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/*
* 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 "webrtc/base/arraysize.h"
#include "webrtc/modules/audio_processing/intelligibility/intelligibility_utils.h"
#include "webrtc/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
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