Implement Stylus Prediction Metrics
Fills out the implementation and tests for MotionPredictorMetricsManager.
(Cherry pick of ag/23861881 from udc-qpr-dev)
Test: atest frameworks/native/libs/input/tests/MotionPredictorMetricsManager_test.cpp
Test: Manual testing on-device, computed metric values seem reasonable.
Bug: 268245099
Change-Id: Iec18415de9c3070f2b285c5c82f5a5e0ceaaf471
diff --git a/libs/input/tests/Android.bp b/libs/input/tests/Android.bp
index 86b996b..e7224ff 100644
--- a/libs/input/tests/Android.bp
+++ b/libs/input/tests/Android.bp
@@ -20,6 +20,7 @@
"InputPublisherAndConsumer_test.cpp",
"InputVerifier_test.cpp",
"MotionPredictor_test.cpp",
+ "MotionPredictorMetricsManager_test.cpp",
"RingBuffer_test.cpp",
"TfLiteMotionPredictor_test.cpp",
"TouchResampling_test.cpp",
@@ -52,13 +53,6 @@
undefined: true,
},
},
- target: {
- host: {
- sanitize: {
- address: true,
- },
- },
- },
shared_libs: [
"libbase",
"libbinder",
@@ -77,6 +71,21 @@
unit_test: true,
},
test_suites: ["device-tests"],
+ target: {
+ host: {
+ sanitize: {
+ address: true,
+ },
+ },
+ android: {
+ static_libs: [
+ // Stats logging library and its dependencies.
+ "libstatslog_libinput",
+ "libstatsbootstrap",
+ "android.os.statsbootstrap_aidl-cpp",
+ ],
+ },
+ },
}
// NOTE: This is a compile time test, and does not need to be
diff --git a/libs/input/tests/MotionPredictorMetricsManager_test.cpp b/libs/input/tests/MotionPredictorMetricsManager_test.cpp
new file mode 100644
index 0000000..b420a5a
--- /dev/null
+++ b/libs/input/tests/MotionPredictorMetricsManager_test.cpp
@@ -0,0 +1,972 @@
+/*
+ * Copyright 2023 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <input/MotionPredictor.h>
+
+#include <cmath>
+#include <cstddef>
+#include <cstdint>
+#include <numeric>
+#include <vector>
+
+#include <gmock/gmock.h>
+#include <gtest/gtest.h>
+#include <input/InputEventBuilders.h>
+#include <utils/Timers.h> // for nsecs_t
+
+#include "Eigen/Core"
+#include "Eigen/Geometry"
+
+namespace android {
+namespace {
+
+using ::testing::FloatNear;
+using ::testing::Matches;
+
+using GroundTruthPoint = MotionPredictorMetricsManager::GroundTruthPoint;
+using PredictionPoint = MotionPredictorMetricsManager::PredictionPoint;
+using AtomFields = MotionPredictorMetricsManager::AtomFields;
+
+inline constexpr int NANOS_PER_MILLIS = 1'000'000;
+
+inline constexpr nsecs_t TEST_INITIAL_TIMESTAMP = 1'000'000'000;
+inline constexpr size_t TEST_MAX_NUM_PREDICTIONS = 5;
+inline constexpr nsecs_t TEST_PREDICTION_INTERVAL_NANOS = 12'500'000 / 3; // 1 / (240 hz)
+inline constexpr int NO_DATA_SENTINEL = MotionPredictorMetricsManager::NO_DATA_SENTINEL;
+
+// Parameters:
+// • arg: Eigen::Vector2f
+// • target: Eigen::Vector2f
+// • epsilon: float
+MATCHER_P2(Vector2fNear, target, epsilon, "") {
+ return Matches(FloatNear(target[0], epsilon))(arg[0]) &&
+ Matches(FloatNear(target[1], epsilon))(arg[1]);
+}
+
+// Parameters:
+// • arg: PredictionPoint
+// • target: PredictionPoint
+// • epsilon: float
+MATCHER_P2(PredictionPointNear, target, epsilon, "") {
+ if (!Matches(Vector2fNear(target.position, epsilon))(arg.position)) {
+ *result_listener << "Position mismatch. Actual: (" << arg.position[0] << ", "
+ << arg.position[1] << "), expected: (" << target.position[0] << ", "
+ << target.position[1] << ")";
+ return false;
+ }
+ if (!Matches(FloatNear(target.pressure, epsilon))(arg.pressure)) {
+ *result_listener << "Pressure mismatch. Actual: " << arg.pressure
+ << ", expected: " << target.pressure;
+ return false;
+ }
+ if (arg.originTimestamp != target.originTimestamp) {
+ *result_listener << "Origin timestamp mismatch. Actual: " << arg.originTimestamp
+ << ", expected: " << target.originTimestamp;
+ return false;
+ }
+ if (arg.targetTimestamp != target.targetTimestamp) {
+ *result_listener << "Target timestamp mismatch. Actual: " << arg.targetTimestamp
+ << ", expected: " << target.targetTimestamp;
+ return false;
+ }
+ return true;
+}
+
+// --- Mathematical helper functions. ---
+
+template <typename T>
+T average(std::vector<T> values) {
+ return std::accumulate(values.begin(), values.end(), T{}) / static_cast<T>(values.size());
+}
+
+template <typename T>
+T standardDeviation(std::vector<T> values) {
+ T mean = average(values);
+ T accumulator = {};
+ for (const T value : values) {
+ accumulator += value * value - mean * mean;
+ }
+ // Take the max with 0 to avoid negative values caused by numerical instability.
+ return std::sqrt(std::max(T{}, accumulator) / static_cast<T>(values.size()));
+}
+
+template <typename T>
+T rmse(std::vector<T> errors) {
+ T sse = {};
+ for (const T error : errors) {
+ sse += error * error;
+ }
+ return std::sqrt(sse / static_cast<T>(errors.size()));
+}
+
+TEST(MathematicalHelperFunctionTest, Average) {
+ std::vector<float> values{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
+ EXPECT_EQ(5.5f, average(values));
+}
+
+TEST(MathematicalHelperFunctionTest, StandardDeviation) {
+ // https://www.calculator.net/standard-deviation-calculator.html?numberinputs=10%2C+12%2C+23%2C+23%2C+16%2C+23%2C+21%2C+16
+ std::vector<float> values{10, 12, 23, 23, 16, 23, 21, 16};
+ EXPECT_FLOAT_EQ(4.8989794855664f, standardDeviation(values));
+}
+
+TEST(MathematicalHelperFunctionTest, Rmse) {
+ std::vector<float> errors{1, 5, 7, 7, 8, 20};
+ EXPECT_FLOAT_EQ(9.899494937f, rmse(errors));
+}
+
+// --- MotionEvent-related helper functions. ---
+
+// Creates a MotionEvent corresponding to the given GroundTruthPoint.
+MotionEvent makeMotionEvent(const GroundTruthPoint& groundTruthPoint) {
+ // Build single pointer of type STYLUS, with coordinates from groundTruthPoint.
+ PointerBuilder pointerBuilder =
+ PointerBuilder(/*id=*/0, ToolType::STYLUS)
+ .x(groundTruthPoint.position[1])
+ .y(groundTruthPoint.position[0])
+ .axis(AMOTION_EVENT_AXIS_PRESSURE, groundTruthPoint.pressure);
+ return MotionEventBuilder(/*action=*/AMOTION_EVENT_ACTION_MOVE,
+ /*source=*/AINPUT_SOURCE_CLASS_POINTER)
+ .eventTime(groundTruthPoint.timestamp)
+ .pointer(pointerBuilder)
+ .build();
+}
+
+// Creates a MotionEvent corresponding to the given sequence of PredictionPoints.
+MotionEvent makeMotionEvent(const std::vector<PredictionPoint>& predictionPoints) {
+ // Build single pointer of type STYLUS, with coordinates from first prediction point.
+ PointerBuilder pointerBuilder =
+ PointerBuilder(/*id=*/0, ToolType::STYLUS)
+ .x(predictionPoints[0].position[1])
+ .y(predictionPoints[0].position[0])
+ .axis(AMOTION_EVENT_AXIS_PRESSURE, predictionPoints[0].pressure);
+ MotionEvent predictionEvent =
+ MotionEventBuilder(
+ /*action=*/AMOTION_EVENT_ACTION_MOVE, /*source=*/AINPUT_SOURCE_CLASS_POINTER)
+ .eventTime(predictionPoints[0].targetTimestamp)
+ .pointer(pointerBuilder)
+ .build();
+ for (size_t i = 1; i < predictionPoints.size(); ++i) {
+ PointerCoords coords =
+ PointerBuilder(/*id=*/0, ToolType::STYLUS)
+ .x(predictionPoints[i].position[1])
+ .y(predictionPoints[i].position[0])
+ .axis(AMOTION_EVENT_AXIS_PRESSURE, predictionPoints[i].pressure)
+ .buildCoords();
+ predictionEvent.addSample(predictionPoints[i].targetTimestamp, &coords);
+ }
+ return predictionEvent;
+}
+
+// Creates a MotionEvent corresponding to a stylus lift (UP) ground truth event.
+MotionEvent makeLiftMotionEvent() {
+ return MotionEventBuilder(/*action=*/AMOTION_EVENT_ACTION_UP,
+ /*source=*/AINPUT_SOURCE_CLASS_POINTER)
+ .pointer(PointerBuilder(/*id=*/0, ToolType::STYLUS))
+ .build();
+}
+
+TEST(MakeMotionEventTest, MakeGroundTruthMotionEvent) {
+ const GroundTruthPoint groundTruthPoint{{.position = Eigen::Vector2f(10.0f, 20.0f),
+ .pressure = 0.6f},
+ .timestamp = TEST_INITIAL_TIMESTAMP};
+ const MotionEvent groundTruthMotionEvent = makeMotionEvent(groundTruthPoint);
+
+ ASSERT_EQ(1u, groundTruthMotionEvent.getPointerCount());
+ // Note: a MotionEvent's "history size" is one less than its number of samples.
+ ASSERT_EQ(0u, groundTruthMotionEvent.getHistorySize());
+ EXPECT_EQ(groundTruthPoint.position[0], groundTruthMotionEvent.getRawPointerCoords(0)->getY());
+ EXPECT_EQ(groundTruthPoint.position[1], groundTruthMotionEvent.getRawPointerCoords(0)->getX());
+ EXPECT_EQ(groundTruthPoint.pressure,
+ groundTruthMotionEvent.getRawPointerCoords(0)->getAxisValue(
+ AMOTION_EVENT_AXIS_PRESSURE));
+ EXPECT_EQ(AMOTION_EVENT_ACTION_MOVE, groundTruthMotionEvent.getAction());
+}
+
+TEST(MakeMotionEventTest, MakePredictionMotionEvent) {
+ const nsecs_t originTimestamp = TEST_INITIAL_TIMESTAMP;
+ const std::vector<PredictionPoint>
+ predictionPoints{{{.position = Eigen::Vector2f(10.0f, 20.0f), .pressure = 0.6f},
+ .originTimestamp = originTimestamp,
+ .targetTimestamp = originTimestamp + 5 * NANOS_PER_MILLIS},
+ {{.position = Eigen::Vector2f(11.0f, 22.0f), .pressure = 0.5f},
+ .originTimestamp = originTimestamp,
+ .targetTimestamp = originTimestamp + 10 * NANOS_PER_MILLIS},
+ {{.position = Eigen::Vector2f(12.0f, 24.0f), .pressure = 0.4f},
+ .originTimestamp = originTimestamp,
+ .targetTimestamp = originTimestamp + 15 * NANOS_PER_MILLIS}};
+ const MotionEvent predictionMotionEvent = makeMotionEvent(predictionPoints);
+
+ ASSERT_EQ(1u, predictionMotionEvent.getPointerCount());
+ // Note: a MotionEvent's "history size" is one less than its number of samples.
+ ASSERT_EQ(predictionPoints.size(), predictionMotionEvent.getHistorySize() + 1);
+ for (size_t i = 0; i < predictionPoints.size(); ++i) {
+ SCOPED_TRACE(testing::Message() << "i = " << i);
+ const PointerCoords coords = *predictionMotionEvent.getHistoricalRawPointerCoords(
+ /*pointerIndex=*/0, /*historicalIndex=*/i);
+ EXPECT_EQ(predictionPoints[i].position[0], coords.getY());
+ EXPECT_EQ(predictionPoints[i].position[1], coords.getX());
+ EXPECT_EQ(predictionPoints[i].pressure, coords.getAxisValue(AMOTION_EVENT_AXIS_PRESSURE));
+ // Note: originTimestamp is discarded when converting PredictionPoint to MotionEvent.
+ EXPECT_EQ(predictionPoints[i].targetTimestamp,
+ predictionMotionEvent.getHistoricalEventTime(i));
+ EXPECT_EQ(AMOTION_EVENT_ACTION_MOVE, predictionMotionEvent.getAction());
+ }
+}
+
+TEST(MakeMotionEventTest, MakeLiftMotionEvent) {
+ const MotionEvent liftMotionEvent = makeLiftMotionEvent();
+ ASSERT_EQ(1u, liftMotionEvent.getPointerCount());
+ // Note: a MotionEvent's "history size" is one less than its number of samples.
+ ASSERT_EQ(0u, liftMotionEvent.getHistorySize());
+ EXPECT_EQ(AMOTION_EVENT_ACTION_UP, liftMotionEvent.getAction());
+}
+
+// --- Ground-truth-generation helper functions. ---
+
+std::vector<GroundTruthPoint> generateConstantGroundTruthPoints(
+ const GroundTruthPoint& groundTruthPoint, size_t numPoints) {
+ std::vector<GroundTruthPoint> groundTruthPoints;
+ nsecs_t timestamp = groundTruthPoint.timestamp;
+ for (size_t i = 0; i < numPoints; ++i) {
+ groundTruthPoints.emplace_back(groundTruthPoint);
+ groundTruthPoints.back().timestamp = timestamp;
+ timestamp += TEST_PREDICTION_INTERVAL_NANOS;
+ }
+ return groundTruthPoints;
+}
+
+// This function uses the coordinate system (y, x), with +y pointing downwards and +x pointing
+// rightwards. Angles are measured counterclockwise from down (+y).
+std::vector<GroundTruthPoint> generateCircularArcGroundTruthPoints(Eigen::Vector2f initialPosition,
+ float initialAngle,
+ float velocity,
+ float turningAngle,
+ size_t numPoints) {
+ std::vector<GroundTruthPoint> groundTruthPoints;
+ // Create first point.
+ if (numPoints > 0) {
+ groundTruthPoints.push_back({{.position = initialPosition, .pressure = 0.0f},
+ .timestamp = TEST_INITIAL_TIMESTAMP});
+ }
+ float trajectoryAngle = initialAngle; // measured counterclockwise from +y axis.
+ for (size_t i = 1; i < numPoints; ++i) {
+ const Eigen::Vector2f trajectory =
+ Eigen::Rotation2D(trajectoryAngle) * Eigen::Vector2f(1, 0);
+ groundTruthPoints.push_back(
+ {{.position = groundTruthPoints.back().position + velocity * trajectory,
+ .pressure = 0.0f},
+ .timestamp = groundTruthPoints.back().timestamp + TEST_PREDICTION_INTERVAL_NANOS});
+ trajectoryAngle += turningAngle;
+ }
+ return groundTruthPoints;
+}
+
+TEST(GenerateConstantGroundTruthPointsTest, BasicTest) {
+ const GroundTruthPoint groundTruthPoint{{.position = Eigen::Vector2f(10, 20), .pressure = 0.3f},
+ .timestamp = TEST_INITIAL_TIMESTAMP};
+ const std::vector<GroundTruthPoint> groundTruthPoints =
+ generateConstantGroundTruthPoints(groundTruthPoint, /*numPoints=*/3);
+
+ ASSERT_EQ(3u, groundTruthPoints.size());
+ // First point.
+ EXPECT_EQ(groundTruthPoints[0].position, groundTruthPoint.position);
+ EXPECT_EQ(groundTruthPoints[0].pressure, groundTruthPoint.pressure);
+ EXPECT_EQ(groundTruthPoints[0].timestamp, groundTruthPoint.timestamp);
+ // Second point.
+ EXPECT_EQ(groundTruthPoints[1].position, groundTruthPoint.position);
+ EXPECT_EQ(groundTruthPoints[1].pressure, groundTruthPoint.pressure);
+ EXPECT_GT(groundTruthPoints[1].timestamp, groundTruthPoints[0].timestamp);
+ // Third point.
+ EXPECT_EQ(groundTruthPoints[2].position, groundTruthPoint.position);
+ EXPECT_EQ(groundTruthPoints[2].pressure, groundTruthPoint.pressure);
+ EXPECT_GT(groundTruthPoints[2].timestamp, groundTruthPoints[1].timestamp);
+}
+
+TEST(GenerateCircularArcGroundTruthTest, StraightLineUpwards) {
+ const std::vector<GroundTruthPoint> groundTruthPoints = generateCircularArcGroundTruthPoints(
+ /*initialPosition=*/Eigen::Vector2f(0, 0),
+ /*initialAngle=*/M_PI,
+ /*velocity=*/1.0f,
+ /*turningAngle=*/0.0f,
+ /*numPoints=*/3);
+
+ ASSERT_EQ(3u, groundTruthPoints.size());
+ EXPECT_THAT(groundTruthPoints[0].position, Vector2fNear(Eigen::Vector2f(0, 0), 1e-6));
+ EXPECT_THAT(groundTruthPoints[1].position, Vector2fNear(Eigen::Vector2f(-1, 0), 1e-6));
+ EXPECT_THAT(groundTruthPoints[2].position, Vector2fNear(Eigen::Vector2f(-2, 0), 1e-6));
+ // Check that timestamps are increasing between consecutive ground truth points.
+ EXPECT_GT(groundTruthPoints[1].timestamp, groundTruthPoints[0].timestamp);
+ EXPECT_GT(groundTruthPoints[2].timestamp, groundTruthPoints[1].timestamp);
+}
+
+TEST(GenerateCircularArcGroundTruthTest, CounterclockwiseSquare) {
+ // Generate points in a counterclockwise unit square starting pointing right.
+ const std::vector<GroundTruthPoint> groundTruthPoints = generateCircularArcGroundTruthPoints(
+ /*initialPosition=*/Eigen::Vector2f(10, 100),
+ /*initialAngle=*/M_PI_2,
+ /*velocity=*/1.0f,
+ /*turningAngle=*/M_PI_2,
+ /*numPoints=*/5);
+
+ ASSERT_EQ(5u, groundTruthPoints.size());
+ EXPECT_THAT(groundTruthPoints[0].position, Vector2fNear(Eigen::Vector2f(10, 100), 1e-6));
+ EXPECT_THAT(groundTruthPoints[1].position, Vector2fNear(Eigen::Vector2f(10, 101), 1e-6));
+ EXPECT_THAT(groundTruthPoints[2].position, Vector2fNear(Eigen::Vector2f(9, 101), 1e-6));
+ EXPECT_THAT(groundTruthPoints[3].position, Vector2fNear(Eigen::Vector2f(9, 100), 1e-6));
+ EXPECT_THAT(groundTruthPoints[4].position, Vector2fNear(Eigen::Vector2f(10, 100), 1e-6));
+}
+
+// --- Prediction-generation helper functions. ---
+
+// Creates a sequence of predictions with values equal to those of the given GroundTruthPoint.
+std::vector<PredictionPoint> generateConstantPredictions(const GroundTruthPoint& groundTruthPoint) {
+ std::vector<PredictionPoint> predictions;
+ nsecs_t predictionTimestamp = groundTruthPoint.timestamp + TEST_PREDICTION_INTERVAL_NANOS;
+ for (size_t j = 0; j < TEST_MAX_NUM_PREDICTIONS; ++j) {
+ predictions.push_back(PredictionPoint{{.position = groundTruthPoint.position,
+ .pressure = groundTruthPoint.pressure},
+ .originTimestamp = groundTruthPoint.timestamp,
+ .targetTimestamp = predictionTimestamp});
+ predictionTimestamp += TEST_PREDICTION_INTERVAL_NANOS;
+ }
+ return predictions;
+}
+
+// Generates TEST_MAX_NUM_PREDICTIONS predictions from the given most recent two ground truth points
+// by linear extrapolation of position and pressure. The interval between consecutive predictions'
+// timestamps is TEST_PREDICTION_INTERVAL_NANOS.
+std::vector<PredictionPoint> generatePredictionsByLinearExtrapolation(
+ const GroundTruthPoint& firstGroundTruth, const GroundTruthPoint& secondGroundTruth) {
+ // Precompute deltas.
+ const Eigen::Vector2f trajectory = secondGroundTruth.position - firstGroundTruth.position;
+ const float deltaPressure = secondGroundTruth.pressure - firstGroundTruth.pressure;
+ // Compute predictions.
+ std::vector<PredictionPoint> predictions;
+ Eigen::Vector2f predictionPosition = secondGroundTruth.position;
+ float predictionPressure = secondGroundTruth.pressure;
+ nsecs_t predictionTargetTimestamp = secondGroundTruth.timestamp;
+ for (size_t i = 0; i < TEST_MAX_NUM_PREDICTIONS; ++i) {
+ predictionPosition += trajectory;
+ predictionPressure += deltaPressure;
+ predictionTargetTimestamp += TEST_PREDICTION_INTERVAL_NANOS;
+ predictions.push_back(
+ PredictionPoint{{.position = predictionPosition, .pressure = predictionPressure},
+ .originTimestamp = secondGroundTruth.timestamp,
+ .targetTimestamp = predictionTargetTimestamp});
+ }
+ return predictions;
+}
+
+TEST(GeneratePredictionsTest, GenerateConstantPredictions) {
+ const GroundTruthPoint groundTruthPoint{{.position = Eigen::Vector2f(10, 20), .pressure = 0.3f},
+ .timestamp = TEST_INITIAL_TIMESTAMP};
+ const std::vector<PredictionPoint> predictionPoints =
+ generateConstantPredictions(groundTruthPoint);
+
+ ASSERT_EQ(TEST_MAX_NUM_PREDICTIONS, predictionPoints.size());
+ for (size_t i = 0; i < predictionPoints.size(); ++i) {
+ SCOPED_TRACE(testing::Message() << "i = " << i);
+ EXPECT_THAT(predictionPoints[i].position, Vector2fNear(groundTruthPoint.position, 1e-6));
+ EXPECT_THAT(predictionPoints[i].pressure, FloatNear(groundTruthPoint.pressure, 1e-6));
+ EXPECT_EQ(predictionPoints[i].originTimestamp, groundTruthPoint.timestamp);
+ EXPECT_EQ(predictionPoints[i].targetTimestamp,
+ groundTruthPoint.timestamp +
+ static_cast<nsecs_t>(i + 1) * TEST_PREDICTION_INTERVAL_NANOS);
+ }
+}
+
+TEST(GeneratePredictionsTest, LinearExtrapolationFromTwoPoints) {
+ const nsecs_t initialTimestamp = TEST_INITIAL_TIMESTAMP;
+ const std::vector<PredictionPoint> predictionPoints = generatePredictionsByLinearExtrapolation(
+ GroundTruthPoint{{.position = Eigen::Vector2f(100, 200), .pressure = 0.9f},
+ .timestamp = initialTimestamp},
+ GroundTruthPoint{{.position = Eigen::Vector2f(105, 190), .pressure = 0.8f},
+ .timestamp = initialTimestamp + TEST_PREDICTION_INTERVAL_NANOS});
+
+ ASSERT_EQ(TEST_MAX_NUM_PREDICTIONS, predictionPoints.size());
+ const nsecs_t originTimestamp = initialTimestamp + TEST_PREDICTION_INTERVAL_NANOS;
+ EXPECT_THAT(predictionPoints[0],
+ PredictionPointNear(PredictionPoint{{.position = Eigen::Vector2f(110, 180),
+ .pressure = 0.7f},
+ .originTimestamp = originTimestamp,
+ .targetTimestamp = originTimestamp +
+ TEST_PREDICTION_INTERVAL_NANOS},
+ 0.001));
+ EXPECT_THAT(predictionPoints[1],
+ PredictionPointNear(PredictionPoint{{.position = Eigen::Vector2f(115, 170),
+ .pressure = 0.6f},
+ .originTimestamp = originTimestamp,
+ .targetTimestamp = originTimestamp +
+ 2 * TEST_PREDICTION_INTERVAL_NANOS},
+ 0.001));
+ EXPECT_THAT(predictionPoints[2],
+ PredictionPointNear(PredictionPoint{{.position = Eigen::Vector2f(120, 160),
+ .pressure = 0.5f},
+ .originTimestamp = originTimestamp,
+ .targetTimestamp = originTimestamp +
+ 3 * TEST_PREDICTION_INTERVAL_NANOS},
+ 0.001));
+ EXPECT_THAT(predictionPoints[3],
+ PredictionPointNear(PredictionPoint{{.position = Eigen::Vector2f(125, 150),
+ .pressure = 0.4f},
+ .originTimestamp = originTimestamp,
+ .targetTimestamp = originTimestamp +
+ 4 * TEST_PREDICTION_INTERVAL_NANOS},
+ 0.001));
+ EXPECT_THAT(predictionPoints[4],
+ PredictionPointNear(PredictionPoint{{.position = Eigen::Vector2f(130, 140),
+ .pressure = 0.3f},
+ .originTimestamp = originTimestamp,
+ .targetTimestamp = originTimestamp +
+ 5 * TEST_PREDICTION_INTERVAL_NANOS},
+ 0.001));
+}
+
+// Generates predictions by linear extrapolation for each consecutive pair of ground truth points
+// (see the comment for the above function for further explanation). Returns a vector of vectors of
+// prediction points, where the first index is the source ground truth index, and the second is the
+// prediction target index.
+//
+// The returned vector has size equal to the input vector, and the first element of the returned
+// vector is always empty.
+std::vector<std::vector<PredictionPoint>> generateAllPredictionsByLinearExtrapolation(
+ const std::vector<GroundTruthPoint>& groundTruthPoints) {
+ std::vector<std::vector<PredictionPoint>> allPredictions;
+ allPredictions.emplace_back();
+ for (size_t i = 1; i < groundTruthPoints.size(); ++i) {
+ allPredictions.push_back(generatePredictionsByLinearExtrapolation(groundTruthPoints[i - 1],
+ groundTruthPoints[i]));
+ }
+ return allPredictions;
+}
+
+TEST(GeneratePredictionsTest, GenerateAllPredictions) {
+ const nsecs_t initialTimestamp = TEST_INITIAL_TIMESTAMP;
+ std::vector<GroundTruthPoint>
+ groundTruthPoints{GroundTruthPoint{{.position = Eigen::Vector2f(0, 0),
+ .pressure = 0.5f},
+ .timestamp = initialTimestamp},
+ GroundTruthPoint{{.position = Eigen::Vector2f(1, -1),
+ .pressure = 0.51f},
+ .timestamp = initialTimestamp +
+ 2 * TEST_PREDICTION_INTERVAL_NANOS},
+ GroundTruthPoint{{.position = Eigen::Vector2f(2, -2),
+ .pressure = 0.52f},
+ .timestamp = initialTimestamp +
+ 3 * TEST_PREDICTION_INTERVAL_NANOS}};
+
+ const std::vector<std::vector<PredictionPoint>> allPredictions =
+ generateAllPredictionsByLinearExtrapolation(groundTruthPoints);
+
+ // Check format of allPredictions data.
+ ASSERT_EQ(groundTruthPoints.size(), allPredictions.size());
+ EXPECT_TRUE(allPredictions[0].empty());
+ EXPECT_EQ(TEST_MAX_NUM_PREDICTIONS, allPredictions[1].size());
+ EXPECT_EQ(TEST_MAX_NUM_PREDICTIONS, allPredictions[2].size());
+
+ // Check positions of predictions generated from first pair of ground truth points.
+ EXPECT_THAT(allPredictions[1][0].position, Vector2fNear(Eigen::Vector2f(2, -2), 1e-9));
+ EXPECT_THAT(allPredictions[1][1].position, Vector2fNear(Eigen::Vector2f(3, -3), 1e-9));
+ EXPECT_THAT(allPredictions[1][2].position, Vector2fNear(Eigen::Vector2f(4, -4), 1e-9));
+ EXPECT_THAT(allPredictions[1][3].position, Vector2fNear(Eigen::Vector2f(5, -5), 1e-9));
+ EXPECT_THAT(allPredictions[1][4].position, Vector2fNear(Eigen::Vector2f(6, -6), 1e-9));
+
+ // Check pressures of predictions generated from first pair of ground truth points.
+ EXPECT_FLOAT_EQ(0.52f, allPredictions[1][0].pressure);
+ EXPECT_FLOAT_EQ(0.53f, allPredictions[1][1].pressure);
+ EXPECT_FLOAT_EQ(0.54f, allPredictions[1][2].pressure);
+ EXPECT_FLOAT_EQ(0.55f, allPredictions[1][3].pressure);
+ EXPECT_FLOAT_EQ(0.56f, allPredictions[1][4].pressure);
+}
+
+// --- Prediction error helper functions. ---
+
+struct GeneralPositionErrors {
+ float alongTrajectoryErrorMean;
+ float alongTrajectoryErrorStd;
+ float offTrajectoryRmse;
+};
+
+// Inputs:
+// • Vector of ground truth points
+// • Vector of vectors of prediction points, where the first index is the source ground truth
+// index, and the second is the prediction target index.
+//
+// Returns a vector of GeneralPositionErrors, indexed by prediction time delta bucket.
+std::vector<GeneralPositionErrors> computeGeneralPositionErrors(
+ const std::vector<GroundTruthPoint>& groundTruthPoints,
+ const std::vector<std::vector<PredictionPoint>>& predictionPoints) {
+ // Aggregate errors by time bucket (prediction target index).
+ std::vector<GeneralPositionErrors> generalPostitionErrors;
+ for (size_t predictionTargetIndex = 0; predictionTargetIndex < TEST_MAX_NUM_PREDICTIONS;
+ ++predictionTargetIndex) {
+ std::vector<float> alongTrajectoryErrors;
+ std::vector<float> alongTrajectorySquaredErrors;
+ std::vector<float> offTrajectoryErrors;
+ for (size_t sourceGroundTruthIndex = 1; sourceGroundTruthIndex < groundTruthPoints.size();
+ ++sourceGroundTruthIndex) {
+ const size_t targetGroundTruthIndex =
+ sourceGroundTruthIndex + predictionTargetIndex + 1;
+ // Only include errors for points with a ground truth value.
+ if (targetGroundTruthIndex < groundTruthPoints.size()) {
+ const Eigen::Vector2f trajectory =
+ (groundTruthPoints[targetGroundTruthIndex].position -
+ groundTruthPoints[targetGroundTruthIndex - 1].position)
+ .normalized();
+ const Eigen::Vector2f orthogonalTrajectory =
+ Eigen::Rotation2Df(M_PI_2) * trajectory;
+ const Eigen::Vector2f positionError =
+ predictionPoints[sourceGroundTruthIndex][predictionTargetIndex].position -
+ groundTruthPoints[targetGroundTruthIndex].position;
+ alongTrajectoryErrors.push_back(positionError.dot(trajectory));
+ alongTrajectorySquaredErrors.push_back(alongTrajectoryErrors.back() *
+ alongTrajectoryErrors.back());
+ offTrajectoryErrors.push_back(positionError.dot(orthogonalTrajectory));
+ }
+ }
+ generalPostitionErrors.push_back(
+ {.alongTrajectoryErrorMean = average(alongTrajectoryErrors),
+ .alongTrajectoryErrorStd = standardDeviation(alongTrajectoryErrors),
+ .offTrajectoryRmse = rmse(offTrajectoryErrors)});
+ }
+ return generalPostitionErrors;
+}
+
+// Inputs:
+// • Vector of ground truth points
+// • Vector of vectors of prediction points, where the first index is the source ground truth
+// index, and the second is the prediction target index.
+//
+// Returns a vector of pressure RMSEs, indexed by prediction time delta bucket.
+std::vector<float> computePressureRmses(
+ const std::vector<GroundTruthPoint>& groundTruthPoints,
+ const std::vector<std::vector<PredictionPoint>>& predictionPoints) {
+ // Aggregate errors by time bucket (prediction target index).
+ std::vector<float> pressureRmses;
+ for (size_t predictionTargetIndex = 0; predictionTargetIndex < TEST_MAX_NUM_PREDICTIONS;
+ ++predictionTargetIndex) {
+ std::vector<float> pressureErrors;
+ for (size_t sourceGroundTruthIndex = 1; sourceGroundTruthIndex < groundTruthPoints.size();
+ ++sourceGroundTruthIndex) {
+ const size_t targetGroundTruthIndex =
+ sourceGroundTruthIndex + predictionTargetIndex + 1;
+ // Only include errors for points with a ground truth value.
+ if (targetGroundTruthIndex < groundTruthPoints.size()) {
+ pressureErrors.push_back(
+ predictionPoints[sourceGroundTruthIndex][predictionTargetIndex].pressure -
+ groundTruthPoints[targetGroundTruthIndex].pressure);
+ }
+ }
+ pressureRmses.push_back(rmse(pressureErrors));
+ }
+ return pressureRmses;
+}
+
+TEST(ErrorComputationHelperTest, ComputeGeneralPositionErrorsSimpleTest) {
+ std::vector<GroundTruthPoint> groundTruthPoints =
+ generateConstantGroundTruthPoints(GroundTruthPoint{{.position = Eigen::Vector2f(0, 0),
+ .pressure = 0.0f},
+ .timestamp = TEST_INITIAL_TIMESTAMP},
+ /*numPoints=*/TEST_MAX_NUM_PREDICTIONS + 2);
+ groundTruthPoints[3].position = Eigen::Vector2f(1, 0);
+ groundTruthPoints[4].position = Eigen::Vector2f(1, 1);
+ groundTruthPoints[5].position = Eigen::Vector2f(1, 3);
+ groundTruthPoints[6].position = Eigen::Vector2f(2, 3);
+
+ std::vector<std::vector<PredictionPoint>> predictionPoints =
+ generateAllPredictionsByLinearExtrapolation(groundTruthPoints);
+
+ // The generated predictions look like:
+ //
+ // | Source | Target Ground Truth Index |
+ // | Index | 2 | 3 | 4 | 5 | 6 |
+ // |------------|--------|--------|--------|--------|--------|
+ // | 1 | (0, 0) | (0, 0) | (0, 0) | (0, 0) | (0, 0) |
+ // | 2 | | (0, 0) | (0, 0) | (0, 0) | (0, 0) |
+ // | 3 | | | (2, 0) | (3, 0) | (4, 0) |
+ // | 4 | | | | (1, 2) | (1, 3) |
+ // | 5 | | | | | (1, 5) |
+ // |---------------------------------------------------------|
+ // | Actual Ground Truth Values |
+ // | Position | (0, 0) | (1, 0) | (1, 1) | (1, 3) | (2, 3) |
+ // | Previous | (0, 0) | (0, 0) | (1, 0) | (1, 1) | (1, 3) |
+ //
+ // Note: this table organizes prediction targets by target ground truth index. Metrics are
+ // aggregated across points with the same prediction time bucket index, which is different.
+ // Each down-right diagonal from this table gives us points from a unique time bucket.
+
+ // Initialize expected prediction errors from the table above. The first time bucket corresponds
+ // to the long diagonal of the table, and subsequent time buckets step up-right from there.
+ const std::vector<std::vector<float>> expectedAlongTrajectoryErrors{{0, -1, -1, -1, -1},
+ {-1, -1, -3, -1},
+ {-1, -3, 2},
+ {-3, -2},
+ {-2}};
+ const std::vector<std::vector<float>> expectedOffTrajectoryErrors{{0, 0, 1, 0, 2},
+ {0, 1, 2, 0},
+ {1, 1, 3},
+ {1, 3},
+ {3}};
+
+ std::vector<GeneralPositionErrors> generalPositionErrors =
+ computeGeneralPositionErrors(groundTruthPoints, predictionPoints);
+
+ ASSERT_EQ(TEST_MAX_NUM_PREDICTIONS, generalPositionErrors.size());
+ for (size_t i = 0; i < generalPositionErrors.size(); ++i) {
+ SCOPED_TRACE(testing::Message() << "i = " << i);
+ EXPECT_FLOAT_EQ(average(expectedAlongTrajectoryErrors[i]),
+ generalPositionErrors[i].alongTrajectoryErrorMean);
+ EXPECT_FLOAT_EQ(standardDeviation(expectedAlongTrajectoryErrors[i]),
+ generalPositionErrors[i].alongTrajectoryErrorStd);
+ EXPECT_FLOAT_EQ(rmse(expectedOffTrajectoryErrors[i]),
+ generalPositionErrors[i].offTrajectoryRmse);
+ }
+}
+
+TEST(ErrorComputationHelperTest, ComputePressureRmsesSimpleTest) {
+ // Generate ground truth points with pressures {0.0, 0.0, 0.0, 0.0, 0.5, 0.5, 0.5}.
+ // (We need TEST_MAX_NUM_PREDICTIONS + 2 to test all prediction time buckets.)
+ std::vector<GroundTruthPoint> groundTruthPoints =
+ generateConstantGroundTruthPoints(GroundTruthPoint{{.position = Eigen::Vector2f(0, 0),
+ .pressure = 0.0f},
+ .timestamp = TEST_INITIAL_TIMESTAMP},
+ /*numPoints=*/TEST_MAX_NUM_PREDICTIONS + 2);
+ for (size_t i = 4; i < groundTruthPoints.size(); ++i) {
+ groundTruthPoints[i].pressure = 0.5f;
+ }
+
+ std::vector<std::vector<PredictionPoint>> predictionPoints =
+ generateAllPredictionsByLinearExtrapolation(groundTruthPoints);
+
+ std::vector<float> pressureRmses = computePressureRmses(groundTruthPoints, predictionPoints);
+
+ ASSERT_EQ(TEST_MAX_NUM_PREDICTIONS, pressureRmses.size());
+ EXPECT_FLOAT_EQ(rmse(std::vector<float>{0.0f, 0.0f, -0.5f, 0.5f, 0.0f}), pressureRmses[0]);
+ EXPECT_FLOAT_EQ(rmse(std::vector<float>{0.0f, -0.5f, -0.5f, 1.0f}), pressureRmses[1]);
+ EXPECT_FLOAT_EQ(rmse(std::vector<float>{-0.5f, -0.5f, -0.5f}), pressureRmses[2]);
+ EXPECT_FLOAT_EQ(rmse(std::vector<float>{-0.5f, -0.5f}), pressureRmses[3]);
+ EXPECT_FLOAT_EQ(rmse(std::vector<float>{-0.5f}), pressureRmses[4]);
+}
+
+// --- MotionPredictorMetricsManager tests. ---
+
+// Helper function that instantiates a MetricsManager with the given mock logged AtomFields. Takes
+// vectors of ground truth and prediction points of the same length, and passes these points to the
+// MetricsManager. The format of these vectors is expected to be:
+// • groundTruthPoints: chronologically-ordered ground truth points, with at least 2 elements.
+// • predictionPoints: the first index points to a vector of predictions corresponding to the
+// source ground truth point with the same index.
+// - The first element should be empty, because there are not expected to be predictions until
+// we have received 2 ground truth points.
+// - The last element may be empty, because there will be no future ground truth points to
+// associate with those predictions (if not empty, it will be ignored).
+// - To test all prediction buckets, there should be at least TEST_MAX_NUM_PREDICTIONS non-empty
+// prediction sets (that is, excluding the first and last). Thus, groundTruthPoints and
+// predictionPoints should have size at least TEST_MAX_NUM_PREDICTIONS + 2.
+//
+// The passed-in outAtomFields will contain the logged AtomFields when the function returns.
+//
+// This function returns void so that it can use test assertions.
+void runMetricsManager(const std::vector<GroundTruthPoint>& groundTruthPoints,
+ const std::vector<std::vector<PredictionPoint>>& predictionPoints,
+ std::vector<AtomFields>& outAtomFields) {
+ MotionPredictorMetricsManager metricsManager(TEST_PREDICTION_INTERVAL_NANOS,
+ TEST_MAX_NUM_PREDICTIONS);
+ metricsManager.setMockLoggedAtomFields(&outAtomFields);
+
+ // Validate structure of groundTruthPoints and predictionPoints.
+ ASSERT_EQ(predictionPoints.size(), groundTruthPoints.size());
+ ASSERT_GE(groundTruthPoints.size(), 2u);
+ ASSERT_EQ(predictionPoints[0].size(), 0u);
+ for (size_t i = 1; i + 1 < predictionPoints.size(); ++i) {
+ SCOPED_TRACE(testing::Message() << "i = " << i);
+ ASSERT_EQ(predictionPoints[i].size(), TEST_MAX_NUM_PREDICTIONS);
+ }
+
+ // Pass ground truth points and predictions (for all except first and last ground truth).
+ for (size_t i = 0; i < groundTruthPoints.size(); ++i) {
+ metricsManager.onRecord(makeMotionEvent(groundTruthPoints[i]));
+ if ((i > 0) && (i + 1 < predictionPoints.size())) {
+ metricsManager.onPredict(makeMotionEvent(predictionPoints[i]));
+ }
+ }
+ // Send a stroke-end event to trigger the logging call.
+ metricsManager.onRecord(makeLiftMotionEvent());
+}
+
+// Vacuous test:
+// • Input: no prediction data.
+// • Expectation: no metrics should be logged.
+TEST(MotionPredictorMetricsManagerTest, NoPredictions) {
+ std::vector<AtomFields> mockLoggedAtomFields;
+ MotionPredictorMetricsManager metricsManager(TEST_PREDICTION_INTERVAL_NANOS,
+ TEST_MAX_NUM_PREDICTIONS);
+ metricsManager.setMockLoggedAtomFields(&mockLoggedAtomFields);
+
+ metricsManager.onRecord(makeMotionEvent(
+ GroundTruthPoint{{.position = Eigen::Vector2f(0, 0), .pressure = 0}, .timestamp = 0}));
+ metricsManager.onRecord(makeLiftMotionEvent());
+
+ // Check that mockLoggedAtomFields is still empty (as it was initialized empty), ensuring that
+ // no metrics were logged.
+ EXPECT_EQ(0u, mockLoggedAtomFields.size());
+}
+
+// Perfect predictions test:
+// • Input: constant input events, perfect predictions matching the input events.
+// • Expectation: all error metrics should be zero, or NO_DATA_SENTINEL for "unreported" metrics.
+// (For example, scale-invariant errors are only reported for the final time bucket.)
+TEST(MotionPredictorMetricsManagerTest, ConstantGroundTruthPerfectPredictions) {
+ GroundTruthPoint groundTruthPoint{{.position = Eigen::Vector2f(10.0f, 20.0f), .pressure = 0.6f},
+ .timestamp = TEST_INITIAL_TIMESTAMP};
+
+ // Generate ground truth and prediction points as described by the runMetricsManager comment.
+ std::vector<GroundTruthPoint> groundTruthPoints;
+ std::vector<std::vector<PredictionPoint>> predictionPoints;
+ for (size_t i = 0; i < TEST_MAX_NUM_PREDICTIONS + 2; ++i) {
+ groundTruthPoints.push_back(groundTruthPoint);
+ predictionPoints.push_back(i > 0 ? generateConstantPredictions(groundTruthPoint)
+ : std::vector<PredictionPoint>{});
+ groundTruthPoint.timestamp += TEST_PREDICTION_INTERVAL_NANOS;
+ }
+
+ std::vector<AtomFields> atomFields;
+ runMetricsManager(groundTruthPoints, predictionPoints, atomFields);
+
+ ASSERT_EQ(TEST_MAX_NUM_PREDICTIONS, atomFields.size());
+ // Check that errors are all zero, or NO_DATA_SENTINEL for unreported metrics.
+ for (size_t i = 0; i < atomFields.size(); ++i) {
+ SCOPED_TRACE(testing::Message() << "i = " << i);
+ const AtomFields& atom = atomFields[i];
+ const nsecs_t deltaTimeBucketNanos = TEST_PREDICTION_INTERVAL_NANOS * (i + 1);
+ EXPECT_EQ(deltaTimeBucketNanos / NANOS_PER_MILLIS, atom.deltaTimeBucketMilliseconds);
+ // General errors: reported for every time bucket.
+ EXPECT_EQ(0, atom.alongTrajectoryErrorMeanMillipixels);
+ EXPECT_EQ(0, atom.alongTrajectoryErrorStdMillipixels);
+ EXPECT_EQ(0, atom.offTrajectoryRmseMillipixels);
+ EXPECT_EQ(0, atom.pressureRmseMilliunits);
+ // High-velocity errors: reported only for the last two time buckets.
+ // However, this data has zero velocity, so these metrics should all be NO_DATA_SENTINEL.
+ EXPECT_EQ(NO_DATA_SENTINEL, atom.highVelocityAlongTrajectoryRmse);
+ EXPECT_EQ(NO_DATA_SENTINEL, atom.highVelocityOffTrajectoryRmse);
+ // Scale-invariant errors: reported only for the last time bucket.
+ if (i + 1 == atomFields.size()) {
+ EXPECT_EQ(0, atom.scaleInvariantAlongTrajectoryRmse);
+ EXPECT_EQ(0, atom.scaleInvariantOffTrajectoryRmse);
+ } else {
+ EXPECT_EQ(NO_DATA_SENTINEL, atom.scaleInvariantAlongTrajectoryRmse);
+ EXPECT_EQ(NO_DATA_SENTINEL, atom.scaleInvariantOffTrajectoryRmse);
+ }
+ }
+}
+
+TEST(MotionPredictorMetricsManagerTest, QuadraticPressureLinearPredictions) {
+ // Generate ground truth points.
+ //
+ // Ground truth pressures are a quadratically increasing function from some initial value.
+ const float initialPressure = 0.5f;
+ const float quadraticCoefficient = 0.01f;
+ std::vector<GroundTruthPoint> groundTruthPoints;
+ nsecs_t timestamp = TEST_INITIAL_TIMESTAMP;
+ // As described in the runMetricsManager comment, we should have TEST_MAX_NUM_PREDICTIONS + 2
+ // ground truth points.
+ for (size_t i = 0; i < TEST_MAX_NUM_PREDICTIONS + 2; ++i) {
+ const float pressure = initialPressure + quadraticCoefficient * static_cast<float>(i * i);
+ groundTruthPoints.push_back(
+ GroundTruthPoint{{.position = Eigen::Vector2f(0, 0), .pressure = pressure},
+ .timestamp = timestamp});
+ timestamp += TEST_PREDICTION_INTERVAL_NANOS;
+ }
+
+ // Note: the first index is the source ground truth index, and the second is the prediction
+ // target index.
+ std::vector<std::vector<PredictionPoint>> predictionPoints =
+ generateAllPredictionsByLinearExtrapolation(groundTruthPoints);
+
+ const std::vector<float> pressureErrors =
+ computePressureRmses(groundTruthPoints, predictionPoints);
+
+ // Run test.
+ std::vector<AtomFields> atomFields;
+ runMetricsManager(groundTruthPoints, predictionPoints, atomFields);
+
+ // Check logged metrics match expectations.
+ ASSERT_EQ(TEST_MAX_NUM_PREDICTIONS, atomFields.size());
+ for (size_t i = 0; i < atomFields.size(); ++i) {
+ SCOPED_TRACE(testing::Message() << "i = " << i);
+ const AtomFields& atom = atomFields[i];
+ // Check time bucket delta matches expectation based on index and prediction interval.
+ const nsecs_t deltaTimeBucketNanos = TEST_PREDICTION_INTERVAL_NANOS * (i + 1);
+ EXPECT_EQ(deltaTimeBucketNanos / NANOS_PER_MILLIS, atom.deltaTimeBucketMilliseconds);
+ // Check pressure error matches expectation.
+ EXPECT_NEAR(static_cast<int>(1000 * pressureErrors[i]), atom.pressureRmseMilliunits, 1);
+ }
+}
+
+TEST(MotionPredictorMetricsManagerTest, QuadraticPositionLinearPredictionsGeneralErrors) {
+ // Generate ground truth points.
+ //
+ // Each component of the ground truth positions are an independent quadratically increasing
+ // function from some initial value.
+ const Eigen::Vector2f initialPosition(200, 300);
+ const Eigen::Vector2f quadraticCoefficients(-2, 3);
+ std::vector<GroundTruthPoint> groundTruthPoints;
+ nsecs_t timestamp = TEST_INITIAL_TIMESTAMP;
+ // As described in the runMetricsManager comment, we should have TEST_MAX_NUM_PREDICTIONS + 2
+ // ground truth points.
+ for (size_t i = 0; i < TEST_MAX_NUM_PREDICTIONS + 2; ++i) {
+ const Eigen::Vector2f position =
+ initialPosition + quadraticCoefficients * static_cast<float>(i * i);
+ groundTruthPoints.push_back(
+ GroundTruthPoint{{.position = position, .pressure = 0.5}, .timestamp = timestamp});
+ timestamp += TEST_PREDICTION_INTERVAL_NANOS;
+ }
+
+ // Note: the first index is the source ground truth index, and the second is the prediction
+ // target index.
+ std::vector<std::vector<PredictionPoint>> predictionPoints =
+ generateAllPredictionsByLinearExtrapolation(groundTruthPoints);
+
+ std::vector<GeneralPositionErrors> generalPositionErrors =
+ computeGeneralPositionErrors(groundTruthPoints, predictionPoints);
+
+ // Run test.
+ std::vector<AtomFields> atomFields;
+ runMetricsManager(groundTruthPoints, predictionPoints, atomFields);
+
+ // Check logged metrics match expectations.
+ ASSERT_EQ(TEST_MAX_NUM_PREDICTIONS, atomFields.size());
+ for (size_t i = 0; i < atomFields.size(); ++i) {
+ SCOPED_TRACE(testing::Message() << "i = " << i);
+ const AtomFields& atom = atomFields[i];
+ // Check time bucket delta matches expectation based on index and prediction interval.
+ const nsecs_t deltaTimeBucketNanos = TEST_PREDICTION_INTERVAL_NANOS * (i + 1);
+ EXPECT_EQ(deltaTimeBucketNanos / NANOS_PER_MILLIS, atom.deltaTimeBucketMilliseconds);
+ // Check general position errors match expectation.
+ EXPECT_NEAR(static_cast<int>(1000 * generalPositionErrors[i].alongTrajectoryErrorMean),
+ atom.alongTrajectoryErrorMeanMillipixels, 1);
+ EXPECT_NEAR(static_cast<int>(1000 * generalPositionErrors[i].alongTrajectoryErrorStd),
+ atom.alongTrajectoryErrorStdMillipixels, 1);
+ EXPECT_NEAR(static_cast<int>(1000 * generalPositionErrors[i].offTrajectoryRmse),
+ atom.offTrajectoryRmseMillipixels, 1);
+ }
+}
+
+// Counterclockwise regular octagonal section test:
+// • Input – ground truth: constantly-spaced input events starting at a trajectory pointing exactly
+// rightwards, and rotating by 45° counterclockwise after each input.
+// • Input – predictions: simple linear extrapolations of previous two ground truth points.
+//
+// The code below uses the following terminology to distinguish references to ground truth events:
+// • Source ground truth: the most recent ground truth point received at the time the prediction
+// was made.
+// • Target ground truth: the ground truth event that the prediction was attempting to match.
+TEST(MotionPredictorMetricsManagerTest, CounterclockwiseOctagonGroundTruthLinearPredictions) {
+ // Select a stroke velocity that exceeds the high-velocity threshold of 1100 px/sec.
+ // For an input rate of 240 hz, 1100 px/sec * (1/240) sec/input ≈ 4.58 pixels per input.
+ const float strokeVelocity = 10; // pixels per input
+
+ // As described in the runMetricsManager comment, we should have TEST_MAX_NUM_PREDICTIONS + 2
+ // ground truth points.
+ std::vector<GroundTruthPoint> groundTruthPoints = generateCircularArcGroundTruthPoints(
+ /*initialPosition=*/Eigen::Vector2f(100, 100),
+ /*initialAngle=*/M_PI_2,
+ /*velocity=*/strokeVelocity,
+ /*turningAngle=*/-M_PI_4,
+ /*numPoints=*/TEST_MAX_NUM_PREDICTIONS + 2);
+
+ std::vector<std::vector<PredictionPoint>> predictionPoints =
+ generateAllPredictionsByLinearExtrapolation(groundTruthPoints);
+
+ std::vector<GeneralPositionErrors> generalPositionErrors =
+ computeGeneralPositionErrors(groundTruthPoints, predictionPoints);
+
+ // Run test.
+ std::vector<AtomFields> atomFields;
+ runMetricsManager(groundTruthPoints, predictionPoints, atomFields);
+
+ // Check logged metrics match expectations.
+ ASSERT_EQ(TEST_MAX_NUM_PREDICTIONS, atomFields.size());
+ for (size_t i = 0; i < atomFields.size(); ++i) {
+ SCOPED_TRACE(testing::Message() << "i = " << i);
+ const AtomFields& atom = atomFields[i];
+ const nsecs_t deltaTimeBucketNanos = TEST_PREDICTION_INTERVAL_NANOS * (i + 1);
+ EXPECT_EQ(deltaTimeBucketNanos / NANOS_PER_MILLIS, atom.deltaTimeBucketMilliseconds);
+
+ // General errors: reported for every time bucket.
+ EXPECT_NEAR(static_cast<int>(1000 * generalPositionErrors[i].alongTrajectoryErrorMean),
+ atom.alongTrajectoryErrorMeanMillipixels, 1);
+ // We allow for some floating point error in standard deviation (0.02 pixels).
+ EXPECT_NEAR(1000 * generalPositionErrors[i].alongTrajectoryErrorStd,
+ atom.alongTrajectoryErrorStdMillipixels, 20);
+ // All position errors are equal, so the standard deviation should be approximately zero.
+ EXPECT_NEAR(0, atom.alongTrajectoryErrorStdMillipixels, 20);
+ // Absolute value for RMSE, since it must be non-negative.
+ EXPECT_NEAR(static_cast<int>(1000 * generalPositionErrors[i].offTrajectoryRmse),
+ atom.offTrajectoryRmseMillipixels, 1);
+
+ // High-velocity errors: reported only for the last two time buckets.
+ //
+ // Since our input stroke velocity is chosen to be above the high-velocity threshold, all
+ // data contributes to high-velocity errors, and thus high-velocity errors should be equal
+ // to general errors (where reported).
+ //
+ // As above, use absolute value for RMSE, since it must be non-negative.
+ if (i + 2 >= atomFields.size()) {
+ EXPECT_NEAR(static_cast<int>(
+ 1000 * std::abs(generalPositionErrors[i].alongTrajectoryErrorMean)),
+ atom.highVelocityAlongTrajectoryRmse, 1);
+ EXPECT_NEAR(static_cast<int>(1000 *
+ std::abs(generalPositionErrors[i].offTrajectoryRmse)),
+ atom.highVelocityOffTrajectoryRmse, 1);
+ } else {
+ EXPECT_EQ(NO_DATA_SENTINEL, atom.highVelocityAlongTrajectoryRmse);
+ EXPECT_EQ(NO_DATA_SENTINEL, atom.highVelocityOffTrajectoryRmse);
+ }
+
+ // Scale-invariant errors: reported only for the last time bucket, where the reported value
+ // is the aggregation across all time buckets.
+ //
+ // The MetricsManager stores mMaxNumPredictions recent ground truth segments. Our ground
+ // truth segments here all have a length of strokeVelocity, so we can convert general errors
+ // to scale-invariant errors by dividing by `strokeVelocty * TEST_MAX_NUM_PREDICTIONS`.
+ //
+ // As above, use absolute value for RMSE, since it must be non-negative.
+ if (i + 1 == atomFields.size()) {
+ const float pathLength = strokeVelocity * TEST_MAX_NUM_PREDICTIONS;
+ std::vector<float> alongTrajectoryAbsoluteErrors;
+ std::vector<float> offTrajectoryAbsoluteErrors;
+ for (size_t j = 0; j < TEST_MAX_NUM_PREDICTIONS; ++j) {
+ alongTrajectoryAbsoluteErrors.push_back(
+ std::abs(generalPositionErrors[j].alongTrajectoryErrorMean));
+ offTrajectoryAbsoluteErrors.push_back(
+ std::abs(generalPositionErrors[j].offTrajectoryRmse));
+ }
+ EXPECT_NEAR(static_cast<int>(1000 * average(alongTrajectoryAbsoluteErrors) /
+ pathLength),
+ atom.scaleInvariantAlongTrajectoryRmse, 1);
+ EXPECT_NEAR(static_cast<int>(1000 * average(offTrajectoryAbsoluteErrors) / pathLength),
+ atom.scaleInvariantOffTrajectoryRmse, 1);
+ } else {
+ EXPECT_EQ(NO_DATA_SENTINEL, atom.scaleInvariantAlongTrajectoryRmse);
+ EXPECT_EQ(NO_DATA_SENTINEL, atom.scaleInvariantOffTrajectoryRmse);
+ }
+ }
+}
+
+} // namespace
+} // namespace android