forked from EEBD_AI/wgz_forecast
26 lines
509 B
Python
26 lines
509 B
Python
import joblib
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import numpy as np
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def load_model(path):
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gbm = joblib.load(path)
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return gbm
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def pv_forecast(inputs: np.ndarray, model):
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"""_summary_
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Args:
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inputs (np.ndarray): 输入序列
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model (_type_): _description_
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"""
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out = model.predict([inputs])
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return out
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# if __name__ == '__main__':
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# model = load_model('models/pv_pred.joblib')
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# inputs = np.random.randn(24)
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#
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# print(inputs.shape)
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# out = pv_forecast(inputs, model)
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# print(out) |