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+/*
+ * Copyright 2022 Google LLC
+ *
+ * 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.
+ */
+
+#ifndef INK_STROKE_MODELER_INTERNAL_PREDICTION_KALMAN_FILTER_AXIS_PREDICTOR_H_
+#define INK_STROKE_MODELER_INTERNAL_PREDICTION_KALMAN_FILTER_AXIS_PREDICTOR_H_
+
+#include <memory>
+
+#include "ink_stroke_modeler/internal/prediction/kalman_filter/kalman_filter.h"
+
+namespace ink {
+namespace stroke_model {
+
+// Class to predict on axis.
+//
+// This predictor use one instance of Kalman filter to predict one dimension of
+// stylus movement.
+class AxisPredictor {
+ public:
+ AxisPredictor(double process_noise, double measurement_noise,
+ int min_stable_iteration);
+
+ // Return true if the underlying Kalman filter is stable.
+ bool Stable() const;
+
+ // Reset the underlying Kalman filter.
+ void Reset();
+
+ // Update the predictor with a new observation.
+ void Update(double observation);
+
+ // Returns the number of times Update() has been called since the last time
+ // the AxisPredictor was reset.
+ int NumIterations() const;
+
+ // Get the predicted values from the underlying Kalman filter.
+ double GetPosition() const;
+ double GetVelocity() const;
+ double GetAcceleration() const;
+ double GetJerk() const;
+
+ private:
+ std::unique_ptr<KalmanFilter> kalman_filter_;
+};
+
+} // namespace stroke_model
+} // namespace ink
+
+#endif // INK_STROKE_MODELER_INTERNAL_PREDICTION_KALMAN_FILTER_AXIS_PREDICTOR_H_