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@ -61,6 +61,12 @@ def load_xlsx(fileName, labelName, max_row_length = 1000, fill_rule = None):
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# 提取偶数列
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# 提取偶数列
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features = df.iloc[0:, 1::2]
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features = df.iloc[0:, 1::2]
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# 计算变化率
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first_value = features.iloc[0, :] # 获取第一行的数据
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features_pct_change = (features - first_value) / first_value
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features = features_pct_change
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features.dropna(inplace=True)
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features.dropna(inplace=True)
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features.reset_index(drop=True, inplace=True)
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features.reset_index(drop=True, inplace=True)
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26
main.py
26
main.py
@ -11,7 +11,7 @@ def main():
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label_names =["Accuracy", "Compress", "Distance", "Loss", "Metal", "Python"]
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label_names =["Accuracy", "Compress", "Distance", "Loss", "Metal", "Python"]
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data = dLoader(projet_name, label_names, isDir=False)
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data = dLoader(projet_name, label_names, isDir=False)
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X_train, X_test, y_train, y_test, encoder = divSet(
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X_train, X_test, y_train, y_test, encoder = divSet(
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data=data, labels=label_names, test_size= 0.5
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data=data, labels=label_names, test_size= 0.2
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)
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)
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print(y_train)
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print(y_train)
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@ -35,20 +35,20 @@ def main():
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# model = Qmlp(
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model = Qmlp(
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# X_train=X_train, X_test=X_test, y_train=y_train, y_test= y_test,
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X_train=X_train, X_test=X_test, y_train=y_train, y_test= y_test,
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# hidden_layers=[32, 32, 32],
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hidden_layers=[64, 64],
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# dropout_rate=0
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dropout_rate=0
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# )
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)
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# model.fit(100)
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model.fit(100)
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# cm = model.get_cm()
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cm = model.get_cm()
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# epoch_data = model.get_epoch_data()
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epoch_data = model.get_epoch_data()
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# from Qfunctions.saveToxlsx import save_to_xlsx as stx
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from Qfunctions.saveToxlsx import save_to_xlsx as stx
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# stx(project_name=projet_name, file_name="cm", data=cm)
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stx(project_name=projet_name, file_name="cm", data=cm)
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# stx(project_name=projet_name, file_name="acc_and_loss", data=epoch_data)
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stx(project_name=projet_name, file_name="acc_and_loss", data=epoch_data)
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# print("Done")
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print("Done")
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if __name__ == '__main__':
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if __name__ == '__main__':
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main()
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main()
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