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Makefile经典教程(入门必备) - C/C++ - 清泛网移动版 - 专注C/C++及内核技术
...述)。
五、make的参数
下面列举了所有GNU make 3.80版的参数定义。其它版本和产商的make大同小异,不过其它产商的make的具体参数还是请参考各自的产品文档。
“-b”
“-m”
这两个参数的作用是忽略和其它版本mak...
BLE(四)嗅探工具 - 创客硬件开发 - 清泛IT社区,为创新赋能!
...,8KB RAM和其他功能强大的配套特征及外设。CC2540有两种版本:CC2540F128 / F256,分别为128和256 KB的闪存,结合TI的低功耗蓝牙协议栈,CC2540F128 / F256形成了市场上最灵活,性价比也最高的单模式蓝牙BLE解决方案。
CC2540 USB Dongle的实...
为AppInventor2开发自己的拓展(Extension) - App Inventor 2 拓展 - 清泛IT社区,为创新赋能!
...只能运行于安卓设备上,对于iOS设备需要使用swift开发iOS版本的拓展。环境配置安装好 Java开发环境 以及 Ant编译环境,这里以Windows为例,供参考:安装完JDK后配置环境变量 计算机(右键)→属性→高级系统设置→高级→环境变...
.prop() vs .attr()
...epts. Moving to prop and attr was meant to de-conflate them. Briefly in v1.6.0 jQuery went too far in that regard, but functionality was quickly added back to attr to handle the common situations where people use attr when technically they should use prop.
...
MVC演化史 - 更多技术 - 清泛网 - 专注C/C++及内核技术
...发工作,为了适应更复杂的逻辑,开发了Classic MVC的改进版,也就是Application Model MVC,在原有架构基础上引入了Application Model,如下图所示:
Application Model MVC
图解:Application Model在Model和View、Controller之间扮演着一个中继者的...
std::function vs template
...
gcc 4.7.2: calc1: 1.1 seconds
gcc 4.7.2: calc2: 6.0 seconds
VS2012 CTPNov calc1: 0.8 seconds
VS2012 CTPNov calc2: 2.0 seconds
VS2015 (14.0.23.107) calc1: 1.1 seconds
VS2015 (14.0.23.107) calc2: 1.5 seconds
MinGW (4.7.2) calc1: 0.9...
O2O江湖:2015大洗牌 2016 BAT等巨头将“肉搏” - 资讯 - 清泛网 - 专注C/C++及内核技术
...回家滴滴推出的跨城顺风车,便利老人的滴滴出租车敬老版,方便上班族的滴滴巴士等;Uber更是天马行空,推出首个电动车日,一键呼叫甜品、萌犬,哦,你还可以呼叫直升机。
但这样的舞姿却戴上了沉重的镣铐,2015年10月滴...
初窥InnoDB的Memcached插件 - 大数据 & AI - 清泛网 - 专注C/C++及内核技术
...整性,我们选择从源代码安装MySQL,需要注意的是早期的版本有内存泄漏,所以推荐安装最新的稳定版,激活WITH_INNODB_MEMCACHED即可:
shell> groupadd mysql
shell> useradd -r -g mysql mysql
shell> tar zxvf mysql-<VERSION>.tar.gz
shell> cd mysql-5.6.13
sh...
How do I export UIImage array as a movie?
...ted in ios6
/*
[videoWriter finishWritingWithCompletionHandler:...]; //ios 6.0+
*/
You’ll still have to fill-in a lot of blanks, but I think that the only really hard remaining part is getting a pixel buffer from a CGImage:
- (CVPixelBufferRef) newPixelBufferFromCGImage: (CGImageRef) image
{
...
How to calculate moving average using NumPy?
...ame example above would also yield:
list(mov_avg(x, 2))
# [4.0, 5.5, 9.0, 6.0, 1.5, 3.0, 3.0, 0.5, 1.0]
So what is being done at each step is to take the inner product between the array of ones and the current window. In this case the multiplication by np.ones(w) is superfluous given that we are...