能将ELF&AFX 文件转换成二进制文件的解析源码

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本实例是在LabWindows环境下，打开windows系统下的ini文件，并读取出其中的信息。-This example is a LabWindows environment, open the windows system, under the ini files, and read out the information.

一个基于ucos的文件管理系统 可以支持cf卡 硬盘等存储器 但是对于单独的flash芯片还需要自己编写硬件的底层驱动-based document management system can support cf memory card drives, etc. But for a separate flash chip also need to prepare themselves to the bottom of the hardware drivers

批量替换,替换目录下的全部文件,开发平台: Microsoft Visual Studio .NET 2003-volume replacement, the replacement directory of all documents, development platforms : Microsoft Visual Studio.NET 2003

实现WINDOWS写字板。实现了很多功能。 解压密码：www.programsalon.com-achieve WINDOWS tablet. Achieving a lot of functions. Extracting Password : www.programsalon.com

To break passoword in an excel file

用VC读取excel 能够很好的将常用的数据格式中的数据读取出来-Read excel with VC can be a very good data format commonly used to read out the data in the

比较两个二进制文件 不同的地方显示不同颜色-to compare 2 bin files,it show different color in different position.

本软件可以将frotran程序的框架全部列出来，能让程序之间的互相调用关系看起来一目了然，同时在一个大型的程序中间查找变量起来特别的方便，不仅可以显示出所在的行数，而且，在查找到的内容里面双击就可以到达相应的位置，对用fortran编程的人来说，我认为还是一个不错的工具。-the software can be frotran the procedures set out in the framework of all, procedures can call among the relations seem clear, at the same time a large-scale search procedures intermediate variables is particularly convenient, not only can demonstrate that the line number, but in search of the contents inside can be reached double-click on the corresponding position, using FORTRAN programming to the people, I believe it is a good tool.

应用背景开始是做movielense的数据，可以把原始数据任意划分为train.dat和test.dat，主要是为了做验证实验。非常简单明了，适合初学者看看，如果不喜欢，请轻喷。关键技术# -*- coding: cp936 -*- from sklearn import cross_validation c = [] filename = r"Raw.data" #原始数据 out_train = open(r"train.txt","w") #训练集 out_test = open(r"test.txt","w") #测试集 for line in open(filename):     items = line.strip().split(",")      c.append(items)   c_train,c_test = cross_validation.train_test_split(c,test_size=0.1)#size =你需要的比例 for i in c_train:     out_train.write(",".join(i)+" ") for i in c_test:     out_test.write(",".join(i)+" ")