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@@ -49,9 +49,8 @@ def model_prediction_bp():
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feature_scaler, target_scaler = get_scaler_model_from_mongo(args)
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scaled_pre_x = dh.pre_data_handler(pre_data, feature_scaler, opt, bp_data=True)
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bp.get_model(args)
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- # result = bp.predict(scaled_pre_x, args)
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- result = list(chain.from_iterable(target_scaler.inverse_transform([bp.predict(scaled_pre_x).flatten()])))
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- pre_data['power_forecast'] = result[:len(pre_data)]
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+ res = list(chain.from_iterable(target_scaler.inverse_transform([bp.predict(scaled_pre_x).flatten()])))
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+ pre_data['power_forecast'] = res[:len(pre_data)]
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pre_data['farm_id'] = 'J00083'
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pre_data['cdq'] = 1
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pre_data['dq'] = 1
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David