54 for (const auto level : levels) { 55 SCOPED_TRACE(std::to_string(level)); 56 const float gain = igc.LookUpGainToApply(level); 57 EXPECT_LE(0.0f, gain); 58 EXPECT_LE(gain, 1.0f); 59 } 60 } 61 62 TEST(GainController2InterpolatedGainCurve, CheckMonotonicity) { 63 InterpolatedGainCurve igc(&apm_data_dumper, ""); 64 65 const auto levels = test::LinSpace( 66 kLevelEpsilon, limiter.max_input_level_linear() + kLevelEpsilon + 0.5, 67 500); 68 float prev_gain = igc.LookUpGainToApply(0.0f); 69 for (const auto level : levels) { 70 const float gain = igc.LookUpGainToApply(level); 71 EXPECT_GE(prev_gain, gain); 72 prev_gain = gain; 73 } 74 } 75 76 TEST(GainController2InterpolatedGainCurve, CheckApproximation) { 77 InterpolatedGainCurve igc(&apm_data_dumper, ""); 78 79 const auto levels = test::LinSpace( 80 kLevelEpsilon, limiter.max_input_level_linear() - kLevelEpsilon, 500); 81 for (const auto level : levels) { 82 SCOPED_TRACE(std::to_string(level)); 83 EXPECT_LT( 84 std::fabs(limiter.GetGainLinear(level) - igc.LookUpGainToApply(level)), 85 kInterpolatedGainCurveTolerance); 86 } 87 } 88 89 TEST(GainController2InterpolatedGainCurve, CheckRegionBoundaries) { 90 InterpolatedGainCurve igc(&apm_data_dumper, ""); 91 92 const std::vector<double> levels{ 93 {kLevelEpsilon, limiter.knee_start_linear() + kLevelEpsilon, 94 limiter.limiter_start_linear() + kLevelEpsilon, 95 limiter.max_input_level_linear() + kLevelEpsilon}}; 96 for (const auto level : levels) { 97 igc.LookUpGainToApply(level); 98 } 99 100 const auto stats = igc.get_stats(); 101 EXPECT_EQ(1ul, stats.look_ups_identity_region); 102 EXPECT_EQ(1ul, stats.look_ups_knee_region); 103 EXPECT_EQ(1ul, stats.look_ups_limiter_region); 104 EXPECT_EQ(1ul, stats.look_ups_saturation_region); 105 } 106 107 TEST(GainController2InterpolatedGainCurve, CheckIdentityRegion) { 108 constexpr size_t kNumSteps = 10; 109 InterpolatedGainCurve igc(&apm_data_dumper, ""); 110 111 const auto levels = 112 test::LinSpace(kLevelEpsilon, limiter.knee_start_linear(), kNumSteps); 113 for (const auto level : levels) { 114 SCOPED_TRACE(std::to_string(level)); 115 EXPECT_EQ(1.0f, igc.LookUpGainToApply(level)); 116 } 117 118 const auto stats = igc.get_stats(); 119 EXPECT_EQ(kNumSteps - 1, stats.look_ups_identity_region); 120 EXPECT_EQ(1ul, stats.look_ups_knee_region); 121 EXPECT_EQ(0ul, stats.look_ups_limiter_region); 122 EXPECT_EQ(0ul, stats.look_ups_saturation_region); 123 } 124 125 TEST(GainController2InterpolatedGainCurve, CheckNoOverApproximationKnee) { 126 constexpr size_t kNumSteps = 10; 127 InterpolatedGainCurve igc(&apm_data_dumper, ""); 128 129 const auto levels = 130 test::LinSpace(limiter.knee_start_linear() + kLevelEpsilon, 131 limiter.limiter_start_linear(), kNumSteps); 132 for (const auto level : levels) { 133 SCOPED_TRACE(std::to_string(level)); 134 // Small tolerance added (needed because comparing a float with a double). 135 EXPECT_LE(igc.LookUpGainToApply(level), 136 limiter.GetGainLinear(level) + 1e-7); 137 } 138 139 const auto stats = igc.get_stats(); 140 EXPECT_EQ(0ul, stats.look_ups_identity_region); 141 EXPECT_EQ(kNumSteps - 1, stats.look_ups_knee_region); 142 EXPECT_EQ(1ul, stats.look_ups_limiter_region); 143 EXPECT_EQ(0ul, stats.look_ups_saturation_region); 144 } 145 146 TEST(GainController2InterpolatedGainCurve, CheckNoOverApproximationBeyondKnee) { 147 constexpr size_t kNumSteps = 10; 148 InterpolatedGainCurve igc(&apm_data_dumper, ""); 149 150 const auto levels = test::LinSpace( 151 limiter.limiter_start_linear() + kLevelEpsilon, 152 limiter.max_input_level_linear() - kLevelEpsilon, kNumSteps); 153 for (const auto level : levels) { 154 SCOPED_TRACE(std::to_string(level)); 155 // Small tolerance added (needed because comparing a float with a double). 156 EXPECT_LE(igc.LookUpGainToApply(level), 157 limiter.GetGainLinear(level) + 1e-7); 158 } 159 160 const auto stats = igc.get_stats(); 161 EXPECT_EQ(0ul, stats.look_ups_identity_region); 162 EXPECT_EQ(0ul, stats.look_ups_knee_region); 163 EXPECT_EQ(kNumSteps, stats.look_ups_limiter_region); 164 EXPECT_EQ(0ul, stats.look_ups_saturation_region); 165 } 166 167 TEST(GainController2InterpolatedGainCurve, 168 CheckNoOverApproximationWithSaturation) { 169 constexpr size_t kNumSteps = 3; 170 InterpolatedGainCurve igc(&apm_data_dumper, ""); 171 172 const auto levels = test::LinSpace( 173 limiter.max_input_level_linear() + kLevelEpsilon, 174 limiter.max_input_level_linear() + kLevelEpsilon + 0.5, kNumSteps); 175 for (const auto level : levels) { 176 SCOPED_TRACE(std::to_string(level)); 177 EXPECT_LE(igc.LookUpGainToApply(level), limiter.GetGainLinear(level)); 178 } 179 180 const auto stats = igc.get_stats(); 181 EXPECT_EQ(0ul, stats.look_ups_identity_region); 182 EXPECT_EQ(0ul, stats.look_ups_knee_region); 183 EXPECT_EQ(0ul, stats.look_ups_limiter_region); 184 EXPECT_EQ(kNumSteps, stats.look_ups_saturation_region); 185 } 186 187 TEST(GainController2InterpolatedGainCurve, CheckApproximationParams) { 188 test::InterpolatedParameters parameters = 189 test::ComputeInterpolatedGainCurveApproximationParams(); 190 191 InterpolatedGainCurve igc(&apm_data_dumper, ""); 192 193 for (size_t i = 0; i < kInterpolatedGainCurveTotalPoints; ++i) { 194 // The tolerance levels are chosen to account for deviations due 195 // to computing with single precision floating point numbers. 196 EXPECT_NEAR(igc.approximation_params_x_[i], 197 parameters.computed_approximation_params_x[i], 0.9f); 198 EXPECT_NEAR(igc.approximation_params_m_[i], 199 parameters.computed_approximation_params_m[i], 0.00001f); 200 EXPECT_NEAR(igc.approximation_params_q_[i], 201 parameters.computed_approximation_params_q[i], 0.001f); 202 } 203 } 204 205 } // namespace webrtc