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/*
* Copyright (c) 2013 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.
*/
// Modified from the Chromium original:
// src/media/base/sinc_resampler_unittest.cc
// MSVC++ requires this to be set before any other includes to get M_PI.
#define _USE_MATH_DEFINES
#include <math.h>
#include <algorithm>
#include <memory>
#include <tuple>
#include "common_audio/resampler/sinc_resampler.h"
#include "common_audio/resampler/sinusoidal_linear_chirp_source.h"
#include "rtc_base/stringize_macros.h"
#include "rtc_base/timeutils.h"
#include "system_wrappers/include/cpu_features_wrapper.h"
#include "test/gmock.h"
#include "test/gtest.h"
using testing::_;
namespace webrtc {
static const double kSampleRateRatio = 192000.0 / 44100.0;
static const double kKernelInterpolationFactor = 0.5;
// Helper class to ensure ChunkedResample() functions properly.
class MockSource : public SincResamplerCallback {
public:
MOCK_METHOD2(Run, void(size_t frames, float* destination));
};
ACTION(ClearBuffer) {
memset(arg1, 0, arg0 * sizeof(float));
}
ACTION(FillBuffer) {
// Value chosen arbitrarily such that SincResampler resamples it to something
// easily representable on all platforms; e.g., using kSampleRateRatio this
// becomes 1.81219.
memset(arg1, 64, arg0 * sizeof(float));
}
// Test requesting multiples of ChunkSize() frames results in the proper number
// of callbacks.
TEST(SincResamplerTest, ChunkedResample) {
MockSource mock_source;
// Choose a high ratio of input to output samples which will result in quick
// exhaustion of SincResampler's internal buffers.
SincResampler resampler(kSampleRateRatio, SincResampler::kDefaultRequestSize,
&mock_source);
static const int kChunks = 2;
size_t max_chunk_size = resampler.ChunkSize() * kChunks;
std::unique_ptr<float[]> resampled_destination(new float[max_chunk_size]);
// Verify requesting ChunkSize() frames causes a single callback.
EXPECT_CALL(mock_source, Run(_, _)).Times(1).WillOnce(ClearBuffer());
resampler.Resample(resampler.ChunkSize(), resampled_destination.get());
// Verify requesting kChunks * ChunkSize() frames causes kChunks callbacks.
testing::Mock::VerifyAndClear(&mock_source);
EXPECT_CALL(mock_source, Run(_, _))
.Times(kChunks)
.WillRepeatedly(ClearBuffer());
resampler.Resample(max_chunk_size, resampled_destination.get());
}
// Test flush resets the internal state properly.
TEST(SincResamplerTest, Flush) {
MockSource mock_source;
SincResampler resampler(kSampleRateRatio, SincResampler::kDefaultRequestSize,
&mock_source);
std::unique_ptr<float[]> resampled_destination(
new float[resampler.ChunkSize()]);
// Fill the resampler with junk data.
EXPECT_CALL(mock_source, Run(_, _)).Times(1).WillOnce(FillBuffer());
resampler.Resample(resampler.ChunkSize() / 2, resampled_destination.get());
ASSERT_NE(resampled_destination[0], 0);
// Flush and request more data, which should all be zeros now.
resampler.Flush();
testing::Mock::VerifyAndClear(&mock_source);
EXPECT_CALL(mock_source, Run(_, _)).Times(1).WillOnce(ClearBuffer());
resampler.Resample(resampler.ChunkSize() / 2, resampled_destination.get());
for (size_t i = 0; i < resampler.ChunkSize() / 2; ++i)
ASSERT_FLOAT_EQ(resampled_destination[i], 0);
}
// Test flush resets the internal state properly.
TEST(SincResamplerTest, DISABLED_SetRatioBench) {
MockSource mock_source;
SincResampler resampler(kSampleRateRatio, SincResampler::kDefaultRequestSize,
&mock_source);
int64_t start = rtc::TimeNanos();
for (int i = 1; i < 10000; ++i)
resampler.SetRatio(1.0 / i);
double total_time_c_us =
(rtc::TimeNanos() - start) / rtc::kNumNanosecsPerMicrosec;
printf("SetRatio() took %.2fms.\n", total_time_c_us / 1000);
}
// Define platform independent function name for Convolve* tests.
#if defined(WEBRTC_ARCH_X86_FAMILY)
#define CONVOLVE_FUNC Convolve_SSE
#elif defined(WEBRTC_ARCH_ARM_V7)
#define CONVOLVE_FUNC Convolve_NEON
#endif
// Ensure various optimized Convolve() methods return the same value. Only run
// this test if other optimized methods exist, otherwise the default Convolve()
// will be tested by the parameterized SincResampler tests below.
#if defined(CONVOLVE_FUNC)
TEST(SincResamplerTest, Convolve) {
#if defined(WEBRTC_ARCH_X86_FAMILY)
ASSERT_TRUE(WebRtc_GetCPUInfo(kSSE2));
#elif defined(WEBRTC_ARCH_ARM_V7)
ASSERT_TRUE(WebRtc_GetCPUFeaturesARM() & kCPUFeatureNEON);
#endif
// Initialize a dummy resampler.
MockSource mock_source;
SincResampler resampler(kSampleRateRatio, SincResampler::kDefaultRequestSize,
&mock_source);
// The optimized Convolve methods are slightly more precise than Convolve_C(),
// so comparison must be done using an epsilon.
static const double kEpsilon = 0.00000005;
// Use a kernel from SincResampler as input and kernel data, this has the
// benefit of already being properly sized and aligned for Convolve_SSE().
double result = resampler.Convolve_C(
resampler.kernel_storage_.get(), resampler.kernel_storage_.get(),
resampler.kernel_storage_.get(), kKernelInterpolationFactor);
double result2 = resampler.CONVOLVE_FUNC(
resampler.kernel_storage_.get(), resampler.kernel_storage_.get(),
resampler.kernel_storage_.get(), kKernelInterpolationFactor);
EXPECT_NEAR(result2, result, kEpsilon);
// Test Convolve() w/ unaligned input pointer.
result = resampler.Convolve_C(
resampler.kernel_storage_.get() + 1, resampler.kernel_storage_.get(),
resampler.kernel_storage_.get(), kKernelInterpolationFactor);
result2 = resampler.CONVOLVE_FUNC(
resampler.kernel_storage_.get() + 1, resampler.kernel_storage_.get(),
resampler.kernel_storage_.get(), kKernelInterpolationFactor);
EXPECT_NEAR(result2, result, kEpsilon);
}
#endif
// Benchmark for the various Convolve() methods. Make sure to build with
// branding=Chrome so that RTC_DCHECKs are compiled out when benchmarking.
// Original benchmarks were run with --convolve-iterations=50000000.
TEST(SincResamplerTest, ConvolveBenchmark) {
// Initialize a dummy resampler.
MockSource mock_source;
SincResampler resampler(kSampleRateRatio, SincResampler::kDefaultRequestSize,
&mock_source);
// Retrieve benchmark iterations from command line.
// TODO(ajm): Reintroduce this as a command line option.
const int kConvolveIterations = 1000000;
printf("Benchmarking %d iterations:\n", kConvolveIterations);
// Benchmark Convolve_C().
int64_t start = rtc::TimeNanos();
for (int i = 0; i < kConvolveIterations; ++i) {
resampler.Convolve_C(
resampler.kernel_storage_.get(), resampler.kernel_storage_.get(),
resampler.kernel_storage_.get(), kKernelInterpolationFactor);
}
double total_time_c_us =
(rtc::TimeNanos() - start) / rtc::kNumNanosecsPerMicrosec;
printf("Convolve_C took %.2fms.\n", total_time_c_us / 1000);
#if defined(CONVOLVE_FUNC)
#if defined(WEBRTC_ARCH_X86_FAMILY)
ASSERT_TRUE(WebRtc_GetCPUInfo(kSSE2));
#elif defined(WEBRTC_ARCH_ARM_V7)
ASSERT_TRUE(WebRtc_GetCPUFeaturesARM() & kCPUFeatureNEON);
#endif
// Benchmark with unaligned input pointer.
start = rtc::TimeNanos();
for (int j = 0; j < kConvolveIterations; ++j) {
resampler.CONVOLVE_FUNC(
resampler.kernel_storage_.get() + 1, resampler.kernel_storage_.get(),
resampler.kernel_storage_.get(), kKernelInterpolationFactor);
}
double total_time_optimized_unaligned_us =
(rtc::TimeNanos() - start) / rtc::kNumNanosecsPerMicrosec;
printf(STRINGIZE(CONVOLVE_FUNC) "(unaligned) took %.2fms; which is %.2fx "
"faster than Convolve_C.\n", total_time_optimized_unaligned_us / 1000,
total_time_c_us / total_time_optimized_unaligned_us);
// Benchmark with aligned input pointer.
start = rtc::TimeNanos();
for (int j = 0; j < kConvolveIterations; ++j) {
resampler.CONVOLVE_FUNC(
resampler.kernel_storage_.get(), resampler.kernel_storage_.get(),
resampler.kernel_storage_.get(), kKernelInterpolationFactor);
}
double total_time_optimized_aligned_us =
(rtc::TimeNanos() - start) / rtc::kNumNanosecsPerMicrosec;
printf(STRINGIZE(CONVOLVE_FUNC) " (aligned) took %.2fms; which is %.2fx "
"faster than Convolve_C and %.2fx faster than "
STRINGIZE(CONVOLVE_FUNC) " (unaligned).\n",
total_time_optimized_aligned_us / 1000,
total_time_c_us / total_time_optimized_aligned_us,
total_time_optimized_unaligned_us / total_time_optimized_aligned_us);
#endif
}
#undef CONVOLVE_FUNC
typedef std::tuple<int, int, double, double> SincResamplerTestData;
class SincResamplerTest : public testing::TestWithParam<SincResamplerTestData> {
public:
SincResamplerTest()
: input_rate_(std::get<0>(GetParam())),
output_rate_(std::get<1>(GetParam())),
rms_error_(std::get<2>(GetParam())),
low_freq_error_(std::get<3>(GetParam())) {}
virtual ~SincResamplerTest() {}
protected:
int input_rate_;
int output_rate_;
double rms_error_;
double low_freq_error_;
};
// Tests resampling using a given input and output sample rate.
TEST_P(SincResamplerTest, Resample) {
// Make comparisons using one second of data.
static const double kTestDurationSecs = 1;
const size_t input_samples =
static_cast<size_t>(kTestDurationSecs * input_rate_);
const size_t output_samples =
static_cast<size_t>(kTestDurationSecs * output_rate_);
// Nyquist frequency for the input sampling rate.
const double input_nyquist_freq = 0.5 * input_rate_;
// Source for data to be resampled.
SinusoidalLinearChirpSource resampler_source(input_rate_, input_samples,
input_nyquist_freq, 0);
const double io_ratio = input_rate_ / static_cast<double>(output_rate_);
SincResampler resampler(io_ratio, SincResampler::kDefaultRequestSize,
&resampler_source);
// Force an update to the sample rate ratio to ensure dyanmic sample rate
// changes are working correctly.
std::unique_ptr<float[]> kernel(new float[SincResampler::kKernelStorageSize]);
memcpy(kernel.get(), resampler.get_kernel_for_testing(),
SincResampler::kKernelStorageSize);
resampler.SetRatio(M_PI);
ASSERT_NE(0, memcmp(kernel.get(), resampler.get_kernel_for_testing(),
SincResampler::kKernelStorageSize));
resampler.SetRatio(io_ratio);
ASSERT_EQ(0, memcmp(kernel.get(), resampler.get_kernel_for_testing(),
SincResampler::kKernelStorageSize));
// TODO(dalecurtis): If we switch to AVX/SSE optimization, we'll need to
// allocate these on 32-byte boundaries and ensure they're sized % 32 bytes.
std::unique_ptr<float[]> resampled_destination(new float[output_samples]);
std::unique_ptr<float[]> pure_destination(new float[output_samples]);
// Generate resampled signal.
resampler.Resample(output_samples, resampled_destination.get());
// Generate pure signal.
SinusoidalLinearChirpSource pure_source(output_rate_, output_samples,
input_nyquist_freq, 0);
pure_source.Run(output_samples, pure_destination.get());
// Range of the Nyquist frequency (0.5 * min(input rate, output_rate)) which
// we refer to as low and high.
static const double kLowFrequencyNyquistRange = 0.7;
static const double kHighFrequencyNyquistRange = 0.9;
// Calculate Root-Mean-Square-Error and maximum error for the resampling.
double sum_of_squares = 0;
double low_freq_max_error = 0;
double high_freq_max_error = 0;
int minimum_rate = std::min(input_rate_, output_rate_);
double low_frequency_range = kLowFrequencyNyquistRange * 0.5 * minimum_rate;
double high_frequency_range = kHighFrequencyNyquistRange * 0.5 * minimum_rate;
for (size_t i = 0; i < output_samples; ++i) {
double error = fabs(resampled_destination[i] - pure_destination[i]);
if (pure_source.Frequency(i) < low_frequency_range) {
if (error > low_freq_max_error)
low_freq_max_error = error;
} else if (pure_source.Frequency(i) < high_frequency_range) {
if (error > high_freq_max_error)
high_freq_max_error = error;
}
// TODO(dalecurtis): Sanity check frequencies > kHighFrequencyNyquistRange.
sum_of_squares += error * error;
}
double rms_error = sqrt(sum_of_squares / output_samples);
// Convert each error to dbFS.
#define DBFS(x) 20 * log10(x)
rms_error = DBFS(rms_error);
low_freq_max_error = DBFS(low_freq_max_error);
high_freq_max_error = DBFS(high_freq_max_error);
EXPECT_LE(rms_error, rms_error_);
EXPECT_LE(low_freq_max_error, low_freq_error_);
// All conversions currently have a high frequency error around -6 dbFS.
static const double kHighFrequencyMaxError = -6.02;
EXPECT_LE(high_freq_max_error, kHighFrequencyMaxError);
}
// Almost all conversions have an RMS error of around -14 dbFS.
static const double kResamplingRMSError = -14.58;
// Thresholds chosen arbitrarily based on what each resampling reported during
// testing. All thresholds are in dbFS, http://en.wikipedia.org/wiki/DBFS.
INSTANTIATE_TEST_CASE_P(
SincResamplerTest,
SincResamplerTest,
testing::Values(
// To 44.1kHz
std::make_tuple(8000, 44100, kResamplingRMSError, -62.73),
std::make_tuple(11025, 44100, kResamplingRMSError, -72.19),
std::make_tuple(16000, 44100, kResamplingRMSError, -62.54),
std::make_tuple(22050, 44100, kResamplingRMSError, -73.53),
std::make_tuple(32000, 44100, kResamplingRMSError, -63.32),
std::make_tuple(44100, 44100, kResamplingRMSError, -73.53),
std::make_tuple(48000, 44100, -15.01, -64.04),
std::make_tuple(96000, 44100, -18.49, -25.51),
std::make_tuple(192000, 44100, -20.50, -13.31),
// To 48kHz
std::make_tuple(8000, 48000, kResamplingRMSError, -63.43),
std::make_tuple(11025, 48000, kResamplingRMSError, -62.61),
std::make_tuple(16000, 48000, kResamplingRMSError, -63.96),
std::make_tuple(22050, 48000, kResamplingRMSError, -62.42),
std::make_tuple(32000, 48000, kResamplingRMSError, -64.04),
std::make_tuple(44100, 48000, kResamplingRMSError, -62.63),
std::make_tuple(48000, 48000, kResamplingRMSError, -73.52),
std::make_tuple(96000, 48000, -18.40, -28.44),
std::make_tuple(192000, 48000, -20.43, -14.11),
// To 96kHz
std::make_tuple(8000, 96000, kResamplingRMSError, -63.19),
std::make_tuple(11025, 96000, kResamplingRMSError, -62.61),
std::make_tuple(16000, 96000, kResamplingRMSError, -63.39),
std::make_tuple(22050, 96000, kResamplingRMSError, -62.42),
std::make_tuple(32000, 96000, kResamplingRMSError, -63.95),
std::make_tuple(44100, 96000, kResamplingRMSError, -62.63),
std::make_tuple(48000, 96000, kResamplingRMSError, -73.52),
std::make_tuple(96000, 96000, kResamplingRMSError, -73.52),
std::make_tuple(192000, 96000, kResamplingRMSError, -28.41),
// To 192kHz
std::make_tuple(8000, 192000, kResamplingRMSError, -63.10),
std::make_tuple(11025, 192000, kResamplingRMSError, -62.61),
std::make_tuple(16000, 192000, kResamplingRMSError, -63.14),
std::make_tuple(22050, 192000, kResamplingRMSError, -62.42),
std::make_tuple(32000, 192000, kResamplingRMSError, -63.38),
std::make_tuple(44100, 192000, kResamplingRMSError, -62.63),
std::make_tuple(48000, 192000, kResamplingRMSError, -73.44),
std::make_tuple(96000, 192000, kResamplingRMSError, -73.52),
std::make_tuple(192000, 192000, kResamplingRMSError, -73.52)));
} // namespace webrtc