频谱分析工具
spectrum的Python项目详细描述
光谱：python中的光谱分析
| contributions: | Please join https://github.com/cokelaer/spectrum |
|---|---|
| contributors: | https://github.com/cokelaer/spectrum/graphs/contributors |
| issues: | Please use https://github.com/cokelaer/spectrum/issues |
| documentation: | http://pyspectrum.readthedocs.io/ |
| Citation: | Cokelaer et al, (2017), ‘Spectrum’: Spectral Analysis in Python, Journal of Open Source Software, 2(18), 348, doi:10.21105/joss.00348 |
spectrum包含使用基于傅里叶变换、参数化方法或特征值分析的方法估计功率谱密度的工具：
- The Fourier methods are based upon correlogram, periodogram and Welch estimates. Standard tapering windows (Hann, Hamming, Blackman) and more exotic ones are available (DPSS, Taylor, …).
- The parametric methods are based on Yule-Walker, BURG, MA and ARMA, covariance and modified covariance methods.
- Non-parametric methods based on eigen analysis (e.g., MUSIC) and minimum variance analysis are also implemented.
- Multitapering is also available
目标受众是多样化的。尽管功率谱的使用 信号是电气工程的基础（例如无线电通信， 雷达），从宇宙学（如探测 2016年的引力波），音乐（模式探测）或生物学（质量 光谱学）。
快速安装
spectrum在pypi上可用：
pip install spectrum
以及conda：
conda config --add channels conda-forge conda install spectrum
要安装conda可执行文件本身，请参见https://www.continuum.io/downloads。
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