import joblib
import numpy as np


def load_model(path):
    gbm = joblib.load(path)
    return gbm

def pv_forecast(inputs: np.ndarray, model):
    """_summary_

    Args:
        inputs (np.ndarray): 输入序列
        model (_type_): _description_
    """
    out = model.predict([inputs])
    return out


# if __name__ == '__main__':
#     model = load_model('models/pv_pred.joblib')
#     inputs = np.random.randn(24)
#
#     print(inputs.shape)
#     out = pv_forecast(inputs, model)
#     print(out)