XDriveBar - Display drive buttons in a fixed toolbar

本文介绍了一个基于2xExplorer的驱动栏组件实现,该组件可在应用程序中提供快速访问计算机驱动器的功能。通过使用CXDriveBar类,可以轻松地在应用中集成垂直或水平的驱动栏,并能自动更新连接的USB设备。
 

Introduction

One of my favorite tools is the free 2xExplorer. It offers a very handy dual pane + tree view that really helps when you are working in several different directories. You can see some of the ways you can use 2xExplorer here. Anyway, one of the interesting things about 2xExplorer is that it has a drive bar next to the tree view, with a button for each drive that will take you to that drive. This is much faster than scrolling through a tree to get to a drive. Please note that the drive bar presented here is a fixed toolbar - not movable or dockable by the user.

The Demo App

The demo app shows two drive bars, one vertical and one horizontal:

screenshot

The buttons will show the drive label on the tooltip:

screenshot

The dialog box can be resized, and the drive bars will also resize:

screenshot

When a new drive is added (for example, a USB disk drive), the drive bars are automatically updated via the WM_DEVICECHANGE message:

screenshot

Implementation Notes

CXDriveBar is derived from CXToolBar, which keeps track of the button locations and creates new CXPStyleButtonST buttons when necessary. The CXDriveBar class loads the system image list, determines what drives exist, and adds the drives to the drive bar via CXToolBar::AddButton().

The code in XDriveBarTestDlg.cpp takes care of creating the drive bars, and also contains the WM_DEVICECHANGE handler (this message is only sent to top-level windows). When a removable device (like a USB disk) is added or removed, several WM_DEVICECHANGE messages are sent. The demo app handles these messages by starting a 1½ second timer when it receives each WM_DEVICECHANGE message, so that the arrival of each message effectively restarts the timer. After the last WM_DEVICECHANGE message, the 1½ second timer ensures that the device is fully installed before updating the drive bars.

Because I wanted an etched look for the border of the drive bar, I decided to use a picture control for the frame, with the color set to etched. The picture control also serves as a placeholder on the dialog template for the drive bar.

How To Use

To integrate CXDriveBar into your app, you first need to add the following files to your project:

  • SystemImageList.cpp
  • SystemImageList.h
  • ThemeHelperST.cpp
  • ThemeHelperST.h
  • XBtnST.cpp
  • XBtnST.h
  • XDriveBar.cpp
  • XDriveBar.h
  • XPStyleButtonST.cpp
  • XPStyleButtonST.h
  • XToolBar.cpp
  • XToolBar.h

Next, include header file XDriveBar.h in appropriate project files (usually, dialog header files). You will probably want to copy and modify some of the code in XDriveBarTestDlg.cpp, such as CXDriveBarTestDlg::CreateDriveBars(), CXDriveBarTestDlg::OnDriveSelected(), CXDriveBarTestDlg::OnDeviceChange(), and CXDriveBarTestDlg::OnTimer().

Revision History

Version 1.0 - 2003 August 11

  • Initial public release.

Acknowledgments

Usage

This software is released into the public domain. You are free to use it in any way you like. If you modify it or extend it, please to consider posting new code here for everyone to share. This software is provided "as is" with no expressed or implied warranty. I accept no liability for any damage or loss of business that this software may cause.

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

About the Author

Hans Dietrich


Mvp
I attended St. Michael's College of the University of Toronto, with the intention of becoming a priest. A friend in the University's Computer Science Department got me interested in programming, and I have been hooked ever since.

Recently, I have moved to Los Angeles where I am doing consulting and development work.

Occupation: Software Developer (Senior)
Location: United States United States
提供了基于BP(Back Propagation)神经网络结合PID(比例-积分-微分)控制策略的Simulink仿真模型。该模型旨在实现对杨艺所著论文《基于S函数的BP神经网络PID控制器及Simulink仿真》中的理论进行实践验证。在Matlab 2016b环境下开发,经过测试,确保能够正常运行,适合学习和研究神经网络在控制系统中的应用。 特点 集成BP神经网络:模型中集成了BP神经网络用于提升PID控制器的性能,使之能更好地适应复杂控制环境。 PID控制优化:利用神经网络的自学习能力,对传统的PID控制算法进行了智能调整,提高控制精度和稳定性。 S函数应用:展示了如何在Simulink中通过S函数嵌入MATLAB代码,实现BP神经网络的定制化逻辑。 兼容性说明:虽然开发于Matlab 2016b,但理论上兼容后续版本,可能会需要调整少量配置以适配不同版本的Matlab。 使用指南 环境要求:确保你的电脑上安装有Matlab 2016b或更高版本。 模型加载: 下载本仓库到本地。 在Matlab中打开.slx文件。 运行仿真: 调整模型参数前,请先熟悉各模块功能和输入输出设置。 运行整个模型,观察控制效果。 参数调整: 用户可以自由调节神经网络的层数、节点数以及PID控制器的参数,探索不同的控制性能。 学习和修改: 通过阅读模型中的注释和查阅相关文献,加深对BP神经网络与PID控制结合的理解。 如需修改S函数内的MATLAB代码,建议有一定的MATLAB编程基础。
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