examples/force_forecasting.py

import numpy as np

from preprocessor.feature_extractor import MotokoFeatureExtractor


def forecast_force(signal: dict[str, np.ndarray]) -> np.ndarray:
    extractor = MotokoFeatureExtractor.from_config("preprocessor/preprocessor_config.json")
    features = extractor(signal)
    force_slice = features["input_values"][:, :3]
    return force_slice[-10:].mean(axis=0)


if __name__ == "__main__":
    signal = {
        "force": np.random.randn(256, 3).astype(np.float32),
        "torque": np.random.randn(256, 3).astype(np.float32),
        "pressure": np.random.randn(256, 16).astype(np.float32),
        "vibration": np.random.randn(256, 6).astype(np.float32),
    }
    print("next_force:", forecast_force(signal))