clear;clc
matrix1 = magic(5);
matrix2 = magic(6);
save matData.mat

import scipy.io
data = scipy.io.loadmat('matData.mat') # 读取mat文件
# print(data.keys())  # 查看mat文件中的所有变量
print(data['matrix1'])
print(data['matrix2'])
matrix1 = data['matrix1'] 
matrix2 = data['matrix2']
print(matrix1)
print(matrix2)
scipy.io.savemat('matData2.mat',{'matrix1':matrix1, 'matrix2':matrix2}) # 写入mat文件

#利用h5py读取-v7.3的.mat文件：
import h5py
dict_data = h5py.File('***.mat')  #在Python中读取的.mat为字典格式
array_data = dict_data['array_name'] 
#其中的array_name为在保存为.mat之前的真正变量名，如 MATLAB命令：save ***.mat array_name -v7.3

data_train = h5py.File('train_order6.mat','r')
input_train = data_train['z_wrap']
input_train = np.transpose(input_train,(0,2,1)) #The shape is changed to be consistent with tensoflow [25000,128,128]->[25000,128,128]
input_train = np.expand_dims(input_train,axis=3) #[25000,128,128]->[25000,128,128,1]
label_train = data_train['z_allRegion']
label_train = np.transpose(label_train,(0,3,2,1))#The shape is changed to be consistent with tensoflow [25000,11,128,128]->[25000,128,128,11]