| /* |
| * Copyright (c) 2015 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 <cmath> |
| #include <complex> |
| #include <vector> |
| |
| #include "modules/audio_processing/intelligibility/intelligibility_utils.h" |
| #include "rtc_base/arraysize.h" |
| #include "test/gtest.h" |
| |
| namespace webrtc { |
| |
| namespace intelligibility { |
| |
| std::vector<std::vector<std::complex<float>>> GenerateTestData(size_t freqs, |
| size_t samples) { |
| std::vector<std::vector<std::complex<float>>> data(samples); |
| for (size_t i = 0; i < samples; ++i) { |
| for (size_t j = 0; j < freqs; ++j) { |
| const float val = 0.99f / ((i + 1) * (j + 1)); |
| data[i].push_back(std::complex<float>(val, val)); |
| } |
| } |
| return data; |
| } |
| |
| // Tests PowerEstimator, for all power step types. |
| TEST(IntelligibilityUtilsTest, TestPowerEstimator) { |
| const size_t kFreqs = 10; |
| const size_t kSamples = 100; |
| const float kDecay = 0.5f; |
| const std::vector<std::vector<std::complex<float>>> test_data( |
| GenerateTestData(kFreqs, kSamples)); |
| PowerEstimator<std::complex<float>> power_estimator(kFreqs, kDecay); |
| EXPECT_EQ(0, power_estimator.power()[0]); |
| |
| // Makes sure Step is doing something. |
| power_estimator.Step(test_data[0].data()); |
| for (size_t i = 1; i < kSamples; ++i) { |
| power_estimator.Step(test_data[i].data()); |
| for (size_t j = 0; j < kFreqs; ++j) { |
| EXPECT_GE(power_estimator.power()[j], 0.f); |
| EXPECT_LE(power_estimator.power()[j], 1.f); |
| } |
| } |
| } |
| |
| // Tests gain applier. |
| TEST(IntelligibilityUtilsTest, TestGainApplier) { |
| const size_t kFreqs = 10; |
| const size_t kSamples = 100; |
| const float kChangeLimit = 0.1f; |
| GainApplier gain_applier(kFreqs, kChangeLimit); |
| const std::vector<std::vector<std::complex<float>>> in_data( |
| GenerateTestData(kFreqs, kSamples)); |
| std::vector<std::vector<std::complex<float>>> out_data( |
| GenerateTestData(kFreqs, kSamples)); |
| for (size_t i = 0; i < kSamples; ++i) { |
| gain_applier.Apply(in_data[i].data(), out_data[i].data()); |
| for (size_t j = 0; j < kFreqs; ++j) { |
| EXPECT_GT(out_data[i][j].real(), 0.f); |
| EXPECT_LT(out_data[i][j].real(), 1.f); |
| EXPECT_GT(out_data[i][j].imag(), 0.f); |
| EXPECT_LT(out_data[i][j].imag(), 1.f); |
| } |
| } |
| } |
| |
| } // namespace intelligibility |
| |
| } // namespace webrtc |