Harang Richard, Bonnet Guillaume, Petzold Linda R
Department of Computer Science, University of California, Santa Barbara, CA, USA.
BMC Res Notes. 2012 Mar 26;5:163. doi: 10.1186/1756-0500-5-163.
Wavelets have proven to be a powerful technique for the analysis of periodic data, such as those that arise in the analysis of circadian oscillators. While many implementations of both continuous and discrete wavelet transforms are available, we are aware of no software that has been designed with the nontechnical end-user in mind. By developing a toolkit that makes these analyses accessible to end users without significant programming experience, we hope to promote the more widespread use of wavelet analysis.
We have developed the WAVOS toolkit for wavelet analysis and visualization of oscillatory systems. WAVOS features both the continuous (Morlet) and discrete (Daubechies) wavelet transforms, with a simple, user-friendly graphical user interface within MATLAB. The interface allows for data to be imported from a number of standard file formats, visualized, processed and analyzed, and exported without use of the command line. Our work has been motivated by the challenges of circadian data, thus default settings appropriate to the analysis of such data have been pre-selected in order to minimize the need for fine-tuning. The toolkit is flexible enough to deal with a wide range of oscillatory signals, however, and may be used in more general contexts.
We have presented WAVOS: a comprehensive wavelet-based MATLAB toolkit that allows for easy visualization, exploration, and analysis of oscillatory data. WAVOS includes both the Morlet continuous wavelet transform and the Daubechies discrete wavelet transform. We have illustrated the use of WAVOS, and demonstrated its utility for the analysis of circadian data on both bioluminesence and wheel-running data. WAVOS is freely available at http://sourceforge.net/projects/wavos/files/
小波已被证明是分析周期性数据的强大技术,例如在昼夜节律振荡器分析中出现的数据。虽然有许多连续和离散小波变换的实现,但我们知道没有一款软件是为非技术终端用户设计的。通过开发一个工具包,使没有大量编程经验的终端用户也能进行这些分析,我们希望促进小波分析的更广泛应用。
我们开发了用于振荡系统小波分析和可视化的WAVOS工具包。WAVOS具有连续(Morlet)和离散(Daubechies)小波变换,在MATLAB中有一个简单、用户友好的图形用户界面。该界面允许从多种标准文件格式导入数据,进行可视化、处理和分析,并且无需使用命令行即可导出。我们的工作受到昼夜节律数据挑战的推动,因此已预先选择了适合此类数据分析的默认设置,以尽量减少微调的需要。然而,该工具包足够灵活,能够处理广泛的振荡信号,并且可用于更一般的情况。
我们展示了WAVOS:一个基于小波的全面MATLAB工具包,可轻松实现振荡数据的可视化、探索和分析。WAVOS包括Morlet连续小波变换和Daubechies离散小波变换。我们已经说明了WAVOS的使用,并展示了其在分析生物发光和转轮运行数据的昼夜节律数据方面的效用。WAVOS可在http://sourceforge.net/projects/wavos/files/上免费获取。