| Index: webrtc/modules/congestion_controller/median_slope_estimator_unittest.cc
|
| diff --git a/webrtc/modules/congestion_controller/median_slope_estimator_unittest.cc b/webrtc/modules/congestion_controller/median_slope_estimator_unittest.cc
|
| index ef942f143d9451dc68df097b2825dc17e9afb6d6..5be0e9b3cbfba69235c795b43101ff2a9fb02e52 100644
|
| --- a/webrtc/modules/congestion_controller/median_slope_estimator_unittest.cc
|
| +++ b/webrtc/modules/congestion_controller/median_slope_estimator_unittest.cc
|
| @@ -18,96 +18,55 @@ namespace {
|
| constexpr size_t kWindowSize = 20;
|
| constexpr double kGain = 1;
|
| constexpr int64_t kAvgTimeBetweenPackets = 10;
|
| -} // namespace
|
| +constexpr size_t kPacketCount = 2 * kWindowSize + 1;
|
|
|
| -TEST(MedianSlopeEstimator, PerfectLineSlopeOneHalf) {
|
| +void TestEstimator(double slope, double jitter_stddev, double tolerance) {
|
| MedianSlopeEstimator estimator(kWindowSize, kGain);
|
| - Random rand(0x1234567);
|
| - double now_ms = rand.Rand<double>() * 10000;
|
| - for (size_t i = 1; i < 2 * kWindowSize; i++) {
|
| - double send_delta = rand.Rand<double>() * 2 * kAvgTimeBetweenPackets;
|
| - double recv_delta = 2 * send_delta;
|
| - now_ms += recv_delta;
|
| - estimator.Update(recv_delta, send_delta, now_ms);
|
| + Random random(0x1234567);
|
| + int64_t send_times[kPacketCount];
|
| + int64_t recv_times[kPacketCount];
|
| + int64_t send_start_time = random.Rand(1000000);
|
| + int64_t recv_start_time = random.Rand(1000000);
|
| + for (size_t i = 0; i < kPacketCount; ++i) {
|
| + send_times[i] = send_start_time + i * kAvgTimeBetweenPackets;
|
| + double latency = i * kAvgTimeBetweenPackets / (1 - slope);
|
| + double jitter = random.Gaussian(0, jitter_stddev);
|
| + recv_times[i] = recv_start_time + latency + jitter;
|
| + }
|
| + for (size_t i = 1; i < kPacketCount; ++i) {
|
| + double recv_delta = recv_times[i] - recv_times[i - 1];
|
| + double send_delta = send_times[i] - send_times[i - 1];
|
| + estimator.Update(recv_delta, send_delta, recv_times[i]);
|
| if (i < kWindowSize)
|
| EXPECT_NEAR(estimator.trendline_slope(), 0, 0.001);
|
| else
|
| - EXPECT_NEAR(estimator.trendline_slope(), 0.5, 0.001);
|
| + EXPECT_NEAR(estimator.trendline_slope(), slope, tolerance);
|
| }
|
| }
|
| +} // namespace
|
| +
|
| +TEST(MedianSlopeEstimator, PerfectLineSlopeOneHalf) {
|
| + TestEstimator(0.5, 0, 0.001);
|
| +}
|
|
|
| TEST(MedianSlopeEstimator, PerfectLineSlopeMinusOne) {
|
| - MedianSlopeEstimator estimator(kWindowSize, kGain);
|
| - Random rand(0x1234567);
|
| - double now_ms = rand.Rand<double>() * 10000;
|
| - for (size_t i = 1; i < 2 * kWindowSize; i++) {
|
| - double send_delta = rand.Rand<double>() * 2 * kAvgTimeBetweenPackets;
|
| - double recv_delta = 0.5 * send_delta;
|
| - now_ms += recv_delta;
|
| - estimator.Update(recv_delta, send_delta, now_ms);
|
| - if (i < kWindowSize)
|
| - EXPECT_NEAR(estimator.trendline_slope(), 0, 0.001);
|
| - else
|
| - EXPECT_NEAR(estimator.trendline_slope(), -1, 0.001);
|
| - }
|
| + TestEstimator(-1, 0, 0.001);
|
| }
|
|
|
| TEST(MedianSlopeEstimator, PerfectLineSlopeZero) {
|
| - MedianSlopeEstimator estimator(kWindowSize, kGain);
|
| - Random rand(0x1234567);
|
| - double now_ms = rand.Rand<double>() * 10000;
|
| - for (size_t i = 1; i < 2 * kWindowSize; i++) {
|
| - double send_delta = rand.Rand<double>() * 2 * kAvgTimeBetweenPackets;
|
| - double recv_delta = send_delta;
|
| - now_ms += recv_delta;
|
| - estimator.Update(recv_delta, send_delta, now_ms);
|
| - EXPECT_NEAR(estimator.trendline_slope(), 0, 0.001);
|
| - }
|
| + TestEstimator(0, 0, 0.001);
|
| }
|
|
|
| TEST(MedianSlopeEstimator, JitteryLineSlopeOneHalf) {
|
| - MedianSlopeEstimator estimator(kWindowSize, kGain);
|
| - Random rand(0x1234567);
|
| - double now_ms = rand.Rand<double>() * 10000;
|
| - for (size_t i = 1; i < 2 * kWindowSize; i++) {
|
| - double send_delta = rand.Rand<double>() * 2 * kAvgTimeBetweenPackets;
|
| - double recv_delta = 2 * send_delta + rand.Gaussian(0, send_delta / 3);
|
| - now_ms += recv_delta;
|
| - estimator.Update(recv_delta, send_delta, now_ms);
|
| - if (i < kWindowSize)
|
| - EXPECT_NEAR(estimator.trendline_slope(), 0, 0.001);
|
| - else
|
| - EXPECT_NEAR(estimator.trendline_slope(), 0.5, 0.1);
|
| - }
|
| + TestEstimator(0.5, kAvgTimeBetweenPackets / 3.0, 0.01);
|
| }
|
|
|
| TEST(MedianSlopeEstimator, JitteryLineSlopeMinusOne) {
|
| - MedianSlopeEstimator estimator(kWindowSize, kGain);
|
| - Random rand(0x1234567);
|
| - double now_ms = rand.Rand<double>() * 10000;
|
| - for (size_t i = 1; i < 2 * kWindowSize; i++) {
|
| - double send_delta = rand.Rand<double>() * 2 * kAvgTimeBetweenPackets;
|
| - double recv_delta = 0.5 * send_delta + rand.Gaussian(0, send_delta / 20);
|
| - now_ms += recv_delta;
|
| - estimator.Update(recv_delta, send_delta, now_ms);
|
| - if (i < kWindowSize)
|
| - EXPECT_NEAR(estimator.trendline_slope(), 0, 0.001);
|
| - else
|
| - EXPECT_NEAR(estimator.trendline_slope(), -1, 0.1);
|
| - }
|
| + TestEstimator(-1, kAvgTimeBetweenPackets / 3.0, 0.05);
|
| }
|
|
|
| TEST(MedianSlopeEstimator, JitteryLineSlopeZero) {
|
| - MedianSlopeEstimator estimator(kWindowSize, kGain);
|
| - Random rand(0x1234567);
|
| - double now_ms = rand.Rand<double>() * 10000;
|
| - for (size_t i = 1; i < 2 * kWindowSize; i++) {
|
| - double send_delta = rand.Rand<double>() * 2 * kAvgTimeBetweenPackets;
|
| - double recv_delta = send_delta + rand.Gaussian(0, send_delta / 5);
|
| - now_ms += recv_delta;
|
| - estimator.Update(recv_delta, send_delta, now_ms);
|
| - EXPECT_NEAR(estimator.trendline_slope(), 0, 0.1);
|
| - }
|
| + TestEstimator(0, kAvgTimeBetweenPackets / 3.0, 0.02);
|
| }
|
|
|
| } // namespace webrtc
|
|
|