| // Copyright (c) 2012 The Chromium Authors. All rights reserved. |
| // Use of this source code is governed by a BSD-style license that can be |
| // found in the LICENSE file. |
| |
| // MSVC++ requires this to be set before any other includes to get M_PI. |
| #define _USE_MATH_DEFINES |
| |
| #include <cmath> |
| |
| #include "base/bind.h" |
| #include "base/bind_helpers.h" |
| #include "base/command_line.h" |
| #include "base/logging.h" |
| #include "base/string_number_conversions.h" |
| #include "base/stringize_macros.h" |
| #include "base/time.h" |
| #include "build/build_config.h" |
| #include "media/base/sinc_resampler.h" |
| #include "testing/gmock/include/gmock/gmock.h" |
| #include "testing/gtest/include/gtest/gtest.h" |
| |
| using testing::_; |
| |
| namespace media { |
| |
| static const double kSampleRateRatio = 192000.0 / 44100.0; |
| static const double kKernelInterpolationFactor = 0.5; |
| |
| // Command line switch for runtime adjustment of ConvolveBenchmark iterations. |
| static const char kConvolveIterations[] = "convolve-iterations"; |
| |
| // Helper class to ensure ChunkedResample() functions properly. |
| class MockSource { |
| public: |
| MOCK_METHOD2(ProvideInput, void(float* destination, int frames)); |
| }; |
| |
| ACTION(ClearBuffer) { |
| memset(arg0, 0, arg1 * 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(arg0, 64, arg1 * 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, |
| base::Bind(&MockSource::ProvideInput, base::Unretained(&mock_source))); |
| |
| static const int kChunks = 2; |
| int max_chunk_size = resampler.ChunkSize() * kChunks; |
| scoped_array<float> resampled_destination(new float[max_chunk_size]); |
| |
| // Verify requesting ChunkSize() frames causes a single callback. |
| EXPECT_CALL(mock_source, ProvideInput(_, _)) |
| .Times(1).WillOnce(ClearBuffer()); |
| resampler.Resample(resampled_destination.get(), resampler.ChunkSize()); |
| |
| // Verify requesting kChunks * ChunkSize() frames causes kChunks callbacks. |
| testing::Mock::VerifyAndClear(&mock_source); |
| EXPECT_CALL(mock_source, ProvideInput(_, _)) |
| .Times(kChunks).WillRepeatedly(ClearBuffer()); |
| resampler.Resample(resampled_destination.get(), max_chunk_size); |
| } |
| |
| // Test flush resets the internal state properly. |
| TEST(SincResamplerTest, Flush) { |
| MockSource mock_source; |
| SincResampler resampler( |
| kSampleRateRatio, |
| base::Bind(&MockSource::ProvideInput, base::Unretained(&mock_source))); |
| scoped_array<float> resampled_destination(new float[resampler.ChunkSize()]); |
| |
| // Fill the resampler with junk data. |
| EXPECT_CALL(mock_source, ProvideInput(_, _)) |
| .Times(1).WillOnce(FillBuffer()); |
| resampler.Resample(resampled_destination.get(), resampler.ChunkSize() / 2); |
| 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, ProvideInput(_, _)) |
| .Times(1).WillOnce(ClearBuffer()); |
| resampler.Resample(resampled_destination.get(), resampler.ChunkSize() / 2); |
| for (int i = 0; i < resampler.ChunkSize() / 2; ++i) |
| ASSERT_FLOAT_EQ(resampled_destination[i], 0); |
| } |
| |
| // Define platform independent function name for Convolve* tests. |
| #if defined(ARCH_CPU_X86_FAMILY) && defined(__SSE__) |
| #define CONVOLVE_FUNC Convolve_SSE |
| #elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON) |
| #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) { |
| // Initialize a dummy resampler. |
| MockSource mock_source; |
| SincResampler resampler( |
| kSampleRateRatio, |
| base::Bind(&MockSource::ProvideInput, base::Unretained(&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 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, |
| base::Bind(&MockSource::ProvideInput, base::Unretained(&mock_source))); |
| |
| // Retrieve benchmark iterations from command line. |
| int convolve_iterations = 10; |
| std::string iterations(CommandLine::ForCurrentProcess()->GetSwitchValueASCII( |
| kConvolveIterations)); |
| if (!iterations.empty()) |
| base::StringToInt(iterations, &convolve_iterations); |
| |
| printf("Benchmarking %d iterations:\n", convolve_iterations); |
| |
| // Benchmark Convolve_C(). |
| base::TimeTicks start = base::TimeTicks::HighResNow(); |
| for (int i = 0; i < convolve_iterations; ++i) { |
| resampler.Convolve_C( |
| resampler.kernel_storage_.get(), resampler.kernel_storage_.get(), |
| resampler.kernel_storage_.get(), kKernelInterpolationFactor); |
| } |
| double total_time_c_ms = |
| (base::TimeTicks::HighResNow() - start).InMillisecondsF(); |
| printf("Convolve_C took %.2fms.\n", total_time_c_ms); |
| |
| #if defined(CONVOLVE_FUNC) |
| // Benchmark with unaligned input pointer. |
| start = base::TimeTicks::HighResNow(); |
| for (int j = 0; j < convolve_iterations; ++j) { |
| resampler.CONVOLVE_FUNC( |
| resampler.kernel_storage_.get() + 1, resampler.kernel_storage_.get(), |
| resampler.kernel_storage_.get(), kKernelInterpolationFactor); |
| } |
| double total_time_optimized_unaligned_ms = |
| (base::TimeTicks::HighResNow() - start).InMillisecondsF(); |
| printf(STRINGIZE(CONVOLVE_FUNC) "(unaligned) took %.2fms; which is %.2fx " |
| "faster than Convolve_C.\n", total_time_optimized_unaligned_ms, |
| total_time_c_ms / total_time_optimized_unaligned_ms); |
| |
| // Benchmark with aligned input pointer. |
| start = base::TimeTicks::HighResNow(); |
| for (int j = 0; j < convolve_iterations; ++j) { |
| resampler.CONVOLVE_FUNC( |
| resampler.kernel_storage_.get(), resampler.kernel_storage_.get(), |
| resampler.kernel_storage_.get(), kKernelInterpolationFactor); |
| } |
| double total_time_optimized_aligned_ms = |
| (base::TimeTicks::HighResNow() - start).InMillisecondsF(); |
| 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_ms, |
| total_time_c_ms / total_time_optimized_aligned_ms, |
| total_time_optimized_unaligned_ms / total_time_optimized_aligned_ms); |
| #endif |
| } |
| |
| #undef CONVOLVE_FUNC |
| |
| // Fake audio source for testing the resampler. Generates a sinusoidal linear |
| // chirp (http://en.wikipedia.org/wiki/Chirp) which can be tuned to stress the |
| // resampler for the specific sample rate conversion being used. |
| class SinusoidalLinearChirpSource { |
| public: |
| SinusoidalLinearChirpSource(int sample_rate, int samples, |
| double max_frequency) |
| : sample_rate_(sample_rate), |
| total_samples_(samples), |
| max_frequency_(max_frequency), |
| current_index_(0) { |
| // Chirp rate. |
| double duration = static_cast<double>(total_samples_) / sample_rate_; |
| k_ = (max_frequency_ - kMinFrequency) / duration; |
| } |
| |
| virtual ~SinusoidalLinearChirpSource() {} |
| |
| void ProvideInput(float* destination, int frames) { |
| for (int i = 0; i < frames; ++i, ++current_index_) { |
| // Filter out frequencies higher than Nyquist. |
| if (Frequency(current_index_) > 0.5 * sample_rate_) { |
| destination[i] = 0; |
| } else { |
| // Calculate time in seconds. |
| double t = static_cast<double>(current_index_) / sample_rate_; |
| |
| // Sinusoidal linear chirp. |
| destination[i] = sin(2 * M_PI * (kMinFrequency * t + (k_ / 2) * t * t)); |
| } |
| } |
| } |
| |
| double Frequency(int position) { |
| return kMinFrequency + position * (max_frequency_ - kMinFrequency) |
| / total_samples_; |
| } |
| |
| private: |
| enum { |
| kMinFrequency = 5 |
| }; |
| |
| double sample_rate_; |
| int total_samples_; |
| double max_frequency_; |
| double k_; |
| int current_index_; |
| |
| DISALLOW_COPY_AND_ASSIGN(SinusoidalLinearChirpSource); |
| }; |
| |
| typedef std::tr1::tuple<int, int, double, double> SincResamplerTestData; |
| class SincResamplerTest |
| : public testing::TestWithParam<SincResamplerTestData> { |
| public: |
| SincResamplerTest() |
| : input_rate_(std::tr1::get<0>(GetParam())), |
| output_rate_(std::tr1::get<1>(GetParam())), |
| rms_error_(std::tr1::get<2>(GetParam())), |
| low_freq_error_(std::tr1::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; |
| int input_samples = kTestDurationSecs * input_rate_; |
| int output_samples = kTestDurationSecs * output_rate_; |
| |
| // Nyquist frequency for the input sampling rate. |
| double input_nyquist_freq = 0.5 * input_rate_; |
| |
| // Source for data to be resampled. |
| SinusoidalLinearChirpSource resampler_source( |
| input_rate_, input_samples, input_nyquist_freq); |
| |
| SincResampler resampler( |
| input_rate_ / static_cast<double>(output_rate_), |
| base::Bind(&SinusoidalLinearChirpSource::ProvideInput, |
| base::Unretained(&resampler_source))); |
| |
| // 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. |
| scoped_array<float> resampled_destination(new float[output_samples]); |
| scoped_array<float> pure_destination(new float[output_samples]); |
| |
| // Generate resampled signal. |
| resampler.Resample(resampled_destination.get(), output_samples); |
| |
| // Generate pure signal. |
| SinusoidalLinearChirpSource pure_source( |
| output_rate_, output_samples, input_nyquist_freq); |
| pure_source.ProvideInput(pure_destination.get(), output_samples); |
| |
| // 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 (int 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::tr1::make_tuple(8000, 44100, kResamplingRMSError, -62.73), |
| std::tr1::make_tuple(11025, 44100, kResamplingRMSError, -72.19), |
| std::tr1::make_tuple(16000, 44100, kResamplingRMSError, -62.54), |
| std::tr1::make_tuple(22050, 44100, kResamplingRMSError, -73.53), |
| std::tr1::make_tuple(32000, 44100, kResamplingRMSError, -63.32), |
| std::tr1::make_tuple(44100, 44100, kResamplingRMSError, -73.53), |
| std::tr1::make_tuple(48000, 44100, -15.01, -64.04), |
| std::tr1::make_tuple(96000, 44100, -18.49, -25.51), |
| std::tr1::make_tuple(192000, 44100, -20.50, -13.31), |
| |
| // To 48kHz |
| std::tr1::make_tuple(8000, 48000, kResamplingRMSError, -63.43), |
| std::tr1::make_tuple(11025, 48000, kResamplingRMSError, -62.61), |
| std::tr1::make_tuple(16000, 48000, kResamplingRMSError, -63.96), |
| std::tr1::make_tuple(22050, 48000, kResamplingRMSError, -62.42), |
| std::tr1::make_tuple(32000, 48000, kResamplingRMSError, -64.04), |
| std::tr1::make_tuple(44100, 48000, kResamplingRMSError, -62.63), |
| std::tr1::make_tuple(48000, 48000, kResamplingRMSError, -73.52), |
| std::tr1::make_tuple(96000, 48000, -18.40, -28.44), |
| std::tr1::make_tuple(192000, 48000, -20.43, -14.11), |
| |
| // To 96kHz |
| std::tr1::make_tuple(8000, 96000, kResamplingRMSError, -63.19), |
| std::tr1::make_tuple(11025, 96000, kResamplingRMSError, -62.61), |
| std::tr1::make_tuple(16000, 96000, kResamplingRMSError, -63.39), |
| std::tr1::make_tuple(22050, 96000, kResamplingRMSError, -62.42), |
| std::tr1::make_tuple(32000, 96000, kResamplingRMSError, -63.95), |
| std::tr1::make_tuple(44100, 96000, kResamplingRMSError, -62.63), |
| std::tr1::make_tuple(48000, 96000, kResamplingRMSError, -73.52), |
| std::tr1::make_tuple(96000, 96000, kResamplingRMSError, -73.52), |
| std::tr1::make_tuple(192000, 96000, kResamplingRMSError, -28.41), |
| |
| // To 192kHz |
| std::tr1::make_tuple(8000, 192000, kResamplingRMSError, -63.10), |
| std::tr1::make_tuple(11025, 192000, kResamplingRMSError, -62.61), |
| std::tr1::make_tuple(16000, 192000, kResamplingRMSError, -63.14), |
| std::tr1::make_tuple(22050, 192000, kResamplingRMSError, -62.42), |
| std::tr1::make_tuple(32000, 192000, kResamplingRMSError, -63.38), |
| std::tr1::make_tuple(44100, 192000, kResamplingRMSError, -62.63), |
| std::tr1::make_tuple(48000, 192000, kResamplingRMSError, -73.44), |
| std::tr1::make_tuple(96000, 192000, kResamplingRMSError, -73.52), |
| std::tr1::make_tuple(192000, 192000, kResamplingRMSError, -73.52))); |
| |
| } // namespace media |