44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
from Qtorch.Models.Qmlp import Qmlp
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from Qtorch.Models.Qcnn import QCNN
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from Qfunctions.divSet import divSet
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from Qfunctions.loaData import load_data
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from Qfunctions.saveToxlsx import save_to_xlsx as save_to_xlsx
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import string
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def main():
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projet_name = '20241130 EMG-write' # 输入元数据文件夹名称
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label_names = list(string.ascii_uppercase) # 请在[]内输入每一个分类的名称
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print(label_names)
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data = load_data(projet_name, label_names, isDir=False, fileClass='xlsx')
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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= 0.3
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)
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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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# hidden_layers = [128],
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# dropout_rate=0
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# )
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model = QCNN(
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X_train=X_train, X_test=X_test, y_train=y_train, y_test= y_test,
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dropout_rate=0
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)
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pca_2d, pca_3d = model.get_PCA()
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model.fit(300)
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cm = model.get_cm()
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epoch_data = model.get_epoch_data()
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save_to_xlsx(project_name=projet_name, file_name="pca_2d", data=pca_2d)
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save_to_xlsx(project_name=projet_name, file_name="pca_3d", data=pca_3d)
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save_to_xlsx(project_name=projet_name, file_name="cm", data=cm )
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save_to_xlsx(project_name=projet_name, file_name="acc_and_loss", data=epoch_data)
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print("Done")
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if __name__ == '__main__':
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main()
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