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@ -58,6 +58,7 @@ def to_data(file_dir, excel):
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df = (df - min_value) / (max_value - min_value)
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df = (df - min_value) / (max_value - min_value)
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dataset_x, dataset_y = create_dataset(df, DAYS_FOR_TRAIN)
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dataset_x, dataset_y = create_dataset(df, DAYS_FOR_TRAIN)
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print()
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print('len(dataset_x:)', len(dataset_x))
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print('len(dataset_x:)', len(dataset_x))
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# 划分训练集和测试集
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# 划分训练集和测试集
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@ -91,7 +92,7 @@ def to_data(file_dir, excel):
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train_loss.append(loss.item())
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train_loss.append(loss.item())
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b = time.time()
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b = time.time()
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print(excel,industry,'训练用时',b-a)
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print(excel, industry, '训练用时', b - a)
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# 保存模型
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# 保存模型
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# torch.save(model.state_dict(),save_filename)
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# torch.save(model.state_dict(),save_filename)
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@ -121,7 +122,7 @@ def to_data(file_dir, excel):
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result_eight = pd.DataFrame({'pred_test': pred_test[-31:], 'real': df[-31:]})
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result_eight = pd.DataFrame({'pred_test': pred_test[-31:], 'real': df[-31:]})
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target = (result_eight['pred_test'][-3:].sum() - result_eight['real'][-3:].sum()) / result_eight[
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target = (result_eight['pred_test'][-3:].sum() - result_eight['real'][-3:].sum()) / result_eight[
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'real'].sum()
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'real'].sum()
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print(target)
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# print(target)
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with open(fr'.\cws_to_data\{excel[:2]}.txt', 'a', encoding='utf-8') as f:
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with open(fr'.\cws_to_data\{excel[:2]}.txt', 'a', encoding='utf-8') as f:
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tmp_data = {'city': excel[:2], 'industry': industry, "month_deviation_rate": round(target, 5)}
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tmp_data = {'city': excel[:2], 'industry': industry, "month_deviation_rate": round(target, 5)}
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f.write(str(tmp_data) + "\n")
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f.write(str(tmp_data) + "\n")
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