import numpy as np

from preprocessor.feature_extractor import MotokoFeatureExtractor


MATERIALS = ["metal", "rubber", "wood", "fabric"]


def predict_material(signal: dict[str, np.ndarray]) -> str:
    extractor = MotokoFeatureExtractor.from_config("preprocessor/preprocessor_config.json")
    features = extractor(signal)
    index = int(abs(features["input_values"].sum())) % len(MATERIALS)
    return MATERIALS[index]


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("material:", predict_material(signal))