# -*- coding: UTF-8 -*- ''' Created on 2017��12��13�� ''' #用于测试python读取matlab中的mat文件 # scipy.io.loadmat(file_name, mdict=None, appendmat=True, **kwargs) # file_name : MATLAB文件名 # appendmat : 如果是true的话,后面就不用加上.mat的后缀了 # result_dict : 返回的是一个字典,变量名作为键,载入的矩阵作为值。 from scipy.io import loadmat import matplotlib.pyplot as plt import numpy as np result_dict=loadmat("DynamicFeature") #查看有返回的类型和他的键 print("type of result:",type(result_dict)) print("keys:",result_dict.keys()) # ('type of result:', <type 'dict'>) # ('keys:', ['DynamicFeature', '__version__', '__header__', '__globals__']) #查看键的内容 #DynamicFeature print("DynamicFeature:",result_dict['DynamicFeature']) DynamicFeatureData = result_dict['DynamicFeature'] print("type of DynamicFeature:",type(result_dict['DynamicFeature'])) print("shape of DynamicFeature:",result_dict['DynamicFeature'].shape) print DynamicFeatureData[:,0] #所有行,第一列 # 数据的矩阵也是很标准的ndarray x = np.linspace(1, 62, 62) print x plt.plot(x,DynamicFeatureData[:,0],color="red",linewidth=2) plt.show()
可以参考这个博客: http://blog.csdn.net/lenbow/article/details/52152766#comments
http://blog.csdn.net/data8866/article/details/60960889
tensorflow学习经历https://www.zhihu.com/question/41667903?from=profile_question_card
极客学院http://wiki.jikexueyuan.com/project/tensorflow-zh/personal.html
http://m.blog.csdn.net/u011974639/article/details/75363565 TensorFlow实战:Chapter-3(CNN-1-卷积神经网络简介)比较重要!
一维卷积使用http://www.uml.org.cn/ai/201711132.asp?artid=20051
ROC: http://blog.csdn.net/zdy0_2004/article/details/44948511
数据读取python读取txt mat文件(matlab中的) http://www.jianshu.com/p/da4ed6407be7
http://blog.csdn.net/xierhacker/article/details/53201308 [重要]-------这块要实际操作一下!-----没什么问题!