from Qtorch.Models.Qcnn import QCNN
from Qfunctions.divSet import divSet
from Qfunctions.loaData import load_data
from Qfunctions.saveToxlsx import save_to_xlsx as save_to_xlsx

def main():
  # 输入元数据文件夹名称
  projet_name = '20241228 Write'                                                                
  # 请在[]内输入每一个分类的名称
  label_names = ['I', 'L', 'O', 'V', 'E', 'F', 'J', 'U', 'T']                                   
  print(label_names)
  data = load_data(projet_name, label_names, isDir=False, fileClass='xlsx')
  X_train, X_test, y_train, y_test, encoder = divSet(
    data=data, labels=label_names, test_size= 0.3
  )
  
  # model = Qmlp(
  #   X_train=X_train, X_test=X_test, y_train=y_train, y_test= y_test,
  #   hidden_layers = [128],
  #   dropout_rate=0
  #   )

  model = QCNN(
     X_train=X_train, X_test=X_test, y_train=y_train, y_test= y_test,
     dropout_rate=0
  )
  
  pca_2d, pca_3d = model.get_PCA()

  model.fit(300)
  
  cm = model.get_cm()
  epoch_data = model.get_epoch_data()

  save_to_xlsx(project_name=projet_name, file_name="pca_2d", data=pca_2d)
  save_to_xlsx(project_name=projet_name, file_name="pca_3d", data=pca_3d)
  save_to_xlsx(project_name=projet_name, file_name="cm", data=cm )
  save_to_xlsx(project_name=projet_name, file_name="acc_and_loss", data=epoch_data)

  print("Done")
  
if __name__ == '__main__':
  main()