问题描述
scipy.signal.cwt 的文档 说:
scipy.signal.cwt(data, wavelet, widths)
小波:函数小波函数，它应该有 2 个参数.第一个参数是返回向量的点数将有 (len(wavelet(width,length)) == length).第二个是宽度参数，定义小波的大小(例如标准高斯偏差).查看满足这些条件的 rickerrequirements.wavelet : function 小波函数，需要 2 个参数.
wavelet : function Wavelet function, which should take 2 arguments. The first argument is the number of points that the returned vector will have (len(wavelet(width,length)) == length). The second is a width parameter, defining the size of the wavelet (e.g. standard deviation of a gaussian). See ricker, which satisfies these requirements.wavelet : function Wavelet function, which should take 2 arguments.
除了scipy.signal.ricket，还有哪些内置小波函数可以传递给scipy.signal.cwt?
Beyond scipy.signal.ricket, what are the other built-in wavelet functions that I can pass to scipy.signal.cwt?
我在 scipy/scipy/signal/wavelets.py 中看到
__all__ = ['daub', 'qmf', 'cascade', 'morlet', 'ricker', 'cwt']
并查看每个小波函数的参数，只有 ricket 似乎与 scipy.signal.cwt(data, wavelet, widths) 一起使用(因为只有ricker 正好接受 2 个参数).
and looking at the arguments of each of those wavelet functions, only ricket seems to work with scipy.signal.cwt(data, wavelet, widths) (as only ricker takes precisely 2 arguments).
推荐答案
我问了 SciPy 用户列表上的问题，答案 1:
我发现 CWT 的模块很混乱，所以我推出了自己的模块:
https://github.com/Dapid/fast-pycwt
它专为速度而生(我的跑步时间从 4 小时缩短到 20 分钟).没有经过彻底的测试，仅限于单双；但对我来说，它处于足够好"的状态.
It is built for speed (I got my running time from 4 h down to 20 min). It is not thoroughly tested, and it is limited to single and double; but for me it is in a "good enough" state.
答案 2:
您可能还会发现我的版本很有用:
https://github.com/aaren/wavelets
我还发现 scipy 小波令人困惑.我的版本包括一个更快的cwt 可以采用以频率或时间表示的小波.
I also found scipy wavelets confusing. My version includes a faster cwt that can take wavelets expressed in either frequency or time.
我发现使用小波函数更直观时间/频率和宽度作为参数而不是当前方法(我更喜欢在真实空间而不是样本空间中思考).
I found it more intuitive to have wavelet functions that take time/frequency and width as arguments rather than the present method (I prefer thinking in real space rather than sample space).
目前，scipy自带的morlet小波，scipy.signal.wavelets.morlet，不能用作 cwt 的输入.这我觉得很不幸.
Presently, the morlet wavelet that comes with scipy, scipy.signal.wavelets.morlet, cannot be used as input to cwt. This is unfortunate I think.
此外，目前的 cwt 不允许复杂的输出.这对 ricker 没有影响，但小波函数很复杂总的来说.
Additionally, the present cwt doesn't allow complex output. This doesn't make a difference for ricker but wavelet functions are complex in general.
我修改后的cwt"方法在这里:
My modified 'cwt' method is here:
https://github.com/aaren/wavelets/blob/master/wavelets.py#L15
它可以接受在时间或频率空间定义的小波函数，使用 fftconvolve，并允许复杂的输出.
It can accept wavelet functions defined in time or frequency space, uses fftconvolve, and allows complex output.
我的背景是基于对 Torrence 和 Compo 的阅读:
My background on this is based on a reading of Torrence and Compo:
Torrence 和 Compo，小波分析实用指南"(BAMS，1998)
Torrence and Compo, 'A Practical Guide to Wavelet Analysis' (BAMS, 1998)
http://paos.colorado.edu/research/wavelets/
希望能帮到你，
阿龙
这篇关于在哪里可以看到可以传递给 scipy.signal.cwt 的内置小波函数列表?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！