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/*
* Copyright (c) 2014 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.
*/
#define _USE_MATH_DEFINES
#include "webrtc/modules/audio_processing/beamformer/covariance_matrix_generator.h"
#include <cmath>
#include "testing/gtest/include/gtest/gtest.h"
#include "webrtc/modules/audio_processing/beamformer/matrix_test_helpers.h"
namespace webrtc {
using std::complex;
TEST(CovarianceMatrixGeneratorTest, TestUniformCovarianceMatrix2Mics) {
const float kWaveNumber = 0.5775f;
const int kNumberMics = 2;
const float kMicSpacing = 0.05f;
const float kTolerance = 0.0001f;
std::vector<Point> geometry;
float first_mic = (kNumberMics - 1) * kMicSpacing / 2.f;
for (int i = 0; i < kNumberMics; ++i) {
geometry.push_back(Point(i * kMicSpacing - first_mic, 0.f, 0.f));
}
ComplexMatrix<float> actual_covariance_matrix(kNumberMics, kNumberMics);
CovarianceMatrixGenerator::UniformCovarianceMatrix(kWaveNumber,
geometry,
&actual_covariance_matrix);
complex<float>* const* actual_els = actual_covariance_matrix.elements();
EXPECT_NEAR(actual_els[0][0].real(), 1.f, kTolerance);
EXPECT_NEAR(actual_els[0][1].real(), 0.9998f, kTolerance);
EXPECT_NEAR(actual_els[1][0].real(), 0.9998f, kTolerance);
EXPECT_NEAR(actual_els[1][1].real(), 1.f, kTolerance);
EXPECT_NEAR(actual_els[0][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[0][1].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][1].imag(), 0.f, kTolerance);
}
TEST(CovarianceMatrixGeneratorTest, TestUniformCovarianceMatrix3Mics) {
const float kWaveNumber = 10.3861f;
const int kNumberMics = 3;
const float kMicSpacing = 0.04f;
const float kTolerance = 0.0001f;
std::vector<Point> geometry;
float first_mic = (kNumberMics - 1) * kMicSpacing / 2.f;
for (int i = 0; i < kNumberMics; ++i) {
geometry.push_back(Point(i * kMicSpacing - first_mic, 0.f, 0.f));
}
ComplexMatrix<float> actual_covariance_matrix(kNumberMics, kNumberMics);
CovarianceMatrixGenerator::UniformCovarianceMatrix(kWaveNumber,
geometry,
&actual_covariance_matrix);
complex<float>* const* actual_els = actual_covariance_matrix.elements();
EXPECT_NEAR(actual_els[0][0].real(), 1.f, kTolerance);
EXPECT_NEAR(actual_els[0][1].real(), 0.9573f, kTolerance);
EXPECT_NEAR(actual_els[0][2].real(), 0.8347f, kTolerance);
EXPECT_NEAR(actual_els[1][0].real(), 0.9573f, kTolerance);
EXPECT_NEAR(actual_els[1][1].real(), 1.f, kTolerance);
EXPECT_NEAR(actual_els[1][2].real(), 0.9573f, kTolerance);
EXPECT_NEAR(actual_els[2][0].real(), 0.8347f, kTolerance);
EXPECT_NEAR(actual_els[2][1].real(), 0.9573f, kTolerance);
EXPECT_NEAR(actual_els[2][2].real(), 1.f, kTolerance);
EXPECT_NEAR(actual_els[0][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[0][1].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[0][2].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][1].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][2].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[2][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[2][1].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[2][2].imag(), 0.f, kTolerance);
}
TEST(CovarianceMatrixGeneratorTest, TestUniformCovarianceMatrix3DArray) {
const float kWaveNumber = 1.2345f;
const int kNumberMics = 4;
const float kTolerance = 0.0001f;
std::vector<Point> geometry;
geometry.push_back(Point(-0.025f, -0.05f, -0.075f));
geometry.push_back(Point(0.075f, -0.05f, -0.075f));
geometry.push_back(Point(-0.025f, 0.15f, -0.075f));
geometry.push_back(Point(-0.025f, -0.05f, 0.225f));
ComplexMatrix<float> actual_covariance_matrix(kNumberMics, kNumberMics);
CovarianceMatrixGenerator::UniformCovarianceMatrix(kWaveNumber,
geometry,
&actual_covariance_matrix);
complex<float>* const* actual_els = actual_covariance_matrix.elements();
EXPECT_NEAR(actual_els[0][0].real(), 1.f, kTolerance);
EXPECT_NEAR(actual_els[0][1].real(), 0.9962f, kTolerance);
EXPECT_NEAR(actual_els[0][2].real(), 0.9848f, kTolerance);
EXPECT_NEAR(actual_els[0][3].real(), 0.9660f, kTolerance);
EXPECT_NEAR(actual_els[1][0].real(), 0.9962f, kTolerance);
EXPECT_NEAR(actual_els[1][1].real(), 1.f, kTolerance);
EXPECT_NEAR(actual_els[1][2].real(), 0.9810f, kTolerance);
EXPECT_NEAR(actual_els[1][3].real(), 0.9623f, kTolerance);
EXPECT_NEAR(actual_els[2][0].real(), 0.9848f, kTolerance);
EXPECT_NEAR(actual_els[2][1].real(), 0.9810f, kTolerance);
EXPECT_NEAR(actual_els[2][2].real(), 1.f, kTolerance);
EXPECT_NEAR(actual_els[2][3].real(), 0.9511f, kTolerance);
EXPECT_NEAR(actual_els[3][0].real(), 0.9660f, kTolerance);
EXPECT_NEAR(actual_els[3][1].real(), 0.9623f, kTolerance);
EXPECT_NEAR(actual_els[3][2].real(), 0.9511f, kTolerance);
EXPECT_NEAR(actual_els[3][3].real(), 1.f, kTolerance);
EXPECT_NEAR(actual_els[0][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[0][1].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[0][2].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[0][3].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][1].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][2].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][3].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[2][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[2][1].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[2][2].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[2][3].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[3][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[3][1].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[3][2].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[3][3].imag(), 0.f, kTolerance);
}
TEST(CovarianceMatrixGeneratorTest, TestAngledCovarianceMatrix2Mics) {
const float kSpeedOfSound = 340;
const float kAngle = static_cast<float>(M_PI) / 4.f;
const float kFrequencyBin = 6;
const float kFftSize = 512;
const int kNumberFrequencyBins = 257;
const int kSampleRate = 16000;
const int kNumberMics = 2;
const float kMicSpacing = 0.04f;
const float kTolerance = 0.0001f;
std::vector<Point> geometry;
float first_mic = (kNumberMics - 1) * kMicSpacing / 2.f;
for (int i = 0; i < kNumberMics; ++i) {
geometry.push_back(Point(i * kMicSpacing - first_mic, 0.f, 0.f));
}
ComplexMatrix<float> actual_covariance_matrix(kNumberMics, kNumberMics);
CovarianceMatrixGenerator::AngledCovarianceMatrix(kSpeedOfSound,
kAngle,
kFrequencyBin,
kFftSize,
kNumberFrequencyBins,
kSampleRate,
geometry,
&actual_covariance_matrix);
complex<float>* const* actual_els = actual_covariance_matrix.elements();
EXPECT_NEAR(actual_els[0][0].real(), 0.5f, kTolerance);
EXPECT_NEAR(actual_els[0][1].real(), 0.4976f, kTolerance);
EXPECT_NEAR(actual_els[1][0].real(), 0.4976f, kTolerance);
EXPECT_NEAR(actual_els[1][1].real(), 0.5f, kTolerance);
EXPECT_NEAR(actual_els[0][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[0][1].imag(), 0.0489f, kTolerance);
EXPECT_NEAR(actual_els[1][0].imag(), -0.0489f, kTolerance);
EXPECT_NEAR(actual_els[1][1].imag(), 0.f, kTolerance);
}
TEST(CovarianceMatrixGeneratorTest, TestAngledCovarianceMatrix3Mics) {
const float kSpeedOfSound = 340;
const float kAngle = static_cast<float>(M_PI) / 4.f;
const float kFrequencyBin = 9;
const float kFftSize = 512;
const int kNumberFrequencyBins = 257;
const int kSampleRate = 42000;
const int kNumberMics = 3;
const float kMicSpacing = 0.05f;
const float kTolerance = 0.0001f;
std::vector<Point> geometry;
float first_mic = (kNumberMics - 1) * kMicSpacing / 2.f;
for (int i = 0; i < kNumberMics; ++i) {
geometry.push_back(Point(i * kMicSpacing - first_mic, 0.f, 0.f));
}
ComplexMatrix<float> actual_covariance_matrix(kNumberMics, kNumberMics);
CovarianceMatrixGenerator::AngledCovarianceMatrix(kSpeedOfSound,
kAngle,
kFrequencyBin,
kFftSize,
kNumberFrequencyBins,
kSampleRate,
geometry,
&actual_covariance_matrix);
complex<float>* const* actual_els = actual_covariance_matrix.elements();
EXPECT_NEAR(actual_els[0][0].real(), 0.3333f, kTolerance);
EXPECT_NEAR(actual_els[0][1].real(), 0.2953f, kTolerance);
EXPECT_NEAR(actual_els[0][2].real(), 0.1899f, kTolerance);
EXPECT_NEAR(actual_els[1][0].real(), 0.2953f, kTolerance);
EXPECT_NEAR(actual_els[1][1].real(), 0.3333f, kTolerance);
EXPECT_NEAR(actual_els[1][2].real(), 0.2953f, kTolerance);
EXPECT_NEAR(actual_els[2][0].real(), 0.1899f, kTolerance);
EXPECT_NEAR(actual_els[2][1].real(), 0.2953f, kTolerance);
EXPECT_NEAR(actual_els[2][2].real(), 0.3333f, kTolerance);
EXPECT_NEAR(actual_els[0][0].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[0][1].imag(), 0.1546f, kTolerance);
EXPECT_NEAR(actual_els[0][2].imag(), 0.274f, kTolerance);
EXPECT_NEAR(actual_els[1][0].imag(), -0.1546f, kTolerance);
EXPECT_NEAR(actual_els[1][1].imag(), 0.f, kTolerance);
EXPECT_NEAR(actual_els[1][2].imag(), 0.1546f, kTolerance);
EXPECT_NEAR(actual_els[2][0].imag(), -0.274f, kTolerance);
EXPECT_NEAR(actual_els[2][1].imag(), -0.1546f, kTolerance);
EXPECT_NEAR(actual_els[2][2].imag(), 0.f, kTolerance);
}
// PhaseAlignmentMasks is tested by AngledCovarianceMatrix and by
// InitBeamformerWeights in BeamformerUnittest.
} // namespace webrtc